Miracle-dz/UniFAR-FTUs huggingface dataset:
NTS6: IPv6 based Network Topology Service System of CERNET2

In this paper, we propose NTS6, an IPv6 based network topology service system, which provides a query and response service of network topology information between any pair of hosts accessing IPv6 Internet via CERNET2. The NTS6 system periodically collects the latest OSPF, BGP and SNMP information of CERNET2. Based on these information, NTS6 provides network topology information such as net distance, available bandwidth and path packet loss in response to users' query. The real-world experiment on CERNET2 confirms the accuracy of our system. Also, NTS6 now performs well on large deployed maze P2P file-sharing system. We believe NTS6 will be a powerful middleware for other applications.
I. Matchings and coverings

Proof. The first equality follows directly from (1). To see the second equality, first let M be a matching of size ν(G). For each of the |V | − 2|M | vertices v missed by M , add to M an edge covering v. We obtain an edge cover of size |M | + (|V | − 2|M |) = |V | − |M |. Hence ρ(G) ≤ |V | − ν(G). Second, let F be an edge cover of size ρ(G). For each v ∈ V delete from F , dF (v) − 1 edges incident with v. We obtain a matching of size at least |F | − ∑
Task-Based Evaluation of NLG Systems: Control vs Real-World Context

Currently there is little agreement about, or even discussion of, methodologies for task-based evaluation of NLG systems. I discuss one specific issue in this area, namely the importance of control vs the importance of ecological validity (real-world context), and suggest that perhaps we need to put more emphasis on ecological validity in NLG evaluations.
Constraining dark energy with X‐ray galaxy clusters, supernovae and the cosmic microwave background

We present new constraints on the evolution of dark energy from an analysis of Cosmic Microwave Background, supernova and X-ray galaxy cluster data. Our analysis employs a minimum of priors and exploits the complementary nature of these data sets. We examine a series of dark energy models with up to three free parameters: the current dark energy equation of state w{sub 0}, the early time equation of state w{sub et} and the scale factor at transition, a{sub t}. From a combined analysis of all three data sets, assuming a constant equation of state and that the Universe is flat, we measure w{sub 0} = 1.05{sub -0.12}{sup +0.10}. Including w{sub et} as a free parameter and allowing the transition scale factor to vary over the range 0.5 < a{sub t} < 0.95 where the data sets have discriminating power, we measure w{sub 0} = -1.27{sub -0.39}{sup +0.33} and w{sub et} = -0.66{sub -0.62}{sup +0.44}. We find no significant evidence for evolution in the dark energy equation of state parameter with redshift. Marginal hints of evolution in the supernovae data become less significant when the cluster constraints are also included in the analysis. The complementary nature of the data sets leads tomore » a tight constraint on the mean matter density, {Omega}{sub m} and alleviates a number of other parameter degeneracies, including that between the scalar spectral index n{sub s}, the physical baryon density {Omega}{sub b}h{sup 2} and the optical depth {tau}. This complementary nature also allows us to examine models in which we drop the prior on the curvature. For non-flat models with a constant equation of state, we measure w{sub 0} = -1.09{sub -0.15}{sup +0.12} and obtain a tight constraint on the current dark energy density, {Omega}{sub de} = 0.70 {+-} 0.03. For dark energy models other than a cosmological constant, energy-momentum conservation requires the inclusion of spatial perturbations in the dark energy component. Our analysis includes such perturbations, assuming a sound speed c{sub s}{sup 2} = 1 in the dark energy fluid as expected for Quintessence scenarios. For our most general dark energy model, not including such perturbations would lead to spurious constraints on w{sub et} which would be tighter than those mentioned above by approximately a factor two with the current data. « less
An Experimental Comparison between Device-free Passive Tracking and Radio Tomographic Imaging

This paper presents a comparison between Radio Tomographic Imaging (RTI) and Device-free Passive (DfP) tracking in standard WiFi networks. We show that for typical WiFi deployments, tracking methods are able to extract location information from a limited number of streams while imaging methods fail to produce meaningful images. On the other hand, we show that when the number of streams increases, imaging methods are able to actually image the area of interest while tracking methods can only infer the location of the user, but with increased accuracy. We further compare the performance and cost trade-offs involved in choosing between these two systems.
A Discretization Method based on Maximizing the Area Under ROC Curve

We present a new discretization method based on Ar ea under ROC Curve (AUC) measure. Maximum Area under ROC Curve B ased Discretization (MAD) is a global, static and supervised discretiza tion method. It discretizes a continuous feature in a way that the AUC based only that feature is to be maximized. The proposed method is compared with alt erna ive discretization methods such as Entropy-MDLP (Minimum Description L ength Principle) which is known as one of the best discretization me thods, Fixed Frequency Discretization (FFD), and Proportional Discretizati on (PD). FFD and PD are proposed recently and designed for naïve Bayes lear ning. Evaluations are performed in terms of M-Measure, an AUC based metri c for multi-class classification, and accuracy values obtained from n aïve Bayes and Aggregating One-Dependence Estimators (AODE) algorithms by usin g real world datasets. Empirical results show that our method is a candida te to be a good alternative to other discretization methods.
A Dependency Treebank for Buryat

There has been little research on natural-language processing of Buryat, in part due to the absence of language resources. In this article we present the first syntactic treebank for Buryat. It is an evolving project based on the Universal Dependencies (UD) annotation guidelines. We report on the procedure of constructing the treebank and explain some features of the labelling scheme with respect to linguistic phenomena in Buryat. The annotation of 919 sentences was done manually from scratch without using any automatic labelling tools. We evaluate the performance of various language models with UDPipe and describe the plans for future work.
Delayed Dynamic Bandwidth Channel Access scheme for IEEE 802.11ac WLANs

IEEE 802.11ac standard aims at providing gigabit throughput with users. One of the main features of IEEE 802.11ac standard is the support of wider bandwidths (20/40/80/160 MHz) than those of previous IEEE 802.11n standard (20/40 MHz) on 5 GHz band. Through wider bandwidths, which consists of the primary channel and secondary channels, enormous amount of throughput enhancement can be achieved. The use of these bandwidths causes channel overlap between the primary channel of one AP and the secondary channel of other APs. In order to transmit a data frame in the overlapped channel, transmission rules have been proposed such as dynamic bandwidth channel access scheme. However, this scheme suffers from a performance bottleneck problem. In this paper, we propose delayed dynamic bandwidth channel access scheme with virtual primary channel reservation. This scheme tries to mitigate the performance bottleneck problem as well as a scalability problem. According to our simulation results, delayed dynamic bandwidth channel access scheme achieves at the maximum of 10% higher throughput than dynamic bandwidth channel access scheme.
Symbolic model checking using interval diagram techniques

In this report a representation of multi valued functions called interval decision diagrams IDDs is introduced It is related to similar representations as binary decision diagrams Compared to other model checking strategies IDDs show some important properties that enable us to verify especially Petri nets process net works and related models of computation more adequately than with conventional approaches Therefore a new form of transition relation representation called in terval mapping diagrams IMDs and their less general version predicate action diagrams PADs is explained A novel approach to symbolic model checking of Petri nets and process networks is presented Several drawbacks of traditional strategies are avoided using IDDs and IMDs Especially the resulting transition relation IMD is very compact allowing for fast image computations Furthermore no arti cial limitations concerning place capacities or equivalent have to be introduced Additionally applications concern ing scheduling of process networks are feasible IDDs and IMDs are de ned their properties are described and computation methods and techniques are given
Evaluation of Deceased Kidney Donors for Renal Stone Disease: Is Computed Tomography Needed?

Objective: To investigate the clinical consequences of neglected risk of urolithiasis in deceased kidney donors in routine clinical practice, this study focused on different management options for transplanted allograft stones, and tried to find new solutions for more accurate detection of urolithiasis in deceased kidney donors prior to renal transplantation. Methods and Results: The overall prevalence of stone disease in endemic countries is between 7 and 29%. Because of the increased risk for stone disease in epidemic countries, screening renal grafts from deceased donors necessitates more sensitive imaging tests. Despite well established procedures on preoperative living related renal donor evaluation, there is no consensus on a preoperative imaging tool in cadaveric renal donor evaluation. The most commonly used imaging modality in deceased renal donors is ultrasonography. The overall sensitivity and specificity of ultrasonography for kidney stones are 45 and 88%, respectively. Use of a computed tomography scan for renal diseases, especially for urinary stones is now almost a routine test in clinical practice. Its sensitivity for renal stones < 3 mm is 85%, whereas for renal stones > 3 mm it is 100%. Conclusion: The use of radiological modalities i.e. computed tomography with higher sensitivity in deceased donors prior to renal transplantation seems reasonable in urinary stone epidemic countries.
The significance of siblings on language development in bilingual Spanish-English children

Abstract The purpose of this study was to investigate if there was a relationship between birth order and language proficiency in English and Spanish bilingual children. This study used data from a preexisting dataset. Participants included 49 Spanish-English bilingual children (age 4;6-7;0), who had at least one sibling. Participants were recruited from school districts in Texas, California, and Pennsylvania during the original study. The investigator examined relationships among birth order, number of children, and language measures. Semantic and morphosyntactic language abilities were measured through the participant’s performance on the corresponding subtests of the Bilingual English Spanish Assessment ( BESA ) (Peña, Gutiérrez-Clellen, Iglesias, Goldstein & Bedore, 2014) and through English productivity measures collected from language samples. These measures included: total number of words (TNW), number of different words (NDW), and mean length of utterances in words (MLUw).
Is maize root growth affected by pig slurry application on a tropical acid soil

The effects of field application of liquid pig (Sus scrofa) slurry (PS) on the root system of maize (Zea mays L.) were assessed during two successive cropping seasons in a tropical environment. Root development was monitored on a plot treated with pig slurry, corresponding to a total nitrogen input of 265 kg N ha-1 the first year and 185 kg N ha-1 the second year, in comparison to that recorded in an unfertilized control plot (C plot). In both treatments, the root system was determined at four phenological stages by the trench-profile method and using a model that calculates root length density from counts of numbers of living roots. The results showed that PS had a positive effect on maize aboveground biomass until harvest. Its effect on root development was very positive during the first third of the cycle (+130% for the root length density), but this beneficial impact quickly vanished. At the grain maturation stage, the root length was 18% lower on the PS plot as compared to the C plot, despite the much higher shoot biomass (+50%). It was concluded that one factor began having an adverse effect on root growth in the surface soil layer during the maize growth cycle. This factor was not fully identified, but several elements suggest that it involved soil acidification associated with the nitrification of ammonium nitrogen in PS in this already relatively acid soil. This could lead to a rhizotoxicity problem.
Factors determining the performance of the “right” candidates using Spearman’s RHO

Urban-rural digital divide occur in most parts of the world and this phenomenon is common in various states in Malaysia. The Rural ICT Guided Home-based Technopreneur (RiGHT) is a dedicated initiative established with an ultimate aim that is to bridge the urban-rural digital divide in Sarawak, a state in East Malaysia. It provides comprehensive and highly relevant information and communication technology (ICT) training to equip the candidates from rural Sarawak. Upon graduation, some selected graduates are supported both financially and technically to establish ICT centres in their villages for providing in-situ services to their community. This paper presents the study on how motivation and study strategy influence the performance of the candidates in the RiGHT programme. An adapted questionnaire was prepared based on the Motivated Strategies for Learning Questionnaire (MSLQ) and Students’ Motivation towards Science Learning (SMTSL). A survey was conducted with 19 candidates from RiGHT programme. In RiGHT, the performance of the candidates were measured via two assessments i.e. Assessment 1 contains office suites software while Assessment 2 consists of a broader range of subjects such as designing software, information technology (IT) theory and practical skills. A non-parametric approach was needed as the score was not distributed evenly. Thus, Spearman’s rho was chosen for measurement. From the analysis conducted for Assessment 1, learning value is found to have the highest correlation (r = 0.495) among the motivation factors while peer learning (r = 0.538) has the highest correlation among the study strategy factors. On the other hand, only the extrinsic scale (r = 0.482) along with time management and study environment (r = 0.482) showed high correlation to the performance in Assessment 2. The significant correlation of assessment scores with the combination of motivation and study strategy (r = 0.714), confirms the hypothesis that motivation and study strategy has an impact on the performance of the RiGHT’s candidates throughout the training period. In this study, it was obvious that motivation had more significant impacts on performance, when compared to study strategy. It can be concluded that study strategy varies for everyone and there is no perfect strategy. Some insights from this survey study will be considered as the guideline for the selection of candidates with high potential, in the following intakes.
Modeling attacks on physical unclonable functions

We show in this paper how several proposed Physical Unclonable Functions (PUFs) can be broken by numerical modeling attacks. Given a set of challenge-response pairs (CRPs) of a PUF, our attacks construct a computer algorithm which behaves indistinguishably from the original PUF on almost all CRPs. This algorithm can subsequently impersonate the PUF, and can be cloned and distributed arbitrarily. This breaks the security of essentially all applications and protocols that are based on the respective PUF. The PUFs we attacked successfully include standard Arbited PUFs and Ring Oscillator PUFs of arbitrary sizes, and XO Arbiter PUFs, Lightweight Secure PUFs, and Feed-Forward Arbiter PUFs of up to a given size and complexity. Our attacks are based upon various machine learning techniques including Logistic Regression and Evolution Strategies. Our work leads to new design requirements for secure electrical PUFs, and will be useful to PUF designers and attackers alike.
The CREATE Method for Expressing Continuous Outcome Data in Absolute Terms for Use in Patient Treatment Decision Aids

Background. Patient decision aids (PtDAs) supplement advice from health care professionals by communicating the absolute risk or benefit of treatment options (i.e., X/100). As such, PtDAs have been amenable to binary outcomes only. We aimed to develop and test the validity of the Conversion to Risk Estimates through Application of Normal Theory (CREATE) method for estimating absolute risk based on continuous outcome data. Methods. CREATE is designed to derive an estimate of the proportion of those who experience a clinically relevant degree of change (CRDoC). We used a 2-stage validation process using real and simulated change score data, respectively. First, using raw data from published intervention trials, we calculated the proportion of patients with a CRDoC and compared that with our CREATE-derived estimate using chi-square tests of association. Second, 200,000 simulated distributions of change scores were generated with widely varying distribution characteristics. Actual and CREATE-derived estimates were compared for each simulated distribution, and relative differences were summarized graphically. Results. The absolute difference between the estimated and actual CRDoC did not exceed 5% for any of the samples based on real data. Applying the CREATE method to 200,000 simulated scenarios demonstrated that the CREATE method should be avoided for outcomes where the underlying distribution can be reasonably assumed to have high levels of skew or kurtosis. Conclusion. Our results suggest that standard statistical theory can be used to estimate continuous outcomes in absolute terms with reasonable accuracy for use in PtDAs; caution is advised if outcome summary statistics are assumed to have been derived from highly skewed distributions.
Moderators and mediators of treatment outcome for youth with ADHD: understanding for whom and how interventions work.

OBJECTIVE To present data on moderators and mediators of treatment response from the Multimodal Treatment Study of Children With ADHD (MTA). METHODS Moderator variables (baseline factors that define subgroups with greater vs lesser intervention response) and mediator variables (factors occurring during treatment that explain how interventions "work") are described with specific application to the outcomes of the MTA Study. RESULTS Key moderator variables (comorbid anxiety disorder, public assistance, severity of attention-deficit/hyperactivity disorder, parental depressive symptomatology, IQ) and mediator processes (negative/ineffective parental discipline) are reviewed. CONCLUSIONS Treatment research in the future should explicitly consider the exploration of moderator and mediator variables, which can greatly aid the explanatory power of clinical trials and specify the critical next steps for intervention research.
Fully Dynamic (2 + epsilon) Approximate All-Pairs Shortest Paths with Fast Query and Close to Linear Update Time

For any fixed $1 ≫ \eps ≫ 0$ we present a fully dynamic algorithm for maintaining $(2 + \eps)$-approximate all-pairs shortest paths in undirected graphs with positive edge weights. We use a randomized (Las Vegas) update algorithm (but a deterministic query procedure), so the time given is the \emph{expected} amortized update time. \\\indent Our query time $O(\log \log \log n)$. The update time is $\widetilde{O}(mn^{O(1/\sqrt{\log n})}\log(nR))$, where $R$ is the ratio between the heaviest and the lightest edge weight in the graph (so $R = 1$ in unweighted graphs). Unfortunately, the update time does have the drawback of a super-polynomial dependence on $\eps$: it grows as $(3 / \eps)^{\sqrt{\log n / \log(3/\eps)}} = n^{\sqrt{\log(3/\eps) / \log n}}$. \\\indent Our algorithm has a significantly faster update time than any other algorithm with sub-polynomial query time. For exact distances, the state of the art algorithm has an update time of $\widetilde{O}(n^2)$. For approximate distances, the best previous algorithm has a $O(kmn^{1/k})$ update time and returns $(2k - 1)$ stretch paths. Thus, it needs an update time of $O(m\sqrt{n})$ to get close to our approximation, and it has to return $O(\sqrt{\log n})$ approximate distances to match our update time.
Isolation and high‐dimensional phenotyping of gastrointestinal immune cells

The gastrointestinal immune system plays a pivotal role in the host relationship with food antigens, the homeostatic microbiome and enteric pathogens. Here, we describe how to collect and process liver and intestinal samples to efficiently isolate and analyse resident immune cells. Furthermore, we describe a step‐by‐step methodology showing how to high‐dimensionally immunophenotype resident leucocytes using cytometry by time‐of‐flight, providing a well‐characterized antibody platform that allows the identification of every leucocyte subset simultaneously. This protocol also includes instructions to purify and cultivate primary murine hepatocytes, a powerful tool to assess basic cell biology and toxicology assays. Gut and liver samples from the same mouse can be collected, processed and stained in less than 6 hr. This protocol enables the recovery of several populations of purified and viable immune cells from solid and fibrous organs, preventing unwanted loss of adherent cells during isolation.
GPU-accelerated, gradient-free MI deformable registration for atlas-based MR brain image segmentation

Brain structure segmentation is an important task in many neuroscience and clinical applications. In this paper, we introduce a novel MI-based dense deformable registration method and apply it to the automatic segmentation of detailed brain structures. Together with a multiple atlas fusion strategy, very accurate segmentation results were obtained, as compared with other reported methods in the literature. To make multi-atlas segmentation computationally feasible, we also propose to take advantage of the recent advancements in GPU technology and introduce a GPU-based implementation of the proposed registration method. With GPU acceleration it takes less than 8 minutes to compile a multi-atlas segmentation for each subject even with as many as 17 atlases, which demonstrates that the use of GPUs can greatly facilitate the application of such atlas-based segmentation methods in practice.