Miracle-dz/UniFAR-FTUs huggingface dataset:
ACCELERATION OF IMAGE RESTORATION ALGORITHMS FOR DYNAMIC MEASUREMENTS IN COORDINATE METROLOGY BY USING OPENCV GPU FRAMEWORK

This paper presents an approach for decreasing the processing time of dynamic image restoration for metrological applications. An extension of the Richardson-Lucy deconvolution algorithm for an optimal breaking of the restoration with respect to the change of the sub pixel-precise edge position is proposed. Therefore a powerful parallelization of the restoration algorithms was tested on graphics processing unit (GPU) by using OpenCV C++ framework. A comparison to a processing on multi-core central processing unit (CPU) with a variation of input data size and restoration calculation amount is performed. The experimental results reveal the optimal break-even point for an time efficient processing of the algorithms on GPU.
Measuring the distribution of fitness effects in somatic evolution by combining clonal dynamics with dN/dS ratios

The distribution of fitness effects (DFE) defines how new mutations spread through an evolving population. The ratio of non-synonymous to synonymous mutations (dN/dS) has become a popular method to detect selection in somatic cells, however the link, in somatic evolution, between dN/dS values and fitness coefficients is missing. Here we present a quantitative model of somatic evolutionary dynamics that yields the selective coefficients from individual driver mutations from dN/dS estimates, and then measure the DFE for somatic mutant clones in ostensibly normal oesophagus and skin. We reveal a broad distribution of fitness effects, with the largest fitness increases found for TP53 and NOTCH1 mutants (proliferative bias 1-5%). Accurate measurement of the per-gene DFE in cancer evolution is precluded by the quality of currently available sequencing data. This study provides the theoretical link between dN/dS values and selective coefficients in somatic evolution, and reveals the DFE for mutations in human tissues.
Mining opinion polarity relations of citations

Opinion mining has been receiving increasing attention recently, and various approaches have been suggested for mining sentiment information, such as mining attitudes or opinions about a topic or product etc. However, as far as we know, little work has been reported on citation opinion mining (COM). By COM, we refer to the process of identifying authors opinions towards the works they cite, such as positive/negative attitudes or approval/disapproval. We contend that such information is useful for semantic information retrieval and text mining, particularly for users who wish to search for documents taking a positive or negative stance towards a specific previous work. In this paper, we propose a system which is based on existing semantic lexical resources and NLP tools, aiming to create a network of opinion polarity relations between documents and citations. This is a web-based system which allows users to access the citations collected from documents and retrieve those documents linked to each of the citations with different opinion polarity relations, namely approval, neutral or disapproval relations. Various approaches will be tested including detecting semantic orientation of subjective words in the context of citations and machine learning using manually annotated data. In particular, we will explore the use of semantic lexicons for this task.
Systematic review of antibacterial activity of eravacycline: a novel fluorocycline against clinically obtained Gram-negative bacteria

ISSN Eravacycline (TP-434 or 7-fluoro-9-pyrrolidinoacetamido-6-demethyl-6-deoxytetracycline) is a novel fluorocycline antibiotic, which was designed to overcome tetracyclinespecific resistance mechanisms. This study aimed to analyze the in-vitro activity of eravacycline against Gram-negative bacteria in published literature, to contribute to the international data on the antimicrobial stewardship programs. A systematic literature review was performed through the electronic databases from January of 2000 to December 2017 to cover all published articles relevant to our scope. Finally, nine studies met our inclusion criteria that were subjected to data extraction and review. The highest activity of eravacycline was against Escherichia coli isolates since in all reports eravacycline at a concentration of 0.5 mg/ml or less inhibited 90% of isolates. In contrast, the lowest activity was seen against Proteeae isolates since except for one report eravacycline at a concentration of at least 2 mg/ml inhibited 90% of isolates. The antibacterial activity of eravacycline against 13 collections of carbapenem-resistant bacteria consists of 1057 isolates was showed that eravacycline at a concentration of 2 mg/ml or less inhibited 90% of isolates. The only exception was for carbapenemresistant Proteeae which 90% of isolates were inhibited at a concentration of at least 4 mg/ml. In summary, eravacycline has a promising in-vitro antibacterial property against several nosocomial pathogens. This was an encouraging result that provides an option for treatment of infections caused by Gram-negative bacteria, regardless of resistance phenotype. However, further clinical studies are necessitate to provide clinical evidence to support these observations. Copyright 2019 Wolters Kluwer Health, Inc. All rights reserved.
Harnessing FPGA technology for rapid circuit debug

Electronic devices have come to permeate every aspect of our daily lives, and at the heart of each device is one or more integrated circuits. State-of-the art circuits now contain several billion transistors. However, designing and verifying that these circuits function correctly under all expected (and unexpected) operation conditions is extremely challenging, with many studies finding that verification can consume over half of the total design effort. Due to the slow speed of logic simulation software, designers increasingly turn to circuit prototypes implemented using field-programmable gate array (FPGA) technology. Whilst these prototypes can be operated many orders of magnitude faster than simulation, on-chip instruments are required to expose internal signal data so that designers can root-cause any erroneous behaviour. This thesis presents four contributions to enable rapid and effective circuit debug when using FPGAs, in particular, by harnessing the reconfigurable and prefabricated nature of this technology. The first contribution presents a post-silicon debug metric to quantify the effectiveness of trace-buffer based debugging instruments, and three algorithms to determine new signal selections for these instruments. Our most scalable algorithm can determine the most influential signals in a large 50,000 flip-flop circuit in less than 90 seconds. The second contribution of this thesis proposes that debug instruments be speculatively inserted into the spare capacity of FPGAs, without any user intervention, and shows this to be feasible. This proposal allows designers to extract more trace data from their circuit on every debug turn, ultimately leading to fewer debug iterations. The third contribution presents techniques to enable faster debug turnaround, by using incrementalcompilation methods to accelerate the process of inserting debug instruments. Specifically, our incremental optimizations can speed up this procedure by almost 100X over recompiling the FPGA from scratch.
Investigating the foliar uptake of zinc from conventional and nano-formulations: a methodological study

Environmental contextZinc, an essential micronutrient often applied to crops as a fertiliser, can be difficult to analyse in plants due to limitations of conventional techniques. Here, we use radiotracers and a non-destructive imaging technique to visualise how zinc applied as a nanofertiliser moves within wheat plants over time. This is an important step towards developing cost-effective fertilisers to help solve one of the world’s most widespread plant deficiencies. AbstractZinc (Zn) deficiency affects half of the world’s arable soil and one-third of the world’s human population. Application of Zn foliar fertilisers to cereal crops can be an effective way to increase grain Zn content; however, commonly used formulations can scorch the leaf (e.g. soluble Zn salts) or are prohibitively expensive (e.g. chelated Zn, ZnEDTA). Zinc oxide nanoparticles (ZnO-NPs) may offer an efficient and cost-effective alternative, but little is known regarding the mechanisms of Zn uptake and translocation within the plant. Foliar-applied Zn is analytically challenging to detect, locate and quantify, as it is omnipresent. Furthermore, any single analytical technique does not have the detection limit or spatial resolution required. In this study, the uptake and mobility of foliar-applied ZnEDTA, ZnO-NPs and ZnO microparticles (ZnO-MPs) to wheat (Triticum aestivum L.) were investigated using inductively coupled plasma mass spectroscopy (ICP-MS), synchrotron-based X-ray fluorescence microscopy (XFM) and radiotracing techniques using 65Zn-labelled formulations. The three techniques were compared to highlight limitations and advantages of each. We also report, for the first time, a novel time-resolved invivo autoradiography imaging technique that can be used to visualise 65Zn in live plants treated with foliar applications of 65ZnO-NPs and MPs. The images were supplemented by gamma spectroscopy analysis for quantification. The results of this study provide important insights into the analytical challenges faced when investigating foliar-applied Zn nanofertilisers in plants. Potential solutions using nuclear techniques are also discussed, which in turn may ultimately lead to the development of more efficient foliar fertilisers.
Instance transformation for declarative solvers

Declarative specification-based problem solving systems, or "model-and-solve" systems, solve combinatorial search problems based on specifications in high-level declarative languages. Users of these systems can solve challenging combinatorial problems by describing what a solution is, rather than describing an algorithm for finding one. While the problem specifications are declarative, users of existing systems must write programs to transform problem instances into solver-specific formats, so problem solving is not fully declarative. We describe a purely declarative method for transforming instances from native file formats to solver-specific formats. We also describe a prototype implementation which, used together with existing declarative solvers, provides fully declarative problem solving. The method can also be seen as a way to produce model finders for new logics, of moderate expressive power, purely declaratively. We illustrate application of the method to a variety of problems, including graph problems and logical satisfiability problems.
Effect of the concentration and carbon chain length of a sulfate-based surfactant on hydrate formation kinetics

This paper reports an experimental study on the effect of the concentration and the carbon chain length of surfactants on the formation kinetics of gas hydrates in a quiescent CO2/CH4/water system. Sodium alkyl sulfates with different carbon chain length (C8, C10, C12, C14, C16 and C18) were tested at different concentrations. The experiments were conducted in a batch configuration, at a temperature of 275 K and with an initial gas pressure of about 3.3 MPa. For each system studied, hydrate crystallization was triggered by suddenly injecting a small amount of THF (4,000 ppm) directly into the surfactant solution in contact with the gas-hydrate-former phase at 275 K and 3.3 MPa. The long induction time for hydrate formation usually observed for these systems at the pressure and temperature conditions used in this study was thus eliminated. The experimental results show that, of the six surfactants tested, only the sodium dodecyl (C12) sulfate efficiently promotes the formation of CO2-CH4 binary hydrate under quiescent conditions. A minimum concentration of 500 ppm of the C12 surfactant was however necessary to obtain a beneficial effect on hydrate formation, and the rate of hydrate crystallization was observed to level off for the surfactant concentrations higher than 3,000 ppm. For the systems containing the C8 and C10 surfactants, which have a Krafft temperature lower than 275 K, the presence or absence of micelles in the surfactant solution does not have any effect on the hydrate formation kinetics.
To post or not to post : undergraduate student perceptions about participating in online discussions

Computer mediated conferencing (CMC) is now a common feature of blended learning environments where students learn in both face to face and online settings. While many teachers recognize the value of online discussions for learning, students appear to have different perspectives. Consequently, their participation in online discussions is often sporadic and not genuinely interactive. This paper examines these issues and provides student perspectives about participation in online discussions which arose from a case study in a conceptually difficult subject. Systems data indicated low numbers of posted messages. Student interviews provide some insights into this lack of participation, and identify the influence of the curriculum design, especially the nature of the learning activity, and its connection to other aspects of the course, for example, assessment and the regular class sessions. Other influential factors include the student’s ideas about learning, managing demands on their time and their acceptance of CMC. The paper also provides recommendations for improving participation in online discussions.
Expert systems maintainability

Design for maintainability in expert systems is examined. Related issues discussed include the software engineering process, the differences between expert systems and conventional software that affect maintainability, and the use of expert system shells and development tools. Specific points to consider when performing a maintainability analysis of expert system code include using conventional software engineering guidelines tailored for expert systems and using basic expert system features as a foundation for a maintainable product. <<ETX>>
Supporting Accounting Students to Read Before Class

There is evidence a large proportion of accounting students prepare inadequately for classes at university. Lack of reading before classes would support passive, surface learning. This study examines how to support accounting students to read before classes. A sample of 81 students in a third year undergraduate accounting course was studied employing a phenomenographic research approach, using five session preparation assignments (SPAs) for each student (supplemented by a focus group, critical incident questionnaires (CIQs) and student surveys) to identify and capture the experience of students reading before classes. A key finding is that it is possible to support a large proportion of students to read before class through use of structured, assessed learning journals and readings with a deep approach to learning embedded in them as part of an integrated set of interventions designed to support deep learning. An implication of this study is the need to support accounting students to read before classes in first year courses as part of their ‘learning how to learn’ at university to enable them to develop personal capabilities in their later university studies.
High-speed architectures for algorithms with quantizer loops

High-speed microelectronic implementation of adaptive equalizers, encoders, and other associated signal processing algorithms is difficult, since the recursive portion of these algorithms contains nonlinear quantization operations. Examples of such algorithms include differential pulse code modulation (DPCM), adaptive DPCM (ADPCM), and differential feedback equalizers (DFEs). In the past, look-ahead computation techniques were successfully applied to create necessary concurrency in linear recursive and some nonlinear recursive operations (such as the add-compare-select operation). Novel computation approaches are presented, and the look-ahead technique is extended to pipeline the feedback loops containing finite-level quantizers. Approaches to pipeline piecewise linear recursive systems are also presented. <<ETX>>
In The Name Of Allah Most Gracious Most Mercyful Quantitative Comparison Between: Temporalis & Masseter Muscles In: Women & Men dentate persons By: Power Spectrum Analysis of EMG Parameters.

This study accomplished by using the power spectrum analysis of EMG parameters registered by surface electrodes secured on major bulk center of anterior temporalis and masseter muscles of (12) women dentate persons and (16) men dentate persons with age range (48-58) years. The results were obtained and statistically analyzed to compare the values of amplitude and frequency parameters obtained from each subject groups during clenching in maximum intercuspation position (MIP), right lateral position (RLP) and left lateral position (LLP) and, also, during chewing (3) grams of peanuts and (5) one cubic centimeter pieces of carrot. The quantitative comparison showed that the men dentate persons registered higher amplitude values than women dentate persons , and that indicate the presence of large size motor units, in temporalis and masseter muscles of men subjects, which were responsible for the registration of the higher values by synchronization of motor unit action potentials. Whereas, the frequency parameters of the two subject groups showed no significant differences which means the number of the motor units and firing phases are almost the same. These results can be utilized in 1. understanding the behavior of masticatory muscles in older ages dentate persons before losing the teeth. 2. Keeping the registered parameter values to be restored when designing the future partial or complete denture. 3. treating any problem occur in masticatory muscles.
miRDRN—miRNA disease regulatory network: a tool for exploring disease and tissue-specific microRNA regulatory networks

Background MicroRNA (miRNA) regulates cellular processes by acting on specific target genes, and cellular processes proceed through multiple interactions often organized into pathways among genes and gene products. Hundreds of miRNAs and their target genes have been identified, as are many miRNA-disease associations. These, together with huge amounts of data on gene annotation, biological pathways, and protein–protein interactions are available in public databases. Here, using such data we built a database and web service platform, miRNA disease regulatory network (miRDRN), for users to construct disease and tissue-specific miRNA-protein regulatory networks, with which they may explore disease related molecular and pathway associations, or find new ones, and possibly discover new modes of drug action. Methods Data on disease-miRNA association, miRNA-target association and validation, gene-tissue association, gene-tumor association, biological pathways, human protein interaction, gene ID, gene ontology, gene annotation, and product were collected from publicly available databases and integrated. A large set of miRNA target-specific regulatory sub-pathways (RSPs) having the form (T, G1, G2) was built from the integrated data and stored, where T is a miRNA-associated target gene, G1 (G2) is a gene/protein interacting with T (G1). Each sequence (T, G1, G2) was assigned a p-value weighted by the participation of the three genes in molecular interactions and reaction pathways. Results A web service platform, miRDRN (http://mirdrn.ncu.edu.tw/mirdrn/), was built. The database part of miRDRN currently stores 6,973,875 p-valued RSPs associated with 116 diseases in 78 tissue types built from 207 diseases-associated miRNA regulating 389 genes. miRDRN also provides facilities for the user to construct disease and tissue-specific miRNA regulatory networks from RSPs it stores, and to download and/or visualize parts or all of the product. User may use miRDRN to explore a single disease, or a disease-pair to gain insights on comorbidity. As demonstrations, miRDRN was applied: to explore the single disease colorectal cancer (CRC), in which 26 novel potential CRC target genes were identified; to study the comorbidity of the disease-pair Alzheimer’s disease-Type 2 diabetes, in which 18 novel potential comorbid genes were identified; and, to explore possible causes that may shed light on recent failures of late-phase trials of anti-AD, BACE1 inhibitor drugs, in which genes downstream to BACE1 whose suppression may affect signal transduction were identified.
Chapter 9: Mining Textual Knowledge for Writing Education and Research: The DocuScope Project

This chapter reviews progress on a new corpus-based text analysis technology developed at Carnegie Mellon, called DocuScope. It describes a new technology used to support research and education involving digitized text, especially corpus-based rhetorical analysis and on-line writing education. The first half of the chapter lays out an overview of analytic choices we have made for conducting textual research. The second half of the chapter explores how the knowledge derived from the DocuScope tool can benefit writing education and the evaluation of writing curricula. The chapter overviews different frameworks and describes a specific system as a result of the choices that confronted us within the space of these frameworks. It overviews some applications of our system, notably using student samples both to evaluate and improve writing instruction and writing curricula itself. Keywords: analytic choices; corpus-based rhetorical analysis; digitized text; DocuScope; on-line writing education; student samples; textual research; writing curricula
The Science of Learning and the Learning of Science Introducing Desirable Difficulties

Students' performance during instruction is commonly viewed as a measure of learning and abasis for evaluating and selecting instructional practices. Laboratory findings question thatview: Conditions of practice that appear optimal during instruction can fail to support long-termretention and transfer of knowledge and, remarkably, conditions that introduce difficulties forthe learner — and appear to slow the rate of the learning — can enhance long-term retentionand transfer. Such "desirable difficulties" (Bjork, 1994) include: spacing rather than massingstudy sessions; interleaving rather than blocking practice on separate topics; varying howto-be-learned material is presented; reducing feedback; and using tests as learning events.Our project, funded by the Institute of Educational Sciences (IES), focuses on whether the benefits of desirable difficulties generalize to realistic educational materials and contexts. In a coordinated series of laboratory and classroom experiments involving college and middle-school students, respectively, we have examined whether introducing desirable difficulties can improve the effectiveness of Web-based Inquiry Science Environment (WISE, http://wise.berkeley.edu) projects. WISE modules, on science topics such as astronomy, genetic inheritance, and chemical reactions, are customizable and are used extensively by middle- and high-school teachers around the world. Among the advantages of WISE as a research tool is that we can study variations in instruction delivered in the same classroom and also quickly propagate promising practices to new modules.