Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and validation of numerical habitat models for juveniles of Atlantic salmon ( Salmo salar ) 1

We evaluated the ability of numerical habitat models (NHM) to predict the distribution of juveniles of Atlan tic salmon (Salmo salar ) in a river. NHMs comprise a hydrodynamic model (to predict water depth and current speed for any given flow) and a biological model (to predict habitat quality for fish using water depth, current speed, and substrate composition). We implemented NHMs with a biological model based on ( i) preference curves defined by the ratio of the use to the availability of physical conditions and ( ii ) a multivariate logistic regression that distinguished be tween the physical conditions used and avoided by fish. Preference curves provided a habitat suitability index (HSI) ranging from 0 to 1, and the logistic regression produced a habitat probabilistic index (HPI) representing the probabil ity of observing a parr under given physical conditions. Pearson’s correlation coefficients between HSI and local densi ties of parr ranged from 0.39 to 0.63 depending on flow. Corresponding values for HPI ranged from 0.81 to 0.98. We concluded that HPI may be a more powerful biological model than HSI for predicting local variations in fish density, forecasting fish distribution patterns, and performing summer habitat modelling for Atlantic salmon juveniles. Résumé: Nous avons évalué la capacité de deux modèles numériques d’habitat (MNH) à prédire la distribution spa tiale des juvéniles de saumon atlantique ( Salmo salar ) en rivière. Les MNH comprennent un modèle hydrodynamique (pour prédire la vitesse moyenne et la profondeur de la colonne d’eau) et un modèle biologique (pour prédire la qualité d’habitat piscicole selon la profondeur, la vitesse moyenne et la composition du substrat). Nous avons utilisé les MNH avec un modèle biologique basé sur ( i) des courbes de préférences définies par le rapport entre l’utilisation et la disponibilité de conditions physiques et ( ii ) une régression logistique multiple permettant de différencier les conditions physiques utilisées de celles évitées par les tacons. Les courbes de préférences ont fourni un indice de qualité d’habitat (IQH) variant entre 0 et 1 et la régression logistique a donné un indice probabiliste de qualité d’habitat (IPH) représentant la probabilité d’observer des tacons sous des conditions physiques spécifiques. Les coefficients de corrélation de Pearson entre IQH et les densités locales de tacons ont varié entre 0,39 et 0,63 selon le débit. Les valeurs correspondantes en utilisant IPH ont varié entre 0,81 et 0,98. Nous avons conclu que l’IPH peut être un modèle biologique plus performant que l’IQH pour prédire les variations locales de la densité des poissons, pour prédire les patrons de distri bution des poissons et pour modéliser l’habitat estival des juvéniles du saumon atlantique.
Assessing the impact of pedigree quality on the validity of quantitative genetic parameter estimates

Investigating the evolutionary dynamics of complex traits in nature requires the accurate assessment of their genetic architecture. Using a quantitative genetic (QG) modeling approach (e.g., animal model), relatedness information from a pedigree combined with phenotypic measurements can be used to infer the amount of additive genetic variance in traits. However, pedigree information from natural systems is not perfect and might contain errors or be of low quality. Published sensitivity analyses revealed a limited impact of expected error rates on parameter estimates. However, natural systems will differ in many respects (e.g., mating system, data availability, pedigree structure), thus it can be inappropriate to generalize outcomes from one system to another. French-Canadian (FC) genealogies are extensive and deep-rooted (up to 9 generations in this study) making them ideal to study how the quality and properties (e.g., errors, completeness) of pedigrees affect QG estimates. We conducted simulation analyses to infer the reliability of QG estimates using FC pedigrees and how it is impacted by genealogical errors and variation in pedigree structure. Broadly, results show that pedigree size and depth are important determinants of precision but not of accuracy. While the mean genealogical entropy (based on missing links) seems to be a good indicator of accuracy. Including a shared familial component into the simulations led to on average a 46% overestimation of the additive genetic variance. This has crucial implications for evolutionary studies aiming to estimate QG parameters given that many traits of interest, such as life history, exhibit important non-genetic sources of variation.
Effects of Dohsa-method induced Positive Mind-body Experiences on Enhancing Nostalgic Affects 懐かしさの感情を高揚させる動作法の快適な心身の体験

こんの よしたか 文教大学人間科学部 よしかわ のぶよ 文教大学人間科学研究科 Abstract: This study examined the effects of positive mind-body experiences on enhancing nostalgic affects elicited by sound stimuli in college students. Experiment 1 examined the effects of the Dohsamethod relaxation on inducing positive mind-body experiences using a body experience scale, a multiple mood scale, and EEG pleasantness evaluation. Experiment 2 examined the effects of positive mind-body experiences on enhancing nostalgic affects with sound stimuli (“a bird’s song,” “the murmur of a stream,” etc.), using a 10-item affective scale consisting of two factors (“intimacy” and “painfulness"). Results indicated that the Dohsa-method relaxation did produce a positive mind-body state and an increased EEG pleasantness and enhanced nostalgic affects with the sound stimuli. These results suggest the possibility of developing a Dohsa-method-based life review therapy for the elderly.
Cardiovascular Data Registry ( 2007 Percutaneous Coronary Intervention : An Updated Report from the National Adoption of Radial Access and Comparison of Outcomes to Femoral Access in

Garratt, Robert N. Piana, William B. Hillegass, Mauricio G. Cohen, Ian C. Gilchrist and Sunil K. Kim, S. Chiu Wong, Robert M. Minutello, John C. Messenger, Issam Moussa, Kirk N. Dmitriy N. Feldman, Rajesh V. Swaminathan, Lisa A. Kaltenbach, Dmitri V. Baklanov, Luke 2012) − Cardiovascular Data Registry (2007 Percutaneous Coronary Intervention: An Updated Report from the National Adoption of Radial Access and Comparison of Outcomes to Femoral Access in Print ISSN: 0009-7322. Online ISSN: 1524-4539 Copyright © 2013 American Heart Association, Inc. All rights reserved. is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231 Circulation doi: 10.1161/CIRCULATIONAHA.112. 000536 2013;127:2295-2306 Circulation. http://circ.ahajournals. org/content/127/23/2295 World Wide Web at: The online version of this article, along with updated information and services, is located on the
DNB STAFF REPORTS

In this paper we investigate Dutch corporate liquidity management in general, and target adjustment behaviour in particular. To this purpose, we use a simple error correction model of corporate liquidity holdings applied to firm-level data for the period 1977-1997. We confirm the existence of long-run liquidity targets at the firm level. We also find that changes in liquidity holdings are driven by short-run shocks as well as the urge to converge towards targeted liquidity levels. The rate of target convergence is higher when we include more firm-specific information in the target. This result supports the idea that the degree of error in defining liquidity targets associates negatively with the observed rate of target convergence. It also suggests that the slow speeds of adjustment obtained in many macro studies on money demand are artefacts of aggregation bias. JEL Classification: C33; C43; E41; G3
Enteric Glial Cell Network Function is Required for Epithelial Barrier Restitution following Intestinal Ischemic Injury in the Early Postnatal Period

Ischemic damage to the intestinal epithelial barrier, such as in necrotizing enterocolitis or small intestinal volvulus, is associated with higher mortality rates in younger patients. We have recently reported a powerful pig model to investigate these age-dependent outcomes in which mucosal barrier restitution is strikingly absent in neonates but can be rescued by direct application of homogenized mucosa from older, juvenile pigs by a yet-undefined mechanism. Within the mucosa, a postnatally developing network of enteric glial cells (EGC) is gaining recognition as a key regulator of the mucosal barrier. Therefore, we hypothesized that the developing EGC network may play an important role in coordinating intestinal barrier repair in neonates. Neonatal and juvenile jejunal mucosa recovering from surgically induced intestinal ischemia was visualized by scanning electron microscopy and the transcriptomic phenotypes were assessed by bulk RNA sequencing. EGC network density and gliosis were examined by gene set enrichment analysis, three-dimensional volume imaging and western blot and its function in regulating epithelial restitution assessed ex vivo in Ussing chamber using the glia-specific inhibitor fluoroacetate, and in vivo by co-culture assay. Here we refine and elaborate our translational model, confirming a neonatal phenotype characterized by a complete lack of coordinated reparative signaling in the mucosal microenvironment. Further, we report important evidence that the subepithelial EGC network changes significantly over the early postnatal period and demonstrate that EGC function in close proximity to wounded intestinal epithelium is critical to intestinal barrier restitution following ischemic injury. NEW & NOTEWORTHY This study refines a powerful translational pig model, defining an age-dependent relationship between enteric glia and the intestinal epithelium during intestinal ischemic injury and confirming an important role of the enteric glial cell activity in driving mucosal barrier restitution. This study suggests that targeting the enteric glial network could lead to novel interventions to improve recovery from intestinal injury in neonatal patients.
Machine-learning interatomic potential for radiation damage and defects in tungsten

We introduce a machine-learning interatomic potential for tungsten using the Gaussian Approximation Potential framework. We specifically focus on properties relevant for simulations of radiation-induced collision cascades and the damage they produce, including a realistic repulsive potential for the short-range many-body cascade dynamics and a good description of the liquid phase. Furthermore, the potential accurately reproduces surface properties and the energetics of vacancy and self-interstitial clusters, which have been long-standing deficiencies of existing potentials. The potential enables molecular dynamics simulations of radiation damage in tungsten with unprecedented accuracy.
CLAY FLOCCULATION WITH A NATURAL POLYELECTOLYTE

The flocculation performance by using biological flocculants (BFs) extracted from Moroccan cactus pads of Opuntia Ficus Indica (OFI) for turbidity removal was investigated. The results showed that BFs were able to eliminate turbidity from natural clay solution over a wide dosage range (initial turbidity about 1000 Nephelometric Turbidity Unit (NTU)). The removal efficiency with BFs reached 98.6 % on average at pH 12.4 adjusted with lime, higher than 62 % with a new Chelating-Soluble extract (CP) from cladode also. For bioflocculants, bridging flocculation other than charge neutralization should be responsible for turbidity removal. The combined applications of CP with H2SO4 increased overall turbidity up to -238 %; from an initial turbidity of about 76 NTU to 257 NTU. It was also shown that combination of BFs and H2SO4 was effective for removing turbidity from raw water and can achieve 94% with a residual turbidity about 10 NTU at pH 2.0. This study provides a proof-in-concept demonstration of BFs for water purification, which can in part reduce operational costs in flocculation treatment, as well, effectively reduce the concentration of residual metallic elements (e.g. aluminum) used as coagulant.
Jet charge modification in dense QCD matter

In these proceedings we report a recent calculation of the jet charge modification in heavy-ion relative to proton collisions at the LHC. Jets have played an essential role in constraining theories of in-medium parton shower evolution and in determining the properties of the quark-gluon plasma created in ultra-relativistic nuclear reactions. It is important to extend these studies to flavor-tagged jets and explore observables that are sensitive to their partonic origin. The average jet charge, introduced early on in the history of quantum chromodynamics, is a proxy for the electric charge of the quark or gluon that initiates the jet. In the framework of soft-collinear effective theory, we show how to evaluate the jet charge in a dense strongly-interacting matter environments. We identify observables that can isolate the contribution of in-medium branching from isospin effects and present predictions for the transverse momentum dependence of the jet charge distribution in nucleus-nucleus collisions and its modification relative to the proton case.
Predictive value of early MRI fi ndings on neurocognitive and psychiatric outcomes in patients with severe traumatic brain injury

Background: Traumatic brain injury (TBI) is the major public health problem worldwide, particularly in the Middle East. Diffuse axonal injury (DAI) is commonly found in TBI. Although DAI can lead to physical and psychosocial disabilities, its prognostic value is still a matter of debate. Magnetic Resonance (MR) is more sensitive for detecting DAI lesions. Objective: To identify the radiological and clinical factors associated with the functional capacity one year after the traumatic brain injury. Methods: The study included 251 patients with severe head trauma for whom Brain MRI was done within one month after injury. Demographic, clinical, and radiological data were collected during hospitalization. Neurocognitive and psychiatric evaluation were done one year thereafter. Results: DAI was more frequent in our patients. Psychiatric disorders, cognitive impairment, and poor functional outcome were more common in patients with DAI especially those with cerebral hemisphere and brain stem lesion, and mixed lesions. Duration of post traumatic amnesia (DPTA), lost consciousness and hospital stay (DHS) as well as the volume of diffuse axonal injury (DAI) were associated with poor neurocognitive outcome. DPTA, and DAIV may be considered independent factors that could predict the neurocognitive outcome. Conclusion: MRI following traumatic brain injury yields important prognostic information, with several lesion patterns significantly associated with poor long-term neurocognitive and psychiatric outcomes.
Fungal community of necrotic and healthy galls in chestnut trees colonized by Dryocosmus kuriphilus (Hymenoptera, Cynipidae)

Abstract: Dryocosmus kuriphilus is a non-native pest that has recently spread through Europe with a special incidence along the Mediterranean Basin. The presence of this exotic wasp (originally from Asia) threatens stands and orchards of sweet chestnut (Castanea sativa Mill.) as it reduces tree growth and consequently fruit production. In this study the living mycobiota in leaves, healthy and necrotic galls collected from two sites in Cantabria (Northern Spain) was investigated. A total of twenty-two fungal taxa based on morphological and molecular traits were determined. In addition, we calculated fungal diversity and identified the dominant taxa among members of the mycobiota. Seven log-linear models were used to analyse whether fungal abundance varied between sites, types of plant material or fungal taxa. Our findings highlight the complex interactions between plant hosts, insect and the endophytic community, and are of potential interest in relation to the biological control of this important pest.
The Mystery of Good Teaching

WHO SHOULD BE RECRUITED TO fill the two to three million K–12 teaching positions projected to come open during the next decade? What kinds of knowledge and training should these new recruits have? These are the questions confronting policymakers as a generation of teachers retires at the same time that the so-called baby boom echo is making its way through the education system. Key to answering these questions is knowing how much influence teachers have over student achievement and what specific teacher attributes lead to higher student achievement. For instance, does holding a master’s degree make one a better teacher? Do the best teachers hail from elite universities? Did they earn high GPAs in college? Did they major in the subject they are teaching? How much does experience matter? Do traditional, university-based teacherpreparation programs produce the best teachers, or are alternatively certified teachers just as good? These questions are particularly relevant given that researchers have raised concerns about the overall quality of today’s teaching workforce. As measured by standardized test scores (mainly the SAT and the ACT), students choosing to major in education tend to be drawn from the lower end of the ability distribution. In Who Will Teach? , Harvard University professor of education Richard Murnane and his colleagues write:“College graduates with high test scores are less likely to take [teaching] jobs, employed teachers with high test scores are less likely to stay, and former teachers with high test scores are less likely to return. ” On average, according to the IL L U S T R A T IO N B Y A N D R E W J U D D /M A S T E R F IL E
WRF ATMOSPHERIC ICING VALIDATION FOR MOUNT ZAO , JAP AN , DURING 19-29 APRIL 2009

A mesoscale atmospheric model Weather Research & Forecasting (WRF, ver. 3.2.1) was used to reconstru ct mid-spring episodes of soft rime formation at the Mt. Zao, Jap an, during 1929 April 2009. One particularly interesting form of soft rime was observed at the Karitadake peak (1758 m). It was pr e ented by feather-looking opaque aggregates of granular ice 1 5-35 cm long, called “shrimp’s tale” in Japanese. Based on an ana lysis of modelgenerated results we could 1) find a good quantitat ive agreement of modeled and observed wind and temperature time s eries at Jizosancho ropeway station; 2) could identify two i cing events (lasting for 26-41 hours each, with temperatures be twe n −6.3o and −0.1oC, relatively constant westerly strong win ds up to 26 m s, and cloud liquid water content up to 0.72-1.05 g m). By considering the general synoptic situation for the simulation period, we found that both in-cloud icing episodes corresponded to a passage of low pressure systems; 3) confirm th at a high resolution modeling (1.1 km) was much more accurate than simulations with coarser grids (10 and 3.3 km).
Measuring the extent of a high performance work system: A mixed methodology approach

High performance work systems (HPWS) and their effect on firm performance is examined using a single holistic case study design in which the Total Strategic Resource Approach (TSRA) is used to measure the extent of HPWS implementation in a private Pakistani hospital. Using a mixed methodology case approach, it is discovered that Pakistan Hospital & Medical College (PHMC) has begun to implement aspects of an HPWS. Profound weaker human resource areas include information sharing and compensation although improvement is needed in all 12 HR practice areas. Firm performance was measured using perceptual measures of the organization’s employees, and it was determined that the HPWS does have a significantly positive effect on firm performance. The study was also designed to test the reliability of the TSRA for the Pakistani context given its unique cultural setting, and it was confirmed that the TSRA is a reliable model that future researchers can use in order to measure the extent of HPWS implementation in other Pakistani organizations.
Quantum anomalous Hall effect driven by magnetic proximity coupling in all-telluride based heterostructure

The quantum anomalous Hall effect (QAHE) is an exotic quantum phenomenon originating from dissipation-less chiral channels at the sample edge. While the QAHE has been observed in magnetically doped topological insulators (TIs), exploiting magnetic proximity effect on the TI surface from adjacent ferromagnet layers may provide an alternative approach to the QAHE by opening an exchange gap with less disorder than that in the doped system. Nevertheless, the engineering of a favorable heterointerface that realizes the QAHE based on the magnetic proximity effect remains to be achieved. Here, we report on the observation of the QAHE in a proximity coupled system of non-magnetic TI and ferromagnetic insulator (FMI). We have designed sandwich heterostructures of (Zn,Cr)Te/(Bi,Sb)2Te3/(Zn,Cr)Te that fulfills two prerequisites for the emergence of the QAHE; the formation of a sizable exchange gap at the TI surface state and the tuning of the Fermi energy into the exchange gap. The efficient proximity coupling in the all-telluride based heterostructure as demonstrated here will enable a realistic design of versatile tailor-made topological materials coupled with ferromagnetism, ferroelectricity, superconductivity, and so on.
NLNL: Negative Learning for Noisy Labels

Convolutional Neural Networks (CNNs) provide excellent performance when used for image classification. The classical method of training CNNs is by labeling images in a supervised manner as in ``input image belongs to this label'' (Positive Learning; PL), which is a fast and accurate method if the labels are assigned correctly to all images. However, if inaccurate labels, or noisy labels, exist, training with PL will provide wrong information, thus severely degrading performance. To address this issue, we start with an indirect learning method called Negative Learning (NL), in which the CNNs are trained using a complementary label as in ``input image does not belong to this complementary label. '' Because the chances of selecting a true label as a complementary label are low, NL decreases the risk of providing incorrect information. Furthermore, to improve convergence, we extend our method by adopting PL selectively, termed as Selective Negative Learning and Positive Learning (SelNLPL). PL is used selectively to train upon expected-to-be-clean data, whose choices become possible as NL progresses, thus resulting in superior performance of filtering out noisy data. With simple semi-supervised training technique, our method achieves state-of-the-art accuracy for noisy data classification, proving the superiority of SelNLPL's noisy data filtering ability.