Search Results (284)

The rising demand for sustainable energy storage has fueled the development of green batteries as alternatives to conventional systems. However, a major research gap lies in the unified integration of environmentally friendly materials and processes across all battery components—electrodes, electrolytes, and separators—without compromising performance or scalability. This review addresses this gap by highlighting recent advances in eco-conscious battery technologies, focusing on green electrode fabrication using water-based methods, electrophoretic deposition, solvent-free dry-press coating, 3D printing, and biomass-derived materials. It also examines the shift toward safer electrolytes, including ionic liquids, deep eutectic solvents, water-based systems, and solid biopolymer matrices, which improve both environmental compatibility and safety. Additionally, biodegradable separators made from natural polymers such as cellulose and chitosan offer enhanced thermal stability and ecological benefits. The review emphasizes the importance of lifecycle considerations like recyclability and biodegradability, aligning battery design with circular economy principles. While significant progress has been made, challenges such as standardization, long-term stability, and industrial scalability remain. By identifying key strategies and future directions, this article contributes to the foundation for next-generation green batteries, promoting their adoption in environmentally sensitive applications ranging from wearable electronics to grid storage. Full article

Background: Developing countries face significant challenges in accessing high-quality pharmaceutical products due to resource constraints, limited regulatory capacity, and market dynamics that often prioritize cost over quality. This review addresses the critical gap in regulatory frameworks that fail to ensure pharmaceutical quality equity between developed and developing nations. Objective: This comprehensive review examines a novel dual-pathway regulatory framework that leverages stringent regulatory authority (SRA) approvals, artificial intelligence-based evaluation systems, and harmonized pricing mechanisms to ensure pharmaceutical quality equity across global markets. Methods: A comprehensive systematic analysis of current regulatory challenges, proposed solutions, and implementation strategies was conducted through an extensive literature review (202 sources, 2019–2025), expert consultation on regulatory science, AI implementation in healthcare, and pharmaceutical policy development. The methodology included an analysis of regulatory precedents, an economic impact assessment, and a feasibility evaluation based on existing technological implementations. Results: The proposed framework addresses key regulatory capacity gaps through two complementary pathways: Pathway 1 enables same-batch distribution from SRA-approved products with pricing parity mechanisms. At the same time, Pathway 2 provides independent evaluation using AI-enhanced systems for differentiated products. Key components include indigenous AI development, which requires systematic implementation over 4–6 years across three distinct stages, outsourced auditing frameworks that reduce costs by 40–50%, and quality-first principles that categorically reject cost-based quality compromises. Implementation analysis demonstrates a potential for achieving a 90–95% quality standardization, accompanied by a 200–300% increase in regulatory evaluation capability. Conclusions: This framework has the potential to significantly improve pharmaceutical quality and access in developing countries while maintaining rigorous safety and efficacy standards through innovative regulatory approaches. The evidence demonstrates substantial public health benefits with projected improvements in population access (85–95% coverage), treatment success rates (90–95% efficacy), and economic benefits (USD 15–30 billion in system efficiencies), providing a compelling case for implementation that aligns with global scientific consensus and Sustainable Development Goal 3.8. Full article

Communication in deep-sea shadow zones remains a significant challenge due to high propagation losses, complex multipath effects, long transmission delays, and strong environmental influences. In recent years, orthogonal chirp division multiplexing (OCDM) has demonstrated promising performance in underwater acoustic communication due to its robustness against multipath interference. However, its high peak-to-average power ratio (PAPR) limits its reliability and efficiency in deep-sea shadow-zone environments. This study applies a recently proposed generalized orthogonal chirp division multiplexing (GOCDM) modulation scheme to deep-sea shadow-zone communication. GOCDM follows the same principles as orthogonal signal division multiplexing (OSDM) while offering the advantage of a reduced PAPR. By segmenting the data signal into multiple vector blocks, GOCDM enables flexible resource allocation, optimizing the PAPR without compromising performance. Theoretical analysis and practical simulations confirm that GOCDM preserves the full frequency diversity benefits of traditional OCDM, while mitigating PARR-related limitations. Additionally, deep-sea experiments were carried out to evaluate the practical performance of GOCDM in shadow-zone environments. The experimental results demonstrate that GOCDM achieves superior performance under low signal-to-noise ratio (SNR) conditions, where the system attains a 0 bit error rate (BER) at 4.2 dB and 6.8 dB, making it a promising solution for enhancing underwater acoustic communication in challenging deep-sea environments. Full article

Innovative plant protection solutions are increasingly sought in modern agriculture. Rapid advances in nanotechnology offer promising opportunities to develop biodegradable, cost-effective composites containing silver nanoparticles (AgNPs) with well-documented antimicrobial properties. The aim of this study was to synthesize sodium alginate gels containing AgNPs, evaluate their physicochemical and antibacterial properties, and assess their effect on the growth of red cabbage (Brassica oleracea var. capitata f. rubra) seedlings. In accordance with the principles of green chemistry, AgNPs were chemically synthesized using sodium alginate as a stabilizer and fructose as a non-toxic reducing agent. The final composite contained 150 mg/L AgNPs and was diluted to 20 and 60 mg/L for biological tests. Antibacterial activity against Bacillus cereus, Enterococcus faecalis, Escherichia coli, and Pseudomonas aeruginosa was tested using agar diffusion assays. Seedling growth parameters and phytochemical content were assessed after 10 days of seedlings exposure to AgNPs. The results showed significant antibacterial activity in all tested strains. Crucially, neither AgNPs concentration negatively affected seedling development or phytochemical concentration. Application of AgNPs at concentration of 60 mg/L increased ascorbic acid and carotenoids content in comparison to control (deionized water). These results suggest that AgNPs-alginate composites may serve as sustainable antimicrobial agents in agriculture, inhibiting pathogens without compromising crop quality. Full article

Xerostomia significantly compromises oral comfort, mucosal integrity, and denture retention. While topical therapies such as oral gels are commonly used to manage symptoms, their effectiveness remains limited due to an inability to replicate the complex biochemical and mechanical functions of natural saliva. This review explores the pathophysiology of salivary dysfunction, the structural and functional roles of mucins, and the tribological and rheological demands of the oral environment—particularly in denture wearers. Emphasis is placed on the interplay between mucosal surfaces, salivary films, and prosthetic biomaterials, as well as the importance of mucoadhesion and aqueous boundary lubrication. A rheological comparison of commercially available oral gels and whole human saliva (WHS) reveals that gels are significantly more viscous and elastic, yet fail to mimic the dynamic responsiveness of saliva. Current formulations lack functional standardization and labeling, limiting clinical guidance. The study proposes design principles for next-generation gels that incorporate amphiphilic, biomimetic components and measurable performance benchmarks. Full article

The precise measurement of crankshaft torsional vibration is critical for diesel engine reliability, yet it is often compromised by systematic errors from toothed disc runout. To address this challenge, this paper elucidates the dual mechanism of these errors, which manifest as micro-level voltage fluctuations in signal and macro-level time-domain deviations. Based on this understanding, a composite compensation method is proposed. First, a dual-line approximation method is presented for preprocessing the raw sensor signals, aiming to eliminate the distortion in rotational speed calculations caused by anomalous voltages. Second, a synchronous sampling scheme based on the differential measurement principle is developed. This scheme utilizes a symmetrically arranged dual-sensor structure to suppress runout errors and is combined with a time-domain feature reconstruction technique to restore the true rotational speed signal. Validation on a custom-built universal joint torsional vibration test rig demonstrates that the proposed method can effectively eliminate systematic deviations arising from toothed disc runout, thereby significantly enhancing the accuracy of torsional vibration measurements. The measurement method presented in this paper offers a valuable reference for the high-precision measurement of engine torsional vibration characteristics. Full article

Five-axis sweep scanning measurement technology, as a novel contact measurement technology, offers excellent reachability and high measurement efficiency for complex parts. However, deviations between the measurement instructions based on the model and the workpiece exist, leading to mismatches between the intended and actual sweep scanning areas, which manifest as displacements of the scanning boundaries and subsequently impact the acquisition of sampling points. When these sampling points are utilized to evaluate the machining quality of workpieces, the accuracy and reliability of the assessment results are compromised. Therefore, by focusing on the phenomenon of boundary displacement in a five-axis sweep scanning measurement, the sampling principle has been analyzed, the constrained sector for the probe tip trajectory in a five-axis scanning measurement has been defined, and the concept of the trajectory constrained sector effect has been proposed for the first time. The constrained sector effect reveals how deviations affect the scanning boundary positions and acquisition of sampling points. Based on the constrained sector effect, the influence of deviations on boundary displacement and sampling point acquisition in single-patch and multiple-patch measurement scenarios is discussed. Furthermore, practical engineering recommendations are provided, aiming to reduce the impact of deviations on the completeness of sampling point acquisition. Full article

This review investigates the potential application of polyphenols extracted from indigenous Malus species as natural stabilizers to enhance ice cream thermodynamic properties. Ice cream quality and stability face significant challenges in regions with unreliable electrical infrastructure, such as Lebanon, where temperature fluctuations compromise product integrity. Polyphenols derived from apple tissues and processing by-products demonstrate promising functionality through interactions with ice cream’s protein and fat components, improving stability, reducing melting rates, and enhancing overall thermodynamic properties. Extraction methodologies are critically evaluated, with emphasis on ultrasound-assisted extraction as an optimal approach balancing efficiency, yield, and the preservation of bioactive compounds. This review provides a comprehensive analysis of polyphenolic profiles across apple varieties and tissues, extraction methodologies, mechanisms of stabilization in frozen desserts, and potential sensory implications. The multifunctional approach addresses both technological challenges in frozen dairy products and evolving consumer preferences for clean-label ingredients while potentially adding nutritional value through the inherent bioactive properties of polyphenols. Furthermore, utilizing apple by-products aligns with circular economy principles, transforming waste streams into value-added ingredients. This approach shows particular promise for regions with cold chain challenges while supporting sustainable agricultural practices. Full article

Depression affects millions of people worldwide and remains a significant challenge in mental health care. Despite advances in pharmacological and psychotherapeutic treatments, there is a critical need for accessible and engaging tools that help individuals manage their mental health in real time. This paper presents a novel gamified, AI-driven system embedded within Internet of Things (IoT)-enabled environments to address this gap. The proposed platform combines micro-games, adaptive surveys, sensor data, and AI analytics to support personalized and context-aware depression monitoring and self-regulation. Unlike traditional static models, this system continuously tracks behavioral, cognitive, and environmental patterns. This data is then used to deliver timely, tailored interventions. One of its key strengths is a research-ready design that enables real-time simulation, algorithm testing, and hypothesis exploration without relying on large-scale human trials. This makes it easier to study cognitive and emotional trends and improve AI models efficiently. The system is grounded in metacognitive principles. It promotes user engagement and self-awareness through interactive feedback and reflection. Gamification improves the user experience without compromising clinical relevance. We present a unified framework, robust evaluation methods, and insights into scalable mental health solutions. Combining AI, IoT, and gamification, this platform offers a promising new approach for smart, responsive, and data-driven mental health support in modern living environments. Full article

Mechanical defects and sensor failures can substantially undermine the reliability of low-cost sensors, especially in applications where measurement inaccuracies or malfunctions may lead to critical outcomes, including system control disruptions, emergency scenarios, or safety hazards. To overcome these challenges, this paper presents a novel Self-X architecture with sensor redundancy, which incorporates dynamic calibration based on multidimensional mapping. By extracting reliable sensor readings from imperfect or defective sensors, the system utilizes Self-X principles to dynamically adapt and optimize performance. The approach is initially validated on synthetic data from tunnel magnetoresistance (TMR) sensors to facilitate method analysis and comparison. Additionally, a physical measurement setup capable of controlled fault injection is described, highlighting practical validation scenarios and ensuring the realism of synthesized fault conditions. The study highlights a wide range of potential TMR sensor failures that compromise long-term system reliability and demonstrates how multidimensional mapping effectively mitigates both static and dynamic errors, including offset, amplitude imbalance, phase shift, mechanical misalignments, and other issues. Initially, four individual TMR sensors exhibited mean absolute error (MAE) of 4.709°, 5.632°, 2.956°, and 1.749°, respectively. To rigorously evaluate various dimensionality reduction (DR) methods, benchmark criteria were introduced, offering insights into the relative improvements in sensor array accuracy. On average, MAE was reduced by more than 80% across sensor combinations. A clear quantitative trend was observed: for instance, the MAE decreases from 4.7°–5.6° for single sensors to 0.111° when the factor analysis method was applied to four sensors. This demonstrates the concrete benefit of sensor redundancy and DR algorithms for creating robust, fault-tolerant measurement systems. Full article

The precise control of thermal–kinetic parameters governs epitaxial perfection in functional oxide heterostructures. Herein, using Iridium/MgO(100) as a model system, the traditional “low-speed/high-temperature” paradigm is revolutionized through the combination of ab initio calculations, multiscale simulations, and subsequent deposition experiments. First-principles modeling reveals the mechanisms of Volmer–Weber (VW, island growth mode) nucleation at low coverage and Stranski–Krastanov (SK, layer-plus-island growth) transitions driven by interface metallization, stress release, and energy reduction, which facilitates coherent monolayer formation by lowering the energy barrier by ~34%. Molecular dynamics simulations demonstrate that the strategic co-optimization of substrate temperature (T_sub) and deposition rate (V_dep) induces an abrupt cliff-like drop in mosaic spread. Experimental validations confirm that this T-V synergy achieves unprecedented interfacial coherence, whereby AFM roughness reaches 0.34 nm (RMS) and the XRC-FWHM of 0.13° approaches single-crystal benchmarks. Notably, our novel “accelerated heteroepitaxy” protocol reduces growth time without compromising quality, addressing the efficiency–quality paradox in industrial-scale diamond substrate fabrication. These findings establish universal thermal–kinetic design principles applicable to refractory metal/oxide heterostructures for next-generation quantum sensors and high-power electronic devices. Full article

The rapid integration of the Internet of Medical Things (IoMT) into healthcare systems raises urgent demands for secure communication mechanisms capable of protecting sensitive patient data. Quantum key agreement (QKA), a collaborative approach to key generation based on quantum principles, provides an attractive alternative to traditional quantum key distribution (QKD), as it eliminates dependence on a trusted authority and ensures equal participation from all users. QKA demonstrates particular suitability for IoMT’s decentralized medical networks by eliminating trusted authority dependence while ensuring equitable participation among all participants. This addresses fundamental challenges where centralized trust models introduce vulnerabilities and asymmetric access patterns that compromise egalitarian principles essential for medical data sharing. However, practical QKA applications in IoMT remain limited, particularly for schemes that avoid complex entanglement operations and authenticated classical channels. Among the few QKA protocols employing Grover’s search algorithm (GSA), existing proposals potentially suffer from limitations in fairness and security. In this paper, the author proposes an improved GSA-based QKA protocol that ensures fairness, security, and correctness without requiring an authenticated classical communication channel. The proposed scheme guarantees that each participant’s input equally contributes to the final key, preventing manipulation by any user subgroup. The scheme combines Grover’s algorithm with the decoy photon technique to ensure secure quantum transmission. Security analysis confirms resistance to external attacks, including intercept-resend, entanglement probes, and device-level exploits, as well as insider threats such as parameter manipulation. Fairness is achieved through a symmetric protocol design rooted in quantum mechanical principles. Efficiency evaluation shows a theoretical efficiency of approximately 25%, while eliminating the need for quantum memory. These results position the proposed protocol as a practical and scalable solution for future secure quantum communication systems, particularly within distributed IoMT environments. Full article

In the era of digital transformation, the environmental impact of software development has become a pressing concern, necessitating the integration of sustainability into software development processes. This paper addresses how DevOps, traditionally celebrated for enhancing efficiency and speed in software delivery, can integrate sustainability principles to mitigate environmental impacts. We propose guidelines for integrating sustainability throughout the DevOps life cycle, aiming for significant carbon footprint reduction without compromising quality. Using a Life Cycle Assessment (LCA) approach, this study enables stakeholders to incorporate green guidelines at various software development and operation stages, enhancing software environmental friendliness. Our model supports sustainable software development and encourages proactive environmental impact minimization. Full article

The operational integrity of the BeiDou-3 Navigation Satellite System (BDS-3) has been significantly challenged by electromagnetic interference, particularly from Distance Measuring Equipment (DME) ground beacons to the newly implemented B2a signal, since its full operational deployment in 2020. This study developed a comprehensive interference evaluation model based on receiver signal processing principles to quantify the degradation of B2a signal reception performance under DME interference scenarios. Leveraging empirical data from the DME beacon network in the Chinese mainland, we systematically analyzed the interference effects through an effective carrier-to-noise ratio ($C/N_0$), signal detection probability, carrier tracking accuracy, and demodulation bit error rate (BER). The results demonstrate that the effective $C/N_0$ of the B2a signal degrades by up to 3.25 dB, the detection probability decreases by 33%, and the carrier tracking errors and BER increase by 2.57° and 5.1%, respectively, in worst-case interference scenarios. Furthermore, significant spatial correlation was observed between the interference hotspots and regions of high aircraft density. DME interference adversely affected the accuracy, availability, continuity, and integrity of the airborne BeiDou navigation system, thereby compromising civil aviation flight safety. These findings establish a scientific foundation for developing Minimum Operational Performance Standards for B2a signal receivers and for strategically optimizing DME beacon deployment throughout the Chinese mainland. Full article

Forestry is recognized as one of the most physically demanding professions. Walking in presents unique biomechanical challenges due to complex, irregular terrain, with several possible risks. This study investigated how human gait adapts across solid surfaces, forest trails, and natural forest environments. Fifteen healthy adult participants (average age 38.3; ten males and five females) completed 150 walking trials, with full-body motion captured via a 17 Inertial Measurement Unit (IMU) sensors (Xsens MVN Awinda system). The analysis focused on spatial and temporal gait parameters, including cadence, step length, foot strike pattern, and center of mass variability. Statistical methods (ANOVA and Kruskal–Wallis) revealed that surface type significantly influenced gait mechanics. On forest terrain, participants exhibited wider steps, reduced cadence, increased step and stride variability, and a substantial shift from heel-to-toe strikes. Gait adaptations reflect compensatory neuromuscular strategies to maintain body balance. The findings confirm that forestry terrain complexity compromises human gait stability and increases physical demands, supporting step variability and slip, trip, and fall risk. By identifying key biomechanical markers of instability, this study contributes to understanding human locomotion principles. Understanding these changes can help design safety measures for outdoor professions, particularly forestry. Full article