Miracle-dz/UniFAR-FTUs huggingface dataset:
Minimum weight routing based on a common link control radio for cognitive wireless ad hoc networks

Cognitive wireless ad hoc is highly focused as a promising future wireless technology. However, cognitive wireless ad hoc networks have some difficulties of neighbor discovery and routing. For helping neighbor discovery and routing in the cognitive wireless ad hoc networks, we introduce a common link control radio (CLCR) that is a common active wireless system of cognitive terminals. In addition, we propose a novel cognitive ad hoc routing protocol based on a common link control radio (CLCR) called a minimum weight routing protocol. We show that the proposed routing protocol can greatly reduce communication overhead in cognitive wireless ad hoc networks.
Kindergarten children's genetic vulnerabilities interact with friends' aggression to promote children's own aggression.

OBJECTIVE To examine whether kindergarten children's genetic liability to physically aggress moderates the contribution of friends' aggression to their aggressive behaviors. METHOD Teacher and peer reports of aggression were available for 359 6-year-old twin pairs (145 MZ, 212 DZ) as well as teacher and peer reports of aggression of the two best friends of each twin. Children's genetic risk for aggression was based on their cotwin's aggression status and the pair's zygosity. RESULTS Children's aggression was highly heritable. Unique environment accounted for most of the variance in friends' aggression, although there was also a small genetic contribution (15%). Both genetic liability to aggression and having aggressive friends predicted twins' aggression. However, the contribution of aggressive friends to children's aggression was strongest among genetically vulnerable children. This result was similar for boys and girls, despite sex differences in both aggression and the level of aggression of friends. CONCLUSIONS Affiliation with aggressive friends at school entry is a significant environmental risk factor for aggression, especially for children genetically at risk for aggressive behaviors. Developmental models of aggression need to take into account both genetic liability and environmental factors in multiple settings, such as the peer context, to more precisely describe and understand the various developmental pathways to aggression. The implications for early prevention programs are discussed.
Predictive Models in Medicine: Some Methods for Construction and Adaptation

Health care personnel make predictions routinely every day. They group patients according to disorders, render prognoses of the health status of a given patients at a future point in time, or classify laboratory specimens. With the emergence of integrated hospital information systems, the potential of using computerized predictive models to support tasks like these is significant. This thesis concerns itself with problems of realizing predictive models based on knowledge of associations, e.g., findings – diagnosis associations. The theoretical context of the work contained in this thesis lies in the intersection between artificial intelligence, machine learning in particular, statistics and medicine. Although predictive model results reported in the literature often surpass the results of control groups of relevant health care professionals, few are found in clinical practice. The reasons for this are multiple and touch upon issues concerned with ethics, sociology, psychology and technology. The work presented here aims at lowering this deployment barrier by addressing some technical problems of predictive models. It also offers methodological showcases for the use of genetic algorithms as search heuristics and the use of empirical measures in construction and adaption of predictive models. This is done in the main part of this thesis, a collection of the following five papers. Minimal Approximate Hitting Sets and Rule Templates A genetic algorithm approach to multi-disorder diagnosis A genetic algorithm to select variables in logistic regression: example in the domain of myocardial infarction A recalibration method for predictive models with dichotomous outcomes Effects of Case Removal in Prognostic Models for Medicine
Securing cloud database by Data Fusing Technique (DFT) using Cloud Storage Controller (CSC)

In the field of cloud computing the approach for sharing of data and storage between a group of people requires efficient approach with cost cutting and low maintenance procedure. Sharing of outsourced files assures security and ensures data veracity according to the frequent changes in shared data files. Issues like preserving privacy of data among the group stored data shared in common cloud storage. Prominent attacks within the cloud requires scheme of defense mechanisms use key distribution mechanism in secured communication channels. Some of the existing system use fine grain access control with revoked user that protects prominent attacks for original data achieving security. In our proposed paper we inculcate a Cloud Storage Controller (CSC) that manages the allocation of group of data stored and it can only referenced and cannot download any database from cloud. The data will be blended together into one of two sets for example if two users storing data of 2 megabyte and 3 megabyte each then that will be merged together as two datasets with 1 megabyte of first user and 1 megabyte of second user. In the second data set it merges 1 megabyte of first user and 2 megabyte of second user using Fusing Data Technique (FDT). Every dataset will be bookmarked which symbolizes the user that dataset belongs to and that will be indexed in the Cloud Storage controller (CSC). It helps in fast and highly secured datasets storage management in cloud storage system. It achieves efficient database privacy and revokes user data swiftly and securely.
Enhancing Data Reuse in Cache Contention Aware Thread Scheduling on GPGPU

GPGPUs have been widely adopted as throughput processing platforms for modern big-data and cloud computing. Attaining a high performance design on a GPGPU requires careful tradeoffs among various design concerns. Data reuse, cache contention, and thread level parallelism, have been demonstrated as three imperative performance factors for a GPGPU. The correlated performance impacts of these factors pose non-trivial concerns when scheduling threads on GPGPUs. This paper proposes a three-staged scheduling scheme to coschedule the threads with consideration of the three factors. The experiment results on a set of irregular parallel applications, when compared with previous approaches, have demonstrated up to 70% execution time improvement.
APE1 overexpression in XRCC1-deficient cells complements the defective repair of oxidative single strand breaks but increases genomic instability

XRCC1 protein is essential for mammalian viability and is required for the efficient repair of single strand breaks (SSBs) and damaged bases in DNA. XRCC1-deficient cells are genetically unstable and sensitive to DNA damaging agents. XRCC1 has no known enzymatic activity and is thought to act as a scaffold protein for both SSB and base excision repair activities. To further define the defects leading to genetic instability in XRCC1-deficient cells, we overexpressed the AP endonuclease APE1, shown previously to interact with and be stimulated by XRCC1. Here, we report that the overexpression of APE1 can compensate for the impaired capability of XRCC1-deficient cells to repair SSBs induced by oxidative DNA damage, both in vivo and in whole-cell extracts. We show that, for this kind of damage, the repair of blocked DNA ends is rate limiting and can be performed by APE1. Conversely, APE1 overproduction resulted in a 3-fold increase in the sensitivity of XRCC1-deficient cells to an alkylating agent, most probably due to the accumulation of SSBs. Finally, the overproduction of APE1 results in increases of 40% in the frequency of micronuclei and 33% in sister chromatid exchanges of XRCC1− cells. These data suggest that the spontaneous generation of AP sites could be at the origin of the SSBs responsible for the spontaneous genetic instability characteristic of XRCC1-deficient cells.
Research on sentiment orientation of product reviews in Chinese based on cascaded CRFs models

Computing sentiment strength of product reviews is a challenge in the field of sentiment analysis. The results obtained by standard condition random fields (CRFs) in the previous work were not well, so cascaded CRFs model is used to compute the strength of sentence sentiment in Chinese in this paper. The present approach contains two layers: in the first layer CRFs model is used to judge the polarity of the sentence, negative, positive or objective, then strength of polarity is obtained by CRFs model in the second layer. The proposed framework facilitates mapping the product reviews into five classes-(i.e. strong positive, general positive, objective, general negative and strong negative) by considering the label redundancy among layers. The authors choose context, conjunction, evaluated-word and the results of the polarity classification as the features of cascaded CRFs model. Experiments on the task3 corpus of COAE2008 show the remarkable performance of the proposed approach. Results of the first layer are added to the features in the second layers which can have the advantage to compute the sentiment strength of sentences.
GTT : A General Transducer for Teaching Computational Linguistics

The GTT-system is a tree-to-tree transducer developed for teaching purposes in machine translation. The transducer is a specialized production system giving the linguists the tools for expressing information in a syntax that is close to theoretical linguistics. Major emphasis was placed on developing a system that is user friendly, uniform and legible. This paper describes the linguistic data structure, the rule formalism and the control facilities that the linguist is provided with.
Scalable and responsive event processing in the cloud

Event processing involves continuous evaluation of queries over streams of events. Response-time optimization is traditionally done over a fixed set of nodes and/or by using metrics measured at query-operator levels. Cloud computing makes it easy to acquire and release computing nodes as required. Leveraging this flexibility, we propose a novel, queueing-theory-based approach for meeting specified response-time targets against fluctuating event arrival rates by drawing only the necessary amount of computing resources from a cloud platform. In the proposed approach, the entire processing engine of a distinct query is modelled as an atomic unit for predicting response times. Several such units hosted on a single node are modelled as a multiple class M/G/1 system. These aspects eliminate intrusive, low-level performance measurements at run-time, and also offer portability and scalability. Using model-based predictions, cloud resources are efficiently used to meet response-time targets. The efficacy of the approach is demonstrated through cloud-based experiments.
Towards a real-time architecture for obstacle avoidance and path planning in mobile robots

The design and partial implementation of a real-time architecture for a mobile robot, aimed particularly towards a vehicle developed for factory automation, is described. The authors develop a layered design to equip the robot with a number of behavioral competences. They examine sensing and a potential field algorithm especially to achieve modification of behavior at a speed close to the robot's operational speed. It is shown how the layered architecture interfaces to the original onboard architecture, which provided sophisticated localization but no ability to deal with environmental exceptions. <<ETX>>
Junctional Adhesion Molecule 2 Mediates the Interaction between Hatched Blastocyst and Luminal Epithelium: Induction by Progesterone and LIF

Background Junctional adhesion molecule 2 (Jam2) is a member of the JAM superfamily. JAMs are localized at intercellular contacts and participated in the assembly and maintenance of junctions, and control of cell permeability. Because Jam2 is highly expressed in the luminal epithelium on day 4 of pregnancy, this study was to determine whether Jam2 plays a role in uterine receptivity and blastocyst attachment in mouse uterus. Methodology/Principal Findings Jam2 is highly expressed in the uterine luminal epithelium on days 3 and 4 of pregnancy. Progesterone induces Jam2 expression in ovariectomized mice, which is blocked by progesterone antagonist RU486. Jam2 expression on day 4 of pregnancy is also inhibited by RU486 treatment. Leukemia inhibitory factor (LIF) up-regulates Jam2 protein in isolated luminal epithelium from day 4 uterus, which is blocked by S3I-201, a cell-permeable inhibitor for Stat3 phosphorylation. Under adhesion assay, recombinant Jam2 protein increases the rate of blastocyst adhesion. Both soluble recombinant Jam2 and Jam3 can reverse this process. Conclusion Jam2 is highly expressed in the luminal epithelium of receptive uterus and up-regulated by progesterone and LIF via tyrosine phosphorylation of Stat3. Jam2 may play a role in the interaction between hatched blastocyst and receptive uterus.
Field-trial of a λ-to-the-user high-budget PON using a novel class of low-cost coherent transceivers and compatible with EPON system operation

COCONUT project demonstrated an innovative DWDM Passive Optical Network implementing the full λ-to-the-user concept in a filterless distribution fiber network. We make use of an innovative class of coherent transceivers that exploit the advantages of coherent detection in terms of sensitivity and channel selectivity in a cost efficient manner. The different transceivers developed target different use case scenarios, showing perfect compatibility with legacy infrastructures installed. In this paper, we report the successful trial of the proposed system in a testbed where 4 different coherent transceivers (plus one legacy E-PON system) ran simultaneously, operating over 14 DWDM channels, in a dark-fiber network in the city of Pisa, delivering real-time and/or test traffic. The testbed demonstrated filterless operations, multi-rate transmission (from 1.25 to 10 Gb/s/λ), high ODN loss (18 – 40 dB) as well as a bi-directional channel monitoring system.
Differences between hard and soft phylogenetic data

When building the tree of life, variability of phylogenetic signal is often accounted for by partitioning gene sequences and testing for differences. The same considerations, however, are rarely applied to morphological data, potentially undermining its use in evolutionary contexts. Here, we apply partition heterogeneity tests to 59 animal datasets to demonstrate that significant differences exist between the phylogenetic signal conveyed by ‘hard’ and ‘soft’ characters (bones, teeth and shells versus myology, integument etc). Furthermore, the morphological partitions differ significantly in their consistency relative to independent molecular trees. The observed morphological differences correspond with missing data biases, and as such their existence presents a problem not only for phylogeny reconstruction, but also for interpretations of fossil data. Evolutionary inferences drawn from clades in which hard, readily fossilizable characters are relatively less consistent and different from other morphology (mammals, bivalves) may be less secure. More secure inferences might be drawn from the fossil record of clades that exhibit fewer differences, or exhibit more consistent hard characters (fishes, birds). In all cases, it will be necessary to consider the impact of missing data on empirical data, and the differences that exist between morphological modules.
Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments

Data augmentation and Gibbs sampling are two closely related, sampling-based approaches to the calculation of posterior moments. The fact that each produces a sample whose constituents are neither independent nor identically distributed complicates the assessment of convergence and numerical accuracy of the approximations to the expected value of functions of interest under the posterior. In this paper methods for spectral analysis are used to evaluate numerical accuracy formally and construct diagnostics for convergence. These methods are illustrated in the normal linear model with informative priors, and in the Tobit-censored regression model.
Melatonin Levels in Preterm and Term Infants and Their Mothers

The prevention of perinatal brain damage following preterm birth remains a public health priority. Melatonin has been shown to be a promising neuroprotectant in neonatal preclinical models of brain damage, but few studies have investigated melatonin secretion in newborns. We hypothesized that melatonin circulating levels would be lower in preterm compared to term infants. We conducted a prospective, longitudinal, multicenter study to assess melatonin, and 6-sulfatoxy-melatonin (aMT6s) concentrations, measured by radioimmunoassay. Among 209 neonates recruited, 110 were born before 34 gestational weeks (GW) and 99 born after 34 GW. Plasma melatonin concentrations, measured at birth and on Day 3 were below detectable levels (≤7 pg/mL) in 78% and 81%, respectively, of infants born before 34 GW compared to 57% and 34%, respectively, of infants born after 34 GW. The distribution of plasma melatonin concentrations was found to be correlated with gestational age at both time-points (p < 0.001). Median urine aMT6s concentrations were significantly lower in infants born before 34 GW, both on Day 1 (230 ng/L vs. 533 ng/L, p < 0.0001) and on Day 3 (197 ng/L vs. 359 ng/L, p < 0.0001). In conclusion, melatonin secretion appears very low in preterm infants, providing the rationale for testing supplemental melatonin as a neuroprotectant in clinical trials.
An Empirical Examination of the Relationship between Ownership Structure and the Performance of Firms in Nigeria

This study examines the relationship between ownership structure and the financial performance of listed firms in the financial sector of the Nigerian economy. To achieve the objective of this study, a total of 31 selected listed firms in the Nigerian stock exchange market were used. Also, the corporate annual reports for the period 2006-2010 were analyzed. This paper basically modeled the corporate ownership structure and firm performance relationship of the selected listed firms using the multivariate multiple regression analysis method to test the research propositions in this study. The study as part of it findings observed that observed that institutional ownership has a significant positive impact on the performance of the selected listed firms in Nigeria. In addition, the study also revealed that that there is a significant positive relationship between foreign ownership and the firm performance in Nigeria.
Reproductive Pathological Changes Associated with Experimental Subchronic Corynebacterium pseudotuberculosis Infection in Nonpregnant Boer Does

Corynebacterium pseudotuberculosis causes caseous lymphadenitis (CLA), which is a contagious and chronic disease in sheep and goats. In order to assess the histopathological changes observed in the reproductive organs of nonpregnant does infected with the bacteria, 20 apparently healthy adult Boer does were divided into four inoculation groups, intradermal, intranasal, oral, and control, consisting of five goats each. Excluding the control group, which was unexposed, other does were inoculated with 107 CFU/1 mL of live C. pseudotuberculosis through the various routes stated above. Thirty days after infection, the ovaries, uterus, and iliac lymph nodes were collected for bacterial recovery and molecular detection, as well as histopathological examination. The mean changes in necrosis, congestion, inflammatory cell infiltration, and oedema varied in severity among the ovaries, uterus, and iliac lymph nodes following different inoculation routes. Overall, the intranasal route of inoculation showed more severe (p < 0.05) lesions in all the organs examined. The findings of this study have shown that C. pseudotuberculosis could predispose to infertility resulting from pathological lesions in the uterus and ovaries of does.
Microbeads display of proteins using emulsion PCR and cell‐free protein synthesis

We developed a method for coupling protein to its coding DNA on magnetic microbeads using emulsion PCR and cell‐free protein synthesis in emulsion. A PCR mixture containing streptavidin‐coated microbeads was compartmentalized by water‐in‐oil (w/o) emulsion with estimated 0.5 template molecules per droplet. The template molecules were amplified and immobilized on beads via bead‐linked reverse primers and biotinylated forward primers. After amplification, the templates were sequentially labeled with streptavidin and biotinylated anti‐glutathione S‐transferase (GST) antibody. The pool of beads was then subjected to cell‐free protein synthesis compartmentalized in another w/o emulsion, in which templates were coupled to their coding proteins. We mixed two types of DNA templates of Histidine6 tag (His6)‐fused and FLAG tag‐fused GST in a ratio of 1:1,000 (His6: FLAG) for use as a model DNA library. After incubation with fluorescein isothiocyanate (FITC)‐labeled anti‐His6 (C‐term) antibody, the beads with the His6 gene were enriched 917‐fold in a single‐round screening by using flow cytometry. A library with a theoretical diversity of 106 was constructed by randomizing the middle four residues of the His6 tag. After a two‐round screening, the randomized sequences were substantially converged to peptide‐encoding sequences recognized by the anti‐His6 antibody.
Going beyond the perception of affordances: Learning how to actualize them through behavioral parameters

In this paper, we propose a method that enables a robot to learn not only the existence of affordances provided by objects, but also the behavioral parameters required to actualize them, and the prediction of effects generated on the objects in an unsupervised way. In a previous study, it was shown that through self-interaction and self-observation, analogous to an infant, an anthropomorphic robot can learn object affordances in a completely unsupervised way, and use this knowledge to make plans in its perceptual space. This paper extends the affordances model proposed in that study by using parametric behaviors and including the behavior parameters into affordance learning and goal-oriented plan generation. Furthermore, for handling complex behaviors and complex objects (such as execution of precision grasp on a mug), the perceptual processing is improved by using a combination of local and global features. Finally, a hierarchical clustering algorithm is used to discover the affordances in non-homogenous feature space. In short, object affordances for object manipulation are discovered together with behavior parameters based on the monitored effects.
Object-transportation control for a human-operated robotic manipulator

Because of the difficulty in realizing fully automated robotic systems from the viewpoint of cost efficiency and available current technologies, human-robot cooperative system has been widely studied to date. This paper deals with a human-operated robotic manipulator that supports the object-transportation task in houseworks and factories. A new controller design that provides two fundamental functions is developed; obstacle avoidance and stable transportation of object, even when the human operator makes mistakes in operation. A general type of three-degree-of-freedom robotic manipulator is considered, which moves in a horizontal plane and can be operated by a joy-stick controller. To achieve both the obstacle avoidance and the stable transportation of object with providing a function that incorporates the human-operatorpsilas command, we propose a model reference control approach in which the robot follows a desired trajectory generated by a reference model. The effectiveness of the proposed method is confirmed by experiments where several unskilled operators operate the manipulator for transporting a object in a narrow space.