Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Chronic Fluoxetine Treatment on Neurogenesis and Tryptophan Hydroxylase Expression in Adolescent and Adult Rats

The antidepressant drug fluoxetine (Prozac) has been increasingly prescribed to children and adolescents with depressive disorders despite a lack of thorough understanding of its therapeutic effects in the paediatric population and of its putative neurodevelopmental effects. Within the framework of PRIOMEDCHILD ERA-NET, we investigated; a) effects of chronic fluoxetine treatment on adult hippocampal neurogenesis, a structural readout relevant for antidepressant action and hippocampal development; b) effects on tryptophan hydroxylase (TPH) expression, a measure of serotonin synthesis; c) whether treatment effects during adolescence differed from treatment at an adult age, and d) whether they were subregion-specific. Stereological quantification of the number of proliferating (Ki-67+) cells and of the number of young migratory neurons (doublecortin+), revealed a significant age-by-treatment interaction effect, indicating that fluoxetine affects both proliferation and neurogenesis in adolescent-treated rats differently than it does in adult-treated rats. In terms of subregional differences, fluoxetine enhanced proliferation mainly in the dorsal parts of the hippocampus, and neurogenesis in both the suprapyramidal and infrapyramidal blades of the dentate gyrus in adolescent-treated rats, while no such differences were seen in adult-treated rats. Fluoxetine exerted similar age-by-treatment interaction effects on TPH cells mainly in the ventral portion of the dorsal raphe nucleus. We conclude that fluoxetine exerts divergent effects on structural plasticity and serotonin synthesis in adolescent versus adult-treated rats. These preliminary data indicate a differential sensitivity of the adolescent brain to this drug and thus warrant further research into their behavioural and translational aspects. Together with recent related findings, they further call for caution in prescribing these drugs to the adolescent population.
Licensing, Popular Practices and Public Spaces: An Inquiry via the Geographies of Street Food Vending

The socio-legal technology of licensing is one of the primary tools governments use to manage spaces and practices deemed risky or threatening to public order. Licensing requirements thus play a crucial role in shaping routine experiences in public space as well as the trajectories of emerging forms of public life. Yet licensing laws have largely been ignored in critical urban scholarship: too often concerned with the interpretation and critique of popular practices and public spaces, the mundane operations of urban governance are often left to practitioners and policy researchers. This article demonstrates how paying closer attention to licensure can provide valuable and unexpected insights into matters of social equality, urban amenity and economic opportunity. It does so through a comparative inquiry into practices of street food vending in New York City, Seattle, and Portland, Oregon. Drawing on ethnographic study and interviews, the article demonstrates how licensing can be involved in the production of quite peculiar and unjust geographies of practice, but also how shifts in popular culture can force a reconsideration of taken-for- granted laws. In conclusion, it is argued that a focus on licensing offers a productive pathway for new forms of critical urban research and provides a potential point of leverage in efforts to configure better and more democratic forms of urban public life.
Ion specific correlations in bulk and at biointerfaces

Ion specific effects are ubiquitous in any complex colloidal or biological fluid in bulk or at interfaces. The molecular origins of these ‘Hofmeister effects’ are not well understood and their theoretical description poses a formidable challenge to the modeling and simulation community. On the basis of the combination of atomistically resolved molecular dynamics (MD) computer simulations and statistical mechanics approaches, we present a few selected examples of specific electrolyte effects in bulk, at simple neutral and charged interfaces, and on a short α-helical peptide. The structural complexity in these strongly Coulomb-correlated systems is highlighted and analyzed in the light of available experimental data. While in general the comparison of MD simulations to experiments often lacks quantitative agreement, mostly because molecular force fields and coarse-graining procedures remain to be optimized, the consensus as regards trends provides important insights into microscopic hydration and binding mechanisms.
Noninvasive Assessment of Atrioventricular Pressure Half‐time by Doppler Ultrasound

The mean pressure drop across the mitral valve and atrioventricular pressure half-time were measured noninvasively by Doppler ultrasound in 40 normal subjects, in 17 patients with mitral regurgitation, 32 patients with mitral stenosis and 12 with combined stenosis and regurgitation. In normal subjects pressure half-times were 20-60 msec, in patients with isolated mitral regurgitation 35-80 msec and in patients with mitral stenosis 90-383 msec. There was no significant change in pressure half-time with exercise or on repeat examinations, indicating relative independence of mitral flow. In 25 patients with mitral stenosis and seven with combined stenosis and regurgitation, pressure half-time was related to mitral valve area calculated from catheterization data. Increasing pressure half-times occurred with decreasing mitral valve area, and this relationship was not influenced by additional mitral regurgitation. Noninvasive measurement of pressure halftime together with mean pressure drop was useful for evaluating patients with mitral valve disease.
Explicit high-order non-canonical symplectic particle-in-cell algorithms for Vlasov-Maxwell systems

Explicit high-order non-canonical symplectic particle-in-cell algorithms for classical particle-field systems governed by the Vlasov-Maxwell equations are developed. The algorithms conserve a discrete non-canonical symplectic structure derived from the Lagrangian of the particle-field system, which is naturally discrete in particles. The electromagnetic field is spatially discretized using the method of discrete exterior calculus with high-order interpolating differential forms for a cubic grid. The resulting time-domain Lagrangian assumes a non-canonical symplectic structure. It is also gauge invariant and conserves charge. The system is then solved using a structure-preserving splitting method discovered by He et al. [preprint arXiv:1505.06076 (2015)], which produces five exactly soluble sub-systems, and high-order structure-preserving algorithms follow by combinations. The explicit, high-order, and conservative nature of the algorithms is especially suitable for long-term simulations of particle-field systems with extremely large number of degrees of freedom on massively parallel supercomputers. The algorithms have been tested and verified by the two physics problems, i.e., the nonlinear Landau damping and the electron Bernstein wave.
Climate change and the welfare state? Exploring Australian attitudes to climate and social policy

Despite growing evidence of significant impacts from human-induced climate change, policy responses have been slow. Understanding this policy inertia has led to competing explanations, which either point to the need to build a consensual politics separated from economic partisanship, or which encourage solidarities between environmental and social movements and issues. This article analyses a recent successful mobilisation, leading to the passage of the Clean Energy Act in Australia, to explore the relationship between attitudes to environmental and social protection, particularly among the core constituency in favour of stronger climate action. Using social survey data from the Australian Election Study, the article finds evidence of independent associations between prioritising environmental concerns and support for welfare state expansion, and a realignment of materialist and post-materialist values. This we argue is consistent with Polanyian analysis that posits a link between social and environmental causes based on resistance to commodification.
Building a High-performance Deduplication System

Modern deduplication has become quite effective at eliminating duplicates in data, thus multiplying the effective capacity of disk-based backup systems, and enabling them as realistic tape replacements. Despite these improvements, single-node raw capacity is still mostly limited to tens or a few hundreds of terabytes, forcing users to resort to complex and costly multi-node systems, which usually only allow them to scale to singledigit petabytes. As the opportunities for deduplication efficiency optimizations become scarce, we are challenged with the task of designing deduplication systems that will effectively address the capacity, throughput, management and energy requirements of the petascale age. In this paper we present our high-performance deduplication prototype, designed from the ground up to optimize overall single-node performance, by making the best possible use of a node's resources, and achieve three important goals: scale to large capacity, provide good deduplication efficiency, and near-raw-disk throughput. Instead of trying to improve duplicate detection algorithms, we focus on system design aspects and introduce novelmechanisms--thatwe combinewith careful implementations of known system engineering techniques. In particular, we improve single-node scalability by introducing progressive sampled indexing and grouped mark-and-sweep, and also optimize throughput by utilizing an event-driven, multi-threaded client-server interaction model. Our prototype implementation is able to scale to billions of stored objects, with high throughput, and very little or no degradation of deduplication efficiency.
Visualization of Learning Scenarios with UML4LD

Present Educational Modelling Languages are used to formally specify abstract learning scenarios in a machine-interpretable format. Current tooling does not provide teachers/designers with some graphical facilities to help them in reusing existent scenarios. They need human-readable representations. This paper discusses the UML4LD experimental research work in relation to the graphical representation of abstract learning scenarios. We discuss the benefits teachers/designers can expect to reach as well as some scientific and/or technical obstacles researchers have to overcome to realize such models transformation. Our experiment concretely concerns the automatic generation of UML activity diagrams from IMS-LD learning scenarios.
Climate change scenarios of surface solar radiation in data sparse regions: a case study in Malaprabha River Basin, India

A variety of methods are available to estimate future solar radiation (SR) scenarios at spatial scales that are appropriate for local climate change impact assessment. However, there are no clear guidelines available in the literature to decide which methodologies are most suitable for different applications. Three methodologies to guide the estimation of SR are discussed in this study, namely: Case 1: SR is measured, Case 2: SR is measured but sparse and Case 3: SR is not measured. In Case 1, future SR scenarios are derived using several downscaling methodologies that transfer the simulated large-scale information of global climate models to a local scale ( measurements). In Case 2, the SR was first estimated at the local scale for a longer time period using sparse measured records, and then future scenarios were derived using several downscaling methodologies. In Case 3: the SR was first estimated at a regional scale for a longer time period using complete or sparse measured records of SR from which SR at the local scale was estimated. Finally, the future scenarios were derived using several downscaling methodologies. The lack of observed SR data, especially in developing countries, has hindered various climate change impact studies. Hence, this was further elaborated by applying the Case 3 methodology to a semi-arid Malaprabha reservoir catchment in southern India. A support vector machine was used in downscaling SR. Future monthly scenarios of SR were estimated from simulations of third-generation Canadian General Circulation Model (CGCM3) for various SRES emission scenarios (A1B, A2, B1, and COMMIT). Results indicated a projected decrease of 0.4 to 12.2 W m(-2) yr(-1) in SR during the period 2001-2100 across the 4 scenarios. SR was calculated using the modified Hargreaves method. The decreasing trends for the future were in agreement with the simulations of SR from the CGCM3 model directly obtained for the 4 scenarios.
Assessing Cochlear Implant Benefit in Very Young Children

3. Tyler RS, Fryauf-Bertschy H, Kelsay DMR, Gantz BJ, Woodworth GP, Parkinson A. Speech perception by prelingually deaf children using cochlear implants. Otolaryngol Head Neck Surg 1997;117:1807. 4. Balkany T, Hodges AV, Luntz M. Update on cochlear implantation. Otolaryngol Clinic North Am 1996;29:277-89. 5. Miyamoto R, Osberger M, Todd S, et al. Variables affecting implant performance in children. Laryngoscope 1994;104:1120-4. 6. Harrison R, Nedzelski J, Picton N, et al. The Paediatric Cochlear Implant Program at the Hospital for Sick Children, Toronto. J Otolaryngol 1997;26:180-7. 7. De Jong A, Nedzelski J, Papsin B. Surgical outcome measures of pédiatrie cochlear implantation. J Otolaryngol 1998;27:26-30. 8. Dawson PW, Blarney PJ, Rowland LC, et al. Cochlear implants in children, adolescents, and prelinguistically deafened adults: speech perception. J Speech Hear Res 1992;35:401-17.
An Investigation on Classroom Learning Environments in Primary Schools

† ABSTRACT. The study aimed to investigate the students' perceptions of their classroom learning environments. 620 primary school students (grade 5 th , 6 th , 7 th ) completed a questionnaire named the Constructivist Learning Environment Survey. The findings showed that students perceive their classrooms as an environment which provide more opportunity to connect between school science and daily-life events, provide for them to experience scientific knowledge, and explain to other students their ideas, but less opportunity to express their concerns about any impediments to their learning and share with the teacher control of the learning environment. SUMMARY Purpose and Significance: The recent national reform movements in Turkey, particularly in science, is grounded in a constructivist approach to learning in which learners should find personal relevance in what they learn, share control over their learning, view knowledge as ever changing, and interact with each other to foster improved understanding. However, reform is often difficult to implement in large systems with inertia set by years of tradition and entrenched beliefs. At this point, it is important knowing the nature of students' views on their learning environments. Therefore, the aim of this study was to investigate the primary school students' perceptions on their classroom learning environments. Method: In this study, the survey method was used. Initially, Constructivist Learning Environment Survey were distributed to students. Data gathered were statistical analysed and results are presented through frequency and percentage tables. The sample of this study which included 620 primary school students was chosen from grade 5 th , 6 th , 7 th among Primary Schools in Tokat during the 2007-2008 academic years. Results: The students perceive their classroom learning environments as highly focused on the connectedness of school science to students' out-of-school experiences, provided opportunities for students to experience scientific knowledge and to explain and justify to other students their newly developing ideas, but less student control of the learning environment, a social climate has been established in which students express concerns about any impediments to their learning. Discussion and Conclusion: The results of the study showed that the reform aimed to fit constructivist learning approach in science and technology curriculum in Turkish Primary Schools approved by curriculum practitioners but also there were traditional beliefs those teaching is a transmissive process exist.
Cancer stem cells: lessons from leukaemia

Abstract. Increasing evidence suggests that leukaemias are sustained by leukaemic stem cells. Leukaemia can indeed be viewed as aberrant haematopoietic processes initiated by rare leukaemic stem cells that have maintained or reacquired the capacity for indefinite proliferation through accumulated mutations and/or epigenetic changes. Yet, despite their critical importance, much remains to be learned about the developmental origin of leukaemic stem cells and the molecular pathways underlying the transformation of normal cells into leukaemic stem cells. This report will review our current knowledge on leukaemic stem cells development and finally demonstrate how these discoveries provide a paradigm for identification of cancer stem cells from solid tumours.
Increasing middle school students’ awareness and interest in manufacturing through digital game‐based learning (DGBL)

The change of the societal appeal of manufacturing among younger generations is a key element in order to address the talent shortage that is currently affecting the sector. In order to pursue this objective, the use of interactive learning environments such as digital games (DGs) can play an important role. Therefore, this paper presents the results of an exploratory study aimed at understanding the impact of digital game‐based learning (DGBL) on the awareness and interest of middle school students in manufacturing. In particular, the students had to deal with the management of EcoFactory, a simplified industrial plant where they had to take care of the main decisions that are typical in the modern manufacturing industry. The study was based on a pre‐test–post‐test quasi‐experimental design conducted in a public middle school in Northern Italy. The research triangulated the results of different methodologies, namely drawings analysis and questionnaires. The results showed a significant impact of the DG both on the awareness and interest of participants, especially in the environmental, social, and economic dimensions. Thus, the outcomes revealed the high potential that DGs have in explaining the complex concepts that are typical of manufacturing and in enhancing students’ proactive motivation toward them. Finally, implications and suggestions for further research derived from these findings are discussed.
On the Stability of Psychological Hardiness: A Three-Year Longitudinal Study

More than 30 years of research has established psychological hardiness as an important individual resiliency resource. One important question still remaining is whether psychological hardiness can be trained. The present study explored this question longitudinally within the context of a 3-year military academy training program. Cadets from 3 different Norwegian military academies (N = 293) completed hardiness questionnaires during the first week of their training, and then again at the end of each year, resulting in a total of 4 waves of data. Using hierarchical linear modeling, no statistically significant effect of time on hardiness scores was found. The nonsignificant growth parameter was examined further using Bayesian statistics as an indicator of the relative evidence for the null hypothesis of no change over time versus the alternative hypothesis of change. The resulting Bayes factor provided substantial support in our data for the null hypothesis of no hardiness development during the 3-year officer training programs.
Pharmacological Profile of Lurasidone, a Novel Antipsychotic Agent with Potent 5-Hydroxytryptamine 7 (5-HT7) and 5-HT1A Receptor Activity

Lurasidone [(3aR,4S,7R,7aS)-2-{(1R,2R)-2-[4-(1,2-benzisothiazol-3-yl)piperazin-1-ylmethyl]cyclohexylmethyl}hexahydro-4,7-methano-2H-isoindole-1,3-dione hydrochloride; SM-13496] is an azapirone derivative and a novel antipsychotic candidate. The objective of the current studies was to investigate the in vitro and in vivo pharmacological properties of lurasidone. Receptor binding affinities of lurasidone and several antipsychotic drugs were tested under comparable assay conditions using cloned human receptors or membrane fractions prepared from animal tissue. Lurasidone was found to have potent binding affinity for dopamine D2, 5-hydroxytryptamine 2A (5-HT2A), 5-HT7, 5-HT1A, and noradrenaline α2C receptors. Affinity for noradrenaline α1, α2A, and 5-HT2C receptors was weak, whereas affinity for histamine H1 and muscarinic acetylcholine receptors was negligible. In vitro functional assays demonstrated that lurasidone acts as an antagonist at D2 and 5-HT7 receptors and as a partial agonist at the 5-HT1A receptor subtype. Lurasidone showed potent effects predictive of antipsychotic activity, such as inhibition of methamphetamine-induced hyperactivity and apomorphine-induced stereotyped behavior in rats, similar to other antipsychotics. Furthermore, lurasidone had only weak extrapyramidal effects in rodent models. In animal models of anxiety disorders and depression, treatment with lurasidone was associated with significant improvement. Lurasidone showed a preferential effect on the frontal cortex (versus striatum) in increasing dopamine turnover. Anti-α1-noradrenergic, anticholinergic, and central nervous system (CNS) depressant actions of lurasidone were also very weak. These results demonstrate that lurasidone possesses antipsychotic activity and antidepressant- or anxiolytic-like effects with potentially reduced liability for extrapyramidal and CNS depressant side effects.
The classification of topologically expansive lorenz maps

We show that topologically expansive Lorenz maps can be described up to topological conjugacy by their kneading invariants. We also give a simple condition on pairs of symbol sequences which is satisfied if and only if that pair of sequences is the kneading invariant for some topologically expansive Lorenz map. A simple extension of the theorems to the case of expansive maps of the interval with multiple discontinuities is described.
Learning Semantic Constraints for the Automatic Discovery of Part-Whole Relations

The discovery of semantic relations from text becomes increasingly important for applications such as Question Answering, Information Extraction, Text Summarization, Text Understanding, and others. The semantic relations are detected by checking selectional constraints. This paper presents a method and its results for learning semantic constraints to detect part-whole relations. Twenty constraints were found. Their validity was tested on a 10,000 sentence corpus, and the targeted part-whole relations were detected with an accuracy of 83%.