Multivariate Analysis of Pelagic Fishes in the South China Sea Area

Pelagic fishes are important fisheries resources in the South China Sea Area. The aim of the study is to determine the dynamics and status of pelagic fishes and develop the fishery management efforts for sustainable development in the region Three analytical methods, correlation analysis, principal component analysis and cluster -:analysis were used for this purpose. In this study, 19 species groups were considered and annual catch data were collected from SEAFDEC Fishery Statistical Bul1etins from 1976 to 1996. For estimation of MSY (Maximum Sustainable Yield) in the East Coast of Peninsular Malaysia, Schaefer's Surplus Production Model was used based on catch and effort data. In the case study of estimation of MSY, the estimated MSY was 94,321 mt and fMSY was 74,011 (days/year) by fishing gear standardization. This study estimated MSY-like value of the whole South China Sea provisionally based on studies done in the East Coast of Peninsular Malaysia. The correlation analysis showed the relationship among 21 sub-areas on the basis of catch composition per year .The study indicated that Taiwan, Hong Kong and Singapore did not show significant relationship with other sub-areas. However, West Sumatra, South Java etc showed significant relationship with other sub-areas. The principal component analysis showed alternation of the major species groups in different sub-areas. The analysis indicated that alternation of major catches .. were observed at two or four years interval while some species groups were found to be stable over the periods in different sub-areas. Alternation of pelagics by sub-area and by species are very important information as the baseline data for multicountry's fisheries management. The cluster analysis was used for grouping of sub-areas on annual basis and overall basis. The results of overall basis are summarized in the following two types of grouping. The first type of grouping is as follows: (1) Taiwan, Indonesian part of Malacca Straits, West Coast of Peninsular Malaysia, East Sumatra and Kalimantan; (2) Luzon, Visayas, Mindanao, Sulewesi & Gulf of Thailand; (3) Hong Kong, West Sumatra, North java, South Java, Bali-Nusa Tenggara, Maluku-Irian Jaya, East Coast of Peninsular Malaysia, Sarawak, Sabah, Indian Ocean and Singapore. The second grouping is that, all sub-areas were grouped into six clusters: (1) Taiwan;(2) Gulf of Thailand; (3) East Coast of Peninsular Malaysia & North Java; (4) Indonesian part of Malacca Straits, West Coast of Peninsular Malaysia; East Sumatra & Kalimantan; (5) Luzon, Visayas, Mindanao & Sulawesi and (6) Hong Kong, West Sumatra, South Java, Bali-Nusa Tenggara, Maluku-Irian Jaya, Sarawak, Sabah, Indian Ocean & Singapore. On the pelagic resources or shared stocks, this study emphasized the importance of multi-country's fisheries management and that detailed information is required to achieve the objectives. This study identified the fisheries relationships among the sub-areas, and also clarified the alternation of pelagics in the South China Sea area, based on the multivariate analyses. The important baseline information obtained from the study can be utilised for multi country's pelagic fisheries management in the South China Sea area

Horus: A Security Assessment Framework for Android Crypto Wallets

Crypto wallet apps help cryptocurrency users to create, store, and manage keys, sign transactions, and keep track of funds. However, if these apps are not adequately protected, attackers can exploit security vulnerabilities in them to steal the private keys and gain ownership of the users’ wallets. We develop a semi-automated security assessment framework, Horus, specifically designed to analyze crypto wallet Android apps. We perform semi-automated analysis on 311 crypto wallet apps and manually inspect the top 18 most popular wallet apps from the Google Play Store. Our analysis includes capturing runtime behavior, reverse-engineering the apps, and checking for security standards crucial for wallet apps (e.g., random number generation and private key confidentiality). We reveal several severe vulnerabilities, including, for example, storing plaintext key revealing information in 111 apps which can lead to losing wallet ownership, and storing past transaction information in 11 apps which may lead to user deanonymization

Work-Life Balance: A Study on Female Teachers of Private Education Institutions of Bangladesh.

As society goes ahead in Bangladesh, there is an increasing expectation that women can  not only play their roles by nurturing and raising families to ensure confident and competent future generations for the betterment of society but can also  generate income    by joining as paid workforce in the working place. Growing cost of living as well as change of mindset is the key reasons for which increasing number of educated women are now working outside their house. Even in recent time, the tendency is increasing gradually. As a result, the traditional family is being replaced by the dualcareer family, thus socio-demographic changes are occurring similar to those in developing and developed societies. This dual responsibility is putting increasing pressure on women to achieve and maintain work life balance. In this article, a survey is conducted on 62 education institutions of Bangladesh taking sample of 320 teachers to know the real status of work-life balance institutions. The study finds that the work-life balance situation is moderate which can be improved by ensuring flexible working hours (roistered days off and family friendly starting and finishing times), transport facility, residential facility, child care center, flexible work arrangements/ job sharing , reduced working hours & workload and child schooling for the female teachers. Keywords: Work life balance, disturbance, energy, time, mood, support, Banglades

Skeletal Keypoint-Based Transformer Model for Human Action Recognition in Aerial Videos

Several efforts have been made to develop effective and robust vision-based solutions for human aerial action recognition. Generally, the existing methods rely on the extraction of either spatial features (patch-based methods) or skeletal key points (pose-based methods) that are fed to a classifier. The pose-based methods are generally regarded to be more robust to background changes and computationally efficient. Moreover, at the classification stage, the use of deep networks has generated significant interest within the community; however, the need remains to develop accurate and computationally effective deep learning-based solutions. To this end, this paper proposes a lightweight Transformer network-based method for human action recognition in aerial videos using the skeletal keypoints extracted with YOLOv8. The effectiveness of the proposed method is shown on a well-known public dataset containing 13 action classes, achieving very encouraging performance in terms of accuracy and computational cost as compared to several existing related methods

A clinical study of arrhythmias associated with acute coronary syndrome: a hospital based study of a high risk and previously undocumented population

Background: ACS represents a global epidemic. Arrhythmia in ACS is common. Careful investigation may lead to further improvement of prognosis. Retrospectively analyzed the year- round data of our center. Study was undertaken to analyze the incidence, frequency and type of arrhythmias in ACS. This is to aid timely intervention and to modify the outcome. Identification of the type of arrhythmia is of therapeutic and prognostic importance.Methods: This cross sectional analytical study was conducted in the Department of Cardiology, Apollo Hospitals Dhaka, from January 2019 to January 2020 with ACS patients. Enrolled consecutively and data analyzed.Results: There were 500 patients enrolled considering inclusion and exclusion criteria. Sample was subdivided into 3 groups on the type of ACS. Group-I with UA, Group-II with NSTE - ACS and Group-III with STE - ACS. Different types of arrhythmia noted. Types of arrhythmia were correlated with type of ACS. 500 patients included. Mean age 55.53±12.70, 71.6% male and 28.4% female. 60.4% hypertensive, 46.2% diabetic, 20.2% positive family history of CAD, 32.2% current smoker, 56.4% dyslipidaemic and 9.6% asthmatic. 31.2% UA, 39.2% NSTE-ACS and 29.6% STE-ACS. Type of arrhythmias noted. 22% sinus tachycardia, 20.2% sinus bradycardia, 9% atrial fibrillation, 5.2% ventricular ectopic, 4.8% supra ventricular ectopic, 2.8% bundle branch block, 2.2% atrio-ventricular block, 1% broad complex tachycardia, 0.4% narrow complex tachycardia, 0.2% sinus node dysfunction and 32.2% without any arrhythmia. Significant incidences of arrhythmia detected - respectively 29.8%, 39.2% and 31%, p<0.001.Conclusions: In conclusion, arrhythmias in ACS are common. More attention should be paid to improve their treatment and prognosis

Climate Services for Resilient Development in South Asia Mid-Term Report, January - June 2018

Aligned with the Global Framework for Climate Services, Climate Services for Resilient Development (CSRD) is a global partnership that works to link climate science, data streams, decision support tools, and training with decision-makers in developing countries. CSRD is led by the United States Government and is supported by the UK Government Department for International Development (DFID), UK Meteorological Office, ESRI, Google, the Inter-American Development Bank, the Asian Development Bank, and the American Red Cross. Led by the International Maize and Wheat Improvement Center (CIMMYT), the CSRD initiative in South Asia implements applied research and facilitates an expanding network of partners assure that actionable climate information and crop management advisories can be generated, refined, and delivered to smallholder farmers. This report details activities of the CSRD project in South Asia during the first six months of 2018

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Skeletal keypoint-based transformer model for human action recognition in aerial videos

Several efforts have been made to develop effective and robust vision-based solutions for human aerial action recognition. Generally, the existing methods rely on the extraction of either spatial features (patch-based methods) or skeletal key points (pose-based methods) that are fed to a classifier. The pose-based methods are generally regarded to be more robust to background changes and computationally efficient. Moreover, at the classification stage, the use of deep networks has generated significant interest within the community; however, the need remains to develop accurate and computationally effective deep learning-based solutions. To this end, this paper proposes a lightweight Transformer network-based method for human action recognition in aerial videos using the skeletal keypoints extracted with YOLOv8. The effectiveness of the proposed method is shown on a well-known public dataset containing 13 action classes, achieving very encouraging performance in terms of accuracy and computational cost as compared to several existing related methods