bluuebunny/crossref_metadata_2025_split huggingface dataset:
PIVKA-II combined with alpha-fetoprotein for the diagnostic value of hepatic tumors in children: a multicenter, prospective observational study
Authors: Gao Hongxiang , Xie Chenjie , Wang Jing , Ma Ji , Liu Shijian , Xie Li , Zheng Yijie , Dong Rui , Wang Shan , Fang Yongjun , Wu Yurui , Zhang Xianwei , Lu Xianying , Li Yang , Li Weisong , Pan Qiuhui , Xu Min , Gu Song 
Published: April 2024

Abstract
Background
To investigate whether protein induced by vitamin K antagonist-II (PIVKA-II) combined with alpha-fetoprotein (AFP) can improve the diagnostic and differential diagnostic accuracy of childhood hepatic tumors.

Methods
A multi-center prospective observational study was performed at nine regional institutions around China. Children with hepatic mass (Group T) were divided into hepatoblastoma group (Group THB) and hemangioendothelioma group (Group THE), children with extrahepatic abdominal mass (Group C). Peripheral blood was collected from each patient prior to surgery or chemotherapy. The area under the curve (AUROC) was used to evaluate the diagnostic efficiency of PIVKA-II and the combined tumor markers with AFP.

Results
The mean levels of PIVKA-II and AFP were both significantly higher in Group T than Group C (p = 0.001, p < 0.001), in Group THB than Group THE (p = 0.018, p = 0.013) and in advanced HB than non-advanced HB (p = 0.001, p = 0.021). For the diagnosis of childhood hepatic tumors, AUROC of PIVKA-II (cut-off value 32.6 mAU/mL) and AFP (cut-off value 120 ng/mL) was 0.867 and 0.857. The differential diagnostic value of PIVKA-II and AFP in hepatoblastoma from hemangioendothelioma was further assessed, AUROC of PIVKA-II (cut-off value 47.1mAU/mL) and AFP (cut-off value 560 ng/mL) was 0.876 and 0.743. The combined markers showed higher AUROC (0.891, 0.895 respectively) than PIVKA-II or AFP alone.

Conclusions
The serum level of PIVKA-II was significantly higher in children with hepatic tumors, especially those with malignant tumors. The combination of PIVKA-II with AFP further increased the diagnostic performance.

Trial registration
Clinical Trials, NCT03645655. Registered 20 August 2018, https://www.clinicaltrials.gov/ct2/show/NCT03645655.
Prediction of prostate cancer aggressiveness using magnetic resonance imaging radiomics: a dual-center study
Authors: Pan Nini , Shi Liuyan , He Diliang , Zhao Jianxin , Xiong Lianqiu , Ma Lili , Li Jing , Ai Kai , Zhao Lianping , Huang Gang 
Published: April 2024

Abstract
Purpose
The Gleason score (GS) and positive needles are crucial aggressive indicators of prostate cancer (PCa). This study aimed to investigate the usefulness of magnetic resonance imaging (MRI) radiomics models in predicting GS and positive needles of systematic biopsy in PCa.

Material and Methods
A total of 218 patients with pathologically proven PCa were retrospectively recruited from 2 centers. Small-field-of-view high-resolution T2-weighted imaging and post-contrast delayed sequences were selected to extract radiomics features. Then, analysis of variance and recursive feature elimination were applied to remove redundant features. Radiomics models for predicting GS and positive needles were constructed based on MRI and various classifiers, including support vector machine, linear discriminant analysis, logistic regression (LR), and LR using the least absolute shrinkage and selection operator. The models were evaluated with the area under the curve (AUC) of the receiver-operating characteristic.

Results
The 11 features were chosen as the primary feature subset for the GS prediction, whereas the 5 features were chosen for positive needle prediction. LR was chosen as classifier to construct the radiomics models. For GS prediction, the AUC of the radiomics models was 0.811, 0.814, and 0.717 in the training, internal validation, and external validation sets, respectively. For positive needle prediction, the AUC was 0.806, 0.811, and 0.791 in the training, internal validation, and external validation sets, respectively.

Conclusions
MRI radiomics models are suitable for predicting GS and positive needles of systematic biopsy in PCa. The models can be used to identify aggressive PCa using a noninvasive, repeatable, and accurate diagnostic method.
Towards a Logical Foundation of Randomized Computation: Doctoral Thesis Abstract
Authors: Antonelli Melissa 
Published: April 2024

AbstractInteractions between logic and theoretical computer science are multiple and profound. In the last decades, they have been deeply investigated, but, surprisingly, the study of probabilistic computation was only marginally touched by such fruitful interchanges. The overall goal of my doctoral thesis was precisely that of start bridging this gap by developing logical systems corresponding to specific aspects of randomized computation and, due to them, by generalizing standard achievements to the probabilistic realm. To do so, the key ingredient is the introduction of new, measure-sensitive quantifiers associated with quantitative interpretations.
Carbamazepine Adsorption onto Giant Macroporous Silica and Adaptive Neuro-Fuzzy Inference System Modeling
Authors: Alver Alper , Yılmaz Bahar Akyüz , Bilican Behlül Koç , Baştürk Emine , Kaya Murat , Işık Mustafa 
Published: April 2024

AbstractThere is an imperative need to eliminate pharmaceutical residues from aquatic environments due to their hazardous properties, including toxicity, mutagenicity, and carcinogenicity, particularly when present in water sources. Conventional water treatment methods have proven insufficient in addressing nano-pollutants such as pharmaceutical residues. Consequently, the ongoing quest for economically viable, sustainable, and environmentally friendly removal mechanisms persists. In this particular study, we employed Giant Macroporous Silica (GMS) derived from marine sponges as a promising biosorbent. GMS exhibits commendable characteristics, including a high specific surface area, swift mass transfer capabilities, and non-discriminatory adsorption qualities. The efficacy of GMS in adsorbing carbamazepine (CBZ), a common drug residue, was scrutinized under diverse experimental conditions, including a sorbate/sorbent ratio ranging from 0.005 to 1.500 weight ratio, contact times spanning from 0 to 240 min, and initial pH values ranging from 5 to 9. Remarkably, at a concentration of 1000 µg L−1, GMS demonstrated an attractive adsorption rate (98.88%) of carbamazepine at pH 7.07, within 90 min. To enhance our understanding, we developed an ANFIS model utilizing the experimental parameters as inputs. The developed model exhibited a high correlation coefficient of 0.9944% and a root mean square error (RMSE) of 1.6693, indicating its dependability in accurately predicting the adsorption of CBZ on GMS. The results of our study highlight the efficacy of GMS in adsorbing CBZ, suggesting its considerable potential for adsorbing other pharmaceutical residues and nano-pollutants. Furthermore, we propose the possibility of developing a solid-phase extraction cartridge from GMS.
Prediction method of stalk content in strip particles after redrying of tobacco leaves
Authors: Xu Qiang , Hu Zongyu , Xue Dong , Miao Chenlin , Xiong Dangan , Zhang Yifan , Mao Wenlong , Yang Yue , Sun Jinghao , Su Xuemiao , Yin Yudong , Liang Yan , Chen Simeng , Yao Zheng 
Published: April 2024

Abstract
Four tobacco leaf modules processed by Yunnan Tobacco Redrying Co., Ltd. during the 2022 roasting season were used to investigate the method of stalk content in strip particles after redrying of tobacco leaves, effectively reducing the loss of strip particles. A total of 151 sets of experimental data were used to construct the prediction model for the stalk content in strip particles after redrying using the BP artificial neural network method, the linear regression method, and the support vector machine method. The results show that the prediction model constructed by the BP artificial neural network method has high accuracy and stability, with a relatively small absolute error of prediction (e = 0.0195%) and the root-mean-square error of interactive verification (RMSECV = 0.0227%), as well as a relatively small mean absolute error of production data validation (e = 0.0675%), while the prediction deviation ratio (RPD = 2.2435) is relatively large. Overall, the prediction model established by BP artificial neural network could provide new insight into the non-destructive detection of stalk content in strip particles of redried tobacco leaves after threshing and redrying and potentially leading to a reduction in tobacco leaf crushing by more than 112,500 kg per year.
The distributed no-idle permutation flowshop scheduling problem with due windows
Authors: Mousighichi Kasra , Avci Mualla Gonca 
Published: April 2024

AbstractThe distributed no-idle permutation flowshop scheduling problem has gained significant attention as a prominent area of research in recent years, particularly in industries where setup operations are so expensive that reactivating the machines is not cost-effective. This study addresses an extension of the distributed permutation flowshop scheduling problem with no-idle and due window constraints. The aim is to determine the job assignments to the factories and their sequences in each factory that provide the minimum total weighted earliness and tardiness (TWET) penalties considering due windows. This study is the first to formulate this problem, offering four different mathematical models, and presents a benchmark to examine different problem cases that may arise in practical applications. Furthermore, to effectively solve the diverse problem instances, two hybrid metaheuristic algorithms based on the Iterated Greedy are proposed. These metaheuristics exhibit promising capabilities, enabling the solution of problem instances involving up to 500 jobs. To assess the effectiveness of the proposed models and algorithms, extensive numerical experiments are conducted, facilitating a thorough evaluation and comparison of their performances.
Towards sustainable injection moulding using 3D printed conformal cooling channels: a comparative simulation study
Authors: Clark Rebecca , Rochman Arif , Refalo Paul , Farrugia Philip , Vella Pierre 
Published: April 2024

AbstractIn recent years, studies have proven that conformal cooling channels (CCC) in an additively manufactured mould result in a more efficient and effective injection moulding process. This can be achieved since CCCs are designed to follow the contour of the part being moulded so that the surface of the part is equidistant from the channel at all points. However, no studies were found which explored the combined effect of mould material thermal conductivity and varying cooling channel designs on the cooling performance of the mould from a sustainability point of view. Within this context, a study was carried out to explore the effect of the tool material’s thermal conductivity on the performance of various CCC designs in comparison with conventional, straight drilled cooling channels. The performance of the cooling channels was analysed from a sustainability point of view by comparing the channel performances in terms of energy consumption, financial implications, and the resulting quality of the part. The results of this study showed that the higher conductivity alloys were especially effective at reducing the cycle time and improving the energy performance of the process in the conventional cooling channel designs. These materials were also capable of reducing the overall cost of the process which was calculated in terms of material costs and electricity consumption. For the CCC designs, however, the high conductivity alloys were less effective in all aspects of this analysis, namely cooling time, energy efficiency, and overall costs. However, it is worth noting that based on the melt flow simulations, the alternative materials had little to no effect on the resulting quality of the part.
Gaussian-discrete restricted Boltzmann machine with sparse-regularized hidden layer
Authors: Yasuda Muneki , Sekimoto Kaiji 
Published: April 2024

Abstract
Overfitting is a critical concern in machine learning, particularly when the representation capabilities of learning models surpass the complexities present in the training datasets. To mitigate overfitting, curtailing the representation power of the model through suitable techniques such as regularization is necessary. In this study, a sparse-regularization method for Gaussian–Discrete restricted Boltzmann machines (GDRBMs) is considered. A GDRBM is a variant of restricted Boltzmann machines that comprises a continuous visible layer and discrete hidden layer. In the proposed model, sparse GDRBM (S-GDRBM), a sparse prior that encourages sparse representations of the hidden layer is employed. The strength of the prior (i.e., the sparse-regularization strength) can be tuned within the standard scenario of maximum likelihood learning; that is, the strength can be adaptively tuned based on the complexities of the datasets during training. We validated the proposed S-GDRBM using numerical experiments.
Green buffers near industrial plants, examples in Jefferson County TX
Authors: Haselbach Liv , Niroula Riwaz , Feizbahr Mahdi 
Published: April 2024

AbstractGreen buffers between industrial plants and residential areas have multiple purposes in mitigating air pollution and protecting the environment. This study focuses on providing information on examples of green space development by industries near residential areas in Jefferson County, Texas. One represents a full buffer where residences were totally removed, another is a partial buffer where some residences were removed in a neighborhood and the third represents vegetation of a formerly industrial facility. Additional estimates on benefits of buffer spaces with respect to a pollutant plume are also considered. The study used geospatial and property data from 1966 to 2020. The transition from a residential area to a full or partial buffers highlights possible mitigation of air pollution impacts while serving additional functions, such as boosting stormwater infiltration and improving the aesthetic attractiveness of the area. The transformation from oil tanks to forested space may display the potential for environmental remediation, but not all spaces are suitable for fully forested buffers, as safety and other limitations should be considered. With the analysis of the classic Plume Equation insights can be provided regarding the possible impact of green buffers on ground-level pollutant concentrations. The calculations for atmospheric stability classes A-F and for various stack heights provide an understanding of how different conditions may affect the pollutant concentrations. The presence of a green buffer can play a crucial role in controlling ground-level pollution concentrations and reduce a community’s perception of risk.
A New Kind of Atomic Force Microscopy Scan Control Enabled by Artificial Intelligence: Concept for Achieving Tip and Sample Safety Through Asymmetric Control
Authors: Degenhardt Johannes , Bounaim Mohammed Wassim , Deng Nan , Tutsch Rainer , Dai Gaoliang 
Published: April 2024

AbstractThis paper introduces a paradigm shift in atomic force microscope (AFM) scan control, leveraging an artificial intelligence (AI)-based controller. In contrast to conventional control methods, which either show a limited performance, such as proportional integral differential (PID) control, or which purely focus on mathematical optimality as classical optimal control approaches, our proposed AI approach redefines the objective of control for achieving practical optimality. This presented AI controller minimizes the root-mean-square control deviations in routine scans by a factor of about 4 compared to PID control in the presented setup and also showcases a distinctive asymmetric response in complex situations, prioritizing the safety of the AFM tip and sample instead of the lowest possible control deviations. The development and testing of the AI control concept are performed on simulated AFM scans, demonstrating its huge potential.
Kindergynäkologische Notfälle
Authors: Semrl Neli 
Published: April 2024

ZusammenfassungMädchen mit akuten Beschwerden suchen häufig medizinische Hilfe außerhalb von kinder- und jugendärztlichen Sprechstunden. Aufgrund der begrenzten Berührungspunkte der Facharztausbildung mit der Kindergynäkologie stellen solche Situationen oft eine Herausforderung dar. Ziel dieses Artikels ist es, eine kindergynäkologische Untersuchung näher zu erläutern und häufige Vorstellungsgründe, wie präpubertäre vaginale Blutungen, Vulvovaginitiden und gynäkologische Ursachen akuter Bauchschmerzen, zu beschreiben.
Applications of knot theory to the detection of heteroclinic connections between quasi-periodic orbits
Authors: Owen Danny , Baresi Nicola 
Published: April 2024

AbstractHeteroclinic connections represent unique opportunities for spacecraft to transfer between isoenergetic libration point orbits for zero deterministic ΔV expenditure. However, methods of detecting them can be limited, typically relying on human-in-the-loop or computationally intensive processes. In this paper we present a rapid and fully systematic method of detecting heteroclinic connections between quasi-periodic invariant tori by exploiting topological invariants found in knot theory. The approach is applied to the Earth–Moon, Sun–Earth, and Jupiter–Ganymede circular restricted three-body problems to demonstrate the robustness of this method in detecting heteroclinic connections between various quasi-periodic orbit families in restricted astrodynamical problems.
Basic Characteristics and Vibration-Serviceability-Related Properties of Recent Footbridges in China
Authors: Gong Ming , Shen Ruili , Song Shubao , Wei Xinxin 
Published: April 2024

Abstract
Purpose
This study identifies basic characteristics and vibration-serviceability-related properties of recent footbridges in China. Also, it characterizes relations between vibration-serviceability-related properties and basic characteristics.

Methods
A database is constructed for recent footbridges in China based on systematic literature survey. For each footbridge, it collects basic information (name, function, province, location, service year), structural information (girder cross-section type, main span length, width, bridge type, girder material, deck material, first lateral and vertical natural frequencies, first lateral and vertical damping ratios), response information (crowd density, acceleration responses, mitigation measures), etc.

Results
Data analysis shows natural frequencies decrease with increasing bridge span. Estimation relations are proposed to quantitatively express fundamental natural frequencies and main spans in vertical and lateral directions. Damping ratios vary from 0.0015 to 0.0325, indicating the low damping capacity of the footbridges. Footbridges with non-solid cross-section are more vulnerable to human-induced excitations. Most footbridges apply mitigation measures, with mitigation efficiency from 18% to 70%.

Conclusion
This study provides designers with first judgements on feasibility of footbridges’ design scheme, for instance, a first estimation of natural frequency. Also, the reported information may guide them towards right directions of better design scheme, for example, by adjusting structural information.
Effect mechanism of phosphorous-containing additives on carbon structure evolution and biochar stability enhancement
Authors: Yang Haiping , Yu Yamian , Zhang Han , Wang Wanwan , Zhu Jinjiao , Chen Yingquan , Zhang Shihong , Chen Hanping 
Published: April 2024

AbstractThe regulation of the pyrolysis process is a key step in increasing the carbon sequestration capacity of biochar. The effect of K3PO4 addition on the yield, chemical composition, characteristic functional groups, macromolecular skeleton, graphite crystallites, and stability of biochar was studied in this paper using two-dimensional infrared correlation spectroscopy (2D-PCIS), X-ray photoelectron spectroscopy, Raman spectrum, and other characterization methods combined with thermal/chemical oxidation analysis. It is discovered that adding K3PO4 may effectively minimize the graphitization temperature range and increase biochar's yield, aromaticity, H/C ratio, and proportion of refractory/recalcitrant organic carbon. The 2D-PCIS and Raman analysis revealed that K3PO4 mostly promoted the dehydrogenation and polycondensation process of the aromatic rings in the char precursor, transforming the amorphous carbon structure of biochar into an ordered turbostratic microcrystalline structure. K3PO4 enhanced biochar stability mostly at medium-high temperatures (350 ~ 750℃) by stimulating the transformation of unstable structures of biochar to stable carbon-containing structures or by inhibiting the interaction of its active sites with oxidants through the mineralization process. A 20% phosphorus addition increased biochar's refractory index (R50) by roughly 11%, and it also boosted biochar's oxidation resistance (H2O2 or K2CrO4) efficiency, reducing carbon oxidation loss by up to 7.31%. However, at higher temperatures (> 750 ℃), the doping of phosphorus atoms into the carbon skeleton degraded the biochar structure's stability. The results of this study suggest that using exogenous phosphorus-containing additives is an efficient way to improve the stability of biochar.
Graphical abstract
Influence of grain boundary plane distribution on ionic conductivity in yttria-stabilized zirconia sintered at elevated temperatures
Authors: Faryna Marek , Adamczyk-Habrajska Małgorzata , Lubszczyk Marta 
Published: April 2024

AbstractThe paper investigates electrical properties of fully stabilized zirconia, which is widely applied as a solid electrolyte in electrochemical devices such as solid oxide fuel cells. High ionic conductivity of these materials is crucial for effective operating of the devices; however, grain boundary resistivity limits conductivity in polycrystalline ceramics. Thus, optimisation of the microstructure of zirconia is necessary from an application point of view. Based on three-dimensional electron backscatter diffraction (3D EBSD) data, the research employed a complex impedance spectroscopy to establish a correlation between microstructure of cubic zirconia sinters and their conductivity. Samples with different levels of anisotropy in grain boundary plane parameters were investigated. The obtained results indicate that the conduction of ions through the grain boundaries is higher in the sample with the higher representation of the near-(001) grain boundaries. Such a relationship suggests that an over-representation of low-energy grain boundaries in zirconia polycrystals leads to an increase of ionic conductivity.