Miracle-dz/UniFAR-FTUs huggingface dataset:
Relation of Coronary Flow Reserve and Diastolic Function to Fractional Pulse Pressure in Hypertensive Patients

Fractional pulse pressure (PPf), is thought to more directly reflect arterial stiffness than pulse pressure. Our aim was to evaluate the relationship between coronary flow reserve (CFR), left ventricular diastolic function (LVDf) and PPf in hypertensive patients with normal coronary arteries. Out of 109 hypertensive patients (aged 52.8 ± 9.4 years), with normal coronary angiography, CFR was calculated successfully in 106 patients. CFR was calculated using transthoracic echo Doppler assessment with hyperemia induced by infusion of dipyridamole at a rate of 0.56 mg/kg over 4 minutes, while diastolic function was evaluated by means of transmitral flow and tissue Doppler imaging. PPf was calculated as pulse pressure divided by mean arterial pressure [Systolic blood pressure − Diastolic blood pressure/Mean arterial pressure (SBP − DBP/MAP)], Hypertensive patients with low CFR (n = 54) compared with those with normal CFR (n = 52) exhibited significantly increased PPf (75.2 ± 11.4 vs. 61.5 ± 6.7 P < 0.001). Moreover, patients with higher PPf had significantly decreased transmitral E/A ratio (P < 0.01), as well as increased E/Em ratio (P < 0.01). In hypertensives with low CFR, PPf was negatively correlated with CFR (r = −0.815, P < 0.0001). After applying multivariate linear regression analysis, PPf turned out to be a powerful independent predictor of CFR. Receiver operating characteristic (ROC) analysis revealed that a PPf of ≥0.63 was the best cutoff value for prediction of CFR <2.0 and E/Em ≥ 8 (AUC = 0.916 and 0.929 respectively; P < 0.001). Increased PPf was associated with impaired CFR and diastolic dysfunction in hypertensive patients with normal coronary arteries. PPf could be used as a simple non‐invasive index for assessment of coronary microcirculation in hypertensives with normal coronary arteries.
Experimental hypoxia and embryonic angiogenesis †

We examined the role of hypoxia and HIF factors in embryonic angiogenesis and correlated the degree of hypoxia with the level of HIF and VEGF expression and blood vessel formation. Quail eggs were incubated in normoxic and hypoxic (16% O2) conditions. Tissue hypoxia marker, pimonidazol hydrochloride, was applied in vivo for 1 hr and detected in sections with Hypoxyprobe‐1 Ab. VEGF and HIF expression was detected by in situ hybridization. HIF‐1α protein was detected in sections and by Western blot. Endothelial cells were visualized with QH‐1 antibody. Hypoxic regions were detected even in normoxic control embryos, mainly in brain, neural tube, branchial arches, limb primordia, and mesonephros. The expression patterns of HIF‐1α and HIF‐1β factors followed, in general, the Hypoxyprobe‐1 marked regions. HIF‐2α was predominantly expressed in endothelial cells. Diffuse VEGF expression was detected in hypoxic areas of neural tube, myocardium, digestive tube, and most prominently in mesonephros. Growing capillaries were directed to areas of VEGF positivity. Hypoxic regions in hypoxic embryos were larger and stained more intensely. VEGF and HIF‐1 factors were proportionately elevated in Hypoxyprobe‐1 marked regions without being expressed at new sites and were followed by increased angiogenesis. Our results demonstrate that normal embryonic vascular development involves the HIF‐VEGF regulatory cascade. Experimentally increasing the level of hypoxia to a moderate level resulted in over‐expression of HIF‐1 factors and VEGF followed by an increase in the density of developing vessels. These data indicate that embryonic angiogenesis is responsive to environmental oxygen tension and, therefore, is not entirely genetically controlled. Developmental Dynamics 235:723–733, 2006. © 2006 Wiley‐Liss, Inc.
Happiness and physical health: Associations with cardiovascular disease risk factors

Evidence suggests that being significantly unhappy is associated with negative cardiac outcomes and that positive affect is beneficial to health. The aim of this study was to examine the relationships between happiness and the individual risk factors for cardiovascular disease (CVD) in otherwise healthy working adults. Participants were recruited from one workplace in Auckland, New Zealand and completed a CVD risk assessment and demographic, nutrition and physical activity, and Authentic Happiness Inventory (AHI) questionnaires. One-way ANOVAs were performed to identify whether any significant differences existed in AHI scores by demographic and health variables. Bivariable linear regression was used to investigate the relationship between potential predictor variables and AHI classification (low or high). Variables associated with AHI classification at p < 0.20 were then examined simultaneously in multivariable logistic regression. After elimination of all non-significant factors in the multivariable logistic regression, only smoking status remained negatively associated with AHI score (p = 0.016). Despite the fact that many smokers report that smoking makes them happy, smoking was negatively associated with happiness in this sample. This finding may be implemented in smoking cessation and CVD interventions and health promotion initiatives
Combining AR filter and sparse Wavelet representation for P300 speller

A variety of experimental paradigms have been proposed in the field of Brain-Computer Interface(BCI). Among them, the P300 speller allows participators to input characters to a computer directly from their own brains. Estimating available features of P300 from raw electroencephalogram(EEG) is a key step of implementing P300 speller. In this paper, a novel combination of Autoregressive model and sparse Wavelet representation is proposed to estimate the P300 features in raw EEG acquired from the P300 speller experiments. Instead of superposition, the P300 features are estimated from raw EEG of single trial in this way. By introducing this method to process signals for BCI, the number of repeated trials may be reduced so that the information transfer rate of P300 speller could be remarkably improved. The proposed approach was tested in off-line data. The results show that the recognition accuracy of above 90% has achieved.
Unit testing of energy consumption of software libraries

The development of energy-efficient software has become a key requirement for a large number of devices, from smartphones to data centers. However, measuring accurately this consumption is a major challenge that state-of-the-art approaches have tried to tackle with a limited success. While monitoring applications' consumption offers a clear insight on where the energy is being spent, it does not help in understanding how the energy is consumed. In this paper, we therefore introduce JalenUnit, a software framework that infers the energy consumption model of software libraries from execution traces. This model can then be used to diagnose application code for detecting energy bugs, understanding energy distribution, establishing energy profiles and classifications, and comparing software libraries against their energy consumption.
An explicit variance reduction expression for the Rao-Blackwellised particle filter

Particle a standard PF with an increased number of particles, which would also increase the accuracy, could be used instead. In this paper, we have analysed the asymptotic variance of the RBPF and provide an explicit expression for the obtained variance reduction. This expression could be used to make an ecient discrimination of when to apply Rao-Blackwellisation, and when not to.
Computation of Approximate Optimal Policies in a Partially Observed Inventory Model With Rain Checks

This paper proposes a new methodology to solve partially observed inventory problems. Generally, these problems have infinite-dimensional states that are conditional distributions of the inventory level. Our methodology involves linearizing the state transitions via unnormalized probabilities. It then uses an appropriate functional basis to represent the state. Considering the speed and stability of computations, we choose truncated Chebyshev polynomials as the basis. We use Fast Fourier Transforms along with an appropriate discretization of inventory levels to speed up the computations. These main ideas are blended to obtain an iterative algorithm to solve a partially observed inventory model with rain checks. In this model, the inventory manager (IM) does not know the inventory level when it is positive. Otherwise, the IM fully observes it. This model provides a context to illustrate our methodology, which applies to other such models. Although this model has been studied mathematically in the literature, the use of our algorithm provides a numerical approximation of the optimal order quantities. These are compared to the orders released under a base mean-stock policy, where the IM replaces the unobserved inventory level with its mean and applies the well-known base stock policy. We show numerically that the optimal order quantity is very close to the base mean-stock order quantity, when the variance of the inventory distribution is small. When the mean of the inventory distribution is large, the optimal order quantity is more than the base mean-stock quantity, and it is the other way around when the mean is small or negative. These insights are explained via uncertainty and information effects and their interplay. We expect this interplay to show up in other partially observed inventory models.
Systematic Update of Computerized Physician Order Entry Order Sets to Improve Quality of Care: A Case Study

BACKGROUND AND OBJECTIVES: Seattle Children’s Hospital was one of the early adopters of computerized physician order entry. As part of our 2003 go-live, order sets were created opportunistically by using an ad hoc development process. A pilot study revealed that this ad hoc development process resulted in order sets that were neither internally nor externally consistent. We sought to update order sets by using software development techniques, to try and improve consistency and also to review clinical content so that they could be updated to current evidence and consensus-based best practice. We also sought to identify and categorize errors found in the original order sets. METHODS: This is a case study of a new order set development process that: (1) assigned order set ownership; (2) created and applied standards for how orders should appear and be organized within order sets; (3) supported multidisciplinary review and update; and (4) enforced submitting completed specifications before order set build. We extracted order sets into Microsoft Word specifications, updated content by using the Track Changes function, and then updated our Clinical Information System. Changes were reviewed and organized according to themes. RESULTS: We created standard order formats for 98 orders; 191 order sets were standardized. Multidisciplinary review identified medication issues in 37% of order sets (used in 47.6% of inpatient admissions). CONCLUSIONS: This case study demonstrates that it is not sufficient to simply implement computerized physician order entry. Clinical decision supports should be subject to rigorous development processes to ensure both clinical appropriateness and correctness.
Determination of S-amlodipine in Human Plasma Using Tizanidine as Internal Standard by Lc/Ms/Ms Method

High performance liquid chromatographic tandom mass spectrometric method for the estimation of S-amlodipine in human plasma has been developed and validated using Tizanidine as internal standard. Sample process was accomplished by Liquid-Liquid Extraction technique. The processed sample was chromatographed and analysed on Phenomenex, Lux 3u Cellulose-2 (150 × 4.6) mm column using mobile phase [0.1% formic acid in water and Acetonitrile (50:50% v/v)]. S-amlodipine was chromatographed and analysed by MS detector. Amlodipine has two basic moiety (one primary and one secondary amino) so it shows pKa=9.45 with two ester linkages and one ether linkage, so it is highly lipid soluble (logP=2.22) whereas Tizanidine has two secondary amino and three tertiary amino groups, so it shows pKa=7.49. Primary amine –NH2 is aliphatic in nature in amlodipine and secondary amine –NH is in ring so it has less action of basicity. Tizanidine has secondary amine –NH is in chain which predominates the basicity (pKa=7.49) and other secondary and tertiary amines are in ring so they show less action with formic acid/ACN mobile phase. Formic acid ionizes (primary amino) –NH2 part, then (secondary amino) –NH part and then (tertiary amino) =N part. So amlodipine elutes 1st then tizanidine comes out. LogP of amlodipine is 2.22 and for tizanidine it is 1.4, so due to Formic acid-water/CAN mobile phase Amlodipine has higher retention time than tizanidine and comparison Rt. The analytical method described is valid the determination of S-amlodipine (over a range of 0.77 ng/ml to 50.98 ng/ml) using Tizanidine as internal standard in human plasma. Signals from the detector were captured in a computer and processed using Analyst software. This validation report provides results of various validation parameters.
Unsupervised Domain Adaptation for Semantic Segmentation with GANs

Visual Domain Adaptation is a problem of immense importance in computer vision. Previous approaches showcase the inability of even deep neural networks to learn informative representations across domain shift. This problem is more severe for tasks where acquiring hand labeled data is extremely hard and tedious. In this work, we focus on adapting the representations learned by segmentation networks across synthetic and real domains. Contrary to previous approaches that use a simple adversarial objective or superpixel information to aid the process, we propose an approach based on Generative Adversarial Networks (GANs) that brings the embeddings closer in the learned feature space. To showcase the generality and scalability of our approach, we show that we can achieve state of the art results on two challenging scenarios of synthetic to real domain adaptation. Additional exploratory experiments show that our approach: (1) generalizes to unseen domains and (2) results in improved alignment of source and target distributions.
Classifying Medical Literature Using k-Nearest-Neighbours Algorithm

The amount of papers published yearly increases since decades. Libraries need to make these resources accessible and available with classification being an important aspect and part of this process. This paper analyzes prerequisites and possibilities of automatic classification of medical literature. We explain the selection, preprocessing and analysis of data consisting of catalogue datasets from the library of the Hanover Medical School, Lower Saxony, Germany. In the present study, 19,348 documents, represented by notations of library classification systems such as e.g. the Dewey Decimal Classification (DDC), were classified into 514 different classes from the National Library of Medicine (NLM) classification system. The algorithm used was k-nearest-neighbours (kNN). A correct classification rate of 55.7% could be achieved. To the best of our knowledge, this is not only the first research conducted towards the use of the NLM classification in automatic classification but also the first approach that exclusively considers already assigned notations from other classification systems for this purpose.
Dichotic Listening, Handedness, Brain Organization, and Transsexuality

ABSTRACT This study investigated the functional brain organization of 68 male-to-female (MtF) transwomen and 26 female-to-male (FtM) transmen by comparing their performance with 36 typical male and 28 typical female controls on two indicators of cerebral lateralization: dichotic listening and handedness. A sex-differentiating dichotic test and a handedness questionnaire were administered. It was hypothesized that the MtF participants’ dichotic performance would be significantly different from the control males and resemble the control female pattern. This hypothesis was supported. It was also hypothesized that the FtM dichotic pattern would be significantly different from the control females and would resemble the control male pattern. This hypothesis was not supported. Finally, it was hypothesized that there would be significantly more nonexclusive right-handers in both trans-groups. This hypothesis was supported. Taken together, the dichotic and handedness data reported here indicate that the MtF and FtM conditions are not mirror images in terms of the verbal-auditory aspects of their brain organization and neurobiology plays an important role, particularly in the development of the male-to-female trans-condition.
Further Evidence for Impairment in Abstract Conceptualization in Schizophrenia

Oltmanns and Neale (1975) have claimed that impairment in abstract conceptualization has not been demonstrated to represent a differential deficit in schizophrenia and that sorting-test measures of impairment exhibit inadequate discriminant validity. Contrary to Oltmanns and Neale's impression, evidence supporting impairment in abstract conceptualization as a differential deficit is found in the studies of Feldman and Drasgow (1951) and Drasgow and Feldman (1957). Furthermore, examination of the relevant evidence suggests that the discriminant validity of sorting-test indices of impairment is adequate and superior to that of proverbs-test measures.
Spam, Phishing, and Fraud Detection Using Random Projections, Adversarial Learning, and Semi-Supervised Learning

Spam, phishing, and fraud detection are security applications that impact most people. Challenges for building spam, phishing, and fraud detection models include difficulty in obtaining annotated data, increased computational complexity for robust detection methods, annotation errors, and changes in the underlying data distribution. We address the above challenges as follows. Clustering and active learning are combined to make efficient use of annotated data, yielding state of the art spam detection performance using only 10% of the annotated data employed by previously published methods. Social Network Analysis (SNA) reputation features for mail transfer agents are introduced to evaluate paths from sender to receiver, increasing the detection rate by 70% (with the same false positive rate) for state of the art spam detection. Random projections with boosting achieve state of the art spam detection with a 75% reduction in computational cost for message classification. The Randomized Hough Transform - Support Vector Machine updates training set annotations, increasing the (precision, recall) F measure by 9.3% compared to a state of the art method for handling adversarial noise. Spectral clustering of URL n-grams and transductive semi-supervised learning are used to increase the detection rate by 100% (doubling the detection rate with the same false positive rate) for state of the art phishing detection under adversarial modification of message text. Reputation and similarity features are used to enhance the ability to withstand changes in underlying data distributions, producing a 13.5% increase in cost savings for state of the art fraud detection.
JADE: An embedded systems specification, code generation and optimization tool

Market pressures with ever-increasing complexity and shorter time urges the use of formal methods in the system development process to produce new systems faster and cheaper due to the capacity to automate the verification, simulation and code generation. A problem that comes up, however, is that code generated from formal languages is not the most efficient because of the mapping between the specification and the implementation models. To cope with this, we present an optimization technique to enhance the performance of SDL (Specification and Description Language) derived system implementations as well as JADE, a tool that supports the complete development process, from the specification to the implementation.
The School Violence Dilemma

Focus group interviews were used to investigate teachers' perceptions of school violence and their sense of safety in schools. Analysis of these data revealed that teachers perceived a discrepancy between their rights to maintain a safe classroom environment and the rights of students in special education to receive a free and appropriate public education. Four major themes emerged: (a) safety in the classroom, (b) disciplinary double standard, (c) limited disciplinary options, and (d) perceived tension in the educational environment. These emergent themes create a complex dilemma for schools as they are faced with balancing their duty to provide a safe working and learning environment with their duty to provide a free and appropriate public education to students with disabilities.
Estimation of Physical Human-Robot Interaction Using Cost-Effective Pneumatic Padding

The idea to use a cost-effective pneumatic padding for sensing of physical interaction between a user and wearable rehabilitation robots is not new, but until now there has not been any practical relevant realization. In this paper, we present a novel method to estimate physical human-robot interaction using a pneumatic padding based on artificial neural networks (ANNs). This estimation can serve as rough indicator of applied forces/torques by the user and can be applied for visual feedback about the user’s participation or as additional information for interaction controllers. Unlike common mostly very expensive 6-axis force/torque sensors (FTS), the proposed sensor system can be easily integrated in the design of physical human-robot interfaces of rehabilitation robots and adapts itself to the shape of the individual patient’s extremity by pressure changing in pneumatic chambers, in order to provide a safe physical interaction with high user’s comfort. This paper describes a concept of using ANNs for estimation of interaction forces/torques based on pressure variations of eight customized air-pad chambers. The ANNs were trained one-time offline using signals of a high precision FTS which is also used as reference sensor for experimental validation. Experiments with three different subjects confirm the functionality of the concept and the estimation algorithm.
Survival of Lactobacillus acidophilus LA-5 and Bifidobacterium bifidum BB-02 in white-brined cheese

The viability of probiotic cultures used as adjunct cultures including Bifidobacterium bifidum BB-02 and Lactobacillus acidophilus LA-5 in white-brined cheese was investigated. The microbiological and biochemical properties of cheeses were assessed throughout 90 days of storage. Two inoculum rates for probiotic starters (2.5% and 5.0%, v/v, corresponding to (1.0–1.3)×109 cfu/g and (2.0–2.1)×109 cfu/g, respectively) were compared with the control cheese. Results obtained showed that a higher inoculum rate resulted in faster proteolysis. The cheese inoculated with 5% probiotic strains had higher water-soluble nitrogen, non-protein nitrogen, proteose-peptone nitrogen and tyrosine values than the other experimental cheeses. At the end of storage, the cheese supplemented with 5% probiotic culture had a ripening coefficient of 28.3%, followed by 2.5% probiotic strains containing the sample being 24.9%, and the control being 23.6%, respectively. It was also found that the colony counts of both probiotic microorganisms declined during storage. After 90 days of storage, the number of probiotic colonies were still around the threshold for a minimum probiotic effect (106 cfu/g).