Fuel cells (FCs), as an efficient and clean renewable energy technology, face commercialization challenges primarily due to their limited operational lifetime. Prognostics and Health Management (PHM) techniques offer a solution by monitoring FC states and estimating their Remaining Useful Life (RUL), thereby providing decision support for proactive maintenance and extending system lifespan. Current PHM challenges include reliable and rapid fault localization, developing accurate degradation models, and adopting precise, reliable, and cost-effective life prediction methods. This review describes the key steps of PHM for fuel cells, enumerates various fault diagnosis and life prediction methods, and provides a comparative analysis of hybrid prediction approaches. It also summarizes data-driven life prediction methods, including those based on machine learning and signal processing. Finally, future research directions are proposed, encompassing enhancing online fault diagnosis capabilities and improving the accuracy of PHM systems.

As the core preheating equipment in polypropylene (PP) strapping tape production, the stretching oven’s performance is critically influenced by the uniformity of its internal thermal flow field, which directly determines the molecular chain orientation of the tape blank and the final product’s mechanical properties. Addressing prevalent operational issues such as non-uniform temperature distribution, localized eddy currents causing excessive temperature gradients across the tape blank, and significant fluctuations in final product thickness, this study focuses on a double-belt PP strapping tape stretching oven. A three-dimensional geometric model was constructed using SolidWorks, and computational fluid dynamics (CFD) simulations were performed with its Flow Simulation module. The analysis employed the standard k-ε turbulence model to investigate the distributions of temperature and velocity fields within the oven systematically. The reliability of the numerical model was validated through experiments involving platinum resistance thermometry and hot-wire anemometry, with a maximum relative error of ≤10%. Four distinct structural optimization schemes were subsequently designed and compared. Results indicated that the original oven configuration yielded a maximum temperature difference of 1.5 °C and a relative RMS deviation of velocity of 0.54 in the strapping tape channel, corresponding to product width fluctuations of ± 0.3 mm. Among the proposed modifications, Optimization Scheme 1, which incorporated curved spacers within the air ducts, demonstrated the most significant improvement. This design reduced the maximum temperature difference to 1.0 °C and decreased the velocity’s relative RMS deviation to 0.25—a reduction of 53.7%. Consequently, the product width fluctuation range was narrowed to ± 0.2 mm, representing a 33.3% improvement in dimensional consistency. This research provides a theoretical foundation and practical guidance for enhancing the performance of strapping tape stretching ovens.

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The advent of artificial intelligence (AI) in algorithm discovery represents a fundamental shift in computer science, unlocking new levels of computational efficiency, performance, and optimization. This paper explores the capabilities of AI - driven methodologies, including reinforcement learning, genetic algorithms, neural architecture search, and symbolic AI, in designing novel and more efficient algorithms. These innovations hold profound significance in areas such as sorting, searching, data structures, and numerical simulations. By analyzing various case studies, including Google DeepMind’s AlphaDev and its groundbreaking contributions to optimizing low - level assembly operations, we delve into the broader implications of AI in software development and theoretical computer science. Furthermore, the study examines AI’s impact on cryptographic security, machine learning model optimization, and high - performance computing. Despite these advancements, challenges such as interpretability, formal verification, and ethical concerns persist, necessitating further research. This paper provides a comprehensive review of AI's role in algorithm discovery and discusses future research directions to refine and standardize AI - generated algorithms.

The system architecture adopts the B/S (Browser/Server) structure. The client side does not require installation of any specialized software; a web browser is sufficient to access and use the monitoring system, enabling energy consumption monitoring anytime and anywhere. It offers good scalability, as future functional expansions and upgrades to the software only need to be implemented on the server side. Anyone can browse and use this system, making energy-saving promotion more extensive and effective.

This study explores the economic importance of the nematode dilemma in cucurbitaceae farming as well as the negative consequences of nematicides. Nematicides' pollution of the biosphere is investigated, and nematode control bio - pesticides are evaluated as potential substitutes. The research identifies practical countermeasures to nematicides' unfavourable effects. The symbiotic interaction between nematodes and cucurbit plants is shown by the research, highlighting its economic significance. Economic losses occur from the disruption of soil ecology, decreased fertility, and hampered agricultural production caused by excessive nematicide usage. It has been demonstrated that bio - pesticides are efficient, cost - efficient alternatives. Sustainable solutions are provided through integrated pest management and alternative control strategies. In order to guarantee long - term food security and environmental health, this study promotes sustainable agricultural practises.

Particle breakage is a pervasive micro-scale damage process in granular soils under high pressures, intense shearing, or complex stress paths, and in soils composed of weak or porous particles. By reshaping particle-size distribution (PSD), morphology, and contact networks, breakage alters compressibility, dilatancy, stiffness and strength evolution, and the location (and sometimes uniqueness) of critical and limiting states. Research has shifted from macroscopic inference toward mechanism-based “macro–micro coupling,” enabled by single-particle crushing tests, high-resolution imaging, high-pressure consolidation and large-strain shear/ring-shear testing, DEM fracture modelling, and energy-partition analyses. This review synthesizes representative studies on: breakage quantification and PSD evolution laws; limiting compression curves and micromechanical explanations based on fractal crushing and minimum-particle control; energy dissipation and modified stress–dilatancy relations including breakage work; critical-state non-uniqueness and higher-dimensional state description; and constitutive/numerical modelling strategies from probabilistic crushing to thermodynamically consistent internal variables. Special soils (carbonate sands, volcanic soils, diatomaceous soils) are discussed as benchmarks for transferability. Research priorities are proposed for building a unified, physically based framework that is identifiable from experiments and usable in engineering prediction under monotonic, cyclic, and stress-reversal loading.

Existing research indicates that furfural extracted oil (FEO) can regenerate aged asphalt. However, previous studies have lacked an investigation into the impact of the viscosity of FEO on the regeneration effect of asphalt. Therefore, this paper proposes the use of two viscosities of FEO to regenerate asphalt and compares the effects of different viscosities of FEO on the regeneration of aged asphalt. The basic physical properties of regenerated asphalt containing 10% and 15% of FEO with viscosities of 3.9 and 17-23 were compared using penetration, softening point, and ductility tests. Rheological characteristics were examined through dynamic shear rheometry and bending beam rheometry. Finally, the regeneration mechanism was analyzed using Fourier transform infrared spectroscopy. The findings revealed that FEO can effectively regenerate aged asphalt. As the viscosity of the extracted oil increased, the high-temperature deformation resistance of the regenerated asphalt improved, while its medium-temperature fatigue resistance and low-temperature cracking resistance decreased. Ultimately, it was determined that the ability of FEO to regenerate aged asphalt is due to its addition of small molecular components that are deficient in the aged asphalt. The lower polarity of the low-viscosity FEO allows for better reduction of the solubility of the aged asphalt compared to the higher viscosity oil, thus enhancing the solubility that decreases during the aging process due to increased polarity.

Herbicides are chemicals used to manipulate or control undesirable vegetation. For study Maleic hydrazide were chosen as herbicide because it is applied to onions in the field at a rate of 2.2kg/ha when the bulbs are mature. It is widely known as plant growth regulator, used to suppress growth and induce dormancy in some crops and mostly used to reduce sprouting in stored crops. In the present investigation, the seeds of Trigonella foenum graceum were treated with four different concentrations (10−1, 10−2, 10−3, 10−4) of maleic hydrazide to observe the cytological effect on them. The treatment was given at the seed level. Various abnormalities were noticed at cytological level in different concentrations. Fragmented nuclear material, Sticky metaphase, Sticky Anaphase, Vacuolated cells, Elongated cells, Binucleated, Disrupted Cells were the most frequent abnormalities. The decrease in germination rate was observed in 10−3. Maximum abnormalities were observed in 10−3 and 10−4.

Biomedical Engineering involves developing new devices and procedures that solve medical and health-related problems by combining advanced technologies like Artificial Intelligence and Machine Learning to improve the human health. Bioengineers developing electrical circuits and software’s for Biomedical Instrumentation. In Biomedical Instrumentation equipments are some may be used for recording such as ECG, EEG, EMG and ERG. Some may be used for critical care patients such as pacemakers, defibrillators and ventilators. Some equipments are used to diagnose defect in human body such as X-ray, CT scan, MRI. Advantages of telemedicine in COVID are also reviewed in this paper.