Miracle-dz/UniFAR-FTUs huggingface dataset:
An aspect-oriented approach to face neighbour saturation issues in proactive ad hoc routing protocols: olsrd as a case study

Ad hoc networking is gaining momentum in contexts of use requiring the rapid, and low cost, deployment of communication networks. However, many studies show that ad hoc routing protocols are threatened by a variety of accidental and malicious faults that limit their use in practice. This paper explores the feasibility of using Aspect-Oriented Programming (AOP) to develop reusable mechanisms to mitigate the negative effects of a high density of neighbour nodes on the dependability of olsrd, an implementation of the Optimised Link-State Routing protocol (OLSR), one of the most widely-used ad hoc routing protocol implementations existing today. On one hand, aspect orientation has the potential to promote a clear separation between existing functional (protocol-related) capabilities and the non-functional (fault tolerance-related) features of the system. On the other hand, this approach eases the adaptation of fault tolerance mechanisms to evolutions the protocol implementations may suffer along the time.
Complete Solution of the Eight-Puzzle and the Benefit of Node Ordering in IDA

The 8-puzzle is the largest puzzle of its type that can be completely solved. It is simple, and yet obeys a combinatorially large problem space of 91/2 states. The N × N extension of the 8-puzzle is NP-hard. In the first part of this paper, we present complete statistical data based on an exhaustive evaluation of all possible tile configurations. Our results include data on the expected solution lengths, the 'easiest' and 'worst' configurations, and the density and distribution of solution nodes in the search tree. In our second set of experiments, we used the 8-puzzle as a workbench model to evaluate the benefit of node ordering schemes in Iterative-Deepening A* (IDA*). One highlight of our results is that almost all IDA* implementations perform worse than would be possible with a simple random ordering of the operators.
Examination of Setarud (IMOD™) in the management of patients with severe sepsis

Background and the purpose of the study Analysis of current immunomodulating strategies indicates that monovalent approaches are unlikely to restore immunostasis or achieve complete therapy of sepsis. Setarud (IMOD) as a mixture of urtica, carotenoids, urea, and selenium has been recently patented for its potential in reduction of Tumor Necrosis Factor alpha (TNF-α) and Interferon-γ and Interleukin-2 levels. The aim of this study was to examine efficacy of IMOD in the management of patients with severe sepsis. Methods Twenty patients with severe sepsis and acute physiology and chronic health evaluation (APACHE) score of more than 20 were randomized to receive standard treatment of severe sepsis (control group) or standard treatment plus IMOD (IMOD group). The group treated with IMOD for 14 days was according to the pilot study and regarding the stability of patient's conditions in the ICU. Of course patients in both groups received standard treatment and all were monitored for 28 days. Blood samples were analyzed for interleukins (IL-1, IL-2, IL-6), plasminogen activator inhibitor (PAI-1), TNF-α, total thiol molecules (TTM), nitric oxide (NO), total antioxidant power (TAP), and lipid peroxidation (LPO). Daily APACHE, Sequential Organ Failure Assessment (SOFA), and Simplified Acute Physiology Score (SAPS) were calculated. Results and major conclusion Comparing with controls, IMOD was significantly effective in improving SAPS, SOFA, and APACHE scores, and reduction of mortality rate. Among tested inflammatory biomarkers, IMOD significantly improved TTM and TNF-α values. It is concluded that IMOD might be added as a safe adjutant to standard treatment of severe sepsis.
Twitter mining for traffic events detection

Nowadays with the proliferation of smartphones and tablets on the market, almost everyone has access to mobile devices that offer better processing capabilities and access to new information and services. The Web is undoubtedly the best tool for sharing content, especially through social networks. One of the most useful information that can be extracted is the geographical one. Current navigation systems lack in several ways to satisfy the need to process and reason upon such volumes of data, namely, to accurately provide information about urban traffic in real-time and the possibility to personalize the information used by such systems. This paper describes an approach to integrate and fuse tweet messages from traffic agencies in UK, with the objective of detecting the geographical focus of traffic events. Tweet messages are considered in this work given its uniqueness, the real time nature of tweets which may be used to quickly detect a traffic event and its simplicity; it only cost 140 characters to generate a message (called “tweet”) for any user. The approach presented here is composed by several steps: tweet classification, event type classification, name entity recognition, geolocation and event tracking. Finally, we do an experimental study on a real dataset composed by traffic related tweet messages to access the accuracy of proposed approach. We present some inaccuracies ranging from lack of geographical information, imprecise and ambiguous toponyms, overlaps and repetitions as well as visualization to our data set in UK. We finally give an outlook into potential corrections. The work presented here is still part of on-going work. Results achieved so far do not address the final conclusions but form the basis for the formalization of a domain knowledge along with the services.
Urban Mines of Copper: Size and Potential for Recycling in the EU

Copper is among the most important metals by production volume and variety of applications, providing essential materials and goods for human wellbeing. Compared to other world regions, Europe has modest natural reserves of copper and is highly dependent on imports to meet the domestic demand. Securing access to raw materials is of strategic relevance for Europe and the recycling of urban mines (also named “in-use stock”) is a significant mean to provide forms of secondary copper to the European industry. A dynamic material flow analysis model is applied to characterize the flows of copper in the European Union (EU-28) from 1960 to 2014 and to determine the accumulation of this metal in the in-use stock. A scrap balance approach is applied to reconcile the flow of secondary copper sent to domestic recycling estimated through the model and that reported by historic statistics. The results show that per capita in-use stock amounts at 160–200 kg/person, and that current end-of-life recycling rate is around 60%. The quantification of historic flows provides a measure of how the European copper cycle has changed over time and how it may evolve in the future: major hindrances to recycling are highlighted and perspectives for improving the current practices at end-of-life are discussed.
Communication processes in virtual cooperative environments

Gregorio Jiménez Valverde es profesor del IES «Mercè Rodoreda» de Hospitalet (Barcelona) (gjimene2@xtec.net) y Anna Llitjós Viza es miembro del Grupo ECEM del Departamento de Didáctica de Experimentales y Matemática de la Universidad de Barcelona (anna.llitjos@ub.edu). En la actualidad, muchos pedagogos, especialmente en el área de la tecnología educativa, abogan por un cambio de enfoque y pasar de la instrucción centrada en el docente, a la instrucción centrada en el estudiante (Hannafin y Land, 1997; Harasim, 1990). La pedagogía centrada en el estudiante se pregunta qué necesitan aprender los estudiantes, cuáles son sus preferencias de aprendizaje y qué es significativo para ellos, más allá de lo que es considerado como conocimiento básico en una disciplina dada o de lo que quiera enseñar el docente. En este sentido, la instrucción basada en la web proporciona una oportuniGregorio Jiménez y Anna Llitjós Barcelona
An approach for Intrusion Detection using Text Mining Techniques

The problem of clustering is NP-Complete. The existing clustering algorithm in literature is the approximate algorithms, which cluster the underlying data differently for different datasets. The K-Means Clustering algorithm is suitable for frequency but not for binary form. When an application runs several system calls are implicitly invoked in the background. Based on these system calls we can predict the normal or abnormal behavior of applications. This can be done by classification. In this paper we tried to perform classification of processes running into normal and abnormal states by using system call behavior. We reduce the system call feature vector by choosing k-means algorithm which uses the proposed measure for dimensionality reduction. We give the design of the proposed measure. The proposed measure has upper and lower bounds which are finite.
Strong asymptotics of orthogonal polynomials with respect to exponential weights

We consider asymptotics of orthogonal polynomials with respect to weights w(x)dx= e Q(x) dx on the real line, where Q(x)=∑ 2m k=0 qkx k , q2m> 0, denotes a polynomial of even order with positive leading coefficient. The orthogonal polynomial problem is formulated as a Riemann-Hilbert problem following [22, 23]. We employ the steepest-descent-type method introduced in [18] and further developed in [17, 19] in order to obtain uniform Plancherel-Rotach-type asymptotics in the entire complex plane, as well as asymptotic formulae for the zeros, the leading coefficients, and the recurrence coefficients of the orthogonal polynomials. c 1999 John Wiley & Sons, Inc.
Diagnosis of Pushdown Systems

Diagnosis problems of discrete-event systems consist in detecting unobservable defects during system execution. For finite-state systems, the theory is well understood and a number of effective solutions have been developed. For infinite-state systems, however, there are only few results, mostly identifying classes where the problem is undecidable. We consider higher-order pushdown systems and investigate two basic variants of diagnosis problems: the diagnosability, which consists in deciding whether defects can be detected within a finite delay, and the bounded-latency problem, which consists in determining a bound for the delay of detecting defects. We establish that the diagnosability problem is decidable for arbitrary sub-classes of higher-order visibly pushdown systems provided unobservable events leave the stacks unchanged. For this case, we present an effective algorithm. Otherwise, we show that diagnosability becomes undecidable already for first-order visibly pushdown automata. Furthermore, we establish that the bounded-latency problem for higher-order pushdown systems is as hard as deciding finiteness of a higher-order pushdown language. This is in contrast with the case of finite-state systems where the problem reduces to diagnosability.
Analogy‐driven 3D style transfer

Style transfer aims to apply the style of an exemplar model to a target one, while retaining the target's structure. The main challenge in this process is to algorithmically distinguish style from structure, a high‐level, potentially ill‐posed cognitive task. Inspired by cognitive science research we recast style transfer in terms of shape analogies. In IQ testing, shape analogy queries present the subject with three shapes: source, target and exemplar, and ask them to select an output such that the transformation, or analogy, from the exemplar to the output is similar to that from the source to the target. The logical process involved in identifying the source‐to‐target analogies implicitly detects the structural differences between the source and target and can be used effectively to facilitate style transfer. Since the exemplar has a similar structure to the source, applying the analogy to the exemplar will provide the output we seek. The main technical challenge we address is to compute the source to target analogies, consistent with human logic. We observe that the typical analogies we look for consist of a small set of simple transformations, which when applied to the exemplar generate a continuous, seamless output model. To assemble a shape analogy, we compute an optimal set of source‐to‐target transformations, such that the assembled analogy best fits these criteria. The assembled analogy is then applied to the exemplar shape to produce the desired output model. We use the proposed framework to seamlessly transfer a variety of style properties between 2D and 3D objects and demonstrate significant improvements over the state of the art in style transfer. We further show that our framework can be used to successfully complete partial scans with the help of a user provided structural template, coherently propagating scan style across the completed surfaces.
Pricing Longevity Bonds using Implied Survival Probabilities

For annuity providers, longevity risk, i.e. the risk that future mortality trends differ from those anticipated, constitutes an important risk factor. In order to manage this risk, new financial products will be needed. One of the basic building blocks for such mortality backed securities is the so-called survivor or longevity bond, the future payments of which depend on the survival rates of a certain population. We propose a methodology for the modeling and pricing of longevity bonds. We generalize the ideas of Lin and Cox (2005) and show how to derive implied survival probabilities from annuity market quotes. Taking those implied survival probabilities as a starting point, we derive the price and the dynamics of longevity bonds by applying the Heath-Jarrow-Morton framework for mortality modeling building on an idea proposed by Miltersen and Persson (2005). We show how the models within our framework can be calibrated and applied for pricing mortality derivatives.
Structural analysis of Bub3 interactions in the mitotic spindle checkpoint

The Mad3/BubR1, Mad2, Bub1, and Bub3 proteins are gatekeepers for the transition from metaphase to anaphase. Mad3 from Saccharomyces cerevisiae has homology to Bub1 but lacks a corresponding C-terminal kinase domain. Mad3 forms a stable heterodimer with Bub3. Negative-stain electron microscopy shows that Mad3 is an extended molecule (≈200 Å long), whereas Bub3 is globular. The Gle2-binding-sequence (GLEBS) motifs found in Mad3 and Bub1 are necessary and sufficient for interaction with Bub3. The calorimetrically determined dissociation constants for GLEBS-motif peptides and Bub3 are ≈5 μM. Crystal structures of these peptides with Bub3 show that the interactions for Mad3 and Bub1 are similar and mutually exclusive. In both structures, the GLEBS peptide snakes along the top surface of the β-propeller, forming an extensive interface. Mutations in either protein that disrupt the interface cause checkpoint deficiency and chromosome instability. We propose that the structure imposed on the GLEBS segment by its association with Bub3 enables recruitment to unattached kinetochores.
Structural and Functional Analysis of Viral siRNAs

A large amount of short interfering RNA (vsiRNA) is generated from plant viruses during infection, but the function, structure and biogenesis of these is not understood. We profiled vsiRNAs using two different high-throughput sequencing platforms and also developed a hybridisation based array approach. The profiles obtained through the Solexa platform and by hybridisation were very similar to each other but different from the 454 profile. Both deep sequencing techniques revealed a strong bias in vsiRNAs for the positive strand of the virus and identified regions on the viral genome that produced vsiRNA in much higher abundance than other regions. The hybridisation approach also showed that the position of highly abundant vsiRNAs was the same in different plant species and in the absence of RDR6. We used the Terminator 5′-Phosphate-Dependent Exonuclease to study the 5′ end of vsiRNAs and showed that a perfect control duplex was not digested by the enzyme without denaturation and that the efficiency of the Terminator was strongly affected by the concentration of the substrate. We found that most vsiRNAs have 5′ monophosphates, which was also confirmed by profiling short RNA libraries following either direct ligation of adapters to the 5′ end of short RNAs or after replacing any potential 5′ ends with monophosphates. The Terminator experiments also showed that vsiRNAs were not perfect duplexes. Using a sensor construct we also found that regions from the viral genome that were complementary to non-abundant vsiRNAs were targeted in planta just as efficiently as regions recognised by abundant vsiRNAs. Different high-throughput sequencing techniques have different reproducible sequence bias and generate different profiles of short RNAs. The Terminator exonuclease does not process double stranded RNA, and because short RNAs can quickly re-anneal at high concentration, this assay can be misleading if the substrate is not denatured and not analysed in a dilution series. The sequence profiles and Terminator digests suggest that CymRSV siRNAs are produced from the structured positive strand rather than from perfect double stranded RNA or by RNA dependent RNA polymerase.
Relative Commodity Price Convergence in Pakistan

This study tests intercity price convergence in Pakistan using monthly panel data on the prices of fifteen commodities and services for ten major cities of Pakistan viz Islamabad, Karachi, Lahore, Peshawar, Faisalabad, Multan, Mardan, Hyderabad, Quetta and Khuzdar for the period January 2000 to December 2011. We categorize all the commodities and services into tradable and non-tradable groups and employ the second generation panel unit root tests to examine the intercity price convergence in Pakistan. We also estimate the speed of convergence in relative commodity prices using half life method. Our results indicate stronger convergence in the tradable goods than the non-tradable goods. For robustness, we examine the impact of price volatility on the speed of convergence and the impact of distance (measured as transportation cost) on relative commodity prices. We observe that our main findings remain intact, however the impact of distance on relative prices is found to be very small but significant. Further, we note that the impact of price volatility on speed of convergence is positive and significant.
Overview of Routing Algorithm in Pocket Switched Networks

Pocket Switched Networks represent one particular intermittent communication network for handheld mobile devices. It is an important branch of delay tolerant network with broad application areas, taken as a necessary technology for human-centered pervasive computing. Compared with traditional networks, pocket switched networks have no stable topology structure. As for the other types of delay tolerant network, the nodes in pocket switched networks follow the mobility module as human society. Thus, the routing problem of pocket switched networks is more complex, and the existing works also focus their attention in this area. Technological advances of social networks are leading to a few routing protocols for pocket switched networks. A survey of current routing solutions is presented. The development of social network for pocket switched networks is introduced as three stages. Then the routing protocols for pocket switched networks are classified based on these three stages. The details of these routing protocols are shown in this paper. At last, the article discusses the trend of social based routing protocols. This work is hopefully beneficial to the researchers from the communities of pocket switched network analysis, social network mining, and pattern matching.
Dendritic Cells Induce Peripheral T Cell Unresponsiveness under Steady State Conditions in Vivo

Dendritic cells (DCs) have the capacity to initiate immune responses, but it has been postulated that they may also be involved in inducing peripheral tolerance. To examine the function of DCs in the steady state we devised an antigen delivery system targeting these specialized antigen presenting cells in vivo using a monoclonal antibody to a DC-restricted endocytic receptor, DEC-205. Our experiments show that this route of antigen delivery to DCs is several orders of magnitude more efficient than free peptide in complete Freund's adjuvant (CFA) in inducing T cell activation and cell division. However, T cells activated by antigen delivered to DCs are not polarized to produce T helper type 1 cytokine interferon γ and the activation response is not sustained. Within 7 d the number of antigen-specific T cells is severely reduced, and the residual T cells become unresponsive to systemic challenge with antigen in CFA. Coinjection of the DC-targeted antigen and anti-CD40 agonistic antibody changes the outcome from tolerance to prolonged T cell activation and immunity. We conclude that in the absence of additional stimuli DCs induce transient antigen-specific T cell activation followed by T cell deletion and unresponsiveness.
Fungicide Effects on Fungal Community Composition in the Wheat Phyllosphere

The fungicides used to control diseases in cereal production can have adverse effects on non-target fungi, with possible consequences for plant health and productivity. This study examined fungicide effects on fungal communities on winter wheat leaves in two areas of Sweden. High-throughput 454 sequencing of the fungal ITS2 region yielded 235 operational taxonomic units (OTUs) at the species level from the 18 fields studied. It was found that commonly used fungicides had moderate but significant effect on fungal community composition in the wheat phyllosphere. The relative abundance of several saprotrophs was altered by fungicide use, while the effect on common wheat pathogens was mixed. The fungal community on wheat leaves consisted mainly of basidiomycete yeasts, saprotrophic ascomycetes and plant pathogens. A core set of six fungal OTUs representing saprotrophic species was identified. These were present across all fields, although overall the difference in OTU richness was large between the two areas studied.
Recommendations For Metrics For Multidrug-Resistant Organisms In Healthcare Settings: SHEA/HICPAC Position Paper

Monitoring multidrug-resistant organisms (MDROs) and the infections they cause in a healthcare setting is important to detect newly emerging antimicrobial resistance profiles, to identify vulnerable patient populations, and to assess the need for and effectiveness of interventions; however, it is unclear which metrics are the best, because most of the metrics are not standardized. This document describes useful and practical metrics and surveillance considerations for measuring MDROs and the infections they cause in the practice of infection prevention and control in healthcare settings. These metrics are designed to aid healthcare workers in documenting trends over time within their facility and should not be used for interfacility comparison.
Semantical Considerations on Dialectical and Practical Commitments

This paper studies commitments in multi agent systems. A dialectical commitment corresponds to an agent taking a position about a putative fact, including for the sake of argument. A practical commitment corresponds to an agent being obliged to another to bring about a condition. Although commitments have been used in many works, an adequate formal semantics and axiomatization for them does not yet exist. This paper presents a logic of commitments that illustrates the commonalities and differences of the two kinds of commitments. In this manner, it generalizes the developments of previous papers, precisely delineates the meanings of commitments, and identifies important postulates used informally or semiformally in previous work.