bluuebunny/crossref_metadata_2025_split huggingface dataset:
Potential use of cold plasma treatment for disinfection and quality preservation of grape inoculated with Botrytis cinerea
Authors: Khalaj Ali , Ahmadi Ebrahim , Mirzaei Sohiela , Ghaemizadeh Fahiemeh 
Published: December 2023

AbstractGray mold caused by Botrytis cinerea is a serious disease of grape (Vitis vinifera) during storage. The aim of this study is to evaluate the effect of atmosphere cold plasma (a novel and nonthermal technology) on inactivation of B. cinerea and preservation of chemical, physical, and mechanical characteristics of grape inoculated with B. cinerea. Herein, different time of cold plasma (0, 10, 20, and 40 s) was firstly considered to be the main factors, besides different storage time (1, 2, 3, 4, and 5 weeks) at 4°C. According to the results, plasma treatment exhibited inhibitory effect on gray mold percentage and microbial load of B. cinerea (log CFU g−1) during postharvest storage. So, in the last week, the gray mold percentage and microbial load in the control were 100% and 3.6 log CFU g−1, and in 40‐s plasma were 4.5% and 2.53 log CFU g−1, respectively. Although the minimum infection and microbial load were observed in 40‐s plasma, better postharvest quality preservation was observed in short‐time cold plasma treatment (≤20 s). Forty‐second plasma caused fruit tissue destruction and negatively decreased mechanical indices (Emod: 0.0028, Fmax = 1.78, and W = 3.18) and weight loss (91.9) in comparison with ≤20‐s plasma, in which mechanical indices (Emod =0.0077, Fmax = 3.6, and W = 10.06) and weight loss (1/1) were higher. The long‐time cold plasma treatment (40 s) had also maximum effects on color changes (10) and surface temperature (2.8°C). Although the highest TSS and TA were observed in 40‐s Plasma, but different time of plasma treatments had no effect on pH. Altogether, these results indicate that the short‐time cold plasma treatment can inactivate B. cinerea on grape berries and preserve crop quality properties.
Calcium administration appears not to benefit acute pancreatitis patients with hypocalcemia
Authors: Yan Tianao , Ma Yifei , Wang Zheng , Lyu Jun , Wu Shuai , Zhang Chun , Wei Wanzhen , Zeng Jiahui , Ma Zhenhua , Xu Kedong 
Published: December 2023

AbstractObjectiveHypocalcemia occurs commonly among patients with acute pancreatitis (AP) in the intensive care unit (ICU). Calcium therapy could be used to correct hypocalcemia and maintain calcium levels, but its impact on the prognosis has not been demonstrated. Our study aimed to determine whether calcium therapy could benefit the multiple outcomes of AP patients with hypocalcemia.MethodsWe extracted 807 AP patients with hypocalcemia from the Beth Israel Deaconess Medical Center (MIMIC‐IV) database and performed retrospective analyses. The outcomes were in‐hospital, 28 days, ICU mortality, and the length of stay (LOS) in the hospital and ICU. We performed propensity matching (PSM) and inverse probability weighting (IPTW) to balance the baseline differences and conducted multivariate regression to investigate the impact of calcium therapy.ResultsA total of 620 patients (76.8%) received calcium treatment (calcium group) during hospitalization, while 187 patients (non‐calcium group) did not. Patients in the calcium group did not present significant survival differences between groups before and after matching. After including covariates, calcium administration had no association with patients' in‐hospital (HR: 1.03, 95% Cl: 0.47–2.27, p = .942), 28 days and ICU mortality and was significantly associated with prolonged length of stay in the hospital (effect estimate: 6.18, 95% Cl: 3.27–9.09, p < .001) and ICU (effect estimate: 1.72, 95% Cl: 0.24–3.20, p < .001). Calcium therapy could not benefit patients in subgroups with exclusive parenteral infusion, early calcium therapy (<48 h), or various degrees of hypocalcemia.ConclusionAP patients with hypocalcemia could not benefit from calcium administration, which has no association with multiple mortality and is significantly associated with prolonged LOS in the hospital and ICU.
Efficiency of different imaging methods in detecting ocular foreign bodies
Authors: Cheng Tongjie , Zhao Hongmei , Chen Qian , Wang Shenjiang , Jiang Chunhui 
Published: December 2023

AbstractBackgroundOcular foreign bodies (OFBs) are a relatively common occurrence in ocular injuries, and a severe risk factor for vision disorders. They are notoriously challenging to identify and localize precisely to allow surgical removal, even with the most recent technological advancements.PurposeTo compare the efficiency of different imaging methods in detecting and localizing OFBs.MethodsWe conducted a retrospective analysis of the medical records of patients with OFBs, detected by ultrasound biomicroscopy (UBM) and confirmed during surgery. Patients who presented to our medical center between January 2016 and January 2022 and also underwent computed tomography (CT), X ray, and/or ocular B‐scan ultrasonography (B‐scans) were selected.ResultsThis study included 134 patients with a history of ocular trauma and OFBs (mean age: 47.25 years, range: 8–78). The mean time interval from injury to UBM examination was 36.31 months (range: 0.2–120 months). Most OFBs were metallic (51.82%) or plant‐based (25.37%); 22.39% of them were located in the sclera, 26.87% in the anterior chamber, and 23.88% in the ciliary body and iris. OFBs ranged in size from 0.10 to 6.67 mm (mean: 1.15 ± 1.10 mm). B‐scans identified OFBs in 37 of the 119 patients examined (31.09%); CT in 52 of 84 patients (61.90%); and radiography in 29 of 50 patients (58.00%). Univariate and multivariate analyses determined that both CT and radiography showed low detection rates for plant‐based versus non‐plant‐based OFBs (CT: p < 0.001; radiography: p = 0.007), small particles (<1.00 mm vs. >1.00 mm; CT: p = 0.001, radiography: p = 0.024), and with eyeball wall locations (vs. intraocular; CT: p < 0.001, radiography: p = 0.021). Similarly, B‐scans were less efficient for plant‐based and eyeball wall‐located OFBs (both p = 0.001), whereas the difference based on dimensions was not significant (p = 0.118).ConclusionsCT, radiography, and B‐scans showed lower detection rates for plant‐based, small, and eyeball wall‐located OFBs. Our findings strongly suggest that UBM could be a more adequate imaging modality when such OFBs are suspected.
Deep learning‐based conditional inpainting for restoration of artifact‐affected 4D CT images
Authors: Madesta Frederic , Sentker Thilo , Gauer Tobias , Werner René 
Published: December 2023

AbstractBackground4D CT imaging is an essential component of radiotherapy of thoracic and abdominal tumors. 4D CT images are, however, often affected by artifacts that compromise treatment planning quality and image information reliability.PurposeIn this work, deep learning (DL)‐based conditional inpainting is proposed to restore anatomically correct image information of artifact‐affected areas.MethodsThe restoration approach consists of a two‐stage process: DL‐based detection of common interpolation (INT) and double structure (DS) artifacts, followed by conditional inpainting applied to the artifact areas. In this context, conditional refers to a guidance of the inpainting process by patient‐specific image data to ensure anatomically reliable results. The study is based on 65 in‐house 4D CT images of lung cancer patients (48 with only slight artifacts, 17 with pronounced artifacts) and two publicly available 4D CT data sets that serve as independent external test sets.ResultsAutomated artifact detection revealed a ROC‐AUC of 0.99 for INT and of 0.97 for DS artifacts (in‐house data). The proposed inpainting method decreased the average root mean squared error (RMSE) by 52 % (INT) and 59 % (DS) for the in‐house data. For the external test data sets, the RMSE improvement is similar (50 % and 59 %, respectively). Applied to 4D CT data with pronounced artifacts (not part of the training set), 72 % of the detectable artifacts were removed.ConclusionsThe results highlight the potential of DL‐based inpainting for restoration of artifact‐affected 4D CT data. Compared to recent 4D CT inpainting and restoration approaches, the proposed methodology illustrates the advantages of exploiting patient‐specific prior image information.
Psychological experiences of family caregivers of patients with breast cancer: Protocol for a meta‐synthesis
Authors: Zhang Qingyuan , Chen Jianfei , Fang Kui , Liu Qianqian , Zhang Pan , Bai Jinbing , Zhang Chunhua 
Published: December 2023

AbstractAimThe number of breast cancer patients is increasing, but there are insufficient sources of information for their family caregivers. The purpose of this systematic review was to elaborate the psychologically realistic experiences and corresponding needs of family members of patients with breast cancer in the course of their experience in the disease which may provide them with effective, targeted intervention strategies to improve their quality of life.DesignProtocol for a meta‐synthesis.MethodsWe will search the Chinese databases (i.e., China National Knowledge Infrastructure, VIP Database and Wanfang Database) and the English databases (i.e., PubMed, Embase, Web of Science, the Cochrane Library, CINAHL and PsycINFO). Qualitative studies from the above databases, studying the psychological experiences of family members of patients with breast cancer, will be searched comprehensively. The quality of the study will be evaluated by two reviewers independently using the Joanna Briggs Institute (JBI) critical appraisal tools for qualitative study, and any disagreements will be discussed and judged by the third reviewer. Data will be extracted using JBI standardized data extraction tool. Then, the literature will be compared and analysed, and the raw results summarized using the JBI meta‐aggregation tool. The reliability and credibility of the overall quality of the included studies will be assessed by using the JBI ConQual approach.ResultsN/A.No Patient or Public Contribution.PROSPERO registration numberREDACTED.
Plant‐based dietary patterns and genetic susceptibility to obesity in the CARTaGENE cohort
Authors: Masip Guiomar , Attar Atheer , Nielsen Daiva E. 
Published: December 2023

AbstractObjectiveThe study's objective was to examine whether adherence to three plant‐based dietary indices (PDIs) mediated or moderated genetic susceptibility to obesity.MethodsBaseline participants were 7037 adults (57% women, aged 55.6 ± 7.7 years) from the CARTaGENE cohort of Quebec adults. Two polygenic risk scores for BMI (PRS‐BMI), 92 single‐nucleotide polymorphisms and 2 million single‐nucleotide polymorphisms, and three plant‐based scores were calculated (overall, healthy, and unhealthy). Follow‐up participants were 2258 adults with data on obesity outcomes, measured 6 years later. General linear models were used to examine the relationships between PRSs and PDI scores on obesity outcomes. Causal mediation analyses were conducted to assess mediation and interaction models.ResultsThe overall‐ and healthy‐PDIs and PRSs were significantly associated with obesity outcomes. Adherence to PDIs did not mediate or moderate genetic susceptibility to obesity. Associations between PRSs and obesity outcomes were partly mediated by meat intake cross‐sectionally and whole grains intake among males both cross‐sectionally and longitudinally. Higher meat intake had a positive association with obesity outcomes, whereas higher whole grains intake had an inverse association.ConclusionsThese findings suggest that components of a plant‐based diet and a shift away from animal products, specifically meat, might be beneficial for nutrition interventions, particularly among individuals with higher genetic risk of obesity.
Effect of ionizing radiation on mechanical and damping properties of phenyl‐vinyl‐methyl‐polysiloxane elastomers cured with platinum
Authors: Esin Zühra Çınar , Şen Murat 
Published: December 2023

AbstractIn this study, phenyl‐vinyl‐methyl‐polysiloxane (PVMQ) elastomers were cured with a Pt catalyst and irradiated with different doses (0–80 kGy) using electron beams. Before irradiation studies, rheological analyses were carried out for the three different Platinum‐A (PtA)/Platinum‐B (PtB) ratios by using a Moving Die Rheometer. End of rheological and mechanical analyses 1/2 PtA/PtB ratio was chosen for irradiation studies. To examine the effect of absorbed dose on the mechanical properties of platinum‐cured PVMQ (Pt‐PVMQ) elastomers, stress–strain behavior, stress relaxation, and energy‐damping behavior at static conditions were investigated by cyclic compression analyses. The effect of absorbed dose on the stiffness, permanent deformation, and crosslink densities of Pt‐PVMQ elastomers was also examined. For the identification of the effect of irradiation on the vibration‐damping properties of Pt‐PVMQ elastomers, dynamic mechanical properties were investigated by using an elastomer testing system, and variation of transmissibility, stiffness, and tan delta values with frequency were examined. As a result of this study, the effect of ionizing radiation on the mechanical and dynamic properties of PVMQ elastomer cured with platinum catalyst has been revealed, and it has been shown that some of these properties can be altered with ionizing radiation. The results obtained in this study also showed that Pt‐PVMQ elastomers have higher damping properties than the damping behavior of Pt‐VMQ elastomers, and these Pt‐PVMQ elastomers can be defined as high damping systems.
Acoustic absorption of3Dprinted glycol‐modified polyethylene terephthalate composites with organically modified montmorillonite and short carbon fibers: Experimentation andANNbased predictive strategy
Authors: Mahesh Vinyas 
Published: December 2023

AbstractIn this article, the acoustic properties of 3D printed glycol‐modified polyethylene terephthalate (PETG) reinforced with organically modified montmorillonite (OMMT) nanoclay/short carbon fiber (SCF) nanocomposites are experimentally investigated using ASTM E1050‐08 standard. To this end, the sound absorption coefficient (SAC) of different PETG composites was calculated with the aid of two microphone impedance tube, working in the frequency range of 50–6300 Hz. The effect of different weight percentages (wt%) of OMMT nanoclay, SCFs, and 3D printing infill density on the acoustic behavior of PETG nanocomposites is studied. The experimental results reveal that higher wt% of OMMT nanoclay and SCFs has a beneficial effect on sound absorption. Further, the trend of variation of SAC is justified with morphological studies. Also, an artificial neural network (ANN) based prediction methodology to predict SAC is developed using the datasets obtained from the experimentation. Levenberg–Marquardt backward propagation algorithm with 20 neurons trains the ANN model. Using the trained ANN model, the acoustic properties of PETG/OMMT/SCF nanocomposites with different operating frequencies, infill density and wt% of reinforcements are predicted with less than 5% average error. This can be beneficial in eliminating the fabrication and experimentation costs incurred while assessing the acoustic properties of the PETG composites.HighlightsPETG/OMMT nanoclay/SCF composite filaments are fabricated.Acoustic absorption of 3D printed PETG composites are experimentally studied.ANN based predictive tool is developed using experimental data.ANN tool predicts the sound absorption and reduces experimentation cost.Microstructural studies justify the trend of sound absorption.
Ultrasmall Nanoparticles Bind to Fibrinogen and Impair Normal Clot Formation
Authors: Mina Natasha , Guido Vinicius S. , Lima André F. , Oliva Maria Luiza V. , Sousa Alioscka A. 
Published: December 2023

AbstractThe formation of a proper fibrin clot is essential during blood coagulation, as abnormal clots can predispose individuals to bleeding or thrombosis. Despite these concerns, there is currently limited understanding of the potential adverse effects of engineered nanomaterials on fibrin clot formation. This is surprising, given that fibrinogen is highly concentrated in plasma and has a large surface area, making it prone to unintended interactions with nanomaterials. In this study, the impact of ultrasmall gold nanoparticles (usGNPs) on fibrin clot formation is investigated. UsGNPs have gained significant interest in biomedical applications due to their unique physicochemical properties and favorable behavior in complex biofluids. It is found that the usGNPs interacted with fibrinogen, delayed the onset of clot formation, and became physically trapped within the forming fibrin matrix. Confocal microscopy showed that the usGNPs disrupted the normal architecture of the fibrin clot, resulting in a less dense network structure. This disruption led to larger clot pore sizes and increased clot permeability to liquid. Considering the potential health risks associated with abnormal clot formation, a detailed examination of the clot formation process should be included in the standard safety assessment of usGNPs and other nanomedicines.
Synthesis‐Kinetics of Violet‐ and Blue‐Emitting Perovskite Nanocrystals with High Brightness and Superior Stability toward Flexible Conversion Layer
Authors: Xie Cong , Zhang Xiao , Chen Hsueh Shih , Yang Ping 
Published: December 2023

AbstractThe low photoluminescence (PL) efficiency and unstable features of small blue‐emitting CsPbX3 nanocrystals (NCs) greatly limit their applications in optoelectronics field. Herein, the synergistic and post‐treatment kinetics are studied to create highly bright and anomalous stable violet (peak position of ≈408 nm) and blue (peak position of ∼ 466 nm) emitting perovskite NCs. Ligand and ion exchange mechanism are systematic studied by the evolution of absorption, PL, and fluorescence lifetime to evaluate ligand bonding, defect engineering, and non‐radiative recombination. Didodecyl dimethyl mmonium chloride (DDAC) and CuX2 post‐synergistic treatment created DDAC‐CsPbCl3‐CuCl2 and DDAC‐CsPbCl3‐CuBr2 NCs that remained the phase composition, morphology, and size of CsPbCl3 NCs. The PL efficiencies are drastically increased to 42 and 85% for violet‐ and blue‐emitting NCs, respectively. The stability test indicated that the NCs enable against various harsh conditions (e.g., ultraviolet light irradiation and heat‐treatment). The NCs retained their initial PL efficiency after 2 months under ambient conditions and UV light irradiation. These NCs also exhibited high stability after heat‐treatment at 120 °C. The emitting NCs embedded in flexible films still revealed bright PL and high stability, suggesting current results provide a new avenue for the application in the field of optoelectronics.
Addendum to consensus opinion from International Deep Endometriosis Analysis (IDEA) group: sonographic evaluation of the parametrium
Authors: Guerriero S. , Condous G. , Rolla M. , Hudelist G. , Ferrero S. , Alcazar J. L. , Ajossa S. , Bafort C. , Van Schoubroeck D. , Bourne T. , Van den Bosch T. , Singh S. S. , Abrao M. S. , Szabó G. , Testa A. C. , Di Giovanni A. , Fischerova D. , Tomassetti C. , Timmerman D. 
Published: December 2023

ABSTRACTPreoperative sonographic staging in patients with suspected parametrial endometriosis is essential to plan surgical intervention and anticipate the need for a multidisciplinary approach, and thus optimize surgical outcome. The results of a recent meta‐analysis suggest that there is a need to define more accurately the ultrasonographic criteria for parametrial involvement in endometriosis. This addendum to the International Deep Endometriosis Analysis (IDEA) consensus highlights the sonographic characteristics of the parametrium and identifies ultrasound techniques to diagnose deep endometriosis in this area. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
Similarity Forest for Time Series Classification
Authors: Górecki Tomasz , Łuczak Maciej , Piasecki Paweł 
Published: December 2023

AbstractThe idea of similarity forest comes from Sathe and Aggarwal (Similarity forests, pp 395–403, 2017, [1]) and is derived from random forest. Random forests, during already 20 years of existence, proved to be one of the most excellent methods, showing top performance across a vast array of domains, preserving simplicity, time efficiency, still being interpretable at the same time. However, its usage is limited to multidimensional data. Similarity forest does not require such representation – it is only needed to compute similarities between observations. Thus, it may be applied to data, for which multidimensional representation is not available. In this paper, we propose the implementation of similarity forest for time series classification. We investigate 2 distance measures: Euclidean and dynamic time warping (DTW) as the underlying measure for the algorithm. We compare the performance of similarity forest with 1-nearest neighbor and random forest on the UCR (University of California, Riverside) benchmark database.We show that similarity forest with DTW, taking into account mean ranks, outperforms other classifiers. The comparison is enriched with statistical analysis.
Detection of the Biliary Atresia Using Deep Convolutional Neural Networks Based on Statistical Learning Weights via Optimal Similarity and Resampling Methods
Authors: Hayashi Kuniyoshi , Hoshino Eri , Suzuki Mitsuyoshi , Nakanishi Erika , Sakai Kotomi , Obatake Masayuki 
Published: December 2023

AbstractRecently, artificial intelligence methods have been applied in several fields, and their usefulness is attracting attention. These methods are techniques that correspond to models using batch and online processes. Because of advances in computational power, as represented by parallel computing, online techniques with several tuning parameters are widely accepted and demonstrate good results. Neural networks are representative online models for prediction and discrimination. Many online methods require large training data to attain sufficient convergence. Thus, online models may not converge effectively for low and noisy training datasets. For such cases, to realize effective learning convergence in online models, we introduce statistical insights into an existing method to set the initial weights of deep convolutional neural networks. Using an optimal similarity and resampling method, we proposed an initial weight configuration approach for neural networks. For a practice example, identification of biliary atresia (a rare disease), we verified the usefulness of the proposed method by comparing existing methods that also set initial weights of neural networks.
Clustering Adolescent Female Physical Activity Levels with an Infinite Mixture Model on Random Effects
Authors: LaLonde Amy , Love Tanzy , Young Deborah R. , Wu Tongtong 
Published: December 2023

AbstractPhysical activity trajectories from the Trial of Activity in Adolescent Girls (TAAG) capture the various exercise habits over female adolescence. Previous analyses of this longitudinal data from the University of Maryland field site, examined the effect of various individual-, social-, and environmental-level factors impacting the change in physical activity levels over 14 to 23 years of age. We aimed to understand the differences in physical activity levels after controlling for these factors. Using a Bayesian linear mixed model incorporating a model-based clustering procedure for random deviations that does not specify the number of groups a priori, we find that physical activity levels are starkly different for about 5% of the study sample. These young girls are exercising on average 23 more minutes per day.