Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Pre‐Stress Losses in Instrumented Pre‐Stressed Concrete Beams Using Stochastic Analysis

Abstract: In this study, stochastic analyses of pre‐stress losses in two pre‐stressed concrete beams are carried out, and the results of the analyses are compared with those obtained from the laboratory experimental investigations. The deterministic models given in ACI 209 (with modelling error) are used for predicting the pre‐stress losses. The compressive strength of concrete, water–cement ratio, coarse aggregate–cement ratio, fine aggregate–cement ratio, cement content, initial stress in steel and relative humidity are considered as random variables. Monte Carlo simulation technique is used to determine the statistical properties of pre‐stress losses at different times. From the results obtained, it is noted that while the relaxation strain can be assumed to follow a normal distribution, the frequency distributions of creep and shrinkage strains are not uni‐modal. A relation for estimating total losses is also proposed in the article. The stochastic analysis approach presented in the article would be useful in the assessment of pre‐stress losses in existing pre‐stressed concrete members in a more rational way.
Model for treatment of copper slag produced during copper alloying

The purpose of this research is to develop a model for treatment of copper slag produced during copper alloying. Two copper slags were used, one from melting very pure metal to produce silicon brass (slag 1) and the other from remelting scrap to produce brass (slag 2). The model involves crushing, sizing and grinding followed by sieving and leaching. The leaching process was carried out on the size fraction <0·074 mm produced by crushing and grinding using sulphuric acid. Leaching parameters such as acid concentration and time of leaching were investigated. Results obtained for both slags 1 and 2 showed that the coarse fraction from −4 to 0·075 mm was enriched with copper and the size fraction <0·075 mm was enriched with silica. The coarse fraction is 68 wt-% slag 1 containing a copper content of 82 wt-% and a SiO2 content of 13 wt-% and a copper recovery of 93 wt-%. In the case of slag 2 the coarse fraction was 40% by weight containing at 80 wt-%Cu and 4·7 wt-%SiO2 with a copper recovery of 80%. Both the coarse fractions from slags 1 and 2 could be recycled either in an alloying process or used for production of copper. The results from leaching size fraction <0·075 mm which represented 32 wt-% of slag 1 and 60 wt-% of slag 2 showed extraction rates of copper of 95 and 97% respectively.
Significant cytotoxic activity in vitro of the EGFR tyrosine kinase inhibitor gefitinib in acute myeloblastic leukaemia

Objectives: Gefitinib inhibits epidermal growth factor receptor (EGFR) signalling, but may also act by non‐EGFR dependent mechanisms. We have investigated the activity of gefitinib in haematological tumour cells, in particular acute myeloblastic leukaemia (AML).
K-invariants of hyperbolic 3-manifolds

We introduce an invariant of the hyperbolic 3-manifolds which appears in the K-theory of certain C*-algebras. Namely, such an invariant is essentially the integral order in an algebraic number field K with a fixed equivalence class of ideals in the ring of integers of K. The C*-algebras in question are the crossed product C*-algebras attached to the monodromy transformation of the 3-manifolds which fiber over the circle. Our approach bridges topology with the number field theory. In particular, we conjecture a volume formula for the 3-manifolds in terms of the arithmetic of the field K.
Leader-follower formation control of Autonomous Underwater Vehicles with limited communications

This paper considers the problem of leader-follower formation control for a team of Autonomous Underwater Vehicles (AUVs) under the constraint of limited communications. First, a new leader follower control strategy is proposed for multiple AUVs in order for the follower vehicles to keep the desired relative distances and angles with respect to the leader. Then, the stability of the overall closed-loop system is shown using Lyapunov stability analysis. Next, a nonlinear filtering approach is used in order to estimate velocity signals communicated among the vehicles with multiple packet dropouts. Simulation results are presented to verify the effectiveness of the proposed method.
Effect of metabolic acidosis on NaCl transport in the proximal tubule.

In metabolic acidosis, the capacity of the proximal tubule for bicarbonate absorption is enhanced, whereas NaCl reabsorption is inhibited. Recent evidence indicates that transcellular NaCl absorption in the proximal tubule is mediated by apical membrane Cl-/formate exchange and Cl-/oxalate exchange, in parallel with recycling of these organic anions. We evaluated whether the effect of metabolic acidosis to inhibit NaCl reabsorption in the proximal tubule is due at least in part to inhibition of organic anion-dependent NaCl transport in this nephron segment. Absorption rates of bicarbonate ([Formula: see text]), chloride ( J Cl), and fluid ( J v) were measured in rat proximal tubule segments microperfused in situ. We confirmed that metabolic acidosis stimulates[Formula: see text]in tubules microperfused with 25 mM[Formula: see text], pH 7.4. For measurements of J Cl, tubules were microperfused with a low-bicarbonate (5 mM), high-chloride solution, simulating conditions in the late proximal tubule. Under these conditions, baseline J Cl and J v measured in the absence of formate and oxalate were not significantly different between control and acidotic rats. However, whereas addition of 50 μM formate or 1 μM oxalate to luminal and capillary perfusates markedly stimulated J Cland J v in control rats, formate and oxalate failed to stimulate J Cl and J v in acidotic rats. We conclude that metabolic acidosis markedly downregulates organic anion-stimulated NaCl absorption, thereby allowing differential regulation of proximal tubule NaHCO3 and NaCl transport.
Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis

It is known that microglia morphology and function are closely related, but only few studies have objectively described different morphological subtypes. To address this issue, morphological parameters of microglial cells were analyzed in a rat model of aseptic neuroinflammation. After the injection of a single dose of the enzyme neuraminidase (NA) within the lateral ventricle (LV) an acute inflammatory process occurs. Sections from NA-injected animals and sham controls were immunolabeled with the microglial marker IBA1, which highlights ramifications and features of the cell shape. Using images obtained by section scanning, individual microglial cells were sampled from various regions (septofimbrial nucleus, hippocampus and hypothalamus) at different times post-injection (2, 4 and 12 h). Each cell yielded a set of 15 morphological parameters by means of image analysis software. Five initial parameters (including fractal measures) were statistically different in cells from NA-injected rats (most of them IL-1β positive, i.e., M1-state) compared to those from control animals (none of them IL-1β positive, i.e., surveillant state). However, additional multimodal parameters were revealed more suitable for hierarchical cluster analysis (HCA). This method pointed out the classification of microglia population in four clusters. Furthermore, a linear discriminant analysis (LDA) suggested three specific parameters to objectively classify any microglia by a decision tree. In addition, a principal components analysis (PCA) revealed two extra valuable variables that allowed to further classifying microglia in a total of eight sub-clusters or types. The spatio-temporal distribution of these different morphotypes in our rat inflammation model allowed to relate specific morphotypes with microglial activation status and brain location. An objective method for microglia classification based on morphological parameters is proposed. Main points Microglia undergo a quantifiable morphological change upon neuraminidase induced inflammation. Hierarchical cluster and principal components analysis allow morphological classification of microglia. Brain location of microglia is a relevant factor.
An autocrine TGF-β/ZEB/miR-200 signaling network regulates establishment and maintenance of epithelial-mesenchymal transition

Epithelial-mesenchymal transition is a form of cellular plasticity that is critical for embryonic development and tumor metastasis. This study shows that a signaling network involving autocrine TGF-β signaling, ZEB transcription factors, and the miR-200 family regulates interconversion between epithelial and mesenchymal states.
Failure detection in masonry shells homogenisation and its incorporation in coupled two-scale computations

The formulation of macroscopic constitutive laws for the behaviour of masonry is complex, due to its strongly heterogeneous microstructure which considerably influences its failure behaviour. Due to the quasi-brittle nature of its constituents, this results in i nitial and damage-induced (evolving) anisotropy properties, accompanied with localisation of damage. In its structural use, such a material may be subjected to cracking, leading to localisation of damage at both the structural and constituents scales. Closed-form laws have therefore been developed for equivalent anisotropic media and applied for the modelling of plate failure [1]. As a complementary approach to closed-form constitutive relations, the multi-scale computational strategies aim at deducing a homogenised response at the structural scale from a representative volume element (RVE), based on constituents properties and averaging theorems. Homogenisation approaches allow to compute evolving homogenised continuum properties from the constituents constitutive behaviour of a heterogeneous mesostructure. In a nested computational procedure, in each point of the structural scale, a sample of the mesostructure is used to determine the material response. The local macroscopic strain measure is applied in an average sense to the sample and the resulting mesostructural stresses are determined numerically. The averaging of these mesostructural stresses and the condensation of the mesostructural t angent stiffness to the homogenised tangent stiffness then furnish the macroscopic material response associated with the macroscopic point. In addition to a fine scale constitutive description for the const ituents, the definition of such a nested scheme essentially requires the choice of a structural scale repre sentation allowing to model localisation of damage, and the set-up of scale transitions able to detect th e onset of such localisation. For in-plane loaded structures, in which both fine and coarse scale descriptions follow similar kinematical assumptions, these adaptations have been proposed recently in [2]. This approach can be extended to shell formulations, where higher order kinematical quantities such as curvatures appear at the structural scale. This requires adaptations of the structural scale de scription as well as of the scale transitions. A scale transition for homogenisation towards a Kirchhoff-Love shell behaviour was recently proposed in [3], based on a periodicity assumption. The constituents inside the unit cell may be modelled using any closed-form formulation. The mortar joints are represented here using cohesive zones equipped with a
Methodological issues in determining the relationship between street trees and asthma prevalence

A study published in the July issue of the Journal of Epidemiology and Community Health 1 documents the relationship between the density of street trees and the prevalence of childhood asthma in New York City. Findings suggest that street trees are associated with a lower prevalence, although no causality was inferred. I would like to point out a number of methodological issues which should benefit future studies on this subject. The prevalence of asthma was determined for 4-year-old and 5-year-old children using data from school screenings in 1999. Street tree density was derived from the 1995 street tree census completed by the Parks and Recreation Department of the City of New York and expressed as the total number of trees on street segments divided by the land area. Data were aggregated at the level of United Hospital Fund (UHF) areas. Additional variables used in the analysis were population density, racial/ethnic composition and a measure of proximity to pollution sources. The initial correlation analysis suggested a negative association between street tree density and prevalence of asthma. However, one of the strongest positive associations was between street tree density and population density. This initially appears somewhat counterintuitive, until it is …
Gibberellin signaling in plants

The plant hormone gibberellin (GA) regulates major aspects of plant growth and development. The role of GA in determining plant stature had major impacts on agriculture in the 1960s, and the development of semi-dwarf varieties that show altered GA responses contributed to a huge increase in grain yields during the ‘green revolution’. The past decade has brought great progress in understanding the molecular basis of GA action, with the cloning and characterization of GA signaling components. Here, we review the molecular basis of the GA signaling pathway, from the perception of GA to the regulation of downstream genes.
Computing cavities, channels, pores and pockets in proteins from non-spherical ligands models

MOTIVATION Identifying protein cavities, channels and pockets accessible to ligands is a major step to predict potential protein-ligands complexes. It is also essential for preparation of protein-ligand docking experiments in the context of enzymatic activity mechanism and structure-based drug design. RESULTS We introduce a new method, implemented in a program named CCCPP, which computes the void parts of the proteins, i.e. cavities, channels and pockets. The present approach is a variant of the alpha shapes method, with the advantage of taking into account the size and the shape of the ligand. We show that the widely used spherical model of ligands is most of the time inadequate and that cylindrical shapes are more realistic. The analysis of the void parts of the protein is done via a network of channels depending on the ligand. The performance of CCCPP is tested with known substrates of cytochromes P450 (CYP) 1A2 and 3A4 involved in xenobiotics metabolism. The test results indicate that CCCPP is able to find pathways to the buried heminic P450 active site even for high molecular weight CYP 3A4 substrates such as two ketoconazoles together, an experimentally observed situation. AVAILABILITY Free binaries are available through a software repository at http://petitjeanmichel.free. fr/itoweb.petitjean. freeware.html CONTACT michel.petitjean@univ-paris-diderot.fr.
Parameter identification for dynamic simulation

Dynamic simulation is potentially a powerful tool for studying complex contact interactions between robots and their environments. One of the main problems of such a simulation is the determination of the model parameters which provide realistic behavior for objects. This paper describes how to identify such parameters for a masses/springs based system (the Robot/spl Phi/ system). This identification process is composed of two main steps: the first step consists in distributing the total mass of the object between the different particles while respecting the inertial properties of the object; the second one consists in finding the values of the physical parameters of the model such as elasticity, viscosity, plasticity, etc. A numerical solution of the first step is described, while a genetic algorithm based approach is proposed for the second step. This approach allows us to find the values of the parameters which provide a consistent behavior under a set of given constraints (position, velocity, volume, etc). It also allows us to minimize the computation time and to attach priorities with these constraints.
Leptin receptor expression and its association with PI3K/AKT signaling pathway in diffuse large B-cell lymphoma

We investigated the role of the leptin receptor (Ob-R) and its relationship with PI3K/AKT activation in diffuse large B-cell lymphoma (DLBCL) clinical samples followed by in vitro studies using a panel of CRC cell lines. Leptin exerts its physiological action through its receptor Ob-R. Overexpression of Ob-R has been implicated in the pathogenesis of a variety of malignancies; however, its role in DLBCL has not been investigated. Using immunohistochemistry on a large cohort of DLBCL samples in a tissue microarray format, Ob-R immunostaining was detected in 86/216 (39.8%). Ob-R overexpression was associated with the catalytic subunit p110 of PI3K (p = 0.0283), activated AKT (p = 0.0003), and antiapoptotic marker XIAP (p = 0.0008) expression. In in vitro analysis using DLBCL cell lines, our data showed that leptin stimulated cell proliferation and inhibited apoptosis via activation of the PI3K/AKT signaling pathway. Pretreatment of DLBCL cells with Ob-R specific small interference RNA or inactivation of PI3K/AKT activity by LY294002 abolished these responses. Altogether, these data suggest that leptin plays a critical role in DLBCL pathogesis through the P13K/AKT pathway via Ob-R.
Electronic and magnetic properties of Mn-doped BeSiAs2 and BeGeAs2 compounds

The structural, electronic and magnetic properties of BeSiAs2 and BeGeAs2 chalcopyrite ternary compounds doped with manganese were investigated by means of ab initio calculations. It was found that substitution of Be atoms by Mn increases the lattice constants of both compounds that provide acceptable mismatch with conventional Si, Ge and GaAs substrates. In spite of the increase of the spin polarization upon doping, both compounds possess antiferromagnetic (AFM) ordering with the impurity in the group II position whereas ferromagnetic (FM) ordering is obtained in the case of an impurity in the group IV position.
Elevated Plasma Endothelin-1 and Pulmonary Arterial Pressure in Children Exposed to Air Pollution

Background Controlled exposures of animals and humans to particulate matter (PM) or ozone air pollution cause an increase in plasma levels of endothelin-1, a potent vasoconstrictor that regulates pulmonary arterial pressure. Objectives The primary objective of this field study was to determine whether Mexico City children, who are chronically exposed to levels of PM and O3 that exceed the United States air quality standards, have elevated plasma endothelin-1 levels and pulmonary arterial pressures. Methods We conducted a study of 81 children, 7.9 ± 1.3 years of age, lifelong residents of either northeast (n = 19) or southwest (n = 40) Mexico City or Polotitlán (n = 22), a control city with PM and O3 levels below the U.S. air quality standards. Clinical histories, physical examinations, and complete blood counts were done. Plasma endothelin-1 concentrations were determined by immunoassay, and pulmonary arterial pressures were measured by Doppler echocardiography. Results Mexico City children had higher plasma endothelin-1 concentrations compared with controls (p < 0.001). Mean pulmonary arterial pressure was elevated in children from both northeast (p < 0.001) and southwest (p < 0.05) Mexico City compared with controls. Endothelin-1 levels in Mexico City children were positively correlated with daily outdoor hours (p = 0.012), and 7-day cumulative levels of PM air pollution < 2.5 μm in aerodynamic diameter (PM2.5) before endothelin-1 measurement (p = 0.03). Conclusions Chronic exposure of children to PM2.5 is associated with increased levels of circulating endothelin-1 and elevated mean pulmonary arterial pressure.
Protein contact prediction from amino acid co-evolution using convolutional networks for graph-valued images

Proteins are the "building blocks of life", the most abundant organic molecules, and the central focus of most areas of biomedicine. Protein structure is strongly related to protein function, thus structure prediction is a crucial task on the way to solve many biological questions. A contact map is a compact representation of the three-dimensional structure of a protein via the pairwise contacts between the amino acid constituting the protein. We use a convolutional network to calculate protein contact maps from inferred statistical coupling between positions in the protein sequence. The input to the network has an image-like structure amenable to convolutions, but every "pixel" instead of color channels contains a bipartite undirected edge-weighted graph. We propose several methods for treating such "graph-valued images" in a convolutional network. The proposed method outperforms state-of-the-art methods by a large margin. It also allows for a great flexibility with regard to the input data, which makes it useful for studying a wide range of problems.
On-line adaptation of the SCHMM parameters based on the segmental quasi-Bayes learning for speech recognition

On-line quasi-Bayes adaptation of the mixture coefficients and mean vectors in semicontinuous hidden Markov model (SCHMM) is studied. The viability of the proposed algorithm is confirmed and the related practical issues are addressed in a specific application of on-line speaker adaptation using a 26-word English alphabet vocabulary.
Fragile watermarking scheme based on the block-wise dependence in the wavelet domain

In transform-domain fragile watermarking schemes for authentication purposes, a common practice is to watermark some selected transform coefficients in order to achieve low embedding distortion. However, we point out in this work that leaving most of the coefficients, usually the low frequency and zero-valued ones, unmarked opens wide security gap for attacks to be mounted on them. In this work, a fragile watermarking scheme is proposed to implicitly watermark all the coefficients by registering the zero-valued coefficients with a key-generated binary sequence so as to create the watermark and involving the unwatermarkable coefficients within a hierarchical neigh-bourhood of the watermarkable coefficients in a random manner during the embedding process. The benefit of this approach is twofold: Firstly, only a small amount of coefficients are marked while all the coefficients are protected, so that high transparency is achieved. Secondly, when the relationship established in a random manner within a hierarchical neighbourhood is disturbed, the watermark detector would fail to extract the watermarking. This puts up resistance to the vector quantisation attack and transplantation attack.
Disulfide connectivity prediction using secondary structure information and diresidue frequencies

MOTIVATION We describe a stand-alone algorithm to predict disulfide bond partners in a protein given only the amino acid sequence, using a novel neural network architecture (the diresidue neural network), and given input of symmetric flanking regions of N-terminus and C-terminus half-cystines augmented with residue secondary structure (helix, coil, sheet) as well as evolutionary information. The approach is motivated by the observation of a bias in the secondary structure preferences of free cysteines and half-cystines, and by promising preliminary results we obtained using diresidue position-specific scoring matrices. RESULTS As calibrated by receiver operating characteristic curves from 4-fold cross-validation, our conditioning on secondary structure allows our novel diresidue neural network to perform as well as, and in some cases better than, the current state-of-the-art method. A slight drop in performance is seen when secondary structure is predicted rather than being derived from three-dimensional protein structures.