Miracle-dz/UniFAR-FTUs huggingface dataset:
Microbial Community Dynamics Associated with Rhizosphere Carbon Flow

ABSTRACT Root-deposited photosynthate (rhizodeposition) is an important source of readily available carbon (C) for microbes in the vicinity of growing roots. Plant nutrient availability is controlled, to a large extent, by the cycling of this and other organic materials through the soil microbial community. Currently, our understanding of microbial community dynamics associated with rhizodeposition is limited. We used a 13C pulse-chase labeling procedure to examine the incorporation of rhizodeposition into individual phospholipid fatty acids (PLFAs) in the bulk and rhizosphere soils of greenhouse-grown annual ryegrass (Lolium multiflorum Lam. var. Gulf). Labeling took place during a growth stage in transition between active root growth and rapid shoot growth on one set of plants (labeling period 1) and 9 days later during the rapid shoot growth stage on another set of plants (labeling period 2). Temporal differences in microbial community composition were more apparent than spatial differences, with a greater relative abundance of PLFAs from gram-positive organisms (i15:0 and a15:0) in the second labeling period. Although more abundant, gram-positive organisms appeared to be less actively utilizing rhizodeposited C in labeling period 2 than in labeling period 1. Gram-negative bacteria associated with the 16:1ω5 PLFA were more active in utilizing 13C-labeled rhizodeposits in the second labeling period than in the first labeling period. In both labeling periods, however, the fungal PLFA 18:2ω6,9 was the most highly labeled. These results demonstrate the effectiveness of using 13C labeling and PLFA analysis to examine the microbial dynamics associated with rhizosphere C cycling by focusing on the members actively involved.
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking

There is a growing interest in large-scale machine learning and optimization over decentralized networks, e.g. in the context of multi-agent learning and federated learning. Due to the imminent need to alleviate the communication burden, the investigation of communication-efficient distributed optimization algorithms --- particularly for empirical risk minimization --- has flourished in recent years. A large faction of these algorithms have been developed for the master/slave setting, relying on the presence of a central parameter server that can communicate with all agents. This paper focuses on distributed optimization over the network-distributed or the decentralized setting, where each agent is only allowed to aggregate information from its neighbors over a network (namely, no centralized coordination is present). By properly adjusting the global gradient estimate via a tracking term, we develop a communication-efficient approximate Newton-type method, called Network-DANE, which generalizes DANE [Shamir et al., 2014] for decentralized networks. We establish linear convergence of Network-DANE for quadratic losses, which shed light on the impact of data homogeneity and network connectivity upon the rate of convergence. Our key algorithmic ideas can be applied, in a systematic manner, to obtain decentralized versions of other master/slave distributed algorithms. A notable example is our development of Network-SVRG, which employs stochastic variance reduction [Johnson and Zhang, 2013] at each agent to accelerate local computation. The proposed algorithms are built upon the primal formulation without resorting to the dual. Numerical evidence is provided to demonstrate the appealing performance of our algorithms over competitive baselines, in terms of both communication and computation efficiency.
Building 3D Morphable Models from a Single Scan - Supplementary Material

In our main paper we build 3DMMs using Gaussian processes that include symmetry and color-channel correlation heuristics. To assess the effects of these heuristics individually, we can also build 3DMMs that include only one of these heuristics. Specifically, we experimented with constructing 3DMMs whose albedo models have correlated color channels but which lack symmetry. This enables us to compare the relative importance in an analysis-by-synthesis setting of the symmetry and color-correlation heuristics of our symmetric 3DMMs. Our main paper defined albedo kernels Kcor a,xyz and K a,rgb. These kernels possess a color-channel correlation heuristic but lack an explicit symmetry heuristic (K a,rgb is symmetric, but this is only because we assume that the reference face is symmetric). We may average these kernels to produce an albedo kernel Kcor a = 0.5(K sym a,rgb +K cor a,xyz) which combines physical-space and RGB-space distance information. Samples from Kcor a,xyz and K cor a are shown in Figure 1. By combining these albedo kernels with our shape kernel Ka, we can construct 3DMMs which possess a color-channel correlation heuristic but which lack an explicit symmetry heuristic. We list these 3DMMs in Table 1.
Comparison of clonal relatedness and antimicrobial susceptibility of fecal Escherichia coli from healthy dogs and their owners

AJVR, Vol 70, No. 9, September 2009 A strong human-animal bond exists for companion animals, with up to 99% of dog and cat owners considering their pets to be part of their family. Close relationships between dogs and their owners raise public health concerns regarding transmission of infectious organisms between species. Dogs have been considered a potential reservoir for Escherichia coli capable of causing urinary tract infections in women Comparison of clonal relatedness and antimicrobial susceptibility of fecal Escherichia coli from healthy dogs and their owners
Effects of Joint Mobilization on Foot Pressure, Ankle Moment, and Vertical Ground Reaction Force in Subjects with Ankle Instability

Objective: The purpose of this study was to investigate the effects of joint mobilization on foot pressure,ankle moment, and vertical ground reaction force in subjects with ankle instability.Method: Twenty male subjects (age, 25.38 ± 3.62 yr; height, 170.92 ± 5.41 cm; weight, 60.74 ± 9.63 kg;body mass index (BMI), 19.20 ± 1.67 kg/m2) participated and underwent ankle joint mobilization. Weightbearingdistribution, ankle dorsi/plantar flexion moment, and vertical ground reaction force were measuredusing a GPS 400 and a VICON Motion System (Oxford, UK), and subsequently analyzed. SPSS 20.0 forWindows was used for data processing and paired t-tests were used to compare pre- and post-mobilizationmeasurements. The significance level was set at α = . 05.Results: The results indicated changes in weight-bearing, ankle dorsi/plantar flexion moment, and verticalground reaction force. The findings showed changes in weight-bearing distribution on the left (pre 29.51± 6.31 kg, post 29.57 ± 5.02 kg) and right foot (pre 32.40 ± 6.30 kg, post 31.18 ± 5.47 kg). There weresignificant differences in dorsi/plantar flexion moment (p < .01), and there were significant increases invertical ground reaction forces at initial stance (Fz1) and terminal stance (Fz2, p < .05). Additionally, therewas a significant reduction in vertical ground reaction force at midstance (Fz2, p < .001). Conclusion: Joint mobilization appears to alter weight-bearing distribution in subjects with ankle instability,with resultant improvements in stability.
Fish and broiler optimal harvesting models in imprecise environment

In this paper, a two-species harvesting model has been considered and developed a solution procedure which is able to calculate the equilibrium points of the model where some biological parameters of the model are interval numbers. A parametric mathematical program is formulated to find the biological equilibrium of the model for different values of parameters. This interval-valued problem is converted into an equivalent crisp model using interval mathematics. The main advantage of the proposed procedure is that different characteristics of the model can be presented in a single framework. Analytically, the existence of steady state and stabilities are looked into. Using mathematical software, the model is illustrated and the results are obtained and presented in tabular and graphical forms.
Coupling dynamics of 2D Notch-Delta signalling

Understanding pattern formation driven by cell-cell interactions has been a significant theme in cellular biology for many years. In particular, due to their implications within many biological contexts, lateral-inhibition mechanisms present in the Notch-Delta signalling pathway led to an extensive discussion between biologists and mathematicians. Deterministic and stochastic models have been developed as a consequence of this discussion, some of which address long-range signalling by considering cell protrusions reaching non-neighbouring cells. The dynamics of such signalling systems reveal intricate properties of the coupling terms involved in these models. In this work, we examine the benefits and limitations of new and existing models of cell signalling and differentiation in a variety of contexts. Using linear and weakly nonlinear stability analyses, we find that pattern selection relies on nonlinear effects that are not covered by such analytical methods.
The MADP Toolbox: An Open Source Library for Planning and Learning in (Multi-)Agent Systems

©2017 Frans A. Oliehoek, Matthijs T. J. Spaan, Bas Terwijn, Philipp Robbel and Joao V. Messias. This article describes the Multiagent Decision Process (MADP) Toolbox, a software library to support planning and learning for intelligent agents and multiagent systems in uncertain environments. Key features are that it supports partially observable environments and stochastic transition models; has unified support for single- and multiagent systems; provides a large number of models for decision-theoretic decision making, including one-shot and sequential decision making under various assumptions of observability and cooperation, such as Dec-POMDPs and POSGs; provides tools and parsers to quickly prototype new problems; provides an extensive range of planning and learning algorithms for single- and multiagent systems; is released under the GNU GPL v3 license; and is written in C++ and designed to be extensible via the object-oriented paradigm.
Apprentissage d'un vocabulaire symbolique pour la détection d'objets dans une image

Nous etudions le probleme fondamental de la selection de variables descriptives d'un signal, selection dediee a divers traitements comme la classification d'objets dans une image. Nous definissons dans un premier temps une loi de probabilites sur les variables descriptives du signal et utilisons un algorithme de descente de gradient, exact puis stochastique pour identifier la bonne distribution de probabilites sur ces variables. Nous donnons alors diverses applications a la classification d'objets (chiffres manuscrits, detection de visages, de spam,. . . ). Dans un second temps, nous implementons un algorithme de diffusion reflechie sur l'espace des probabilites puis de diffusion reflechie avec sauts pour permettre plus facilement de faire evoluer l'espace des variables, ainsi que la probabilite apprise. Cette seconde approche necessite un effort particulier au niveau des simulations stochastiques, qui sont alors etudiees le plus clairement possible. Nous concluons par quelques experiences dans les memes domaines que precedemment.
Working Papers Department of Economics University of Vienna Evidence on the Insurance Effect of Redistributive Taxation *

and at the EUI for comments on a very early draft. We also thank Tim Storey at the National Conference of State Legislatures for providing data on state political affiliations. All errors remain our own. Correspon-Abstract We show that redistributive tax and transfer systems have a distortionary effect and an insurance effect, if agents face idiosyncratic uninsurable earnings risk. These two effects imply that redistributive taxes decrease both mean consumption and the standard deviation of consumption. Using household data, we construct an 'income compression' measure of the redistributiveness of the tax system and empirically test for the presence of these two effects by exploiting differences in US state taxes. We find that tax redistributiveness explains much of the variation in the mean and standard deviation of the within-state consumption distributions over the US. This provides evidence for the presence of both distortionary and insurance effects of redistributive taxes and transfers.
Transformative Social and Emotional Learning (SEL): Toward SEL in Service of Educational Equity and Excellence

This article seeks to develop transformative social and emotional learning (SEL), a form of SEL intended to promote equity and excellence among children, young people, and adults. We focus on issues of race/ethnicity as a first step toward addressing the broader range of extant inequities. Transformative SEL is anchored in the notion of justice-oriented citizenship, and we discuss issues of culture, identity, agency, belonging, and engagement as relevant expressions of the Collaborative for Academic, Social and Emotional Learning 5 core competencies. We also point to programs and practices that hold promise for cultivating these competencies and the importance of adult professional development in making these efforts maximally effective for diverse children and youth. We conclude by offering a few next steps to further advance transformative SEL research and practice.
Dimethyl sulfoxide ( DMSO ) exacerbates cisplatin-induced sensory hair cell death in zebrafish ( Danio rerio )

Inner ear sensory hair cells die following exposure to aminoglycoside antibiotics or chemotherapeutics like cisplatin, leading to permanent auditory and/or balance deficits in humans. Zebrafish (Danio rerio) are used to study drug-induced sensory hair cell death since their hair cells are similar in structure and function to those found in humans. We developed a cisplatin dose-response curve using a transgenic line of zebrafish that expresses membrane-targeted green fluorescent protein under the control of the Brn3c promoter/enhancer. Recently, several small molecule screens have been conducted using zebrafish to identify potential pharmacological agents that could be used to protect sensory hair cells in the presence of ototoxic drugs. Dimethyl sulfoxide (DMSO) is typically used as a solvent for many pharmacological agents in sensory hair cell cytotoxicity assays. Serendipitously, we found that DMSO potentiated the effects of cisplatin and killed more sensory hair cells than treatment with cisplatin alone. Yet, DMSO alone did not kill hair cells. We did not observe the synergistic effects of DMSO with the ototoxic aminoglycoside antibiotic neomycin. Cisplatin treatment with other commonly used organic solvents (i.e. ethanol, methanol, and polyethylene glycol 400) also did not result in increased cell death compared to cisplatin treatment alone. Thus, caution should be exercised when interpreting data generated from small molecule screens since many compounds are dissolved in DMSO. Citation: Uribe PM, Mueller MA, Gleichman JS, Kramer MD, Wang Q, et al. (2013) Dimethyl Sulfoxide (DMSO) Exacerbates Cisplatin-induced Sensory Hair Cell Death in Zebrafish (Danio rerio). PLoS ONE 8(2): e55359. doi:10.1371/journal.pone. 0055359 Editor: Sheng-Ping Lucinda Hwang, Institute of Cellular and Organismic Biology, Taiwan Received August 24, 2012; Accepted December 28, 2012; Published February 1, 2013 Copyright: 2013 Uribe et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported by Pomona College, National Institutes of Health (NIH) DC010998 (JIM), NIH DC010231 (PSS, MSV, RMS), Harvard College (MAM, MDK), and Sarah Fuller Funder (DAC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: Senior author Jonathan I. Matsui is a PLOS ONE Editorial Board member. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials. * E-mail: Jonathan.Matsui@pomona.edu . These authors contributed equally to this work.
THE FIRST PHOTOMETRIC ANALYSES OF THE ALGOL BINARY SYSTEMS GSC 04328-02164 AND GSC 03164-01558

The CCD observations for the eclipsing Algol type binary systems GSC 04328-02164 in wideband BVRcIc filters and GSC 03164-01558 in B and I filters have been analyzed using the PHOEBE package (v 0.31a) to determine their orbital and physical parameters. The absolute parameters and evolutionary tracks of the two systems have been determined. The results show that the mass ratio, inclination, distance, and age for the system GSC 04328-02164 are equal to q = 0.674 ± 0.002, i = 75.997 ± 0.022, d = 375.477 ± 4.299 pc, and τ = 26.76 ± 15.65 ∗ 108 years, respectively. For the other system, GSC 03164-01558, q = 0.941 ± 0.006, i = 88.0484 ± 0.030, d = 444.651 ± 9.444 pc, and τ = 53.63 ± 9.16 ∗ 108 years.
Implementation and Evaluation of Obstetric Early Warning Systems in tertiary care hospitals in Nigeria

Aminu Umar (  amin.umar@nhs.net ) Health Education North East: Health Education England North East https://orcid.org/0000-0002-9901946X Saidu Ibrahim University of Ilorin Teaching Hospital Idris Liman National Hospital Abuja Calvin Chama Abubakar Tafawa Balewa University Teaching Hospital Munirdeen Ijaiya University of Ilorin Teaching Hospital Matthews Mathai Liverpool School of Tropical Medicine Charles Ameh Liverpool School of Tropical Medicine
The Need-Adapted Approach in psychosis: the impact of psychosis on the treatment, the psychiatrists, and other professionals

Psychosis is a challenging phenomenon for professionals. In the Need-Adapted Approach (NAA), therapy meetings constitute a deliberate effort to meet the challenges by bringing all the main parties together within a common discussion. The aims of this study are to analyze and evaluate psychiatrists’ experiences of the treatment processes in psychosis. A qualitative multiple case study approach has been used. Between August 2007 and January 2009 coresearch interviews (CR-Is) and stimulated-recall interviews (STR-Is) with ten psychiatrists from three different part of Finland were videoed and transcribed verbatim. The material was analyzed using qualitative content analysis. The difficult emotions of the professionals and the critical views expressed had a prominent role. It was almost impossible to proceed with the treatment until the memories of coercive acts had been addressed. There were fewer harmful effects in outpatient than in inpatient care. If the client-centered principles of NAA were not followed, the CR-Is functioned primarily as critical evaluations of the treatment processes. The STR-Is helped the psychiatrists to find words for difficult experiences. For the sake of both practice and research, the experiences of staff in the treatment of psychosis should be taken into account. For better prediction of failure, routine measures to obtain feedback could be included
Calculating the misspecification in beta from using a proxy for the market portfolio

This study investigates the effects of the market portfolio being unknown on the estimation of beta in the CAPM. Providing an analysis of the impact of using a proxy for the market portfolio when the market portfolio is known. This allows one to ask and answer ‘if what’ questions, such as if portfolio A is the true market portfolio, what happens to beta if one uses portfolio B as a proxy for A. It is shown that for a given universe of investible assets, frequently used equally weighted and value weighted portfolios are far from the Markowitz market portfolio and thus the betas calculated with the equally weighted and value weighted portfolios are quite different from those obtained with the Markowitz portfolio. These calculations are based on sequential assumptions that one portfolio is a proxy whilst another is the actual market.
COV-ELM classifier: An Extreme Learning Machine based identification of COVID-19 using Chest-Ray Images

Coronaviruses constitute a family of virus that gives rise to respiratory diseases. Coronavirus disease 2019 (COVID-19) is an infectious disease caused by a newly discovered coronavirus also termed as Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Due to its rapid spread, WHO has declared COVID-19 outbreak a pandemic on 11th March 2020. Reverse transcription-polymerase chain reaction (RT-PCR) test is popularly used worldwide for the detection of COVID-19. However, due to the high false-negative rate of RT-PCR test, chest X-ray (CXR) imaging is emerging as a feasible alternative for the detection of COVID-19. In this work, we propose a multiclass classification model COV-ELM, based on the extreme learning machine which classifies the CXR images into one of the three classes, namely COVID-19, normal, and pneumonia. The choice of ELM in this work has been motivated by its significantly short training time as compared to conventional gradient-based learning algorithms. After some preprocessing, we extract a pool of features based on texture and frequency. This pool of features serves as an input to the ELM and a 10-fold cross-validation method is employed to evaluate the proposed model. For experimentation, we use chest X-ray (CXR) images from three publicly available sources. The results of applying COV-ELM on test data are quite promising. The COV-ELM achieved a macro average F1-score of 0.95 and the overall sensitivity of ${0.94 \pm 0.02}$ at 95% confidence interval. When compared to state-of-the-art machine learning algorithms, the COV-ELM is found to outperform in a three-class classification scenario. The main advantage of COV-ELM is that its training time being quite low, as bigger and diverse datasets become available, it can be quickly retrained as compared to its gradient-based competitor models.
Lower bounds for zero energy eigenfunctions of Schrödinger operators

Soit g une solution non nulle dans L 2 (R n ), n≥2, de (−Δ+V)g=0. Si le potentiel V s'annule assez rapidement a l'infini, alors g ne peut pas decroitre (au sens L 2 ) plus rapidement qu'une puissance de |x|
Ein Ansatz zur qualitativen Modellierung und Regelung dynamischer Systeme

A linear discrete-time continuous-variable system is considered for which only a quantised state measurement is available. It is shown that the qualitative behaviour of the system is nondeterministic and, thus, nondeterministic or stochastic automata represent reasonable forms of qualitative models. On the basis of such models, a qualitative regulator is designed. The results are illustrated by means of the pole balancing problem