Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Obstructive Sleep Apnea on the Cardiovascular Variability

Sleep apnea is a serious medical condition that influence millions of adults and children in the United States. It is unknown whether or not sleep apnea can cause any abnormalities in cardiovascular variability in patients with no cardiovascular disease. In this study, we investigated new cardiovascular variables which correspond with obstructive sleep apnea. The power spectrum of the electrocardiogram signal (ECG) was studied in healthy aged-matched adults $\boldsymbol{(\mathrm{n}=15)}$ and patients diagnosed with moderate obstructive sleep apnea $\boldsymbol{(\mathrm{n}=15)}$. The power spectral analysis was divided into three main frequency bands: very low frequency $\boldsymbol{(0.0033\sim 0.04\mathrm{Hz})}$; low frequency $\boldsymbol{(0.04\sim 0.15\ \mathrm{Hz})}$; and high frequency $\boldsymbol{(0.15\sim 0.4\mathrm{Hz})}$. Frequency domain analysis revealed that the very low frequency component of the ECG signal was increased in obstructive sleep apnea patients during episodes of obstructive sleep apnea, whereas other frequencies (low and high frequency) showed no significant changes. This new cardiovascular variable can be used as a new important feature in any comprehensive obstructive sleep apnea prediction model (to increase the accuracy of the model) or in any other noninvasive approaches for diagnosing or monitoring obstructive sleep apnea at home.
Signal Pre-Equalization in a Silicon Photomultiplier-Based Optical OFDM System

In this article, the performance of a new time domain signal pre-equalization method for use with optical orthogonal frequency division multiplexing (OFDM) and a silicon photomultiplier (SiPM) based receiver is studied. A SiPM contains a large array of microcells and each microcell is able to detect single photons. Therefore, a SiPM can be used to create arguably the most sensitive optical receiver, which can detect light intensity signals by counting the number of arriving photons within each signal sampling period. However, each photon detection triggers an avalanche-and-quenching process and the related microcell becomes inactive for a recovery time of several nanoseconds. Consequently, any photons arriving during this period cannot be detected. This effect can cause a non-linear distortion of the received signal and, when the OFDM sampling period is short, also introduces interference between signal samples. In this article, a new signal pre-equalization method is specifically designed to compensate for the impact of the finite recovery time. In this method, the number of active microcells during the transmission of each OFDM signal sample is first estimated. Then, the amplitude of the time domain signal sample is pre-adjusted based on the predicted fraction of microcells that are active. Using this approach, the negative impacts of the recovery time of the microcells are significantly reduced. The results that are presented show that when this new form of pre-equalization is used the bit error rate (BER) performance of the system is improved for a wide range of irradiance levels.
Operational Space Formulation and Inverse Kinematics for an Arm Exoskeleton with Scapula Rotation

The operational space of an 8-axis arm exoskeleton is partitioned into "tasks" based on the human arm motion, and a task priority approach is implemented to perform the inverse kinematics. The tasks are prioritized in the event that singularities or other constraints such as joint limits render the full desired operational space infeasible. The task reconstruction method is used to circumvent singularities in a deterministic manner so that the arm is never physically in a singular configuration. This is especially advantageous when the arm is fully extended because it allows the hand to move smoothly along the workspace boundary. The task priority inverse kinematics approach is also more computationally efficient than full Jacobian inverse methods and naturally manages the motion of the arm in a more anthropomorphic-friendly manner. The new methodology is demonstrated with four operational tasks on the MGA Exoskeleton.
Broadband and High-Gain Circularly Polarized Antenna by Using EBG Structures

A broadband and high-gain circularly polarized antenna based on electromagnetic band gap (EBG) structures is proposed by analyzing the influence of EBG layouts on antenna performances. Compared with the reference circularly polarized antenna, the impedance bandwidth, the axial ratio bandwidth and the broadside gain of the proposed EBG antenna are significantly improved. In addition, the method of optimizing the layout of EBG structures provides a general strategy for designing broadband and high-gain EBG antenna.
Geometric Sequence Technique for Effective RTO Estimation in CoAP

Internet of Things (IoT) is a network where physical objects with Internet connectivity can interact and exchange information with other connected objects. IoT devices are constrained in terms of power and memory, and have limited communication capabilities. The Constrained Application Protocol (CoAP) is a lightweight messaging protocol which is widely used by various IoT applications in low power and lossy wireless networks. CoAP provides reliability and minimal congestion control via a fixed Retransmission TimeOut (RTO) and Binary Exponential Backoff (BEB). It does not maintain end-to-end connection information and therefore, cannot adapt RTO based on the network conditions. Moreover, CoAP resets the RTO to its default value after having received the ACK for the retransmitted packet. This approach of resetting the RTO degrades the performance in a network with high latency and leads to spurious retransmissions. In this paper, we propose a Geometric Sequence Technique (GST) for effective RTO estimation in CoAP. GST retains the previous RTO value after having received the ACK for the retransmitted packet and eventually returns to the default value by decreasing the RTO depending on the number of consecutive successful transmissions. The proposed technique is implemented in Contiki OS and validated against the existing mechanisms. The experiments have been conducted using the Cooja simulator and the FIT/IoT-LAB testbed to verify the effectiveness of the proposed technique. The results show that GST minimizes the Flow Completion Times (FCT), reduces the number retransmissions and improves the network throughput.
Predicting the human behaviour in human-robot co-assemblies: an approach based on suffix trees

Prediction of the human behaviour is essential for allowing an efficient human-robot collaboration. This was confirmed recently showing how scheduling approaches can significantly increase the productivity of a robotic cell by planning the robotic actions in a way as much as possible compliant with the human predicted behaviour. This work proposes an innovative approach for human activity prediction, exploiting both a-priori information and knowledge revealed during operation. The resulting approach is proved to achieve good performance through both off-line simulated sequences and in a realistic co-assembly involving a human operator and a dual arm collaborative robot.
On the use of (lockable) parallel elasticity in active prosthetic ankles

New challenges arise when investigating the use of active prostheses for lower limb replacement, such as high motor power requirements, leading to increased weight and reduced autonomy. Series and parallel elasticity are often explored to reduce the necessary motor power but often the effect on the energy consumption of the prosthesis is not directly investigated, as the mechanical power properties are examined yet the motor and gearbox dynamics and efficiencies are not considered. This paper presents the investigation of a parallel elasticity compared to a series elastic actuation system used in an active ankle prosthesis. Using a matched electromechanical model of the actuator shows that the electrical efficiency can be influenced using parallel elasticity. The optimal configuration depends on the motor characteristics (dynamic behavior) and limitations, which should always be taken into account when designing optimal series and parallel springs. It has been shown that adding parallel elasticity allows to reduce the required gear ratio and thus associated friction and inertial losses. Allowing the parallel elasticity to be lockable can further influence the behavior and allow for a more versatile actuator.
Test Reduction for Power Density Emitted by Handset mmWave Antenna Arrays

The exposure to electromagnetic field (EMF) from phased antenna arrays integrated into wireless devices operating at the millimeter-wave (mmWave) part of the spectrum should be evaluated in terms of power density (PD). Two aspects related to test reduction when evaluating the radiation from handset antenna arrays are considered. First, the peak PD decay with the distance from 4-elements antenna arrays is analyzed. The focus is on finding the size of the volume around the handset beyond which the PD is so low that its measurement can be omitted. By limiting the measurements to the inside of the exposed volume, the total test time is reduced. Antenna configurations that are representative for current trends in handset technology are chosen: arrays of half-wavelength dipoles and patches operating at 26 GHz, 28 GHz, and 39 GHz, and having inter-element spacing either <inline-formula> <tex-math notation="LaTeX">$0.5\lambda $ </tex-math></inline-formula> or <inline-formula> <tex-math notation="LaTeX">$0.9\lambda $ </tex-math></inline-formula>. The second investigation aims to determine the critical distance between two 4-elements phased arrays for which the peak PD when the two arrays operate simultaneously is similar to the peak PD when only one array operates at the time. The study shows the configurations for which the number of tests can be reduced while having sufficiently accurate results.
A Novel Inverse Kinematics Method for Upper-Limb Exoskeleton under Joint Coordination Constraints

In this study, we address the inverse kinematics problem for an upper-limb exoskeleton by presenting a novel method that guarantees the satisfaction of joint-space constraints, and solves closed-chain mechanisms in a serial robot configuration. Starting from the conventional differential kinematics method based on the inversion of the Jacobian matrix, we describe and test two improved algorithms based on the Projected-Gradient method, that take into account joint-space equality constraints. We use the Harmony exoskeleton as a platform to demonstrate the method. Specifically, we address the joint constraints that the robot maintains in order to match anatomical shoulder movement and the closed-chain mechanisms used for the robot’s joint control. Results show good performances of the proposed algorithms, which are confirmed by the ability of the robot to follow the desired task-space trajectory while ensuring the fulfilment of joint-space constraints, with a maximum error of about 0.05 degrees.
Observer-Based Disturbance Control for Small-Scale Collaborative Robotics

Collaborative robotics allows merging the best capabilities of humans and robots to perform complex tasks. This allows the user to interact with remote and directly inaccessible environments such as the micro-scale world. This interaction is made possible by the bidirectional exchange of information (displacement - force) between the user and the environment through a haptic interface. The effectiveness of the human/robot interaction is highly dependent on how the human feels the forces. This is a key point to enable humans to make the right decisions in a collaborative task. This paper discusses the design of a dynamic observer to estimate the forces applied by a human operator on a class of parallel pantograph-type haptic interfaces used to control small-scale robotic systems. The objective is to reject disturbances in order to improve the human force perception capability over a wide frequency range. A dynamic pantograph model is proposed and experimentally validated. The observer is designed on the basis of the proposed dynamic model and its efficiency in estimating the applied human force is demonstrated for the first time with pantograph-type interfaces. Experimental validation first shows the effectiveness of the perturbation observer for external human force estimation with a response time of less than 0.2 s and a mean error of less than 7 mN and then the effectiveness of the controller in improving the quality of human sensation of forces down to 10 mN.
Group based Publisher-Subscriber Communication Primitives for ndnSIM

Named Data Networking (NDN), an information centric network architecture, aims to provide an efficient and scalable alternative for content distribution. Modern Internet applications have more emphasis on data, and are less concerned about the location from where data is retrieved. NDN’s communication primitives being strictly pull based help in bringing this focus shift from location of data to the data itself. A concern for NDN is to enable the support of other popular communication primitives, such as the Publisher-Subscriber (Pub-Sub) model, seamlessly. The Pub-Sub model is well suited for applications that require periodic retrieval of data or event triggered data, such as in Industrial Automation Control Systems (IACS). This paper presents the design and development of a model to support the group based Pub-Sub communication primitives in ndnSIM, a popular ns-3 based network simulator for NDN. The functionality of the proposed model is tested by developing an end-to-end simulation environment in ndnSIM that is representative of the popular use cases of Pub-Sub communication primitives.
Towards General Infeasibility Proofs in Motion Planning*

We present a general approach for constructing proofs of motion planning infeasibility. Effective high-dimensional motion planners, such as sampling-based methods, are limited to probabilistic completeness, so when no plan exists, these planners either do not terminate or can only run until a timeout. We address this completeness challenge by augmenting a sampling-based planner with a method to create an infeasibility proof in conjunction with building the search tree. An infeasibility proof is a closed polytope that separates the start and goal into disconnected components of the free configuration space. We identify possible facets of the polytope via a nonlinear optimization procedure using sampled points in the non-free configuration space. We identify the set of facets forming the separating polytope via a linear constraint satisfaction problem. This proof construction is valid for general (i.e., non-Cartesian) configuration spaces. We demonstrate this approach on the low-dimensional Jaco manipulator and discuss engineering approaches to scale to higher dimensional spaces.
Organic carbon additions: effects on soil bio‐physical and physico‐chemical properties

The effects of organic carbon (OC) additions from farm manures and crop residues on selected soil bio‐physical and physico‐chemical properties were measured at seven experimental sites, on contrasting soil types, with a history of repeated applications of farm manure or differential rates of inorganic fertilizer nitrogen (N). Repeated (> 7 years annual additions) and relatively large OC inputs (up to 65 t OC ha−1) were needed to produce measurable changes in soil properties, particularly physical properties. However, over all the study sites, there was a positive relationship between OC inputs and changes in total soil OC and ‘light’ fraction OC (LFOC), with LFOC providing a more sensitive indicator of changes in soil organic matter status. Total soil OC increased by an average of 3% for every 10 t ha−1 manure OC applied, whereas LFOC increased by c. 14%. The measured soil OC increases were equivalent to c. 23% of the manure OC applied (up to 65 t OC ha−1 applied over 9 years) and c. 22% of the crop residue OC applied (up to 32 t OC ha−1 over 23 years). The manure OC inputs (but not crop residue OC inputs) increased topsoil porosity and plant available water capacity, and decreased bulk density by 0.6%, 2.5% and 0.5% with every 10 t ha−1 manure OC applied, respectively. Both OC sources increased the size of the microbial biomass (11% increase in biomass C with 10 t OC ha−1 input), but only manure OC increased its activity (16% increase in the soil respiration rate with 10 t OC ha−1 input). Likewise, the potentially mineralizable N pool only increased with manure N inputs (14% increase with 1 t manure total N ha−1). However, these soil quality benefits need to be balanced with any potential environmental impacts, such as excessive nutrient accumulation, increased nitrate leaching and phosphorus losses and gaseous emissions to the atmosphere.
Online Spatio-Temporal Action Detection in Long-Distance Imaging Affected by the Atmosphere

Current state-of-the-art approaches for spatio-temporal action detection deal with stable videos and quite sterilized environments, as seen in the UCF-101 benchmark. In addition, the objects of interest are typically relatively close to the camera, and therefore fairly clear and easily distinguished. This study presents an approach method for online human action detection in long-distance imaging affected by atmospheric distortions. We created a unique dataset of typical actions in long-range imaging. Various CNN frameworks were examined for the initial moving object detection phase, including 2D, 3D, one stream, and two-stream (RGB frames and optical flow). The basic object detection methods examined within these frameworks include the YOLOv3 and an extension of the inflated 3D ConvNet with a Feature-Fused Single Shot Multibox Detector (FFSSD) to improve small object detection. To cope with the harmful effect of the spatio-temporal random movements induced by atmospheric effects on motion estimation, we first fit the optical flow stream characteristics to a temporally noisy turbulent environment. A significant improvement of the action detection quality under such noisy conditions was obtained by constructing an online tracking algorithm that incrementally constructs and labels the objects’ tracks from the network’s frame-level detections. Experimental results show that our approach outperforms the state-of-the-art on our dataset in terms of the mAP measure.
Practical Secure Two-Party EdDSA Signature Generation with Key Protection and Applications in Cryptocurrency

In cryptocurrency and blockchain-based distributed ledgers, transfer of money (digital coins) can be presented as a transaction. Due to the irreversibility nature of blockchain transactions, a single fraudulent use of private key (used to sign transactions) could have significant consequences (e.g. financial loss). Key protection alone is not adequate in protecting cryp-tocurrencies, and threshold signature is a viable method to avoid fraudulent key usage or key theft. In this paper, we focus on the Edwards-curve digital security algorithm (EdDSA), which has been applied in several cryptocurrencies (e.g. Cardano, Zcash, and Decred) and design the first efficient two-party EdDSA signing protocol. Unlike standard secret sharing, a valid signature is generated using an interactive protocol without the original key ever being exposed. We mathematically prove the security of our proposed protocol. Findings from the performance evalation of the protocol show that it achieves good performance for curve Ed25519, with a single signing operation in the malicious setting taking approximately 3.32 ms between two devices.
QT-RR Relation Is Different in Humans and Rats

The QT interval (QT) variability has been recently computed to infer cardiac control of rats. It has been suggested that QT variability markers in rats have the same physiological meaning as in humans. However, some evidences indicate a different dependence of QT on the previous RR interval (RR). Thus, the aim of this study was to compare the relation of the QT to the preceding RR in humans and in rats. Electrocardiogram was recorded in supine position (REST) and during tilt test (T90) in 23 healthy subjects and in 9 Wistar (WI) and 14 wild-type Groningen (WT) rats during the dark period. Pearson product moment correlation coefficient r computed between RR and QT was calculated for each subject or animal within each experimental condition. In humans we found that r was positive and decreased from REST to T90. Conversely, r was negative in rats and did not differ between WI and WT. The r absolute value was significantly higher in humans than in rats. Our results showed that trends toward longer RRs lead to longer QTs in humans but shorter QTs in rats and that the strength of the QT-RR association is lower in rats. We conclude that attention should be paid when using the rat model in translational studies assessing the QT-RR relation.
Effective Plantation Management with Crowd-sensing and Data-driven Insights: A Case Study on Tea

We have an assortment of upcoming technologydriven ways to assist specific activities with precision such as spraying with drones, pest assessment with images, mechanisation to complement farm labour, macro farm health assessment with remote sensing, and Internet of Things (IoT) in general that plays a key role on the farm-edge in different capacities. With effective digital plantation management as an end-objective, we present our work on development of the framework constructs to (a) digitise pest management activities to record crop-stress data along with field operations, and (b) build insights from the data to respond faster to stress incidents with precise control measures. As part of the digitisation, we employed design thinking concepts and a human-centric approach to develop user-friendly interfaces where crowd-sensing with the help of ground staff is used as a foundational activity. Descriptive and diagnostic insights on the gathered data were brought out to correlate incidents with operations based on aggregated patterns, and generate deep insights on crop images with artificial intelligence. Image-based insights include localisation and recognition of symptoms associated with insect pests, diseases, and nutrient deficiencies that were non-trivial to get earlier through manual operations. Such insights were used to generate system recommendations that support experts in issuing effective advisory towards curative action on the field thus sowing the seeds for an Industry 4.0 future for plantations.