Muhammad Irfan

Phenomena involving interactions among magnons, phonons, and photons in cavity magnomechanical systems have attracted considerable attention recently, owing to their potential applications in the microwave frequency range. One such important effect is the response of a probe field to such a tripartite interaction between photon-magnon-phonon. In this paper we study the Goos-Hänchen shift (GHS) of a reflected probe field in a cavity magnomechanical system. We consider a yttrium iron garnet (YIG) sphere positioned within a microwave cavity. A microwave control field directly drives the magnon mode in the YIG sphere, whereas the cavity is driven via a weak probe field. Our results show that the GHS can be coherently controlled through magnon-phonon coupling via the control field. For instance, the GHS can be tuned from positive to negative by tuning the magnon-phonon coupling. Similarly, the effective cavity detuning is another important controlling parameter for the GHS. Furthermore, we observe that the enhancement of the GHS occurs when magnon-phonon coupling is weak at resonance and when the magnon-photon coupling is approximately equal to the loss of microwave photons. Our findings may have potential significance in applications related to microwave switching and sensing.

Agricultural productivity is one of the critical factors towards ensuring food security across the globe. However, some of the main crops, such as potato, tomato, and mango, are usually infested by leaf diseases, which considerably lower yield and quality. The traditional practice of diagnosing disease through visual inspection is labor-intensive, time-consuming, and can lead to numerous errors. To address these challenges, this study evokes the AgirLeafNet model, a deep learning-based solution with a hybrid of NASNetMobile for feature extraction and Few-Shot Learning (FSL) for classification. The Excess Green Index (ExG) is a novel approach that is a specified vegetation index that can further the ability of the model to distinguish and detect vegetative properties even in scenarios with minimal labeled data, demonstrating the tremendous potential for this application. AgirLeafNet demonstrates outstanding accuracy, with 100% accuracy for potato detection, 92% for tomato, and 99.8% for mango leaves, producing incredibly accurate results compared to the models already in use, as described in the literature. By demonstrating the viability of a deep learning/IoT system architecture, this study goes beyond the current state of multi-crop disease detection. It provides practical, effective, and efficient deep-learning solutions for sustainable agricultural production systems. The innovation of the model emphasizes its multi-crop capability, precision in results, and the suggested use of ExG to generate additional robust disease detection methods for new findings. The AgirLeafNet model is setting an entirely new standard for future research endeavors.

As the world's demand for sustainable and reliable energy source intensifies, the need for efficient energy storage systems has become increasingly critical to ensuring a reliable energy supply, especially given the intermittent nature of renewable sources. There exist several energy storage methods, and this paper reviews and addresses their growing requirements. In this paper, the energy storage options are subdivided according to their primary discipline, including electrical, mechanical, thermal, and chemical. Different possible options for energy storage under each discipline have been assessed and analyzed, and based on these options, a handsome discussion has been made analyzing these technologies in the hybrid mode for efficient and reliable operation, their advantages, and their limitations. Moreover, combinations of each storage element, hybrid energy storage systems (HESSs), are systems that combine the characteristics of different storage elements for fulfilling the gap between energy supply and demand. HESSs for different storage systems such as pumped hydro storage (PHS), battery bank (BB), compressed air energy storage (CAES), flywheel energy storage system (FESS), supercapacitor, superconducting magnetic coil, and hydrogen storage are reviewed to view the possibilities for hybrid storage that may help to make more stable energy systems in the future. This review of combinations of different storage elements is made based on the previous literature. Moreover, it is assessed that sodium-sulfur batteries, lithium-ion batteries, and advanced batteries are the most helpful element in HESSs, as they can be hybridized with different storage elements to fulfill electricity needs. The results also show that HESSs outperformed other storage systems and, hence, hybridizing the characteristics of different storage elements can be employed for optimizing the performance of energy storage systems.

This paper focuses on the perspectives of passengers who were railway users and how railways as a service can be uplifted with technological advancements through the introduction of information and communication technologies (ICTs). For this purpose, a questionnaire was designed comprised of six sections related to information on socio-economic-demographics, travel, station facilities, train facilities, customer care, and familiarity with and benefits of ICTs. A total of 800 respondents were recruited on trains and in railway stations to collect data through a random sampling technique. Data were analyzed through descriptive statistics, factor analysis, bivariate correlation analysis, and ordered logistic regression analysis. The three hypotheses tested showed that (i) there is a correlation between socio-demographic factors, train frequency, and satisfaction levels, (ii) satisfaction with station and train facilities and customer care impacts users' travel likelihood with the train service, and (iii) users' familiarity with perceived benefits of ICTs influences passengers' travel likelihood with the train service. The results indicate that the users' satisfaction with attributes of station facilities, train facilities, and customer care and perceptions about ICTs significantly influences their travel frequency with the train service. This study is useful for multiple stakeholders, especially for railway management authorities, to provide inclusive services to passengers and to plan for future transportation, which should be well-equipped with ICTs, well-integrated with other transport modes, and well-connected with optimum stops.

This study investigates the effect of altitude on the fatty acid composition of pasture grass, yak milk, and yak ghee on the Qinghai–Tibet Plateau, aiming to understand how environmental factors influence the nutritional quality of these products. Samples were collected from four different altitudes and analyzed for fatty acid profiles using gas chromatography. The analysis reveals that higher altitudes are associated with an increased prevalence of beneficial unsaturated fatty acids, such as oleic acid (C18:1) and linoleic acid (C18:2n6c). These findings highlight the significant influence of altitude on yak lipid metabolism, ultimately enhancing the nutritional value of dairy products. This adaptation not only supports the health and resilience of yaks, but also provides vital nutritional benefits to residents in high-altitude regions. The research underscores the importance of further investigations to optimize dairy production practices, ensuring improved food security and health outcomes for residents of the plateau.

Jurnal Administrasi Bisnis , Sep 2024 Generation Z has great potential to become future investors. However, their interest in investing remains relatively low.

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Abstract Complex neurodevelopmental disorders involve motor as well as cognitive dysfunction and these impairments are associated with both cerebral and cerebellar maturity.

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State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, China