Miracle-dz/UniFAR-FTUs huggingface dataset:
An Improved Link Model for Window Flow Control and Its Application to FAST TCP

This paper presents a link model which captures the queue dynamics in response to a change in a transmission control protocol (TCP) source's congestion window. By considering both self-clocking and the link integrator effect, the model generalizes existing models and is shown to be more accurate by both open loop and closed loop packet level simulations. It reduces to the known static link model when flows' round trip delays are identical, and approximates the standard integrator link model when there is significant cross traffic. We apply this model to the stability analysis of fast active queue management scalable TCP (FAST TCP) including its filter dynamics. Under this model, the FAST control law is linearly stable for a single bottleneck link with an arbitrary distribution of round trip delays. This result resolves the notable discrepancy between empirical observations and previous theoretical predictions. The analysis highlights the critical role of self-clocking in TCP stability, and the proof technique is new and less conservative than existing ones.
Analysis of the Zooplankton Community by the Shannon - Weaver Index in Kesikköprü Dam Lake, Turkey

Kesikköprü Dam Lake that is oligotrophic is represented by 11 Rotifera, nine Cladocera and eight Copepoda species. The data obtained from the zooplankton community in Kesikköprü Dam Lake were analysed by the Shannon Weaver index. The index values showed no positive correlation with the total number of zooplanktonic organisms. Therefore, the index value (H= 2.10) is higher in autumn than in other seasons. The abundance data and Shannon – Weaver index values were both analysed by UPGM clustering method. Winter and summer seasons were found to be the most similar by using Shannon – Weaver index values, but spring and autumn showed similarity with seasonal abundance. In this respect, the Shannon Weaver index is not useful for monitoring and determining the trophic status of Kesikköprü Dam Lake. However, H values express seasonal homogeneity in the species abundance of zooplankton community.
English Usage among Hispanics in the United States.

Revised 12-06-07 to add the following note to Figure 13: " Puerto Ricans are excluded from the estimates in this figure. " The Pew Hispanic Center is a nonpartisan research organization that seeks to improve public understanding of the diverse Hispanic population in the United States and to chronicle Latinos' growing impact on the nation. It does not take positions on policy issues. The center is part of the Pew Research Center, a nonpartisan "fact tank" based in Washington, D.C., and it is funded by The Pew Charitable Trusts, a Philadelphia-based public charity. All of the Center's reports are available at Executive Summary Nearly all Hispanic adults born in the United States of immigrant parents report they are fluent in English. By contrast, only a small minority of their parents describe themselves as skilled English speakers. This finding of a dramatic increase in English-language ability from one generation of Hispanics to the next emerges from a new analysis of six Pew Hispanic Center surveys conducted this decade among a total of more than 14,000 Latino adults. The surveys show that fewer than one-in-four (23%) Latino immigrants reports being able to speak English very well. However, fully 88% of their U.S.-born adult children report that they speak English very well. Among later generations of Hispanic adults, the figure rises to 94%. Reading ability in English shows a similar trend. As fluency in English increases across generations, so, too, does the regular use of English by Hispanics, both at home and at work. For most immigrants, English is not the primary language they use in either setting. But for their grown children, it is. The surveys also find that Latino immigrants are more likely to speak English very well, and to use it often, if they are highly educated, arrived in the United States as children or have spent many years here. College education, in particular, plays an important role in the ability to speak and read English. Among the major Hispanic origin groups, Puerto Ricans and South Americans are the most likely to say they are proficient in English; Mexicans are the least likely to say so. The transition to English dominance occurs at a slower pace at home than it does at work. Just 7% of foreign-born Hispanics speak mainly or only English at home; about half of their adult children do. By contrast, four times as many foreign-born Latinos …
Trends in Job Instability and Wages for Young Adult Men

Data and measurement problems have complicated the debate over trends in job instability in the United States. We compare two cohorts of young white men from the National Longitudinal Surveys (NLS), construct a rigorous measure of job change, and confirm earlier findings of a significant increase in job instability. We then benchmark the NLS against other main data sets in the field and conduct a thorough attrition analysis. Extending the analysis to wages, we find that the wage returns to job changing have both declined and become more unequal for young adults, mirroring trends in their long‐term wage growth.
Gravitational radiation in black-hole collisions at the speed of light. II. Reduction to two independent variables and calculation of the second-order news function.

This paper describes analytical simplifications which make feasible the numerical calculation of the second-order news function, which gives partial information about the angular distribution of gravitational radiation emitted in the axisymmetric collision of two black holes at the speed of light. In the preceding paper, paper I, the curved radiative region of the space-time, produced after the collision of the two incoming plane-fronted shock waves, was treated using perturbation theory by making a large Lorentz boost to a frame in which a weak shock of energy λ scatters offa strong shock of energy v>>λ
Robust Local Community Detection: On Free Rider Effect and Its Elimination

Given a large network, local community detection aims at finding the community that contains a set of query nodes and also maximizes (minimizes) a goodness metric. This problem has recently drawn intense research interest. Various goodness metrics have been proposed. However, most existing metrics tend to include irrelevant subgraphs in the detected local community. We refer to such irrelevant subgraphs as free riders. We systematically study the existing goodness metrics and provide theoretical explanations on why they may cause the free rider effect. We further develop a query biased node weighting scheme to reduce the free rider effect. In particular, each node is weighted by its proximity to the query node. We define a query biased density metric to integrate the edge and node weights. The query biased densest subgraph, which has the largest query biased density, will shift to the neighborhood of the query nodes after node weighting. We then formulate the query biased densest connected subgraph (QDC) problem, study its complexity, and provide efficient algorithms to solve it. We perform extensive experiments on a variety of real and synthetic networks to evaluate the effectiveness and efficiency of the proposed methods.
An Environment for Rule Extraction and Evaluation from Databases

Classi cation for very large databases has many practical applications in Data Mining. Thus, Machine Learning algorithms should be able to operate in massive datasets in order to extract symbolic classi ers. In this context, a symbolic classi er is the one that can be transformed into a set of rules. When a dataset is too big for a particular learning algorithm, there are other ways to make learning feasible such as dataset sampling: for each sample a classi er is extracted for further investigation, like accuracy evaluation. It is also possible to evaluate the performance of combining all extracted classi ers into an ensemble. However, combining symbolic classi ers into a single one by a majority (or other) vote mechanism does not result into a symbolic classi er any more. The approach adopted in this under development work consists in evaluating the induced knowledge as white-box i.e., looking to the rules and trying to combine them using a computational environment. The environment is designed as a test-bed for Data Mining research, as well as a generic knowledge discovery tool for varied database domains. Flexibility is achieved by an open-ended design for extensibility, enabling integration of existing Machine Learning algorithms, support functions for pre-processing as well as new locally developed algorithm and functions.
Normal distribution of urinary polyphenol excretion among Egyptian males 7–14 years old and changes following nutritional intervention with tomato juice (Lycopersiconesculentum)

Background The urinary flavonoids are considered a reliable biomarker for the intake of polyphenol-rich foods. Objectives To assess the normal distribution of urinary polyphenol [PP] excretion among healthy male children and adolescents on a typical Egyptian diet. To follow up the impact of nutritional intervention with tomato juice on the urinary excretion of [PP]. Subjects Forty-nine male subjects 7–14 years old collected a 24-h urine sample and filled a dietary record during a 7-day period. A daily serving of 230 g fresh tomato juice was followed for 18 days in a subgroup. Total urinary [PP] excretions were measured before and after termination of the intervention program. The total urinary [PP] was analyzed after a clean-up solid-phase extraction step by the Folin–Ciocalteu reagent in the 96 micro plates. The results were expressed as gallic acid equivalents (GAE). Results The urinary [PP] excretion averaged 48.6±5.5 mg GAE/24 h, equivalent to 89.5±8.4 mg GAE/g creatinine. The mean urinary [PP] excretion increased significantly (P<0.05) following the intervention with tomato juice (287.4±64.3 mg GAE/g creatinine) compared with the respective mean baseline level (94.5±8.92 mg GAE/g creatinine). Conclusion Clinical laboratory reference limits for urinary polyphenols are presented for Egyptian male children and adolescents. Measuring the urinary polyphenol excretion proved a good biomarker for the dietary polyphenol intake and the results demonstrated that tomato [PP] was highly bioavailable in the human body.
21---- Networks in Finance l

Modem financial systems exhibit a high degree of interdependence, with connections between finanCial institutions stemming from both the asset and the liability sides of their balance sheets. Networks-broadly understood as a collection of nodes and links between nodes-ean be a useful representation offinanCial systems. By modeling eco­ nomic interactions, network analyses can better explain certain economic phenomena. In this chapter, Allen and Babus argue that the use of network theories can enrich our understanding of finanCial systems. They explore several critical issues. First, they address the issue ofsystemic risk, by studying two questions: how resilient finanCial net­ works are to contagion, and how financial institutions form connections when exposed to the risk ofcontagion. Second, they consider how network theory can be used to explain freezes in the interbank market. Third, they examine how social networks can improve investment decisions and corporate governance, based on recent empirical results. Fourth, they examine the role of networks in distributing primary issues of securities. Finally, they consider the role of networks as a form of mutuat monitoring, as in microfinance. 1 We are grateful to the editors and to participants at the Wharton INSEAD conference on November 8-9, 2007, where the book's papers were presented for their helpful comments.
Does Anxiety Cause Freezing of Gait in Parkinson's Disease?

Individuals with Parkinson's disease (PD) commonly experience freezing of gait under time constraints, in narrow spaces, and in the dark. One commonality between these different situations is that they may all provoke anxiety, yet anxiety has never been directly examined as a cause of FOG. In this study, virtual reality was used to induce anxiety and evaluate whether it directly causes FOG. Fourteen patients with PD and freezing of gait (Freezers) and 17 PD without freezing of gait (Non-Freezers) were instructed to walk in two virtual environments: (i) across a plank that was located on the ground (LOW), (ii) across a plank above a deep pit (HIGH). Multiple synchronized motion capture cameras updated participants' movement through the virtual environment in real-time, while their gait was recorded. Anxiety levels were evaluated after each trial using self-assessment manikins. Freezers performed the experiment on two separate occasions (in their ON and OFF state). Freezers reported higher levels of anxiety compared to Non-Freezers (p<0.001) and all patients reported greater levels of anxiety when walking across the HIGH plank compared to the LOW (p<0.001). Freezers experienced significantly more freezing of gait episodes (p = 0.013) and spent a significantly greater percentage of each trial frozen (p = 0.005) when crossing the HIGH plank. This finding was even more pronounced when comparing Freezers in their OFF state. Freezers also had greater step length variability in the HIGH compared to the LOW condition, while the step length variability in Non-Freezers did not change. In conclusion, this was the first study to directly compare freezing of gait in anxious and non-anxious situations. These results present strong evidence that anxiety is an important mechanism underlying freezing of gait and supports the notion that the limbic system may have a profound contribution to freezing in PD.
Residue BDD and Its Application to the Verification of Arithmetic Circuits

The paper describes a verification method for arithmetic circuits based on residue arithmetic. In the verification, a residue module is attached to the specification and the implementation, and these outputs are compared by constructing BDD's. For the BDD construction without node explosion, we introduce a residue BDD whose width is less than or equal to a modulus. The method is useful for multipliers including C6288.
An architecture for emotional decision-making agents

Our research focuses on complex agents that are capable of interacting with their environments in ways that are increasingly similar to individual humans. In this article we describe a cognitive architecture for an interactive decision-making agent with emotions. The primary goal of this work is to make the decision-making process of complex agents more realistic with regard to the behavior moderators, including emotional factors that affect humans. Instead of uniform agents that rely entirely on a deterministic body of expertise to make their decisions, the decision making process of our agents will vary according to select emotional factors affecting the agent as well as the agent's parameterized emotional profile. The premise of this model is that emotions serve as a kind of automatic assessment system that can guide or otherwise influence the more deliberative decision making process. The primary components of this emotional system are pleasure/pain and clarity/confusion subsystems that differentiate between positive and negative states. These, in turn, feed into an arousal system that interfaces with the decision-making system. We are testing our model using synthetic special-forces agents in a reconnaissance simulation.
Evolution and Function of the Plant Cell Wall Synthesis-Related Glycosyltransferase Family 81[W][OA]

Carbohydrate-active enzyme glycosyltransferase family 8 (GT8) includes the plant galacturonosyltransferase1-related gene family of proven and putative α-galacturonosyltransferase (GAUT) and GAUT-like (GATL) genes. We computationally identified and investigated this family in 15 fully sequenced plant and green algal genomes and in the National Center for Biotechnology Information nonredundant protein database to determine the phylogenetic relatedness of the GAUTs and GATLs to other GT8 family members. The GT8 proteins fall into three well-delineated major classes. In addition to GAUTs and GATLs, known or predicted to be involved in plant cell wall biosynthesis, class I also includes a lower plant-specific GAUT and GATL-related (GATR) subfamily, two metazoan subfamilies, and proteins from other eukaryotes and cyanobacteria. Class II includes galactinol synthases and plant glycogenin-like starch initiation proteins that are not known to be directly involved in cell wall synthesis, as well as proteins from fungi, metazoans, viruses, and bacteria. Class III consists almost entirely of bacterial proteins that are lipooligo/polysaccharide α-galactosyltransferases and α-glucosyltransferases. Sequence motifs conserved across all GT8 subfamilies and those specific to plant cell wall-related GT8 subfamilies were identified and mapped onto a predicted GAUT1 protein structure. The tertiary structure prediction identified sequence motifs likely to represent key amino acids involved in catalysis, substrate binding, protein-protein interactions, and structural elements required for GAUT1 function. The results show that the GAUTs, GATLs, and GATRs have a different evolutionary origin than other plant GT8 genes, were likely acquired from an ancient cyanobacterium (Synechococcus) progenitor, and separate into unique subclades that may indicate functional specialization.
QoS-UniFrame: a Petri net-based modeling approach to assure QoS requirements of distributed real-time and embedded systems

Assuring quality of service (QoS) requirements is critical when assembling a distributed real-time and embedded (DRE) system from a repository of existing components. This paper presents a two-level approach for assuring satisfaction of QoS requirements in the context of a reduced design space for DRE systems. A dynamic and parallel approach is introduced to prune off the infeasible design spaces at the first level. Evolutionary algorithms cooperating with a domain-specific scripting language then discard less probable design spaces using statistics. These techniques fulfill the collective objectives of pruning and assuring the design space at system assembly time.
ProQ2: estimation of model accuracy implemented in Rosetta

Motivation: Model quality assessment programs are used to predict the quality of modeled protein structures. They can be divided into two groups depending on the information they are using: ensemble methods using consensus of many alternative models and methods only using a single model to do its prediction. The consensus methods excel in achieving high correlations between prediction and true quality measures. However, they frequently fail to pick out the best possible model, nor can they be used to generate and score new structures. Single-model methods on the other hand do not have these inherent shortcomings and can be used both to sample new structures and to improve existing consensus methods. Results: Here, we present an implementation of the ProQ2 program to estimate both local and global model accuracy as part of the Rosetta modeling suite. The current implementation does not only make it possible to run large batch runs locally, but it also opens up a whole new arena for conformational sampling using machine learned scoring functions and to incorporate model accuracy estimation in to various existing modeling schemes. ProQ2 participated in CASP11 and results from CASP11 are used to benchmark the current implementation. Based on results from CASP11 and CAMEO-QE, a continuous benchmark of quality estimation methods, it is clear that ProQ2 is the single-model method that performs best in both local and global model accuracy. Availability and implementation: https://github.com/bjornwallner/ProQ_scripts Contact: bjornw@ifm.liu. se Supplementary information: Supplementary data are available at Bioinformatics online.
Clinical and molecular delineation of the 17q21.31 microdeletion syndrome

Background: The chromosome 17q21.31 microdeletion syndrome is a novel genomic disorder that has originally been identified using high resolution genome analyses in patients with unexplained mental retardation. Aim: We report the molecular and/or clinical characterisation of 22 individuals with the 17q21.31 microdeletion syndrome. Results: We estimate the prevalence of the syndrome to be 1 in 16 000 and show that it is highly underdiagnosed. Extensive clinical examination reveals that developmental delay, hypotonia, facial dysmorphisms including a long face, a tubular or pear-shaped nose and a bulbous nasal tip, and a friendly/amiable behaviour are the most characteristic features. Other clinically important features include epilepsy, heart defects and kidney/urologic anomalies. Using high resolution oligonucleotide arrays we narrow the 17q21.31 critical region to a 424 kb genomic segment (chr17: 41046729–41470954, hg17) encompassing at least six genes, among which is the gene encoding microtubule associated protein tau (MAPT). Mutation screening of MAPT in 122 individuals with a phenotype suggestive of 17q21.31 deletion carriers, but who do not carry the recurrent deletion, failed to identify any disease associated variants. In five deletion carriers we identify a <500 bp rearrangement hotspot at the proximal breakpoint contained within an L2 LINE motif and show that in every case examined the parent originating the deletion carries a common 900 kb 17q21.31 inversion polymorphism, indicating that this inversion is a necessary factor for deletion to occur (p<10−5). Conclusion: Our data establish the 17q21.31 microdeletion syndrome as a clinically and molecularly well recognisable genomic disorder.
EnerJ: approximate data types for safe and general low-power computation

Energy is increasingly a first-order concern in computer systems. Exploiting energy-accuracy trade-offs is an attractive choice in applications that can tolerate inaccuracies. Recent work has explored exposing this trade-off in programming models. A key challenge, though, is how to isolate parts of the program that must be precise from those that can be approximated so that a program functions correctly even as quality of service degrades. We propose using type qualifiers to declare data that may be subject to approximate computation. Using these types, the system automatically maps approximate variables to low-power storage, uses low-power operations, and even applies more energy-efficient algorithms provided by the programmer. In addition, the system can statically guarantee isolation of the precise program component from the approximate component. This allows a programmer to control explicitly how information flows from approximate data to precise data. Importantly, employing static analysis eliminates the need for dynamic checks, further improving energy savings. As a proof of concept, we develop EnerJ, an extension to Java that adds approximate data types. We also propose a hardware architecture that offers explicit approximate storage and computation. We port several applications to EnerJ and show that our extensions are expressive and effective; a small number of annotations lead to significant potential energy savings (10%-50%) at very little accuracy cost.