Miracle-dz/UniFAR-FTUs huggingface dataset:
An Intervention-Based Program of Research on Teachers’ Motivating Styles

Abstract Purpose Our ongoing program of research works with teachers to help them become more autonomy supportive during instruction and hence more able to promote students’ classroom motivation and engagement. Design/methodology/approach We have published five experimentally based, longitudinally designed, teacher-focused intervention studies that have tested the effectiveness and educational benefits of an autonomy-supportive intervention program (ASIP). Findings Findings show that (1) teachers can learn how to become more autonomy supportive and less controlling toward students, (2) students of the teachers who participate in ASIP report greater psychological need satisfaction and lesser need frustration, (3) these same students report and behaviorally display a wide range of important educational benefits, such as greater classroom engagement, (4) teachers benefit as much from giving autonomy support as their students do from receiving it as teachers show large postintervention gains in outcomes such as teaching efficacy and job satisfaction, and (5) these ASIP-induced benefits are long lasting as teachers use the ASIP experience as a professional developmental opportunity to upgrade the quality of their motivating style. Originality/value Our ASIP helps teachers learn how to better support their students’ autonomy during instruction. The value of this teaching skill can be seen in teachers’ and students’ enhanced classroom experience and functioning.
Molecular codes for neuronal individuality and cell assembly in the brain

The brain contains an enormous, but finite, number of neurons. The ability of this limited number of neurons to produce nearly limitless neural information over a lifetime is typically explained by combinatorial explosion; that is, by the exponential amplification of each neuron's contribution through its incorporation into “cell assemblies” and neural networks. In development, each neuron expresses diverse cellular recognition molecules that permit the formation of the appropriate neural cell assemblies to elicit various brain functions. The mechanism for generating neuronal assemblies and networks must involve molecular codes that give neurons individuality and allow them to recognize one another and join appropriate networks. The extensive molecular diversity of cell-surface proteins on neurons is likely to contribute to their individual identities. The clustered protocadherins (Pcdh) is a large subfamily within the diverse cadherin superfamily. The clustered Pcdh genes are encoded in tandem by three gene clusters, and are present in all known vertebrate genomes. The set of clustered Pcdh genes is expressed in a random and combinatorial manner in each neuron. In addition, cis-tetramers composed of heteromultimeric clustered Pcdh isoforms represent selective binding units for cell-cell interactions. Here I present the mathematical probabilities for neuronal individuality based on the random and combinatorial expression of clustered Pcdh isoforms and their formation of cis-tetramers in each neuron. Notably, clustered Pcdh gene products are known to play crucial roles in correct axonal projections, synaptic formation, and neuronal survival. Their molecular and biological features induce a hypothesis that the diverse clustered Pcdh molecules provide the molecular code by which neuronal individuality and cell assembly permit the combinatorial explosion of networks that supports enormous processing capability and plasticity of the brain.
The Reliability of Small Area Estimation Prediction Methods to Track Poverty

Tracking poverty is predicated on the availability of comparable consumption data and reliable price deflators. However, regular series of strictly comparable data are only rarely available. Poverty prediction methods that track consumption correlates as opposed to consumption itself have been developed to overcome such data gaps. These methods typically assume that the estimated relation between consumption and its predictors is stable over time—assumptions that usually cannot be tested directly. This study analyses the performance of poverty prediction models based on small area estimation (SAE) techniques. Predicted poverty estimates are compared to directly observed levels in a series of country settings that are widely divergent, but where data comparability over time is not judged to be a problem. Prediction models that employ either nonfood expenditures or a full set of assets as predictors, yield poverty estimates that match observed poverty fairly closely. This offers some support for using SAE techniques especially those based on models employing household assets, to approximate the evolution of poverty in settings where comparable consumption data are absent or settings where price deflators are of dubious validity. However, the findings also call for further validation especially in settings with rapid, transitory poverty deterioration, as in Russia during the 1998 financial crisis.
Combining RDF Graph Data and Embedding Models for an Augmented Knowledge Graph

Vector embedding models have recently become popular for encoding both structured and unstructured data. In the context of knowledge graphs such models often serve as additional evidence supporting various tasks related to the knowledge base population: e.g., information extraction or link prediction to expand the original dataset. However, the embedding models themselves are often not used directly alongside structured data: they merely serve as additional evidence for structured knowledge extraction. In the metaphactory knowledge graph management platform, we use federated hybrid SPARQL queries for combining explicit information stated in the graph, implicit information from the associated embedding models, and information extracted using vector embeddings in a transparent way for the end user. In this paper we show how we integrated RDF data with vector space models to construct an augmented knowledge graph to be used in customer applications.
Posterolateral Bundle Reconstruction With Anteromedial Bundle Remnant Preservation in ACL Tears

Background: Augmentation consisting of a selective reconstruction of the ruptured bundle while preserving the remnant bundle has been proposed as a treatment option for partial anterior cruciate ligament (ACL) tears. Good clinical outcomes after selective anteromedial (AM) bundle augmentation have been reported, whereas little is known about selective reconstruction of the posterolateral (PL) bundle with preservation of the AM bundle remnant. Purpose: The purpose of this study was to evaluate the clinical outcomes and the magnetic resonance imaging (MRI) characteristics of selective PL bundle reconstruction with a median follow-up of 24 months. Study Design: Case series; Level of evidence, 4. Methods: In a consecutive series of 741 ACL reconstructions, 44 patients underwent a selective PL bundle reconstruction with preservation of the AM remnant. Four patients with contralateral knee ligament surgery and 1 patient who sustained a traumatic rupture of his graft were excluded, leaving 39 patients for final evaluation. Clinical evaluation of knee function and laxity were recorded preoperatively and at a mean 24.2-month follow-up. Magnetic resonance imaging was performed on 35 patients at a mean 25.9-month follow-up for evaluation of graft and remnant bundle continuity, tunnel enlargement, and graft remodeling status by measuring the signal intensity of the graft (contrast/noise quotient [CNQ]). Results: Tegner and Lysholm knee scores were significantly improved after surgery. The subjective International Knee Documentation Committee (IKDC) score was 43.5 ± 16.6 preoperatively and 89.9 ± 6.6 at the final follow-up (P < .01). The objective IKDC score was “B” for 17 patients, “C” for 21 patients, and “D” for 1 patient preoperatively, while it was “A” for 34 patients and “B” for 5 patients postoperatively (P < .01). The mean side-to-side anteroposterior laxity was 5 mm (range, 4-10 mm) preoperatively and 1.5 mm (range, −1 to 4 mm) at final follow-up (P < .01). On MRI, the graft was visible and continuous in all cases. No cyclops lesions were noted. The average CNQ for the PL graft and the AM remnant bundle was 3.2 ± 1 and 2.9 ± 1.2, respectively. Minimum bone tunnel enlargement was found. Conclusion: Selective PL bundle reconstruction restores knee stability and function. At final follow-up, MRI showed continuity of the PL graft without signs of dramatic tunnel enlargement or cyclops syndrome.
Mutations associated with virological response to darunavir/ritonavir in HIV-1-infected protease inhibitor-experienced patients.

OBJECTIVE The aim of the study was to identify a pattern of protease gene mutations associated with the virological response to darunavir/ritonavir-based regimens. PATIENTS AND METHODS We analysed 153 treatment-experienced patients receiving a darunavir/ritonavir salvage regimen as a sole protease inhibitor (PI). Virological response was defined as an HIV-1 RNA load of <200 copies/mL at month 3. The impact of individual protease gene mutations on the virological response to darunavir/ritonavir was examined, and the combination of mutations most strongly associated with the virological response was identified. RESULTS The baseline median HIV RNA level was 4.7 log(10) copies/mL and the median CD4 cell count was 142 cells/mm(3). At month 3, 55% of patients had a virological response and the median fall in viral load from baseline was 1.7 log(10) copies/mL. All the patients had detectable darunavir concentrations at month 3. Cochran-Armitage procedure identified eight mutations with a negative impact on the virological response, namely K14R, K20I, E34Q, I47V, I54M, K55R, T74P and I84V; and two mutations (E35D and V82A) with a positive impact. In multivariate analyses, our genotypic scores were highly predictive of the virological response at month 3, along with the baseline plasma viral load and enfuvirtide co-prescription to enfuvirtide-naive patients. CONCLUSIONS Among the eight mutations with a negative impact on the virological response, I47V, I54M, T74P and I84V were previously described as darunavir resistance-associated mutations. Some PI resistance mutations had a positive impact on the virological response. These findings might help to explain the potency of darunavir/ritonavir on PI-resistant HIV.
Lymphangiogenesis Is Required for Pancreatic Islet Inflammation and Diabetes

Lymphangiogenesis is a common phenomenon observed during inflammation and engraftment of transplants, but its precise role in the immune response and underlying mechanisms of regulation remain poorly defined. Here we showed that in response to injury and autoimmunity, lymphangiogenesis occurred around islets and played a key role in the islet inflammation in mice. Vascular endothelial growth factors receptor 3 (VEGFR3) is specifically involved in lymphangiogenesis, and blockade of VEGFR3 potently inhibited lymphangiogenesis in both islets and the draining LN during multiple low-dose streptozotocin (MLDS) induced autoimmune insulitis, which resulted in less T cell infiltration, preservation of islets and prevention of the onset of diabetes. In addition to their well-known conduit function, lymphatic endothelial cells (LEC) also produced chemokines in response to inflammation. These LEC attracted two distinct CX3CR1hi and LYVE-1+ macrophage subsets to the inflamed islets and CX3CR1hi cells were influenced by LEC to differentiate into LYVE-1+ cells closely associated with lymphatic vessels. These observations indicate a linkage among lymphangiogenesis and myeloid cell inflammation during insulitis. Thus, inhibition of lymphangiogenesis holds potential for treating insulitis and autoimmune diabetes.
Social relationships between staff and youth in a physical activity-based positive youth development program

This study used a randomized controlled design to test the pathways in basic psychological needs theory where social relationships characterized by autonomy support, involvement, and structure foster psychological need satisfaction and well-being (Deci & Ryan, 2000). Study participants were recruited from a physical activity-based youth program. A randomized controlled trial of a new staff training was implemented to manipulate the use of each interpersonal characteristic by program staff (N=24), and perceptions of each interpersonal characteristic, psychological need satisfaction, hope, and self-worth in youth (N=379). Compared to the control condition, the intervention condition engaged youth using more autonomy support and structure. Staff condition assignment did not lead to differences in youth perceptions, but youth perceptions of staff predicted well-being. Findings indicate that the staff training manipulated how staff interacted with youth, and autonomy support, involvement, and structure are useful strategies to help staff develop social relationships that foster well-being in youth.
The GSR implications in the human unfamiliar faces recognition

This paper is focused on showing the implications of GSR reactivity to unfamiliar human faces recognition. The method: The participants were the undergraduate students at the Faculty of Psychology and Educational Sciences, University of Bucharest, both male and female in all three experiments. The instruments: The Lafayette Polygraph 4000 platinum series and three sets of photos as follows: red neutral unfamiliar faces, lamp lighted neutral unfamiliar faces and cap covered neutral unfamiliar faces. The results highlighted that the GSR reactivity to correct and incorrect unfamiliar faces recognition is coordinated by the limbic system. Furthermore, the GSR has implications in the memory task of faces recognition. The conclusions emphasize the fact that the faces seen by the participants are unconsciously memorized and with the help of the GSR, which is coordinated by the limbic system, a signal appears and reveals the incongruity or the false recognition when the subject has mistakenly recognized and when he or she did not recognize the image containing the stimulus (the face) previously seen. Keywords-unfamiliar faces recognition, unfamiliar dark lamp lighted faces, unfamiliar red neutral faces.
International Journal of Physical Distribution & Logistics Management

Purpose – The purpose of this paper is to investigate the impact of demand uncertainty on inventory turnover performance through empirical modeling. In particular the authors use the inaccuracy of quarterly sales forecasts as a proxy for demand uncertainty and study its impact on firm-level inventory turnover ratios. Design/methodology/approach – The authors use regression analysis to study the effect of various measures on inventory performance. The authors use a sample financial data for 304 publicly listed US retail firms for the 25-year period from 1985 to 2009. Findings – Controlling for the effects of retail segments and year, it is found that inventory turnover is negatively correlated with mean absolute percentage error of quarterly sales forecasts and gross margin and positively correlated with capital intensity and sales surprise. These four variables explain 73.7 percent of the variation across firms and over time and 93.4 percent of the within-firm variation in the data. Practical implications – In addition to conducting an empirical investigation for the sources of variation in a major operational metric, the results in this study can also be used to benchmark a retailer ’ s inventory performance against its competitors. Originality/value – The authors develop a new proxy to measure the demand uncertainty that a firm faces and show that this measure may help to explain the variation in inventory performance.
Low and Medium Level Vision Using Channel Representations

This thesis introduces and explores a new type of representation for low and medium level vision operations called channel representation. The channel representation is a more general way to represent information than e.g. as numerical values, since it allows incorporation of uncertainty, and simultaneous representation of several hypotheses. More importantly it also allows the representation of “no information” when no statement can be given. A channel representation of a scalar value is a vector of channel values, which are generated by passing the original scalar value through a set of kernel functions. The resultant representation is sparse and monopolar. The word sparse signifies that information is not necessarily present in all channels. On the contrary, most channel values will be zero. The word monopolar signifies that all channel values have the same sign, e.g. they are either positive or zero. A zero channel value denotes “no information”, and for non-zero values, the magnitude signifies the relevance. In the thesis, a framework for channel encoding and local decoding of scalar values is presented. Averaging in the channel representation is identified as a regularised sampling of a probability density function. A subsequent decoding is thus a mode estimation technique. ' The mode estimation property of channel averaging is exploited in the channel smoothing technique for image noise removal. We introduce an improvement to channel smoothing, called alpha synthesis, which deals with the problem of jagged edges present in the original method. Channel smoothing with alpha synthesis is compared to mean-shift filtering, bilateral filtering, median filtering, and normalized averaging with favourable results. A fast and robust blob-feature extraction method for vector fields is developed. The method is also extended to cluster constant slopes instead of constant regions. The method is intended for view-based object recognition and wide baseline matching. It is demonstrated on a wide baseline matching problem. A sparse scale-space representation of lines and edges is implemented and described. The representation keeps line and edge statements separate, and ensures that they are localised by inhibition from coarser scales. The result is however still locally continuous, in contrast to non-max-suppression approaches, which introduce a binary threshold. The channel representation is well suited to learning, which is demonstrated by applying it in an associative network. An analysis of representational properties of associative networks using the channel representation is made. Finally, a reactive system design using the channel representation is proposed. The system is similar in idea to recursive Bayesian techniques using particle filters, but the present formulation allows learning using the associative networks.
Numerical Analysis of the Arc Plasma in a Simplified Low-voltage Circuit Breaker Chamber with Ferromagnetic Materials

This paper is devoted to the simulation of the arc plasma in a simplified low-voltage circuit breaker chamber. Based on a group of coupled governing equations, a three-dimensional (3-D) arc plasma model is built and solved by a modified commercial code. Firstly, this paper presents a solution of the stationary state of the arc plasma and discusses the distribution of some parameters throughout the chamber. Secondly, with the ferromagnetic materials included, the balance of the stationary state is broken and a transient course is calculated. In light of the simulation results, the temperature distribution sequence, the arc motion and the plasma jet are then described and analyzed in detail.
Is there a deprivation and maternal education gradient to child obesity and moderate‐to‐vigorous physical activity? Findings from the Millennium Cohort Study

The primary aim was to examine associations between individual‐level and area‐level measures of socioeconomic status (SES) and different measures of overweight/obesity in 7‐year‐old English children. A secondary aim was to examine associations between individual‐level and area‐level measures of SES and moderate‐to‐vigorous intensity physical activity (MVPA).
Efficient Dynamic Framed Slotted ALOHA for RFID Passive Tags

Radio frequency identification systems with passive tags dramatically increase the ability of an organization to acquire a vast array of data about the location and properties of any entity that can be physically tagged and wirelessly scanned within certain technical limitations. However, if multiple tags are to be identified simultaneously, messages from the tags can collide and cancel each other out. One of the popular anti-collision algorithms is the ALOHA-type algorithm, which is simple and has good performance when the number of tags to be read is reasonably small. In this paper we extended our previous research to an efficient dynamic framed slotted ALOHA for RFID passive tags. Some problems related to the ALOHA for RFID passive tags are investigated and corrected.
The development and validation of a learning progression for argumentation in science

Given the centrality of argumentation in the Next Generation Science Standards, there is an urgent need for an empirically validated learning progression of this core practice and the development of high-quality assessment items. Here, we introduce a hypothesized three-tiered learning progression for scientific argumentation. The learning progression accounts for the intrinsic cognitive load associated with orchestrating arguments of increasingly complex structure. Our proposed learning progression for argumentation in science also makes an important distinction between construction and critique. We present validity evidence for this learning progression based on item response theory, and discuss the development of items used to test this learning progression. By analyzing data from cognitive think-aloud interviews of students, written responses on pilot test administrations, and large-scale test administrations using a Rasch analysis, we discuss the refinement both of our items and our learning progression to improve construct validity and scoring reliability. Limitations to this research as well as implications for future work on assessment of scientific argumentation are discussed. © 2016 Wiley Periodicals, Inc. J Res Sci Teach
Cultural Differences in Retrieval of Self-Defining Memories

Australians and Asians were asked to provide autobiographical memories of events they believe shaped who they are as individuals (self-defining memories). The authors found the anticipated cultural differences for the memories' themes. Contrary to previous suggestions, however, elaboration of personal memories occurred equally for both groups and was dependent on the content of the memory. Australians provided more elaborate autonomous memories and Asians more elaborate relatedness memories. The findings indicate that elaborating personal memories may function to enhance the dominant self-focus.
Fast complex adaptive spline neural networks for digital signal processing

We study a complex-domain artificial neural networks, called the adaptive spline neural network, defined in the complex domain, which is able to adapt its activation functions by varying the control points of a Catmull-Rom cubic spline. This kind of neural network can be implemented as a very simple structure which is able to improve the generalization capabilities using few training epochs. Due to its low architectural complexity the network can be used to cope with several nonlinear DSP problems at high sampling rate. In particular, we investigate the application of this new neural network model to the adaptive channel equalization problem. The goal is to design a receiver which compensates the high power amplifier nonlinearities in digital radio links and performs the symbols extraction from the received data (demodulation process), when a 16-QAM is used.