Miracle-dz/UniFAR-FTUs huggingface dataset:
Strategic retailer behaviour in an electricity contract market

Generators in a wholesale electricity market can exercise market power, but the existence of forward hedging contracts between consumers and generators mitigates this market power. A question arises as to why generators are willing to enter contracts with consumers to surrender their market power. In this paper, we model the role of the consumers (retailers here) in offering hedging contracts to generators. We suppose that the retailer gives the generators economic incentives to enter into contracts, quite apart from any risk premium. Our model shows that the retailer can increase its profit in comparison with the case when there are no contracts, and that the social welfare is maximized. We also consider a situation with multiple retailers and model the contracting game between the retailers.
Analysing Security Threats and Vulnerabilities Using Abuse Frames

In this paper, we present an approach using problem frames to analyse security problems in order to determine security threats and vulnerabilities. We use problem frames to capture and bound the base system that is to be protected. We consider threats to this base problem frame from the point of view of the attacker. For each class of threats, their successful realisation is regarded as the anti-requirement in an abuse frame. Antirequirements are quantified existentially: that is, the attacker succeeds by realising the threat in any one instance. For a threat to be realised, its abuse frame must be composed with the base problem frame in the sense that the asset attacked in the abuse frame must overlap, or be identified with, a domain of the base problem frame. We explain the process of composition and some of its variations. We illustrate and assess our approach using a case study of a medical information system, and suggest how abuse frames can provide a means for bounding the scope of and reasoning about security problems in order to analyse security threats and identify vulnerabilities. We conclude with an agenda for future work.
A recognition based system for segmentation of touching handwritten numeral strings

A novel recognition-based system for segmentation of touching handwritten numeral strings is proposed. In this paper, we combine external contour analysis and projection analysis to find candidate segmentation points. With internal contour analysis, the candidate segmentation points is utilized to determine the corresponding candidate segmentation lines with which the numeral string is over-segmented. Each sub-image of the over segmented string is defined as a fragment. The combination of one or more adjacent fragments is defined as a clique. Thus, each candidate segmentation result is composed of one or more cliques. Subsequently, all the candidate segmentation results are described in a probabilistic model, and a classifier is embedded to recognize each clique. Finally, with the maximum a posterior (MAP) criterion, the optimal segmentation result is selected from all candidate segmentation results. This scheme is effective and robust for both single and multiple touching numerals. Experiment results on collection of samples from NIST SD19 show that our system can achieve a correct rate of 97.72% without rejection, which compares favorably with those reported in the literature.
International Journal of General Medicine Dovepress a 25-year Trace of Methicillin-resistant Staphylococcus Aureus Dissemination in a Geriatric Hospital in Japan

We analyzed 218 strains of methicillin-resistant Staphylococcus aureus (MRSA) isolated from the septicemia patients in a geriatric hospital for 25 years. These strains were classified into 11 major DNA types, A through K, and 27 minor types. The strains belonging to group A and B isolated before 1990 were susceptible to imipenem (IPM), fluoroquinolone, and most other antibiotics tested, except that they were markedly resistant to gentamicin. Strains mostly isolated in 1985 and thereafter were classified into group C through K, and they were mainly resistant to IPM, fluoroquinolones, and clindamycin. Analysis of the MRSA marker gene, staphylococcal cassette chromosome mec (SCCmec), of these strains revealed that the strains in groups A and B had mainly type IV and type I, respectively, and that strains in groups C through J had mainly type II. These results suggested that the strains holding type II SCCmec were resistant to IPM, fluoroquinolone, and clindamycin and they were dominant-resistant type after late 1980s. The antibiotic resistance profiles of MRSA dramatically changed during late 1980s, and these were correlated with the SCCmec types. The lesson from this study would be that consistent execution of surveillance study is needed to update the resistant profiles.
Clusters as Single Underlying Consonants: Evidence from Children's Production

Some historical data (Gamkrelidze 1966) indicates that some clusters are equivalent to a single consonant at some point in time and then later are realized as two separate sounds. It has also been proposed (Hoffman 1967) that initial clusters are best described as a single element in the underlying phonological representation. Later rules decompose the cluster into segments with each segment containing its complete set of features. The underlying representation of a speech sound and of the clusters in which it participates would be different, as indicated in Figure l.
A novel fusion algorithm for visible and infrared image using non-subsampled contourlet transform and pulse-coupled neural network

An image fusion algorithm between visible and infrared images is significant task for computer vision applications such as multi-sensor systems. Among them, although a visible image is clear perfectly able to be seen through the naked eyes, it is often suffers with noise; while an infrared image is unclear but it has high anti-noise property. In this paper, we propose a novel image fusion algorithm for visible and infrared images using a non-subsampled contourlet transform (NSCT) and a pulse-coupled neural network (PCNN). First, we decompose two original images above mentioned into low and high frequency coefficients based on the NSCT. Moreover, each low frequency coefficients for both images are duplicated at multiple scales, and are processed by laplacian filter and average filter respectively. Finally, we can fuse the normalized coefficients by using the PCNN. Conversely, we can reconstruct a fused image based on the low and high frequency coefficients, which are fused by using the inverse NSCT. Experimental results show that the proposed image fusion algorithm surpasses the conventional and state-of-art image fusion algorithm.
Iterative sharpening for image contrast enhancement

In this paper, the problem of iterative sharpening for local contrast enhancement is addressed. We present a fast algorithm that spreads the high frequencies of an image to successively lower resolutions resulting in an improvement in sharpness and local contrast. The algorithm is similar to the well established unsharp masking with certain fundamental differences. The image is blurred with a Gaussian filter and a difference image representing the hight frequencies is calculated. This difference is then amplified and added back to the blurred image and the process is repeated without altering the original high frequencies. Our result demonstrate that up to 100 iterations can be applied without image artifacts.
Nurturing ‘buds of development’: from outcomes to opportunities in early childhood practice

ABSTRACT The current future-focused, outcomes driven early childhood policy climate presents a danger that early years pedagogy will lose sight of the ‘present’ child. Increasingly policy support for early childhood education is built around an emphasis on preparing children for school and positioning it as a key element in enhancing society through preparing future citizens to become productive members of society. The measurable outcomes discourse, in emphasising product, renders invisible the critical contribution of the processes of everyday practice to children’s development. To challenge and counteract the strong outcome discourse early years professionals must have confidence in their pedagogy. However, research suggests that those working in the early years may lack the language and strategies for supporting their educational practice. Using the bio-ecological model of development and drawing on the capabilities approach this paper calls for a shift in policy and pedagogical discourse from measuring competencies towards enhancing capabilities, from assessing outcomes towards providing rich, day-to-day learning opportunities. Such a shift in narrative could weaken the neo-liberal, outcome language of early childhood policy and refocus on supporting an early childhood pedagogy that would explicitly reflect current understanding of what is most beneficial to children’s development and well-being and provide a powerful potential for change.
Macrophages participate in local and systemic inflammation induced by amorphous silica nanoparticles through intratracheal instillation

Silica nanoparticles (SiNPs) are amongst the most commonly used materials in the field of nanomedicine and, therefore, their influence on organisms has drawn increasing attention in recent years. Most reports have focused on the single tissue reactions induced by SiNPs. Herein, the reaction of primary organs to SiNPs following intratracheal instillation in mice was analyzed by histopathology and ultrastructure observation. Following elucidation of the role of macrophages in local and systemic inflammation, the underlying mechanisms were explored using a macrophage cell line in vitro. The results suggest that macrophages swallow the SiNPs and secrete inflammatory factors by activating the NLRP3 inflammasome, thus participating in local and systemic inflammation.
A Preliminary Study of Severe Wind-Producing MCSs in Environments of Limited Moisture

Abstract An examination of severe wind-producing mesoscale convective systems that occur in environments of very limited moisture is presented. Such systems, herein referred to as low-dewpoint derechos (LDDs), are difficult to forecast as they form in regions where the level of convective instability is well below that normally associated with severe convective weather. Using a dataset consisting of 12 LDDs that affected various parts of the continental United States, composite surface and upper-level analyses are constructed. These are used to identify factors that appear to be associated with LDD initiation and sustenance. It is shown that LDDs occur in mean kinematic and thermodynamic patterns notably different from those associated with most derechos. LDDs typically form along or just ahead of cold fronts, in the exit region of strong, upper-level jet streaks. Based on the juxtaposition of features in the composite analysis, it appears that linear forcing for ascent provided by the front, and/or ageos.
Learning to Rank for Information Retrieval Using Genetic Programming

central problem of information retrieval (IR) is to determine which documents are relevant and which are not to the user information need. This problem is practically handled by a ranking function which defines an ordering among documents according to their degree of relevance to the user query. This paper discusses work on using machine learning to automatically generate an effective ranking function for IR. This task is referred to as "learning to rank for IR" in the field. In this paper, a learning method, RankGP, is presented to address this task. RankGP employs genetic programming to learn a ranking function by combining various types of evidences in IR, including content features, structure features, and query-independent features. The proposed method is evaluated using the LETOR benchmark datasets and found to be competitive with Ranking SVM and RankBoost.
Toward a stereoscopic encoder/decoder for digital cinema

The digital cinema is very challenging because it represents tomorrow way of capturing, post-producing and projecting movies. Specifications on this media are provided by DCI (Digital Cinema Initiatives) founded by the Hollywood Majors. Among the specifications we can find issues about resolution, bitrate, JPEG2000 compression Moreover, the market assumes that 3D could raise the turnover of cinema industry. The problem with is the availability of 2 streams (left and right) that double the amount of data and need adapted devices to decode and project movies. Cinema industry, represented by the stereoscopic group in SMPTE has expressed the need of having a unique master that combines two streams in one. This paper focuses on the study of the generation of a master with one of the streams and the embedment of the redundant information as metadata in JPEG2000 code-stream or MXF. The idea is to use the reference image in addition to some metadata to reconstruct the target image. The metadata represent the residual image and the contours description. Quality of reconstructed images depends on the compression ratio of the residual image. The obtained results are encouraging and the choice between JPEG2000 metadata embedding and MXF metadata still to be done.
Towards mediator connectors for application level interoperability

My research work aims at overcoming the heterogeneity barriers that prevent networked systems to interoperate, thus enabling them to communicate responding to the continuously evolving networked environment. The thesis focusses on the concept of mediator connector as the key enabler for system interoperability. The proposed work about mediator connectors is investigated in the scope of the CONNECT1 European project.
DEVELOPMENT OF DSP BASED INSTRUMENT FOR MONITORING PLC AND OTHER HIGH FREQUENCY SIGNALS IN DISTRIBUTION NETWORKS

Concerns in identifying and diagnosing power quality related disturbances in power line communication (PLC) network has enforced special requirement for power quality monitoring equipment and creates a need for sophisticated software to analyze the monitored data. Most of the existing monitoring equipment are too expensive, they are neither handy nor capable of detecting the disturbances in realtime. Therefore, there is a need for remotely readable lowcost monitoring equipment that can be used to perform accurate and real-time detection of power disturbances. Digital signal processor (DSP) is the optimal choice to fulfill real-time analysis. Advanced DSP provides fast data capture, fast data processing and flexibility in processing signals, increased system performance and reduced system cost. Successful completion of this research work would be of immense benefit to electrical power industry in general and smart grid applications in particular. KeywordsDigital Signal Processors, Information Technology (IT), Power Line Communication, Power Quality Measurement, Smart Grid.
Computational Intelligence in Music Composition: A Survey

Composing music is an inspired yet challenging task, in that the process involves many considerations such as assigning pitches, determining rhythm, and arranging accompaniment. Algorithmic composition aims to develop algorithms for music composition. Recently, algorithmic composition using artificial intelligence technologies received considerable attention. In particular, computational intelligence is widely used and achieves promising results in the creation of music. This paper attempts to provide a survey on the computational intelligence techniques used in music composition. First, the existing approaches are reviewed in light of the major musical elements considered in composition, to wit, musical form, melody, and accompaniment. Second, the review highlights the components of evolutionary algorithms and neural networks designed for music composition.
Prevalent Role of Gene Features in Determining Evolutionary Fates of Whole-Genome Duplication Duplicated Genes in Flowering Plants1[W][OA]

Some gene features, including evolution rate and gene structural complexity, are highly correlated to a gene’s evolutionary fate after whole-genome duplication. The evolution of genes and genomes after polyploidization has been the subject of extensive studies in evolutionary biology and plant sciences. While a significant number of duplicated genes are rapidly removed during a process called fractionation, which operates after the whole-genome duplication (WGD), another considerable number of genes are retained preferentially, leading to the phenomenon of biased gene retention. However, the evolutionary mechanisms underlying gene retention after WGD remain largely unknown. Through genome-wide analyses of sequence and functional data, we comprehensively investigated the relationships between gene features and the retention probability of duplicated genes after WGDs in six plant genomes, Arabidopsis (Arabidopsis thaliana), poplar (Populus trichocarpa), soybean (Glycine max), rice (Oryza sativa), sorghum (Sorghum bicolor), and maize (Zea mays). The results showed that multiple gene features were correlated with the probability of gene retention. Using a logistic regression model based on principal component analysis, we resolved evolutionary rate, structural complexity, and GC3 content as the three major contributors to gene retention. Cluster analysis of these features further classified retained genes into three distinct groups in terms of gene features and evolutionary behaviors. Type I genes are more prone to be selected by dosage balance; type II genes are possibly subject to subfunctionalization; and type III genes may serve as potential targets for neofunctionalization. This study highlights that gene features are able to act jointly as primary forces when determining the retention and evolution of WGD-derived duplicated genes in flowering plants. These findings thus may help to provide a resolution to the debate on different evolutionary models of gene fates after WGDs.
Improving bridle low-speed regulation using cascaded current followers

The torque or current references to the current loops of motor drives providing power to helper-rolls in bridles are usually slaved directly from the current reference of the master speed regulated roll. At low line speeds, the current required to overcome losses in the master speed regulated roll will differ significantly from the current required to overcome losses in the helper-rolls, resulting in overall erratic speed regulation in the bridle. A scheme based on cascaded current major loops is described and shown to provide a substantial improvement in low-speed regulation. An additional benefit is that higher speed-loop bandwidths are made possible by the de-coupling effect provided by the cascaded current major loop.
"Going for Gold": Print and Digital Media Reports of Performance Expectations for Olympic and Paralympic Athletes

Abstract:The purpose of this study was to understand how performance expectations conveyed within print and digital media are reported at specific time points (i.e., before, during, and after a major sporting event). A total of 9,236 media reports were analyzed using inductive content analysis, each of which made reference to one of eight Great British athletes (Mage = 23.00, SD = 2.67 years) who competed at the London 2012 Olympic (n = 4) or Paralympic (n = 4) Games. The results highlight that the media regularly reported content associated with performance expectations of high-performance athletes before, during, and after the London 2012 Games. The formation of these expectations appears to be an evolving process that is subject to change dependent on athletes' previous performances. Factors that were highlighted by the media as influential in athletes meeting performance expectations included the athlete's ability to cope with pressure and the home advantage. The media's response to the athletes' performances appeared to differ according to whether or not the athlete had achieved the initial expectation. The findings also suggested that expectations were related to the athlete's support staff (e.g., coaches) as well as to the athletes. These results indicate that performance expectations of athletes are a key focus of media reports ahead of a major competition and that these expectations are likely to influence the content presented within the media reports. The results also demonstrate the importance of performance expectations to key stakeholders (e.g., coaches, sports psychologists, athletes) within high-performance sport.
Effects of Corporate Diversification on Productivity

Using plant-level observations from the Longitudinal Research Database I show that conglomerates are more productive than stand-alone firms at a given point in time. Dynamically, however, firms that diversify experience a net reduction in productivity. While the acquired plants increase productivity, incumbent plants suffer. Moreover, stock prices track firm productivity and this tracking is equally strong for diversified and stand-alone firms. Therefore, lower transparency of conglomerates is unlikely to explain the discrepancy between productivity and stock prices on average. Finally, I offer some evidence that this discrepancy may arise because conglomerates dissipate rents in the form of higher wages.
Visual Discovery of Communication Patterns in Email Networks

In the age of social networks, it is very popular to analyze Twitter and Facebook to detect relationships and communities and to discover how information flows between groups. However, both Facebook and Twitter are examples of “performed” social networks: because a user has full control over who he or she “friends” or “follows,” he can artificially create a persona that he wishes the outside world to perceive him as. In fact, it has been well-studied that expressions of taste typically exclude the most critical groups to communication flows, and that social networks are merely the expressions of performed taste [9].
Comparative clinical implications of admission electrocardiographic findings for patients with non-ST-segment elevation myocardial infarction

Abstract Early risk stratification is crucial for appropriate management using invasive strategies in non-ST elevation myocardial infarction (NSTEMI), and electrocardiography (ECG) has been widely used for risk stratification. However, ECG findings in NSTEMI vary, and there is a need to define the clinical characteristics and outcomes according to ECG. We analyzed the admission ECGs of 345 NSTEMI patients who underwent coronary angiography from 2006 to 2013. Demographics, procedural characteristics, and clinical outcomes were analyzed. The ST-segment depression, T-wave inversion, and no ECG change groups included 114, 90, and 141 patients, respectively. The ST-segment depression group trended toward older, nonsmoking, and female, with a lower body mass index (BMI) and a higher incidence of comorbidities, than the no ECG change group. The ST-segment depression group also had a higher Killip class, a lower left ventricular ejection fraction, a higher regional wall motion score index (RWMSI), and 3-vessel coronary artery disease angiographically, than the no ECG change group. Patients with T-wave inversion trended toward older, female, lower BMI, less smoking, lower creatine kinase MB, and more left anterior descending (LAD) artery involvement, than the no ECG change group. In clinical outcomes, the ST-segment depression group had a higher mortality rate at 30 days and 12 months after the index procedure than the no ECG change group, whereas the T-wave inversion group showed similar clinical outcomes. Patients with ST-segment depression have a greater burden of comorbidities with risk factors and worse clinical outcomes, whereas patients with T-wave inversion have an intermediate number of risk factors but similar outcomes, compared with the no ECG change group. Further study is necessary to evaluate the prognostic impact of the baseline ECG on admission.