Miracle-dz/UniFAR-FTUs huggingface dataset:
Trading Robustness for Privacy in Decentralized Recommender Systems

Collaborative filtering (CF) recommender systems are very popular and successful in commercial application fields. One end-user concern is the privacy of the personal data required by such systems in order to make personalized recommendations. Recently, peer-to-peer decentralized architectures have been proposed to address this privacy issue. On the other hand system managers must be concerned about system robustness. In particular, it has been shown that recommender systems are vulnerable to profile injection, although model-based CF algorithms show greater stability against malicious attacks that have been studied in the state-of-the-art. In this paper we generalize the generic model for decentralized recommendation and discuss the trade-off between robustness and privacy. In this context, we argue that exposing knowledge of the model parameters allows new, highly effective, model-based attack strategies to be considered. We conclude that the security concerns of privacy and robustness stand in opposition to each other and are difficult to satisfy simultaneously.
Public Auditing Scheme for Cloud-Based Wireless Body Area Network

WBAN (Wireless Body Area Network) plays a fundamental role in telemedicine. However, due to the small size of sensor devices and weak capabilities in data processing/storage, WBAN is limited in application. In order to improve the ability of WBAN system and provide a richer service, the cloud-assisted WBAN has been proposed. Recently, He et al. proposed a method to check the data integrity in cloud-assisted WBAN. However, we found that in their scheme, the cloud server (storage service provider) can access the user's medical information directly. As we know, the cloud service provider can be divided into three kinds: public cloud, private cloud and hybrid cloud. Except of the private cloud, the cloud server should be considered as not trusted in the other two situations. Based on this assumption, in this paper, we proposed a certificateless public auditing scheme with privacy preserving and revocation in group sharing data model. Compared with He et al.'s scheme, the cloud server can not access any useful information from the stored data. Furthermore, our scheme supports properties of multi-user sharing data, public auditing, forward security and revocation of illegal group members.
Early Postmodernism in Social Education—Revisiting “Decision Making: The Heart of Social Studies Instruction”

M ore than 40 years have passed since Shirley Engle's article "Decision-Making: The Heart of Social Studies Instruction" was published. It was, in today's vernacular, an instant hit. It somehow reached into the hearts and minds of social studies teachers and gave them a sense of what made their field different from other areas of instruction. It was not just a question of teaching history or civics but of helping young people become effective decision makers in a democracy. There were numerous antecedents to Engle's article, such as Raup, Axtelle, Benne, and Smith's book The Improvement of Practical Intelligence (1950) and John Dewey's extended work in problem solving (e.g., 1910, 1916), but none spoke so clearly and directly to teachers-none reflected so well the incipient postmodernism of the post-World War II era, none opened the social studies
Unconditional Quantile Regression with Endogenous Regressors

This paper proposes an extension of the Fortin, Fipro and Lemieux (2009) unconditional quantile regression approach by allowing endogenous regressors in a nonseparable triangular model. The RIF (Re-centered Influence Function) regression has been identified by using the control variable approach developed by Imbens and Newey (2009). The results are not specific to models with endogenous regressors, but also applies to the exogenous case for which there is no need for a control variable. We also derive the Unconditional Quantile Partial Effect (UQPE) and RIF regression for the nonlinear additively separable model and show that Fipro et al. (2009) results can be obtained from our results by assuming no endogenous regressors in X. We have illustrated our theoretical results by using the Box-Cox unconditional quantile regression model as an example. We also show that in the nonlinear additively separable model, we can separate out the bias terms for UQPE and RIF regression functions by using the additive separability condition between regressors and error terms. We show that the bias terms for UQPE and RIF regression are non monotonic across the quantiles.
Survey of background scattering from materials found in small-angle neutron scattering

The paper describes quantitative methods for determining the background scattering from materials, including gases, liquids and solids, found in small-angle neutron scattering measurements. By understanding the dependence of the background on material type, thickness, wavelength and temperature, the investigator can design experiments that minimize the background scattering and thus improve the statistical accuracy of the background-corrected data.
A Configurable Monitoring Infrastructure for NoC-Based Architectures

In this brief, we propose a monitoring architecture for networks-on-chip that provides system information useful for designers to efficiently exploit, at design time and run-time, the system resources available in multiprocessor system-on-chip platforms. We focus on the analysis of the architectural details and design challenges of such a system, by describing powerful tools for monitoring information that can be used both at run-time for detecting dynamic changes in system behavior and at post-execution time for debugging and profiling of applications. This brief describes the design of the monitoring probes, together with the events detectable by them, and discusses an architecture for collecting, storing, and analyzing the information gathered during an application execution.
MACHINE LEARNING MEETS AGENT-BASED MODELING : WHEN NOT TO

One of the promises of ABM is the ability to have adaptive agents make decisions in changing environments. Though great work has been done using adaptive agents in ABM, more research into the theoretical understanding of these systems would be useful. Adaptive agents have already been studied within machine learning (ML)—an area of artificial intelligence specifically concerned with adaptation and building internal models. The first part of this paper presents a framework for understanding ML as a component of ABM, and describes how different ML techniques can be incorporated into some ABMs. At the high level this framework consists of two cycles that involve evaluating input, making decisions and then generating output. Within this generalized framework, the ML algorithm is using the ABM as an environment and a reward generator, while the ABM is using the ML algorithm to refine the internal models of the agents. There are many details that must be answered before any ML technique can be incorporated into an ABM. In this paper I start to explore some guidelines for how to more closely integrate ABM and ML and will discuss complications that arise when combining ABM and ML techniques. To illustrate some of these issues, I will describe an integration of a ML technique within the El Farol Bar Problem. I will conclude with some discussion of this integration and a look toward future research.
The Diagnostic Guideline for Anxiety and Challenging Behaviour for Persons with Intellectual Disabilities: Preliminary Outcomes on Internalizing Problems, Challenging Behaviours, Quality of Life and Clients' Satisfaction

BACKGROUND People with intellectual disabilities are vulnerable to develop psychopathology (in particular anxiety) and related challenging behaviour. A diagnostic guideline was developed to support professionals to better diagnose and thus treat psychopathology and related CB. This study examined preliminary outcomes from the application of this guideline. METHOD A comparative multiple case study with an experimental and a control condition. RESULTS The application of the guideline showed a trend of decreases of internalizing problems (P = 0.07) and anxiety/depressed problems (P = 0.09). We found no statistically significant decreases of externalizing problems and no increases in perceived quality of life as compared with care as usual. Clients were not more satisfied with the support they received for coping with their emotional and behaviour problems. CONCLUSION The application of the Diagnostic Guideline for Anxiety and Challenging Behaviour did not show statistically significant changes in externalizing problems and Quality of Life. Despite the small sample size of n = 59, we did find a trend in decreasing internalizing problems and anxiety/depressed problems. Further research into either or not confirming these trends is recommended.
MobiZone: personalized interaction with multiple items on interactive surfaces

Current interactive surfaces do not support user identification. Hence, personalized applications that consider user-specific access control are not possible. Diverse approaches for identifying and distinguishing users have been investigated in previous research. Token-based approaches -- e.g., which utilize the user's mobile phone -- are especially promising, as they also allow for consideration of the user's personal digital context (e.g., stored messages, contacts, or media data). However, existing interaction techniques are limited regarding their ability to enable users to manipulate (e.g., select or copy) multiple items at the same time, as they are cumbersome when the number of files exceeds a certain amount. We present MobiZone, a technique that enables users to interact with large numbers of items on an interactive surface while enabling personalized access by using the mobile phone as a token. MobiZone provides a spatial zone that can be positioned, resized and associated with any action according to the user's needs; items enclosed by the zone can be manipulated simultaneously. We present three interaction techniques (FlashLight&Control, Remote&Control, and Place&Control) that enable users to control the zone. Additionally, we report the results of a comparative user study in which we compared the different interaction techniques for MobiZone. The results indicate that users are fastest with Remote&Control, and they also rated Remote&Control slightly higher than the other techniques.
Disturbance Attenuation Tracking Control for Wheeled Mobile Robots With Skidding and Slipping

In this paper, a robust tracking control scheme is proposed for wheeled mobile robots with skidding, slipping, and input disturbance. Considering the existing skidding and slipping, a desired disturbance-observer-based virtual velocity control law is first designed. Then, the robust tracking control scheme is developed by considering the prescribed tracking performance requirement and using the disturbance observer. In the tracking control scheme design, the prescribed performance function method is employed to guarantee the desired tracking performance. To handle the skidding, slipping, and input disturbance, the disturbance observer is developed in the control scheme design. Experiment results demonstrate the effectiveness of the proposed tracking control scheme for wheeled mobile robots with skidding, slipping, and input disturbance.
Small molecule-driven mitophagy-mediated NLRP3 inflammasome inhibition is responsible for the prevention of colitis-associated cancer

Nonresolving inflammation in the intestine predisposes individuals to the development of colitis-associated cancer (CAC). Inflammasomes are thought to mediate intestinal homeostasis, and their dysregulation contributes to inflammatory bowel diseases and CAC. However, few agents have been reported to reduce CAC by targeting inflammasomes. Here we show that the small molecule andrographolide (Andro) protects mice against azoxymethane/dextran sulfate sodium-induced colon carcinogenesis through inhibiting the NLRP3 inflammasome. Administration of Andro significantly attenuated colitis progression and tumor burden. Andro also inhibited NLRP3 inflammasome activation in macrophages both in vivo and in vitro, as indicated by reduced expression of cleaved CASP1, disruption of NLRP3-PYCARD-CASP1 complex assembly, and lower IL1B secretion. Importantly, Andro was found to trigger mitophagy in macrophages, leading to a reversed mitochondrial membrane potential collapse, which in turn inactivated the NLRP3 inflammasome. Moreover, downregulation of the PIK3CA-AKT1-MTOR-RPS6KB1 pathway accounted for Andro-induced autophagy. Finally, Andro-driven inhibition of the NLRP3 inflammasome and amelioration of murine models for colitis and CAC were significantly blocked by BECN1 knockdown, or by various autophagy inhibitors. Taken together, our findings demonstrate that mitophagy-mediated NLRP3 inflammasome inhibition by Andro is responsible for the prevention of CAC. Our data may help guide decisions regarding the use of Andro in patients with inflammatory bowel diseases, which ultimately reduces the risk of CAC.
Model-guided symbolic execution testing for network protocol binary software

Traditional symbolic execution for testing software focuses on exploring the paths of the program. However, for stateful network protocol, this method is hard to explore all the protocol states. This paper proposes a novel method based on model-guided symbolic execution, which can associate the program paths with the protocol states and utilize the protocol model to guide the test to explore interesting deep states of the protocol. This paper also presents a prototype system, S2EProtocol-MG, upon Selective Symbolic Execution (S2E) platform to test for network protocol binary software. To demonstrate S2EProtocol-MG's effectiveness, this paper employs it to detect vulnerabilities on several real-world network protocol software.
Toward a Global Consumer “Eco-orientation” Model: A Cross-national Perspective

ABSTRACT A third-order global consumer eco-orientation model is developed that captures similarities among cross-national consumers with different cultural and economic backgrounds. Two second-order constructs emerge. The first second-order construct, eco-notions, is conceptualized to capture intangible environmental notions. The other second-order construct, eco-actions, is conceptualized to capture tangible environmental actions. The systematic specification of the model sheds light on universal environmental concerns at the consumer level of three economy types. The model adds understanding of the value that cross-national consumers place on the environment. In the process of model specification, the foundational perspective of the properties associated with the multifactor eco-scale is challenged. The result is a new third-order, multidimensional model characterizing ecological concerns of cross-national consumers.
Web-Document Retrieval by Genetic Learning of Importance Factors for HTML Tags

In contrast to conventional documents, a Web document consists of a number of tags which provide hints on the structure of the documents. In this paper, we propose a Web-document retrieval method using the characteristics of HTML tags. This method learns the importance of tags from a training text set. We use a genetic algorithm for learning the importance weights. We also present a modi ed similarity measure which uses the tag information. Experiments have been performed on the TREC document collection consisting of 247,491 documents. Compared to the traditional IR method, the proposed method has achieved 15% improvement in average precision.
The effects of capsaicin and capsaicinoid analogs on metabolic molecular targets in highly energetic tissues and cell types

There is increasing interest in dietary chemicals that may provide benefits for pathologies such as diabetes and obesity. Capsaicinoids found in chili peppers and pepper extracts, are responsible for the “hot” or “spicy” sensation associated with these foods. Capsaicinoid consumption is also associated with enhanced metabolism, making them potentially therapeutic for metabolic disease by promoting weight loss. This review summarizes much of the current experimental evidence (ranging from basic to applied investigations) of the biochemical and molecular metabolic effects of capsaicinoids in metabolically significant cell types. Along with influencing metabolic rate, findings demonstrate capsaicinoids appear to alter molecular metabolic signaling, regulate hunger and satiety, blood metabolites, and catecholamine release. Notably, the majority of the experiments summarized herein utilized isolated supplemental or research grade capsaicinoids rather than natural food sources for experimental interventions. Additional work should be conducted using primary food sources of capsaicin to explore pharmacological, physiological, and metabolic benefits of both chronic and acute capsaicin consumption. © 2016 BioFactors, 42(3):229–246, 2016
Human friendship favours cooperation in the Iterated Prisoner's Dilemma

In the last decades, many studies have attempted to analyse the factors that may favour the evolution of cooperation. Among unrelated individuals, cooperation is expected to occur when partners exchange altruistic acts one another (i.e., reciprocity) or when the donor of an altruistic act may obtain secondary benefits from the act (e.g., increased reputation). The iterated prisoner's dilemma (IPD) is frequently used to analyse cooperation between two players. In this game, cooperation is constantly at risk of exploitation. Therefore, previous knowledge of the other player's attitude towards cooperation may positively affect an individual's decision to cooperate during the game. In various social species (including humans), group members may form friendly relationships that reduce uncertainty about the partner response and increase the mutual exchange of benefits. In light of this, we analysed whether humans cooperate more when playing an IPD with a friend than with a stranger. Each subject played an IPD twice, with a friend and a stranger, and had £10 per round to donate or not to the other player. Our results evidenced that humans cooperate more with, and donate more money to the other player when playing with a friend than with a stranger. Moreover, in game two subjects playing with unfamiliar players followed a raise the stakes strategy (RTS), i.e. they donated more money as the game progressed. The sense of trust in the other player's willingness to reciprocate the altruistic act is probably an important pre-requisite favouring cooperation and it may explain the differences between friends and unfamiliar players. The use of a RTS strategy in game two, however, indicates that subjects were attempting to increase the level of cooperation with unfamiliar players. These findings are consistent with the observation that friendship (and the capacity to build cooperative relationships) may be beneficial to individuals in many social animals and in humans.
Age-related and thymus-dependent rejection of adenovirus 2-transformed cell tumors in the Syrian hamster.

Adenovirus type 2-transformed hamster cell-induced newborn tumor lines were usually rejected when transplanted s.c. into 21-day-old syngeneic, weanling hamsters. The tumor-inducing capacity of two of these lines (Ad2HTL3 and Ad2HTL6) was tested in intact and neonatally thymectomized hosts. After s.c. injection of suspensions prepared from these lines, none of the weaning hamsters developed tumors while 100% of the newborns and 35.2% of neonatally thymectomized, weanling hamsters developed progressively enlarging neoplasms. The susceptibility of neonatally thymectomized hamsters to tumor challenge was directly related to the degree of immunosuppression observed following thymectomy as indicated by the amplitude of the in vitro response of blood leukocytes to concanavalin A. Pretreatment of thymectomized weanlings with syngeneic adult lymphoid cells (i.p.) resulted in a significant reduction in tumor susceptibility (p = 0.03). These findings suggest that acquisition of resistance to adenovirus type 2-transformed cells during the first 21 days of life may be a thymus-dependent cellular immune process.
Offset Encoding for Multiple-Access Relay Channels

An offset encoding technique is presented that improves sliding-window decoding with decode-and-forward for K-user multiple-access relay channels. The technique offsets user transmissions by one block per user and achieves the corner points of the destination's backward decoding rate regions but with a smaller delay. As a result, one achieves boundary points of the best known decode-and-forward rate regions with a smaller delay than with backward decoding.
Psychophysiological Responses to Salsa Dance

Speculation exists whether dance provides physiological stimuli adequate to promote health and fitness benefits. Unfortunately, research to date has not addressed the affective and exertional responses to dance. These responses are of interest as positive affective and exertional responses experienced during physical activity may play an important role in predicting adherence. The present study aims to examine the psychophysiological responses of different Salsa dance styles. Ten pairs of dancers performed two different structured lessons of Salsa dance, including Typical Salsa and Rueda de Casino lessons, and a non-structured Salsa dance at a night club. Physiological responses (i.e., percent of heart rate reserve; %HRR) were continuously assessed and perceived exertion and affective valence were rated every 15 min throughout the trials. %HRR responses differed between the Salsa dance styles (%HRR from 41.3 to 51.9%), and participants were dancing at intensities near their ventilatory threshold. Specifically, Typical Salsa lesson elicited lower %HRR responses than Rueda de Casino lesson (p < 0.05), but similar %HRR responses to Salsa dance at a night club condition (p > 0.05). Surprisingly, exertional (from 8 to 11) and affective (from +3 to +5) responses were unaffected by Salsa dance styles (p > 0.05). These data support that different Salsa dance styles provide physiological stimuli adequate to promote health and fitness benefits, and perhaps more importantly, produce pleasurable experiences, which in turn might lead to an increase in adherence to Salsa dancing which likely provides exercise-like health benefits.
Response-based Learning for Machine Translation of Open-domain Database Queries

Response-based learning allows to adapt a statistical machine translation (SMT) system to an extrinsic task by extracting supervision signals from task-specific feedback. In this paper, we elicit response signals for SMT adaptation by executing semantic parses of translated queries against the Freebase database. The challenge of our work lies in scaling semantic parsers to the lexical diversity of opendomain databases. We find that parser performance on incorrect English sentences, which is standardly ignored in parser evaluation, is key in model selection. In our experiments, the biggest improvements in F1-score for returning the correct answer from a semantic parse for a translated query are achieved by selecting a parser that is carefully enhanced by paraphrases and synonyms.