Miracle-dz/UniFAR-FTUs huggingface dataset:
Firm Survival, Uncertainty, and Financial Frictions: Is There a Financial Uncertainty Accelerator?

Using a large panel of unquoted UK firms over the period 2000-09, we examine the impact of firm-specific uncertainty on corporate failures. In this context we also distinguish between firms which are likely to be more or less dependent on bank finance as well as public and non-public companies. Our results document a significant effect of uncertainty on firm survival. This link is found to be more potent during the recent financial crisis compared with tranquil periods. We also uncover significant firm-level heterogeneity since the survival chances of bank-dependent and non-public firms are most affected by changes in uncertainty, especially during the recent global financial crisis.
The effect of autonomic arousal on attentional focus

This study investigates the effect of arousal on visual selection processes. Arousal is predicted to narrow the window of attention surrounding a point of focus. BOLD response to a letter discrimination task was measured under aroused (aversive noise) and non-aroused conditions (n = 8). Results revealed spatially distinct responses for trials invoking a narrow versus wide attentional focus. Under arousal a wide focus showed posterior thalamic activation similar to that associated with the narrowed attentional focus. This reflects altered stimulus filtering and supported the hypothesis. Relevant neuroanatomy involving the locus coeruleus and a triangular circuit of selective attention is discussed. The data demonstrates the intersection of arousal and visual stimulus selection systems, identifies a cognitive consequence of arousal, and provides the first fMRI evidence for brain stem autonomic arousal.
On a selfish caching game

In this work we define and study a new model for the caching problem in a heterogeneous wireless network under a flash-crowd scenario. Using non-cooperative game theory, we cast the caching problem as an anti-coordination game. We start by defining the social optimum in the general case and then focus on a two-player game to obtain insights into the design of efficient caching strategies. Based the theoretical findings, our current work focuses on the development of strategies to be implemented in a practical network setting.
ENTROPY STABLE APPROXIMATIONS OF NAVIER-STOKES EQUATIONS WITH NO ARTIFICIAL NUMERICAL VISCOSITY

We construct a new family of entropy stable difference schemes which retain the precise entropy decay of the Navier–Stokes equations, To this end we employ the entropy conservative differences of [24] to discretize Euler convective fluxes, and centered differences to discretize the dissipative fluxes of viscosity and heat conduction. The resulting difference schemes contain no artificial numerical viscosity in the sense that their entropy dissipation is dictated solely by viscous and heat fluxes. Numerical experiments provide a remarkable evidence for the different roles of viscosity and heat conduction in forming sharp monotone profiles in the immediate neighborhoods of shocks and contacts.
Broadband auditory stream segregation by hearing-impaired and normal-hearing listeners.

PURPOSE To investigate the effects of hearing loss on auditory stream segregation of broadband inharmonic sounds. METHOD Auditory stream segregation by listeners with normal and impaired hearing was measured for 6-component inharmonic sounds ("A" and "B") using objective and subjective methods. Components in the A stimuli ranged between 1000 and 4000 Hz, whereas B stimuli were generated at the same frequency ratio but scaled upward in frequency relative to the A stimuli. In Experiment 1, streaming was measured by having listeners detect a delay inserted into a sequence of A and B stimuli (A_B_A_B_.) for B stimuli with different frequencies. In Experiment 2, streaming was measured using an ABA_ABA_. sequence, and the frequency of the B stimulus decreased until listeners reported that they could "no longer hear two separate streams. " RESULTS Experiment 1 indicated no significant differences between groups in the size of the just detectable delay and no significant interactions between group and the scaling factor between the B and A stimuli. Experiment 2 revealed no significant differences in streaming abilities between normal-hearing and hearing-impaired groups. CONCLUSIONS Overall, results indicate that listeners with normal and impaired hearing have similar auditory streaming abilities for broadband inharmonic complex stimuli.
Role of Marital Status in the Impact of Forgiveness on Psychological Resilience among Women

Mental health includes several components of living a healthy life such as one’s ability to enjoy life and to cope with stresses. Forgiveness is also one path to mental health. Present study aimed to investigate the role of marital status in the impact of forgiveness on psychological resilience. 289 women (married=151, unmarried=138) aged between 21-40 participated in the study and provided data on Heartland Forgiveness Scale (Thompson et al., 2005) and The Brief Resilience Scale (Smith et. al., 2008). Results showed a significant positive impact of forgiveness on psychological resilience among women. Findings further revealed that marital status was the significant determinant of forgiveness and resilience among women. It was found that married women have significant effects on forgiveness and resilience. Study has the implication to enhance the mental health by learning forgiveness skills, because universal forgiveness exercises can help to find best strategies to deal with feeling of stress, hurt, pain, revenge, resentment and so on.
Combining words and prosody for information extraction from speech

Information extraction from speech is a crucial step on the way from speech recognition to speech understanding. A preliminary step toward speech understanding is the detection of topic boundaries, sentence boundaries, and proper names in speech recognizer output. This is important since speech recognizer output lacks the usual textual cues to these entities (such as headers, paragraphs, sentence punctuation, and capitalization). Numerous word-based approaches to these tasks have been developed in the past; in this work we demonstrate the use of prosodic cues, alone and in combination with words, for segmentation and name finding. In experiments on the Broadcast News corpus, we find that prosodic cues alone allow sentence and topic segmentation that is at least as good as word-based methods alone, and that combining both types of cues gives significant wins. Named entity recognition, on the other hand, currently does not seem to benefit from prosodic cues, for several interesting reasons.
Approximate Closed-Form Energy Efficient PA for MIMO Relaying Systems in the High SNR Regime

Energy efficient power coefficients at the relay are derived in a closed-form expression for the green multi-input-multi-output relaying system in the high signal-to-noise ratio (SNR) regime, where the objective is to maximize the energy efficiency (EE), which is defined by the ratio of the spectral efficiency (SE) to total power consumption, with a minimum SE requirement under practical power consumption models. In particular, we derive closed-form solutions using the high SNR approximation, which turn out to be different from the water-filling solution. Simulation results show that the proposed solution nearly achieves the optimal EE in all SNR regimes.
Bayesian Statistics BAYESIAN STATISTICS ∗

Mathematical statistics uses two major paradigms, conventional (or frequentist), and Bayesian. Bayesian methods provide a complete paradigm for both statistical inference and decision making under uncertainty. Bayesian methods may be derived from an axiomatic system, and hence provide a general, coherent methodology. Bayesian methods contain as particular cases many of the more often used frequentist procedures, solve many of the difficulties faced by conventional statistical methods, and extend the applicability of statistical methods. In particular, Bayesian methods make it possible to incorporate scientific hypothesis in the analysis (by means of the prior distribution) and may be applied to problems whose structure is too complex for conventional methods to be able to handle. The Bayesian paradigm is based on an interpretation of probability as a rational, conditional measure of uncertainty, which closely matches the sense of the word ‘probability’ in ordinary language. Statistical inference about a quantity of interest is described as the modification of the uncertainty about its value in the light of evidence, and Bayes’ theorem precisely specifies how this modification should be made. The special situation, often met in scientific reporting and public decision making, where the only acceptable information is that which may be deduced from available documented data, is addressed by objective Bayesian methods, as a particular case.
Novel pathogenic SLC25A46 splice‐site mutation causes an optic atrophy spectrum disorder

The inherited optic neuropathies comprise a group of genetically heterogeneous disorders causing optic nerve dysfunction. In some cases, optic neuropathies are associated with cerebellar atrophy which mainly affects the vermis. Here, we describe a Moroccan girl of consanguineous parents with optic atrophy and cerebellar atrophy. Exome sequencing revealed a novel homozygous mutation (c.283+3G>T) in the donor splice site for exon 1 of SLC25A46. RNA analysis revealed that an alternative splice site within exon 1 was used leading to a premature termination codon within exon 2. SLC25A46 mRNA expression showed there is no wild‐type transcript present in the patient and the mutant transcript does not undergo nonsense‐mediated mRNA decay. Futhermore, we observed c.283+3G>T SLC25A46 mutation induces mitochondrial fragmentation. An additional 10 patients with optic atrophy and cerebellar atrophy, which were negative for mtDNA and OPA1 variants, were tested for pathogenic mutations in the SLC25A46 gene. However, no additional variants were identified. Our findings confirm the recent report of pathogenic SLC25A46 mutations as a novel cause for optic atrophy spectrum disorder.
Design and implementation of natural language processing with syntax and semantic analysis for extract traffic conditions from social media data

Traffic congestion is still a crucial issue because it has a huge impact from the waste of time, the fuel to air pollution. Search information on traffic conditions have been widely available such as through Twitter and the website of CCTV, but the rapid development of online information services resulted in the lack of time to read the complete information. By utilizing the Twitter data, then created a summary regarding the traffic, the summary can improve time efficiency and effectiveness in obtaining information about traffic conditions. However, the structure of the language of Twitter tweets unstructured and raw cause difficult to process information computer, to solve these problems then summarize it using Natural Language Processing approach the syntactic and semantic analysis to improve the structure of words and sentence parsing so that it can classify traffic conditions tweet of the sentence.
The scale dependence and structure of convergence fields preceding the initiation of deep convection

Links between convergence and convection are poor in global models, and poor representation of convection is the source of many model biases in the tropics. State‐of‐the‐art convection‐permitting simulations allow us to analyze realistic convection statistically. The analysis of fractal dimension is used to show that in convection‐permitting simulations (grid spacings 1.5, 4, and 12 km) of the West African monsoon, 50% of deep convective initiations occur in the near vicinity of low‐level boundary layer convergence lines that are orientated along the mean wind. In these simulations, more than 80% of the initiations occur within large‐scale (300 × 300 km) convergence, with some 20% in large‐scale divergence, and almost all cases occur within local scale (60 × 60 km) convergence. The behavior alters in a simulation with a convection scheme and a grid spacing of 12 km; initiation is less frequent over convergence lines, and there is less dependency on high‐magnitude low‐level local convergence.
Retrieval of soil moisture variations in agricultural fields through a new Bayesian change detection approach

A new change detection algorithm based on a Bayesian approach is developed and tested. The main objective of this approach is to exploit the changes in backscattering signals and relate them to soil moisture variations over agricultural fields under the hypothesis of both constant and variable roughness. The proposed methodology overcomes the limitations of the some change detection methods because it takes into account also possible changes in the radar signal due to roughness variability. The method is trained and tested on two data sets considering both C and L-band backscattering coefficients in relation to soil moisture and roughness measurements. The C-band dataset was acquired over bare soils while the L-band data set was acquired on vegetated fields and was exploited to understand the impact of vegetation in such approach. The results indicate that the approach is able to detect soil moisture changes both for C-and L-band data. In case of L band data, the presence of vegetation seems to determine backscattering dynamics reduction with respect to soil moisture changes.
Type of Vegetarian Diet, Body Weight, and Prevalence of Type 2 Diabetes

OBJECTIVE We assessed the prevalence of type 2 diabetes in people following different types of vegetarian diets compared with that in nonvegetarians. RESEARCH DESIGN AND METHODS The study population comprised 22,434 men and 38,469 women who participated in the Adventist Health Study-2 conducted in 2002–2006. We collected self-reported demographic, anthropometric, medical history, and lifestyle data from Seventh-Day Adventist church members across North America. The type of vegetarian diet was categorized based on a food-frequency questionnaire. We calculated odds ratios (ORs) and 95% CIs using multivariate-adjusted logistic regression. RESULTS Mean BMI was lowest in vegans (23.6 kg/m2) and incrementally higher in lacto-ovo vegetarians (25.7 kg/m2), pesco-vegetarians (26.3 kg/m2), semi-vegetarians (27.3 kg/m2), and nonvegetarians (28.8 kg/m2). Prevalence of type 2 diabetes increased from 2.9% in vegans to 7.6% in nonvegetarians; the prevalence was intermediate in participants consuming lacto-ovo (3.2%), pesco (4.8%), or semi-vegetarian (6.1%) diets. After adjustment for age, sex, ethnicity, education, income, physical activity, television watching, sleep habits, alcohol use, and BMI, vegans (OR 0.51 [95% CI 0.40–0.66]), lacto-ovo vegetarians (0.54 [0.49–0.60]), pesco-vegetarians (0.70 [0.61–0.80]), and semi-vegetarians (0.76 [0.65–0.90]) had a lower risk of type 2 diabetes than nonvegetarians. CONCLUSIONS The 5-unit BMI difference between vegans and nonvegetarians indicates a substantial potential of vegetarianism to protect against obesity. Increased conformity to vegetarian diets protected against risk of type 2 diabetes after lifestyle characteristics and BMI were taken into account. Pesco- and semi-vegetarian diets afforded intermediate protection.
Don't Think, Just Feel the Music: Individuals with Strong Pavlovian-to-Instrumental Transfer Effects Rely Less on Model-based Reinforcement Learning

Behavioral choice can be characterized along two axes. One axis distinguishes reflexive, model-free systems that slowly accumulate values through experience and a model-based system that uses knowledge to reason prospectively. The second axis distinguishes Pavlovian valuation of stimuli from instrumental valuation of actions or stimulus–action pairs. This results in four values and many possible interactions between them, with important consequences for accounts of individual variation. We here explored whether individual variation along one axis was related to individual variation along the other. Specifically, we asked whether individuals' balance between model-based and model-free learning was related to their tendency to show Pavlovian interferences with instrumental decisions. In two independent samples with a total of 243 participants, Pavlovian–instrumental transfer effects were negatively correlated with the strength of model-based reasoning in a two-step task. This suggests a potential common underlying substrate predisposing individuals to both have strong Pavlovian interference and be less model-based and provides a framework within which to interpret the observation of both effects in addiction.
Analyzing Rule Evaluation Measures with Educational Datasets: A Framework to Help the Teacher

Rule evaluation measures play an important role in educational data mining. A lot of measures have been proposed in different fields that try to evaluate features of the rules obtained by different types of mining algorithms for association and classification tasks. This paper describes a framework for helping non-expert users such as instructors analyze rule evaluation measures and define new ones. We have carried out several experiments in order to test our framework using datasets from several Cordoba University Moodle courses.
FORGETTING AND REMEMBERING IN FREE RECALL: INTENTIONAL AND UNINTENTIONAL '

ROBERT A. BJORKUniversity of MichiganTwo free recall experiments were designed to study the processes by which5s remember some items and forget others. In both experiments, 5s werecued immediately after each word in a list whether to remember (R word) or toforget (F word) that word. After each of six such lists, 5s were asked to recallthe R words and to avoid recalling the F words; in general, 5s were remarkablyable to do both. At the end of the experiment, 5s were asked, without fore-warning, to recall any and all R words and F words they could remember. InExp. I, final recall of F words was very poor: they seemed not to be in memory.In Exp. II, which employed categorized lists, 5s recalled F words quite wellgiven that there were R words in the same semantic category. The results sug-gest that the differential rehearsal devoted to R words operates primarily onretrieval rather than on storage.
Pseudo-bimodal community detection in Twitter-based networks

We present a novel approach to clustering Twitter users and characterizing their preferences (political or otherwise) based on the features of communication networks extracted from their tweets. We make the assumption that central users in the network, the so-called “top”, or “power” users, set the agenda, while other, “regular” users often retweet and/or mention their tweets, and behavior towards “top” users differs from the behaviour of “regular” users towards each other. We show that network clustering on Twitter can be observed more distinctively on unimodal projections of specially created bimodal networks (bipartite graphs), where top users in the networks are artificially separated into a second part according to node centrality measures. We evaluate our approach on Twitter-based datasets of mentions and retweets related to Russian political protests and a benchmark English-language Twitter dataset with distinctly polarized clusters; we compare various centrality measures and show that our algorithm yields high modularity in the resulting community structure.
Unravelling the drivers of short- and long-term variability in the Amazon hydrological cycle using tree-ring oxygen isotopes

The Amazon hydrological cycle has intensified since approximately 1990, and yet long-term meteorological data from the region are limited, making it difficult to determine the cause of current variability. Proxy records can be used to reconstruct past climate, thus providing useful historical context for recent changes. This thesis focuses on the climate insights that can be gained from oxygen isotopes in tree rings (δ18OTR). The consistency of annual ring formation was tested first, as this is an important prerequisite for constructing a well-dated proxy record. Cedrela trees were found to form annual rings across most of the species’ natural range, but biannual rings in Suriname (Chapter 3). Next, new δ18OTR records were developed from Cedrela and seven other tree species from northern Bolivia. δ18OTR signals were shown to correlate between different species, and between sites large distances apart (<1000 km), indicating a large-scale environmental control on δ18OTR (Chapter 4). Following this, atmospheric back-trajectory modelling and basin-scale vapour transport analysis were used to confirm that rainout of heavy isotopes during moisture transport across the continent is the primary control on interannual δ18OTR signals in the western Amazon (Chapter 5). Finally, new Cedrela δ18OTR chronologies from Ecuador and Bolivia were developed. These records show an increase in δ18OTR from the early 1800s until approximately 1950, indicating a change in hydrological functioning over this period, with a reversal in the trend over the last 1–2 decades. The increase is most likely driven by a reduction in the fraction of incoming water vapour that rains out over the Amazon, which could be caused by a reduction in precipitation, or an increase in the volume of imported vapour. Overall, these results provide evidence for long-term changes in Amazon hydrology over the past 200 years, and make an important contribution to the field of tropical dendroclimatology.
Design of Power Efficient Schema for Energy Optimization in Data Center With Massive Task Execution Using DVFS

The proposed system highlights a novel energy efficient technique by considering an entire datacenter using DVFS (Dynamic Voltage and Frequency Scaling). Unwanted power consumption was always a matter of concern from last 2 years for the administrators of datacenters. Therefore, a research trial in order to minimize the power consumption has become of the prominent concern in the area of cloud computing as it claims zero down-time as per Service Level Agreement. In this research work, we consider the case of multimedia video sharing web services, which we believe is frequently in top of the hit counter with millions of user sharing high size of video application, giving rise of power consumption from data center. The proposed system presents a unique provisioning technique which amalgamates the power factor with network resources. The simulation results also show that the system is successful in maintaining an equilibrium between power utilization at data center along with unit of task allocation processing.
Testing linear and non-linear analog circuits using moment generating functions

Circuit under test (CUT) is treated as a transformation on the probability density function of its input excitation, which is, a continuous random variable (RV) of gaussian probability distribution. Probability moments of the output, which is now the transformed RV, is used as a metric for testing catastrophic and parametric faults in circuit components that make up the CUT. Use of probability moments as circuit test metric with white noise excitation as input addresses three important problems faced in analog circuit test, namely: 1) Reduces complexity of input signal design, 2) Increases resolution of fault detection, and 3) Reduces production test cost as it has no area overhead and marginally reduces test time. We develop the theory, test procedure and report SPICE simulation results of the proposed scheme on a benchmark elliptic filter. With the proposed scheme, we are able to detect all catastrophic faults and single parametric faults that are off from their nominal value by just over 10%. Method reported in this paper paves way for future research in circuit diagnosis, leveraging moments of the output to diagnose parametric faults in analog circuits.