bluuebunny/crossref_metadata_2025 huggingface dataset:
Ophthalmic artery angioplasty for age-related macular degeneration
Authors: Lylyk Ivan , Bleise Carlos , Lylyk Pedro N , Perez Nicolas , Lundquist Javier , Scrivano Esteban , Francone Anibal A , Charles Martin , Zompa Tamara , Lylyk Pedro
Published: January 2022

Background

There is considerable overlap of contributors to cardiovascular disease and the development of age-related macular degeneration (AMD). Compromised ocular microcirculation due to aging and vascular disease contribute to retinal dysfunction and vision loss. Decreased choroidal perfusion is evident in eyes with dry AMD and is thought to play a role in retinal pigment epithelial dysfunction, the rate of development of geographic atrophy, and the development of neovascularization. The aim of the study was to demonstrate that AMD is correlated with a compromised blood flow in the ocular pathway and show OA angioplasty as a potential treatment of late-stage AMD.

Methods

Based on the potential for the ophthalmic artery (OA) to be an anatomical target for the treatment of AMD as outlined above, five patients were found to be eligible for compassionate use treatment, presenting clinically significant late-stage AMD with profound vision loss in one or both eyes, and are included in this retrospective study.

Results

OA narrowing, or significant calcium burden at the ophthalmic segment of the internal carotid artery compromising the origin of the OA was confirmed in all cases. Subsequent OA cannulation was achieved in all patients with some difficulty. Subjective patient reports indicated that all patients perceived a benefit following the procedure; however, improved postoperative visual acuity did not confirm that perceived benefit for one of the patients.

Conclusions

Feasibility and safety of the OA angioplasty were demonstrated, and a benefit perceived in five patients with profound vision loss and a desire to achieve improved quality of life. A clinical trial with controlled schedule, imaging, and methodologies is needed to confirm these results.
Nickels and tines: the myth of nickel allergy in intracranial stents
Authors: Vanent Kevin N , Federico Emma M , Bass David I , Barros Guilherme , Keen Jade , Levitt Michael R
Published: January 2022

Background

Most intracranial stents contain nickel alloy, and nickel allergy or hypersensitivity is common. Neurological injury following endovascular treatment with a nickel containing intracranial stent has been reported in patients with purported nickel allergy, but it is unclear whether these reactions represent true nickel hypersensitivity. We quantified nickel release from commonly used intracranial stents to investigate whether such stents should be avoided in patients with nickel allergy.

Methods

We examined nickel release from seven commonly used intracranial stents: Enterprise, LVIS Jr, Neuroform, Wingspan, Zilver, Pipeline Flex Embolization Device, and Surpass Evolve. We incubated each stent in human plasma-like media for 30 days. Dimethylglyoxime (DMG) spot testing was performed on each stent to detect released nickel at 0 and 30 days. Inductively coupled plasma–optical emission spectroscopy (ICP-OES) was then used to quantify the nickel concentration of the media at 30 days. Nickel currency and nickel standard for atomic absorption spectrometry were used as positive controls.

Results

DMG spot tests indicated nickel release only from nickel currency at 0 and 30 days of incubation. No nickel release was detected from any stent at 30 days using ICP-OES.

Conclusions

Nickel release from commonly used intracranial stents is negligible. These results suggest that previously reported hypersensitivity to these stents may be misattributed to nickel allergy, and that patients with nickel allergy may be safely treated with select nickel-containing stents.
Sleep problems in rheumatoid arthritis over 12 years from diagnosis: results from the Swedish EIRA study
Authors: Lyne Lauren , Åkerstedt Torbjörn , Alfredsson Lars , Lehtonen Tiina , Saevarsdottir Saedis , Klareskog Lars , Westerlind Helga
Published: January 2022

Objective

Most studies of rheumatoid arthritis (RA) and sleep have focused on established RA. We here investigate sleep quality and sleep duration in patients with newly diagnosed RA and during 1–12 years after diagnosis.

Methods

Data were collected on sleep 1–12 years after diagnosis from patients diagnosed 1998–2018 in the Swedish study Epidemiological Investigation of RA. Six sleep domains (sleep problems, non-restorative sleep, insomnia, insufficient sleep, sleep quality perceived as poor and sleep considered a health problem); a global sleep score and time spent in bed were estimated. Using logistic regression, ORs were calculated for each sleep outcome by disease duration. We explored whether pain (low (Visual Analogue Scale=0–20 mm, reference), intermediate=21–70, high=71–100) or functional impairment (Health Assessment Questionnaire>1.0) was associated with problems.

Results

We had sleep data on 4131 observations (n=3265 individuals). Problems with ≥1 sleep domain (global sleep score) was reported in 1578 observations (38%) and increased with disease duration (OR 1.04, 95% CI 1.02 to 1.07). Median time in bed was 8 hours (Q1-Q3: 7.5–9.0). High-grade pain increased the likelihood of sleep problems ~3–9 fold, and increased functional impairment ~4–8 fold.

Conclusion

In this cohort of newly diagnosed patients with RA with access to the current treatment from diagnosis, we did not find any major problems with sleep, and existing sleep problems related mainly to pain and reduced function. Treatment of sleep problems in RA should be guided towards treating the underlying problem causing the sleep disturbance.
Immunogenicity of BNT162b2 mRNA SARS-CoV-2 vaccine in patients with psoriatic arthritis on TNF inhibitors
Authors: Venerito Vincenzo , Stefanizzi Pasquale , Fornaro Marco , Cacciapaglia Fabio , Tafuri Silvio , Perniola Simone , Iannone Florenzo , Lopalco Giuseppe
Published: January 2022

Background

Scanty data on the immunogenicity of the BNT162b2 vaccine in patients with psoriatic arthritis (PsA) on Tumor Necrosis Factor inhibitors (TNFi) have been published.

Objective

To investigate the humoral response to BNT162b2 vaccination patients with PsA on TNFi, comparing immunogenicity with healthy controls.

Methods

Forty patients with classified PsA on TNFi undergoing vaccination with the BNT162b2 mRNA SARS-CoV-2 vaccine (BioNTech/Pfizer) were enrolled. Fifteen days after the second shot, serum IgG levels against SARS-CoV-2 (Abbott ARCHITECT i2000SR, positivity cut-off 50 AU/mL) were assayed in all patients. Clinimetrics and treatment data were gathered. TNFi treatment was not discontinued throughout the whole period, whereas methotrexate (MTX) was discontinued for 1 week after each shot in those on combination therapy. Sera from healthcare professionals were considered as healthy controls for 1:1 propensity score matching; any of them was taking medication.

Student’s t-test and logistic regression were used for investigating differences in immunogenicity between groups and predictors of antibody response.

Results

Clinical Disease Activity Index did not change before and after vaccination (7.06±5.23 to 7.10±5.27, p=0.92).

Patients with PsA achieved a positive anti-SARS-CoV-2 IgG level with a mean (±SD) of 13794.44±15 815.42 AU/mL. Although lower, the antibody level was not significantly different from matched controls (19227.4±11.8460.45 AU/mL, p=0.08). In the overall sample, those on MTX (12/80, 15%) had a trend toward lower immune response (p=0.07); glucocorticoid therapy (11/80, 13.8%) predicted lower antibody levels (p=0.04).

Conclusions

Continuing TNFi in patients with PsA throughout the vaccination did not hamper immunogenicity.
Immune responses to mRNA vaccines against SARS-CoV-2 in patients with immune-mediated inflammatory rheumatic diseases
Authors: Sieiro Santos Cristiana , Calleja Antolin Sara , Moriano Morales Clara , Garcia Herrero Juan , Diez Alvarez Elvira , Ramos Ortega Fernando , Ruiz de Morales Jose G
Published: January 2022

Background

Patients with immune-mediated rheumatic diseases (IMRDs) are commonly treated with immunosuppressors and prone to infections. Recently introduced mRNA SARS-CoV-2 vaccines have demonstrated extraordinary efficacy across all ages. Immunosuppressed patients were excluded from phase III trials with SARS-CoV-2 mRNA vaccines.

Aims

To fully characterise B-cell and T-cell immune responses elicited by mRNA SARS-CoV-2 vaccines in patients with rheumatic diseases under immunotherapies, and to identify which drugs reduce vaccine’s immunogenicity.

Methods

Humoral, CD4 and CD8 immune responses were investigated in 100 naïve patients with SARS-CoV-2 with selected rheumatic diseases under immunosuppression after a two-dose regimen of SARS-CoV-2 mRNA vaccine. Responses were compared with age, gender and disease-matched patients with IMRD not receiving immunosuppressors and with healthy controls.

Results

Patients with IMRD showed decreased seroconversion rates (80% vs 100%, p=0.03) and cellular immune responses (75% vs 100%, p=0.02). Patients on methotrexate achieved seroconversion in 62% of cases and cellular responses in 80% of cases. Abatacept decreased humoral and cellular responses. Rituximab (31% responders) and belimumab (50% responders) showed impaired humoral responses, but cellular responses were often preserved. Antibody titres were reduced with mycophenolate and azathioprine but preserved with leflunomide and anticytokines.

Conclusions

Patients with IMRD exhibit impaired SARS-CoV-2 vaccine immunogenicity, variably reduced with immunosuppressors. Among commonly used therapies, abatacept and B-cell depleting therapies show deleterious effects, while anticytokines preserved immunogenicity. The effects of cumulative methotrexate and glucocorticoid doses on immunogenicity should be considered. Humoral and cellular responses are weakly correlated, but CD4 and CD8 tightly correlate. Seroconversion alone might not reflect the vaccine’s immunogenicity.
Vessel inflammation and morphological changes in patients with large vessel vasculitis: a retrospective study
Authors: Besutti Giulia , Muratore Francesco , Mancuso Pamela , Ferrari Marco , Galli Elena , Spaggiari Lucia , Monelli Filippo , Casali Massimiliano , Versari Annibale , Boiardi Luigi , Marvisi Chiara , Ligabue Guido , Pattacini Pierpaolo , Giorgi Rossi Paolo , Salvarani Carlo
Published: January 2022

Objective

The aim was to identify any association between imaging signs of vessel wall inflammation (positron emission tomography–CT (PET-CT) score and CT/MR wall thickening) and synchronous and subsequent vascular damage (stenoses/dilations) in patients with large vessel vasculitis (LVV).

Methods

Consecutive patients with LVV referred to a tertiary centre in 2007–2020 with baseline PET-CT and morphological imaging (CT/MR angiography) performed within 3 months were included. All available PET-CT and CT/MR scans were reviewed to assess PET-CT uptake (4-point semi-quantitative score), wall thickening, stenoses and dilations for 15 vascular segments. The associations of baseline PET score and CT/MR wall thickening with synchronous and incident stenoses/dilations at CT/MR performed 6–30 months from baseline were evaluated in per-segment and per-patient analyses. Respective areas under the receiver operating characteristic curve (AUC) were calculated.

Results

We included 100 patients with LVV (median age: 48 years, 22% males). Baseline PET score and wall thickening were strongly associated (Cuzick non-parametric test for trend across order groups (NPtrend) <0.001). The association with synchronous stenoses/dilations was weak for PET score (NPtrend=0.01) and strong for wall thickening (p<0.001). In per-patient analyses, sensitivity/specificity for ≥1 synchronous stenoses/dilations were 44%/67% for PET score ≥2 and 66.7%/60.5% for wall thickening. Subsequent CTs/MRs were available in 28 patients, with seven incident stenoses/dilations. Baseline PET score was strongly associated with incident stenoses/dilations (p=0.001), while baseline wall thickening was not (p=0.708), with AUCs for incident stenoses/dilations of 0.80 for PET score and 0.52 for wall thickening.

Conclusion

PET score and wall thickening are strongly associated, but only baseline PET score is a good predictor of incident vessel wall damage in LVV.
Constituent vs Dependency Parsing-Based RDF Model Generation from Dengue Patients’ Case Sheets
Authors: Devi Runumi , Mehrotra Deepti , Lamine Sana Ben Abdallah Ben , Zghal Hajer Baazaoui
Published: January 2022

Electronic Health Record (EHR) systems in healthcare organisations are primarily maintained in isolation from each other that makes interoperability of unstructured(text) data stored in these EHR systems challenging in the healthcare domain. Similar information may be described using different terminologies by different applications that can be evaded by transforming the content into the Resource Description Framework (RDF) model that is interoperable amongst organisations. RDF requires a document’s contents to be translated into a repository of triplets (subject, predicate, object) known as RDF statements. Natural Language Processing (NLP) techniques can help get actionable insights from these text data and create triplets for RDF model generation. This paper discusses two NLP-based approaches to generate the RDF models from unstructured patients’ documents, namely dependency structure-based and constituent(phrase) structure-based parser. Models generated by both approaches are evaluated in two aspects: exhaustiveness of the represented knowledge and the model generation time. The precision measure is used to compute the models’ exhaustiveness in terms of the number of facts that are transformed into RDF representations.
Effect of TiO2 surface treatment on electron transfer in dye-sensitized solar cells
Authors: Jia Suping , Cheng Tong , Zhang Huinian , Wang Hao , Hao Caihong
Published: January 2022

Defect states in the TiO2 nanoparticles can cause severe charge recombination and poor electron-transport efficiency when used as a photoanode in dye-sensitized solar cells (DSSCs). Herein, we report a simple and practical way to passivate the surface defects of TiO2 through hydrothermal treating with acetic acid and H2SO4, introducing a high percentage of 101 facets and sulfonic acid functional groups on the TiO2 surface. A high efficiency of 8.12% has been achieved, which is 14% higher than that of untreated TiO2 under the same condition. EIS results prove that the multiacid-treated TiO2 can promote electron transport and reduce charge recombination at the interface of the TiO2 and electrolyte. This work provides an efficient approach to engineer the electron-transport pathway in DSSCs.
Multimodal Spatio-Temporal Prediction with Stochastic Adversarial Networks
Authors: Saxena Divya , Cao Jiannong
Published: January 2022

Spatio-temporal (ST) data is a collection of multiple time series data with different spatial locations and is inherently stochastic and unpredictable. An accurate prediction over such data is an important building block for several urban applications, such as taxi demand prediction, traffic flow prediction, and so on. Existing deep learning based approaches assume that outcome is deterministic and there is only one plausible future; therefore, cannot capture the multimodal nature of future contents and dynamics. In addition, existing approaches learn spatial and temporal data separately as they assume weak correlation between them. To handle these issues, in this article, we propose a stochastic spatio-temporal generative model (named D-GAN) which adopts Generative Adversarial Networks (GANs)-based structure for more accurate ST prediction in multiple time steps. D-GAN consists of two components: (1) spatio-temporal correlation network which models spatio-temporal joint distribution of pixels and supports a stochastic sampling of latent variables for multiple plausible futures; (2) a stochastic adversarial network to jointly learn generation and variational inference of data through implicit distribution modeling. D-GAN also supports fusion of external factors through explicit objective to improve the model learning. Extensive experiments performed on two real-world datasets show that D-GAN achieves significant improvements and outperforms baseline models.
COVID-GAN+: Estimating Human Mobility Responses to COVID-19 through Spatio-temporal Generative Adversarial Networks with Enhanced Features
Authors: Bao Han , Zhou Xun , Xie Yiqun , Zhang Yingxue , Li Yanhua
Published: January 2022

Estimating human mobility responses to the large-scale spreading of the COVID-19 pandemic is crucial, since its significance guides policymakers to give Non-pharmaceutical Interventions, such as closure or reopening of businesses. It is challenging to model due to complex social contexts and limited training data. Recently, we proposed a conditional generative adversarial network (COVID-GAN) to estimate human mobility response under a set of social and policy conditions integrated from multiple data sources. Although COVID-GAN achieves a good average estimation accuracy under real-world conditions, it produces higher errors in certain regions due to the presence of spatial heterogeneity and outliers. To address these issues, in this article, we extend our prior work by introducing a new spatio-temporal deep generative model, namely, COVID-GAN+. COVID-GAN+ deals with the spatial heterogeneity issue by introducing a new spatial feature layer that utilizes the local Moran statistic to model the spatial heterogeneity strength in the data. In addition, we redesign the training objective to learn the estimated mobility changes from historical average levels to mitigate the effects of spatial outliers. We perform comprehensive evaluations using urban mobility data derived from cell phone records and census data. Results show that COVID-GAN+ can better approximate real-world human mobility responses than prior methods, including COVID-GAN.
Location-Centered House Price Prediction: A Multi-Task Learning Approach
Authors: Gao Guangliang , Bao Zhifeng , Cao Jie , Qin A. K. , Sellis Timos
Published: January 2022

Accurate house prediction is of great significance to various real estate stakeholders such as house owners, buyers, and investors. We propose a location-centered prediction framework that differs from existing work in terms of data profiling and prediction model. Regarding data profiling, we make an important observation as follows – besides the in-house features such as floor area, the location plays a critical role in house price prediction. Unfortunately, existing work either overlooked it or had a coarse grained measurement of locations. Thereby, we define and capture a fine-grained location profile powered by a diverse range of location data sources, including transportation profile, education profile, suburb profile based on census data, and facility profile. Regarding the choice of prediction model, we observe that a variety of approaches either consider the entire data for modeling, or split the entire house data and model each partition independently. However, such modeling ignores the relatedness among partitions, and for all prediction scenarios, there may not be sufficient training samples per partition for the latter approach. We address this problem by conducting a careful study of exploiting the
Multi-Task Learning (MTL)
model. Specifically, we map the strategies for splitting the entire house data to the ways the tasks are defined in MTL, and select specific MTL-based methods with different regularization terms to capture and exploit the relatedness among tasks. Based on real-world house transaction data collected in Melbourne, Australia, we design extensive experimental evaluations, and the results indicate a significant superiority of MTL-based methods over state-of-the-art approaches. Meanwhile, we conduct an in-depth analysis on the impact of task definitions and method selections in MTL on the prediction performance, and demonstrate that the impact of task definitions on prediction performance far exceeds that of method selections.
Receptor-Ribosome Coupling: A Link Between Extrinsic Signals and mRNA Translation in Neuronal Compartments
Authors: Koppers Max , Holt Christine E.
Published: January 2022

Axons receive extracellular signals that help to guide growth and synapse formation during development and to maintain neuronal function and survival during maturity. These signals relay information via cell surface receptors that can initiate local intracellular signaling at the site of binding, including local messenger RNA (mRNA) translation. Direct coupling of translational machinery to receptors provides an attractive way to activate this local mRNA translation and change the local proteome with high spatiotemporal resolution. Here, we first discuss the increasing evidence that different external stimuli trigger translation of specific subsets of mRNAs in axons via receptors and thus play a prominent role in various processes in both developing and mature neurons. We then discuss the receptor-mediated molecular mechanisms that regulate local mRNA translation with a focus on direct receptor-ribosome coupling. We advance the idea that receptor-ribosome coupling provides several advantages over other translational regulation mechanisms and is a common mechanism in cell communication.
Challenges of Organoid Research
Authors: Andrews Madeline G. , Kriegstein Arnold R.
Published: January 2022

Organoids are 3D cell culture systems derived from human pluripotent stem cells that contain tissue resident cell types and reflect features of early tissue organization. Neural organoids are a particularly innovative scientific advance given the lack of accessibility of developing human brain tissue and intractability of neurological diseases. Neural organoids have become an invaluable approach to model features of human brain development that are not well reflected in animal models. Organoids also hold promise for the study of atypical cellular, molecular, and genetic features that underscore neurological diseases. Additionally, organoids may provide a platform for testing therapeutics in human cells and are a potential source for cell replacement approaches to brain injury or disease. Despite the promising features of organoids, their broad utility is tempered by a variety of limitations yet to be overcome, including lack of high-fidelity cell types, limited maturation, atypical physiology, and lack of arealization, features that may limit their reliability for certain applications.
The ECS Battery Division: Putting Electrochemistry to Work in Energy Storage and Conversion Devices
Authors: Holmes Curtis F. , Surampudi Subbarao
Published: January 2022

Batteries, those remarkable electrochemical devices that allow us to start our cars, listen to music while jogging, use laptop computers, keep our hearts beating, and a host of other important functions, are the focus of one of the largest and most active Divisions of The Electrochemical Society. This issue of Interface is intended to familiarize the members of the Society with the Battery Division, its purpose, and its activities. This issue also features three articles on batteries and fuel cells from Division members.
Carbon Nanotubes: A Status Report
Authors: Subramoney Shekhar
Published: January 2022

To begin with, one could ask “Why are we so interested in nanometer scale hollow tubes of carbon with typical aspect ratios of about 100?” From a materials science perspective, the oil crisis of the 1970s provided a major impetus for the development of materials that combined light weight with exceptional mechanical properties.
Mixed matrix factorization: a novel algorithm for the extraction of kinematic-muscular synergies
Authors: Scano Alessandro , Mira Robert Mihai , d’Avella Andrea
Published: January 2022

The mixed matrix factorization (MMF) is a novel method for extracting kinematic-muscular synergies. The previous state of the art algorithm (NMFpn) factorizes separately positive and rectified negative waveforms; the MMF instead employs a gradient descent method to factorize from mixed kinematic unconstrained data and muscular non-negative data. MMF achieves perfect reconstruction on noiseless data, improving the NMFpn. MMF shows promising applicability on real data.
Mapping whole brain seizure network recruitment with optogenetic kindling
Authors: Niemeyer James E.
Published: January 2022

Epilepsy is often labeled as a network disorder, though a common view of seizures holds that they initiate in a singular onset zone before expanding contiguously outward. A recent report by Choy et al. (Choy M, Dadgar-Kiani E, Cron GO, Duffy BA, Schmid F, Edelman BJ, Asaad M, Chan RW, Vahdat S, Lee JH. Neuron 2021 Oct 23: S0896-6273(21)00778-9.) leverages new tools to study whole brain dynamics during epileptic seizures originating in the hippocampus. Cell-type-specific kindling and functional imaging revealed how various brain regions were recruited to seizures and uncovered a novel form of migrating seizure core.
The Potential Mechanisms by which Artemisinin and Its Derivatives Induce Ferroptosis in the Treatment of Cancer
Authors: Hu Yingying , Guo Nan , Yang Ting , Yan Jianghong , Wang Wenjun , Li Xiang
Published: January 2022

Artemisinin (ART) is a bioactive molecule derived from the Chinese medicinal plant Artemisia annua (Asteraceae). ART and artemisinin derivatives (ARTs) have been effectively used for antimalaria treatment. The structure of ART is composed of a sesquiterpene lactone, including a peroxide internal bridge that is essential for its activity. In addition to their well-known antimalarial effects, ARTs have been shown recently to resist a wide range of tumors. The antineoplastic mechanisms of ART mainly include cell cycle inhibition, inhibition of tumor angiogenesis, DNA damage, and ferroptosis. In particular, ferroptosis is a novel nonapoptotic type of programmed cell death. However, the antitumor mechanisms of ARTs by regulating ferroptosis remain unclear. Through this review, we focus on the potential antitumor function of ARTs by acting on ferroptosis, including the regulation of iron metabolism, generation of reactive oxygen species (ROS), and activation of endoplasmic reticulum stress (ERS). This article systematically reviews the recent progress in ferroptosis research and provides a basis for ARTs as an anticancer drug in clinical practice.
Research on the Trust Mechanism of Individual Consumers in Rural Financial Markets Based on the Dynamic CGE Model
Authors: Lin Fang , Chen Wenxiang
Published: January 2022

In order to obtain the complete equilibrium state of rural financial market and ensure the stable development of rural financial consumer market, this paper introduces CGE model and analyzes the dynamic trust mechanism of individual consumers in rural financial market. In this paper, the single variable evolutionary fuzzy clustering algorithm is used to analyze the orthogonal eigenvector solutions of individual consumers; the big data of individual consumers under the mode of perceived trust is automatically clustered, so as to obtain the fuzzy analogy function of individual consumers in the rural financial market; and finally the prediction value of consumer trust is obtained. The results show that trust, customer satisfaction, and service quality are positively correlated. Under the same sample expectation constraints, the dynamic CGE model is more robust, and the individual consumer trust mechanism of rural financial market in the study area has higher advantages.
[Retracted] Research on the Spread Path and Evolution Causes of Oral Language in the Digital Era
Authors: Li Zhiqiang
Published: January 2022

Visual orientation seems to indicate the decline of oral communication, but oral communication has its own living space under the new media ecology. Research has found that in the digital media era, voice communication is manifested as a single‐level feature that simulates current interaction and information communication. Although voice communication is a lie constructed by individuals, the interaction between the subject’s discourse and the actual field of interaction separate the emotional distance, but the situation is harmonious and inclusive. The following voice communication and new media technologies are still trustworthy. Aiming at multifactor evolutionary algorithm (MFEA), the most classical multifactor evolutionary algorithm in multitask computation, we theoretically analyze the inherent defects of MFEA in dealing with multitask optimization problems with different subfunction dimensions and propose an improved version of the multifactor evolutionary algorithm, called HD‐MFEA. In HD‐MFEA, we proposed heterodimensional selection crossover and adaptive elite replacement strategies, enabling HD‐MFEA to better carry out gene migration in the heterodimensional multitask environment. At the same time, we propose a benchmark test problem of multitask optimization with different dimensions, and HD‐MFEA is superior to MFEA and other improved algorithms in the test problem. Secondly, we extend the application scope of multitask evolutionary computation, and for the first time, the training problem of neural networks with different structures is equivalent to the multitask optimization problem with different dimensions. At the same time, according to the hierarchical characteristics of neural networks, a heterodimensional multifactor neural evolution algorithm HD‐MFEA neuro‐evolution is proposed to train multiple neural networks simultaneously. Through experiments on chaotic time series data sets, we find that HD‐MFEA neuro‐evolution algorithm is far superior to other evolutionary algorithms, and its convergence speed and accuracy are better than the gradient algorithm commonly used in neural network training.
Analysis of microRNA Expression after Glutamine Intervention in Acute Renal Ischemia-Reperfusion Injury
Authors: Li Suhua , Huang Xuan , Wang Shun , Chu Xueqian , Aierken Munire
Published: January 2022

Background. Ischemia-reperfusion acute kidney injury (I/R AKI) is a severe kidney disease with high mortality and morbidity. This study aimed to explore the protective mechanism of glutamine (GLN) against I/R AKI. Methods.The I/R AKI rat model was established, and HE staining of kidney tissue and serum creatinine (SCr) and blood urea nitrogen (BUN) detection were performed. The miRNAs were sequenced by high throughput in rat kidney tissue samples. Differentially expressed miRNAs (DEmiRs) between the I/R group and I/R + GLN group were screened, and enrichment analysis for target genes of DEmiRs was performed. Meanwhile, human HK-2 cells were cultured, and an I/R model was established to verify the expression of DEmiRs. Results. Compared with the I/R group, the SCr and BUN levels at each time point were lower in the I/R + GLN group. Vacuolar degeneration of renal tubules in the I/R + GLN group was significantly reduced. In the 104 DEmiRs, we selected miR-132-5p, miR-205, and miR-615 as key miRNAs. KEGG analysis showed that the Notch signaling pathway, PI3K-Akt signaling pathway, and cGMP signaling pathway were mainly related to the GLN against I/R. qRT-PCR verified the downregulation of miR-205 in the I/R group, compared to the sham and I/R + GLN group. The I/R model was established with HK-2 cells, and the expression of miR-132-5p and miR-205 was decreased. Conclusion. GLN reduced I/R-induced AKI. There were significant differences between miRNAs expression in I/R after GLN treatment. The process of GLN against I/R-induced AKI may be related to the Notch and PI3K-Akt signaling pathway.
Sliding Mode Control of Flexible Articulated Manipulator Based on Robust Observer
Authors: Gao Yanghua , Lu Hailiang
Published: January 2022

In this paper, a robust observer-based sliding mode control algorithm is proposed to address the modelling and measurement inaccuracies, load variations, and external disturbances of flexible articulated manipulators. Firstly, a sliding mode observer was designed with exponential convergence to observe system state accurately and to overcome the measuring difficulty of the state variables, unmeasurable quantities, and external disturbances. Next, a robust sliding mode controller was developed based on the observer, such that the output error of the system converges to zero in finite time. In this way, the whole system achieves asymptotic stability. Finally, the convergence conditions of the observer were theoretically analyzed to verify the convergence of the proposed algorithm, and simulation was carried out to confirm the effectiveness of the proposed method.
An Analysis of the Catastrophe Model and Catastrophe Characteristics of Traffic Flow Based on Cusp Catastrophe Theory
Authors: Huang Yanguo , Zhang Huimin , Liu Hongjun , Zhang Shengsheng
Published: January 2022

—The state of urban road traffic flow shows discontinuity and jumping phenomenon in the process of running. There was a data gap in the collected traffic flow data. Through the data analysis, it was found that the traffic flow state had the characteristics of multimode, mutation, inaccessibility, divergence and hysteresis, which were similar to the mutation characteristics of the basic model of catastrophe theory when the system state changed. The cusp catastrophe model of traffic flow based on traffic wave theory was established by analyzing the movement process of traffic flow. In this model, the traffic density was taken as the state variable, and traffic flow and wave speed were taken as the control variable. Referring to the basic idea of catastrophe theory, the solution method of the model was given, and the structural stability of the traffic flow state was analyzed. Through the critical equilibrium surface equation, the stability of the extreme value of the system potential function can be analyzed, and the bifurcation set equation when the traffic flow state changed can be obtained, which can be used to determine the critical range of the structural stability of the system. This paper discussed and analyzed the changing trend and constraint relationship among the wave speed, traffic density and traffic flow when the traffic flow state changed suddenly in different running environments. The analysis results were consistent with the actual road traffic flow state. A case was given, and the results showed that the cusp catastrophe model could describe the relationship among the three parameters of traffic flow from three-dimensional space, and could effectively analyze the internal relationship of the parameters when the traffic flow state changed. The validity of the model and analysis method was verified. The goal of this paper is to provide an analysis method for the judgment of urban road traffic state.
Bearing Behavior of H‐Shaped Honeycombed Steel Web Composite Columns with Rectangular Concrete‐Filled Steel Tube Flanges under Eccentrical Compression Load
Authors: Ji Jing , Yu Chenyu , Jiang Liangqin , Zhan Jiedong , Ren Hongguo , Hao Sixue , Fan Shaojie , Jiang Li , Lin Yubo , He Lingjie
Published: January 2022

In order to investigate the bearing capacity of H‐shaped honeycombed steel web composite columns with rectangular concrete‐filled steel tube flanges (STHCCs) subjected to eccentrical compression load, 33 full‐scale STHCCs were designed with the eccentricity(e), the slenderness ratio (λ), the cubic compressive strength of concrete(fcuk), the thickness of the steel tube flange (t1), the thickness of honeycombed steel web (t2), diameter‐depth ratio (d/hw), space‐depth (s/hw), and the yield strength of the steel tube (fy) as the main parameters. Considering the nonlinear constitutive model of concrete and simplified constitutive model of steel, the finite element (FE) model of STHCCs was established by ABAQUS software. By comparison with the existing test results, the rationality of the constitutive model of materials and FE modeling was verified. The numerical simulation of 33 full‐scale STHCCs was conducted, and the influence of different parameters on the ultimate eccentrical compression bearing capacity was discussed. The results show that the cross‐sectional stress distribution basically conforms to the plane‐section assumption. With the increase in e, λ, and d/hw, the ultimate eccentrical compression bearing capacity of the full‐scale STHCCs decreases, whereas it gradually increases with the increase in fcuk, t1, t2, s/hw, and fy. By introducing bias‐stress stability coefficient (φ), the calculation formula of full‐scale STHCCs under eccentrical compression is proposed by statistical regression, which can lay a foundation for the popularization and application of these types of composite columns in practical engineering.
Investigation of Salt‐Frost Heaving Rules and Mechanical Properties of Chlorite Saline Soil along the Duku Highway under Freezing‐Thawing Action
Authors: Huang Xuebang , Zhang Zizhao , Guo Zezhou , Hao Ruihua , Lv Qianli , Liu Tianchao , Zhou Tiansheng
Published: January 2022

Aiming to investigate salt‐frost heaving rules and the mechanical properties of natural saline soil along the Duku Highway subjected to multiple freezing‐thawing cycles, we collected natural saline soil samples from the alluvial‐proluvial plain in front of the Dushanzi Mountain at the starting point of the Duku Highway. Then, we conducted mineral composition analysis tests, essential laboratory physical property measurement, large scale multiple freezing‐thawing cyclic salt‐frost heaving tests, shear strength tests, and unconfined compressive strength tests on the samples. According to the test results presented, the collected saline soil differed from saline soil in other regions and fell into “chlorite saline soils.” As the number of freezing‐thawing cycles increased, the overall salt‐frost heaving capacity increased and then decreased in the freezing process but first reduced and then increased in the thawing process. Thus, the salt‐frost heaving capacity was cumulative in freezing/thawing cycles. The peak salt‐frost heaving capacity reached a maximum after 1 freezing‐thawing cycle and then dropped drastically and fluctuated regularly. After 6 freezing‐thawing cycles, the displacement deformation and time formed a new equilibrium. After 7 freezing‐thawing cycles, the displacement and deformation of the soil no longer appear negative. As the number of freezing‐thawing cycles increased, the cohesive force of saline soil first increased and then dropped steadily, the internal friction angle first dropped and then increased steadily, and the unconfined shear strength first increased and then decreased. These research results provided data supporting the prevention and controlling highway saline soil disasters with insightful references for the other projects in this region.
Big Data Analytics and Discrete Choice Model for Enterprise Credit Risk Early Warning Algorithm
Authors: Yu Jiangbo
Published: January 2022

A business credit risk early warning algorithm based on big data analysis and discrete selection model is presented to address the issues of poor sample fitting performance, long warning time, and low warning accuracy that plague the traditional enterprise credit risk early warning algorithm. A-share listed enterprises in China were chosen as the credit data source for screening the samples based on big data analysis. After screening, financial failure firms were coupled, and paired samples were created. The credit risk variables, which included financial and corporate governance characteristics, were chosen based on the created samples. The enterprise financial risk submodel and the nonfinancial risk submodel were built based on the enterprise credit risk variables, and the financial and nonfinancial index scores of enterprise customers were evaluated separately to develop a discrete choice model of enterprise credit risk. The algorithm’s sample fitting performance was employed to achieve early warning of corporate credit risk. The algorithm based on big data analytics and discrete choice model is compared to the traditional method in order to verify its validity. The findings of the experiment reveal that the algorithm’s sample fitting performance is superior to the traditional one, making it more suitable for enterprise credit risk early warning. The proposed model depicts 85% accuracy.
[Retracted] Research on Fast Compensation Algorithm for Interframe Motion of Multimedia Video Based on Manhattan Distance
Authors: Li Ning , Wan Shuai
Published: January 2022

To improve the video quality, aiming at the problems of low peak signal‐to‐noise ratio, poor visual effect, and low bit rate of traditional methods, this paper proposes a fast compensation algorithm for the interframe motion of multimedia video based on Manhattan distance. The absolute median difference based on wavelet transform is used to estimate the multimedia video noise. According to the Gaussian noise variance estimation result, the active noise mixing forensics algorithm is used to preprocess the original video for noise mixing, and the fuzzy C‐means clustering method is used to smoothly process the noisy multimedia video and obtain significant information from the multimedia video. The block‐based motion idea is to divide each frame of the video sequence into nonoverlapping macroblocks, find the best position of the block corresponding to the current frame in the reference frame according to the specific search range and specific rules, and obtain the relative Manhattan distance between the current frame and the background of multimedia video using the Manhattan distance calculation formula. Then, the motion between the multimedia video frames is compensated. The experimental results show that the algorithm in this paper has a high peak signal‐to‐noise ratio and a high bit rate, which effectively improves the visual effect of the video.
[Retracted] Research on Sports Training Action Image Recognition Based on SDN
Authors: Wang Dianhai , Shen Lianmei
Published: January 2022

Current image recognition methods cannot combine the transmission of image data with the interaction of image features, so the steps of image recognition are too independent, and the traditional methods take longer time and cannot complete the image denoising. Therefore, a recognition method of sports training action image based on software defined network (SDN) architecture is proposed. The SDN architecture is used to integrate the image data transmission and interactive process and to optimize the image processing centralization. The network architecture is composed of application layer, control layer, and infrastructure layer. Based on this, the dimension of image sample set is reduced, and the edge detection operator in any direction is constructed. The image edge filter is realized by calculating the response and threshold of image edge by using lag threshold and nonmaximum suppression (NMS). The Hough transform algorithm is improved to optimize the detection range. Extracting the neighborhood feature of sports training action, the recognition of sports training action image based on SDN architecture is completed. Simulation results show that the proposed method takes less time and the image denoising effect is better. In addition, the F1 test results of the proposed method are higher than those of the literature, and the convergence is better. Therefore, the performance of the proposed method is better.
Monitoring of Insecticide Resistance in Anopheles culicifacies in Twelve Districts of Madhya Pradesh, Central India (2017–2019)
Authors: Mishra Ashok K. , Bharti Praveen K , Chand Gyan , Das Aparup , Jayswar Himanshu , Rahi Manju , Raghavendra Kamaraju
Published: January 2022

Background. Indoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs) are malaria vector control measures used in India, but the development of insecticide resistance poses major impediments for effective vector control strategies. As per the guidelines of the National Vector Borne Disease Control Programme (NVBDCP), the study was conducted in 12 districts of Madhya Pradesh to generate data on insecticide resistance in malaria vectors. Methods. The susceptibility tests were conducted on adult An. culicifacies as per the WHO standard technique with wild-caught mosquitoes. The blood-fed female mosquitoes were exposed in 3 to 4 replicates on each occasion to the impregnated papers with specified discriminating dosages of the insecticides (DDT: 4%, malathion: 5%, deltamethrin: 0.05%, and alphacypermethrin: 0.05%), for one hour, and mortality was recorded after 24-hour holding. Results. An. culicifacies was found resistant to DDT 4% in all the 12 districts and malathion in 11 districts. The resistance to alphacypermethrin was also observed in two districts, and possible resistance was found to alphacypermethrin in seven districts and to deltamethrin in eight districts, while the vector was found susceptible to both deltamethrin and alphacypermethrin in only 3 districts. Conclusion. An. culicifacies is resistant to DDT and malathion and has emerging resistance to pyrethroids, alphacypermethrin, and deltamethrin. Therefore, regular monitoring of insecticide susceptibility in malaria vectors is needed for implementing effective vector management strategies. However, studies to verify the impact of IRS with good coverage on the transmission of disease are required before deciding on the change of insecticide in conjunction with epidemiological data.
Landscape Perspective Distance-Included Angle Shape Distribution Analysis Based on 3D CAD Model Retrieval Algorithm
Authors: Bi Huijuan
Published: January 2022

In view of the results obtained in the retrieval process of the 3D CAD model, which can show the differences in the local feature details of the model, the 3D CAD model retrieval algorithm is introduced into the analysis of the perspective distance-angle shape distribution of the garden landscape in this paper. Random sampling is performed on the surface of the constructed 3D CAD model, combined with the test distance between the sampling point and the neighboring points, and the corresponding garden landscape perspective distance-angle shape distribution characteristics in this area are calculated in order to achieve the similarity of the CAD model high-speed retrieval. Finally, experimental research shows that the algorithm proposed in this paper is better than the overall shape distribution algorithm and the spherical harmonic algorithm in the search performance of the CAD model, and it can effectively improve the recognition ability of the local detailed features of the 3D CAD model.