Miracle-dz/UniFAR-FTUs huggingface dataset:
Service Function Chaining (SFC) Control Plane Components & Requirements

This document describes requirements for conveying information between Service Function Chaining (SFC) control elements (including management components) and SFC functional elements. Also, this document identifies a set of control interfaces to interact with SFC- aware elements to establish, maintain or recover service function chains. This document does not specify protocols nor extensions to existing protocols. This document exclusively focuses on SFC deployments that are under the responsibility of a single administrative entity. Inter- domain considerations are out of scope.
Integrative analysis of miRNA and mRNA expression profiles reveals a novel mRNA/miRNA signature to improve risk classification for patients with gastric cancer

Gastric cancer (GC) is one of the most common types of malignant cancer and is associated with poor prognosis. Although the prognosis of patients with GC is associated with grade, stage and lymph node metastases, these traditional clinical features are inadequate to predict the outcome of GC. Therefore, there has been an increased focus on identifying novel molecular biomarkers for early diagnosis and prognosis, in order to improve outcomes in GC. In the present study, an integrative analysis of microRNA (miRNA) expression profiles, mRNA expression profiles and clinical characteristics was performed in a large cohort of patients with GC in order to identify an integrative prognostic model for improving postoperative risk classification. An integrative mRNA/miRNA signature (IMMIS), comprised of three miRNAs and one mRNA, was identified from a large number of differentially expressed miRNAs and mRNAs using univariate and multivariate Cox regression analysis. The prognostic value of the IMMIS was validated in the discovery cohort, testing cohort and The Cancer Genome Atlas (TCGA) cohort. The present results suggested that the identified signature had a reliable predictive performance and could classify the patients into high- and low-risk groups with significantly different overall survival times. In the discovery cohort, the hazard ratio (HR) was 2.805 with a 95% CI=1.722–4.567 (P<0.001). The median overall survival time as 1.49 vs. 3.85 years. In the testing cohort, the HR was 1.625 with a 95% CI=1.004–2.638 (P=0.039) and the median overall survival time was 2.17 vs. 4.62 years. In the TCGA cohort, the HR was 2.139 with a 95% CI=1.519–3.012 (P<0.001) and the median overall survival time was 1.53 vs. 4.62 years. The IMMIS constituted a reliable independent prognostic factor compared with clinical covariates, including age, sex, grade and stage, as indicated by multivariate and stratified analyses. Furthermore, comparative analysis revealed that the predictive value of the IMMIS was superior to the mRNA-based signature alone. The present results suggested the potential value of the IMMIS as a promising novel biomarker for improving the clinical management of patients with GC.
Related factors for ProSeal™ laryngeal mask airway failure

Introduction: The laryngeal mask airway (LMA) is a device for airway management that is easy to insert, safe, and efficient. However, there are associated complications that can lead to important patient morbidity and mortality, as ventilator failure, can occur with reported incidence between 0.2% and 4.7%. Male gender, advanced age, obesity, short thyromental distance, and poor dentition are known related factors to LMA failure. Objective: Determine the incidence of ProSeal™ LMA ventilatory failure and identify clinical related conditions. Materials and methods: Observational analytic study a group of adult patients with ProSealTM laryngeal mask for airway management. Statistical analysis was performed using STATA 12.1 software. Bivariate analysis was done using Fisher's exact test or Chi2 as it corresponded with statistical significance defined as P value <0.05. Skewed logistic regression for multivariate analysis was performed for estimating adjusted odd ratios (ORs). Results: Incidence of ProSealTM LMA ventilatory failure was 5.2%. In the group of patients that presented failure, 69 were older than 75 years (OR=1.06, 95% confidence interval [CI] 1.03-1.09, P < 0.001), 6 (23.1%) thyromental distance less than 6 x0200A;cm (OR = 2.48, 95% CI 0.93-6.62, P = 0.069), 5 (19.2%), inadequate anesthetic depth and/or laryngospasm (OR=5.78, 95% CI 2.23-14.96, P< 0.001) and 9 (34.6%) vintraoperative use of neuromuscular blockers (NMB) (OR=2.35, 95% CI 1.06-5.21, P=0.035). Conclusion: In patients with LMA management, the age, intraoperative use of NMB and inadequate anesthetic depth and/ or laryngospasm are clinical related conditions for ProSealTMLMA ventilatory failure.
Prevalence and Predictors of Lower Extremity Peripheral Artery Disease among Adults with Type 2 Diabetes Mellitus Attending a Tertiary Hospital in Owerri, Nigeria

Background: Lower extremity peripheral artery disease [LEAD] is common among patients with Diabetes mellitus (DM) and is under-diagnosed and under-treated. Early diagnosis and treatment will prevent associated cardiovascular events, minimize long term disability and improve quality of life. There is paucity of data on LEAD in Owerri and Southeastern Nigeria in general. Study Objectives: To determine the prevalence and predictors of LEAD among adults with type 2 diabetes mellitus (T2DM). Study Design: Cross-sectional analytical. Study Site: Endocrinology Clinic, Federal Medical Centre, Owerri, Nigeria. Methodology: Two hundred and seventy (270) T2DM patients and 135 non-diabetic controls were recruited consecutively between January and June, 2016. Questionnaires were used to collect relevant information, followed by focused physical examination and anthropometry. A portable Ankle Brachial Index (ABI) kit was used for measurement of ABI and participants with values < 0.9 were diagnosed as having LEAD. For participants with ABI ≥ 1.3, a toe pressure kit was used to measure their toe systolic pressure and those with toe brachial index (TBI) ≤ 0.7 were diagnosed as having LEAD. Fasting blood samples were also collected for assessment of glycated haemoglobin (HbA1c), fasting plasma glucose (FPG) and lipid profile. Data analysis was performed with SPSS version 22 and p-value < 0.05 was considered significant. Results: The mean ages of the T2DM and control participants were 59.8 ± 10.7 and 59.6 ± 12.3 years respectively (P = 0.89) while their mean ABIs were 0.97 ± 0.18 and 0.99 ± 0.16 respectively (P = 0.26). The prevalence of LEAD was 31.1% and 27.4% among T2DM and control participants respectively (P = 0.44) while among the T2DM participants that had LEAD, 57 (67.8%), 26 (31.0%) and 1 (1.2%) had mild, moderate and severe LEAD respectively. The only predictor of LEAD among T2DM participants was absent/reduced dorsalis pedis artery pulsation (AOR = 3.57, CI = 1.13 – 11.29, P = 0.03). Conclusions and Recommendations: There is a high prevalence of LEAD among adults with T2DM but this is not significantly higher than the prevalence among non-diabetic individuals. Regular screening of T2DM patients for LEAD should be encouraged. There is also need for regular palpation of dorsalis pedis artery among adults with T2DM to identify those with absent or reduced pulsation which may be an indication of the presence of LEAD.
The Algorithms for Segmentation of Text-Lines in Handwriting Images

Text line segmentation from handwriting image is the basis of handwriting text image processing, and the accuracy of line segmentation plays a decisive role in handwriting identification, handwriting recognition, handwriting retrieval and other research fields. The accuracy of line segmentation may directly lead to the accuracy and efficiency of handwriting identification, character recognition and text retrieval. Because offline handwriting has lost the order of writing and other information, which makes it more difficult to segment the offline handwriting image. This paper mainly aims at the complexity of the segmentation problem caused by the diversity of off-line handwriting styles, such as tilt, adhesion, overlap and so on, and compares the related solutions in recent years. In the end, some problems in line segmentation research are put forward or omitted, which is more convenient for readers to understand the field.
Parameter Estimation and Verification of the DSSATModel of Winter Wheat for Simulation and Development in North China

DSSAT crop model is used to carry out estimation and verification on the model parameters of the major winter wheat variety (Jimai-22) in typical experimental sites of North China. Based on the field experiment data of 12 crops with sufficient-irrigation and non-sufficient irrigation during two continuous winter wheat planting seasons in the survey regions of Daxing District, Beijing and Tangshan, Hebei, the DSSAT model is used for verification, estimation and verification schemes for genetic coefficients of different crop varieties are developed and compared. We evaluate the reliability and applicability of growth & development and yield response of winter wheat in North China in the DSSAT model in the conditions of water stress and non-sufficient irrigation, verify and assess different model calibration schemes, and finally select a set of optimal crop model parameters as the basis of simulating crop optimal irrigation system, so as to provide data support for the optimal irrigation system in North China.
Access to Relational Databases Using Interrogative Sentences in Indonesian Language

One of way to access relational databases is using Natural Language Interface to Databases or NLIDB, which is accessing relational databases using natural language. Generally, NLIDB developed for domain specific databases. NLIDB in Indonesian language that can be used in any domain already developed by Fibrian in 2016. However, this NLIDB system only accept imperative sentences, while interrogative sentences was not handled yet. Therefore, this paper was carried out to design the translation method from interrogative sentences in Indonesian language to SQL query. Methods from Fibrian's NLIDB are modified to be able to process interrogative sentences in Indonesian language. The proposed method is tested and able to translate interrogative sentences in Indonesian language to SQL query.
Variations in Family Attitudes towards Coping with People Living with Mental Illness

BACKGROUND: The major challenge faced in Nigeria regarding the care of people living with mental illness are a stigma, caregiver burden and financial aid. This has led to high premature deaths and has also hindered the attainment of Sustainable Development Goal 3 target 4. In an attempt to find lasting solutions to increased mortality caused by mental illness, it is important to evaluate family attitudes towards people living with mental illness. AIM: To examine variations in family attitudes towards coping with people living with mental illness in Nigeria. SUBJECTS AND METHODS: Thirty In-Depth Interview (IDI) were conducted among caregivers of people living with mental illness (those presently receiving treatment and those recovering). During all the interview sessions, field notes were taken. Responses from interviewees were transcribed and analysed with the aid of ‘systematic-content analysis. RESULTS: It found out that family members of people living with mental illness or caregivers usually suffer from stress and stigma, which affects adherence to treatment. CONCLUSION: Caregivers must have sufficient knowledge and support to assume the responsibilities of caring for the mentally ill, leading to recurrence. The caregiver remains in contact with professional healthcare workers and helps the mentally ill with decision-making and matters affecting their daily life.
A qualitative analysis of student experiences of a blended learning course

Blended learning has become a popular topic in higher education. A blended learning course combines face-to-face instructions with computer-mediated instructions in any possible ratio. Even though studies have investigated effects of blended learning on education costs and student performance, not much is known about how students experience a blended learning course. The current study provides insights into student experiences in a blended learning course in which all materials were available online, and a minimum number of face-to-face meetings was organized. Three students of the course participated in an in-depth interview, and all fourteen students of the course provided answers to questions during four face-to-face tutorials. Findings indicate similarities in their needs, but differences in their perception of the flexibility that was given to them in the course. A possible explanation for the differences in perception of flexibility could be the students’ self-efficacy. Future studies should be designed to investigate which factors contribute to a positive student experience of blended learning.
Development of Predictive Maintenance Technology for Wafer Transfer Robot using Clustering Algorithm

Semiconductor equipment is closely related to production yield and should be periodically inspected to maintain the performance. However, traditional equipment maintenance methods have difficulty responding to sudden failures and economic losses due to unpredicted situation. Recently, predictive maintenance technologies have been actively studied, with many advantages, such as the ability to predict the right time of equipment maintenance in advance to ensure system stability and maximize return on capital. Economic gains and increased equipment stability are particularly important in the semiconductor industry. In this paper, we developed a predictive maintenance technique for wafer transport robots. A technology was developed to predict the failure of the robot by tracing the median values of clusters of the frequency data, which were acquired using acceleration sensors attached on the handler of the robot. By applying this system to the wafer transport robot, the simulation results showed that the time of repair can be predicted in real time.
Predicting Unsubscription from Customer's E-Mail Using Deep Learning

In recent years, the scale of E-commerce web sites and the number of users have increased remarkably. Along with that, it is required to respond promptly to requests from customers via online. In this research, we identify costumers, who want to withdraw their order by analyzing their e-mail text sent to customer support for classification model to urge operators to respond. The classification model was carried out in a convolution neural network after embedding expressions of words. We tuned the parameters in the experiment and found it possible to classify with accuracy of 79.2%. In addition, we compared the accuracy with predictive model by customer status. As a result, we obtained high accuracy compared with logistic regression models and support vector machines. From these results, it was proven that the mail document contained information indicating to resign from EC site customers.
Energy-based modelling and control of electric power systems with guaranteed stability properties

To deal with nonlinear, large scale, multidomain, systems, as power systems are, we have witnessed in the last few years an increasing interest in energy–based modeling, analysis and controller design techniques. Energy is one of the fundamental concepts in science and engineering practice, where it is common to view dynamical systems as energy-transformation devices. This perspective is particularly useful in studying complex nonlinear systems by decomposing them into simpler subsystems which, upon interconnection, add up their energies to determine the full systems behavior. This is obviously the most natural and intuitive language to represent power systems. In particular, the use of port–Hamiltonian (pH) systems has been already proven highly successful in many applications, namely for mechanical, electrical and electromechanical systems. The port-Hamiltonian systems paradigm theremore provides a solid foundation, which suggests new ways to look at power systems analysis and control problems.Based on this framework, this thesis is structured in three main steps.1 - Modelling of a generalized class of electric power systems, based on graph theory and port-Hamiltonian representation of the individual components.2 - Modelling, analysis and control of multiterminal hvdc transmission systems. With the intention to bridge the gap between theory and applications, one of the main concerns is to establish connections between existing engineering solutions, usually derived via ad hoc considerations, and the solutions stemming from theoretical analysis.3 - Additional contributions of the author in other fields of electric power systems, including traditional ac power systems an microgrids.
A Conversation with Jeff Wu

Chien-Fu Jeff Wu was born January 15, 1949, in Taiwan. He earned a B.Sc. in Mathematics from National Taiwan University in 1971, and a Ph.D. in Statistics from the University of California, Berkeley in 1976. He has been a faculty member at the University of Wisconsin, Madison (1977– 1988), the University of Waterloo (1988–1993), the University of Michigan (1995–2003; department chair 1995–8) and currently is the Coca-Cola Chair in Engineering Statistics and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology. He is known for his work on the convergence of the EM algorithm, resampling methods, nonlinear least squares, sensitivity testing and industrial statistics, including design of experiments, robust parameter design and computer experiments, and has been credited for coining the term “data science” as early as 1997. Jeff has received several awards, including the COPSS Presidents’ Award (1987), the Shewhart Medal (2008), the R. A. Fisher Lectureship (2011) and the Deming Lecturer Award (2012). He is an elected member of Academia Sinica (2000) and the National Academy of Engineering (2004), and has received many other awards and honors including an honorary doctorate from the University of Waterloo. Jeff has supervised 45 Ph.D. students to date, many of whom are active researchers in the statistical sciences. He has published more than 170 peerreviewed articles and two books. He was the second Editor of Statistica Sinica (1993–96). Jeff married Susan Chang in 1979, and they have two children, Emily and Justin. This conversation took place in Atlanta, Georgia, on April 21, 2015.
A Design of Data Path Based on CMOS Logic for a 72-Gb/s PAM-4 Transmitter in 28-nm CMOS

This paper presents a 36 GS/s data path that is based on CMOS logic. The proposed non-clocked delay generator achieves high bandwidth as well as produces near-1-UI delay by employing digitally controlled cross-coupled latches. In addition, the proposed 4-to-2 serializer with pre-charging/discharging transistors not only reduces a data-dependent jitter but also mitigates non-ideal effects such as charge injection and clock feedthrough by removing the floating nodes of the multiplexer. As a result, the 8-to-2 serializer has extremely low rms jitter of 146 fs and peak-to-peak jitter of 980 fs at the output node. Moreover, thanks to the simple architecture of the 8-to-2 serializer and the delay generator, power consumption is remarkably reduced. The data path that dissipates 21.87 mW from 1.2-V supply is implemented and laid-out in 28-nm CMOS technology.
Change in Perception of The Mandible Caused by Wearing Dentures

Purpose: Although many denture wearers often complain more about pain or irritation in their mandibular ridge mucosa, some patients do not complain pain or dullness even though they have prominet ulcers. However, no investigation has been done yet with the mandibular perception. Thus, this study aimed to investigate the influence of denture wearing on the mandibular nerve by measuring current perception threshold(CPT) and pain threshold(PT), and objectively understand the pain experienced by the denture wearers. Methods: The CPT and PT values were obtained from the left mental foramen of 40 volunteers(20 edentulous and 20 dentulous) by using the Neurometer CPT/C ® device to deliver electrical stimulation. The PT values were directly proportional to the CPT values. Results and Discussions: The results showed that edentulous subjects exhibit a change in sensory nerve response to stimulation compared with dentulous subjects. The CPT value of the edentulous subjects was significantly higher. This indicated that the sensation is blunted in these subjects. If the CPT increases, there is a possibility that the subjects will not complain of symptoms even if there is excessive contact of the denture. Those with high CPT as well as PT values are presumed to be less likely to complain of the initial symptoms, but they may later complain of symptoms such as pain. Conclusion: It suggests that perception is blunted by wearing a denture.
A Case Based Reasoning Algorithm for Enterprises' Integration of Informatization and Industrialization

The integration of informatization and industrialization is depth integration of informatization and industrialization in many fields, which is the new developing way for informatization and industrialization. It is a complicated process of integration for enterprises, which is necessary to learn from the experience of other enterprises to improve efficiency. But facing numerous cases, it is hard for enterprises to pick up the right cases, because of shorting of effective recommended algorithm in academic field and practical application. Base on the studying the existing recommend algorithm, this paper try to design new algorithm with analyzing the structure and characters of the cases. First of all, the case structure is analyzed and are classified and the information of cases are classified and graded according to the degree of integrity; secondly, AHP is used to give weights to different attributes; then, the recommended algorithm is illustrated; finally, the cases similarity are calculated and the high similarity cases are outputted to the users.
An Interdisciplinary Approach to Recording the State of Redundancy of the Source in Dentistry for Rheumatoid Diseases

An information approach based on the concept of source redundancy is used to create a mathematical model with the goal of formalizing the state of a person’s body or part of it, which facilitates signal generation. The possibility of digital processing of content with formalized transformation is shown. We can provide more than fifteen years of experience in on-board highly skilled dental care for children suffering from rheumatic diseases instead of emergency solutions. The primary algorithm was formed dental examination for these children with the opportunity to adopt an interdisciplinary communication of various specialists when installing diagnosis and treatment, especially at distant moving objects.
Automatic Red-eye Detection and Correction Method

Red-eye is the most common problem in image evaluation and correctio n. This paper presents a new efficient algorithm to detect and correct the red-e yes. The algorithm has been divided into five parts: (1) Get the improved HSI mo del using mixed color feature of the red-eyes; (2) Detect all the suspicious red regions automatically; (3) Use a filter to get the real red-eye regions automat ically; (4) Correct the red-eyes by reducing the color using the color features of the red-eye and the circumferences; (5) Gaussian smooth. To test the efficien cy, this algorithm has been realized using Visual C++ under Windows 2000 and the results show that it has fast processing speed and a good repair result.