Network Route Minimization Using Time Based Interface Control

The demand for networking is increasing day by day with the progressive need of communication. As a result the communication channel and state database are increased with correspondingly. A rise in the amount of state database maintenance is one of the important cost effective issues for communication devices. The most challenging think is router state database reducing. As of now, many different types of state table accomplishments method are proposed for router state database reducing. In this purpose, we apply and modify the SPF algorithm by time based interface control. Dijkstra’s SPF algorithms searching the shortest specific link among from the all link then build a router state database table. If the state table size is little amount, then router OS using little amount of clock cycle. Some of Network interface are down for a fixed amount of time in a router. Therefore, we proposed a time based interface control method on SPF algorithm for re-build a new state database table. The modified SPF time based interfaces control algorithm suggests a new approach on dynamic routing protocol for reducing routing table size and saving router state-database size, resulting in a better convergence time

A review on deep-learning-based cyberbullying detection

Bullying is described as an undesirable behavior by others that harms an individual physically, mentally, or socially. Cyberbullying is a virtual form (e.g., textual or image) of bullying or harassment, also known as online bullying. Cyberbullying detection is a pressing need in today’s world, as the prevalence of cyberbullying is continually growing, resulting in mental health issues. Conventional machine learning models were previously used to identify cyberbullying. However, current research demonstrates that deep learning surpasses traditional machine learning algorithms in identifying cyberbullying for several reasons, including handling extensive data, efficiently classifying text and images, extracting features automatically through hidden layers, and many others. This paper reviews the existing surveys and identifies the gaps in those studies. We also present a deep-learning-based defense ecosystem for cyberbullying detection, including data representation techniques and different deep-learning-based models and frameworks. We have critically analyzed the existing DL-based cyberbullying detection techniques and identified their significant contributions and the future research directions they have presented. We have also summarized the datasets being used, including the DL architecture being used and the tasks that are accomplished for each dataset. Finally, several challenges faced by the existing researchers and the open issues to be addressed in the future have been presented

Women’s Preferences for Maternal Healthcare Services in Bangladesh: Evidence from a Discrete Choice Experiment

Despite substantial improvements in several maternal health indicators, childbearing and birthing remain a dangerous experience for many women in Bangladesh. This study assessed the relative importance of maternal healthcare service characteristics to Bangladeshi women when choosing a health facility to deliver their babies. The study used a mixed-methods approach. Qualitative methods (expert interviews, focus group discussions) were initially employed to identify and develop the characteristics which most influence a women’s decision making when selecting a maternal health service facility. A discrete choice experiment (DCE) was then constructed to elicit women’s preferences. Women were shown choice scenarios representing hypothetical health facilities with nine attributes outlined. The women were then asked to rank the attributes they considered most important in the delivery of their future babies. A Hierarchical Bayes method was used to measure mean utility parameters. A total of 601 women completed the DCE survey. The model demonstrated significant predictive strength for actual facility choice for maternal health services. The most important attributes were the following: consistent access to a female doctor, the availability of branded drugs, respectful provider attitudes, a continuum of maternal healthcare including the availability of a c-section delivery and lower waiting times. Attended maternal healthcare utilisation rates are low despite the access to primary healthcare facilities. Further implementation of quality improvements in maternal healthcare facilities should be prioritised

Screening and quantification of antibiotic residues in poultry products and feed in selected areas of Bangladesh

Background and Aim: Antibiotic residues in livestock farming have been identified as a potential cause of antimicrobial resistance in humans and animals. This study aimed to determine whether antibiotic residues were present in the chicken meat, eggs, feces, and feed collected from all four districts in the Mymensingh division of Bangladesh. Materials and Methods: To detect antibiotic residues in the collected samples, qualitative thin-layer chromatography (TLC) and quantitative high-performance liquid chromatography (HPLC) were used. A total of 230 samples were analyzed for commonly used 11 antibiotics residue. Out of these, 40 meats and 40 feces samples were collected from broilers and layers, 30 egg samples from duck and layer, and 120 feed samples from both broilers and layers from the study area. Thin-layer chromatography was used for screening the presence of antibiotic residues; TLC-positive samples were then subjected to further HPLC analysis to determine the residue concentrations. Results: Thin-layer chromatography analysis revealed that 23.5% of the tested samples contained residues from six different antibiotic classes (tetracyclines, quinolones, beta-lactams, sulfonamides, aminoglycosides, and macrolides). Thin-layer chromatography analysis showed that 35% and 25% of the meat samples were positive for residues from the broiler and layer, respectively. About 15% and 30% of layer and duck egg samples had positive residues, respectively. Out of 120 feed samples analyzed, about 15.8% had various antibiotic residues. In addition, feces samples from broilers and layers had 50% and 35% antibiotic residues, respectively. A total of 2.5% meat and 3.3% egg samples had antibiotic residues above the maximum residue limit (MRL). Based on the findings of this study, the highest percentage of oxytetracycline, followed by doxycycline and ciprofloxacin, were detected in feed samples, and oxytetracycline was detected in meat and egg samples. Conclusion: This study clearly showed the misuse of antibiotics in the poultry sector in Bangladesh. Although antibiotic residues below the MRL level are suitable for human consumption, they may result in antimicrobial drug resistance to pathogens

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Cloud Accounting: A New Business Model in Challenging Context of China

This chapter presents a descriptive literature review-based research on cloud accounting that published during 2013–2019 to make a comprehensive analysis of the current discourse and impact of cloud accounting in China. This chapter is organized to answer three questions: (a) how cloud accounting a new business model in China, (b) how does cloud accounting influence the business in China and (c) what the accountant’s perspective in China is on emerging accounting technology. By comparing the cloud accounting with traditional accounting, we answered the first question. In the second question, this chapter explains from the perspective of opportunity and risks. In the third question, this chapter analyzes perspectives from accountants on accounting discipline and accounting work. All the influence and characters of cloud accounting mentioned in this chapter are all based on Chinese social and institutional background. This chapter promotes the exploration and innovation of the basic theory of accounting informatization and provides a theoretical basis for Chinese enterprises to use cloud accounting

A Review of the Prospects and Constraints for Using Artificial Intelligence for the Interpretation of Remote Sensing Data

<p>The abstract of a paper on the prospects and restrictions of applying artificial intelligence (AI) for remote sensing data interpretation will most likely discuss the junction of AI and remote sensing, stressing potential benefits and challenges. It may discuss advances in AI approaches and their applications in evaluating large and complicated remote sensing datasets, as well as limitations and issues that researchers and practitioners should be aware of. The abstract could underline the significance of precise remote sensing data interpretation for environmental monitoring, resource management, disaster response, and other essential applications. The rapid growth of artificial intelligence (AI) tools has changed the field of remote sensing data interpretation, creating previously unimaginable prospects for extracting useful insights from enormous and complicated datasets. This study provides an in-depth examination of the opportunities and restrictions involved with using AI to understand remote sensing data, offering insight on the revolutionary potential of this integration. This research also discusses the essential restrictions and challenges associated with AI integration in remote sensing. Some AI models are black boxes, which raises concerns about transparency, interpretability, and the possibility of biased decision-making. To ensure the ethical use of AI in remote sensing interpretation, a careful balance of algorithmic complexity and the capacity to give interpretable results that fit with domain knowledge must be struck. This article offers a comprehensive evaluation of the opportunities and restrictions associated with using artificial intelligence to understand remote sensing data. Researchers and practitioners can use AI's revolutionary potential to gain deeper insights into Earth's dynamics and contribute to a more sustainable and informed future.</p><p>Keywords:- Artificial Intelligence, Remote Sensing, Constraints, Interpretation, Prospects.</p&gt

Regulatory influence on sustainability reporting: evidence from Murray–Darling Basin Authority in Australia

Purpose: The purpose of this study is to explore the sustainability reporting of a public sector organisation (PSO). This study focuses on socio-environmental practices of a major agro-economic platform in Australia – the Murray–Darling Basin Authority (MDBA) to provide a unique perspective on water resource management and sustainability. Design/methodology/approach: This longitudinal qualitative case study collects published data from the MDBA’s annual reports over 21 years (1998–2018) and considers economic, social and environmental dimensions of sustainability using legitimacy and institutional theory. Findings: This study finds that the MDBA’s sustainability reporting is influenced by its response to the Water Act 2007 and the Basin Plan 2012 regulations and to maintain its legitimacy with stakeholders. The MDBA wished to pursue sustainability through integrating these regulations complemented by stakeholder expectations. Although all categories increased in reporting, the environment category has the highest primacy in achieving a healthy basin through sustainable water management for the long-term benefit of the stakeholders. Research limitations/implications: This study contributes to the PSOs sustainability reporting literature. Particularly, this study provides insights of sustainability reporting patterns and practices over a long period through a longitudinal study. This study contributes new knowledge on the awareness of PSOs sustainability practice which has implications for governments, regulators, policymakers, managers and other stakeholders. Originality/value: The Australian PSOs setting is under-researched from the perspective of a regulatory framework. The MDBA case provides unique insights on water resource management and sustainability which has value for many countries around the world