Miracle-dz/UniFAR-FTUs huggingface dataset:
Stability Control of Stretch-Twist-Fold Flow by Using Numerical Methods

In this study, the multistep method is applied to the STF system. This method has been tested on the STF system, which is a three-dimensional system of ODE with quadratic nonlinearities. A computer based Matlab program has been developed in order to solve the STF system. Stable and unstable position of the system has been analyzed graphically and finally a comparison as well as accuracy between two-step sizes with detail. Newton’s method has been applied to show the best convergence of this system.
Regional patterns of genetic diversity in swine influenza A viruses in the United States from 2010 to 2016

Regular spatial and temporal analyses of the genetic diversity and evolutionary patterns of influenza A virus (IAV) in swine inform control efforts and improve animal health. Initiated in 2009, the USDA passively surveils IAV in U.S. swine, with a focus on subtyping clinical respiratory submissions, sequencing the hemagglutinin (HA) and neuraminidase (NA) genes at a minimum, and sharing these data publicly.
Towards temporal cognition for robots: A neurodynamics approach

If we want robots to engage effectively with humans in service applications or in collaborative work scenarios they have be endowed with the capacity to perceive the passage of time and control the timing of their actions. Here we report result of a robotics experiment in which we test a computational model of action timing based on processing principles of neurodynamics. A key assumption is that elapsed time is encoded in the consistent buildup of persistent population activity representing the memory of sensory or motor events. The stored information can be recalled using a ramp-to-threshold dynamics to guide actions in time. For the experiment we adopt an assembly paradigm from our previous work on natural human-robot interactions. The robot first watches a human executing a sequence of assembly steps. Subsequently, it has to execute the steps from memory in the correct order and in synchrony with an external timing signal. We show that the robot is able to efficiently adapt its motor timing and to store this information in memory using the temporal mismatch between the neural processing of the sensory feedback about executed actions and the external cue.
A Power-Ef fi cient Multichannel Neural Stimulator Using High-Frequency Pulsed Excitation From an Un fi ltered Dynamic Supply

This paper presents a neural stimulator system that employs a fundamentally different way of stimulating neural tissue compared to classical constant current stimulation. A stimulation pulse is composed of a sequence of current pulses injected at a frequency of 1 MHz for which the duty cycle is used to control the stimulation intensity. The system features 8 independent channels that connect to any of the 16 electrodes at the output. A sophisticated control system allows for individual control of each channel’s stimulation and timing parameters. This flexibility makes the system suitable for complex electrode configurations and current steering applications. Simultaneous multichannel stimulation is implemented using a high frequency alternating technique, which reduces the amount of electrode switches by a factor 8. The system has the advantage of requiring a single inductor as its only external component. Furthermore it offers a high power efficiency, which is nearly independent on both the voltage over the load as well as on the number of simultaneously operated channels. Measurements confirm this: in multichannel mode the power efficiency can be increased for specific cases to 40% compared to 20% that is achieved by state-of-the-art classical constant current stimulators with adaptive power supply.
The Journal of Systems and Software

Code packing is one of the most frequently used protection techniques for malware to evade detection. Particularly, Android packers originally designed to protect intellectual property are widely utilized by Android malware nowadays to hide their malicious behaviors. What’s worse, Android code packing techniques are evolving rapidly with new features of Android system (e.g., the use of new Android runtime). Meanwhile, unpacking techniques and tools generally do not respond to the evolving of packers immediately, which weakens the effectiveness of new malware detection. To address the unpacking challenge especially for Android packers with advanced code hiding strategies, in this paper we propose AppSpear , an automated unpacking system for both Dalvik and ART. AppSpear adopts a universal unpacking strategy that combines runtime instrumentation, interpreter-enforced execution, and executable reassembling to guarantee the hidden code is extracted and reconstructed as a complete executable. Our experimental evaluation with 530 packed samples shows that AppSpear is able to unpack protected code generated by latest versions of mainstream Android packers effectively.
Protein arginine N-methyltransferase 2 reverses tamoxifen resistance in breast cancer cells through suppression of ER-α36

Breast cancer is one of the most common malignancies in females, and 17β-estradiol (E2)/estrogen receptor α (ERα) signaling plays an important role in the initiation and progression of breast cancer. The role of the ER-α subtype and its co-regulator in the initiation of breast cancer and the occurrence of tamoxifen resistance remains to be further elucidated. In our previous studies, protein arginine N-methyltransferase 2 (PRMT2), a co-regulator of estrogen receptor-α (ER-α), was confirmed to interact with ER-α66 and has the ability to inhibit cell proliferation in breast cancer cells. In the present study, we found that tamoxifen treatment induced a decrease in PRMT2 and an increase in ER-α36 as well as ER-α36-mediated non-genomic effect in MDA-MB-231 cells, which were relatively resistant to tamoxifen by contrast to MCF-7 cells. Moreover, PRMT2 was able to interact with ER-α36 directly, suppress ER-α36 and downstream PI3K/Akt and MAPK/ERK signaling, reversing the tamoxifen resistance of breast cancer cells. The present study may be meaningful for understanding the role of PRMT2 in breast cancer progression and for developing a new endocrine therapeutic strategy for breast cancer patients with tamoxifen resistance.
Bringing low-level languages to the JVM: efficient execution of LLVM IR on Truffle

Although the Java platform has been used as a multi-language platform, most of the low-level languages (such as C, Fortran, and C++) cannot be executed efficiently on the JVM. We propose Sulong, a system that can execute LLVM-based languages on the JVM. By targeting LLVM IR, Sulong is able to execute C, Fortran, and other languages that can be compiled to LLVM IR. Sulong combines LLVM’s static optimizations with dynamic compilation to reach a peak performance that is near to the performance achievable with static compilers. For C benchmarks, Sulong’s peak runtime performance is on average 1.39× slower (0.79× to 2.45×) compared to the performance of executables compiled by Clang O3. For Fortran benchmarks, Sulong is 2.63× slower (1.43× to 4.96×) than the performance of executables compiled by GCC O3. This low overhead makes Sulong an alternative to Java’s native function interfaces. More importantly, it also allows other JVM language implementations to use Sulong for implementing their native interfaces.
Negative affect varying in motivational intensity influences scope of memory

ABSTRACT Emotions influence cognitive processes involved in memory. While some research has suggested that cognitive scope is determined by affective valence, recent models of emotion–cognition interactions suggest that motivational intensity, rather than valence, influences these processes. The present research was designed to clarify how negative affects differing in motivational intensity impact memory for centrally or peripherally presented information. Experiments 1 & 2 found that, relative to a neutral condition, high intensity negative affect (anger) enhances memory for centrally presented information. Experiment 3 replicated this effect using another high intensity negative affect (threat). Experiment 4 extended this by finding that, relative to a neutral condition, low intensity negative affect (sadness) enhanced memory for peripherally presented information. Finally, in Experiment 5, the effects of sadness and threat on scope of memory were directly compared, finding that threat narrowed scope of memory, while sadness broadened scope of memory. Together, these results provide additional support for the motivational dimensional model of cognitive scope, in that high intensity emotions narrow cognitive scope, while low intensity emotions broaden cognitive scope.
A-T-LAS$_{2,1}$: A Multi-Penalty Approach to Compressed Sensing of Low-Rank Matrices with Sparse Decompositions

Compressed Sensing is about recovering an unknown vector of dimension $n$ from $m \ll n$ linear measurements. This task becomes possible, for instance, when few entries of the vector have large magnitude and, hence, the vector is essentially of low intrinsic dimension. If one wishes to recover an $n_1\times n_2$ matrix instead, low-rankness can be added as sparsity structure of low intrinsic dimensionality. For this purpose we propose a novel algorithm, which we call Alternating Tikhonov regularization and Lasso (A-T-LAS$_{2,1}$). It is based on a multi-penalty regularization for recovery of low-rank matrices with approximately sparse singular vectors, which is able to leverage both structures (low-rankness and sparsity) simultaneously and effectively reduce further the number of necessary measurements with respect to the sole use of one of the two sparsity structures. We provide nearly-optimal recovery guarantees of A-T-LAS$_{2,1}$. The analysis is surprisingly relatively simple, e.g., compared to the one of other similar approaches such as Sparse Power Factorization (SPF). It relies on an adaptation of restricted isometry property to low-rank and approximately sparse matrices, LASSO technique, and results on proximal alternating minimization. We show that A-T-LAS$_{2,1}$ is more efficient than convex relaxation and exhibits similar performance to the state of the art method SPF, outperforming it in strong noise regimes and for matrices whose singular vectors do not possess exact (joint-) sparse support. Moreover, contrary to SPF, A-T-LAS$_{2,1}$, if properly initialized, is shown to converge even for measurements not fulfilling the restricted isometry property to matrices with some guaranteed sparsity and minimal discrepancy to data.
Cross-device tracking with machine learning

Personalizing the user experience on the web is important for news or product recommendations, online advertising and other domains. Users increasingly expect personalized experiences, and personalization technologies allow publishers to create more appealing digital products that they can charge for or otherwise monetize. On the web users are generally anonymous and the majority of traffic comes from users that haven’t logged in or otherwise authenticated themselves. For this reason, one of the big challenges for personalization is the fact that the same user will often access websites from several different devices (e.g., PCs, mobile phones, or tablets) and the websites have problems discerning if the requests come from the same user or not. The problem of identifying users across multiple devices is known as cross-device tracking, and has not been extensively researched yet. In this project we carried out a number of experiments with cross-device tracking techniques based on applying machine learning to real-world traffic data. We extracted labelled datasets from traffic logs, applied both supervised classifiers and unsupervised clustering techniques to the data, focusing on minimizing the number of false connections, and evaluated them using the standard binary recall and precision metrics. Some of the resulting models performed well enough for practical applications, although important issues remain unsolved, such as how to make sure that a model performs well after applying it to the data from a new website.
XML3D - Interactive 3D Graphics for the Web

XML3D is a extension to HTML5 to support interactive 3D graphics in the Browser. XML3D is designed to integrate and interoperate well with ubiquitous W3C standards such as DOM, CSS, and others. Embedding XML3D into this family of standards brings many benefits: It allows millions of exiting web programmers to directly apply their existing knowledge also to interactive 3D graphics. The XML3D proposal and its implementations serve as a demonstrator platform for the W3C Community Group ”Declarative 3D for the Web Architecture”. In this demo description, we present a selection of features of XML3D, that demonstrate the advantages of a web-based declarative approach to 3d graphics.
Applications of Cancer Cell-Specific Aptamers in Targeted Delivery of Anticancer Therapeutic Agents

Aptamers are single-stranded oligonucleotides that specifically bind and interact with their corresponding targets, including proteins and cells, through unique three-dimensional structures. Numerous aptamers have been developed to target cancer biomarkers with high specificity and affinity, and some are employed as versatile guiding ligands for cancer-specific drug delivery and anti-cancer therapeutics. In this review, we list the aptamers that target tumor surface biomarkers and summarize the representative applications of aptamers as agonists and antagonists that activate anti-cancer and inactivate pro-cancer biomarkers, respectively. In addition, we describe applications of aptamer-drug or aptamer-oligonucleotide conjugates that can deliver therapeutic agents, including small interfering RNAs, micro RNAs, short hairpin RNAs, and chemotherapeutic molecules, to cancer cells. Moreover, we provide examples of aptamer- conjugated nano-vehicles, in which cancer-targeting oligonucleotide aptamers are conjugated with nano-vehicles such as liposomes, micelles, polymeric nanoparticles, and quantum dots. Conjugation of aptamers with anti-cancer drugs and nano-vehicles will facilitate innovative applications of aptamer-based cancer therapeutics.
Migration and human capital in an endogenous fertility model

How do high and low skilled migration affect fertility and human capital in migrants' origin countries? This question is analyzed within an overlapping generations model where parents choose the number of high and low skilled children they would like to have. Individuals migrate with a certain probability and remit to their parents. It is shown that a brain drain induces parents to have more high and less low educated children. Under certain conditions fertility may either rise or decline due to a brain drain. Low skilled emigration leads to reversed results, while the overall impact on human capital of either type of migration remains ambiguous. Subsequently, the model is calibrated on a developing economy. It is found that increased high skilled emigration reduces fertility and fosters human capital accumulation, while low skilled emigration induces higher population growth and a lower level of education.
Three-dimensional analysis for functionally graded piezoelectric semiconductors

This article presents numerical analyses of functionally graded piezoelectric beam with piezoelectric semiconducting material properties using meshless method. Unlike piezoelectric dielectric materials, electron density and electric current are additionally considered in constitutive equations for piezoelectric semiconductors. Mutual coupling of elastic displacements, electric potentials, and electron density increases the complexity of the analyzed problem. For the solution of the set of partial differential equations with non-constant coefficients, the local radial basis function collocation method is proposed in this work. Approximating the spatial variations of all physical fields in the partial differential equations by the multiquadric radial basis function entails an ensuing system for time-dependent problems solved by the Houbolt finite-difference scheme as a time-stepping method. The presented local radial basis function collocation method is verified using the corresponding results obtained using the finite element method. The influence of material parameter gradation and initial electron density is then investigated, along with transient analyses.
TOWARDS VISUAL DATA MINING François Poulet

In this paper, we present our work in a new data mining approach called Visual Data Mining (VDM). This new approach tries to involve the user (being the data expert not a data mining or analysis specialist) more intensively in the data mining process and to increase the part of the visualisation in this process. The visualisation part can be increased with cooperative tools: the visualisation is used as a preor postprocessing step of usual (automatic) data mining algorithms, or the visualisation tools can be used instead of the usual automatic algorithms. All these topics are addressed in this paper with an evaluation of the algorithms presented and a discussion of the interactive algorithms compared with automatic ones. All this work must be improved in order to allow the data specialists to efficiently use these kinds of algorithms to solve their problems.
A Dissociation between the Representation of Tool-use Skills and Hand Dominance: Insights from Left- and Right-handed Callosotomy Patients

The overwhelming majority of evidence indicates that the left cerebral hemisphere of right-handed humans is dominant both for manual control and the representation of acquired skills, including tool use. It is, however, unclear whether these functions involve common or dissociable mechanisms. Here we demonstrate that the disconnected left hemispheres of both right- and left-handed split-brain patients are specialized for representing acquired tool-use skills. When required to pantomime actions associated with familiar tools (Experiment 2), both patients show a right-hand (left hemisphere) advantage in response to tool names, pictures, and actual objects. Accuracy decreases as stimuli become increasingly symbolic when using the left hand (right hemisphere). Tested in isolation with lateralized pictures (Experiment 3), each patient's left hemisphere demonstrates a significant advantage over the right hemisphere for pantomiming tool-use actions with the contralateral hand. The fact that this asymmetry occurs even in a left-handed patient suggests that the left hemisphere specialization for representing praxis skills can be dissociated from mechanisms involved in hand dominance located in the right hemisphere. This effect is not attributable to differences at the conceptual level, as the left and right hemispheres are equally and highly competent at associating tools with observed pantomimes (Experiment 4).
Participant reputation aware data collecting mechanism for mobile crowd sensing

The malicious behaviors of participants can reduce the reliability significantly in data collecting process of Mobile Crowd Sensing. To solve this problem, a participant reputation aware data collecting mechanism is proposed, which analyzes reputation state, quantifies historical reputation of participants according to willingness and data quality, and then updates the reputation of participants by logistic regression function. Furthermore, the server can accurately choose participant and efficiently collect sensing data in multitasking scenario. Simulation results show that the proposed mechanism can significantly improve the quality of sensing data with excellent real-time performance and reduce overhead.
The Genevan and Cattell-Horn Conceptions of Intelligence Compared : Early Implementation of Numerical Solution Aids Irvin

The Genevan and Cattell-Horn theories of intelligence are compared. The theories are found to be similar in the following respects: Intelligence (operative intelligence and fluid ability) is conceptualized as adaptational in function; the products of everyday learning and crystallized skills reflect the impress of experience; one category of intelligence (operative intelligence, fluid ability) is conceptualized as prior or more fundamental than the other (learned products, crystallized skills). Important differences were also found: Whereas fluid ability is characterized as formless and fixed, operative intelligence is viewed as highly structured and evolving; a compensatory relation between noegenetic crystallized skills and fluid ability is hypothesized where such a relation is not conceived to exist between operative intelligence and learning. The relation of Piagetian operative level to the child's capacity to use crystallized solution procedures (aids) in making elementary numerical comparisons was investigated. Performance on quantitative comparison tasks reflecting the child's understanding of correspondence relations was highly related to operative level. It was also found that the child's capacity to implement solution aids in making quantitative comparisons was, to some extent, moderated by his or her level of operative development.
Immunophenotypic markers in adult acute lymphoblastic leukemia: the prognostic significance of CD20 and TdT expression

Background Efforts to overcome poor outcomes in patients with adult acute lymphoblastic leukemia (ALL) have focused on combining new therapeutic agents targeting immunophenotypic markers (IPMs) with classical cytotoxic agents; therefore, it is important to evaluate the clinical significance of IPMs. Methods Baseline characteristics and clinical outcomes of patients with adult ALL were retrospectively analyzed. The percentage of blasts expressing IPMs at diagnosis was measured by multicolor flow cytometry analysis. Samples in which ≥20% of blasts expressed an IPM were considered positive. Results Among the total patient population (N=230), almost all (92%) were in first or second hematological complete remission (HCR) and 54% received allogeneic hematopoietic cell transplant (allo-HCT). Five-year hematologic relapse-free survival (HRFS) and overall survival (OS) rates were 36% and 39%, respectively, and 45.6% and 80.5% of patients were positive for the IPMs CD20 and terminal deoxynucleotidyl transferase (TdT), respectively. Expression of CD20, CD13, CD34, and TdT was associated with HRFS rate, and expression of CD20 and CD13 was associated with OS rate, as was the performance of allo-HCT. In multivariate analysis, positivity for CD20 (HRFS: hazard ratio [HR], 2.21, P<0.001; OS: HR, 1.63, P=0.015) and negativity for TdT (HRFS: HR, 2.30, P=0.001) were both significantly associated with outcomes. When patients were categorized into three subgroups according to positivity for CD20 and TdT, there were significant differences in HRFS and OS among the subgroups. Conclusion Positivity for CD20 and TdT expression and clinical risk group were prognostic factors in adult ALL.