Miracle-dz/UniFAR-FTUs huggingface dataset:
SolarView: Low Distortion Radial Embedding with a Focus

We propose a novel type of low distortion radial embedding which focuses on one specific entity and its closest neighbors. Our embedding preserves near-exact distances to the focus entity and aims to minimize distortion between the other entities. We present an interactive exploration tool SolarView which places the focus entity at the center of a “solar system” and embeds its neighbors guided by concentric circles. SolarView provides an implementation of our novel embedding and several state-of-the-art dimensionality reduction and embedding techniques, which we adapted to our setting in various ways. We experimentally evaluated our embedding and compared it to these state-of-the-art techniques. The results show that our embedding competes with these techniques and achieves low distortion in practice. Our method performs particularly well when the visualization, and hence the embedding, adheres to the solar system design principle of our application. Nonetheless—as with all dimensionality reduction techniques—the distortion may be high. We leverage interaction techniques to give clear visual cues that allow users to accurately judge distortion. We illustrate the use of SolarView by exploring the high-dimensional metric space of bibliographic entity similarities.
Differential Effects of Intranasal Vasopressin on the Processing of Adult and Infant Cues: An ERP Study

Arginine vasopressin (AVP) is a powerful regulator of various social behaviors across many species. However, seemingly contradictory effects of AVP have been found in both animal and human studies, e.g., promoting aggression on one hand and facilitating social bonding on the other hand. Therefore, we hypothesize that the role of AVP in social behaviors is context-dependent. To this end, we examined the modulatory effect of AVP on male’s behavioral and neural responses to infant and adult cues. After intranasal and double-blind treatment of AVP or placebo, male participants were asked to rate their subjective approaching willingness to infant and adult faces in specific contexts informed by cue words while EEG recording. Our results showed that AVP treatment increased approaching ratings to neutral and positive other-gender adult faces compared to emotional matched same-gender adult faces, and to negative girl faces compared to negative boy faces. Furthermore, compared to placebo treatment, AVP treatment induced larger N1 amplitudes to neutral cues associated with both adults and infants, whereas AVP treatment only sustained pronounced late positive potential amplitudes to neutral cues of infants but not adults. Those findings implicate differential roles of AVP in the processing of adult- and infant-related cues and thus lend support to the context-dependent account.
BandReader - A Mobile Application for Data Acquisition from Wearable Devices in Affective Computing Experiments

As technology becomes more ubiquitous and pervasive, special attention should be given to human-computer interaction, especially to the aspect related to the emotional states of the user. However, this approach assumes very specif c mode of data collection and storage. This data is used in the affective computing experiments for human emotion recognition. In the paper we describe a new software solution for mobile devices that allows for data acquisition from wristbands. The application reads physiological signals from wristbands and supports multiple recent devices. In our work we focus on the Heart Rate (HR) and Galvanic Skin Response (GSR) readings. The recorded data is conveniently stored in CSV fles, ready for further interpretation. We provide the evaluation of our application with several experiments. The results indicate that the BandReader is a reliable software for data acquisition in affective computing scenarios.
Improvement of Vegetation Water Content Estimation Over the Tibetan Plateau Using Field Measurements

Vegetation water content (VWC) plays a significant role in the retrieval of soil moisture using microwave remote sensing, which further supports applications such as weather forecasting, flood prediction, and landslide early-warning. In the current SMAP algorithm, the commonly used vegetation index (i.e., the NDVI) was utilized to determine the VWC. This study evaluates the accuracy of SMAP VWC product, together with other Jackson's algorithm using NDVI and Paloscia's method using LAI. Comparing to ground observation, SMAP overestimates VWC, while Jackson's method, in which stem factor is not included, performs better than other two. By using Jackson's method, we found the accuracy of soil moisture retrieved from SMAP could be improved.
An Improved ORB Algorithm Based on Multi-Feature Fusion

In order to improve the matching accuracy and reduce mismatch of the ORB algorithm when it was directly applied into image matching, an improved ORB algorithm is proposed based on the LATCH feature and the improved LBP feature. In feature point detection, the multi-scale FAST corner detection algorithm is used to find out the feature point with scale invariance. In feature point description, the LATCH feature and the LBP feature are used to generate feature point descriptor. Aiming at the problem that the LBP feature is too sensitive to noise and image local change, image block method is applied into the generate the improved LBP feature proposed in this paper. Then these two features are combined to form a new binary LATCH/LBP feature by multi-feature fusion method. Then combined with the Center of gravity method used in the ORB algorithm, the new LATCH/LBP feature can obtain strong robustness. In feature matching, the nearest neighbor matching algorithm is used to realize the matching between two image feature vectors. Finally, the matching results are screened by RANSAC algorithm to eliminate mismatch points. The experiment results show that the improved ORB algorithm proposed in this paper can effectively improve the matching accuracy of the ORB algorithm on the basis of real-time performance.
Does Severity of Alzheimer's Disease Contribute to Its Responsiveness to Modifying Gut Microbiota? A Double Blind Clinical Trial

Alzheimer's disease (AD) is associated with cognitive dysfunction. Evidence indicates that gut microbiota is altered in the AD and, hence, modifying the gut flora may affect the disease. In the previous clinical research we evaluated the effect of a probiotic combination on the cognitive abilities of AD patients. Since, in addition to pathological disorders, the AD is associated with changes in oxidant/antioxidant and inflammatory/anti-inflammatory biomarkers, the present work was designed to evaluate responsiveness of the inflammatory and oxidative biomarkers to the probiotic treatment. The control (CON) and probiotic (PRO) AD patients were treated for 12 weeks by the placebo and probiotic supplementation, respectively. The patients were cognitively assessed by Test Your Memory (TYM = 50 scores). Also serum concentrations of nitric oxide (NO), glutathione (GSH), total antioxidant capacity (TAC), malondialdehyde (MDA), 8-hydroxy-2′ -deoxyguanosine (8-OHdG) and cytokines (TNF-a, IL-6, and IL-10) were measured. The cognitive test and the serum biomarkers were assessed pre- and post-treatment. According to TYM test 83.5% of the patients showed severe AD. The CON (12.86% ± 8.33) and PRO (−9.35% ± 16.83) groups not differently scored the cognitive test. Not pronounced change percent was found in the serum level of TNF-α (1.67% ± 1.33 vs. −0.15% ± 0.27), IL-6 (0.35% ± 0.17 vs. 2.18% ± 0.15), IL-10 (0.05% ± 0.10 vs. −0.70% ± 0.73), TAC (0.07% ± 0.07 and −0.06% ± 0.03), GSH (0.08% ± 0.05 and 0.04% ± 0.03) NO (0.11% ± 0.06 and 0.05% ± 0.09), MDA (−0.11% ± 0.03 and −0.17% ± 0.03), 8-OHdG (43.25% ± 3.01 and 42.70% ± 3.27) in the CON and PRO groups, respectively. We concluded that the cognitive and biochemical indications in the patients with severe AD are insensitive to the probiotic supplementation. Therefore, in addition to formulation and dosage of probiotic bacteria, severity of disease and time of administration deeply affects results of treatment.
Nonlinear Dynamic Analysis of Air Traffic Flow at Different Temporal Scales: Nonlinear Analysis Approach versus Complex Networks Approach

Insights into the temporal-spatial characteristics of air traffic flow is the prerequisite of air traffic flow modeling, prediction and optimization. The intrinsic dynamics of air traffic flow were analyzed according to radar track data by classical nonlinear analysis and complex network methods. The nonlinear dynamic characteristics of air traffic flow were revealed from multiple perspectives by means of phase space reconstruction, recurrence plot, Lyapunov exponent, correlation dimension and Hurst exponent. The experimental results show that the example traffic flow became the most chaotic and the state persistence was poorest at time scale of 30 min. Besides, this paper explored the application of a complex network to analyze the nonlinearity of air traffic flow, and verified the chaotic and fractal characteristics by analyzing the degree distribution of the converted network. The degree distribution of the network derived from the traffic flow time series was approximately fitted to the exponential function and featured a strength level of chaos that was positively correlated with the size of network degree distribution power exponent. The linear relationship between network degree distribution power exponent and Hurst exponent was revealed, and the nonlinearity of air route traffic flow was systematically characterized. Particularly, the complex network-based analysis method helped examine air traffic flow from a new perspective, enriching the research means. These novel findings will provide theoretical basis for aggregated air traffic flow modeling, decision support system design and tactical flow management.
An Optimal Policy for Patient Laboratory Tests in Intensive Care Units

Laboratory testing is an integral tool in the management of patient care in hospitals, particularly in intensive care units (ICUs). There exists an inherent trade-off in the selection and timing of lab tests between considerations of the expected utility in clinical decision-making of a given test at a specific time, and the associated cost or risk it poses to the patient. In this work, we introduce a framework that learns policies for ordering lab tests which optimizes for this trade-off. Our approach uses batch off-policy reinforcement learning with a composite reward function based on clinical imperatives, applied to data that include examples of clinicians ordering labs for patients. To this end, we develop and extend principles of Pareto optimality to improve the selection of actions based on multiple reward function components while respecting typical procedural considerations and prioritization of clinical goals in the ICU. Our experiments show that we can estimate a policy that reduces the frequency of lab tests and optimizes timing to minimize information redundancy. We also find that the estimated policies typically suggest ordering lab tests well ahead of critical onsets—such as mechanical ventilation or dialysis—that depend on the lab results. We evaluate our approach by quantifying how these policies may initiate earlier onset of treatment.
Active Attack Against Oblivious RAM

When a user consumes an encrypted digital content (for example video and music files), the player application accesses the secret key to decrypt the content. If the user is malicious, he can analyse the access pattern of the player application to extract the secret key efficiently. Oblivious RAMs (ORAMs) are effective solution for such threats. However, ORAMs are only effective for `passive' attackers who can observe the RAM access done by the application, but cannot alter data stored on RAM. The attacker with ability to alter data on RAM can be called `active' attackers. In this paper, we evaluate the security of ORAM schemes against active adversaries where they alter data on RAM and try to efficiently extract the secret information. We also propose countermeasures against active adversaries.
Maximum Power Point Estimation of a PV Array by Using Improve Bisection Method

This paper presents a novel approach to estimate the maximum power point (MPP) of a photovoltaic (PV) array. The MPP of the PV array is directly estimated from the current-voltage (I-V) curve by using Improved Bisection Method (IBM) under different irradiation and temperature conditions. The five parameters single diode model PV module parameters are estimated from the data sheet values given by the manufacturer under standard test condition (STC). The IBM is simple, fast and returns the MPP more accurately. The estimation of MPP of a PV array under different environmental conditions is presented by using MATLAB program. Also, a comparison of the proposed method with different existing methods has been presented for tracking of MPP of the PV array. It is observed that the estimated MPP of the module is nearly equal to the actual MPP values and thus the performance of the proposed method is more accurate.
Walking with perturbations: a guide for biped humans and robots

This paper provides an update on the neural control of bipedal walking in relation to bioinspired models and robots. It is argued that most current models or robots are based on the construct of a symmetrical central pattern generator (CPG). However, new evidence suggests that CPG functioning is basically asymmetrical with its flexor half linked more tightly to the rhythm generator. The stability of bipedal gait, which is an important problem for robots and biological systems, is also addressed. While it is not possible to determine how biological biped systems guarantee stability, robot solutions can be useful to propose new hypotheses for biology. In the second part of this review, the focus is on gait perturbations, which is an important topic in robotics in view of the frequent falls of robots when faced with perturbations. From the human physiology it is known that the initial reaction often consists of a brief interruption followed by an adequate response. For instance, the successful recovery from a trip is achieved using some basic reactions (termed elevating and lowering strategies), that depend on the phase of the step cycle of the trip occurrence. Reactions to stepping unexpectedly in a hole depend on comparing expected and real feedback. Implementation of these ideas in models and robotics starts to emerge, with the most advanced robots being able to learn how to fall safely and how to deal with complicated disturbances such as provided by walking on a split-belt.
Relationship between diet quality and carotid intima-media thickness in people with and without carotid atherosclerosis

Background: Dietary assessment and management appear to be essential to limit the impact of cardiovascular risk. Aim: This study aims to assess the association between diet quality as measured by Alternate Healthy Eating Index (AHEI) and coronary risk as determined by carotid artery intima-media thickness (CIMT) among Saudi adults. Methods: A case–control study was conducted in 210 participants who were matched for age and sex and recruited sequentially from King Abdulaziz University Hospital, Jeddah, Saudi Arabia. Demographic and anthropometric variables were measured in all study participants. Dietary intake was measured by food frequency questionnaire. Results: Obesity was highly prevalent among the study population. The mean AHEI score for the total sample was found to be 58.3 ± 1.67. There were no differences according to the presence and absence of atherosclerotic disease; 45% had a poor diet, and 39% had a diet that needs improvement. Participants with higher CIMT values tended to be of lower AHEI category. Negative correlations were observed between CIMT and AHEI scores and components after adjustment for age and energy intake. Conclusions: Adherence to a healthier diet, as reflected by a higher AHEI score, is associated with lower coronary risk, as estimated by CIMT value, independently from obesity and personal behavior factors.
CareFi: Sedentary Behavior Monitoring System via Commodity WiFi Infrastructures

Sedentary behavior (SB) has been proved to be an important risk factor for poor health, such as blood pressure and even cancer. However, existing sensor- and vision-based SB detection approaches have limitations on practical usage and privacy concerns, respectively. In this paper, we take the first attempt to develop a device-free SB monitoring and recommendation system namely CareFi, which leverages tremendous information behind WiFi signals to monitor the indoor environment and identify series of activities in SB. We deeply investigate the properties of channel state information and various activities in SB. According to different characteristics of static and dynamic activities, we design a foreground detection method to separate two categories and then adopt discriminative features of wireless signals in the frequency and time domains to recognize them. Besides, we propose an updated strategy to overcome the mutability of environment. We implement CareFi on commercial off-the-shelf WiFi routers and evaluate its performance in both office and home environments. Experimental results demonstrate the robustness and accuracy of our method.
Negative synergistic effect of SF6/N2 gas mixtures in non-uniform electric field under lightning impulse

In recent years, SF6/N2 binary mixtures have been used as insulation in second generation gas-insulated metal-enclosed transmission lines mainly because of the greenhouse effect and diseconomy of SF6. Though the synergistic effect of SF6 is known in a uniform electric field, there is little understanding of the synergistic effect phenomenon with parameters in a non-uniform electric field under standard lightning impulse. A series of experiments were designed to increase our knowledge of this and the breakdown characteristics of SF6/N2 under multiple parameters show a negative synergistic effect. Our experimental results with negative lightning impulse demonstrated that the breakdown voltage of N2 increased greater than with both SF6 and its mixtures with increasing gas pressure. When the gas pressure exceeded 0.3MPa, the breakdown voltage of pure N2 was higher than SF6/N2 gas mixtures and even exceeded the value of SF6 at 0.5MPa. A normalization coefficient h was introduced in this research to evaluate the negative synergistic effect. Under negative lightning impulse the analytical results show that the negative synergistic effect increased with the augment of gas pressure. On the other hand, the synergistic effect was reduced with decreasing gas pressure under positive polarity impulse and it appeared to be a negative synergistic effect with the enhancement of field non-uniformity. The analysis of streamer discharge propagation indicates three reasons lead to the negative synergistic effect: similar streamer corona onset voltage, different space charge effect, and dissimilar discharge form of N2 and SF6/N2 gas mixtures.
Saliency detection via PageRank and local spline regression

Abstract. A saliency detection method based on the PageRank algorithm and local spline regression (LSR) is proposed. Unlike the principles of most existing bottom-up methods, in the proposed method, saliency detection is considered a label propagation and regression problem. The input image is represented as two-scale graphs with homogeneous superpixels. Multiple color features and spatial information are effectively captured to define the relevance of each node to its surroundings. PageRank is used to assign the saliency value to each region depending on the similarity of the image elements with boundary cues. Furthermore, to comprehensively consider both foreground and background cues, a robust classifier based on LSR is employed to highlight more complete foreground regions. The integrated and refined pixel-level saliency map provides a significant performance boost in the final result. Extensive experiments on three large public datasets demonstrate that the proposed algorithm consistently achieves superior performance compared with state-of-the-art saliency models.
Protective effects of methanol extract of Plukenetia conophora seeds and 4H-Pyran-4-One 2,3-Dihydro-3,5-Dihydroxy-6-Methyl on the reproductive function of male Wistar rats treated with cadmium chloride

Objectives Male infertility caused by exposure to heavy metals is a current global issue. Exposure to cadmium chloride (CdCl2) negatively affects the male reproductive system. Many infertile people, especially in developing countries, resort to folkloric treatment. Plukenetia conophora is used in Nigerian folk medicine to promote fertility. This study investigated the effects of Plukenetia conophora (PC) and 4H-Pyran-4-One 2,3-Dihydro-3,5-Dihydroxy-6-Methyl (DDMP) on Wistar rats with cadmium chloride-induced testicular damage. Methods Forty-two male Wistar rats (150-190g) were divided into seven groups (n=6) and treated daily for 54 days as follows: Controls (normal saline); CdCl2 (2mg/kg single IP dose); CdCl2 + 200 mg/kg vitamin E; CdCl2 + 100 or 200 mg/kg PC; and CdCl2 + 25 or 50 mg/kg DDMP. The rats were sacrificed 55 days after the start of the study; Samples were collected for analysis. Biochemical parameters malondialdehyde, nitric oxide, antioxidant enzymes, and proton pumps were measured by spectrophotometry. Reproductive hormones were measured using ELISA. Data were analysed using ANOVA and differences in mean values were considered significant at p<0.05. Results Significant increases in sperm count, motility, and viability were observed in the groups given CdCl2+Vitamin E, CdCl2+PC or CdCl2+DDMP as compared with the CdCl2 group. Malondialdehyde and nitric oxide levels in the groups treated with CdCl2+PC or CdCl2+DDMP decreased significantly when compared with the group given CdCl2. Significant increases were observed in antioxidant enzymes, proton pump, and testosterone in the groups treated with CdCl2+PC or CdCl2+DDMP, respectively. Conclusion Plukenetia conophora alleviated male reproductive toxicity induced by cadmium chloride in Wistar rats. 4H-Pyran-4-One 2,3-Dihydro-3,5-Dihydroxy-6-Methyl present in Plukenetia conophora may be responsible for the ameliorative effects.
Simple-structured, subfemtosecond-resolution optical-microwave phase detector.

We demonstrate a simple all-fiber photonic phase detector that can measure the phase (timing) difference between an optical pulse train and a microwave signal with subfemtosecond resolution and -60 dB-level amplitude-to-phase conversion coefficient. It is based on passive phase biasing of a Sagnac loop by the intrinsic phase shift of a symmetric 3×3 fiber coupler. By eliminating the necessity of magneto-optic components or complex radio frequency (RF) electronics for phase biasing of the Sagnac loop, this phase detector has potential to be implemented as an integrated photonic device as well. When using this device for synchronization between a 250 MHz mode-locked Er-fiber laser and an 8 GHz microwave oscillator, the minimum residual phase noise floor reaches <-154 dBc/Hz (at 8 GHz carrier) with integrated root mean square (rms) timing jitter of 0.97 fs [1 Hz-1 MHz]. The long-term rms timing drift and frequency instability are 0.92 fs (over 5000 s) and 4×10-19 (at 10,000 s averaging time), respectively.