Miracle-dz/UniFAR-FTUs huggingface dataset:
Semilocal Milnor K-theory

In this paper, semilocal Milnor $K$-theory of fields is introduced and studied. A strongly convergent spectral sequence relating semilocal Milnor $K$-theory to semilocal motivic cohomology is constructed. In weight 2, the motivic cohomology groups $H^p_{Zar}(k,\mathbb Z(2))$, $p\leq 1$, are computed as semilocal Milnor $K$-theory groups $\widehat{K}^M_{2,3-p}(k)$. The following applications are given: (i) several criteria for the Beilinson-Soule Vanishing Conjecture; (ii) computation of $K_4$ of a field; (iii) the Beilinson conjecture for rational $K$-theory of fields of prime characteristic is shown to be equivalent to vanishing of rational semilocal Milnor $K$-theory.
An ontology for flow thinking based on decoupling points – unravelling a control logic for lean thinking

ABSTRACT Continuous flow is the guiding star for lean thinking and considered the ideal state for value streams. Despite this objective, it is seldom possible to obtain a state of continuous flow in a wider context. Decision makers face dynamic environments, and variable internal preconditions require a flow-thinking approach that provides support in response to these challenges. In the present study, the underlying logic of flow thinking is first identified as the key management layer, and thereafter the effectiveness of flow is targeted. The vision of continuous flow is challenged by different exogenous requirements that result in flow discontinuities. Flow thinking is then used to identify 10 decision categories based on these discontinuities, each related to a type of decoupling point and classified as time-based (exogenous) or conversion-based (endogenous). The flow-thinking approach is finally applied in three different contexts: a time-phased product structure, a modularized approach for planning and control, and a mixed-model value stream.
The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: N-body mock challenge for the quasar sample

The growth rate and expansion history of the Universe can be measured from large galaxy redshift surveys using the Alcock-Paczynski effect. We validate the Redshift Space Distortion models used in the final analysis of the Sloan Digital Sky Survey (SDSS) extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 16 quasar clustering sample, in configuration and Fourier space, using a series of HOD mock catalogues generated using the OuterRim N-body simulation. We test three models on a series of non-blind mocks, in the OuterRim cosmology, and blind mocks, which have been rescaled to new cosmologies, and investigate the effects of redshift smearing and catastrophic redshifts. We find that for the non-blind mocks, the models are able to recover $f\sigma_8$ to within 3% and $\alpha_\parallel$ and $\alpha_\bot$ to within 1%. The scatter in the measurements is larger for the blind mocks, due to the assumption of an incorrect fiducial cosmology. From this mock challenge, we find that all three models perform well, with similar systematic errors on $f\sigma_8$, $\alpha_\parallel$ and $\alpha_\bot$ at the level of $\sigma_{f\sigma_8}=0.013$, $\sigma_{\alpha_\parallel}=0.012$ and $\sigma_{\alpha_\bot}=0.008$. The systematic error on the combined consensus is $\sigma_{f\sigma_8}=0.011$, $\sigma_{\alpha_\parallel}=0.008$ and $\sigma_{\alpha_\bot}=0.005$, which is used in the final DR16 analysis. For BAO fits in configuration and Fourier space, we take conservative systematic errors of $\sigma_{\alpha_\parallel}=0.010$ and $\sigma_{\alpha_\bot}=0.007$.
Projected WIMP sensitivity of the XENONnT dark matter experiment

XENONnT is a dark matter direct detection experiment, utilizing 5.9 t of instrumented liquid xenon, located at the INFN Laboratori Nazionali del Gran Sasso. In this work, we predict the experimental background and project the sensitivity of XENONnT to the detection of weakly interacting massive particles (WIMPs). The expected average differential background rate in the energy region of interest, corresponding to (1, 13) keV and (4, 50) keV for electronic and nuclear recoils, amounts to 12.3 ± 0.6 (keV t y)-1 and (2.2± 0.5)× 10−3 (keV t y)-1, respectively, in a 4 t fiducial mass. We compute unified confidence intervals using the profile construction method, in order to ensure proper coverage. With the exposure goal of 20 t y, the expected sensitivity to spin-independent WIMP-nucleon interactions reaches a cross-section of 1.4×10−48 cm2 for a 50 GeV/c2 mass WIMP at 90% confidence level, more than one order of magnitude beyond the current best limit, set by XENON1T . In addition, we show that for a 50 GeV/c2 WIMP with cross-sections above 2.6×10−48 cm2 (5.0×10−48 cm2) the median XENONnT discovery significance exceeds 3σ (5σ). The expected sensitivity to the spin-dependent WIMP coupling to neutrons (protons) reaches 2.2×10−43 cm2 (6.0×10−42 cm2).
Effects of elevated CO2 on leaf gas exchange in beech and oak at two levels of nutrient supply: Consequences for sensitivity to drought in beech

Beech (Fagus sylvatica L.) and pedunculate oak (Quercus robur L,) were grown from seed for two whole seasons at two CO, concentrations (ambient and ambient + 250 mu mol mol(-1)) with two levels of soil nutrient supply, Measurements of net leaf photosynthetic rate (A) and stomatal conductance (g(s)) of well-watered plants were taken over both seasons; a drought treatment was applied in the middle of the second growing season to a separate sample of beech drawn from the same population, The net leaf photosynthetic rate of well-watered plants was stimulated in elevated CO2 by an average of 75% in beech and 33% in oak; the effect continued through both growing seasons at both nutrient levels, There were no interactive effects of CO2 concentration and nutrient level on A or g(s) in beech or oak, Stomatal conductance was reduced in elevated CO2 by an average of 34% in oak, but in beech there were no significant reductions in g(s) except under cloudy conditions (-22% in elevated CO2), During drought, there was no effect of CO2 concentration on g(s) in beech grown with high nutrients, but for beech grown with low nutrients, g(s) was significantly higher in elevated CO2, causing more rapid soil drying, With high nutrient supply, soil drying was more rapid at elevated CO2 due to increased leaf area, It appears that beech may substantially increase whole-plant water consumption in elevated CO2, especially under conditions of high temperature and irradiance when damage due to high evaporative demand is most likely to occur, thereby putting itself at risk during periods of drought.
A student made MOOC for medical students during the SARS-CoV-2 pandemic.

Background: Latin America was one of the last regions of the world to become affected by the COVID-19 pandemic. As a response to the emergency virtual education was implemented in almost every country of the region. Methods: a massive open online course about epilepsy was made using only free software and platforms following the international league against epilepsy competence-based domains for epileptology teaching. Results: 250 healthcare students signed up for the course and only 17.2% of them had previously participated in courses like this one. This course had a completion rate of 37.2% and of the students that completed the course 98.3% would participate in course like this in the future. Conclusion: In conclusion MOOCs can be easily implemented as a powerful pedagogic strategy during the COVID-19 pandemic and can have a positive impact not only in in its proposed learning objectives but it can help closing the gap that prevent Latin American healthcare students to acquire actively knowledge trough them.
An optimal 1H-MRS technique at 7T: Proof-of-principle in Chronic Multiple Sclerosis and Neuromyelitis Optica Brain Lesions and Normal Appearing Brain Tissue.

Magnetic Resonance Spectroscopy (MRS) allows for the non-invasive quantification of neurochemicals and has the potential to differentiate between the pathologically distinct diseases, multiple sclerosis (MS) and AQP4Ab-positive neuromyelitis optica spectrum disorder (AQP4Ab-NMOSD). In this study we characterised the metabolite profiles of brain lesions in 11 MS and 4 AQP4Ab-NMOSD patients using an optimised MRS methodology at ultra-high field strength (7T) incorporating correction for T2 water relaxation differences between lesioned and normal tissue. MS metabolite results were in keeping with the existing literature: total NAA was lower in lesions compared to normal appearing brain white matter (NAWM) with reciprocal findings for Inositol. An unexpected subtlety revealed by our technique was that total NAA differences were driven by NAA-glutamate (NAAG), a ubiquitous CNS molecule with functions quite distinct from NAA though commonly quantified together with NAA in MRS studies as total NAA. Surprisingly, AQP4Ab-NMOSD showed no significant differences for total NAA, NAA, NAAG or Inositol between lesion and NAWM sites, nor were there any differences between MS and AQP4Ab-NMOSD for a priori hypotheses. Post-hoc testing did however reveal greater total NAA in MS compared to AQP4Ab-NMOSD NAWM. Post-hoc testing also revealed a significant correlation between NAWM Ins:NAA and disability (as measured by EDSS) for disease groups combined, driven by the AP4Ab-NMOSD group. Utilising an optimised MRS methodology, our study highlights some under-explored subtleties in MRS profiles, such as the absence of Inositol concentration differences in AQP4Ab-NMOSD brain lesions versus NAWM and the important influence of NAAG differences between lesions and normal appearing white matter in MS.
An Optimization Framework to Study the Balance Between Expected Fatalities Due to COVID-19 and the Reopening of U.S. Communities

During the COVID-19 pandemic, communities faced two conflicting objectives: 1) minimizing infections among vulnerable populations with higher risk for severe illness and 2) enabling reopening to revive American livelihoods. The U.S. pandemic strategy myopically considered one objective at a time, with lockdowns that addressed the former, but was detrimental to the latter, and phased reopening that pursued the latter, but lost control over the former. How could we prioritize interventions to simultaneously minimize cases of severe illness and fatalities while reopening? A team of researchers anchored by the Center on Stochastic Modeling, Optimization, & Statistics (COSMOS), The University of Texas at Arlington, has formulated a computationally efficient optimization framework, referred to as COSMOS COVID-19 Linear Programming (CC19LP), to study the delicate balance between the expected fatality rate due to cases of severe illness and the level of normalcy in the community. The key to the CC19LP framework is a focus on “key contacts” that separate individuals at higher risk from the rest of the population. CC19LP minimizes expected fatalities by optimizing the use of available interventions, namely, COVID-19 testing, personal protective equipment (PPE), COVID-19 vaccines, and social precautions, such as distancing, handwashing, and face coverings. A C3.ai award-winning online CC19LP tool is accessible from the COSMOS COVID-19 project site (https://cosmos.uta.edu/projects/covid-19/) and has been tested for all 3142 U.S. county areas. Results are demonstrated for several metropolitan counties with a deeper investigation for Miami-Dade County in Florida. Note to Practitioners—In this article, a computationally fast optimization framework is presented to study the delicate balance between reopening U.S. communities and controlling severe cases of COVID-19 that lead to hospitalizations and fatalities. This framework can provide guidance to decision-makers on optimal intervention strategies for protecting high-risk individuals while reopening communities. This optimization framework demonstrates a practical approach to conduct decision-making in an uncertain environment and can be useful for the prioritization of resources and interventions in the case of future epidemics or pandemics. Resources on understanding and implementing the framework are publicly available, including an award-winning online optimization tool that automatically accesses county-level data from Census, Centers for Disease Control and Prevention (CDC), and Johns Hopkins COVID-19 repositories.
The Infectious Nature of Patient-Generated SARS-CoV-2 Aerosol

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission causing coronavirus disease 2019 (COVID-19) may occur through multiple routes. We collected aerosol samples around six patients admitted into mixed acuity wards in April of 2020 to identify the risk of airborne SARS-CoV-2. Measurements were made to characterize the size distribution of aerosol particles, and size-fractionated, aerosol samples were collected to assess the presence of infectious virus in particles sizes of >4.1 m, 1-4 m, and <1 m in the patient environment. Samples were analyzed by real-time reverse-transcriptase polymerase chain reaction (rRT-PCR), cell culture, western blot, and transmission electron microscopy (TEM). SARS-CoV-2 RNA was detected in all six rooms in all particle size fractions (>4.1 m, 1-4 m, and <1 m). Increases in viral RNA during cell culture of the virus from recovered aerosol samples demonstrated the presence of infectious, replicating virions in three <1 m aerosol samples (P<0.05). Viral replication of aerosol was also observed in the 1-4 m stage but did not reach statistical significance (0.05<P<0.10). Western blot and TEM analysis of these samples also showed evidence of viral proteins and intact virions. The infectious nature of aerosol collected in this study further suggests that airborne transmission of COVID-19 is possible, and that aerosol prevention measures are necessary to effectively stem the spread of SARS-CoV-2.
ABC-GWAS: Functional Annotation of Estrogen Receptor-Positive Breast Cancer Genetic Variants

Over the past decade, hundreds of genome-wide association studies (GWAS) have implicated genetic variants in various diseases, including cancer. However, only a few of these variants have been functionally characterized to date, mainly because the majority of the variants reside in non-coding regions of the human genome with unknown function. A comprehensive functional annotation of the candidate variants is thus necessary to fill the gap between the correlative findings of GWAS and the development of therapeutic strategies. By integrating large-scale multi-omics datasets such as the Cancer Genome Atlas (TCGA) and the Encyclopedia of DNA Elements (ENCODE), we performed multivariate linear regression analysis of expression quantitative trait loci, sequence permutation test of transcription factor binding perturbation, and modeling of three-dimensional chromatin interactions to analyze the potential molecular functions of 2,813 single nucleotide variants in 93 genomic loci associated with estrogen receptor-positive breast cancer. To facilitate rapid progress in functional genomics of breast cancer, we have created “Analysis of Breast Cancer GWAS” (ABC-GWAS), an interactive database of functional annotation of estrogen receptor-positive breast cancer GWAS variants. Our resource includes expression quantitative trait loci, long-range chromatin interaction predictions, and transcription factor binding motif analyses to prioritize putative target genes, causal variants, and transcription factors. An embedded genome browser also facilitates convenient visualization of the GWAS loci in genomic and epigenomic context. ABC-GWAS provides an interactive visual summary of comprehensive functional characterization of estrogen receptor-positive breast cancer variants. The web resource will be useful to both computational and experimental biologists who wish to generate and test their hypotheses regarding the genetic susceptibility, etiology, and carcinogenesis of breast cancer. ABC-GWAS can also be used as a user-friendly educational resource for teaching functional genomics. ABC-GWAS is available at http://education.knoweng. org/abc-gwas/.
The Effect of Preparation Techniques on Sem-Imaging of Pit Membranes

This paper examines the effects of 30 preparation techniques on SEMimages of pit membranes in vessels and tracheids from the two latest growth rings in twigs of Pinus wallichiana, Fraxinus americana and Laurus nobilis. Most variation observed is due to coating and treatment with chemical solutions, such as acetone, ethanol and hydrogen peroxide. The effects of chemicals appear to be associated with the thickness of the pit membrane, resulting in an increased density and diameter of pores in pit membranes of F. americana and L. nobilis and an almost complete dissolution of the porous margo in P. wallichiana. Although different protocols offer advantages for different species, the following methods are recommended: (1) the use of fresh material, (2) air-drying without any chemical treatment, (3) splitting of dried samples, (4) vacuum evaporation with platinum, and (5) SEM-imaging at an accelerating voltage below 5 kV.
Disinfection of Drinking Water from Escherichia coli and Pseudomonas aeruginosa by Using Silver Nanoparticles

Due to the lack of raining levels, accretion population growth and increasing pollution in the water resources, the world nowadays is facing a real challenge of providing enough drinking water supplies. Many common species of bacteria could be founded in the water resources like Escherichia coli and Pseudomonas aeruginosa. This paper is an attempt to find an effective agent to eliminate these bacteria. silver nanoparticles (AgNPs) have been tested against these bacteria. Sliver nanoparticles were synthesized by wet chemistry method and were dispersed in an aqueous suspension and prepared in different concentrations. Also, some common antibiotics have been tested against the selected bacteria including; gentamycin (GN), cephalexin (KF), erythromycin (E), ampicillin (AM) and amoxicillin (AMX). The results confirmed that silver nanoparticles had a good antibacterial effect against the selected bacteria in comparison with the tested antibiotics.
Effect of Tool Rotation Speed on the Microstructure and Mechanical Properties of Al-12.7 % Si Alloy by Friction Stir Processing

FSP was applied to the as-cast Al-12.7Si alloy at a traverse speed of 150mm/min and different rotation speeds (700rpm to 1000rpm). The coarse α-Al dendrites and eutectic Si phase can be refined by friction stir process. After FSP, Si particles are homogeneously distributed in the Al matrix with equaixed grains. Tool rotation speed has an effect on the microstructure and mechanical properties of the Al-12.7Si alloy. The size of Si particles decreases and that of the Al matrix grains increases with increase of the rotation speed. The microhardness values of the stir zone increase with increase of rotation speed. With rotation speed increases, the ultimate tensile strength is slightly increased and the elongation is greatly improved.
Tailoring Polylactic Acid Properties for Packaging Applications: Effects of Co‐Addition of Halloysite Nanotubes and Selected Plasticizers

Polylactic acid (PLA) has recently given a huge attention because of its mechanical properties and good physical like good biodegradability and processability, high tensile modulus and strength. In the current research, the researchers utilized sesame oil (SO) and low molecular weight polyethylene glycol (PEG) as hydrophobic and hydrophilic plasticizers, towards improvise the ductility and toughness of PLA. The researchers synthesized nanocomposites by solution casting of the neat PLA/HNTs and PLA blends with weight ratio of (0,10, 20 and 30 wt%) for PEG and (0, 5 and 10 wt%) for SO. The influence of both plasticizers on chemical, thermal and mechanical properties of the nanocomposites were investigated. Characterization of the systems was achieved by mechanical testing and thermogravimetric analysis (TGA), field emission scanning electron microscope (FESEM), Fourier transform infrared spectroscopy (FTIR). The FTIR analyses confirmed the existing of hydrogen bonding between PLA and both PEG and SO. significant improvement was shown by the plasticized nanocomposites in elongation at break with the adding of PEG and SO, meanwhile, the plasticized films’ strength were decreased. For the thermal analyses, all the films exhibited lower thermal stability compared to PLA/HNTs film.
Assessment of maternal health services utilization in Pakistan: the role of socio-demographic characteristics

Abstract Background High-quality prenatal care has a significant positive impact on maternal and infant health as it helps timely diagnosis and treatment of pregnancy complications. Objective To examine factors associated with the utilization of maternal health care using the optimal count regression model. Methods A sample of 16,314 women of reproductive ages (15–49) was used. Andersen and Newman's behavioral model of health services utilization was employed for the selection of covariates. Poisson, negative binomial, zero-inflated Poisson, zero-inflated negative binomial (ZINB), Poisson hurdle, and negative binomial hurdle models were fitted and compared to identify the best model. Maternal health care utilization is found associated with maternal age and education, area of residence, domestic violence, the income level of family, access to media, knowledge about AIDS, parity, birth order, and having a child who later died. Results ZINB model is found to be best fitted for the observed data resulting strong influence of mother's education and income level of the family on maternal health care utilization. Conclusion Interventions to improve maternal care services utilization should address individuals and systems to reduce social and economic marginalization.
Avian assemblage along an urban gradient: diversity, abundance and richness

Abstract Diversity in avian assemblages of urban (UR), peri-urban (PE) and rural (RU) areas was studied to explore variations in the avian community dynamics in rural – urban gradient. For this purpose, sampling was done from September 2013 to August 2015. A total of 35 sites, each covering an area of 300 m2 were sampled by using point count method. At each site, randomly three points (minimally 5 m apart from each other) were selected to study the birds. According to data, species richness (F2, 32=47.18, P<0.001) varied significantly along a rural-urban gradient. A significant difference in avian density per sampling site (F2, 32=105.41, P<0.001) was also observed along urbanization gradient. In PE and RU areas, avian assemblages were more diverse than UR areas. Among avian guilds, omnivores were the most abundant in UR while insectivores in PE areas. Frugivores and carnivores were abundant in RU areas. Granivores were recorded in all habitats with similar diversity. A close association was recorded in bird density of RU and PE areas than UR areas. Bird species richness and diversity showed negative correlation with built area and positive correlation with vegetation cover in an area.