Miracle-dz/UniFAR-FTUs huggingface dataset:
Phishing URL Detection: A novel hybrid Approach using Long Short-Term Memory and Gated Recurrent Units

Phishing is one of the oldest types of cyber-attack, which mostly comes in the form of camouflaged URLs to delude the users to disclose their personal information for malevolent purposes of the attacker. It is one of the easiest ways of inducing people into revealing their personal credentials including credit card details. Usually, most phishing attacks come up as fake websites pretending to mimic a trustworthy website, and the attackers use these malicious website URLs for successful data breaches. Therefore, it is a necessity to filter up which URLs are benign, and which are malicious. This study proposes three non-hybrid deep learning models, namely CNN (1D), LSTM, GRU, and four hybrid deep learning models, namely GRU-LSTM, LSTM-LSTM, BI (GRU)-LSTM, and BI (LSTM)-LSTM. Based on the results obtained, it was found that BI (GRU)-LSTM model was the best performing model with an accuracy of 93.91%, precision of 93.94 %, recall of 93.38 %, and F1-Score of 93.66 %. Thus, the primary objective of this paper is to provide an insight into the hybrid deep learning approaches in phishing URL detection by evaluating their accuracy, precision, recall, and f1 score.
Food consumption and factors related to weight variation in patients with Non-Alcoholic Fatty Liver Disease during the COVID-19 pandemic

This study longitudinal investigated food consumption and factors related to weight variation in 81 adult patients with Non-Alcoholic Fatty Liver Disease (NAFLD) during the COVID-19 pandemic. Sociodemographic, anthropometric, physical activity and food intake data were collected during two periods: before and during the pandemic. For analysis, variations in weight were divided into two categories: weight gain less than or equal to two kilos and weight gain greater than two kilos. Mann Whitey test was used to verify the difference between the medians, while Spearman's correlation coefficient to calculate correlations, Fisher's exact test to assess associations. The significance level adopted in the decision of the tests was 5%. Results showed increases in the consumption of processed and ultra-processed foods among NAFLD patients alongside a reduction in the consumption of natural or minimally processed foods. Both findings were more frequent among patients demonstrating weight gain greater than two kilograms. However, analysis of the nutritional composition of patients’ diets revealed increases in carbohydrate consumption to be the only factor significantly correlated with weight gain. There was a high percentage of individuals who did not practice physical exercise before the pandemic, and this number was exacerbated during home isolation. Thus, it is observed that NAFLD patients have difficulty maintaining a healthy lifestyle and these difficulties have worsened during the pandemic, as reflected by weight gain. Therefore, it is suggested that specialized nutritional assistance be aimed at NAFLD patients seeing as they are at an increased risk for progression to more severe forms of COVID-19.
Manual on application of molecular tools in aquaculture and inland fisheries management. Part 2. Laboratory protocols and data analysis

The aim of this manual is to provide a comprehensive practical tool for the generation and analysis of genetic data for subsequent application in aquatic resources management in relation to genetic stock identification in inland fisheries and aquaculture. The material only covers general background on genetics in relation to aquaculture and fisheries resource management, the techniques and relevant methods of data analysis that are commonly used to address questions relating to genetic resource characterisation and population genetic analyses. No attempt is made to include applications of genetic improvement techniques e.g. selective breeding or producing genetically modified organisms (GMOs). The manual includes two ‘stand-alone’ parts, of which this is the second volume: Part 1 – Conceptual basis of population genetic approaches: will provide a basic foundation on genetics in general, and concepts of population genetics. Issues on the choices of molecular markers and project design are also discussed. Part 2 – Laboratory protocols, data management and analysis: will provide step-by-step protocols of the most commonly used molecular genetic techniques utilised in population genetics and systematic studies. In addition, a brief discussion and explanation of how these data are managed and analysed is also included. This manual is expected to enable NACA member country personnel to be trained to undertake molecular genetic studies in their own institutions, and as such is aimed at middle and higher level technical grades. The manual can also provide useful teaching material for specialised advanced level university courses in the region and postgraduate students. The manual has gone through two development/improvement stages. The initial material was tested at a regional workshop and at the second stage feedback from participants was used to improve the contents.
Investigating the Relationship between Supervisory Change and Community Bank Failure in a Competing Risk Framework

Bank failures began to rise in 2007 and more than 350 were closed by the end of 2011. A number of observers have asserted that the ability of banks to switch among competing supervisors was an important contributing factor, but the issue has not been carefully investigated in empirical work. This study explores this issue using a sample of almost 6500 community banks that existed at the end of 2007. A competing risk hazard model developed by Fine and Gray (1999) is employed to estimate the effect of supervisory changes during the 2004-2007 period on bank failure over the 2008-2011 time period. The model explicitly recognizes that merger as well as subsequent supervisory change represent possibly important competing risks. The evidence indicates that community banks that changed their primary federal supervisor during the four year period ending on 12/31/2007 were more likely to fail over the following 4 year interval than those that did not make such a switch. This effect is evident for banks that switched to all three primary federal supervisors. Another interesting finding is that state banks that changed only their primary federal supervisor and not their charter were also more likely to fail all else equal. No significant differences in failure likelihoods are apparent when the banks continuously supervised by each primary federal supervisor are compared to one another. These results are evident in both simple comparisons of failure rates, and in the estimated multivariate competing risk failure models. These findings taken together suggest that differences in agency funding sources or organizational responsibilities are not the primary cause of the higher failure rates of the switching banks.
Organizing the Exploitation of Vulnerable People: A Qualitative Assessment of Human Trafficking

Focusing on the organizing practices by which vulnerable individuals are exploited for their labor, we build a model that depicts how human traffickers systematically target impoverished girls and women and transform their autonomous objection into unquestioned compliance. Drawing from qualitative interviews with women forced into labor in the sex industry, human traffickers, brothel managers, and other sources (e.g., doctors, nongovernment organizations, and police officers fighting human trafficking), we inductively theorize that organizing of vulnerable individuals for human exploitation involves four interrelated practices—(1) deceptive recruiting of the vulnerable, (2) entrapping through isolation, (3) extinguishing alternatives by building barriers, and (4) converting the exploited into exploiters—that together erode and eventually eliminate workers’ autonomy. We conclude by discussing implications of our research for theory—specifically, the literature on human exploitation and loss of worker agency.
Nonwoven Textiles from Hyaluronan for Wound Healing Applications

Nonwoven textiles are used extensively in the field of medicine, including wound healing, but these textiles are mostly from conventional nondegradable materials, e.g., cotton or synthetic polymers such as polypropylene. Therefore, we aimed to develop nonwoven textiles from hyaluronan (HA), a biocompatible, biodegradable and nontoxic polysaccharide naturally present in the human body. For this purpose, we used a process based on wet spinning HA into a nonstationary coagulation bath combined with the wet-laid textile technology. The obtained HA nonwoven textiles are soft, flexible and paper like. Their mechanical properties, handling and hydration depend on the microscale fibre structure, which is tuneable by selected process parameters. Cell viability testing on two relevant cell lines (3T3, HaCaT) demonstrated that the textiles are not cytotoxic, while the monocyte activation test ruled out pyrogenicity. Biocompatibility, biodegradability and their high capacity for moisture absorption make HA nonwoven textiles a promising material for applications in the field of wound healing, both for topical and internal use. The beneficial effect of HA in the process of wound healing is well known and the form of a nonwoven textile should enable convenient handling and application to various types of wounds.
The Stability Analysis of Slope of Shegang Protecting Dyke

Appraisal of dam slope safety is essential for security and stability of the dyke that has been constructed for many years. According to the requirements of the appraisal of dam safety, the stability analysis of slope of Shegang dyke has been carried out by using Sweden circular-arc method, Bishop method, Engineer Corps method and Lowe method four methods under many kinds of working conditions and some conditions when the saturation line raising. Combined with the design code form embankment dam, the calculation results can be analyzed. The analysis can show that the security indexes of anti-slide under four kinds of working conditions and some conditions when the saturation line raising meet the requirements of the design code. This can provide basis for the reinforcement design of the dam, which also has a certain directive significance for the safe operation and observation of the dam in the future.
An Efficient Deep Learning Framework for Distracted Driver Detection

The number of road accidents has constantly been increasing recently around the world. As per the national highway traffic safety administration’s investigation, 45% of vehicle crashes are done by a distracted driver right around each. We endeavor to build a precise and robust framework for distinguishing diverted drivers. The existing work of distracted driver detection is concerned with a limited set of distractions (mainly cell phone usage). This paper uses the first publicly accessible dataset that is the state farm distracted driver detection dataset, which contains eight classes: calling, texting, everyday driving, operating on radio, inactiveness, talking to a passenger, looking behind, and drinking performed by 26 subjects to prepare our proposed model. The transfer values of the pertained model EfficientNet are used, as it is the backbone of EfficientDet. In contrast, the EfficientDet model detects the objects involved in these distracting activities and the region of interest of the body parts from the images to make predictions strong and accomplish state-of-art results. Also, in the Efficientdet model, we implement five variants: Efficientdet (D0-D4) for detection purposes and compared the best Efficientdet version with Faster R-CNN and Yolo-V3. Experimental results show that our approach outperforms earlier methods in the literature and conclude that EfficientDet-D3 is the best model for detecting distracted drivers as it achieves Mean Average Precision (MAP) of 99.16% along with learning rate (le-3), epoch 50, batch size 4, and step size 250, demonstrating that it can potentially help drivers maintain safe driving habits.
Ultrasound Imaging for the Diagnosis and Evaluation of Sarcopenia: An Umbrella Review

There is an increasing number of reviews investigating the value of ultrasound (US) in the assessment of aging-related muscle loss. The present umbrella review aimed to systematically investigate the evidence of US imaging in the diagnosis and evaluation of sarcopenia. PubMed, Medline, Embase and Web of Science were searched from their inceptions to 31 October 2021. Systematic reviews and reviews using a systematic strategy for literature search were enrolled. The extracted data were narrated at the level of systematic reviews and meta-analyses. This umbrella review included four articles pertaining to 125 original studies and yielded several important findings. First, US is a reliable and valid imaging tool for the assessment of skeletal muscle mass. Second, among all the US parameters in B-mode, muscle thickness is the most commonly used one, which has good correlation with other standard measurements. Third, although sonoelastography and contrast-enhanced US are promising imaging modalities, their clinical utility is still limited at the current stage. Finally, a future systematic review is warranted to analyze how different ultrasonographic diagnostic criteria influence the prevalence of sarcopenia as well as its adverse health outcomes.
Robust Automotive Positioning: Integration of GPS and Relative Motion Sensors

Automotive positioning systems relying exclusively on the input from a GPS receiver, which is a line of sight sensor, tend to be sensitive to situations with limited sky visibility. Such situations include: urban environments with tall buildings; inside parking structures; underneath trees; in tunnels and under bridges. In these situations, the system has to rely on integration of relative motion sensors to estimate vehicle position. However, these sensor measurements are generally affected by errors such as offsets and scale factors, that will cause the resulting position accuracy to deteriorate rapidly once GPS input is lost. The approach in this thesis is to use a GPS receiver in combination with low cost sensor equipment to produce a robust positioning module. The module should be capable of handling situations where GPS input is corrupted or unavailable. The working principle is to calibrate the relative motion sensors when GPS is available to improve the accuracy during GPS intermission. To fuse the GPS information with the sensor outputs, different models have been proposed and evaluated on real data sets. These models tend to be nonlinear, and have therefore been processed in an Extended Kalman Filter structure. Experiments show that the proposed solutions can compensate for most of the errors associated with the relative motion sensors, and that the resulting positioning accuracy is improved accordingly.
User-friendly analysis of droplet array images

Water-in-oil droplets allow researchers to perform massive experimental parallelization and high-throughput studies, such as single-cell experiments. However, the analysis of such vast arrays of droplets usually requires advanced expertise and sophisticated workflow tools, which limits the accessibility for wider user base in chemistry and biology. Thus, there is a need for more user-friendly tools for droplet analysis. In this article, we deliver a set of analytical pipelines for user-friendly analysis of typical scenarios in droplet-based experiments. We build the pipelines combining different open-source image-analysis software with the custom-developed data visualization tool “EasyFlow”. Our pipelines are designed to be applicable for the typical experimental scenarios users encounter with droplets: i) mono- and polydisperse droplets, ii) brightfield and fluorescent images, iii) droplet and object detection, iv) signal profile of droplets and objects (e.g., fluorescence).
Calmodulin and Its Interactive Proteins Participate in Regulating the Explosive Growth of Alexandrium pacificum (Dinoflagellate)

Alexandrium pacificum is a typical dinoflagellate that can cause harmful algal blooms, resulting in negative impacts on ecology and human health. The calcium (Ca2+) signal transduction pathway plays an important role in cell proliferation. Calmodulin (CaM) and CaM-related proteins are the main cellular Ca2+ sensors, and can act as an intermediate in the Ca2+ signal transduction pathway. In this study, the proteins that interacted with CaM of A. pacificum were screened by two-dimensional electrophoresis analysis and far western blots under different growth conditions including lag phase and high phosphorus and manganese induced log phase (HPM). The interactive proteins were then identified using matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Four proteins were identified, including Ca2+/CaM-dependent protein kinase, serine/threonine kinase, annexin, and inositol-3-phosphate synthase, which all showed high expression levels under HPM. The gene expression levels encoding these four proteins were also up-regulated under HPM, as revealed by quantitative polymerase chain reaction, suggesting that the identified proteins participate in the Ca2+ transport channel and cell cycle regulation to promote cell division. A network of proteins interacting with CaM and their target proteins involved in the regulation of cell proliferation was raised, which provided new insights into the mechanisms behind the explosive growth of A. pacificum.
Studies on the Reduction of Coefficient of Variation: A Case Study

In a spinning mill, yarn is the final product. Linear density expressed in terms of count is one of the important characteristics of yarn. Because variability of textile strands increases as the linear density increases, the variability in the count is often measured in terms of coefficient of variation (CV)%. The yarn with a high CV% of count leads to a higher end breakage rate during the spinning and subsequent weaving/knitting operations, and consequently, results in lesser productivity and poorer appearance quality of the woven/knitted fabric. When this woven/knitted fabric is dyed, uneven shades are generated. Because the production of yarn involves processing of raw cotton in multimachines at multistages, possible sources that lead to a high CV% of count are many. Enrick's (1960) analysis procedure, which is based on the modification of the range method for analysis of variance, is used conventionally for detecting the stages where excessive “between-machine” differences are present. When the CV% of count is inflated due to the generation of systematic variation in any machine or introduction of high variability by any machine, this inflation remains undetected when using Enrick's procedure. The case study presented here demonstrates that a step-by-step analysis of linear densities of different stage-outputs starting from yarn to card sliver, using appropriate nested design models along with Duncan's multiple range test, is very useful in detecting all possible sources of a high CV% of count of yarn.
Spectral and near-field characteristics of induced microseismicity

Summary Microseismic methods have emerged as an important tool for monitoring fluid processes at the reservoir scale, especially for hyrofrac treatment of tight gas reservoirs. The signals produced by microseismic events carry significant information about the characteristics of the source, as well as the effects of wavefield propagation between the source and receiver. If propagation effects can be estimated and removed, inferences can be made about the source such as the style and dimensions of rupture, or stress drop. Moreover, if the path length is less than a few seismic wavelengths (10’s m), the recorded wavefield is expected to include exotic near-field terms with atypical pulse characteristics that might inhibit conventional analysis. Such near-field terms could be important if geophones are deployed within the treatment well, rather than in a separate observation well. This theoretical study considers the potential to extract additional information from microseismic observations, in both near- and far-field recording environments. Source spectrum and stress drop A simple model for shear displacement due to slip on a circular crack is given by
Body Satisfaction as Antecedent to Virtual Product Experience in an Online Apparel Shopping Context

Body satisfaction, largely ignored in studies of online shopping for body-involved products, was examined as an antecedent variable to the virtual product experience. The purpose of this study was to investigate how body satisfaction relates to the virtual product experience and attitudinal and behavioral intentions in the body-absent, online apparel shopping environment. Data were collected through a Web-based survey, and 403 female students from a Midwestern university in the U.S. responded. Findings from structural equation modeling showed that participants with higher body satisfaction tended to perceive more enjoyment of the virtual product experience in online apparel shopping, which helped them to facilitate more positive attitude toward products and increase online purchase intention. Results indicate that body satisfaction shapes enjoyment of the virtual product experience and leads to individual differences in online apparel shopping. Managerial implications to improve virtual product experience-related strategies in online apparel shopping are proposed.
Natural Variation in the Control of Flowering and Shoot Architecture in Diploid Fragaria Species

In perennial fruit and berry crops of the Rosaceae family, flower initiation occurs in late summer or autumn after downregulation of a strong repressor TERMINAL FLOWER1 (TFL1) and flowering and fruiting takes place the following growing season. Rosaceous fruit trees typically form two types of axillary shoots, short flower-bearing shoots called spurs and long shoots that are respectively analogous to branch crowns and stolons in strawberry. However, regulation of flowering and shoot architecture differs between species and environmental and endogenous controlling mechanisms have just started to emerge. In woodland strawberry (Fragaria vesca L.), long days maintain vegetative meristems and promote stolon formation by activating TFL1 and GIBBERELLIN 20-OXIDASE4 (GA20ox4), respectively, while silencing of these factors by short days and cool temperatures induces flowering and branch crown formation. We characterized flowering responses of 14 accessions of seven diploid Fragaria species native to diverse habitats in the northern hemisphere, and selected two species with contrasting environmental responses, F. bucharica Losinsk. and F. nilgerrensis Schlecht. ex J. Gay for detailed studies together with F. vesca. Similar to F. vesca, F. bucharica was induced to flower in short days at 18°C and regardless of photoperiod at 11°C after silencing of TFL1. F. nilgerrensis maintained higher TFL1 expression level and likely required cooler temperatures or longer exposure to inductive treatments to flower. We also found that high expression of GA20ox4 was associated with stolon formation in all three species, and its downregulation by short days and cool temperature caused branch crown formation in F. vesca and F. nilgerrensis, although the latter did not flower. F. bucharica, in contrast, rarely formed branch crowns, regardless of flowering or GA20ox4 expression level. Our findings highlighted diploid Fragaria species as a rich source of genetic variation controlling flowering and plant architecture, with potential applications in breeding of Rosaceous crops.