bluuebunny/crossref_metadata_2025 huggingface dataset:
Upadacitinib in active ankylosing spondylitis: results of the 2-year, double-blind, placebo-controlled SELECT-AXIS 1 study and open-label extension
Authors: van der Heijde Désirée , Deodhar Atul , Maksymowych Walter P , Sieper Joachim , Van den Bosch Filip , Kim Tae-Hwan , Kishimoto Mitsumasa , Östör Andrew J , Combe Bernard , Sui Yunxia , Duan Yuanyuan , Wung Peter K , Song In-Ho
Published: July 2022

Introduction

Long-term safety and efficacy of upadacitinib in patients with active ankylosing spondylitis (AS) has not been previously reported.

Methods

In SELECT-AXIS 1, patients receiving placebo were switched to upadacitinib 15 mg once daily at week 14 while patients initially randomised to upadacitinib continued their regimen through week 104. Efficacy was assessed using as-observed (AO) and non-responder imputation (NRI).

Results

Of 187 patients randomised, 144 patients (77%) completed week 104. Among patients receiving continuous upadacitinib, 85.9% (AO) and 65.6% (NRI) achieved Assessment of SpondyloArthritis international Society 40 response (ASAS40) at week 104. Similar magnitude of ASAS40 responses were observed among patients who switched from placebo to upadacitinib (88.7% and 63.8%, respectively). The mean change from baseline to week 104 in Spondyloarthritis Research Consortium of Canada MRI spine and sacroiliac joint inflammation scores were –7.3 and –5.3, respectively, in the continuous upadacitinib group and –7.9 and –4.9 in the placebo-to-upadacitinib switch group. The mean (95% CI) change from baseline to week 104 in the modified Stoke Ankylosing Spondylitis Spine Score was 0.7 (0.3, 1.1) in the total group. Adverse event rate was 242.7/100 patient-years. No serious infections, adjudicated major adverse cardiovascular events, lymphoma, non-melanoma skin cancer, or gastrointestinal perforations were observed.

Conclusions

Upadacitinib 15 mg once daily showed sustained and consistent efficacy over 2 years for ASAS40 and other clinically relevant endpoints. A low rate of radiographic progression was observed and no new safety findings were observed.
High prevalence of anal papillomavirus infection in men who have sex with men PrEP users
Authors: Rossotti Roberto , Nava Alice , Baiguera Chiara , Calzavara Daniele , D’Amico Federico , Fanti Diana , Bana Nicholas Brian , Vismara Chiara , Cernuschi Massimo , Scaglione Francesco , Puoti Massimo
Published: July 2022

Objectives

Human papillomavirus (HPV) is the most common STI and is associated with a wide range of diseases from anogenital warts to malignancies. Anal HPV infection is considerably more common in men who have sex with men (MSM) living with HIV. Aims of the present study are to (i) describe the prevalence of anal HPV infection in MSM who started pre-exposure prophylaxis (PrEP) and (ii) analyse factors associated with anal infection from genotypes that would be covered by nonavalent vaccination.

Methods

This monocentric, cross-sectional study included all subjects who started PrEP from May 2018 to November 2021. PrEP candidates underwent full behavioural and clinical evaluation, including digital anal rectal examination and swabbing for HPV determination. Descriptive statistics, Mann-Whitney U test for continuous and χ2 tests for categorical variables were adopted. Unadjusted and adjusted regression analyses were performed to assess factors associated with positive anal swabs and to the presence of genotypes covered by the nonavalent vaccination.

Results

The analysis included 288 subjects: anal swabs tested positive in 87.2% of cases, 79.2% of the subjects had a high-risk genotype (mainly 16), whereas 67.4% had a genotype covered by nonavalent vaccine. Sexual role was the only factor associated with anal HPV infection. Use of recreational drugs and a diagnosis of ≥2 STIs correlated with the presence of genotypes that would have been covered by vaccine, while previous vaccination had a protective role.

Conclusions

PrEP candidates showed a high prevalence of anal HPV infection, especially due to high-risk genotypes, comparable to what has been reported in MSM living with HIV.
Cancer treatment-related cardiac dysfunction
Authors: Brady Bernadette , Murphy Ross
Published: July 2022

Objectives

This paper describes cardiotoxicity and cancer treatment-related cardiac dysfunction (CTRCD). Long-term sequelae of treatment are important, and changing, and may manifest when a patient is under the care of a supportive care service.

Methods

Key messages for supportive and palliative care clinicians are outlined to facilitate identification and management of CTRCD.

Results

Not all cardiotoxicity is alike. Types of cardiotoxicity, cardiac complications of immunotherapy, the challenge of autonomic nervous system dysfunction in cancer and management of cardiotoxicity are highlighted.

Conclusions

The key strategies are early detection of cardiotoxicity, monitoring for development of CTRCD during treatment and surveillance in survivorship.
Economic research in waterpipe tobacco smoking: reflections on data, demand, taxes, equity and health modelling
Authors: Bteddini Dima , Nakkash Rima T , Chalak Ali , Jawad Mohammed , Khader Yousef , Abu-Rmeileh Niveen M E , Mostafa Aya , Abla Ruba , Awawda Sameera , Salloum Ramzi G
Published: July 2022

Economic evaluation of tobacco control policies is common in high-income settings and mainly focuses on cigarette smoking. Evidence suggests that increasing the excise tax of tobacco products is a consistently effective tool for reducing tobacco use and is an efficient mechanism for increasing government revenues. However, less research has been conducted in low/middle-income countries where other tobacco forms are common. This paper presents insights from our work on the economics of waterpipe tobacco smoking conducted in the Eastern Mediterranean Region where waterpipe smoking originated and is highly prevalent. The specific areas related to economics of waterpipe smoking considered herein are: price elasticity, taxation, government revenue, expenditure and healthcare costs. This paper aims to provide practical guidance for researchers investigating the economics of waterpipe tobacco with potential implications for other novel tobacco products. We present lessons learnt across five thematic areas: data, demand, taxes, equity and health modelling. We also highlight knowledge gaps to be addressed in future research. Research implications include designing comprehensive assessment tools that investigate heterogeneity in waterpipe smoking patterns; accounting for cross-price elasticity of demand with other tobacco products; exploring the change in waterpipe tobacco smoking in response to a tax increase and analysing the equity impact of waterpipe tobacco control interventions.
Expanding local sales restrictions on flavoured tobacco products to include menthol: retail sales changes in two Minnesota cities
Authors: Olson Lindsay T , Gammon Doris G , Rogers Todd , Brown Elizabeth M , Nonnemaker James M , Spinks James G , Ross Ashley , Xu Xin , Moze Joanne , Matter Christine M , D’Silva Joanne
Published: July 2022

Background

In 2018, Minneapolis and St. Paul, Minnesota, expanded existing local sales restrictions on flavoured (non-menthol/mint/wintergreen) tobacco products (‘flavour policies’) to include menthol/mint/wintergreen-flavoured tobacco products (‘menthol policies’). All policies included exemptions for certain store types.

Methods

We obtained weekly retail tobacco product sales for 2015 through 2019 from NielsenIQ for convenience stores and other outlets in the policy jurisdictions and two comparison areas (rest of the state of Minnesota and total USA). We standardised unit sales across product categories and used NielsenIQ-provided descriptors to classify products as menthol (including mint/wintergreen) or flavoured (non-menthol/non-tobacco). Using single group interrupted time series models, we analysed unit sales by product category and by flavour separately for each geography to assess associations between menthol policy implementation and trends in tobacco product unit sales.

Results

Following menthol policy implementation, unit sales of menthol cigarettes and menthol smokeless tobacco decreased in both cities, with smaller decreases in comparison areas. Flavoured cigar sales—which decreased following the flavour policies—further decreased after the menthol policies, while sales of menthol electronic nicotine delivery systems (ENDS) increased in both cities and sales of flavoured ENDS increased in St. Paul.

Conclusion

Expanding flavour policies to include menthol/mint/wintergreen was associated with significant decreases in unit sales of most menthol products and in total unit sales by tobacco product category. Increases in menthol and flavoured ENDS sales in these cities may be associated with legal sales by exempted retailers and/or illicit sales by non-compliant retailers, highlighting opportunities for retailer education and enforcement.
Rhythm of the streets: a street classification framework based on street activity patterns
Authors: Su Tianyu , Sun Maoran , Fan Zhuangyuan , Noyman Ariel , Pentland Alex , Moro Esteban
Published: July 2022

As the living tissue connecting urban places, streets play significant roles in driving city development, providing essential access, and promoting human interactions. Understanding street activities and how these activities vary across different streets is critical for designing both efficient and livable streets. However, current street classification frameworks primarily focus on either streets’ functions in transportation networks or their adjacent land uses rather than actual activity patterns, resulting in coarse classifications. This research proposes an activity-based street classification framework to categorize street segments based on their temporal street activity patterns, which is derived from high-resolution de-identified and privacy-enhanced mobility data. We then apply the proposed framework to 18,023 street segments in the City of Boston and reveal 10 distinct activity-based street types (ASTs). These ASTs highlight dynamic street activities on streets, which complements existing street classification frameworks, which focus on the static or transportation characteristics of the street segments. Our results show that a street classification framework based on temporal street activity patterns can identify street categories at a finer granularity than current methods, which can offer useful implications for state-of-the-art urban management and planning. In particular, we find that our classification distinguishes better those streets where crime is more prevalent than current functional or contextual classifications of streets.
Learning to increase matching efficiency in identifying additional b-jets in the $$\text {t}\bar{\text {t}}\text {b}\bar{\text {b}}$$ process
Authors: Jang Cheongjae , Ko Sang-Kyun , Choi Jieun , Lim Jongwon , Noh Yung-Kyun , Kim Tae Jeong
Published: July 2022

The$$\text {t}\bar{\text {t}}\text {H}(\text {b}\bar{\text {b}})$$tt¯H(bb¯)process is an essential channel in revealing the Higgs boson properties; however, its final state has an irreducible background from the$$\text {t}\bar{\text {t}}\text {b}\bar{\text {b}}$$tt¯bb¯process, which produces a top quark pair in association with a b quark pair. Therefore, understanding the$$\text {t}\bar{\text {t}}\text {b}\bar{\text {b}}$$tt¯bb¯process is crucial for improving the sensitivity of a search for the$$\text {t}\bar{\text {t}}\text {H}(\text {b}\bar{\text {b}})$$tt¯H(bb¯)process. To this end, when measuring the differential cross section of the$$\text {t}\bar{\text {t}}\text {b}\bar{\text {b}}$$tt¯bb¯process, we need to distinguish the b-jets originating from top quark decays and additional b-jets originating from gluon splitting. In this paper, we train deep neural networks that identify the additional b-jets in the$${\text {t}}{\bar{\text {t}}}{\text {b}}{\bar{\text {b}}}$$tt¯bb¯events under the supervision of a simulated$$\text{t}\bar{\text{t}}\text{b}\bar{\text{b}}$$tt¯bb¯event data set in which true additional b-jets are indicated. By exploiting the special structure of the$$\text {t}\bar{\text {t}}\text {b}\bar{\text {b}}$$tt¯bb¯event data, several loss functions are proposed and minimized to directly increase matching efficiency, i.e., the accuracy of identifying additional b-jets. We show that, via a proof-of-concept experiment using synthetic data, our method can be more advantageous for improving matching efficiency than the deep learning-based binary classification approach presented in [1]. Based on simulated$$\text {t}\bar{\text {t}}\text {b}\bar{\text {b}}$$tt¯bb¯event data in the lepton+jets channel from pp collision at$$\sqrt{s}$$s= 13 TeV, we then verify that our method can identify additional b-jets more accurately: compared with the approach in [1], the matching efficiency improves from 62.1$$\%$$%to 64.5$$\%$$%and from 59.9$$\%$$%to 61.7$$\%$$%for the leading order and the next-to-leading order simulations, respectively.
LiCAM: Long-Tailed Instance Segmentation with Real-Time Classification Accuracy Monitoring
Authors: Ye Rongguang , Guo Yantong , Shuai Xian , Ye Rongye , Jiang Siyang , Jiang Hui
Published: July 2022

Recently, deep neural networks have achieved remarkable progress in class balancing instance segmentation. However, most applications in the real world have a long-tailed distribution, i.e., limited training examples in the majority of classes. The long-tailed challenge leads to a catastrophic drop in instance segmentation because the gradient of the head classes suppresses the gradient of the tail classes, leading to a bias towards the major classes. We propose LiCAM, a novel framework for long-tailed segmentation. It features an adaptive loss function named Moac Loss, which is adjustable during the training according to the monitored classification accuracy. LiCAM also cooperates with an oversampling technique named RFS, which alleviates the severe imbalance between head and tail classes. We conducted extensive experiments on the LVIS v1 dataset to evaluate LiCAM. With a coherent end-to-end training pipeline, LiCAM significantly outperforms other baselines.
Fractal Feature Based Image Resolution Enhancement Using Wavelet–Fractal Transformation in Gradient Domain
Authors: Jakhar Shyo Prakash , Nandal Amita , Dhaka Arvind , Jiang Bojie , Zhou Liang , Mishra Vishnu Narayan
Published: July 2022

The fractal geometries are applied extensively in many applications like pattern recognition, texture analysis and segmentation. The application of fractal geometry requires estimation of the fractal features. The fractal dimension and fractal length are found effective to analyze and measure image features, such as texture, resolution, etc. This paper proposes a new wavelet–fractal technique for image resolution enhancement. The resolution of the wavelet sub-bands are improved using scaling operator and then it is transformed into texture vector. The proposed method then computes fractal dimension and fractal length in gradient domain which is used for resolution enhancement. It is observed that by using scaling operator in the gradient domain, the fractal dimension and fractal length becomes scale invariant. The major advantage of the proposed wavelet–fractal technique is that the feature vector retains fractal dimension and fractal length both. Thus, the resolution enhanced image restores the texture information well. The texture information has also been observed in terms of fractal dimension with varied sample size. We present qualitative and quantitative analysis of the proposed method with existing state of art methods.
Performance Metrics on Hyperspectral Images in Fuzzy Contextual Convolutional Neural Network for Food Quality Analyzer
Authors: Arumuga Maria Devi T. , Darwin P.
Published: July 2022

The quality of food and the safety of consumer is one of the major essential things in our day-to-day life. To ensure the quality of foods through their various attributes, different types of methods have been introduced. In this proposed method, three underlying blocks namely Hyperspectral Food Image Context Extractor (HFICE), Hyperspectral Context Fuzzy Classifier (HCFC) and Convolutional Neural Network (CNN) for Food Quality Analyzer (CFQA). Hyperspectral Food Image Context Extractor module is used as the preprocess to get food attributes such as texture, color, size, shape and molecular particulars. Hyperspectral Context Fuzzy Classifier module identifies a particular part of the food (zone entity) is whether carbohydrate, fat, protein, water or unusable core. CNN for Food Quality Analyzer module uses a Tuned Convolutional Layer, Heuristic Activation Operation, Parallel Element Merge Layer and a regular fully connected layer. Indian Pines, Salinas and Pavia are the benchmark dataset to evaluate hyperspectral image-based machine learning procedures. These datasets are used along with a dedicated chicken meat Hyper Spectral Imaging dataset is used in the training and testing process. Results are obtained that about 7.86% of average values in various essential evaluation metrics such as performance metrics such as accuracy, precision, sensitivity and specificity have improved when compared to existing state of the art results.
CoRec: An Efficient Internet Behavior-based Recommendation Framework with Edge-cloud Collaboration on Deep Convolution Neural Networks
Authors: Li Yangfan , Li Kenli , Wei Wei , Zhou Tianyi , Chen Cen
Published: July 2022

Both accurate and fast mobile recommendation systems based on click behaviors analysis are crucial in e-business. Deep learning has achieved state-of-the-art accuracy and the traditional wisdom often hosts these computation-intensive models in powerful cloud centers. However, the cloud-only approaches put significant computational pressure on cloud servers and increase the latency in heavy-load scenarios. Moreover, existing work often adopts RNN structures to model behaviors that suffer from low processing speed for under-utilization of parallel devices such as GPUs. In this work, we propose an efficient internet behavior-based recommendation framework with edge-cloud collaboration on deep CNNs (CoRec) to improve both the accuracy and speed for mobile recommendation. A novel convolutional interest network (CIN) improves the accuracy by modeling the long- and short-term interests and accelerates the prediction through parallel-friendly convolutions. To further improve the serving throughput and latency, a novel device-cloud collaboration strategy reduces workloads by pre-computing and caching long-term interests in the cloud offline and real-time computation of short-term interests in devices. Extensive experiments on real-world datasets show that CoRec significantly outperforms the state-of-the-art methods in accuracy and has achieved at least an order of magnitude improvement in latency and throughput compared to cloud-only RNN-based approaches for long behaviors.
Resolution Identification of Encrypted Video Streaming Based on HTTP/2 Features
Authors: Wu Hua , Li Xin , Wang Gang , Cheng Guang , Hu Xiaoyan
Published: July 2022

With the inevitable dominance of video traffic on the Internet, Internet service providers (ISP) are striving to deliver video streaming with high quality. Video resolution, as a direct reflection of video quality, is a key factor of the video quality of experience (QoE). Since the displayed information of video cannot be observed by ISPs, ISPs can only measure the video resolution from traffic. However, with HTTP/2 being gradually adopted in video services, the multiplexing feature of HTTP/2 allows audio and video chunks to be mixed during transmission, making existing monitoring approaches unusable. In this article, we propose a method called H2CI to monitor resolution for adaptive encrypted video traffic under HTTP/2. We consider the size of the mixed data for identification. Specifically, H2CI consists of a length restoration method to extract restored fingerprints and a fingerprint-matching method for fine-grained resolution identification. The experimental results show that H2CI can achieve more than 98% accuracy for fine-grained resolution identification. Our method can be effectively applied to infer the adaptation behavior of encrypted video streaming and monitor the QoE of video services under HTTP/2.
Li-Ion Battery Electrode Contact Resistance Estimation by Mechanical Peel Test
Authors: Vogel John E. , Sederholm Jarom G. , Shumway Edmund M. , Abello Gabriel J. , Trask Stephen E. , Wheeler Dean R. , Mazzeo Brian A.
Published: July 2022

Li-ion battery electrode electronic properties, including bulk conductivity and contact resistance, are critical parameters affecting cell performance and fast-charge capability. Contact resistance between the coating and current collector is often the largest electronic resistance in an electrode and is affected by chemical, microstructural, and interfacial variations. Direct measurements of contact resistance and bulk conductivity have proven to be challenging. In their absence, a mechanical electrode peel test is often used to compare adhesion and electrical contact resistance. However, using a micro-flexible-surface probe, contact resistance can be directly determined. This work compares contact resistance and mechanical peel strength of multiple commercial-grade HE5050 and NCM523 cathodes and graphite and silicon anodes. It was found that peel strength correlates well with contact resistance in a carefully curated data set (p < 0.05) and in some situations may be a good metric to estimate electrical properties. However, there were distinct outliers in the data set, indicating that peel strength may not accurately reflect electrical properties when there is significant variation in electrode composition. These results illustrate the value of the micro-flexible-surface probe in quantifying contact resistance and bulk conductivity to better understand how battery composition and processing steps affect microstructure and resulting cell performance.
New Electrochemical Sensor Based on Electrospun Carbon Nanofibers Modified with Cobalt Nanoparticles and Its Application for Atorvastatin Determination
Authors: Górska Anna , Zambrzycki Marcel , Paczosa-Bator Beata , Piech Robert
Published: July 2022

The presented work reports the application of the electrospun carbon nanofibers decorated with cobalt nanoparticles (CNF-Co) in the fabrication of a new, highly sensitive electrochemical sensor (GCE-CNF-Co). Morphology, phase composition and structure as well as the chemical state of the surface of used material were evaluated using the following methods: scanning electron microscopy (SEM), X-ray diffraction (XRD), Raman spectroscopy and X-ray Photoelectron Spectroscopy (XPS). The proposed sensor might be characterized by a simple and fast process of preparation and low cost but in the same time exhibits excellent electrical conductivity and electrocatalytic properties. Reproducibility of its preparation expressed as relative standard deviation (%RSD) was estimated to be 9.0% (n = 5 electrodes). A single sensor might perform at least 700 measurements without compromising metrological parameters. The developed sensor was used in the determination of atorvastatin (ATOR)—substance used for the prevention of cardiovascular incidents. ATOR exhibits linear response in the range 0.08–1.04 μM (r = 0.998) and 1.2–9.1 μM (r = 0.999). Limit of detection (LOD) was equal to 3.4 nM (1.9 μg l−1) (tacc = 50 s). The applicability of the method was proved by analysis of urine and pharmaceutical products containing ATOR. Recoveries were in the range 102%–110%, what proves the accuracy of the method.
Sensitive Electrochemical Detection of Thiourea Utilizing a Novel Silver Nanoparticle-Decorated Porous Silicon-Polyaniline Nanocomposite
Authors: Ahmed Jahir , Faisal M. , Alsareii S. A. , Jalalah Mohammed , Harraz Farid A.
Published: July 2022

Thiourea (TU) causes multiple types of adverse effects on human health, and hence the monitoring of TU content in the environment and implementing proper safety procedures become vital. Therefore, in this article, we proposed an electrochemical thiourea sensor utilizing a novel silver-embedded mesoporous silicon-polyaniline (Ag@PSi-PANI) nanocomposite fabricated glassy carbon electrode (GCE) with the widest linear dynamic range (LDR = 0.02–38.7 mM) than existing TU sensors, and significantly improved other sensor parameters. Modern characterization techniques including FESEM, TEM, EDXS, XRD, XPS, and FTIR spectroscopy were employed to systematically characterize this novel Ag@PSi-PANI nanocomposite. XRD and XPS investigations confirmed the successful formation of a nanocomposite containing the PSi, PANI, and silver nanoparticles (AgNPs). TEM images revealed that AgNPs were randomly distributed onto the PSi-PANI sheets. During the electrochemical exploration via square wave voltammetry (SWV), the Ag@PSi-PANI/GCE sensor demonstrated an excellent sensitivity (1.2135 μAmM−1) and an extremely low detection limit (LOD ∼12 μM). This novel TU sensor was also employed to study the potential chemical interference utilizing some closely related chemicals, demonstrating the proper selectivity in the TU determination. During the TU determination, the Ag@PSi-PANI/GCE sensor also showed exceptional reproducibility, repeatability, and stability. The Ag@PSi-PANI/GCE sensor also showed ∼100% quantitative recovery from spiked samples. It is expected that this Ag@PSi-PANI/GCE assembly will emerge as an efficient route in developing an effective TU sensor.
A Novel Molecularly Imprinted Electrochemical Sensor Based on PANI@GO for Highly Sensitive and Selective Analysis of Trace Epigoitrin
Authors: Sun Bolu , Gao Chengyang , Yang Lin , Shi Hongxia , Kan Lei , Ma Quhuan , Shi Xiaofeng
Published: July 2022

Identification and quantification of epigoitrin (EP) in some herbs and traditional Chinese medicine (TCM) preparations are critical to pharmacokinetic study and pharmaceutical quality control due to its distinct antiviral activity. So, developing highly sensitive and selective method for detection of EP is essential for clinical treatment and drug development. In this study, a novel molecularly imprinted electrochemical sensor for detection of EP was firstly constructed. With acrylamide imprinting systems, surface imprinting on the polyaniline functionalized graphene oxide was employed to prepare molecularly imprinted polymer by electro-polymerization, which follow-up constructed afford specific binding cavities, endowing the exclusive recognition ability. Furthermore, the polyacrylamide chain is anchored to the polyaniline chain by covalent bonds, which is beneficial for raising electrochemistry signal. Under the optimized condition, the sensor demonstrates a linear wide range of 4.6 × 10−7 mol l−1 ∼ 4.6 × 10−5 mol l−1 with a correlation coefficient of 0.9953 and a low LOD of 8.21 × 10−8 mol l−1 (S/N = 3). Additionally, the sensor showed good stability, repeatability (RSD 1.52%) and selectivity. The method was applied to analyze EP in the extraction from Isatidis Radix with a recovery higher than 97.8% and RSD less than 1.81%. This work provided a novel strategy for on-site, real-time and rapid detection of indicator components from TCM.
Review—Gate Oxide Thin Films Based on Silicon Carbide
Authors: Odesanya Kazeem Olabisi , Ahmad Roslina , Andriyana Andri , Bingol Sedat , Wong Yew Hoong
Published: July 2022

A comprehensive review of the features of silicon carbide (SiC) and various methods of deposition of gate oxides are presented in this report. The SiC material, which is mostly employed as base component in metal oxide semiconductor field effect transistors (MOSFETs) is very promising; for its high voltage, high power, high temperature and high breakdown field properties. These features have made it very attractive for use in power electronic devices over its counterparts in the field. Despite these great features, and the significant progress recorded in the past few years regarding the quality of the material, there are still some issues relating to optimization of the surface and interface processing. This review discusses the effect of surface modification and treatment as a means of enhancing the electrical performance of the SiC-based MOSFETs. It also identifies the challenges of controlling the density of dielectric/SiC interface trap that is needed to improve the values of mobility channels, and several oxidation techniques that could be used to surmount the structural limitations presently encountered by the SiO2/SiC system. Reliability as a significant aspect of electronic structures was also discussed with much emphasis on causes of their breakdown and possible solutions, especially in high thermal applications.
Protease-activated receptors in health and disease
Authors: Peach Chloe J. , Edgington-Mitchell Laura E. , Bunnett Nigel W. , Schmidt Brian L.
Published: July 2022

Proteases are signaling molecules that specifically control cellular functions by cleaving protease-activated receptors (PARs). The four known PARs are members of the large family of G protein-coupled receptors. These transmembrane receptors control most physiological and pathological processes and are the target of a large proportion of therapeutic drugs. Signaling proteases include enzymes from the circulation; from immune, inflammatory epithelial, and cancer cells; as well as from commensal and pathogenic bacteria. Advances in our understanding of the structure and function of PARs provide insights into how diverse proteases activate these receptors to regulate physiological and pathological processes in most tissues and organ systems. The realization that proteases and PARs are key mediators of disease, coupled with advances in understanding the atomic level structure of PARs and their mechanisms of signaling in subcellular microdomains, has spurred the development of antagonists, some of which have advanced to the clinic. Herein we review the discovery, structure, and function of this receptor system, highlight the contribution of PARs to homeostatic control, and discuss the potential of PAR antagonists for the treatment of major diseases.
Metabolic Profiling of Serum for Osteoarthritis Biomarkers
Authors: Xiao Ziqian , Zhang Zhenyang , Huang Shanbin , Lon Jerome Rumdon , Xie Shuilin
Published: July 2022

Osteoarthritis is a prevalent aging disease in the world, and in recent years it has shown a trend toward younger age, which is becoming a major health problem in the world and seriously endangers the health of the elderly. However, the etiology and pathogenesis of osteoarthritis are still unclear, causing great trouble for treatment. To screen out candidate biomarkers that could be used for the identification of osteoarthritis and explore the pathogenesis of osteoarthritis, we performed an untargeted metabolomics analysis of nine New Zealand rabbit serum samples by LC-MS/MS, including three normal serum samples (control group) and six osteoarthritis serum samples (case group). Finally, 44 differential metabolites were identified, and the ROC analysis results indicated that a total of 36 differential metabolites could be used as candidate biomarkers. Further metabolic pathway enrichment analysis was performed on these differential metabolites, and we found that a total of 17 metabolic pathways were affected, which may provide directions for the study of osteoarthritis mechanisms.
Application of Automatic Motor Control System Based on Sensor Technology
Authors: Qi Dehui
Published: July 2022

In order to solve the application problems in motor automation control, a motor automation control system based on sensor technology is proposed. Sensor technology has been widely used in the field of automation. Therefore, when studying sensor technology, we should also study its specific application in the process of motor automation control. This paper briefly introduces the sensor technology in electromechanical automation control, discusses the application of this technology in various fields, and analyzes the development trend of sensor technology in electromechanical automation control in the future. The experimental data show that in the motor starting phase, the sensorless SRM using the observer can quickly identify the given speed, quickly approach the given speed in 0.05 seconds, and make the motor run faster and reach a stable state. The application of sensor technology has greatly improved the quality and production efficiency of mechanical manufacturing.
MRI Using Artificial Intelligence Algorithm to Evaluate Concurrent Chemoradiotherapy for Local Recurrence and Distant Metastasis of Cervical Squamous Cell Carcinoma
Authors: Wu Youyi , Chen Tingting , Huang Yiwei , Li Yongchou , Wang Xiaoyan
Published: July 2022

The aim of this study was to investigate the magnetic resonance imaging (MRI) features of patients with local recurrence and distant metastasis of cervical squamous cell carcinoma before and after concurrent chemoradiotherapy based on artificial intelligence algorithm. In this study, 100 patients with cervical squamous cell carcinoma with local recurrence and distant metastasis who underwent concurrent chemoradiotherapy were collected as the research subjects, and all underwent MRI multisequence imaging scans. At the same time, according to the evaluation criteria of solid tumor efficacy, patients with complete remission were classified into the effective group, and patients with partial remission, progressive disease, and stable disease were classified into the ineffective group. In addition, an image segmentation algorithm based on Balloon Snake model was proposed for MRI image processing, and simulation experiments were carried out. The results showed that the Dice coefficient of the proposed model segmentation of the reconstructed image was significantly higher than that of the level set model and the greedy algorithm, while the running time was the opposite (

P
<
0.05

). The lesion volume (

38.76
±
5.34

 cm3) in the effective group after treatment was significantly smaller than that in the noneffective group (

46.33
±
4.64

 cm3), and the rate of lesion volume shrinkage (28.71%) was significantly larger than that in the noneffective group (12.49%) (

P
<
0.05

). The relative apparent diffusion coefficient (rADC) value and rADC value change rate of the lesion after treatment in the effective group were significantly greater than those in the noneffective group (

P
<
0.05

). In summary, the image segmentation and reconstruction algorithm based on Balloon Snake model can not only improve the quality of MRI images but also shorten the processing time and improve the diagnostic efficiency. The volume regression rate and rADC value change rate of cervical squamous cell carcinoma lesion can reflect the early efficacy of concurrent chemoradiotherapy for cervical squamous cell carcinoma and have predictive value.
Investigation of Utilizing Industrial Waste Residue Proportion on Concrete Structure: Computer Finite Element Analysis
Authors: Wang Baoyuan , Tong Qianhao , Zhu Jichao
Published: July 2022

To study the influence of different proportions and amounts of admixtures on the structural performance of concrete, increase the utilization rate of waste material, and finally reduce the cost and environmental pollution, a computer-based finite element analysis method is proposed to investigate the structural performance of concrete composing of waste residue. Firstly, the available types of industrial waste residue and their application in concrete cementitious materials are researched. Secondly, the fly ash in the industrial waste residue is utilized as an example to design an experiment composed of material selection and mixed design set up to determine factors. Finally, the finite element analysis method is proposed and conducted. This model is employed to calculate early shrinkage stress and temperature deformation of concrete with varying contents of fly ash. The results suggest that when the content of fly ash reaches more than 40%, the compressive strength of concrete decreases gradually with the increase of the content, and the decrease is consistent with the increase of the content. Besides, different amounts of fly ash have a certain effect on the hydrated reaction and stress reduction of concrete. The effect becomes more obvious when an increase in dosage is observed.
Neovascular Glaucoma from Ocular Ischemic Syndrome Treated with Serial Monthly Intravitreal Bevacizumab and Panretinal Photocoagulation: A Case Report
Authors: Asif Hassaan , Si Zhuangjun , Quan Steven , Amin Pathik , Dao David , Shaw Lincoln , Skondra Dimitra , Qiu Mary
Published: July 2022

Purpose. To describe a case of open-angle neovascular glaucoma (NVG) secondary to ocular ischemic syndrome (OIS) treated with a planned series of 6 monthly anti-VEGF injections with interspersed panretinal photocoagulation (PRP) sessions. We term this treatment protocol the Salvaging Conventional Outflow Pathway in Neovascular Glaucoma (SCOPING) Protocol, and this is our (MQ and DS) standard of care for all NVG patients presenting with partially or completely open angles. Case. A 66-year-old man’s right eye had a visual acuity of 20/50, intraocular pressure (IOP) of 42 mmHg on 0 IOP-lowering medications, and neovascularization of the iris and angle with no peripheral anterior synechiae. Fundoscopy revealed midperipheral dot-blot hemorrhages without diabetic retinopathy or vein occlusion. Fluorescein angiography revealed peripheral retinal nonperfusion in both eyes. The patient was diagnosed with open-angle NVG secondary to OIS and treated with 6 serial monthly anti-VEGF injections interspersed with 4 PRP sessions, after which his anterior segment neovascularization regressed and IOP normalized on 0 medications. Ten weeks after the last injection, the anterior segment neovascularization and elevated IOP recurred, so he underwent 4 more monthly anti-VEGF injections and 4 PRP sessions, after which his anterior segment neovascularization regressed and his IOP normalized on 0 medications. However, 6 weeks after the last injection, the anterior segment neovascularization and elevated IOP again recurred, so he was resumed on a third course of lifetime monthly anti-VEGF injections, which may be continued in perpetuity. Conclusion. The patient’s NVG was quiescent while under the protection of serial anti-VEGF injections with interspersed PRP; however, the disease recurred each time injections were stopped. Therefore, in patients with open-angle NVG secondary to OIS, serial monthly anti-VEGF injections may be necessary combined with PRP to suppress underlying neovascular drive and regress anterior segment neovascularization, maintain physiologic IOP, and prevent synechial angle closure.
Oils Combination with Microalgal Products as a Strategy for Increasing the N-3 Long-Chain Polyunsaturated Fatty Acid Content in Fish Oil-Free Diets for Meagre (Argyrosomus regius)
Authors: Carvalho Marta , Izquierdo Marisol , Valdés Marco , Montero Daniel , Farías Ana
Published: July 2022

Diversification of species and ingredients is essential for further developing aquaculture production. The present study aimed to evaluate the potential of a blend of microalgae oils and poultry oil as total replacers of fish oil in aquafeeds, a fast-growing species for aquaculture diversification, that was shown to require high dietary n-3 LC-PUFA levels. For that purpose, meagre juveniles (

2.74
±
0.01

 g initial body weight) were fed one of the four experimental diets for 30 days. A control diet (FO diet) was based on 5% fish oil and 7% of rapeseed oil, whereas in the other three diets, fish oil was totally replaced by either poultry oil only (PO diet), or blending poultry oil and one of two commercial algal oils (ED and DD diets). Growth performance, tissue composition, and the expression of genes related to fatty acid biosynthesis, antioxidant defense system, and heat shock proteins were determined. Diets with blends of poultry and microalgae oils supported good growth and feed utilization of meagre. Besides, these diets maintained high DHA tissue contents and good fillet lipid quality indices, like in those fish fed the control diet containing fish oil. Furthermore, the meagre fed ED diet showed the highest expression of gpx, in agreement with the highest dietary polyunsaturated fatty acid content. These results demonstrated the good potential of blending these two commercial microalgae oils with poultry oil to completely replace fish oil cost-effectevily in diets for meagre. In contrast, PO as the sole replacer of fish oil was not able to support fish growth performance and tissue contents of n-3 LC-PUFA, leading to an increased thrombogenic index in fish fillets. Additionally, the low dietay n-3 LC-PUFA content of PO diet upregulated the relative expression offads2 while downregulating gpx compared to microalgal diets.
Controllability of Linear Fractional Systems with Delay in Control
Authors: Ghasemi Mina , Nassiri Kameleh
Published: July 2022

This paper discusses the controllability of continuous-time linear fractional systems with control delay. The Atangana-Baleanu fractional derivative with the Caputo approach is used. First, the solution expression for a linear fractional system is obtained. Then, the corresponding fractional delay controllability Gramian matrix is defined, and its non-singularity as necessary and sufficient conditions for the controllability is proved. Finally, another equivalent condition based on the matrix rank formed by the coefficients matrices of the original system is provided that is much easier to check.
Control Optimization of Scenic Spot Navigation System Based on Map Matching Algorithm
Authors: Cui Wenjing
Published: July 2022

In order to solve the problem that the smart phone GPS positioning technology cannot guarantee the location accuracy in the scenic spot navigation system, a tourist spot matching method based on the improved HMM model was proposed. Firstly, the traditional linear road model is improved in electronic map design. Secondly, the concept of minimum peripheral error rectangle is proposed based on the theory of error ellipse. Then, combined with location data, road data, and scenic spot data, the improved HMM model is used to calculate the matching road. Finally, Matlab simulation experiment and comparison experiment are carried out. The results show that the accuracy of the map matching algorithm based on the improved HMM model can reach 94.5%, and the average accuracy can reach 93.1%, which is 3.6% higher than that of the traditional HMM model. The test results show that the proposed algorithm is correct and practical and has a good application prospect.
Comprehensive Expression Profiling and Molecular Basis of CDC28 Protein Kinase Regulatory Subunit 2 in Cervical Cancer
Authors: Qin Li , Luo Xiaoqiong , Qin Xiao , Huang Hongbao , Zhang Lianling , Chen Shengcai , Wu Xiaoqin , Huang Bingsheng , Pan Jian , Wei Jingxi
Published: July 2022

More and more evidence suggests the oncogenic function of overexpressed CDC28 protein kinase regulatory subunit 2 (CKS2) in various human cancers. However, CKS2 has rarely been studied in cervical cancer. Herein, taking advantage of massive genetics data from multicenter RNA-seq and microarrays, we were the first group to perform tissue microarrays for CKS2 in cervical cancer. We were also the first to evaluate the clinical significance of CKS2 with large samples (980 cervical cancer cases and 422 noncancer cases). We further excavated the mechanism of the tumor-promoting activities of CKS2 in cervical cancer through analysis of genetic mutation profiles, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) significant enrichment of genes coexpressed with CKS2. According to the results, expression data from multilevels unanimously supported the overexpression of CKS2 in cervical cancer. Patients with cervical cancer in stage II from inhouse microarrays had significantly higher expression of CKS2, and CKS2 overexpression had an adverse impact on the disease-free survival status of cervical cancer patients in GSE44001. Both mutation types of mRNA high and mRNA low appeared in cervical cancer cases from the TCGA Firehose project. Gene coexpressed with CKS2 participated in pathways including the cell cycle, estrogen signaling pathway, and DNA replication. In summary, upregulated CKS2 is closely associated with the malignant clinical development of cervical cancer and might serve as a valuable therapeutic target in cervical cancer.
Classroom Behaviour of Talent Cultivation in Colleges and Universities Supported by Deep Learning Technology
Authors: Han Jing
Published: July 2022

Among the current significant issues in talent cultivation is changing colleges’ unique talent cultivation strategies and regulating the spontaneous connection of the talent cultivation, industrial, and entrepreneurial chains. In other terms, the growing disparity between college and university incorporation and industry demand for talent has made the growth of creative applied skills targeted to the industry want an acute problem. That is why colleges and universities must cultivate practical talent in a way that is effective, strong, low-cost, and creative. As a result, this research uses deep learning to develop an ensemble convolutional neural network with an attention mechanism to increase the performance and reliability of talent cultivation in universities and colleges and assess the talents properly. For this research, the datasets are gathered with the primary student and classroom information. Followed by standardising the data, the normalization technique is utilised. Then, the proposed method is employed for the data analysis. ANOVA, Chi-square test, and Student’s

t

-test are applied for the statistical analysis. Finally, the performance of the proposed technique is examined and compared with existing methods to prove the students’ highest performance in talent cultivation.
Mechanical Performance Analysis of Steel-Timber Structure System with Reinforced Layer Based on Particle Algorithm
Authors: Fu Meizhen , Tang Guoxi
Published: July 2022

With the continuous development of science and technology, the state attaches great importance to industry, and the research on materials by researchers is getting more and more in-depth. The steel-wood structure is one of the material structures that has been focused on. The steel-timber composite (STC) structure has the characteristics of good mechanical performance, sustainable attributes, and lightweight. For the steel-timber structure with reinforced layer, its mechanical performance is better, stronger, and more durable. Particle algorithm (PSO for short) is an intelligent search algorithm derived from simulating the foraging behavior of birds. The PSO algorithm uses the information exchange ability of the population to search for the problem to obtain the optimal solution. The purpose of this paper is to study the mechanical properties of steel-timber structural systems with reinforced layers. In this paper, an improved PSO algorithm is proposed, and the algorithm model is used to conduct static tests on steel-timber structures with reinforced layers. The experimental results in this paper show for A and B two different steel-timber specimens with reinforced layers. When the number of reinforced layers of the A specimen is twice that of the B specimen, the stagnation amplitude of the B specimen is twice that of the A specimen. The cumulative energy consumption of A will be relatively more, in every 1 mm of displacement. A specimen is 4.6 kN·mm on average than B specimen, and the damping coefficient of A specimen is 0.028 larger than that of B specimen. This shows that for specimens with more reinforced layers, the higher the ultimate fatigue strength, the stronger the bearing capacity and the better the stability.