Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on a Precision Positioning Stage Based on Piezoelectric Actuators and it's Validation

Ultrasonic micro-motor gathers a lot of advantages,such as high resolution,good dynamic performance,small volume,compact structure,low cost,high output force,quickly response,high precision and no electromagnetic interference etc.However,it has some shortcomings,such as vertical displacement,lag error,and small travel,especially those shortcomings have many seriously affection on the positioning accuracy and 3Dprocessing because of increasing compensation after electrode loss.Based on ultra-precision 3Dplatform of piezoelectric motor driver in the paper,its large travel and small step is combined by adopting macroscopic-microcosmic and double-direction drive control system.After testing of micro-precision worktable,the running curves are obtained.Results show it has good dynamic and steady performance,realizing ultra-low speed,fast response,high resolution and high precision of two-way stepping movement.Simultaneously,it has achieved the sub-micrometer to nanometer positioning accuracy and satisfied the positioning accuracy of micro-EDM.The research provides significant scientific reference for further development of piezoelectric motor application in ultra precision motion system position precision of the system.
Genome-wide detection of human variants that disrupt intronic branchpoints

Pre-mRNA splicing is initiated with the recognition of a single-nucleotide intronic branchpoint (BP) within a BP motif by spliceosome elements. Fifty-six rare variants in 44 human genes have been reported to alter splicing and cause disease by disrupting BP. However, until now, no computational approach has been available to efficiently detect such variants in next-generation sequencing (NGS) data. We established a comprehensive human genome-wide BP database by integrating existing BP data, and by generating new BP data from RNA-seq of lariat debranching enzyme DBR1-mutated patients and from machine-learning predictions. We in-depth characterize multiple features of BP in major and minor introns, and find that BP and BP-2 (two-nucleotides upstream of BP) positions exhibit a lower rate of variation in human populations and higher evolutionary conservation than the intronic background, whilst being comparable to the exonic background. We develop BPHunter as a genome-wide computational approach to systematically and efficiently detect intronic variants that may disrupt BP recognition in NGS data. BPHunter retrospectively identifies 48 of the 56 known pathogenic BP mutations in which we summarize a strategy for prioritizing BP mutation candidates, and the remaining 8 all create AG dinucleotides between BP and acceptor site which is probably the reason for mis-splicing. We demonstrate the utility of BPHunter prospectively by using it to identify a novel germline heterozygous BP variant of STAT2 in a patient with critical COVID-19 pneumonia, and a novel somatic intronic 59-nucleotide deletion of ITPKB in a lymphoma patient, both of which we validate experimentally. BPHunter is publicly available from https://hgidsoft.rockefeller. edu/BPHunter and https://github.com/casanova-lab/BPHunter.
Fleeting Effects of Incentives: Adult Age Differences in ERP Measures of Motivated Attention

Reward-based motivation is associated with transient and sustained dopaminergic activity and with modulatory effects on attention and cognitive control. Age-related changes in the dopamine system are well documented, but little is known about age differences in the temporal dynamics of motivational influences on cognitive functions. The current study examined the effects of financial incentives on visual attention using event-related potentials (ERPs). Participants (26 younger, aged 18-33; 24 older, aged 65-95) completed an incentivized flanker task in which trial-level incentive cues signaled the availability of performance-contingent reward, and subsequent alerting cues signaled the onset of the flanker target. ERP components of interest included incentive-cue P2 and CNV, alerting-cue N1, target N1, and target P3. Transient effects of incentives were assessed by comparing ERP amplitudes across incentive and non-incentive trials from mixed-incentive blocks. Younger adults showed transient effects of incentives on all components, whereas older adults showed effects for incentive-cue P2 and alerting-cue N1 only. Sustained effects of incentives were assessed by comparing ERP amplitudes across non-incentive trials from mixed-incentive blocks and non-incentive trials from pure non-incentive blocks. Both age groups showed sustained effects of incentives on cue-locked ERPs, but only younger adults showed sustained effects on target-locked ERPs. Reaction-time patterns mirrored the ERP findings, in that younger adults showed greater incentive-based modulation than older adults. Overall, these findings suggest that both transient and sustained effects of incentives on visual attention are more fleeting for older than younger adults, consistent with widespread alterations in dopaminergic neuromodulation in aging.
A coupled atrioventricular-aortic setup for in-vitro hemodynamic study of the systemic circulation: Design, fabrication, and physiological relevancy

In-vitro models of the systemic circulation have gained a lot of interest for fundamental understanding of cardiovascular dynamics and for applied hemodynamic research. In this study, we introduce a physiologically accurate in-vitro hydraulic setup that models the hemodynamics of the coupled atrioventricular-aortic system. This unique experimental simulator has three major components: 1) an arterial system consisting of a human-scale artificial aorta along with the main branches, 2) an artificial left ventricle (LV) sac connected to a programmable piston-in-cylinder pump for simulating cardiac contraction and relaxation, and 3) an artificial left atrium (LA). The setup is designed in such a way that the basal LV is directly connected to the aortic root via an aortic valve, and to the LA via an artificial mitral valve. As a result, two-way hemodynamic couplings can be achieved for studying the effects that the LV, aorta, and LA have on each other. The collected pressure and flow measurements from this setup demonstrate a remarkable correspondence to clinical hemodynamics. We also investigate the physiological relevancies of isolated effects on cardiovascular hemodynamics of various major global parameters found in the circulatory system, including LV contractility, LV preload, heart rate, aortic compliance, and peripheral resistance. Subsequent control over such parameters ultimately captures physiological hemodynamic effects of LV systolic dysfunction, preload (cardiac) diseases, and afterload (arterial) diseases. The detailed design and fabrication of the proposed setup is also provided.
Optimization And Water Resources Management

This introductory chapter includes some thoughts on the essence of optimization and on its role in water resources management. First, the relevance of the notion of optimization to most scientifi c fi elds is pointed out, using the example of Aristotle’s Ethics. Then the importance of optimal management of water resources is stressed and certain issues related to the defi nition of optimization problems and to the role of fl ow simulation models are selectively discussed.
LDO less non capacitive on-chip dynamic output voltage regulator for self-powered IoT applications

In this paper, a LDO less non capacitive dynamic output voltage regulator has been proposed for self-powered IoT applications. Strong arm latch has been employed to provide a regulated supply to the load from an energy harvester continuously. It diverts the harvester's energy to a storage unit in case of excess energy available than the load requirement and supplies this stored energy back to the load in case energy harvester is not able to supply the load requirement continuously. The simulations have been carried out with LTspice in 0. 18µm CMOS technology using tsmc model.
Understanding Shoulder Surfer Behavior Using Virtual Reality

We explore how attackers behave during shoulder surfing. Unfortunately, such behavior is challenging to study as it is often opportunistic and can occur wherever potential attackers can observe other people's private screens. Therefore, we investigate shoulder surfing using virtual reality (VR). We recruited 24 participants and observed their behavior in two virtual waiting scenarios: at a bus stop and in an open office space. In both scenarios, avatars interacted with private screens displaying different content, thus providing opportunities for shoulder surfing. From the results, we derive an understanding of factors influencing shoulder surfing behavior.
Technique for Detecting Computer Attacks on a Wi-Fi Networks

According to Cisco's forecast, 52.6% of the world's Internet traffic will be transmitted via Wi-Fi technology in 2021. Wireless connection to Wi-Fi network makes possible attacks through deauthentication and rogue access points. In this regard, it becomes necessary to timely detect attacks on a Wi-Fi network. The article discusses technique for detecting computer attacks on a Wi-Fi network and ways to assess its effectiveness. The results of the experiment with the model are presented.
Subjective and Objective Analyses of Collaboration and Co-Presence in a Virtual Reality Remote Environment

Remote collaboration in virtual reality has gained attention and proved to be a viable solution for providing effective collaboration environments for physically distant collaborators. This study compares head-mounted display (HMD)- and computer-based remote collaboration solutions that allow users to interact with each other through immersive environments. Analyzing remote collaboration in immersive environments requires understanding group interactions and personal experiences. For this purpose, a 3D object assembly task was performed by 10 participants using self-reported surveys and physiological measures to investigate the effectiveness of collaboration from the users' perspective. The results showed that the HMD-based remote collaboration in a virtual reality environment increased the sense of co-presence among the users.
Technology of Putting Infrared Sensors for Remote Monitoring of Power Facilities by UAS Into Operation

The use of unmanned aircraft systems (further on referred to as UAS) for monitoring power facilities is a relevant and promising way of developing a modern diagnostic process and methods for preventing accidents at power supply equipment.The main purpose of this type of work is remote data collection from various sensors which are on board the UAS. It is necessary to have cameras of various spectra in order to obtain the comprehensive information about the state of power facilities. For these cameras to perform efficiently, various factors are to be taken into account.The article will consider infrared (further on referred to as IR) sensors and the technology of putting them into operation on board the UAS. IR cameras can determine the temperature of power supply equipment, but their use is linked with various difficulties, which must be taken into account at each setting of the sensors before the UAS takes off.
Emotional Avatars: Effect of Uncanniness in Identifying Emotions using Avatar Expressions

This work analyses the effect of uncanniness behaviour in identifying emotions from different humanoid avatar representations. Expressive avatars play a vital role in immersive environments. However, technical limitations in replicating subtle emotional cues using realtime expression conversion techniques create an uncanniness to the viewers. Hence, achieving the desired emotional awareness is arguable. Therefore, using an avatar representation resistant to uncanniness in systems sensitive to emotional changes is vital. Therefore, here we analyse the level of uncanniness noticed by people for different avatars exhibiting various emotions using expressive faces and the behavioural trends of people in catching emotion-related uncanniness.
Denoising of Maritime Unmanned Aerial Vehicles Photography Based on Guidance Correlation Pixel Sampling and Aggregation

In this paper, we proposed a guidance correlation pixel Sampling and aggregation image denoising for maritime Unmanned Aerial Vehicles(UAVs) photography, providing a reliable data base for maritime reconnaissance work. The overall step is mainly composed of two parts, pixel sampling and pixel aggregation. To improve the content correlation of sampled pixels, we propose a guided sampling scheme based on the basic estimated map and extend this algorithm to the restoration of maritime UAVs image. Finally, a UAVs image denoising system is shown. Our experimental results show that the proposed algorithm can effectively remove noise and achieves 32.98dB and 31.83dB in Set12 and BSD68 datasets with less and image distortion. In the actual scene, the PSNR of our denoising algorithm has reached 35.33dB, meets the basic needs of practical vision and follow-up research.
Parallel Operation of a Synchronous Generator and VSG Using Multilevel Energy Converters

The article presents analysis of the process of pre-synchronization and synchronization of AC and DC sources connected to a common static load. It is proposed to use power converters of DC power sources based on multilevel structures of voltage source inverters, which improves the quality of the generated voltage, reduce the required voltage on a separate battery assembly. It simplifies the task of balancing voltages on elementary battery cells, implements an uninterruptible power supply device on one converter thus increasing reliability and functionality of the system. The feasibility of the proposed approach is confirmed by a comparative analysis of electricity quality in the case of using two-level and multilevel structures of voltage source inverters by means of mathematical modeling in Matlab & Simulink.
Perceptually-Based Optimization for Radiometric Projector Compensation

Radiometric compensation techniques have been proposed to manipulate the appearance of arbitrarily textured surfaces using projectors. However, due to the limited dynamic range of the projectors, these compensation techniques often fail under bright environmental lighting or when the projection surface contains high contrast textures, resulting in clipping artifacts. To address this issue, we propose to apply a perceptually-based tone mapping technique to generate compensated projection images. The experimental results demonstrated that our approach minimizes the clipping artifacts and contrast degradation under challenging conditions.
Graphene antenna on polyamide for 2.4GHz WLAN applications

This paper deals with the design, simulation and fabrication of two graphene antennas. CPW fed rectangular patch antenna with U-shaped slot and inverted U-shaped slot are named as design-1 and design-2 respectively. The resonance frequency of both antennas is 2.4GHz (sub 6GHz range). The antennas are designed to work within the range available for Wi-Fi use. Polyamide kapton tape of thickness 100µm and relative permittivity of 3.5 is used as a substrate. Graphene is used to make the conducting patch, feed, and grounds of the antenna design. Two antenna designs are compared based on different antenna parameters and the best of the two is studied extensively throughout the paper.
Empathy building ‘in the wild’ - a reflection on an avoidance of the emotional engagement

In 2019 we were asked to prepare a VR stand providing an opportunity to experience applications with social impact during an open event. Every visitor of our stand could choose among several applications (therapeutic, relaxing vs educational vs perspective-taking & empathy-building) and after testing was asked (optionally) to fill in the shortened immersion questionnaire $(\mathrm{N}=44, \text{age}\ 8\ \text{to}\ 62,\ \text{mean}: 31)$. We have noticed that although people declared they appreciate this kind of experiences, they avoided them (probably because of the potential emotional labor). In this article we share insights and conclusions on differences in conducting research on VR social applications in the controlled laboratory conditions, and in the field testing. Taking into account advantages and disadvantages of this approach as well as methodological challenges, we also advocate for taking this kind of research as a supplementary for typical laboratory research.
Automated Sleep Staging Classification System Based On Convolutional Neural Network Using Polysomnography Signals

Manual inspection of sleep staging is one of the critical challenges for the last few years because it is a time-consuming process, laborious task, and also gives a heavy burden to the sleep experts for manipulating the entire sleep recording, which alternatively affects their performance. To overcome this challenging issue, we propose an efficient approach to improve the sleep staging accuracy and multi-class classification for sleep behavior analysis using a One-dimensional Convolutional Neural Network (1D-CNN) model with the inputs of polysomnography signal. Methods: The proposed system considers the base model as 1D-CNN model because of its effectiveness, robust and high accuracy to automatically classify the sleep stages from the different medical-conditioned subjects. The proposed system has used stacking ensemble learning techniques for training and classification to improve the sleep staging accuracy for multi-class classification problems and make the system more robust and accurate predictions. Results: The proposed model has been validated on the SHHS dataset using 10-fold cross-validation techniques. This experimental results for the entire fold have been reported for the 1D-CNN for five to two sleep states classification problems. It has been found that the results of the proposed model are incomparable to the earlier state-of-the-art works in terms of classification accuracy. The proposed model is effective for clinical trials during the diagnosis of different types of sleep related disorders, and it becomes helpful to the sleep experts during the diagnosis process.
Whac-A-Mole: Exploring Virtual Reality (VR) for Upper-Limb Post-Stroke Physical Rehabilitation based on Participatory Design and Serious Games

This paper describes a Human-Centered Design process aimed at understanding how Virtual Reality (VR) can assist in post-stroke physical rehabilitation. Based on insights from stroke survivors and healthcare professionals, a serious game prototype is proposed. We focused on upper-limb rehabilitation, which inspired the game narrative and the movements users must perform. The game supports two modes: 1- normal version - users can use any arm to pick a virtual hammer and hit objects; 2- mirror version - converts a traditional approach to VR, providing the illusion that the arm affected by the stroke is moving. These were evaluated through a user study.
A Literature Mini-Review of Transcranial Direct Current Stimulation in Schizophrenia

Transcranial direct current stimulation (tDCS) is a non-invasive neurostimulation method that utilizes the effect of low-current on brain tissue. In recent years, the effect of transcranial direct current stimulation has been investigated as a therapeutic modality in various neuropsychiatric indications, one of them being schizophrenia. This article aims to provide an overview of the potential application and effect of tDCS in treating patients with schizophrenia. A literature search was performed using the PubMed, Web of Science, and Google Scholar databases for relevant research published from any date until December 2021. Eligible studies included those that used randomized controlled parallel-group design and focused on the use of transcranial direct current stimulation for the treatment of positive, negative, or cognitive symptoms of schizophrenia. Studies were divided into groups based on the focus of research and an overview is provided in separate sections and tables in the article. The original database search yielded 705 results out of which 27 randomized controlled trials met the eligibility criteria and were selected and used for the purpose of this article. In a review of the selected trials, transcranial direct current stimulation is a safe and well-tolerated method that appears to have the potential as an effective modality for the treatment of positive and negative schizophrenic symptoms and offers promising results in influencing cognition. However, ongoing research is needed to confirm these conclusions and to further specify distinct application parameters.
Distinct Functional Metagenomic Markers Predict the Responsiveness to Anti-PD-1 Therapy in Chinese Non-Small Cell Lung Cancer Patients

Background Programmed death 1 (PD-1) and the ligand of PD-1 (PD-L1) are central targets for immune-checkpoint therapy (ICT) blocking immune evasion-related pathways elicited by tumor cells. A number of PD-1 inhibitors have been developed, but the efficacy of these inhibitors varies considerably and is typically below 50%. The efficacy of ICT has been shown to be dependent on the gut microbiota, and experiments using mouse models have even demonstrated that modulation of the gut microbiota may improve efficacy of ICT. Methods We followed a Han Chinese cohort of 85 advanced non-small cell lung cancer (NSCLC) patients, who received anti-PD-1 antibodies. Tumor biopsies were collected before treatment initiation for whole exon sequencing and variant detection. Fecal samples collected biweekly during the period of anti-PD-1 antibody administration were used for metagenomic sequencing. We established gut microbiome abundance profiles for identification of significant associations between specific microbial taxa, potential functionality, and treatment responses. A prediction model based on random forest was trained using selected markers discriminating between the different response groups. Results NSCLC patients treated with antibiotics exhibited the shortest survival time. Low level of tumor-mutation burden and high expression level of HLA-E significantly reduced progression-free survival. We identified metagenomic species and functional pathways that differed in abundance in relation to responses to ICT. Data on differential enrichment of taxa and predicted microbial functions in NSCLC patients responding or non-responding to ICT allowed the establishment of random forest algorithm-adopted models robustly predicting the probability of whether or not a given patient would benefit from ICT. Conclusions Overall, our results identified links between gut microbial composition and immunotherapy efficacy in Chinese NSCLC patients indicating the potential for such analyses to predict outcome prior to ICT.