bluuebunny/crossref_metadata_2025 huggingface dataset:
Protocol for a feasibility study of a cancer symptom awareness campaign to support the rapid diagnostic centre referral pathway in a socioeconomically deprived area: Targeted Intensive Community-based campaign To Optimise Cancer awareness (TIC-TOC)
Authors: Smith Pamela , Moody Gwenllian , Clarke Eleanor , Hiscock Julia , Cannings-John Rebecca , Townson Julia , Edwards Adrian , Quinn-Scoggins Harriet D , Sewell Bernadette , Jones Daniel , Lloydwin Christina , Thomas Sara , Casey Dawn , Lloyd-Bennett Catherine , Stanton Helen , Lugg-Widger Fiona V , Huws Dyfed , Watkins Angela , Newton Gareth , Thomas Ann Maria , McCutchan Grace M , Brain Kate
Published: October 2022

Introduction

Rapid diagnostic centres (RDCs) are being implemented across the UK to accelerate the assessment of vague suspected cancer symptoms. Targeted behavioural interventions are needed to augment RDCs that serve socioeconomically deprived populations who are disproportionately affected by cancer, have lower cancer symptom awareness and are less likely to seek help for cancer symptoms. The aim of this study is to assess the feasibility and acceptability of delivering and evaluating a community-based vague cancer symptom awareness intervention in an area of high socioeconomic deprivation.

Methods and analysis

Intervention materials and messages were coproduced with local stakeholders in Cwm Taf Morgannwg, Wales. Cancer champions will be trained to deliver intervention messages and distribute intervention materials using broadcast media (eg, local radio), printed media (eg, branded pharmacy bags, posters, leaflets), social media (eg, Facebook) and attending local community events. A cross-sectional questionnaire will include self-reported patient interval (time between noticing symptoms to contacting the general practitioner), cancer symptom recognition, cancer beliefs and barriers to presentation, awareness of campaign messages, healthcare resource use, generic quality of life and individual and area-level deprivation indicators. Consent rates and proportion of missing data for patient questionnaires (n=189) attending RDCs will be measured. Qualitative interviews and focus groups will assess intervention acceptability and barriers/facilitators to delivery.

Ethics and dissemination

Ethical approval for this study was given by the London—West London & GTAC Research Ethics (21/LO/0402). This project will inform a potential future controlled study to assess intervention effectiveness in reducing the patient interval for vague cancer symptoms. The results will be critical to informing national policy and practice regarding behavioural interventions to support RDCs in highly deprived populations.
Dose optimisation and scarce resource allocation: two sides of the same coin
Authors: Strohbehn Garth , Persad Govind , Parker William F , Murthy Srinivas
Published: October 2022

Objective

A deep understanding of the relationship between a scarce drug's dose and clinical response is necessary to appropriately distribute a supply-constrained drug along these lines.

Summary of key data

The vast majority of drug development and repurposing during the COVID-19 pandemic – an event that has made clear the ever-present scarcity in healthcare systems –has been ignorant of scarcity and dose optimisation's ability to help address it.

Conclusions

Future pandemic clinical trials systems should obtain dose optimisation data, as these appear necessary to enable appropriate scarce resource allocation according to societal values.
Development of a respiratory quality improvement faculty in an acute hospital using QI methodology
Authors: Boast Lucy Anne , Hampson Judith Anne , Saville Rachel Louise , Toplis Emma , Baguneid Abdulla , Williams Daniel Alexander , Choudhury Aklak
Published: October 2022

National Health Service (NHS) clinical staff are required to demonstrate involvement in quality improvement (QI) and patient safety. Clinicians are often best placed to identify problems and design solutions for their own clinical environments, yet the rotational nature of training can impact on the design, implementation and sustainability of projects.

The In-hospital Quality Improvement for Respiratory team was created in August 2020 within a busy respiratory department to inspire a culture of continuous improvement and provide a sustainable infrastructure to support and progress QI projects (QIPs).

The trust uses the LifeQI platform which provides a change score from 0.5 (intention to participate) to 5.0 (outstanding sustainable results) as a representation of a QIP’s progress.

We aimed to increase the number of QIPs in the respiratory department registered on the LifeQI platform from 1 to at least 10 projects by September 2021.

A QI framework was used to identify and address four primary improvement drivers: (1) QI understanding/training, (2) QI faculty communication, (3) QI participation, and (4) QIP completion using multiple Plan-Do-Study-Act cycles. Data were collected on the number of active respiratory projects registered within the LifeQI platform, mean LifeQI change score and the number of projects with a change score ≤1.

Twenty-four new QIPs were initiated in the first 12 months, with a number of projects leading to sustainable change. The largest improvements were seen in autumn 2020 as the faculty’s multidisciplinary membership expanded.

We achieved our aim of increasing the number of registered QIPs, sustaining the QI faculty throughout the COVID-19 pandemic. Our multidisciplinary membership continues to increase and the faculty has improved access, organisation and project progression across a large department with an established process for rotating staff to join existing QIPs. Our model has the potential to be replicated in other clinical departments within NHS organisations.
First-line thrombectomy strategy for distal and medium vessel occlusions: a systematic review
Authors: Bilgin Cem , Hardy Nicole , Hutchison Kristen , Pederson John Michael , Mebane Alexander , Olaniran Peace , Kobeissi Hassan , Kallmes Kevin M , Fiorella David , Kallmes David F , Brinjikji Waleed
Published: October 2022

Background

The benefit of mechanical thrombectomy (MT) and efficacy of different first-line MT techniques remain unclear for distal and medium vessel occlusions (DMVOs). In this systematic review, we aimed to compare the performance of three first-line MT techniques in DMVOs.

Methods

The PubMed database was searched for studies examining the utility of MT in DMVOs (middle cerebral artery M2-3-4, anterior cerebral artery, and posterior cerebral artery). Studies providing data for aspiration thrombectomy (ASP), stent retriever thrombectomy (SR), and combined SR+ASP technique were included. Non-comparative studies were excluded. Safety and efficacy data were collected for each technique. The Nested Knowledge AutoLit platform was utilized for literature search, screening, and data extraction. Pooled data were presented as descriptive statistics.

Results

13 studies comprising 2422 MT procedures were identified. The overall successful recanalization rate was 77.0% (1513/1964) for DMVOs. SR+ASP had a successful recanalization rate of 83.7% (297/355), SR had a 75.6% rate (638/844), while ASP alone had a 74.2% rate (386/520). The overall functional independence rate was 51.3% (851/1659) among DMVOs. The ASP alone group had a functional independence rate of 46.9% (219/467), while functional independence rates of the SR and SR+ASP groups were 51.5% (372/723) and 61.7% (174/282), respectively. Finally, the subarachnoid hemorrhage rates were 1.8% (4/217) for the ASP group, 9.3% (26/281) for the SR group, and 11.9% (41/344) for the SR+ASP group.

Conclusions

Our systematic review supports the proposition that MT is a safe and effective treatment option for DMVOs. Additionally, while the SR+ASP group had consistently high rates of clot clearance and good neurological outcomes, the SR and SR+ASP groups also had higher rates of subarachnoid hemorrhage, highlighting the need for improved DMVO treatment devices.
CBRNE3medicine in the austere environment: the challenges
Authors: Smith Max , Weir A
Published: October 2022

Chemical, Biological, Radiological, Nuclear and Explosive/Environmental/Endemic Disease (CBRNE3) incidents encompass a wide spectrum of events from natural events/disasters to industrial accidents through to deliberate military release and nuclear war. The UK military operates globally and in environments that are often austere. The very nature of these environments means that CBRNE3incidents are a very real risk, and a CBRNE3incident in a well-developed society could ultimately create an austere environment. Responding to such an event in an austere environment poses challenges.

The very nature of the environment may be problematic. It may be very remote with limited or no access by road and/or air. It may have limited resources such as water and infrastructure required to manage the event. Extremes of temperature and weather may pose a risk to casualties and responders alike. Specialist teams and equipment may be required, but the host or partner nations may not have suitable capability and these resources may take time to mobilise from the home base. The volume of equipment and material needed in the response may overwhelm logistical chains which may not be robust enough to withstand the initial incident.

Proper planning and preparedness is crucial to operating in and managing a CBRNE3incident in an austere environment. Recognition of the potential threat by intelligence gathering and recognition by personnel on the ground are essential. This requires an appropriate awareness at all levels of command and appropriate prior training, including interoperability training with partner forces. Ultimately, robust planning and training is key to managing CBRNE3incidents in an austere environment.
How does traffic affect erosion of unpaved forest roads?
Authors: Alvis Amanda D. , Luce Charles H. , Istanbulluoglu Erkan
Published: October 2022

The relationship between traffic and forest road erosion has been studied for decades, and the answer to the question “what happens when traffic is present on unpaved forest roads?” is simple: erosion increases. However, the answer to the question “why does it increase?” is complex and requires us to consider forest road erosion through an integrated lens. Fully understanding how traffic affects forest road erosion will allow us to control forest road erosion effectively. In this synthesis, we look at forest road erosion literature and focus the discussion on the interactions between traffic and erosion. Specifically, we explore four main hypotheses that have been proposed to explain how traffic affects erosion. These hypotheses are discussed in detail, including what data and information are required to evaluate them. In addition to the specific traffic-erosion interactions, we review important factors that interact with traffic to enhance erosion. Finally, we propose a framework that describes forest road erosion as a combination of all limiting factors. This framework can help guide future data collection needs, allow us to form a more holistic understanding of forest road erosion, and ultimately improve predictions of erosion from forest roads.
Quantum encryption with quantum permutation pad in IBMQ systems
Authors: Kuang Randy , Perepechaenko Maria
Published: October 2022

Quantum permutation pad or QPP is a quantum-safe symmetric cryptographic algorithm proposed by Kuang and Bettenburg in 2020. The theoretical foundation of QPP leverages the linear algebraic representations of quantum gates which makes QPP realizable in both, quantum and classical systems. By applying the QPP with 64 of 8-bit permutation gates, holding respective entropy of over 100,000 bits, we accomplished quantum random number distributions digitally over today’s classical internet. The QPP has also been used to create pseudo quantum random numbers and served as a foundation for quantum-safe lightweight block and streaming ciphers. This paper continues to explore numerous applications of QPP, namely, we present an implementation of QPP as a quantum encryption circuit on today’s still noisy quantum computers. With the publicly available 5-qubit IBMQ devices, we demonstrate quantum secure encryption (256 bits of entropy) using 2-qubit QPP with 56 permutation gates, and 3-qubit QPP with 17 permutation gates respectively. Initial qubits of the encryption circuit correspond to the plaintext and after applying quantum encryption operations, cipher qubits are measured with probabilistic distributions, and the results with the highest probability are recorded as cipher bits. The cipher bits are then decrypted with an inverse QPP circuit. The output state plaintext qubits are measured and the most frequent count measurement results are recorded as plaintext bits. This quantum encryption and decryption process clearly demonstrates that QPP quantum implementations works exactly as symmetric encryption and decryption schemes should. The plaintext and ciphertext bits can also be encrypted and decrypted respectively by any classical computing device with the corresponding QPP algorithm as in quantum computers. This work reveals that it is possible to build quantum-secure communications between quantum-to-quantum and quantum-to-classical computers over today’s internet and the future quantum internet.
The possible actiniarian sea anemone burrow
Bergaueria hemispherica
from the Pliensbachian (Lower Jurassic) of the Lusitanian Basin (Central Portugal)
Authors: Neto de Carvalho Carlos , Paredes Ricardo
Published: October 2022

The shallow marine carbonate deposits of the S. Miguel Formation in the Lusitanian Basin reveal erosional events exposing stiff substrates with abundant
Bergaueria hemispherica
. The ichnoassociation represented by
B. hemispherica
,
Thalassinoides suevicus
,
Spongeliomorpha
isp.,
Asterosoma ludwigae
and
Rhizocorallium commune
is dated from lowermost Pliensbachian by the association with ammonites from the
jamesoni
Biozone,
brevispina
Subzone. The unlined forms of
B. hemispherica
include peripheral and bottom burrow concentrations of shell debris, annular-like structures in the burrow margin and paired burrows-to-linear clusters that are comparable with the penetrative burrowing mechanism, anchoring and feeding behaviours of sea anemones. From the ethological point of view, and comparing with modern behaviours of burrowing anemones, the
B. hemispherica
from the Lusitanian Basin may represent temporary burrowing and relocation of actiniarian anemones. Their comparison with either thenarian or athenarian actiniarians may evidence a preferred surficial feeding strategy on the organic-rich muddy sediments they burrowed.
InviSeal: A Stealthy Dynamic Analysis Framework for Android Systems
Authors: Kumar Saurabh , Mishra Debadatta , Panda Biswabandan , Shukla Sandeep Kumar
Published: October 2022

With wide adaptation of open-source Android into mobile devices by different device vendors, sophisticated malware are developed to exploit security vulnerabilities. As comprehensive security analysis on physical devices are impractical and costly, emulator-driven security analysis has gained popularity in recent times. Existing dynamic analysis frameworks suffer from two major issues: (i) they do not provide foolproof anti-emulation-detection measures even for fingerprint-based attacks, and (ii) they lack efficient cross-layer profiling capabilities. In this work, we present InviSeal, a comprehensive and scalable dynamic analysis framework that includes low-overhead cross-layer profiling techniques and detailed anti-emulation-detection measures along with the basic emulation features. While providing an emulator-based comprehensive analysis platform, InviSeal strives to remain behind-the-scene to avoid emulation-detection. We empirically demonstrate that the proposed OS layer profiling utility to achieve cross-layer profiling is ∼1.26× faster than existing
strace
-based approaches. Overall, on average, InviSeal incurs ∼1.04× profiling overhead in terms of the number of operations performed by the various workloads of the CaffeineMark-3.0 benchmark, which is better than the contemporary techniques. Furthermore, we measure the anti-emulation-detection strategies of InviSeal against the fingerprint-based emulation-detection attacks. Experimental results show that the emulation-detection attacks carried out by the malware samples do not find InviSeal as an emulated platform.
Quantifying the Impact of Charge Rate and Number of Cycles on Structural Degeneration of Li-Ion Battery Electrodes
Authors: Furat Orkun , Finegan Donal P. , Yang Zhenzhen , Tanim Tanvir R. , Smith Kandler , Schmidt Volker
Published: October 2022

A quantitative link between crack evolution in lithium-ion positive electrodes and the degrading performance on cells is not yet well established nor is any single technique capable of doing so widely available. Here, we demonstrate a widely accessible high-throughput approach to quantifying crack evolution within electrodes. The approach applies super-resolution scanning electron microscopy (SEM) imaging of cross-sectioned NMC532 electrodes, followed by segmentation and quantification of crack features. Crack properties such as crack intensity, crack width and length are quantified as a function of charge rate (1C, 6C, and 9C) and cycle number (25, 225, and 600 cycles). Hundreds of particles are characterized for statistical confidence in the quantitative crack measurements. The data on crack evolution is compared to electrochemical data from full cells and half cells with the NMC532 positive electrodes. We show that while crack evolution strongly correlates with capacity fade in the first 25 cycles, it does not correlate well for the following hundreds of cycles indicating that cracking may not be the dominant cause of capacity fade throughout the cycle-life of cells.
Electrochemical Performance of Sandwich-Like Porous Co3O4 Nanostructures on Nickel Foam
Authors: Sun Bo , Zhang Hui , Chen Wenge , Elmarakbi Ahmed , Fu Yong-Qing
Published: October 2022

Co3O4 is a good anode candidate for high-performance lithium ion batteries (LIBs), attributed to its high specific capacity. However, due to its poor conductivity and significant volume expansion during electrochemical reactions, electrochemical performance of Co3O4 electrode is quite poor for practical applications. Co3O4 electrodes with various micro-/nanostructures have been designed and synthesized but their performances are still unsatisfied. In this study, we propose and develop a novel sandwich type of Co3O4 nanostructures by adjusting the ratio of ammonium fluoride and urea during hydrothermal reactions. When this sandwich-like Co3O4 composite electrode was used as the electrode for LIBs, it retained an outstanding reversible capacity of 857 mAh g−1 after 70 cycles at a current density of 500 mA g−1. When the current density was increased to 1000 mA g−1, the reversible capacity was kept at 865 mAh g−1 with insignificant changes of its capacity.
Investigating the Particle Growth in Bimodal Pt/C Catalysts by In-Situ Small-Angle X-ray Scattering: Challenges in the Evaluation of Stress Test Protocol-Dependent Degradation Mechanisms
Authors: Schröder Johanna , Pittkowski Rebecca K. , Du Jia , Kirkensgaard Jacob J. K. , Arenz Matthias
Published: October 2022

The influence of different combinations of accelerated stress test (AST) protocols simulating load-cycle and start/stop conditions of a proton exchange membrane fuel cell (PEMFC) vehicle is investigated on a bimodal Pt/C catalyst. The bimodal Pt/C catalyst, prepared by mixing two commercial catalysts, serves as a model system and consists of two distinguishable size populations. The change in mean particle size was investigated by in situ small-angle X-ray scattering (SAXS). The comparison to the reference catalysts, i.e., the two single-size population catalysts, uncovers the presence of electrochemical Ostwald ripening as a degradation mechanism in the bimodal catalyst. Increasing the harshness of the applied AST protocol combinations by faster changing between load-cycle or start/stop conditions, the particle size of the larger population of the bimodal catalyst increases faster than expected. Surprisingly, the change in mean particle size of the smaller size population indicates a smaller increase for harsher AST protocols, which might be explained by a substantial electrochemical Ostwald ripening.
Time Evolution of the Passivation Behavior of Ti-6Al-4V in 0.5 M Sulfuric Acid
Authors: Wang Qingrui , Zhang Hongbo , Yoshida Hiroaki , Cui Yi-Tao , Qiang Yujie , Wen Lei , Huang Feifei , Jin Ying
Published: October 2022

The passivation behavior of Ti-6Al-4V alloy was studied by electrochemical and surface analyses, and a model was proposed to elucidate the connection between polarization time and properties of the passive film. Three stages of passive film growth can be divided based on the changes of current density during the formation process of passive film and the passive film grew and stabilized after polarized for 0 ∼ 2000 s under 1.0 V vs Ag/AgCl in 0.5 M H2SO4 solution. The chemical state of Ti at the topmost surface of passive film was independent of the polarization time, while the formation of oxides inside the passive film was promoted. The structure evolution of passive film was investigated by high-resolution XAS through the synchrotron radiation source. The formation and increase of thermodynamically stable rutile-TiO2 contributed to the enhancement of the impedance and corrosion resistance of passive film.
Mildred T. Stahlman: a centenarian who pioneered modern scientific neonatal intensive care
Authors: Reese Corey Nason , Sucre Jennifer M. S. , Sundell Håkan , Reese Jeff
Published: October 2022

Neonatology pioneer Mildred (Millie) T. Stahlman celebrated her 100th birthday on July 31, 2022. Her distinguished career at Vanderbilt University Medical Center in Nashville, TN, is reviewed to commemorate this milestone. Stahlman was arguably the first to establish a modern neonatal intensive care unit in 1961, successfully utilizing negative pressure ventilation and umbilical arterial and venous catheters to monitor blood gasses and pH levels. She received early invaluable training in newborn physiology at the Karolinska Institute in Stockholm, Sweden, under John Lind and Petter Karlberg, and at Vanderbilt under Elliot V. Newman. Stahlman also consulted with luminaries Geoffrey Dawes, Donald Barron, and L. Stanley James. As director of the Vanderbilt NICU, she trained 80 fellows from more than 20 countries. The latter 20 years of her career were highlighted by collaborations with Jeff Whitsett. She was the recipient of the AAP Virginia Apgar Award, the APS John Howland Medal, and served as a member of the Institute of Medicine.
The Modal Analysis of Multifactor Coupling of Regional Industrial Innovation
Authors: Liu Yubo , Guo Qian
Published: October 2022

In order to maintain the sustainable development of resource-based industrial clusters, research on the coupling relationship between resource-based industrial clusters and regional innovation networks is proposed. Combined with the historical data of 11 typical resource-based cities from 2013 to 2021, the grey relational model is used to measure the correlation between resource-based clusters and regional innovation networks. And the concept of capacity coupling and the capacity coupling coefficient model in physics is used as a reference to obtain the coupling degree model of resource-based industrial clusters and regional innovation networks. The coupling degree model is used to measure the coupling degree of the two, and a reasonable analysis is carried out on the result of the measurement. The results show that there is a correlation between resource-based industrial clusters and regional innovation networks. And the correlation between the two is above 0.65, indicating a strong correlation. The coupling between resource-based industrial clusters and regional innovation networks has entered the subsequent high-level coupling stage from the run-in coupling stage that began in 2013 and continues to maintain a high-level coupling. It is pointed out that cluster governance plans should be formulated according to regional differences and local conditions, so as to guide the transformation and upgrading of resource-based industrial clusters and to avoid the negative impact on the regional economy due to resource exhaustion.
Artificial Intelligence and Deep Learning Assisted Rapid Diagnosis of COVID‐19 from Chest Radiographical Images: A Survey
Authors: Sinwar Deepak , Dhaka Vijaypal Singh , Tesfaye Biniyam Alemu , Raghuwanshi Ghanshyam , Kumar Ashish , Maakar Sunil Kr. , Agrawal Sanjay
Published: October 2022

Artificial Intelligence (AI) has been applied successfully in many real‐life domains for solving complex problems. With the invention of Machine Learning (ML) paradigms, it becomes convenient for researchers to predict the outcome based on past data. Nowadays, ML is acting as the biggest weapon against the COVID‐19 pandemic by detecting symptomatic cases at an early stage and warning people about its futuristic effects. It is observed that COVID‐19 has blown out globally so much in a short period because of the shortage of testing facilities and delays in test reports. To address this challenge, AI can be effectively applied to produce fast as well as cost‐effective solutions. Plenty of researchers come up with AI‐based solutions for preliminary diagnosis using chest CT Images, respiratory sound analysis, voice analysis of symptomatic persons with asymptomatic ones, and so forth. Some AI‐based applications claim good accuracy in predicting the chances of being COVID‐19‐positive. Within a short period, plenty of research work is published regarding the identification of COVID‐19. This paper has carefully examined and presented a comprehensive survey of more than 110 papers that came from various reputed sources, that is, Springer, IEEE, Elsevier, MDPI, arXiv, and medRxiv. Most of the papers selected for this survey presented candid work to detect and classify COVID‐19, using deep‐learning‐based models from chest X‐Rays and CT scan images. We hope that this survey covers most of the work and provides insights to the research community in proposing efficient as well as accurate solutions for fighting the pandemic.
New Choke Ring Design for Eliminating Multipath Effects in the GNSS System
Authors: Lin Daming , Wang Encheng , Wang Jie
Published: October 2022

An anti-multipath antenna is an antenna that can effectively suppress multipath signals from the source of signal reception. There are many problems in the traditional choke design, such as excessive volume and low elevation gain damage. In this paper, the conventional choke ring is improved by using the complementary trapezoidal structure, and the detailed design process is given. The measured results show that the choke has good resistance to a multipath effect in the navigation frequency band (1.1–1.7 GHz) and can significantly improve the front-to-back ratio of the antenna.
Prediction of Purchase Intention of High and Middle Potential Users in Luxury Hotels Based on Data Mining
Authors: Wu Xue
Published: October 2022

In recent years, the term “big data” has attracted the attention of many scholars and business managers, and the emergence of massive data has ushered in a major transformation of the times. Service quality and customer repeat purchase intention are two of the hot issues in the field of service research. Clarifying the mechanism of the two can help enterprises establish long-term customer relations with more customers through the improvement of service quality, enhance their competitive strength, and improve enterprise performance. According to the actual consumer purchase data provided, the existing data sets are visually analyzed and processed to find the consumer purchase rules, build features and build a reasonable consumer purchase prediction experimental data set. Based on the obtained experimental data set, a single prediction model of consumer purchase is designed. According to the analysis of the instantiation results of the single prediction model, the single model consumed in the fusion model of consumer purchase prediction is determined. In order to demonstrate the viewpoints put forward, the research model is established, the research hypothesis is put forward, the questionnaire is designed by referring to the literature and field investigation, and the results of the questionnaire are empirically analyzed. Using the methods of descriptive statistical analysis, factor analysis, reliability and validity test, and regression analysis, the hypothesis that service quality has a direct impact on customer repeat purchase intention is verified.
Impact of Agricultural Use of Sand Land on Water Yield Services under Different Development Intensities in the Agro-Pastoral Ecotone of Northern Shaanxi
Authors: Xiu Yuan , Wang Ni , Liu Siyuan , Guo Zihan , Peng Fangxu
Published: October 2022

The impact of development on the ecological environment is a matter of concern, especially in the ecologically fragile agro-pastoral ecotone. The agro-pastoral ecotone of northern Shaanxi (ANS) is a representative region of the agro-pastoral ecotone in northern China. The agricultural use of sand land (AUSL) is an effective way to respond to the development needs of this region. The AUSL will certainly have an impact on water yield services in the ANS, where water resources are already scarce. In this study, the Integration Valuation of Ecosystem Services and Tradeoffs Tool (InVEST) model was used to simulate the water yield of the ANS under different intensity scenarios of AUSL. The results showed that AUSL reduces the regional water yield, but the impact is limited. At the maximum scale of development, the total regional water yield decreased by 1.35% compared to the base year of 2020. In terms of distribution pattern, water yield decreased the most in Yuyang District and the least in Fugu County due to the uneven distribution of sand land. At the land use and land cover (LULC) scale, the AUSL has a diminishing effect on the water yield of both cultivated land and sand land due to the more intense evapotranspiration from cropland. This study can provide data and decision support for the ANS region for building the resource-economical and environment-friendly society.
IoT-Based English Translation Teaching from the Perspective of Artificial Intelligence
Authors: Liu Dandan
Published: October 2022

In recent years, with the development of artificial intelligence, the Internet of Things (IoT) has become a research hotspot in industry and academia. At the same time, as a derivative tool of artificial intelligence, machine translation based on the IoT is constantly being applied to English translation and its teaching. In teaching, helping students learn English translation has been the focus of machine translation in recent years. Compared with human translation, machine translation is more efficient and convenient. However, machine translation also has some problems. Compared with traditional human translation, it cannot meet the requirements of faithfulness, expressiveness, and elegance of translation. In many fields, neural network translation is comparable to human translation. In the field of English translation teaching, neural network translation has broad prospects. With the gradual maturity of neural network translation, we should think about how to use neural network translation to make it a powerful English translation teaching tool instead of sticking to traditional teaching and cultivating students who are completely unable to compare it with neural network translation. Therefore, in the context of rapid AI iteration, college English translation teaching should also keep pace with the times. With the help of tools such as neural network translation, English translation talents who can skillfully use AI technology can be trained quickly and efficiently so that they can keep pace with the times and master the power of AI. The research in this paper provides important guidance for the application of artificial intelligence and the Internet of Things, especially for intelligent relaying.
A Mixed Methods Investigation of the Prevalence and Influencing Factors of Compassion Fatigue among Midwives in Different Areas of China
Authors: Liang Xin , Yuan Ping , Su Xingyan , Xing Yuanyuan , Qiang Kejiao , Gao Zumei , Wang Jun
Published: October 2022

Objective. Exploring the influencing factors of compassion fatigue among midwives to prevent compassion fatigue from occurring and improve their mental health. Methods. A method integrating the quantitative research method and qualitative research method is used. For the quantitative research, a cross-sectional study was carried out. State-run hospitals from three economic areas in China were selected as investigation scope from June 2018 to May 2021. A total of 515 midwives were chosen randomly from three economic areas. SPSS 22.0 was used for data cleaning and statistical description and analysis. The influencing factors of compassion fatigue among midwives were analyzed by fitting these two-level logistic models. For qualitative research, purposive sampling and maximum variation strategy were used to select midwives with mild or above compassion fatigue in the questionnaire survey. Field study and interviews were used to collect data. Results. The results in the quantitative research showed that 515 valid questionnaires were received with 82.14% of midwives whose compassion fatigue were moderate or above. Multilevel statistical model analysis demonstrated that hospital level, children situation, area, working atmosphere, experiences of traumatic delivery, sleep quality, and social support level had impacts on the degree of midwives’ compassion fatigue (

p
<
0.05

). The result in the qualitative research showed that 34 midwives were interviewed, and 7 topic ideas were refined. Conclusion. Overall, the incidence of compassion fatigue among midwives is high. Risk factors influencing the degree of midwives’ compassion fatigue include lower social support, disharmonious working atmosphere, toddler situation, huge workload, experiences of traumatic delivery, and poor quality of sleep.
[Retracted] Risk Factors Affecting the Infusion Rate of Chemotherapeutic Agents within 2 Hours after Preparation and the Intervention Effect of the Quality Control Circle
Authors: Wu Xiao , Chen Xinxin , He Lihang
Published: October 2022

Objective. To investigate the risk factors for the infusion rate of chemotherapeutic agents within 2 hours after preparation and to observe the application effect of the quality control circle. Methods. The infusion rates of chemotherapeutic agents within 2 hours after the preparation in different wards of our hospital in February 2019 were counted and relevant factors were collected. Binary logistic regression analysis was utilized to screen the risk factors for the infusion rate of chemotherapeutic agents within 2 hours after the preparation. In March 2019, the quality control circle intervention was implemented according to risk factors. The application effect of the quality control circle was observed. Results. Logistic regression analysis results exhibited that insufficient attention to key performance indicator (KPI), heavy workload, forgotten or unfamiliar KPI, no real‐time attention by the head of the department, simultaneous preparation of multiple groups of infusions for the same patient, preparation of all chemotherapeutic agents in the morning, and self‐prepared medicine without a medical order were independent risk factors for infusion of chemotherapeutic agents beyond 2 hours after preparation (P < 0.05). The infusion rate of the chemotherapeutic agents (96.54%) within 2 hours after the preparation was significantly higher after the application of the quality control circle than that before the application (60.45%). The improvement rate was 59.65% and the goal achievement rate was 104.37% (P < 0.01). Conclusion. Insufficient attention to KPI, heavy workload, forgotten or unfamiliar KPI, no real‐time attention by the head of the department, simultaneous preparation of multiple groups of infusions for the same patient, preparation of all chemotherapeutic agents in the morning, and self‐prepared medicine without a medical order are crucial risk factors for limiting the increase in the infusion rate of chemotherapeutic agents within 2 hours after the preparation. Quality control circle intervention based on risk factors can effectively improve the infusion rate of chemotherapeutic agents within 2 hours after the preparation.
Construction of Standard Fast Medical Procedures for Traumatic Shock and Its Application Effects
Authors: Wang Yan , Luo Siqi
Published: October 2022

Objective. To explore the construction of standard fast medical procedures for traumatic shock and its application effects. Methods. 84 patients with traumatic shock were admitted to emergency department of the hospital between January 2018 and January 2020. Using random number table method, the patients were divided into the control group (was given emergency treatment by routine emergency rescue procedures) and the study group (was given emergency treatment by standard fast medical procedures) with 42 patients in each group. The treatment time (rescue time, consultation time in each department, and examination time), shock index (SI), blood pressure fluctuation range, urine output, serum lactate (LAC) level, activated partial thromboplastin time (APTT), and international normalized ratio (INR) were recorded. The incidences of complications in the two groups within 3 days were counted. Results. The rescue time, consultation time, and examination time of the study group were shorter than those of the control group (

P
<
0.05

). After 18 h of treatment, the SI, blood pressure fluctuation range, LAC, and APTT in the study group were lower or shorter than those in the control group (

P
<
0.05

), while urine volume and INR were higher than those in the control group (

P
<
0.05

). Within 3 days of treatment, the incidence of complications in the study group was 5.41% lower than that in the control group which was 24.14% (

P
<
0.05

). Conclusion. Standard fast medical procedures can effectively shorten the time of each stage of emergency treatment for traumatic shock, which allows patients to receive effective treatment in the shortest time while improving shock symptoms and reducing related complications.
Design and Research of Artificial Intelligence in Multimedia Intelligent Question-Answering System and Self-Test System
Authors: Yao Xiaoyan
Published: October 2022

With the development of computer science and technology, online education is gradually accepted by more and more users, and has become one of the main teaching methods in schools under the influence of the epidemic in recent years. In addition, online vocational education or higher education has also captured the psychology of national learning, and online tutoring has gradually entered into nonstudent groups such as office workers. Although online education has the advantages of low cost and no limitation of time and space, it also has some problems, such as low classroom satisfaction, delayed feedback from students, and poor teaching effect. Therefore, this paper aims at this problem by combining the development background of foreign intelligent answer system and self-test system, and introducing it into our computer application, using artificial intelligence for natural language processing, aiming at online teaching students cannot get timely answer, and self-test questions intelligent system design. The final experimental results show that the system effectively alleviates the problems of students’ delay in answering questions and poor self-test effect, and increases the satisfaction of online classroom by 13%.
Automatic Diagnosis of Elbow Arthritis Based on Edge Algorithm
Authors: Xia Minwei , Ao Peng , Zhang Bin , Liao Yongjun , Zhao Huixue
Published: October 2022

Osteoarthritis is an age-related degenerative joint disease; it is mainly because the cartilage tissue between bones is worn and thinned, which leads to the damage of the periosteum and bone including the surrounding ligaments. Clinically, its manifestations are mainly joint pain, swelling, stiffness, and even partial loss of function, which seriously affects the quality of life of patients. The main clinical manifestations are elbow joint pain and limited movement. Elbow articular cartilage degenerates and falls off, and the more serious manifestation is subchondral hyperosteogeny and sclerosis, which leads to unsmooth articular surface and narrow joint space. Finally, elbow joint pain is severe with different degrees of mobility disorder, elbow joint extension and flexion range is getting smaller and smaller, and elbow joint pain is getting more and more serious. In this paper, the segmentation of left and right elbow images is completed based on gray projection through the analysis of image gray distribution. After obtaining the region of interest of elbow joint, the extraction algorithm of elbow joint hard bone edge is studied. Firstly, the extraction of elbow joint hard bone contour edge is completed based on active shape model algorithm combined with image characteristics. Finally, according to the extraction results of hard bone contour edge, this paper realizes the automatic diagnosis of multiple elbow arthritis indexes and compares with the results given by the image set, which proves that the whole algorithm has good adaptability and accuracy.
Application of Multimedia Semantic Extraction Method in Fast Image Enhancement Control
Authors: Gao Yuyang , Chen Ming , Du Shouqing , Feng Guofu
Published: October 2022

In order to solve the problem that it is difficult to effectively enhance the details of the compressed domain and maintain the overall brightness and clarity of the image when improving the image contrast in the current image enhancement method in the compressed domain, a multimedia semantic extraction method is applied in fast image enhancement control. It has been proposed that thealgorithm that synthesizes training samples according to the Retinex model converts the original low-light image from RGB (red-green-blue) space to HSI (hue saturation intensity) color space, keeps the chrominance and saturation components unchanged, and uses DCNN to enhance the luminance component; finally, it converts the HSI color space to RGB space to get the final enhanced image. The experimental results show that the performance of the model will increase with the increase of the number of convolution kernels, but the increase of the number of convolution kernels will undoubtedly increase the amount of calculation; it can also be found that when the number of network layers is 7, the PSNR of the image output by the model increases. The highest value, increasing the number of network layers, does not necessarily improve the performance of the model; with or without BN, his training method converges more easily than direct RGB image enhancement, with higher average PSNR and SSIM values. The experimental results show that, compared with the traditional Retinex enhancement algorithm and the DCT compression domain enhancement algorithm, the algorithm has better detail enhancement and color preservation effects and can better suppress the block effect.
Weighting Research on the First-Class Curriculum Evaluation System of Landscape Architecture Based on the Analytic Network Process Method
Authors: Qiao Lifang , Qi Anguo , Zhang Yichuan , Wang Baoquan , Zhou Jian
Published: October 2022

China has been implementing a brand-new reform in agricultural education and teaching, and the construction of a first-class curriculum is an important guarantee for improving teaching quality and talent training. In line with the survey results of senior students from the field of landscape architecture, 15 frequent elements are selected, namely, teaching team, teaching strategy, teaching method, curriculum ideology and politics, online teaching, offline teaching informatization, teaching material resources, hardware resources, social resources, curriculum structure, teaching process, curriculum organization, applicability, foresight, innovation, and practicality. According to affiliation relationships, they are then classified into five clusters, which are curriculum intelligence support, informatization, resources, normalization, and content. By adopting the analytic network process method and using the super decision software, the hierarchical network model reflecting the dependence and feedback relationship between elements is established. The research results show that, among the five clusters, curriculum content and intelligence support weight relatively are high, which account for 67% of the total weight. The elements of the teaching team, online teaching, teaching material resources, teaching process normalization, and applicability and practicality of curriculum content weigh high, respectively, among the clusters. In the overall ranking of the system weight, the weights of three elements exceed 0.1, namely, the teaching team, content practicability, and teaching process normalization. The weights of the top eight elements account for approximately 85% of the total weight. This study can be used as a reference for the optimal allocation of curriculum construction resources.
Based on the CT Image Rebuilding the Micromechanics Hierarchical Model of Concrete
Authors: Guangyu Lei , Jichang Han
Published: October 2022

Establishing a mesoscopic numerical model to investigate the mechanical properties of concrete has very important significance. This paper considers the random distribution of aggregate in concrete. The aggregate is assumed to be spherical, respectively, to simulate the interface layer as the entity unit or the contact elements. The random aggregate model and the interface model of random aggregate were established. Based on the CT image and the application of MATLAB and MIMICS software, the different characteristics of the concrete model for 3D reconstruction were set up. Through comparative analysis of the advantages and disadvantages of different models, considering the CT number included in the CT images, this paper establishes the reconstruction model, which includes the shape of concrete aggregates, gradation, holes, etc. The analysis results have shown that the model can infer realistic concrete behavior, providing a new approach for studying concrete properties at the mesoscale.
Genetic Programming-Based Prediction Model for Microseismic Data
Authors: Wang Man , Zhou Hongwei , Zhang Dongming , Wang Yingwei , Du Weihang , Yu Beichen
Published: October 2022

Microseismic monitoring is a rock breakdown monitoring technology, and it has become a major technical tool for underground disaster warning and prevention. However, the massive amount of data involved in multipoint monitoring raises the difficulty for microseismic research when the research object involves underground large-scale complex engineering on time and space scales. The risk predictions of rockburst based on microseismic parameters rely only on the experience of researchers and subjective factors by the human factor. The dependent variable cannot be related to the acoustic and energy signals in the form of a functional equation. Therefore, we collected a large amount of microseismic data obtained from the working faces of Shoushan Mine of Pingdingshan Coal Group in China and filtered the data, then we constructed a prediction model of microseismic data based on underground spatial three-dimensional coordinates using genetic programming (GP), which can realize real-time monitoring and disaster warning of microseismic signals. We established the magnitude and energy prediction formulas by GP and obtained the real-time evolution of each parameter of the optimal individual. The results showed that the actual seismic and energy data of the working faces exhibited good agreement with those predicted by the prediction formulas. The high energy and seismic distribution were caused by the mining stress at the edge of working faces due to the excavation and unloading effect of the surface, and the energy and seismic evolution predicted by GP could also show this phenomenon well.