27 research outputs found
A Review on Software Architecture Documentation in Agile Development
With the growing development of world every software product demands extra features to compete with competitors. To solve this problem, we have required Agile with defined and clear architecture to avoid the failure of project. But you do not know how it is possible and how we can stable our architecture and Agile model…? To ease the solution of problem we divided our product development models into two sections. 1. Traditional Models and 2. Agile Models
The traditionally models are highly time consuming with dense documentation as compared to agile with frivolous documentation and intercommunications to satisfy customer. There are different methodologies available for starting products and complex systems development consisting the simple requirement with well-structured architecture objects. But we choose the agile process to make our architecture slim and least documentation which can easily review, update and conversate. There are also problems in our documentation and architecture design but we propose solutions with problems for the easiness of reader. We also propose different solutions in documentation problems
Single nucleotide polymorphism and phylogenetic analysis of the exon 2 of leptin gene in Lohi sheep
Background: Leptin hormone, encoded by leptin (LEP) gene is involved in many biological and physiological processes in the body. Polymorphism in LEP gene has been observed and correlated with a variety of reproductive and productive traits in several sheep breeds worldwide, but its role has not been much studied in local sheep breeds of Pakistan. The present study was conducted to analyze polymorphism in LEP gene in Lohi breed of sheep.Methods: Subsequent to statistical analysis (generalized linear model), 18 animals were selected randomly from the flock for blood samples collection followed by DNA extraction, amplification using PCR prior to sequencing. The amplified product of exon 2 and partial intron 2 regions of LEP gene was 268bp.Results: Molecular analysis showed a heterozygous condition i.e. C>Y at position 15 and 18 in exon 2. The data on average daily weight gain (ADG) from birthday to 90 days were used for association study, while environmental effects were minimized by means of generalized linear model. Association of polymorphisms in LEP gene with ADG did not yield any significant results.Conclusion: In conclusion, analysis of LEP gene sequence verified the existence of genetic changes in Lohi sheep. Further investigations are needed to find variations that might be linked with traits of economic importance for upcoming breeding program sand marker-assisted selection.Keywords: DNA; Exon 2; LEP; PCR; Loh
Carrot and Stick Approach: The Exploitative Leadership and Absenteeism in Education Sector
Utilizing the conservation of resources theory, this study investigates serial mediation of facades of conformity and depression between exploitative leadership and absenteeism. A total of 211 education sector employees using the convenient sampling technique took part in the survey with data collected in a time-lagged research design. Findings of the study reveal that facades of conformity and depression mediate the independent paths and play a serial mediating role between EL and absenteeism path. This study suggests that EL works as a workplace stressor, under which employees try to protect their valuable resources from further loss in the form of facades of conformity, in doing so, it leads to depression; thus, employees ultimately use absenteeism as an active coping strategy to cope with workplace stressors
Recommended from our members
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
Identification of sex from footprint dimensions using machine learning: a study on population of Punjab in Pakistan
Abstract Background Likewise the fingerprints and palm prints, footprints are also helpful in solving a crime puzzle; however, very few studies have been reported targeting the identification of sex-based upon footprint features. Therefore, the present study aims at the identification of sex using footprint features from the population of Punjab, Pakistan. The foot measurements, i.e., toe length ratio, individual toe lengths, foot breadth, and foot index, are used as features for the identification of sex. Footprint samples were collected from 280 volunteers (142 males and 138 females) from all over Punjab (age range 18–50 years). A sex identification method is proposed in this study employing various machine learning algorithms, i.e., Naïve Bayes, J48, Random Forest, Random Tree, and REP Tree, and compared them. Results The designed model was cross-validated using 10-fold cross-validation. The results demonstrated the varying accuracy of the machine learning algorithms, using different combinations of footprint features. However, the Naïve Bayes algorithm demonstrated an accuracy of 87.8%, for sex identification, using the combination of toe length and foot indexes. Conclusions It is concluded that by using a combination of toe length and foot indexes and employing the Naïve Bayes algorithm, sex can be identified more accurately as compared to the other methods
Optimized Small Waterbird Detection Method Using Surveillance Videos Based on YOLOv7
Waterbird monitoring is the foundation of conservation and management strategies in almost all types of wetland ecosystems. China’s improved wetland protection infrastructure, which includes remote devices for the collection of larger quantities of acoustic and visual data on wildlife species, increased the need for data filtration and analysis techniques. Object detection based on deep learning has emerged as a basic solution for big data analysis that has been tested in several application fields. However, these deep learning techniques have not yet been tested for small waterbird detection from real-time surveillance videos, which can address the challenge of waterbird monitoring in real time. We propose an improved detection method by adding an extra prediction head, SimAM attention module, and sequential frame to YOLOv7, termed as YOLOv7-waterbird, for real-time video surveillance devices to identify attention regions and perform waterbird monitoring tasks. With the Waterbird Dataset, the mean average precision (mAP) value of YOLOv7-waterbird was 67.3%, which was approximately 5% higher than that of the baseline model. Furthermore, the improved method achieved a recall of 87.9% (precision = 85%) and 79.1% for small waterbirds (defined as pixels less than 40 × 40), suggesting a better performance for small object detection than the original method. This algorithm could be used by the administration of protected areas or other groups to monitor waterbirds with higher accuracy using existing surveillance cameras and can aid in wildlife conservation to some extent
Low-field magnetic resonance imaging in a boy with intracranial bolt after severe traumatic brain injury: Illustrative case
Background: Conventional magnetic resonance imaging (cMRI) is sensitive to motion and ferromagnetic material, leading to suboptimal images and image artifacts. In many patients with neurological injuries, an intracranial bolt (ICB) is placed for monitoring intracranial pressure (ICP). Repeated imaging (computed tomography [CT] or cMRI) is frequently required to guide management. A low-field (0.064-T) portable magnetic resonance imaging (pMRI) machine may provide images in situations that were previously considered contraindications for cMRI.Observations: A 10-year-old boy with severe traumatic brain injury was admitted to the pediatric intensive care unit, and an ICB was placed. Initial head CT showed a left-sided intraparenchymal hemorrhage with intraventricular dissection and cerebral edema with mass effect. Repeated imaging was required to assess the brain structure because of continually fluctuating ICP. Transferring the patient to the radiology suite was risky because of his critical condition and the presence of an ICB; hence, pMRI was performed at the bedside. Images obtained were of excellent quality without any ICB artifact, guiding the decision to continue to manage the patient conservatively. The child later improved and was discharged from the hospital.Lessons: pMRI can be used to obtain excellent images at the bedside in patients with an ICB, providing useful information for better management of patients with neurological injuries
Assessment and simulation of land use and land cover change impacts on the land surface temperature of Chaoyang District in Beijing, China
Rapid urbanization is changing the existing patterns of land use land cover (LULC) globally, which is consequently increasing the land surface temperature (LST) in many regions. The present study is focused on estimating current and simulating future LULC and LST trends in the urban environment of Chaoyang District, Beijing. Past patterns of LULC and LST were identified through the maximum likelihood classification (MLC) method and multispectral Landsat satellite images during the 1990–2018 data period. The cellular automata (CA) and stochastic transition matrix of the Markov model were applied to simulate future (2025) LULC and LST changes, respectively, using their past patterns. The CA model was validated for the simulated and estimated LULC for 1990–2018, with an overall Kappa (K) value of 0.83, using validation modules in IDRISI software. Our results indicated that the cumulative changes in built-up to vegetation area were 74.61 km2 (16.08%) and 113.13 km2 (24.38%) from 1990 to 2018. The correlation coefficient of land use and land cover change (LULCC), including vegetation, water bodies and built-up area, had values of r = − 0.155 (p > 0.005), −0.809 (p = 0.000), and 0.519 (p > 0.005), respectively. The results of future analysis revealed that there will be an estimated 164.92 km2 (−12%) decrease in vegetation area, while an expansion of approximately 283.04 km2 (6% change) will occur in built-up areas from 1990 to 2025. This decrease in vegetation cover and expansion of settlements would likely cause a rise of approximately ∼10.74 °C and ∼12.66 °C in future temperature, which would cause a rise in temperature (2025). The analyses could open an avenue regarding how to manage urban land cover patterns to enhance the resilience of cities to climate warming. This study provides scientific insights for environmental development and sustainability through efficient and effective urban planning and management in Beijing and will also help strengthen other research related to the UHI phenomenon in other parts of the world