bluuebunny/crossref_metadata_2025_split huggingface dataset:
Disease control and quality of life in chronic spontaneous urticaria and recurrent angioedema are strongly linked, but not in all patients
Authors: Neisinger Sophia , Salameh Pascale , Gutsche Annika , Aulenbacher Felix , Siebenhaar Frank , Maurer Marcus 
Published: January 2025

AbstractBackgroundPatient‐reported outcome measures (PROMs) help to assess disease control and quality of life (QoL) in chronic spontaneous urticaria (CSU) and recurrent angioedema (RA). This study aimed to assess the correlation between two different concepts: disease control and QoL, using disease‐specific PROMs.MethodsWe analyzed data from 445 CSU and 330 RA patients who completed both a disease control and QoL PROM as part of the clinical routine. We included the UCT and CU‐Q2oL for CSU and AECT and AE‐QoL for RA.ResultsIn CSU and RA, disease control scores positively correlated with QoL scores (Spearman's rho correlation coefficient (CR) −0.757, −0.735; p < 0.001) with better disease control corresponding to better quality of life. However, 5.9% of CSU patients and 28% of RA patients with complete disease control had impaired QoL. In CSU, QoL was impaired in 69.2% of patients based on the CU‐Q2oL and in 62.7% of patients based on a single numeric question from the UCT, with a mismatch in 89/445 patients. In RA, QoL was impaired in 58.5% using the AE‐QoL and in 52.7% using a single numeric question from the AECT30mo, with a mismatch in 69/330 patients. Different domains of the QoL PROMs showed different degrees of influence on disease control, with “Itching/Embarrassment” showing the strongest correlation with the UCT (CR −0.804; p < 0.001) and “Functioning” with the AECT3mo (CR −0.824; p < 0.001).ConclusionAlthough most patients with controlled disease have better quality of life, unexpectedly, quality of life remains impaired in up to one‐fourth of patients with completely controlled CSU and RA. Reasons behind this should be investigated in further studies.
Astral Microtubules Are Dispensable for Pavarotti Localization During Drosophila Spermatogonial Mitoses
Authors: Riparbelli Maria Giovanna , Migliorini Massimo , Callaini Giuliano 
Published: January 2025

ABSTRACTWe analysed here the dynamic of the kinesin‐like Pavarotti (Pav) during male gametogenesis of wild‐type and Sas4 mutant flies. Pav localizes to the equatorial region and the inner central spindle of late anaphase wild‐type spermatogonia and displays a strong concentration at the midbody during late telophase. At metaphase of the first meiotic division, Pav shows widespread localization on the equatorial region of the spermatocytes. This unusual distribution restricts and enhances during anaphase where antiparallel cortical microtubules overlap. Additional Pav staining is also found in the inner central spindle where the microtubules overlap between the segregating chromosomes. At late telophase, Pav accumulates to the midbody and on a weak ring that surround the cytoplasmic bridges. Pav localizes in an equatorial discontinuous ring of Sas4 spermatogonia where the non‐centrosomal microtubules overlap, but the motor protein is absent in the interior central spindle where the inner microtubules are lacking. However, the anastral spindles properly support cell division, suggesting that astral microtubules are dispensable for Pav localization in the Sas4 spermatogonial cell cortex. This function is presumably replaced by the antiparallel cortical microtubules extending from the acentriolar polar regions. In contrast, the majority of the meiotic spindles in Sas4 mutant testes do not progress beyond late anaphase, and only a small fraction of the primary spermatocytes experienced an abnormal division with the assembly of aberrant telophase spindles. Pav accumulates around the chromatin clusters or enhanced at the plus ends of the antiparallel non‐centrosomal cortical bundles of microtubules. However, these bundles are not arranged properly in the equatorial region of the cell and cytokinesis is abnormal or fails. Therefore, the observations in Sas4 mutant testes suggest that the spermatogonial mitoses correctly occur in the absence of astral microtubules, whereas meiotic divisions fail.
Boosting the Performance of a Zero‐gap Flow Microbial Fuel Cell by Immobilized Redox Mediators
Authors: Chikin Dmitry , Petrov Mikhail , Loktionov Pavel , Pichugov Roman , Antipov Anatoly 
Published: January 2025

AbstractAlthough microbial fuel cells (MFC) could be a promising energy source, their implementation is largely limited by low performance. There are several approaches to overcome this issue. For example, MFC performance can be enhanced using redox mediators (RM) capable of transferring electrons between microorganisms and MFC electrodes. The other, quite novel approach is to use zero‐gap electrochemical cells, which minimize the distance between MFC electrodes and, therefore, its internal resistance. This work aims to investigate the compatibility of these approaches. First, a template electropolymerization of polypyrrole (PPy) on carbon felt was carried out in the presence of 2,7‐anthraquinone disulfonate (AQDS) acting as an RM. These materials were then used as the anode of a zero‐gap double chamber MFC inoculated with sediment from a natural water body and continuously fed with artificial wastewater. On the scales of 45 and 64 days, such cells exhibited power density of up to 900 mW m−2, while unmodified cells demonstrated values tens of times lower, indicating that RM appears to extensively incorporate weak electricigens from the inoculant in the MFC operation. PPy/AQDS electrodes retain electroactive properties during long‐term tests, resulting in a theoretical turnover rate of AQDS molecules up to 590.
Two‐Dimensional BiOCl Nanosheet‐Encapsulated Cu2O Octahedra: p‐n Junction Photocatalysts for Efficient Visible Light Driven CO2‐To‐CH4 Conversion
Authors: Maryama Putri Jasmitha , Wi Dae Han , Bin Azizar Ghufran Aulia , Kim Beom Jin , Hong Jong Wook 
Published: January 2025

AbstractCu2O has attracted significant attention as a potential photocatalyst for CO2 reduction. However, its practical use is limited by rapid charge recombination, insufficient catalytic sites, and poor stability. In this study, we report a facile synthesis of Cu2O@BiOCl core–shell hybrids with a well‐defined shape of Cu2O and a two‐dimensional nanosheet structure of BiOCl. The strategic selection of BiOCl nanosheet promotes charge separation efficiency via the formation of interfacial p‐n junction and provides the active site for the CO2 reduction leading to enhanced photocatalytic CO2‐to‐CH4 conversion efficiency. In addition, the core–shell hybrids also showed improved stability against photocorrosion of Cu2O. These findings highlight the potential of Cu2O@BiOCl core–shell hybrids as robust and efficient photocatalysts for sustainable fuel production.
Real‐Time Communication System Using Canonical Cortical Graph Neural Network With High‐Level Target Navigation Pigeon‐Inspired Optimization
Authors: Uthayakumar Gadyam Somasundaram , Mathivanan Prasad , Kuppan Padmanaban , Naidu Ganta Bhavani Sankara Rao 
Published: January 2025

ABSTRACTRadio‐frequency (RF) fingerprinting is an emerging technology for advanced device authentication. This work addresses the issue by improving both the algorithm and hardware to target real‐time AI processing in communication systems. Here, efficient real‐time communication system using canonical cortical graph neural network with high‐level target navigation pigeon‐inspired optimization (RCS‐CCGNN‐HTNPIO) is proposed. Initially, radio frequencies from multiple devices such as modem, TV, and mobile phone, these devices transmit RF signals, which are captured and processed via RF fingerprinting. Then, RF fingerprinting system is designed to distinguish between known signals and unknown signals. Afterwards, the canonical cortical graph neural network (CCGNN) for analyzing and identifying the specific RF fingerprint of each signal. The CCGNN evaluates the signals and categorizes them as known signal or unknown signal based on the RF fingerprint characteristics. Hence, the high‐level target navigation pigeon‐inspired optimization (HTNPIO) is used to optimize the CCGNN. The performance metrics provide a complete assessment of the system's ability to manage the demands of real‐time processing in communication networks. The RCS‐CCGNN‐HTNPIO approach attains19.21%, 26.12%, and 30.15% higher accuracy compared with existing techniques likes deep learning based multidimensional radio‐frequency fingerprinting enhancement approach for IoT device identification (DL‐RFF‐DI), embedding‐assisted attentional deep learning for real‐world RF fingerprinting of Bluetooth (ADL‐RW‐RFF), and multichannel attentive feature fusion for radio‐frequency fingerprinting (MCA‐RFF). The simulation results prove that the RCS‐CCGNN‐HTNPIO can provide a robust and adaptive solution for achieving high accuracy in next‐generation radio access networks.
Ecological Momentary Assessment for Adolescents With Anorexia Nervosa and Their Parents/Caregivers in Family‐Based Treatment
Authors: Singh Manya , Austin Amelia , Lindenbach David , Vander Steen Heidi , Habina Courtney , Marcoux‐Louie Gisele , Loeb Katharine L. , Engel Scott , Le Grange Daniel , Dimitropoulos Gina 
Published: January 2025

ABSTRACTIntroductionStudies have shown that early weight gain in family‐based treatment (FBT) predicts treatment response in adolescents with anorexia nervosa (AN); however, research examining factors associated with early weight gain in FBT is limited. This study tested the feasibility and acceptability of ecological momentary assessment (EMA) in early FBT, particularly to capture momentary data on family climate during mealtimes.MethodsUsing multiple methods, quantitative (EMA) and qualitative (interviews) data were collected in the first 4 weeks of FBT. Participants (11 families; 9 adolescents, 19 parents/caregivers) completed EMA assessments daily on the emotional climate during meals, parental strategies and confidence/agreement in renourishment. Qualitative interviews obtained technological and procedural data using EMA. Completion rates and markers of change were explored using repeated measures ANOVA. Interviews were analyzed using reflexive thematic analysis.ResultsThe EMA completion rate for all family members was 78%: 84% for adolescents, 83% for mothers, 64% for fathers. Results demonstrated changes in caregivers' use of renourishment strategies and in the emotional climate (decreased anger) at mealtimes. No changes were observed in caregiver confidence/agreement in renourishment. Qualitative analyses revealed factors interfering with and facilitating the use of EMA.DiscussionEMA is an acceptable and feasible tool for use with adolescents and their families in early FBT, particularly to capture momentary data on family climate during mealtimes. Future research is needed with larger sample sizes to examine the mechanisms of change in early FBT, and the utility of EMA as a clinical tool in FBT.
Stability Analysis Considering PLL Effects for Grid‐Following Inverter by Complex Vector Control
Authors: Tamari Yoshio , Kato Toshiji , Inoue Kaoru 
Published: January 2025

ABSTRACTThis paper analyzes the stability of a grid‐following inverter by the complex vector control in αβ domain and by the PLL synchronization control in dq domain. It is known that the frequency transfer function of the PLL may affect mutual interactions between grid and line impedances. This paper analyzes the frequency characteristics of the inverter based on the mixed‐domain control for stability by the impedance method. Considering frequency coupling effects by the PLL control, it is found that the passivity of the inverter is violated and it may become unstable for a weak grid. This result is validated by analytical derivation, simulation, and experiment.
Blood Cells Parameters in Second Trimester of Pregnancy and Gestational Diabetes Mellitus: A Systematic Review and Meta‐Analysis
Authors: Ghasemi Vida , Banaei Mojdeh , Kiani Zahra , Ramezani Tehrani Fahimeh , Saei Ghare Naz Marzieh 
Published: January 2025

ABSTRACTObjectiveGestational diabetes mellitus (GDM) is one of the most common complications during pregnancy. There is inconsistency between previous studies regarding the blood and inflammatory parameters levels among pregnant women and its association with GDM. This study aimed to investigate the relationship between blood parameters in relation to GDM.MethodsSystematic literature searches were carried out through databases like PubMed, Web of Science, Epistemonikos, Scopus, Scientific Information Database and Magiran till May 2024. The effect size of serum blood parameters levels was determined by using standard mean deviations (SMDs) and 95% confidence intervals (CIs).ResultsThirty articles were included in this study. Meta‐analysis showed that compared with the control group, women with GDM had significantly higher levels of haemoglobin (0.343 [95% CI 0.134–0.553] p = 0.01, sensitivity analysis: 0.174 [95% CI 0.0343–0.315] p = 0.01), red blood cell (0.387 [95% CI 0.224–0.550] p < 0.001), mean platelet volume (0.498 [95% CI 0.165–0.831] p = 0.003), white blood cell count (0.351 [95% CI 0.0882–0.615] p = 0.009) and neutrophil–lymphocyte ratio (0.534 [95% CI 0.127–0.941] p = 0.01). However, women with GDM had lower levels of mean corpuscular haemoglobin concentration (−0.249 [95% CI −0.386–−0.112] p < 0.001). Pooled results from MPV showed no association between adjusted MPV and GDM (adjusted OR 1.33 [95% CI 0.8–1.86] I2 = 57.2%).ConclusionsFinding supports higher levels of blood parameters (Hb, RBC, WBC, NLR and MPV) among women with GDM in the second trimester of pregnancy. Future studies should investigate the potential role of these haematological markers as predictive tools for adverse pregnancy outcomes and evaluate therapeutic interventions targeting these parameters to enhance maternal and fetal health.
Short‐Term Ensemble Insolation Forecasting Method Using Parallelized NE
Authors: Kawasaki Shoji , Ishibe Koshi 
Published: January 2025

ABSTRACTIn this paper, the authors propose an ensemble forecasting method using multiple individuals for short‐time‐ahead (1 h ahead) insolation forecasting by using neuroevolution (NE), in which a genetic algorithm is applied to the learning algorithm of a neural network for insolation. Although the method improves the accuracy compared to a single forecast, NE has a problem that the training time is long. In order to solve this problem, the authors propose a parallelization method of GPU processing for short‐time‐ahead forecasting and try to solve the problem by parallelizing the GPU.
Silver‐Nanowire/Graphene Stacked Transparent Electrodes and Its Application to Flexible Thin Film Photovoltaic Device
Authors: Akasaka Miho , Noguchi Masahiko , Kobayashi Taizo 
Published: January 2025

ABSTRACTIn this study, silver nanowire covered with graphene (AgNW/Graphene) transparent conducting electrodes (TCE) were developed as bendable TCE instead of conventionally used indium tin oxide (ITO) for flexible photovoltaic applications. CVD‐grown graphene films were transferred from a Cu foil onto a spin‐coated AgNW TCE. AgNW/Graphene TCE exhibited lower electrical resistance than 10 Ω and high optical transmission of approximately 80% at visible wavelengths before and after bending of 20 cycles at a radius of 15 mm. Thermal tolerance of AgNW was drastically improved by protecting silver nanowires with graphene from oxidation at the 300°C air annealing test. ZnMgO/Se thin film photovoltaic devices with AgNW/graphene were successfully demonstrated by insertion of a sol‐gel ZnO buffer layer in order to protect AgNW/graphene from sputtering bombardment.
Ni‐SPO‐Al Catalyzed Stereoselective C−H Alkenylation of Quinazolinones with Alkynes to Prepare Trans‐Isomers
Authors: Zhang Yaqi , Ni Qiang , Jiang Long , Cao Rihui , Qiu Liqin 
Published: January 2025

AbstractA stereoselective Ni−Al bimetal‐catalyzed C−H alkenylation of quinazolinones with alkynes has been successfully developed. Good selectivity of Z‐type quinazolinone products was obtained using readily available substrates, which exhibits a trans‐configuration opposite to the conventional alkynylation reactions and improves the diversity of quinazolinone compounds. In addition, the reaction process was further explored through KIE and other control experiments, and a possible mechanism was proposed.
Exploring glycemic variability and time in range: Emerging indicators of at‐risk pregnancy in type 2 diabetes mellitus
Authors: Khurana Vishwani , Nigam Aruna , De Arpita 
Published: January 2025

AbstractObjectiveThis study compares ambulatory glycemic profile and glycemic variability between pregnant women diagnosed with type 2 diabetes mellitus (T2DM) receiving pharmacotherapy and healthy pregnant women without diabetes and assesses their correlation with fetal outcome.MethodThis was a case–control study involving 60 pregnant women (40 with T2DM and 20 healthy controls) in the third trimester of pregnancy. A flash glucose monitor device was applied over the upper arm to obtain the ambulatory glucose profile. Various glycemic parameters were analyzed and correlated with fetal outcomes among the two groups.ResultsA total of 720 days of glucose data, comprising 69 120 data points, were analyzed. This included 46 080 glucose values from the T2DM group and 23 040 from the healthy control group. Mean glucose levels in the T2DM group were 23.75% higher compared to the controls. All measures of glycemic variability were significantly elevated in the T2DM group, including mean amplitude of glycemic excursions (MAGE) (52.85 mg/dL vs. 35.72 mg/dL, P = 0.036) and standard deviation (22.84 mg/dL vs. 14.00 mg/dL, P = 0.029). A MAGE >55 mg/dL was associated with adverse fetal outcomes, such as large‐for‐gestational‐age (LGA) infants, neonatal hypoglycemia, and stillbirth. In the T2DM group, poor outcomes were also linked to a higher time above range (TAR) (13.39% vs. 2.5%, P = 0.0001). The LGA subgroup exhibited an elevated TAR (15.2%) compared to those with normal outcomes.ConclusionPregnant women with T2DM exhibit higher glycemic variability compared to healthy pregnant women. A MAGE >55 mg/dL was associated with adverse fetal outcomes, and elevated TAR significantly influenced these outcomes.
A Cascade Model to Detect and Segment Lung Nodule Using YOLOv8 and Resnet50U‐Net
Authors: Mammeri Selma , Haouam Mohamed‐Yassine , Amroune Mohamed , Bendib Issam , Benkhelifa Elhadj 
Published: January 2025

ABSTRACTIn our research, we introduce a sophisticated “two‐stage” or cascade model designed to enhance the precision of lung nodule analysis. This innovative approach integrates two crucial processes: detection and segmentation. In the initial stage, a specialized object detection algorithm efficiently scans medical images to identify potential areas of interest, specifically focusing on lung nodules. This plays a crucial role in minimizing the segmentation area, particularly in the context of lung imaging, where the structures exhibit heterogeneity. This algorithm helps focus the segmentation process only on the relevant areas, reducing unnecessary computation and potential errors. Subsequently, the second stage employs advanced segmentation algorithms to precisely delineate the boundaries of the identified nodules, providing detailed and accurate contours. The combination of object detection and segmentation not only enhances the overall accuracy of lung cancer detection but also minimizes false positives, streamlines the workflow for radiologists, and provides a more comprehensive understanding of potential abnormalities. Additionally, it improves the efficiency and accuracy of segmentation, especially in cases where the complexity and heterogeneity of the lung structure make the segmentation task more challenging. This proposed method has been tested on the LIDC‐IDRI dataset, demonstrating favorable results in both nodule detection and segmentation steps, with 81.3% mAP and 83.54% DSC, respectively. These results serve as evidence that the proposed method effectively improves the accuracy of lung nodule detection and segmentation.
Analysing Land Use and Land Cover Dynamics (1972–2020) and Evaluating Drainage System Efficacy: A Case Study of Bangladesh Polders
Authors: Jubaed Md Arifin , Mishra Ashish , Arya D. S. , Rahman Md Mizanur 
Published: January 2025

ABSTRACTIn recent years, aquaculture has significantly expanded in tropical and subtropical developing countries. This expansion has led to substantial economic, food security, and environmental impacts. The southwestern region of the Ganges–Brahmaputra Basin faces severe waterlogging problems, largely because the expansion of shrimp farming affects local livelihoods. This study examines the consequences of land‐use changes in the polders of Bangladesh by analysing 48 years of Landsat imagery from 1972 to 2020. This highlights a significant shift from rice cultivation to shrimp farming, leading to more waterlogged areas and fewer settlements because of poor drainage, freshwater scarcity, and increased salinity. We developed a drainage model for the polders via MIKE11 software to assess the area's drainage capacity and found that the current systems are insufficient, especially for monsoon drainage. This inadequacy encouraged a shift toward shrimp farming. Our research aims to shed light on the environmental and economic challenges of the area, promoting sustainable management of water resources. The detailed insights from this study provide a framework to develop practical and united strategies to address waterlogging issues and minimize their varied impacts on the people and economy of the region.
Deep Learning Model‐Driven Channel Estimation and Equalization for Underwater Acoustic OFDM Receivers
Authors: Cui Xuerong , Zhang Chuang , Li Juan , Jiang Bin , Li Shibao , Liu Jianhang 
Published: January 2025

ABSTRACTThe performance of traditional channel estimation algorithms is seriously degraded by the complex and variable underwater acoustic (UWA) environment. In this article, we proposed a model‐driven UWA communication receiver that is based on orthogonal frequency division multiplexing (OFDM), and the model mainly consists of two parts: channel estimation and equalization. The channel estimation module uses a convolutional neural network (CNN) to extract UWA channel state features from the pre‐estimated channel frequency domain response (CFR), and then implements the equalization of the receiver based on a long short‐term memory (LSTM). The equalization module uses discrete Fourier transform (DFT) to denoise the LS channel estimation and use it to construct the pre‐equalized symbols, meanwhile, the obtained pre‐equalized symbols, the received signals, and the CFR are used as inputs, which effectively improves the generalization capability of the receiver. Experiments show that the proposed model has more accurate recovery accuracy compared with the traditional algorithm and deep learning (DL) based receiver, especially when the channel environment is mismatched, the model shows better robustness.
Recognizing complexity and taking action: Supporting adolescents' foundational literacy skills in culturally and linguistically sustaining ways
Authors: Lupo Sarah , Townsend Dianna , Knecht Rachel , Massey Dixie 
Published: January 2025

AbstractThe editors of the special issue share themes from the research about how to develop foundational literacy skills for adolescents with a culturally and linguistically sustaining lens. The authors define foundational literacy skills and share a framework for supporting learners' development of these skills with culturally and linguistically sustaining pedagogy at the center of planning and instruction.