1,886 research outputs found

    Using HCMM Thermal Data to Improve Classification of MSS Data

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    Spectral overlap between urban and rural land use/land cover categories can lead to unacceptable map accuracy levels in the classification of LANDSAT multispectral scanner (MSS) data. The four MSS bands used alone are not always adequate to distinguish among various land uses and cover types having similar spectral responses. The use of thermal data from the Heat Capacity Mapping Mission (HCMM) satellite as a means of improving MSS land cover classification accuracies for urban versus rural categories was investigated. The approaches used to integrate the HCMM data are described

    Genetic Optimization Using Derivatives: The rgenoud Package for R

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    genoud is an R function that combines evolutionary algorithm methods with a derivative-based (quasi-Newton) method to solve difficult optimization problems. genoud may also be used for optimization problems for which derivatives do not exist. genoud solves problems that are nonlinear or perhaps even discontinuous in the parameters of the function to be optimized. When the function to be optimized (for example, a log-likelihood) is nonlinear in the model's parameters, the function will generally not be globally concave and may have irregularities such as saddlepoints or discontinuities. Optimization methods that rely on derivatives of the objective function may be unable to find any optimum at all. Multiple local optima may exist, so that there is no guarantee that a derivative-based method will converge to the global optimum. On the other hand, algorithms that do not use derivative information (such as pure genetic algorithms) are for many problems needlessly poor at local hill climbing. Most statistical problems are regular in a neighborhood of the solution. Therefore, for some portion of the search space, derivative information is useful. The function supports parallel processing on multiple CPUs on a single machine or a cluster of computers.

    Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning

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    There is growing interest in estimating and analyzing heterogeneous treatment effects in experimental and observational studies. We describe a number of meta-algorithms that can take advantage of any supervised learning or regression method in machine learning and statistics to estimate the Conditional Average Treatment Effect (CATE) function. Meta-algorithms build on base algorithms---such as Random Forests (RF), Bayesian Additive Regression Trees (BART) or neural networks---to estimate the CATE, a function that the base algorithms are not designed to estimate directly. We introduce a new meta-algorithm, the X-learner, that is provably efficient when the number of units in one treatment group is much larger than in the other, and can exploit structural properties of the CATE function. For example, if the CATE function is linear and the response functions in treatment and control are Lipschitz continuous, the X-learner can still achieve the parametric rate under regularity conditions. We then introduce versions of the X-learner that use RF and BART as base learners. In extensive simulation studies, the X-learner performs favorably, although none of the meta-learners is uniformly the best. In two persuasion field experiments from political science, we demonstrate how our new X-learner can be used to target treatment regimes and to shed light on underlying mechanisms. A software package is provided that implements our methods

    Choline transporter-like protein 4 (CTL4) links to non-neuronal acetylcholine synthesis.

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    Synthesis of acetylcholine (ACh) by non-neuronal cells is now well established and plays diverse physiologic roles. In neurons, the Na(+) -dependent, high affinity choline transporter (CHT1) is absolutely required for ACh synthesis. In contrast, some non-neuronal cells synthesize ACh in the absence of CHT1 indicating a fundamental difference in ACh synthesis compared to neurons. The aim of this study was to identify choline transporters, other than CHT1, that play a role in non-neuronal ACh synthesis. ACh synthesis was studied in lung and colon cancer cell lines focusing on the choline transporter-like proteins, a five gene family choline-transporter like protein (CTL)1-5. Supporting a role for CTLs in choline transport in lung cancer cells, choline transport was Na(+) -independent and CTL1-5 were expressed in all cells examined. CTL1, 2, and 5 were expressed at highest levels and knockdown of CTL1, 2, and 5 decreased choline transport in H82 lung cancer cells. Knockdowns of CTL1, 2, 3, and 5 had no effect on ACh synthesis in H82 cells. In contrast, knockdown of CTL4 significantly decreased ACh secretion by both lung and colon cancer cells. Conversely, increasing expression of CTL4 increased ACh secretion. These results indicate that CTL4 mediates ACh synthesis in non-neuronal cell lines and presents a mechanism to target non-neuronal ACh synthesis without affecting neuronal ACh synthesis

    Sexual abuse and HIV-risk behaviour among black and minority ethnic men who have sex with men in the UK

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    Black and minority ethnic (BME) men who have sex with men (MSM) face a major burden in relation to HIV infection. It was hypothesised that sexual abuse would predict sexual risk-taking, and that this relationship would be mediated by victimisation and maladaptive coping variables. Four hundred and thirty-two BME MSM completed the survey; 54% reported no sexual abuse and 27% reported sexual abuse. Mann–Whitney tests showed that MSM with a history of sexual abuse reported higher frequency of drug use, and of homophobia and racism than those reporting no prior sexual abuse. A structural equation model showed that the experience of sexual abuse was positively associated with sexual risk-taking and that this relationship was mediated by victimisation variables: frequency of racism and frequency of homophobia and by the maladaptive coping variable: frequency of drug use. The findings can inform the design of psycho-sexual and behavioural interventions for BME MSM

    SynthoPlate: A platelet-inspired hemostatic nanotechnology for treatment of bleeding complications

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    Platelet transfusions are routinely used in the clinic to treat bleeding complications stemming from trauma, surgery, malignancy-related bone marrow dysfunctions, and congenital or drug-related defects platelet defects. These transfusions primarily use allogeneic platelet concentrates (PCs) that pose issues of limited availability and portability, high risk of bacterial contamination, very short shelf life (~3-5 days), need for antigen matching and several biologic side effects. While robust research is being directed at resolving some of these issues, there is in parallel a significant clinical interest in synthetic platelet substitutes that can render efficient hemostasis by leveraging and amplifying endogenous clotting mechanisms while avoiding the above issues. To this end, we have developed a unique platelet-inspired synthetic hemostat technology called the SynthoPlate® (US Patent 9107845). Since platelets promote primary hemostasis via adhesion to vWF and collagen at the injury site and concomitant aggregation via fibrinogen binding to integrin GPIIb-IIIa on active platelets, we have mimicked and integrated these key hemostatic mechanisms on the SynthoPlate® by heteromultivalent surface-engineering of a liposomal platform with vWF-binding peptides (VBP), collagen-binding peptides (CBP) and fibrinogen-mimetic peptides (FMP). These ~150nm diameter SynthoPlate® vesicles are sterilizable and can be stored as lyophilized powder for long periods of time. We demonstrated, in vitro, that this platelet-mimetic integrative design renders hemostatically relevant functions at levels significantly higher than designs that mimic platelet’s adhesion function only or aggregation function only. We further demonstrated in vitro that SynthoPlate®-mediated site-selective amplification of primary hemostatic mechanisms (active platelet recruitment and aggregation) in effect results in site-selective enhancement of secondary hemostatic function (fibrin generation). We also established that SynthoPlate® does not activate and aggregate resting platelets or trigger coagulation mechanisms in plasma, suggesting that this technology will not have systemic pro-thrombotic and coagulatory risks. The hemostatic efficacy of SynthoPlate® was tested in appropriate tail-transection and liver bleeding models in mice, as well as, pilot studies in arterial bleeding model in pigs. In tail-transection bleeding model in normal as well as thrombocytopenic mice, prophylactically administered SynthoPlate® was able to significantly reduce bleeding time by 60-70%. In laparotomy traumatic bleeding model in mice, prophylactically administered SynthoPlate® was able to reduce blood volume loss by ~30%, reduced hypotension effects and increased survival by \u3e80%. In pilot pig models of arterial bleeding, emergency administration of SynthoPlate® has shown substantial reduction in blood volume loss. Immunohistological evaluation of tissues from various treated animals have shown marked co-localization of red fluorescent SynthoPlate® with green fluorescent platelets localized at the clot site. Biodistribution studies in animals indicate that SynthoPlate® is cleared primarily by liver and spleen, similar to clinically known liposomal technologies. We have also demonstrated that the platelet-mimetic heteromultivalent surface-decoration approach can be adapted to other biomedically relevant particle platforms. Altogether, our studies establish the promise of SynthoPlate® nanotechnology as a platelet-mimetic intravenous hemostat for treatment of bleeding complications in prophylactic and emergency scenarios. Ongoing studies are focused on evaluating this technology in clinically motivated large animal bleeding models, with a vision for translation

    Extra-short-duration pigeonpea for diversifying wheat-based cropping systems in the sub-tropics

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    The performance of newly developed extra-short-duration pigeonpea (Cajanus cajan) genotypes and traditional short-duration pigeonpea cultivars was compared in rotation with wheat in on-farm trials conducted in 1996–97 and 1997–98 in Sonepat (28° N) district in Haryana, and in 1996–97 at Ludhiana (30° N) district in Punjab, India. At both locations, a wheat crop (Triticum aestivum cv. HD 2329) followed pigeonpea. At Sonepat, an indeterminate extra-short-duration genotype ICPL 88039 matured up to three weeks earlier, yet gave 12% higher yield (1.57 t ha−1) and showed less susceptibility to borer damage than did the short-duration cv. Manak. At Ludhiana, extra-short-duration pigeonpea genotypes, ICPL 88039, ICPL 85010 and AL 201 gave similar grain yields to the short-duration T 21 in spite of maturing three to four weeks earlier. Yields of wheat crops following extra-short-duration genotypes were up to 0.75 t ha−1 greater at Sonepat and up to 1.0 t ha−1 greater at Ludhiana. The results of the study provide empirical evidence that extra-short-duration pigeonpea genotypes could contribute to higher productivity of pigeonpea–wheat rotation systems. Most of the farmers who grew on-farm trials in Sonepat preferred extra-short-duration to short-duration pigeonpea types for their early maturity, bold seed size, and the greater yield of the following wheat crop
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