Miracle-dz/UniFAR-FTUs huggingface dataset:
A sound effect: Exploration of the distinctiveness advantage in voice recognition

Summary Two experiments are presented, which explore the presence of a distinctiveness advantage when recognising unfamiliar voices. In Experiment 1, distinctive voices were recognised significantly better, and with greater confidence, in a sequential same/different matching task compared with typical voices. These effects were replicated and extended in Experiment 2, as distinctive voices were recognised better even under challenging listening conditions imposed by nonsense sentences and temporal reversal. Taken together, the results aligned well with similar results when processing faces, and provided a useful point of comparison between voice and face processing.
Plasmonic Sensing Characteristics of Gold Nanorods with Large Aspect Ratios

Plasmonic gold nanorods play important roles in nowadays state-of-the-art plasmonic sensing techniques. Most of the previous studies and applications focused on gold nanorods with relatively small aspect ratios, where the plasmon wavelengths are smaller than 900 nm. Gold nanorods with large aspect ratios are predicted to exhibit high refractive-index sensitivity (Langmir 2008, 24, 5233–5237), which therefore should be promising for the development of high-performance plasmonic chemical- and bio-sensors. In this study, we developed gold nanorods with aspect ratios over 7.9, which exhibit plasmon resonances around 1064 nm. The refractive index (RI) sensitivity of these nanorods have been evaluated by varying their dielectric environment, whereby a sensitivity as high as 473 nm/RIU (refractive index unit) can be obtained. Furthermore, we have demonstrated the large-aspect-ratio nanorods as efficient substrate for surface enhanced Raman spectroscopy (SERS), where an enhancement factor (EF) as high as 9.47 × 108 was measured using 4-methylbenzenethiol (4-MBT) as probe molecule. Finally, a type of flexible SERS substrate is developed by conjugating the gold nanorods with the polystyrene (PS) polymer. The results obtained in our study can benefit the development of plasmonic sensing techniques utilized in the near-infrared spectral region.
Could resistance to lactate accumulation contribute to the better swimming performance of Brycon amazonicus when compared to Colossoma macropomum?

Background In the wild, matrinchã (Brycon amazonicus) and tambaqui (Colossoma macropomum) rely strongly on their swimming capacity to perform feeding, migration and reproductive activities. Sustained swimming speed in fishes is performed almost exclusively by aerobic red muscles. The white muscle has high contraction power, but fatigue quickly, being used mainly in sprints and bursts, with a maximum duration of few seconds. The Ucrit test, an incremental velocity procedure, is mainly a measure of the aerobic capacity of a fish, but with a high participation of anaerobic metabolism close to the velocity of fatigue. Our previous study has indicated a high swimming performance of matrinchã (Ucrit) after hypoxia exposure, despite increased levels of lactate in plasma. In contrast, tambaqui with high lactate levels in plasma presented very low swimming performance. Therefore, we aimed to study the resistance of matrinchã and tambaqui to the increased lactate levels in muscle over an incremental velocity test (Ucrit). As a secondary aim, we analyzed the differences in anaerobic metabolism in response to environmental hypoxia, which could also support the better swimming performance of matrinchã, compared to tambaqui. Methods We measured, over incremented velocities in both species, the metabolic rate (the oxygen consumption by the fish; MO2), and the concentrations of lactate and nitrites and nitrates (NOx) in muscles. NOx was measured as an indicator of nitric oxide and its possible role in improving cardiorespiratory capacity in these fishes, which could postpone the use of anaerobic metabolism and lactate production during the swimming test. Also, we submitted fishes until fatigue and hypoxia (0.5 mg L−1) and measured, in addition to the previous parameters, lactate dehydrogenase activity (LDH; the enzyme responsible for lactate production), since that swimming performance could also be explained by the anaerobic capacity of producing ATP. Results Matrinchã exhibited a better swimming performance and higher oxygen consumption rates. Lactate levels were higher in matrinchã only at the moment of fatigue. Under hypoxia, LDH activity increased in the white muscle only in tambaqui, but averages were always higher in matrinchã. Discussion and conclusions The results suggest that matrinchã is more resistant than tambaqui regarding lactate accumulation in muscle at the Ucrit test, but it is not clear how much it contributes to postpone fatigue. The higher metabolic rate possibly allows the accumulated lactate to be used as aerobic fuel by the matrinchã, improving swimming performance. More studies are needed regarding matrinchã’s ability to oxidize lactate, the effects of exercise on muscle acidification, and the hydrodynamics of these species, to clarify why matrinchã is a better swimmer than tambaqui.
Understanding the Association between Environmental Factors and Longevity in Hechi, China: A Drinking Water and Soil Quality Perspective

The aging population is a big challenge all over the world. However, there are few studies to date investigating the effects of trace element and mineral levels in drinking water and soil (especially in karst areas) on longevity. This study aims to examine temporal and spatial variations in longevity in Hechi (which is recognized as a longevity city) and to investigate relationships between longevity and trace element and mineral levels in drinking water and soils in this city (the karst landscape). Population data were collected from relevant literature and four national population censuses in 1982, 1990, 2000 and 2010. Drinking water and soil samples from Hechi were collected and analyzed. The results demonstrated an obvious clustered distribution for the longevity population in Hechi that has existed stably for decades. The longevity index tended to be significantly positively correlated with H2SiO3, Ca and Fe in drinking water and significantly negatively correlated with Sr in soil, indicating that drinking water characteristics contributed significantly to the observed regional longevity. The karst landscape is responsible for abundant trace elements in underground rivers in Hechi, which are beneficial to human health when consumed as drinking water. Good quality and slightly alkaline drinking water rich in trace elements such as H2SiO3, Ca, Fe, Na, Mg and low in heavy metals such as Pb and Cd might be an important factor contributing to the longevity phenomenon in Hechi.
Degenerative Mitral Valve Repair: From Etiology, Pathology, Surgical Strategy to Durability

To the Editor: Degenerative mitral valve disease is a common disorder afflicting 2–3% of the general population and nearly half of them are elderly. [1] Plenty of studies have confirmed that mitral repair would result in better outcomes than mitral replacement for degenerative valve disease. [2] In order to illustrate the relation of etiology, pathology, valvular dysfunction, surgical strategy, and midterm durability of mitral valve repair for degenerative valve disease, we retrospectively analyzed the data of a single center. In the consecutive cohort, all of operations were performed by a skillful surgeon (G. D.) based on 100% repair criteria.
Molecular cloning and characterization of two ARNT (ARNT‐1 and ARNT‐2) genes in Atlantic croaker and their expression during coexposure to hypoxia and PCB77

Aryl hydrocarbon receptor nuclear translocator (ARNT) is an important transcriptions factor that binds/coactivates drug‐metabolizing genes in vertebrates. In this study, we report the cloning and characterization of two ARNT (ARNT‐1 and ARNT‐2) genes and their mRNA and protein expression in liver tissues of Atlantic croaker after co‐exposure to hypoxia and 3,3′,4,4′‐tetrachlorobiphenyl (PCB77). The full‐length croaker ARNT‐1 and ARNT‐2 genes encode proteins of 537 and 530 amino acids, respectively, and are highly homologous to ARNT‐1 and ARNT‐2 genes of other vertebrates. ARNT mRNAs are ubiquitously expressed in all tissues. Hypoxia (dissolved oxygen: 1.7 mg/L) exposure (1‐4 weeks) did not affect hepatic ARNTs mRNA levels. Dietary PCB77 treatment (2 and 8 μg/g body weight/day for 4 weeks) caused marked increases in ARNTs mRNA and protein levels in normoxic fish. However, coexposure to hypoxia and PCB77 for 4 weeks significantly blunted the increase in ARNTs mRNA and protein levels in response to PCB77 exposure. These results suggest that ARNT activity and functions induced by exposure to PCB aryl hydrocarbon receptor (AhR) agonists could be compromised in croaker inhabiting hypoxic coastal regions.
An Assist-as-Needed Controller for Robotic Rehabilitation Therapy Based on RBF Network

The rehabilitation training with active involvement and efforts of impaired subjects can enhance the outcome of rehabilitation therapies. To promote patients’ voluntary engagement, a variety of assist as needed (AAN) controllers have been proposed for robot-aided therapy. However, patients’ impairment level is not taken into account in the implementation of those control schemes. In this study, a novel AAN controller is developed for upper limb rehabilitation therapy. The control paradigm uses Gaussian radial basis function (RBF) network to learn the model of subjects’ motor capability in workspace. The update of weight vectors of RBF network is based on a greedy strategy, which has the potential to promote subjects’ voluntary engagement by providing task challenge for them. Considering the difference in the impairment degree of patients, the assistance and impedance level of robot control is regulated based on the task performance of patients. The results of experiments at four healthy subjects verify the feasibility and adaptability of the proposed AAN controller.
Improving Hierarchical Classification of Transposable Elements using Deep Neural Networks

Transposable Elements (TEs) are DNA sequences capable of moving within a cell’s genome. Their transposition has many effects in genomes, such as creating genetic variability and promoting changes in genes’ functionality. Recently, TEs classification has been addressed using Machine Learning (ML), more specifically by Hierarchical Classification (HC) methods. Such works proved to be superior than previous ones in the literature. However, there is still room for improvement performance wise. In this direction, Deep Neural Networks (DNNs) have attracted a lot of attention in ML. In particular, Stacked Denoising Auto-Encoders (DAEs) and Deep Multi Layer-Perceptrons (MLPs) are known to provide outstanding results. By performing an extensive evaluation, our results point out that DNNs can enhance the performance of HC methods, being able to push further the state-of-art in TEs’ classification.
Analyzing Body Fat from Depth Images

We present a novel framework to directly estimate body fat percentage from depth images of human subjects and to visually evaluate salient points of the body shape related to the fat distribution. For this purpose, we created a novel, publicly available dataset including front and back depth images of a set of subjects with specific features (active young men or professional sportsmen) with associated ground truth fat values estimated with dual-energy x-ray absorptiometry (DXA) scanning. These depth images were obtained with depth rendering of an available dataset of whole body scans, simulating low-cost depth sensor acquisitions. We customized a ResNet-50 regressor to estimate fat percentage values directly from the front/back scans, achieving promising accuracy (standard errors of estimate SEE less than 2.1 on the depth renderings and 2.5 on a small set of real depth scans. We also demonstrate that, using a custom perturbation-based procedure for analyzing deep networks, it is possible to highlight, on subjects' depth images, the specific body areas related to fat accumulation (typically neck, shoulders, hip, and abdomen) and those characterizing skinny subjects (chest and abdomen).
Merlin: A Language for Managing Network Resources

This paper presents Merlin, a framework for managing resources in software-defined networks. With Merlin, administrators express high-level policies using programs in a declarative language. The language includes logical predicates to identify sets of packets, regular expressions to encode forwarding paths, and arithmetic formulas to specify bandwidth constraints. The compiler maps these policies into a constraint problem that determines bandwidth allocations using parametrizable heuristics. It then generates a code that can be executed on the network elements to enforce the policies. To allow network tenants to dynamically adapt policies to their needs, Merlin provides mechanisms for delegating control of sub-policies and for verifying that modifications made to sub-policies do not violate global constraints. Experiments demonstrate the expressiveness and effectiveness of Merlin on realistic scenarios. Overall, Merlin simplifies network administration by providing high-level abstractions for specifying and enforcing network policies.
Building Evaluation Functions for Chess and Shogi with Uniformity Regularization Networks

Building evaluation functions for chess variants is a challenging goal. At this time, only AlphaZero succeeded with millions of self-play records produced by using thousands of tensor processing units (TPUs), which are not available for most researchers. This paper presents the challenge of training evaluation functions on the basis of deep convolutional neural networks using decent data and computing resources, where regularization is crucial as complex models trained with limited data are more prone to overfitting. We present a novel training scheme by introducing a uniformity regularization (UR) network. In the proposed approach, a value network and a discriminator network share common convolutional layers and both networks are trained simultaneously. Loss functions for them are based on the difference between the score of a random move and that of an experts’ move as a comparison training method. The value network is expected to give precise scores for all positions, while the discriminator makes qualitative evaluations for move pairs, and acts as a regularizer that penalizes differences in evaluation results to ensure all samples are uniformly discriminated. Due to the existence of shared layers, such regularization is beneficial for improving the overall accuracy of the value network. Experimental results for chess and shogi demonstrate the proposed method surpassed the standard L2 regularization method, and successfully helped obtain decently accurate value networks.
Validating the 6-minute walk test as an indicator of recovery in patients undergoing cardiac surgery

Abstract The 6-minute walk test (6MWT) has been applied to assess postsurgical recovery in cardiac populations. This study mainly investigated whether the 6MWT could serve as an indicator for physical functioning in patients undergoing cardiac surgery. Participants completed the 6MWT and the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) at baseline, discharge, and 3 months postoperatively, in order to analyze the construct validity and responsiveness of the 6MWT. The participants in this study were 125 patients (92 males and 33 females) with an average age of 65.1 ± 11.1 years. The mean 6MWT was 308.9 ± 77.3 m in the preoperative phase, decreased to 277.3 ± 85.7 m at discharge, and returned to 378.1 ± 95.2 m at 3-month follow-up. The results showed that the 6-minute walk distances at baseline and at 3-month follow-up were moderately to highly correlated with the physical functioning subscale of the SF-36 (rs = .44 and .54, respectively) and had weak correlation with the nonphysical functioning subscales. The recovery level of physical functioning is meaningfully associated with the 6MWT change from baseline to discharge and from baseline to 3-month follow-up. Patients with higher New York Heart Association (NYHA) Functional Classification levels had lower 6MWT. Additionally, the 6MWT was sensitive to change during the perioperative period (effect sizes from −0.51 to 1.72). The supporting evidence includes the construct validity and responsiveness of the 6MWT. This study supports the feasibility of the 6MWT as an evaluation tool of physical functioning for assessment of postcardiac surgical recovery.
Localization of Mobile Robots with Topological Maps and Classification with Reject Option using Convolutional Neural Networks in Omnidirectional Images

In this paper, we propose a new localization and navigation approach for mobile robots using topological maps and classification with reject option applying convolutional neural networks (CNN) for feature extraction in omnidirectional images. The use of CNN as feature extractor is based on the concept of Transfer Learning. Reject option is used to improve the task of the classifiers, querying information from the topological map. With the objective of evidencing the high performance of the technique considered, an analysis is made between several feature extractors and classifiers, established in the literature. Parameters such as processing time and accuracy are calculated to prove the credibility and effectiveness of the approach, since these properties are fundamental in the analysis of embedded systems. Considering the proposed approach, CNN stands out among the other feature extractors, as it generated the best results in extraction time and accuracy. It obtained an average accuracy of 99.86% and an extraction time of 0.1517s, proving to be a relevant method for the localization and navigation activities.
Evaluation of Diagnostic Efficiency of Alpha-Fetoprotein in Patients with Liver Cirrhosis and Hepatocellular Carcinoma: Single-Center Experience

BACKGROUND: AFP serum levels are considered as diagnostic and specific for hepatocellular carcinoma (HCC) in patients with liver cirrhosis (LC). AIM: This study aimed to examine the diagnostic value of AFP in the distinguishing of patients with HCC from patients with LC, and to analyse the potential correlation between AFP levels and liver disease stages. MATERIAL AND METHODS: Fifty patients with LC and fifty patients with HCC were included in this study. The majority of the patients were males, while the HBV aetiology was dominant. RESULTS: Significant differences between LC and HCC patients were detected for AST, ALT, GGT, bilirubin, AFP and AP. Patients with HCC had higher AFP values compared to LC. There was no significant correlation between the size of the tumour lesion and serum AFP levels. A positive correlation between AFP concentration and GGT activity was determined, as was the negative correlation between AFP and age of the subjects. The AFP value of 23.34 ng/m showed high sensitivity (84%) and specificity (82%). CONCLUSION: The size of the surface below the ROC curve (AUC) was 0.877 (0.80-0.95), which makes AFP a good biomarker and this diagnostic test is sufficient to separate patients with HCC and LC.
Randomized study of intravesical pirarubicin chemotherapy with low and intermediate-risk nonmuscle-invasive bladder cancer in Japan

Purpose: The objective of this study was to evaluate the efficacy, defined by the 3-year tumor recurrence-free survival rate, of intravesical chemotherapy using pirarubicin (THP) in patients with low or intermediate-risk nonmuscle-invasive bladder cancer (NMIBC). Patients and methods: Between October 2010 and January 2015, 206 patients were enrolled, and finally 113 were randomized to receive either a single immediate postoperative intravesical instillation of THP (30 mg) (Group A), or 8 additional weekly intravesical instillations of THP (30 mg) after a single postoperative instillation (Group B). The patients were examined by performing cystoscopy and urine cytology every 3 months after transurethral resection to determine bladder tumor recurrence. The primary endpoint was 3-year-recurrence-free survival rate. Results: All 113 patients were bacillus Calmette–Guérin (BCG)-naïve. The 3-year recurrence free survival rate was 63.7% for Group A and 85.3% for Group B (log-rank test, P = .0070). In patients with intermediate recurrence risk, the 3-year recurrence-free survival rate was 63.4% in Group A and 86.1% in Group B (log-rank test, P = .0036). Cox regression analysis revealed that only additional instillation of THP was a significant independent factor for recurrence-free rate in patients with intermediate risk. No patient with progression was noted during this period. Frequent adverse effects (AEs) were frequent urination and micturition pain, and no severe AEs (Grade 3 or more) occurred. Conclusion: Additional instillation of THP (30 mg) weekly for 8 weeks reduced the risk of tumor recurrence without severe AEs in BCG-naïve NMIBC patients with intermediate risk.
Rebalancing Multiple Assets with Mutual Price Impact

We find asymptotically optimal trading policies for long-term investors with constant relative risk aversion, in a multiple-assets market, where expected returns and covariances are constant, and the execution price of each asset is linear in the trading intensities of all assets. Trading toward the frictionless target is optimal, when the current portfolio differs from the target by a principal portfolio—an eigenvector of the inverse impact matrix times the covariance matrix. Optimal policies approach the frictionless target along nonlinear, power-shaped paths, trading faster in more liquid directions, while tolerating wider oscillations along less liquid directions.
Effects of wine-cap Stropharia cultivation on soil nutrients and bacterial communities in forestlands of northern China

Background Cultivating the wine-cap mushroom (Stropharia rugosoannulata) on forestland has become popular in China. However, the effects of wine-cap Stropharia cultivation on soil nutrients and bacterial communities are poorly understood. Methods We employed chemical analyses and high-throughput sequencing to determine the impact of cultivating the wine-cap Stropharia on soil nutrients and bacterial communities of forestland. Results Cultivation regimes of Stropharia on forestland resulted in consistent increases of soil organic matter (OM) and available phosphorus (AP) content. Among the cultivation regimes, the greatest soil nutrient contents were found in the one-year interval cultivation regime, and the lowest total N and alkaline hydrolysable N contents were observed in the current-year cultivation regime. No significant differences were observed in alpha diversity among all cultivation regimes. Specific soil bacterial groups, such as Acidobacteria, increased in abundance after cultivation of Stropharia rugosoannulata. Discussion Given the numerous positive effects exerted by OM on soil physical and chemical properties, and the consistent increase in OM content for all cultivation regimes, we suggest that mushroom cultivation is beneficial to forest soil nutrient conditions through increasing OM content. Based on the fact that the one-year interval cultivation regime had the highest soil nutrient content as compared with other cultivation regimes, we recommend this regime for application in farming practice. The spent mushroom compost appeared to be more influential than the hyphae of S. rugosoannulata on the soil nutrients and bacterial communities; however, this requires further study. This research provides insight into understanding the effects of mushroom cultivation on the forest soil ecosystem and suggests a relevant cultivation strategy that reduces its negative impacts.