Miracle-dz/UniFAR-FTUs huggingface dataset:
Three-dimensional ambient noise tomography of the Bohemian Massif

We have performed 3D ambient noise tomography of the Bohemian Massif. We invert adopted inter-station dispersion curves of both Love and Rayleigh waves in periods 4–20 s, which were extracted from ambient noise crosscorrelations, using a two-step approach. In the first step, the inter-station dispersion curves are localized for each period into the so-called dispersion maps. To account for finite-frequency effects, gradient method employing Fréchet kernels is used. Assuming membrane wave approximation of the surface wave propagation at each period, the kernels were calculated using the adjoint method. To reduce the effect of data noise, the kernels were regularized by Gaussian smoothing. The proper level of regularization is assessed on synthetic tests. In the second step, the phase-velocity dispersion maps are inverted into a 3D S-wave velocity model using the Bayesian approach. The posterior probability density function describing the solution is sampled by more than one million models obtained by Monte-Carlo approach (parallel tempering). The calculated variance of the model shows that the well resolved part corresponds to the upper crust (i.e., upper 20 km). The mean velocity model contains mainly large scale structures that show good correlation with the main geologic domains of the Bohemian Massif. Furthermore, in the well-studied area of Western Bohemia our model agrees well with S-wave velocity models published by other authors.
Static Minimization of Total Energy Consumption in Memory Subsystem for Scratchpad-Based Systems-on-Chips

In VLSI systems-on-chips (SoC), leakage is expected to override 50% of the total power consumption, and the memory sub-system can be responsible for up to 75% of the power. Scratch-pad memories (SPM) are a proven alternative to cache memories in power-aware SoCs. Optimal SPM mapping has already been investigated for dynamic power reduction in the main memory and for leakage reduction in the SPM itself. This paper addresses the problem of global energy optimization (i.e., active + leakage) in the whole memory sub-system of an SPM-based SoC. We focus on SPMs dedicated to instructions and constant data. We present the technology-level foundation, the mathematical problem formulation, its solution as an integer-linear-programming (ILP) problem, the implemented design flow, and the power reduction results referring to standard benchmarks and ITRS technology data.
HMM Based Online Handwritten Bangla Character Recognition Using Dirichlet Distributions

A reasonably large database of online handwritten Bangla characters has been developed. Such a handwritten character sample is composed of one or more strokes. Seventy five such stroke classes have been identified on the basis of the varying handwriting styles present in the character database. Each character sample is a sequence of strokes emanating from these stroke classes. Another database of handwritten Bangla strokes has been developed from the character database. This is the first such database for Bangla script. Certain stroke level features are defined on the basis of certain extremum points which represent the stroke shape reasonably well. The proposed character classification method is a two-stage approach. First, a probability distribution is estimated for each stroke class using the stroke features and then an HMM based character classifier is designed using each stroke class as a state. The parameters of both the stroke class distributions and the character class HMMs are estimated on the basis of the training set having 29,951 character samples. The character level recognition accuracy obtained by the proposed method on the test set having 8,616 samples, is 91.85%.
A Review of Disc Scrubbing and Intra Disc Redundancy Techniques for Reducing Data Loss in Disc File Systems

of high demand that applications and new technologies have today for data storage capacity, more disk drives are needed, resulting in increased probability to inaccessible sectors, referred as Latent Sector Errors (LSE). Aiming to reduce data loss by LSE, two main techniques are extensively studied lately: Disk Scrubbing, which performs reading operations during idle periods on systems to search for errors and Intra Disk Redundancy which is based on redundancy codes. This paper reviews and discusses the problems of LSE and the main causes that lead to LSE, its properties and their correlation on nearline and enterprise disks. Focusing on reducing LSE with regards to security, processing overhead and disk space, we analyze and compare the latest techniques: Disc Scrubbing and Intra Disk Redundancy aiming to highlight the issues and challenges according to different statistical approaches. Furthermore, based on previous evaluation results, we discuss and introduce the benefits on using both schemes simultaneously: combining different IDR coding schemes with Accelerated Scrubbing and Staggered Scrubbing in particular regions of disc drives that store crucial data during idle periods. Finally, we discuss and evaluate from an extended statistical analysis the best ways on how reduce data loss with a minimum impact on system performance.
Analogy Makes Proofs Feasible

Many mathematical proofs are hard to generate forhumans and even harder for automated theoremprovers. Classical techniques of automated theoremproving involve the application of basic rules, of built-in special procedures, or of tactics. Melis (Melis 1993)introduced a new method for analogical reasoning inautomated theorem proving. In this paper we showhow the derivational analogy replay method is relatedand extended to encompass analogy-driven proof planconstruction. The method is evaluated by showing theproof plan generation of the Pumping Lemma for con-text free languages derived by analogy with the proofplan of the Pumping Lemma for regular languages.This is an impressive evaluation test for the analogicalreasoning method applied to automated theorem prov-ing, as the automated proof of this Pumping Lemmais beyond the capabilities of any of the current auto-mated theorem provers.
Community Detection to Identify Fraud Events in Telecommunications Networks

Telecommunications' industry evolves into a high competitive market which demands companies to establish an effective revenue assurance framework. Social network analysis can be used to increase the knowledge about the customers' behavior, not just in terms of individual usage but mostly in relation to the customers' connections and how they create communities according to their call and text messages. By performing community detection, telecommunications companies are able to recognize groups of customers which unexpected behavior in terms of usage and also in regard to types of social structures. Outliers groups might be pointed out as suspicious communities in terms of fraud events, delivering a relevant knowledge about possible leakages of money.
Associations and interactions between SNPs in the alcohol metabolizing genes and alcoholism phenotypes in European Americans.

BACKGROUND Alcohol dependence is a major cause of morbidity and mortality worldwide and has a strong familial component. Several linkage and association studies have identified chromosomal regions and/or genes that affect alcohol consumption, notably in genes involved in the 2-stage pathway of alcohol metabolism. METHODS Here, we use multiple regression models to test for associations and interactions between 2 alcohol-related phenotypes and SNPs in 17 genes involved in alcohol metabolism in a sample of 1,588 European American subjects. RESULTS The strongest evidence for association after correcting for multiple testing was between rs1229984, a nonsynonymous coding SNP in ADH1B, and DSM-IV symptom count (p = 0.0003). This SNP was also associated with maximum number of drinks in 24 hours (p = 0.0004). Each minor allele at this SNP predicts 45% fewer DSM-IV symptoms and 18% fewer max drinks. Another SNP in a splice site in ALDH1A1 (rs8187974) showed evidence for association with both phenotypes as well (p = 0.02 and 0.004, respectively), but neither association was significant after accounting for multiple testing. Minor alleles at this SNP predict greater alcohol consumption. In addition, pairwise interactions were observed between SNPs in several genes (p = 0.00002). CONCLUSIONS We replicated the large effect of rs1229984 on alcohol behavior, and although not common (MAF = 4%), this polymorphism may be highly relevant from a public health perspective in European Americans. Another SNP, rs8187974, may also affect alcohol behavior but requires replication. Also, interactions between polymorphisms in genes involved in alcohol metabolism are likely determinants of the parameters that ultimately affect alcohol consumption.
Dynamics of ellipsoidal tracers in swimming algal suspensions.

Enhanced diffusion of passive tracers immersed in active fluids is a universal feature of active fluids and has been extensively studied in recent years. Similar to microrheology for equilibrium complex fluids, the unusual enhanced particle dynamics reveal intrinsic properties of active fluids. Nevertheless, previous studies have shown that the translational dynamics of spherical tracers are qualitatively similar, independent of whether active particles are pushers or pullers-the two fundamental classes of active fluids. Is it possible to distinguish pushers from pullers by simply imaging the dynamics of passive tracers? Here, we investigated the diffusion of isolated ellipsoids in algal C. reinhardtii suspensions-a model for puller-type active fluids. In combination with our previous results on pusher-type E. coli suspensions [Peng et al., Phys. Rev. Lett. 116, 068303 (2016)PRLTAO0031-900710.1103/PhysRevLett.116. 068303], we showed that the dynamics of asymmetric tracers show a profound difference in pushers and pullers due to their rotational degree of freedom. Although the laboratory-frame translation and rotation of ellipsoids are enhanced in both pushers and pullers, similar to spherical tracers, the anisotropic diffusion in the body frame of ellipsoids shows opposite trends in the two classes of active fluids. An ellipsoid diffuses fastest along its major axis when immersed in pullers, whereas it diffuses slowest along the major axis in pushers. This striking difference can be qualitatively explained using a simple hydrodynamic model. In addition, our study on algal suspensions reveals that the influence of the near-field advection of algal swimming flows on the translation and rotation of ellipsoids shows different ranges and strengths. Our work provides not only new insights into universal organizing principles of active fluids, but also a convenient tool for detecting the class of active particles.
Gene expression profiling demonstrates a novel role for foetal fibrocytes and the umbilical vessels in human fetoplacental development

There is a difference in the susceptibility to inflammation between the umbilical vein (UV) and the umbilical arteries (UAs). This led us to hypothesize that there is an intrinsic difference in the pro‐inflammatory response between UA and UV. Real‐time quantitative RT‐PCR and microarray analysis revealed higher expression of interleukin (IL)‐1β and IL‐8 mRNA in the UV and differential expression of 567 genes between the UA and UV associated with distinct biological processes, including the immune response. Differential expression of human leukocyte antigen (HLA)‐DRA mRNA between the UA and UV was due to unexpected HLA‐DR+ cells migrating via the umbilical vessels into Wharton's jelly, more frequently in the UV. A significant proportion of these cells co‐expressed CD45 and type I pro‐collagen, and acquired CD163 or α‐smooth muscle actin immunoreactivity in Wharton's jelly. Migrating cells were also found in the chorionic and stem villous vessels. Furthermore, the extent of migration increased with progression of gestation, but diminished in intrauterine growth restriction (IUGR). The observations herein strongly suggest that circulating foetal fibrocytes, routing via umbilical and placental vessels, are a reservoir for key cellular subsets in the placenta. This study reports fibrocytes in the human umbilical cord and placenta for the first time, and a novel role for both circulating foetal cells and the umbilical vessels in placental development, which is deranged in IUGR.
Friction‐Stability‐Permeability Evolution of a Fracture in Granite

The evolution of frictional strength, stability, and fracture permeability is intimately linked both to the seismic cycle and to the impact of hydraulic stimulation for fractured reservoirs. However, despite this importance, the poromechanical relationships between fault permeability and strength remain unclear. The present study explores this relationship via laboratory experiments for concurrent shear‐flow on smooth fractures of Westerly granite. The novelty of these experiments is that the shear velocity is precisely controlled during the measurement of fracture permeability. Results indicate permeability enhancement during velocity‐weakening (potentially unstable) frictional slip. To decipher key processes contributing to this response, we evaluate the state of contacting asperities and of fracture surface asperities via digital rock fracture modeling of statistically equivalent surfaces. We propose two plausible mechanisms constraining the relationship between friction and permeability evolution—one based on changes in asperity contact distribution and one on shear‐induced dilation triggered by changes in fault slip velocity. These mechanisms should be taken into account in interpreting field observation such as the abrupt permeability increase of natural faults at the onset of seismic slip.
How Does Investment Risk Mediate the Effect of Investment Literacy on Online Interest in Investing Among Generation Z?

This study aims to determine whether or not there is an influence of investment literacy on online investment interest with investment risk as an intervening variable. The type of research used is case study research with a quantitative approach and uses data collection techniques through questionnaires distributed online. The population in this study is generation Z in Cirebon City with a sampling technique using probability sampling, namely with a simple random sampling method of 155 people, with path analysis using the help of IBM Stastistic SPSS software version 25. The results showed that the level of investment literacy had a positive and significant effect on online investment interest with a calculation of 12,251 (>1,655) and a significance value of 0,000 (<0.05). Investment risk has a positive and significant effect on online investment interest with a calculation of 5.377 (>1.655) and a significance value of 0.000 (<0.05). While in the sobel test, it is known that investment risk can mediate the influence of investment literacy on online investment interest of 4.2353714571305.
Selective value prediction

Value prediction is a relatively new technique to increase instruction-level parallelism by breaking true data dependence chains. A value prediction architecture produces values, which may be later consumed by instructions that execute speculatively using the predicted value. This paper examines selective techniques for using value prediction in the presence of predictor capacity constraints and reasonable misprediction penalties. We examine prediction and confidence mechanisms in light of these constraints, and we minimize capacity conflicts through instruction filtering. The latter technique filters which instructions put values into the value prediction table. We examine filtering techniques based on instruction type, as well as giving priority to instructions belonging to the longest data dependence path in the processor's active instruction window. We apply filtering both to the producers of predicted values and the consumers. In addition, we examine the benefit of using different confidence levels for instructions using predicted values on the longest dependence path.
Performance Evaluation of ½ Rate Convolution Coding with Different Modulation Techniques for DS-CDMA System over Rician Channel

this paper we evaluate the performance of ½ rate convolution coding with different modulation techniques such as Binary phase shift keying (BPSK), Quadrature phase shift keying (QPSK) and Quadrature amplitude modulation (QAM- 16) for direct sequence code division multiple access(DS- CDMA) system using maximal ratio combining (MRC) and equal gain combining (EGC) diversity techniques over Rician fading channel. The performance of ½ rate convolution coding with different modulation techniques are analyzed in terms of Bit error rate (BER) and Signal to noise ratio (SNR). Based on simulation results we have concluded that we obtain better gain in SNR performance when ½ rate convolution coding is used with different modulation techniques.
Interference reflection separation from a single image

The interference image is defined as the superpositioning of a reflection image and an object image. A technique for separating reflection and object components of a single interference image is presented. The proposed method classifies edges of the interference image into either reflection or object related. Our method utilizes total variation (TV) method, blur measure, and region segmentation as evidence with a fuzzy integral technique to classify the edge pixels. Based on the results of edge pixel classification, the reflection and object components of the input image are reconstructed. Compared to previous published research, the proposed method is fast and requires no manual operations. The experimental results have demonstrated that the proposed method can perform separation of a single interference image effectively with small misadjustments and rapid convergence.
Low‐level alcohol consumption during adolescence and its impact on cognitive control development

Adolescence is a critical period for maturation of cognitive control and most adolescents start experimenting with alcohol around that time. On the one hand, recent studies indicate that low control abilities predict future problematic alcohol use. On the other hand, binge drinking during young adulthood can (further) impair cognitive control. However, so far no study examined the effects of low‐level alcohol use during adolescence. In the present longitudinal fMRI study, we therefore investigated the development of cognitive control in a community‐based sample of 92 adolescents at ages 14, 16 and 18. Two different cognitive control functions, i.e. inhibition of pre‐potent responses (operationalized by incongruence effects) and switching between different task sets, were measured within one task. Alcohol use in our sample was low (mean: 54 g/week at age 18). The study revealed that neither behavioural nor neural measures of cognitive control function at age 14 predicted alcohol use at age 18 but confirmed established predictors such as gender and personality. As expected, from age 14 to 18, cognitive control abilities were improving (decreased reaction times and/or errors), and activation of cognitive control networks (dorsal anterior cingulate cortex and pre‐supplementary motor area) during incongruent trials increased. Unexpectedly, higher alcohol consumption during adolescence was associated with a more pronounced increase in cognitive performance and a smaller increase of neural activation when incongruent trials afforded inhibitory control. We conclude that low‐level alcohol use during adolescence does not severely impair ongoing maturation of cognitive control abilities and networks.
Ordering, Indexing, and Searching Semantic Data: A Terminology Aware Index Structure

Indexing data for efficient search capabilities is a core problem in many domains of computer science. As applications centered around semantic data sources become more common, the need for more sophisticated indexing and querying capabilities arises. In particular, the need to search for specific information in the presence of a terminology or ontology (i.e. a set of logic based rules that describe concepts and their relations) becomes of particular importance, as the information a user seeks may exists as an entailment of the explicit data by means of the terminology. This variant on traditional indexing and search problems forms the foundation of a range of possible technologies for semantic data. In this work, we propose an ordering language for specifying partial orders over semantic data items modeled as descriptions in a description logic. We then show how these orderings can be used as the basis of a search tree index for processing concept searches in the presence of a terminology. We study in detail the properties of the orderings and the associated index structure, and also explore a relationship between ordering descriptions called order refinement. A sound and complete procedure for deciding refinement is given. We also empirically evaluate a prototype implementation of our index structure, validating its potential efficacy in semantic query problems.
Positive Influence of Intercrops on Natural Enemies in Groundnut Eco-System

Groundnut (Arachis hypogaea L.) is a leading oilseed crop in India. It is called as „the king of oilseeds‟. The seeds are rich source of edible oil (43-55%) and protein (25-28%), also a valuable source of vitamins viz., E, K and B (Kandakoor et al., 2014). Groundnut is native of Brazil which was introduced into India in the sixteenth century. The most important groundnut growing countries are India, China, Nigeria, Sudan and USA. It is grown over an area of 18.9 million hectares with a total production of 17.8 million tonnes in the World. However it is grown in an area of 5.5 Million hectares with a production of 9.7 Million tonnes in India, contributing about 55 per cent of the total oil seed production of the Country which ranks first in the world in terms of total area and 2 nd in production. It‟s cultivation is mostly confined to the Southern Indian states, viz., Gujarat, Andhra Pradesh, Karnataka, Tamil Nadu and Maharashtra accounting more than 80 per cent of the total production and acreage. The mean yield of groundnut is about 1784 kg. of pods/ha. in Tamil Nadu, which is higher than the world average (1336 kg./ha.) and it ranks first in India. Tamil Nadu accounts for about 12 per cent (0.41 Million hectares) of the total area under groundnut, it contributes to 22 per cent (0.81 Million Tons) of the total production (Anonymous, 2015).
Recognizing Textual Relatedness with Predicate-Argument Structures

In this paper, we first compare several strategies to handle the newly proposed three-way Recognizing Textual Entailment (RTE) task. Then we define a new measurement for a pair of texts, called Textual Relatedness, which is a weaker concept than semantic similarity or paraphrase. We show that an alignment model based on the predicate-argument structures using this measurement can help an RTE system to recognize the Unknown cases at the first stage, and contribute to the improvement of the overall performance in the RTE task. In addition, several heterogeneous lexical resources are tested, and different contributions from them are observed.