Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceived Influence on Service Goals Among Community-Working Occupational Therapists in Norway

Aim: This study aimed to assess the perceived influence that community-working occupational therapists in Norway have on the service goals of their respective organizations. In addition, we aimed to assess sociodemographic and work-related factors associated with the perceived level of influence. Methods: A cross-sectional survey was distributed to occupational therapists in community-based services in Norway (n = 1767), to which 561 (32%) responded. By multivariate regression analysis, factors associated with “self-perceived influence” were assessed. Results: After controlling for all variables, having a master’s degree (β = 0.09, P < .05), being involved in a research and development project (β = 0.25, P < .001), and not working with assistive technology (β = −0.19, P < .001) were associated with higher perceived influence. Conclusions: For occupational therapy to reach its potential in Norwegian community-based health care, the profession needs to establish itself more firmly and increase its influence within the health care services. To do so, it appears important to support occupational therapists’ educational aspirations, their participation in research and development projects, and their autonomous role in relation to the provision of assistive technology equipment.
The Effect of the Embodied Guidance in the Insight Problem Solving: An Eye Movement Study

Insight is an important cognitive process in creative thinking. The present research applied embodied cognitive perspective to explore the effect of embodied guidance on insight problem solving and its underlying mechanisms by two experiments. Experiment 1 used the matchstick arithmetic problem to explore the role of embodied gestures guidance in problem solving. The results showed that the embodied gestures facilitate the participants’ performance. Experiment 2 investigated how embodied attention guidance affects insight problem solving. The results showed that participants performed better in prototypical guidance condition. Experiment 2a adopted the Duncker’s radiation problem to explore how embodied behavior and prototypical guidance influence problem solving by attention tracing techniques. Experiment 2b aimed to further examine whether implicit attention transfer was the real cause which resulted in participants over-performing in prototypical guidance condition in Experiment 2a. The results demonstrated that overt physical motion was unnecessary for individuals to experience the benefits of embodied guidance in problem solving, which supported the reciprocal relation hypothesis of saccades and attention. In addition, the questionnaire completed after experiments showed that participants did not realize the relation between guidance and insight problem solving. Taken together, the current study provided further evidence for that embodied gesture and embodied attention both facilitated the insight problem solving and the facilitation is implicit.
Sex‐specific effects of outbreeding on offspring quality in pike (Esox lucius)

Abstract Intraspecific genetic admixture occurs when previously separated populations within a species start interbreeding, and it can have either positive, negative, or neutral effects on reproductive performance. As there currently is no reliable predictor for the outcome of admixture, an increased knowledge about admixture effects in different species and populations is important to increase the understanding about what determines the response to admixture. We tested for effects of admixture on F1 offspring quality in three subpopulations of pike (Esox lucius). Gametes were collected in the field, and eggs from each female were experimentally fertilized with milt from a male from each population (one “pure” and two “admixed” treatments). Three offspring quality measures (hatching success, fry survival, and fry length) were determined and compared between (a) pure and admixed population combinations and (b) the sex‐specific treatments within each admixed population combination (based on the origin of the male and female, respectively). The results suggested that although there were no overall effects of admixture on offspring quality, the consequences for a given population combination could be sex‐specific and thus differ depending on which of the parents originated from one or the other population. All offspring quality traits were influenced by both maternal ID and paternal ID. Sex‐ and individual‐specific effects can have implications for dispersal behavior and gene flow between natural populations, and are important to consider in conservation efforts.
An Affect-Rich Neural Conversational Model with Biased Attention and Weighted Cross-Entropy Loss

Affect conveys important implicit information in human communication. Having the capability to correctly express affect during human-machine conversations is one of the major milestones in artificial intelligence. In recent years, extensive research on open-domain neural conversational models has been conducted. However, embedding affect into such models is still under explored. In this paper, we propose an endto-end affect-rich open-domain neural conversational model that produces responses not only appropriate in syntax and semantics, but also with rich affect. Our model extends the Seq2Seq model and adopts VAD (Valence, Arousal and Dominance) affective notations to embed each word with affects. In addition, our model considers the effect of negators and intensifiers via a novel affective attention mechanism, which biases attention towards affect-rich words in input sentences. Lastly, we train our model with an affect-incorporated objective function to encourage the generation of affect-rich words in the output responses. Evaluations based on both perplexity and human evaluations show that our model outperforms the state-of-the-art baseline model of comparable size in producing natural and affect-rich responses.
Link Prediction in Dynamic Graphs for Recommendation

Recent advances in employing neural networks on graph domains helped push the state of the art in link prediction tasks, particularly in recommendation services. However, the use of temporal contextual information, often modeled as dynamic graphs that encode the evolution of user-item relationships over time, has been overlooked in link prediction problems. In this paper, we consider the hypothesis that leveraging such information enables models to make better predictions, proposing a new neural network approach for this. Our experiments, performed on the widely used ML-100k and ML-1M datasets, show that our approach produces better predictions in scenarios where the pattern of user-item relationships change over time. In addition, they suggest that existing approaches are significantly impacted by those changes.
Similar survival outcome after endoscopic and open approaches for sinonasal mucosal melanoma.

BACKGROUND To describe a cohort of sinonasal mucosal melanoma (SNMM) patients, and to assess if choice of surgical approach (open versus endoscopic) has impact on survival. METHODOLOGY Adequate data on clinical presentation, treatment, and recurrence pattern were available for 58 consecutive patients treated for SNMM at the Helsinki University Hospital (HUH) between 1983 and 2016. RESULTS The 5-year disease-specific survival (DSS) was 27% and overall survival 25% for the whole cohort. The 3-year DSS for patients treated with curative intent with endoscopic surgery was comparable to open surgery (56% and 51%, respectively). Patients with tumours arising from the paranasal sinuses and patients with Stage IV disease had significantly worse prognosis compared with other locations and Stage III patients. All patients who had disease persistence at three months after primary treatment succumbed to SNMM. Post-operative radiotherapy did not affect survival significantly, but a trend towards improved local control was observed. CONCLUSIONS Local control after endoscopic surgery was comparable to open surgery. Small tumours without local or locoregional spread had improved prognosis, independent of surgical approach. Disease persistence after treatment with curative intent led to death invariably.
Amyloid precursor protein‐mediated mitochondrial regulation and Alzheimer's disease

Despite clear evidence of a neuroprotective physiological role of amyloid precursor protein (APP) and its non‐amyloidogenic processing products, APP has been investigated mainly in animal and cellular models of amyloid pathology in the context of Alzheimer's disease. The rare familial mutations in APP and presenilin‐1/2, which sometimes drive increased amyloid β (Aβ) production, may have unduly influenced Alzheimer's disease research. APP and its cleavage products play important roles in cellular and mitochondrial metabolism, but many studies focus solely on Aβ. Mitochondrial bioenergetic metabolism is essential for neuronal function, maintenance and survival, and multiple reports indicate mitochondrial abnormalities in patients with Alzheimer's disease. In this review, we focus on mitochondrial abnormalities reported in sporadic Alzheimer's disease patients and the role of full‐length APP and its non‐amyloidogenic fragments, particularly soluble APPα, on mitochondrial bioenergetic metabolism. We do not review the plethora of animal and in vitro studies using mutant APP/presenilin constructs or experiments using exogenous Aβ. In doing so, we aim to invigorate research and discussion around non‐amyloidogenic APP processing products and the mechanisms linking mitochondria and complex neurodegenerative disorders such as sporadic Alzheimer's disease.
Short-Term Psychological and Physiological Effects of Varying the Volume of High-Intensity Interval Training in Healthy Men

We assessed the short-term effects of varying the volume of high-intensity interval training (HIIT) on psychological and physiological responses of 23 healthy adult males (M = 21 years; M peak oxygen uptake [VO2peak] = 47.2 ml·kg−1·min−1). Participants were randomly assigned to low- and very-low-volume HIIT groups and engaged in nine supervised exercise sessions over three weeks. The low-volume HIIT group performed 8-12 60-second work bouts on a cycle ergometer at the peak power output achieved during the incremental test, interspersed by 75 seconds of low-intensity active recovery. The very-low-volume HIIT performed 4-6 work bouts with the same intensity, duration, and rest intervals. During training, participants’ ratings of perceived exertion (Borg Category Ratio-10 scale) and their affective responses (Feeling Scale −5/+5) during the last 15 seconds of each work bout were recorded. Physiological data were VO2peak, endurance, and anaerobic performance before and after the intervention. Throughout training, participants in the very-low-volume group (relative to the low-volume group) reported lower ratings of perceived exertion in Week 1 (M = 4.1 vs. M = 6.3; p < .01) and Week 3 (M = 4.0 vs. M = 6.2; p < .01), and higher affective response in these same two weeks (Week 1: M = 1.9 vs. M = 0.3; p = .04; Week 3: M = 2.1 vs. M = 0.9; p = .06). Regarding physical fitness, Wingate peak power increased significantly after training in the very-low-volume HIIT group (M = 1,049 W vs. M = 1,222 W; p < .05), but not in the low-volume HIIT group (M = 1,050 W vs. M = 1,076 W). No significant change was found after training in physiological variables of peak power output, VO2peak, and endurance performance. In summary, in this short-term training period, the very-low-volume HIIT enhanced anaerobic capacity and was perceived as less strenuous and more pleasurable than low-volume HIIT.
Okuma Yazma Güçlüğü ve Bir Eylem Araştırması: İkinci Sınıf Örneği

Bu calismada, okuma ve yazma guclugu ceken bir ilkokul ikinci sinif ogrencisinin Fernald yontemi, yankili ve tekrarli okuma stratejileri ile okuma ve yazma becerilerinin gelistirilmesi amaclanmistir. Nitel arastirma desenlerinden eylem arastirmasinin kullanildigi calisma 2015 – 2016 bahar yariyilinda gerceklestirilmistir. Okuma hatalarinin belirlenmesinde Yanlis Analiz Envanteri; yazinin okunaklilik duzeyinin belirlenmesinde Cok Boyutlu Okunaklilik Olcegi kullanilmistir. Okuma ile ilgili durum belirleme calismasinda, ogrenci ikinci sinif metnini okuyamamis ve ogrencinin endise duzeyinde oldugu belirlenmistir. Uygulamalar sonunda bes dakikalik sure icinde 92 kelimeden olusan ikinci sinif metninin 30 kelimelik bolumune kadar okuyabildigi gorulmus ve ogrencinin 6 kez yanlis okuma ve 2 ekleme hatasi yaptigi tespit edilmistir. Yapilan etkinlikler sonucunda ogrencinin okuma istegi artmis, sesli okumaya baslamis ve dogru okuyabildigi ve okuyamadigi kelimeleri tespit etmeye baslamistir. Hem bakarak yazma hem de dikte calismasi uygulamalari sonunda katilimcinin yazisinin okunaklilik duzeyinin orta duzeye yukseldigi gorulmustur.
Cohort by Education Interactions in Longitudinal Changes in Functional Abilities

Objective: Investigations of cohort differences in relationships between education and health tend to focus on mortality or self-reported health. We report one of the first analyses of cohort differences in relationships between education and objective measures of functional abilities across the lifespan. Method: Up to 26 years of follow-up data were available from 859 adults from the Swedish Adoption/Twin Study of Aging. The sample was divided into two cohorts by birth year: 1900-1924 and 1925-1948. Latent growth curve models (LGCM) were compared across cohort and educational levels. Results: LGCM indicated divergence between adults with lower and higher educational attainment in longitudinal trajectories of change with age in the Balance and Flexibility factors for the later born cohort only. Discussion: Results support the cumulative advantage theory and suggest that education–health disparities are increasing in recent cohorts, even in counties with national health care systems and strong support of education.
Examining Student Performance and Attitudes on Distributed Pair Programming

Pair programming (PP) has become popular in the research and software industry as well as being studied for a number of years in computer science courses with positive findings on student performance and attitudes. Advantages of PP reported in the literature are satisfaction, design quality, code productivity, team building, and communication. More recently, distributed pair programming (DPP), which enables two programmers to work remotely, has also attracted the interest of researchers and instructors. The difference between DPP and PP is that the former allows geographically distributed teams to collaborate and share program code. Such collaboration is, thus, only feasible if an underlying infrastructure supports all necessary interactions. The integrated development environments (IDEs) for DPP should cover the basic requirements for remote software development as well as address common PP problems, such as unequal contributions from each member of a pair, feedback during DPP sessions, and communication problems. This paper presents the findings of a study on student performance and attitudes towards DPP in an object-oriented programming (OOP) course. The factors examined were student performance, in terms of assignment grade, exam grade and implementation time in relation to students’ programming experience, and confidence, as well as student attitudes towards DPP, i.e., the feelgood factor, working alone or with a partner, and the perception of their partner’s technical competence. The results suggest that a students’ performance is associated with their programming experience and confidence in programming but not with how comfortable they feel during DPP sessions. Students evaluate the DPP sessions positively regardless of their confidence on programming or their perception of their partners’ technical competence. Students who consider themselves to have about the same programming competence as their partners tend to be more satisfied with DPP sessions. Overall, students prefer working with a partner regardless of their confidence on programming.
Indoor GeoNet: Weakly Supervised Hybrid Learning for Depth and Pose Estimation

Humans naturally perceive a 3D scene in front of them through accumulation of information obtained from multiple interconnected projections of the scene and by interpreting their correspondence. This phenomenon has inspired artificial intelligence models to extract the depth and view angle of the observed scene by modeling the correspondence between different views of that scene. Our paper is built upon previous works in the field of unsupervised depth and relative camera pose estimation from temporal consecutive video frames using deep learning (DL) models. Our approach uses a hybrid learning framework introduced in a recent work called GeoNet, which leverages geometric constraints in the 3D scenes to synthesize a novel view from intermediate DL-based predicted depth and relative pose. However, the state-of-the-art unsupervised depth and pose estimation DL models are exclusively trained/tested on a few available outdoor scene datasets and we have shown they are hardly transferable to new scenes, especially from indoor environments, in which estimation requires higher precision and dealing with probable occlusions. This paper introduces "Indoor GeoNet", a weakly supervised depth and camera pose estimation model targeted for indoor scenes. In Indoor GeoNet, we take advantage of the availability of indoor RGBD datasets collected by human or robot navigators, and added partial (i.e. weak) supervision in depth training into the model. Experimental results showed that our model effectively generalizes to new scenes from different buildings. Indoor GeoNet demonstrated significant depth and pose estimation error reduction when compared to the original GeoNet, while showing 3 times more reconstruction accuracy in synthesizing novel views in indoor environments.
Label-Free Digital Holo-tomographic Microscopy Reveals Virus-Induced Cytopathic Effects in Live Cells

This study introduces label-free digital holo-tomographic microscopy (DHTM) and refractive index gradient (RIG) measurements of live, virus-infected cells. We use DHTM to describe virus type-specific cytopathic effects, including cyclic volume changes of vaccinia virus infections, and cytoplasmic condensations in herpesvirus and rhinovirus infections, distinct from apoptotic cells. This work shows for the first time that DHTM is suitable to observe virus-infected cells and distinguishes virus type-specific signatures under noninvasive conditions. It provides a basis for future studies, where correlative fluorescence microscopy of cell and virus structures annotate distinct RIG values derived from DHTM. ABSTRACT Cytopathic effects (CPEs) are a hallmark of infections. CPEs are difficult to observe due to phototoxicity from classical light microscopy. We report distinct patterns of virus infections in live cells using digital holo-tomographic microscopy (DHTM). DHTM is label-free and records the phase shift of low-energy light passing through the specimen on a transparent surface with minimal perturbation. DHTM measures the refractive index (RI) and computes the refractive index gradient (RIG), unveiling optical heterogeneity in cells. We find that vaccinia virus (VACV), herpes simplex virus (HSV), and rhinovirus (RV) infections progressively and distinctly increased RIG. VACV infection, but not HSV and RV infections, induced oscillations of cell volume, while all three viruses altered cytoplasmic membrane dynamics and induced apoptotic features akin to those caused by the chemical compound staurosporine. In sum, we introduce DHTM for quantitative label-free microscopy in infection research and uncover virus type-specific changes and CPE in living cells with minimal interference. IMPORTANCE This study introduces label-free digital holo-tomographic microscopy (DHTM) and refractive index gradient (RIG) measurements of live, virus-infected cells. We use DHTM to describe virus type-specific cytopathic effects, including cyclic volume changes of vaccinia virus infections, and cytoplasmic condensations in herpesvirus and rhinovirus infections, distinct from apoptotic cells. This work shows for the first time that DHTM is suitable to observe virus-infected cells and distinguishes virus type-specific signatures under noninvasive conditions. It provides a basis for future studies, where correlative fluorescence microscopy of cell and virus structures annotate distinct RIG values derived from DHTM.
Deep learning for retinopathy of prematurity screening

Retinopathy of prematurity (ROP) is a neurovascular disorder of retina, characterised by abnormal fibrovascular proliferation at the boundary of the vascularised and avascular peripheral retina. Globally, it is estimated that 19 million children are suffering from visual impairment.1 Of those, ROP accounts for 6%–18% childhood blindness,2 causing significant psychosocial impact on the child and the family.3 According to the Early Treatment for Retinopathy of Prematurity (ETROP) trial,4 early treatment has shown to be beneficial to improve the visual acuity of the high-risk patients with ROP, although 9% still eventually became blind. Thus, early screening with regular monitoring is extremely crucial. The at-risk groups are babies who are born preterm or those with neonatal morbidity, for example, respiratory distress syndrome, infection and hyperglycaemia.5 These groups of neonates usually require high oxygen demand due to the systemic issues. Oxygen regulation is important for normal retinal vascular development. In the UK, the current guidelines recommend that babies born at <32 weeks or with birth weight <1.5 kg should be screened for ROP.6 For the medically unstable infants who require high supplemental oxygen, the screening is recommended to be done earlier, although the screening criteria may vary slightly between different countries around the world. Based on the International Classification of ROP, ROP is divided into five stages (table 1) with or without plus diseases.7 Early recognition of plus diseases is extremely crucial for initiation of treatment. The disease involvement is usually documented in terms of location and the extent of clock hours. For location, it is divided into zones 1–3 (figure 1). It is important to detect the patients with prethreshold (type 1 ROP and type 2 ROP) and aggressive posterior ROP (also known as ‘rush disease’ previously). Serial diagnostic examinations should be performed until each eye …
SDN-Based Architecture for Providing QoS to High Performance Distributed Applications

The specification of quality of service (QoS) requirements in traditional networks is limited by the high administrative cost of these environments. Nevertheless, newer network paradigms, as software-defined networks (SDNs), simplify and relaxes the management of networks. In this sense, SDN can provide a simple/effective way to develop QoS provisioning. In this paper, we propose a QoS provision architecture exploiting the capabilities of SDN. Our approach allows the specification of classes of service and also negotiates the QoS requirements between applications and the SDN network controller. The SDN controller, in turn, monitors the network and adjusts its performance through resource reservation and traffic prioritization. We developed a proof-of-concept of our proposal and, our experimental results show that the additional routines present low overhead, whereas- -for a given test application- we observe a reduction of up to 47% in transfer times.