bluuebunny/crossref_metadata_2025 huggingface dataset:
A new performance‐based seismic design method using endurance time analysis for linked column frame system and a comparison of structural systems and seismic analysis methods
Authors: Jaberi Vahid , Jaberi Masume , Asghari Abazar
Published: February 2024

This paper presents a new performance‐based seismic design method for the design of repairable linked column frame (LCF) and linked column system (LCS). Currently, the biggest problem of these systems is the lack of a simple and practical design method that leads to the design of optimal models with sufficient seismic capacity. The interaction of the primary and secondary systems, changing the lateral load pattern during an earthquake, and the implementation of the target performance objectives have complicated the design of these systems. The evaluations carried out in this research show that the rotation of link beams must be controlled in the design. Therefore, the ultimate plastic rotation of links is determined to be 0.01 rad for the seismic intensity of design base earthquake and 0.015 rad for maximum considered earthquake. The results show that the models designed using the presented method are optimal, have sufficient seismic capacity, and achieve the target performance objectives. In addition, although previous researches have shown that these systems have a suitable seismic behavior, their seismic behavior have not been compared with other structural systems. Comparing can show the behavioral characteristics of a new structural system; hence, the elastic and plastic behavior of the LCF and LCS models have been compared with other common steel structural systems using all analysis methods. Moreover, in the presented method for the design of LCF and LCS systems, nonlinear time history analysis using the endurance time method (ETM) is used, and due to the newness of the endurance time method, its results are compared with the median results of nonlinear time history analysis at different seismic hazard levels and incremental dynamic analysis (IDA), in 45 samples. The results show that the endurance time analysis is a reasonable and efficient method, and in this comparison, the difference between the results of ETM and IDA methods is 6% on average.
Managing the Will: Managerial Normativity from the Wage Society to the Platform Age
Authors: Nicoli Massimiliano , Paltrinieri Luca
Published: February 2024

At different times in the history of industrial capitalism, the firm has replaced the State, or anticipated it, by constructing regulatory models which were then legally sanctioned by State legislation, or generalised within public policies concerning, for example, education systems. This is what Pollman and Barry call “regulatory entrepreneurship”. Alongside this legal normativity, management practices have always entailed a psychological normative production aiming to shape the workforce as a subject, also according to the political instances of current forms of State governmentality. Indeed, the very birth of modern management is to be conceived in relation to these practices of production of forms of subjectivity in the workplace.
Renormalon cancellation and linear power correction to threshold-like asymptotics of space-like parton correlators
Authors: Liu Yizhuang , Su Yushan
Published: February 2024

Abstract

In this paper, we show that the common hard kernel of double-log-type or threshold-type factorization for certain space-like parton correlators that arise in the context of lattice parton distributions, the heavy-light Sudakov hard kernel, has linear infrared (IR) renormalon. We explicitly demonstrate how this IR renormalon correlates with ultraviolet (UV) renormalons of next-to-leading power operators in two explicit examples: threshold asymptotics of space-like quark-bilinear coefficient functions and transverse momentum dependent (TMD) factorization of quasi wave function amplitude. Theoretically, the pattern of renormalon cancellation complies with general expectations to marginal asymptotics in the UV limit. Practically, this linear renormalon explains the slow convergence of imaginary parts observed in lattice extraction of the Collins-Soper kernel and signals the relevance of next-to-leading power contributions. Fully factorized, fully controlled threshold asymptotic expansion for space-like quark-bilinear coefficient functions in coordinate and moment space has also been proposed.
Interpolator Symmetries and New Kalton-Peck Spaces
Authors: Castillo Jesús M. F. , Corrêa Willian H. G. , Ferenczi Valentin , González Manuel
Published: February 2024

We study the six diagrams generated by the first three Schechter interpolators $$\Delta _2(f)= f''(1/2)/2!, \Delta _1(f)= f'(1/2), \Delta _0(f)=f(1/2)$$

Δ
2

(
f
)

=

f

′
′

(
1
/
2
)

/
2
!
,

Δ
1

(
f
)

=

f
′

(
1
/
2
)

,

Δ
0

(
f
)

=
f

(
1
/
2
)

acting on the Calderón space associated to the pair $$(\ell _\infty , \ell _1)$$

(

ℓ
∞

,

ℓ
1

)

. We will study the remarkable and somehow unexpected properties of all the spaces appearing in those diagrams: two new spaces (and their duals), two Orlicz spaces (and their duals) in addition to the third order Rochberg space, the standard Kalton-Peck space $$Z_2$$

Z
2

and, of course, the Hilbert space $$\ell _2$$

ℓ
2

. We will also deal with a nice test case: that of weighted $$\ell _2$$

ℓ
2

spaces, in which case all involved spaces are Hilbert spaces.
Conflicts between priming and episodic retrieval: a question of fluency?
Authors: Weller Peter , Recio Guillermo , Kaltwasser Laura , Rostami Hadiseh Nowparast , Stürmer Birgit , Sommer Werner
Published: February 2024

Human memory consists of different underlying processes whose interaction can result in counterintuitive findings. One phenomenon that relies on various types of mnemonic processes is the repetition priming effect for unfamiliar target faces in familiarity decisions, which is highly variable and may even reverse. Here, we tested the hypothesis that this reversed priming effect may be due to a conflict between target fluency signals and episodic retrieval processes. After replicating the reverse priming effect, three different manipulations were effective in diminishing it. We suggest that each of these manipulations diminished the ambiguity regarding the source of priming-induced fluency of target processing. Our findings argue against a strictly independent view of different types of memory.
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

Intelligent 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

Better (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

Kinetic 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

This 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

High 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

In 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

Considering 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

Binary 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

As 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

In 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

The 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

The 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

Knowledge 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

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.
Denoising of Geochemical Data using Deep Learning–Implications for Regional Surveys
Authors: Zhang Steven E. , Bourdeau Julie E. , Nwaila Glen T. , Parsa Mohammad , Ghorbani Yousef
Published: February 2024

Regional geochemical surveys generate large amounts of data that can be used for a number of purposes such as to guide mineral exploration. Modern surveys are typically designed to permit quantification of data uncertainty through data quality metrics by using quality assurance and quality control (QA/QC) methods. However, these metrics, such as data accuracy and precision, are obtained through the data generation phase. Consequently, it is unclear how residual uncertainty in geochemical data can be minimized (denoised). This is a limitation to propagating uncertainty through downstream activities, particularly through complex models, which can result from the usage of artificial intelligence-based methods. This study aims to develop a deep learning-based method to examine and quantify uncertainty contained in geochemical survey data. Specifically, we demonstrate that: (1) autoencoders can reduce or modulate geochemical data uncertainty; (2) a reduction in uncertainty is observable in the spatial domain as a decrease of the nugget; and (3) a clear data reconstruction regime of the autoencoder can be identified that is strongly associated with data denoising, as opposed to the removal of useful events in data, such as meaningful geochemical anomalies. Our method to post-hoc denoising of geochemical data using deep learning is simple, clear and consistent, with the amount of denoising guided by highly interpretable metrics and existing frameworks of scientific data quality. Consequently, variably denoised data, as well as the original data, could be fed into a single downstream workflow (e.g., mapping, general data analysis or mineral prospectivity mapping), and the differences in the outcome can be subsequently quantified to propagate data uncertainty.
Novel LMI-Based Boundary Stabilization of Stochastic Delayed Reaction-Diffusion Cohen–Grossberg BAM Neural Networks with Impulsive Effects
Authors: Gokulakrishnan V. , Srinivasan R. , Syed Ali M. , Rajchakit Grienggrai , Priya Bandana
Published: February 2024

The stabilization problem of stochastic delayed reaction-diffusion Cohen–Grossberg BAM neural networks (SDRDCGBAMNNs) with impulsive effects and boundary control is studied in this paper. By using suitable boundary controllers, Lyapunov–Krasovskii functional, linear matrix inequalities and average impulsive interval method, new sufficient criteria are found to ensure that the SDRDCGBAMNNs achieve boundary stabilization in finite-time. Based on these criteria, the effects of impulsive and boundary controllers on finite-time stability are analyzed. Numerical simulations are performed to demonstrate the feasibility of the theoretical results.
Poset Ramsey Number $$R(P,Q_n)$$. II. N-Shaped Poset
Authors: Axenovich Maria , Winter Christian
Published: February 2024

Given partially ordered sets (posets) $$(P, \le _P)$$

(
P
,

≤
P

)

and $$(P', \le _{P'})$$

(

P
′

,

≤

P
′

)

, we say that $$P'$$

P
′

contains a copy of P if for some injective function $$f:P\rightarrow P'$$

f
:
P
→

P
′

and for any $$A, B\in P$$

A
,
B
∈
P

, $$A\le _P B$$

A

≤
P

B

if and only if $$f(A)\le _{P'} f(B)$$

f

(
A
)

≤

P
′

f

(
B
)

. For any posets P and Q, the poset Ramsey number R(P, Q) is the least positive integer N such that no matter how the elements of an N-dimensional Boolean lattice are colored in blue and red, there is either a copy of P with all blue elements or a copy of Q with all red elements. We focus on the poset Ramsey number $$R(P, Q_n)$$

R
(
P
,

Q
n

)

for a fixed poset P and an n-dimensional Boolean lattice $$Q_n$$

Q
n

, as n grows large. It is known that $$n+c_1(P) \le R(P,Q_n) \le c_2(P) n$$

n
+

c
1

(
P
)

≤
R

(
P
,

Q
n

)

≤

c
2

(
P
)

n

, for positive constants $$c_1$$

c
1

and $$c_2$$

c
2

. However, there is no poset P known, for which $$R(P, Q_n)> (1+\epsilon )n$$

R

(
P
,

Q
n

)

>

(
1
+
ϵ
)

n

, for $$\epsilon >0$$

ϵ
>
0

. This paper is devoted to a new method for finding upper bounds on $$R(P, Q_n)$$

R
(
P
,

Q
n

)

using a duality between copies of $$Q_n$$

Q
n

and sets of elements that cover them, referred to as blockers. We prove several properties of blockers and their direct relation to the Ramsey numbers. Using these properties we show that $$R(\mathcal {N},Q_n)=n+\Theta (n/\log n)$$

R

(
N
,

Q
n

)

=
n
+
Θ

(
n
/
log
n
)

, for a poset $$\mathcal {N}$$
N
with four elements A, B, C,  and D, such that $$A<C$$

A
<
C

, $$B<D$$

B
<
D

, $$B<C$$

B
<
C

, and the remaining pairs of elements are incomparable.
Hazardous impacts of heavy metal pollution on biometric and biochemical composition of pearl oyster Pinctada radiata from five sites along Alexandria coast, with reference to its potential health risk assessment
Authors: Abdel-Mohsen Hala Ahmed , Ismail Mona Mohamed , Moussa Moussa Ragia
Published: February 2024

This study investigated the effect of heavy metals on the pearl oyster Pinctada radiata from 5 sites along the coast of Alexandria, with focus on its ecological health and potential risks to human consumption. Pollution results showed that Abu-Qir had the highest Cu and Cd values. Montaza and Eastern Harbor had the highest Fe and Pb values, respectively. Statistically, differences in metal concentrations among study sites were significant (p < 0.05). Non-carcinogenic risk (TTHQ) of tested metals and carcinogenic ones of Cd and Pb showed “high risk” on human health by consuming pearl oysters. Morphometric measurements and condition indices were studied to assess growth patterns and health in relation to heavy metals exposure. Key findings showed detectable declines in size and condition index in Eastern Harbor, whereas Abu-Qir recorded the highest values. This condition index performance presented Abu-Qir, Mammora, and Miami as ideal locations for spat collection and oyster rearing, potentially enhancing Egyptian pearl farming. Average values of spatial proximate contents of pearl oyster showed that it was rich in proteins (33.07–58.52%) with low fat content (1.39–1.87%) and carbohydrates (9.72–17.63%). Biochemical composition of pearl oyster demonstrated its high nutritional value which supported its promotion as a functional food for human consumption. The calorie content of pearl oyster was less than 2 Kcal, making this species an alternative source of healthy food to reduce obesity. Regression analysis indicated that Cu, Cd, and Pb had significant effect on 2-diphenyl-1-picrylhydrazyl (DPPH) scavenging activity, calories, vitamins, and pigment content of the collected oysters.
Optimum Dimensions for Au Nanoframe Tuning in the Near-Infrared Second Window Range for Biomedical Applications: A Numerical Study
Authors: Alali Fatema Abdullah , Alhindi Khadeeja Bader
Published: February 2024

Au nanoparticles are favored in biomedical applications owing to their low cost and negligible cytotoxicity to biological cells. Nanoframes outshine their solid counterparts because of their porosity, which produces pronounced redshifts in their local surface plasmon resonance (LSPR). This feature enables the utilization of nanoframes in photothermal-based therapy, where LSPR excitation of particles within the near-infrared range (NIR) is essential. LSPR redshift in nanoframes is highly sensitive to their dimensions. A slight difference in the nanoframe dimension can result in substantial redshift, potentially pushing its LSPR beyond or below the required NIR range. We perform a systematic numerical study to investigate the optimum dimensions within a range of 1–100 nm for a spherical frame (SpF) and standard cubic frame (CF) to precisely tune their LSPR within the NIR-II window (1000–1400 nm). Our findings indicate that SpF exhibits a shorter LSPR redshift than CF’s at a certain porosity limit that is related to the geometry of the frame. Moreover, SpF displays higher LSPR sensitivity in the NIR region compared to CF. These insights provide valuable guidance for nanoframe design tailored for photothermal-based biomedical applications.
Choice of Open Access in Elsevier Hybrid Journals
Authors: Asai Sumiko
Published: February 2024

Open access articles in hybrid journals have recently increased despite high article processing charges. This study investigated the impacts of grants and transformative agreements on authors’ choice of open and non-open access articles by comparing two article types. The samples were hybrid journals launched independently by Elsevier. The results revealed that the authors who received more grants in countries with transformative agreements were more likely to choose open access articles. By contrast, authors in developing countries were likely to publish non-open access articles. These findings imply that authors’ choices depend on the funding systems and open access policies in individual countries. Consequently, open access may become a barrier to the dissemination of work for researchers who have financial difficulty choosing open access, although it enables everyone to access articles free of charge.
Designing incentive systems for participation in digital ecosystems—An integrated framework
Authors: Mihale-Wilson Cristina , Carl K. Valerie
Published: February 2024

Digital ecosystems are a highly relevant phenomenon in contemporary practice, offering unprecedented value creation opportunities for both companies and consumers. However, the success of these ecosystems hinges on their ability to establish the appropriate incentive systems that attract and engage diverse actors. Following the notion that setting “the right” incentives is essential for forming and growing digital ecosystems, this article presents an integrated framework that supports scholars and practitioners in identifying and orchestrating incentives into powerful incentive systems that encourage active participation and engagement. This framework emphasizes the importance of understanding how individuals and groups are motivated to engage in the ecosystem to incentivize them effectively. To demonstrate its applicability and value, we show its application in the context of an emergent digital ecosystem within the Smart Living domain.
Pharmacokinetic and safety analysis of biosimilar adalimumab in healthy volunteers in Bangladesh
Authors: Kulsum Umme , Azad Kasrina , Washif Mubasshir , Hossain Mohabbat , Sultana Nishat , Hossain Ismail , Ahmed Faez , Rahman Ridwanur , Muktadir Abdul , Muktadir Hasneen , Karim Mahbubul , Rahman Mohammad Mizanur , Hossain Md Shawkat , Monim Syed Abdul , Pandey Alex S. , Qadri Firdausi , Kawser Zannat
Published: February 2024

Aims

Advixa is a monoclonal antibody manufactured as a biosimilar to adalimumab (Humira, Abbvie Inc.). The key objectives of this study were to use a healthy population group to assess pharmacokinetics (PK) and safety similarity between Advixa and Humira in healthy participants and to quantify the effects on adalimumab PK and safety to assess the impact of treatment with Advixa.

Methods

A group of healthy participants selected by screening aged between 18 and 45 years. According to the randomization table, each participant was given Adalimumab (Advixa or Humira) in the inpatient facilities in a hospital and observed for 72 h. Several blood samples were collected from the participants at different time points up to day 64 to measure their Pharmacokinetics and biosimilarity. The study was registered at clinicaltrial.gov retrospectively.

Results

The serum concentration–time profiles for PK and safety were compared in this randomized, double-blinded study between Humira and Advixa. A review of the data for biosimilarity confirmed that these products are similar to each other regarding healthy participants. 90% confidence interval of the relative mean Cmax, AUC0-t, and AUCo-inf of the Advixa and Humira were found within the acceptance criteria. No differences in safety profiles were observed in these studies.

Conclusion

PK and safety are similar between Advixa and Humira in participants with healthy status demonstrated in this clinical trial (NCT05172817; Registration Date/Initial Release Date: 28/09/2021). Adalimumab PK was also similar to treatment with Humira and Advixa.
DeepMCGCN: Multi-channel Deep Graph Neural Networks
Authors: Meng Lei , Ye Zhonglin , Yang Yanlin , Zhao Haixing
Published: February 2024

Graph neural networks (GNNs) have shown powerful capabilities in modeling and representing graph structural data across various graph learning tasks as an emerging deep learning approach. However, most existing GNNs focus on single-relational graphs and fail to fully utilize the rich and diverse relational information present in real-world graph data. In addition, deeper GNNs tend to suffer from overfitting and oversmoothing issues, leading to degraded model performance. To deeply excavate the multi-relational features in graph data and strengthen the modeling and representation abilities of GNNs, this paper proposes a multi-channel deep graph convolutional neural network method called DeepMCGCN. It constructs multiple relational subgraphs and adopts multiple GCN channels to learn the characteristics of different relational subgraphs separately. Cross-channel connections are utilized to obtain interactions between different relational subgraphs, which can learn node embeddings richer and more discriminative than single-channel GNNs. Meanwhile, it alleviates overfitting issues of deep models by optimizing convolution functions and adding residual connections between and within channels. The DeepMCGCN method is evaluated on three real-world datasets, and the experimental results show that its node classification performance outperforms that of single-channel GCN and other benchmark models, which improves the modeling and representation capabilities of the model.
Representing Variability
Authors: Chetverikov Andrey , Kristjánsson Árni
Published: February 2024

The visual world is full of detail. This Element focuses on this variability in perception, asking how it affects performance in visual tasks and how the variability is represented by human observers. The authors highlight different methods for assessing representations of variability and suggest that understanding visual variability can be elusive when straightforward explicit methods are used, while more implicit methods may be better suited to uncovering such processing. The authors conclude that variability is represented in far more detail than previously thought and that this aspect of perception is vital for understanding the complexity of visual consciousness.
Multiple Streams and Policy Ambiguity
Authors: DeLeo Rob A. , Zohlnhöfer Reimut , Zahariadis Nikolaos
Published: February 2024

The last decade has seen a proliferation of research bolstering the theoretical and methodological rigor of the Multiple Streams Framework (MSF), one of the most prolific theories of agenda-setting and policy change. This Element sets out to address some of the most prominent criticisms of the theory, including the lack of empirical research and the inconsistent operationalization of key concepts, by developing the first comprehensive guide for conducting MSF research. It begins by introducing the MSF, including key theoretical constructs and hypotheses. It then presents the most important theoretical extensions of the framework and articulates a series of best practices for operationalizing, measuring, and analyzing MSF concepts. It closes by exploring existing gaps in MSF research and articulating fruitful areas of future research.
Modulational instability of the interacting electron whistlers and magnetosonic perturbations
Authors: Cheng Jiao-Jiao , Wang Fang-Ping , Li Zhong-Zheng , Duan Wen-Shan
Published: February 2024

A modulational instability of nonlinearly interacting electron whistlers and magnetosonic perturbations is studied in the present paper. For typical parameters, there is no modulational instability. However, modulational instability appears in special cases. For example, when the whistler wavenumber is small enough, there is modulational instability. Its growth rate decreases as the angle between the external magnetic field and the perturbed wave's direction increases, while it increases as the whistler wavenumber increases. It is also found that there is no modulational instability when the whistler wavenumber is larger than a critical value (

$k_0 > 0.05$

), in which the perturbed wave frequency increases as the angle between the external magnetic field and the perturbed wave's direction increases when the angle between the external magnetic field and the perturbed wave's direction is large enough. Whereas, the perturbed wave frequency first increases as the whistler wavenumber increases, reaches a peak value and then decreases as whistler wavenumber increases.