Miracle-dz/UniFAR-FTUs huggingface dataset:
VNTR-DAT1 and COMTVal158Met Genotypes Modulate Mental Flexibility and Adaptive Behavior Skills in Down Syndrome

Down syndrome (DS) is an aneuploidy syndrome that is caused by trisomy for human chromosome 21 resulting in a characteristic cognitive and behavioral phenotype, which includes executive functioning and adaptive behavior difficulties possibly due to prefrontal cortex (PFC) deficits. DS also present a high risk for early onset of Alzheimer Disease-like dementia. The dopamine (DA) system plays a neuromodulatory role in the activity of the PFC. Several studies have implicated trait differences in DA signaling on executive functioning based on genetic polymorphisms in the genes encoding for the catechol-O-methyltransferase (COMTVal158Met) and the dopamine transporter (VNTR-DAT1). Since it is known that the phenotypic consequences of genetic variants are modulated by the genetic background in which they occur, we here explore whether these polymorphisms variants interact with the trisomic genetic background to influence gene expression, and how this in turn mediates DS phenotype variability regarding PFC cognition. We genotyped 69 young adults of both genders with DS, and found that VNTR-DAT1 was in Hardy-Weinberg equilibrium but COMTVal158Met had a reduced frequency of Met allele homozygotes. In our population, genotypes conferring higher DA availability, such as Met allele carriers and VNTR-DAT1 10-repeat allele homozygotes, resulted in improved performance in executive function tasks that require mental flexibility. Met allele carriers showed worse adaptive social skills and self-direction, and increased scores in the social subscale of the Dementia Questionnaire for People with Intellectual Disabilities than Val allele homozygotes. The VNTR-DAT1 was not involved in adaptive behavior or early dementia symptoms. Our results suggest that genetic variants of COMTVal158Met and VNTR-DAT1 may contribute to PFC-dependent cognition, while only COMTVal158Met is involved in behavioral phenotypes of DS, similar to euploid population.
Recurrent Neural Collective Classification

With the recent surge in availability of data sets containing not only individual attributes but also relationships, classification techniques that take advantage of predictive relationship information have gained in popularity. The most popular existing collective classification techniques have a number of limitations-some of them generate arbitrary and potentially lossy summaries of the relationship data, whereas others ignore directionality and strength of relationships. Popular existing techniques make use of only direct neighbor relationships when classifying a given entity, ignoring potentially useful information contained in expanded neighborhoods of radius greater than one. We present a new technique that we call recurrent neural collective classification (RNCC), which avoids arbitrary summarization, uses information about relationship directionality and strength, and through recursive encoding, learns to leverage larger relational neighborhoods around each entity. Experiments with synthetic data sets show that RNCC can make effective use of relationship data for both direct and expanded neighborhoods. Further experiments demonstrate that our technique outperforms previously published results of several collective classification methods on a number of real-world data sets.
No-Fault Insurance and Automobile Accidents PAUL HEATON AND

Removing accident liability through a no-fault system may only have minor effects on driver care, yet existing studies assessing whether no-fault auto insurance requirements increase accidents use fatal accidents as the primary outcome. In this paper we estimate the effect of no-fault on overall accident rates using detailed data from police accident reports in New Jersey, North Carolina, and Utah. We focus on accidents involving out-of-state drivers and account for differences in driving prevalence using accidents beyond the control of the driver. Controlling for a wide variety of accident, driver, and vehicle characteristics, we find little evidence that drivers under no-fault cause more accidents. Results on accident severity are mixed. JEL Classification: K13, G28 ______________________________________________________________________________ We wish to thank David Loughran, Stephen Carroll, and seminar participants at RAND helpful comments. We also appreciate the assistance of Yusuf Mohamedshah, who provided help in obtaining the HSIS data. The contents of this paper are solely the responsibility of the authors and do not reflect the opinions of the RAND Corporation. Heaton can be reached at pheaton@rand.org and Helland at eric.helland@claremontmckenna.edu.
Action Structures for the -Calculus

In a previous paper, action structures were proposed as a variety of algebra to underlie concrete models of concurrent computation and interaction. That work is summarised here, to make the paper self-contained. In particular, the uniform construction of a process calculus upon an arbitrary action structure is reviewed. Another relevant concept from the previous paper is recalled, namely the notion of incident set. Its importance is that, in the process calculus uniformly constructed upon any action structure, a bisimulation equivalence which rests upon an incident set is guaranteed to be a congruence for the calculus. The main purpose of this paper is to give a family of action structures for the -calculus. Using one of these, the original -calculus is obtained by the uniform construction. The most substantial technical element here is the construction of an appropriate incident set for this action structure, yielding a bisimulation congruence for the -calculus. Another action structure is used to provide (again via the uniform construction) a synchronous version of the -calculus, in the sense that MEIJE or SCCS is a synchronous version of CCS. The natural version of this action structure contains an anomaly which appears to prevent the existence of the appropriate incident set. However, a so-called reflexive version of the action structure does indeed yield a natural incident set, and thereby again a bisimulation congruence. Two innovations are noteworthy. One is the definition of reflexive substitution. With this new kind of substitution, restricting a port-name x (in the sense of CCS) amounts to “making x denote itself” – i.e. reflexively substitutingx for itself. This notion simplifies the action structure for the synchronous -calculus. The second innovation is that the action structures are presented graphically, giving a new perspective on the -calculus. Indeed, both definition and proof of the incident set for the reflexive -calculus are in terms of a simple graph-theoretic notion of reachability. This work was done with the support of a Senior Fellowship from the Science and Engineering Research Council, UK.
Fast Gaussian Mixture Clustering for Skin Detection

EM is one of the popular algorithms which can be applied to skin segmentation. Due to the high computational cost of EM, traditional EM is difficult to apply to a large skin database. Inspired by the idea of subsampling, we integrate EM with incremental clustering and hierarchical clustering to estimate the parameters of mixture models. The algorithm first selects the samples by the incremental clustering approach and hierarchical clustering approach. Then, EM is applied to the sample set. The experiments show that the new EM algorithm works well in the skin database.
USING THE ECONFERENCE TOOL FOR SYNCHRONOUS DISTRIBUTED REQUIREMENTS WORKSHOPS

eConference is an XMPP-based conferencing tool that supports synchronous, structured communication in distributed scenarios. We present the usage of eConference in the context of distributed requirements engineering, where groups of stakeholders from different organizations are temporarily involved in communication-rich processes such as requirements workshops. We also describe an initial evaluation of the tool in the context of student project works.
Web Similarity

Normalized web distance (NWD) is a similarity or normalized semantic distance based on the World Wide Web or any other large electronic database, for instance Wikipedia, and a search engine that returns reliable aggregate page counts. For sets of search terms the NWD gives a similarity on a scale from 0 (identical) to 1 (completely different). The NWD approximates the similarity according to all (upper semi)computable properties. We develop the theory and give applications. The derivation of the NWD method is based on Kolmogorov complexity.
Deformation modeling using global medial representation structures and evaluation by biset mesh matching

In this paper, we present a novel hybrid deformation model using global mass-spring medial representation structures and local finite element model. We employ the hybrid models, by fully calculating the FEM deformation in the local operation part while only calculating the global deformation by medial representation method. To achieve the real-time requirement of realistic deformable modeling, it is necessary to use the GPU parallel computing for FEM on regional deformation details, so the major calculation work in the conjugate gradient solver for the solution matrix is moved from CPU to GPU to accelerate the effectiveness. Evaluation and experiments are also discussed.
Software Process Improvement In Bangladesh

the process is not understood or the process is not operating at its best. With offshore outsourcing and growing countries like Bangladesh is in a position of exporting their local Information Technology services. However, what is the state of Information Technology in Bangladesh? No documented cases of Bangladesh companies have the maturity of CMM level 3 or above. What are the challenges faced by Information Technology companies in Bangladesh? 2. Current Scenario of Bangladesh in SPI Bangladesh is one of the largest developing countries in the world with a population of more than 135 million. The software industry in Bangladesh has come a long way over the last few decades. In the last five to ten years, a good number of entrepreneurs and talented professionals have come forward to make the industry more dynamic and more vibrant. According to the BASIS (the Bangladesh Association of Software and Information Services), more than three hundred (300) registered software companies are currently operating in Bangladesh. From them, more than fifty (50) software and IT service companies are exporting their product and services to thirty (30) different countries in the world including USA, Canada, European countries, Middle East, Japan, Australia, South Africa and some of the South East Asian countries (Mashroor 2005). However, it is reported that not a single company has achieved SEI's (Software Engineering Institute at Carnegie-Mellon University, USA) SW-CMM or CMMI level 3, though some of them exercise PSP (Personal Software Process) to improve the quality of their development process (Hossain 2004, p.5). CMM/CMMI level three (3) is generally considered the minimum requirement for a company to be eligible to participate in global software industry. Therefore, it seems that software process and process improvement is not realized properly among the software organizations of Bangladesh. Recently, some companies are claiming that they are on the way of gaining CMM/CMMI level 3 even one foreign company claiming, whose local office is in Bangladesh, it has already achieved CMMI level 3, and it is a good news for software industry in Bangladesh. This scenario would influence software companies to introduce Software Process Improvement program in their organizations. ABSTRACT
AQUILA network architecture: first trial experiments

The paper presents trial experiments with IP QoS network services (NS) defined and implemented in the AQUILA pilot installation. The AQUILA NSs (premium CBR, premium VBR, premium multimedia and premium mission critical) provide a framework for supporting a variety of applications generating both streaming and elastic traffic. The measurement experiments confirm that AQUILA architecture differentiates the QoS offered to these NSs. The presented numerical results were obtained in the test network installed in the Polish Telecom (Warsaw) consisting of 8 CISCO routers.
Performance comparisons of all-pass transform adaptation with maximum likelihood linear regression

All-pass transform (APT) adaptation transforms the cepstral means of a hidden Markov model so as to mimic the effect of warping the short-time frequency axis of a segment of speech, much like vocal tract length normalization (VTLN). However, APT adaptation can be implemented as a linear transformation in the cepstral domain, much like the better known maximum likelihood linear regression (MLLR). Recent work demonstrated the superior performance of APT adaptation to MLLR for a large vocabulary conversational speech recognition task. This work presents similar comparisons on the switchboard corpus. We found that without VTLN, the best MLLR and APT systems achieved word error rates (WERs) of 43.0% and 40.2% respectively. Similarly, with VTLN the respective error rates were 40.3%, and 39.2%, so that APT adaptation is significantly better in both cases. We also undertook a set of experiments to determine whether APT adaptation can be combined with a linear semi-tied covariance (STC) transform. With a single APT per speaker, the application of STC reduced the WER from 42.9% to 39.4%.
Density Kernels on Unordered Sets for Kernel-Based Signal Processing

Algorithms involved in applications such as speaker recognition or image classification need to be able to process data which are sets of vectors with variable size. As opposed to the standard setting for kernel methods, where the data are individual vectors, it is difficult to build a reliable reproducing kernel between such sets of unordered vectors. Most effective techniques rely on the design of kernel calculated on densities estimated independently on each set of vectors; however, this calculation can be numerically tricky: therefore these techniques either use poor estimates such as histograms, or assume unjustified restrictive conditions. In this paper, we improve on the existing framework and design kernels between densities, where these are estimated using an effective nonparametric technique, namely the Akaike-Parzen-Rosenblatt (APR) estimate. Closed-form expressions are obtained for positive definite kernels, and simulation results illustrate the soundness of the approach.
Integration of the intertwining operator for $h$-harmonic polynomials associated to reflection groups

Let V be the intertwining operator with respect to the reflection invariant measure hαdω on the unit sphere S d−1 in Dunkl’s theory on spherical h-harmonics associated with reflection groups. Although a closed form of V is unknown in general, we prove that ∫ Sd−1 V f(y)hα(y)dω = Aα ∫ Bd f(x)(1 − |x|2)|α|1−1dx, where Bd is the unit ball of Rd and Aα is a constant. The result is used to show that the expansion of a continuous function as Fourier series in h-harmonics with respect to hαdω is uniformly Cesáro (C, δ) summable on the sphere if δ > |α|1 + (d− 2)/2, provided that the intertwining operator is positive.
Genes that influence yield in tomato

Yield is the most important breeding trait of crops. For fruit-bearing plants such as Solanum lycopersicum (tomato), fruit formation directly affects yield. The final fruit size depends on the number and volume of cell layers in the pericarp of the fruit, which is determined by the degree of cell division and expansion in the fertilized ovaries. Thus, fruit yield in tomato is predominantly determined by the efficiency of fruit set and the final cell number and size of the fruits. Through domestication, tomato fruit yield has been markedly increased as a result of mutations associated with fruit size and genetic studies have identified the genes that influence the cell cycle, carpel number and fruit set. Additionally, several lines of evidence have demonstrated that plant hormones control fruit set and size through the delicate regulation of genes that trigger physiological responses associated with fruit expansion. In this review, we introduce the key genes involved in tomato breeding and describe how they affect the physiological processes that contribute to tomato yield.
Aspects of anthocyanin absorption, metabolism and pharmacokinetics in humans

Abstract Interest in the health-promoting properties of berry anthocyanins is intensifying; however, findings are primarily based on in vitro characteristics, leaving mechanisms associated with absorption, metabolism and pharmacokinetics largely unexplored. The present review integrates the available anthocyanin literature with that of similar flavonoids or polyphenols in order to form hypotheses regarding absorption, metabolism and clearance in humans. Of the limited available literature regarding the absorption and clearance kinetics of anthocyanins, maximum plasma concentrations are reported anywhere between 1·4 and 592 nmol/l and occur at 0·5–4 h post-consumption (doses; 68–1300 mg). Average urinary excretion is reported between 0·03 and 4 % of the ingested dose, having elimination half-lives of 1·5–3 h. In addition, much is unknown regarding the metabolism of anthocyanins. The most commonly cited conjugation reactions involved in the metabolism of other flavonoids include glucuronidation, methylation and sulfation. It is reasonable to suspect that anthocyanins are metabolised in much the same manner; however, until recently, there was little evidence to suggest that anthocyanins were metabolised to any significant extent. New evidence now suggests that anthocyanins are absorbed and transported in human serum and urine primarily as metabolites, with recent studies documenting as much as 68–80 % of anthocyanins as metabolised derivatives in human urine. Further research is required to resolve mechanisms associated with the absorption, metabolism and clearance of anthocyanins in order to establish their true biological activities and health effects. The presented evidence will hopefully focus future research, refining study design and propagating a more complete understanding of anthocyanins' biological significance in humans.
Finite horizon analysis of infinite CTMDPs

Continuous Time Markov Decision Processes (CTMDPs) are used to describe optimization problems in many applications including system maintenance and control. Often one is interested in a control strategy or policy to optimize the gain of a system over a finite interval which is denoted as finite horizon. The computation of an ε-optimal policy, i.e., a policy that reaches the optimal gain up to some small ε, is often hindered by state space explosion which means that state spaces of realistic models can be very large or even infinite. The paper presents new algorithms to compute approximately optimal policies for CTMDPs with large or infinite state spaces. The new approach allows one to compute bounds on the achievable gain and a policy to reach the lower bound using a variant of uniformization on a finite subset of the state space. It is also shown how the approach can be applied to models with unbounded rewards or transition rates for which uniformization cannot be applied per se.
Fried food consumption, genetic risk, and body mass index: gene-diet interaction analysis in three US cohort studies

Objective To examine the interactions between genetic predisposition and consumption of fried food in relation to body mass index (BMI) and obesity. Design Prospective cohort study. Setting Health professionals in the United States. Participants 9623 women from the Nurses’ Health Study, 6379 men from the Health Professionals Follow-up Study, and a replication cohort of 21 421 women from the Women’s Genome Health Study. Main outcome measure Repeated measurement of BMI over follow-up. Results There was an interaction between fried food consumption and a genetic risk score based on 32 BMI-associated variants on BMI in both the Nurses’ Health Study and Health Professionals Follow-up Study (P≤0.001 for interaction). Among participants in the highest third of the genetic risk score, the differences in BMI between individuals who consumed fried foods four or more times a week and those who consumed fried foods less than once a week amounted to 1.0 (SE 0.2) in women and 0.7 (SE 0.2) in men, whereas the corresponding differences were 0.5 (SE 0.2) and 0.4 (SE 0.2) in the lowest third of the genetic risk score. The gene-diet interaction was replicated in the Women’s Genome Health Study (P<0.001 for interaction). Viewed differently, the genetic association with adiposity was strengthened with higher consumption of fried foods. In the combined three cohorts, the differences in BMI per 10 risk alleles were 1.1 (SE 0.2), 1.6 (SE 0.3), and 2.2 (SE 0.6) for fried food consumption less than once, one to three times, and four or more times a week (P<0.001 for interaction); and the odds ratios (95% confidence intervals) for obesity per 10 risk alleles were 1.61 (1.40 to 1.87), 2.12 (1.73 to 2.59), and 2.72 (2.12 to 3.48) across the three categories of consumption (P=0.002 for interaction). In addition, the variants in or near genes highly expressed or known to act in the central nervous system showed significant interactions with fried food consumption, with the FTO (fat mass and obesity associated) variant showing the strongest result (P<0.001 for interaction). Conclusion Our findings suggest that consumption of fried food could interact with genetic background in relation to obesity, highlighting the particular importance of reducing fried food consumption in individuals genetically predisposed to obesity.
SMOOTHING A PBSMT MODEL BY FACTORING OUT ADJUNCTS

Phrase-Based Statistical Machine Translation (PBSMT) became a leading paradigm in Statistical Machine Translation after its introduction in 2003. From the start, one has tried to improve PBSMT by using linguistic knowledge, often by incorporating syntactic information into the model. This thesis proposes a simple approach to improve PBSMT using a general linguistic notion, that of adjuncts, or modifiers: One expects that in structurally similar languages like French and English, adjuncts in one language are likely to be translated as adjuncts in the other language. After verifying this assumption, this thesis describes how adjunct pairs are deleted from a bilingual corpus to generate new training data for a model, which is then used to smooth a PBSMT baseline. Experiments on a smoothed French-English model show only a marginal improvement over the baseline. It appears that few of the phrase pairs gained by adjunct-pair deletion are actually used in testing, so that improvement in performance mostly results from successful smoothing. Further research directions would be to find out in how far performance can be improved for this system, but also to apply adjunct-pair deletion to other language pairs and to hierarchical SMT models.
A Directional Broadcast Protocol for Emergency Message Exchange in Inter-Vehicle Communications

Broadcast is an effective approach for safety-related information exchange to achieve cooperative driving in vehicular ad hoc network (VANET). However, it suffers from several fundamental challenges such as message redundancy, link unreliability, hidden terminal and broadcast storm, etc., which degrade the efficiency of the network greatly. To address these issues, this paper proposes a position based multi-hop broadcast protocol (PMBP) for emergency message dissemination in inter-vehicle communications. By adopting a cross-layer approach considering both the MAC and Network layers in the proposed scheme, the candidate vehicle for forwarding an emergency message is selected according to its distance from the source vehicle in the message propagation direction. Analysis and simulation results show that PMBP can not only quickly deliver emergency messages, but also reduce broadcast message redundancy significantly.