Miracle-dz/UniFAR-FTUs huggingface dataset:
A Neural-Functionalist Approach to Learning

Researchers within the field of learning have traditionally divided their empirical world according to methodology, with phenomena classified as single stimulus learning, Pavlovian conditioning, or in- strumental learning. This trichotomy, a vestige of our behaviorist past, continues to influence the field, both in the classroom and in the laboratory. Relying on data collected using a simple model system (learning within the mammalian spinal cord), evidence is presented that organisms can learn about an environmental relationship in multiple ways, an observation that argues against a simple isomorphism between methodology and mechanism. It is suggested that a new classification system is needed that focuses on mechanism rather than methodology, subdividing our empirical world along lines that make sense given commonalties in the neural-functional mechanisms involved. For over a century, learning has remained a central force within psychol- ogy. Introductory students hear of Thorndike (1898), Pavlov (1927), and Skinner (1938), and advanced students routinely take a course on learning to fulfill their core requirements. It was learning theorists (e.g., Hull, 1943; Watson, 1913; also see Boakes, 1984) who sold psychologists on the value of studying animal behav- ior, providing evidence that we and our evolutionary brethren often adjust to new situations in a similar fashion. This proof of principle laid the foundation for the study of the neurobiology of learning and memory, an enterprise that relies primar- ily on infrahuman creatures, from simple invertebrates (Kandel & Schwartz, 1982) to primates (Mishkin, 1982). The field of learning has remained a central focus of investigation primar- ily because many endorse its core assumptions. The first core assumption is that learning is essential. Natural selection cannot prepare a response for every situa- tion that an organism might encounter. The range of environmental situations is simply too great and biologically relevant stimuli often occur in an unpredictable
Performance and economic viability of protein supplementation for grazing cattle steers in the wet and dry-wet transition season

The objective was to evaluate performance and economic viability of protein supplementation of grazing beef cattle in the wet and dry-wet transition season. Eighty non-castrated Nellore steers, body weight of 371 ± 11.3 kg were used in the experiment. The treatments were the following: SM – Mineral supplement; Protein mineral supplements (SMP 20% FS - soybean meal: 410 g/animal; SMP 40% UR - urea: 223 g/animal; and SMP 40% UP - protect urea: 236 g/animal). It was used a complete random design with 20 replicates per treatment. There was a difference in the results (P 0.10) of treatments on the rate of accumulation of fat in the rump region. All treatments presented a positive net margin. The best net margin was observed for treatment PMS 40% UP, that is, R$123.92 per animal/period, whereas the smallest was observed in treatment PMS 20% FS, that is, R$98.91 per animal/period. Protein supplementation with a source of protected nitrogen can be used as a strategy to increase the performance of beef cattle on pasture of Brachiaria brizantha cv. Xaraes during the wet and dry-wet transition.
Establishing Causal Order in Longitudinal Studies Combining Binary and Continuous Dependent Variables

Longitudinal studies with a mix of binary outcomes and continuous variables are common in organizational research. Selecting the dependent variable is often difficult due to conflicting theories and contradictory empirical studies. In addition, organizational researchers are confronted with methodological challenges posed by latent variables relating to observed binary outcomes and within-subject correlation. We draw on Dueker’s qualitative vector autoregression (QVAR) and Lunn, Osorio, and Whittaker’s multivariate probit model to develop a solution to these problems in the form of a qualitative short panel vector autoregression (QSP-VAR). The QSP-VAR combines binary and continuous variables into a single vector of dependent variables, making every variable endogenous a priori. The QSP-VAR identifies causal order, reveals within-subject correlation, and accounts for latent variables. Using a Bayesian approach, the QSP-VAR provides reliable inference for short time dimension longitudinal research. This is demonstrated through analysis of the durability of elite corporate agents, social networks, and firm performance in France. We provide our OpenBUGS code to enable implementation of the QSP-VAR by other researchers.
Nephrology Dialysis Transplantation An EDTA Registry for the year 2000 ?

Close collaboration between various centres, covering large populations has become a prerequisite for progress in medicine. Critical assessment of therapeutic developments, a hall mark of Western medicine, relies more and more on large, expensive multi-centre studies, an impressive example of which is given by the recent Modification of Diet in Renal Disease (MDRD) study [1]. Evaluation of health care delivery also depends on the survey of large patient populations as illustrated by the study of Parker et al. on the prognostic value of urea reduction ratio in dialysed patients [2]. The introduction of peer review of the performance of individual centres relies on the availability of adequate information on predefined populations in the same geographic area. The natural history of a variety of rare diseases can be defined only by gathering information scattered in different hospitals. Finally, information on the distribution of health care facilities has become a priority for health authorities.
One‐dimensional shock‐capturing for high‐order discontinuous Galerkin methods

Discontinuous Galerkin methods have emerged in recent years as an alternative for nonlinear conservation equations. In particular, their inherent structure (a numerical flux based on a suitable approximate Riemann solver introduces some stabilization) suggests that they are specially adapted to capture shocks. However, numerical fluxes are not sufficient to stabilize the solution in the presence of shocks. Thus, slope limiter methods, which are extensions of finite volume methods, have been proposed. These techniques require, in practice, mesh adaption to localize the shock structure. This is is more obvious for large elements typical of high‐order approximations. Here, a new approach based on the introduction of artificial diffusion into the original equations is presented. The order is not systematically decreased to one in the presence of the shock, large high‐order elements can be used, and several linear and nonlinear tests demonstrate the efficiency of the proposed methodology. Copyright © 2012 John Wiley & Sons, Ltd.
Printed Half-Circular Monopole Antenna for UWB Applications

In this paper, a printed half circular monopole antenna fed by a simple rectangular Microstrip line is investigated. This antenna was designed on Taconic RF-30 (tm) substrate, High-frequency structure simulator (HFSS) that evolved over a period of years with input from many users and industries was used to design, optimize, and simulate this antenna. The structural properties and performance characteristics of this antenna is investigated through numerical simulations. Then the design process, parametric study, optimization as well as simulated results such as return loss, radiation patterns and VSWR are provided. We found that the -10dB return loss bandwidth of the simulated antenna is approximately 7.1GHz (3.2GHz – 10.3GHz). The proposed half circular patch UWB Monopole antenna is having better performance and good bandwidth than the conventional circular patch UWB monopole antennas.
Minor Pediatric Head Trauma in the Emergency Unit

The management of children with minor TBI and radiographic findings of intracranial injury on CT is not clearly defined. Most head trauma in children is minor and not associated with brain injury or long-term sequel. A small number of children who appear to be at low risk after minor head trauma may have clinically important traumatic (ciTBI) brain injury. Children with clinically significant intracranial injuries require urgent identification to prevent further damage to the brain. This cause to use of head computed tomography (CT) in the evaluation of pediatric TBI. The rate of cranial CT use in children increased fivefold between 1995 and 2006 [5]. However, there is an increasing evidence of the risk associated with CT. As many as 1 in 1,200 children scanned will die secondary to malignancy caused by radiation exposure from diagnostic imaging [6,7]. Children may require sedation to allow imaging with consequent sedation associated risks [8]. They also have resource implication for EDs and health system [9].
Applying geometric morphometrics to compare changes in size and shape arising from finite elements analyses

We consider how the methods of geometric morphometrics (GM) might combine with functional simulations using finite elements analysis (FEA). In particular we are concerned with how the deformations arising from FEA might be compared and visualized using GM. To these ends we apply these methods to a study of coronal plane forces applied to a model of an armadillo femur. We simulate the stance phase in the hind limb where the femur is subject to bending strains due to longitudinal compressive as well as abduction loads on the greater trochanter. We use this model to examine the hypothesis that muscles attaching to the third trochanter can reduce these bending strains in the loaded femur. The analysis uses standard finite element methods to produce strain maps and examine the strains at 200 point locations on the femur, but we also use the locations of the 200 points to run novel geometric morphometric analyses to assess the gross deformation of the model under different loadings. These provide insights into the application and usefulness of geometric morphometric methods in interpreting the results of finite element analyses. With further mathematical, engineering and statistical development the combination of FEA and GMM should open up new avenues of investigation of skeletal form and function in evolutionary biology. Download the complete "Yellow Book" on "Virtual Morphology and Evolutionary Morphometrics in the new millenium".
Semantic workflows for benchmark challenges: Enhancing comparability, reusability and reproducibility

Benchmark challenges, such as the Critical Assessment of Structure Prediction (CASP) and Dialogue for Reverse Engineering Assessments and Methods (DREAM) have been instrumental in driving the development of bioinformatics methods. Typically, challenges are posted, and then competitors perform a prediction based upon blinded test data. Challengers then submit their answers to a central server where they are scored. Recent efforts to automate these challenges have been enabled by systems in which challengers submit Docker containers, a unit of software that packages up code and all of its dependencies, to be run on the cloud. Despite their incredible value for providing an unbiased test-bed for the bioinformatics community, there remain opportunities to further enhance the potential impact of benchmark challenges. Specifically, current approaches only evaluate end-to-end performance; it is nearly impossible to directly compare methodologies or parameters. Furthermore, the scientific community cannot easily reuse challengers’ approaches, due to lack of specifics, ambiguity in tools and parameters as well as problems in sharing and maintenance. Lastly, the intuition behind why particular steps are used is not captured, as the proposed workflows are not explicitly defined, making it cumbersome to understand the flow and utilization of data. Here we introduce an approach to overcome these limitations based upon the WINGS semantic workflow system. Specifically, WINGS enables researchers to submit complete semantic workflows as challenge submissions. By submitting entries as workflows, it then becomes possible to compare not just the results and performance of a challenger, but also the methodology employed. This is particularly important when dozens of challenge entries may use nearly identical tools, but with only subtle changes in parameters (and radical differences in results). WINGS uses a component driven workflow design and offers intelligent parameter and data selection by reasoning about data characteristics. This proves to be especially critical in bioinformatics workflows where using default or incorrect parameter values is prone to drastically altering results. Different challenge entries may be readily compared through the use of abstract workflows, which also facilitate reuse. WINGS is housed on a cloud based setup, which stores data, dependencies and workflows for easy sharing and utility. It also has the ability to scale workflow executions using distributed computing through the Pegasus workflow execution system. We demonstrate the application of this architecture to the DREAM proteogenomic challenge.
Effect of plant-mediated oxygen supply and drainage on greenhouse gas emission from a tropical peatland in Central Kalimantan, Indonesia

Abstract To evaluate the hypothesis that plant-mediated oxygen supplies decrease methane (CH4) production and total global warming potential (GWP) in a tropical peatland, the authors compared the fluxes and dissolved concentrations of greenhouse gases [GHGs; CH4, carbon dioxide (CO2) and nitrous oxide (N2O)] and dissolved oxygen (DO) at multiple peatland ecosystems in Central Kalimantan, Indonesia. Study ecosystems included tropical peat swamp forest and degraded peatland areas that were burned and/or drained during the rainy season. CH4 fluxes were significantly influenced by land use and drainage, which were highest in the flooded burnt sites (5.75 ± 6.66 mg C m−2 h−1) followed by the flooded forest sites (1.37 ± 2.03 mg C m−2 h−1), the drained burnt site (0.220 ± 0.143 mg C m−2 h−1), and the drained forest site (0.0084 ± 0.0321 mg C m−2 h−1). Dissolved CH4 concentrations were also significantly affected by land use and drainage, which were highest in the flooded burnt sites (124 ± 84 μmol L−1) followed by the drained burnt site (45.2 ± 29.8 μmol L−1), the flooded forest sites (1.15 ± 1.38 μmol L−1) and the drained forest site (0.860 ± 0.819 μmol L−1). DO concentrations were influenced by land use only, which were significantly higher in the forest sites (6.9 ± 5.6 μmol L−1) compared to the burnt sites (4.0 ± 2.9 μmol L−1). These results suggest that CH4 produced in the peat might be oxidized by plant-mediated oxygen supply in the forest sites. CO2 fluxes were significantly higher in the drained forest site (340 ± 250 mg C m−2 h−1 with a water table level of −20 to −60 cm) than in the drained burnt site (108 ± 115 mg C m−2 h−1 with a water table level of −15 to +10 cm). Dissolved CO2 concentrations were 0.6–3.5 mmol L−1, also highest in the drained forest site. These results suggested enhanced CO2 emission by aerobic peat decomposition and plant respiration in the drained forest site. N2O fluxes ranged from −2.4 to −8.7 μg N m−2 h−1 in the flooded sites and from 3.4 to 8.1 μg N m−2 h−1 in the drained sites. The negative N2O fluxes might be caused by N2O consumption by denitrification under flooded conditions. Dissolved N2O concentrations were 0.005–0.22 μmol L−1 but occurred at < 0.01 μmol L−1 in most cases. GWP was mainly determined by CO2 flux, with the highest levels in the drained forest site. Despite having almost the same CO2 flux, GWP in the flooded burnt sites was 20% higher than that in the flooded forest sites due to the large CH4 emission (not significant). N2O fluxes made little contribution to GWP.
A new approach for absorption enhancement in plasmonic photodetectors

A new structure for absorption enhancement in plasmonic MSM photodetector is presented. This structure contains a layer of SiO2 between gold and semiconductor layers. The SiO2 layer creates a more suitable path for light to penetrate under the metal layer, transmits the wave to both sides of the device, involves a greater part of semiconductor in electron-hole generation, and increases the coupling of light into the semiconductor. This construction is simulated using Lumerical FDTD. Absorption enhancement in this paper is 4 times greater than similar structures.
Isolation, characterization and antagonistic effect of phosphate solubilizing microorganisms from Vigna radiata L. Rhizospheric soil

Phosphorus, the second most important micronutrient required by the plants, next to nitrogen, is reported to be a critical factor of many crop production system, due to the fact that the limited availability in soluble forms in the soils (Xiao et al., 2011). Microbes present in the soil employ different strategies to make use of unavailable forms of phosphorus and in turn also help in making phosphorus available for plant to absorb. When phosphoric fertilizers are applied to the soil they often become insoluble (more than 70%) and are convert into complexes and in phosphate in the soil (Mittal et al., 2008 involved in the solubilization of insoluble phosphorus include bacteria, fungi, actinomycetes . Microorganisms and arbuscular mycorrhial (VAM) fungi (Khan et al., 2007; Wani et al., 2007; Xiao et al., 2009). Numerous rhizosphere microorganisms possessing phosphate solubilizing activity are reported (Mittal et al., 2008). Among the soil bacterial communities, ectorhizosphere strains from Bacillus and Pseudomonas(Wani et al., 2007). And endosymbiotic rhizobia have been described as effective phosphate solubilizers (Igualet al., 2001) strains from bacterial genera Pseudomonas, ISSN: 2319-7706 Volume 2 Number 5 (2013) pp. 83-88 http://www.ijcmas. com
Porphyromonas gingivalis gingipains induce a pro-inflammatory extracellular microenvironment : the role of PAR-2 and fibronectin.

POSTER PRESENTATIONS 1) “Engineering Biomimetic Hydrogels for induced recruitment of mesenchymal stem cells in vitro and in vivo” PS Lienemann, M Karlsson, A Sala, S Hoehnel, O Naveiras, JS Marschall, W Weber, MP Lutolf, and M Ehrbar. Tissue Engineering and Regenerative Medicine World Congress Vienna, Austria, (09/2012) 2) “Dichotomy of Porphyromonas gingivalis gingipains proteolytic activity: Differential degradation and stimulation of fibronectin in fibroblasts” J.S. Marschall, J.D. Ritzenthaler, B.A. Potempa, J Roman, J.S. Potempa, Research! Louisville September 2011 Annual Meeting, University of Louisville, Louisville, KY (10/2011) 3) “Porphyromonas gingivalis gingipains induce a pro-inflammatory extracellular microenvironment: The role of PAR-2 and fibronectin”. J.S. Marschall, J.D. Ritzenthaler, B.A. Potempa, J Roman, J.S. Potempa; Research! Louisville September 2012 Annual Meeting, University of Louisville, Louisville, KY (09/2012) 4) “Porphyromonas gingivalis gingipains promote self propagating inflammation”. J.S. Marschall, J.D. Ritzenthaler, B.A. Potempa, J. Roman, J.S. Potempa; Research! Louisville September 2014, University of Louisville, Louisville, KY (09/2014) 5) “Long-term Cell Demanded Release of TG-VEGF121 for the Development of Mature Vascular Networks In Vivo,” R.A. Largo*, J.S. Marschall, A. Banfi, V.M. Ramakrishnan, A. Ziogas, T. Sulser, K. Lorentz, J. Hubbell, M. Ehrbar, and D. Eberli, Tissue Engineering and Regenerative Medicine World Congress (TERMIS) 2012 Annual Meeting, Vienna, Austria (09/2012).
Phylogenetics: The Theory and Practice of Phylogenetic Systematics

INTRODUCTION SPECIES AND SPECIATION. SUPRASPECIFIC TAXA. PHYLOGENETIC TREES. CHARACTERS AND RECONSTRUCTION OF PHYLOGENIES. PHYLOGENETIC CLASSIFICATION. TAXONOMIC ALTERNATIVES TO THE PHYLOGENETIC SYSTEM. BIOGEOGRAPHY. SPECIMENS AND CURATION. CHARACTERS AND QUANTITATIVE CHARACTER ANALYSIS. PUBLICATION AND RULES OF NOMENCLATURE.
Does rainwater harvesting pay? water-energy nexus assessment as a tool to achieve sustainability in water management

Demographic growth that will take place on urban centers for the next decades may constitute a new challenge for water providers, which may then have to rely on more distant and/or poorer quality sources, or opt for energy-intensive technological solutions. In this context, the water–energy nexus will assume great relevance in near future water management policies and rainwater harvesting systems (RHS) may arise as an appealing alternative. The goal of this paper was to describe RaINvesT, a holistic tool developed to assess the viability of RHS, helping to adequately size the system, while allowing estimating its embodied energy per cubic meter (kWh/m 3 ). Additionally, considering the independence towards the public water supply network, an investment analysis is performed for both the water provider and the final user perspectives. RaINvesT was tested for a university campus: evidencing, in terms of embodied energy, a positive ratio of 0.013 kWh/m 3 . The investment analysis has proven the RHS to be economically viable, revealing an investment return of about 12 years. The promotion of RHS can therefore represent a viable business model for water utilities, and can be a step forward in water systems decentralization, contributing to this sector sustainability for future cities.
Using Inverse Optimal Control To Predict Human Reaching Motion in Collaborative Tasks

A great deal of work in the fields of neuroscience [1], [2], [3] and biomechanics [4] has sought to model the principles underlying human motion. However, human motion in environments with obstacles has been difficult to characterize. Furthermore, human motion in collaborative tasks where two humans share a workspace is difficult to model due to unclear social, interference, and comfort criteria. In this work we present a method to learn the cost function of a motion planner that mimics human collaborative manipulation tasks. Our approach is based on Inverse Optimal Control (IOC), which, by considering a set of demonstrations allows us to find a cost function that balances different feature functions. The demonstrations are generated through motion capture, while the feature functions are designed to avoid interference and collision with the partner as well as maintain smoothness of the trajectories. Prediction of human motion is then performed by iterative replanning using the trajectory optimizer STOMP [5], which is able to handle difficult environmental constraints. IOC, occasionally named Inverse Reinforcement Learning, is the problem of finding the cost or reward function that an agent optimizes when computing a trajectory or policy. The early Apprenticeship learning approach [6] consists of solving iteratively the forward problem, modifying the weights at each iteration. Our approach is based on the more recent PIIRL algorithm [7], which does not require solving the forward problem and thus allows handling highdimensional continuous state spaces by only requiring local optimality of the demonstrated trajectories.
Magnetically tunable metallic photonic crystals immersed in liquid crystal for terahertz wave

We investigated the phenomena of a metallic photonic crystal (MPC) immersed in liquid crystal. According to our design, the photonic crystal has specific photonic band gap (PBG) and can be utilized as a filter. The device is filled with nematic liquid crystal (NLC), MDA-00-3461. The refractive indices of NLC can be magnetically controlled by reorienting the NLC molecules. Consequently, the corresponding PBG and the filtering performance of the device are tunable. According to our experimental results, the low frequency boundary of PBG at 0.121 THz can be blue shifted by 6.17 GHz, and the high frequency boundary of PBG at 0.175 THz can be shifted to the blue by 11.04 GHz. As a tunable THz filter, the peak transmittance at 0.187 THz can be blue shifted by 3.66 GHz.