Miracle-dz/UniFAR-FTUs huggingface dataset:
Everolimus in Breast Cancer

Objective: To highlight the potential role of pharmacists in facilitating use of everolimus in breast cancer and increase practitioner knowledge of everolimus therapy to enhance patient outcomes. Data Sources: A PubMed (1966 to May 2013) search included the terms everolimus, breast cancer, adverse events (AEs), pharmacist, and pharmacy. Abstracts presented at the American Society of Clinical Oncology 2012 Annual Meeting were also reviewed. Study Selection and Data Extraction: Articles published in English and directly related to everolimus clinical trials in breast cancer and other cancers were included, as were general pharmacy practice articles. Data Synthesis: Phase 3 clinical trials are currently exploring the efficacy of everolimus in combination therapy for breast cancer and the pharmacotherapeutical implications of the drug’s mechanism of action in relation to the PI3K/Akt pathway. Everolimus treatment–related topics relevant for pharmacists include drug administration, AE profile, potential drug interactions, dose adjustments, and comorbidity management. This comprehensive literature review of all components of everolimus treatment reveals the complexity of this treatment approach and the need for increased pharmacist involvement. Conclusions: Research based on the current treatment landscape and health care delivery system shows that pharmacists can greatly enhance patient care by providing teaching as part of a comprehensive cancer treatment approach. Because of their advanced knowledge of pharmacotherapy, pharmacists can directly support safe and effective use of everolimus while promoting optimal patient outcomes through a multidisciplinary approach that addresses comorbid conditions; they can also provide effective counseling and patient teaching in an ever-changing health care delivery system.
Mutation Analysis for System of Systems Policy Testing

A System of Systems (SoS) is a set of the constituent systems (CS) which has managerial and operational independence. To address an SoS-level goal that cannot be satisfied by each CS, an SoS policy guides or forces the CSs to collaborate with each other. If there is a fault in the SoS policy, SoS may fail to reach its goal, even if there is no fault in the CSs. Such a call for SoS policy testing leads to an essential question—how can testers evaluate the effectiveness of test cases? In this paper, we suggest a mutation analysis approach for SoS policy testing. Mutation analysis is a systematic way of evaluating test cases using artificial faults called mutants. As a general mutation framework for SoS policy testing, we present an overview of mutation analysis in SoS policy testing as well as the key aspects that must be defined in practice. To demonstrate the applicability of the proposed approach, we provide a case study using a traffic management SoS with the Simulation of Urban Mobility (SUMO) simulator. The results show that the mutation analysis is effective at evaluating fault detection effectiveness of test cases for SoS policies at a reasonable cost.
Poxvirus Tumor Necrosis Factor Receptor (TNFR)-Like T2 Proteins Contain a Conserved Preligand Assembly Domain That Inhibits Cellular TNFR1-Induced Cell Death

ABSTRACT The poxvirus tumor necrosis factor receptor (TNFR) homologue T2 has immunomodulatory properties; secreted myxoma virus T2 (M-T2) protein binds and inhibits rabbit TNF-α, while intracellular M-T2 blocks virus-induced lymphocyte apoptosis. Here, we define the antiapoptotic function as inhibition of TNFR-mediated death via a highly conserved viral preligand assembly domain (vPLAD). Jurkat cell lines constitutively expressing M-T2 were generated and shown to be resistant to UV irradiation-, etoposide-, and cycloheximide-induced death. These cells were also resistant to human TNF-α, but M-T2 expression did not alter surface expression levels of TNFRs. Previous studies indicated that T2's antiapoptotic function was conferred by the N-terminal region of the protein, and further examination of this region revealed a highly conserved N-terminal vPLAD, which is present in all poxvirus T2-like molecules. In cellular TNFRs and TNF-α-related apoptosis-inducing ligand (TRAIL) receptors (TRAILRs), PLAD controls receptor signaling competency prior to ligand binding. Here, we show that M-T2 potently inhibits TNFR1-induced death in a manner requiring the M-T2 vPLAD. Furthermore, we demonstrate that M-T2 physically associates with and colocalizes with human TNFRs but does not prevent human TNF-α binding to cellular receptors. Thus, M-T2 vPLAD is a species-nonspecific dominant-negative inhibitor of cellular TNFR1 function. Given that the PLAD is conserved in all known poxvirus T2-like molecules, we predict that it plays an important function in each of these proteins. Moreover, that the vPLAD confers an important antiapoptotic function confirms this domain as a potential target in the development of the next generation of TNF-α/TNFR therapeutics.
Spectral Efficiency in MIMO Systems Using Space and Pattern Diversities Under Compactness Constraints

The aim of this paper is to evaluate the performance of multiple-input-multiple-output (MIMO) systems using multimode patch antennas as basic elements. The focus is compactness in the antenna design and suitability for being deployed in relatively small terminals. To this purpose, the performance in terms of spectral efficiency of a MIMO system with small multimode patch antennas on the terminal side is presented. We assume no knowledge of the channel at the transmitter and perfect channel knowledge at the receiver. Several multielement multimode-antenna scenarios are compared to alternative scenarios with single-mode antennas.
Ieee Transactions on Affective Computing, Manuscript Id 1 Exploring Temporal Patterns in Classifying Frustrated and Delighted Smiles

—We create two experimental situations to elicit two affective states: frustration, and delight. In the first experiment, participants were asked to recall situations while expressing either delight or frustration, while the second experiment tried to elicit these states naturally through a frustrating experience and through a delightful video. There were two significant differences in the nature of the acted vs. natural occurences of expressions. First, the acted instances were much easier for the computer to classify. Second, in 90% of the acted cases, participants did not smile when frustrated, whereas in 90% of the natural cases, participants smied during the frustrating interaction, despite self-reporting significant frustration with the experience. As a follow up study, we develop an automated system to distinguish between naturally occurring spontaneous smiles under frustrating and delightful stimuli by exploring their temporal patterns given video of both. We extracted local and global features related to human smile dynamics. Next, we evaluated and compared two variants of Support Vector Machine (SVM), Hidden Markov Models (HMM), and Hidden-state Conditional Random Fields (HCRF) for binary classification. While human classification of the smile videos under frustrating stimuli was below chance, an accuracy of 92% distinguishing smiles under frustrating and delighted stimuli was obtained using a dynamic SVM classifier.
Quantitavely Comparing Virtual and Real Draping of Clothes

Several cloth modeling techniques have been proposed. Their main purpose is the realistic simulation of the garments of virtual actors for entertainment and advertising. In these areas, the main concern is to construct fast algorithms, able to produce impressive and qualitatively satisfactory draping of clothes. Other applications, as designing, manufacturing and selling real garments, call for a virtual draping which not only satisfies the human eye, but also closely mimics the real physical draping of clothes. From this viewpoint we will discuss some modeling techniques, and present some result concerning the quantitative comparison between the draping of real clothes and their virtual counterpart.
The neural substrates of natural reading: a comparison of normal and nonword text using eyetracking and fMRI

Most previous studies investigating the neural correlates of reading have presented text using serial visual presentation (SVP), which may not fully reflect the underlying processes of natural reading. In the present study, eye movements and BOLD data were collected while subjects either read normal paragraphs naturally or moved their eyes through “paragraphs” of pseudo-text (pronounceable pseudowords or consonant letter strings) in two pseudo-reading conditions. Eye movement data established that subjects were reading and scanning the stimuli normally. A conjunction fMRI analysis across natural- and pseudo-reading showed that a common eye-movement network including frontal eye fields (FEF), supplementary eye fields (SEF), and intraparietal sulci was activated, consistent with previous studies using simpler eye movement tasks. In addition, natural reading versus pseudo-reading showed different patterns of brain activation: normal reading produced activation in a well-established language network that included superior temporal gyrus/sulcus, middle temporal gyrus (MTG), angular gyrus (AG), inferior frontal gyrus, and middle frontal gyrus, whereas pseudo-reading produced activation in an attentional network that included anterior/posterior cingulate and parietal cortex. These results are consistent with results found in previous single-saccade eye movement tasks and SVP reading studies, suggesting that component processes of eye-movement control and language processing observed in past fMRI research generalize to natural reading. The results also suggest that combining eyetracking and fMRI is a suitable method for investigating the component processes of natural reading in fMRI research.
A data-driven approach to four-view image-based hair modeling

We introduce a novel four-view image-based hair modeling method. Given four hair images taken from the front, back, left and right views as input, we first estimate the rough 3D shape of the hair observed in the input using a predefined database of 3D hair models, then synthesize a hair texture on the surface of the shape, from which the hair growing direction information is calculated and used to construct a 3D direction field in the hair volume. Finally, we grow hair strands from the scalp, following the direction field, to produce the 3D hair model, which closely resembles the hair in all input images. Our method does not require that all input images are from the same hair, enabling an effective way to create compelling hair models from images of considerably different hairstyles at different views. We demonstrate the efficacy of our method using a wide range of examples.
Distributed Mining Model and Algorithm of Association Rules for Chain Retail Enterprise

Association rules discovery is the most important and demanding task of retail enterprises data mining. It has reflected the interesting related relation of products and is helpful to make correct decisions for retail enterprises. The paper describes distributed mining technology which is suitable for retail enterprise mining, the paper analyzes its distributed management system from three aspects: 1. the communication bandwidth, 2. branch storepsilas quantity 3. the characteristics of local database, and divides chain retail enterprises into two types in term of their distributed management systems. Define two kinds of retail enterprises; they are chain retail enterprise based on massed learning and chain retail enterprise based on dispersed learning. In order to satisfy mining task for two kinds of chain retail enterprise, the paper proposes two mining models and corresponding algorithms, finally do two contrast experiments under the simulation distributed setting. From the results of experiments, two algorithms ran well on corresponding chain retail enterprises.
R-FCN-3000 at 30fps: Decoupling Detection and Classification

We propose a modular approach towards large-scale real-time object detection by decoupling objectness detection and classification. We exploit the fact that many object classes are visually similar and share parts. Thus, a universal objectness detector can be learned for class-agnostic object detection followed by fine-grained classification using a (non)linear classifier. Our approach is a modification of the R-FCN architecture to learn shared filters for performing localization across different object classes. We trained a detector for 3000 object classes, called R-FCN-3000, that obtains an mAP of 34.9% on the ImageNet detection dataset. It outperforms YOLO-9000 by 18% while processing 30 images per second. We also show that the objectness learned by R-FCN-3000 generalizes to novel classes and the performance increases with the number of training object classes - supporting the hypothesis that it is possible to learn a universal objectness detector. Code will be made available.
Representing space and objects in monkeys and apes

Primate foraging can be construed as a set of interconnected problems that include finding food, selecting efficient travel routes, anticipating the positions of moving prey, and manipulating, and occasionally, extracting food items using tools. The evidence reviewed in this paper strongly suggests that both monkeys and apes use three types of representation (i.e., static, dynamic, and relational) to solve various problems. Static representations involve recalling certain features of the environment, dynamic representations involve imagining changes in the trajectories of moving objects, and relational representations involve encoding the properties of objects in relation to other objects. Contrary to previous claims, no clear differences were found between the representational skills of monkeys and apes. Current evidence also suggests that primates may be better at representing general compared to specific problem features. Finally, we have characterized the domains of space and objects as complementary and indicated future lines of research in these domains.
Analysis of topologies of synchronous machine with full converters applied in wind power

The development of many technologies has provided a fast growth in the wind power. In this context, the variable speed wind turbines are preferred because more power is extracted from the wind. The synchronous machines has been gained attention because eliminates the gearbox, source of many mechanical problems. Moreover, the use of full converters improves the performance of the system because the grid disturbances are not transmitted to the machine. In this context, this work compares the three main topologies of wind turbines using synchronous generators. The performance of these models will be compared when voltage sags occur and will be discussed the strengths and weaknesses of each technology.
Representation models for text classification: a comparative analysis over three web document types

Text classification constitutes a popular task in Web research with various applications that range from spam filtering to sentiment analysis. To address it, patterns of co-occurring words or characters are typically extracted from the textual content of Web documents. However, not all documents are of the same quality; for example, the curated content of news articles usually entails lower levels of noise than the user-generated content of the blog posts and the other Social Media. In this paper, we provide some insight and a preliminary study on a tripartite categorization of Web documents, based on inherent document characteristics. We claim and support that each category calls for different classification settings with respect to the representation model. We verify this claim experimentally, by showing that topic classification on these different document types offers very different results per type. In addition, we consider a novel approach that improves the performance of topic classification across all types of Web documents: namely the n-gram graphs. This model goes beyond the established bag-of-words one, representing each document as a graph. Individual graphs can be combined into a class graph and graph similarities are then employed to position and classify documents into the vector space. Accuracy is increased due to the contextual information that is encapsulated in the edges of the n-gram graphs; efficiency, on the other hand, is boosted by reducing the feature space to a limited set of dimensions that depend on the number of classes, rather than the size of the vocabulary. Our experimental study over three large-scale, real-world data sets validates the higher performance of n-gram graphs in all three domains of Web documents.
Energy metabolic state in hypothermically stored boar spermatozoa using a revised protocol for efficient ATP extraction

ABSTRACT Mammalian spermatozoa utilize ATP as the energy source for key functions on the route to fertilization. ATP and its precursor nucleotides ADP and AMP are regularly investigated in sperm physiology studies, mostly by bioluminescence assays. Assay results vary widely, mainly due to different efficiencies in nucleotide extraction and prevention of their enzymatic degradation. Here, we describe a revised, validated protocol for efficient phosphatase inhibition and adenine nucleotide extraction resulting in consistently high ATP concentrations exceeding previously reported values for boar spermatozoa up to 20-fold. The revised assay is applicable for determining ATP concentrations and adenylate energy charge in extracts from fresh and frozen samples, thereby allowing simultaneous assessment of semen samples from long-term storage experiments. After validation, the assay was applied to liquid-preserved boar spermatozoa stored at 17°C and 5°C for 24 and 72 h. Cooling to 5°C, but not storage duration, reduced ATP concentration in spermatozoa (P<0.05), which was accompanied by the appearance of AMP and ADP in the preservation medium. ATP and energy charge were highly correlated to the proportion of membrane-intact spermatozoa, supporting the idea of nucleotides leaking through disrupted membranes in cold-shocked cells. The present assay allows highly standardized studies of energy metabolism in spermatozoa. Summary: A revised protocol for efficient extraction of ATP from boar spermatozoa is presented that consistently yields high ATP contents and energy charge values from fresh and frozen samples.
Diversity, Endemism, and Age Distributions in Macroevolutionary Sources and Sinks

Quantitative tests of historical hypotheses are necessary to advance our understanding of biogeographic patterns of species distributions, but direct tests are often hampered by incomplete fossil or historical records. Here we present an alternative approach in which we develop a dynamic model that allows us to test hypotheses about regional rates of taxon origination, extinction, and dispersal using information on ages and current distributions of taxa. With this model, we test two assumptions traditionally made in the context of identifying regions as “centers of origin”—that regions with high origination rates will have high diversity and high endemism. We find that these assumptions are not necessarily valid. We also develop expressions for the regional age distributions of extant taxa and show that these may yield better insight into regional evolutionary rates. We then apply our model to data on the biogeography and ages of extant genera of marine bivalves and conclude that diversity in polar regions predominantly reflects dispersal of taxa that evolved elsewhere rather than in situ origination‐extinction dynamics.
Blind Predictions of DNA and RNA Tweezers Experiments with Force and Torque

Single-molecule tweezers measurements of double-stranded nucleic acids (dsDNA and dsRNA) provide unprecedented opportunities to dissect how these fundamental molecules respond to forces and torques analogous to those applied by topoisomerases, viral capsids, and other biological partners. However, tweezers data are still most commonly interpreted post facto in the framework of simple analytical models. Testing falsifiable predictions of state-of-the-art nucleic acid models would be more illuminating but has not been performed. Here we describe a blind challenge in which numerical predictions of nucleic acid mechanical properties were compared to experimental data obtained recently for dsRNA under applied force and torque. The predictions were enabled by the HelixMC package, first presented in this paper. HelixMC advances crystallography-derived base-pair level models (BPLMs) to simulate kilobase-length dsDNAs and dsRNAs under external forces and torques, including their global linking numbers. These calculations recovered the experimental bending persistence length of dsRNA within the error of the simulations and accurately predicted that dsRNA's “spring-like” conformation would give a two-fold decrease of stretch modulus relative to dsDNA. Further blind predictions of helix torsional properties, however, exposed inaccuracies in current BPLM theory, including three-fold discrepancies in torsional persistence length at the high force limit and the incorrect sign of dsRNA link-extension (twist-stretch) coupling. Beyond these experiments, HelixMC predicted that ‘nucleosome-excluding’ poly(A)/poly(T) is at least two-fold stiffer than random-sequence dsDNA in bending, stretching, and torsional behaviors; Z-DNA to be at least three-fold stiffer than random-sequence dsDNA, with a near-zero link-extension coupling; and non-negligible effects from base pair step correlations. We propose that experimentally testing these predictions should be powerful next steps for understanding the flexibility of dsDNA and dsRNA in sequence contexts and under mechanical stresses relevant to their biology.
A High-Frequency Link Multilevel Cascaded Medium-Voltage Converter for Direct Grid Integration of Renewable Energy Systems

Recent advances in solid-state semiconductors have led to the development of medium-voltage power converters (e.g., 6-36 kV) which could obviate the need for the step-up transformers of renewable power generation systems. The modular multilevel cascaded converters have been deemed as strong contenders for the development of medium-voltage converters, but the converters require multiple isolated and balanced dc supplies. In this paper, a high-frequency link multilevel cascaded medium-voltage converter is proposed. The common high-frequency link generates multiple isolated and balanced dc supplies for the converter, which inherently minimizes the voltage imbalance and common mode issues. An 11-kV system is designed and analyzed taking into account the specified system performance, control complexity, cost, and market availability of the power semiconductors. To verify the feasibility of the proposed system, a scaled down 1.73-kVA laboratory prototype test platform with a modular five-level cascaded converter is developed and explored in this paper, which converts a 210 V dc (rectified generator voltage) into three-phase 1 kV rms 50 Hz ac. The experimental results are analyzed and discussed. It is expected that the proposed new technology will have great potential for future renewable generation systems and smart grid applications.
Role of microprojections in myoendothelial feedback – a theoretical study

• Endothelial microprojections (MPs) are cellular extensions of endothelial cells (ECs) that may be involved in regulation of smooth muscle cell (SMC) constriction in blood vessels. • We developed computational models to investigate the role of MPs in generating EC feedback during SMC stimulation. The models account for the geometry of MPs and heterogeneous distribution of membrane channels and receptors in an EC. • Simulations show that SMC stimulation causes calcium release in and around EC MPs that activates hyperpolarizing currents in ECs and moderates SMC constriction. • The results help us better understand the mechanisms that regulate blood flow and pressure.