Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of Paramagnetic Ions and Water Proton Spin-Lattice Relaxation Time in Biological Systems

Summary This paper summarizes the observations of different studies concerning the influence of paramagnetic ions on spin-lattice relaxation times in magnetic resonance imaging. Based on findings that manganese ion content in cancer tissues is decreased in comparison to normal tissues, the results of different papers analysing the influence of tissue manganese concentration on spin- lattice relaxation times are collected and compared. Neither the comparison between different organs, different animals nor the comparison between different tissues (normal and malignant) showed correlations of practical consequences between manganese concentrations and spin-lattice relaxation times. These results are consistent with those from studies with copper and iron ions in living systems. Zusammenfassung Die vorliegende Arbeit faßt als Literaturübersicht Beobachtungen über die Beeinflussung der T1-Relaxationszeit bei der Kernspintomographie durch paramagnetische Ionen zusammen. Ausgehend von Beobachtungen einer niedrigeren Mangankonzentration in karzinomatösen Geweben, verglichen mit normalen Geweben, werden die Ergebnisse verschiedener Studien zur Beeinflussung der T1-Relaxationszeiten durch Organ- und Tumor-Mangankonzentrationen zusammengestellt und verglichen. Weder im Vergleich verschiedener Organe, verschiedener Tierarten noch im Vergleich verschiedener Gewebe (normales und tumoröses Gewebe) fanden sich verwertbare Korrelationen zwischen Mangankonzentrationen und T1-Relaxationszeiten. Damit sind die Ergebnisse denen bei Kupfer- und Eisenionen in lebenden Geweben vergleichbar.
Left atrial appendage closure in patients with osler disease and atrial fibrillation

Background: Treatment of patients with atrial fibrillation (AF) and Osler disease is difficult due to increased risk of bleeding. In these patients, left atrial appendage closure (LAAc) has been shown to be non-inferior to OAC in preventing thromboembolic events. We present our experience of three clinical cases to assess the safety and efficacy of LAAc and post-procedural single antiplatelet therapy in preventing thrombi formation in Osler patients at 6-months follow-up. Methods: Three patients, 2 females and 1 male, mean age 64.6 ± 1.5, and CHA2DS2-VASc-score≥1 range 1-3, received LAA closure between 2013 and 2016. All three had Osler disease and AF with no anomalies or pre-existing LAA thrombi. Under the guidance of TEE, they underwent percutaneous LAA closure with AMPLATZERTM AmuletTM device. They received a single antiplatelet therapy with Aspirin or Clopidogrel for six months or until complete device endothelialization. TEE was repeated at six months’ follow-up. Findings: Percutaneous LAA closure was successful in all the three patients. At six months’ follow-up, while controlling for their other medical situations, there were no peri-procedural complications, bleeding and thrombus formation around the LAA closure device. Conclusion: Percutaneous LAA closure with post-procedural single antiplatelet therapy presents an alternative to chronic OAC therapy in preventing thromboembolic events in patients intolerant or contraindicated for OAC. Future studies are warranted to assess the indication for LAA closure in patients with Osler disease. Correspondence to: Aref Albakri, St-Marien hospital Bonn Venusberg, department of internal medicine, Bonn, Germany, E-mail: arefalbakri@yahoo.com
Research of Data Cleaning Methods Based on Dependency Rules

 Abstract — This paper introduces the concept and principle of data cleaning, analyzes the types and causes of dirty data, and proposes several key steps of typical cleaning process, puts forward a well scalability and versatility data cleaning framework, in view of data with attribute dependency relation, designs several of violation data discovery algorithms by formal formula, which can obtain inconsistent data to all target columns with condition attribute dependent no matter data is structured (SQL) or unstructured (NoSql), and gives 6 data cleaning methods based on these algorithms.
Canine Distemper Virus Strains Circulating among North American Dogs

ABSTRACT Canine distemper virus (CDV) is a highly contagious virus that causes multisystemic disease in dogs. We received seven samples from dogs with CD from the United States during 2007. CDV isolates from these samples formed large, multinucleated syncytia in a Vero cell line expressing canine signaling lymphocyte activation molecule (SLAM). Based on the hemagglutinin gene sequences, the CDV isolates from three states (California, Missouri, and Oklahoma) formed two CDV genetic groups: group I (major; six of seven isolates) consisted of CDV isolates closely related to the European wildlife lineage of CDV, and group II (minor; one of seven isolates) was genetically related to the Arctic-like lineage of CDV. However, both CDV groups were genetically different from the current vaccine strains that belong to the American-1 lineage of the old (1930 to 1950) CDV isolates.
Gender Differences on the Scholastic Aptitude Test, the American College Test and College Grades

Gender differences for a nationally representative sample of American college graduates obtained from the Baccalaureate and Beyond 1993-94 study were examined on the Scholastic Aptitude Test and the American College Test, taken at the age of approximately 18 years, and on grades obtained in college at the ages of approximately 18-22 years. It was found that males obtained significantly higher means on the two tests for college entrance and that females obtained significantly higher grades while in college.
Knowledge of Stroke among an Urban Population in Cotonou (Benin)

Background: Studies on the knowledge of stroke, its related risk factors and warning symptoms in the populations of Sub-Saharan Africa are scarce. No study has been performed in Benin until now. Methods: A door-to-door survey was performed in two districts of Cotonou with a broad socioeconomic range. 15,155 individuals aged ≥15 years were interviewed using a semi-structured questionnaire adapted from previous reports. Results: 15,155 individuals consented to participate in the survey. 14.1% correctly identified the brain as the affected organ in stroke. The most commonly identified risk factor was hypertension (34.5%). The most often cited warning signs of stroke were paralysis and hemiplegia (34.4%). Relatives were the major source of information about stroke (25.1%). In multivariate analysis, age, education level, occupation, self-reported risk factors of stroke, overweight and obesity were associated with at least one correct response to the questionnaire about stroke risk factors or symptoms. Conclusion: The awareness of stroke, and its risk factors and symptoms is low in Cotonou. The results suggest that specific education programs may improve people’s knowledge of stroke and their awareness of related risk factors in Sub-Saharan African countries.
The microRNA cluster miR-106b~25 regulates adult neural stem/progenitor cell proliferation and neuronal differentiation

In adult mammals, neural stem cells (NSCs) generate new neurons that are important for specific types of learning and memory. Controlling adult NSC number and function is fundamental for preserving the stem cell pool and ensuring proper levels of neurogenesis throughout life. Here we study the importance of the microRNA gene cluster miR-106b~25 (miR-106b, miR-93, and miR-25) in primary cultures of neural stem/progenitor cells (NSPCs) isolated from adult mice. We find that knocking down miR-25 decreases NSPC proliferation, whereas ectopically expressing miR-25 promotes NSPC proliferation. Expressing the entire miR-106b~25 cluster in NSPCs also increases their ability to generate new neurons. Interestingly, miR-25 has a number of potential target mRNAs involved in insulin/insulin-like growth factor-1 (IGF) signaling, a pathway implicated in aging. Furthermore, the regulatory region of miR-106b~25 is bound by FoxO3, a member of the FoxO family of transcription factors that maintains adult stem cells and extends lifespan downstream of insulin/IGF signaling. These results suggest that miR-106b~25 regulates NSPC function and is part of a network involving the insulin/IGF-FoxO pathway, which may have important implications for the homeostasis of the NSC pool during aging.
A novel algorithm for simultaneous face detection and recognition

Face detection and recognition has been introduced in many real world applications. Several algorithms have been implemented for either detection or recognition. In this paper, a novel algorithm, which simultaneously detects and recognizes facial images employing the same method, is presented. The proposed algorithm is based on a new 2D representation for the Histogram of Oriented Gradients (2D-HOG) in conjunction with 2DPCA for feature extraction. Experimental results conducted on existing datasets, FERET, ORL, UMIST, JAFFE, and MIT-CMU, achieved better accuracy and running time compared with existing techniques.
Introduction to redundant arrays of inexpensive disks (RAID)

The authors discuss various types of RAIDs (redundant arrays of inexpensive disks), a cost-effective option to meet the challenge of exponential growth in the processor and memory speeds. They argue that the size reduction of personal-computer (PC) disks is the key to the success of disk arrays. While large arrays of mainframe processors are possible, it is certainly easier to construct an array from the same number of microprocessors (or PC drives). With advantages in cost-performance, reliability, power consumption, and floor space, the authors expect RAIDs to replace large drives in future I/O systems. <<ETX>>
Altered Cortisol Response to Psychologic Stress in Breast Cancer Survivors With Persistent Fatigue

Objective: Fatigue is one of the most common and distressing symptoms experienced by cancer patients and survivors. However, the etiology of cancer-related fatigue has not been determined. In previous studies, we have shown alterations in morning serum cortisol levels and diurnal cortisol rhythms in fatigued breast cancer survivors compared with nonfatigued control subjects. The purpose of the current study was to evaluate cortisol responses to an experimental psychologic stressor in fatigued and nonfatigued survivors. Methods: Participants included 27 breast cancer survivors (11 fatigued, 16 nonfatigued). All had completed cancer treatment at least 3 years previously and were currently healthy with no evidence of recurrence. A standardized laboratory stressor, the Trier Social Stress Test (TSST), was administered during a 90-minute afternoon session. Saliva samples and autonomic measures (heart rate, blood pressure) were collected at 15-minute intervals throughout the session. Results: Fatigued survivors showed a significantly blunted cortisol response to the stressor compared with nonfatigued survivors, controlling for depression and other potential confounds (p <.05). No differences in autonomic measures were observed. Conclusions: These results, together with our earlier findings, suggest a dysregulation in hypothalamic–pituitary–adrenal (HPA) axis responsiveness among breast cancer survivors with enduring fatigue. Although the sample size was small, results suggest that attention to the HPA axis may be important for understanding cancer-related fatigue. BDI = Beck Depression Inventory; HPA = hypothalamic–pituitary–adrenal; TSST = Trier Social Stress Test.
Dynamic Sign Language Recognition for Smart Home Interactive Application Using Stochastic Linear Formal Grammar

This paper presents the state-of-the art dynamic sign language recognition (DSLR) system for smart home interactive applications. Our novel DSLR system comprises two main subsystems: an image processing (IP) module and a stochastic linear formal grammar (SLFG) module. Our IP module enables us to recognize the individual words of the sign language (i.e., a single gesture). In this module, we used the bag-of-features (BOFs) and a local part model approach for bare hand dynamic gesture recognition from a video. We used dense sampling to extract local 3-D multiscale whole-part features. We adopted 3-D histograms of a gradient orientation descriptor to represent features. The k-means++ method was applied to cluster the visual words. Dynamic hand gesture classification was conducted using the BOFs and nonlinear support vector machine methods. We used a multiscale local part model to preserve temporal context. The SLFG module analyzes the sentences of the sign language (i.e., sequences of gestures) and determines whether or not they are syntactically valid. Therefore, the DSLR system is not only able to rule out ungrammatical sentences, but it can also make predictions about missing gestures, which, in turn, increases the accuracy of our recognition task. Our IP module alone seals the accuracy of 97% and outperforms any existing bare hand dynamic gesture recognition system. However, by exploiting syntactic pattern recognition, the SLFG module raises this accuracy by 1.65%. This makes the aggregate performance of the DSLR system as accurate as 98.65%.
Behavioral and Neural Bases of Noncoincidence Learning inHermissenda

Neurobiological studies of associative learning and memory have focused nearly exclusively on the analysis of neural plasticity resulting from paired stimuli. A second major category of associative-learning processes, one that has been conspicuously neglected in cellular studies, is that of conditioned inhibition (CI), learning that one stimulus signals the absence of another. The physiological bases of CI are obscure and unexplored. To study the behavioral and neural bases of CI, we exposed the nudibranch molluscHermissenda crassicornis to explicitly unpaired (EU) presentations of light and rotation. We report here thatHermissenda exhibited persistent increases in phototactic behavior after EU training. Retardation-of-learning test results provided further evidence that EU animals learned that light signaled the absence of rotation. The increased phototactic behavior of EU animals was paralleled by selective decreases in the magnitude of ocular type B cell photoresponses and the frequency of light-elicited action potentials: the first report of a neural correlate of noncoincidence learning. Plasticity arising from explicitly unpaired stimulus presentations raises provocative questions as to how noncoincidence is detected and represented within the nervous system.
Modulation of the Rate of Peptidyl Transfer on the Ribosome by the Nature of Substrates*

The ribosome catalyzes peptide bond formation between peptidyl-tRNA in the P site and aminoacyl-tRNA in the A site. Here, we show that the nature of the C-terminal amino acid residue in the P-site peptidyl-tRNA strongly affects the rate of peptidyl transfer. Depending on the C-terminal amino acid of the peptidyl-tRNA, the rate of reaction with the small A-site substrate puromycin varied between 100 and 0.14 s–1, regardless of the tRNA identity. The reactivity decreased in the order Lys = Arg > Ala > Ser > Phe = Val > Asp ≫ Pro, with Pro being by far the slowest. However, when Phe-tRNAPhe was used as A-site substrate, the rate of peptide bond formation with any peptidyl-tRNA was ∼7 s–1, which corresponds to the rate of binding of Phe-tRNAPhe to the A site (accommodation). Because accommodation is rate-limiting for peptide bond formation, the reaction rate is uniform for all peptidyl-tRNAs, regardless of the variations of the intrinsic chemical reactivities. On the other hand, the 50-fold increase in the reaction rate for peptidyl-tRNA ending with Pro suggests that full-length aminoacyl-tRNA in the A site greatly accelerates peptide bond formation.
Neural Mechanisms Underlying Self-Localization in Rodents

The ability to self-localize and navigate in both stable and changing environments is crucial for the survival of many species. Research conducted on the non-human mammalian hippocampus and surrounding brain structures has uncovered several classes of spatial related cells. These cells provide the rest of the brain with knowledge of the animal’s location and direction—knowledge that is subsequently used in spatial navigation. This thesis provides an overview of three types of cells underlying this ability in rodents. First, place cells located in the hippocampus encode the animal’s specific location in the environment. Second, head direction cells found throughout the Papez circuit convey the angular direction of the animal’s head. Last, grid cells in the medial entorhinal cortex generate a regular triangular grid spanning the entire explored setting. The focus of this review lies on the most salient features of these types of cells. It is also considered how the cells respond to manipulations of external and internal information, as well as how different lesions affect their activity.
APPLICATION OF HYPNOTIC STRATEGIES SUSTAINED BY A POSITIVE PSYCHOLOGY ORIENTATION IN TREATING OCD PATIENTS

The hypnotherapeutic literature is abundant with numerous techniques aimed at helping practitioners deal with different types of patients and problems during hypnotic psychotherapy. Yet hypnosis and hypnotherapy textbooks have only minimally addressed the treatment of obsessive-compulsive disorder (OCD) patients. Those that do discuss this topic refer mainly to the field as a whole and do not offer specific hypnotic interventions. The objective of the present paper is to promote psychotherapy for OCD patients by proposing that practitioners use strategically oriented hypnotic intervention enhanced by a ‘positive psychology’ orientation.
Scheduling algorithms for workflow optimization

Pipelined workflows are a popular programming paradigm for parallel applications. In these workflows, the computation is divided into several stages and these stages are connected to each other through first-in first-out channels. In order to execute these workflows on a parallel machine, we must first determine the mapping of the stages onto the various processors on the machine. After finding the mapping, we must compute the schedule — the order in which the various stages execute on their assigned processors. In this paper, we explore the scheduling problem for linear workflows, assuming that the mapping is given. Linear workflows are a special case of workflows for which the dependencies between stages can be represented by a linear graph. The objective of the scheduling algorithm is either to maximize throughput or to minimize latency or both. We consider two realistic execution models: the one-port model and the multi-port model. In both models, finding a schedule to minimize latency is easy. However, computing the schedule to minimize period (maximize throughput) is NP-hard in the one-port model, but can be done in polynomial time in the multi-port model. We also present an approximation algorithm to minimize period in the one-port model. Finally, the bi-criteria problem, which consists in finding a schedule respecting a given period and a given latency, is NP-hard in both models.
Propiedades psicométricas de la escala de intencionalidad de ser físicamente activo en Educación Primaria Psychometric properties of the intention to be physically active scale in primary education

The aims of this study were: (a) to know the psychometric properties of the intention of being physically active adapted scale to primary education, and (b) to verify this measurement in the same educative stage. Seventy hundred fifty seven students were deliberately selected. The investigation was divided in two parts. First, the instrument was initially adapted, 12 expert judges were consulted to obtain content validity, and 24 children to obtain understanding validity. Second, the instrument was administered and the data were obtained. With regard the first aim, the experts and children suggested the adaptation and clarification of four items. Exploratory factorial analysis reported that all the items were grouped in a factor (explained variance = 50.88%) and confirmatory factor analysis was acceptable (χ2/g. l. = 4.83; CFI = .93; GFI = .91; RMSEA = .06). The instrument had a high internal consistency (a = .80) and temporal reliability (ICC = .79). With regard the second aim, the participants reported a high intention of being physically active (3.94). The age variable influenced in the prediction of intention of being physically active (B = .529; ET = .192; p = .006). The intention of being physically active to 11-12 years old participants was greater with respect to those of 9-10 years old (F = 8.684; d. f. = 1; p = 0.003; η2 = 0.013). In conclusion, this study displays a valid, reliable, and easy instrument to know the primary students future intention of being physically active. The participants showed high values of intention of being physically active, and in particular, the values were higher in the higher years old participants.
Scale-Aware Pixelwise Object Proposal Networks

Object proposal is essential for current state-of-the-art object detection pipelines. However, the existing proposal methods generally fail in producing results with satisfying localization accuracy. The case is even worse for small objects, which, however, are quite common in practice. In this paper, we propose a novel scale-aware pixelwise object proposal network (SPOP-net) to tackle the challenges. The SPOP-net can generate proposals with high recall rate and average best overlap, even for small objects. In particular, in order to improve the localization accuracy, a fully convolutional network is employed which predicts locations of object proposals for each pixel. The produced ensemble of pixelwise object proposals enhances the chance of hitting the object significantly without incurring heavy extra computational cost. To solve the challenge of localizing objects at small scale, two localization networks, which are specialized for localizing objects with different scales are introduced, following the divide-and-conquer philosophy. Location outputs of these two networks are then adaptively combined to generate the final proposals by a large-/small-size weighting network. Extensive evaluations on PASCAL VOC 2007 and COCO 2014 show the SPOP network is superior over the state-of-the-art models. The high-quality proposals from SPOP-net also significantly improve the mean average precision of object detection with Fast-Regions with CNN features framework. Finally, the SPOP-net (trained on PASCAL VOC) shows great generalization performance when testing it on ILSVRC 2013 validation set.
Modular Modeling for the Diagnostic of Complex Discrete-Event Systems

For the complex systems, the development of a methodology of fault diagnosis is important. Indeed, for such systems, an efficient diagnosis contributes to the improvement of the availability, the growth of production, and, of course, the reduction of maintenance costs. It is a key action in the improvement of performance of industrial feature. This paper proposes a new approach to diagnose complex systems modeled by communicating timed automata. Each component has been modeled separately by a timed automaton integrating various operating modes while the communication between the various components is carried out by the control module. Starting from each module of the complex system, a single deterministic automaton, called a diagnoser, is constructed that uses observable events to detect the occurrence of a failure. This modeling formalism provides means for formal verification of the complex system model and its diagnoser. The model-checking methods are used to check correctness properties. The steps of the method are described by an algorithm and illustrated through a batch neutralization process. The implementation of the algorithm is also discussed.