An Assessment of Poverty Studies in India with Special Reference to Economic Reforms

As it is well-known, the study of poverty is extremely important on moral and philosophical and also, political grounds. Further, evidences are available to show that poverty affects growth adversely. We, therefore, have made an attempt to review some of the important studies on poverty in India. The concept of poverty relates to socially perceived deprivation with respect to basic minimum needs. In the Indian context, poverty is measured in terms of a specified normative poverty line reflecting the minimum living standard of the people. Defining a poverty line is, therefore, the first step in estimating poverty. According to the Expert Group (1993), a poverty line, dividing the poor from the non-poor, is used by putting a price on the minimum required consumption levels of food, clothing, shelter, fuel and health care, etc. In equal practice however, the poverty lines are normative only in terms of calorie requirements of the diet. Since the beginning of sixties a number of studies have been conducted to estimate the incidence of poverty and to find out the determinants of poverty. Different methods have been used to estimate the incidence. All these are, however, based on the use of poverty lines and the distribution of expenditure of households. These lines have been updated by using alternative price index numbers, and, expectedly, it has resulted in different estimates. Even the base year poverty lines, used by various authors, are different. Various measures of poverty to know its severity and depth have also been estimated by the researchers. The relationships between the incidence of poverty and its determinants have been estimated by using different variables and models.

Strong Convergence Theorems for Strictly Asymptotically Pseudocontractive Mappings in Hilbert Spaces

We propose a new (CQ) algorithm for strictly asymptotically pseudo-contractive mappings and obtain a strong convergence theorem for this class ofmappings in the framework of Hilbert spaces.DOI : http://dx.doi.org/10.22342/jims.16.1.29.25-3

Storage Induced Changes in Sensory Characteristics and Viscosity of Cocoa and Whey Protein Enriched Functional Dairy Drink

The functional dairy drink product developed in the present study was packaged in LDPE pouches stored at refrigeration temperature 4±1°C. The results of storage studies depict that the product can be stored upto 18 days at 4±1°C without significantly affecting its sensory qualities. Overall acceptability scores decreased from initial 93.0 to 69.2 after 18 days of storage at 4±1°C for the drink enriched with whey protein; for the drink enriched with whey protein and cocoa, the scores decreased from 93.4 to 72.4. The consistency score of the product decreased from 27.5 to 19.5 for whey protein enhanced drink and from 27.7 to 20.6 in case of cocoa & whey protein enriched product after 18 days of storage at 4±1°C in LDPE pouch. The Color and appearance score decreased from 18.6 to 14.1 for the whey protein enriched drink and to 15.3 for the product enriched with cocoa & whey protein. The study clearly depicted that the sensory attributes viz. overall acceptability, flavor, taste, consistency and color & appearance scores between 15th and 18th day of storage of both the products differed significantly; indicating that the products were shelf stable upto 15th day when stored at 4±1°C

PHARMACOGNOSTICAL AND PRELIMINARY PHYTOCHEMICAL INVESTIGATIONS OF AERIAL PARTS OF TRICHODESMA INDICUM R. BR.

Objective: This study was undertaken to carry out pharmacognostical studies and phytochemical studies on aerial parts of Trichodesma indicum R. Br belonging to the family Boraginaceae.Methods: The aerial parts of plant leaf and stem were evaluated for pharmacognostical studies such as macroscopy, microscopy, powder study, and quantitative microscopy. The powder was evaluated for proximate analysis like ash vale, extracting value, moisture content, swelling index, elemental analysis, fluorescence analysis, and preliminary phytochemical studies.Results: Transverse section of leaf of T. indicum R. Br. showed presence of covering trichomes with bulbous base upper and lower epidermis, collenchyma, prisms of calcium oxalate, vascular bundle and palisade cells. Surface preparation showed the presence of wavy epidermal cells, anomocytic stomata, anisocytic stomata, trichomes. Transverse section of Stem of Trichodesma indicum R. Br showed the presence of trichomes with, epidermis, hypodermis, cortex, xylem and pith. Powder study of aerial parts of T. indicum R. Br showed the presence of trichomes, xylem vessels, parenchyma, epidermal cells, fibres, calcium oxalate crystals. The powder of aerial parts was evaluated for proximate analysis such as ash value, extractive value, moisture content, total solid content, and the swelling index, which give idea about the presence of siliceous material, and amount of constituents extracted into different solvent. The elemental analysis of aerial parts showed that plant was free from heavy metal contamination i.e. arsenic, lead. The fluorescence analysis of plant powder showed that plant contains phenolic compounds. Qualitative chemical examination showed that the aerial parts of Trichodesma indicum R. Br, is credited with phytosterol, triterpenoids, tannins, phenolic compounds, carbohydrates, fixed oil, fatty acids mucilage.Conclusion: The study reveals specific identifying characteristics for the particular crude drug which will be of significant use in identification and control to adulteration of the raw drug and can serve as a reference for any further investigations.Â

PHARMACOGNOSTIC AND PHYTOCHEMICAL EVALUATION OF TREMA ORIENTALIS LEAF

Trema orientalis (Ulmaceae) is native to India. This tree species has been of interest to researchers because it is a medicinal plant employed in the Indian indigenous system of medicine. Pharmacognostic standardization, physic-chemical evaluation of the leafs of Trema orientalis was carried out to determine its macro-and micro-scopical characters and also some insoluble ash and sulphated ash values, alcohol-and water-soluble extractive values were determined for phytochemical evaluations. Preliminary phytochemical screening was also done to detect different phytoconstituents. Microscopically, Leaf showed trichomes, Lamina, midrib regions, stomata and calcium oxalate crystals. Powder microscopy showed mesophyll region, abundant xylem vessels with annular thickenings and xylem vessels, Unicellular, multiseriate covering trichomes and glandular trichomes, Rosette and prism shape calcium oxalate crystals, Anomocytic stomata. Total ash was approximately two times and four times more than acid insoluble and water soluble as, respectively Ethanol soluble extractive was approximately two times higher than water soluble extractive. TLC of petroleum ether and ethanol extract showed five spots using Hexane: Ethyl acetate (12:4) and four spot using Choloroform: Ethyl acetate (5:4). Phytochemically, root exhibited phytosterols, Flavanoids, Tannin and phenolic compounds

School environment assessment tools to address behavioural risk factors of non-communicable diseases: A scoping review

We aimed to identify, describe and analyse school environment assessment (SEA) tools that address behavioural risk factors (unhealthy diet, physical inactivity, tobacco and alcohol consumption) for non-communicable diseases (NCD). We searched in MEDLINE and Web of Science, hand-searched reference lists and contacted experts. Basic characteristics, measures assessed and measurement properties (validity, reliability, usability) of identified tools were extracted. We narratively synthesized the data and used content analysis to develop a list of measures used in the SEA tools. Twenty-four SEA tools were identified, mostly from developed countries. Out of these, 15 were questionnaire based, 8 were checklists or observation based tools and one tool used a combined checklist/observation based and telephonic questionnaire approach. Only 1 SEA tool had components related to all the four NCD risk factors, 2 SEA tools has assessed three NCD risk factors (diet/nutrition, physical activity, tobacco), 10 SEA tools has assessed two NCD risk factors (diet/nutrition and physical activity) and 11 SEA tools has assessed only one of the NCD risk factor. Several measures were used in the tools to assess the four NCD risk factors, but tobacco and alcohol was sparingly included. Measurement properties were reported for 14 tools. The review provides a comprehensive list of measures used in SEA tools which could be a valuable resource to guide future development of such tools. A valid and reliable SEA tool which could simultaneously evaluate all NCD risk factors, that has been tested in different settings with varying resource availability is needed

Explainable Artificial Intelligence for Human Decision Support System in the Medical Domain

In this paper, we present the potential of Explainable Artificial Intelligence methods for decision support in medical image analysis scenarios. Using three types of explainable methods applied to the same medical image data set, we aimed to improve the comprehensibility of the decisions provided by the Convolutional Neural Network (CNN). In vivo gastral images obtained by a video capsule endoscopy (VCE) were the subject of visual explanations, with the goal of increasing health professionals’ trust in black-box predictions. We implemented two post hoc interpretable machine learning methods, called Local Interpretable Model-Agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP), and an alternative explanation approach, the Contextual Importance and Utility (CIU) method. The produced explanations were assessed by human evaluation. We conducted three user studies based on explanations provided by LIME, SHAP and CIU. Users from different non-medical backgrounds carried out a series of tests in a web-based survey setting and stated their experience and understanding of the given explanations. Three user groups (n = 20, 20, 20) with three distinct forms of explanations were quantitatively analyzed. We found that, as hypothesized, the CIU-explainable method performed better than both LIME and SHAP methods in terms of improving support for human decision-making and being more transparent and thus understandable to users. Additionally, CIU outperformed LIME and SHAP by generating explanations more rapidly. Our findings suggest that there are notable differences in human decision-making between various explanation support settings. In line with that, we present three potential explainable methods that, with future improvements in implementation, can be generalized to different medical data sets and can provide effective decision support to medical experts