Miracle-dz/UniFAR-FTUs huggingface dataset:
Double auction mechanisms for resource allocation in autonomous networks

Auction mechanisms are used for allocating a resource among multiple agents with the objective to maximize social welfare. What makes auctions attractive is that they are agnostic to utility functions of agents. Auctions involve a bidding method by agents-buyers, which is then mapped by a central controller to an allocation and a payment for each agent. In autonomic networks comprising self-interested nodes with different needs and utility functions, each entity possesses some resource and can engage in transactions with others to achieve its needs. In fact, efficient network operation relies on node synergy and multi-lateral resource trading. Nodes face the dilemma of devoting their limited resource to their own benefit versus acting altruistically and anticipating to be aided in the future. Wireless ad-hoc networks, peer-to-peer networks and disruption-tolerant networks are instances of autonomic networks where the challenges above arise and the traded resource is energy, bandwidth and storage space respectively. Clearly, the decentralized complex node interactions and the double node role as resource provider and consumer amidst resource constraints cannot be addressed by single-sided auctions and even more by mechanisms with a central controller. We introduce a double-sided auction market framework to address the challenges above. Each node announces one bid for buying and one for selling the resource. We prove that there exist bidding and charging strategies that maximize social welfare and we explicitly compute them. We generalize our result to a generic network objective. Nodes are induced to follow these strategies, otherwise they are isolated by the network. Furthermore, we propose a decentralized realization of the double-sided auction with lightweight network feedback. Finally, we introduce a pricing method which does not need a charging infrastructure. Simulation results verify the desirable properties of our approach.
Egg Consumption and Risk of Upper Aero-Digestive Tract Cancers: A Systematic Review and Meta-Analysis of Observational Studies.

Limited data are available that summarize the relation between egg intake and the risk of upper aero-digestive tract (UADT) cancers. This systematic review and meta-analysis was conducted to investigate the association between egg intake and the risk of UADT cancers. Medline/PubMed, ISI web of knowledge, EMBASE, Scopus, and Google Scholar were searched using relevant keywords. Observational studies conducted on humans investigating the association between egg consumption and the risk of UADT cancers were included. Overall, 38 studies with a total of 164,241 subjects (27, 025 cases) were included. Based on 40 effect sizes from 32 case-control studies, we found a 42% increased risk of UADT cancers among those with the highest egg consumption (ranging from ≥1 meal/d to ≥1 time/mo among studies) compared to those with the lowest intake (ranging from 0-20 g/d to never consumed among studies) (overall OR: 1.42; 95% CI: 1.19, 1.68; P < 0.001). However, this association was only evident in hospital-based case-control (HCC) studies (OR = 1.50; 95% CI: 1.34, 1.68; P < 0.001 for 'oropharyngeal and laryngeal cancer' and OR: 1.27; 95% CI: 1.08, 1.50; P = 0.004 for esophageal cancer) and not in population-based case-control (PCC) studies (OR = 1.25; 95% CI: 0.59, 2.67; P = 0.56 for 'oropharyngeal and laryngeal cancer' and OR: 1.29; 95% CI: 0.92, 1.81; P = 0.13 for esophageal cancer). In addition, the association was not significant in prospective cohort studies (overall OR: 0.86; 95% CI: 0.71, 1.04; P = 0.11). Considering individual cancers, a positive association was observed between the highest egg consumption, compared with the lowest, and risk of oropharyngeal (OR: 1.88; 95% CI: 1.61, 2.20; P < 0.001), laryngeal (OR: 1.83; 95% CI: 1.45, 2.32; P < 0.001), oral & pharyngeal & laryngeal (OR: 1.37; 95% CI: 1.12, 1.67; P < 0.001), and esophageal cancers (OR: 1.28; 95% CI: 1.10,1.48; P = 0.001). We also found an inverse association between egg intake and the risk of oral cancer (OR: 0.78; 95% CI: 0.62, 0.99; P = 0.04). In conclusion, high egg consumption (ranging from ≥1 meal/d to ≥1 time/mo among studies) was associated with increased risk of UADT cancers only in HCC studies but not in PCC or prospective cohort studies. PROSPERO registration number: CRD42018102619.
Modeling and Improving TCP Performance over Cellular Link with Variable Bandwidth

To facilitate a viable evolution of cellular networks toward extensive packet data traffic, the High Speed Downlink Packet Access (HSDPA) technology is introduced. The various link adaptation techniques employed by HSDPA augment the bandwidth variation, which is identified as one of the most important factors resulting in the deterioration of TCP performance. In this paper, we firstly build an analytical model of TCP throughput to explain why the bandwidth variation degrades the TCP performance. Subsequently, a split-connection Window Adaptation TCP Proxy is proposed to improve the TCP throughput in HSDPA networks. To use the precious cellular link resources sufficiently, the length of the queue in Node-B is intentionally kept around the reference value through adaptively adjusting the sending window size of TCP proxy based on the dynamic values of varying bandwidth. Since both the disturbance caused by bandwidth variation and the feedback delay are prone to lead an unstable queue system, the robust sliding mode variable structure control theory is employed to design the proper control law to weaken the impact of noise and delay on the stability of the queue system in Node-B. The theoretical analysis and the enhanced scheme are verified through simulation experiments. The simulation results show that our TCP proxy is able to resist against bandwidth oscillation and improve the cellular link utilization.
Secure Communication Over Fading Channels

The fading broadcast channel with confidential messages (BCC) is investigated, where a source node has common information for two receivers (receivers 1 and 2), and has confidential information intended only for receiver 1. The confidential information needs to be kept as secret as possible from receiver 2. The broadcast channel from the source node to receivers 1 and 2 is corrupted by multiplicative fading gain coefficients in addition to additive Gaussian noise terms. The channel state information (CSI) is assumed to be known at both the transmitter and the receivers. The parallel BCC with independent subchannels is first studied, which serves as an information-theoretic model for the fading BCC. The secrecy capacity region of the parallel BCC is established, which gives the secrecy capacity region of the parallel BCC with degraded subchannels. The secrecy capacity region is then established for the parallel Gaussian BCC, and the optimal source power allocations that achieve the boundary of the secrecy capacity region are derived. In particular, the secrecy capacity region is established for the basic Gaussian BCC. The secrecy capacity results are then applied to study the fading BCC. The ergodic performance is first studied. The ergodic secrecy capacity region and the optimal power allocations that achieve the boundary of this region are derived. The outage performance is then studied, where a long-term power constraint is assumed. The power allocation is derived that minimizes the outage probability where either the target rate of the common message or the target rate of the confidential message is not achieved. The power allocation is also derived that minimizes the outage probability where the target rate of the confidential message is not achieved subject to the constraint that the target rate of the common message must be achieved for all channel states.
Impedance control for elastic joints industrial manipulators

An impedance controller for industrial manipulators is presented in this paper. Special attention has been paid to all the aspects that qualify an industrial robot, including decentralized proportional-integral-derivative position control, torsional flexibility, and friction at the joints. A discussion of a single-degree-of-freedom (DOF) case is first presented. The selection of the impedance parameters is based on the behavior in contact and makes reference to a new design parameter, the compliance bandwidth. The single-DOF analysis is then used in the design of the impedance controller for a complete manipulator. A rotational impedance based on a geometrically consistent representation of the orientation is used. Several experimental results obtained on a 6-DOF industrial robot, equipped with a force/torque sensor, are presented. The experiments show the effectiveness of the proposed approach in several conditions, including contact with an extremely stiff surface and noncontact/contact transition.
A concentration-of-measure inequality for multiple-measurement models

Classical compressive sensing typically assumes a single measurement, and theoretical analysis often relies on corresponding concentration-of-measure results. There are many real-world applications involving multiple compressive measurements, from which the underlying signals may be estimated. In this paper, we establish a new concentration-of-measure inequality for a block-diagonal structured random compressive sensing matrix with Rademacher-ensembles. We discuss applications of this newly-derived inequality to two appealing compressive multiple-measurement models: for Gaussian and Poisson systems. In particular, Johnson-Lindenstrauss-type results and a compressed-domain classification result are derived for a Gaussian multiple-measurement model. We also propose, as another contribution, theoretical performance guarantees for signal recovery for multi-measurement Poisson systems, via the inequality.
Identity at work : developing and using an integrated approach to explore the role of identity (both as a struggle and as a resource) in a knowledge intensive organizational setting

This research explores the role of identity within a knowledge intensive organizational setting in which frequent change, ambiguous work, autonomous work practices, and pervasive client relationships mean that organizational members face many complex challenges in their day-to-day work life. On the basis of a longitudinal, multi-level, intra-and inter-organizational study of a group of people within a regional marketing agency, an integrated approach is proposed and developed as a way to explore and emphasise the complex role of identity, as both a resource and a struggle, in this organizational setting. The approach is generated from iterative cycling between data and existing theory in which the concepts of social identities and identity work are drawn together as a way to provide insight into the role of identity within the research setting. The research participants are seen to engage in identity work in order to create, change, protect and switch between multiple work-related social identities. It is argued that this is a crucial part of agency work, which agency employees work hard to achieve. It is also argued that they use this ‘fluid framework’ of identity as way of dealing with some of the challenges of their everyday work. The research itself is underpinned by a methodology guided by symbolic interactionism. The conceptualisation of identity as an ongoing process with occasional pauses is rooted in the Meadian concept of the ‘I’ and the ‘me’. The contribution of this study to the developing field of identity and organizations is in the building of a conceptual bridge between those whose main concern is with the dynamics of identity creation and those whose main concern is with the product or outcome of identity processes. A practical contribution is also made to further understanding identity at work through the insights gained within this research setting.
A Predictive Model for the Automated Management of Conditioning Systems in Smart Buildings

The paper describes a technological basis for dynamic actions targeted to an effective, real-time control of air conditioning systems in smart buildings with a focus on energy management. The proposed procedure could be extended to more complex systems, usually including a number of prosumer (producer and consumer) nodes, connected to a smart grid and remotely controlled by a Distributed System Operator (DSO) in distributed control and monitoring systems. Accurate, continuously-recorded local weather data are then used to make decisions aimed at both reducing energy consumption and assuring pre-established comfort levels. The amount of saved energy can be estimated by observing a building's energy performance under the action of different meteorological agents through data mining and machine learning methods. Moreover, some possible advantages from real-time exploitation of a building's thermal inertia are shown. The proposed on-line management was also validated through laboratory experimental tests, whose results are reported and discussed.
Push-pull based critical information gathering in VANETs: Multi agent system based approach

Today's vehicles have the capability of sensing, computing, and communicating capabilities. Different components in the vehicle constantly exchange the available information with other vehicles on the road and cooperate for the purpose of ensuring safety and comfort, known as Vehicular Ad hoc Network (VANET). VANETs are a specific type of Mobile Ad hoc Networks (MANETs) that are currently attracting the attention of researchers around the world. With pervasiveness of mobile computing technology and wireless communications, VANETs could be a key networking technology of the future vehicle communications. In VANETs, critical informations like navigation, cooperative collision avoidance, lane-changing, speed limit, accident, obstacle or road condition warnings, etc. plays a significant role for safety-related applications. Such kind of critical information gathering is challenging, because of their delay-critical nature. In order to gather critical informations efficiently dynamic time sensitive algorithms are necessary. In this position paper we have introduced a new multi agent (combination of Heavy-weight static and light-weight mobile agents) based push-pull algorithm that probabilistically considers the push and pull operations for critical information gathering, depending on the information relevance and importance. The push and pull probabilities of informations are computed dynamically, without any prior knowledge. The main contribution of our work lies in the efficiency of the algorithm in gathering the information with minimum time. The time taken to gather the information by a vehicle is modeled analytically.
The dynamic neural field approach to cognitive robotics

This tutorial presents an architecture for autonomous robots to generate behavior in joint action tasks. To efficiently interact with another agent in solving a mutual task, a robot should be endowed with cognitive skills such as memory, decision making, action understanding and prediction. The proposed architecture is strongly inspired by our current understanding of the processing principles and the neuronal circuitry underlying these functionalities in the primate brain. As a mathematical framework, we use a coupled system of dynamic neural fields, each representing the basic functionality of neuronal populations in different brain areas. It implements goal-directed behavior in joint action as a continuous process that builds on the interpretation of observed movements in terms of the partner's action goal. We validate the architecture in two experimental paradigms: (1) a joint search task; (2) a reproduction of an observed or inferred end state of a grasping–placing sequence. We also review some of the mathematical results about dynamic neural fields that are important for the implementation work.
First Year Student Adjustment, Success, and Retention: Structural Models of Student Persistence Using Electronic Portfolios

This study explores the deployment of electronic portfolios to a university-wide cohort of freshman undergraduates that included a subgroup of at-risk and lower academically prepared learners. Five evaluative dimensions based on persistence and engagement theory were included in the development of four assessment rubrics exploring goal clarity, support from friends and family, academic engagement, social integration, and quality of effort were used to assess student ePortfolios. Data collected from these five were integrated with institutional measures producing two structural equation models explaining undergraduate persistence for students returning with 2.5 and 3.2 GPAs with an explained variance of 31 and 39 percent respectively. Carefully designed interventions geared to assist students in continuing their studies as second year undergraduates are considered.
StarClique: guaranteeing user privacy in social networks against intersection attacks

Building on the popularity of online social networks (OSNs) such as Facebook, social content-sharing applications allow users to form communities around shared interests. Millions of users worldwide use them to share recommendations on everything from music and books to resources on the web. However, their increasing popularity is beginning to attract the attention of malicious attackers. As social network credentials become valued targets of phishing attacks and social worms, attackers look to leverage compromised accounts for further financial gain. In this paper, we analyze the state of privacy protection in social content-sharing applications, describe effective privacy attacks against today's social networks, and propose anonymization techniques to protect users. We show that simple protection mechanisms such as anonymizing shared data can still leave users open to social intersection attacks, where a small number of compromised users can identify the originators of shared content. Modeling this as a graph anonymization problem, we propose to provide users with k-anonymity privacy guarantees by augmenting the social graph with "latent edges. " We identify StarClique, a locally minimal graph structure required for users to attain k-anonymity, where at worst, a user is identified as one of k possible contributors of a data object. We prove the correctness of our approach using analysis. Finally, using experiments driven by traces from the del.icio. us social bookmark site, we demonstrate the practicality and effectiveness of our approach on real-world systems.
Message in a Sealed Bottle: Privacy Preserving Friending in Mobile Social Networks

Many proximity-based mobile social networks are developed to facilitate connections between any two people, or to help a user to find people with a matched profile within a certain distance. A challenging task in these applications is to protect the privacy of the participants' profiles and communications. In this paper, we design novel mechanisms, when given a preference-profile submitted by a user, that search persons with matching-profile in decentralized mobile social networks. Meanwhile, our mechanisms establish a secure communication channel between the initiator and matching users at the time when a matching user is found. These techniques can also be applied to conduct privacy preserving keywords based search without any secure communication channel. Our analysis shows that our mechanism is privacy-preserving (no participants' profile and the submitted preference-profile are exposed), verifiable (both the initiator and any unmatched user cannot cheat each other to pretend to be matched), and efficient in both communication and computation. Extensive evaluations using real social network data, and actual system implementation on smart phones show that our mechanisms are significantly more efficient than existing solutions.
Functional redundancy for dynamic exploitation of performance-energy consumption trade-offs

This paper presents a novel approach for system design, the functional redundancy, as one way to allow dynamic exchange of system's characteristics, in order to obtain the lowest power consumption still meeting performance requirements. The basic idea is to have different implementation instances of circuits with the same functionality but with different performance-energy consumption characteristics. An RTOS aware of the functional redundancy present in the circuit will make the dispatch of instructions to the highest performance or to the lowest power consuming IP core, according to the system load. We extend the task model for real-time scheduling and demonstrate the effectiveness of the method through some experiments.
Views of recent Singapore nursing graduates: factors influencing nurse–patient interaction in hospital settings

Background: The nurse–patient relationship is central to the provision of positive and effective care delivery. Aim: This exploratory study investigated recent Singapore nursing graduates’ experience of factors that facilitate and/or impede nurse–patient interaction in hospital settings. Design: Qualitative descriptive design using semi-structured interviews. Methods: Individual interviews were conducted with 11 graduate nurses until theoretical saturation of ideas was achieved. Interviews were audio-recorded, transcribed and analysed using thematic analysis. Findings: The three themes that emerged from the nursing interviews were: patient-related factors, nurse-related factors, and care culture-related factors. Conclusions: Transitioning to practice can be challenging for new graduate nurses. These findings have implications for education programs and the role of the nurse.
Cyclooxygenase 2 Inhibitor Celecoxib Inhibits Glutamate Release by Attenuating the PGE2/EP2 Pathway in Rat Cerebral Cortex Endings

The excitotoxicity caused by excessive glutamate is a critical element in the neuropathology of acute and chronic brain disorders. Therefore, inhibition of glutamate release is a potentially valuable therapeutic strategy for treating these diseases. In this study, we investigated the effect of celecoxib, a selective cyclooxygenase-2 (COX-2) inhibitor that reduces the level of prostaglandin E2 (PGE2), on endogenous glutamate release in rat cerebral cortex nerve terminals (synaptosomes). Celecoxib substantially inhibited the release of glutamate induced by the K+ channel blocker 4-aminopyridine (4-AP), and this phenomenon was prevented by chelating the extracellular Ca2+ ions and by the vesicular transporter inhibitor bafilomycin A1. Celecoxib inhibited a 4-AP–induced increase in cytosolic-free Ca2+ concentration, and the celecoxib-mediated inhibition of glutamate release was prevented by the Cav2.2 (N-type) and Cav2.1 (P/Q-type) channel blocker ω-conotoxin MVIIC. However, celecoxib did not alter 4-AP–mediated depolarization and Na+ influx. In addition, this glutamate release–inhibiting effect of celecoxib was mediated through the PGE2 subtype 2 receptor (EP2) because it was not observed in the presence of butaprost (an EP2 agonist) or PF04418948 [1-(4-fluorobenzoyl)-3-[[6-methoxy-2-naphthalenyl)methyl]-3-azetidinecarboxylic acid; an EP2 antagonist]. The celecoxib effect on 4-AP–induced glutamate release was prevented by the inhibition or activation of protein kinase A (PKA), and celecoxib decreased the 4-AP–induced phosphorylation of PKA. We also determined that COX-2 and the EP2 receptor are present in presynaptic terminals because they are colocalized with synaptophysin, a presynaptic marker. These results collectively indicate that celecoxib inhibits glutamate release from nerve terminals by reducing voltage-dependent Ca2+ entry through a signaling cascade involving EP2 and PKA.