bluuebunny/crossref_metadata_2025_split huggingface dataset:
BinDMO: a new Binary Dwarf Mongoose Optimization algorithm on based Z-shaped, U-shaped, and taper-shaped transfer functions for CEC-2017 benchmarks
Authors: BAS Emine 
Published: February 2024

AbstractIntelligent swarm optimization algorithms have become increasingly common due to their success in solving real-world problems. Dwarf Mongoose Optimization (DMO) algorithm is a newly proposed intelligent swarm optimization algorithm in recent years. It was developed for continuous optimization problem solutions in its original paper. But real-world problems are not always problems that take continuously variable values. Real-world problems are often problems with discrete variables. Therefore, heuristic algorithms proposed for continuous optimization problems need to be updated to solve discrete optimization problems. In this study, DMO has been updated for binary optimization problems and the Binary DMO (BinDMO) algorithm has been proposed. In binary optimization, the search space consists of binary variable values. Transfer functions are often used in the conversion of continuous variable values to binary variable values. In this study, twelve different transfer functions were used (four Z-shaped, four U-shaped, and four Taper-shaped). Thus, twelve different BinDMO variations were obtained (BinDMO1, BinDMO2, …, BinDMO12). The achievements of BinDMO variations were tested on thirteen different unimodal and multimodal classical benchmark functions. The effectiveness of population sizes on the effectiveness of BinDMO was also investigated. When the results were examined, it was determined that the most successful BinDMO variation was BinDMO1 (with Z1-shaped transfer function). The most successful BinDMO variation was compared with three different binary heuristic algorithms selected from the literature (SO, PDO, and AFT) on CEC-2017 benchmark functions. According to the average results, BinDMO was the most successful binary heuristic algorithm. This has proven that BinDMO can be chosen as an alternative algorithm for binary optimization problems.
Like a human: The social facilitation/inhibition effect in presence of a virtual observer depends on arousal
Authors: Sterna Radosław , Szczugieł Jakub , Pilarczyk Joanna , Siry Agnieszka , Kuniecki Michał 
Published: February 2024

AbstractBetter (social facilitation) or worse (social inhibition) performance in a task while being observed has repeatedly been demonstrated with real human observers, yet it has not been fully tested with virtual observers. We tested this effect in a virtual environment using a visual search task to verify if the mere presence of a virtual observer would boost participants’ performance in the easy variant of the task and hinder it in the difficult one. We used electrodermal (EDA) activity measurement to test whether physiological arousal would moderate this effect. The presence of a virtual character affected search performance, which was moderated by arousal, with lower arousal leading to better performance. These results confirm that the mere presence of virtual characters can evoke a social facilitation/inhibition effect similar to that of human beings; this could confirm Zajonc’s theory and serve as encouragement for further development of VR-based training & educational tools with virtual agents.
Model order reduction for the 1D Boltzmann-BGK equation: identifying intrinsic variables using neural networks
Authors: Koellermeier Julian , Krah Philipp , Reiss Julius , Schellin Zachary 
Published: February 2024

AbstractKinetic equations are crucial for modeling non-equilibrium phenomena, but their computational complexity is a challenge. This paper presents a data-driven approach using reduced order models (ROM) to efficiently model non-equilibrium flows in kinetic equations by comparing two ROM approaches: proper orthogonal decomposition (POD) and autoencoder neural networks (AE). While AE initially demonstrate higher accuracy, POD’s precision improves as more modes are considered. Notably, our work recognizes that the classical POD model order reduction approach, although capable of accurately representing the non-linear solution manifold of the kinetic equation, may not provide a parsimonious model of the data due to the inherently non-linear nature of the data manifold. We demonstrate how AEs are used in finding the intrinsic dimension of a system and to allow correlating the intrinsic quantities with macroscopic quantities that have a physical interpretation.
Metals and metallothionein evolution in snails: a contribution to the concept of metal-specific functionality from an animal model group
Authors: Dallinger Reinhard 
Published: February 2024

AbstractThis is a critical review of what we know so far about the evolution of metallothioneins (MTs) in Gastropoda (snails, whelks, limpets and slugs), an important class of molluscs with over 90,000 known species. Particular attention will be paid to the evolution of snail MTs in relation to the role of some metallic trace elements (cadmium, zinc and copper) and their interaction with MTs, also compared to MTs from other animal phyla. The article also highlights the important distinction, yet close relationship, between the structural and metal-selective binding properties of gastropod MTs and their physiological functionality in the living organism. It appears that in the course of the evolution of Gastropoda, the trace metal cadmium (Cd) must have played an essential role in the development of Cd-selective MT variants. It is shown how the structures and Cd-selective binding properties in the basal gastropod clades have evolved by testing and optimizing different combinations of ancestral and novel MT domains, and how some of these domains have become established in modern and recent gastropod clades. In this context, the question of how adaptation to new habitats and lifestyles has affected the original MT traits in different gastropod lineages will also be addressed. The 3D structures and their metal binding preferences will be highlighted exemplarily in MTs of modern littorinid and helicid snails. Finally, the importance of the different metal requirements and pathways in snail tissues and cells for the shaping and functionality of the respective MT isoforms will be shown.
Poor patient outcome correlates with active engulfment of cytokeratin positive CTCs within cancer-associated monocyte population in lung cancer
Authors: Wiegmans A. P. , Ivanova E. , Naei V. Y. , Monkman J. , Fletcher J. , Mullally W. , Warkiani M. E. , O’Byrne K. , Kulasinghe A. 
Published: February 2024

AbstractHigh rates of mortality in non-small cell lung cancer lung cancer is due to inherent and acquired resistance to systemic therapies and subsequent metastatic burden. Metastasis is supported by suppression of the immune system at secondary organs and within the circulation. Modulation of the immune system is now being exploited as a therapeutic target with immune checkpoint inhibitors. The tracking of therapeutic efficacy in a real-time can be achieved with liquid biopsy, and evaluation of circulating tumour cells and the associated immune cells. A stable liquid biopsy biomarker for non-small cell lung cancer lung cancer has yet to be approved for clinical use. We performed a cross-sectional single-site study, and collected liquid biopsies from patients diagnosed with early, locally advanced, or metastatic lung cancer, undergoing surgery, or systemic therapy (chemotherapy/checkpoint inhibitors). Evaluation of overall circulating tumour cell counts, or cluster counts did not correlate with patient outcome. Interestingly, the numbers of Pan cytokeratin positive circulating tumour cells engulfed by tumour associated monocytes correlated strongly with patient outcome independent of circulating tumour cell counts and the use of checkpoint inhibitors. We suggest that Pan cytokeratin staining within monocytes is an important indicator of tumour-associated inflammation post-therapy and an effective biomarker with strong prognostic capability for patient outcome.
The Effects of Problem-Based, Project-Based, and Case-Based Learning on Students’ Motivation: a Meta-Analysis
Authors: Wijnia Lisette , Noordzij Gera , Arends Lidia R. , Rikers Remigius M. J. P. , Loyens Sofie M. M. 
Published: February 2024

AbstractIn this meta-analysis, we examined the effects on students’ motivation of student-centered, problem-driven learning methods compared to teacher-centered/lecture-based learning. Specifically, we considered problem-based (PBL), project-based (PjBL), and case-based learning (CBL). We viewed motivation as a multifaceted construct consisting of students’ beliefs (competence and control beliefs), perceptions of task value (interest and importance), and reasons for engaging in tasks (intrinsic or extrinsic). In addition, we included students’ attitudes toward school subjects (e.g., science). We included 139 subsamples from the 132 included reports (83 PBL, 37 PjBL, and 19 CBL subsamples). Overall, PBL, PjBL, and CBL had a small to moderate, heterogeneous positive effect (d = 0.498) on motivation. Moderator analyses revealed that larger effect sizes were found for students’ beliefs, values, and attitudes compared to students’ reasons for studying. No differences were found between the three instructional methods on motivation. However, effect sizes were larger when problem-driven learning was applied in a single course (when compared to a curriculum-level approach). Larger effects were also found in some academic domains (i.e., healthcare and STEM) than in others. While the impact of problem-driven learning on motivation is generally positive, the intricate interplay of factors such as academic domain and implementation level underscores the need for a nuanced approach to leveraging these instructional methods effectively with regard to increasing student motivation.
Investigating the environmental Kuznets curve modified with HDI: evidence from a panel of eco-innovative countries
Authors: Polat Buğra , Çil Nilgün 
Published: February 2024

AbstractConsidering the increase in polluting emissions, the importance of determining the relationship between economic development and environmental quality is a crucial issue in achieving sustainable development goals. This study explores and empirically tests the validity of the Environmental Kuznets Curve (EKC) hypothesis in a panel data of 39 countries is assembled over the period 1993–2018. For this purpose, the Human Development Index is used as a measure of development, contrary to classical studies in which GDP growth was determined as an indicator of economic growth. Also using by two different measures of pollutant emissions, such as methane ($${{\text{CH}}}_{4}$$

CH
4

) and carbon ($${{\text{CO}}}_{2}$$

CO
2

) emissions, examining to the validity of the EKC hypothesis. The analysis method consists of the fixed effect and robustness estimation of the panel data model, and employed the U-test approach in the study. Empirical findings in this study show that strong evidence to support an inverted U-shaped relationship between CO2 emissions and human development, although the U-test results point at mixed results for CH4 emissions. In addition, it is detected that negative relationship between environmental related technological innovation and pollutants emission such as $${{\text{CH}}}_{4}$$

CH
4

and $${{\text{CO}}}_{2}$$

CO
2

, which highlights the importance of promoting innovative technologies in struggle global warming.
On the Impact of Plastic Fines on the Compaction Characteristics of Sand
Authors: Lieske Wolfgang , Sarkar Debdeep , Goudarzy Meisam , Wichtmann Torsten 
Published: February 2024

AbstractBinary mixtures of plastic fines and a non-cohesive host material are used in geotechnical barriers to obtain high shear strength and low permeability. To achieve such properties, the sand grains must form the force chain and the clay must fill the voids of the host material. However, clays are known to affect the grain to grain contacts by forming cohesive membranes. Since engineered barriers are usually compacted at water contents below saturation (Proctor conditions), it is still unclear whether such membranes will form. The aim of the current research is to shed light on the compaction characteristics of such mixtures. Proctor datasets were analysed in terms of skeleton and fines void ratio and optimal water content. Oedometric compression behaviour and limiting void ratios were studied to outline the characteristics of mixtures in a saturated or dry state, respectively. The results show that depending on the mixing ratio, compaction properties can be divided into three different ranges, where either the properties of one of the input materials dominate the behaviour or a transitional range exists that is characterised by a strong mutual influence of both materials. Furthermore, even a small amount of the highly plastic clay was found to influence the properties of the host sand.
Towards a Socio-Constructivist Didactic Model for Integrated STEM Education
Authors: Toma Radu Bogdan , Yánez-Pérez Iraya , Meneses-Villagrá Jesús Ángel 
Published: February 2024

AbstractAs science education shifts toward integrated STEM (Science, Technology, Engineering, and Mathematics) approaches, guidelines for designing teaching and learning episodes that integrate curricular content and procedures from multiple disciplines become increasingly in demand. The existing plethora of conceptualizations of STEM makes difficult such an endeavor, leading to ill-defined lesson plans focused on only two –mainly science and technology or science and mathematics– out of the four STEM disciplines. The question addressed, therefore, is how the integrated STEM approach could be translated into classroom practices that integrate the four STEM disciplines in a way that is consistent and coherent with elementary education curricula. This manuscript advances a theoretically informed didactic model for the design and implementation of integrated STEM in elementary education. The article discusses how the model uses socio-constructivist principles to establish intentional and explicit connections between STEM disciplines via scientific inquiry, engineering design, and computational thinking practices. The model is rooted in learning theories developed by Piaget, Vygotsky, Ausubel, and Bruner and could serve as a roadmap for educators and researchers designing integrated STEM lessons. Future empirical research testing the model is warranted.
Intrinsic and post-hoc XAI approaches for fingerprint identification and response prediction in smart manufacturing processes
Authors: Puthanveettil Madathil Abhilash , Luo Xichun , Liu Qi , Walker Charles , Madarkar Rajeshkumar , Cai Yukui , Liu Zhanqiang , Chang Wenlong , Qin Yi 
Published: February 2024

AbstractIn quest of improving the productivity and efficiency of manufacturing processes, Artificial Intelligence (AI) is being used extensively for response prediction, model dimensionality reduction, process optimization, and monitoring. Though having superior accuracy, AI predictions are unintelligible to the end users and stakeholders due to their opaqueness. Thus, building interpretable and inclusive machine learning (ML) models is a vital part of the smart manufacturing paradigm to establish traceability and repeatability. The study addresses this fundamental limitation of AI-driven manufacturing processes by introducing a novel Explainable AI (XAI) approach to develop interpretable processes and product fingerprints. Here the explainability is implemented in two stages: by developing interpretable representations for the fingerprints, and by posthoc explanations. Also, for the first time, the concept of process fingerprints is extended to develop an interpretable probabilistic model for bottleneck events during manufacturing processes. The approach is demonstrated using two datasets: nanosecond pulsed laser ablation to produce superhydrophobic surfaces and wire EDM real-time monitoring dataset during the machining of Inconel 718. The fingerprint identification is performed using a global Lipschitz functions optimization tool (MaxLIPO) and a stacked ensemble model is used for response prediction. The proposed interpretable fingerprint approach is robust to change in processes and can responsively handle both continuous and categorical responses alike. Implementation of XAI not only provided useful insights into the process physics but also revealed the decision-making logic for local predictions.
Spatial Engineering of Mammary Epithelial Cell Cultures with 3D Bioprinting Reveals Growth Control by Branch Point Proximity
Authors: Koskinen Leena M. , Nieminen Lari , Arjonen Antti , Guzmán Camilo , Peurla Markus , Peuhu Emilia 
Published: February 2024

AbstractThe three-dimensional (3D) structure of the ductal epithelium and the surrounding extracellular matrix (ECM) are integral aspects of the breast tissue, and they have important roles during mammary gland development, function and malignancy. However, the architecture of the branched mammary epithelial network is poorly recapitulated in the current in vitro models. 3D bioprinting is an emerging approach to improve tissue-mimicry in cell culture. Here, we developed and optimized a protocol for 3D bioprinting of normal and cancerous mammary epithelial cells into a branched Y-shape to study the role of cell positioning in the regulation of cell proliferation and invasion. Non-cancerous cells formed continuous 3D cell networks with several organotypic features, whereas the ductal carcinoma in situ (DCIS) –like cancer cells exhibited aberrant basal polarization and defective formation of the basement membrane (BM). Quantitative analysis over time demonstrated that both normal and cancerous cells proliferate more at the branch tips compared to the trunk region of the 3D-bioprinted cultures, and particularly at the tip further away from the branch point. The location-specific rate of proliferation was independent of TGFβ signaling but invasion of the DCIS-like breast cancer cells was reduced upon the inhibition of TGFβ. Thus, our data demonstrate that the 3D-bioprinted cells can sense their position in the branched network of cells and proliferate at the tips, thus recapitulating this feature of mammary epithelial branching morphogenesis. In all, our results demonstrate the capacity of the developed 3D bioprinting method for quantitative analysis of the relationships between tissue structure and cell behavior in breast morphogenesis and cancer.
On Poisson Approximation
Authors: Novak S. Y. 
Published: February 2024

AbstractThe problem of evaluating the accuracy of Poisson approximation to the distribution of a sum of independent integer-valued random variables has attracted a lot of attention in the past six decades. Among authors who contributed to the topic are Prokhorov, Kolmogorov, LeCam, Shorgin, Barbour, Hall, Deheuvels, Pfeifer, Roos, and many others. From a practical point of view, the problem has important applications in insurance, reliability theory, extreme value theory, etc. From a theoretical point of view, the topic provides insights into Kolmogorov’s problem concerning the accuracy of approximation of the distribution of a sum of independent random variables by infinitely divisible laws. The task of establishing an estimate of the accuracy of Poisson approximation with a correct (the best possible) constant at the leading term remained open for decades. We present a solution to that problem in the case where the accuracy of approximation is evaluated in terms of the point metric. We generalise and sharpen the corresponding inequalities established by preceding authors. A new result is established for the intensively studied topic of compound Poisson approximation to the distribution of a sum of integer-valued r.v.s.
Understanding university technicians’ role in creating knowledge exchange routines and capabilities: a research agenda
Authors: Noke Hannah , Mosey Simon , Vere Kelly 
Published: February 2024

AbstractKnowledge exchange (KE) is becoming a strategic imperative for universities globally. Research examining KE has tended to focus on a limited and select group of stakeholders. This paper builds on calls for a wider consideration of KE activities and other contributors to the KE agenda. The technical community is one such group that has received little attention or acknowledgement of their part in KE. We argue that the technical community makes a significant yet overlooked contribution to a broad array of KE activities. Technicians are problem solvers that often undertake work that their academic counterparts could not do—as users and managers of complex equipment to enable innovation. To date the literature provides limited understanding of the technician’s role and a lack of conceptualization of the contribution of technicians in KE. Adopting a micro-foundation approach, we present a conceptual framework which draws on the multi-level categories of individuals, processes and structures. We take a broader perspective of KE by including activities such as working with external businesses, enabling access to facilities and providing analysis, and contributing to public engagement and training. By synthesizing contemporary research with recent policy work we reveal the potential contribution of technician’s talent, know-how and boundary spanning activities. We conclude with a structured agenda and conceptual framework to help guide future research, showing how investigating the integration of individual, process and structural factors affecting technicians can help reveal new insights into KE capability development at the university level.
Effects of land surface temperatures on vegetation phenology along urban–rural local climate zone gradients
Authors: Xie Jing , Li Xinwei , Chung Lamuel Chi Hay , Webster Christopher John 
Published: February 2024

Abstract
Context
Urbanization and local urban climate have multiple impacts on vegetation phenology in urban and suburban areas. Understanding these effects and their interactions with the surface urban heating effect remains limited.

Objective
We employed a time series of Earth observation data to analyze land surface phenology (LSP) dynamics and related environmental drivers in the highly urbanized Pearl River Delta (PRD) region.

Methods
First, local climate zone (LCZ) maps were generated from Earth observation datasets of 2000 and 2019. Second, LSP (i.e., start, end, and length of season) were extracted from vegetation indices for 2000–2019. Thirdly, land surface temperature (LST) was used as an explanatory variable based on the LCZ of cities. Finally, interannual trends of LSP and their association with LST were analyzed, depending on the distance gradient of vegetation to compact high-rise buildings.

Results
Urban surface characteristics showed that LSP in regions dominated by compact and high-rise urban areas presented significant spatiotemporal variation at the start and end of season than those dominated by open, mid-rise, and low-rise areas. The impacts of spring and autumn LST in the daytime on LSP were slightly more substantial than those in the nighttime. The association of decreasing spring LST in the daytime with a delayed start of season is especially pronounced in urban domains.

Conclusions
The results indicate that vegetated areas adjacent to urban domains presented greater spatiotemporal dynamics than suburban and rural regions. Our study emphasizes the dependence of spatiotemporal changes in vegetation phenology on the effects of urban surface warming.