Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing User Experience Via Calibration Minimization using ML Techniques

—Electromyogram (EMG) signals are used to recognize gestures that could be used for prosthetic-based and hands-free human computer interaction. Minimizing calibration times for users while preserving the accuracy, is one of the main challenges facing the practicality, user acceptance and spread of upper limb movements’ detection systems. This paper studies the effect of minimized user involvement, thus user calibration time and effort, on the user-independent system accuracy. It exploits time based features extracted from EMG signals. One-versus-all kernel based Support Vector Machine (SVM) and K Nearest Neighbors (KNN) are used for classification. The experiments are conducted using a dataset having five subjects performing six distinct movements. Two experiments performed, one with complete user dependence condition and the other with the partial dependence. The results show that the involvement of at least two samples, representing around 2% of sample space, increase the performance by 62.6% in case of SVM, achieving accuracy result equal to 89.6% on average; while the involvement of at least three samples, representing around 3% of sample space, cause the increase by 50.6% in case of KNN, achieving accuracy result equal to 78.2% on average. The results confirmed the great impact on system accuracy when involving only small number of user samples in the model-building process using traditional classification methods.
Field Evaluation of a Safe, Easy, and Low-Cost Protocol for Shipment of Samples from Suspected Cases of Foot-and-Mouth Disease to Diagnostic Laboratories

Identification and characterization of the foot-and-mouth disease virus (FMDV) strains circulating in endemic countries and their dynamics are essential elements of the global FMD control strategy. Characterization of FMDV is usually performed in reference laboratories (RL). However, shipping of FMD samples to RL is a challenge due to the cost and biosafety requirements of transportation, resulting in a lack of knowledge about the strains circulating in some endemic areas. In order to simplify this step and to encourage sample submission to RL, we have previously developed a low-cost protocol for the shipment of FMD samples based on the use of lateral flow devices (LFDs) combined with a simple virus inactivation step using 0.2% citric acid. The present study aimed to evaluate this inactivation protocol in the field. For this purpose, 60 suspected FMD clinical samples were collected in Nigeria, Pakistan, and Turkey, three countries where FMD is endemic. Sample treatment, testing on LFDs, and virus inactivation steps were performed in the field when possible. The effectiveness of the virus inactivation was confirmed at the RL. After RNA extraction from the 60 inactivated LFDs, all were confirmed as FMDV positive by real-time reverse transcription polymerase chain reaction (RT-PCR). The serotype was identified by conventional RT-PCR for 86% of the samples. The topotype and/or lineage was successfully determined for 60% of the samples by Sanger sequencing and sequence analyses. After chemical transfection of RNA extracted from inactivated LFDs, into permissive cells, infectious virus was rescued from 15% of the samples. Implementation of this user-friendly protocol can substantially reduce shipping costs, which should increase the submission of field samples and therefore improve knowledge of the circulating FMDV strains.
Seasonal inﬂuenza vaccine effectiveness against laboratory-conﬁrmed inﬂuenza hospitalizations – Latin America, 2013 q the REVELAC-i network participants

Background: Despite widespread utilization of inﬂuenza vaccines, effectiveness (VE) has not been rou- tinely measured in Latin America. Methods: We used a case test-negative control design to estimate trivalent inactivated inﬂuenza VE against laboratory-conﬁrmed inﬂuenza among hospitalized children aged 6 months-5 years and adults aged (cid:1) 60 years which are age-groups targeted for vaccination. We sought persons with severe acute res- piratory infections (SARI), hospitalized at 71 sentinel hospitals in Argentina, Brazil, Chile, Colombia, Costa Rica, El Salvador, Honduras, Panama, and Paraguay during January–December 2013. Cases had an inﬂu- enza virus infection conﬁrmed by real-time reverse transcription PCR (rRT-PCR); controls had a negative rRT-PCR result for inﬂuenza viruses. We used a two-stage random effects model to estimate pooled VE per target age-group, adjusting for the month of illness onset, age and preexisting medical conditions. Results: We identiﬁed 2620 SARI patients across sites: 246 inﬂuenza cases and 720 inﬂuenza-negative controls aged (cid:3) 5 years and 448 cases and 1206 controls aged (cid:1) 60 years. The most commonly identiﬁed subtype among participants (48%) was the inﬂuenza A(H1N1)pdm09 virus followed by inﬂuenza A (H3N2) (34%) and inﬂuenza B (18%) viruses. Among children, the adjusted VE of full vaccination (one dose for previously vaccinated or two if vaccine naïve) against any inﬂuenza virus SARI was 47% (95% conﬁ- dence interval [CI]: 14–71%); VE was 58% (95% CI: 16–79%) against inﬂuenza A(H1N1)pdm09, and 65% (95% CI: (cid:4) 9; 89%) against inﬂuenza A(H3N2) viruses associated SARI. Crude VE of full vaccination against inﬂuenza B viruses associated SARI among children was 3% (95% CI: (cid:4) 150; 63). Among adults aged (cid:1) 60 years, adjusted VE against any inﬂuenza SARI was 48% (95% CI: 34–60%); VE was 54% (95% CI: 37–69%) against inﬂuenza A(H1N1)pdm09, 43% (95% CI: 18–61%) against inﬂuenza A(H3N2) and 34% (95% CI: (cid:4) 4; 58%) against B viruses associated SARI. Conclusion: Inﬂuenza vaccine provided moderate protection against severe inﬂuenza illness among fully vaccinated young children and older adults, supporting current vaccination strategies.
Seasonal Influenza Vaccine Effectiveness in Persons Aged 15–64 Years: A Systematic Review and Meta-Analysis

Influenza is a respiratory disease caused by the influenza virus, which is highly transmissible in humans. This paper presents a systematic review and meta-analysis of randomized controlled trials (RCTs) and test-negative designs (TNDs) to assess the vaccine effectiveness (VE) of seasonal influenza vaccines (SIVs) in humans aged 15 to 64 years. An electronic search to identify all relevant studies was performed. The outcome measure of interest was VE on laboratory-confirmed influenza (any strain). Quality assessment was performed using the Cochrane risk-of-bias tool for RCTs and the ROBINS-I tool for TNDs. The search identified a total of 2993 records, but only 123 studies from 73 papers were included in the meta-analysis. Of these studies, 9 were RCTs and 116 were TNDs. The pooled VE was 48% (95% CI: 42–54) for RCTs, 55.4% (95% CI: 43.2–64.9) when there was a match between the vaccine and most prevalent circulating strains and 39.3% (95% CI: 23.5–51.9) otherwise. The TNDs’ adjusted VE was equal to 39.9% (95% CI: 31–48), 45.1 (95% CI: 38.7–50.8) when there was a match and 35.1 (95% CI: 29.0–40.7) otherwise. The match between strains included in the vaccine and strains in circulation is the most important factor in the VE. It increases by more than 25% when there is a match with the most prevalent circulating strains. The laboratorial method for confirmation of influenza is a possible source of bias when estimating VE.
Estimation of peak-discharge frequency of urban streams in Jefferson County, Kentucky

An investigation of flood-hydrograph characteristics for streams in urban Jefferson County, Kentucky, was made to obtain hydrologic information needed for waterresources management. Equations for estimating peak-discharge frequencies for ungaged streams in the county were developed by combining (1) long-term annual peakdischarge data and rainfall-runoff data collected from 1991 to 1995 in 13 urban basins and (2) long-term annual peak-discharge data in four rural basins located in hydrologically similar areas of neighboring counties. The basins ranged in size from 1.36 to 64.0 square miles. The U.S. Geological Survey RainfallRunoff Model (RRM) was calibrated for each of the urban basins. The calibrated models were used with long-term, historical rainfall and pan-evaporation data to simulate 79 years of annual peak-discharge data. Peak-discharge frequencies were estimated by fitting the logarithms of the annual peak discharges to a Pearson-Type III frequency distribution. The simulated peak-discharge frequencies were adjusted for improved reliability by application of bias-correction factors derived from peakdischarge frequencies based on local, observed annual peak discharges. The three-parameter and the preferred seven-parameter nationwide urban-peak-discharge regression equations previously developed by USGS investigators provided biased (high) estimates for the urban basins studied. Generalized-least-square regression procedures were used to relate peakdischarge frequency to selected basin characteristics. Regression equations were developed to estimate peak-discharge frequency by adjusting peak-dischargefrequency estimates made by use of the threeparameter nationwide urban regression equations. The regression equations are presented in equivalent forms as functions of contributing drainage area, main-channel slope, and basin development factor, which is an index for measuring the efficiency of the basin drainage system. Estimates of peak discharges for streams in the county can be made for the 2-, 5-, 10-, 25-, 50-, and 100-year recurrence intervals by use of the regression equations. The average standard errors of prediction of the regression equations ranges from ± 34 to ± 45 percent. The regression equations are applicable to ungaged streams in the county having a specific range of basin characteristics.
The influence of Big Five personality traits on college students’ key competencies: the mediating effect of psychological capital

Background In recent years, both society and employers have put forward higher requirements for the comprehensive quality of college students in the new era. Based on the conservation of resources theory and life-cycle approach, this study aimed to examine the relationship between the Big Five personality traits, the psychological capital, and the key competencies among college students and analyzed the mediating role of the psychological capital in this link. Methods A total of 1,132 Chinese undergraduates (67.40% girls; 48.67% from key universities) participated. Participants completed self-report questionnaires that evaluated the five key characteristics of personality, psychological capital, and key competencies. Results There were extremely significant university-type differences in key competencies of college students. And the mediating role of psychological capital in the link between Big Five personality traits and key competencies was validated according to PROCESS model 4. Psychological capital serves as a partial mediator in the relationships between neuroticism and critical thinking, openness and creativity, conscientiousness and creativity, openness and communication, conscientiousness and communication, extraversion and collaboration, as well as openness and collaboration. The proportion of mediating effects for the above models was 5.97, 10.89, 11.82, 12.24, 11.98, 12.39, and 22.72%, respectively. Discussion The findings provide a better understanding of the key competencies of college students from the perspectives of the Big Five personality traits and psychological capital and suggest a greater emphasis to focusing on personality and improving psychological capital.
A New Gradient-Wind Nomogram*

A nomographic solution is found for the gradient-wind equation in terms of the curvature of pressure-contour lines and the motion of pressure-contour systems. From the nomogram the gradient wind can be found as a function of the geostrophic wind, and in addition the radius of curvature of the trajectory can be evaluated. Subsidiary aids in determining the quantities involved are discussed, as well as the application of the computing device to routine upper wind forecasting.
A Hybrid Neuro-Fuzzy Approach for Heterogeneous Patch Encoding in ViTs Using Contrastive Embeddings and Deep Knowledge Dispersion

Vision Transformers (ViT) are commonly utilized in image recognition and related applications. It delivers impressive results when it is pre-trained using massive volumes of data and then employed in mid-sized or small-scale image recognition evaluations such as ImageNet and CIFAR-100. Basically, it converts images into patches, and then the patch encoding is used to produce latent embeddings (linear projection and positional embedding). In this work, the patch encoding module is modified to produce heterogeneous embedding by using new types of weighted encoding. A traditional transformer uses two embeddings including linear projection and positional embedding. The proposed model replaces this with weighted combination of linear projection embedding, positional embedding and three additional embeddings called Spatial Gated, Fourier Token Mixing and Multi-layer perceptron Mixture embedding. Secondly, a Divergent Knowledge Dispersion (DKD) mechanism is proposed to propagate the previous latent information far in the transformer network. It ensures the latent knowledge to be used in multi headed attention for efficient patch encoding. Four benchmark datasets (MNIST, Fashion-MNIST, CIFAR-10 and CIFAR-100) are used for comparative performance evaluation. The proposed model is named as SWEKP-based ViT, where the term SWEKP stands for Stochastic Weighted Composition of Contrastive Embeddings & Divergent Knowledge Dispersion (DKD) for Heterogeneous Patch Encoding. The experimental results show that adding extra embeddings in transformer and integrating DKD mechanism increases performance for benchmark datasets. The ViT has been trained separately with combination of these embeddings for encoding. Conclusively, the spatial gated embedding with default embeddings outperforms Fourier Token Mixing and MLP-Mixture embeddings.
Perspectives in nonlinear diffusion : between analysis , physics and geometry

We review some topics in the mathematical theory of nonlinear diffusion. Attention is focused on the porous medium equation and the fast diffusion equation, including logarithmic diffusion. Special features are the existence of free boundaries, the limited regularity of the solutions and the peculiar asymptotic laws for porous medium flows, while for fast diffusions we find the phenomena of finite-time extinction, delayed regularization, nonuniqueness and instantaneous extinction. Logarithmic diffusion with its strong geometrical flavor is also discussed. Connections with functional analysis, semigroup theory, physics of continuous media, probability and differential geometry are underlined. Mathematics Subject Classification (2000). Primary 35K55; Secondary 35K65.
Few-shot Learning with Multilingual Language Models

Large-scale autoregressive language models such as GPT-3 are few-shot learners that can perform a wide range of language tasks without fine-tuning. While these models are known to be able to jointly represent many different languages, their training data is dominated by English, potentially limiting their cross-lingual generalization. In this work, we train multilingual autoregressive language models on a balanced corpus covering a diverse set of languages, and study their few-and zero-shot learning capabilities in a wide range of tasks. Our largest model with 7.5 billion parameters sets new state of the art in few-shot learning in more than 20 representative languages, outperforming GPT-3 of comparable size in multilingual commonsense reasoning (with +7.4% absolute accuracy improvement in 0-shot settings and +9.4% in 4-shot settings) and natural language inference (+5.4% in each of 0-shot and 4-shot settings). On the FLORES-101 machine translation benchmark, our model outperforms GPT-3 on 171 out of 182 translation directions with 32 training examples, while surpassing the official supervised baseline in 45 directions. We present a detailed analysis of where the model suc-ceeds and fails, showing in particular that it enables cross-lingual in-context learning on some tasks, while there is still room for improvement on surface form robustness and adaptation to tasks that do not have a natural cloze form. Finally, we evaluate our models in social value tasks such as hate speech detection in 5 languages and find it has limitations similar to comparably sized GPT-3 models.
Evaluating student pharmacist knowledge, attitudes, and confidence in caring for paediatric patients with HIV

Background: Despite advances in the management of human immunodeficiency virus (HIV), people living with HIV (PLWH) experience stigma that impacts the healthcare they receive. Numerous studies demonstrate that provider education regarding HIV helps alleviate bias. Pharmacy schools significantly vary in their curriculum surrounding HIV education, with a limited focus on HIV in the paediatric population. Being one of the most accessible healthcare providers, improving pharmacist education and attitudes could positively impact treatment outcomes for children living with HIV. Method: An Advanced HIV Elective course that included content in the management of children living with HIV (CLWH) was developed and implemented by faculty at a Doctor of Pharmacy program in the United States. Student pharmacist knowledge, confidence, and perceptions of providing care for this population were assessed before and after the didactic module. Results: The incorporation of a paediatric HIV module increased the knowledge and confidence of student pharmacists in the management of PLWH and CLWH. Areas of improvement include the selection of antiretroviral therapy (ART), ART medication counselling, and paediatric immunisations. However, a significant difference in attitudes and perceptions towards PLWH and CLWH was not observed. Conclusion: Although improvement in student pharmacist knowledge and confidence was seen after the implementation of a paediatric HIV module, innovative ways to address bias, stigma, and misinformation are needed to promote positive health outcomes for marginalised communities, including those living with HIV.
A fast algorithm for the nonparametric maximum likelihood estimate in the cox-gene model

The Cox model with the gene effect for age at onset was introduced and studied by Li, Thompson and Wijsman (1998) and Li and Thompson (1997). This paper concerns the numerical performance of the nonparametric maximum likelihood estimate of the environmental effects and the genetic effect in this model. Based on the self-consistency equations derived from the score functions, we propose a fast iterative algorithm for the computations of the nonparametric maximum likelihood estimate and its asymptotic variance. Simulation studies conducted using these algorithms indicate that the profile likelihood-based normal approximations for the estimates are valid with reasonable sample sizes, and the bootstrap methods work well also for smaller sample sizes, and are computationally feasible.
Inequality and Growth in China

We provide estimates of the effects that income inequality has on economic growth in China. Our empirical analysis is at the county level. Using data provided by the China Health and Nutrition Survey, we construct measures of inequality and the growth rates of household incomes per capita for 72 Chinese counties during the period 1989–2015. System-GMM estimates of panel models show that the within-county effect of inequality on economic growth is significantly decreasing in initial average income. For the relatively low levels of initial average incomes that were prevalent in China during the 1980s and 1990s, our model estimates imply that the increase in inequality that occurred in China during the 1980s and 1990s had a significant positive effect on economic growth. However, for current levels of average income, our panel model predicts that inequality has a negative effect on economic growth: a 1 percentage point increase in the Gini would reduce the per annum growth rate by around 1 percentage point.
Influence of dietary supplementation of vitamin E in ameliorating adverse effects of ochratoxin on biochemical profile and immune response in broiler chickens

In the present study, the effect of supplementation of vitamin E in ochratoxin A (OTA) contaminated diet in ameliorating adverse effects of ochratoxin on biochemical parameters and immune response in broiler chickens was investigated. Day old broiler chicks (240) were divided into 6 treatment groups (T1- control (basal diet), T2 - T1 + 200 ppb OTA, T3 -T1 + 100 mg vit. E, T4 -T1 + 200 mg vit. E, T5 -T2 + 100 mg vit. E and T6 -T2 + 200 mg vit. E). Each diet was fed to 5 replicated groups of 8 birds each from 0 to 42 days of age. The blood samples were collected on 42 days of age of broilers. The total serum protein and haemoglobin (Hb) concentrations in T2 (200 ppb OTA) and T5 (200 ppb OTA + 100 mg vit. E) were lower (P<0.05) than that of control (T1) diet. The serum protein and Hb contents in group T6 was higher (P<0.05) than that of T2 but statistically similar to that of control. The serum uric acid, creatinine, alkaline phosphatase (ALP), serum glutamic oxaloacetic transferase (SGOT) and serum glutamic pyruvic transferase (SGPT) value in T2 was higher (P<0.05) than that of T1. The serum uric acid, creatinine, ALP, SGOT and SGPT value in T6 (200 ppb OTA + 200 mg vit. E) was lower (P<0.05) than that of T2 and statistically similar to that of control (T1). The CMI and HA titre value in T2 was lower (P<0.05) than that of control (T1). The CMI and HA titre value of T3 and T4 was statistically similar to that of control. The CMI value of T5 and T6 was lower (P<0.05) than control, but higher (P<0.05) than T2. The CMI of group T6 was higher (P<0.05) than T5. The HA titre value of group T5 was higher (P<0.05) than T2 and lower than T1. The HA titre value in T6 was statistically similar to that of T1, indicating that inclusion of vit. E (200 mg/kg diet) ameliorated the adverse effect of ochratoxicosis in broiler chickens. Thus, it was concluded that ochratoxin contamination at 200 ppb level in broiler diet had adverse effect on blood biochemical profile and immune response, which were restored through supplementation of vitamin E at 200 mg/kg of feed in ochratoxin contaminated diet in broiler chickens.
Experiential Marketing and E-Wom Create Brand Loyalty Through Brand Trust

This study examines and explains the relationship of variables that become income factors from the application of marketing concepts, namely experiential marketing, E-WOM, Brand Trus, which then form brand loyalty. The object of this research is a hotel in Malang. The data was obtained by distributing online questionnaires to 160 people. Furthermore, the data were analyzed using the Partial Leasr Square (PLS) analysis tool with SmartPLS software. The results of this study indicate that; first, experiential marketing has a significant positive effect on brand trust, the second experiential marketing has a significant positive effect on brand trust, the third experiential marketing has a significant positive effect on brand loyalty, the fourth E-WOM has a significant positive effect on brand loyalty and fifth, brand trust has a significant positive effect on brand loyalty
Corporate Cash Holdings and Share Buyback: Evidence from Emerging Markets

This study evaluates corporate cash holdings (CCHs) as a determinant of share buyback for three emerging economies, India, Malaysia, and South Korea, from 2002 to 2020. We find CCH as a significant determinant of share buyback for our sample nations. Our results suggest that share buyback is a flexible way for firms to distribute excess cash across our sample nations. Our study also documents the impact of different country-level investor protection frameworks on buybacks. A favorable relationship between a strong investor protection environment (good governance) and buyback explains the effective role of buyback in resolving agency conflicts compared to dividends. JEL Codes: C5, F3, G3