Poverty and Wellbeing Impacts of Microfinance : What Do We Know?

Over the last 35 years, microfinance has been generally regarded as an effective policy tool in the fight against poverty. Yet, the question of whether access to credit leads to poverty reduction and improved wellbeing remains open. To address this question, we conduct a systematic review of the quantitative literature of microfinance’s impacts in the developing world, and develop a theory of change that links inputs to impacts on several welfare outcomes. Overall, we find that the limited comparability of outcomes and the heterogeneity of microfinance-lending technologies, together with a considerable variation in socio-economic conditions and contexts in which impact studies have been conducted, render the interpretation and generalization of findings intricate. Our results indicate that, at best, microfinance induces short-term dynamism in the financial life of the poor; however, we do not find compelling evidence that this dynamism leads to increases in income, consumption, human capital and assets, and, ultimately, a reduction in poverty

Differential livelihood adaptation to social-ecological change in coastal Bangladesh

Social-ecological changes, brought about by the rapid growth of the aquaculture industry and the increased occurrence of climatic stressors, have significantly affected the livelihoods of coastal communities in Asian mega-deltas. This paper explores the livelihood adaptation responses of households of different wealth classes, the heterogeneous adaptation opportunities, barriers and limits (OBLs) faced by these households and the dynamic ways in which these factors interact to enhance or impede adaptive capacities. A mixed methods approach was used to collect empirical evidence from two villages in coastal Bangladesh. Findings reveal that households’ adaptive capacities largely depend on their wealth status, which not only determine their availability of productive resources, but also empower them to navigate social-ecological change in desirable ways. Households operate within a shared response space, which is shaped by the broader socio-economic and political landscape, as well as their previous decisions that can lock them in to particular pathways. While an adaptive response may be effective for one social group, it may cause negative externalities that can undermine the adaptation options and outcomes of another group. Adaptation OBLs interact in complex ways; the extent to which these OBLs affect different households depend on the specific livelihood activities being considered and the differential values and interests they hold. To ensure more equitable and environmentally sustainable livelihoods in future, policies and programs should aim to expand households’ adaptation space by accounting for the heterogeneous needs and complex interdependencies between response processes of different groups

Numerical study of nonlinear heat transfer from a wavy surface to a high permeability medium with pseudo-spectral and smoothed particle methods

Motivated by petro-chemical geological systems, we consider the natural convection boundary layer flow from a vertical isothermal wavy surface adjacent to a saturated non-Darcian high permeability porous medium. High permeability is considered to represent geologically sparsely packed porous media. Both Darcian drag and Forchheimer inertial drag terms are included in the velocity boundary layer equation. A high permeability medium is considered. We employ a sinusoidal relation for the wavy surface. Using a set of transformations, the momentum and heat conservation equations are converted from an (x, y) coordinate system to an (x,η) dimensionless system. The two-point boundary value problem is then solved numerically with a pseudo-spectral method based on combining the Bellman–Kalaba quasi linearization method with the Chebyschev spectral collocation technique (SQLM). The SQLM computations are demonstrated to achieve excellent correlation with smoothed particle hydrodynamic (SPH) Lagrangian solutions. We study the effect of Darcy number (Da), Forchheimer number (Fs), amplitude wavelength (A) and Prandtl number (Pr) on the velocity and temperature distributions in the regime. Local Nusselt number is also computed for selected cases. The study finds important applications in petroleum engineering and also energy systems exploiting porous media and undulating (wavy) surface geometry. The SQLM algorithm is shown to be exceptionally robust and achieves fast convergence and excellent accuracy in nonlinear heat transfer simulations

Long-lasting XUV activation of helium nanodroplets for avalanche ionization

We study the dynamics of avalanche ionization of pure helium nanodroplets activated by a weak extreme-ultraviolet (XUV) pulse and driven by an intense near-infrared (NIR) pulse. In addition to a transient enhancement of ignition of a nanoplasma at short delay times $\sim200$~fs, long-term activation of the nanodroplets lasting up to a few nanoseconds is observed. Molecular dynamics simulations suggest that the short-term activation is caused by the injection of seed electrons into the droplets by XUV photoemission. Long-term activation appears due to electrons remaining loosely bound to photoions which form stable `snowball' structures in the droplets. Thus, we show that XUV irradiation can induce long-lasting changes of the strong-field optical properties of nanoparticles, potentially opening new routes to controlling avalanche-ionization phenomena in nanostructures and condensed-phase systems

Environmental contaminants as etiologic factors for diabetes.

For both type 1 and type 2 diabetes mellitus, the rates have been increasing in the United States and elsewhere; rates vary widely by country, and genetic factors account for less than half of new cases. These observations suggest environmental factors cause both type 1 and type 2 diabetes. Occupational exposures have been associated with increased risk of diabetes. In addition, recent data suggest that toxic substances in the environment, other than infectious agents or exposures that stimulate an immune response, are associated with the occurrence of these diseases. We reviewed the epidemiologic data that addressed whether environmental contaminants might cause type 1 or type 2 diabetes. For type 1 diabetes, higher intake of nitrates, nitrites, and N-nitroso compounds, as well as higher serum levels of polychlorinated biphenyls have been associated with increased risk. Overall, however, the data were limited or inconsistent. With respect to type 2 diabetes, data on arsenic and 2,3,7,8-tetrachlorodibenzo-p-dioxin relative to risk were suggestive of a direct association but were inconclusive. The occupational data suggested that more data on exposure to N-nitroso compounds, arsenic, dioxins, talc, and straight oil machining fluids in relation to diabetes would be useful. Although environmental factors other than contaminants may account for the majority of type 1 and type 2 diabetes, the etiologic role of several contaminants and occupational exposures deserves further study

Kualitas Hidup Pasien Diabetes Melitus Tipe 2 di Puskesmas Se Kota Kupang

Diabetes Mellitus is well known as a chronic disease which can lead to a decrease in quality of life in all domains. The study aims to explore the diabetic type 2 patient\u27s quality of life and find out the factors affecting in type 2 diabetic mellitus patients. The cross-sectional study design is used that included 65 patient with type 2 diabetes mellitus, in 11 public health centers of Kupang City. Data were collected by using Short Form Survey (SF-36) that assessed 8-scale health profile. Independent sample t-test is used to analyze the correlation between the factors affecting and the quality of life. the study showed that the QoL of DM patients decreased in all 8- health profile including physical functioning, social functioning, mental health, general health, pain, change in the role due to physical problems and emotional problems. The Study also showed there was a relationship between gender, duration of suffering from Diabetes mellitus, and complications to the quality of life. Male perceived a better quality of life than female

Large-scale computations on histology images reveal grade-differentiating parameters for breast cancer

BACKGROUND: Tumor classification is inexact and largely dependent on the qualitative pathological examination of the images of the tumor tissue slides. In this study, our aim was to develop an automated computational method to classify Hematoxylin and Eosin (H&E) stained tissue sections based on cancer tissue texture features. METHODS: Image processing of histology slide images was used to detect and identify adipose tissue, extracellular matrix, morphologically distinct cell nuclei types, and the tubular architecture. The texture parameters derived from image analysis were then applied to classify images in a supervised classification scheme using histologic grade of a testing set as guidance. RESULTS: The histologic grade assigned by pathologists to invasive breast carcinoma images strongly correlated with both the presence and extent of cell nuclei with dispersed chromatin and the architecture, specifically the extent of presence of tubular cross sections. The two parameters that differentiated tumor grade found in this study were (1) the number density of cell nuclei with dispersed chromatin and (2) the number density of tubular cross sections identified through image processing as white blobs that were surrounded by a continuous string of cell nuclei. Classification based on subdivisions of a whole slide image containing a high concentration of cancer cell nuclei consistently agreed with the grade classification of the entire slide. CONCLUSION: The automated image analysis and classification presented in this study demonstrate the feasibility of developing clinically relevant classification of histology images based on micro- texture. This method provides pathologists an invaluable quantitative tool for evaluation of the components of the Nottingham system for breast tumor grading and avoid intra-observer variability thus increasing the consistency of the decision-making process

Quantitative Methylation Profiles for Multiple Tumor Suppressor Gene Promoters in Salivary Gland Tumors

Methylation profiling of tumor suppressor gene (TSGs) promoters is quickly becoming a powerful diagnostic tool for the early detection, prognosis, and even prediction of clinical response to treatment. Few studies address this in salivary gland tumors (SGTs); hence the promoter methylation profile of various TSGs was quantitatively assessed in primary SGT tissue to determine if tumor-specific alterations could be detected.DNA isolated from 78 tumor and 17 normal parotid gland specimens was assayed for promoter methylation status of 19 TSGs by fluorescence-based, quantitative methylation-specific PCR (qMSP). The data were utilized in a binary fashion as well as quantitatively (using a methylation quotient) allowing for better profiling and interpretation of results..Screening promoter methylation profiles in SGTs showed considerable heterogeneity. The methylation status of certain markers was surprisingly high in even normal salivary tissue, confirming the need for such controls. Several TSGs were found to be associated with malignant SGTs, especially SDC. Further study is needed to evaluate the potential use of these associations in the detection, prognosis, and therapeutic outcome of these rare tumors

Grafting of Poly(methyl methacrylate) Brushes from Magnetite Nanoparticles Using a Phosphonic Acid Based Initiator by Ambient Temperature Atom Transfer Radical Polymerization (ATATRP)

Poly(methyl methacrylate) in the brush form is grown from the surface of magnetite nanoparticles by ambient temperature atom transfer radical polymerization (ATATRP) using a phosphonic acid based initiator. The surface initiator was prepared by the reaction of ethylene glycol with 2-bromoisobutyrl bromide, followed by the reaction with phosphorus oxychloride and hydrolysis. This initiator is anchored to magnetite nanoparticles via physisorption. The ATATRP of methyl methacrylate was carried out in the presence of CuBr/PMDETA complex, without a sacrificial initiator, and the grafting density is found to be as high as 0.90 molecules/nm2. The organic–inorganic hybrid material thus prepared shows exceptional stability in organic solvents unlike unfunctionalized magnetite nanoparticles which tend to flocculate. The polymer brushes of various number average molecular weights were prepared and the molecular weight was determined using size exclusion chromatography, after degrafting the polymer from the magnetite core. Thermogravimetric analysis, X-ray photoelectron spectra and diffused reflection FT-IR were used to confirm the grafting reaction

3D Protein structure prediction with genetic tabu search algorithm

Abstract Background Protein structure prediction (PSP) has important applications in different fields, such as drug design, disease prediction, and so on. In protein structure prediction, there are two important issues. The first one is the design of the structure model and the second one is the design of the optimization technology. Because of the complexity of the realistic protein structure, the structure model adopted in this paper is a simplified model, which is called off-lattice AB model. After the structure model is assumed, optimization technology is needed for searching the best conformation of a protein sequence based on the assumed structure model. However, PSP is an NP-hard problem even if the simplest model is assumed. Thus, many algorithms have been developed to solve the global optimization problem. In this paper, a hybrid algorithm, which combines genetic algorithm (GA) and tabu search (TS) algorithm, is developed to complete this task. Results In order to develop an efficient optimization algorithm, several improved strategies are developed for the proposed genetic tabu search algorithm. The combined use of these strategies can improve the efficiency of the algorithm. In these strategies, tabu search introduced into the crossover and mutation operators can improve the local search capability, the adoption of variable population size strategy can maintain the diversity of the population, and the ranking selection strategy can improve the possibility of an individual with low energy value entering into next generation. Experiments are performed with Fibonacci sequences and real protein sequences. Experimental results show that the lowest energy obtained by the proposed GATS algorithm is lower than that obtained by previous methods. Conclusions The hybrid algorithm has the advantages from both genetic algorithm and tabu search algorithm. It makes use of the advantage of multiple search points in genetic algorithm, and can overcome poor hill-climbing capability in the conventional genetic algorithm by using the flexible memory functions of TS. Compared with some previous algorithms, GATS algorithm has better performance in global optimization and can predict 3D protein structure more effectively