bluuebunny/crossref_metadata_2025_split huggingface dataset:
Which Meditation Technique for Whom? An Experimental Single-Case Study Comparing Concentrative, Humming, Observing-Thoughts, and Walking Meditation
Authors: Matko Karin , Sedlmeier Peter 
Published: November 2023

Abstract
Objectives
Meditation encompasses a variety of techniques, but little is known on how and for whom they work. This study explored potential mechanisms of four different meditation techniques in beginners and which technique might be suited for whom.

Method
Using an experimental single-case design, we compared the longitudinal effects of concentrative, humming, observing-thoughts, and walking meditation. Forty-four healthy participants without meditation experience were randomly assigned to one of the four techniques and 42 completed the treatment. Following a baseline period of 2 to 4 weeks, participants learned and practiced their technique 20 min daily for 6 to 8 weeks and completed daily online questionnaires throughout the entire study period. At pretest, we assessed participants’ motivation and personality. We analyzed the data visually and by conducting single-case meta-analyses, correlation, and multivariate analyses.

Results
Body awareness, decentering, and emotion regulation improved reliably and continuously over time, for all four techniques. Thus, these processes could represent common mechanisms for novice meditators. Walking meditation led to the smallest improvements in decentering and mind-wandering, but the highest in body awareness and emotion regulation. Individuals varied in response to the treatment. The two “classic” techniques (concentration, observing-thoughts) led to more consistently positive multivariate response patterns and to better responses in participants high in neuroticism. In contrast, those high in extraversion benefitted more from the two unusual ones (humming, walking). We additionally observed interesting interactions with different motivational reasons.

Conclusions
With this study, we hope to contribute to theory building and answering two urgent questions—what the key mechanisms of meditation are and who benefits most from what kind of practice.
Pan-cancer analyses of senescence-related genes in extracellular matrix characterization in cancer
Authors: Yan Bo , Liao Pan , Shi Liqiu , Lei Ping 
Published: November 2023

Abstract
Purpose
The aged microenvironment plays a crucial role in tumor onset and progression. However, it remains unclear whether and how the aging of the extracellular matrix (ECM) influences cancer onset and progression. Furthermore, the mechanisms and implications of extracellular matrix senescence-related genes (ECM-SRGs) in pan-cancer have not been investigated.

Methods
We collected profiling data from over 10,000 individuals, covering 33 cancer types, 750 small molecule drugs, and 24 immune cell types, for a thorough and systematic analysis of ECM-SRGs in cancer.

Results
We observed a significant correlation between immune cell infiltrates and Gene Set Variation Analysis enrichment scores of ECM-SRGs in 33 cancer types. Moreover, our results revealed significant differences in immune cell infiltration among patients with copy number variations (CNV) and single nucleotide variations (SNV) in ECM-SRGs across various malignancies. Aberrant hypomethylation led to increased ECM-SRGs expression, and in specific malignancies, a connection between ECM-SRGs hypomethylation and adverse patient survival was established. The frequency of CNV and SNV in ECM-SRGs was elevated. We observed a positive correlation between CNV, SNV, and ECM-SRGs expression. Furthermore, a correlation was found between the high frequency of CNV and SNV in ECM-SRGs and poor patient survival in several cancer types. Additionally, the results demonstrated that ECM-SRGs expression could serve as a predictor of patient survival in diverse cancers. Pathway analysis unveiled the role of ECM-SRGs in activating EMT, apoptosis, and the RAS/MAPK signaling pathway while suppressing the cell cycle, hormone AR, and the response to DNA damage signaling pathway. Finally, we conducted searches in the “Genomics of Drug Sensitivity in Cancer” and “Genomics of Therapeutics Response Portal” databases, identifying several drugs that target ECM-SRGs.

Conclusions
We conducted a comprehensive evaluation of the genomes and immunogenomics of ECM-SRGs, along with their clinical features in 33 solid tumors. This may provide insights into the relationship between ECM-SRGs and tumorigenesis. Consequently, targeting these ECM-SRGs holds promise as a clinical approach for cancer treatment.
Practices of Knowledge Exchange in the Context of the COVID-19 Pandemic
Authors: Peschke Lutz , Gyftopoulos Sotirios , Kapusuzoğlu Ayhan , Folkvord Frans , Gümüş Ağca Yasemin , Kaldoudi Eleni , Drosatos George , Ceylan Nildağ Başak , Pecchia Leandro , Güneş Peschke Seldağ 
Published: November 2023

AbstractThis paper contributes to a better understanding of a system of pandemic knowledge exchanges. Therefore, three different case studies conducted in Germany, Greece, and Turkiye and executed in multiple countries were analyzed in the context of Mode 3 knowledge production and the Quintuple Helix system. While the Quintuple Helix system describes the knowledge exchange processes between the systems of science, economy, politics, public, and natural environment of societies for sustainable innovation processes, Mode 3 emphasizes the importance of a creative environment for research and innovation. The COVID-19 pandemic revealed that the need for knowledge exchange with the media-based public increased dramatically. In both models, Mode 3 and the Quintuple Helix but also in the Design Thinking approach, the creative environment incorporates the knowledge of the media-based public. Nonetheless, the reality of the public is constructed as media reality. Therefore, a mix of evidence-based and opinion-based knowledge is produced and transferred during knowledge exchange in the context of innovation processes including public engagement. It could be understood that the mediating entities media and general practitioners have a similar double function in the context of knowledge exchange with the public during the pandemic times. The results reveal the big need for knowledge communication and exchange platforms which on the one hand strengthen citizen participation by transforming opinion-based into evidence-based content. On the other hand, reach the status of a global standard medium for the pandemic knowledge exchange accepted by all stakeholders of the Quintuple Helix. This generates a shared-knowledge environment with a gain for all systems of the Quintuple Helix during the sustainable innovation processes.
Guided Play Supporting Immigrant Children’s Participation and Bilingual Development in Preschools
Authors: Cekaite Asta , Simonsson Maria 
Published: November 2023

AbstractIn recent decades, refugee immigration has had significant impact on educational contexts in Sweden, with preschools the primary arenas for young children’s language learning experiences. The present study examines second language and literacy training practices for immigrant children (aged 1–5) in preschools in Sweden. The empirical data consist of video recordings of teacher-guided play activities. These were designed to create rich linguistic and cultural environments facilitating active and democratic participation by the children. Guided play activities were developed in close collaboration between teachers and researchers during action-based interventions that were aimed at constructing child-oriented participatory language learning practices in ethnically and linguistically diverse ECEC settings. The children’s first languages were Tigrinya, Arabic dialects, Somalian, Kurdish dialects, Russian, Spanish and Swedish. The participatory learning potential of guided play was collaboratively analyzed and assessed, and new and revised activities were implemented, based on the goals of inclusivity and children’s active engagement in play and language learning. The analysis shows that teachers’ use of multimodal semiotic means, such as questions, texts and cultural artifacts (stories, material story-related objects, play spaces) were important strategies for the preparation of appealing play environments and activities that contributed to children’s curiosity and participation. These resources served as affordances for guided play, allowing the simultaneous scaffolding of children’s play competencies and their language learning.
On the Material Constitutive Behavior of the Aortic Root in Patients with Transcatheter Aortic Valve Implantation
Authors: Catalano Chiara , Turgut Tahir , Zahalka Omar , Götzen Nils , Cannata Stefano , Gentile Giovanni , Agnese Valentina , Gandolfo Caterina , Pasta Salvatore 
Published: November 2023

Abstract
Background
Transcatheter aortic valve implantation (TAVI) is a minimally invasive procedure used to treat patients with severe aortic valve stenosis. However, there is limited knowledge on the material properties of the aortic root in TAVI patients, and this can impact the credibility of computer simulations. This study aimed to develop a non-invasive inverse approach for estimating reliable material constituents for the aortic root and calcified valve leaflets in patients undergoing TAVI.

Methods
The identification of material parameters is based on the simultaneous minimization of two cost functions, which define the difference between model predictions and cardiac-gated CT measurements of the aortic wall and valve orifice area. Validation of the inverse analysis output was performed comparing the numerical predictions with actual CT shapes and post-TAVI measures of implanted device diameter.

Results
A good agreement of the peak systolic shape of the aortic wall was found between simulations and imaging, with similarity index in the range in the range of 83.7% to 91.5% for n.20 patients. Not any statistical difference was observed between predictions and CT measures of orifice area for the stenotic aortic valve. After TAVI simulations, the measurements of SAPIEN 3 Ultra (S3) device diameter were in agreement with those from post-TAVI angio-CT imaging. A sensitivity analysis demonstrated a modest impact on the S3 diameters when altering the elastic material property of the aortic wall in the range of inverse analysis solution.

Conclusions
Overall, this study demonstrates the feasibility and potential benefits of using non-invasive imaging techniques and computational modeling to estimate material properties in patients undergoing TAVI.
Automated lead toxicity prediction using computational modelling framework
Authors: Chaurasia Priyanka , McClean Sally I. , Mahdi Abbas Ali , Yogarajah Pratheepan , Ansari Jamal Akhtar , Kunwar Shipra , Ahmad Mohammad Kaleem 
Published: November 2023

Abstract
Background
Lead, an environmental toxicant, accounts for 0.6% of the global burden of disease, with the highest burden in developing countries. Lead poisoning is very much preventable with adequate and timely action. Therefore, it is important to identify factors that contribute to maternal BLL and minimise them to reduce the transfer to the foetus. Literacy and awareness related to its impact are low and the clinical establishment for biological monitoring of blood lead level (BLL) is low, costly, and time-consuming. A significant contribution to an infant’s BLL load is caused by maternal lead transfer during pregnancy. This acts as the first pathway to the infant’s lead exposure. The social and demographic information that includes lifestyle and environmental factors are key to maternal lead exposure.

Results
We propose a novel approach to build a computational model framework that can predict lead toxicity levels in maternal blood using a set of sociodemographic features. To illustrate our proposed approach, maternal data comprising socio-demographic features and blood samples from the pregnant woman is collected, analysed, and modelled. The computational model is built that learns from the maternal data and then predicts lead level in a pregnant woman using a set of questionnaires that relate to the maternal’s social and demographic information as the first point of testing. The range of features identified in the built models can estimate the underlying function and provide an understanding of the toxicity level. Following feature selection methods, the 12-feature set obtained from the Boruta algorithm gave better prediction results (kNN = 76.84%, DT = 74.70%, and NN = 73.99%).

Conclusion
The built prediction model can be beneficial in improving the point of care and hence reducing the cost and the risk involved. It is envisaged that in future, the proposed methodology will become a part of a screening process to assist healthcare experts at the point of evaluating the lead toxicity level in pregnant women. Women screened positive could be given a range of facilities including preliminary counselling to being referred to the health centre for further diagnosis. Steps could be taken to reduce maternal lead exposure; hence, it could also be possible to mitigate the infant’s lead exposure by reducing transfer from the pregnant woman.
Food stimuli decrease activation in regions of the prefrontal cortex related to executive function: an fNIRS study
Authors: Cheng Chen , Yang Yong 
Published: November 2023

Abstract
Purpose
Overweight/obese individuals show impairments in executive functions such as inhibitory control. However, the neural mechanisms underlying these disturbances—and specifically, whether or not they involve altered activation of the specific prefrontal cortex regions—are not yet fully understood.

Methods
The motivational dimensional model of affect suggests that high approach-motivated positive affect (e.g., desire) may impair executive function. In the present study, we investigated individual differences in neural responses to videos of food stimuli, and examined brain activity during a cognitive task in an approach-motivated positive state using functional near-infrared spectroscopy (fNIRS). In Experiment 1, in 16 healthy young adults, we tested whether prefrontal cortex activation differed during a food video clip versus a neutral video clip. Then, after viewing each video clip, we tested for differences in executive function performance and prefrontal cortex activation during a Stroop task. Experiment 2 was the same, except that we compared 20 overweight/obese with 20 healthy young adults, and it incorporated only the food video clip.

Results and conclusions
The results of both experiments indicated that food stimuli decrease activation in regions of the prefrontal cortex related to executive function. This study also suggests that overweight/obese might consciously suppress their responses to a desired stimulus, yet here it seems that effect was less pronounced than in healthy controls.

Level of evidence
Level II, Cohort Studies.
From Liquid to Solid-State Lithium Metal Batteries: Fundamental Issues and Recent Developments
Authors: Zhang Zhao , Han Wei-Qiang 
Published: November 2023

AbstractThe widespread adoption of lithium-ion batteries has been driven by the proliferation of portable electronic devices and electric vehicles, which have increasingly stringent energy density requirements. Lithium metal batteries (LMBs), with their ultralow reduction potential and high theoretical capacity, are widely regarded as the most promising technical pathway for achieving high energy density batteries. In this review, we provide a comprehensive overview of fundamental issues related to high reactivity and migrated interfaces in LMBs. Furthermore, we propose improved strategies involving interface engineering, 3D current collector design, electrolyte optimization, separator modification, application of alloyed anodes, and external field regulation to address these challenges. The utilization of solid-state electrolytes can significantly enhance the safety of LMBs and represents the only viable approach for advancing them. This review also encompasses the variation in fundamental issues and design strategies for the transition from liquid to solid electrolytes. Particularly noteworthy is that the introduction of SSEs will exacerbate differences in electrochemical and mechanical properties at the interface, leading to increased interface inhomogeneity—a critical factor contributing to failure in all-solid-state lithium metal batteries. Based on recent research works, this perspective highlights the current status of research on developing high-performance LMBs.
A Time Series Decomposition and Reinforcement Learning Ensemble Method for Short-Term Passenger Flow Prediction in Urban Rail Transit
Authors: Wu Jinxin , He Deqiang , Li Xianwang , He Suiqiu , Li Qin , Ren Chonghui 
Published: November 2023

AbstractShort-term passenger flow prediction (STPFP) helps ease traffic congestion and optimize the allocation of rail transit resources. However, the nonlinear and nonstationary nature of passenger flow time series challenges STPFP. To address this issue, a hybrid model based on time series decomposition and reinforcement learning ensemble strategies is proposed. Firstly, the improved arithmetic optimization algorithm is constructed by adding sine chaotic mapping, a new dynamic boundary strategy, and adaptive T distribution mutations for optimizing variational mode decomposition (VMD) parameters. Then, the original passenger flow data containing nonlinear and nonstationary irregular changes of noise is decomposed into several intrinsic mode functions (IMFs) by using the optimized VMD technology, which reduces the time-varying complexity of passenger flow time series and improves predictability. Meanwhile, the IMFs are divided into different frequency series by fluctuation-based dispersion entropy, and diverse models are utilized to predict different frequency series. Finally, to avoid the cumulative error caused by the direct superposition of each IMF’s prediction result, reinforcement learning is adopted to ensemble the multiple models to acquire the multistep passenger flow prediction result. Experiments on four subway station passenger flow datasets proved that the prediction performance of the proposed method was better than all benchmark models. The excellent prediction effect of the proposed model has important guiding significance for evaluating the operation status of urban rail transit systems and improving the level of passenger service.
Graph Neural Network-Based Short‑Term Load Forecasting with Temporal Convolution
Authors: Sun Chenchen , Ning Yan , Shen Derong , Nie Tiezheng 
Published: November 2023

AbstractAn accurate short-term load forecasting plays an important role in modern power system’s operation and economic development. However, short-term load forecasting is affected by multiple factors, and due to the complexity of the relationships between factors, the graph structure in this task is unknown. On the other hand, existing methods do not fully aggregating data information through the inherent relationships between various factors. In this paper, we propose a short-term load forecasting framework based on graph neural networks and dilated 1D-CNN, called GLFN-TC. GLFN-TC uses the graph learning module to automatically learn the relationships between variables to solve problem with unknown graph structure. GLFN-TC effectively handles temporal and spatial dependencies through two modules. In temporal convolution module, GLFN-TC uses dilated 1D-CNN to extract temporal dependencies from historical data of each node. In densely connected residual convolution module, in order to ensure that data information is not lost, GLFN-TC uses the graph convolution of densely connected residual to make full use of the data information of each graph convolution layer. Finally, the predicted values are obtained through the load forecasting module. We conducted five studies to verify the outperformance of GLFN-TC. In short-term load forecasting, using MSE as an example, the experimental results of GLFN-TC decreased by 0.0396, 0.0137, 0.0358, 0.0213 and 0.0337 compared to the optimal baseline method on ISO-NE, AT, AP, SH and NCENT datasets, respectively. Results show that GLFN-TC can achieve higher prediction accuracy than the existing common methods.
Imagination und Erfahrung
Authors: Bernard Andreas 
Published: November 2023

ZusammenfassungDieser Essay beschäftigt sich mit dem Verhältnis von Imagination und Erfahrung in gegenwärtigen poetologischen Debatten. Es geht um die vieldiskutierte Frage, welche Autorensubjekte welche literarischen Darstellungen hervorbringen können und sollen. Der Essay versucht diese aktuellen Positionen in der Geschichte der literarischen Hermeneutik seit Dilthey zu verorten.
»Soviel Gegenwart war selten.«
Authors: Amlinger Carolin 
Published: November 2023

ZusammenfassungDer Beitrag beobachtet in dem Phänomen des Debattenromans einen neuen Bearbeitungsmodus von Ungewissheit. Außerliterarische Wertigkeiten der Aktualität sollen eine Kommensurabilität zwischen fiktiven Erfolgserwartungen von Büchern und realisierten Beachtungserfolgen öffentlicher Debatten herstellen. Mit ähnlichen Wertigkeitsprüfungen wird die Germanistik konfrontiert, die angesichts messbarer Beachtungsverluste mithilfe heteronomer Valorisierungen auf ihre Gegenwärtigkeit hin befragt wird.
The history of fire blight biocontrol with Gram-negative bacteria and bacteriophages
Authors: Puławska Joanna , Mikiciński Artur , Sobiczewski Piotr 
Published: November 2023

AbstractFire blight caused by bacterium Erwinia amylovora is one of the most damaging diseases of apple and pear trees and many other plant species of the Rosaceae family. So far, it has been detected in almost all areas of pome fruit cultivation and in some regions it causes economic damage every year. Plant protection against fire blight is aimed at both preventing their infection and controlling the disease. However, the protection of plants against bacteriosis is generally difficult due to the small range of plant protection products and the growing doubts about their safety for the environment. Limitations related to their use have resulted in an increased interest in alternative methods, including the method of biological protection using various microorganisms. The first research on biological control agents was conducted in the USA about 100 years ago. Currently, it is also carried out in other countries, especially where fire blight causes economic losses. Commercial products whose active ingredients are mainly bacteria have already been developed. This work is a review of the studies and achievements in this field from its beginnings focusing on the Gram-negative bacteria and bacteriophages as a biocontrol agents.