Miracle-dz/UniFAR-FTUs huggingface dataset:
P 3 ON : Proximity-based Peer-to-Peer Overlay Networks

Peer-to-peer(P2P) overlay networks provide robust, scalable file sharing services. The hop distance between two virtual nodes in P2P overlay networks is irrelevant to the real distance between two nodes. Therefore, many lookup operations may be executed, without considering the real distance, even though a node wants to find a file object located in another node within the same subnet. To overcome this drawback, we propose a proximity-based peer-to-peer overlay networks (P3ON). In P3ON, the proximity between two nodes is exploited to achieve a fast lookup operation. In other words, two nodes within the same subnet are mapped to the adjacent overlay nodes, so that the lookup time between them can be reduced significantly. In addition, two phase lookup algorithm and caching scheme are suggested to maximize the locality in P3ON. In our future work, we will extend P3ON to support large-scale P2P services as well as hierarchical mobile P2P services.
The Size of Projections of Relations Satisfying a Functional Dependency

In this paper we consider tabulated data or relations in a data base __I__-_ system which are constrained by functional dependencies. This implies that the data in certain columns of each table is determined by the data contained in some other columns. The problem we address is that of the computation of the size of projections of the data on a subset of the columns. This may be viewed as the projection of data in some k dimensional space into a smaller subspace. We thus extend results we had previously obtained 1 [I for relations without functional dependencies to the case with functional dependencies.
Saliency Detection via Absorbing Markov Chain With Learnt Transition Probability

In this paper, we propose a bottom–up saliency model based on absorbing Markov chain (AMC). First, a sparsely connected graph is constructed to capture the local context information of each node. All image boundary nodes and other nodes are, respectively, treated as the absorbing nodes and transient nodes in the absorbing Markov chain. Then, the expected number of times from each transient node to all other transient nodes can be used to represent the saliency value of this node. The absorbed time depends on the weights on the path and their spatial coordinates, which are completely encoded in the transition probability matrix. Considering the importance of this matrix, we adopt different hierarchies of deep features extracted from fully convolutional networks and learn a transition probability matrix, which is called learnt transition probability matrix. Although the performance is significantly promoted, salient objects are not uniformly highlighted very well. To solve this problem, an angular embedding technique is investigated to refine the saliency results. Based on pairwise local orderings, which are produced by the saliency maps of AMC and boundary maps, we rearrange the global orderings (saliency value) of all nodes. Extensive experiments demonstrate that the proposed algorithm outperforms the state-of-the-art methods on six publicly available benchmark data sets.
Patterns of justice system involvement among child welfare-involved youth

Using empirical data to examine the nature and extent of justice system involvement among groups of young people with placement experiences in the child welfare system can help streamline policies to better target those most at-risk for juvenile detention and jail. However,research has yet to fully address the unique groups within this population utilizing juvenile and criminal justice system measures. Thus, I use trajectory analysis to examine differences in justice system involvement and child welfare placements as related to demographics, child welfare experiences, and other systems involvement. Data come from a larger study on child welfare children and youth in a birth cohort in Allegheny County, Pennsylvania; the sample for this study focused on one child per family with at least one year in out of home child welfare placement (N = 794). I performed semiparametric group-based polynomial logistic regression trajectory analysis to determine distinct trajectory groups within the larger sample on juvenile and criminal justice system measures, as well as for three main child welfare placement types. I conducted multinomial logistic regression to examine predictors that differentiated justice system group membership. I performed crosstabulations of the trajectory groups to show detail of the relationship between justice system trajectories and placement trajectories. Results indicated that a five-group model fit the best conceptually and statistically for justice systems, foster homes, and group homes, and a four-group model fit best for regular residential placements. Child welfare youth have high percentages of involvement in multiple systems, and heterogeneity of justice system involvement exists among child welfare youth. Although most have no to low justice system involvement, others have substantial involvement grouped on similar experiences. Congregate care placement was only a significant predictor for the chronic justice system group. This research has important findings that can guide our interventions for youth, particularly in the areas of screening and assessment. A quantitative screening tool could be an efficient way of identifying young people most at risk for justice system involvement, while a qualitative assessment could include in-depth questions acknowledging that child welfare and other system experiences matter for justice system involvement.
Preclinical Evaluation of the Novel, Orally Bioavailable Selective Inhibitor of Nuclear Export (SINE) KPT-335 in Spontaneous Canine Cancer: Results of a Phase I Study

Background The purpose of this study was to evaluate the activity of Selective Inhibitors of Nuclear Export (SINE) compounds that inhibit the function of the nuclear export protein Exportin 1 (XPO1/CRM1) against canine tumor cell lines and perform a Phase I clinical trial of KPT-335 in dogs with spontaneous cancer to provide a preliminary assessment of biologic activity and tolerability. Methods and Findings Canine tumor cell lines derived from non-Hodgkin lymphoma (NHL), mast cell tumor, melanoma and osteosarcoma exhibited growth inhibition and apoptosis in response to nanomolar concentrations of SINE compounds; NHL cells were particularly sensitive with IC50 concentrations ranging from 2–42 nM. A Phase I clinical trial of KPT-335 was performed in 17 dogs with NHL (naive or relapsed), mast cell tumor or osteosarcoma. The maximum tolerated dose was 1.75 mg/kg given orally twice/week (Monday/Thursday) although biologic activity was observed at 1 mg/kg. Clinical benefit (CB) including partial response to therapy (PR, n = 2) and stable disease (SD, n = 7) was observed in 9/14 dogs with NHL with a median time to progression (TTP) for responders of 66 days (range 35–256 days). A dose expansion study was performed in 6 dogs with NHL given 1.5 mg/kg KPT-335 Monday/Wednesday/Friday; CB was observed in 4/6 dogs with a median TTP for responders of 83 days (range 35–354 days). Toxicities were primarily gastrointestinal consisting of anorexia, weight loss, vomiting and diarrhea and were manageable with supportive care, dose modulation and administration of low dose prednisone; hepatotoxicity, anorexia and weight loss were the dose limiting toxicities. Conclusions This study provides evidence that the novel orally bioavailable XPO1 inhibitor KPT-335 is safe and exhibits activity in a relevant, spontaneous large animal model of cancer. Data from this study provides critical new information that lays the groundwork for evaluation of SINE compounds in human cancer.
Clinical use of vaginal or rectally applied microbicides in patients suffering from HIV/AIDS

Microbicides, primarily used as topical pre-exposure prophylaxis, have been proposed to prevent sexual transmission of HIV. This review covers the trends and challenges in the development of safe and effective microbicides to prevent sexual transmission of HIV Initial phases of microbicide development used such surfactants as nonoxynol-9 (N-9), C13G, and sodium lauryl sulfate, aiming to inactivate the virus. Clinical trials of microbicides based on N-9 and C31G failed to inhibit sexual transmission of HIV. On the contrary, N-9 enhanced susceptibility to sexual transmission of HIV-1. Subsequently, microbicides based on polyanions and a variety of other compounds that inhibit the binding, fusion, or entry of virus to the host cells were evaluated for their efficacy in different clinical setups. Most of these trials failed to show either safety or efficacy for prevention of HIV transmission. The next phase of microbicide development involved antiretroviral drugs. Microbicide in the form of 1% tenofovir vaginal gel when tested in a Phase IIb trial (CAPRISA 004) in a coitally dependent manner revealed that tenofovir gel users were 39% less likely to become HIV-infected compared to placebo control. However, in another trial (VOICE MTN 003), tenofovir gel used once daily in a coitally independent mode failed to show any efficacy to prevent HIV infection. Tenofovir gel is currently in a Phase III safety and efficacy trial in South Africa (FACTS 001) employing a coitally dependent dosing regimen. Further, long-acting microbicide-delivery systems (vaginal ring) for slow release of such antiretroviral drugs as dapivirine are also undergoing clinical trials. Discovering new markers as correlates of protective efficacy, novel long-acting delivery systems with improved adherence in the use of microbicides, discovering new compounds effective against a broad spectrum of HIV strains, developing multipurpose technologies incorporating additional features of efficacy against other sexually transmitted infections, and contraception will help in moving the field of microbicide development forward.
There Is No Free Phish: An Analysis of "Free" and Live Phishing Kits

Phishing is a form of identity theft in which an attacker attempts to elicit confidential information from unsuspecting victims. While in the past there has been significant work on defending from phishing, much less is known about the tools and techniques used by attackers, i.e., phishers. Of particular importance to understanding the phishers' methods and motivations are phishing kits, packages that contain complete phishing web sites in an easy-to-deploy format. In this paper, we study in detail the kits distributed for free in underground circles and those obtained by crawling live phishing sites. We notice that phishing kits often contain backdoors that send the entered information to third parties. We conclude that phishing kits target two classes of victims: the gullible users from whom they extort valuable information and the unexperienced phishers who deploy them.
A Study in Scarlet

'There's a scarlet thread of murder running through the colourless skein of life, and our duty is to unravel it, and isolate it, and expose every inch of it'. From the moment Dr John Watson takes lodgings in Baker Street with the consulting detective Sherlock Holmes, he becomes intimately acquainted with the bloody violence and frightening ingenuity of the criminal mind. In "A Study in Scarlet", Holmes and Watson's first mystery, the pair are summoned to a south London house where they find a dead man whose contorted face is a twisted mask of horror. The body is unmarked by violence but on the wall a mysterious word has been written in blood. The police are baffled by the crime and its circumstances. But when Sherlock Holmes applies his brilliantly logical mind to the problem he uncovers a tragic tale of love and deadly revenge.
Miocene to present kinematics of fault-bend folding across the Huerguosi anticline, northern Tianshan (China), derived from structural, seismic, and magnetostratigraphic data

We combine surface structural measurements, subsurface seismic imaging, and magnetostratigraphic dating to retrieve, through geometric modeling, the detailed history of fold growth and sedimentation across the Huerguosi anticline, on the northern Tianshan piedmont, taking advantage of a beautifully exposed section of growth strata. The model assumes a fault-bend folding mechanism, consistent with subsurface fold geometry. The shortening history is obtained by least-squares fi tting of the measured dip angles of the growth strata. The shortening rate across the anticline is shown to have been remarkably constant: it increased only slightly from 0.84 ± 0.04 mm/yr between 10 and 4 Ma to 1.14 ± 0.02 mm/yr over the past 4 m.y. This approach also allows correcting syntectonic sedimentation rates for the effect of the fold growth and shows that the sedimentation rates in the piggyback basin increased abruptly from ~0.4 to ~0.7 mm/yr ca. 4 Ma.
Attentive Path Combination for Knowledge Graph Completion

Knowledge graphs (KGs) are often signiﬁcantly incomplete, necessitating a demand for KG completion. Path-based relation inference is one of the most important approaches to this task. Traditional methods treat each path between entity pairs as an atomic feature, thus inducing sparsity. Recently, neural network models solve this problem by decomposing a path as the sequence of relations in the path, before modelling path representations with Recurrent Neural Network (RNN) architectures. In cases there are multiple paths between an entity pair, state-of-the-art neural models either select only one path, or make usage of simple score pooling methods like Top-K, Average, LogSumExp. Unfortunately, none of these methods can model the scenario where relations can only be inferred by considering multiple informative paths collectively. In this paper, we propose a novel path-based relation inference model that learns entity pair representations with attentive path combination. Given an entity pair and a set of paths connecting the pair, our model allows for integrating information from each informative path, and form a dynamic entity pair representation for each query relation. We empirically evaluate the proposed method on a real-world dataset. Experimental results show that the proposed model achieves better performance than state-of-the-art path-based relation inference methods.
A Caenorhabditis elegans MAP kinase kinase, MEK‐1, is involved in stress responses

The c‐Jun N‐terminal kinase (JNK), a member of the mitogen‐activated protein kinase (MAPK) family, was shown to be involved in the response to various stresses in cultured cells. However, there is little in vivo evidence indicating a role for a JNK pathway in the stress response of an organism. We identified the Caenorhabditis elegans mek‐1 gene, which encodes a 347 amino acid protein highly homologous to mammalian MKK7, an activator of JNK. Mek‐1 reporter fusion proteins are expressed in pharyngeal muscle, uterus, a portion of intestine, and neurons. A mek‐1 deletion mutant is hypersensitive to copper and cadmium ions and to starvation. A wild‐type mek‐1 transgene rescued the hypersensitivity to the metal ions. Double mutants of mek‐1 with an eat‐5, eat‐11 or eat‐18 mutation, which are characterized by a limited feeding defect, showed distinct growth defects under normal conditions. Expression of an activated form of MEK‐1 in the whole animal or specifically in the pharynx inhibited pharyngeal pumping. These results suggest a role for mek‐1 in stress responses, with a focus in the pharynx and/or intestine.
Business orientation in knowledge security risk management – a literature review

This paper examines the information systems literature field from the viewpoint of knowledge security risk management. The review this paper reports was able to identify 7 papers presenting a knowledge security risk management model. The models represent different takes and perspectives on knowledge security risk management. The main finding is that business orientation in the risk management models, and a comprehensive approach that would emphasize also continuous monitoring of the implementation and success of the risk mitigation solutions are not common in the literature. We suggest further theoretical and empirical studies that would address these issues.
The regional distribution of hydroxylase cofactor in rat brain

TETRAHYDROBIOPTERIN (BH,) is thought to be the natural (in ciuo) cofactor for both tyrosine hydroxylase and tryptophan hydroxylase (KAUFMAN, 1974), the initial and rate limiting enzymes in the biosynthesis of the katecholamines (UDENFRIEND, 1966) and serotonin (JEQUIER et al., 1967), respectively. It has been suggested that the concentration of BH, in tissue may play a regulatory role in determining the rates of hydroxylase enzyme activity (KAUFMAN, 1973; LOVENBERG & VICTOR, 1974; LOVENBERG & KUHN, 1978). However, only recently have attempts been made to quantify BH, in brain and to correlate the distribution of BH, with the activity of these hydroxylase enzymes (GAL et al., 1976; BULLARD et al., 1978). The results of this communication confirm the presence of high concentrations of hydroxylase cofactor (presumably BH4) in brain areas known to contain large amounts of tyrosine (striatum) and tryptophan (mesencephalic tegmentum) hydroxylase activity. In addition, our results demonstrate the existence of large quantities of hydroxylase cofactor in other areas known to be involved in neuroendocrine function, but having relatively little hydroxylase activity.
Visual Analysis of Multi‐Dimensional Categorical Data Sets

We present a set of interactive techniques for the visual analysis of multi‐dimensional categorical data. Our approach is based on multiple correspondence analysis (MCA), which allows one to analyse relationships, patterns, trends and outliers among dependent categorical variables. We use MCA as a dimensionality reduction technique to project both observations and their attributes in the same 2D space. We use a treeview to show attributes and their domains, a histogram of their representativity in the data set and as a compact overview of attribute‐related facts. A second view shows both attributes and observations. We use a Voronoi diagram whose cells can be interactively merged to discover salient attributes, cluster values and bin categories. Bar chart legends help assigning meaning to the 2D view axes and 2D point clusters. We illustrate our techniques with real‐world application data.
Developing Role-Based Open Multi-Agent Software Systems

An open multi-agent system (MAS) is a dynamic system in which agents can not only join or leave an agent society at will, but also take or release roles at runtime. Traditional multi-agent system development methodologies are not suitable for developing open multi-agent systems because they assume a fixed number of agents that are specified during the system analysis phase. In this paper, we propose a formal role-based modeling framework for open multi-agent software systems. We specify role organizations and role spaces as containers of conceptual roles and role instances, respectively, where role instances can be dynamically taken or released by agents from agent societies. To support rapid development of role-based open multi-agent systems, we introduce a three-layered design model of open MAS, and developed a prototype Role-based Agent Development Environment (RADE). Finally, we present a case study to demonstrate how an open MAS application can be efficiently built on RADE.
High-speed, low-power optical modulators in silicon

Silicon modulators are maturing and it is anticipated that they are going to substitute state-of-the art modulators. We review current silicon modulator approaches and then discuss the silicon-organic hybrid (SOH) approach in more detail. The SOH approach has recently enabled the operation with an energy consumption of 60 fJ/bit and demonstrated the generation of up to 112 Gbit/s per polarization in a compact silicon modulator of 1.5 mm length.
Dominance and valence : A two-factor model for emotion in HCI

Emotions play an important role in human-computer interaction (HCI). Central to the design of some future computer systems are the questions of how emotions can be specified, expressed, and accounted for by machines. Drawing on social psychology research, a two-factor model for emotion in HCI is proposed. This model was tested with a laboratory study of emotions in HCI. A project is currently underway to build a system that demonstrates how this model can inform the design of computer interfaces.
On the Potential of Handover Parameter Optimization for Self-Organizing Networks

Self-organizing networks (SONs) aim to raise the level of automated operation in next-generation networks. One of the use cases defined in this field is the optimization of the handover (HO) process, which involves a tradeoff between the amount of signaling load due to HOs and the quality of the active connections in the network. In this paper, first, a sensitivity analysis of the two main HO parameters, i.e., the HO margin (HOM) and the time-to-trigger (TTT), is carried out for different system load levels and user speeds in a Long-Term Evolution (LTE) network. Second, a fuzzy logic controller (FLC) that adaptively modifies HOMs is designed for HO optimization. In this case, different parameter optimization levels (network-wide, cell-wide, and cell-pair-wide) and the impact of measurement errors have been considered. Results of the sensitivity analysis show that tuning HOMs is an effective solution for HO optimization in LTE networks. In addition, the FLC is shown as an effective technique to adapt HOM to different network conditions so that the signaling load in the network is decreased while an admissible level of call dropping is achieved.
Modeling and exploiting query interactions in database systems

The typical workload in a database system consists of a mixture of multiple queries of different types, running concurrently and interacting with each other. Hence, optimizing performance requires reasoning about query mixes and their interactions, rather than considering individual queries or query types. In this paper, we show the significant impact that query interactions can have on workload performance. We present a new approach based on planning experiments and statistical modeling to capture the impact of query interactions. This approach requires no prior assumptions about the internal workings of the database system or the nature or cause of query interactions, making it portable across systems. As a concrete demonstration of the potential of capturing, modeling, and exploiting query interactions, we develop a novel interaction-aware query scheduler that targets report-generation workloads in Business Intelligence (BI) settings. Under certain assumptions, the schedule found by this scheduler is within a constant factor of optimal. An experimental evaluation with TPC-H queries on IBM DB2 demonstrates that our scheduler consistently outperforms (up to 4x) conventional schedulers that do not account for query interactions.