Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical Study of Taylor Cone Dynamics in Electrospinning of Nanofibers

Nanofibers produced by electrospinning are attractive for a large variety of applications in material science. Formation of Taylor cone is an integral part of electrospinning process. To understand deeply its formation, a two-phase electro-hydrodynamic simulation under the volume-of-fluid (VOF) model is proposed. The electric force in such systems acts only at the interface and is zero elsewhere in the two fluids. Continuum surface force (CSF) model is adopted to compute the electric field force at the interface. For the study case, transient analyses showed the moving flow fronts and their interactions with the applied electric field. Two symmetric vortices, which occur in Taylor cone, will increase the solution velocity. A beaded nanofiber can be formed owing to the beads occur in cone jet. The numerical results were consistent with previous studies. According to the numerical results, the formation mechanism and nanofiber dynamics of the Taylor cone in a multiphase flow were well disclosed for deep explanation of the process.
BiTermEx Un prototype d’extraction de mots composés à partir de documents comparables via la méthode compositionnelle (BiTermEx , A prototype for the extraction of multiword terms from comparable documents through the compositional approach) [in French]

We describe BiTermEx, a prototype for extracting multiword terms from comparable corpora, using the compositional method. We focus on morphology-based variations of multiword constituents and their recombinaison. We experimented our approach on scientific and popular science corpora. We record TOP1 precisions of 92% and 97,5% on French to English alignments and 94% on French to Japanese.
The University of Amsterdam at CLEF@QA 2007

We describe the official runs of our team for the CLEF 2004 ad hoc tasks. We took part in the monolingual task (for Finnish, French, Portuguese, and Russian), in the bilingual task (for Amharic to English, and English to Portuguese), and, finally, in the multilingual task. In the CLEF 2004 evaluation exercise we participated in all three ad hoc retrieval tasks. We took part in the monolingual tasks for four non-English languages, Finnish, French, Portuguese, and Russian. The Portuguese language was new for CLEF 2004. Our participation in the monolingual task was a further continuation of our earlier efforts to monolingual retrieval [11, 5, 6]. Our first aim was to continue our experiments with a number of language-dependent techniques, in particular stemming algorithms for all European languages [14], and compound splitting for the compound rich Finnish language. A second aim was to continue our experiments with languageindependent techniques, in particular the use of character n-grams, where we may also index leading and ending character sequences, and retain the original words. Our third aim was to experiment with combinations of runs. We took part in the bilingual task, this year focusing on Amharic into English, and on English to Portuguese. Our bilingual runs were motivated by the following aims. Our first aim was to experiment with a language for which resources are few and far between, Amharic, and to see how far we could get by combining the scarcely available resources. Our second aim was to experiment with the relative effectiveness of a number of translation resources: machine translation [16] versus a parallel corpus [7], and query translation versus collection translation. Our third aim was to evaluate the effectiveness of our monolingual retrieval approaches for imperfectly translated queries, shedding light on the robustness of these approaches. Finally, we continued our participation for the multilingual task, where we experimented with straightforward ways of query translation, using machine translation whenever available, and a translation dictionary otherwise. We also experimented with combination methods using runs made on varying types of indexes. In Section 2 we describe the FlexIR system as well as the approaches used for each of the tasks in which we participated. Section 3 describes our official retrieval runs for CLEF 2004. In Section 4 we discuss the results we have obtained. Finally, in Section 5, we offer some conclusions regarding our document retrieval efforts.
High voltage power supply to electrostatic precipitator with transformer of helical winding structure

In this paper, a highly efficient design for production of high voltage power supply to electrostatic precipitators (ESP) is put forward. Conventional electrostatic precipitators use thyristor controlled high voltage power supply for electrostatic charging of dust particles in the gas stream. The charged particles are then attracted to and deposited on plates or other collection devices. But the present technology is not efficient enough to provide the optimal waveforms of the high voltage and current requirements. Hence to solve this problem, we bring our idea of IGBT controlled high frequency high voltage power supply to ESP. We also replace the usual power transformers by our new design of transformers with helical winding structure which helps to solve all the major problems related to power transformers in ESP applications. This new design will be a milestone in the evolution of design of electrostatic precipitators.
Technological studies for plasmonic metasurfaces

This work will present the technological processes necessary to experimentally obtain plasmonic metasurfaces for developing flat optical components or diffractive optical elements (DOE) which have reflexion functionalities. This class of metasurfaces offers the possibility to manipulate the beam shape using an array of metallic nanoscale elements patterned on a substrate. The main feature of these structures is that one can manipulate the phase behavior by modifying some of the geometrical parameters of the nano-antennas in order to achieve the required phase shift values for the desired applications. The first important step in experimentally obtaining a plasmonic metasurface structures is the electron beam lithography (EBL) followed by the lift-off method. Due to the small sizes of the gold nano-antennas and tight periodicity of the array a number of impediments can emerge in experimentally obtaining such geometries which can be overcome by the parameter optimization of the employed technologies.
Analysis of Content Aware Image Retargeting Technique

images are being viewed on the slimmest and the smallest display devices which is a challenge for various image resizing techniques and algorithms. Traditional methods have been used to change the height and width of the image which are ignorant to the content of the image. Effective resizing of images should focus on image content more than anything else. A manageable technique called seam carving is used for image and video retargeting. Seam carving is therefore used in the reduction or expansion of the height and width ratio known as the aspect ratio. The most important objects in an image are conserved and the inessential objects are edited by placing seams across, which remove the pixels of that object and hence reduce the size of the image. This method can be used for object removal, image enhancement, reducing the size of image, expanding or enlarging the size of image. This article looks upon the basics of seam carving, its types, its basic algorithm, problems in object exclusion and reduction in size of different images.
Mouse Models in Arrhythmogenic Right Ventricular Cardiomyopathy

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a heart muscle disorder characterized by fibro-fatty replacement of cardiomyocytes. The cardinal manifestations are arrhythmias, sudden cardiac death, and seldom heart failure. Mutations in genes encoding desmosomal proteins and their interaction partners have been implicated in the pathogenesis of ARVC and it is now widely accepted that ARVC is a disease caused by abnormal cell–cell adhesion. The mechanism(s) by which mutations in desmosomal proteins lead to fibro-fatty replacement remains to be fully elucidated. To this aim over the last 10 years different transgenic and targeted mouse models have been developed, these models and what they have taught us will be discussed in this review.
RNA helicase A is a downstream mediator of KIF1Bβ tumor-suppressor function in neuroblastoma.

UNLABELLED Inherited KIF1B loss-of-function mutations in neuroblastomas and pheochromocytomas implicate the kinesin KIF1B as a 1p36.2 tumor suppressor. However, the mechanism of tumor suppression is unknown. We found that KIF1B isoform β (KIF1Bβ) interacts with RNA helicase A (DHX9), causing nuclear accumulation of DHX9, followed by subsequent induction of the proapoptotic XIAP-associated factor 1 (XAF1) and, consequently, apoptosis. Pheochromocytoma and neuroblastoma arise from neural crest progenitors that compete for growth factors such as nerve growth factor (NGF) during development. KIF1Bβ is required for developmental apoptosis induced by competition for NGF. We show that DHX9 is induced by and required for apoptosis stimulated by NGF deprivation. Moreover, neuroblastomas with chromosomal deletion of 1p36 exhibit loss of KIF1Bβ expression and impaired DHX9 nuclear localization, implicating the loss of DHX9 nuclear activity in neuroblastoma pathogenesis. SIGNIFICANCE KIF1Bβ has neuroblastoma tumor-suppressor properties and promotes and requires nuclear-localized DHX9 for its apoptotic function by activating XAF1 expression. Loss of KIF1Bβ alters subcellular localization of DHX9 and diminishes NGF dependence of sympathetic neurons, leading to reduced culling of neural progenitors, and, therefore, might predispose to tumor formation.
High-fidelity virtual stenting: modeling of flow diverter deployment for hemodynamic characterization of complex intracranial aneurysms.

OBJECT Flow diversion via Pipeline Embolization Device (PED) represents the most recent advancement in endovascular therapy of intracranial aneurysms. This exploratory study aims at a proof of concept for an advanced device-modeling tool in conjunction with computational fluid dynamics (CFD) to evaluate flow modification effects by PED in actual, treated cases. METHODS The authors performed computational modeling of 3 PED-treated complex aneurysm cases. The patient in Case 1 had a fusiform vertebral aneurysm treated with a single PED. In Case 2 the patient had a giant internal carotid artery (ICA) aneurysm treated with 2 PEDs. Case 3 consisted of tandem ICA aneurysms (III-a and III-b) treated by a single PED. The authors' recently developed high-fidelity virtual stenting (HiFiVS) technique was used to recapitulate the clinical deployment process of PEDs in silico for these 3 cases. Pretreatment and posttreatment aneurysmal hemodynamics studies performed using CFD simulation were analyzed. Changes in aneurysmal flow velocity, inflow rate, wall shear stress (WSS), and turnover time were calculated and compared with the clinical outcome. RESULTS In Case 1 (occluded within the first 3 months), the aneurysm had the most drastic flow reduction after PED placement; the aneurysmal average velocity, inflow rate, and average WSS were decreased by 76.3%, 82.5%, and 74.0%, respectively, whereas the turnover time was increased to 572.1% of its pretreatment value. In Case 2 (occluded at 6 months), aneurysmal average velocity, inflow rate, and average WSS were decreased by 39.4%, 38.6%, and 59.1%, respectively, and turnover time increased to 163.0%. In Case 3, Aneurysm III-a (occluded at 6 months) had a decrease by 38.0%, 28.4%, and 50.9% in average velocity, inflow rate, and average WSS, respectively, and turnover time increased to 139.6%, which was quite similar to Aneurysm II. Surprisingly, the adjacent Aneurysm III-b had more substantial flow reduction (a decrease by 77.7%, 53.0%, and 84.4% in average velocity, inflow rate, and average WSS, respectively, and an increase to 213.0% in turnover time) than Aneurysm III-a, which qualitatively agreed with angiographic observation at 3-month follow-up. However, Aneurysm III-b remained patent at both 6 months and 9 months. A closer examination of the vascular anatomy in Case 3 revealed blood draining to the ophthalmic artery off Aneurysm III-b, which may have prevented its complete thrombosis. CONCLUSIONS This proof-of-concept study demonstrates that HiFiVS modeling of flow diverter deployment enables detailed characterization of hemodynamic alteration by PED placement. Posttreatment aneurysmal flow reduction may be correlated with aneurysm occlusion outcome. However, predicting aneurysm treatment outcome by flow diverters also requires consideration of other factors, including vascular anatomy.
An Ensemble Method for Predicting Subnuclear Localizations from Primary Protein Structures

Background Predicting protein subnuclear localization is a challenging problem. Some previous works based on non-sequence information including Gene Ontology annotations and kernel fusion have respective limitations. The aim of this work is twofold: one is to propose a novel individual feature extraction method; another is to develop an ensemble method to improve prediction performance using comprehensive information represented in the form of high dimensional feature vector obtained by 11 feature extraction methods. Methodology/Principal Findings A novel two-stage multiclass support vector machine is proposed to predict protein subnuclear localizations. It only considers those feature extraction methods based on amino acid classifications and physicochemical properties. In order to speed up our system, an automatic search method for the kernel parameter is used. The prediction performance of our method is evaluated on four datasets: Lei dataset, multi-localization dataset, SNL9 dataset and a new independent dataset. The overall accuracy of prediction for 6 localizations on Lei dataset is 75.2% and that for 9 localizations on SNL9 dataset is 72.1% in the leave-one-out cross validation, 71.7% for the multi-localization dataset and 69.8% for the new independent dataset, respectively. Comparisons with those existing methods show that our method performs better for both single-localization and multi-localization proteins and achieves more balanced sensitivities and specificities on large-size and small-size subcellular localizations. The overall accuracy improvements are 4.0% and 4.7% for single-localization proteins and 6.5% for multi-localization proteins. The reliability and stability of our classification model are further confirmed by permutation analysis. Conclusions It can be concluded that our method is effective and valuable for predicting protein subnuclear localizations. A web server has been designed to implement the proposed method. It is freely available at http://bioinformatics.awowshop. com/snlpred_page. php.
The impact of a point-of-care testing device on CVD risk assessment completion in New Zealand primary-care practice: A cluster randomised controlled trial and qualitative investigation

Objectives To assess the effect of a point of care (POC) device for testing lipids and HbA1c in addition to testing by community laboratory facilities (usual practice) on the completion of cardiovascular disease (CVD) risk assessments in general practice. Methods We conducted a pragmatic, cluster randomised controlled trial in 20 New Zealand general practices stratified by size and rurality and randomised to POC device plus usual practice or usual practice alone (controls). Patients aged 35–79 years were eligible if they met national guideline criteria for CVD risk assessment. Data on CVD risk assessments were aggregated using a web-based decision support programme common to each practice. Data entered into the on-line CVD risk assessment form could be saved pending blood test results. The primary outcome was the proportion of completed CVD risk assessments. Qualitative data on practice processes for CVD risk assessment and feasibility of POC testing were collected at the end of the study by interviews and questionnaire. The POC testing was supported by a comprehensive quality assurance programme. Results A CVD risk assessment entry was recorded for 7421 patients in 10 POC practices and 6217 patients in 10 control practices; 99.5% of CVD risk assessments had complete data in both groups (adjusted odds ratio 1.02 [95%CI 0.61–1.69]). There were major external influences that affected the trial: including a national performance target for CVD risk assessment and changes to CVD guidelines. All practices had invested in systems and dedicated staff time to identify and follow up patients to completion. However, the POC device was viewed by most as an additional tool rather than as an opportunity to review practice work flow and leverage the immediate test results for patient education and CVD risk management discussions. Shortly after commencement, the trial was halted due to a change in the HbA1c test assay performance. The trial restarted after the manufacturing issue was rectified but this affected the end use of the device. Conclusions Performance incentives and external influences were more powerful modifiers of practice behaviours than the POC device in relation to CVD risk assessment completion. The promise of combining risk assessment, communication and management within one consultation was not realised. With shifts in policy focus, the utility of POC devices for patient engagement in CVD preventive care may be demonstrated if fully integrated into the clinical setting. Trial registration Australian New Zealand Clinical Trials Registry ACTRN12613000607774
A Rich Feature Vector for Protein-Protein Interaction Extraction from Multiple Corpora

Because of the importance of protein-protein interaction (PPI) extraction from text, many corpora have been proposed with slightly differing definitions of proteins and PPI. Since no single corpus is large enough to saturate a machine learning system, it is necessary to learn from multiple different corpora. In this paper, we propose a solution to this challenge. We designed a rich feature vector, and we applied a support vector machine modified for corpus weighting (SVM-CW) to complete the task of multiple corpora PPI extraction. The rich feature vector, made from multiple useful kernels, is used to express the important information for PPI extraction, and the system with our feature vector was shown to be both faster and more accurate than the original kernel-based system, even when using just a single corpus. SVM-CW learns from one corpus, while using other corpora for support. SVM-CW is simple, but it is more effective than other methods that have been successfully applied to other NLP tasks earlier. With the feature vector and SVM-CW, our system achieved the best performance among all state-of-the-art PPI extraction systems reported so far.
Time Preference and Its Relationship with Age, Health, and Longevity Expectations

Although theories in both evolutionary biology and economics predict that an individual's health should be associated with the individual's time preference, no prior study has been done to empirically support or refute such predictions. By collecting detailed measures of health, time preference, and expected longevity on a sample of individuals in townships around Durban, South Africa, this study breaks new ground by being the first to analyze in detail the relationship between time preference and health, in an area of the world with high mortality and morbidity. Interestingly, we find that both physical health and expectations of longevity have a U-shaped relationship with the person's subjective discount rate. This suggests that those in very poor health have high discount rates, but those in very good health also have high discount rates. Similarly those with longevity expectations on the extremes have high discount rates. The research question addressed by this pilot project is policy relevant, as the study tries to determine the importance of health in economic development, not from the commonly asserted productivity-gain argument, but from a much broader investment-for-the-future argument.
Assessing Malaria Risks in Greater Mekong Subregion based on Environmental Parameters

At 4,200 km, the Mekong River is the tenth longest river in the world. It directly and indirectly influences the lives of hundreds of millions of inhabitants in its basin. The riparian countries - Thailand, Myanmar, Cambodia, Laos, Vietnam, and a small part of China - form the Greater Mekong Subregion (GMS). This geographical region has the misfortune of being the world's epicenter of falciparum malaria, which is the most severe form of malaria caused by Plasmodium falciparum. Depending on the country, approximately 50 to 90% of all malaria cases are due to this species. In the Malaria Modeling and Surveillance Project, we have been developing techniques to enhance public health s decision capability for malaria risk assessments and controls. The main objectives are: 1) identifying the potential breeding sites for major vector species; 2) implementing a malaria transmission model to identify the key factors that sustain or intensify malaria transmission; and 3) implementing a risk algorithm to predict the occurrence of malaria and its transmission intensity. The potential benefits are: 1) increased warning time for public health organizations to respond to malaria outbreaks; 2) optimized utilization of pesticide and chemoprophylaxis; 3) reduced likelihood of pesticide and drug resistance; and 4) reduced damage to environment. Environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. The NASA Earth science data sets that have been used for malaria surveillance and risk assessment include AVHRR Pathfinder, TRMM, MODIS, NSIPP, and SIESIP. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Socioeconomic factors that may influence malaria transmissions will also be incorporated into the predictive models.
Using lexical, syntactic and semantic features for non-terminal grammar rule induction in Spoken Dialogue Systems

In this work, we propose an algorithm for the automatic induction of non-terminal grammar rules for Spoken Dialogue Systems (SDS). Initially, a grammar developer provides the system with a minimal set of rules that serve as seeding examples. Using these seed rules and (optionally) a seed corpus, in-domain data are harvested and filtered from the web. A challenging task is identifying relevant chunks (phrases) in the web-harvested corpus that are good candidates for enhancing the seed grammar. We propose and evaluate rule-based and statistical classification algorithms for this purpose that use lexical, syntactic and semantic features. Induced grammars are evaluated in terms of accuracy of the proposed rules for two spoken dialogue domains. Results show up to four times absolute precision improvement compared to the naive grammar induction approach using semantic phrase similarity.
Probabilistic 3D Polyp Detection in CT Images: The Role of Sample Alignment

Automatic polyp detection is an increasingly important task in medical imaging with virtual colonoscopy [15] being widely used. In this paper, we present a 3D object detection algorithm and show its application on polyp detection from CT images. We make the following contributions: (1) The system adopts Probabilistic Boosting Tree (PBT) to probabilistically detect polyps. Integral volume and 3D Haar filters are introduced to achieve fast feature computation. (2) We give an explicit convergence rate analysis for the AdaBoost algorithm [2] and prove that the error at each step \in t+1. is tightly bounded by the previous error \in t. (3) For a 3D polyp template, a generative model is defined. Given the bound and convergence analysis, we analyze the role of "sample alignment" in the template design and devise a robust and efficient algorithm for polyp detection. The overall system has been tested on 150 volumes and the results obtained are very encouraging.