Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhanced Milieu Teaching in resource-constrained settings: Stakeholder-informed adaptation guidelines

Background Enhanced Milieu Teaching (EMT) is an evidence-based naturalistic developmental behavioural intervention (NDBI) for children with developmental disabilities. Little is known about the EMT’s fit or what adaptations might be needed to improve its applicability within a resource-constrained setting. Objectives To explore stakeholders’ perceptions of the contextual fit of EMT for young children with developmental disabilities in a resource-constrained context and to identify adaptations to improve EMT’s contextual fit. Method We conducted a descriptive qualitative study using semi-structured interviews and focus groups. Participants included 5 speech and language therapists and 11 caregivers of children with developmental disabilities who speak English and Afrikaans or isiXhosa. Using thematic analysis, data were coded into 10 subthemes and grouped according to the Adaptome framework components. Results Overall, stakeholders view EMT as an appropriate intervention in the South African context. They indicated that certain intervention components may need to be modified. Specifically, clinicians may need to adapt intervention materials and activities to be sensitive to families’ available resources, preferred activity routines and priorities. From these data, we provide guidelines to improve the fit of EMT in South Africa. Conclusion Enhanced Milieu Teaching is an appropriate intervention in the South African context, although some adaptations can enhance its fit. Contribution This article highlights the importance of engaging with stakeholders to determine the fit of NDBIs, like EMT, as they are implemented in new contexts. Based on these insights, stakeholder-informed adaptation guidelines are provided for improving the contextual fit of EMT in resource-constrained settings.
Does the leap-for-distance test correlate with short sprint performance in young soccer players? A between- and within-player analysis

This study analysed the longitudinal relationship between short sprint time and the leap-for-distance test using novel motion tracking in young soccer players. Players (n = 144, age 14.8 ± 1.8 years) from six English Elite Player Performance Plan category three clubs completed two linear sprints (10 m, 20 m) and a leap-for-distance test (cm), on three to seven occasions across three seasons. Within-player (repeated measures) and between-player (mean of the repeated measures) correlation coefficients were calculated and stratified by pre-and post-peak height velocity (PHV). Very large, negative between-player correlations were found for leap-for-distance vs. sprint time (10 m: r = -0.70, 95% CI [- 0.77, -0.61]; 20 m: r = -0.77, 95% CI [-0.83, -0.70]). Correlations were large for pre-PHV (10 m: r = -0.52, 95% CI [-0.71, -0.26]; 20 m: r = -0.62, 95% CI [-0.78, -0.39]) and moderate-to-large for post-PHV (10 m: r = -0.43, 95% CI [-0.60, -0.24]; 20 m: r = -0.54, 95% CI [-0.68, -0.36], respectively). Within-player correlations were trivial-to-small for all players (10 m: r = -0.14, 95% CI [-0.24, -0.06]; 20 m: r = -0.24, 95% CI [-0.34, -0.16]) and for pre-and post-PHV subgroups (r’s < -0.30). Leap-for-distance is a useful discriminator of sprint performance but should not be used for tracking intra-player sprint changes in young soccer players, irrespective of maturation.
Deep Flow Cytometry Unveils Distinct Immune Cell Subsets in Inducible T Cell Co-Stimulator Ligand (ICOSL)- and ICOS-Knockout Mice during Experimental Autoimmune Encephalomyelitis

The inducible T cell co-stimulator ligand (ICOSL), expressed by antigen presenting cells, binds to the inducible T cell co-stimulator (ICOS) on activated T cells. Improper function of the ICOS/ICOSL pathway has been implicated in several autoimmune diseases, including multiple sclerosis (MS). Previous studies showed that ICOS-knockout (KO) mice exhibit severe experimental autoimmune encephalomyelitis (EAE), the animal model of MS, but data on ICOSL deficiency are not available. In our study, we explored the impact of both ICOS and ICOSL deficiencies on MOG35-55 -induced EAE and its associated immune cell dynamics by employing ICOSL-KO and ICOS-KO mice with a C57BL/6J background. During EAE resolution, MOG-driven cytokine levels and the immunophenotype of splenocytes were evaluated by ELISA and multiparametric flow cytometry, respectively. We found that both KO mice exhibited an overlapping and more severe EAE compared to C57BL/6J mice, corroborated by a reduction in memory/regulatory T cell subsets and interleukin (IL-)17 levels. It is noteworthy that an unsupervised analysis showed that ICOSL deficiency modifies the immune response in an original way, by affecting T central and effector memory (TCM, TEM), long-lived CD4+ TEM cells, and macrophages, compared to ICOS-KO and C57BL/6J mice, suggesting a role for other binding partners to ICOSL in EAE development, which deserves further study.
Mucoadhesive Polymeric Polyologels Designed for the Treatment of Periodontal and Related Diseases of the Oral Cavity

The study objective was to design and characterise herein unreported polyologels composed of a range of diol and triol solvents and polyvinyl methyl ether-co-maleic acid (PVM/MA) and, determine their potential suitability for the treatment of periodontal and related diseases in the oral cavity using suitable in vitro methodologies. Polyologel flow and viscoelastic properties were controlled by the choice of solvent and the concentration of polymer. At equivalent polymer concentrations, polyologels prepared with glycerol (a triol) exhibited the greatest elasticity and resistance to deformation. Within the diol solvents (PEG 400, pentane 1,5-diol, propane 1,2-diol, propane 1,3-diol, and ethylene glycol), PEG 400 polyologels possessed the greatest elasticity and resistance to deformation, suggesting the importance of distance of separation between the diol groups. Using Raman spectroscopy bond formation between the polymer carbonyl group and the diol hydroxyl groups was observed. Polyologel mucoadhesion was influenced by viscoelasticity; maximum mucoadhesion was shown by glycerol polyologels at the highest polymer concentration (20% w/w). Similarly, the choice of solvent and concentration of PVM/MA affected the release of tetracycline from the polyologels. The controlled release of tetracycline for at least 10 h was observed for several polyologels, which, in combination with their excellent mucoadhesion and flow properties, offer possibilities for the clinical use of these systems to treat diseases within the oral cavity.
Perbandingan Normalisasi Data untuk Klasifikasi Wine Menggunakan Algoritma K-NN

Abstrak— Rentang nilai yang tidak seimbang pada setiap atribut dapat mempengaruhi kualitas hasil data mining. Untuk itu diperlukan adanya praproses data. Praproses ini diharapkan dapat meningkatkatkan keakuratan hasil dari pengklasifikasian dataset wine. Metode praproses yang digunakan adalah transformasi data dengan normalisasi. Ada tiga cara yang dilakukan dalam transformasi data dengan normalisasi, yaitu min-max normalization, z-score normalization, dan decimal scaling. Data yang telah diproses dari setiap metode normalisasi akan dibandingan untuk melihat hasil akurasi terbaik klasifikasi dengan menggunakan algoritama K-NN. K yang digunakan dalam perbandingan adalah 1, 3, 5, 7, 9, 11. Sebelum dilakukan pengklasifikasian dataset wine yang telah dinormalisasi dibagi menjadi data uji dan data latih dengan k-fold cross validation. Pembagian data menggunakan k sama dengan 10. Hasil pengujian klasifikasi dengan algoritma K-NN menunjukkan, bahwa akurasi terbaik terletak pada dataset wine yang telah dinormalisasi menggunakan metode min-max normalization dengan K = 1 sebesar 65,92%. Rata-rata yang diperoleh, yaitu 59,68%. Keywords— Normalisasi, K-fold cross validation, K-NN
The Pythia-JNI Package: A Java Interface to Pythia

The Pythia-JNI package is a stand-alone software system for setting up and running the Pythia Monte Carlo program from within Java. Full Pythia functionality is provided through a simple “straghtforward” interface to native FORTRAN code. The package includes examples for running Pythia within a Java framework for Linear Collider detector (LCD) simulations. These LCD examples use Pythia for event generation, execute the U.S. Fast Monte Carlo (FMC) detector simulation and perform user analysis in Java and/or FORTRAN.
Single Image Reflection Removal with Edge Guidance, Reflection Classifier, and Recurrent Decomposition Supplementary Materials

In this section, we demonstrate the computation time and memory usage under two real-world benchmark datasets, in comparison with several baselines. Since some baselines take up a lot of memory, we adjust the size of the input image to 256× 256 in order to run the process on only one GPU. As shown in Table 1 and Table 2, we can see that our proposed method is 3.3 times faster than the state-of-the-art IBCLN [3] with comparable memory usage.
Energy and Throughput Optimization of Wireless Mesh Network with Continuous Power Control

Providing high data rate with minimum energy consumption is a crucial challenge for next generation wireless networks. This paper focuses on wireless mesh networks using a MAC layer based on S-TDMA (Spatial Time Division Multiple Access). We investigate on the optimization issues combining throughput and energy consumption. Our contributions are two-fold. First, we formulate and solve using column generation a new MILP to compute the energy-throughput tradeoff curve under a physical interference model when the nodes can perform continuous power control and can use a discrete set of data rates. Second, we highlight some network engineering insights. In particular, we show that power control and multi-rate functionalities allow to reach optimal throughput with lower energy consumption using a mix of single hop and multihop routes. Key-words: Mesh networks, capacity, energy, scheduling, resource allocation. ∗ Corresponding author Partially supported by ANR VERSO ECOSCells † Université de Lyon, INRIA, INSA Lyon, CITI, F-69621, France ‡ Université de Lyon, INRIA, INSA Lyon, CITI, F-69621, France § Department of Electrical and Computer Engineering, University of Waterloo, Canada Optimisation de la la consommation d’énergie et de débit des réseaux radio maillés avec un contrôle de puissance continu Résumé : Offrir un haut débit avec une consommation d’énergie faible est un défi pour les réseaux sans fil de nouvelle génération. Ce papier se focalise sur les réseaux maillés sans fil à large bande utilisant la technique S-TDMA (Spatial Time Division Multiple Access). Nous nous intéressons en particulier à la problématique motivante de l’optimisation de la capacité du réseau et de la consommation d’énergie. Nous développons des modèles d’optimisation en programmation linéaire intégrant un modèle d’interférences SINR avec un contrôle de puissance continu et une variation de taux de transmission. Nous utilisons la technique de génération de colonnes pour résoudre le problème d’une manière efficace. Ensuite, Nous mettons en lumière un ensemble de règles d’ingénieries. En particulier, nous montrons que le contrôle de puissance et la variation de taux de transmission sont nécessaires pour un fonctionnement optimale du réseau offrant un débit maximal avec une consommation efficace en énergie. Mots-clés : Réseaux Radio Maillés, capacité, consommation énergétique, allocation de ressource. Energy and Throughput Optimization of WMN 3
Web Page Classification: Features and Algorithms

Classification of web page content is essential to many tasks in web information retrieval such as maintaining web directories and focused crawling. The uncontrolled nature of web content presents additional challenges to web page classification as compared to traditional text classification, but the interconnected nature of hypertext also provides features that can assist the process. As we review work in web page classification, we note the importance of these web-specific features and algorithms, describe state-of-the-art practices, and track the underlying assumptions behind the use of information from neighboring pages.
Geographic Information Systems Applications on an ATM-Based Distributed High Performance Computing System

We present a distributed geographic information system (DGIS) built on a distributed high performance computing environment using a number of software infrastructural building blocks and computational resources interconnected by an ATM-based broadband network. Archiving, access and processing of scientific data are discussed in the context of geographic and environmental applications with special emphasis on the potential for local-area weather, agriculture, soil and land management products. Software technologies such as tiling and caching techniques can be used to optimise storage requirements and response time for applications requiring very large data sets such as multi-channel satellite data. Distributed High Performance Computing hardware technology underpins our proposed system. In particular, we discuss the capabilities of a distributed hardware environment incorporating: high bandwidth communications networks such as Telstra’s Experimental Broadband Network (EBN); large capacity hierarchical storage systems; and high performance parallel computing resources.
The Role of Digital Knowledge Richness in Green Technology Adoption

Ⅰ. IntroductionⅡ. Theoretical Background2.1 Green Technology2.2 The UTAUT22.3 Digital Option Theory: Digitized KnowledgeⅢ. Research Model and Hypotheses3.1 Preliminary Study3.2 Research ModelⅣ. Methods4.1 Measures4.2 Participants and Experimental ProceduresⅤ. Data Analysis and Results5.1 Measurement Model5.2 Structural Model5.3 Moderating EffectsⅥ. Discussion6.1 Summary6.2 Theoretical Contributions6.3 Practical Implications6.4 Limitations and Future Research
A debate dashboard to enhance on-line knowledge sharing

(2010). A debate dashboard to enhance on-line knowledge sharing. Copyright and Moral Rights for the articles on this site are retained by the individual authors and/or other copyright owners. For more information on Open Research Online's data policy on reuse of materials please consult the policies page. Structured Abstract Purpose – Web 2.0 technologies have radically modified the way in which knowledge is created, managed and shared, improving productivity and accelerating innovation processes for the enterprises. These technologies have allowed enterprises to produce knowledge, leverage collective intelligence and build social capital on a scale that was unimaginable a few years ago. In this paper we focus on a particular kind of web-based collaborative platforms known as argument mapping tools and we discuss the main barriers to the adoption of them. Literature has proved that these argument mapping tools provide large and small and medium enterprise with several advantages, but nevertheless, they have low level adoption. In this paper we explore new technological solutions to support the adoption of argument mapping tools. In particular, we propose the design of a Debate Dashboard to provide visual feedback to support online deliberation. These visual feedback aims at compensating the loss of information due to the mediation of the technology. The Debate Dashboard is composed of a set of suitable visualization tools that have been selected on the basis of a literature review of the visualization tools. Design/methodology/approach – We propose a literature review of existing visualization tools. Building on the literature review we selected thirty visualization tools, which have been classified on the basis of the kind of feedback they are able to provide. We identify three classes of feedback: Community feedback (identikit of users), Interaction feedback (about how users interact) and Absorption feedback (about generated 2 content and its organization). We distilled the Debate Dashboard features by building on results of a literature review on Web 2.0 tools for data visualization. As output of literature review we selected six visualization tools. We consider these selected tools as a sort of starting point. Indeed, our aim is the improvement of them through the addition of further features and functions in order to make them more effective in providing feedback. Originality/value – Our paper enriches the debate about computer mediated conversation and visualization tools. We propose a Dashboard prototype to augment collaborative knowledge mapping tools by providing visual feedback on conversations. The Dashboard will …
Towards a Web Decision System Support for Planning Micro-Watershed Using Pressure-State-Response and Logic Fuzzy, Study Case in Colombia

This paper presents a conceptual web decision support systems (DSS) for assessment of a tropical Andean micro-watershed. A combination of pressure-state-response (PSR) indicators and logic fuzzy were used. Three indices were defined: climate change (ICC), quality water (IQW) and soil degradation (ISD). Each index is a combination of qualitative and quantitative indicators. Fuzzy functions were defined to generate operability in each index. Trapezoidal, triangular and singleton functions were defined. The inputs are the indicators value in each zones of the watershed: high zone, medium zone and low zone. Outputs of WebDSS are the value of each index. The Web DSS was applied in an Andean watershed named “El Chocho”, in Colombia. The results indicate the high degradation level in the watershed, evidenced by the indices values. This study indicates the possibility of building and applying a DSS to support management decision process in Andean microwatersheds.
Interior Design Using Augmented Reality

In this paper we are going to represent an application of Augmented Reality technology for interior design. Along with the time and growth of digital technology, virtual techniques are required . We know that nowadays , people are busy with their work and thus it’s very time consuming to visit various stores to buy furniture for their everyday use. There is difficulty to fulfill the customers wish of decorate their room without imaginary view of how the furniture will look like actually in the room. We propose to use AR for implementing a new design approach for interior design. This AR environment will allow the user to select from a range of furniture and then display or render the virtual furniture selected on the real environment.Along with it , Utilizing the latest ARtechnology, users can place 3D models of virtual objects as e.g., chairs or tables on top of a layout plan and interact with these on their mobile devices . In this paper, we present our research on utilization of augmented reality for interactive and personalized furnishing that the actual user wants in these busy wolrd. The psychology says that , the average person learns better by observing and listening something as compared to by simply reading something. We will be using this specific property of the human mind to accelerate the real time problem.
Speculation will overcome the limitations in dividing a single program into multiple threads that can execute on the multiple logical processing elements needed to enhance performance through parallelization

S emiconductor technologies—along with innovative computer architectures—have provided the bricks and mortar for building phenomenal improvements in processing speed during the past decade, culminating ultimately in the hundreds of millions of transistors used to build increasingly fast on-chip devices. Innovations in computer microarchitecture and accompanying compilers have enabled us to make good use of these building materials to provide highperformance computing systems. Typically, we decide how to use available semiconductor resources in two steps. First, we choose the desired functionality—the techniques for extracting and enhancing performance. In the implementation phase, we translate those techniques into structures and signals that we must then design, build, and verify. Although often described separately, in practice these two phases are tightly coupled. During the 1990s, novel functionality played the dominant role in processor design. Given a reasonable limit on overall design size—for example, fewer than tens of millions of transistors—we could divide up the transistor budget simply by using high-level performance metrics. Doing so made verification relatively simple, and designs did not have to explicitly account for wire delays, which were not significant compared to logic delays. In the future, implementation issues will likely dominate even basic functionality. We have begun to realize that scaling conventional superscalar designs increases complexity and cost with no guarantee that such designs will meet performance goals. Monolithic designs that use hundreds of millions of transistors will be very difficult to design, debug, and verify, and increasing wire delays will make intrachip communication and clock distribution costly. Consequently, some computer architects advocate a shift from highperformance to high-throughput processing, using distributed components that divide and conquer design process complexity and exploit communication locality to overcome wire delays. With this trend comes a renewed and increasing interest in multithreaded architectures. Such architectures can extract parallelism from a sequential program via thread-level speculation—be it control-driven or data-driven—giving them the flexibility to operate in both multiple-program, high-throughput and single-program, high-performance environments.
Requet: Real-Time QoE Metric Detection for Encrypted YouTube Traic

As video trac dominates the Internet, it is important for operators to detect video Quality of Experience (QoE) in order to ensure adequate support for video trac. With wide deployment of end-to-end encryption, traditional deep packet inspection-based trac monitoring approaches are becoming ineective. This poses a challenge for network operators to monitor user QoE and improve upon their experience. To resolve this issue, we develop and present a system for REal-time QUality of experience metric detection for Encrypted Trac, Requet, that is suitable for network middlebox deployment. Requet uses a detection algorithm we develop to identify video and audio chunks from the IP headers of encrypted trac. Features extracted from the chunk statistics are used as input to a Machine Learning (ML) algorithm to predict QoE metrics, specically, buer warning (low buer, high buer), video state (buer increase, buer decay, steady, stall), and video resolution. We collect a large YouTube dataset consisting of diverse video assets delivered over various WiFi and LTE network conditions to evaluate the performance. We compare Requet with a baseline system based on previous work and show that Requet outperforms the baseline system in accuracy of predicting buer low warning, video state, and video resolution by 1.12⇥, 1.53⇥, and 3.14⇥, respectively.