Miracle-dz/UniFAR-FTUs huggingface dataset:
HeadPoST

Objective To critique the Head Positioning in Stroke Trial (HeadPoST) study methods in relation to preceding research findings in an aim to clarify the potential efficacy of positioning interventions and direction for future research. Methods Head positioning research prior to the conduct of HeadPoST was reviewed by a team of international stroke experts, and methods and findings were compared to HeadPoST. Results Methods used to select HeadPoST patients differ substantially from those used in original head positioning studies, in particular enrollment of all types of stroke. HeadPoST enrolled primarily minor strokes (median NIH Stroke Scale 4, interquartile range [IQR] 2–8) without vascular imaging confirmation of subtype; elapsed time from stroke symptom onset to the initiation of intervention was late (median 14 hours, IQR 5–35), and time from hospital admission to enrollment was delayed (median 7 hours, IQR 2–26). Intervention integrity was not reported, including ability to achieve/maintain 30° head elevation in beds lacking head elevation capabilities. Deterioration or improvement associated with the intervention is unknown as serial assessments were not completed, and the trial's 3-month outcome was powered using unrelated study data. Conclusions The design of HeadPoST was suboptimal to measure differences produced by the intervention. Future head positioning trials in discrete patient cohorts (in particular, large vessel occlusion) with endpoints supported by pilot work are required to understand the efficacy of this simple yet potentially important intervention.
Initial denaturing conditions influence the slow folding phase of acylphosphatase associated with proline isomerization

The folding kinetics of human common‐type acylphosphatase (cAcP) from its urea‐ and TFE‐denatured states have been determined by stopped‐flow fluorescence techniques. The refolding reaction from the highly unfolded state formed in urea is characterized by double exponential behavior that includes a slow phase associated with isomerism of the Gly53–Pro54 peptide bond. However, this slow phase is absent when refolding is initiated by dilution of the highly α‐helical denatured state formed in the presence of 40% trifluoroethanol (TFE). NMR studies of a peptide fragment corresponding to residues Gly53–Gly69 of cAcP indicate that only the native‐like trans isomer of the Gly–Pro peptide bond is significantly populated in the presence of TFE, whereas both the cis and trans isomers are found in an ∼1:9 ratio for the peptide bond in aqueous solution. Molecular modeling studies in conjunction with NMR experiments suggest that the trans isomer of the Gly53–Pro54 peptide bond is stabilized in TFE by the formation of a nonnative‐like hydrogen bond between the CO group of Gly53 and the NH group of Lys57. These results therefore reveal that a specific nonnative interaction in the denatured state can increase significantly the overall efficiency of refolding.
The metabolic syndrome in hypertension: European society of hypertension position statement

The metabolic syndrome considerably increases the risk of cardiovascular and renal events in hypertension. It has been associated with a wide range of classical and new cardiovascular risk factors as well as with early signs of subclinical cardiovascular and renal damage. Obesity and insulin resistance, beside a constellation of independent factors, which include molecules of hepatic, vascular, and immunologic origin with proinflammatory properties, have been implicated in the pathogenesis. The close relationships among the different components of the syndrome and their associated disturbances make it difficult to understand what the underlying causes and consequences are. At each of these key points, insulin resistance and obesity/proinflammatory molecules, interaction of demographics, lifestyle, genetic factors, and environmental fetal programming results in the final phenotype. High prevalence of end-organ damage and poor prognosis has been demonstrated in a large number of cross-sectional and a few number of prospective studies. The objective of treatment is both to reduce the high risk of a cardiovascular or a renal event and to prevent the much greater chance that metabolic syndrome patients have to develop type 2 diabetes or hypertension. Treatment consists in the opposition to the underlying mechanisms of the metabolic syndrome, adopting lifestyle interventions that effectively reduce visceral obesity with or without the use of drugs that oppose the development of insulin resistance or body weight gain. Treatment of the individual components of the syndrome is also necessary. Concerning blood pressure control, it should be based on lifestyle changes, diet, and physical exercise, which allows for weight reduction and improves muscular blood flow. When antihypertensive drugs are necessary, angiotensin-converting enzyme inhibitors, angiotensin II-AT1 receptor blockers, or even calcium channel blockers are preferable over diuretics and classical β-blockers in monotherapy, if no compelling indications are present for its use. If a combination of drugs is required, low-dose diuretics can be used. A combination of thiazide diuretics and β-blockers should be avoided.
Learning recurrent dynamics in spiking networks

Spiking activity of neurons engaged in learning and performing a task show complex spatiotemporal dynamics. While the output of recurrent network models can learn to perform various tasks, the possible range of recurrent dynamics that emerge after learning remains unknown. Here we show that modifying the recurrent connectivity with a recursive least squares algorithm provides sufficient flexibility for synaptic and spiking rate dynamics of spiking networks to produce a wide range of spatiotemporal activity. We apply the training method to learn arbitrary firing patterns, stabilize irregular spiking activity of a balanced network, and reproduce the heterogeneous spiking rate patterns of cortical neurons engaged in motor planning and movement. We identify sufficient conditions for successful learning, characterize two types of learning errors, and assess the network capacity. Our findings show that synaptically-coupled recurrent spiking networks possess a vast computational capability that can support the diverse activity patterns in the brain.
Traffic Flow Prediction from Loop Counter Sensor Data using Machine Learning Methods

Due to increasing demand and growing cities, traffic prediction has been a topic of interest for many researchers for the past few decades. The availability of large amounts of traffic-related data and the emerging field of machine learning algorithms has led to a significant leap towards data-driven methods. In this paper, loop counter data are used to develop models that can predict traffic flow for several different prediction intervals into the future. In depth exploratory data analysis and statistical testing is performed to obtain good quality informative features. Several feature sets were compared by using different machine learning methods: Ridge Regression, SVR and Random Forests. The results show that in order to obtain good prediction results thorough feature extraction is just as or even more important than learning method selection. Good features enables us to use less complex methods, which run faster, are more reliable and easier to maintain. In conclusion, we address ideas regarding how predictions could be improved even further.
The Nature of Countercyclical Income Risk

We study business cycle variation in individual earnings risk using a confidential and very large data set from the US Social Security Administration. Contrary to past research, we find that the variance of idiosyncratic shocks is not countercyclical. Instead, it is the left-skewness of shocks that is strongly countercyclical: during recessions, large upward earnings movements become less likely, whereas large drops in earnings become more likely. Second, we find that the fortunes during recessions are predictable by observable characteristics before the recession. Finally, the cyclicality of earnings risk is dramatically different for the top 1 percent compared with the rest of the population.
Parents’ concerns regarding the growth characteristics of their adolescents: a qualitative inquiry in Iran

ABSTRACT In recent times, parents have become increasingly concerned, both subjectively and objectively, about their adolescents' body height/weight growth. Parent-adolescent interactions about this issue and the potential socio-psychological consequences of such interactions should be considered as an important influencing factor on the future of adolescents' sexual and reproductive health. To achieve a greater understanding of such concerns, it is necessary to further elucidate parents' experiences on this topic, so as to expand the existing literature. This study aimed to explain the perceptions of parents' concerns regarding their adolescents' growth characteristics in the socio-cultural context of Iran as a transitional society. This paper is part of a larger qualitative study designed using the Constructivist Grounded Theory Methodology (CGTM). We conducted open-ended intensive interviews with eleven parents individually and recruited them through purposeful and theoretical sampling from a teaching hospital, community, and a primary school in Tehran with theoretical sampling variation in terms of teenagers' age, sex, and birth order, place of residence, parents' occupation and education, and the self-reported socio-economic status. Using the analytical procedures of the CGTM, we performed analyses. In the findings, the concept of 'living with constant sense of uncertainty' emerged from the subcategories including 'feeling existing and potential concern about expected minimum and maximum bio-positions of growth,' 'feeling potential concern about biological health consequences,' 'feeling potential concern about the emergence of early/late maturity signs,' 'feeling potential concern about adolescent's emotional threat,' 'feeling concerned about future employment, education, marriage, and fertility,' and 'feeling potential concern about the society's view'. These findings suggest that parents are living with a constant sense of uncertainty about their teens' growth characteristics throughout the transition from adolescence. All stakeholders including parents, health-care practitioners and policymakers, and anthropologists/sociologists should be focus on such concerns, in order to manage them and their possible socio-psychological burdens.
Empirical Algorithm for Significant Wave Height Retrieval from Wave Mode Data Provided by the Chinese Satellite Gaofen-3

Gaofen-3 (GF-3), the first Chinese civil C-band synthetic aperture radar (SAR), was successfully launched by the China Academy of Space Technology on 10 August 2016. Among its 12 imaging modes, wave mode is designed to monitor the ocean surface waves over the open ocean. An empirical retrieval algorithm of significant wave height (SWH), termed Quad-Polarized C-band WAVE algorithm for GF-3 wave mode (QPCWAVE_GF3), is developed for quad-polarized SAR measurements from GF-3 in wave mode. QPCWAVE_GF3 model is built using six SAR image and spectrum related parameters. Based on a total of 2576 WaveWatch III (WW3) and GF-3 wave mode match-ups, 12 empirical coefficients of the model are determined for 6 incidence angle modes. The validation of the QPCWAVE_GF3 model is performed through comparisons against independent WW3 modelling hindcasts, and observations from altimeters and buoys from January to October in 2017. The assessment shows a good agreement with root mean square error from 0.5 m to 0.6 m, and scatter index around 20%. In particular, applications of the QPCWAVE_GF3 model in SWH estimation for two storm cases from GF-3 data in wave mode and Quad-Polarization Strip I mode are presented respectively. Results indicate that the proposed algorithm is suitable for SWH estimation from GF-3 wave mode and is promising for other similar data.
Association between blood cholesterol and sodium intake in hypertensive women with excess weight

Abstract Restricted sodium intake has been recommended for more than 1 century for the treatment of hypertension. However, restriction seems to increase blood cholesterol. In women with excess weight, blood cholesterol may increase even more because of insulin resistance and the high lipolytic activity of adipose tissue. The aim of this study was to assess the association between blood cholesterol and sodium intake in hypertensive women with and without excess weight. This was a cross-sectional study with hypertensive and nondiabetic women aged 20 to 59 years, recruited at the primary healthcare units of Maceio, Alagoas, Brazilian Northeast. Excess weight was defined as body mass index (BMI) ≥25.0 kg/m2. Sodium intake was estimated by the 24-hour urinary excretion of sodium. Blood cholesterol was the primary outcome investigated by this study, and its relationship with sodium intake and other variables was assessed by Pearson correlation and multivariate linear regression using a significance level of 5%. This study included 165 hypertensive women. Of these, 135 (81.8%) were with excess weight. The mean sodium intake was 3.7 g (±1.9) and 3.4 g (±2.4) in hypertensive women with and without excess weight, respectively. The multiple normal linear regression models fitted to the “blood cholesterol” in the 2 groups reveal that for the group of hypertensive women without excess weight only 1 independent variable “age” is statistically significant to explain the variability of the blood cholesterol levels. However, for the group of hypertensive women with excess weight, 2 independent variables, age and sodium intake, can statistically explain variations of the blood cholesterol levels. Blood cholesterol is statistically inversely related to sodium intake for hypertensive women with excess weight, but it is not statistically related to sodium intake for hypertensive women without excess weight.
Genomic Characterization of Colistin Heteroresistance in Klebsiella pneumoniae during a Nosocomial Outbreak

ABSTRACT Klebsiella pneumoniae is emerging as an important nosocomial pathogen due to its rapidly increasing multidrug resistance, which has led to a renewed interest in polymyxin antibiotics, such as colistin, as antibiotics of last resort. However, heteroresistance (i.e., the presence of a subpopulation of resistant bacteria in an otherwise susceptible culture) may hamper the effectiveness of colistin treatment in patients. In a previous study, we showed that colistin resistance among extended-spectrum-beta-lactamase (ESBL)-producing K. pneumoniae isolates emerged after the introduction of selective digestive tract decontamination (SDD) in an intensive care unit (ICU). In this study, we investigated heteroresistance to colistin among ESBL-producing K. pneumoniae isolates by using population analysis profiles (PAPs). We used whole-genome sequencing (WGS) to identify the mutations that were associated with the emergence of colistin resistance in these K. pneumoniae isolates. We found five heteroresistant subpopulations, with colistin MICs ranging from 8 to 64 mg/liter, which were derived from five clonally related, colistin-susceptible clinical isolates. WGS revealed the presence of mutations in the lpxM, mgrB, phoQ, and yciM genes in colistin-resistant K. pneumoniae isolates. In two strains, mgrB was inactivated by an IS3-like or ISKpn14 insertion sequence element. Complementation in trans with the wild-type mgrB gene resulted in these strains reverting to colistin susceptibility. The MICs for colistin-susceptible strains increased 2- to 4-fold in the presence of the mutated phoQ, lpxM, and yciM alleles. In conclusion, the present study indicates that heteroresistant K. pneumoniae subpopulations may be selected for upon exposure to colistin. Mutations in mgrB and phoQ have previously been associated with colistin resistance, but we provide experimental evidence for roles of mutations in the yciM and lpxM genes in the emergence of colistin resistance in K. pneumoniae.
The Effect of Weld Reinforcement and Post-Welding Cooling Cycles on Fatigue Strength of Butt-Welded Joints under Cyclic Tensile Loading

This research deals with the fatigue behavior of butt-welded joints, by considering the geometry and post-welding cooling cycles, as a result of cooling in quiet air and immersed in water. ASTM A-36 HR structural steel was used as the base metal for the shielded metal arc welding (SMAW) process with welding electrode E6013. The welding reinforcement was 1 mm and 3 mm, respectively; axial fatigue tests were carried out to determine the life and behavior in cracks propagation of the tested welded joints, mechanical characterization tests of properties in welded joints such as microhardness, Charpy impact test and metallographic analysis were carried out. The latter were used as input for the analysis by finite elements which influence the initiation and propagation of cracks and the evaluation of stress intensity factors (SIF). The latter led to obtaining the crack propagation rate and the geometric factor. The tested specimens were analyzed, by taking photographs of the cracks at its beginning in order to make a count of the marks at the origin of the crack. From the results obtained and the marks count, the fatigue crack growth rate and the influence of the cooling media on the life of the welded joint are validated, according to the experimental results. It can be concluded that the welded joints with a higher weld reinforcement have a shorter fatigue life. This is due to the stress concentration that occurs in the vicinity of the weld toe.
Applying Contextual Integrity to Open Data Publishing

Data is fast becoming a commodity to be traded, utilised and shared between individuals and businesses alike, so much so that it has been branded ’the new oil’ (Palmer, 2006); (Van’t Spijker, 2014). Open data is data which can be freely downloaded, used and shared for any purpose by anyone (Open Data Institute, 2016), while open government data is open data that originates from a government controlled entity a public body (Open Government Data Working Group, 2016). A public body is a body or organisation that is governed by public law which exercises public functions that are woven ”into the fabric of public regulation” (Burton, 2002).
On the Interpretation of Path-specific Effects in Health Disparities Research.

Disparities in healthcare and health outcomes are a substantial public health issue in many areas of the world. From an epidemiologic perspective, understanding the causes of disparity may inform the design of policies or interventions that address health inequity. Epidemiologists and others have sought such understanding for decades, often relying on traditional regression-based techniques, such as the Baron-Kenny approach to mediation analysis, to unpack how health disparities arise. Recently, epidemiologists have turned to novel causal mediation analysis approaches that overcome many limitations of the strict Baron-Kenny approach. Yet, the interpretation of these new methods, as cast in a potential outcomes framework, has not always been precise or clear in the disparities context. In this issue of EPIDEMIOLOGY, Blakely et al examined disparities in mortality in New Zealand in three periods of time, 1981 to 1984, 1996 to 1999, and 2006 to 2011. They compared mortality among the indigenous Mãori versus Europeans who colonized and settled New Zealand since the 19th century. In each period, they asked (1) how much the ethnic disparity was mediated by socioeconomic factors in adulthood [adult socioeconomic status (SES)], a natural indirect effect; (2) how much the ethnic disparity was mediated by smoking beyond mediation by adult SES, a pathspecific effect; and (3) how much the ethnic disparity would have changed if smoking had been eliminated in that period, a controlled direct effect. The literature on causal mediation analysis in the disparities context has noted nontrivial challenges with pursuing the natural indirect effect (and by extension, the path-specific effect). Perhaps because of these challenges, the authors appear to emphasize their controlled direct effect estimates as relevant for policy-making but withhold this status from their estimates of the natural indirect effect and path-specific effect. In this commentary, I present alternative ways to interpret their natural indirect effect and path-specific effect estimates that are relevant for policy-making, ways that relate to the “weaker interpretation” of VanderWeele and Robinson and “randomized interventional analogues” that the authors mention. To provide some context, I begin with a review of the distinction between natural indirect effects and their randomized interventional analogues in the disparities context. I then review alternative interpretations of path-specific effects as randomized interventional analogues, with formal proofs provided in the eAppendix; http://links.lww. com/EDE/B344. Note that I use the term disparity throughout to describe differences that society considers avoidable and unjust. This notion is consistent with the concept of inequity. I assume that this use aligns with use of “inequalities” by Blakely et al.
Visible Light Based Occupancy Inference Using Ensemble Learning

As a key component of building management and security, occupancy inference through smart sensing has attracted a lot of research attention for nearly two decades. Recently, a cutting edge technique visible light sensing (VLS) that utilizes the LED luminaires as light sensors has shown its promising application potentials in occupancy inference as it piggybacks on pervasive lighting infrastructure without extra equipment deployment. Although existing inference algorithms based on the VLS data set can achieve high accuracy, the performance degrades when the occupants are moving. This paper focuses on the occupancy inference issue and presents an ensemble learning algorithm to improve the inference accuracy. We use heterogeneous learning algorithms to generate diverse learners. Consequently, we adopt forward sequential pruning to enhance the ensemble that pursues inference error minimization. We conduct extensive experiments based on the field data. The experiment results show that the proposed algorithm is able to improve inference accuracy, especially for highly dynamic occupancy data set.