Miracle-dz/UniFAR-FTUs huggingface dataset:
Compliance with pharmacological treatment among patients after minimally invasive coronary bypass grafting.

BACKGROUND We sought to evaluate patients' adherence to optimal pharmacotherapy as recommendedby the European Society of Cardiology, together with the assessment of potential clinical determinants of medical non-compliance in a large cohort of patients after endoscopic atraumatic coronary artery bypassing (EACAB). METHODS This cross sectional study was conducted in a group of 706 individuals who underwent EACAB between April 1998 and December 2010. Data covering current pharmacological treatment with antiplatelet agents, beta-blockers (BB) (or heart rate lowering calcium channel blockers [CCB] in case of intolerance and/or poor efficacy of beta-blockade), angiotensin-converting enzyme (ACE) inhibitors (or angiotensin receptor blockers [ARB]) and statins was acquired. Mean duration of observation after the surgery was 2132 ± 1313 days. RESULTS Complete follow-up data has been obtained from 415 living patients (341 males). Amongst them, 353 (85%) received antiplatelet agents, while BB or CCB were routinely ingested by 349 (84%) patients. Statins were used by 310 (74.7%) individuals and 274 (66%) subjects took ACE inhibitors or ARB. Baseline demographic and clinical features, including major co-morbidities had no impact on patients' compliance with all investigated medications. There was no clear association between adherence to treatment and risk of rehospitalization or occurrence of major cerebral and cardiovascular events. CONCLUSIONS EACAB patients' compliance with pharmacotherapy guidelines is insufficient and is unrelated to demographic and clinical features of the subjects. Multidisciplinary approach involving health education, enhancement in prescription drug affordability and a better rapport between doctors and patients should be incorporated into clinical practice to overcome therapeutic disobedience.
Multi-objective resource allocation in multiuser orthogonal frequency division multiplexing system

This study presents a new technique for resource allocation in multiuser orthogonal frequency division multiplexing systems. The goal is to maximise the minimum data rate available to any user while minimising the total transmitted power. The strength Pareto evolutionary algorithm (SPEA-2) is used to achieve this goal. The SPEA-2 algorithm solves the contradicting multiple objectives by evaluating individual's fitness value based on the number of external non-dominated individuals that dominate it and then searching the solution space to minimise this fitness value. Most of the existing multi-objective solutions, for the problem under consideration, have used binary coded chromosomes which restricted the number of users to be in power of two only. This limitation is overcome in the proposed scheme by using an integer coded chromosome. The population density information is also incorporated into the fitness function to refine the search. Simulation results indicate that the proposed algorithm achieves higher data rates as compared with previous algorithms. Furthermore, the proposed scheme allocates both subcarriers and bits jointly, without being computationally expensive. The faster convergence of the algorithm to near-optimal value, as compared with previous algorithms is indicative of its reduced complexity, which is attributed to the modification in the power objective.
Un partitionnement d'arêtes à base de blocs pour les algorithmes de marches aléatoires dans les grands graphes sociaux

RÉSUMÉ. Des résultats récents (Bourse et al., 2014; Gonzalez et al., 2012; Xin et al., 2013) montrent que le partitionnement des arêtes (vertex-cut) s’avère être plus efficace que le partitionnement des sommets (edge-cut) traditionnellement utilisé pour les calculs sur des graphes réels comme les graphes des réseaux sociaux. Compte tenu de la distribution de type « power-law » de la plupart des graphes, le partitionnement des arêtes (vertex-cut) permet d’éviter des calculs asymétriques. Par conséquent, plusieurs systèmes de calcul de graphe basés sur cette approche ont été proposés, tels que PowerGraph (GraphLab2) (Gonzalez et al., 2012) et GraphX (Xin et al., 2013). Leurs stratégies de partitionnement sont génériques et ne dépendent pas des algorithmes utilisés pour effectuer les différents calculs. Nous proposons dans cet article une nouvelle stratégie de partitionnement de graphe (de ses arêtes) optimisant l’exécution des algorithmes basés sur les marches aléatoires qui prennent en compte les propriétés topologiques des graphes. Notre stratégie est basée sur la construction de blocs qui modélisent des communautés locales. Notre approche de partitionnement en blocs fournit une distribution équilibrée des arêtes sur les noeuds de calcul et permet de la maintenir dynamiquement. Les coûts de communication pour les calculs utilisant des marches aléatoires sont réduits de manière significative par rapport aux approches existantes.
Soluble Fas (sFas) and soluble Fas ligand (sFas‐L) balance in laryngeal carcinoma before and after surgical treatment

Fas and its specific ligand (Fas‐L), both of which are involved in apoptosis, exist in membrane‐bound and soluble forms. The soluble forms (sFas and sFas‐L) have been observed in various tumours, but their clinical significance has not yet been clarified. The aim of this study was to assess serum sFas and sFas‐L levels in patients with laryngeal squamous cell carcinoma (LSCC) and their possible correlations with surgical treatment.
A program searching for a functional dependence using genetic programming with coefficient adjustment

When modeling many traffic problems, it is necessary to find the functional dependence of the output of two input variables. This task can be solved by a neural network, by using some spline interpolation or polynomials, etc. These approaches can produce a model, but its internal description is unreadable and its transfer to another program can be difficult. Therefore, a program to determine this functional dependence using genetic programming has been developed. The result is prepared in such a way that it can be transferred into a source code of another program, or copied to an MS Excel sheet. The program reads data available as triplets, [[x, y], z], and looks for their functional interdependencies by using a selected set of elementary functions and a vector of multiplicative constants. The input data do not have to meet any additional conditions. They can be defined on measured intervals, or even as individual points. For a successful outcome, the only condition is to have a sufficient amount of data. For some functions, the level of noise has to be determined in order to make the model complete. In this case, noise characteristics can be evaluated from the results of the program.
Fault Detection and Diagnosis of Nuclear Power Plant Using Deep Learning Architecture

Being a safety-critical system, safety is extremely important for any nuclear power plant (NPP). Therefore, to maintain the safety of NPPs at an acceptable level, preventive measures are necessary to deal with potential issues. During plant operation, faults and failures can occur in sensors, equipment, and processes which can have impact on the performance of the plant. These faults are more prominent in aged NPPs because of their vulnerability to aging-related faults [1]. Hence there is need to monitor the status of the plant during operation. To do this, fault detection and diagnosis (FDD) techniques are developed and used in NPPs. FDD is the process of detecting and identifying unexpected behavior in a system. One of these techniques is data-driven methods, which comprises of artificial neural network (ANN), multivariate state estimation technique (MSET), principal component analysis (PCA), and autoassociative kernel regression (AAKR) [2]. However, the possibility and applicability of the deep learning – the current trend in the field of machine learning, to FDD of NPPs is not yet explored. Therefore, this work seeks to propose and apply deep learning techniques to FDD of NPPs. Deep learning originated from artificial neural network, and it is a branch of machine learning algorithms that use a cascade of many layers of non-linear processing units for feature extraction and transformation. It based on a set of algorithms that attempt to model/learn high level abstractions and hierarchy representations in data. There are various deep learning architectures, which include Restricted Boltzmann Machine (RBM) based deep belief network (DBN), Convolutional Neural Network (CNN), deep Auto-encoders, and Recurrent Neural Network (RNN). Recently, deep learning has been successfully adopted in various areas such as computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics [3, 4], where they have been shown to produce state-of-the-art results on various tasks. To verify the applicability of the proposed deep learning model, we used the NPP simulation data for accident detection and identification. The verified model showed high performance applicability to FDD of NPPs.
Clinical Diagnosis and the Order of Information

Background. Information order can influence judgment. However, it remains unclear whether the order of clinical data affects physicians' interpretations of these data when they are engaged in familiar diagnostic tasks. Methods. Of 400 randomly selected family physicians who were given a questionnaire involving a brief written scenario about a young woman with acute dysuria, 315 (79%) returned usable responses. The physicians had been randomized into two groups, and both groups had received the same clinical information but in different orders. After learning the patient's chief com plaint, physicians received either the patient's history and physical examination results followed by the laboratory data (the H&P-first group) or the laboratory data followed by the history and physical examination results (the H&P-last group). The results of the history and physical examination were supportive of the diagnosis of UTI, while the laboratory data were not. All physicians judged the probability of a urinary tract infection (UTI) after each piece of information. Results. The two groups had similar mean estimates of the probability of a UTI after learning the chief complaint (67.4% vs 67.8%, p = 0.85). At the end of the scenario, the H&P-first group judged UTI to be less likely than did the H&P-last group (50.9% vs 59.1 %, p = 0.03) despite having identical information. Comparison of the mean likelihood ratios attributed to the clinical information showed that the H&P-first group gave less weight to the history and phys ical than did the H&P-last group (p = 0.04). Conclusions. The order in which clinical information was presented influenced physicians' estimates of the probability of dis ease. The clinical history and physical examination were given more weight by phy sicians who received this information last. Key words: diagnosis; urinary tract infec tions ; judgment; primary care; clinical decision making. (Med Decis Making 1998;18: 412-417)
Chronic intestinal pseudo-obstruction due to buserelin-induced formation of anti-GnRH antibodies.

BACKGROUND & AIMS A 30-year-old woman, treated with buserelin, an analogue of gonadotropin-releasing hormone (GnRH) (also called luteinizing hormone-releasing hormone, LH-RH), developed chronic intestinal pseudo-obstruction (CIPO). The sudden onset of this disease in a previously healthy woman perplexed us. CIPO refers to a gastrointestinal disorder that can have a variety of causes, such as drugs, among others. Thus, we wanted to examine whether in this patient the development of CIPO is related to the treatment with buserelin. METHODS The patient was examined using esophagogastroduodenoscopy, esophageal, and antroduodenojejunal manometry, gastric emptying tests, and histologic analyses and immunohistochemistry on full-thickness biopsies including staining with anti-GnRH antibody. Plasma samples were examined by the standard serologic analyses and specifically for the occurrence of anti-GnRH antibodies by enzyme-linked immunosorbent assay methods. RESULTS CIPO was diagnosed based on symptoms (abdominal pain, vomiting, and constipation), and the results of the clinical examinations, such as signs of esophageal aperistalsis, delayed gastric emptying, and small intestinal bursts. Histologic examination revealed a decreased number of myenteric neurons as well as increased neuronal degeneration and an abnormal immune profile. There was a loss of GnRH-containing neurons. The patient had high plasma titers of anti-GnRH antibodies, which occurred on the occasions of the treatment with buserelin. CONCLUSIONS Our findings suggest that the patient has developed CIPO due to buserelin-induced formation of anti-GnRH antibodies destroying GnRH-producing neurons of the myenteric plexus.
Crystallographic insights into the self‐assembly of KLVFF amyloid‐beta peptides

Amyloidogenic peptide fragment KLVFF (H2N‐Lys‐Leu‐Val‐Phe‐Phe‐COOH, Aβ16‐20), the core‐sequence of the polypeptide Aβ40, is a well‐studied model for amyloid formation. However, due to its low crystallinity, detailed atomic information of KLVFF structure is lacking. Here we report the high‐resolution single‐crystal X‐ray structure of two monohalogenated KLVFF derivatives, KLVFF(I) and KLVFF(Br). The obtained results highlight how halogenation is a good strategy to promote crystallization and facilitate the phase determination of KLVFF(I) and KLVFF(Br) fragments. Detailed structural studies on the packing features of both monohalogenated derivatives reveal the role of the halogen atoms showing that when they are positioned on the Phe aromatic moiety at the C‐terminus they do not form halogen bonds and thus do not produce any extra stabilization of the β‐sheet in the self‐assembly process. The structural evidences gained from these studies corroborate the various polymorphic nanostructures of the halogenated variants of KLVFF and confirm the possibility to use halogenation as innovative strategy to tune the morphology of this pentapeptide.
Pulmonary Thromboembolism in Klinefelter’s Syndrome Patient with Deficient of Protein C

Klinefelter syndrome (KS) is a common genetic disorder caused by one or more supernumerary X chromosomes. KS poses an increased risk for venous thromboembolic events such as deep venous thrombosis and pulmonary embolism. Klinefelter syndrome is prone to hypercoagulability due to hormonal imbalance and one or more inherited thrombophilic factors. Therefore, patients with KS having a medical history of venous thromboembolism require chest computed tomographic (CT) images and oral anticoagulation therapy for a period of at least six months. A 21 year old, male patient diagnosed with Klinefelter syndrome was presented to the emergency department of our hospital with primary complaints of left lower extremity pain lasting for 2 months. Deep venous thromboembosis (DVT) was diagnosed via venous doppler ultrasound and pulmonary thromboembolism in his chest CT images. Following anticoagulation treatment, his symptoms recovered. An endocrinologic test should be ordered in patients having klinefelter syndrome with a medical or familial history of venous thromboembolism as well as additional assessment of innate or acquired thrombophilia should be made.
Conservation development in blind children.

GOTTESMAN, MILTON. Conservation Development in Blind Children. CHILD DEVELOPMENT, 1973, 44, 824-827. The performance of 45 congenitally blind subjects was compared to that of 90 sighted subjects, half of whom were blindfolded, in a study of conservation development based on the work of Piaget and Inhelder (1941). Conservation tasks of mass, weight, and volume were administered to 3 age groups: 4-5, 6-7, and 8-11-year-olds. The order of acquisition was similar for all subjects in each age group. A significant difference was found on tasks of mass and weight between blind and sighted groups. An additional analysis revealed no significant differences between the subjects in the oldest age groups. The data suggest that developmental stages of blind and sighted subjects are similar as measured by performance on tasks of conservation.
Structure and properties of carotenoids in relation to function

The basic principles of structure, stereochemistry, and nomenclature of carotenoids are described and the relationships between structure and the chemical and physical properties on which all the varied biological functions and actions of carotenoids depend are discussed. The conjugated polyene chromophore determines not only the light absorption properties, and hence color, but also the photochemical properties of the molecule and consequent light‐harvesting and photoprotective action. The polyene chain is also the feature mainly responsible for the chemical reactivity of carotenoids toward oxidizing agents and free radicals, and hence for any antioxidant role. In vivo, carotenoids are found in precise locations and orientations in subcellular structures, and their chemical and physical properties are strongly influenced by other molecules in their vicinity, especially proteins and membrane lipids. In turn, the carotenoids influence the properties of these subcellular structures. Structural features such as size, shape, and polarity are essential determinants of the ability of a carotenoid to fit correctly into its molecular environment to allow it to function. A role for carotenoids in modifying structure, properties, and stability of cell mem branes, and thus affecting molecular processes associated with these membranes, may be an important aspect of their possible beneficial effects on human health. —Britton, G. Structure and properties of carotenoids in relation to function. FASEB J. 9, 1551–1558 (1995)
Enhanced anti-cancer and antimicrobial activities of curcumin nanoparticles

Abstract Background Curcumin (diferuloylmethane) is a polyphenol derived from the plant Curcuma longa, commonly called turmeric. Extensive research over the last 50 years has demonstrated that these polyphenols play an important role in the maintenance of health and prevention of diseases, in addition to its therapeutic benefits such as anti-tumor, anti-inflammatory, and anti-oxidant activities. Materials and methods This study is devoted to the enhancement of the solubility and bioavailability of curcumin nanoparticles prepared by a process based on a wet-milling technique and then examine in vitro against prostate cancer cell line 3 (PC3), human embryonic kidney cell line (HEK), human erythrocytes (red blood cells (RBCs)), and against fourth different bacterial strains two gram-positive (Micrococcus luteus ATCC 9341, Staphylococcus aureus ATCC 29213), two gram-negative (Escherichia coli ATCC 25922, Pseudomonas aeruginosa ATCC 27853). Results The cell viability curve, the half maximal inhibitory concentration (IC50), and the minimum bactericidal concentration (MBC) were evaluated. Nanocurcumin displayed significant activity against cancer cell line (PC3) and low toxicity against normal cells (HEK) compared with parent curcumin in favor of PC3 (P < 0.05). In addition, it was found that the efficiency of toxicity for nanocurcumin against PC3 (E% = 59.66%) was much better than HEK (E% = 36.07%) compared with parent curcumin. The results also demonstrate that, although nanocurcumin has a little more ability to lays RBCs than parent curcumin after incubated 60 min, but the hemolysis % remained very low and there was no significant difference between hemolysis % of nanocurcumin and parent curcumin (P > 0.05). On the other hand, the results demonstrate that, the MBCs of nanocurcumin were lower than curcumin for all different bacterial strains. Moreover, the selected gram-positive bacteria had higher sensitivity than the selected gram-negative bacteria for both curcumin and nanocurcumin. In conclusion, all these findings not only indicate that nanocurcumin safe compound has a potent ability as anti-cancer and antimicrobial activities, but also well justify the avail of using nanocurcumin as prostate cells PC3 anti-cancer, and antimicrobial agent for nanocurcumin are markedly improved by decreasing particle size to the nano-scale regime.
Design and performance analysis of optimal reduced order H-infinity controller: L1 norm based genetic algorithm technique

The H-infinity methods are widely used in control system to synthesize controller, achieving stabilization with assured performance. Usually, the order of designed H- infinity controller is as high as the order of the considered system. The design and implementation of full-order H- infinity controller often require advanced hardware and high computational cost. However, if a restriction on the maximum order of the controller is imposed, that is lower than the order of the system, the problem becomes non-convex and non- smooth (non-differentiable), and it is relatively difficult to solve. In this paper, an optimal reduced order H-infinity controller, based on Hankel singular values (HSV), has been proposed using genetic algorithm (GA) on the basis of minimization of Li norm of the error function. The algebraic Riccati equation (ARE) has been used to design H-infinity controller for a boiler system. The obtained results have been compared with well know hybrid algorithm for non-smooth and non-convex optimization based on quasi-Newton updating and gradient sampling method.
A retrospective analysis of the impact of 18F-FDG PET scans on clinical management of 133 breast cancer patients.

AIM While it is well-known that there is 18F-FDG uptake in breast tumors, clinical impact of (18)F-FDG PET in managing breast cancer patients is not well-studied. METHODS One hundred and thirty-three consecutive breast cancer patients from May 1996 to June 2000 were studied. All patients were treated and being followed. Reasons of referral included equivocal conventional studies, staging/re-staging, clinical suspicion of recurrence, and elevated serum tumor markers. Clinical status at 6 months postPET is used as the gold standard in lesions of worsening versus stable or improving. RESULTS PET was 69% sensitive and 80% specific in predicting clinical stage at 6 months. This 69% of the patients who got worse at 6 months was PET positive and 80% of the patients who were stable or improving at 6 months were PET negative. There was a significant association between PET results and clinical outcome, after adjusting for stage of disease (P=0.04), or for the treatment patients received (P<0.01). Negative PET results changed therapy as often as positive ones did. PET influenced treatment decisions in 74% of the patients referred for study. CONCLUSIONS PET holds promise as a sensitive and specific modality in following treated breast cancer patients. PET results contain information on 6 month outcome that is independent of stage or past treatment and influence patient management.