bluuebunny/crossref_metadata_2025_split huggingface dataset:
Frequency‐specific dual‐attention based adversarial network for blood oxygen level‐dependent time series prediction
Authors: Zheng Weihao , Bao Cong , Mu Renhui , Wang Jun , Li Tongtong , Zhao Ziyang , Yao Zhijun , Hu Bin 
Published: September 2024

AbstractFunctional magnetic resonance imaging (fMRI) is currently one of the most popular technologies for measuring brain activity in both research and clinical contexts. However, clinical constraints often result in short fMRI scan durations, limiting the diagnostic performance for brain disorders. To address this limitation, we developed an end‐to‐end frequency‐specific dual‐attention‐based adversarial network (FDAA‐Net) to extend the time series of existing blood oxygen level‐dependent (BOLD) data, enhancing their diagnostic utility. Our approach leverages the frequency‐dependent nature of fMRI signals using variational mode decomposition (VMD), which adaptively tracks brain activity across different frequency bands. We integrated the generative adversarial network (GAN) with a spatial–temporal attention mechanism to fully capture relationships among spatially distributed brain regions and temporally continuous time windows. We also introduced a novel loss function to estimate the upward and downward trends of each frequency component. We validated FDAA‐Net on the Human Connectome Project (HCP) database by comparing the original and predicted time series of brain regions in the default mode network (DMN), a key network activated during rest. FDAA‐Net effectively overcame linear frequency‐specific challenges and outperformed other popular prediction models. Test–retest reliability experiments demonstrated high consistency between the functional connectivity of predicted outcomes and targets. Furthermore, we examined the clinical applicability of FDAA‐Net using short‐term fMRI data from individuals with autism spectrum disorder (ASD) and major depressive disorder (MDD). The model achieved a maximum predicted sequence length of 40% of the original scan durations. The prolonged time series improved diagnostic performance by 8.0% for ASD and 11.3% for MDD compared with the original sequences. These findings highlight the potential of fMRI time series prediction to enhance diagnostic power of brain disorders in short fMRI scans.
Analysis on pulse rate variability for pilot workload assessment based on wearable sensor
Authors: Wang Yunbiao , Zhang Chenyang , Liu Chenglin , Liu Kun , Xu Fang , Yuan Jixue , Jiang Chaozhe , Liu Chuang , Cao Weiwei 
Published: September 2024

AbstractThe workload levels of pilots directly affect their flight performance and the safety of the whole flight. To explore the real‐time workload of pilots in different flight phases (takeoff, cruise, and landing), this paper leveraged National Aeronautics and Space Administration Task Load Index (NASA‐TLX), a subjective evaluation scale, and PhotoPlethysmoGraphy (PPG) signals of 21 participants using a flight simulator and a wearable sensor. First, the workloads of pilots under different phases were explored by the NASA‐TLX scales; secondly, the pulse rate variability (PRV) features were selected by variance analysis and random forest importance evaluation; finally, the performances of the k‐nearest neighbor (KNN), random forest (RF), and support vector machine (SVM) were compared for workload levels identification. It is shown that the workloads are ranked as follows: landing > takeoff > cruise. SDNN, CVCD, CVNNI, LF, TP, SD2, and SD2/SD1 were used as selected features with significant differences in different flight phases. In addition, machine learning models can effectively identify pilot workloads, and feature selection enhances the performance of both KNN and RF classifiers. The best identification of workload was achieved using the selected PRV features as inputs to the KNN classifier, with an average accuracy of 88.9%. Our results indicate that the KNN classifier and PRV features are suitable for identifying pilot workload. The pilot workload is highest during the landing phase, which provides a reference for flight safety management. The findings from this research could contribute to developing a robust pilot workload detection system and improve current flight operation safety regulations.
Understanding resurgence and other emergent activity with the laws of allocation, induction, and covariance
Authors: Podlesnik Christopher A. , Baum William M. 
Published: September 2024

AbstractResurgence is defined as an increase in a previously extinguished target response (B1) resulting from the worsening of conditions for a more recently reinforced alternative response (B2). Worsening includes extinction or reductions in rate, amount, and immediacy of delivery of food or some other phylogenetically important event (PIE). In the first part of the article, we apply the laws of allocation, induction, and covariance to understand not only resurgence of operant activity previously covarying with the PIE (B1) but also a constellation of ontogenetic and phylogenetic activities both related to the PIE (B0) and unrelated to the PIE (BN). In the second part, we discuss how induction might be incorporated into and provide alternative processes within an existing matching‐based framework, resurgence as choice (RaC). We begin to identify how this range of activities could depend on changes in the relative competitive weight (V) of all available activities (B1, B2, B0, BN) in addition to only those receiving explicit training (B1, B2). Future empirical and theoretical research is needed within this framework to provide a more complete understanding of resurgence and behavior more generally.
Towards the automatic risk of bias assessment on randomized controlled trials: A comparison of RobotReviewer and humans
Authors: Tian Yuan , Yang Xi , Doi Suhail A. , Furuya‐Kanamori Luis , Lin Lifeng , Kwong Joey S. W. , Xu Chang 
Published: September 2024

AbstractRobotReviewer is a tool for automatically assessing the risk of bias in randomized controlled trials, but there is limited evidence of its reliability. We evaluated the agreement between RobotReviewer and humans regarding the risk of bias assessment based on 1955 randomized controlled trials. The risk of bias in these trials was assessed via two different approaches: (1) manually by human reviewers, and (2) automatically by the RobotReviewer. The manual assessment was based on two groups independently, with two additional rounds of verification. The agreement between RobotReviewer and humans was measured via the concordance rate and Cohen's kappa statistics, based on the comparison of binary classification of the risk of bias (low vs. high/unclear) as restricted by RobotReviewer. The concordance rates varied by domain, ranging from 63.07% to 83.32%. Cohen's kappa statistics showed a poor agreement between humans and RobotReviewer for allocation concealment (κ = 0.25, 95% CI: 0.21–0.30), blinding of outcome assessors (κ = 0.27, 95% CI: 0.23–0.31); While moderate for random sequence generation (κ = 0.46, 95% CI: 0.41–0.50) and blinding of participants and personnel (κ = 0.59, 95% CI: 0.55–0.64). The findings demonstrate that there were domain‐specific differences in the level of agreement between RobotReviewer and humans. We suggest that it might be a useful auxiliary tool, but the specific manner of its integration as a complementary tool requires further discussion.
The Surgical Management of Intracranial Metastasis Secondary to Follicular Cell‐Derived Thyroid Carcinoma
Authors: Harries Victoria , Eagan Alana , Tuttle R. Michael , Shaha Ashok R. , Wong Richard J. , Shah Jatin P. , Patel Snehal G. , Brennan Cameron , Ganly Ian 
Published: September 2024

ABSTRACTBackgroundIntracranial metastases (ICM) from follicular cell‐derived thyroid carcinoma (FCDTC) are rare and are associated with a poor prognosis. The objective of this study is to report our experience in the surgical management of patients with ICM secondary to FCDTC.MethodsPatients with FCDTC who underwent surgical resection of an ICM were identified at our institution from 1998 to 2018.ResultsThirty‐two patients were included in this study. Nineteen patients (59%) had involvement of the brain parenchyma only, 8 (25%) had a dural‐based metastasis, 3 (9%) had a calvarial metastasis with dural extension, and 2 (6%) had a skull base metastasis with dural extension.In patients who had an R0‐1 resection, the estimated lesional control at the site of resection was 91% at 3 years. However, overall ICM control was 37% at 3 years due to the progression of other ICM lesions. The 1‐year disease‐specific survival (DSS) was 87% and 5‐year DSS was 37%.ConclusionsICM management in FCDTC is based on the size, number, and location of metastatic lesions. Complete resection of ICM may provide lesional control at the site of resection, however, DSS is poor due to the presence of other ICMs and metastases at multiple distant sites.
Patients' Experiences, Satisfaction and Quality of Life With Physiotherapy Follow‐Up After Total Knee Arthroplasty: A Phenomenological Qualitative Study Protocol
Authors: Shetty Saloni , Samuel Asir John 
Published: September 2024

ABSTRACTIntroductionAvailable quantitative studies indicate that patients who have undergone Total Knee Arthroplasty (TKA) experience dissatisfaction. There is a lack of comprehensive information on the experiences, satisfaction, and quality of life of patients after TKA. Hence, there is a need to explore the patients' perspective about the satisfaction and experiences undergoing rehabilitation and to explore the factors influencing quality of life with physiotherapy after 1st and 3rd months of TKA.Methods35 patients with post TKA, aged from 45 years, will participate in semi‐structured face‐to‐face or telephone interviews. The participants will be recruited using criterion‐based purposive sampling. The interviews will be audio‐recorded and transcribed. NVivo 14V software and Braun and Clarke thematic analysis will be used. Credibility, transferability, dependability, and confirmability will be ensured.ResultsThe transcribed verbatim transcript will be analysed to generate sub‐themes and themes using thematic analysis. Irrespective of the responses received from male or female patients' data would be analysed using inductive qualitative analysis to explore their perspectives.ConclusionThis study is the first qualitative study from lower‐ and middle‐income country that aims to investigate the satisfaction and experiences of patients after undergoing TKA rehabilitation. The efficacy of the data and subsequent suggestions would rely on the insights generated from the qualitative study, which would support the rehabilitation of patients in their later years.
Decoding Methane Flow in Fractured Clay: A Semi‐Analytical Model With Matrix Diffusion and Advection
Authors: Wang Qiao , Zha Fusheng , Rajabi Hamid , Xu Long , Yan Huaxiang 
Published: September 2024

ABSTRACTLandfills emissions, ranking as the third‐largest anthropogenic source of methane in the atmosphere, pose environmental challenges and threaten public health. The pivotal role of clay as a mitigating agent for methane emission within landfill cover systems cannot be overstated; however, our understanding of methane escape from fractured clay remains limited. This study aims to address the existing gaps by proposing a robust analytical model of methane transport in both fractures and clay matrix. Our investigation also includes a dimensionless analysis to govern the relative significance of diffusion and advection in methane emission from fractured clay, systematically reviewing factors such as the degree of water saturation (Sr) and fracture width. The methane concentration profiles in cracked clay demonstrated escalating sensitivity to Péclet (Pe) numbers, especially when advection dominates transport. Our findings also highlight the prevalence of preferential methane flow with increasing Sr in the clay matrix. The flux of methane emission from fractures at Sr = 0.8 was 130 times greater than that from intact clay. However, the study necessitates considering methane emission from clay matrix, particularly in dry clay conditions (Sr = 0.2 and 0.4). The accumulated methane emission flux from intact clay, more than that emitted from fractures by about 2.5 times at Sr = 0.2, was 1.3 × 10−5 g/m/s. The findings significantly advance the understanding of gas transport in fractured geomaterials, revealing the effect of water saturation and crack width on methane emissions from fractures. Overall, the outcomes emphasize the inclusion importance of methane emission from cracked clay in the design of gas barriers.
Selection of appropriate multispectral camera exposure settings and radiometric calibration methods for applications in phenotyping and precision agriculture
Authors: Swaminathan Vaishali , Thomasson J. Alex , Hardin Robert G. , Rajan Nithya , Raman Rahul 
Published: September 2024

AbstractExposure time and gain are camera‐related parameters that affect the radiometric accuracy of unmanned aerial vehicle (UAV)‐based multispectral images used in quantitative precision agriculture. This study quantified the potential radiometric errors from the conventionally used autoexposure settings and compared the agronomic implications of fixed exposure and autoexposure settings. The exposure and gain in the auto‐exposed UAV images varied scene‐to‐scene based on the reflectance range of objects on the ground. Hence, to capture multispectral images with fixed exposure, the ideal exposure ranges were determined to prevent loss of spectral detail from overexposure or underexposure of the canopy and soil. Reflectance measurements from the fixed exposure orthomosaic had a higher coefficient of determination (R2 = 0.97–0.99) and lower mean absolute percentage error (MAPE = 3.07%–5.97%) than those from autoexposure (R2 = 0.79–0.96 and MAPE = 7.42%–25.06%), indicating better radiometric uniformity and accuracy, respectively. Calibrating images with reflectance targets captured with different exposure settings resulted in MAPE < 5% for the blue, green, red, and near infrared bands and <7% for the red‐edge band when exposure settings were within the ideal ranges; outside of those ranges MAPE increased exponentially. These observations highlighted the challenges in appropriately calibrating canopy and soil reflectance values subjected to exposure setting variabilities. Finally, early‐season plant nitrogen uptake (g/m2) from 2 years was estimated somewhat better with vegetation indices derived with fixed exposure (R2 = 0.32–0.40 and MAPE = 13%–14%) than with autoexposure (R2 = 0.00–0.19 MAPE = 15%–18%).
Serum levels of prostate specific antigen, free PSA, [−2]proPSA, fPSA/tPSA ratio, Prostate Health Index, and glycosylation patterns of free PSA in patients with benign prostatic hyperplasia pharmacotherapy
Authors: Jirásko Michal , Viták Roman , Pecen Ladislav , Pinkeová Andrea , Tkáč Jan , Bertók Tomáš , Bergman Natalie , Kučera Radek 
Published: September 2024

AbstractBackgroundThe medication used to treat benign prostate hyperplasia (BPH), a common condition in men over 50 years of age, can alter the levels of biomarkers used in prostate cancer detection. Commonly used medications for BPH include alpha‐blockers, 5‐alpha reductase inhibitors (5‐ARIs), and muscarinic antagonists. We studied the impact of these drugs on total prostate‐specific antigen (tPSA), free PSA (fPSA), [−2]proPSA, fPSA/tPSA ratio, and the Prostate Health Index (PHI), as well as novel potential biomarkers in the form of glycan composition of fPSA.Patients and MethodsSerum samples were collected from 564 males with BPH, with a mean age of 68.5 years. The samples were used to measure levels of tPSA, fPSA, and [−2]proPSA. The fPSA/tPSA and PHI were then calculated. The glycan composition of fPSA was analyzed using lectin‐based glycoprofiling. Pharmacotherapy data was collected from the patients' medical records.ResultsAlpha‐blocker monotherapy was associated with higher fPSA and fPSA/tPSA ratio, and decreased PHI. Levels of tPSA were not impacted. Alpha‐blocker and 5‐ARI dual therapy was associated with reduced levels of fPSA, [−2]proPSA, and PHI. Therapy combining alpha‐blockers and antimuscarinic agents did not significantly influence biomarker levels apart from an increase in a Maackia amurensis lectin‐recognized glycan originating in fPSA.ConclusionBPH pharmacotherapy notably affects prostate cancer biomarkers. Recognizing the impact of pharmacotherapy is crucial for achieving an accurate diagnosis of prostate cancer and for planning treatment.
Impact of general anesthesia on the echocardiographic assessment of right ventricular function in pediatric patients with pulmonary arterial hypertension
Authors: Simpkin Charles T. , McElroy Billy J. , Morgan Gareth J. , Dunbar Ivy David , Burkett Dale A. , Twite Mark D. , Frank Benjamin S. 
Published: September 2024

AbstractOne of the great diagnostic challenges for children with pulmonary arterial hypertension is the need for general anesthesia (GA) to enable successful right heart catheterization. Here, for the first time, we describe how echocardiographic estimates of right ventricular function and pulmonary pressures change in pediatric patients during GA.
Genetically supported causal genes for rheumatoid arthritis: Mendelian randomization and co‐localization analyses
Authors: Niu Yuanyuan , Su Fan , Chen Simin , Wang Jingnan , Zhang Shuoyang , Li Ruiru , Kuang Yu , Liang Liuqin , Xiao Youjun , Xu Hanshi 
Published: September 2024

AbstractBackgroundRheumatoid arthritis (RA) is a globally prevalent condition that has a significant impact on morbidity and mortality rates. As a result, there is growing interest in understanding its pathogenetic mechanisms, particularly genetic susceptibility. To explore the potential genes that may cause RA, we conducted a comprehensive Mendelian randomization analysis and co‐localization based on data from large sample size genome‐wide association studies.MethodsWe used two transcriptome datasets to identify expression quantitative trait loci as the exposure and employed genome‐wide association studies data from the FinnGen study as the outcome. We then performed co‐localization analysis to confirm that the expression quantitative trait loci and RA share causal genetic variants. Furthermore, we implemented a phenome‐wide scan to identify other clinical phenotypes associated with significant causal genes.ResultsAt a Bonferroni significance level of p < 2.70 × 10−6, the Mendelian randomization analysis revealed that 20 genes increased the risk of RA, while 16 genes showed a marginally protective effect. Co‐localization analyses indicated that AP4B1, GGA2, KEAP1, PTPN22, REG4, and TRAV38‐2DV8 were associated with the risk of RA. The phenome‐wide scan demonstrated shared genetic determinants between RA and other immune‐mediated disorders, including autoimmune thyroid disease, diabetes mellitus, cardiovascular disorders, inflammatory bowel disease, and malignant tumors.ConclusionsOur study identified six risk genes (AP4B1, GGA2, KEAP1, PTPN22, REG4, and TRAV38‐2DV8) that may have a causal role in RA. These findings provide novel therapeutic targets for the treatment of RA. Further exploration is required to elucidate the underlying biological mechanisms.
Synthesis, Molecular Modeling, and Evaluation of Novel Methylated Benzene Sulfonamide Derivatives as Cholesteryl Ester Transfer Protein (CETP) Inhibitors
Authors: Khalaf Reema Abu , Abuarqoub Rand , Afaneh Marah , Habash Maha 
Published: September 2024

AbstractCardiovascular disease (CVD) is a leading cause of global mortality, with dyslipidemia being a significant modifiable risk factor. Dyslipidemia refers to all abnormalities in blood lipid levels. It plays a fundamental role in the development and progression of atherosclerosis. The reduction of low‐density lipoprotein (LDL) cholesterol has been shown to decrease cardiovascular risk. Cholesteryl ester transfer protein (CETP) plays a role in LDL metabolism, and its inhibition results in lower LDL levels. This study synthesizes and evaluates novel benzene sulfonamide derivatives as CETP inhibitors. Twenty compounds were synthesized and tested for their inhibitory activity using an in vitro bioassay. The results revealed that para‐methylated derivatives exhibited higher inhibitory activity compared to meta‐methylated derivatives, where compound 6n has an IC50 of 24.4 µM. Furthermore, electron withdrawing groups such as chlorine and nitro substitutions on the sulfanamido‐phenyl rings demonstrated superior inhibitory effects compared to electron donating groups. Positional isomerism of the substitutions also influenced inhibitory activity, with para substitutions being more effective. Nitro‐substituted compounds showed greater inhibition than chlorine‐substituted compounds, where compound 6t has an IC50 of 18.3 µM. Overall, this study provides valuable insights into the SAR of CETP inhibitors and identifies promising compounds for further investigation as potential therapeutics for CVD.
Influence of CuO Nanoparticles on the Tribological Performance of Karanja Oil (Pongamia pinnata)
Authors: Lepcha Passang Tshering , Ghosh Pranab 
Published: September 2024

AbstractThe environmental concerns associated with mineral oil lubricants have led to the exploration of vegetable oil‐based lubricants as a more sustainable and benign alternative. Nanolubricants have emerged as one of the innovative solution for producing improved friction reduction as well as better thermal and tribological performances. This research investigates the potential of karanja oil as a base lubricant, improved with copper oxide (CuO) nanoparticles as additives. Different amounts of CuO (ranging from 0.01% to 0.1% w/w) were introduced to karanja oil to form nanobiolubricants. These formulations were subsequently evaluated for their physiochemical and tribological properties, such as thermal stability by thermogravimetric analysis (TGA), kinematic viscosity, viscosity index, pour point, and anti‐wear characteristics following ASTM standards. Remarkably, even at low nanoparticle loadings, significant improvements in anti‐wear performance were observed. The study aims to elucidate the lubricating behavior of karanja oil when combined with CuO nanoparticles, revealing that these nanobiolubricants exhibit enhanced physicochemical and tribological properties, as well as improved thermal stability. These results emphasize the key role of nanoparticle concentration in optimizing the effectiveness of formulations.