New Software Process Model Designed from the Basics of Evolutionary Biology and Software Evolution

The process of software development is achieved by using different software life cycle models to design, code and test the software. Process models like the water fall model, spiral model and prototyping are used by companies. Most of these models were designed for a single generation of software. In this research, methods to correct the problems in existing models are proposed based on the principles of evolution in biology and biochemistry, and an abstract model has been generated. The model is called the Infinity Model. The basic principles of biological evolution have been incorporated into the varying steps in the Infinity Model to generate an evolutionary process model. It consists of a completely new design cycle which incorporates both the creation of software and the maintenance of software. In this model, methods to correct deficiencies like resource allocation, documentation and requirement updating in the existing models have been incorporated. Several case studies of large company software and the problems they faced were studied. From the case studies several methods like requirement evolution, consolidation and architectural evolution have been incorporated into the Infinity Model.Computer Science Departmen

Aeroallergens, air pollutants, and chronic rhinitis and rhinosinusitis

Chronic rhinitis and rhinosinusitis are among the most common conditions worldwide with significant morbidity and decreased quality of life. Although the pathogenesis of these conditions is multifactorial, there has been increasing evidence for the role of environmental factors such as aeroallergens and air pollutants as initiating or exacerbating factors. This review will outline the current literature focusing on the role of aeroallergens and air pollution in the pathogenesis of chronic sinonasal inflammatory conditions. Keywords: Aeroallergens, Air pollutants, Inflammatory cytokines, Innate immunity, Particulate matter, Rhiniti

Association between temperature variability and global meningitis incidence

Background: Meningitis can cause devastating epidemics and is susceptible to climate change. It is unclear how temperature variability, an indicator of climate change, is associated with meningitis incidence. Methods: We used global meningitis incidence data along with meteorological and demographic data over 1990–2019 to identify the association between temperature variability and meningitis. We also employed future (2020–2100) climate data to predict meningitis incidence under different emission levels (SSPs: Shared Socioeconomic Pathways). Results: We found that the mean temperature variability increased by almost 3 folds in the past 30 years. The largest changes occurred in Australasia, Tropical Latin America, and Central Sub-Saharan Africa. With a logarithmic unit increase in temperature variability, the overall global meningitis risk increases by 4.8 %. Australasia, Central Sub-Saharan Africa, and High-income North America are the most at-risk regions. Higher statistical differences were identified in males, children, and the elderly population. Compared to high-emission (SSP585) scenario, we predicted a median reduction of 85.8 % in meningitis incidence globally under the low-emission (SSP126) climate change scenario by 2100. Conclusion: Our study provides evidence for temperature variability being in association with meningitis incidence, which suggests that global actions are urgently needed to address climate change and to prevent meningitis occurrence

Exposure to Particulate Matter Air Pollution and Anosmia

Importance: Anosmia, the loss of the sense of smell, has profound implications for patient safety, well-being, and quality of life, and it is a predictor of patient frailty and mortality. Exposure to air pollution may be an olfactory insult that contributes to the development of anosmia. Objective: To investigate the association between long-term exposure to particulate matter (PM) with an aerodynamic diameter of no more than 2.5 μm (PM2.5) with anosmia.Design, Setting, and Participants: This case-control study examined individuals who presented from January 1, 2013, through December 31, 2016, at an academic medical center in Baltimore, Maryland. Case participants were diagnosed with anosmia by board-certified otolaryngologists. Control participants were selected using the nearest neighbor matching strategy for age, sex, race/ethnicity, and date of diagnosis. Data analysis was conducted from September 2020 to March 2021. Exposures: Ambient PM2.5 levels.Main Outcomes and Measures: Novel method to quantify ambient PM2.5 exposure levels in patients diagnosed with anosmia compared with matched control participants.Results: A total of 2690 patients were identified with a mean (SD) age of 55.3 (16.6) years. The case group included 538 patients with anosmia (20%), and the control group included 2152 matched control participants (80%). Most of the individuals in the case and control groups were women, White patients, had overweight (BMI 25 to 2.5 was significantly higher in patients with anosmia compared with healthy control participants at 12-, 24-, 36-, 60-month time points: 10.2 (1.6) μg/m3vs 9.9 (1.9) μg/m3; 10.5 (1.7) μg/m3vs 10.2 (1.9) μg/m3; 10.8 (1.8) μg/m3vs 10.4 (2.0) μg/m3; and 11.0 (1.8) μg/m3vs 10.7 (2.1) μg/m3, respectively. There was an association between elevated PM2.5 exposure level and odds of anosmia in multivariate analyses that adjusted for age, sex, race/ethnicity, body mass index, alcohol or tobacco use, and medical comorbidities (12 mo: odds ratio [OR], 1.73; 95% CI, 1.28-2.33; 24 mo: OR, 1.72; 95% CI, 1.30-2.29; 36 mo: OR, 1.69; 95% CI, 1.30-2.19; and 60 mo: OR, 1.59; 95% CI, 1.22-2.08). The association between long-term exposure to PM2.5 and the odds of developing anosmia was nonlinear, as indicated by spline analysis. For example, for 12 months of exposure to PM2.5, the odds of developing anosmia at 6.0 µg/m3 was OR 0.79 (95% CI, 0.64-0.97); at 10.0 µg/m3, OR 1.42 (95% CI, 1.10-1.82); at 15.0 µg/m3, OR 2.03 (95% CI, 1.15-3.58).Conclusions and Relevance: In this study, long-term airborne exposure to PM2.5 was associated with anosmia. Ambient PM2.5 represents a potentially ubiquitous and modifiable risk factor for the loss of sense of smell.</p