Miracle-dz/UniFAR-FTUs huggingface dataset:
Scaling the Revised PSVT-R: Characteristics of the First-Year Engineering Students' Spatial Ability

Past literature in engineering education has generally agreed that spatial ability plays a crucial role in determining students’ achievement in engineering courses, especially graphic and design courses. While various spatial tests are available, the Purdue Spatial Visualization Tests: Visualization of Rotation (PSVT:R) has been commonly used to predict students’ success in the engineering field for more than three decades. However, little attention had been given to the validity of the PSVT:R in measuring spatial ability. Therefore, the purpose of this study was twofold: (a) to characterize the itemand test-level functions of the Revised PSVT:R for incoming first-year engineering (FYE) students based on two fundamental measurement frameworks: Classical Test Theory (CTT) and Item Response Theory (IRT); and (b) to investigate its relationship with academic-related variables to provide validity evidence. Approximately 600 freshmen enrolled in the fall 2010 FYE Program in a large Midwestern public university completed the Revised PSVT:R. Students’ academic performance, such as SAT/ACT subject scores and high school core GPA, were retrieved from the university archives along with students’ demographic backgrounds. The results indicated that the revised PSVT:R measures a unidimentional subcomponent of spatial ability and the scores are reliable for measuring spatial visualization ability of FYE students. They also indicated that the test is relatively easy for this population.
Sensitivity of satellite microwave and infrared observations to soil moisture at a global scale: Relationship of satellite observations to in situ soil moisture measurements

[1] This study presents a systematic and integrated analysis of the sensitivity of the available satellite observations to in situ soil moisture measurements. Although none of these satellites is optimized for land surface characterization, before the launches of the SMOS- and HYDROS-dedicated missions they are the only potential sources of global soil moisture measurements. The satellite observations include passive microwave emissivities, active microwave scatterometer data, and infrared estimates of the diurnal amplitude of the surface skin temperature. The Global Soil Moisture Data Bank provides in situ soil moisture measurements in five separate regions. This simultaneous analysis of various satellite observations and the large amount of in situ measurements has two major advantages. First, this analysis helps identify and separate the physical mechanisms that affect the satellite observations. For example, we show that the passive microwave polarization differences at 19 GHz and above are essentially sensitive to the vegetation and not to the soil moisture (i.e., the correlation between microwave observations and soil moisture is only indirect and comes from the statistical correlation between vegetation and soil moisture). Second, this analysis enables an objective comparison of the relative potential of the various satellite observations for soil moisture retrieval when other conditions are held constant. The second part of this study benefits from this synthesis to derive a relationship between satellite observations and soil moisture at a global scale.
Mindfulness as substitute for transformational leadership

Purpose Transformational leaders spark the intrinsic motivation of employees, thereby stimulating their extra-role performance. However, not all employees are lucky enough to have a transformational leader. The purpose of this paper is to investigate to what extent mindfulness can function as a substitute for transformational leadership. By being attentive to and aware of what is taking place in the present, mindfulness provides employees with a source of intrinsic motivation that lies within the person, thereby possibly making employees less dependent on transformational leadership. Design/methodology/approach An online survey was used to collect data of 382 employees working in diverse sectors in the Netherlands. Findings Moderated mediation analyses indicated that mindfulness partly compensates for a low levels of transformational leadership in fostering intrinsic motivation and in turn extra-role performance, thereby providing evidence for the substitutes for leadership theory. Moreover, the findings extend previous research on the contribution of mindfulness to in-role performance by showing its additional value for intrinsic motivation and extra-role performance. Research limitations/implications Despite the use of validated measures and the presence of an interaction effect, common-source bias cannot be out ruled completely. Practical implications Since mindfulness can be developed, the results suggest a training intervention to make employees less dependent on their leaders for their motivation. Originality/value This paper is the first to show that mindful people are more resilient against the absence of transformational leadership. Given the frequent changes in management layers in organizations, knowledge about resources for individual resilience and self-management is sorely needed.
Social agents: The first generations

Embodied Conversational Agents can be viewed as spoken dialogue systems with a graphical representation of a human body. But the embodiment is not the only difference. Whereas Spoken Dialogue Systems are mostly focused on computing the linguistic dimensions of communication, conversational agents are conceived as intelligent agents that have an identity, a persona. Thus, cognitive modeling is often more involved in ECAs including the modeling of emotion. Whereas spoken dialogue systems are focused on the task, virtual humans are also equipped with social skills involved in interaction. This can take various forms. In this paper we review some of the approaches that have been taken in the first decade of ECA research, by presenting the social signaling skills of three agents we have developed in our group.
Do Formal Contracts and Relational Governance Function as Substitutes or Complements

While transaction cost economists have generally argued that hazardous exchange conditions warrant complex contracts or vertical integration, other scholars have argued that trust or relational forms of governance effectively support exchange. These scholars view relational governance as a substitute for complex, explicit contracts. Indeed, some have suggested that contracts directly undermine the evolution of trust in exchanges. We advance and empirically test the alternative argument that formal contracts and relational governance are complements. Rather than hindering or replacing relational governance, contracts may promote the formation of long-term, trusting exchange relations. Using data from a sample of exchanges in information services, we find empirical support for the proposed complementary relationship.
CD68 reactivity of non-macrophage derived tumours in cytological specimens.

AIMS--To investigate the presence of the macrophage associated antigen CD68 in non-haematopoietic tumours. METHODS--Cytological specimens from non-macrophage derived tumours were stained using the alkaline phosphatase anti-alkaline phosphatase immunocytochemical method (APAAP) and three monoclonal anti-CD68 antibodies, Y1/82A, EBM11, and KP1. RESULTS--Reactivity of malignant cells with one or more of the antibodies was seen in 11 out of 40 adenocarcinomas and in one of seven poorly differentiated carcinomas; other neoplasms, including 10 cases of squamous carcinoma, three of malignant melanoma, and four of oat cell carcinoma were negative. Monoclonal antibody KP1 gave the strongest staining and reacted with the highest proportion of neoplastic cells. CONCLUSIONS--CD68 is expressed in a proportion of epithelial tumours although the labelling is usually less intense than in macrophages. Anti-CD68 antibodies should therefore be used as part of a panel in the diagnosis of poorly differentiated neoplasms in cytological material.
On the average spectral efficiency of interference-limited full-duplex networks

This paper studies how dense deployments of small cells with full duplex technology perform under various network configurations and channel conditions. The resulting interference at the receiver of interest combines both its intrinsic self-interference and components from co-channel base stations and user equipment transmissions. Network deployment is represented by a Poisson field of transmitters, while a composite channel with log-normal shadowing and Nakagami-m fading describes our propagation model. Herein, a stochastic geometry framework is used to first characterize the interference profiles for the full duplex scenarios under consideration, and then derive closed-form expressions for the Average Spectral Efficiency (ASE). Results show that the Self-Interference (SI) dominates the aggregate interference component and Full-Duplex (FD) networks outperform Half-Duplex (HD) networks in terms of ASE for SI cancellation values lower than -70dB.
Image segmentation and object recognition by Bayesian grouping

We propose a Bayesian grouping approach for recognition and segmentation of large-scale structures representing objects in images. It is based on detection of local image properties, extraction of simple geometrical primitives, and grouping these primitives according to probability rules and prior models. As opposed to the various template matching techniques, our method does not rely on a fixed set of input data to generate the prior with a maximum likelihood. Instead, it selects a list of subsets of the local primitives and finds the optimum set of model priors that maximizes the likelihood of the model samples representing the selected subsets. In contrast with global recognition methods that classify the whole image, our approach aims at solving the recognition task together with the segmentation task. As an illustration we give a medical data example of feature grouping in 2D images involving vessel detection from local ridges.
Predicting self-efficacy in test preparation: Gender, value, anxiety, test performance, and strategies

ABSTRACT Considerable evidence indicates that self-efficacy, task value, anxiety, and the use of language learning strategies are related. However, there is currently an insufficient understanding about their relations in high-stakes testing contexts. The author aimed to investigate how well social factors, test value, anxiety, test performance, and learning strategies predict high school students' self-efficacy in preparing for the English listening test as part of the University Entrance Examination in Taiwan. This research involved a large-scale questionnaire survey and a collection of students' English test scores. The participants were 636 students in Grade 12 of high school in Taiwan. A quantitative analysis of the questionnaire was conducted via hierarchical regression analysis. The results show that students' recent English test performance and test anxiety were two strong predictors of self-efficacy in preparing for the high-stakes test. In addition, resource management and metacognitive listening strategies had better predictive power over prior English level and test value.
Arguments for exception in US security discourse

In his influential State of Exception, Giorgio Agamben proposes that, even in apparently liberal western democracies, the state will routinely use the contingency of national emergency to suspend civil liberties and justify expansion of military and police powers. We investigated rhetorical strategies deployed in the web pages of US security agencies, created or reformed in the aftermath of the 9/11 events, to determine whether they present argumentation conforming to Agamben’s model. To expose rhetorical content, we examined strategies operating at two levels within our corpus. Argument schemes and underlying warrants were identified through close examination of systematically selected core documents. Semantic fields establishing themes of threat and danger were also explored, using automatic corpus tools to expose patterns of lexical selection established across the whole corpus. The study recovered evidence of rhetoric broadly consistent with the logic predicted by State of Exception theory, but also presented nuanced findings whose interpretation required careful re-appraisal of core ideas within Agamben’s work.
Network Location and Risk of Human Immunodeficiency Virus Transmission among Injecting Drug Users: Results of Multiple Membership Multilevel Modeling of Social Networks

Background Despite the implementation of harm reduction program, some injecting drug users (IDU) continue to engage in high-risk behaviors. It seems that there are some social factors that contribute to risk of human immunodeficiency virus (HIV) transmission in IDUs. The aim of this study was to analysis the social network of IDUs and examines the effect of network location on HIV transmission risk using the multiple membership multilevel models. Methods From October 2013 to March 2014 we conducted face-to-face interviews on 147 IDUs. We asked participants to nominate up to 20 people whom they had more than causal contact with them during the last month and specify if each nominee is drug injector or not. We defined four Network locations as Core and Peripheries of main components. The risk of HIV transmission for each individual was measured based on 7 items scale. We applied Multiple Membership Multilevel Linear Regression analysis to examine the relationship between network location and HIV transmission risk. We used Stata and UCINET software’s for the analysis of data. Findings The mean age of participants was 37 ± 9.32. Most of the individuals were male, single and educated up to guidance school. Being a core member of the main component as like as being a member of other small components in comparison with Isolates/unlinked significantly increased the HIV Transmission risk. Engagement in methadone maintenance therapies (MMT) was associated with a decrease in HIV transmission score. Conclusion Network analysis is a useful guide to find the most influential members of IDUs network and may have a complementary role for harm reduction program. The efficacy of interventions programs can be reinforced by addressing them to core individuals within the network. Furthermore, it provides the harm reduction staff to find the broader number of IDUs who are usually hard to reach by routine outreach case-finding tasks.
Embedding online patient record access in UK primary care: a survey of stakeholder experiences

Objectives To explore the integration of online patient Record Access within UK Primary Care, its perceived impacts on workload and service quality, and barriers to implementation. Design Mixed format survey of clinicians, administrators and patients. Telephone interviews with non-users. Setting Primary care centres within NHS England that had offered online record access for the preceding year. Participants Of the 57 practices initially agreeing to pilot the system, 32 had adopted it and 16 of these returned questionnaires. The 42 individual respondents included 14 practice managers, 15 clinicians and 13 patients. Follow-up interviews were conducted with one participant from 15 of the 25 non-adopter practices. Results Most professionals believed that the system is easy to integrate within primary care; while most patients found it easy to integrate within their daily lives. Professionals perceived no increase in the volume of patient queries or clinical consultations as a result of Record Access; indeed some believed that these had decreased. Most clinicians and patients believed that the service had improved mutual trust, communication, patients' health knowledge and health behaviour. Inhibiting factors included concerns about security, liability and resource requirements. Non-adoption was most frequently attributed to competing priorities, rather than negative beliefs about the service. Conclusions Record access has an important role to play in supporting patient-focused healthcare policies in the UK and may be easily accommodated within existing services. Additional materials to facilitate patient recruitment, inform system set-up processes, and assure clinicians of their legal position are likely to encourage more widespread adoption.
A Comparison Between Signature and GP-Based IDSs for Link Layer Attacks on WiFi Networks

Data link layer attacks on WiFi networks are known to be one of the weakest points of WiFi networks. While these attacks are very simple in implementation, their effect on WiFi networks can be devastating. To this end, several intrusion detection systems (IDS) have been employed to detect these attacks. In this paper, we compare the ability of Snort-Wireless and a genetic programming (GP) based intrusion detector, in the detection of a particular data link layer attack, namely the deauthentication attack. We focus particularly on a scenario where the attacker stealthily injects the attack frames into the target network. Results show that the GP based detection system is much more robust against the different versions of the attack compared to Snort-Wireless and can achieve a detection rate in average 100% and a false positive rate in average 0.1%
Supporting cross-modal collaboration in the workplace

We address the challenge of supporting collaborators who access a shared interactive space through different sets of modalities. This was achieved by designing a cross-modal tool combining a visual diagram editor with auditory and haptic views to allow simultaneous visual and non-visual interaction. The tool was deployed in various workplaces where visually-impaired and sighted coworkers access and edit diagrams as part of their daily jobs. We use our observations and analyses of the recorded interactions to outline preliminary design recommendations for supporting cross-modal collaboration.
Too Few Victims: Finding the Optimal Minimum Victim Threshold for Defining Serial Murder

Objective: Despite substantial interest in the topic, there remains no consensus on the definition of serial killing, particularly in terms of the minimum victim count. Whereas most scholars had settled on either a three-victim or four-victim minimum, the Federal Bureau of Investigation (FBI) decided a decade ago to lower the threshold down to just two murders. In this article we empirically examine the effect of lowering the threshold on the statistical profile of serial homicide and suggest what appears to be the optimal threshold based on distinguishing attributes. Method: A series of multinomial logistic regression analyses is used to compare two-victim, three-victim and four-victim offenders (as well as those who claimed even larger victim counts) on a variety of traits generally considered stereotypical of the serial killer. Results: Two-victim offenders differ significantly from all other serial killers in terms of motive, partnership, and crime scene behaviors, and arguably should not be pooled into a single population. Moreover, those who have slain between three and seven victims differ significantly in terms of these same characteristics from those who have killed eight or more. Conclusions: A minimum victim threshold of at least three should be used, separating potential or would-be serial killers from those who are characterized by more extreme levels of violent behavior. Furthermore, the population of serial killers can be subdivided into typical offenders claiming three to seven victims and their far more deadly counterparts with eight or more murders.
Fast and scalable list ranking on the GPU

General purpose programming on the graphics processing units (GPGPU) has received a lot of attention in the parallel computing community as it promises to offer the highest performance per dollar. The GPUs have been used extensively on regular problems that can be easily parallelized. In this paper, we describe two implementations of List Ranking, a traditional irregular algorithm that is difficult to parallelize on such massively multi-threaded hardware. We first present an implementation of Wyllie's algorithm based on pointer jumping. This technique does not scale well to large lists due to the suboptimal work done. We then present a GPU-optimized, Recursive Helman-JaJa (RHJ) algorithm. Our RHJ implementation can rank a random list of 32 million elements in about a second and achieves a speedup of about 8-9 over a CPU implementation as well as a speedup of 3-4 over the best reported implementation on the Cell Broadband engine. We also discuss the practical issues relating to the implementation of irregular algorithms on massively multi-threaded architectures like that of the GPU. Regular or coalesced memory accesses pattern and balanced load are critical to achieve good performance on the GPU.
Welfare and Employment: A European Dilemma?

The majority of the Member States of the European Union have undertaken remarkably comprehensive welfare and labor market reforms in the years since the 1990s. Many of these reforms, however, have not followed the conventional retrenchment and deregulation recipes, but rather took a liking to social pacts, activation, active ageing/avoidance of early retirement, part-time work, lifelong learning, parental leave, gender mainstreaming, flexicurity (balancing flexibility with security), reconciling work and family life. At first sight, these reforms seem to have resulted in relatively robust employment growth, especially for women and more recently older workers. European economic integration has fundamentally recast the boundaries of national systems of employment regulation and social protection, both by constraining the autonomy for domestic policy options but also by opening opportunities for EU-led social and employment coordination and agenda setting.
Peruse and Profit: Estimating the Accelerability of Loops

There exist a multitude of execution models available today for a developer to target. The choices vary from general purpose processors to fixed-function hardware accelerators with a large number of variations in-between. There is a growing demand to assess the potential benefits of porting or rewriting an application to a target architecture in order to fully exploit the benefits of performance and/or energy efficiency offered by such targets. However, as a first step of this process, it is necessary to determine whether the application has characteristics suitable for acceleration. In this paper, we present Peruse, a tool to characterize the features of loops in an application and to help the programmer understand the amenability of loops for acceleration. We consider a diverse set of features ranging from loop characteristics (e.g., loop exit points) and operation mixes (e.g., control vs data operations) to wider code region characteristics (e.g., idempotency, vectorizability). Peruse is language, architecture, and input independent and uses the intermediate representation of compilers to do the characterization. Using static analyses makes Peruse scalable and enables analysis of large applications to identify and extract interesting loops suitable for acceleration. We show analysis results for unmodified applications from the SPEC CPU benchmark suite, Polybench, and HPC workloads. For an end-user it is more desirable to get an estimate of the potential speedup due to acceleration. We use the workload characterization results of Peruse as features and develop a machine-learning based model to predict the potential speedup of a loop when off-loaded to a fixed function hardware accelerator. We use the model to predict the speedup of loops selected by Peruse and achieve an accuracy of 79%.