Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of the Instruction in Inferring Meanings From Context on the Comprehension of Middle School Students at Frustration Reading Level

The purpose of this study was to examine the effects of the context clue instruction program to infer meaning from context as a way to enhance reading comprehension. Participants were fifth-grade middle school students (four boys) who were at a frustration reading level (initial comprehension score range = 40%-48%) at their grade level. In addition, one student served as a control participant and did not any receive instruction in this study. A multiple-baseline across-students design was used. All the instruction for the three experimental participants was one on one using the direct instruction method. Maintenance of treatment effects was probed at 2, 4, and 6 weeks following the intervention for Participants 1, 2, and 3, respectively. The results demonstrated that the instructional program produced increases in all three experimental participants’ comprehension scores to above 70% (range = 75%-82%) as measured by the short-answer questions; thus, they found they achieved an instructional level score in their comprehension after the instruction. The social validity results confirmed that participants enjoyed the intervention, and had a better understanding of what they read through individual experience on the strategy of learning from context. The information gained from this study suggested that a strategy instruction concerning the use of context clues may be a useful component (Tier 2 setting) of response to intervention (RTI) model for students who struggle with reading comprehension.
The 16-day planetary waves: multi-MF radar observations from the arctic to equator and comparisons with the HRDI measurements and the GSWM modelling results

Abstract. The mesospheric and lower thermospheric (MLT) winds (60–100 km) obtained by multiple MF radars, located from the arctic to equator at Tromso (70° N, 19° E), Saskatoon (52° N, 107° W), London (43° N, 81° W), Hawaii (21° N, 157° W) and Christmas Island (2° N, 157° W), respectively, are used to study the planetary-scale 16-day waves. Based on the simultaneous observations (1993/1994), the variabilities of the wave amplitudes, periods and phases are derived. At mid- and high-latitude locations the 16-day waves are usually pervasive in the winter-centred seasons (October through March), with the amplitude gradually decreasing with height. From the subtropical location to the equator, the summer wave activities become strong at some particular altitude where the inter-hemisphere wave ducts possibly allow for the leakage of the wave from the other hemispheric winter. The observational results are in good agreement with the theoretical conclusion that, for slowly westward-traveling waves, such as the 16-day wave, vertical propagation is permitted only in an eastward background flow of moderate speed which is present in the winter hemisphere. The wave period also varies with height and time in a range of about 12–24 days. The wave latitudinal differences and the vertical structures are compared with the Global Scale Wave Model (GSWM) for the winter situation. Although their amplitude variations and profiles have a similar tendency, the discrepancies are considerable. For example, the maximum zonal amplitude occurs around 40° N for radar but 30° N for the model. The phase differences between sites due to the latitudinal effect are basically consistent with the model prediction of equatorward phase-propagation. The global 16-day waves at 95 km from the HRDI wind measurements during 1992 through 1995 are also displayed. Again, the wave is a winter dominant phenomenon with strong amplitude around the 40–60° latitude-band on both hemispheres. Key words. Meteorology and atmospheric dynamics – waves and tides – middle atmosphere dynamics – thermospheric dynamics
A Flexible Architecture for Representing Personality in Distributed Systems Development

The agent-oriented (AO) methodology is an effective means for constructing distributed systems. Despite a great deal of research, a number of challenges still exist before making agent-based computing a widely accepted paradigm in software engineering practice. In order to solve the problem of "a variety in number, difficult to apply", the paper presents a hierarchical development architecture (HDA) for customizing a new AO methodology according to the given project. Through applying the HDA-based meta models and design patterns, developers can build applications from third party off-the-shelf solution components. To exemplify its feasibility and effectiveness, the construction of C4I system is presented as a case study.
Addition of Anti-Angiogenetic Therapy with Bevacizumab to Chemo- and Radiotherapy for Leptomeningeal Metastases in Primary Brain Tumors

Leptomeningeal dissemination of a primary brain tumor is a condition which is challenging to treat, as it often occurs in rather late disease stages in highly pretreated patients. Its prognosis is dismal and there is still no accepted standard of care. We report here a good clinical effect with a partial response in three out of nine patients and a stable disease with improvement on symptoms in two more patients following systemic anti-angiogenic treatment with bevacizumab (BEV) alone or in combination with chemo- and/or radiotherapy in a series of patients with leptomeningeal dissemination from primary brain tumors (diffuse astrocytoma WHO°II, anaplastic astrocytoma WHO°III, anaplastic oligodendroglioma WHO°III, primitive neuroectodermal tumor and glioblastoma, both WHO°IV). This translated into effective symptom control in five out of nine patients, but only moderate progression-free and overall survival times were reached. Partial responses as assessed by RANO criteria were observed in three patients (each one with anaplastic oligodendroglioma, primitive neuroectodermal tumor and glioblastoma). In these patients progression-free survival (PFS) intervals of 17, 10 and 20 weeks were achieved. In three patients (each one with diffuse astrocytoma, anaplastic astrocytoma and primitive neuroectodermal tumor) stable disease was observed with PFS of 13, 30 and 8 weeks. Another three patients (all with glioblastoma) were primary non-responders and deteriorated rapidly with PFS of 3 to 4 weeks. No severe adverse events were seen. These experiences suggest that the combination of BEV with more conventional therapy schemes with chemo- and/or radiotherapy may be a palliative treatment option for patients with leptomeningeal dissemination of brain tumors.
Evaluation of Bayesian Changepoint Detection of Sepsis in Hospital Patient Monitoring

Advances in healthcare technology have made more expansive time-series data available for modeling and monitoring health outcomes. Gaussian processes (GP), a form of Bayesian time-series monitoring, has been a popular method for modeling this data because GPs take observed values at a finite set of time points and generate robust predicted values over all unobserved time points. However, patient time-series data often undergoes drastic and sudden changes as a result of clinical events and treatment. In other contexts, research has shown that modeling these sudden changes as changepoints, that is as time points in which the model parameters of the GP alter, can improve the quality of predictions. The clinical event of sepsis, a potentially life-threatening complication of the body’s infection fighting response, causes particularly dramatic changes in heart rate time-series. This paper uses sample heart rate time-series obtained from the Hospital at the University of Pennsylvania to evaluate if treating the clinical event of sepsis as a model changepoint in the heart rate GP can improve model fit. Secondly, we evaluate if detection of changepoints can lead to earlier predictions of sepsis as compared to the time of clinical diagnosis.
Fitting and Benchmarking of Monte Carlo Output Parameters for 192 Ir High Dose Rate Brachytherapy “ New or v 2 ” Source

A robust model to directly represent output from contemporary brachytherapy calculation had been proposed and developed to make clinical implementation practicable. The model was used to minimize inherent uncertainties associated with the AAMP TG-43 formalism, with consolidation of the TG-43 parameters into new parameter to speed up computational time. Analytical computations were performed to hybridize the anisotropy function, ) , (  r F and radial dose function, ) (r g into a single new function ) , (  r f for a Nucletron microSelectron High Dose Rate “new or v2” (mHDRv2) 192 Ir brachytherapy source. Outputs obtained with the new function were curve fitted with MatLab and compared to those of Monte Carlo serving as the standard to evaluate the average and maximum uncertainties. Dose rate deviations between the Monte Carlo data and MatLab fits, quantified as errors showed minimal deviations less than 0.3%. In comparison with Lliso‟s study, this work shows marginal improvement in the deviated values. This work has shown much promise in building robust models to represent outputs from contemporary brachytherapy dosimetry calculations.
The Relation Between Daily Stress and Health.

INTRODUCTION . 1 M E T H O D O L O G Y . 38 RESULTS . 48 D ISCUS S I O N . 65 R E F E R E N C E S . 81 A P P E N D I C E S . 96 V I T A . 110
Characterization of a Novel PQQ-Dependent Quinohemoprotein Pyranose Dehydrogenase from Coprinopsis cinerea Classified into Auxiliary Activities Family 12 in Carbohydrate-Active Enzymes

The basidiomycete Coprinopsis cinerea contains a quinohemoprotein (CcPDH named as CcSDH in our previous paper), which is a new type of pyrroloquinoline-quinone (PQQ)-dependent pyranose dehydrogenase and is the first found among all eukaryotes. This enzyme has a three-domain structure consisting of an N-terminal heme b containing a cytochrome domain that is homologous to the cytochrome domain of cellobiose dehydrogenase (CDH; EC 1.1.99.18) from the wood-rotting basidiomycete Phanerochaete chrysosporium, a C-terminal family 1-type carbohydrate-binding module, and a novel central catalytic domain containing PQQ as a cofactor. Here, we describe the biochemical and electrochemical characterization of recombinant CcPDH. UV-vis and resonance Raman spectroscopic studies clearly reveal characteristics of a 6-coordinated low-spin heme b in both the ferric and ferrous states, as well as intramolecular electron transfer from the PQQ to heme b. Moreover, the formal potential of the heme was evaluated to be 130 mV vs. NHE by cyclic voltammetry. These results indicate that the cytochrome domain of CcPDH possesses similar biophysical properties to that in CDH. A comparison of the conformations of monosaccharides as substrates and the associated catalytic efficiency (k cat/K m) of CcPDH indicates that the enzyme prefers monosaccharides with equatorial C-2, C-3 hydroxyl groups and an axial C-4 hydroxyl group in the 1C4 chair conformation. Furthermore, a binding study shows a high binding affinity of CcPDH for cellulose, suggesting that CcPDH function is related to the enzymatic degradation of plant cell wall.
Answering XML Queries on Heterogeneous Data Sources

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PSO-ANFIS tuned real-time VVoIP in Cloud with access control security

This paper introduces Cloud-Mobile Computing system to realize a real-time video/voice over IP (VVoIP) applications, called Cloud-VVoIP. In addition, access control designs authentication authorization, and accounting mechanism using biometrics technology (including face recognition and fingerprint identification) that is applied to secure legal access from the outsider, giving a safer way to login into Cloud-VVoIP. After that adaptive network-based fuzzy inference system (ANFIS) together with particle swarm optimization (PSO) has been employed to tune seamless handoff properly and analyze network traffic flow over time. Finally the performance of Cloud-VVoIP is measured and discussed. Cloud-based VVoIP outperforms the traditional peer-to-peer type of VVoIP due to three benefits. According to the analysis of Cloud-VVoIP, power consumption will be estimated in web-based browsing and Android APP. In addition, through stress test to analyze the performance of Cloud-VVoIP, we found the resources allocation about CPU, memory, bandwidth and disk.
World Integrated Warning Forecasting System Based on System Dynamics Principles as a Basic Factor in Sustainable Development

World is in crisis. To reach sustainable development, it is necessary to change methods of shaping policy into that based on knowledge of its complex and future results. We ought to create a possibility of forecasting and measurable evaluating policy effects and other changes in life–conditions . This will allow us to change economics into based on account of complex profits and costs with its social and nature elements. With this end in view a large scale international science and technology operation on popular and common use system dynamics should be undertaken. For proper governance I also propose a conceptual model System of Life (SoL). The SoL reflects common properties and structural features of systems: man – technology – environment (social and/or natural). The model reflects life-systems feedbacks. It also reflects the process of life. The SoL includes static as well as dynamic properties and structural features of these systems.
VOLARE: context-aware adaptive cloud service discovery for mobile systems

With the recent widespread use of smart mobile devices, as well as the increasing availability of fast and reliable wireless Internet connections for mobile devices, there is increased interest in mobile applications where the majority of the processing occurs on the server side. The flexibility, stability and scalability offered by cloud services make them an ideal architecture to use in client applications in a resource limited mobile environment. This is because mobile application usage patterns tend to be uneven, with various usage spikes according to time and location. However, the mobile setting presents a set of new challenges that cloud service discovery methods developed for non-mobile environments cannot address. The requirements a mobile client device will have from a cloud service may change due to changes in the context of the device, which may include hardware resources, environmental variables or user preferences. Binding to a service offering different quality of service levels from the ones required may lead to excess consumption of mobile resources such as battery life, as well as unnecessarily high provision costs. This paper introduces VOLARE, a middleware-based solution that monitors the resources and context of the device, and dynamically adapts cloud service requests accordingly, at discovery time or at runtime. This approach will allow for more resource-efficient and reliable cloud service discovery, as well as significant cost savings at runtime.
Non-local image reconstruction for efficient BTF synthesis

Virtual reproduction of optical material properties is an important task for many computer graphics applications. Recently, bidirectional texture functions (BTFs) [Dana et al. 1999] have become quite popular for photo-realistic rendering of surfaces. BTFs can represent a huge variety of different materials. They can be easily integrated into any modern rendering system which offers programmable surface shaders. BTFs of real materials can be optically measured, they are known to be efficiently compressible and can be used for real-time graphics rendering applications even on the web using WebGL.
Voltage-Dependent Structural Interactions in the Shaker K+ Channel

Using a strategy related to intragenic suppression, we previously obtained evidence for structural interactions in the voltage sensor of Shaker K+ channels between residues E283 in S2 and R368 and R371 in S4 (Tiwari-Woodruff, S.K., C.T. Schulteis, A.F. Mock, and D.M. Papazian. 1997. Biophys. J. 72:1489–1500). Because R368 and R371 are involved in the conformational changes that accompany voltage-dependent activation, we tested the hypothesis that these S4 residues interact with E283 in S2 in a subset of the conformational states that make up the activation pathway in Shaker channels. First, the location of residue 283 at hyperpolarized and depolarized potentials was inferred by substituting a cysteine at that position and determining its reactivity with hydrophilic, sulfhydryl-specific probes. The results indicate that position 283 reacts with extracellularly applied sulfhydryl reagents with similar rates at both hyperpolarized and depolarized potentials. We conclude that E283 is located near the extracellular surface of the protein in both resting and activated conformations. Second, we studied the functional phenotypes of double charge reversal mutations between positions 283 and 368 and between 283 and 371 to gain insight into the conformations in which these positions approach each other most closely. We found that combining charge reversal mutations at positions 283 and 371 stabilized an activated conformation of the channel, and dramatically slowed transitions into and out of this state. In contrast, charge reversal mutations at positions 283 and 368 stabilized a closed conformation, which by virtue of the inferred position of 368 corresponds to a partially activated (intermediate) closed conformation. From these results, we propose a preliminary model for the rearrangement of structural interactions of the voltage sensor during activation of Shaker K+ channels.
The Returns on Human Capital: Good News on Wall Street is Bad News on Main Street

We use a standard single-agent model to conduct a simple consumption growth accounting exercise. Consumption growth is driven by news about current and expected future returns on the market portfolio. We impute the residual of consumption growth innovations that cannot be attributed to either news about financial asset returns or future labor income growth to news about expected future returns on human wealth, and we back out the implied human wealth and market return process. Innovations in current and future human wealth returns are negatively correlated with innovations in current and future financial asset returns, regardless of the elasticity of intertemporal substitution. The Author 2006. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.
Lazy Learning for Local Modeling and Control

This paper presents local methods for modeling and control of discrete-time unknown nonlinear dynamical systems, when only a limited amount of input-output data is available. We propose the adoption of lazy learning, a memory-based technique for local modeling. The modeling procedure uses a query-based approach to select the best model connguration by assessing and comparing diierent alternatives. A new recursive technique for local model identiication and validation is presented, together with an enhanced statistical method for model selection. Also, three methods to design controllers based on the local linearization provided by the lazy learning algorithm are described. In the rst method the lazy technique returns the forward and inverse models of the system which are used to compute the control action to take. The second is an indirect method inspired to self-tuning regulators where recursive least squares estimation is replaced by a local approximator. The third method combines the linearization provided by the local learning techniques with optimal linear control theory, to control nonlinear systems about regimes which are far from the equilibrium points. Simulation examples of identiication and control of nonlinear systems starting from observed data are given.
A Grid and Density-Based Clustering Algorithm for Processing Data Stream

This paper proposes DD-Stream, a framework for density-based clustering stream data. The algorithm adopts a density decaying technique to capture the evolving data stream and extracts the boundary point of grid by the DCQ-means algorithm. Our method resolving the problem of evolving automatic clustering of real-time data streams, cannot only find arbitrary shaped clusters with noise, but also avoid the clustering quality problems caused by discarding the boundary point of grid, our algorithm has better scalability in processing large-scale and high dimensional stream data as well.
Identifying the Topic-Specific Influential Users Using SLM

Social Influence can be described as the ability to have an effect on the thoughts or actions of others. The objective of this research is to investigate the use of language in detecting the influential users in a specific topic on Twitter. From a collection of tweets matching a specified query, we want to detect the influential users from the tweets' text. The study investigates the Arabic Egyptian dialect and if it can be used for detecting the author's influence. Using a Statistical Language Model, we found a correlation between the users' average Retweets counts and their tweets' perplexity, consolidating the hypothesis that SLM can be trained to detect the highly retweeted tweets. However, the use of the perplexity for identifying influential users resulted in low precision values. The simplistic approach carried out did not produce good results. There is still work to be done for the SLM to be used for identifying influential users.
Discussion on "Strict Geometric Model Based on Affine Transformation for Remote Sensing Image with High Resolution"

This paper is based on "strict geometric model based on affine transformation for remote sensing image with high resolution",amending the strict geometric model of the calculation for the position and orientation parameters of the remote sensing image with high resolution.According to condition of CCD scanning Earth,amend and get a more exact geometric model,whose computation formula is inferred.Experiments demonstrate the new model is more strict and reliable,though it has the same effect as the(original) model.
A middleware for building context-aware mobile services

Computing becomes increasingly mobile and pervasive today; these changes imply that applications and services must be aware and adapt to highly dynamic environments. Today, building context-aware mobile services is a complex and time-consuming task. We present a service-oriented context-aware middleware (SOCAM) architecture for the building and rapid prototyping of context-aware mobile services. We propose an ontology-based approach to model various contexts. Our context model supports semantic representation, context reasoning and context knowledge sharing. We take a service-oriented approach to build our middleware which supports tasks including acquiring, discovering, interpreting, accessing various contexts and interoperability between different context-aware systems.