bluuebunny/crossref_metadata_2025 huggingface dataset:
Describing, predicting and explaining adherence to total skin self-examination (TSSE) in people with melanoma: a 12-month longitudinal study
Authors: Allan Julia L , Johnston Derek W , Johnston Marie , Murchie Peter
Published: August 2022

Objectives

To describe trajectories in melanoma survivors’ adherence to monthly total skin self-examination (TSSE) over 12 months, and to investigate whether adherence trajectories can be predicted from demographic, cognitive or emotional factors at baseline.

Design

A longitudinal observational study nested within the intervention arm of the ASICA (Achieving Self-Directed Integrated Cancer Aftercare) randomised controlled trial.

Setting

Follow-up secondary care in Aberdeen and Cambridge UK.

Participants

n=104 adults (48 men/56 women; mean age 58.83 years, SD 13.47, range 28–85 years; mean Scottish Index of Multiple Deprivation score 8.03, SD 1.73, range 2–10) who had been treated for stage 0–IIC primary cutaneous melanoma in the preceding 60 months and were actively participating in the intervention arm of the ASICA trial.

Interventions

All participants were using the ASICA intervention—a tablet-based intervention designed to support monthly TSSE.

Primary and secondary outcome measures

The primary outcome was adherence to guideline recommended (monthly) TSSE over 12 months. This was determined from time-stamped TSSE data recorded by the ASICA intervention app.

Results

Latent growth mixture models identified three TSSE adherence trajectories (adherent −41%; drop-off −35%; non-adherent −24%). People who were non-adherent were less likely to intend to perform TSSE as recommended, intending to do it more frequently (OR=0.21, 95% CI 0.06 to 0.81, p=0.023) and were more depressed (OR=1.31, 95% CI 1.06 to 1.61, p=0.011) than people who were adherent. People whose adherence dropped off over time had less well-developed action plans (OR=0.78, 95% CI 0.63 to 0.96, p=0.016) and lower self-efficacy about TSSE (OR=0.92, 95% CI 0.86 to 0.99, p=0.028) than people who were adherent.

Conclusions

Adherence to monthly TSSE in people treated for melanoma can be differentiated into adherent, drop-off and non-adherent trajectories. Collecting information about intentions to engage in TSSE, depression, self-efficacy and/or action planning at outset may help to identify those who would benefit from additional intervention.

Trial registration number

ClinicalTrials.gov Registry (NCT03328247).
Analysis of wheelchair falls in team sports at the Paralympic Games: video-based descriptive comparison between the Rio 2016 and Tokyo 2020 games
Authors: Fukui Kazuki , Maeda Noriaki , Sasadai Junpei , Shimizu Reia , Tsutsumi Shogo , Arima Satoshi , Tashiro Tsubasa , Kaneda Kazuki , Yoshimi Mitsuhiro , Mizuta Rami , Abekura Takeru , Esaki Hinata , Terada Tomoki , Komiya Makoto , Suzuki Akira , Urabe Yukio
Published: August 2022

Objectives

To identify the fall characteristics of athletes in wheelchair rugby and wheelchair basketball during the Tokyo 2020 Paralympic Games and descriptively compare these with those of the Rio 2016 Paralympic Games.

Design

Cross-sectional analysis.

Primary and secondary outcome measures

We obtained video footage from the International Paralympic Committee of the Tokyo 2020 Paralympic Games that included 8 teams from each of the 18 wheelchair rugby and 10 wheelchair basketball games (men and women). The data were analysed to evaluate the number of falls, class difference (low or high pointer), time of play during the fall, phase of play, contact with other athletes, fall direction, fall location and the body part that first contacted the floor during the fall. These data from the Rio 2016 and Tokyo 2020 games were compared.

Results

Overall, 430 falls (rugby, 104; men’s basketball, 230 and women’s basketball, 96) occurred (average per game ±SD: 5.8±3.1, 23.0±5.4 and 9.6±5.0, respectively). Significant differences in class, direction, fall location and body part point of contact between the three sports were observed. In wheelchair rugby, falls occurred mainly in high pointers and tended to be more lateral due to contact. In wheelchair basketball, falls occurred more in female high-pointers and in male low pointers, with more forward falls due to forward contact. Unlike in the Rio 2016 games, no difference between the events based on the presence or absence of contact was observed in the Tokyo 2020 games.

Conclusions

The number of falls increased in Tokyo 2020 compared with Rio 2016, with no significant difference in the characteristics of falls between the Rio 2016 and Tokyo 2020 games. Only in men’s wheelchair basketball, the number of falls in low pointers significantly increased in the Tokyo 2020 games when compared with that in the Rio 2016 games.
Biomonitoring of heavy metals and metalloids with wild mammals in the Iberian Peninsula: a systematic review
Authors: Jota Baptista Catarina , Seixas Fernanda , Gonzalo-Orden José M. , Oliveira Paula A.
Published: August 2022

Trace elements (including heavy metals) can negatively affect the environment and the health of living beings. Biomonitoring is a transdisciplinary tool to evaluate this pollution type and its respective consequences in ecosystems, food chains, and webs. This review used systematic methods to identify published literature on biomonitoring of heavy metal(loid)s using wild mammals on the Iberian Peninsula. A total of 30 different mammalian species (30/141) were included in 62 Iberian biomonitoring studies: 22 species from terrestrial habitats and 8 from aquatic habitats. Carnivores (including piscivores) were the most represented in both habitat types (7/22 in terrestrial; 8/8 in aquatic). Most studies used more than one tissue (2.8 ± 1.3), with a preference for the liver and kidney. Cd was the most determined metal, measured in 45% of the biomonitoring studies analysed, highlighting its potential health impact on mammals. Further research is crucial to provide more information on mammalian species' susceptibility to this One Health problem, and to cover more habitats, trophic chains, and (or) geographical areas.
In SilicoPrediction of Andrographolide Dosage Regimens for COVID-19 Treatment
Authors: Saeheng Teerachat , Karbwang Juntra , Na-Bangchang Kesara
Published: August 2022

Andrographolide (APE) has been used for COVID-19 treatment in various clinical settings in South-East Asia due to its benefits on reduction of viral clearance and prevention of disease progression. However, the limitation of APE clinical use is the high incidence of adverse events. The objective of this study was to find the optimal dosage regimens of APE for COVID-19 treatment. The whole-body physiologically-based pharmacokinetic (PBPK) models were constructed using data from the published articles and validated against clinical observations. The inhibitory effect of APE was determined for the potency of drug efficacy. For prevention of pneumonia, multiple oral doses such as 120[Formula: see text]mg for three doses, followed by 60[Formula: see text]mg three times daily for 4 consecutive days, or 200[Formula: see text]mg intravenous infusion at the rate of 20 mg/h once daily is advised in patients with mild COVID-19. For prevention of pneumonia and reduction of viral clearance time, the recommended dosage regimen is 500[Formula: see text]mg intravenous infusion at the rate of 25[Formula: see text]mg/h once daily in patients with mild-to-moderate COVID-19. One hundred virtual populations (50 males and 50 females) were simulated for oral and intravenous infusion formulations of APE. The eligible PBPK/PD models successfully predicted optimal dosage regimens and formulations of APE for prevention of disease progression and/or reduction of viral clearance time. Additionally, APE should be co-administered with other antiviral drugs to enhance therapeutic efficacy for COVID-19 treatment.
Transformational Leadership and Organisational Performance: The Combined Impact of Organisational Learning and Open Innovation
Authors: Horchani Samah Chemli , Doghri Sinda Ben Sedrine , Ghanney Amna
Published: August 2022

This work deals with the effect of transformational leadership (TL) on organisational performance (OP) through the mediating roles of organisational learning (OL) and open innovation (OI). Data was collected from 202 respondents in Tunisian enterprises using non-probabilistic convenience sampling. Based on structural equation modelling, the findings demonstrate a positive effect of TL on OP through an OI mediation. The study highlighted the direct and indirect effects of TL on OP through a double partial mediation of OI and OL. The document sheds new light on the gaps between TL and entrepreneurial leadership, not as a continuum, but as coexisting entrepreneurial leadership styles.
Closing the Gap Between Stakeholder Pressure and SME Owner-Managers’ Commitment to Sustainability: Does the Business Case Logic Matter?
Authors: Courrent Jean-Marie , Omri Waleed
Published: August 2022

Taking the lead from stakeholder management theory, this study seeks to shed light on the association between the stakeholder pressure and the involvement of small- and medium-sized enterprises (SMEs) in sustainable actions. The study also proposes a moderating role of the business case for corporate sustainability on this relationship. Questionnaire responses from 135 French SMEs were analysed, confirming the positive effect of various stakeholders on the commitment to sustainable business practices among SMEs. The empirical results show that this effect differs according to the three pillars of sustainable development. Empirical results also suggest that a business case for sustainability is the overwhelming driver for the adoption of more responsibility-oriented practices. These results are consistent with the instrumental approach of stakeholder theory, which reveals that incorporating stakeholders’ concerns into a firm’s sustainability strategy depends on the owner-manager’s perception of the economic-financial advantage of such practices.
Machine Intelligence for Language Translation from Kashmiri to English
Authors: Lone Nawaz Ali , Giri Kaiser J. , Bashir Rumaan
Published: August 2022

Machine translation (MT) is an emerging research as well as application area in the contemporary world. It is receiving significant attention from academia, industry and corporate houses. A wide range of translation techniques are being applied either individually or in combination for machine translation of different languages across the globe. However, there are still many languages that are either completely missing or poorly visible on the machine translation map. The Kashmiri language is one such language where very little or negligible work has been done related to its machine translation. This paper aims to present a Kashmiri-to-English Machine Translation System and highlight various features of the Kashmiri language. The system is based on machine intelligence having the ability to learn various translation rules from the translated set of input sentences, using Long Short-term Memory (LSTM) architecture for deep sequence learning. The paper also discusses various challenges related to machine translation from Kashmiri to English or other languages. The work presented in this paper is the first of its nature and can serve as a bedrock for research community interested to work on machine translation of Kashmiri language.
Kv1.3 K+Channel Physiology Assessed by Genetic and Pharmacological Modulation
Authors: Varanita Tatiana , Angi Beatrice , Scattolini Valentina , Szabo Ildiko
Published: August 2022

Potassium channels are widespread over all kingdoms and play an important role in the maintenance of cellular ionic homeostasis. Kv1.3 is a voltage-gated potassium channel of the Shaker family with a wide tissue expression and a well-defined pharmacology. In recent decades, experiments mainly based on pharmacological modulation of Kv1.3 have highlighted its crucial contribution to different fundamental processes such as regulation of proliferation, apoptosis, and metabolism. These findings link channel function to various pathologies ranging from autoimmune diseases to obesity and cancer. In the present review, we briefly summarize studies employing Kv1.3 knockout animal models to confirm such roles and discuss the findings in comparison to the results obtained by pharmacological modulation of Kv1.3 in various pathophysiological settings. We also underline how these studies contributed to our understanding of channel function in vivo and propose possible future directions.
“These People Had Taken Advantage of Me”: A Grounded Theory of Problematic Consequences of Player Interaction with Mobile Games Perceived as “Designed to Drive Spending”
Authors: Petrovskaya Elena , Zendle David
Published: August 2022

Many games which incorporate microtransactions—uncapped, repeated in-game purchases—are described by players as having had their 'dynamics designed to drive spending'. Such games are perceived by players as designed primarily to encourage spending, rather than with the improvement of the player experience in mind. However, it is unknown how playing these games affects players. We addressed the research question of “What consequences might there be of interaction with games perceived as having had their dynamics designed to drive spending?” considering adult players. We conducted semi-structured interviews and used a grounded theory method of analysis. Our findings revealed five life areas of problematic consequences: financial issues, problems at work and education due to distraction and lack of productivity, emotional consequences for self-perception, problems sleeping, and social consequences. These outcomes emerge from the interaction of players with certain vulnerability traits with these game mechanics. We discuss these findings in the context of gaming disorder and the gamblification of games.
The Diversified Communication Methods of Chinese and Korean Cultural Education Based on New Media Technology
Authors: Wang Guanen , Li Duan
Published: August 2022

In the current era of multicultural exchange and integration, the Chinese and Korean cultures have shown the ideal effect of cultural deep integration through interaction and exchange to promote cultural exchanges better, to view the diversified communication between Chinese and Korean cultures with correct cultural views, so as to better find the common points of effective integration of the two cultures, understand and respect the differences between Chinese and Korean cultures, and effectively improve the effect of the application of Chinese and Korean cultural integration by selecting appropriate integration perspective. Based on the understanding of cultural connotation and the analysis of the current situation of cultural education in China and South Korea, this study explores the mechanism of cultural and educational diversification exchange in China and South Korea under the cultural background and puts forward relevant optimization suggestions.
Enterprise Financial Risk Prediction and Prevention Based on Big Data Analysis
Authors: Cheng Jinfeng
Published: August 2022

With the rapid development of the times, the financial status of many enterprises has become the top priority, and the prediction and prevention of enterprise financial risks are more important. The financial risk prediction of enterprises under big data can better collect data and analyze it, which can help workers bring convenience. In order to make the public better understand the corporate financial risk forecasting, the research on the prediction and prevention of corporate financial risk based on big data analysis is as follows: (1) the broad and narrow senses of corporate finance readers gain a clearer understanding of the importance of corporate finance; (2) an introduction to the calculation algorithm of enterprise financial risk, which facilitates the staff to better calculate the financial risk of the enterprise and establish a financial risk model; (3) conduct an example investigation on a representative pharmaceutical company, analyze its various financial indicators, and compare with the indicators in the same industry to judge whether the financial data is normal; and (4) conduct comparative research on corporate finance under big data and find that big data can better prevent corporate financial risks. It is concluded that this risk prediction method is very effective. It shows that corporate financial risk is very important to social development, and based on big data, risks can be better predicted and prevented.
Location Selection of Digital Cultural Tourism Town Based on Improved Genetic Algorithm and BP Neural Network
Authors: LeahWu Liping , Qiao Guanghui , Jia Qiaoran , Liu Mengyu , Chang Jinghao , Smiling Renyue , Li Shiru , Shen Huawen
Published: August 2022

Due to the short development time of cultural and tourism towns in China, local governments and investors lack experience in building cultural and tourism towns and do not pay enough attention to the positioning of towns. Alternatively, this issue results in chaos in domestic cultural and tourism towns and even a large number of empty towns in some provinces. Therefore, how to accurately locate cultural tourism towns is a problem that must be studied in depth at present. This paper uses the regional economic theory to collect the influencing factors of cultural tourism town positioning. Based on the BP neural network and the improved genetic algorithm, a genetic neural network model is constructed to train and predict the samples of cultural tourism towns. Taking a small town in the East as a case, the data were collected and analyzed. Established on the prediction outcomes of the genetic neural network, the best location of a small town was selected according to the actual situation of the region. In terms of accuracy and training time, our experimental evaluation confirmed that the neural network enhanced by genetic algorithms outperforms the conventional BP neural network. Furthermore, we observed that besides the classification capabilities of the BP neural network-based model, the classical BP neural network improved by the genetic algorithm also exhibits great macrosearch capabilities and good global optimization performance.
[Retracted] Analysis of the Effectiveness of International Law in Global Environmental Relations from the Perspective of International Institutional Theory
Authors: Yu Zeyang
Published: August 2022

Since the 1970s, mankind has become increasingly sensitive to major world environmental protection issues, and the globalenvironmental protection laws and regulations system formed to deal with suchspecific issues has rapidly expanded in scope and depth. From the initial environmental issues in the study of international relations theory to the development of environmental issues in the study of global governance, and then the concept of global environmental governance came out and developed rapidly. This trend provides a desire to deal with many environmental protection issues and various issues related to worldenvironmental protection issues. But are these wishes real? We must also doubtthe rationality of the legal systems of various countries that have been formedand fought to deal with all environmental protection relations, especially theworld environmental protection issues. Today, the world environmental problemhas formed a relatively perfect academic field. The concept theory of globalproblems starting from ecological problems has moved from ecological problemsto world governance problems. With the introduction and rapid improvement ofthe concept of world ecological problems. The articlestarts from the role of non‐state actors in the original internationalframework, further expands and deepens, and presents a multiangle andall‐round perspective, showing that international law can still play a crucial role in the settlement of international environmental problems. It not only caters to the needs of the current international situation and development but also provides forward‐looking guidance for future environmental governance at the global level.
A Review of Emerging Goose Astrovirus Causing Gout
Authors: Liu Chenggang , Sun Minhua , Liao Ming
Published: August 2022

In recent years, an infection in geese caused by goose astrovirus (GAstV) has repeatedly occurred in coastal areas of China and rapidly spread to inland provinces. The infection is characterized by joint and visceral gout and is fatal. The disease has caused huge economic losses to China’s goose industry. GAstV is a nonenveloped, single‐stranded, positive‐sense RNA virus. As it is a novel virus, there is no specific classification. Here, we review the current understanding of GAstV. The virus structure, isolation, diagnosis and detection, innate immune regulation, and transmission route are discussed. In addition, since GAstV can cause gout in goslings, the possible role of GAstV in gout formation and uric acid metabolism is discussed. We hope that this review will inform researchers to rapidly develop effective methods to prevent and treat this disease.
Analysis of the Effect of Mindfulness Behavior Intervention Combined with Progressive Breathing Training on Pulmonary Function Rehabilitation in Patients with Chronic Obstructive Pulmonary Disease
Authors: Yu Shan , Fan Hui
Published: August 2022

Purpose. Studies have shown that 50%–70% of patients with chronic obstructive pulmonary disease (COPD) have fatigue in addition to respiratory symptoms, so relieving respiratory symptoms and reducing fatigue are the main treatment objectives for COPD patients. This study focuses on the effect of positive behavioral intervention combined with progressive breathing training on pulmonary function rehabilitation in patients with COPD. Methods. 86 patients who underwent COPD treatment in our hospital between August 2020 and December 2021 were selected as study subjects and were divided into control (n = 43) and study groups (n = 43) using the random number table method. Patients in the control group were given conventional care, treatment, and health guidance, while patients in the study group were given positive behavioral intervention combined with progressive breathing training on this basis. Patients in both groups were compared on the basis of Multidimensional Fatigue Inventory 20 (MFI-20) score, the Medical Coping Questionnaire (MCMQ score), the Massive Attentional Awareness Scale (MAAS) score, and pulmonary function indicators (including the percentage of forced expiratory volume one second (FEV1%), peak expiratory flow (PEF), forced vital capacity (FVC), and 6-min walk distance (6MWD)) and quality of life (MCMQ) scores before and after 12 weeks of intervention. Results. After 12 weeks of intervention, the study group had higher MFI-20 scores (comprehensive fatigue, physical fatigue, reduced activity, decreased power, and mental fatigue), confrontation scores on the MCMQ scale, MAAS scores (observation, description, nonjudgmental to intrinsic experience, nonresponsiveness to intrinsic experience, and perceived behavior), FEV1%, PEF, FVC, and 6MWD levels than the control group (P<0.05). The scores of avoidance and submission on the MCMQ scale, and all scores of quality of life (cough, expectoration, shortness of breath, chest tightness, housework, going out, sleep, and energy) were lower than those of the control group (P<0.05). Conclusion. Positive behavioral interventions combined with progressive breathing training have a strengthening effect on the clinical treatment of COPD patients. Positive behavioral interventions combined with progressive breathing training are simple to implement as individual self-regulation methods and can be practiced on their own after being familiar with certain methods and techniques, and long-term adherence helps individuals cope with the stimulation of adverse events. Trail Registration. The clinical registration number for this research is L2020083.
Image Analysis Method of Substation Equipment Based on Convolutional Neural Network
Authors: Zhang Jingjing , Liu Yuxin , Yuan Lin , Jia Haowei
Published: August 2022

Due to the continuous development of computer technology to promote the continuous progress of substation automation technology, the current substation equipment is diverse and there are many interferences, making the accuracy of the image processing algorithm to be low, and there is a lack of a complete automatic processing system. Convolutional neural networks (CNNs) are one of the most important breakthroughs in artificial intelligence in the last decade, especially in the field of image recognition, and have made important research achievements. In this study, we apply CNNs to substation equipment image processing, a method that performs feature extraction for recognition through substation equipment images. The research focuses on the expansion of the image sample set, the automatic training method based on recognition rate, and the voting strategy based on integrated learning, which not only improves the training efficiency of the model but also increases the recognition rate, and the proposed method is of high practicality.
Analysis, Optimization, and Hardware Implementation of Dipole Antenna Array for Wireless Applications
Authors: Abdul Malek Norun , Seager Rob D. , Flint James A. , Zainal Abidin Zuhairiah
Published: August 2022

The antenna pattern synthesis is one of the significant problems in the phased array antenna. Pattern synthesis refers to the optimized weight excitation of each antenna element in order to steer the beam electronically without mechanically rotating the antenna. It can be achieved by using a combination of phase shifters and attenuator circuits. In this paper, a 2 by 2 dipole antennas with an RF beamforming circuit has been designed to steer the main beam along the azimuth plane. The main beam coverage from 100° to 140° with a step size of 10° has been successfully optimized using a hybrid of the induced EMF method and a genetic algorithm. The optimization results were compared to the full-wave simulation technique implemented in Empire XCCel. The design is realistically implemented at 2.45 GHz, with both simulation and measurement results shown. The measured reflection coefficient of the phased array antenna is −48 dB at 2.56 GHz. The feasibility of the beam synthesis has been validated successfully with the main beam being steered at 110°. The possibility of a fabrication discrepancy resulting in minor radiation degradation is also discussed in this research. The dipole antenna system with RF beamformer circuit can be applied to indoor positioning systems such as Wi-Fi, wireless local area network (WLAN), and fifth-generation.
Improved Chaotic Algorithm-Based Optimization Technology of Architectural Engineering Drawing Parameters
Authors: Ma Xiaoqiu
Published: August 2022

The traditional methods deal with large sample data sets of architectural engineering drawings and they have high time complexity and space complexity as well. Their searching time is long and sometimes the results are unsatisfactory. Therefore, this paper proposes an optimization method designed for architectural engineering drawing parameters to overcome the limitations of the traditional methods. It is based on the improved chaotic algorithm. The algorithm proposes the optimization model of architectural engineering drawing (AED) parameters in the first phase. In the second phase, an improved chaos algorithm is used to optimize the parameters of architectural engineering drawing, and the modeling strategy of visual parameter optimization environment is constructed. Finally, the visualization parameter optimization process of architectural engineering drawing is completed. Through experiments, it is evidently observed that the method presented in this paper can effectively reduce the optimization time, improve the lighting illumination of buildings, and improve the optimization precision of architectural engineering drawing parameters. The proposed method considers multiple parameters and it has greater application ability in the field of architectural designs.
Construction of Pulmonary Nodule CT Radiomics Random Forest Model Based on Artificial Intelligence Software for STAS Evaluation of Stage IA Lung Adenocarcinoma
Authors: Liu Qian , Qi Wanyin , Wu Yanping , Zhou Yingjun , Huang Zhiwei
Published: August 2022

Objective. Spread through air space (STAS) is an invasive characterization of lung adenocarcinoma and is regarded as a risk factor for poor prognosis. The aim of this study is to develop a random forest model for preoperative prediction of spread through air spaces (STAS) in stage IA lung adenocarcinoma. Methods. 92 patients with stage IA lung adenocarcinoma, who underwent computed tomography (CT) scan and surgical resection, were retrospectively reviewed. Each pulmonary nodule was automatically segmented by artificial intelligence (AI) software, and its CT-based radiomics were extracted. All patients were pathologically classified into STAS-negative and STAS-positive cohorts; then, clinical pathological and CT-based radiomics were compared between the two cohorts. Finally, a prediction model for evaluating STAS status in stage IA lung adenocarcinoma was established by a random forest model. Results. Among 92 patients with stage IA lung adenocarcinoma, STAS positive was identified in 19 patients. The random forest classification model identified predictive features, including CT maximum value, consolidation to tumor ratio (CTR), 3D diameter, CT mean value, entropy, and CT minimum value. The misclassification rate of the random forest model is only 7.69%. Conclusion. The risk factors of STAS in stage IA lung adenocarcinoma can be effectively identified based on the random forest model, and the hierarchical management of characteristic risk can be effectively realized. A random forest model for predicting STAS in IA lung adenocarcinoma is simple and practical.
Coexistence of Pemphigus Vulgaris and Lichen Planus following COVID-19 Vaccination
Authors: Aryanian Zeinab , Balighi Kamran , Azizpour Arghavan , Kamyab Hesari Kambiz , Hatami Parvaneh
Published: August 2022

SARS-CoV-2 vaccines were approved without long-term monitoring due to emergent situation and might have several side effects. Herein, we describe the first case with development of both LP and PV following COVID-19 vaccination. Immunological alteration due to COVID-19 vaccination and its potential role in triggering autoimmune disorders were also dealt with.
Evaluation Model of Land Use Spatial Equilibrium Based on Regional Collaborative Remote Sensing Observation
Authors: Huang Lu
Published: August 2022

In order to improve the evaluation effect of the balance of land use space, this paper uses computer intelligence technology to assist land space observation and provide basic data for land space planning. Moreover, this paper analyzes the existing land space assessment algorithms, identifies the shortcomings of the traditional algorithms, and improves the traditional methods by combining random forest classification and image texture features. In addition, this paper builds a regional collaborative remote sensing observation model based on the improved algorithm. Furthermore, after the system structure is constructed, the system performance is tested by the simulation method, and the system performance is verified by the experimental analysis method. Finally, the validity of the improved algorithm in this paper is also verified by simulation experiments, and the validity of the model in this paper is verified. The research shows that the method proposed in this paper has certain reliability.
Influence of the Level of Emergency Medical Facility on the Short-Term Treatment Results of Cardiac Arrest: Out-of-Hospital Cardiac Arrest and Interhospital Transfer
Authors: Chung Je Young , Choi Yuri , Jeong Jinwoo , Lee Sung Woo , Han Kap Su , Kim Su Jin , Kim Won Young , Kang Hyunggoo , Hong Eun Seog
Published: August 2022

Objective. This study aimed to elucidate whether direct transport of out-of-hospital cardiac arrest (OHCA) patients to higher-level emergency medical centres (EMCs) would result in better survival compared to resuscitation in smaller local emergency departments (EDs) and subsequent transfer. Methods. This study was a retrospective population-based analysis of cases registered in the national database of 2019. This study investigated the immediate results of cardiopulmonary resuscitation for OHCA compared between EMCs and EDs and the results of therapeutic temperature management (TTM) compared between the patients directly transported from the field and those transferred from other hospitals. In-hospital mortality was compared using multivariate logistic regression. Results. From the population dataset, 11,493 OHCA patients were extracted. (8,912 in the EMC group vs. 2,581 in the ED group). Multivariate logistic regression revealed that the odds for ED mortality were lower with treatment in EDs than with treatment in EMCs. (odds ratio 0.712 (95% confidence interval (CI): 0.638–0.796)). From the study dataset, 1,798 patients who received TTM were extracted. (1,164 in the direct visit group vs. 634 in the transferred group). Multivariate regression analysis showed that the odds ratio for overall mortality was 1.411 (95% CI: 0.809–2.446) in the transferred group. (

p
=
0.220

). Conclusion. The immediate outcome of OHCA patients who were transported to EDs was not inferior to that of EMCs. Therefore, it would be acceptable to transport OHCA patients to the nearest emergency facilities rather than to the specialized centres in distant areas.
Clinical Significance of Neuregulin 4, Afamin, and SERPINB1 in Gestational Diabetes Mellitus and Their Relationship with Insulin Resistance
Authors: Li Qian , Li Chunmei , Jin Jing , Shen Yang , Wang Mei
Published: August 2022

Objective. This study aims to explore the serum levels of neuregulin 4 (NRG4), afamin (AFM), and serpin family B member 1 (SERPINB1) in gestational diabetes mellitus (GDM) patients and their relationship with insulin resistance. Method. Serum levels of AFM, SERPINB1, and NRG4 were measured in GDM (n = 58), and non-GDM women (n = 60) using enzyme-linked immunosorbent assay (ELISA) kits. Besides, the serum insulin and glucose levels were also measured followed by calculating the homeostatic model assessment of insulin resistance (HOMA-IR). The correlation was performed using the Pearson analysis. Results. The increased serum levels of AFM and SERPINB1 were revealed in GDM patients as compared with non-GDM women, accompanied by the lower NRG4 serum level. ROCs for AFM concentrations showed an AUC of 0.629 (95% CI: 0.527∼0.731), 0.832 (95% CI: 0.754∼0.909) for the SERPINB1 serum level, and 0.626 (95% CI: 0.524∼0.728) for the NRG4 serum level. The threshold was 108.05 mg/L, 8.75 ng/mL, and 96.25 ng/mL of AFM, SERPINB1, and NRG4. Moreover, the combined ROC of AFM, SERPINB1, and NRG4 serum levels showed higher sensitivity (72.41%) and specificity (85.00%) for the diagnosis of GDM (AUC = 0.839; 95% CI: 0.764∼0.913). In GDM patients, the Pearson analysis revealed a significant correlation between AFM and SERPINB1 (r = 0.776), AFM and NRG4 (r = −0.799), as well as SERPINB1 and NRG4 (r = −0.783). Moreover, AFM and SERPINB1 serum concentrations in GDM patients were positively related to insulin levels, fasting glucose levels, and HOMA-IR values. However, the SERPINB1 serum level was negatively correlated with serum insulin and glucose levels and HOMA-IR. Conclusion. Abnormal serum levels of NRG4, AFM, and SERPINB1, as highly sensitive diagnostic tools, are closely related to insulin resistance in GDM patients.
Design and Implementation of Hybrid PV/Battery-Based Improved Single-Ended Primary-Inductor Converter-Fed Hybrid Electric Vehicle
Authors: Aljafari Belqasem , Devarajan Gunapriya , Arumugam Selvi , Vairavasundaram Indragandhi
Published: August 2022

In order to enhance the power transformation stage’s power transfer capabilities and efficiency, in this article, improved three-port two step-up single-ended primary-inductor converters (SEPIC) converter fed (Photovoltaic )PV- Hybrid Electric Vehicle was proposed. In comparison to the standard single-stage SEPIC, the proposed converter accepts a wider range of input voltages. The proposed three-port converter uses a multiple-winding high-frequency transformer (HFT) to integrate the dual sources and provide greater voltage gain with lesser elements. Furthermore, by predicting the drive torque need, the power management algorithm (PMA) included with the proposed PV-hybrid electric vehicle (HEV) minimizes the drive motor’s power consumption. An experimental model with a power output of 6 kW and a voltage range of 12 to 600 volts has been created and tested. The designed model has 94.11% efficiency.
Research into the Automatic Guidance System for AGVs Used for Logistics Based on Millimeter Wave Radar Imaging
Authors: Lin Rong
Published: August 2022

AGV technology has been increasingly widely used in intelligent warehousing and logistics as well as automatic chemical plants along with the accelerating industrialization and rapid advancement of the design and manufacturing industry in China. This paper elaborates on the characteristics, application scenarios, and values of AGVs used for logistics, compares and analyzes the common automatic guidance modes of the vehicle, and puts forward a design scheme of AGVs used for logistics system based on millimeter wave radar imaging technology from the perspective of enhancing the accuracy of vehicle guidance. In this scheme, millimeter wave radar, array antenna, and BP forward-looking imaging algorithm are used to present high-resolution target images. Then, according to the result of target trace condensation, the travel route is re planned to realize the automatic guidance of AGVs used for logistics. The simulation results show that the design scheme is highly accurate in target detection and imaging resolution, and thus, the scheme is effective and feasible.
Effect of Multimodal Teaching on Language Comprehensive Ability under the Background of Artificial Intelligence
Authors: Zhang Yuwan , Chen Binbin , Zhang Xiaomei
Published: August 2022

Reading comprehension is an important language learning skill. In English class, we should pay attention to cultivating students’ reading comprehension ability to help students improve their reading comprehension ability. The application of language service products of artificial intelligence has brought great challenges and opportunities to language teaching. This research starts from the current situation of the teaching mode of English language and literature reading under the background of artificial intelligence. The following four questions are mainly studied. Can the multimodal oral teaching model improve students’ oral English performance? Has the students’ spoken English improved in the three aspects of language content, language accuracy, and pronunciation and intonation? Does multimodal oral teaching have a positive impact on students’ attitudes towards oral learning? How can students improve their English writing? This study uses two research methods, experimental research and questionnaire survey, to explore the above research questions through a 16-week multimodal oral teaching experiment. The subjects of the experiment were 61 non-English majors in two parallel classes in the first year of a university in Xi’an. The experiment is divided into three phases: pretest of oral test, implementation of multimodal oral teaching, and posttest of oral test. The experiment proved that most students (about 67.35%) did not show much interest in reading and writing in English. Only a few students (12.24%) like to read and write. It shows that after accepting the multimodal teaching experiment, the students’ oral English scores have been significantly improved, which is reflected in the language accuracy, pronunciation intonation, and language content. The students’ oral English learning attitude is positive after the multimodal oral teaching.
Exploring the Mechanism of Wenshen Huatan Quyu Decotion for PCOS Based on Network Pharmacology and Molecular Docking Verification
Authors: Guo Xin , Xu Yunyi , Sun Juan , Wang Qianqian , Kong Haibo , Zhong Zixing
Published: August 2022

Objective. To identify the active chemical in Wenshen Huatan Quyu Decotion (WHQD) and to explore its possible network interactions with the polycystic ovary syndrome (PCOS). Methods. The Traditional Chinese Medicine Systematic Pharmacology Database and Analysis Platform (TCMSP) and the Bioinformatics Analysis Tool for Molecular Mechanisms in Chinese Medicine (BATMAN-TCM) were used to decompose compound formulations, detect active chemicals and their corresponding target genes, and then convert them into UniProt gene symbols. Meanwhile, PCOS-related target genes were collected from GeneCards to construct a protein-protein interaction (PPI) network, which was further analyzed by STRING online database. Gene Ontology (GO) functional analysis was also performed afterwards to construct the component-target gene-disease network to visualize the correlation between WHQD and PCOS. We then performed an in silico molecular docking study to validate the predicted relationships. Results. WHQD consists of 14 single drugs containing a total of 67 chemical components. 216 genes were predicted as possible targets. 123 of the 216 target genes overlapped with PCOS. GO annotation analysis revealed that 1968 genes were associated with biological processes, 145 with molecular functions, and 71 with cellular components. KEGG analysis revealed 146 pathways involved PPI, and chemical-target gene-disease networks suggest that PGR, AR, ADRB2, IL-6, MAPK1/8, ESR1/2, CHRM3, RXRA, PPARG, BCL2/BAX, GABRA1, and NR3C2 may be key genes for the pharmacological effects of WHQD on PCOS. Molecular docking analysis confirmed that hydrogen bonding was the main interaction between WHQD and its targets. Conclusion. WHQD exerts its pharmacological effects by improving insulin sensitivity, subfertility, and hormonal imbalance, increasing ovulation rates, which in turn may increase pregnancy rates in patients with significant efficacy.
Risk Mechanism and Architecture of Investment and Financing Based on DEA-Malmquist Index
Authors: Chu Jun
Published: August 2022

After the outbreak of the epidemic, the external environment has changed, affecting social and economic development. In the unfavorable economic and social environment, the behavior of many businesses and consumers has also changed. Therefore, companies do not have enough income and expenditure, which leads to the breakage of their capital chain or even bankruptcy. As a result, proper financing has been critical for many businesses in the near term. Today, listed companies are mainly financed from internal financing, equity, and debt. Generally speaking, most companies prefer debt financing because equity financing costs can be deducted before taxes and investment costs are lower than equity financing. Enterprises face certain risks when choosing debt financing; in addition, they also face the risk of future repayment. This paper adopts the research method of DEA-Malmquist index for analysis, which can effectively help enterprises avoid or reduce the risk of debt financing and is worthy of in-depth research and exploration by entrepreneurs and scholars.
The Construction of College English Smart Classroom Based on Artificial Intelligence and Big Data
Authors: Sun Shan , Li Dapeng , Sun Meng
Published: August 2022

In today’s era, the English level of college students is very important. Different English classes can cultivate different English abilities. Smarter classroom is a concept put forward in the new century. This paper proposes the construction of a smarter classroom for college English with artificial intelligence and big data and proposes a deep neural network text semantic matching original model (OM), which uses different lexical information to match different English digital information. Combined with the K-means clustering method, different lexical semantic information is matched. After the comparison of experiments, the combination of the research theory and the algorithm in this paper is effective and has good use value.
Analysis of the Influencing Factors of Enterprise Environmental Ethics on Enterprise Economic Performance
Authors: Jiang Yufang , Lyu Xujie
Published: August 2022

In the information age, people’s awareness of living environmental protection has increased unprecedentedly, and the concept of green environmental protection in enterprise economic behavior has been paid more and more attention by the market and consumers. The integration of green ideas, the improvement of production technology, and the research and development of environmental protection products have become the development trend of enterprises, and environmental ethical responsibility has also become an inevitable problem for enterprises. This paper analyzes the impact of enterprises’ conscious commitment to environmental ethics on their economic benefits, identifies the key influencing factors with the help of scientific statistical methods, analyzes the action mechanism of influencing factors in performance on the basis of the effect model and communication model, and analyzes the correlation between environmental ethics and economic benefits. The experimental results show that the long‐term dissemination of innovation and reputation factors in environmental ethics is conducive to the dissemination of green innovative technologies and products, obtaining the attention and recognition of more enterprises and stakeholders, broadening the scope of cooperation and sales, and obtaining the support of German consumers. Environmental ethics has a short‐term direct effect on performance. When the direct effect is reduced, the intermediary effect of innovation and reputation factors can achieve a positive effect on performance by transmitting benefits.