Miracle-dz/UniFAR-FTUs huggingface dataset:
Sensor fusion in autonomous vehicle using LiDAR and camera Sensor with Odometry

In this paper sensor fusion methodology along with odometry and motion estimation for autonomous vehicles (AVs) using Light Detection and Ranging (LiDAR) and camera is explored. Since during bad weather conditions, dim light or night time the sensor may not give very good readings, odometry can used in such situations. Odometry gives an estimation of change in position of given vehicle using data from sensors. The study also examines the impact of Extended Kalman Filter (EKF) to reduce error in position estimate of the vehicle both before and after using odometry through a KITTI data-set on vehicle motion.
An I/O Virtualization Framework With I/O-Related Memory Contention Control for Real-Time Systems

Modern applications are often characterized by a tight interaction with I/O devices. At the same time, many application domains are also facing a shift toward an integrated approach where multiple applications with mixed levels of safety and security need to co-exist on top of a shared hardware platform, which is typically managed by a hypervisor. This gives rise to the need for a predictable mechanism allowing multiple virtual machines to share I/O devices, while at the same time controlling contention delays when they access global memory. To deal with these shortcomings, this article proposes an I/O virtualization framework providing support for controlling the I/O-related memory contention by leveraging the ARM QoS-400 regulators. Extensive experiments are performed to compare the proposed solution with the Xen hypervisor, showing improvements up to $8\times $ when controlling the I/O-related memory contention.
VMD based Modified Multi-View Neural Network for Long-Term Load Forecasting

Long-term load forecasting is required for power system planning, long-term investments, and expansion policies. In this paper, an ensemble of Long Short Term Memory (LSTM) and Convolutional Neural Network (CNN) is proposed that minimizes the forecasting error for the long-term. The features are extracted from the decomposition of load series using Variational Mode Decomposition (VMD) into various timescale subseries' and are combined with the exogenous variables like temperature and rain. This data is then used to train a Fully Connected Neural Network (FCNN) that produces the final output. This ensemble is expected to provide an accurate forecast as local variations in the series are captured by CNN and long-term dependencies by LSTM, while the VMD decomposes the raw data into low and high-frequency subsequences. The efficacy of the methodology is assessed on the actual load data of Madhya Pradesh (MP) State, India. It is observed that the proposed method has higher forecasting accuracy.
An On-Line Monitoring and Warning System of Multi-Rotor VAV

The flight safety of UAV has posed a serious threat to public security. The abnormality of any component may cause the whole rotorcraft out of control even crash. To detect even control the potential failure of UAV, it makes great sense to trace the real-time status of UAV. This paper addresses the issue of the online monitoring and alarm system for multi-rotor UAV. The framework of the system, design of the acquisition board and method for data collection are specifically discussed. Also, the system prototype for airborne is developed based on DSP+FPGA platform. Experimental results show that the system can effectively realize the online status monitoring of multi-rotor UAV.
Advances in Cancer Diagnosis: Bio-Electrochemical and Biophysical Characterizations of Cancer Cells

Cancer is a worldwide leading cause of death, and it is projected that newly diagnosed cases globally will reach 27.5 million each year by 2040. Cancers (malignant tumors), unlike benign tumors are characterized by structural and functional dedifferentiation (anaplasia), breaching of the basement membrane, spreading to adjacent tissues (invasiveness), and the capability to spread to distant sites (metastasis). In the cancer biology research field, understanding and characterizing cancer metastasis as well as features of cell death (apoptosis) is considered a technically challenging subject of study and clinically is very critical and necessary. Therefore, in addition to the cytochemical methods traditionally used, novel biophysical and bioelectrochemical techniques (e.g., cyclic voltammetry and electrochemical impedance spectroscopy), atomic force microscopy, and electron microscopic methods are increasingly being deployed to better understand these processes. Implementing those methods at the preclinical level enables the rapid screening of new anticancer drugs with understanding of their central mechanism for cancer therapy. In this review, principles and basic concepts of new techniques suggested for metastasis, and apoptosis examinations for research purposes are introduced, along with examples of each technique. From our recommendations, the privilege of combining the bio-electrochemical and biosensing techniques with the conventional cytochemical methods either for research or for biomedical diagnosis should be emphasized.
Recent Advances in the Application of Piezoelectric Materials in Microrobotic Systems

Recent advances in precision manufacturing technology and a thorough understanding of the properties of piezoelectric materials have made it possible for researchers to develop innovative microrobotic systems, which draw more attention to the challenges of utilizing microrobots in areas that are inaccessible to ordinary robots. This review paper provides an overview of the recent advances in the application of piezoelectric materials in microrobots. The challenges of microrobots in the direction of autonomy are categorized into four sections: mechanisms, power, sensing, and control. In each section, innovative research ideas are presented to inspire researchers in their prospective microrobot designs according to specific applications. Novel mechanisms for the mobility of piezoelectric microrobots are reviewed and described. Additionally, as the piezoelectric micro-actuators require high-voltage electronics and onboard power supplies, we review ways of energy harvesting technology and lightweight micro-sensing mechanisms that contain piezoelectric devices to provide feedback, facilitating the use of control strategies to achieve the autonomous untethered movement of microrobots.
Compact W-band Silicon-Micromachined Filters with Increased Fabrication Robustness

In this paper, we present a new, robust fabrication and assembly method which allows for achieving highly-accurate responses of multilayer silicon-micromachined filters containing large-sized cavities. To obtain coupled-resonator filters with accurate and predictable frequency responses, chips fabricated with two different techniques are combined: (1) the first technique allows for fabricating geometries with accurate dimensions and well-controlled side walls, and these chips determine the electrical functionality; (2) the other fabrication technique allowing for complex 3-D geometries, including waveguide roofs, does not have the same geometrical confidence, but these chips don't dominate the electrical performance. A 5th-order all-pole bandpass filter with fractional bandwidth of 1.3% at 76.5 GHz is designed using rectangular TE101cavities and fabricated by silicon micromachining with gold metallization. The measured average insertion loss in the passband of the filter is 3.1 dB. The experimentally extracted unloaded quality-factor is 850. The measured insertion loss shows excellent agreement with the simulation results, while the return loss is slightly detuned.
Independent Loss of Cloacal Bursae and Age-Dependent Surfacing Postures in Diamond-Backed Terrapins (Chelonia: Emydidae: Malaclemys terrapin)

Malaclemys terrapin is a species of turtle that lives in brackish waters along the eastern coast of the United States from Cape Cod to Texas. We documented distinctive underwater postures during surfacing in hatchlings versus individuals after one year (yearlings). Hatchlings approach the water's surface in horizontal postures, while yearlings approach in a more vertical posture. Because cloacal bursae play a role in controlling buoyancy in freshwater turtles, we investigated their potential role in determining surface postures. We discovered that cloacal bursae are absent in M. terrapin, and we attribute this absence to the osmoregulatory challenges presented by the brackish habitats of this species. We posit that the horizontal postures in the hatchlings create a broader visual target to both aerial and aquatic predators and that the younger turtles likely do not have the strength, muscle mass, lung-volume coordination, or sufficient bone density in the shell to adopt the more visually streamlined vertical posture at the surface.
The Lasso Method for Multi-Robot Foraging

We propose a novel approach to multi-robot foraging. This approach makes use of a scalar field to guide robots throughout an environment while gathering objects towards the goal. The environment must be planar with a closed, contiguous boundary. However, the boundary's shape can be arbitrary. Conventional robot foraging methods assume an open environment or a simple boundary that never impedes the robots—a limitation which our method overcomes. Our distributed control algorithm causes the robots to circumnavigate the environment and nudge objects inwards towards the goal. We demonstrate the performance of our approach using real-world and simulated experiments and study the impact of the number of robots, the complexity of the boundary, and limitations on the sensing range.
Efficiency Improvement of Grid Inverters With Hybrid Devices

In this paper, a hybrid switch with the combination of large-current silicon (Si) insulated gate bipolar transistor (IGBT) and small-current silicon carbide (SiC) metal-oxide semiconductor field-effect transistor (mosfet) is utilized in a three-phase T-type three-level grid inverter. The hybrid switch can optimize the cost of the system while achieving high efficiency. The relationship between efficiency improvement and cost of the hybrid switch is investigated. Several switching patterns, which can decrease the loss of the small-current SiC mosfet for the hybrid switch, are studied. Different switching patterns for the hybrid switch of the grid inverter are compared based on the inverter efficiency. Finally, a 20 kW three-phase T-type three-level grid inverter prototype with the hybrid switch of large-current Si IGBT and small-current SiC mosfet (1:2.4 SiC/Si current ratio) is built to verify the main results.
A Building Height-Dependent Gaussian Mixture Model to Characterize Air-to-Ground Wireless Channels

With the continuous evolution of Unmanned Aerial Vehicles (UAVs) in terms of flight autonomy and high payload capabilities, many new applications have emerged recently. In this context, potential usage of UAVs has been explored in providing wireless communication service. However, our understanding of the wireless channels associated with UAVs is still in its infancy. Therefore, in this paper, we use ray-tracing simulations to develop a novel Gaussian Mixture Model (GMM) for Air-to-Ground (A2G) channels. An urban environment with mean building heights of 10m, 20m, 50m, and 80m is considered to develop the proposed model. An extensive set of simulations are performed using a ray-tracing simulator, Wireless InSite®. Our results show that the Probability Density Function (PDF) of the received power or the path loss vary depending on the mean building height and can be modelled using a GMM. The proposed model is then validated by using it to generate PDFs of a certain test set of city environments.
Advances in Technologies for Boron Removal from Water: A Comprehensive Review

Boron overabundance in aquatic environment raises severe concerns about the environment and human health because it is toxic to various crops and induces many human and animal diseases with long-term consequences. In response to the boron pollution of water resources and the difficulty of eliminating boron from water for production and living purposes, this article summarizes the progress in research on boron removal technology, addressing the following aspects: (1) the reasons for the difficulty of removing boron from water (boron chemistry); (2) ecological/biological toxicity and established regulations; (3) analysis of different existing processes (membrane processes, resin, adsorption, chemical precipitation, (electric) coagulation, extraction, and combined methods) in terms of their mechanisms, effectiveness, and limitations; (4) prospects for future studies and possible improvements in applicability and recyclability. The focus of this paper is thus to provide a comprehensive summary of reported deboronation processes to date, which will definitely identify directions for the development of boron removal technology in the future.
“It felt like they were trying to destabilise us”: Parent assessment in UK children’s gender services

Abstract Background: Pediatric gender clinics have a long history of analyzing and scrutinizing parents of trans children. At present, gender services in countries like the UK continue to hold clinical sessions with parents of pre-adolescent transgender children, sometimes extending over many years. Clinician viewpoints dominate the limited existing literature, with little analysis of the perspectives of parents of trans children. Aims: The study aimed to understand the experiences that parents of socially transitioned pre-adolescent trans children have had in UK gender clinics. Methods: Data were drawn from semi-structured qualitative interviews with 30 UK-based parents of socially transitioned trans children – children who socially transitioned, for example, changed pronoun, under the age of eleven. This article analyzed a subset of a wider dataset, focusing on data from 23 parents relating to parental engagement with UK NHS gender clinics before their child reached adolescence. Results: Themes emerging from the dataset included parents feeling under a microscope, and parents finding gender clinic sessions judgemental, intrusive and inappropriate. Interviewees reported clinician discouragement of listening to and validating their children, as well as a lack of emotional support. Discussion: The article presents evidence of continued pathologisation and problematisation of childhood gender diversity in parental engagements with UK children’s gender clinics. It concludes by contrasting current UK practice as described in parental accounts with gender affirmative approaches to supporting parents of trans children.
The Azadirachta indica (Neem) Seed Oil Reduced Chronic Redox-Homeostasis Imbalance in a Mice Experimental Model on Ochratoxine A-Induced Hepatotoxicity

Liver damage severity depends on both the dose and the exposure duration. Oxidative stress may increase the Ochratoxine-A (OTA) hepatotoxicity and many antioxidants may counteract toxic liver function. The present study aims to investigate the hepatoprotective potential of Azadirachta indica A (A. indica; neem oil) seed oil to reduce acute oxidative disorders and residual OTA toxicity in a 28-day experimental model. The activity of antioxidant and hepatic enzymes, cytokines and the levels of oxidative stress biomarkers –MDA, GSPx, Hydroxiproline, GST, PCC, AGEs, PGC-1, and STIR-1 were analyzed by ELISA. The free radicals ROS and RNS levels were measured by EPR. The protective effects were studied in BALB/C mice treated with A. indica seed oil (170 mg/kg), alone and in combination with OTA (1.25 mg/kg), by gavage daily for 28 days. At the end of the experiment, mice treated with OTA showed changes in liver and antioxidant enzymes, and oxidative stress parameters in the liver and blood. A. indica oil significantly reduced oxidative stress and lipid peroxidation compared to the OTA group. In addition, the hepatic histological evaluation showed significant adipose tissue accumulation in OTA-treated tissues, while treatment with 170 mg/kg A. indica oil showed moderate adipose tissue accumulation.
Graphene Nanostructures by Pulsed Laser Ablation in Liquids: A Review

High-quality graphene has demonstrated remarkable mechanical, thermal, electronic, and optical properties. These features have paved the road for the introduction of graphene into numerous applications such as optoelectronics and energy devices, photodegradation, bioimaging, photodetectors, sensors, and biosensors. Due to this, graphene research has accelerated exponentially, with the aim of reaching a sustainable large-scale production process of high-quality graphene that can produce graphene-based technologies at an industrial scale. There exist numerous routes for graphene fabrication; however, pulsed laser ablation in liquids (PLAL) has emerged as a simple, fast, green, and environmentally friendly method as it does not require the use of toxic chemicals. Moreover, it does not involve the use of expensive vacuum chambers or clean rooms. However, the great advantage of PLAL is its ability to control the size, shape, and structure of the produced nanostructures through the choice of laser parameters and liquid used. Consequently, this review will focus on recent research on the synthesis of graphene nanosheets and graphene quantum dots via PLAL and the effect of experimental parameters such as laser wavelength, pulse width, pulse energy, repetition rate, irradiation time, and liquid media on the produced nanostructures. Moreover, it will discuss extended PLAL techniques which incorporate other methods into PLAL. Finally, different applications that utilize nanostructures produced by PLAL will be highlighted. We hope that this review will provide a useful guide for researchers to further develop the PLAL technique and the fabrication of graphene-based materials.
Emergency Disaster Information Delivery on Information-Centric Networking

Information-Centric Networking (ICN) is attracting attention as a content distribution method against increasing network traffic. On the other hand, emergency information is required to be reliably transmitted even under network traffic congestions. This paper analyses network congestions of ICN. And we propose a new method that a router adds emergency information to contents in order to dispatch the emergency information when network congestions have happened. As a result of the simulation, we confirmed that the proposed method can improve the data arrival rate of emergency information by almost 40% compared to the usual method.
Nephrotic syndrome in children during the COVID-19 pandemic

The COVID-19 pandemic resulted in public health measures and fewer viral infections, which trigger the nephrotic syndrome. Our objectives were to characterize the effect of the COVID-19 pandemic on children with nephrotic syndrome. This single-center retrospective chart review compared children with nephrotic syndrome one year before the pandemic with the first wave of the pandemic. Epidemiologic events, clinical characteristics, and health care utilization were compared using paired t-tests, Fisher’s exact tests and Wilcoxon Rank Sum tests. Among 96 children the mean age was 10.7 ± 5.28 years. The distribution was minimal change disease (16.7%), focal segmental glomerulosclerosis (12.5%), membranous nephropathy (1%) and not biopsied (69.8%). Medication responsiveness was steroid-sensitive (25%), frequently relapsed (54%) and steroid-resistant (20.8%). There were 14 new diagnoses of nephrotic syndrome pre-pandemic and 18 during the pandemic. Fewer relapses during the pandemic were likely due to fewer viral illnesses from public health measures during the pandemic.
Enhanced Two-Way Communication for Battery-Free Wireless Sensors: SWIPT with IM3 Backscattering

This paper presents a combined multi-tone simultaneous wireless information and power transfer (SWIPT)/third-order intermodulation (IM3) backscattering architecture. This integrated system uses the diode's nonlinear behaviour as well as frequency division duplex (FDD) to perform three critical functions: downlink communication, uplink communication, and energy harvesting. Measurements of the prototype design prove that the downlink and uplink communication does not affect the wireless power transfer. A downlink data rate of 1 kbps, 4.84 dB IM3 backscattering dynamic range, and 30% power conversion efficiency demonstrated when the tag is fed with 100 $\mu W$ RF power.
An Inductor-First Single-Inductor Multiple-Output Hybrid DC–DC Converter With Integrated Flying Capacitor for SoC Applications

With the increasing complexity of highly integrated system on chips (SoCs), the power management system (PMS) is required to provide several power supplies efficiently for individual blocks. This paper presents a single-inductor multiple-output (SIMO) inductor-first hybrid converter that generates three outputs between 0.4V and 1.6V from a 1.8V input. The proposed multiple-output hybrid power stage can improve the conversion efficiency by reducing inductor current while extending the output voltage range compared with the existing hybrid topologies. In addition, the proposed converter employs an on-chip switched-capacitor power stage (SCPS) with a dual-switching frequency technique, resulting in a fast response time, low cross-regulation, and reduced number of on-chip pads. Measurement results show that the converter achieves a peak efficiency of 87.5% with the maximum output current of 450mA. The converter is integrated with a fast voltage regulation loop with 500MHz system clock to achieve a less than 0.01mA/mV cross-regulation and a maximum 20mV overshoot at full-load transient response. The design is fabricated in the standard 180nm CMOS technology.
Dynamic Super Round-Based Distributed Task Scheduling for UAV Networks

Networks of Unmanned Aerial Vehicles (UAVs) are emerging in many application domains, e.g., military surveillance. To perform collaborative tasks, the involved UAVs exchange several types of information, e.g., sensor data and commands. The major question here is how to schedule the tasks under dynamic traffic flows to provide network services. Existing solutions use the Round-Robin Strategy (RRS), where the tasks are scheduled statistically by dividing the time into fixed-length rounds. However, the RRS wastes significant network and device resources due to task scheduling in each round. This paper proposes DROVE– a novel clustering approach that allows the UAVs for dynamic task scheduling. However, determining the task scheduling is crucial, as it significantly affects several network parameters, e.g., throughput. Therefore, we devise the problem of distributed task scheduling under dynamic traffic flow scenarios to optimize the throughput. We propose a clustering task scheduling algorithm to serve dynamic traffic flows. Particularly, we integrate the dynamic traffic flows into the Lyapunov drift analysis framework, and determine the throughput optimality of our proposed scheduling algorithm. We perform extensive simulations to validate the effectiveness of DROVE. The results show that DROVE outperforms the state-of-the-art solutions in terms of energy consumption, clustering overhead, throughput, end-to-end delay, flow success rate and packet drop rate.
The reach of the ATLAS experiment in SUSY parameter space

Already with very first data, the ATLAS experiment should be sensitive to a SUSY signal well beyond the regions explored by the Tevatron. We present a detailed study of the ATLAS discovery reach in the parameter space for various SUSY models. The expected uncertainties on the background estimates are taken ito account.