Miracle-dz/UniFAR-FTUs huggingface dataset:
Mixture Model Framework for Traumatic Brain Injury Prognosis Using Heterogeneous Clinical and Outcome Data

Prognoses of Traumatic Brain Injury (TBI) outcomes are neither easily nor accurately determined from clinical indicators. This is due in part to the heterogeneity of damage inflicted to the brain, ultimately resulting in diverse and complex outcomes. Using a data-driven approach on many distinct data elements may be necessary to describe this large set of outcomes and thereby robustly depict the nuanced differences among TBI patients’ recovery. In this work, we develop a method for modeling large heterogeneous data types relevant to TBI. Our approach is geared toward the probabilistic representation of mixed continuous and discrete variables with missing values. The model is trained on a dataset encompassing a variety of data types, including demographics, blood-based biomarkers, and imaging findings. In addition, it includes a set of clinical outcome assessments at 3, 6, and 12 months post-injury. The model is used to stratify patients into distinct groups in an unsupervised learning setting. We use the model to infer outcomes using input data, and show that the collection of input data reduces uncertainty of outcomes over a baseline approach. In addition, we quantify the performance of a likelihood scoring technique that can be used to self-evaluate the extrapolation risk of prognosis on unseen patients.
Intermittency of three-dimensional perturbations in a point-vortex model.

Three-dimensional (3D) instabilities on a (potentially turbulent) two-dimensional (2D) flow are still incompletely understood, despite recent progress. Here, based on known physical properties of such 3D instabilities, we propose a simple, energy-conserving model describing this situation. It consists of a regularized 2D point-vortex flow coupled to localized 3D perturbations ("ergophages"), such that ergophages can gain energy by altering vortex-vortex distances through an induced divergent velocity field, thus decreasing point-vortex energy. We investigate the model in three distinct stages of evolution: (i) The linear regime, where the amplitude of the ergophages grows or decays exponentially on average, with an instantaneous growth rate that fluctuates randomly in time. The instantaneous growth rate has a small auto-correlation time, and a probability distribution featuring a power-law tail with exponent between -2 and -5/3 (up to a cutoff) depending on the point-vortex base flow. Consequently, the logarithm of the ergophage amplitude performs a Lévy flight. (ii) The passive-nonlinear regime of the model, where the 2D flow evolves independently of the ergophage amplitudes, which saturate by non-linear self-interactions without affecting the 2D flow. In this regime the system exhibits a new type of on-off intermittency that we name Lévy on-off intermittency, which we define and study in a companion paper [van Kan et al., Phys. Rev. E 103, 052115 (2021)1063-651X10.1103/PhysRevE.103. 052115]. We compute the bifurcation diagram for the mean and variance of the perturbation amplitude, as well as the probability density of the perturbation amplitude. (iii) Finally, we characterize the fully nonlinear regime, where ergophages feed back on the 2D flow, and study how the vortex temperature is altered by the interaction with ergophages. It is shown that when the amplitude of the ergophages is sufficiently large, the condensate is disrupted and the 2D flow saturates to a zero-temperature state. Given the limitations of existing theories, our model provides a new perspective on 3D instabilities growing on 2D flows, which will be useful in analyzing and understanding the much more complex results of DNS and potentially guide further theoretical developments.
Polymorphism and Migratory Chiral Resolution of the Free Base of Venlafaxine. A Remarkable Topotactical Solid State Transition from a Racemate to a Racemic Conglomerate

The unique behavior of the active pharmaceutical ingredient Venlafaxine free base, used as an antidepressant, with respect to polymorphism and chiral resolution is reported. Using several complementary techniques, three crystal structures of Venlafaxine were identified and isolated. All three structures are composed of virtually identical enantiomeric pure layers with different stacking modes. In the crystal structure with the highest melting point, the enantiomeric separation is complete, leading to a racemic conglomerate. The conglomerate can be grown from solution or via a solid–solid phase transition of the lowest melting racemic compound. Remarkably, the crystal shape is conserved during the transition. The corresponding chiral resolution is achieved via a local melting process, allowing for a long-range migration of the molecules between layers.
Learning the Gap in the Day-Ahead and Real-Time Locational Marginal Prices in the Electricity Market

In this paper, statistical machine learning algorithms, as well as deep neural networks, are used to predict the values of the price gap between day-ahead and real-time electricity markets. Several exogenous features are collected and impacts of these features are examined to capture the best relations between the features and the target variable. Ensemble learning algorithm namely the Random Forest issued to calculate the probability distribution of the predicted electricity prices for day-ahead and real-time markets. Long-Short-Term-Memory (LSTM) is utilized to capture long term dependencies in predicting direct gap values between mentioned markets and the benefits of directly predicting the gap price rather than subtracting the predictions of day-ahead and real-time markets are illustrated. Case studies are implemented on the California Independent System Operator (CAISO) electricity market data for a two years period. The proposed methods are evaluated and neural networks showed promising results in predicting the exact values of the gap.
Intelligent Architectures for Intelligent Computing Systems

Computing is bottlenecked by data. Large amounts of application data overwhelm storage capability, communication capability, and computation capability of the modern machines we design today. As a result, many key applications' performance, efficiency and scalability are bottlenecked by data movement. In this invited special session talk, we describe three major shortcomings of modern architectures in terms of 1) dealing with data, 2) taking advantage of the vast amounts of data, and 3) exploiting different semantic properties of application data. We argue that an intelligent architecture should be designed to handle data well. We show that handling data well requires designing architectures based on three key principles: 1) data-centric, 2) data-driven, 3) data-aware. We give several examples for how to exploit each of these principles to design a much more efficient and high performance computing system. We especially discuss recent research that aims to fundamentally reduce memory latency and energy, and practically enable computation close to data, with at least two promising novel directions: 1) processing using memory, which exploits analog operational properties of memory chips to perform massively-parallel operations in memory, with low-cost changes, 2) processing near memory, which integrates sophisticated additional processing capability in memory controllers, the logic layer of 3D-stacked memory technologies, or memory chips to enable high memory bandwidth and low memory latency to near-memory logic. We discuss how to enable adoption of such fundamentally more intelligent architectures, which we believe are key to efficiency, performance, and sustainability. We conclude with some guiding principles for future computing architecture and system designs. This accompanying short paper provides a summary of the invited talk and points the reader to further work that may be beneficial to examine.
Quantum Noise in a Fabry-Perot Interferometer Including the Influence of Diffraction Loss of Light

The DECi-hertz Interferometer Gravitational wave Observatory (DECIGO) is designed to detect gravitational waves at frequencies between 0.1 and 10 Hz. In this frequency band, one of the most important science targets is the detection of primordial gravitational waves. DECIGO plans to use a space interferometer with optical cavities to increase its sensitivity. For evaluating its sensitivity, diffraction of the laser light has to be adequately considered. There are two kinds of diffraction loss: leakage loss outside the mirror and higher-order mode loss. These effects are treated differently inside and outside of the Fabry-Perot (FP) cavity. We estimated them under the conditions that the FP cavity has a relatively high finesse and the higher-order modes do not resonate. As a result, we found that the effects can be represented as a reduction of the effective finesse of the cavity with regard to quantum noise. This result is useful for optimization of the design of DECIGO. This method is also applicable to any FP cavities with a relatively small beam cut and the finesse sufficiently higher than 1.
Simultaneous optimization of temperature and energy in linear energy system models

Linear programming is used as a standard tool for optimizing unit commitment or power flows in energy supply systems. For heat supply systems, however, it faces a relevant limitation: For them, energy yield depends on the output temperature, thus, both quantities would have to be optimized simultaneously and the resulting problem is quadratic. As a solution, we describe a method working with discrete temperature levels. This paper presents mathematical models of various technologies and displays their potential in a case study focused on integrated residential heat and electricity supply. It is shown that the technique yields reasonable results including the choice of operational temperatures. Finally, MTRESS, an open source implementation of the method is introduced briefly.
A Note on the Significance Adjustment for FA*IR with Two Protected Groups

In this report we provide an improvement of the significance adjustment from the FA*IR algorithm in Zehlike et al. [2], which did not work for very short rankings in combination with a low minimum proportion p for the protected group. We show how the minimum number of protected candidates per ranking position can be calculated exactly and provide a mapping from the continuous space of significance levels (α) to a discrete space of tables, which allows us to find αcorr using a binary search heuristic. In this report we describe a correction of the significance adjustment procedure from [2], which did not work for very small k and α . For binomial distributions, i.e. where only one protected and one non-protected group is present, the inverse CDF can be stored as a simple table, which we compute using Algorithm 1. We will call such a table mTable. Algorithm 1: Algorithm ConstructMTable computes the data structure to efficiently verify or construct a ranking that satisfies binomial ranked group fairness. input :k , the size of the ranking to produce; p , the expected proportion of protected elements; αcorr, the significance for each individual test. output :mTable: A list that contains the minimum number of protected candidates required at each position of a ranking of size k . 1 mTable← [k] // list of size k 2 for i ← 1 to k do 3 mTable[i] ← F−1 (i, p, αcorr) // the inverse binomial cdf 4 end 5 return mTable Table 1 shows an example of mTables for different k and p , using α = 0.1. For instance, for p = 0.5 we see that at least 1 candidate from the protected group is needed in the top 4 positions, and 2 protected candidates in the top 7 positions. Figure 1 shows that we need a correction for α as we are testing multiple hypothesis in the ranked group fairness test, namely k of them (note that the scale is logarithmic). In the following, we show that the special case of having only one protected group offers possibilities for verifying ranked group fairness efficiently. A key advantage of considering just one protected group, rather than multiple, is that we can calculate the exact failure probability Pfail (i.e. a fair ranking gets rejected by the ranked group fairness test), which results in an efficient binary search for αcorr. First we introduce the necessary notation for the binomial case and describe how we calculate the exact Pfail. Then we show that we can divide the continuum of possible α values in discrete . This paper is published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license. Authors reserve their rights to disseminate the work on their personal and corporate Web sites with the appropriate attribution. © 2020 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC-BY 4.0 License. XXXX-XXXX/2020/12-ART https://doi.org/10.1145/nnnnnnn.nnnnnnn ar X iv :2 01 2. 12 79 5v 1 [ cs . I R ] 2 3 D ec 2 02 0
Group-Aware Robot Navigation in Crowded Environments

—Human-aware robot navigation promises a range of applications in which mobile robots bring versatile assistance to people in common human environments. While prior research has mostly focused on modeling pedestrians as independent, intentional individuals, people move in groups; consequently, it is imperative for mobile robots to respect human groups when navigating around people. This paper explores learning group-aware navigation policies based on dynamic group formation using deep reinforcement learning. Through simulation experiments, we show that group-aware policies, compared to baseline policies that neglect human groups, achieve greater robot navigation performance (e.g., fewer collisions), minimize violation of social norms and discomfort, and reduce the robot’s movement impact on pedestrians. Our results contribute to the development of social navigation and the integration of mobile robots into human environments.
Liquid to gas transition in the adsorption of alkanes on smooth gold surfaces

A systematic trend in the adsorption isotherms of alkanes onto smooth gold substrates has been observed as the alkane molecule becomes smaller. Analysis of isotherms and especially of the isosteric heat of adsorption found from temperature-dependent studies shows that this is a trend from adsorption as a liquid to adsorption as a gas, as a result of the weaker intermolecular interactions in the lighter liquids. 12 refs., 6 figs.
Dynamics of APRI and FIB-4 in HCV cirrhotic patients who achieved SVR after DAA therapy

There are limited data available on the regression of fibrosis in hepatitis C virus (HCV) patients who have achieved sustained virologic response (SVR) after interferon-free treatments. Moreover, a perfect method for assessing liver fibrosis and its dynamics has not been established yet. The main objective of this study was to evaluate the dynamics of aspartate aminotransferase to platelet ratio index (APRI) and Fibrosis-4 (FIB-4) scores in patients with HCV who registered SVR. We performed ROC curve analysis to evaluate the diagnostic performance of APRI and FIB-4 scores in determining the presence of cirrhosis in comparison to FibroTest. In total 251 patients were enrolled: 164 cirrhotic and 83 non-cirrhotic patients, and they were evaluated at baseline, at 6 and at 12 months post-end of treatment (EOT). In the cirrhotic group, at baseline, there was a weak but statistically significant correlation between APRI and FibroTest (τ=0.173, P=0.001), as well as between FIB-4 and FibroTest (τ=0.265, P<0.001). At the 6-month follow-up, APRI no longer correlated with FibroTest (τ=0.144, P=0.057), while FIB-4 was correlated (τ=0.256, P=0.001). The same pattern was shown at 12 months post-EOT. Between baseline and the 6-month evaluation, there was a significant decrease in APRI (P<0.001) and FIB-4 (P<0.001) scores, but for the next follow-up period, there was no reduction. In the non-cirrhotic group, APRI and FIB-4 did not correlate with the FibroTest value at any of the evaluation times. There was a significant difference between baseline and the 6-month visit for APRI (P=0.01) and for FIB-4 (P=0.014). The areas under the receiver operating characteristics curve (AUROCs) for the presence of cirrhosis compared with FibroTest for APRI and FIB-4 were 0.682 [95% confidence interval (CI), 0.613-0.752] and 0.693 (95% CI 0.625-0.76). Both APRI and FIB-4 prove to be easy, quick and inexpensive tools for screening HCV cirrhosis, with moderate diagnostic accuracy and FIB-4 can be useful for monitoring patients post-EOT.
The somatic care situation of people with mental illness

People with mental illness have worse physical health and reduced life expectancy compared to the general population. Nevertheless, their medical care is often insufficient. The present study aimed to investigate the somatic status of people with mental illness with a focus on somatic diagnoses, metabolic risk factors, regular somatic care, and routine check‐ups.
Astigmatic Results of a Diffractive Trifocal Toric IOL Following Intraoperative Aberrometry Guidance

Purpose To determine if intraoperative aberrometry (IA) improves astigmatic outcomes for trifocal toric IOL (TTI) cases. Patients and Methods This was a retrospective study examining 137 eyes that underwent cataract extraction and TTI implantation using femtosecond laser, digital registration, and IA. Final cylinder power and axis of placement were determined by IA. Monocular uncorrected distance visual acuity (UDVA), uncorrected intermediate visual acuity (UIVA), uncorrected near visual acuity (UNVA), and refractive data were collected at 3 months. Postoperative residual astigmatism (PRA) determined by manifest refraction was compared to back-calculated residual astigmatism (BRA) using the cylinder power calculated preoperatively. Results Postoperatively, 97.8% of eyes had IA PRA ≤ 0.50D and 80.3% had BRA ≤ 0.50 D, a difference of 17.5%. Mean PRA for IA was 0.07 D ± 0.19 (range 0.00–1.00 D) compared to BRA 0.31 D ± 0.33 (range 0.00–1.34 D) (P < 0.001). Cylinder power was changed in 50.4% of cases based upon IA. Postoperative mean UDVA (LogMAR) was 0.04 ± 0.09 (range −0.12–0.30 logMAR), and 65% of eyes were ≤ 0.0, 85% ≤ 0.1, and 99% ≤ 0.18. Conclusion The proportion of eyes with PRA ≤ 0.50 D and mean PRA was significantly lower using IA versus the preoperative planned cylinder power.
Diabetes-Related Distress and Its Associated Factors Among Patients with Diabetes in Vietnam

Background Psychometric properties are regarded as one of the significant contributors related to diabetes treatment efficacy. Diabetes-related distress (DD) is one of the emotional burdens. The aims of this study were to investigate the prevalence of DD and to determine its associated factors among Vietnamese diabetic patients. Methods A cross-sectional study was conducted at a single medical center in the central of Vietnam. A total of 138 eligible DM outpatients were invited and a total of 112 patients who completed the questionnaire were utilized in this analysis using convenience sampling. DD was assessed using the diabetes distress scale (DDS). The participant’s sociodemographic and clinical information was obtained through face-to-face interviews and medical records. Multivariate logistic regression was used to determine independent factors associated with the presence of DD. Results Approximately, 12.5% of the patients experienced DD based on DDS self-administered questionnaire. The rates of mild/moderate and high distress were 8.0% and 4.5%, respectively. DD was found to be significantly higher in type 1 DM (p=0.04), insulin only in treatment regime (p=0.04), physical inactivities (p=0.02), times of mild hypoglycemia (time/month) (p=0.01), and fasting plasma glucose (mmol/l) (p=0.04). The occurrence of distress among DM patients was negatively correlated with their age and amount of physical exercise. Meanwhile, poor HbA1c control (HbA1c≥7%) was associated with an increased occurrence of diabetes distress. Conclusion The findings of single medical center in Vietnam highlights that DD is prevalent among DM patients. It should be of marked concerns, particularly the type 1 diabetic patients, younger age, and poor glycemic control patients.
Development and Assessment of a Prenatal Cytomegalovirus (CMV) Educational Survey: Implementation and Impact in a Metropolitan University-Based Clinic

Purpose Congenital CMV infection can result in serious sequelae in the newborn. The goal of this study was to assess pregnant women’s knowledge and understanding of CMV infection during pregnancy and develop an educational tool about CMV infection to be utilized during prenatal care. Materials and Methods This is a prospective intervention study that assessed pregnant women’s knowledge before and after receiving an educational handout about CMV infection in pregnancy and the perceived value of this education. Pre- and post-education questionnaires were utilized to assess knowledge. The pre-education questionnaire and CMV educational handout were given at the same clinic visit. The educational handout was given after the pre-education questionnaire had been completed. The post-education questionnaire was given at the next scheduled prenatal clinic appointment and included questions regarding the level of satisfaction with the education and the perceived value of the information. Pregnant women less than 34 weeks of gestation were eligible. Results A total of 263 women were enrolled, 263 completed the pre-CMV educational questionnaire and 215 women completed both questionnaires. Some women only partially completed the questionnaires and those partial responses have been included. Prior to education, 33% (85/261) of participants had heard of CMV. This increased to 75% (160/214) after education. Participants scored each of the recommended hygiene practices between 1 and 5 (5 is the most acceptable) and each recommended hygiene practice received an average score between 3.8 and 5. 74% (134/180) of participants reported increasing their hygienic practices after education. 96% (180/188) of participants indicated they were satisifed to have received the education. 98% (187/190) thought more women should receive this education during prenatal care. Conclusion Pregnant women viewed education about CMV favorably and increased the frequency of recommended hygiene practices. Introducing an educational handout to routine prenatal care may be beneficial in increasing awareness of CMV infection in pregnancy.