Academic literature on the topic 'Temporal delay'

OBJECTIVE The Brain Trauma Foundation recommendation regarding the timing of surgical evacuation of epidural hematomas and subdural hematomas is to perform the procedure as soon as possible. Indeed, faster evacuation is associated with better outcome. However, to the authors' knowledge, no study has looked at where delays in intrahospital care occurred for patients suffering from traumatic intracranial mass lesions. The goals of this study were as follows: 1) to characterize the performance of a Level 1 trauma center in terms of delays for emergency trauma craniotomies, 2) to review step by step where delays occurred in patient care, and 3) to propose ways to improve performance. METHODS A retrospective review was conducted covering a 5-year period of all emergency trauma craniotomies. Demographic data, injury severity, neurological status, and functional outcome data were collected. The time elapsed between emergency department (ED) arrival and CT imaging, between CT imaging and arrival at the operating room (OR), between ED arrival and OR arrival, between OR arrival and skin incision, and between ED arrival and skin incision were calculated. Patients were also subcategorized as either having immediate life-threatening emergencies (E0) or life-threatening emergencies (E1). The operative technique was also reviewed (standard craniotomy opening vs immediate bur hole decompression followed by craniotomy). RESULTS The study included 166 patients. Of these, 58 (35%) were classified into the E0 group and 108 (64.2%) into the E1 group. The median ED-to-CT delay was 54 minutes with no significant difference between the E0 and the E1 groups. The median CT-to-OR time delay was 57 minutes. The median delay for the E0 group was 39 minutes and that for the E1 group was 70 minutes (p = 0.002). The median delay from ED to OR arrival for patients with a CT scanning done at an outside hospital was 75 minutes. The median delay from ED to OR arrival was 85 minutes for the E0 group and 127 minutes for the E1 group (p < 0.0001). The median delay from OR arrival to skin incision was 35 minutes (E0: median 27 minutes; E1: median 39 minutes; p < 0.0001). The median total time elapsed between ED arrival and skin incision was 150 minutes (E0: median 131 minutes; E1: median 180 minutes). Overall, only 17% of patients underwent immediate bur hole decompression, but the proportion climbed to 41% in the E0 group. A lower Glasgow Coma Scale score was associated with a shorter delay (p = 0.0004). CONCLUSIONS A long delay until surgery still exists for patients requiring urgent mass lesion evacuation. Many factors contribute to this delay, including performing imaging and transfer to and preparation in the OR. Strategies can be implemented to reduce delays and improve the delivery of care.

Movement adaptation in response to systematic motor perturbations exhibits distinct spatial and temporal properties. These characteristics are typically studied in isolation, leaving the interaction largely unknown. Here we examined how the temporal decay of visuomotor adaptation influences the spatial generalization of the motor recalibration. First, we quantified the extent to which adaptation decayed over time. Subjects reached to a peripheral target, and a rotation was applied to the visual feedback of the unseen motion. The retention of this adaptation over different delays (0–120 s) 1) decreased by 29.0 ± 6.8% at the longest delay and 2) was represented by a simple exponential, with a time constant of 22.5 ± 5.6 s. On the basis of this relationship we simulated how the spatial generalization of adaptation would change with delay. To test this directly, we trained additional subjects with the same perturbation and assessed transfer to 19 different locations (spaced 15° apart, symmetric around the trained location) and examined three delays (~4, 12, and 25 s). Consistent with the simulation, we found that generalization around the trained direction (±15°) significantly decreased with delay and distance, while locations >60° displayed near-constant spatiotemporal transfer. Intermediate distances (30° and 45°) showed a difference in transfer across space, but this amount was approximately constant across time. Interestingly, the decay at the trained direction was faster than that based purely on time, suggesting that the spatial transfer of adaptation is modified by concurrent passive (time dependent) and active (movement dependent) processes. NEW & NOTEWORTHY Short-term motor adaptation exhibits distinct spatial and temporal characteristics. Here we investigated the interaction of these features, utilizing a simple motor adaptation paradigm (recalibration of reaching arm movements in response to rotated visual feedback). We examined the changes in the spatial generalization of motor adaptation for different temporal manipulations and report that the spatiotemporal generalization of motor adaptation is generally local and is influenced by both passive (time dependent) and active (movement dependent) learning processes.

In this paper, we mainly discuss effects of partial time delay on temporal dynamics of Watts–Strogatz (WS) small-world neuronal networks by controlling two parameters. One is the time delay [Formula: see text] and the other is the probability of partial time delay [Formula: see text]. Temporal dynamics of WS small-world neuronal networks are discussed with the aid of temporal coherence and mean firing rate. With the obtained simulation results, it is revealed that for small time delay [Formula: see text], the probability [Formula: see text] could weaken temporal coherence and increase mean firing rate of neuronal networks, which indicates that it could improve neuronal firings of the neuronal networks while destroying firing regularity. For large time delay [Formula: see text], temporal coherence and mean firing rate do not have great changes with respect to [Formula: see text]. Time delay [Formula: see text] always has great influence on both temporal coherence and mean firing rate no matter what is the value of [Formula: see text]. Moreover, with the analysis of spike trains and histograms of interspike intervals of neurons inside neuronal networks, it is found that the effects of partial time delays on temporal coherence and mean firing rate could be the result of locking between the period of neuronal firing activities and the value of time delay [Formula: see text]. In brief, partial time delay could have great influence on temporal dynamics of the neuronal networks.

When changes occur in our environment, we usually know whether we caused these changes by our actions or not. Yet, this feeling of authorship for changes — the so-called sense of agency (SoA) — depends on the temporal relationship between action and resulting change (i.e., effect). More precisely, SoA might depend on whether the effect occurs temporally predictable, and on the duration of the delay between action and effect. In previous studies, SoA was measured either explicitly, asking for the perceived control over external stimuli, or implicitly by measuring a characteristic temporal judgement bias (intentional binding, i.e., a shortening of the perceived interval between action and effect). We used a novel paradigm for investigating explicit SoA more directly by asking participants in a forced-choice paradigm whether they caused a temporally predictable or a temporally unpredictable effect by their action. Additionally, we investigated how the temporal contiguity of the effects influenced the participants’ explicit SoA. In two experiments (48 participants each), there was no influence of temporal predictability on explicit SoA. Temporally predictable and unpredictable effects were equally often rated as own effects. Yet, effects after shorter delays were more often perceived as own effects than effects after longer delays. These findings are in line with previous results concerning the influence of effect delay on other explicit measures of SoA and concluding that explicit SoA is stronger for early effects.

Uncertainty about the waiting time before obtaining an outcome is integral to intertemporal choice. Here, we showed that people express different time preferences depending on how they learn about this temporal uncertainty. In two studies, people chose between pairs of options: one with a single, sure delay and the other involving multiple, probabilistic delays (a lottery). The probability of each delay occurring either was explicitly described ( timing risk) or could be learned through experiential sampling ( timing uncertainty; the delay itself was not experienced). When the shorter delay was rare, people preferred the lottery more often when it was described than when it was experienced. When the longer delay was rare, this pattern was reversed. Modeling analyses suggested that underexperiencing rare delays and different patterns of probability weighting contribute to this description–experience gap. Our results challenge traditional models of intertemporal choice with temporal uncertainty as well as the generality of inverse-S-shaped probability weighting in such choice.

Rapidly forgetting information once attention is diverted seems to be a ubiquitous phenomenon. The cause of this rapid decline has been debated for decades; some researchers claim that memory traces decay as a function of time out of the focus of attention, whereas others claim that prior memory traces cause confusability by interfering with the current trace. Here we demonstrate that performance after a long delay can be better than performance after a short delay if the temporal confusability between the current item and previous items is reduced. These results provide strong evidence for the importance of temporal confusability, rather than decay, as the cause of forgetting over the short term.

Time plays a pivotal role in causal inference. Nonetheless most contemporary theories of causal induction do not address the implications of temporal contiguity and delay, with the exception of associative learning theory. Shanks, Pearson, and Dickinson (1989) and several replications (Reed, 1992, 1999) have demonstrated that people fail to identify causal relations if cause and effect are separated by more than two seconds. In line with an associationist perspective, these findings have been interpreted to indicate that temporal lags universally impair causal induction. This interpretation clashes with the richness of everyday causal cognition where people apparently can reason about causal relations involving considerable delays. We look at the implications of cause-effect delays from a computational perspective and predict that delays should generally hinder reasoning performance, but that this hindrance should be alleviated if reasoners have knowledge of the delay. Two experiments demonstrated that (1) the impact of delay on causal judgement depends on participants’ expectations about the timeframe of the causal relation, and (2) the free-operant procedures used in previous studies are ill-suited to study the direct influences of delay on causal induction, because they confound delay with weaker evidence for the relation in question. Implications for contemporary causal learning theories are discussed.

In airway smooth muscle (ASM), ACh induces propagating intracellular Ca2+ concentration ([Ca2+]i) oscillations (5–30 Hz). We hypothesized that, in ASM, coupling of elevations and reductions in [Ca2+]i to force generation and relaxation (excitation-contraction coupling) is slower than ACh-induced [Ca2+]i oscillations, leading to stable force generation. When we used real-time confocal imaging, the delay between elevated [Ca2+]i and contraction in intact porcine ASM cells was found to be ∼450 ms. In β-escin-permeabilized ASM strips, photolytic release of caged Ca2+ resulted in force generation after ∼800 ms. When calmodulin (CaM) was added, this delay was shortened to ∼500 ms. In the presence of exogenous CaM and 100 μM Ca2+, photolytic release of caged ATP led to force generation after ∼80 ms. These results indicated significant delays due to CaM mobilization and Ca2+-CaM activation of myosin light chain kinase but much shorter delays introduced by myosin light chain kinase-induced phosphorylation of the regulatory myosin light chain MLC20 and cross-bridge recruitment. This was confirmed by prior thiophosphorylation of MLC20, in which force generation occurred ∼50 ms after photolytic release of caged ATP, approximating the delay introduced by cross-bridge recruitment alone. The time required to reach maximum steady-state force was >15 s. Rapid chelation of [Ca2+]i after photolytic release of caged diazo-2 resulted in relaxation after a delay of ∼1.2 s and 50% reduction in force after ∼57 s. We conclude that in ASM cells agonist-induced [Ca2+]i oscillations are temporally and spatially integrated during excitation-contraction coupling, resulting in stable force production.

Neighboring line switching can contribute to a large portion of the delay of a line for today's deep submicron designs. The impact of this switching on delay is usually estimated by scaling the coupling capacitances (often by a factor of 2) and modeling them as grounded. This simple approach has been shown to be overly pessimistic in some cases, while somewhat optimistic in others. Apart from the delay modeling inaccuracies, the temporal and functional isolation of the aggressors can contribute to the pessimism. This paper introduces TACO, a timing analysis approach that addresses both these issues. TACO captures the provably worst-and best-case delays as a function of the timing-window inputs to the gates. We then present a comprehensive ATPG-based approach that uses functional information to identify valid interactions between coupled lines. Our algorithm accounts for glitches on aggressors that can be caused by static and dynamic hazards in the circuit. Results on industrial examples and benchmark circuits show the value of our approach.

The code observable of global navigation satellite systems (GNSS) is influenced by group delay variations (GDV) of transmitter and receiver antennas. For the Global Positioning System (GPS), the variations can sum up to 1 m in the ionosphere-free linear combination and thus can significantly affect precise code applications. The contribution of the GPS transmitters can amount to 0.8 m peak-to-peak over the entire nadir angle range. To verify the assumption of their time-invariance, we determined daily individual satellite GDV for GPS transmitter antennas over a period of more than two years. Dual-frequency observations of globally distributed reference stations and their multipath combination form the basis for our analysis. The resulting GPS GDV are stable on the level of a few centimeters for C1, P2, and for the ionosphere-free linear combination. Our study reveals that the inconsistencies of the GDV of space vehicle number (SVN) 55 with respect to earlier studies are not caused by temporal instabilities, but are rather related to receiver properties.

International Telemetering Conference Proceedings / October 20-23, 2003 / Riviera Hotel and Convention Center, Las Vegas, Nevada
In many test ranges, it is often required to acquire a number of telemetry streams and to process the data simultaneously. Frequently, the streams have different delay characteristics, requiring temporal alignment before the processing step. It is desired to have the capability to align these streams so that the events in each stream are coincident in time. Terawave Communications has developed technology to perform temporal alignment for a number of streams automatically. Additionally, the algorithm performs the delay compensation independent of the source data rate of each stream. Terawave will present the algorithm and share the results of their testing in a test installation.

Delays and cancelled trains are often described as a problem for companies that transport goods by rail. Lack of reliability of freight trains is seen as a disadvantage compared to other modes. To date there has been limited quantitative information in Sweden about the size and the structure of the problem of trains not arriving in time. In this thesis information for two years, 2008 and 2009 is available that enable us to do the analysis of distribution on a spatial, temporal and seize-frequency scale. Since the spatial and frequency-size distributions describe the vulnerability of a transport network it has potentially important policy implications. In the size-frequency scale, we analyzed different distribution to fit with the arrival delay at the final station and we conclude that, it is not possible to find a distribution for the whole range of observations. However, considering the tail of arrival delays we find that it is exponentially distributed. This implies that the tail makes up the biggest part of total delay time. The 20 % largest delays contribute to about 78% of total delay minutes. In the spatial scale, we defined stations which have the highest value of arrival delay in the whole network and ranked them. We found out that more than 50% of the total arrival delay per year occurs in just 7% of stations. With the help of regression analysis we analyze how delays are propagated in the network. We find that delays at the origin increase arrival delay but that some part of the initial delay is gained at arrival, probably due to large slack in the time tables. Finally, in the temporal scale we analyzed arrival delays in different time scales such as monthly, weekly and daily delays. We expected that the reduction of the total number of trains in 2009 would reduce not only total but also the average arrival delay since there would be more free capacity. The data shows however, that the average delay did not decrease as the number of trains decreased due to the economic contraction in 2009, indicating that capacity might not be as crucial for explaining delays as previously expected.

This thesis investigates the computer-based modelling and simulation of complex geospatial phenomena. Geospatial systems are real world processes which extend over some meaningful extent of the Earth's surface, such as cities and fisheries. There are many problems that require urgent attention in this domain (for example relating to sustainability) but despite increasing amounts of data and computational power there is a significant gap between the potential for model-based analyses and their actual impact on real world policy and planning. Analytical methods are confounded by the high dimensionality and nonlinearity of spatio-temporal systems and/or are hard to relate to meaningful policy decisions. Simulation-based approaches on the other hand are more heuristic and policy oriented in nature, but they are difficult to validate and almost always over-fit the data: although a given model can be calibrated on a given set of data, it usually performs very poorly on new unseen data sets. The central contribution of this thesis is a framework which is formally grounded and able to be rigourously validated, yet at the same time is interpretable in terms of real world phenomena and thus has a strong connection to domain knowledge. The scope of the thesis spans both theory and practice, and three specific contributions range along this span. Starting at the theoretical end, the first contribution concerns the conceptual and theoretical basis of the framework, which is a technique known as delay reconstruction. The underlying theory is rooted in the rather technical field of dynamical systems (itself largely based on differential topology), which has hindered its wider application and the formation of strong links with other areas. Therefore, the first contribution is an exposition of delay reconstruction in non-technical language, with a focus on explaining how some recent extensions to this theory make the concept far more widely applicable than is often assumed. The second contribution uses this theoretical foundation to develop a practical, unified framework for pattern discovery and hypothesis exploration in geo-spatial data. The central aspect of this framework is the linking of delay reconstruction with domain knowledge. This is done via the notion that determinism is not an on-off quantity, but rather that a given data set may be ascribed a particular 'degree' of determinism, and that that degree may be increased through manipulation of the data set using domain knowledge. This leads to a framework which can handle spatiotemporally complex (including multi-scale) data sets, is sensitive to the amount of data that is available, and is naturally geared to be used interactively with qualitative feedback conveyed to the user via geometry. The framework is complementary to other techniques in that it forms a scaffold within which almost all modelling approaches - including agent-based modelling - can be cast as particular kinds of 'manipulations' of the data, and as such are easily integrated. The third contribution examines the practical efficacy of the framework in a real world case study. This involves a high resolution spatio-temporal record of fishcatch data from trawlers operating in a large fishery. The study is used to test two fundamental capabilities of the framework: (i) whether real world spatio-temporal phenomena can be identified in the degree-of-determinism signature of the data set, (ii) whether the determinism-level can then be increased by manipulating the data in response to this phenomena. One of the main outcomes of this study is a clear identification of the influence of the lunar cycle on the behaviour of Tiger and Endeavour prawns. The framework allows for this to be 'non-destructively subtracted', increasing the detect-ability of further phenomena.

The two processes of outbreak identification and disease modelling are fundamental in the study of disease outbreaks affecting livestock and wildlife. Rapid detection and the implementation of appropriate preventative or control measures from an understanding of the mechanisms of disease spread may limit the impact of an outbreak. The performance of several on-line warning algorithms in their ability to detect outbreaks in both real-life and simulated data is investigated. A version of Farrington's well established outbreak detection algorithm, referred to as the EDS scheme is compared to approaches based on the Kalman Filter, namely a Prediction Interval approach and three types of CUSUM scheme. All the schemes are able to successfully identify outbreaks and we find that no single approach appears to outperform the others in all the measures considered. However the EDS scheme is the most efficient in detecting outbreaks promptly and one of the CUSUM schemes is best at producing consistent warnings throughout the outbreak period. In addition we formulate deterministic models describing the transmission dynamics of the midge-borne disease bluetongue, with cattle and sheep as hosts. The models take the form of delay differential equations and incorporate the incubation time of bluetongue in cattle, sheep and midges, and also the larval developmental time of midges. An autonomous model assuming midges to be active year round and a periodic model allowing midge activity to vary with the seasons are analysed. The transmission of the disease via midge diffusion and migration is studied in detail and the effects of vaccination are also considered. Important findings include the need for prompt diagnosis of latent infection and appropriate action before the animal becomes infectious, and the need for measures that reduce insect bites. This reinforces the importance of timely identification of disease outbreaks in order for effective intervention to be possible.

Background. Patients with anorexia nervosa (AN) are characterized by a very low body weight but readily give up immediate rewards (food) for long-term goals (slim figure), which might indicate an unusual level of self-control. This everyday clinical observation may be quantifiable in the framework of the anticipation-discounting dilemma. Method. Using a cross-sectional design, this study compared the capacity to delay reward in 34 patients suffering from acute AN (acAN), 33 weight-recovered AN patients (recAN) and 54 healthy controls. We also used a longitudinal study to reassess 21 acAN patients after short-term weight restoration. A validated intertemporal choice task and a hyperbolic model were used to estimate temporal discounting rates. Results. Confirming the validity of the task used, decreased delay discounting was associated with age and low selfreported impulsivity. However, no group differences in key measures of temporal discounting of monetary rewards were found. Conclusions. Increased cognitive control, which has been suggested as a key characteristic of AN, does not seem to extend the capacity to wait for delayed monetary rewards. Differences between our study and the only previous study reporting decreased delay discounting in adult AN patients may be explained by the different age range and chronicity of acute patients, but the fact that weight recovery was not associated with changes in discount rates suggests that discounting behavior is not a trait marker in AN. Future studies using paradigms with disorder-specific stimuli may help to clarify the role of delay discounting in AN.

Artificial neural networks are learning paradigms which mimic the biological neural system. The temporal coding Spiking Neural Network, a relatively new artificial neural network paradigm, is considered to be computationally more powerful than the conventional neural network. Research on the network of spiking neurons is an emerging field and has potential for wider investigation. This research explores alternative learning models with temporal coding spiking neural networks for clustering and classification tasks. Neurons are known to be operating in two modes namely, as integrators and coincidence detectors. Previous temporal coding spiking neural networks, realising spiking neurons as integrators, were utilised for analytical studies. Temporal coding spiking neural networks applied successfully for clustering and classification tasks realised spiking neurons as coincidence detectors and encoded input in formation in the connection delays through a weight adaptation technique. These learning models select suitably delayed connections by enhancing the weights of those connections while weakening the others. This research investigates the learning in temporal coding spiking neural networks with spiking neurons as integrators and coincidence detectors. Focus is given to both supervised and unsupervised learning through weight as well as through delay adaptation. Three novel models for learning in temporal coding spiking neural networks are presented in this research. The first spiking neural network model, Self- Organising Weight Adaptation Spiking Neural Network (SOWA_SNN) realises the spiking neuron as integrator. This model adapts and encodes input information in its connection weights. The second learning model, Self-Organising Delay Adaptation Spiking Neural Network (SODA_SNN) and the third model, Super vised Delay Adaptation Spiking Neural Network (SDA_SNN) realise the spiking neuron as coincidence detector. These two models adapt the connection delays in order to detect temporal patterns through coincidence detection. The first two models were developed for clustering applications and the third for classification tasks. All three models employ Hebbian-based learning rules to update the network connection parameters by utilising the difference between the input and output spike times. The proposed temporal coding spiking neural network models were implemented as discrete models in software and their characteristics and capabilities were analysed through simulations on three bench mark data sets and a high dimensional data set. All three models were able to cluster or classify the analysed data sets efficiently with a high degree of accuracy. The performance of the proposed models, was found to be better than the existing spiking neural network models as well as conventional neural networks. The proposed learning paradigms could be applied to a wide range of applications including manufacturing, business and biomedical domains.

Difficulties in speech production are often marked by disfluency; fillers, hesitations, prolongations, repetitions and repairs. In recent years a body of work has emerged that demonstrates that listeners are sensitive to disfluency, and that this affects their expectations for upcoming speech, as well as their attention to the speech stream. This thesis investigates the extent to which delay may be responsible for triggering these effects. The experiments reported in this thesis build on an Event Related Potential (ERP) paradigm developed by Corley et al., (2007), in which participants listened to sentences manipulated by both fluency and predictability. Corley et al. reported an attenuated N400 effect for words following disfluent ers, and interpreted this as indicating that the extent to which listeners made predictions was reduced following an er. In the current set of experiments, various noisy interruptions were added to Corley et al.,'s paradigm, time matched to the disfluent fillers. These manipulations allowed investigation of whether the same effects could be triggered by delay alone, in the absence of a cue indicating that the speaker was experiencing difficulty. The first experiment, which contrasted disfluent ers with artificial beeps, revealed a small but significant reduction in N400 effect amplitude for words affected by ers but not by beeps. The second experiment, in which ers were contrasted with speaker generated coughs, revealed no fluency effects on the N400 effect. A third experiment combined the designs of Experiments 1 and 2 to verify whether the difference between them could be characterised as a context effect; one potential explanation for the difference between the outcomes of Experiments 1 and 2 is that the interpretation of an er is affected by the surrounding stimuli. However, in Experiment 3, once again no effect of fluency on the magnitude of the N400 effect was found. Taken together, the results of these three studies lead to the question of whether er's attenuation effect on the N400 is robust. In a second part to each study, listeners took part in a surprise recognition memory test, comprising words which had been the critical words in the previous task intermixed with new words which had not appeared anywhere in the sentences previously heard. Participants were significantly more successful at recognising words which had been unpredictable in their contexts, and, importantly, for Experiments 1 and 2, were significantly more successful at recognising words which had featured in disfluent or interrupted sentences. There was no difference between the recognition rates of words which had been disfluent and those which were affected by a noisy interruption. Collard et al., (2008) demonstrated that disfluency could raise attention to the speech stream, and the finding that interrupted words are equally well remembered leads to the suggestion that any noisy interruption can raise attention. Overall, the finding of memory benefits in response to disfluency, in the absence of attenuated N400 effects leads to the suggestion that different elements of disfluencies may be responsible for triggering these effects. The studies in this thesis also extend previous work by being designed to yield enough trials in the memory test portion of each experiment to permit ERP analysis of the memory data. Whilst clear ERP memory effects remained elusive, important progress was made in that memory ERPs were generated from a disfluency paradigm, and this provided a testing ground on which to demonstrate the use of linear mixed-effects modelling as an alternative to ANOVA analysis for ERPs. Mixed-effects models allow the analysis of unbalanced datasets, such as those generated in many memory experiments. Additionally, we demonstrate the ability to include crossed random effects for subjects and items, and when this is applied to the ERPs from the listening section of Experiment 1, the effect of fluency on N400 amplitude is no longer significant. Taken together, the results from the studies reported in this thesis suggest that temporal delay or disruption in speech can trigger raised attention, but do not necessarily trigger changes in listeners' expectations.

A self-control procedure that involved a later onset of a stimulus signalling a small reinforcer within the waiting time for a larger reinforcer was investigated to determine a point of shifting preference and a discounting function as the delay varied. The results from Experiment 1 to Experiment 3 showed exclusive impulsive choices regardless of the delay. In order to examine if the results were due to the procedure and the parameters, or the species used, Experiment 4 attempted to obtain shifts in preference using simultaneous onset of stimuli with the same species. The results demonstrated no changes in preference but an increase in proportion of self-control choices was shown. Due to the limited information from the replicated studies, the accounts for the results could not be concluded. The explanations derived from choice models seemed most plausible, but limitations of the choice models were discussed.

In a 2 December article entitled “Rising Tide of Sentiment against German Music,” critic W. J. Henderson detailed the ways that musical attitudes in the United States had been altered in recent months. Fritz Kreisler and Karl Muck were restricted in their performances, while Schumann-Heink took a temporary break from public concerts. Walter Damrosch and Leopold Stokowski took pains to emphasize their loyalty, but Damrosch’s new arrangement of “The Star-Spangled Banner” was criticized for being too ornate. The Original Dixieland Jazz Band and the Original Creole Band continued to ride the wave of jazz popularity. After further delays, the Fifteenth New York National Guard Regiment finally crossed the Atlantic Ocean and prepared to join the war in France.

In temporal planning, agents must schedule a set of events satisfying a set of predetermined constraints. These scheduling problems become more difficult when the duration of certain actions are outside the agent's control. Delay controllability is the generalized notion of whether a schedule can be constructed in the face of uncertainty if the agent eventually learns when events occur. Our work introduces the substantially more complex setting of determining variable-delay controllability, where an agent learns about events after some unknown but bounded amount of time has passed. We provide an efficient O(n^3) variable-delay controllability checker and show how to create an execution strategy for variable-delay controllability problems. To our knowledge, these essential capabilities are absent from existing controllability checking algorithms. We conclude by providing empirical evaluations of the quality of variable-delay controllability results as compared to approximations that use fixed delays to model the same problems.

In additive construction, ambitious goals to fabricate a concrete building in less than 24 hours are attempted. In the field, this goal relies on a metric of print time to make this conclusion, which excludes rest time and delays. The task to complete a building in 24 hours was put to the test with the first attempt at a fully continuous print of a structurally reinforced additively constructed concrete (ACC) building. A time series analysis was performed during the construction of a 512 ft2 (16’x32’x9.25’) building to explore the effect of delays on the completion time. This analysis included a study of the variation in comprehensive layer print times, expected trends and forecasting for what is expected in future prints of similar types. Furthermore, the study included a determination and comparison of print time, elapsed time, and construction time, as well as a look at the effect of environmental conditions on the delay events. Upon finishing, the analysis concluded that the 3D-printed building was completed in 14-hours of print time, 31.2- hours elapsed time, a total of 5 days of construction time. This emphasizes that reports on newly 3D-printed constructions need to provide a definition of time that includes all possible duration periods to communicate realistic capabilities of this new technology.

Industrial soil contamination is frequently unearthed by transportation agencies during construction within the right-of-way. As a result, transportation agencies may experience construction delays. Soils co-contaminated with high-molecular-weight polycyclic aromatic hydrocarbons (HMW-PAHs) and metals are commonly encountered in Illinois and exhibit recalcitrance towards conventional treatment technologies. This issue is exacerbated in the fine-grained soils common to Illinois, where low-permeability and immense sorption capacity increase treatment complexity, cost, and duration. Contaminated sites are spatially and temporally restrictive and require rapid in situ treatments, whereas conventional soil remediation requires 1 to 3 years on average. Consequently, transportation agencies typically pursue excavation and off-site disposal for expediency. However, this solution is expensive, so a comparatively expeditious and affordable treatment alternative is needed to combat the increasing cost of hazardous waste disposal. The objective of this work was to develop an accelerated in situ treatment approach adaptable for use at any construction site to cost-effectively remove HMW-PAHs and metals from clayey soil. It was hypothesized that an in situ electrochemical treatment which augments electrokinetics with H2O2 could remediate both HMW-PAHs and metals in less than a month. Bench-scale reactors resemblant of field-scale in situ electrokinetic systems were designed and fabricated to assess the electrochemical treatment of clayey soils contaminated with HMW-PAHs and metals. Pyrene, chromium, and manganese were used as model contaminants, spiked into kaolinite as a model clay. Electrokinetics were imposed by a low-intensity electrical field distributed by graphite rods. Electrolytic H2O2 systems were leveraged to distribute electrical current and facilitate contaminant removal. Average contaminant removals of 100%, 42.3%, and 4.5% were achieved for pyrene, manganese, and chromium, respectively. Successful development of this bench-scale treatment approach will serve to guide transportation agencies in field-scale implementation. The results from this work signify that electrochemical systems that leverage eco-friendly oxidant addition can replace excavation and disposal as a means of addressing clayey soils co-contaminated with HMW-PAHs and metals.

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%.