Miracle-dz/UniFAR-FTUs huggingface dataset:
From traffic matrix to routing matrix

Traﬃc matrices play a pivotal role in the management of an ISP’s network such as various levels of traﬃc engineering and capacity planning. However, it is unclear how the interaction between the internal traﬃc routing policies chosen by the ISPs and large-scale content providers, and the ongoing trend of “cloud-computing” aﬀect the traﬃc matrices. In this paper, we use network data collected by a Tier-1 ISP to understand the characteristics of a PoP-level traﬃc matrix. We also shed light on the role of “routing matrix” in shaping the characteristics of the traﬃc matrix. Two of the most important observations in this study are: a) multi-exit preﬁxes and use of early-exit routing are the major reasons why PoP level traﬃc for the large ISPs do not follow the gravity model(i.e. proportional distribution based on size) as assumed by previous works, and b) routing plays a fundamental role in shaping the traﬃc matrix.
A Dynamic Priority Based Algorithm for Distributed Deadlock Detection and Resolution

In this paper we develop a distributed algorithm, using probes stamped with dynamic priorities, for detecting deadlocks in the single resource model. The correctness of the algorithm is proven. A dynamic priority is a pair where is a process and is the counter value in when initiates a deadlock detection computation. The pair is called a detector when it is referenced in a process or a resource manager. It is maintained in a process and a resource manager, updated dynamically upon certain events, and used as the priority of a probe in a deadlock detection computation. Introduction of a dynamic priority to the probes, combined with a dynamically updated detector in a process and resource manager, make the algorithm more efficient and less complex to implement than the existing ones. Our algorithm has an space complexity for each process. In certain cases, the algorithm uses messages to detect a deadlock and has an detection delay where is the number of processes and resource managers that are involved in the deadlock.
GENOTYPE DIVERSITY AND SELECTION IN ASEXUAL BRINE SHRIMP (ARTEMIA)

An obligately asexual population of Artemia parthenogenetica at Salin de Giraud, France consists of numerous clones that are genetically and ecologically divergent. The clones are distributed in a nonrandom fashion among eight ponds of highly variable environments. A total of 63 allozymically unique genotypes were identified, with significant differences in numerous fitness traits found among a sample subset of clones. The frequencies of four alleles, as well as the percentage of loci polymorphic, were significantly correlated with salinity. Genotypes face rapid selection along salinity gradients in the field and this selection is reproducible in the lab. mtDNA analysis suggests that obligate asexuality in this population is of monophyletic origin.
Meta‐analysis: effect of hepatitis C virus infection on mortality in dialysis

Background : The natural history of hepatitis C virus infection among patients on long‐term dialysis treatment remains incompletely understood. Efforts to elucidate the natural history of hepatitis C virus in this population are difficult because of the slowly progressive nature of hepatitis C virus with often an unrecognized onset in patients whose life‐expectancy is substantially diminished by end‐stage renal disease.
Analyzing Sentiment of Movie Review Data using Naive Bayes Neural Classifier

Now a days sentiment analysis is active field of research, to extract people's opinion about particular product or service. The most useful application of sentiment analysis is the sentiment classification of product reviews. The task of sentiment classification is to classify reviews of user as positive or negative from textual information alone. For that purpose many researchers used data mining classification techniques such as Naive Bayes classifier with strong independence assumption. But Naive Bayes classifier lack in accuracy for many complex real-world situations where there exists dependency among features. Further, the Neural Network with appropriate network structure is good enough to handle the correlation or dependence between input variables. In proposed system, the Naive Bayes and Neural Network classifier are combined for sentiment classification. In Experimental results, the movie review is classified into positive or negative polarities of sentiment using classifiers. The accuracy of sentiment analysis is increased upto 80.65% by combining Naive Bayes classifier with Neural Network for unigram feature on movie review dataset.
Boundary alignment enables 11-month-olds to segment vowel initial words from speech*

ABSTRACT Past research has indicated that English-learning infants begin segmenting words from speech by 7·5 months of age (Jusczyk & Aslin, 1995). More recent work has demonstrated, however, that 7·5-month-olds' segmentation abilities are severely limited. For example, the ability to segment vowel-initial words from speech reportedly does not appear until 13·5 to 16 months of age (Mattys & Jusczyk, 2001; Nazzi, Dilley, Jusczyk, Shattuck-Hufnagel & Jusczyk, 2005). In this paper, we report on three experiments using the Headturn Preference procedure that investigate both phonetic and phonological factors influencing 11-month-olds' segmentation of vowel-initial words from speech. We replicate earlier findings suggesting that infants have difficulty segmenting vowel-initial words from speech. In addition we extend these findings by demonstrating that under certain conditions, infants are capable of segmenting vowel-initial words from speech at a much younger age than earlier studies have reported. Our findings suggest that infants' ability to segment vowel-initial words from speech is tightly constrained by acoustic-phonetic factors such as pitch movement at the onset of vowel-initial words and segmental strengthening. These experiments underscore the complexity of early word segmentation, and highlight the importance of including contextual factors in developmental models of word segmentation.
Isolation, phenotype, and allostimulatory activity of mouse liver dendritic cells.

Donor liver-derived dendritic cells (DC) have recently been identified within various lymphoid and nonlymphoid tissues of organ allograft recipients, including nonimmunosuppressed mice transplanted with and permanently accepting major histocompatibility complex (MHC)-disparate hepatic allografts. These findings have raised questions about the basis of the tolerogenicity of the liver--and, in particular, about the properties of liver-derived DC. To study further the structure, immunophenotype and allostimulatory activity of leukocytes resident in normal mouse (B10.BR;H-2k, I-Ek) liver, a procedure was developed to maximize the yield of viable, nonparenchymal cells (NPC) obtained following collagenase digestion of perfused liver fragments and density centrifugation (Percoll). These cells comprised populations expressing lymphoid and myeloid cell surface antigens. As compared with spleen cells, they proved good allostimulators of naive (B10; H-2b, I-E-) splenic T cells when tested in primary mixed leukocyte reactions (MLR). After overnight (18-hr) incubation of the NPC, enrichment for transiently adherent, low-density (LD) cells on metrizamide gradients permitted the recovery of low numbers of cells (approx. 2-5 x 10(5) per liver), many of which displayed distinct DC morphology. Flow cytometric analysis revealed that these cells were CD3-, CD4-, CD8-, and B220-, but strongly expressed CD45 (leukocyte-common antigen), and mild-to-moderate levels of CD11b, heat-stable antigen, and CD44. The cells also expressed moderate intensity of NLDC 145 but not 33D1, DC restricted markers which have been shown to be differentially expressed on mouse DC isolated from various organs. This DC-enriched population was more strongly MHC class II(I-Ek)+ than NPC, as determined by immunocytochemistry and flow cytometry and exhibited much more potent allostimulatory activity for naive T cells. These findings demonstrate that freshly isolated murine liver NPC, and perhaps their counterparts in situ, exhibit allostimulatory activity that is enhanced in the non-adherent, low-density (DC-enriched) fraction after overnight culture. They further suggest that the maturation of liver DC may play a key role in determining the immunogenicity and or tolerogenicity of hepatic allografts.
Appropriate Timing of CD40 Ligation for RNA‐Pulsed DCs to Induce Antitumor Immunity

Dendritic cell (DC) based anti‐cancer immunotherapy is believed to be a promising treatment. However, appropriate conditioning including the method of antigen loading and stimulation for DC maturation is still unclear. Total RNA pulsing is one of the most attractive methods to load antigen, since RNA is easily replicated by the PCR technique and is absolutely free of tumor cell contamination. On the other hand, CD40 ligation is capable of producing one of the most potent signals for immature DCs to start functional maturation, which is required to induce adaptive immunity, resulting in altered migration ability to secondary lymphoid organs and augmented antigen presenting activity. Here, we demonstrate that DCs pulsed with total RNA extracted from tumor cells required CD40 stimulation with an appropriate sequence to present tumor‐associated antigens. RNA derived antigens were presented for both CD4+ and CD8+ T cells in an antigen‐specific manner. Dendritic cells that were pulsed with RNA followed by the stimulation through CD40 successfully primed antitumor effector T cells in draining LNs and subsequently induced antitumor protective immunity.
Counterexample-Guided Abstraction Refinement

We present an automatic iterative abstraction-refinement methodology in which the initial abstract model is generated by an automatic analysis of the con- trol structures in the program to be verified. Abstract models may admit erroneous (or "spurious") counterexamples. We devise new symbolic techniques which ana- lyze such counterexamples and refine the abstract model correspondingly. The refinement algorithm keeps the size of the abstract state space small due to the use of abstraction functions which distinguish many degrees of abstraction for each program variable. We describe an implementation of our methodology in NuSMV. Practical experiments including a large Fujitsu IP core design with ab- out 500 latches and 10000 lines of SMV code confirm the effectiveness of our approach.
Non-Sentential Utterances in Dialogue: Experiments in Classification and Interpretation

Non-sentential utterances (NSUs) are utterances that lack a complete sentential form but whose meaning can be inferred from the dialogue context, such as "OK", "where? ", "probably at his apartment". The interpretation of non-sentential utterances is an important problem in computational linguistics since they constitute a frequent phenomena in dialogue and they are intrinsically context-dependent. The interpretation of NSUs is the task of retrieving their full semantic content from their form and the dialogue context. The first half of this thesis is devoted to the NSU classification task. Our work builds upon Fern\'andez et al. (2007) which present a series of machine-learning experiments on the classification of NSUs. We extended their approach with a combination of new features and semi-supervised learning techniques. The empirical results presented in this thesis show a modest but significant improvement over the state-of-the-art classification performance. The consecutive, yet independent, problem is how to infer an appropriate semantic representation of such NSUs on the basis of the dialogue context. Fern\'andez (2006) formalizes this task in terms of "resolution rules" built on top of the Type Theory with Records (TTR). Our work is focused on the reimplementation of the resolution rules from Fern\'andez (2006) with a probabilistic account of the dialogue state. The probabilistic rules formalism Lison (2014) is particularly suited for this task because, similarly to the framework developed by Ginzburg (2012) and Fern\'andez (2006), it involves the specification of update rules on the variables of the dialogue state to capture the dynamics of the conversation. However, the probabilistic rules can also encode probabilistic knowledge, thereby providing a principled account of ambiguities in the NSU resolution process.
On the Existence of Answer Sets in Normal Extended Logic Programs

One of the serious problems in answer set programming is that relatively small pieces of information can cause a total absence of answer sets. To cope with this problem, this paper introduces a class of normal extended logic programs which are extended logic programs, whose defeasible rules are comparable to normal defaults in default logic. Under suitable program transformations, we show that every normal extended logic program always yields at least one answer set.
Speaking the Unspeakable: Marital Violence among South Asian Immigrants in the United States

Over the past 20 years, much work has focused on domestic violence, yet little attention has been paid to the causes, manifestations, and resolutions to marital violence among ethnic minorities, especially recent immigrants. Margaret Abraham's Speaking the Unspeakable is the first book to focus on South Asian women's experiences of domestic violence, defined by the author as physical, sexual, verbal, mental, or economic coercion, power, or control perpetrated on a woman by her spouse or extended kin. Abraham explains how immigration issues, cultural assumptions, and unfamiliarity with the American social, legal, and economic systems, coupled with stereotyping, make these women especially vulnerable to domestic violence. Through the actual stories of South Asian women, we learn of their weaknesses and strengths and their encounters of domestic violence within the larger cultural, social, economic, and political context. We see both the individual strategies of resistance against their abusers as well as the pivotal role South Asian women's help organizations play in helping these women escape abusive relationships. Abraham also describes the central role played by South Asian activism as it emerged in the 1980s in the United States, and addresses the practices both within and outside of the South Asian community that stereotype, discriminate, and oppress South Asians in their everyday lives.
Structural and Functional Insights of RANKL–RANK Interaction and Signaling

Bone remodeling involves bone resorption by osteoclasts and synthesis by osteoblasts and is tightly regulated by the receptor activator of the NF-κB ligand (RANKL)/receptor activator of the NF-κB (RANK)/osteoprotegerin molecular triad. RANKL, a member of the TNF superfamily, induces osteoclast differentiation, activation and survival upon interaction with its receptor RANK. The decoy receptor osteoprotegerin inhibits osteoclast formation by binding to RANKL. Imbalance in this molecular triad can result in diseases, including osteoporosis and rheumatoid arthritis. In this study, we report the crystal structures of unliganded RANK and its complex with RANKL and elucidation of critical residues for the function of the receptor pair. RANK represents the longest TNFR with four full cysteine-rich domains (CRDs) in which the CRD4 is stabilized by a sodium ion and a rigid linkage with CRD3. On association, RANK moves via a hinge region between the CRD2 and CRD3 to make close contact with RANKL; a significant structural change previously unseen in the engagement of TNFR superfamily 1A with its ligand. The high-affinity interaction between RANK and RANKL, maintained by continuous contact between the pair rather than the patched interaction commonly observed, is necessary for the function because a slightly reduced affinity induced by mutation produces significant disruption of osteoclast formation. The structures of RANK and RANKL–RANK complex and the biological data presented in the paper are essential for not only our understanding of the specific nature of the signaling mechanism and of disease-related mutations found in patients but also structure based drug design.
Determination of Shear-w Surface ( Rayleigh ) Seismic

UMR will acquire multi-channel surface-wave (Rayleigh wave) seismic data in the vicinity of the Wahite Ditch Bridge and St. Francis River Bridge test sites. These Rayleigh wave data will be processed and analyzed, and used to construct subsurface shear-wave velocity profiles to depths on the order of 100 feet. These Rayleigh wave data will be compared to borehole seismic and seismic CPT data previously acquired at the test sites. The objective is to determine if the multi-channel surface-wave seismic tool is a cost-effective and accurate means of determining shear-wave velocity profiles for the shallow subsurface. Researchers from the University of Missouri-Rolla (UMR) and their scientific research colleagues from the Mining Institute in Perm (MIP), Russia, acquired multi-channel surface-wave (Rayleigh wave) seismic control at six separate bridge sites in southeast Missouri. Each acquired surface wave data set was processed (spectral analysis of surface waves; SASW) and transformed into a site-specific vertical shear-wave velocity profile (SASW shear-wave velocity profile). Each SASW shear-wave velocity profile extends from the surface to a depth on the order of 60 m. The SASW shear-wave velocity profiles generated for each bridge site were compared to other geotechnical data (provided by the Missouri Department of Transportation; MoDOT), including seismic cone penetrometer test shear-wave velocity profiles (SCPT shear-wave velocity profiles), cross-borehole shear-wave velocity profiles (CH shear-wave velocity profiles), and borehole lithology logs. The primary objective of this study was to determine how well SASW shear-wave velocity profiles compare to more standard geotechnical data. The geotechnical data presented herein indicate the SASW shear-wave velocity profiles correlate as well with subsurface lithology logs and available cross-borehole shear-wave velocity control. More specifically, clays, silts and sands exhibit relatively characteristic SASW-velocities, which increase almost monotonically (step-wise and incrementally) with increasing depth of burial. We believe these correlations demonstrate that SASW shear-wave velocities are reliable. The data presented herein indicate the SCPT shear-wave profiles do not appear to correlate well with available borehole lithologic control, available cross-borehole shear-wave velocity profiles, or the generated SASW shear-wave velocity profiles. SCPT shear-wave interval velocities often vary significantly over short vertical distances within essentially uniform lithogic units. Additionally, SCPT shear-wave velocities for essentially the same lithologic units differ significantly at proximal test sites. In our opinion, the SCPT shear-wave interval velocity data (as provided by MoDOT) cannot be used to assess the reliability/reasonableness of the SASW shear-wave velocity profiles. On the basis of this study, we conclude that …
Biodiversity and Climate Change: Consequences for Norway Spruce Mountain Forests in Slovakia

Study of the effects of climate change on Norway Spruce (Picea abies) forests has mainly focused on the diversity of tree species diversity of tree species as a result of the ability of species to tolerate temperature and moisture changes as well as some effects of disturbance regime changes. The tree species’ diversity changes in spruce forests due to climate change have been analyzed via gap model. Forest gap model is a dynamic model for calculation basic characteristics of individual forest trees. Input ecological data for model calculations have been taken from the permanent research plots located in primeval forests in mountainous regions in Slovakia. The results of regional scenarios of the climatic change for the territory of Slovakia have been used, from which the values are according to the CGCM3.1 (global) model, KNMI and MPI (regional) models. Model results for conditions of the climate change scenarios suggest a shift of the upper forest limit to the region of the present subalpine zone, in supramontane zone. N. spruce representation will decrease at the expense of beech and precious broadleaved species (Acer sp., Sorbus sp., Fraxinus sp.). The most significant tree species diversity changes have been identified for the upper tree line and current belt of dwarf pine (Pinus mugo) occurrence. The results have been also discussed in relation to most important disturbances (wind storms, snow and ice storms) and phenological changes which consequences are little known. Special discussion is focused on biomass production changes in relation to carbon storage diversity in different carbon pools. Keywords—Biodiversity, climate change, Norway spruce forests, gap model.
Interference-aware power coordination game for ISM bands

The use of wireless equipment in the already-overcrowded ISM bands had been further growing in recent years. This increase leads to high interference levels, which causes unstable communication and an average throughput reduction in heavily-used channels. This calls for more robust, interference-aware means of channel-access for Wi-Fi and similar wireless devices in ISM bands. In this paper, we propose a Game Theory (GT) based power allocation mechanism for IEEE 802.11 networks, which might incorporate some aspects of Cognitive Radio (CR) functionality. Up to now operation of 802.11 devices was constrained by regulations in terms of maximum transmission power, in order to limit the extent of interference from uncoordinated emissions. Our proposed mechanism, with its feasibility backed by the practical experimentation reported in this paper, would allow embracing lighter regulatory rules or complete abolition of power limits for unlicensed access in ISM bands. Moreover, our proposed concept of channel access based on power balancing game might also make unnecessary the use of CSMA/CA protocol.
A software framework for efficient system-level performance evaluation of embedded systems

The Sesame environment provides modeling and simulation methods and tools for the efficient design space exploration of heterogeneous embedded multimedia systems. In this paper we describe the Sesame software system and demonstrate its capabilities using several examples. We show that Sesame significantly reduces model construction time through the use of modeling component libraries, hierarchy, and advanced model structure description features.
The incremental funding method: data-driven software development

Software development projects don't get funded unless they return clearly defined value to the business. Demands for shorter investment periods, faster time-to-market, and increased agility require new, radical software development approaches. These approaches must draw on the expertise of both software architects and financial stakeholders and open the traditional black box of software development to rigorous financial analysis. We can accomplish this only by positioning software development as a value-creation activity in which business analysis is integral. The incremental funding method is a financially informed approach to software development. IFM maximizes returns by delivering functionality in "chunks" of customer-valued features, carefully sequenced to optimize the project's net present value (NPV). We derived the IFM concepts from several years' experience in winning competitive contracts for large-systems integration and application development projects.