Miracle-dz/UniFAR-FTUs huggingface dataset:
Applications of evolving technologies in sleep medicine

Summary Nocturnal polysomnography (PSG) is the most important laboratory technique in the management of sleep–wake disturbances and is considered the “gold standard” [1]. New sensor technologies are entering the field, and rapid development in telecommunications and mobile technology has accelerated the introduction of telemedicine as a viable and reliable option [2]. The present broad review is an amalgam of the current knowledge with proposed new sensors and remote control. The reader should note that not all of the techniques discussed here have strong clinical validation, and this should be considered when purchasing equipment.
Employees’ perceptions of trust, fairness, and management of change using an organisational justice framework: a brief review of the literature

A theoretical approach is presented of an organisational justice framework that may provide an enriched perspective to examine strategic change, enhancing the understanding, design, implementation, and effectiveness of strategic change initiatives. The organisational justice framework provides an understanding of employees’ perceptions on trust and fairness during an organisational strategic change process in the context of the justice approach, although perceived fairness has been seen as playing an important role in the process of sustaining trust in the organisation. The study demonstrates the importance of analysis of the response to strategic change by employees, the impact on organisational trust, and the influence of the fairness judgment.
An efficient block mode decision for temporal scalability in scalable video coding

In this paper, a fast intermode decision scheme which is suitable for the hierarchical B-picture structure in which much computational power is spent for combined variable block sizes and bi-predictive motion estimation is introduced. The hypothesis testing considering the characteristics of the hierarchical B-picture structure in the proposed method is performed on 16x16 and 8x8 blocks to have early termination for RD computation of all possible modes. The early termination in intermode decision is performed by comparing the pixel values of current blocks and corresponding motion-compensated blocks. When the hypothesis tests are performed, the confidence intervals to accept the null hypothesis or not are decided according to the temporal scalability levels under the consideration of properties of hierarchical B-pictures. The proposed scheme exhibits effective early termination behavior in intermode decision of temporal scalabilities and leads to a significant reduction up to 69% in computational complexity with slight increment in bit amounts. The degradation of visual quality turns out to be negligible in terms of PSNR values.
Multisensor classification of wetland environments using airborne multispectral and SAR data

Near concurrent airborne data were acquired over the wetlands of the Bolivar Peninsula on the Texas coast by the NASA/JPL AIRSAR (June 28, 1996) and NASA/Stennis Space Center Calibrated Airborne Multispectral Scanner (CAMS) (July 3, 1996), both at 4 m spatial resolution. Several approaches which utilize information from both sensors are investigated for classifying the landcover in these data sets. Differences in statistical characteristics of the data necessitate individual parametric models for observations from each sensor, so data are initially classified separately, then a final classification is obtained by combining results from the statistical models using different multisensor integration techniques. These integrated results are compared to single-sensor classification results, as well as to a multisensor classification based on artificial neural networks.
An introduction to programming and problem solving with PASCAL

Introduces all aspects of programming and problem solving in the Pascal language, with special attention to good programming habits and style. Covers the use of algorithm thinking as a means for problem solving, refinement, recursion, and top down modular programming. Extensive exercises are included at the end of each chapter, with answers to selected exercises at the end of the book.
Ranking Marketing Journals Using the Search Engine Google Scholar

Using Google Scholar as a citation source and the hg-index as a citation metric, this study provides an up-to-date ranking of 69 pure marketing journals based on actual cites of articles published between 2003 and 2007. Results show that the top four journals are Journal of Marketing, Journal of Consumer Research, Journal of Marketing Research, and Marketing Science. Furthermore, this study investigates the relationships between the hg-index, the journal impact factor, the index of familiarity and rank, the number of articles that a journal publishes, and the journal's age. It also provides a comparison between the hg-index and citation-based metrics used in two recent ranking studies.
Daily river flow forecasting using wavelet ANN hybrid models

Advance time step stream flow forecasting is of paramount importance in controlling flood damage. During the past few decades, artificial neural network (ANN) techniques have been used extensively in stream flow forecasting and have proven to be a better technique than other forecasting methods such as multiple regression and general transfer function models. This study uses discrete wavelet transformation functions to preprocess the time series of the flow data into wavelet coefficients of different frequency bands. Effective wavelet coefficients are selected from the correlation analysis of the decomposed wavelet coefficients of all frequency bands with the observed flow data. Neural network models are proposed for 1-, 2- and 3-day flow forecasting at a site of Brahmani River, India. The effective wavelet coefficients are used as input to the neural network models. Both the wavelet and ANN techniques are employed to form a loose type of wavelet ANN hybrid model (NW). The hybrid models are trained using Levenberg‐Marquart (LM) algorithm and the results are compared with simple ANN models. The results revealed that the predictabilities of NW models are significantly superior to conventional ANN models. The peak flow conditions are predicted with better accuracy using NW models than compared to ANN models.
Optimization of the radiative antenna for 7‐T magnetic resonance body imaging

Magnetic resonance prostate imaging at 300 MHz is complicated by the effects arising from the short RF wavelength in biological tissue. A radiative antenna leads to a better RF signal penetration for sites located at one or more wavelengths depth, i.e. beyond the near zone. It consists of a dipole antenna placed on a high-dielectric substrate. The effects of changes in substrate dimensions and relative permittivity upon the electromagnetic fields, the B efficiency and the Poynting vector at 10 cm depth are investigated for a realistic body phantom by using electromagnetic simulations. A high relative permittivity substrate is favorable in terms of B efficiency, practical dimensions and weight but it leads to a higher SAR exposure. For optimal B efficiency a relative permittivity in the range of 90 to 110 should be preferred and a minimum thickness of 40 to 50 mm and a width of 50 mm. For optimal local SAR/(B)2 ratio, an optimal thickness would be around 50 mm and the width would be as large as possible. This may lead to an impractical element size in terms of weight. © 2013 Wiley Periodicals, Inc. Concepts Magn Reson Part B (Magn Reson Engineering) 43B: 1–10, 2013
The Effects of Content Familiarity and Language Ability on Reading Comprehension Performance of Low- and High-ability Saudi Tertiary Students Studying English as a Foreign Language

This study investigates the effects of content familiarity and language ability (defined as general L2 proficiency) on the comprehension performance of low- and high-ability Saudi students of English as a foreign language. One hundred and thirty-two male and female university students participated in this study, performing two reading comprehension tests on two different types of text (familiar and unfamiliar). The results showed that content familiarity and language ability had significant effects on the students' comprehension performance. They indicated that content familiarity facilitated reading comprehension, and that language ability had a significant effect on the comprehension performance of students at different levels. Language ability level may have played a compensatory role in facilitating the comprehension of the unfamiliar text. Educators designing and implementing reading courses need to consider these related factors.
Making Information and Communications Technology Work

Abstract This article describes the consequences of using an assessment portfolio as a means of implementing information and communications technology (ICT) in initial teacher education. The study involved a group of 18 mathematics student teachers both during their training year and in their first year of teaching. The results suggest that the aim of motivating them to use ICT in teaching mathematics was achieved, but the students did not value the portfolio per se. It seems that it needs to be made a more formative experience if it is to fulfil its potential.
System response time effects on user productivity

Abstract The present study tested the proposal that reducing computer system response times from a few seconds to sub-second levels results in dramatic increases in user productivity. Subjects completed data-entry and problem-solving tasks using a computer statistical package, under a range of computer response times from 0⋅1 to 5 seconds. Results indicated that some increase in productivity does occur as system response time decreases; however, (1) the size of the effect is considerably smaller than previously indicated, (2) the effect occurred only for data-entry tasks, disappearing in problem-solving situations and declining in strength as the data-entry task became more complex, and (3) the relationship between response time and productivity was linear rather than exponential, as was indicated previously. These results suggest that an attentional'automatic processing model of the user is more appropriate than a model proposing that users do not need time to think between entries to the computer.
Modeling and Optimization of Double-Clad Fiber Amplifiers Using Chaotic Propagation of the Pump

Abstract A complete theoretical study of double-clad fiber amplifiers is proposed. The notion of chaotic propagation is taken into account in order to improve the pumping process. In addition, a space–time algorithm is used to optimize the distribution of rare-earth dopant in the double-clad fiber. Finally, computed gain curves versus wavelength show attractive results for wavelength multiplexing applications.
Phytoplankton community of Elechi creek, Niger Delta, Nigeria - a nutrient-polluted tropical creek.

Problem statement: Elechi Creek of the Upper Bonny Estuary in the Niger Delta contributes to the Rivers State Fish resources. It is a sink receiving organic anthropogenic wastes from Diobu, Eagle Island and waterfront dwellers of Diobu areas. Fishing, car washing, bathing, swimming and other human activities are constantly going on within and around this creek. Based on these activities, there is urgent need to study the phytoplankton community that supports its fisheries. Approach: The study investigated the phytoplankton composition, diversity, abundance and distribution as well as surface water physico-chemical parameters. Phytoplankton and surface water samples were collected bi-monthly from October 2007-March 2008 at high tide from five stations according to APHA methods. These were analyzed for temperature, transparency, dissolved oxygen, salinity, alkalinity, chloride and nutrients. Phytoplankton was identified microscopically. Species diversity was calculated using standard indices. Results: A total of 169 species of phytoplankton, based on cell counts, was dominated by diatoms, 33255 counts mL-1 (36%) and blue-green algae, 32909 counts mL-1 (35.7%) were identified. The abundance of phytoplankton decreased downstream of this creek (1>2>3>4) except in station 5 with the highest phytoplankton abundance (23938 counts mL-1). There was slight fluctuation in the measured physico-chemical parameters. The results of this study indicated the characteristic species and distribution of phytoplankton in Elechi Creek during the dry months. Conclusion/Recommendation: The high level of phosphate above the permissive limit showed that this creek is hypereutrophic and organic polluted. The high nutrients status favors the high abundance of phytoplankton. The municipal effluents (especially raw human and animal faces) discharges must be discontinued. Detergents with low concentration of phosphate are recommended for manufacturing and use. Municipal wastes must be treated and/or recycled before discharge into this natural aquatic body. Therefore, a continuous environmental surveillance of this creek is advocated to keep its biological integrity.
Adaptive Methods for Partial Differential Equations

Abstract : Topics contained in this volume include the reliability of computations; a posteriori error estimation; adaptive h-, p-, and r-refinement; method of lines and local refinement methods for time-dependent problems; parallel solution techniques; and applications of adaptive methods to problems in elasticity, fluid mechanics, and combustion. Issues of reliability, presented in the contributions by Babuska and Szabo', note the importance of specifying computational accuracy in relation to the idealizations of the mathematical model. Thus, one should envision a sequence of computations where the enhancements and refinements are added to the physical mode as the computational procedure is enriched. These ideas are a relatively new and important innovation in the field. The contributions of Berger and Hassanzadeh et al. discuss parallel adaptive procedures, which is another aspect of the field that has emerged since the early conferences and workshops. (KR)
Dynamic search tree decomposition for balancing assembly lines by parallel search

We consider the simple assembly line balancing problem of type 1 (SALB-1). Although several branch-and-bound algorithms have been developed for optimally solving the SALB-1, until now to the best of our knowledge no parallel approach has been presented for this classical problem. In this paper we propose a parallel algorithm for solving the SALB-1. The parallel approach is based on a competitive serial algorithm. The parallel approach benefits from the substitution of a powerful but memory-intensive dominance concept through solution characteristics. Using the master-slave principle the master dynamically generates subproblems which are, upon request, assigned to the slaves for evaluation. The subproblems depend on previously assigned and on previously evaluated subproblems. The characteristics allow each slave to decide on potential dominances without requiring information from another slave or the master. The algorithm has been coded in GNU C using the Parallel Virtual Machine to allow process communication. Experimental studies have been performed on a simulated cluster of personal computers. Benchmark sets from the literature served as a testbed. The computational results are extremely promising. It seems that the SALB-1 is an ideal application of parallel search.
Synthesis and Molecular Structure of Spirocyclic 2-Oxindole Derivatives of 2-Amino-4H-pyran Condensed with the Pyrazolic Nucleus.

Abstract 4,3′-Spiro[(6-amino-5-R-3-methyl-2H,4H-pyrano[2,3-c]pyrazolo)-2′-oxindoles] were synthesized based on the three-component condensation of isatins with 3-methyl-pyrazolone-5 and respective methylene active nitriles in the presence of basic catalysts. The molecular structure of the resulting compounds was proved unambiguously by X-ray diffraction.
Research on Parallel Geo-Spatial Index Replication Strategy Based on PC Cluster System and its 3D Visualization Application

In the field of spatial information, the amount of spatial data becomes more and more large, and every operation becomes more and more complicated. Now, parallel techniques gradually become valid means of resolving this kind of complicated problem. Therefore, this paper studies the spatial partitioning method of massive data and the parallel geo-spatial index replication strategy after fully considering characteristics of PC cluster based on shared-nothing structure. After studying excellent linear mapping characteristics of Hilbert spatial ordering code, this paper applies it to spatial partitioning of data, and gives a concrete algorithm. In this algorithm, the clustering performance of spatial objects is considered, and the balance of data storage on each processing unit is also done, which greatly improves the processing efficiency of parallel spatial database. Based on this, this paper builds the parallel geo-spatial index based on R-tree, and proposes the spatial index replicas update mechanism based on master replica and weak consistency suitable for the parallel environment of shared-nothing structure after deeply analyzing current synchronous mechanisms of replicas. It is a kind of update mechanism based on message with low cost, enhances the power of parallel spatial data access and using PC cluster, and improves the availability of index data. In the field of 3D visualization application, it is also efficient. Experiments prove that the spatial partitioning strategy and the parallel geo-spatial index replication mechanism presented in this paper can improve load balance of system, and enhance performance of the whole system.
PARTICIPATORY EXTENSION PROCESSES AS CATALYST FOR CHANGE IN SOCIAL DYNAMICS AMONG RURAL POOR

As agricultural education based on participatory approaches expand, knowledge is needed about the impact it has on the daily lives of participants beyond farming gains. The study explores how involvement in the participatory extension practice “Farmer Field Schools (FFS)” results in shifting world views among participants and to what extent it has an impact on peoples' sense of well-being and agency in society. The paper discuss how transformative learning in participatory research and extension enables poor people to gain agency; generate more equitable spousal relations; improve relationships with community and adopt more productive and profitable farming and marketing practices that contribute to a sustainable society.
A Trace-Driven Simulation Study of Dynamic Load Balancing

A trace-driven simulation study of dynamic load balancing in homogeneous distributed systems supporting broadcasting is presented. Information about job CPU and input/output (I/O) demands collected from production systems is used as input to a simulation model that includes a representative CPU scheduling policy and considers the message exchange and job transfer cost explicitly. Seven load-balancing algorithms are simulated and their performances compared. Load balancing is capable of significantly reducing the mean and standard deviation of job response times, especially under heavy load, and for jobs with high resource demands. Algorithms based on periodic or nonperiodic load information exchange provide similar performance, and, among the periodic policies, the algorithms that use a distinguished agent to collect and distribute load information cut down the overhead and scale better. With initial job placements only, source initiative algorithms were found to perform better than server initiative algorithms. The performances of all hosts, even those originally with light loads, are generally improved by load balancing. >
2-Hydroxy­propanammonium benzene­thiol­ate

The asymmetric unit of the title compund, C3H10NO+·C6H5S−, contains two benzeno­thiol­ate anions and two 2-hydroxypropanammonium cations. The ions are linked into sheets of R24(8), R24(11) and R24(14) rings by a combination of N—H⋯S, O—H⋯S and N—H⋯O hydrogen bonds.
Wind turbines in icing conditions: performance and prediction

Abstract. Icing on structures is an important issue for wind energy developments in many regions of the world. Unfortunately, information about icing conditions is mostly rare due to a lack of measurements. Additionally, there is not much known about the operation of wind turbines in icing conditions. It is the aim of the current study to investigate the effect of icing on power production and to evaluate the potential of icing forecasts to help optimizing wind turbine operation. A test site with two Enercon E-82 turbines was set up in the Jura region in Switzerland in order to study the turbines' behaviour in icing conditions. Icing forecasts were performed by using an accretion model driven by results of the mesoscale weather forecast model WRF. The icing frequency at the test site is determined from pictures of a camera looking at the measurement sensors on the nacelle. The results show that the site is affected by frequent icing: 11.5 days/year of meteorological icing and 41.5 days/year of instrumental icing were observed corresponding to a factor of about four. The comparison of power production with and without blade heating shows that blade heating results in a 3.5% loss and operation without blade heating results in a 10% loss of the annual power production due to icing. Icing forecasts are performed for winter 2009/2010. Simulated and observed icing events agree well and also coincide with periods of power drop. Thus, the results suggest that icing forecasts can help to optimize the operation of wind parks in icing conditions.
Towards interlingual subtitling for the deaf and the hard of hearing

Abstract The article examines interlingual subtitling for the deaf and the hard of hearing (SDH) as a self-contained audiovisual translation modality. Although interlingual SDH shares some common ground with its elder siblings, i.e. standard interlingual subtitling for hearing viewers and monolingual subtitling for the deaf and the hard of hearing, it differs from them in terms of text reduction, redundancy and editing.
Display of Quantitative Information: Are Grables better than Plain Graphs or Tables?

Previous research is equivocal on the most efficient, effective methods for displaying quantitative information in tables and graphs. Guidelines suggest different display types are more appropriate for certain purposes but not others. However, there is little empirical evidence to support the recommendations. This study examines several methods of displaying quantitative information (e.g., line graphs, bar charts, tables) factorially crossed with different kinds of data extraction questions (i.e., inquiries about trends, comparisons, and exact numerical quantities). Results showed that tables, bar grables (combined bar graph and table) and line grables produced the most accurate responses, and line graphs and bar charts produced the fastest responses across question types. Results are discussed with respect to prior theoretical work and the potential benefits of hybrid forms of quantitative data displays for multiple kinds of data extraction inquiries.