Miracle-dz/UniFAR-FTUs huggingface dataset:
Image Task Detection of Microcalcification on Mammogram

2 Abstract: Texture analysis has been very much used in medical image problems as well as related areas such as computer vision and pattern recognition. Among all medical image task detection of microcalcification on mammograms is the most difficult one because breast cancer is the most prevalent cancer that leads to death in women today. More over microcalcification are deposits of calcium that can be seen in mammograms, which is the best way to detect breast cancer in the earliest stage and also to reduce death from breast cancer. Owing to the small size of micro calcification with a diameter of less than 0.5 mm level and are in the form of groups as clusters and in homogeneous back ground it is very difficult to detect. In this paper, we propose to develop a supervised texture mammography technique for image classification that includes supervised and unsupervised methods. In the unsupervised method for the detection of microcalcification, the prior information is required and in the case of supervised method information on microcalcification is very much needed for the processing. Previously many methods have been developed for the detection of microcalcification on mammogram. This paper analyses the texture analysis of mammography images using supervised and unsupervised classification methods and the results identifies that the unsupervised method has high accuracy than the supervised methods.
Time-frequency representations for nonlinear frequency scales — Coorbit spaces and discretization

The fixed time-frequency resolution of the short-time Fourier transform has often been considered a major drawback. In this contribution we review recent results on a class of time-frequency transforms that adapt to a large class of frequency scales in the same sense that wavelet transforms are adapted to a logarithmic scale. In particular, we show that each transform in this class of warped time-frequency representations is a tight continuous frame satisfying orthogonality relations similar to Moyal's formula. Moreover, they satisfy the prerequisites of generalized coorbit theory, giving rise to coorbit spaces and associated discrete representations, i.e. atomic decompositions and Banach frames.
Gamma-ray emission from Cassiopeia A produced by accelerated cosmic rays

The nonlinear kinetic model of cosmic ray (CR) acceleration in supernova remnants (SNRs) is used to describe the relevant properties of Cassiopeia A (Cas A). In order to reproduce the SNR's observed size, expansion rate and thermal X-ray emission we employ a piecewise homogeneous model for the progenitor's circumstellar medium developed by Borkowski et al. (1996). It consists of a tenuous inner wind bubble, a dense shell of swept-up red supergiant wind material, and a subsequent red supergiant wind region. A quite large SNR interior magnetic field Bd 1 mG is required to give a good fit for the radio and X-ray synchrotron emission. The steep radio spectrum is consistent with ecient proton acceleration which produces a significant shock modification and leads to a steep electron spectrum at energies e < 1 GeV. The calculated integral-ray flux from Cas A, F / 1 , is dominated by 0 -decay-rays due to relativistic protons. It extends up to roughly 30 TeV if CR diusion is as strong as the Bohm limit. At TeV energies it satisfactorily agrees with the value 5:8 10 13 cm 2 s 1 detected
1 cs 260 r Project Proposal

A. Motivation Concurrency bugs are one of the hardest to detect and most prevalent in software systems today (20% of driver bugs examined in a previous study [10] are concurrency bugs). They are pernicious to the extent that they have caused real world disasters such as the 2003 Northeast blackout [9]. And today with the ubiquity multicore machines, this becomes an ever more pressing problem. While reliability and debugging has made significant steps in sequential software [4], [2], and some have even shown steps to put scheduling in user control [6], the prospect for bug free concurrent code still remains bleak. The complexity lies in part in the idea of interleavings. Interleavings are not only complicated to reason about heuristically, but also impossible to reason about holistically because of the dramatic increase in the state space. In general, one can devide the research into concurrency bug detection in two categories: symptom based detection, and invariant based detection. [1] Current symptom based techniques to address this problem have relied on overarching structural patterns of interleavings and zoomed in on the ones most probable to cause problems. The patterns include race conditions [5], atomicity violations [7], and context-switch bounded interleavings [3]. While these techniques do exist, they leave us with substantial problems, most important of which are: False Negative and Positives. [11] Current invariant based approaches have their own strengths and weaknesses. Proposals like AVIO [7] detect atomicity violation bugs, and find interleaving in supposedly atomic instructions. Recently, works like Vulcan [8] focus on detecting sequential consistency violations, and the idea that some memory operations get preformed in a simply unintuitive manor. It then flags these violations and presents invariants. Existing invariant based proposals generally work by collecting a large number of execution traces by using various test inputs either written before by the developers or explicitly for the trace. Then they analyze the traces and extract the required invariants. For this reason they suffer from four problems. First, they cannot test all the possible thread interleavings, thus miss invariants and contain false negatives. Second, the proposals replicate the production run environment, thus a lack of diversity of tests. Third, as the program is extended, many of the invariants become invalid, and if run again, they loose information from the previous runs that had not been invalidated. And fourth, they cannot check the correctness of an invariant if it is not found …
From 'playstations' to 'workstations': youth preferences for unionisation in Canada

Differences in preferences for unions between youths and adults in Canada are analysed based on a survey of approximately 1500 persons. The results indicate that the preferences of youth for unionisation are strongly influenced by social factors such as familial union status and the attitudes of close peers. Preferences for unionisation are also shaped by the perceived costs and benefits of unionisation to deal with a wide range of workplace issues such as merit pay, voice, fair treatment, opportunities for advancement, layoffs, seniority, and a lack of progressive HRM and legislative protection at the workplace. The different preferences of youths and adults are generally consistent with the divergent effects that unions would have on youths and adults with respect to these issues. Youths have a stronger preference than do adults for unions in general. Most of that stronger preference reflects the stronger desire of youths to have unions deal with workplace issues, than it reflects the exposure of youths to these issues. The fact that preferences of youths for unionisation are strongly shaped by social capital factors such as union membership in the family and the attitudes of family and friends towards unions, highlights the cumulative and inter-generational effects that are involved in the unionisation process. Possible substitutes for unionisation such as progressive HRM practices and legislative protection exert a powerful negative effect on preferences for unionisation, especially for youths. The implications of these and other findings for the future of unionisation are also discussed.
Quadrature Rules Needed in Galerkin-wavelets Methods*

In this article we will review several numerical quadrature rules, their theoretical background and implementations, that are needed in a discretization of Galerkin type for diierential equations, using wavelets as basis functions. Material given here will be a summary of results of the recent three years by several groups of researchers in this eld, including the author himself.
Nitrogen metabolism and remobilization during senescence.

Senescence is a highly organized and well-regulated process. As much as 75% of total cellular nitrogen may be located in mesophyll chloroplasts of C(3)-plants. Proteolysis of chloroplast proteins begins in an early phase of senescence and the liberated amino acids can be exported to growing parts of the plant (e.g. maturing fruits). Rubisco and other stromal enzymes can be degraded in isolated chloroplasts, implying the involvement of plastidial peptide hydrolases. Whether or not ATP is required and if stromal proteins are modified (e.g. by reactive oxygen species) prior to their degradation are questions still under debate. Several proteins, in particular cysteine proteases, have been demonstrated to be specifically expressed during senescence. Their contribution to the general degradation of chloroplast proteins is unclear. The accumulation in intact cells of peptide fragments and inhibitor studies suggest that multiple degradation pathways may exist for stromal proteins and that vacuolar endopeptidases might also be involved under certain conditions. The breakdown of chlorophyll-binding proteins associated with the thylakoid membrane is less well investigated. The degradation of these proteins requires the simultaneous catabolism of chlorophylls. The breakdown of chlorophylls has been elucidated during the last decade. Interestingly, nitrogen present in chlorophyll is not exported from senescencing leaves, but remains within the cells in the form of linear tetrapyrrolic catabolites that accumulate in the vacuole. The degradation pathways for chlorophylls and chloroplast proteins are partially interconnected.
Processing of polarimetric infrared images for landmine detection

Infrared (IR) cameras are often used in a vehicle-based multi-sensor platform for landmine detection. Additional to thermal contrasts, an IR polarimetric sensor also measures surface properties and therefore has the potential of increased detection performance. We have developed a polarimetric IR setup, which has to be used in a forward-looking manner. This paper describes all the steps to reach detection performance. The first step is the acquisition of the polarimetric IR image data. The next step is the pre-processing to (re)construct polarimetric images. A subsequent segmentation step is made to identify objects. Features, like intensity, reflectivity and shape, of these objects are measured. For independent performance analyses, the data set is divided into a training and evaluation section. A classifier is trained on the training section and evaluated on the classification section. The detection performance of the forward-looking IR camera is shown in receiver operator characteristics (ROC) curves.
A Better Update Policy

Some file systems can delay writing modified data to disk, in order to reduce disk traffic and overhead. Prudence dictates that such delays be bounded, in case the system crashes. We refer to an algorithm used to decide when to write delayed data back to disk as an update policy. Traditional UNIX® systems use a periodic update policy, writing back all delayed-write data once every 30 seconds. Periodic update is easy to implement but performs quite badly in some cases. This paper describes an approximate implementation of an interval periodic update policy, in which each individual delayed-write block is written when its age reaches a threshold. Interval periodic update adds little code to the kernel and can perform much better than periodic update. In particular, interval periodic update can avoid the huge variances in read response time caused by using periodic update with a large buffer cache.
Mast Cells Mobilize Myeloid-Derived Suppressor Cells and Treg Cells in Tumor Microenvironment via IL-17 Pathway in Murine Hepatocarcinoma Model

Tumor immunosuppression is commonly braided with chronic inflammation during tumor development. However, the relationship between immunosuppression and inflammation in tumor microenvironment is still unclear. We have demonstrated that mast cells are accumulated and exacerbate the inflammation and immunosuppression in tumor microenvironment via SCF/c-kit signaling pathway. Here, we further elucidate the underlying mechanism, which involves both myeloid-derived suppressor cells (MDSCs) and regulatory T (Treg) cells. Our data showed that mast cells mobilized the infiltration of MDSCs to tumor and induced the production of IL-17 by MDSCs; MDSCs-derived IL-17 indirectly attracted Treg cells, enhanced their suppressor function, and induced the IL-9 production by Treg cells; in turn, IL-9 strengthened the survival and protumor effect of mast cells in tumor microenvironment. Our findings disclose a closed loop among mast cells, MDSCs and Treg cells in tumor microenvironment, which provides a new insight into the paralleled developments of inflammation and immunosuppression in tumor microenvironment. Based on these findings, we propose that targeting tumor inflammation might be a potential strategy to reverse the immunosuppression of tumor microenvironment, thus facilitating cancer immunotherapy.
The relations between maternal mind-mindedness, parenting stress and obstetric history among Chinese mothers

ABSTRACT Relations between maternal mind-mindedness, parenting stress and obstetric history were investigated in a Chinese sample of 96 mother-infant dyads (Minfants' age = 15.95 months, Mmaternal age = 30 years). Parenting stress and obstetric history were assessed through questionnaires while mind-mindedness was observed through video recordings of mother-infant interactions. Among mothers who perceived their pregnancy to have been difficult, those who had planned to conceive were more likely to comment appropriately on their infants' mental states. Mothers who displayed a highly emotional reaction of an exclusively positive nature when their babies were first given to them experienced lower total parenting stress scores. Mothers who were more mind-mindedness experienced lower parenting stress. Main carer status and daily time spent with child were related to parenting stress. Results are discussed in relation to socio-cultural factors that might shape antenatal perceptions and influence parenting stress which in turn affect mothers' relationships with their children.
Detecting optic disk based on AdaBoost and active geometric shape model

Detecting the optic disk (OD) is very important in the fundus image analysis. In this paper, we propose a new OD detection algorithm consisting of four main steps: first, obtaining the sub-image which includes the OD from the fundus image based on the saliency map; second, generating the super-pixel from the sub-image with a simple linear iterative clustering (SLIC) algorithm; third, classifying the super-pixel into OD or non-OD based on the AdaBoost algorithm; fourth, fitting the detected OD region with a circle based on the active geometric shape model. The proposed method has been evaluated on the Digital Retinal Images for Optic Nerve Segmentation (DRIONS) database. Experimental results show that our algorithm is very competitive with the state-of-the-art method.
Understanding Data Completeness in Network Monitoring Systems

In many networks including Internet Service Providers, transportation monitoring systems and the electric grid, measurements from a set of objects are continuously taken over time and used for important decisions such as provisioning and pricing. It is therefore vital to understand the completeness and reliability of such data. Given the large volume of data generated by these systems, rather than enumerating the times and objects incurring missing or spurious data, it is more effective to provide patterns (groups of tuples) concisely summarizing trends that may not otherwise be readily observable. In this paper, we define the Graph Tableau Discovery Problem where the measured tuples can be thought of as edges in a bipartite graph on an ordered attribute (time) and an unordered attribute (object identifiers). We define the problem of finding an optimal summary, show that it is NP-complete, and then provide a polynomial-time approximation algorithm with guarantees to find a good summary. Experiments on real and synthetic data demonstrate the effectiveness and efficiency of our approach.
Spatial numerical associations in preschoolers

ABSTRACT Three-to-five-year-old French children were asked to add or remove objects to or from linear displays. The hypothesis of a universal tendency to represent increasing number magnitudes from left to right led to predict a majority of manipulations at the right end of the rows, whatever children's hand laterality. Conversely, if numbers are not inherently associated with space, children were expected to favour laterality-consistent manipulations. The results showed a strong tendency to operate on the right end of the rows in right-handers, but no preference in left-handers. These findings suggest that the task elicited a left-to-right oriented representation of magnitudes that counteracted laterality-related responses in left-handed children. The young age of children and the lack of a developmental trend towards right preference weaken the hypothesis of a cultural origin of this oriented representation. The possibility that our results are due to weaker brain lateralisation in left-handers compared to right-handers is addressed in Discussion section.
Childbearing, breastfeeding, other reproductive factors and the subsequent risk of hospitalization for gallbladder disease.

BACKGROUND While parous women are known to be at an increased risk of gallbladder disease, little is known about the effects of other reproductive factors such as breastfeeding, age at menarche and age at menopause. METHODS The Million Women Study is a prospective cohort study of 1.3 million middle-aged women in England and Scotland recruited from 1996 to 2001. Participants were followed-up by record-linkage for a mean of 6.1 years for admissions to hospital. The adjusted relative risk of hospital admission for cholelithiasis, cholecystitis or cholecystectomy according to parity, breastfeeding, age at menarche and age at menopause was examined. RESULTS During follow-up of 1 289 029 eligible women, 25 111 were admitted to hospital for gallbladder disease, of whom 21 735 (87%) had a cholecystectomy. The hospital admission rate over 5 years for gallbladder disease was 1.6/100 women and for cholecystectomy was 1.4/100 women. The adjusted relative risk of gallbladder disease increased with increasing parity by 8% (95% CI 7-9%, P < 0.0001) for each birth. Among women of a given parity, breastfeeding reduced the risk of gallbladder disease, the relative risk decreasing by 7% (95% CI 5-10%, P < 0.0001) per year of breastfeeding. Women's age of menarche and age at menopause did not alter the risk of gallbladder disease (P = 0.4 and P = 0.3, respectively for linear trend). CONCLUSION Hospitalization for gallbladder disease is common in middle-aged women. The risk increases the more children a woman has had, but decreases the longer she breastfeeds. The increased risk of gallbladder disease associated with having children can be offset by breastfeeding.
Mining fuzzy association rules with 2-tuple linguistic terms in stock market data by using genetic algorithm

An evolutionary approach for finding fuzzy association rule with 2-tuple linguistic representation model is presented in this work. We propose a method based on multi objective genetic algorithm for identifying fuzzy association rules without specifying minimum support and minimum confidence. In fact our algorithm extracts both association rules and membership function in one step. Also we use Iterative Rule Learning (IRL) process to try to cover those instances that were still uncovered. To evaluate the proposed algorithm we use the stock price dataset and compare our results with the fuzzy mining approach which uses uniform fuzzy partitioning to extract fuzzy association rule. Obtained results show that our technique outperforms the uniform fuzzy partitioning method.
L'orientation en CAP Métiers de l'automobile et Coiffure. Entre élaboration d'aspirations et conditions d'affectation

Cet article etudie les processus d’orientation post-troisieme a partir d’une enquete menee aupres de jeunes preparant un CAP coiffure ou metiers de l’automobile en lycee professionnel ou en CFA. Ces deux specialites ont en commun d’etre a la fois attractives et relativement selectives, accueillant des jeunes issus des fractions stabilisees des classes populaires. Mais elles se differencient par leur recrutement genre et par la structuration des diplomes. L’analyse tient ensemble les conditions d’elaboration des aspirations juveniles et les conditions d’affectation dans ces specialites et voies de formation. Si elles conduisent a la formulation de voeux d’orientation vers des specialites distinctes selon leur sex-ratio, les conditions d’elaboration des aspirations juveniles semblent proches, au regard des parcours scolaires, des conseils institutionnels et des soutiens parentaux dont les eleves de troisieme font l’objet. La comparaison des specialites et voies de formation fait apparaitre une distinction des criteres de selection en lycee professionnel et en CFA, ou les profils scolaires des candidats ont plus ou moins d’importance. Elle met aussi en evidence des formes de selection differenciees entre une specialite masculine proposant un baccalaureat, et une specialite feminine structuree autour d’une filiere CAP-BP (brevet professionnel).
Unambiguous Decoding of Generalized Reed–Solomon Codes Beyond Half the Minimum Distance

The Schmidt–Sidorenko–Bossert scheme extends a low-rate Reed–Solomon code to an Interleaved Reed–Solomon code and achieves the decoding radius of Sudan’s original list decoding algorithm while the decoding result remains unambiguous. We adapt this result to the case of Generalized Reed–Solomon codes and calculate the parameters of the corresponding Interleaved Generalized Reed–Solomon code. Furthermore, the failure probability is derived.
Challenges and Usage of Link Mining to Semantic Web 1

It is an emerging challenge for data mining is the problem of mining richly structures datasets, where the objects are linked in some way. Links among the objects may demonstrate certain patterns, which can be helpful for many data mining tasks and are usually hard to capture with traditional statistical models. Many datasets of interest today are best described as a linked collection of interrelated objects. These may represent homogeneous networks, in which there is a single-object type and link type (eg. people connected by friendship links, or the WWW, a collection of linked web pages) or richer, heterogeneous networks, in which there may be multiple object and link types (and possibly other semantic information). Examples of heterogeneous networks include those in medical domains describing patients, diseases, treatments and contacts, or in bibliographic domains describing publications, authors, and venues. Link mining refers to data mining techniques that explicitly consider these links when building predictive or descriptive models of the linked data. Commonly addressed link mining tasks include object ranking, group detection, collective classification, link prediction and subgraph discovery. This is an exciting and rapidly expanding area. In this article we review some of the common emerging themes and discuss ongoing link mining challenges; open issues and suggest ideas that could be opportunities for solutions. The most conclusion of this article is that providing an idea to usage link mining techniques from link mining to help to construct the Semantic Web.