Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing risk prediction models for ambulatory no-shows across different specialties and clinics

Abstract Objective As available data increases, so does the opportunity to develop risk scores on more refined patient populations. In this paper we assessed the ability to derive a risk score for a patient no-showing to a clinic visit. Methods Using data from 2 264 235 outpatient appointments we assessed the performance of models built across 14 different specialties and 55 clinics. We used regularized logistic regression models to fit and assess models built on the health system, specialty, and clinic levels. We evaluated fits based on their discrimination and calibration. Results Overall, the results suggest that a relatively robust risk score for patient no-shows could be derived with an average C-statistic of 0.83 across clinic level models and strong calibration. Moreover, the clinic specific models, even with lower training set sizes, often performed better than the more general models. Examination of the individual models showed that risk factors had different degrees of predictability across the different specialties. Implementation of optimal modeling strategies would lead to capturing an additional 4819 no-shows per-year. Conclusion Overall, this work highlights both the opportunity for and the importance of leveraging the available electronic health record data to develop more refined risk models.
fMRI Evidence for Separable and Lateralized Prefrontal Memory Monitoring Processes

Source memory research suggests that attempting to remember specific contextual aspects surrounding prior stimulus encounters results in greater left prefrontal cortex (PFC) activity than simple item-based old/new recognition judgments. Here, we tested a complementary hypothesis that predicts increases in the right PFC with tasks requiring close monitoring of item familiarity. More specifically, we compared a judgment of frequency (JOF) task to an item memory task, in which the former required estimating the number of previous picture encounters and the latter required discriminating old from new exemplars of previously seen items. In comparison to standard old/new recognition, both source memory and the JOF task examined here require more precise mnemonic judgments. However, in contrast to source memory, cognitive models suggest the JOF task relies heavily upon item familiarity, not specific contextual recollections. Event-related fMRI demonstrated greater recruitment of right, not left, dorso-lateral and frontopolar PFC regions during the JOF compared to item memory task. These data suggest a role for right PFC in the close monitoring of the familiarity of objects, which becomes critical when contextual recollection is ineffective in satisfying a memory demand.
The Single Transmembrane Segment of Minimal Sensor DesK Senses Temperature via a Membrane-Thickness Caliper

ABSTRACT Thermosensors detect temperature changes and trigger cellular responses crucial for survival at different temperatures. The thermosensor DesK is a transmembrane (TM) histidine kinase which detects a decrease in temperature through its TM segments (TMS). Here, we address a key issue: how a physical stimulus such as temperature can be converted into a cellular response. We show that the thickness of Bacillus lipid membranes varies with temperature and that such variations can be detected by DesK with great precision. On the basis of genetic studies and measurements of in vitro activity of a DesK construct with a single TMS (minimal sensor DesK [MS-DesK]), reconstituted in liposomes, we propose an interplay mechanism directed by a conserved dyad, phenylalanine 8-lysine 10. This dyad is critical to anchor the only transmembrane segment of the MS-DesK construct to the extracellular water-lipid interphase and is required for the transmembrane segment of MS-DesK to function as a caliper for precise measurement of membrane thickness. The data suggest that positively charged lysine 10, which is located in the hydrophobic core of the membrane but is close to the water-lipid interface, pulls the transmembrane region toward the water phase to localize its charge at the interface. Nevertheless, the hydrophobic residue phenylalanine 8, located at the N-terminal extreme of the TMS, has a strong tendency to remain in the lipid phase, impairing access of lysine 10 to the water phase. The outcome of this interplay is a fine-tuned sensitivity to membrane thickness that elicits conformational changes that favor different signaling states of the protein. IMPORTANCE The ability to sense and respond to extracellular signals is essential for cell survival. One example is the cellular response to temperature variation. How do cells “sense” temperature changes? It has been proposed that the bacterial thermosensor DesK acts as a molecular caliper measuring membrane thickness variations that would occur as a consequence of temperature changes and activates a pathway to restore membrane fluidity at low temperature. Here, we demonstrated that membrane thickness variations do occur at physiological temperatures by directly measuring Bacillus lipid membrane thickness. We also dissected the N-terminal sensing motif of MS-DesK at the molecular-biophysical level and found that the dyad phenylalanine-lysine at the water-lipid phase is critical for achievement of a fine-tuned sensitivity to temperature.
Automatic lung ultrasound B-line recognition in pediatric populations for the detection of pneumonia

Pneumonic lung sonograms are known to include vertical comet-tail artifacts called B-lines. In this study, the potential of histogram properties from lung ultrasound images for the automatic identification of B-line artifacts is explored. Five histogram features (skewness, kurtosis, standard deviation, energy and average) were calculated for intercostal spaces. The sample consisted of 15 positive- and 15 negative-diagnosed B-mode videos selected by a medical expert and captured in a local pediatric health institute. For each frame, an initial domain of interest (DOI) starting from the pleural line is automatically outlined. The pleura is detected by a brightness based thresholding. Smaller regions containing the intercostal spaces inside the DOI are then outlined and histogram features are estimated. The potential classification of properties was evaluated independently, in pairs and using the group of 5. For single feature analysis, the optimal threshold was selected based on ROC (receiver operator characteristic) curve. For studying features in pairs a support vector machine (SVM) analysis using a RBF kernel was performed. Finally, for studying the five features, PCA (principal component analysis) was useful to determine the two principal components and apply an algorithm able to identify a B-line in the intercostal space. The results revealed that energy performed best as discriminator when using a single feature with 77% sensitivity, 75% specificity and 75% accuracy. When using features in pairs, average and skewness performed best with 93% sensitivity, 86% specificity and 88% accuracy. Finally, analyzing the 5 features, the results were 100% sensitivity, 98% specificity and 98% accuracy.
Extended Characterization of Human Uropathogenic Escherichia coli Isolates from Slovenia

Escherichia coli (E. coli) is a very diverse bacterial species found naturally in the intestinal tract of humans and many other animal species. Even though E. coli is known to be part of the normal gut microbiota, some strains – that are pathogenic – cause a wide variety of different intestinal and extraintestinal diseases (Marrs et al., 2005). Typical extraintestinal infections due to E. coli include urinary tract infections (UTI), diverse intra-abdominal infections, pneumonia, surgical-site infection, meningitis, osteomyelitis, soft-tissue infections, bacteremia (Russo & Johnson, 2006). UTIs are one of the most frequently acquired bacterial infections and E. coli accounts for as many as 90% of all community-acquired UTIs. Approximately 50% of all women have had a UTI by their late 20s. About 20–30% of women with first UTI will have two or more infections; while 5%, will develop chronic recurring infections which greatly disrupt a woman’s life (Marrs et al., 2005). In Slovenia E. coli is the causative agent of approximately 80% of uncomplicated UTIs (Lindic, 2005). E. coli isolates that cause UTI exhibit a number of specific characteristics and are classified, as uropathogenic E. coli (UPEC), a subgroup of extraintestinal pathogenic E. coli (ExPEC) (Russo & Johnson, 2000). UPEC strains mainly belong to the B2 phylogenetic group and to a lesser extent to the D group, while commensal strains belong to groups A and B1 (Picard et al., 1999). Further, some O-antigens (O1, O2, O4, O6, O7, O18 and O83) are more prevalent among uropathogenic E. coli strains and are therefore associated with UTI (Moreno et al. 2006). In comparison to commensal E. coli strains, UPEC possess an array of virulence factors namely, adhesins, toxins, polysaccharide coatings, invasins, iron uptake systems and systems to evade host immune responses (Oelschlaeger et al., 2002). Of serious concern and an increasing health problem, on a global scale, is the appearance and spread of antimicrobial resistance. One of the major health care concerns is emergence of multidrug resistant bacteria and clinical microbiologists increasingly agree that multidrug resistant Gram-negative bacteria pose the greatest risk to public health (Kumarasamy et al., 2010). Therefore, it is essential to determine susceptibility of pathogenic strains for antimicrobial agents and association of antimicrobial resistance with virulence genes. One of the means for acquiring specific virulence factor genes and antimicrobial resistance genes, is via mobile DNA (e. g. conjugal plasmids, transposons/integrons) (Alekshun &
How to choose training set for language modeling

This paper investigates the problem of choosing the training set for language modeling in large vocabulary continuous speech recognition system. From our investigation, we find that the language style is more important than the domain in language modeling. Keeping the similarity of language style, extending of domain is not harmful. On the contrast, under this condition, the expanding size of the training set will improve the quality of the language model. Diversity of language styles in the training set will result in the degradation of the language model. The analysis of the correlation between CER and evaluation measures of language model indicates that under condition of same domain, same language style and whole model without cutoff, the perplexity correlates with CER strongly. Otherwise this correlation will be weakened. Another evaluation measure in our investigation, the N-gram hitting rate performs similarly to that of perplexity. To the back-off trigram model, the bigram hitting rate correlates stronger to CER than the trigram-hitting rate, which is meaningful to the size reduction of language model.
Countering Feedback Delays in Multi-Agent Learning

We consider a model of game-theoretic learning based on online mirror descent (OMD) with asynchronous and delayed feedback information. Instead of focusing on specific games, we consider a broad class of continuous games defined by the general equilibrium stability notion, which we call λ-variational stability. Our first contribution is that, in this class of games, the actual sequence of play induced by OMD-based learning converges to Nash equilibria provided that the feedback delays faced by the players are synchronous and bounded. Subsequently, to tackle fully decentralized, asynchronous environments with (possibly) unbounded delays between actions and feedback, we propose a variant of OMD which we call delayed mirror descent (DMD), and which relies on the repeated leveraging of past information. With this modification, the algorithm converges to Nash equilibria with no feedback synchronicity assumptions and even when the delays grow superlinearly relative to the horizon of play.
Enhancing the performance of adaptive iterative learning control with reinforcement learning

In this study we propose a new method to enhance the performance of iterative learning control (ILC). We focus on robotic tasks dealing with adaptation to the unknown or partially known environment, where the robot has to learn the environment geometry in order to perform the desired task with the given reference forces and torques. The initial motion trajectories are obtained by kinesthetic teaching, whereas the required forces and torques are prescribed by the task. We are interested in incremental learning, which assures smooth and safe operation, aiming at handling of delicate, fragile objects, such as objects made of glass. In order to achieve these goals we propose a new adaptive ILC scheme, where the adaptation is supervised by reinforcement learning. We also show how to apply ILC to orientational motion, taking into account the curved geometry of SO(3). The performance of the proposed algorithm is verified on a bi-manual glass wiping task.
Opportunistic Interference Alignment and Cancellation for the Uplink of Cellular Networks

In this letter, we propose an opportunistic interference alignment and cancellation (OIAC) scheme for cellular networks to exploit the multi-user diversity gain and the backhual resources among base stations. Particularly, an opportunistic user scheduling strategy is proposed by synthesizing opportunistic interference alignment (OIA) and successive interference cancellation (SIC). In the OIAC scheme, we propose a new user scheduling metric and a sequential user selection scheme based on the characteristics of SIC, and guarantee a target signal-to-interference-plus-noise ratio (SINR) for each selected user by performing user selection, decoder design and power control jointly in the user selection process. The OIAC scheme improves system performance by using SIC and keeps the low implementation complexity property of OIA. The simulation results show that the OIAC scheme can improve the achievable sum rate significantly compared to OIA and other schemes.
How to Gauge the Relevance of Codes in Qualitative Data Analysis? - A Technique Based on Information Retrieval

Qualitative research has experienced broad acceptance in the IS discipline. Despite the merits for exploring new phenomena, qualitative methods are criticized for their subjectivity when it comes to interpretation. Therefore, research mostly emphasized the development of criteria and guidelines for good practice. I present an approach to counteract the issue of credibility and traceability in qualitative data analysis and expand the repertoire of approaches used in IS research. I draw on an existing approach from the information science discipline and adapt it to analyze coded qualitative data. The developed approach is designed to answer questions about the specific relevance of codes and aims to support the researcher in detecting hidden information in the coded material. For this reason, the paper contributes to the IS methodology with bringing new insights to current methods by enhancing them with an approach from another discipline.
Draft Genome Sequence of Listeria monocytogenes Strain CIIMS-PH-1, a Serovar 4b Isolate from Infant Septicemia

ABSTRACT We report here the draft genome sequence of Listeria monocytogenes CIIMS-PH-1, an isolate obtained from a 16-day-old infant with septicemia. The draft genome of CIIMS-PH-1 consisted of 2,939,183 bp and is a member of sequence type 308, clonal complex 1, and lineage I.
Friedreich’s ataxia: clinical features, pathogenesis and management

Introduction Friedreich's ataxia is the most common inherited ataxia. Sources of data Literature search using PubMed with keywords Friedreich's ataxia together with published papers known to the authors. Areas of agreement The last decade has seen important advances in our understanding of the pathogenesis of disease. In particular, the genetic and epigenetic mechanisms underlying the disease now offer promising novel therapeutic targets. Areas of controversy The search for effective disease-modifying agents continues. It remains to be determined whether the most effective approach to treatment lies with increasing frataxin protein levels or addressing the metabolic consequences of the disease, for example with antioxidants. Areas timely for developing research Management of Freidreich's ataxia is currently focussed on symptomatic management, delivered by the multidisciplinary team. Phase II clinical trials in agents that address the abberrant silencing of the frataxin gene need to be translated into large placebo-controlled Phase III trials to help establish their therapeutic potential.
Test Procedures to Assess Somatosensory Abnormalities in Individuals with Peripheral Joint Pain: A Systematic Review of Psychometric Properties

Test procedures that were developed to assess somatosensory abnormalities should possess optimal psychometric properties (PMPs) to be used in clinical practice. The aim of this systematic review was to evaluate the literature to assess the level of evidence for PMPs of test procedures investigated in individuals with peripheral joint pain (PJP).
Non linear viscoelasticity and extensional viscosity of linear maleated polypropylene-clay nanocomposites

NON LINEAR VISCOELASTICITY AND EXTENSIONAL VISCOSITY OF LINEAR MALEATED POLYPROPYLENE-CLAY NANCOMPOSITES By Tanmay Janardan Pathak Strain hardening of polymer melts in elongational flow is important for a variety of polymer processing operations such as thermoforming, foaming and blow molding. As such the measurement of transient extensional viscosity becomes important to understand the elongational behavior of the polymeric materials. It is well known that linear polypropylene; a widely used commodity polymer; does not strain harden in melt extensional flow and there arises a need to structurally modify this polymer so as to achieve strain hardening. In the present work, the effect of dispersing two different organoclays in linear maleated polypropylene on the transient uniaxial extensional viscosity and shear viscoelasticity (linear and nonlinear) has been investigated. The matrix polymer was a linear random copolymer of propylene and ethylene grafted with maleic anhydride (PP-g-MA). Two different grades of nanoclay organically modified with different ionic surfactants were used as fillers. The extensional rheology was carried out at different strain rates, on an Extensional Viscosity Fixture (EVF) mounted on a TA-ARES rheometer. The neat PP-g-MA matrix did not show any strain hardening at different extensional strain rates whereas the nanocomposites with different organoclays showed different extents of strain hardening. Strain hardening was quantified by calculating the ratio of transient extensional viscosity to the viscosity obtained from linear viscoelastic envelope, called as the strain hardening parameter (χ) which was around 3 at lower strain rates for one of the nanocomposite with 5wt% clay loading. Linear and non-linear shear rheology of these nanocomposites was also investigated to understand the reinforcement effects upon filler additions in the polymer matrix and to get an insight on the nanocomposite structure. From the combined observations in linear and nonlinear shear rheology along with nonlinear extensional rheology we were able to conclude that the polymer matrix chains physically coupled (mainly by hydrogen bonding) to the nanoclays and these particle attached polymer chains formed hindered chain entanglements with the free matrix chains. The formation of such entangled structure led to improvements in the reinforcement levels as well as strain hardening behavior in uniaxial extensional flow. The second part of this study is focused on understanding the effects of filler loadings on the strain hardening and non-linear viscoelasticity of these nanocomposites. This study showed that there lies an optimum level of nanoclay loading (2 vol%) with an effective aspect ratio and specific surface area that are necessary to form hindered chain entanglements necessary for strain hardening. For composites with higher nanoclay loadings, the strain hardening diminishes with decreasing effective aspect ratios.
A MODEL FOR THE OXIDATION ENHANCED DIFFUSION OF BORON IN EXTRINSIC SILICON

It has been reported earlier that in the case of diffusion of boron into silicon, the sheet resistance values observed in narrow diffusion windows differ significantly from the values obtained on plain un-marked check slices with the former always being greater than the latter. The actual value of this discrepancy depends upon several factors such as the size of the window, the surrounding masking oxide geometry and the process parameters. These observations add another important factor in 2-D simulation for diffusion processes. An attempt has been made to present a theoretical model to explain the experimental observations. The results of a careful series of experiments using multilayered mask structures have been presented. On the basis of these experiments it is suggested that most of the experimental observations may be explained with the help of a theoretical model based on surface diffusion of boron over silicon and silicon dioxide. The model is based upon the phenomenon of surface diffusion over silicon and silicon dioxide with a high solubility of boron in oxide. Numerical calculations demonstrate the capability of the model to explain most of the experimental observations. Further details of the modeling and calculations will be presented.
Experience Guided Mobile Manipulation Planning

The most critical moves that determine the success of a manipulation task are performed within the close vicinities of the object prior to grasping, and the goal prior to the final placement. Memorizing these state-action sequences and reusing them can dramatically improve the task efficiency, whereas even the state-of-the-art planning algorithms may require significant amount of time and computational resources to generate a solution from scratch depending on the complexity and the constraints of the task. In this paper, we propose a hybrid approach that combines the reliability of the past experiences gained through demonstration and the flexibility of a generative motion planning algorithm, namely RRT∗, to improve the task execution efficiency. As a side benefit of reusing these final moves, we can dramatically reduce the number of nodes used by the generative planner, hence the planning time, by either early-terminating the planner when the generated plan reaches a “recalled state”, or deliberately biasing it towards the memorized state-action sequences that are feasible at the moment. This complementary combination of the already available partial plans and the generated ones yield to fast, reliable, and repeatable solutions.