Miracle-dz/UniFAR-FTUs huggingface dataset:
Behavioural responses in mice exposed to predator odour components

It is essential for prey species to be able to detect predators to avoid them. The sense of smell is used by a number of prey species for this purpose. The aim of the present study was to assess if one of the odourants that make up a predator odour is sufficient to induce a behavioural response in mice (Mus musculus). Two predator odourants were used, 2,2-dimethylthietane and methyl-2-phenylethyl sulfide, which are both found in the secretions of natural predators of mice. An odourant found in fruits, n-pentyl acetate, was also used. All three odourants were presented at a concentration that was a factor of 100 above the olfactory detection threshold of mice. Ten adult predator-naive CD-1 mice were individually put in a two-compartment chamber one of which contained an odourant while the other contained a near-odourless solvent (diethyl phthalate). The results indicated that methyl-2-phenylethyl sulfide was actively avoided by the mice. Towards 2,2-dimethylthietane and n-pentyl acetate, in contrast, the mice behaved indifferent. Further, the results suggest a significant correlation between the number of switches between the two compartments of the test chamber and the test sessions when the animals were presented with n-pentyl acetate, but not when they were presented with the predator odourants. The results support the notion of an innate fear response towards the predator odourant methyl-2-phenylethyl sulfide in mice, but further studies with more animals and different concentrations of the odourants are necessary.
NoCs: a new contract between hardware and software

Future single chip systems will resemble more traditional computer networks than traditional central processors. The main reasons for this trend are the infeasibility of global synchrony on a single chip, the necessity of reuse of existing hardware and software components as much as possible, and the heterogeneity and irregularity of system functions and features. The consequences of this trend are far reaching and imply the shift in concern from computation and sequential algorithms to concurrency, communication and interaction in every aspect of design and development of hardware and software. Based on an analysis of current trends we suggest that there is an opportunity for defining an interface between applications and Network-on-Chip (NoC) platform implementations with significant benefits for both worlds. We analyze the desirable properties of such an interface by means of studying a particular NoC platform, the Nostrum. We draw the general conclusion that such an interface, which we also call contract, has to include (1) description of functionality, (2) description of communication semantics and performance, and (3) mapping of task to resources.
Predicting the Time Course of Gene Expression in a Relational Learning Framework

In gene regulation prediction, the task is to predict the regulation of a gene under specific condition from binding side information, the state of regulators, and additional information. Previous work showed that relational learning techniques (in particular boosted first-order decision trees) are particularly useful for this kind of task, as (1) they can be adapted to complex datasets flexibly, and (2) they are able to integrate different types of data from diverse sources. This extended abstract describes our first steps towards refining this model for the prediction of the time course of gene expression.
Discrete-valued input control of crane systems using optimal dynamic quantizers

This paper is concerned with control of systems with discrete-valued control input, and addresses an optimal design problem of dynamic quantizers in a feedback loop. We first derive a closed form upper bound of the performance of a class of dynamic quantizers. Next, based on this, we propose an optimal dynamic quantizer, which allows us to easily design a controller by linear control theory for plants with discrete-valued input. Finally, it is demonstrated through an experiment with a crane system that the proposed optimal dynamic quantizer is effective for discrete-valued input feedback control.
Institute of Physics Publishing Journal of Micromechanics and Microengineering a 32-site Neural Recording Probe Fabricated by Drie of Soi Substrates

An all-dry silicon-etch based micromachining process for neural probes was demonstrated in the manufacture of a probe with a 32-site recording electrode array. The fork-like probe shafts were formed by double-sided deep reactive ion etching (DRIE) of a silicon-on-insulator (SOI) substrate, with the buried SiO 2 layer acting as an etch stop. The shafts typically had the dimensions 5 mm × 25 µm × 20 µm and ended in chisel-shaped tips with lateral taper angles of 4 •. An array of Ir electrodes, each 100 µm 2 , and Au conductor traces were formed on top of the shafts by e-beam evaporation. An accompanying interconnect solution based on flexible printed circuitry was designed, enabling precise and flexible positioning of the probes in neural tissue. SEM studies showed sharply defined probes and probe tips. The electrical yield and function were verified in bench-top measurements in saline. The magnitude of the electrode impedance was in the 1 M range at 1 kHz, which is consistent with neurophysiological recordings.
Grain Boundaries in Uranium Dioxide: Scanning Electron Microscopy Experiments and Atomistic Simulations

The distribution and atomic structure of grain boundaries has been investigated in UO 2 . Our scanning electron microscopic/ electron backscatter diffraction experiments on a depleted UO 2 sample showed real nuclear fuels contain a combination of special coincident site lattice (CSL) and general boundaries. The experimental data indicated that ∼ 16% of the boundaries were CSL boundaries and the CSL distribution was dominated by low Σ boundaries; namely E9, E3, and Σ5 Based on our experimental observations, the structures of select low E (E5 tilt, Σ5 twist, Σ3 tilt) and a random boundary were analyzed in greater detail using empirical potential atomic-scale calculations. Our calculations indicate that the boundaries have very different structures and each CSL boundary had multiple minima on the γ-surface. The presence of a significant fraction of CSL boundaries and the differences in their structures are expected to have important consequences on fuel properties.
Perturbation Models: A New Approach to Improving Handwriting Recognition

This paper discusses the application of the perturbation method to handwriting recognition. First the standard pattern recognition operations of preprocessing, feature extraction, and classification are reviewed. Then we introduce the perturbation method as a new approach to overcoming the problems that result from the sequential architecture traditionally found in pattern recognition systems. Two case studies in handwriting recognition, namely, isolated numeral recognition and cursive handwriting recognition, are presented. Experimental results show that the perturbation method significantly improves the recognition rates of state-of-the-art systems.
A Time-Over-Threshold Technique for Wide Dynamic Range Gamma-Ray Spectroscopy With the AGATA Detector

Wide-range energy measurements have been carried out with an encapsulated 36-fold segmented germanium detector of AGATA (Advanced GAmma-ray Tracking Array). An unprecedented equivalent energy range of 5 keV to 180 MeV, or ~90 dB, has been obtained using a single acquisition chain, while maintaining a high energy resolution in the whole spectrum. For energies larger than 3 MeV the pulse-height is obtained with a Time- over-Threshold (ToT) technique. The measured resolution in all the tested range from 3 to 50 MeV is of <0.4%. The ToT technique has been demonstrated using a 241Am + Be source with Ni target generating high-energy gamma photons by neutron capture reactions. A remarkable resolution of 0.21% has been obtained on the Ni spectrum line at the energy of 8.998 MeV.
Proteolysis in tempeh-type products obtained with Rhizopus and Aspergillus strains from grass pea (Lathyrus sativus) seeds.

BACKGROUND Tempeh is a food product obtained from legumes by means of solid-state fermentation with Rhizopus sp. Our previous research proved that mixed-culture inoculum may also be successfully applied. The objective of present research was to study the proteolytic activity of R. microsporus var. chinensis and A. oryzae during tempeh-type fermentation of grass pea seeds, and the effect of inoculum composition on the protein level and in vitro protein bioavailability in products. METHODS Fermentation substrate were soaked and cooked grass pea seeds. Material was mixed with single- or mixed-culture inoculum, and incubated in perforated plastic bags at 30°C for 32 hrs. In the products, the proteolytic activity (pH 3, 5 and 7), glucosamine, total protein and free amino acids levels, as well as protein in vitro bioavailability and degree of protein hydrolysis were obtained. RESULTS The significant correlation was found between glucosamine content and proteolytic activity in grass pea seeds fermented with Rhizopus or Aspergillus. The activities of Rhizopus proteases were higher than Aspergillus ones, which corresponded with the degree of seed protein hydrolysis. Both strains showed the highest activity of protease at pH 3. Tempeh made with pure culture of Rhizopus had 37% protein of 69% in-vitro bioavailability. Mixed-culture fermentation improved nutritional parameters of products only when the dose of Aspergillus spores in the inoculum was equal and lower than that of Rhizopus. This process resulted in higher in-vitro bioavailability of protein, slightly more efficient protein hydrolysis and higher level of free amino acids, as compared to standard tempeh. CONCLUSIONS The activity of A. oryzae in tempeh-type fermentation is beneficial as long as it does not dominate the activity and/or growth of Rhizopus strain.
Size Dependent Optical Nonlinearity and Optical Limiting Properties of Water Soluble CdSe Quantum Dots

We present third-order optical nonlinear absorption in CdSe quantum dots (QDs) with particle sizes in the range of 4.16–5.25 nm which has been evaluated by the -scan technique. At an excitation irradiance of 0.54 GW/cm2 the CdSe QDs exhibit reverse saturation indicating a clear nonlinear behavior. Nonlinearity increases with particle size in CdSe QDs within the range of our investigations which in turn depends on the optical band gap. The optical limiting threshold of the QDs varies from 0.35 GW/cm2 to 0.57 GW/cm2 which makes CdSe QDs a promising candidate for reverse-saturable absorption based devices at high laser intensities such as optical limiters.
Any Cortical Bridging Predicts Healing of Tibial Shaft Fractures.

BACKGROUND There is no consensus regarding the optimal radiographic criteria for predicting the final healing of fractures. The purpose of this study was to determine if the time to the radiographic appearance of cortical bridging predicted the final healing of tibial shaft fractures, to examine the reliability of this assessment, and to determine when it is most accurate during the postoperative period. METHODS We retrospectively reviewed the data on 176 tibial fractures (OTA [Orthopaedic Trauma Association] 42-A, B, and C) treated with intramedullary nailing at a level-I trauma center from 2007 through 2010. Postoperative radiographs were assessed for varying degrees of cortical bridging, and interobserver reliability was calculated. Receiver operating characteristic (ROC) curve and chi-square analyses determined the accuracy of cortical bridging assessments in predicting union. RESULTS The nonunion rate was 7%. Any cortical bridging within four months was an excellent predictor of final healing (accuracy = 99%, area under the curve [AUC] = 0.995, p < 0.0001) and was the most reliable criterion (kappa = 0.90). All fractures that showed unicortical bridging eventually showed bridging of three cortices without additional intervention. CONCLUSIONS Assessment for any cortical bridging by four months postoperatively is a reliable, accurate predictor of tibial shaft fracture-healing. This relatively early radiographic finding discriminates between fractures that will undergo late union with observation alone and those destined for nonunion. LEVEL OF EVIDENCE Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.
Growth in an Open Economy: Some Recent Developments

This paper discusses some of the recent developments in growth theory, doing so from the perspective of a small open economy. After setting out a basic generic model, we show how it may yield two of the key models that have played a prominent role in the recent literature, the endogenous growth model and the non-scale growth model. We focus initially on the former, emphasizing how the simplest such model leads to an equilibrium in which the economy is always on its balanced growth path. One aspect of the model is the importance of fiscal policy as a determinant of the equilibrium growth rate, an aspect that is discussed in detail. We also show how the endogeneity or otherwise of the labor supply is crucial in determining the equilibrium growth rate and its responsiveness to macroeconomic policy. But transitional dynamics are an important aspect of the growth process and indeed much research has been directed to determining the speed with which the economy converges to its balanced growth path. We discuss alternative ways that such transitional dynamics may be introduced. These include (i) restricted access to the world capital market; (ii) the introduction of government capital , and (iii) the two-sector production model, pioneered by Lucas. In the original analysis, the two capital goods relate to physical and human capital and in the international context these naturally can be identified with traded and nontraded capital, respectively. Criticism of the endogenous growth model has led to the development of the nonscale growth model. This too is characterized by transitional dynamics, which are more flexible than those of the corresponding endogenous growth model. This model is much closer to the neoclassical model; in particular, the long-run growth rate is independent of macroeconomic policy. However, since such models are typically associated with slow convergence speeds, policy can influence the accumulation of capital for extended periods of time, leading to significant long-run level effects. The discussion seeks to emphasize the adaptability of the models to a wide range of issues. A final extension addresses the impact of volatililty on growth. This has been extensively analyzed empirically and a stochastic extension of the endogenous growth model provides a convenient framework within which to interpret this research.
Simulation Of Electrochemical Processes

Section 1: Cathodic protection systems Computer simulation of the interference between a ship's and a dock's cathodic protection systems Zonal ICCP system control interactions Optimum design of cathodic protection using the Boundary Element Method Experimental vs. computational system analysis Numerical 3D BEM simulation of a CP system for a buried tank influenced by a steel reinforced concrete foundation Section 2: Modelling methodologies Galvanic corrosion modeling in flowing systems Polarization characteristics of geometrically confined spaces Calculation of temperature fields with DC and pulsed ECM Durable building technology benefiting electrochemical methods as a preventive Modelling the localized corrosion effects experienced by zinc-4.5wt. per cent aluminium steel coatings in 5 per cent NaCl solution Numerical simulation of metal corrosion with cluster formation Temperature and heat transfer profiles of a fluid film squeezed between two permeable isothermal discs rotating within a magnetic field Section 3: Electrodeposition and Electroforming Time-dependent simulation of electrochemical machining under non-ideal conditions Simulation of electrocodeposition Modeling the electrodeposition process: from the macroscopic to the mesoscopic, from continuous mathematics to discrete algorithms Heat transfer analysis of the EDM process on silicon carbide Section 4: Modelling of coatings Numerical 3D BEM simulation of the chromium layer thickness distribution on parts in a rack plating configuration BEM analysis of protective mechanism of patinas against atmospheric corrosion Electrochemical evaluation of a high solid coating in acid media Simulation of the formation mechanism of a viscous layer for the electropolishing process Section 5: Modelling stress corrosion cracking and corrosion fatigue The roles of microstructure and mechanics in intergranular stress corrosion cracking Stress-corrosion of cold drawn prestressing steels The effect of chromate on stress corrosion cracking of type 316 austenitic stainless steel in hydrochloric acid solution and the transgranular SCC mechanism
Preparation and antibacterial activity of Fe3O4@Ag nanoparticles

Bifunctional Fe3O4@Ag nanoparticles with both superparamagnetic and antibacterial properties were prepared by reducing silver nitrate on the surface of Fe3O4 nanoparticles using the water-in-oil microemulsion method. Formation of well-dispersed nanoparticles with sizes of 60 ± 20 nm was confirmed by transmission electron microscopy and dynamic light scattering. X-ray diffraction patterns and UV–visible spectroscopy indicated that both Fe3O4 and silver are present in the same particle. The superparamagnetism of Fe3O4@Ag nanoparticles was confirmed with a vibrating sample magnetometer. Their antibacterial activity was evaluated by means of minimum inhibitory concentration value, flow cytometry, and antibacterial rate assays. The results showed that Fe3O4@Ag nanoparticles presented good antibacterial performance against Escherichia coli (gram-negative bacteria), Staphylococcus epidermidis (gram-positive bacteria) and Bacillus subtilis (spore bacteria). Furthermore, Fe3O4@Ag nanoparticles can be easily removed from water by using a magnetic field to avoid contamination of surroundings. Reclaimed Fe3O4@Ag nanoparticles can still have antibacterial capability and can be reused.
Preparation and Characterization of Polyacetylene/Expanded Graphite Composites

Expanded graphite (EG) is a promising conducting filler to enhance the conductivity of the polyacetylene (PA)/EG composites and also an ideal support to catalyst PA to polymerize on the surface of EG. The expanded interlayers of EG prepared by chemical oxidation is between 100 and 1500 nm. Diameters of the Fe (naph)3 nanoparticles deposited on the external surface and internal surface (i.e. surface of the expanded graphitic layers) of EG range from 7 to15 nm. PA/EG composites were prepared by heterogeneous polymerization. PA catalyzed by Fe (naph)3 nanoparticles supported on the external surface and at the edge of the expanded layers was inclined to form bigger aggregation, while PA grown between the interlayers exhibit smaller size. The bulk conductivity of the prepared composites is 5.78×103 S·m-1.
A reversible jump MCMC algorithm for Bayesian curve fitting by using smooth transition regression models

This paper proposes a Bayesian algorithm to estimate the parameters of a smooth transition regression model. With in this model, time series are divided into segments and a linear regression analysis is performed on each segment. Unlike a piecewise regression model, smooth transition functions are introduced to model smooth transitions between the sub-models. Appropriate prior distributions are associated with each parameter to penalize a data-driven criterion, leading to a fully Bayesian model. Then, a reversible jump Markov Chain Monte Carlo algorithm is derived to sample the parameter posterior distributions. It allows one to compute standard Bayesian estimators, providing a sparse representation of the data. Results are obtained for real-world electrical transients with a view to non-intrusive load monitoring applications.
DNA Sequence Evolution and Rare Homoeologous Conversion in Tetraploid Cotton

Allotetraploid cotton species are a vital source of spinnable fiber for textiles. The polyploid nature of the cotton genome raises many evolutionary questions as to the relationships between duplicated genomes. We describe the evolution of the cotton genome (SNPs and structural variants) with the greatly improved resolution of 34 deeply re-sequenced genomes. We also explore the evolution of homoeologous regions in the AT- and DT-genomes and especially the phenomenon of conversion between genomes. We did not find any compelling evidence for homoeologous conversion between genomes. These findings are very different from other recent reports of frequent conversion events between genomes. We also identified several distinct regions of the genome that have been introgressed between G. hirsutum and G. barbadense, which presumably resulted from breeding efforts targeting associated beneficial alleles. Finally, the genotypic data resulting from this study provides access to a wealth of diversity sorely needed in the narrow germplasm of cotton cultivars.
Integrative Computational and Experimental Approaches to Establish a Post-Myocardial Infarction Knowledge Map

Vast research efforts have been devoted to providing clinical diagnostic markers of myocardial infarction (MI), leading to over one million abstracts associated with “MI” and “Cardiovascular Diseases” in PubMed. Accumulation of the research results imposed a challenge to integrate and interpret these results. To address this problem and better understand how the left ventricle (LV) remodels post-MI at both the molecular and cellular levels, we propose here an integrative framework that couples computational methods and experimental data. We selected an initial set of MI-related proteins from published human studies and constructed an MI-specific protein-protein-interaction network (MIPIN). Structural and functional analysis of the MIPIN showed that the post-MI LV exhibited increased representation of proteins involved in transcriptional activity, inflammatory response, and extracellular matrix (ECM) remodeling. Known plasma or serum expression changes of the MIPIN proteins in patients with MI were acquired by data mining of the PubMed and UniProt knowledgebase, and served as a training set to predict unlabeled MIPIN protein changes post-MI. The predictions were validated with published results in PubMed, suggesting prognosticative capability of the MIPIN. Further, we established the first knowledge map related to the post-MI response, providing a major step towards enhancing our understanding of molecular interactions specific to MI and linking the molecular interaction, cellular responses, and biological processes to quantify LV remodeling.