Miracle-dz/UniFAR-FTUs huggingface dataset:
Digital Breast Tomosynthesis: Technique and Cases

Mammography has been the primary screening test for early breast cancer for more than five decades, but conventional mammography imaging continues to have limitations in sensitivity and specificity. Digital mammography detects some cases of cancer that are not identified by film mammography, but overall detection is similar for many women. Digital breast tomosynthesis offers the potential to overcome one of the primary limitations of mammography, which is the inability to image overlapping dense normal breast tissue. Clinical data suggest that digital mammography with tomosynthesis produces a better image, improved accuracy, and lower recall rates compared with digital mammography alone. Further study will be necessary to confirm whether digital mammography with tomosynthesis is a cost-effective approach, capable of replacing digital mammography alone as the first-line screening modality of choice for breast cancer screening. Mammography has been the primary screening test for early breast cancer for more than five decades. Advances in mammography and treatment of breast cancer have contributed to a 30% reduction in breast cancer mortality since 1990 (1). However, conventional mammography imaging used for screening continues to have limitations, with a sensitivity of 77–95% and a specificity of 94–97% (2). Alternative breast imaging modalities have been developed in an effort to improve the sensitivity and specificity of breast cancer screening. These modalities include digital mammography, ultrasonography, magnetic resonance imaging (MRI), and three-dimensional digital breast tomosynthesis. Ideally, any new screening modality would decrease recall rates, reduce the number of breast biopsies for benign lesions, and improve cancer detection. A primary three-dimensional modality used for breast cancer screening is MRI. Studies that use MRI for breast cancer screening indicate greater sensitivity but less specificity than mammography for detection of breast cancer in high-risk women (3). The American Cancer Society recommends annual screening using MRI in addition to mammography beginning at age 30 years for women at high risk of breast cancer (greater than 20–25% lifetime risk). High-risk status is based on the woman having a BRCA1 or BRCA2 mutation, a strong family history of breast cancer or ovarian cancer, or prior chest radiation therapy (4). Digital mammography detects some cases of cancer that are not identified by film mammography, but overall detection is similar for many women. technology assessment in obstetrics and gynecology This Technology Assessment was developed by the Committee on Gynecologic Practice. This document reflects emerging clinical and scientific advances as of the date issued and is subject to change. The information should not be construed as dictating an exclusive course of treatment or procedure to be followed. Number 9, JuNe 2013
Symmetrical and asymmetrical liquid crystal dimers: synthesis, characterisation and mesomorphic behaviour

ABSTRACT A series of new asymmetrical liquid crystal dimers, RnO–S2O–ORn (n = 2–10), linked by an ethylene spacer having carbothiol – COS – and carboxyl – COO – linkages to the core centre of the molecule and bearing different lengths of terminal alkoxy chains were synthesised in order to study the effects of the length of the terminal alkoxy chains on mesomorphic properties. As well as, five symmetrical and asymmetrical dimers linked by butylene spacers bearing different linkages to the core and various terminal chains were also synthesized in order to study the effect of the nature of the spacer and terminal groups. The structures of the synthesised dimers were confirmed by physico-chemical techniques, i.e. FTIR, NMR and mass spectra. Differential scanning calorimetry and polarising optical microscopy verified the liquid crystal behaviour transition temperatures. The isotropic transition temperatures of the dimers RnO–S2O–ORn (n = 2–10) decreased with increasing length of alkoxy chain. Structural effects on the mesomorphic and physical properties were investigated in terms of alteration of carboxylate and thioester groups linking the spacer. The mesomorphic investigation reveals that all the dimers formed an enantiotropic Nematic phase except for dimer HO2SH which is not a liquid crystal. Graphical abstract
Implementation and Evaluation of Image Sequence Based Place Recognition Utilizing a Humanoid Robot

In the domain of image based localization, alternatives to image feature based algorithms have been developed making use of similarity metrics that operate directly on pixel intensity values. These approaches can work robustly and efficiently in cases when the recognition process needs to deal for example with varying lighting conditions or changes in scenery detail. In addition to employing such a pixel based similarity metric a recent algorithm called OpenSeqSLAM processes image sequences instead of single images to improve the recognition. However OpenSeqSLAM is not robust in cases of perspective change. This makes it problematic to use in many robotic applications when the camera perspective is not fixed to certain positions with fixed orientations. In this contribution an approach is developed and evaluated that aims to mitigate the effect of perspective change on recognition performance by combining the concept of OpenSeqSLAM with an alternative similarity metric called tangent distance. It was further analyzed if the algorithm can be suitably designed to run on a humanoid robotic platform and how it can utilize the robots capabilities. To enable evaluation a test application called DreamViewer for image sequence based localization algorithms has been developed. In result of the first tests an adapted and heuristic version of the algorithm was developed and evaluated as well. This algorithm aims to run on hardware performance constraint robotic embedded systems. Developed algorithms were tested offline with recorded image data as well as online on a humanoid robot platform called Myon. Results indicated that the developed algorithms using tangent distance can perform superior in terms of recognition performance compared to the standard OpenSeqSLAM algorithm in the tested cases of perspective change.
The New Handbook Of Cognitive Therapy Techniques

the new handbook of cognitive therapy techniques is available in our book collection an online access to it is set as public so you can get it instantly. Our books collection saves in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the the new handbook of cognitive therapy techniques is universally compatible with any devices to read.
Moving object detection and tracking in video surveillance

For the stationary scene,a block based background reconstruction algorithm is presented which can overcome fuzzy shortcoming by mean method.Then the background-subtraction method is used to detect the moving objects.After that the morphological process is adopted to fill the holes in moving objects,wipe out the noise spots and improve the detection.In order to fit to the background changet,he adaptive background updating is used.To improve the accuracy of trackingt,he modified Meanshift algorithm is carried out.Simulations show that this algorithm can detect objects effectively and track the objects rapidly and accurately.
Integrating of Grapheme-Based and Phoneme-Based Transliteration Unit Alignment Method

In order to solve the errors caused by only using the pheneme-based method or the grapheme-based method, applying the theory of statistics and rules, this paper proposes a new method for transliteration unit alignment which integrates the two main transliteration methods. Four experiments are designed to compare with the traditional methods. Experimental results show that proposed method outperforms other methods in terms of performance in machine transliteration.
Building an Information Extraction and Question Answering Model for Text Based on the Human Brain Process

An information extraction and question answering model for text, which is based loosely on the human brain process, is showcased in this paper. The ideology used is based on how humans perceive and interact with text, and the process of storing the text for future reference. Each word of each sentence is cross referenced and linked with all available information and the answer is given based on matching information found. The model is basic, but the future applications and scope of improvement is also shown.
Predictive Analysis of Message Passing Applications

Message passing (MP) has gained a widespread adoption over the years, so much so, that even heterogeneous embedded multicore systems are running programs that are developed using message passing libraries. Such a phenomenon is a shift in computing practices, since, traditionally MP programs have been developed specifically for high performance computing. With growing importance and the complexity of MP programs in today’s times, it becomes absolutely imperative to have formal tools and sound methodologies that can help reason about the correctness of the program. It has been demonstrated by many researchers in the area of concurrent program verification that a suitable strategy to verify programs which heavily rely on non-determinism, is dynamic verification. Dynamic verification integrates the best features of testing and model-checking. In the area of MP program verification, however, there have been only a handful of dynamic verifiers. These dynamic verifiers, despite their strengths, suffer from the explosion in execution scenarios. All existing dynamic verifiers, to our knowledge, exhaustively explore the non-deterministic choices in an MP program. It is apparent that an MP program with many non-deterministic constructs will quickly inundate such tools. This dissertation focuses on the problem of containing the exponential space of execution scenarios (or interleavings) while providing a soundness and completeness guarantee over safety properties of MP programs (specifically deadlocks). We present a predictive verification methodology and an associated framework, called MAAPED(Messaging Application Analysis with Predictive Error Discovery), that operates in polynomial time over MP programs to detect deadlocks among other safety property violations. In brief, we collect a single execution trace of an MP program and without re-running other execution schedules, reliably construct the artifacts necessary to predict any mis-happening in an un-explored execution schedule with the afore-mentioned formal guarantee. The main contributions of the thesis are the following: • The Functionally Irrelevant Barrier Algorithm to increase program productivity and ease in verification complexity. • A sound pragmatic strategy to reduce the interleaving space of existing dynamic verifiers which is complete only for a certain class of MPI programs. • A generalized Matches-Before ordering for MP programs. • A predictive polynomial time verification framework as an alternate solution in the dynamic MP verification landscape. • A soundness and completeness proof for the predictive framework’s deadlock detection strategy for many formally characterized classes of MP programs. In the process of developing solutions that are mentioned above, we also collected important experiences relating to the development of dynamic verification schedulers. We present those experiences as a minor contribution of this thesis.
Research on the data link layer secure protocol of TES network based on ECC

A workable and efficient data link layer security protocol had been proposed on the need of safety information transfer requirements of the TES system.The protocol provides a software registration solution for the remote sites and a information encryption method base on the elliptic curves cryptography(ECC) algorithm as well as a combined key allocation method.The protocol takes the characters of the TES system into account,improves its ability to identify remote sites,and provides ways to prevent information stealing and network attacks.
AUDA as a modulator of lipid profile and endothelial function in diet induced hypercholesterolemia in rats

Background: Epoxyeicosatrienoic acids (EETs) are cytochrome P450 metabolites of arachidonic acid produced by the vascular endothelium and act as important regulators of vascular tone. Objectives: to study the effect of soluble epoxide hydrolase inhibition AUDA on endothelial function in hypercholesterolemic rats. Methods: Hypercholesterolemia was induced by using Matos diet for 8 weeks and it significantly increased TC, TG, and LDL-C and decreased HDL-C. AUDA, was used with a dose of 0.35 mg/ kg for 10 weeks via gastric gavage every other day. Results: AUDA treated group has significantly lower total-C, TG, LDL-C and higher HDL-C as compared to untreated group. AUDA also improved vascular reactivity and vasodilatory response to different doses of Acetyl choline. Histopathological examination of aortic rings showed reduced development of atherosclerotic changes in the vascular wall with no effect on e-NOS expression in vascular endothelial cells. Conclusions: We can conclude that AUDA treatment has improved lipid profile and protect against development of atherosclerotic histopathological changes.
Research on rough-fuzzy set theorybased decision support approach of component adaptation

In current real software reuse,system developers understand and adapt components subjectively.And adaptation schema selected by developers' understanding ability and reuse experiences,without scientific and objective basis,thereby it increases system developers' tension and affects the efficiency of component reuse.In this paper we improved on traditional component library architecture to propose a hierarchical component library architecture firstly.And then,we proposed a rough-fuzzy set theory-based decision support approach of component adaptation.What's more,we gave the approach's algorithm.The case study shows that this approach can support objective component adaptation decision、 decreasing the cost to understand and adapt components and improve the efficiency and correctness of component reuse.
Cloud Computing in Computer Science and Engineering Education

Cloud Computing opens a new chapter in Information Technology. It has its roots in internet technology, and like the Internet, it is rapidly and forcefully advancing into a large range of applications and services. While standardization of Cloud Computing is ongoing, there is every indication that cloud technology is here to stay and will cover most sectors of society, including education. This paper discusses the potentials of Cloud-Based Education (CBE) in STEM areas to better stimulate and engage students in their pursuit of knowledge and learning. This paper introduces the concept of Cloud-Based Education for Computer Science (CBE-CS) and discusses how its framework can be achieved. Further, it shows how the platform can be generalized to use in various STEM areas. The authors argue that the potentials in using Cloud Computing for teaching Computer Science courses are extraordinary since CS has an intimate relationship with the cloud infrastructure. Thus, CBE-CS can greatly facilitate teaching complex underlying organizations of CS courses such as Operating Systems, Communication Networks, Cyberspace Security, Web-Based Applications, Database, and High Performance Computing. While other STEM education can extensively benefit from CBE at the Software as a Service (SaaS) level to present meaningful examples in the lectures, CS courses can move deeper and also utilize the lower levels of cloud services. Such capability can deliver valuable examples and laboratories for CS students to better understand large scale applications and their complexities.
Monitoring Our Online Representations -Avatars, the Digital Mirror

Avatars are graphical online images that individuals create to represent themselves in virtual social interactions. Research suggests that individuals differentially monitor their offline self-presentations (Snyder, 1974, 1979), with some using external cues to create self-presentations (high self-monitors) and others integrating their own internal aspects (low self-monitors). This study was designed to test these concepts with avatars as the new self-presentation form. How does self-monitoring impact one’s online selfpresentation? Findings suggest that individuals did not differ their types of portrayal, demographics, or presentation characteristics of their avatars across situations by selfmonitoring dimensions. For the most part, there were few findings related specifically to the monitoring dimensions: self-presentation, sensitivity to expressive behaviors, otherdirectedness and social comparison.
A new Weighted Naive Bayesian Classification Algorithm

Naive Bayes algorithm is a simple and efficient classification algorithm,but its conditional independence assumption is not always true in real life which is affected to some extent.Weighted Naive Bayesian classifier relaxes the conditional independence assumptions to increase accuracy.Based on Identifiability matrix of Rough Set,a new weighted naive Bayes method based on attribute frequency is proposed.Different condition attributes are weighted differently,the Naive Bayesian classification algorithm performance is improved effectively.Experiments have proved that the calculation of this algorithm is easier and more effective.
Aggregation of the bacteriochlorophylls c, d, and e. Models for the antenna chlorophylls of green and brown photosynthetic bacteria

Aggregates of bacteriochlorophylls c, d, and e and of zinc(II) methyl bacteriopheophorbides c and d, which exhibit large red shifts in hexane without the essential intervention of any carbonyl function on ring V are described. The aggregates appear to provide viable in vitro models for the antenna chlorophylls of green and brown photosynthetic bacteria and a rationale for the presence of the 2-(1-hydroxyethyl) group in bacteriochlorophylls c, d, and e.
The Relations between Cadmium, Zinc and Oxidative stress in Oligoasthenozoospermic Men

Background: Cadmium (Cd) has been found to accumulate in male reproductive organs and induce male reproductive toxicity in several animal species. Objective: To study the levels of Cadmium and Zinc in blood and seminal plasma of oligoathenozoospermic men and to investigate their possible role and their relation to oxidative stress in pathophysiology of oligoathenozoospermia. Study Design: Blood and seminal plasma were collected from thirty primary infertile males with oligoasthenozoospermic, and 30 control subjects. Cadmium (Cd), zinc (Zn), malondialdehyde (MDA) and superoxide dismutase (SOD) activity were estimated in all samples. Results: The serum and seminal concentrations of Cd and MDA of oligpasthenozoospermic group were significantly higher than those of control groups. Levels of blood and seminal plasma of Zn and SOD activity of infertile men were significantly lower than those of control group. The seminal plasma levels of Cd of oligoathenozoospermic group were correlated positively and significantly with MDA levels in seminal plasma. However, there were significant negative correlations between seminal plasma levels of Cd and seminal levels of Zn and seminal SOD activity ,sperm count and sperm motility . There were inverse correlations between seminal plasma levels of MDA and SOD activity, sperm count and sperm motility in oligoathenozoospermic group. The results also shows that there was a positive and significant correlation between the seminal SOD activity and sperm motility in infertile men. Seminal plasma levels of Zinc were negatively and significantly correlated with sperm motility of oligoathenozoospermic group. Conclusion: Cadmium may have adverse impacts on semen quality and male reproductive health. The pathophysiological mechanism of high Cadmium levels in oligoathenozoospermic men is probably through induction of oxidative stress. Lowered levels of zinc may contribute to infertility through its significant effects on semen motility. There is competitive mechanism of interaction between Zn in relation to Cd in oligoathenozoospermic men
Risk Assessment of Information Security Based on Mutual Information and K-means

This paper proposes a new information security risk assessment method based on mutual information calculation and K-means clustering algorithm in order,to solve the problems of small training data and to find optimal value.Fuzzy evaluation is applied to quantify risk factors,calculating the mutual information value of risk factors to indicate the dependent degree of risk factors and risk degree.The data are classified by K-means with the optimal mutual information data as the initial centers.This method is less computation,and also can overcome the K-means's shortcoming sensitive to initial value and solve problems of optimal value and conclusion blurring defects.Experimental results show the effectiveness of the method.
Identificación de aplicaciones de red mediante técnicas de aprendizaje automático Network Application Identification based on Machine Learning Techniques

El presente articulo describe un nuevo metodo de identificacion de aplicaciones de red basado en tecnicas de aprendizaje automatico. Este metodo pretende solucionar las limitaciones de precision de las tecnicas tradicionales que utilizan los numeros de puerto y los problemas de rendimiento que presentan los algoritmos basados en el reconocimiento de patrones. Este metodo ha sido evaluado experimentalmente en la Anella Cientifica, obteniendo un porcentaje de identificacion superior al 95%. Palabras clave: identificacion de aplicaciones, clasificacion de trafico, monitorizacion pasiva. Summary This paper describes a novel method for network application identification using machine learning techniques. This method tries to solve the accuracy limitations of traditional port-based techniques and performance issues of previous payload-based algorithms. This method has been experimentally evaluated in the Scientific Ring network, obtaining an identification accuracy greater than 95%.
Face and Eye Recognition on Gray Image using DWT with RBFSVM Method

Facial part detection or extraction shows the most important role in face and eye recognition. In this article proposed a new algorithm for Face and Eye Recognition (FER) using radial basis function support vector machine (RBFSVM) classifier. The discrete wavelet transform (DWT) is used for feature extraction and selection. For the experimental results, used JAFFE and ORL database. In this algorithm, extract face component like left eye, right eye, mouth and nose. In the preprocessing stage, apply median filtering for removing noise from an image. This stage improves the feature extraction process. Finding an image from the image components is a typical task in pattern recognition. The detection rate has reached up to100% for eye recognition and for face recognition is 90-96%. The proposed system estimates the value of precision and recall. This algorithm is compared with SVM and our proposed proved better than previous algorithms.