The Potential Role of Nitric Oxide in Halting Cancer Progression Through Chemoprevention

Nitric oxide (NO) in general plays a beneficial physiological role as a vasorelaxant and the role of NO is decided by its concentration present in physiological environments. NO either facilitates cancer-promoting characters or act as an anti-cancer agent. The dilemma in this regard still remains unanswered. This review summarizes the recent information on NO and its role in carcinogenesis and tumor progression, as well as dietary chemopreventive agents which have NO-modulating properties with safe cytotoxic profile. Understanding the molecular mechanisms and cross-talk modulating NO effect by these chemopreventive agents can allow us to develop better therapeutic strategies for cancer treatment

Comparison of effectiveness of various treatment strategies in COVID-19 patients: A Systematic Review

Background: The purpose of this study is to systematically review the effectiveness of various drugs and therapies by assessing already conducted studies on COVID-19 patients. Methods: The eligibility criterion for this systematic review was to include the observational and experimental studies including case reports; conducted on the possible treatments of COVID-19. Only those studies were included that were written in the English language either published or unpublished from December 2019 to April 10, 2020. Quality of articles was assessed and flawed studies were excluded based on incomplete outcome data. Treatment strategies experimented on animals or those assessed through artificial intelligence were also excluded. The databases searched were PubMed, Google Scholar, Cochrane Library, and bioRxiv. The last date to search the databases was April 10, 2020. Results: We selected 25 articles which include 12 case studies, 10 retrospective studies, one randomized controlled trial, one non-randomized Controlled trial, and one prospective observational study. Hydroxychloroquine proved to be effective in all three studies under consideration especially when it was used in a combination with azithromycin. Antivirals showed significant results in eleven out of sixteen studies. The remaining five studies showed antiviral therapy to be ineffective. Lopinavir/ritonavir did not show satisfactory results in most of the COVID-19 patients. Both of the studies regarding convalescent plasma therapy showed significant improvement in patients undergoing treatment. Two studies regarding treatment with immunoglobulins also showed good results. A study on the use of Mesenchymal stem cell transplant for treatment of COVID-19 patients also proved to be effective. Likewise, a study on the use of Traditional Chinese Medicine along with Western Medicine also showed good results. In patients of organ transplant, withdrawal of immunosuppressive drugs, and the use of methylprednisolone along with antivirals had shown significantly good results. Among all these therapeutic approaches we found convalescent plasma therapy to be most effective. Conclusion: So far, a small number of studies have been conducted on the treatment of COVID-19 patients and most of them were conducted on the Chinese population. More randomized controlled trials are needed to evaluate the effectiveness of different treatment strategies at a broader level

Federating cloud systems for collaborative construction and engineering

The construction industry has undergone a transformation in the use of data to drive its processes and outcomes, especially with the use of Building Information Modelling (BIM). In particular, project collaboration in the construction industry can involve multiple stakeholders (architects, engineers, consultants) that exchange data at different project stages. Therefore, the use of Cloud computing in construction projects has continued to increase, primarily due to the ease of access, availability and scalability in data storage and analysis available through such platforms. Federation of cloud systems can provide greater flexibility in choosing a Cloud provider, enabling different members of the construction project to select a provider based on their cost to benefit requirements. When multiple construction disciplines collaborate online, the risk associated with project failure increases as the capability of a provider to deliver on the project cannot be assessed apriori. In such uncontrolled industrial environments, “trust” can be an efficacious mechanism for more informed decision making adaptive to the evolving nature of such multi-organisation dynamic collaborations in construction. This paper presents a trust based Cooperation Value Estimation (CoVE) approach to enable and sustain collaboration among disciplines in construction projects mainly focusing on data privacy, security and performance. The proposed approach is demonstrated with data and processes from a real highway bridge construction project describing the entire selection process of a cloud provider. The selection process uses the audit and assessment process of the Cloud Security Alliance (CSA) and real world performance data from the construction industry workloads. Other application domains can also make use of this proposed approach by adapting it to their respective specifications. Experimental evaluation has shown that the proposed approach ensures on-time completion of projects and enhanced..

Qualitative Research in Applied Linguistics: A Practical Introduction, edited by Juanita Heigham and Robert Croker

This review makes a point in favor of the assertion made for the book that it is a practical introduction to the qualitative research in applied linguistics. The book consists of four parts: an overview of qualitative research, qualitative research methods, qualitative data collection methods, ethical practice issues and the writing of research reports. After proving a rich introduction to the qualitative research, the book discusses qualitative research approaches using a reader-friendly and interactive structure: pre-reading and post-reading questions along with the list of further readings. Then the data collection tools have been thoroughly discussed. What makes this book more useful is the use of illustrative examples for each qualitative research approach and data collection tool. The last part discusses core issues of ethics and drafting a research report. From the perspective of a novice researcher, it has achieved the goal of educating readers about qualitative research methods and data collection tools, as it gradually tracks the reader and provides them with a linking concept for a better understanding. However, reference to one study for both ethnography and case study remains a confusing point. Besides, the review suggests addition of some images to make reading of the book more interesting, especially for visual learners. Besides, a diagram should be given at the end of research methods chapters to outline the steps taken by researchers to do their studies

Customer churn prediction using composite deep learning technique

Customer churn, a phenomenon that causes large financial losses when customers leave a business, makes it difficult for modern organizations to retain customers. When dissatisfied customers find their present company\u27s services inadequate, they frequently migrate to another service provider. Machine learning and deep learning (ML/DL) approaches have already been used to successfully identify customer churn. In some circumstances, however, ML/DL-based algorithms lacks in delivering promising results for detecting client churn. Previous research on estimating customer churn revealed unexpected forecasts when utilizing machine learning classifiers and traditional feature encoding methodologies. Deep neural networks were also used in these efforts to extract features without taking into account the sequence information. In view of these issues, the current study provides an effective method for predicting customer churn based on a hybrid deep learning model termed BiLSTM-CNN. The goal is to effectively estimate customer churn using benchmark data and increase the churn prediction process\u27s accuracy. The experimental results show that when trained, tested, and validated on the benchmark dataset, the proposed BiLSTM-CNN model attained a remarkable accuracy of 81%

Sustainable supply chain management performance in post COVID-19 era in an emerging economy: a big data perspective

Purpose Big data analytics capabilities are the driving force and deemed as an operational excellence approach to improving the green supply chain performance in the post COVID-19 situation. Motivated by the COVID-19 epidemic and the problems it poses to the supply chain's long-term viability, this study used dynamic capabilities theory as a foundation to assess the imperative role of big data analytics capabilities (management, talent and technological) toward green supply chain performance. Design/methodology/approach This study was quantitative and cross-sectional. Data were collected from 374 executives through a survey questionnaire method by applying an appropriate random sampling technique. The authors employed PLS-SEM to analyze the data. Findings The findings revealed that big data analytics capabilities play a significant role in boosting up sustainable supply chain performance. It was found that big data analytics capabilities significantly contributed to supply chain risk management and innovative green product development that ultimately enhanced innovation and learning performance. Moreover, innovation and green learning performance has a significant and positive relationship with sustainable supply chain performance. In the post COVID-19 situation, organizations can enhance their sustainable supply chain performance by giving extra attention to big data analytics capabilities and supply chain risk and innovativeness. Originality/value The paper specifically emphasizes on the factors that result in the sustainability in supply chain integrated with the big data analytics. Additionally, it offers the boundary condition for gaining the sustainable supply chain management.Post-print / Final draf

Physico-Chemical Assessment of Drinking Water Available to the Inhabitants of Low Income and Thickly Populated Areas of Karachi City

The aim of this study was to investigate the physico-chemical properties of drinking water available to the population of low income areas of Karachi city. The study incorporated the attention towards the fluoride content in water being used for domestic and drinking purpose by the inhabitants of low income and thickly populated areas of Karachi. Samples were collected from selected locations from all the districts of Karachi city. Laboratory tests were performed to analyze both physical and chemical characteristics of drinking water. It was observed in this study that except few of the locations, fluoride content was present either in low concentration or in high concentration. Medical data of the areas under study was collected through questionnaires and survey forms. The consequence of the variation of fluoride concentration was found to be in agreement with the findings of medical data analyzed from concerned areas where both cases of Fluorosis and dental cavities were reported. Correlation of fluoride with other parameters was analyzed using principle component analysis determined PC1 & PC2 as most significant components. PC1 showed dominance of TDS with salts while PC2 indicated loadings were temperature DO & pH. Monitoring of fluoride ion concentration and other health related parameters are essential for the development of efficient water management system. Fluoride content in drinking water should be regulated by periodic assessment and elevated levels can be controlled by adsorption or membrane techniques. Keywords: Physico-chemical properties, drinking water, districts of Karachi, fluoride variation, correlation analysis, principle component analysis, water management system. DOI: 10.7176/JNSR/11-14-01 Publication date:July 31st 202