Miracle-dz/UniFAR-FTUs huggingface dataset:
Localization of Interaction using Fibre-Optic Shape Sensing in Soft-Robotic Surgery Tools

Minimally invasive surgery requires real-time tool tracking to guide the surgeon where depth perception and visual occlusion present navigational challenges. Although vision-based and external sensor-based tracking methods exist, fibre-optic sensing can overcome their limitations as they can be integrated directly into the device, are biocompatible, small, robust and geometrically versatile. In this paper, we integrate a fibre Bragg grating-based shape sensor into a soft robotic device. The soft robot is the pneumatically attachable flexible (PAF) rail designed to act as a soft interface between manipulation tools and intra-operative imaging devices. We demonstrate that the shape sensing fibre can detect the location of the tools paired with the PAF rail, by exploiting the change in curvature sensed by the fibre when a strain is applied to it. We then validate this with a series of grasping tasks and continuous US swipes, using the system to detect in real-time the location of the tools interacting with the PAF rail. The overall location-sensing accuracy of the system is 64.6%, with a margin of error between predicted location and actual location of 3.75 mm.
Correlating Test Events With Monitoring Logs For Test Log Reduction And Anomaly Prediction

Automated fault identification in long test logs is a tough problem, mainly because of their sequential character and the impossibility of constructing training sets for zero-day faults. To reduce software testers' workload, rule-based approaches have been extensively investigated as solutions for efficiently finding and predicting the fault. Based on software system status monitoring log analysis, we propose a new learning-based technique to automate anomaly detection, correlate test events to anomalies and predict system failures. Since the meaning of fault is not established in system status monitoring-based fault detection, the suggested technique first detects periods of time when a software system status encounters aberrant situations (Bug-Zones). The suggested technique is then tested in a real-time system for anomaly prediction of new tests. The model may be used in two ways. It can assist testers to focus on faulty-like time intervals by reducing the number of test logs. It may also be used to forecast a Bug-Zone in an online system, allowing system administrators to anticipate or even prevent a system failure. An extensive study on a real-world database acquired by a telecommunication operator demonstrates that our approach achieves 71 % accuracy as a Bug-Zones predictor.
Autonomic ZTA-based Network Management Engine (AZNME)

The advancements in computer and networking technologies created closely connected cyberspaces. Nevertheless, this also invalidated many traditional and isolated/local network solutions and introduced higher cybersecurity risk. As a solution, NIST's Zero-Trust Architecture (ZTA) with “never trust, always verify” principle has been widely accepted; yet, its implementation, enforcement, and compliance-check mechanisms are still immature as the solutions are generally applied manually. In this paper, we present an autonomic computing based management engine for networking of a cyberspace, we refer as Autonomic ZTA-based Network Management Engine (AZNME), which monitors an asset's network connections, checks if these connections fulfill ZTA requirements, and evaluates trust continuously, and takes mitigation actions as needed. As a proof of concept, we implemented the AZNME focusing on active connections (e.g., IPs and ports) to enforce policies and create firewall rules based on trust evaluation.
Research on PMSM Control for Position Sensorless Based on Fractional PD Sliding Mode Observer

According to the phase delaying question of estimated rotor position angle in traditional sliding mode observer, using fractional order calculus theory and singular perturbation two-time-scale decomposition theory, making up the parameter designing rules of fractional order PD sliding mode observer, proposed position sensorless control strategy for permanent magnet synchronous motor based on fractional order PD sliding mode observer. On one side, taking fast time-varying subsystem of singular perturbation two-time-scale decomposition theory to establish fractional order sliding mode observer; on the other side, taking slow time-varying subsystem of singular perturbation two-time-scale decomposition theory to obtain parameter of fractional order sliding mode observer. The results show that the method could not only making estimated rotor position angle follow actual rotor angle, but also establishing a global compensating control strategy of estimated rotor position angle effectively.
Measurement of interstitial convective heat transfer and frictional drag for flow across metal foams

Convective heat transfer and friction drag in a duct inserted with aluminum foams have been studied experimentally. The combined effects of foam porosity (e=0.7, 0.8, and 0.95) and flow Reynolds number (1900≤Re≤7800) are examined. Frictional drags for flow across the aluminum foam are measured by pressure taps, while interstitial heat transfer coefficients in the aluminum foam are determined using a transient single-blow technique with a thermal non-equilibrium two-equation model. Solid material temperature distribution is further measured for double check of the heat transfer results. To understand the frictional drag mechanisms, smoke-wire flow visualization is conducted in the aluminum-foam ducts. Results show that both the friction factor and the volumetric heat transfer coefficient increase with decreasing the foam porosity at a fixed Reynolds number. In addition, the aluminum foam of e=0.8 has the best thermal performance under the same pumping power constraint among the three aluminum foams investigated. Finally, empirical correlations for pore Nusselt number are developed in terms of pore Reynolds number under various foam porosities
Integrated Grasshopper Algorithm-Evolutionary Programming Technique for Distributed Energy Resources Allocation

Distributed energy resources (DER) are among important components or additional supplies to an existing power system network. Its installation in an existing power system network will help improve the voltage level in a system, reduce current values through the transmission lines and reduce the total transmission loss. The sizing and locations for the installation of DER or distributed generation (DG) require optimal values. Otherwise, the system will experience either over-compensation or under-compensation phenomena. Thus, a reliable optimization technique is a crucial factor. Several optimization techniques are not reliable enough as they cannot reach optimal solutions and sometimes, they are not accurate. This paper presents a new optimization technique termed Integrated Grasshopper Evolutionary Programming Technique (IGEPT). IGEPT integrates some operators in the grasshopper optimization into the original evolutionary programming (EP). It was validated on the IEEE 30-Bus Reliability Test System (RTS) for voltage maximization effort as the objective function. Several cases were taken into account so as to highlight the robustness of this technique. A comparative study with other techniques is also conducted, which highlights the merit of IGEPT.
Investigation of Impulse Voltage on the Thermally-Aged Empty Fruit Bunches (EFB) Fiber Paper Immersed in Transformer Oil

Empty Fruit Bunch (EFB) from palm oil residue is one of the materials with development potential. The tensile strength and lightning impulse tests of Kraft paper are compared in this paper to those of unrefined and refined EFB fibre insulation papers aged at 90°C and 140°C, respectively. The performance of the insulation paper should be prioritised by impregnating it with transformer oil (mineral oil) and ageing it for 30 days at 90°C and 140°C. To undergo the impulse breakdown testing, a multistage impulse generator is used with the increment of 1 kV charging voltage for the first test and 2 kV charge voltage for the second test. Lianapac Measure (v15.5.1e) and CCK-2712 controller (100) software are used to observe the result of the impulse breakdown. In comparison to Kraft insulating paper, refined EFB paper has a higher tensile strength than unrefined EFB and Kraft paper. However, as the temperature of ageing increased, the trend of EFB decreased gradually. When it comes to lightning impulse tests, refined EFB paper performs better than Kraft paper. This demonstrates the potential for refined EFB paper to replace Kraft paper in transformer insulation systems.
Roughness effects in turbulent pipe flow

Mean flow measurements are presented for fully developed turbulent pipe flow over a Reynolds number range of $57\,{\times}\,10^3$ to $21\,{\times}\,10^6$ where the flow exhibits hydraulically smooth, transitionally rough, and fully rough behaviours. The surface of the pipe was prepared with a honing tool, typical of many engineering applications, achieving a ratio of characteristic roughness height to pipe diameter of 1 : 17000. Results for the friction factor show that in the transitionally rough regime this surface follows a Nikuradse (1933)-type inflectional relationship rather than the monotonic Colebrook (1939) relationship used in the Moody diagram. This result supports previous suggestions that the Moody diagram in the transitional regime must be used with caution. Outer scaling of the mean velocity data shows excellent collapse and strong evidence for Townsend's outer layer similarity hypothesis for rough-walled flows. Finally, the pipe exhibited smooth behaviour for scaled roughness height $k_s^+ \,{\le}\, 3.5$, which supports the suggestion by Zagarola & Smits (1998) that their pipe was hydraulically smooth for $Re_D\,\,{\leq}\, 24\,{\times}\,10^6$.
Radiative Einstein-Maxwell spacetimes and 'no-hair' theorems

Friedrich's construction (1988) of purely radiative solutions out of static, asymptotically flat solutions of Einstein's vacuum equations is generalized to the Einstein-Maxwell case. These radiative solutions can be considered as being conformal and analytic extensions, to neighbourhoods of infinity, of local solutions to a certain time-symmetric initial value problem. The author points out that the non-existence of non-trivial global solutions to the corresponding constraints provides the basis for known uniqueness proofs for static, asymptotically flat black-hole and perfect-fluid solutions. The author also obtains a uniqueness theorem for static, charged perfect fluids whose equation of state belongs to a certain one-parameter family.
Catastrophe-Based Antibody Clone Algorithm

In solving complex optimization problems, intelligent optimization algorithms such as immune algorithm show better advantages than traditional optimization algorithms. Most of these immune algorithms, however, have disadvantages in population diversity and preservation of elitist antibodies genes, which will lead to the degenerative phenomenon, the zigzag phenomenon, poor global optimization, and low convergence speed. By introducing the catastrophe factor into the ACAMHC algorithm, we propose a novel catastrophe-based antibody clone algorithm (CACA) to solve the above problems. CACA preserves elitist antibody genes through the vaccine library to improve its local search capability; it improves the antibody population diversity by gene mutation that mimics the catastrophe events to the natural world to enhance its global search capability. To expand the antibody search space, CACA will add some new random immigrant antibodies with a certain ratio. The convergence of CACA is theoretically proved. The experiments of CACA compared with the clone selection algorithm (ACAMHC) on some benchmark functions are carried out. The experimental results indicate that the performance of CACA is better than that of ACAMHC. The CACA algorithm provides new opportunities for solving previously intractable optimization problems.
Multi-fingered Tactile Servoing for Grasping Adjustment under Partial Observation

Grasping of objects using multi-fingered robotic hands often fails due to small uncertainties in the hand motion control and the object's pose estimation. To tackle this problem, we propose a grasping adjustment strategy based on tactile seroving. Our technique employs feedback from a sensorized multi-fingered robotic hand to collaboratively servo the fingers and palm to achieve the desired grasp. We demonstrate the performance of our method through simulation and physical experiments by having a robot grasp different objects under conditions of variable uncertainty. The results show that our approach achieved a higher success rate and tolerated greater uncertainty than an open-looped grasp.
Energy Transport in a Concentrated Suspension of Bacteria

Coherent structures appear in a concentrated suspension of swimming bacteria. While transport phenomena in a suspension have been studied extensively, how energy is transported from the individual cell scale to the larger mesoscale remains unclear. In this study, we carry out the first successful measurement of the three-dimensional velocity field in a dense suspension of bacteria. The results show that most of the energy generated by individual bacteria dissipates on the cellular scale. Only a small amount of energy is transported to the mesoscale, but the gain in swimming velocity and mass transport due to mesoscale coherent structures is enormous. These results indicate that collective swimming of bacteria is efficient in terms of energy. This paper sheds light on how energy can be transported toward smaller wave numbers in the Stokes flow regime.
Conventional Radiofrequency of the Peripheral Branches of the Trigeminal Nerve versus Conventional Radiofrequency of the Gasserian Ganglion for Treatment of Idiopathic Trigeminal Neuralgia

Background: Trigeminal neuralgia (TGN) is the most prevalent kind of neuralgia. Conventional radiofrequency (CRF) of the Gasserian ganglion provides the highest rate of total pain alleviation. CRF of the peripheral trigeminal branches is considered a minimally invasive and safe operation. The aim of this work was to compare the safety and efficacy of CRF for the peripheral trigeminal branches with CRF of the Gasserian ganglion for treating idiopathic trigeminal neuralgia (ITGN). Methods: This prospective randomized controlled trial was conducted on 60 cases aged 21-65 years, with confirmed diagnosis of ITGN, refractory to medications for TGN for an adequate period. Patients were subdivided in to two groups: group I (study group): 30 cases underwent CRF of the peripheral trigeminal branches and group II (control group): 30 cases underwent CRF of the Gasserian ganglion. All patients were subjected to history taking, physical examination and magnetic resonance imaging (MRI) of the brain. Results: NRS and barrow neurological institute (BNI) pain intensity scale were insignificantly different between both groups at all times of measurements. Pain relief and patients’ satisfaction were insignificantly different at all measurements between both groups. The incidence of numbness and ccomplications were insignificantly different between both groups. Conclusions: Peripheral nerve branches CRF is a safe and effective procedure as gasserian ganglion CRF for treatment of ITGN.
Real-Time Distributed Multi-Robot Target Tracking via Virtual Pheromones

Actively searching for targets using a multi-agent system in an unknown environment poses a two-pronged prob-lem, where on the one hand we need agents to cover as much of the environment as possible and on the other have a higher density of agents where there are potential targets to maximize detection performance. This paper proposes a fully distributed solution for an ad hoc network of agents to cooperatively search an unknown environment and actively track found targets. The solution combines a distributed pheromone-based coverage control strategy with a distributed target selection mechanism.
Restricting Chaos to a Small Region in the Phase Space

The idea of restricting chaos in dissipative systems to a small region in the phase space is proposed. The possibility of realization of this idea is demonstrated by applying a simple method summed up from computer simulations successfully to three different dynamical systems. It is found that not only does the trajectory of the controlled system occupy a region smaller than that of the uncontrolled chaotic system, the corresponding attractor of the Poincare map is also smaller than that of the uncontrolled system. In addition, but also the maximum Lyapunov characteristic exponent of the system is greatly lowered.
Design and Analysis of Inverted F-shaped Slotted Patch Multiband Microstrip Antenna for S, C, X, and Ku Band Applications

This paper looks into a brand-new multiband microstrip antenna design. The designed antenna can operate at 8 different frequencies between 2.5 GHz and 14.0 GHz. An inverted F-shaped slot is added to the radiating patch to create multi-band frequencies. Initially different patch sizes, substrate material, and different shaped slots are investigated for creating multiband and also improving antenna performance. An FR4 dielectric substrate is used whose relative permittivity is 4.4 and thermal conductivity is 0.3[W/K/m]. A microstrip line is also used for feeding. The resonant frequencies of 8 bands are 2.9 GHz, 5.05 GHz, 5.8 GHz, 8.5 GHz, 9.5 GHz, 10.9 GHz, 12.8 GHz, and 13.5 GHz with the reflected power of -16.3 dB, -14.9 dB, -16.7 dB, -14.6 dB, -10.9 dB, -18.6 dB, -11.1 dB, and -20.9 dB respectively. The acquired bandwidth is satisfactory and the VSWR is improved, being less than 2. This antenna is designed for S, C, X, and Ku band applications so it can be used for many purposes. CST Studio Suite software is used to design all the simulation results.
Organ‐specific immune profiling of Leishmania donovani‐infected hamsters

Visceral leishmaniasis (VL) is a neglected disease with a broad spectrum of clinical manifestations and involvement of visceral organs. Organ‐specific immune response against the Leishmania donovani (Ld) complex is not yet understood due to the unavailability of an appropriate experimental model. In reference to our recent work on comparing the hamster model with VL patients, it is now possible to understand immune profiling in different visceral organs. This may offer an answer to varying parasite loads in different visceral organs in the same host. Herein, we analysed a panel of immune markers (Th‐2/Th‐1) in visceral organs of Ld‐infected hamsters and quantified parasitic load in the same tissues using qPCR assay. In spleen, liver, bone marrow and lymph node (mesenteric) from Ld‐infected hamsters, the parasite burden was quantified along with mRNA expression of a panel of Th‐2 and Th‐1 type immune markers, namely IL‐10, IL‐4, Arginase‐I, GATA‐3, SOCS‐3, IL‐12, IFN‐γ, iNOS, T‐bet and SOCS‐5. A clear dichotomy was absent between Th‐2 and Th‐1 type immune markers and the major players of this immune response were IFN‐γ, IL‐10, T‐bet, GATA‐3, SOCS‐5 and SOCS‐3.
Single-polarization single-mode optical fibers

Strictly speaking, an ordinary axially symmetrical single-mode fiber is a "two-mode" fiber because two orthogonally polarized HE 11 modes can be propagated in it. This fact results in the instability of the polarization state of the propagated mode when geometrical perturbation exists in the fiber, and also the so-called polarization mode dispersion. These are harmful in some applications of single-mode fibers to communication and measurement. To prevent these adverse effects, single-polarization single-mode (SPSM) optical fibers have been developed. Three basic types of the SPSM fiber are elliptical-core fiber, stress-induced birefringent fiber, and side-pit fiber. This paper describes the principles of these three types, performance obtained experimentally, theoretical approaches, and measurement techniques related to the SPSM fibers. Finally, relevant technical tasks in the future are mentioned.
A Fully Connected Quantum Convolutional Neural Network for Classifying Ischemic Cardiopathy

The prevalence of heart diseases is rising quickly throughout the world, which has an impact on both the world economy and public health. According to the recent statistical survey reports, the increasing mortality rate is due to high blood pressure, high cholesterol, the use of tobacco, obesity, and an inconsistent pulse rate. It is difficult and time-consuming to investigate the various variations of these factors and their impact on Coronary Artery Disease (CAD). Therefore, it is necessary to use modern approaches to diagnose the disease early and minimize the mortality rate. The fields of machine learning and data mining have a wide research dimension and various novel techniques that could help in the prediction of CAD in its early stages and identify their patterns and behaviors in a huge amount of data. The results of such predictions will aid the clinical staff in decision making and early diagnosis. In such a scenario, we proposed a quantum version of the Fully Convolutional Neural Network (FCQ-CNN) for Ischemic Heart Disease (IHD) classification. The proposed model evaluates the quantum circuit-based technique that was inspired by convolutional neural networks, a very successful machine learning model. This method provides $O(log (n))$ depth for $n$ qubits, reducing the number of parameters and allowing for effective training and testing of real quantum devices. The model has been evaluated by considering the IHD dataset after the data has been cleaned and filtered through the Maximally Relevant Minimally Redundancy (MRMR) filter. For dimension reduction, a Support Vector Machine along with Recursive Feature Elimination (SVM-RFE) has been considered. Initially, the model is tested with 20% of the whole dataset and gets the promising results of a testing accuracy of 84.6% with a testing loss of 0.28. By taking into account the same optimal parameters, the proposed model outcomes are compared to those of the classical Optimized Convolution Neural Network (Optimized-CNN) and Fully Connected Neural Network (FCNN) models. Comparing the model’s competency to that of earlier published quantum models yields improvements in accuracy of 8.6%, 12.6%, 3.5%, and 1.8% respectively.
Current status and future direction of duck hepatitis A virus vaccines

ABSTRACT Duck viral hepatitis (DVH), mainly caused by duck hepatitis A virus (DHAV), is a highly fatal and rapidly spreading infectious disease of young ducklings that seriously jeopardizes the duck industry worldwide. DHAV type 1 (DHAV-1) is the main genotype responsible for disease outbreaks since 1945, and the disease situation is complicated by the emergence and dissemination of a novel genotype (DHAV-3) in some countries in Asia and Africa. Live attenuated DHAV vaccines are widely used to induce a considerable degree of protection in ducklings. Breeder ducks are immunized with inactivated or/and live DHAV vaccines to achieve satisfactory levels of passive immunity in progeny. In addition, novel characteristics of virus transmission, pathogenicity and pathogenesis of DHAV were recently characterized, necessitating the development of new vaccines and effective vaccination programmes against DVH. Therefore, a systematic dissection of the profiles, strengths and shortcomings of the available DHAV vaccines is essential. Moreover, to further increase the efficiency of vaccine production and administration, the development of next-generation DHAV vaccines using cutting-edge technologies is also required. In this review, based on a comprehensive summary of the research advances in the epidemiology, pathogenicity, and genomic features of DHAV, we focus on reviewing and analysing the features of the commercial and experimental DHAV vaccines. We also propose perspectives for disease control based on the specific disease situations in different countries. This review provides essential information for vaccine development and disease control of DVH.