Traditional uses of medicinal plants to prevent and treat diabetes; an updated review of ethnobotanical studies in Iran

Background: Obesity and physical inactivity are currently on the rise due to industrialization of the communities, which has recently led to increased incidence of different diseases such as diabetes. Epidemiological studies and figures have demonstrated the growing incidence of diabetes. Relevantly, the side effects of chemical drugs have led patients to use medicinal plants and traditional approaches despite advances in development of chemical drugs. The aim of this review article is to report the medicinal plants and their traditional uses to prevent and treat diabetes according to the findings of ethnobotanical studies conducted in different regions of Iran. Evidence Acquisitions: The search terms including ethnobotany, ethnomedicine, ethnopharmacology, phytopharmacology, phytomedicine, Iran, and traditional medicine in combination with diabetes, blood sugar and hyperglycemic were searched from scientific databases. Results: The results of this article can be a comprehensive guideline, based on ethnobotany of different regions of Iran, to prevent and treat diabetes. According to this review article, certain plant species such as Urtica dioica L., popularly called nettle, in eight regions, Teucrium polium L., popularly called poleigamander, in five regions, and Trigonella foenum-graecum L., Citrullus colocynthis (L.), Schrad., and Juglans regia L. in four regions, were reported to be frequently used to prevent and treat diabetes Conclusions: The introduced medicinal plants in this review can be investigated in further research and produce new drugs with limited side effects

Effects of clinical education and evaluation with portfolio method on nursing students' satisfaction: a clinical trial

زمینه و هدف: لزوم بازنگری در روش های فعلی آموزش در پرستاری و استفاده از روش های آموزش و ارزشیابی نوین در سال های اخیر مورد توجه جدی قرار گرفته است؛ لذا این مطالعه با هدف مقایسه رضایتمندی دانشجویان پرستاری از به کارگیری روش آموزش و ارزشیابی بالینی پورت فولیو و روش روتین صورت گرفت. روش بررسی: در این پژوهش کارآزمایی بالینی، کلیه دانشجویان ترم 6 کارشناسی پرستاری دانشکده پرستاری و مامایی دانشگاه جندی شاپور اهواز (37 دانشجو)که طبق برنامه ریزی دانشکده به 4 گروه تقسیم شده بودند، جهت گذراندن کارآموزی به روش پورت فولیو و روتین انتخاب شدند. روش کار بدین صورت بود که در یک واحد کارآموزی به صورت روتین و واحد کارآموزی بعدی به شیوه پورت فولیو آموزش داده و ارزشیابی شدند. رضایت دانشجویان از دو شیوه آموزشی با استفاده از پرسشنامه محقق ساخته رضایت سنجی مقایسه گردید. یافته ها: در موارد مشابه بودن موضوعات موجود در روش آموزش و فرم ارزشیابی با تجربیات بالینی مواجه شده، ایجاد علاقه و انگیزه برای مشارکت دانشجو در یادگیری، ایجاد انگیزه برای استفاده از کتاب ها و سایر منابع علمی، کمک به یافتن موارد نقص و جبران آن طی کارآموزی، همسو بودن موضوعات موجود در روش ارزشیابی به شیوه پورت فولیو با اهداف آموزشی و میزان یادگیری در روش پورت فولیو میزان رضایتمندی دانشجویان بیشتر و معنی دار بود (01/0>P). همچنین متوسط نمره کل رضایت مندی دانشجویان از روش پورت فولیو (25/2±83/29) بیشتر از روش متداول (06/3±89/27) بود (01/0>P). نتیجه گیری: رضایت بیشتر دانشجویان در برخی زمینه ها از شیوه آموزش پورت فولیو، مؤید مزایای استفاده از این روش آموزشی جدید می باشد و می توان آن را به عنوان یک روش تلفیقی از آموزش و ارزشیابی دانشجو محور به کار برد

Effects of supply chain transparency, alignment, adaptability, and agility on blockchain adoption in supply chain among SMEs

This study aims to investigate the extent to which the contributions of blockchain technology to supply chain parameters influence blockchain adoption among SMEs. Drawing on contingency theory, the study investigates the moderating effect of market turbulence. The data were collected from 204 SMEs in Malaysia\u27s manufacturing sector and analysed using the partial least squares technique. The results showed that the intention of SMEs’ managers to adopt blockchain is influenced by the contributions of blockchain to supply chain transparency and agility. Supply chain transparency, alignment, adaptability, and agility are interrelated. Market turbulence moderates positively the association between agility and intention to adopt blockchain. This study extends the literature by decomposing the concept of relative advantages and investigating the influences of blockchain benefits on blockchain adoption. The moderating effect of market turbulence indicates that the influence of blockchain on agility is more important for SMEs operating in a turbulent environment than the SMEs in a stable market. The findings help the policymakers and blockchain vendors in developing effective plans and strategies to speed up the adoption of blockchain among SMEs. Furthermore, the results give confidence to the managers and owners of SMEs that blockchain can be a valuable competitive advantage source

An integrated model for information adoption & trust in mobile social commerce

Despite the growing importance of mobile social commerce (ms-commerce), little research has been conducted on the effects of informational and social factors on users’ post-adoption behavior. We, therefore, build on the understanding of mobile social commerce in the UK market and how it affects users’ post-adoption behaviors. Our theoretical model leverages the information adoption model, social support theory, and social influence theory. Data was gathered from 377 ms-commerce users from the UK and analyzed via Partial Least Squares (PLS-SEM). The research findings show that both informational and social factors have a positive impact on information adoption in ms-commerce apps. Furthermore, information adoption has a positive impact on trust, which leads to ms-commerce purchase intention, ms-commerce continuance intention, and willingness to share an ms-commerce experience

Understanding institutional repository in higher learning institutions: a systematic literature review and directions for future research

Institutional repositories (IRs) have received considerable attention from researchers across disciplines and around the globe. They have potentially increased the public value, ranking, prestige and visibility of researchers and relevant universities. However, despite the important and rapid growth of research in this area, few efforts have been made to systematically review and integrate the findings from previous research studies or to examine the current state of study regarding IRs. The primary goal of this paper is to provide a better understanding and an in-depth review of the current state of study regarding IRs. This research uses systematic literature review (SLR) and followed a protocol to properly organize the work related to institutional repositories. The data were collected from primary studies published from 2007 to 2018 from the six major databases (ScienceDirect, IEEE Explorer, Springer, ACM, Taylor and Francis and Emerald insight). Several papers regarding IRs were reviewed, applying inclusion and exclusion criteria, and a total of 115 studies were included as the main part of this research. The results obtained from these studies indicated that the absence of knowledge of open access IRs among scholars and institutions, and inadequate information and communication technology infrastructure were significant challenges behind the development of open access IRs. Meanwhile, enhanced visibility of the academic institution, increased local and global rankings, increased prestige and public value, and improved teaching, learning and research development by the scholars of the institution were found to be the main benefits of institutional repositories. This study also highlighted that most of the studies in this research area were focused on the "deployment, implementation and adoption" and "benefits and challenges" of institutional repositories. The outcomes of this study can assist future researchers by providing a roadmap of institutional repositories and highlighting guidelines for successful implementation of IRs in higher learning institutions

Neuromarketing: a review of research and implications for marketing

In this research, we reviewed existing studies which used neuromarketing techniques in various fields of research. The results revealed that most attempts in neuromarketing have been made for business research. This research provides important results on the use of neuromarketing techniques, their limitations and implications for marketing research. We hope that this research will provide useful information about the neuromarketing techniques, their applications and help the researchers in conducting the research on neuromarketing with insight into the state-of-the-art of development methods

Determinants of Intention to Use Simulation-Based Learning in Computers and Networking Courses: An ISM and MICMAC Analysis

Simulation-based learning (SBL) presents a wide variety of opportunities to practice complex computer and networking skills in higher education, employing various platforms to enhance educational outcomes. The integration of SBL tools in teaching computer networking courses is useful for both instructors and learners. Furthermore, the increasing importance of SBL in higher education highlights the necessity to further explore the factors that affect the adoption of SBL technologies, particularly in the field of computer networking courses. Despite these advantages, minimal effort has been made to examine the factors that impact instructors’ intentions to use SBL tools for computers and networking courses. The main objective of this study is to examine the factors that affect instructors' intentions to utilize SBL tools in computer networking courses offered by higher education institutions. By employing Interpretive structural modeling (ISM) and Matriced’ Impacts Croise’s Multiplication Appliquee a UN Classement (MICMAC) analysis, the research attempts to provide an in-depth understanding of the interdependencies and hierarchical associations among twelve identified factors. Results showed that system quality, self-efficacy, technological knowledge, and information quality have high driving power. This study offers valuable perspectives for higher education institutions and for upcoming empirical studies and aids in comprehending the advantages of using SBL tools in teaching and higher education

Industry 5.0 implications for inclusive sustainable manufacturing: an evidence-knowledge-based strategic roadmap

Despite the hype surrounding Industry 5.0 and its importance for sustainability, the micro-mechanisms through which this agenda can lead to socio-environmental values are largely understudied. The present study strived to address this knowledge gap by developing a strategic roadmap that outlines how Industry 5.0 can boost sustainable manufacturing. The study first conducted a content-centric literature review and identified 12 functions through which Industry 5.0 can inclusively boost sustainable manufacturing. The study further developed a strategic roadmap that identified the complex contextual relationships among the functions and explained how they should be synergistically leveraged to maximize their contribution to sustainability. Results reveal that value network integration, sustainable technology governance, sustainable business model innovation, and sustainable skill development are the most driver and tangible implications of Industry 5.0 for sustainable manufacturing. Alternatively, renewable integration and manufacturing resilience are among the most dependent and hard-to-reach sustainable functions of Industry 5.0, and their materialization requires major strategic collaboration among stakeholders. The strategic roadmap outlines how Industry 5.0 stakeholders can leverage the technological and functional constituents of this agenda to promote sustainable manufacturing inclusively

Investigating factors influencing decision-makers’ intention to adopt green IT in Malaysian manufacturing industry

Green IT has attracted policy makers and IT managers within organizations to use IT resources in cost-effective and energy-efficient ways. Investigating the factors that influence decision-makers’ intention towards the adoption of Green IT is important in the development of strategies that promote the organizations to use Green IT. Therefore, the objective of this study stands to understand potential factors that drive decisions makers in Malaysian manufacturing sector to adopt Green IT. This research accordingly developed a model by integrating two theoretical models, Theory of Planned Behavior and Norm Activation Theory, to explore individual factors that influence decision’ makers in manufacturing sector in Malaysia to adopt Green IT via the mediation of personal norms. Accordingly, to determine predictive factors that influence managerial intention toward Green IT adoption, the researchers conducted a comprehensive literature review. The data was collected from 183 decision-makers from Malaysian manufacturing sector and analyzed by Structural Equation Modelling. This research provides important preliminary insights in understanding the most significant factors that determined managerial intention towards Green IT adoption. The model of Green IT adoption explained factors which encourages individual decision-makers in the Malaysian organizations to adopt Green IT initiatives for environment sustainability

Sustainability Performance Assessment Using Self-Organizing Maps (SOM) and Classification and Ensembles of Regression Trees (CART)

This study aims to develop a new approach based on machine learning techniques to assess sustainability performance. Two main dimensions of sustainability, ecological sustainability, and human sustainability, were considered in this study. A set of sustainability indicators was used, and the research method in this study was developed using cluster analysis and prediction learning techniques. A Self-Organizing Map (SOM) was applied for data clustering, while Classification and Regression Trees (CART) were applied to assess sustainability performance. The proposed method was evaluated through Sustainability Assessment by Fuzzy Evaluation (SAFE) dataset, which comprises various indicators of sustainability performance in 128 countries. Eight clusters from the data were found through the SOM clustering technique. A prediction model was found in each cluster through the CART technique. In addition, an ensemble of CART was constructed in each cluster of SOM to increase the prediction accuracy of CART. All prediction models were assessed through the adjusted coefficient of determination approach. The results demonstrated that the prediction accuracy values were high in all CART models. The results indicated that the method developed by ensembles of CART and clustering provide higher prediction accuracy than individual CART models. The main advantage of integrating the proposed method is its ability to automate decision rules from big data for prediction models. The method proposed in this study could be implemented as an effective tool for sustainability performance assessment