Miracle-dz/UniFAR-FTUs huggingface dataset:
The Power of Prefix Hijackings in the Internet Hierarchy

The correct functioning of inter-domain routing is of vital importance to the ever expanding Internet. As a common threat to the Internet, prefix hijackings often hijack traffic destined to some Autonomous Systems(ASes), leading to routing black holes or traffic interception. In this paper, we study two typical categories of prefix hijackings, namely false origin hijacking and man-in-the-middle interception, by extensive simulations. Our simulations are based on a new model which takes both the hierarchical Internet structure and the AS connectivity degrees into consideration. With this model, we explore the attacking/hijacking power of different ASes and their resisting power to this attack, where different categories of hijackings exhibit different characteristics. In addition, we also confirm that our results still hold considering various factors in the real Internet, including hidden links, prefix distribution, and RPKI, a countermeasure to prefix hijackings that is undergoing an active deployment in inter-domain routing. Some explanations and case studies are given to help better understanding of our results, which we hope will facilitate the deployment of RPKI and inspire new research.
Study of Iron, Copper and Zinc Removal from Acidic Solutions by Sorption

The attenuation of mining activity in the Slovak Republic which started in 1989 led to the extensive closing of deposits using wet conservation, i.e. flooding. Negative effects of acid mine drainage can be observed mainly in the localities where sulphide ores and sulphide-containing raw materials used to be mined. The treatment of acid mine drainage requires the study of using of physical–chemical methods in acidic conditions. Sorption belongs to the effective and economically acceptable methods to remove heavy metals. The paper deals with the utilization of two sorbents: turf brush PEATSORB and zeolite for Fe, Cu and Zn removal from model sulphuric acid solutions (pH 4). The objectives of this work were to evaluate the effects of different parameters (ion concentration, pH) on sorption efficiency and the study of the mechanism of Fe, Cu and Zn removal in acidic conditions with the aim to use results for metals removal from acid mine drainage.
Supporting the Sense-Making Processes of Web Users by Using a Proxy Server

This paper presents a study on how we can support knowledge creation - especially a process called comprehension - in a Web 2.0 environment by providing new functionalities to users of existing Web services. The contribution of this paper is twofold. Firstly, a framework for providing new functionalities is presented. Secondly, a prototype Web service is implemented and evaluated. The prototype uses Wikipedia as an example and as a knowledge repository. The emphasis is on the prototype, a service that allows us to 1) insert sticky notes in Wikipedia articles, 2) enhance the translation capabilities of Wikipedia, and 3) highlight texts in Wikipedia. The analysis of the prototype service shows that we can provide new functionalities to Web users with a proxy server and that the implemented tools offers some support for knowledge creation process called comprehension. The translation service proved especially useful.
Evolution of image regularization with PDEs toward a new anisotropic smoothing based on half kernels

This paper is dedicated to a new anisotropic diffusion approach for image regularization based on a gradient and two diffusion directions obtained from half Gaussian kernels. This approach results in smoothing an image while preserving edges. From an anisotropic edge detector, built of half Gaussian derivative kernels, we introduce a new smoothing method preserving structures which drives the diffusion function of the angle between the two edge directions and the gradient value. Due to the two directions diffusion used in the control function, our diffusion scheme enables to preserve edges and corners, contrary to other anisotropic diffusion methods. Moreover, parameters of the Gaussian kernel can be tuned to be sufficiently thin extracting precisely edges whereas its length allows detecting in contour orientations which leads to a coherent image regularization. Finally, we present some experimental results and discuss about the choice of the different parameters.
Power Efficient Time-Controlled CSMA/CA MAC Protocol for Lunar Surface Networks

Lunar surface networks are critical to a manned mission to the Moon, but encounter many challenges including lack of infrastructure, shortage of power, long distance communications, and quality of service (QoS) support. These challenges demand both power efficient and reliable networking protocols. In this paper a power efficient and reliable MAC protocol is proposed based on commercial IEEE 802.11 chipsets. It includes an innovative mechanism, called time controlled CSMA/CA (TC-CSMA/CA), to reduce power consumption of a communication device to the minimum. Additionally, due to time control, QoS of various applications is highly improved. Both simulations and testbed implementation are carried out to evaluate the performance of the proposed MAC protocol. Experimental results illustrate that the TC-CSMA/CA MAC is highly effective in reducing power consumption and increasing service reliability.
Virus-Like Particles as a vaccinal strategy against tumors induced by papillomavirus infection

Papillomavirus (PV) are small DNA viruses that infect mucosal and cutaneous epithelium and cause benign hyperproliferative lesions in human and animals. Occasionally these lesions can progress to cancer under appropriated environmental conditions. The human papillomavirus (HPV) is associated with many different types of cancer with approximately 450,000 newly diagnosed cases each year and a 50% mortality rate. The bovine papillomavirus (BPV) is associated with papillomatosis and cancer. Cattle cutaneous papillomatosis is not only a health problem but also has economic consequences. Occasionally, entire herds have to be culled if the papillomatosis does not regress. Infections with papillomatosis induce type-specific immune responses, mainly directed against the major capsid protein, L1. Based on the propensity of the L1 protein to self-assemble into virus-like particles (VLPs), our group has lead to research into the development of BPV and HPV vaccine strategies. This work focuses on the expression of L1 HPV gene to use in the Pichia pastoris expression system as a base to VLP production.
Nutritional screening is strongly associated with overall survival in patients treated with targeted agents for metastatic renal cell carcinoma

Although commonly observed, malnutrition is poorly characterized and frequently underdiagnosed in patients with metastatic renal cell carcinoma (RCC). The ability of nutritional screening tools to predict overall survival (OS) in patients with RCC has not been adequately validated. The objective of this study was to investigate the performance of nutritional screening tools and their additional prognostic value in patients with metastatic RCC treated with targeted therapies.
Embedding Emotional Context in Recommender Systems

Emotions are crucial for user's decision making in recommendation processes. We first introduce ambient recommender systems, which arise from the analysis of new trends on the exploitation of the emotional context in the next generation of recommender systems. We then explain some results of these new trends in real-world applications through the smart prediction assistant (SPA) platform in an intelligent learning guide with more than three million users. While most approaches to recommending have focused on algorithm performance. SPA makes recommendations to users on the basis of emotional information acquired in an incremental way. This article provides a cross-disciplinary perspective to achieve this goal in such recommender systems through a SPA platform. The methodology applied in SPA is the result of a bunch of technology transfer projects for large real-world rccommender systems.
Fast Convergence Rates for Distributed Non-Bayesian Learning

We consider the problem of distributed learning, where a network of agents collectively aim to agree on a hypothesis that best explains a set of distributed observations of conditionally independent random processes. We propose a distributed algorithm and establish consistency, as well as a nonasymptotic, explicit, and geometric convergence rate for the concentration of the beliefs around the set of optimal hypotheses. Additionally, if the agents interact over static networks, we provide an improved learning protocol with better scalability with respect to the number of nodes in the network.
Bound in Honor: How Honor Values and Insults Affect the Experience and Management of Conflicts

A quasi‐experiment tested the effects of honor values and the use of insults by the other party on perceived conflict, negative emotions, and intentions to behave distributively and integratively during a workplace conflict. After honor values were measured, participants read a scenario in which a conflict was described. In the scenarios, we manipulated whether the other party used an insult by describing the other party's statements such that either an insult was uttered or no insult was uttered. Consistent with our hypotheses, results showed that conflicts in which the other party used an insult lead to higher ratings of perceived conflict, more negative emotions, and stronger intentions to engage in distributive behavior than conflicts in which the other party did not use an insult in high‐honor‐value participants, but not in low‐honor‐value participants. Mediation analyses showed that the interactive effect of honor values and other party's insults on intentions to behave distributively could be explained by perceived conflict and negative emotions.
Knowledge of malignant melanoma and how it relates to clinical practice among nurse practitioners and dermatology and oncology nurses

Cutaneous malignant melanoma (CMM) is a growing health problem in the United States. This study evaluated nurses' frequency of skin cancer assessment, ability to recognize CMM, knowledge of risk factors and preventive measures, teaching practices, and barriers to skin cancer assessment. The sample (n = 178) consisted of nurse practitioners (NP), oncology nurses (ON), and dermatology nurses (DN). The participants indicated that skin cancer assessment was within their scope of practice but reported frequencies of performance were low. NP scored lower in overall knowledge, although they had received the highest level of formal skin cancer education (P < 0.05). Recognition of melanoma was moderate, with scores of 54–68% for the three groups. Recognition scores for premalignant and benign lesions were lower. Frequency of skin cancer assessment and teaching were higher for DN (p < 0.05). Total knowledge scores were not predictive of teaching practices. Time limitations and inadequate knowledge were barriers that inversely correlated with frequency of skin cancer assessment. Findings suggest that individual CMM knowledge and experience correlated highly with frequency of assessment and teaching. Programs are needed to educate nurses in skin cancer prevention and detection. The broader implications for future research will be presented.
Regulatory Tasks of the Phosphoenolpyruvate-Phosphotransferase System of Pseudomonas putida in Central Carbon Metabolism

ABSTRACT Two branches of the phosphoenolpyruvate-phosphotransferase system (PTS) operate in the soil bacterium Pseudomonas putida KT2440. One branch encompasses a complete set of enzymes for fructose intake (PTSFru), while the other (N-related PTS, or PTSNtr) controls various cellular functions unrelated to the transport of carbohydrates. The potential of these two systems for regulating central carbon catabolism has been investigated by measuring the metabolic fluxes of isogenic strains bearing nonpolar mutations in PTSFru or PTSNtr genes and grown on either fructose (a PTS substrate) or glucose, the transport of which is not governed by the PTS in this bacterium. The flow of carbon from each sugar was distinctly split between the Entner-Doudoroff, pentose phosphate, and Embden-Meyerhof-Parnas pathways in a ratio that was maintained in each of the PTS mutants examined. However, strains lacking PtsN (EIIANtr) displayed significantly higher fluxes in the reactions of the pyruvate shunt, which bypasses malate dehydrogenase in the TCA cycle. This was consistent with the increased activity of the malic enzyme and the pyruvate carboxylase found in the corresponding PTS mutants. Genetic evidence suggested that such a metabolic effect of PtsN required the transfer of high-energy phosphate through the system. The EIIANtr protein of the PTSNtr thus helps adjust central metabolic fluxes to satisfy the anabolic and energetic demands of the overall cell physiology. IMPORTANCE This study demonstrates that EIIANtr influences the biochemical reactions that deliver carbon between the upper and lower central metabolic domains for the consumption of sugars by P. putida. These findings indicate that the EIIANtr protein is a key player for orchestrating the fate of carbon in various physiological destinations in this bacterium. Additionally, these results highlight the importance of the posttranslational regulation of extant enzymatic complexes for increasing the robustness of the corresponding metabolic networks. This study demonstrates that EIIANtr influences the biochemical reactions that deliver carbon between the upper and lower central metabolic domains for the consumption of sugars by P. putida. These findings indicate that the EIIANtr protein is a key player for orchestrating the fate of carbon in various physiological destinations in this bacterium. Additionally, these results highlight the importance of the posttranslational regulation of extant enzymatic complexes for increasing the robustness of the corresponding metabolic networks.
Soil Macroinvertebrate Communities Across a Productivity Gradient in Deciduous Forests of Eastern North America

Abstract Within the temperate, deciduous forests of the eastern US, diverse soil-fauna communities are structured by a combination of environmental gradients and interactions with other biota. The introduction of non-native soil taxa has altered communities and soil processes, and adds another degree of variability to these systems. We sampled soil macroinvertebrate abundance from forested sites in Missouri (MO), Michigan (MI), Massachusetts (MA), and New Hampshire (NH), with the objective of comparing community assemblages and evaluating the role of invasive earthworms along the temperature—productivity gradient represented by the sites. The primary detritivores encountered were earthworms and millipedes. Earthworms were collected only in MO and MI, and at much greater density in MO. Millipedes were found at every site except in MO, and at their highest mean density in NH. Warmer temperatures, higher litter productivity, and low Oa horizon depth (as found in MO) were correlated with high earthworm activity. Oa horizon depth was the greatest in NH, where the macroinvertebrate community was dominated (in terms of abundance) by predators and herbivores, not detritivores. Our results are suggestive of, and congruent with, the concept of earthworms as ecosystem engineers, as we found that the presence of non-native earthworm species was associated with significant differences in soil characteristics such as apparent rapid decomposition rates and reduced carbon storage in the Oa horizon.
Double Sparsity: Learning Sparse Dictionaries for Sparse Signal Approximation

An efficient and flexible dictionary structure is proposed for sparse and redundant signal representation. The proposed sparse dictionary is based on a sparsity model of the dictionary atoms over a base dictionary, and takes the form D = ¿ A, where ¿ is a fixed base dictionary and A is sparse. The sparse dictionary provides efficient forward and adjoint operators, has a compact representation, and can be effectively trained from given example data. In this, the sparse structure bridges the gap between implicit dictionaries, which have efficient implementations yet lack adaptability, and explicit dictionaries, which are fully adaptable but non-efficient and costly to deploy. In this paper, we discuss the advantages of sparse dictionaries, and present an efficient algorithm for training them. We demonstrate the advantages of the proposed structure for 3-D image denoising.
A novel path planning proposal based on the combination of deterministic sampling and harmonic functions

The sampling-based approach is currently the most successful and yet more promising approach to path planning problems. Sampling-based methods are demonstrated to be probabilistic complete, being their performance reliant on the generation of samples. To obtain a good set of samples, this paper proposes a new sampling paradigm based on deterministic sampling paradigm based on a deterministic sampling sequence guided by an harmonic potential function computed on a hierarchical cell decomposition of C-space. In the proposed method, known as Kautham sampler, samples are not isolated configurations but parts of a whole. As samples are generated they are dynamically grouped into cells that capture the C-space structure. This allows the use of harmonic functions to share information and guide further sampling towards more promising regions of C-space. Finally, using the samples obtained, a roadmap is easily built taking advantage of the known neighbourhood relationships.
Creating trust through charity advertisement : focusing on charity successes or future goals, by using statistical or anecdotal evidence?

Trust plays an important role in the charity sector, as for donors it is difficult to assess whether their money has been used as directed. If the public has little confidence in a charitable organization, they will be less willing to support the organization. As a consequence, for charities it is of importance that their advertisements create trust in order for donors to donate and to continue donating. This study examines several message factors and their influence on people’s trust and intentions to donate to a charitable organization. One way to possibly influence potential donors to contribute to charitable organizations is through communicating the successes of the organization to the public. Another way is by emphasizing what goals the charity yet wants to accomplish in the future. Next to focusing the advertising message on successes or future goals, potential donors can also be influenced by the type of evidence that is presented. In this study a distinction is made between presenting the message with statistical and anecdotal evidence. A study in this field was carried out, to examine the effectiveness of different charity advertisements in relation to trust and donation intention. A 2 (advertising strategy scenarios: future goals versus past successes) by 2 (evidence type: anecdotal versus statistical) between subjects design was used. Four manipulated charity advertisements were used, about a fictive charitable organization that raises money for research into childhood cancer. An online survey was carried out, in which 171 participants from the Netherlands took part. The effects of the advertising strategy scenarios and evidence types were measured on five constructs; trust in the charitable organization, message- and messenger credibility, risk perception and donation intention. Results showed that participants exposed to anecdotal evidence scored statistically significantly higher on trust in the charitable organization as opposed to those exposed to statistical evidence. However, no significant differences were found for message- and messenger credibility, the perceived risk and donation intention between the two evidence types. Results showed no statistically significant differences between participants exposed to charity advertisements that focused on future goals and those exposed to past successes. In addition, also no interaction effects between the advertising strategy scenarios and evidence types were found. Notably, in all four conditions participants scored low on donation intention. The findings of this study provide insight into the effects of evidence types combined with different advertising strategy scenarios in charity fundraising messages, which charitable organizations should take into account when developing advertising messages.
Model-Lite Planning : Diverse Multi-Option Plans & Dynamic Objective Functions

Knowledge acquisition is one major bottle-neck in using planning systems. Model-lite planning reduces this burden by placing responsibility on the planning system to cope with partially specified models. For example, eliciting the planning objective can be difficult in applications where it is necessary to reason about multiple plan metrics, such as cost, time, risk, human life, etc. Traditional approaches, often require a (sometimes subjective) combination of these objectives into a single optimization metric. For example, decision theoretic planners combine plan cost and probability of goal satisfaction into a single reward metric. However, users may not know how to combine their metrics into a single objective without first exploring several diverse plan options. To avoid premature objective function commitments at plan synthesis time (and even plan execution time), we develop the notion of multi-option plans. Much like conditional plans that branch to deal with execution-time observations, multi-option plans branch to deal with execution-time assessments of plan objectives. That is, a multi-option plan is a compact representation of the diverse Pareto set of plans, where at each step the user can execute one of several non-dominated options. We formulate multi-option planning within the context of conditional probabilistic planning, where plans satisfy the goal with different probabilities and costs. Our approach is based on multi-objective dynamic programming in state space, where each plan node maintains a set of nondominated sub-plan options, that are each a conditional plan.
Exposure of Lactating Dairy Cows to Acute Pre-Ovulatory Heat Stress Affects Granulosa Cell-Specific Gene Expression Profiles in Dominant Follicles

High environmental temperatures induce detrimental effects on various reproductive processes in cattle. According to the predicted global warming the number of days with unfavorable ambient temperatures will further increase. The objective of this study was to investigate effects of acute heat stress during the late pre-ovulatory phase on morphological, physiological and molecular parameters of dominant follicles in cycling cows during lactation. Eight German Holstein cows in established lactation were exposed to heat stress (28°C) or thermoneutral conditions (15°C) with pair-feeding for four days. After hormonal heat induction growth of the respective dominant follicles was monitored by ultrasonography for two days, then an ovulatory GnRH dose was given and follicular steroid hormones and granulosa cell-specific gene expression profiles were determined 23 hrs thereafter. The data showed that the pre-ovulatory growth of dominant follicles and the estradiol, but not the progesterone concentrations tended to be slightly affected. mRNA microarray and hierarchical cluster analysis revealed distinct expression profiles in granulosa cells derived from heat stressed compared to pair-fed animals. Among the 255 affected genes heatstress-, stress- or apoptosis associated genes were not present. But instead, we found up-regulation of genes essentially involved in G-protein coupled signaling pathways, extracellular matrix composition, and several members of the solute carrier family as well as up-regulation of FST encoding follistatin. In summary, the data of the present study show that acute pre-ovulatory heat stress can specifically alter gene expression profiles in granulosa cells, however without inducing stress related genes and pathways and suggestively can impair follicular growth due to affecting the activin-inhibin-follistatin system.