Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Deep Belief Network Enabled Malware Detection and Classification Model

Cybercrime has increased considerably in recent times by creating new methods of stealing, changing, and destroying data in daily lives. Portable Document Format (PDF) has been traditionally utilized as a popular way of spreading malware. The recent advances of machine learning (ML) and deep learning (DL) models are utilized to detect and classify malware. With this motivation, this study focuses on the design of mayfly optimization with a deep belief network for PDF malware detection and classification (MFODBN-MDC) technique. The major intention of the MFODBN-MDC technique is for identifying and classifying the presence of malware exist in the PDFs. The proposed MFODBN-MDC method derives a new MFO algorithm for the optimal selection of feature subsets. In addition, Adamax optimizer with the DBN model is used for PDF malware detection and classification. The design of the MFO algorithm to select features and Adamax based hyperparameter tuning for PDF malware detection and classification demonstrates the novelty of the work. For demonstrating the improved outcomes of the MFODBN-MDC model, a wide range of simulations are executed, and the results are assessed in various aspects. The comparison study highlighted the enhanced outcomes of the MFODBN-MDC model over the existing techniques with maximum precision, recall, and F1 score of 97.42%, 97.33%, and 97.33%, respectively.
The use of FTIR spectroscopy combined with pattern recognition and
multivariate calibration for rapid authentication of Etawa goat milk from
soymilk

Etawa goat milk (EGM) is valuable milk with a higher price compared to other kinds of milk. It is susceptible to being adulterated with low-priced milk for economical reasons. Therefore, the development of an analytical method for rapid authentication of EGM from soymilk (SM) is highly required. Fourier transform infrared (FTIR) spectroscopy combined with chemometrics was evaluated for rapid qualitative and quantitative analysis of SM in raw fresh EGM samples. Samples were prepared by mixing goat milk with soymilk in several concentration levels ranging from 0-100% (v/v). FTIR spectra revealed the differences between authentic and adulterated EGM samples in certain wavenumber regions. Linear discriminant analysis (LDA) at wavenumbers of 3000-750 cm-1 was successfully used for discrimination between authentic and adulterated EGM samples. The Cooman plot showed a clear classification between pure and adulterated goat milk samples. Partial least square (PLS) using wavenumber combination of 3000-2800 cm-1 and 1800-650 cm-1 as well as principal component regression (PCR) using wavenumber of 3000-750 cm-1 has been successfully used for quantification of SM in EGM. However, PLS offered a better model for quantification with higher values of R2 calibration (0.9997) and validation (0.9992) and lower values of RMSEC (0.848) and RMSEP (1.19). It can be concluded that this method is promising for the rapid authentication of goat milk s
Cosmology from very high energy $\gamma$-rays

In this work we study how the cosmological parameter, the Hubble constant $H_0$, can be constrained by observation of very high energy (VHE) $\gamma$-rays at the TeV scale. The VHE $\gamma$-rays experience attenuation by background radiation field through $e^+e^-$ pair production during the propagation in the intergalactic space. This effect is proportional to the distance that the VHE $\gamma$-rays go through. Therefore the absorption of TeV $\gamma$-rays can be taken as cosmological distance indicator to constrain the cosmological parameters. Two blazars Mrk 501 and 1ES 1101-232, which have relatively good spectra measurements by the atmospheric Cerenkov telescope, are studied to constrain $H_0$. The mechanism constraining the Hubble constant adopted here is very different from the previous methods such as the observations of type Ia supernovae and the cosmic microwave background. However, at $2\sigma$ level, our result is consistent with other methods.
Detailed estimation of battery life in a WSN deployment in the field

— This document presents a detailed analytical and practical method for the estimation of battery life expectancy of a multi-hop mesh network. This network is composed by a set of MicaZ nodes using the XMesh routing protocol. The energy drawn for each of the tasks performed by the nodes is measured, and network topology and radio propagation are characterized in order to obtain accurate predictions of the lower bound for the battery duration of the nodes. This estimation is of paramount importance for field deployments, where energy is a scarce resource and replacing node batteries is a slow and costly process that can disable the network for relatively long periods of time.
Automated Computer-Assisted Image Analysis for the Fast Quantification of Kidney Fibrosis

Simple Summary Chronic kidney disease is a health problem in which the kidneys cannot function normally. Thus, they cannot filter blood effectively and cause waste accumulation in the organism, leading to serious health problems. Researchers use animals as models to replicate the human body’s behavior to understand this disease. In these studies, it is essential to evaluate the percentage of fibrosis (growth of fibrotic tissue similar to a scar in response to damage) to know the degree of kidney damage. Some researchers use programs to make the evaluation of fibrosis easier. However, this analysis is time-consuming because it needs to be made one image at a time and there are hundreds of samples in an animal model study. Here, we explain a method to conduct the same analysis but in a faster automated way with the assistance of a computer and a software package called CellProfiler™. The percentage of fibrosis using CellProfiler™ is similar to that obtained with the most widely used software for this kind of analysis called ImageJ. With the help of this approach, researchers can make more studies faster and easier and find new antifibrogenic therapies to address the common and worldwide health problem caused by chronic kidney disease. Abstract Chronic kidney disease (CKD) is a common and worldwide health problem and one of the most important causes of morbidity and mortality. Most primary research on this disease requires evaluating the fibrosis index in animal model kidneys, specifically using Masson’s trichrome stain. Different programs are used to calculate the percentage of fibrosis; however, the analysis is time-consuming since one image must be performed at a time. CellProfiler™ is a program designed to analyze data obtained from biological samples and can process multiple images through pipelines, and the results can be exported to databases. This article explains how CellProfiler™ can be used to automatically analyze kidney histology photomicrographs from samples stained with Masson’s trichrome stain to assess the percentage of fibrosis in an experimental animal model of CKD. A pipeline was created to analyze Masson’s trichrome-stained slides in a model of CDK induced by adenine at doses of 50 mg/kg and 100 mg/kg, in addition to samples with the vehicle (75% glycerin). The results were compared with those obtained by ImageJ, and no significant differences were found between both programs. The CellProfiler™ pipeline made here is a reliable, fast, and easy alternative for kidney fibrosis analysis and quantification in experimental animal models.
The Evolution of Financial Risk Management

Purpose: This paper aims to track the history of financial risk management and how this progress affected the evolution of financial risk management. In the first part of this paper, we will look at how risk is defined, the concept of risk management, and the transaction from risk philosophy to the risk culture. The second part examines the evolution of risk management and different models used in financial risk measurements, such as variance, covariance, standard deviation, and value at risk models. In the third part, the Bretton Woods system, its effects on the global financial system, and after the Bretton Woods system is studied. In the final cut, we conclude and present our recommendations for future studies.Methodology: This theoretical research will focus on the historical evolution of financial risk management and the financial tools used while measuring risk. The finance field has evolved with crises, technological developments, and globalization. While the finance field has been growing, how financial risks are defined, managed, and measured has also changed. In addition to these changes, the finance field was introduced with a new area called “blockchain” and new investment instruments called cryptocurrencies.Practical Implications: This theoretical research investigates the evolution of financial risk management from a historical perspective and argues that the current financial risk management tools are insufficient to project today’s risks fully.
The Effect of Binaural Beat Audio on Operative Pain and Anxiety in Cataract Surgery under Topical Anaesthesia: A Randomized Controlled Trial

Background: The aim of this paper was to examine the analgesic and anxiolytic effects of binaural beat audio in patients undergoing cataract surgery under topical anaesthesia. Methods: This was a prospective, randomized controlled trial of 61 patients undergoing cataract surgery under topical anaesthesia. They were divided into two research conditions; the binaural beat audio group, and a sham-control group (ear phones with no music). Patients completed the State-Trait Anxiety Inventory questionnaire (STAI), and their blood pressure (BP) and heart rate (HR) were measured pre- and post-intervention. Intraoperative pain levels were ascertained using a visual analog scale (VAS) completed immediately after the surgery. Results: The binaural beat group had significantly lower pain scores (p < 0.001), HR (p < 0.001), diastolic BP (p = 0.003), mean arterial pressure (p = 0.007) and anxiety (p = 0.009) than the control group. Within the binaural beat group, subjects experienced a statistically significant reduction in HR (p = 0.004) and anxiety (p < 0.001) levels compared to baseline values, while all parameters, except anxiety, increased significantly in the control group. Conclusions: Binaural beat audio decreases operative pain and anxiety in cataract surgery under topical anaesthesia. It may have additional benefits in modulating the tachycardic response to stress.
Unveiling the Galaxy Population at 1.3 < z < 4: the HUDF05 NICMOS Parallel Fields

Using the Hubble Ultra Deep Field Near Infrared Camera and Multi-Object Spectrometer (HUDF-NICMOS) UDF05 parallel fields, we cross-matched 301 out of 630 galaxies with the ACS filters V606 and z850, NICMOS filters J110 and H160, and Spitzer IRAC filters at 3.6, 4.5, 5.8 , and 8.0 (mu)m. We modeled the spectral energy distributions (SEDs) to estimate: photometric redshifts, dust extinction, stellar mass, bolometric luminosity, starburst age and metallicity. To validate the photometric redshifts, comparisons with 16 spectroscopic redshifts give 75% within Delta or approx. 1.3. Based on the robustness of the photometric redshifts, we analyze a subsample of the 301 galaxies at 1.3 < or = z < or = 2 (35 objects) and 3 < or = z < or = 4 (31 objects) and determine that L(BoI) and the star formation rate increase significantly from z approx. 1.5 to 4. The Balmer decrement is indicative of more evolved galaxies, and at high redshifts, they serve as records of some of the first galaxies. Therefore, the galaxies in this sample are great candidates for future surveys with the James Webb Space Telescope and Atacama Large Millimeter Array.
Comparison of PHP Programming Language with Codeigniter Framework in Project CRUD

Programming Language is a certain code that is designed to create an application program design. The number of programming languages currently circulating, it is necessary to test the level of reliability of a programming language. The purpose of this research is to compare the programming language PHP and Codeigniter Framework, both of these programming languages are back end languages so that they have close specifications in processing data from the database. Implementation developed with CRUD-based Codelgniter Framework. CodeIgniter is an open source web application network that is used to build dynamic PHP applications on the Project CRUD (Create Read Update Delete) model. In general, the two programming languages aim to manage the database so that it can be displayed and managed by the application. The research method used is literature study and practicum in lectures with students. The basic difference in this study is that the PHP language does not require special Driver Connection Tools so that in connecting the database to the application, it is enough to create a connection script, while the Codeigniter Framework is required to use Driver Connections when connecting to the database. The final result of this research is based on System Testing at PHP Performance Level 85% and Framework 75%, PHP Information 73% and Framework 85%, PHP Control 74% and Framework 87%, PHP 75% Efficiency Framework 82%, Service on PHP 73 % and Framework 82%.
Determination of Sudan III in Food by Supramolecular Microextraction and Spectrophotometry

Abstract A novel, accurate, and rapid procedure is reported using supramolecular liquid-phase microextraction of Sudan III combined with spectrophotometric detection at 510 nm. Analytical conditions such as the pH, supramolecular solvent volume, tetrahydrofuran (THF) volume, ultrasonication and centrifugation duration, initial and final sample volumes, and matrix effects were optimized. The quantitative recovery of Sudan III was obtained at pH 4.0. The relative standard deviation was less than 5%. The preconcentration factor was 33. The limits of detection and quantification were 0.79 μg L−1 and 2.6 μg L−1, respectively. The presented microextraction procedure was applied to determination of Sudan III in fortified spices including sumac, pepper flakes, soy sauce, and chili powder.
Raccourcissement de courbes et décomposition de surfaces

Théorème barycentrique de Tutte appliqué aux isotopies avec Michel Pocchiola et Gert Vegter. Théorème barycentrique de Tutte appliqué aux isotopies avec Michel Pocchiola et Gert Vegter. Théorème barycentrique de Tutte appliqué aux isotopies avec Michel Pocchiola et Gert Vegter.
THE ROLE OF ARTIFICIAL INTELLIGENCE IN IMPROVING SERVICE AND STRENGTHENING TOURIST EXPERIENCE IN EGYPT

Artificial intelligence is the most recent trend in technology and has received considerable attention, especially in the tourism and hospitality industry. AI enhances tourism services and acts as an effective complementary dimension to the future of tourism. The emergence of artificial intelligence makes travel arrangements easier than before, as helps tourists to make a series of decisions about their future trips, for example, choosing a destination, transport, accommodation, and other activities. These decisions will have a significant impact on the tourist experience. Moreover, AI allows travelers to learn about their behaviors, interests to inclinations. Gone are the days to consult a travel agent, meet him physically, and indulge in an endless chain of troubling phone calls to inquire about travel arrangements. Hence, Artificial intelligence is a major complement to a travel agent and not a hindrance. Artificial intelligence also plays an increasingly important role in the hospitality industry because of its ability to carry out traditionally human functions very precisely at any time of the day, which leads to saving significant money, saving time, eliminating human error, and delivering superior service. Accordingly, this study depends on the quantitative approach through distributing questionnaires to obtain rich and detailed information about the respondents' perceptions and attitudes toward Artificial intelligence, as well as identifying the role of artificial intelligence in
PRODUCTION OF SALT-TOLERANT SOUR ORANGE PLANTS (Citrus aurantium L.) USING TISSUE CULTURE TECHNIQUE: II- IN VITRO EVALUATION AND SELECTION OF SALT TOLERANT CALLUS

This study was conducted through 1996-1999 years in the Department of Alexandria University. The work involved the evaluation and selection of salt tolerant callus of sour orange under in vitro conditions. The main results can be summarized in the following points: 1-Concerning the effect of exposure to different concentrations of NaCl salt in culture medium on callus survival percentage, the results indicated that the 10gl -1 NaCl concentration was lethal for most callus with only 20.00% surviving. 2- Regarding the effect of exposure to different concentrations of NaCl salt in culture medium on ion content percentage (on dry weight basis) of salt-sensitive and salt-tolerant calluses of sour orange, the results revealed that at 5gl -1 NaCl concentration, the NaCl –tolerant callus had higher K + content, as compared with the NaCl-sensitive callus. On the contrary, the NaCl-tolerant callus had lower Cl - , Ca 2+ and Mg 2+ contents, as compared with NaCl-sensitive callus, at the same external NaCl concentration (5gl -1 NaCl). 3-The obtained results also revealed that proline content increased in salt-tolerant callus as compared to salt-sensitive callus (control). Accumulation of proline in the salt-tolerant callus has been shown to be an adaptive mechanism for resistance to salt stress.
Multi-Sector Assessment and Client-Perception of Social Need at Long-Term Follow-Up of a Group-Randomized Trial of Community-Engaged Collaborative Care for Adults with Depression

Understanding client perceptions of need for underlying social determinant support may improve services for depression care. This secondary analysis examines perceptions of “social needs” related to housing and employment, financial, and legal (EFL) concerns among individuals with depression. Data were analyzed from Community Partners in Care, a randomized comparative effectiveness trial of multi-sector collaborative care for depression among a sample of people who were predominantly racial/ethnic minorities and low-income. Adults with depression (n = 980) in both interventions were surveyed at 36-month follow-up for (1) being asked about and (2) having social needs for housing or EFL concerns. In multivariate models, life difficulty and mental health visits in non-healthcare sectors predicted being asked about housing and EFL. Lower social determinants of health-related life satisfaction increased the odds of having unmet housing and EFL needs. These findings underscore the role of non-healthcare organizations as community resources for depression care and in screening and addressing social needs.
A new concept of modular magnetic levitation train for urban transport

Aim: The aim of our project is to solve all technological and functional problems related to the development of the suspended urban Maglev, while maintaining the requirement of simplicity and low cost of construction, operation and maintenance. Both the infrastructure and the vehicle are designed to be industrially produced and assembled on site. Methods of the studies: Our study is based on the theoretical and experimental results obtained during a project of the Italian National Research Council, concerning the performances of opposing permanent magnets, the design of the linear synchronous motor and the possible solutions for realizing the guidance system. On the basis of these results the study of the suspended system was carried out. Results: The paper describes the suspended urban Maglev with PM/PM primary suspension (with opposing permanent magnets) and proposes a mechanical guidance system that uses for stabilization the same repulsive forces between permanent magnets. We also propose a new configuration with HTS/PM primary suspension (with high temperature superconductors opposed to permanent magnets), evaluating pros and cons of this solution. Finally we provide design data on the linear synchronous motor suitable for our system. Conclusion: This paper describes our proposal for a suspended urban Maglev using permanent magnets; our interest focuses on the need to further develop industrially feasible solutions, easy to build and manage, in order to propose a system that is also commercially viable and competitive. The identified advantages justify further studies.
H2O2 and Ca2+ Signaling Crosstalk Counteracts ABA to Induce Seed Germination

Seed germination is a critical stage and the first step in the plant’s life cycle. H2O2 and Ca2+ act as important signal molecules in regulating plant growth and development and in providing defense against numerous stresses; however, their crosstalk in modulating seed germination remains largely unaddressed. In the current study, we report that H2O2 and Ca2+ counteracted abscisic acid (ABA) to induce seed germination in melon and Arabidopsis by modulating ABA and gibberellic acid (GA3) balance. H2O2 treatment induced a Ca2+ influx in melon seeds accompanied by the upregulation of cyclic nucleotide-gated ion channel (CNGC) 20, which encodes a plasma membrane Ca2+-permeable channel. However, the inhibition of cytoplasmic free Ca2+ elevation in the melon seeds and Arabidopsis mutant atcngc20 compromised H2O2-induced germination under ABA stress. CaCl2 induced H2O2 accumulation accompanied by the upregulation of respiratory burst oxidase homologue (RBOH) D and RBOHF in melon seeds with ABA pretreatment. However, inhibition of H2O2 accumulation in the melon seeds and Arabidopsis mutant atrbohd and atrbohf abolished CaCl2-induced germination under ABA stress. The current study reveals a novel mechanism in which H2O2 and Ca2+ signaling crosstalk offsets ABA to induce seed germination. H2O2 induces Ca2+ influx, which in turn increases H2O2 accumulation, thus forming a reciprocal positive-regulatory loop to maintain a balance between ABA and GA3 and promote seed germination under ABA stress.
Alternative multivariate multimodal crash frequency models

Abstract The central issue for successful implementation of a multimodal approach is the development of appropriate crash frequency models that can jointly estimate the crash risk of different mode users. This study proposed two multivariate spatial-temporal models to analyze 6 years of modal crash data from counties in California: one with fixed time trend applied to all modes, the other with mode-varying time trend coefficients. These models were compared with three other multivariate models from past studies. The major objective was to examine the benefits of the newly proposed models that have substantially increased computational cost, because both dimensions of time and space, and their interaction, are considered. The model fitness results from penalized criterion revealed that the proposed models significantly improved the model fitting by pooling strength from neighboring sites, consideration of time trend, as well as their interactions. The model with mode-varying time coefficients was observed to be superior in terms of prediction accuracy. The posterior deviance was observed to be the governing factor for overall fit and consistently showed a strong positive correlation between model fit and prediction accuracy. Overall, the study is anticipated to enhance the understanding of safety impacts from the interaction of various modes.