Miracle-dz/UniFAR-FTUs huggingface dataset:
A Multi-Modal Oculography-Based Mouse Controlling System: Via Facial Expressions & Eye Movement

Hand free mouse controlling systems is an eﬀective and essential research area in human computer interaction (HCI), as they can be an ideal communication and interaction means for the physical disabled persons, who don’t have means for communication except their moving eyes. In addition, these types of application provide usability and welfare for the normal users in the computer interaction. This paper presents a fully automatic multi-modal oculography-based mouse controlling system. This is done via integration between the recognized facial expressions with the eye movement and utilizing them in the mouse controlling. This paper presents a powerful multi-detector technique to localize the key facial feature points so that contours of the facial components are sampled such as the eyes, nostrils, chin, and the mouth. Also, the beholder’s gaze is estimated. Based on the 66 extracted facial features points, 20 geometric formulas (GF) and 15 ratios (Rs) are calculated, and the classiﬁer based on rule-based reasoning approach are then formed for both of the gaze direction and the facial expression (Normal, Smiling or Surprising). Tests were performed for 7 users with diﬀerent ages and diﬀerent facial characteristics then their overall satisfaction was measured. Our proposed multi-modal system obtained about 91.1% to 94.6% user satisfaction.
Evaluating Information Coverage in Machine Generated Summary and Variable Length Documents

In this paper we present an automatic technique to evaluate the information coverage in machine generated summary and other variable length documents. We believe that, most of the documents (either human written summary or machine generated summary or model document) may contain more than one topic. Even the coverage and importance of topics may be different. Based on these facts, our devised system concentrates on three important issues for evaluation purpose: (1) how many topics are covered in modal document(s), (2) what are their importances, and (3) what percentage of information covered in test document(s) w.r. t. every identified topic of model document. We introduce: (1) community detection based approach for automatic topic identification from model document, (2) a weighting scheme to identify the coverage strength of identified topics, and (3) a unique mapping based evaluation scheme, to evaluate the information coverage in test document w.r. t. given model document. We evaluate our system on (1) DUC 2005 dataset and (2) variable length documents. The experimental results show that our devised system performs better than the state-of-the-art systems of this area and also effective with variable length texts (i.e. when there is a significant variation in length of model or benchmark document and test document).
A Randomized, Double-blind, Placebo-controlled, Parallel-group, Pilot Study of Cannabidiol-rich Botanical Extract in the Symptomatic Treatment of Ulcerative Colitis.

Background Cannabidiol (CBD) exhibits anti-inflammatory properties that could improve disease activity in inflammatory bowel disease. This proof-of-concept study assessed efficacy, safety and tolerability of CBD-rich botanical extract in ulcerative colitis (UC) patients. Methods Patients aged 18 years or older, with left-sided or extensive UC, Mayo scores of 4-10 (endoscopy scores ≥1), and on stable 5-aminosalicylic acid dosing, were randomized to 10-weeks' CBD-rich botanical extract or placebo capsules. The primary endpoint was the percentage of patients in remission after treatment. Statistical testing was 2-sided, using a 10% significance level. Results Patients were less tolerant of CBD-rich botanical extract compared with placebo, taking on average one-third fewer capsules, and having more compliance-related protocol deviations (principally insufficient exposure), prompting identification of a per protocol (PP) analysis set. The primary endpoint was negative; end of treatment remission rates were similar for CBD-rich botanical extract (28%) and placebo (26%). However, PP analysis of total and partial Mayo scores favoured CBD-rich botanical extract (P = 0.068 and P = 0.038, respectively). Additionally, PP analyses of the more subjective physician's global assessment of illness severity, subject global impression of change, and patient-reported quality-of-life outcomes were improved for patients taking CBD-rich botanical extract (P = 0.069, P = 0.003, and P = 0.065, respectively). Adverse events (AEs) were predominantly mild/moderate with many in the CBD-rich botanical extract group potentially attributable to the ∆9-tetrahydrocannabinol content. A greater proportion of gastrointestinal-related AEs, indicative of UC worsening, was seen on placebo. Conclusion Although the primary endpoint was not reached, several signals suggest CBD-rich botanical extract may be beneficial for symptomatic treatment of UC.
Building a classifier for identifying sentences pertaining to disease-drug relationships in tardive dyskinesia

In this paper, we attempt to build a pipeline that identifies and extracts disease-drug relationships via sentence classification, and demonstrate the feasibility and utility of our approach using tardive dyskinesia as a case study. We manually developed and annotated a biomedicai training corpus for tardive dyskinesia. Using 10-fold cross validation, we tested and trained a naïve Bayes classifier to identify sentences pertaining to disease-drug relationships. Our precision, recall, and F-measure were all approximately 66%, and area under the ROC curve was over 80%. Our method helps to elucidate various drug effects on tardive dyskinesia and constitutes an initial effort toward the task of disease-drug relationship extraction.
EREL: an Entity Recognition and Linking algorithm

ABSTRACT This paper introduces the EREL algorithm that integrates Entity Recognition, Co-reference Resolution (CR) and Disambiguation. The algorithm recognizes entity mentions as the longest name based on the name dictionary constructed from the Wikipedia data. The CR is integrated into the algorithm to improve the performance in processing short-form or abbreviated names. The algorithm employs a new approach in disambiguation entities using new features as entity-level context information and case-sensitive data about the mention in disambiguation. Tested on four benchmark data sets in the GERBIL framework, EREL outperforms the current Entity Linking methods. EREL achieves the micro f-score as 0.83 in both tasks Disambiguate to Wikipedia and Annotate to Wikipedia.
On Formal Consistency between Value and Coordination Models

In information systems (IS) engineering dierent techniques for modeling inter-organizational collaborations are applied. In particular, value models estimate the profitability for involved stakeholders, whereas coordination models are used to agree upon the inter-organizational processes before implementing them. During the execution of inter-organizational collaboration, in addition, event logs are collected by the individual organizations representing another view of the IS. The combination of the two models and the event log represent the IS and they should therefore be consistent, i.e., not contradict each other. Since these models are provided by dierent user groups during design time and the event log is collected during run-time consistency is not straight forward. Inconsistency occurs when models contain a conflicting description of the same information, i.e., there exists a conflicting overlap between the models. In this paper we introduce an abstraction of value models, coordination models and event logs which allows ensuring and maintaining alignment between models and event log. We demonstrate its use by outlining a proof of an inconsistency resolution result based on this abstraction. Thus, the introduction of abstractions allows to explore formal inter-model relations based on consistency.
Map-Aided Dead-Reckoning With Lane-Level Maps and Integrity Monitoring

Navigation maps provide critical information for advanced driving assistance systems and autonomous vehicles. When these maps are refined to lane-level, ambiguities may occur during the map-matching process, particularly when positioning estimates are inaccurate. This paper presents a dead-reckoning method implementing a particle filter to estimate a set of likely map-matched hypotheses containing the correct solution with a high probability. Our method uses lane-level maps that feature dedicated attributes such as connectedness and adjacency. The vehicle position is essentially estimated by dead-reckoning sensors and lane detection using an intelligent camera. We also describe an integrity monitoring method for assessing the coherence of the set of hypotheses, using the fix of a global navigation satellite system receiver. The method provides in real-time a “Use/Don’t Use” characterization of the vehicle positioning information that is transmitted to safety functions, where integrity is fundamental. The performance of the proposed map-aided dead-reckoning method with integrity monitoring is evaluated using data acquired by an experimental car on suburban public roads. The results obtained validate the approach.
Improved fluorescence-enhanced optical imaging and tomography by enhanced excitation light rejection

Improved Fluorescence-enhanced Optical Imaging and Tomography by Enhanced Excitation Light Rejection. (December 2006) Kil Dong Hwang, B.S., Chung-Ang University, Korea Chair of Advisory Committee: Dr. Eva M. Sevick-Muraca Fluorescence enhanced optical imaging and tomography studies involve the detection of weak fluorescent signals emanating from nanoto picomolar concentrations of exogenous or endogenously produced fluorophore concurrent with the rejection of an overwhelmingly large component of backscattered excitation light. The elimination of the back-reflected excitation light of the collected signal remains a major and often unrecognized challenge for further reducing the noise floor and increasing sensitivity of small animal fluorescence imaging. In this dissertation, we adapted collimating and gradient index (GRIN) lenses in an existing frequency-domain system to improve excitation light rejection and enhance planar and tomographic imaging. To achieve this goal, we developed planar and tomographic imaging systems based upon ray tracing calculations for improved rejection of excitation light. The “out-of-band (S (λx))” to “in-band (S (λm) S (λx))” signal ratio assessing excitation leakage was acquired with and without collimating optics. The addition of collimating optics resulted in a 51 to 75% reduction in the transmission ratio
Beyond Stack Inspection: A Unified Access-Control and Information-Flow Security Model

Modern component-based systems, such as Java and Microsoft . NET common language runtime (CLR), have adopted stack-based access control (SBAC). Its purpose is to use stack inspection to verify that all the code responsible for a security-sensitive action is sufficiently authorized to perform that action. Previous literature has shown that the security model enforced by SBAC is flawed in that stack inspection may allow unauthorized code no longer on the stack to influence the execution of security-sensitive code. A different approach, history-based access control (HBAC), is safe but may prevent authorized code from executing a security-sensitive operation if less trusted code was previously executed. In this paper, we formally introduce information-based access control (IBAC), a novel security model that verifies that all and only the code responsible for a security-sensitive operation is sufficiently authorized. Given an access-control policy a, we present a mechanism to extract from it an implicit integrity policy i, and we prove that IBAC enforces i. Furthermore, we discuss large-scale application code scenarios to which IBAC can be successfully applied.
Predictive gene signatures of nodal metastasis in papillary thyroid carcinoma.

BACKGROUND Cervical lymph node metastases (LNM) in papillary thyroid carcinomas (PTCs) are common and develop in approximately 30-80% of PTCs. The presence of cervical LNM significantly increases the rate of locoregional recurrence in PTCs. OBJECTIVE To search for predictive gene signatures for nodal metastasis in PTCs. METHODS We used unsupervised clustering with unbiased manner to compare molecular profiles between PTCs with nodal metastasis and PTCs without nodal metastasis using mRNA-seq of TCGA data. Using gene ontology (GO) and logistic regression test, we generated 12-predictive genes for nodal metastasis in PTCs. RESULTS Unsupervised clustering of mRNA-seq (training set, N = 158) revealed that PTCs with nodal metastasis showed different gene expression patterns compared to PTCs without nodal metastasis. We generated 12 predictive genes and these gene signatures showed consistency for predicting nodal metastasis when we applied them to a validation set (N = 80). Based on multivariate analysis, these 12 predictive gene signatures showed more significant odds ratio compared to other variables. CONCLUSIONS These 12 gene signatures could be used to predict the chance of nodal metastasis in PTCs in preoperative evaluation using fine needle aspiration biopsy (FNAB) so that appropriate plan such as central neck dissection could be made.
REINFORCEMENT OF NATURAL CELLULOSE WHISKER ON NATURAL RUBBER

Cellulose whisker(CW) was prepared by hydrolysis of natural microcrystalline cellulose(MCC) with sulfate acid.The NR/CW composite was prepared by natural rubber(NR) latex coagulated with CW suspension.The results show CW has well reinforcement effect to NR.The modulus,elongation at break,tear strength of NR composites are further improved by using CW modified by resorcinol(R) and hexamethylene tetraamine(H). The mechanical properties of hot air aging(100℃,72 h) of NR/CW composite vulcanizates are markedly superior to those of NR.The tensile strength of NR/RH-CW composites was dropped from 28.54 MPa to 21.78 MPa,the rate of change was down to 23.7%,and the elongation at break decreased from 594% to 493% and the change rate decreased to 17.0%. The tensile strength of pure NR was dropped from 22.02 MPa to 2.40 MPa,and the change rate was 89.1%;and the elongation at break was dropped from 579% to 168% and the change rate was 71.0%. SEM photo shows the interface compatibility between RH-CW and NR matrix was improved in comparison with CW and NR.TGA results show the 5% weight loss temperature of composites is decreased and the residue increases with CW adding.In addition,there is a peak of the derivative TGA curve at 520℃,and the peak becomes larger and the residue increases with RH-CW adding.
Study on resistance to deformation of artificially frozen soil in deep alluvium

The resistance to deformation of artificially frozen soils in deep alluvium is investigated by relation between the secant Young’s modulus and the axial strain for different type of soil, loading or unloading, frozen temperature and initial confining pressure. It is observed that the stress-strain behavior of frozen soils in deep alluvium is highly nonlinear and the secant Young’s modulus might decrease with increasing strain, the limit of the elastic stage appeared similar for all conditions and was approximately 0.05% axial strain. On the other hand, the secant Young’s modulus of studied frozen soils and its degradation was closely related to the type of soils, loading or unloading, frozen temperature and initial confining pressure. Results indicate that the factors which can increase the secant Young’s modulus before yield of frozen soils would accelerates the rate of degradation of the secant Young’s modulus after yield of frozen soils.
Approach to Spoken Chinese Paraphrasing Based on Feature Extraction

This paper presents an approach to spoken Chinese language paraphrasing based on feature extraction and techniques of language generation. In this approach, an input utterance is first analyzed in terms of phrase structure, dependency of chunks, etc., by using multiple methods. Then, the main features of the input utterance are extracted, and the extraction results are represented by a frame. Finally, other possible expressions of the input are generated based on the analysis results by different methods. Preliminary results are shown in the paper.
Attended Visual Content Degradation Based Reduced Reference Image Quality Assessment

Reduced-reference (RR) image quality assessment (IQA), which aims to use a small amount of the reference information but achieve high accuracy, is greatly demanded in quality-orientated systems. In order to design a better RR IQA model which performs consistently with the subjective perception, the inner mechanism of the human visual system (HVS) is usually investigated and imitated. In this paper, the attention mechanism is thoroughly analyzed and used for RR IQA modeling. Generally, the HVS is more sensitive to the distortion on the attended region than that on the unattended region. Thus, the saliency of each region is calculated to highlight its importance, and a saliency weighted local structure (SWLS)-based histogram is created for visual structure degradation measurement. Meanwhile, the distortion may cause attention shift (changing the attended region). In other words, the difference of attention between the reference and distorted images can efficiently represent the quality degradation. Therefore, the attention distribution is analyzed with the salient map, and an orientation located global saliency (OLGS)-based histogram is built for attention shift measurement. Finally, combining the quality degradations from both SWLS and OLGS, a novel attended visual content degradation-based RR IQA method is introduced.1 Experimental results demonstrate that the proposed method uses only several values (18 values) and performs consistently with the subjective perception. Moreover, the proposed attention procedure can be easily extended to the existing RR IQA models and improve their performances.1The source code of the proposed method will be available at http://web.xidian. edu.cn/wjj/en/index.html
Design, Modeling and Control of Hybrid DC Circuit Breaker Based on Fast Thyristors

This paper presents a systematic study on designing a hybrid direct current (dc) circuit breaker (CB) based on fast thyristors. As an illustration, the dc CB main parameters are calculated for a 120 kV, 1.5 kA test breaker with an interrupting current of 10 kA. The studies indicate that the opening time of 2.3 ms can be achieved only if fast thyristors are employed. It is further illustrated that there is a design tradeoff between minimum interrupting current capability and discharge time for the internal capacitors (reclosing speed). The dc CB control system for opening and closing is presented based on different levels of protection and the self-protection. The dc CB is modeled in PSCAD and simulation results are used to evaluate the breaker performance under different operating conditions. It is concluded that the model represents well the dc CB and can be employed for dc grid protection studies. It is further shown that the opening time becomes longer as interrupting current reduces, and it is very long in the case of load current interruption.
Novel Modification of HistoGel-Based Cell Block Preparation Method: Improved Sufficiency for Molecular Studies.

CONTEXT - Cell block preparation methods vary substantially across institutions and are frequently suboptimal. The growing importance of biomarker testing in the era of targeted therapies makes optimization of cell block preparation critically important. OBJECTIVE - To develop an improved cell block preparation method. DESIGN - Ex vivo fine-needle aspirates and scrapes from surgically resected tumors were used to develop an improved HistoGel (Thermo Fisher Scientific, Waltham, Massachusetts)-based cell block preparation method. Cellularity yield with the new versus the standard method was assessed in ex vivo split samples and in consecutive clinical fine-needle aspirates processed before (n = 100) and after (n = 100) the new method was implemented in our laboratory. Sufficiency of cell block material for potential molecular studies was estimated by manual cell quantitation. RESULTS - The key modification in the new method was pretreatment of the pelleted cells with 95% ethanol before the addition of HistoGel (HistoGel + ethanol method). In addition, we optimized the melting conditions of HistoGel and added a dark, inorganic marker to the cell pellets to highlight the desired level of sectioning during microtomy. Cell blocks from ex vivo split samples showed that the HistoGel + ethanol method yielded, on average, an 8.3-fold (range, 1-20) greater cellularity compared with the standard HistoGel-only method. After the switch from the standard HistoGel method to the modified method in our clinical practice, sufficiency of positive fine-needle aspirates for some molecular studies increased from 72% to 97% ( P = .002). CONCLUSIONS - We describe a simple and readily adoptable modification of the HistoGel method, which results in substantial improvement in cell capture in cell blocks, leading to a significant increase in sufficiency for potential molecular and other ancillary studies.
Emergence of mcr-1 in Raoultella ornithinolytica and Escherichia coli Isolates from Retail Vegetables in China

ABSTRACT The presence of mcr-1 among Enterobacteriaceae isolates collected from retail vegetables in China between 2015 and 2016 was investigated. Two Raoultella ornithinolytica and seven Escherichia coli strains recovered from lettuce and tomato samples were identified as MCR-1-producers. Similar to isolates from animals and humans, the mcr-1 gene was located on the IncHI2/ST3, IncI2, or IncX4 plasmids. The presence of MCR-1-producing organisms in ready-to-eat food samples represents a serious risk for human health.
Rating visual contents of website using brain computer interface

Websites are part of our everyday life and are used to exchange and convey information between user communities. Despite website proliferation, assessment of site quality remains a challenging area of research. Scientific literature identifies several aspects, or criteria, of quality, which are often aggregated to content, structure, design, navigation and multimedia but they cannot determine what the user is thinking about the content while browsing. Previous researches supported the notion that the internet users do not read the websites. Only thing that attract them is the visual contents. This project aims to develop an EEG (Electroencephalogram) based application to rate interest in presented visual content. The idea is to analyze the feeling difference of a human mind as compare to the subjects' verbal interest. Some popular websites are selected for this purpose having similarities in the main contents. Brain signals collected through EEG device are send to an application for processing. It compares results of all the websites observed by the user and produces a rating which is displayed on the user interface of the application as a feed back to the user. Knowledge from the results can be basically used when designing websites and marketing campaigns online.
A Quadratically Convergent Newton Method for Computing the Nearest Correlation Matrix

The nearest correlation matrix problem is to find a correlation matrix which is closest to a given symmetric matrix in the Frobenius norm. The well-studied dual approach is to reformulate this problem as an unconstrained continuously differentiable convex optimization problem. Gradient methods and quasi-Newton methods such as BFGS have been used directly to obtain globally convergent methods. Since the objective function in the dual approach is not twice continuously differentiable, these methods converge at best linearly. In this paper, we investigate a Newton-type method for the nearest correlation matrix problem. Based on recent developments on strongly semismooth matrix valued functions, we prove the quadratic convergence of the proposed Newton method. Numerical experiments confirm the fast convergence and the high efficiency of the method.