Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Evaluation of a Knee Support Exoskeleton using Variable Non-Active Interval for Energy Storage

This paper describes the design and the experimental testing of a knee exoskeleton with variable non-active interval (NAI) specifically designed to fit the human gait. This exoskeleton is designed to provide support at the knee joint by supplying assistive torque around the knee in order to reduce the maximum muscular effort required to perform daily activities such as walking and squat lifting, thus, enabling users like elderly people to continue those activities longer. The main mechanism of the exoskeleton behaves like a torsion spring with a variable NAI. The torque provided by the mechanism outside the NAI is quasi-linear with respect to the angle variation. The position of this NAI can be modified to disable the mechanism. Moreover, the angular stiffness of the mechanism can be modified to adapt the magnitude of the support to the user. Experimental evaluation was conducted in two phases: during the first one, the NAI was tested for following the walking pattern of the user, in order to avoid disturbing the user's gait. During the second one, the performance of the support provided by the device was measured by the muscle activity during squatting series. The results show the ability to modify the position of the NAI and a decrease of the maximum muscle activity during squatting while wearing the device, concluding that the exoskeleton could assist the knee joint although further evaluation is required to establish the whole support in the gait cycle.
A SiGe Highly Integrated FMCW Transmitter Module With a 59.5–70.5-GHz Single Sweep Cover

A fully integrated wide-bandwidth transmitter (TX) module intended for use in short-range frequency-modulated continuous-wave radar applications is proposed. By incorporating an on-chip fractional-<inline-formula> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> phase-locked loop based on the fundamental voltage-controlled oscillator, the TX is able to synthesize highly programmable 11-GHz linear chirps around the 65-GHz central frequency, hence theoretically enabling sub-1.5-cm spatial resolutions. Implemented in a 0.13-<inline-formula> <tex-math notation="LaTeX">$\mu \text {m}$ </tex-math></inline-formula> BiCMOS process, the test-chip delivers more than +5 dBm of output power and achieves the measured root-mean-square ramp error (nonlinearity) of 340 kHz for a 60-GHz/ms modulation rate signal over the complete range of interest. The presented TX module dissipates 550mW and also includes an adequate on-board directional <inline-formula> <tex-math notation="LaTeX">$4\times4$ </tex-math></inline-formula> antenna array.
Therapeutic effect of berberine on renal ischemia-reperfusion injury in rats and its effect on Bax and Bcl-2

This study aimed to investigate the therapeutic effect of berberine on renal ischemia-reperfusion injury in rats and its effect on Bax and Bcl-2. Sixty adult SD rats were randomly divided into four groups: control group A, renal ischemia-reperfusion group B, berberine group C and berberine + exendin-(9–39) treatment group D. In group A, right kidney was resected and left renal pedicle was separated, but left renal artery was not blocked. Renal ischemia-reperfusion model was established in other groups. Rats in group C were not subjected to any treatment after model construction. Rats in group C and D were subjected to intraperitoneal injection of berberine 7 days before the experiment. Besides that, intraperitoneal injection of exendin-(9–39) was performed at day 1 and 4 after model construction. Automatic biochemical analyzer was used to measure serum creatinine (SCr) and blood urea nitrogen (BUN). Malondialdehyde (MDA) in renal cortex was measured by enzyme-linked immunosorbent assay and contents of Bax and Bcl-2 in renal tissue were measured by western blot analysis. Apoptosis of rat renal cells was detected by TUNEL assay. The results showed that levels of SCr, BUN, MDA and Bax were significantly higher in group B than in other groups (P<0.05). Levels of Bcl-2 in group B were significantly higher than those in group A but significantly lower than those in group C and D. Compared with group A, apoptosis of renal cells was more severe in group B. Compared with group B, apoptosis of renal cells was significantly improved in group C and D, but was still more severe than that in group A. In conclusion, berberine can effectively improve renal function in rats with renal ischemia-reperfusion injury by inhibiting Bax expression and promoting Bcl-2 expression.
Fault-Tolerant Control of a Hexacopter UAV based on Self-Scheduled Control Allocation

In this paper, a control allocation (CA) algorithm for the fault-tolerant control (FTC) system of a multirotor unmanned aerial vehicle (UAV) is presented. The proposed CA design is based on gain-scheduling control in the framework of structured ${\cal H}_{\infty }$ synthesis. Given the appropriate fault detection and diagnosis (FDD) system, allocation laws are parameterized as polynomial functions of actuators effectiveness levels. The polynomial coefficients are then tuned with Matlab-based function systune to meet the robustness and fault tolerance requirements. Unlike conventional CA schemes in the literature, the proposed method has the advantage of not solving any online optimization problem. Moreover, actuator constraints after a failure are also taken into account during the tuning process using a multi-model approach. In comparison with other FTC systems based on reconfigurable controller, this smooth self-scheduled CA has a very simple structure and allows one to avoid undesirable transient phenomena during the controller reconfiguration process. High fidelity simulations and experimental results performed on a hexacopter show the effectiveness and robustness of the proposed FTC in accommodating different levels of actuator degradation.
Labeled PSI from Fully Homomorphic Encryption with Malicious Security

Private Set Intersection (PSI) allows two parties, the sender and the receiver, to compute the intersection of their private sets without revealing extra information to each other. We are interested in the unbalanced PSI setting, where (1) the receiver's set is significantly smaller than the sender's, and (2) the receiver (with the smaller set) has a low-power device. Also, in a Labeled PSI setting, the sender holds a label per each item in its set, and the receiver obtains the labels from the items in the intersection. We build upon the unbalanced PSI protocol of Chen, Laine, and Rindal (CCS~2017) in several ways: we add efficient support for arbitrary length items, we construct and implement an unbalanced Labeled PSI protocol with small communication complexity, and also strengthen the security model using Oblivious Pseudo-Random Function (OPRF) in a pre-processing phase. Our protocols outperform previous ones: for an intersection of 220 and $512$ size sets of arbitrary length items our protocol has a total online running time of just $1$~second (single thread), and a total communication cost of 4 MB. For a larger example, an intersection of 228 and 1024 size sets of arbitrary length items has an online running time of $12$ seconds (multi-threaded), with less than 18 MB of total communication.
Predictors of cognitive stability or decline during aging: A longitudinal study in primary care

Abstract We aimed to identify the early predictors of cognitive decline, and primary care physicians’ (PCP) ability to diagnose cognitively impaired subjects, in a cohort of individuals recruited in primary care centers. Independent adults, aged ≥50 years at inception, with an overall low level of education, undertook a prospective clinical and cognitive evaluation targeting memory, attention and executive functions. At follow-up subjects were classified as cognitively normal (CN) or impaired (CI). Of 275 subjects (70.4 ± 8.3 years old, 176 females, 7.5 ± 4.4 education, 162 with MRI), 31 (11.2%) presented CI 4.9 years later, the majority (64.5%) presenting subjective cognitive complaints. PCP could correctly identify 40% of CI individuals, particularly if they presented current cognitive complaints. Male sex (OR = 3.117; CI95%: 1.007–9.645), age (OR = 1.063; CI95%: 1.004–1.126) and baseline scores on TMT-B (OR = 0.225; CI95%: 0.073–0.688) and Vocabulary (OR = 0.940; 95% CI: 0.894–0.986) predicted CI. This study shows that measures indicating poor cognitive reserve and low executive performance (as shown by low vocabulary and executive test scores, respectively) can be early indicators of the risk of decline, stressing the role of cognitive assessment as part of prevention/early intervention programs. The results also underline the need to help PCP to improve the detection of subjects with cognitive decline.
Digital Urban Sensing: A Multi-layered Approach

Studies of human mobility increasingly rely on digital sensing, the large-scale recording of human activity facilitated by digital technologies. Questions of variability and population representativity, however, in patterns seen from these sources, remain major challenges for interpreting any outcomes gleaned from these records. The present research explores these questions by providing a comparison of the spatial and temporal activity distributions seen from taxi, subway and Citi Bike trips, mobile app records, geo-tagged Twitter data as well as 311 service requests in the five boroughs of New York City. The comparison reveals substantially different spatial and temporal patterns amongst these datasets, emphasizing limitations in the capacity of individual datasets to represent urban dynamics in their entirety. We further provide interpretations on these differences by decomposing the spatial distributions with working-residential balance and different propensities for demographic groups to use different activities. Nevertheless, the differences also highlight the opportunity to leverage the plurality to create multi-layered models of urban dynamics. We demonstrate the capacity of such models to advance urban zoning and socio-economic modeling - two common applications of digital urban sensing.
Malicious Entities are in Vain: Preserving Privacy in Publish and Subscribe Systems

Publish and subscribe (pub/sub) system is a decoupled communication paradigm that allows routing of publications. Through a set of dedicated third party servers, referred to as brokers, publications are disseminated without establishing any link between publishers and subscribers. However, the involvement of these brokers raises security and privacy issues as they can harvest sensitive data about subscribers. Furthermore, a malicious broker may collude with malicious subscribers and/or publishers to infer subscribers' interests. Our solution is such that subscribers' interests are not revealed to curious brokers and published data can only be accessed by the authorised subscribers. Moreover, the proposed protocol is secure against the collusion attacks between malicious brokers, publishers, and subscribers.
A Systematic Literature Review of Requirements Volatility Prediction

Requirements volatility is a crucial risk factor in software projects as it directly results in cost and time overruns. Accurately predicting requirements volatility is important for better project management. This paper presents a systematic literature review that focuses on the prediction of the requirements volatility. This literature review aims to answer four research questions: 1) how is requirements volatility prediction applied to different software development methods? 2) What are the machine learning algorithms used to predict requirements volatility in software development? 3) What are the attributes (predictors) used to predict requirements volatility in software development? 4) What are the performance metrics for evaluating existing prediction models? This study presents predictors used in the literature and their performances.
Ferulic acid ameliorated placental inflammation and apoptosis in rat with preeclampsia

ABSTRACT Preeclampsia (PE) occurs specifically during pregnancy characterized by new-onset hypertension. The pathogenesis of PE was complicated, and inflammation may be central to the pathogenesis of PE. Ferulic acid (FA) is recognized to prevent cell damage and apoptosis induced by oxidative stress and inflammation. In our study, we used NG-nitro-l-arginine methyl ester (L-NAME)-induced rat model of PE to investigate whether FA improved PE and its possible mechanism. We found that FA significantly reduced blood pressure, urine volume, and urinary protein level in rats with PE. Meanwhile, FA decreased L-NAME induced higher expression of circulating TNF-α、IL-6、IL-1β and PlGF, it reduced placental TNF-α and NF-κB p65. Furthermore, FA rescued L-NAME induced decreasing expression of IL-4 and IL-10 expression in the circulation and placenta of rats. FA also ameliorated placental apoptosis in L-NAME induced rats by increasing Bcl-2 whereas decreasing Bax expression in placenta. It suggested FA as a potential candidate for the treatment of various disorders including L-NAME induced preeclampsia in rats through decreasing placental inflammation and apoptosis.
Prognostic Factors Analysis for Colon Cancer with Lymph Node Negative.

PURPOSE The analysis of high risk relapse prognosis factors and their importance regarding recurrence risk for stage I and II colon cancer, according to TNM classification 8th edition, 2017. MATERIAL AND METHOD We performed a retrospective analysis regarding the impact of prognosis factors for patients with high recurrence risk in stages I and II. We studied 99 patients with T2, T3 and T4 tumors who suffered a curative resection and whom may or may not present indication for adjuvant chemotherapy according to histoprognostic factors and molecular biomarkers. Results: We performed a univariate Cox regression which highlighted that male sex is a risk factor for disease relapse (HR=5.53, p 0.05, IC95% = 1.29 to 23.73). Although with a low statistical significance effect, T4 tumors seems to be associated with a poor prognosis regarding disease relapse (HR = 2.56, p = 0.06, IC95% = 0.94 to 6.99) compared to T2 and T3 tumors. Patients with d'MMR (MSI-H) seem to have a more favorable evolution compared to patients with p'MMR (MSS/MSI-L) - HR (d'MMR vs p'MMR) = 0.19, IC95% = 0.02 to 1.61, p = 0.13. Conclusions: We believe that it would be useful for MSS / MSI to be systematically analyzed, our data suggesting a better response of d`MMR patients to adjuvant chemotherapy. The multivariate Cox regression did not identify independent risk factors of relapse.
Supervised Committee of Convolutional Neural Networks in Automated Facial Expression Analysis

Automated emotion recognition from facial images is an unsolved problem in computer vision. Although recent methods achieve close to human accuracy in controlled scenarios, the recognition of emotions in the wild remains a challenging problem. Recent advances in Deep learning have supposed a significant breakthrough in many computer vision tasks, including facial expression analysis. Particularly, the use of Deep Convolutional Neural Networks has attained the best results in the recent public challenges. The current state-of-the-art algorithms suggest that the use of ensembles of CNNs can outperform individual CNN classifiers. Two key considerations influence these results: (i) The design of CNNs involves the adjustment of parameters that allow diversity and complementarity in the partial classification results, and (ii) the final classification rule that assembles the result of the committee. In this paper we propose to improve the assembling of the committee by introducing supervised learning on the ensemble computation. We train a CNN on the posterior-class probabilities resulting from the individual members allowing to capture non-linear dependencies among committee members, and to learn this combination from data. The validation shows an accuracy 5 percent higher with respect to previous state-of-the art results based on averaging classifiers, and 4 percent to the majority voting rule.
An Object Detection Method Based on the Joint Feature of the H-S Color Descriptor and the SIFT Feature

Object detection base on pattern feature is an important approach of object recognition. In this paper, we proposed a joint feature consisted of the chromatic feature and the structural feature. First the sift feature of the pattern is adapted to express the structural feature, it has the same invariance with the sift vector. Second we utilize the correlations of the points in sift vector to resolve the match region in patterns. Then the hue-saturation histogram of match region is calculated, and applied to be the color descriptor (denoted as H-S color descriptor) of the match region in our detection method. It is robust and invariant of rotation, scale and transformation. Experiments indicates that our approach has fast speed and high accuracy in our private ceramic datasets.
Polygenic risk score for predicting weight loss after bariatric surgery.

BACKGROUND The extent of weight loss among patients undergoing bariatric surgery is highly variable. Herein, we tested the contribution of genetic background to such interindividual variability after biliopancreatic diversion with duodenal switch. METHODS Percentage of excess body weight loss (%EBWL) was monitored in 865 patients over a period of 48 months after bariatric surgery, and two polygenic risk scores were constructed with 186 and 11 (PRS186 and PRS11) single nucleotide polymorphisms previously associated with body mass index (BMI). RESULTS The accuracy of the %EBWL logistic prediction model - including initial BMI, age, sex, and surgery modality, and assessed as the area under the receiver operating characteristics (ROC) curve adjusted for optimism (AUCadj = 0.867) - significantly increased after the inclusion of PRS186 (ΔAUCadj = 0.021; 95% CI of the difference [95% CIdiff] = 0.005-0.038) but not PRS11 (ΔAUCadj= 0.008; 95% CIdiff= -0.003-0.019). The overall fit of the longitudinal linear mixed model for %EBWL showed a significant increase after addition of PRS186 (-2 log-likelihood = 12.3; P = 0.002) and PRS11 (-2 log-likelihood = 9.9; P = 0.007). A significant interaction with postsurgery time was found for PRS186 (β = -0.003; P = 0.008) and PRS11 (β = -0.008; P = 0.03). The inclusion of PRS186 and PRS11 in the model improved the cost-effectiveness of bariatric surgery by reducing the percentage of false negatives from 20.4% to 10.9% and 10.2%, respectively. CONCLUSION These results revealed that genetic background has a significant impact on weight loss after biliopancreatic diversion with duodenal switch. Likewise, the improvement in weight loss prediction after addition of polygenic risk scores is cost-effective, suggesting that genetic testing could potentially be used in the presurgical assessment of patients with severe obesity. FUNDING Heart and Stroke Foundation of Canada (G-17-0016627) and Canada Research Chair in Genomics Applied to Nutrition and Metabolic Health (no. 950-231-580).
Provably Secure Password Reset Protocol: Model, Definition, and Construction

Many online services adopt a password-based user authentication system because of its usability. However, several problems have been pointed out on it, and one of the well-known problems is that a user forgets his/her password and cannot login the services. To solve this problem, most online services support a backup authentication mechanism with which a user can reset a password. However, negative facts about security have been reported for a popular backup authentication mechanism. In this paper, we consider a provable security treatment for a password reset protocol. First, we formalize a model and security definitions. We consider security against active adversaries that can mount man-in-the-middle attacks and concurrent attacks. Then we propose a generic construction of a password reset protocol secure under our definitions based on pseudorandom functions and public key encryption. In addition, we implement a prototype of our protocol to evaluate its efficiency.
Energy-Efficient Task Execution for Application as a General Topology in Mobile Cloud Computing

Mobile cloud computing has been proposed as an effective solution to augment the capabilities of resource-poor mobile devices. In this paper, we investigate energy-efficient collaborative task execution to reduce the energy consumption on mobile devices. We model a mobile application as a general topology, consisting of a set of fine-grained tasks. Each task within the application can be either executed on the mobile device or on the cloud. We aim to find out the execution decision for each task to minimize the energy consumption on the mobile device while meeting a delay deadline. We formulate the collaborative task execution as a delay-constrained workflow scheduling problem. We leverage the partial critical path analysis for the workflow scheduling; for each path, we schedule the tasks using two algorithms based on different cases. For the special case without execution restriction, we adopt one-climb policy to obtain the solution. For the general case where there are some tasks that must be executed either on the mobile device or on the cloud, we adopt Lagrange Relaxation based Aggregated Cost (LARAC) algorithm to obtain the solution. We show by simulation that the collaborative task execution is more energy-efficient than local execution and remote execution.
A User-Oriented Approach toward Price Prediction for IaaS Service

With the continuous development of cloud services, the types and the number of services have increased significantly. It has become the current focus on how to find a service to meet their needs in cloud market. However in cloud market, the difficult is that how to maximize the benefit of users and make users understand the reasonable pricing of their services. So this paper proposes a method based on the ARIMA (Autoregressive Integrated Moving Average Model) model to predict the future price of the cloud service, and choose the service is used ontology collaborative filtering algorithm. Finally, we take the cloud service of infrastructure as a service (IaaS) as an example to do experiment. The experimental results show our approach can find the optimal service price accuracy. This will make it possible to provide more accuracy service to user.
Human Pose Estimation Based on Deep Neural Network

This paper aimed to single pose estimation of two-dimensional image based on the deep neural network. We constructed a Stacked Hourglass network structure on the training data set, regress the precise pixel location of human body joint point through heat map with different activation function is analyzed and compared, which had certain reference value to the improvement on the final performance. At the same time, this paper analyzes the theory and application of multi-scale and analyzes the structure and advantages of network.
Wideband Compact Comb-Line Antenna Array for 79 GHz Automotive Radar Applications

A wideband microstrip comb-line antenna array is developed for 79 GHz multiple-input–multiple-output radar applications. This array is composed of four radiating subarrays, with 180° phase shift. This topology leads to a more stable radiation pattern behavior and broadside gain flatness along the frequency bandwidth. The antenna is taped out with a new high-resolution multilayer printed circuit board (PCB) technology, called “any-layer PCB. ” This technology provides the possibility to stack small microvias, instead of using thick machine-drilled vias. A measured impedance and gain bandwidth of 12.5% is achieved. The sidelobe suppression is higher than 15 dB, and the array gain is 12.36 dBi at 79 GHz.