Rainfall analysis using conventional and non-conventional rainfall information on monthly scale

The aim of this paper is to describe the technique used to create the merged analysis of rainfall over the Indian and adjoining region (1.5° to 35.5° N and 63.5° to 97.5° E). The technique is tested for monthly gridded fields of rainfall for a 2–year monsoon period (2001 and 2003) on a 1° x 1° latitude–longitude grid by merging rainfall estimates from different sources, viz satellite based estimates, rain gauge analysis and numerical weather prediction model rainfall. First, in order to reduce the random error involved in the satellite rainfall estimates and the model predictions, satellite and model estimates are combined linearly based on a maximum likelihood estimate method. In this case the weight for each component is inversely proportional to the squares of the individual random errors. The weight is determined by comparing the components with the concurrent gauge analysis. As the combined analysis contains bias from the individual input data sources, the combined analysis is then blended with the analysis based on gauge observations. It is seen that the merged analysis produced here is closer to the observations than the individual sources. It is observed that the magnitude and distribution of the orographic heavy rainfall along the Western Ghats of India is very different and more realistic compared to the Global Precipitation Climatology Project (GPCP) and the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP). When compared with the India Meteorological Department analysis, it is found that the merged analysis shows higher correlation than the satellite and model predicted rainfall. From the results it can be concluded that this study has shown promising results and the analyses can be used as a bench mark for evaluating model simulations which serves as a basis for real–time monitoring. Based on these promising results, long term datasets on high resolution grid for daily and monthly scale over Indian and adjoining region will be generated, which in turn can be used to study spatial and temporal variability of rainfall over Indian and adjoining regio

Work-related stressors and coping strategies during COVID-19 pandemic: A qualitative study on reflections of frontline health care workers from India

Background: Frontline healthcare workers, a vital workforce in developing countries is often out of mainstream vision and their challenges and coping behaviors under stressful conditions remain unclear to stakeholders. This study was undertaken with the objective to explore the challenges faced by community surveillance workers and their coping strategies during COVID-19 pandemic. Methods: A qualitative descriptive study with constructivism paradigm was undertaken for a period of one year by conducting eight focus group discussions and eight in-depth interviews among the health workers undertaking COVID-19 surveillance selected purposively from eight wards within three Boroughs of a Municipal Corporation using interview guide. Thematic analysis was used to compare and contrast the codes to generate themes inductively under two constructs. Results: The first construct, factors influencing work related stress was categorized into four themes related to- work environment, community’s response towards pandemic surveillance, organizational support and personal factors. Main predisposing factors of work place stress were risk of self-infection, concern for family safety, inadequate training, shortage of manpower and protective equipment etc. While a strong commitment towards work, assistance from local community influencers, administrative appreciation and supportive supervision were protective factors against stress. Second construct on coping strategies was categorized into managing stress by problem-focused strategies like adapting with experience, gathering information and sharing experiences, adopting self-care practices; while emotion-based coping strategies included denial, venting out, or turning to religion etc. Conclusion: Community surveillance workers faced considerable and variable stress during pandemics due to various underlying work stressors, managed innovatively, using self-coping strategies

High prevalence of Helicobacter pylori infection with dual resistance to metronidazole and clarithromycin in Hong Kong

Background: Metronidazole resistance is a common problem in most Asian countries, and clarithromycin has been widely used in Hong Kong. Aim: To determine the prevalence of Helicobacter pylori strains resistant to metronidazole and clarithromycin in Hong Kong and to assess the effect on eradication rates. Also to determine the genetic mutation in relation to phenotypic divergence in clarithromycin-resistant strains. Methods: H. pylori were cultured from gastric biopsies obtained from 87 patients during upper endoscopy. Minimal inhibitory concentrations of metronidazole and clarithromycin were determined by Etest and agar dilution methods. Mutations in clarithromycin-resistant strains were identified by polymerase chain reaction and restriction analysis. Random amplified polymorphic DNA fingerprinting was performed on clarithromycin-resistant and susceptible isolates. Results: The prevalences of H. pylori strains resistant to metronidazole and clarithromycin were 49.4% and 10.8%, respectively, in Hong Kong. Dual resistance to metronidazole and clarithromycin were found in 7.2% of patients. The agreement between E-test and agar dilution methods was determined by error-rate bound analysis as 95.4% for metronidazole and 100% for clarithromycin. Dual resistant strains reduced the eradication rate to 66.7%. Among clarithromycin-resistant strains tested, all were due to A2144G point mutation in 23S rRNA gene. Random amplified polymorphic DNA fingerprinting suggested various phenotypically mixed populations. Conclusions: The prevalence of metronidazole-resistant H. pylori strains remained static whilst the prevalence of clarithromycin-resistant strains was not rare in Hong Kong. An alarming 7.2% of patients were resistant to both the antimicrobials, which had a definite impact on treatment success. All cases of resistance to clarithromycin were due to A2144G mutation in 23S rRNA of H. pylori.postprin

The Role of the Mucus Barrier in Digestion

Mucus forms a protective layer across a variety of epithelial surfaces. In the gastrointestinal (GI) tract, the barrier has to permit the uptake of nutrients, while excluding potential hazards, such as pathogenic bacteria. In this short review article, we look at recent literature on the structure, location, and properties of the mammalian intestinal secreted mucins and the mucus layer they form over a wide range of length scales. In particular, we look at the structure of the gel-forming glycoprotein MUC2, the primary intestinal secreted mucin, and the influence this has on the properties of the mucus layer. We show that, even at the level of the protein backbone, MUC2 is highly heterogeneous and that this is reflected in the networks it forms. It is evident that a combination of charge and pore size determines what can diffuse through the layer to the underlying gut epithelium. This information is important for the targeted delivery of bioactive molecules, including nutrients and pharmaceuticals, and for understanding how GI health is maintained

Remarks on quiver gauge theories from open topological string theory

We study effective quiver gauge theories arising from a stack of D3-branes on certain Calabi-Yau singularities. Our point of view is a first principle approach via open topological string theory. This means that we construct the natural A-infinity-structure of open string amplitudes in the associated D-brane category. Then we show that it precisely reproduces the results of the method of brane tilings, without having to resort to any effective field theory computations. In particular, we prove a general and simple formula for effective superpotentials

Machine-Part cell formation through visual decipherable clustering of Self Organizing Map

Machine-part cell formation is used in cellular manufacturing in order to process a large variety, quality, lower work in process levels, reducing manufacturing lead-time and customer response time while retaining flexibility for new products. This paper presents a new and novel approach for obtaining machine cells and part families. In the cellular manufacturing the fundamental problem is the formation of part families and machine cells. The present paper deals with the Self Organising Map (SOM) method an unsupervised learning algorithm in Artificial Intelligence, and has been used as a visually decipherable clustering tool of machine-part cell formation. The objective of the paper is to cluster the binary machine-part matrix through visually decipherable cluster of SOM color-coding and labelling via the SOM map nodes in such a way that the part families are processed in that machine cells. The Umatrix, component plane, principal component projection, scatter plot and histogram of SOM have been reported in the present work for the successful visualization of the machine-part cell formation. Computational result with the proposed algorithm on a set of group technology problems available in the literature is also presented. The proposed SOM approach produced solutions with a grouping efficacy that is at least as good as any results earlier reported in the literature and improved the grouping efficacy for 70% of the problems and found immensely useful to both industry practitioners and researchers.Comment: 18 pages,3 table, 4 figure

Of cattle, sand flies and men : a systematic review of risk factor analyses for South Asian visceral leishmaniasis and implications for elimination

Background: Studies performed over the past decade have identified fairly consistent epidemiological patterns of risk factors for visceral leishmaniasis (VL) in the Indian subcontinent. Methods and Principal Findings: To inform the current regional VL elimination effort and identify key gaps in knowledge, we performed a systematic review of the literature, with a special emphasis on data regarding the role of cattle because primary risk factor studies have yielded apparently contradictory results. Because humans form the sole infection reservoir, clustering of kala-azar cases is a prominent epidemiological feature, both at the household level and on a larger scale. Subclinical infection also tends to show clustering around kala-azar cases. Within villages, areas become saturated over a period of several years; kala-azar incidence then decreases while neighboring areas see increases. More recently, post kalaazar dermal leishmaniasis (PKDL) cases have followed kala-azar peaks. Mud walls, palpable dampness in houses, and peridomestic vegetation may increase infection risk through enhanced density and prolonged survival of the sand fly vector. Bed net use, sleeping on a cot and indoor residual spraying are generally associated with decreased risk. Poor micronutrient status increases the risk of progression to kala-azar. The presence of cattle is associated with increased risk in some studies and decreased risk in others, reflecting the complexity of the effect of bovines on sand fly abundance, aggregation, feeding behavior and leishmanial infection rates. Poverty is an overarching theme, interacting with individual risk factors on multiple levels. Conclusions: Carefully designed demonstration projects, taking into account the complex web of interconnected risk factors, are needed to provide direct proof of principle for elimination and to identify the most effective maintenance activities to prevent a rapid resurgence when interventions are scaled back. More effective, short-course treatment regimens for PKDL are urgently needed to enable the elimination initiative to succeed