To see the other types of publications on this topic, follow the link: Generalized serial network.
Journal articles on the topic 'Generalized serial network'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 22 journal articles for your research on the topic 'Generalized serial network.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Ji, Bin, Dezhi Zhang, Samson S. Yu, and Binqiao Zhang. "Optimally solving the generalized serial-lock scheduling problem from a graph-theory-based multi-commodity network perspective." European Journal of Operational Research 288, no. 1 (January 2021): 47–62. http://dx.doi.org/10.1016/j.ejor.2020.05.035.
Full text
2
Chen, Rui, Zhenzhong Li, and Yi Lai. "Construction of a Multimodal Neuroimaging Data Fusion System and Evaluation of Mental Fatigue Using Nonlinear Analysis." Complexity 2021 (June 9, 2021): 1–13. http://dx.doi.org/10.1155/2021/8478868.
Full textAbstract:
The purpose of this research is to explore the optimization and fusion application of multimodal neuroimaging technology and analyze the evaluation method of human brain fatigue based on multimodal neuroimaging technology. Based on electroencephalogram (EEG) and fMRI (functional magnetic resonance imaging), the four-dimensional consistency of local neural activities (FOCA) and local multimodal serial analysis (LMSA) are first introduced to fuse EEG and fMRI organically. Second, the eigenspace maximal information canonical correlation analysis (emiCCA) is introduced to construct the multimodal neuroimaging data fusion system. Finally, how the brain function network is constructed is introduced. Based on the binary and the weighted brain function networks, the relationship between the human brain fatigue and the brain function network is evaluated by calculating the fractal dimension. Results demonstrate that FOCA performs well in temporal and spatial consistency indexes, and the mean level and standard deviation in the case of temporal and spatial consistency are approximately 0.45. The effect of LMSA indexes is significantly better than generalized linear models (GLMs). Under different signal-to-noise ratios (SNRs), the regression coefficient based on LMSA is much larger than the GLM estimate; the corresponding significance level is p < 0.05 ; and the maximum value of the regression coefficient appears near 0.2. In the data fusion system, the time-space matching has good results under the time accuracy based on EEG and the space accuracy based on fMRI, with the time accuracy above 88% and the space accuracy above 89%. The fractal dimension analysis based on the brain function network reveals that the weighted brain function network is more sensitive to mental fatigue. The state of human brain fatigue will make the brain function network more complicated. The fractal dimension with more network edges is around 2.2, while the fractal dimension with fewer network edges is around 1.6. The proposed data analysis and fusion system have great application potential and propose a new idea for analyzing human brain fatigue and brain aging.
3
Ramlow, Lukas, and Benjamin Lindner. "Interspike interval correlations in neuron models with adaptation and correlated noise." PLOS Computational Biology 17, no. 8 (August 27, 2021): e1009261. http://dx.doi.org/10.1371/journal.pcbi.1009261.
Full textAbstract:
The generation of neural action potentials (spikes) is random but nevertheless may result in a rich statistical structure of the spike sequence. In particular, contrary to the popular renewal assumption of theoreticians, the intervals between adjacent spikes are often correlated. Experimentally, different patterns of interspike-interval correlations have been observed and computational studies have identified spike-frequency adaptation and correlated noise as the two main mechanisms that can lead to such correlations. Analytical studies have focused on the single cases of either correlated (colored) noise or adaptation currents in combination with uncorrelated (white) noise. For low-pass filtered noise or adaptation, the serial correlation coefficient can be approximated as a single geometric sequence of the lag between the intervals, providing an explanation for some of the experimentally observed patterns. Here we address the problem of interval correlations for a widely used class of models, multidimensional integrate-and-fire neurons subject to a combination of colored and white noise sources and a spike-triggered adaptation current. Assuming weak noise, we derive a simple formula for the serial correlation coefficient, a sum of two geometric sequences, which accounts for a large class of correlation patterns. The theory is confirmed by means of numerical simulations in a number of special cases including the leaky, quadratic, and generalized integrate-and-fire models with colored noise and spike-frequency adaptation. Furthermore we study the case in which the adaptation current and the colored noise share the same time scale, corresponding to a slow stochastic population of adaptation channels; we demonstrate that our theory can account for a nonmonotonic dependence of the correlation coefficient on the channel’s time scale. Another application of the theory is a neuron driven by network-noise-like fluctuations (green noise). We also discuss the range of validity of our weak-noise theory and show that by changing the relative strength of white and colored noise sources, we can change the sign of the correlation coefficient. Finally, we apply our theory to a conductance-based model which demonstrates its broad applicability.
4
Zhao, Yang. "A spectral analysis based heteroscedastic model for the estimation of value at risk." Journal of Risk Finance 19, no. 3 (May 21, 2018): 295–314. http://dx.doi.org/10.1108/jrf-01-2017-0012.
Full textAbstract:
Purpose This paper aims to focus on a better model to capture the trait of varying volatility in various financial time series, as well as to obtain reliable estimate of value at risk (VaR). Design/methodology/approach The typical methods in spectral analysis are used to obtain the sample of conditional mean, conditional variance and residual term. The generalized regression neural network is used to establish a time-varying non-linear model, and the non-parametric kernel density estimation method is applied for the estimation of VaR. Findings The proposed model is able to follow the heteroscedastic characteristic which is common in financial time series, and the estimated VaR is satisfactory. Practical implications The analysis method in this study allows the hedgers, bankers, financial analysts as well as economists to draw a better inference from financial time series. Also, relatively more precise estimate of the VaR value for a certain kind of financial asset is available. The model with its derived estimates would definitely help in developing other models. Originality/value Up-to-date, the study in literature which models financial time serial from the viewpoint of spectral analysis is rare to see. Thus, the proposed model, along with a comprehensive empirical study which reveals desirable result for the estimation of VaR would enrich the related researches at present.
5
Tremblay, Antoine, Elissa Asp, Anne Johnson, Malgorzata Zarzycka Migdal, Tim Bardouille, and Aaron J. Newman. "What the Networks Tell us about Serial and Parallel Processing." Mental Lexicon 11, no. 1 (June 7, 2016): 115–60. http://dx.doi.org/10.1075/ml.11.1.06tre.
Full textAbstract:
A large literature documenting facilitative effects for high frequency complex words and phrases has led to proposals that high frequency phrases may be stored in memory rather than constructed on-line from their component parts (similarly to high frequency complex words). To investigate this, we explored language processing during a novel picture description task. Using the magneto-encephalographam (MEG) technique and generalised additive mixed-effects modelling, we characterised the effects of the frequency of use of single words as well as two-, three-, and four-word sequences (N-grams) on brain activity during the pre-production stage of unconstrained overt picture description. We expected amplitude responses to be modulated by N-gram frequency such that if N-grams were stored we would see a corresponding reduction or flattening in amplitudes as frequency increased. We found that while amplitude responses to increasing N-gram frequencies corresponded with our expectations about facilitation, the effect appeared at low frequency ranges and for single words only in the phonological network. We additionally found that high frequency N-grams elicited activity increases in some networks, which may be signs of competition or combination depending on the network. Moreover, this effect was not reliable for single word frequencies. These amplitude responses do not clearly support storage for high frequency multi-word sequences. To probe these unexpected results, we turned our attention to network topographies and the timing. We found that, with the exception of an initial ‘sentence’ network, all the networks aggregated peaks from more than one domain (e.g. semantics and phonology). Moreover, although activity moved serially from anterior ventral networks to dorsal posterior networks during processing, as expected in combinatorial accounts, sentence processing and semantic networks ran largely in parallel. Thus, network topographies and timing may account for (some) facilitative effects associated with frequency. We review literature relevant to the network topographies and timing and briefly discuss our results in relation to current processing and theoretical models.
6
Maiborodin, Igor, Aleksandr Shevela, Michael Toder, Sergey Marchukov, Natalya Tursunova, Marina Klinnikova, Vitalina Maiborodina, Elena Lushnikova, and Andrew Shevela. "Multipotent Stromal Cell Extracellular Vesicle Distribution in Distant Organs after Introduction into a Bone Tissue Defect of a Limb." Life 11, no. 4 (April 1, 2021): 306. http://dx.doi.org/10.3390/life11040306.
Full textAbstract:
When administered intravenously, extracellular vesicles derived from multipotent stromal cells (MSC EVs) immediately pass through the lungs along with the blood and regularly spread to all organs. When administered intraperitoneally, they are absorbed either into the blood or into the lymph and are quickly disseminated throughout the body. The possibility of generalized spread of MSC EVs to distant organs in case of local intratissular administration remains unexplored. However, it is impossible to exclude MSC EV influence on tissues distant from the injection site due to the active or passive migration of these injected nanoparticles through the vessels. The research is based on findings obtained when studying the samples of lungs, heart, spleen, and liver of outbred rabbits of both sexes weighing 3–4 kg at various times after the injection of EVs derived from MSCs of bone marrow origin and labeled by PKH26 into an artificially created defect of the proximal condyle of the tibia. MSC EVs were isolated by serial ultracentrifugation and characterized by transmission electron microscopy and flow cytometry. After the introduction of MSC EVs into the damaged proximal condyle of the tibia of rabbits, these MSC EVs can be found most frequently in the lungs, myocardium, liver, and spleen. MSC EVs enter all of these organs with the blood flow. The lungs contained the maximum number of labeled MSC EVs; moreover, they were often associated with detritus and were located in the lumen of the alveoli. In the capillary network of various organs except the myocardium, MSC EVs are adsorbed by paravasal phagocytes; in some cases, specifically labeled small dust-like objects can be detected throughout the entire experiment—up to ten days of observation. Therefore, we can conclude that the entire body, including distant organs, is effected both by antigenic detritus, which appeared in the bloodstream after extensive surgery, and MSC EVs introduced from the outside.
7
Sharon, Eran, Noam Presman, and Simon Litsyn. "Convergence analysis of generalized serial message-passing schedules." IEEE Journal on Selected Areas in Communications 27, no. 6 (August 2009): 1013–24. http://dx.doi.org/10.1109/jsac.2009.090819.
Full text
8
Datsikas, Christos K., Kostas P. Peppas, Nikos C. Sagias, and George S. Tombras. "Serial relaying communications over generalized-gamma fading channels." Wireless Communications and Mobile Computing 12, no. 13 (February 3, 2011): 1191–202. http://dx.doi.org/10.1002/wcm.1047.
Full text
9
Rudenko, Oleg, Oleksandr Bezsonov, and Oleksandr Romanyk. "Neural network time series prediction based on multilayer perceptron." Development Management 17, no. 1 (May 7, 2019): 23–34. http://dx.doi.org/10.21511/dm.5(1).2019.03.
Full textAbstract:
Until recently, the statistical approach was the main technique in solving the prediction problem. In the framework of static models, the tasks of forecasting, the identification of hidden periodicity in data, analysis of dependencies, risk assessment in decision making, and others are solved. The general disadvantage of statistical models is the complexity of choosing the type of the model and selecting its parameters. Computing intelligence methods, among which artificial neural networks should be considered at first, can serve as alternative to statistical methods. The ability of the neural network to comprehensively process information follows from their ability to generalize and isolate hidden dependencies between input and output data. Significant advantage of neural networks is that they are capable of learning and generalizing the accumulated knowledge. The article proposes a method of neural networks training in solving the problem of prediction of the time series. Most of the predictive tasks of the time series are characterized by high levels of nonlinearity and non-stationary, noisiness, irregular trends, jumps, abnormal emissions. In these conditions, rigid statistical assumptions about the properties of the time series often limit the possibilities of classical forecasting methods. The alternative methods to statistical methods can be the methods of computational intelligence, which include artificial neural networks. The simulation results confirmed that the proposed method of training the neural network can significantly improve the prediction accuracy of the time series.
10
Zhang, Shiyong, and Gongliang Chen. "Micro-Trivium: A lightweight algorithm designed for radio frequency identification systems." International Journal of Distributed Sensor Networks 13, no. 2 (February 2017): 155014771769417. http://dx.doi.org/10.1177/1550147717694171.
Full textAbstract:
Distributed sensor networks have been widely applied to healthcare, environmental monitoring and management, intelligent transportation, and other fields in which network sensors collect and transmit information about their surrounding environment. Radio frequency identification technology transmits an object’s identification as a unique serial number—using radio waves as the transmission carrier—and is becoming an important building block for distributed sensor networks. However, the security of radio frequency identification systems is a major industrial concern that can significantly hinder the market growth of distributed sensor networks. Trivium is a well-known lightweight synchronous stream cipher that was submitted to the European eSTREAM project in April 2005. In this article, we generalize Trivium to the Trivium-Model algorithm and highlight that security is mainly determined by the internal state bits and the number of nonlinear terms. We propose principles for choosing parameters and generating better parameters that are feasible for low-cost radio frequency identification tags in distributed sensor networks. The new algorithm, named Micro-Trivium, requires less power and a smaller chip area than the original Trivium, which is proven using experimental data and results. Mathematical analysis shows that using Micro-Trivium is as secure as using Trivium.
11
Gupta, Meenu, Man Singh, and Deepak Gupta. "The Time Independent Analysis of Finite Waiting Space Generalised Multichannel Mixed Queuing System with Balking and Reneging Due to Long Queue and Some Urgent Message." Journal of Computational and Theoretical Nanoscience 17, no. 11 (November 1, 2020): 5057–61. http://dx.doi.org/10.1166/jctn.2020.9341.
Full textAbstract:
The Proposed queuing model comprises of M serial service channels connected to N non-serial service channels. Inside every serial as well as non-serial service channel multiple parallel servers are allocated. Customers are allowed to balk as well as renege at any server inside the queuing model. Along with welsh because of long queue, reneging due to some urgent phone call or text information received, while waiting in the queue is applied in this queuing model. Using (Kelly, F.P., 1975. Networks of queues with customers of different types. Journal of Applied Probability, 12(3), pp.542–554) the difference-differential equations of the proposed model are obtained. Considering the system to be time independent, the time independent equations and corresponding solutions for various cases in the proposed queuing model are obtained. Further, it is submitted that the appearance process is Poisson, the administration time circulation is exponential, waiting space is finite, arrival of the customer depends upon the queue size at every service channel (serial/nonserial) and Service is done in random order rather than First come first serve principle.
12
TSANG, ERIC C. C., S. S. QIU, and DANIEL S. YEUNG. "CONVERGENCE ANALYSIS OF A DISCRETE HOPFIELD NEURAL NETWORK WITH DELAY AND ITS APPLICATION TO KNOWLEDGE REFINEMENT." International Journal of Pattern Recognition and Artificial Intelligence 21, no. 03 (May 2007): 515–41. http://dx.doi.org/10.1142/s0218001407005491.
Full textAbstract:
This paper investigates the convergence theorems that are associated with a Discrete Hopfield Neural Network (DHNN) with delay. We present two updating rules, one for serial mode and the other for parallel mode. The speed of convergence of these proposed updating rules is faster than all of the existing updating rules. It has been proved in this paper that a DHNN with delay will converge to a stable state when operating in a serial mode if the matrix of weights of the no-delay term is symmetric. In addition, it has been proved that they will converge to a stable state when operating in a parallel mode if the matrix of weights of the no-delay term is a symmetric and non-negative definite matrix. The condition for convergence of a DHNN without delay can been relaxed from the need to have a symmetric matrix to an even weaker condition of having a quasi-symmetric matrix. The results in this paper extend both the existing results concerning the convergence of a DHNN without delay and our previous findings. By means of the new network structure and its convergence theorems, we propose a local searching algorithm for combinatorial optimization. We also relate the maximum value of a bivariate energy function to the stable states of a DHNN with delay, which generalizes Hopfield's energy function. Moreover, for the serial model we give the relationship between the convergence of the energy function and the convergence of the corresponding network. One application is presented to demonstrate the higher rate of convergence and the accuracy of the classification using our algorithm.
13
Ahn, Hyun-Soo, and Rhonda Righter. "Dynamic load balancing with flexible workers." Advances in Applied Probability 38, no. 03 (September 2006): 621–42. http://dx.doi.org/10.1017/s0001867800001208.
Full textAbstract:
We study the problem of dynamically allocating flexible workers to stations in tandem or serial manufacturing systems. Workers are trained to do a subset of consecutive tasks. We show that the optimal policy is often LBFS (last buffer first-served) or FBFS (first buffer first-served). These results generalize earlier results on the optimality of the pick-and-run, expedite, and bucket brigade-type policies. We also show that, for exponential processing times and general manufacturing networks, the optimal policy will tend to have several workers assigned to the same station.
14
Ahn, Hyun-Soo, and Rhonda Righter. "Dynamic load balancing with flexible workers." Advances in Applied Probability 38, no. 3 (September 2006): 621–42. http://dx.doi.org/10.1239/aap/1158684995.
Full textAbstract:
We study the problem of dynamically allocating flexible workers to stations in tandem or serial manufacturing systems. Workers are trained to do a subset of consecutive tasks. We show that the optimal policy is often LBFS (last buffer first-served) or FBFS (first buffer first-served). These results generalize earlier results on the optimality of the pick-and-run, expedite, and bucket brigade-type policies. We also show that, for exponential processing times and general manufacturing networks, the optimal policy will tend to have several workers assigned to the same station.
15
Giunta, G., A. Neri, and M. Carli. "Constrained optimization of noncoherent serial acquisition of spread-spectrum code by exploiting the generalized Q-functions." IEEE Transactions on Vehicular Technology 52, no. 5 (September 2003): 1378–85. http://dx.doi.org/10.1109/tvt.2003.816649.
Full text
16
Tuzlukov, Vyacheslav. "Interference Cancellation for MIMO Systems Employing the Generalized Receiver with High Spectral Efficiency." WSEAS TRANSACTIONS ON SIGNAL PROCESSING 17 (March 31, 2021): 1–15. http://dx.doi.org/10.37394/232014.2021.17.1.
Full textAbstract:
In this paper, we investigate the performan-ce in terms of symbol error probability (SEP) of multipleinput multiple-output (MIMO) systems employing the ge-neralized receiver with high spectral efficiency. In particular, we consider the coherent detection of M-PSK signals in a flat Rayleigh fading environment. We focus on spectrally efficient MIMO systems where after serial-to-parallel con-version, several sub-streams of symbols are simultaneously transmitted by using an antenna array, thereby increasing the spectral efficiency. The reception is based on linear mi-nimum mean-square-error (MMSE) combining, eventually followed by successive interference cancellation. Exact and approximate expressions are derived for an arbitrary nu-mber of transmitting and receiving antenna elements. Sim-ulation results confirm the validity of our analytical meth-odology.
17
Pavlović, Nina, and Jasmina Petrović. "Trust and subjective well-being in Serbia during the pandemic: Research results." Socioloski pregled 54, no. 3 (2020): 560–82. http://dx.doi.org/10.5937/socpreg54-27816.
Full textAbstract:
The context of a pandemic caused by an infectious agent and the resulting health risk to a large number of people is a new type of risk contemporary humans are not quite familiar with. In addition to forcing citizens to rely on the effects of controlled medical and epidemiological measures, this kind of situation steers citizens towards cooperation and solidarity as well as towards personal capabilities of functioning during a crisis and it requires a certain degree of trust, not only in the institutions but also in other persons. The aim of this paper is to learn to what degree Serbian citizens trust others during the COVID-19 pandemic and whether this level of generalized trust differs among different sociodemographic groups, or more precisely, which groups were affected the most by the absence of generalized trust. The paper also analyzes a set of variables which are either a part of the concept of subjective well-being (feeling of happiness and life satisfaction) or are closely connected to it (the feeling of control over life, subjective health assessment, and assessments of solidarity and honesty of others). The analyzed data were obtained from a sample of 602 adult Serbian citizens who participated in an online survey in May 2020 by completing a questionnaire they received via e-mail and social networks from multiple access points. These data are compared to the newest available data on the given indicators in Serbia before the pandemic, collected within the European Values Study (EVS) in 2017 and the European Social Survey (ESS) in 2018. The results indicate a significant decrease in happiness and continuously low levels of the feeling of control over life and life satisfaction, but also an increase in the assessed honesty and solidarity of others. These findings are in accordance with the results of the previous studies, which revealed different dominant aspects in the analyzed concepts, leading to their different flexibility and (non)resilience to the changes in society.
18
Bihl, Trevor J., Todd J. Paciencia, Kenneth W. Bauer, and Michael A. Temple. "Cyber-Physical Security with RF Fingerprint Classification through Distance Measure Extensions of Generalized Relevance Learning Vector Quantization." Security and Communication Networks 2020 (February 24, 2020): 1–12. http://dx.doi.org/10.1155/2020/3909763.
Full textAbstract:
Radio frequency (RF) fingerprinting extracts fingerprint features from RF signals to protect against masquerade attacks by enabling reliable authentication of communication devices at the “serial number” level. Facilitating the reliable authentication of communication devices are machine learning (ML) algorithms which find meaningful statistical differences between measured data. The Generalized Relevance Learning Vector Quantization-Improved (GRLVQI) classifier is one ML algorithm which has shown efficacy for RF fingerprinting device discrimination. GRLVQI extends the Learning Vector Quantization (LVQ) family of “winner take all” classifiers that develop prototype vectors (PVs) which represent data. In LVQ algorithms, distances are computed between exemplars and PVs, and PVs are iteratively moved to accurately represent the data. GRLVQI extends LVQ with a sigmoidal cost function, relevance learning, and PV update logic improvements. However, both LVQ and GRLVQI are limited due to a reliance on squared Euclidean distance measures and a seemingly complex algorithm structure if changes are made to the underlying distance measure. Herein, the authors (1) develop GRLVQI-D (distance), an extension of GRLVQI to consider alternative distance measures and (2) present the Cosine GRLVQI classifier using this framework. To evaluate this framework, the authors consider experimentally collected Z-wave RF signals and develop RF fingerprints to identify devices. Z-wave devices are low-cost, low-power communication technologies seen increasingly in critical infrastructure. Both classification and verification, claimed identity, and performance comparisons are made with the new Cosine GRLVQI algorithm. The results show more robust performance when using the Cosine GRLVQI algorithm when compared with four algorithms in the literature. Additionally, the methodology used to create Cosine GRLVQI is generalizable to alternative measures.
19
Stanojevic, Dragan, and Dragana Stokanic. "Between Sicilia and Lombardy: Relation between trust, civil norms and social participation among citizens of Serbia." Sociologija 56, no. 2 (2014): 181–200. http://dx.doi.org/10.2298/soc1402181s.
Full textAbstract:
The one of the key precondition of social and political participation of citizens is their interpersonal and institutional trust. In order to avoid the increase of individual atomization and/or excessively rise of informal support networks, institutional organizations are crucial. For that reason, it is necessary to exist certain level of trust in institutional arrangements. This paper will be focused on widely used concept of social capital for analysis of interaction between trust, social norms and participation. Concerning participation, in this paper the difference between ?generalized? trust in public institutions and ?specific?, personalized trust in people is explained. This situation of low trust in people and institutions which are interlinked and create general atmosphere of distrust is present in post-socialist societies, such as Serbia. Firstly, the aim of this paper is to show level of participation in different organizations and the trust of citizens of Serbia in political institutions, as well as trust in people in general. Additionally, the acceptance of civil norms will be presented. Secondly, it will be analyzed in what extant formal organizations contribute to the trust creation and the acceptance of social norms as forms of universal values which are necessary for basic social consensus and solidarity. Also, it will be presented the relation between trust in certain institutions and organizations and the acceptance of civil norms. In order to achieve these goals, it will be used quantitative analysis and databases World Values Survey, fifth wave conducted from 2005 to 2007.
20
Giovenco, Danielle, Katherine Gill, Lauren Fynn, Menna Duyver, Shannon O’Rourke, Ariane van der Straten, Jennifer F. Morton, Connie L. Celum, and Linda-Gail Bekker. "Experiences of oral pre-exposure prophylaxis (PrEP) use disclosure among South African adolescent girls and young women and its perceived impact on adherence." PLOS ONE 16, no. 3 (March 5, 2021): e0248307. http://dx.doi.org/10.1371/journal.pone.0248307.
Full textAbstract:
Introduction There is limited understanding of how social dynamics impact pre-exposure prophylaxis (PrEP) adherence among adolescent girls and young women (AGYW) in generalized HIV-epidemic settings. We examined experiences of oral PrEP use disclosure to various social groups with the goal of identifying supportive relationships that can be leveraged to promote adherence. Methods We used qualitative methods to explore experiences disclosing PrEP use and the perceived impact of disclosure on adherence among 22 South African AGYW (16–25 years) taking daily oral PrEP. Serial in-depth-interviews (IDIs) were conducted 1-, 3-, and 12-months post-PrEP initiation. Respondents also self-reported their disclosures separately for various social groups and adherence was assessed using intracellular tenofovir-diphosphate levels. Results Qualitative respondents had a median age of 20.5 years and reported disclosing their PrEP use to friends (n = 36 total disclosures), partners, siblings, other family members (n = 24 disclosures each), and parents (n = 19 disclosures). IDI data revealed that parents and partners provided the most support to respondents and a lack of support from these groups was most often perceived as negatively affecting PrEP use. AGYW described difficulties explaining PrEP to their mothers, who believed PrEP was HIV treatment or would lead to HIV infection. Disclosure to household members was notably meaningful for AGYW (both positively and negatively). Respondents reported leveraging supportive relationships for pill reminders. For respondents who perceived a household member would be unsupportive, however, non-disclosure was less feasible and PrEP use was often stigmatized. To avoid stigma, several respondents hid or discontinued PrEP. Conclusions While supportive relationships may facilitate PrEP use, disclosure can also lead to stigma. Counselors should support AGYW in disclosing to key people in their social networks and provide AGYW with materials that lend credibility to explanations of PrEP. Community education is necessary to alleviate PrEP-related stigma and facilitate disclosure.
21
Wang, Peng, Jun Wang, Yun Yan, Yingdong Si, Xiangping Zhan, and Yu Tian. "Relationship Between Loneliness and Depression Among Chinese Junior High School Students: The Serial Mediating Roles of Internet Gaming Disorder, Social Network Use, and Generalized Pathological Internet Use." Frontiers in Psychology 11 (February 12, 2021). http://dx.doi.org/10.3389/fpsyg.2020.529665.
Full textAbstract:
This study aimed to explore the mediating effects of internet gaming disorder, social network use, and generalized pathological internet use (GPIU) on the association between loneliness and depression. A total of 2211 junior high school students completed questionnaires regarding loneliness, internet gaming disorder, social network use, GPIU, and depression (aged 10–16 years). The results of a structural equation model revealed that (a) the path coefficient of loneliness to depression was significantly positive, (b) loneliness could not predict depression through GPIU directly, but (c) loneliness could predict depression through internet gaming disorder to GPIU, (d) loneliness could predict depression through social network use to GPIU, and (e) loneliness could not predict depression through internet gaming disorder to social network use to GPIU. These results provided significant implications for the prevention and reduction of depression in Chinese junior high school students.
22
Palowitch, John. "Computing the statistical significance of optimized communities in networks." Scientific Reports 9, no. 1 (December 2019). http://dx.doi.org/10.1038/s41598-019-54708-8.
Full textAbstract:
AbstractIn scientific problems involving systems that can be modeled as a network (or “graph”), it is often of interest to find network communities - strongly connected node subsets - for unsupervised learning, feature discovery, anomaly detection, or scientific study. The vast majority of community detection methods proceed via optimization of a quality function, which is possible even on random networks without communities. Therefore there is usually not an easy way to tell if a community is “significant”, in this context meaning more internally connected than would be expected under a random graph model without communities. This paper generalizes existing null models and statistical tests for this purpose to bipartite graphs, and introduces a new significance scoring algorithm called Fast Optimized Community Significance (FOCS) that is highly scalable and agnostic to the type of graph. Compared with existing methods on unipartite graphs, FOCS is more numerically stable and better balances the trade-off between detection power and false positives. On a large-scale bipartite graph derived from the Internet Movie Database (IMDB), the significance scores provided by FOCS correlate strongly with meaningful actor/director collaborations on serial cinematic projects.