bluuebunny/crossref_metadata_2025_split huggingface dataset:
Staphylococcus aureus sequence type (ST) 45, ST30, and ST15 in the gut microbiota of healthy infants — persistence and population counts in relation to ST and virulence gene carriage
Authors: Nowrouzian Forough L. , Stadler Liselott Svensson , Östblom Anna , Lindberg Erika , Lina Gerard , Adlerberth Ingegerd , Wold Agnes E. 
Published: January 2023

AbstractStaphylococcus aureus colonizes the anterior nares, and also the gut, particularly in infants. S. aureus is divided into lineages, termed clonal complexes (CCs), which comprise closely related sequence types (STs). While CC30 and CC45 predominate among nasal commensals, their prevalence among gut-colonizing S. aureus is unknown. Here, 67 gut commensal S. aureus strains from 49 healthy Swedish infants (aged 3 days to 12 months) were subjected to multi-locus sequence typing. The STs of these strains were related to their virulence gene profiles, time of persistence in the microbiota, and fecal population counts. Three STs predominated: ST45 (22% of the strains); ST15 (21%); and ST30 (18%). In a logistic regression, ST45 strains showed higher fecal population counts than the others, independent of virulence gene carriage. The lower fecal counts of ST15 were linked to the carriage of fib genes (encoding fibrinogen-binding proteins), while those of ST30 were linked to fib and sea (enterotoxin A) carriage. While only 11% of the ST15 and ST30 strains were acquired after 2 months of age, this was true of 53% of the ST45 strains (p = 0.008), indicating that the former may be less fit for establishment in a more mature microbiota. None of the ST45 strains was transient (persisting < 3 weeks), and persistent ST45 strains colonized for significantly longer periods than persistent strains of other STs (mean, 34 vs 22 weeks, p = 0.04). Our results suggest that ST45 strains are well-adapted for commensal gut colonization in infants, reflecting yet-unidentified traits of these strains.
Thermal and Postural Effects on Fluid Mixing and Irrigation Patterns for Intraventricular Hemorrhage Treatment
Authors: Bilgi Coskun , Amlani Faisal , Wei Heng , Rizzi Nick , Pahlevan Niema M. 
Published: January 2023

AbstractIntraventricular hemorrhage is characterized by blood leaking into the cerebral ventricles and mixing with cerebrospinal fluid. A standard treatment method involves inserting a passive drainage catheter, known as an external ventricular drain (EVD), into the ventricle. EVDs have common adverse complications, including the occlusion of the catheter, that may lead to permanent neural damage or even mortality. In order to prevent such complications, a novel dual-lumen catheter (IRRAflow®) utilizing an active fluid exchange mechanism has been recently developed. However, the fluid dynamics of the exchange system have not been investigated. In this study, convective flow in a three-dimensional cerebral lateral ventricle with an inserted catheter is evaluated using an in-house lattice-Boltzmann-based fluid–solid interaction solver. Different treatment conditions are simulated, including injection temperature and patient position. Thermal and gravitational effects on medication distribution are studied using a dye simulator based on a recently-introduced (pseudo)spectral convection–diffusion equation solver. The effects of injection temperature and patient position on catheter performance are presented and discussed in terms of hematoma irrigation, vortical structures, mixing, and medication volume distribution. Results suggest that cold-temperature injections can increase catheter efficacy in terms of dye distribution and irrigation potential, both of which can be further guided by patient positioning.
Mindful Parenting Group Intervention for Parents of Children with Anxiety Disorders
Authors: Farley Robyn , de Diaz Natalja A. Nabinger , Emerson Lisa Marie , Simcock Gabrielle , Donovan Caroline , Farrell Lara J. 
Published: January 2023

AbstractParenting behaviour and rearing style contribute to the intergenerational relationship between parental and child anxiety. Current psychological interventions for child anxiety typically do not adequately address parental mental health, parenting behaviours or the parent–child relationship. The current pilot study examines the effectiveness of a mindful parenting intervention (MPI) for parents of young children with clinical anxiety. It was hypothesised that the intervention would be associated with improvements in parental stress, mental health, and mindfulness, and a reduction in child clinical anxiety symptoms. Twenty-one parents of children aged 3–7 years diagnosed with anxiety disorders participated in an 8-week group MPI program that aimed to increase their intentional moment to moment awareness of the parent–child relationship. Parental (anxiety, depression, hostility, stress, burden, mindfulness, mindful parenting) and child (anxiety diagnoses, anxiety severity, comorbidities) outcomes were assessed at pre- and post-intervention, and at 3-month follow-up. Parents reported a significant increase in mindful parenting and a significant reduction in parent–child dysfunctional interaction, but no change in mental health symptoms. There was a significant reduction in parent-rated child anxiety symptoms, severity of child anxiety diagnosis and number of comorbid diagnoses at post and 3-month follow-up. Limitations include a lack of waitlist control, small sample size, and participants were largely mothers, from intact families and highly educated. There was attrition of 43% and outcomes were predominantly self-report. MPIs offer a novel and potentially effective method of increasing mindful parenting, decreasing dysfunctional parent–child interactions, reducing parenting stress and might also be an effective early intervention for indirectly decreasing young children’s clinical anxiety symptoms. Larger-scale controlled trials of MPIs are needed.
Characterising patterns of COVID-19 and long COVID symptoms: evidence from nine UK longitudinal studies
Authors: Bowyer Ruth C. E. , Huggins Charlotte , Toms Renin , Shaw Richard J. , Hou Bo , Thompson Ellen J. , Kwong Alex S. F. , Williams Dylan M. , Kibble Milla , Ploubidis George B. , Timpson Nicholas J. , Sterne Jonathan A. C. , Chaturvedi Nishi , Steves Claire J. , Tilling Kate , Silverwood Richard J. ,   the CONVALESCENCE Study
Published: January 2023

AbstractMultiple studies across global populations have established the primary symptoms characterising Coronavirus Disease 2019 (COVID-19) and long COVID. However, as symptoms may also occur in the absence of COVID-19, a lack of appropriate controls has often meant that specificity of symptoms to acute COVID-19 or long COVID, and the extent and length of time for which they are elevated after COVID-19, could not be examined. We analysed individual symptom prevalences and characterised patterns of COVID-19 and long COVID symptoms across nine UK longitudinal studies, totalling over 42,000 participants. Conducting latent class analyses separately in three groups (‘no COVID-19’, ‘COVID-19 in last 12 weeks’, ‘COVID-19 > 12 weeks ago’), the data did not support the presence of more than two distinct symptom patterns, representing high and low symptom burden, in each group. Comparing the high symptom burden classes between the ‘COVID-19 in last 12 weeks’ and ‘no COVID-19’ groups we identified symptoms characteristic of acute COVID-19, including loss of taste and smell, fatigue, cough, shortness of breath and muscle pains or aches. Comparing the high symptom burden classes between the ‘COVID-19 > 12 weeks ago’ and ‘no COVID-19’ groups we identified symptoms characteristic of long COVID, including fatigue, shortness of breath, muscle pain or aches, difficulty concentrating and chest tightness. The identified symptom patterns among individuals with COVID-19 > 12 weeks ago were strongly associated with self-reported length of time unable to function as normal due to COVID-19 symptoms, suggesting that the symptom pattern identified corresponds to long COVID. Building the evidence base regarding typical long COVID symptoms will improve diagnosis of this condition and the ability to elicit underlying biological mechanisms, leading to better patient access to treatment and services.
Observation of the Coastal Areas, Estuaries and Deltas from Space
Authors: Laignel Benoit , Vignudelli Stefano , Almar Rafael , Becker Mélanie , Bentamy Abderrahim , Benveniste Jérôme , Birol Florence , Frappart Frédéric , Idier Deborah , Salameh Edward , Passaro Marcello , Menende Melisa , Simard Marc , Turki Emma Imen , Verpoorter Charles 
Published: January 2023

AbstractCoastal regions (including estuaries and deltas) are very complex environments with diverse hydrodynamic and bio-geomorphological contexts and with important socio-economic and ecological problems. These systems are among the most affected by human impact through urbanization and port activities, industrial and tourism activities. They are directly affected by the impact of climate change on sea level, storm surges frequency and strength, as well as recurrence of coastal river floods. A sustainable future for coastal zones depends on our capacity to implement systematic monitoring with focus on: (1) forcings affecting coastal zones at different spatio-temporal scales (sea level rise, winds and waves, offshore and coastal currents, tides, storm surges, river runoff in estuaries and deltas, sediment supply and transport, vertical land motions and land use); (2) morphological response (e.g., shoreline migration, topographical changes). Over the last decades, remote sensing observations have contributed to major advances in our understanding of coastal dynamics. This paper provides an overview of these major advances to measure the main physical parameters for monitoring the coastal, estuarine and delta environments and their evolution, such as the water level and hydrodynamics near the shoreline, water/sediment contact (i.e., shoreline), shoreline position, topography, bathymetry, vertical land motion, bio-physical characteristics of sediments, water content, suspended sediment, vegetation, and land use and land cover.
Challenges and strategies for the internationalization of higher education in low-income East African countries
Authors: Moshtari Mohammad , Safarpour Alireza 
Published: January 2023

AbstractAs it becomes more crucial to push the boundaries of science to develop new technologies and important global initiatives, internationalization can be instrumental in helping underdeveloped countries overcome challenges such as poverty, climate change, and educational inequalities. Higher education institutions have always faced challenges in the process of internationalization, which have occupied scholarly attention in recent decades, but little research has been conducted on the internationalization of higher education in less developed African countries. This qualitative study aims to shed light on the challenges of internationalization of higher education in low-income countries in East Africa. After reviewing the literature and interviewing academics, the obtained data were thematically analyzed. The results suggested 12 main challenges, which were classified into four major categories. The challenges include a lack of clear policies and guidelines; the inefficiency of the organizational structure of internationalization; financial, infrastructure, and equipment problems; weaknesses in scientific, skill, and language competences; cultural differences; non-reciprocal relationships; and a brain drain. Finally, strategies for responding to these challenges with regard to the internal and external environments of higher education institutions were proposed. Among the internal strategies of higher education institutions are the development of clear policies and visions, planning for the development of human resources, and sustainable budgeting for internationalization programs. External strategies emphasize the development of national policies and laws based on contextual and environmental conditions, as well as interaction and participation in international meetings to expand communication and use the scientific and economic capacities of international agencies and institutions.
The Methodological Quality and Intervention Fidelity of Randomised Controlled Trials Evaluating Social Skills Group Programs in Autistic Adolescents: A Systematic Review and Meta-analysis
Authors: Afsharnejad Bahareh , Black Melissa H. , Falkmer Marita , Bölte Sven , Girdler Sonya 
Published: January 2023

AbstractA systematic review and meta-analysis were utilised to explore the methodological quality, program fidelity, and efficacy of social skills group programs (SSGPs) aiming to support autistic adolescents in navigating their everyday social worlds. The study evaluated the methodological quality and theoretical fidelity of studies, with a random effect meta-analysis conducted to summarise the overall efficacy of SSGP and its effect on social communication and interaction, behavioural/emotional challenges, adaptive functioning, and autism characteristics. Although findings from the 18 identified studies indicated an adjusted medium overall effect with these programs successfully supporting autistic adolescents’ socialisation needs (g = 0. 60, p < 0.001), most studies demonstrated medium to low program fidelity despite their good methodological quality. Given the significant heterogeneity of SSGPs and variations in the design and measurement frameworks of efficacy studies, understanding the generalisability of the findings of this research is unclear.
Task allocation model for human-robot collaboration with variable cobot speed
Authors: Faccio Maurizio , Granata Irene , Minto Riccardo 
Published: January 2023

AbstractNew technologies, such as collaborative robots, are an option to improve productivity and flexibility in assembly systems. Task allocation is fundamental to properly assign the available resources. However, safety is usually not considered in the task allocation for assembly systems, even if it is fundamental to ensure the safety of human operator when he/she is working with the cobot. Hence, a model that considers safety as a constraint is here presented, with the aim to both maximize the productivity in a collaborative workcell and to promote a secure human robot collaboration. Indexes that consider both process and product characteristics are considered to evaluate the quality of the proposed model, which is also compared with one without the safety constraint. The results confirm the validity and necessity of the newly proposed method, which ensures the safety of the operator while improving the performance of the system.
Dislocation-based high-temperature plasticity of polycrystalline perovskite SrTiO3
Authors: Porz Lukas , Scherer Michael , Höfling Marion , Nakamura Atsutomo , Rheinheimer Wolfgang , Rödel Jürgen 
Published: January 2023

AbstractDislocation networks have been demonstrated to substantially enhance functional properties. As-sintered samples are virtually devoid of dislocations, new innovative techniques for introducing sufficiently high dislocation densities into polycrystalline ceramics are needed. While dislocation-based plasticity at high temperatures has been demonstrated for a large range of ceramic single crystals, plasticity in polycrystals is much less understood. Here, we demonstrate plastic strains in excess of several % based on dislocation motion in polycrystalline SrTiO3 at ≈ 1100 °C with 3.9 µm grain size. Ultra-high voltage electron microscopy reveals an associated increase in dislocation density by three orders of magnitude. Achievable strain rates are comparable to creep-based mechanisms and much less sensitive to applied stress than observed for metals. A specialized testing protocol allows quantification of the deformability via stress exponent, activation volume and activation enthalpy giving additional quantification. In conjunction with TEM images, the mechanical data gives insight into the underlying mechanisms.
Well-Posedness Properties for a Stochastic Rotating Shallow Water Model
Authors: Crisan Dan , Lang Oana 
Published: January 2023

AbstractIn this paper, we study the well-posedness properties of a stochastic rotating shallow water system. An inviscid version of this model has first been derived in Holm (Proc R Soc A 471:20140963, 2015) and the noise is chosen according to the Stochastic Advection by Lie Transport theory presented in Holm (Proc R Soc A 471:20140963, 2015). The system is perturbed by noise modulated by a function that is not Lipschitz in the norm where the well-posedness is sought. We show that the system admits a unique maximal solution which depends continuously on the initial condition. We also show that the interval of existence is strictly positive and the solution is global with positive probability.
Conditional Lipschitz Shadowing for Ordinary Differential Equations
Authors: Backes Lucas , Dragičević Davor , Onitsuka Masakazu , Pituk Mihály 
Published: January 2023

AbstractWe introduce the notion of conditional Lipschitz shadowing, which does not aim to shadow every pseudo-orbit, but only those which belong to a certain prescribed set. We establish two types of sufficient conditions under which certain nonautonomous ordinary differential equations have such a property. The first criterion applies to a semilinear differential equation provided that its linear part is hyperbolic and the nonlinearity is small in a neighborhood of the prescribed set. The second criterion requires that the logarithmic norm of the derivative of the right-hand side with respect to the state variable is uniformly negative in a neighborhood of the prescribed set. The results are applicable to important classes of model equations including the logistic equation, whose conditional shadowing has recently been studied. Several examples are constructed showing that the obtained conditions are optimal.
The Helping Networks of Transgender Women Living with HIV
Authors: Hill Miranda , Sevelius Jae , Sherman Athena D. F. , Balthazar Monique , Klepper Meredith , Radix Asa , Rebchook Greg , Hansen Nathan 
Published: January 2023

AbstractTransgender women living with HIV face significant barriers to healthcare that may be best addressed through community-centered interventions holistically focused on their HIV-related, gender-related, and other important needs. Community health ambassador (CHA) interventions (education and training programs designed to engage communities and community leaders in health promotion) may be an effective option, though information about the natural helping networks of this vulnerable population is too limited to inform the implementation of this approach. This study uses social network analysis to describe the natural helping networks of transgender women living with HIV, their help-seeking patterns for HIV-related, gender-related, and ancillary resources, and the characteristics of potential network ambassadors. From February to August 2019, transgender women living with HIV in the US (N = 231) participated a 30-min online survey asking them to describe their natural helping networks (N = 1054). On average, participants were embedded within natural helping networks consisting of 4–5 people. They were more likely to seek help from informal network members vs. formal service providers (p < .01), and from chosen family and partners/spouses (p < .05) above other social connections. Older network members (p < .01), other transgender women (p < .05), and those with whom they regularly engaged face-to-face (p < .01) (vs. social technology) were identified as potential network ambassadors for HIV-, gender-related, and other important issues. These findings suggest an opportunity to develop CHA interventions that leverage existing help networks and potential network ambassadors to promote equitable access to HIV, gender-affirming, and other crucial resources among this medically underserved group.
SECAP Switch—Defeating Topology Poisoning Attacks Using P4 Data Planes
Authors: Smyth Dylan , Scott-Hayward Sandra , Cionca Victor , McSweeney Sean , O’Shea Donna 
Published: January 2023

AbstractProgrammable networking is evolving from programmable control plane solutions such as OpenFlow-based software-defined networking (SDN) to programmable data planes such as P4-based SDN. To support the functionality of the SDN, the correct view of the network topology is required. However, multiple attacks aimed at topology poisoning have been demonstrated in SDNs. While several controller-centralised security solutions have been proposed to defeat topology poisoning attacks, some attacks e.g., the Data Plane ARP Cache Poisoning Attack and the relay-type Link Fabrication Attack are difficult to detect using a fully centralised security solution. In this paper, we present the Security-Aware Programmable (SECAP) Switch—a lightweight, in-network, P4-based security solution that is designed to prevent attacks that might otherwise evade control plane solutions. The SECAP switch verifies source address details contained within the headers of protocols commonly used to perform topology poisoning attacks. This function is supported by a novel variance-based anomaly detection solution to provide a layered defence. We demonstrate the ability of the SECAP switch to defeat topology poisoning attacks with minimal memory and processing overhead.
Efficient learning of large sets of locally optimal classification rules
Authors: Huynh Van Quoc Phuong , Fürnkranz Johannes , Beck Florian 
Published: January 2023

AbstractConventional rule learning algorithms aim at finding a set of simple rules, where each rule covers as many examples as possible. In this paper, we argue that the rules found in this way may not be the optimal explanations for each of the examples they cover. Instead, we propose an efficient algorithm that aims at finding the best rule covering each training example in a greedy optimization consisting of one specialization and one generalization loop. These locally optimal rules are collected and then filtered for a final rule set, which is much larger than the sets learned by conventional rule learning algorithms. A new example is classified by selecting the best among the rules that cover this example. In our experiments on small to very large datasets, the approach’s average classification accuracy is higher than that of state-of-the-art rule learning algorithms. Moreover, the algorithm is highly efficient and can inherently be processed in parallel without affecting the learned rule set and so the classification accuracy. We thus believe that it closes an important gap for large-scale classification rule induction.
The ‘Double Fuzzy Set’ Approach to Multidimensional Poverty Measurement: With a Focus on the Health Dimension
Authors: Handastya Nita , Betti Gianni 
Published: January 2023

AbstractIn more recent times, there is an increasing consensus in the field of development study to view poverty as a multidimensional deprivation beyond the more commonly used monetary perspective. Although the multidimensional poverty measurement is gaining more acceptance among policy makers, it is still based on the clear distinction between the poor and non-poor through an arbitrary threshold. One alternative to this shortcoming is offered by a multidimensional poverty measurement with a fuzzy-set approach in which it is possible to recognize deprivations as a matter of degree. The integrated fuzzy approach allows this possibility, although there is an unexplored opportunity of recognising that two or more dimensions can be attributed to a single item or attribute. This paper aims to contribute to this strand of research by introducing a ‘Double-Fuzzy’ approach. The methodology is applied to Tunisia using the Tunisian National Survey on Household Budget and Consumption (HBS) 2015.