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Naturally occurring food-derived active ingredients have received huge attention for their chemopreventive and chemotherapy capabilities in several diseases. Rosmarinic acid (RA) is a caffeic acid ester and a naturally-occurring phenolic compound in a number of plants belonging to the Lamiaceae family, such as Rosmarinus officinalis (rosemary) from which it was formerly isolated. RA intervenes in carcinogenesis through different ways, including in tumor cell proliferation, apoptosis, metastasis, and inflammation. On the other hand, it also exerts powerful antimicrobial, anti-inflammatory, antioxidant and even antidepressant, anti-aging effects. The present review aims to provide an overview on anticancer activities of RA and to deliberate its therapeutic potential against a wide variety of diseases. Given the current evidence, RA may be considered as part of the daily diet in the treatment of several diseases, with pre-determined doses avoiding cytotoxicity.

The European Union, producing over 2.5 billion tons of waste annually, has prompted the European Parliament to implement legal measures and encourage the shift towards a circular economy. Millions of tons of biowaste from olive plant leaves are generated annually, resulting in environmental and economic challenges. To address this, the biowaste of olive leaves was valorized, resulting in the extraction of valuable components, triterpenes and polyphenols, which hold potential pharmaceutical, food, or cosmetic applications. Our research involved the formulation of a triterpene extract (TTP70, 70% triterpenes) as a solid dispersion using Poloxamer-188 (P188) and Poloxamer-407 (P407). The solid dispersions were prepared using a kneading method and various extract-to-polymer weight ratios, including 1:1, 1:2, and 1:5. The influence of hydrophilic carriers on the solubility, dissolution profile, and in vitro passive permeability of TTP70 was evaluated. Both carriers and all considered weight ratios significantly improved the solubility of hydrophobic extract and the dissolution of triterpenes. PAMPA experiments demonstrated the efficacy of the formulation in improving the passive permeation of triterpenes. Subsequently, the solid dispersions were physically mixed with a polyphenol-enriched extract (OPA40, 49% of polyphenols) also obtained from olive leaves, and they were used to fill hard gelatin capsules and produce an oral dosage form. The composite formulations improved the dissolution of both classes of constituents.

The growing interest in oleanolic acid (OA) as a triterpenoid with remarkable health benefits prompts an emphasis on its efficient use in pharmaceutical research. OA exhibits a range of pharmacological effects, including antidiabetic, anti-inflammatory, immune-enhancing, gastroprotective, hepatoprotective, antitumor, and antiviral properties. While OA demonstrates diverse pharmacological effects, optimizing its therapeutic potential requires overcoming significant challenges. In the field of pharmaceutical research, the exploration of efficient drug delivery systems is essential to maximizing the therapeutic potential of bioactive compounds. Efficiently delivering OA faces challenges, such as poor aqueous solubility and restricted bioavailability, and to unlock its full therapeutic efficacy, novel formulation strategies are imperative. This discussion thoroughly investigates different approaches and advancements in OA drug delivery systems with the aim of enhancing the biopharmaceutical features and overall efficacy in diverse therapeutic contexts.

Raster-stereography and Moiré Fringe Topography are widely recognized as effective techniques for surface screening. Traditionally, these methods have been applied in various medical and clinical contexts, such as assessing human body symmetry, analyzing spinal deformities, evaluating scapular positioning, and predicting trunk-related abnormalities. Both techniques have proven to be reliable tools for examining the human body surface and identifying health-related issues. However, in these techniques, line grids projected onto non-uniform surfaces often break or distort, complicating curvature detection. Capturing and digitizing these distortions through photographymeans further reducing accuracy due to low contrast between background and projected lines. In this paper, we present a modified, i.e., dotted-based, approach to Moiré Fringe Topography construction, offering a simpler, more accurate, and efficient method for recording human body surface curvatures. The proposed technique significantly reduces the complexity of the data acquisition process while maintaining precision in surface analysis. A Single-Photon Avalanche Diode (SPAD) image sensor was used to capture the Moiré patterns.

Herein, the review aims to compile some reportable work of researchers carried concerning the use of nanomaterials in the polymeric composites for significant improvements in the properties and to report the application areas of such nanocomposites. Carbon nanotubes, cellulose nanoparticles, titanium dioxide, and other nanoparticles are used in the polymeric composites to enhance their mechanical, electrical, inter-laminar, optical, chemical, electrochemical, electromagnetic shielding, and ballistic properties. Such nanocomposites have a wide range of applications in structural, biomedical, electronics, automobiles, aircraft, oil pipelines, gas pipeline construction, electromagnetic shielding, and protected areas. According to the reported results of researchers, the incorporation of nanomaterials into polymers significantly enhance their properties, which make them able to widen their application areas.

Based on sociocultural theory and pragmatism philosophical underpinnings, this study explores the classroom assessment practices of tertiary EFL practitioners, focusing on their alignment with contemporary constructivist assessment trends, methods, and approaches, rather than psychometrical assessments. The study extends knowledge on language teachers’ preparedness for implementing classroom assessment literacy. Participants were tertiary EFL instructors from four higher educational institutions in Saudi Arabia. Adopting an explanatory sequential mixed-methods research design, data were collected through self-reported questionnaires, classroom observations, and a review of assessment documents and artifacts. Descriptive statistics were used to analyze quantitative data and thematic analysis qualitative data. The dominance of traditional over alternative assessment methods was demonstrated, indicating gaps in teachers’ classroom assessment literacy. The findings highlight the contradiction, discrepancy, and complexity of the relationship between teachers’ articulated and exercised assessment practices. They provide baseline data for L2 classroom assessment policy, a classroom-based assessment framework, and a guide for teachers’ professional development in language assessment literacy.

The textile industry of Pakistan plays a vital role in the national economy; however, it faces increasing pressure to adopt sustainable and circular practices. The circular economy (CE) approach minimizes waste and enhances resource efficiency. However, prior studies have focused on technical and legislative elements of CE adoption, while eco-capability remains understudied in developing economies. This study investigates the role of green skills development (GSD), employee training on CE (ETCE), and employee proactive behavior (EPB) in enhancing circular economy performance (CEP) in Pakistan’s textile sector, supported by the Resource-Based View theory. Using a quantitative, cross-sectional survey design, primary data were collected from 215 middle-to-top-level employees working in textile manufacturing organizations across Pakistan through a structured five-point Likert scale questionnaire. Measurement and structural models were examined using PLS-SEM to assess reliability, and validity, and model relationships. Results indicate that GSD (β = 0.431, t = 5.846) and ETCE (β = 0.357, t = 4.728) significantly enhance CEP, emphasizing the importance of technical skills and structural training. EPB, however, showed no significant effect (β = −0.008, t = 0.080), indicating that individual initiative alone is insufficient. The finding suggested that formal skill development and systemic CE training are critical for improving sustainable performance and advancing UN SDGs 8 and 12 in Pakistan’s textile industry.

The Internet has been vulnerable to several attacks as it has expanded, including spoofing, viruses, malicious code attacks, and Distributed Denial of Service (DDoS). The three main types of attacks most frequently reported in the current period are viruses, DoS attacks, and DDoS attacks. Advanced DDoS and DoS attacks are too complex for traditional security solutions, such as intrusion detection systems and firewalls, to detect. The combination of machine learning methods with AI-based machine learning has led to the introduction of several novel attack detection systems. Due to their remarkable performance, machine learning models, in particular, have been essential in identifying DDoS attacks. However, there is a considerable gap in the work on real-time detection of such attacks. This study uses Mininet with the POX Controller to simulate an environment to detect DDoS attacks in real-time settings. The CICDDoS2019 dataset identifies and classifies such attacks in the simulated environment. In addition, a virtual software-defined network (SDN) is used to collect network information from the surrounding area. When an attack occurs, the pre-trained models are used to analyze the traffic and predict the attack in real-time. The performance of the proposed methodology is evaluated based on two metrics: accuracy and detection time. The results reveal that the proposed model achieves an accuracy of 99% within 1 s of the detection time.

The robotic airship can be used as an aerostatic platform for many potential applications, for example, communication, hovering payload deliveries, data-gathering for research studies, etc. These applications require a fully autonomous perspective of an airship. One of the important aspects of airship autonomy is trajectory tracking control. An airship has complex and uncertain nonlinear dynamics which pose a major challenge for designing a precise trajectory tracking control. This paper addresses the airship trajectory tracking control problem under model uncertainties and wind disturbance. We propose a lumped model uncertainties and wind disturbance estimation approach based on an unscented Kalman filter. The estimated lumped uncertainty is used by the Sliding Mode Controller (SMC) for ultimate control of airship trajectory tracking. This comprehensive algorithm, Unscented Kalman filter-based Sliding Mode Controller (USMC), is used as a robust adaptive control solution to track the desired trajectory. The stability and convergence of the proposed method are investigated using the Lyapunov stability analysis. Simulation results show that the proposed method efficiently tracks the desired trajectory. The method solves the stability, convergence, and chattering problem of SMC without the bound constraint of model uncertainties and wind disturbance.

Inherited Metabolic Disorders (IMDs) constitute a varied group of genetic disorders marked by disruptions in essential molecule metabolism, resulting in diverse clinical manifestations. Early diagnosis and prompt intervention are critical for optimal disease management and the prevention of long-term complications. Metabolomics, an impactful analytical approach, has surfaced as a valuable tool in the screening, diagnosis, and monitoring of IMDs. This review offers an insight into the role of metabolomics in IMD screening, emphasizing its applications, challenges, and future potential. Metabolomics interrogates the complete spectrum of small-molecule metabolites in biological samples, allowing precise detection of metabolic perturbations that serve as signatures of specific disease states. Despite challenges in data interpretation and standardization, the ongoing evolution of technology positions metabolomics as a promising avenue for early detection and personalized management of IMDs, contributing to advancements in both research and clinical practice.