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This study aims to analyze, determine, and quantify the literature on student intention toward entrepreneurship development (ED) and identify trends, developments, or progressions in the SCOPUS database. By utilizing an electronic search methodology, the most pertinent scholarly articles were identified. VOS Viewer software and R program code were utilized to evaluate each analytical instrument. Coauthorship, co-citation, conceptual structure, co-word occurrence, and citation analysis were among the numerous factors investigated. The study incorporates data from 1,465 sources, including conference proceedings, journals, and books. The source with the second-highest impact is the International Journal of Education, while Computers and Education has the greatest influence. This study provides a complete picture and description of the resulting body of knowledge in student intention toward entrepreneurship development. [ABSTRACT FROM AUTHOR]

Device-to-Device (D2D) communication is a gifted component for 5G as it has two innate returns such as traffic reduction and consistent quality of services. Also, D2D is more elastic and efficient and exploits less power than other techniques. Few research works have been designed to provide better D2D communication but, providing maximum throughput is still a demanding one. A novel nature-inspired approach called Multi-Objective Binomial Scrambled Bumble Bees Mating Optimization (MOBSBBMO) technique is proposed to perform D2D communication with higher throughput and lesser loss rate. The MOBSBBMO technique uses multiple objective functions to obtain the optimal mobile device for D2D communication. First, the population (i.e. number of mobile devices) gets initialized arbitrarily. The fitness function is calculated for the number of mobile devices depending on multiple objectives such as energy efficiency, bandwidth capacity, and device cooperativeness. According to the fitness, tournament selection is applied to determine the optimal mobile device. If the fitness criterion is satisfied, then the mobile device is said to be optimal. The MOBSBBMO technique uses the binomial crossover applied to obtain broods by the mating process. Next, scramble mutation is employed to get the best drone bees. Yet, again the mating process is carried out to obtain the optimal solution for the best mobile device. The proposed MOBSBBMO technique is compared with benchmark methods in terms of throughput, data delivery rate, energy efficiency, packet loss rate, and latency. Simulation results show that the proposed MOBSBBMO can notably improve network throughput. [ABSTRACT FROM AUTHOR]

The activation of caspases is a crucial event and an indicator of programmed cell death, also known as apoptosis. These enzymes play a central role in cancer biology and are considered one promising target for current and future advancements in therapeutic interventions. Traditional methods of measuring caspase activity such as antibody-based methods provide fundamental insights into their biological functions, and are considered essential tools in the fields of cell and cancer biology, pharmacology and toxicology, and drug discovery. However, traditional methods, though extensively used, are now recognized as having various shortcomings. In addition, these methods fall short of providing solutions to and matching the needs of the rapid and expansive progress achieved in studying caspases. For these reasons, there has been a continuous improvement in detection methods for caspases and the network of pathways involved in their activation and downstream signaling. Over the past decade, newer methods based on cutting-edge state-of-the-art technologies have been introduced to the biomedical community. These methods enable both the temporal and spatial monitoring of the activity of caspases and their downstream substrates, and with enhanced accuracy and precision. These include fluorescent-labeled inhibitors (FLIs) for live imaging, single-cell live imaging, fluorescence resonance energy transfer (FRET) sensors, and activatable multifunctional probes for in vivo imaging. Recently, the recruitment of mass spectrometry (MS) techniques in the investigation of these enzymes expanded the repertoire of tools available for the identification and quantification of caspase substrates, cleavage products, and post-translational modifications in addition to unveiling the complex regulatory networks implicated. Collectively, these methods are enabling researchers to unravel much of the complex cellular processes involved in apoptosis, and are helping generate a clearer and comprehensive understanding of caspase-mediated proteolysis during apoptosis. Herein, we provide a comprehensive review of various assays and detection methods as they have evolved over the years, so to encourage further exploration of these enzymes, which should have direct implications for the advancement of therapeutics for cancer and other diseases. [ABSTRACT FROM AUTHOR]