Miracle-dz/UniFAR-FTUs huggingface dataset:
Dispersal of an introduced larval cohort in a coastal lagoon

Patterns of larval dispersal influence the structure of marine biological communities, but many aspects of larval dispersal remain poorly understood. For example, much of our present understanding of larval dispersal is based on models that integrate aspects of physical oceanography and larval biology, but the predictions of those models are generally not tested because we lack the methodology for real‐time larval tracking. In the present study, we used both modeled and measured data to track an introduced larval cohort essentially from fertilization to presumed settlement. Larvae of the hard clam Mercenaria were released into a labeled water parcel in the Banana River Lagoon, Florida, within 8.5 h of nursery production and then were tracked for the duration of their estimated 8‐d pelagic life span. Comparisons of modeled versus measured larval distribution indicate that the fate of the larvae as predicted by a tracer model and by the concentration of coincidentally released sulfur hexafluoride (SF6) did not agree with the fate of the larvae as predicted by the path of subsurface drifters and by a particle trajectory model. Thus, modeled predictions of larval dispersal must be interpreted with care. Additionally, one component of larval dispersal that was observed in the study but that was not accounted for in the model was the spread of larvae along the path of advection. That trail of larvae may have important consequences for patterns of recruitment and resultant community structure, but it is not considered in most treatments of larval dispersal.
Perceived Organizational Discrimination. Its Societal Antecedents, Individual Outcomes, and the Effects of Organizational Culture across Contexts

Research has found that perceived discrimination leads to a range of negative outcomes across various contexts. In the societal context, it is associated with stress, mental health related issues, and a decrease in quality of life (Tummala-Narra et al., 2011). In the organizational level, it is negatively linked with psychological well-being, job satisfaction, job attitude, and turnover intention (Shaffer et al., 2000; Triana et al., 2015). Although there is an abundance of research looking into factors that mitigate the impact of perceived discrimination in the workplace, there is a lack of research that looks into the antecedents of perceived discrimination in an organizational context. This research project looked into the association of perceived discrimination between societal and organizational contexts, its impact on psychological well-being, and turnover intention. Furthermore, this research predicted that organizational culture (i.e. constructive culture norms, passive-defensive culture norms, aggressive-defensive culture norms) affects the association of perceived societal and organizational contexts. Overall, a weak but significant correlation was found on the relationship between perceived societal and organizational discrimination, but the culture of an organization did not impact the association of perceived discrimination between contexts. However, the culture of an organization made a contribution on predicting perceived discrimination in the workplace. Constructive culture norms were found to significantly reduce, while aggressive-defensive culture norms were found to significantly increase an individual’s perception of discrimination in the workplace; passive-defensive culture norms, on the other hand, did not have significant impact to predict perceived organizational discrimination. Consistent with previous literature, perceived discrimination in the workplace predicted an individual’s psychological well-being and turnover intention.
Digging behaviour and responses to photic and gravitational cues as elements of escape behaviour of bumblebees.

We have investigated escape behaviour of workers of two bumblebee species, Bombus terrestris and B. pascuorum, when confined to test tubes plugged with soil and either exposed to sunlight or kept in darkness. In both these situations B. terrestris performed better (i.e. escaped after a shorter time) than B. pascuorum. B. terrestris (but not B. pascuorum) also performed better in darkness than in tubes exposed to sunlight. This implies that in both situations B. terrestris showed higher readiness to dig than B. pascuorum, and that in tubes exposed to sunlight only B. terrestris showed high readiness to display photopositive behaviour as well. B. pascuorum displayed, however, photopositive behaviour in another escape situation: when released in a dark room in front of a vertical array of four sources of white light. In that situation, B. pascuorum also displayed the tendency to fly upwards, based most probably on responses to gravitational cues.
Career success of preschool teachers in Germany – the significance of the Big Five personality traits, locus of control, and occupational self-efficacy

ABSTRACT The career success of preschool teachers has been discussed to be important because it can be a precondition for the ability to provide a high-quality preschool education. Consequently, the identification of factors that can help explain individual differences in career success is a crucial research issue. Previous research covering various occupations indicates that the Big Five, internal locus of control (LOC), and occupational self-efficacy are good predictors of objective and subjective career success. However, there is a research gap on this topic in preschool teachers. This study examined whether the Big Five, LOC, and occupational self-efficacy could predict the career success of 560 preschool teachers in Germany. After controlling for other predictors, internal LOC corresponded with higher objective career success, but neuroticism and conscientiousness corresponded with lower subjective career success. Occupational self-efficacy corresponded with higher subjective career success. The findings are discussed with respect to practical conclusions.
A parts-based approach for automatic 3D shape categorization using belief functions

Grouping 3D objects into (semantically) meaningful categories is a challenging and important problem in 3D mining and shape processing. Here, we present a novel approach to categorize 3D objects. The method described in this article, is a belief-function-based approach and consists of two stages: the training stage, where 3D objects in the same category are processed and a set of representative parts is constructed, and the labeling stage, where unknown objects are categorized. The experimental results obtained on the Tosca-Sumner and the Shrec07 datasets show that the system efficiently performs in categorizing 3D models.
The Acceleration Mechanism of Resistive Magnetohydrodynamic Jets Launched from Accretion Disks

We analyzed the results of nonlinear resistive magnetohydrodynamic (MHD) simulations of jet formation to study the acceleration mechanism of axisymmetric, resistive MHD jets. The initial state is a constant angular momentum, polytropic torus threaded by weak uniform vertical magnetic fields. The time evolution of the torus is simulated by applying the CIP-MOCCT scheme extended for resistive MHD equations. We carried out simulations up to 50 rotation periods at the innermost radius of the disk created by accretion from the torus. The acceleration forces and the characteristics of resistive jets were studied by computing forces acting on Lagrangian test particles. Since the angle between the rotation axis of the disk and magnetic field lines is smaller in resistive models than in ideal MHD models, magnetocentrifugal acceleration is smaller. The effective potential along a magnetic field line has a maximum around z ~ 0.5r0 in resistive models, where r0 is the radius at which the density of the initial torus is maximum. Jets are launched after the disk material is lifted to this height by pressure gradient force. Even in this case, the main acceleration force around the slow magnetosonic point is the magnetocentrifugal force. The power of the resistive MHD jet is comparable to the mechanical energy liberated in the disk by mass accretion. Joule heating is not essential for the formation of jets.
Is Prevent a safe space?

In this article, I test the claims of the UK government and universities that the Prevent programme aims to create a safe space for the discussion of ‘extremist’ ideas in universities. I do this by comparing the main elements of the Prevent duty that has been imposed on universities with those of safe spaces as imagined by student campaigners and some educational writers. I conclude that, while there are manifest and significant differences in the harms that the two strategies aim to prevent, and in the sources, nature and targets of the coercion that the two strategies entail, their overall form and the underlying assumptions that rationalise them are shared. I consider some implications of their differences and of their shared characteristics for the critics of the two strategies.
Transmodal Learning of Functional Networks for Alzheimer's Disease Prediction

Functional connectivity describes neural activity from resting-state functional magnetic resonance imaging (rs-fMRI). This noninvasive modality is a promising imaging biomark-er of neurodegenerative diseases, such as Alzheimer's disease (AD), where the connectome can be an indicator to assess and to understand the pathology. However, it only provides noisy measurements of brain activity. As a consequence, it has shown fairly limited discrimination power on clinical groups. So far, the reference functional marker of AD is the fluorodeoxyglucose positron emission tomography (FDG-PET). It gives a reliable quantification of metabolic activity, but it is costly and invasive. Here, our goal is to analyze AD populations solely based on rs-fMRI, as functional connectivity is correlated to metabolism. We introduce transmodal learning: leveraging a prior from one modality to improve results of another modality on different subjects. A metabolic prior is learned from an independent FDG-PET dataset to improve functional connectivity-based prediction of AD. The prior acts as a regularization of connectivity learning and improves the estimation of discriminative patterns from distinct rs-fMRI datasets. Our approach is a two-stage classification strategy that combines several seed-based connectivity maps to cover a large number of functional networks that identify AD physiopathology. Experimental results show that our transmodal approach increases classification accuracy compared to pure rs-fMRI approaches, without resorting to additional invasive acquisitions. The method successfully recovers brain regions known to be impacted by the disease.
Approval of Raxibacumab for the Treatment of Inhalation Anthrax Under the US Food and Drug Administration “Animal Rule”

On December 14, 2012, the FDA approved Raxibacumab, the first monoclonal antibody product developed under Project BioShield to achieve this milestone, and the first biologic product to be approved through the FDA animal efficacy rule (or “Animal Rule”). Raxibacumab is approved for the treatment of adult and pediatric patients with inhalational anthrax due to Bacillus anthracis in combination with appropriate antibiotic drugs and for prophylaxis of inhalational anthrax when alternative therapies are not available or not appropriate. The developmental process required for approval of Raxibacumab illustrates many of the challenges that product developers may encounter when pursuing approval under the Animal Rule and highlights a number of important regulatory and policy issues.
Stories of Agency in the Lives of Incarcerated Women

The purpose of this study was to explore the lived experiences of incarcerated women. The research questions were: (1) How do incarcerated women demonstrate agency in their life narratives? (2) How does McAdams’ agency (2001) framework apply to the life histories of women in jail? Findings have implications for educators of those in the penal system and helping professionals.
Explaining Variations in the Effects of Supportive Messages A Dual-Process Framework

Although some recipients benefit from exposure to sophisticated and sensitive support messages, the effects of these messages are moderated (sometimes substantially) by characteristics of the recipient, the helper, and the situation. Thus, enhancing the success of helpers who provide support requires a comprehensive explanation of why support messages are effective in some circumstances but less effective in others. To understand why supportive messages work, we must understand how these messages are worked on (i.e., processed) by their recipients. This chapter uses a recently developed dual-process theory of supportive message outcomes to explain how and why multiple variables moderate the effects of supportive messages. We provide a comprehensive review of published research findings concerning the demographic, personality, cognitive, and situational moderators of supportive messages and show that these moderators can be interpreted as (1) factors influencing the message recipient’s ability and/or motivation to systematically process these messages or (2) environmental cues that quickly trigger responses to the message.
Determination of vitamins, minerals, and microbial loads of fortified nonalcoholic beverage (kunun zaki) produced from millet

Abstract The objective of this study was to evaluate the possibility of fortifying kunun zaki with tigernut milk extract due to nutritional deficiency of the former. Kunun zaki and tigernut milk extract (TME) were produced using traditional methods, with little modification. They were mixed in respective percentages of 90:10 (KN10), 80:20 (KN20), and 70:30 (KN30) while whole kunun zaki without addition of tigernut milk extract (KN00) served as control. The resulting kunun zaki samples were analyzed for proximate composition, vitamins, minerals, microbial loads, and sensory evaluation. Results showed improvement in thiamine and riboflavin contents of the fortified samples over the unfortified counterparts, with the KN30 sample having highest values of 1.05 and 0.56 mg/kg thiamine and riboflavin, respectively. Minerals were higher in the samples containing TME than their KN00 counterparts; the KN30 sample had highest values of 23.5, 8.8, 148.9, 63.7, 6.7, and 18.6 mg/100 mL for respective Na, Ca, K, Mg, P, and Fe while lowest values were recorded for the KN00 sample. Microbial analysis indicated that total viable bacteria and yeast and molds were in the range 2.2–2.6 and 2.1–2.7 log CFU/g, respectively, while there was no detection of coliforms and Staphylococcus in the samples. The sensory evaluation of the kunun zaki samples indicated that higher mean scores were recorded for samples containing TME than those without it in most of the attributes tested. The KN30 sample was most preferred, having highest mean scores of 7.2, 7.8, 6.9, and 7.4 in the attributes of appearance, flavor, taste, and acceptability, respectively. The study concluded that inclusion of tigernut extract in kunun zaki resulted in improved nutritional and sensory qualities.
Modular Neural Networks for Reinforcement Learning with Temporal Intrinsic Rewards

Inspired by intrinsic motivation that is thought to play a crucial role in animal development and learning, several artificial learning systems with built in intrinsic rewards were recently studied. Here we suggest an intrinsically rewarded learning system for autonomous task achievements that copes with several kinds of transitions. The system consists of neural networks equipped with a modular reinforcement learning algorithm. The modular system that decomposes the observed state space stabilizes the intrinsic rewards calculated from prediction errors. On-line learning via the proposed system takes place under various kinds of transitions, including deterministic, probabilistic and partially observable, without any specific adjustments of parameters for each transition. The combined system with both the modular network and the intrinsic reward generator led to performance that converged to the optimal sequences of actions in all tested transitions, in which external rewards were delivered only at the completion of tasks.
The Role of Social Referents in Consumer' E-Commerce Adoption in China

From the perspective of social influence, this study developed an integrated model to explain different roles of social referents in an individual's e-commerce adoption based on theory of planned behavior (TPB) and trust relative theories. On basis of available research, online consumers' social referents were divided into three types: interpersonal norm, social norm of subjective norm and external norm on website. Empirical data was collected from a survey of users to verify proposed hypotheses. The result shows that consumers' use intention towards e-commerce is mainly determined by subjective norm and consumer's trust belief. Both interpersonal and social norm have positive effect on use intention, with the former a more important role. External norm by external referents on website shows a positive impact on users' trust but no significant effect on use intention. After consideration of the impact of external referents on customer behavior intention, the social influence on consumer's use intention is extend and different roles of various social referents can be better explained.
Cognitive Changes after Deep Brain Stimulation in Parkinson's Disease: A Critical Review

Concern about cognitive worsening, especially after subthalamic nucleus (STN) deep brain stimulation (DBS) has been reported in Parkinson’s disease (PD) patients, although it has not been deemed severe enough to discredit DBS as a powerful tool in the armamentarium against PD. We here provide an in-depth and critical review of the current literature on this topic, summarizing the available data on the impact of STN and globus pallidus interna (GPi) DBS on each of the following cognitive domains: language, executive function, attention and concentration, memory, visual function, psychomotor and processing speed, and global cognition; then looking in more details into controlled studies as well as studies directly comparing GPi and STN DBS. We conclude that worsening of one or more cognitive function is rare and subtle after DBS in PD patients, without negative impact on quality of life, and that there is very little data supporting that STN DBS has a worse cognitive outcome than Gpi DBS.
Numerical investigation and preliminary modeling of a turbulent flow over a multi-perforated plate

Wall-resolved LES of a turbulent flow around a multi-perforated plate are presented. Periodic conditions are used in both directions tangential to the plate so that only one or a few micro-jets are computed. Comparisons between one and four holes computations show that single hole domain calculations allow to capture the essential characteristics and statistics of the flow. The results from two different numerical codes and strategies also compare favorably with the existing experimental data in the case of a large scale cold flow with effusion. The overall quality of the simulations being established, further analysis of the flow structure is performed. Two results relevant to further modeling studies are obtained: the jet angle somewhat departs from the hole angle and the velocity profile in the jet is highly inhomogeneous with a strong recirculation zone in the downstream side. Preliminary testing of a simple dynamic model for the normal velocity is also presented. A robust algorithm for implementing this model in coupled computational domains is developed. Deficiencies in the model are identified and discussed.
PROTEIN MICROARRAYS BASED ON SINGLE FRAMEWORK RECOMBINANT ANTIBODY FRAGMENTS (SINFABS)

Antibody-based microarrays are among the novel class of rapidly evolving proteomic technologies. In recent years, antibody microarrays have emerged as a unique tool for high-throughput protein expression profiling with great promise within biomedicine and a wide range of potential applications, including disease diagnostics and biomarker discovery. In order to evolve the technology from small dedicated microarrays to high-density well-performing arrays for true global proteome analysis, this thesis focussed on the design of the two key components of the antibody microarray setup: the probe and the solid support, i.e. ? catcher and carrier? The thesis is based upon five original papers that deal with i) the central features of the probe (on-chip functionality and stability, sensitivity and immobilisation strategies) and ii) the biocompatibility of the solid support (defined by the spot morphology, binding capacity, signal to noise ratio, dynamic range, sensitivity, reproducibility and the long-term performance). Single-framework recombinant antibody fragments (sinFabs), selected from the nCoDeR-library, were found to fulfil most, if not all, of the prerequisites required by well-performing probes for high-density antibody microarrays. In more detail, sinFabs were shown to be functional and stable on the chip with a constant on-chip performance (paper I and II) and to provide sensitive detection of low-abundant analytes (paper III). Furthermore, they could be genetically engineered for improved affinity coupling, thereby enabling non-purified probes to be coupled in an orientated way and purified directly on the chip (paper III and IV). Although sinFab microarrays were shown to be biocompatible with several commercially available and in-house designed solid supports of different structure (1-, 2- and 3-dimensional) and coupling chemistry (adsorption, covalent coupling and affinity binding), no single surface was found to fulfil all the requirements for a sensitive and high-density antibody microarray analysis (paper II and V). Thus, the development of a novel highly biocompatible macroporous silicon support coated with nitrocellulose (MAP3-NC7) (paper V) was a first step towards the specific design of optimised antibody microarray supports.
Investigation of School Professionals’ Self-Efficacy for Working With Students With ASD

School professionals who work with students with autism spectrum disorder (ASD) play a significant role in the academic experiences of these students, but some evidence suggests that teachers of students with ASD experience a high risk of burnout. Research has begun to examine factors that ameliorate or prevent teacher burnout, including teacher training and teacher self-efficacy, or teachers’ beliefs regarding their abilities to bring about positive outcomes for their students. The present study examined variables associated with the self-efficacy of school professionals for working with students with ASD, including knowledge about ASD, prior experience working with students with ASD, and prior training in ASD and evidence-based practices. A second goal of the present study was to investigate the impact of training on ASD and evidence-based practices on school professionals’ knowledge and self-efficacy related to working with students with ASD. In particular, the participants received training on the Prevent–Teach–Reinforce model. Results of the present study suggested the importance of training to school professionals’ self-efficacy, highlighting the need for continued efforts to provide quality training to individuals who work with students with ASD.