Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Generation of Russian News Headlines

Text summarization is one of the key Natural Language Processing tasks. Automated text summarization has the potential to save time when creating reviews, abstracts etc. of the texts across multiple domains. Automatic headline generation is a challenging kind of text summarization. Basically, the distinction between extractive and abstractive summarization methods is drawn. Application of the extractive summarization techniques results in the extraction of relevant words or sentences from the original text. Abstractive summarization models synthesize a summary in which some of its material is not present in the input document . This paper deals with the fine-tuning the pretrained model based on Transformer architecture for the task of generation of Russian news headlines. Experiments discussed were carried out for the new dataset of Russian news which was automatically compiled from the “Bumaga” website. The paper contains the quantitative evaluation results using BLEU und ROUGE metrics as well as the human evaluation results. Finally, the paper presents error analysis and discussion of particular contexts.
Can Computers Outperform Humans in Detecting User Zone-Outs? Implications for Intelligent Interfaces

The ability to identify whether a user is “zoning out” (mind wandering) from video has many HCI (e.g., distance learning, high-stakes vigilance tasks). However, it remains unknown how well humans can perform this task, how they compare to automatic computerized approaches, and how a fusion of the two might improve accuracy. We analyzed videos of users’ faces and upper bodies recorded 10s prior to self-reported mind wandering (i.e., ground truth) while they engaged in a computerized reading task. We found that a state-of-the-art machine learning model had comparable accuracy to aggregated judgments of nine untrained human observers (area under receiver operating characteristic curve [AUC] = .598 versus .589). A fusion of the two (AUC = .644) outperformed each, presumably because each focused on complementary cues. Furthermore, adding more humans beyond 3–4 observers yielded diminishing returns. We discuss implications of human–computer fusion as a means to improve accuracy in complex tasks.
Structure dynamic characteristic analysis of electromagnetic rail launcher

Based on the new idea of electromagnetic rail launcher,the dynamic model of electromagnetic rail launcher was established.And the electromagnetic rail launcher was simplified as an infinity long Bernoulli-Euler beam which was fixed on a flexible support.The dynamic equation was given by some adequacy assumptions.Based on Fourier transform,the electromagnetic rail launcher critical speed and orbit dynamic characteristic were obtained.Finally,how the armature velocity,rail elastic modulus,rail density,rail section moment of inertia and other parameters affect the dynamic characteristic of electromagnetic rail launcher is investigated using finite element analysis software.The result showed that the rail deformation was the largest at the armature critical speed.The research work gives theoretic support to the structure design and vibration control of electromagnetic rail launcher.
The Cut Effect of a Gear Wave Wall on Air Shock Wave

The cut effect of gear wave wall on explosion in air is analyzed. The results show that the gear wave wall of certain height and thickness around the blast source can reduce the pressure of peak value by 20%～30% away from air shock wave after the wall. Mean while, the interaction between shock wave and gear wave wall has been calculated with the numerical simulation method.And initial development at the explosive site of barrier around the blast source, as well as entire spread course has been obtained by the numberical simulation. The calculated result basically coincides with the experimental results.
A methodology for assessing the seismic risk of buildings

Many infrastructure networks rely on each other to deliver utilities and services to the community. In the event of a disaster, these networks can sustain significant damage. It is therefore important to identify interdependencies among networks to mitigate the disaster consequences. In 2003, Public Safety Canada (PSC) and NSERC initiated the Joint Infrastructure Interdependencies Research Program (JIIRP) for this purpose. The research was carried out at six Universities across Canada including the University of British Columbia (UBC). The aim of JIIRP at UBC was to study infrastructure interdependencies during disasters in order to aid in decision making. This involved the development disaster simulation methodology and tool, and the implementation of a case study. UBC's Point Grey campus was used as case study. The campus is located in southwestern British Columbia, a known seismic zone, therefore earthquake disaster scenario was chosen. Reasonable estimations of the expected seismic damage and losses are required in order to simulate a realistic disaster scenario. For this reason, in this thesis, seismic risk assessment was carried out for the buildings at UBC. This involved the development of a building database, the assessment of the expected level of damage to the structural and nonstructural building components, and the estimation of monetary, human and functionality losses. Buildings in the database were classified into prototypes and the damage was estimated for several levels of intensity using damage probability matrices. As expected, the most vulnerable buildings on campus were those containing unreinforced masonry. These buildings make up 7% of the buildings on campus. The least vulnerable buildings were multi-family residential wood buildings which account for 27% of the buildings on campus. Losses were estimated following the damage assessments. Casualties were estimated for three times of day. 2PM was determined to be the critical time of day the campus population is the greatest at this time. Monetary loss and functionality trends were examined with respect to earthquake intensity and it was shown that for moderate intensity earthquakes, the losses depend primarily on nonstructural damage, while structural damage plays the most important role for higher intensities.
Digitizing Mathematics and Science Learning: What Do We Need to Prepare?

Massive disruption in a short time has occurred due to the Global Pandemic of Covid-19. Digitization of learning has been inevitable at all levels of education after the pandemic forced us to close all educational institutions. This qualitative study aimed to describe perception and experience of teachers in secondary schools related to the digitization of education in aspects of learning implementation. Data were collected using an open-ended questionnaire which was completed online by 61 teachers in the fields of science and mathematics at the secondary schools. The data were analysed by conducting data reduction, verification and drawing conclusion. The results show that the teachers share their positive perception of the digitization of learning. Availability of devices and support system to digitized learning, such as curriculum, learning management system, internet connection, and electricity sources was the main obstacle to digitize learning so that it must be prepared immediately. Furthermore, knowledge about digital learning and strengthening of character education also needs to be prepared for educators and students in order to digitize math and science learning.
Thermodynamic Analysis and Calculation of the Drying and Heating System of Automatic Stirring Equipment

Received: 17 August 2021 Accepted: 3 November 2021 The drying and heating system (DHS) is the core component of automatic stirring equipment, so analyzing its thermodynamics is crucial for improving the efficiency of the equipment. However, existing empirical thermodynamic formulas generally take certain working conditions as prerequisites, and substituting relevant parameters of DHS into calculation can cause large errors. In view of this problem, this paper attempts to perform thermodynamic analysis and calculation on the DHS of automatic stirring equipment. At first, the material ratio of the automatic stirring equipment was analyzed in the text, and the drying and heating process of mixture was divided into three stages: mixture preheating, mixture drying, and heating mixture to the working temperature. Then, the heat consumption of DHS, the heat consumption of fuel combustion, the consumption rate of the fuel, and the heat efficiency of DHS were measured and calculated. At last, the thermodynamic analysis results of DHS of automatic stirring equipment were given, and the measurement and calculation methods adopted in the paper were proved to be effective.
Expectation and Reality: International Students' Motivations and Motivational Adjustments to Sustain Academic Journey in Chinese Universities

Considering the increasing influx of international students to Chinese universities in recent decades, it is surprising to find that few empirical research, especially longitudinal ones, have been conducted in exploring the motivation of international students in China. To fill up the existing gap, this study explored and tracked international students' motivations dynamically. Mixed research design, such as surveys, reflective journals, and interviews, was employed in this study. Data were collected from 671 international students and three teachers in three Chinese universities in Zhejiang province, mainland China on a longitudinal basis. The present study found that international students' motivation could be discussed with considerations to the following two different phases: preliminary phase before they come to China and follow-up phase when they are in China. This study found that the integrative understanding of the external pulling force and the self-motivated pushing force plays a vital role in answering international students' motivations to China. International students were driven more by the self-motivated pushing force than the external pulling force in selecting China as their study destinations. Moreover, international students experienced motivational changes when their expectations conflict with reality and their positive motivational adjustments and social interaction were important to the sustainability of their academic journey. Moreover, this study provides implications for the government, universities and international students in the aspects of policymaking, education and application.
Predicting Elevated TSH Levels in the Physical Examination Population With a Machine Learning Model

Objective The purpose of this study was to predict elevated TSH levels by developing an effective machine learning model based on large-scale physical examination results. Methods Subjects who underwent general physical examinations from January 2015 to December 2019 were enrolled in this study. A total of 21 clinical parameters were analyzed, including six demographic parameters (sex, age, etc.) and 15 laboratory parameters (thyroid peroxidase antibody (TPO-Ab), thyroglobulin antibody (TG-Ab), etc.). The risk factors for elevated TSH levels in the univariate and multivariate Logistic analyses were used to construct machine learning models. Four machine learning models were trained to predict the outcome of elevated TSH levels one year/two years after patient enrollment, including decision tree (DT), linear regression (LR), eXtreme Gradient boosting (XGBoost), and support vector machine (SVM). Feature importance was calculated in the machine learning models to show which parameter plays a vital role in predicting elevated TSH levels. Results A total of 12,735 individuals were enrolled in this study. Univariate and multivariate Logistic regression analyses showed that elevated TSH levels were significantly correlated with gender, FT3/FT4, total cholesterol (TC), TPO-Ab, Tg-Ab, creatinine (Cr), and triglycerides (TG). Among the four machine learning models, XGBoost performed best in the one-year task of predicting elevated TSH levels (AUC (0.87(+/- 0.03))). The most critical feature in this model was FT3/FT4, followed by TPO-Ab and other clinical parameters. In the two-year task of predicting TSH levels, none of the four models performed well. Conclusions In this study, we trained an effective XGBoost model for predicting elevated TSH levels one year after patient enrollment. The measurement of FT3 and FT4 could provide an early warning of elevated TSH levels to prevent relative thyroid diseases.
Inhibitory Control and the Structural Parcelation of the Right Inferior Frontal Gyrus

The right inferior frontal gyrus (rIFG) has most strongly, although not exclusively, been associated with response inhibition, not least based on covariations of behavioral performance measures and local grey matter characteristics. However, the white matter microstructure of the rIFG as well as its connectivity has been less in focus, especially when it comes to the consideration of potential subdivisions within this area. The present study reconstructed the structural connections of the three main subregions of the rIFG (i.e. pars opercularis, pars triangularis and pars orbitalis) using diffusion tensor imaging, and further assessed their associations with behavioral measures of inhibitory control. The results revealed a marked heterogeneity of the three subregions with respect to the pattern and extent of their connections, with the pars orbitalis showing the most widespread inter-regional connectivity, while the pars opercularis showed the least amount of connections. When relating behavioral performance measures of a stop signal task to brain structure, the data indicated a differential association of dorsal and ventral opercular connectivity with the go reaction time and the stopping accuracy, respectively.
Case Report: DRESS Syndrome Induced by Two Antituberculosis Drugs in an 8-Year-Old Girl

DRESS syndrome is defined as drug-induced hypersensitivity syndrome with rash, eosinophilia, and systemic symptoms. This syndrome is mostly associated with anticonvulsants, antibacterial and anti-inflammatory drugs. DRESS syndrome is a rare disease and is more frequently seen in adults. We present the first case report of DRESS syndrome in an 8-year-old girl, after 3 months of treatment with isoniazid and rifampicin. After discontinuation of drugs and a short course of prednisolone the girl recovered. After 5 years of follow-up, she is healthy and has no complaints but patch tests with isoniazid and rifampicin remain positive. The reported case emphasizes the importance of thorough medical history and including drug reactions in differential diagnosis.
Identification of Human Walking Balance Controller Based on COM-ZMP Model of Humanoid Robot

The purpose of this research is to build a technology that enables wearable robotic systems that support human movement to maintain stable balance. By expanding our knowledge of conventional human gait analysis technology and robotics technology, we will build a technology that can estimate the state of human balance. In order to build a technology for estimating the human balance state based on the balance control technology of humanoid robots, we conducted joint research with Osaka University. We applied our knowledge of humanoid robot control to human stepping and braking motions, and confirmed the effectiveness of the balance control model using data measured by a motion capture system and a floor reaction force sensor system. In order to build a technology for estimating the human balance state based on the balance control technology of humanoid robots, we conducted joint research with Osaka University. We applied our knowledge of humanoid robot control to human stepping and braking motions to build a human balance control model. We confirmed the effectiveness of the balance control model using data measured by a motion capture system and a floor reaction force sensor system. In order to understand the state of human walking, the human walking motion was measured by motion capture and analyzed in detail. Following the norms of gait analysis techniques, we extended the balance control model of human foot-stepping and braking motions to a gait model that includes continuous straight-line walking and change of direction during walking. The effectiveness of the constructed balance control model was confirmed using a motion capture system and a floor reaction force sensor system.
Effects and Mechanism of Different Phospholipid Diets on Ovary Development in Female Broodstock Pacific White Shrimp, Litopenaeus vannamei

Research on nutrition and feed development for the broodstock of the Pacific white shrimp, Litopenaeus vannamei, is rare, and a poor broodstock quality is a critical factor restricting the seed supply in shrimp farming. As an essential nutrient for the gonadal development of L. vannamei, one control diet (no phospholipid) and three typical phospholipids (soybean lecithin, egg yolk lecithin, and krill oil) were evaluated in a semipurified diet of 4% phospholipid for a 28-day trial (initial weight 34.7 ± 4.2 g). Dietary phospholipid supplementation significantly promoted the ovarian maturation of female L. vannamei. Compared with soybean lecithin and egg yolk lecithin, krill oil showed the best positive results. Shrimp fed with a diet krill oil has obtained a significantly higher gonadosomatic index, yolk particle deposition, lipid accumulation, and estrogen secretion than from other sources. Ovary lipidomic analysis showed that the krill oil enriched the lipid composition of the ovary. The “glycerophospholipid metabolism” and “sphingolipid metabolism” pathways were significantly varied via topological pathway analysis. Genes and hub genes, with significantly different expression levels, were significantly enriched in the “fatty acid metabolism pathway,” “glycerophospholipid metabolism,” and “arachidonic acid metabolism” pathways by transcriptomic analysis. Correlation analysis of the transcriptome and lipidomics showed that the differential gene “hormone-sensitive lipase-like” (HSL) was positively correlated with various lipids [triglycerides (TG), phosphatidic acid (PA), phosphatidylserine (P), phosphatidylethanolamine (PE), glucosylceramide (GlcCer), phosphatidylglycerol (PG), and phosphatidylinositol (PI)] but was negatively correlated with diacylglycerol (DG), lysophosphatidylethanolamine (LPE), and sphingomyelin (SM). In conclusion, the dietary phospholipids, especially krill oil as a phospholipid source, can promote the development of L. vannamei ovaries by increasing the accumulation of nutrients such as triglycerides and sterols, and the secretion of estrogen or related hormones, such as estradiol and methylfarneside, by affecting the metabolism of glycerol phospholipids and some key fatty acids. Graphical Abstract
Cost-Effectiveness of Sequential Teriparatide/Zoledronic Acid Compared With Zoledronic Acid Monotherapy for Postmenopausal Osteoporotic Women in China

Objective We aimed to assess the cost-effectiveness of sequential teriparatide/zoledronic acid relative to zoledronic acid monotherapy for postmenopausal osteoporotic women in China. Methods A previously validated Markov microsimulation model was updated to examine the cost-effectiveness of daily subcutaneous teriparatide for 2 years followed by annual intravenous zoledronic acid for 3 years (sequential teriparatide/zoledronic acid), compared with zoledronic acid monotherapy for 3 years in Chinese women with postmenopausal osteoporosis at ages 65, 70, 75, and 80 from the health care payer perspective. Results The incremental cost-effectiveness ratios (ICERs) (US dollars [$] per quality-adjusted life-year [QALY]) of sequential teriparatide/zoledronic acid vs. zoledronic acid monotherapy was $173,223/QALY at age 65 years, which was much higher than the pre-determined willingness-to-pay (WTP) threshold of $ 31,512/QALY, and the results were similar at other ages. In one-way sensitivity analyses, the two most impactful parameters were the cost of teriparatide and the residual effects of the medications included in this study. Sequential teriparatide/zoledronic acid became cost-effective at age 80 with the cost of teriparatide reduced by 50%. Without the residual effect, the ICER increased to $257,982/QALY. Probabilistic sensitivity analyses shown that the probabilities of zoledronic acid monotherapy being cost-effective were 100% at a WTP of $31,512/QALY. Conclusions Among Chinese women with postmenopausal osteoporosis, sequential teriparatide/zoledronic acid was not cost-effective unless the cost of teriparatide was reduced by 50% only for the participants over 80 years.
Identifying Multiple Influential Spreaders in Complex Networks by Considering the Dispersion of Nodes

Identifying multiple influential spreaders, which relates to finding k (k > 1) nodes with the most significant influence, is of great importance both in theoretical and practical applications. It is usually formulated as a node-ranking problem and addressed by sorting spreaders’ influence as measured based on the topological structure of interactions or propagation process of spreaders. However, ranking-based algorithms may not guarantee that the selected spreaders have the maximum influence, as these nodes may be adjacent, and thus play redundant roles in the propagation process. We propose three new algorithms to select multiple spreaders by taking into account the dispersion of nodes in the following ways: (1) improving a well-performed local index rank (LIR) algorithm by extending its key concept of the local index (an index measures how many of a node’s neighbors have a higher degree) from first-to second-order neighbors; (2) combining the LIR and independent set (IS) methods, which is a generalization of the coloring problem for complex networks and can ensure the selected nodes are non-adjacent if they have the same color; (3) combining the improved second-order LIR method and IS method so as to make the selected spreaders more disperse. We evaluate the proposed methods against six baseline methods on 10 synthetic networks and five real networks based on the classic susceptible-infected-recovered (SIR) model. The experimental results show that our proposed methods can identify nodes that are more influential. This suggests that taking into account the distances between nodes may aid in the identification of multiple influential spreaders.
Case Report: Biventricular Noncompaction Cardiomyopathy With Pulmonary Stenosis and Bradycardia in a Fetus With KCNH2 Mutation

Background: Left ventricular noncompaction (LVNC) is a rare cardiomyopathy, long QT syndrome (LQTS) is a rare ion channel disease, and simultaneous occurrence of both is even rarer. Further clinical reports and studies are needed to identify the association between LVNC and LQTS and the underlying mechanism. Methods and Results: A 26-year-old primigravida was referred at 25 weeks gestation for prenatal echocardiography due to fetal bradycardia detected during the routine ultrasound examination. The echocardiographic findings were consistent with biventricular noncompaction cardiomyopathy (BVNC) with pulmonary stenosis and suspected LQTS. After detailed counseling, the couple decided to terminate the pregnancy, and subsequent postmortem examination confirmed BVNC and pulmonary stenosis. Then, A trio (fetus and the parents) whole-exome sequencing (WES) and copy number variation sequencing (CNV-seq) were performed. CNV-seq identified no aneuploidy or pathogenic CNV. A de novo missense variant in KCNH2 (NM_000238.3:c.1847A > G,p.Tyr616Cys) was identified by WES. This KCNH2 missense mutation was classified as pathogenic according to the American College of Medical Genetics and Genomics and the Association for Molecular Pathology variant interpretation guidelines. Conclusion: We report the first prenatal case of KCNH2 mutation presenting with LVNC combined with bradycardia and second-degree 2:1 atrioventricular block. Importantly, this case reminds clinicians to systematically search ion channel gene mutations in patients with LVNC and arrhythmia.