Notes

The way to effectively promote interprofessional venture? * a qualitative study on physicians' and also pharmacists' perspectives influenced by the concept of prepared habits.
One in every of the key finding of this analysis is that there's a weak tail asymmetry, however some tail dependence, that COPAR-model with efficiency absorbs to account. Furthermore, the fashions monitor lagged reactions of interest rate and industrial production on adjustments in fuel prices inside Pakistan. The oil price result on the inflation rate; on the other hand, is quite rapid.The Covid-19 pandemic has shocked the global energy system. It has resulted in tremendous uncertainty and diminished the recent advances to increase access to affordable, reliable, sustainable and modern energy-an objective preserved in the UN Sustainable Development Goal 7 (SDG-7). According to the IEA, attaining universal electricity access in Africa in line with SDG-7 entails annual investments of approximately $20 billion over the next decade. Given the sizeable magnitudes involved, it is inevitable that energy projects will need to rely on richer nations for energy aid. This paper explores the linkages between energy-related external aid, carbon emissions, per capita GDP, and electricity access for a sample of 30 low-income SSA countries over 1995 to 2016. Our econometric analysis reveals that while all types of energy aid facilitate economic growth in the long run, there is no direct impact of energy-related aid on electricity access. However, an increase in per capita GDP is positively associated with electricity access in both rural and urban areas. We also find that energy-related aid helps mitigate carbon emissions as well as contribute to GDP. Taken together, our results suggest that enhanced energy-related aid to low-income SSA countries can directly facilitate climate compatible growth and indirectly impel improvements in electricity access thereby helping with poverty reduction. We also advocate regional cooperation among SSA countries as a collective effort to confront shared energy challenges.This contribution offers the author's personal experience with a project that took place 25 years ago in Latin America. This was about Second Order Auditing in Colombia during the second part of the 1990s. This project was carried out at the Country's National Auditing Office (CGR), and was an application of the Viable System Model (VSM) and the Viplan Methodology to a National Context. It was an innovative project at the CGR, focused on Second Order Auditing, to improve communications within the fabric of the Colombian government. Its emphasis was building responsible trust between public enterprises, ministries and political agencies. Its emphasis was building communications between ministries and public entities, with the aim of increasing their effectiveness. At its core were methodological and epistemological developments. Key questions it attempted to answer were how to model the complexity of the enterprises and how to transform the auditors' views of their relations with people in public entities, from one focused on requesting information, to one focused on communications. Structural changes were proposed for the National Audit Office and state enterprises, and hundreds of auditors were trained, through epistemological methodological workshops, in second order auditing and the reports of their auditing were debated extensively in government and beyond. This paper finishes with a short discussion of these transformations in the light of organisational cybernetics and in particular of the Viable System Model.With the development of the Internet, information on the stock market has gradually become transparent, and stock information is easy to obtain. For investors, investment performance depends on the amount of capital and effective trading strategies. The analysis tool commonly used by investors and securities analysts is technical analysis (TA). Technical analysis is the study of past and current financial market information, and a large amount of statistical data is used to predict price trends and determine trading strategies. Technical indicators (TIs) are a type of technical analysis that summarizes possible future trends of stock prices based on historical statistical data to assist investors in making decisions. The stock price trend is a typical time series data with special characteristics such as trend, seasonality, and periodicity. In recent years, time series deep neural networks (DNNs) have demonstrated their powerful performance in machine translation, speech processing, and natural language proceries deep neural network has significant effects in stock price prediction and return on investment.There has been a resurgence between two closely related discussions concerning modern science funding policy. The first revolves around the coherence and usefulness of the distinction between basic and applied science and the second concerns whether science should be free to pursue research according to its own internal standards or pursue socially responsible research agendas that are held accountable to moral or political standards. In this paper, I argue that the distinction between basic and applied science, and the concomitant debate about freedom and social responsibility, require revision. I contend that the distinction can only be maintained in cases of urgent science. I go on to elucidate the notion of urgent science using a case study from research of the climate refugee crisis.Clustering analysis is essential for obtaining valuable information from a predetermined dataset. However, traditional clustering methods suffer from falling into local optima and an overdependence on the quality of the initial solution. Given these defects, a novel clustering method called gradient-based elephant herding optimization for cluster analysis (GBEHO) is proposed. A well-defined set of heuristics is introduced to select the initial centroids instead of selecting random initial points. Specifically, the elephant optimization algorithm (EHO) is combined with the gradient-based algorithm GBO for assigning initial cluster centers across the search space. Second, to overcome the imbalance between the original EHO exploration and exploitation, the initialized population is improved by introducing Gaussian chaos mapping. In addition, two operators, i.e., random wandering and variation operators, are set to adjust the location update strategy of the agents. Nine datasets from synthetic and real-world datasets are adopted to evaluate the effectiveness of the proposed algorithm and the other metaheuristic algorithms. The results show that the proposed algorithm ranks first among the 10 algorithms. It is also extensively compared with state-of-the-art techniques, and four evaluation criteria of accuracy rate, specificity, detection rate, and F-measure are used. The obtained results clearly indicate the excellent performance of GBEHO, while the stability is also more prominent.U.S. history is fraught with examples of systemic racism-at all ecological levels and within all geopolitical contexts. Whether scholars historically punctuate these phenomena through white racial framing begun in the 1600s or the Black civil rights movement of the 1960s, research across disciplines brings into focus a twenty-generation story of injustice. These phenomena present a paradoxical struggle within healthcare systems populated by professionals who have made a "conscious commitment to equity and helping those in need." However, both healthcare systems and embedded care providers operate in relation to organizational structures that frequently reify racist policies. As natural and professional agents of change, medical family therapists are especially positioned to examine how regulatory systems at every level influence institutional racism within the medical and mental health fields. In this manuscript we examine health system policies and practices using the lens of C.J. Peek's Four Worlds Clinical, Operational, Financial, and Training. Examples of institutional racism are discussed and recommendations for approaches to change are provided.This paper offers a critical analysis of program evaluation in contemporary urban agriculture. Drawing on data from an exploratory study designed at the request of and in collaboration with urban agriculture practitioners in Massachusetts, it describes both their critiques of extant practices of program evaluation and their visions for alternative ways of telling the story of their work. Related, it explores practitioners' interest in building capacity for policy advocacy, working collectively to create transformative social change, and, related, establishing new kinds of relationships with state and philanthropic funders. Building on scholarship that has observed that urban agriculture is characterized by an internal contradiction-i.e., its simultaneous orientation to "neoliberal" (social service) and "radical" (social justice) agendas (McClintock in Local Environ 19147-171, 2014)-this analysis calls attention, especially, to the complex role of metrics, which may not only entrench neoliberalism in UA organizations, but also provide a mechanism for challenging its assumptions and advancing the radical project of food justice.COVID 19 has exacerbated and underscored structural inequalities and endemic vulnerabilities in food, economic, and social systems, compounding concerns about environmental sustainability and racial and economic justice. selleck Convergent crises have amplified a growing chorus of voices and movements calling for new thinking and new practices to adapt to these shifts, mitigate their impact, and address their root causes through far reaching changes in social and economic life and values, including breaking with the free market paradigm. In the face of a historic choice between transition or multiple systems collapse that deepen injustice and threaten planetary survival, I make the case for expanding on liberatory tendencies in Extension programs to build capacities for response-ability to transition toward more just and sustainable futures.While the agricultural knowledges and practices of Black, Indigenous, and People of Color (BIPOC) and women have shaped agriculture in the US, these knowledges have been colonized, exploited, and appropriated, cleaving space for the presently dominant white male agricultural narrative. Simultaneously, these knowledges and practices have been transformed to fit within a society that values individualism, production, efficiency, and profit. The authors use a decolonial Feminist Political Ecology framework to highlight the ways in which the knowledges of Indigenous, Black, and women farmers have been and are being colonized; a tradition that makes alternative agriculture a predominantly white space. The authors interviewed 10 BIPOC and women farmers in Colorado to understand what values and knowledges were shaping their often-appropriated agricultural practices. Three themes emerged people, place, and patterns. By centering these values, farmers create relational agricultural practices that support the well-being of human and more-than-human beings. To support the widespread implementation of these practices, food systems practitioners must elevate the voices and knowledges of historically excluded farmers. Only then can truly just and equitable alternative agricultural practices be realized in the US.
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