Miracle-dz/UniFAR-FTUs huggingface dataset:
Solar and QBO Influences on the Middle Atmosphere Dynamics

Abstract. This study is focused on the sensitivity of the middle atmosphere dynamics to important climatic phenomena such as the 11-yr solar cycle (SC) and Quasi-Biennial Oscillation (QBO). The analysis is based on the composition analysis regarding the SC maximum and SC minimum or QBO west and east conditions. These influences are studied using the last generation of reanalysis, i.e., ERA-Interim, MERRA and JRA-55. Current scientific findings are reviewed together with description of mechanisms for the Holton–Tan relationship.
Deriving A Drinking Water Guideline for A Non-Carcinogenic Contaminant: The Case of Manganese

Manganese is a natural contaminant of water sources. It is an essential oligo-element, which may exert toxicity at high doses, particularly via inhalation. Its toxicity by the oral route is less known, but epidemiological and experimental studies tend to support its neurodevelopmental toxicity in infants and children. This paper describes the method used by a middle-size public health institution to derive a Drinking Water Guideline (DWG) for manganese. After reviewing the work done by major public health institutions, authors confirmed the use of experimental data to derive a point-of-departure (POD) of 25 mg of manganese/kg/day, based on neurodevelopmental effects on pup rats. Then, a total uncertainty factor of 450 was applied to calculate a Toxicological Reference Value (TRV) of 55 µg/kg/day. The final DWG proposed for manganese is 60 µg/L and is based on a relative source contribution (RSC) of water of 20% and an infant drinking scenario of 182 mL/kg of body weight (BW) of water (95th percentile of the ingestion rate distribution for 0–6 months). Despite its limitations, e.g., starting with the work done by other agencies, such an approach demonstrates in a transparent way the rationale and challenging choices made by regulators when deriving a DWG.
Automated detection of polyps in CT colonography images using deep learning algorithms in colon cancer diagnosis

Colon cancer is cancer that is present on the inner side of colon walls or the rectum walls in the large intestine. Most of these types of cancer begin as abnormal growth of tissue called as polyp. Colonography uses low dose radiation Computed tomography (CT) scanning to obtain an interior view of the colon making use of special x-ray machine to view the large intestine for cancer and abnormal growths known as polyps. Radiologists examine these images to find polyp like structure using computer tools. As CT Colonography image contain noise such as lungs, small intestine, instruments during image capturing; segmenting colon from noise is the key task. Polyp occurrence can be detected mainly using shape feature; eliminating shapes similar to polyp is challenging. Hence, to tackle above issues, Image processing techniques are used by applying deep learning algorithm - Convolution Neural Network (CNN) and the results are compared with classical machine learning algorithm. In proposed method, each image is pre-processed to filter air filled dark region that includes colon, lungs etc. Next, each pre-processed CT Image separated into fixed number of blocks. Using pre-trained CNN, each block of ROI is classified as Type 1 (Usually Ascending and descending colon), Type 2 (Usually Traversal and sigmoidal colon) and Type3 (Noise such as lungs, instruments) to segment colon blocks by eliminating noise. Classified Blocks is further diagnosed for polyp like structure using pre-trained CNN by classifying each colon block as normal or abnormal. The experiment is setup with classical machine learning algorithms - Random Forest (RF) and k-nearest neighbor (KNN) by extracting texture feature - Local binary pattern (LBP) and shape feature - Histogram oriented gradient (HOG) for comparison. The experiment results showed the accuracy of proposed method for colon segmentation using CNN (87%) outperforms RF (85%) and KNN (83%). In, addition, the polyp detection accuracy of CNN (88%) is better than Random forest (85%) and KNN (80%). Hence, in the proposed method, there is significant accuracy improvement using deep learning algorithm compared to classical machine learning algorithms. It also provide baseline for automated colon cancer diagnosis using Deep learning algorithms for further research.
A Comparison of Genetic Diversity between Sympatric Populations of the Endangered Winged-Mapleleaf (Quadrula fragosa) and the Pimpleback (Amphinaias pustulosa) in the St. Croix River, U.S.A.

Abstract Assessing genetic variation in species of conservation concern is critical for developing sound recovery strategies. In this study, we compared sympatric populations of two related species, the endangered Quadrula fragosa (Conrad, 1836) and its common relative Amphinaias pustulosa (Lea, 1831), using standard genetic parameters such as allelic richness, heterozygosity, and effective population size. Our primary aim was to determine if a small population size and isolation from conspecifics had negatively affected the genetic diversity of this population of Q. fragosa. By comparing the endangered species to a related and sympatric, common species we can assess the rare species for genetic effects associated with reduced population size, and in addition, develop management targets for what a recovered Q. fragosa population looks like genetically. Examination of eight microsatellite loci indicated that Quadrula fragosa exhibited reduced genetic variation when compared to A. pustulosa at all measures, however, no evidence of a genetic bottleneck or inbreeding was discovered for either species. A comparison of known fish hosts and reproductive period for these two species point to competition for fish hosts as one possible explanation for the smaller population size of Q. fragosa. We discuss the implications of our findings for the conservation and management of freshwater mussels.
Impacto da escleroterapia com espuma de polidocanol guiada por ultrassom em pacientes com úlcera venosa

Resumo Contexto A escleroterapia com espuma de polidocanol guiada por ultrassom tem sido utilizada no tratamento de pacientes com úlceras venosas. É um procedimento minimamente invasivo e de fácil execução, porém apresenta taxas de recidiva elevadas. Objetivos Relatar a evolução a curto e médio prazo de pacientes com úlcera venosa tratados com escleroterapia com espuma de polidocanol guiada por ultrassom. Métodos Foram reavaliados 19 pacientes submetidos ao tratamento de escleroterapia com espuma de polidocanol guiada por ultrassom no período de janeiro de 2013 a dezembro de 2014. Foram analisados tempo de cicatrização da úlcera, melhora de sintomas clínicos, recanalização das veias tratadas, recidiva dos sintomas e da úlcera venosa. Resultados Foram analisados 15 pacientes do sexo feminino (78,9%) e quatro do sexo masculino (21,1%). A média geral de idade foi de 53 anos. O tempo de seguimento dos pacientes variou de 448 dias a 1.276 dias (média de 791 dias). O tempo médio de presença das úlceras foi de 53 meses. Na avaliação pós-procedimento, foram observadas recanalização total em 15,7%, recanalização parcial em 21% e oclusão em 47,3% das veias tratadas. Apenas em um caso foi observada recidiva da úlcera. Pela avaliação das médias do Venous Clinical Severity Score (VCSS), houve diferença significativa antes e após o procedimento, com variação entre os grupos de 11,2 (p < 0,01). Conclusões A escleroterapia por espuma guiada por ultrassom apresenta altas taxas de sucesso terapêutico, com índices de cicatrização de úlceras venosas elevados.
4 GENERIC ANALYSIS OF UTILITY MODELS

It is now firmly established that expected utility (EU) theory and subjective expected utility (SEU) theory are descriptively invalid (Kahneman and Tversky, 1979; Luce, 1988b; MacCrimmon and Larsson, 1979; Slovic and Lichtenstein, 1983; Weber and Camerer, 1987). Descriptive utility theory is undergoing extensive revision, stimulated by empirical findings that challenge existing theories, and by new theories that more adequately account for the cognitive processes that underly preference behavior (Becker and Sarin, 1987; Bell, 1982; Kahneman and Tversky, 1979; Loomes and Sugden, 1982; Luce, 1988a, 1990; Luce and Narens, 1985; Quiggin, 1982). Although these developments are undoubtedly salutory for the theory and practice of decision making, it might appear that in the short term they undermine the usefulness of multiattribute , utility theory (MAUT), or at least that part of MAUT that is built upon EU or SEU assumptions. (Henceforth, I will refer only to SEU theory', noting that EU theory can be construed as a special case of SEU theory.) A substantial part of MAUT methodology is based on preference assumptions that characterize classes of utility models under the assump-
Decentralized Optimization of Multi-Area Electricity-Natural Gas Flows Based on Cone Reformulation

A large-scale integrated energy system can represent several subsystems representing areas that are tied by electricity and natural gas networks. Accordingly, we propose a decentralized optimal energy flow (DOEF) calculation as compared with a centralized solution method. The proposed approach demonstrates the merits of the decentralized operation and control of a multi-area integrated electricity-natural gas system (IEGS), in terms of large-scale modeling requirements, faster computations, and data management for local sensitivity analyses. Using the proposed decentralized structure, the communication burden is relatively light as individual area operators in a multi-area IEGS will make optimal dispatch decisions independently and the corresponding information is shared with adjacent subsystems. The reformulation of the second-order cone (SOC) is proposed using advanced sequential cone programming (SCP) to handle the nonlinear steady-state natural gas flow, which provides a feasible solution with a high degree of computational efficiency. Furthermore, an iterative alternating direction method of multipliers (I-ADMM) is adopted to manage the nonconvexity of integer variables, which guarantees a satisfactory convergence performance. Case studies on three multi-area IEGS validate the effectiveness of the proposed model in a multi-area IEGS.
Evaluation of the Impact of Genetically Modified Cotton After 20 Years of Cultivation in Mexico

For more than 20 years cotton has been the most widely sown genetically modified (GM) crop in Mexico. Its cultivation has fulfilled all requirements and has gone through the different regulatory stages. During the last 20 years, both research-institutions and biotech-companies have generated scientific and technical information regarding GM cotton cultivation in Mexico. In this work, we collected data in order to analyze the environmental and agronomic effects of the use of GM cotton in Mexico. In 1996, the introduction of Bt cotton made it possible to reactivate this crop, which in previous years was greatly reduced due to pest problems, production costs and environmental concerns. Bt cotton is a widely accepted tool for cotton producers and has proven to be efficient for the control of lepidopteran pests. The economic benefits of its use are variable, and depend on factors such as the international cotton-prices and other costs associated with its inputs. So far, the management strategies used to prevent development of insect resistance to GM cotton has been successful, and there are no reports of insect resistance development to Bt cotton in Mexico. In addition, no effects have been observed on non-target organisms. For herbicide tolerant cotton, the prevention of herbicide resistance has also been successful since unlike other countries, the onset of resistance weeds is still slow, apparently due to cultural practices and rotation of different herbicides. Environmental benefits have been achieved with a reduction in chemical insecticide applications and the subsequent decrease in primary pest populations, so that the inclusion of other technologies—e.g., use of non-Bt cotton- can be explored. Nevertheless, control measures need to be implemented during transport of the bolls and fiber to prevent dispersal of volunteer plants and subsequent gene flow to wild relatives distributed outside the GM cotton growing areas. It is still necessary to implement national research programs, so that biotechnology and plant breeding advances can be used in the development of cotton varieties adapted to the Mexican particular environmental conditions and to control insect pests of regional importance.
Robust multiview featurematching frommultiple unordered views

This paper explores the problem of multi-view feature matching from an unordered set of widely separated views. A set of local invariant features is extracted independently from each view. First we propose a new view-ordering algorithm that organizes all the unordered views into clusters of related (i.e. the same scene) views by efficiently computing the view-similarity values of all view pairs by reasonably selecting part of extracted features to match. Second a robust two-view matching algorithm is developed to find initial matches, then detect the outliers and finally incrementally find more reliable feature matches under the epipolar constraint between two views from dense to sparse based on an assumption that changes of both motion and feature characteristics of one match are consistent with those of neighbors. Third we establish the reliable multi-view matches across related views by reconstructing missing matches in a neighboring triple of views and efficiently determining the states of matches between view pairs. Finally, the reliable multi-view matches thus obtained are used to automatically track all the views by using a self-calibration method. The proposed methods were tested on several sets of real images. Experimental results show that it is efficient and can track a large set of multi-view feature matches across multiple widely separated views. 2007 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
Measuring ligand efficacy at the mu-opioid receptor using a conformational biosensor

The intrinsic efficacy of orthosteric ligands acting at G-protein-coupled receptors (GPCRs) reflects their ability to stabilize active receptor states (R*) and is a major determinant of their physiological effects. Here, we present a direct way to quantify the efficacy of ligands by measuring the binding of a R*-specific biosensor to purified receptor employing interferometry. As an example, we use the mu-opioid receptor (µ-OR), a prototypic class A GPCR, and its active state sensor, nanobody-39 (Nb39). We demonstrate that ligands vary in their ability to recruit Nb39 to µ-OR and describe methadone, loperamide, and PZM21 as ligands that support unique R* conformation(s) of µ-OR. We further show that positive allosteric modulators of µ-OR promote formation of R* in addition to enhancing promotion by orthosteric agonists. Finally, we demonstrate that the technique can be utilized with heterotrimeric G protein. The method is cell-free, signal transduction-independent and is generally applicable to GPCRs.
Does a negative discriminative stimulus function as a punishing consequence?

The study and use of punishment in behavioral treatments has been constrained by ethical concerns. However, there remains a need to reduce harmful behavior unable to be reduced by differential-reinforcement procedures. We investigated whether response-contingent presentation of a negative discriminative stimulus previously correlated with an absence of reinforcers would punish behavior maintained by positive reinforcers. Across four conditions, pigeons were trained to discriminate between a positive discriminative stimulus (S+) signaling the presence of food, and a negative discriminative stimulus (S-) signaling the absence of food. Once learned, every five responses on average to the S+ produced S- for a duration of 1.5 s. S+ response rate decreased for a majority of pigeons when responses produced S-, compared to when they did not, or when a neutral control stimulus was presented. In Condition 5, choice between two concurrently presented S+ alternatives shifted away from the alternative producing S-, despite a 1:1 reinforcer ratio. Therefore, presenting contingent S- stimuli punishes operant behavior maintained on simple schedules and in choice situations. Development of negative discriminative stimuli as punishers of operant behavior could provide an effective approach to behavioral treatments for problem behavior and subverting suboptimal choices involved in addictions.
Computability Beyond Church-Turing via Choice Sequences

Church-Turing computability was extended by Brouwer who considered non-lawlike computability in the form of free choice sequences. Those are essentially unbounded sequences whose elements are chosen freely, i.e. not subject to any law. In this work we develop a new type theory BITT, which is an extension of the type theory of the Nuprl proof assistant, that embeds the notion of choice sequences. Supporting the evolving, non-deterministic nature of these objects required major modifications to the underlying type theory. Even though the construction of a choice sequence is non-deterministic, once certain choices were made, they must remain consistent. To ensure this, BITT uses the underlying library as state and store choices as they are created. Another salient feature of BITT is that it uses a Beth-like semantics to account for the dynamic nature of choice sequences. We formally define BITT and use it to interpret and validate essential axioms governing choice sequences. These results provide a foundation for a fully intuitionistic version of Nuprl.
Operon-mapper: a web server for precise operon identification in bacterial and archaeal genomes

Abstract Summary Operon-mapper is a web server that accurately, easily and directly predicts the operons of any bacterial or archaeal genome sequence. The operon predictions are based on the intergenic distance of neighboring genes as well as the functional relationships of their protein-coding products. To this end, Operon-mapper finds all the ORFs within a given nucleotide sequence, along with their genomic coordinates, orthology groups and functional relationships. We believe that Operon-mapper, due to its accuracy, simplicity and speed, as well as the relevant information that it generates, will be a useful tool for annotating and characterizing genomic sequences. Availability and implementation http://biocomputo.ibt. unam.mx/operon_mapper/
Investigating the interactions of the 18 kDa translocator protein and its ligand PK 11195 in planar lipid bilayers

a Medical Imaging & Radiation Sciences Faculty Research Group, Faculty of Health Sciences, The University of Sydney, c/o Brain & Mind Research Institute, 94 Mallett Street, Camperdown, NSW 2050, Australia b Bragg Institute, Australian Nuclear Science and Technology Organisation, New Illawarra Road, Lucas Heights, NSW 2234, Australia c ISIS Pulsed Neutron and Muon Source, Science and Technology Facilities Council, Rutherford Appleton Laboratory, Harwell Oxford, Didcot OX11 0QX, UK d Life Sciences, Australian Nuclear Science and Technology Organisation, New Illawarra Road, Lucas Heights, NSW 2234, Australia e School of Chemistry, University of New South Wales, Kensington NSW 2052, Australia
Time to sputum culture conversion and its determinants among Multi-drug resistant Tuberculosis patients at public hospitals of the Amhara Regional State: A multicenter retrospective follow up study

Background In Ethiopia, Multi-drug resistant Tuberculosis (MDR-TB) is one of the major public health problems that need great attention. Time to sputum culture conversion is often used as an early predictive value for the final treatment outcome. Although guidelines for MDR-TB are frequently designed, medication freely provided, and centers for treatment duly expanded, studies on time to sputum culture conversion have been very limited in Ethiopia. This study was aimed at determining the time to sputum culture conversion and the determinants among MDR-TB patients at public Hospitals of the Amhara Regional State. Methods A retrospective follow up study was conducted between September 2010 and December 2016. Three hundred ninety two MDR-TB patients were included in the study. Parametric frailty models were fitted and Cox Snell residual was used for goodness of fit, which the Akaike’s information criteria was used for model selection. Adjusted hazard ratio (AHR) with a 95% confidence interval (CI) was reported to show the strength of association. Result Out of the 392 participants, sputum culture changed for 340(86.7%) during the follow up period. The median culture conversion time in this study was 65 (60–70 days). Alcohol drinking (AHR = 3.79, 95%CI = 1.65–8.68), sputum smear grading +2 (AHR = 0.39, 95%CI 0.19–0.79), smear grading +3 (AHR = 0.30, CI = 0.14–064), cavitations (AHR = 0.36, 95%CI = 0.19–0.68), and consolidation (AHR = 0.29, CI = 0.13–0.69) were the determinants of time to sputum culture conversion. Conclusion In this study, time to sputum culture was rapid as compared to 4 months WHO recommendation. Alcohol drinking, sputum smear grading, cavitations and consolidations were found to be the determinants of time to sputum culture conversion. Therefore, providing a special attention to patients who had baseline radiological finding is recommended, high bacillary load and patients with a history of alcohol intake at baseline should be given priority.
Influence of dinoflagellate cell toxicity on uptake and loss of paralytic shellfish toxins in the northern quahog Mercenaria mercenaria * '

The northern quahog Mercenaria mercenaria was exposed to bloom concentrations of the toxic red-tide dinoflagellate Alexanddum, the proximal cause of paralytic shellfish poisoning (PSP) in eastern North America, under controlled conditions in the laboratory. Two cultured isolates of Alexandrium, exhibiting markedly different PSP toxin compositions and specific toxicities, were used independently to determine the kinetics of toxin accumulation and loss, as well as the potential for biotransformation of individual PSP toxins in certain tissues. Clams readily ingested and absorbed a monospecific diet of the low toxlcity A. tamarense isolate GtLI22 They also ingested cells of the high toxicity A , fundyense isolate GtCA29, but at a lower rate, and only when the diet was supplemented with a nontoxic d~a tom, Thalass~osira weissflogii. As natural populations of M. mercenaria rarely accumulate a substantial PSP toxin load, this suggests the existence of a toxin recognition mechanism Maximum toxicities In clam t~ssues , attained within 2 wk of exposure to either toxic dinoflagellate, exceeded the regulatory harvest closure level (80 lig STXeq 100g-l) by several orders of magn~tude. Detoxification to levels acceptable for human consumption occurred within 3 to 6 wk. HPLC analyses revealed significant differences between the toxic profile of the dinoflagellates and that accumulated in various clam tissues. Clams toxified with isolate GtLI22, a strain rich in low potency C-toxins, showed: (1) de novo appearance of STX, (2) significant reduction in the proportion of C-toxins, and (3) reciprocal increase in the proportion of the gonyautoxins GTX2+,. Significant relative enrichment in STX also occurred in tissues of clams fed upon GtCA29, an isolate rich in the more potent carbamate toxins. The f~rs t experimental evidence of PSP accumulation/detoxification by M mercenaria is provided, underscoring the potential of t h ~ s pecies to act as a vector of PSP in humans.