Miracle-dz/UniFAR-FTUs huggingface dataset:
Supplementary Material for Paper 3233: Towards Fast Training of More Robust Models Against Adversarial Attacks

Table 1 shows the accuracy against other white-box attacks. We compare with the winner, TRADES [6], in NeurIPS18 Adversarial Vision Challenge. We use the default settings in the Cleverhands package to generate the attacks. “MI” refers to the MI-FGSM method [2]. “Ori-CW” refers to the original CW attack [1], and the two numbers refer to two common sets of hyper-parameters: {const=100, confid=0, lr=1e-1, max iter=1e2} / {const=100, confid=0, lr=1e-2, max iter=1e3}. “DF-l2” refers to the DeepFool attack with l2-norm [4]. We see that our models generally outperform the baseline, except against the DeepFool attack. We note that our network is smaller, and our training method is an-order-of-magnitude faster1.
Implications for Adoptive Immunotherapy Lymphocytes Is Induced by IL-12: Expression of CD94/NKG2-A on Human T

NK cell receptors (NKRs) are expressed on a subset of human T cells, predominantly CD8 (cid:1) , within which they can modulate TCR-mediated functions. In an attempt to identify the mechanisms leading to NKR expression, we analyzed the capacity of IL-12 to modulate the expression by T cells of the components of the CD94/NKG2-A inhibitory receptor, a member of the C-type lectin-like family of NKR. We show that IL-12 induces the expression of NKG2-A and/or CD94 by CD8 (cid:1) T cells in culture, and that this induction was mediated neither by IFN- (cid:2) nor by IL-15. We also show, using the redirected killing assay, that IL-12-induced expression of both CD94 and NKG2-A led to the acquisition by T cells of a functional inhibitory receptor. Expression of the CD94/NKG2-A inhibitory receptor was also induced by IL-12 during T cell Ag stimulation so that in the presence of this cytokine a high proportion of melanoma-reactive CTL induced from PBL by melanoma peptide stimulation expressed this receptor. This study emphasizes the implication of IL-12 in the modulation of immune responses through NKR induction. The Journal of Immunology, 2002, 168: 4864–4870.
NONEQUILIBRIUM FLOW COMPUTATIONS I . An Analysis of Numerical Formulations of Conservation Laws

Modern numerical techniques employing properties of flux Jacobian matrices are extended to general, nonequilibrium flows. Generalizations of the BeamWarming scheme, Steger-Warming and van Leer flux-vector splittings, and Roe’s approximate Riemann solver are presented for three-dimensional, time-varying grids. The analysis is based on a thermodynamic model that includes the most general thermal and chemical nonequilibrium flow of an arbitrary gas. Various special cases are also discussed.
ANALYZING STUDENTS’ ATTITUDES TOWARDS THE ADOPTION OF E- LEARNING: THE CASE OF TECHNICAL VOCATIONAL SCHOOLS

─ABSTRACT ─ In response to the educational opportunities made available by dramatic technological innovations, e-learning practices are being adopted in secondary education to help the next generation of school children to be better educated and better prepared for the evolving demands of the new economy. However the adoption of e-learning in Greece is still in its infancy. Knowing exactly how students perceive e-learning and web based technologies is an important first step. The survey aims at assessing the experience, skills and computer efficacy of students of Technical Vocational Schools, measuring their attitudes towards the use of education technology and distinguishing obstacles and drivers for the development of an e-learning environment
ANTAGONISTIC EFFECT OF Bacillus pumilus AND/OR Trichoderma viride AGAINST Fusarium solani OF COMMON BEAN

Root rot disease, caused by Fusarium solani f. sp. phaseoli, is one of the main root diseases impacting production of common bean in Egypt. The antagonistic effects of Bacillus pumilus and Trichoderma viride, were tested against F. solani, in vitro and in greenhouse conditions. In vitro tests, B. pumilus and T. viride significantly reduced the mycelial growth of pathogenic fungi. In greenhouse experiment, B. pumilus and T. viride, as soil treatments, significantly reduced the pre and post-emergence damping off disease incidence of F. solani under artificial infection. The percentages of disease incidence in treated plants ranged from 26.2 to 30.0%, compared to 72.0% in control plants, in both pre and post-emergence stages, respectively. The best protection of damping off disease was obtained by T. viride, followed by B. pumilus . All treatments improved the survival plant and growth parameters. Results showed increased levels of peroxidase and polyphenoloxidase activities in treated bean plants, compared to untreated ones.
CCR5D32 Genotypes in a German HIV-1 Seroconverter Cohort and Report of HIV-1 Infection in a CCR5D32 Homozygous Individual

Background: Homozygosity (D32/D32) for the 32 bp deletion in the chemokine receptor 5 (CCR5) gene is associated with strong resistance against HIV infection. Heterozygosity is associated with protection of HIV-1 disease progression. Methodology/Principal Findings: We genotyped a population of 737 HIV-positive adults and 463 healthy controls for the CCR5D32 deletion and found heterozygous frequencies of 16.2% (HIV-negative) and 17.5% (HIV-positive) among Caucasian individuals. Analysis of CCR5D32 influence on disease progression showed notably lower viral setpoints and a longer time to a CD4 count of ,200 ml in seroconverters heterozygous for the deletion. Furthermore, we identified one HIV-positive man homozygous for the D32 deletion. Conclusions/Significance: The protective effect of CCR5 D32 heterozygosity is confimed in a large cohort of German seroconverters. The HIV-infected CCR5 D32 homozygous individual, however, displays extremely rapid disease progression. This is the 12th case of HIV-infection in this genotype described worldwide. Citation: Oh D-Y, Jessen H, Kücherer C, Neumann K, Oh N, et al. (2008) CCR5D32 Genotypes in a German HIV-1 Seroconverter Cohort and Report of HIV-1 Infection in a CCR5D32 Homozygous Individual. PLoS ONE 3(7): e2747. doi:10.1371/journal.pone. 0002747 Editor: Srikanth Tripathy, National AIDS Research Institute, India Received May 12, 2008; Accepted June 29, 2008; Published July 23, 2008 Copyright: 2008 Oh et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: D. -Y. O. is a recipient of a Rahel Hirsch Grant of the Charité-Universitätsmedizin Berlin. R.R. S. was supported by grants obtained from the Deutsche Forschungsgemeinschaft (DFG). Competing Interests: The authors have declared that no competing interests exist. * E-mail: doh@tuftsmedicalcenter.org ¤ Current address: The Floating Hospital for Children at Tufts Medical Center, Boston, Massachusetts, United States of America . These authors contribute equally to this work.
The impact of public support on firms’ R&D investment: Evidence from Slovenia

Private R&D investment in the business sector is often subject to the market failures, asymmetric information and risk, which makes their level lower than socially desirable level. This constitutes the main reason why many modern governments around the world provide different R&D public policy instruments for stimulating firms’ R&D investment. Accordingly, the main aim of this paper is to establish the impact of public support on firm’ R&D investment in Slovenia. The research will take into the account R&D subsidies as a way of direct funding and R&D tax incentives as a way of indirect funding. The paper therefore takes advantages of the unique database of Slovenian companies for the period 2012-2016. The empirical results of the multiple linear regression models on a sample of 3,113 company-year observations show that public support for R&D investment plays an important role in terms of firms’ R&D expenditures. For R&D subsidies, the empirical results show that they are in general not effective since they displace firms’ R&D expenditures. However, they are effective when they are used in a combination with R&D tax incentives and when growing companies receive them. Moreover, the empirical results reveal that R&D tax incentives are effective in any case, when companies have sufficient tax base. The findings are beneficial especially for policymakers in terms of designing R&D public support policies for R&D investment in the future.
Measurement error modelling from a Bayesian perspective

In this talk, we examine the Bayesian formulation of general measurement error problems in epidemiological studies. Measurement error problems are concerned with inference on regression coe cients for an outcome Y in terms of covariates X, in cases where X is not measured accurately on all subjects, but information on X is available through the recording of an imperfect surrogate U . It is well known that regressing Y on U and ignoring measurement error can be seriously misleading, and many methods have been proposed for countering this (see for example Carroll, Ruppert and Stefanski, 1995). Bayesian analysis of measurement error problems has been developed from the seminal work of Clayton (1992). It is based on structural speci cations and functional speci cations. Structural speci cations entail the formulation of three submodels: a regression model relating X and Y , a measurement model relating U and X and a prior model p(Xj ) for the prior distribution of X. These submodels are linked through a graphical model using suitable conditional independence assumptions. Information on the measurement error process can be built in a exible way into the graphical model (Richardson and Gilks, 1993).
HUMAN POSTURE DETECTION WITH THE HELP OF LINEAR SVM AND HOG FEATURE ON GPU

Detection of human posture is a research topic in visual research which finds its application in many areas such as intelligent digital content manager, social robotics and human activity reorganization, crowd behavior analysis and control, etc. Apart from this human posture detection is also used in pedestrian detection, 2D-3D animation, surveillance and robotics. Using the human posture detection method in real system is a challenging problem. As it require to compute the detection process in real time. Parallel computation provides the functionality to run the computation in minimum time utilizing all the resources. This paper provides an approach to run the human detection system with parallel feature extraction method in GPU. Support vector machine is a suitable technique for high dimensional feature space such as an image. HOG and BO features are combined together to form a single feature called fusion feature vector with linear SVM and better results are observed. To reduce the time the support vector machine is used by running the HOG feature in parallel with the help of GPU. By calculating features in parallel the time required for computation is reduced. The method is capable of detecting the human posture with SVM and fusion feature vector for INRIA dataset.
Planned AlltoAllv

The MPI AlltoAllv operation is generally based on a large number of point-to-point messages being sent by all the processes in the communication. This report aims to discover whether this process can be optimised for a clustered architecture by collating the data from all the processors within a node into a shared memory segment and then sending all the data for one node using a single message. This planned method has the potential to decrease overheads by greatly reducing the number of messages sent, and therefore diminishing latency, of the AlltoAllv call. We compare the performance of the planned AlltoAllv with that of the standard MPI AlltoAllv on a number of clustered architectures, and find that for a standard benchmark the planned AlltoAllv can perform considerably better than the MPI version, but for a more realistic benchmark the performance benefit is not as great.
Laminar fMRI at ultra-high fields: Acquisition and analysis strategies

• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
About preparation of students of higher education institution for professional activity in the course of studying of elective disciplines

Problems of formation of readiness of students of higher education institution in the course of studying of elective disciplines were studied. The model of formation of readiness of students for future professional activity modern conditions of training of specialists of higher education institution is described. For an effective functioning of the model of formation of readiness of students for future professional activity the following pedagogical conditions were defined: implementation of a multilevel monitoring of formation of readiness of students of pedagogical higher education institution for professional activity in the course of studying of elective disciplines by means of information and communication technologies; inclusion of the elements of professional activity in the process of formation of designing tasks in the course of studying of elective disciplines; ensuring participation of the teacher of elective disciplines and teachers of profile disciplines in designing and analytical activity of students. The indicators of readiness of students for future professional activity were justified. Conclusions were formulated. [Asenova N.S. , Zhumabaeva Z.E. , Kenenbaeva M.A., Sakenov D. Zh. , Toktarbaev D.G. About preparation of students of higher education institution for professional activity in the course of studying of elective disciplines. Life Sci J 2013;10(10s):96100] (ISSN:1097-8135). http://www.lifesciencesite. com. 15
APPLICATION OF THE END POINT POLYMERASE CHAIN REACTION METHOD TO THE DETECTION OF CERTAIN MILK-BORNE BACTERIA

The polymerase chain reaction (PCR) is a modern method that could differentiate microorganisms from each other by detecting certain DNA sequences uniquely associated with each species. This study aimed to develop a relevant end point PCR assay to detect Salmonella ser. Typhimurium in milk. To pursue this objective, the conditions of both DNA extraction and PCR reactions were developed in terms of the boiling time for DNA extraction and primer concentration for the PCR assay. Results showed that all of the three examined boiling times of 10, 15 and 20 min were equally effective for carrying out efficient DNA extraction. PCR reaction mixture involving a primer concentration of 1300 nM was the most efficient concentration, compared to 650 nM, and 325 nM for detecting Salmonella ser. Typhimurium. The sensitivity of the developed PCR method to detect different viable numbers of Salmonella Typhimurium in tryptone soya broth (TSB) and reconstituted skim milk (RSM) was examined. The PCR assay was able to detect 10 9 , 10 8 , 10 7 , and 10 6 cfu mL -1 of Salmonella in TSB. Whereas, it could detect 10 9 , and 10 8 cfu mL -1 of Salmonella in RSM. These results suggested that the developed PCR method had higher sensitivity to detect Salmonella in TSB, compared to RSM. This was attributed to some milk components that could be inhibitory to PCR reactions.
SUDA-Alibaba at MRP 2019: Graph-Based Models with BERT

In this paper, we describe our participating systems in the shared task on Cross- Framework Meaning Representation Parsing (MRP) at the 2019 Conference for Computational Language Learning (CoNLL). The task includes five frameworks for graph-based meaning representations, i.e., DM, PSD, EDS, UCCA, and AMR. One common characteristic of our systems is that we employ graph-based methods instead of transition-based methods when predicting edges between nodes. For SDP, we jointly perform edge prediction, frame tagging, and POS tagging via multi-task learning (MTL). For UCCA, we also jointly model a constituent tree parsing and a remote edge recovery task. For both EDS and AMR, we produce nodes first and edges second in a pipeline fashion. External resources like BERT are found helpful for all frameworks except AMR. Our final submission ranks the third on the overall MRP evaluation metric, the first on EDS and the second on UCCA.
Rapid Non-Linear Uncertainty Propagation via Analytical Techniques

Situational awareness of Earth-orbiting particles is known to be both a data starved and well-modeled problem. These two ideas are combined in this paper: a method of analytically propagating non-linear orbit uncertainties is discussed. In particular, the uncertainty is expressed as an analytic probability density function for all time, which is powerful as propagation is only a matter of changing the time parameter. Even when closed-form expressions are not available for a given system, solutions in tractable series form exist. Due to the large uncertainties and potentially long mapping time-spans, even initially Gaussian PDFs may become significantly non-Gaussian.
The influence of age on transfer of pediatric trauma patients after initial transport to hospitals with a higher capacity for general emergency care

Objective: The aim of this study was to investigate factors associated with the decision to transfer, rather than admit, pediatric trauma patients who were initially transported to emergency departments with a high capacity for general emergency care (regional emergency centers, RECs). Methods: In this retrospective analysis of the 2014 emergency medical services (EMS) sample of injured pediatric patients, we included injured patients below 19 years of age who were transported by EMS to an REC. The main exposure variable was age, which was categorized into four groups by 5-year intervals. The primary outcome was the emergency department (ED) disposition of the patients (admission versus transfer). A multivariable logistic regression analysis was conducted to estimate the effect of age group on ED disposition. Results: Data from 2,031 patients were analyzed. The transfer rate was 49.5%. In a uni-variate analysis, no statistically significant associations were found between severity or age group and ED disposition (19.9% vs. 18.6%, P=0.76; 20.1% vs. 16.8%, P=0.49; respectively). After adjusting for potential covariates, age group had a significant effect on transfer. When compared to 15-19 years old, the younger age groups had higher adjusted odds ratios (aORs) for transfer (0-4 years old, aOR 7.65 [95% CI, 1.24 to 47.38]; 5-9 years old, aOR 14.48 [95% CI, 2.08 to 100.55]; 10-14 years old, aOR 5.03 [95% CI, 10.5 to 26.79]). Conclusion: Younger pediatric patients with moderate to severe trauma are more likely to be transferred to another hospital despite initial transportation to a REC.
The Moderating Effect of Gender on the Relationship Between Intellectual Capital and Audit Quality

In our globe today, the auditing profession is under scrutiny. This is because of how audit quality can be ensured, obtained, and maintained. The problem of audit quality is discussed from the viewpoint of intellectual capital and the interaction of the gender of the auditor. Audit quality consists of auditors’ competence and independent, while intellectual capital is made up of human capital, rational capital, and structural capital. This research was a correlational design which applied self-constructed questionnaires with Cronbach alpha of 0.82 and 0.75 for intellectual capital and audit quality respectively. Using a convenience sampling technique, 354(8%) out of 4,390 registered chartered accountants with Chartered Institute of Accountants, Ghana (ICA, GH) who were practicing auditors were used in this study. The study respondents were made up of 191 (54%) males and 163 females, of which 210 (59.3%) had attained degrees, and 144 (40.7%) had an MBA. The study used PROCESS v3.2 and Andrew Haye model 1 to establish the regression and the moderating effect. The results of the study disclosed that there is a high positive significant relationship between intellectual capital and audit quality, and intellectual capital can predict audit quality by 53.68%. Also, there is an enhancing moderating effect of gender on the relationship between intellectual capital and audit quality but not statistically significant. The study recommends that the role of the auditor on audit quality and their intellectual capital must not be differentiated. Therefore, attention must not be placed on the gender of the auditor to give a quality audit.
Identifying Influential Nodes in Complex Networks Based on Local Effective Distance

With the rapid development of Internet technology, the social network has gradually become an indispensable platform for users to release information, obtain information, and share information. Users are not only receivers of information, but also publishers and disseminators of information. How to select a certain number of users to use their influence to achieve the maximum dissemination of information has become a hot topic at home and abroad. Rapid and accurate identification of influential nodes in the network is of great practical significance, such as the rapid dissemination, suppression of social network information, and the smooth operation of the network. Therefore, from the perspective of improving computational accuracy and efficiency, we propose an influential node identification method based on effective distance, named KDEC. By quantifying the effective distance between nodes and combining the position of the node in the network and its local structure, the influence of the node in the network is obtained, which is used as an indicator to evaluate the influence of the node. Through experimental analysis of a lot of real-world networks, the results show that the method can quickly and accurately identify the influential nodes in the network, and is better than some classical algorithms and some recently proposed algorithms.