bluuebunny/crossref_metadata_2025 huggingface dataset:
Bayesian Network Structure Learning and Application
Authors: Zhang Liwei , Liu Dayou , Wang Zheng , Wang Xinlu
Published: June 2022

With the continuous development of artificial intelligence technology and information technology, a large number of background data are constantly generated. How to obtain effective and useful data in a large and complex data group becomes important and meaningful. The traditional Bayesian network can represent the probability distribution of data variables from a large number of data based on graphical models. It has relatively clear and reliable reasoning ability and decision-making mechanism. However, the traditional Bayesian network structure has serious shortcomings in the recognition accuracy of corresponding key data, so the efficiency of the corresponding algorithm is seriously low. Based on this, this study adds an adaptive genetic algorithm with causality to the original Bayesian structure, so as to optimize the strategy of its structure operation, quantitatively describe the order of the corresponding data nodes, creatively arrange the corresponding data nodes in order by using the node priority, and initialize the initial architecture of Bayesian network based on this. Finally, the network is initialized through information exchange and data score correction, so as to get the final learning results. In this study, the convolution neural network algorithm in a database is verified in the experiment. The experimental results show that the accuracy of the experimental results given by the Bayesian network structure proposed in this study is about 10% higher than the traditional accuracy, and its corresponding learning results basically cover the important algorithms, hypotheses, and verification of convolution neural network, from this level; the algorithm proposed in this study has obvious advantages in bibliometrics.
A Diffuse Reflection Approach for Detection of Surface Defect Using Machine Learning
Authors: Hui Meng , Li Mingyong
Published: June 2022

Diffuse reflection occurs when light, further waves, or particles are reflected off a surface in such a way that a ray encountered on the surface is dispersed at several angles instead of one as in specular reflection. With the rapid development of modern industry, irregular diffuse reflection may appear due to the particles on the surface, such as frosted paint surfaces, making the defect information easy to be covered up by scattered light, preventing the defect from being detected, and reducing detection accuracy. Therefore, this paper aims to deeply explore the diffuse reflection surface defect detection approach based on machine learning. The Gray code and four-step phase shift technique are used to resolve the absolute phase of a reflection image while the image defect is determined by converting the absolute phase's gradient. The automatic edge finding algorithm is then used to obtain the image vertex of the sample to be measured, the affine transformation is used for attitude correction, and the module matching approach is used to locate the diffuse reflection surface defect. The gray morphological opening and closing operation is used for the original image to obtain the morphology and position information of the defect. Finally, Adam optimizer is chosen as the gradient descent algorithm's optimizer. Experimental results show that the proposed approach can effectively improve the accuracy of diffuse reflection surface defect detection and reduce the economic cost of defect detection, which has a certain practical value.
Clinical Efficacy of Xueshuantong plus Urokinase in the Treatment of Sudden Deafness
Authors: Wang Yanling , Wang Jian , Chen Xiulan
Published: June 2022

Objective. To investigate the clinical effect of Xueshuantong combined with urokinase in the treatment of sudden deafness. Methods. A total of 90 patients with sudden deafness who were treated in South China Hospital affiliated to Shenzhen University from June 2019 to August 2020 were recruited and assigned (1 : 1) into the control group (n = 45, urokinase) and the experimental group (n = 45, Xueshuantong plus urokinase) according to the different treatment methods. The clinical treatment effect, the degree of tinnitus, the average auditory valve of the damaged frequency, and the changes in hemorheology (plasma viscosity, whole blood high-shear reduced viscosity, whole blood low-shear reduced viscosity, hematocrit, and fibrinogen) were compared between the two groups of patients. Results. The treatment with urokinase and Xueshuangtong injection in the experimental group resulted in a significantly higher clinical treatment effect when compared with the treatment in the control group (

P
<
0.05

). After treatment, the degree of tinnitus and the average auditory valve of the damaged frequency in the experimental group were significantly lower than those in the control group (

P
<
0.05

). The levels of hemorheology (plasma viscosity, whole blood high-shear reduced viscosity, whole blood low-shear reduced viscosity, hematocrit, and fibrinogen) in the experimental group after treatment were significantly lower than those in the control group (

P
<
0.05

). Conclusion. The clinical effect of Xueshuantong combined with urokinase in the treatment of patients with sudden deafness is remarkable, and it can effectively improve the hearing level and hemorheology-related indexes of patients, and it thus merits clinical application.
Effects of Different Doses of Dexmedetomidine Combined with Thoracic Paravertebral Nerve Block Anesthesia on Agitation and Hemodynamics in Patients Undergoing Thoracotomy during Recovery
Authors: Zu Baoli , Yang Yong , Shi Shengchi
Published: June 2022

Objective. To investigate the effect of different doses of dexmedetomidine combined with thoracic paravertebral nerve block anesthesia on agitation and hemodynamics in patients undergoing thoracotomy during recovery. Methods. One hundred patients who underwent thoracotomy in our hospital from August 2018 to April 2021 were enrolled and assigned (1 : 1 : 1 : 1) into 4 groups via the random number table method. The patients in the control group were treated with double-lumen tube general anesthesia + ropivacaine for thoracic paravertebral nerve block anesthesia; patients in experimental group A received double-lumen general anesthesia +0.5 μg·kg−1 dexmedetomidine + ropivacaine for thoracic paravertebral nerve block anesthesia; patients in experimental group B received thoracic paravertebral nerve block anesthesia with double-lumen general anesthesia +1.0 μg·kg−1 dexmedetomidine + ropivacaine; patients in experimental group C received thoracic paravertebral nerve block anesthesia with double-lumen general anesthesia +1.5 μg·kg−1 dexmedetomidine + ropivacaine. The postoperative recovery time and visual analog scale (VAS), level of hemodynamics (heart rate (HR), mean arterial pressure (MAP)), agitation during the recovery period, and complications were compared amongst the 4 groups of patients at different time points. Results. The postoperative VAS scores of patients in groups B2 and B3 were slightly lower than those of patients in groups A and B1, but a one-way analysis of variance revealed no statistical difference in the postoperative recovery time and VAS pain scores of the four groups (

P
>
0.05

), and the recovery time of patients in experimental group C was slightly higher than that of patients in group B2. At T0 and T1, there was no significant difference in the levels of HR and MAP among the four groups (

P
>
0.05

). The levels of HR and MAP of the patients in groups B2 and B3 were significantly different from the patients in the control group and experimental group A at T2 and T3 (

P
<
0.05

). The patients in experimental group B and experimental group C showed better outcomes than those in the control group and experimental group A in the assessment of agitation during the recovery period (

P
<
0.05

). There was no significant difference in the incidence of complications among the four groups (

P
>
0.05

). Conclusion. In line with the principle of preference for a small anesthesia dose, 1.0 μg·kg−1 dose of dexmedetomidine combined with ropivacaine produces a pronounced efficacy in patients undergoing thoracotomy. It effectively controls the occurrence of agitation during the recovery period and maintains the stability of the patient’s hemodynamics, with a high clinical safety profile.
Virtual Reality and Its Application for Producing TV Programs
Authors: Lin Liya
Published: June 2022

This paper aims to conduct an in-depth study on the effective application of virtual reality technology in TV program production. To begin, construct the three-dimensional animation system’s overall structure, determine the animation system’s user interface, and establish the three-dimensional animation system for TV program production. Second, software like YOLOv3 and ResNet-50 network is used for identification and facial recognition. Then, the pixel cross-support window is built using the adaptive stereo matching method. The adaptive filter window is built using the horizontal expansion of the cross-support window. For the successful application of virtual reality technology in TV program creation, the aggregation is completed by regional filtering, and the final parallax image is obtained by parallax selection and parallax optimization. This technology has the ability to improve the visual effect and quality of TV programs, increase the amount of information in programs’ content, and shorten the production cycle of the program in the context of the gradual development of science and technology and the new technology period. In comparison to other approaches, simulation experiments demonstrate that the proposed method has the potential to increase the quality and attractiveness of TV programs and meet the psychological demand of viewers.
[Retracted] Analysis of O2O Teaching Assistant Mode of College English in MOOC Environment
Authors: Zhang Yan
Published: June 2022

In the past, teaching assistants always focused on the physical environment and actions, resulting in a lot of carbon emissions and material waste. This paper discusses the online and offline integration of college English teaching assistance model, which helps inspire the significance of saving energy and reduce carbon emissions in higher education environment. Our country has been putting education informationization in a very important position. In recent years, the demand of college education informatization is more urgent, which calls for the reform of college classroom teaching mode. “O2O teaching mode” is a teaching mode that integrates online and offline teaching, uses computer information network technology, makes use of network media, and relies on online MOOC platform to carry out online network learning and offline face‐to‐face classroom learning. “O2O teaching mode” has the characteristics of openness, interactivity, individuality, convenience, and generation, which is conducive to changing students’ learning mode and teachers’ teaching mode, realizing resource sharing, and improving teaching quality. English is a practical course. In the practice of modern English teaching, it is necessary to maintain and develop the advantages of traditional humanistic teaching, and to make efficient use of the media resources and network resources under the condition of modern educational technology, so as to ensure that English learners have active and sufficient practice opportunities. With the popularity of the Internet and the development of MOOC, more and more English learners begin to learn independently online. English online learning platform has become an indispensable tool for independent learning and daily English teaching. Especially when the Internet is connected with the campus network, the role of the network has changed from teaching auxiliary resources to teaching platform, making online learning become a new way of learning, realizing the interaction of English teaching in the network environment.
What Determines the Behavior of a System and How to Design a Satisfactory System for an Expected Behavior
Authors: Lin Fuyong , Du Chunlei , Huang Cheng
Published: June 2022

Systems are everywhere around us, such as products, production lines, the Internet, companies, schools, hospitals, airports, communities, cities, countries, governments, and military forces. System researchers and engineers always strive to achieve their desired system behaviors. Thus, this paper aims to solve two fundamental problems of systems engineering: what determines the behavior of a system and how to design a satisfactory system for the expected behavior. First, we determine the dimensions of a relationship flow, such as information flow, material flow, and capital flow. Second, we develop new theorems and propositions to solve the first problem. For example, they show that, for a given behavior of a system, if the dominant subsystem of the behavior has the basic level for the behavior, the behavior is only determined by its input flow and relationship flows at or above the basic level, all of which are collectively referred to as total relationship flow (TRF). Third, we develop a relationship flow diagram which is of great significance to system design, just as a circuit diagram to circuit design, and a TRF-oriented system design framework to solve the second problem. In order to show how the framework works, we apply it step by step to the schematic design of an airport system for the required passenger departure procedure service behavior, and get a system example; using this framework to design a system will greatly simplify the complexity of development and improve the maintainability of the system. Therefore, our findings provide a new theory for systems engineering and improve its methods and tools systematically.
Iatrogenic Infective Endocarditis in Hemodialysis Patients: A Case Report and Review of the Literature
Authors: Oullaï Ali , Cubilier Edouard , Salaouatchi Mohamed Tayeb , Taghavi Maxime , Zouggari Yasmin , Nortier Joëlle , Mesquita Maria Do Carmo Filomena
Published: June 2022

Foreign bodies such as implanted cardiac devices are susceptible to infections and may be involved in infective endocarditis. Exposure to pathogens, by frequent use of intravascular accesses for hemodialysis (i.e., catheters or fistulas), combined with high rates of degenerative heart valve diseases in hemodialysis patients, both favor the development of infective endocarditis in this population. The mitral and aortic valves are predominantly implicated in endocardial infections. The involvement of both mitral and tricuspid valves is rare in the general population but can occur in hemodialysis patients with implanted cardiac devices. Infective endocarditis is associated with high morbidity and mortality rates among hemodialysis patients, mostly because of the complications of septic emboli. Prevention, prophylaxis, and early diagnosis of endocarditis can be lifesaving in this fragile population. We report a case of right and left heart methicillin-sensitive Staphylococcus aureus endocarditis with cerebral septic emboli in an elderly hemodialysis patient carrier of an arteriovenous fistula and an ipsilateral nonleadless pacemaker.
Innovation Service Platform of Small and Medium-Sized Microenterprises Based on Social Perception and Neural Network Algorithm
Authors: Shao Jishu , Yu Zuwei , Huang Tao
Published: June 2022

In recent years, the number and scale of small, medium-sized, and micro enterprises have continued to increase, which is the main force to promote the development of China’s national economy, the guarantee of China’s rapid and stable economic development, and has a direct impact on social stability and people’s livelihood. In China’s economic growth, small, medium-sized, and micro businesses play a critical role. However, several limitations limit their current growth stage, preventing them from expanding their size, such as resource and environmental limits, an inappropriate industrial structure, and institutional issues, such as severe market rivalry. To address this issue, this paper develops a micro innovation service platform for small and medium-sized businesses, offers a variety of services to small and medium-sized businesses, fully realizes data sharing and transmission in all aspects using social perception and neural network algorithms, and effectively utilizes social attributes on mobile nodes to assist each node. Also, it investigates the impact of the innovation service platform for small and medium-sized micro firms in practice. After the construction of the innovation service platform for small and medium-sized micro enterprises in 2018, it analyzes the number of transaction projects of platform technology transfer, technology development, technical consultation, and technical services from 2018 to 2020 and analyzes the transaction volume of projects in four aspects. The results show that they have significantly improved, which plays an important role in realizing the transformation of achievements and improving the innovation ability of small and medium-sized micro enterprises in China. At the same time, according to the investigation and analysis of 8 innovative service platforms in the western region, 25% of them have developed well.
Effect of Perioperative Comprehensive Nursing Intervention on Transcatheter Arterial Chemoembolization in Patients with Primary Hepatic Carcinoma
Authors: Hu Min , Fan Ziyan , Han Yu
Published: June 2022

Objective. To study and analyze the effect of perioperative comprehensive nursing intervention on transcatheter arterial chemoembolization (TACE) in patients with primary hepatic carcinoma (PHC). Methods. One hundred and ten patients with PHC diagnosed in our hospital from May 2019 to January 2022 were randomly selected and divided into a control group (n = 55) and an observation group (n = 55) by random number sorting according to odd and even numbers. Patients in the control group received conventional nursing interventions and those in the observation group received comprehensive nursing interventions. The two groups were compared in terms of surgical status, quality of life (QoL), and nursing satisfaction. Results. The operation time, postoperative bed rest time, and hospital stay in the observation group were significantly (

P
<
0.05

) shorter than those in the control group; the observation group had significantly (

P
<
0.05

) higher scores of quality of life, including somatic function, emotional function, role function, social function, and cognitive function than the control group; chemotherapy adverse reactions including fever, abdominal pain, urinary retention, and gastrointestinal reactions in the observation group were significantly less than those in the control group (

P
<
0.05

); the total incidence of complications in the observation group was significantly (

P
<
0.05

) lower than that in the control group. The total satisfaction with nursing care in the observation group was significantly (

P
<
0.05

) higher than that in the control group. Conclusion. The perioperative application of comprehensive nursing intervention in TACE for patients with PHC aids in the smooth operation, improves patients’ QoL, lowers the risk of chemotherapy reactions and complications, and enhances patient satisfaction and nursing quality. These advantages justify a wider perioperative application of comprehensive nursing intervention in TACE clinical practice.
Behavior Pattern Mining from Traffic and Its Application to Network Anomaly Detection
Authors: Meng Yongwei , Qin Tao , Li Shancang , Wang Pinghui
Published: June 2022

Accurately detecting and identifying abnormal behaviors on the Internet are a challenging task. In this work, an anomaly detection scheme is proposed that employs the behavior attribute matrix and adjacency matrix to characterize user behavior patterns. Then, anomaly detection is conducted by analyzing the residual matrix. By analyzing network traffic and anomaly characteristics, we construct the behavior attribute matrix, which incorporates seven features that characterize user behavior patterns. To include the effects of network environment, we employ the similarity between IP addresses to form the adjacency matrix. Further, we employ CUR matrix decomposition to mine the changing trends of the matrices and obtain the residual pattern characteristics that are used to detect anomalies. To validate the effectiveness and accuracy of the proposed scheme, two datasets are used: (1) the public MAWI dataset, collected from the WIDE backbone network, which is used to validate accuracy; (2) the campus network dataset, collected from the northwest center of Chinese Education and Research Network (CERNET), which is used to verify practicability. The experimental results demonstrate that the proposed scheme can not only accurately detect and identify abnormal behaviors but also trace the source of anomalies.
Modeling and Simulation of English Speech Optimization Teaching Recognition Based on Intelligent Edge Detection Algorithm
Authors: Tang Yuan , Tian Xin
Published: June 2022

English speech modeling is one of the key problems in the field of speech recognition. Its accuracy directly affects the performance of the English speech recognition system, and how to establish a more accurate acoustic model has always been the focus of researchers. This paper is based on the intelligent edge detection algorithm of the English speech optimization teaching recognition modeling simulation analysis to improve the accuracy of acoustic models such as parameters and the performance of continuous speech recognition system as the main purpose. In this paper, the accuracy of the neural network is improved on the premise of improving the training speed and decoding speed of the model. It proposes a new model and how to use the intelligent edge detection algorithm to build a complete English speech optimization teaching recognition system. The whole system includes the mobile terminal and the server, which realizes the most basic business logic of the speech recognition system. The experimental results of this paper show that from the point of view of the average recognition rate, the recognition effect of the optimized feature set has been further improved compared with the fusion feature. From the point of view of the recognition rate under different SNR environments, the recognition rate of the optimized feature set PCA-Features2 decreased by 0.47% compared with the FFPRLS_D + TEOCC feature set under 10dB10 words. Compared with the FFPLMS_D + TEOCC feature set, the recognition rate under 5dB10 words also drops by 0.47%.
Remote Sensing Recognition and Classification of Forest Vegetation Based on Image Feature Depth Learning
Authors: Jiang Gang , Zheng Quanshun
Published: June 2022

In order to study the remote sensing recognition and classification of forest vegetation based on image feature depth learning, this paper presents a deep learning method using classical algorithms such as the maximum class method and maximum entropy method, as well as the FRFCM algorithm and convolutional neural network. In this method, SVM is used to train, classify, and recognize the color information of a high-resolution remote sensing image, remove the nongreen background of the classified image, and finally convert it to HSI space for morphological opening and closing reconstruction, so as to obtain the final extraction target. Then, a visual interface is designed to facilitate operation, which can compare the forest vegetation extraction results and operation processing time under different algorithms, so as to realize the rapid and accurate monitoring of karst forest vegetation change with remote sensing big data. The algorithm research shows that the overall accuracy of multifeature ant colony intelligent classification based on vegetation zoning is 88.85%, Kappa = 0.86, which is better than the traditional remote sensing image classification method, and provides an effective method for land use land cover remote sensing information extraction in large-scale complex terrain areas. In this way, the error extraction and missing extraction can be reduced in the extraction results of forest vegetation area in remote sensing images, and the experimental extraction results will be further close to the optimal segmentation effect.
Clinical Application Effect of Cluster Management in Noninvasive Ventilator Nursing Care of Patients with Severe Heart Failure
Authors: Luo Huanli , Zhu Guangyu
Published: June 2022

Objective. To elucidate the clinical application effect of cluster management in noninvasive ventilator nursing care of patients with severe heart failure (HF). Methods. A total of 116 severe patients with HF who received treatment in the our hospital between October 2018 and December 2019 were included, including 50 cases (control group) treated with routine nursing and 66 cases (research group) treated with cluster management. The treatment-related indexes (mechanical ventilation time and hospitalization expenses), symptom resolution (dyspnea, insomnia, nausea, and upper abdominal pain), systolic/diastolic blood pressure (SBP/DBP), heart rate (HR), and prognosis (mortality and disability rate) were observed and compared between the two groups. Results. Statistically shorter time of mechanical ventilation and symptom (dyspnea, insomnia, nausea, and upper abdominal pain) resolution were found in the research group compared with the control group. In addition, the research group showed significantly lower hospitalization expenses, SBP, DBP, and HR than the control group. Moreover, lower mortality and disability rates were determined in the research group, yet with no statistical significance between the two cohorts. Conclusion. The above results indicate the remarkable clinical application effect of cluster management in noninvasive ventilator nursing of severe HF, which can enhance the treatment efficacy, blood pressure and HR of patients, and facilitate their recovery.
Grammar System of TCFL Driven by Neural Network Technology
Authors: Xiao Rui , Luo Shengquan
Published: June 2022

With the economy’s continued and stable growth, China’s political and economic influence in the international community has grown, and more and more friends from all over the world are requesting to learn Chinese and visit China. The growth of information technology and curriculum integration has had a significant impact on TCFL (teaching Chinese as a foreign language). Facing the new situation will enable us to gain a fresh perspective on the current state of TCFL grammar system research. Through specific teaching practice, this paper verifies the effectiveness of teaching Chinese as a foreign language and cultural vocabulary. This paper proposes a grammar error correction scheme based on hybrid models—Transformer model and N-gram model—that dynamically combine the outputs of different neural modules to improve the model’s ability to capture semantic information, with the goal of correcting Chinese grammar errors. Experiments show that the Transformer and N-gram model-based Chinese grammar error correction strategy performs well in the global effect, and the overall performance is the best in the detection and positioning levels. At the detection level, the model in this document has the highest error correction accuracy of 0.64 and the highest recall rate of 0.67. The results show that adding an attention mechanism to a grammatical error correction model can improve its computational efficiency.
Life’s Essential 8: Updating and Enhancing the American Heart Association’s Construct of Cardiovascular Health: A Presidential Advisory From the American Heart Association
Authors: Lloyd-Jones Donald M. , Allen Norrina B. , Anderson Cheryl A.M. , Black Terrie , Brewer LaPrincess C. , Foraker Randi E. , Grandner Michael A. , Lavretsky Helen , Perak Amanda Marma , Sharma Garima , Rosamond Wayne ,   on behalf of the American Heart Association
Published: June 2022

In 2010, the American Heart Association defined a novel construct of cardiovascular health to promote a paradigm shift from a focus solely on disease treatment to one inclusive of positive health promotion and preservation across the life course in populations and individuals. Extensive subsequent evidence has provided insights into strengths and limitations of the original approach to defining and quantifying cardiovascular health. In response, the American Heart Association convened a writing group to recommend enhancements and updates. The definition and quantification of each of the original metrics (Life’s Simple 7) were evaluated for responsiveness to interindividual variation and intraindividual change. New metrics were considered, and the age spectrum was expanded to include the entire life course. The foundational contexts of social determinants of health and psychological health were addressed as crucial factors in optimizing and preserving cardiovascular health. This presidential advisory introduces an enhanced approach to assessing cardiovascular health: Life’s Essential 8. The components of Life’s Essential 8 include diet (updated), physical activity, nicotine exposure (updated), sleep health (new), body mass index, blood lipids (updated), blood glucose (updated), and blood pressure. Each metric has a new scoring algorithm ranging from 0 to 100 points, allowing generation of a new composite cardiovascular health score (the unweighted average of all components) that also varies from 0 to 100 points. Methods for implementing cardiovascular health assessment and longitudinal monitoring are discussed, as are potential data sources and tools to promote widespread adoption in policy, public health, clinical, institutional, and community settings.
Status of Cardiovascular Health in US Adults and Children Using the American Heart Association’s New “Life’s Essential 8” Metrics: Prevalence Estimates From the National Health and Nutrition Examination Survey (NHANES), 2013 Through 2018
Authors: Lloyd-Jones Donald M. , Ning Hongyan , Labarthe Darwin , Brewer LaPrincess , Sharma Garima , Rosamond Wayne , Foraker Randi E. , Black Terrie , Grandner Michael A. , Allen Norrina B. , Anderson Cheryl , Lavretsky Helen , Perak Amanda M.
Published: June 2022

Background:

The American Heart Association recently published an updated algorithm for quantifying cardiovascular health (CVH)—the Life’s Essential 8 score. We quantified US levels of CVH using the new score.

Methods:

We included individuals ages 2 through 79 years (not pregnant or institutionalized) who were free of cardiovascular disease from the National Health and Nutrition Examination Surveys in 2013 through 2018. For all participants, we calculated the overall CVH score (range, 0 [lowest] to 100 [highest]), as well as the score for each component of diet, physical activity, nicotine exposure, sleep duration, body mass index, blood lipids, blood glucose, and blood pressure, using published American Heart Association definitions. Sample weights and design were incorporated in calculating prevalence estimates and standard errors using standard survey procedures. CVH scores were assessed across strata of age, sex, race and ethnicity, family income, and depression.

Results:

There were 23 409 participants, representing 201 728 000 adults and 74 435 000 children. The overall mean CVH score was 64.7 (95% CI, 63.9–65.6) among adults using all 8 metrics and 65.5 (95% CI, 64.4–66.6) for the 3 metrics available (diet, physical activity, and body mass index) among children and adolescents ages 2 through 19 years. For adults, there were significant differences in mean overall CVH scores by sex (women, 67.0; men, 62.5), age (range of mean values, 62.2–68.7), and racial and ethnic group (range, 59.7–68.5). Mean scores were lowest for diet, physical activity, and body mass index metrics. There were large differences in mean scores across demographic groups for diet (range, 23.8–47.7), nicotine exposure (range, 63.1–85.0), blood glucose (range, 65.7–88.1), and blood pressure (range, 49.5–84.0). In children, diet scores were low (mean 40.6) and were progressively lower in higher age groups (from 61.1 at ages 2 through 5 to 28.5 at ages 12 through 19); large differences were also noted in mean physical activity (range, 63.1–88.3) and body mass index (range, 74.4–89.4) scores by sociodemographic group.

Conclusions:

The new Life’s Essential 8 score helps identify large group and individual differences in CVH. Overall CVH in the US population remains well below optimal levels and there are both broad and targeted opportunities to monitor, preserve, and improve CVH across the life course in individuals and the population.
Sex‐Specific Differences in Endothelial Function Are Driven by Divergent Mitochondrial Ca
2+
Handling
Authors: Damacena de Angelis Celio , Endoni Benney T. , Nuno Daniel , Lamping Kathryn , Ledolter Johannes , Koval Olha M. , Grumbach Isabella M.
Published: June 2022

Background

Sex‐specific differences in vasodilation are mediated in part by differences in cytosolic Ca
2+
handling, but how variations in mitochondrial Ca
2+
contributes to this effect remains unknown. Here, we investigated the extent to which mitochondrial Ca
2+
entry via the MCU (mitochondrial Ca
2+
uniporter) drives sex differences in vasoreactivity in resistance arteries.

Methods and Results

Enhanced vasodilation of mesenteric resistance arteries to acetylcholine (ACh) was reduced to larger extent in female compared with male mice in 2 genetic models of endothelial MCU ablation. Ex vivo Ca
2+
imaging of mesenteric arteries with Fura‐2AM confirmed higher cytosolic Ca
2+
transients triggered by ACh in arteries from female mice versus male mice. MCU inhibition both strongly reduced cytosolic Ca
2+
transients and blocked mitochondrial Ca
2+
entry. In cultured human aortic endothelial cells, treatment with physiological concentrations of estradiol enhanced cytosolic Ca
2+
transients, Ca
2+
buffering capacity, and mitochondrial Ca
2+
entry in response to ATP or repeat Ca
2+
boluses. Further experiments to establish the mechanisms underlying these effects did not reveal significant differences in the expression of MCU subunits, at either the mRNA or protein level. However, estradiol treatment was associated with an increase in mitochondrial mass, mitochondrial fusion, and the mitochondrial membrane potential and reduced mitochondrial superoxide production.

Conclusions

Our data confirm that mitochondrial function in endothelial cells differs by sex, with female mice having enhanced Ca
2+
uptake capacity, and that these differences are attributable to the presence of more mitochondria and a higher mitochondrial membrane potential in female mice rather than differences in composition of the MCU complex.
Enhancing Lifelong Language Learning by Improving Pseudo-Sample
Generation
Authors: Kanwatchara Kasidis , Horsuwan Thanapapas , Lertvittayakumjorn Piyawat , Kijsirikul Boonserm , Vateekul Peerapon
Published: June 2022

To achieve lifelong language learning, pseudo-rehearsal methods leverage samples generated from a language model to refresh the knowledge of previously learned tasks. Without proper controls, however, these methods could fail to retain the knowledge of complex tasks with longer texts since most of the generated samples are low in quality. To overcome the problem, we propose three specific contributions. First, we utilize double language models, each of which specializes in a specific part of the input, to produce high-quality pseudo samples. Second, we reduce the number of parameters used by applying adapter modules to enhance training efficiency. Third, we further improve the overall quality of pseudo samples using temporal ensembling and sample regeneration. The results show that our framework achieves significant improvement over baselines on multiple task sequences. Also, our pseudo sample analysis reveals helpful insights for designing even better pseudo-rehearsal methods in the future.
Supramodal Sentence Processing in the Human Brain: fMRI Evidence for the Influence of Syntactic Complexity in More Than 200 Participants
Authors: Uddén Julia , Hultén Annika , Schoffelen Jan-Mathijs , Lam Nietzsche , Harbusch Karin , van den Bosch Antal , Kempen Gerard , Petersson Karl Magnus , Hagoort Peter
Published: June 2022

This study investigated two questions. One is: To what degree is sentence processing beyond single words independent of the input modality (speech vs. reading)? The second question is: Which parts of the network recruited by both modalities is sensitive to syntactic complexity? These questions were investigated by having more than 200 participants read or listen to well-formed sentences or series of unconnected words. A largely left-hemisphere frontotemporoparietal network was found to be supramodal in nature, i.e., independent of input modality. In addition, the left inferior frontal gyrus (LIFG) and the left posterior middle temporal gyrus (LpMTG) were most clearly associated with left-branching complexity. The left anterior temporal lobe showed the greatest sensitivity to sentences that differed in right-branching complexity. Moreover, activity in LIFG and LpMTG increased from sentence onset to end, in parallel with an increase of the left-branching complexity. While LIFG, bilateral anterior temporal lobe, posterior MTG, and left inferior parietal lobe all contribute to the supramodal unification processes, the results suggest that these regions differ in their respective contributions to syntactic complexity related processing. The consequences of these findings for neurobiological models of language processing are discussed.
Hierarchy, Not Lexical Regularity, Modulates Low-Frequency Neural Synchrony During Language Comprehension
Authors: Lo Chia-Wen , Tung Tzu-Yun , Ke Alan Hezao , Brennan Jonathan R.
Published: June 2022

Neural responses appear to synchronize with sentence structure. However, researchers have debated whether this response in the delta band (0.5–3 Hz) really reflects hierarchical information or simply lexical regularities. Computational simulations in which sentences are represented simply as sequences of high-dimensional numeric vectors that encode lexical information seem to give rise to power spectra similar to those observed for sentence synchronization, suggesting that sentence-level cortical tracking findings may reflect sequential lexical or part-of-speech information, and not necessarily hierarchical syntactic information. Using electroencephalography (EEG) data and the frequency-tagging paradigm, we develop a novel experimental condition to tease apart the predictions of the lexical and the hierarchical accounts of the attested low-frequency synchronization. Under a lexical model, synchronization should be observed even when words are reversed within their phrases (e.g., “sheep white grass eat” instead of “white sheep eat grass”), because the same lexical items are preserved at the same regular intervals. Critically, such stimuli are not syntactically well-formed; thus a hierarchical model does not predict synchronization of phrase- and sentence-level structure in the reversed phrase condition. Computational simulations confirm these diverging predictions. EEG data from N = 31 native speakers of Mandarin show robust delta synchronization to syntactically well-formed isochronous speech. Importantly, no such pattern is observed for reversed phrases, consistent with the hierarchical, but not the lexical, accounts.
Magnetohydrodynamic (MHD) Convective Nanofluid Flow, Heat Transfer and Irreversibility Analysis in a Horizontal Micro Tall Cavity with Heat Sources in the Slip Regime
Authors: Ferhi Mokhtar , Djebali Ridha , Abboudi Said , Al-kouz Wael
Published: June 2022

The contemporary study aims to numerically analyze the MHD convective heat transfer and entropy generation analysis for the case of a micro open tall cavity filled with Al2O3/water under the effect of uniform magnetic field in the slip flow regime using the LBM for resolving the governing equations. The slip velocity and the temperature jump conditions are used to incorporate the micro aspect. The Brownian motion effects are considered in the thermal conductivity. The flow pattern and heat transfer characteristics and the irreversibility are studied dependently on various dimensionless independent variables such as: nanoparticles volume fractionΦ(0–4%), Rayleigh number (Ra) (102–104), Knudsen number (Kn) (0–10−1) and Hartmann number (Ha) (0–75). It is found that the change of aspect ratio, Ra,Φand the magnetic field strength affect the hydrodynamic and thermal behaviors inside the micro medium. Concerning the Kn, which presents the most influential parameter on the heat transfer, flow pattern, thermal field and entropy generation, it was concluded it decreases the heat transfer, entropy generation and Bejan number inside the micro tall open cavity. Moreover, it deteriorates the formed rolling cells and the plumes in the micro domain. The nanoparticles size effect is also studied, and found to reduce the heat transfer.
Pressure Effects on Simultaneous Optical and Acoustics Data from Laser-Induced Plasmas in Air: Implications to the Differentiation of Geological Materials
Authors: Alvarez-Llamas César , Purohit Pablo , Moros Javier , Laserna J Javier
Published: June 2022

The shockwave generated alongside the plasma is an intimately linked, yet often neglected additional input for the characterization of solid samples by laser-induced breakdown spectroscopy (LIBS). The present work introduces a dual LIBS–acoustics sensor that takes advantage of the analysis of the acoustic spectrum yielded by shockwaves produced on different geological samples to enhance the discrimination power of LIBS in materials featuring similar optical emission spectra. Six iron-based minerals were tested at a distance of 2 m using 1064 nm laser light and under pressure values ranging from 7 to 1015 mbar. These experimental parameters were selected to assess the effects of pressure, one of the main factors conditioning the propagation of sound as well as a commonly investigated influence in LIBS experiments. Moreover, precise values for carrying out the analyses were set based on one of the most exciting scenarios in which LIBS data may be enhanced by laser-induced acoustics: space exploration. This is exemplified by the tasks performed by the Mars 2020 SuperCam instrument located onboard the Perseverance rover. Authors evaluated the use of acoustic signals both in the time-domain and frequency-domain in sensitive cases for the distinguishing of minerals exhibiting LIBS spectra featuring almost the same emission lines using PCA schemes for each pressure setting. Thus, we report herein the impact of the surrounding pressure level upon this diagnostic tool. Overall, this paper seeks to show how the analytical potential of simultaneous phenomena taking place during a laser-produced plasma event is subjected to the defined operational conditions.
What’s the point of being a discipline? Four disciplinary strategies and the future of International Relations
Authors: Corry Olaf
Published: June 2022

While disciplinary identities are among the most fraught subjects in academia, much less attention has been given to what disciplinarity actually entails and what risks different disciplinary strategies involve. This article sets out a theory of disciplinarity that recognises not only their coercive but also their redeeming features, particularly in view of the coexistence of multiple competing disciplines and powerful transdisciplinary movements (such as rationalism). On this basis it identifies four disciplinary strategies and each is assessed in relation to the future of IR: (1) remaining a subdiscipline of Political Science (‘stay put’), (2) becoming an interdisciplinary field (‘reach out’), (3) dissolving into transdisciplinarity or abolishing IR (‘burn down’), or (4) establishing IR as a discipline in its own right (‘break out’). Rejecting the false choice of disciplinary constraint versus epistemic freedom, this framework allows IR and other subfields to more consciously consider a range of disciplinary strategies and to entertain the risks and affordances they each offer. The article concludes that a future independent discipline focused on the implications of ‘the international’ not just for politics but all fields – including disciplinarity – would make for a broader, more diverse IR, ultimately also better able to engage other disciplines.
Static and dynamic deformation response of smart laminated composite plates induced by inclined piezoelectric actuators
Authors: Gohery Scott , Mozafari Farzin , Moslemi Navid , Mouloodi Saeed , Alebrahim Reza , Ahmed Mizan , Abdi Behzad , Sudin Izman , Burvill Colin
Published: June 2022

A Levi-type analytical solution procedure is developed to characterize static and dynamic deformation response of smart laminated simply-supported composite rectangular plates induced by inclined piezoelectric actuators under (1) constant electrical voltage and (2) time-dependent electrical voltage with excitation frequency. The key to development of this analytical solution is to employ higher order finite integral transform and discretized higher order partial differential unit step function equations. Unlike earlier studies, this research aims to investigate the effect of inclination angle of piezoelectric actuators on static and dynamic deformation response of laminated composite plates under both static and dynamic conditions. The developed analytical solution procedure is implemented computationally through Matlab-based computer code. Its accuracy is initially investigated through convergence study and results comparison with the published literature for a particular case when inclination angle is θ = 0°, which is only limited to bending deformation response. Since there is no published benchmark data for twisting deformation response analysis caused by inclination angle of piezoelectric actuators (θ ≠ 0°), a set of robust and realistic numerical analysis using Abaqus finite element analysis (FEA) is conducted. Good agreement between the analytical and numerical results is observed. Unlike applied electrical voltage, inclination angle of a piezoelectric actuator does not have a significant impact on twisting deformation response during static mode; whereas, both the excitation frequency and inclination angle can significantly influence maximum amplitude of vibration.
Experimental study on the properties of Alfa/wool woven fabrics reinforced epoxy composite as an application in wind turbine blades
Authors: Lamhour Kawtar , Rouway Marwane , Tizliouine Abdeslam , El Hachemi Omari Lhaj , Salhi Hayat , Cherkaoui Omar
Published: June 2022

Wind energy is the kinetic energy of wind transformed into electrical energy by a system known as a wind turbine. All of the different parts of a wind turbine, like blades, hub, gearbox, nacelle, and tower, blades are usually made of glass and carbon fibers for better strength, lower weight, and better resistance to corrosion. The main limitations of these materials are the availability, non-biodegradable, health hazards, and fabrication cost. The development of interwoven fabric based on natural fiber for composite production is a novel approach that can be adopted to address the challenges of the balanced mechanical properties of composites. In this paper, alfa and wool fibers were selected as reinforcing materials to develop four woven fabrics, and unsaturated low viscosity epoxy resin was chosen as the matrix, the wovens were produced using the weaving of taffetas technique. The vacuum molding process was adopted to produce the hybrid composite due to its superior advantages over the hand lay-up technique. Alfa fibers have been previously treated with various concentrations of NaOH (1, 2, 3 mol) for 2 h. The effect of the alkaline treatment on the interface fiber matrix is analyzed. The results of static tests on composites showed an improvement in the tensile and flexural strengths of composites reinforced with woven fabrics. The mechanical performances of Alfa/wool yarns and fabrics obtained allow us to predict the actual perspectives of substitution of glass fibers by natural fibers for the application in wind blades.