Miracle-dz/UniFAR-FTUs huggingface dataset:
Proteomics-based Development of Biomarkers for Prion Diseases

We analyzed the proteomic profile of ME7 scrapie-infected mouse brains, and the interactions and functions of selected differentially expressed proteins to identify potential new biomarkers to be applicable for the diagnosis of Prion diseases. Mice were intracerebrally inoculated with 10% homogenate of ME7 scrapie-infected mouse brains, and monitored for neurological symptoms. We screened for proteins specifically expressed in infected brain samples using one-dimensional gel electrophoresis and liquid chromatography-mass spectrometry. 317 proteins based on their peptide scores and ratio values were selected. The major biological processes identified were cellular and metabolic processes, localization, and transport. Selected proteins had functions related to neurological processes, including cell-cell signaling, transmission of nerve impulse, and synaptic transmission. We analyzed infected host cells using experimental and computational methods, and found many significant protein expression changes. We identified 43 candidate proteins with high peptide scores and ratio values. Of these, 36 potential candidate proteins were related to up regulated biological processes, and 7 to down regulated biological processes. We confirmed the presence of two of these differentially expressed candidate proteins using immunoblotting.
Insulin sensitivity tools for critical care.

Stress induced hyperglycaemia is prevalent in critical care. Since the landmark paper published by Van den Berghe et al. (2001) a great deal of attention has been paid to intensive insulin therapy in an ICU setting to combat the adverse e ects of elevated glucose levels and poor glycaemic control. Glycaemic control protocols have been extensively developed, tested and validated within an ICU setting. However, little research has been conducted on the e ects of a glycaemic control protocol in a less acute ward setting. There are many additional challenges presented in a ward setting, such as the variation in meals and levels of activity between patients, from day to day and throughout the day. A simple compartment model is used to describe the nature of insulin and glucose metabolism in patients of the Cardiothoracic Ward (CTW). A stochastic model of the tted insulin sensitivity parameter is generated for this cohort and validated against cohorts of similar characteristics. The stochastic model is then used to run simulations of predictive control on 7 CTW patients, which shows signi cantly tighter glucose control than what is obtained with regular clinical procedures. However, the rate of severe hypoglycaemia is an unacceptably high 4.2%. The greatest challenge in maintaining tight glycaemic control in such patients is the consumption of meals at irregular times and of inconsistent quantities. Insulin sensitivity was compared to extensive hourly clinical data of 36 ICU patients. From this data a sepsis score of value 0-4 was generated as gold standard marker of sepsis. Comparing the sepsis score to insulin sensitivity found that insulin sensitivity provides a negative predictive diagnostic for sepsis. High insulin sensitivity of greater than SI = 8 10 5 L mU 1 min 1 rules out sepsis for the majority of patient hours and may be determined non-invasively in real-time from glycaemic control protocol data. Low insulin sensitivity is not an e ective diagnostic, as it can equally mark the presence of sepsis or other conditions.
Diffusion MRI of the ex vivo porcine heart

In conventional Diffusion Tensor Imaging (DTI), water diffusion is assumed to occur in a free and unrestricted environment, in which the diffusion profile of water molecules can be modelled to be Gaussian. However, in biological tissue the complex microstructure makes the diffusion process highly hindered or even restricted. The aim of this study was to get a better understanding of the non Gaussian diffusion profile in the ex vivo porcine heart using different DW-MRI (Diffusion Weighted Magnetic Resonance Imaging) techniques and different post processing approaches. Previous studies showed a non mono-exponential signal decay in cardiac tissue due to the effect of the applied b-values. Evidence was also found of dependence of the estimation of diffusion parameters on the experimental diffusion time. In this study, experiments with different diffusion times and different b-values were performed and the results connected to microstructure at the cellular level. Based on experimental observation and data fitting including both conventional DTI and bi-exponential models, it was speculated that water moving in the direction perpendicular to the axis of the cell is always in regime of restricted diffusion, while along the cell different regimes can be observed by tuning the experimental diffusion time. A second MRI approach used Diffusion Kurtosis Imaging (DKI), which quantifies the level of diffusion restriction by providing a measure of deviation of the diffusion profile from a Gaussian shape. This method was found to be more sensitive to tissue microstructure than conventional DTI-based approaches, and kurtosis maps provided contrast between left and right ventricle, which was not visualized in conventional diffusion maps. The last approach was to try to connect regional differences of diffusion parameters across the heart and deviations from a Gaussian diffusion profile with the presence of ”crossing fibers”. Partial volume effects are in fact to be expected in MRI scans, since previous histological studies showed the presence of intersecting myolaminae across the cardiac wall, which are intersecting each others. Constrained Spherical Deconvolution (CSD) method was proposed in order to overcome the ”crossing fibers” problem, and used for data fitting and fiber tracking. The results show the presence of crossing fiber tracts at the level of a single voxel, which are not correctly identified with standard DTI.
A preliminary look at relationships between married gay men and lesbians and their parents-in-law: Five case studies

Abstract With marriage between lesbians and between gays now legal in the United States, it is important to gain an understanding of how in-law relationships function for this population. Five case studies, part of a larger study of in-law relationships, are presented that help further knowledge of the potential obstacles that some couples may face in relation to their in-laws. Common experiences include relationships improving over time; struggling with acceptance; feeling closer to parents-in-law because other adult children or adult children-in-law have fallen out of favor; recognizing the significant role that the child-in-law’s spouse plays in the relationship between the child-in-law and the parent-in-law; understanding the role that the larger community plays; considering both parents-in-law as separate voices in the in-law dyad; and experiencing feelings of ambivalence that arise between family members. Practice implications for clinicians are included as are implications for future research.
The acute effect of whole-body vibration on cycling peak power output

The aim of the present study was to determine if an acute bout of whole-body vibration (WBV) prior to sprint cycling would increase peak power output. Ten male cyclists, all familiar with maximal sprint cycling exercise performed, on two separate occasions, a ten second standing sprint on a cycle ergometer. For one trial the sprint was preceded by a 2 minute WBV intervention, requiring the participant to stand on a vibrating platform that produced sinusoidal oscillations. The frequency and amplitude of the vibration was set at 26Hz and ‘high’ (approximately 2mm) respectively. For the other trial participants stood in the same position, however the platform did not vibrate (no-WBV; 0Hz and 0mm for frequency and amplitude respectively). No significant difference was recorded for peak power output between trials (1458.0 + 283.7 W versus 1506.3 + 232.5 W for WBV and no-WBV respectively, P = 0.17). The results suggest that WBV prior to maximal standing sprint cycling does not increase peak power output.
Growth of a poplar short rotation coppice under elevated atmospheric CO2 concentrations (EUROFACE) depends on fertilization and species

La croissance de taillis de peuplier a courte rotation dans une atmosphere a concentration en CO 2 elevee depend de la fertilisation et de l'espece. La croissance et la production ligneuse de biomasse de trois especes de peuplier (Pinus nigra L. clone J. Pourtet, P. alba L. clone 2AS-11 et P. x euramericana clone I-214) ont ete suivies pendant la premiere saison de croissance apres la coupe du taillis a courte rotation expose a une concentration elevee en CO 2 , au moyen d'un systeme FACE et a une fertilisation azotee. Le FACE accroit significativement le nombre de pousses par pied. En septembre, le FACE a augmente l'indice foliaire (LAI) de 5,5 a 16,4 % selon les especes. FACE stimule significativement la production de biomasse ligneuse (25 %) mais pour P. alba et P. x euramericana cette stimulation ne concerne que le traitement fertilise. Des differences significatives ont ete observees entre les especes. Nous concluons que le taillis amoindrit l'effet du FACE, que l'effet positif du FACE etait limite pour un sol peu fertile et que les especes different dans leur reponse au FACE.
Ultraviolet photo-ionisation in far-infrared selected sources

It has been reported that there is a deficit of stellar heated dust, as evident from the lack of far-infrared (FIR) emission, in sources within the Herschel-SPIRE sample with X-ray luminosities exceeding a critical value of LX ∼ 1037 W. Such a scenario would be consistent with the suppression of star formation by the AGN, required by current theoretical models. Since absorption of the 21 cm transition of neutral hydrogen (H I), which traces the star-forming reservoir, also exhibits a critical value in the ultraviolet band (above ionising photon rates of Q ≈ 3 × 1056 s−1), we test the SPIRE sample for the incidence of the detection of 250 μm emission with Q. The highest value at which FIR emission is detected above the SPIRE confusion limit is Q = 8.9 × 1057 s−1, which is ≈30 times that for the H I, with no critical value apparent. Since complete ionisation of the neutral atomic gas is expected at Q ≳ 3 × 1056 s−1, this may suggest that much of the FIR must arise from heating of the dust by the AGN. However, integrating the ionising photon rate of each star over the initial mass function, we cannot rule out that the high observed ionising photon rates are due to a population of hot, massive stars.
Current trends in evolutionary multi-objective optimization

In a short span of about 14 years, evolutionary multi-objective optimization (EMO) has established itself as a mature field of research and application with an extensive literature, many commercial softwares, numerous freely downloadable codes, a dedicated biannual conference running successfully four times so far since 2001, special sessions and workshops held at all major evolutionary computing conferences, and full-time researchers from universities and industries from all around the globe. In this paper, we make a brief outline of EMO principles, some EMO algorithms, and focus on current research and application potential of EMO. Besides, simply finding a set of Pareto-optimal solutions, EMO research has now diversified in hybridizing its search with multi-criterion decision-making tools to arrive at a single preferred solution, in utilizing EMO principle in solving different kinds of single-objective optimization problems efficiently, and in various interesting application domains which were not possible to be solved adequately due to the lack of a suitable solution technique.
BagStack Classification for Data Imbalance Problems with Application to Defect Detection and Labeling in Semiconductor Units

Despite the fact that machine learning supports the development of computer vision applications by shortening the development cycle, finding a general learning algorithm that solves a wide range of applications is still bounded by the ”no free lunch theorem”. The search for the right algorithm to solve a specific problem is driven by the problem itself, the data availability and many other requirements. Automated visual inspection (AVI) systems represent a major part of these challenging computer vision applications. They are gaining growing interest in the manufacturing industry to detect defective products and keep these from reaching customers. The process of defect detection and classification in semiconductor units is challenging due to different acceptable variations that the manufacturing process introduces. Other variations are also typically introduced when using optical inspection systems due to changes in lighting conditions and misalignment of the imaged units, which makes the defect detection process more challenging. In this thesis, a BagStack classification framework is proposed, which makes use of stacking and bagging concepts to handle both variance and bias errors. The classifier is designed to handle the data imbalance and overfitting problems by adaptively transforming the multi-class classification problem into multiple binary classification problems, applying a bagging approach to train a set of base learners for each specific problem, adaptively specifying the number of base learners assigned to each problem, adaptively specifying the number of samples to use from each class, applying a novel data-imbalance aware cross-validation technique to generate the meta-data while taking into account the data imbalance problem at the meta-data level and, finally, using a multi-response random forest regression classifier as a meta-classifier. The BagStack classifier makes use of multiple features to solve the defect classification problem. In order to detect defects, a locally adaptive statistical background modeling is proposed. The proposed BagStack classifier outperforms state-of-the-art image classification techniques on our dataset in terms of overall classification accuracy and average per-class classification accuracy. The proposed detection method achieves high performance on the considered dataset in terms of recall and precision.
Increased perpendicular magnetocrystalline anisotropy governed by magnetic boundary in an asymmetrically terminated FeRh(001) thin film

Rh-terminated FeRh(001) film is known to be stable in a ferromagnetic (FM) state different from a G-type antiferromagnetic (G-AFM) bulk ground state, while an Fe-terminated FeRh(001) film has the same ground state as the bulk. In this paper, we investigate the magnetic properties of asymmetrically terminated FeRh(001) films: one surface is Fe-terminated and the other is Rh-terminated. Rh surface only ] (RhSO) FM state in asymmetrically terminated FeRh(001) film is identified to exhibit 40% increased perpendicular MCA energy as compare to that of the whole-layer (WL) FM state. This increased MCA energy is governed by Rh atom which is placed at the magnetic boundary. Since FM and G-AFM states are mixed up at the magnetic boundary, spin-orbit couplings which give positive contribution to perpendicular MCA are revealed.
Lattice Boltzmann Simulation of Transport Phenomena in Food and Bioprocesses: Fundamentals and Applications

As part of ongoing research on computational modelling of agroindustrial biosystems, lattice Boltzmann method (LBM) have been applied in order to numerically simulate transport phenomena in food and bioprocesses. This paper addresses LBM simulation of two different continuousflow processes in fixed-bed equipment whose models are quite similar, namely bioaffinity chromatography and extraction of biocompounds. Considering a dynamic onedimensional model framework for those processes, LBM was implemented in D1Q2 lattice and particle distribution functions were assigned to species (adsorbate or extract) concentrations in both fluid and solid phases. Equilibrium distribution functions were set by considering diffusiveconvective transport in the fluid phase whereas the solid phase remains stationary. LBM simulations were carried out in view of existing research work on bioseparation of lysozyme and extraction of essential oil from gorse. As the governing equation for species concentration in the solid phase lacked partial derivatives with respect to the spatial coordinate, the corresponding streaming step was suppressed in the LBM code. No loss of functionality was verified and the expected shapes of breakthrough as well as extraction yield curves were suitably reproduced in all LBM simulations.
Rank-deficient representations in Howe duality over finite fields arise from quantum codes.

Let V be a symplectic vector space and let $\mu$ be the oscillator representation of Sp(V). It is natural to ask how the tensor power representation $\mu^{\otimes t}$ decomposes. If V is a real vector space, then Howe duality asserts that there is a one-one correspondence between the irreducible subrepresentations of Sp(V) and the irreps of an orthogonal group O(t). It is well-known that this duality fails over finite fields. Addressing this situation, Gurevich and Howe have recently assigned a notion of rank to each Sp(V) representation. They show that Howe duality continues to hold over finite fields, if one restricts attention to subrepresentations of maximal rank. The nature of the rank-deficient components was left open. Here, we show that all rank-deficient Sp(V)-subrepresentations arise from embeddings of lower-order tensor products of $\mu$ and $\bar\mu$ into $\mu^{\otimes t}$. The embeddings live on spaces that have been studied in quantum information theory as tensor powers of self-orthogonal Calderbank-Shor-Steane (CSS) quantum codes. We then find that the irreducible Sp(V) subrepresentations of $\mu^{\otimes t}$ are labelled by the irreps of orthogonal groups O(r) acting on certain r-dimensional spaces for r $\leq$ t. The results hold in odd charachteristic and the "stable range" t $\leq$ 1/2 dim V. Our work has implications for the representation theory of the Clifford group. It can be thought of as a generalization of the known characterization of the invariants of the Clifford group in terms of self-dual codes.
Phytochemical Screening and In vitro Anti-inflammatory Activity of the Stem of Coleus forskohlii.

Abstract The extracts of Coleus forskohlii prepared by using hexane, chloroform, methanol, 80% methanol and water as solvents were screened for secondary metabolites and for its invitro anti-inflammatory activity. The extracts revealed the presence of alkaloids, phenols, tannins, proteins, carbohydrates, saponins, glycosides and cardiac glycosides and most of these compounds were observed in the aqueous, 80% methanol and methanolic extracts. DPPH antioxidant assay and the in vitro anti-inflammatory activity assays viz., BSA anti-denaturation and HRBC membrane stabilization assay indicated that the aqueous and methanolic extracts of Coleus forskohlii possess constituents with anti-inflammatory properties. TLC profile of the methanolic extract confirmed the presence of forskolin, which is a major bioactive compound isolated from the roots of Coleus forskohlii. Of all the extracts that were tested for their in vitro anti-inflammatory activity, methanolic and aqueous extracts showed maximum activity.
Parameterized quantum circuits as machine learning models

Hybrid quantum–classical systems make it possible to utilize existing quantum computers to their fullest extent. Within this framework, parameterized quantum circuits can be regarded as machine learning models with remarkable expressive power. This Review presents the components of these models and discusses their application to a variety of data-driven tasks, such as supervised learning and generative modeling. With an increasing number of experimental demonstrations carried out on actual quantum hardware and with software being actively developed, this rapidly growing field is poised to have a broad spectrum of real-world applications.
Effect of Moderators on Determinants: A Case Study of Technology Acceptance Models

From a few decades, studies has been conducted on various technology acceptance models to predict user acceptance of information technologies. These days various types of tools and information technologies are used in organizations. The success of organization depends on use of these technologies. For the organizations to meet their goals, it becomes important that the technologies are adopted in the organizations and those technologies are accepted by the users. But sometimes these technologies are rejected due to the lack of understanding of behavioral intention of the users. TAM has remained important model in the previous studies and has provided good results also, but now a new model UTAUT has evolved in this study. This research paper conducts an experimental study on both technology acceptance models to check the effect of moderators on determinants for understanding behavioral intention of the users. Questionnaire related to the models were distributed to students of colleges, who were using computer software like Tally, Photoshop, Ms-excel. Analysis was done by cronbach’s alpha analysis, correlation analysis and regression analysis. The research concludes perceived usefulness and performance expectancy are more important determinants than the others in understanding behavioral intention of users and suitable moderators provide better understanding of user acceptance of information technology.
MANY-BODY FORCES IN THE EQUATION OF STATE OF HYPERONIC MATTER

In this work we introduce an extended version of the formalism proposed originally by Taurines et al. that considers the effects of many-body forces simulated by nonlinear self-couplings and meson–meson interaction contributions. In this extended version of the model, we assume that matter is at zero temperature, charge neutral, and in beta-equilibrium, considering that the baryon octet interacts by the exchange of scalar–isoscalar (σ, &sgr; * ? > ), vector–isoscalar (ω, ϕ), vector–isovector ( ϱ ? > ), and scalar–isovector (δ) meson fields. Using nuclear matter properties, we constrain the parameters of the model that describe the intensity of the indirectly density dependent baryon–meson couplings to a small range of possible values. We then investigate asymmetric hyperonic matter properties. We report that the formalism developed in this work is in reasonable agreement with experimental data and also allows for the existence of massive hyperon stars (with more than 2 M ⊙ ? > ) with small radii, compatible with astrophysical observations.
AffectiveTweets: a Weka Package for Analyzing Affect in Tweets

AffectiveTweets is a set of programs for analyzing emotion and sentiment of social media messages such as tweets. It is implemented as a package for the Weka machine learning workbench and provides methods for calculating state-of-the-art affect analysis features from tweets that can be fed into machine learning algorithms implemented in Weka. It also implements methods for building affective lexicons and distant supervision methods for training affective models from unlabeled tweets. The package was used by several teams in the shared tasks: EmoInt 2017 and Affect in Tweets SemEval 2018 Task 1.
The size distribution and growth of manufacturing firms in C8te d'Ivoire

In this paper, we examine the size distribution of manufacturing firms in C6te d'Ivoire and analyse the underlying firm dynamics that generate the observed distribution. We also present the obstacles to firm growth, as they are perceived by the owners or managers of the firms. The size distribution is characterised by a relative overrepresentation of firms at both extremes of the size distribution. The emergence of this bimodal structure cannot be explained by a stochastic growth process of firms. Gibrat's Law is rejected asfirm size and firm age have a significant negative impact on the growth of firms. There is a highly positive and significant effect of the formal status of a firm on its growth performance. The significant role of this variable suggests that institutionalfactors can help to explain the observed dual size distribution.