Miracle-dz/UniFAR-FTUs huggingface dataset:
The Psychological Reality of Local Coherences in Sentence Processing

Dynamical systems of language processing predict that sentence processing complexity is not only a function of the globally coherent structure ranging from the beginning of the sentence to its current point of processing, but also a function of locally coherent sub-parses. This paper presents an experiment that tests whether locally coherent, yet globally false continuations affect on-line anomaly detection times. The results indicate that they do interfere with processing, but only if the global analysis is not too demanding. This result can be seen as an indicator of the psychological reality of local coherence processing, and hence supports the dynamic system view on language processing.
Quality improvement in the TESOL curriculum: a generic benchmarking approach

Whilst there are different types of benchmarking, this article, as a result of our research into TESOL (Teaching of English to Speakers of Other Languages), argues for a type of benchmarking that we call generic benchmarking to help develop quality education. The term generic is used to indicate that this type of benchmark is drawn from a detailed analysis and synthesis of extant literature, leading to the development and codification of quality characteristics and standards for an area. As the approach was used in research in TESOL, the context of the research is provided, as is a worked example drawn from the extensive literature review on planning for TESOL. Possible implications for staff development and curriculum improvement are identified.
Constant Delay Enumeration for Conjunctive Queries

We survey some of the recent results about enumerating the answers to queries over a database. We focus on the case where the enumeration is performed with a constant delay between any two consecutive solutions, after a linear time preprocessing. This cannot be always achieved. It requires restricting either the class of queries or the class of databases. We consider conjunctive queries and describe several scenarios when this is possible.
Short Paper: Data Mining-based Fault Prediction and Detection on the Grid

This paper describes a novel approach to fault detection and prediction on the grid based on data mining techniques. Data mining techniques are here applied as a mean to effectively process the significant amount of captured data from grid sites, services, workflows and activities. The paper provides a first approach of proposed techniques in terms of its ability of utilizing relevant information and the fault tolerance requirements. Such approach is one intelligent, distributed framework of fault detection and prediction for anomaly and failed activity by using resource- and workflow-based information. We use fault predictions to improve the performance of the workflow execution by avoiding potential faults of activities
Z-rays: divide arrays and conquer speed and flexibility

Arrays are the ubiquitous organization for indexed data. Throughout programming language evolution, implementations have laid out arrays contiguously in memory. This layout is problematic in space and time. It causes heap fragmentation, garbage collection pauses in proportion to array size, and wasted memory for sparse and over-provisioned arrays. Because of array virtualization in managed languages, an array layout that consists of indirection pointers to fixed-size discontiguous memory blocks can mitigate these problems transparently. This design however incurs significant overhead, but is justified when real-time deadlines and space constraints trump performance. This paper proposes z-rays, a discontiguous array design with flexibility and efficiency. A z-ray has a spine with indirection pointers to fixed-size memory blocks called arraylets, and uses five optimizations: (1) inlining the first N array bytes into the spine, (2) lazy allocation, (3) zero compression, (4) fast array copy, and (5) arraylet copy-on-write. Whereas discontiguous arrays in prior work improve responsiveness and space efficiency, z-rays combine time efficiency and flexibility. On average, the best z-ray configuration performs within 12.7% of an unmodified Java Virtual Machine on 19 benchmarks, whereas previous designs have two to three times higher overheads. Furthermore, language implementers can configure z-ray optimizations for various design goals. This combination of performance and flexibility creates a better building block for past and future array optimization.
Potential and natural output

We estimate a DSGE model with imperfectly competitive products and labor markets, and sticky prices and wages. We use the model to back out two counterfactual objects: potential output, i.e. the level of output that would prevail under perfect competition, and natural output, i.e. the level of output that would prevail with flexible prices and wages. We find that potential output is smooth, resulting in an output gap that closely resembles traditional measures of detrended output. Meanwhile natural output is extremely volatile, due to the very high variability of wage markup shocks. These disturbances, however, are very similar to measurement errors because they only explain price and wage inflation at very high frequencies. Under this alternative interpretation, potential and natural output move one-to-one.
Spiritual development: constructing an inclusive and progressive approach

This article examines the notion of spiritual development as it was conceptualised for state schools in Britain through the Conservative Government’s education reforms of the 1980s and 1990s, reforms which also introduced the National Curriculum. The article puts forward the argument that spiritual development was conceptualised in such a way as to attempt to reinstate progressive pedagogical values rejected by the National Curriculum reforms, but that the conceptualisation led to two conservative outcomes. First, spiritual development was not sufficiently robust to counteract the reforms and may have helped ease their passage. Second, education for the development of spiritual beliefs and values continued to be primarily located in Religious Education, even though a first principle of spiritual development was that spirituality should not be synonymous with religion in order that spiritual development should be inclusive. The article recommends that changes to Religious Education should be encouraged to ensure schools can provide opportunities for an inclusive and progressive education for spiritual development.
What are Thick Concepts?

Many theorists hold that there is, among value concepts, a fundamental distinction between thin ones and thick ones. Among thin ones are concepts like good and right. Among concepts that have been regarded as thick are discretion, caution, enterprise, industry, assiduity, frugality, economy, good sense, prudence, discernment, treachery, promise, brutality, courage, coward, lie, gratitude, lewd, perverted, rude, glorious, graceful, exploited, and, of course, many others. Roughly speaking, thick concepts are value concepts with significant descriptive content. I will discuss a number of problems having to do with how best to understand the notion of a thick concept. Thick concepts have been widely discussed in the metaethical literature. But some important problems concerning what thick concepts are supposed to be have not been squarely addressed even in the most systematic of these discussions. Here I want to highlight these problems.
Chapter Five: Biomechanics of Abusive Head Trauma

Summary The chapter provides a reference to the basic concepts of physics and the biomechanics necessary to the understanding of the mechanism of injury in abusive head trauma. Specific attention is given to the whiplash shaken-infant syndrome and shaken-impact models of abusive head trauma. The mechanical implications of falls from low heights are analyzed. The concluding section highlights unresolved problems in our understanding of these injuries and provides direction for future research.
FGF10 controls the patterning of the tracheal cartilage rings via Shh

During embryonic development, appropriate dorsoventral patterning of the trachea leads to the formation of periodic cartilage rings from the ventral mesenchyme and continuous smooth muscle from the dorsal mesenchyme. In this work, we have investigated the role of two crucial morphogens, fibroblast growth factor 10 and sonic hedgehog, in the formation of periodically alternating cartilaginous and non-cartilaginous domains in the ventral mesenchyme. Using a combination of gain- and loss-of-function approaches for FGF10 and SHH, we demonstrate that precise spatio-temporal patterns and appropriate levels of expression of these two signaling molecules in the ventral area are crucial between embryonic day 11.5 and 13.5 for the proper patterning of the cartilage rings. We conclude that the expression level of FGF10 in the mesenchyme has to be within a critical range to allow for periodic expression of Shh in the ventral epithelium, and consequently for the correct patterning of the cartilage rings. We propose that disturbed balances of Fgf10 and Shh may explain a subset of human tracheomalacia without tracheo-esophageal fistula or tracheal atresia.
Satisfaction with Career Choice among U.S. Plastic Surgeons: Results from a National Survey

Background: The authors' purpose was to describe patterns and correlates of satisfaction with career choice among U.S. plastic surgeons. Methods: A mailed, self-administered survey was sent to 708 U.S. plastic surgeons who were randomly sampled from the American Society of Plastic Surgeons registry (71 percent response rate, n = 505). The dependent variable was satisfaction with the decision to become a plastic surgeon, which was created from a scale of four validated questions measuring decisional satisfaction and decisional regret. The independent variables included surgeon and practice characteristics. Logistic regression was used to evaluate associations between satisfaction with the decision to become a plastic surgeon and independent factors. Results: Few respondents (4 percent) regretted becoming plastic surgeons. Factors independently associated with greater satisfaction with the decision to become a plastic surgeon included group practice compared with solo practice (odds ratio, 1.65; 95 percent confidence interval, 1.0 to 2.71), resident educator (odds ratio, 1.88; 95 percent confidence interval, 1.06 to 3.31), and a highly cosmetic practice mix: primarily cosmetic versus primarily reconstructive (odds ratio, 2.42; 95 percent confidence interval, 1.25 to 4.66) and mixed versus primarily reconstructive (odds ratio, 1.59, 95 percent confidence interval, 0.92 to 2.76). Demographic factors such as age and gender were not associated with surgeon satisfaction. Conclusions: Overall, the majority of plastic surgeons are satisfied with their career choice despite the current health care and economic environment. Factors significantly associated with greater satisfaction with career choice included group practice, involvement in resident education, and a highly elective cosmetic practice.
Myths about rough set theory

T he main concept of rough set theory (RST) is an indiscernibility relation normally associated with a set of attributes. For example, it may be the set consisting of attributes BloodPressure, Headache, and Temperature for an information table containing patient examination records. The key problem in this description is the informal term " normally associated. " In real life, such an association does not exist until additional assumptions are made. In a similar situation (an information table resembles a relation) Codd assumes the existence of functional dependencies stressing that they cannot be found by just examining the data, and hence must be specified by the database designer. Even simple values such as Yes or No cannot be considered objective for the attribute Headache since it may not be easy to decide if one does or does not have a headache (at least not to a high degree of accuracy). For example, is a minute headache still a headache or it not a headache at all? This problem is even more evident for another attribute, BloodPres-sure. Values Low, Normal, and High are a result of subjective judgements necessary for establishing boundaries for (more or less) objective measurements of blood pressure. Establishing these boundaries (say, <110,130> for normal), is as subjective as assuming a belief function in Dempster-Shafer theory or a membership function in fuzzy set theory. In fact the situation here is even more complex. From a medical point of view, it is reasonable to assume that if <110,130> is a normal systolic blood pressure, then so is <109.999,130> since 0.001 is far below the precision of a regular sphygmomanometer. Moreover , we should also be prepared 110,000 subtractions of 0.001 from the originally assumed value) unless an arbitrary decision is made about where to stop, since otherwise we may arrive at the rather risky medical conclusion that every deceased person has a normal blood pressure. To those who may argue that RST does not need discretization but simply works for rough values , we reply that there aren't any polar bears roaming freely around the North Pole with their fur coats marked Small, Medium, and Large, and yet we are inundated with all kinds of measurements such as time, velocity, pressure, temperature, and so forth, that require dis-cretization since RST is reduced to classic (crisp) set theory for continuous values. The subjectivity issue in RST is more complicated than in …
Co-Cap: energy-efficient cooperative CPU-GPU frequency capping for mobile games

Mobile platforms are increasingly using Heterogeneous Multi-Processor Systems-on-Chip (HMPSoCs) with differentiated processing cores and GPUs to achieve high performance for graphics-intensive applications such as mobile games. Traditionally, separate CPU and GPU governors are deployed in order to achieve energy efficiency through Dynamic Voltage Frequency Scaling (DVFS), but miss opportunities for further energy savings through coordinated system-level application of DVFS. We present Co-Cap, a cooperative CPU-GPU DVFS strategy that orchestrates energy-efficient CPU and GPU DVFS through coordinated CPU and GPU frequency capping to avoid frequency over-provisioning while maintaining desired performance. Unlike traditional approaches that target a narrow set of mobile games, our Co-Cap approach is applicable across a wide range of mobile games. Our methodology deploys a training phase followed by a deployment phase, allowing not only deployment across a wide range of mobile games with varying graphics workloads, but also across new mobile architectural platforms. Our experimental results across a large set of over 70 mobile games show that Co-Cap improves energy per frame by 10.6% and 10.0% (23.1% and 19.1% in CPU dominant applications) on average and achieves minimal frames per second (FPS) loss by 0.5% and 0.7% (1.3% and 1.7% in CPU dominant applications) on average in training- and deployment sets, respectively, compared to the default CPU and GPU governors, with negligible overhead in execution time and power consumption on the ODROID-XU3 platform.
Automated Diagnostic Systems With Diverse and Composite Features for Doppler Ultrasound Signals

In this paper, we present the automated diagnostic systems for Doppler ultrasound signals classification with diverse and composite features and determine their accuracies. We compared the classification accuracies of six different classifiers, namely multilayer perceptron neural network (MLP), combined neural network (CNN), mixture of experts (ME), modified mixture of experts (MME), probabilistic neural network (PNN), and support vector machine (SVM), which were trained on diverse or composite features. The present study was conducted with the purpose of answering the question of whether the automated diagnostic systems improve the capability of classification of ophthalmic arterial (OA) and internal carotid arterial (ICA) Doppler signals. Our research demonstrated that the SVM trained on composite feature and the MME trained on diverse features achieved accuracy rates which were higher than that of the other automated diagnostic systems
Prediction Analysis for Transition to Schizophrenia in Individuals at Clinical High Risk for Psychosis: The Relationship of DAO, DAOA, and NRG1 Variants with Negative Symptoms and Cognitive Deficits

Schizophrenia is characterized by positive and negative symptoms and cognitive dysfunction. The glutamate hypothesis of schizophrenia has been hypothesized to explain the negative symptoms and cognitive deficits better than the dopamine hypothesis alone. Therefore, we aimed to evaluate whether glutamatergic variants such as d-amino acid oxidase (DAO), DAO activator (DAOA)/G72, and neuregulin 1 (NRG1) single-nucleotide polymorphisms (SNPs) and their mRNA levels predicted (i) transition to schizophrenia spectrum disorders and (ii) research domain criteria (RDoC) domains, mainly negative valence and cognitive systems. In a 3-year prospective study cohort of 185 individuals (age: 13–35 years) at high risk and ultra-high risk (UHR) for psychosis, we assessed DAO (rs3918347, rs4623951), DAOA (rs778293, rs3916971, rs746187), and NRG1 (rs10503929) SNPs and their mRNA expression. Furthermore, we investigated their association with RDoC domains, mainly negative valence (e.g., anxiety, hopelessness) and cognitive (e.g., perception disturbances, disorganized symptoms) systems. NRG1 rs10503929 CC + CT versus TT genotype carriers experienced significantly more disorganized symptoms. DAOA rs746187 CC versus CT + TT genotype, DAOA rs3916971 TT versus TC + CC genotype, and DAO rs3918347 GA + AA versus GG genotype carriers experienced nominally more hopelessness, visual perception disturbances, and auditory perception disturbances, respectively. The schizophrenia risk G-allele of DAO rs3918347 nominally increased risk for those UHR individuals with attenuated positive symptoms syndrome. No association between DAO, DAOA, NRG1 SNPs, and conversion to schizophrenia spectrum disorders was observed. Our findings suggest that DAO, DAOA, and NRG1 polymorphisms might influence both RDoC negative valence and cognitive systems, but not transition to schizophrenia spectrum disorders.
Delivering Business Value through Information Literacy in the Workplace

This paper presents a real-life example as to how the world's largest environmental consulting firm – Environmental Resources Management (ERM) – recognises ‘information literacy’ as a critical component of its knowledge management program to create value for the company. With the rise of information technology which allows vast amounts of information to flow across an organisation very quickly, many employees have been complaining about ‘information overload’ and ‘knowledge underload’. Companies in the past 10 years have ‘recognised’ the value of information and knowledge, and it is becoming a strategic issue to provide employees with access to the right information at the right time. As a result, managing information and knowledge becomes a business critical agenda item discussed in the boardroom, with the aim to apply global knowledge to deliver the highest quality solutions to clients. Despite all the investment, however, employees find that the information/knowledge management systems generate too many reports/results which nobody reads, and when employees need information to support their work, they are not getting what they want. Why are employees not getting the full benefits out of a global knowledge management system? What is the common perception of the ‘information overload’ problem in the workplace? Is this a symptom of a much bigger problem? Is there an alternative perspective that can shed some light on this issue? The modern workplace requires employees who are confident and competent in interacting with information to deliver maximum business value. In this paper, the author argues there is a body of existing information literacy knowledge (mostly developed in the education context) which can be adapted to address ‘information overload’ in the workplace context.
Potential Histamine H2‐Receptor Antagonists: Analogues of Classical Antagonists Containing 4‐Substituted‐3‐Aminofurazan Moieties

Analogues of classical H2‐receptor antagonists containing aminofurazan moieties as polar groups were synthesized and tested “in vitro” for their activities. Compounds containing 3‐amino‐4‐methylfurazan and 4‐amino‐3‐methylfuroxan substructures show good antagonistic properties. The compound containing the 3‐amino‐4‐phenylfurazan moiety is inactive. An SAR approach is discussed.
Accelerating Raster Processing with Fine and Coarse Grain Parallelism in GRASS

GIS technology is deployed across a wide range of applications, from relatively simple maps to applications that require huge computational power such as remote sensing data storage and processing, and natural phenomena such as fire, flooding, landslide, and pollution. High quality modeling and data sources produce huge rasters and long processing times. Parallelizing such applications is a well researched field, with proven and efficient methods[8]. The dataset is usually large. As a consequence, raster processing algorithms are sensitive to memory limitations. Based on those observations, the use of a Beowulf cluster [10] for raster processing appears convincing. Each node in a cluster adds memory, cache, memory bandwidth, I/O bandwidth and a CPU, and communication overhead. Fine grain parallelism and the use of massively parallel computation represent a promising solution. The remote sensing community has very early on used the power of parallel computers to process satellite and airborne data. But the number of cells to be processed is very high which by consequence requires an architecture containing a high number of processors. SIMD (Single Instruction Multiple Data) machines such as Connexion machine CM-2 and CM-200, and the MasPar machine MP-1 have been a good choice to process this kind of applications. But those machines, expensive and too specialized, have been abandoned. Nowadays, current microprocessors integrate Multimedia units, which reproduce on a smaller scale this paradigm. This approach has been termed SWAR[2] (SIMD Within A Register) and allows fine grain parallelism on standard microprocessors. And the maturation of new computing devices such as FPGAs1 and Reconfigurable Computing capable of efficient fine grain parallelism and tools offers another solution to fine grain parallelism[1]. Our approach is to used a hybrid Beowulf cluster where each node contains a microprocessor and a fine grain parallel processor. The coarse grain parallelism is implemented among nodes. The fine grain processor will run fine grain parallel tasks with a SIMD paradigm. Current microprocessors support SIMD processing through SWAR (SIMD Within A Register). They provide large registers that may be partitioned in smaller fields, and instructions that operate on all fields simultaneously. The next section presents more aspects of raster based GIS applications, followed by a discussion on parallelizing this kind of applications. Further a beowulf cluster combined with fine grain processors will be presented. Some experiments and results will be discussed before concluding and discussing some future aspects of this work.
Performance maximization of 3D-stacked cache memory on DVFS-enabled processor

3D integration increases chip integration density, reduces wire length, wire delay and power consumption on wires. However, increased power density causes increase of temperature, which results in the increase of leakage power consumption and performance degradation. In this paper, we propose a solution to compromise these issues on stacking cache memory on a processor core. Experimental results have shown that the proposed method yields, on the average, 16% performance improvement in terms of instructions per second compared to conventional method. The proposed method also reduces energy consumption by 20% on average, in terms of energy per instruction.