Miracle-dz/UniFAR-FTUs huggingface dataset:
Examining the Relationship between Physical Activity and Student Achievement and Behavior: Results from a Three-Year Intervention

This study examines the relationship between physical activity (PA) levels and academic achievement and student behavior in schools that completed a three-year initiative to increase and improve PA for students. Using difference-in-difference and discontinuity analyses, we find schools that participated in a PA intervention saw greater academic achievement during the three years of PA programming as compared to non-participating schools. The significant effects of the intervention were realized during the first year of programming; subsequent years saw stable achievement but not significant growth. There did not, however, appear to be differences in maladaptive student behavior between schools based on participation in the PA intervention.
Neurite outgrowth induced by an endothelial cell mitogen isolated from retina

Retina-derived growth factor (RDGF) is a polypeptide growth factor purified from salt extracts of bovine retinas on the basis of its mitogenic activity for capillary endothelial cells (EC) and BALB/c 3T3 cells. RDGF is angiogenic in vivo. We show here that RDGF induces neurite extension by PC12 cells and that this neurite outgrowth is dramatically potentiated by heparin. Neurite formation elicited by RDGF in the presence of heparin cannot be distinguished from that elicited by nerve growth factor (NGF) either by the time course of neurite formation or by the morphology of the neurites at the level of the light microscope. Neurite outgrowth induced by either purified RDGF or by a crude retinal extract is not blocked by antibodies to NGF. Furthermore, neurite outgrowth induced by NGF is not potentiated by heparin and NGF is not mitogenic for capillary EC. Thus, RDGF has profound regulatory effects on cell types of very different embryonic origins. These results indicate that the physiological role for this growth factor may be far more complex than previously suspected and suggest that the formation of neural connections and the process of vascularization may unexpectedly share common regulatory elements.
Anti-Neutrophil Cytoplasmic Antibodies Positivity and Anti-Leukotrienes in Eosinophilic Granulomatosis with Polyangiitis: A Retrospective Monocentric Study on 134 Italian Patients

Background: Eosinophilic granulomatosis with polyangiitis (EGPA) is a systemic vasculitis associated with asthma, anti-neutrophil cytoplasmic antibodies (ANCA) positivity, and tissue eosinophilia. Objective: To describe the presenting clinical features, significant biochemical alterations, and also potential pathogenic factors in adult patients diagnosed in our Center over a period of >20 years. Method: A retrospective study of EGPA patients diagnosed from 1994 to 2019 at ASST Grande Ospedale Metropolitano Niguarda Ca’ Granda, Milan (Italy), which was performed according to the 1990 American College of Rheumatology criteria and Chapel Hill Consensus Conference definition. A dataset was compiled, registering demographic and clinical features, biochemical analysis at onset, and also the therapies received 3 months prior to EGPA diagnose. Statistical analyses were subsequently conducted dividing patients in 2 groups based on ANCA positivity and comparing them. Results: Two groups were clearly identified by ANCA serology and specific organ involvement in accordance with literature reports; however, our data underline for the first time the association between anti-leukotriene receptor antagonists (LTRAs) and ANCA positivity. The group of previously treated patients presents an OR of 6.42 to be ANCA positive. This finding could be attributed to an imbalanced stimulation of leukotriene receptors, inducing both mast cells activation and an increased neutrophil extracellular traps release from neutrophils. Conclusion: Despite the limitations of this retrospective study, the association between LTRAs and ANCA antibodies elucidates the mechanism by which innate immunity is directly involved in tolerance breakdown and autoantibodies production. Validation of our results with targeted studies could clarify the differences between ANCA-positive and ANCA-negative patients with important consequences on the use of some drug classes in the treatment of EGPA and asthmatic subjects.
Visual monitoring of heartbeat and respiration in Antarctic seals

Heartbeat and respiration of southern elephant seals (Mirounga leonina), Weddell seals (Leptonychotes weddellii) and Antarctic fur seals (Arctocephalus gazella) were monitored simultaneously using a visual and non-intrusive method, at King George Island, South Shetland Islands. All three species demonstrated sleep apnoea with reduced heart rate. In adult elephant seals, heartbeat fell 18% in apnoea; spells lasted up to nine min, usually ending in disturbance from conspecifics or human visitors. Slight human disturbance (notably slight noise) reduced time spent in apnoea from over 40% to 4%, significantly reducing the frequency of falling into apnoea and increasing mean heartbeat. Further disturbance resulted in head raising, aggression, scratching, rolling and movement away. The visual monitoring of heartbeat and respiration can be used with resting or slightly disturbed animals but not when major body movements occur.
Artificial Force Field for Haptic Feedback in UAV Teleoperation

The feedback upon which operators in teleoperation tasks base their control actions differs substantially from the feedback to the driver of a vehicle. On the one hand, there is often a lack of sensory information; on the other hand, there is additional status information presented via the visual channel. Haptic feedback could be used to unload the visual channel and to compensate for the lack of feedback in other modalities. For collision avoidance, haptic feedback could provide repulsive forces via the control inceptor. Haptic feedback allows operators to interpret the repulsive forces as impedance to their control deflections when a potential for collision exists. Haptic information can be generated from an artificial force field (AFF) that maps environment constraints to repulsive forces. This paper describes the design and theoretical evaluation of a novel AFF, i.e., the parametric risk field, for teleoperation of an uninhabited aerial vehicle (UAV). The field allows adjustments of the size, shape, and force gradient by means of parameter settings, which determine the sensitivity of the field. Computer simulations were conducted to evaluate the effectiveness of the field for collision avoidance for various parameter settings. Results indicate that the novel AFF more effectively performs the collision avoidance function than potential fields known from literature. Because of its smaller size, the field yields lower repulsive forces, results in less force cancellation effects, and allows for larger UAV velocities. This indicates less operator control demand and more effective UAV operations, both expected to lead to lower operator workload, while, at the same time, increasing safety.
High performance threaded data streaming for large scale simulations

We have developed a threaded parallel data streaming approach using logistical networking (LN) to transfer multiterabyte simulation data from computers at NERSC to our local analysis/visualization cluster, as the simulation executes, with negligible overhead. Data transfer experiments show that this concurrent data transfer approach is more favorable compared with writing to local disk and later transferring this data to be post-processed. Our algorithms are network aware, and can stream data at up to 97 Mbs on a 100 Mbs link from CA to NJ during a live simulation, using less than 5% CPU overhead at NERSC. This method is the first step in setting up a pipeline for simulation workflow and data management.
Bayesian inference for Hidden Markov Model

Hidden Markov Models can be considered an extension of mixture models, allowing for dependent observations. In a hierarchical Bayesian framework, we show how Reversible Jump Markov Chain Monte Carlo techniques can be used to estimate the parameters of a model, as well as the number of regimes. We consider a mixture of normal distributions characterized by different means and variances under each regime, extending the model proposed by Robert et al. (2000), based on a mixture of zero mean normal distributions.
Real Time Corner Detection for Miniaturized Electro-Optical Sensors Onboard Small Unmanned Aerial Systems

This paper describes the target detection algorithm for the image processor of a vision-based system that is installed onboard an unmanned helicopter. It has been developed in the framework of a project of the French national aerospace research center Office National d’Etudes et de Recherches Aérospatiales (ONERA) which aims at developing an air-to-ground target tracking mission in an unknown urban environment. In particular, the image processor must detect targets and estimate ground motion in proximity of the detected target position. Concerning the target detection function, the analysis has dealt with realizing a corner detection algorithm and selecting the best choices in terms of edge detection methods, filtering size and type and the more suitable criterion of detection of the points of interest in order to obtain a very fast algorithm which fulfills the computation load requirements. The compared criteria are the Harris-Stephen and the Shi-Tomasi, ones, which are the most widely used in literature among those based on intensity. Experimental results which illustrate the performance of the developed algorithm and demonstrate that the detection time is fully compliant with the requirements of the real-time system are discussed.
Australia and the USA promotion in China compared to Thailand , Reported awareness of tobacco advertising and

http://tobaccocontrol.bmj. com/content/18/3/222.full. html Updated information and services can be found at: These include: References http://tobaccocontrol.bmj. com/content/18/3/222.full. html#related-urls Article cited in: http://tobaccocontrol.bmj. com/content/18/3/222.full. html#ref-list-1 This article cites 11 articles, 6 of which can be accessed free at: Open Access is properly cited. use, distribution, and reproduction in any medium, provided the original work Commons Attribution Non-commercial License, which permits unrestricted This is an open-access article distributed under the terms of the Creative
Online clustering algorithms for radar emitter classification

Radar emitter classification is a special application of data clustering for classifying unknown radar emitters from received radar pulse samples. The main challenges of this task are the high dimensionality of radar pulse samples, small sample group size, and closely located radar pulse clusters. In this paper, two new online clustering algorithms are developed for radar emitter classification: One is model-based using the minimum description length (MDL) criterion and the other is based on competitive learning. Computational complexity is analyzed for each algorithm and then compared. Simulation results show the superior performance of the model-based algorithm over competitive learning in terms of better classification accuracy, flexibility, and stability.
Query Anchoring Using Discriminative Query Models

Pseudo-feedback-based query models are induced from a result list of the documents most highly ranked by initial search performed for the query. Since the result list often contains much non-relevant information, query models are anchored to the query using various techniques. We present a novel {\em unsupervised} discriminative query model that can be used, by several methods proposed herein, for query anchoring of existing query models. The model is induced from the result list using a learning-to-rank approach, and constitutes a discriminative term-based representation of the initial ranking. We show that applying our methods to generative query models can improve retrieval performance.
Energy efficient clustering based 3-rank heterogeneous network model for wireless sensor network

Now-a-days many advanced technologies have been innovated in the field of Wireless Sensor Networks (WSN). The main problem regarding wireless sensor network is the improvement of its energy efficiency in the clustering protocol. Most of the direction-finding or path finding challenges are faced by WSN in terms of node deployment, energy consumption, communication range, fault tolerance, quality of service, etc. In this paper, the impact of heterogeneity of nodes are related to their nodes energy are considered. In wireless sensor networks nodes are divided into three types (type-1, 2, 3) based on their energy. We assume that nodes of type-1 energy are equipped with the additional energy resources than type-2 nodes and type-2 is having more energy than type-3 nodes. It is also assumed that the sensor nodes are arbitrarily disseminated. The dimension and sensor field and the coordinates of sink are known in advance. In homogeneous clustering protocol, all sensor nodes have same amount of energy. In this work we worked on energy efficient heterogeneous clustered scheme for WSN. Also we have simulated the results and find that the proposed approach in heterogeneous clustering is more effective in lifetime as compared to other protocols.
Efficient Computation of Spreading Activation Using Lazy Evaluation

Spreading activation is an important component of many computational models of declarative long-term memory retrieval but it can be computationally expensive. The computational overhead has led to severe restrictions on its use, especially in real-time cognitive models. In this paper we describe a series of successively more efficient algorithms for spreading activation. The final model uses lazy evaluation to avoid much of the computation normally associated with spreading activation. We evaluate its efficiency on a commonly-used wordsense disambiguation task where it is significantly faster than a naive model, achieving an average time of 0.43ms per query for a spread to 300 nodes.
Biafra and the Question of Genocide: Examining the Dimensions of Violence in Heroes and Toads of War

Summary Genocide is often used to describe the Igbo experience during the Biafra/Nigeria civil war, particularly within secessionist discourse. This has become a potent tool in gathering support among the Igbo youths – who did not witness the war and consequently rely on “available” narratives of the war. The classification of the war as a genocide presents certain polemics, some are: the difficulty of casting Biafra as vulnerable and lacking in agency; the framing of the war suffering as a universal Igbo experience; the presentation of Biafra as ethnically homogeneous, and that Biafra stimulated linear solidarity from its inhabitants as a force for absolute good. Employing insights from literature, this study reads the dimensions of violence in selected literary narratives of Biafra against International Criminal Court’s definition of genocide. It concludes that there were events that could be described as cases of war crimes narrated in the texts; but there was no intention to annihilate the Igbo. The texts narrate acts of brutality perpetrated by both belligerents. It finds also, that genocide was used as a tool for mobilizing support for the Biafran cause during the war. It was a propaganda tool to gain the attention of the world and to motivate a fight to the end.
Learning as becoming through performance, play and dialogue: A model of game-based learning with the game Legends of Alkhimia.

Thomas and Brown (2007) suggest that games and virtual worlds allow play and learning to merge, enabling “learning to be” rather than “learning about”. In this context, I address the challenge of designing game-based learning to enact a pedagogy of ‘learning as becoming’ in classroom contexts. I argue that the theory of human information processing fails to provide a tenable account of human learning. I propose a pragmatist notion of education that foregrounds experience and inquiry to provide an alternative foundation for envisioning education today. I then draw on social theory to provide a theoretical framing for game-based learning design. I instantiate this framing via the Performance–Play– Dialog (PPD) Model and argue in favour of a shift to performance as a key construct for framing human learning. I illustrate the PPD Model using the game Legends of Alkhimia, a multiplayer game addressing the chemistry curriculum in lower secondary school.
Segmentation and Timbre Similarity in Electronic Dance Music

In this paper we argue that the notion of music similarity should be expanded into sub-similarities, meaning that similarity of music has to be judged with respect to a certain context, such as melody, harmony, rhythm or timbre. We start by focusing on timbre similarity, restricted to the domain of Electronic Dance Music (EDM). We will assess the similarity of segments of music, thus we start by studying segmentation before we come to the topic of similarity. The segmentation algorithm performs well on an EDM dataset as well as on a standard MIREX dataset. Initial listening tests of the similarity model give promising results but will have to be further evaluated in future research.
Shape‐Controlled Synthesis of Metal Nanostructures: The Case of Palladium

This article features shape‐controlled synthesis of Pd nanostructures. Similar to the Ag system, both the crystallinity of seeds and the growth rates of different crystallographic facets play a vital role in determining the final shape of a resultant nanostructure. We specifically discuss how the reduction rate can be controlled to maneuver the crystallinity (i.e., single‐crystal, single twinned, and multiple twinned) of seeds in the nucleation stage. The distribution of multiple twinned and single‐crystal seeds can be further manipulated by employing oxidative etching. As the seed grows into a nanocrystal, the growth rates of different facets (e.g., {111} versus {100}) can be altered with capping agents to control the final shape. The ability to generate Pd nanostructures with a variety of geometrical shapes provides a great opportunity to systematically evaluate their electrical, plasmonic, and catalytic properties, as well as to fully explore their applications.
The World in a Nutshell: Concise Range Queries

With the advance of wireless communication technology, it is quite common for people to view maps or get related services from the handheld devices, such as mobile phones and PDAs. Range queries, as one of the most commonly used tools, are often posed by the users to retrieve needful information from a spatial database. However, due to the limits of communication bandwidth and hardware power of handheld devices, displaying all the results of a range query on a handheld device is neither communication-efficient nor informative to the users. This is simply because that there are often too many results returned from a range query. In view of this problem, we present a novel idea that a concise representation of a specified size for the range query results, while incurring minimal information loss, shall be computed and returned to the user. Such a concise range query not only reduces communication costs, but also offers better usability to the users, providing an opportunity for interactive exploration. The usefulness of the concise range queries is confirmed by comparing it with other possible alternatives, such as sampling and clustering. Unfortunately, we prove that finding the optimal representation with minimum information loss is an NP-hard problem. Therefore, we propose several effective and nontrivial algorithms to find a good approximate result. Extensive experiments on real-world data have demonstrated the effectiveness and efficiency of the proposed techniques.
Augmented Reality Applied in Dietary Monitoring

Abstract Recent advances in augmented reality (AR) have attracted much attention in nutrition and healthcare education. In the context of obtaining dietary knowledge, a mobile AR system was developed for learning and exploration, which allowed students to scan food images, receive information about nutrient content and record as well as accumulate daily nutrient intake. Students could also access learning materials provided in the system to achieve the learning objectives. Their learning outcomes were gathered at the close, with reactions to the learning experiences also assessed via a set of questionnaire items (using a 5 point Likert scale) in various criteria. Both qualitative and quantitative data were gathered, showing that most students achieved the learning objectives and were positive about exploring with AR. The results of this study indicated that students with high levels of monitoring had better learning outcomes (p<0.05) and were more positive about the varied criteria in their responses, including: visual interest and learning enjoyment, functional use, personal relevance and learning of knowledge (p<0.05). The effect of the self-participatory aspect of AR on learning is emphasized.
Fine-grained and efficient lineage querying of collection-based workflow provenance

The management and querying of workflow provenance data underpins a collection of activities, including the analysis of workflow results, and the debugging of workflows or services. Such activities require efficient evaluation of lineage queries over potentially complex and voluminous provenance logs. Näive implementations of lineage queries navigate provenance logs by joining tables that represent the flow of data between connected processors invoked from workflows. In this paper we provide an approach to provenance querying that: (i) avoids joins over provenance logs by using information about the workflow definition to inform the construction of queries that directly target relevant lineage results; (ii) provides fine grained provenance querying, even for workflows that create and consume collections; and (iii) scales effectively to address complex workflows, workflows with large intermediate data sets, and queries over multiple workflows.
Effects of Valproic Acid and Dexamethasone Administration on Early Bio-Markers and Gene Expression Profile in Acute Kidney Ischemia-Reperfusion Injury in the Rat

Renal ischemia-reperfusion (IR) causes acute kidney injury (AKI) with high mortality and morbidity. The objective of this investigation was to ameliorate kidney IR injury and identify novel biomarkers for kidney injury and repair. Under general anesthesia, left renal ischemia was induced in Wister rats by occluding renal artery for 45 minutes, followed by reperfusion and right nephrectomy. Thirty minutes prior to ischemia, rats (n = 8/group) received Valproic Acid (150 mg/kg; VPA), Dexamethasone (3 mg/kg; Dex) or Vehicle (saline) intraperitoneally. Animals were sacrificed at 3, 24 or 120 h post-IR. Plasma creatinine (mg/dL) at 24 h was reduced (P<0.05) in VPA (2.7±1.8) and Dex (2.3±1.2) compared to Vehicle (3.8±0.5) group. At 3 h, urine albumin (mg/mL) was higher in Vehicle (1.47±0.10), VPA (0.84±0.62) and Dex (1.04±0.73) compared to naïve (uninjured/untreated control) (0.14±0.26) group. At 24 h post-IR urine lipocalin-2 (μg/mL) was higher (P<0.05) in VPA, Dex and Vehicle groups (9.61–11.36) compared to naïve group (0.67±0.29); also, kidney injury molecule-1 (KIM-1; ng/mL) was higher (P<0.05) in VPA, Dex and Vehicle groups (13.7–18.7) compared to naïve group (1.7±1.9). Histopathology demonstrated reduced (P<0.05) ischemic injury in the renal cortex in VPA (Grade 1.6±1.5) compared to Vehicle (Grade 2.9±1.1). Inflammatory cytokines IL1β and IL6 were downregulated and anti-apoptotic molecule BCL2 was upregulated in VPA group. Furthermore, kidney DNA microarray demonstrated reduced injury, stress, and apoptosis related gene expression in the VPA administered rats. VPA appears to ameliorate kidney IR injury via reduced inflammatory cytokine, apoptosis/stress related gene expression, and improved regeneration. KIM-1, lipocalin-2 and albumin appear to be promising early urine biomarkers for the diagnosis of AKI.