Do households gain from community-based natural resource management? An evaluation of community conservancies in Namibia

Community-based natural resource managementis an important strategy to conserve and sustainably use biodiversity and wildlife in Namibia. The authors examine the extent to which conservancies have been successful in meeting their primary goal of improving the lives of rural households. They evaluate the benefits of community conservancies in Namibia by asking three questions: Do conservancies increase household welfare? Are conservancies pro-poor? And, do participants in conservancies gain more relative to those who choose not to participate? The authors base their analyses on a 2002 survey covering seven conservancies and 1,192 households. The results suggest that community conservancies have a positive impact on household welfare. This impact is poverty-neutral in some regions and pro-poor in others. Further, welfare benefits from conservancies appear to be somewhat evenly distributed between participant and nonparticipant households.Poverty Monitoring&Analysis,Economic Theory&Research,Health Economics&Finance,Housing&Human Habitats,Decentralization,Housing&Human Habitats,VN-Acb Mis -- IFC-00535908,Poverty Monitoring&Analysis,Economic Theory&Research,Poverty Assessment

Integration of MS Teams as an LMS Tool for Language Classroom: An Analysis using SAMR Model

The digital transformation that happened in the field of education has made its way in teaching methodology supported by the integration of digital technologies. With the normalization of using digital technology among the generation Z and Alpha, the educational approaches are being constructed and reconstructed using latest digital technologies. The change in approaches can be identified from computer assisted to mobile assisted, blended to flipped and regular courses to Massive Open Online Courses (MOOC) or Learning Management System (LMS). In the context of language teaching and learning, the current digital technologies are being supportive tools in imparting language skills. Hence, this study aims to analyse the effectiveness of integrating Microsoft Teams (Teams) as an LMS tool to support language teaching using Substitution, Augmentation, Modification and Redefinition (SAMR) framework. The four degrees of the SAMR framework helps in understanding the effectiveness of the integration of digital technologies to language teaching methods. The findings of the study conclude that MS Teams can be considered as an efficient LMS tool for language teaching-learning process

Quantum circuit fidelity estimation using machine learning

The computational power of real-world quantum computers is limited by errors. When using quantum computers to perform algorithms which cannot be efficiently simulated classically, it is important to quantify the accuracy with which the computation has been performed. In this work we introduce a machine-learning-based technique to estimate the fidelity between the state produced by a noisy quantum circuit and the target state corresponding to ideal noise-free computation. Our machine learning model is trained in a supervised manner, using smaller or simpler circuits for which the fidelity can be estimated using other techniques like direct fidelity estimation and quantum state tomography. We demonstrate that, for simulated random quantum circuits with a realistic noise model, the trained model can predict the fidelities of more complicated circuits for which such methods are infeasible. In particular, we show the trained model may make predictions for circuits with higher degrees of entanglement than were available in the training set, and that the model may make predictions for non-Clifford circuits even when the training set included only Clifford-reducible circuits. This empirical demonstration suggests classical machine learning may be useful for making predictions about beyond-classical quantum circuits for some non-trivial problems.Comment: 27 pages, 6 figure

EVALUATION OF SERUM TOLL-LIKE RECEPTOR 4 AND NUCLEAR FACTOR-ΚBP65 PROTEINS IN ORAL SQUAMOUS CELL CARCINOMA

Objective: The present study is aimed to estimate the serum toll-like receptor 4 (sTLR 4) and nuclear factor-κB (NF-κB) p65 proteins in patients of oral squamous cell carcinoma (OSCC). Methods: The study was performed in prospective cases of 22 OSCC patients, 10 oral epithelial dysplasia patients, 8 control with chewing habits, and 4 control patients. The estimation of sTLR 4 and NF-κBp65 proteins was done by enzyme-linked immunosorbent assay method. The Pearson correlation test was performed to find out the relationship between these two proteins. Results: There was an increase in the sTLR 4 protein level in study groups OSCC, oral premalignant disorders, control with chewing habits, and control habits such as 1.31 ng/ml±1.06 ng/ml, 1.99 ng/ml±0.98 ng/ml, and 2.11 ng/ml±0.61 ng/ml, respectively, when comparable (p=0.008) to control patients with 0.60 ng/ml±0.24 ng/ml. However, in the case of serum level NF-κBp65 protein all the study groups including the control showed same values. The Pearson correlation test showed significant relationship (rpearson=0.91, [p<0.0005]) of these two proteins only in the OSCC patients. Conclusion: It can be concluded that serum levels of TLR 4 are increased in OSCC patients, but there was no variation seen for the NF-κBp65 protein. There is a strong interrelationship exist between the serum levels of TLR 4 and NF-κBp65 proteins in the OSCC patients only

Heat Energy Recovery Using Thermo Electric Generator

Internal combustion Engines converts only a small portion of heat energy into useful work resulting in a very low thermal efficiency. Most of the heat energy is lost in forms of cooling, exhaust gas, friction and unaccounted losses. Though energy lost in exhaust gas can be recovered by using thermoelectric generators (TEGs, also known as peltier element), which converts heat into electrical energy. A model has been prepared which helps TEG to extract heat from exhaust gas efficiently. This electrical energy obtained is used for powering hybrid drive

Facile and smart synthesis of benzyl salicylate via vapor-phase transesterification over monoliths coated with zirconia and its modified versions

Al(III)/ZrO2 catalysts with Al(III) content ranging from 5–25 wt% have been coated on honeycomb monoliths by dip & dry technique. These catalysts have also been prepared in their powder form. All the prepared catalysts have been characterized by surface acidity, crystallinity, functionality and morphology. The catalytic activity of Al(III)/ZrO2 has been determined in vapor-phase as well as liquid-phase transesterification of methyl salicylate with benzyl alcohol. The honeycomb form of the catalysts shows almost a 1.4 fold time increase in the catalytic activity when compared to the powder forms. Further, the effect of calcination temperature on the activity has also been discussed. The effect of poisoning of acid sites by adsorbed pyridine (base) and its effect on the surface acidity has been correlated with PXRD phases along with catalytic activity. Catalytic recyclability of Al(III)/ZrO2 catalysts has also been measured

Simvastatin decreases the level of heparin-binding protein in patients with acute lung injury

Background: Heparin-binding protein is released by neutrophils during inflammation and disrupts the integrity of the alveolar and capillary endothelial barrier implicated in the development of acute lung injury and systemic organ failure. We sought to investigate whether oral administration of simvastatin to patients with acute lung injury reduces plasma heparin-binding protein levels and improves intensive care unit outcome. Methods: Blood samples were collected from patients with acute lung injury with 48 h of onset of acute lung injury (day 0), day 3, and day 7. Patients were given placebo or 80 mg simvastatin for up to 14 days. Plasma heparin-binding protein levels from patients with acute lung injury and healthy volunteers were measured by ELISA. Results: Levels of plasma heparin-binding protein were significantly higher in patients with acute lung injury than healthy volunteers on day 0 (p = 0.011). Simvastatin 80 mg administered enterally for 14 days reduced plasma level of heparin-binding protein in patients. Reduced heparin-binding protein was associated with improved intensive care unit survival. Conclusions: A reduction in heparin-binding protein with simvastatin is a potential mechanism by which the statin may modify outcome from acute lung injury

Systematic Evaluation of Candidate Blood Markers for Detecting Ovarian Cancer

Epithelial ovarian cancer is a significant cause of mortality both in the United States and worldwide, due largely to the high proportion of cases that present at a late stage, when survival is extremely poor. Early detection of epithelial ovarian cancer, and of the serous subtype in particular, is a promising strategy for saving lives. The low prevalence of ovarian cancer makes the development of an adequately sensitive and specific test based on blood markers very challenging. We evaluated the performance of a set of candidate blood markers and combinations of these markers in detecting serous ovarian cancer.We selected 14 candidate blood markers of serous ovarian cancer for which assays were available to measure their levels in serum or plasma, based on our analysis of global gene expression data and on literature searches. We evaluated the performance of these candidate markers individually and in combination by measuring them in overlapping sets of serum (or plasma) samples from women with clinically detectable ovarian cancer and women without ovarian cancer. Based on sensitivity at high specificity, we determined that 4 of the 14 candidate markers--MUC16, WFDC2, MSLN and MMP7--warrant further evaluation in precious serum specimens collected months to years prior to clinical diagnosis to assess their utility in early detection. We also reported differences in the performance of these candidate blood markers across histological types of epithelial ovarian cancer.By systematically analyzing the performance of candidate blood markers of ovarian cancer in distinguishing women with clinically apparent ovarian cancer from women without ovarian cancer, we identified a set of serum markers with adequate performance to warrant testing for their ability to identify ovarian cancer months to years prior to clinical diagnosis. We argued for the importance of sensitivity at high specificity and of magnitude of difference in marker levels between cases and controls as performance metrics and demonstrated the importance of stratifying analyses by histological type of ovarian cancer. Also, we discussed the limitations of studies (like this one) that use samples obtained from symptomatic women to assess potential utility in detection of disease months to years prior to clinical detection

Tissue-specific gene expression templates for accurate molecular characterization of the normal physiological states of multiple human tissues with implication in development and cancer studies

<p>Abstract</p> <p>Background</p> <p>To elucidate the molecular complications in many complex diseases, we argue for the priority to construct a model representing the normal physiological state of a cell/tissue.</p> <p>Results</p> <p>By analyzing three independent microarray datasets on normal human tissues, we established a quantitative molecular model GET, which consists of 24 tissue-specific <it>G</it>ene <it>E</it>xpression <it>T</it>emplates constructed from a set of 56 genes, for predicting 24 distinct tissue types under disease-free condition. 99.2% correctness was reached when a large-scale validation was performed on 61 new datasets to test the tissue-prediction power of GET. Network analysis based on molecular interactions suggests a potential role of these 56 genes in tissue differentiation and carcinogenesis.</p> <p>Applying GET to transcriptomic datasets produced from tissue development studies the results correlated well with developmental stages. Cancerous tissues and cell lines yielded significantly lower correlation with GET than the normal tissues. GET distinguished melanoma from normal skin tissue or benign skin tumor with 96% sensitivity and 89% specificity.</p> <p>Conclusions</p> <p>These results strongly suggest that a normal tissue or cell may uphold its normal functioning and morphology by maintaining specific chemical stoichiometry among genes. The state of stoichiometry can be depicted by a compact set of representative genes such as the 56 genes obtained here. A significant deviation from normal stoichiometry may result in malfunction or abnormal growth of the cells.</p