Miracle-dz/UniFAR-FTUs huggingface dataset:
Review on recent Computer Vision Methods for Human Action Recognition

The subject of human activity recognition is considered an important goal in the domain of computer vision from the beginning of its development and has reached new levels. It is also thought of as a simple procedure. Problems arise in fast-moving and advanced scenes, and the numerical analysis of artificial intelligence (AI) through activity prediction mistreatment increased the attention of researchers to study. Having decent methodological and content related variations, several datasets were created to address the evaluation of these ways. Human activities play an important role but with challenging characteristic in various fields. Many applications exist in this field, such as smart home, helpful AI, HCI (Human-Computer Interaction), advancements in protection in applications such as transportation, education, security, and medication management, including falling or helping elderly in medical drug consumption. The positive impact of deep learning techniques on many vision applications leads to deploying these ways in video processing. Analysis of human behavior activities involves major challenges when human presence is concerned. One individual can be represented in multiple video sequences through skeleton, motion and/or abstract characteristics. This work aims to address human presence by combining many options and utilizing a new RNN structure for activities. The paper focuses on recent advances in machine learning-assisted action recognition. Existing modern techniques for the recognition of actions and prediction similarly because the future scope for the analysis is mentioned accuracy within the review paper.
Fault Detection Observer Design for Nonlinear Systems via Fuzzy Lyapunov Functions

This article focuses on the design problem of fault detection (FD) observer for a class of continuous-time nonlinear systems. The <inline-formula> <tex-math notation="LaTeX">$\mathcal {H_{-}}$ </tex-math></inline-formula> index is employed to measure the worst cast fault sensitivity. First, the nonlinear systems are represented by the Takagi–Sugeno (T–S) fuzzy dynamic models. Then, a novel fuzzy Lyapunov function (FLF) analyzing approach is proposed to reduce the conservatism in stability analysis and <inline-formula> <tex-math notation="LaTeX">$\mathcal {H_{-}}$ </tex-math></inline-formula> index estimation for the T–S fuzzy model. In particular, employing this new type of the FLF, the stability analysis of the T–S fuzzy systems perfectly overcomes the difficulty of evaluating the upper bound of the time derivative of the membership function. Based on the descriptor system approach, some new sufficient conditions on the existence of fuzzy FD observers are obtained in terms of linear matrix inequalities (LMIs). Finally, illustrative examples are given to show the effectiveness of the proposed method.
Metal-to-metal charge transfer driven by electropositive species for stable anionic redox

Apart from conventional redox chemistries, exploring high-voltage redox processes, such as high-valent redox of a transition metal (TM) or novel anionic redox, is challenging due to unstable energy states correlated with destructive structural disorder in intercalation-type cathode materials. Here, we show a new strategy to design high-energy-density 4d-based Li-excess oxides with strong structural reversibility by substituting electropositive species. It is known that TMs in 4d-based Li-excess oxides, in contrast to 3d-based oxides, actively interact with neighboring oxygen ligands, inducing b1/b1* energy levels. Metal-to-metal charge transfer, driven by covalency competition within the asymmetric TM3d-O-TM4d backbone, induces a larger overlap between electronegative species and oxygen ligands, leading to stable high-voltage redox. Furthermore, we reveal that redox-inactive dopants control the reversibility of cation migration, thereby extending the battery lifetime. These insights open new perspectives for the control of intrinsic redox chemistry and enable rational designs for high-energy-density Li-excess cathodes.
Probe Vehicles Sample Size for Mobile Traffic Detection System

On the basis of researches on the world-wide probe vehicles sample size for mobile traffic detection system,authors analyzed shortcomings of existing products.Aimed at the conditions of uniform and non-uniform distribution of traffic flow density,using mathematical statistics method,bi-level sample size model of probe vehicles sample size on road network was established which took into account probe vehicle speed,calculation time interval and data precision.The result shows that if calculation interval is 5 min and traffic flow density is uniform on road network,probe vehicles proportion should be at least 5.0%. Otherwise,it should be at least 7.0%.
Selection on assessment methods of typical water quality

There are many comprehensive methods with different characteristics for assessing water environmental quality.This article firstly introduces four assessment methods which are worst factor judgment method,organic pollutant comprehensive index assessment method,principal component analysis method and fuzzy theory based comprehensive assessment method.And taking Shanghai as example,monitoring data at several monitoring stations are analyzed by using four methods.From the results of assessment,water quality assessed by worst factor judgment method is relative worse,and water quality assessed by fuzzy theory based on comprehensive assessment method is rather good.In addition,using organic pollutant comprehensive index assessment method needs to calculate and compare index several times,so this method is complicate.Principal component analysis method takes weight of every factor into account,and only needs to calculate once to get a discriminator or criteria which can be used directly for future assessment.And result from this assessment method is relative reasonable,so it is a rather good method for water quality assessment.
The best of both worlds: cicada males change costly signals to achieve mates while females choose a mate based on both calling and courtship songs

Abstract Cicadas usually sing and mate in the higher parts of trees. Studies addressing the effects of different acoustic signals on mate choice in Cicadidae are very limited. We investigated the effects of both acoustical features and morphological traits on mate choice in an East Asian cicada Platypleura kaempferi. Males produce high-rate calling songs that attract females, then produce low-rate courtship songs to secure mating when a female is attracted. Higher calling song rate (CR), shorter single-pulse duration, and shorter pulse period of the calling song, together with lower courtship song rate and longer echeme period of the courtship song, are the most desirable traits used by females to choose a mate. These traits indicate that the more a male can raise the rate of song production, the higher the probability he is sexually selected by the female. No correlation was found between morphological traits and mating success. After mating, a minority of males started emitting calling songs again, but the CR was significantly lower than before mating and none of them attracted a new mate later. This promotes females mating with unmated males. We hypothesize that P. kaempferi may have the best of both worlds due to the unique song modulation and the mechanism of female mate choice: males change energetically, costly acoustic signals to achieve mates, while females choose a mate based on males’ acoustic properties. Our results contribute to better understanding the diversity of mating preference and enrich the mechanism of mate choice in acoustic insects.
White matter microstructure in Parkinson’s disease with and without elevated rapid eye movement sleep muscle tone

Abstract People with Parkinson’s disease who have elevated muscle activity during rapid eye movement sleep (REM sleep without atonia) typically have a worse motor and cognitive impairment compared with those with normal muscle atonia during rapid eye movement sleep. This study used tract-based spatial statistics to compare diffusion MRI measures of fractional anisotropy, radial, mean and axial diffusivity (measures of axonal microstructure based on the directionality of water diffusion) in white matter tracts between people with Parkinson’s disease with and without rapid eye movement sleep without atonia and controls and their relationship to measures of motor and cognitive function. Thirty-eight individuals with mild-to-moderate Parkinson’s disease and 21 matched control subjects underwent ultra-high field MRI (7 T), quantitative motor assessments of gait and bradykinesia and neuropsychological testing. The Parkinson’s disease cohort was separated post hoc into those with and without elevated chin or leg muscle activity during rapid eye movement sleep based on polysomnography findings. Fractional anisotropy was significantly higher, and diffusivity significantly lower, in regions of the corpus callosum, projection and association white matter pathways in the Parkinson’s group with normal rapid eye movement sleep muscle tone compared with controls, and in a subset of pathways relative to the Parkinson’s disease group with rapid eye movement sleep without atonia. The Parkinson’s disease group with elevated rapid eye movement sleep muscle tone showed significant impairments in the gait and upper arm speed compared with controls and significantly worse scores in specific cognitive domains (executive function, visuospatial memory) compared with the Parkinson’s disease group with normal rapid eye movement sleep muscle tone. Regression analyses showed that gait speed and step length in the Parkinson’s disease cohort were predicted by measures of fractional anisotropy of the anterior corona radiata, whereas elbow flexion velocity was predicted by fractional anisotropy of the superior corona radiata. Visuospatial memory task performance was predicted by the radial diffusivity of the posterior corona radiata. These findings show that people with mild-to-moderate severity of Parkinson’s disease who have normal muscle tone during rapid eye movement sleep demonstrate compensatory-like adaptations in axonal microstructure that are associated with preserved motor and cognitive function, but these adaptations are reduced or absent in those with increased rapid eye movement sleep motor tone.
Antitumor effect of isoquercetin on tissue vasohibin expression and colon cancer vasculature

Tumor cells trigger angiogenesis through the expression of angiogenic factors. Vasohibins (VASHs) are a family of peptides that regulate angiogenesis. Flavonoids have antiproliferative antitumor properties; however, few studies have highlighted their antiangiogenic potential. This study evaluated the flavonoid isoquercetin (Q3G) as an antitumor compound related to colon cancer vascularization and regulation of VASH1 and 2. Mice bearing xenogeneic colon cancer (n = 15) were divided into 3 groups: Q3G-treated (gavage, daily over a week), bevacizumab-treated (intraperitoneal, single dose), or untreated animals. Tumor growth, histological characteristics, blood vessel volume, and VASH1 and 2 expressions were analyzed. Q3G impaired tumor growth and vascularization, upregulated VASH1, and downregulated VASH2 in comparison to untreated animals. Mice treated with Q3G showed approximately 65% fewer blood vessels than untreated animals and 50% fewer blood vessels than mice treated with bevacizumab. Thus, we show that Q3G has antitumor activity, impairs vascularization, and differentially modulates VASH1 and 2 expressions in colon cancer.
3D Finite Element Modeling and Simulation on Claw Pole Generator

Aiming at the complicated calculation for inside magnetic field of claw pole generator,a three dimensional(3D) finite element model of a conventional claw pole generator was presented using Rmxprt of Ansoft.Optimized using Maxwell 3D,the 3D transient simulation model was constructed by integrating the 3D finite element model and the windings circuit model.Then the no load output voltage of the motor was simulated and the simulated voltage agree well with the experimental results,which demonstrates the accuracy of the model.Moreover,the transient distribution performance of the air gap flux was analyzed using the postprocessing function of Ansoft,which can provide foundation for the electromagnetic characteristic research of claw pole generator.
Discovery and Identification of Memory Corruption Vulnerabilities on Bare-Metal Embedded Devices

Memory corruption vulnerabilities remain a prevalent threat on low-cost bare-metal devices. Fuzzing is a popular technique for automatically discovering such vulnerabilities. However, bare-metal devices lack even basic security mechanisms such as Memory Management Unit. Consequently, fuzzing approaches encounter silent memory corruptions with no visible effects, making even discovery difficult. Once discovered, it is also essential to identify the type of observed vulnerability for applying mitigation. Both discovery and identification remain open challenges in the case of fuzzing firmware binaries. This article addresses these problems by proposing an automated instrumentation technique that allows the observation of memory corruption vulnerabilities that are otherwise not observable and facilitates the automated identification of the observed vulnerability. Additionally, we surveyed state-of-the-art IoT fuzzers and analyzed their experimental methodologies. We found that existing approaches have fundamental problems that lead to incorrect or misleading results. To evaluate the effectiveness of IoT fuzzers, it is essential to determine the range and type of vulnerabilities that these fuzzers can discover. Thus, we propose the first ground-truth benchmark suite for IoT fuzzers that enables accurate and consistent evaluation of their vulnerability-finding performance. Our instrumentation framework's efficacy and efficiency in combination with state-of-the-art IoT fuzzers are assessed using the proposed benchmark.
Using Six Sigma Method to Increase the Filling Value of Cut Tobacco

Six sigma method has been used to improve the filling value of cut tobacco which is an important index in the tobacco production process.First the ergodic analysis of primary processing of cigarette was conducted to determine the key factors which affected the filling value of cut tobacco.Then the key factors which were the result of the potential failure mode analysis(FMEA) were determined based on hypothesis test.Finally,the design of experiment which focused on the key factors was carried on to confirm the optimal parameters and integrated into the control of the production process.
The use of weighted averages of Hedges' d in meta‐analysis: Is it worth it?

Hedges' d is a measure of effect size widely used to standardize results across different studies in ecological and evolutionary meta‐analyses. When summarizing Hedges' d or other effect sizes across multiple studies, it is considered a best practice to use weighted averages, with weights inversely proportional to the variances of the estimated effect sizes. Importantly, the within‐study variance of Hedges' d , υ2 , is a function of sample size, n , and δ , the effect size itself. Since true effect sizes are unknown, υ2 is also unknown and needs to be estimated, for which numerous approaches have been proposed. We examined the behaviour of inverse‐variance weights, specifically the performance of 14 different weighted and unweighted variants of the Hedges' d estimator, to test the conditions under which weighting improved performance. We found that when sample sizes (per group) were >10, there was little difference between the estimators and weighting did not notably improve performance; bias was <5% and differences in root mean squared error were <10% for all estimators, except when the between‐study variance for effect size, τ2 , was relatively small compared to the within‐study variance ( τ2/υ2<0.5 ). We also propose a new estimator that was found to be (a) the most efficient of a subset of minimally biased estimators and (b) had the least bias when estimating τ2. Contrary to current guidance, we contend that the simpler unweighted Hedges' d estimator is generally acceptable. Exceptions are when the between‐study variance is small relative to within‐study variance ( τ2/υ2<0.5 ) and there is a large disparity (>3X) in sample sizes for a large proportion of effect sizes in the meta‐analysis. Using unweighted averages may enable more robust inferences by allowing studies for which variance cannot be extracted (a common practical limitation) to be included. That said, weighted averaging is necessary where estimation of τ2 is itself of interest.
Mathematical Model of Elasticity Missiles with Swing Nozzle Thrust Vector Control

According to the characteristic of swing nozzle different from aero-fin,coordinates of swing nozzle is established.Force and torque of single nozzle are analyzed.Elasticity vibration formula with nozzle thrust vector control are derived.Based on the condition of small error linearization,attitude motion formula on pitch plane of missiles are educed.The formula can be used as the credential on the calculation of missiles elasticity and further design of control system.
Reclassification of Five BRCA1/2 Variants with Unknown Significance Using Complex Functional Study

Purpose While BRCA1/2 genes are commonly investigated, variants of unknown significance (VUS) and variants with potential splice effect are still being detected and they represent a substantial challenge in genetic counseling and therapy. Materials and Methods Out of genetically tested 3,568 hereditary breast and ovarian cancer probands five, functionally not investigated variants with potential splice-modifying effect were subjected to functional characterization. Transcript-level analysis on peripheral blood-derived RNA of the carriers was performed to test aberrant splicing. The completeness of the aberrant splicing event was also studied, existence and extent of nonsense-mediated decay was even addressed. Clinical and phenotype data, pedigree and co-segregation analyses were also done. Locus-specific loss of heterozygosity (LOH) in tumor tissues was additionally tested. Results In case of the BRCA1:c.4484+4dupA and the BRCA1:c.5407-10G>A variants functional results allowed us to reclassify them from VUS into likely pathogenic category. BRCA1:c.4358-31A>C, by producing incomplete aberrant splicing, was highlighted as strong VUS, but in lack of other supporting evidence, re-categorization was not possible. The likely pathogenic assertion of previously not reported BRCA2:c.8487G>T was reinforced based on its spliceogenic property and tumor LOH, while BRCA2:c.793G>A failed to present aberrant splicing in spite of suggestive predictions, which altered its original VUS evaluation into likely benign class. Conclusion We presented molecular and clinical evidence for reclassification of four out of five BRCA1/2 variants. Both up- and down-classification harbour important clinical significance. Patients carrying re-classified pathogenic variants in the future will not be dropped out from medical surveillance, preventive measures, treatment and predictive family screening in relatives at risk.
Patients’ Perceptions of Quality of Care: A Teamwork Intervention Study in a Surgical Ward

Introduction Improving teamwork competencies among health care professionals is important for patient safety. Few previous studies have investigated whether a teamwork intervention has an impact on patients’ perceptions of quality of care. Objective To investigate patients’ perceptions of quality of care before and after the implementation of a team training program in a surgical ward. Methods A quasi-experimental pre- and posttest design was used. The TeamSTEPPS® team training program was implemented in a surgical ward. Three groups of consecutively sampled patients responded to the Quality from the Patient's Perspective (QPP) questionnaire including four dimensions with 25 items. In addition to the QPP, six items were developed for this study. In total, 223 patients responded to the questionnaire. The mean age was 59.6 years, and there were 128 males and 94 females. Results The physical-technical condition dimension and four items showed significantly higher scores after six months of intervention. The majority of the patients scored quality of care in the four dimensions as very high at all three time points. Younger patients reported the lowest care quality. Conclusion The results in this study indicate that the teamwork intervention had a minimal impact on the patients’ perceptions of quality of care, with only significant differences between baseline and six months of intervention in one dimension and three items. At each data collection time point, the numbers of patients who perceived quality of care as modest decreased slightly. Younger patients were more likely to perceive care quality as modest.
The politicization of medical preprints on Twitter during the early stages of COVID-19 pandemic

We examine the patterns of medical preprint sharing on Twitter during the early stages of the COVID-19 pandemic. Our analysis demonstrates a stark increase in attention to medical preprints among the general public since the beginning of the pandemic. We also observe a political divide in medical preprint sharing patterns - a finding in line with previous observations regarding the politicisation of COVID-19-related discussions. In addition, we find that the increase in attention to preprints from the members of the general public coincided with the change in the social media-based discourse around preprints.
Learning Bilingual Word Embedding Mappings with Similar Words in Related Languages Using GAN

ABSTRACT Cross-lingual word embeddings display words from different languages in the same vector space. They provide reasoning about semantics, compare the meaning of words across languages and word meaning in multilingual contexts, necessary to bilingual lexicon induction, machine translation, and cross-lingual information retrieval. This paper proposes an efficient approach to learn bilingual transform mapping between monolingual word embeddings in language pairs. We choose ten different languages from three different language families and downloaded their last update Wikipedia dumps1 1. https://dumps.wikimedia. org. Then, with some pre-processing steps and using word2vec, we produce word embeddings for them. We select seven language pairs from chosen languages. Since the selected languages are relative, they have thousands of identical words with similar meanings. With these identical dictation words and word embedding models of each language, we create training, validation and, test sets for the language pairs. We then use a generative adversarial network (GAN) to learn the transform mapping between word embeddings of source and target languages. The average accuracy of our proposed method in all language pairs is 71.34%. The highest accuracy is achieved for the Turkish-Azerbaijani language pair with the accuracy 78.32%. , which is noticeably higher than prior methods.
Research on Influence of Objective Function on HEC-HMS Model Parameter Calibration

Taking Qingjiang River(Upstream of Yuxiakou) for an example,distributed hydrological model HEC-HMS is applied to study parameters automatic calibration function of the model.The objective functions with parameter optimization are selected to discuss the impact of objective function on model simulation results and analyze its causes.The results show that the simulation result of peak-weighted root mean square error function has the best effect.Thus,it provides theory evidence for selecting flood to simulate objective functions with parameter optimization.