bluuebunny/crossref_metadata_2025_split huggingface dataset:
Suboptimal Rootzone Growth Prevents Long Island (NY) Salt Marshes from Keeping Pace with Sea Level Rise
Authors: Maher Nicole , Starke Adam 
Published: November 2023

AbstractSalt marsh habitat loss and conversion are well documented across the marine-coastal district of New York. Regionally, these losses are characterized by marsh edge erosion, ditch and creek widening, internal ponding, and conversion from irregularly flooded marsh to regularly flooded marsh and intertidal mudflats. These changes in horizontal extent and shifts in vegetation composition suggest that NY’s salt marshes may not be keeping pace with sea level rise. To evaluate elevation building processes, deep rod surface elevation tables, marker horizons, and shallow rod surface elevation tables (SET-MHs and shallow RSETs) were installed as a network across Long Island, NY. Contributions of surface, shallow subsurface, and deeper processes to overall elevation changes were observed from 2008 to 2022. Using a linear mixed model approach, surface accretion, shallow subsurface rootzone growth, and deeper below-ground processes were evaluated against regional sea level rise, nutrient loading, and marsh area trends. We found that marshes on Long Island are not keeping pace with sea level rise because they lack vertical elevation growth within the rootzone. Optimizing conditions for belowground growth of native salt marsh plants and preservation of organic matter within the peat matrix is key for restoring salt marshes to a positive elevation trajectory relative to sea level rise. Much like a retirement savings account, knowing whether our marshes are increasing in elevation is important, but understanding the full suite of deposits and withdrawals is critical for managing this valuable resource for the future.
On Estimation of the Effect Lag of Predictors and Prediction in a Functional Linear Model
Authors: Liu Haiyan , Aivaliotis Georgios , Kumar Vijay , Houwing-Duistermaat Jeanine 
Published: November 2023

AbstractWe propose a functional linear model to predict a functional response using multiple functional and longitudinal predictors and to estimate the effect lags of predictors. The coefficient functions are written as the expansion of a basis system (e.g. functional principal components, splines), and the coefficients of the basis functions are estimated via optimizing a penalization criterion. Then effect lags are determined by simultaneously searching on a prior designed grid mesh based on minimization of a proposed prediction error criterion. Mathematical properties of the estimated regression functions and predicted responses are studied. The performance of the method is evaluated by extensive simulations and a real data analysis application on chronic obstructive pulmonary disease (COPD).
Food system resilience measurement: principles, framework and caveats
Authors: Béné Christophe , Frankenberger Timothy R. , Nelson Suzanne , Constas Mark Alexander , Collins Gregory , Langworthy Mark , Fox Karyn 
Published: November 2023

AbstractThere is growing recognition that a better understanding of how food systems respond to crises is critical to build and protect the food security of local populations. But rigorous and reliable methods to measure food system resilience are still missing. In this paper, we build on the current literature to develop an analytical framework aimed at assessing the resilience of food systems at local level. The novel element of the analysis lies in the levels at which resilience is considered. Combining the individual actor level with the notion of 'emergent properties' of food systems, we argue that the overall resilience of food system results from processes that take place – and need to be measured – at both individual and system levels. The framework is structured around three components: (i) the mapping of the actors and the local food system; (ii) the assessment of the resilience of these actors and that of the food system, and (iii) the outcomes of this resilience, assessed in term of local population’s food security. For each of those components, indicators are proposed and the ways to collect them are discussed. The paper then presents the types of analyses that would be necessary to complete to gain a better understanding of the situation regarding the resilience of the local food system under consideration, including the analysis of “positive deviance” among food system actors. The paper concludes with a series of reflections about the caveats and challenges that one may face when attempting to assess food system resilience.
Drawing as a Pedagogical Resource for Immigrant Children’s Stories About Belonging
Authors: Bateman Amanda , Mitchell Linda 
Published: November 2023

AbstractThis article explores how drawing, facilitated by teacher prompts, provides opportunities for children to communicate their new connections in and sense of belonging with Aotearoa New Zealand, whilst sustaining connections with people and experiences from their home country. We use an ethnomethodological framework (Garfinkel, 1967) and a conversation analysis approach (Sacks et al., 1974) to explore spontaneous interactions between children and early childhood teachers around drawing activities. Four children, aged 3 and 4 years and who are from immigrant backgrounds, are the focus for the article. They participated with their families as case studies in research about the role of early childhood education in strengthening belonging for refugee and immigrant families (Mitchell et al., 2018). Families selected for case studies were of differing ethnicities, had come to Aotearoa New Zealand as refugees or immigrants, and wanted to participate in the research. The examples here involve the children restricting their talk to include only the characters they have drawn, demonstrating drawing as a unique resource which restricts possible unintentional ‘hijacking’ (Davis & Peters, 2008). Our findings demonstrate how touch and talk intertwine to co-construct a sequential unfolding of a story where characters are identified prior to the child telling about activities and location. As such, the drawings act as tangible resources which facilitate talk about an abstract concept such as belonging. ‘Slow pedagogies’ and a dedicated space for uninterrupted work with small groups were other facilitating features.
On the condition of Setting Independence
Authors: Müller Thomas , Placek Tomasz 
Published: November 2023

AbstractQuantum mechanics predicts non-local correlations in spatially extended entangled quantum systems, and these correlations are empirically very well confirmed. This raises philosophical questions of how nature could be that way, prompting the study of purported completions of quantum mechanics by hidden variables. Bell-type theorems connect assumptions about hidden variables with empirical predictions for the outcome of quantum correlation experiments. From among these assumptions, the Setting Independence assumption has received the least formal attention. Its violation is, however, central in the recent discussion about super-deterministic models for quantum correlation experiments. In this paper, we focus on the non-local modal correlations in the GHZ experiment. We model the introduction of hidden variables in the form of instruction sets via structure extensions in the framework of Branching Space-Times. This framework allows us to show in formal detail how the introduction of non-contextual instruction sets results in a specific violation of Setting Independence; a similar result is derived for contextual instruction sets. Our discussion provides additional reasons for foregoing the introduction of local hidden variables, and for accepting non-local quantum correlations as a resource provided by nature.
Anomaly detection in oil-producing wells: a comparative study of one-class classifiers in a multivariate time series dataset
Authors: Fernandes Wander , Komati Karin Satie , Assis de Souza Gazolli Kelly 
Published: November 2023

AbstractAnomalies in oil-producing wells can have detrimental financial implications, leading to production disruptions and increased maintenance costs. Machine learning techniques offer a promising solution for detecting and preventing such anomalies, minimizing these disruptions and expenses. In this study, we focused on detecting faults in naturally flowing offshore oil and subsea gas-producing wells, utilizing the publicly available 3W dataset comprising multivariate time series data. We conducted a comparison of different anomaly detection methods, specifically one-class classifiers, including Isolation Forest, One-class Support Vector Machine (OCSVM), Local Outlier Factor (LOF), Elliptical Envelope, and Autoencoder with feedforward and LSTM architectures. Our evaluation encompassed two variations: one with feature extraction and the other without, each assessed in both simulated and real data scenarios. Across all scenarios, the LOF classifier consistently outperformed its counterparts. In real instances, the LOF classifier achieved an F1-measure of 87.0% with feature extraction and 85.9% without. In simulated instances, the LOF classifier demonstrated superior performance, attaining F1 measures of 91.5% with feature extraction and 92.0% without. These results show an improvement over the benchmark established by the 3W dataset. Considering the more challenging nature of real data, the inclusion of feature extraction is recommended to improve the effectiveness of anomaly detection in offshore wells. The superior performance of the LOF classifier suggests that the boundaries of normal cases as a single class may be ill-defined, with normal cases better represented by multiple clusters. The statistical analysis conducted further reinforces the reliability and robustness of these findings, instilling confidence in their generalizability to a larger population. The utilization of individual classifiers per instance allows for tailored hyperparameter configurations, accommodating the specific characteristics of each offshore well.
A multi-task network approach for calculating discrimination-free insurance prices
Authors: Lindholm Mathias , Richman Ronald , Tsanakas Andreas , Wüthrich Mario V. 
Published: November 2023

AbstractIn applications of predictive modeling, such as insurance pricing, indirect or proxy discrimination is an issue of major concern. Namely, there exists the possibility that protected policyholder characteristics are implicitly inferred from non-protected ones by predictive models and are thus having an undesirable (and possibly illegal) impact on prices. A technical solution to this problem relies on building a best-estimate model using all policyholder characteristics (including protected ones) and then averaging out the protected characteristics for calculating individual prices. However, such an approach requires full knowledge of policyholders’ protected characteristics, which may in itself be problematic. Here, we address this issue by using a multi-task neural network architecture for claim predictions, which can be trained using only partial information on protected characteristics and produces prices that are free from proxy discrimination. We demonstrate the proposed method on both synthetic data and a real-world motor claims dataset, in which proxy discrimination can be observed. In both examples we find that the predictive accuracy of the multi-task network is comparable to a conventional feed-forward neural network, when the protected information is available for at least half of the insurance policies. However, the multi-task network has superior performance in the case when the protected information is known for less than half of the insurance policyholders.
Gene Expression Alterations in Peripheral Blood Following Sport-Related Concussion in a Prospective Cohort of Collegiate Athletes: A Concussion Assessment, Research and Education (CARE) Consortium Study
Authors: Simpson Edward , Reiter Jill L. , Ren Jie , Zhang Zhiqi , Nudelman Kelly N. , Riggen Larry D. , Menser Michael D. , Harezlak Jaroslaw , Foroud Tatiana M. , Saykin Andrew J. , Brooks Alison , Cameron Kenneth L. , Duma Stefan M. , McGinty Gerald , Rowson Steven , Svoboda Steven J. , Broglio Steven P. , McCrea Michael A. , Pasquina Paul F. , McAllister Thomas W. , Liu Yunlong ,   CARE Consortium Investigators, Campbell Darren , Jackson Jonathan , Houston Megan , Giza Christopher , Goldman Joshua , Guskiewicz Kevin , Mihalik Jason P. 
Published: November 2023

Abstract
Background
Molecular-based approaches to understanding concussion pathophysiology provide complex biological information that can advance concussion research and identify potential diagnostic and/or prognostic biomarkers of injury.

Objective
The aim of this study was to identify gene expression changes in peripheral blood that are initiated following concussion and are relevant to concussion response and recovery.

Methods
We analyzed whole blood transcriptomes in a large cohort of concussed and control collegiate athletes who were participating in the multicenter prospective cohort Concussion Assessment, Research, and Education (CARE) Consortium study. Blood samples were collected from collegiate athletes at preseason (baseline), within 6 h of concussion injury, and at four additional prescribed time points spanning 24 h to 6 months post-injury. RNA sequencing was performed on samples from 230 concussed, 130 contact control, and 102 non-contact control athletes. Differential gene expression and deconvolution analysis were performed at each time point relative to baseline.

Results
Cytokine and immune response signaling pathways were activated immediately after concussion, but at later time points these pathways appeared to be suppressed relative to the contact control group. We also found that the proportion of neutrophils increased and natural killer cells decreased in the blood following concussion.

Conclusions
Transcriptome signatures in the blood reflect the known pathophysiology of concussion and may be useful for defining the immediate biological response and the time course for recovery. In addition, the identified immune response pathways and changes in immune cell type proportions following a concussion may inform future treatment strategies.
A Crucial Step Toward Carbon Neutrality in Pyrometallurgical Reduction of Nickel Slag
Authors: Attah-Kyei Desmond , Sukhomlinov Dmitry , Tiljander Mia , Klemettinen Lassi , Taskinen Pekka , Jokilaakso Ari , Lindberg Daniel 
Published: November 2023

AbstractThis study aims at recovering valuable metals from nickel slag by employing pyrometallurgical techniques. A large amount of slag is generated during the nickel matte smelting. Nickel slag contains valuable elements such as copper, nickel, and cobalt, which can be recovered. Disposal of this slag results in loss of resources and may cause pollution of the environment. It is important to retrieve these metals for environmental and economic reasons. In this study, the slag was reacted with non-fossil reducing agents (biochar) which were produced from hydrolysis lignin and black pellet biomass by pyrolysis at 600 and 1200 °C, and with metallurgical coke for comparison. The reduction experiments were done at 1400 °C for 15, 30, and 60 min under inert gas atmosphere. The samples were quickly quenched and analyzed with Electron Probe X-ray Microanalysis. The results showed that the use of biochar resulted in faster reaction kinetics in the reduction process compared to coke. Moreover, thermodynamic modeling was also performed using Factsage to simulate equilibria with different amounts of biochar. The metal-to-slag distribution coefficient calculated from the results of thermodynamic modeling was consistent with experimental results.
Graphical Abstract
A Practical Approach to Estimate the Min-Entropy in PUFs
Authors: Frisch Christoph , Wilde Florian , Holzner Thomas , Pehl Michael 
Published: November 2023

AbstractHelper data algorithms reliably extract secrets from physical unclonable functions. The necessary helper data can leak information, though. One state-of-the-art approach to assess the remaining min-entropy is limited to homogeneous bias or correlation, not both. Another one extends this to only local bias without correlation but is limited to short code lengths. This work presents a new approach for determining the min-entropy based on convolving histograms. It provides a better bound and good approximation given arbitrary bias, more realistic correlation effects, and practically relevant code sizes. Experiments on real-world and synthetic data show the benefit of the new method compared with state-of-the-art ones. This work also facilitates a better understanding of how the error correction as post-processing impacts the min-entropy.
Green synthesis of silver nanoparticles using Moringa oleifera and its efficacy against gram-negative bacteria targeting quorum sensing and biofilms
Authors: Haris Zarrin , Ahmad Iqbal 
Published: November 2023

AbstractGram-negative pathogenic bacteria are the leading cause of high morbidity and mortality in humans globally. The majority of such pathogens has gained the status of multidrug resistance and requires the development of new anti-pathogenic agent. Moringa oleifera is a widely distributed and quickly proliferating medicinal plant, making it an easy source for extracting bioactive components. It is rich in bioactive compounds which can act as stabilizing and reducing agents during the synthesis of silver nanoparticles. It is well-recognized for its several medical benefits, including antibacterial action. As a result, it is an excellent option for synthesizing AgNPs with improved antibacterial characteristics. Considering the above properties, less explored Moringa oleifera was used for the green synthesis of nanoparticles. Targeting biofilms and virulence factors of Gram-negative bacteria by green synthesized metal nanoparticles is an alternative approach to combat antimicrobial resistance. Silver nanoparticles (MO-AgNPs) synthesized using Moringa oleifera leaf (MOL) extract were characterized using Ultraviolet–visible spectroscopy (UV–vis spectroscopy), Fourier-transform infrared spectroscopy (FTIR), Scanning electron microscopy-energy dispersive X-ray analysis (SEM–EDX), Transmission Electron Microscopy (TEM), and X-Ray Diffraction analysis (XRD). The absorption spectra of silver nanoparticles showed a band of absorption near 440 nm, associated with spherical silver nanoparticles. At sub-minimum inhibitory concentrations (sub-MICs), the MO-AgNPs inhibit the Quorum Sensing-mediated virulence factors and biofilm formation against three Gram-negative bacteria (Escherichia fergusonii, Serratia marcescens, and Chromobacterium violaceum). QS-mediated virulence factors in test bacteria were reduced by 80.67% (violacein), prodigiosin production (77.45%), exoprotease activity (76.02%), and swarming motility (86.5%). MO-AgNPs also demonstrated broad-spectrum antibiofilm activity against test bacteria, ranging from 77.95 to 82.4% inhibition. Microscopic analysis of biofilms showed significant structural change and inhibition. Our results demonstrate appreciable in vitro activity of MO-AgNPs against the selected pathogens, which could be used as an alternative therapeutic agent for treating infection caused by drug-resistant bacteria and preventing biofilm development by bacteria on medical devices and other surfaces.
Graphical abstract
Virginal breast hypertrophy – An uncommon breast disease
Authors: Ayandipo Omobolaji , Ajagbe Oluwasanmi , Obajimi Gbolahan , Idowu Olusola , Adeleye Amos , Ogundiran Temidayo 
Published: November 2023

Abstract

Introduction
Virginal breast hypertrophy VBH with the sobriquet “gigantomastia” is an uncommon condition with sporadic presentation usually in adolescence.

Case presentation
In this retrospective study, eight patients (three case summaries presented, while the clinicopathologic features of all the patients are presented in Table 1) were managed.

Discussion
The age range in this retrospective cohort study is 13–34 years and the series consists predominantly of teenagers, a third had bilateral disease, and the symptoms triad of mastalgia, cosmetic concerns, and psychosocial/esteem issues were present in all the patients. With a third consenting to surgical intervention.
We present what to our knowledge must be in the global literature, one of the few largest accruals of cases of gigantomastia, the VBH, seen over time in our surgical oncology practice.

Conclusion
VBH should be appraised along with other BBD to exclude malignancies and provide prompt and appropriate care whilst limiting complications. A multidisciplinary approach is particularly important and incorporating care for perceived low self-esteem cannot be over-emphasized.

Highlights
The Drivers of U.S. Meat Goat Prices: A Hedonic Analysis of Goat Auction Data
Authors: Khanal Binod , Dhoubhadel Sunil P. 
Published: November 2023

AbstractThis study employs a hedonic price model on slaughter goat auction data to examine the factors affecting U.S. meat goat prices. Wether-kids and wethers with superior muscularity receive high premiums in the auction markets. We find a non-linear relationship between average price and average weight, with the average price declining with increasing average weight within the reasonable weight range. The results reveal a seasonal effect on U.S. meat goat prices, primarily due to the seasonality of goat supply caused by goat breeding practices. Our results do not show a significant effect of the foreign-born population on meat goat auction prices.
Extremity Tourniquet Self-Application by Antarctica Zodiac Crew Members
Authors: Yánez Benñitez Carlos , Lorente-Aznar Teófilo , Labaka Idurre , Soteras Iñigo , Baselga Marta , Morishita Koji , Ribeiro Marcelo , Güemes Antonio 
Published: November 2023

Abstract
Search and rescue teams and Antarctic research groups use protective cold-water anti-exposure suits (AES) when cruising on Zodiacs. Extremity tourniquet (ET) self-application (SA) donned with AESs has not been previously studied. Our study therefore assessed the SA of 5 commercial ETs (CAT, OMNA, RATS, RMT, and SWAT-T) among 15 volunteers who donned these suits. Tourniquet‘s SA ability, ease of SA, tolerance, and tourniquet preference were measured. All ETs tested were self-applied to the upper extremity except for the SWAT, which was self-applied with the rest to the lower extremity. Ease- of- SA mean values were compared using the Friedman and Durbin-Conover post hoc tests (P < 0.001). Regarding the upper extremity, OMNA achieved the highest score of 8.5 out of 10, while RMT, and SWAT received lower scores than other options (P < 0.001). For lower extremities, SWAT was found to be inferior to other options (P < 0.01). Overall, OMNA was the best performer. The RATS showed significantly lower tolerance than the other groups in repeated- measures ANOVA with a Tukey post hoc test (P < 0.01). Additionally, out of the 5 ETs tested, 60% of subjects preferred OMNA. The study concluded that SA commercial ETs are feasible over cold-water anti-exposure suits in the Antarctic climate.