bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of wear properties of CaO and MgO doped stabilized zirconia ceramics produced with different pressing methods using adaptive neuro fuzzy inference systems
Authors: Yüksek A. G. , Boyraz T. , Akkuş A. 
Published: August 2024

AbstractThe present paper describes the fabrication and wear behaviour of CaO and MgO added stabilized zirconia (ZrO2) ceramics produced by powder metallurgy method were examined and modelling with artificial neural networks was studied using the experimental data obtained. CaO/MgO added stabilized zirconia ceramics were fabricated by using a combined method of ball milling, cold pressing ‐ cold isostatic pressing and sintering. CaO and MgO in different amounts (0–8 %mole) were mixed with zirconia. These mixtures were prepared by mechanical alloying method. The green compacts were sintered at 1600 °C. The wear experimental results obtained were converted into data suitable for modelling with artificial neural networks. Wear Load, wear time, CaO and MgO data were used as artificial neural networks input variables. The amount of wear according to the pressing method was taken as the output variables of artificial neural networks. An artificial neural networks was established for the prediction of wear properties of zirconia pressed using the adaptive neuro fuzzy inference systems (ANFIS) learning technique. As a result, a high R2 value of 0.9187 for cold pressing samples and 0,9449 for cold isostatic pressing samples was achieved based on the approach of comparing the success of the model with the test data set and the result produced.
Mechanical and viscoelastic properties of dental composites reinforced with silicon dioxide nanoparticles
Authors: Verma R. , Azam M.S. , Kumar S.R. 
Published: August 2024

AbstractIn the current study, dental nanocomposite reinforced with silanized silicon dioxide nanoparticles was developed. The silicon dioxide nanoparticles were varied from 0 to 30 weight‐%. Polymer resin of bisphenol A‐glycidyl methacrylate/ triethylene glycol dimethacrylate (BisGMA/TEGDMA) was used along with camphorquinone and ethyl 4‐(dimethylamino) benzoate as polymerization initiator and accelerator respectively. The role of silicon dioxide nanoparticles in mechanical and viscoelastic properties of dental composites was evaluated. Physical properties like void content and water sorption were increased by 10 % and 25 % respectively. However, mechanical and viscoelastic properties were improved with the addition of silicon dioxide nanoparticles. Data were analyzed statistically with one‐way analysis of variance (ANOVA) and post hoc Tukey′s HSD test (α<0.05). The incorporation of 10 weight‐% of silicon dioxide nanoparticles increased the micro‐hardness by 126.1 %, compressive strength by 7.6 % and flexural strength by 28.8 %. The storage modulus was increased by 37 % and loss modulus was decreased by 1 % with the introduction of 10 weight‐% of silicon dioxide nanoparticles.
Association between MAPK and PI3K/Akt signaling pathway‐related gene polymorphisms and migraine
Authors: Wang Mingxue , Gu Yujia , Meng Shuhan , Kang Lixin , Yang Jing , Sun Degang , Liu Yuxing , Wan Ze , Shan Yi , Xue Dongjie , Su Chang , Li Shufen , RanYan  , Liu Yu , Pan Yonghui , Zhao Yashuang 
Published: August 2024

AbstractBackgroundThe causes of migraine remain unclear. Evidence suggests that the MAPK and PI3K/Akt signaling pathways play a role in migraine pathogenesis. However, studies on genetic polymorphisms in the two pathways associated with migraine are still limited.MethodsThis study included 226 migraineurs and 452 age‐ and sex‐matched nonmigraine control individuals. Genotyping of 31 Single Nucleotide Polymorphisms (SNPs) in 21 genes was performed. The relationship between migraine and gene polymorphisms was analyzed by using logistic regression. SNP–SNP interactions were examined by a generalized multifactor dimension reduction (GMDR) approach. The possible role of SNPs was evaluated with gene expression data from the GTEx database.ResultsThe RASGRP2‐rs2230414 GT genotype was associated with decreased migraine risk compared with the wild‐type GG genotype [ORadj (95% CI): 0.674(0.458–0.989)]. PIK3R1‐rs3730089 was associated with migraine in the recessive model [ORadj (95% CI): 1.446(1.004–2.083)]. The CACNA1H‐rs61734410 CT genotype was associated with migraine risk [ORadj (95% CI): 1.561(1.068–2.281)]. One significant two‐way SNP–SNP interaction was found (PRKCA rs2228945‐BDNF rs6265) (p = 0.0107). Significant eQTL and sQTL signals were observed for the SNP rs2230414.ConclusionsThis is the first study to systematically reveal significant associations between MAPK and PI3K/Akt signaling pathway‐related gene polymorphisms and migraine risk.
Automatic localization of anatomical landmarks in head cine fluoroscopy images via deep learning
Authors: Fum Wilbur KS , Md Shah Mohammad Nazri , Raja Aman Raja Rizal Azman , Abd Kadir Khairul Azmi , Leong Sum , Tan Li Kuo 
Published: August 2024

AbstractBackgroundFluoroscopy guided interventions (FGIs) pose a risk of prolonged radiation exposure; personalized patient dosimetry is necessary to improve patient safety during these procedures. However, current FGIs systems do not capture the precise exposure regions of the patient, making it challenging to perform patient‐procedure‐specific dosimetry. Thus, there is a pressing need to develop approaches to extract and use this information to enable personalized radiation dosimetry for interventional procedures.PurposeTo propose a deep learning (DL) approach for the automatic localization of 3D anatomical landmarks on randomly collimated and magnified 2D head fluoroscopy images.Materials and methodsThe model was developed with datasets comprising 800 000 pseudo 2D synthetic images (mixture of vessel‐enhanced and non‐enhancement), each with 55 annotated anatomical landmarks (two are landmarks for eye lenses), generated from 135 retrospectively collected head computed tomography (CT) volumetric data. Before training, dynamic random cropping was performed to mimic the varied field‐size collimation in FGI procedures. Gaussian‐distributed additive noise was applied to each individual image to enhance the robustness of the DL model in handling image degradation that may occur during clinical image acquisition in a clinical environment. The model was trained with 629 370 synthetic images for approximately 275 000 iterations and evaluated against a synthetic image test set and a clinical fluoroscopy test set.ResultsThe model shows good performance in estimating in‐ and out‐of‐image landmark positions and shows feasibility to instantiate the skull shape. The model successfully detected 96.4% and 92.5% 2D and 3D landmarks, respectively, within a 10 mm error on synthetic test images. It demonstrated an average of 3.6 ± 2.3 mm mean radial error and successfully detected 96.8% 2D landmarks within 10 mm error on clinical fluoroscopy images.ConclusionOur deep‐learning model successfully localizes anatomical landmarks and estimates the gross shape of skull structures from collimated 2D projection views. This method may help identify the exposure region required for patient‐specific organ dosimetry in FGIs procedures.
Biocompatible nanocomposite for scaffolds in tissue engineering: A breakthrough discovery for regenerative therapy
Authors: Praseetha P. K. , Alexander Princy , Gangadhar Lekshmi , Subburaj Saranyadevi , Kumar D. J. Mukesh , Aldawood Saad , Selvankumar T. , Vijayakumar S. 
Published: August 2024

AbstractBy promoting tissue regeneration, porous nano‐scaffolds offer improved chances for the maintenance, repair, and enhancement of damaged tissues and organ functioning. In this study, the nanosilica extract obtained from the agricultural waste, that is, rice husk after surface modification shows higher hydrophobicity in the hexamethyldisilazane and methyltrimethoxysilane‐modified nanosilica and hydrophilic nature in 3‐aminopropyl triethoxysilane‐modified nanosilica. Fourier transform infrared spectroscopy results reveal the functional groups exist in the scaffold and its surface morphology was evaluated by Field emission scanning electron microscope/energy dispersive X‐ray analysis which shows a cross‐network structure that could impart the proper cell adhesion. The presence of amorphous nanosilica in ultrapure form was confirmed using X‐ray diffraction analysis where a broad peak was obtained in the range of 15°–40°. The crystallization phase of the hybrid scaffold shows 2θ values obtained at 22.6°, 28.7°, and 40.6°. The graph thus obtained confirms that the material used is 3‐aminopropyl‐triethoxysilane‐modified silk/silica nanocomposite. The decomposition rates and temperature of the composite were analyzed using the thermogravimetry/differential thermal technique. The antibacterial activity of the hybrid scaffolds and silk and silica shows the metabolic pathways were not disrupted for both Gram‐positive and ‐negative microbes. Cell cytotoxicity analysis proved that the electrospun hybrid scaffold was nontoxic to L929 cells and promoted cell adhesion and growth. The cells were highly proliferated onto the surface layers in a regular systematic pattern thus proving that these scaffolds were suitable for bone regeneration applications. Hence these economically viable scaffolds turn to be biocompatible and are promising as a novel product for cell culture regneration realted to therapy.
Oncofertility care for children, adolescents, and young adults at risk for treatment‐related fertility loss
Authors: Talbot Lindsay , Corkum Kristine S. , McCracken Kate , Cost Nicholas G. , Aldrink Jennifer H. 
Published: August 2024

AbstractAs therapy for childhood malignancies becomes more sophisticated and survival has improved, long‐term therapy‐related sequelae have emerged. Loss of reproductive potential among childhood cancer survivors is one such concern that has become increasingly recognized among patients, families, and healthcare providers. The risk status for infertility based upon therapy received, state of current reproductive technology and outcomes, and an emphasis on adequate referral and counseling for fertility preservation options are reviewed. Contributing factors to infertility are discussed, and options for female and male preservation based upon age and pubertal status are summarized. This article highlights the current state of fertility opportunities for children and adolescents undergoing therapy for cancer. Providers caring for these young patients should be familiar with such options and should routinely initiate evaluations for eligibility of fertility preservation.
Fetal Therapy for Congenital Pulmonary Malformations: A Prospective Population‐Based National Cohort Study
Authors: Weber Mathilde , Monier Isabelle , Rahshenas Makan , Salomon Laurent J. , Sananes Nicolas , Castaigne Vanina , Houfflin‐Debarge Véronique , Jouannic Jean‐Marie , Massardier Jérôme , Tsatsaris Vassilis , Khoshnood Babak , Lelong Nathalie ,   for the MALFPULM study group, Delacourt Christophe , Benachi Alexandra 
Published: August 2024

ABSTRACTObjectiveTo assess the frequency of fetal therapy for fetuses with congenital pulmonary malformations (CPMs) and to investigate their short‐term outcomes.MethodThe study population included 435 singleton fetuses diagnosed with CPMs from a national population‐based cohort study in France in 2015–2018. Information was obtained from medical records on CPM volume ratio (CVR), signs of compression, fetal therapy and perinatal outcomes. The characteristics and outcomes of fetuses with and without fetal therapy were compared using a univariate test.ResultsTwenty six fetuses (6.0%, 95% CI: 4.1–8.6) received at least one fetal therapy including thoracoamniotic shunts only (n = 3), antenatal steroids only (n = 12), and a combination of several therapies including thoracentesis and amniodrainage, in addition to shunts and steroids (n = 11). Compared with fetuses without fetal therapy, those who did have higher CVR (1.6 ± 0.3 vs. 0.7 ± 0.04, p < 0.001) and more severe signs of compression (73.1% vs. 12.8%, p < 0.001). The proportion of live births after fetal therapy was 84.6% versus 98.5% (p < 0.001) for those without fetal therapy and the hospital mortality rate was 13.6% versus 1.0% (p = 0.004), respectively.ConclusionA small minority of fetuses with CPMs underwent fetal therapy. These patients had a lower survival compared with those who did not receive fetal therapy.Trial RegistrationNCT02352207
Monitoring yellow rust progression during spring critical wheat growth periods using multi‐temporal Sentinel‐2 imagery
Authors: Ma Huiqin , Zhang Jingcheng , Huang Wenjiang , Ruan Chao , Chen Dongmei , Zhang Hansu , Zhou Xianfeng , Gui Zhiqin 
Published: August 2024

AbstractBACKGROUNDYellow rust (Puccinia striiformis f. sp. tritici) is a devastating hazard to wheat production, which poses a serious threat to yield and food security in the main wheat‐producing areas in eastern China. It is necessary to monitor yellow rust progression during spring critical wheat growth periods to support its prediction by providing timely calibrations for disease prediction models and timely green prevention and control.RESULTSThree Sentinel‐2 images for the disease during the three wheat growth periods (jointing, heading, and filling) were acquired. Spectral, texture, and color features were all extracted for each growth period disease. Then three period‐specific feature sets were obtained. Given the differences in field disease epidemic status in the three periods, three period‐targeted monitoring models were established to map yellow rust damage progression in spring and track its spatiotemporal change. The models' performance was then validated based on the disease field truth data during the three periods (87 for the jointing period, 183 for the heading period, and 155 for the filling period). The validation results revealed that the representation of the wheat yellow rust damage progression based on our monitoring model group was realistic and credible. The overall accuracy of the healthy and diseased pixel classification monitoring model at the jointing period reached 87.4%, and the coefficient of determination (R2) of the disease index regression monitoring models at the heading and filling periods was 0.77 (heading period) and 0.76 (filling period). The model‐group‐result‐based spatiotemporal change detection of the yellow rust progression across the entire study area revealed that the area proportions conforming to the expected disease spatiotemporal development pattern during the jointing‐to‐heading period and the heading‐to‐filling period reached 98.2% and 84.4% respectively.CONCLUSIONSOur jointing, heading, and filling period‐targeted monitoring model group overcomes the limitations of most existing monitoring models only based on single‐phase remote sensing information. It performs well in revealing the wheat yellow rust spatiotemporal epidemic in spring, can timely update disease trends to optimize disease management, and provide a basis for disease prediction to timely correct model. © 2024 Society of Chemical Industry.
Total reflection x‐ray fluorescence analysis of trace elements in highly saline samples
Authors: Wiggershaus Bastian , Franke Eric , Vogt Carla 
Published: August 2024

AbstractThe reliable trace analysis of high‐purity chemicals and environmentally relevant samples is more important than ever and has led to the development of novel analytical methods. Total reflection x‐ray fluorescence (TXRF) analysis is an increasingly known method for the determination of heavy metals at low concentration levels in environmental and industrial sample systems. However, there is still a need for optimization to obtain fast and precise results, especially for highly saline samples like brines and salts used in battery production or sea water. In this study, multi‐element standard solutions containing analytes like Co, Cr, Cu, Fe, Mn, Ni, or Zn in a concentration range between 0.1 and 1 mg/L were analyzed in the matrices lithium carbonate (Li2CO3) and artificial seawater (ASW) containing 1000 mg/L Li and 24,000 mg/L NaCl, respectively, leading to matrix‐analyte ratios of up to 240,000:1. Different sample preparation methods were compared in order to achieve the highest possible repeatability (1) and signal‐to‐noise ratios (2) with the least amount of time (3). Various parameters such as sample volume, drying conditions, time, temperature and additive concentration were varied. The relative standard deviation (RSD%) was used as a measure of repeatability for three replicates per sample. For lithium carbonate, a method with a preparation time of only 2 min and a measurement time of 500 s could be developed, which allowed to obtain RSD% well below 5%, a high linearity (R2 > 0.99) and limits of detection (LOD) in the range of 30 μg/L to 60 μg/L for most elements. Seawater analysis could be optimized with respect to signal‐to‐noise ratio, whereby the Kα‐line of the internal standard (Ga) was used for evaluation and the use of a desiccator was found to yield the best results.
Falcon 7b for Software Mention Detection in Scholarly Documents
Authors: Khan AmeerAli , Ramadan Qusai , Yang Cong , Boukhers Zeyd 
Published: August 2024

AbstractThis paper aims to tackle the challenge posed by the increasing integration of software tools in research across various disciplines by investigating the application of Falcon-7b for the detection and classification of software mentions within scholarly texts. Specifically, the study focuses on solving Subtask I of the Software Mention Detection in Scholarly Publications (SOMD), which entails identifying and categorizing software mentions from academic literature. Through comprehensive experimentation, the paper explores different training strategies, including a dual-classifier approach, adaptive sampling, and weighted loss scaling, to enhance detection accuracy while overcoming the complexities of class imbalance and the nuanced syntax of scholarly writing. The findings highlight the benefits of selective labelling and adaptive sampling in improving the model’s performance. However, they also indicate that integrating multiple strategies does not necessarily result in cumulative improvements. This research offers insights into the effective application of large language models for specific tasks such as SOMD, underlining the importance of tailored approaches to address the unique challenges presented by academic text analysis.
Relations between closed string amplitudes and mixed string amplitudes at tree-level
Authors: Yuenyong Aphiwat , Srisangyingcharoen Pongwit 
Published: August 2024

Abstract
This paper investigates the relationships between closed and mixed string amplitudes at the tree level in string theory. Through the analytic continuation of complex variables, we establish a factorization of closed string amplitudes into those involving (n − 2) open strings and a single closed string. Expressions for four-, five-, and six-point amplitudes are provided, together with systematic formulations for n-point string amplitudes. The paper addresses possible correction terms arising from integration along infinite tubes during the process of Wick rotations. The implications of our findings are discussed in certain limits.
Reformvorhaben „Gelegenheits-Onkochirurgie“
Authors: Spreider Valesca , Fichtner-Feigl Stefan , Wenz Frederik , Bockelmann Dalibor 
Published: August 2024

Zusammenfassung
Hintergrund
Nach wie vor stellen Krebsleiden die zweithäufigste Todesursache in Deutschland dar. Leistungssteuerung und Spezialisierungskonzepte in der Medizin bergen Potenziale, die Versorgung und die Überlebenschancen von Patientinnen und Patienten positiv zu beeinflussen.

Ziel der Arbeit
Aus der Gesetzesinitiative im Rahmen des KHVVG resultiert aus der Perspektive des UKF eine ganze Reihe medizinstrategischer Implikationen. Diese Arbeit erläutert und diskutiert die Hintergründe, Ziele und Inhalte des Reformvorhabens „Gelegenheits-Onkochirurgie“ und gibt Perspektiven auf strategische Handlungsfelder.

Material und Methoden
Analyse und Interpretation des Entwurfs eines Gesetzes zur Verbesserung der Versorgungsqualität im Krankenhaus und zur Reform der Vergütungsstrukturen (Gesetzentwurf der Bundesregierung).

Ergebnisse
Aus Sicht des UKF sollten Krankenhäuser frühestmöglich und proaktiv Kooperationsgespräche mit benachbarten Krankenhäusern zur Gestaltung der regionalen Gesundheitsversorgung führen mit den Zielen, die lokale Allokation onkologischer Patientinnen und Patienten im Sinne einer bestmöglichen Behandlung abzubilden, den Verlust von Patienten an den betroffenen Standorten abzufedern sowie den Patientenaufwuchs bei den Einrichtungen, die weiterhin onkochirurgisch versorgen werden, vorzubereiten.

Diskussion
Das noch laufende Gesetzgebungsverfahren sowie der Umstand, dass eine belastbare Analyse der relevanten Leistungsbereiche erst im ersten Halbjahr 2025 für Krankenhäuser möglich sein wird, stellt die Einrichtungen vor besondere Herausforderungen in der strategischen Planung ihrer Aktivitäten. Die im Rahmen dieser Arbeit dargestellten Lücken im Gesetzesvorhaben sollten dringend geschlossen werden, um die Ziele des Vorhabens nicht zu konterkarieren und die im System verbleibenden Leistungserbringer bei ihren Vorbereitungen zu unterstützen.
Critical review on in silico methods for structural annotation of chemicals detected with LC/HRMS non-targeted screening
Authors: Hupatz Henrik , Rahu Ida , Wang Wei-Chieh , Peets Pilleriin , Palm Emma H. , Kruve Anneli 
Published: August 2024

AbstractNon-targeted screening with liquid chromatography coupled to high-resolution mass spectrometry (LC/HRMS) is increasingly leveraging in silico﻿ methods, including machine learning, to obtain candidate structures for structural annotation of LC/HRMS features and their further prioritization. Candidate structures are commonly retrieved based on the tandem mass spectral information either from spectral or structural databases; however, the vast majority of the detected LC/HRMS features remain unannotated, constituting what we refer to as a part of the unknown chemical space. Recently, the exploration of this chemical space has become accessible through generative models. Furthermore, the evaluation of the candidate structures benefits from the complementary empirical analytical information such as retention time, collision cross section values, and ionization type. In this critical review, we provide an overview of the current approaches for retrieving and prioritizing candidate structures. These approaches come with their own set of advantages and limitations, as we showcase in the example of structural annotation of ten known and ten unknown LC/HRMS features. We emphasize that these limitations stem from both experimental and computational considerations. Finally, we highlight three key considerations for the future development of in silico methods.
Graphical Abstract