Miracle-dz/UniFAR-FTUs huggingface dataset:
Human Motion Generation Using Variational Recurrent Neural Network

∗ Human motion control, edit, and synthesis are important tasks to create 3D computer graphics video games or movies, because some characters act like humans in most of them. The purpose of this study is to construct a system which can generate various natural character motions. In this study, we consider that the process of human motion generation is complicated and non-linear, and it can be modeled by deep neural network. Since the motion generation process (deep neural network parameters) cannot be observed directly, it needs to be estimated by learning from observable human motion data recorded by motion capture system. On the other hand, the process of inference which is opposite to the generation is also expressed by deep neural network. And inference and generation are performed for human motion data, and the parameters of the both deep neural networks are optimized based on the criteria that the original motion should be obtained through inference and generation processes. In this study, we constructed a human motion generative model using recurrent neural network and variational autoencoders, and confirmed that various human motions can be generated from a low-dimensional latent space.
An Effective Method for Weak Multi-target Detection and Tracking in Clutter Environment

Weak target detection and tracking is a difficult problem, especially in the case of multi-target and strong clutters. Track-before-detect (TBD) is the common method to deal with this problem, and this paper proposes a new effective method based on TBD. Firstly, keystone transform (KT) and phase gradient autofocus (PGA) are used for migration compensation to improve the signal-to-noise ratio (SNR) of moving targets. Then dynamic programming based TBD (DP-TBD) with joint intensity-spatial CFAR (J-CA-CFAR) is presented for noncoherent integration, where J-CA-CFAR uses both intensity and spatial information to achieve automatic target detection. Finally, the effectiveness of the proposed method was demonstrated by experimental results on real data.
Situational expectancy or association? The influence of event knowledge on the N400

ABSTRACT Electrophysiological studies suggest that situational event knowledge plays an important role in language processing, but often fail to distinguish whether observed effects are driven by combinatorial expectations, or simple association with the context. In two ERP experiments, participants read short discourses describing ongoing events. We manipulated the situational expectancy of the target word continuing the event as well as the presence of an associated, but inactive event in the context. In both experiments we find an N400 effect for unexpected compared to expected target words, but this effect is significantly attenuated when the unexpected target is nonetheless associated with non-occurring context events. Our findings demonstrate that the N400 is simultaneously influenced by both simple association with – and combinatorial expectations derived from – situational event knowledge. Thus, experimental investigations and comprehension models of the use of event knowledge must accommodate the role of both expectancy and association in electrophysiological measures.
Proposed Scheme of Pliable Gas Insulated Transmission Line and Its Comparative Appraisal Regarding Electrostatic and Dielectric Aspects

Gas insulated transmission lines (GILs) are being used in electrical systems regarding power transmission and substation interconnection. However, operational complexities of conventional schemes, such as structural rigidity, corrosion protection, gas leakage in case of seismic vibrations, larger bending radius and jointing complexities which restrain their application perspectives, could be curtailed by developing a flexible GIL. In this research paper, a new pliable scheme of gas insulated transmission line is proposed. Further, COMSOL Multiphysics® (version 5.1, COMSOL Inc., Stockholm, Sweden) based electrostatic assay and practically performed high voltage tests-based dielectric analysis is performed for the proposed scheme. Electrostatic appraisal is comprised of field utilization based electrostatic stress analysis. In addition, dimensional optimization of pliable GIL regarding enclosure and pitch sizes in relation to electrostatic stresses and field utilization is also performed. Regarding dielectric perusal, experimental setup has been developed for standard lightning impulse and disruptive discharge tests in order to investigate the synergistic dielectric characteristics of proposed flexible post insulators for pliable GIL. Experimental and simulation appraisal unveil that the proposed scheme exhibits almost analogous electrostatic and dielectric behavior in comparison to the conventional GIL scheme and could simplify the operational intricacies associated with conventional scheme. The proposed modifications could eliminate the requirement of trench development, corrosion protection and acceleration dampers, along with a significant reduction in required land area at bends, due to a smaller bending radius which will ultimately result in substantial cost reduction.
Improving the efficiency of intrusion detection in information systems

Abstract Policy Interaction Graph Analysis is a Host-based Intrusion Detection tool that uses Linux MAC Mandatory access control policy to build the licit information flow graph and uses a detection policy defined by the administrator to extract illicit behaviour from the graph. The main limitation of this tool is the generation of a huge signature base of illicit behaviours; hence, this leads to the use of huge memory space to store it. Our primary goal in this article is to reduce this memory space while keeping the tool’s efficiency in terms of intrusion detection rate and false generated alarms. First, the interactions between the two nodes of the graph were grouped into a single interaction. The notion of equivalence class was used to classify the paths in the graph and was compressed by using a genetic algorithm. Such an approach showed its efficiency compared to the approach proposed by Pierre Clairet, by which the detection rate obtained was 99.9%, and no false-positive with a compression rate of illicit behaviour signature database reached 99.44%. Having these results is one of the critical aspects of realizing successful host-based intrusion detection systems.
Ultra-Low Power CMOS Readout for Resonant MEMS Strain Sensors

This paper presents an ultra-low power, silicon-integrated readout for resonant MEMS strain sensors. The analogue readout implements a negative-resistance amplifier based on first-generation current conveyors (CCI) that, thanks to the reduced number of active elements, targets both low-power and low-noise. A prototype of the circuit was implemented in a 0.18-µm technology occupying less than 0.4 mm2 and consuming only 9 µA from the 1.8-V power supply. The prototype was earliest tested by connecting it to a resonant MEMS strain resonator.
The shape of a word: single word characteristics’ effect on novice L2 listening comprehension

Abstract The purpose of this study was to expand upon available research which quantifies the relationship between single word characteristics and L2 listening comprehension. The effect of single word characteristics on L2 listening have been mostly studied in isolation in past research. Furthermore, little research exists on listening comprehension during the first years of L2 acquisition. To begin filling this gap, 172 English L2 novice participants were administered an isolated phrase transcription test in which participants must quickly attempt to transcribe phrases of four to five words they hear only one time. The independent variable word characteristics in this study were part of speech, phrasal position, word length, frequency, and Minkowski3 sensorimotor norms, an embodiment semantic variable. Word transcription probability (i.e., whether a word was transcribed or not) was analyzed using Rasch analysis and hierarchical linear mixed effects regression. Part of speech and phrasal position did not significantly predict word transcription probability. Word length, frequency, and Minkowski3 sensorimotor norms significantly predicted transcription probability. The findings of this study have implications for the creation of listening texts and theoretical models of L2 listening comprehension.
Analyzing Traditional-Based Teaching Methods Versus Technology-based Teaching Methods in Collegiate Aviation Classrooms

This study is a comparative analysis of traditional-based teaching methods versus technology-based teaching methods in collegiate aviation classrooms. Education is in a transformational period. Technology use in the classroom is a major part of this transformation. However, this change in pedagogy is not occurring as rapid as one might believe. Out of ten undergraduate professors in the United States teaching in higher education, fewer than two seriously use computers and other technologies in their classrooms. Of the ten, four to five professors never use the machines at all. The same is true in collegiate aviation classrooms; technology-based teaching methods and technology use in the classroom for instructional purposes are in the early stages. This study was conducted at a Florida university. The population was aviation students enrolled in a Florida university Aeronautics Program. The sample consisted students enrolled in the technology-based teaching methods course in the spring of 2004. The same course was taught once with traditional-based teaching methods in the spring of 2003. Ex-post facto data was used from the spring 2003 course. The main purpose of the study was to understand how technology-based teaching methods affect student's overall final grade performance in an aviation course, at a Florida university. In the study, the final grade averages of the traditional-based teaching methods course were analyzed between the technology-based teaching methods course. In the spring 2004 (technology-based) the students' perceptions of technology-based teaching methods were correlated with their final grades, and a correlation analysis was run between the students' final grade and their total flight time experience as measured in flight hours. The results of the statistical tests did not yield a statistic at the . 05 alpha level or higher. However, perception survey question #5 did yield a . 042 alpha level. The researcher concludes that technology-based teaching methods may not always improve a students' performance in the class but, it will not hurt a students' performance. The researcher also concludes that if a student perceives technology useful in learning school subjects, then that student will perform better in the specific aviation class than another student who does not believe technology is useful in learning school subjects. However, students' perceptions of technology need to be investigated further. The researcher is compelled to recommend that a qualitative and quantitative research study should be conducted to better understand the coursework performance of aviation students' before and after they become C.F. 1.s in a collegiate aeronautics program. Table of
A natural definition for a bacterial strain and clonal complex .

Large scale surveys of prokaryotic communities (metagenomics) as well as isolate 2 genomes have recently revealed that prokaryotic diversity is predominantly organized in 3 sequence-discrete units that may be equated to species. Specifically, genomes of the same unit 4 (or species) commonly show >95% genome-aggregate average nucleotide identity (ANI) to each 5 other and <90% ANI to members of other species, while genomes showing 90-95% ANI are 6 comparatively rare. However, it remains unclear if such “discontinuities” or gaps in ANI values 7 can be observed within species and thus, be used to define strains or clonal complexes; two 8 cornerstone concepts for microbiology that remain ill-defined. By analyzing 18,123 complete 9 isolate genomes from 330 bacterial species with at least ten genome representatives each, we 10 show that such a natural discontinuity exists at around 99.5% ANI. Further, we show that the 11 99.5% ANI threshold is largely consistent with how clonal complexes have been defined in 12 previous epidemiological studies but provides clusters with ~20% higher accuracy in terms of 13 evolutionary relatedness of the grouped genomes and greater homogeneity in gene content. 14 Collectively, our results should facilitate future micro-diversity studies across clinical or 15 environmental settings because they provide a more natural definition of a clonal complex and 16 strain. 17
A DNase T6SS effector requires its MIX domain for secretion

Gram-negative bacteria often employ the type VI secretion system (T6SS) to deliver diverse cocktails of antibacterial effectors into rival bacteria. In many cases, even when the identity of the delivered effectors is known, their toxic activity and mechanism of secretion are not. Here, we investigate VPA1263, a Vibrio parahaemolyticus T6SS effector that belongs to a widespread class of polymorphic effectors containing a MIX domain. We reveal a C-terminal DNase toxin domain belonging to the HNH nuclease superfamily, and we show that it mediates the antibacterial toxicity of this effector during bacterial competition. Furthermore, we demonstrate that the VPA1263 MIX domain is necessary for T6SS-mediated secretion and intoxication of recipient bacteria. These results are the first indication of a functional role for MIX domains in T6SS secretion. IMPORTANCE Specialized protein delivery systems are used during bacterial competition to deploy cocktails of toxins that target conserved cellular components. Although numerous toxins have been revealed, the activity of many remains unknown. In this study, we investigated such a toxin from the pathogen Vibrio parahaemolyticus. Our findings indicated that the toxin employs a DNase domain to intoxicate competitors. We also showed that a domain used as a marker for secreted toxins is required for secretion of the toxin via a type VI secretion system.
Three-dimensional mitochondrial fission, fusion and depolarisation event location prediction for a high throughput analysis of fluorescence microscopy images

This paper documents the development of a novel method to predict the occurrence and exact locations of mitochondrial fission, fusion and depolarisation events in three dimensions. These occurrence and location of these events were successfully predicted with a three-dimensional version of the Pix2Pix generative adversarial network (GAN) as well as a three-dimensional adversarial segmentation network called the Vox2Vox GAN. The Pix2Pix GAN predicted the locations of mitochondrial fission, fusion and depolarisation events with accuracies of 35.9%, 33.2% and 4.90%, respectively. Similarly, the Vox2Vox GAN achieved accuracies of 37.1%, 37.3% and 7.43%. The accuracies achieved by the networks in this paper are too low for the immediate implementation of these tools in life science research. They do however indicate that the networks have modelled the mitochondrial dynamics to some degree of accuracy and may therefore still be helpful as an indication of where events might occur if time lapse sequences are not available. The prediction of these morphological mitochondrial events have, to our knowledge, never been achieved before in literature. The results from this paper can be used as a baseline for the results obtained by future work.
Desiccation resistance differences in Drosophila species can be largely explained by variations in cuticular hydrocarbons

Maintaining water balance is a universal challenge for organisms living in terrestrial environments, especially for insects, which have essential roles in our ecosystem. Although the high surface area to volume ratio in insects makes them vulnerable to water loss, insects have evolved different levels of desiccation resistance to adapt to diverse environments. To withstand desiccation, insects use a lipid layer called cuticular hydrocarbons (CHCs) to reduce water evaporation from the body surface. It has long been hypothesized that the waterproofing capability of this CHC layer, which can confer different levels of desiccation resistance, depends on its chemical composition. However, it is unknown which CHC components are important contributors to desiccation resistance and how these components can determine differences in desiccation resistance. In this study, we used machine learning algorithms, correlation analyses, and synthetic CHCs to investigate how different CHC components affect desiccation resistance in 50 Drosophila and related species. We showed that desiccation resistance differences across these species can be largely explained by variation in cuticular hydrocarbons. In particular, length variation in a subset of CHCs, the methyl-branched CHCs (mbCHCs), is a key determinant of desiccation resistance. We also showed a significant correlation between the evolution of longer mbCHCs and higher desiccation resistance. Given the ubiquitous presence of mbCHCs in insects, the evolution of mbCHCs may be a general mechanism of how insects evolve desiccation resistance and adapt to diverse and changing environments. Significance As our planet is becoming more arid due to global warming, preventing dehydration is key to the survival of insects, an essential part of our ecosystem. However, factors that determine how insects may evolve resistance to desiccation are relatively unknown. Using Drosophila species from diverse habitats, we showed that variations in the composition of cuticular hydrocarbons (CHCs), a hydrophobic layer found on insects to prevent evaporative water loss, can largely explain desiccation resistance differences. In addition, the evolution of longer methyl-branched CHCs (mbCHCs), underlies the evolution of higher desiccation resistance in this genus. As mbCHCs are ubiquitously present in most insects, we suggest that evolutionary changes in mbCHCs may be a general determinant of desiccation resistance across insect species.
Are cell wall traits a component of the succulent syndrome?

Succulence is an adaptation to low water availability characterised by the presence of water-storage tissues that alleviate water stress under low water availability. The succulent syndrome has evolved convergently in over 80 plant families and is associated with anatomical, physiological and biochemical traits. Despite the alleged importance of cell wall traits in drought responses, their significance in the succulent syndrome has long been overlooked. Here, by analysing published pressure–volume curves, we show that elastic adjustment, whereby plants change cell wall elasticity, is uniquely beneficial to succulents for avoiding turgor loss. In addition, we used comprehensive microarray polymer profiling (CoMPP) to assess the biochemical composition of cell walls in leaves. Across phylogenetically diverse species, we uncover several differences in cell wall biochemistry between succulent and non-succulent leaves, pointing to the existence of a ‘succulent glycome’. We also highlight the glycomic diversity among succulent plants, with some glycomic features being restricted to certain succulent lineages. In conclusion, we suggest that cell wall biomechanics and biochemistry should be considered among the characteristic traits that make up the succulent syndrome.
Software assistant for management tasks in a fish farm

iii ACKNOWLEDGEMENTS . iv TABLE OF CONTENTS . v List of Figures. vii Glossary. viii 1. Background Information. 1 2. Getting Started . 4 3. Existing Processes . 7 3.1 Fish Order Invoice/Worksheet . 7 3.2 Cutting Report. 7 3.3 Smoke Assessment . 7 3.4 E-mails. 8 4. Fish Processing Application . 9 4.1 Requirement Gathering . 9 4.2 Roles and Responsibilities . 11 4.3 Cross Cutting Concerns . 13 4.4 Benefits of the Software Assistant . 13 5. Application Architecture . 15 5.1 Spring Framework . 17 5.2 Hibernate Persistence . 18 5.3 Tiles View. 19 5.4 Spring Webflow Controller. 20 5.5 AJAX, DWR, and DOJO. 21 5.6 Apache POI. 23 5.7 Source Control. 23 6. Detailed Design . 24 6.1 Entity Classes and Database Design. 24 6.2 Business Logic and Persistence Classes . 28 7. User Interface Design. 31 8. Testing . 35 8.1 Project Challenges. 37 9. Continuing Work . 39 10. Conclusion . 40 11. Bibliography . 41 12. Appendices . 42 Appendix A. Sample Fish Order Screens . 42 Appendix B. Sample E-mail Screens . 51 Appendix C. Sample Cutting Report Screens . 55 Appendix D. Sample Smoke Assessment Screens . 5960
A Model for Predicting Ischemic Stroke Using Data Mining Algorithms

Data mining appears in the middle of the 1990s in the United States as a new discipline at the interface of Statistics and Information Technology: databases, artificial intelligence, machine learning. Along with advanced researches in health Domain monstrous of data are available, but the main difficulty is how to cultivate the existing information into a useful practices. Data mining has a great potential to enable healthcare systems to use data more effectively. Hence, DM improves care and reduces costs. In this paper, we used the various Data Mining techniques such as classification, logistic regression in health domain to predict Ischemic Stroke.
Orthogonal Simplex Chebyshev-Laguerre Cubature Kalman Filter Applied in Nonlinear Estimation Systems

: To further improve the ﬁltering accuracy in nonlinear estimation systems, a nonlinear ﬁlter, called the orthogonal simplex Chebyshev-Laguerre cubature Kalman ﬁlter (OSCL-CKF), is proposed. The ﬁlter is built within the cubature Kalman ﬁlter framework, which transforms the multidimensional, Gaussian weighted integral into a spherical-radial coordinate system. In the spherical integral, an orthogonal method is introduced to the third-degree spherical simplex rule, and then the nonlocal sampling effects can be reduced by tuning the high order interference terms. In the radial integral, the quadrature points and corresponding weights are determined according to the Chebyshev-Laguerre (CL) equation, which enables the nonlinear ﬁlter to improve the precision by the order of the CL polynomial. Numerical results show that the proposed ﬁlter outperforms the conventional algorithms.
Research on Plug-in Hybrid Electric Vehicle Bus Utility Factor Based on Real-World Data

The energy consumption and emission of plug-in hybrid electric vehicle (PHEV) vary with the use characteristics of the vehicle and the proportion of pure electric mileage. Based on the actual road operation data of 169 PHEV buses in six typical cities such as Beijing and Shanghai in 2018, this paper analyzes the use characteristics (including travel characteristics and charging characteristics) of PHEV buses by constructing the characteristic data set, and studies the calculation method of pure electric mileage proportion based on the use characteristics. One of the most important results is that the actual charging frequency of PHEV buses in China is low, the charging power is small, basically with no charging travel behavior characteristics, resulting in a significant reduction in utility factor, which will make the actual energy saving and emission reduction effect greatly reduced. The research reflects the use status of PHEV buses in typical cities of China, which can lay a foundation for the research on energy consumption and emission test methods of PHEV buses, and provide suggestions for the formulation of test methods and standards for energy consumption and emission of PHEV buses.