Academic literature on the topic 'Reduced sample size'

Financial investment with collection and laboratory analysis of soil samples is an important factor to be considered when mapping agricultural areas with soybean planting. One of the alternatives is to use the spatial autocorrelation between the sample points to reduce the number of elements sampled, thus restricting the collection of redundant information. This work aimed to reduce the sample size of this agricultural area, composed of 102 sample points, and use it to analyze the spatial dependence of soil macro- and micro- nutrients, as well as the soil penetration resistance. The agricultural area used in this study has 167.35 ha, cultivated with soybean, which the soil is Red Dystroferric Latosol, and the sampling design has used in this agricultural area is the lattice plus close pairs. The reduction of the sample size was made by the multivariate effective sample size (ESSmulti) methodology. The studies with the simulation data and the soil attributes showed an inverse relationship between the practical range and the estimated value of the univariate effective sample size. With the calculation of ESSmulti, the sample configuration was reduced to 53 points. The Overall Accuracy and Tau concordance index showed differences between the thematic maps elaborated with the original and reduced sampling designs. However, the analysis of the variance inflation factor and the standard error of the spatial dependence parameters showed efficient results with the resized sample size.

Determining the required sample size is still a challenge in biological studies, including work on seed germination estimation. In this context, we studied a mathematical model to calculate sufficient sample size, using seeds of Bowdichia virgilioides Kunth. as a biological model. Coefficients of variation of the germinability (CVG) were calculated to determine the sufficient sample size (nc) to test the germination process. These CVG were subjected to the mathematical model (modified maximum curvature method – MMCM) and sufficient sample size was determined algebraically by the mathematical expression nc = [a2b2(2b + 1)/(b + 2)]1/(2b + 2) where a is the parameter of the model and b is here called the germinability heterogeneity index. Coefficients presented significant adjustment to this model, regardless of the physiological quality of the sample (99.94% ≤ R2 ≤ 99.99%). The nc is the maximum point of inflection of the CVG curve and depends on the physiological quality of the sample. Samples with higher germinability required fewer seeds to reach the nc than those with lower germinability. Thus, considering the variability of the studied material (measured by the CVG), the MMCM allows us to calculate the nc of the germination process. Our results demonstrate that is possible to prepare protocols to test the germination process for any species, with a reduced number of seeds.

Nanocrystalline NiFe 2 O 4 powder has been prepared by an oxidative precipitation process at room-temperature and the crystallite size dependent magnetic properties have been studied. The NiFe 2 O 4 powders prepared at room-temperature had an average crystallite size of 6 nm and showed a reduced saturation magnetisation (M s ) of 3 emu · g -1. The crystallite size was increased by heating the samples to increasingly higher temperatures. The M s value increased from 3 to 40 emu·g -1 as the crystallite size was increased from 6 to 120 nm. The samples having crystallite sizes from 6 to 20 nm were superparamagnetic at room-temperature. The Mössbauer spectrum of the 6 nm sized sample showed a broad quadruple doublet, whereas, the 40 nm sized sample showed a clear sextet pattern, with a hyperfine field values of 466 and 504 kOe for A(tetraheral) and B(octahedral) sublattices, respectively. It is shown that the saturation magnetisation and magnetic hyperfine field values are significantly reduced in nanocrystalline NiFe 2 O 4 as a function of crystallite size.

In order to research that statics properties of concrete cylinder sample are influenced by micro-concrete material heterogeneity, by random aggregate models generated by different random number were established. By fixed aggregate size and constantly changing of the sample size, the concrete numerical model was simulated and Strength change of concrete samples was analyzed .So that strength influence of the aggregate location of the concrete random sample was study. Calculation shows that: the strength of concrete has been little effect by the aggregate random location, the size effect on concrete has been changed regularly, with the size effect ratio coefficient of aggregate and sample gradually increasing, the error square sum of strain was reduced and the brittlness of the samples becomes obvious.

AbstractNanocrystalline iron was obtained by fusing magnetite and promoters. The oxidized form was reduced with hydrogen and passivated (sample P0). The average nanocrystallite size in sample P0 was d(P0) =16 nm and the width of size distribution was σ(P0) = 18 nm. Samples of nanocrystalline iron with narrower diameter ranges and larger and smaller average crystallite sizes were also synthesized. They were: sample P1 (d(P1) = 28 nm, σ(P1) = 5 nm), sample P2 (d(P2) = 22 nm, σ(P1) = 5 nm), sample P3 (d(P3) = 12 nm, σ(P1) = 9 nm). These four samples were studied at room temperature by dc magnetization measurements and ferromagnetic resonance at microwave frequency. Correlations between samples sizes distributions (average size and width of the sizes) and magnetic parameters (effective magnetization, anisotropy field, anisotropy constant, FMR linewidth) were investigated. It was found that the anisotropy field and effective magnetization determined from FMR spectra scale linearly with nanoparticle sizes, while the effective magnetic anisotropy constant determined from the hysteresis loops decreases with nanoparticle size increase.

Abstract The need to use reduced sample sizes, in order to attain improved spatial resolution in (µ-CT) tests applied in Portland cement composites, makes researchers perform the fractionation of materials to obtain samples with dimensions compatible with the capacity of the scanning equipment, which might cause alterations in the microstructure under analysis. Therefore, a test specimen (TS) with dimensions compatible with the scanning capacity of a microtomography system that operates with an X-ray tube and voltage ranging from 20 to 100 kV was proposed. Axial compression strength tests were made and their total porosity was assessed by an apparent density and solid fraction density ratio, which were obtained by means of mercury and helium pycnometry and µ-CT technique, respectively. The adoption of that TS has shown to be viable for providing a sample with a higher level of representation.

Aim of study: To reduce the sample size in an agricultural area of 167.35 hectares, cultivated with soybean, to analyze the spatial dependence of soil penetration resistance (SPR) with outliers. Area of study: Cascavel, Brazil Material and methods: The reduction of sample size was made by the univariate effective sample size ( ) methodology, assuming that the t-Student model represents the probability distribution of SPR. Main results: The radius and the intensity of spatial dependence have an inverse relationship with the estimated value of the . For the depths of SPR with spatial dependence, the highest estimated value of the reduced the sample size by 40%. From the new sample size, the sampling redesign was performed. The accuracy indexes showed differences between the thematic maps with the original and reduced sampling designs. However, the lowest values of the standard error in the parameters of the spatial dependence structure evidenced that the new sampling design was appropriate. Besides, models of semivariance function were efficiently estimated, which allowed identifying the existence of spatial dependence in all depth of SPR.Research highlights: The sample size was reduced by 40%, allowing for lesser financial investments with data collection and laboratory analysis of soil samples in the next mappings in the agricultural area. The spatial t-Student model was able to reduce the influence of outliers in the spatial dependence structure.

O trabalho tem por principal objetivo verificar, preliminarmente, a possibilidade de reduzir a quantidade de indivíduos na amostra de Pesquisa de Entrevistas Domiciliares, sem prejudicar a qualidade e representatividade da mesma. Analisar a influência das características espaciais e de uso de solo da área urbana constitui o objetivo intermediário. Para ambos os objetivos, a principal ferramenta utilizada foi o minerador de dados denominado Árvore de Decisão e Classificação contido no software S-Plus 6.1, que encontra as relações entre as características socioeconômicas dos indivíduos, as características espaciais e de uso de solo da área urbana e os padrões de viagens encadeadas. Os padrões de viagens foram codificados em termos de sequência cronológica de: motivos, modos, durações de viagem e períodos do dia em que as viagens ocorrem. As análises foram baseadas nos dados da Pesquisa de Entrevistas Domiciliares realizada pela Agência de Cooperação Internacional do Japão e Governo do Estado do Pará em 2000 na Região Metropolitana de Belém. Para se atingir o objetivo intermediário o método consistiu em analisar, através da Árvore de Decisão e Classificação, a influência da variável categórica Macrozona, que representa as características espaciais e de uso de solo da área urbana, nos padrões de viagens encadeadas realizados pelos indivíduos. Para o objetivo principal, o método consistiu em escolher, aleatoriamente, sub-amostras contendo 25% de pessoas da amostra final e verificar, através do Processamento de Árvores de Decisão e Classificação e do teste estatístico Kolmogorov - Smirnov, se os modelos obtidos a partir das amostras reduzidas conseguem ilustrar bem a freqüência de ocorrência dos padrões de viagens das pessoas da amostra final. Concluiu-se que as características espaciais e de uso de solo influenciam os padrões de encadeamento de viagens, e portanto foram incluídas como variáveis preditoras também nos modelos obtidos a partir das sub-amostras. A conclusão principal foi a não rejeição da hipótese de que é possível reduzir o tamanho da amostra de pesquisas domiciliares para fins de estudo do encadeamento de viagens. Entretanto ainda são necessárias muitas outras verificações antes de aceitar esta conclusão.<br>The main aim of this work is to verify, the possibility of reducing the sample size in home-interview surveys, without being detrimental to the quality and representation. The sub aim of this work is to analyze the influence of spatial characteristics and land use of an urban area. For both aims, the main analyses tool used was Data Miner called the Decision and Classification Tree which is in the software S-Plus 6.1. The Data Miner finds relations between trip chaining patterns and individual socioeconomic characteristics, spatial characteristics and land use patterns. The trip chaining patterns were coded in terms of chronological sequence of trip purpose, travel mode, travel time and the period of day in which travel occurs. The analyses were based on home-interview surveys carried out in the Belém Metropolitan Area in 2000, by Japan International Cooperation Agency and Pará State Government. In order to achieve the sub aim of this work, the method consisted of analyzing, using the Decision and Classification Tree, the influence of the categorical variable \"Macrozona\", which represents spatial characteristics and urban land use patterns, in trip chaining patterns carried by the individuals. Concerning the main aim, the method consisted of choosing sub-samples randomly containing 25% of the final sample of individuals and verifying (using Decision and Classification Tree and Kolmogorov-Smirnov statistical test) whether the models obtained from the reduced samples can describe the frequency of the occurrence of the individuals trip chaining patterns in the final sample well. The first conclusion is that spatial characteristics and land use of the urban area have influenced the trip chaining patterns, and therefore they were also included as independent variables in the models obtained from the sub-samples. The main conclusion was the non-rejection of the hypothesis that it is possible to reduce the sample size in home-interview surveys used for trip-chaining research. Nevertheless, several other verifications are necessary before accepting this conclusion.

In this chapter, we summarize the main results of a recent empirical research concerning European banks. We first explore the main drivers of the differences in risk-weighted assets (RWAs) across a sample of fifty large European banking groups. We then assess the impact of RWA-based capital regulations on those banks’ asset allocations in 2008–14. We find that risk weights are affected by bank size, business models, and asset mix. We also find that the adoption of internal ratings-based (IRB) approaches is an important driver of RWAs and that national segmentations explain a significant (albeit decreasing) share of the variability in risk weights. As for the impact of internal ratings on banks’ asset allocation in 2008–14, we uncover that banks using IRB approaches more extensively have reduced more (or increased less) their corporate loan portfolio. This effect is somewhat stronger for banks located in Eurozone periphery countries during the 2010–12 sovereign crisis. We do not find evidence, however, of internal models producing a reallocation from corporate loans to government exposures, suggesting that other motives prevailed in driving banks towards sovereign bonds during the Eurozone sovereign crisis, including the so-called ‘financial repression’ channel.

Cancer risk increases with age, but a patient’s tolerance to conventional treatments may be reduced with aging and associated morbidities. The development and expansion of age-appropriate therapies and approaches will be crucial as the population of elderly patients with cancer grows in the upcoming years. Taking into account the unique needs of this population will be of great importance. This chapter introduces the field of integrative oncology, the practice of supporting the whole person before, during, and after conventional treatments for cancer. Current evidence recognizes the safe use of many integrative interventions, such as lifestyle and diet changes and supplement and botanical use, to prevent cancer; to reduce side effects and optimize wellness during treatments such as surgery, chemotherapy, and radiation; and to promote full recovery after treatment. Many of these same interventions act directly to optimally regulate pathways in the unique metabolism of the malignant cell process.

Heaven’s Wrath explores the religious thought and religious rites of the early Dutch Atlantic world. The book argues that the Reformed Church and the West India Company forged and maintained a close union, with considerable consequences. Merchants, officers, sailors, and soldiers found in their faith an ideology and justification for mercantile, martial activities. The company, on the other hand, supported the church financially in Europe and helped spread Calvinism to other continents. Calvinist employees and colonists both benefitted from the familiar, comforting aspects of religious instruction and public worship. But the church-company union had a destructive side, too: Calvinists became the instruments of divine wrath in fighting Catholic enemies and punishing sinners and non-conformers in colonial courts, all of which imposed costs that the small Dutch Republic and its people-strapped colonies could not afford. At the same time, the Reformed Church in the Netherlands contributed to problems later blamed on the West India Company because the church kept an iron grip on colonial hires, publications, and organization. Heaven’s Wrath shows that the expense of the Calvinist-backed war and the church’s meticulous, worried management of colonial affairs hampered the mission and reduced the size and import of the Dutch Atlantic world.

Caesarean delivery (CD) is one of the most common operations in the world and providing effective pain relief is important not only for humanitarian reasons but also to speed up recovery and reduce postoperative complications. An understanding of the anatomy and physiology of pain transmission after CD has led to a multimodal approach to analgesia. This involves combining analgesics which work by different mechanisms resulting in an additive effect whilst at the same time reducing side effects. In contemporary practice, most CDs are carried out under neuraxial anaesthesia and neuraxial techniques using either intrathecal or epidural opioids have become central to the provision of effective postoperative analgesia. They reduce the need for systemic opioid analgesia and have few side effects, respiratory depression being the most significant but extremely uncommon. In circumstances where it is not possible to use neuraxial analgesia, for example, after general anaesthesia, other techniques such as intravenous patient-controlled analgesia using opioids and the transversus abdominis plane block have been shown to be effective. As part of the multimodal analgesic approach, many patients will require systemic analgesics to further improve pain relief and to limit side effects. Paracetamol and non-steroidal anti-inflammatory drugs are now widely established in the management of postoperative CD pain where they have been shown to potentiate opioid effects, decrease opioid consumption, reduce side effects, and complement the somatic pain relief provided by opioids. As part of a step-down approach after primary management with neuraxial or intravenous opioids, oral opioids are often required as part of a multimodal regimen.

The majority of suicides occur in LAMIC. This chapter presents findings from two low-cost, feasible interventions aimed at reducing suicides. The Suicide Prevention Multisite Intervention Study (SUPRE-MISS) of WHO assessed the effectiveness of brief intervention and contact (BIC) as an intervention strategy in five countries. Another trial in South India examined the effectiveness of a central pesticide storage facility as a means of reducing pesticide suicides. Some challenges that such trials face are the large sample sizes required to detect a significant change, making them uneconomical and unfeasible. Dearth of reliable data on suicide and underreporting because of cultural norms and legal barriers compound the problem. Future research should incorporate effective surveillance for reliable data, address high-risk groups, and initiate large-scale intervention at the community level involving multiple collaborators. Multipronged strategies, addressing social inequities, and improving health services would be the way forward to reduce the burden of suicide.

This handbook is currently in development, with individual articles publishing online in advance of print publication. At this time, we cannot add information about unpublished articles in this handbook, however the table of contents will continue to grow as additional articles pass through the review process and are added to the site. Please note that the online publication date for this handbook is the date that the first article in the title was published online. For more information, please read the site FAQs. Wind storms impact human lives, their built as well as natural habitat. During the last century, society’s vulnerability to wind storms has been reduced by enhanced knowledge of their impact and by controlling exposure through better design. However, only two of the wind systems have so far been considered in the design of buildings and structures, i.e., synoptic winds resulting from macroscale weather systems spanning thousands of kilometers, e.g., extratropical storms, and mesoscale tropical storms spanning hundreds of kilometers and traveling fast, e.g., hurricanes/typhoons/cyclones. During the last two decades, enough evidence has surfaced to support that a third type of very localized wind storms, the non-synoptic winds, are the most damaging in some regions of the world. Thus far there are no design provisions established for the codification of these wind storms. Their characterization in terms of climatology, wind field and intensity, frequency and occurrence, as well as their impact on the built environment, is slowly developing. This handbook presents the state-of-the-art of knowledge related to all these features including their risk, insurance issues, and economics. The research in this area is on the one hand more arduous given the reduced scale, the three-dimensionality, and nonstationary aspects of these non-synoptic winds while, at the same time, its understanding and modeling are being aided by the emergence of novel modeling and simulation techniques which are addressed in this handbook. This will serve as a guiding resource for those interested in learning about and contributing to the advancement of the field.

As a social historian, James W. Sanders takes a new look at a critical period in the development of Boston schools. Focusing on the burgeoning Irish Catholic population and framing the discussion around Catholic hierarchy, Sanders considers the interplay of social forces in the nineteenth and early twentieth centuries that led to Irish Catholics’ emerging with political control of the city and its public schools. The latter reduced the need for parochial schools; by at least the 1920s, the public and parochial schools had taken giant steps toward one another in theory and practice under the leadership of the Catholics who presided over both systems. The public schools taught the same morality as the Catholic ones, and, in the generous use of Catholic saints and heroes as moral exemplars, they came dangerously close to breaching the wall of separation between religion and the public school. As a result, despite the large Irish Catholic population, Boston’s parochial school system looked very different from parochial schools in other American cities, and did not match them in size or influence. The book begins in 1822 when Boston officially became a city and ends with the Irish Catholic takeover of the Boston public school system before the Second World War.

Latin America and the Caribbean, unlike other regions, is still quite young demographically: people over age 60 make up around 11% of the total population. However, the region is expected to experience the fastest rate of population aging in the world over the coming decades. This projected growth of the elderly population raises challenges related to pensions, health, and long-term care. At the same time, it opens up numerous business opportunities in different sectorshousing, tourism, care, and transportation, for examplethat could generate millions of new jobs. These opportunities are termed the “silver economy,” which has the potential to be one of the drivers of post-pandemic economic recovery. Importantly, women play key roles in many areas of this market, as noted in the first report published by the IDB on this subject (Okumura et al., 2020). This report maps the actors whose products or services are intended for older people and examines silver economy trends in the region by sector: health, long-term care, finance, housing, transportation, job market, education, entertainment, and digitization. The mapping identified 245 actors whose products or services are intended for older people, and it yielded three main findings. The first is that the majority of the actors (40%) operate in the health and care sectors. The prevalence of these sectors could be due to the fact that they are made up of many small players, and it could also suggest a still limited role of older people in active consumption, investment, and the job market in the region. The second finding is that 90% of the silver economy actors identified by the study operate exclusively in their countries of origin, and that Mexico has the most actors (47), followed by the Southern Cone countriesBrazil, Chile, and Argentinawhich have the regions highest rates of population aging. The third finding is that private investment dominates the silver economy ecosystem, as nearly 3 out of every 4 actors offering services to the elderly population are for-profit enterprises. The sectors and markets of the silver economy differ in size and degree of maturity. For example, the long-term care sector, which includes residential care settings, is the oldest and has the largest number of actors, while sectors like digital, home automation, and cohousing are still emerging. Across all sectors, however, there are innovative initiatives that hold great potential for growth. This report examines the main development trends of the silver economy in the region and presents examples of initiatives that are already underway. The health sector has a wealth of initiatives designed to make managing chronic diseases easier and to prevent and reduce the impact of functional limitations through practices that encourage active aging. In the area of long term careone of the most powerful drivers of job creationinitiatives to train human resources and offer home care services are flourishing. The financial sector is beginning to meet a wide range of demands from older people by offering unique services such as remittances or property management, in addition to more traditional pensions, savings, and investment services. The housing sector is adapting rapidly to the changes resulting from population aging. This shift can be seen, for example, in developments in the area of cohousing or collaborative housing, and in the rise of smart homes, which are emerging as potential solutions. In the area of transportation, specific solutions are being developed to meet the unique mobility needs of older people, whose economic and social participation is on the rise. The job market offers older people opportunities to continue contributing to society, either by sharing their experience or by earning income. The education sector is developing solutions that promote active aging and the ongoing participation of older people in the regions economic and social life. Entertainment services for older people are expanding, with the emergence of multiple online services. Lastly, digitization is a cross-cutting and fundamental challenge for the silver economy, and various initiatives in the region that directly address this issue were identified. Additionally, in several sectors we identified actors with a clear focus on gender, and these primarily provide support to women. Of a total of 245 actors identified by the mapping exercise, we take a closer look at 11 different stories of the development of the silver economy in the region. The featured organizations are RAFAM Internacional (Argentina), TeleDx (Chile), Bonanza Asistencia (Costa Rica), NudaProp (Uruguay), Contraticos (Costa Rica), Maturi (Brazil), Someone Somewhere (Mexico), CONAPE (Dominican Republic), Fundación Saldarriaga Concha (Colombia), Plan Ibirapitá (Uruguay), and Canitas (Mexico). These organizations were chosen based on criteria such as how innovative their business models are, the current size and growth potential of their initiatives, and their impact on society. This study is a first step towards mapping the silver economy in Latin America and the Caribbean, and the hope is to broaden the scope of this mapping exercise through future research and through the creation of a community of actors to promote the regional integration of initiatives in this field.

AbstractMachine learning (ML) methods are increasingly being used to predict pathologies and biological traits using neuroimaging data. Here controlling for confounds is essential to get unbiased estimates of generalization performance and to identify the features driving predictions. However, a systematic evaluation of the advantages and disadvantages of available alternatives is lacking. This makes it difficult to compare results across studies and to build deployment quality models. Here, we evaluated two commonly used confound removal schemes–whole data confound regression (WDCR) and cross-validated confound regression (CVCR)–to understand their effectiveness and biases induced in generalization performance estimation. Additionally, we study the interaction of the confound removal schemes with Z-score normalization, a common practice in ML modelling. We applied eight combinations of confound removal schemes and normalization (pipelines) to decode sex from resting-state functional MRI (rfMRI) data while controlling for two confounds, brain size and age. We show that both schemes effectively remove linear univariate and multivariate confounding effects resulting in reduced model performance with CVCR providing better generalization estimates, i.e., closer to out-of-sample performance than WDCR. We found no effect of normalizing before or after confound removal. In the presence of dataset and confound shift, four tested confound removal procedures yielded mixed results, raising new questions. We conclude that CVCR is a better method to control for confounding effects in neuroimaging studies. We believe that our in-depth analyses shed light on choices associated with confound removal and hope that it generates more interest in this problem instrumental to numerous applications.

AbstractWeather information is needed for smart decisions because uncertainties in weather phenomena are beyond capacity of smallholders for autonomous responses. The study analyzed determinants of farmers’ use of weather information as smart adaptation strategy. Arable crop farmers were sampled in the derived savannah agro-ecology area of Ondo State, Nigeria. Heckman probit model estimates show that gender and agricultural extension services were significant positive drivers of farmers’ access to weather information. Should weather information becomes an alternative adaptation strategy, access to credit was found as the major driver of farmers’ propensity to use weather information before taking climate smart agricultural decisions. Further results reveal that increasing knowledge of onset date, large farm size, and access to agricultural extension services significantly reduced farmers’ propensity to use improved weather information for smart decisions in the dry savannah area.

AbstractHyperproperties are properties of computational systems that require more than one trace to evaluate, e.g., many information-flow security and concurrency requirements. Where a trace property defines a set of traces, a hyperproperty defines a set of sets of traces. The temporal logics HyperLTL and HyperCTL* have been proposed to express hyperproperties. However, their semantics are synchronous in the sense that all traces proceed at the same speed and are evaluated at the same position. This precludes the use of these logics to analyze systems whose traces can proceed at different speeds and allow that different traces take stuttering steps independently. To solve this problem in this paper, we propose an asynchronous variant of HyperLTL. On the negative side, we show that the model-checking problem for this variant is undecidable. On the positive side, we identify a decidable fragment which covers a rich set of formulas with practical applications. We also propose two model-checking algorithms that reduce our problem to the HyperLTL model-checking problem in the synchronous semantics.

Abstract Economics is concerned with the analysis of choice and the efficient use of resources. Markets for antibiotics are heavily affected by their ‘public good’ nature and the externality that results from their consumption in terms of resistance. The non-excludability and non-rivalry associated with knowledge production in antibiotic development also has implications for the supply of antibiotics. On the demand side there are ethical issues associated with free-riding by consumers, free-riding across nations and free-riding across time. On the supply side, the lack of a pipeline for new antibiotics for the future causes both ethical and economic issues – and from both perspectives, efforts should perhaps focus more on alternatives to antibiotics and adjustments to heath care systems to reduce reliance on antibiotics. Indeed, unlike many areas of health care, where economics and ethical perspectives may differ, antimicrobial resistance is a case where the two perspectives align in terms of ensuring efficient and sustainable development and use of this precious resources. All strategies for dealing with resistance should share the same goals of achieving an optimal balance in the use of antimicrobial agents and explicit consideration of the distributional implications.

AbstractSession types describe patterns of interaction on communicating channels. Traditional session types include a form of choice whereby servers offer a collection of options, of which each client picks exactly one. This sort of choice constitutes a particular case of separated choice: offering on one side, selecting on the other. We introduce mixed choices in the context of session types and argue that they increase the flexibility of program development at the same time that they reduce the number of synchronisation primitives to exactly one. We present a type system incorporating subtyping and prove preservation and absence of runtime errors for well-typed processes. We further show that classical (conventional) sessions can be faithfully and tightly embedded in mixed choices. Finally, we discuss algorithmic type checking and a runtime system built on top of a conventional (choice-less) message-passing architecture.

AbstractThe valve train plays a major role in the performance of internal combustion engines by controlling the combustion process and it is therefore one of the key aspects for increasing the efficiency of combustion engines. Considering the dynamics, the spring force must be high enough to reliably close the valve preventing from seating bouncing due to surge modes after the valve closure. On the other side, the spring force should be kept as low as possible in order to reduce the engine friction losses and consequently the fuel consumption. In the high-performance engines, the valve springs have to be designed and optimized for sustaining higher stresses with compact dimensions leading to critical material and manufacturing processes. This requires a reduction of moving masses and a strong focus on design and process optimization of the coil springs for reducing the mechanical load and the friction losses at low engine speed. At the same time, valve train should be reliable at high engine speed. The calculation of stresses and contact forces for moving parts under dynamic load is essential for durability analysis. A method to calculate the contact of moving masses is described and proposed to justify valve motions experimental results. To fully understand the failure mechanism of test bed reliability trials, the dynamic stresses have been calculated modeling the real springs’ shape. The contact forces have been reproduced considering the coil clash effects and the dynamic behavior of the flexible spring.

This chapter presents solutions to some challenges when calculating CAPM Beta. Three methods for calculating traditional beta are presented and illustrated through the case of Facebook. Different choices of market index, data frequency, and sample size result in different values of beta; however, in all cases beta was greater than one. The chapter explores ordinal beta as an alternative measure to treat outliers in both developed and thin markets. Using a sample of 84 US stocks, there was no statistical difference between median traditional and ordinal betas. This was not the case for a sample of 47 Colombian stocks, which questions the usefulness of traditional beta in thin markets. In contrast with median traditional beta, median ordinal beta did not change significantly as a result of irregular data series. The contrary occurred when the observation (sampling) period was reduced; this leaves open the question of subjectivity when defining such period. Finally, the process of valuing a private company was illustrated through the case of Palmoil Ltd., a Colombian company.

&lt;i&gt;Abstract.&lt;/i&gt;—Linking landscape features, both natural and human-altered, to aquatic ecosystem structure and function is a fundamental objective in landscape ecology and freshwater science, but this process is data- and resource-intensive. Quantifying how landscape stressors influence aquatic communities requires balancing logistic and financial constraints with effectively sampling the landscape to capture gradients of interest. There are a variety of ways to balance these constraints, such as using existing data, handpicked site selection, or a statistical site-selection scheme. Poor sampling design reduces statistical power; however, we do not know how differences in site-selection designs influence our ability to measure ecological responses to landscape gradients. We quantified how the distribution of sample sites across landscape gradients affected the measured responses of stream fish assemblages to these gradients at different sample sizes. Specifically, we used randomization tests to compare the variability in the responses of fish assemblage structure (species richness and composition) to catchment area and land use (agricultural land) with manipulated distributions (random, highly skewed, and uniform) of sites across these landscape gradients. Assemblage composition was more sensitive than species richness to sampling design, and we observed less variability in the detected response of assemblage composition when samples were distributed uniformly across landscape gradients, especially when sample sizes were small. Although strong responses to environmental gradients, such as species richness to catchment area, are robust to sampling distributions, large sample size and a uniform distribution of samples might help elucidate more subtle responses to environmental gradients.

Existing research work has established that many of today's manufacturing organizations have failed to develop a comprehensive supply chain performance measures. In this chapter, the authors intend to empirically assess the effects of supplier buyer relations and human metrics on supply chain performance in the context of Indian manufacturing organizations. After rigorous literature review, total 18 variables have been identified which are later on reduced in number by factor analysis. As a pilot study, primary data is collected from 100 manufacturing organizations by means of a questionnaire and a scale is developed. On a sample size of 100, the proposed hypotheses are tested by applying two-tailed tests. t-test and factor analysis resulted in 5 factors, 2 related to supplier-buyer relations and 3 related to human metrics. The overall reliability of the scale comes out to be 0.697. The research work provides a new approach to the manufacturing organizations to understand the factors affecting supply chain performance. The present study is limited to Indian manufacturing organizations.

&lt;em&gt;Abstract.&lt;/em&gt;—A total of 276 chinook salmon &lt;em&gt; Oncorhynchus tshawytscha&lt;/em&gt;, less than 660-mm total length, were drift mooch-caught using barbless circle hooks and held for four days in 8,700 L, onboard holding tanks for wound location-specific, mortality rate evaluation. Only gut-hooked fish died in the first 24 hours of holding, and only lower-jaw hooked and gut-hooked fish died within the first 48 hours of holding. Gut-hooked fish that survived the four day holding period but whose internal organs were severely damaged were considered mortalities. The four day mortality rate attributable to the effects of handling and holding alone was estimated to be 0.048, based on a surrogate control group consisting of tank-held fish having no wounds or superficial wounds. The controladjusted, four day mortality rates depended strongly on hook wound location. The distribution of wound locations in the California recreational drift mooch salmon fishery was estimated based on a sample of 522 fish, less than 660-mm total length; the relative frequency of gut-hooked fish (0.406) was twice that of any other location. The fishery overall hook-and-release mortality rate was estimated to be 0.422 (95% confidence interval of 0.342–0.502), obtained by weighting the wound location-specific, four day mortality rates by the relative frequency of those wound locations in the fishery. The distribution of wound locations was found to depend on both hook size and fish-size class, but the effects of these factors were not additive on the log-odds scale. Blood plasma cortisol concentration, a measure of stress, was significantly higher in fish held for four days than in ocean-caught (presumably stress-free) fish, but there was considerable variation among individuals and the results were not useful in evaluating the effects of wound-induced stress. The requirement that (only) barbless circle hooks be used in the California drift mooch fishery substantially reduced the hook-and-release mortality rate in this fishery; however, the rate is still high. Hook-and-release mortality might be reduced further by educating anglers on the use of drift mooch methods that lessen the probability of gut hooking. If such education is effective in changing the fishery’s wound location profile, our estimate of the hook-and-release mortality rate can be easily updated using the methods described in this paper.

The instability of a pipeline crack eventually leads to brittle or ductile crack propagation. The resistance to ductile crack propagation is assessed by the energy dissipated in the CVN test. However the Charpy specimen exhibits mainly mode I failure, with no small shear lips, while real failure is a combined mode often described as slant failure. In the present investigation, instrumented Charpy tests with nominal and reduced thickness down to 2.5 mm are carried out. Instrumented Battelle drop weight tear tests where also performed with nominal and reduced thickness, in order to vary the ligament versus thickness ratio. The results of the Charpy tests are simulated by the finite element method. The results are then discussed in terms of energy dissipated during crack initiation and crack propagation. It is shown that by reducing the size of the Charpy specimen, slant failure is promoted, which results in a decrease of the specific energy absorbed. However, most of the difference of absorbed energy is in the crack initiation mode, and only marginally in crack propagation. Consequently, the fraction of the total energy dissipated in crack propagation is increased by reducing the sample thickness, making it a possible tool to assess the resistance of a material to crack propagation, provided that brittle fracture is avoided and no separation is present.

This paper reports an improved technique to enhance microfluidic temperature gradient focusing (TGF) of sample solutes using Joule heating effects induced by a combined AC and DC electric field. By introducing the AC field component, additional Joule heating effects are obtained to generate temperature gradient for concentrating sample solutes, while the electroosmotic flow is suppressed under the high frequency AC electric field. Therefore, the required DC voltages for achieving certain sample concentration by Joule heating induced TGF technique are remarkably reduced. Moreover, the lower DC voltages lead to smaller electroosmotic flow (EOF), thereby reducing the backpressure effects due to the finite reservoir size. Concentration enhancements of sample solutes are improved by using a combined AC and DC electric field.

This paper studied the relationship between matrix microstructure of plant materials and drying behavior using Astragalus and Chinese Angelica root slices as examples. Astragalus and Chinese Angelica, two kinds of traditional Chinese Medicine Herb (CMH), are species of stem and root medicinal herb with the widely curative effects. Based on the measured results by using automatic surface area-porosity analyzer (at smaller scale ≤ 100nm), the volume fractal dimensions (DV) were estimated to characterize the pore size distribution inside matrix of samples dried by different drying technologies, including microwave drying at 200W and conventional hot air drying at 60 °C. In cases studied in this paper, the values of DV are well related with drying time. As compared to hot air dried sample, DV of microwave dried sample increases by 5.9% for Astragalus, while 7.7% for Chinese Angelica. In comparison with hot air drying, the microwave drying time is reduced to 1/6 (30min/180 min) for Astragalus, while 1/16 (50min/810min) for Chinese Angelica. Combined the observation of SEM images of sample, our findings is that, higher fractal dimension, less concentration of pore size distribution, better connectivity of pore or channel with multi-scale characteristics (aperture about 0.1μm–1μm, plasmodesma about 1nm–10nm, or 10Å–100Å), much loose distribution of cytoplasm inside parenchyma cells, better permeability of moisture transfer path during drying process, shorter drying time. Our results demonstrate that the volume fractal dimension (DV) of pore size distribution at smaller scale (≤ 100nm) could give a better understanding the mass transfer behavior of plant materials.

Lab-on-a-Chip technology now becomes increasingly attractive due to advantages such as reduced sample size, reduced reagent consumption, shortened analysis time, potential for high throughput and automation and reduced costs, leading to the potential for manufacturing of disposable devices. On such microchip system, the ability to handling microfluid is important. Extensive microfluidic handling componets including microflow regulator, microfluidic sensor, microvalve and micropump have been reported. Although these microfluid handling methods are successful, for the polymer based microfluidic device, a simple design, easy fabrication and the ability to integrate into the microsystem lacks report. In this paper, we presented such microvalve by utilizing the hydrophobicity of the PDMS material, a popular biocompatible material widely used in microfluidic system. The valve utilized air trapped on the side wall of microchannel by a special microconcave structure design. Controlled by an external coil heater, the trapped air will be enlarged to reduce channel width and so reduce the fluid flow in the microchannel. The valve can work in on/off mode or on flow regulating mode depending on specific flow control requirement.

Fatigue design curve construction is commonly used for durability and reliability assessment of engineering components subjected to cyclic loading. A wide variety of design curve construction methods have been developed over the last decades. Some of the methods have been adopted by engineering codes and widely used in industry. However, the traditional design curve construction methods usually require significant amounts of test data in order for the constructed design curves to be consistently and reliably used in product design and validation. In order to reduce the test sample size and associated testing time and cost, several Bayesian statistics based design curve construction methods have been recently successfully developed by several research groups. Among all of these methods, an efficient Monte Carlo simulation based resampling method developed by the authors of this paper is of particular importance. The method is based on a large amount of reliable historical fatigue test data, the associated probabilistic distributions of the mean and standard deviation of the failure cycles, and an advanced acceptance-rejection resampling algorithm. However, finite element analysis (FEA) methods and a special stress recovery technique are required to process the test data, which is usually a time-consuming process. A more straightforward approach that does not require these intermediate processes is strongly preferred. This study presents such an approach, in which the only historical information needed is the distribution of the standard deviation of the cycles to failure. The distribution of the mean is directly calculated from the current tested data and the Central Limit Theorem. Neither FEA nor stress recovery technique is required for this approach, and the effort put into design curve construction can be significantly reduced. This method can be used to complement the previously developed Bayesian methods.

One of the industrial applications of ultrafiltration membrane system is water purification and wastewater treatment. Membranes act as physical barriers by eliminating particles such as pollen, yeast, bacteria, colloids, viruses, and macromolecules from feed water. The effectiveness of the membrane to separate particles is determined by its molecular weight cut-off and feed water characteristics. Typically, pre-filtration strainers are installed upstream of an ultrafiltration membrane system to separate large particles from the flow stream. The criteria for selection of the strainer pore size is unclear and is often determined by the feed water average particle size distribution. This paper is motivated by the hydraulic loading failure of a 125 μm strainer by average feed water particle size of 1.6 μm when the volumetric flow is at or greater than 40% of the rated design flow capacity. The objective of this paper are to: a) determine if the feed particle size distribution is a sufficient parameter for selection of pre-filtration strainer, b) evaluate the effect of feed flow velocity on strainer performance, and c) enhance strainer performance using vortex generator. In this experimental study, a Single Particle Optical Sensing, Accusizer, was used to analyze particle size distribution of five water samples collected at strainer feed, strainer filtrate, and strainer backwash. All samples were analyzed using a lower detection limit of 0.5 μm. In order to capture more counts of the larger particles present in the sample, a second analysis was done for each sample at a higher detection limit, 5.09 μm for feed sample, and 2.15 μm for the rest of the samples. Particle size data based on individual detection limits were statistically combined to generate comprehensive blended results of total number and total volume. The volume was determined based on assumption that each particle is spherically shaped. The Particle Size Distribution Measurement Accuracy is ±0.035 μm. Results showed that the feed particle size diameter and volume was insufficient to determine strainer size. Particle size distribution is needed at the feed, filtrate, and backwash to evaluate the strainer particle separation efficiency. It was observed that the total particle count in the filtrate (4.4 × 106) was an order of magnitude higher than the feed (3.2 × 105). Specifically, the total count for particles with diameter less than 7.22 μm were higher in the filtrate while larger particle size ≥ 7.22 μm were more in the feed stream. It appears that the large particles in the feed breaks down into smaller particles at the strainer interface and the small particles (≤ 7.22μm) passed through the pore into the filtrate. The particle breakdown, detachment of particles in the strainer pore into the filtrate, and particle to particle interactions are enhanced by increase in flow velocity hence increasing the hydrodynamic shear that acts on attached particles. A vortex generator inserted in to the strainer reduced pore clogging and pressure drop.

Microfluidic concentration is achieved by utilizing Joule heating effect induced temperature gradient focusing (TGF) under a combined AC and DC electric field imposed in a straight microchannel with sudden expansion in cross-section. The introduction of AC electric field component services dual functions: one is to produce Joule heating effects for generating temperature gradient, and the other is to suppress electroosmotic flow with high frequencies. Therefore, the required DC voltage for achieving sample concentration with Joule heating induced TGF technique is remarkably reduced. The lower DC voltage can lead to smaller electroosmotic flow (EOF), thereby reducing the backpressure effect due to the finite reservoir size. It was demonstrated that using the proposed new TGF technique with Joule heating effect under a combined AC and DC field, more than 2500-fold concentration enhancement was obtained within 14 minutes in a PDMS/PDMS microdevice, which is an order of magnitude higher than the literature reported concentration enhancement achieved by microfluidic devices utilizing the Joule heating induced TGF technique.

In this paper, we integrate two or more compliant mechanisms to get enhanced functionality for manipulating and mechanically characterizing the grasped objects of varied size (cm to sub-mm), stiffness (1e5 to 10 N/m), and materials (cement to biological cells). The concepts of spring-lever (SL) model, stiffness maps, and non-dimensional kinetoelastostatic maps are used to design composite and multi-scale compliant mechanisms. Composite compliant mechanisms comprise two or more different mechanisms within a single elastic continuum while multi-scale ones possess the additional feature of substantial difference in the sizes of the mechanisms that are combined into one. We present three applications: (i) a composite compliant device to measure the failure load of the cement samples; (ii) a composite multi-scale compliant gripper to measure the bulk stiffness of zebrafish embryos; and (iii) a compliant gripper combined with a negative-stiffness element to reduce the overall stiffness. The prototypes of all three devices are made and tested. The cement sample needed a breaking force of 22.5 N; the zebrafish embryo is found to have bulk stiffness of about 10 N/m; and the stiffness of a compliant gripper was reduced by 99.8 % to 0.2 N/m.

Campylobacter spp. are the most common bacterial cause of foodborne illness in the UK, with chicken considered to be the most important vehicle for this organism. The UK Food Standards Agency (FSA) agreed with industry to reduce Campylobacter spp. contamination in raw chicken and issued a target to reduce the prevalence of the most contaminated chickens (those with more than 1000 cfu per g chicken neck skin) to below 10 % at the end of the slaughter process, initially by 2016. To help monitor progress, a series of UK-wide surveys were undertaken to determine the levels of Campylobacter spp. on whole UK-produced, fresh chicken at retail sale in the UK. The data obtained for the first four years was reported in FSA projects FS241044 (2014/15) and FS102121 (2015 to 2018). The FSA has indicated that the retail proxy target for the percentage of highly contaminated raw whole retail chickens should be less than 7% and while continued monitoring has demonstrated a sustained decline for chickens from major retailer stores, chicken on sale in other stores have yet to meet this target. This report presents results from testing chickens from non-major retailer stores (only) in a fifth survey year from 2018 to 2019. In line with previous practise, samples were collected from stores distributed throughout the UK (in proportion to the population size of each country). Testing was performed by two laboratories - a Public Health England (PHE) laboratory or the Agri-Food &amp; Biosciences Institute (AFBI), Belfast. Enumeration of Campylobacter spp. was performed using the ISO 10272-2 standard enumeration method applied with a detection limit of 10 colony forming units (cfu) per gram (g) of neck skin. Antimicrobial resistance (AMR) to selected antimicrobials in accordance with those advised in the EU harmonised monitoring protocol was predicted from genome sequence data in Campylobacter jejuni and Campylobacter coli isolates The percentage (10.8%) of fresh, whole chicken at retail sale in stores of smaller chains (for example, Iceland, McColl’s, Budgens, Nisa, Costcutter, One Stop), independents and butchers (collectively referred to as non-major retailer stores in this report) in the UK that are highly contaminated (at more than 1000 cfu per g) with Campylobacter spp. has decreased since the previous survey year but is still higher than that found in samples from major retailers. 8 whole fresh raw chickens from non-major retailer stores were collected from August 2018 to July 2019 (n = 1009). Campylobacter spp. were detected in 55.8% of the chicken skin samples obtained from non-major retailer shops, and 10.8% of the samples had counts above 1000 cfu per g chicken skin. Comparison among production plant approval codes showed significant differences of the percentages of chicken samples with more than 1000 cfu per g, ranging from 0% to 28.1%. The percentage of samples with more than 1000 cfu of Campylobacter spp. per g was significantly higher in the period May, June and July than in the period November to April. The percentage of highly contaminated samples was significantly higher for samples taken from larger compared to smaller chickens. There was no statistical difference in the percentage of highly contaminated samples between those obtained from chicken reared with access to range (for example, free-range and organic birds) and those reared under standard regime (for example, no access to range) but the small sample size for organic and to a lesser extent free-range chickens, may have limited the ability to detect important differences should they exist. Campylobacter species was determined for isolates from 93.4% of the positive samples. C. jejuni was isolated from the majority (72.6%) of samples while C. coli was identified in 22.1% of samples. A combination of both species was found in 5.3% of samples. C. coli was more frequently isolated from samples obtained from chicken reared with access to range in comparison to those reared as standard birds. C. jejuni was less prevalent during the summer months of June, July and August compared to the remaining months of the year. Resistance to ciprofloxacin (fluoroquinolone), erythromycin (macrolide), tetracycline, (tetracyclines), gentamicin and streptomycin (aminoglycosides) was predicted from WGS data by the detection of known antimicrobial resistance determinants. Resistance to ciprofloxacin was detected in 185 (51.7%) isolates of C. jejuni and 49 (42.1%) isolates of C. coli; while 220 (61.1%) isolates of C. jejuni and 73 (62.9%) isolates of C. coli isolates were resistant to tetracycline. Three C. coli (2.6%) but none of the C. jejuni isolates harboured 23S mutations predicting reduced susceptibility to erythromycin. Multidrug resistance (MDR), defined as harbouring genetic determinants for resistance to at least three unrelated antimicrobial classes, was found in 10 (8.6%) C. coli isolates but not in any C. jejuni isolates. Co-resistance to ciprofloxacin and erythromycin was predicted in 1.7% of C. coli isolates. 9 Overall, the percentages of isolates with genetic AMR determinants found in this study were similar to those reported in the previous survey year (August 2016 to July 2017) where testing was based on phenotypic break-point testing. Multi-drug resistance was similar to that found in the previous survey years. It is recommended that trends in AMR in Campylobacter spp. isolates from retail chickens continue to be monitored to realise any increasing resistance of concern, particulary to erythromycin (macrolide). Considering that the percentage of fresh, whole chicken from non-major retailer stores in the UK that are highly contaminated (at more than 1000 cfu per g) with Campylobacter spp. continues to be above that in samples from major retailers more action including consideration of interventions such as improved biosecurity and slaughterhouse measures is needed to achieve better control of Campylobacter spp. for this section of the industry. The FSA has indicated that the retail proxy target for the percentage of highly contaminated retail chickens should be less than 7% and while continued monitoring has demonstrated a sustained decline for chickens from major retailer stores, chicken on sale in other stores have yet to meet this target.

Because many patients reduce exercise following outpatient cardiac rehabilitation (CR), we developed an intervention to assist with the transition and evaluated its feasibility and preliminary efficacy using a one-group pretest–posttest design. Five CR patients were enrolled ~1 month prior to CR discharge and provided an activity tracker. Each week during CR they received a summary of their physical activity and steps. Following CR discharge, participants received an individualized report that included their physical activity and step history, information on specific features of the activity tracker, and encouraging messages from former CR patients for each of the next 6 weeks. Mixed model trajectory analyses were used to test the intervention effect separately for active minutes and steps modeling three study phases: pre-intervention (day activity tracking began to CR discharge), intervention (day following CR discharge to day when final report sent), and maintenance (day following the final report to ~1 month later). Activity tracking was successfully deployed and, with weekly reports following CR, may offset the usual decline in physical activity. When weekly reports ceased, a decline in steps/day occurred. A scaled-up intervention with a more rigorous study design with sufficient sample size can evaluate this approach further.

Soils containing inorganic compounds are frequently encountered by transportation agencies during construction within the right-of-way, and they pose a threat to human health and the environment. As a result, construction activities may experience project delays and increased costs associated with management of inorganic compounds containing soils required to meet environmental regulations. Recalcitrance of metal-contaminated soils toward conventional treatment technologies is exacerbated in clay or organic content-rich fine-grained soils with low permeability and high sorption capacity because of increased treatment complexity, cost, and duration. The objective of this study was to develop an accelerated in situ electrochemical treatment approach to extract inorganic compounds from fine-grained soils, with the treatment time comparable to excavation and off-site disposal. Three reactor experiments were conducted on samples collected from two borehole locations from a field site in Illinois that contained arsenic (As)(~7.4 mg/kg) and manganese (Mn)(~700 mg/kg). A combination of hydrogen peroxide (H2O2) and/or citrate buffer solution was used to treat the soils. A low-intensity electrical field was applied to soil samples using a bench-scale reactor that resembles field-scale in situ electrochemical systems. For the treatment using 10% H2O2 and citrate buffer solution, average removal of 23% and 8% were achieved for Mn and As, respectively. With 4% H2O2 and citrate buffer, 39% and 24% removal were achieved for Mn and As; while using only citrate buffer as the electrolyte, 49% and 9% removal were achieved for Mn and As, respectively. All chemical regimes adopted in this study reduced the inorganic compound concentrations to below the maximum allowable concentration for Illinois as specified by the Illinois Environmental Protection Agency. The results from this work indicate that electrochemical systems that leverage low concentrations of hydrogen peroxide and citrate buffer can be effective for remediating soils containing manganese and arsenic.

Background: In an era of explosive growth in biomedical evidence, improving systematic review (SR) search processes is increasingly critical. Text-mining tools (TMTs) are a potentially powerful resource to improve and streamline search strategy development. Two types of TMTs are especially of interest to searchers: word frequency (useful for identifying most used keyword terms, e.g., PubReminer) and clustering (visualizing common themes, e.g., Carrot2). Objectives: The objectives of this study were to compare the benefits and trade-offs of searches with and without the use of TMTs for evidence synthesis products in real world settings. Specific questions included: (1) Do TMTs decrease the time spent developing search strategies? (2) How do TMTs affect the sensitivity and yield of searches? (3) Do TMTs identify groups of records that can be safely excluded in the search evaluation step? (4) Does the complexity of a systematic review topic affect TMT performance? In addition to quantitative data, we collected librarians' comments on their experiences using TMTs to explore when and how these new tools may be useful in systematic review search¬¬ creation. Methods: In this prospective comparative study, we included seven SR projects, and classified them into simple or complex topics. The project librarian used conventional “usual practice” (UP) methods to create the MEDLINE search strategy, while a paired TMT librarian simultaneously and independently created a search strategy using a variety of TMTs. TMT librarians could choose one or more freely available TMTs per category from a pre-selected list in each of three categories: (1) keyword/phrase tools: AntConc, PubReMiner; (2) subject term tools: MeSH on Demand, PubReMiner, Yale MeSH Analyzer; and (3) strategy evaluation tools: Carrot2, VOSviewer. We collected results from both MEDLINE searches (with and without TMTs), coded every citation’s origin (UP or TMT respectively), deduplicated them, and then sent the citation library to the review team for screening. When the draft report was submitted, we used the final list of included citations to calculate the sensitivity, precision, and number-needed-to-read for each search (with and without TMTs). Separately, we tracked the time spent on various aspects of search creation by each librarian. Simple and complex topics were analyzed separately to provide insight into whether TMTs could be more useful for one type of topic or another. Results: Across all reviews, UP searches seemed to perform better than TMT, but because of the small sample size, none of these differences was statistically significant. UP searches were slightly more sensitive (92% [95% confidence intervals (CI) 85–99%]) than TMT searches (84.9% [95% CI 74.4–95.4%]). The mean number-needed-to-read was 83 (SD 34) for UP and 90 (SD 68) for TMT. Keyword and subject term development using TMTs generally took less time than those developed using UP alone. The average total time was 12 hours (SD 8) to create a complete search strategy by UP librarians, and 5 hours (SD 2) for the TMT librarians. TMTs neither affected search evaluation time nor improved identification of exclusion concepts (irrelevant records) that can be safely removed from the search set. Conclusion: Across all reviews but one, TMT searches were less sensitive than UP searches. For simple SR topics (i.e., single indication–single drug), TMT searches were slightly less sensitive, but reduced time spent in search design. For complex SR topics (e.g., multicomponent interventions), TMT searches were less sensitive than UP searches; nevertheless, in complex reviews, they identified unique eligible citations not found by the UP searches. TMT searches also reduced time spent in search strategy development. For all evidence synthesis types, TMT searches may be more efficient in reviews where comprehensiveness is not paramount, or as an adjunct to UP for evidence syntheses, because they can identify unique includable citations. If TMTs were easier to learn and use, their utility would be increased.

Invasive exotic plant (IEP) species are a significant threat to natural ecosystem integrity and biodiversity, and controlling them is a high priority for the National Park Service. The North-ern Colorado Plateau Network (NCPN) selected the early detection of IEPs as one of 11 monitoring protocols to be implemented as part of its long-term monitoring program. From May 30 to June 1, 2019, network staff conducted surveys for priority IEP species along the Scenic Drive and Cathedral Valley Road monitoring routes at Capitol Reef National Park. We detected 119 patches of six priority IEP species along 34 kilometers of the two monitor-ing routes. There were more patches of IEPs, and a higher percentage of large patches, than in previous years. This indicates that previously identified infestations have expanded and grown. The most common (47.1%) patch size among priority species was 1,000–2,000 m2 (0.25–0.5 acre). The vast majority (93.2%) of priority patches ranked either low (58.8%) or very low (34.4%) on the patch management index scale. Tamarisk (Tamarix sp., 72 patches) was the most prevalent priority IEP species. African mustard (Malcolmia africana, 32 patch-es), field bindweed (Convolvulus arvensis, 9 patches), and Russian olive (Elaeagnus angusti-folia, 3 patches) occurred less commonly. Together, these four species represented 97.5% of all patches recorded in 2019. Four IEP species were found on the monitored routes for the first time: Russian olive (Elaeagnus angustifolia), quackgrass (Elymus repens), Siberian elm (Ulmus pumila), and African mustard (Malcolmia africana, not on the priority species list before 2019). Cathedral Valley Road had higher IEP priority patches per kilometer (5.68) than the Scenic Drive (2.05). IEP species were found on 37.9% (25 of 66) of monitored transects. Almost all these detections were Russian thistle (Salsola sp.). Russian thistle was widespread, present in 33.3% of transects, with an estimated cover of 0.2% across all transects sampled. Across routes monitored in all three rotations (2012, 2015, and 2019), Russian thistle has increased in frequency. However, its frequency remained about the same from 2015 to 2019, and percent cover remains low. Tamarisk and field bindweed have both increased in preva-lence since monitoring began, with tamarisk showing a dramatic increase in the number and size of patches. Immediate control of tamarisk and these other species is recommended to reduce their numbers on these routes. The NCPN plans to Capitol Reef in 2020 to monitor Oak and Pleasant creeks, completing the third rotation of invasive plant monitoring.

Background Opioid analgesia has become the mainstay for acute pain management in the postoperative setting. However, the use of opioid medications comes with significant risks and side effects. Due to increasing numbers of prescriptions to those with chronic pain, opioid medications have become more expensive while becoming less effective due to the buildup of patient tolerance. The idea of opioid-free analgesic techniques has rarely been breached in many hospitals. Emerging research has shown that opioid-sparing approaches have resulted in lower reported pain scores across the board, as well as significant cost reductions to hospitals and insurance agencies. In addition to providing adequate pain relief, the predicted cost burden of an opioid-free or opioid-sparing approach is significantly less than traditional methods. Methods The following groups were considered in our inclusion criteria: those who speak the English language, all races and ethnicities, male or female, home medications, those who are at least 18 years of age and able to provide written informed consent, those undergoing inpatient or same-day surgical procedures. In addition, our scoping review includes the following exclusion criteria: those who are non-English speaking, those who are less than 18 years of age, those who are not undergoing surgical procedures while admitted, those who are unable to provide numeric pain score due to clinical status, those who are unable to provide written informed consent, and those who decline participation in the study. Data was extracted by one reviewer and verified by the remaining two group members. Extraction was divided as equally as possible among the 11 listed references. Discrepancies in data extraction were discussed between the article reviewer, project editor, and group leader. Results We identified nine primary sources addressing the use of ketamine as an alternative to opioid analgesia and post-operative pain control. Our findings indicate a positive correlation between perioperative ketamine administration and postoperative pain control. While this information provides insight on opioid-free analgesia, it also revealed the limited amount of research conducted in this area of practice. The strategies for several of the clinical trials limited ketamine administration to a small niche of patients. The included studies provided evidence for lower pain scores, reductions in opioid consumption, and better patient outcomes. Implications for Nursing Practice Based on the results of the studies’ randomized controlled trials and meta-analyses, the effects of ketamine are shown as an adequate analgesic alternative to opioids postoperatively. The cited resources showed that ketamine can be used as a sole agent, or combined effectively with reduced doses of opioids for multimodal therapy. There were noted limitations in some of the research articles. Not all of the cited studies were able to include definitive evidence of proper blinding techniques or randomization methods. Small sample sizes and the inclusion of specific patient populations identified within several of the studies can skew data in one direction or another; therefore, significant clinical results cannot be generalized to patient populations across the board.

1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lower than estimates from January’s Monetary Policy Report (-7.2%). High-frequency indicators suggest that economic performance was significantly more dynamic than expected in January, despite mobility restrictions and quarantine measures. This has also come amid declines in total and core inflation, the latter of which was below January projections if controlling for certain relative price changes. This suggests that the unexpected strength of recent growth contains elements of demand, and that excess capacity, while significant, could be lower than previously estimated. Nevertheless, uncertainty over the measurement of excess capacity continues to be unusually high and marked both by variations in the way different economic sectors and spending components have been affected by the pandemic, and by uneven price behavior. The size of excess capacity, and in particular the evolution of the pandemic in forthcoming quarters, constitute substantial risks to the macroeconomic forecast presented in this report. Despite the unexpected strength of the recovery, the technical staff continues to project ample excess capacity that is expected to remain on the forecast horizon, alongside core inflation that will likely remain below the target. Domestic demand remains below 2019 levels amid unusually significant uncertainty over the size of excess capacity in the economy. High national unemployment (14.6% for February 2021) reflects a loose labor market, while observed total and core inflation continue to be below 2%. Inflationary pressures from the exchange rate are expected to continue to be low, with relatively little pass-through on inflation. This would be compatible with a negative output gap. Excess productive capacity and the expectation of core inflation below the 3% target on the forecast horizon provide a basis for an expansive monetary policy posture. The technical staff’s assessment of certain shocks and their expected effects on the economy, as well as the presence of several sources of uncertainty and related assumptions about their potential macroeconomic impacts, remain a feature of this report. The coronavirus pandemic, in particular, continues to affect the public health environment, and the reopening of Colombia’s economy remains incomplete. The technical staff’s assessment is that the COVID-19 shock has affected both aggregate demand and supply, but that the impact on demand has been deeper and more persistent. Given this persistence, the central forecast accounts for a gradual tightening of the output gap in the absence of new waves of contagion, and as vaccination campaigns progress. The central forecast continues to include an expected increase of total and core inflation rates in the second quarter of 2021, alongside the lapse of the temporary price relief measures put in place in 2020. Additional COVID-19 outbreaks (of uncertain duration and intensity) represent a significant risk factor that could affect these projections. Additionally, the forecast continues to include an upward trend in sovereign risk premiums, reflected by higher levels of public debt that in the wake of the pandemic are likely to persist on the forecast horizon, even in the context of a fiscal adjustment. At the same time, the projection accounts for the shortterm effects on private domestic demand from a fiscal adjustment along the lines of the one currently being proposed by the national government. This would be compatible with a gradual recovery of private domestic demand in 2022. The size and characteristics of the fiscal adjustment that is ultimately implemented, as well as the corresponding market response, represent another source of forecast uncertainty. Newly available information offers evidence of the potential for significant changes to the macroeconomic scenario, though without altering the general diagnosis described above. The most recent data on inflation, growth, fiscal policy, and international financial conditions suggests a more dynamic economy than previously expected. However, a third wave of the pandemic has delayed the re-opening of Colombia’s economy and brought with it a deceleration in economic activity. Detailed descriptions of these considerations and subsequent changes to the macroeconomic forecast are presented below. The expected annual decline in GDP (-0.3%) in the first quarter of 2021 appears to have been less pronounced than projected in January (-4.8%). Partial closures in January to address a second wave of COVID-19 appear to have had a less significant negative impact on the economy than previously estimated. This is reflected in figures related to mobility, energy demand, industry and retail sales, foreign trade, commercial transactions from selected banks, and the national statistics agency’s (DANE) economic tracking indicator (ISE). Output is now expected to have declined annually in the first quarter by 0.3%. Private consumption likely continued to recover, registering levels somewhat above those from the previous year, while public consumption likely increased significantly. While a recovery in investment in both housing and in other buildings and structures is expected, overall investment levels in this case likely continued to be low, and gross fixed capital formation is expected to continue to show significant annual declines. Imports likely recovered to again outpace exports, though both are expected to register significant annual declines. Economic activity that outpaced projections, an increase in oil prices and other export products, and an expected increase in public spending this year account for the upward revision to the 2021 growth forecast (from 4.6% with a range between 2% and 6% in January, to 6.0% with a range between 3% and 7% in April). As a result, the output gap is expected to be smaller and to tighten more rapidly than projected in the previous report, though it is still expected to remain in negative territory on the forecast horizon. Wide forecast intervals reflect the fact that the future evolution of the COVID-19 pandemic remains a significant source of uncertainty on these projections. The delay in the recovery of economic activity as a result of the resurgence of COVID-19 in the first quarter appears to have been less significant than projected in the January report. The central forecast scenario expects this improved performance to continue in 2021 alongside increased consumer and business confidence. Low real interest rates and an active credit supply would also support this dynamic, and the overall conditions would be expected to spur a recovery in consumption and investment. Increased growth in public spending and public works based on the national government’s spending plan (Plan Financiero del Gobierno) are other factors to consider. Additionally, an expected recovery in global demand and higher projected prices for oil and coffee would further contribute to improved external revenues and would favor investment, in particular in the oil sector. Given the above, the technical staff’s 2021 growth forecast has been revised upward from 4.6% in January (range from 2% to 6%) to 6.0% in April (range from 3% to 7%). These projections account for the potential for the third wave of COVID-19 to have a larger and more persistent effect on the economy than the previous wave, while also supposing that there will not be any additional significant waves of the pandemic and that mobility restrictions will be relaxed as a result. Economic growth in 2022 is expected to be 3%, with a range between 1% and 5%. This figure would be lower than projected in the January report (3.6% with a range between 2% and 6%), due to a higher base of comparison given the upward revision to expected GDP in 2021. This forecast also takes into account the likely effects on private demand of a fiscal adjustment of the size currently being proposed by the national government, and which would come into effect in 2022. Excess in productive capacity is now expected to be lower than estimated in January but continues to be significant and affected by high levels of uncertainty, as reflected in the wide forecast intervals. The possibility of new waves of the virus (of uncertain intensity and duration) represents a significant downward risk to projected GDP growth, and is signaled by the lower limits of the ranges provided in this report. Inflation (1.51%) and inflation excluding food and regulated items (0.94%) declined in March compared to December, continuing below the 3% target. The decline in inflation in this period was below projections, explained in large part by unanticipated increases in the costs of certain foods (3.92%) and regulated items (1.52%). An increase in international food and shipping prices, increased foreign demand for beef, and specific upward pressures on perishable food supplies appear to explain a lower-than-expected deceleration in the consumer price index (CPI) for foods. An unexpected increase in regulated items prices came amid unanticipated increases in international fuel prices, on some utilities rates, and for regulated education prices. The decline in annual inflation excluding food and regulated items between December and March was in line with projections from January, though this included downward pressure from a significant reduction in telecommunications rates due to the imminent entry of a new operator. When controlling for the effects of this relative price change, inflation excluding food and regulated items exceeds levels forecast in the previous report. Within this indicator of core inflation, the CPI for goods (1.05%) accelerated due to a reversion of the effects of the VAT-free day in November, which was largely accounted for in February, and possibly by the transmission of a recent depreciation of the peso on domestic prices for certain items (electric and household appliances). For their part, services prices decelerated and showed the lowest rate of annual growth (0.89%) among the large consumer baskets in the CPI. Within the services basket, the annual change in rental prices continued to decline, while those services that continue to experience the most significant restrictions on returning to normal operations (tourism, cinemas, nightlife, etc.) continued to register significant price declines. As previously mentioned, telephone rates also fell significantly due to increased competition in the market. Total inflation is expected to continue to be affected by ample excesses in productive capacity for the remainder of 2021 and 2022, though less so than projected in January. As a result, convergence to the inflation target is now expected to be somewhat faster than estimated in the previous report, assuming the absence of significant additional outbreaks of COVID-19. The technical staff’s year-end inflation projections for 2021 and 2022 have increased, suggesting figures around 3% due largely to variation in food and regulated items prices. The projection for inflation excluding food and regulated items also increased, but remains below 3%. Price relief measures on indirect taxes implemented in 2020 are expected to lapse in the second quarter of 2021, generating a one-off effect on prices and temporarily affecting inflation excluding food and regulated items. However, indexation to low levels of past inflation, weak demand, and ample excess productive capacity are expected to keep core inflation below the target, near 2.3% at the end of 2021 (previously 2.1%). The reversion in 2021 of the effects of some price relief measures on utility rates from 2020 should lead to an increase in the CPI for regulated items in the second half of this year. Annual price changes are now expected to be higher than estimated in the January report due to an increased expected path for fuel prices and unanticipated increases in regulated education prices. The projection for the CPI for foods has increased compared to the previous report, taking into account certain factors that were not anticipated in January (a less favorable agricultural cycle, increased pressure from international prices, and transport costs). Given the above, year-end annual inflation for 2021 and 2022 is now expected to be 3% and 2.8%, respectively, which would be above projections from January (2.3% and 2,7%). For its part, expected inflation based on analyst surveys suggests year-end inflation in 2021 and 2022 of 2.8% and 3.1%, respectively. There remains significant uncertainty surrounding the inflation forecasts included in this report due to several factors: 1) the evolution of the pandemic; 2) the difficulty in evaluating the size and persistence of excess productive capacity; 3) the timing and manner in which price relief measures will lapse; and 4) the future behavior of food prices. Projected 2021 growth in foreign demand (4.4% to 5.2%) and the supposed average oil price (USD 53 to USD 61 per Brent benchmark barrel) were both revised upward. An increase in long-term international interest rates has been reflected in a depreciation of the peso and could result in relatively tighter external financial conditions for emerging market economies, including Colombia. Average growth among Colombia’s trade partners was greater than expected in the fourth quarter of 2020. This, together with a sizable fiscal stimulus approved in the United States and the onset of a massive global vaccination campaign, largely explains the projected increase in foreign demand growth in 2021. The resilience of the goods market in the face of global crisis and an expected normalization in international trade are additional factors. These considerations and the expected continuation of a gradual reduction of mobility restrictions abroad suggest that Colombia’s trade partners could grow on average by 5.2% in 2021 and around 3.4% in 2022. The improved prospects for global economic growth have led to an increase in current and expected oil prices. Production interruptions due to a heavy winter, reduced inventories, and increased supply restrictions instituted by producing countries have also contributed to the increase. Meanwhile, market forecasts and recent Federal Reserve pronouncements suggest that the benchmark interest rate in the U.S. will remain stable for the next two years. Nevertheless, a significant increase in public spending in the country has fostered expectations for greater growth and inflation, as well as increased uncertainty over the moment in which a normalization of monetary policy might begin. This has been reflected in an increase in long-term interest rates. In this context, emerging market economies in the region, including Colombia, have registered increases in sovereign risk premiums and long-term domestic interest rates, and a depreciation of local currencies against the dollar. Recent outbreaks of COVID-19 in several of these economies; limits on vaccine supply and the slow pace of immunization campaigns in some countries; a significant increase in public debt; and tensions between the United States and China, among other factors, all add to a high level of uncertainty surrounding interest rate spreads, external financing conditions, and the future performance of risk premiums. The impact that this environment could have on the exchange rate and on domestic financing conditions represent risks to the macroeconomic and monetary policy forecasts. Domestic financial conditions continue to favor recovery in economic activity. The transmission of reductions to the policy interest rate on credit rates has been significant. The banking portfolio continues to recover amid circumstances that have affected both the supply and demand for loans, and in which some credit risks have materialized. Preferential and ordinary commercial interest rates have fallen to a similar degree as the benchmark interest rate. As is generally the case, this transmission has come at a slower pace for consumer credit rates, and has been further delayed in the case of mortgage rates. Commercial credit levels stabilized above pre-pandemic levels in March, following an increase resulting from significant liquidity requirements for businesses in the second quarter of 2020. The consumer credit portfolio continued to recover and has now surpassed February 2020 levels, though overall growth in the portfolio remains low. At the same time, portfolio projections and default indicators have increased, and credit establishment earnings have come down. Despite this, credit disbursements continue to recover and solvency indicators remain well above regulatory minimums. 1.2 Monetary policy decision In its meetings in March and April the BDBR left the benchmark interest rate unchanged at 1.75%.