bluuebunny/crossref_metadata_2025_split huggingface dataset:
NBS-Predict: An Easy-to-Use Toolbox for Connectome-Based Machine Learning
Authors: Serin Emin , Vaidya Nilakshi , Walter Henrik , Kruschwitz Johann D. 
Published: December 2024

AbstractNBS-Predict is a prediction-based extension of the Network-based Statistic (NBS) approach, which aims to alleviate the curse of dimensionality, lack of interpretability, and problem of generalizability when analyzing brain connectivity. NBS-Predict provides an easy and quick way to identify highly generalizable neuroimaging-based biomarkers by combining machine learning (ML) with NBS in a cross-validation structure. Compared with generic ML algorithms (e.g., support vector machines, elastic net, etc.), the results from NBS-Predict are more straightforward to interpret. Additionally, NBS-Predict does not require any expertise in programming as it comes with a well-organized graphical user interface (GUI) with a good selection of ML algorithms and additional functionalities. The toolbox also provides an interactive viewer to visualize the results. This chapter gives a practical overview of the NBS-Predict’s core concepts with regard to building and evaluating connectome-based predictive models with two real-world examples using publicly available neuroimaging data. We showed that, using resting-state functional connectomes, NBS-Predict: (i) predicted fluid intelligence scores with a prediction performance of r = 0.243; (ii) distinguished subjects’ biological sexes with an average accuracy of 65.9%, as well as identified large-scale brain networks associated with fluid intelligence and biological sex.
Normative Modeling with the Predictive Clinical Neuroscience Toolkit (PCNtoolkit)
Authors: Rutherford Saige , Marquand Andre F. 
Published: December 2024

AbstractIn this chapter, we introduce normative modeling as a tool for mapping variation across large neuroimaging datasets. We provide practical guidance to illustrate how normative models can be used to map diverse patterns of individual differences found within the large datasets used to train the models. In other words, while normative modeling is a method often applied to big datasets containing thousands of subjects, it provides single subject inference and prediction. We use an open-source Python package, Predictive Clinical Neuroscience Toolkit (PCNtoolkit) and showcase several helpful tools (including an interface that does not require coding) to run a normative modeling analysis, evaluate the model fit, and visualize the results.
Establishing a Reproducible and Sustainable Analysis Workflow
Authors: Ramduny Jivesh , Garcia Mélanie , Kelly Clare 
Published: December 2024

AbstractGetting started on any project is often the hardest thing—and when it comes to starting your career in research, just figuring out where and how to start can seem like an insurmountable challenge. This is particularly true at this moment—when there are so many programming languages, programs, and systems that are freely available to neuroimaging researchers, and even more guides, tutorials, and courses on how to use them. This chapter is intended to set you off on the right foot as you get stuck into the task of learning to work with large neuroimaging data. We will cover a number of processes, systems, and practices that you should adopt to help ensure that your work is efficient, your processing steps traceable and repeatable, your analyses and findings reproducible, and your data and processing scripts amenable to sharing and open science. While this chapter is aimed at those getting started, it will also be of use to established researchers who want to streamline their processes and maximize robustness and reproducibility of their neuroimaging analyses. Finally, this chapter is also intended to help make neuroimaging work practices and processes more environmentally sustainable by reducing demands on computational resources through better planning, efficiency, and awareness of resource use.
End-to-End Processing of M/EEG Data with BIDS, HED, and EEGLAB
Authors: Truong Dung , Robbins Kay , Delorme Arnaud , Makeig Scott 
Published: December 2024

AbstractReliable and reproducible machine-learning enabled neuroscience research requires large-scale data sharing and analysis. Essential for the effective and efficient analysis of shared datasets are standardized data and metadata organization and formatting, a well-documented, automated analysis pipeline, a comprehensive software framework, and a compute environment that can adequately support the analysis process. In this chapter, we introduce the combined Brain Imaging Data Structure (BIDS) and Hierarchical Event Descriptors (HED) frameworks and illustrate their example use through the organization and time course annotation of a publicly shared EEG (electroencephalography) dataset. We show how the open-source software EEGLAB can operate on data formatted using these standards to perform EEG analysis using a variety of techniques including group-based statistical analysis. Finally, we present a way to exploit freely available high-performance computing resources that allows the application of computationally intensive learning methods to ever larger and more diverse data collections.
Actionable Event Annotation and Analysis in fMRI: A Practical Guide to Event Handling
Authors: Denissen Monique J. M. , Richlan Fabio , Birklbauer Jürgen , Pawlik Mateusz , Ravenschlag Anna N. , Himmelstoß Nicole A. , Hutzler Florian , Robbins Kay 
Published: December 2024

AbstractMany common analysis methods for task-based functional MRI rely on detailed information about experiment design and events. Event recording and representation during cognitive experiments deserves more attention, as it forms an essential link between neuroimaging data and the cognition we wish to understand. The use of standardized data structures enables tools to directly use event-based metadata for preprocessing and analysis, allowing for more efficient processing and more standardized results. However, the complex paradigms utilized by cognitive neuroscience often have different requirements for event representation. The process of generating event files from experimental logs and to iteratively restructuring these event files is a time-intensive process. Careful planning and effective tools can reduce the burden on the researcher and create better documented and more shareable datasets. This chapter discusses event representation within the BIDS (Brain Imaging Data Structure) framework. We discuss some of the common pitfalls in event representation and introduce tools to easily transform event files to meet specific analysis requirements. We demonstrate these tools and the corresponding analysis by comparing two BIDS datasets in which participants performed a stop-signal task. We work through the required event restructuring, and use Fitlins to calculate several comparable contrasts across the two datasets.
Effect of Water-Binder Ratio, Alkali Mass Fraction and Lightweight Aggregate Size on Mechanical Properties of Alkali-Activated Concrete
Authors: Deng Peng , Niu Zhiwei , Yang Kun , Liu Yan , Zhang Xianglong 
Published: December 2024

AbstractAlkali-Activated Ceramsite Concrete (AACC), a novel green building material, is important for the reutilization of industrial waste. Although there has been considerable progress in research on AACC, further investigation is still needed on ceramsite size, early strength, etc. In this paper, 11 groups containing 198 standard cubic specimens were fabricated to investigate the effects of water-binder ratio, alkali mass fraction and ceramsite diameter on compressive strength and splitting tensile strength at different ages. And the slump constant of the mixtures was tested for different water-binder ratios and alkali mass fractions during fabrication. The results showed that the slump and strength increased with the increase of water-binder ratio. As the alkali mass fraction increased the slump decreased and then increased but the strength increased and then decreased. Therefore the proper value of alkali mass fraction was about 6%. When the diameter of ceramsite increased, the compressive strength first increased and then decreased. Thus the 5–15 mm diameter was the optimum. Splitting tensile strength always decreased with the increase of diameter of ceramsite.
Experimental Study on the Behaviour and Deformation Prediction of Underwater Deep Cement Mixing (DCM) Foundation
Authors: Huang Ruiyi , Tao Ran , Cao Zhongxin , Peng Yun 
Published: December 2024

AbstractBased on the marine project of Hong Kong Integrated Waste Management Facilities Phase 1, this paper presents the static loading test of the underwater DCM foundation, and compares the instrumentation monitoring results with the predicted results by finite element analysis. In conclusion, the predicted total DCM compression and settlement is significantly higher than the actual site-measured records. Therefore, the adopted design parameters for the DCM are appropriate and conservatively under-estimate the field strength, which satisfies the requirement as stipulated in the specification.
Analysis of Impact Resistance and Optimization of Protective Capacity for Steel Reinforced Concrete Columns
Authors: Hu Zongbo 
Published: December 2024

AbstractThrough simulated horizontal impact tests on steel-reinforced concrete column components, the dynamic response of steel-reinforced concrete columns under different impact heights, boundary conditions, and impact velocities was obtained. The results indicate that with an increase in impact energy, the peak impact force shows an upward trend. As the impact height increases, the impact force gradually decreases, with higher forces near the end. When the mass of the impacting object is 2580 kg and the minimum velocity is 4.58 m/s, the maximum residual displacement occurs in the impact zone. Based on the simulated test results, the impact failure modes of steel-reinforced concrete columns can be classified as slight damage, moderate damage, severe damage, and critical damage. A model reflecting the changes in mechanical characteristics of steel-reinforced concrete column structures was established based on the damage states and impact resistance mechanisms at each loading stage of the column components. Active and passive protective structures were proposed.
The Influence of Nonlinear Characteristics of Diagonal Rod Insulators on the Seismic Performance of Converter Valve
Authors: Zhang Lihong , Xiao Jin , Zeng Di , Lü Wei 
Published: December 2024

AbstractSeismic safety of the converter valve is crucial for the safe operation of the entire flexible DC transmission system. In order to enhance the seismic resistance of the supported converter valve, composite diagonal rod insulators were designed to be added between the support insulators, which have a nonlinear property that can only be subjected to tension but not compression. Using finite element method, modal analysis of the valve structure was first conducted to study the impact of diagonal rod insulators on the dynamic characteristics of the valve structure. Secondly, artificial seismic waves were input for dynamic time history analysis, and the differences in dynamic response between two valve structure models with nonlinear and linear characteristics of diagonal rod insulators were compared and analyzed. Finally, according to the current specification requirements, three seismic waves were input to conduct seismic safety analysis and evaluation of the valve structure with nonlinear property of diagonal rod insulators. The results indicate that the acceleration and stress response results of the nonlinear valve structure model are greater than those of the linear model, indicating that using a linear model for seismic safety evaluation is more risky. Therefore, it is necessary to consider the nonlinear characteristics of diagonal rod insulators for seismic performance analysis of valve structure.
Mean-Squared Response Sensitivity Method for Bridge Damage Detection
Authors: An Ning , Ma Rui , Dong Peng 
Published: December 2024

AbstractA new sensitivity approach for detecting bridge deterioration using the mean-squared response is proposed, in which the dynamic responses of the bridge are estimated using a vehicle-bridge dynamic interaction model. The sensitivity of the mean-squared response to bridge damage is investigated and matrices are generated by defining the stiffness variation of the bridge element as an index of damage factor. The mean-squared response sensitivity method detects local bridge damage with significantly fewer iteration times, and the identification accuracy is proportional to the number of measuring points. The mean-squared response sensitivity approach may correctly identify bridge local damage, including single-element and two-element damage.
Study on Seismic Design Method of 30-Storey Self-Centering Buckling-Restrained Brace Steel Frame Considering the Influence of High Order Vibration Modes
Authors: Wang Binlei , Tan Xiao 
Published: December 2024

AbstractA design method of 30-storey self-centering buckling-restrained brace steel frame (SCBRBF) is presented considering the effect of high order vibration modes. For SCBRBF, the equal strength principle and capability design method can be used to design from BRBF. The research shows that, for the 30-storey SCBRBF, the structure is greatly affected by the high-order vibration modes, and there is a problem of conservative design by adopting the capability design method. By considering the influence of the high vibration mode of the structure in the capacity design method, the secondary design can be carried out by reasonably changing the distribution form of the corresponding brace axial force. The structure designed by this method has a small amount of steel and the seismic resistance can still meet the requirements.
Research on the Conversion Relationship of Nuclear-TNT Blast Loading Based on a Protective Door Test Under TNT Blast Loading
Authors: Dong Shangwei , Tian Zhimin , Tian Ce , Li Jiuyi 
Published: December 2024

AbstractTo solve the technical problem of converting the nuclear blast loading to equivalent chemical blast loading, based on a certain protective door test under TNT blast loading, taking the same maximum dynamic response of the protective door as the equivalent principle, numerical simulation method, impulse equivalence method, and Duhamel integration method are carried out to obtain the peak overpressure of nuclear blast under different TNT blast, conversion function of nuclear-TNT blast loading is fitted as a consequence. The fitting results show that all three methods are reasonable and effective. In comparison, when the stand-off distance z is greater than or equal to 1.71 m/kg1/3, the Duhamel integration method is more suitable, while when z is less than 1.71 m/kg1/3, the impulse equivalence method is.
Study on the Durability of Manufactured Sand Concrete with the Change of Mix Proportion Parameters
Authors: Guo Liangyu , Ma Fushan , Zhao Binhui 
Published: December 2024

AbstractCement, aggregate, mineral admixture, concrete admixture, and mixing water were used as the main raw materials to prepare manufactured sand concrete. By adjusting the proportioning parameters of manufactured sand concrete, such as sand ratio and water-cement ratio, the influence of proportioning parameters on the durability of manufactured sand concrete was studied. Experimental results show that when the sand ratio is between 0.38 and 0.44, the mechanism of sand best workability and durability of the concrete strength, the best value for the mechanism of sand concrete, sand ratio range within the scope of the young stage of mechanism sand concrete stress is almost not affected by sand ratio increase, age stage mechanism of sand concrete stress along with the increase in sand ratio decreased significantly; The stress of natural medium sand concrete and manufactured sand concrete increases with the increase in the water-cement ratio, and the compressive strength of manufactured sand concrete is slightly higher than that of ordinary natural sand concrete. When the stone powder content is 10.5%, its filling performance is better, and the frost resistance of mechanized sand concrete can be improved by adjusting the stone powder content. When the powder volume is 158 dm3, the manufactured sand concrete has good workability and the highest durability. The increase in the water-binder ratio will lead to the aggravation of carbonization depth, serious carbonization phenomenon, and reduced durability of machined sand concrete.
Aquaphotomics study of fresh cannabis inflorescence: near infrared spectral analysis of water matrix structures
Authors: Birenboim Matan , Brikenstein Nimrod , Kenigsbuch David , Shimshoni Jakob A. 
Published: December 2024

Abstract
Aquaphotomics is an approach that describes the water–light interactions in aqueous solutions or biological systems and retrieves information about the nature of the underlying water-related interactions. We evaluated the water spectral pattern (WASP) and water matrix structure of freshly harvested cannabis inflorescence from seven different chemovars using near-infrared (NIR) spectral data coupled with chemometric models. Six activated water bands—1342, 1364, 1384, 1412, 1440, and 1462 nm, occurred consistently in all of the spectrum exploration steps as well as in the partial least squares-discriminant analysis (PLS-DA) steps. However, according to major class and chemovar aquagram values, the largest spectral variation was associated with the following bands: 1412, 1364, 1374, 1384, 1488, and 1512 nm. A strong positive correlation between 1364, 1374, and 1384 nm aquagram values and a strong negative correlation between 1412 and 1512 nm aquagram values were observed through all aquagram analysis steps. These water activated bands were found to serve as good discriminators and classifiers according to either major class or chemovar. Furthermore, significant differences in the water matrix structure of different cannabis chemovars were observed, with the highest variations associated with the presence of free water molecules, small molecule solvation shells, extent of strongly bound water, and the number of hydrogen bonds per water molecule. Minor cannabinoids and terpenes such as cannabigerolic acid and (-)-guaiol displayed relatively high correlations with these bands. The results of this study suggest that the most accurate way to explore the cannabis inflorescence water matrix spectral pattern is by chemovars and not by major classes.

Graphical Abstract
Intraprocedural 3D-vena contracta area predicts survival after transcatheter edge-to-edge repair: results from MITRA-PRO registry
Authors: Rottländer Dennis , Hausleiter Jörg , Schmitz Thomas , Bufe Alexander , Seyfarth Melchior , von Bardeleben Ralph Stephan , Beucher Harald , Ouarrak Taoufik , Schneider Steffen , Boekstegers Peter ,   the MITRA-PRO investigators
Published: December 2024

Abstract
Background
The MITRA-PRO registry revealed residual mitral regurgitation (MR) to be an important predictor of survival following transcatheter edge-to-edge repair (TEER). Intraprocedural MR assessment using 3D-Vena Contracta Area (VCA) might be a feasible tool to guide mitral TEER procedures. The study aimed to assess the impact of residual MR assessed by 3D-VCA on 1-year mortality.

Methods
823 patients with residual MR quantification using 3D-VCA in the MITRA-PRO registry, were included in this study. 1-year mortality, NYHA classification and major adverse events were assessed 1-year after mitral TEER.

Results
Patients with trace residual MR after mitral TEER were allocated to the 3D-VCA < 0.1 cm2 group (27.8%), while a 3D-VCA ≥ 0.1 < 0.3 cm2 (55.4%) was considered as mild and a 3D-VCA ≥ 0.3 cm2 (16.8%) as relevant residual MR. One-year mortality was significantly lower in patients with non-relevant residual MR (3D-VCA < 0.1 cm2: 10.5%; ≥ 0.1 < 0.3 cm2: 16.0%; ≥ 0.3: 24.8%, p = 0.003). An increasing 3D-VCA post mitral TEER was associated with a higher 1-year mortality. At a 3D-VCA of 0.07 cm2 mortality increased significantly (1-year mortality 3D-VCA post mitral TEER ≥ 0.07 cm2: 16.5% vs. < 0.07 cm2: 7.8%; p = 0.005) indicating a 3D-VCA of 0.07 cm2 to be a cut-off value for survival in daily practice.

Conclusions
Residual MR assessed by 3D-VCA after TEER is associated with 1-year mortality. Therefore, 3D-VCA is a valuable echocardiographic tool for intraprocedural MR assessment during mitral TEER and achieving a lower 3D-VCA improve patient survival. (German Clinical Trials Register: DRKS00012288).

Trial Registration Number
DRKS00012288
Impact of levetiracetam use in glioblastoma: an individual patient-level meta-analysis assessing overall survival
Authors: Vychopen Martin , Güresir Agi , Basaran Alim Emre , Güresir Erdem , Wach Johannes 
Published: December 2024

Abstract
Background
Levetiracetam (Lev), an antiepileptic drug (AED), enhances alkylating chemotherapy sensitivity in glioblastoma (GB) by inhibiting MGMT expression. This meta-analysis evaluates Lev's impact on GB treatment by analyzing overall survival of individual patient data (IPD) from published studies.

Methods
IPD was reconstructed using the R package IPDfromKM. Pooled IPD Kaplan–Meier charts of survival stratified by Lev therapy were created using the R package Survminer. One- and two-stage meta-analyses of Lev treatment regarding survival was performed.

Results
Three articles covering 825 patients were included out of 3567 screened records. Lev usage prevalence was 0.36. IPD from 590 IDH wild-type glioblastomas, with a median follow-up of 16.1 months, were utilized. Pooled data revealed median survival times of 19.2 months (95%CI: 16.4–22.0) for Lev users versus 16.5 months (95%CI: 15.2–17.8) for partial/no use (p = 0.006). One-stage meta-analysis indicated a significant association between Lev use and survival in IDH wild-type GB (HR: 1.33, 95%CI: 1.08–1.64, p = 0.007). Two-stage meta-analysis confirmed these results.

Conclusions
This meta-analysis highlights that Lev use may prolong survival in IDH wild-type GB patients. Further randomized trials are needed to confirm these findings and identify subgroups benefiting most from Lev treatment.
The preferred mix of urban and rural destinations in domestic and international travel
Authors: Hon-Snir Shlomit , Teitler-Regev Sharon 
Published: December 2024

AbstractWhile tourists usually choose a combination of urban and rural destinations for the same trip, research in tourism has focused primarily on one type of tourism. The purpose of this research is to investigate the tourist’s continuum preferences of urban and rural destinations and ascertain the influence of the tourists’ residence, experience, and characteristics on their preferences in the contexts of international and domestic travel. The study proposes a mediation model to examine the direct and indirect effects of tourist’s experience and characteristics on urban and rural preferences and to shed more light on differences obtained by sociodemographic variables. We found that most respondents prefer a combination of urban and rural destinations as opposed to just one. Our results indicate that growing up in the city influences tourists’ experiences and characteristics, which, in turn, affects their urban/rural preferences. Urban residents prefer more urban destinations and vice versa for rural residents.