Miracle-dz/UniFAR-FTUs huggingface dataset:
What makes a good general practitioner: do patients and doctors have different views?

BACKGROUND General practitioners (GPs) are expected to be responsive to patients' expectations, but patients and doctors may have different views on what constitutes good general practice care. AIM To elicit areas of controversy as well as areas of mutual agreement between the opinions of patients and GPs with regard to good general practice care. METHOD A questionnaire, distributed to 850 patients and 400 GPs, measured which of 40 aspects of general practice care were given priority. A second questionnaire, distributed to 400 different GPs, measured the GPs' perception of the priorities of patients. RESULTS The priority rank order of all 40 aspects was highly correlated for patients and GPs (0.72), as was the rank order of aspects for patients and the perception of them by GPs (0.71). Nevertheless, when comparing the priorities of patients and GPs, 23 out of 40 aspects differed significantly (P = 0.00125) in their rank number. Similarly, when comparing the priorities of patients with the perception of them by GPs, 23 aspects differed significantly. CONCLUSIONS There is great similarity between the priorities of patients and those of GPs. GPs are quite capable of assessing most of the priorities of patients. However, potentially controversial areas of general practice care do exist.
An Improved Genetic Algorithm Based Complex-valued Encoding

Summary Genetic algorithm is a useful tool to tackle optimization problems. In this paper the complex numbers were introduced into the traditional genetic algorithm, in which binary or real value data representation was used in the past, and a complex-value encoding genetic algorithm was proposed. Comparing with the conventional genetic algorithm which based on real-valued encoding or binary encoding, the proposed algorithm expands the dimension for search region and avoided getting into the local minimum efficiently. The computer simulation results showed it is useful for the problem of function optimization.
Toxic Shock Syndrome Toxin-1-Mediated Toxicity Inhibited by Neutralizing Antibodies Late in the Course of Continual in Vivo and in Vitro Exposure

Toxic shock syndrome (TSS) results from the host’s overwhelming inflammatory response and cytokine storm mainly due to superantigens (SAgs). There is no effective specific therapy. Application of immunoglobulins has been shown to improve the outcome of the disease and to neutralize SAgs both in vivo and in vitro. However, in most experiments that have been performed, antiserum was either pre-incubated with SAg, or both were applied simultaneously. To mirror more closely the clinical situation, we applied a multiple dose (over five days) lethal challenge in a rabbit model. Treatment with toxic shock syndrome toxin 1 (TSST-1) neutralizing antibody was fully protective, even when administered late in the course of the challenge. Kinetic studies on the effect of superantigen toxins are scarce. We performed in vitro kinetic studies by neutralizing the toxin with antibodies at well-defined time points. T-cell activation was determined by assessing T-cell proliferation (3H-thymidine incorporation), determination of IL-2 release in the cell supernatant (ELISA), and IL-2 gene activation (real-time PCR (RT-PCR)). Here we show that T-cell activation occurs continuously. The application of TSST-1 neutralizing antiserum reduced IL-2 and TNFα release into the cell supernatant, even if added at later time points. Interference with the prolonged stimulation of proinflammatory cytokines is likely to be in vivo relevant, as postexposure treatment protected rabbits against the multiple dose lethal SAg challenge. Our results shed new light on the treatment of TSS by specific antibodies even at late stages of exposure.
Inter frame coding with template matching spatio-temporal prediction

A new algorithm is proposed for predicting pixels for inter frame coding without side information. There are many approaches in the past that exploited either spatial or temporal correlations for generating prediction signals of an image in a block-by-block basis. Our method proposed in this paper exploits both spatial and temporal correlations at once to predict the pixels to be encoded. The prediction is achieved by using a template matching mechanism, with reference to previously reconstructed groups of pixels in the same frame or adjacent frames, to fill in the pixels of target regions of a frame. This process is conducted at both the encoder and decoder, and hence allows the decoder to produce the same predictor as the encoder does without any side information. Our coder uses the proposed prediction in addition to conventional motion compensation means. Simulation results show that our approach achieves up to 11.14% of improvements at the same PSNR over a codec which uses conventional block-based motion compensation.
A General Framework for Image Sequence Analysis

We present a new concept for image sequence processing that extends the classical brightness change constraint equation to incorporate changes due to dynamic physical processes. In order to estimate both the velocity and the parameters that govern the observed processes we introduce a general total least squares estimation framework. The strength of this technique is illustrated on a few example image sequences.
Learning by Doing: Skills and Jobs in Urban Ghana

Abstract This paper investigates the relationship between on-the-job mathematics skills acquisition and jobs that involve the handling of money in urban Ghana. This relationship is identified in a panel dataset by examining individuals who change jobs between survey rounds, while controlling for individual time invariant characteristics. We argue that the process of job choice in Ghana allows us to identify causal impacts. The findings show that money handling is positively associated with higher mathematics skills.
May AR Manipulate Users Subconsciously?

Asimov’s first law states: A robot may not injure a human being or, through inaction, allow a human being to come to harm. The increasing capabilities or AR now allow changing reality insofar that the reality may be perceived differently. Situations can be hidden or changed in appearance. This raises the question whether computer systems and AR may have the right to alter the reality and – if so – under which circumstances. Some examples are discussed to illustrate the spectrum of application and to build a foundation for further investigation now incorporating aspects of morality.
Multi-objective flexible job shop schedule based on improved ant colony algorithm

Flexible job shop scheduling problem is a very important research in the field of combinatorial optimization. It is also important for practical production. A method for solving multi-objective flexible job shop scheduling problem based on ant colony algorithm is presented in this paper. Ant colony algorithm is improved from the following aspects in this paper: The number of subsets is defined by the number of jobs; A new method of constructing allowed set is given in this paper; An effective local search method is applied in the improved ant colony algorithm for searching a better scheduling. The problem of choosing suitable parameters for the improved ant colony algorithm is also discussed in this paper. The algorithm we presented is validated by practical instances. The results obtained have shown the proposed approach is feasible and effective for the multi-objective flexible job shop scheduling problem.
Fast and Accurate Part { of { Speech Tagging : The SVMApproach RevisitedJes

In this paper we present a very simple and effective part{of{speech tagger based on Support Vector Machines (SVM). Simplicity and ee-ciency are achieved by working with linear sep-arators in the primal formulation of SVM, and by using a greedy left-to-right tagging scheme. By means of a rigorous experimental evaluation, we conclude that the proposed SVM{based tag-ger is robust and exible for feature modelling (including lexicalization), trains eeciently with almost no parameters to tune, and is able to tag thousands of words per second, which makes it really practical for real NLP applications. Regarding accuracy, the SVM{based tagger significantly outperforms the TnT tagger exactly under the same conditions, and achieves a very competitive accuracy of 97.0% on the WSJ corpus , which is comparable to the best taggers reported up to date.
TRPV1 expression‐dependent initiation and regulation of filopodia

Transient receptor potential vanilloid subtype 1 (TRPV1), a non‐selective cation channel, is present endogenously in dorsal root ganglia (DRG) neurons. It is involved in the recognition of various pain producing physical and chemical stimuli. In this work, we demonstrate that expression of TRPV1 induces neurite‐like structures and filopodia and that the expressed protein is localized at the filopodial tips. Exogenous expression of TRPV1 induces filopodia both in DRG neuron‐derived F11 cells and in non‐neuronal cells, such as HeLa and human embryonic kidney (HEK) cells. We find that some of the TRPV1 expression‐induced filopodia contain microtubules and microtubule‐associated components, and establish cell‐to‐cell extensions. Using live cell microscopy, we demonstrate that the filopodia are responsive to TRPV1‐specific ligands. But both, initiation and subsequent cell‐to‐cell extension formation, is independent of TRPV1 channel activity. The N‐terminal intracellular domain of TRPV1 is sufficient for filopodial structure initiation while the C‐terminal cytoplasmic domain is involved in the stabilization of microtubules within these structures. In addition, exogenous expression of TRPV1 results in altered cellular distribution and in enhanced endogenous expression of non‐conventional myosin motors, namely myosin IIA and myosin IIIA. These data indicate a novel role of TRPV1 in the regulation of cellular morphology and cellular contact formation.
Ethnic differences in diet: A focus on methodology, determinants and Type 2 Diabetes Mellitus

The overall aim of this thesis was to enhance the scientific basis for dietary analysis and the role of diet in T2DM prevalence in an ethnically diverse population. A large multi-ethnic population including five ethnic groups - South Asian origin Surinamese, African origin Surinamese, Turkish, Moroccan and Dutch origin - was utilized to achieve this goal. To address the main aim of this thesis the following questions were formulated: 1. How feasible it is to develop ethnic specific food frequency questionnaire and how stable are dietary patterns over time? 2. What are the dietary patterns of the main migrant groups in the Netherlands and what is the association between social-economic status, acculturation and these dietary patterns? 3. What is the association between diet and T2DM and what is the role of ethnicity in this respect? The studies described in this thesis were based on different sources of data. Data was obtained from the HELIUS Study and the HELIUS-Dietary Patterns study, which included men and women of all five ethnic groups. Additionally, data collected within the SUNSET study was used, which included South Asian origin Surinamese, African origin Surinamese and Dutch origin. Also, data was obtained from the Doetinchem Cohort Study, including men and women from Dutch origin, and from The Singapore Prospective Study Program 2, which included migrants of Indian origin.
Rational Design and Characterization of D-Phe-Pro-D-Arg-Derived Direct Thrombin Inhibitors

The tremendous social and economic impact of thrombotic disorders, together with the considerable risks associated to the currently available therapies, prompt for the development of more efficient and safer anticoagulants. Novel peptide-based thrombin inhibitors were identified using in silico structure-based design and further validated in vitro. The best candidate compounds contained both l- and d-amino acids, with the general sequence d-Phe(P3)-Pro(P2)-d-Arg(P1)-P1′-CONH2. The P1′ position was scanned with l- and d-isomers of natural or unnatural amino acids, covering the major chemical classes. The most potent non-covalent and proteolysis-resistant inhibitors contain small hydrophobic or polar amino acids (Gly, Ala, Ser, Cys, Thr) at the P1′ position. The lead tetrapeptide, d-Phe-Pro-d-Arg-d-Thr-CONH2, competitively inhibits α-thrombin's cleavage of the S2238 chromogenic substrate with a Ki of 0.92 µM. In order to understand the molecular details of their inhibitory action, the three-dimensional structure of three peptides (with P1′ l-isoleucine (fPrI), l-cysteine (fPrC) or d-threonine (fPrt)) in complex with human α-thrombin were determined by X-ray crystallography. All the inhibitors bind in a substrate-like orientation to the active site of the enzyme. The contacts established between the d-Arg residue in position P1 and thrombin are similar to those observed for the l-isomer in other substrates and inhibitors. However, fPrC and fPrt disrupt the active site His57-Ser195 hydrogen bond, while the combination of a P1 d-Arg and a bulkier P1′ residue in fPrI induce an unfavorable geometry for the nucleophilic attack of the scissile bond by the catalytic serine. The experimental models explain the observed relative potency of the inhibitors, as well as their stability to proteolysis. Moreover, the newly identified direct thrombin inhibitors provide a novel pharmacophore platform for developing antithrombotic agents by exploring the conformational constrains imposed by the d-stereochemistry of the residues at positions P1 and P1′.
Occurrence and Predictors of Futile Recanalization following Endovascular Treatment among Patients with Acute Ischemic Stroke: A Multicenter Study

BACKGROUND AND PURPOSE: Although recanalization is the goal of thrombolysis, it is well recognized that it fails to improve outcome of acute stroke in a subset of patients. Our aim was to assess the rate of and factors associated with “futile recanalization,” defined by absence of clinical benefit from recanalization, following endovascular treatment of acute ischemic stroke. MATERIALS AND METHODS: Data from 6 studies of acute ischemic stroke treated with mechanical and/or pharmacologic endovascular treatment were analyzed. “Futile recanalization” was defined by the occurrence of unfavorable outcome (mRS score of ≥3 at 1–3 months) despite complete angiographic recanalization (Qureshi grade 0 or TIMI grade 3). RESULTS: Complete recanalization was observed in 96 of 270 patients treated with IA thrombolysis. Futile recanalization was observed in 47 (49%). In univariate analysis, patients with futile recanalization were older (73 ± 11 versus 58 ± 15 years, P < .0001) and had higher median initial NIHSS scores (19 versus 14, P < .0001), more frequent BA occlusion (17% versus 4%, P = .049), less frequent MCA occlusion (53% versus 76%, P = .032), and a nonsignificantly higher rate of symptomatic hemorrhagic complications (2% versus 9%, P = .2). In logistic regression analysis, futile recanalization was positively associated with age >70 years (OR, 4.4; 95% CI, 1.9–10.5; P = .0008) and initial NIHSS score 10–19 (OR, 3.8; 95% CI, 1.7–8.4; P = .001), and initial NIHSS score ≥20 (OR, 64.4; 95% CI, 28.8–144; P < .0001). CONCLUSIONS: Futile recanalization is a relatively common occurrence following endovascular treatment, particularly among elderly patients and those with severe neurologic deficits.
Partially Reduced SQP Methods for Optimal Turbine and Compressor Blade Design

In this paper we present an algorithm for turbomachinery optimal blade-to-blade (S1-streamsurface) design over a full working range. We formulate the design task as a constrained boundary control multiple setpoint optimization problem in partial differential equations and develop a partially reduced SQP (PRSQP) algorithm that makes way for an efficient parallel implementation. We present numerical results based on a 2D coupled Euler/boundary-layer solver that is widely used in engineering practice.
Learning environment simulator: a tool for local decision makers and first responders

The National Infrastructure Simulation and Analysis Center (NISAC) has developed a prototype learning environment simulator (LES) based on the Critical Infrastructure Protection Decision Support System (CIPDSS) infrastructure and scenario models. The LES is designed to engage decision makers at the grass-roots level (local/city/state) to deepen their understanding of an evolving crisis, enhance their intuition and allow them to test their own strategies for events before they occur. An initial version is being developed, centered on a pandemic influenza outbreak and has been successfully tested with a group of hospital administrators and first responders. LES is not a predictive tool but rather a simulated environment allowing the user to experience the complexities of a crisis before it happens. Users can contrast various approaches to the crisis, competing with alternative strategies of their own or other participants. LES is designed to assist decision makers in making informed choices by functionally representing relevant scenarios before they occur, including impacts to critical infrastructures with their interdependencies, and estimating human health & safety and economic impacts. In this paper a brief overview of the underlying models are given followed by a description of the LES, its interface and usage and an overview of the experiencemore » testing LES with a group of hospital administrators and first responders. The paper concludes with a brief discussion of the work remaining to make LES operational. « less
Emotion Recognition of GSR Based on an Improved Quantum Neural Network

Five kinds of emotions including happy, fear, grief, anger and calm were induced by experimental environment, the galvanic skin response(GSR) signals of five kinds of emotions were effectively collected as samples from 35 subjects, and a small fragment of GSR signal was intercepted from each sample data to make up sample database which contained 175 samples, then the processed data was used to emotion classification after preprocessing GSR signals and extracting 30 features of the GSR signals. Since each feature is not fully able to reflect changes in five kinds of emotion, and there are overlaps in the optimal feature sets of GSR signal for different emotions, the paper constructed a quantum neural network recognition model for recognizing different emotions. Furthermore, the training algorithm of the traditional quantum neural network is easy to fall into local optimum and has poor convergence performance. This paper proposed an improved quantum neural network based on particle swarm optimization algorithm. Experimental results showed that the performance of quantum neural network based on improved particle swarm optimization was better than that of the quantum neural network based on the conventional gradient descent.
R egional left ventricular deafferentation increases baroreﬂex sensitivity following myocardial infarction

Objective: Depressed baroreﬂex sensitivity (BRS) has been observed following MI and has adverse prognostic implications. The mechanism for this ﬁnding is unknown. We tested the hypothesis that depressed BRS following myocardial infarction (MI) is related to augmented input from afferent receptors in the left ventricle. Methods: Conscious, chronically-instrumented dogs were trained to undergo BRS testing. This testing was performed before and 4 weeks after creation of experimental anterior MI. Animals were then randomized to undergo regional deafferentation or sham thoracotomy. One week later, BRS testing was repeated. Results: Animals with reduced BRS post-MI showed slight increases in sensitivity values after regional deafferentation. Following sham thoracotomy, animals with reduced BRS post-MI exhibited further decreases in sensitivity values. The differences in mean BRS values measured after regional or sham deafferentation were signiﬁcant (17.4 6 2.0 ms/mmHg vs. 11.7 6 1.4 ms/mmHg; P , 0.05). Conclusions: In animals with reduced BRS post-MI, deafferentation of the infarcted region prevented the progressive decline in sensitivity values that was noted in the control group. These data suggest that depressed BRS following MI is related to augmented afferent input from left ventricular receptors.  2003 European Society of Cardiology. Published by Elsevier Science B.V. All rights reserved. Mean BRS following MI and after t -tests were used for within group BRS comparisons were than the between experimental stages. Unpaired t -tests were used before 11 for BRS comparisons between regional and sham deaf-animals, improved following regional deafferentation. ferentation groups. For these and all other comparisons, a value 0.05 signiﬁcant.
Automatic Classification of Sentences in Dutch Laws

The work described here builds on [1], where we presented a categorisation of norms or provisions in legislation. We claimed that the categories are characterized by the use of typical sentence structures and that this would enable automatic detection and classification. In this paper we present the results of experiments in such automatic classification of provisions. We have defined fourteen different categories of provisions, and compiled a list of 81 sentence structures for those categories from twenty Dutch laws. Based on these structures, a parser was used to classify the sentences in fifteen different Dutch laws, classifying 94% of 476 sentences correctly. It compares well with other, statistical approaches. An important improvement of our classifier will be the distinction of principal and auxiliary sentences.
COBBS: A Multicloud Architecture for better business solutions

Adapting to the latest technological advancement is the only means for sustainability and growth for any organization in this era of fast growing business world. Cloud computing have proved to be a great boon for business development as it provides servers across the globe for storing data securely and performing computations on them. However security challenges still pose a great threat for using clouds especially in handling sensitive data. This paper throws light into different existing Multicloud approaches and then proposes a novel architecture named COBBS. Partitioning data and logic part of an application and performing a strong encryption scheme like homomorphic encryption before storing in cloud is the base of COBBS. Homomorphic encryption is different from other encryption schemes as it can perform computations on encrypted data, excluding the need for sharing a secret key and preventing the exposure of most valuable data even from the cloud service providers.