Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Clustering in Fast Collaborative Filtering Recommender Systems

—Searching the huge amount of information available on the Internet is undoubtedly a challenging task. A lot of new Web sites are created every day, containing not only text, but other types of resources: e.g., songs, movies or images. As a consequence, a simple search result list from search engines becomes insufﬁcient. Recommender systems are the solution supporting users in ﬁnding items, which are interesting for them. These items may be information as well as products, in general. The main distinctive feature of recommender systems is taking into account the personal needs and tastes of users. Collaborative ﬁltering approach is based on users’ interactions with the electronic system. Its main challenge is generating on-line recommendations in reasonable time when coping with a large data size. Appropriate tools to support recommender systems in increasing time efﬁciency are clustering algorithms, which ﬁnd similarities in off-line mode. Commonly, this causes a decrease in prediction accuracy of the ﬁnal recommendations. This article presents a high time efﬁciency approach based on multi-clustered data, which avoids negative consequences. The input data is represented by clusters of similar items or users, where one item or user may belong to more than one cluster. When recommendations are generated, the best cluster for the user or item is selected. The best cluster means that the user or item is the most similar to the center of the cluster. As a result, the ﬁnal accuracy is not decreased.
Efficient deactivation of unused LCC inverter for multiple transmitter wireless power transfer

The study addresses the difficulties in deactivating an unused transmitter (TX) element for a multiple-transmitter wireless power system that is driven by LCC resonant inverters. One difficulty of TX deactivation is a high-level of unwanted circulating current in unused TX coil, which increases the losses in unused TX. To suppress the unwanted current without the aid of high-voltage isolated switches and detuning capacitors, it is proposed that low-side switches in LCC bridge should be constantly turned on. The other difficulty is the runtime detuning of LCC resonant inverter in response to the activation or deactivation status of adjacent TX coil, which degrades the LCC inverter efficiency. A tuning switch and capacitor cannot directly be inserted at the LCC resonant path due to high-voltage stress and complex driving scheme. Instead, this study proposes a loop that adjusts the effective inductance of the TX coil with low-voltage stress and easy gate driving, thereby increasing the LCC inverter efficiency. The loop also provides an additional power path towards the receiver so that the coil-to-coil efficiency is also increased.
CEOR_A_302404 519..529

1Center of Rheumatoid Arthritis, BIOMAB, Bogota, Colombia; 2Universidad de la Costa-CUC, Departamento de Ciencias Económicas, Barranquilla, Colombia; 3Sociomedical Research Unit, Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Ciudad de México, Mexico; 4Sociomedical Research Unit, Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Ciudad de México, México; 5Fundación Santa Fé de Bogotá, Bogotá, Colombia Background: Seronegative rheumatoid arthritis (SRA) is a condition that is not well understood and difficult to confirm by a conventional diagnostic process. We aimed to quantify the potential cost-savings of an alternative diagnostic process (ADP) imagingbased, for patients with presumptive SRA from everyday clinical practice. Methods: We performed a retrospective analysis for patients with presumptive SRA who tested negative for both rheumatoid factor and anti-cyclic citrullinated peptide antibodies, through an ADP imaging-based, that is a standard clinical practice in our center. After we confirmed the diagnosis of SRA or reclassified patients in terms of another proper diagnosis, we estimate direct costs in two scenarios: a conventional and ADP. We compared the cost of RA treatment during the first year against the cost of the most misdiagnosed treatment (osteoarthritis) found after applying the ADP to determine potential cost-savings. Results: We included 440 patients with a presumptive diagnosis of SRA. According to the imaging-based ADP, SRA was confirmed in 106/440 (24.1%), unspecified RA in 9/440 (2.0%), and osteoarthritis in 325/440 (73.9%) of those patients. Although the costs of conventional diagnosis per patient is lower than those of ADP ($59,20 USD vs $269,57 USD), we found a potential drug cost-savings of $1,570,775.20 US Dollars after 1 year of correct treatment. Conclusion: An alternative diagnosis process, including X-rays, US and MRI imaging, and clinical and blood-test assessment, not only increased diagnostic certainty in patients referred for evaluation of presumptive SRA but also suggested a potential cost-savings in pharmacological treatments avoided in misdiagnosed patients.
Function of the Family Modulates Locomotor Circuit Activity in a Caenorhabditis elegans Seizure Model.

The highly conserved cochaperone DnaJ/Hsp40 family proteins are known to interact with molecular chaperone Hsp70, and can regulate many cellular processes including protein folding, translocation, and degradation. In studies of Caenorhabditis elegans locomotion mutants, we identi ﬁ ed a gain-of-function (gf) mutation in dnj-17 closely linked to the widely used e156 null allele of C. elegans GAD (glutamic acid decarboxylase) unc-25 . dnj-17 encodes a DnaJ protein orthologous to human DNAJA5. In C. elegans DNJ-17 is a cytosolic protein and is broadly expressed in many tissues. dnj-17(gf) causes a single amino acid substitution in a conserved domain, and behaves as a hypermorphic mutation. The effect of this dnj-17(gf) is most prominent in mutants lacking GABA synaptic transmission. In a seizure model caused by a mutation in the ionotropic acetylcholine receptor acr-2(gf) , dnj-17(gf) exacerbates the convulsion phenotype in conjunction with absence of GABA. Null mutants of dnj-17 show mild resistance to aldicarb, while dnj-17(gf) is hypersensitive. These results highlight the importance of DnaJ proteins in regulation of C. elegans locomotor circuit, and provide insights into the in vivo roles of DnaJ proteins in humans.
Replication / NeurIPS 2019 Reproducibility Challenge [Re] Hamiltonian Neural Networks

In today’s world, neural networks are being in almost every discipline resulting in signiﬁcant improvement in all the tools and applications. But in the ﬁeld of Physics, they struggle to attain the basic laws like conservation of momentum. The paper Hamiltonian Neural Networks addresses this issue by using Hamiltonian mechanics to train the neural network in an unsupervised method. The following report is an explanation of the paper and the code to reproduce the claimed results.
Nicola Maggini and Vincenzo Emanuele

Nicola Maggini and Vincenzo Emanuele Contextual effects on individual voting behaviour: the impact of party system nationalization in Europe Introduction The purpose of this article is to assess if and how party system nationalization—conceived as a contextual dimension—affects individual voting behaviour. Contemporary political science shows clearly that "context matters" (Lane and Ersson 1990; Marsh 2002). As far as voting behaviour is concerned, contextual effects are undoubtedly among the key factors influencing voting decision. Comparative studies on electoral behaviour are increasingly influenced by the expectation that characteristics of context, in which party choice takes place, are an important source of its variation. In the current analysis we focus on the territorial dimension of context and we conceive party system nationalization as the level of territorial homogeneity of party support in a given country. It is therefore considered as a contextual variable which may moderate the impact of individual-level characteristics on voting behaviour. In this regard, whether or not political parties are able to represent nationwide interests and preferences of the voters has important consequences on the way people vote.
Bayesian nowcasting with Laplacian-P-splines

During an epidemic, the daily number of reported (infected/death) cases is often lower than the actual number of cases due to underreporting. Nowcasting aims to estimate the cases that have not yet been reported and combine it with the already reported cases to obtain an estimate of the daily cases. In this paper, we present a fast and flexible Bayesian approach to nowcasting combining P-splines and Laplace approximations. The main benefit of Laplacian-P-splines (LPS) is the flexibility and faster computation time compared to Markov chain Monte Carlo (MCMC) algorithms that are often used for Bayesian inference. In addition, it is natural to quantify the prediction uncertainty with LPS in the Bayesian framework, and hence prediction intervals are easily obtained. Model performance is assessed through simulations, and the method is applied to the Belgian COVID-19 mortality cases for the year 2021. Simulation results show that our model has good predictive performance except when the nowcast date is near the peak date, where it has lower prediction interval coverage.
Prenatal exposure to persistent organic pollutants and changes in infant growth and childhood growth trajectories

Background: Children are born with a burden of persistent organic pollutants (POPs) which may have endocrine disrupting properties and have been postulated to contribute to the rise in childhood obesity. The current evidence is equivocal, which may be because many studies investigate the effects at one time point during childhood. We assessed associations between prenatal exposure to POPs and growth during infancy and childhood. Methods: We used data from two Belgian cohorts with cord blood measurements of five organochlorines [(dichlorodiphenyldichloroethylene (p,p'-DDE), hexachlorobenzene (HCB), polychlorinated biphenyls (PCB-138, -150, -180)] (N = 1,418) and two perfluoroalkyl substances [perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS)] (N = 346). We assessed infant growth, defined as body mass index (BMI) z-score change between birth and 2 years, and childhood growth, characterized as BMI trajectory from birth to 8 years. To evaluate associations between POP exposures and infant growth, we applied a multi-pollutant approach, using penalized elastic net regression with stability selection, controlling for covariates. To evaluate associations with childhood growth, we used single-pollutant linear mixed models with random effects for child individuals, parametrized using a natural cubic spline formulation. Results: Prenatal exposures to p,p'-DDE and PCB-153 were selected in elastic net models for infant growth analysis, but the selections were unstable. No clear association between any of the exposures and longer-term childhood growth trajectories was observed. We did not find evidence of effect modification by child sex. Conclusion: Our results suggest that prenatal exposure to PCB-153 and p,p'-DDE may affect infant growth in the first two years, with little evidence of more persistent effects. Keywords: organochlorines, poly- and perfluoroalkyl substances, infant growth, childhood growth trajectory, longitudinal study
Social Health and Change in Cognitive Capability among Older Adults: Findings from Four European Longitudinal Studies

Introduction: In this study, we examine whether social health markers measured at baseline are associated with differences in cognitive capability and the rate of cognitive decline over an 11-to-18-year period among older adults and compare results across studies. Methods: We applied an integrated data analysis approach to 16,858 participants (mean age 65 years; 56% female) from the National Survey for Health and Development (NSHD), the English Longitudinal Study of Aging (ELSA), the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K), and the Rotterdam Study. We used multilevel models to examine social health in relation to cognitive capability and the rate of cognitive decline. Results: Pooled estimates show distinct relationships between markers of social health and cognitive domains, e.g., a large network size (≥6 people vs. none) was associated with higher executive function (0.17 standard deviation [SD] [95% CI: 0.00, 0.34], I2 = 27%) but not with memory (0.08 SD [95% CI: −0.02, 0.18], I2 = 19%). We also observed pooled associations between being married or cohabiting, having a large network size, and participating in social activities with slower decline in cognitive capability. However, estimates were close to zero, e.g., 0.01 SD/year (95% CI: 0.01, 0.02) I2 = 19% for marital status and executive function. There were clear study-specific differences: results for average processing speed were the most homogenous, and results for average memory were the most heterogeneous. Conclusion: Overall, markers of good social health have a positive association with cognitive capability. However, we found differential associations between specific markers of social health and cognitive domains and differences between studies. These findings highlight the importance of examining between-study differences and considering the context specificity of findings in developing and deploying interventions.
Randomized Clinical Trials Patient- and Trial-Speciﬁc Barriers to Participation in Cardiovascular Randomized Clinical Trials

Objectives The purpose of this study was to quantitatively examine the association of patient- and trial-speciﬁc factors with participation in cardiovascular randomized clinical trials. Background Randomized clinical trials are central to evidenced-based medicine, but low patient participation rates and potentially modiﬁable barriers are not well understood. Methods At a large U.S. academic health system, we examined screening logs from December 1, 2005, to February 28, 2011, from 15 cardiovascular randomized clinical trials. We identiﬁed 655 patients who were screened and potentially eligible for participation in at least 1 trial. We used multivariable Poisson regression to quantify the risk of not participating in a trial associated with patient- and trial-speciﬁc factors. Results The median age was 63 years (interquartile range: 54 to 72), 35% were women, and the median Charlson Index was 2 (interquartile range: 1 to 5). Forty-two percent of patients did not participate in a trial. In multivariable regression (C-Index 0.85), trial-speciﬁc factors strongly associated with not participating included intensive trial-related testing (relative risk [RR]: 1.89; 95% conﬁdence interval [CI]: 1.63 to 2.20) and anticipated trial participation (cid:1) 6 months (RR: 4.10; 95% CI: 2.30 to 7.29). Patient-speciﬁc factors associated with not participating included older age (RR: 1.23; 95% CI: 1.11 to 1.36, per 10-year increase if age (cid:1) 65 years), out-of-state residence (RR: 1.26; 95% CI: 1.04 to 1.54), and female sex (RR: 1.17; 95% CI: 1.01 to 1.35). Race was not associated with participation. While patient-speciﬁc factors were associated with not participating in cardiovascular trials, longer trial duration and intensive trial-related testing were most strongly associated with risk for patients not participating. Innovative trial designs fostering convenience may most enhance trial participation. (J Am Coll Cardiol 2013;61: 762–9) ©
RAPID DETECTION OF METHICILLIN RESISTANT STAPHYLOCOCCI FROM THE NASAL SCREENING SWABS BY MANNITOL SALT AGAR WITH CEFOXITIN AND OXACILLIN DISKS

Objective: To assess the reliability of Manitol salt agar (MSA) for directly identifying Methicillin Resistant Staphylococcus aureus (MRSA) and Methicillin Resistant Coagulase negative Staphylococci, (MRCoNS) in nasal swabs for screening purposes using cefoxitin and oxacillin
DMSO_A_297315 683..690

1Faculty of Public Health, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam; 2Center for Population Health Sciences, Hanoi University of Public Health, Hanoi, Vietnam; 3Infection Control Department, University Medical Center Ho Chi Minh City, Ho Chi Minh City, Vietnam; 4Family Medicine Training Center, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam Background: Diabetes-related distress (DRD) refers to the condition of negative emotion as a result of living with diabetes and the burden of self-care. This study aims to evaluate the prevalence and associated factors of DRD among people with type 2 diabetes. Methods: A cross-sectional study was carried out on people with Type 2 Diabetes at three hospitals in Ho Chi Minh City, between April and November 2020. The study used the Vietnamese version of the Diabetes Distress Scale (DDS) which includes 17 items. The mean total distress score was calculated on the average of the 17 items. A mean score of equal to 2.0 or higher was classified as moderate to severe distress. Descriptive statistics were performed by frequency and percentage, and the multivariate Logistic Regression Analysis was used to assess information where p-value <0.05 was considered statistically significant. Results: A total of 517 participants, who were mainly over 60 years old (56.8%) with females being 65.0%, participated in the study. Results showed that 23.6% and 5.8% of them, respectively, were found as being moderately or highly distressed. Some factors that correlated with the total distress results included age, timescale of diabetes, and glycemic control level (HbA1c). The rate of total distress in those who were over 60 years old and had a HbA1c <7 were less prevalent than those who were under 60, and had a HbA1c ≥7 (OR 0.5 95% CI 0.3–0.7; OR 0.5 95% CI: 0.3–0.9, respectively, all p<0.05), whilst the timescale of diabetes between 5 and 10 years was significantly more prevalent than those who had a timescale less 5 years (OR 1.8 95% CI 1.1–2.9, p<0.05). Conclusion: A high rate of distress exists in people with diabetes. Therefore, combining the evaluation of distress as part of the regular diagnostic procedures of diabetes care, and recommending physicians apply a comprehensive approach to diabetes management, is necessary.
An efficient numerical algorithm for the L2 optimal transport problem with applications to image processing

We present a numerical method to solve the optimal transport problem with a quadratic cost when the source and target measures are periodic probability densities. This method is based on a numerical resolution of the corresponding Monge-Amp\`ere equation. We extend the damped Newton algorithm of Loeper and Rapetti \cite{LR} to the more general case of a non uniform density which is relevant to the optimal transport problem, and we show that our algorithm converges for sufficiently large damping coefficients. The main idea consists of designing an iterative scheme where the fully nonlinear equation is approximated by a non-constant coefficient linear elliptic PDE that we solve numerically. We introduce several improvements and some new techniques for the numerical resolution of the corresponding linear system. Namely, we use a Fast Fourier Transform (FFT) method by Strain \cite{St}, which allows to increase the efficiency of our algorithm against the standard finite difference method. Moreover, we use a fourth order finite difference scheme to approximate the partial derivatives involved in the nonlinear terms of the Newton algorithm, which are evaluated once at each iteration; this leads to a significant improvement of the accuracy of the method, but does not sacrifice its efficiency. Finally, we present some numerical experiments which demonstrate the robustness and efficiency of our method on several examples of image processing, including an application to multiple sclerosis disease detection.
Forecasting Responses of a Northern Peatland Carbon Cycle to Elevated CO 2 and a Gradient of Experimental Warming Geophysical Research: Biogeosciences

The ability to forecast ecological carbon cycling is imperative to land management in a world where past carbon ﬂ uxes are no longer a clear guide in the Anthropocene. However, carbon- ﬂ ux forecasting has not been practiced routinely like numerical weather prediction. This study explored (1) the relative contributions of model forcing data and parameters to uncertainty in forecasting ﬂ ux- versus pool-based carbon cycle variables and (2) the time points when temperature and CO 2 treatments may cause statistically detectable differences in those variables. We developed an online forecasting work ﬂ ow (Ecological Platform for Assimilation of Data (EcoPAD)), which facilitates iterative data-model integration. EcoPAD automates data transfer from sensor networks, data assimilation, and ecological forecasting. We used the Spruce and Peatland Responses Under Changing Experiments data collected from 2011 to 2014 to constrain the parameters in the Terrestrial Ecosystem Model, forecast carbon cycle responses to elevated CO 2 and a gradient of warming from 2015 to 2024, and specify uncertainties in the model output. Our results showed that data assimilation substantially reduces forecasting uncertainties. Interestingly, we found that the stochasticity of future external forcing contributed more to the uncertainty of forecasting future dynamics of C ﬂ ux-related variables than model parameters. However, the parameter uncertainty primarily contributes to the uncertainty in forecasting C pool-related response variables. Given the uncertainties in forecasting carbon ﬂ uxes and pools, our analysis showed that statistically different responses of fast-turnover pools to various CO 2 and warming treatments were observed sooner than slow-turnover pools. Our study has identi ﬁ ed the sources of uncertainties in model prediction and thus leads to improve ecological carbon cycling forecasts in the future.
Institutional Knowledge at Singapore Management University UDEL/SMU at TREC 2009 Entity Track

We report our methods and experiment results from the collaborative participation of the InfoLab group from University of Delaware and the school of Information Systems from Singapore Management University in the TREC 2009 Entity track. Our general goal is to study how we may apply language modeling approaches and natural language processing techniques to the task. Speci(cid:12)cally, we proposed to (cid:12)nd supporting information based on segment retrieval, to extract entities using Stanford NER tagger, and to rank entities based on a previously proposed probabilistic framework for expert (cid:12)nding.
Treating dynamical stability as an observable: a 5:2 MMR configuration for the extrasolar system HD 181433

The three-planet extrasolar system of HD 181433 has been detected with HARPS. The best-fit solution, announced by the discovery team, describes a highly unstable, self-disrupting configuration. In fact, a narrow observational window, only partially covering the longest orbital period, can lead to solutions representing unrealistic scenarios. Taking into account the dynamical stability as an additional observable while interpreting the RV data, we can analyse the phase space in a neighbourhood of the statistically best-fit and derive dynamically stable configurations that reproduce the observed RV signal. Our Newtonian stable best-fit model is capable of surviving for at least 250 Myrs. The two giant companions are found to be locked in the 5:2 MMR as Jupiter and Saturn in the Solar System. This mechanism does not allow close encounters even in case of highly eccentric orbits. Moreover, planets c and d are located in regions spanned by many other strong low-order MMRs. We study the dynamics of some plausible scenarios and we illustrate the behaviours caused by secular apsidal resonances and mean motion resonances. Furthermore, we find a terrestrial planet in the habitable zone of HD 181433 can retain stability. Apart from filling an empty gap in the system, this body could offer a harbour for life indeed. Additional measurements are necessary in order to investigate this hypothesis and can confirm the predictions outlined in the paper.