Miracle-dz/UniFAR-FTUs huggingface dataset:
Research status of autism spectrum disorders related to virtual reality technology in China

The purpose of this paper is to examine the current state of research on the application of virtual reality technology in autism spectrum disorders in China. A precise search for virtual reality and autism was accessed through CNKI's advanced search topic, and there were 21 results. By carefully reading and studying the research results of others, this paper analyzes the latest applications of virtual reality technology in the treatment of autism spectrum disorders. Virtual reality technology can effectively reduce unreasonable fear of specific situations and objects and significantly enhance social-emotional recognition and processing for people with ASD. By compensating for language barriers through nonverbal expression, more people with ASD can transfer the skills learned in virtual reality to real social life.
A SiCN Thin Film Thermistor Based on DVB Modified Polymer-Derived Ceramics

Carbon-rich SiCN ceramics were prepared by divinylbenzene (DVB)-modified polysilazane (PSN2), and a high-conductivity SiCN thin film sensor suitable for medium-low temperature sensing was fabricated. The modified liquid precursors were patterned by direct ink writing to produce SiCN resistive grids with line widths of several hundreds of micrometers and thicknesses of several micrometers. The introduction of DVB not only increases the critical thickness of SiCN ceramics several times, but also significantly improves the conductivity of SiCN, making it meet the conductivity requirements of sensing applications in the mid-low temperature range. The electrical conductivity and microstructure of DVB-modified SiCN ceramics were studied in detail. In the temperature range of 30~400 °C, the temperature resistance performance of DVB modified SiCN resistance grid was measured. The SiCN ceramics with low DVB content not only have excellent electrical conductivity, but also have good oxidation resistance.
The performance of improved XLNet on text classification

Text classification is the most common application of Natural Language Processing(NLP), and Transformer models have dominated the field in recent years. Currently, pre-training modeling of text through deep learning methods is a common way of text classification. This paper firstly proposes an improved XLNet text classification model based on the problems of long-term dependence and insufficient contextual semantic expression in previous pre-trained language models, and uses XLNet pre-trained language modeling to represent text as low-dimensional word vectors to obtain sequences. Secondly, the generated word vector sequence is passed into the LSTM network, and the two-way features of the sentence are extracted by the memory unit of the LSTM. On the basis of effectively extracting text features, the Multi-head attention model is used to calculate the multi-angle attention probability, to focus on the important words. Finally, text classification is achieved through a fully connected network. The experimental results show that the accuracy of the model is 0.9457 and the loss rate is 0.3133. Compared with other related models, it has achieved better results.
Fusion-Based Smartphone Positioning Using Unsupervised Calibration of Crowdsourced Wi-Fi FTM

This paper presents a multi-source fusion smartphone localization solution using Wi-Fi Fine Time Measurement (FTM) and Pedestrian Dead Reckoning (PDR), calibrated via multi-source and unsupervised crowdsourcing. In crowdsourcing phase, user movement within the site utilizes PDR to infer their location, and this location is used to calibrate the FTM data. The multi-layer perceptron (MLP) of the ranging model is suitable for non-line-of-sight (NLOS) reception, and the ranging accuracy is improved by more than 24%. In the positioning phase, the 90 percentile error of the ranging model trained using only crowdsourced data is less than 1.37m, which is 32% smaller than the traditional weighted least squares (WLS) localization error.
Energy Flow And Impulse Predictors Of Bat Speed During Baseball Tee Batting Using The Least Absolute Shrinkage And Selection Operator (LASSO) Regression

The purposes of this study were to examine how energy is generated, absorbed, and transferred through the pelvis during the baseball swing and to identify the best model of ground reaction force (GRF) and energy flow (EF) predictors of bat speed using a LASSO regression, which reduced the dataset to a model of four EF and two impulse variables that best predicts bat speed. The findings indicate that the mechanical energy flows from the trunk to the lead leg via the pelvis as these segments rotate during the swing. It is hoped that these findings will aid coaches and athletes in better understanding which elements of the swing movement are most closely related to bat speed. Thus, coaches may be able to develop and implement training strategies accordingly to improve bat speed and player performance. Nine healthy position players from an NCAA Division II collegiate men’s baseball team between the ages of 19 and 23 volunteered to participate in the study. All participants signed informed consent forms before participating in the study, which was approved by the university’s institutional review board prior to data collection. Players performed tee batting while their movements and GRF were recorded using an 8-camera 3D motion capture system (Motion Analysis Corp., Santa Rosa, CA) and two force platforms (AMTI, Watertown, MA) at data capture rates of 240 Hz and 1200 Hz, respectively. Bat speed was recorded using an inertial measuring unit (IMU) sensor (Blast Motion, Carlsbad, CA) fixed to the knob of the bat. Biomechanical metrics were extracted from a total of 33 swings for energy flow and impulse analysis using a 14-segment, 26 degrees-of freedom (DOF) full-body model configured in Visual3D (C-Motion, Germantown, MD). The rates of energy generation, absorption, and transfer and their respective totals through the pelvis were computed using an energy flow analysis as detailed by Aguinaldo and Nicholson (2021). The key events of the hitting motion were identified as foot-off (FO), maximum trunk rotation (MTR), ball impact (BI), and swing finish. The EF and impulse variables were further extracted by the phases of the hitting motion defined as the stance (FO to MTR), acceleration (MTR to BI), and follow-through (BI to swing finish) phases. A set of 27 discrete variables that includes all components of the peak GRF, impulse, and energy terms for the drive and stride legs
Applying probabilistic model for ranking Webs in multi-context

A bstract. The PageRank algorithm, used in the Google search engine, greatly improves the results of Web search by applying probabilistic model on the link structure of Webs to evaluate the “importance” of Webs. In PageRank probabilistic niodel, the links and webs are uniíòrm, so the rank score of vvebs are quite independent from their content. In practice, the researchers often hope that the web results can be ranked by their proposed topics. Moreover, vvhen computer’s techniques solve given problems ineffectively, it*s necessary to do better research in theoretical problems. From this judgement, in this paper, we introduce and describe the MPageRank based on a nevv probabilistic model supporting multi-context for ranking Webs. A Web now has diíĩerent ranking scores, which depends on the given multi topics. The basic idea in establishing the new MPageRank model is that partition our Web graph into smaller-size sub Web graph. As a consequence of evaluation and rejection about pages iníluence weakly to other pages, the rank score of pages of the original Web graph can be approximated from the rank score of pages in the nevv partition Web graph. Similar to the PageRank, the multi ranking scores in the MPageRank are pre-computed and reílect the hyperlink of Web environment.
Computations related to G-stability of linear multistep methods. [Backward differentiation, Adams-Bashforth, and Adams-Moulton methods]

In Dahlquist's recent proof of the equivalence of A-stability and G-stability (BIT 18, 384-401(1978)), an algorithm was presented for calculating a G-stability matrix for any A-stable linear multistep method. Such matrices, and various quantities computable from them, are useful in many aspects of the study of the stability of a given method. For example, information may be gained as to the shape of the stability region, or the rate of growth of unstable solutions. A summary of the relevant theory and the results of some numerical calculations performed for several backward differentiation, Adams-Bashforth, and Adams-Moulton methods of low order are presented in this work. 9 figures, 4 tables.
The logical complexity of queries on unordered graphs

The beam lead tool is for picking up and bonding semi-conductor wafers or dice to a substrate and includes an accommodating recess in which the wafer is positioned and a suction duct for permitting the wafer to be retained in the tool. The tool is formed as a tip at one end having a peripheral beam lead contacting surface that is formed by a grinding and lapping process wherein a radius or other curvature is defined along the inner facing edges defined by the contacting surface. The surface is first ground to a flatness and is then lapped by a vibratory motion against a resilient stationary pad such as a chamois impregnated with an abrasive material such as a conventional diamond paste.
Cellulose Production from Sago Frond with Alkaline Delignification and Bleaching on Various Types of Bleach Agents

Sago frond is a lignocellulose waste that it has not been utilized optimally. The purpose of this study was to produce cellulose from sago frond with alkaline delignification and bleaching on various types of bleach agents. The study was conducted in three stages, namely a characterization of sago frond, alkaline delignification, and bleaching. Proximate analysis showed that sago fronds are potentially used as a cellulose source. The treatments of alkaline delignification and bleaching on various types of bleach agents significantly affected the characteristics of cellulose. The delignification using 10% NaOH for 2 h, after which the bleaching was carried out using the alkaline hydrogen peroxide for the same duration, thereby, producing cellulose of the highest degree of crystallinity and whiteness, while the hemicellulose and lignin contents were relatively low. Thus, sago frond has the potential to be used as a cellulose source and is widely applied.
Interactions composants-circuits dans les onduleurs de tension : caractérisation, modélisation, simulation

Ce memoire traite de la modelisation fine de composants semiconducteurs a l'aide d'elements lineaires par morceaux (resistances, inductances, sources de courant et tension, etc. . . ) et utilisables, par exemple, dans le progiciel de simulation success. Tout d'abord, nous avons developpe et valide un modele de diode pin, qui rend compte des principaux phenomenes observes experimentalement, en particulier lors de la commutation de la diode au blocage. A partir des resultats obtenus avec la diode, nous avons concu des modeles de transistor bipolaire et de gto. Puis nous avons caracterise l'environnement de ces semiconducteurs. La derniere partie de ce memoire est consacree aux applications aux cellules de commutation a transistor bipolaire (etude de la commande rapprochee des composants et des interactions puissance/commande)
Polarization Descattering Imaging of Underwater Complex Targets Based on Mueller Matrix Decomposition

The traditional polarization imaging techniques cannot obtain the polarization characteristics with global variation, and the reconstruction of the target with different optical properties concurrently is seriously distorted. In this work, we overcome the aforementioned shortcomings by using the polar decomposition method to estimate the Mueller matrix of the target in the full field of view. Simultaneously, the illumination light with globally varying polarization state is calculated to suppress the noise caused by computational imaging. The descattering imaging experiments through turbid water indicate that the images recovered by our method present the similarity to the targets without scattering, and the noise is suppressed to some extent. Further, we prove the superiority of the proposed method by comparing with other polarization underwater imaging strategies.
Sensitive Detection of CMB B-Mode Polarization: Instrumentation and Systematics

Author(s): Moyerman, Stephanie | Abstract: Numerous experiments in the last two decades have shown that the cosmic microwave background (CMB) is a powerful cosmological probe. The temperature anisotropy of the CMB has now been mapped to exquisite precision by many experiments, yielding tight constraints on the standard LCDM cosmological model. Many current and upcoming experiments focus on measuring CMB polarization, in particular the B-mode polarization, which potentially encodes information from long before the epoch of matter- radiation decoupling. However, the magnitude of the inflationary B-mode signal is constrained by an upper limit of tens of nK, which represents a massive experimental challenge. Foreground contamination and systematic effects, among other factors, further increase the difficulty of detection. A measurement of this signal therefore requires the development of dedicated telescopes with exquisite control of systematics and large kilo-pixel arrays of background limited detectors. This thesis describes my work on Cosmic Microwave Background polarization studies. Specifically, it describes my data analysis efforts on two CMB polarization telescopes, BICEP and POLARBEAR, my contribution to hardware efforts on POLARBEAR, and my design and fabrication work on next generation detector arrays
The ATIC Science Flight in 2002-03: Description and Preliminary Results

The Advanced Thin Ionization Calorimeter (ATIC) balloon experiment completed a 19.7 day science flight, 29 Dec. 02 to 18 Jan. 03, from McMurdo, Antarctica, yielding 65 Gbytes of science data. The instrument was fully recovered just over the trans-Antarctic mountain range. ATIC is designed to make new measurements of the composition and energy spectra of cosmic rays in the region up to 100 TeV total energy. The flight and the instrument performance are described and compared to the ATIC-1 flight from 2000-01. Although the data from this new flight will not be fully processed and analyzed, some preliminary results are discussed.
Assessment of seasonal changes in biochemical composition of freshwater bivalve, Parreysia cylindrica in relation to heavy metal pollution of Jayakwadi reservoir (M.S.), India

The objective of present study is to determine seasonal changes in biochemical content of freshwater bivalve, Parreysia cylindrica in relation to heavy metal pollution of Jayakwadi reservoir. Heavy metal concentrations were determined seasonally from surface water, soil sediment and soft body tissues of freshwater bivalve, Parreysia cylindrica . The heavy metal concentrations in surface water, soil sediment and soft body tissues of Parreysia cylindrica were highest during summer season than winter and monsoon season. The Protein, DNA, RNA and Ascorbic acid content were estimated during summer, monsoon and winter season from mantle, gills, digestive glands and whole soft body tissues. In the present study Protein, DNA, RNA and Ascorbic acid content were highest during monsoon than summer and winter season.
Exact solutions in the Dirac-Born-Infeld effective theory and the fate of tachyon

We show that the equation of motion from the Dirac-Born-Infeld effective action of a general scalar field with some specific potentials admits exact solutions after appropriate field redefinitions. Based on the exact solutions and their energy-momentum tensors, we find that massive scalars and massless scalars of oscillating modes in the DBI effective theory are not pressureless generically for any possible momenta, which implies that the pressureless "tachyon matter" forming at late time of the tachyon condensation process should not really be some massive matter. It is more likely that the tachyon field at late time behaves as a massless scalar of zero modes. At kinks, the tachyon can be viewed as a massless scalar of a translational zero mode describing a stable and static D-brane with one dimension lower. Near the vacuum, the tachyon in regions without the caustic singularities can be viewed as a massless scalar that has the same zero mode solution as a fundamental string moving with a critical velocity. We find supporting evidences to this conclusion by considering a DBI theory with modified tachyon potential, in which the development of caustics near the vacuum may be avoided.
Intrusion detection using deep learning on packet data

Deep learning has made good progress in intrusion detection field due to its powerful adaptive learning capability, but deep learning computes more and more slowly as model layers deepen, and existing deep learning models rely on datasets with artificially designed features, which in turn makes the models need to be deepened to learn the complete features, such data also makes it difficult to generalize the trained model. To solve these problems, we propose a method for extracting packet bytes from PCAP files as features to enable the models to learn the original features. Then propose a deep learning model IDPnet, which mainly employs one dimensional depthwise separable convolution, it regards each packet as channels, learns features through depthwise and pointwise convolution hierarchically, which greatly reduces the inference time while improving the accuracy compared to common CNN models that using converted grayscale image as input. Finally, we conduct transfer learning on IoT dataset, demonstrating that pre-trained model can be reused on data from different devices and protocols using packet data as features, reducing training time.
Hybodontiform Shark Remains (Chondrichthyes, Elasmobranchii) from the Lower Triassic of Yunnan Province, China, with Comments on Hybodontiform Diversity across the PTB

ABSTRACT Hybodontiform shark teeth, cephalic and fin spines as well as placoid scales are reported here for the first time from the continental, Lower Triassic Dongchuan Formation near the village of Zhaojia (Huize County, Yunnan Province) in south-west China. The isolated teeth are assigned to three unidentified hybodontiforms but also to a new species of Parvodus, P. huizodus sp. nov., the oldest record of this small-toothed lonchidiid shark genus, extending its range well down into the Lower Triassic. This new species, together with additional hybodontiform remains, provides new evidence of shark occurrences in the aftermath of the end-Permian mass extinction event, when freshwater environments might have acted as centers of origin rather than refugia for sharks. A review of the species assigned to Parvodus and similar small hybodontiform sharks reveals two distinct ecomorphological groups. Group 1, which is characterized by clutching-type dentitions, includes eight species (three of which remain unnamed) ranging from the Middle Triassic to Lower Cretaceous, while group 2, characterized by cutting-crushing type dentitions, comprises 11 species (six of which remain unnamed) including the type-species, P. rugianus ranging from the Lower Triassic to the Lower Cretaceous. The new fossils documented here reveal that hybodontiforms were already adapted to freshwater environments in the Lower Triassic rather than in the Jurassic in China.
A Thorough Documentation of Obtained Results on Real-Valued Continious and Combinatorial Multi-Objective Optimization Problems Using Diversity Preserving Mixture-Based Iterated Density Estimation Evolutionary Algorithms

In this paper, we present the results of performing experiments with three different multi– objective evolutionary algorithms (MOEAs) on eight different optimization problems. As such, this paper is only an extension of an earlier publication in which one of the three MOEAs is introduced [1]. Although the experiments and the obtained results have already been reported in the earlier publication, not all information could be reported due to space limitations. In this paper, we present even more information about the experiments that were performed.
A UNIFIED APPROACH TO ANALYTICAL SOLUTION OF A HYDROMAGNETIC FREE CONVECTION FLOW

Free convection ow near an in nite vertical plate of an electrically conducting uid of Prandtl number unity has been considered when the ow takes place under the combined in uence of heat ux at the boundary and an externally applied magnetic eld. For the impulsive and accelerated motions of the boundary, uni ed closed form analytical solutions have been obtained for the uid velocity and the skin friction corresponding to the cases of magnetic eld xed relative to the uid or to the boundary. As a special case, an approximation of the solution in terms of exponential functions is also discussed.
Serial Focus Groups: A Longitudinal Design for Studying Interactive Discourse

Focus group methods specialize in the analysis of interactive discourse, but are only rarely employed as a stand-alone method to study such phenomena, owing to inherent limitations concerning the comparability and generalizability of findings. In this paper, we argue that focus groups undergo three kinds of transformations, involving changes in participants’ cognitive states, social ties, and discursive behavior, which raise both analytic challenges and valuable opportunities for the study of shared meanings and interactive negotiation processes in society. Introducing Serial Focus Groups, we extend familiar focus group designs as a method for studying interactive discourse in a longitudinal perspective, capitalizing on the analytic potentials raised by these transformations. Reviewing the methodological literature and drawing upon two large-scale focus group studies of socially interactive sense-making, we argue that serial focus groups can help overcome some of the limitations of cross-sectional focus groups and offer valuable new opportunities for analysis and validation.
Are vegetation influences on Arctic–boreal snow melt rates detectable across the Northern Hemisphere?

The timing and rate of northern high latitude spring snowmelt plays a critical role in surface albedo, hydrology, and soil carbon cycling. Ongoing changes in the abundance and distribution of trees and shrubs in tundra and boreal ecosystems can alter snowmelt via canopy impacts on surface energy partitioning. It is unclear whether vegetation-related processes observed at the ecosystem scale influence snowmelt patterns at regional or continental scales. We examined the influence of vegetation cover on snowmelt across the boreal and Arctic region across a ten-year reference period (2000–2009) using a blended snow water equivalent (SWE) data product and gridded estimates of surface temperature, tree cover, and land cover characterized by the dominant plant functional type. Snow melt rates were highest in locations with a late onset of melt, higher temperatures during the melt period, and higher maximum SWE before the onset of melt. After controlling for temperature, melt onset, and the maximum SWE, we found snow melt rates were highest in evergreen needleleaf forest, mixed boreal forest, and herbaceous tundra compared to deciduous needleleaf forest and deciduous shrub tundra. Tree canopy cover had little effect on snowmelt rate within each land cover type. While accounting for the influence of vegetative land cover type is necessary for predictive understanding of snowmelt rate variability across the Arctic–Boreal region. The relationships differed from observations at the ecosystem and catchment scales in other studies. Thus highlighting the importance of spatial scale in identifying snow-vegetation relationships.