Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical Research Abstracts of the British Equine Veterinary Association Congress 2015.

REASONS FOR PERFORMING STUDY New therapeutic strategies to modulate immune responses in human and equine allergic airway diseases are under extensive investigation. Stimulation of Treg cells with immune modulating agents is a novel therapeutic option. OBJECTIVES The aim of this field study was to compare the effects of a nebulised nanoparticulate CpG immunotherapy (CpG-GNP) with and without specific allergens. STUDY DESIGN Longitudinal clinical study comparing 2 therapeutic options. METHODS Twenty RAO-affected horses were divided into 2 treatment groups (CpG alone and CpG with allergens). Two specific allergens were selected for each horse according to anamnesis and a functional in vitro test. Treatments were given by nebulisation 7 times and the horses were examined 3 times: baseline (I), after the treatment course (II), and after 6 weeks later (III). Clinical parameters, indirect intrapleural measurement, arterial blood gas, amount of tracheal mucus and neutrophil percentage were evaluated. RESULTS CpG alone resulted in a significant improvement in clinical parameters and a significant reduction of tracheal mucus after treatment and at 6 weeks post treatment. After CpG plus specific allergens, there was significant improvement of 70% of examined parameters. However, there were no significant differences in the results compared with CpG-GNP treatment alone. CONCLUSIONS There were no significant differences between treatment groups. CpG-GNP immunotherapy alone produced a potent and persistent effect on allergic and inflammatory parameters and may have potential as for treatment of equine and human allergic inflammatory airway diseases. Ethical animal research: The study was approved by the regional legal agency for animal experiments of the Government of Bavaria, Germany (No. 55.2-1-54-2531-31-10). Owners gave informed consent for their horses' inclusion in the study. Sources of funding: Partly supported by the Deutsche Forschungsgemeinschaft (DFG) (Germany) (GE'2044/4-1). The AeroNeb Go™ vibrating mesh nebuliser (Aerogen, Galway, Ireland) was sponsored by Inspiration Medical (Bochum, Germany). Competing interests: None declared.
A low-power CMOS super-regenerative receiver at 1 GHz

A low-power and low-voltage super-regenerative receiver operating at 1 GHz and implemented in a 0.35 /spl mu/m CMOS process is described. The receiver includes a LNA, a super-regenerative oscillator, an envelope detector, AGC circuitry with sample/hold capability and a baseband amplifier. The die-surface is equal to 0.25 mm/sup 2/. An overall noise figure of 14.7 dB is achieved. The power consumption is less than 1.2 mW at V/sub DD/=1.5 V. A 100 kHz saw tooth quench signal has been used to achieve an interferer rejection of -35.9 dB at 500 kHz from the center frequency.
Using Schema-based Instruction to Improve Seventh Grade Students' Learning of Ratio and Proportion

Improving students' mathematical word problem solving skills has proved to be a significant challenge in the US. When solving story problems, children need to understand the language and factual information in the problem, translate the problem using relevant information to create an adequate mental representation, devise and monitor a solution plan, and In short, solving word problems is closely related to comprehension of the relations and goals in story problems are critical in helping children connect different meanings, interpretations, and relationships to the mathematical operations (Van de Walle, 2007). Although there is evidence to support reform based mathematics methods and curricula in enhancing the mathematics performance of high and average achieving students research on how to address low achieving students' difficulties with word problem solving is somewhat conflicting. In the field of mathematics education, the approach advocated by the NCTM Standards (and that is used in most of the NSF-funded reform curricula) advocates a student-centered, guided discovery approach for teaching students problem solving (Mayer, 2004; NRC, 2001). However, recommendations for this kind of instructional approach are at odds with the literature on problem solving instruction for low achieving students in the field of special education, which has found that low achieving students benefit far more from direct instruction and practice atoriented classrooms indicates that many low achieving students (particularly those with learning disabilities) may assume passive roles and may encounter difficulties with the cognitive load of the discovery-oriented activities and curricular materials despite the clear supporting literature from special education in support of more direct instruction for low achieving students and those with learning disabilities, many in the mathematics education community have strong negative reactions to this instructional approach, in part because of perceived associations between direct instruction and the development of rote, inflexible knowledge. The goal of the present study, which is a collaboration between a mathematics education researcher and a special education mathematics education researcher, was to design an instructional intervention specifically geared toward low achieving students which attempts to use the research literatures from both special education and mathematics education. Although we use a form of direct instruction, in keeping with the strong supporting literature on the success of such approaches for at-risk populations, we make two critical improvements to the ways that direct instruction has sometimes been (mis)applied. First, it is clear that not all methods of direct instruction on problem solving strategies are equally effective …
DC-current-free low-power A/D converter circuitry using dynamic latch comparators with divided-capacitance voltage reference

We have developed a new A/D converter architecture by applying the concept of clocked-neuron-MOS circuitry. It features no DC power dissipation at any component in the A/D converter. In this architecture a comparator employs dynamic latch and the reference voltage is generated by a capacitive voltage divider configuration. As a result, all components in the A/D converter have become purely dynamic in their operation, resulting in a dramatic reduction in the power dissipation. These techniques have been combined with a flash and a two-step flash mechanism, and extremely-low-power A/D converters have been developed. Test circuits were fabricated using standard double-polysilicon CMOS process with 3 /spl mu/m rules. The basic performance has been confirmed by the measurement of test circuits as well as by HSPICE simulation.
Expanding contexts for computer music: one composer's experience

Using his own experience of forty-three professional engagements over a period of a year, most of which involved performances on a laptop computer, the author examines the nature of the ‘musical scenes’ into which involvement with computer music has led him. The author contends that the social nature of ‘computer music’ is changing not only because of changes in the technology, but also because of a number of social factors, some of which are examined in this article.
Topology control in Heterogeneous Wireless Sensor Network

Topology of a Wireless Sensor Network determines the connectivity of the wireless network and topology Control is the important technique of extending network lifetime while preserving network connectivity. In this paper, we consider a heterogeneous multi-hop wireless sensor network consisting of sensor nodes and relay nodes. Relay nodes strategically deployed for fault tolerance and virtual backbone creation. We propose topology control algorithm based on hybrid approaches to maximize the topological network lifetime of the WSN. The experimental performance evaluation demonstrates the topology control with efficient use of relay nodes maximizes the network lifetime of WSNs.
Loading and Batching to Minimize Flow Times in Flexible Manufacturing Systems

A mixed integer nonlinear program is formulated to solve the problem of tool loading and batching production for multi-product types on single flexible machines (SFMs) among several logical workstations. The decisions involve loading tools from each SFM’s limited capacity tool maga-zine, allocating work to each SFM, and setting batch-sizes so as to minimize the total flow time. For the case of single-product type on parallel heterogeneous SFMs, the problem can be proved to be NP-hard. A relaxed flow problem and a heuristic solution are used to develop a branch-and-bound algorithm for computing the optimal solution. Based on the analysis of the optimal solution, a ratio comparison method is used to develop a heuristic procedure for obtain-ing a good solution in a short time. Computational results show that the algorithms are quite efficient. Several valuable managerial implications are derived from the ratio comparison method and its excellent performance.
Segmentation methods in face recognition

Feature extraction (this includes face segmentation because the face itself is considered a global feature) is a very useful step in face recognition and in pattern matching in general. The goodness of a particular feature extraction method is judged on the basis of how much it is efficient and accurate in discrimination between objects of interest herein called human faces. The current investigated features can be categorized into four categories
Evaluating the Factors Influencing E-book Technology Acceptance among School Children Using TOPSIS Technique

Technology can change the nature of learning environment. Moreover, different modes of education enhance the ways in which school children learn. Nowadays, the classroom technology includes interactive learning technology, for example, electronic book (e-book) technology. The e-book is a book that is displayed on a computer screen or on an electronic device that is held in the hand, instead of being printed on paper. Acceptance of a new technology such as e-book technology is important for school children in Malaysia. Despite many claimed benefits, the school children would not accept technology without interaction with a computer. The purpose of this study is to identify determinants of usability and interface factors of Children Computer Interaction (CCI) leading to e-book behaviour intention to use for school children. Through the theoretical background unification of behaviour use intention, in particular, the Technology Acceptance Model (TAM) and interdisciplinary literature review relevant to e-book technology, a comprehensive set of constructs and their interrelationship were found as research hypotheses. The research hypotheses build the development of measurement framework, which was specified in an instrument. To find the importance of factors incorporated in the proposed framework, the data is collected by conducting a survey through a structured questionnaire-based instrument comprising 5-point Likert-type scale and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied. The results from this study analyses are discussed and a future research is suggested.
Creating an Effective Model for Digital Storytelling in the ESL Writing Class

Using technology in the classroom is no longer the exception but the rule in most college classrooms. Now the question is not whether to use technology, but which technology to use. Among recent innovations is digital storytelling, a multimodal tool that can be used across disciplines. This paper reports on a pilot study designed to determine the feasibility and pedagogical value of using digital storytelling in an ESL writing course at an urban community college. The report documents a detailed plan for implementation and some of the challenges this
Segmentation of microarray images using gradient vector flow active contours boosted by gaussian mixture models

In this paper, a new methodology for the segmentation of cDNA microarray images is proposed, based on the combination of Gaussian Mixture Models (GMM) with Gradient Vector Flow (GVF) active contours. A simulated microarray image of 1000 spots was produced using a standard procedure. 5 real microarray images were used to evaluate the performance of our algorithm. GMM was firstly applied in all individual cells (spot with each background). The output was used to initialize a GVF active contour. The major advance of our method is that it overcomes limitations of both GMM and active contours when used individually. Segmentation matching factors and mean intensity values were calculated for every cell using GMM, GVF, and the combination of GMM and GVF in the simulated data. Pairwise correlations and mean absolute errors were also calculated by using real microarrays. Numerical experiments using both simulated and real images showed that our method was more accurate in measuring intensity values and detecting actual boundaries of spots, compared with GMM and active contours used individually. Results concerning the segmentability and the mean intensity value of the proposed algorithm were more accurate, as compared with those methods when used individually.
Improved rolling schedules for the dynamic single level lot sizing problem

A major argument for favoring simple lot-sizing heuristics-like the Silver/Meal or Groff's heuristic-to solve instances of the dynamic single-level uncapacitated lot-sizing problem SLLSP instead of exact algorithms-like those of Wagner/Whitin or Federgruen/Tzur-is that exact algorithms applied in a rolling horizon environment are heuristics too and may be outperformed by simple heuristics. This article shows how to modify the model of the SLLSP by looking beyond the planning horizon. Extensive tests within a rolling horizon environment have demonstrated that the modified model solved by an exact algorithm now performs at least as well as well-known heuristics and is fairly insensitive to the length of the planning horizon. Furthermore, our principal idea of improving rolling schedules by considering only a portion of the fixed cost related to a decision with an impact on periods beyond the planning horizon is applicable to a wide range of decision models.
Domain generalisation in artificial language learning*

Many languages have restrictions on word-final segments, such as a requirement that any word-final obstruent be voiceless. There is a phonetic basis for such restrictions at the ends of utterances, but not the ends of words. Historical linguists have long noted this mismatch, and have attributed it to an analogical generalisation of such restrictions from utterance-final to word-final position. To test whether language learners actually generalise in this way, two artificial language learning experiments were conducted. Participants heard nonsense utterances in which there was a restriction on utterance-final obstruents, but in which no information was available about word-final utterance-medial obstruents. They were then tested on utterances that included obstruents in both positions. They learned the pattern and generalised it to word-final utterance-medial position, confirming that learners are biased toward word-based distributional patterns.
Improvement of Forecasting Accuracy by the Utilization of Genetic Algorithm with an Application to the Sanitary Materials Data

How to improve forecasting accuracy such as sales, shipping is one of the critical success factor in supply chain management. There are many researches made on this. In this paper, a hybrid method is introduced and plural methods are compared. Focusing that the equation of exponential smoothing method(ESM) is equivalent to (1,1) order ARMA model equation, new method of estimation of smoothing constant in exponential smoothing method is proposed before by us which satisfies minimum variance of forecasting error. Generally, smoothing constant is selected arbitrarily. But in this paper, we utilize above stated theoretical solution. Firstly, we make estimation of ARMA model parameter and then estimate smoothing constants. Thus theoretical solution is derived in a simple way and it may be utilized in various fields. Furthermore, combining the trend removing method with this method, we aim to improve forecasting accuracy. An approach to this method is executed in the following method. Trend removing by the combination of linear and 2 nd order non-linear function and 3 rd order non-linear function is executed to the manufacturer’s data of sanitary materials. The weights for these functions are set 0.5 for two patterns at first and then varied by 0.01 increment for three patterns and optimal weights are searched. Genetic Algorithm is utilized to search the optimal weight for the weighting parameters of linear and non-linear function. For the comparison, monthly trend is removed after that. Theoretical solution of smoothing constant of ESM is calculated for both of the monthly trend removing data and the non-monthly trend removing data. Then forecasting is executed on these data. The new method shows that it is useful for the time series that has various trend characteristics and has rather strong seasonal trend. The effectiveness of this method should be examined in various cases.
The Utilization of MapReduce for Ecient Protein Sequencing on HPC

A growing number of applied biocomputation applications utilize parallelism in several dierent forms. Most approaches oering a high degree of control require an extensive rewrite of potentially large and complex software programs; we have developed an alternative. In our approach, we deploy Apache Hadoop as a parallelism framework, which does not require modication of existing software. This allows parallelism to be implemented for tasks with many dependencies, but with few interdependencies. eThread, a protein structure prediction program, was our candidate for parallelization. We have created several scripts encapsulating inpedendent algorithm and program functionality, which eThread depends on. These scripts are executed in parallel utilizing the MapReduce paradigm. MapReduce and Hadoop MapReduce is a distributed/cloud computing paradigm. Computation Jobs are broken into two main stages: mapping and reducing. Mappers receive plain text in format and process this text to produce output. This output is given to reducers, which combine the separate mapper results.
Multi-stage and meta-programming support in strongly typed execution engines

Program development and execution involves a number of processing and transformation steps performed by a variety of tools such as: preprocessors, compilers, program development environments, parser generators, software installers, operating system loaders, just to mention the most common ones. Each system takes as input a program in source or object form and produces a new program, which can be used as input to another system. This thesis develops a technique suitable to express staged computations, targeted to modern execution environments, such as the JVM and the CLR. Code fragments are introduced in programs as first class values, which can be composed by means of an operator called Bind. We discuss power of this operator showing that it is type-safe and complete: only type sound code fragments can be generated; all possible programs can be produced from a finite set of base code fragments. Binding provides meta-programming support in the runtime environment. We show that the staging operators of MetaML can be expressed in term of our mechanism. Implementation and performance issues are discussed for Bind and code values, i.e. the values representing code fragments. An execution model for programs based on the mechanism is proposed. A program is executed not only at runtime: a program evaluator may evaluate it at different times of its lifetime (after compilation, during installation, and so on). A distinctive feature of the model is that program transformations before runtime can be expressed in the program itself.
Evaluating the impact of architectural-level optimizations on clock power

A clock energy model is incorporated into a cycle-accurate energy simulator for an embedded architecture, which also resembles processor cores present in System-on-a-Chip (SoC) designs. This framework is used to study and quantify the influence on clock energy of several architectural-level decisions and their relative impact on the overall system energy. The design cases include various cache architectures and support for clock gating at different levels (global and local). At the software level, the influence on clock energy of power-oriented memory compiler optimizations is assessed.
Optimizing Ruby on Rails for performance and scalability

Web applications are becoming more and more popular as the boundaries of what can be done in a browser are pushed forward. Ruby on Rails is a very popular web application framework for the Ruby programming language. Ruby on Rails allows for rapid prototyping and development of web applications but it suffers from performance problems with large scale applications. This thesis focuses on optimization of a Ruby on Rails application to improve its performance. We performed three optimizations to a benchmark application that was developed for this project. First, we removed unnecessary modules from Ruby on Rails and optimized the database interaction with Active Record which is the default object relational mapping (ORM) in Ruby on Rails. It allows us to fetch and store models in the database without having to write database specific query code. These optimizations resulted in up to 36% decrease in application response time. Second, we implemented a caching mechanism for JavaScript Object Notation (JSON) representation of models in the optimized application. This second optimization resulted in a total of 96% response time decrease for one of the benchmarks. However, we also observed an increased response time (with approximately with 15%) for a second benchmark compared to the unoptimized application. Third, we tuned the garbage collector for CRuby. CRuby is the original implementation of Ruby created by the inventor of the language Yukihiro Matsumoto. This optimization was performed on top of the already optimized application with caching and resulted in an overall decrease in response time: one benchmark showed a response time decrease of 29% with regard to the unoptimized application. In addition, we evaluated the performance of different Ruby implementations: we studied the performance of the application with CRuby, JRuby and Rubinius. We observed that JRuby had the best performance. When the optimized and cached application executed in JRuby it obtained a decrease in response time of up to 32% with regard to the unoptimized application in CRuby. In conclusion, we presented that different optimization techniques can be applied to improve Ruby on Rails performance leading to maximum performance increase of 96%. In addition, we showed that the choice of Ruby implementation is very important as the JRuby implementation has potential to further increase application performance. This work is very important for future development and success of the Ruby on Rails framework as performance is largely seen as the biggest disadvantage with the framework.
How Do Websites Engage Customers? An Evaluation of the Impact of Web Page Visual Appeal on Customers’ Initial Perceptions

According to the rapid growth of online commerce, the competition landscape has become increasingly aggressive. Consequently, new online vendors are facing more difficulty in capturing customers’ attention and engage them in their websites. This study aims to investigate how website design components influence online customers’ immediate perceptions and their subsequent responses, such as engagement and intention to use websites. An experiment was conducted to examine the consistency of the relationships between website design components and user responses across different exposure times (1 second vs. 10 seconds). The findings suggest that website engagement could be made quickly (within 1 second) and is determined by high level of visual complexity and visual appeal in website design.