Miracle-dz/UniFAR-FTUs huggingface dataset:
Hemispheric specialization for English and ASL: left invariance‐right variability

FUNCTIONAL magnetic resonance imaging (fMRI) was used to compare the cerebral organization during sentence processing in English and in American sign language (ASL). Classical language areas within the left hemisphere were recruited by both English in native speakers and ASL in native signers. This suggests a bias of the left hemisphere to process natural languages independently of the modality through which language is perceived. Furthermore, in contrast to English, ASL strongly recruited right hemisphere structures. This was true irrespective of whether the native signers were deaf or hearing. Thus, the specific processing requirements of the language also in part determine the organization of the language systems of the brain.
Two-Relay-Based Cooperative MAC Protocol for Wireless Ad hoc Networks

The cooperative communication approach promises improved throughput and delay performance by effective use of spatial diversity in wireless ad hoc networks. The CoopMAC I protocol proposed by Liu picks either a direct path or a relay path based on rate comparison to enhance average throughput and delay performances. However, its performance deteriorates under fading conditions due to lower direct path or relay path reliability. UtdMAC, which was proposed by Agarwal , performs better than CoopMAC I in terms of average throughput and delay performances due to improved transmission reliability provided by the backup relay path. Although it is better than CoopMAC I, UtdMAC does not fully benefit from higher throughput relay path (compared with the direct path) since it uses relay path only as a secondary backup path. In this paper, a new cooperative medium access control (MAC) protocol, which is termed the 2rcMAC protocol, is proposed for a small-sized network. The protocol makes use of two cooperating nodes to achieve superior throughput and delay performances, compared with the existing cooperative MAC protocols. The secondary relay path is invoked as a backup path for better transmission reliability and higher throughput through the relay path. Moreover, handshaking and single-bit feedbacks resolve contentions among relay nodes in proximity at the time and further provide the source node with rate information on source-to-destination, source-to-relay, and relay-to-destination links. Performance gains achieved by the 2rcMAC protocol under fast-fading conditions over the existing cooperative MAC protocols are compared and discussed. Simulation results clearly show an average throughput improvement of 7% and 25% and an average delay improvement of 94.8% and 98.9%, compared with UtdMAC and CoopMAC I, respectively.
Influenza A H5N1 Replication Sites in Humans

Tissue tropism and pathogenesis of influenza A virus subtype H5N1 disease in humans is not well defined. In mammalian experimental models, H5N1 influenza is a disseminated disease. However, limited previous data from human autopsies have not shown evidence of virus dissemination beyond the lung. We investigated a patient with fatal H5N1 influenza. Viral RNA was detected by reverse transcription–polymerase chain reaction in lung, intestine, and spleen tissues, but positive-stranded viral RNA indicating virus replication was confined to the lung and intestine. Viral antigen was detected in pneumocytes by immunohistochemical tests. Tumor necrosis factor-α mRNA was seen in lung tissue. In contrast to disseminated infection documented in other mammals and birds, H5N1 viral replication in humans may be restricted to the lung and intestine, and the major site of H5N1 viral replication in the lung is the pneumocyte.
THE ECONOMICS OF A BITING MINIMUM WAGE

Conventional wisdom as regards the effects of a biting Minimum Wage (MW) is challenged in this paper through the findings of a System Dynamics model. Given a number of different plausible assumptions, a number of counter intuitive results are found to emerge such as a longer term permanent increase in employment levels, a greater total number of businesses in the economy associated with lower total employment levels than originally, and a trade-off in the well being and the employment levels between those firms whose cost structure was affected by the MW and the unaffected firms. Finally, two variables that are normally considered to be irrelevant to the investigation of the economic effects of a biting MW, namely consumption spending and fixed costs per business, come to the forefront of the analysis.
On 3D DDFV Discretization of Gradient and Divergence Operators: Discrete Functional Analysis Tools and Applications to Degenerate Parabolic Problems

Abstract. We present a detailed survey of discrete functional analysis tools (consistency results, Poincaré and Sobolev embedding inequalities, discrete W1,p compactness, discrete compactness in space and in time) for the so-called Discrete Duality Finite Volume (DDFV) schemes in three space dimensions. We concentrate mainly on the 3D CeVe-DDFV scheme presented in [IMA J. Numer. Anal. , 32 (2012), pp. 1574–1603]. Some of our results are new, such as a general time-compactness result based upon the idea of Kruzhkov (1969); others generalize the ideas known for the 2D DDFV schemes or for traditional two-point-flux finite volume schemes. We illustrate the use of these tools by studying convergence of discretizations of nonlinear elliptic-parabolic problems of Leray–Lions kind, and provide numerical results for this example.
Variability of Active Galactic Nuclei

Continuum and emission-line variability of active galactic nuclei provides a powerful probe of microarcsecond scale structures in the central regions of these sources. In this contribution, we review basic concepts and methodologies used in analyzing AGN variability. We develop from first principles the basics of reverberation mapping, and pay special attention to emission-line transfer functions. We discuss application of cross-correlation analysis to AGN light curves. Finally, we provide a short review of recent important results in the field.
Calcium-Mediated Induction of Paradoxical Growth following Caspofungin Treatment Is Associated with Calcineurin Activation and Phosphorylation in Aspergillus fumigatus

ABSTRACT The echinocandin antifungal drug caspofungin at high concentrations reverses the growth inhibition of Aspergillus fumigatus, a phenomenon known as the “paradoxical effect,” which is not consistently observed with other echinocandins (micafungin and anidulafungin). Previous studies of A. fumigatus revealed the loss of the paradoxical effect following pharmacological or genetic inhibition of calcineurin, yet the underlying mechanism is poorly understood. Here, we utilized a codon-optimized bioluminescent Ca2+ reporter aequorin expression system in A. fumigatus and showed that caspofungin elicits a transient increase in cytosolic free Ca2+ ([Ca2+]c) in the fungus that acts as the initial trigger of the paradoxical effect by activating calmodulin-calcineurin signaling. While the increase in [Ca2+]c was also observed upon treatment with micafungin, another echinocandin without the paradoxical effect, a higher [Ca2+]c increase was noted with the paradoxical-growth concentration of caspofungin. Treatments with a Ca2+-selective chelator, BAPTA [1,2-bis(o-aminophenoxy)ethane-N,N,N′,N′-tetraacetic acid], or the L-type Ca2+ channel blocker verapamil abolished caspofungin-mediated paradoxical growth in both the wild-type and the echinocandin-resistant (EMFR-S678P) strains. Concomitant with increased [Ca2+]c levels at higher concentrations of caspofungin, calmodulin and calcineurin gene expression was enhanced. Phosphoproteomic analysis revealed that calcineurin is activated through phosphorylation at its serine-proline-rich region (SPRR), a domain previously shown to be essential for regulation of hyphal growth, only at a paradoxical-growth concentration of caspofungin. Our results indicate that as opposed to micafungin, the increased [Ca2+]c at high concentrations of caspofungin activates calmodulin-calcineurin signaling at both a transcriptional and a posttranslational level and ultimately leads to paradoxical fungal growth.
When the Mind “Flies”: the Effects of Mind-Wandering on Driving

Mind wandering (MW) refers to a shift of attention away from a primary task toward internal information, such as memories, future thoughts, or fantasies. Several lines of research showed that MW has a costly influence on many cognitive processes, such as reading comprehension, sustained attention and working memory. The aim of the present study was to assess whether MW impairs, like secondary-task distraction, driver’s performance. Results showed that MW is indeed pervasive during daily driving, as indicated by the participants’ answers to an ad-hoc questionnaire assessing the source of inattentiveness during daily driving; furthermore, MW states detected during simulated driving were found to affect driving performance.
Classification of cells in detrusor smooth muscle syncytium based on analysis of spontaneous electrical activities

The wide variety of action potential shapes observed in the spontaneous electrical activities of the the urinary bladder smooth muscle tissue (detrusor) is difficult to comprehend. the Experimental exploration of the same is near impossible because of the small size of the smooth muscle cells and the heterogeneous syncytial arrangement of interconnected smooth muscle cells and their complex innervation. In this paper, an approach to uncover the biophysical environment of a smooth muscle cell based on the analysis of the intracellularly recorded spontaneous electrical activities is presented. From the recordings taken from 20 smooth muscle cells, templates were formed which represent the types of shapes seen in the spontaneous activity of the detrusor. The signals expressed by the individual muscle cells are then classified into different groups represented by the above templates. The statistics of the signals in each group, expressed by the cells are then used to classify the cells types. Four categories of cells are thus identified in this study. It is expected that the cells belonging to a single category have identical biophysical environments. Based on the types of shapes and their frequencies expressed by the cells belonging to each of the categories, some properties of the biophysical environment could be inferred.
A Monocular Video-Based Facial Expression Recognition System by Combining Static and Dynamic Knowledge

In this paper, a real-time monocular video-based facial expression recognition system is proposed. An adaptively weighted online statistical appearance model is first constructed to retrieve the continuous facial motion information from each frame of input video. The static and dynamic knowledge of facial expression are obtained by facial expression anatomy and manifold learning respectively, and then fused for recognition in framework of particle filtering. The experimental results confirm the advantage of the system, even in the presence of significant head pose and occlusions.
Cloud provider selection models for cloud storage services to meet availability requirements

Cost-effective cloud storage services attract users with their convenience; there is a trade-off between the service availability and the usage cost. We develop two cloud provider selection models for cloud storage services to minimize the total cost of usage. The models select multiple cloud providers with considering unavailability to meet the user requirements. The first model, called a user-copy (UC) model, allows to select multiple cloud providers, where a user itself makes copies of its data for multiple providers. In addition to the user copy function of the UC model, the second model, which is called a user and cloud-provider copy (UCC) model, allows cloud providers to make copies of the data to deliver them to other cloud providers. The cloud service is available if at least one cloud provider is available. We formulate both models as integer linear programming (ILP) problems. Our performance evaluation observes that both models reduce the total cost of usage, compared to the single cloud provider selection. As the cost of bandwidth usage between a user and a cloud provider increases, the UCC model becomes more beneficial than the UC model. We implement the prototype for cloud storage services.
A Novel Approach to Drastic Test Data Compression for Multiple Scan Designs

This paper presents a comprehensive test data compression scheme based on adjustable width decompression and X-compact techniques for multiple scan designs. Adjustable width scan chain is employed for test stimuli decompression, and test response takes the advantages of X-compact. A response shaper further minimizes the probability of fault masking. The enhanced broadcast-scan based mode for CUT is able to deal with FFs (flip-fops) with the identical values as well as the opposing values. Two modes can handle the rest compact FF values after filling the unknown values. The merits of proposed approach are as follows. Test storage requirement is reduced significantly, and test input/output pins, test channels coupled with test application time decrease, thus improving test compression ratio completely. The experimental results on benchmark circuits ISCAS'89 demonstrate the improvement upon the previous proposed algorithms.
Fiscal Policy and Regional Output Volatility: Evidence from Russia

Eller M. , Fidrmuc J. and Fungácˇ ová Z. Fiscal policy and regional output volatility: evidence from Russia, Regional Studies. This paper investigates the relationship between fiscal policy and output volatility in Russian regions between 2000 and 2009. Accounting for endogeneity between output volatility and fiscal developments by using system-generalized method of moments (GMM) estimation techniques, the results indicate that discretionary fiscal policy contributes to output volatility and induces macroeconomic instability at the regional level in Russia. This corroborates previous studies using cross-country data. To reduce business cycle fluctuations, it would be necessary to curtail procyclical fiscal activism at the regional level, e.g. via fiscal rules and sound institutions of fiscal federalism.
Artificial Neural Network Applications in Transportation Infrastructure Asset Management

SYNOPSIS Transportation officials are faced every day with competing investment demands, and they must distribute limited resources so that the transportation infrastructure is maintained in the best possible condition. Thus, they have resorted to the use of asset management tools to support their decisions. Since transportation infrastructure management decisions are often based on data that is uncertain, ambiguous, and incomplete, soft computing techniques, such as neural networks, are gaining widespread applications. This paper reviews the application of artificial neural networks in transportation infrastructure asset management, highlighting their advantages over traditional approaches. Artificial neural networks imitate, to a small extent, some of the operations perceived in biological neurons: they can be trained to assess an observed function when its shape is unknown. The main advantages of neural networks are their learning capabilities and their distributed architecture that allows for highly parallel implementation. These computational algorithms have excellent pattern recognition capabilities, can make generalizations, and are particularly appropriate in those cases in which there is a significant amount of examples available. Within the transportation asset management field, artificial neural networks have been used successfully for condition assessment, deterioration modeling, performance prediction, project and treatment selection, and prioritization. As an example, two practical applications are presented in the paper. The first application describes the development of a neural network-based project screening procedure developed for a state highway agency in the U.S. The second application describes a pavement friction prediction model developed for an Italian motorway. The review conducted suggests that artificial neural networks hold great promise for supporting infrastructure management decisions, especially in the areas of modeling deterioration, performance prediction and project selection.
Effects of Texture, Illumination, and Surface Reflectance on Stereoscopic Shape Perception

Observers viewed computer-generated stereograms of randomly structured smooth surfaces and were required to judge the perceived local orientation at numerous probe points by adjusting a monocular gauge figure. The surfaces were depicted with specular or Lambertian reflectance functions, either with or without identifiable texture elements, and with varying directions of illumination. The results revealed a strong linear correlation between the judged patterns of relief and the actual depicted objects, though there were systematic differences in the magnitude of depth scaling in the different conditions. In general, the accuracy and reliability of observers' judgments for the smoothly shaded shiny surfaces was slightly lower than for the textured surfaces and slightly higher than for the smoothly shaded Lambertian surfaces. The direction of illumination had no detectable effect on the observers' judgments.
Drivers of forests and tree-based systems for food security and nutrition

With the establishment of the Global Forest Expert Panels (GFEP) initiative in the year 2007, the Collaborative Partnership on Forests (CPF) created an international mechanism which effectively links scientific knowledge with political decision-making on forests. The GFEP responds directly to key forest-related policy questions by consolidating available scientific knowledge and expertise on these questions at a global level. It provides decision-makers with the most relevant, objective and accurate information, and thus makes an essential contribution to international forest governance. This report entitled “Forests, Trees and Landscapes for Food Security and Nutrition” presents the results of the fourth global scientific assessment undertaken so far in the framework of GFEP. Previous assessments addressed the adaptation of forests and people to climate change; international forest governance; and the relationship between biodiversity, carbon, forests and people. All assessment reports were prepared by internationally recognised scientists from a variety of biophysical and social science disciplines. They have all been presented to decision-makers across relevant international policy fora. In this way, GFEP supports a more coherent policy dialogue about the role of forests in addressing broader environmental, social and economic challenges. The current report reflects the importance of policy coherence and integration more than any previous GFEP assessment. It comes at a time when the United Nations General Assembly seeks to adopt a set of Sustainable Development Goals (SDGs) which build upon the Millennium Development Goals (MDGs) and converge with the post-2015 development agenda. In this context, the eradication of hunger, realisation of food security and the improvement of nutrition are of particular relevance. By 2050, the international community will face the challenge of providing 9 billion people with food, shelter and energy. Despite impressive productivity increases, there is growing evidence that conventional agricultural strategies will fall short of eliminating global hunger and malnutrition. The assessment report in hand provides comprehensive scientific evidence on how forests, trees and landscapes can be – and must be - an integral part of the solution to this global problem. In other words, we must connect the dots and see the bigger picture. The review of the International Arrangement on Forests by the member states of the United Nations Forum on Forests provides a unique opportunity to integrate forests into the SDGs in a holistic manner and to promote synergies in the implementation of the post-2015 development agenda across multiple levels of governance. It is my hope that those with a responsibility for forests, food security and nutrition at all levels will find this report, and its accompanying policy brief, a useful source of information and inspiration.
Adult Lysophosphatidic Acid Receptor 1-Deficient Rats with Hyperoxia-Induced Neonatal Chronic Lung Disease Are Protected against Lipopolysaccharide-Induced Acute Lung Injury

Aim: Survivors of neonatal chronic lung disease or bronchopulmonary dysplasia (BPD) suffer from compromised lung function and are at high risk for developing lung injury by multiple insults later in life. Because neonatal lysophosphatidic acid receptor-1 (LPAR1)-deficient rats are protected against hyperoxia-induced lung injury, we hypothesize that LPAR1-deficiency may protect adult survivors of BPD from a second hit response against lipopolysaccharides (LPS)-induced lung injury. Methods: Directly after birth, Wistar control and LPAR1-deficient rat pups were exposed to hyperoxia (90%) for 8 days followed by recovery in room air. After 7 weeks, male rats received either LPS (2 mg kg−1) or 0.9% NaCl by intraperitoneal injection. Alveolar development and lung inflammation were investigated by morphometric analysis, IL-6 production, and mRNA expression of cytokines, chemokines, coagulation factors, and an indicator of oxidative stress. Results: LPAR1-deficient and control rats developed hyperoxia-induced neonatal emphysema, which persisted into adulthood, as demonstrated by alveolar enlargement and decreased vessel density. LPAR1-deficiency protected against LPS-induced lung injury. Adult controls with BPD exhibited an exacerbated response toward LPS with an increased expression of pro-inflammatory mRNAs, whereas LPAR1-deficient rats with BPD were less sensitive to this “second hit” with a decreased pulmonary influx of macrophages and neutrophils, interleukin-6 (IL-6) production, and mRNA expression of IL-6, monocyte chemoattractant protein-1, cytokine-induced neutrophil chemoattractant 1, plasminogen activator inhibitor-1, and tissue factor. Conclusion: LPAR1-deficient rats have increased hyperoxia-induced BPD survival rates and, despite the presence of neonatal emphysema, are less sensitive to an aggravated “second hit” than Wistar controls with BPD. Intervening in LPA-LPAR1-dependent signaling may not only have therapeutic potential for neonatal chronic lung disease, but may also protect adult survivors of BPD from sequelae later in life.
Evaluation of IP Geolocation Algorithms on PingER and Planet-Lab Infrastructures

Geolocation is a leading Internet trend due to its significance in the commercial and services realm. So far, the network infrastructural dependency of IP geolocation has restricted its use to North America and Europe. However, the real potential of geolocation is in being a global rather than just a regional application. Since the last decade world-wide Internet usage and performance have increased exponentially. This directly urges the need to re-evaluate the performance of geolocation in more of the world. In this paper we first analyze various parameters in different regions. These are parameters that we believe affect geolocation performance and include: average distance and delay between landmarks and target, density of landmarks around a target, correlation between delay and distance around a target and the stability of proportionality between round trip times (RTT) and distance (referred to as alpha, α) around the target. We then test the performance of several well known geolocation techniques in different regions. These techniques include: Shortest Ping, TULIP, Constraint Based Geolocation with Speed of Internet, Constraint Based Geolocation and Topology Based Geolocation. We then quantify the estimates of each technique in relation to the values of the aforementioned parameters. Finally we analyze the impact of selecting a geometric technique (trilateration, multilateration and apollonius) on the performance of a geolocation solution.