Miracle-dz/UniFAR-FTUs huggingface dataset:
CNN-BiLSTM Based Federated Learning for Field Worker Safety

Since the fourth industrial revolution, industries have become increasingly interested in human-centered technology and management. In particular, worker safety in industrial sites has become an important topic as discussions on ensuring the right to survival and corporate social responsibility have expanded. In this context, this study aims to develop a worker safety management system considering the characteristics of industrial sites. To this end, we propose a federated learning (FL) technique utilizing the convolutional neural networks and bidirectional long short-term memory (CNN-BiLSTM) mechanism, which addresses the heterogeneous resource constraints of edge devices and ensures performance, data confidentiality, and system stability. The proposed technique uses a deep learning algorithm, CNN-BiLSTM, to detect subtle activity anomalies and contribute to predicting potentially dangerous situations. It utilizes wearable sensors to analyze workers’ biometric indicators and serves to increase industrial safety and proactively prevent potential threats. This research is expected to provide a new approach to industrial safety and improve safety management at industrial sites.
AI-Powered Real-Time Speech-to-Speech Translation for Virtual Meetings Using Machine Learning Models

In our interconnected world, language diversity poses communication challenges, particularly in virtual meetings. Our solution, a Real-Time Speech-to-Speech Translation system for Virtual Meetings, bridges these gaps. It captures speech in one language, providing clear and understandable translations in real-time during virtual meetings. By seamlessly integrating Automatic Speech Recognition (ASR), Machine Translation (MT), and Text-to-Speech (TTS) components, this system transcends language barriers, enabling participants to engage effortlessly and effectively in multilingual virtual interactions. It's more than text; it fosters spoken interaction, revolutionizing cross-lingual communication in virtual meetings. Applications abound, from enhancing global business negotiations to aiding virtual travelers and connecting educators to broader international audiences of diverse languages in virtual educational platforms. In an era where virtual communication is paramount, our project empowers meaningful connections, proving technology's remarkable ability to unite people and transcend language barriers in virtual settings worldwide.
Probabilistic Modeling, Statistical Analysis, and Stochastic Optimization for Random Horizontal Ranges of Projectile

In this paper, we propose a simple and novel probabilistic model for random projectile paths with uniformly distributed launch angles. Specifically, we formulate a stochastic range maximization problem and derive a closed-form expression for probability density function (PDF) of the maximum horizontal range random variable. Using its PDF, we derive analytical results for various statistical parameters such as mean, standard deviation, median, and mode. We then present numerical results for those statistical parameters and interpret them qualitatively. Finally, we formulate a novel and insightful stochastic range optimization problem and present its solution. The proposed probabilistic model, its statistical analysis, and range optimization could be useful in modeling and analyzing events that involve motion like a projectile.
Personal privacy vs population privacy: learning to attack anonymization

Over the last decade great strides have been made in developing techniques to compute functions privately. In particular, Differential Privacy gives strong promises about conclusions that can be drawn about an individual. In contrast, various syntactic methods for providing privacy (criteria such as k-anonymity and l-diversity) have been criticized for still allowing private information of an individual to be inferred. In this paper, we consider the ability of an attacker to use data meeting privacy definitions to build an accurate classifier. We demonstrate that even under Differential Privacy, such classifiers can be used to infer "private" attributes accurately in realistic data. We compare this to similar approaches for inference-based attacks on other forms of anonymized data. We show how the efficacy of all these attacks can be measured on the same scale, based on the probability of successfully inferring a private attribute. We observe that the accuracy of inference of private attributes for differentially private data and $l$-diverse data can be quite similar.
Comparison of Vibrio choleraePathogenicity Islands in Sixth and Seventh Pandemic Strains

ABSTRACT Epidemic Vibrio cholerae strains possess a large cluster of essential virulence genes on the chromosome called theVibrio pathogenicity island (VPI). The VPI contains thetcp gene cluster encoding the type IV pilus toxin-coregulated pilus colonization factor which can act as the cholera toxin bacteriophage (CTXΦ) receptor. The VPI also contains genes that regulate virulence factor expression. We have fully sequenced and compared the VPI of the seventh-pandemic (El Tor biotype) strain N16961 and the sixth-pandemic (classical biotype) strain 395 and found that the N16961 VPI is 41,272 bp and encodes 29 predicted proteins, whereas the 395 VPI is 41,290 bp. In addition to various nucleotide and amino acid polymorphisms, there were several proteins whose predicted size differed greatly between the strains as a result of frameshift mutations. We hypothesize that these VPI sequence differences provide preliminary evidence to help explain the differences in virulence factor expression between epidemic strains (i.e., the biotypes) of V. cholerae.
Designing an End-to-End UAV System for Insulator Inspection Under Transmission Tower Environments

This paper proposes an unmanned aerial vehicle (UAV) equipped with a rigid contact module and two supplementary forward-direction motors, designed for the contact-based inspection of porcelain insulators. During the free-flight, this aerial robot is controlled by a geometric tracking controller. When approaching and contacting the insulators, the impedance controller generates enough force to sustain contact by using two forward-direction motors, while the geometric tracking controller maintains its orientation. This platform is validated through simulations, demonstrating its effectiveness in performing contact-based inspection tasks.
A Novel Biomarker Panel Examining Response to Gemcitabine with or without Erlotinib for Pancreatic Cancer Therapy in NCIC Clinical Trials Group PA.3

Purpose NCIC Clinical Trials Group PA.3 was a randomized control trial that demonstrated improved overall survival (OS) in patients receiving erlotinib in addition to gemcitabine for locally advanced or metastatic pancreatic cancer. Prior to therapy, patients had plasma samples drawn for future study. We sought to identify biomarkers within these samples. Experimental Design Using the proximity ligation assay (PLA), a probe panel was built from commercially available antibodies for 35 key proteins selected from a global genetic analysis of pancreatic cancers, and used to quantify protein levels in 20 uL of patient plasma. To determine if any of these proteins levels independently associated with OS, univariate and mulitbaraible Cox models were used. In addition, we examined the associations between biomarker expression and disease stage at diagnosis using Fisher's exact test. The correlation between Erlotinib sensitivity and each biomarkers was assessed using a test of interaction between treatment and biomarker. Results and Conclusion Of the 569 eligible patients, 480 had samples available for study. Samples were randomly allocated into training (251) and validation sets (229). Among all patients, elevated levels of interleukin-8 (IL-8), carcinoembryonic antigen (CEA), hypoxia-inducible factor 1-alpha (HIF-1 alpha), and interleukin-6 were independently associated with lower OS, while IL-8, CEA, platelet-derived growth factor receptor alpha and mucin-1 were associated with metastatic disease. Patients with elevated levels of receptor tyrosine-protein kinase erbB-2 (HER2) expression had improved OS when treated with erlotinib compared to placebo. In conclusion, PLA is a powerful tool for identifying biomarkers from archived, small volume serum samples. These data may be useful to stratify patient outcomes regardless of therapeutic intervention. Trial Registration ClinicalTrials.gov NCT00040183
Tetrahedral-mesh-based computational human phantom for fast Monte Carlo dose calculations

Although polygonal-surface computational human phantoms can address several critical limitations of conventional voxel phantoms, their Monte Carlo simulation speeds are much slower than those of voxel phantoms. In this study, we sought to overcome this problem by developing a new type of computational human phantom, a tetrahedral mesh phantom, by converting a polygonal surface phantom to a tetrahedral mesh geometry. The constructed phantom was implemented in the Geant4 Monte Carlo code to calculate organ doses as well as to measure computation speed, the values were then compared with those for the original polygonal surface phantom. It was found that using the tetrahedral mesh phantom significantly improved the computation speed by factors of between 150 and 832 considering all of the particles and simulated energies other than the low-energy neutrons (0.01 and 1 MeV), for which the improvement was less significant (17.2 and 8.8 times, respectively).
Influence of mutation of the HFE gene on the progression of chronic viral hepatitis B and C in Moroccan patients

The implication of hemochromatosis (HFE) gene mutations in chronic viral hepatitis remains controversial. The aim of the present study was to measure the frequencies of the common HFE gene mutations in Moroccan subjects with chronic viral hepatitis B and C and to assess their influence on the progression of liver disease. H63D and C282Y mutations were screened by the polymerase chain reaction followed by restriction fragment length polymorphism analysis in 170 chronic hepatitis B patients, 168 chronic hepatitis C patients, and 200 healthy controls. A very small proportion of patients infected with hepatitis B virus (HBV) or hepatitis C virus (HCV; 1.8% and none, respectively) were heterozygous for the C282Y mutation, that is, rates not statistically different from those observed in healthy control (2%, P > 0.05). Similarly, the frequency of the H63D allele was not significantly different between HBV (13.8%) or HCV (14.3%) patients and controls (13.5%, P > 0.05). Multivariate analysis showed that carriers of the H63D mutation infected with HBV are at higher risk to progress towards an advanced liver disease when compared with patients infected with HBV with wild‐type (OR = 2.45, 95% CI = 1.07–5.58). In contrast, no association between HFE mutated HCV‐infected patients and an increased risk of disease progression was found (OR = 1.24, 95% CI = 0.61–2.50, P = 0.547). In conclusion, in Morocco the frequency of the HFE C282Y allele is very low and H63D mutation carriage occurs in almost 14% of the patients, a rate similar in chronic hepatitis patients and healthy controls. In the case of chronic hepatitis B, the carriage of the H63D variant represents a risk factor of evolution towards a more active disease. J. Med. Virol. 83:2096–2102, 2011. © 2011 Wiley Periodicals, Inc.
Functional anatomy of the second visual area (V2) in the macaque

To study the functional organization of secondary visual cortex (V2) in the primate, 14C-2-deoxy-d-glucose (DG) was injected while macaque monkeys were shown specific visual stimuli. Wherever possible, patterns of DG uptake were compared with the position of dark and light cytochrome oxidase (cytox) stripes (Tootell et al., 1983). Often, the DG effects of 2 different stimuli were compared in the same hemisphere to eliminate ambiguities inherent in between-animal comparisons. Data were obtained from a large number of animals in conjunction with related DG studies in area V1 (primary visual or striate cortex). The following conclusions were reached: (1) in some macaque monkeys, dark cytox stripes were faint or absent. Although this could conceivably be due to poor staining technique, some evidence suggests that the lack of enzyme stripe pattern is real. In all animals, including those that showed poor or no cytox staining evidence for stripes, the functional architecture revealed by the DG was consistently present and robust. (2) Uniform gray stimuli produce a relatively uniform pattern and minimal stimulus-related DG uptake. (3) Eye movements per se produce some uptake in the V2 stripes. (4) Very generalized visual stimulation conditions (e.g., binocular stimulation with a grating of varied orientation and varied spatial frequency) produced a pattern of uptake that is greatest in both sets of dark cytox stripes and lighter in the light cytochrome stripes. (5) In both the DG and cytox results, the V2 “stripes” are more accurately described as stripe-shaped collections of patches. (6) In almost all cases, DG patterns were columnar in shape, extending from white matter to cortical surface. The boundaries of the columns were most sharply defined, and the contrast was highest, in layers 3B/4, becoming slightly more blurry and lower in contrast in other layers. Laminar differences between DG patterns in V2 were almost negligible, compared with the profound laminar differences in macaque V1. (7) There is no DG evidence for, and much against, the possibility of an ocular dominance architecture in V2. (8) There are orientation columns in macaque V2. DG-labeled orientation columns are spaced further apart than those in V1, by a factor of about 1.6, but the columns are not correspondingly wider. (9) Spatially diffuse variations in color produce high uptake confined, at least largely, to the thin cytox stripes. (10) There is evidence for spatially antagonistic color surrounds in color cells in the thin stripes. (ABSTRACT TRUNCATED AT 400 WORDS)
The Effects of Childhood Family Stress on Women's Depressive Symptoms

This study uses a life course approach to observe the interaction between stressful childhood events and recent undesirable events to predict depressive symptoms in women. Data are from a community sample (N = 205) of adult daughters from the Cornell Women's Roles Project, aged 26-58 years. Results indicate that women who experienced mild stressors during childhood are less likely to have depressive responses to undesirable events than are those who did not have stressful family backgrounds. This buffering influence appears to be partially mediated through a woman's belief in her control over external events. In the absence of childhood strains, a close father—daughter relationship during childhood may also teach women protective mastery skills. Overall, findings suggest that women's differing depressive responses to undesirable events follow a developmental pathway beginning with early childhood experiences. We suggest that the milder childhood stressors measured in this study stimulated an adaptive family environment from which these women were able to garner life course coping strategies.
Deep Learning based Abnormal Event Detection in Pedestrian Pathways

A video surveillance system is capable of detecting any kind of motions that are unusual and hence proves to be a major contributor of the surveillance sector. The unusual or strange movements that has been recorded by the surveillance cameras have been used and their patterns have been studied. The pattern that do not match with the patterns of normal behavior are then used captured. In video sequences they can be seen in numerous ways which includes bikers, skaters, small carts in pedestrian pathways, etc. The main aim of the study is to develop a efficiently working Video Anomaly Detection(VAD) system that is capable of identifying and analyzing strange movements in videos using the techniques of deep learning and image processing.
The Dictyostelium Kinome—Analysis of the Protein Kinases from a Simple Model Organism

Dictyostelium discoideum is a widely studied model organism with both unicellular and multicellular forms in its developmental cycle. The Dictyostelium genome encodes 285 predicted protein kinases, similar to the count of the much more advanced Drosophila. It contains members of most kinase classes shared by fungi and metazoans, as well as many previously thought to be metazoan specific, indicating that they have been secondarily lost from the fungal lineage. This includes the entire tyrosine kinase–like (TKL) group, which is expanded in Dictyostelium and includes several novel receptor kinases. Dictyostelium lacks tyrosine kinase group kinases, and most tyrosine phosphorylation appears to be mediated by TKL kinases. About half of Dictyostelium kinases occur in subfamilies not present in yeast or metazoa, suggesting that protein kinases have played key roles in the adaptation of Dictyostelium to its habitat. This study offers insights into kinase evolution and provides a focus for signaling analysis in this system.
An Intelligent System for Case Review and Risk Assessment in Social Services

This article reports on the development and implementation of DISXPERT, an intelligent rule-based system tool for referral of social security disability recipients to vocational rehabilitation services. The growing use of paraprofessionals as caseworkers responsible for assessment in the social services area provides fertile domain areas for new and innovative application of intelligent system technology. The main function of DISXPERT is to provide support to paraprofessional caseworkers in reaching unbiased and consistent assessment decisions regarding referral of clients to vocational rehabilitation services. The results after four years of use demonstrate that paraprofessionals using DISXPERT can make assessments in less time and with a level of accuracy superior to the vocational rehabilitation domain professionals using manual methods. This article discusses the problem domain, the design and development of the system, uses of AI technology, payoffs, and deployment and maintenance of the system.
Ontologies as Background Knowledge to Explore Document Collections

This paper introduces a new approach to provide users with solutions to explore a domain via an information space. A key point in our approach is that information searching and exploring takes place in a domain-dependent semantic context. A given context is described through its vocabulary organised along hierarchies that structure the information space. These hierarchies are simplified views on a more complex domain specific ontology, that form a shared and coherent background knowledge representation. So the system benefits from the combination of two innovations that make the exploration of the document space more effective. First, hierarchies (extracted from the ontology) provide with a language and synthetic representation to be explored by the users to express their information need. Additionally, a visual interface presents answers to their queries using multi-dimensional analysis and a global visualisation of document collections. At both stages, ontology is the key structure that guides a meaningful browsing for query formulation and for the document set exploration.
Subjective stress and serious illness of a spouse: wives of heart patients.

This paper examines stability and change in reported subjective stress during one year among 263 wives whose husbands suffered a first myocardial infarction. Patterns of subjective stress scores remained relatively stable over the study year. Level of severity of illness in the husband had some relationship to stress score at particular points in time, although clear-cut findings did not emerge. Some variations in subjective stress levels were also found between women of different educational and ethnic backgrounds. Reported subjective stress is reviewed as part of a more general stress experience, reflected in emotional volatility and marital unhappiness, rather than as a correlate of such variables as illness burdens in the household, employment of wife, age, and socioeconomic status.
A New Asymptotic Preserving Scheme Based on Micro-Macro Formulation for Linear Kinetic Equations in the Diffusion Limit

We propose a new numerical scheme for linear transport equations. It is based on a decomposition of the distribution function into equilibrium and nonequilibrium parts. We also use a projection technique that allows us to reformulate the kinetic equation into a coupled system of an evolution equation for the macroscopic density and a kinetic equation for the nonequilibrium part. By using a suitable time semi-implicit discretization, our scheme is able to accurately approximate the solution in both kinetic and diffusion regimes. It is asymptotic preserving in the following sense: when the mean free path of the particles is small, our scheme is asymptotically equivalent to a standard numerical scheme for the limit diffusion model. A uniform stability property is proved for the simple telegraph model. Various boundary conditions are studied. Our method is validated in one-dimensional cases by several numerical tests and comparisons with previous asymptotic preserving schemes.
Spectral zero-crossings: Localization properties and application to epoch extraction in speech signals

We analyze the spectral zero-crossing rate (SZCR) properties of transient signals and show that SZCR contains accurate localization information about the transient. For a train of pulses containing transient events, the SZCR computed on a sliding window basis is useful in locating the impulse locations accurately. We present the properties of SZCR on standard stylized signal models and then show how it may be used to estimate the epochs in speech signals. We also present comparisons with some state-of-the-art techniques that are based on the group-delay function. Experiments on real speech show that the proposed SZCR technique is better than other group-delay-based epoch detectors. In the presence of noise, a comparison with the zero-frequency filtering technique (ZFF) and Dynamic programming projected Phase-Slope Algorithm (DYPSA) showed that performance of the SZCR technique is better than DYPSA and inferior to that of ZFF. For highpass-filtered speech, where ZFF performance suffers drastically, the identification rates of SZCR are better than those of DYPSA.
Altered Methylation of IGF2 Locus 20 Years after Preterm Birth at Very Low Birth Weight

Introduction People born preterm at very low birth weight (VLBW, ≤1500g) have higher rates of risk factors for adult-onset diseases, including cardiovascular diseases and type 2 diabetes. These risks may be mediated through epigenetic modification of genes that are critical to normal growth and development. Methods We measured the methylation level of an imprinted insulin-like-growth-factor 2 (IGF2) locus (IGF2/H19) in young adults born preterm at VLBW and in their peers born at term. We studied 158 VLBW and 161 control subjects aged 18 to 27 years from the Helsinki Study of Very Low Birth Weight Adults. Methylation fraction at two IGF2 differentially methylated regions (DMRs) – IGF2 antisense transcript (IGF2AS, also known as IGF2 DMR0) and last exon of IGF2 (IGF2_05, also known as IGF2 DMR2) – were measured with Sequenom Epityper. We used linear regression and adjustment for covariates to compare methylation fractions at these DMRs between VLBW and control subjects. Results At one IGF2AS CpG site, methylation was significantly lower in VLBW than in control subjects, mean difference −0.017 (95% CI; −0.028, −0.005), P = 0.004. Methylation at IGF2_05 was not different between the groups. Conclusions Methylation of IGF2AS is altered 20 years after preterm birth at VLBW. Altered methylation may be a mechanism of later increased disease risk but more data are needed to indicate causality.