Miracle-dz/UniFAR-FTUs huggingface dataset:
Fine-grained Arabic named entity recognition

This thesis addresses the problem of fine-grained NER for Arabic, which poses unique linguistic challenges to NER; such as the absence of capitalisation and short vowels, the complex morphology, and the highly in infection process. Instead of classifying the detected NE phrases into small sets of classes, we target a broader range (i.e. 50 fine-grained classes 'hierarchal-based of two levels') to increase the depth of the semantic knowledge extracted. This has increased the number of classes, complicating the task, when compared with traditional (coarse-grained) NER, because of the increase in the number of semantic classes and the decrease in semantic differences between fine-grained classes. Our approach to developing fine-grained NER relies on two different supervised Machine Learning (ML) technologies (i.e. Maximum Entropy 'ME' and Conditional Random Fields 'CRF'), which require annotated training data in order to learn by extracting informative features. We develop a methodology which exploit the richness of Arabic Wikipedia (A W) in order to create a scalable fine-grained lexical resource and a corpus automatically. Moreover, two gold-standard created corpora from different genres were also developed to perform comparable evaluation. The thesis also developed a new approach to feature representation by relying on the dependency structure of the sentence to overcome the limitation of traditional window-based (i.e. n-gram) representation. Furthermore, by exploiting the richness of unannotated textual data to extract global informative features using word-level clustering technique was also achieved. Each contribution was evaluated via controlled experiment and reported using three commonly applied metrics, i.e. precision, recall and harmonic F-measure.
Tapered Work Roll Shape Design and Optimization for Cold Tandem Rolling Mill

K-WRS technology has a better edge drop control effect in cold tandem rolling mill, but it still exists some problems such as contact pressure peak beyond the limit, transition peak and the uneven distribution of contact pressure between the rolls in practical application. In this paper, tapered work roll shape is designed and optimized. The simulation analysis shows that the optimized roll shape not only can effectively control the edge drop of strip，but also can improve the contact pressure between the rolls. At the same time, it also can reduce the influence on the flatness control from the edge drop control.
Incremental learning of reach-to-grasp behavior: A PSO-based Inverse optimal control approach

In recent years, there has been an increasing interest in modeling natural human movements. The main question to be addressed is: what is the optimality criteria that human has optimized to achieve a certain movement. One of the most significant current discussions is the modeling of the reach-to-grasp movements that human naturally perform while approaching a certain object for grasping. Recent advances in Inverse Reinforcement Learning (IRL) approaches have facilitated investigation of reach-to-grasp movements in terms of the optimal control theory. IRL aims to learn the cost function that best describes the demonstrated human reach-to-grasp movements. Thus far, gradient-based techniques have been used to obtain the parameters of the underlying cost function. Such approaches, however, have failed to find the global optimal parameters since they are limited by locating only local optimum values. In this research, learning of the cost function for the reach-to-grasp movements is addressed as an Inverse Linear Quadratic Regulator (ILQR) problem, where linear dynamic equations and a quadratic cost are assumed. An efficient evolutionary optimization technique, Particle Swarm Optimization (PSO), is used to obtain the unknown cost for the reach-to-grasp movements under consideration. Moreover, an incremental-ILQR Algorithm is proposed to adjust the learned cost once new untrained demonstrations exist to overcome the over-fitting issue. The obtained results are encouraging and show harmony with those in neuroscience literature.
Ubiquitous postnatal LoxP recombination using a doxycycline auto‐inducible Cre transgene (DAI‐Cre)

Conventional knockouts of numerous genes are embryonic or perinatal lethal (Brandon et al ., 1995). To assess the postnatal roles of these and other genes by means of loss-of-function mutations and studying their postnatal phenotypes, ubiquitous inducible mutation during development or after birth may be advantageous. Among inducible systems, combinations of Cre-LoxP and doxy-cycline (Dox) activated systems are promising
Prevention of dental caries: A review of effective treatments

Background The objective of this study is to review medical and non medical treatments for prevention of caries. Material and Methods A comprehensive literature search of the most relevant and updated published studies from 01/01/2002 through December 2015 in PubMed/MEDLINE, Embase and Scopus databases regarding the efficacy of strategies and treatments aiming to prevent the development of caries was performed selecting papers on the basis of the Evidence-based Medicine Criteria. Results We identified thirty systematic reviews on prevention of caries. Analyzing the data the retrieved literature, performance of prevention treatments seems to be high. Conclusions Prevention treatments may have a relevant impact on the avoiding the development of caries planning. Key words:Dental caries, prevention, fluoride.
Modeling of Human Movement Behavioral Knowledge from GPS Traces for Categorizing Mobile Users

Human movement analysis and categorization of mobile users based on their movement semantics are challenging tasks. Further, due to security and privacy issues, insufficient labeled or user-annotated data (or, ground-truth data) makes the user-classification from GPS traces more complex. In this work, we present a framework which models user movement patterns containing both spatio-temporal and semantic information, generates semantic stay-point taxonomy by analysing GPS traces of all users, summarizes individuals' GPS traces and clusters users based on the semantics of their movement patterns. To alleviate labelled data scarcity problem while user categorization in a particular region of interest (ROI), we propose a method to transfer knowledge derived from a set of GPS traces of a geographically distanced but similar type of ROI. An extensive set of experiments using real GPS trace dataset of Kharagpur, India and Dartmouth, Hanover, USA have been carried out to demonstrate the effectiveness of our proposed framework.
PEB sensitivity studies of ArF resist

In an effort to develop a production-worthy 193-resist, it is important to understand the critical factors that impacts the CD variation during a routine photo lithographic process. A comprehensive investigation was done on factors affecting PEB sensitivity in ArF resist system. The areas of interest are polymer components, PAGs, bases, and photo lithographic process. In order to understand effects of the PAGs on PEB sensitivity, a number of PAGs possessing different types of cations and anions were investigated. Sulfonium type cations and acids with longer alkyl chains were found to be effective in reducing the PEB sensitivity. Influence of lithography process conditions was also studied on the PEB sensitivity. Increasing the soft bake (SB) temperature and decreasing the post exposure bake (PEB) temperature reduced the PEB sensitivity but mostly at the expense of line-edge roughness (LER). This paper presents our findings of the critical factors affecting PEB sensitivity and describes improved lithographic results of an optimized experimental formulation. In addition, delay effects after coating, soft bake, exposure, and post exposure bake (PEB) were also investigated and these results are included.
Evaluating the Impact of Human Amnion Epithelial Cells on Angiogenesis

The effects of human amnion epithelial cells (hAECs) on angiogenesis remain controversial. It is yet unknown if the presence of inflammation and/or gestational age of hAEC donors have an impact on angiogenesis. In this study, we examined the differences between term and preterm hAECs on angiogenesis in vitro and in vivo. Conditioned media from term hAECs induced the formation of longer huVEC tubules on Matrigel. Both term and preterm hAECs expressed VEGFA, PDGFB, ANGPT1, and FOXC1, which significantly increased after TNFα and IFNγ stimulation. In the presence of TNFα and IFNγ, coculture with term hAECs reduced gene transcription of Tie-2 and Foxc1 in huVECs, while coculture with preterm hAECs increased gene transcription of PDGFRα and PDGFRβ and reduced gene transcription of FOXC1 in huVECs. In vivo assessment of angiogenesis using vWF immunostaining revealed that hAEC treatment decreased angiogenesis in a bleomycin model of lung fibrosis but increased angiogenesis in a neonatal model of hyperoxia-induced lung injury. In summary, our findings suggested that the impact of hAECs on angiogenesis may be influenced by the presence of inflammation and underlying pathology.
Organizational Factors that Contribute to Operational Failures in Hospitals

The performance gap between hospital spending and outcomes is indicative of inefficient care delivery. Operational failures—breakdowns in internal supply chains that prevent work from being completed—contribute to inefficiency by consuming 10% of nurses’ time (Hendrich et al. 2008, Tucker 2004). This paper seeks to identify organizational factors associated with operational failures, with a goal of providing insight into effective strategies for removal. We observed nurses on medical/ surgical units at two hospitals, shadowed support staff who provided materials, and interviewed employees about their internal supply chain’s performance. These activities created a database of 120 operational failures and the organizational factors that contributed to them. We found that employees believed their department’s performance was satisfactory, but poorly trained employees in other departments caused the failures. However, only 14% of the operational failures arose from errors or training. They stemmed instead from multiple organizationally-driven factors: insufficient workspace (29%), poor process design (23%), and a lack of integration in the internal supply chains (23%). Our findings thus suggest that employees are unlikely to discern the role that their department’s routines play in operational failures, which hinders solution efforts. Furthermore, in contrast to the “Pareto Principle” which advocates addressing “large” problems that contribute a disproportionate share of the cumulative negative impact of problems, the failures and causes were dispersed over a wide range of factors. Thus, removing failures will require deliberate crossfunctional efforts to redesign workspaces and processes so they are better integrated with patients’ needs.
Surgical excision versus antibiotic treatment for nontuberculous mycobacterial cervicofacial lymphadenitis in children: a multicenter, randomized, controlled trial.

BACKGROUND The optimal treatment of nontuberculosis mycobacterial cervical lymphadenitis in children has not been established. Until recently, surgical excision was the standard treatment, but the number of reports of successful antibiotic treatment is increasing, which questions whether surgery is the preferred treatment. In this randomized, multicenter trial, we compared surgical excision with antibiotic treatment. METHODS One hundred children with microbiologically proven nontuberculous mycobacterial cervicofacial lymphadenitis were randomly assigned to undergo surgical excision of the involved lymph nodes or to receive antibiotic therapy with clarithromycin and rifabutin for at least 12 weeks. The primary end point was cure, defined as regression of the lymph node enlargement by at least 75%, with cure of the fistula and total skin closure without local recurrence or de novo lesions after 6 months, as assessed by clinical and ultrasound evaluation. Secondary end points included complications of surgery and adverse effects of antibiotic therapy. RESULTS Intention-to-treat analysis revealed that surgical excision was more effective than antibiotic therapy (cure rates, 96% and 66%, respectively; 95% confidence interval for the difference, 16%-44%). Treatment failures were explained neither by noncompliance nor by baseline or acquired in vitro resistance to clarithromycin or rifabutin. Surgical complications were seen in 14 (28%) of 50 patients; staphylococcal wound infection occurred in 6 patients, and a permanent grade 2 facial marginal branch dysfunction occurred in 1 patient. The vast majority of patients who were allocated to antibiotic therapy reported adverse effects (39 [78%] of 50 patients), including 4 patients who had to discontinue treatment. CONCLUSIONS Surgical excision is more effective than antibiotic treatment for children with nontuberculous mycobacterial cervicofacial lymphadenitis.
Classification of diffuse lung diseases patterns by a sparse representation based method on HRCT images

This paper describes a computer-aided diagnosis (CAD) method to classify diffuse lung diseases (DLD) patterns on HRCT images. Due to the high variety and complexity of DLD patterns, the performance of conventional methods on recognizing DLD patterns featured by geometrical information is limited. In this paper, we introduced a sparse representation based method to classify normal tissues and five types of DLD patterns including consolidation, ground-glass opacity, honeycombing, emphysema and nodular. Both CT values and eigenvalues of Hessian matrices were adopted to calculate local features. The 2360 VOIs from 117 subjects were separated into two independent set. One set was used to optimize parameters, and the other set was adopted to evaluation. The proposed technique has a overall accuracy of 95.4%. Experimental results show that our method would be useful to classify DLD patterns on HRCT images.
Effect of a therapeutic intervention for the hemiplegic upper limb in the acute phase after stroke: a single-blind, randomized, controlled multicenter trial.

BACKGROUND AND PURPOSE Arm function recovery is notoriously poor in stroke patients. The effect of treatment modalities, particularly those directed at improving upper limb function, has been studied primarily in chronic stroke patients. The purpose of this study was to investigate the effect of a specific therapeutic intervention on arm function in the acute phase after stroke. METHODS In a single-blind, randomized, controlled multicenter trial, 100 consecutive patients were allocated to either an experimental group that received an additional treatment of sensorimotor stimulation or to a control group. The intervention was applied for 6 weeks. Patients were evaluated for level of impairment (Brunnström-Fugl-Meyer test) and disability (Action Research Arm test, Barthel Index) before, midway, and after the intervention period and at follow-up 6 and 12 months after stroke. RESULTS Patients in the experimental group performed better on the Brunnström-Fugl-Meyer test than those in the control group throughout the study period, but differences were significant only at follow-up. Results on the Action Research Arm test and Barthel Index revealed no effect at the level of disability. The effect of the therapy was attributed to the repetitive stimulation of muscle activity. The treatment was most effective in patients with a severe motor deficit and hemianopia or hemi-inattention. No adverse effects due to the intervention were found. CONCLUSIONS Adding a specific intervention during the acute phase after stroke improved motor recovery, which was apparent 1 year later. These results emphasize the potential beneficial effect of therapeutic interventions for the arm.
Carboxymethylation Fiber of Dissolved Air Flotation Rejects and its Influences on Paper Properties

Fibers of dissolved air flotation rejects were been carboxymethylated to make dry strengthening agent. The effects of carboxymethylated time on carboxyl content, water retention value and physical properties of paper sheets were discussed. The effects of pH, dose of additive agent and additive aluminum sulfate on paper properties were discussed. The result show that carboxyl content and water retention values increased with the increasing of carboxymethylated time according to the research. IR analysis indicates that carboxymethyl has been connected to the surface of fibers. SEM micrographs shown that fibers were intergraded more closely benefit from the addition of dry strengthening agent. Tensile index, burst index and folding endurance respectively increased by 90.1% 101.8% and 833.3% on the condition: the additive agent amount 3%, pH 5, additive aluminum sulfate 0.5% of original pulp. Tensile index, burst index and folding endurance respectively increased by 74.0%, 87.8% and 877.8% when the carboxymethylated time was 110min for recycled pulp. This paper can be used as the theoretical basis for reusing of fiber of dissolved air flotation rejects.
The Optimal Number of Learning Samples and Hidden Units in Function Approximation With a Feedforward

{ This paper presents a methodology to estimate the optimal number of learning samples and the number of hidden units needed to obtain a desired accuracy of a function approximation by a feedforward network. The representation error and the generalization error, components of the total approximation error are analyzed and the approximation accuracy of a feedforward network is investigated as a function of the number of hidden units and the number of learning samples. Based on the asymptotical behavior of the approximation error, an asymptotical model of the error function (AMEF) is introduced of which the parameters can be determined experimentally. An alternative model of the error function, which include theoretical results about general bounds of approximation, is also analyzed. In combination with knowledge about the computational complexity of the learning rule an optimal learning set size and number of hidden units can be found resulting in a minimum computation time for a given desired precision of the approximation. This approach was applied to optimize the learning of the camera-robot mapping of a visually guided robot arm and a complex logarithm function approximation.
On crowd-retweeting spamming campaign in social networks

Crowdsourcing is often used to solicit contributions from an online community for ideas, evaluation and opinions. However, spamming can pollute such a system and manipulate the results of crowdsourcing. For detection of those spammers, the training data used in previous studies is often derived by experts labeling collected data and manually identifying spammers. The reliability of such training data is questionable. In this paper, we utilize two web based service providers Zhubajie (ZBJ) and Sandaha (SDH) and obtain reliable data about the spammers. We use such data to investigate the crowd-retweeting spam in Sina Weibo. We analyze profile features, social relationship and retweeting behavior of such spammers. We find that although these spammers are likely to connect more closely than legitimate users, the underlying social tie is different from the social relationship in other spam campaigns because of the unique retweeting features with the information cascade effect. Based on these findings, we propose retweeting-aware link based ranking algorithms to detect suspect spam accounts using seeds of identified spammers. Our evaluation shows that our algorithm is more effective than other link-based methods.
Complex event processing

Gartner has determined that ¿Complex Event Processing¿ (CEP) is one of the emerging areas on the rise in the ¿hype cycle¿ and become dominant in the area of Business Process Integration and Management (BPIM) as well as other areas (such as: command and control). According to Gartner¿s prediction, within 5-10 years this area will get to maturity. Activities in this industry have already started, and it is of the interest of this community to have early acquaintance with an area that may be dominant in several of the application types. The aim of this tutorial is to educate the audience about CEP and it¿s relevant to the some of the other emergent areas such as: Web services, autonomic computing, and grid management, as well as to traditional data management areas. The tutorial will cover introduction to the area, model-based approaches, architectures, several use cases, relationships to other concepts. It does not require any prior knowledge in the CEP.
Modelling of Phase Transformation Kinetics by Correction of Dilatometry Results for a Ferritic Nb-microalloyed Steel

Using the dilatometry technique, γ→α transformation kinetics has been determined at different cooling rates in a steel with low carbon and low niobium contents (0.09 and 0.017 mass% respectively). First of all the real and the conventional transformation temperatures of the steel were determined. The real start temperature for proeutectoid ferrite formation (A' r3 ) corresponds to the point where the dilatometric curve starts to diverge from the straight during cooling. The conventional start and finish temperatures for proeutectoid ferrite formation (A r3 and A r1 ) are given by two points close to the minimum and the first maximum of the curve, respectively. The real start and finish eutectoid transformation temperatures -(A' r1 ) s and (A' r1 ) f - correspond to the second point of inflection and a point close to the second relative maximum of the curve, respectively. Carbon enrichment of the remaining austenite, as the transformation to ferrite advances, is corrected taking into account the dependence on the carbon content of the atomic volume of austenite. On the other hand, the dilatometric data have also been corrected with regard to the different expansion coefficients of austenite and ferrite. In this way it has been seen that the lever-rule method applied to the dilatometric curve is useful for determining transformation temperatures, but not for determining transformation kinetics, since the amount of proeutectoid ferrite calculated with this method was up to 10% greater than the real amount measured with an image analyser. Finally a model based on Avrami's law has been developed for the real γ→α transformation kinetics.
Study on identification algorithm of a class of nonlinear model

A parameter identification method of Hammerstein model with two-segment piecewise nonlinearities is studied in this paper. Firstly, expressing output of the nonlinear Hammerstein model as a regressive equation in all parameters via the key term separation principle and separating key term from linear block and nonlinear block. Secondly, the unknown true outputs in the information vector are replaced with the outputs of an auxiliary model, the unknown internal variables and the unmeasured noise terms are replaced with the estimated internal variables and the estimated residuals, respectively. Accordingly, the problem of the nonlinear system identification is cast as a function optimization over parameter space, and then an improved particle swarm optimization (IPSO) algorithm is adopted to solve the optimization problem. Finally, simulation results show the effectiveness of the presented identification algorithm.