Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient and Accurate Inverse Kinematics for 7-DOF Redundant Manipulators Based on a Hybrid of Analytical and Numerical Method

This paper proposes an efficient and accuracy inverse kinematic algorithm for 7-DOF redundant manipulators with obstacles avoidance and singularities avoidance based on the hybrid of analytical and numerical method (IK-HAN). Specially, the paper focuses on how to solve the inverse kinematics problem accurately and efficiently for a novel configuration, i.e. SSRMS-type manipulator. First, the elbow orientation is introduced and the algebraic relationship between the elbow orientation and joint angles is derived. Second, the optimization algorithm is designed to find the optimal elbow orientation based on Particle Swarm Optimization. To improve the efficiency, the equivalent optimization model based on the azimuth angle is investigated. Third, optimal models are developed to avoid obstacles and singularities and improve manipulability in the constraint domain. Moreover, how to employ optimization resolution to solve the inverse kinematics problem is discussed. Finally, the validity of the algorithm is verified via kinematics simulations and the result illustrates that the algorithm performs well in accuracy, stability and efficiency.
Tensor-based Blind fMRI Source Separation Without the Gaussian Noise Assumption — A β-Divergence Approach

The advantages of tensor- over matrix-based methods have been recently demonstrated in the context of functional magnetic resonance imaging (fMRI) blind source unmixing. However, these methods rely on the assumption of a Gaussian distribution for the noise, which suggests a least squares criterion for the tensor decomposition. One can instead argue that a Rician model for the fMRI noise is much more accurate and hence alternative cost functions should also be investigated. In this paper, β-divergences are used to parametrize the Canonical Polyadic Decomposition (CPD) fitting to fMRI data and the effect of β on the source separation performance is evaluated, for different values of signal to noise ratio (SNR). Our results confirm that the commonly used squared error is not the best choice, particularly at low SNRs.
Optimal temporal logic planning with cascading soft constraints

In this paper, we address the problem of temporal logic planning given both hard specifications of the robot’s mission and soft preferences on the plans that achieve the mission. In particular, we consider a problem whose inputs are a transition system, a linear temporal logic (LTL) formula specifying the robot’s mission, and an ordered sequence of formulas expressed in linear dynamic logic over finite traces (LDLf) specifying the user’s preferences for how the mission should be completed. The planner’s objective is to synthesize, on this transition system, an infinite trajectory that best fits the user’s preferences over finite prefixes of that trajectory while nonetheless satisfying the overall objective. We describe an algorithm for this problem that constructs, from the inputs, a product automaton —which is, in fact, a special kind of state-weighted Büchi automaton— over which an optimal trajectory is synthesized. This synthesis problem is solved via reduction to the minimax path problem in vertex weighted graphs, which can be solved by variants of the standard algorithms for computing shortest paths in a graph or by algorithms for the all-pairs bottleneck paths problem on vertex-weighted graphs. We show the applicability of the approach via some case studies, for which we present results computed by an implementation.
Challenges in Secure Engineering of Critical Infrastructure Systems

Modern critical infrastructure (CI), such as water supply, smart power grids, and transportation networks, face major security challenges that arise due to complex interactions between software and physical components as well as human operators. Such systems are an attractive target for attackers who intend to disrupt the safe, normal operation of CI by exploiting vulnerabilities in software components such as the supervisory control and data acquisition (SCADA) workstations and programmable logic controllers (PLCs). In this reference paper, we elaborate on problems and challenges learned from our own experience in automating security analysis, assessment, and defense mechanisms for CI. These challenges are presented in the context of two real-world CI systems-namely, a water treatment plant and a water distribution system.
Metagenomic Insights on the Role of Gut Microbiota in Type-2 Diabetes

Gut microbiota is intrinsically linked to modulation of physiological behavior of the host in both health and disease. The microDiab project, implemented at "Stefan cel Mare" University in Suceava, Romania has, as one of its objectives, the characterization of the gut microbiome in type-2 diabetic patients using high throughput metagenomic sequencing technologies. Microbiota of placebo and probiotic-treated patients was sequenced using 16S rRNA metagenomics on Next Generation Sequencing platform. Preliminary results indicate differences in gut microbiota composition profile across treatments and points to the importance of this community of microorganisms in type-2 diabetes mellitus.
Biped Robot Pelvis Kinematics Estimation based on the Touch-Point Updating Method

This study proposes a biped-robot pelvis-kinematics estimator based on the touch-point updating method. Because the pelvis frame is used as the base coordinate for the control, the kinematics of it with respect to the global frame should be precisely estimated. To this end, it was necessary to know where the robot made contact with the ground. The touch-point concept was introduced as the temporal contact-point, which was instantly the robot’s rotation center. By updating this point, the biped's global pelvis-kinematics could be estimated. The proposed estimator was implemented into the actual robot, and its superiority was verified through ground-truth data.
Buckling-induced Shape Morphing using Dielectric Elastomer Actuators Patterned with Spatially-varying Electrodes

Shape morphing is at the core of future research, which shows promise for wide applications ranging from reconfigurable electronics to soft material robots. In this paper, we present a novel buckling-induced mechanism for shape morphing using dielectric elastomer actuators (DEAs), by bonding the planar precursor structure’s “feet” with the DEA. With spatially-varying electric fields applied, the inplane deformation of the DEA generates compressive loads to trigger buckling of planar precursors into desired three-dimensional configurations. To enlarge the achievable motion range at the “feet”, we develop a design optimization approach to the electrode arrangement which is concisely described by cosine functions. By numerically optimizing the cosine function coefficients, we obtain the optimal spatially-varying electrodes for various precursors with different patterns of bonding sites. The experimental results demonstrate the remarkable shape-morphing from two dimensions to three dimensional configurations. Our work paves the way to novel actuation mechanisms for shape-morphing structures, with advantages of rapid response and reversible controllability.
Radar Localization and Mapping for Indoor Disaster Environments via Multi-modal Registration to Prior LiDAR Map

This paper presents a localization and mapping algorithm that leverages a radar system in low-visibility environments. We aim to address disaster situations in which prior knowledge of a place is available from CAD or light detection and ranging (LiDAR) maps, but incoming visibility is severely limited. In smoky environments, typical sensors (e.g., cameras and LiDARs) fail to perform reliably due to the large particles in the air. Radars recently attracted attention for their robust perception in low-visibility environments; however, radar measurements’ angular ambiguity and low resolution prevented the direct application to the simultaneous localization and mapping (SLAM) framework. In this paper, we propose registering radar measurements against a previously built dense LiDAR map for localization and applying radar-map refinement for mapping. Our proposed method overcomes the significant density discrepancy between LiDAR and radar with a density-independent point registration algorithm. We validate the proposed method in an environment containing dense fog.
A Scalable Real-Time Biomonitoring Platform

Our paper presents a biomonitoring platform comprised of a software backend and an affordable wearable monitoring device. The biomonitoring field demands for large scale solutions involving plug and play devices in order to conduct ample studies.Our software platform is aimed at a scalable web backend with dedicated microservices for storing and processing real time data streams coming from a multitude of sensors. The hardware module was developed using an ergonomic design fit for outdoor environments and a fast connection using Bluetooth 4.0. We integrated sensors for electrocardiogram, oxygen saturation and heart rate.Our proposed platform allows for real time data monitoring of multiple subjects in an active environment.
Performance Analysis of UAV-assisted Ferrying for the Internet of Things

IoT sensor networks are applied in several areas, including research, security, and monitoring. All these applications are based on data collection. A practical solution is a use of unmanned aerial vehicles (UAVs) as aerial relays to ensure connectivity between IoT-devices and the destination node. Most applications have been based on using a single UAV to transmit information, while our work focuses on forming a network of multiple UAVs. In this paper, a novel deployment of UAVs moving along non-concentric rings is analyzed. First, they collect packets generated by IoT-devices and then transmit them throughout a UAV-to-UAV forwarding schema to the destination. We derive a closed formula for the end-to-end throughput of the proposed gathering network architecture.
Compact Reachability Map for Excavator Motion Planning

In this paper, we propose a novel compact reachability map representation for excavator motion planning. The constructed reachability map can concisely encode the bucket’s reachable pose and the translation capability limited by excavator’s kinematic structure. By explicitly exploiting the property that the basic excavation motion lies on the excavation plane determined by excavator links, we further reduce the construction of the map from 3D Euclidean space to 2D excavation plane. We show the pre-computed reachability map can be used to develop new excavator motion planning approach. By indexing on the pre-computed reachability map, we can efficiently compute the feasible full-bucket trajectory for single step excavation operation. We highlight the results of the reachability map construction and demonstrate the simulation results of motion planning using a commercial dynamic simulator.
Kinematic Modeling of a Soft Pneumatic Actuator Using Cubic Hermite Splines

Soft material robotic systems provide increased adaptability and flexibility compared to conventional rigid metal robots. The soft systems benefit from their inherent compliance, which enables them to be used in applications that require safe interaction between humans and robots or manipulation in cluttered environment. Despite advancements in recent years research on soft material robots still needs to make progress in terms of modeling for model based control or path planning. The high nonlinearity of soft material robots makes efficient and accurate modeling difficult. In this work we introduce a kinematic modeling approach based on cubic hermite splines. The method is applied to a soft pneumatic actuator and evaluated against the widely used constant curvature approach. The hermite spline offers the possibility of accurate shape reconstruction from simulated or measured deformation data. Both the shape of a robot’s segment and its orientation can be approximated this way. In this paper a machine learning approach is used to train the kinematic relation between actuating pressure and configuration parameters.
Magnetic-Needle-Assisted Micromanipulation of Dynamically Self-Assembled Magnetic Droplets for Cargo Transportation

Dynamic self-assembly is treated as a promising approach for generating a robotic swarm to perform coordinated tasks, and the assembled pattern can be tuned by regulating the energy input. However, location of a dynamically assembled pattern is hard to be determined, especially under global fields, such as magnetic field. In this paper, we report the formation and manipulation of dynamic self-assembled droplets at the air-liquid interface with the assistance of a magnetic needle. Affected by the locally induced field gradient near the needle, reconfigurable assembled droplets are obtained with higher time-efficiency, and the location of the pattern can be determined. The pattern is reversibly tuned to exhibit expansion and shrinkage by adjusting the height of the needle. Assembled droplets are able to be steered via following the needle in a controlled manner. Moreover, cargo is trapped by exploiting the induced rotational flow around the droplets, and it can also be caged into the central area of the pattern and transported to the desired location. The proposed method opens new prospects of using energy-dissipative pattern as an untethered end-effector for microrobotic manipulation.
Range-limited, Distributed Algorithms on Higher-Order Voronoi Partitions in Multi-Robot Systems

This paper studies the problem of distributed computation of higher order Voronoi partition over a bounded region by a group of robots with both range-limited visibility sensors and communication devices. We model the sensing and communication capabilities by discs with limited radius. Motivated by the concept of dominating region in higher-order Voronoi partition, we propose a detecting ray based algorithm, which computes the boundary points of the dominating region of a robot in an omnidirectional manner, with local position information of its neighbors within the communication range. Simulations are provided to demonstrate the performance of our proposed algorithm by using a thirteen-robot group.
Analysis of Scattering Environment for Reliable Indoor Communications Over Millimeter-Waves

Millimeter-wave (mm-wave) technologies for wireless communications like 5G New Radio or WiGig offer multi-Gigabit per second connectivity but are sensitive to signal blockages and outages. In this study, we analyze capability of exploiting scattering environment for reliable multi-beam communications. Reliability is critical for interactive applications such as video conferencing or industrial control. To this end, 60 GHz channel measurements have been carried out in typical cubicle offices and the impact of the receiving antenna parameters on the channel characteristics have been addressed. We conclude that there is a trade-off between achievable data rates and their sustainability.
Constructing QC-LDPC codes based on dimension reduction for physical layer security

As a recently proposed physical layer security scheme, the two-dimensional transmission scheme prevents eavesdropping, but the bit error rate (BER) of the receiver becomes high. A new coding scheme for Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) codes to improve the performance of the receiver is proposed and named as dimension reduction coding. This new scheme constructs the base matrix, which is necessary to obtain the parity check matrix of QC-LDPC codes, from the channel coefficient matrix of two-dimensional transmission scheme. Then, by analyzing the relationship between the base matrix and the parity check matrix of QC-LDPC codes, we find out the conditions that the base matrix must satisfy so that the corresponding parity check matrix has no shortest cycle in Tanner graph. Furthermore, a dimension reduction algorithm is presented to modify the base matrix and obtain parity check matrices with good performance. Finally, simulation results are given and validate the feasibility of this method.
Evaluation of Electrical Impedance Tomography for a Measurement of Tidal Volume in High-frequency Ventilation of the Pig – Case Study

We have analyzed dynamic lung impedance recorded by electric impedance tomography in the high-frequency oscillatory ventilation of the laboratory pig. The aim of the study was find out if electrical impedance tomography can be used for an assessing of the tidal volume in high-frequency oscillatory ventilation. The analyzed amplitude of dynamic lung impedance was compared with the tidal volume computed from flow that was measured at the orifice placed before endotracheal tube. We have found out that amplitude of dynamic lung impedance does not correspond with tidal volume within conducted experiment.
Leveraging Mobile Edge Computing on Smart Grids Using LTE Cellular Networks

Given the advance of the Smart Grid technology, the electrical grid is now in a process of transformation never seen in history. This new grid model allows customers and providers to generate and manage electrical power efficiently. To support such transformation, a key element of the model is the communication network responsible for delivering measurement data from sensors on the grid to the applications that analyze and adapt distribution according to demands. This work proposes and evaluates a system architecture that copes with reliability and latency demands that are of much importance for a successful Smart Grid deployment, also considering the internal design of distributed applications in the context of Smart Grids. The architecture adopts a Mobile Edge Computing based infrastructure that is suitable for 4G and 5G mobile cellular networks. Experiments made on NS-3 shows that the proposed system architecture is capable of handling a realistic number of smart meters while providing low latency and network reliability, supporting many use cases of a Smart Grid deployment.
Red/ET recombineering enhances extracellular lipase production by Burkholderia glumae

Background: Microbial lipases are utilized widely in industrial fields, and the LipA lipase produced by Burkholderia glumae PG1 has been used for the production of enantiopure pharmaceuticals. However, efficient lipase expression and secretion are still problematic. LipA is encoded in an operon that also contains the lipase-specific foldase gene lipB. The purpose of this study was to enhance the production of active lipase by overexpressing lipAB in B. glumae PG1 using a host-vector system.Results: The lipAB operon, isolated from the genomic DNA of B. glumae PG1, was directly cloned into broad-host-range vectors, with pBBR1 or pRk2 backbones, using the Red/ET recombination system and then transformed into the original host strain. Lipase activity of the derivative strains, including PG1/Bl and PG1/Rl, were evaluated. When 1% olive oil was included in the growth medium, the maximum activities of the resultant strains were approximately 39.5- and 15.3-fold higher, respectively, than that of the wild-type PG1, indicating that increased lipase gene dosage resulted in high expression yields of lipase. To further enhance lipase expression, two recombinant strains, PG1/Ba and PG1/Ra, were generated with the plasmid-borne lipAB operon driven by the strong constitutive promoter Papra. PG1/Ba and PG1/Ra displayed 15.0- and 4.3-fold improvements in lipase production in 0.5% glucose-containing medium compared to PG1/Bl and PG1/Rl, respectively. However, glucose repressed lipase gene expression in strain PG1 when the native lipAB promoter was used.Conclusions: Homologous expression of lipase genes in B. glumae PG1 was achieved by the use of high-copy expression vectors, and the resulting presence of multiple copies of lipAB significantly improved extracellular lipase expression. Our results demonstrate that modification of B. glumae PG1 can improve this host system for lipase production.
The epidemiology of P. falciparum and P. vivax in East Sepik Province, Papua New Guinea, pre- and post-implementation of national malaria control efforts

BackgroundIn the past decade, national malaria control efforts in Papua New Guinea (PNG) have received renewed support, facilitating nationwide distribution of free long-lasting insecticidal nets (LLINs), as well as improvements in access to parasite-confirmed diagnosis and effective artemisinin-combination therapy in 2011-12. MethodsTo study the effects of these intensified control efforts on the epidemiology and transmission of P. falciparum and P. vivax infections and investigate risk factors at the individual and household level, two cross-sectional surveys were conducted in the East Sepik Province of PNG; one in 2005, before the scale-up of national campaigns and one in late 2012-early 2013, after 2 rounds of LLIN distribution (2008 and 2011-12). Differences between studies were investigated using chi-square (χ²), Fischer’s exact tests and Student’s t-test. Multivariable logistic regression models were built to investigate factors associated with infection at the individual and household level. ResultsThe prevalence of P. falciparum and P. vivax in surveyed communities decreased from 55% (2005) to 9% (2013) and 36% to 6%, respectively. The mean multiplicity of infection (MOI) decreased from 1.8 to 1.6 for P. falciparum (p=0.08) and from 2.2 to 1.4 for P. vivax (p<0.001). Alongside these reductions, a shift towards a more uniform distribution of infections and illness across age groups was observed but there was greater heterogeneity across the study area and within the study villages. Microscopy positive infections and clinical cases in the household were associated with high rate infection households (>50% of household members with Plasmodium infection). ConclusionAfter the scale-up of malaria control interventions in PNG between 2008 and 2012, there was a substantial reduction in P. falciparum and P. vivax infection rates in the studies villages in East Sepik Province. Understanding the extent of local heterogeneity in malaria transmission and the driving factors is critical to identify and implement targeted control strategies to ensure the ongoing success of malaria control in PNG and inform the development of tools required to achieve elimination. In household-based interventions, diagnostics with a sensitivity similar to (expert) microscopy could be used to identify and target high rate households.
Synchrony and perturbation transmission in trophic metacommunities

In a world where natural habitats are ever more fragmented, the dynamics of meta-communities is essential to properly understand species responses to perturbations. If species’ populations fluctuate asynchronously, the risk of their simultaneous extinction is low, thus reducing the species’ regional extinction risk. We propose a metacommunity model consisting of two food chains connected by dispersal to study the transmission of small perturbations affecting populations in the vicinity of an equilibrium. We show that perturbing a species in one patch can lead to asynchrony between patches if the perturbed species is not the most affected by dispersal. Dispersal affects rare species the most, thus making biomass distribution critical to understand the response of trophic metacommunities to perturbations. We further partition the effect of each perturbation on species synchrony when several independent perturbations are applied. Our approach allows disentangling and predicting the responses of simple trophic metacommunities to perturbations, thus providing a theoretical foundation for future studies considering more complex spatial ecological systems.