Miracle-dz/UniFAR-FTUs huggingface dataset:
Flexible Coupling of Respiration and Vocalizations with Locomotion and Head Movements in the Freely Behaving Rat

Quadrupedal mammals typically synchronize their respiration with body movements during rhythmic locomotion. In the rat, fast respiration is coupled to head movements during sniffing behavior, but whether respiration is entrained by stride dynamics is not known. We recorded intranasal pressure, head acceleration, instantaneous speed, and ultrasonic vocalizations from male and female adult rats while freely behaving in a social environment. We used high-speed video recordings of stride to understand how head acceleration signals relate to locomotion and developed techniques to identify episodes of sniffing, walking, trotting, and galloping from the recorded variables. Quantitative analysis of synchrony between respiration and head acceleration rhythms revealed that respiration and locomotion movements were coordinated but with a weaker coupling than expected from previous work in other mammals. We have recently shown that rats behaving in social settings produce high rates of ultrasonic vocalizations during locomotion bouts. Accordingly, rats emitted vocalizations in over half of the respiratory cycles during fast displacements. We present evidence suggesting that emission of these calls disrupts the entrainment of respiration by stride. The coupling between these two variables is thus flexible, such that it can be overridden by other behavioral demands.
Purification and Characterization of a Cold-Adapted Lipase from Oceanobacillus Strain PT-11

We isolated a moderately halophilic lipase-producing bacterium from the saline soil. Based on the morphological, physiological, chemotaxonomic and phylogenetic analysis, the isolate PT-11 was postulated to be a novel species identified as Oceanobacillus rekensis PT-11. The lipase was purified 2.50-fold by Q-Sepharose FF and SP-Sepharose FF chromatography and its molecular mass was estimated to be 23.5 kDa by SDS-PAGE. It was highly active over the broad temperature ranging from 10 to 35°C and showed up to 80% of the maximum activity at 10°C indicating the lipase to be a typical cold-adapted enzyme. The enzyme activity was slightly enhanced by Na+, Li+ and K+. Incubation with detergents, such as Tween-20 and Tween-80, slightly inhibited the enzyme activity; while Triton X-100decreased the enzyme activity. The enzyme was fairly stable in the presence of long-chain alcohols but was highly denatured in hydrophilic solvents such as acetone or short-chain alcohols (C1–C3).
Climate Change, Crop Yields, and Internal Migration in the United States

We investigate the link between agricultural productivity and net migration in the United States using a county-level panel for the most recent period of 1970-2009. In rural counties of the Corn Belt, we find a statistically significant relationship between changes in net outmigration and climate-driven changes in crop yields, with an estimated semi-elasticity of about -0.17, i.e., a 1% decrease in yields leads to a 0.17% net reduction of the population through migration. This effect is primarily driven by young adults. We do not detect a response for senior citizens, nor for the general population in eastern counties outside the Corn Belt. Applying this semi-elasticity to predicted yield changes under the B2 scenario of the Hadley III model, we project that, holding other factors constant, climate change would on average induce 3.7% of the adult population (ages 15-59) to leave rural counties of the Corn Belt in the medium term (2020-2049) compared to the 1960-1989 baseline, with the possibility of a much larger migration response in the long term (2077-2099). Since there is uncertainty about future warming, we also present projections for a range of uniform climate change scenarios in temperature or precipitation.
RSSI — Based localization and tracking algorithm for indoor environments

The paper reports the preliminary results of a RSSI-based localization algorithm that implements an exhaustive exploration of the data space, i. e. the power maps of the received signal in an indoor environment. The technique takes advantage of previous experimental results that served to calibrate the signal level simulated by a ray tracer. Numerical precalculated maps include perturbed scenarios that simulate actual conditions in which the signal fluctuates. The localization algorithm draws at random a perturbed map and it extracts the power values corresponding to the probe location. Then, an exhaustive exploration of the spatial domain over an average map is performed to single out the minimum of a cost function expressing the residual between the power values of the test point and those of the candidate points.
Nucleosynthesis in Chandrasekhar Mass Models for Type Ia Supernovae and Constraints on Progenitor Systems and Burning-Front Propagation

The major uncertainties involved in the Chandrasekhar mass models for Type Ia supernovae (SNe Ia) are related to the companion star of their accreting white dwarf progenitor (which determines the accretion rate and consequently the carbon ignition density) and the flame speed after the carbon ignition. We calculate explosive nucleosynthesis in relatively slow deflagrations with a variety of deflagration speeds and ignition densities to put new constraints on the above key quantities. The abundance of the Fe group, in particular of neutron-rich species like 48Ca,50Ti,54Cr,54,58Fe, and 58Ni, is highly sensitive to the electron captures taking place in the central layers. The yields obtained from such a slow central deflagration, and from a fast deflagration or delayed detonation in the outer layers, are combined and put to comparison with solar isotopic abundances. To avoid excessively large ratios of 54Cr/56Fe and 50Ti/56Fe, the central density of the "average" white dwarf progenitor at ignition should be as low as ≲2 × 109 g cm-3. To avoid the overproduction of 58Ni and 54Fe, either the flame speed should not exceed a few percent of the sound speed in the central low Ye layers or the metallicity of the average progenitors has to be lower than solar. Such low central densities can be realized by a rapid accretion as fast asimg1.gif ≳ 1 × 10-7 M☉ yr-1. In order to reproduce the solar abundance of 48Ca, one also needs progenitor systems that undergo ignition at higher densities. Even the smallest laminar flame speeds after the low-density ignitions would not produce sufficient amount of this isotope. We also found that the total amount of 56Ni, the Si-Ca/Fe ratio, and the abundance of some elements like Mn and Cr (originating from incomplete Si burning), depend on the density of the deflagration-detonation transition in delayed detonations. Our nucleosynthesis results favor transition densities slightly below 2.2 × 107 g cm-3.
Accurate Nodes Localization in Anisotropic Wireless Sensor Networks

An accurate localization algorithm tailored for anisotropic wireless sensors networks (WSNs) is proposed in this paper. Using the proposed algorithm, each regular or position-unaware node estimates its distances only to reliable anchors or position-aware nodes. The latter are properly chosen following a new reliable anchor selection strategy that ensures an accurate distance estimation making thereby our localization algorithm more precise. It is shown that the proposed algorithm is implementable in both 2-dimensional (2D) and 3-dimensional (3D) scenarios. A power saving mechanism aiming to enhance the WSN lifetime is also envisaged in this paper. It is proven that the proposed algorithm could easily incorporate such a mechanism. Simulations show that our algorithm, whether combined or not with the power saving mechanism, consistently outperforms the best representative localization algorithms currently available in the literature in terms of accuracy, even with the presence of nonuniform node distribution or radiation irregularities.
Worker Heterogeneity and General Training

Worker heterogeneity can generate conditions under which firms will invest in the general training of their employees. A high ability worker raises the average level of talent in a firm and may consequently increase the range of tasks that can be performed within its ranks. In the absence of any countervailing worker power, some firms acquire monopsony power in the market for labour trained to do the more advanced tasks. Because the degree of monopsony power is increasing in task complexity, firms whose employees undertake more sophisticated tasks are more willing to finance general training. We conclude that training will take place in better-than-average or ‘good’ firms, while ‘bad’ firms will have low-ability workers unlikely to receive much training.
Approximate transmission conditions for time-harmonic Maxwell equations in a domain with thin layer

We study the behavior of the electromagnetic field in a biological cell modelized by a medium surrounded by a thin layer and embedded in an ambient medium. We derive approximate transmission conditions in order to replace the membrane by these conditions on the boundary of the interior domain. Our approach is essentially geometric and based on a suitable change of variables in the thin layer. Few notions of differential calculus are given in order to obtain our asymptotic conditions in a simple way. This paper extends to time-harmonic Maxwell equations the previous works of C.Poignard. Asymptotic transmission conditions at any order are given in Appendix~1.
Stability, change, and heritability of borderline personality disorder traits from adolescence to adulthood: A longitudinal twin study

Abstract Although personality disorders are best understood in the context of lifetime development, there is a paucity of work examining their longitudinal trajectory. An understanding of the expected course and the genetic and environmental contributions to these disorders is necessary for a detailed understanding of risk processes that lead to their manifestation. The current study examined the longitudinal course and heritability of borderline personality disorder (BPD) over a period of 10 years starting in adolescence (age 14) and ending in adulthood (age 24). In doing so, we built on existing research by using a large community sample of adolescent female twins, a sensitive dimensional measure of BPD traits, an extended follow-up period, and a longitudinal twin design that allowed us to investigate the heritability of BPD traits at four discrete ages spanning midadolescence to early adulthood. Results indicated that mean-level BPD traits significantly decline from adolescence to adulthood, but rank order stability remained high. BPD traits were moderately heritable at all ages, with a slight trend for increased heritability from age 14 to age 24. A genetically informed latent growth curve model indicated that both the stability and change of BPD traits are highly influenced by genetic factors and modestly by nonshared environmental factors. Our results indicate that as is the case for other personality dimensions, trait BPD declines as individuals mature from adolescence to adulthood, and that this process is influenced in part by the same genetic factors that influence BPD trait stability.
Endophyte species influence the biomass production of the native grass Achnatherum sibiricum (L.) Keng under high nitrogen availability

Abstract Research on the interaction of endophytes and native grasses normally takes infection status into account, but less often considers the species of endophyte involved in the interaction. Here, we examined the effect of endophyte infection, endophyte species, nitrogen availability, and plant maternal genotype on the performance of a wild grass, Achnatherum sibiricum. Six different Epichloë‐infected maternal lines of A. sibiricum were used in the study; three lines harbored Epichloë gansuensis (Eg), while three lines harbored Epichloë sibirica (Es). These endophytes are vertically transmitted, while Eg also occasionally produces stromata on host tillers. We experimentally removed the endophyte from some ramets of the six lines, with the infected (E+) and uninfected (E−) plants grown under varying levels of nitrogen availability. Eg hosts produced more aboveground biomass than Es hosts only under high nitrogen supply. Endophyte species did not show any influence on the maximum net photosynthetic rate (P max), photosynthetic nitrogen use efficiency, or total phenolics of A. sibiricum under all nitrogen conditions. However, the plant maternal genotype did influence the P max and shoot biomass of A. sibiricum. Our results show that endophyte species influenced the shoot biomass of A. sibiricum, and this effect was dependent on nitrogen supply. As with most coevolutionary interactions, A. sibiricum that harbored Eg and Es may show pronounced geographic variation in natural habitats with increased nitrogen deposition. In addition, stroma‐bearing endophyte (Eg) provides positive effects (e.g., higher biomass production) to A. sibiricum plants during the vegetative growth stage.
On Block Thresholding in Wavelet Regression with Long Memory Correlated Noise

Johnstone and Silverman (1997) and Johnstone (1999) described a level-dependent thresholding method for extracting signals from both shortand long range dependent noise in the wavelet domain structure. It is shown that their Stein unbiased risk estimators (SURE) attain the exact optimal convergence rates in a wide range of Besov balls in certain asymptotic models of standard sample-data models. Based on the asymptotic equivalence between nonparametric regression model and white noise model over Besov spaces, they conjectured that the results obtained from the asymptotic model would carry over to the sampled data model with long memory stationary Gaussian noise. In this paper, we study block thresholding projection-based estimators of mean regression functions for the sampled data model directly as in Hall, et al. (1999). Based on a result that the discrepancy between empirical wavelet coefficients and true wavelet coefficients is within certain small rate, we are able to show that these estimators achieve optimal minimax convergence rates over a large range of Besov function classes B p,q, where s > 1/p, p ≥ 2, q ≥ 1, and nearly optimal convergence rates when 1 ≤ p < 2. These results are analogous to those in the standard regression problem with i.i. d. Gaussian errors. Therefore, in the presence of long memory Gaussian errors, wavelet estimators still provide extensive adaptivity over a wide range of Besov classes. Short title: Wavelet Regression with Long Memory Data 2000 Mathematics Subject Classification: Primary: 62G07; Secondary: 62C20
The Open World of Micro-Videos

Micro-videos are six-second videos popular on social media networks with several unique properties. Firstly, because of the authoring process, they contain significantly more diversity and narrative structure than existing collections of video "snippets". Secondly, because they are often captured by hand-held mobile cameras, they contain specialized viewpoints including third-person, egocentric, and self-facing views seldom seen in traditional produced video. Thirdly, due to to their continuous production and publication on social networks, aggregate micro-video content contains interesting open-world dynamics that reflects the temporal evolution of tag topics. These aspects make micro-videos an appealing well of visual data for developing large-scale models for video understanding. We analyze a novel dataset of micro-videos labeled with 58 thousand tags. To analyze this data, we introduce viewpoint-specific and temporally-evolving models for video understanding, defined over state-of-the-art motion and deep visual features. We conclude that our dataset opens up new research opportunities for large-scale video analysis, novel viewpoints, and open-world dynamics.
A New Feature for Automatic Speaker Verification Anti-Spoofing: Constant Q Cepstral Coefficients

Efforts to develop new countermeasures in order to protect automatic speaker veriﬁcation from spooﬁng have intensiﬁed over recent years. The ASVspoof 2015 initiative showed that there is great potential to detect spooﬁng attacks, but also that the detection of previously unforeseen spooﬁng attacks remains challenging. This paper argues that there is more to be gained from the study of features rather than classiﬁers and introduces a new feature for spooﬁng detection based on the constant Q transform, a perceptually-inspired time-frequency analysis tool popular in the study of music. Experimental results obtained using the standard ASVspoof 2015 database show that, when coupled with a standard Gaussian mixture model-based classiﬁer, the proposed constant Q cepstral coefﬁcients (CQCCs) outperform all previously reported results by a signiﬁcant margin. In particular, those for a subset of unknown spooﬁng attacks (for which no matched training data was used) is 0.46%, a relative improvement of 72% over the best, previously reported results.
Salience and Asset Prices

We present a simple model of asset pricing in which payoff salience drives investors' demand for risky assets. The key implication is that extreme payoffs receive disproportionate weight in the market valuation of assets. The model accounts for several puzzles in finance in an intuitive way, including preference for assets with a chance of very high payoffs, an aggregate equity premium, and countercyclical variation in stock market returns.
A Unit Selection Methodology for Music Generation Using Deep Neural Networks

Several methods exist for a computer to generate music based on data including Markov chains, recurrent neural networks, recombinancy, and grammars. We explore the use of unit selection and concatenation as a means of generating music using a procedure based on ranking, where, we consider a unit to be a variable length number of measures of music. We first examine whether a unit selection method, that is restricted to a finite size unit library, can be sufficient for encompassing a wide spectrum of music. We do this by developing a deep autoencoder that encodes a musical input and reconstructs the input by selecting from the library. We then describe a generative model that combines a deep structured semantic model (DSSM) with an LSTM to predict the next unit, where units consist of four, two, and one measures of music. We evaluate the generative model using objective metrics including mean rank and accuracy and with a subjective listening test in which expert musicians are asked to complete a forced-choiced ranking task. We compare our model to a note-level generative baseline that consists of a stacked LSTM trained to predict forward by one note.
Testing for PPP: Should we use panel methods?

Abstract.A common finding in the empirical literature on the validity of purchasing power parity (PPP) is that it holds when tested for in panel data, but not in univariate (i.e. country-specific) analysis. The usual explanation for this mismatch is that panel tests for unit roots are more powerful than their univariate counterparts. In this paper we suggest an alternative explanation. Existing panel methods assume that cross-unit cointegrating relationships, that would tie the units of the panel together, are not present. Using simulations, we show that if this important underlying assumption of panel unit root tests is violated, the empirical size of the tests is substantially higher than the nominal level, and the null hypothesis of a unit root is rejected too often even when it is true. More generally, this finding warns against the “automatic” use of panel methods for testing for unit roots in macroeconomic time series.
Job Search, Conditional Treatment and Recidivism: The Employment Services for Ex-Offenders Program Reconsidered

Abstract The objective of this paper is to re-evaluate the effect of the 1985 “Employment Services for Ex-Offenders” (ESEO) program on recidivism in San Diego, Chicago and Boston. The initial group of program participants was split randomly in a control group and a treatment group. The actual treatment (mainly being job related counseling) only takes place conditional on finding a job and not having been arrested for those selected in the treatment group. We use interval-censored proportional hazard models for job search and recidivism time, where the latter model incorporates the conditional treatment effect, depending on covariates. We find that the effect of the program depends on location and age. The ESEO program reduces the risk of recidivism only for ex-inmates over the age of 27 in San Diego and Chicago and over the age of 36 in Boston, but increases the risk of recidivism for the other ex-inmates in the treatment group.
A SWIMMING MEMS DEVICE

Small scale swimming systems have received an increasing attention from the academic community during the last decade. This study is an investigation of a motion effector that departs from commonly seen in nature, highly flexible and compliant flagella. We propose that a rigid, spring like variant of flagella manufactured by current microelectromechanical-devices technology can provide an alternative to concepts based on bio mimicry of flexible organs of natural microorganisms. For validating the concept of propulsion in viscous media using a rigid, small motion amplitude effector, we modeled a Fluid Structure Interaction simulation.
Decreased FOXF2 mRNA Expression Indicates Early-Onset Metastasis and Poor Prognosis for Breast Cancer Patients with Histological Grade II Tumor

The transcription factor, FOXF2, plays an important role in tissue development, extracellular matrix synthesis, and epithelial-mesenchymal interactions, implying that it may be associated with the metastatic capabilities of cancer cells. However, the relationship between FOXF2 expression and breast cancer progression, metastasis, and prognosis, remains to be elucidated. In this study, FOXF2 mRNA levels in 305 primary breast cancer tissues were examined using RT-QPCR. Results showed that FOXF2 mRNA levels in primary breast cancer were negatively associated with tumor progression, including tumor size, number of metastatic lymph nodes, and clinical stage. Patients with low FOXF2 mRNA levels had a high risk of relapse and metastasis within three years. Low FOXF2 mRNA levels could predict shorter disease-free survival for those patients with histological grade II and triple-negative breast cancer. Taken together, we conclude that decreased FOXF2 expression indicates the early-onset metastasis and poor prognosis for patients with histological grade II and triple-negative breast cancer.
Getting Noticed in Economics: The Determinants of Academic Citations

Academics strive for citations, but there has been little work done to identify the determinants of citations, primarily due to a lack of usable data. This paper uses new data to confirm the intuition that reputation, documented research, collaboration, and signalling are important. However, the results shed new light on (and refute) some widely held conceptions about the effects of self-citation, author experience, editor biases, and gender equality.
Multilevel Computational Creativity

Creativity can hardly be understood in isolation from a context where values such as novelty and usefulness are ascribed. This paper presents a multi-level perspective for the study of creativity and formulates a framework for computational creativity that consists of 1) Culture; 2) Society; 3) Groups; 4) Products; 5) Personality; 6) Cognition, 7) Neural processes; and 8) CC processes. This model enables the definition of functional relationships among these levels. As an initial step to illustrate its usefulness, an analysis is made of the ICCC’12 proceedings in view of this model.