This paper aims to show the crisis of contemporary criminal systems, however legislative excess of stipulating the penalty of imprisonment, as a penalty depriving freedom, while sometimes stipulating the penalty of imprisonment is mandatory, rather combining it with other penalties, and more than that, depriving the judge of his discretionary power in determining the punishment, this threatens the theory of individualized punishment in a fatal way, so as a result, prisons are overcrowded with inmates, which places a heavy burden on the state from an economic perspective that exhausts and drains its budget, while there is also a social cost of the prison sentence, paid by the prisoner’s family and close circle, moreover the greatest cost is the failure of the penal system to perform its role towards the prisoner by reforming and rehabilitating, therefore, this paper focuses on presenting the causes of the problem and its negative repercussions, trying to find some solutions, by presenting alternatives to the prison sentence, while expanding the view to include some criminal systems, such as the Islamic criminal system and its decision on the penalty of exile.

In the context of establishing businesses in a new region, neglecting environmental orientation may lead to the omission of crucial motives for entrepreneurs’ migration and the subsequent course of their businesses. This present study aims to investigate the effect of green space quality (GSQ), green campaign (GC), and green attitude (GA) on green entrepreneurship pioneering intention (GEPI). Further, national pride (NP) was added as a moderator. This study utilized a cross-sectional approach using a survey method targeting small and medium-sized enterprise (SME) owners who will be relocated to the new capital city. Partial least square structural equation modeling was employed in the data analysis. The results revealed that GSQ, GC, and GA positively influence GEPI. Also, NP moderates the positive influences of GC and GA on GEPI. Entrepreneurs were motivated to pioneer green entrepreneurship in the new region due to environmental factors. Furthermore, their nationalism reinforces the connection between environmental motivations and the aspirations to undertake such pioneering endeavors. The findings present valuable insights for governments to formulate policies that encourage entrepreneurs to migrate internally and establish new economic nodes. Further, the results demonstrate how nationalism encourages green business pioneering endeavors in an untapped market.

In the rapidly evolving landscape of China’s pharmaceutical industry, this study investigates how pharmaceutical enterprises can achieve profitable sales innovation amid the process of digital transformation. Grounded in the Affordance theory, it posits that the positive impact of digital transformation on sales innovation is driven by the affordance afforded by digital technology and ubiquity. The research focuses on A-share pharmaceutical companies in China, utilizing data from 2012 to 2022 and employing multiple regression analysis to examine the influence of digital transformation on corporate sales innovation. The results demonstrate a significant positive effect of digital transformation on sales innovation. The study further categorizes digital transformation into technological affordance and ubiquity affordance, separately validating their roles in promoting sales innovation. Moreover, by considering synergistic effects, the research unveils the intricate relationship between digital transformation and corporate innovation performance. The findings provide a fresh perspective on understanding how digital technology propels sales innovation and offer concrete guidance for the digital transformation practices in the pharmaceutical industry.

This study fills a significant need in the literature by exploring the efficacy of wearable technologies as helpful aids for special needs students in Saudi Arabia. This 12-month quantitative study used a purposive sample of 150 kids representing a range of disability classifications. This study examines the effects of wearable technology, such as smartwatches and augmented reality goggles, on students’ concentration and performance in the classroom. Wearable technology offers great promise, as descriptive statistics show that the experimental group had better involvement and academic achievement. The experimental and control groups vary significantly in terms of academic performance and engagement, as shown by independent samples t-tests. Wearable technology’s distinct benefits are further shown by regression analysis, which shows a favorable correlation with academic achievement after the intervention. According to the results, wearable tech has great promise for inclusive education in Saudi Arabia. Strategic integration, teacher professional development, ongoing research, better accessibility, and wearable gadget customization are some of the suggestions. Stakeholders may use these recommendations as a road map to build a welcoming and technologically sophisticated classroom. This study adds to the growing body of knowledge on assistive technology, especially in Saudi Arabia, and has important implications for academics, politicians, and educators.

Accurate drug-drug interaction (DDI) prediction is essential to prevent adverse effects, especially with the increased use of multiple medications during the COVID-19 pandemic. Traditional machine learning methods often miss the complex relationships necessary for effective DDI prediction. This study introduces a deep learning-based classification framework to assess adverse effects from interactions between Fluvoxamine and Curcumin. Our model integrates a wide range of drug-related data (e.g., molecular structures, targets, side effects) and synthesizes them into high-level features through a specialized deep neural network (DNN). This approach significantly outperforms traditional classifiers in accuracy, precision, recall, and F1-score. Additionally, our framework enables real-time DDI monitoring, which is particularly valuable in COVID-19 patient care. The model’s success in accurately predicting adverse effects demonstrates the potential of deep learning to enhance drug safety and support personalized medicine, paving the way for safer, data-driven treatment strategies.

With the advent of the big data era, the amount of various types of data is growing exponentially. Technologies such as big data, cloud computing, and artificial intelligence have achieved unprecedented development speed, and countries, regions, and multiple fields have included big data technology in their key development strategies. Big data technology has been widely applied in various aspects of society and has achieved significant results. Using data to speak, analyze, manage, make decisions, and innovate has become the development direction of various fields in society. Taxation is the main form of China’s fiscal revenue, playing an important role in improving the national economic structure and regulating income distribution, and is the fundamental guarantee for promoting social development. Re examining the tax administration of tax authorities in the context of big data can achieve efficient and reasonable application of big data technology in tax administration, and better serve tax administration. Big data technology has the characteristics of scale, diversity, and speed. The effect of tax big data on tax collection and management is becoming increasingly prominent, gradually forming a new tax collection and management system driven by tax big data. The key research content of this article is how to organically combine big data technology with tax management, how to fully leverage the advantages of big data, and how to solve the problems of insufficient application of big data technology, lack of data security guarantee, and shortage of big data application talents in tax authorities when applying big data to tax management.

This study investigates the critical skills required for new entrants to succeed in today’s workforce, focusing on both soft and hard skills. Through a comprehensive systematic review of existing literature using the PRISMA method, we analyzed 12 selected journals from an initial pool of 870, sourced from major databases such as Scopus, Science Direct, and Emerald Insight. Our research uncovers four key insights. First, we provide a clear and precise definition of employability skills, establishing the foundation for what competencies are essential for workforce readiness. Second, our analysis identifies a distinct separation between soft and hard skills, with soft skills such as communication, problem-solving, teamwork, ethics, and leadership being universally critical across all industries. Third, while soft skills have broad applicability, hard skills are highly specialized, varying significantly depending on industry and job role. To simplify their understanding and application, we categorized these hard skills into specific groups. Finally, the study highlights the urgent need for further empirical research to validate these findings in real-world settings, as the current conclusions are drawn solely from literature. This potential gap between academic preparation and industry expectations underscores the necessity for ongoing collaboration between educational institutions and employers, which will be a primary focus of our future research.

This study aims to examine the impact of an innovative self-directed professional development (SDPD) model on fostering teachers’ professional development and improving their ability to manage this development independently. A quantitative research method was adopted, involving 60 participants from Almaty State Humanitarian and Pedagogical College No. 2, Almaty, Kazakhstan. Descriptive and inferential statistics were used to assess the SDPD model’s effectiveness, specifically in promoting teacher engagement, adoption of new pedagogical techniques, and improvement in reflective practices. The study findings reveal that teachers, particularly in developing regions, often face challenges in accessing formal professional development programs. The implementation of the SDPD model addresses these barriers by providing teachers with the tools and strategies required for self-improvement, regardless of geographic or economic constraints. The study participants in the pilot phase showed increased engagement with new pedagogical methods, improved reflective practices, and greater adaptability to emerging educational technologies. The algorithmic aspect of the model streamlined the professional development process, while the activity-based approach ensured that learning remained practical and relevant to teachers’ everyday needs. By offering a clear framework for continuous improvement, the model addresses the gaps in formal training access and cultivates a culture of lifelong learning. These findings suggest that the SDPD model can contribute to elevating teaching standards globally, particularly in regions with limited professional development resources.