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The world is undergoing a digital disruption whereby many sectors of the economy are dependent on technological advancements to thrive. Therefore, many organizations are striving to move toward digital transformation in order to remain competitive. However, the success of digital transformation initiatives in an organization is highly dependent on the organization's leadership. Therefore, the main objective of the research study is to explore the effect of transformational leadership on the digital transformation of an organization. The following research study uses the context of AI initiatives in a public library in Qatar. The research study is based on the four dimensions of transformational leadership: idealized influence, inspirational motivation, intellectual stimulation, and individualized consideration. The researcher seeks to evaluate the effect of these four transformational leadership traits on the digital transformation of a public organization. To achieve this, the researcher adopts a qualitative research methodology. The researcher adopts a Thematic analysis. The researcher conducts interviews with employees working in the Library in Qatar to get their insights and perspectives on the research area. The data analysis process is done using the Qsr Nvivo software. The researcher establishes eight relevant themes. The researcher concludes that there is a positive relationship between each of the four transformational leadership traits and digital transformation in an organization. The first finding is that the idealized influence trait of transformational leadership positively and significantly influences digital transformation in an organization. The second finding of this research study is that a company's digital transformation is positively and significantly affected by the inspirational motivation trait of transformational leadership. The third finding is that transformational leadership's intellectual stimulation positively and strongly enhances digital transformation efforts. The study's fourth finding is that transformational leadership's individualized consideration positively and significantly influences digital transformation success. The findings of this research contribute significantly to the knowledge and literature in Qatar. The leaders in public organizations can adopt those traits of a transformative leader, which fosters a culture of creativity and innovation that can adapt to the digital age. This research can help library managers and policymakers learn successful leadership approaches that can positively impact digital transformation.

The rise of chronic disease patients and the pandemic pose immediate threats to healthcare expenditure and mortality rates. This calls for transforming healthcare systems away from one-on-one patient treatment into intelligent health systems, leveraging the recent advances of Internet of Things and smart sensors. Meanwhile, reinforcement learning (RL) has witnessed an intrinsic breakthrough in solving a variety of complex problems for distinct applications and services. Thus, this article presents a comprehensive survey of the recent models and techniques of RL that have been developed/used for supporting Intelligent-healthcare (I-health) systems. It can guide the readers to deeply understand the state-of-the-art regarding the use of RL in the context of I-health. Specifically, we first present an overview of the I-health systems' challenges, architecture, and how RL can benefit these systems. We then review the background and mathematical modeling of different RL, deep RL (DRL), and multiagent RL models. We highlight important guidelines on how to select the appropriate RL model for a given problem, and provide quantitative comparisons, showing the results of deploying key RL models in two scenarios that can be followed in monitoring applications. After that, we conduct an in-depth literature review on RL's applications in I-health systems, covering edge intelligence, smart core network, and dynamic treatment regimes. Finally, we highlight emerging challenges and future research directions to enhance RL's success in I-health systems, which opens the door for exploring some interesting and unsolved problems. Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Networked Systems

The rise of plasticulture as mulching material in farming systems has raised concerns about microplastics (MPs) in the agricultural landscape. MPs are emerging pollutants in croplands and water systems with significant ecological risks, particularly over the long term. In the soil systems, MPs polymer type, thinness, shape, and size induces numerous effects on soil aggregates, dissolved organic carbon (C), rapidly oxidized organic C, microbial biomass C, microbial biomass nitrogen (N), microbial immobilization, degradation of organic matter, N cycling, and production of greenhouse gas emissions (GHGs), thereby posing a significant risk of impairing soil physical and biochemical properties over time. Further, toxic chemicals released from polyethylene mulching (PMs) might indirectly harm plant growth by affecting soil wetting-drying cycles, releasing toxic substances that interact with soil matrix, and suppressing soil microbial activity. In the environment, accumulation of MPs poses a risk to human health by accelerating emissions of GHGs, e.g., methane and carbon dioxide, or directly releasing toxic substances such as phthalic acid esters (PAEs) into the soils. Also, larger sizes MPs can adhere to root surface and block stomata could significantly change the shape of root epidermal cells resulting in arrest plant growth and development by restricting water-nutrient uptake, and gene expression and altering the biodiversity of the soil pollutants. In this review, we systematically analyzed the potential risks of MPs to the soil-plant and human body, their occurrence, abundance, and migration in agroecosystems. Further, the impacts of MPs on soil microbial function, nutrient cycling, soil C, and GHGs are mechanistically reviewed, with emphasis on potential green solutions such as organic materials amendments along with future research directions for more eco-friendly and sustainable plastic management in agroecosystems. The current work was supported by the Fundamental Research Funds for the National Natural Science Foundation of China (32161143012).

Background: Acute kidney injury (AKI) after robot-assisted partial nephrectomy (RAPN) is a robust surrogate for chronic kidney disease. The objective of this study was to evaluate the association of ischemia type and duration during RAPN with postoperative AKI. Materials and methods: We reviewed all patients who underwent RAPN at our institution since 2011. The ischemia types were warm ischemia (WI), selective artery clamping (SAC), and zero ischemia (ZI). AKI was defined according to the Risk Injury Failure Loss End-Stage (RIFLE) criteria. We calculated ischemia time thresholds for WI and SAC using the Youden and Liu indices. Logistic regression and decision curve analyses were assessed to examine the association with AKI. Results: Overall, 154 patients met the inclusion criteria. Among all RAPNs, 90 (58.4%), 43 (28.0%), and 21 (13.6%) were performed with WI, SAC, and ZI, respectively. Thirty-three (21.4%) patients experienced postoperative AKI. We extrapolated ischemia time thresholds of 17 min for WI and 29 min for SAC associated with the occurrence of postoperative AKI. Multivariable logistic regression analyses revealed that WIT ≤ 17 min (odds ratio [OR] 0.1, p p = 0.002), and ZI (OR 0.1, p = 0.035) significantly reduced the risk of postoperative AKI. Conclusions: Our results confirm the commonly accepted 20 min threshold for WI time, suggest less than 30 min ischemia time when using SAC, and support a ZI approach if safely performable to reduce the risk of postoperative AKI. Selecting an appropriate ischemia type for patients undergoing RAPN can improve short- and long-term functional kidney outcomes.

Background: the advent of Industry 4.0 (I4.0) innovations has revolutionized supply chain management through technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) integrated into procurement processes. Methods: this study addresses a critical knowledge gap by conducting a comprehensive review of 111 papers sourced from the Scopus database. These papers are classified into seven sub-themes encompassing I4.0 or procurement 4.0 (P4.0), big data, IoT, additive manufacturing, blockchain, e-procurement, and AI. Results: the investigation reveals that I4.0 technologies, particularly e-procurement and blockchain, have garnered substantial attention. Such technologies offer diverse value propositions, encompassing streamlined supplier evaluation, lead time reduction, cost optimization, and enhanced data security. Conclusion: the paper underscores pivotal trends and insights for the evolution of Procurement 4.0, illuminating a path toward more efficient supply chain management.

Transitioning from fossil to renewable energy is a global challenge, especially for countries with large fossil-fuel reserves and exports, such as Iran. This study analyses agricultural students’ knowledge of, attitudes toward, and perceptions of renewable energies in the agriculture sector in Guilan Province in Iran. The research was based on a structured questionnaire comprising three sections: (i) respondents’ socio-demographics; (ii) practicality and relevance of academic material and curriculum; and (iii) respondents’ knowledge of and attitudes and perceptions toward renewable energies in agriculture. The results showed that students’ attitudes regarding renewable energies ranked highest, and their perception was lowest. The results also showed a positive and significant relationship between the respondents’ knowledge, marital status, age, and level of education. Moreover, respondents’ age and educational level significantly impacted their attitudes. Cluster analysis divided students’ behavior into three different clusters. These clusters were most affected by attitude. In clustering students’ behavior towards using renewable energies, 38.5%, 33.5%, and 28% of respondents were positioned in the first, third, and second clusters, respectively. This is a pioneering study analyzing agricultural students’ behavior regarding renewable energies in agriculture in Guilan Province, Iran. The results of this study can assist agricultural organizations, politicians in the field of energy, and local authorities in promoting sustainable energy in Guilan Province.

The frequency of heat events is likely to increase due to global climate change, posing an increasing risk to wheat production. To optimize crop management strategies for coping with future climates, it is crucial to quantify the high-temperature occurrence during cropping seasons. Here, sixty-six years (1955~2020) of meteorological data during wheat reproductive growth were collected from six meteorological stations in the Huaibei Plain of Anhui Province. These data were analyzed to quantify the pattern and characteristics of post-anthesis heat stress for wheat crops. Five levels of annual mean daily maximum temperature (Tmax) were defined, from normal to extreme temperatures. Six crop developmental phases of winter wheat, i.e., phase i to phase vi, were divided from flowering to maturity. The data suggest an annual mean temperature of 17~24 °C from flowering to maturity, with an annual effective cumulative temperature ranging from 725 °C d to 956 °C d. The mean temperature and effective cumulative temperature increased as crop growth progressed, along with more frequent heat events during phase ii (8~14 days after anthesis) and phase iii (15~21 days after anthesis). We also found that the frequency of extremely high temperatures (≥33 °C) from 1990 to 2020 was significantly greater than that from 1957 to 1990. Interestingly, it was found that the intensity of post-anthesis night temperatures also increased with crop growth, i.e., from phase i to phase vi. Wheat grain yield increased with increasing effective accumulative temperature and Tmax, but it started to decline when thresholds of effective accumulative temperature and Tmax were reached. Overall, these findings could provide guidelines for winter wheat cropping in the Huaibei Plain, China, or similar climate and cropping regions. This study was funded by the National Key Research and Development Program of China (2017YFD0300204-3).

The agricultural sector is crucial to attaining the Sustainable Development Goals (SDGs) since it ensures food security, protects natural resources, and promotes rural livelihoods. However, the success of sustainable agricultural practices depends not only on effective policies and technologies but also on agricultural experts’ perceptions and attitudes, as well as their willingness to embrace sustainable practices. Therefore, this study aims to: (i) investigate the perceptions and attitudes of agricultural experts in Guilan Province (Iran) towards the SDGs, and (ii) determine their educational needs regarding the SDGs and identify specific areas requiring more attention and targeted interventions. This research adopts a quantitative approach and relies on a survey with a random sample of 152 agricultural experts. The collected data were analyzed using SPSS 26 software and descriptive and inferential statistics. Agricultural experts perceived most SDGs as having high educational needs. Priority SDGs for education and training included SDG 14 (Life below water), whereas areas requiring increased knowledge among the employees relate, inter alia, to SDGs 1 (No poverty) and 2 (Zero hunger). The study contributes to the effective implementation of the SDGs by encouraging a more sustainable and resilient agricultural sector connected with broader goals of sustainable development.