Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic diversity and population history of the endangered killifish Aphanius baeticus.

The secondary freshwater fish fauna of the western-Iberian Peninsula basin is primarily restricted to local coastal streams, and man-made salt evaporation ponds, etc., which are susceptible to periodical flood and drought events. Despite its uniqueness in ecological adaptation to high saltwater tolerance, very little is known about this fauna's population dynamics and evolutionary history. The killifish, Aphanius baeticus (Cyprinodontidae) is an endemic species restricted to river basins on Spain's southern Atlantic coastline, considered as "Endangered. " In this study, the genetic structure, diversity and historical demography of A. baeticus were analyzed using mitochondrial (cytochrome b, N=131) and nuclear (4 out of 19 microsatellites tested, N=288) markers across its distribution range. The phylogenetic and networking reconstruction revealed subtle phylogeographic structuring. A scattered expansion at the beginning of the interglacial periods, coupled with posterior events of extinction and colonization caused by periodical cycles of flooding, could explain the absence of well-defined phylogenetic relationships among populations. Moreover, very low genetic diversity values and a weak population differentiation were detected. We proposed that dispersals allowed by periodic floods connecting river drainages may have promoted a wide genetic exchange among populations and could have contributed to the current genetic relatedness of these populations.
Frequency Comparison of I-Stabilized Nd : YAG Lasers

A first international comparison of I 2-stabilized Nd : YAG lasers has been made between the National Research Laboratory of Metrology (NRLM), Tsukuba, Japan, the Joint Institute for Laboratory Astrophysics JILA (formerly the Joint Institute for Laboratory Astrophysics), Boulder, CO, the National Institute of Standards and Technology (NIST), Boulder, and the University of Colorado, Boulder. The results of the comparison show that the square root Allan variance of the portable NRLM laser has reached2 10 14 when the integration time is larger than 300 s. Matrix measurements were made for five hyperfine components froma6 to a10 of the R(56)32-0 line. The averaged frequency difference between the NRLM and JILA lasers for four measurements made on three separate days was 4996 Hz (NRLM-JILA, at 532 nm) with a standard deviation of 88 Hz.
Detector performance analysis of watermark-based error concealment in image communications

In this work, the detector performance of a watermark-based error concealment (WEC) system proposed in C.B. Adsumilli is mathematically analyzed. The spread spectrum based WEC algorithm embeds a low resolution version of an image in itself during encoding. At the receiver, this embedded watermark is extracted and used as a reference to conceal the transmission losses in the reconstructed image. For the application of error concealment, the detector modelling varies from the conventional watermark detectors due to the fact that we use a full frame DCT to embed the watermark data and vary the strength of the watermark in accordance with the embedding coefficients to reduce the standard deviation of the resulting distribution. We further approximate the full frame DCT coefficients to follow a generalized Gaussian distribution (GGD) like in the case of modelling block-based DCT coefficients and consequently, we provide a comparison between the performance of this system and conventional block-based embedding strategies for various packet loss probabilities. Both analytical and simulation results show that our system of full frame DCT embedding is more effective for error concealment in detecting the embedded bits with lesser probability of error.
WIDER Working Paper No . 2013 / 124 Foreign capital inflow and economic growth in Cameroon

The purpose of this paper is to capture the impact of foreign capital inflows (which include foreign aid and foreign direct investment) on economic growth in Cameroon. Using the autoregressive distributive lag approach to cointegration and time-series data for the period 1980–2008, the results of the study indicate that the domestic capital stock and foreign direct investment have positive and significant impacts on economic growth in the short and long terms, while the impact of the labour force on growth was significantly negative in both terms, a result that may be attributable to the fact that Cameroon is a developing country with an unlimited supply of labour whose increase has a detrimental effect on the country’s growth.
Social Interaction in Flickr: Mechanisms and Role in Link Formation

Online social networking sites such as Facebook, Twitter and Flickr are among the most popular sites on the Web, providing platforms for sharing information and interacting with a large number of people. The different ways for users to interact, such as liking, retweeting and favoriting usergenerated content, are among the defining and extremely popular features of these sites. While empirical studies have been done to infer network growth processes in these sites, few studies have characterized social interaction behavior and the role of social interaction in network growth. In this paper, we analyze large-scale data collected from the Flickr social network to understand favoriting behavior and study the effect of a favorite on network growth. We do this using a systematic formulation of Flickr as a twolayer temporal multiplex network: the first layer describes the follow relationship between users and the second layer describes the social interaction between users in the form of favorite markings to photos uploaded by them. Our investigation reveals that (a) favoriting is well-described by preferential attachment, (b) over 50% of favorites are reciprocated within 10 days if at all they are reciprocated, (c) different kinds of favorites differ in how fast they are reciprocated, and (d) favoriting leads to link formation in the follow layer through multiplex triadic closure.
Effect of gender on students’ emotion with gender-related public self-consciousness as a moderator in mixed-gender physical education classes

The present study investigates whether gender-related public self-consciousness moderates the relationship between students’ gender and emotions in mixed-gender physical education classes. The Positive and Negative Affect Scales and the Gender-related Public Self-Consciousness Scale were administered to 380 middle-school students in South Korea. The preliminary analysis included a t-test and ANOVA. Subsequently, a hierarchical regression analysis was performed. The results showed that girls’ gender-related public self-consciousness was significantly higher than that of boys. Further, gender-related public self-consciousness significantly moderated the relationship between gender and positive emotion, and while it moderated the relationship between gender and negative emotion, the effect was negligible. Gender-related public self-consciousness plays a role in mixed-gender physical education class. Thus, gender and gender-related public self-consciousness can help educators better understand students’ emotions. These findings can inform guidelines for planning mixed-gender physical education course curricula
Title Fiscal Policy Switching : Evidence from Japan , US , and UK

This paper estimates fiscal policy feedback rules in Japan, the United States, and the United Kingdom, allowing for stochastic regime changes. Using Markov-switching regression methods, we find that the Japanese data clearly reject the view that fiscal policy regime is fixed; i.e., the Japanese government has been adopting either of Ricardian or Non-Ricardian policy at all times. Instead, our results indicate that fiscal policy regimes evolve over time in a stochastic manner. This is in a sharp contrast with the U.S. and U.K. results in which the government’s fiscal behavior is consistently characterized by Ricardian policy. JEL Classification Numbers : E62
Transparent and Flexible Network Management for Big Data Processing in the Cloud

We introduce FlowComb, a network management framework that helps Big Data processing applications, such as Hadoop, achieve high utilization and low data processing times. FlowComb predicts application network transfers, sometimes before they start, by using software agents installed on application servers and while remaining completely transparent to the application. A centralized decision engine collects data movement information from agents and schedules upcoming flows on paths such that the network does not become congested. Results on our lab testbed show that FlowComb is able to reduce the time to sort 10GB of randomly generated data by 35% while changing paths for only 6% of the transfers.
The Eudoxus Real Numbers

This note describes a representation of the real numbers due to Schanuel. The representation lets us construct the real numbers from first principles. Like the well-known construction of the real numbers using Dedekind cuts, the idea is inspired by the ancient Greek theory of proportion, due to Eudoxus. However, unlike the Dedekind construction, the construction proceeds directly from the integers to the real numbers bypassing the intermediate construction of the rational numbers. The construction of the additive group of the reals depends on rather simple algebraic properties of the integers. This part of the construction can be generalised in several natural ways, e.g., with an arbitrary abelian group playing the role of the integers. This raises the question: what does the construction construct? In an appendix we sketch some generalisations and answer this question in some simple cases. The treatment of the main construction is intended to be self-contained and assumes familiarity only with elementary algebra in the ring of integers and with the definitions of the abstract algebraic notions of group, ring and field.
Figure 1: Combining Inductive and Analytical Learn- Ing: in the Ideal Case, a Learning System Deals with All Levels

of domain theories, i.e., it is robust with respect to severe errors therein. It operates purely inductively if no domain theory is available or the domain theory is random, and purely analytically if the domain theory is perfect. form they require correct and complete prior knowledge of the domain. In contrast, inductive learning methods require no such prior knowledge, but rely instead on many more training examples to guide generalization , together with some syntactic inductive bias. One of the major open problems in machine learning is to combine analytical and inductive learning in order to gain the beneets of both approaches: reduced requirement for training data, and robustness with respect to poor prior knowledge. Figure 1 illustrates the spectrum of domain theories over which a general learning system should be able to operate. At present, we h a ve inductive learning methods that operate well at the leftmost point on the spectrum , in which no domain theory is available. We also have explanation-based methods that operate well on the right under certain assumptions about the character of potential errors in the domain knowledge. We seek a single uniied method, which i s Robust with respect to severe errors in the domain theory, i.e., it should operate across the entire spectrum. In particular, if no domain theory is available or one that is even worse than random, we desire that the system learns as well as a purely inductive system. At the other extreme, if perfect knowledge is available, the system should perform comparably to current explanation-based methods. domain knowledge that it has previously learned from scratch, as well as knowledge provided by the designer. In particular, we are interested in methods that can operate under a broad variety of domain theory errors , such as those typical of inductively learned do
Essential characteristics of Lizu, a Qiangic language of Western Sichuan

This article covers essential characteristics of Lizu, a Sino-Tibtan language of Western Sichuan (China), currently classified as belonging to the Qiangic subgroup of the Sino-Tibetan language family. The article provides general information on Lizu: location, origins, dialect variation and endangerment; details Lizu phonetic, phonological and tonal make-up and outlines Lizu nominal and verbal marking. The article is concluded by a preliminary comparison between Lizu and its neighbouring Qiangic languages (Lusu, Ersu and Shixing).
Energy dissipation in multifrequency atomic force microscopy

Summary The instantaneous displacement, velocity and acceleration of a cantilever tip impacting onto a graphite surface are reconstructed. The total dissipated energy and the dissipated energy per cycle of each excited flexural mode during the tip interaction is retrieved. The tip dynamics evolution is studied by wavelet analysis techniques that have general relevance for multi-mode atomic force microscopy, in a regime where few cantilever oscillation cycles characterize the tip–sample interaction.
INFORMATION SECURITY RISK ASSESSMENT: BAYESIAN PRIORITIZATION FOR AHP GROUP DECISION MAKING

Increasing complexity of risk management requires the use of more flexible approaches to measure information security risk. Adapting complex risk analysis tools in today’s information systems is a very difficult task due to the shortage of reliable data. Analytic Hierarchy Process group decision making (AHP-GDM) offers a technical support for risk analysis by taking the judgements of managers and systematically calculating the relative risk values. This paper presents how Bayesian Prioritization procedure (BPP) provides a more effective way of risk assessment than proposed by the conventional approaches used in AHP-GDM.
Coherent electron-phonon coupling and polaronlike transport in molecular wires

We present a technique to calculate the transport properties through one-dimensional models of molecular wires. The calculations include inelastic electron scattering due to electron-lattice interaction. The coupling between the electron and the lattice is crucial to determine the transport properties in one-dimensional systems subject to Peierls transition since it drives the transition itself. The electron-phonon coupling is treated as a quantum coherent process, in the sense that no random dephasing due to electron-phonon interactions is introduced in the scattering wave functions. We show that charge-carrier injection, even in the tunneling regime, induces lattice distortions localized around the tunneling electron. The transport in the molecular wire is due to polaronlike propagation. We show typical examples of the lattice distortions induced by charge injection into the wire. In the tunneling regime, the electron transmission is strongly enhanced in comparison with the case of elastic scattering through the undistorted molecular wire. We also show that although lattice fluctuations modify the electron transmission through the wire, the modifications are qualitatively different from those obtained by the quantum electron-phonon inelastic scattering technique. Our results should hold in principle for other one-dimensional atomic-scale wires subject to Peierls transitions.
A Reconfigurable Low Power High Throughput Architecture for Deep Network Training

General purpose computing systems are used for a large variety of applications. Extensive supports for flexibility in these systems limit their energy efficiencies. Neural networks, including deep networks, are widely used for signal processing and pattern recognition applications. In this paper we propose a multicore architecture for deep neural network based processing. Memristor crossbars are utilized to provide low power high throughput execution of neural networks. The system has both training and recognition (evaluation of new input) capabilities. The proposed system could be used for classification, dimensionality reduction, feature extraction, and anomaly detection applications. The system level area and power benefits of the specialized architecture is compared with the NVIDIA Telsa K20 GPGPU. Our experimental evaluations show that the proposed architecture can provide up to five orders of magnitude more energy efficiency over GPGPUs for deep neural network processing.
The Evolutionarily Conserved Longevity Determinants HCF-1 and SIR-2.1/SIRT1 Collaborate to Regulate DAF-16/FOXO

The conserved DAF-16/FOXO transcription factors and SIR-2.1/SIRT1 deacetylases are critical for diverse biological processes, particularly longevity and stress response; and complex regulation of DAF-16/FOXO by SIR-2.1/SIRT1 is central to appropriate biological outcomes. Caenorhabditis elegans Host Cell Factor 1 (HCF-1) is a longevity determinant previously shown to act as a co-repressor of DAF-16. We report here that HCF-1 represents an integral player in the regulatory loop linking SIR-2.1/SIRT1 and DAF-16/FOXO in both worms and mammals. Genetic analyses showed that hcf-1 acts downstream of sir-2.1 to influence lifespan and oxidative stress response in C. elegans. Gene expression profiling revealed a striking 80% overlap between the DAF-16 target genes responsive to hcf-1 mutation and sir-2.1 overexpression. Subsequent GO-term analyses of HCF-1 and SIR-2.1-coregulated DAF-16 targets suggested that HCF-1 and SIR-2.1 together regulate specific aspects of DAF-16-mediated transcription particularly important for aging and stress responses. Analogous to its role in regulating DAF-16/SIR-2.1 target genes in C. elegans, the mammalian HCF-1 also repressed the expression of several FOXO/SIRT1 target genes. Protein–protein association studies demonstrated that SIR-2.1/SIRT1 and HCF-1 form protein complexes in worms and mammalian cells, highlighting the conservation of their regulatory relationship. Our findings uncover a conserved interaction between the key longevity determinants SIR-2.1/SIRT1 and HCF-1, and they provide new insights into the complex regulation of FOXO proteins.
EVALUATING THE BEHAVIOUR OF DOMESTIC ROBOTS USING VIDEO-BASED STUDIES

As robots are used for more complex applications in human oriented environments, they will have to be able to interact with inexperienced users. Findings from human-human interaction and human-computer interaction research are relevant, but often limited because robot are different from both humans and computers . Therefore, new methods have to be developed in Human-Robot Interaction (HRI) research to inform the design of these robots in order to build robots that are suitable for inexperienced users. A Video-based HRI (VHRI) methodology was used to carry out a multi-national HRI user study which employed our robot BIRON (BIelefeld RObot companioN) which is designed for use in domestic environments. Participants watched videos of the robot system interacting with a human actor, and rated two different robot behaviours (extrovert and introvert). Their perceptions and ratings of the robot behaviours differed with regard to verbal output and person following by the robot. Participants’ ratings of the robot behaviours were evaluated and compared and suggestions made with the aim of improving the human-robot interaction.
Clarifying the debate on population-based screening for breast cancer with mammography

Background: The recent controversy about using mammography to screen for breast cancer based on randomized controlled trials over 3 decades in Western countries has not only eclipsed the paradigm of evidence-based medicine, but also puts health decision-makers in countries where breast cancer screening is still being considered in a dilemma to adopt or abandon such a well-established screening modality. Methods: We reanalyzed the empirical data from the Health Insurance Plan trial in 1963 to the UK age trial in 1991 and their follow-up data published until 2015. We first performed Bayesian conjugated meta-analyses on the heterogeneity of attendance rate, sensitivity, and over-detection and their impacts on advanced stage breast cancer and death from breast cancer across trials using Bayesian Poisson fixed- and random-effect regression model. Bayesian meta-analysis of causal model was then developed to assess a cascade of causal relationships regarding the impact of both attendance and sensitivity on 2 main outcomes. Results: The causes of heterogeneity responsible for the disparities across the trials were clearly manifested in 3 components. The attendance rate ranged from 61.3% to 90.4%. The sensitivity estimates show substantial variation from 57.26% to 87.97% but improved with time from 64% in 1963 to 82% in 1980 when Bayesian conjugated meta-analysis was conducted in chronological order. The percentage of over-detection shows a wide range from 0% to 28%, adjusting for long lead-time. The impacts of the attendance rate and sensitivity on the 2 main outcomes were statistically significant. Causal inference made by linking these causal relationships with emphasis on the heterogeneity of the attendance rate and sensitivity accounted for the variation in the reduction of advanced breast cancer (none-30%) and of mortality (none-31%). We estimated a 33% (95% CI: 24–42%) and 13% (95% CI: 6–20%) breast cancer mortality reduction for the best scenario (90% attendance rate and 95% sensitivity) and the poor scenario (30% attendance rate and 55% sensitivity), respectively. Conclusion: Elucidating the scenarios from high to low performance and learning from the experiences of these trials helps screening policy-makers contemplate on how to avoid errors made in ineffective studies and emulate the effective studies to save women lives.
Voltage‐gated K+ channels in layer 5 neocortical pyramidal neurones from young rats: subtypes and gradients

1 We investigated the types and distribution of voltage‐gated K+ channels in the soma and apical dendrite of layer 5 (L5) neocortical pyramidal neurones, of young rats (postnatal days 13–15), in acute brain slices. 2 A slow inactivating outward K+ current and a fast inactivating outward K+ current were detected in nucleated patches. The slow K+ current was completely blocked by tetraethylammonium (TEA) with an IC50 of 5 ± 1 mm (mean ±s.e.m.) and was partially blocked by 4‐aminopyridine (4‐AP). The fast K+ current was blocked by 4‐AP with an IC50 of 4.2 ± 0.5 mM, but was not blocked by TEA. 3 The activation kinetics of the slow K+ current were described by a second order Hodgkin‐Huxley model. The slow K+ current displayed bi‐exponential inactivation. A fourth order Hodgkin‐Huxley model for activation and first order for inactivation described the kinetics of the fast K+ current. 4 In somatic cell‐attached recordings, three classes of single K+ channels could be differentiated based on their unitary conductance and inactivation kinetics, a fast inactivating channel having a conductance of 13 ± 1 pS, a slow inactivating channel having a conductance of 9.5 ± 0.5 pS, and a very slowly inactivating channel having a conductance of 16 ± 1 pS. 5 The inactivation time constants of the slow and of the very slow K+ channel corresponded to the two inactivation time constants of the slow K+ current observed in nucleated patches. This suggested that two distinct K+ channels mediated the slow K+ current in nucleated patches. 6 The three subtypes of K+ channels that were observed in somatic recordings were present along the apical dendrite. The amplitude of ensemble K+ currents in cell‐attached patches decreased along the apical dendrite as the distance from the soma increased, with a slope of −0.9 ± 0.3 pA per 100 μm. 7 The results suggest that the decrease of the voltage‐gated K+ channel density from the soma along the apical dendrite of L5 pyramidal neurones helps to define a distal, low threshold region for the initiation of dendritic regenerative potentials.