bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deconstructing Customer Value Propositions for the Circular Product-as-a-Service Business Model: A Case Study from the Textile Industry
Authors: Petänen Päivi , Sundqvist Henna , Antikainen Maria 
Published: February 2024

AbstractOffering products as a service is a way to implement circular economy principles in business models and promote sustainability. However, in many markets, the model is still in its infancy in terms of market maturity and lacks customer acceptance. More understanding is needed of how product-as-a-service companies can enhance and reconfigure their competitive position by proposing meaningful customer value. For this purpose, this study focuses on customer value propositions (CVPs) as a strategic management concept in the circular economy. The aim of the study is to outline a deconstruction framework for systematically identifying the strategically manageable components of CVPs in circular product-as-a-service business models. The framework establishes a link between the elements of circular product-as-a-service business models and competitive CVPs. The framework is developed and validated with seven product-as-a-service business cases in the textile and clothing industry context. The results of the study provide insights into how product-as-a-service companies in the textile field aim to differentiate, how they structure customer value by identifying customer benefits and sacrifices, and what kind of resources and capabilities are needed for competing in the circular economy context.
Do people value farmers markets: A spatial hedonic pricing model approach
Authors: Zheng Yanan , Yang Meng , An Henry , Qiu Feng 
Published: February 2024

AbstractFarmers markets can generate positive externalities by improving food access and negative externalities through pollution. The presence of both may influence people’s willingness to pay (WTP) for living nearby. This study employs spatial hedonic pricing models to estimate the WTP for living near farmers markets in Edmonton, Canada. We find an inverted U-shaped relationship between proximity to a farmers market and property values. Our results suggest that local governments might consider the economic impact of building new or relocating existing farmers markets on residential housing values, alongside the benefits of improved access to high-quality food sources.
On a self-embedding problem for self-similar sets
Authors: XIAO JIAN-CI 
Published: February 2024

AbstractLet
$K\subset {\mathbb {R}}^d$
be a self-similar set generated by an iterated function system
$\{\varphi _i\}_{i=1}^m$
satisfying the strong separation condition and let f be a contracting similitude with
$f(K)\subseteq K$
. We show that
$f(K)$
is relatively open in K if all
$\varphi _i$
share a common contraction ratio and orthogonal part. We also provide a counterexample when the orthogonal parts are allowed to vary. This partially answers a question of Elekes, Keleti and Máthé [Ergod. Th. & Dynam. Sys.30 (2010), 399–440]. As a byproduct of our argument, when
$d=1$
and K admits two homogeneous generating iterated function systems satisfying the strong separation condition but with contraction ratios of opposite signs, we show that K is symmetric. This partially answers a question of Feng and Wang [Adv. Math.222 (2009), 1964–1981].
Angle of repose of granulated ice: effect of wood ash
Authors: Harris William M. , Murdza Andrii , Schulson Erland M. 
Published: February 2024

Abstract
New experiments have revealed that the addition of a small amount of wood ash doubles the angle of repose of granulated ice at −10°C, but has little effect at −30°C. It is hypothesized that this behavior may be explained in terms of the freezing of water that is formed at the higher temperature through the reaction of salt within the ash.
Integrated Algorithm for High‐Resolution Crustal‐Scale Imaging Using Complementary OBS and Streamer Data
Authors: Zand Toktam , Górszczyk Andrzej 
Published: February 2024

AbstractWe present an integrated algorithm for high‐resolution crustal‐scale imaging utilizing long‐offset wide‐angle ocean‐bottom seismometer (OBS) data and short‐offset multichannel streamer (MCS) data. The algorithm adopts a two‐step imaging strategy, initially using the OBS data to enhance deep structure imaging and capture long‐wavelength features of the migration velocity. Subsequently, the MCS data are migrated to recover detailed short‐wavelength components and shallow structures using the migration velocity model modified by the OBS result. Both steps employ the least‐squares reverse time migration (LSRTM) method with appropriate regularization techniques. The algorithm is implemented using the Bregmanized operator splitting (BOS) approach, known for its efficiency and adaptability in handling non‐smooth regularization, such as total‐variation (TV) constraints. To improve computational efficiency, compressed sensing is employed to store incident wavefields at half their actual size and reconstruct them accurately when required. Convergence is expedited through the use of preconditioners and the Anderson acceleration method. The proposed algorithm is validated through large‐scale numerical examples, demonstrating its robustness even with an initially imprecise velocity model. Results showcase improved resolution and accuracy achieved through the integration of OBS and MCS data. This study offers a comprehensive framework for crustal‐scale imaging, addresses computational complexities, and provides enhanced imaging capabilities.
Global Precipitation Correction Across a Range of Climates Using CycleGAN
Authors: McGibbon J. , Clark S. K. , Henn B. , Kwa A. , Watt‐Meyer O. , Perkins W. A. , Bretherton C. S. 
Published: February 2024

AbstractAccurate precipitation simulations for various climate scenarios are critical for understanding and predicting the impacts of climate change. This study employs a Cycle‐generative adversarial network (CycleGAN) to improve global 3‐hr‐average precipitation fields predicted by a coarse grid (200 km) atmospheric model across a range of climates, morphing them to match their statistical properties with those of reference fine‐grid (25 km) simulations. We evaluate its performance on both the target climates and an independent ramped‐SST simulation. The translated precipitation fields remove most of the biases simulated by the coarse‐grid model in the mean precipitation climatology, the cumulative distribution function of 3‐hourly precipitation, and the diurnal cycle of precipitation over land. These results highlight the potential of CycleGAN as a powerful tool for bias correction in climate change simulations, paving the way for more reliable predictions of precipitation patterns across a wide range of climates.
Lightning Characteristics Associated With Storm Modes Observed During RELAMPAGO
Authors: Rocque Marquette N. , Deierling Wiebke , Rasmussen Kristen L. , Albrecht Rachel I. , Medina Bruno L. 
Published: February 2024

AbstractGlobal satellite studies show a maximum in deep convection and lightning downstream of the Andes in subtropical South America. The Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign was designed to investigate the physical processes that contribute to the rapid development of deep convection and mesoscale convective systems (MCSs) in Argentina. A lightning mapping array (LMA) was deployed to Argentina as part of RELAMPAGO to collect lightning observations from extreme storms in the region. This study combines lightning data from the LMA and the Geostationary Lightning Mapper onboard GOES‐16 with 1‐km gridded radar data to examine the electrical characteristics of a variety of convective storms throughout their life cycle observed during RELAMPAGO. Results from the full campaign show 48% of flashes are associated with deep convection that occurs along the eastern edge of the Sierras de Córdoba (SDC) overnight. These flashes are 65 km2 smaller on average compared to stratiform flashes, which occur most frequently 50–100 km east of the SDC in the early morning hours, consistent with the upscale growth of MCSs off the terrain. Analysis of the 13–14 December MCS shows that sharp increases in flash rates correspond to deep and wide convective cores that have high graupel and hail mass, 35‐dBZ volume, and ice water path. This work validates previous satellite studies of lightning in the region, but also provides higher spatial and temporal resolution information across the convective life cycle that has not been available in previous studies.
MarkerMap: nonlinear marker selection for single-cell studies
Authors: Gregory Wilson , Sarwar Nabeel , Kevrekidis George , Villar Soledad , Dumitrascu Bianca 
Published: February 2024

AbstractSingle-cell RNA-seq data allow the quantification of cell type differences across a growing set of biological contexts. However, pinpointing a small subset of genomic features explaining this variability can be ill-defined and computationally intractable. Here we introduce MarkerMap, a generative model for selecting minimal gene sets which are maximally informative of cell type origin and enable whole transcriptome reconstruction. MarkerMap provides a scalable framework for both supervised marker selection, aimed at identifying specific cell type populations, and unsupervised marker selection, aimed at gene expression imputation and reconstruction. We benchmark MarkerMap’s competitive performance against previously published approaches on real single cell gene expression data sets. MarkerMap is available as a pip installable package, as a community resource aimed at developing explainable machine learning techniques for enhancing interpretability in single-cell studies.
Advanced methods for insect nets: red-colored nets contribute to sustainable agriculture
Authors: Tokumaru Susumu , Tokushima Yoshiaki , Ito Shun , Yamaguchi Terumi , Shimoda Masami 
Published: February 2024

AbstractDevelopment of advanced pest control methods that do not rely on insecticides is an important issue for sustainable agriculture. Particularly with regards to micro pests that are not only highly resistant to various insecticides but also because we are running out of options for which insecticide to use against them, resulting in enormous economic damage worldwide. Here we report that the effectiveness of the conventional insect net can be greatly advanced by changing their color to red that helps significantly reduce pesticide use. We demonstrate the red effect using Onion thrips, Thrips tabaci a main vector of Iris Yellow Spot Virus (IYSV) and Tomato Spotted Wilt Virus (TSWV) that cause serious damage to various vegetables. New red nets succeeded in suppressing the invasion rates and damages (white spots on the leaves) in a Welsh onion greenhouse with minimum use of pesticides. We discuss how red nets are compatible with labor-saving, sustainable agriculture and the future potential of “optical pest control” based on insect color vision and its behavioral response.
Novel hybrid kepler optimization algorithm for parameter estimation of photovoltaic modules
Authors: Mohamed Reda , Abdel-Basset Mohamed , Sallam Karam M. , Hezam Ibrahim M. , Alshamrani Ahmad M. , Hameed Ibrahim A. 
Published: February 2024

AbstractThe parameter identification problem of photovoltaic (PV) models is classified as a complex nonlinear optimization problem that cannot be accurately solved by traditional techniques. Therefore, metaheuristic algorithms have been recently used to solve this problem due to their potential to approximate the optimal solution for several complicated optimization problems. Despite that, the existing metaheuristic algorithms still suffer from sluggish convergence rates and stagnation in local optima when applied to tackle this problem. Therefore, this study presents a new parameter estimation technique, namely HKOA, based on integrating the recently published Kepler optimization algorithm (KOA) with the ranking-based update and exploitation improvement mechanisms to accurately estimate the unknown parameters of the third-, single-, and double-diode models. The former mechanism aims at promoting the KOA’s exploration operator to diminish getting stuck in local optima, while the latter mechanism is used to strengthen its exploitation operator to faster converge to the approximate solution. Both KOA and HKOA are validated using the RTC France solar cell and five PV modules, including Photowatt-PWP201, Ultra 85-P, Ultra 85-P, STP6-120/36, and STM6-40/36, to show their efficiency and stability. In addition, they are extensively compared to several optimization techniques to show their effectiveness. According to the experimental findings, HKOA is a strong alternative method for estimating the unknown parameters of PV models because it can yield substantially different and superior findings for the third-, single-, and double-diode models.
The role of strategic visibility in shaping wayfinding behavior in multilevel buildings
Authors: Gath-Morad Michal , Grübel Jascha , Steemers Koen , Sailer Kerstin , Ben-Alon Lola , Hölscher Christoph , Aguilar Leonel 
Published: February 2024

AbstractIn this paper, we explore the mutual effect of prior background expectations and visibility afforded by the 3D configuration of the physical environment on wayfindingefficiencyandstrategyin multilevel buildings. We perform new analyses on data from 149 participants who performed six unaided and directed wayfinding tasks in virtual buildings with varying degrees of visibility. Our findings reveal that the interaction between visibility and prior background expectations significantly affects wayfinding efficiency and strategy during between-floor wayfinding tasks. We termed this interaction effectstrategic visibility, which emphasizes the importance of the strategic allocation of visibility towards actionable building elements in promoting efficient wayfinding and shaping wayfinding strategy. Our study highlights the significance ofstrategic visibilityin promoting inclusive and accessible built environments for neurodiversity. Finally, we provide an open-source dataset that can be used to develop and test new wayfinding theories and models to advance research in the emerging field of human-building interaction.
Analysis of the transplacental transmission of SARS CoV-2 virus and antibody transfer according to the gestational age at maternal infection
Authors: Lucot-Royer Louise , Nallet Camille , Vouga Manon , Puyraveau Marc , Mauny Frederic , Marty-Quinternet Solène , Bertholdt Charline , Bory Jean-Paul , Devalland Christine , Canaguier Margaux , Copolla Camille , Eszto Marie-Laure , Montoya Yohny , Roesch Marion , Reviron Sandrine , Riethmuller Didier , Rufenacht Emma , Simon Emmanuel , Mottet Nicolas 
Published: February 2024

AbstractTo quantify transplacental transmission of SARS-CoV-2 virus and antibody transfer in pregnant women and their newborns according to the gestational age at maternal infection. A prospective observational multicenter study including pregnant women with a positive RT-PCR or a positive serology for SARS-CoV-2 and compatible symptoms, from April to December 2020, in 11 French maternities. The study was designed to obtain a systematic collection of mother-infant dyad’s samples at birth. SARS-CoV-2 viral load was measured by RT-PCR. IgG and IgM antibodies against the SARS-CoV-2 spike protein were measured by enzyme-linked immunosorbent assay. Antibody concentrations and transplacental transfer ratios were analyzed according to the gestational age at maternal infection. The primary outcome was the rate of SARS CoV-2 materno-fetal transmission at birth. The secondary outcome was the quantification of materno-fetal antibody transfer. Maternal and neonatal outcomes at birth were additionally assessed. Among 165 dyads enrolled, one congenital infection was confirmed {n = 1 (0.63%) IC95% [0.02%; 3.48%]}. The average placental IgG antibody transfer ratio was 1.27 (IC 95% [0.69–2.89]). The transfer ratio increased with increasing time between the onset of maternal infection and delivery (P Value = 0.0001). Maternal and neonatal outcomes were reassuring. We confirmed the very low rate of SARS-CoV-2 transplacental transmission (< 1%). Maternal antibody transfer to the fetus was more efficient when the infection occurred during the first and second trimester of pregnancy.
Exponential super-twisting control for nonlinear systems with unknown polynomial perturbations
Authors: Liu Jianghua , Zhu Jiang , Khayati Karim , Zhong Dong , Jiang Jinguang 
Published: February 2024

AbstractThe study focuses on the control of nonlinear dynamic systems in the presence of parameter uncertainties, unmodeled dynamics, and external disturbances. The lumped perturbation is assumed to be bounded within a polynomial in the system state with the polynomial parameters and degrees unknown a priori such that it accommodates a quite wider range dynamic systems. Based on the studies in recent super-twisting algorithm designs and the idea from adaptive sliding mode control for nonlinear systems with uncertainties, we propose a novel adaptive super-twisting algorithm with exponential reaching law, or exponential super-twisting algorithm (ESTA), for the high-stability and acceptable accuracy control of the aimed nonlinear dynamics. The stability analysis and practical finite-time (PFT) convergence are proven using Lyapunov theory and an intuitive analysis of the control behaviour. Simulations are performed to compare the proposed ESTA with the existing super-twisting method and the traditional proportional integral differential control. The simulation results demonstrate the effectiveness of the proposed ESTA in terms of the fastest settling time and the smallest overshoot.
Gut microbiome signature of metabolically healthy obese individuals according to anthropometric, metabolic and inflammatory parameters
Authors: Lee Ho-Kyoung , Kim Nam-Eun , Shin Cheol Min , Oh Tae Jung , Yoon Hyuk , Park Young Soo , Kim Nayoung , Won Sungho , Lee Dong Ho 
Published: February 2024

AbstractIn this study, we investigated the characteristics of gut microbiome in the metabolically healthy obese (MHO) patients, and how they correlate with metabolic and inflammatory profiles. A total of 120 obese people without metabolic comorbidities were recruited, and their clinical phenotypes, metabolic and inflammatory parameters were analysed. The faecal microbial markers originating from bacterial cell and extracellular vesicle (EV) were profiled using 16S rDNA sequencing. The total study population could be classified into two distinct enterotypes (enterotype I: Prevotellaceae-predominant, enterotype II: Akkermansia/Bacteroides-predominant), based on their stool EV-derived microbiome profile. When comparing the metabolic and inflammatory profiles, subjects in enterotype I had higher levels of serum IL-1β [false discovery rate (FDR) q = 0.050] and had a lower level of microbial diversity than enterotype II (Wilcoxon rank-sum test p < 0.01). Subjects in enterotype I had relatively higher abundance of Bacteroidetes, Prevotellaceae and Prevotella-derived EVs, and lower abundance of Actinobacteria, Firmicutes, Proteobacteria, Akkermansia and Bacteroides-derived EVs (FDR q < 0.05). In conclusion, HMO patients can be categorised into two distinct enterotypes by the faecal EV-derived microbiome profile. The enterotyping may be associated with different metabolic and inflammatory profiles. Further studies are warranted to elucidate the long-term prognostic impact of EV-derived microbiome in the obese population.
Mental health disorders among medical students during the COVID-19 pandemic in the area with no mandatory lockdown: a multicenter survey in Tanzania
Authors: Bintabara Deogratius , Singo Joseph B. , Mvula Mathew , Jofrey Sichone , Shayo Festo K. 
Published: February 2024

AbstractThe COVID-19 pandemic brought about a major public health concern worldwide. It forced many countries to enforce lockdowns, leading to the closure of higher learning institutions. The abrupt shift in the lifestyle of students had a profound impact on their mental health. This study aims to determine the prevalence and factors associated with mental health conditions among university students in Tanzania during the COVID-19 pandemic. A sample of 425 students from six medical universities and colleges in Tanzania completed an online survey and was included in the analysis. The questionnaire consisted of validated Depression, Anxiety and Stress Scale—21 Items (DASS-21) questions (Cronbach’s alpha = 0.92) assessing the presence of mental health symptoms: depression, anxiety, and stress. Multivariable logistic regression models were fitted to explain the factors associated with mental health conditions. A P-value < 0.05 was considered statistically significant in all inferential analyses. The median age (interquartile range) of the participants was 24 (22–26). The prevalence of mental health conditions was 28.94%, 54.12%, and 15.06% for depression, anxiety, and stress, respectively, while the prevalence of having any mental health condition was 58.59%. In an adjusted regression model, being in the fourth and fifth years of study and living with a spouse were significantly associated with increased odds of depression: AOR = 5.99 (1.31–27.47), AOR = 5.52 (1.18–25.81), and AOR = 1.84 (1.08–3.15), respectively. Moreover, studying in private universities and living with a spouse were significantly associated with an increased likelihood of anxiety: AOR = 2.35 (1.72–2.76), and AOR = 2.32 (1.20–4.50), respectively. The likelihood of stress was only among participants studying in private universities; AOR = 2.90 (1.60–5.27). The study revealed alarmingly high rates of mental health conditions among medical students in Tanzania during the COVID-19 pandemic. The findings suggest the need for regular checkups for medical students regarding their mental health status. Additionally, it recommends that the government and other stakeholders establish mental health services within the universities for the effective prevention of the rising burden of mental health problems among universities in Tanzania and other countries with similar settings.
Battery deactivation with redox shuttles for safe and efficient recycling
Authors: Mikita Riho , Suzumura Akitoshi , Kondo Hiroki 
Published: February 2024

AbstractTo safely recycle spent lithium-ion batteries (LIBs), their deactivation as a pretreatment is essential. However, the conventional deactivation methods, mainly inducing an external short circuit, cannot be applied to LIBs with disconnected electrical circuits or Li deposited, despite their safety risk. Here, we propose a deactivation method using redox shuttles (RSs). The addition of an RS with redox potentials located between the two electrode potentials into a LIB electrochemically induces an internal short circuit with or without disconnected electrical circuits. A fully charged LIB discharges to approximately 0 V when a deactivation agent containing ferrocene or phenothiazine as an RS is added. Moreover, we demonstrate that RSs introduced into LIB can simultaneously dissolve Li deposited on the negative electrode surface and return it to the positive electrode as mobile ions. These characteristics of our method contribute to the improvement in safety and collection rate of Li in the recycling processes, promoting the sustainability of LIBs.