Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Role of Regulatory Standards: Specification and Some Empirical Evidence from Motor Vehicle Fuel Economy

This paper proposes a simple model to evaluate the role of regulatory controls. It is formulated so as to enable drawing empirical conclusions on the basis of usual hypothesis tests. Three potential roles of standards are examined they can act as penalties for non-compliant firms, as norms to which all firms converge, and as controls with cumulative impact over time. I test this specification focusing on automobile fuel economy (CAFE) standards that have been imposed in the US since 1978, using annual data from each major auto manufacturer. Results show that CAFE rules, functioning mainly as penalties, have been an important determinant of car fuel consumption. The hypothesis that standards acted also as norms is rejected. Finally, the automobile industry as a whole became less constrained by regulations over the years because of stagnating CAFE standards since 1990 and progress in vehicle technology.
The Bottlenecks in Biological Networks

A well-established goal in the biological networks is to investigate relations between the topological features and the functional properties of systems biology. Nodes with high betweenness centrality, as bottlenecks, have surprising functional and dynamic properties in biological networks. Bottlenecks, that have many shortest paths passing through them, are connector hubs for many inter-modular connections to nodes of different modules. Thus, detection of bottleneck nodes in the networks will be of great interest. In this paper, we propose a new approach to efficiently identify the bottlenecks in the biological networks, using compressive sensing with indirect measurements. This method uses only the local information at each node, thus it is applicable to large real-world and unknown networks in which the global methods are often impossible. We experimentally evaluated the performance of the proposed method by extensive simulations on several biological networks. The evaluation results show that our algorithm outperforms the best existing methods with notable improvements in terms of F-Measure.
Black Garlic Supplementation's Effect on Exercise-Induced Increase of Oxidative Stress

This study investigated the effects of black garlic (BG) supplementation on exercise-induced increase of oxidative stress (EIOS) and recovery of muscle function. 20 healthy males were assigned to either a BG group (n=11, GG) or placebo group (n=9, PG), during a 14-day-study. Before and after eccentric exercise of elbow flexors, we measured muscle function, blood and urinary biochemistries. Maximal voluntary contraction strength decreased by 35% immediately post exercise in both groups. Recovery of circumference of biceps brachii in GG was significantly faster than in PG during 3-7 days post-exercise. reactive oxygen metabolites (d-ROMs) level was lower in GG than in PG during 1-3 days post-exercise, but no significant difference in anti oxidative potential (BAP) was observed between groups. Exercise induced leukocytosis and monocytes, lymphocytes and neutrophils all exhibited significant time effects. A significantly greater creatine kinase level was found on day 3 post-exercise in PG than in GG. Lipid peroxide concentration was lower during 3-7 days post exercise in GG than in PG and the 8-iso-prostaglandin F2α level was significantly greater in PG than in GG at every post-exercise point. These results suggest that BG supplementation had certain effects on suppression of EIOS and might promote the recovery of edema in injured tissue.
Comparison of Single Classifier Models for Predicting Long-term Business Failure of Construction Companies Using Finance-based Definition of the Failure

This study compares the performance of six classifier models (ANN, KNN, C4.5, SVM, LR, and NB) for predicting the business failure of construction companies after three years from 2010 to 2012. Although previous studies have explored numerous business failure prediction models for construction companies, these models have focused on short-term failure, defined as failure occurring within one year, and have defined business failure based on companies’ experiencing serious legal events, including bankruptcy, delisting, and default. However, the construction industry is typically characterized by projects with longer durations, usually exceeding one year. This implies that previous short-term models cannot predict the business failure of construction companies until the end of particular projects. Moreover, this problem is compounded by the fact that legal events can involve lengthy proceedings, which are often initiated much later than the actual moment of the business failure. Therefore, in this study, six classifier models will be used to predict the business failure of the construction companies within three years using a finance-based definition of failure. The results show that all six models’ performances noticeably decrease when they predict more than one year. These results demonstrate that previous short-term prediction models with outstanding performance cannot be practical in predicting the long-term business failure of construction companies.
Deciphering the origin of nonlocal resistance in multiterminal graphene on hexagonal-boron-nitride with ab initio quantum transport: Fermi surface edge currents rather than Fermi sea topological valley currents

The recent observation (Gorbachev et al 2014 Science 346 448) of nonlocal resistance RNL near the Dirac point (DP) of multiterminal graphene on aligned hexagonal-boron nitride (G/hBN) has been interpreted as the consequence of topological valley Hall currents carried by the Fermi sea states just beneath the bulk gap Eg induced by inversion symmetry breaking. However, the corresponding valley Hall conductivity σ xy v , quantized inside Eg, is not directly measurable. Conversely, the Landauer–Büttiker formula, as a numerically exact approach to observable nonlocal transport quantities, yields RNL ≡ 0 for the same simplistic Hamiltonian of gapped graphene that generates σ xy v ≠ 0 via the Kubo formula. We combine ab initio with quantum transport calculations to demonstrate that G/hBN wires with zigzag edges host dispersive edge states near the DP that are absent in theories based on the simplistic Hamiltonian. Although such edge states exist also in isolated zigzag graphene wires, aligned hBN is required to modify their energy–momentum dispersion and generate R NL ≠ 0 near the DP. The Fermi surface-determined edge currents carrying the nonlocal signal persist also in the presence of edge disorder and over long distances. Concurrently, they resolve the long-standing puzzle of why the highly insulating state of G/hBN is rarely observed. Thus, we conclude that the observed RNL is unrelated to Fermi sea topological valley currents conjectured for gapped Dirac spectra.
Microsatellite fingerprinting of grapevine ( Vitis vinifera L.) varieties of the Carpathian Basin

Altogether 101 Vitis vinifera L. genotypes were analysed at 6 microsatellite loci (Scu8vv, Scu10vv, VVMD21, VVMD36, ssrVRZAG64, ssrVRZAG79). Ninety-seven were autochthonous accessions of the Carpathian Basin and 4 were international cultivars. The allele composition and sizes obtained with the 6 microsatellite primer pairs were appropriate for discrimination of 95 cultivars. Berry colour-variants of cvs Goher (Goher feher-white and Goher piros-red), Lisztes (Lisztes feher and Lisztes piros) as well as the cvs Bakator (Bakator piros and Bakator tudőszin - light red) were exceptions.
Empirically Informed Sound Synthesis Application for Enhancing the Perception of Expressive Robotic Movement

Since people often communicate internal states and intentions through movement, robots can better interact with humans if they too can modify their movements to communicate changing state. These movements, which may be seen as supplementary to those required for workspace tasks, may be termed “expressive. ” However, robot hardware, which cannot recreate the same range of dynamics as human limbs, often limit expressive capacity. One so-lution is to augment expressive robotic movement with expressive sound. To that end, this paper presents an application for synthesizing sounds that match various movement qualities. Its design is based on an empirical study analyzing sound and movement qualities, where movement qualities are parametrized according to La-ban’s Effort System. Our results suggests a number of correspondences between movement qualities and sound qualities. These correspondences are presented here and discussed within the context of designing movement-quality-to-sound-quality mappings in our sound synthesis application. This application will be used in future work testing user perceptions of expressive movements with synchronous sounds.
Bump formations in attractor neural network and their application in image reconstruction

In this paper we analyze the bump formations in binary attractor neural networks with distance dependent connectivity. We show that by introducing a two stage learning procedure an increase of the critical storage capacity of the network is observed. The procedure has been tested on a network with N = 64K neurons by using a selection of 3700 natural images. Our analysis shows that the bumps can be regarded as intrinsic characteristics of the image and the topology of the network and they can be used to improve the performance of the network by increasing its capacity.
Lead and Nickel Accumulation in Brassica juncea arawali Growing in Contaminated Soil

Brassica juncea arawali plants were exposed to 0, 100, 200, 400 and 800 mg/l concentrations of Lead (Pb) and Nickel (Ni). Plants were treated with control, ethylene diamine tetraacetic acid (EDTA) and salicylic acid (SA) chelant applications at Micromodel experimental site of Indian Institute of Technology, Delhi in 2009. A high level of combined metal concentrations (1600 mg/l) was taken to assess the feasibility of phytoextraction on a high-level metal contaminated soil. Plants were analyzed for growth parameters, biochemical parameters and metal accumulation. EDTA decreased all morphological parameters whereas SA stimulated them. All biochemical parameters showed declination with increasing Pb and Ni concentrations. A higher accumulation of chlorophyll, soluble sugars, soluble proteins and proline occurred in Indian mustard plants treated with SA. Pb and Ni accumulation in plants increased in a dose-response manner with increasing levels of metal treatments and time. EDTA was found to be more efficient chelant than SA for removal of Pb and Ni from contaminated soil.
2.2.5. Kognition und Sprache

Kognitive Leistungen, im Alltag oft als „Denken“ bezeichnet, und Sprache sind zwei dem Menschen typische Fähigkeiten und eng mit Begriffen wie Intelligenz, Kommunikation und Kultur verbunden. Sie ermöglichen dem Menschen die systematische Wissensaneignung und -erweiterung beispielsweise durch Lernprozesse und schlussfolgerndes Denken oder Problemlösen sowie die Möglichkeit, diese Erkenntnisse zu vermitteln und an die nächste Generation weiterzugeben. Da in vorhergehenden und folgenden Kapiteln bereits Teile der Kognition beschrieben werden, wird dieses Kapitel gezielt auf eine kleine Zahl bestimmter kognitiver Leistungen fokussiert. Zudem wird vor allem beim Thema Sprache ein Zuschnitt von Themen vorgenommen, die für Medizinstudierende relevant sind, indem v.a. der Spracherwerb sowie die Störungen der Sprache nach Hirnschädigungen in den Vordergrund gestellt werden.
Adaptive Clipping for a Deterministic Peak-To-Average Power Ratio

Orthogonal Frequency Division Multiplexing (OFDM) is the most commonly used multicarriers modulation in telecommunication systems due to the efficient use of frequency resources and its robustness to multipath fading channel. However, as multicarriers modulation in general, OFDM suffers from high Peak-to-Average Power Ratio (PAPR). Many works exist in literature for PAPR mitigation among which Clipping is one of the most efficient adding signal techniques in terms of numerical complexity. However, clipping techniques is a probabilistic technique for PAPR mitigation. In other words, the instantaneous PAPR of each clipped OFDM symbol depends on its content and then the PAPR at any value of the Complementary Cumulative Distribution Function (CCDF) increases when its corresponding CCDF values decreases. In this paper, we propose an adaptive clipping which offers a constant PAPR, so deterministic, at any value of the CCDF and so this approach outperforms the classical clipping in terms of signal degradation with the same performance in terms of PAPR reduction. Simulation results validate the interest of this approach.
Multimodality treatment in limited small cell lung cancer (L-SCLC): different perspectives about the optimal approach

Small cell lung cancer (SCLC) is characterized by an aggressive behaviour, but limited-stage disease could be treated with curative intent. In order to improve prognosis in terms of local control and survival in this setting, several studies evaluated the benefit of a multimodality strategy including surgery, chemotherapy and radiotherapy. Recently Yang et al . confirmed the benefit of adjuvant chemotherapy alone or with cranial irradiation in a population-based cohort of patients with early-stage SCLC who underwent complete surgical resection. Results of this study are consistent with previous retrospective analysis or small prospective trials without adding anything to the current knowledge and clinical practice. In this perspective, we discuss the role and evidence supporting different locoregional approaches, in a two-hand debate, underlining the importance of a prospective randomized trial defining the best treatment strategy in limited SCLC.
C-arm CT Perfusion Imaging in the Interventional Suite

Diagnostic perfusion imaging using CT or MRI has been available for several years. One of its applications is acute stroke diagnosis. Interventional perfusion imaging using C-arm CT is a novel field of research. It could provide perfusion information during catheter-guided stroke treatment in order to optimize patient management. In this survey article, the clinical and technical background of this topic are described and first results from in-vivo measurements are presented.
Accident Prediction Models for Urban and Rural Carriageways Based on Data from The Hague Region Haaglanden

This report describes accident prediction models for traffic lanes of rural and urban distributor roads in the Haaglanden region of the Netherlands. The length of the traffic lane and the amount of average daily traffic it carries both impact the number of injury accidents in a particular traffic lane. Distinctions are made between traffic lanes that are one way versus two way, and also between rural and urban traffic lanes.
Analysis of student academics performance using Hadoop

In recent years the amount of data generated in educational sector is growing rapidly. In order to gain deeper insights from the available data and extract useful knowledge to support decision making and improve the education service efficient storage management and fast processing analytics is needed. Academic data of a student helps institute to measure their progress. Students facing severe academic challenges are often recognized too late. Analytics play a critical role in performing a thorough analysis of student and learning data to make an informed decision. Big Data solution enables to analyze the wider variety of data sources and data types which improves the accuracy of predictions. Hadoop platforms provide highly scalable platforms and can store a much greater volume of data at lower cost. The purpose of the proposed Project is to help in identifying “at risk” students who are not progressing towards graduation early in order to get them back on track. The cause of lack of adequate progression can be identified and addressed. The system proposed will be helpful for educational decision-makers to reduce the failure rate among students. The implementation is done in Hadoop framework. The PAMAE algorithm is implemented for analyzing student’s academic data.
New Integrators and Differentiators Using a MMCC

Using the new building block Multiplication-Mode Current Conveyor (MMCC), some inverting/non-inverting type integrator and differentiator designs are presented, wherein the time constant (τ) is tuned electronically. The MMCC is implemented by a readily available chip-level configuration using a multiplier (ICL 8013) and a current feedback amplifier (AD-844 IC) CFA. Detailed analysis, taking into account the device non-idealities, had been carried out that indicates slight deviations affecting the values of the nominal time constant but the design is practically insensitive to the port mismatch errors (e). Satisfactory response on wave conversion, for signal frequencies up to 600 Khz had been verified with both hardware circuit test and PSPICE macromodel simulation.
AUTOMATED MOSAICKING OF GEOSTATIONARY OCEAN COLOR IMAGER BY COMBINATION OF SPATIAL AND FREQUENCY MATCHING

Abstract. In general, image mosaicking is a useful and important processing for handling images with narrow field of view. It is being used widely for images from commercial cameras as well as from aerial and satellite cameras. For mosaicking images with geometric distortion, geometric correction of each image should be performed before combining images. However, automated mosaicking images with geometric distortion is not a trivial task. The goal of this paper is the development of automated mosaicking techniques applicable to handle GOCI images. In this paper, we try to extract tie-points by using spatial domain and frequency domain matching and perform the mosaicking of GOCI. The method includes five steps. First, we classify GOCI image slots according to the existence of shorelines by spatial domain matching. Second, we perform precise geometric correction on the slots with shorelines. Third, we perform initial sensor modelling for the slots without shorelines and apply geometric correction based on the initial model. Fourth, the relative relationship between the slots without shorelines and the slots with shorelines is estimated through frequency domain matching. Lastly, mosaicking of geometrically corrected all 16 image slots is performed. The proposed method was verified by applying to real GOCI images. The proposed method was able to perform automated mosaicking even for images without shorelines, and its accuracy and processing time were satisfactory. For future research, we will improve frequency matching to generate multiple tie-points and to analyse the applicability of precise sensor modelling directly from frequency matching. It is expected that the proposed method can be applied to the follow-up sensor of the GOCI, GOCI-II, and other ocean satellite images.
Wave variance partitioning in the trough of a barred beach

The wave-induced velocity field in the nearshore is composed of contributions from incident wind waves (f > 0.05 Hz), surface infragravity waves (f 2/g), where fis the frequency,  = 2f, }c is the radial alongshore wavenumber (2re/L, L being the alongshore wavelength), [ is the beach slope, and g is the acceleration due to gravity. Using an alongshore array of current meters located in the trough of a nearshore bar (mean depth = 1.5 m), we investigate the bulk statistical behaviors of these wave bands over a wide range of incident wave conditions. The behavior of each contributing wave type is parameterized in terms of commonly measured or easily predicted variables describing the beach profile, wind waves, and current field. Over the 10-day period, the mean contributions (to the total variance) of the incident, infragravity, and shear wave bands were 71.5%, 14.3% and 13.6% for the alongshore component of flow (mean rms oscillations of 44, 20, and 19 cm s -1, respectively), and 81.9%, 10.9%, and 6.6% for the cross-shore component (mean rms oscillations of 92, 32, and 25 cm s -1, respectively). However, the values varied considerably. The contribution to the alongshore (cross-shore) component of flow ranged from 44.888. 4% (58.5-95.8%) for the incident band, to 6.2-26.6% (2.5-32.4%) for the infragravity band, and 3.433. 1% (0.6-14.3%) for the shear wave band. Incident wave oscillations were limited by depth-dependent saturation over the adjacent bar crest and varied only with the fide. The infragravity wave rms oscillations on this barred beach are best parameterized by the offshore wave height, consistent with previous studies on planar beaches. Comparison with data from four other beaches of widely differing geometries shows the shoreline infragravity amplitude to be a near-constant ratio of the offshore wave height. The magnitude of the ratio is found to be dependent on the Iribarren number, 0 = [(H/Lo) -1/2. Shear waves are, as previous observation and theory suggest (Oltman-Shay et al., 1989; Bowen and Holman, 1989), significantly correlated with a prediction of the seaward facing shear of the longshore current.
Cigarette Smoking Provoked Proinflammatory Cytokines and Oxidative Stress in Healthy Smokers

Cigarette smoking is a major risk factor in the development of various lung diseases. The mechanisms of these diseases include the inappropriate production of inflammatory cytokines and generation various reactive oxygen species (ROS) and reactive nitrogen species (RNS) that can be inactivate endogenous antioxidants mechanisms. This study aimed to evaluate the effect of cigarette smoking on proinflammatory cytokines and antioxidant enzyme activities related to oxidative stress in apparently healthy smokers. The study included 45 apparently healthy smokers divided into mild, moderate and heavy smokers according the smoking index and 40 healthy non smoker males served as control group Inflammatory markers, interleukin-6 (IL-6), tissue necrosis factor-α (TNF-α), antioxidant enzymes, superoxide dismutase (SOD), catalase (CAT), glutathione (GSH) as well as total homocysteine (tHcy), malondialdehyde (MDA), protein carbonyl content (PCC), were measured in plasma of all participants. The results revealed significant difference between smokers as compared with nonsmokers in levels of tHcy, MDA, PCC, IL-6, TNF-α, Vit C, GSH, CAT and SOD and significant difference among mild, moderate and heavy smokers. These findings insist that smoking leads to increase free radical load and relatively low antioxidant status which results in an imbalance between oxidant/antioxidant status, reinforcing recommendations concerning the benefits of smoking cessation.
Mitochondrial respiratory chain deficiency in older men and its relationship with muscle mass and performance

Sarcopenia is the loss of muscle mass and physical performance with age, and recognition of its importance in clinical practice is growing. Age‐related decline in muscle mitochondrial function has been described although less is known about the role of mitochondrial dysfunction in sarcopenia. The aim of this study was to investigate whether respiratory chain deficiency is associated with muscle mass and physical performance among a sample of healthy older men participating in the Hertfordshire Sarcopenia Study.
Pulping Catalysts From Lignin (5). Nitrogen Dioxide Oxidation Of Lignin Models To Benzoquinones

ABSTRACT Several syringyl lignin models have been oxidized to 2,6-dimethoxy- p-benzoquinone (DMBQ) in high yields with nitrogen dioxide (NO2) in methanol solvent. The yields of DMBQ were high for syringyl alcohol, syringaldehyde, and disyringyl methane and moderate for several other phenolic syringyl models. Benzoquinones were not formed from non phenolic substrates. The yields were slightly improved by the presence of N- hydroxysuccinimide. Guaiacyl lignin model compounds gave low benzo-quinone yields; the major products were C-5 nitro substituted compounds. A radical mechanism is proposed to explain the observed results.