Miracle-dz/UniFAR-FTUs huggingface dataset:
Kinetics of selenate and selenite adsorption/desorption at the goethite/water interface

Kinetics and mechanisms of selenate and selenite adsorption/desorption at the goethite/water interface were studied by using pressure-jump (p-jump) relaxation with conductivity detection at 298.15 K. A single relaxation was ascribed to SeO{sub 4}{sup 2{minus}} on a surface site through electrostatic attraction accompanied simultaneously by a protonation process. The intrinsic rate constant for adsorption (log k{sub 1}{sup int} = 8.55) was much larger than that for desorption (log k{sub 1{minus}}{sup int} = 0.52). The intrinsic equilibrium constant obtained from the kinetic study (log K{sub kinetic}{sup int} = 8.02) was of the same order of magnitude as that obtained from the equilibrium study (log K{sub model}{sup int} = 8.65). Unlike SeO{sub 4}{sup 2{minus}}, selenite adsorption on goethite produced two types of complexes, XHSeO{sub 3}{sup 0} and XSeO{sub 3}{sup {minus}}, via a ligand-exchange mechanism. Double relaxations were attributed to two reaction steps. The first step was the formation of an outer-sphere surface complex through electrostatic attraction. In the second step, the adsorbed selenite ion replaced a H{sub 2}O from the protonated surface hydroxyl group and formed an inner-sphere surface complex.
Spread of tetracycline resistance genes at a conventional dairy farm

The use of antibiotics in animal husbandry contributes to the worldwide problem of increasing antibiotic resistance in animal and human pathogens. Intensive animal production is considered an important source of antibiotic resistance genes released to the environment, while the contribution of smaller farms remains to be evaluated. Here we monitor the spread of tetracycline resistance (TC-r) genes at a middle-size conventional dairy farm, where chlortetracycline (CTC, as intrauterine suppository) is prophylactically used after each calving. Our study has shown that animals at the farm acquired the TC-r genes in their early age (1–2 weeks), likely due to colonization with TC-resistant bacteria from their mothers and/or the farm environment. The relative abundance of the TC-r genes tet(W), tet(Q), and tet(M) in fresh excrements of calves was about 1–2 orders of magnitude higher compared to heifers and dairy cows, possibly due to the presence of antibiotic residues in milk fed to calves. The occurrence and abundance of TC-r genes in fresh excrements of heifers and adult cows remained unaffected by intrauterine CTC applications, with tet(O), tet(Q), and tet(W) representing a “core TC-resistome” of the farm, and tet(A), tet(M), tet(Y), and tet(X) occurring occasionally. The genes tet(A), tet(M), tet(Y), and tet(X) were shown to be respectively harbored by Shigella, Lactobacillus and Clostridium, Acinetobacter, and Wautersiella. Soil in the farm proximity, as well as field soil to which manure from the farm was applied, was contaminated with TC-r genes occurring in the farm, and some of the TC-r genes persisted in the field over 3 months following the manure application. Concluding, our study shows that antibiotic resistance genes may be a stable part of the intestinal metagenome of cattle even if antibiotics are not used for growth stimulation, and that smaller dairy farms may also contribute to environmental pollution with antibiotic resistance genes.
Genetic learning of accurate TS models based on local fuzzy prototyping

This work presents the use of local fuzzy prototypes as a ﬁrst approximation to obtain accurate local semantics-based Takagi-Sugeno rules. A two-stage evolutionary al-gorithm considering the interaction between input and output variables has been developed. Firstly, it performs a local iden-tiﬁcation of prototypes, and then, a post-processing stage is considered to reﬁne them. The proposal has been tested with a real-world problem achieving good results.
Verbalization of business rules: Application to OCL constraints in the utility domain

Business rules are defined, specified and validated by business experts but they are designed and implemented by technical implementers. Each of them uses languages adapted to their activity and skill. Verbalization of business rules permits to business experts to get a semi-natural expression of rules designed by technical implementers thus facilitating their task of validation. A transformation tool is proposed to automate verbalization and applied to OCL (Object Constraint Language) constraints in the Utility domain.
Expression of Heat Shock Protein Genes in Different Developmental Stages and After Temperature Stress in the Maize Weevil (Coleoptera: Curculionidae)

ABSTRACT The maize weevil, Sitophilus zeamais Motschulsky, is a major pest of rice and other postharvest grain stocks in tropical countries. Heating and cooling treatments have been adopted to control this pest. Because heat shock protein (hsp) genes respond to temperature stress, we examined the association of hsp genes with development and thermal stress in S. zeamais. The temperature response of the insect to heat and cold treatments was assessed at four developmental stages: egg, larva, pupa, and adult. LT50 values at high temperatures were similar among the four developmental stages, while adults were the most tolerant to low temperatures, and eggs, larvae, and pupae exhibited similar LT50 values. Expression levels of three hsps—Szhsp70, Szhsc70, and Szhsp90—fluctuated substantially throughout the four stages at a rearing temperature of 28°C. Heat shock and cold shock increased the expression of all three hsps, and the highest upregulation was observed at 40°C, although the intensity of upregulation varied among the three genes: strongly in Szhsp70, moderately in Szhsp90, and slightly in Szhsc70. Basal expression of the three hsps at 28°C and gene responses to heat and cold shock also varied significantly at the tissue level.
Immunological and Physicochemical Characterization of Heat-Labile Enterotoxins Isolated from Two Strains of Escherichia coli

Heat-labile enterotoxins from Escherichia coli strains of human and porcine origins had identical subunit composition, arrangement, and size in sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Immunological differences recently described by others were shown to reside exclusively in the B subunits.
Variational approximation of long-span language models for lvcsr

Long-span language models that capture syntax and semantics are seldom used in the first pass of large vocabulary continuous speech recognition systems due to the prohibitive search-space of sentence-hypotheses. Instead, an N-best list of hypotheses is created using tractable n-gram models, and rescored using the long-span models. It is shown in this paper that computationally tractable variational approximations of the long-span models are a better choice than standard n-gram models for first pass decoding. They not only result in a better first pass output, but also produce a lattice with a lower oracle word error rate, and rescoring the N-best list from such lattices with the long-span models requires a smaller N to attain the same accuracy. Empirical results on the WSJ, MIT Lectures, NIST 2007 Meeting Recognition and NIST 2001 Conversational Telephone Recognition data sets are presented to support these claims.
Compensating for Word Posterior Estimation Bias in Confusion Networks

This paper looks at the problem of confidence estimation at the word network level, where multiple hypotheses from a recognizer are represented in a confusion network. Given features of the network, an SVM is used to estimate the probability that the correct word is missing from a candidate slot and then other word probabilities are normalized accordingly. The result is a reduction in overall bias of the estimated word posteriors and an improvement in the confidence estimate for the top word hypothesis in particular
Metalinguistic Semantics for Echo Questions

This paper proposes a novel formal semantic analysis of echo questions built upon the idea that they are questions about expressions. Although similar concepts have been occasionally expressed in the literature, no formal models have been proposed that directly reflect this metalinguistic concept. Specifically, we propose a compositional semantics of echo questions formulated in the structured meanings theory of questions. The novelty of our analysis is the use of variables that range over natural language expressions, which allow natural language to express quantified statements about itself. We also criticize two previous semantic analyses of echo questions by Ginzburg and Sag (2001) and Artstein (2002), neither of which is metalinguistic unlike our model.
Global high-gain-based observer and backstepping controller for generalized output-feedback canonical form

We provide results and extensions for global output feedback design for systems in the generalized output-feedback canonical form. Our investigations reveal several conceptual and structural connections between high-gain design and two recent results on the generalized output-feedback canonical form. The recognition of these links provides new insight into the stabilization mechanisms of these designs, particularly in the observer design. Furthermore, we have extended the results to include output dependent upper diagonal terms and also shown that the additional scaling proposed in a recent paper can be removed through a simultaneous stabilization result (i.e., solving a special pair of coupled matrix Lyapunov equations). We provide necessary and sufficient conditions for solvability of these coupled Lyapunov equations. The removal of the additional scaling makes the connection between the obtained results and proofs and our earlier results assuming cascading upper diagonal dominance (CUDD) more transparent. Moreover, removing the additional scaling (and possibly introducing a negative scaling) provides a better guaranteed convergence of the observer errors and allows smaller controller gains. It is shown that the high gain scaling induces the CUDD structure on the observer error dynamics. Finally, the design utilizes a reduced-order observer.
A Review of the Contemporary International Literature on Student Retention in Higher Education

One of the major issues that concerns tertiary institutions around the world is the student retention rate. In general, higher rates of completion give more positive image about the academic, administrative and financial statues of these institutions. However, improving the student completion and retention rates can be a challenging task. One way toward this goal is utilising strategies and techniques that are informed by the findings of theoretical models and empirical studies. Therefore, this paper reviews some of the contemporary studies in the student retention literature from different higher educational contexts around the world followed by a list of the variables that are commonly linked to the student retention phenomenon in higher education and a discussion of the factors that are most frequently associated with student attrition as reported by these studies. A summary of the factors associated with the student attrition phenomenon suggested that, the central factors were the quality of students’ institutional experiences and their level of integration into the academic and social systems of their academic institutions. These factors relate to students’ experiences with the administrative system of their academic institution, including the admission, registration and disciplinary rules and policies and the availability and quality of student services and facilities. Keywords : Higher education, student retention, attrition, persistence
Neuregulin-1 regulates LTP at CA1 hippocampal synapses through activation of dopamine D4 receptors

Neuregulin-1 (NRG-1) is genetically linked with schizophrenia, a neurodevelopmental cognitive disorder characterized by imbalances in glutamatergic and dopaminergic function. NRG-1 regulates numerous neurodevelopmental processes and, in the adult, suppresses or reverses long-term potentiation (LTP) at hippocampal glutamatergic synapses. Here we show that NRG-1 stimulates dopamine release in the hippocampus and reverses early-phase LTP via activation of D4 dopamine receptors (D4R). NRG-1 fails to depotentiate LTP in hippocampal slices treated with the antipsychotic clozapine and other more selective D4R antagonists. Moreover, LTP is not depotentiated in D4R null mice by either NRG-1 or theta-pulse stimuli. Conversely, direct D4R activation mimics NRG-1 and reduces AMPA receptor currents and surface expression. These findings demonstrate that NRG-1 mediates its unique role in counteracting LTP via dopamine signaling and opens future directions to study new aspects of NRG function. The novel functional link between NRG-1, dopamine, and glutamate has important implications for understanding how imbalances in Neuregulin-ErbB signaling can impinge on dopaminergic and glutamatergic function, neurotransmitter pathways associated with schizophrenia.
Effective run-and-tumble dynamics of bacteria baths

E. coli bacteria swim in straight runs interrupted by sudden reorientation events called tumbles. The resulting random walks give rise to density fluctuations that can be derived analytically in the limit of non-interacting particles or equivalently of very low concentrations. However, in situations of practical interest, the concentration of bacteria is always large enough to make interactions an important factor. Using molecular dynamics simulations, we study the dynamic structure factor of a model bacterial bath for increasing values of densities. We show that it is possible to reproduce the dynamics of density fluctuations in the system using a free run-and-tumble model with effective fitting parameters. We discuss the dependence of these parameters, e.g., the tumbling rate, tumbling time and self-propulsion velocity, on the density of the bath.
Presence and Memory: Immersive Virtual Reality Effects on Cued Recall

Presence, the psychological experience of “being there,” is an important construct to consider when investigating the impact of mediated experiences on cognition. Though several studies have investigated the influence of presence on the memory of virtual environments (i.e. recalling virtual objects), few have tested how presence impacts memory on subsequent tasks in the physical world. Thirty-three male and female college students were exposed to a pro-environmental message in an immersive virtual environment. After the virtual reality treatment, they completed a memory task in the physical world regarding pro-environmental principles. Results showed a significant negative association between levels of reported presence in the virtual world and the number of correct water conservation examples remembered in the physical world. These findings suggest that media technology that induces presence can influence an individual’s ability to remember information in the physical world. Possible theoretical explanations of how presence may negatively impact cognition are presented.
Robot Skill Learning

Learning robots that can acquire new motor skills and refine existing ones have been a long standing vision of robotics, artificial intelligence, and the cognitive sciences. Early steps towards this goal in the 1980s made clear that reasoning and human insights will not suffice. Instead, new hope has been offered by the rise of modern machine learning approaches. However, to date, it becomes increasingly clear that off-the-shelf machine learning approaches will not be adequate for robot skill learning as these methods often do not scale into the high-dimensional domains of manipulator and humanoid robotics, nor do they fulfill the real-time requirement of the domain. As an alternative, we propose to divide the generic skill learning problem into parts that can be well-understood from a robotics point of view. After designing appropriate learning approaches for these basic components, these will serve as the ingredients of a general approach to robot skill learning. In this paper, we discuss our recent and current progress in this direction. As such, we present our work on learning to control, learning elementary movements, as well as our steps towards the learning of complex tasks. We show several evaluations using both real robots as well as physically realistic simulations.
Plasma Biomarkers That Reflect Determinants of Matrix Composition Identify the Presence of Left Ventricular Hypertrophy and Diastolic Heart Failure

Background— Chronic pressure overload (such as arterial hypertension) may cause left ventricular (LV) remodeling, alterations in cardiac function, and the development of diastolic heart failure. Changes in the composition of the myocardial extracellular matrix may contribute to the development of pressure-overload–induced LV remodeling. We hypothesized that a specific pattern of plasma biomarker expression that reflected changes in these pathophysiological mechanisms would have diagnostic application to identify (1) patients who have development of LV hypertrophy (LVH) and (2) patients with LVH who have development of diastolic heart failure. Methods and Results— Plasma concentration of 17 biomarkers (matrix metalloproteinase [MMP]-1, -2, -3, -7, -8, and -9; tissue inhibitors -1, -2, -3, and -4; N-terminal propeptide of brain natriuretic peptide (NT-proBNP); cardiotrophin; osteopontin; soluble receptor for advanced glycation end products; collagen I teleopeptide; collagen I NT-proBNP; and collagen III N-terminal propetide [PIIINP]), an echocardiogram, and 6-minute hall walk were performed on 241 referent control subjects, 144 patients with LVH but no evidence of heart failure, and 61 patients with LVH and diastolic heart failure (DHF). A plasma multibiomarker panel consisting of increased MMP-7, MMP-9, TIMP-1, PIIINP, and NT-proBNP predicted the presence of LVH with an area under the curve of 0.80. A plasma multibiomarker panel consisting of increased MMP-2, TIMP-4, PIIINP, and decreased MMP-8 predicted the presence of DHF with an area under the curve of 0.79. These multibiomarker panels performed better than any single biomarker including NT-proBNP and better than using clinical covariates alone (area under the curve, 0.73 for LVH and 0.68 for DHF). Conclusions— Plasma biomarkers reflecting changes in extracellular matrix fibrillar collagen homeostasis, combined into a multibiomarker panel, have discriminative value in identifying the presence of structural remodeling (LVH) and clinical disease (DHF).
Battery energy storage efficiency calculation including auxiliary losses: Technology comparison and operating strategies

The overall efficiency of battery electrical storage systems (BESSs) strongly depends on auxiliary loads, usually disregarded in studies concerning BESS integration in power systems. In this paper, detailed electrical-thermal battery models have been developed and implemented in order to assess a realistic evaluation of the efficiency of NaS and Li-ion batteries. BESSs have been sized in order to operate on a real low voltage distribution network, based on load and photovoltaic generation measurements during an 8-month period. The performance of NaS and Li-ion batteries have been evaluated for two different operating strategies. Results show that, considering auxiliary losses, overall efficiencies of both technologies are very low with respect to the charge/discharge efficiency. Finally, two simplified formulas, able to evaluate the efficiency and the auxiliary losses of a NaS BESS, are presented.
The impacts of sleep and sleep deprivation on human brain and behavioral incentive processing

Despite an emerging link between alterations in motivated behavior and a lack of sleep, the impact of sleep deprivation as well as the potential benefit of sleep, when it is achieved, on human brain mechanisms of reward and punishment remain largely unknown. Targeting these unanswered questions, this thesis aims to determine the impact sleep loss on human brain incentive processing in topics of 1) food desire and 2) monetary gains and losses. From these investigations four main findings have emerged that make up the first four chapters of this report: 1) In the context of food choices, sleep deprivation leads to significantly decreases activity in appetitive evaluation regions within the human frontal cortex and insular cortex during food desirability choices, combined with a converse amplification of activity within the amygdala ultimately leading to increased high calorie food choices. 2) In the context of monetary rewards and losses, sleep deprivation did not lead to measurable changes in activation to the anticipation of rewards and losses in the nucleus accumbens or insula respectively. However, sleep deprivation did lead to diminished medial prefrontal cortex responses to gain outcomes and increased anterior insula response to loss outcomes. 3) Although there were no observable sleep deprivation group effects on anticipation of monetary gains and losses, there was a significant interaction of sleep deprivation with a trait dopamine transporter genetic polymorphism that determined the impact of sleep deprivation on anticipatory response to gain and loss in the nucleus accumbens and anterior insula respectively. 4) In the context of learning from monetary incentives, sleep deprivation led to a specific deficit in the ability to learn from monetary gains but no change in the learning profile for monetary losses. Finally, in addition to these four findings on the impacts of sleep deprivation on human incentive processing, the final chapter (5) focuses on the relationship between sleep, when it is achieved, and next day reward responsivity. Here there is a significant relationship between individual differences in REM sleep beta power and next day nucleus accumbens response to anticipation of rewards. Beyond these basic scientific insights, such results offer potential clinical relevance given that sleep disruption is highly co-morbid with numerous psychiatric and neurological conditions associated with dysfunctional dopaminergic reward processing (e.g., Parkinson's disease, substance abuse, and obesity). Such findings further indicate that sleep intervention may represent an under appreciated and novel therapeutic target particularly for disorders of the reward system.
A Dual-Mode Quadrature-Fed Wideband Circularly Polarized Dielectric Resonator Antenna

In this letter, a rectangular dielectric resonator antenna (DRA) structure fed by two vertical strips with quadrature in phase is studied. Both the fundamental TE111 and the higher order TE113 modes can be simultaneously excited to generate a wideband circular polarization. The measured 10-dB impedance bandwidth is 32.8% from 2.7 to 3.76 GHz, under which the axial ratio is less than 4 dB. The radiation pattern and antenna gain are also studied.