bluuebunny/crossref_metadata_2025 huggingface dataset:
Effectiveness of checklists in multidisciplinary rounds for improving patient safety in the pediatric intensive care unit: a systematic review protocol
Authors: dos Santos Alves Daniela Fernanda , da Silva Sarah Oliveira , Ullman Amanda , Maia Flávia de Oliveira Motta
Published: June 2022

Objective:

This review will evaluate the effectiveness of checklist use in multidisciplinary rounds, compared with multidisciplinary rounds without checklists, for improving mortality and patient safety in the pediatric intensive care unit.

Introduction:

Single studies have demonstrated that checklists can potentially improve communication of care between health professionals, reduce adverse events, and increase adherence to best practice guidelines. However, no systematic review of the literature has explored the use of checklists in the pediatric intensive care unit.

Inclusion criteria:

This review will consider studies that include pediatric patients, under 18 years of age, admitted to a pediatric intensive care unit. Identified studies will compare the use of checklists in multidisciplinary rounds with multidisciplinary rounds with no checklists. The studies will also evaluate mortality and patient safety outcomes. We will consider experimental and observational studies, published in any language, with no date restrictions.

Methods:

The search strategy will aim to locate both published and unpublished studies. Databases to be searched include MEDLINE, the Cochrane Library, Web of Science, LILACS, Scopus, Embase, CINAHL, the Center for Reviews and Dissemination, Database of Abstracts of Reviews of Effects, and Epistemonikos. The studies will be screened and those meeting the inclusion criteria will be retained by two independent researchers. Assessment of methodology and data extraction will then be carried out. The data will be presented using a narrative synthesis and the studies will be pooled with a statistical meta-analysis, where possible.

Systematic review registration number:

PROSPERO CRD42021233798.
Experiences of health professionals in screening for postpartum depressive symptoms: a qualitative systematic review protocol
Authors: Brito Ana Paula Almeida , Silva Carla Marins , Riesco Maria Luiza , McArthur Alexa
Published: June 2022

Objective:

This review will assess and synthesize the available qualitative evidence on the experiences of health professionals in screening for postpartum depression.

Introduction:

Postpartum depression is a significant public health problem. Clinical screening is essential to develop appropriate interventions to meet the needs of women and their families. The findings of this review will have important implications for decision-making and policy development for continuous professional development programs that promote evidence-based postpartum depression screening.

Inclusion criteria:

This review will consider studies that explore the experiences of health professionals who screen for postpartum depression in any geographic location at any health care level (primary, secondary, or tertiary). The review will focus on qualitative data, including methods such as phenomenology, grounded theory, ethnography, action research, and feminist research.

Methods:

The review will follow a 3-step search strategy, in line with the JBI methodology for systematic reviews of qualitative evidence. The databases to be searched will include MEDLINE, CINAHL, Embase, Scopus, LILACS, ScienceDirect, PsycINFO, Index Psi Periódicos, and PePsic. Unpublished studies will be searched for in Google Scholar, Cybertesis, Dart-E, EthOS, and OATD. Two independent reviewers will evaluate the included studies for methodological quality and extract data using the JBI data extraction and synthesis tools. There will be no language or date limitations.

Systematic review registration number:

PROSPERO CRD42021253792.
Efficacy of digital nasoalveolar molding in reducing severity of cleft lip or palate malformation in infants: a systematic review protocol
Authors: Chaudhari Prabhat Kumar , Dhingra Kunaal , Dhillon Harnoor , Zere Edlira , Sharan Jitendra , Kumar Amit , Alam Mohammad Khursheed , Marya Anand
Published: June 2022

Objective:

This review will compare the efficacy of nasoalveolar molding plates fabricated using a digital workflow to conventional fabrication methods or no intervention in infants with cleft lip or palate.

Introduction:

Nasoalveolar molding reduces the severity of orofacial defects in infants with cleft lip or palate using a series of adaptable plates for the maxillary arch. The conventional method needs multiple patient visits at short intervals for treatment. A digital workflow can be used to fabricate multiple plates in one appointment, which eliminates human error, reduces the number of appointments, and allocates more time for patient care for the orthodontic team than appliance fabrication.

Inclusion criteria:

This review will consider clinical studies that report the results of digital nasoalveolar molding in infants with cleft lip or palate and compare it to the conventional method or to no treatment. Outcomes of interest will be objective measures of craniofacial form, nasolabial measurements, or palatal form.

Methods:

This review will be conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Databases including PubMed, Embase, Cochrane Oral Health Group Trial Register, and ClinicalTrials.gov will be searched using appropriate keywords. Publications in English will be considered. Screening based on titles and abstracts will be done after de-duplication, followed by full-text reading for selection based on the inclusion criteria. Data extracted from the studies will be tabulated and assessed for risk of bias. If applicable, a meta-analysis of the pooled data will be conducted.

Systematic review registration number:

PROSPERO CRD42020186452
Nursing students’ experiences of a post-licensure practical nurse bridging program: a qualitative systematic review protocol
Authors: McCloskey Rose , Keeping-Burke Lisa , Morris Patricia , Witherspoon Richelle , Knight Holly , Cave Sara
Published: June 2022

Objective:

This systematic review will synthesize the qualitative literature on students’ experiences of a post-licensure practical nurse to registered nurse bridging program.

Introduction:

The worldwide shortage of registered nurses has prompted governments and educational institutions to develop alternative pathways to nursing licensure. One strategy used to increase the supply of registered nurses is bridging programs. These grant practical nurses academic credit for previous educational and practical experience, which allows them to complete a Bachelor of Nursing degree in a shorter period of time. However, attrition in bridging programs is a concern. Understanding the experiences of students enrolled in bridging programs will help identify their specific needs and the educational support needed for them to successfully transition into the registered nursing role.

Inclusion criteria:

This review will include published and unpublished studies that examine the experiences of practical nurses enrolled in bridging programs. Studies published in English will be considered, with no date limitations.

Methods:

Databases to be searched include CINAHL, MEDLINE, Embase, and ERIC. Gray literature will be searched for in ProQuest Dissertations and Theses and GreyNet International. Reference lists of included studies will also be reviewed to identify additional studies. The critical appraisal of selected studies and the extraction of data will be independently undertaken by two reviewers using JBI methodology. The findings will be pooled using meta-aggregation to produce comprehensive synthesized findings. A ConQual Summary of Findings will also be presented.

Systematic review registration number:

PROSPERO CRD42021278408
Low Muscle Strength, Low Bone Mineral Density, and High Body Mass Index Among Adult Special Olympics Athletes: A Cross-Sectional Examination
Authors: Cleveringa Morgan , Pitchford E. Andrew
Published: June 2022

Adults with intellectual disabilities have increasing life expectancy but may be susceptible to early aging-related conditions. The purpose of this study was to examine associations between the presence of low muscle strength, low bone mineral density, and high body mass index with age and sex in adult Special Olympics athletes. Grip strength (n = 6,477; 40.9% female), chair stand time (n = 6,444; 40.5% female), body mass index (n = 7,824; 43.7% female), and bone mineral density (n = 3,091; 43.2% female) measurements were provided by Special Olympics International. Poor grip strength, chair stand time, bone mineral density, and body mass index were identified in 43.8%, 46.2%, 28.7%, and 50.3% of each sample, respectively. Increasing age was a risk factor for all conditions (odds ratio = 1.30–10.89; p < .05). High rates of adverse health conditions were observed in a sample of adults with intellectual disabilities. Increased risk was observed as early as the fourth decade of life.
Print Media Framing of the Olympic Games Before Canadian Referendums: The Cases of Calgary 2026 and Vancouver 2010
Authors: Monaghan Jared F.K. , Rocha Claudio M.
Published: June 2022

This study used a quantitative content analysis and a qualitative thematic analysis to explore how the Olympic Games were framed in print media prior to two Canadian Winter Olympic referendums. Content-analysis results showed that the salient topics and the tone of newspaper articles were framed more positively prior to the successful Vancouver 2010 referendum compared with the unsuccessful Calgary 2026 referendum. The thematic analysis indicated four themes. First, news discourse emphasized the importance of Olympic vision that is congruent with host city needs. Second, the prominence of health promotion through sport as a reported theme was more associated with a successful bid. Third, the communication and quantification of intangible benefits were reported to be increasingly important so that the value of the Olympics can be assessed fairly against the ever-burgeoning hosting costs. Finally, the Olympic brand has been deteriorating, at least over the last 15–16 years according to print media. Implications for theory and practice are discussed.
Relationship Between Dual-Energy X-Ray Absorptiometry, Ultrasonography, and Anthropometry Methods to Estimate Muscle Mass and Muscle Quality in Older Adults
Authors: Schemes Márcio Beck , Bach Simone de Azevedo , Machado Carlos Leonardo Figueiredo , Neske Rodrigo Rabuski , Schneider Cláudia Dornelles , Pinto Ronei Silveira
Published: June 2022

Decreased muscle quality (MQ) may explain functional capacity impairments during aging. Thus, it is essential to verify the interaction between MQ and functional capacity in older adults. We investigated the relationship between MQ and functional capacity in older adults (n = 34; 66.3 ± 4.6 year). MQ was estimated by maximum strength of knee extensors normalized to thigh muscle mass. Maximum strength was assessed on an isokinetic dynamometer (peak torque), while dual-energy X-ray absorptiometry (DXA), ultrasonography, and anthropometry were used to determine thigh muscle mass. Functional capacity was verified by 30-s sit to stand and timed up and go tests. Significant correlations were found between MQ assessed by DXA with 30-s sit to stand (r = .35; p < .05) and timed up and go (r = −.47; p < .05), and MQ assessed by anthropometry with timed up and go (r = −.41; p < .05), but not between MQ assessed by ultrasonography with functional capacity (p > .05). No significant relationship between muscle mass with functional capacity was observed. Thus, MQ assessed by DXA and MQ assessed by anthropometry may partially explain functional capacity in older adults. Interestingly, muscle mass alone did not explain performance in functional tests in this population.
Feasibility of a Novel Video Game-Based Electromyography Biofeedback System in Patients With Knee Osteoarthritis
Authors: Krepkovich Eileen , Kaur Mandeep , Mangum L. Colby , Saliba Susan , Lichter Matthew , Olowin Aaron , Richardson Neal , Hart Joseph
Published: June 2022

Context: A novel virtual game system Knee Biofeedback Rehabilitation Interface for game-based home therapy (KneeBright) was developed for strength training using integrated electromyography biofeedback of the quadriceps muscle to control the game. The study aimed to compare the KneeBright and electromyography biofeedback interface among patients with knee osteoarthritis. Design: Controlled before and after design. Methods: Nineteen patients with knee osteoarthritis took part in this laboratory-based study. Exercise sessions took place on 2 separate days. During session 1, participants used a conventional electromyography biofeedback system while performing 3 sets of lower body exercises with emphasis on maximal muscle activation, endurance, and precision. During session 2, participants used the KneeBright game to match the exercise sets in the first session. For both sessions, knee extension torque during the isometric muscle activation exercises and time to voluntary additional exercise were recorded. Patient engagement was assessed using the technology acceptance model and System Usability Score questionnaires. Results: The peak knee extension torque produced during the control exercise session and the KneeBright exercise session were positively correlated. Knee extension torque generated during KneeBright game exercise sessions was increased by an average of 25% compared to the control sessions (2.14 vs 1.77 N·m/kg, P = .02). The mean technology acceptance model score for the KneeBright system was 3.4/5 and the mean System Usability Score was 79, both indicating positive patient engagement. Conclusions: Patients using the KneeBright game produced greater knee torque than patients using the conventional system, had positive levels of engagement, and exercised longer with the KneeBright game.
The Role of the Type of Sport in the Effects of the Jigsaw Method on Students’ Motivation and Moderate to Vigorous Physical Activity in Physical Education
Authors: Cochon Drouet Océane , Lentillon-Kaestner Vanessa , Roure Cédric , Margas Nicolas
Published: June 2022

Purpose: Jigsaw is a popular cooperative method, but its effect on students’ motivation in physical education (PE) remains uncertain. The purpose of this study was to estimate this Jigsaw effect and to explore whether the type of sport taught in PE modified this effect. Method: Overall, 136 middle-school students participated in two PE sequences in Jigsaw or control conditions, one in gymnastics and one in racket sports. These two types of sports were selected because they are frequently taught in PE and for their opposing characteristics. Students’ motivation was estimated during the third and sixth lessons of each sequence with a subjective measure, that is, situational interest; moderate to vigorous physical activity was added as an objective measure related to motivation. Results: Compared to control conditions, Jigsaw progressively enhanced moderate to vigorous physical activity and the novelty dimension of situational interest in gymnastics, whereas it undermined moderate to vigorous physical activity and the challenge dimension of situational interest in rackets. Discussion: We discuss the decisive role of the type of sport according to their characteristics when implementing Jigsaw.
Seasonal Variations in the b-Value of the Reservoir-Triggered Seismicity in the Koyna–Warna Region, Western India
Authors: Smirnov V. B. , Potanina M. G. , Kartseva T. I. , Ponomarev A. V. , Patonin A. V. , Mikhailov V. O. , Sergeev D. S.
Published: June 2022

Abstract—The analysis of the local earthquake catalog revealed fine features in the behavior of seasonal components of induced seismicity in the Koyna–Warna region, western India. The seasonal variations in seismicity associated with annual fluctuations in water levels in the Koyna and Warna reservoirs have local maxima during the year, corresponding to the known mechanisms of immediate and delayed responses of reservoir-triggered seismicity (RTS). The superposed epoch analysis combined with the stochastic modeling of random earthquake catalogs revealed regular changes in the b-value of the frequency–magnitude relationship of the earthquakes within the annual cycle of seasonal seismicity fluctuations. The minimum b-values fall in the intervals of the maxima of both the immediate and delayed seismic responses. The maximum b-values are observed during the rise and fall phases of water levels in the reservoirs. The pattern of changes in the seismicity together with the b-value behavior at the activation phase of the immediate RTS response is consistent with the scenario of gradual redistribution of the failure process from the lower to higher scales, characteristic of the activation of transient seismicity. A pilot laboratory experiment on cyclic initiation of fracture process by pore pressure in a granite sample extracted from a well in the Koyna–Warna region of reservoir-triggered seismicity demonstrated the patterns of changes in the acoustic regime similar to the seasonal features of the Koyna–Warna region seismicity.
ID-Based Multireceiver Homomorphic Proxy Re-Encryption in Federated Learning
Authors: Fan Chun-I , Hsu Ya-Wen , Shie Cheng-Han , Tseng Yi-Fan
Published: June 2022

Data privacy has become a growing concern with advances in machine learning. Federated learning (FL) is a type of machine learning invented by Google in 2016. In FL, the main aim is to train a high-accuracy global model by aggregating the local models uploaded by participants, and all data in the process are kept locally. However, compromises to security in the cloud server or among participants render this process insufficiently secure. To solve the problem, this article presents an identity-based multireceiver homomorphic proxy re-encryption (IMHPRE) scheme that utilizes homomorphism operations and re-encryption to provide improved encrypted-data processing and access control. When this scheme is employed, participants can directly use public identities for encryption. The IMHPRE scheme is also secure against the chosen-plaintext attacks. Comparison results indicated that the IMHPRE outperforms its counterparts because it allows a cloud server to perform model aggregation on re-encrypted models for multiple receivers.
Supervised Contrastive Learning for Interpretable Long-Form Document Matching
Authors: Jha Akshita , Rakesh Vineeth , Chandrashekar Jaideep , Samavedhi Adithya , Reddy Chandan K.
Published: June 2022

Recent advancements in deep learning techniques have transformed the area of semantic text matching (STM). However, most state-of-the-art models are designed to operate with
short
documents such as tweets, user reviews, comments, and so on. These models have fundamental limitations when applied to long-form documents such as scientific papers, legal documents, and patents. When handling such long documents, there are three primary challenges: (i) the presence of different contexts for the same word throughout the document, (ii) small sections of contextually similar text between two documents, but dissimilar text in the remaining parts (this defies the basic understanding of “similarity”), and (iii) the coarse nature of a single global similarity measure which fails to capture the heterogeneity of the document content. In this article, we describe
CoLDE
:
Co
ntrastive
L
ong
D
ocument
E
ncoder—a transformer-based framework that addresses these challenges and allows for interpretable comparisons of long documents. CoLDE uses unique positional embeddings and a multi-headed chunkwise attention layer in conjunction with a supervised contrastive learning framework to capture similarity at three different levels: (i) high-level similarity scores between a pair of documents, (ii) similarity scores between different sections within and across documents, and (iii) similarity scores between different
chunks
in the same document and across other documents. These fine-grained similarity scores aid in better interpretability. We evaluate CoLDE on three long document datasets namely, ACL Anthology publications, Wikipedia articles, and USPTO patents. Besides outperforming the state-of-the-art methods on the document matching task, CoLDE is also robust to changes in document length and text perturbations and provides interpretable results. The code for the proposed model is publicly available at
https://github.com/InterDigitalInc/CoLDE
.
Multi-Turn and Multi-Granularity Reader for Document-Level Event Extraction
Authors: Yang Hang , Chen Yubo , Liu Kang , Zhao Jun , Zhao Zuyu , Sun Weijian
Published: June 2022

Most existing event extraction works mainly focus on extracting events from one sentence. However, in real-world applications, arguments of one event may scatter across sentences and multiple events may co-occur in one document. Thus, these scenarios require document-level event extraction (DEE), which aims to extract events and their arguments across sentences from a document. Previous works cast DEE as a two-step paradigm: sentence-level event extraction (SEE) to document-level event fusion. However, this paradigm lacks integrating document-level information for SEE and suffers from the inherent limitations of error propagation. In this article, we propose a multi-turn and multi-granularity reader for DEE that can extract events from the document directly without the stage of preliminary SEE. Specifically, we propose a new paradigm of DEE by formulating it as a machine reading comprehension task (i.e., the extraction of event arguments is transformed to identify the answer span from the document). Beyond the framework of machine reading comprehension, we introduce a multi-turn and multi-granularity reader to capture the dependencies between arguments explicitly and model long texts effectively. The empirical results demonstrate that our method achieves superior performance on the MUC-4 and the ChFinAnn datasets.
Enabling Short-Term Energy Flexibility Markets Through Blockchain
Authors: Boerger Michell , Lämmel Philipp , Tcholtchev Nikolay , Hauswirth Manfred
Published: June 2022

Climate change has put significant pressure on energy markets. Political decisions such as the plan of the German government to shut down coal power plants by 2038 are shifting electricity production towards renewable and distributed energy resources. The share of these resources will continue to grow significantly in the coming years. This trend changes the ways how energy markets work which mandates fundamental changes in the underlying IT infrastructure. In this paper, we propose a blockchain-based solution which enables an economically viable and grid-serving integration of distributed energy resources into the existing energy system. Our blockchain-based approach targets intraday and day-ahead operating reserve markets, on which energy grid operators and operators of distributed energy resources can trade flexibilities within the schedulable energy production and consumption of their resources. By utilizing these flexibilities as an operating reserve, renewable and climate-friendly technologies can contribute to maintaining the grid stability and security of supply while simultaneously creating economically interesting business models for their operators. We propose to define blockchain-based short-term energy markets by utilizing the concept of general-purpose smart contracts and cryptocurrencies. This enables direct and decentralized trading of energy flexibilities without any intermediary or central instance. We demonstrate the feasibility of our approach through an implementation of a prototype of the proposed markets based on the Ethereum blockchain and provide a detailed evaluation of its efficiency and scalability.
Early Findings on the Impacts of Developing Evidence-Based Practice Briefs on Middle School Computer Science Teachers
Authors: McGill Monica M. , Reinking Anni
Published: June 2022

Problem.
K-12 teachers face many challenges when teaching a new subject like computer science (CS). They are often far removed from the research being conducted to identify evidence-driven solutions to these challenges. Likewise, researchers are also often removed from the challenges of classroom practices that teachers face when teaching CS.

Research Questions.
To create a collaborative process for teachers and researchers
outside
of a research practice partnership, we piloted a facilitated process in which CS middle school teachers and CS education researchers collaboratively created CS teacher practice briefs. Our research question for this study was:
In what ways are teachers impacted by the process of creating teacher practice briefs in collaboration with researchers?

Methodology.
We conducted a qualitative study, using a semi-structured interview protocol to interview five teachers and three researchers to gain an understanding of how this process impacted the participants. We used thematic content analysis to identify several subthemes across our pre-established themes: motivation for teachers to participate, impacts on teachers, perceived impacts on students, and impacts on researchers.

Findings.
We found that the impact on teachers mirrored impacts found on teachers who engage in Research Practice Partnerships, including increased self-efficacy, expanded professional networks, and changed classroom practices.

Implications.
By bringing researchers and educators together with a clear focus on equity-based problems of practice in CS education, the results display a multitude of positive impacts. Teachers indicate that they are are positively impacted, researchers develop a clear understanding of realistic practices, and students are peripherally impacted through changed practices in the classroom. Therefore, the most significant contribution to advance the disciplinary understanding is the potential for this new process to decrease the gap between research and practice.
Progressive Localization Networks for Language-Based Moment Localization
Authors: Zheng Qi , Dong Jianfeng , Qu Xiaoye , Yang Xun , Wang Yabing , Zhou Pan , Liu Baolong , Wang Xun
Published: June 2022

This article targets the task of language-based video moment localization. The language-based setting of this task allows for an open set of target activities, resulting in a large variation of the temporal lengths of video moments. Most existing methods prefer to first sample sufficient candidate moments with various temporal lengths, then match them with the given query to determine the target moment. However, candidate moments generated with a fixed temporal granularity may be suboptimal to handle the large variation in moment lengths. To this end, we propose a novel multi-stage Progressive Localization Network (PLN) that progressively localizes the target moment in a coarse-to-fine manner. Specifically, each stage of PLN has a localization branch and focuses on candidate moments that are generated with a specific temporal granularity. The temporal granularities of candidate moments are different across the stages. Moreover, we devise a conditional feature manipulation module and an upsampling connection to bridge the multiple localization branches. In this fashion, the later stages are able to absorb the previously learned information, thus facilitating the more fine-grained localization. Extensive experiments on three public datasets demonstrate the effectiveness of our proposed PLN for language-based moment localization, especially for localizing short moments in long videos.
Realization of Music-Assisted Interactive Teaching System Based on Virtual Reality Technology
Authors: Gao Yan , Gao Lin
Published: June 2022

Virtual reality technology has attracted researchers’ attention because it can provide users with a virtual interactive learning environment. Based on the theory of virtual reality technology, this paper proposes the system model design and architecture of virtual interactive music-assisted interactive teaching and realizes key technologies such as modeling, music-assisted interactive teaching scene interaction, and database access. In the simulation process, based on the VRML/X3D bottom interactive system template, after comprehensive application research, comparative analysis of various modeling methods, the system verified the use of digital cameras combined with the modeling technology based on music elements to collaboratively establish VRML virtual model connections. For inline node function, we combined it with Outline3D to realize VRML integration and then use VizX3D, X3D-Edit to build X3D model and realize the conversion from VRML to X3D, which solves the system completeness problem of music-assisted interactive teaching. The experimental results show that, according to the statistical analysis of the data after the experiment, when the position changes in the virtual 3D music-assisted interactive teaching scene, it will be displayed in the plane layer, and the real-time coordinates of the virtual music-assisted interactive teaching scene displayed in HTML have case. By analyzing the scenes and dynamic effects in the works, the effects of the virtual world can be better displayed through the performance of details. The better accuracy and delay error reached 89.7% and 3.11%, respectively, which effectively improved the effect and feasibility of applying virtual reality technology to music-assisted interactive teaching.
Design of Growth Trend Map of Children and Adolescents Based on Bone Age
Authors: Chen Kaiyan , Shi Weiyuan , Mao Keji , He Wenxiu , Ahmed Ahmedin M. , Fang Kai
Published: June 2022

Accurate height prediction has important reference significance for the development of children and adolescents and the selection of athletes. The current mainstream height prediction methods include the B-P (Bayley–Pinneau) method and the TW2 (Tanner–Whitehouse) method. A large number of documents show that the B-P method and the TW2 method have relatively large deviations in the lifelong height prediction results of Chinese children and adolescents. Based on the data collected by the Chinese Adolescent Students’ Physical Fitness and Growth and Development Health Project in Zhejiang’s primary and secondary schools, this paper proposes a graph of height growth trends based on bone age. The height map of age has more reference value. Aiming at the feasibility of the height data in the statistical results, the interpolation prediction method is used to verify the data, and the height growth trend graph is drawn through the method of fitting. Validation results with actual data show that the average error of the lifetime height prediction of the height growth trend map proposed in this paper is 2.1 cm, which is 1.4 cm lower than the 3.5 cm error predicted by the B-P method and 0.4 cm lower than the 2.5 cm error predicted by the TW2 method.
Multimedia Tilt Photography-Assisted Remote Sensing Technology in Mine Ecological Restoration
Authors: He Yanjun , Chen Shuzhao , Zhang Bin , Chen Kai
Published: June 2022

Ecological restoration with the assistance of certain artificial measures is to restore the original ecological function and productivity of the ecosystem or to make the ecosystem develop to a virtuous circle, which is a complex systematic project. Based on this, combined with the actual needs of a mine ecological restoration project, this paper puts forward the technical process and method of quickly acquiring the geographic information of abandoned mines by using the oblique photography technology of unmanned aerial vehicles. The verification results show that the maximum plane/elevation residual error of the checkpoints measured in the field is 0.221 m−0.181 m, and the median error is 0.030 m–0.112 m. According to the encryption requirement of 1∶500 scale topographic mapping in hilly land, the plane position error of the inspection point relative to the field control point should be less than 0.175 m. The elevation should be less than 0.280 m, and the experimental results in this paper can meet the requirements. Oblique photography can provide abundant digital results, and it can play an important role in mine restoration scheme design, restoration construction, and monitoring and management after restoration.
Serum IMA and LP-PLA2 Levels in Patients with Coronary Heart Disease and Their Correlation with the Degree of Myocardial Ischaemia and Their Diagnostic Value
Authors: Zhang Likui , Li Zipeng , Li Ning
Published: June 2022

Purpose. To measure serum levels of ischaemia-modified albumin (IMA) and lipoprotein-associated phospholipase A2 (LP-PLA2) in patients with coronary heart disease (CHD) and to analyse their correlation with the degree of myocardial ischaemia and their diagnostic value. Methods. A sample of 150 patients diagnosed with CHD by coronary angiography in our hospital from March 2019 to September 2021 was taken as the CHD group. The patients were divided into acute myocardial infarction (AMI) group (n = 52), unstable angina pectoris (UAP) group (n = 54), and stable angina pectoris (SAP) group (n = 44) according to the degree of myocardial ischaemia, and then 50 healthy physical examination patients were selected as the health group during the same period. Serum C-reactive protein (CRP), interleukin-6 (IL-6), IMA, and LP-PLA2 levels were measured in each group separately. Multiple ordered logistic regression was used to analyse the factors influencing the degree of myocardial ischaemia in patients with CHD. Pearson correlation was used to analyse the correlation between serum IMA, LP-PLA2 levels and serum CRP, IL-6 levels in CHD patients. The diagnostic value of IMA alone, LP-PLA2 alone, and in combination for CHD was analysed using receiver operating characteristic (ROC) curves. Results. In terms of serum CRP, IL-6, IMA, and LP-PLA2 levels, the CHD group was higher than the health group, the AMI and UAP groups were higher than the SAP and health groups, and the AMI group was higher than the UAP group (

P
<
0.05

). Multiple ordered logistic regression analysis showed that serum CRP, IL-6, IMA, and LP-PLA2 levels were all independent influences on the degree of myocardial ischaemia in patients with CHD (

P
<
0.05

). Pearson correlation analysis showed a positive correlation between serum IMA, LP-PLA2 levels and serum CRP, IL-6 levels in CHD patients (

P
<
0.001

). The area under curve (AUC) for serum IMA levels to predict myocardial ischaemia in patients with CHD was 0.754 (95% CI: 0.684–0.825), with a sensitivity of 61.3% and specificity of 84.0% when the best cut-off value was 0.453; the AUC for serum LP-PLA2 levels to predict myocardial ischaemia in patients with CHD was 0.747 (95% CI: 0.681–0.813), with a sensitivity of 62.0% and specificity of 82.0% when the optimal cut-off value was 0.440; and the AUC of IMA + LP-PLA2 for predicting myocardial ischaemia in patients with CHD was 0.892 (95% CI: 0.847–0.938), with a sensitivity of 86.7% and specificity of 80.0% when the optimal cut-off value was 0.667. The specificity was 80.0%. Conclusions. Serum IMA and LP-PLA2 levels are elevated in patients with CHD. Serum IMA and LP-PLA2 levels are closely related to the degree of myocardial ischaemia and its inflammatory level, and the combination of IMA + LP-PLA2 can improve the diagnosis efficacy of myocardial ischaemia in CHD patients.
The Artificial Intelligence and Neural Network in Teaching
Authors: Luo Qun , Yang Jiliang
Published: June 2022

This study aims to explore the application of artificial intelligence (AI) and network technology in teaching. By studying the AI-based smart classroom teaching mode and the advantages and disadvantages of network teaching using network technology and taking the mathematics classroom as an example, this study makes an intelligent analysis of the questioning link of classroom teachers in the teaching process. For the questions raised by teachers, the network classification models of convolutional neural network (CNN) and long short-term memory (LSTM) are used to classify the questions according to the content and types of questions and carry out experimental verification. The results show that the overall performance of the CNN model is better than that of the LSTM model in the classification results of the teacher’s question content dimension. CNN has higher accuracy, and the classification accuracy of essential knowledge points reaches 86.3%. LSTM is only 79.2%, and CNN improves by 8.96%. In the classification results of teacher question types, CNN has higher accuracy. The classification accuracy of the prompt question is the highest, reaching 87.82%. LSTM is only 83.2%, and CNN improves by 4.95%. CNN performs better in teacher question classification results.
The Improvement of Automated Crack Segmentation on Concrete Pavement with Graph Network
Authors: Chen Jiang , Yuan Ye , Lang Hong , Ding Shuo , Lu Jian John
Published: June 2022

Crack is a common concrete pavement distress that will deteriorate into severe problems without timely repair, which means the automated detection of pavement crack is essential for pavement maintenance. However, automatic crack detection and segmentation remain challenging due to the complex pavement condition. Recent research on pavement crack detection based on deep learning has laid a good foundation for automated crack segmentation, but there can still be improvements. This paper proposes an automatic concrete pavement crack segmentation framework with enhanced graph network branch. First, the nodes of the graph and nodes’ attributions are generated based on the image dividing. The edges of the graph are determined based on Gaussian distribution. Then, the graph from the image is input into the graph branch. The graph feature map of the graph branch output is fused with the image feature map of the encoder and then enters the decoder to recover the image resolution to obtain the crack segmentation result. Finally, the method is tested on a self-built 3D concrete pavement crack dataset. The proposed method achieves the highest F1 and IoU (Intersection over Union) in the comparison experiments. And the graph branch addition improves 0.08 on F1 and 0.06 on IoU compared with U-Net.
Design and Implementation of Online Education Mode of Music Course Based on Web
Authors: Yu Jiakun , Gong Yufei
Published: June 2022

In order to meet people’s demand for music, especially the obsession of contemporary young people with music, through the design of online education mode of music course on the web, we can realize the online education of students by using the network platform, which is conducive to the reasonable arrangement of students’ time and course management. With the enrichment of materials, the demand of the young generation for the spiritual world has attracted more and more attention, especially the element that can relieve human emotions, such as music, is more popular in the market among young people. The traditional music teaching mode does not pay attention to the design of music courses, only weak preaching, which makes students’ interest in music appreciation not high, and online education of music courses on the web can satisfy it. The emergence of music course auxiliary teaching system based on the web enables students to find more platforms to stimulate their interests and hobbies, and bring new learning experience to students through the system, which is conducive to enriching their after-school life and improving their self-cultivation.
Research on Public Administration and Resource Allocation Based on Blockchain and Structured Occupational Therapy
Authors: Zhu Qiyou
Published: June 2022

In order to explore the public administration and resource allocation based on blockchain and structured occupational therapy, this paper takes the public affairs in the prevention and control of the Corona Virus Disease 2019 (COVID-19) epidemic as an example to conduct research. On the basis of summarizing and analyzing the previous published literatures, this study expounded the research status and significance of public administration and resource allocations; elaborated the development background, current status and future challenges of blockchain, and structured occupational therapy; introduced the methods and principles of data quality collaboration model and multiparty collaboration standard management; analyzed the case background of public administration and resource allocation in the prevention and control of the COVID-19 epidemic; discussed the public administration mechanism based on blockchain and structured occupational therapy; established a resource allocation method based on blockchain and structured occupational therapy; fathomed the role of the distributed ledger established by blockchain to increase the information symmetry of public administration activities; proposed a blockchain-established special machine trust for resource allocation; and finally, anatomized the data security sharing and access control mechanism based on blockchain and structured occupational therapy. The research results show that the public administration and resource allocation in this paper can effectively realize the data integration of the whole process and all departments and show the whole data and realize the traceability of the whole process. The blockchain revolutionizes the hierarchical leadership method of traditional resource allocation, shortens the distance between superiors and subordinates, makes information dissemination more fluent, and handles things more efficiently, making resource allocation ultimately form a flatter organization structure. In the original trust system of resource allocation, the blockchain and structured occupational therapy realizes the reconstruction of the trust system by preventing information tampering, using information encryption technology, and using information traceability technology. The results of this paper provide a reference for further research on the public administration and resource allocation based on blockchain and structured occupational therapy.
Mobile Sink-Based Path Optimization Strategy in Heterogeneous WSNs for IoT Using Pigeon-Inspired Optimization Algorithm
Authors: Wang Zhengzong , Yue Yinggao , Cao Li
Published: June 2022

Data collection is the basic purpose of deploying in heterogeneous WSNs for Internet of things, and the problem of data collection is the key problem that needs to be solved in heterogeneous WSNs. How to collect energy-efficient and reliable data is one of the key technologies of heterogeneous WSNs. Collecting the sensor node data by mobile sink is an effective measure to solve data collection efficiency. To this end, a data collection strategy of mobile sink for heterogeneous WSNs based on pigeon-inspired optimization by PSO algorithm is proposed. The proposed algorithm uses the improved pigeon-inspired optimization by particle swarm optimization algorithm to select the best dwell point and then regards the construction of the moving path based on the dwell point as a traveling salesman problem to optimize the moving path and solve the optimal moving path. The experimental analysis and simulation results show that, compared with other algorithms, the algorithm proposed in this paper can effectively prolong the lifetime of the network and reduce the delay of data collection, increasing the amount of data collection.
NLP Technique for Malware Detection Using 1D CNN Fusion Model
Authors: Yeboah Paul Ntim , Baz Musah Haruna Balle
Published: June 2022

With the record of the highest market share of mobile operating systems, the Android operating system has become a prime target for cyber perpetrators as malicious applications are leveraged as attack vectors to exploit Android systems. Machine learning detection solutions that have become a resort mostly rely on handcrafted features, a process deemed to be laborious and time-consuming. In this article, we employ a deep learning-based model consisting of 1-dimensional convolutional neural network (1D CNN) to automate the detection of Android malware. Our choice of 1D CNN was motivated by the computational advantage of 1D convolution operations over 2D CNN. The proposed model automatically extracts features from semantically embedded n-grams of raw static operation code (opcodes) sequences to determine the maliciousness of a binary file. Predictions of the 1D CNN model trained on multiple feature sets of n-gram opcode sequences are combined using a weighted average ensemble. Optimal prediction weights were obtained using a grid search on values in the range 0 to 1. With an Android dataset comprising 4951 malware and 2477 benign samples, our model yielded a positive predictive value of 98% and sensitivity of 97% using a weight parity of 0.5 for ensemble unigram and bigram opcode sequences.
Correlation Analysis of Japanese Literature and Psychotherapy Effects Based on an Equation Diagnosis Algorithm
Authors: Tingting Zhang
Published: June 2022

Objective. On the basis of inheriting the classical aesthetic orientation of Japanese literature, contemporary Japanese literature changes the creative methods of traditional Japanese writers, strives to transcend the national limitations of Japanese literature, and strives to capture literary materials with a “modern feel.” Combined with modern western literary techniques to express the “modern self,” and integrating popular literature with pure literature, Japanese writers created a “healing” literature that is popular all over the world. There is some value in exploring the correlation between Japanese literature and the influence of psychotherapy. Method. In this paper, an equation diagnosis algorithm based on iterative learning for a class of linear discrete systems is studied, and the existing discrete iterative learning diagnostics are improved. We exchange the order of time domain and iterative domain to achieve the purpose of point-by-point equation diagnosis. On this basis, a virtual influence initial value estimation algorithm with a sliding window is proposed. The impact that has not been diagnosed is estimated and used as the initial value of the impact, so as to reduce the number of iterations and improve the efficiency of equation diagnosis. This paper takes the public and readers as different perspectives, based on the use and satisfaction theory and prospect theory, and uses interviews and questionnaires to study the communication effect of Japanese literature from the three dimensions of cognition, emotion, and behavior. The cognitive part includes the public’s understanding and readers’ understanding and reading; the emotional part includes the public’s and readers’ impressions and emotional attitudes; the behavioral part includes the public’s reading situation and readers’ behavior changes. Results/Discussion. In the survey of loyal readers, although readers’ understanding of Japanese literature has improved compared with the general public, it is not high, and their liking and influence on behavior are slightly lower than the preset level. This paper believes that the existing problems of Japanese literature dissemination are mainly concentrated in three aspects: the market is somewhat biased, which narrows the cognitive scope of users; as a cross-cultural literary work, Japanese literature still makes readers feel that it exists; there is some sense of estrangement, which will affect their enjoyment in reading; as a niche interest, readers lack timely communication and sharing objects after reading, so it is difficult to enhance their sense of identity.