Miracle-dz/UniFAR-FTUs huggingface dataset:
Differentiating poor validity from probable impairment on the medical symptom validity test: a cross-validation study

Abstract Aims: In neuropsychological evaluations, it is often difficult to ascertain whether poor performance on measures of validity is due to poor effort or malingering, or whether there is genuine cognitive impairment. Dunham and Denney created an algorithm to assess this question using the Medical Symptom Validity Test (MSVT). We assessed the ability of their algorithm to detect poor validity versus probable impairment, and concordance of failure on the MSVT with other freestanding tests of performance validity. Methods: Two previously published datasets (n = 153 and n = 641, respectively) from outpatient neuropsychological evaluations were used to test Dunham and Denney’s algorithm, and to assess concordance of failure rates with the Test of Memory Malingering and the forced choice measure of the California Verbal Learning Test, two commonly used performance validity tests. Results: In both datasets, none of the four cutoff scores for failure on the MSVT (70%, 75%, 80%, or 85%) identified a poor validity group with proportionally aligned failure rates on other freestanding measures of performance validity. Additionally, the protocols with probable impairment did not differ from those with poor validity on cognitive measures. Conclusions: Despite what appeared to be a promising approach to evaluating failure on the easy MSVT subtests when clinical data are unavailable (as recommended in the advanced interpretation program, or advanced interpretation [AI], of the MSVT), the current findings indicate the AI remains the gold standard for doing so. Future research should build on this effort to address shortcomings in measures of effort in neuropsychological evaluations.
A Robust Extrinsic Calibration Method for Non-Contact Gaze Tracking in the 3-D Space

In general, 3-D gaze tracking methods employ both a frontal-viewing camera and an eye-capturing camera facing the opposite direction to precisely estimate the point-of-regard (POR) in the 3-D space. The extrinsic calibration of these two cameras for accurate 3-D gaze tracking is a challenging task. This paper presents a robust extrinsic calibration method for non-contact gaze tracking in the 3-D space. Even in a noisy environment, the extrinsic calibration parameters are precisely estimated by minimizing the proposed cost function consisting of both the angular and Euclidean errors. Furthermore, using the estimated parameters, the 3-D POR is exactly determined based on the two-view geometry. Compared with the conventional methods, the proposed method provides superior results in experiments considering various factors such as the noise level, head movement, and camera configuration. In real experiments, we achieved an average Euclidean error of 12.6 cm and the average angular error of 0.98° when estimating the 3-D coordinates of PORs that were 4–8 m away from the user.
Design Considerations of Novel Modular-Spoke-Type Permanent Magnet Machines

According to the specific characteristics, including even-order harmonics and unbalanced magnetic force (UMF), etc., special considerations for the design of a novel modular-spoke-type permanent magnet (MSTPM) machine are investigated and implemented in this paper. First, the geometric topology and operating principle of MSTPM machines are briefly introduced. Then, the permanent magnet magneto-motive-force and no-load air-gap flux density in MSTPM machines are compared with those of conventional surface-mounted permanent magnet (SPM) machines to expose the nature of MSTPM machines. Thereafter, the even-order harmonics and UMF in MSTPM machines are elaborately analyzed and the elimination is proposed by designing specific combinations of stator slots and rotor poles. Besides, the electromagnetic torque is optimized to achieve high torque and low torque ripple based on analytical and finite element analysis methods. Then, the performance of an MSTPM machine and a commercial outer-rotor (OR) SPM machine for in-wheel traction application are compared, and the results indicate that the MSTPM machine can produce better flux-weakening performance than the OR-SPM machine with the same rated torque and speed. Finally, a prototype MSTPM machine is manufactured and tested, and the measured results have a good agreement with the analytical and predictive results.
Exposure to indoor air pollution and its perceived impact on health of women and their children: A household survey in a slum of Kolkata, India

Background: One's house is believed to be the safest and the healthiest place to live in. Indoor air pollution (IAP) means the presence of unwanted substances in the indoor air at concentration toxic to health. Objective: The objective of this study is to study the presence of IAP, its associated factors and impact on health of women residing in an urban slum of Kolkata, West Bengal, India. Methods: It was a cross-sectional study done from January 2017 to March 2017 among 120 households of a slum. Data were collected using a pre-designed pre-tested schedule from the homemaker of the households. All analyses were conducted with R: A Language and Environment for Statistical Computing. Results: About 60% households used kerosene as cooking fuel predominantly. Smoke from the neighbouring houses troubled 57.5% respondents. More than 60% houses were overcrowded and more than 70% houses were poorly ventilated. IAP-related symptoms such as irritation in the eye, suffocation, dry cough significantly correlated with the presence of IAP sources and its contributory factors. Of 120, 78 (65%) perceived the presence of IAP in their houses. Lower per capita income (PCI), ground floor, and joint family were found to have higher odds of sources of IAP. Younger age, lower PCI, and ground floor were found to be strongly associated with higher contributory factors of IAP. Conclusion: The present study found that the majority of the households were exposed to IAP due to kerosene, neighborhood smoke while overcrowding and ill-ventilation accentuated it. Effective intervention with intersectoral coordination is the need of the hour.
Deep Learning for Super-Resolution Channel Estimation and DOA Estimation Based Massive MIMO System

The recent concept of massive multiple-input multiple-output (MIMO) can significantly improve the capacity of the communication network, and it has been regarded as a promising technology for the next-generation wireless communications. However, the fundamental challenge of existing massive MIMO systems is that high computational complexity and complicated spatial structures bring great difficulties to exploit the characteristics of the channel and sparsity of these multi-antennas systems. To address this problem, in this paper, we focus on channel estimation and direction-of-arrival (DOA) estimation, and a novel framework that integrates the massive MIMO into deep learning is proposed. To realize end-to-end performance, a deep neural network (DNN) is employed to conduct offline learning and online learning procedures, which is effective to learn the statistics of the wireless channel and the spatial structures in the angle domain. Concretely, the DNN is first trained by simulated data in different channel conditions with the aids of the offline learning, and then corresponding output data can be obtained based on current input data during online learning process. In order to realize super-resolution channel estimation and DOA estimation, two algorithms based on the deep learning are developed, in which the DOA can be estimated in the angle domain without additional complexity directly. Furthermore, simulation results corroborate that the proposed deep learning based scheme can achieve better performance in terms of the DOA estimation and the channel estimation compared with conventional methods, and the proposed scheme is well investigated by extensive simulation in various cases for testing its robustness.
Head-to-Head Comparison of Modified Laparoscopic Pyeloplasty and Robot-Assisted Pyeloplasty for Ureteropelvic Junction Obstruction in China

Objective: To compare the outcomes of modified laparoscopic pyeloplasty (LP) and robot-assisted pyeloplasty (RLP) for ureteropelvic junction obstruction (UPJO) in China patients. Materials and Methods: We retrospectively reviewed the medical records of patients who underwent modified LP and RLP using a transperitoneal laparoscopic approach at 2 different medical institutions between October 2009 and November 2017. Results: Seventy-six patients underwent modified LP and 140 patients underwent RLP. No open conversion occurred. The mean operative time of RLP was shorter than that of modified LP (p = 0.042). For UPJO concomitant with renal calculi, there was no difference in operative time between 2 groups (p = 0.656). With RLP, the operative time for UPJO concomitant with horseshoe was shorter (p = 0.011). In terms of complication rate, there was no significant difference between 2 groups (p = 0.596). The postoperative hospital stay for modified LP was shorter than that for RLP (p < 0.05). The mean follow-up time for modified LP and RLP was 31.79 months and 10.85 months respectively (p < 0.05). The success rate was 96.05 and 97.86% for modified LP and RLP, respectively (p = 0.736). Conclusions: Modified LP and RLP are safe and efficient treatment for UPJO with similar success rates.
Differential gene expression profiling of the sciatic nerve in type 1 and type 2 diabetic mice

Diabetic peripheral neuropathy (DPN) is a common complication of diabetes mellitus (DM). The pathogenic mechanisms of DPN and the therapeutic interventions required may be distinct between type 1 (T1) and type 2 (T2) DM. However, the molecular mechanisms underlying the pathogenesis of DPN in both types of diabetes remain unclear. The aim of the current study was to identify the changes in genes and pathways associated with DPN in sciatic nerves of T1- and T2DM mice using bioinformatics analysis. The microarray profiles of sciatic nerves of T1DM (GSE11343) and T2DM (GSE27382) mouse models were downloaded from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) in each. DEGs in the two types of DM (with fold change ≥2 and P<0.05) were identified with BRB-ArrayTools. Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins and visualized using Cytoscape. Compared with control samples, 623 and 1,890 DEGs were identified in sciatic nerves of T1- and T2DM mice, respectively. Of these, 75 genes were coordinately dysregulated in the sciatic nerves of both models. Many DEGs unique to T1DM mice were localized to the nucleoplasm and were associated with regulation of transcription processes, while many unique to T2DM mice were localized at cell junctions and were associated with ion transport. In addition, certain DEGs may be associated with the different treatment strategies used for the two types of DM. This analysis provides insight into the functional gene sets and pathways operating in sciatic nerves in T1- and T2DM. The results should improve understanding of the molecular mechanisms underlying the pathophysiology of DPN, and provide information for the development of therapeutic strategies for DPN specific to each type of DM.
Leveraging Contact Forces for Learning to Grasp

Grasping objects under uncertainty remains an open problem in robotics research. This uncertainty is often due to noisy or partial observations of the object pose or shape. To enable a robot to react appropriately to unforeseen effects, it is crucial that it continuously takes sensor feedback into account. While visual feedback is important for inferring a grasp pose and reaching for an object, contact feedback offers valuable information during manipulation and grasp acquisition. In this paper, we use model-free deep reinforcement learning to synthesize control policies that exploit contact sensing to generate robust grasping under uncertainty. We demonstrate our approach on a multi-fingered hand that exhibits more complex finger coordination than the commonly used two-fingered grippers. We conduct extensive experiments in order to assess the performance of the learned policies, with and without contact sensing. While it is possible to learn grasping policies without contact sensing, our results suggest that contact feedback allows for a significant improvement of grasping robustness under object pose uncertainty and for objects with a complex shape.
Impact of Deceased Donor Cardiac Arrest Time on Postpancreas Transplant Graft Function and Survival

Introduction Transplantation of pancreas allografts from donors that have experienced preprocurement cardiopulmonary arrest (PPCA) is not common, though use of PPCA grafts is routine in liver and kidney transplantation. This article reviews a large number of PPCA pancreas grafts at a single center and reports posttransplant outcomes including early graft dysfunction, length of hospital stay, rejection, and early and late graft survival. Methods Preprocurement cardiopulmonary arrest, arrest time, and donor and recipient pancreatic enzyme levels were collected from electronic and written medical records. The PPCA donors were stratified into 4 groups: none, less than 20 minutes, 20-39 minutes, and 40 minutes or greater. Graft survival was assessed at 7 and 90 days and at 1 year. Long-term graft survival was assessed by Cox regression analysis. Results The records of 606 pancreas transplants were reviewed, including 328 (54%) simultaneous pancreas and kidney transplants. Preprocurement cardiopulmonary arrest occurred in 176 donors (29%; median time, 20 minutes). Median peak donor lipase was higher in PPCA donors (40 &mgr;/L vs 29 &mgr;/L, P = 0.02). Posttransplant, peak recipient amylase, and lipase levels were similar (P = 0.63). Prolonged arrest time (>40 minutes) was associated with higher donor peak lipase and lower recipient peak amylase (P = 0.05 for both). Stratified by donor arrest time, there was no difference in 7-day, 90-day, or 1-year graft survival. Cox regression comparing the 4 groups demonstrated no statistical difference in 10-year survival. Conclusions These results support transplantation of pancreas allografts from PPCA donors. Prolonged asystole was associated with higher peak donor serum lipase but lower peak recipient serum amylase. There were no differences in allograft survival.
Bioactive Composition, Antioxidant Activity, and Anticancer Potential of Freeze-Dried Extracts from Defatted Gac (Momordica cochinchinensis Spreng) Seeds

Background: Gac (Momordica cochinchinensis Spreng) seeds have long been used in traditional medicine as a remedy for numerous conditions due to a range of bioactive compounds. This study investigated the solvent extraction of compounds that could be responsible for antioxidant activity and anticancer potential. Methods: Defatted Gac seed kernel powder was extracted with different solvents: 100% water, 50% methanol:water, 70% ethanol:water, water saturated butanol, 100% methanol, and 100% ethanol. Trypsin inhibitors, saponins, phenolics, and antioxidant activity using the 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS), the 2,2-diphenyl-1-picrylhydrazyl (DPPH) and the ferric reducing antioxidant power (FRAP) assays; and anticancer potential against two melanoma cancer cell lines (MM418C1 and D24) were analysed to determine the best extraction solvents. Results: Water was best for extracting trypsin inhibitors (581.4 ± 18.5 mg trypsin/mg) and reducing the viability of MM418C1 and D24 melanoma cells (75.5 ± 1.3 and 66.9 ± 2.2%, respectively); the anticancer potential against the MM418C1 cells was highly correlated with trypsin inhibitors (r = 0.92, p < 0.05), but there was no correlation between anticancer potential and antioxidant activity. The water saturated butanol had the highest saponins (71.8 ± 4.31 mg aescin equivalents/g), phenolic compounds (20.4 ± 0.86 mg gallic acid equivalents/g), and antioxidant activity, but these measures were not related to anticancer potential. Conclusions: Water yielded a Gac seed extract, rich in trypsin inhibitors, which had high anticancer potential against two melanoma cell lines.
Creatinine-Based Renal Function Estimates and Dosage of Postoperative Pain Management for Elderly Acute Hip Fracture Patients

Many analgesics and their metabolites are renally excreted. The widely used Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI)-estimated glomerular filtration rate (eGFR) equations are not developed for use in the elderly, while the recent Berlin Initiative Study (BIS), Full Age Spectrum (FAS), and Lund-Malmö revised (LMR) equations are. This observational study investigated differences between creatinine-based eGFR equations and how the choice of equation influences dosage of analgesics in elderly (≥70 years) patients admitted with acute hip fracture. eGFR was calculated by the CKD-EPI, BIS, Cockcroft-Gault (CG), FAS, LMR, and Modification of Diet in Renal Disease (MDRD) equations. Standard daily dose for postoperative pain medications ibuprofen, morphine and gabapentin was simulated for each equation according to dosage recommendations in Renbase®. For 118 patients, mean eGFR from the CKD-EPI, BIS, CG, FAS, LMR, and MDRD equations was 67.3 mL/min/1.73 m2, 59.1 mL/min/1.73 m2, 56.9 mL/min/1.73 m2, 60.3 mL/min/1.73 m2, 58.9 mL/min/1.73 m2, and 79.1 mL/min/1.73 m2, respectively (p < 0.0001). Mean difference to CKD-EPI was −10.4 mL/min/1.73 m2 to 11.8 mL/min/1.73 m2. Choice of eGFR equation significantly influenced the recommended dose (p < 0.0001). Shifting to BIS, FAS, or LMR equations led to a lower recommended dose in 20% to 31% of patients. Choice of eGFR equation significantly influenced dosing of ibuprofen, morphine, and gabapentin.
Characterization and Compact Modeling of Self-Aligned Short-Channel Organic Transistors

In this paper, we present the characterization and modeling of downscaled flexible organic thin-film transistors fabricated by photolithography and self-alignment of the source and drain contacts to the gate. A SPICE model based on the unified model and extraction method for thin-film transistors (TFTs) is tailored with high accuracy for the subthreshold regime in order to include the channel length dependence of two semiempirical parameters, viz., the effective mobility and the onset voltage. In addition, we demonstrate the modeling of the hump effect, a phenomenon often present in TFTs fabricated by lithographic methods.
A CSP\AM-BA-SVM Approach for Motor Imagery BCI System

Brain–computer interface (BCI) has become extremely popular in recent decades. It gained its significance from the intention of helping paralyzed people communicate with the external environment. One of the major challenges facing BCI systems is obtaining reliable classification accuracy of motor imagery (MI) mental tasks. In this paper, a novel CSP\AM-BA-SVM approach is proposed using bio-inspired algorithms for feature selection and classifier optimization to improve classification accuracy of the MI-BCI systems. The proposed approach applies optimum selection of time interval for each subject. The features are extracted from EEG signal using the common spatial pattern (CSP). Binary CSP is extended to multi-class problems by utilizing one-vs-one strategy. This paper introduces applying a hybrid attractor metagene (AM) algorithm along with the Bat optimization algorithm (BA) to select the most discriminant CSP features and optimize SVM parameters. The efficacy of the proposed approach was examined using three data sets. The proposed approach has achieved 78.55% accuracy and 0.71 mean kappa for BCI Competition IV data set 2a, 86.6% accuracy and 0.82 mean kappa for BCI Competition III data set IIIa, and 85% for the binary class BCI Competition III data set IVa. For multi-class data sets, the proposed approach outperforms winners of BCIC IV, 2a and BCIC III, IIIa with kappa 0.14 and 0.17, respectively. For binary class BCIC III, IVa, it performed slightly better than existing studies in the literature by $\approx ~0.5$ %. The proposed CSP\AM-BA-SVM transcends the traditional CSP\SVM approach and other existing studies.
Effects of captopril and valsartan on ventricular remodeling and inflammatory cytokines after interventional therapy for AMI

The effects of captopril and valsartan on ventricular remodeling and inflammatory cytokines after interventional therapy for acute myocardial infarction (AMI) were investigated. A total of 94 patients with AMI admitted to Honggang Hospital of Dongying from July 2016 to June 2017 were selected as study subjects. The patients were treated with interventional therapy and randomly divided into the observation group (n=47) and the control group (n=47). The control group received aspirin after operation, while the observation group received captopril and valsartan after operation. Three-dimensional ultrasonography was performed to evaluate ventricular remodeling. The related parameters included left ventricular end-diastolic volume (LVEDV), left ventricular end-systolic volume (LVESV), left ventricular ejection fraction (LVEF), end-systolic sphericity index/end-diastolic sphericity index (ESSI/EDSI), systolic dyssynchrony index (SDI), diastolic dyssynchrony index (DDI), dispersion end systole (DISPES), DDI-late and DISPED-late. The levels of inflammatory cytokines were determined by enzyme-linked immunosorbent assay (ELISA). The incidence of adverse reactions after treatment was compared. After treatment, LVEF in the control group was significantly lower than that in the observation group, while LVEDV, LVESV and the ratio of early diastolic (E) and late diastolic (A) (E/A) in the control group were significantly higher than those in the observation group (p<0.05). EDSI, DDI-late and DISPED-late in the control group were significantly higher than those in the observation group (p<0.05). ESSI, SDI and DISPES in the control group were significantly higher than those in the observation group (p<0.05). The levels of interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP) and tumor necrosis factor-α (TNF-α) in the observation group were significantly lower than those in the control group at 1, 4 and 8 weeks after treatment (p<0.05). The administration of captopril and valsartan after interventional therapy for AMI can effectively improve the cardiac function of patients, improve the synchronism of left ventricular diastole and contraction, and reduce the level of inflammation. It is safe and reliable, and has important clinical significance.
Design of a Tri-Band Microstrip Patch Antenna for 5G Application

Triple band microstrip patch antenna is yet to design for 5G Application. The paper proposed a triple band microstrip patch antenna for 5G communication. Here, Rogers RT Duroid-5880 is used having a low relative permittivity, εr = 2.2 as a substrate with thickness 0.25 mm. The proposed antenna is designed and simulated by IE3D and HFSS software. Finally, their outcome is compared by HFSS software. Simulation result shows that the proposed antenna provides reflection coefficient less than −10 dB, good gain & bandwidth at (24.4/28/38 GHz) having comparatively less antenna size and substrate thickness.
Teriflunomide's Effect on Glia in Experimental Demyelinating Disease: A Neuroimaging and Histologic Study

Teriflunomide reduces disability progression and brain atrophy in multiple sclerosis patients. The exact mechanism of action by which teriflunomide exerts these effects is currently unknown. We assessed the effect of teriflunomide on brain glial cells in the Theiler's murine encephalomyelitis virus (TMEV) by using a histological approach in combination with neuroimaging.