Miracle-dz/UniFAR-FTUs huggingface dataset:
TANGIBLE INTERFACE GAME FOR STIMULATING CHILD LANGUAGE COGNITIVE SKILL

The intervention for cognitive language development is required to be conducted at a young age. As children usually gain the skill through their play, this study proposed a physical interactive game to help children improve their language skill in both Thai and English language for pre-schoolers. The motivation of this research is to create a game that has characteristics of a toy where children require bodily engagement with the objects to enhance their cognitive processes to effectively develop language skills. The research proposed and developed a novel game system underpinned by the interactive technologies. The game is evaluated by three methods: paired t-test is used to determine the overall performance of the proposed game; the 90/90 standard evaluation is also applied to see whether if the game is used for formal education the majority of the group (>90%) will achieve the objective of learning. Also, the feedbacks from expert validation are collected. All three evaluation methods indicate the primary success of the game is to assist Thai pre-schoolers in improving their skill at a young age.
Integrated Weed Management in Transplanted Rice (Oryza sativa)

A field experiment was conducted during the kharif season of 2010 and 2011 at the Regional Research Station, Kalimpong (1250 m a.s.l), to find out eff ective and suitable method of weed control in transplanted rice under mid hill conditions. The major weed found in control plot were Echinochloa crus-galli, Echinochloa colonum, Cynodon dactylon Cyperus rotundus, Cyperusiria, Cyperus difformis, Fimbristylis miliaceae, Ammania baccifera, Ludwigia parviflora. Pre-emergence application of metsulfuron methyl + chlorimuron ethyl supplemented with one hand weeding at 40 DAT, provided a broad - spectrum weed control and was significantly superior to rest all other integrated approach of weed control. The highest weedcontrol efficiency (91.4%) was also recorded under this treatment. The grain yield was highest with hand weeding thrice (6.61 t/ha) which was comparable with treatment of metsulfuron methyl + chlorimuron ethyl (0.005 kg/ha) supplemented with one hand weeding (6.47 t/ha). The highest benefit: cost ratio was with metsulfuron methyl + chlorimuron ethyl (0.005 kg/ha) supplemented with one hand weeding at 40 DAT (2.18) and was followed by pretilachlor (0.5 kg/ha) followed by one hand weeding (2.14). Metsulfuron methyl + chlorimuron ethyl (0.005 kg/ha) followed by one hand weeding at 40 DAT controlled weed population and gave yield a ributing traits and yield comparable to those of hand weeding thrice and proved more remunerative than other weed management practices.
Isolation and characterization of α ‐amylase encoding gene in Bacillus amyloliquefaciens PAS

Amylolytic bacteria are a source of amylase, which is an essential enzyme to support microalgae growth in the bioreactor for microalgae culture. In a previous study, the highest bacterial isolate to hydrolyze amylum (namely PAS) was successfully isolated from Ranu Pani, Indonesia, and it was identified as Bacillus amyloliquefaciens. That bacterial isolate (B. amyloliquefaciens PAS) also has been proven to accelerate Chlorella vulgaris growth in the mini bioreactor. This study aims to detect, isolate, and characterize the PAS’s α‐amylase encoding gene. This study was conducted with DNA extraction, amplification of α‐amylase gene with polymerase chain reaction (PCR) method with the specific primers, DNA sequencing, phylogenetic tree construction, and protein modeling. The result showed that α‐amylase was successfully detected in PAS bacterial isolate. The α‐amylase DNA fragment was obtained 1,468 bp and that translated sequence has an identity of about 98.3% compared to the B. amylolyquefaciens α‐amylase 3BH4 in the Protein Data Bank (PDB). The predicted 3D protein model of the PAS’s α‐amylase encoding gene has amino acid variations that predicted affect the protein’s structure in the small region. This research will be useful for further research to produce recombinant α‐amylase.
YARA-Signator: Automated Generation of Code-based YARA Rules

Effective detection and identiﬁcation signatures are an important component in the toolkit for malware analysis. The creation of such signatures is still widely a manual task that requires notable experience and knowledge on the side of analysts. In this paper, we present YARA-Signator, an approach for the automated generation of code-based YARA rules. The method is based on the isolation of instruction n-grams that on the one hand appear frequently within a malware family and on the other hand are not found in any other family. Applying YARA-Signator to the Malpedia data set, we show that in fact on average 51.85% of the instruction n-grams of length 4 and higher are only found in the respective family. The rules produced by the system using this data set achieve an overall F1 score of 0.983 and cause only very few false positives in a sanity check against a large goodware data set. YARA-Signator is made available as open source and a periodically updated reference rule set is provided for free through Malpedia.
Polysaccharide Based Polymers Produced by Scabby Cankered Cactus Pear (Opuntia ficus-indica L.) Infected by Neofusicoccum batangarum: Composition, Structure, and Chemico-Physical Properties

Neofusiccocum batangarum is the causal agent of scabby canker of cactus pear (Opuntia ficus-indica L.). The symptoms of this disease are characterized by crusty, perennial cankers, with a leathery, brown halo. Characteristically, a viscous polysaccharide exudate, caking on contact with air, leaks from cankers and forms strips or cerebriform masses on the surface of cactus pear cladodes. When this polysaccharide mass was partial purified, surprisingly, generated a gel. The TLC analysis and the HPLC profile of methyl 2-(polyhydroxyalkyl)-3-(o-tolylthiocarbomoyl)-thiazolidine-4R-carboxylates obtained from the mixture of monosaccharides produced by acid hydrolysis of the three EPSs examined in this research work [the polysaccharide component of the exudate (EPSC) and the EPSs extracted from asymptomatic (EPSH) and symptomatic (EPSD) cladodes] showed the presence of d-galactose, l-rhamnose, and d-glucose in a 1:1:0.5 ratio in EPSC while d-galactose, l-rhamnose, d-glucose, and d-xylose at the same ratio were observed in EPSH and EPSD. The presence of uronic acid residues in EPSC was also showed by solid state NMR and IR investigation. Furthermore, this manuscript reports the chemical-physical characterization of the gel produced by the infected cactus pear.
Room acoustics simulations using head-related transfer functions of children and adults

Today, the evaluation of the acoustic quality of classrooms is mainly based on parameters such as late reverberation and noise level. However, when designing/optimizing classrooms the teaching situation must be considered, too. Especially the speech perception under the influence of deficient noise and reverberation in various classroom types are of high acoustic interest. In addition, the speech perception is heavily affected by different kinds and levels of noise inside the classroom. Thus, the whole binaural room acoustic situation has to be taken into account for a more realistic evaluation. Furthermore, recent investigations have shown that the differences between head-related transfer functions of children and adults are significant and cannot be neglected. In this contribution room acoustic simulations of classrooms are presented and discussed. In order to gain an impression of the room's influences on speech perception, the simulations are carried out with various setups using deficient noise and three different types of receivers (microphone, child, adult).
Comprehensive meta-analysis of associations between temperament and character traits in Cloninger’s psychobiological theory and mental disorders

Objective To explore the relationship between temperament and character traits in Cloninger’s psychobiological theory and mental disorders. Methods: A systematic literature search was conducted of five international databases for all articles published in English between January 1990 and April 2019 (PROSPERO-CRD42019133214). Owing to heterogeneity, pooled estimates of correlations for personality disorders and standardized mean differences for case–control studies related to other mental disorders were calculated using the random-effects method. Results The pooled effect sizes obtained from 149 studies showed that high harm avoidance (related to 22/24 diagnostic categories), low self-directedness (21/23), low cooperativeness (17/23), high self-transcendence (14/23), low reward dependence (11/24), high novelty-seeking (10/24), low novelty-seeking (7/24), high persistence (2/23), low persistence (2/23) and high reward dependence (2/24) were related to psychopathology. Conclusions All traits provided unique psychobiological tools for differential diagnosis of mental disorders. However, high harm avoidance and low self-directedness played a canonical role in psychopathology. Despite the study limitations, additional studies are warranted to evaluate the differential diagnoses suggested by the present model.
Deep Convolutional Neural Networks for Accurate Diagnosis of COVID-19 Patients Using Chest X-Ray Image Databases from Italy, Canada, and the USA

Introduction: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), famously known as COVID-19, has quickly become a global pandemic. Chest X-ray (CXR) imaging has proven reliable, fast, and cost-effective for identifying COVID-19 infections, which presents with atypical unilateral patchy infiltration in the lungs like typical pneumonia. We employed the deep convolutional neural network (DCNN) ResNet-34 to detect and classify CXR images from patients with COVID-19, other viral pneumonias, and normal controls. Methods: We created a single database, containing 781 source CXR images for COVID-19 (n=240), other viral pneumonias (n=274), and normal controls (n=267) from four different international sub-databases: the Società Italiana di Radiologia Medica e Interventistica (SIRM), the GitHub Database, the Radiology Society of North America (RSNA), and the Kaggle Chest X-Ray Database. Images were resized, normalized without any augmentation, and arranged in m batches of 16 images before supervised training, testing, and cross-validation of the DCNN classifier. Results: The ResNet-34 had a diagnostic accuracy as of the receiver operating characteristic (ROC) curves of the truepositive rate versus the false-positive rate with the area under the curve (AUC) of 1.00, 0.99, and 0.99, for COVID-19, other viral pneumonia, and normal control CXR images, respectively. This accuracy implied identical high sensitivity and specificity values of 100%, 99%, and 99% for the three groups, respectively. ResNet-34 achieved identical sensitivity and specificity of 100%, 99.6%, and 98.9% for classifying CXR images of the three groups, with an overall accuracy of 99.5% for the testing subset for diagnosis/prognosis. Conclusion: Based on this high classification precision, we believe that the output activation map of the final layer of the ResNet-34 is a powerful tool for the accurate diagnosis of COVID-19 infection from CXR images.
Predication of the Effector Proteins Secreted by Fusarium sacchari Using Genomic Analysis and Heterogenous Expression

One of the causative agents of pokkah boeng disease (PBD), which affects sugarcane crops globally, is the fungus Fusarium sacchari. These fungal infections reduce sugar quality and yield, resulting in severe economic losses. Effector proteins play important roles in the interactions between pathogenic fungi and plants. Here, we used bioinformatic prediction approaches to identify 316 candidate secreted effector proteins (CSEPs) in the complete genome of F. sacchari. In total, 95 CSEPs contained known conserved structures, representing 40 superfamilies and 18 domains, while an additional 91 CSEPs contained seven known motifs. Of the 130 CSEPs containing no known domains or motifs, 14 contained one of four novel motifs. A heterogeneous expression system in Nicotiana benthamiana was used to investigate the functions of 163 CSEPs. Seven CSEPs suppressed BAX-triggered programmed cell death in N. benthamiana, while four caused cell death in N. benthamiana. The expression profiles of these eleven CSEPs during F. sacchari infection suggested that they may be involved in sugarcane-F. sacchari interaction. Our results establish a basis for further studies of the role of effector molecules in pathogen–sugarcane interactions, and provide a framework for future predictions of pathogen effector molecules.
An Improved Inter-Intra Contrastive Learning Framework on Self-Supervised Video Representation

In this paper, we propose a self-supervised contrastive learning method to learn video feature representations. In traditional self-supervised contrastive learning methods, constraints from anchor, positive, and negative data pairs are used to train the model. In such a case, different samplings of the same video are treated as positives, and video clips from different videos are treated as negatives. Because the spatio-temporal information is important for video representation, we set the temporal constraints more strictly by introducing intra-negative samples. In addition to samples from different videos, negative samples are extended by breaking temporal relations in video clips from the same anchor video. With the proposed Inter-Intra Contrastive (IIC) framework, we can train spatio-temporal convolutional networks to learn feature representations from videos. Strong data augmentations, residual clips, as well as head projector are utilized to construct an improved version. Three kinds of intra-negative generation functions are proposed and extensive experiments using different network backbones are conducted on benchmark datasets. Without using pre-computed optical flow data, our improved version can outperform previous IIC by a large margin, such as 19.4% (from 36.8% to 56.2%) and 5.2% (from 15.5% to 20.7%) points improvements in top-1 accuracy on UCF101 and HMDB51 datasets for video retrieval, respectively. For video recognition, over 3% points improvements can also be obtained on these two benchmark datasets. Discussions and visualizations validate that our IICv2 can capture better temporal clues and indicate the potential mechanism.
ERF Transcription Factor OsBIERF3 Positively Contributes to Immunity against Fungal and Bacterial Diseases but Negatively Regulates Cold Tolerance in Rice

We previously showed that overexpression of the rice ERF transcription factor gene OsBIERF3 in tobacco increased resistance against different pathogens. Here, we report the function of OsBIERF3 in rice immunity and abiotic stress tolerance. Expression of OsBIERF3 was induced by Xanthomonas oryzae pv. oryzae, hormones (e.g., salicylic acid, methyl jasmonate, 1-aminocyclopropane-1-carboxylic acid, and abscisic acid), and abiotic stress (e.g., drought, salt and cold stress). OsBIERF3 has transcriptional activation activity that depends on its C-terminal region. The OsBIERF3-overexpressing (OsBIERF3-OE) plants exhibited increased resistance while OsBIERF3-suppressed (OsBIERF3-Ri) plants displayed decreased resistance to Magnaporthe oryzae and X. oryzae pv. oryzae. A set of genes including those for PRs and MAPK kinases were up-regulated in OsBIERF3-OE plants. Cell wall biosynthetic enzyme genes were up-regulated in OsBIERF3-OE plants but down-regulated in OsBIERF3-Ri plants; accordingly, cell walls became thicker in OsBIERF3-OE plants but thinner in OsBIERF3-Ri plants than WT plants. The OsBIERF3-OE plants attenuated while OsBIERF3-Ri plants enhanced cold tolerance, accompanied by altered expression of cold-responsive genes and proline accumulation. Exogenous abscisic acid and 1-aminocyclopropane-1-carboxylic acid, a precursor of ethylene biosynthesis, restored the attenuated cold tolerance in OsBIERF3-OE plants while exogenous AgNO3, an inhibitor of ethylene action, significantly suppressed the enhanced cold tolerance in OsBIERF3-Ri plants. These data demonstrate that OsBIERF3 positively contributes to immunity against M. oryzae and X. oryzae pv. oryzae but negatively regulates cold stress tolerance in rice.
Wave propagation in inhomogeneous media via FE/PML method

The Perfectly Matched Layer (PML) method is an efficient approach to imposing radiation conditions at the bounded region of interest in case of wave propagation in unbounded domains. This paper presents and validates 3D FE/PML numerical schemes based on two different PML formulations for homogeneous and inhomogeneous geological media exhibiting discrete or continuous inhomogeneity. In the equation of motion for the PML domain the applied stretching behavior is expressed either as complex material properties or as complex coordinates. Both PML formulations are implemented in the FEM and verified against analytical solutions. Three different types of material inhomogeneity are considered: layered half‐space, continuously inhomogeneous half‐space with linear velocity profile and continuously inhomogeneous half‐space with nonlinear velocity profile. Sensitivity analyses are conducted, and the performance of the developed numerical schemes is investigated taking into account a broad variation of the PML parameters. Recommendations are given for the optimal values of the PML parameters for the case of homogeneous and inhomogeneous geological media.
Optimal Event-Based Policy for Remote Parameter Estimation in Wireless Sensing Architectures Under Resource Constraints

Energy is a resource bottleneck in wireless sensing networks (WSNs) relying on energy harvesting for their operations. This is pronounced in WSNs whose data is used for remote parameter estimation because only a subset of the measured information can be transmitted to the estimator. While much attention has been separately paid to communication schemes for energy-aware data transmission in WSNs under resource constraints and controlled parameter estimation, there has yet to emerge a censoring policy that minimizes the variance of a measured process’ estimated component parameters subject to realistic constraints imposed by the WSN. Consequently, this paper presents the derivation of an optimal event-based policy governing data collection and transmission that accounts for energy and data buffer sizes, stochastic models of harvested energy and event arrivals, value of information of measured data, and temporal death. The policy is optimal in the sense that it maximizes the information rate of transmitted data, thereby producing the best possible estimates of the process parameters using the modified maximum likelihood estimation given the system constraints. Experimental and simulation-based results reflect these objectives and illustrate that the framework is robust against significant uncertainty in the initial parameter estimates.
Stakeholder Engagement: Past, Present, and Future

Stakeholder engagement has grown into a widely used yet often unclear construct in business and society research. The literature lacks a unified understanding of the essentials of stakeholder engagement, and the fragmented use of the stakeholder engagement construct challenges its development and legitimacy. The purpose of this article is to clarify the construct of stakeholder engagement to unfold the full potential of stakeholder engagement research. We conduct a literature review on 90 articles in leading academic journals focusing on stakeholder engagement in the business and society, management and strategy, and environmental management and environmental policy literatures. We present a descriptive analysis of stakeholder engagement research for a 15-year period, and we identify the moral, strategic, and pragmatic components of stakeholder engagement as well as its aims, activities, and impacts. Moreover, we offer an inclusive stakeholder engagement definition and provide a guide to organizing the research. Finally, we complement the current understanding with a largely overlooked dark side of stakeholder engagement. We conclude with future research avenues for stakeholder engagement research.
Motion generation for walking exoskeleton robot using multiple dynamic movement primitives sequences combined with reinforcement learning

Abstract In order to assist patients with lower limb disabilities in normal walking, a new trajectory learning scheme of limb exoskeleton robot based on dynamic movement primitives (DMP) combined with reinforcement learning (RL) was proposed. The developed exoskeleton robot has six degrees of freedom (DOFs). The hip and knee of each artificial leg can provide two electric-powered DOFs for flexion/extension. And two passive-installed DOFs of the ankle were used to achieve the motion of inversion/eversion and plantarflexion/dorsiflexion. The five-point segmented gait planning strategy is proposed to generate gait trajectories. The gait Zero Moment Point stability margin is used as a parameter to construct a stability criteria to ensure the stability of human-exoskeleton system. Based on the segmented gait trajectory planning formation strategy, the multiple-DMP sequences were proposed to model the generation trajectories. Meanwhile, in order to eliminate the effect of uncertainties in joint space, the RL was adopted to learn the trajectories. The experiment demonstrated that the proposed scheme can effectively remove interferences and uncertainties.
Molecular Genetic Analysis with Microsatellite-like Loci Reveals Specific Dairy-Associated and Environmental Populations of the Yeast Geotrichum candidum

Geotrichum candidum is an environmental yeast, also found as part of the cheese surface microbiota, where it is important in the ripening of many traditional cheeses, such as Camembert. We have previously developed a Multi Locus Sequence Typing (MLST) scheme, which differentiated five clades, of which one contained only environmental isolates, two were composed almost entirely of dairy isolates, and two others contained a mixture of dairy, environmental, and miscellaneous food isolates. In order to provide a simple method to uniquely type G. candidum strains, and in addition to permit investigation of the population structure at a fine level, we describe here a molecular analysis using a set of twelve highly discriminating microsatellite-like markers. The present study consolidates the previously suggested division between dairy and environmental strains, and in addition distinguishes a specifically European group of environmental strains. This analysis permitted the discrimination of 72 genotypes from the collection of 80 isolates, while retaining the underlying meaningful phylogenetic relation between groups of strains.
Biobased Composites by Photoinduced Polymerization of Cardanol Methacrylate with Microfibrillated Cellulose

Biobased monomers and green processes are key to producing sustainable materials. Cardanol, an aromatic compound obtained from cashew nut shells, may be conveniently functionalized, e.g., with epoxy or (meth)acrylate groups, to replace petroleum-based monomers. Photoinduced polymerization is recognized as a sustainable process, less energy intensive than thermal curing; however, cardanol-based UV-cured polymers have relatively low thermomechanical properties, making them mostly suitable as reactive diluents or in non-structural applications such as coatings. It is therefore convenient to combine them with biobased reinforcements, such as microfibrillated cellulose (MFC), to obtain composites with good mechanical properties. In this work a cardanol-based methacrylate monomer was photopolymerized in the presence of MFC to yield self-standing, flexible, and relatively transparent films with high thermal stability. The polymerization process was completed within few minutes even in the presence of filler, and the cellulosic filler was not affected by the photopolymerization process.