Population and development:impacts on environmental performance

Population growth and development patterns have a significant impact on the environmental performance.The issue of concern is whether population growth or the consumption/production patterns are responsible for environmental deterioration.This paper is an attempt to capture the impact of technological development,affluence,and population on environmental performance index,while previous stuthes had captured the impact of these three factors on environment only through CO_2emissions.The analysis reveals that technological development and population size have a negative impact on environmental performance,whereas measures to improve affluence have a positive impact.Technological development has increased the production of energy efficient products but at the same time consumption of these products has increased manifold leading to environmental deterioration.Demographic attributes need specific attention to improve environmental performance.This paper concludes on some policy reflections on slowing the population growth as well as persuades individuals and economies to relook to their consumption and production patterns and channelize their efforts to protect the environment.

Adoption of green finance and green innovation for achieving circularity:An exploratory review and future directions

There is growing attention from governments and regulators towards crucial matters such as climate change and global warming,resulting in a pressing need to investigate the factors that make it possible for businesses to engage in green finance(GF).The externality of environmental pollution prioritizes the need of green innovation(GI)in public management.GF distributes financial resources to the research and development(R&D)of clean energy and environmentally friendly goods and processes;it is complementary to the GI process for environmental protection.GF policies help to alleviate the impacts of financial constraints and GI impaired industries involving new products,processes,services and the global market.To better understand how GF and GI have functioned as a catalyst for circular economy practices,this paper seeks to present a historical and contemporary overview of these concepts.The research is thoroughly dissected by a systematic literature evaluation of articles from 2016 to 2023 that appear in peer-reviewed journals and are indexed in the SCOPUS database.To attain supply chain circularity,this article encompasses four major research themes concerning the adoption of GF and green technologies.The research also includes a network analysis of shortlisted articles to examine the overall citation trends.It is shown that several institutional theories are associated with the investigated area.As a final step,a framework is provided to illustrate how GF and GIs might be used to achieve supply chain circularity.The research findings provide a novel concept related to GF within the context of GI which are significant for environmentalists,policymakers,green investors,and researchers.Through its findings,the study provides a conceptual framework that promotes sustainable strategies to effectively balance financial considerations and environmental innovation.It helps to leverage the potential of green research and practice to create value for businesses and to benefit society at large.The analysis provides an unexplored and significant contribution to current literature in terms of delivering evidence of the past and present approaches to GF and GI in a circular economy.The results of this study will attract the attention of policymakers and stakeholders to develop and combine the two concepts in research and practice to attain environmental balance in the circular economy and to promote long term sustainability.

Diagnosis and Detection of Alzheimer’s Disease Using Learning Algorithm

In Computer-Aided Detection(CAD)brain disease classification is a vital issue.Alzheimer’s Disease(AD)and brain tumors are the primary reasons of death.The studies of these diseases are carried out by Magnetic Resonance Imaging(MRI),Positron Emission Tomography(PET),and Computed Tomography(CT)scans which require expertise to understand the modality.The disease is the most prevalent in the elderly and can be fatal in its later stages.The result can be determined by calculating the mini-mental state exam score,following which the MRI scan of the brain is successful.Apart from that,various classification algorithms,such as machine learning and deep learning,are useful for diagnosing MRI scans.However,they do have some limitations in terms of accuracy.This paper proposes some insightful pre-processing methods that significantly improve the classification performance of these MRI images.Additionally,it reduced the time it took to train the model of various pre-existing learning algorithms.A dataset was obtained from Alzheimer’s Disease Neurological Initiative(ADNI)and converted from a 4D format to a 2D format.Selective clipping,grayscale image conversion,and histogram equalization techniques were used to pre-process the images.After pre-processing,we proposed three learning algorithms for AD classification,that is random forest,XGBoost,and Convolution Neural Networks(CNN).Results are computed on dataset and show that it outperformed with exiting work in terms of accuracy is 97.57%and sensitivity is 97.60%.

试论巴以跨文化冲突:跨文化的视角(英文)

虽然文化威力巨大,但往往让人觉察不到,文化可能不知不觉中造成了冲突,影响冲突的解决。每场冲突之中都有文化的影子,因为冲突来自人类的关系,人类命名、想象、责怪、处理冲突的方式都受文化的影响。没有一种万能的解决冲突的方法,因为文化始终是一个因素。文化上的流畅度对于介入冲突的人来说是一种核心竞争力。承认并考虑到文化流畅度对冲突的影响可以帮助人们作出更有目标的、有适应性的决定。本文是对巴以冲突的分析性评估,认为民主并不能解决所有问题,可信度和信任同样重要。建立信任本身就是一个问题。最后,本文建议用建立信任的方式促进和平。