Miracle-dz/UniFAR-FTUs huggingface dataset:
Acute effects of theanine, caffeine and theanine–caffeine combination on attention

Objective: l-theanine is a constituent of tea which is claimed to enhance cognitive functions. We aimed to determine whether theanine and theanine–caffeine combination have acute positive effects on cognitive and neurophysiological measures of attention, compared to caffeine (a positive control) and a placebo in healthy individuals. Design: In a placebo-controlled, five-way crossover trial in 20 healthy male volunteers, we compared the effects of l-theanine (200 mg), caffeine (160 mg), their combination, black tea (one cup) and a placebo (distilled water) on cognitive (simple [SVRT] and recognition visual reaction time [RVRT]) and neurophysiological (event-related potentials [ERPs]) measures of attention. We also recorded visual (VEPs) and motor evoked potentials (MEPs) to examine any effects of treatments on peripheral visual and motor conduction, respectively. Results: Mean RVRT was significantly improved by theanine (P = 0.019), caffeine (P = 0.043), and theanine–caffeine combination (P = 0.001), but not by tea (P = 0.429) or placebo (P = 0.822). VEP or MEP latencies or SVRT did not show significant inter-treatment differences. Theanine (P = 0.001) and caffeine (P = 0.001) elicited significantly larger mean peak-to-peak N2-P300 ERP amplitudes than the placebo, whereas theanine–caffeine combination elicited a significantly larger mean N2-P300 amplitude than placebo (P < 0.001), theanine (P = 0.029) or caffeine (P = 0.005). No significant theanine × caffeine interaction was observed for RVRT or N2-P300 amplitude. Discussion: A dose of theanine equivalent of eight cups of back tea improves cognitive and neurophysiological measures of selective attention, to a degree that is comparable with that of caffeine. Theanine and caffeine seem to have additive effects on attention in high doses.
Reproductive Aging and Hepatic Fibrosis Progression in Human Immunodeficiency Virus/Hepatitis C Virus–Coinfected Women

Background Severity of hepatic fibrosis is greater in postmenopausal than in premenopausal women, perhaps owing to protective effects of estrogens. However, prior studies of estrogen and liver fibrosis lack serial fibrosis measures, adjustment for age, or longitudinal observations in coinfected populations. Methods In a longitudinal cohort of women coinfected with human immunodeficiency virus (HIV) and hepatitis C virus (HCV), we assessed fibrosis progression across reproductive age, using validated serum fibrosis markers, aminotransferase platelet ratio index (APRI) and fibrosis 4 (FIB-4). Fibrosis rate was evaluated within each woman as she transitioned from pre- to postmenopause, defined by a biomarker of ovarian function. Results The median follow-up (n = 405) was 9.1 years (interquartile range, 5.0-15.2 years), with a median menopausal age of 49 years (47-52 years). When fully controlled for chronologic aging, the fibrosis progression rate was accelerated during perimenopause, as shown using FIB-4 (0.12 units per year faster than during premenopause; 95% confidence interval [CI], .02-.21; P = .01) and APRI (0.05 units per year faster; -.002 to .09; P = .06). Accelerated fibrosis was also observed during postmenopause compared with premenopause, for FIB-4 (0.14 units per year faster; 95% CI, -.01 to .29; P = .07) and APRI (0.07 units per year faster; -.003 to .15; P = .06). Accelerated fibrosis in perimenopause persisted after adjustment for Hispanic ethnicity, antiretroviral use, and alcohol (0.10 FIB-4 units per year faster than during premenopause; 95% CI, .008-.20; P = .03). Conclusions In HIV/HCV-coinfected women, hepatic fibrosis accelerates with reproductive aging. Accelerated fibrosis begins in perimenopause, highlighting a previously unrecognized group of women at increased risk for advanced fibrosis and associated complications. Longitudinal analyses of fibrosis rates across reproductive age should be conducted in non-HCV-related liver diseases, given potential implications in a broader spectrum of women.
Stress Analysis of Composite Plates with Different Types of Cutouts

This research presents an experimental and theoretical investigation of the effect of cutouts on the stress and strain of composite laminate plates subjected to static loads. The experimental program covers measurement of the normal strain at the edges of circular and square holes with different number of layers and types of composite materials by using strain gages technique under constant tensile loads. A numerical investigation has been achieved by using the software package (ANSYS), involving static analysis of symmetric square plates with different types of cutouts. The numerical results include the parametric effects of lamination angle, hole dimensions, types of hole and the number of layers of a symmetric square plate. The experimental results show good agreement compared with numerical results. It is found that increasing the number of layers reduces the value of normal strain at the edges of circular and square holes of a symmetric plate and the maximum value of stress occurs at a lamination angle of (30 o ) and the maximum value of strain occurs at a lamination angle of (50 o ) for the symmetric square plates subjected to uni-axial appl ied load. The hole dimensions to width of plates ratio is found to increase the maximum value of stress and strain of a symmetric square plate subjected to uniaxial applied load. Moreover, the value of maximum stress increases with the order of type of circular, square, triangular and hexagonal cutout, whereas the value of maximum strain increases with the order of type of circular, square, hexagonal and triangular cutout.
Organoleptic Quality of Chicken Meat Rolls and Patties Added with the Combination Levels of Black Gram Hull and Psyllium Husk

The present study was envisaged to prepare dietary fiber rich chicken meat rolls and patties. The combination of two different sources of dietary fiber viz. black gram hull and psyllium husk has been used. They were added in three different levels viz. 5% black gram hull and 2% psyllium husk, 5% black gram hull and 4% psyllium husk and 5% black gram hull and 6% psyllium husk. The sensory characteristics such as colour, flavour, tenderness, juiciness, texture and overall acceptability of fiber added chicken meat rolls and patties were studied. In general, the sensory scores showed a decreasing trend with increasing levels of incorporation but 5% black gram hull and 4% psyllium husk combination was found to be suitable organoleptically.
Time to Do the Right Thing: End Fee-for-Service for Primary Care

> You can always count on Americans to do the right thing - after they’ve tried everything else. > > –Winston Churchill Current fee-for-service (FFS) payment rates for physician visits trace to the origins of Blue Cross Blue Shield insurance in the 1930s. At that time, rates were set that paid
Reconstruction of undersampled radial free-breathing 3D abdominal MRI using stacked convolutional auto-encoders.

PURPOSE Free-breathing three-dimensional (3D) abdominal imaging is a challenging task for MRI, as respiratory motion severely degrades image quality. One of the most promising self-navigation techniques is the 3D golden-angle radial stack-of-stars (SOS) sequence, which has advantages in terms of speed, resolution, and allowing free breathing. However, streaking artifacts are still clearly observed in reconstructed images when undersampling is applied. This work presents a novel reconstruction approach based on a stacked convolutional auto-encoder (SCAE) network to solve this problem. METHODS Thirty healthy volunteers participated in our experiment. To build the dataset, reference and artifact-affected images were reconstructed using 451 golden-angle spokes and the first 20, 40, or 90 golden-angle spokes corresponding to acceleration rates of 31.4, 15.7, and 6.98, respectively. In the training step, we trained the SCAE by feeding it with patches from artifact-affected images. The SCAE outputs patches in the corresponding reference images. In the testing step, we applied the trained SCAE to map each input artifact-affected patch to the corresponding reference image patch. RESULT The SCAE-based reconstruction images with acceleration rates of 6.98 and 15.7 show nearly similar quality as the reference images. Additionally, the calculation time is below 1 s. Moreover, the proposed approach preserves important features, such as lesions not presented in the training set. CONCLUSION The preliminary results demonstrate the feasibility of the proposed SCAE-based strategy for correcting the streaking artifacts of undersampled free-breathing 3D abdominal MRI with a negligible reconstruction time.
Forgetting methods for incremental matrix factorization in recommender systems

Numerous stream mining algorithms are equipped with forgetting mechanisms, such as sliding windows or fading factors, to make them adaptive to changes. In recommender systems those techniques have not been investigated thoroughly despite the very volatile nature of users' preferences that they deal with. We developed five new forgetting techniques for incremental matrix factorization in recommender systems. We show on eight datasets that our techniques improve the predictive power of recommender systems. Experiments with both explicit rating feedback and positive-only feedback confirm our findings showing that forgetting information is beneficial despite the extreme data sparsity that recommender systems struggle with. Improvement through forgetting also proves that users' preferences are subject to concept drift.
Chemometric profile, antioxidant and tyrosinase inhibitory activity of Camel’s foot creeper leaves (Bauhinia vahlii)

Abstract The present study is the first effort to a comprehensive evaluation of antityrosinase activity and chemometric analysis of Bauhinia vahlii. The experimental results revealed that the methanol extract of Bauhinia vahlii (BVM) possesses higher polyphenolic compounds and total antioxidant activity than those reported elsewhere for other more conventionally and geographically different varieties. The BVM contain saturated fatty acids such as hexadecanoic acid (10.15%), octadecanoic acid (1.97%), oleic acid (0.61%) and cis-vaccenic acid (2.43%) along with vitamin E (12.71%), α-amyrin (9.84%), methyl salicylate (2.39%) and β-sitosterol (17.35%), which were mainly responsible for antioxidant as well as tyrosinase inhibitory activity. Tyrosinase inhibitory activity of this extract was comparable to that of Kojic acid. These findings suggested that the B. vahlii leaves could be exploited as potential source of natural antioxidant and tyrosinase inhibitory agent, as well.
Catabolism of the Cholesterol Side Chain in Mycobacterium tuberculosis Is Controlled by a Redox-Sensitive Thiol Switch

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), is a highly successful human pathogen and has infected approximately one-third of the world’s population. Multiple drug resistant (MDR) and extensively drug resistant (XDR) TB strains and coinfection with HIV have increased the challenges of successfully treating this disease pandemic. The metabolism of host cholesterol by Mtb is an important factor for both its virulence and pathogenesis. In Mtb, the cholesterol side chain is degraded through multiple cycles of β-oxidation and FadA5 (Rv3546) catalyzes side chain thiolysis in the first two cycles. Moreover, FadA5 is important during the chronic stage of infection in a mouse model of Mtb infection. Here, we report the redox control of FadA5 catalytic activity that results from reversible disulfide bond formation between Cys59-Cys91 and Cys93-Cys377. Cys93 is the thiolytic nucleophile, and Cys377 is the general acid catalyst for cleavage of the β-keto-acyl-CoA substrate. The disulfide bond formed between the two catalytic residues Cys93 and Cys377 blocks catalysis. The formation of the disulfide bonds is accompanied by a large domain swap at the FadA5 dimer interface that serves to bring Cys93 and Cys377 in close proximity for disulfide bond formation. The catalytic activity of FadA5 has a midpoint potential of −220 mV, which is close to the Mtb mycothiol potential in the activated macrophage. The redox profile of FadA5 suggests that FadA5 is fully active when Mtb resides in the unactivated macrophage to maximize flux into cholesterol catabolism. Upon activation of the macrophage, the oxidative shift in the mycothiol potential will decrease the thiolytic activity by 50%. Thus, the FadA5 midpoint potential is poised to rapidly restrict cholesterol side chain degradation in response to oxidative stress from the host macrophage environment.
Failing to Learn: Autonomously Identifying Perception Failures for Self-Driving Cars

One of the major open challenges in self-driving cars is the ability to detect cars and pedestrians to safely navigate in the world. Deep learning-based object detector approaches have enabled great advances in using camera imagery to detect and classify objects. But for a safety critical application, such as autonomous driving, the error rates of the current state of the art are still too high to enable safe operation. Moreover, the characterization of object detector performance is primarily limited to testing on prerecorded datasets. Errors that occur on novel data go undetected without additional human labels. In this letter, we propose an automated method to identify mistakes made by object detectors without ground truth labels. We show that inconsistencies in the object detector output between a pair of similar images can be used as hypotheses for false negatives (e.g., missed detections) and using a novel set of features for each hypothesis, an off-the-shelf binary classifier can be used to find valid errors. In particular, we study two distinct cues–temporal and stereo inconsistencies—using data that are readily available on most autonomous vehicles. Our method can be used with any camera-based object detector and we illustrate the technique on several sets of real world data. We show that a state-of-the-art detector, tracker, and our classifier trained only on synthetic data can identify valid errors on KITTI tracking dataset with an average precision of 0.94. We also release a new tracking dataset with 104 sequences totaling 80,655 labeled pairs of stereo images along with ground truth disparity from a game engine to facilitate further research.
Design and control of robot legs with bi-articular muscle-tendon complex

The musculoskeletal system of animals is evolved to an optimal form for their locomotion in their living environments. Their phenomenal dynamic motions are performed by synergistically using those muscles and tendons. In particular, it is known that the muscle-tendon complex in lower leg greatly contributes to the fast running and jumping of felidae like cats and cheetahs. This complex, which is composed of gastrocnemius and Achilles' tendon, generates large output by storing and reusing the kinetic energy during their locomotions. To realize creature-like dynamic motion, we have developed leg mechanism called elastic four-bar linkage mechanism, which is made of four-bar linkage mechanism with one elastic linkage and electrical motor, inspired by bi-articular muscle-tendon complex of cats. In this paper, we optimize the design of the four-bar linkage mechanism including elasticity characteristics of elastic linkage in this leg mechanism by vertical jump simulation. Moreover, we propose the motion control strategy for drop jump inspired from the Stretch-Shortening Cycle (SSC) of bi-articular muscle-tendon complex. As a result of drop jump experiment using two-legged robot, the robot realized high jumps owing to the optimal design and the new control strategy.
Process Protocol and Cost of Production of Functional Fiber-Enriched Pork Loaves

The objectives of the present study was to standardize the protocol for production of functional pork loaves and to assess the economics of production of the developed product. Four treatments were prepared with incorporation of inulin powder (IP) as fibre source viz. Control (0% IP; C), 1% (T1), 2% (T2) and 3% (T3) by replacing the amount of lean meat in the product formulation. Different batches were steam cooked at 110 oC for 40 minutes, cooled, sliced and evaluated for different quality parameters. The cooking yield and emulsion stability improved with the increase in level of incorporation of inulin. The cost of production also increased with increase in inulin level in product and calculated as highest in T3. The net profit for the control and 1% IP enriched pork loaves was highest whereas lowest for 3% IP pork loaves. The break-even point was estimated on the basis of value marketed product and calculated as 1195188.00 for control whereas 1331576.00 for T3 and cost-benefit ratio 35% for control and T1. Net Income (/month) after repayment of loan was highest for control and T1 as 77533.00 and lowest for T3 70033.00. The estimated details of economics of the developed product concluded that there is marginal increase about 1% in the price of functional pork loaves and this venture can a successful enterprise.
The Role of Urinary Neutrophil Gelatinase-Associated Lipocalin in Predicting Acute Kidney Dysfunction in Patients With Liver Cirrhosis

Background Early detection of acute kidney dysfunction (AKD) in cirrhotic patients is crucial. Urinary neutrophil gelatinase-associated lipocalin (uNGAL) has been identified as an early marker of AKD. The aim of the study was to evaluate serial uNGAL as a marker and predictor of AKD in liver cirrhosis patients. Methods Serial uNGAL and serum creatinine (sCr) levels were measured daily during the first 6 days of admission. Furthermore, sCr levels and the estimated glomerular filtration rate (eGFR) were measured after 3 - 6 weeks. The uNGAL levels in patients with and without abnormal sCr were compared. Results Fifty-seven consecutive cirrhotic patients were enrolled in the study. Eight of 14 patients (57%) who developed abnormal uNGAL level also had abnormal sCr level (odds ratio (OR) = 3.4, 95% CI: 0.99 - 12.03, P = 0.05). After 6 weeks, 41% of patients exhibited an abnormal uNGAL level and abnormal sCr (OR = 6.7, 95% CI: 1.55 - 28.85, P = 0.01). Area under the curve (AUROC) and the best cut-off point for highest NGAL in 6 days were 0.64 and 72.55 ng/mL, respectively. Conclusions There is a modest association between highest uNGAL in the first 6 days of admission and sCr at week 6 in all participants. This may indicate that in cirrhotic patients, uNGAL level during the first 6 days of admission has a potential predictability for the development of high sCr and low eGFR 6 weeks later. The AUROC of 0.64 quantifies the overall ability of uNGAL to discriminate between those individuals who will have a raised sCr levels and those who will not.
Probabilistic States Versus Multiple Certainties: the Obstacle of Uncertainty in Contingent Reasoning

We propose a new hypothesis, the Power of Certainty, to help explain agents' difficulties in making choices when there are multiple possible payoff-relevant states. In the probabilistic ‘Acquiring-a-Company’ problem an agent submits a price to a firm before knowing whether the firm is of low or high value. We construct a deterministic problem with a low and high value firm, where the agent submits a price that is sent to each firm separately. Subjects are much more likely to use dominant strategies in deterministic than in probabilistic problems, even though computations for profit maximization are identical for risk-neutral agents.
A computationally efficient and robust kinematic calibration model for industrial robots with kinematic parallelogram

We propose a computationally efficient and robust DH kinematic calibration model to solve the kinematic calibration of the robots with kinematic parallelogram. This model segments the closed chain of kinematic parallelogram into two open chains. Then, by constraining positions of two endpoints in every chain, this model reconstructs kinematic parallelogram as a serial structure. This reconstruction-based DH model (called RST-based kinematic calibration model) has not only proven to be robust and effective in calibration but it is also favored from a computational efficiency viewpoint since it consists of comparatively fewer error parameters. To calculate the error parameters, the genetic algorithm is applied here. The positioning errors on the end-effector (EE) of a Comau Smart5 NJ 220-2.7 robot based on the proposed RST-based kinematic calibration model, modified kinematic calibration model and continuous kinematic calibration model are performed. By comparing the means, standard deviations and computational time of the positioning errors, computational efficiency and robustness of these three models are compared. Finally, the experimental results validate among the three DH calibration models, the proposed RST-based model has the advantages of computational efficiency and robustness. And they successfully validate the feasibility of the present model.
In Silico Prediction of Compounds Binding to Human Plasma Proteins by QSAR Models

Plasma protein binding (PPB) is a significant pharmacokinetic property of compounds in drug discovery and design. Due to the high cost and time‐consuming nature of experimental assays, in silico approaches have been developed to assess the binding profiles of chemicals. However, because of unambiguity and the lack of uniform experimental data, most available predictive models are far from satisfactory. In this study, an elaborately curated training set containing 967 diverse pharmaceuticals with plasma‐protein‐bound fractions (fb) was used to construct quantitative structure–activity relationship (QSAR) models by six machine learning algorithms with 26 molecular descriptors. Furthermore, we combined all of the individual learners to yield consensus prediction, marginally improving the accuracy of the consensus model. The model performance was estimated by tenfold cross validation and three external validation sets comprising 242 pharmaceutical, 397 industrial, and 231 newly designed chemicals, respectively. The models showed excellent performance for the entire test set, with mean absolute error (MAE) ranging from 0.126 to 0.178, demonstrating that our models could be used by a chemist when drawing a molecular structure from scratch. Meanwhile, structural descriptors contributing significantly to the predictive power of the models were related to the binding mechanisms, and the trend in terms of their effects on PPB can serve as guidance for the structural modification of chemicals. The applicability domain was also defined to distinguish favorable predictions from unfavorable predictions.