Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of Extra Length of Stay Attributable to Hospital-Acquired Infections in Adult ICUs Using a Time-Dependent Multistate Model*

Objectives: The objective of the study was to estimate the length of stay of patients with hospital-acquired infections hospitalized in ICUs using a multistate model. Design: Active prospective surveillance of hospital-acquired infection from January 1, 1995, to December 31, 2012. Setting: Twelve ICUs at the University of Lyon hospital (France). Patients: Adult patients age greater than or equal to 18 years old and hospitalized greater than or equal to 2 days were included in the surveillance. All hospital-acquired infections (pneumonia, bacteremia, and urinary tract infection) occurring during ICU stay were collected. Interventions: None. Measurements and Main Results: The competitive risks of in-hospital death, transfer, or discharge were considered in estimating the change in length of stay due to infection(s), using a multistate model, time of infection onset. Thirty-three thousand four-hundred forty-nine patients were involved, with an overall hospital-acquired infection attack rate of 15.5% (n = 5,176). Mean length of stay was 27.4 (± 18.3) days in patients with hospital-acquired infection and 7.3 (± 7.6) days in patients without hospital-acquired infection. A multistate model–estimated mean found an increase in length of stay by 5.0 days (95% CI, 4.6–5.4 d). The extra length of stay increased with the number of infected site and was higher for patients discharged alive from ICU. No increased length of stay was found for patients presenting late-onset hospital-acquired infection, more than the 25th day after admission. Conclusions: An increase length of stay of 5 days attributable to hospital-acquired infection in the ICU was estimated using a multistate model in a prospective surveillance study in France. The dose-response relationship between the number of hospitalacquired infection and length of stay and the impact of early-stage hospital-acquired infection may strengthen attention for clinicians to focus interventions on early preventions of hospital-acquired infection in ICU.
The Role of Inertia in Modeling Decisions from Experience with Instance-Based Learning

One form of inertia is the tendency to repeat the last decision irrespective of the obtained outcomes while making decisions from experience (DFE). A number of computational models based upon the Instance-Based Learning Theory, a theory of DFE, have included different inertia implementations and have shown to simultaneously account for both risk-taking and alternations between alternatives. The role that inertia plays in these models, however, is unclear as the same model without inertia is also able to account for observed risk-taking quite well. This paper demonstrates the predictive benefits of incorporating one particular implementation of inertia in an existing IBL model. We use two large datasets, estimation and competition, from the Technion Prediction Tournament involving a repeated binary-choice task to show that incorporating an inertia mechanism in an IBL model enables it to account for the observed average risk-taking and alternations. Including inertia, however, does not help the model to account for the trends in risk-taking and alternations over trials compared to the IBL model without the inertia mechanism. We generalize the two IBL models, with and without inertia, to the competition set by using the parameters determined in the estimation set. The generalization process demonstrates both the advantages and disadvantages of including inertia in an IBL model.
Simultaneous Recognition and Assessment of Post-Stroke Hemiparetic Gait by Fusing Kinematic, Kinetic, and Electrophysiological Data

Gait analysis for the patients with lower limb motor dysfunction is a useful tool in assisting clinicians for diagnosis, assessment, and rehabilitation strategy making. Implementing accurate automatic gait analysis for the hemiparetic patients after stroke is a great challenge in clinical practice. This study is to develop a new automatic gait analysis system for qualitatively recognizing and quantitatively assessing the gait abnormality of the post-stroke hemiparetic patients. Twenty-one post-stroke patients and twenty-one healthy volunteers participated in the walking trials. Three of the most representative gait data, i.e., marker trajectory (MT), ground reaction force (GRF), and electromyogram, were simultaneously acquired from these subjects during their walking. A multimodal fusion architecture is established by using these different modal data to qualitatively distinguish the hemiparetic gait from normal gait by different pattern recognition techniques and to quantitatively estimate the patient’s lower limb motor function by a novel probability-based gait score. Seven decision fusion algorithms have been tested in this architecture, and extensive data analysis experiments have been conducted. The results indicate that the recognition performance and estimation performance of the system become better when more modal gait data are fused. For the recognition performance, the random forest classifier based on the GRF data achieves an accuracy of 92.26% outperformed other single-modal schemes. When combining two modal data, the accuracy can be enhanced to 95.83% by using the support vector machine (SVM) fusion algorithm to fuse the MT and GRF data. When integrating all the three modal data, the accuracy can be further improved to 98.21% by using the SVM fusion algorithm. For the estimation performance, the absolute values of the correlation coefficients between the estimation results of the above three schemes and the Wisconsin gait scale scores for the post-stroke patients are 0.63, 0.75, and 0.84, respectively, which means the clinical relevance becomes more obvious when using more modalities. These promising results demonstrate that the proposed method has considerable potential to promote the future design of automatic gait analysis systems for clinical practice.
Evidence for Competition for Target Innervation in the Medial Prefrontal Cortex

Inputs to sensory cortices are known to compete for target innervation through an activity-dependent mechanism during critical periods. To investigate whether this principle also applies to association cortices such as the medial prefrontal cortex (mPFC), we produced a bilateral lesion during early development to the ventral hippocampus (vHC), an input to the mPFC, and analyzed the intensity of the projection from another input, the basolateral amgydala (BLA). We found that axons from the BLA had a higher density of “en passant” boutons in the mPFC of lesioned animals. Furthermore, the density of neurons labeled with retrograde tracers was increased, and neurons projecting from the BLA to the mPFC showed increased expression of FosB. Since neonatal ventral hippocampal lesion has been used as an animal model of schizophrenia, we investigated its effects on behavior and found a negative correlation between the density of retrogradely labeled neurons in the BLA and the reduction of the startle response in the prepulse inhibition test. Our results not only indicate that the inputs from the BLA and the vHC compete for target innervation in the mPFC during postnatal development but also that subsequent abnormal rewiring might underlie the pathophysiology of neuropsychiatric disorders such as schizophrenia.
The Role of Managers in Employee Wellness Programs: A Mixed-Methods Study

Purpose: The purpose of this study is to evaluate managers’ barriers and facilitators to supporting employee participation in the Washington State Wellness program. Design: Exploratory sequential mixed methods. Setting: Four Washington State agencies located in Olympia and Tumwater, Washington. Participants: State employees in management positions (executive, middle, and line), whose job includes supervision of subordinates and responsibility for the performance and conduct of a subunit or group. Methods: We interviewed 23 managers and then used the results to create a survey that was fielded to all managers at the 4 agencies. The survey response rate was 65% (n = 607/935). Analysis: We used qualitative coding techniques to analyze interview transcripts and descriptive statistics to summarize survey data. We used the Total Worker Health framework to organize our findings and conclusions. Results: Managers support the wellness program, but they also face challenges with accommodating employees’ participation due to workload, scheduling inflexibility, and self-efficacy to discuss wellness with direct reports. About half the managers receive support from the manager above them, and most have not received training on the wellness program. Conclusion: Our findings point to several strategies that can strengthen managers’ role in supporting the wellness program: the provision of training, targeted messages, formal expectations, and encouragement (from the manager above) to support employees’ participation.
Using salinity to identify common bottlenose dolphin habitat in Barataria Bay, Louisiana, USA

Following the Deepwater Horizon (DWH) oil spill, numerous studies were conducted to determine impacts on common bottlenose dolphins Tursiops truncatus. Common bottlenose dolphins are found in estuarine environments of the northern Gulf of Mexico which vary in salinity, depending on location (e.g. distance to freshwater source), season, and ocean tides. Although common bottlenose dolphins can be found in low-salinity waters (<15 ppt), they cannot tolerate very low salinity for long periods of time. We matched dolphin telemetry data in Barataria Bay, Louisiana (USA), with contemporaneous estimates of salinity to establish a salinity threshold and identify preferred dolphin habitat. Dolphins frequently used areas where salinity was higher than ~11 ppt, sometimes used areas for short periods of time with predicted salinity of ~8 ppt, and avoided waters with salinities below ~5 ppt. While not a hard boundary, the ~8 ppt threshold can be used to delineate reasonable polygons of preferred dolphin habitat. We temporally averaged the location of the ~8 ppt isohaline from 2005 through 2012 to establish areas of preferred dolphin habitat. In Barataria Bay, the polygon of dolphin habitat encompasses 1167 km2, and extends from the bay’s barrier islands to approximately half-way through marshes in northern parts of the bay. This polygon of suitable common bottlenose dolphin habitat was then ultimately used to quantify cetacean injury due to DWH oil.
Effect of Yield Stress on Fatigue Strength of Non-Load-Carrying Fillet Welded Joints

The purpose of this paper is to make clear the influence of yield stress on the fatigue strength of non-load-carrying fillet welded joints. First of all, brief descriptions about relations between the actual maximum stress considering weld residual stress and the stress range are given, and the combined effect of stress ratio and residual stress is shown. Then, using published fatigue test results, the effect of yield stress on the fatigue strength is studied.In the first step, the results, whose actual maximum stresses are inferred to reach yield stress, are dealt with, and an expression of fatigue strength is obtained. Then, in the next step, the whole data are treated. Finally, the fatigue strength is expressed as follows : Δσ= 33680·σr-0.2282·NF-0.3071 +47.76·σr-0.5508·NF-0.1249· (σr-σmax') where Δσ is the stress range in MPa, σr is the yield stress in MPa, NF is the number of cycles to failure and σmax' is the actual maximum stress considering residual stress in MPa.Based on the equation above mentioned, the effect of yield stress on the fatigue strength of welded joints is discussed. The most important finding is ; that, in the case of high tensile residual stress, the fatigue strength of welded joints tends to decrease with increase in yield stress.
Effects of Volume Overload and Current Techniques for the Assessment of Fluid Status in Patients with Renal Disease

Volume overload is an important, may be the foremost, independent prognostic factor determining the outcome of hemodialysis patients. Therefore, it is crucial to measure fluid status of these patients and avoid volume overload. This review aims to evaluate volume overload, its effects on patients with renal diseases and current methodologies measuring volume status in the body. These techniques will be first classified as clinical evaluation and non-clinical and/or instrumental techniques, which includes biomarkers, ultrasonography, relative blood volume monitoring, bioimpedance, echocardiography, pulmonary artery catheterization, esophageal and/or suprasternal Doppler, and blood viscosity. Advantages and limitations of these different techniques will be reviewed extensively by comparing each other. At last, insights gained from this review can highlight the future prospects in this active area of research.
OUTDOOR DELAYED-STATE VISUALLY AUGMENTED ODOMETRY

This paper presents an efficient approach to outdoor visually augmented odometry. The technique computes relative pose constraints via a robust least squares minimisation of 3D point correspondences, which are in turn obtained from the matching of SIFT features over two consecutive image pairs. Pose constraints are then used to build a history of pose estimates with and incremental delayed-state information filter. The efficiency of the approach resides on the exact sparseness of the delayed-state information form used.
Diagnostic microstructures for the measurement of intrinsic strain in thin films

Freestanding flexible microstructures fabricated from deposited thin films become mechanically unstable when internal stresses exceed critical values. A series of structures with varying geometries is used to determine the critical geometry at which buckling occurs. Observation with an optical microscope quickly reveals qualitative and quantitative information about the internal strain in the film. Strain values between +or-1.5% can be measured for a 2.0 mu m thick film using doubly-supported beams for compressive strain fields, and ring and beam structures for tensile strain fields. Parametric formulae are developed for diagnostic structure response with selected verification by finite element computations.
Climate Change and Anthropogenic Impacts on Wetland and Agriculture in the Songnen and Sanjiang Plain, Northeast China

Influences of the increasing pressure of climate change and anthropogenic activities on wetlands ecosystems and agriculture are significant around the world. This paper assessed the spatiotemporal land use and land cover changes (LULCC), especially for conversion from marshland to other LULC types (e.g., croplands) over the Songnen and Sanjiang Plain (SNP and SJP), northeast China, during the past 35 years (1980–2015). The relative role of human activities and climatic changes in terms of their impacts on wetlands and agriculture dynamics were quantitatively distinguished and evaluated in different periods based on a seven-stage LULC dataset. Our results indicated that human activities, such as population expansion and socioeconomic development, and institutional policies related to wetlands and agriculture were the main driving forces for LULCC of the SJP and SNP during the past decades, while increasing contributions of climatic changes were also found. Furthermore, as few studies have identified which geographic regions are most at risk, how the future climate changes will spatially and temporally impact wetlands and agriculture, i.e., the suitability of wetlands and agriculture distributions under different future climate change scenarios, were predicted and analyzed using a habitat distribution model (Maxent) at the pixel-scale. The present findings can provide valuable references for policy makers on regional sustainability for food security, water resource rational management, agricultural planning and wetland protection as well as restoration of the region.
Re-evaluating classical body type theories: genetic correlation between psychiatric disorders and body mass index

Body type theories, proposed by Kretschmer and Sheldon, are historical concepts that attempt to correlate somatotypes and personalities or psychiatric disorders (Kretschmer, 1925; Sheldon, 1940). Accordingly, Kretschmer classified four types of people: (1) the asthenic type who has a slender body (‘leptosome’) and is more prone to schizophrenia (SCZ); (2) the pyknic type who has a round body and is likely to become manic-depressive illness [bipolar disorder (BD)]; (3) the athletic type with a muscular body who may suffer from epilepsy; and (4) the dysplastic type who cannot be classified as any of the other three types (Kretschmer, 1925). Sheldon had a similar insight, classifying people into ectomorphic (corresponding to Kretschmer's asthenic type), endomorphic (corresponding to the pyknic type), and mesomorphic (corresponding to the athletic type). Interestingly, Sheldon also claimed that there was a deeper connection, with genetic components being linked to both the somatotypes and personality (Sheldon, 1940). Such classifications proposed by these celebrated psychiatrists or psychologists were based on their observational surveys in the beginning of the twentieth century; however, scientific evidence thereof is limited (Sorensen et al. 2006; Zammit et al. 2007). Nevertheless, recent genetic studies have re-evaluated their body type theories by conducting genetic correlation analysis, which employs genetic association results from genome-wide association studies (GWASs) to examine the genetic relationship between two independent phenotypes, that is, theoretically, excluding environmental factors. The first study reported a significant correlation between SCZ and low body mass index (BMI) in a European (EUR) ancestry (Bulik-Sullivan et al. 2015); however, no correlation was observed between BD and BMI (Bulik-Sullivan et al. 2015). Following this, we conducted a study in which we replicated a significant negative correlation between SCZ and BMI, but again found no correlation between BMI and BD in the Japanese samples (Akiyama et al. 2017). More recently, the PGC2 major depressive disorder (MDD) group has reported a positive correlation between BMI and MDD (Major Depressive Disorder Working Group of the PGC, 2017), using EUR samples.
Spatiotemporal Dynamics in Vegetation GPP over the Great Khingan Mountains Using GLASS Products from 1982 to 2015

Gross primary productivity (GPP) is an important parameter that represents the productivity of vegetation and responses to various ecological environments. The Greater Khingan Mountain (GKM) is one of the most important state-owned forest bases, and boreal forests, including the largest primeval cold-temperature bright coniferous forest in China, are widely distributed in the GKM. This study aimed to reveal spatiotemporal vegetation variations in the GKM on the basis of GPP products that were generated by the Global LAnd Surface Satellite (GLASS) program from 1982 to 2015. First, we explored the spatiotemporal distribution of vegetation across the GKM. Then we analyzed the relationships between GPP variation and driving factors, including meteorological elements, growing season length (GSL), and Fraction of Photosynthetically Active Radiation (FPAR), to investigate the dominant factor for GPP dynamics. Results demonstrated that (1) the spatial distribution of accumulated GPP (AG) in spring, summer, autumn, and the growing season varied due to three main reasons: understory vegetation, altitude, and land cover; (2) interannual AG in summer, autumn, and the growing season significantly increased at the regional scale during the past 34 years under climate warming and drying; (3) interannual changes of accumulated GPP in the growing season (AGG) at the pixel scale displayed a rapid expansion in areas with a significant increasing trend (p < 0.05) during the period of 1982–2015 and this trend was caused by the natural forest protection project launched in 1998; and finally, (4) an analysis of driving factors showed that daily sunshine duration in summer was the most important factor for GPP in the GKM and this is different from previous studies, which reported that the GSL plays a crucial role in other areas.
A New Method for Noninvasive Genetic Sampling of Saliva in Ecological Research

Noninvasive samples for genetic analyses have become essential to address ecological questions. Popular noninvasive samples such as faeces contain degraded DNA which may compromise genotyping success. Saliva is an excellent alternative DNA source but scarcity of suitable collection methods makes its use anecdotal in field ecological studies. We develop a noninvasive method of collection that combines baits and porous materials able to capture saliva. We report its potential in optimal conditions, using confined dogs and collecting saliva early after deposition. DNA concentration in saliva extracts was generally high (mean 14 ng μl-1). We correctly identified individuals in 78% of samples conservatively using ten microsatellite loci, and 90% of samples using only eight loci. Consensus genotypes closely matched reference genotypes obtained from hair DNA (99% of identification successes and 91% of failures). Mean genotyping effort needed for identification using ten loci was 2.2 replicates. Genotyping errors occurred at a very low frequency (allelic dropout: 2.3%; false alleles: 1.5%). Individual identification success increased with duration of substrate handling inside dog’s mouth and the volume of saliva collected. Low identification success was associated with baits rich in DNA-oxidant polyphenols and DNA concentrations <1 ng μl-1. The procedure performed at least as well as other noninvasive methods, and could advantageously allow detection of socially low-ranked individuals underrepresented in sources of DNA that are involved in marking behaviour (faeces or urine). Once adapted and refined, there is promise for this technique to allow potentially high rates of individual identification in ecological field studies requiring noninvasive sampling of wild vertebrates.