Miracle-dz/UniFAR-FTUs huggingface dataset:
Ant Colony Optimization for resource sharing among D2D communications

Device-to-Device (D2D) communication has been recently devised as a new paradigm that boosts spectrum reuse inside a cell, leading to enhanced quality of service and user experience. The design of proper D2D resource allocation schemes, which constitute the enablers towards this direction, is an open challenge. In this paper, we propose a D2D resource allocator based on the Ant Colony Optimization (ACO) theory. ACO is exploited towards identifying interference isolated D2D links that can safely share the same resources, consulting a graph representation of the network. Simulation studies demonstrate the self-learning nature of this method, which results to a comparable performance to that of an optimal resource allocator of significantly higher computational complexity.
The 'policy-preferences model' : a new perspective on how researchers can facilitate the take-up of evidence by educational policy makers

The phrase ‘knowledge adoption’ refers to the often-complicated process by which policy makers ‘take on board’ evidence. While models have been put forward to explain this activity, this paper argues that such models are flawed and fail to fully address those complexities affecting the successful realisation of knowledge adoption efforts. Existing frameworks are examined, critiqued and an alternative, sociologically based approach presented. It is argued that this alternative conceptualisation provides a more effective account of the knowledge adoption process. The paper illustrates how this model has been tested and examines its implications for both research impact and evidence-informed policy making.
Using Self-Organizing Feature Maps and Data Mining to Analyze Liability Authentications of Two-Vehicle Traffic Crashes

In this study, both self-organizing feature maps and data mining models were generated for analysis of liability authentications of two-vehicle crashes, respectively, to evaluate their applicability on such an application. Factors critical to crash liability attributions were theoretically selected through Chi square test and F test. Meanwhile, factors considered important to committee members of government founded authentication committees in Taiwan were identified using fuzzy Delphi process. Factors commonly appeared in both theoretical results and practical opinions were considered truly critical in this study. Data mining models and self- organizing feature maps models were then generated with identified critical factors and associated liability attribution results of selected crash cases, for frontal, side, and rear collisions of two vehicle crashes, in an attempt to provide appropriate tools for decision support on crash liability authentications. Nine factors, viz. right-of-way, perception, speeding, lane changing, signal status, maneuver, irregularity, mutual position, and perception distance were identified critical. Data mining models can give 60 ~ 83% accurate liability authentications, yet are incapable of giving specific liability attributions corresponding to crash cases. As to SOM models, acceptable silhouette coefficient indicate that generated models can allocate cases to adequate clusters. Meanwhile, qualities of clustering were confirmed by calculated high grey relational coefficients. Although with small data size, a combination of data mining and SOM models were considered to be able to give reasonably good liability attributions predictions and references on given crash cases.
Personality Traits, Music Preferences and Depression in Adolescence

ABSTRACT This six-month longitudinal study was conducted with 311 adolescents and verifies: (1) if music preferences can predict depression; (2) if personality traits can predict music preferences; (3) if music listening can represent a protective factor against depression. Results indicate that Soul music listening (e.g., hip hop, R&B) is a predictor of lower depression levels in adolescent girls. Personality dimensions from the Big Five reveal various predictive relations with music preferences, for instance Openness predicts music eclecticism. Soul music listening is a moderator of the predictive relationship between Neuroticism and depression levels in adolescent girls, thus pointing to a possible protective effect. Research paths for studies on music and adolescent development, personality traits, and evolutionary psychology are succinctly discussed.
Booster: A WWW-based prototype of the global software highway

A framework for globally distributed software development and management environments, which we call Booster is presented. Additionally, the first experiences with WebMake, an application developed to serve as an experimental platform for a software development environment based on the World Wide Web and the Booster framework is introduced. Booster encompasses the basic building blocks and mechanisms necessary to support a truly cooperative distributed software development from the very beginning to the last steps in a software life cycle. It is thus a precursor of the Global Software Highway, in which providers and users can meet for the development, management, exchange and usage of all kind of software. <<ETX>>
The research of relationship benefits management strategy: Based on customer sex types preference

In recent years, as the relationship marketing becomes an important part of enterprises' marketing activities, more enterprises start to take seriously to the relationship with the customers, based on this, there comes the concept of relationship benefits. Scholars believe that the establishment of strong customer relationship should be an important means for an enterprise to gain competitive advantage. Enterprises hope the customers can take the largest benefits from the relationship. Customer sex types have significant correlation with relationships, different sex types customers have different benefits preference. This paper firstly explores the basic dimensions of relationship benefits in services markets based on literature review for the past years, then analyzes the relationship benefits preference of different sex type customers. Finally, this paper proposes a relationship benefits management strategy. The findings of this paper are directions for future research and managerial implications.
Shielding effect on secondary cosmic-ray neutron- and muon-induced soft errors

Transports of secondary cosmic-ray neutrons and muons in a building and a stacked server are simulated by Particle and Heavy Ion Transport code System (PHITS) with considering distributions of energy and zenith-angle of secondary cosmic-rays by PHITS based analytical radiation model in the atmosphere (PARMA) model. The calculated neutron fluxes are in surprisingly good agreement with measured data. Soft errors in an n-type metal-oxide-semiconductor field-effect transistor caused by secondary cosmic-ray neutron and muon in the open air and on the first floor of the building are analyzed based on the multiple sensitive volume (MSV) model using PHITS. It is found that the secondary cosmic-ray neutron-induced SER decrease by shielding effect of the building while that caused by secondary cosmic-ray muons is not affected.
Comparing leading theoretical models of behavioral predictions and post-behavior evaluations

This study aimed at comparing the predictive power of the Theory of Planned Behavior (TPB), the Model of Goal-Directed Behavior (MGB), and the Extended Model of Goal-Directed Behavior (EMGB) for observed and self-reported behaviors concerning consumer nondurables. More specifically, the three models were compared in terms of their predictive power for intention and for behavioral desire (only MGB and EMGB). Additionally, the validity of four different models for predicting post-behavior evaluations was examined. Results showed that the EMGB is the most powerful in predicting both intention and behavioral desire. Moreover, results revealed that, as expected, all three models showed a better predictive power for SRB than for observed behavior. Finally, results demonstrated that post-behavior evaluations are both online and memory-based. ©2008 Wiley Periodicals, Inc.
Racial/Ethnic differences in the association between college attendance and heavy alcohol use: a national study.

OBJECTIVE This study examined racial/ethnic differences in the association between college attendance and heavy alcohol use and factors that may underlie this relationship. METHOD Interview data collected from 12,993 young adults who participated in the National Longitudinal Study of Adolescent Health were analyzed to determine if 4- or 2-year college status is differentially associated with heavy alcohol use for five racial/ethnic groups (white, black, Hispanic, Asian, Other) and to assess the explanatory value of selected social and psychological factors. RESULTS Four-year college status was positively associated with heavy alcohol use among white young adults but inversely related to heavy drinking among blacks and Asians. Two-year college status also was inversely associated with heavy drinking among blacks, Hispanics and Others. Among whites, the association between 4-year college attendance and heavy drinking was partially explained by living away from parents, friends' heavy drinking and time socializing with friends. Among blacks, the inverse relationship between college attendance and heavy alcohol use was partially explained by lower levels of friends' heavy drinking, depression and delinquency. Friends' heavy drinking also partially explained observed relationships between college attendance and heavy drinking among Asians and Others. CONCLUSIONS Four-year college attendance increases the likelihood of heavy alcohol use among white young adults but may decrease the likelihood of heavy drinking among blacks and Asians. Two-year college attendance also may reduce the risk for heavy drinking among blacks, Hispanics and young adults who are Native American or multi-ethnic. Social and psychological factors partly explain these relationships and also differ for racial/ethnic groups.
Disturbed development of the enteric nervous system after in utero exposure of selective serotonin re-uptake inhibitors and tricyclic antidepressants. Part 2: Testing the hypotheses.

AIMS Antidepressant use has increased in the last decade. Several studies have suggested a possible association between maternal antidepressant use and teratogenic effects. METHODS The pharmacy prescription database IADB.nl was used for a cohort study in which laxative and antidiarrhoeal medication use in children after in utero exposure to antidepressants (TCA, SSRI, fluoxetine or paroxetine exposed) was compared with no antidepressant exposure. Laxatives and antidiarrhoeal medication use were applied as a proxy for constipation and diarrhoea respectively, which may be associated with disturbed enteric nervous system (ENS) development. RESULTS Children exposed in utero to SSRIs (mainly fluoxetine and paroxetine) in the second and third trimester or to TCAs in the first trimester, more often received laxatives. Combined exposure to TCAs and SSRIs in pregnancy was associated with a 10-fold increase in laxative use. In utero exposure to SSRIs is not associated with antidiarrhoeal medication use compared with non-exposed children. In contrast, antidiarrhoeal medication use was significantly higher in children exposed to TCAs anytime in pregnancy. CONCLUSIONS The increased laxative use after second and third trimester exposure to SSRIs might be explained through the inhibitory effect of the serotonin re-uptake transporter (SERT) and because of selectivity for the 5-HT(2B) receptor which affects the ENS. TCA exposure during the first trimester leads to increased laxative use probably through inhibition of the norepinephrine transporter (NET). Exposure of TCAs anytime in pregnancy leads to increase diarrhoeal use possibly through down-regulation of α₂-adrenoceptors or up-regulation of the pore forming α(1c) subunit.
The Development of Anxiety Symptoms in Adolescents

markdownabstract__Abstract__ Anxiety symptoms predict the onset of anxiety disorder and depression, and have been associated with lower levels of well-being even before they reach disorder status. Adolescence is a primary period of interest when it comes to anxiety research, since anxiety disorders most commonly have their onset at an early age, and they are the most frequent mental health problem in children and adolescents. The aim of this thesis is to further our knowledge of the development of anxiety symptoms from late childhood into young adulthood. I used data from the TRacking Adolescents’ Individual Lives Survey (TRAILS), a longitudinal cohort study of children and adolescents (N=2,230) from the general population in the Netherlands. Specifically, we investigated risk factors for the development of panic attacks in adolescence, since the incidence of panic attacks increases dramatically during adolescence. We found that a wide spectrum of Internalizing and Externalizing Problems at age 10-12 years was associated with an increased risk of experience of a panic attack in adolescence, but only Social Problems had a unique association with onset of panic attacks. Furthermore, we examined the relation between pubertal timing (the timing of pubertal development in relation to peers) and anxiety symptoms. We found that in boys, the relation between pubertal timing and anxiety symptoms was age-dependent, while in girls, pubertal timing was not associated with anxiety symptoms. Lastly, we also studied anxiety symptoms in relation to sleep problems. We found that sleep problems and anxiety symptoms hold a direct bidirectional longitudinal association in early adolescence, while later in adolescence, anxiety symptoms still predicted sleep problems, but sleep problems no longer significantly predicted anxiety symptoms. Additionally, we found that the association between anxiety symptoms at age 10-12 and sleep problems at age 12-15 was moderated by parasympathetic reactivity. Two main conclusions of this thesis are (1) that even mild anxiety symptoms are associated with other health predictors and outcomes and (2) that we oversimplify reality if we disregard the possibility of dynamic relations of predictors and outcomes with anxiety symptoms during adolescence.
The Well-Being of African American Adolescents Within Formal and Informal Adoption Arrangements

Abstract This study assessed the well-being of African American adolescents in formal (n = 67) and informal (n = 194) adoption arrangements using Waves I and III of the National Longitudinal Study of Adolescent Health (Add Health). Controlling for demographic and early risk factors, the outcomes of adolescents in the two adoption groups were more similar than different. Adoption type was not a statistically signifi-Investigators gratefully acknowledge support provided by grant HD36479 from the National Institute of Child Health and Human Development, to Brent C. Miller, P.I. , through a Minority Supplement to Priscilla A. Gibson, University of Minnesota. cant predictor for nine of eleven indicators of adolescent well-being. Significant differences were found on only two indicators: anti-social behavior and adolescents' perception of how much their caregivers and family care about them. Informally adopted youth had more favorable outcomes on these indicators, although the effect sizes were small. Implications of this study are forwarded for policy and practice in child welfare.
Collaborative Data and Information Processing for Target Tracking In Wireless Sensor Networks

In this paper, we present the development of data and information processing algorithms for target tracking in wireless sensor networks. Firstly, we propose a collaborative data and information processing framework and describe hierarchical sensor network architecture. Then we design the novel particle filter (PF) based tracking algorithms. By using Gaussian mixture model (GMM), we develop the distributive particle filter based tracking algorithms. Finally, we present the simulation results.
Counterfactual Choice and Learning in a Neural Network Centered on Human Lateral Frontopolar Cortex

Decision making and learning in a real-world context require organisms to track not only the choices they make and the outcomes that follow but also other untaken, or counterfactual, choices and their outcomes. Although the neural system responsible for tracking the value of choices actually taken is increasingly well understood, whether a neural system tracks counterfactual information is currently unclear. Using a three-alternative decision-making task, a Bayesian reinforcement-learning algorithm, and fMRI, we investigated the coding of counterfactual choices and prediction errors in the human brain. Rather than representing evidence favoring multiple counterfactual choices, lateral frontal polar cortex (lFPC), dorsomedial frontal cortex (DMFC), and posteromedial cortex (PMC) encode the reward-based evidence favoring the best counterfactual option at future decisions. In addition to encoding counterfactual reward expectations, the network carries a signal for learning about counterfactual options when feedback is available—a counterfactual prediction error. Unlike other brain regions that have been associated with the processing of counterfactual outcomes, counterfactual prediction errors within the identified network cannot be related to regret theory. Furthermore, individual variation in counterfactual choice-related activity and prediction error-related activity, respectively, predicts variation in the propensity to switch to profitable choices in the future and the ability to learn from hypothetical feedback. Taken together, these data provide both neural and behavioral evidence to support the existence of a previously unidentified neural system responsible for tracking both counterfactual choice options and their outcomes.
Smooth talking: Articulatory join costs for unit selection

Join cost calculation has so far dealt exclusively with acoustic speech parameters, and a large number of distance metrics have previously been tested in conjunction with a wide variety of acoustic parameterisations. In contrast, we propose here to calculate distance in articulatory space. The motivation for this is simple: physical constraints mean a human talker's mouth cannot "jump" from one configuration to a different one, so smooth evolution of articulator positions would also seem desirable for a good candidate unit sequence. To test this, we built Festival Multisyn voices using a large articulatory-acoustic dataset. We first synthesised 460 TIMIT sentences and confirmed our articulatory join cost gives appreciably different unit sequences compared to the standard Multisyn acoustic join cost. A listening test (3 sets of 25 sentence pairs, 30 listeners) then showed our articulatory cost is preferred at a rate of 58% compared to the standard Multisyn acoustic join cost.
Dynamic rebinding for marshalling and update, via redex-time and destruct-time reduction

Abstract Most programming languages adopt static binding, but for distributed programming an exclusive reliance on static binding is too restrictive: dynamic binding is required in various guises, for example, when a marshalled value is received from the network, containing identifiers that must be rebound to local resources. Typically, it is provided only by ad hoc mechanisms that lack clean semantics. In this paper, we adopt a foundational approach, developing core dynamic rebinding mechanisms as extensions to the simply typed call-by-value λ calculus. To do so, we must first explore refinements of the call-by-value reduction strategy that delay instantiation, to ensure computations make use of the most recent versions of rebound definitions. We introduce redex-time and destruct-time strategies. The latter forms the basis for a λmarsh calculus that supports dynamic rebinding of marshalled values, while remaining as far as possible statically typed. We sketch an extension of λmarsh with concurrency and communication, giving examples showing how wrappers for encapsulating untrusted code can be expressed. Finally, we show that a high-level semantics for dynamic updating can also be based on the destruct-time strategy, defining a λupdate calculus with simple primitives to provide type-safe updating of running code. We show how the ideas of this simple calculus extend to more real-world, module-level dynamic updating in the style of Erlang. We thereby establish primitives and a common semantic foundation for a variety of real-world dynamic rebinding requirements.
A Network-Flow Based Cell Sizing Algorithm

We propose a timing-driven discrete cellsizing algorithm that can incorporate total cell size constraints. We model cell sizing as a min-cost network flow problem. In the network flow graph, available sizes of each cell are modeled as nodes. Flow passing through a node indicates the choice of the corresponding cell size, and the total flow cost reflects the timing objective function value change with the chosen sizes of cells. Compared to other discrete optimization methods for cell sizing, our method can obtain a near-optimal solution in a very timeefficient manner. We tested our algorithm on the ISCAS’85 benchmark, and compared our results with an optimal solution produced by an exhaustive search method with exponential time complexity. The results show that given the same initial sizing, the improvement obtained by our method is only 1% worse (11.9% v.s. 12.9%) than the optimal solution, while satisfying a given total cell area constraint. Furthermore, our method is 60 times faster than the optimal method.
East Meets West

This study allows a better understanding of the multifaceted and richly blended nature of tangible and intangible cultural appeal co-created from both indigenous and Western cultural traditions that tourists seek in postcolonial destinations. It showcases an example of how two dominant cultures coexist and co-create a unique symbiotic hybrid culture that tourists like. It also draws upon Goossens’s hedonic tourism motivational model by linking cultural travel motivation, destination constraints, cultural interest, and hedonic responses. It further explores the moderating effect of past travel experience on the mediating role of cultural interest. The findings suggest that postcolonial cultural interest depends on tourists’ origin, while the effects of destination constraints on cultural interest and the effect of cultural travel motives on cultural satisfaction are contingent on past travel experience.
CanalSense: Face-Related Movement Recognition System based on Sensing Air Pressure in Ear Canals

We present a jaw, face, or head movement (face-related movement) recognition system called CanalSense. It recognizes face-related movements using barometers embedded in earphones. We find that face-related movements change air pressure inside the ear canals, which shows characteristic changes depending on the type and degree of the movement. We also find that such characteristic changes can be used to recognize face-related movements. We conduct an experiment to measure the accuracy of recognition. As a result, random forest shows per-user recognition accuracies of 87.6% for eleven face-related movements and 87.5% for four OpenMouth levels.