Anthropometry of Workers for some Specific Regions in Bangladesh

The anthropometric measurements are mainly used to design human fitted tools clothing workstation personal equipment comfortable devices that increases human comfort safety quality of working and efficiency The intension of this paper is to forecast the anthropometric characteristics of Bangladeshi population by geographical region Khulna Division- Khulna Bagerhat Chuadanga Jessore Kushtia Magura Meherpur Narail and Satkhira age and gender which are used for various purposes of design We have considered here both male and female This is based on the study done with several industries from districts in Khulna Division of Bangladesh There are almost 300 measurements in anthropometry but used only 36 of them because these measurements are commonly used in industry The measurements are almost same and does not vary too much except the tribal region Here we calculated 5P 50P and 95P which will help to design an adjustable system which will consider flexible to al

Fuzzy Clustering-Based Ensemble Approach to Predicting Indian Monsoon

Indian monsoon is an important climatic phenomenon and a global climatic marker. Both statistical and numerical prediction schemes for Indian monsoon have been widely studied in literature. Statistical schemes are mainly based on regression or neural networks. However, the variability of monsoon is significant over the years and a single model is often inadequate. Meteorologists revise their models on different years based on prevailing global climatic incidents like El-Niño. These indices often have degree of severity associated with them. In this paper, we cluster the monsoon years based on their fuzzy degree of associativity to these climatic event patterns. Next, we develop individual prediction models for the year clusters. A weighted ensemble of these individual models is used to obtain the final forecast. The proposed method performs competitively with existing forecast models

Isolation, Characterization, and Identification of Gut Bacteria from Piscine Ectoparasite, Argulus Bengalensis (Ramakrishna 1951) and their Relationship with Haematophagy

Gut microbiome plays a pivotal role in health and nutrition of most organisms. Argulus bengalensis is a haematophagus ectoparasite of fresh water carp and its infection causes extensive damage to fish farms. The present study aims at isolation, characterization and identification of the gut bacteria from Argulus bengalensis and to decipher its potential contribution in haematophagy of the parasite. The gut bacteria were isolated, cultured and identified based on analysis of its morphological, physiological and biochemical features as well as 16s rDNA analyses against the NCBI genetic database. Antibiotic sensitivity was tested. Haemolytic activity and ability of the isolates to produce anticoagulant substance were also tested to justify the hypothesis. Two isolates were identified to be similar type strains of Acenatobacter baumanii and Aeromonas hydrophila respectively which have accession number MW811800 and MW806655 respectively. Both bacteria were found sensitive to most antibiotics. Both Acenatobacter baumanii and Aeromonas hydrophila showed their haemolytic activities and able to secrete anticoagulant substances establishing their mutualistic association which increase the fitness of the parasitic host facilitating haematophagy. The outcome of the study thus may provide a scientific direction to develop novel methods to control of Argulosis

Our stories: Women speak out against HIV and AIDS—An interactive communication package for rural low-literate women

The National AIDS Control Organisation (NACO) estimates that there are over 5.1 million people living with HIV and AIDS in India. Among new infections reported in 2006, 88 percent were reported in the reproductive age group (15–49 years). The virus is spreading rapidly among women, including married and monogamous women, and adolescent girls. Existing literature shows that women\u27s vulnerability is compounded due to their gendered disadvantage in information access, literacy, and decision-making. This disadvantage is particularly acute in the case of married women in rural India. NACO has indicated the need to develop audience-appropriate strategies for communicating HIV-related information. To ensure that rural low- and neo-literate women are equipped with correct information about HIV and AIDS it is necessary to design communication strategies that are evidence-based, participatory, and take women\u27s visual perceptions into account. As detailed in this brief, the Population Council and partners undertook a participatory communications project to develop visually appropriate communication materials on HIV and AIDS for married rural women

Computed tomography guided fine needle aspiration cytology of pulmonary mass lesions in a tertiary care hospital: A two-year prospective study

Background: Percutaneous or transthoracic fine needle aspiration cytology (FNAC) is a rapidly emerging diagnostic modality to assess the nature of radiologically demonstrated lung lesions. Aims: The present study was conducted to evaluate the usefulness of computed tomography (CT)-guided FNAC in the diagnosis of pulmonary mass lesions. Materials and Methods: The present prospective study was carried out on 74 cases of radiologically diagnosed pulmonary mass lesions involving the periphery of the lung parenchyma with strong clinical suspicion of pulmonary neoplasm. CT-guided transthoracic fine needle aspiration was performed and cytology smears were stained with May-Grόnwald-Giemsa (MGG) stain and conventional Papanicolaou (Pap) stain. Smears were broadly categorized into unsatisfactory, benign, suspicious of malignancy and malignant lesion. The cytological diagnosis was compared with subsequent histopathology report where it was necessary. Results: A total of 74 cases of pulmonary mass lesions were included in the present study, of which 58 were males (78.4%). The mean age of the patients was 51.6 years, but the mean age in case of malignant lesions was 62.5 years. Cough was the most common respiratory symptoms (100%) followed by weight loss (91.9%) and fever (62.2%). Maximum cases of benign lesions were chronic non-specific inflammation (10.8%; 8 cases) followed by tuberculosis (8.1%). Regarding the malignant categories, non-small cell carcinoma, not otherwise specified (NOS) (13.5%; 10 cases) was the most common malignancy followed by adenocarcinoma (10.8%; 8 cases), small cell carcinoma (8.1%; 6 cases) and squamous cell carcinoma (6.7%, 5 cases) respectively. All the 38 cases of malignant lesions were confirmed by histopathology. Out of 10 cases of non-small cell carcinoma, NOS 4 cases were diagnosed histopathologically as poorly differentiated adenocarcinoma, 2 cases as high grade squamous cell carcinoma, 2 cases as large cell carcinoma, 1 case as pleomorphic carcinoma and 1 case as adenosquamous carcinoma. Conclusion: CT guided FNAC is a less expensive, simple, fast and reliable method for diagnosis of pulmonary mass lesions

Identification of Indian monsoon predictors using climate network and density-based spatial clustering

The Indian summer monsoon is a complex climatic phenomenon with a large variability over the years. The climatic predictors affecting the phenomenon evolve with time, and consequently new predictors have gained importance. Several statistical approaches are being explored in the literature to identify the potential predictors influencing the Indian summer monsoon. A complex network paradigm involving climatic variables at the grids over the globe has been proposed for predictor identification and monsoon prediction. The approach initiates with the identification of communities in the climate network considering mutual similarity and the influence of climate variables of grids on the Indian summer monsoon. Spatial clustering is performed over the communities to identify the geographical regions of significance. The climatic predictors extracted from variables of these regions are evaluated in terms of their correlation with the monsoon as well as their forecasting skills in predicting the summer monsoon of the country. The newly identified predictors forecast monsoon with an error of 4.2%, which is significant for the prediction of the complex phenomenon of monsoon

N (2013) Genetic algorithm and fuzzyrough based dimensionality reduction applied on real valued dataset

Abstract: Real-world datasets are often vague and redundant, creating problem to take decision accurately. Very recently, Rough-set theory has been used successfully for dimensionality reduction but is applicable only on discrete dataset. Discretisation of data leads to information loss and may add inconsistency in the datasets. The paper aims at applying fuzzy-rough concept to overcome the above limitations. However, handling of non discretized values increases computational complexity of the system. Therefore, to build an efficient classifier Genetic Algorithm (GA) has been applied to obtain optimal subset of attributes, sufficient to classify the objects. The proposed algorithm reduces dimensionality to a great extent without degrading the accuracy of classification and avoid of being trapped at local minima. Results are compared with the existing algorithms, demonstrate compatible outcome

Spectrophotometric Assessment of Heme Oxygenase-1 Activity in Leishmania-infected Macrophages

Heme oxygenase-1 (HO-1) is a stress responsive enzyme that metabolizes heme and releases free iron, carbon monoxide (CO), and biliverdin (BV), which rapidly undergoes conversion to bilirubin (BL). Estimation of bilirubin is the basis of HO-1 assay. HO-1 activity is widely employed to determine antioxidant response of cells under different physiological stress environment. Intra-macrophage infection often acts as such a stress inducer and measurement of HO-1 activity in infected cells indicates the ability of pathogens towards modulating oxidative response of host. The present protocol describes analysis of HO-1 activity in infected macrophages by spectrophotometric method, which is much less complex and therefore advantageous over other methods like high-performance liquid chromatography, radiochemical methods and detection of CO by gas chromatography. The main steps include: (1) Preparation of macrophage microsomal fraction containing HO-1 (2) Isolation of rat liver cytosolic fraction containing biliverdin reductase and (3) Assessment of heme oxygenase-1 activity by spectrophotometric detection of bilirubin. This method provides a simple and sensitive approach to measure cellular antioxidant response under infected condition

Predictor-Year Subspace Clustering Based Ensemble Prediction of Indian Summer Monsoon

Forecasting the Indian summer monsoon is a challenging task due to its complex and nonlinear behavior. A large number of global climatic variables with varying interaction patterns over years influence monsoon. Various statistical and neural prediction models have been proposed for forecasting monsoon, but many of them fail to capture variability over years. The skill of predictor variables of monsoon also evolves over time. In this article, we propose a joint-clustering of monsoon years and predictors for understanding and predicting the monsoon. This is achieved by subspace clustering algorithm. It groups the years based on prevailing global climatic condition using statistical clustering technique and subsequently for each such group it identifies significant climatic predictor variables which assist in better prediction. Prediction model is designed to frame individual cluster using random forest of regression tree. Prediction of aggregate and regional monsoon is attempted. Mean absolute error of 5.2% is obtained for forecasting aggregate Indian summer monsoon. Errors in predicting the regional monsoons are also comparable in comparison to the high variation of regional precipitation. Proposed joint-clustering based ensemble model is observed to be superior to existing monsoon prediction models and it also surpasses general nonclustering based prediction models

Aggregate planning problem solving using linear programming method

Aggregate production planning is concerned with the determination of production, inventory, and work force levels to meet fluctuating demand requirements over a planning horizon that ranges from six months to one year. An aggregate planning model based on linear programming is developed here. In our paper we mainly focus on experimenting with workforce. We mainly follow changing three criteria of workforce such as fixed workforce, changing workforce and the combination of fixed and changing workforce. Using these three criteria the total cost of production of a cable industry is reduced. The percentage of cost reduction is different in these criteria’s. TORA software has been used to evaluate the optimized value