Miracle-dz/UniFAR-FTUs huggingface dataset:
Practical frame synchronization for data with unknown distribution on AWGN channels

We study practical frame synchronization based on sequential search of sync markers: these synchronizers can be used for frames of both known or unknown lengths. First, according to the hypothesis testing theory, a new simple metric is derived for the additive white Gaussian noise (AWGN) channel, based on the generalized likelihood ratio test, thus without any assumption on the statistical distribution of the data symbols. An analytical performance evaluation is then given, with closed form expression for the characteristic function of the decision variable. It is shown that a remarkable gain is obtained with respect to correlation based tests.
Anti‐insulin antibody structure and conformation. II. Molecular dynamics with explicit solvent

Molecular dynamics at 300 K was used as a conformation searching tool to analyze a knowledge‐based structure prediction of an anti‐insulin antibody. Solvation effects were modeled by packing water molecules around the antigen binding loops. Some loops underwent backbone and side‐chain conformational changes during the 95‐ps equilibration, and most of these new, lower potential energy conformations were stable during the subsequent 200‐ps simulation. Alterations to the model include changes in the intraloop, main‐chain hydrogen bonding network of loop H3, and adjustments of Tyr and Lys side chains of H3 induced by hydrogen bonding to water molecules. The structures observed during molecular dynamics support the conclusion of the previous paper that hydrogen bonding will play the dominant role in antibody‐insulin recognition. Determination of the structure of the antibody by x‐ray crystallography is currently being pursued to provide an experimental test of these results. The simulation appears to improve the model, but longer simulations at higher temperatures should be performed.
Joint genomic and metabolomic analysis of toxic dose-response experiments

A methodology has been implemented for analyzing microarray and NMR spectral data obtained from the same set of toxic-exposure dose-response experiments. The NMR spectra additionally track the time course of exposure. Analyses consist of screening the data to eliminate variates with insignificant signal, normalization appropriate to the experimental design, principal components analysis, and nonlinear classification using a support vector machine. It is found that exposure at subtoxic levels can be detected.
Screening for cutaneous melanoma by skin self-examination.

BACKGROUND Although some evidence indicates that early detection protects against the development of lethal melanoma, no randomized clinical trials have been conducted to measure the efficacy of early detection (or screening) in preventing death from this disease. Since melanoma incidence in the United States is relatively rare, a randomized clinical trial to test the efficacy of screening would be extremely expensive. PURPOSE As an alternative to a randomized clinical trial, we conducted a population-based, case-control study to investigate whether early detection through skin self-examination (SSE) is associated with a decreased risk of lethal melanoma (includes the presence of advanced disease with distant metastases in addition to death from melanoma). METHODS SSE (conducting a careful, deliberate, and purposeful examination of the skin) was assessed in all subjects by use of a structured questionnaire and personal interviews. The major exposure variable, SSE, was defined following focus-group interviews with melanoma patients and healthy control subjects. The final study population consisted of 1199 Caucasian residents of the state of Connecticut enrolled from January 15, 1987, through May 15, 1989; 650 individuals were newly diagnosed with cutaneous melanoma, and the remaining 549 individuals were age- and sex-frequency matched control subjects from the general population. During the study interviews, nevi on the arms and backs of subjects were counted. In 5 years of follow-up (through March 1994), 110 lethal cases of melanoma were identified. The study design allowed separate estimation of the impact of SSE on reduced melanoma incidence (primary prevention) and survival among incident cases (secondary prevention). Odds ratios (ORs) were used to measure the associations between SSE and melanoma and between SSE and lethal melanoma. RESULTS SSE, practiced by only 15% of all subjects, was associated with a reduced risk of melanoma incidence (adjusted OR = 0.66; 95% confidence interval [CI] = 0.44-0.99; comparing case patients with control subjects). The data indicated further that SSE may reduce the risk of advanced disease among melanoma patients (unadjusted risk ratio = 0.58; 95% CI = 0.31-1.11); however, longer follow-up is required to confirm this latter estimate. If both estimates are correct, they suggest, in combination, that SSE may reduce mortality from melanoma by 63% (adjusted OR = 0.37; 95% CI = 0.16-0.84; comparing lethal cases with general population controls). CONCLUSIONS AND IMPLICATIONS SSE may provide a useful and inexpensive screening method to reduce the incidence of melanoma. SSE may also reduce the development of advanced disease. The results of this study need to be replicated before strategies to increase the practice of SSE are further developed and promoted.
Quantifying Exocytosis by Combination of Membrane Capacitance Measurements and Total Internal Reflection Fluorescence Microscopy in Chromaffin Cells

Total internal reflection fluorescence microscopy (TIRF-Microscopy) allows the observation of individual secretory vesicles in realtime during exocytosis. In contrast to electrophysiological methods, such as membrane capacitance recording or carbon fiber amperometry, TIRF-Microscopy also enables the observation of vesicles as they reside close to the plasma membrane prior to fusion. However, TIRF-Microscopy is limited to the visualization of vesicles that are located near the membrane attached to the glass coverslip on which the cell grows. This has raised concerns as to whether exocytosis measured with TIRF-Microscopy is comparable to global secretion of the cell measured with membrane capacitance recording. Here we address this concern by combining TIRF-Microscopy and membrane capacitance recording to quantify exocytosis from adrenal chromaffin cells. We found that secretion measured with TIRF-Microscopy is representative of the overall secretion of the cells, thereby validating for the first time the TIRF method as a measure of secretion. Furthermore, the combination of these two techniques provides a new tool for investigating the molecular mechanism of synaptic transmission with combined electrophysiological and imaging techniques.
What contributes to individual differences in brain structure?

Individual differences in adult human brain structure have been found to reveal a great deal of information about variability in behaviors, cognitive abilities and mental and physical health. Driven by such evidence, what contributes to individual variation in brain structure has gained accelerated attention as a research question. Findings thus far appear to support the notion that an individual’s brain architecture is determined largely by genetic and environmental influences. This review aims to evaluate the empirical literature on whether and how genes and the environment contribute to individual differences in brain structure. It first considers how genetic and environmental effects may separately contribute to brain morphology, by examining evidence from twin, genome-wide association, cross-sectional and longitudinal studies. Next, evidence for the influence of the complex interplay between genetic and environmental factors, characterized as gene-environment interactions and correlations, is reviewed. In evaluating the extant literature, this review will conclude that both genetic and environmental factors play critical roles in contributing to individual variability in brain structure.
Clustering and Correlation based Collaborative Filtering Algorithm for Cloud Platform

With the development of the Internet, recommender systems have played a more and more important role in the field of big data processing, such as e-business. In order to deal with big data in recommender systems, we propose a clustering and correlation based collaborative filtering algorithm for cloud platform, which improves the traditional user-based collaborative filtering algorithm with k-medoids clustering and a data structure named correlation multi-tree in this paper. Firstly, we analyze the user-based collaborative filtering for cloud platform. On the basic of it, we propose a k-medoids based collaborative filtering algorithm for cloud platform by using the k-medoids clustering. It can solve the problem of data sparsity effectively. As a result, it can be more efficient with the recall rate and recommendation ratings improved at the same time. Considering the falling of recommendation accuracy by using clustering technology, this paper introduces a data structure named correlation multi-tree to correlate the user information and their neighbors information. It can be used to compute the extended user-item score, which makes full use of the correlation between data on cloud platform. As a result, the clustering and correlation based collaborative filtering algorithm for cloud platform proposed by us can improve the recommendation accuracy effectively, and ensure the effect of recommendation and the time efficiency at the same time. An extensive experimental evolution with Ali data sets on Hadoop cloud platform shows that our collaborative filtering algorithm has a better recommendation and is more efficient in handling big data.
High-performance liquid chromatography LTQ-Orbitrap mass spectrometry method for tomatidine and non-target metabolites quantification in organic and normal tomatoes

Abstract Tomatoes, members of the Solanaceae plant family, produce biologically active secondary metabolites, including glycoalkaloids and aglycons, which may have both adverse and beneficial biological effects. A new liquid chromatography method that utilized LTQ-Orbitrap MS was developed for the analysis of tomatidine, the main aglycon in tomatoes. Recoveries of tomatidine were >98.3% with the relative standard deviations (RSDs) below 6.1%. The limit of detection (LODs) was 0.0003 mg kg−1. The limit of quantitation (LOQs) is 0.001 mg kg−1. The linear range was between with 0.0025 and 1 mg kg−1 with an excellent correlation coefficient (R2) equal to 0.9990. Various tomato samples were analyzed and the level of tomatidine in the 11 samples analysed was higher in normal respect to organic tomatoes. The capability of the set-up Full Scan LTQ-Orbitrap MS method allowed us to quantified two non-target analytes. The m/z 1032 was identified as dehydrotomatine, confirmed through accurate mass studies (mass error in ppm equal to 1.5017) meanwhile m/z 902 as (Glc)2–Gal-Tomatidine (β1-Tomatine) (mass error in ppm equal to 2.0719).
Robustness Analysis and Optimally Robust Control Design via Sum-of-Squares

A control analysis and design framework is proposed for systems subject to parametric uncertainty. The underlying strategies are based on sum-of-squares (SOS) polynomial analysis and nonlinear optimization to design an optimally robust controller. The approach determines a maximum uncertainty range for which the closed-loop system satisfies a set of stability and performance requirements. These requirements, de ned as inequality constraints on several metrics, are restricted to polynomial functions of the uncertainty. To quantify robustness, SOS analysis is used to prove that the closed-loop system complies with the requirements for a given uncertainty range. The maximum uncertainty range, calculated by assessing a sequence of increasingly larger ranges, serves as a robustness metric for the closed-loop system. To optimize the control design, nonlinear optimization is used to enlarge the maximum uncertainty range by tuning the controller gains. Hence, the resulting controller is optimally robust to parametric uncertainty. This approach balances the robustness margins corresponding to each requirement in order to maximize the aggregate system robustness. The proposed framework is applied to a simple linear short-period aircraft model with uncertain aerodynamic coefficients.
A low-power FPGA based on self-adaptive multi-voltage control

This paper presents a low-power FPGA that the supply voltage of each logic block autonomously changes to suit their deadlines. Dual-rail coding is used in FPGA datapaths to make data transfer time sensible in each pipeline stage. The deadline of the logic block in each pipeline stage is evaluated by comparing the data transfer time and the pipeline cycle time. When a low supply voltage does not violate the deadline, the supply voltage of the logic block is autonomously switched to the low voltage. This self-adaptive voltage control scheme saves power consumption without deteriorating the circuit performance. Moreover, level converters are unnecessary in the proposed FPGA which has a simple and efficient architecture.
Dispersion of single-walled carbon nanotubes of narrow diameter distribution.

The dispersibility and bundle defoliation of single-walled carbon nanotubes (SWNTs) of small diameter (<1 nm) have been evaluated on CoMoCAT samples with narrow distribution of diameters. As previously observed by photoluminescence and Raman spectroscopy, the CoMoCAT sample exhibits a uniquely narrow distribution of (n,m) structures that remains unchanged after different dispersion conditions. This narrow distribution allowed us to develop a method for quantifying the dispersability of the samples from their optical absorption spectra in terms of two ratios: the "resonance ratio" and the "normalized width. " The former is defined as the quotient of the resonant band area and its nonresonant background. The latter is defined as the ratio of the width of the band at half-height to the peak height on a spectrum that has been normalized at 900 nm, making this an intensive property, rather than varying with the path length. In this study of the CoMoCAT sample, we have used the S22 transition corresponding to the (6,5) nanotube to do these calculations, which is the most abundant species. These two ratios provide a quantitative tool to compare different dispersion parameters (time of sonication, degree of centrifugation, etc.) on the same type of sample. From this comparison, an optimal procedure that maximizes the spectral features was selected; this procedure allowed us to contrast various surfactants at different pH values and concentrations. Several surfactants were as good or even better than the one we have used in previous studies, dodecylbenesulfonic acid sodium salt (NaDDBS). Despite differences in their dispersion abilities, none of the surfactants investigated generated new features in the absorption spectra nor changed the distribution of nanotube types, which confirms that the high selectivity of the CoMoCAT sample is in the original sample rather than caused by selective suspension of specific (n,m) nanotubes.
Proteoform-Specific Insights into Cellular Proteome Regulation

Knowledge regarding compositions of proteomes at the proteoform level enhances insights into cellular phenotypes. A strategy is described herein for discovery of proteoform-specific information about cellular proteomes. This strategy involved analysis of data obtained by bottom-up mass spectrometry of multiple protein OGE separations on a fraction by fraction basis. The strategy was exemplified using five matched sets of lysates of uninfected and human respiratory syncytial virus-infected A549 cells. Template matching demonstrated that 67.3% of 10475 protein profiles identified focused to narrow pI windows indicative of efficacious focusing. Furthermore, correlation between experimental and theoretical pI gradients indicated reproducible focusing. Based on these observations a proteoform profiling strategy was developed to identify proteoforms, detect proteoform diversity and discover potential proteoform regulation. One component of this strategy involved examination of the focusing profiles for protein groups. A novel concordance analysis facilitated differentiation between proteoforms, including proteoforms generated by alternate splicing and proteolysis. Evaluation of focusing profiles and concordance analysis were applicable to cells from a single and/or multiple biological states. Statistical analyses identified proteoform variation between biological states. Regulation relevant to cellular responses to human respiratory syncytial virus was revealed. Western blotting and Protomap analyses validated the proteoform regulation. Discovery of STAT1, WARS, MX1, and HSPB1 proteoform regulation by human respiratory syncytial virus highlighted the impact of the profiling strategy. Novel truncated proteoforms of MX1 were identified in infected cells and phosphorylation driven regulation of HSPB1 proteoforms was correlated with infection. The proteoform profiling strategy is generally applicable to investigating interactions between viruses and host cells and the analysis of other biological systems.
Phylogenetic Diversity in Core Region of Hepatitis C Virus Genotype 1a as a Factor Associated with Fibrosis Severity in HIV-1-Coinfected Patients

High hepatitis C virus (HCV) genetic diversity impacts infectivity/pathogenicity, influencing chronic liver disease progression associated with fibrosis degrees and hepatocellular carcinoma. HCV core protein is crucial in cell-growth regulation and host-gene expression. Liver fibrosis is accelerated by unknown mechanisms in human immunodeficiency virus-1- (HIV-1-) coinfected individuals. We aimed to study whether well-defined HCV-1a core polymorphisms and genetic heterogeneity are related to fibrosis in a highly homogeneous group of interferon-treated HIV-HCV-coinfected patients. Genetic heterogeneity was weighed by Faith's phylogenetic diversity (PD), which has been little studied in HCV. Eighteen HCV/HIV-coinfected patients presenting different liver fibrosis stages before anti-HCV treatment-initiation were recruited. Sampling at baseline and during and after treatment was performed up to 72 weeks. At inter/intrahost level, HCV-1a populations were studied using molecular cloning and Sanger sequencing. Over 400 complete HCV-1a core sequences encompassing 573 positions of C were obtained. Amino acid substitutions found previously at positions 70 and 91 of HCV-1b core region were not observed. However, HCV genetic heterogeneity was higher in mild than in severe fibrosis cases. These results suggest a potential utility of PD as a virus-related factor associated with chronic hepatitis C progression. These observations should be reassessed in larger cohorts to corroborate our findings and assess other potential covariates.
Context-aware mobile crowdsourcing

Ubiquity of internet-connected media-and sensor-equipped portable devices has emerged a range of opportunities for direct involvement of citizens into public decision making, leading to a new participatory format of public administration functioning. Intersecting the power of the crowdsourcing problem-solving paradigm by directly relying on human intelligence, with instantaneity and situation-awareness of mobile technologies, one gets a context-aware crowdsourcing approach for problem-solving in the right circumstances with the right people. In this paper, we present a prototype implementation of a context-aware mobile crowdsourcing system that enables the deployment and execution of crowdsourcing campaigns with users carrying mobile devices. The system is designed to maximize conditions for user participation, while minimizing the usage of energy. The paper describes the system architecture, defines an optimized sampling algorithm, and outlines a preliminary experimentation study carried out.
BEHAVIOR OF FRP- CONFINED CONCRETE SQUARE COL UMNS UNDER UNIAXIAL LOADING

The behavior of the FRPO confined concrete square columns under uniaxial loading is studied in the paper. The finite ele2 ment method is used in the study ; a computer program is developed. The computing results are compared with test one. The former can simulate the behavior of the columns with proper numerical model . The interaction between FRP material and con2 crete is discussed based on the numerical results. Some useful conclusions are obtained through the study.
An Open Source-Based Approach to Software Development Infrastructures

As software systems become larger and more complex, automated software engineering tools play a crucial role for effective software development management, which is a key factor to lead quality software systems. In this work, we present TRICA, an open source-based software development infrastructure. The name of TRICA represents its features such as Traceability, Relationship, Informativeness, Cost-effectiveness, and Automation. Essentially, in TRICA, a continuous integration tool is coupled with a software configuration management tool and an issue tracking tool. We provisioned a mechanism to connect the open source tools in TRICA so that project members use the collaborated information to solve various issues and implementation problems efficiently, and easily share forthcoming issues during the course of the project. We show that TRICA can help to decentralize risks throughout the software development cycle and achieve successful software development.
Optimal controller design for a class of networked control systems

This paper is concerned with the optimal controller design of networked control systems (NCSs). Aiming at a class of NCSs, in which network-induced delay and data packet dropout exist simultaneously from sensor to controller, this paper proposes a novel optimal controller based on a new adaptive genetic algorithm and simulated anneal algorithm (AGASA), guaranteed cost controller (GCC) and state feedback controller (SFC). The proposed controller is less conservative than GCC and SFC, and can be applied to both linear and nonlinear NCSs. Two examples are presented to illustrate the proposed controller.
Familiarity and Trust: Measuring Familiarity with a Web Site

This work aims at measuring familiarity to contribute to the formalization of trust. Trust has always been bundled with familiarity to become a popular topic in the areas of psychology, sociology and computer science. Correlation between familiarity and trust has been explored and proved by many studies from different perspectives. A new model of trust has been proposed by Carter and Ghorbani to formalize the value-centric trust in agent societies. However, the measurement of familiarity in their work is roughly the similarity of values between two agents. Familiarity measurements proposed by other researchers are not convenient due to the instability and abstruseness of familiarity, or are useful only in certain circumstances and are quite problem-specific. We propose a convenient way of measuring familiarity with a Web site and continuously updating its value based on the exploration of factors that may affect familiarity. The five major factors include prior experience, repeated exposure, study duration, level of processing and forgetting rate. The human factors are mapped to the properties of Web application domain through a factors hierarchy. Experiments to evaluate the performance of the proposed measurement are discussed in the future work section.