Miracle-dz/UniFAR-FTUs huggingface dataset:
Dialectal variation in the perception of phonological contrasts

The present study examined the cross-dialectal variability in perceptual patterns of the alveolarretroflex contrast, a critical feature often used to differentiate Beijing Mandarin from other dialects of Mandarin, such as Taiwan Mandarin. While previous research has focused on dialectally and contextually driven variation in alveolar and retroflex productions, little is known about whether similar variability is also present in perception. We investigated the categorical and gradient modes of alveolar-retroflex perceptions in different vowel contexts by listeners from Beijing and Taiwan. The results indicate that that Beijing and Taiwan listeners have different perceptual boundaries along the acoustic continuum, with a lower cutoff frication frequency required for the retroflex percepts for Beijing listeners. Both groups of listeners’ category boundaries shift to lower frequencies in the rounded vowel context to normalize for vowel coarticulatory effects. Discrepant within-category sensitivity was found in that while both Beijing and Taiwan listeners perceived all retroflex variants as equally good exemplars, Beijing listeners considered the endpoint variant of the alveolar as the preferred category exemplar. We concluded an articulatory explanation for this asymmetrical within-category discriminability and also discussed the findings with respect to the hyperspace effect in perception. Together, our results show that linguistic (i.e., vowel context) and sociolinguistic (i.e., dialect) factors collectively and variably affect the perception of the Mandarin alveolar-retroflex contrast.
Comparing Detection Capabilities of AntiVirus Products: An Empirical Study with Different Versions of Products from the Same Vendors

In this paper we report results of an empirical analysis of the detection capabilities of 9 AntiVirus (AV) products when they were subjected to 3605 malware samples collected on an experimental network over a period of 31 days in NovemberDecember 2013. We compared the detection capabilities of the version of the AV products that the vendors make available for free in VirusTotal versus the full capability products that they make available via their own website. The analysis has been done using externally observable properties of the AV products: namely whether they detect a given malware. The paper reports extensive analysis of the results. A surprising finding of our study was that only one of the vendors had a full capability version which detected all the malware that their VirusTotal version could detect.
Nowcasting thunderstorms in the Alpine region using a radar based adaptive thresholding scheme

In this paper we present a new automated, radar based tool for thunderstorms nowcasting called TRT (Thun- derstorms Radar Tracking). The goal of this real-time tool is the automated detection, tracking and characterization of intense convective precipitation systems. TRT uses the re- flectivity data of the composite image of the Swiss radar net- work. The algorithm is based on an adaptive thresholding scheme, which allows the detection of convective cells at in- dividual thresholds, depending on their development phase. In this way, thunderstorms can be tracked very early during their growing phase (cells as small as a few 2◊2 km pixels) as well as in the mature stage, and trajectories are created from a sequence of radar images. The tracking is based on the method of the geographical overlapping of cells. Splits and merges are also taken into account. TRT forecasts storm movement by extrapolating the motion of individual cells up to 1 h, using the weighted cell displacement velocity. TRT is used as a nowcasting tool in a pre-operational mode at Me- teoSwiss since May 2003. on observations. The main tools in this context are remote sensing observations like radar, satellite and lightning, as well as mesonet data. Operational nowcasting systems for precipitation are mainly based on the extrapolation of radar echoes.
Implementing a secure setuid program

Setuid programs are often exploited by malicious attackers to obtain unauthorized access to local systems. Setuid programs, especially owned by the root user, are granted root privileges, allowing attackers to gain root privileges by exploiting vulnerabilities in the setuid-root programs. The vulnerabilities usually lie in code that does not require root privileges. Nevertheless, the entire code of setuid-root programs is granted root privileges. This paper presents a scheme called privileged code minimization that reduces the risk to setuid programs. In this scheme, setuid-root programs are divided into privileged code and non-privileged code. Privileged code is granted root privileges, while non-privileged code is not. This scheme reduces the size of trusted computing base (TCB) because it reduces the code running with root privileges, reducing the chances of attackers gaining root privileges by subverting setuid programs. Protection between privileged code and nonprivileged code are enforced by fine-grained protection domains: a novel protection mechainsm of the operating system proposed by the authors.
The Design of Pre-Processing Multidimensional Data Based on Component Analysis

Increased implementation of new databases related to multidimensional data involving techniques to support efficient query process, create opportunities for more extensive research. Pre-processing is required because of lack of data attribute values, noisy data, errors, inconsistencies or outliers and differences in coding. Several types of pre-processing based on component analysis will be carried out for cleaning, data integration and transformation, as well as to reduce the dimensions. Component analysis can be done by statistical methods, with the aim to separate the various sources of data into a statistical pattern independent. This paper aims to improve the quality of pre-processed data based on component analysis. RapidMiner is used for data pre-processing using FastICA algorithm. Kernel K-mean is used to cluster the pre-processed data and Expectation Maximization (EM) is used to model. The model was tested using wisconsin breast cancer datasets, lung cancer datasets and prostate cancer datasets. The result shows that the performance of the cluster vector value is higher and the processing time is shorter.
Phase I Trial of Sorafenib and Gemcitabine in Advanced Solid Tumors with an Expanded Cohort in Advanced Pancreatic Cancer

Background: With its potent inhibitory effects against Raf-1 kinase and vascular endothelial growth factor receptor-2, sorafenib is a novel oral anticancer agent targeting signal transduction and angiogenic pathways. This study is designed to combine sorafenib and gemcitabine due to their compatibility in preclinical models and nonoverlapping clinical toxicities. Experimental Design: An initial dose-escalation part of the study enrolled patients with advanced solid tumors, followed by an expanded cohort at the recommended dose for patients with advanced unresectable or metastatic pancreatic cancer. Sorafenib is administered continuously, whereas gemcitabine is given at 1,000 mg/m2 weekly × 7 followed by 1 rest week, then weekly × 3 every 4 weeks. Results: Forty-two patients have been enrolled overall, including 19 in the dose-escalation part and 23 in the extended pancreatic cancer cohort. Demographics were as follows: male-to-female ratio = 26:16; median age = 61 years (range 39-83 years); Eastern Cooperative Oncology Group performance status 0:1:2 ratio = 16:21:5. The recommended dose of this combination is sorafenib 400 mg twice daily and gemcitabine 1,000 mg/m2. The most frequent grade 3 or 4 adverse events of all causalities were thrombocytopenia (28.6%), lymphopenia (21.4%), lipase elevation (19%), neutropenia (16.7%), and fatigue (14.3%). Antitumor activity was observed in both groups, with 2 (10.5%) confirmed partial responses in ovarian cancer and 12 patients (63.2%) with disease stabilization in the dose-escalation part; 13 patients (56.5%) achieved disease stabilization in the pancreatic cohort. There was no consistent pharmacokinetic drug-to-drug interaction between sorafenib and gemcitabine. Conclusions: Sorafenib and gemcitabine are well tolerated in combination; further evaluations in pancreatic and ovarian cancers are warranted.
Geometry of all supersymmetric four-dimensional N=1 supergravity backgrounds

We solve the Killing spinor equations of ${\cal N}=1$ supergravity, with four supercharges, coupled to any number of vector and scalar multiplets in all cases. We find that backgrounds with N=1 supersymmetry admit a null, integrable, Killing vector field. There are two classes of N=2 backgrounds. The spacetime in the first class admits a parallel null vector field and so it is a pp-wave. The spacetime of the other class admits three Killing vector fields, and a vector field that commutes with the three Killing directions. These backgrounds are of cohomogeneity one with homogenous sections either $\bR^{2,1}$ or $AdS_3$ and have an interpretation as domain walls. The N=3 backgrounds are locally maximally supersymmetric. There are N=3 backgrounds which arise as discrete identifications of maximally supersymmetric ones. The maximally supersymmetric backgrounds are locally isometric to either $\bR^{3,1}$ or $AdS_4$.
The visualization of diffusion tensor fields in the brain

Di usion Tensor Imaging DTI is a relatively new image modality which can be used to gain in vivo infor mation about the anatomy of the brain We have developed a visualization workbench for the analysis of tensor elds in biological tissue and will describe an incremental approach for the exploration of di usion tensor data Our approach starts with slice images familiar to the medical specialist and progressively expands the dimension and abstraction level of the representation in order to provide new insight into the data In particular we present two new techniques for the visualization of DTI data Barycentric colour maps allow an integrated view of di erent types of di usion anisotropy Transparency modulated Line Integral Convolution creates an image segmented by tissue type and incorporating a tex ture representing the D orientation of nerve bers The quality of our exploration approach and new visualization techniques is demonstrated by identifying various anatomi cal structures and features in a di usion tensor data set of a healthy brain
Intermediaries in International Trade: Direct Versus Indirect Modes of Export

This paper examines the factors that give rise to intermediaries in exporting and explores the implications for trade volumes. Export intermediaries such as wholesalers serve different markets and export different products than manufacturing exporters. In particular, high market-specific fixed costs of exporting, the (lack of) quality of the general contracting environment and product-specific factors play important roles in explaining the existence of export intermediaries. These underlying differences between direct and intermediary exporters have important consequences for trade flows. The ability of export intermediaries to overcome country and product fixed costs means that they can more easily respond along the extensive margin to external shocks. Intermediaries and direct exporters respond differently to exchange rate fluctuations both in terms of the total value of shipments and the number of products exported as well as in terms of prices and quantities. Aggregate exports to destinations with high shares of indirect exports are much less responsive to changes in the real exchange rate than are exports to countries served primarily by direct exporters.
Matrix Metalloproteinase-3 Causes Dopaminergic Neuronal Death through Nox1-Regenerated Oxidative Stress

In the present study we investigated the interplay between matrix metalloproteinase 3 (MMP3) and NADPH oxidase 1 (Nox1) in the process of dopamine (DA) neuronal death. We found that MMP3 activation causes the induction of Nox1 via mitochondrial reactive oxygen species (ROS) production and subsequently Rac1 activation, eventually leading to Nox1-derived superoxide generation in a rat DA neuronal N27 cells exposed to 6-OHDA. While a MMP3 inhibitor, NNGH, largely attenuated mitochondrial ROS and subsequent Nox1 induction, both apocynin, a putative Nox inhibitor and GKT137831, a Nox1 selective inhibitor failed to reduce 6-OHDA-induced mitochondrial ROS. However, both inhibitors for MMP3 and Nox1 similarly attenuated 6-OHDA-induced N27 cell death. RNAi-mediated selective inhibition of MMP3 or Nox1 showed that knockdown of either MMP3 or Nox1 significantly reduced 6-OHDA-induced ROS generation in N27 cells. While 6-OHDA-induced Nox1 was abolished by MMP3 knockdown, Nox1 knockdown did not alter MMP3 expression. Direct overexpression of autoactivated MMP3 (actMMP3) in N27 cells or in rat substantia nigra (SN) increased expression of Nox1. Selective knockdown of Nox1 in the SN achieved by adeno-associated virus-mediated overexpression of Nox1-specific shRNA largely attenuated the actMMP3-mediated dopaminergic neuronal loss. Furthermore, Nox1 expression was significantly attenuated in Mmp3 null mice treated with N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Together we established novel molecular mechanisms underlying oxidative stress-mediated dopaminergic neuronal death in which MMP3 activation is a key upstream event that leads to mitochondrial ROS, Nox1 induction and eventual dopaminergic neuronal death. Our findings may lead to the development of novel therapeutic approach.
Parasitoids use herbivore‐induced information to adapt patch exploitation behaviour

Abstract. 1. Optimal foraging models ultimately predict that female parasitoids should exploit rich host patches for longer than poorer ones. At the proximate level, mechanistic models and experimental studies show that parasitoids use both chemicals produced by their hosts and direct encounters with their hosts to estimate patch quality. Although it has been extensively studied in the context of host location, the use of herbivore‐induced plant response by insect parasitoids has never been considered in the context of patch time allocation.
Improvement of prognostic models for ESRD mortality by the bootstrap method with random hot deck imputation

Prognostic models for end-stage renal disease (ESRD) have been researched extensively as an increasing prevalence internationally. Different machine learning and statistic algorithms for the models were proposed in studies corresponding to different medical datasets including a quantity of missing values for optimal outcomes. We approached this issue by applying stepwise logistic regression, ANN, and SVM algorithms to an ESRD dataset after case deletion and calculated areas under ROC curves of three algorithms as comparisons, resulting in 0.757, 0.664 and 0.704, respectively. The random hot deck, oversampling, and bootstrap methods were employed in data preprocessing to compensate the minor mortality. Afterward, average AUC of three algorithms approximated 0.90 (p<;0.02, unpaired t-test). As a result, the mentioned strategies dealing with bias medical data may ameliorate prognostic ESRD models in clinic.
Does Facial Width-to-Height Ratio Predict Aggressive Behavior in Association Football?

A growing body of research has emphasized the role of facial structures in affecting human social behavior. In particular, the facial width-to-height ratio (fWHR) was found to predict aggressive behavior, most notably in men of low social status. The current study aimed at broadening the insights into the role of fWHR in sports regarding the indicators of aggressive behavior and performance. We questioned the impact of fWHR in association football by analyzing fouls committed by players, their (yellow and red) cards received, and their goals scored and assists in the German (n = 278) and Austrian (n = 194) first division in the 2016–2017 season (306/180 matches). The market values of players were used as a measure of social status. Generalized estimating equation models taking negative binomial distribution into account did not reveal any significant impact of fWHR on fouls committed, yellow and red cards received, or assists and goals scored. Even the consideration of players’ field positions, players’ body mass index (BMI), their market value, and the interactional term of players’ fWHR and players’ market value did not affect the results. The analyses refuted any impact of fWHR in association football both on parameters of aggressive behavior (fouls and cards received) and performance (goals and assists). Merely, players’ market value was found to predict players’ goals and assists. The current study adds to the empirical evidence encouraging a critical assessment and discussion of fWHR research in sports.
ON THE APPROXIMATION OF CERTAIN PROBABILITY MEASURES BY A SET OF POINTS

In this paper we describe a framework for the comparison of a finite set of points with a probability measure if the latter belongs to a simple class. The measure of closeness chosen quantifies the degree of agreement obtained when a prescribed collection of test functions is simultaneously integrated with the respect to the given probability measure, and the set of points (identified with a set of point masses). No specific assumptions are made about the provenance of the point set, although our results have a clear application to certain Markov chain Monte Carlo integration problems.
A Delay-Based Routing Protocol for Human-Oriented Delay Tolerant Mobile Sensor Network (DTMSN)

With the vigorous development of IOT (Internet of Things), sensor units carried by human beings will form the largest DTMSN in the world. However, most of the existing DTMSN routing protocols haven't taken the characteristics of human mobility into account, and may not work well in human-oriented data gathering. In this paper, we analyze the characteristics of human mobility, and propose a novel delay- based routing protocol (DRP) for human-oriented DTMSN. In DRP, a sensor node calculates the estimated data delivery delay and takes it as a measure of the delivery capacity, the smaller the estimated delay, the higher the delivery capacity of a sensor node. When two nodes meet, data messages are forwarded to the one with smaller estimated delay. To minimize transmission overhead, DRP employs the message rank and survival time to decide message's transmission or dropping. We evaluate the proposed scheme in a real human moving scenario provided by MIT Reality datasets, which collected the traces of 100 individuals of MIT over the course of 9 months. Simulation results have shown that the proposed DRP routing protocol achieves a better performance than some other DTMSN data gathering approaches.
Position and velocity filters for intervention AUVs based on single range and depth measurements

This paper proposes novel cooperative navigation solutions for an Intervention Autonomous Underwater Vehicle (I-AUV) working in tandem with an Autonomous Surface Craft (ASC). The I-AUV is assumed to be moving in the presence of constant unknown ocean currents, and aims to estimate its position relying on measurements of its range to the ASC and of its depth relatively to the sea level. Two different scenarios are considered: in one, the ASC transmits its position and velocity to the I-AUV, while in the other the ASC transmits only its position, and the I-AUV has access to measurements of its velocity relative to the ASC. A sufficient condition for observability and a method for designing state observers with Globally Asymptotically Stable (GAS) error dynamics are presented for both problems. Finally, simulation results are included and discussed to assess the performance of the proposed solutions in the presence of measurement noise.
Heterogeneity of Violent Offenders and the Implications for Correctional Treatment: A Descriptive Profile and Examination of Treatment-Related Outcomes and Executive Cognitive Functioning in Reactive and Instrumental Violent Offenders

Purpose: By merging neuropsychological theory and practice with forensic correctional tenets, the goal of the current thesis was to explore the profile of treatment-related outcomes and executive cognitive functioning (ECF) among reactive violent offenders and instrumental violent offenders. Method: Three studies were conducted to examine the following key areas: 1) the prevalence and profile of reactive and instrumental violent offenders in terms of demographic characteristics, offence types, static risk, criminogenic needs, and psychometric measures assessing constructs related to aggression (n = 395); 2) an examination of treatment-related variables, such as readiness to change, program completion rates, and release outcomes across violent offender subtypes; and 3) an examination of ECF in reactive and instrumental violent and nonviolent offenders (n = 171). Results: In terms of profile results, violent offender subtypes were differentiated regarding the severity of violence, degree of provocation, familiarity with victim, type of substance used, and emotional state during the incident. With respect to treatment outcomes, reactive violent offenders were more likely to drop out of correctional treatment; however, they had lower rates of return to custody relative to instrumental violent offenders. ECF was differentially related to offender subtypes; specifically, reactive violent offenders were more deficient relative to nonviolent offenders. Conclusion: Many of the findings are preliminary, and as such, further replication is required. Given the differential results related to substance abuse, assessment of risk, program outcomes, and ECF, differential treatment programs for violent offenders are an important direction to consider in future program development.
Inference in Polytrees with Sets of Probabilities

Inferences in directed acyclic graphs associated with probability intervals and sets of probabilities are NP-hard, even for polytrees. We propose: 1) an improvement on Tessem's A/R algorithm for inferences on polytrees associated with probability intervals; 2) a new algorithm for approximate inferences based on local search; 3) branch-and-bound algorithms that combine the previous techniques. The first two algorithms produce complementary approximate solutions, while branch-and-bound procedures can generate either exact or approximate solutions. We report improvements on existing techniques for inference with probability sets and intervals, in some cases reducing computational effort by several orders of magnitude.
Fate of sound and diffusion in a holographic magnetic field

It was shown by Buchbinder, Buchel, and Vazquez [J. High Energy Phys. 12 (2008) 090] that, in the presence of the magnetic field, the sound waves in (2 + 1)-dimensional plasma disappear and are replaced by a diffusive mode. Similarly, the shear and charge diffusion fluctuations form a subdiffusive mode. However, since the limit of a small magnetic field does not commute with the hydrodynamic limit, it is not obvious whether or not these modes are stable under higher order corrections. Using AdS/CFT correspondence we show that, in the case of the M2-brane plasma, these modes do exist as we find the corresponding supergravity solutions. This allowed us to compute the conductivity and the shear viscosity to all orders in a magnetic field. We find that the viscosity to entropy ratio saturates the Kovtun-Son-Starinets bound. This extends the universality property of the shear viscosity to the case of the strongly coupled plasma in an external magnetic field.