Miracle-dz/UniFAR-FTUs huggingface dataset:
Semantic-preserving Reinforcement Learning Attack Against Graph Neural Networks for Malware Detection

To address the costs of reverse engineering and signature extraction, advanced research on malware detection focuses on using neural networks to learn malicious behaviors with static and dynamic features. However, deep learning-based malware detection models are vulnerable to a hack from adversarial samples. The attackers' goal is to generate imperceptible perturbations to the original samples and evade detection. In the context of malware, the generated samples should have one more important character: it should not change the malicious behaviors of the original code. So the original features can not be removed and changed. In this paper, we proposed a reinforcement learning based attack to deceive graph based malware detection models. Inspired by obfuscation techniques, the central idea of the proposed attack is to sequentially inject semantic Nops, which will not change the program's functionality, into CFGs(Control Flow Graph). Specifically, the Semantics-preserving Reinforcement Learning(SRL) Attack is to learn an RL agent to iteratively select the semantic Nops and insert them into basic blocks of the CFGs. Variants of obfuscation methods, hill-climbing methods, and gradient based algorithms are proposed: 1) Semantics-preserving Random Insertion(SRI) Attack: randomly inserting semantic Nops into basic blocks. ; 2) Semantics-preserving Accumulated Insertion(SAI) Attack: declining certain random transformation according to the probability of the target class; 3) Semantics-preserving Gradient based Insertion(SGI) Attack: applying transformation on the original CFG in the direction of the gradient. We use real-world Windows programs to show that a family of Graph Neural Network models are vulnerable to these attacks. The best evasion rate of the benchmark attacks are 97% on the basic GCN model and 96% on DGCNN model. The SRL attack can achieve 100% on both models.
Well-Posedness and Orbital Stability of Periodic Traveling Waves for Schamel's Equation

In this paper we will prove results of global well-posedness and orbital stability of periodic traveling-wave solutions related to the Schamel equation. The global solvability will be established by using compactness tools. In order to overcome the lack of smoothness of the nonlinearity, we approximate the original problem by regularizing the nonlinear term through a convenient polynomial near the origin. By following an adaptation of the well-known method introduced by Grillakis, Shatah, and Strauss, the orbital stability will be determined by proving, under certain conditions, that the periodic waves minimize an augmented Hamiltonian.
Isotropic surface remeshing

This paper proposes a new method for isotropic remeshing of triangulated surface meshes. Given a triangulated surface mesh to be resampled and a user-specified density function defined over it, we first distribute the desired number of samples by generalizing error diffusion, commonly used in image halftoning, to work directly on mesh triangles and feature edges. We then use the resulting sampling as an initial configuration for building a weighted centroidal Voronoi tessellation in a conformal parameter space, where the specified density function is used for weighing. We finally create the mesh by lifting the corresponding constrained Delaunay triangulation from parameter space. A precise control over the sampling is obtained through a flexible design of the density function, the latter being possibly low-pass filtered to obtain a smoother gradation. We demonstrate the versatility of our approach through various remeshing examples.
Isotropic Surface Remeshing

This paper proposes a new method for isotropic remeshing of triangulated surface meshes. Given a triangulated surface mesh to be resampled and a user-specified density function defined over it, we first distribute the desired number of samples by generalizing error diffusion, commonly used in image halftoning, to work directly on mesh triangles and feature edges. We then use the resulting sampling as an initial configuration for building a weighted centroidal Voronoi tessellation in a conformal parameter space, where the specified density function is used for weighting. We finally create the mesh by lifting the corresponding constrained Delaunay triangulation from parameter space. A precise control Pierre Alliez INRIA Sophia-Antipolis pierre.alliez@sophia.inria. fr Éric Colin de Verdière ENS Paris Eric.Colin. de.Verdiere@ens.fr Olivier Devillers INRIA Sophia-Antipolis olivier.devillers@sophia.inria. fr Martin Isenburg University of North Carolina at Chapell Hill isenburg@cs.unc. edu 2 Pierre Alliez, Éric Colin de Verdière, Olivier Devillers and Martin Isenburg over the sampling is obtained through a flexible design of the density function, the latter being possibly low-pass filtered to obtain a smoother gradation. We demonstrate the versatility of our approach through various remeshing examples. Key-words: Surface sampling, error diffusion, centroidal Voronoi tessellation, constrained Delaunay triangulation, parameterization, optimal cutting, polygonal schema.
Neural Gas and k-means Methods with Reduced Communication Costs for Secure Distributed Processing

—From the viewpoint of developing machine learning as a safe and secure AI method, research in this ﬁeld has focused on machine learning on a single server using encrypted or noise-added data, or distributed processing on multiple servers using decomposition data or distributed dataset. However, few learning methods have been proposed that achieve both data conﬁdentiality and usability at a high level. The authors proposed a machine learning method based on secure distributed processing with decomposition data and parameters. However, although this distributed processing method is superior in terms of security, it is computationally expensive. To solve this problem, the authors proposed a learning method that updates only one element of each decomposed parameter. In this paper, we propose an improvement method in communication cost for the NG and k-means methods and show its effectiveness. The proposed method means that the computational complexity of the NG and k-means methods with distributed processing can be almost the same as that of the conventional NG and k-means methods with a single server.
An active kinase domain is required for retention of PKCθ at the T cell immunological synapse

In response to antigen stimulation, PKCθ translocates to the T cell plasma membrane, becoming highly focused at the immunological synapse (IS). cis-Acting sequences that regulate IS retention are not known. It is shown that a catalytically competent PKCθ kinase domain is essential for IS retention but not for membrane translocation.
Development and gene expression of C57BL/6 mouse embryo palate shelves in rotary organ culture

The aim of the present study was to improve methods for the suspension culture of mouse palatal shelves by comparing the expression of platelet-derived growth factor receptor (PDGFR)-α in palatal shelves in vivo, to that in vitro. The palatal shelves of C57BL/6 mouse embryos were obtained on gestation days (GDs) 13.5, 14.5, 15.0 and 15.5 for in vivo experiments. The palatal shelves were removed and observed under a stereomicroscope to investigate palatal development. For in vitro experiments, the palatal shelves were dissected under a stereomicroscope on GD 13.5 and then subjected to rotary culture for 0, 24, 36 or 48 h. The expression of PDGFR-α at different time points was detected by immunohistochemical staining and western blot analysis. Both methods of analysis displayed PDGFR-α expression in mesenchymal and epithelial cells at GD 13.5, 14.5, 15.0 and 15.5, in vivo and in vitro. The level of PDGFR-α expression peaked on GD 14.5. The expression of PDGFR-α in palatal shelves in in vitro rotary culture was consistent with that in vivo. Therefore, the novel technique of palatal rotary organ culture presented in the current study could provide a good model for studying the mechanism of pathological palatal fusion in vitro. Additionally, the present study further confirmed that PDGFR-α gene expression was associated with the development of palatal shelves.
RECOGNIZING SIX EMOTIONAL STATES USING SPEECH SIGNALS

This paper examines three algorithms to recognize speaker`s emotion using the speech signals. Target emotions are happiness, sadness, anger, fear, boredom and neutral state. MLB(Maximum-Likeligood Bayes), NN(Nearest Neighbor) and HMM (Hidden Markov Model) algorithms are used as the pattern matching techniques. In all cases, pitch and energy are used as the features. The feature vectors for MLB and NN are composed of pitch mean, pitch standard deviation, energy mean, energy standard deviation, etc. For HMM, vectors of delta pitch with delta-delta pitch and delta energy with delta-delta energy are used. We recorded a corpus of emotional speech data and performed the subjective evaluation for the data. The subjective recognition result was 56% and was compared with the classifiers` recognition rates. MLB, NN, and HMM classifiers achieved recognition rates of 68.9%, 69.3% and 89.1% respectively, for the speaker dependent, and context-independent classification. ㅂ
An FPGA-specific approach to floating-point accumulation and sum-of-products

This article studies two common situations where the flexibility of FPGAs allows one to design application-specific floating-point operators which are more efficient and more accurate than those offered by processors and GPUs. First, for applications involving the addition of a large number of floating-point values, an ad-hoc accumulator is proposed. By tailoring its parameters to the numerical requirements of the application, it can be made arbitrarily accurate, at an area cost comparable to that of a standard floating-point adder, and at a higher frequency. The second example is the sum-of-product operation, which is the building block of matrix computations. A novel architecture is proposed that feeds the previous accumulator out of a floating-point multiplier whose rounding logic has been removed, again improving the area/accuracy tradeoff. These architectures are implemented within the FloPoCo generator, freely available under the LGPL.
Elimination of the Single Phase Parallel Active Power Filter Harmonic in Distribution Network

In this work, the harmonics of the semiconductors used in industrial applications are given. Harmonics allowed voltage and current waveforms to move away from basic waveforms cause a decrease to power factor, an increase to power losses and damage to electronic elements. Harmonics formed by non-linear loads at the source were eliminated by means of Parallel Active Filter (PAF). A non-linear single-phase load model was formed by Matlab /Simulink program, and harmonics formed at source were simulated. Harmonics were eliminated by forming at single-phase PAF simulation environment. Thus, power factor was enhanced and power losses were reduced to minimum.
Supplemental Information Supplemental Data

Figure S1. Outline of COFACTOR protocol for protein-ligand binding site predictions. (1) Template proteins from the ligand-binding library are identified using TM-align global similarity search. (2) Conserved residues in query sequence are identified based on Shannon diverge score which are used to glean local 3D-fragments from the query structure. (3) Each local 3D-motif of query is iteratively aligned with known binding site residues fragments from template where the binding pocket similarity between query and template is evaluated using BS-score. (4) The template ligand is transferred onto the query structure which is refined by a short Monte Carlo (MC) simulation to improve the local geometry.
When Do Firms Adjust Prices? Evidence from Micro Panel Data

The price-setting behavior of manufacturing firms is examined using a large panel of quarterly firm survey data from 1984 to 2007, which allows changes in firms’ prices to be linked to several firm-specific variables. The results show that state-dependent pricing is clearly present in a low-inflation environment and that variables measuring the current situation of the firm, especially costs for intermediate products, are important determinants of price adjustments. Compared to purely time-dependent features, the state-dependent variables significantly add to the explanatory power of a price adjustment probability model. Macroeconomic factors are significant but contribute little in terms of the goodness of fit. Furthermore, when taking into account sticky plan models by excluding possibly predetermined price changes, the importance of state-dependent factors becomes even greater.
Identification of potentially inappropriate medications with risk of major adverse cardiac and cerebrovascular events among elderly patients in ambulatory setting and long-term care facilities

Purpose: Cardiovascular diseases (CVDs) are extremely common among the elderly, but information on the use of potentially inappropriate medications (PIMs) with cardiovascular risk is scarce. We aimed to determine the prevalence of PIMs with risk of cardiac and cerebrovascular adverse events (CCVAEs), including major adverse cardiac and cerebrovascular events (MACCE). Patients and methods: A cross-sectional study was performed using a convenience sample from four long-term care facilities and one community pharmacy in Portugal. Patients were included if they were aged 65 or older and presented at least one type of medication in their medical and pharmacotherapeutic records from 2015 until December 2017. The main outcome was defined as the presence of PIMs with risk of MACCE and was assessed by applying a PIM-MACCE list that was developed from a previous study. All medications included in this list were assessed for their availability in Portugal. Results: A total of 680 patients were included. Of those, 428 (63%) were female with a mean age of 78.4 ± 8.1 years. Four-hundred and four (59.4%) patients were taking medications associated with CCVAEs risk (mean = 1.7 ± 1.0 drugs/patient), including 264 patients (38.8%) who used drugs with MACCE risk (mean = 1.4 ± 0.8 drugs/patient). Fifty percent of patients with a previous history of CVD (n = 521) were taking PIMs with risk of CCVAEs, including 30.0% with risk of MACCE. Conclusion: Our findings show that 50% of patients with previous history of CVD were taking drugs with risk of CCAVEs and 30% with risk of MACCE. More tailored tools for the management of drug therapy in elderly patients with CVD are of major importance in clinical practice.
Maternal diet and gut microbiome composition modulate early life immune responses

20 In early life, the intestinal mucosa and immune system undergo a critical developmental process to 21 contain the expanding gut microbiome while promoting tolerance towards commensals, yet the 22 influence of maternal diet and gut microbial composition on offspring immune maturation remains 23 poorly understood. We colonized gnotobiotic mice with a defined consortium of 14 strains, fed them 24 a fiber-free diet, and then longitudinally assessed offspring development during the weaning period. 25 Unlike pups born to dams fed a standard, fiber-rich chow, pups of fiber-deprived dams demonstrated 26 delayed colonization with Akkermansia muciniphila , a mucin-foraging bacterium that can also utilize 27 milk oligosaccharides. The pups of fiber-deprived dams exhibited an enrichment of colonic tissue 28 transcripts corresponding to defense response pathways and a peak in Il22 expression at weaning. 29 Removal of A . muciniphila from the community, but maintenance on the fiber-rich diet, was 30 associated with reduced proportions of RORγt-positive innate and adaptive immune cell subsets. 31 Our results highlight the potent influence of maternal dietary fiber intake and discrete changes in 32 microbial composition on the postnatal microbiome assemblage and early immune priming. 33
Instantaneous Landing Position Determination for Biped Robots Taking Into Account Terrain, Kinematics and Capturability

開けた平坦地では既に多く の研究で転倒回避に成功している. Prattら [1]は踏み出すことで重心を停止させることの出来る位置 を Capture Pointとして提案し , そこへ踏み出すことで大きな外 力に耐えられることを示した. Koolen ら [2]は N 歩の踏み出し で Capture Point に到達可能であるかを N -Step Capturability と呼び, それを満たす領域として Capture Region を定義した. Pratt ら [3] は Capture Region内に目標着地位置を修正するこ とで, ある程度着地位置を誘導しながら転倒回避が可能であるこ とを示した. Griffin ら [4]は踏み出し足速度と目標着地位置を修 正する方法を提案し , より 大きな外力にも耐えられることを示し た. しかし , 凹凸地形での転倒回避に関する研究は殆ど無い.
Large eddy simulations of cavitating flow in a step nozzle with injection into gas

We present results of large eddy simulations of a cavitating nozzle flow and injection into gas, investigating the interactions of cavitation in the nozzle, primary jet breakup, mass-flow rates, and gas entrainment. During strong cavitation, detached vapor structures can reach the nozzle outlet, leading to partial entrainment of gas from the outflow region into the nozzle. The gas entrainment can affect cavitation dynamics, mass-flow rates, and jet breakup.Moreover, the implosion of detached vapor structures induces pressure peaks that on the one hand amplify turbulent fluctuations and subsequently can enhance jet breakup and on the other hand can damage walls in the proximity and thus lead to cavitation erosion. Our numerical setup is based on a reference experiment, in which liquid water is discharged into ambient air through a step nozzle. The cavitating liquid and the noncondensable gas phase are modeled with a barotropic homogeneous mixture model while for the numerical model a high-order implicit large eddy approach is employed. Full compressibility of all components is taken into account, enabling us to capture the effects of collapsing vapor structures. Two operating points covering different cavitation regimes and jet characteristics are investigated. Special emphasis is placed on studying the effects of cavitation on the mass flow and the jet as well as the impact of partial gas entrainment. Therefore, frequency analyses of the recorded time-resolved signals are performed. Furthermore, the dynamics and intensities of imploding vapor structures are assessed.
Parallel database systems: the future of database processing or a passing fad?

The concept of parallel database machines consisting of exotic hardware has been replaced by a fairly conventional shared-nothing hardware base along with a highly parallel dataflow software architecture. Such a design provides speedup and scaleup in processing relational database queries. This paper reviews the techniques used by such systems, and surveys current commercial and research systems.
RXR Agonists Enhance Lenalidomide Anti-Myeloma Activity and T Cell Functions while Retaining Glucose-Lowering Effect

Retinoid X receptor (RXR) heterodimerizes with the PPAR nuclear hormone receptor and regulates its downstream events. We investigated the effects of RXR agonists (LG100754, bexarotene, AGN194204, and LG101506) on lenalidomide’s anti-myeloma activity, T cell functions, and the level of glucose and lipids in vivo. Genetic overexpression and CRISPR/Cas9 knockout experiments were conducted in multiple myeloma (MM) cell lines and Jurkat T cell lines to determine the roles of CRBN in RXR-agonist mediated effects. A xenograft mouse model of MM was established to determine the combination effect of LG100754 and lenalidomide. The combination of RXR agonists and lenalidomide demonstrated synergistic activity in increasing CRBN expression and killing myeloma cells. Mechanistically, the RXR agonists reduced the binding of PPARs to the CRBN promoter, thereby relieving the repressor effect of PPARs on CRBN transcription. RXR agonists downregulated the exhaustion markers and increased the activation markers of Jurkat T cells and primary human T cells. Co-administration of LG100754 and lenalidomide showed enhanced anti-tumor activity in vivo. LG100754 retained its glucose- and lipid-lowering effects. RXR agonists demonstrate potential utility in enhancing drug sensitivity and T-cell function in the treatment of myeloma.
STiMuL: a Software for Modeling Steady-State Temperature in Multilayers - Description and user manual

This report describes STiMuL, a model and software for steady-state temperature in multilayers. STiMuL is primarily intended for modeling steady-state heat conduction in microprocessors and their packaging. STiMuL can be used to model temperature in 2D and 3D circuits from 2D power density maps provided by the user. It can also be used to obtain power density maps from temperature maps. The STiMuL software is publicly available. This report describes the theoretical model and its software implementation. It explains how to use the software and provides some examples of utilization.
The role of the coarsest resolution subband in the wavelet-based reconstruction of signals from gradients

An efficient wavelet-based algorithm to reconstruct non-square/non-cubic signals from gradient data is proposed. This algorithm is motivated by applications such as image or video processing in the gradient domain. In some earlier approaches, the non-square/non-cubic gradients were extended to enable a square/cubic Haar wavelet decomposition and the coarsest resolution subband was derived from the mean value of the signal. In this paper, a non-square/non-cubic wavelet decomposition is obtained directly without extending the gradient data. The challenge comes from finding the coarsest resolution subband of the wavelet decomposition and an algorithm to compute this is proposed. The performance of the algorithm is evaluated in terms of accuracy and computation time, and is shown to outperform the considered earlier approaches in a number of cases. Further, a closer look on the role of the coarsest resolution subband coefficients reveals a trade-off between errors in reconstruction and visual quality which has interesting implications in image and video processing applications.
Tag clouds for summarizing web search results

In this paper, we describe an application, PubCloud that uses tagclouds for the summarization of results from queries over thePubMed database of biomedical literature. PubCloud responds toqueries of this database with tag clouds generated from wordsextracted from the abstracts returned by the query. The results ofa user study comparing the PubCloud tag-cloud summarization ofquery results with the standard result list provided by PubMedindicated that the tag cloud interface is advantageous in presenting descriptive information and in reducing user frustrationbut that it is less effective at the task of enabling users to discoverrelations between concepts.
Learning information diffusion process on the web

Many text documents on the Web are not originally created but forwarded or copied from other source documents. The phenomenon of document forwarding or transmission between various web sites is denoted as Web information diffusion. This paper focuses on mining information diffusion processes for specific topics on the Web. A novel system called LIDPW is proposed to address this problem using matching learning techniques. The source site and source document of each document are identified and the diffusion process composed of a sequence of diffusion relationships is visually presented to users. The effectiveness of LIDPW is validated on a real data set. A preliminary user study is performed and the results show that LIDPW does benefit users to monitor the information diffusion process of a specific topic, and aid them to discover the diffusion start and diffusion center of the topic.