Miracle-dz/UniFAR-FTUs huggingface dataset:
A Hybrid Approach to Example based Machine Translation for Indian Languages

Corpus based approaches to machine translation namely Example based machine translation and Statistical machine translation have received wide focus in the recent years. Hybrid approaches combining the two further improved the performance. Indian language machine translation has mostly focussed on rule based machine translation. We propose a hybrid approach to Example based machine translation making use of statistical machine translation methods and minimal linguistic resources. Our motive in this paper is to obtain a ’good enough’ translation as opposed to a perfect translation aimed by earlier machine translation efforts. Our approach can be used for translation of english to any indian language. In this paper, we perform experiments for translation of english to hindi and report BLEU scores.
Age Differences in Calibration of Comprehension.

Young adults have been shown to predict their reading comprehension (calibration of comprehension [CC]) based on subjective assessments of both their ease in processing text and their levels of comprehension. Predictions based on a processing ease heuristic are likely cognitively simpler than those based on assessing comprehension directly. Thus, we hypothesized that older adults base test predictions more on the simpler task of evaluating processing ease and tested whether this preference was related to their diminished working memory capacity. Young and older adults read texts, predicted performance, and evaluated their processing ease and comprehension level. Although both groups showed similar CC, older adults’ CC was significantly related to evaluating processing ease, whereas young adults’ CC was related to evaluating comprehension. This difference was not associated with working memory capacity, suggesting that older adults'reliance on evaluating processing ease was not due to cognitive difficultie.
Turbulence statistics in solid-liquid flow using a refractive index matching and particle image velocimetry technique

Turbulence statistics of solid-liquid slurry flow are measured using particle image velocimetry (PIV). Experiments are carried out in a 50.6 mm inner diameter vertical pipe loop for Reynolds number (Re) 320,000 with 0.8% particle volume concentration. Water and nearly monosized 2 mm glass beads are used as carrier and dispersed phases, respectively. During PIV post processing, particle masking is used to identify slurry particles and allow calculation of instantaneous velocity of both phases. Liquid phase axial and radial turbulent fluctuation velocity profiles are obtained from instantaneous velocity data of just the single-phase and compared with both solids and fluid in two-phase flow. The presence of the dispersed phase has no significant effect on liquid phase turbulence for 0.8% particle concentration. PIV, in conjunction with phase separation in collected images is only practicable for particle concentrations less than 1%. At higher concentrations, phase boundaries produce an unacceptable level of light scattering. To test more concentrated slurries, a refractive index matching technique, in combination with PIV, is utilized. In this experimental study, an alternative index matching fluid (aqueous potassium thiocyanate solution) is compared with a sodium iodide solution, which has been more commonly used for refractive index matching studies. The present study describes the use of a 62.4% (by mass) solution of KSCN in water, along with monosized 3 mm borosilicate glass beads for measurements of concentrated slurry flows.
Depth-dependent transverse shear properties of the human corneal stroma.

PURPOSE To measure the transverse shear modulus of the human corneal stroma and its profile through the depth by mechanical testing, and to assess the validity of the hypothesis that the shear modulus will be greater in the anterior third due to increased interweaving of lamellae. METHODS Torsional rheometry was used to measure the transverse shear properties of 6 mm diameter buttons of matched human cadaver cornea pairs. One cornea from each pair was cut into thirds through the thickness with a femtosecond laser and each stromal third was tested individually. The remaining intact corneas were tested to measure full stroma shear modulus. The shear modulus from a 1% shear strain oscillatory test was measured at various levels of axial compression for all samples. RESULTS After controlling for axial compression, the transverse shear moduli of isolated anterior layers were significantly higher than central and posterior layers. Mean modulus values at 0% axial strain were 7.71 ± 6.34 kPa in the anterior, 1.99 ± 0.45 kPa in the center, 1.31 ± 1.01 kPa in the posterior, and 9.48 ± 2.92 kPa for full thickness samples. A mean equilibrium compressive modulus of 38.7 ± 8.6 kPa at 0% axial strain was calculated from axial compression measured during the shear tests. CONCLUSIONS Transverse shear moduli are two to three orders of magnitude lower than tensile moduli reported in the literature. The profile of shear moduli through the depth displayed a significant increase from posterior to anterior. This gradient supports the hypothesis and corresponds to the gradient of interwoven lamellae seen in imaging of stromal cross-sections.
Noise Resistant Morphological Algorithm of Moving Forklift Truck Detection on Noisy Image Data

In this paper the authors focus on the specific problem of machine vision, namely, the video-based detection of the moving forklift truck. It is shown that the detection quality of the state-of-the-art local descriptors SURF, SIFT, etc. is not satisfactory if the resolution is low and the illumination is changed dramatically. The authors propose a novel algorithm to detect the presence of a cargo on the forklift truck on the basis of the mathematical morphological operators. At first, the movement direction is estimated with the updating motion history image method and the front part of the moving object is obtained. Next, contours are detected and the morphological operations in front of the moving object are used to compute several geometric features of an empty forklift. In the experimental study, it has been shown that the proposed method has 40% lower false positive rate and 27% lower false negative rate in comparison with conventional matching of local descriptors. Moreover, this algorithm is 7-35 times faster.
Coherence beamforming applied to velocity estimation and partially coherent signals

Time-delay and phase-shift estimators are often used to track speckle signals in order to estimate parameters such as strain, displacement, and velocity. These estimators rely on the beamformed RF signal to accurately estimate time and phase shifts. Partially coherent targets such as speckle, however, introduce variance and bias errors into the estimation because the delay-and-sum beamformer does not adapt to the spatial variation of the sampled waveform. In addition, the presence of acoustic and thermal noise can exacerbate this problem. We introduce a method that modifies the information used by the beamformer when it is applied to velocity and displacement estimation. Using simulations, velocity was estimated between RF channel signals, rather than beamformed RF signals, using Kasai's and Loupas' autocorrelation methods. Velocity and displacement was estimated from those channel signal pairs that exhibited high correlation. By eliminating incoherent information in Kasai's and Loupas' velocity estimators, jitter was reduced in high noise environments. For example, at 0 dB noise relative to the blood in the channel signals, Limiting the signal to high coherence signals (e.g. 10 spatial lags) reduced the jitter in the Kasai velocity estimator from approximately 6.0 mm/s to 2.5 mm/s. In general, jitter increased with increasingly incoherent information added into the beamformed signal and low noise yielded smaller jitter.
MICROECONOMIC TESTS OF RICARDIAN EQUIVALENCE

This paper tests the Ricardian Equivalence Concept by constructing “Ricardian” time series for the incomes of U.S. States. “Ricardian” income is taken to be standard disposable income minus the net increment to state debt plus the State’s apportioned share of Federal Debt. Regressions are then run using “Ricardian” and, alternatively, “standard” concepts of disposable income to explain residential electricity consumption in each state. The simplest tests used just real income and relative price as regressors. Later tests added weather and natural-gas-price variables. The “standard” concepts prove preferable, at high levels of significance in all the tests performed. * * * * The purpose of this paper is threefold: a) to make a further contribution to the already substantial literature on the empirical testing of hypotheses concerning Ricardian Equivalence, b) to demonstrate the value and illustrate some of the subtleties of working with subnational (in this case U.S. State) data, and c) to advertise the existence of a new data set on the public finances of the 50 states, which may be of considerable use to others in our profession.
Secure and Privacy Preserving Protocol for Cloud-Based Vehicular DTNs

Cloud-assisted vehicular delay tolerant networks (DTNs) have been utilized in wide-ranging applications where a continuous end-to-end connection is unavailable, the message transmission is fulfilled by the cooperation among vehicular nodes and follows a store-carry-and-forward manner, and the complex computational work can be delegated to the disengaged vehicles in the parking lots which constitute the potential vehicular cloud. Nevertheless, the existing incentive schemes as well as the packet forwarding protocols cannot well model continuous vehicle collaboration, resist vehicle compromise attacks and collusion attacks, leaving the privacy preservation issues untouched. In this paper, a novel threshold credit-based incentive mechanism (TCBI) is proposed based on the modified model of population dynamics to efficiently resist the node compromise attacks, stimulate the cooperation among intermediate nodes, maximize vehicular nodes' interest, and realize the fairness of possessing the same opportunity of transmitting packets for credits. Then, a TCBI-based privacy-preserving packet forwarding protocol is proposed to solve the open problem of resisting layer-adding attack by outsourcing the privacy-preserving aggregated transmission evidence generation for multiple resource-constrained vehicles to the cloud side from performing any one-way trapdoor function only once. The vehicle privacy is well protected from both the cloud and transportation manager. Finally, formal security proof and the extensive simulation show the effectiveness of our proposed TCBI in resisting the sophisticated attacks and the efficiency in terms of high reliability, high delivery ratio, and low average delay in cloud-assisted vehicular DTNs.
Self-adjusting binary trees

We use the idea of self-adjusting trees to create new, simple data structures for priority queues (which we call heaps) and search trees. Unlike other efficient implementations of these data structures, self-adjusting trees have no balance condition. Instead, whenever the tree is accessed, certain adjustments take place. (In the case of heaps, the adjustment is a sequence of exchanges of children, in the case of search trees the adjustment is a sequence of rotations.) Self-adjusting trees are efficient in an amortized sense: any particular operation may be slow but any sequence of operations must be fast. Self-adjusting trees have two advantages over the corresponding balanced trees in both applications. First, they are simpler to implement because there are fewer cases in the algorithms. Second, they are more storage-efficient because no balance information needs to be stored. Furthermore, a self-adjusting search tree has the remarkable property that its running time (for any sufficiently long sequence of search operations) is within a constant factor of the running time for the same set of searches on any fixed binary tree. It follows that a self-adjusting tree is (up to a constant factor) as fast as the optimal fixed tree for a particular probability distribution of search requests, even though the distribution is unknown.
Enhancing link-based similarity through the use of non-numerical labels and prior information

Several key applications like recommender systems require to compute similarities between the nodes (objects or entities) of a bipartite network. These similarities serve many important purposes, such as finding users sharing common interests or items with similar characteristics, as well as the automated recommendation and categorization of items. While a broad range of methods have been proposed to compute similarities in networks, such methods have two limitations: (1) they require the link values to be in the form of numerical weights representing the strength of the corresponding relation, and (2) they do not take into account prior information on the similarities. This paper presents a novel approach, based on the SimRank algorithm, to compute similarities between the nodes of a bipartite network. Unlike current methods, this approach allows one to model the agreement between link values using any desired function, and provides a simple way to integrate prior information on the similarity values directly in the computations. To evaluate its usefulness, we test this approach on the problem of predicting the ratings of users for movies and jokes.
Structure of outer membrane protein G by solution NMR spectroscopy

The bacterial outer membrane protein G (OmpG), a monomeric pH-gated porin, was overexpressed in Escherichia coli and refolded in β-octyl glucoside micelles. After transfer into dodecylphosphocholine micelles, the solution structure of OmpG was determined by solution NMR spectroscopy at pH 6.3. Complete backbone assignments were obtained for 234 of 280 residues based on CA, CB, and CO connection pathways determined from a series of TROSY-based 3D experiments at 800 MHz. The global fold of the 14-stranded β-barrel was determined based on 133 long-range NOEs observed between neighboring strands and local chemical shift and NOE information. The structure of the barrel is very similar to previous crystal structures, but the loops of the solution structure are quite flexible.
An Analysis of the Drivers of Microfinance Rating Assessments

Rating assessments of microfinance institutions (MFIs) are claimed to measure a combination of creditworthiness, trustworthiness, and excellence in microfinance. Using a global data set covering reports from 304 microfinance institutions, this study suggests that these ratings are mainly driven by size, profitability, and risk. The overall results suggest that microfinance ratings convey information similar to that communicated by traditional credit ratings. All results are remarkably consistent across rating agencies. The determinants of the rating grades are found to be the same in all subsamples.
Genome‐wide association study of schizophrenia in Ashkenazi Jews

Schizophrenia is a common, clinically heterogeneous disorder associated with lifelong morbidity and early mortality. Several genetic variants associated with schizophrenia have been identified, but the majority of the heritability remains unknown. In this study, we report on a case‐control sample of Ashkenazi Jews (AJ), a founder population that may provide additional insights into genetic etiology of schizophrenia. We performed a genome‐wide association analysis (GWAS) of 592 cases and 505 controls of AJ ancestry ascertained in the US. Subsequently, we performed a meta‐analysis with an Israeli AJ sample of 913 cases and 1640 controls, followed by a meta‐analysis and polygenic risk scoring using summary results from Psychiatric GWAS Consortium 2 schizophrenia study. The U.S. AJ sample showed strong evidence of polygenic inheritance (pseudo‐R2 ∼9.7%) and a SNP‐heritability estimate of 0.39 (P = 0.00046). We found no genome‐wide significant associations in the U.S. sample or in the combined US/Israeli AJ meta‐analysis of 1505 cases and 2145 controls. The strongest AJ specific associations (P‐values in 10−6–10−7 range) were in the 22q 11.2 deletion region and included the genes TBX1, GLN1, and COMT. Supportive evidence (meta P < 1 × 10−4) was also found for several previously identified genome‐wide significant findings, including the HLA region, CNTN4, IMMP2L, and GRIN2A. The meta‐analysis of the U.S. sample with the PGC2 results provided initial genome‐wide significant evidence for six new loci. Among the novel potential susceptibility genes is PEPD, a gene involved in proline metabolism, which is associated with a Mendelian disorder characterized by developmental delay and cognitive deficits. © 2015 Wiley Periodicals, Inc.
Lightweight monitoring system for IOT devices

The Internet of Things (IoT) brings millions of devices, in the form of sensor, actuator, or embedded electronic devices interconnected through the Internet. Monitoring abundant of IoT devices is a big challenge, especially in a constrained condition of sensor nodes (e.g. limited CPU, memory, and battery). Therefore, a good monitoring system with an efficient monitoring protocol is often needed to compensate the limited resources of sensor nodes. SNMP is a protocol that widely used for a monitoring system. However, SNMP was developed without taking into account of devices with limited resources. This paper presents a proposed prototype of a light weight monitoring system based on agent-manager model. The testing result shows that the developed prototype system generates smaller packet sizes than the SNMP-based monitoring system on the same function and shows a low CPU and memory usage in monitoring thousands of devices.
Model-Based Analysis of Java EE Web Security Configurations

The widespread use of Java EE web applications as a means to provide distributed services to remote clients imposes strong security requirements, so that the resources managed by these applications remain protected from unauthorized disclosures and manipulations. For this purpose, the Java EE framework provides developers with mechanisms to define access-control policies. Unfortunately, the variety and complexity of the provided security configuration mechanisms cause the definition and manipulation of a security policy to be complex and error prone. As security requirements are not static, and thus, implemented policies must be changed and reviewed often, discovering and representing the policy at an appropriate abstraction level to enable their understanding and reenginering appears as a critical requirement. To tackle this problem, this paper presents a (model-based) approach aimed to help security experts to visualize, (automatically) analyse and manipulate web security policies.
Development of multiple thinking and creativity in organizational learning

Purpose – Based on a typology of contextualized multiple thinking, this paper aims to elaborate how the levels of thinking (data, information, knowledge, and intelligence), and the types of thinking as a whole, can be used to profile the characteristics of multiple thinking in organizational learning, re‐conceptualize the nature of creativity in organizational action and thinking, and provide a new systematic framework to broaden the possibilities and approaches to developing multiple thinking and creativity in organizational action and learning in education and other sectors.Design/methodology/approach – The paper presents a theoretical framework of multiple thinking and creativity in organizational learning.Findings – Based on the typology of contextualized multiple thinking, a new theoretical framework can be proposed to facilitate understanding and development of multiple thinking and creativity in organizational learning and to enhance the effectiveness of action of individuals and organizations in e.
Data Randomization

Attacks that exploit memory errors are still a serious problem. We present data randomization, a new technique that provides probabilistic protection against thes e attacks by xoring data with random masks. Data randomization uses static analysis to partition instruction operands into equivalence classes: it places two operands in the same class if they may refer to the same object in an execution that does not violate memory safety. Then it assigns a random mask to each class and it generates code instrumented to xor data read from or written to memory with the mask of the memory operand’s class. Therefore, attacks that violate the results of the static analysis have unpredictable results. We implemented a data randomization prototype that compiles programs without modifications and can prevent many attacks with low overhead. Our prototype prevents all the attacks in our benchmarks while introducing an average runtime overhead of 11% (0% to 27%) and an average space overhead below 1%.
On the survival of frozen bacteria.

SUMMARY: Steadily growing Aerobacter aerogenes organisms were largely killed by slow freezing in buffer or by freeze drying. 100% survival was obtained after dropping bacteria suspended in 10% aqueous glycerol into liquid nitrogen and thawing. Ten per cent solutions of diethylene glycol, i-erythritol, glucose, sucrose or polyethylene glycol (MW = 10,000) protected equally well; the last three substances did not penetrate the cell cytoplasm. The most lethal medium was dilute NaCl; broth, water or a dilute salt mixture were moderately lethal. These findings are incompatible with the view that the lethal effects of freezing are connected with osmotic shock or that protection from freezing damage requires (a) penetration of the protective agent or (b) osmotic dehydration of the cytoplasm. Cells frozen and thawed, even with a protective agent, showed a lowered rate of glycerol oxidation and a higher death rate when starved at the optimal temperature and pH value for growth. The storage life of frozen organisms at -20° depended on the protective agent used; only glycerol permitted extended storage.
Tolerance of anaerobic conditions caused by flooding during germination and early growth in rice (Oryza sativa L.)

Rice is semi-aquatic, adapted to a wide range of hydrologies, from aerobic soils in uplands to anaerobic and flooded fields in waterlogged lowlands, to even deeply submerged soils in flood-prone areas. Considerable diversity is present in native rice landraces selected by farmers over centuries. Our understanding of the adaptive features of these landraces to native ecosystems has improved considerably over the recent past. In some cases, major genes associated with tolerance have been cloned, such as SUB1A that confers tolerance of complete submergence and SNORKEL genes that control plant elongation to escape deepwater. Modern rice varieties are sensitive to flooding during germination and early growth, a problem commonly encountered in rainfed areas, but few landraces capable of germination under these conditions have recently been identified, enabling research into tolerance mechanisms. Major QTLs were also identified, and are being targeted for molecular breeding and for cloning. Nevertheless, limited progress has been made in identifying regulatory processes for traits that are unique to tolerant genotypes, including faster germination and coleoptile elongation, formation of roots and leaves under hypoxia, ability to catabolize starch into simple sugars for subsequent use in glycolysis and fermentative pathways to generate energy. Here we discuss the state of knowledge on the role of the PDC-ALDH-ACS bypass and the ALDH enzyme as the likely candidates effective in tolerant rice genotypes. Potential involvement of factors such as cytoplasmic pH regulation, phytohormones, reactive oxygen species scavenging and other metabolites is also discussed. Further characterization of contrasting genotypes would help in elucidating the genetic and biochemical regulatory and signaling mechanisms associated with tolerance. This could facilitate breeding rice varieties suitable for direct seeding systems and guide efforts for improving waterlogging tolerance in other crops.