bluuebunny/crossref_metadata_2025 huggingface dataset:
Convolutional neural network-based techniques and error level analysis for image tamper detection
Authors: Shetty Sadanand Vijaya , Shetty Janardhana Shruthi , Purushothaman Sowmya , Hande Sarojadevi , Prakash Ramya
Published: January 2024

Photographs are the foremost powerful and trustworthy media of expression. At present, digital pictures not only serve forged information but also disseminate deceptive information. Users and experts with various objectives edit digital photographs. Images are frequently used as proof of reality or fact, therefore fake news or any publication that makes use of photos that have been altered in any way has a larger chance of deceiving readers. There is a need for a high-resolution image analysis model that processes individual pixels in images and a substantial amount of diverse image data, to detect image falsification. Convolutional neural network (CNN) with error level analysis (ELA) adopted in this research is found to be an ideal deep learning concept for detecting image manipulation. The model exhibited a validation accuracy of 99.6%, 99.7%, and 99.4% for CASIA V1.0, CASIA V2.0 and MICC datasets respectively. The accuracy for handmade tampered images was found to be 99.2%.
Enhancing fault tolerance: dual Q-learning with dynamic scheduling
Authors: Kalaskar Chetankumar , Somasundaram Thangam
Published: January 2024

Cloud computing has revolutionized IT delivery by offering scalable on-demand internet services encompassing software, platforms, and infrastructure. However, cloud services face significant performance challenges due to their susceptibility to failures given their vast operational scale. Implementing fault tolerance in dynamic cloud services is a key challenge, with complex configurations and dependencies complicating deployment. This paper introduces an innovative approach that combines double deep Q-learning (DDQL) with a dynamic fault-tolerant real-time scheduling algorithm (DFTRTSA) to enhance fault tolerance in real-time systems. DDQL, an extension of deep Q-learning, optimizes the fault-tolerance decision-making process. The algorithm adjusts scheduling strategies dynamically based on system conditions and errors. The fusion of DDQL and DFTRTSA aims to create a resilient and adaptive fault-tolerant mechanism, ensuring uninterrupted operation while meeting real-time requirements. This adaptive approach efficiently manages resources, meets deadlines, and gracefully handles errors, as demonstrated through experiments. Our DDQL-DFTRTSA method outperforms conventional fault-tolerant mechanisms in defect tolerance, energy efficiency, downtime reduction, and system dependability. It proves to be an ideal solution for real-time systems in dynamic and unpredictable environments.
Security enhancement of cyber-physical system using modified encryption AESGNRSA technique
Authors: Rameshwar Saraf Kundankumar , Malathi P.
Published: January 2024

A cyber-physical system (CPS) is a combination of physical components with computational elements to interact with the physical world. The integration of these two systems has led to an increase in security concerns. Traditional encryption algorithms designed for general-purpose computing environments may not adequately address the distinct challenges of CPS, such as limited processing power, delay, and resource-constrained hardware. Therefore, there is a pressing need to develop an encryption algorithm that is optimized for CPS security without compromising the critical real-time aspects of these systems. This research has designed a modified encryption technique named the advanced encryption standard in galois counter mode with nonce and rivest-shamir-adleman algorithm (AESGNRSA). A smart medical system is designed to monitor the health of remotely located patients. The AESGNRSA algorithm is applied to the three servers of this system. The data of 1.5 lakh patients is fed to this system to verify the effectiveness of the AESGNRSA algorithm. The performance parameters like encryption and decryption time, encryption and decryption throughput, and encrypted file size are calculated for the AESGNRSA algorithm. The comparative analysis proved that AESGNRSA has the highest performance as compared to other algorithms and it can protect CPS against many cyber-attacks.
Multimodal approach for early prediction of COVID-19 disease using convolutional neural network
Authors: Ankleshwar Milind , Chavan Pramod , Chavan Pratibha , K. Ambhore Sushil
Published: January 2024

The latest human coronavirus is COVID-19. Chest radiography imaging is essential for screening, early detection, and monitoring COVID-19 infections since the virus resides in the lungs. Classical real time reverse transcriptase polymerase chain reaction (RT-PCR) data and chest X-ray pictures will become more important for COVID-19 identification as the pandemic spreads due to their affordability, wide availability, and infection control benefits, which reduce cross-contamination. This work presents multi-modal hybrid automated approaches to classify COVID-19 illness into three clinical categories: normal, pathogenic, and COVID-19 utilising RT-PCR test data and online chest X-ray datasets. The RT-PCR and chest X-ray image datasets were processed using supervised machine learning and convolutional neural networks (CNN). Together, these measures help us separate COVID-19 patients, those with similar symptoms, and healthy persons. The author improved detection times and classification accuracy with extra tree classifier’s feature selection and openCV’s image sharpening. The proposed approaches were tested using a research dataset. The proposed methods allowed reliable COVID-19 disease categorization for clinical decision-making, with random forest (RF) classifier global precision values of 91.58% on the RT-PCR dataset and CNN model accuracy of 95.46% on improved sharpened images.
Generative adversarial networks with attentional multimodal for human face synthesis
Authors: BJ Sowmya , Meeradevi Meeradevi , Shedole Seems
Published: January 2024

Face synthesis and editing has increased cumulative consideration by the improvement of generative adversarial networks (GANs). The proposed attentional GAN-deep attentional multimodal similarity modal (AttnGAN-DAMSM) model focus on generating high-resolution images by removing discriminator components and generating realistic images from textual description. The attention model creates the attention map on the image and automatically retrieves the features to produce various sub-areas of the image. The DAMSM delivers fine-grained image-text identical loss to generative networks. This study, first describe text phrases and the model will generate a photorealistic high-resolution image composed of features with high accuracy. Next, model will fine-tune the selected features of face images and it will be left to the control of the user. The result shows that the proposed AttnGAN-DAMSM model delivers the performance metrics like structural similarity index measure (SSIM), feature similarity index measure (FSIM) and frechet inception distance (FID) using CelebA and CUHK face sketch (CUFS) dataset. For CelebFaces attribute (CelebA) dataset, the SSIM achieves 78.82% and for CUFS dataset, the SSIM achieves 81.45% which ensures accurate face synthesis and editing compared with existing methods such as GAN, SuperstarGAN and identity-sensitive GAN (IsGAN) models.
Multi-domain aspect-oriented sentiment analysis for movie recommendations using feature extraction
Authors: Kadurhalli Sangappa Jyothi , Chikkanaravangala Paramashivaia Shantala
Published: January 2024

Sentiment analysis is a well-recognized research field that has acknowledged significant attention in recent years. Researchers have made extensive efforts in employing various methodologies to explore these domains. Sentiment classification plays a fundamental role in natural language processing (NLP). However, studies have shown that sentiment classification models heavily depend on the specific domain. In the context of movie industry, where the demand for reliable movie reviews is high and not all movies are of exceptional quality and worthy of viewers time. Therefore, people depend on movie reviews before watching a movie. This explores the use of data from various domains to improve classification performance within each domain, addressing the difficulty of multi-domain sentiment classification in natural language processing. Therefore, it is crucial to effectively utilize shared sentiment knowledge across different domains for real-world applications. To solve these issues, a multi-domain aspect-oriented sentiment analysis for movie recommendation using feature extraction techniques. The main contribution of this work is to eliminate the time for users to go through a lengthy list of movies to make their decision. The novelty of this work is analysis of different movie genres, TV shows genres with accurate results. The presented approach's performance is validated by evaluating various metrics, including precision, recall, mean square error (MSE) and F1-score.
An efficient smart grid stability prediction system based on machine learning and deep learning fusion model
Authors: Lakshmanarao Annemneedi , Srisaila Ampalam , Srinivasa Ravi Kiran Tummala , Vasanth Kumar Kamathamu , Sekhar Koppireddy Chandra
Published: January 2024

A smart grid is a modern power system that allows for bidirectional communication, driven mostly by the idea of demand responsiveness. Predicting the stability of the smart grid is necessary for improving its dependability and maximizing the efficacy and regularity of electricity delivery. Predicting smart grid stability is difficult owing to the various elements that impact it, including consumer and producer engagement, which may contribute to smart grid stability. This research work proposes machine learning (ML) and deep learning (DL) approaches for predicting smart grid sustainability. Five ML algorithms, namely support vector machine (SVM), decision tree (DT), K-nearest neighbor (KNN), random forest (RF), and logistic regression (LR), were applied for the prediction of smart grid stability. Later, the stacking ensemble and voting ensemble of ML algorithms were also applied for prediction. To further increase accuracy, a novel fusion model with DL artifical neural networks (ANN) and ML SVM was applied and achieved an accuracy of 98.92%. The experiment results show that the proposed model outperformed existing models for smart grid stability prediction.
Implementing decision support tool for low-back pain diagnosis and prediction based on the range of motions
Authors: Gambo Ishaya , Mbada Chidozie , Aina Segun , Ogundare Timilehin , Ikono Rhoda , Alimi Olasunkami , Saah Francis , Magreola Michael , Agbonkhese Christopher
Published: January 2024

Low-back pain (LBP) is a complex health problem requiring accurate diagnosis and effective treatment. However, the current decision support system (DSS) for LBP only considers the patient’s pain intensity and treatment suitability, which may not lead to optimal outcomes. This paper proposes a novel DSS that combines machine learning (ML) and expert input to classify LBP types and provide more reliable and personalized recommendations. We used an open-source dataset to train and test various ML models, including an ensemble model that combines multiple classifiers. We also performed data analysis and feature extraction to enhance the model’s predictive power. We developed a prototype tool to demonstrate the model’s performance and usability. Our results show that the ensemble model achieved the highest accuracy of 92.02%, followed by random forest (RF) (91.01%), multilayer perceptron (MP) (91.01%), and support vector machine (SVM) (87.88%). Our findings suggest that ML can help LBP specialists diagnose and treat LBP more effectively by learning from historical data and predicting LBP categories. Our DSS can potentially improve the quality of life for LBP patients and reduce the burden on the healthcare system.
Long-term power prediction of photovoltaic panels based on meteorological parameters and support vector machine
Authors: Gupta Saurabh , Ramasamy Palanisamy , Maharajan Murugamani Pandi , Kuppusamy Selvakumar , Devadoss Selvabharathi , Suresh Barath , Kumar Vignesh
Published: January 2024

Solar energy is the most generally accessible energy in the entire globe. Proper solar panel maintenance is necessary to reduce reliance on imported energy. Continuous monitoring of the solar panel's power output is required. The deployment of internet of things (IoT) monitoring of solar panels for maintenance is the basis for the current research. A multi-variable long-term photovoltaic (PV) power production prediction approach based on support vector machine (SVM) is developed in this study with the aim of completely evaluating the influence of PV panels performance and actual operational state factors on the power generation efficiency. This study examines the use of SVM and climatic factors to forecast the long-term output of power from solar panels. A solar power facility in a semi-arid area provided the data utilized in this investigation. Temperature, humidity, wind speed, and sun radiation are some of the meteorological variables that were considered in the study. To anticipate the power generation of the panels, the SVM is trained using the climatic factors and the power generation data. The findings demonstrate that the SVM model consistently predicts the panels' long-term power generation with a high degree of accuracy.
Characteristics of symmetrical components for high impedance faults in distribution networks with photovoltaic inverters
Authors: Yamashika Herris , Syafii Syafii
Published: January 2024

This work models a photovoltaic (PV) inverter connected to an IEC microgrid system. The purpose of this study was to find the characteristics of symmetrical components before and after a high impedance single phase short-circuit fault. The IEC microgrid system is tailored to the distribution system in Indonesia, where the applied voltage is 20 kV. Only parameters related to the short-circuit study are included in the model. A second-order generalized integrator frequency-locked-loop is utilized to represent the 3-phase PV inverter. The inverter model, previously treated as an ideal current source, and positive sequence current are no longer employed, as they fail to depict the characteristics of symmetric components during a phase-to-ground short-circuit fault. The IEC microgrid system connected to the PV inverter is simulated using ATPDraw-electro magnetic transient program (EMTP). Simulation results reveal that the changes in the symmetric component values of current after a fault experience a very insignificant increase. Meanwhile, the positive sequence voltage values following the short-circuit fault exhibit a negligible decrease. In contrast, the negative sequence and zero sequence voltage components after the short-circuit fault undergo a significant increase.
Fault protection of quasi-delay-insensitive pipeline models using efficient coding for asynchronous network-on-chip
Authors: Siddagangappa Renu , Dunthur Krishnagowda Nayana , Tumkur Srinivas Murthy Deepthi
Published: January 2024

One promising approach for creating the chip-level connection of multiprocessing system on chip (MPSoC) is asynchronous logic. However, asynchronous systems are susceptible to errors. In this manuscript, the efficient fault-tolerant (FT) quasi-delay-insensitive (QDI) pipeline modules are designed using a delay-insensitive redundant check (DIRC) coding mechanism. The DIRC coding approach can tolerate single and multi-bit transient faults (TFs) in QDI-pipeline modules. The 4-phase 1-of-n coding approach incorporates DIRC-based QDI pipeline stages to strengthen the asynchronous links against TFs. The DIRC-based QDI pipeline stages are further used as asynchronous links in asynchronous network-on-chip ((NoC) for fault-free communication. The performance metrics like chip area, delay, and power parameters are evaluated in detail against different data widths for both basic unprotected and DIRC-based QDI pipeline modules.
 The DIRC-based QDI-pipeline module with 1-of-4 code uses only <2% chip area with a delay of 7.4 ns and power of 117 mW on Artix-7 chip for data width 128. The code rate of the proposed work decreased by 33.33% for both 1-of-2 and 1-of-4 codes in DIRC-based QDI-pipeline modules.
The influences of LaVO4:Eu3+,Cr3+ red phosphors on white light-emitting diode applications
Authors: Hung Khanh Nguyen , Le Thai Nguyen , Minh Bui Thuc , Phuc Dang Huu , Thanh Thien Huynh
Published: January 2024

In this present paper, the LaVO4:Eu3+,Cr3+ (LV:Eu,Cr) red-orange phosphorsare introduced in WLED fabrication. The LV:Eu,Cr phosphor is synthesized with high-temperature solid-phase reaction. The luminescence properties of the phosphor are monitored with ultraviolet-visible and near-infrared (UV-vis-NIR) measurements. The heat generating in the phosphor sample is also investigated with different power densities of the 980 nm laser. The phosphor exhibits absorption bands at 254 nm and 316 nm, suitable for UV light-emitting diodes (UV LED) applications. The Cr3+ concentrations have noticeable effects on the luminescence of the phosphor. The increasing Cr3+ dosage initiates reduction in Eu3+ emission intensity and luminescence lifetime average. The heat-activated amount in the phosphor is also significant with the higher concentration of Cr3+ ions. When using the LV:Eu,Cr phosphor in white light-emitting model (WLED), the dominant red-orange emission centered at 595 nm is observed, in addition to the blue peak at 453 nm. The luminosity, color rendition, and color uniformity of the WLED light are also discussed. The findings indicate that the phosphor can be combined with other high-efficiency blue and green phosphors to obtain the improved color rendition and luminous performances and used in heat-creating optical applications.
A new approximate solution of the fractional trigonometric functions of commensurate order to a regular linear system
Authors: Boucherma Djamel , Idiou Daoud , Achour Toufik , Lotfi Cherrad Mohamed , Chettah Khaled , Hamadi Billel
Published: January 2024

This paper introduces a novel approach to the approximate solution of linear differential equations associated with principal fractional trigonometry and the R function. This method proposes a solution that is expressed by adding appropriate fractional linear fundamental functions. Laplace transforms of these functions are irrational. Therefore, we rounded these functions to obtain rational functions in the form of damped cosine, damped sine, cosine, sine and exponential functions. This transformation was achieved by utilizing the concept of fractional commensurate order and, as a result, has direct practical relevance to real-world physics. The precision and effectiveness of the approach are demonstrated through illustrative examples of solving fractional linear systems.
Optimisation of nonlinear controllers for a quadrotor using metaheuristic algorithm
Authors: Samantha Zuñiga-Peña Nadia , Hernandez-Romero Norberto , Carlos Seck-Tuoh Mora Juan , Medina-Marín Joselito , Cesar Ramos-Fernández Julio
Published: January 2024

Unmanned aerial vehicles (UAVs) facilitate complex activities and are widely used for aerial transport. Quadrotor UAVs (QUAV), the most popular UAV containing four motors, are characterised by higher control properties since they have fewer actuators than degrees of freedom, implying a nonlinear underactuated system. In addition, the coupling of dynamics, flaws while modelling and parameter uncertainty are the factors that hinder the design and implementation of a controller. Here, we present the modelling, optimisation, simulation, and implementation methodology for controllers, proportional-integralderivative (PID), and super-twisting-sliding mode control (ST-SMC). We carry out the parameterisation problem of controllers using the hunger game search (HGS) metaheuristic algorithm. This process was developed offline, and the values obtained were successfully implemented in simulation and experimental form. The testing platform comprises a motion capture system, Vicon® Bonita cameras, linked by ROS, that allows the known position and the attitude of a Parrot® QUAV bebop1. The whole six dynamics of the QUAV are included in the implementation, translational trajectories X-Y are trapezoidal, and the altitude trajectory is a ramp. The results enabled the comparison of the statistics calculation of each controller. Successful tracking trajectories were obtained even with disturbance when the ST-SMC algorithm was implemented with root mean square error (RMSE)=0.0176.
Risk Prediction in Male Adolescents With Congenital Long QT Syndrome: Implications for Sex‐Specific Risk Stratification in Potassium Channel‐Mediated Long QT Syndrome
Authors: Bjelic Milica , Goldenberg Ido , Younis Arwa , Chen Anita Y. , Huang David T. , Yoruk Ayhan , Aktas Mehmet K. , Rosero Spencer , Cutter Kristina , McNitt Scott , Sotoodehnia Nona , Kudenchuk Peter J. , Rea Thomas D. , Arking Dan E. , Zareba Wojciech , Ackerman Michael J. , Goldenberg Ilan
Published: January 2024

Background

Sex‐specific risk management may improve outcomes in congenital long QT syndrome (LQTS). We recently developed a prediction score for cardiac events (CEs) and life‐threatening events (LTEs) in postadolescent women with LQTS. In the present study, we aimed to develop personalized risk estimates for the burden of CEs and LTEs in male adolescents with potassium channel‐mediated LQTS.

Methods and Results

The prognostic model was derived from the LQTS Registry headquartered in Rochester, NY, comprising 611 LQT1 or LQT2 male adolescents from age 10 through 20 years, using the following variables: genotype/mutation location, QTc‐specific thresholds, history of syncope, and β‐blocker therapy. Anderson‐Gill modeling was performed for the end point of CE burden (total number of syncope, aborted cardiac arrest, and appropriate defibrillator shocks). The applicability of the CE prediction model was tested for the end point of the first LTE (excluding syncope and adding sudden cardiac death) using Cox modeling. A total of 270 CEs occurred during follow‐up. The genotype–phenotype risk prediction model identified low‐, intermediate‐, and high‐risk groups, comprising 74%, 14%, and 12% of the study population, respectively. Compared with the low‐risk group, high‐risk male subjects experienced a pronounced 5.2‐fold increased risk of recurrent CEs (
P
<0.001), whereas intermediate‐risk patients had a 2.1‐fold (
P
=0.004) increased risk . At age 20 years, the low‐, intermediate‐, and high‐risk adolescent male patients had on average 0.3, 0.6, and 1.4 CEs per person, respectively. Corresponding 10‐year adjusted probabilities for a first LTE were 2%, 6%, and 8%.

Conclusions

Personalized genotype–phenotype risk estimates can be used to guide sex‐specific management in male adolescents with potassium channel‐mediated LQTS.
Mitral Annulus Calcium Score in Patients With Calcific Mitral Stenosis Undergoing Invasive Hemodynamic Assessment
Authors: El Sabbagh Abdallah , Parikh Pragnesh , Ray Jordan , Nishimura Rick A. , Pislaru Sorin V. , Pellikka Patricia A. , Guerrero Mayra , Hochwald Alexander , Miranda William R.
Published: January 2024

Background

Aortic valve calcium score is associated with hemodynamic severity of aortic stenosis. Whether this association is present in calcific mitral stenosis remains unknown.

Methods and Results

This study was a retrospective analysis of consecutive patients with mitral stenosis secondary to mitral annular calcification (MAC) undergoing transseptal catheterization. All patients underwent invasive mitral valve assessment via direct left atrial and left ventricular pressure measurement. Computed tomography within 1 year of cardiac catheterization and with adequate visualization of the mitral annulus was included. MAC calcium score quantification by Agatston method was obtained offline using dedicated software (Aquarius, TeraRecon, V.4). Median patient age was 66.9±11.2 years, 47% of patients were women, 50% had coronary artery disease, 40% had atrial fibrillation, 47% had prior cardiac surgery, and 33% had prior chest radiation. Median diastolic mitral valve gradient was 9.4±3.4 mm Hg on echocardiography and 8.5±4 mm Hg invasively. Invasive median mitral valve area using the Gorlin formula was 1.87±0.9 cm
2
. Median MAC calcium score for the cohort was 7280±7937 Hounsfield units. MAC calcium score correlated with the presence of atrial fibrillation (
P
=0.02) but was not associated with other comorbidities. There was no correlation between MAC calcium score and mitral valve area (
r
=0.07;
P
=0.6) or mitral valve gradient (
r
=−0.03;
P
=0.8).

Conclusions

MAC calcium score did not correlate with invasively measured mitral valve gradient and mitral valve area in patients with MAC‐related mitral stenosis, suggesting that calcium score should not be used as a surrogate for invasive hemodynamic parameters.
Role of Cerebral Embolic Protection Devices in Patients Undergoing Transcatheter Aortic Valve Replacement: An Updated Meta‐Analysis
Authors: Kaur Arpanjeet , Dhaliwal Arshdeep S. , Sohal Sumit , Gwon Yeongjin , Gupta Soumya , Bhatia Kirtipal , Dominguez Abel Casso , Basman Craig , Tamis‐Holland Jacqueline
Published: January 2024

Background

Cerebral embolic protection devices (CEPD) capture embolic material in an attempt to reduce ischemic brain injury during transcatheter aortic valve replacement. Prior reports have indicated mixed results regarding the benefits of these devices. With new data emerging, we performed an updated meta‐analysis examining the effect of CEPD during transcatheter aortic valve replacement on various clinical, neurological, and safety parameters.

Methods and Results

A comprehensive review of electronic databases was performed comparing CEPD and no‐CEPD in transcatheter aortic valve replacement. Primary clinical outcome was all‐cause stroke. Secondary clinical outcomes were disabling stroke and all‐cause mortality. Neurological outcomes included worsening of the National Institutes of Health Stroke Scale score, Montreal Cognitive Assessment score from baseline at discharge, presence of new ischemic lesions, and total lesion volume on neuroimaging. Safety outcomes included major or minor vascular complications and stage 2 or 3 acute kidney injury. Seven randomized controlled trials with 4016 patients met the inclusion criteria. There was no statistically significant difference in the primary clinical outcome of all‐cause stroke; secondary clinical outcomes of disabling stroke, all‐cause mortality, neurological outcomes of National Institutes of Health Stroke Scale score worsening, Montreal Cognitive Assessment worsening, presence of new ischemic lesions, or total lesion volume on diffusion‐weighted magnetic resonance imaging between CEPD versus control groups. There was no statistically significant difference in major or minor vascular complications or stage 2 or 3 acute kidney injury between the groups.

Conclusions

The use of CEPD in transcatheter aortic valve replacement was not associated with a statistically significant reduction in the risk of clinical, neurological, and safety outcomes.
One‐Year Disability Trajectories and Long‐Term Cardiovascular Events, Recurrent Stroke, and Mortality After Ischemic Stroke
Authors: Du Jigang , Zhai Yujia , Dong Wenjing , Che Bizhong , Miao Mengyuan , Peng Yanbo , Ju Zhong , Xu Tan , He Jiang , Zhang Yonghong , Zhong Chongke
Published: January 2024

Background

Patients with stroke are often affected by varying degrees of functional disability and have different evolution patterns in functional disability. However, little is known about the predictive usefulness of disability changes after stroke. We aimed to describe 1‐year disability trajectories and to assess the associations of longitudinal disability trajectories with 24‐month clinical outcomes after ischemic stroke.

Methods and Results

A total of 3533 patients with ischemic stroke from CATIS (China Antihypertensive Trial in Acute Ischemic Stroke) were studied. Distinct trajectories of disability were identified by the group‐based trajectory model, as measured by modified Rankin Scale score within 12 months. Cox proportional hazards regression models were used to examine the associations of disability trajectories with 24‐month cardiovascular events and all‐cause mortality. We identified 4 distinct disability trajectories: no significant disability (562 participants [15.9%]), slight disability to recovery (1575 participants [44.6%]), severe to moderate disability (1087 participants [30.8%]), and persistent severe disability (309 participants [8.7%]). Compared with no significant disability trajectory, the multivariable adjusted hazard ratios (95% CIs) of patients within the persistent heavy–severe trajectory were 2.63 (1.20–5.76) for cardiovascular events, 2.55 (1.12–5.79) for recurrent stroke, and 6.10 (2.22–16.72) for all‐cause mortality; notably, the hazard ratios (95% CIs) for patients within the severe to moderate disability trajectory were 1.99 (1.01–3.94) for cardiovascular events and 1.85 (1.03–3.33) for the composite outcome of cardiovascular events and all‐cause mortality.

Conclusions

Functional disability trajectories within 12 months after stroke onset were associated with the risk of 24‐month adverse outcomes. Patients with persistent severe disability or severe to moderate disability had higher risk of cardiovascular events and all‐cause mortality.

Registration

URL:
https://www.clinicaltrials.gov
; Unique identifier:
NCT01840072
Primary and Secondary Cardiovascular and Kidney Prevention With Canagliflozin: Insights From the CANVAS Program and CREDENCE Trial
Authors: Sharma Abhinav , Razaghizad Amir , Joury Abdulaziz , Levin Adeera , Bajaj Harpreet S. , Mancini G. B. John , Wong Norman C. , Slee April , Ang Fernando G. , Rapattoni Wally , Neuen Brendon L. , Arnott Clare , Perkovic Vlado , Mahaffey Kenneth W.
Published: January 2024

Background

This study evaluated the effects of canagliflozin in patients with type 2 diabetes with and without prevalent cardiovascular disease (secondary and primary prevention).

Methods and Results

This was a pooled participant‐level analysis of the CANVAS (Canagliflozin Cardiovascular Assessment Study) Program and CREDENCE (Canagliflozin and Renal Events in Diabetes With Established Nephropathy Clinical Evaluation) trial. The CANVAS Program included participants with type 2 diabetes at elevated cardiovascular risk, whereas the CREDENCE trial included participants with type 2 diabetes and albuminuric chronic kidney disease. Hazard ratios (HRs) with interaction terms were obtained from Cox regression models to estimate relative risk reduction with canagliflozin versus placebo across the primary and secondary prevention groups. We analyzed 5616 (38.9%) and 8804 (61.1%) individuals in the primary and secondary prevention subgroups, respectively. Primary versus secondary prevention participants were on average younger (62.2 versus 63.8 years of age) and more often women (42% versus 31%). Canagliflozin reduced the risk of major adverse cardiovascular events (HR, 0.84 [95% CI, 0.76–0.94]) consistently across primary and secondary prevention subgroups (
P
interaction
=0.86). Similarly, no treatment effect heterogeneity was observed with canagliflozin for hospitalization for heart failure, cardiovascular death, end‐stage kidney disease, or all‐cause mortality (all
P
interaction
>0.5).

Conclusions

Canagliflozin reduced cardiovascular and kidney outcomes with no statistical evidence of heterogeneity for the treatment effect across the primary and secondary prevention subgroups in the CANVAS Program and CREDENCE trial. Although studies on the optimal implementation of canagliflozin within these populations are warranted, these results reinforce canagliflozin's role in cardiorenal prevention and treatment in individuals with type 2 diabetes.

Registration

URL:
https://www.clinicaltrials.gov
; Unique identifiers: NCT01032629, NCT01989754, NCT02065791.
Administrative Model for Profiling Hospital Performance on Coronary Artery Bypass Graft Surgery: Based on the Chinese Hospital Quality Monitoring System
Authors: Su Xiaoting , Zhang Danwei , Gu Dachuan , Rao Chenfei , Chen Sipeng , Fan Jing , Zheng Zhe
Published: January 2024

Background

We aimed to develop an administrative model to profile the performance on the outcomes of coronary artery bypass grafting across hospitals in China.

Methods and Results

This retrospective study was based on the Chinese Hospital Quality Monitoring System (HQMS) from 2016 to 2020. The coronary artery bypass grafting cases were identified by procedure code, and those of 2016 to 2017 were randomly divided into modeling and validation cohorts, while those in other years were used to ensure the model stability across years. The outcome was discharge status as “death or withdrawal,” and that withdrawal referred to discharge without medical advice when patients were in the terminal stage but reluctant to die in the hospital. Candidate covariates were mainly identified by diagnoses or procedures codes. Patient‐level logistic models and hospital‐level hierarchical models were established. A total of 203 010 coronary artery bypass grafts in 699 hospitals were included, with 60 704 and 20 233 cases in the modeling and validation cohorts and 40 423, 42 698, and 38 952 in the years 2018, 2019, and 2020, respectively. The death or withdrawal rate was 3.4%. The areas under the curve were 0.746 and 0.729 in the patient‐level models of modeling and validation cohorts, respectively, with good calibration and stability across years. Hospital‐specific risk‐standardized death or withdrawal rates were 2.61% (interquartile range, 1.87%–3.99%) and 2.63% (interquartile range, 1.97%–3.44%) in the modeling and validation cohorts, which were highly correlated (correlation coefficient, 0.96;
P
<0.001). Between‐hospital variations were distinguished among hospitals of different volumes and across years.

Conclusions

The administrative model based on Hospital Quality Monitoring System could profile hospital performance on coronary artery bypass grafting in China.
Gestational Hypoxia Impaired Endothelial Nitric Oxide Synthesis Via miR‐155‐5p/NADPH Oxidase/Reactive Oxygen Species Axis in Male Offspring Vessels
Authors: Zhao Meng , Lei Jiahui , Deng Fengying , Zhao Chenxuan , Xu Ting , Ji Bingyu , Fu Mengyu , Wang Xietong , Sun Miao , Zhang Meihua , Gao Qinqin
Published: January 2024

Background

Nitric oxide (NO) is the most important vasodilator secreted by vascular endothelial cells, and its abnormal synthesis is involved in the development of cardiovascular disease. The prenatal period is a critical time for development and largely determines lifelong vascular health in offspring. Given the high incidence and severity of gestational hypoxia in mid‐late pregnancy, it is urgent to further explore whether it affects the long‐term synthesis of NO in offspring vascular endothelial cells.

Methods and Results

Pregnant Sprague–Dawley rats were housed in a normoxic or hypoxic (10.5% O
2
) chamber from gestation days 10 to 20. The thoracic aortas of fetal and adult male offspring were isolated for experiments. Gestational hypoxia significantly reduces the NO‐dependent vasodilation mediated by acetylcholine in both the fetal and adult offspring thoracic aorta rings. Meanwhile, acetylcholine‐induced NO synthesis is impaired in vascular endothelial cells from hypoxic offspring thoracic aortas. We demonstrate that gestational hypoxic offspring exhibit a reduced endothelial NO synthesis capacity, primarily due to increased expression of NADPH oxidase 2 and enhanced reactive oxygen species. Additionally, gestational hypoxic offspring show elevated levels of miR‐155‐5p in vascular endothelial cells, which is associated with increased expression of NADPH oxidase 2 and reactive oxygen species generation, as well as impaired NO synthesis.

Conclusions

The present study is the first to demonstrate that gestational hypoxia impairs endothelial NO synthesis via the miR‐155‐5p/NADPH oxidase 2/reactive oxygen species axis in offspring vessels. These novel findings indicate that the detrimental effects of gestational hypoxia on fetal vascular function can persist into adulthood, providing new insights into the development of vascular diseases.
Interleukin 17A Contributes to Blood‐Brain Barrier Disruption of Hypothalamic Paraventricular Nucleus in Rats With Myocardial Infarction
Authors: Yu Yang , Weiss Robert M. , Wei Shun‐Guang
Published: January 2024

Background

Elevated inflammatory cytokines in the periphery have been identified as active contributors to neuroinflammation and sympathetic overactivity in heart failure (HF). Yet, the exact mechanisms by which these cytokines breach the blood‐brain barrier (BBB) to exert their effects on the brain remain elusive. Interleukin 17A has been linked to BBB disruption in various neurologic disorders, and its levels were significantly augmented in circulation and the brain in HF. The present study aimed to determine whether the BBB integrity was compromised within the hypothalamic paraventricular nucleus (PVN), and if so, whether interleukin 17A contributes to BBB disruption in myocardial infarction–induced HF.

Methods and Results

Male Sprague‐Dawley rats underwent coronary artery ligation to induce HF or sham surgery. Some HF rats received bilateral PVN microinjections of an interleukin 17 receptor A small interfering RNA or a scrambled small interfering RNA adeno‐associated virus. Four weeks after coronary artery ligation, the permeability of the BBB was evaluated by intracarotid injection of fluorescent dyes (fluorescein isothiocyanate–dextran 10 kDa+rhodamine‐dextran 70 kDa). Compared with sham‐operated rats, HF rats exhibited an elevated extravasation of fluorescein isothiocyanate–dextran 10 kDa within the PVN but not in the brain cortex. The plasma interleukin 17A levels were positively correlated with fluorescein isothiocyanate 10 kDa extravasation in the PVN. The expression of caveolin‐1, a transcytosis marker, was augmented, whereas the expression of tight junction proteins was diminished in HF rats. Interleukin 17 receptor A was identified within the endothelium of PVN microvessels. Treatment with interleukin 17 receptor A small interfering RNA led to a significant attenuation of fluorescein isothiocyanate 10 kDa extravasation in the PVN and reversed expression of caveolin‐1 and tight junction–associated proteins in the PVN.

Conclusions

Collectively, these data indicate that BBB permeability within the PVN is enhanced in HF and is likely attributable to increased interleukin 17A/interleukin 17 receptor A signaling in the BBB endothelium, by promoting caveolar transcytosis and degradation of tight junction complexes.
Optimizing ASReview Simulations: A generic Multiprocessing Solution for ‘Light-data’ and ‘Heavy-data’ Users
Authors: Romanov Sergei , Siqueira Abel Soares , de Bruin Jonathan , Teijema Jelle , Hofstee Laura , van de Schoot Rens
Published: January 2024

Active learning can be used for optimizing and speeding up the screening phase of systematic reviews. Running simulation studies mimicking the screening process can be used to test the performance of different machine-learning models or to study the impact of different training data. This paper presents an architecture design with a multiprocessing computational strategy for running many such simulation studies in parallel, using the ASReview Makita workflow generator and Kubernetes software for deployment with cloud technologies. We provide a technical explanation of the proposed cloud architecture and its usage. In addition to that, we conducted 1140 simulations investigating the computational time using various numbers of CPUs and RAM settings. Our analysis demonstrates the degree to which simulations can be accelerated with multiprocessing computing usage. The parallel computation strategy and the architecture design that was developed in the present paper can contribute to future research with more optimal simulation time and, at the same time, ensure the safe completion of the needed processes.
‘Solving’ the Paradox of the Odyssean Ethiopians’ Twin Dual Localization
Authors: Gordon Joel
Published: January 2024

This paper considers the narrative significance of localization in Homer’s Odyssey, in particular singular places that are associated with multiple spaces (identified here as dual localization). Our reading posits that spatial features hold narrative significance and, once uncovered, this resolves ‘problematic’ issues that may arise from spatial paradoxes. The chosen case study is the Odyssean land of the Ethiopians with its twin dual localization: (1) it is located simultaneously at the eastern and western peripheries of the world while also located singularly ‘with Poseidon’; and (2) this peripheral localization contrasts with a later ‘real world’ setting in Egypt/North Africa. While this people’s localization has been the subject of prior study, this paper presents a novel analysis: these localizations serve a characterizing function which, in turn, relates to the thematic function of Menelaus’ embedded narrative as foreshadowing the primary narrative of Odysseus’ nostos.
On Prodicus and the Derveni Papyrus
Authors: Henry John
Published: January 2024

Another identification for the author of the Derveni papyrus has been suggested: the fifth-century BCE sophist Prodicus of Ceos. Producing over 18 testimonia, Lebedev argues that the Derveni papyrus and the thought of Prodicus agree on many points that have previously been disregarded, including their linguistic approach and cosmological doctrines. On the basis of this evidence, it is suggested that Prodicus wrote the Derveni papyrus as an atheistic polemic and a sophistic deconstruction of popular religion. However, this article will suggest that the testimonia does not establish the case, and consequently the authorship of the Derveni papyrus remains undetermined.
The Stirring Tropics: The Ubiquity of Moisture Modes and Moisture–Vortex Instability
Authors: Mayta Víctor C. , Adames Corraliza Ángel F.
Published: January 2024

Observations of column water vapor in the tropics show significant variations in space and time, indicating that it is strongly influenced by the passage of weather systems. It is hypothesized that many of the influencing systems are moisture modes, systems whose thermodynamics are governed by moisture. On the basis of four objective criteria, results suggest that all oceanic convectively coupled tropical depression (TD)-like waves and equatorial Rossby waves are moisture modes. These modes occur where the horizontal column moisture gradient is steep and not where the column water vapor content is high. Despite geographical basic-state differences, the moisture modes are driven by the same mechanisms across all basins. The moist static energy (MSE) anomalies propagate westward by horizontal moisture advection by the trade winds. Their growth is determined by the advection of background moisture by the anomalous meridional winds and anomalous radiative heating. Horizontal maps of column moisture and 850-hPa streamfunction show that convection is partially collocated with the low-level circulation in nearly all the waves. Both this structure and the process of growth indicate that the moisture modes grow from moisture–vortex instability. Last, space–time spectral analysis reveals that column moisture and low-level meridional winds are coherent and exhibit a phasing that is consistent with a poleward latent energy transport. Collectively, these results indicate that moisture modes are ubiquitous across the tropics. That they occur in regions of steep horizontal moisture gradients and grow from moisture–vortex instability suggests that these gradients are inherently unstable and are subject to continuous stirring.

Significance Statement

Over the tropics, column water vapor has been found to be highly correlated with precipitation, especially in slowly evolving systems. These observations and theory support the hypothesis that moisture modes exist, a type of precipitating weather system that does not exist in dry theory. In this study, we found that all oceanic tropical depression (TD)-like waves and equatorial Rossby waves are moisture modes. These systems exist in regions where moisture varies greatly in space, and they grow by transporting air from the humid areas of the tropics toward their low pressure center. These results indicate that the climatological-mean distribution of moisture in the tropics is unstable and is subject to stirring by moisture modes.
Policing the pandemic: Exploring public perceptions of the enforcement of COVID-19 restrictions in the United Kingdom
Authors: Boulton Laura , Simanovic Tia , McManus Michelle , Walker Dominique
Published: January 2024

Traditional UK policing relies on Peelian principles of policing by consent in which public views of police legitimacy are crucial. This study used a mixed methods survey design to explore the impact of the Coronavirus Act 2020 on public perceptions towards the police in one UK force region. The findings indicate that self-reported compliance with COVID-19 measures was significantly related to trust in local policing. Qualitative responses indicate that police enforcement of Covid regulations was believed to infringe on individual liberties while losing focus on ‘real crime’ and decreasing trust in police.
‘It’s why you get up in the morning’. A Straussian grounded theory study of coping in police officers who investigate rape and child abuse
Authors: Foley Jim , Hassett Alex , Williams Emma
Published: January 2024

Policing by its very nature has been widely recognised as being inherently stressful with little that can be done to prevent police officers’ exposure to both primary and secondary trauma. Officers involved in the investigation of child abuse and sexual offences have been further recognised as working in some of the most stressful and demanding roles in policing. However, there has been little research within this high-risk group of officers which seeks to understand how they cope with both the organisational and occupational stressors they are exposed to, as well as which strategies help them to ‘ get up in the morning’. Data were collected through twenty-three (23) semi-structured interviews, with Straussian Grounded Theory used as a framework to develop a model of coping. This study highlighted that although some officers were affected by the traumatic nature of their work, there were other risk factors present which appear to have impacted on them more significantly including ‘burnout’, ’compassion fatigue’ and ‘moral injury’. Protective factors were identified as ‘being in control’, ‘organisational, social and peer support’ as well as ‘having a purpose’ all of which impacted on an officer’s ability to cope with the work they do. The present findings extend our knowledge of key concepts relating to police officer coping which may help officers working in these high-risk roles to cope with challenges they face daily. Recommendations for further research on how to support this group of officers, as well as implications for practice are discussed.