Miracle-dz/UniFAR-FTUs huggingface dataset:
The fluid mechanics of root canal irrigation

Root canal treatment is a common dental operation aimed at removing the contents of the geometrically complex canal chambers within teeth; its purpose is to remove diseased or infected tissue. The complex chamber is first enlarged and shaped by instruments to a size sufficient to deliver antibacterial fluids. These irrigants help to dissolve dying tissue, disinfect the canal walls and space and flush out debris. The effectiveness of the procedure is limited by access to the canal terminus. Endodontic research is focused on finding the instruments and clinical procedures that might improve success rates by more effectively reaching the apical anatomy. The individual factors affecting treatment outcome have not been unequivocally deciphered, partly because of the difficulty in isolating them and in making the link between simplified, general experimental models and the complex biological objects that are teeth. Explicitly considering the physical processes within the root canal can contribute to the resolution of these problems. The central problem is one of fluid motion in a confined geometry, which makes the dispersion and mixing of irrigant more difficult because of the absence of turbulence over much of the canal volume. The effects of treatments can be understood through the use of scale models, mathematical modelling and numerical computations. A particular concern in treatment is that caustic irrigant may penetrate beyond the root canal, causing chemical damage to the jawbone. In fact, a stagnation plane exists beyond the needle tip, which the irrigant cannot penetrate. The goal is therefore to shift the stagnation plane apically to be coincident with the canal terminus without extending beyond it. Needle design may solve some of the problems but the best design for irrigant penetration conflicts with that for optimal removal of the bacterial biofilm from the canal wall. Both irrigant penetration and biofilm removal may be improved through canal fluid agitation using a closely fitting instrument or by sonic or ultrasonic activation. This review highlights a way forward by understanding the physical processes involved through physical models, mathematical modelling and numerical computations.
A Blood Assist Index Control by Intraaorta Pump: A Control Strategy for Ventricular Recovery

Left ventricular assist devices (LVAD) are increasingly used for long-term support in heart failure patients. To promote ventricular reverse remodeling, a defined and adjustable energy distribution of LVAD and native heart is important. Therefore, a blood assist index (BAI), which is a ratio of power of LVAD and total power of the cardiovascular system, is defined to indicate the energy distribution of LVAD and native heart. Subsequently, an LVAD control algorithm that uses the BAI as control input is designed. The control strategy maintains the measured BAI tracking the desired BAI. A mathematic model of cardiovascular system is used to verify the feasibility of control strategy in the presence of left ventricular failure, physical active, and a recovery of cardiac function. The simulation results show that the control strategy automatically increases pump speed in response to the reduced peripheral systemic resistance (5,500 vs. 6,000 RPM). When Emax is increased from 0.6 to 1.8 mm Hg/ml to mimic left ventricular recovery, the blood flow is automatically increased from 5 to 8 L/min. As a key feature, the proposed control strategy provides a defined and adjustable energy distribution of LVAD and native heart by regulating the rotational speed of the pump, which is benefit to promote the left ventricular reverse remodeling.
Chapter 2 Behavioural and socio-demographic characteristics of Dutch neighbourhoods with high prevalence of childhood obesity

Objective To identify neighbourhoods with increased prevalence of overweight children and to examine whether the association between neighbourhood and overweight can be explained by demographic characteristics and energy-related behaviours. Method This cross-sectional study was carried out among 4,072 primary schoolchildren in the city of Zwolle, The Netherlands. Data collection consisted of measured height, weight and waist circumference, and a parental questionnaire on socio-demographic characteristics, dietary and (in)activity behaviour of their child. With Multivariate Logistic regressions, associations between unhealthy behaviours and neighbourhoods (defined by postal code) with high and low prevalence of childhood overweight were investigated. Results In three neighbourhoods the prevalence of overweight was significantly higher (16.5% vs. 10.6%, p < 0.05). The odds of living in these neighbourhoods were higher among children watching > 2 h television/day (OR: 1.57; 95% CI: 1.15 – 2.14), not eating breakfast daily (OR: 2.86; 95% CI: 1.93 – 4.23), drinking > 3 glasses/day sugared drinks (OR: 1.23; 95% CI: 1.01 – 1.50) on weekdays and not participating in organized sports (OR: 1.32; 95% CI: 1.09 – 1.59). This odds was however lower among children eating < 2 fruit/day (OR: 0.83; 95% CI: 0.69 – 1.00) on weekends. The association between neighbourhood and overweight altered slightly after adjustment for socio-demographic and behavioural characteristics during weekdays (OR: 1.42; 95% CI: 1.05 – 1.92) and weekends (OR: 1.50; 95% CI; 1.11 – 2.02). Conclusion Three neighbourhoods with higher prevalence of overweight were identified. A small part of the association between overweight and neighbourhood is explained by sociodemographic factors and unhealthy behaviours measured in this study. Neighbourhoods with higher overweight prevalence are a priority setting for targeted interventions to prevent overweight. The association between neighbourhood and overweight needs to be explored further to understand the role the neighbourhood can play in tackling overweight.
Face recognition using common matrix approach

In this paper, a new approach which is called the common matrix approach is proposed for face recognition. The common matrix for each class can be calculated either using Gram-Schmidt orthogonalization method or using scatter matrix of each class. In both ways, orthonormal matrices in the indifference subspace represent the directions that contain important discriminative information. The proposed approach overcomes the small sample size problem and the dimensionality problem in face recognition. The applications on AR-Face database give satisfactory results.
The First Digit Phenomenon

If asked whether certain digits in numbers collected randomly from, for example, the front pages of newspapers or from stock-market prices should occur more often than others, most people would think not. Nonetheless, in 1881, the astronomer and mathematician Simon Newcomb published a two-page article in the American Journal of Mathematics reporting an example of exactly that pheonomenon. Newcomb described his observation that books of logarithms in the library were quite dirty at the beginning and progressively cleaner throughout. From this he inferred that fellow scientists using the logarithm tables were looking up numbers starting with 1 more often than numbers starting with 2, numbers with first digit 2 more often than 3, and so on. After a short heuristic argument, Newcomb concluded that the probability that a number has a particular first significant digit (that is, first nonzero digit) d can be calculated as follows: Prob (first significant digit = d) = log10 (1 + 1/d), d = 1,2,. ,9
Immobilization of glucose isomerase.

The immobilization of glucose isomerase (D-xylose ketol isomerase, EC 5.3.1.5) by covalently bonding to various carriers and by adsorption to ion exchange resins was attempted in order to obtain a stable immobilized enzyme which can be used for continuous isomerization of glucose in a column. Of the covalent bonding methods, the colloidal silica-glutaraldehyde method showed the highest binding capacity and gave the most stable immobilized glucose isomerase. The Ludox HS-30 bound glucose isomerase column showed a half-life of 24 days and an enzyme usage of 0.07 units per gram of isomerized sugar (d.s, fructose 45%). Of the resins used, the macromolecular type or porous type strongly basic anion exchange resins showed the highest binding capacity and gave the most stable immobilized glucose isomerase. The Amberlite IRA-904 resine-bound glucose isomerase showed a half-life of 23 days and an enzyme usage of 0.06 units per gram of isomerized sugar (d.s., fructose 45%). Based on the ease of the immobilization process, the possibility of carrier reuse and the extensive use already achieved by ion exchange resins in the sugar industry, IRA-904 resin was selected as the candidate for commercialization.
Humidity Sensitivity of Carbon Nanotube and Poly (Dimethyldiallylammonium Chloride) Composite Films

This paper demonstrates a highly sensitive humidity sensor based on carbon nanotube and poly(dimethyldiallylammonium chloride) composite films. The composite film is deposited between interdigitated electrodes on a Si/SiO2 substrate through layer-by-layer self-assembly technique. The resistance stability of the composite film is effectively improved through thermal annealing, and I-V characteristic of the film exhibits a very good linear behavior. The resistance increases exponentially with relative humidity from 20% to 98%, and a much higher sensitivity in comparison with pure carbon nanotube networks is achieved. With temperature increased, the water vapor density versus RH shifts upwards, while the resistance is reduced downwards. The resistance is dependent on temperatures with a negative coefficient. The composite films with multiwalled carbon nanotubes show an adjacent sensitivity, compared with the single-walled carbon nanotube composite films. The experimental results show that the humidity sensors have a fast response and a short recovery time, and their response is reversible. A simple model is proposed to explain the change of composite film resistance with humidity. The carbon nanotubes junctions may play a more important role in the overall resistance change for water molecule absorption.
Geographic Routing in Wireless Multimedia Sensor Networks

In this paper, a two-phase geographic greedy forwarding (TPGF) routing algorithm is proposed in wireless multimedia sensor networks (WMSNs). TPGF is a pure geographic greedy forwarding routing algorithm, which does not include the face routing and does not use planarization algorithms. Simulation comparison in this paper indicates that TPGF is highly suitable for multimedia transmission in WMSNs.
Image segmentation based on active contours without edges

There are a lot of image segmentation techniques that try to differentiate between background and object pixels, but many of them fail to discriminate between different objects that are close to each other. Some image characteristics like low contrast between background and foreground or inhomogeneity within the objects increase the difficulty of correctly segmenting images. We designed a new segmentation algorithm based on active contours without edges. We also used other image processing techniques such as nonlinear anisotropic diffusion and adaptive thresholding in order to overcome the images' problems stated above. Our algorithm was tested on very noisy images, and the results were compared to those obtained with known methods, like segmentation using active contours without edges and graph cuts. The new technique led to very good results, but the time complexity was a drawback. However, this drawback was significantly reduced with the use of graphical programming. Our segmentation method has been successfully integrated in a software application whose aim is to segment the bones from CT datasets, extract the femur and produce personalized prostheses in hip arthroplasty.
Dynamic Integration of Data Mining Methods Using Selection in a Knowledge Discovery Management System

One of the important directions in improvement of the data-mining and knowledge discovery methods is the integration of multiple classification techniques. An integration technique should estimate and then select the most appropriate component classifiers from an ensemble of classifiers. We discuss an advanced dynamic integration technique with multiple classifiers as one variation of the stacked generalization method based on the assumption that each component classifier is the best inside some sub areas of the application domain. In the learning phase a performance matrix of each component classifier is derived and it is then used during the application phase to estimate the performance of each component classifier with new instances.
Knowledge sharing success and resistance in an engineering department: A case study

Abstract The centrality of knowledge sharing to organizations’ sustainability has been established. This research explores and illustrates the influences for individual professionals and paraprofessionals – specifically civil engineers and design drafters – to share their deep, personally constructed knowledge, in a public sector provider of railways infrastructure. It investigates the extent to which: (i) knowledge sharing will be positively influenced by the professional identity, values and knowledge culture to achieve organizational and project goals; and (ii) sharing of deep personal expertise will be influenced by the quality of relational capital among individuals and individual perspectives. It finds that knowledge sharing develops within frameworks established through the alignment among sector, profession and organization values. However, individual behavior is found to be most strongly influenced by the presence and quality of relational capital and individuals’ personal perspectives.
Analysis of Genetic Variation in Akt2/PKB-β in Severe Insulin Resistance, Lipodystrophy, Type 2 Diabetes, and Related Metabolic Phenotypes

We previously reported a family in which a heterozygous missense mutation in Akt2 led to a dominantly inherited syndrome of insulin-resistant diabetes and partial lipodystrophy. To determine whether genetic variation in AKT2 plays a broader role in human metabolic disease, we sequenced the entire coding region and splice junctions of AKT2 in 94 unrelated patients with severe insulin resistance, 35 of whom had partial lipodystrophy. Two rare missense mutations (R208K and R467W) were identified in single individuals. However, insulin-stimulated kinase activities of these variants were indistinguishable from wild type. In two large case-control studies (total number of participants 2,200), 0 of 11 common single nucleotide polymorphism (SNPs) in AKT2 showed significant association with type 2 diabetes. In a quantitative trait study of 1,721 extensively phenotyped individuals from the U.K., no association was found with any relevant intermediate metabolic trait. In summary, although heterozygous loss-of- function mutations in AKT2 can cause a syndrome of severe insulin resistance and lipodystrophy in humans, such mutations are uncommon causes of these syndromes. Furthermore, genetic variation in and around the AKT2 locus is unlikely to contribute significantly to the risk of type 2 diabetes or related intermediate metabolic traits in U.K. populations.
An Efficient Method for Analysis of EM Scattering from Objects Straddling the Interface of a Half-Space

An efficient method for the analysis of electromagnetic scattering from 3-D objects straddling the interface of a half-space has been presented in this letter. By truncating the interface, the analysis of scattering from an object within a half-space can be cast into that of a composite (high contrast) dielectric object in the free space. The conventional half-space Green's function involves a Sommerfeld integral that is extremely time-consuming to evaluate, especially when objects get close to or straddle the interface. In this letter, the Green's function of free space has been used to totally avoid the numerical evaluation of Sommerfeld integral. Moreover, fast algorithms, such as the multilevel fast multiple algorithm, can be incorporated easily without any restrictions, effectively compensating the cost due to the introduction of additional unknowns by the truncation. The factors affecting the accuracy and computational cost, such as the truncation radius and the angle of incident wave, have been investigated carefully through an example of a partially buried PEC sphere. A criterion for the truncation radius has been presented based on the coupling mechanism between the scatterer and the interface. Furthermore, the far-field response of the target in a half-space background should be expressed as a differential radar cross section. However, the high contrast problem of air/sea or air/ground requires efficient evaluations, and an integral formulation for modeling high-contrast dielectric objects has been employed to further expedite the computation. Numerical results have been presented to demonstrate the effectiveness and accuracy of the new method.
Katabatic Winds on Ice Sheets: A Refinement of the Prandtl Model

Katabatic winds on ice sheets and glaciers are buoyancy-driven flows, much like turbidity currents in the ocean. These winds are driven by radiative cooling of the ice surface and are not resolved by the typical horizontal and vertical discretization of general circulation models; therefore, a parameterization of their magnitude is desirable. In this paper, it is shown that the simplest such parameterization, based on the classical Prandtl model of slope winds, is physically inadmissible, and an improved model, which removes this irregularity, is presented. It is also shown that the improved model allows favorable comparison with both observations and regional numerical models.
Power rating of photovoltaic modules per IEC 61853-1 standard using a new outdoor test method

Photovoltaic modules are typically rated at three test conditions: STC, NOCT and Low irradiance. This paper discusses the power rating of modules at twenty-three test conditions as per the IEC 61853-1 standard using a new outdoor test method. Polycrystalline silicon modules from four different manufacturers were installed on the two-axis tracker and monitored for up to 12 continuous days. In order to obtain the I-V data at wide range of temperatures and irradiance levels, four identical modules were simultaneously installed on the tracker with and without thermal insulators on the back of the modules and with and without mesh screens on the front of the modules. This work investigates the minimum number of days required to perform power rating of modules at twenty-three test conditions.
Digital Mont’e Prama: Exploring Large Collections of Detailed 3D Models of Sculptures

We present and evaluate a scalable interactive system for the exploration of large collections of detailed three-dimensional digital models of sculptures. The system has been applied to the valorization of the Mont’e Prama complex, an extraordinary collection of protostoric Mediterranean sculptures, which depict models of cone-shaped stone towers, as well as larger-than-life human figures. The software architecture is based on scalable components for efficient distribution and adaptive rendering of extremely detailed surface meshes with overlaid information. The user interface, based on a simple and effective interactive camera controller tailored for touch interaction, has been designed for targeting both small screens and large display systems. The system components have been integrated in different interactive applications, ranging from large-screen museum setups and low-end mobile devices both with very high visual quality. The large-scale system has been installed in a variety of temporal and permanent exhibitions and has been extensively used by tens of thousands of visitors. We provide an early analysis in this article of the data gathered during a 20-month period in the National Archaeological Museum in Cagliari and a 6-month period in the Civic Museum in Cabras, for a total of over 67,000 exploration sessions.
Evaluating Large-scale Text Mining Applications Beyond the Traditional Numeric Performance Measures

Text mining methods for the biomedical domain have matured substantially and are currently being applied on a large scale to support a variety of applications in systems biology, pathway curation, data integration and gene summarization. Community-wide challenges in the BioNLP research field provide goldstandard datasets and rigorous evaluation criteria, allowing for a meaningful comparison between techniques as well as measuring progress within the field. However, such evaluations are typically conducted on relatively small training and test datasets. On a larger scale, systematic erratic behaviour may occur that severely influences hundreds of thousands of predictions. In this work, we perform a critical assessment of a large-scale text mining resource, identifying systematic errors and determining their underlying causes through semi-automated analyses and manual evaluations 1 .
The protein kinase IKKε can inhibit HCV expression independently of IFN and its own expression is downregulated in HCV‐infected livers

During a viral infection, binding of viral double‐stranded RNAs (dsRNAs) to the cytosolic RNA helicase RIG‐1 leads to recruitment of the mitochondria‐associated Cardif protein, involved in activation of the IRF3‐phosphorylating IKKε/TBK1 kinases, interferon (IFN) induction, and development of the innate immune response. The hepatitis C virus (HCV) NS3/4A protease cleaves Cardif and abrogates both IKKε/TBK1 activation and IFN induction. By using an HCV replicon model, we previously showed that ectopic overexpression of IKKε can inhibit HCV expression. Here, analysis of the IKKε transcriptome profile in these HCV replicon cells showed induction of several genes associated with the antiviral action of IFN. Interestingly, IKKε still inhibits HCV expression in the presence of neutralizing antibodies to IFN receptors or in the presence of a dominant negative STAT1α mutant. This suggests that good IKKε expression levels are important for rapid activation of the cellular antiviral response in HCV‐infected cells, in addition to provoking IFN induction. To determine the physiological importance of IKKε in HCV infection, we then analyzed its expression levels in liver biopsy specimens from HCV‐infected patients. This analysis also included genes of the IFN induction pathway (RIG‐I, MDA5, LGP2, Cardif, TBK1), and three IKKε‐induced genes (IFN‐β, CCL3, and ISG15). The results show significant inhibition of expression of IKKε and of the RNA helicases RIG‐I/MDA5/LGP2 in the HCV‐infected patients, whereas expression of TBK1 and Cardif was not significantly altered. In conclusion, given the antiviral potential of IKKε and of the RNA helicases, these in vivo data strongly support an important role for these genes in the control of HCV infection. (HEPATOLOGY 2006;44:1635–1647.)
Two-Phase Semantic Role Labeling based on Support Vector Machines

In this study, we try to apply SVMs to the semantic role labeling task, which is one of the multiclass problems. As a result, we propose a two-phase semantic role labeling model which consists of the identiﬁcation phase and the clas-siﬁcation phase. We ﬁrst identify semantic arguments, and then assign semantic roles to the identiﬁed semantic arguments. By taking the two-phase approach, we can alleviate the unbalanced class distribution problem, and select the features appropriate for each task.