Miracle-dz/UniFAR-FTUs huggingface dataset:
Title: The effects of sodium bicarbonate ingestion on cycling performance and acid base balance recovery in acute normobaric hypoxia.

This study investigated the effects of two separate doses of sodium bicarbonate (NaHCO 3 ) on 4 km time trial (TT) cycling performance and post-exercise acid base balance recovery in hypoxia. 14 club-level cyclists completed four cycling TT’s, followed by a 40 min passive recovery in normobaric hypoxic conditions (FiO 2 = 14.5%) following one of either: two doses of NaHCO 3 (0.2 g . kg -1 BM; SBC2, or 0.3 g . kg -1 BM; SBC3), a taste-matched placebo (0.07 g . kg -1 BM sodium chloride; PLA), or a control trial in a double-blind, randomized, repeated-measures and crossover design study. Compared to PLA, TT performance was improved following SBC2 (p = 0.04, g = 0.16, very likely beneficial), but was improved to a greater extent following SBC3 (p = 0.01, g = 0.24, very likely beneficial). Furthermore, a likely benefit of ingesting SBC3 over SBC2 was observed (p = 0.13, g = 0.10), although there was a large inter-individual variation. Both SBC treatments achieved full recovery within 40 min, which was not observed in either PLA or CON following the TT. In conclusion, NaHCO 3 improves 4 km TT performance and acid base balance recovery in acute moderate hypoxic conditions, however the optimal dose warrants an individual approach.
C AUSALLY C OMPLETE S CIENCE FOR THE R EASON -B ASED S OCIETY

Modern fundamental science tends to avoid the principle of physical causality and realism, re-placing it with heuristically postulated and separated mathematical constructions that impose their own rules before being adjusted to measurement results. While it is officially accepted as the single possible kind of rigorous knowledge, we argue that another, explicitly extended kind of science can provide the causally complete picture of reality avoiding the glaring gaps, growing problems and persisting stagnation of the artificially reduced knowledge paradigm. The logic of science development and especially its current state call for the urgently needed transition to the extended, causally complete kind of knowledge and related sustainable progress at superior creativity levels of self-aware, reason-based society.
Utilización de lectinas en la inhibición de la adhesión de Pasteurella multocida

The first step of infection is the adhesion of pathogens to target cells. This feature not only allows them to penetrate and deploy offensive strategies to initiate colonization, but to contribute to their protection and preservation against both the immunological and mechanical defense mechanisms of the host. This process is conducted largely by the interaction of lectins, which are proteins of non-immune origin with the ability to recognize and bind carbohydrates. This mechanism has been reported for many microorganisms such as bacteria and viruses. In the particular case of Pasteurella multocida, which is a Gram-negative, opportunistic pathogen bacterium that starts the infection in the respiratory epithelium of many animals, lectin substances have been described on its surface, such as type IV fimbria, and carbohydrates such as lipopolysaccharide or the capsule that recognizes carbohydrates and lectins, respectively, on the surface of epithelial cells of the trachea, a circumstance that allows it to adhere and escape the mucociliary effect. Seeing as, to most of these microorganisms —including P. multocida—the decreased susceptibility to antibacterial agents and the effectiveness of vaccines is evident, new therapeutic and prophylactic tactics have been sought in order to interrupt pathogenic infection by blocking the carbohydrate-lectin bond by competition, where the union of the microorganism to the tissue and, therefore, the infection, is diminished.
International Journal of Life science and Pharma Research M-UNet for Segmentation of Brain Images

: A mass or progress of unusual cells in the brain is termed as brain tumor. Several categories of brain tumors occur in human. Certain types of brain tumors are non-cancerous which is indicated as benign, whereas certain brain tumors are cancerous, called malignant. In this paper, images are segmented using Modified-Universal Education and Training , Ltd. (M-UNet). The main aim is to investigate network architectures (M-UNet) based on deep learning which is used for enhanced classification and segmentation of brain tumor images. Segmentation of brain cancer images is the procedure of splitting the tumor from usual brain muscles; in medical routine, it offers valuable information for analysis and treatment planning. It is still a complex job due to the asymmetrical arrangement and perplexing borders of tumors. The Convolutional Neural Network (CNN) and Universal Education and Training , Ltd.(UNet) are considered to be notable techniques in segmentation of images. The concept of CNN is a dominant technique for recognition of images and forecasts. CNN is typically utilized for brain cancer separation, classification, and estimate of existence period for infected people. UNet is a familiar image separation method established mainly for analyzing clinical images that can exactly divide images using an unusual quantity of preparation facts. These qualities make UNet efficient in clinical imaging forum and support wide-ranging implementation of UNet in performing separation jobs in therapeutic imaging. M-UNet is recommended in this paper to slice the given input images in a well-defined manner. Experimental results have shown that the proposed M-UNet achieves accuracy of 97% which is notably better when compared to the existing CNN and UNet techniques. The results are also compared based on Dice Coefficient, Jaccard Coefficient and time period. It is evident that the M-UNet outperforms the existing techniques on all assessment parameters. A novel frame work using M-UNet that includes extraction of both global and local features is proposed to increase the segmentation accuracy. The outcomes show better performance in segmenting the 5 tumor areas on the huge BRATs 2018 dataset. The performance of the network is assessed by comparing the forecast segmentation of tumor areas to the ground truth offered by the dataset. Dice Similarity Coefficient (DSC) and Jaccard Coefficient (JC) give the like nessamid the anticipated tumor area and ground truth by associating the overlay areas. In this paper, brain image segmentation is performed using UNet and M-UNet methods and the proposed method efficiently predicts the border of then segmentation pixel.
Endogenous Small Intestinal Microbiome Determinants of Transient Colonization Efficiency by Bacteria from Fermented Dairy Products; A Randomized Controlled Trial

BackgroundThe effects of fermented food consumption on the small intestine microbiome and its role on host homeostasis are largely uncharacterized as our knowledge on intestinal microbiota relies mainly on faecal samples analysis. We investigated changes in the small intestinal microbial composition and functionality, short chain fatty acid (SCFA) profiles, and on the gastro-intestinal (GI) permeability in ileostomy subjects upon the consumption of fermented milk products.ResultsWe report the results from a randomized, cross-over, explorative study where 16ileostomy subjects underwent 3, 2-week interventions periodsin which they daily consumed either milk fermented by Lacticaseibacillus rhamnosus CNCM I-3690, or milk fermented by Streptococcus thermophilus CNCM I-1630 and Lactobacillus delbrueckii subsp. bulgaricus CNCM I-1519, or a chemically acidified milk (placebo). Weperformed metataxonomic, metatranscriptomic analysis and SCFA profiling of ileostomy effluents as well as a sugar permeability test andto investigate the microbiome impact of these interventions and their potential effect on mucosal barrier function. Consumption of the intervention products significantly impacted the small intestinal microbiome composition and functionality but did not affect the SCFA levels in ileostoma effluent, or the gastro-intestinal permeability. Theimpact on microbiome composition was highly personalized,andwe identified the poorly characterized bacterial family, Peptostreptococcaceae, to be positively associated with low abundance of the ingested bacteria. Activity profiling of the microbiota revealed that carbon- versus amino acid-derived energy metabolism of the endogenous microbiome could be responsible for the individual-specific intervention effects on the small intestine microbiome composition and function.ConclusionsThe ingested bacteria are the main drivers of the intervention effect on the small intestinal microbiota composition. Their transient abundance level is highly personalized and influenced by the energy metabolism of the ecosystem that is reflected by its microbial composition (http://www.clinicaltrials.gov, ID NCT NCT02920294).
Modeling and compensating dynamic nonlinearities in LED photon-emission rates to enhance OWC

LEDs can be modulated at relatively high speeds to support wireless optical data communication (OWC). Yet, particularly LEDs optimized for illumination act as a non-linear low-pass communication channel. It has become clear in recent literature that their non-linearity and low-pass behavior cannot be seen as two separable, cascaded mechanisms. Although standard nonlinear equalizer schemes, e.g. based on Volterra Series, have been proposed and tested before, our recent research results show that a more dedicated approach in which we specifically analyze the hole-electron recombination mechanisms, yield a very effective and computationally-efficient compensation approach. In this manuscript, we will review the non-linear differential equations for photon emissions, its electrical equivalent circuit and a discrete-time variant with delays and non-linearities. This can be inverted, in the sense that we can actively eliminate or mitigate the non-linear dynamic LED distortion by adequate signal processing. We propose an aggressive simplification of the compensation circuit that allows us to use a relatively simple structure with only a couple of parameters.
Validation of a methodological model to incubate successful agribusinesses in marginalized areas from South Mexico

Given the situation of poverty and marginalization in which most of the communities in the rural areas of the Mexican South Southeast are found, a situation that affects 17 million people classified as in a situation of extreme poverty, agribusiness is an alternative under these conditions for it. An operational and practical methodology is required that allows a good identification and implementation of initiatives according to the situation and the environment. The objective of this work was to validate an operational methodological model called model for the competitiveness of small farmers in extreme poverty based on agribusiness. The validation project was developed in four pilot communities in the Mexican South Southeast considered to be highly marginalized and poor: San Andrés Tuxtla, Veracruz; Tahdziu, Yucatan; Ocotepec, Chiapas and San Jerónimo Taviche, Oaxaca. The applied model consists of four stages, diagnosis, incubation, development and maturity. The diagnosis considered in turn two sub-stages, one on the description of the environment and the actors and the second on the definition of the portfolio of opportunities. The incubation considered the sub-stages of prioritization through a qualification criteria and the business plan itself according to the conditions of the actors and the environment. The development stage is nothing more than the start-up and consolidation of the business with a view to continuous improvement. The results obtained were four agribusinesses in progress, one for each pilot community, with profitability indicators such as the Internal Rate of Return (IRR) of 35.0%, 100.0%, 41.0% and 45.9% for jam production in San Andrés Tuxtla Veracruz, Stevia production and marketing in Tadhziu Yucatán, Hass avocado production and marketing in San Pablo Huacanó Chiapas and tomato production and marketing in greenhouses in San Jerónimo Taviche Oaxaca, respectively. The operational methodological model to identify and develop agribusiness in poor and marginalized communities was successfully validated. It is concluded that it is possible to develop profitable and competitive agribusiness in conditions of extreme poverty and marginalization.
Barrière hémato-encéphalique humaine et endothéline 1 : régulation des transporteurs ABC et des cytokines inflammatoires

Le systeme nerveux central est un organe complexe et privilegie, protege, entre autres, par la barriere hemato-encephalique (BHE), sur laquelle se trouvent des transporteurs d'efflux telle que la P-glycoproteine (Pgp). La BHE est impliquee dans la neuro-inflammation et les maladies cerebrales associees, et la litterature laisse penser que l'endotheline 1 (ET-1) y joue un role important. En utilisant un modele in vitro autologue de BHE humaine adulte et un modele in vitro de BHE humaine fœtale (co-culture de cellules gliales et de cellules endotheliales microvasculaires cerebrales), nous avons etudie l'effet de l'ET-1 sur la Pgp. Une difference, en termes de modulation de l'activite de la Pgp, a ete observee entre la BHE fœtale et la BHE adulte suite a l'exposition a l'ET-1. Nous avons egalement evalue la modulation induite par l'ET-1 sur la secretion de la MCP-1 (Monocyte chemoattractant protein 1) et de l'IL-8. Les resultats montrent que l'ET-1 diminue l'activite de la Pgp et induit la secretion de MCP-1 et d'IL-8.
Using FIA data to inform United States forest carbon national-level accounting needs: 1990-2010

Forests are partially made up of carbon. Live vegetation, dead wood, forest floor, and soil all contain carbon. Through the process of photosynthesis, trees reduce carbon dioxide to carbohydrates and store the carbon in wood. By removing carbon dioxide from the atmosphere, forests mitigate climate change that may be brought on by increased atmospheric CO2. However, the specific role of forests in climate mitigation continues to be debated. Several decades ago, the debate was whether forest carbon could be measured accurately enough to include it in national inventories related to greenhouse gases (GHGs), especially carbon dioxide (CO2). Today, this debate has expanded to include all lands, including non-forest land. It includes the specifics of how to best design and conduct land-based inventories for greenhouse gases, as well as how to design carbon markets or set policies to best manage land, especially forestland, to mitigate climate change. For the last several decades, forest carbon estimates for reporting and planning in the U.S. have often been based on data collected by the USDA Forest Service, Forest Inventory and Analysis (FIA) Program. Smith et al. (2004a) is an introductory publication describing methods to derive forest carbon estimates. Carbon estimates can be reported in terms of carbon dioxide using the elemental weights and proportions of the carbon and oxygen atoms in carbon dioxide compared to carbon. That is, multiplying carbon mass by 44/12 gives the corresponding mass in terms of carbon dioxide. In this paper, I discuss the evolving use of FIA data as a basis for forest carbon estimates for broad-scale, policy-related needs from the 1990's to 2010. I briefly discuss the FIA survey and the improving availability of data, explain indirect and direct methods that were used to calculate carbon stock and change estimates from FIA data, and present examples of policy-relevant reports that use FIA-based estimates and web tools that can provide customized estimates to users.
Subclinical thyroid dysfunction and the risk of heart failure in older persons at high cardiovascular risk.

CONTEXT Subclinical thyroid dysfunction is common in older people. However, its clinical importance is uncertain. OBJECTIVE Our objective was to determine the extent to which subclinical hyperthyroidism and hypothyroidism influence the risk of heart failure and cardiovascular diseases in older people. SETTING AND DESIGN The Prospective Study of Pravastatin in the Elderly at Risk (PROSPER) is an prospective cohort study. PATIENTS Patients included men and women aged 70-82 yr (n=5316) with known cardiovascular risk factors or previous cardiovascular disease. MAIN OUTCOME MEASURES Incidence rate of heart failure hospitalization, atrial fibrillation, and cardiovascular events and mortality according to baseline thyroid status were evaluated. Euthyroid participants (TSH=0.45-4.5 mIU/liter) were compared with those with subclinical hyperthyroidism (TSH<0.45 mIU/liter) and those with subclinical hypothyroidism (TSH≥4.5 mIU/liter, both with normal free T4). RESULTS Subclinical hyperthyroidism was present in 71 participants and subclinical hypothyroidism in 199 participants. Over 3.2 yr follow-up, the rate of heart failure was higher for subclinical hyperthyroidism compared with euthyroidism [age- and sex-adjusted hazard ratio (HR)=2.93, 95% confidence interval (CI)=1.37-6.24, P=0.005; multivariate-adjusted HR=3.27, 95% CI=1.52-7.02, P=0.002). Subclinical hypothyroidism (only at threshold>10 mIU/liter) was associated with heart failure (age- and sex-adjusted HR=3.01, 95% CI=1.12-8.11, P=0.029; multivariate HR=2.28, 95% CI=0.84-6.23). There were no strong evidence of an association between subclinical thyroid dysfunction and cardiovascular events or mortality, except in those with TSH below 0.1 or over 10 mIU/liter and not taking pravastatin. CONCLUSION Older people at high cardiovascular risk with low or very high TSH along with normal free T4 appear at increased risk of incident heart failure.
An energy budget approach to simulate snow melt and soil frost depth.

Evaluation of WEPP (Water Erosion Prediction Project) of USDA-ARS indicates the winter subroutines in this model predict longer soil freezing periods and deeper frost depths than are actually observed in many areas. An energy budget approach was selected and tested for its potential in replacing the current winter subroutines in WEPP. This approach has been used to model snow pack development and snow melting in many studies. It has also been used to predict the occurrence of soil freezing. This project further develops the energy concept to quantify temporal depth variation of soil frost. It is based on an energy balance relationship composed of four components: net radiation, latent heat, sensible heat and the heat flow through the soil surface. Results of testing with observed data show this approach satisfies our needs and has flexibility for future enhancements.
A HEALTHY DIET TO REDUCE THE RISK OF DEMENTIA IN PEOPLE WITH A LEARNING DISABILITY

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SGD Algorithms based on Incomplete U-statistics : Large-Scale Minimization of Empirical Risk Supplementary Material

We follow the proof of [1] to derive bounds. We highlight the fact that since the loss function H is l-smooth, ĝn(θt) and g̃n′(θt) are l-Lipschitz. We introduce the sequence γ̃t = γt(1 − lγt). In all generality we will denote by gt(θ) an unbiased estimator of the gradient at iteration t, l-Lipschitz in θ. We study the recursion θt+1 = θt − γtgt(θt). We will make use of the two following classical inequalities from convex analysis (see [7]) :
Regional control after concomitant chemoradiotherapy without planned neck dissection in node-positive head and neck squamous cell carcinomas

Objectives: Although three-weekly high-dose (100mg/m2) cisplatin (three cycles) chemoradiotherapy has been considered a standard regimen for patients with advanced head and neck squamous cell carcinomas (HNSCC), this protocol is associated with significant acute and late toxicities. Therefore, weekly cisplatin at a dose of 40mg/m2 has been used at our institution since 2006. This retrospective study was aimed at assessing the oncologic efficacy of weekly cisplatin chemoradiotherapy for the control of nodal metastasis. Methods: We analyzed 28 patients with node-positive HNSCC treated with weekly cisplatin and concurrent radiotherapy. Computed tomography was performed 4-8 weeks after the completion of chemoradiotherapy to evaluate nodal response. If residual neck disease was apparent or suspected, we performed early salvage neck dissection (ND). In cases with a complete response (CR), we took a “ wait and see ” approach. When no viable tumor cells were observed in the surgical specimens obtained by ND, nodal metastasis was defined as controlled by weekly cisplatin chemoradiotherapy alone. Results: Nodal metastasis was evaluated as having a CR in 20 patients (71%). Eight patients (29%) underwent early salvage ND. Recurrent primary tumors were observed in the other four patients (14%). Salvage primary resection and associated ND were performed for these four patients. In 7 of 12 patients undergoing ND, no viable tumor cells were observed. In 23 of 28 patients, neck diseases were controlled by chemoradiotherapy alone (not including salvage by ND). In 27 of 28 patients, neck diseases were controlled by the overall treatment (including salvage by ND). The rate of nodal control by chemoradiotherapy alone and by the overall treatment was found to be 82.0% and 96.3%, respectively, using the Kaplan-Meier method. The three-year overall and disease free survival rates were 86.8% and 80.8%, respectively. Conclusion: Concomitant weekly cisplatin at a dose of 40mg/m2 chemoradiotherapy showed a good control rate of not only primary lesions but also neck diseases.
Clusters of Galaxies : Probes of Cosmological Structure and Galaxy Evolution

We have analyzed deep, Chandra observations of several clusters of galaxies to identify Active Galactic Nuclei (AGN). Comparison of these X-ray observations with ground-based imaging reveals that some of these X-ray sources are associated with optically-bright counterparts. Our spectroscopy of these sources reveals that many are cluster members. These results imply the AGN fraction in clusters is higher than expected and has implications for the impact of the cluster environment on galaxy evolution, the fueling of AGN, the growth of supermassive black holes, and the role of AGN feedback in heating the intracluster medium.