bluuebunny/crossref_metadata_2025_split huggingface dataset:
Performance of North Wall Modified Passive and Active Greenhouse Groundnuts Dryers
Authors: Shimpy  , Kumar Mahesh , Sahu Vishal , Mahesh  , Yadav Shravan , Saini Aman 
Published: November 2024

ABSTRACTAn even‐span greenhouse groundnuts dryer having a reflective north wall has been developed and tested under passive and active modes. The effects of varying sample mass (580, 880, and 1180 g) on the thermal and enviro‐economic performance indicators of the dryer have been investigated. The Nusselt number expression, embodied energy (EE), and capital cost (Cc) were used for thermal, environmental, and economic assessment of the dryer. The drying behavior of the groundnuts samples has also been estimated using the moisture ratio in drying models. Thermal indicators were observed to increase with increased sample mass and were found higher under active mode. The values of EE and Cc of the dryer under passive and active modes were 145.24 and 158.42 kWh, and INR 1257.11 and INR 2157.11, respectively. Enviro‐economic indicators were also observed to improve with increased sample mass and were comparable for both the passive and active modes. The moisture ratio for all the samples shows an excellent fit with the Midilli–Kucuk model. An average Midilli–Kucuk model has been recommended to predict the drying behavior of groundnuts in the developed greenhouse dryer.
Two golf course putting green turfgrass responses to urea nitrogen and nickel
Authors: Menchyk N. , Liu H. , Luo H. , Li Z. , Martin S. B. , Bethea F. G. , Park D. M. 
Published: November 2024

AbstractUrea is a popular foliar nitrogen (N) source in turfgrass (TG) management. Before urea can be assimilated, it must be hydrolyzed by urease, a nickel (Ni) dependent metalloenzyme, into ammonium and carbon dioxide. Due to the prevalence of urea use in TG management and the low use efficiency associated with N fertility, more research is necessary to improve efficiency of foliar applied N. Two experiments were conducted to examine N metabolism under foliar urea fertility and Ni application of two warm‐season TG species. TifEagle ultradwarf bermudagrass [Cynodon dactylon (L) Pers. × C. transvaalensis Burtt‐Davy] and Diamond zoysiagrass [Zoysia matrella (L.) Merr.] were established in solution culture containing three Ni concentrations [Control (tap water), 200, and 400 µg Ni L−1]. Urease activity and amino acid pools were increased under Ni applications, however, an overall decrease in N concentration in leaf tissue was observed over the course of the study. In the second study, TifEagle and Diamond received four Ni concentrations (Control, 400, 800, and 1600 µM supplied as NiCl2) with irrigation to replace evapotranspiration (ET) every 48 h for 6 weeks. The Control turfgrass not receiving Ni had 3 mg kg−1 Ni concentrations in leaf tissue and no toxicity symptoms. Visual toxicity symptoms and growth reductions were observed in TG receiving 400, 800, and 1600 µM Ni regimes which resulted in leaf tissue Ni concentrations of 101, 227, and 420, respectively. There was a reduction in clipping yields from Diamond and TifEagle receiving 1600 µM Ni compared to Control (24.1% and 32.5%, respectively, p < 0.0001 for both), and a significant linear relationship (p = 0.004, R2 = 0.34 and (p < 0.0001, R2 = 0.47, respectively) between Ni concentration and clipping yield. Growth and quality of Diamond and TifEagle declined as leaf tissue Ni concentration surpassed 3 mg kg−1.
1550 Nm Optical Coherence Tomography for In Vivo Deep Brain Cerebral Blood Flow Imaging
Authors: Chen Wei , Guo Xiangsen , Zhou Junxiong , Zhang Yanjun , Bao Yuerong , Wang Yongchao , Yang Fen , Tang Jianbo 
Published: November 2024

ABSTRACTEmploying longer wavelengths in optical microscopic imaging is recognized for its advantage in deep penetration. However, the 1550 nm spectrum band is often overlooked due to water's high absorption coefficient. This study investigates the feasibility of 1550 nm center wavelength‐based optical coherence tomography (OCT) for imaging the cerebral vasculature and blood flow in the mouse brain cortex. In comparison to a commercial 1310 nm OCT system, the 1550 nm OCT system exhibits greater attenuation in deeper regions while yielding similar results in blood flow imaging across the entire cortex layers. Given the widespread use of the 1550 nm wavelength band in the communication industry, the associated costs for light sources, linear cameras, and optic components are relatively lower than those of the 1310 and 1700 nm bands. Therefore, the 1550 nm band OCT could be a favorable choice for imaging deep brain cerebral hemodynamics.
Clinical Effect Analysis and Prognostic Factors of Photodynamic Therapy for Cervical Precancerous Lesions
Authors: Zhu Hong , Guo Xiangrui , Li Xu , Chang Mengran , Zhang Zhongyin , Dai Junjun 
Published: November 2024

ABSTRACTObjectiveTo evaluate the therapeutic effect of photodynamic therapy (PDT) on cervical precancerous lesions and prognostic factors.Methods173 patients diagnosed with cervical precancerous lesions and treated with PDT were included. Univariate analysis was performed on human papillomavirus (HPV) infection, patient age, number of treatments and number of medications before and after treatment, to evaluate the efficacy, adverse reactions and patient satisfaction.Results112 patients (64.5%) showed HPV clearance afrer PDT. Age ≥ 40 years was positively correlated with poor prognosis and number of treatments ≥ 6 was negatively correlated with poor prognosis. The satisfaction rate reached 94.79%, with 6 patients experiencing tolerable pain and no treatment discontinuations due to adverse reactions.ConclusionPDT is effective and safe for treating cervical precancerous lesions, with patient age and treatment frequency impacting outcomes. High patient satisfaction and tolerable adverse reactions support the application of PDT in clinical practice.
Chemical Bond Overlap Descriptors From Multiconfiguration Wavefunctions
Authors: Santos‐Jr Carlos V. , Kraka Elfi , Moura Renaldo T. 
Published: November 2024

ABSTRACTThe chemical bond is a fundamental concept in chemistry, and various models and descriptors have evolved since the advent of quantum mechanics. This study extends the overlap density and its topological descriptors (OP/TOP) to multiconfigurational wavefunctions. We discuss a comparative analysis of OP/TOP descriptors using CASSCF and DCD‐CAS(2) wavefunctions for a diverse range of molecular systems, including X–O bonds in X–OH (XH, Li, Na, H2B, H3C, H2N, HO, F) and Li–X′ (XF, Cl, and Br). Results show that OP/TOP aligns with bonding models like the quantum theory of atoms in molecules (QTAIM) and local vibrational modes theory, revealing insights such as overlap densities shifting towards the more electronegative atom in polar bonds. The Li–F dissociation profile using OP/TOP descriptors demonstrated sensitivity to ionic/neutral inversion during Li–F dissociation, highlighting their potential for elucidating complex bond phenomena and offering new avenues for understanding multiconfigurational chemical bond dynamics.
Spontaneously Immortalised Nonhuman Primate Müller Glia Cell Lines as Source to Explore Retinal Reprogramming Mechanisms for Cell Therapies
Authors: Salman Ahmed , Bolinches‐Amorós Arantxa , Storm Tina , Moralli Daniela , Bryika Paulina , Russell Angela J. , Davies Stephen G. , Barnard Alun R. , MacLaren Robert E. 
Published: November 2024

ABSTRACTCell replacement therapies for ocular diseases characterised by photoreceptors degeneration are challenging due to poor primary cell survival in culture. A stable retinal cell source to replace lost photoreceptors holds promise. Müller glia cells play a pivotal role in retinal homoeostasis by providing metabolic and structural support to retinal neurons, preventing aberrant photoreceptors migration, and facilitating safe glutamate uptake. In fish and amphibians, injured retinas regenerate due to Müller‐like glial stem cells, a phenomenon absent in the mammalian retina for unknown reasons. Research on Müller cells has been complex due to difficulties in obtaining pure cell population and their rapid de‐differentiation in culture. While various Müller glia cell lines from human and rats are described, no nonhuman primate Müller glia cell line is currently available. Here, we report spontaneously immortalised Müller glia cell lines derived from macaque neural retinas that respond to growth factors and expand indefinitely in culture. They exhibit Müller cells morphology, such as an elongated shape and cytoplasmic projections, express Müller glia markers (VIMENTIN, GLUTAMINE SYNTHASE, glutamate‐aspartate transporter, and CD44), and express stem cell markers such as PAX6 and SOX2. In the presence of factors that induce photoreceptor differentiation, these cells show a shift in gene expression patterns suggesting a state of de‐differentiation, a phenomenon known in reprogrammed mammalian Müller cells. The concept of self‐renewing retina might seem unfeasible, but not unprecedented. While vertebrate Müller glia have a regeneration potential absent in mammals, understanding the mechanisms behind reprogramming of Müller glia in mammals could unlock their potential for treating retinal degenerative diseases.
Four timing patterns of initiation of advance care planning discussions as practiced by home visiting nurses: A qualitative study
Authors: Ushikubo Mitsuko , Ishikawa Maho 
Published: November 2024

AbstractBackgroundThe purpose of this study was to explore the actual timing of the initiation of advance care planning (ACP) discussions by experienced visiting nurses for older homebound patients.MethodsSemi‐structured interviews were conducted with 12 home visit nurses, followed by a qualitative, inductive analysis.ResultsFour ACP initiation timing patterns were extracted.ConclusionsHome visit nurses used the following timing patterns differently depending on each patient's situation: “Starting when visiting nurses get to know the patients,” “Waiting for a change in the patient's medical condition,” “Waiting to begin ACP discussions until the patient and nurse are emotionally ready,” and “Starting ACP discussions in a proactive, but non‐shocking manner.”
Effects of catechins, resveratrol, silymarin components and some of their conjugates on xanthine oxidase‐catalyzed xanthine and 6‐mercaptopurine oxidation
Authors: Bencsik Tímea , Balázs Orsolya , Vida Róbert G , Zsidó Balázs Z , Hetényi Csaba , Valentová Kateřina , Poór Miklós 
Published: November 2024

AbstractBACKGROUNDOver the past two decades, the global incidence of gout has markedly increased, affecting people worldwide. Considering the side effects of xanthine oxidase (XO) inhibitor drugs (e.g. allopurinol and febuxostat) used in the treatment of hyperuricemia and gout, the potential application of phytochemicals has been widely studied. In addition, XO also takes part in the elimination of certain drugs, including 6‐mercaptopurine. In the current explorative study, we aimed to examine the potential effects of tea catechins, resveratrol, silymarin flavonolignans and some of their conjugated metabolites on XO‐catalyzed xanthine and 6‐mercaptopurine oxidation, applying in vitro assays and modeling studies.RESULTSCatechins, resveratrol and resveratrol conjugates exerted no or only weak inhibitory effects on XO. Silybin A, silybin B and isosilybin A were weak, silychristin was a moderate, while 2,3‐dehydrosilychristin was a potent inhibitor of the enzyme. Sulfate metabolites of silybin A, silybin B and isosilybin A were considerably stronger inhibitors compared to the parent flavonolignans, and the sulfation of 2,3‐dehydrosilychristin slightly increased its inhibitory potency. Silychristin was the sole flavonolignan tested, where sulfate conjugation decreased its inhibitory effect.CONCLUSION2,3‐Dehydrosilychristin seems to be a promising candidate for examining its in vivo antihyperuricemic effects, because both the parent compound and its sulfate conjugate are highly potent inhibitors of XO. © 2024 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
An improved low‐rank plus sparse unrolling network method for dynamic magnetic resonance imaging
Authors: Jiang Ming‐feng , Chen Yun‐jiang , Ruan Dong‐sheng , Yuan Zi‐han , Zhang Ju‐cheng , Xia Ling 
Published: November 2024

AbstractBackgroundRecent advances in deep learning have sparked new research interests in dynamic magnetic resonance imaging (MRI) reconstruction. However, existing deep learning‐based approaches suffer from insufficient reconstruction efficiency and accuracy due to the lack of time correlation modeling during the reconstruction procedure.PurposeInappropriate tensor processing steps and deep learning models may lead to not only a lack of modeling in the time dimension but also an increase in the overall size of the network. Therefore, this study aims to find suitable tensor processing methods and deep learning models to achieve better reconstruction results and a smaller network size.MethodsWe propose a novel unrolling network method that enhances the reconstruction quality and reduces the parameter redundancy by introducing time correlation modeling into MRI reconstruction with low‐rank core matrix and convolutional long short‐term memory (ConvLSTM) unit.ResultsWe conduct extensive experiments on AMRG Cardiac MRI dataset to evaluate our proposed approach. The results demonstrate that compared to other state‐of‐the‐art approaches, our approach achieves higher peak signal‐to‐noise ratios and structural similarity indices at different accelerator factors with significantly fewer parameters.ConclusionsThe improved reconstruction performance demonstrates that our proposed time correlation modeling is simple and effective for accelerating MRI reconstruction. We hope our approach can serve as a reference for future research in dynamic MRI reconstruction.
Lung CT‐based multi‐lesion radiomic model to differentiate between nontuberculous mycobacteria and Mycobacterium tuberculosis
Authors: Hu Yanlin , Zhong Lingshan , Liu Hongying , Ding Wenlong , Wang Li , Xing Zhiheng , Wan Liang 
Published: November 2024

AbstractBackgroundNontuberculous mycobacterial lung disease (NTM‐LD) and Mycobacterium tuberculosis lung disease (MTB‐LD) are difficult to distinguish based on conventional imaging examinations. In recent years, radiomics has been used to discriminate them. However, existing radiomic methods mainly focus on specific lesion types, and have limitations in handling the presence of multiple lesion types that vary among different patients.PurposeWe aimed to establish a radiomic model based on multiple lesion types in the patient's CT scans, and analyzed the importance of different lesion types in distinguishing the two diseases.Methods120 NTM‐LD and 120 MTB‐LD patients were retrospectively enrolled in this study and randomly split into the training (168) and testing (72) sets. A total of 1037 radiomic features were extracted separately for each lesion type. The univariate analysis, least absolute shrinkage, and selection operator were used to select the significant radiomic features. The radiomic signature score (Radscore) from each lesion type was estimated and aggregated to construct the multi‐lesion feature vector for each patient. A multi‐lesion radiomic (MLR) model was then established using the random forest classifier, which can estimate importance coefficients for different lesion types. The performances of the MLR model and single radomic models were investigated by the receiver operating characteristic curve (ROC). The impact of the predicted lesion importance was also evaluated in subjective imaging diagnosis.ResultsThe MLR model achieved an area under the curve (AUC) of 90.2% (95% CI: 86.2% 94.1%) in differentiating NTM‐LD and MTB‐LD, outperforming the models using specific lesion types following existing radiomic models by 1% to 13%. Among different lesion types, tree‐in‐bud pattern demonstrated the highest distinguishing value, followed by consolidation, nodules, and lymph node enlargement. Given the estimated lesion importance, two senior radiologists exhibited improved accuracy in diagnosis, with an increased accuracy of 8.33% and 8.34%, respectively.ConclusionsThis is the first radiomic study to use multiple lesion types to distinguish NTM‐LD and MTB‐LD. The developed MLR model performed well in differentiating the two diseases, and the lesion types with high importance exhibited the potential to assist experienced radiologists in clinical decision‐making.
Rapid in vivo EPID image prediction using a combination of analytically calculated attenuation and AI predicted scatter
Authors: Anderson Brian , Moore Lance , Bojechko Casey 
Published: November 2024

AbstractBackgroundThe electronic portal imaging device (EPID) can be used in vivo, to detect on‐treatment errors by evaluating radiation exiting a patient. To detect deviations from the planning intent, image predictions need to be modeled based on the patient's anatomy and plan information. To date in vivo transit images have been predicted using Monte Carlo (MC) algorithms. A deep learning approach can make predictions faster than MC and only requires patient information for training.PurposeTo test the feasibility and reliability of creating a deep‐learning model with patient data for predicting in vivo EPID images for IMRT treatments.MethodsIn our approach, the in vivo EPID image was separated into contributions from primary and scattered photons. A primary photon attenuation function was determined by measuring attenuation factors for various thicknesses of solid water. The scatter component of in vivo EPID images was estimated using a convolutional neural network (CNN). The CNN input was a 3‐channel image comprised of the non‐transit EPID image and ray tracing projections through a pretreatment CBCT. The predicted scatter component was added to the primary attenuation component to give the full predicted in vivo EPID image. We acquired 193 IMRT fields/images from 93 patients treated on the Varian Halcyon. Model training:validation:test dataset ratios were 133:20:40 images. Additional patient plans were delivered to anthropomorphic phantoms, yielding 75 images for further validation. We assessed model accuracy by comparing model‐calculated and measured in vivo images with a gamma comparison.ResultsComparing the model‐calculated and measured in vivo images gives a mean gamma pass rate for the training:validation:test datasets of 95.4%:94.1%:92.9% for 3%/3 mm and 98.4%:98.4%:96.8% for 5%/3 mm. For images delivered to phantom data sets the average gamma pass rate was 96.4% (3%/3 mm criteria). In all data sets, the lower passing rates of some images were due to CBCT artifacts and patient motion that occurred between the time of CBCT and treatment. ConclusionsThe developed deep‐learning‐based model can generate in vivo EPID images with a mean gamma pass rate greater than 92% (3%/3 mm criteria). This approach provides an alternative to MC prediction algorithms. Image predictions can be made in 30 ms on a standard GPU. In future work, image predictions from this model can be used to detect in vivo treatment errors and on‐treatment changes in patient anatomy, providing an additional layer of patient‐specific quality assurance.
Biodegradable PBAT/SWCNT Porous Material for Piezoresistive Sensing and Electromagnetic Interference Shielding
Authors: Jiang Ming , Zhao Haili , Chen Tao , Li Guangming 
Published: November 2024

ABSTRACTPorous biodegradable polybutylene adipate terephthalate (PBAT)‐based material, used in wearable electronics for sensing human motion, is beneficial for environmental protection. Although PBAT demonstrates good elongation at break and impact performance, specific studies on its processing, modification, and porous structure are needed. Therefore, PBAT/single‐walled carbon nanotube (SWCNT) porous material was prepared via a salt‐templating method. It was found that part of the SWCNT was embedded in the walls of the pores in the PBAT substrate, while another part was exposed on the pore surface. PBAT served as the structural framework, and SWCNT functioned mainly as the active component, especially the SWCNT exposed on the surface. This unique microstructure imparted the porous material with desirable piezoresistive properties and effective electromagnetic interference (EMI) shielding capabilities. When the material was compressed, the exposed SWCNT was forced into closer contact, increasing the number of electrical transport pathways and further enhancing conductivity. The resulting porous sensor exhibited a notable response to strain up to 100% and demonstrated high sensitivity (1.25) while maintaining robust cyclic stability after 1000 cycles. Human pulse and finger flexion were successfully recorded using the fabricated porous sensor. Moreover, the porous material displayed EMI shielding capabilities, primarily through the absorption of electromagnetic (EM) waves, a phenomenon associated with the rough surface of the pores created by the exposed SWCNT. The overall electromagnetic shielding effectiveness was around 60 dB. Given these advantages, the green biodegradable material PBAT shows significant potential for application in piezoresistive sensors and electromagnetic interference shielding with appropriate modification and preparation.
Stronger Empathy and Better Peer Relationship? One‐Year Cross‐Lagged Panel Analysis in Preschoolers
Authors: Zeng Xiao , Xiong Yao , Mo Kainian , Yang Mengyao , Xie Binglin , Yan Zhiqiang 
Published: November 2024

ABSTRACTThe development of empathy and the establishment of peer relationships significantly influence the quality of preschoolers' social lives. Past research consistently demonstrates a strong correlation between empathy and peer relationships. However, debates persist regarding causality. To provide evidence on this matter, we conducted a year‐long longitudinal study involving 160 preschoolers at T1, with 137 children (mean age = 60.99 months, SD = 3.51; 66 males) retained at T2, 1 year later. Our study employed a two‐wave design and cross‐lagged panel analysis. Data on empathy and peer relationships were collected through empathy story tasks and peer nominations. For the analysis of peer nominations, we selected three centrality measures from social network analysis: degree centrality (number of direct friendships), closeness centrality (proximity between network members), and betweenness centrality (control/mediation of information exchange). Results from the cross‐lagged panel analysis reveal that preschoolers' affective and cognitive empathy at T1 positively and significantly predict peer relationships at T2. Specifically, both forms of empathy predict degree centrality and closeness centrality. Additionally, hierarchical linear modeling indicates that, even after controlling for affective empathy, cognitive empathy significantly predicts both degree centrality and closeness centrality at T2. These findings underscore the importance of nurturing empathy, especially cognitive empathy, to enhance peer relationships among preschoolers. Consequently, educators can play a vital role in improving peer relationships by intervening in empathy development, promoting greater social interaction.