Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential involvement of nigral subregions in idiopathic parkinson's disease

In this study, the prevalence of abnormality in putative nigrosome 1 and nigrosome 4 (N1 and N4, respectively) was investigated in early versus late‐stage idiopathic Parkinson's disease (IPD) patients. A total of 128 IPD patients (early stage[n = 89]; late stage[n = 39]) and 15 healthy subjects were scanned for high‐resolution (0.5 × 0.5 × 1.0 mm3) multiecho gradient‐recalled echo MRI and dopamine transporter PET imaging. The MRI data were processed for susceptibility map‐weighted imaging (SMWI) to improve a contrast‐to‐noise ratio, and the images were resliced at 0.5 mm to define N1 and N4. When each side of N1 and N4 was assessed separately for the loss of hyperintensity by two independent reviewers, the consensus review results showed that in early‐stage IPD (178 substantia nigras [SNs]), the loss of hyperintensity was observed more often in only the N1 region (65.2%) when compared to in both N1 and N4 regions (34.8%). In late‐stage IPD (78 SNs), on the other hand, the loss in only the N1 region (25.6%) was less prevalent than in both N1 and N4 (74.4%) (P < 0.0001). Additionally, intact SNs (both in N1 and N4) were observed 17 SNs (9.6%) of the early‐stage IPD patients, whereas it was not found in any SNs of the late‐stage IPD patients (P = 0.005). Moreover, involvement of both N1 and N4 on both sides was found in 19.1% of the early‐stage IPD patients, whereas its incidence was higher (61.5%) in the late‐stage IPD patients (P < 0.0001), suggesting that the loss of hyperintensity in IPD progresses from N1 to N4 as the disease advances. Hum Brain Mapp 39:542–553, 2018. © 2017 Wiley Periodicals, Inc.
Manifold inconsistency constrained sparse coding for image super-resolution reconstruction

In the most of super-resolution reconstruction algorithms, high-resolution (HR) and low-resolution (LR) images are assumed to have the same manifold. However, this assumption is not suitable for the practical applications. Therefore, this paper proposes a new algorithm with the consideration of inconsistent manifold between HR and LR images. In the proposed method, LR dictionary and spare representation coefficient set are trained first. Then, HR dictionary can be obtained based on HR sample set and spare representation coefficients which are obtained in the first step. PCA algorithm is introduced to reduce the dimensionality of LR feature image to reduce the dictionary training time. A global optimization algorithm is provided to eliminate the blocking effect of the reconstruction image. Results show that the proposed method can reduce training time rapidly and improve the quality of reconstruction image in the aspects of both objective evaluation and subjective visual effect.
Incompatibility Boundaries for Properties of Community Partitions

We prove the incompatibility of certain desirable properties of community partition quality functions. Our results generalize the impossibility result of [Kleinberg 2003] by considering sets of weaker properties. In particular, we use an alternative notion to solve the central issue of the consistency property. (The latter means that modifying the graph in a way consistent with a partition should not have counterintuitive effects). Our results clearly show that community partition methods should not be expected to perfectly satisfy all ideally desired properties. We then proceed to show that this incompatibility no longer holds when slightly relaxed versions of the properties are considered, and we provide examples of simple quality functions satisfying these relaxed properties. An experimental study of these quality functions shows a behavior comparable to established methods in some situations, but more debatable results in others. This suggests that defining a notion of good partition in communities probably requires imposing additional properties.
Maternal high-salt diet alters redox state and mitochondrial function in newborn rat offspring’s brain

Abstract Excessive salt intake is a common feature of Western dietary patterns, and has been associated with important metabolic changes including cerebral redox state imbalance. Considering that little is known about the effect on progeny of excessive salt intake during pregnancy, the present study investigated the effect of a high-salt diet during pregnancy and lactation on mitochondrial parameters and the redox state of the brains of resulting offspring. Adult female Wistar rats were divided into two dietary groups (n 20 rats/group): control standard chow (0·675 % NaCl) or high-salt chow (7·2 % NaCl), received throughout pregnancy and for 7 d after delivery. On postnatal day 7, the pups were euthanised and their cerebellum, hypothalamus, hippocampus, prefrontal and parietal cortices were dissected. Maternal high-salt diet reduced cerebellar mitochondrial mass and membrane potential, promoted an increase in reactive oxygen species allied to superoxide dismutase activation and decreased offspring cerebellar nitric oxide levels. A significant increase in hypothalamic nitric oxide levels and mitochondrial superoxide in the hippocampus and prefrontal cortex was observed in the maternal high-salt group. Antioxidant enzymes were differentially modulated by oxidant increases in each brain area studied. Taken together, our results suggest that a maternal high-salt diet during pregnancy and lactation programmes the brain metabolism of offspring, favouring impaired mitochondrial function and promoting an oxidative environment; this highlights the adverse effect of high-salt intake in the health state of the offspring.
Power allocation for multi-homing heterogeneous network aided by energy harvesting

In this paper, we consider an energy harvested heterogeneous network where the base stations (BSs) in each tier is powered by different energy harvesting unit, which leads to time-and-spatial variable power assumption for both downlink and uplink transmitting. Then, an optimal power allocation method for maximizing system transmission rate under multi-homing scenario is investigated with the consideration of service quality requirements of mobile terminals (MTs). Based on the optimization framework, we further propose a simplified power allocation scheme. Simulation results demonstrate that the proposed algorithm is capable of approaching the optimal system capacity as well as reducing the computational complexity compared to the optimal method.
Effect of Hardness Distribution on Crack Initiation Life and Fracture Life of Induction Hardened Steels for Automotive Shafts

Synopsis : The purpose of this study is to clarify an effect of hardness distribution on the torsional fatigue strength of induction hardened steels. The factors of hardness controlling crack initiation life and breakage life were investigated against the each fracture mode of internal and surface fracture origin. Torsional fatigue strength of induction hardened steels was dependent on each of the hardness and depth of the hardened layer and the hardness of core zone on the internal and surface fracture origin, respectively. In addition torsional fatigue strength increased with increasing these factors of hardness distribution. The crack initiation life of the test-pieces fractured with surface origin could be expressed by a new indicater, "equivalent hardness", defined as a mean hardness weighted with the radius squared. The breakage life of the test-pieces fractured with surface origin in low cycles faigue test could be expressed by the equivalent hardness, too. This was because the crack initiation life was dominant to the breakage life in low cycles fatigue test. The crack initiation life of the test-pieces fractured with internal origin could be expressed by a new indicater, "projected core hardness", defined as a core hardness projected from internal fracture origin site to surface along stress distribution. The breakage life of the test-pieces fractured with internal origin could be expressed roughly by the projected core hardness, too.
Query and Output: Generating Words by Querying Distributed Word Representations for Paraphrase Generation

Most recent approaches use the sequence-to-sequence model for paraphrase generation. The existing sequence-to-sequence model tends to memorize the words and the patterns in the training dataset instead of learning the meaning of the words. Therefore, the generated sentences are often grammatically correct but semantically improper. In this work, we introduce a novel model based on the encoder-decoder framework, called Word Embedding Attention Network (WEAN). Our proposed model generates the words by querying distributed word representations (i.e. neural word embeddings), hoping to capturing the meaning of the according words. Following previous work, we evaluate our model on two paraphrase-oriented tasks, namely text simplification and short text abstractive summarization. Experimental results show that our model outperforms the sequence-to-sequence baseline by the BLEU score of 6.3 and 5.5 on two English text simplification datasets, and the ROUGE-2 F1 score of 5.7 on a Chinese summarization dataset. Moreover, our model achieves state-of-the-art performances on these three benchmark datasets.
Study the effect of series and parallel LEDs connections on the output current ripple for LED driver of solar street lighting

LED lighting fixtures become very important and largely used to replace the conventional sodium and metal-halide lighting fixtures used to illuminate streets. LED lighting fixture consists of group of high brightness LEDs lenses arranged in specific configuration and energized from power source via LED driver, the power source in this research is considered batteries storage system charged from micro-generation PV system at the daylight hours. Then, the required LED driver is a current controlled DC-DC converter. This paper studies the effect of series, parallel and hybrid connections for LEDs' array on the equivalent dynamic resistance that is inversely proportional to the output LED current ripple. It is very important to connect the LEDs array of street lighting fixtures in suitable connection to draw low current ripple. Lower output current ripples guide to minimize the size of the electrolytic capacitor, then increasing the LEDs life timer.
The effect of seed cotton moisture during harvesting on – part 1 – fiber quality

It is generally accepted that harvesting and storing of seed cotton above a moisture content of 12% prior to ginning will compromise fiber quality. This advice stems from research conducted on harvesting seed cotton with the conventional basket and separate module building system, which produces large rectangular modules. It is hypothesized that the 12% moisture content limit will also hold true for harvesting seed cotton in a high-production system using alternative harvesters. The latest generation of harvesters, such as the John Deere (JD) 7760 spindle harvester with on-board module building capacity producing smaller round modules, have greater horsepower, traction and fan capacity, which enables them to harvest cotton when field conditions would have made harvesting difficult with conventional systems. This study examined the fiber quality of saw ginned Upland cotton, harvested from one field using a JD 7760 at two moisture levels, <12% and >12%, and storing the harvested modules for 12 weeks prior to ginning. There was a significant difference between the two moisture levels for fiber color, with seed cotton harvested at >12% resulting in fiber that was yellower, with lower reflectance and a color grade of 52, compared to a 51 grade for seed cotton harvested at <12% treatment. The seed cotton harvested at >12% had more trash with a leaf grade of 3, compared to a leaf grade of 2 for the seed cotton harvested at the <12% level. There was no significant difference between the two moisture levels in terms of fiber length and strength, but fiber micronaire was higher for the higher moisture content. There was no significant difference between the moisture levels for total nep count, but the seed cotton harvested at >12% had larger neps and more seed coat neps.
Cedar studio: an IDE supporting adaptive model-driven user interfaces for enterprise applications

Support tools are necessary for the adoption of model-driven engineering of adaptive user interfaces (UI). Enterprise applications in particular, require a tool that could be used by developers as well as I.T. personnel during all the development and post-development phases. An IDE that supports adaptive model-driven enterprise UIs could further promote the adoption of this approach. This paper describes Cedar Studio, our IDE for building adaptive model-driven UIs based on the CEDAR reference architecture for adaptive UIs. This IDE provides visual design and code editing tools for UI models and adaptive behavior. It is evaluated conceptually using a set of criteria from the literature and applied practically by devising example adaptive enterprise user interfaces.
A projection matrix-based geometric calibration algorithm in CBCT system

Accurate geometric parameter information for cone-beam CT (CBCT) systems is crucial for high-quality image reconstruction. To validate the performance of the algorithms for geometric parameter extraction and projection matrix computation, this paper presents test calibration methods based on a computer simulation. We simulate the projection operation on a calibration phantom using Visual C++ and obtain the center of projection images through an approach based on least squares and genetic algorithm using Matlab programs. To verify the performance of the presented geometric calibration algorithm for projection matrix computation and geometric parameter extraction, CBCT consisting of a flat-panel detector is simulated and the un-calibration reconstructed image is compared with the reconstructed images of the calibration method in this paper. The extracted geometric parameters from the calculated projection matrix are very close to the input values. Compared with the uncorrected reconstructed image, the corrected reconstructed image significantly reduces many artifacts. Experimental results reveal that the presented method is robust and accurate, and can suppress undesirable artifacts of reconstructed images which caused by misaligned scanner geometry.
The impact of credit counseling on subsequent borrower credit usage and payment behavior

Consumer Finance in 1969. During its 3-year existence the Commission coordinated a massive research program to study the operation of consumer credit markets in the United States. Delivered to Congress in 1972, the Commission's multi-volume report established the value of academic research for guiding public policy towards markets for financial services. With a combination of foundation and corporate grants, Dr. Johnson established the Credit Research Center at Purdue to provide an ongoing means of directing academic research expertise toward practical problems in consumer and mortgage credit markets. Over the past quarter-century the Center has gained a national reputation for its work in evaluating public policy toward credit markets. The Center's operations have been sustained by generous grants from both the public and private sectors. Over one hundred articles and monographs by distinguished scholars document its research product. The Center's senior research staff have frequently testified before Congress and state legislatures on such topics as Truth-in-Lending disclosures, the impact of interest rate ceilings on credit availability, equal credit opportunity regulations, personal bankruptcy, credit insurance, credit scoring, credit card usage, and the impact of privacy regulations. The value of these contributions to rational discourse stems from CRC's academic affiliation, rigorous external review of its research, and the years of research experience of its principal researchers and authors. In July of 1997 the Center relocated its offices to Georgetown University in Washington, D.C. The Center is a non-profit unit of the McDonough School of Business where it continues its tradition of non-partisan research and education on economic issues relating to consumer credit and markets for retail financial services. For more information about the Center and its publications visit its website at www.msb. edu/prog/crc. ACKNOWLEDGMENTS We are deeply grateful to Trans Union, LLC, for providing the credit report data at the core of this empirical study. We also thank the members of the Creditor Relations Committee of the National Foundation for Credit Counseling, especially Chairman Bob Runke, who provided the inspiration and creative direction to launch the project. Special thanks also go to Cecelia Diehl and all the NFCC national staff who have provided guidance and comments throughout the project. Stephanie Wilshusen at the Credit Research Center provided expert statistical support in the construction of the empirical models. Credit Research Center Advisory Council members provided many helpful comments that improved the analysis. Last, but certainly not least, we thank the five participating agencies for sharing …
Bioluminescence-Inspired Human-Robot Interaction : Designing Expressive Lights that Affect Human’s Willingness to Interact with a Robot

Bioluminescence is the production and emission of light by a living organism. It, as a means of communication, is of importance for the survival of various creatures. Inspired by bioluminescent light behaviors, we explore the design of expressive lights and evaluate the effect of such expressions on a human’s perception of and attitude toward an appearance-constrained robot. Such robots are in urgent need of finding effective ways to present themselves and communicate their intentions due to a lack of social expressivity. We particularly focus on the expression of attractiveness and hostility because a robot would need to be able to attract or keep away human users in practical human-robot interaction (HRI) scenarios. In this work, we installed an LED lighting system on a Roomba robot and conducted a series of two experiments. We first worked through a structured approach to determine the best light expression designs for the robot to show attractiveness and hostility. This resulted in four recommended light expressions. Further, we performed a verification study to examine the effectiveness of such light expressions in a typical HRI context. On the basis of the findings, we offer design guidelines for expressive lights that HRI researchers and practitioners could readily employ.
Brain region-specific effects of cGMP-dependent kinase II knockout on AMPA receptor trafficking and animal behavior

Phosphorylation of GluA1, a subunit of AMPA receptors (AMPARs), is critical for AMPAR synaptic trafficking and control of synaptic transmission. cGMP-dependent protein kinase II (cGKII) mediates this phosphorylation, and cGKII knockout (KO) affects GluA1 phosphorylation and alters animal behavior. Notably, GluA1 phosphorylation in the KO hippocampus is increased as a functional compensation for gene deletion, while such compensation is absent in the prefrontal cortex. Thus, there are brain region-specific effects of cGKII KO on AMPAR trafficking, which could affect animal behavior. Here, we show that GluA1 phosphorylation levels differ in various brain regions, and specific behaviors are altered according to region-specific changes in GluA1 phosphorylation. Moreover, we identified distinct regulations of phosphatases in different brain regions, leading to regional heterogeneity of GluA1 phosphorylation in the KO brain. Our work demonstrates region-specific changes in GluA1 phosphorylation in cGKII KO mice and corresponding effects on cognitive performance. We also reveal distinct regulation of phosphatases in different brain region in which region-specific effects of kinase gene KO arise and can selectively alter animal behavior.
Two dimensional autoregressive modeling-based interpolation algorithms for image super-resolution: A comparison study

Image interpolation is a key technique of image super-resolution. Four two dimensional (2-D) autoregressive (AR) modeling-based image interpolation algorithms have been reported to have better performance in edge and texture preservation than conventional image polynomial interpolation algorithms. However, there is lack of performance comparison among them. For super-resolution reconstruction quality, this paper is going to fill up the gap by a comparison study on the four 2-D AR modeling-based interpolation methods: novel edge-directed interpolation (NEDI), soft-decision adaptive interpolation (SAI), sparse representation interpolation with nonlocal autoregressive modeling (SR-NARM), and adaptive super-pixel-guided AR modeling (ASARM). Furthermore, the four interpolation algorithms are compared in the light of peak signal to noise ratio, feature similarity index, mean squared error and structural similarity index. From comparative results we observe that ASARM method has relatively better performance than other three methods but is more time-consuming than the NEDI and SAI methods.
Single Classifier-Based Passive System for Source Printer Classification Using Local Texture Features

An important aspect of examining printed documents for potential forgeries and copyright infringement is the identification of the source printer as it can be helpful for detecting forged documents and ascertaining the leak. This paper proposes a system for classification of source printer from scanned images of printed documents using all the printed letters simultaneously. The proposed system uses local texture patterns-based features and a single classifier for classifying all the printed letters. Letters are extracted from scanned images using connected component analysis followed by morphological filtering without the need of using an optical character recognition. Each letter is sub-divided into a flat region and an edge region, and local tetra patterns are estimated separately for these two regions. A strategically constructed pooling technique is used to extract the final feature vectors. The proposed method has been tested on both a publicly available data set of ten printers, and a new data set of 18 printers scanned at a resolution of 600 as well as 300 dpi printed in four different fonts. The results indicate that the proposed system is capable of simultaneously dealing with all the printed letters and using a single classifier outperforms existing handcrafted feature-based methods. To achieve accuracies similar to that of state-of-art methods, it needs a much smaller number of training pages by using all the printed letters.
Saying ‘Hi!’ is not enough: Mining inputs for effective test generation

Automatically generating unit tests is a powerful approach to exercise complex software. Unfortunately, current techniques often fail to provide relevant input values, such as strings that bypass domain-specific sanity checks. As a result, state-of-the-art techniques are effective for generic classes, such as collections, but less successful for domain-specific software. This paper presents TestMiner, the first technique for mining a corpus of existing tests for input values to be used by test generators for effectively testing software not in the corpus. The main idea is to extract literals from thousands of tests and to adapt information retrieval techniques to find values suitable for a particular domain. Evaluating the approach with 40 Java classes from 18 different projects shows that TestMiner improves test coverage by 21% over an existing test generator. The approach can be integrated into various test generators in a straightforward way, increasing their effectiveness on previously difficult-to-test classes.