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For their pungency and tanginess, ginger rhizomes (Zingiber officinale) are often used in cooking. Ginger has long been used in traditional medicine and home remedies to treat pain and inflammation. This research tests Z. officinale (EOZ) essential oils’ chemical composition, insecticidal, and antioxidant properties in vitro and in silico. EOZ yielded 0.69% of root mass with 23 chemicals. The main chemicals in EOZ were α-zingiberene (23.850%), Geranial (14.160%), and (E,E)-α-farnesene (9.980%). EOZ demonstrated noteworthy antioxidant activity in all tests, with an IC50 of 9.53 ± 0.41 mg/mL in the DPPH test and an EC50 of 87.46 ± 3.19 mg/mL in the FRAP system. The results indicate that EOZ has strong efficacy against C. maculatus, even at low concentrations (1.00 μL/100 g). Note that EOZ killed 20 ± 0% and 13.33 ± 4.44% of adult C. maculatus in inhalation and contact tests, respectively. High concentration (20.00 μL/100 g) resulted in 100% adult mortality in inhalation tests and 96.67 ± 4.44% mortality in contact testing. We then used molecular docking to identify EO major component binding modes by targeting insecticidal and antioxidant protein structures 1R20 and 1R4U. This research helps create insecticides and antioxidants from common ginger essential oil.

Juniperus thurifera was selected for this study due to its crucial ecological role in high mountain ecosystems and the increasing threats it faces, such as habitat degradation and regeneration challenges. The analysis of stand structure by altitude shows that the distribution of individuals and stem count vary with elevation, highlighting the species’ adaptability to mountainous conditions. Altitudinal degradation significantly impacts seed production, with a positive correlation (r = 0.65) between stem and fruit numbers in females. J. thurifera also plays a vital role in soil retention, as indicated by the positive correlation (r = 0.511) between ground projection and soil thickness, emphasizing its importance in slope stabilization and erosion prevention. Sexual dimorphism reveals dendrometric differences between males and females, affecting regeneration and reproduction. Age estimation based on circumference shows the predominance of aging, non-reproductive trees, threatening future regeneration. Principal component analysis (PCA) further refines recommendations by revealing complex relationships between dendrometric characteristics and environmental factors, providing precise guidelines for J. thurifera conservation.

Introduction/purpose: This study establishes sufficient conditions for a sequence to be Cauchy within the framework of controlled revised fuzzy metric spaces. It also generalizes the concept of Banach's contraction principle by introducing several new contraction conditions. The aim is to derive various fixed-point results that enhance the understanding of these mathematical structures. Methods: The researchers employ rigorous mathematical techniques to develop their findings. By defining a set of novel contraction mappings and utilizing properties of controlled revised fuzzy metric spaces, they analyze the implications for sequence convergence. The methodology includes constructing specific examples to illustrate the theoretical results. Results: The study presents several fixed-point theorems derived from the generalized contraction conditions. Additionally, it provides a number of non-trivial examples that substantiate the claims and demonstrate the applicability of the results in practical scenarios. A significant application is explored regarding the conversion of solar energy into electric power, utilizing differential equations to highlight this connection. Conclusion: The findings deepen the understanding of Cauchy sequences in fuzzy metric spaces and offer a broader perspective on the application of the fixed-point theory in real-world scenarios. The results pave the way for further research in both theoretical mathematics and its practical applications, particularly in the field of renewable energy.

The objective of this study is to determine the larvicidal activity of essential oils (EOs) extracted from three plants of the genus Artemisia against the mosquito Culex pipiens (C. pipiens) using in vitro and in silico studies. A total number of 20 third- and fourth-instar larvae were exposed to various concentrations of the three plants. The LC50 and LC90 values of the tested Artemisia EOs were determined using Probit analysis. In addition, the sensitivity of C. pipiens to these EOs was determined and compared against a standard insecticide, temephos, under laboratory conditions. Furthermore, in silico assessments were carried out on the major constituents to help understand and explain the acquired in vivo results. Gas chromatography analysis identified the major compounds as d-limonene and β-pinene for Artemisia flahaultii, camphor and borneol for Artemisia. aragonensis, and artemisia ketone and caryophyllene for Artemisia annua. A. flahaultii oil showed the highest efficacy against C. pipiens larvae, followed by A. annua oil with average larvicidal activity. In contrast, A. aragonensis EO, composed of a high percentage of monoterpenes, was the least active. Docking simulation indicated that several studied ligands had promising binding scores within the receptor’s binding site compared to the reference insecticide temephos. The obtained results allow us to conclude that A. flahaultii, a species endemic to Morocco, is an excellent means of controlling C. pipiens.

Purpose – The purpose of this paper is to investigate the link between Islamic finance for entrepreneurship activities and economic growth in Malaysia within the model of endogenous growth. Design/methodology/approach – This study applied a parametric analysis represented by vector autoregression (VAR) Granger causality and a non-parametric analysis represented in the bootstrapped quantile regression to examine the effect of Islamic finance for entrepreneurship activities on economic growth within the model of endogenous growth. This paper used a sample of all Islamic banks working in Malaysia covering a period from 2014 first quarter until 2019 third quarter (2014Q1–2019Q3). Findings – The findings demonstrated that Islamic finance for entrepreneurship activities are promoting economic growth in Malaysia which indicates that Islamic finance is a vital contributor to economic growth through financing entrepreneurial domains small and medium-sized enterprises. Practical implications – The analysis in this paper would fill the literature gap by investigating the link between Islamic finance for entrepreneurship activities and economic growth within the model of endogenous growth in Malaysia as this study serves as a guide for the researchers and decision-makers to the necessity of merging Islamic finance as a major player in the economy to finance the entrepreneurial domain which contributes to economic growth. Originality/value – This study is the first that investigates the relationship between Islamic finance for entrepreneurship activities and economic growth empirically using the causality and quantile regression within a new theoretical approach over the model of endogenous growth to provide a proven valuable experiment from Malaysia concerning Islamic finance for the entrepreneurial domain which promotes economic growth.

Malware analysis is the process of dissecting malicious software to understand its functionality, behavior, and potential risks. Artificial Intelligence (AI) and deep learning are ushering in a new era of automated, intelligent, and adaptive malware analysis. This convergence of AI and deep learning promises to revolutionize the way cybersecurity professionals detect, analyze and respond to malware threats. This paper proposed a Deep Neural Network (DNN) model built from features selected by ANalysis Of Variance (ANOVA) F-test (DNN-ANOVA) to increase accuracy by identifying informative features. ANOVA is a feature selection method used for numerical input data when the target variable is categorical. The top k most relevant features are those whose score values are greater than a certain threshold equal to the ratio between the sum of all features scores and the total number of features. Experiments are conducted on CIC-MalMem-2022 dataset. Malware Analysis is performed using binary classification to detect the presence or absence of malware and multiclass classification to detect not only the malware but also its type. According to the test results, DNN-ANOVA model achieves best values of 100 %, 99.99 %, 99.99 %, and 99.98 % in terms of precision, accuracy, F1-score and recall respectively for binary classification. In addition, DNN-ANOVA outperforms the current works with an overall accuracy rate of 85.83 %, and 73.98 % for family attacks and individual attacks respectively in the case of multiclass classification.

Cutaneous angiosarcoma is a rare malignant vascular tumor that most often affects the scalp and face of elderly males. It is most frequently associated with lung metastases, with the appearance of thin-walled cyst. We report the case of a 78-year-old male who presented with acute chest pain and dyspnea, subsequently revealing bilateral pneumothorax caused by cystic pulmonary metastases from a neglected facial angiosarcoma. The diagnosis was confirmed through comprehensive radiological evaluations, emphasizing the critical role of CT imaging. This case underscores the critical need to not underestimate pneumothorax complicating cystic lung lesions and to consider angiosarcoma metastases, particularly in elderly men, as a potential diagnosis.

This research aims to examine the physical, structural and chemical properties of Aster Squamatus (AS) fibres, which are commonly found in Algeria, Brazil, France and the West Indies. In this work, we assess their appropriateness as reinforcing fillers to fabricate components for polymer composites principally designed for lightweight applications. To accomplish this objective, an extraction of fibres from plants modification of AS fibres and characterization of both untreated fibres (UASFs) and alkali-treated AS fibres (TASFs) are conducted. We analysed the crystallinity, chemical composition, thermal characteristics, and mechanical properties of AS fibres as per standard methods. It's clear from chemical treatment that amorphous components were successfully eliminated from the AS fibres, including hemicellulose, lignin, and wax. Consequently, the fibres' thermal, physical, and mechanical characteristics including Young's modulus, tensile strength, crystalline index, and surface roughness were substantially enhanced. It was determined that the fibres possessed a thermal stability of around 250 °C, with the maximal degradation temperature rising from 372.50 to 375.35 °C. The maximum stress rose from 183.24 ± 25.27 to 302.00 ± 24.91 MPa, the Young's modulus increased from 11.08 ± 1.1 to 18.53 ± 1.45 GPa, and the crystallinity index increased from 43% to 45%. Two-parameter Weibull statistics showed a strong link between experimental data and mechanical features of the twenty samples. We concluded from this work that AS plant fibres can serve as a robust reinforcing material in polymer composites for various applications.

Lacrimal sac tumors are rare with epithelial tumors being the most common type. Melanoma of the lacrimal sac is an exceptional finding. Few cases have been reported so far in the literature. We report the case of a sixth year old male, with no pathological background, who was referred to the hospital for chronic dacryocystitis resistant to treatment. Computed tomography dacryocystography and magnetic resonance imaging were performed, in favor of a large mass of the lacrimal sac and lacrimal canal suggestive of melanoma. Biopsy confirmed the diagnosis. PET-CT was positive and showed abnormal activity in the lung, liver and bones, in favor of metastasis.