Experimental evidence on promotion of electric and improved biomass cookstoves.

Improved cookstoves (ICS) can deliver "triple wins" by improving household health, local environments, and global climate. Yet their potential is in doubt because of low and slow diffusion, likely because of constraints imposed by differences in culture, geography, institutions, and missing markets. We offer insights about this challenge based on a multiyear, multiphase study with nearly 1,000 households in the Indian Himalayas. In phase I, we combined desk reviews, simulations, and focus groups to diagnose barriers to ICS adoption. In phase II, we implemented a set of pilots to simulate a mature market and designed an intervention that upgraded the supply chain (combining marketing and home delivery), provided rebates and financing to lower income and liquidity constraints, and allowed households a choice among ICS. In phase III, we used findings from these pilots to implement a field experiment to rigorously test whether this combination of upgraded supply and demand promotion stimulates adoption. The experiment showed that, compared with zero purchase in control villages, over half of intervention households bought an ICS, although demand was highly price-sensitive. Demand was at least twice as high for electric stoves relative to biomass ICS. Even among households that received a negligible price discount, the upgraded supply chain alone induced a 28 percentage-point increase in ICS ownership. Although the bundled intervention is resource-intensive, the full costs are lower than the social benefits of ICS promotion. Our findings suggest that market analysis, robust supply chains, and price discounts are critical for ICS diffusion

Hemoglobin E syndromes in Pakistani population

<p>Abstract</p> <p>Background</p> <p>Hemoglobin E is an important hemoglobin variant with a worldwide distribution. A number of hemoglobinopathies have been reported from Pakistan. However a comprehensive description of hemoglobin E syndromes for the country was never made. This study aimed to describe various hemoglobin E disorders based on hematological parameters and chromatography. The sub-aim was to characterize hemoglobin E at molecular level.</p> <p>Methods</p> <p>This was a hospital based study conducted prospectively for a period of one year extending from January 1 to December 31, 2008. EDTA blood samples were analyzed for completed blood counts and hemoglobin variants through automated hematology analyzer and Bio-Rad beta thalassaemia short program respectively. Six samples were randomly selected to characterize HbE at molecular level through RFLP-PCR utilizing <it>Mnl</it>I restriction enzyme.</p> <p>Results</p> <p>During the study period, 11403 chromatograms were analyzed and Hb E was detected in 41 (or 0.36%) samples. Different hemoglobin E syndromes identified were HbEA (n = 20 or 49%), HbE/β-thalassemia (n = 14 or 34%), HbEE (n = 6 or 15%) and HbE/HbS (n = 1 or 2%). Compound heterozygosity for HbE and beta thalassaemia was found to be the most severely affected phenotype. RFLP-PCR utilizing <it>Mnl</it>I successfully characterized HbE at molecular level in six randomly selected samples.</p> <p>Conclusions</p> <p>Various HbE phenotypes are prevalent in Pakistan with HbEA and HbE/β thalassaemia representing the most common syndromes. Chromatography cannot only successfully identify hemoglobin E but also assist in further characterization into its phenotype including compound heterozygosity. Definitive diagnosis of HbE can easily be achieved through RFLP-PCR.</p

Accurate molecular classification of cancer using simple rules

<p>Abstract</p> <p>Background</p> <p>One intractable problem with using microarray data analysis for cancer classification is how to reduce the extremely high-dimensionality gene feature data to remove the effects of noise. Feature selection is often used to address this problem by selecting informative genes from among thousands or tens of thousands of genes. However, most of the existing methods of microarray-based cancer classification utilize too many genes to achieve accurate classification, which often hampers the interpretability of the models. For a better understanding of the classification results, it is desirable to develop simpler rule-based models with as few marker genes as possible.</p> <p>Methods</p> <p>We screened a small number of informative single genes and gene pairs on the basis of their depended degrees proposed in rough sets. Applying the decision rules induced by the selected genes or gene pairs, we constructed cancer classifiers. We tested the efficacy of the classifiers by leave-one-out cross-validation (LOOCV) of training sets and classification of independent test sets.</p> <p>Results</p> <p>We applied our methods to five cancerous gene expression datasets: leukemia (acute lymphoblastic leukemia [ALL] vs. acute myeloid leukemia [AML]), lung cancer, prostate cancer, breast cancer, and leukemia (ALL vs. mixed-lineage leukemia [MLL] vs. AML). Accurate classification outcomes were obtained by utilizing just one or two genes. Some genes that correlated closely with the pathogenesis of relevant cancers were identified. In terms of both classification performance and algorithm simplicity, our approach outperformed or at least matched existing methods.</p> <p>Conclusion</p> <p>In cancerous gene expression datasets, a small number of genes, even one or two if selected correctly, is capable of achieving an ideal cancer classification effect. This finding also means that very simple rules may perform well for cancerous class prediction.</p

Endocrinologic, neurologic, and visual morbidity after treatment for craniopharyngioma

Craniopharyngiomas are locally aggressive tumors which typically are focused in the sellar and suprasellar region near a number of critical neural and vascular structures mediating endocrinologic, behavioral, and visual functions. The present study aims to summarize and compare the published literature regarding morbidity resulting from treatment of craniopharyngioma. We performed a comprehensive search of the published English language literature to identify studies publishing outcome data of patients undergoing surgery for craniopharyngioma. Comparisons of the rates of endocrine, vascular, neurological, and visual complications were performed using Pearson’s chi-squared test, and covariates of interest were fitted into a multivariate logistic regression model. In our data set, 540 patients underwent surgical resection of their tumor. 138 patients received biopsy alone followed by some form of radiotherapy. Mean overall follow-up for all patients in these studies was 54 ± 1.8 months. The overall rate of new endocrinopathy for all patients undergoing surgical resection of their mass was 37% (95% CI = 33–41). Patients receiving GTR had over 2.5 times the rate of developing at least one endocrinopathy compared to patients receiving STR alone or STR + XRT (52 vs. 19 vs. 20%, χ2P < 0.00001). On multivariate analysis, GTR conferred a significant increase in the risk of endocrinopathy compared to STR + XRT (OR = 3.45, 95% CI = 2.05–5.81, P < 0.00001), after controlling for study size and the presence of significant hypothalamic involvement. There was a statistical trend towards worse visual outcomes in patients receiving XRT after STR compared to GTR or STR alone (GTR = 3.5% vs. STR 2.1% vs. STR + XRT 6.4%, P = 0.11). Given the difficulty in obtaining class 1 data regarding the treatment of this tumor, this study can serve as an estimate of expected outcomes for these patients, and guide decision making until these data are available

Renewable energy harvesting for low power wireless monitoring networks

—Energy Harvesting Technologies for wireless electronics networks have undergone a tremendous development in the recent past. Several micro level energy generating units have been developed to convert variety of renewable energy sources to useable electrical energy. In order to integrate and exploit maximum benefits from renewable sources, an intelligent power electronics interface is mandatory. This paper presents a multiport power electronics circuitry to extract maximum energy from renewable energy sources and route it to power up wireless electronics networks. This new topology has ability to cope with different voltage level requirements and is capable of integrating several energy sources to satisfy the variable load demands. The sources can be utilized independently or concurrently. Surplus energy can also be stored and made available in case of absence of renewable energy sources. Analytical and simulation results in Continuous Conduction mode are presented and are validated by experimental results on a prototype modelfals

Negative resistance phenomenon in dual-frequency capacitively coupled plasma-enhanced chemical vapor deposition system for photovoltaic manufacturing process

The validity of effective frequency concept is investigated for dual-frequency (DF) capacitively coupled plasma (CCP) discharges by using particle-in-cell/Monte Carlo collision simulations. This concept helps in analyzing DF CCP discharges in a fashion similar to single-frequency (SF) CCP discharges with effective parameters. Unlike the driving frequency of SF CCP discharges, the effective frequency in DF CCP is dependent on the ratio of the two driving currents (or voltages) and this characteristic makes it possible to control the ion flux and the ion bombardment energy independently. This separate control principally allows to increase the ion flux and plasma density for high deposition rates, while keeping the ion mean energy constant at low values to prevent the bombardment of highly energetic ions at the substrate surface to avoid unwanted damage in the solar cell manufacturing. The abrupt transition of the effective frequency leads to the phenomenon of negative resistance which is one of the several physical phenomena associated uniquely with DF CCP discharges. Using effective frequency concept, the plasma characteristics have been investigated in the negative resistance regime for solar cell manufacturing. (C) 2012 American Institute of Physics. [doi:10.1063/1.3679107]open112sciescopu

Wireless sensors linked to climate financing for globally affordable clean cooking

Three billion of the world's poorest people mostly rely on solid biomass for cooking, with major consequences to health and environment. We demonstrate the untapped potential of wireless sensors connected to the 'internet of things' to make clean energy solutions affordable for those at the bottom of the energy pyramid. This breakthrough approach is demonstrated by a 17-month field study with 4,038 households in India. Major findings include: self-reported data on cooking duration have little correlation with actual usage data from sensors; sensor data revealed that the distribution of high and low users varied over time, and the actual mitigation of climate pollution was only 25% of the projected mitigation; climate credits were shown to significantly incentivize the use of cleaner technologies