Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Electrical Energy Consumption of Active Ankle Prostheses with Series and Parallel Elastic Elements

With series and parallel elastic elements, considerable reductions in the mechanical peak power and energy consumption of active ankle prostheses can be obtained. Very few works, however, evaluate the electrical energy consumption of these devices. In this work, we analyze and discuss the differences between the mechanical and electrical energy consumption of these actuators. Design optimizations based on mechanical and electrical energy consumption are compared for a series elastic actuator, parallel elastic actuator and series elastic actuator with unidirectional spring. The results are then analyzed by means of torque-angle plots, power flow graphs and motor efficiency maps. The analysis highlights the impact of drivetrain inertia on the peak power and energy efficiency of the system. Moreover, interaction between the series spring and unidirectional parallel spring is identified as a potential cause of reduced actuator bandwidth. A parallel elastic actuator is found to be the most compact and energy-efficient solution overall as it makes the most efficient use of the electric motor.
Design of a fractional-order adaptive integral sliding mode controller for the trajectory tracking control of robot manipulators

In this study, trajectory tracking control of six–degrees of freedom robotic manipulator has been performed using the proposed fractional-order adaptive integral sliding mode control scheme. The proposed method is first composed by fractional-order and adaptive integral sliding mode control to achieve the finite-time convergence, chattering-free control inputs, better tracking performance and robustness for the robotic manipulator. Furthermore, an adaptive method has been utilized to evaluate and compensate the uncertain and unknown dynamics of the system without relying on the prior knowledge of the upper bounds. To illustrate the efficiency of the proposed fractional-order adaptive integral sliding mode control method, the real-time experimental studies have been performed for the six–degrees of freedom industrial robot manipulator. The experimental outcomes strongly verified that the proposed controller gives quite well trajectory tracking response and faster convergence compared with the classical integral sliding mode control under the external payload.
RichRDF: A Tool for Enriching Food, Energy, and Water Datasets with Semantically Related Facts and Images

Food, energy, and water (FEW) are the key resources to sustain human life and economic growth on Earth. While there is a plethora of information related to FEW systems online, there is a lack of reliable knowledge management tools that enable easy consumption of such information. In this paper, we present a web-based tool called RichRDF with the goal of enriching exiting FEW systems with semantically related facts and images. The main features of RichRDF include (1) an entity extraction algorithm that extracts meaningful subjects from Resource Description Framework (RDF) statements using natural language processing (NLP) techniques, (2) a reliable approach to add semantic similarity scores and relationships between different RDF subjects based on ConceptNet, (3) an efficient way to use the numbers of WordNet synsets to request the associated images from ImageNet, and (4) a user friendly interface that allows users to load and convert FEW datasets to RDF and then query the RDF datasets using an existing SPARQL engine. A video highlighting the key features of RichRDF is available at https://youtu.be/vyHgh4LgKCo .
A  $1\times8$  Linear Ultra-Wideband Phased Array With Connected Dipoles and Hyperbolic Microstrip Baluns

A <inline-formula> <tex-math notation="LaTeX">$1\times 8$ </tex-math></inline-formula> linear single polarized ultra-wideband connected dipole phased array with wide angle scan range is proposed. The dipoles in the array are connected with each other in E-plane to improve the impedance matching on the low end of the frequency band. The frequency band and the scan range in E-plane is 2~9 GHz for broadside radiation, 2~8 GHz for 30° scan, 2~7 GHz for 45° scan, and 2~6.5 GHz for 60° scan. The VSWR is better than 2.0 across the frequency band from 2 to 9 GHz for broadside radiation and the cross-polarization level is below −10 dB. A hyperbolic microstrip balun is used as an impedance transformer to connect the 50 <inline-formula> <tex-math notation="LaTeX">$\Omega $ </tex-math></inline-formula> SMA connector to a <inline-formula> <tex-math notation="LaTeX">$150~\Omega $ </tex-math></inline-formula> broadband dipole in an array. The structure of this antenna is totally planar and low profile, thus it is made easy to integrate with the PCB boards. To eliminate the surface wave blindness, no other dielectric layer is used in the array. The proposed balun supports common mode (CM) current and the radiation of this CM current cancels the radiation of the dipole in some frequency for a certain scan angle, this results in feed blindness. Adding H-plane PEC walls decreases the feed blindness frequency in the design.
Enforcing Access Control Policies over Data Stored on Untrusted Server

One of the security issues in data outsourcing scenario is the enforcement of data owner’s access control policies. This includes some challenges; namely, the number of keys required to access authorized resources, efficient policy updating, write access control enforcement, user and data owner overhead, and preserving confidentiality of data and policies. Most of the existing solutions address only some of the challenges, while they impose high overhead on both the data owner and users. Though, policy management in the Role-Based Access Control (RBAC) model is easier and more efficient due to the existence of role hierarchical structure and role inheritance; most of the existing solutions address only enforcement of policies in form of access control matrix. In this paper, we propose an approach to enforce RBAC policies on encrypted data outsourced to service provider (SP). We utilize Chinese Remainder Theorem (CRT) for key management and role/permission assignment. Efficient user revocation, support of role hierarchical structure updates, availability of authorized resources for users of newly added roles, and enforcement of write access control policies as well as static separation of duties (SSD), are of the proposed solution advantages. In addition, the ciphertext size is linearly proportional to the plaintext size, regardless of the number of roles and users.
A Robust Observer of Rotor Position and Speed for IPMSM HFI Sensorless Drives

This paper proposes a new tracking algorithm associated to high frequency (HF) signal injection techniques for sensorless control of Interior Permanent Synchronous Machine (IPMSM). The proposed strategy allows to overcome the knowledge of the machine parameters and HF signal characteristics which are the main drawbacks of the existing tracking algorithms (phase-locked loop (PLLs), mechanical system observers, inverse of tangent). Several simulation experimental results are provided to verify and to test the robustness of the proposed sensorless control method in the framework of electric propulsion used in automotive applications.
Exploratory Evaluation of the Force Myography (FMG) Signals Usage for Admittance Control of a Linear Actuator

Force Myography (FMG) is a technique involving the use of force sensors on the surface of the limb to detect the volumetric changes in the underlying musculotendinous complex. This paper investigates the feasibility of employing force-sensing resistors (FSRs) worn on the arm that measure the FMG signals for force prediction in dynamic conditions. The predicted force value can be mapped into velocity value to control a linear actuator to track hand movements. Two FMG bands were donned on the participant wrist and forearm muscle belly to measure the FMG signals during force exertion. An accurate force transducer was used for labeling the FM G signals by measuring the exerted force. Three regression algorithms including kernel ridge regression (KRR), support vector regression (SVR), and general regression neural network (G RNN), were used in this study for predicting hand force using the FMG signals. The data were collected for 200 seconds for training the regression model. Then, the trained model was used for online force prediction for 430 seconds. The testing accuracy was 0.92, 0.90 and 0.79, using KRR, SVR and GRNN, respectively. These results will be beneficial for monitoring hand force during human-robot interaction or controlling the robot movement.
Redundancy Elimination on Unidirectional Lossy Links

Redundant data transmission, which is very common in computer networks, degrades bandwidth efficiency and wastes energy. To reduce such redundancy, many redundancy elimination (RE) techniques have been proposed. Most of them require strict history synchronization between the sender and receiver, and therefore assume the existence of bidirectional links to maintain the synchronization. This paper presents MinMax, a new RE mechanism that is specially designed for unidirectional lossy links. Using an existing fingerprinting algorithm, MinMax eliminates a region of payload in an outgoing packet only when the region is common in a certain number of previous packets. Thus over a lossy link, MinMax significantly reduces decompression failures at the receiver without resorting to any forms of feedback and retransmission. Experiments on synthetic data and real-world traffic show that MinMax is able to maintain fair bandwidth savings while inducing negligible decompression failures even when the packet loss rate of the link is as high as 20%.
Dynamic bandwidth allocation in SDN based next generation virtual networks: a deterministic network calculus approach

Software-defined networking (SDN), recognized as next-generation paradigm, decouples the network control plane from the data forwarding plane for a logically centralized controller, allowing rapid networking technology innovations to serve great varieties of users' applications. SDN empowers the evolution of Internet with Open-Flow (OF) and taking advantages of Network Virtualization (NV) to provide efficient service slicing strategies. One of key research issues in both SDN and NV environments is a lack of resource scheduling mechanisms in the physical infrastructure. The resource scheduling mechanisms should be highly capable of ensuring network stability to add further benefits to SDN based next generation virtual networks. We propose a service discipline of dynamic bandwidth scheduling (DBS) within OF switches that dynamically allocates data rates to flows regarding QoS and flow dynamics. Furthermore, we formulate a coherent analysis framework of scheduling disciplines as a mathematical model based on the deterministic network calculus to provide a fast characterization of deterministic service guarantees in SDN. Finally, simulations validate derived theoretical bounds from the analysis framework and confirm that the DBS discipline guarantees QoS of all flows through dynamic bandwidth allocation and ensures an efficient allocation of system bandwidth.
Validity of the DSM‐5 anxious distress specifier for major depressive disorder

DSM‐5 introduced the anxious distress specifier in recognition of the clinical significance of anxiety in depressed patients. Recent studies that supported the validity of the specifier did not use measures that were designed to assess the criteria of the specifier but instead approximated the DSM‐5 criteria from scales that were part of an existing data base. In the present report from the Rhode Island Methods to Improve Diagnostic Assessment and Services (MIDAS) project, we examined the validity of the specifier diagnosed with a semistructured interview.
Pose Guided Deep Model for Pedestrian Attribute Recognition in Surveillance Scenarios

Recognizing pedestrian attributes, such as gender, backpack, and cloth types, has obtained increasing attention recently due to its great potential in intelligent video surveillance. Existing methods usually solve it with end-to-end multi-label deep neural networks, while the structure knowledge of pedestrian body has been little utilized. Considering that attributes have strong spatial correlations with human structures, e.g. glasses are around the head, in this paper, we introduce pedestrian body structure into this task and propose a Pose Guided Deep Model (PGDM) to improve attribute recognition. The PGDM consists of three main components: 1) coarse pose estimation which distillates the pose knowledge from a pre-trained pose estimation model, 2) body parts localization which adaptively locates informative image regions with only image-level supervision, 3) multiple features fusion which combines the part-based features for attribute recognition. In the inference stage, we fuse the part-based PGDM results with global body based results for final attribute prediction and the performance can be consistently improved. Compared with state-of-the-art models, the performances on three large-scale pedestrian attribute datasets, i.e., PETA, RAP, and PA-100K, demonstrate the effectiveness of the proposed method.
A Joint Space-Time Array for Communication Signals-Based on a Moving Platform and Performance Analysis

A joint space-time array for communication signals is constructed in this paper to settle the contradiction between the performance of angle estimation and the array aperture. It introduces Doppler information caused by platform motion into the signal processing to obtain favorable performance with limited array aperture. We analyze the theoretical performance in the aspects of distinguishable source number, spatial resolution and Cramér-Rao bound (CRB), respectively. Both theoretical analysis and simulation results demonstrate that the proposed space-time array can give rise to a significant enhancement in achievable array performance.
Receive-Beam Resource Allocation for Multiple Target Tracking With Distributed MIMO Radars

A distributed multiple-input multiple-output (MIMO) radar system is capable of tracking multiple targets under the “defocused transmit-focused receive” (DTFR) operating mode, in which each transmitter forms a completely defocused beam to illuminate the whole surveillance region and each receiver adopts a focused beam to attain a higher resolution. However, when operating in this mode, there exists a resource optimization problem on the allocation of receive-beams. To address this problem, a receive-beam resource allocation (RBRA) strategy is proposed in this paper. The key mechanism is to implement the optimal allocation between receive-beams and targets based on the feedback information in the tracking recursion cycle, with the objective of improving the worst tracking accuracy with multiple targets. Since the posterior Cramér–Rao lower bound (PCRLB) provides a lower bound on the accuracy of target state estimates, it is derived and adopted as an optimization criterion. It is shown that the optimal RBRA is a multidimensional nonconvex assignment problem that is NP-hard. We propose an efficient convex relaxation optimization to solve it. Numerical results demonstrate the superior performance of the proposed strategy in terms of the worst case tracking root mean-square errors.
Flexible Hybrid Electronics Technology Using Die-First FOWLP for High-Performance and Scalable Heterogeneous System Integration

A technological platform is established for scalable flexible hybrid electronics based on a novel fan-out wafer-level packaging (FOWLP) methodology. Small dielets are embedded in flexible substrates we call FlexTrate. These dielets can be interconnected through high-density wirings formed in wafer-level processing. We demonstrate homogeneous integration of 625 (25 by 25) 1-mm2 Si dielets and heterogeneous integration of GaAs and Si dielets with various thicknesses in a biocompatible polydimethylsiloxane (PDMS). In this paper, 8- $\mu \text{m}$ -pitch die-to-die interconnections are successfully implemented over a stress buffer layer formed on the PDMS. In addition, coplanarity between the PDMS and embedded dielets, die shift concerned in typical die-first FOWLP, and the bendability of the resulting FlexTrate are characterized.
A Biased Bayesian Inference for Decision-Making and Cognitive Control

Although classical decision-making studies have assumed that subjects behave in a Bayes-optimal way, the sub-optimality that causes biases in decision-making is currently under debate. Here, we propose a synthesis based on exponentially-biased Bayesian inference, including various decision-making and probability judgments with different bias levels. We arrange three major parameter estimation methods in a two-dimensional bias parameter space (prior and likelihood), of the biased Bayesian inference. Then, we discuss a neural implementation of the biased Bayesian inference on the basis of changes in weights in neural connections, which we regarded as a combination of leaky/unstable neural integrator and probabilistic population coding. Finally, we discuss mechanisms of cognitive control which may regulate the bias levels.
A Frequency Offset Estimation Algorithm Based on Under-Sampling for THz Communication

The frequency offset estimation algorithm for terahertz (THz) communication is not only required to deal with estimation accuracy, SNR (signal-to-noise ratio) threshold and estimation range, but also needs to take high Doppler shift caused by high operating band, the complexity of real-signal processing and large hardware cost into consideration. A carrier frequency offset estimation algorithm based on under sampling for THz communication is proposed in this paper. This algorithm utilizes methods including narrow band filtering (the bandwidth of filtered signal is only about 0.1% of the original signal bandwidth), under-sampling based on coprime sampling and second time estimation. For signal processing, we use FFT (Fast Fourier Transform) to achieve correlation operation on the frequency domain, which effectively reduce the computational complexity. The method we proposed significantly reduce the sampling rate as well as improve the estimation accuracy and thus can be applied to THz communication. The simulation results show that the algorithm can estimate a large dynamic range of the frequency offset at a low SNR with a low sampling rate, which reduce the difficulty of signal processing and hardware design.
Worker Recruitment Strategy for Self-Organized Mobile Social Crowdsensing

Mobile crowdsensing recruits a massive group of mobile workers to cooperatively finish a sensing task through their smart devices (mobile phones, ipads, etc.). In this paper, the communication in social network for delivering the sensing data of mobile crowdsensing is considered, where some requesters publish the sensing tasks to all the Point of Interests (PoIs), and the workers are recruited to take the sensing data in the PoI until they could communicate with the requester through an offline and online connection. We first use the semi-Markov model to predict the offline encounter situation. Then, the worker's utility is decided by both the offline encounter and social connection probabilities. The Worker Recruitment for Self-organized MSC (WEO) is further presented through recruiting a set of workers, who have the maximum communication probability with the requesters. We prove that the optimal recruitment problem is NP-hard, and we introduce a practical greedy heuristic method for this problem, the performance of the greedy method is also tested. Two real-world traces, roma/taxi and epfl are tested in our simulations, where WEO always achieves the highest delivery ratio of sensing tasks among different recruitment strategies.
A Coupled-Line Isolation Network for the Design of Filtering Power Dividers With Improved Isolation

A coupled-line isolation network is proposed for the design of filtering power dividers. The isolation network functions as the input coupling structures for two bandpass filters (BPFs), and meanwhile isolates the filters to realize a filtering power divider. It can be embedded into various types of BPFs to implement a variety of filtering power dividers. As demonstrated by the theoretical and experimental treatment, the isolation network provides a flexible and effective means of isolating two BPFs and achieving the isolation. Specifically, a fabricated four-pole microstrip filtering power divider achieves 25-dB isolation in the passband centered at 1.96 GHz. In addition, the measured results show that isolation better than 17 dB is achieved from dc to 20 GHz or about 10 times of the midband frequency of the BPFs.
Decreased LIN28B in preeclampsia impairs human trophoblast differentiation and migration

Preeclampsia (PE) is a common cause of maternal morbidity, characterized by impaired trophoblast invasion and spiral artery transformation resulting in progressive uteroplacental hypoxia. Given the primary role of LIN28A and LIN28B in modulating cell metabolism, differentiation, and invasion, we hypothesized that LIN28A and/or LIN28B regulates trophoblast differentiation and invasion, and that its dysregulation may contribute to PE. Here we show that LIN28B is expressed ∼1300‐fold higher than LIN28A in human term placenta and is the predominant paralog expressed in primary human trophoblast cultures. The expression of LIN28B mRNA and protein levels are significantly reduced in gestational age–matched preeclamptic vs. normal placentas, whereas LIN28A expression is not different. First trimester human placental sections displayed stronger LIN28B immunoreactivity in extravillous (invasive) cytotrophoblasts and syncytial sprouts vs. villous trophoblasts. LIN28B overexpression increased HTR8 cell proliferation, migration, and invasion, whereas LIN28B knockdown in JEG3 cells reduced cell proliferation. Moreover, LIN28B knockdown in JEG3 cells suppressed syncytin 1 (SYN‐1), apelin receptor early endogenous ligand (ELABELA), and the chromosome 19 microRNA cluster, and increased mRNA expression of ITGp4and TNF‐α. Incubation of BeWo and JEG3 cells under hypoxia significantly decreased expression of LIN28B and LIN28A, SYN‐1, and ELABELA, whereas TNF‐α is increased. These results provide the first evidence that LIN28B is the predominant paralog in human placenta and that decreased LIN28B may play a role in PE by reducing trophoblast invasion and syncytialization, and by promoting inflammation. —Canfield, J., Arlier, S. , Mong, E. F. , Lockhart, J., Vanwye, J., Guzeloglu‐Kayisli, O. , Schatz, F. , Magness, R. R. , Lockwood, C. J., Tsibris, J. C. M. , Kayisli, U. A. , Totary‐Jain, H. Decreased LIN28B in preeclampsia impairs human trophoblast differentiation and migration. FASEB J. 33, 2759–2769 (2019). www.fasebj. org
CHL1 expression differentiates Hürthle cell carcinoma from benign Hürthle cell nodules

Hürthle cell carcinoma (HCC) is an unusual and relatively rare type of differentiated thyroid cancer. Currently, cytologic analysis of fine‐needle aspiration biopsy is limited in distinguishing benign Hürthle cell neoplasms from malignant ones. The aim of this study was to determine whether differences in the expression of specific genes could differentiate HCC from benign Hürthle cell nodules by evaluating differential gene expression in Hürthle cell disease.