bluuebunny/crossref_metadata_2025_split huggingface dataset:
Formation tracking for interconnected networks with interaction silence and minimum total energy restriction
Authors: Yang Jianye , Dang Hongtao , Yu Zhiwei , Gao Jiuan , Li Junlong 
Published: March 2023

AbstractThe minimum‐energy formation tracking design and analysis problems for interconnected networks with distributed tracking protocols are addressed, where the effects of the total energy restriction and the interaction silence on the formation tracking are discussed, respectively. The key characteristic of this article is that the value of the energy restriction is required to be minimum, while the guaranteed‐cost tracking strategy and the energy‐constraint tracking strategy cannot ensure the minimum property of the total energy restriction. For interconnected networks without the interaction silence, sufficient conditions for minimum‐energy formation tracking are presented, whose effectiveness can be checked by the optimization procedure associated with the generalized eigenvalue method. Then, for interconnected networks with the interaction silence, by constructing the specific constraint associated with the maximum silent rate and two inhibition parameters, sufficient conditions for minimum‐energy formation tracking are proposed. Finally, numerical examples are shown to illustrate the efficacy of main results.
Drawing from Indigenous ontologies and practices to rethink European water policy
Authors: Linton Jamie , Pahl‐Wostl Claudia 
Published: March 2023

AbstractThe purpose of this article is to begin a discussion of how Indigenous ontologies and practices might be brought to bear on water policy and management in Europe. Such a discussion represents an ironic historical shift in the sense that these ontologies and practices have survived and continue to evolve in countries that have been characterized by European colonization (i.e., Australia, Canada, US, New Zealand, countries of Africa and South America, and not excluding the Sámi people of northern Europe). Increasingly research and policy interest has been directed toward the inclusion of Indigenous knowledge and perspectives in water governance in some of these places, especially Australia, Canada, and New Zealand. Here, we ask whether they might be a source of inspiration for rethinking the water policy in Europe. We argue that certain elements of Indigenous water knowledge and practices can be drawn from to reform European water policy on the ontological premise that people are part of nature and based on establishing and nurturing moral and legal relationships between water and people based on principles of respect and reciprocity.
Facial nerve palsy following parotid gland surgery: A machine learning prediction outcome approach
Authors: Chiesa‐Estomba Carlos M. , González‐García Jose A. , Larruscain Ekhiñe , Sistiaga Suarez Jon A. , Quer Miquel , León Xavier , Martínez‐Ruiz de Apodaca Paula , López‐Mollá Celia , Mayo‐Yanez Miguel , Medela Alfonso 
Published: March 2023

AbstractIntroductionMachine learning (ML)‐based facial nerve injury (FNI) forecasting grounded on multicentric data has not been released up to now. Three distinct ML models, random forest (RF), K‐nearest neighbor, and artificial neural network (ANN), for the prediction of FNI were evaluated in this mode.MethodsA retrospective, longitudinal, multicentric study was performed, including patients who went through parotid gland surgery for benign tumors at three different university hospitals.ResultsSeven hundred and thirty‐six patients were included. The most compelling aspects related to risk escalation of FNI were as follows: (1) location, in the mid‐portion of the gland, near to or above the main trunk of the facial nerve and at the top part, over the frontal or the orbital branch of the facial nerve; (2) tumor volume in the anteroposterior axis; (3) the necessity to simultaneously dissect more than one level; and (4) the requirement of an extended resection compared to a lesser extended resection. By contrast, in accordance with the ML analysis, the size of the tumor (>3 cm), as well as gender and age did not result in a determining favor in relation to the risk of FNI.DiscussionThe findings of this research conclude that ML models such as RF and ANN may serve evidence‐based predictions from multicentric data regarding the risk of FNI.ConclusionAlong with the advent of ML technology, an improvement of the information regarding the potential risks of FNI associated with patients before each procedure may be achieved with the implementation of clinical, radiological, histological, and/or cytological data.
The Bacterial Microbiome of the Coral Skeleton Algal Symbiont Ostreobium Shows Preferential Associations and Signatures of Phylosymbiosis
Authors: Pushpakumara B. L. D. Uthpala , Tandon Kshitij , Willis Anusuya , Verbruggen Heroen 
Published: March 2023

AbstractOstreobium, the major algal symbiont of the coral skeleton, remains understudied despite extensive research on the coral holobiont. The enclosed nature of the coral skeleton might reduce the dispersal and exposure of residing bacteria to the outside environment, allowing stronger associations with the algae. Here, we describe the bacterial communities associated with cultured strains of 5 Ostreobium clades using 16S rRNA sequencing. We shed light on their likely physical associations by comparative analysis of three datasets generated to capture (1) all algae associated bacteria, (2) enriched tightly attached and potential intracellular bacteria, and (3) bacteria in spent media. Our data showed that while some bacteria may be loosely attached, some tend to be tightly attached or potentially intracellular. Although colonised with diverse bacteria, Ostreobium preferentially associated with 34 bacterial taxa revealing a core microbiome. These bacteria include known nitrogen cyclers, polysaccharide degraders, sulphate reducers, antimicrobial compound producers, methylotrophs, and vitamin B12 producers. By analysing co-occurrence networks of 16S rRNA datasets from Porites lutea and Paragoniastrea australensis skeleton samples, we show that the Ostreobium-bacterial associations present in the cultures are likely to also occur in their natural environment. Finally, our data show significant congruence between the Ostreobium phylogeny and the community composition of its tightly associated microbiome, largely due to the phylosymbiotic signal originating from the core bacterial taxa. This study offers insight into the Ostreobium microbiome and reveals preferential associations that warrant further testing from functional and evolutionary perspectives.
Brownian Motion in an N-Scale Periodic Potential
Authors: Duncan A. B. , Duong M. H. , Pavliotis G. A. 
Published: March 2023

AbstractWe study the problem of Brownian motion in a multiscale potential. The potential is assumed to have $$N+1$$

N
+
1

scales (i.e. N small scales and one macroscale) and to depend periodically on all the small scales. We show that for nonseparable potentials, i.e. potentials in which the microscales and the macroscale are fully coupled, the homogenized equation is an overdamped Langevin equation with multiplicative noise driven by the free energy, for which the detailed balance condition still holds. This means, in particular, that homogenized dynamics is reversible and that the coarse-grained Fokker–Planck equation is still a Wasserstein gradient flow with respect to the coarse-grained free energy. The calculation of the effective diffusion tensor requires the solution of a system of N coupled Poisson equations.
Digitalization of Multistep Chemistry Exercises with Automated Formative Feedback
Authors: Eitemüller Carolin , Trauten Florian , Striewe Michael , Walpuski Maik 
Published: March 2023

AbstractFor various reasons, students receive less formative feedback at post-secondary institutions compared to secondary school. Considering feedback as one of the most important influencing factors on learning processes, formative feedback is a promising approach to improving students’ performances. In this context, new technologies, such as learning management systems (LMS) or intelligent tutoring systems (ITS), can make a valuable contribution to improving higher education teaching by providing automated and individualized error-specific just-in-time (JIT) feedback. However, the digitalization especially of paper-based open-ended tasks that can be used by LMS is currently still associated with a loss of quality. In this paper, we present an approach that allows us to transfer open-ended paper-based tasks in the field of chemistry into online tasks without losing quality and provide large university courses with automated and individualized error-specific JIT feedback. Results of a study of 238 first-year chemistry students reveal that the automated individualized error-specific JIT feedback had a significant positive influence on students’ performance.
Rotation to Sparse Loadings Using Lp\documentclass[12pt]{minimal}
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Authors: Liu Xinyi , Wallin Gabriel , Chen Yunxiao , Moustaki Irini 
Published: March 2023

Researchers have widely used exploratory factor analysis (EFA) to learn the latent structure underlying multivariate data. Rotation and regularised estimation are two classes of methods in EFA that they often use to find interpretable loading matrices. In this paper, we propose a new family of oblique rotations based on component-wise Lp\documentclass[12pt]{minimal}
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\begin{document}$$L^p$$\end{document} loss functions (0<p≤1)\documentclass[12pt]{minimal}
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\begin{document}$$(0 < p\le 1)$$\end{document} that is closely related to an Lp\documentclass[12pt]{minimal}
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\begin{document}$$L^p$$\end{document} regularised estimator. We develop model selection and post-selection inference procedures based on the proposed rotation method. When the true loading matrix is sparse, the proposed method tends to outperform traditional rotation and regularised estimation methods in terms of statistical accuracy and computational cost. Since the proposed loss functions are nonsmooth, we develop an iteratively reweighted gradient projection algorithm for solving the optimisation problem. We also develop theoretical results that establish the statistical consistency of the estimation, model selection, and post-selection inference. We evaluate the proposed method and compare it with regularised estimation and traditional rotation methods via simulation studies. We further illustrate it using an application to the Big Five personality assessment.
Shifted-windows transformers for the detection of cerebral aneurysms in microsurgery
Authors: Zhou Jinfan , Muirhead William , Williams Simon C. , Stoyanov Danail , Marcus Hani J. , Mazomenos Evangelos B. 
Published: March 2023

Abstract
Purpose
Microsurgical Aneurysm Clipping Surgery (MACS) carries a high risk for intraoperative aneurysm rupture. Automated recognition of instances when the aneurysm is exposed in the surgical video would be a valuable reference point for neuronavigation, indicating phase transitioning and more importantly designating moments of high risk for rupture. This article introduces the MACS dataset containing 16 surgical videos with frame-level expert annotations and proposes a learning methodology for surgical scene understanding identifying video frames with the aneurysm present in the operating microscope’s field-of-view.

Methods
Despite the dataset imbalance (80% no presence, 20% presence) and developed without explicit annotations, we demonstrate the applicability of Transformer-based deep learning architectures (MACSSwin-T, vidMACSSwin-T) to detect the aneurysm and classify MACS frames accordingly. We evaluate the proposed models in multiple-fold cross-validation experiments with independent sets and in an unseen set of 15 images against 10 human experts (neurosurgeons).

Results
Average (across folds) accuracy of 80.8% (range 78.5–82.4%) and 87.1% (range 85.1–91.3%) is obtained for the image- and video-level approach, respectively, demonstrating that the models effectively learn the classification task. Qualitative evaluation of the models’ class activation maps shows these to be localized on the aneurysm’s actual location. Depending on the decision threshold, MACSWin-T achieves 66.7–86.7% accuracy in the unseen images, compared to 82% of human raters, with moderate to strong correlation.

Conclusions
Proposed architectures show robust performance and with an adjusted threshold promoting detection of the underrepresented (aneurysm presence) class, comparable to human expert accuracy. Our work represents the first step towards landmark detection in MACS with the aim to inform surgical teams to attend to high-risk moments, taking precautionary measures to avoid rupturing.
Atmospheric dust intrusions from the peninsular region into the Northern Gulf of California: case study
Authors: Morales-Acuña Enrique , Santamaría-del-Ángel Eduardo , Linero-Cueto Jean 
Published: March 2023

AbstractThrough atmospheric transport, coming from the mainland, an important amount of dust arrives to surface waters of open-ocean regions and many coastal zones. Semi-arid and desert areas tend to act as important sources of dust. The Gulf of California (GC) is one of the most productive marginal seas of the world, and it is surrounded by the semi-arid deserts located in Baja California Peninsula, United States, and Sonora (Mexico). Dust fluxes coming from the BCP during the summer are relevant due to biological impact on the California Gulf. In the northern region of the BCP, meteorological events have not been well studied. These events are known in popular slang as "El Torito". The characterization of a dust event that originated in the Baja California Peninsula (BCP) on June 14, 2016, is presented. Meteorological variables (from North American Regional Reanalysis -NARR), daily sea surface temperature, and aerosol optical thickness (from MODIS) are used to explain the dust event genesis, are used. Results suggest that sea surface temperature fluctuations in the Pacific Ocean off the coast of the BCP generate changes in hydrometeorological variables (wind, relative humidity, and atmospheric pressure) that can give rise to dust events. The June 14 dust storm originates in the San Felipe desert and disperses aeolian to the northern Gulf of California, as shown by aerosol optical thickness images and trajectories simulated with the HYSPLIT model, which establishes vertical distributions with predominant heights between 0 and 500 m.
Modeling condensing flows of humid air in transonic nozzles
Authors: Hertwig Tim , Wittmann Tim , Wiśniewski Piotr , Friedrichs Jens 
Published: March 2023

AbstractThe ability to accurately model condensing flows is crucial for understanding such flows in many applications. Condensing flows of pure steam have been studied extensively in the past, and several droplet growth models have been derived. The rationale for the choice of growth models for condensation in humid air is less established. Furthermore, only a few validation cases for condensation in such flows exist. This paper aims to identify existing limitations of common droplet growth laws. The Hertz—Knudsen model is compared to heat-transfer-based models by Gyarmathy and Young, using an Euler—Lagrange approach in Ansys Fluent. For this, an adaption for Young’s growth law is introduced, allowing its application in condensation of different gas mixtures. The numerical model has been validated and applied to flows in nozzles and turbines in previous publications. The accuracy of the droplet growth models is investigated in transonic nozzle test cases. A case with pure steam and a case with humid air at two different humidity values are considered. Finally, the influence of humidity, Knudsen number, and droplet radius on the growth rate of each model is shown analytically. Flows at lower humidity values with longer condensation zones are shown to benefit from the higher sensitivity of the Hertz—Knudsen model to the mass fraction of water vapor in the flow. Heat-transfer-based models tend to overestimate condensation in such flows. However, the ability to empirically adapt the growth model by Young and its applicability in different Knudsen numbers results in good agreement with validation data over a wide range of cases.
Polyketides with potential bioactivities from the mangrove-derived fungus Talaromyces sp. WHUF0362
Authors: Lv Huawei , Su Haibo , Xue Yaxin , Jia Jia , Bi Hongkai , Wang Shoubao , Zhang Jinkun , Zhu Mengdi , Emam Mahmoud , Wang Hong , Hong Kui , Li Xing-Nuo 
Published: March 2023

AbstractMetabolites of microorganisms have long been considered as potential sources for drug discovery. In this study, five new depsidone derivatives, talaronins A-E (1–5) and three new xanthone derivatives, talaronins F–H (6–8), together with 16 known compounds (9–24), were isolated from the ethyl acetate extract of the mangrove-derived fungus Talaromyces species WHUF0362. The structures were elucidated by analysis of spectroscopic data and chemical methods including alkaline hydrolysis and Mosher’s method. Compounds 1 and 2 each attached a dimethyl acetal group at the aromatic ring. A putative biogenetic relationship of the isolated metabolites was presented and suggested that the depsidones and the xanthones probably had the same biosynthetic precursors such as chrysophanol or rheochrysidin. The antimicrobial activity assay indicated that compounds 5, 9, 10, and 14 showed potent activity against Helicobacter pylori with minimum inhibitory concentration (MIC) values in the range of 2.42–36.04 μmol/L. While secalonic acid D (19) demonstrated significant antimicrobial activity against four strains of H. pylori with MIC values in the range of 0.20 to 1.57 μmol/L. Furthermore, secalonic acid D (19) exhibited cytotoxicity against cancer cell lines Bel-7402 and HCT-116 with IC50 values of 0.15 and 0.19 μmol/L, respectively. The structure–activity relationship of depsidone derivatives revealed that the presence of the lactone ring and the hydroxyl at C-10 was crucial to the antimicrobial activity against H. pylori. The depsidone derivatives are promising leads to inhibit H. pylori and provide an avenue for further development of novel antibiotics.
Decreased antimicrobial prescribing rate following academic detailing of resident physicians in outpatient clinic
Authors: Andrews Shannon L. , Gravely Amy A. , Beaudoin Amanda , Rothenberger Meghan K. , Drekonja Dimitri M. 
Published: March 2023

Abstract
Among 37 internal-medicine resident physicians assigned to our outpatient clinic at Minneapolis Veterans’ Affairs Health Care System (MVAHCS) on July 1, 2017, we designed a pre- and postintervention observational study. Our results show that in-person academic detailing around outpatient antimicrobial selection was associated with a decrease in outpatient antimicrobial prescriptions in a group of high-prescribing resident physicians.
El clientelismo en Paraguay: ¿Compra de votos o compra de participación electoral?
Authors: Dosek Tomás 
Published: March 2023

ResumenEl clientelismo en Paraguay es generalizado y socialmente aceptado tanto por los políticos como por la ciudadanía, pero relativamente poco estudiado por la literatura comparada. Este artículo ofrece una descripción cualitativa de los principales actores y lógicas del funcionamiento en los vínculos clientelares entre políticos y la ciudadanía en Paraguay, enfocándose tanto en las relaciones de largo plazo como en las prácticas durante los períodos electorales. El artículo argumenta que el clientelismo en Paraguay está anclado en las estructuras partidarias territoriales, la identificación ciudadana con los principales partidos políticos y en las redes de brokers con vínculos con los vecinos. Durante los períodos electorales los intercambios particularistas se intensifican y culminan con la compra de participación electoral durante el día de las elecciones. El artículo muestra que la parte relacional y electoral del clientelismo en el caso paraguayo son inseparables, condicionando la primera a la segunda. La compra de participación electoral es una práctica que se deriva de relaciones cultivadas a lo largo del tiempo. La investigación está basada en entrevistas a profundidad y trabajo de campo en cuatro ciudades de la zona metropolitana de Asunción.
A note on grid homology in lens spaces: coefficients and computations
Authors: Celoria Daniele 
Published: March 2023

AbstractWe present a combinatorial proof for the existence of the sign-refined grid homology in lens spaces and a self-contained proof that
$\partial _{\mathbb{Z}}^2 = 0$
. We also present a Sage programme that computes
$\widehat{\mathrm{GH}} (L(p,q),K;\mathbb{Z})$
and provide empirical evidence supporting the absence of torsion in these groups.
Impacts of passive elephant rewilding: assessment of human fatalities in India
Authors: Natarajan Lakshminarayanan , Nigam Parag , Pandav Bivash 
Published: March 2023

SummaryElephant ranges in Asia overlap with human-use areas, leading to frequent and often negative two-way interactions, a fraction of which result in human fatalities. Minimizing such negative interactions rests on gaining a mechanistic understanding of their patterns and underlying processes. In Chhattisgarh (India), a rewilding population of 250–300 elephants that have recently expanded their range from neighbouring states through dispersal has been causing annual losses of >60 human lives. Using logistic regression models, we examined the influences of eight plausible predictors of the occurrence of elephant-related human fatality incidents. We found that 70% of incidents occurred in areas with high-intensity habitat use by elephants; the other 30% were in areas of intermediate and sporadic elephant habitat use. The probability of human fatalities was high along the roads connecting settlements and in areas with frequent house break-ins by elephants, and this probability was also affected by the spatial geometry of forest patches. Immediate practical options to minimize fatal interactions include community-based early-warning systems and the use of portable barriers around settlements. Judicious landscape-level land-use planning aimed at maintaining the resilience of remnant intact elephant habitats will be critical to preventing the dispersal of elephants into suboptimal habitats, which can create complex conflict situations.
Personality Is Associated with Driving Avoidance in the Canadian Longitudinal Study on Aging (CLSA)
Authors: Stinchcombe Arne , Hopper Shawna , Hammond Nicole G. , Weaver Bruce , Bédard Michel 
Published: March 2023

AbstractAs individuals age and become aware of changes in their driving capabilities, they are more likely to self-regulate their driving by avoiding certain driving situations (i.e., night driving, rush hour traffic, etc.). In this paper, we sought to examine the correlates of situational driving avoidance with a particular emphasis on the roles of personality traits, gender, and cognition within a large sample of mid-life and older adults from the Canadian Longitudinal Study on Aging (CLSA). Our findings show that women of older ages tend to report more driving avoidance and that personality traits, specifically extraversion, emotional stability, and openness to experience, may reduce driving avoidance. A negative association was also found between cognition and driving avoidance, such that individuals with higher cognition reported less driving avoidance.