bluuebunny/crossref_metadata_2025_split huggingface dataset:
Amyloid plaques and normal ageing have differential effects on microglial Ca2+ activity in the mouse brain
Authors: Izquierdo Pablo , Jolivet Renaud B. , Attwell David , Madry Christian 
Published: November 2023

AbstractIn microglia, changes in intracellular calcium concentration ([Ca2+]i) may regulate process motility, inflammasome activation, and phagocytosis. However, while neurons and astrocytes exhibit frequent spontaneous Ca2+ activity, microglial Ca2+ signals are much rarer and poorly understood. Here, we studied [Ca2+]i changes of microglia in acute brain slices using Fluo-4–loaded cells and mice expressing GCaMP5g in microglia. Spontaneous Ca2+ transients occurred ~ 5 times more frequently in individual microglial processes than in their somata. We assessed whether microglial Ca2+ responses change in Alzheimer's disease (AD) using AppNL−G−F knock-in mice. Proximity to Aβ plaques strongly affected microglial Ca2+ activity. Although spontaneous Ca2+ transients were unaffected in microglial processes, they were fivefold more frequent in microglial somata near Aβ plaques than in wild-type microglia. Microglia away from Aβ plaques in AD mice showed intermediate properties for morphology and Ca2+ responses, partly resembling those of wild-type microglia. By contrast, somatic Ca2+ responses evoked by tissue damage were less intense in microglia near Aβ plaques than in wild-type microglia, suggesting different mechanisms underlying spontaneous vs. damage-evoked Ca2+ signals. Finally, as similar processes occur in neurodegeneration and old age, we studied whether ageing affected microglial [Ca2+]i. Somatic damage-evoked Ca2+ responses were greatly reduced in microglia from old mice, as in the AD mice. In contrast to AD, however, old age did not alter the occurrence of spontaneous Ca2+ signals in microglial somata but reduced the rate of events in processes. Thus, we demonstrate distinct compartmentalised Ca2+ activity in microglia from healthy, aged and AD-like brains.
Factors specifying sex determination in maize
Authors: Guerrero-Méndez Cristina , Abraham-Juárez María Jazmín 
Published: November 2023

AbstractPlant architecture is an important feature for agronomic performance in crops. In maize, which is a monoecious plant, separation of floral organs to produce specific gametes has been studied from different perspectives including genetic, biochemical and physiological. Maize mutants affected in floral organ development have been key to identifying genes, hormones and other factors like miRNAs important for sex determination. In this review, we describe floral organ formation in maize, representative mutants and genes identified with a function in establishing sexual identity either classified as feminizing or masculinizing, and its relationship with hormones associated with sexual organ identity as jasmonic acid, brassinosteroid and gibberellin. Finally, we discuss the challenges and scopes of future research in maize sex determination.
Shallow groundwater characterisation and hydrograph classification in the coastal city of Ōtautahi/Christchurch, New Zealand
Authors: Bosserelle Amandine L. , Morgan Leanne K. , Dempsey David E. , Setiawan Irene 
Published: November 2023

AbstractGroundwater is present at shallow depth under many coastal low-lying cities. Despite the importance of protecting coastal urbanised areas from flooding and climate-change-induced sea-level rise, the effects of shallow groundwater fluctuations are rarely investigated. The aim of this study was to determine characteristics of shallow groundwater, including spatial and temporal trends in depths to groundwater and their relationship to natural and anthropogenic stressors. The study uses depth to groundwater measurements from a uniquely extensive and densely spaced monitoring network in Ōtautahi/Christchurch, New Zealand. Data-driven analysis approaches were applied, including spatial interpolation, autocorrelation, clustering, cross-correlation and trend analysis. These approaches are not commonly applied for groundwater assessments despite the potential for them to provide insights and information for city-wide systems. The comprehensive approach revealed discernible clusters and trends within the dataset. Responses to stresses such as rainfall events and stream flow were successfully classified using clustering analysis. The time series analysis indicated that in areas of shallow groundwater, low variation in levels occurred and this was also found using clustering. However, attributing some clusters to specific hydrogeological attributes or stressors posed challenges. The primary feature in hydrograph classification proved to be the proximity to tidal rivers and their correlation with tidal signals. These results highlight the value of using large datasets to characterise spatial and temporal variability of shallow groundwater in urban coastal settings and to assist with monitoring infrastructure planning in the face of future climate-change hazards.
A linear algebra perspective on the random multi-block ADMM: the QP case
Authors: Cipolla Stefano , Gondzio Jacek 
Published: November 2023

AbstractEmbedding randomization procedures in the Alternating Direction Method of Multipliers (ADMM) has recently attracted an increasing amount of interest as a remedy to the fact that the direct multi-block generalization of ADMM is not necessarily convergent. Even if, in practice, the introduction of such techniques could mitigate the diverging behaviour of the multi-block extension of ADMM, from the theoretical point of view, it can ensure just the convergence in expectation, which may not be a good indicator of its robustness and efficiency. In this work, analysing the strongly convex quadratic programming case from a linear algebra perspective, we interpret the block Gauss–Seidel sweep performed by the multi-block ADMM in the context of the inexact Augmented Lagrangian Method. Using the proposed analysis, we are able to outline an alternative technique to those present in the literature which, supported from stronger theoretical guarantees, is able to ensure the convergence of the multi-block generalization of the ADMM method.
Monotonicity Reasoning in the Age of Neural Foundation Models
Authors: Chen Zeming , Gao Qiyue 
Published: November 2023

AbstractThe recent advance of large language models (LLMs) demonstrates that these large-scale foundation models achieve remarkable capabilities across a wide range of language tasks and domains. The success of the statistical learning approach challenges our understanding of traditional symbolic and logical reasoning. The first part of this paper summarizes several works concerning the progress of monotonicity reasoning through neural networks and deep learning. We demonstrate different methods for solving the monotonicity reasoning task using neural and symbolic approaches and also discuss their advantages and limitations. The second part of this paper focuses on analyzing the capability of large-scale general-purpose language models to reason with monotonicity.
Utilising personas as a methodological approach to support prospective mathematics teachers’ adaptation and development of digital mathematics learning resources
Authors: Weinhandl Robert , Kleinferchner Lena Maria , Schobersberger Carina , Schwarzbauer Katharina , Houghton Tony , Lindenbauer Edith , Anđić Branko , Lavicza Zsolt , Hohenwarter Markus 
Published: November 2023

AbstractPersonas, initially originated in user experience research, are short and simplified representations of particular user groups, and this methodological approach has recently gained ground in educational research. This study aims to explore aspects of personas that may be beneficial for prospective mathematics teachers when they develop digital learning resources. To explore such aspects, we employed qualitative interviews, thinking-out-loud techniques, and jointly developed learning resources with prospective mathematics teachers, and analysed this diverse data with a combination of case study and grounded theory approaches. Consequently, we were able to identify the following essential aspects of using personas in our study: (A) personas as representatives of real people, (B) personas as planning & feedback tools for material development, (C) professionalisation of prospective mathematics teachers (by using personas), (D) differentiation/individualisation for personas through digital learning resources, and (E) motivational elements of digital mathematics learning resources. Based on our results, we concluded that using personas could broaden prospective mathematics teachers’ views on student characteristics and demands that may enable teachers to facilitate the development of differentiated and individualised digital mathematics learning resources.
The COVID-19 pandemic and house price convergence in Poland
Authors: Tomal Mateusz 
Published: November 2023

AbstractThe effect of the COVID-19 pandemic on price convergence in the housing market is largely unknown. This paper aims to assess the impact of the pandemic on the convergence of sales and rental housing prices. The residential markets in Polish voivodeship capitals were chosen as a case study. The convergence evaluation was based on a local linear version of the log t regression test, which allowed the estimation of a time-varying convergence speed parameter. The causal effect of the pandemic on convergence was examined using a Bayesian structural time series model. The study results revealed that the pandemic led to divergence in the primary sales housing market, growth convergence in the secondary sales housing market, and a weakening growth convergence in the rental housing market. Finally, this paper provides the R function logt that enables running the local linear and dummy variable log t regression tests.
Digital twins for breast cancer treatment – an empirical study on stakeholders’ perspectives on potentials and challenges
Authors: Konopik Jens , Wolf Larissa , Schöffski Oliver 
Published: November 2023

Abstract
Purpose
With 2.3 million diagnoses and 685,000 deaths annually, breast cancer is the most common cancer in women. The provision of necessary information throughout the whole patient journey is key to minimize the risk of breast cancer, to detect breast cancer as early as possible, and to aid the treatment process. Digital solutions provide abilities to holistically collect, transfer, and sophisticatedly analyze information. Specifically, digital twins in healthcare, as dynamic replicas of human bodies, are promising approaches for monitoring the condition of their patients and predicting tumor developments based on biometric data. However, the acceptance and adoption of such digital twin solutions in healthcare heavily depend on the individual stakeholders of the treatment process. This study aims to identify potentials and challenges of the introduction of digital twins in breast cancer applications from the involved stakeholders’ perspectives.

Methods
We conducted semi-structured interviews with 14 relevant stakeholders from the breast cancer treatment process. The interviews were then analyzed, based on the qualitative content analysis according to Mayring.

Results
The results show that stakeholders see great potential in digital twin solutions to further facilitate personalized medicine, efficiency increases, and scientific benefits. However, the sensitive nature of healthcare causes numerous potential challenges in the technical, regulatory, user interface, and the strategic domain.

Conclusions
The stakeholders unanimously agreed on the potential benefits of digital twins. However, existing systemic and individual stakeholder-level barriers hamper their introduction in breast cancer settings.
Characterization of particle size segregation and heterogeneity along the slopes of a waste rock pile using image analysis
Authors: Qiu Peiyong , Pabst Thomas 
Published: November 2023

AbstractLarge amounts of waste rock are produced during mining operations and often disposed of in large piles. Particle size segregation usually occurs during waste rock disposal, which can lead to high variations of particle size distribution (PSD) along the pile slope, increasing the risk for hydrogeotechnical instabilities. Determining segregation in situ is, therefore, critical to implement control measures and optimize deposition plans. However, characterizing PSD at field scale remains challenging because of the large dimensions of the pile, the instability of the blocks and the steep slopes. In this study, images, covering a 1400 m wide and 10 m high section of a waste rock pile, were taken and analyzed using image analysis to characterize segregation along the slope of the pile. PSD curves in different sections along the slope were determined and the segregation degree and characteristic diameters (e.g., D10, D50, D80,D95) were quantitatively compared. Results allowed to quantify segregation along the vertical direction of the pile, showing that segregation degree increased from − 0.77 ± 0.39 in the top (finer zone) to + 0.4 ± 0.14 in the bottom (coarser zone). Significant lateral heterogeneity was also observed with maximum diameters varying between 80 and 180 cm in the bottom section. Such segregation and lateral heterogeneity could induce significant variations of waste rock properties, with, for example, hydraulic conductivities varying by more than 2 orders of magnitude within the pile.
Comparing petrophysical properties and pore network characteristics of carbonate reservoir rocks using micro X-ray tomography imaging and microfacies analyses
Authors: Alatrash Hasan , Velledits Felicitász 
Published: November 2023

AbstractCarbonate rocks have complex pore structures as a result of sedimentological and diagenetic processes. We investigated the pore network of four carbonate rock samples originating from an oil well in Hungary. Two samples were from the productive part of the Sarmatian limestone, and the other two were from the dry interval. We employed X-ray computed tomography (micro-XCT) in combination with lab measurements and microfacies analysis. To achieve accurate X-ray image segmentation we investigated and compared several segmentation techniques, including entropy and clustering. We then employed the Naïve Bayes classifier and tenfold cross-validation to assess the accuracy of our results. Our study achieved high accuracy with the type-2 fuzzy entropy technique on various metrics, including precision and recall. The comparison between the measured helium porosity and image-derived porosity showed a close match. Micro-XCT measurements revealed connected pore structure in the productive interval, compared to isolated pores in the dry interval. Microfacies analyses indicated that both the rocks of the productive and dry intervals were deposited in a marine environment, but different diagenetic processes altered the sediment into productive and dry rocks, respectively. The diagenesis of the productive rocks occurred in a meteoric phreatic environment, where secondary pores were created (porosity enhancement). In contrast, the dry rocks underwent meteoric vadose and marine diagenesis, where all previously created pores were filled with cement (porosity destruction). Our study highlights the importance of accurately characterizing the pore network of carbonate rocks, which can aid in understanding reservoir properties and predicting fluid flow behavior.
Adrenergic receptors blockade alleviates dexamethasone-induced neurotoxicity in adult male Wistar rats: Distinct effects on β-arrestin2 expression and molecular markers of neural injury
Authors: Mohamed Rasha M. S. M. , Ahmad Ahmad Enssaf , Amin Dalia M. , Abdo Samar Ahmed , Ibrahim Islam A. A. E.-H. , Mahmoud Mona F. , Abdelaal Shimaa 
Published: November 2023

Abstract
Background
Dexamethasone-induced neurotoxicity has been previously reported. However, the molecular mechanisms are still not completely understood.

Objectives
The current work aimed to investigate the modulatory effects of α- and β-adrenergic receptors on dexamethasone-induced neurotoxicity in rats focused on changes in β-arrestin2 and molecular markers of neural injury in cerebral cortex.

Methods
Male Wistar rats were subcutaneously injected with dexamethasone (10 mg/kg/day) for 7 days to induce neural injury in the cerebral cortex. The experiment involved 5 groups: control, dexamethasone, carvedilol, propranolol, and doxazosin. In the last 3 groups, drugs were given 2 hours before dexamethasone injection. At the end of experiment, brain samples were collected for measurement of brain derived neurotrophic factor (BDNF), glial fibrillary acidic protein (GFAP), kinase activity of protein kinase B (Akt), diacylglycerol (DAG), α-smooth muscle actin (α-SMA), Smad3, β-amyloid and phospho-tau protein levels in addition to histopathological examination of brain tissue using hematoxylin-eosin, Nissl, and Sirius red stains. Moreover, β-arrestin2 levels in the cerebral cortex were measured using immunohistochemical examination.

Results
Dexamethasone slightly reduced brain weight and significantly decreased BDNF, Akt kinase activity and β-arrestin2 but markedly induced degeneration of cortical neurons and significantly increased GFAP, DAG, α-SMA, Smad3, β-amyloid and phospho-tau protein levels compared to controls. Carvedilol, propranolol, and doxazosin reversed all dexamethasone-induced molecular changes and slightly ameliorated the histopathological changes. Carvedilol significantly increased brain weight and β-arrestin2 levels compared to dexamethasone, propranolol, and doxazosin groups.

Conclusion
blocking α- and/or β-adrenergic receptors alleviate dexamethasone-induced neurotoxicity despite their distinct effects on β-arrestin2 levels in the cerebral cortex.

Graphical abstract
How and Why Does Corporate Reputation Moderate Mass Media News’ Impact On Market Value?
Authors: Guitart Ivan A. , Schwaiger Manfred , Eberhardt Johanna 
Published: November 2023

AbstractIn this study, we investigate whether corporate reputation reduces or amplifies mass media news’ impact on market value. We conceptualize reputation as comprising a prior knowledge, prominence, and favorability component. Additionally, we theorize about its role in moderating news’ effect on market value. Using 11 semesters’ data from 38 publicly listed German companies, we offer evidence of corporate reputation amplifying both negative and positive mass media news’ impact on market value. We further find that positive media mentions could reduce negative mentions’ negative impact up to the point that it loses its significance. Finally, our empirical analysis suggests that reputation’s moderating effect is mostly due to the favorability mechanism. Our results contribute to the literature by empirically assessing the role that reputation’s multiple dimensions play in shaping investors’ response to positive and negative mass media news. Our results also show that ensuring the media’s positive coverage of the company is an effective strategy to mitigate bursts of negative news’ negative consequences.
Users’ Visual Experience During Temporal Navigation in Forecast Weather Maps on Mobile Devices
Authors: Cybulski Paweł , Medyńska-Gulij Beata , Horbiński Tymoteusz 
Published: November 2023

AbstractThis study investigated the impact of graphical user interface (GUI) design on the efficiency and effectiveness of map-based tasks on mobile devices, using time-based weather data as a case study. Three different GUI designs (button-type, circle-type, and slidebar) were tested in a between-subjects design, with 50 participants completing a set of map-based tasks on each GUI design. The results showed that GUI design significantly affected the effectiveness of map-based tasks. Participants performed better at tasks involving the search for the highest and lowest temperature amplitudes on the button-type GUI whereas the circle-type GUI showed lower effectiveness for tasks involving the search for day temperatures. Analysis of the visual attention distribution based on fixation count revealed that different GUI designs led to different patterns of visual attention. The study highlights the importance of considering GUI design in the development of mobile map applications, particularly for map-based tasks involving time-based data. The study shows that separating the date from the time navigation panel reduces necessary visual focus on the GUI itself and is a valuable insight for future GUI design.
Observation on structural and optical features of new nanostructured lead-free methylammonium zinc or cobalt iodide perovskites for solar cells applications
Authors: Zeenelabden Hager H. , Elseman Ahmed Mourtada , El-Aasser Mostafa A. , Gad Nasr , Rashad Mohamed M. 
Published: November 2023

AbstractThe toxicity of lead-based halide perovskites has become a significant drawback to be employed in optoelectronic devices. Therefore, developing other environmentally friendly candidates with tunable optoelectronic properties for highly efficient solar cells is indispensable. Lead-free perovskite solar cells (PSCs) are promising to have a crucial role in large-scale commercial non-toxic photovoltaic devices. Here, the microstructure and optoelectronic properties of 2D halide perovskites without pb (CH3NH3)2BI4 (where B = Zn or Co) have been investigated for use in solar cells. The synthesized samples are characterized by X-ray diffraction (XRD), Raman spectroscopy, FT-IR, FESEM, and TEM. The variation in the optical and photoluminescence (PL) is recognized. The results indicate that (CH3NH3)2ZnI4 and (CH3NH3)2CoI4 crystals demonstrate a wide band gap of about 2.42 and 1.87 eV, respectively. A comparative study is presented for the optical properties of Zn- versus Co-based perovskites. It is noticed that Co is a better candidate than Zn to be a good replacement choice for Pb as Co-containing compounds have lower optical bandgap than Zn-containing compounds. PCBM is employed as a hole transport material, and PEDOT:PSS as an electron transport layer. The p-i-n PSCs are fabricated, and the electrical parameters are measured, obtaining power conversion efficiencies (PCE) of 0.73 and 2.45% for (CH3NH3)2ZnI4 and (CH3NH3)2CoI4, respectively. This work opens the door for further investigations to increase the PCE of both devices.
Innovation and entrepreneurship in dental curriculum: from practice to creativity in the face of pandemic
Authors: Jumlongkul Arnon 
Published: November 2023

AbstractCOVID-19 virus spread has resulted in the most dramatic changes for all of us. The purpose of this article is to develop a curriculum and share teaching experience in innovation and entrepreneurship for dental students during the pandemic, in order to help train future dentists. This article made extensive use of the adaptive design thinking model, which included brainstorming, classroom presentation, reflection, and revision. Sixth year dental students from the academic years 2020 and 2021 attended, with 26 and 29 students, respectively. Students of both classes were divided into five groups. Each group was tasked with creating an innovative research proposal related to clinical dental issues encountered during the pandemic. After a 6 h team-based discussion that included a 2-time presentation, all dental students were able to develop an innovation research proposal and present it in front of the class. This study reveals the process of developing dental curricula and sharing teaching experiences in innovation and entrepreneurship with dental students during a pandemic. Future research should compare traditional study, online teaching, and blended learning in innovation-related topics among dental students. The application of this novel method to multidisciplinary student teams as well as clinical subjects is also a challenge.