Miracle-dz/UniFAR-FTUs huggingface dataset:
Inclusion of Bidirectional Angular Positioning Deviations in the Kinematic Model of a Six-DOF Articulated Robot for Static Volumetric Error Compensation

To improve a robot’s absolute positioning accuracy, researchers have extensively studied the robot kinematic model containing position and orientation errors of rotary axis average lines, widely known as Denavit–Hartenberg (D-H) parameters. To further improve the absolute positioning accuracy of industrial robots, this article proposes a novel kinematic model and its identification scheme. The proposed kinematic model for a serial-linked industrial robot contains the bidirectional angular positioning deviations of each rotary axis, represented in a lookup table, in addition to its D-H parameters. The angular positioning deviations of the rotary axes are modeled as a function of angular command positions, along with the direction of rotation to model the influence of backlash. This article also proposes a novel approach to identify the proposed kinematic model with the bidirectional angular positioning deviations using a laser tracker with indexing each rotary axis at specified angular positions (“circle point method”). Moreover, the model-based compensation technique is being experimentally investigated to validate the prediction accuracy of the proposed model. The findings of the experiment show that the proposed model enhances the robot’s absolute positioning accuracy significantly over the entire workspace.
Application of VR Technology in Brand IP Image Design

Virtual reality (VR) refers to the computer-generated simulation of a three-dimensional image environment that can be interacted within a seemingly physical way by a person using special electronic equipment and making people interactive and immersive. VR technology is applied to communication activities, producing VR communication. VR technology is applied to news reports, giving birth to the emergence of VR news. The great significance of VR technology for news communication lies in the comprehensive intake and recording and transmission of news site materials so that news events can “reproduce” and “restore. ” The most prominent feature of VR transmission is immersion. Immersivity is mainly reflected in the perceptual system and the behavioral system of the human body. The immersion of perception system includes visual immersion, auditory immersion, touch immersion, and other sensory immersion; behavioral system immersion includes the immersion of language system, direction system immersion, and expression system immersion. Immersive communication has experienced three development stages: interactive communication, invasive communication, infiltration, and audience experience. There are three hidden dangers in VR technology in the communication. One is the hidden danger of the technical operation level: the lack of security and stability of the production process may lead to the disappearance of the traditional reporter, the second is the ethical hidden danger: the degradation of “audience” to “mass,” and third is “body” weakening the authority of “addiction”: the emergence of “brain in the cylinder,” the emergence of snooping feast, and the formation of exposed carnival. There are three aspects to prevent VR hidden dangers, layout and top-level design, improve security, and communication efficiency, promote industrial application, enhance user stickiness, strengthen brand building, and create ace IP and quality content.
A flexible and easy-to-use open-source tool for designing functionally graded 3D porous structures

ABSTRACT Advances in additive manufacturing technologies are leading to an increased interest in the design of intricate 3D geometries for applications ranging from aerospace to biomedical engineering. In this paper, we present ASLI (A Simple Lattice Infiller), a cross-platform tool for the generation of cellular solid structures that allows users to provide implicitly defined lattice infills to 3D objects by specifying the desired local unit cell type, size and feature. It is written in C++ and relies on the open-source libraries Mmg and CGAL to handle the implicit domain discretisation. Although developed to design lattice infills for skeletal tissue engineering applications, ASLI can be used for any application that requires the user to provide lattice infills to 3D objects. Its capabilities are shown through a series of examples that demonstrate complex designs can easily be accomplished. The code is published under an open-source license and is available for download at github.com/tpms-lattice/ASLI.
Waste-Derived Cellulosic Fibers and Their Applications

The use of bio-based materials has become a focus of research nowadays. For the development of new generations of advanced resources, renewable and available resources must be combined with advanced technologies. Researchers have looked into biomass and waste cellulosic materials as sustainable sources for nano-crystalline cellulose extraction. Besides the different treatment methods suitable for various applications, this review aims to provide integrated details on the extraction methods and applications of cellulosic fibers and cellulose nanocrystals derived from wastes of different sources. There are numerous applications including building materials, electronics, furniture, automobiles, medical applications, sports goods, filtrations, water purification, and delivery systems of drugs which have been discussed.
Clinical Value of Measurable Residual Disease in Acute Lymphoblastic Leukemia

Abstract Measurable (minimal) residual disease (MRD) status in acute lymphoblastic leukemia (ALL) has largely superseded the importance of traditional risk factors for ALL, such as baseline white blood cell count, cytogenetics, and immunophenotype, and has emerged as the most powerful independent prognostic predictor. The development of sensitive MRD techniques, such as multicolor flow cytometry (MFC), quantitative polymerase chain reaction (PCR), and next-generation sequencing (NGS), may further improve risk stratification and expand its impact in therapy. Additionally, the availability of highly effective agents for MRD eradication, such as blinatumomab, inotuzumab ozogamicin, and chimeric antigen receptor (CAR) T-cell therapies, enabled the development of frontline regimens capable of eradicating MRD early in the treatment course. While long-term follow-up of this approach is lacking, it has the potential to significantly reduce the need for intensive post-remission treatments, including allogeneic bone marrow transplantation, in a significant proportion of patients with ALL.
A Data Augmentation Method for Prohibited Item X-Ray Pseudocolor Images in X-Ray Security Inspection Based on Wasserstein Generative Adversarial Network and Spatial-and-Channel Attention Block

For public security and crime prevention, the detection of prohibited items in X-ray security inspection based on deep learning has attracted widespread attention. However, the pseudocolor image dataset is scarce due to security, which brings an enormous challenge to the detection of prohibited items in X-ray security inspection. In this paper, a data augmentation method for prohibited item X-ray pseudocolor images in X-ray security inspection is proposed. Firstly, we design a framework of our method to achieve the dataset augmentation using the datasets with and without prohibited items. Secondly, in the framework, we design a spatial-and-channel attention block and a new base block to compose our X-ray Wasserstein generative adversarial network model with gradient penalty. The model directly generates high-quality dual-energy X-ray data instead of pseudocolor images. Thirdly, we design a composite strategy to composite the generated and real dual-energy X-ray data with background data into a new X-ray pseudocolor image, which can simulate the real overlapping relationship among items. Finally, two object detection models with and without our data augmentation method are applied to verify the effectiveness of our method. The experimental results demonstrate that our method can achieve the data augmentation for prohibited item X-ray pseudocolor images in X-ray security inspection effectively.
Robotic micromanipulation: b) grippers for biological objects

Recent progress in the field of microrobotics tightly linked to an ability to grab an object firmly without the damage to the surface and structure. Process of biological object grabbing by microgrippers faces numerous limitations in the mechanical, electric and thermal domains; these limitations varies from case to case with different objects, therefore, analysis in this area was an aim of this review. This paper covers an area of micrometric size biological object manipulation and performs an analysis of used actuators and kinematic chains of the grippers in the sense of their application. Limitations and restriction of microgrippers applications analysed along available publications in numerous recent references as well as their successful implementation history. Paper provides result of analysis as compact big picture, which will be useful for researchers and designers in the area of microrobotics. electromagnetic, piezoelectric.
AN ADAPTIVE ENERGY EFFICIENT MAC PROTOCOL FOR WIRELESS SENSOR NETWORKS

Sensor networks are deployed in remote locations with limited processor capabilities, memory capacities, and battery supplies. Wireless Sensor Networks (WSN) detects environmental information with sensors in remote settings. One problem facing WSNs is the inability to resupply power to these energy-constrained devices due to their remoteness. Therefore to extend a WSN's effectiveness, the lifetime of the network must be increased by making them as energy efficient as possible. An energy-efficient medium access control (MAC) can boost a WSN's lifetime. This paper focuses on a protocol stack solution that deals with MAC layer, that minimizes the energy consumption and delay required to transmit packets across the network. It is based on Sensor Medium Access Control (S-MAC) called Adaptive SMAC protocol designed for sensor networks. It enables low duty cycle operation in a multi-hop network and common sleep schedules to reduce control overhead and enable traffic adaptive wakeup. To reduce control overhead and latency, introduces coordinated sleeping among neighboring nodes. It is a contention based protocol based on CSMA/CA mechanism. This protocol is simulated in NS-2 and performance evaluated using various topologies under various traffic conditions. In addition with this we tried to improve the energy efficiency of Adaptive SMAC with the help of a new design called Adaptive Cross MAC protocol
An effective method to summarise the outcomes of questionnaire-based studies in systematic reviews

Abstract With an increased number of questionnaire-based knowledge, attitude, practice and other types of studies, there is a need to perform evidence-based research in such designs as well. The systematic reviews (SR) and meta-analyses (MA) of the questionnaire-based studies are difficult to conduct and summarise due to the wide variations in the questions included in each of them. The presentation of these reviews often leads to ambiguous conclusions, and meta-analysis is not possible due to wide heterogeneity. This paper aims to highlight a method known as the ‘Knowledge-Attitude-Practice’ or ‘KAP’ Heat Map, which was developed and validated for the effective presentation of the outcomes of varied questionnaires in systematic reviews.
Numerical Simulation of Interior Flow in Vortex-Pump for Liquid-solid Two-phase Medium with Small Size Particles

To study the flow characteristics of vortex-pump,solid-liquid two-phase turbulent flow in vortex-pump centrifugal rotor is simulated by using Fluent software with Eulerian model,standard κ-eturbulence model and SIMPLEC algorithm.Distribution of volume fraction is analyzed for different solid particle diameters and sandy volume fractions.Near the exit of rotor,solid particles tend towards suction surface at the conditions of small particle diameter and low sandy volume fraction.However,solid particles are mainly concentrated on pressure surface,thus the wear of pressure surface will be accelerated.From simulation results it can be concluded that hydro head of impeller and efficiency decline with the increase of volume fraction or at the bigger particle diameter.Changing in volume fraction impact on hydro head and efficiency is more obvious.
IPA-Based Service Quality Evaluation

Given existing problems with service quality evaluation,a criterion system of service quality was devised,and service quality was evaluated based on the idea and methodology of importance-performance analysis(IPA). The service quality evaluation process utilized initial evaluation information obtained by customer questionnaires.Criterion performance was then calculated from the evaluation information.Next,taking into account the causal relationship between criterion importance and criterion performance in service quality evaluation,criterion importance was computed by constructing a BP neural network.Evaluation results were analyzed using IPA.An example is provided to show the feasibility and validity of the proposed method.
It's all about the signal routing: understanding the reliability of qca circuits and systems

Much has been written and predicted about the demise of Moore’s law in advancing computing technology. While many of these predictions have fallen by the wayside, the end may be approaching since the ”red brick wall” (areas where scaling progress may end if breakthroughs are not identified) is barely being pushed further into the future. As a result, numerous nanoelectronic devices are being investigated to determine if they can augment or replace silicon-based transistors. Due to a variety of factors, a significant challenge when building a system from any of these devices is how to produce a reliable, predictable system from unreliable components with unpredictable behavior? In this dissertation, the reliability aspects of a specific nanoelectronic architecture – Quantum-dot Cellular Automata (QCA) – are explored. QCA is a unique architecture to explore since the same basic device, a simple cell, is used to implement both logic and interconnect components. The device itself can be implemented using different physical properties, which in turn, influences how the signal routing within the QCA circuits and systems should be designed. This dissertation computes the reliability of QCA circuits and systems based on the reliabilities of the underlying components. This is used to identify how reliable the components should be to achieve a target circuit or system reliability and to identify which components are the most critical to circuit reliability. Additionally, various techniques for improving reliability through the use of hardware redundancy are evaluated to determine how a reliable QCA system should be designed. Lastly, various organizations for a specific interconnect component, a straight wire segment, built from a specific device type, are compared to determine how reliable a component can be. Throughout this dissertation, a constant theme is observed: the organization and reliability of the signal routing has a major impact on circuit and system reliability.
A DDES Model with Subgrid-scale Eddy Viscosity for Turbulent Flow

The original (delayed) detached-eddy simulation ((D)DES), a widely used and efficient hybrid turbulence method, is confronted with some flaws containing grid-induced separation (GIS), log-layer mismatch (LLM), and slow RANS-LES transition. A novel hybrid turbulence model, namely production-limited eddy simulation (PLES), depleting the production through introducing the subarid-scale eddy viscosity is proposed. The simulation data of the zero-pressure gradient boundary layer proves that a good performance in mitigating the GIS issue is obtained from the PLES model. The results of the channel flows reveal that the PLES model has eliminated the LLM of the velocity. A good conformity is given for the backward-facing step flow in the PLES simulation, which proves that the PLES model is validated for complex flow. More turbulent scales in the shear layer are captured by the PLES model, which testifies that the PLES model has a faster RANS/LES switch than the IDDES model. The PLES model has a good performance in predicting the cylinder flow with coarser grid resolution. Due to the new LES mode, the PLES model behaves better than the IDDES model in simulating the cylinder flow. Furthermore, the PLES model allows one to use different LES model in the LES portion for other complex flows.
Paeoniflorin Upregulates Mitochondrial Thioredoxin of Schwann Cells to Improve Diabetic Peripheral Neuropathy Indicated by 4D Label-Free Quantitative Proteomics

Diabetic peripheral neuropathy (DPN) is a diabetic complication characterized by demyelination. The pathogenesis of DPN has not been fully elucidated, thus lacking therapies. In the current study, we aimed to confirm whether paeoniflorin (PF) could improve DPN by upregulating mitochondrial thioredoxin (Trx2) based on 4D Label-free proteomic experiments of Schwann cells (SCs) mitochondria. Firstly, PF increased the expression of mitochondrial processing peptidase α (Pmpca) and small ubiquitin-related modifier 1 (Sumo1) to increase mitochondrial protein processing of Trx2. Then, PF increased the protein expression of Trx reductase 2 (TrxR2) and peroxiredoxin 3 (Prx3), which belong to mitochondrial Trx systems. Accordingly, PF decreased mitochondrial reactive oxygen species (ROS) while increasing mtDNA and mitochondrial membrane potential to improve mitochondria function under high glucose environment. Furthermore, total glucosides of paeony capsules (TGP), containing more than 90% PF, increased the Trx2, TrxR2, and Prx3 levels in sciatic nerve of DPN rats, thus reducing demyelination as well as improving mechanical pain threshold, thermal pain threshold, motor nerve conduction velocity (MNCV), and sensor nerve conduction velocity (SNCV). Overall, these results suggest that PF could provide protection for DPN by upregulating Trx2.
A contemporary survey of bumble bee diversity across the state of California

Abstract Bumble bees (genus Bombus) are important pollinators with more than 260 species found worldwide, many of which are in decline. Twenty‐five species occur in California with the highest species abundance and diversity found in coastal, northern, and montane regions. No recent studies have examined California bumble bee diversity across large spatial scales nor explored contemporary community composition patterns across the state. To fill these gaps, we collected 1740 bumble bee individuals, representing 17 species from 17 sites (~100 bees per site) in California, using an assemblage monitoring framework. This framework is intended to provide an accurate estimate of relative abundance of more common species without negatively impacting populations through overcollection. Our sites were distributed across six ecoregions, with an emphasis on those that historically hosted high bumble bee diversity. We compared bumble bee composition among these sites to provide a snapshot of California bumble bee biodiversity in a single year. Overall, the assemblage monitoring framework that we employed successfully captured estimated relative abundance of species for most sites, but not all. This shortcoming suggests that bumble bee biodiversity monitoring in California might require multiple monitoring approaches, including greater depth of sampling in some regions, given the variable patterns in bumble bee abundance and richness throughout the state. Our study sheds light on the current status of bumble bee diversity in California, identifies some areas where greater sampling effort and conservation action should be focused in the future, and performs the first assessment of an assembly monitoring framework for bumble bee communities in the state.
Painting Modeling Language Based on Convolution Neural Networks in Digital Media Art

Digital media, as a high-tech method, has gradually affected all aspects of social production, including artistic creation, in the information age. Contemporary painting art, as an important form of artistic expression, will inevitably be baptized by digital media in the tide of time. The color of digital media ushers in a new era in contemporary painting. The development of deep learning makes the research field of artificial intelligence move towards a deeper and more practical level. Among them, CNN (Convolutional Neural Network) has very important research value in image feature expression. The digitization of painting works is of great significance to the effective use of painting resources. The traditional image classification methods do not consider the subjective characteristics of painting works, and most of the features need to be extracted manually, resulting in the loss of detailed features. The research and design of image retrieval system in this paper is based on CNN. One is to extract the features of the image using convolution neural network. The scale of image data sets in the resource database is still small. For the field of deep learning research, data sets can only be regarded as small-scale data sets. Combined with the actual situation, the convolution neural network model is trained, and the better convolution neural network structure Artnet is selected through experimental analysis. It is a seven-layer network structure including two volume layers, two pool layers, and a full connection layer. The second is to design and implement a practical image retrieval system based on Artnet and effectively integrate it with other systems of the project as an important function of the project construction.
Electrically small folded spherical helix antennas using copper strips and 3D printing technology

Folded spherical helix (FSH) antennas using thin and wide copper strips instead of thick wires as a means of reducing the electrical size of ka is designed. It is found that FSH antennas made of copper strips show comparable radiation properties to FSH antennas made of thick wires. Furthermore, such designs can achieve even smaller size down to ka of 0.11 while keeping the radiation quality factors approaching the lower physical bound. An FSH antenna made of copper strips with ka of 0.21 is fabricated as a prototype using 3D printing technology. The measured resonance occurs at 307 MHz with the radiation efficiency of about 90%, verifying the simulated results and the proposed method of utilising copper strips in designing extremely small yet highly efficient volumetric folded helix antennas.