Thermochromic materials (TCMs) have attracted increasing attention as passive adaptive materials for solar regulation in buildings because they can reversibly change their optical properties in response to temperature without external energy input. Owing to this temperature-triggered optical modulation, they have been widely investigated for smart windows, temperature indicators, anti-counterfeiting labels, and flexible devices. In recent years, representative systems such as VO2-based materials, polymers, hydrogels, and organic–inorganic hybrids have shown steady progress, especially in transition-temperature tuning, spectral selectivity, and cycling stability. This review summarizes the main classes of TCMs as well as their color-changing mechanisms, preparation methods, and performance-regulation strategies, with an emphasis on building energy efficiency and passive solar regulation. Typical applications and current bottlenecks are also discussed, including response speed, durability, environmental compatibility, and large-scale manufacturing. Finally, several practical directions for future work are highlighted, particularly low-cost synthesis, multifunctional integration, and application-oriented material design.

Medicinal animals are integral to traditional healthcare worldwide, yet ethnozoological knowledge in many Ethiopian regions remains under-documented. This study documented the diversity of medicinal animals, associated cultural knowledge, preparation methods, and conservation implications among communities in Andracha District, Ethiopia. A cross-sectional ethnobiological survey was conducted from January to August 2025 using semi-structured interviews, focus group discussions (FGDs), and field observations. Sixty-five informants participated, including 25 key informants purposively selected and 40 general participants randomly chosen. FGDs refined data collection instruments and validated traditional knowledge. Quantitative indices Relative Frequency of Citation (RFC), Informant Consensus Factor (ICF), Fidelity Level (FL), and Zoological Ethnoknowledge Index (ZEI) summarized knowledge patterns, species importance, and cultural reliability. Jaccard Similarity Index (JSI) and Rahman's Similarity Index (RSI) assessed cross-community similarity. Statistical analyses, including t-tests, ANOVA, and linear regression, explored variations across gender, age, education, and experience using R software. A total of 52 medicinal animal species were documented in Andracha District. Bos taurus, Apis mellifera, and Halictus scabiosae exhibited the highest RFC values. ICF ranged from 0.60 to 0.97, with the strongest agreement observed for respiratory and gastrointestinal ailments. The highest FL was recorded for Capra aegagrus hircus (FL = 83.3%), followed by Apis mellifera (FL = 77.8%). Knowledge of medicinal animals varied significantly with age, gender, literacy, and healer experience (P < 0.05). Major threats to medicinal fauna included agricultural expansion, overgrazing, and overexploitation, while indigenous conservation practices such as sacred forest protection and community stewardship were actively maintained. Medicinal animals are crucial for healthcare, cultural identity, and livelihoods in Andracha District. Environmental pressures and generational gaps threaten both species and associated knowledge. Strengthening community-based conservation, sustainable harvesting, and intergenerational knowledge transmission is essential to safeguard this biocultural heritage. The study documents traditional practices but does not endorse ingestion or application of potentially hazardous animal products.

Breast cancer remains a leading cause of cancer-related morbidity and mortality worldwide, and conventional chemotherapy with paclitaxel (PTX) is limited by poor solubility, systemic toxicity, and suboptimal tumor targeting. Liposomal formulations of PTX have emerged as promising nanocarrier-based strategies to overcome these challenges by enhancing drug solubility, improving pharmacokinetics, reducing adverse effects, and enabling targeted delivery. This review provides a comprehensive overview of PTX liposomal formulations, including conventional, PEGylated, targeted, and stimuli-responsive liposomes, with emphasis on their composition, preparation methods, and optimization parameters. Clinical and preclinical studies, including recent advances (2024-2025), highlight improved cellular uptake, antitumor efficacy, and safety profiles compared to conventional PTX. The review also discusses approved formulations (e.g., Lipusu ® ), ongoing clinical trials, and combination therapy approaches. Finally, challenges related to scale-up, stability, regulatory approval, and clinical translation are addressed, alongside emerging trends such as smart liposomes, hybrid nanocarriers, and personalized therapy. Collectively, liposomal PTX represents a promising platform for enhancing therapeutic outcomes in breast cancer, with ongoing research paving the way for next-generation, safer, and more effective chemotherapy strategies.

Abstract -Medicinal plants have long played a vital role in traditional healthcare systems, yet accurate identification remains challenging due to visual similarities, regional variations, and language barriers. This project introduces an intelligent system leveraging Convolution Neural Networks (CNNs) with Transfer Learning using ResNet50 for medicinal plant identification from images. By fine-tuning ResNet50 on a labelled dataset of medicinal plant images, the system achieves high classification accuracy while efficiently extracting discriminative features such as leaf veins and texture patterns. Once a plant is identified, the platform retrieves ethnopharmacological insights and displays its scientific name, regional name, medicinal uses, parts used, and preparation methods. Multilingual support in both English and Telugu ensures accessibility for diverse users, including researchers, herbal practitioners, and local communities. The system addresses challenges such as image variability, class imbalance, and real-time identification requirements through optimized deep learning models and an intuitive user interface. By integrating artificial intelligence with ethno botanical knowledge, this project contributes to preserving traditional medicinal wisdom while enhancing its accessibility through modern technology. The scalability of the platform ensures usability across different devices, making it a valuable tool for education, research, and practical applications in traditional medicine. Key Words: Machine Learning, Deep Learning, Transfer Learning, Convolution Neural Network, Plant Disease identification, ResNet 50.

Rectal drug delivery is an important alternative route for administering drugs, especially in conditions where oral administration is not feasible such as vomiting, unconsciousness, and seizures. Phenytoin is a widely used antiepileptic drug, but its oral and parenteral administration presents several limitations including poor patient compliance and variable bioavailability. The present review focuses on the design and development of phenytoin rectal suppositories using natural polymers. Natural polymers such as alginate, pectin, and xanthan gum are gaining attention due to their biocompatibility, biodegradability, and ability to provide controlled drug release. These polymers play a significant role in enhancing drug stability, improving release characteristics, and increasing patient acceptability. The formulation of suppositories involves careful selection of base, polymer, and preparation method to achieve desired therapeutic outcomes. This review highlights the principles of rectal drug delivery, types of suppository bases, role of natural polymers, formulation techniques, and evaluation parameters such as drug content, melting point, and in vitro drug release. Additionally, recent advances and challenges associated with rectal suppository formulations are discussed. Overall, phenytoin rectal suppositories containing natural polymers represent a promising approach for effective and controlled management of epilepsy, particularly in emergency and pediatric conditions, offering improved bioavailability and better patient compliance.

Perovskitoids have attracted widespread attention in recent years by extending octahedral connectivity, thereby overcoming the traditional 3D perovskite materials' limitations on the tolerance factor, expanding structural diversity, and enhancing stability and bandgap tunability. This review first summarizes the advanced preparation methods for high-quality perovskitoid single crystals. Subsequently, we systematically classify perovskitoids into 0D, 1D, 2D, and 3D structures based on their dimensionality, elaborating on the relationship between their unique octahedral connectivity modes and optoelectronic properties. Furthermore, advances in perovskitoids for optoelectronic applications are highlighted, with a focus on their roles in solar cells, light-emitting devices, and detectors. Finally, to address current bottlenecks, we propose future perspectives to accelerate their practical commercialization.

The research focuses on assessing the economic efficiency of implementing a jigless manufacturing preparation method in light aircraft production. The relevance of the research is determined by the need to reduce costs and lead times for manufacturing preparation when developing new aircraft types, which is especially important for small-batch aircraft production. Traditional template-based manufacturing preparation methods require significant expenditures for the design and production of assembly tooling, which reduces the economic efficiency of production processes. The use of digital product models and coordinate-based alignment technologies creates prerequisites for the transition to jigless manufacturing preparation methods. The aim of the study is to develop a methodology for assessing the economic efficiency of implementing a jigless manufacturing preparation method for light aircraft production. To achieve this aim, the following tasks were addressed: analyzing of the cost structure of manufacturing preparation; development of a cost model for implementing the jigless manufacturing preparation method; identification of the main sources of economic benefits; and development of an algorithm for calculating integrated indicators of economic efficiency. The research methodology is based on econometric modeling, analysis of aircraft manufacturing processes, and the application of discounted cash flow methods for investment evaluation. The results of the study provide a formalized methodology for assessing the economic efficiency of implementing jigless manufacturing preparation technologies. The proposed methodology makes it possible to quantitatively evaluate the economic effects obtained through the reduction of assembly tooling manufacturing costs, the decrease in labor intensity of manufacturing preparation processes, and the improvement of flexibility in manufacturing systems. The conclusions confirm that the implementation of a jigless manufacturing preparation method is economically feasible and contributes to reducing manufacturing preparation costs and improving the efficiency of resource utilization in light aircraft production. The scientific novelty of the study lies in the development of a formalized methodology for the economic evaluation of jigless manufacturing preparation technologies, which considers the structure of assembly tooling manufacturing costs, the labor intensity of manufacturing preparation processes, and the influence of production volume on the economic feasibility of implementing jigless technologies. The practical significance of the obtained results lies in the possibility of using the proposed methodology for the techno-economic justification of implementing jigless manufacturing preparation technologies at aircraft manufacturing enterprises.

Background: Growing global water pollution and the need for sustainable treatment technologies have intensified the demand for high-performance coagulants like PAC. Consequently, research has focused on developing economically viable and environmentally friendly manufacturing approaches without compromising its efficiency. Aims: Polyaluminium chloride (PAC) has emerged to be the most effective coagulant for water treatment over most conventional coagulants because of its low dosage amounts required, less flocculation time, less sludge, high efficiency and less aluminium residues remain in treated water. The current commercial preparation method involves the use of rigorous conditions and expensive raw materials which drives high production cost such that its adoption by low-income economies is hindered. Over the years various studies have been devoted to find cost effective methods of producing PAC. Thus, the present review aims at providing a systematic review of such methods. Study Design: Systematic review of literature. Place and Duration of Study: Harare Institute of technology Jan-March 2026. Methodology: Data collection was performed by searching major databases, Scopus, Google scholar, Scifinder and Springer up to March 2026 with the key phrases cost-effective or low-cost methods of preparing PAC. The inclusion criteria involved only scientific studies reporting cost-effective methods while the exclusion criteria involved rejecting all studies describing high-cost PAC synthesis methods and those reporting vigorous conditions Results: A total of 338 publications were systematically screened. Relevant records from Google scholar were 150, Science Direct 100, Scopus 66 and SciFinder 22. On analysis the final selection consisted of 17 (5%) primary publications reporting cost effective manufacturing procedures, and 5 (29%) with real industrial applications. From the greened studies, there is a general agreement that in order to bring down the cost, methods that utilizes locally available, affordable, sustainable and promote ecofriendly efforts and allows the use of mild preparation conditions should be adopted. Natural, industrial, mining and home waste residues have been selected for use as raw materials in PAC preparations. Among the raw materials selected bauxite, kaolin and aluminium tins and scrapings have been widely studied and they produced PAC that was pure, highly efficient and of desirable basicity. Its performance was not inferior to PAC produced by the standard industrial preparation method. Calcination and electrochemical methods have been reported to be cost effective methods that do not depend on the use of vigorous conditions. Thus, PAC produced using these alternative procedures was said to be also useful not only in the treatment of waste water but also in treating drinking water. Conclusion: Although the PAC produced by alternative methods was extensively checked for quality in terms of purity (Al/OH) ratio, contamination and other important parameters, few studies went further to utilize it to treat real environmental water and check the feasibility in terms of process cost and efficiency in its application in a real industrial set up. This gap require interrogation so that the studies can be complete and useful.

Introduction . Multi-stage spinal surgery in child is a significant source of recurring psychoemotional stress for the patient and his parents, which increases the risk of postoperative complications, including agitation and delirium. In this regard, the search for safe non-pharmacological methods of correcting the perioperative condition is relevant. Aromatherapy is considered as one of these methods, but its use in the context of multi-stage spinal surgery in children with simultaneous effects on the parent-child dyad has not been sufficiently studied. The objective was to evaluate the effect of preoperative aromatherapy on the level of anxiety and depression in parents, as well as on the frequency of postoperative agitation in children undergoing multi-stage spinal surgery. Materials and methods . A prospective randomized open-label controlled trial was conducted. Children aged 5-15 years (n = 50) who were scheduled for surgery using the envelope method were divided into the main group (n = 25; aromatherapy sessions using a mixture of essential oils) and the control group (n = 25; without aromatherapy). The parents’ anxiety and depression levels were assessed on the HADS scale before and on the 3rd day after surgery. Postoperative agitation in children was assessed on the RASS scale during the first 3 hours of awakening. The occurrence of delirium was assessed on the Pediatric Anesthesia Emergence Delirium scale PAED scale on the first day after surgical treatment. Results . In the preoperative period, all parents demonstrated a high level of anxiety on the HADS scale, with no significant differences between the groups (control group: Me [Q1; Q3] = 7.0 [5.0; 9.0]; main group: 8.5 [6.0; 11.0]). In the postoperative period, the main group recorded a significant decrease in the anxiety index to 4.7 [2.0; 7.0] points, while in the control group it increased slightly to 8.5 [6.0; 11.0] (p &lt; 0.005). No episodes of post-operative agitation were recorded in the child in the main group, 5 cases of agitation (20%) were recorded in the control group. There were no cases of delirium in the groups, as well as the relationship between the level of preoperative anxiety in the parent and the development of agitation in the child. Conclusions . The results obtained suggest that preoperative aromatherapy can be an effective auxiliary method for reducing psychoemotional stress in parents and preventing postoperative agitation in children during multi-stage spinal surgeries.

Abstract - Securing employment in the current job market is increasingly challenging, and effective interview preparation remains a significant hurdle for many candidates. Common preparation methods such as online videos, peer mock sessions, and generic question banks often fail to provide meaningful performance insights or actionable feedback. This paper presents a web-based platform designed to address these limitations. The system makes use of the Groq AI Engine API to conduct live mock interviews, dynamically generate role-specific questions, and evaluate candidate responses in real time. In addition, the platform incorporates an aptitude assessment and two coding challenges to strengthen technical proficiency. The frontend is developed using ReactJS, while Firebase Firestore manages backend data, including user records, performance scores, and session history. Overall, the system delivers a reliable, efficient, and user-centered solution for interview preparation, providing candidates with practical insights and measurable performance improvements. Key Words: Artificial Intelligence, Mock Interview, Groq API, ReactJS, Firebase Firestore, Natural Language Processing, Coding Challenges Aptitude Testing, Real-time Feedback, Career Preparation, Web Application.

Background/Objectives: Cannabidiol (CBD) has emerged as a potential therapeutic agent for respiratory disorders, including asthma and chronic obstructive pulmonary disease. However, its clinical translation via pulmonary delivery is limited by poor aqueous solubility, chemical instability, and low local bioavailability. This study aimed to develop and optimize a sodium stearate (NaSt)-based spray-dried dry powder inhaler (DPI) formulation to enhance the aerosol performance, dissolution, and storage stability of CBD. Methods: CBD microparticles were prepared by spray drying using NaSt as the primary excipient. The feed preparation method, spray-drying parameters, and CBD:NaSt ratios were systematically optimized. The resulting powders were evaluated for aerodynamic properties using cascade impaction, dissolution behavior in simulated lung fluid, solid-state characteristics, and accelerated stability under stress conditions. Results: The optimized formulation, SD-4, a spray-dried CBD:NaSt formulation prepared at a 20:80 weight ratio using Process B, demonstrated excellent aerosolization performance, with a fine particle fraction (FPF) exceeding 50% and a mass median aerodynamic diameter (MMAD) of 5.08 ± 0.1 μm. Dissolution testing revealed more than a three-fold increase in drug release compared with raw CBD, attributed to amorphous dispersion within the NaSt matrix and surfactant-induced micellization. Accelerated stability studies confirmed improved retention of the amorphous state and drug content, while antioxidant incorporation further reduced oxidative degradation. Conclusions: The NaSt-based spray-dried formulation significantly improved aerosol deposition efficiency, dissolution rate, and physicochemical stability of CBD. This formulation strategy may provide a promising platform for pulmonary delivery of poorly water-soluble compounds.

Diaryliodonium(III) salts with N ‐reactive amides are proposed as new attractive synthetic tools for the construction of benzo‐fused nitrogen heterocycles. In this study, we have developed an efficient preparation method for ortho ‐functionalized diaryliodonium salts bearing N ‐phthalimide ( N ‐NPhth) groups. Unlike strategies requiring ortho ‐leaving groups, these salts demonstrated their application in both transition metal‐free and transition metal‐catalyzed sequential coupling reactions, leading to the construction of five‐ and seven‐membered heterocyclic compounds.

ABSTRACT Nickel oxide (NiO x ), an efficient inorganic hole transport layer (HTL), has emerged as a key material driving the industrialization of inverted perovskite solar cells (PSCs). Its success stems from favorable energy‐level alignment, excellent charge transport features, high stability, and low cost. Among various preparation methods, solution‐based syntheses are particularly attractive for NiO x ‐based PSCs, due to their simplicity, compatibility, and scalability. This review systematically summarizes four mainstream solution‐based techniques for synthesizing NiO x HTLs, including pre‐synthesized nanoparticles, sol‐gel, solution combustion, and chemical bath depositions. For each method, we discuss the reaction mechanisms and processing features, the resulting film properties, and strategies for performance optimization in PSCs. We then outline challenges associated with each route and highlight recent advances in material modification, process engineering, and structural design aimed at overcoming these bottlenecks and enhancing device efficiency. Further research should address critical issues such as uniformity control in large‐area, rapid synthesis processes and reliable preparation of high‐crystallinity, low‐defect films at low temperatures. A deeper understanding of the relationships among solution processes, microstructure, and device performance will be essential for fully realizing the potential of solution‐based NiO x HTLs in high‐performance, high‐stability, and low‐cost perovskite photovoltaic technologies.

Milk fat globule membrane (MFGM), as a key structural component of milk fat globules (MFG) in breast milk, plays a vital role in infant growth and development. Increasing evidence indicates that MFGM supports this process by supplying essential nutrients and regulating metabolic pathways. Its preparation and incorporation into infant formula have become prominent research topics. This article reviews the secretory pathways, structural organization and physiological functions of MFGM, and summarizes in detail the effects of MFGM on lipid metabolism, brain neurodevelopment, immune system and intestinal health. In addition, the major preparation methods of MFGM at the present stage, and their progress in the application of infant formula are presented in this paper. The development of additional new processes and clinical studies are emphasized as key to constructing and evaluating infant formulas with MFG-mimicking structures, providing new insights into the breastfeeding of infant formulas.

Disulfides play pivotal roles in diverse scientific domains, ranging from protein folding and cellular redox homeostasis to advanced materials development and pharmaceutical innovation. While various synthetic methodologies have been established, the efficient and selective construction of unsymmetrical disulfides continues to present significant synthetic challenges. This review highlights innovative approaches for synthesizing unsymmetrical disulfides utilizing different sulfur sources, including thiols (or thiophenols), disulfurating reagents, and symmetrical disulfides as sulfur sources, demonstrating broad substrate applicability and functional group tolerance under mild conditions. These innovative methodologies demonstrate significant advantages in substrate diversity, functional group compatibility, and reaction efficiency under mild conditions, marking substantial progress over conventional methods. The synthetic protocols can be further enhanced through strategic optimization of reaction parameters, such as catalyst selection, substrate modification, and condition adjustment, to achieve the desired unsymmetrical disulfides. Beyond summarizing current achievements, this review outlines promising directions for future research, emphasizing the development of more sustainable and selective synthetic pathways. These advancements are anticipated to significantly contribute to the progress of pharmaceutical sciences, materials engineering, and related interdisciplinary fields, ultimately driving innovation in both fundamental research and practical applications.

mNGS is a powerful and unbiased approach towards pathogen detection that has mostly been applied to blood and cerebrospinal fluid samples. However mNGS has recently been applied to more areas including the respiratory pathogen detection space, with potential applications in both in-patient diagnostics and public health surveillance. Saliva samples are an ideal sample type for these use cases since they can be collected non-invasively. However, saliva is also a challenging sample type due to its high RNase activity and often yields low-quality nucleic acid. This study explores the feasibility of using saliva specimens in mNGS with contrived SARS-CoV-2 samples to optimize the combination of two factors: nucleic acid extraction and RNA-seq library preparation. Exploration in this area could enhance the sensitivity of saliva-based mNGS assays, with the goal of future expansion of this specimen type in clinical diagnostics and public health surveillance. The choice of RNA-Seq library preparation kit has a greater impact on pathogen detection than the nucleic acid extraction method.The combination of Zymo Quick-RNA Magbead extraction kit and TECAN Revelo RNA-Seq High Sensitivity RNA library kit recovered the highest percentage of total SARS-CoV-2 reads.RNA quantity and RINe score do not correlate with viral read capture, indicating a need for an alternative metric to assess RNA quality for downstream mNGS clinical diagnostics.

ABSTRACT Polymer‐based electromagnetic interference (EMI) shielding composite fibers have gradually become a research hotspot in the field of EMI shielding due to their advantages of being lightweight, corrosion‐resistant, highly flexible, and easily weavable. This review focuses on the preparation strategies of polymer‐based EMI shielding composite fibers, systematically reviewing the research progress and characteristics of wet spinning, electrospinning, and other methods such as chemical deposition and template methods. Starting from the structural design principles of fibers, it specifically analyzes the construction strategies, preparation methods, and development status of solid, core–shell, and hollow structures of polymer‐based EMI shielding composite fibers. It summarizes the effects of different preparation processes and structural morphologies on the EMI shielding performance and mechanical properties of polymer‐based EMI shielding composite fibers, identifies key scientific and technical issues that need to be resolved in current preparation methods, and looks ahead to the future development trends of polymer‐based EMI shielding composite fibers. This review aims to provide theoretical guidance for the innovation of preparation strategies and performance improvement of polymer‐based EMI shielding composite fibers, promote their applications in aerospace, smart wearables, medical electronics, and other fields, and open up new directions for the development of electromagnetic protection materials.

Lonicera japonica Flos (LJF) is widely used in pharmaceuticals and functional foods, with its bioactive constituents significantly influenced by processing methods. This study characterized the dynamic changes in chemical components in LJF under different maceration and decoction durations. Using UPLC-Q-TOF-MS and molecular networking, a total of 260 metabolites were unambiguously identified or tentatively characterized, including 66 iridoids, 42 flavonoids and 49 phenolic acids. Among these, 11 phenolic acids and 3 flavonoids were absent in the macerated samples. Twenty-two representative compounds were quantified using calibration curves. Most secondary metabolites, particularly phenolic acids, exhibited lower levels in the macerated samples than the decocted samples (e.g., 5-O-caffeoylquinic acid: 65.67-106.41 μg/g during maceration vs. 32,783.05-55,754.68 μg/g during decoction). The decoction process significantly enhances the extraction of active constituents. Notably, certain iridoids (e.g., 7-O-methyl morroniside: 92.91-354.59 μg/g during maceration vs. 50.43-171.40 μg/g during decoction) were better preserved under maceration, highlighting its advantage for retaining heat-sensitive bioactive components. During the decoction process, 5-hydroxycinnamoylquinic acids tended to transform into 3- and 4-hydroxycinnamoylquinic acid isomers. Most di-hydroxycinnamoylquinic acids and flavonoids significantly decreased after 30 min. Nitrogen-containing seco-iridoids declined rapidly after 15 min. To balance extraction efficiency with the preservation of heat-sensitive bioactive components, a decoction time of 15-30 min is recommended. The study systematically elucidates the dynamic changes in bioactive components under two preparation methods, offering critical insights and a scientific foundation for the precision utilization of LJF in pharmaceutical and functional food industries.

The increasing demand for transparent and individualized dietary guidance has stimulated the application of machine learning techniques in nutrition assessment. Nevertheless, many existing models emphasize predictive accuracy while providing limited domain validation and contextual interpretability. This study develops an expert-integrated, goal-oriented decision-support framework for meal healthiness evaluation. Using a publicly available Kaggle dataset containing 2,000 meal observations, an interpretable logistic regression model was estimated to classify meals according to nutritional composition and preparation methods. The model demonstrated robust performance, achieving an accuracy of 94.17% and an AUC-ROC of 0.967, indicating strong discriminative capacity. To strengthen reliability and applied relevance, model predictions were subjected to independent expert nutritional review to ensure consistency with established dietary guidelines. In addition, a goal-adaptation layer was implemented to contextualize classifications according to user-specific objectives, including weight reduction, muscle hypertrophy, endurance performance, and general health maintenance. By integrating statistical modeling, expert validation, and personalized objective mapping, the framework extends beyond static prediction toward an operational decision-support system. This approach advances interpretable artificial intelligence in nutrition analytics and provides scalable potential for digital health and performance-oriented dietary applications.

Low-grade inflammation in musculoskeletal disorders: biological basis and role of PRGF