Miracle-dz/UniFAR-FTUs huggingface dataset:
3D reconstruction measurement method based on binocular vision

At present, the measurement of irregular workpiece is mainly carried out by coordinate measuring machine, but this kind of equipment is expensive and inconvenient to operate, and can’t be applied to soft objects. This paper proposed a 3D surface reconstruction method based on binocular vision to imitate the structure of human eyes, and then measured various sizes on the point cloud model. The reconstruction method based on binocular vision is fast, efficient and lowcost. Then, the 3D coordinates of the feature points in the world coordinate system are solved by the reprejectImgeTo3d function to generate the point cloud. The final point cloud model has rich surface texture information and can completely reflect the 3D size information of the object.
Benchmarking Teamwork of Humans and Cobots—An Overview of Metrics, Strategies, and Tasks

Human-robot teaming receives an ever-increasing level of attention in research, development and industry. Novel approaches to task sharing in hybrid teams range from optimized schedules to intelligent cobot assistants with a high degree of autonomy. These approaches must prove their usefulness and benefits compared to manual work or full automation – particularly when it comes to assessing their potential for productive industrial use. This leverages demand for standardized, repeatable benchmarks to compare approaches and measure improvements in a reproducible way. Designing such benchmarks is challenging as numerous aspects, from safety considerations to human factors and team performance, must be considered. This survey seeks to contribute to the future development of benchmarks for the field of collaborative assembly, handling, and industrial cobot applications by giving a comprehensive overview of relevant metrics, evaluation strategies, and tasks for human-robot teams.
Effect of Quadriceps and Hamstring Strength Relative to Body Weight on Risk of a Second ACL Injury: A Cohort Study of 835 Patients Who Returned to Sport After ACL Reconstruction

Background: Anterior cruciate ligament (ACL) injuries are common sports-related injuries with a high risk of reinjury after return to sport (RTS). Rehabilitation aims to regain symmetrical knee strength and function to minimize the risk of a second ACL injury after RTS. Purpose: To determine the effect of absolute quadriceps and hamstring strength, normalized by body weight, on the risk of a second ACL injury during the first 2 years after RTS in patients who have undergone ACL reconstruction (ACLR). Study Design: Cohort study; Level of evidence, 3. Methods: Data from patients after index ACLR at the time of RTS were extracted from a rehabilitation registry—Project ACL. Patients who had performed isokinetic tests for quadriceps and hamstring strength and hop tests before RTS were included. The endpoint was a second ACL injury or a follow-up of 2 years after RTS after ACLR. Results: A total of 835 patients (46% women), with a mean age of 23.9 ± 7.7 years, were included. During the study period, 69 (8.3%) second ACL injuries (ipsilateral and contralateral) occurred. Greater relative quadriceps strength in the injured leg increased the risk of a second ACL injury (relative risk [RR], 1.69 [95% CI, 1.05-2.74]; P = .032). In patients who had recovered symmetrical quadriceps strength (limb symmetry index ≥90%), there was no effect of quadriceps strength on the risk of second ACL injury (RR, 1.33 [95% CI, 0.69-2.56]; P = .39). Quadriceps strength on the healthy side or hamstring strength, regardless of side, had no effect on the risk of a second ACL injury. Conclusion: Greater relative quadriceps strength in the injured leg at the time of RTS after ACLR was associated with an increased risk of a second ACL injury. There was no effect of relative quadriceps strength on the risk of a second ACL injury in patients who had recovered symmetrical quadriceps strength.
The Presence of Two MyoD Genes in a Subset of Acanthopterygii Fish Is Associated with a Polyserine Insert in MyoD1

The MyoD gene was duplicated during the teleost whole genome duplication and, while a second MyoD gene (MyoD2) was subsequently lost from the genomes of some lineages (including zebrafish), many fish lineages (including Alcolapia species) have retained both MyoD paralogues. Here we reveal the expression patterns of the two MyoD genes in Oreochromis (Alcolapia) alcalica using in situ hybridisation. We report our analysis of MyoD1 and MyoD2 protein sequences from 54 teleost species, and show that O. alcalica, along with some other teleosts, include a polyserine repeat between the amino terminal transactivation domains (TAD) and the cysteine-histidine rich region (H/C) in MyoD1. The evolutionary history of MyoD1 and MyoD2 is compared to the presence of this polyserine region using phylogenetics, and its functional relevance is tested using overexpression in a heterologous system to investigate subcellular localisation, stability, and activity of MyoD proteins that include and do not include the polyserine region.
An Attention-Based Convolutional Neural Network for Intrusion Detection Model

Network technology has had a distinctive impact on the entire human civilization and has become an important factor of production in many countries and regions. However, with the widespread popularity of network technology, security flaws have been scattered in various fields, and potential crises may break out by attackers at any time. Therefore, it is crucial to establish a traffic monitoring mechanism for network systems. Some researchers have already implemented intrusion detection models by convolutional neural networks (CNNs) combined with attention mechanisms and achieved good results. However, few attempts have been made to improve the computational efficiency of the model by organizing the appropriate image structure, and the integration of attention mechanisms could be further enhanced. In this study, an attention-based CNN intrusion detection model has been proposed. Together with the image generation methods described in this paper, an efficient and accurate processing flow is formed. To optimize the use of the feature information in the experiments, the feature fields in the experimental images were arranged according to the results of their importance analysis. And a more integrated attention mechanism has been applied to the CNN for building the detection model. A series of comparative experiments were conducted on a subset of the CSE-CIC-IDS2018 dataset, and the results show that the detection process and model proposed in this paper can swiftly complete the detection procedure while maintaining high accuracy.
Analytical Validation of a Webcam-Based Assessment of Speech Kinematics: Digital Biomarker Evaluation following the V3 Framework

Introduction: Kinematic analyses have recently revealed a strong potential to contribute to the assessment of neurological diseases. However, the validation of home-based kinematic assessments using consumer-grade video technology has yet to be performed. In line with best practices for digital biomarker development, we sought to validate webcam-based kinematic assessment against established, laboratory-based recording gold standards. We hypothesized that webcam-based kinematics would possess psychometric properties comparable to those obtained using the laboratory-based gold standards. Methods: We collected data from 21 healthy participants who repeated the phrase “buy Bobby a puppy” (BBP) at four different combinations of speaking rate and volume: Slow, Normal, Loud, and Fast. We recorded these samples twice back-to-back, simultaneously using (1) an electromagnetic articulography (“EMA”; NDI Wave) system, (2) a 3D camera (Intel RealSense), and (3) a 2D webcam for video recording via an in-house developed app. We focused on the extraction of kinematic features in this study, given their demonstrated value in detecting neurological impairments. We specifically extracted measures of speed/acceleration, range of motion (ROM), variability, and symmetry using the movements of the center of the lower lip during these tasks. Using these kinematic features, we derived measures of (1) agreement between recording methods, (2) test-retest reliability of each method, and (3) the validity of webcam recordings to capture expected changes in kinematics as a result of different speech conditions. Results: Kinematics measured using the webcam demonstrated good agreement with both the RealSense and EMA (ICC-A values often ≥0.70). Test-retest reliability, measured using the absolute agreement (2,1) formulation of the intraclass correlation coefficient (i.e., ICC-A), was often “moderate” to “strong” (i.e., ≥0.70) and similar between the webcam and EMA-based kinematic features. Finally, the webcam kinematics were typically as sensitive to differences in speech tasks as EMA and the 3D camera gold standards. Discussion and Conclusions: Our results suggested that webcam recordings display good psychometric properties, comparable to laboratory-based gold standards. This work paves the way for a large-scale clinical validation to continue the development of these promising technologies for the assessment of neurological diseases via home-based methods.
A cloud-based approach to network security situational awareness

The traditional network security situational awareness method obtains the clustering results of network behavior analysis by using adaptive weight clustering algorithm, which leads to poor perception due to the lack of fusion of situational indicators. In this regard, a cloud computing-based network security situational awareness approach is proposed. By using Hadoop cloud computing network platform to collect security posture information and establish Bayesian network to fuse network security posture indicators and construct a posture perception model. In the experiments, the proposed method is verified for the perception effect. The analysis of the experimental results shows that the proposed method is used for network security situational awareness of network data, and the perception is less time-consuming and has a more excellent performance of network security situational awareness.
Theoretical calculation method of the nolinear buckling of deepsea pipes

A theoretical calculation method for the nolinear buckling of deepsea pipes is developed,which includes the deformation response of the pre-buckling stage and the collapse pressure on the lateral pressure condition.Provided that the ovillity deformation of the cross-section is uniform along the axial direction of the pipe on the pre-buckling stage,the application of circular ring model is reasonable.Considering large deformation kinematics relations and the elastic-plastic constitutive relations of material,balance equations are establishied with the principle of virtual work.Appropriate displacement function in discrete form is chosen to solve the equations by Newton method.By comperison of the the results of experiment,finite method analysis and specifications,the theoretical calculation method presented in the paper is proved to be accurate and consistent with the fact.At last,the impact of the initial ovility on the collapse pressure of pipes with different D/t is calculated.
Eddy Current Sensors Optimization for Defect Detection in Parts Fabricated by Laser Powder Bed Fusion

The production of parts by additive manufacturing is an important issue for the reduction in manufacturing costs and the creation of complex geometries. Optical inspection is often implemented in the machines during the manufacturing process in order to monitor the possible generated defects. However, it is also crucial to test the quality of the manufactured parts after their fabrication and monitor their health throughout their industrial lifetime. Therefore structural health monitoring (SHM) methods need to be studied or designed. In this paper, the eddy current method is used to control fabricated parts, as this technique is adapted to detect surface and shallow defects in conductive materials. Using simulations with the CIVA non-destructive testing software package, several sensors and their parameters were tested in order to determine the most optimal ones: a separate transmitter/receiver sensor and an isotropic sensor were finally designed. The comparison of these sensors’ efficiency was made on the detection of notches and engraved letters based on simulation and experimental tests on parts fabricated by laser powder bed fusion (L-PBF) in order to determine the optimal sensor. The various tests showed that the isotropic sensor is the optimal one for the detection and characterization of defects.
Neuroprotective Effects of IVIG against Alzheimer’s Disease via Regulation of Antigen Processing and Presentation by MHC Class I Molecules in 3xTg-AD Mice

Background The results of clinical trials for Alzheimer’s disease (AD) patients treated with Intravenous immunoglobulin (IVIG) revealed inconsistency in efficacy. Objective To explore the neuroprotective effects and possible mechanisms of different IVIG in 3xTg-AD mice. Methods 3-month-old 3xTg-AD mice were administered intraperitoneally with different IVIG (A/B/C) for 3 months and then the therapeutic effects were observed and tested at 9 months of age. The bioavailability of IVIG and Aβ40/42 concentrations in parietotemporal cortex was measured by ELISA. Behavioral tests were performed to examine cognitive functions. Immunohistochemistry was utilized to examine the deposition of Aβ, the phosphorylation of tau, the levels of GFAP and Iba-1 in the hippocampus. Proteomics, Luminex assay and parallel reaction monitoring were performed to identify and verify the proteins that showed a marked change in the hippocampus. Results IVIG-C was more effective than IVIG-A and IVIG-B in counteracting cognitive deficits, ameliorating Aβ deposits and tau phosphorylation, attenuating the activation of microglia and astrocytes in the hippocampus and inhibiting the secretion of pro-inflammatory factors. IVIG-C affected innate immunity and suppressed the activation of antigen processing and presentation by MHC class I molecule (APP-MHC-I). Conclusion The efficacy of different IVIG on AD was significantly different, and only IVIG-C has been confirmed to possess significant neuroprotective effects, which are related to the inhibition of APP-MHC-I. IVIG may be a potential therapeutic for AD but further research is needed to evaluate the functional of IVIG before clinical trials of AD treatment.
Anti-Alopecia Activity of Coumarin Derivatives Isolated from Merremia peltata Leaves and Computational Study of Their Binding to Androgen Receptors Using Molecular Docking and Molecular Dynamic Simulation

Alopecia is a condition in which hair on the scalp or other areas of the body is lost or falls out excessively. Nutritional deficiency causes blood flow to the head to decrease causing the hormone testosterone to be changed by the enzyme 5-α-reductase to dihydrotestosterone, which inhibits the growth phase and accelerates the death phase. One of the methods developed to treat alopecia is through inhibition of the 5-α-reductase enzyme, which converts testosterone to its more potent metabolite, dihydrotestosterone (DHT). Ethnomedicinally, Merremia peltata leaf is used by the people of Sulawesi as a remedy for baldness. Therefore, in this research, an in vivo study was conducted on rabbits to determine the anti-alopecia activity of M. peltata leaf compounds. The structure of the compounds isolated from the M. peltata leaf ethyl acetate fraction was determined by analysis of NMR and LC-MS data. An in silico study was then carried out using minoxidil as a comparison ligand; scopolin (1) and scopoletin (2) isolated from M. peltata leaf were identified as anti-alopecia compounds by predicting docking, simulating molecular dynamics and predicting absorption, distribution, metabolism, excretion, and toxicology (ADME-Tox). Compounds 1 and 2 had a better effect on hair growth compared to positive controls, and NMR and LC-MS analysis showed that they had comparable binding energies to receptors in the molecular docking interaction study: −4.51 and −4.65 kcal/mol, respectively, compared to −4.8 kcal/mol for minoxidil. Molecular dynamics simulation analysis with the parameters binding free energy calculated using the MM-PBSA method and complex stability based on SASA, PCA, RMSD, and RMSF showed that scopolin (1) has a good affinity for androgens receptors. The ADME-Tox prediction for scopolin (1) showed good results for the parameters of skin permeability, absorption and distribution. Therefore, scopolin (1) is a potential antagonist to androgen receptors and could be useful in the treatment of alopecia.
Maximum Likelihood Estimation for the Double-Count Method With Independent Observers

influenced the detection probabilities included perpendicular distance of bear groups from the flight line and the number of individuals in the groups. A series of models were considered which vary from (1) the simplest, where the probability of detection was the same for both observers and was not affected by either distance from the flight line or group size, to (2) models where probability of detection is different for the two observers and depends on both distance from the transect and group size. Estimation procedures are developed for the case when additional variables may affect detection probabilities. The methods are illustrated using data from the pilot polar bear survey and some recommendations are given for design of a survey over the larger Chukchi Sea between Russia and the United States.
Sit Still, Talk Pretty: Partisan Differences Among Women Candidates’ Campaign Appeals

ABSTRACT Women running for Congress make different choices from men about how to connect with constituents on social media, and the increasing number of women running for Congress from both parties suggests that further assessment of the gendered patterns of emotional appeals is needed. We use this opportunity to assess the joint influence of gender and partisanship on patterns of emotional appeals, showing how party moderates the distinct appeals women candidates make on social media. We use a dictionary-based computational approach to catalog congressional candidates’ emotional rhetoric on Twitter during the 2020 election year, finding Republican women use more joyful appeals and fewer angry appeals compared to both Republican men and Democratic women, suggesting a gap in emotive appeals and differing expectations for how women communicate that varies with party. Our results underscore the importance of accounting for relative partisanship in developing a more nuanced explanation of how and when women adopt stereotypical styles of campaign communication as the number of Republican women running for Congress continues to increase.
Fiber Optic Sensing Technology and Vision Sensing Technology for Structural Health Monitoring

Structural health monitoring is currently a crucial measure for the analysis of structural safety. As a structural asset management approach, it can provide a cost-effective measure and has been used successfully in a variety of structures. In recent years, the development of fiber optic sensing technology and vision sensing technology has led to further advances in structural health monitoring. This paper focuses on the basic principles, recent advances, and current status of applications of these two sensing technologies. It provides the reader with a broad review of the literature. It introduces the advantages, limitations, and future directions of these two sensing technologies. In addition, the main contribution of this paper is that the integration of fiber optic sensing technology and vision sensing technology is discussed. This paper demonstrates the feasibility and application potential of this integration by citing numerous examples. The conclusions show that this new integrated sensing technology can effectively utilize the advantages of both fields.
Linear and nonlinear receptivity of the boundary layer in transonic flows

In this paper we analyse the process of the generation of Tollmien–Schlichting waves in a laminar boundary layer on an aircraft wing in the transonic flow regime. We assume that the boundary layer is exposed to a weak acoustic noise. As it penetrates the boundary layer, the Stokes layer forms on the wing surface. We further assume that the boundary layer encounters a local roughness on the wing surface in the form of a gap, step or hump. The interaction of the unsteady perturbations in the Stokes layer with steady perturbations produced by the wall roughness is shown to lead to the formation of the Tollmien–Schlichting wave behind the roughness. The ability of the flow in the boundary layer to convert ‘external perturbations’ into instability modes is termed the receptivity of the boundary layer. In this paper we first develop the linear receptivity theory. Assuming the Reynolds number to be large, we use the transonic version of the viscous–inviscid interaction theory that is known to describe the stability of the boundary layer on the lower branch of the neutral curve. The linear receptivity theory holds when the acoustic noise level is weak, and the roughness height is small. In this case we were able to deduce an analytic formula for the amplitude of the generated Tollmien–Schlichting wave. In the second part of the paper we lift the restriction on the roughness height, which allows us to study the flows with local separation regions. A new ‘direct’ numerical method has been developed for this purpose. We performed the calculations for different values of the Kármán–Guderley parameter, and found that the flow separation leads to a significant enhancement of the receptivity process.
Artificial Intelligence Technologies in the Microsurgical Operating Room (Review)

Surgery performed by a novice neurosurgeon under constant supervision of a senior surgeon with the experience of thousands of operations, able to handle any intraoperative complications and predict them in advance, and never getting tired, is currently an elusive dream, but can become a reality with the development of artificial intelligence methods. This paper has presented a review of the literature on the use of artificial intelligence technologies in the microsurgical operating room. Searching for sources was carried out in the PubMed text database of medical and biological publications. The key words used were “surgical procedures”, “dexterity”, “microsurgery” AND “artificial intelligence” OR “machine learning” OR “neural networks”. Articles in English and Russian were considered with no limitation to publication date. The main directions of research on the use of artificial intelligence technologies in the microsurgical operating room have been highlighted. Despite the fact that in recent years machine learning has been increasingly introduced into the medical field, a small number of studies related to the problem of interest have been published, and their results have not proved to be of practical use yet. However, the social significance of this direction is an important argument for its development.