Miracle-dz/UniFAR-FTUs huggingface dataset:
Age- and Sex-Specific Reference Values for Media/Lumen Ratio in Small Arteries and Relationship With Risk Factors

Small-artery remodeling is an early feature of target organ damage in hypertension and retains a negative prognostic value. The aim of the study is to establish age- and sex-specific reference values for media/lumen in small arteries obtained in humans by biopsy. Data from 91 healthy individuals and 200 individuals with cardiovascular risk factors in primary prevention from 4 Italian centers were pooled. Sex-specific equations for media/lumen in the healthy subpopulation, with age as dependent variable, were calculated. These equations were used to calculate predicted media/lumen values in individuals with risk factors and Z scores. The association between classical risk factors and Z scores was then explored by multiple regression analysis. A second-degree polynomial equation model was chosen to obtain sex-specific equations for media/lumen, with age as dependent variable. In the population with risk factors (111 men, age 50.5±14.0 years, hypertension 80.5%), media/lumen Z scores were independently associated with body mass index (standardized &bgr;=0.293, P=0.0001), total cholesterol (&bgr;=0.191, P=0.031), current smoking (&bgr;=0.238, P=0.0005), fasting blood glucose (&bgr;=0.204, P=0.003), systolic blood pressure (&bgr;=0.233, P=0.023), and female sex (&bgr;=0.799, P=0.038). A significant interaction between female sex and total cholesterol was found (&bgr;=−0.979, P=0.014). Results were substantially similar in the hypertensive subgroup. A method to calculate individual values of remodeling and growth index based on reference values was also presented. Age- and sex-specific percentiles of media/lumen in a healthy population were estimated. In a predominantly hypertensive population, media/lumen Z scores were associated with major cardiovascular risk factors, including body mass index, cholesterol, smoking, glucose, and systolic blood pressure. Significant sex differences were observed.
Dynamic resource allocation for shared data centers using online measurements

Since web workloads are known to vary dynamically with time, in this paper, we argue that dynamic resource allocation techniques are necessary to provide guarantees to web applications running on shared data centers. To address this issue, we use a system architecture that combines online measurements with prediction and resource allocation techniques. To perform resource allocation, we model a server resource that services multiple applications as a generalized processor sharing (GPS) server. We use a time-domain description of the server to model transient system states and use a constrained non-linear optimization technique to dynamically allocate the server resources. The parameters of this model are continuously updated using an online monitoring and prediction framework. Our prediction technique is based on an autoregressive stochastic process model. The main goal of our techniques is to react to changing workloads by dynamically varying the resource shares of applications. In addition, these techniques can also handle nonlinearity in system behavior unlike some prior techniques. We evaluate our techniques using simulations with synthetic as well as real-world web workloads. Our results show that these techniques can judiciously allocate system resources, especially under transient overload conditions.
HAVE LESS EFEICIENT SUPPRESSION MECHANISMS

One approach io understanding the component processes and mechanisms underlying adult reading skill is to compare the performance of more skilled and less skilled readers on laboratory experiments. The results of some recent experiments employing this approach demonstrate that less skilled adult readers suppress less efficiently the inappropriate meanings of ambiguous words (e.g., the playing card vs. garden tool meanings of spadej, the incorrect forms of homophones (e.g., patients V5. patience), the typical-but-absent members of scenes (e.g., a tractor in a farm scene), and words superimposed on pictures. Less skilled readers are not less efficient in activating contextuaity appropriate information; in fact, they activate contextually appropriate information more strongly than more skilled readers do. Therefore, one conclusion that can be drawn from these experiments is that less skilled adult readers suffer from less efficient suppression
Adenovirus E3-10.4K/14.5K protein complex inhibits tumor necrosis factor-induced translocation of cytosolic phospholipase A2 to membranes

We have reported that three adenovirus (Ad) proteins, named E3-10.4K/14.5K, E3-14.7K, and E1B-19K, independently inhibit tumor necrosis factor (TNF)-induced apoptosis in Ad-infected cells. E3-10.4K/14.5K and E3-14.7K also inhibit TNF-induced release of arachidonic acid (AA). TNF-induced apoptosis and AA release are thought to require TNF-activation of the 85-kDa cytosolic phospholipase A2 (cPLA2). cPLA2 normally exists in a latent form in the cytosol; it is activated by phosphorylation by mitogen-activated protein kinase, and in the presence of agents that mobilize intracellular Ca2+, cPLA2 translocates to membranes where it cleaves AA from membrane phospholipids. We now report that TNF induces translocation of cPLA2 from the cytosol to membranes in Ad-infected human A549 cells and that E3-10.4K/14.5K but not E3-14.7K or E1B-19K is required to inhibit TNF-induced translocation of cPLA2. Ad infection also inhibited TNF-induced release of AA. Under the same conditions, Ad infection did not inhibit TNF-induced phosphorylation of cPLA2 or TNF activation of NFkappaB. Ad infection also inhibited cPLA2 translocation in response to the Ca2+ ionophore A23187 and to cycloheximide, but this inhibition did not require E3-10.4K/14.5K. Ad infection did not inhibit cPLA2 translocation in response to interleukin-1beta or platelet-derived growth factor. We propose that E3-10.4K/14.5K inhibits TNF-induced AA release and apoptosis by directly or indirectly inhibiting TNF-induced translocation of cPLA2 from the cytosol to membranes. AA formed by cPLA2 can be metabolized to prostaglandins, leukotrienes, and lipoxyns, molecules that amplify inflammation. E3-10.4K/14.5K probably functions in Ad infections to inhibit both TNF-induced apoptosis and inflammation.
High‐load strength training improves outcome in patients with plantar fasciitis: A randomized controlled trial with 12‐month follow‐up

The aim of this study was to investigate the effectiveness of shoe inserts and plantar fascia‐specific stretching vs shoe inserts and high‐load strength training in patients with plantar fasciitis. Forty‐eight patients with ultrasonography‐verified plantar fasciitis were randomized to shoe inserts and daily plantar‐specific stretching (the stretch group) or shoe inserts and high‐load progressive strength training (the strength group) performed every second day. High‐load strength training consisted of unilateral heel raises with a towel inserted under the toes. Primary outcome was the foot function index (FFI) at 3 months. Additional follow‐ups were performed at 1, 6, and 12 months. At the primary endpoint, at 3 months, the strength group had a FFI that was 29 points lower [95% confidence interval (CI): 6–52, P = 0.016] compared with the stretch group. At 1, 6, and 12 months, there were no differences between groups (P > 0.34). At 12 months, the FFI was 22 points (95% CI: 9–36) in the strength group and 16 points (95% CI: 0–32) in the stretch group. There were no differences in any of the secondary outcomes. A simple progressive exercise protocol, performed every second day, resulted in superior self‐reported outcome after 3 months compared with plantar‐specific stretching. High‐load strength training may aid in a quicker reduction in pain and improvements in function.
The farnesoid X receptor and colon cancer

The farnesoid X receptor and colon cancer Guofeng Xie, Jean-Pierre Raufman Division of Gastroenterology and Hepatology, Veterans Affairs Maryland Health Care System, University of Maryland School of Medicine, Baltimore, MD 21201, USA. Correspondence to: Dr. Guofeng Xie, Division of Gastroenterology and Hepatology, Veterans Affairs Maryland Health Care System, University of Maryland School of Medicine, 22 South Greene Street, Baltimore, MD 21201, USA. E-mail: gxie@medicine.umaryland. edu Worldwide, colorectal cancer (CRC) is a leading cause of cancer death, primarily because of limited therapeutic options for those with advanced disease. The farnesoid X receptor (FXR) is a member of the nuclear receptor superfamily of ligand-activated transcription factors. Besides its prominent role in bile acid synthesis, and lipoprotein and glucose metabolism, recent data indicate that FXR also plays a key role in regulating intestinal cell proliferation and carcinogenesis. Here, we review the role of FXR as a tumor suppressor in CRC, with particular emphasis on the molecular mechanisms underlying FXR-dependent tumorigenesis and its regulation, FXR-bile acid relationships and FXR-targeted drugs as potential therapeutic agents.
Computational Approaches to Storytelling and Creativity

This paper deals with computational approaches to storytelling, or the production of stories by computers, with a particular attention on the way human creativity is modelled or emulated, also in computational terms. Features relevant to creativity and to stories are analysed, and existing systems are reviewed under the light of that analysis. The extent to which they implement the key features proposed in recent models of computational creativity is discussed. Limitations, avenues of future research and expected trends are outlined.
Functional MRI of swallowing: From neurophysiology to neuroplasticity

Swallowing is a complex neurogenic sensorimotor process involving all levels of the neuraxis and a vast number of muscles and anatomic structures. Disruption of any of these anatomic or functional components can lead to swallowing disorders (also known as dysphagia). Understanding the neural pathways that govern swallowing is necessary in diagnosing and treating patients with dysphagia. Functional MRI (fMRI) is a prevalent and effective neuroimaging method that has been used to study the complex neurophysiologic control of swallowing in vivo. This article presents a summary of the research studies that have used fMRI to study the neural control of swallowing in normal subjects and dysphagic patients, and to investigate the effects of swallowing treatments on neuroplasticity. Methodologic challenges and caveats are discussed, and a case study of a pre‐posttreatment paradigm is presented to highlight potential future directions of fMRI applications in swallowing research and clinical practice. © 2011 Wiley Periodicals, Inc. Head Neck, 2011
A neural network based fault detection and identification scheme for pneumatic process control valves

This paper outlines a method for detection and identification of actuator faults in a pneumatic process control valve using a neural network. First, the valve signature and dynamic error band tests, used by specialists to determine valve performance parameters, are carried out for a number of faulty operating conditions. A commercially available software package is used to carry out the diagnostic tests, thus eliminating the need for additional instrumentation of the valve. Next, the experimentally determined valve performance parameters are used to train a multilayer feedforward network to successfully detect and identify incorrect supply pressure, actuator vent blockage, and diaphragm leakage faults.
Investigation of transfer-free catalytic CVD graphene on SiO2 by means of conductive atomic force microscopy

Transfer-free graphene on SiO2 has been produced by catalytic chemical vapor deposition (CCVD) using an additional PMMA carbon source. During our CCVD process the graphene grows laterally, extending beyond prestructured metal catalyst perimeters, covering part of the SiO2 surface. The such grown graphene has been investigated by atomic force microscopy (AFM) showing a smooth surface with a roughness of Rums ~ 0.346 nm. However, by means of conductive AFM microscopic defects as well as graphene layer edges can be found in the graphene film. An electrical characterization of a field effect device shows a typical few-layer graphene subthreshold characteristic.
EUP-Growth +-Efficient Algorithm for Mining High Utility Itemset

In recent years, Utility mining becomes an emerging topicin the field of data mining. From a transaction database the discovery of itemsets with high utility like profits are referred as a high utility itemsets mining. In this paper, a new algorithm is proposed,named Enhanced Utility Pattern Growth + (EUP-Growth+), for reducing a large number of candidate itemsets for high utility itemsetswith a set of effective strategies. These strategies are used for pruning candidate itemsets effectively. By reducing a hefty number of candidate itemsets the mining performance upgrades in terms of execution time and space requirement. The selective information ofpotential high utility itemsetsare stored in the appropriate memory using a hashing technique and maintained in a tree-based data structure named Improved Utility Pattern Tree (IMUP-Tree). The performance of EUP-Growth+ is compared with the State-of-the-art algorithms on many types of both real and synthetic data sets. Experimental and comparative results reveal that the proposed algorithms, EUP-Growth+, not only reduce the number of PHUIs effectivelybut also outperform other algorithms.
CONCURRENT MANUFACTURING SYSTEM OPTIMIZATION FOR TWO-PRODUCT OPERATION

Product/process design and optimization are typically aimed at a single product for a single customer. Such approach, however, often leads to underutilization of available production capacity. It is therefore reasonable for the manufacturer to make an effort to minimize available excess capacity to improve overall facility performance. Excess capacity can be allocated to the production of another product/process design, which can be also independently optimized. However, exploring possible synergies between the two products/processes may bring higher benefits. This paper presents a case where a manufacturing process (plastic blow moulding) was shared among two different products for two different customers, each with a different set of needs. These customer needs were mapped into core value-creating processes, recognizing both the differences in their requirements as well as the similarities in their expectations. Conflicting differences in complexity, production volumes and quality requirements were reconciled using QFD_based approach, and led to improved customer satisfaction and cost performance.
Do growth monitoring and promotion programs answer the performance criteria of a screening program? A critical analysis based on a systematic review

Objective Growth Monitoring and Promotion programs (GMP) have been intensively promoted to improve children's health in developing countries. It has been hoped that regularly weighing children would result in the early detection of growth falterers, and that the growth chart would serve as an educational tool to make that state apparent to both health workers and caretakers in order to trigger improved caring practices. Our objective was to review whether GMP answers the theoretical grounds of a screening and intervention program.
Effects of Tick Population Dynamics and Host Densities on the Persistence of Tick-borne Infections Article in Press

The transmission and the persistence of tick-borne infections are strongly influenced by the densities and the structure of host populations. By extending previous models and analysis, in this paper we analyse how the persistence of ticks and pathogens, is affected by the dynamics of tick populations, and by their host densities. The effect of host densities on infection persistence is explored through the analysis and simulation of a series of models that include different assumptions on tick–host dynamics and consider different routes of infection transmission. Ticks are assumed to feed on two types of host species which vary in their reservoir competence. Too low densities of competent hosts (i.e., hosts where transmission can occur) do not sustain the infection cycle, while too high densities of incompetent hosts may dilute the competent hosts so much to make infection persistence impossible. A dilution effect may occur also for competent hosts as a consequence of reduced tick to host ratio; this is possible only if the regulation of tick populations is such that tick density does not increase linearly with host densities.
Particle size distribution of exosomes and microvesicles determined by transmission electron microscopy, flow cytometry, nanoparticle tracking analysis, and resistive pulse sensing

Enumeration of extracellular vesicles has clinical potential as a biomarker for disease. In biological samples, the smallest and largest vesicles typically differ 25‐fold in size, 300 000‐fold in concentration, 20 000‐fold in volume, and 10 000 000‐fold in scattered light. Because of this heterogeneity, the currently employed techniques detect concentrations ranging from 104 to 1012 vesicles mL–1.
Triplet Spike Time Dependent Plasticity: A floating-gate Implementation

Synapse plays an important role of learning in a neural network; the learning rules which modify the synaptic strength based on the timing difference between the pre- and post-synaptic spike occurrence is termed as Spike Time Dependent Plasticity (STDP). The most commonly used rule posits weight change based on time difference between one pre- and one post spike and is hence termed doublet STDP (DSTDP). However, D-STDP could not reproduce results of many biological experiments; a triplet STDP (T-STDP) that considers triplets of spikes as the fundamental unit has been proposed recently to explain these observations. This paper describes the compact implementation of a synapse using single floating-gate (FG) transistor that can store a weight in a nonvolatile manner and demonstrate the triplet STDP (T-STDP) learning rule by modifying drain voltages according to triplets of spikes. We describe a mathematical procedure to obtain control voltages for the FG device for T-STDP and also show measurement results from a FG synapse fabricated in TSMC 0.35um CMOS process to support the theory. Possible VLSI implementation of drain voltage waveform generator circuits are also presented with simulation results.
Regional Differences in South American Monsoon Precipitation Inferred from the Growth and Isotopic Composition of Tropical Trees

Abstract The authors present results on the relationship between tree-ring proxies and regional precipitation for several sites in tropical South America. The responsiveness of oxygen isotopes (δ18O) and seasonal growth as precipitation proxies was first validated by high-resolution sampling of a Tachigali myrmecophila from Manaus, Brazil (3.1°S, 60.0°W). Monthly growth of Tachigali spp. was significantly correlated with monthly precipitation. Intra-annual measurements of cellulose δ18O in Tachigali spp. were also significantly correlated with monthly precipitation at a lag of approximately one month. The annual ring widths of two tropical tree taxa, Cedrela odorata growing in the Amazon (12.6°S, 69.2°W) and Polylepis tarapacana growing in the Altiplano (22.0°S, 66.0°W), were validated using bomb-derived radiocarbon 14C. Estimated dates were within two to three years of bomb-inferred 14C dates, indicating that these species exhibit annual rings but uncertainties in our chronologies remain. A multiproxy re.
Performance Analysis of FSO Communication Systems with Higher-Order Spatial Diversity Schemes Using BPSK-SIM over Log-Normal Atmospheric Turbulence Channels

—Free Space Optical (FSO) communication system is an optical wireless connectivity operating at an unlicensed optical spectrum, with lots of advantages over the conventional Radio Frequency (RF) transmission. However, the performance of the FSO channel is limited due to atmospheric turbulence and severe weather conditions. There are many authors who have worked on mitigating these effects by using Spatial Diversity (SD) with 2X2-MIMO systems and few have worked up to 4X4-MIMO systems, blended with BPSK-Sub-carrier Intensity Modulation (BPSK-SIM) under the log-normal atmospheric turbulence model. However, in this paper, we extended the SD technique to higher-order configurations such as 8X8-MIMO system in order to improve the performance obtained from lower-order FSO systems. This study was considered at log-irradiance variance values of 0.1 and 0.9, representing the mildly weak and moderately weak atmospheric turbulence regimes respectively. This work has presented the performance analysis of various FSO-SD techniques. As a result, at BER of 10 -9 the 1X8, 4X4, 6X6 and 8X8 higher-order SD systems were ≈ 46%, 55%, 61% and 69% respectively better than the "non-diversity" FSO system during the moderately weak atmospheric condition. Also, their channel capacities were ≈ 74%, 77%, 85% and 89% respectively better than the "non-diversity" FSO system at SNR of 30 dB. 
Experiments in acoustic source localization using sparse arrays in adverse indoors environments

In this paper we experiment with 2-D source localization in smart homes under adverse conditions using sparse distributed microphone arrays. We propose some improvements to deal with problems due to high reverberation, noise and use of a limited number of microphones. These consist of a pre-filtering stage for dereverberation and an iterative procedure that aims to increase accuracy. Experiments carried out in relatively large databases with both simulated and real recordings of sources in various positions indicate that the proposed method exhibits a better performance compared to others under challenging conditions while also being computationally efficient. It is demonstrated that although reverberation degrades localization performance, this degradation can be compensated by identifying the reliable microphone pairs and disposing of the outliers.
Which Algorithm Performs Best: Algorithm Selection for Community Detection

A myriad of community detection methods have been designed to discover communities based on specific network features in different disciplines, such as sociology, physics, and computer science. Consequentially, we have to face the problem of Algorithm Selection for Community Detection (ASCD): Given a specific network, which algorithm should we select to reveal its latent community structures In this study, we propose a model called CYDES to address the ASCD problem. CYDES consists of two parts, namely feature matrix generation and algorithm classification. We combine three effective feature extraction methods with the idea of BOW model to construct a fixed-size feature matrix. After a nonlinear transformation to the feature matrix, a softmax regression model is utilized to generate a classification label representing the best community detection algorithm we select. Extensive experimental results demonstrate that CYDES has high algorithm selection quality for community detection in networks.