TMS: Ensemble Deep Learning Model for Accurate Classification of Monkeypox Lesions Based on Transformer Models with SVM.

Background/objectives: The emergence of monkeypox outside its endemic region in Africa has raised significant concerns within the public health community due to its rapid global dissemination. Early clinical differentiation of monkeypox from similar diseases, such as chickenpox and measles, presents a challenge. The Monkeypox Skin Lesion Dataset (MSLD) used in this study comprises monkeypox skin lesions, which were collected primarily from publicly accessible sources.

Towards efficient IoT communication for smart agriculture: A deep learning framework.

The integration of IoT (Internet of Things) devices has emerged as a technical cornerstone in the landscape of modern agriculture, revolutionising the way farming practises are viewed and managed. Smart farming, enabled by interconnected sensors and technologies, has surpassed traditional methods, giving farmers real-time, granular information into their farms. These Internet of Things devices are responsible for collecting and sending greenhouse data (temperature, humidity, and soil moisture) for the required destination, to provide a comprehensive awareness of environmental factors critical to crop growth.

Phycoremediation of 1,4 dioxane-laden wastewater: A Techno-economic and sustainable development approach.

Microalgal tolerance to emerging contaminants (ECs) such as 1,4 dioxane (DXN) and its impact on phycoremediation performance, algal growth, biomolecules generated, and recycling the produced biomass for biochar production has been rarely reported. Hence, Chlorella vulgaris was cultivated in DXN-free wastewater (WW1) and 100 mg L DXN-laden wastewater (WW2) in 1-liter photobioreactors with an operating volume of 800 ml under controlled conditions: temperature (25 ± 1 °C), light intensity (351 μmol ms), and photoperiod (12 h light:12 h dark). Interestingly, this microalgal-based system achieved up to 32.

Toxicity of bisphenol A and -nitrophenol on tomato plants: Morpho-physiological, ionomic profile, and antioxidants/defense-related gene expression studies.

Bisphenol A (BPA) and -nitrophenol (PNP) are emerging contaminants of soils due to their wide presence in agricultural and industrial products. Thus, the present study aimed to integrate morpho-physiological, ionic homeostasis, and defense- and antioxidant-related genes in the response of tomato plants to BPA or PNP stress, an area of research that has been scarcely studied. In this work, increasing the levels of BPA and PNP in the soil intensified their drastic effects on the biomass and photosynthetic pigments of tomato plants.

Revealing the diversity of Jojoba-associated fungi using amplicon metagenome approach and assessing the in vitro biocontrol activity of its cultivable community.

Jojoba shrubs are wild plants cultivated in arid and semiarid lands and characterized by tolerance to drought, salinity, and high temperatures. Fungi associated with such plants may be attributed to the tolerance of host plants against biotic stress in addition to the promotion of plant growth. Previous studies showed the importance of jojoba as jojoba oil in the agricultural field; however, no prior study discussed the role of jojoba-associated fungi (JAF) in reflecting plant health and the possibility of using JAF in biocontrol.

Biodegradation of polystyrene nanoplastics by Achromobacter xylosoxidans M9 offers a mealworm gut-derived solution for plastic pollution.

Nanoplastics pose significant environmental problems due to their high mobility and increased toxicity. These particles can cause infertility and inflammation in aquatic organisms, disrupt microbial signaling and act as pollutants carrier. Despite extensive studies on their harmful impact on living organisms, the microbial degradation of nanoplastics is still under research.

Theoretical estimation of the thermal damages of living tissues caused by laser irradiation in tumor thermal therapy.

This article aims to provide theoretical predictions for the thermal reactions of human tissues during tumor thermotherapy when exposed to laser irradiation and an external heat source. For the construction of a theoretical study of bioheat transfer, the selection of a suitable thermal model capable of accurately predicting the required thermal responses is essential. The effect of heat production by heat treatment on a spherical multilayer tumor tissue is evaluated using this approach.

Generalized thermomechanical interaction in two-dimensional skin tissue using eigenvalues approach.

The aim of this work is to analytically study the thermo-mechanical response of two-dimensional skin tissues when subjected to instantaneous heating. A complete understanding of the heat transfer process and the associated thermal and mechanical effects on the patient's skin tissues is critical to ensuring the effective applications of thermal therapy techniques and procedures. The surface boundary of the half-space undergoes a heat flux characterized by an exponentially decaying pulse, while maintaining a condition of zero traction.

A novel proposed class of estimators under ranked set sampling: Simulation and diverse applications.

This study presents a novel enhanced exponential class of estimators for population mean under RSS by employing data on an auxiliary variable. The suggested estimators' mean square error (MSE) is calculated approximately at order one. The efficiency conditions that make the suggested enhanced exponential class of estimators superior to the traditional estimators are found.

Dual phytoremediation and biochar production by in hydroponic system receiving different 1,4-dioxane dosages.

This study focuses on applying phytoremediation as a low-effective and simple process to treat wastewater laden with 1,4 dioxane (DIOX). A floating macrophyte () was cultivated under hydroponic conditions (relative humidity 50-67%, photoperiod cycle 18:6 h light/dark, and 28-33 °C) and subjected to different DIOX loads between 0.0 (control) and 11.

Novel hydrazone-isatin derivatives as potential EGFR inhibitors: Synthesis and in vitro pharmacological profiling.

Merging isatin and arylhydrazone moieties constitutes an efficient strategy to access new potential anticancer derivatives. Consequently, 14 hydrazone-isatin derivatives were synthesized and evaluated for their antiproliferative activity against the NCI-60 cancer cell line panel. A kinase assay demonstrated that compound VIIIb inhibited the epidermal growth factor receptor (EGFR), which was confirmed by docking studies, molecular dynamics, and binding free energy calculations.

Influence of COVID-19 vaccination on the dynamics of new infected cases in the world.

The initial COVID-19 vaccinations were created and distributed to the general population in 2020 thanks to emergency authorization and conditional approval. Consequently, numerous countries followed the process that is currently a global campaign. Taking into account the fact that people are being vaccinated, there are concerns about the effectiveness of that medical solution.

Prevalence and determinants of wasting among under-5 Egyptian children: Application of quantile regression.

Wasting is one of the symptoms of malnutrition that has been connected to the deaths of malnourished children. This study was intended to explain the effect of socio-demographic and economic factors on under-5 wasting by evaluating their conditional effect across the distribution of weight-for-height Z (WHZ) scores using the quantile regression (QR) model. The weighted sample which included 13,680 children under 5 years was taken from the countrywide Egyptian DHS 2014 survey.

General two-parameter distribution: Statistical properties, estimation, and application on COVID-19.

In this paper, we introduced a novel general two-parameter statistical distribution which can be presented as a mix of both exponential and gamma distributions. Some statistical properties of the general model were derived mathematically. Many estimation methods studied the estimation of the proposed model parameters.

3-Substituted-2,3-Dihydrothiazole as a promising scaffold to design EGFR inhibitors.

The overexpression of EGFR has been recognized as the driver mechanism in the development of several human malignancies and the clinical use of EGFR inhibitors currently constitutes the standard of care for a wide range of malignancies, including colorectal cancer. However, the clinical efficacy of EGFR targeted inhibitors is limited by the development of intrinsic or acquired resistance, requiring the discovery of new compounds with different structural characteristics from those already developed. In this context, we explored the replacement of the aminoquinazoline pharmacophore of several FDA-approved EGFR inhibitors by its bioisosteric hydrazinothiazole moiety.

Statistical modelling for a new family of generalized distributions with real data applications.

The modern trend in distribution theory is to propose hybrid generators and generalized families using existing algebraic generators along with some trigonometric functions to offer unique, more flexible, more efficient, and highly productive G-distributions to deal with new data sets emerging in different fields of applied research. This article aims to originate an odd sine generator of distributions and construct a new G-family called "The Odd Lomax Trigonometric Generalized Family of Distributions". The new densities, useful functions, and significant characteristics are thoroughly determined.

The antibacterial effect of silver, zinc-oxide and combination of silver/ zinc oxide nanoparticles coating of orthodontic brackets (an in vitro study).

Background: Preventive measures are essential during the length of orthodontic treatment to reduce the risk of decalcification and white spot lesions formation. With the evolution of procedures that enable coating of the orthodontic brackets using nanoparticles known for their good antibacterial activity, coating the brackets with nanoparticles of silver, zinc oxide and combination of silver and zinc oxide to evaluate their antibacterial effect in comparison to a control group without coating was carried out in this study.

Methods: Four groups of 12 brackets each were included in the study.

Fe Nanoparticle Size Control of the Fe-MOF-Derived Catalyst Using a Solvothermal Method: Effect on FTS Activity and Olefin Production.

The design of a highly active Fe-supported catalyst with the optimum particle and pore size, dispersion, loading, and stability is essential for obtaining the desired product selectivity. This study employed a solvothermal method to prepare two Fe-MIL-88B metal-organic framework (MOF)-derived catalysts using triethylamine (TEA) or NaOH as deprotonation catalysts. The catalysts were analyzed using X-ray diffraction, N-physisorption, Fourier transform infrared spectroscopy, scanning electron microscopy, transmission electron microscopy, H temperature-programed reduction, and thermogravimetric analysis and were evaluated for the Fischer-Tropsch synthesis performance.

A new versatile modification of the Rayleigh distribution for modeling COVID-19 mortality rates.

The aim of this paper is to specify a new flexible statistical model to analyze COVID-19 mortality rates in Italy and Canada. A new versatile lifetime distribution with four parameters is proposed by using the exponentiated generalized class of distributions and the gull alpha power Rayleigh distribution to form the exponentiated generalized gull alpha power Rayleigh (EGGAPR) distribution. This new distribution is characterized by a tractable cumulative distribution function.

Some new findings on the survival Rényi entropy and application of COVID-19 data.

Motivated by the connotation of survival Rényi entropy and its related dynamic version, we introduce them in terms of their lower bounds and mean residual life function. Moreover, we illustrate the relation between survival Rényi entropy and some of measures of information. Furthermore, the hazard rate order implies ordering of dynamic survival Rényi entropy.

Stress-Strength Parameter Estimation under Small Sample Size: A Testing Hypothesis Approach.

In this paper, uniformly most powerful unbiased test for testing the stress-strength model has been presented for the first time. The end of the paper is recommending a method which is appropriate for no large data where a normal asymptotic distribution is not applicable. The previous methods for inference on stress-strength models use almost all the asymptotic properties of maximum likelihood estimators.

Quercetin stimulates the non-amyloidogenic pathway via activation of ADAM10 and ADAM17 gene expression in aluminum chloride-induced Alzheimer's disease rat model.

Aims: Alzheimer's disease (AD) is the most common progressive neurodegenerative disorder characterized by declined cognitive functions in the elderly. Quercetin (Q) is a potent flavonol that has neuroprotective effects on AD derangements. The present study aimed to evaluate the α-secretase stimulatory function of Q through activation of ADAM10 and ADAM17 gene expression in the aluminum chloride (AlCl3)-induced AD rat model.

Classical and Bayesian Inference of Conditional Stress-Strength Model under Kumaraswamy Distribution.

Stress-strength models have been frequently studied in recent years. An applicable extension of these models is conditional stress-strength models. The maximum likelihood estimator of conditional stress-strength models, asymptotic distribution of this estimator, and its confidence intervals are obtained for Kumaraswamy distribution.

Decision-Making for the Lifetime Performance Index.

The purpose of this research is to develop a maximum likelihood estimator (MLE) for lifetime performance index for the parameter of mixture Rayleigh-Half Normal distribution (RHN) under progressively type-II right-censored samples under the constraint of knowing the lower specification limit (). Additionally, we suggest an asymptotic normal distribution for the MLE for in order to construct a mechanism for evaluating products' lifespan efficiency. We have specified all the steps to carry out the test.

Estimate Stress-Strength Reliability Model Using Rayleigh and Half-Normal Distribution.

In the field of life testing, it is very important to study the reliability of any component under testing. One of the most important subjects is the "stress-strength reliability" term which always refers to the quantity  ( > ) in any statistical literature. It resamples a system with random strength () that is subjected to a random strength () such that a system fails in case the stress exceeds the strength.