An Empirical Evaluation Of Predictive Models Of Programmer Navigation

The process of software development consists of many activities, such as writing code, debugging, and navigating through code. Navigating through the code to understand or seek information for developing new code is a very time consuming and tedious task. Many tools are developed based on predictive models to help programmers in navigation. These models predict the fragments of code which might be of developer’s interest. There have been studies for comparing these models to determine their predictive accuracy. However, the models are often based on crude approximations of where a developer’s attention is. For example, prior work has both where the developer’s cursor location as well as what is on the center of the screen to approximate where he/she is looking. To address this concern, we conducted an empirical evaluation of these approximations to see how well they agree with a human evaluator’s perception of where the developer’s attention is. We conducted a replication study on 10 participants and manually coded their navigation pattern. The goals of the study was to evaluate the generalizability of prior work as well as to evaluate the prior operationalizations of navigation. The key findings of this study are: (a) The operationalization based on where the programmer clicks agreed most closely with human evaluator’s assessment and, (b) prior navigation results did not generalize well likely due to small sample size and particulars of the task content

FUNGAL ISOLATION AND CHARACTERIZATION FROM SPOILED VEGETABLES LYCOPERSICON ESCULENTUM, BRASSICA OLERACEA, SPINACIA OLERACEA

This study investigated the micro organisms associated with the spoilage of vegetables of Tomato (Lycopersicon esculentum), Spinach (Spinacea oleracea), Cabbage (Brassica oleracea) obtained from local market of Haridwar. Five vegetable spoilage fungi were isolate & identified as follows Aspergilus, Fusarium, Penicilium, Trichoderma. In antifungal sensitivity test different antifungal drugs were used to test the susceptibility behavior as the isolated organism. Antifungal activity was determined by agar well diffusion technique. Penicillium show resistance to both antifungal resistance to griseofluvin & sensitive to fluconazole & inhibition zone was 30mm against fluconazole, gave highest inhibition zone against fluconazole that was 32nm. Trichoderma shows sensitivity to fluconazole & resistance to fluconazole, inhibition zone is 31nm. The need for microbial assessment of vegetables for production of salads and other use is also emphasized to reduce possible contamination. Key words: fungal, Lycopersicon esculentum , Brassica oleracea, Spinacea oleracea

Spatio-Temporal Analysis of Rainfall Dynamics of 120 Years (1901–2020) Using Innovative Trend Methodology: A Case Study of Haryana, India

As we know, climate change and climate variability significantly influence the most important component of global hydrological cycle, i.e., rainfall. The study pertaining to change in the spatio-temporal patterns of rainfall dynamics is crucial to take appropriate actions for managing the water resources at regional level and to prepare for extreme events such as floods and droughts. Therefore, our study has investigated the spatio-temporal distribution and performance of seasonal rainfall for all districts of Haryana, India. The gridded rainfall datasets of 120 years (1901 to 2020) from the India Meteorological Department (IMD) were categorically analysed and examined with statistical results using mean rainfall, rainfall deviation, moving-average, rainfall categorization, rainfall trend, correlation analysis, probability distribution function, and climatology of heavy rainfall events. During each season, the eastern districts of Haryana have received more rainfall than those in its western equivalent. Rainfall deviation has been positive during the pre-monsoon season, while it has been negative for all remaining seasons during the third quad-decadal time (QDT3, covering the period of 1981–2020); rainfall has been declining in most of Haryana’s districts during the winter, summer monsoon, and post-monsoon seasons in recent years. The Innovative Trend Analysis (ITA) shows a declining trend in rainfall during the winter, post-monsoon, and summer monsoon seasons while an increasing trend occurs during the pre-monsoon season. Heavy rainfall events (HREs) were identified for each season from the last QDT3 (1981–2020) based on the available data and their analysis was done using European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis Interim (ERA-Interim), which helped in understanding the dynamics of atmospheric parameters during HREs. Our findings are highlighting the qualitative and quantitative aspects of seasonal rainfall dynamics at the districts level in Haryana state. This study is beneficial in understanding the impact of climate change and climate variability on rainfall dynamics in Haryana, which may further guide the policymakers and beneficiaries for optimizing the use of hydrological resources

Impact of urbanization on the abundance and distribution of Anophelines population in Ghaziabad district, Uttar Pradesh, India

Background & objectives: In urban areas, upsurge in population has resulted in more breeding sites for malaria vectors, and hence this scenario potentially undermine malaria elimination and control programs. The change in land use due to urbanization may result in the presence and distribution of malaria vectors. Understanding potential malaria vectors is essential for current and future malaria transmission control strategies. This study investigated the effects of rapid urbanization on malaria vectors An. culicifacies s.l. and An. stephensi L. in Ghaziabad district. Methods: Ghaziabad district which presents several levels of urbanization was selected for this study. Entomological investigations were conducted seasonally from 2014-2016 in the rural, urban, and peri-urban regions. Vector incrimination study was done using ELISA (confirmation by PCR) on suspected Anopheles vectors viz. An. culicifacies, An. stephensi, An. annularis and An. subpictus. Results: An. culicifacies showed alteration in distribution influenced by rural and agricultural land whereas An. stephensi was found to be influenced by artificial habitats and population growth. Interpretation & conclusion: The study also confirms the association between the abundance of malaria vectors and land use change

Influence of climatic factors on the life stages of Aedes mosquitoes and vectorial transmission: A review

Vector-borne diseases are rampant across the world. Studies have been conducted to assess the impact of climatic factors on the life stages of various mosquito species. In this study, the overall effect of climatic factors such as temperature and relative humidity on the life span, survivability, development, and vectorial capacity of Aedes mosquito species has been evaluated. A literature survey was done through PubMed, Google Scholar, and Shodhganga databases using the keywords’ “Aedes”, “temperature”, and “humidity”. The search output was analyzed in terms of the impact of environmental factors on the life stages of Aedes species and it was observed that both temperature and relative humidity act as significant indicators for dengue vector propagation and virus transmission. A total of 86 research papers were selected for inclusion, and the study is divided into five criteria: (i) egg eclosion, (ii) larval development, (iii) pupal development, (iv) adult survival, and (v) vector transmission. A 95% Confidence Interval (CI) was estimated using SPSS software. Literature mining results revealed the most optimal temperatures for egg eclosion, larval development, pupal development, adult survival, and vector transmission were 24.03±3.79, 24.81±3.23, 26.18±3.96, 26.55±2.71, and 29.78±2.77, respectively. The study finds a knowledge gap regarding the impacts of relative humidity on Aedes biology. The outcomes of this work will contribute to a comprehensive understanding of the core behavioral patterns of Aedes mosquitoes under evolving climatic circumstances. Furthermore, these findings will play a pivotal role in shaping forthcoming strategies for mosquito control

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Not AvailableThe evaluation of climatic change impact on maize grain and biomass yield under different N management practices through a well-calibrated and validated APSIM model in Vertisol of central India has been made. Climate scenarios were derived from seven global climate models (GCM) for two representative concentration pathways (RCPs), i.e. RCP4.5 and RCP8.5, and two-time slices, i.e. 2050 and 2080. The five N scenarios, namely N0%, N50%, N100%, N150%, and 100% organic, were studied in different climatic scenarios. The probability of exceedance showed that N0%, N50%, N100%, N150%, and 100% organic treatments have a 50% chance of yield greater than 1.0, 3.40, 4.20, 4.45 and 3.84 t ha-1, respectively. The average reduction of maize yield was -44.4, -20, -19.7 - 17.9 and 22.5 per cent in N 0%, N 50%, N 100%, N 150%, 100% organic, respectively under RCP4.5 over the baseline period (1980-2010). For RCP8.5, the average reduction of maize yield in N 0%, N 50%, N 100%, N 150%, 100% organic was 41.2, 21.2, 20.8 20.6 and 23.1 per cent, respectively. Simulation results suggested that a higher decrease of maize yield in 100 per cent organic treatments than inorganic treatments is due to variability in N uptake.Not Availabl

Maize productivity analysis in response to climate change under different nitrogen management strategies

The evaluation of climatic change impact on maize grain and biomass yield under different N management practices through a well-calibrated and validated APSIM model in Vertisol of central India has been made. Climate scenarios were derived from seven global climate models (GCM) for two representative concentration pathways (RCPs), i.e. RCP4.5 and RCP8.5, and two-time slices, i.e. 2050 and 2080. The five N scenarios, namely N0%, N50%, N100%, N150%, and 100% organic, were studied in different climatic scenarios. The probability of exceedance showed that N0%, N50%, N100%, N150%, and 100% organic treatments have a 50% chance of yield greater than 1.0, 3.40, 4.20, 4.45 and 3.84 t ha-1, respectively. The average reduction of maize yield was -44.4, -20, -19.7 - 17.9 and 22.5 per cent in N 0%, N 50%, N 100%, N 150%, 100% organic, respectively under RCP4.5 over the baseline period (1980-2010). For RCP8.5, the average reduction of maize yield in N 0%, N 50%, N 100%, N 150%, 100% organic was 41.2, 21.2, 20.8 20.6 and 23.1 per cent, respectively. Simulation results suggested that a higher decrease of maize yield in 100 per cent organic treatments than inorganic treatments is due to variability in N uptake

SARS-CoV-2 seroprevalence among the general population and healthcare workers in India, December 2020–January 2021

Background: Earlier serosurveys in India revealed seroprevalence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) of 0.73% in May–June 2020 and 7.1% in August–September 2020. A third serosurvey was conducted between December 2020 and January 2021 to estimate the seroprevalence of SARS-CoV-2 infection among the general population and healthcare workers (HCWs) in India. Methods: The third serosurvey was conducted in the same 70 districts as the first and second serosurveys. For each district, at least 400 individuals aged ≥10 years from the general population and 100 HCWs from subdistrict-level health facilities were enrolled. Serum samples from the general population were tested for the presence of immunoglobulin G (IgG) antibodies against the nucleocapsid (N) and spike (S1-RBD) proteins of SARS-CoV-2, whereas serum samples from HCWs were tested for anti-S1-RBD. Weighted seroprevalence adjusted for assay characteristics was estimated. Results: Of the 28,598 serum samples from the general population, 4585 (16%) had IgG antibodies against the N protein, 6647 (23.2%) had IgG antibodies against the S1-RBD protein, and 7436 (26%) had IgG antibodies against either the N protein or the S1-RBD protein. Weighted and assay-characteristic-adjusted seroprevalence against either of the antibodies was 24.1% [95% confidence interval (CI) 23.0–25.3%]. Among 7385 HCWs, the seroprevalence of anti-S1-RBD IgG antibodies was 25.6% (95% CI 23.5–27.8%). Conclusions: Nearly one in four individuals aged ≥10 years from the general population as well as HCWs in India had been exposed to SARS-CoV-2 by December 2020