Miracle-dz/UniFAR-FTUs huggingface dataset:
Co-occurrence features characterizing gland distribution patterns as new prognostic markers in prostate cancer whole-slide images

Classifying whole-slide images of prostate cancer resections to derive an accurate prognosis for tumor progression is a highly challenging problem. We here introduce a novel type of high-level features which operate on the gland level for the application in computer-aided prognosis using a Tissue Phenomics approach. Since tissue architecture, and in particular, the gland distribution possibly provide information on the aggressiveness of the individual tumor, our features exploit the spatial relationship of different gland types. Glands are classified into cancerous and healthy glands, and also, into morphological classes based on size and shape. Co-occurrences of the classified glands are quantified and Haralick-like features are computed based on the derived gland co-occurrence matrices. The resulting gland co-occurrence features are mined to automatically determine the best parametrization. In experiments on whole-slide images it turned out that our novel features allow accurate stratification of patients into the prognostic groups tumor progression and nonprogression outperforming clinical features. Our results indicate a strong correlation of tumor progression with invasion phenotypes.
The Anabaptist Story: An Introduction to Sixteenth-Century Anabaptism

Four hundred seventy years ago the Anabaptist movement was launched with the inauguration of believer's baptism and the formation of the first congregation of the Swiss Brethren in Zurich, Switzerland. This standard introduction to the history of Anabaptism by noted church historian William R. Estep offers a vivid chronicle of the rise and spread of teachings and heritage of this important stream in Christianity. This third edition of "The Anabaptist Story" has been substantially revised and enlarged to take into account the numerous Anabaptist sources that have come to light in the last half-century as well as the significant number of monographs and other scholarly works on Anabaptist themes that have recently appeared. Estep challenges a number of assumptions held by contemporary historians and offers fresh insights into the Anabaptist movement.
Hydrogen sulfide is essential for Schwann cell responses to peripheral nerve injury

Hydrogen sulfide (H2S) functions as a physiological gas transmitter in both normal and pathophysiological cellular events. H2S is produced from substances by three enzymes: cystathionine β‐synthase (CBS), cystathionine γ‐lyase (CSE), and 3‐mercaptopyruvate sulfurtransferase (MST). In human tissues, these enzymes are involved in tissue‐specific biochemical pathways for H2S production. For example, CBS and cysteine aminotransferase/MST are present in the brain, but CSE is not. Thus, we examined the expression of H2S production‐related enzymes in peripheral nerves. Here, we found that CSE and MST/cysteine aminotransferase, but not CBS, were present in normal peripheral nerves. In addition, injured sciatic nerves in vivo up‐regulated CSE in Schwann cells during Wallerian degeneration (WD); however, CSE was not up‐regulated in peripheral axons. Using an ex vivo sciatic nerve explant culture, we found that the inhibition of H2S production broadly prevented the process of nerve degeneration, including myelin fragmentation, axonal degradation, Schwann cell dedifferentiation, and Schwann cell proliferation in vitro and in vivo. Thus, these results indicate that H2S signaling is essential for Schwann cell responses to peripheral nerve injury.
Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS

A need exists for technologies that permit the direct quantification of differences in protein and posttranslationally modified protein expression levels. Here we present a strategy for the absolute quantification (termed AQUA) of proteins and their modification states. Peptides are synthesized with incorporated stable isotopes as ideal internal standards to mimic native peptides formed by proteolysis. These synthetic peptides can also be prepared with covalent modifications (e.g., phosphorylation, methylation, acetylation, etc.) that are chemically identical to naturally occurring posttranslational modifications. Such AQUA internal standard peptides are then used to precisely and quantitatively measure the absolute levels of proteins and posttranslationally modified proteins after proteolysis by using a selected reaction monitoring analysis in a tandem mass spectrometer. In the present work, the AQUA strategy was used to (i) quantify low abundance yeast proteins involved in gene silencing, (ii) quantitatively determine the cell cycle-dependent phosphorylation of Ser-1126 of human separase protein, and (iii) identify kinases capable of phosphorylating Ser-1501 of separase in an in vitro kinase assay. The methods described here represent focused, alternative approaches for studying the dynamically changing proteome.
What Affects the Implied Cost of Equity Capital?

We estimate implied cost of equity capital for a sample of firms from 1984 to 1998 using the Ohlson and Juettner (2000) model that does not make restrictive assumptions about clean surplus and payout policies. We find that cost of equity capital is strongly positively associated with conventional risk factors such as earnings variability, systematic and unsystematic return volatility, and leverage, and is negatively associated with analyst following. These associations are robust to controls for industry membership and to running the regression in changes instead of levels. Our results support the Ohlson-Juettner metric as a robust and appealing measure of cost of equity capital.
An Optimized Cooperative Beamforming Scheme in MIMO Relay Broadcast Channels

We consider relay broadcast channels (RBCs) with multiple antennas at all nodes. A practical linear precoding, relaying and combining scheme is proposed. Under an overall power constraint, we derive the optimal power allocation solution in a closed form. A low complexity beamforming vector optimization algorithm is proposed to maximize the effective channel gains and improve the system performance. Simulation results are presented for various channel configurations, which show that the proposed optimized beamforming algorithm achieves performance very close to that of the exhaustive search algorithm but with a much lower complexity, and the maximum diversity gain is always attained.
Experimental analysis of the errors induced into Linux by three fault injection techniques

The main goal of the experimental stud), reported in this paper is to investigate to what extent distinct fault injection techniques lead to similar consequences (errors and failures). The target system we are using to carry out our investigation is the Linux kernel as it provides a representative operating system. It is featuring full controllability and observability thanks to its open source status. Three types of software-implemented fault injection techniques are considered, namely: i) provision of invalid values to the parameters of the kernel calls, ii) corruption of the parameters of the kernel calls, and iii) corruption of the input parameters of the internal functions of the kernel. The workload being used for the experiments is tailored to activate selectively each functional component. The observations encompass typical kernel failure modes (e.g., exceptions and kernel hangs) as well as a detailed analysis of the reported error codes.
Studies on the Metabolism and Biological Activity of the Epimers of Sulindac

Sulindac is a nonsteroidal, anti-inflammatory drug (NSAID) that has also been studied for its anticancer activity. Recent studies suggest that sulindac and its metabolites act by sensitizing cancer cells to oxidizing agents and drugs that affect mitochondrial function, resulting in the production of reactive oxygen species and death by apoptosis. In contrast, normal cells are not killed under these conditions and, in some instances, are protected against oxidative stress. Sulindac has a methyl sulfoxide moiety with a chiral center and was used in all of the previous studies as a mixture of the R- and S-epimers. Because epimers of a compound can have very different chemical and biological properties, we have separated the R- and S-epimers of sulindac, studied their individual metabolism, and performed preliminary experiments on their effect on normal and lung cancer cells exposed to oxidative stress. Previous results had indicated that the reduction of (S)-sulindac to sulindac sulfide, the active NSAID, was catalyzed by methionine sulfoxide reductase (Msr) A. In the present study, we purified an enzyme that reduces (R)-sulindac and resembles MsrB in its substrate specificity. The oxidation of both epimers to sulindac sulfone is catalyzed primarily by the microsomal cytochrome P450 (P450) system, and the individual enzymes responsible have been identified. (S)-Sulindac increases the activity of the P450 system better than (R)-sulindac, but both epimers increase primarily the enzymes that oxidize (R)-sulindac. Both epimers can protect normal lung cells against oxidative damage and enhance the killing of lung cancer cells exposed to oxidative stress.
Translational readthrough generates new astrocyte AQP4 isoforms that modulate supramolecular clustering, glial endfeet localization, and water transport

Regulation of water homeostasis is a central feature of central nervous system pathophysiology. In this context, several lines of evidence suggest a crucial role for the water channel aquaporin‐4 (AQP4) and its plasma membrane supramolecular organization as the key element. Here, we demonstrate the expression in tissues of additional isoforms of AQP4 characterized by a C‐terminal extension generated by programmed translational readthrough. These extended isoforms (AQP4ex) display a perivascular polarization and expression in dystrophin‐dependent pools. AQP4ex reduces supramolecular clustering tendency and allows AQP4 interactions with syntrophin. Furthermore, site‐directed mutagenesis of two serines in the extended C‐terminus of AQP4ex showed potential regulation of water permeability by phosphorylation. Finally, AQP4ex expression can be positively modulated by gentamicin treatment, demonstrating the possibility of regulating the AQP4 translational readthrough frequency. This novel regulatory mechanism could have important pathophysiological implications for conditions in which alternations have been reported in AQP4 structure.
On the minimum time optimal control problem of an aircraft in its climbing phase

In this article, the minimum time optimal control problem of an aircraft in its climbing phase is studied.First, a reduction of the initial dynamics into a three dimensional single-input system with a linear de-pendence with respect to the control is performed. This reduced system is then studied using geometriccontrol techniques. In particular, the maximum principle leads to describe a multi-point boundary valueproblem which is solved by indirect methods. These methods are the implementation of the maximumprinciple and are initialized by direct methods. We check that the extremal solution of the boundary valueproblem satisfies necessary and sufficient conditions of optimality. From this reference case and consider-ing small-time optimal trajectories, we give a local classification with respect to the initial mass and finalvelocity of BC-extremals for the climbing phase.
Data compression techniques for improving of performance and reliability of a multifunctional radio receiving center

In this paper we consider the structure of a multifunctional radio receiving center. We talk about the issues of narrowband signals performance and reliability and the spectral mapping storage subsystem. The article presents two methods of reducing the volume of the data recorded and broadcast through the network. We have described the algorithm of the digital signal data packaging and have identified its application limits.
Clustering Techniques for Document Classification

This paper is intended to study the existing classification and information retrieval techniques in order to use an algorithm that will group the a set of documents. Therefore, the unfolding of knowledge in texts is selected as the proper methodology to be followed and the steps are explained in order to reach the unsupervised documents classification. After conducting an experiment with three of the most known methods of unsupervised documents classification and the assessment of the results with the Silhoutte index, it could be observed that the better grouping was with four groups, whose main characteristic was to deal with subjects such as: information management information, systems
A Differentiable Transition Between Additive and Multiplicative Neurons

Existing approaches to combine both additive and multiplicative neural units either use a fixed assignment of operations or require discrete optimization to determine what function a neuron should perform. However, this leads to an extensive increase in the computational complexity of the training procedure. We present a novel, parameterizable transfer function based on the mathematical concept of non-integer functional iteration that allows the operation each neuron performs to be smoothly and, most importantly, differentiablely adjusted between addition and multiplication. This allows the decision between addition and multiplication to be integrated into the standard backpropagation training procedure.
Quantitative and Qualitative Differences in the T Cell Response to HIV in Uninfected Ugandans Exposed or Unexposed to HIV-Infected Partners

ABSTRACT HIV-exposed and yet persistently uninfected individuals have been an intriguing, repeated observation in multiple studies, but uncertainty persists on the significance and implications of this in devising protective strategies against HIV. We carried out a cross-sectional analysis of exposed uninfected partners in a Ugandan cohort of heterosexual serodiscordant couples (37.5% antiretroviral therapy naive) comparing their T cell responses to HIV peptides with those of unexposed uninfected individuals. We used an objective definition of exposure and inclusion criteria, blinded ex vivo and cultured gamma interferon (IFN-γ) enzyme-linked immunospot assays, and multiparameter flow cytometry and intracellular cytokine staining to investigate the features of the HIV-specific response in exposed versus unexposed uninfected individuals. A response rate to HIV was detectable in unexposed uninfected (5.7%, 95% confidence interval [CI] = 3.3 to 8.1%) and, at a significantly higher level (12.5%, 95% CI = 9.7 to 15.4%, P = 0.0004), in exposed uninfected individuals. The response rate to Gag was significantly higher in exposed uninfected (10/50 [20.%]) compared to unexposed uninfected (1/35 [2.9%]) individuals (P = 0.0004). The magnitude of responses was also greater in exposed uninfected individuals but not statistically significant. The average number of peptide pools recognized was significantly higher in exposed uninfected subjects than in unexposed uninfected subjects (1.21 versus 0.47; P = 0.0106). The proportion of multifunctional responses was different in the two groups, with a higher proportion of single cytokine responses, mostly IFN-γ, in unexposed uninfected individuals compared to exposed uninfected individuals. Our findings demonstrate both quantitative and qualitative differences in T cell reactivity to HIV between HESN (HIV exposed seronegative) and HUSN (HIV unexposed seronegative) subject groups but do not discriminate as to whether they represent markers of exposure or of protection against HIV infection.
Decomposing multilayer transportation networks using complex network analysis: a case study for the Greek aviation network

This article studies the topology of the multiplex Greek Aviation Network (GAN) consisting of layers representing networks of the aviation companies that operate in the regional Greek aviation market, by using complex network analysis and empirical techniques. The purpose of the study is to decode the strategic plans of the aviation companies constituting multiplex network’s layers and to evaluate which layer contributes more in the composition of the overlaid GAN. Secondarily, this paper evaluates the operational utility of a new centrality measure, named mobility centrality, regarding its ability to quantify the potential that a node attribute induces to the topology of the network. Under an overall assessment, this article advances multilayer network analysis by applying a multivariate regression technique for evaluating in common the participation of each layer to the formation of the overlaid network and it provides insights on transportation management and policy.
Plant trace generation for formal plant model inference: Methods and case study

Cyber-physical system correctness can be ensured by employing formal methods, including model inference. A rather new direction of research is using formal plant models for closed-loop verification and inferring these models from execution traces of the system. Since the quality of the resulting model heavily depends on trace coverage, in this paper we propose efficient methods for automatic plant trace generation. A method of checking the conformance between system and generated models is suggested and is used to analyze traces generation and model inference methods. Modifications of plant model inference approaches are proposed and comparison of the resulting models is performed.
Optimal linear precoding for indoor visible light communication system

Visible light communication (VLC) is an emerging technique that uses light-emitting diodes (LED) to combine communication and illumination. It is considered as a promising scheme for indoor wireless communication that can be deployed at reduced costs while offering high data rate performance. In this paper, we focus on the design of the downlink of a multi-user VLC system. Inherent to multi-user systems is the interference caused by the broadcast nature of the medium. Linear precoding based schemes are among the most popular solutions that have recently been proposed to mitigate inter-user interference. This paper focuses on the design of the optimal linear precoding scheme that solves the max-min signal-to-interference-plus-noise ratio (SINR) problem. The performance of the proposed precoding scheme is studied under different working conditions and compared with the classical zero-forcing precoding. Simulations have been provided to illustrate the high gain of the proposed scheme.
Comparative Study of k-means and k-Means++ Clustering Algorithms on Crime Domain

This study presents the results of an experimental study of two document clustering techniques which are k-means and k-means++. In particular, we compare the two main approaches in crime document clustering. The drawback of k-means is that the user needs to define the centroid point. This becomes more critical when dealing with document clustering because each center point represented by a word and the calculation of distance between words is not a trivial task. To overcome this problem, a k-means++ was introduced in order to find a good initial center point. Since k-means++ has not being applied before in crime document clustering, this study presented a comparative study between k-means and k-means++ to investigate whether the initialization process in k-means++ does help to get a better results than k-means. We proposes the k-means++ clustering algorithm, to identify best seed for initial cluster centers in clustering crime document. The aim of this study is to conduct a comparative study of two main clustering algorithms, namely k-means and k-means++. The method of this study includes a pre-processing phase, which in turn involves tokeniza-tion, stop-words removal and stemming. In addition, we evaluate the impact of the two similarity/distance measures (Cosine similarity and Jaccard coefficient) on the results of the two clustering algorithms. Exper-imental results on several settings of the crime data set showed that by identifying the best seed for initial cluster centers, k-mean++ can significantly (with the significance interval at 95%) work better than k-means. These results demonstrate the accuracy of k-mean++ clustering algorithm in clustering crime doc-uments.
Design optimization of spoke-type ferrite magnet machines by combined design of experiments and differential evolution algorithms

In this paper, a combined design optimization method utilizing Design of Experiments (DOE) and Differential Evolution (DE) algorithms was implemented to provide practical insights in the multi-objective design optimization of a 12-slot, 8-pole, spoke-type, ferrite magnet machine, with fractional-slot concentrated windings. A robust parametric model of this type of machine is provided here. In this combined design optimization approach, the Central Composite Design (CCD) method, as one of the DOE approaches, was used to perform the variables sensitivity study, from which the significant design variables were selected and the corresponding variables ranges were defined, for the DE design optimization procedure. A Computationally Efficient-Finite Element Analysis (CE-FEA) approach was utilized to estimate the performance and characteristics of 3000 candidate designs. From the study of design objectives utilizing the pareto-set and color maps, three candidate designs with minimized losses, material cost and torque ripple were compared.
Treatment of Social Phobia with Atenolol

Social phobia is the least well studied phobic disorder of those included in DSM-III. Reports from the British literature indicate that the condition is a distinct one that usually begins in adolescence and affects males more often than females. Patients characteristically complain of somatic symptoms and a fear of humiliation when confronted with specific social stimuli. Ten social phobic patients were openly treated with the cardioselective, peripherally active β-adrenergic blocking drug atenolol. Five patients had complete response and four had moderate response. Side effects were minimal. Atenolol appears to work in social phobic patients by reducing autonomic nervous system response to phobic stimuli. (J Clin Psychopharmacol 1985;5:298–301)
Intelligent techniques for electrical power system restoration

Today's society depends heavily upon a high level of power system reliability. Accordingly, it is very important not only to avoid power failures, but also to restore power systems quickly and safely if these failures happen. In that sense, utilities arc becoming increasingly interested in developing computer aided restoration systems. This paper presents an intelligent techniques using artificial neural network (ANN) to generate and implement a dynamic restoration plan for a partial or total blackout in a bulk power system. The final output of this research could be used in the centers of operation of the system, assisting the operators during emergency situations.