Miracle-dz/UniFAR-FTUs huggingface dataset:
Biologic Monitoring of Exposure to Environmental Chemicals throughout the Life Stages: Requirements and Issues for Consideration for the National Children’s Study

Biomonitoring of exposure is a useful tool for assessing environmental exposures. The matrices available for analyses include blood, urine, breast milk, adipose tissue, and saliva, among others. The sampling can be staged to represent the particular time period of concern: preconceptionally from both parents, from a pregnant woman during each of the three trimesters, during and immediately after childbirth, from the mother postnatally, and from the child as it develops to 21 years of age. The appropriate sample for biomonitoring will depend upon matrix availability, the time period of concern for a particular exposure or health effect, and the different classes of environmental chemicals to be monitored. This article describes the matrices available for biomonitoring during the life stages being evaluated in the National Children’s Study; the best biologic matrices for exposure assessment for each individual chemical class, including consideration of alternative matrices; the analytical methods used for analysis, including quality control procedures and less costly alternatives; the costs of analysis; optimal storage conditions; and chemical and matrix stability during long-term storage.
Building Heterogeneous Unified Virtual Memories (UVMs) without the Overhead

This work proposes a novel scheme to facilitate heterogeneous systems with unified virtual memory. Research proposals implement coherence protocols for sequential consistency (SC) between central processing unit (CPU) cores and between devices. Such mechanisms introduce severe bottlenecks in the system; therefore, we adopt the heterogeneous-race-free (HRF) memory model. The use of HRF simplifies the coherency protocol and the graphics processing unit (GPU) memory management unit (MMU). Our protocol optimizes CPU and GPU demands separately, with the GPU part being simpler while the CPU is more elaborate and latency aware. We achieve an average 45% speedup and 45% energy-delay product reduction (20% energy) over the corresponding SC implementation.
Three Ia species with different structures and alloantigenic determinants in an HLA-homozygous cell line

Three distinct molecular subsets with different structures and alloantigenic determinants were identified in human Ia antigens from cells of an HLA-Dw7 homozygous cell line. The subsets carried DR7 specificity, BR4X7 supertypic specificity and MB2 supertypic specificity, respectively, and were immunospecifically separated by the use of operationally monospecific alloantisera. These specificities showed HLA-linked segregation in families and they were distributed in the population according to different but partially overlapping patterns. On peptide mapping analysis, the three subsets showed marked differences in the beta-chains. The alpha-chains of DR7 and BR4X7 subsets were very similar to each other, whereas the alpha-chains of MB2 subset were distinctive from those of DR7 and BR4X7. These data indicate the presence of a minimum of three HLA-linked loci; DR locus, a locus that encodes BR4X7, and a locus that encodes MB2, and substantiate the three-loci concept for the genetic control of human I antigens.
Faculty Statement

Traditional mobile robot research focuses on a robot navigating its environment to reach a single goal while avoiding obstacles. This paper proposes a new method called O to solve the challenges presented at the Intelligent Ground Vehicle Competition (IGVC) where a navigation course includes multiple goals to be found in an optimal order. The O technique includes improvements on traditional path planning and obstacle avoidance techniques while providing an explicit ability to change course as obstacles are discovered. This method uses modern trajectories such as minimum-weighted Hamiltonian circuits, A* algorithm for obstacle avoidance, and local points of opportunity to update the globally optimal path using Voronoi polygons. Environmental mapping is also used to speed up the search algorithms in static environments. Overall, the O technique exploits local points of opportunity while avoiding obstacles and ultimately finding a globally optimal path through an unknown environment. This methodology will be implemented on an autonomous web-based tour guide robot to serve the Internet community reviewing Elizabethtown College. This methodology can be extended to other research areas where multiple locations need to be traversed independent of their order such as city map, trip planners, and distribution networks (power, internet, etc) due to its balance between weighted graphs and obstacle avoidance (objects, traffic, construction, etc).
Classification of Graph Structures

Classification is a classical and fundamental data mining (machine learning) task in which individual items (objects) are divided into groups (classes) based on their features (attributes). Classification problems have been deeply researched as they have a large variety of applications. They appear in different fields of science and industry and may be solved using different algorithms and techniques: e.g. neural networks, rough sets, fuzzy sets, decision trees, etc. These methods operate on various data representations. The most popular one is information system/decision table (e.g. Dominik, & Walczak, 2006) denoted by a table where rows represent objects, columns represent attributes and every cell holds a value of the given attribute for a particular object. Sometimes it is either very difficult and/or impractical to model a real life object (e.g. road map) or phenomenon (e.g. protein interactions) by a row in decision table (vector of features). In such a cases more complex data representations are required e.g. graphs, networks. A graph is basically a set of nodes (vertices) connected by either directed or undirected edges (links). Graphs are used to model and solve a wide variety of problems including classification. Recently a huge interest in the area of graph mining can be observed (e.g. Cook, & Holder, 2006). This field of science concentrates on investigating and discovering relevant information from data represented by graphs. In this chapter, we present basic concepts, problems and methods connected with graph structures classification. We evaluate performance of the most popular and effective classifiers on two kinds of classification problems from different fields of science: computational chemistry, chemical informatics (chemical compounds classification) and information science (web documents classification). BACKGROUND
Cardiac ATP-sensitive K+ channels. Evidence for preferential regulation by glycolysis

The ability of glycolysis, oxidative phosphorylation, the creatine kinase system, and exogenous ATP to suppress ATP-sensitive K+ channels and prevent cell shortening were compared in patch-clamped single guinea pig ventricular myocytes. In cell-attached patches on myocytes permeabilized at one end with saponin, ATP-sensitive K+ channels were activated by removing ATP from the bath, and could be closed equally well by exogenous ATP or substrates for endogenous ATP production by glycolysis (with the mitochondrial inhibitor FCCP present), mitochondrial oxidative phosphorylation, or the creatine kinase system. In the presence of an exogenous ATP-consuming system, however, glycolytic substrates (with FCCP present) were superior to substrates for either oxidative phosphorylation or the creatine kinase system at suppressing ATP-sensitive K+ channels. All three groups of substrates were equally effective at preventing cell shortening. In 6 of 38 excised inside-out membrane patches, ATP-sensitive K+ channels activated by removing ATP from the bath were suppressed by a complete set of substrates for the ATP-producing steps of glycolysis but not by individual glycolytic substrates, which is consistent with the presence of key glycolytic enzymes located near the channels in these patches. Under whole-cell voltage-clamp conditions, inclusion of 15 mM ATP in the patch electrode solution dialyzing the interior of the cell did not prevent activation of the ATP-sensitive K+ current under control conditions or during exposure to complete metabolic inhibition. In isolated arterially perfused rabbit interventricular septa, selective inhibition of glycolysis caused an immediate increase in 42K+ efflux rate, which was prevented by 100 microM glyburide, a known blocker of ATP-sensitive K+ channels. These observations suggest that key glycolytic enzymes are associated with cardiac. ATP-sensitive K+ channels and under conditions in which intracellular competition for ATP is high (e.g., in beating heart) that act as a preferential source of ATP for these channels.
Thresholding RULES and iterative shrinkage/thresholding algorithm: A convergence study

Imaging inverse problems can be formulated as an optimization problem and solved thanks to algorithms such as forward-backward or ISTA (Iterative Shrinkage/Thresholding Algorithm) for which non smooth functionals with sparsity constraints can be minimized efficiently. However, the soft thresholding operator involved in this algorithm leads to a biased estimation of large coefficients. That is why a step allowing to reduce this bias is introduced in practice. Indeed, in the statistical community, a large variety of thresholding operators have been studied to avoid the biased estimation of large coefficients; for instance, the non negative Garrote or the the SCAD thresholding. One can associate a non convex penalty to these operators. We study the convergence properties of ISTA, possibly relaxed, with any thresholding rule and show that they correspond to a semi-convex penalty. The effectiveness of this approach is illustrated on image inverse problems.
Secured data communication system using RSA with mersenne primes and Steganography

To add multiple layers of security our present work proposes a method for integrating together cryptography and Steganography for secure communication using an image file. We have used here combination of cryptography and steganography that can hide a text in an image in such a way so as to prevent any possible suspicion of having a hidden text, after RSA cipher. It offers privacy and high security through the communication channel.
Context-Sensitive Spelling Error Correction Using Inter-Word Semantic Relation Analysis

Error words that appear in Korean texts can be largely categorized into non-word spelling errors and context-sensitive spelling errors. Of the two, context-sensitive spelling errors are shown only when considering the meaning of the word in the given context and its syntactic relation, and they are the most difficult to correct among spelling errors. Context-sensitive spelling errors can be categorized into homophone errors, typographical errors, grammatical errors, and cross-word boundary errors. To correct context-sensitive spelling errors that occur due to typographical errors, this study proposes a statistical context-sensitive spelling check using inter-word semantic relation analysis. With confusion sets created in advance, we can find and correct context-sensitive spelling errors using reliability based on the conditional probability and chi-square statistics between each word of the confusion sets and the context as well as the typing error rate. As a result of applying the proposed method, all 5 confusion sets showed higher precision (92.68%) and recall (83.95%) than the baseline (precision 80%, recall 80%).
Road crash proneness prediction using data mining

Developing safe and sustainable road systems is a common goal in all countries. Applications to assist with road asset management and crash minimization are sought universally. This paper presents a data mining methodology using decision trees for modeling the crash proneness of road segments using available road and crash attributes. The models quantify the concept of crash proneness and demonstrate that road segments with only a few crashes have more in common with non-crash roads than roads with higher crash counts. This paper also examines ways of dealing with highly unbalanced data sets encountered in the study.
Authenticating operation-based history in collaborative systems

Within last years multi-synchronous collaborative editing systems became widely used. Multi-synchronous collaboration maintains multiple, simultaneous streams of activity which continually diverge and synchronized. These streams of activity are represented by means of logs of operations, i.e. user modifications. A malicious user might tamper his log of operations. At the moment of synchronization with other streams, the tampered log might generate wrong results. In this paper, we propose a solution relying on hash-chain based authenticators for authenticating logs that ensure the authenticity, the integrity of logs, and the user accountability. We present algorithms to construct authenticators and verify logs. We prove their correctness and provide theoretical and practical evaluations.
Finite-time Regret Bound of a Bandit Algorithm for the Semi-bounded Support Model

In this paper we consider stochastic multiarmed bandit problems. Recently a policy, DMED, is proposed and proved to achieve the asymptotic bound for the model that each reward distribution is supported in a known bounded interval, e.g. [0,1]. However, the derived regret bound is described in an asymptotic form and the performance in finite time has been unknown. We inspect this policy and derive a finite-time regret bound by refining large deviation probabilities to a simple finite form. Further, this observation reveals that the assumption on the lower-boundedness of the support is not essential and can be replaced with a weaker one, the existence of the moment generating function.
Seismic parameters of hcp‐Fe alloyed with Ni and Si in the Earth's inner core

Iron alloyed with Ni and Si has been suggested to be a major component of the Earth's inner core. High‐pressure results on the combined alloying effects of Ni and Si on seismic parameters of iron are thus essential for establishing satisfactory geophysical and geochemical models of the region. Here we have investigated the compressional (VP) and shear (Vs) wave velocity‐density (ρ) relations, Poisson's ratio (ν), and seismic heterogeneity ratios (dlnρ/dlnVP, dlnρ/dlnVS, and dlnVP/dlnVS) of hcp‐Fe and hcp‐Fe86.8Ni8. 6Si4.6 alloy up to 206 GPa and 136 GPa, respectively, using multiple complementary techniques. Compared with the literature velocity values for hcp‐Fe and Fe‐Ni‐Si alloys, our results show that the combined addition of 9.0 wt % Ni and 2.3 wt % Si slightly increases the VP but significantly decreases the VS of hcp‐Fe at a given density relevant to the inner core. Such distinct alloying effects on velocities of hcp‐Fe produce a high ν of about 0.40 for the alloy at inner core densities, which is approximately 20% higher than that for hcp‐Fe. Analysis of the literature high P‐T results on VP and VS of Fe alloyed with light elements shows that high temperature can further enhance the ν of hcp‐Fe alloyed with Ni and Si. Most significantly, the derived seismic heterogeneity ratios of this hcp alloy present a better match with global seismic observations. Our results provide a multifactored geophysical constraint on the compositional model of the inner core which is consistent with silicon being a major light element alloyed with Fe and 5 wt % Ni.
Intragraft Th17 Infiltrate Promotes Lymphoid Neogenesis and Hastens Clinical Chronic Rejection

To evaluate the influence of intragraft inflammatory infiltrate on the course of chronic rejection, 11 human renal grafts, detransplanted for terminal failure, were analyzed. Samples were divided into two groups according to their graft survival (> or ≤8 y). In both groups, the main cell population infiltrating the graft interstitia was T lymphocytes. The extent of the lymphocytic infiltration and the distribution of naive and memory, CD4+ and CD8+ T cells, were similar in both groups. Although all types of Th polarization profiles can lead to terminal chronic rejection, a correlation between shorter graft survival and the presence of Th17 cells that produce IL-17 and IL-21 was observed. In contrast, grafts infiltrated by regulatory T cells survived significantly longer. The correlation between the expressions of activation-induced cytidine deaminase (the key enzyme of the germinal center reaction) and IL-21 suggests that Th17 could exert their deleterious effect by promoting lymphoid neogenesis, namely, the organization of inflammatory effectors into ectopic germinal centers in which a local humoral immune response is elicited. Further studies will determine whether Th17 infiltration can be used as a prognosis tool and whether theTh17 subset constitutes a therapeutic target for slowing down chronic rejection.
Development of a lesion-mimic phenotype in a transgenic wheat line overexpressing genes for pathogenesis-related (PR) proteins is dependent on salicylic acid concentration.

In the course of coexpressing genes for pathogenesis-related (PR) proteins for a class IV chitinase and an acidic glucanase in transgenic wheat plants, we regenerated a wheat line that developed necrotic lesions containing dead cells in the T2 and subsequent generations. Lesion spots were detected at the booting stage (5- to 6-week-old plants) in lines homozygous for the transgene loci. In contrast, lesions were not observed in hemizygous transgenic lines or lines silenced for transgene expression, indicating a requirement for high levels of transgene expression for the development of the lesioned phenotype. Lesion development was associated with the accumulation of host-encoded PR proteins, e.g., chitinases, beta-1,3-glucanases, thaumatin-like protein, and production of reactive oxygen intermediates. F1 progeny of a cross between the lesion-plus transgenic line and wild-type nontransgenic plants produced progeny with a normal phenotype, while the F2 progenies segregated for the lesion phenotype. Salicylic acid (SA) levels in plants with the lesion-plus phenotype were found to be several times higher than controls and nearly double the levels in hemizygous transgenic plants that lack lesions. SA application activated lesion development in excised leaf pieces of these hemizygous transgenic plants. Similar activation of lesion development in control plants occurred only when high concentrations of SA were applied for prolonged periods. Transcripts for phenylalanine-ammonia lyase, which provides precursors of SA, were elevated in homozygous transgenic plants. Our data suggest that transgene-induced lesion-mimic phenotype correlates with enhanced SA biosynthesis.
Analysis Of Interference Reduction In Mc-Cdma System Using Binary Spreading Sequences

In this paper, we explore the effects of various spreading codes chiefly GMW, WG and 3- term sequences on interference levels in the multicarrier code-division multiple access (MC-CDMA) system. We evaluate the performances of these codes in terms of interference cancellation in differentsubcarrier systems. In the system, the data from the user is spreaded using a special sequence (code). The spreaded data is transmitted using the orthogonal frequency division multiplexing (OFDM) notioni.e. , the data is transmitted simultaneously via numerous subcarriers. The orthogonality among the subcarriers further reduces the interference level. Simulation results show that 3-term sequence performs better than other spreading sequences. Based on the simulations, we propose that 3-term sequence can be used as the spreading code in higher order subcarrier systems for mitigating interference and achieving a better bit error rate (BER) performance.
IDENTIFYING COMMUNITIES IN SOCIAL NETWORKS : A SURVEY

Many networks of interest now include a variety of social and technological networks, which are naturally divided into communities or modules. How to identify these community structures has considerably attracted the attention of researchers, and it is the aim of this paper. A review of the main algorithms used for finding communities is presented, starting with graph theory and including the latest algorithms for detecting Web communities. The existence of communities that can overlap is also taken into account, and the main commonly used software tools for depicting communities are pointed out.
Clustering Evolutionary Computation for Solving Travelling Salesman Problems

This paper proposes the methods for solving the traveling salesman problems using clustering techniques and evolutionary methods. Gaussian mixer model and K-means clustering are two clustering techniques that are considered in this paper. The traveling salesman problems are clustered in order to group the nearest nodes in the problems. Then, the evolutionary methods are applied to each cluster. The results of genetic algorithm and ant colony optimization are compared. In the last steps, a cluster connection method is proposed to find the optimal path between any two clusters. These methods are implemented and tested on the benchmark datasets. The results are compared in terms of the average minimum tour length and the average computational time. These results show that the clustering techniques are able to improve the efficiency of evolutionary methods on traveling salesman problems. Moreover, the proposed methods can be applied to other problems.
Implicit news recommendation based on user interest models and multimodal content analysis

This paper presents an implicit news recommender system based on the user's interests and multimodal content analysis. Multimodality is here intended as the capability of integrating multiple modes, e.g. radio-television channels and Web sites, and different media, e.g. written text and spoken content. Personal interests are inferred by natural language processing of the users' blogs. Latent semantic analysis is used to find the relationships between such interests and both online newspaper articles and broadcast news stories. The novelty of this system is the ability to treat equally and simultaneously online press reports and TV news streams. Experiments in a long-term real-world usage scenario demonstrate the quality of the proposed recommendations.
The Nature of Computation and The Development of Computational Models

We need much better understanding of information processing and its primary form computation than we have now. As there is no information without (physical) representation, the dynamics of information is implemented on different levels of granularity by different physical processes, including the levels of computation performed by computing machines and living organisms. There are a lot of open problems related to the nature of information and essence of computation, as well as to their relationships. How is information dynamics represented in computational systems, in machines, as well as in living organisms? Are computers processing only data or information and knowledge as well? What do we know of computational processes in machines and living organisms and how these processes are related? What can we learn from natural computational processes that can be useful for information systems and knowledge management?
Adaptive Agent-based Systems for the Web : An Application to the NECTAR Project

The paper presents an overall framework for devising adaptive Web systems characterised by a smart interface that exploits personalised anthropoid characters. Part of the framework is currently investigated for the NECTAR system, a smart interface for on-line shopping. We propose an agent architecture and highlight the roles of different agents that can carry out tasks required for a smart interface. We define knowledge structures and reasoning abilities that can be considered by such adaptive systems. In particular, we point out how adaptive Web applications could benefit from using case-based reasoning, data mining, and knowledge discovery techniques.