Reviewerly/exHarmony huggingface dataset:
The risk factors of abnormal circadian rhythm of blood pressure for Stanford B aortic dissection

ObjectiveTo investigate the risk factors of abnormal circadian rhythm of blood pressure in patients with Stanford type B aortic dissection.MethodsCase information of 204 patients with Stanford type B aortic dissection admitted to vascular surgery department of the Second Xiangya hospital of Central South University from January 2016 to December 2018 were retrospectively analyzed. According to patients′ blood pressure rhythm during hospitalization, patients were divided into normal blood pressure circadian rhythm group (127 cases) and abnormal blood pressure circadian rhythm group (77 cases). Demographic information, ambulatory blood pressure monitoring results, comorbilities and medication treatment of the two groups were compared by using multivariate logistics regression analysis.ResultsThe difference of the ambulatory blood pressure monitoring results {average night systolic blood pressure [(112.90±10.00)mmHg vs (128.15±15.20)mmHg], average night diastolic blood pressure [(66.40±7.91)mmHg vs (76.10±7.97)mmHg]}, comorbilities hyperlipidemia, renal failure, obstructive sleep apnea hypopnea syndrome, smoking and the medication treatment (analgesics, hypnotics and intravenous antihypertensive medicine) were statistically significant (P<0.05); multivariate logistic regression analysis showed that obstructive sleep apnea hypopnea syndrome and renal failure were independent risk factors of abnormal blood pressure rhythm in Stanford type B aortic dissection patients. While analgesics, hypnotics and intravenous antihypertensive medicine were protective factors.ConclusionsThe risk factors of abnormal circadian rhythm of blood pressure in patients with Stanford type B aortic dissection are renal failure and obstructive sleep apnea hypopnea syndrome. Protective factors were the usage of analgesics, hypnotics and intravenous antihypertensive medicine.Key words: Aneurysm, dissecting; Aortic diseases; Blood pressure; Risk factors
PENGEMBANGAN MEDIA LAYANAN INFORMASI STUDI LANJUT BERBASIS MULTIMEDIA FLIP E-BOOK UNTUK SISWA SMA

Abstract:The research purposes is to result of media-based information service further studies flip multimedia e-book for high school students which acceptable theoretically and practices that can be seen in terms of usability, accuracy, attractiveness and ease. this research adopts a draft research and development from Borg &amp; Gall. This product development is based on the results of questionnaires and interviews with counselors and students. the result of the research are based on assessment media expert, materials expert, prospective users, and small group. of the results of the assessment it can be concluded that the flip multimedia e-book being developed fit for use and acceptable theoretical and practical.&#x0D; Keywords: Information service, further studies, flip e-book, high school students
Android 10 – The Latest Operating System From Google

The long-anticipated Android 10 operating system has finally arrived. It offers lots of new features and there have also been some changes in the way the ...
Principal component analysis with successive interval in K-Means Cluster Analysis (Study case: Poverty data 2013 in East Nusa Tenggara)

Abstract K-Means Cluster is a cluster analysis for continuous variables with the concept ofdistance used is a euclidean distancewhere that distance is used as observation variables, which are uncorrelated with each other. The case with the type of data that is correlated categorical can be solved by making categorical data into numerical data by the method called the successive interval and then used Principal Component Analysis. Applied this method in poverty data of East Nusa Tenggara Province in K-Means clusterobtained that Principal Component Analysis with Successive interval obtained variables that take effect to the cluster formation are toilet, fuel, and job.
新HSK 5급의 화제 범주와 출제의 경향성 고찰 ― 2012년, 2014년 기출문제를 중심으로

This study, based on the ‘topic syllabus’ of New HSK Test Syllabus (2015) analyzes the topic categories of the materials from the tests of the new HSK level 5 and based on the results, examines the topic tendency. First, to acknowledge that the study was based on New HSK Test Syllabus (2015) , the topic points of International Curriculum (2014) and New HSK Test Syllabus (2015) were compared. In the case of the ‘Chinese teaching topic’ category of International Curriculum (2014), school life was the core part and it was designed for the learners to select according to their level. When it comes to the ‘topic syllabus’ of New HSK Test Syllabus (2015), level-category and category-item were systematically defined in the overall workplace level. The topic category of the new HSK level 5 presupposed the learners' situation where they had to experience social life. In the new HSK level 5 questions, the highest distribution rate was the daily life. Comparing 2012 to 2014, the rate of reduction of empirical awareness was the highest. In the case of the topic categories, the new HSK level 5 tends to address questions that reflect reality or judge social values. The question items related to the everyday life, science and technology, nature and economic categories reflect reality. The question types of literary arts, empirical enlightenment, work and job, culture and education categories are determining social values. Based on distribution rates, the rate of reality-based questions were higher than that of social value-oriented questions.
Custom Collections - About C++ Templates and .NET Generics

In this chapter, I will continue to talk about fundamental aspects of implementing custom collections using the features and organization required for any .NET platform library implementation, but with a focus on generic technology.
Fixed Set Search Applied to the Traveling Salesman Problem.

In this paper we present a new population based metaheuristic called the fixed set search (FSS). The proposed approach represents a method of adding a learning mechanism to the greedy randomized adaptive search procedure (GRASP). The basic concept of FSS is to avoid focusing on specific high quality solutions but on parts or elements that such solutions have. This is done through fixing a set of elements that exist in such solutions and dedicating computational effort to finding near optimal solutions for the underlying subproblem. The simplicity of implementing the proposed method is illustrated on the traveling salesman problem. Our computational experiments show that the FSS manages to find significantly better solutions than the GRASP it is based on, the dynamic convexized method and the ant colony optimization combined with a local search.
Concept Annotation for Intelligent Textbooks

With the increased popularity of electronic textbooks, there is a growing interests in developing a new generation of "intelligent textbooks", which have the ability to guide the readers according to their learning goals and current knowledge. The intelligent textbooks extend regular textbooks by integrating machine-manipulatable knowledge such as a knowledge map or a prerequisite-outcome relationship between sections, among which, the most popular integrated knowledge is a list of unique knowledge concepts associated with each section. With the help of this concept, multiple intelligent operations, such as content linking, content recommendation or student modeling, can be performed. However, annotating a reliable set of concepts to a textbook section is a challenge. Automatic unsupervised methods for extracting key-phrases as the concepts are known to have insufficient accuracy. Manual annotation by experts is considered as a preferred approach and can be used to produce both the target outcome and the labeled data for training supervised models. However, most researchers in education domain still consider the concept annotation process as an ad-hoc activity rather than an engineering task, resulting in low-quality annotated data. In this paper, we present a textbook knowledge engineering method to obtain reliable concept annotations. The outcomes of our work include a validated knowledge engineering procedure, a code-book for technical concept annotation, and a set of concept annotations for the target textbook, which could be used as gold standard in further research.
Research Guides: Electronic Reserves (Temporary Service): Available Textbooks

This guide lists the items available while the libraries are operating under remote services.
Universities of China: Current Status and Global Development Strategy Until 2035

Introduction. Now China is completing the “State program for medium and long-term reform and development of education for 2010–2020.” The results achieved during the implementation of this program and the new strategy for the development of China’s education, including in the field of higher education and higher education institutions, are becoming a new subject of research in domestic science and require careful study. The purpose of the study is to characterize the current state of Chinese universities and identify a strategy for their development until 2035. Methods and materials. As research methods, analysis of open data sources and comparative analysis were used. The source base includes regulatory documents of the People’s Republic of China in the field of education (laws, the state program and state projects), CPC documents related to the development of the education system (reports of the party congress and plenum), information resources of the Ministry of Education of the People’s Republic of China (National Statistical Reports on Education Development for 2016–2018), data from QS World University Rankings and Times Higher Education World University Rankings for the period 2016–2020. Analysis. As a result of the reform, the gross enrollment ratio of high school education (10–12 grades) increased from 79.2% (2009) to 88.8% (2018), and higher education from 24.2% (2009) to 48.1% (2018). The fulfillment of the tasks of reforming the higher education system, including the implementation of Projects 211 and 985, by the beginning of the 13th five-year plan (2016) has enabled 85 Chinese universities to enter the world ranking THE (2016–2017). In 2016, China switched to a new strategy for the global development of higher education, embarking on the implementation of the “Project of First-Class Universities and Scientific Disciplines”. At the 19th CPC Congress (2017), this strategy was supplemented by the task of intensive development of higher education. Currently, the global development strategy for higher education and universities in the country is continuing as part of the overall modernization of education, according to which China plans to strengthen the combined power and influence of country’s education in the international arena by 2020, and by 2035 to increase the competitiveness of higher education in the context of transforming the country into a global educational power. Results. The results of the study include the following: 1) the current state of Chinese universities significantly exceeds the state of 2009 in both quantitative and qualitative indicators; 2) the modern strategy for the development of higher education is the strategy of global development of Chinese universities, aimed at their achievement of leading and first positions in the world, as well as strengthening the competitiveness of China’s higher education, contributing to the transformation of China into a world educational power in 2035.
Evaluation of Software Fault Prediction Models Considering Faultless Cases

To enhance the prediction accuracy of the number of faults, many studies proposed various prediction models. The model is built using a dataset collected in past projects, and the number of faults is predicted using the model and the data of the current project. Datasets sometimes have many data points where the dependent variable, i.e., the number of faults is zero. When a multiple linear regression model is made using the dataset, the model may not be built properly. To avoid the problem, the Tobit model is considered to be effective when predicting software faults. The model assumes that the range of a dependent variable is limited and the model is built based on the assumption. Similar to the Tobit model, the Poisson regression model assumes there are many data points whose value is zero on the dependent variable. Also, log-transformation is sometimes applied to enhance the accuracy of the model. Additionally, ensemble methods are effective to enhance prediction accuracy of the models. We evaluated the prediction accuracy of the methods separately, when the number of faults is zero and not zero. In the experiment, our proposed ensemble method showed the highest accuracy, and Pred25 was 21% when the number of faults was not zero, and it was 45% when the number was zero.
Quantum asymptotic phase reveals signatures of quantum synchronization

Synchronization of quantum nonlinear oscillators has attracted much attention recently. To characterize the quantum oscillatory dynamics, we recently proposed a fully quantum-mechanical definition of the asymptotic phase, which is a key quantity in the synchronization analysis of classical nonlinear oscillators (Kato and Nakao 2022 Chaos 32 063133). In this work, we further extend this theory and introduce multiple asymptotic phases using the eigenoperators of the adjoint Liouville superoperator of the quantum nonlinear oscillator associated with different fundamental frequencies. We analyze a quantum van der Pol oscillator with Kerr effect in the strong quantum regime and show that the system has several different fundamental frequencies. By introducing order parameters and power spectra in terms of the associated quantum asymptotic phases, we reveal that phase locking of the system with a harmonic drive at several different frequencies, an explicit quantum signature observed only in the strong quantum regime, can be interpreted as synchronization on a torus rather than a simple limit cycle.
Single spectrum image denoising via aggregation for intelligent monitoring system

Intelligent monitoring system plays an important role in construction of smart city, but suffers from noise in the captured images. Thus, it is important to remove noise for images before fedding into the intelligent monitoring system. On one hand, most of the non‐local means methods and its variants often oversmooth image details. On the other hand, the transform‐based methods (eg, NSCT) are efficient in preserving the image details (eg, edges), but often result in edge ringing. Hence, how to combine these two types of denoising methods better deserves to be studied. In this paper, we explore the optimal aggregation of the patch‐based method NLM and transform‐based method NSCT. Our method can be divided into three stages. The first stage is in the spatial domain using the NLM method to obtain one smoothing denoised estimator; the second stage is in the NSCT domain using the simple hard thresholding to obtain one edge‐preserving denoised estimator; the final stage explores various aggregations of these obtained denoised estimators to get the final denoised image. Experiments show that PBCT achieves competitive performance compared to the state‐of‐the‐art patch‐based denoising algorithms.
Solving First-Order Differential Equations of <i>Z</i>-Numbers’ Initial Value Using Radial Basic Function

In this paper, a method was proposed based on RBF for numerical solution of first-order differential equations with initial values that are valued by Z -numbers. The proposed method consists of two parts. The first part has stated the amount of limitation of the fragmentation solution, while the second part has described the assurance of the first part. The limitation section also has two parts. The first part has included the initial condition of the problem, while the second part has included the RBF network. The confidence interval was also considered as a function based on the probability function, which has calculated the confidence level of the first part (limitation). The RBF network or the radial-base grid network has three distinct layers: the input layer that is the set of elementary nodes (sensory units); the second layer is the hidden layers with high dimensions, in which the output layer that has responded to the network response and the activation patterns used in the input layer. The advantage of using RBF is that the use of this technique does not require sufficient information. It only relies on the domain and the boundary. In an example, we have showed that our proposed approach could approximate the problem with acceptable confidence.
FCN+RL: A Fully Convolutional Network followed by Refinement Layers to Offline Handwritten Signature Segmentation

Although secular, handwritten signature is one of the most reliable biometric methods used by most countries. In the last ten years, the application of technology for verification of handwritten signatures has evolved strongly, including forensic aspects. Some factors, such as the complexity of the background and the small size of the region of interest - signature pixels - increase the difficulty of the targeting task. Other factors that make it challenging are the various variations present in handwritten signatures such as location, type of ink, color and type of pen, and the type of stroke. In this work, we propose an approach to locate and extract the pixels of handwritten signatures on identification documents, without any prior information on the location of the signatures. The technique used is based on a fully convolutional encoder-decoder network combined with a block of refinement layers for the alpha channel of the predicted image. The experimental results demonstrate that the technique outputs a clean signature with higher fidelity in the lines than the traditional approaches and preservation of the pertinent characteristics to the signer's spelling. To evaluate the quality of our proposal, we use the following image similarity metrics: SSIM, SIFT, and Dice Coefficient. The qualitative and quantitative results show a significant improvement in comparison with the baseline system.
Utilizing FastText for Venue Recommendation

Venue recommendation systems model the past interactions (i.e., check-ins) of the users and recommend venues. Traditional recommendation systems employ collaborative filtering, content-based filtering or matrix factorization. Recently, vector space embedding and deep learning algorithms are also used for recommendation. In this work, I propose a method for recommending top-k venues by utilizing the sequentiality feature of check-ins and a recent vector space embedding method, namely the FastText. Our proposed method; forms groups of check-ins, learns the vector space representations of the venues and utilizes the learned embeddings to make venue recommendations. I measure the performance of the proposed method using a Foursquare check-in dataset.The results show that the proposed method performs better than the state-of-the-art methods.
The Use of Competence-Based Approach in Future Teacher Training for Educational Content Development in Mathematics and Computer Science Subject Field

Current scientific and technological advances contribute to society change-over to digital economy. The education system is imposed on a duty of new reality-adaptable personality formation. This article is focused on the issues of teaching personnel training in the context of information technologies significance in future professional activity. Consistent with new regulatory documents, there has been developed a technology of bachelor’s professional competence formation in the course of study “Pedagogic Education” with two majors: “Computer Science. Mathematics”. The competence under consideration will enable a teacher to create and use digital educational resources in his/her professional activity.
Advancing the study of endangered languages with computational tools for morphology

Though many computational tools are designed for high-resource languages, they can also benefit under-described and endangered languages. This is exemplified by our ongoing project on the description and documentation of Asama, an endangered language of Japan. We focus on the use of finite-state transducers to implement a grammar of verb morphology. This computational implementation enabled us to directly check the accuracy of our analysis, correct mistakes, and fill gaps in the description. These tools were also put to use for improving and speeding up the production of interlinear glossed texts with standard tools used by fieldworkers. Such tools also provide a straightforward mean to quantitatively explore the complexity of morphological systems
Multitask Hopfield Networks

Multitask algorithms typically use task similarity information as a bias to speed up and improve the performance of learning processes. Tasks are learned jointly, sharing information across them, in order to construct models more accurate than those learned separately over single tasks. In this contribution, we present the first multitask model, to our knowledge, based on Hopfield Networks (HNs), named HoMTask. We show that by appropriately building a unique HN embedding all tasks, a more robust and effective classification model can be learned. HoMTask is a transductive semi-supervised parametric HN, that minimizes an energy function extended to all nodes and to all tasks under study. We provide theoretical evidence that the optimal parameters automatically estimated by HoMTask make coherent the model itself with the prior knowledge (connection weights and node labels). The convergence properties of HNs are preserved, and the fixed point reached by the network dynamics gives rise to the prediction of unlabeled nodes. The proposed model improves the classification abilities of singletask HNs on a preliminary benchmark comparison, and achieves competitive performance with state-of-the-art semi-supervised graph-based algorithms.
Cannabis users turn to darkweb as Covid-19 lockdown hits supply lines.

Cannabis users have increasingly turned to the darkweb to source the drug as lockdowns across Europe affect traditional supply lines, new research has found......