bluuebunny/crossref_metadata_2025_split huggingface dataset:
The existential risk space of climate change
Authors: Huggel Christian , Bouwer Laurens M. , Juhola Sirkku , Mechler Reinhard , Muccione Veruska , Orlove Ben , Wallimann-Helmer Ivo 
Published: September 2022

AbstractClimate change is widely recognized as a major risk to societies and natural ecosystems but the high end of the risk, i.e., where risks become existential, is poorly framed, defined, and analyzed in the scientific literature. This gap is at odds with the fundamental relevance of existential risks for humanity, and it also limits the ability of scientific communities to engage with emerging debates and narratives about the existential dimension of climate change that have recently gained considerable traction. This paper intends to address this gap by scoping and defining existential risks related to climate change. We first review the context of existential risks and climate change, drawing on research in fields on global catastrophic risks, and on key risks and the so-called Reasons for Concern in the reports of the Intergovernmental Panel on Climate Change. We also consider how existential risks are framed in the civil society climate movement as well as what can be learned in this respect from the COVID-19 crisis. To better frame existential risks in the context of climate change, we propose to define them as those risks that threaten the existence of a subject, where this subject can be an individual person, a community, or nation state or humanity. The threat to their existence is defined by two levels of severity: conditions that threaten (1) survival and (2) basic human needs. A third level, well-being, is commonly not part of the space of existential risks. Our definition covers a range of different scales, which leads us into further defining six analytical dimensions: physical and social processes involved, systems affected, magnitude, spatial scale, timing, and probability of occurrence. In conclusion, we suggest that a clearer and more precise definition and framing of existential risks of climate change such as we offer here facilitates scientific analysis as well societal and political discourse and action.
A Novel Method for Smart Fire Detection Using Acoustic Measurements and Machine Learning: Proof of Concept
Authors: Martinsson John , Runefors Marcus , Frantzich Håkan , Glebe Dag , McNamee Margaret , Mogren Olof 
Published: September 2022

AbstractFires are a major hazard resulting in high monetary costs, personal suffering, and irreplaceable losses. The consequences of a fire can be mitigated by early detection systems which increase the potential for successful intervention. The number of false alarms in current systems can for some applications be very high, but could be reduced by increasing the reliability of the detection system by using complementary signals from multiple sensors. The current study investigates the novel use of machine learning for fire event detection based on acoustic sensor measurements. Many materials exposed to heat give rise to acoustic emissions during heating, pyrolysis and burning phases. Further, sound is generated by the heat flow associated with the flame itself. The acoustic data collected in this study is used to define an acoustic sound event detection task, and the proposed machine learning method is trained to detect the presence of a fire event based on the emitted acoustic signal. The method is able to detect the presence of fire events from the examined material types with an overall F-score of 98.4%. The method has been developed using laboratory scale tests as a proof of concept and needs further development using realistic scenarios in the future.
Equivalence checking and intersection of deterministic timed finite state machines
Authors: Bresolin Davide , El-Fakih Khaled , Villa Tiziano , Yevtushenko Nina 
Published: September 2022

AbstractThere has been a growing interest in defining models of automata enriched with time, such as finite automata extended with clocks (timed automata). In this paper, we study deterministic timed finite state machines (TFSMs), i.e., finite state machines with a single clock, timed guards and timeouts which transduce timed input words into timed output words. We solve the problem of equivalence checking by defining a bisimulation from timed FSMs to untimed ones and vice versa. Moreover, we apply these bisimulation relations to build the intersection of two timed finite state machines by untiming them, intersecting them and transforming back to the timed intersection. It is known that many problems like inclusion and equivalence checking are undecidable for timed automata. Our results show that TFSMs correspond to a decidable subclass of timed automata that admits a restricted form of $$\varepsilon $$
ε
-transitions (i.e., timeouts) where most of the relevant problems like equivalence and intersection are decidable.
Students Do Not Always Mean What We Think They Mean: A Questioning Strategy to Elicit the Reasoning Behind Unexpected Causal Patterns in Student System Models
Authors: Stephens A. Lynn , Roderick Steven , Shin Namsoo , Damelin Daniel 
Published: September 2022

AbstractAn ability to engage in system thinking is necessary to understand complex problems. While many pre-college students use system modeling tools, there is limited evidence of student reasoning about causal relationships that interact in diverging and converging chains, and how these affect system behavior. A chemistry unit on gas phenomena was implemented in two successive years with 73 high school students. Although the phenomena could be explained with simple linear causal reasoning, many student models included surprising and problematic causal chains and non-linear patterns. Commonly, discussion about student models in classrooms and interviews focuses on individual causal relationships. However, in our experience, this can fail to bring to the surface conceptual issues that result from the combination of two or more relationships. Using interview data from 19 students, we looked for instances where students explained their conceptions and we identified questioning strategies that elicited these explanations. Questions that appeared most productive asked about distal relationships between nonadjacent variables in model substructures of three to four variables. In response to these questions, eight students expressed their thinking about relationship combinations, including unexpected reasoning that had not emerged during classroom instruction. Using exemplars from three interviews, we argue that students engage in complex causal reasoning that may be implicit and unexpected, and that if this is not recognized, it cannot be responded to during instruction. We suggest that using model substructures as a mutual visual referent along with a simple questioning strategy shows promise for helping students make their causal reasoning explicit.
The Association Between Individualised Religiosity and Health Behaviour in Denmark: Are Social Networks a Mediating Factor?
Authors: Svensson Nanna Herning , Larrabee Sonderlund Anders , Wehberg Sonja , Hvidt Niels Christian , Søndergaard Jens , Thilsing Trine 
Published: September 2022

AbstractThe present study investigates whether social networks mediate the well-established positive association between religiosity and health behaviour. Most research has focused on traditional public religiosity (e.g. regular church attendance). This study, however, focuses on the Danish population in which non-traditional and private religiosity is common. We utilise data from the Danish population-based project, Early Detection and Prevention. Our results suggest that religiosity is linked to health behaviour; however, this association is not mediated by social network.
Interplay between local and landscape-scale effects on the taxonomic, functional and phylogenetic diversity of aerial insectivorous neotropical bats
Authors: López-Baucells Adrià , Rowley Sarah , Rocha Ricardo , Bobrowiec Paulo E. D. , Palmeirim Jorge M. , Farneda Fábio Z. , Meyer Christoph F. J. 
Published: September 2022

Abstract
Context
Human-modified landscapes are globally ubiquitous. It is critical to understand how habitat loss and fragmentation impact biodiversity from both a local habitat context and landscape-scale perspective to inform land management and conservation strategies.

Objectives
We used an experimentally fragmented landscape in the Brazilian Amazon to investigate variation in aerial insectivorous bat diversity in response to local habitat and wider landscape characteristics, applying a multiscale approach.

Methods
We conducted bat acoustic surveys at 33 sites, comprising old secondary forests and fragments of primary forest. Taxonomic, functional and phylogenetic diversity facets were calculated within a Hill numbers framework. We analysed responses to fragment size, interior-edge-matrix gradients, as well as local vegetation structure, continuous forest cover, edge density and patch density across five spatial scales (0.5−3 km) surrounding detector locations.

Results
Compared with continuous forest, secondary forest matrix around the smallest fragments harboured lower diversity. The overall negative effect of the matrix became less pronounced with increasing fragment size. In contrast, forest edges generally contained higher taxonomic, functional and phylogenetic diversity. We found subtle scale-sensitive associations for functional diversity, responding positively to forest cover (at the 1 km scale) and negatively to edge (1 km scale) and patch density (2.5 km scale).

Conclusions
Despite a low-contrast matrix of tall secondary forest surrounding fragments after ~ 30 years of forest recovery, aerial insectivorous bat diversity is not comparable to continuous primary forest. Assemblage functional diversity responds to compositional and configurational landscape characteristics at scales deserving further evaluation at guild and species level.
LADDER: Latent boundary-guided adversarial training
Authors: Zhou Xiaowei , Tsang Ivor W. , Yin Jie 
Published: September 2022

AbstractDeep Neural Networks (DNNs) have recently achieved great success in many classification tasks. Unfortunately, they are vulnerable to adversarial attacks that generate adversarial examples with a small perturbation to fool DNN models, especially in model sharing scenarios. Adversarial training is proved to be the most effective strategy that injects adversarial examples into model training to improve the robustness of DNN models against adversarial attacks. However, adversarial training based on the existing adversarial examples fails to generalize well to standard, unperturbed test data. To achieve a better trade-off between standard accuracy and adversarial robustness, we propose a novel adversarial training framework called LAtent bounDary-guided aDvErsarial tRaining (LADDER) that adversarially trains DNN models on latent boundary-guided adversarial examples. As opposed to most of the existing methods that generate adversarial examples in the input space, LADDER generates a myriad of high-quality adversarial examples through adding perturbations to latent features. The perturbations are made along the normal of the decision boundary constructed by an SVM with an attention mechanism. We analyze the merits of our generated boundary-guided adversarial examples from a boundary field perspective and visualization view. Extensive experiments and detailed analysis on MNIST, SVHN, CelebA, and CIFAR-10 validate the effectiveness of LADDER in achieving a better trade-off between standard accuracy and adversarial robustness as compared with vanilla DNNs and competitive baselines.
Astrocyte Responses to Complement Peptide C3a are Highly Context-Dependent
Authors: Pekna Marcela , Siqin Sumen , de Pablo Yolanda , Stokowska Anna , Torinsson Naluai Åsa , Pekny Milos 
Published: September 2022

AbstractAstrocytes perform a range of homeostatic and regulatory tasks that are critical for normal functioning of the central nervous system. In response to an injury or disease, astrocytes undergo a pronounced transformation into a reactive state that involves changes in the expression of many genes and dramatically changes astrocyte morphology and functions. This astrocyte reactivity is highly dependent on the initiating insult and pathological context. C3a is a peptide generated by the proteolytic cleavage of the third complement component. C3a has been shown to exert neuroprotective effects, stimulate neural plasticity and promote astrocyte survival but can also contribute to synapse loss, Alzheimer’s disease type neurodegeneration and blood–brain barrier dysfunction. To test the hypothesis that C3a elicits differential effects on astrocytes depending on their reactivity state, we measured the expression of Gfap, Nes, C3ar1, C3, Ngf, Tnf and Il1b in primary mouse cortical astrocytes after chemical ischemia, after exposure to lipopolysaccharide (LPS) as well as in control naïve astrocytes. We found that C3a down-regulated the expression of Gfap, C3 and Nes in astrocytes after ischemia. Further, C3a increased the expression of Tnf and Il1b in naive astrocytes and the expression of Nes in astrocytes exposed to LPS but did not affect the expression of C3ar1 or Ngf. Jointly, these results provide the first evidence that the complement peptide C3a modulates the responses of astrocytes in a highly context-dependent manner.
Modelling and analysis of Parkinsonian gait
Authors: Parakkal Unni Midhun , Menon Prathyush P. 
Published: September 2022

AbstractFreezing of gait is a late-stage debilitating symptom of Parkinson’s disease (PD) characterised by a sudden involuntary stoppage of forward progression of gait. The present understanding of PD gait is limited, and there is a need to develop mathematical models explaining PD gait’s underlying mechanisms. A novel hybrid system model is proposed in this paper, in which a mechanical model is coupled with a neuronal model. The proposed hybrid system model has event-dependent feedback and demonstrates PD-relevant behaviours such as freezing, high variability and stable gait. The model’s robustness is studied by analysing relevant parameters such as gain in the event-dependent feedback and level of activation of the central pattern generator neurons. The effect of augmented feedback on the model is also studied to understand different FoG management methods, such as sensory and auditory cues. The model indicates the frequency-dependent behaviours in PD, which are in line with the STN stimulation and external cueing-related studies. The model allows one to estimate the parameters from the data and thereby personalise the cueing regimes for patients. The model can be of help in understanding the mechanism of FoG and developing measures to counter its severity.
Historical and future trends in emergency pituitary referrals: a machine learning analysis
Authors: Pandit A. S. , Khan D. Z. , Hanrahan J. G. , Dorward N. L. , Baldeweg S. E. , Nachev P. , Marcus H. J. 
Published: September 2022

Abstract
Purpose
Acute pituitary referrals to neurosurgical services frequently necessitate emergency care. Yet, a detailed characterisation of pituitary emergency referral patterns, including how they may change prospectively is lacking. This study aims to evaluate historical and current pituitary referral patterns and utilise state-of-the-art machine learning tools to predict future service use.

Methods
A data-driven analysis was performed using all available electronic neurosurgical referrals (2014–2021) to the busiest U.K. pituitary centre. Pituitary referrals were characterised and volumes were predicted using an auto-regressive moving average model with a preceding seasonal and trend decomposition using Loess step (STL-ARIMA), compared against a Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) algorithm, Prophet and two standard baseline forecasting models. Median absolute, and median percentage error scoring metrics with cross-validation were employed to evaluate algorithm performance.

Results
462 of 36,224 emergency referrals were included (referring centres = 48; mean patient age = 56.7 years, female:male = 0.49:0.51). Emergency medicine and endocrinology accounted for the majority of referrals (67%). The most common presentations were headache (47%) and visual field deficits (32%). Lesions mainly comprised tumours or haemorrhage (85%) and involved the pituitary gland or fossa (70%). The STL-ARIMA pipeline outperformed CNN-LSTM, Prophet and baseline algorithms across scoring metrics, with standard accuracy being achieved for yearly predictions. Referral volumes significantly increased from the start of data collection with future projected increases (p < 0.001) and did not significantly reduce during the COVID-19 pandemic.

Conclusion
This work is the first to employ large-scale data and machine learning to describe and predict acute pituitary referral volumes, estimate future service demands, explore the impact of system stressors (e.g. COVID pandemic), and highlight areas for service improvement.
Seasonal and Spatial Variations in the Presence of Giardia and Cryptosporidium in Rural Drinking Water Supply Systems in Different Municipalities of Antioquia, Colombia
Authors: Escobar Catalina , Becerra-Agudelo Evelyn , Hernández Torres , Stiven Maicol , Londoño Yudy Andrea , Rodríguez Diana Catalina , Peñuela Gustavo A. 
Published: September 2022

Abstract
This study evaluated the seasonal and spatial variations in the presence of Giardia and Cryptosporidium in rural drinking water supply systems of different municipalities of Antioquia. The municipalities evaluated were Envigado, Caldas, Sabaneta, La Estrella, Itagüi, Bello, Barbosa, Copacabana, and Girardota, located in the department of Antioquia, Colombia. The experimentation was carried out over 9 sampling campaigns in the period between July 2019 and November 2020. This period encompassed the two seasons presented in Colombia: dry and wet. Each municipality included in this study has a conventional basic drinking water treatment system (DWTS) which includes sand trap, rapid filtration, and chlorination. The results showed good removal efficiencies of Cryptosporidium and Giardia in the DWTS evaluated. However, evaluation of other characteristics of water quality and of the water quality risk index for human consumption (IRCA) showed concerning water quality conditions in the rural drinking water systems supply. The prevailing risk levels of the drinking water are medium, high, or non-viable sanitary, which means the population is supplied with water that does not meet the minimum quality criteria established by Colombian regulations.
Lifestyle and environmental factors may induce airway and systemic inflammation in firefighters
Authors: Orysiak Joanna , Młynarczyk Magdalena , Piec Robert , Jakubiak Agnieszka 
Published: September 2022

AbstractHealth status depends on multiple genetic and non-genetic factors. Nonheritable factors (such as lifestyle and environmental factors) have stronger impact on immune responses than genetic factors. Firefighters work is associated with exposure to air pollution and heat stress, as well as: extreme physical effort, mental stress, or a changed circadian rhythm, among others. All these factors can contribute to both, short-term and long-term impairment of the physical and mental health of firefighters. Increased levels of some inflammatory markers, such as pro-inflammatory cytokines or C-reactive protein (CRP) have been observed in firefighters, which can lead to local, acute inflammation that promotes a systemic inflammatory response. It is worth emphasizing that inflammation is one of the main hallmarks of cancer and also plays a key role in the development of cardiovascular and respiratory diseases. This article presents possible causes of the development of an inflammatory reaction in firefighters, with particular emphasis on airway inflammation caused by smoke exposure.
The challenges in the identification of Escherichia coli from environmental samples and their genetic characterization
Authors: Osińska Adriana , Korzeniewska Ewa , Korzeniowska-Kowal Agnieszka , Wzorek Anna , Harnisz Monika , Jachimowicz Piotr , Buta-Hubeny Martyna , Zieliński Wiktor 
Published: September 2022

AbstractEscherichia coli bacteria are an essential indicator in evaluations of environmental pollution, which is why they must be correctly identified. This study aimed to determine the applicability of various methods for identifying E. coli strains in environmental samples. Bacterial strains preliminary selected on mFc and Chromocult media as E. coli were identified using MALDI Biotyper techniques, based on the presence of genes characteristic of E. coli (uidA, uspA, yaiO), as well as by 16S rRNA gene sequencing. The virulence and antibiotic resistance genes pattern of bacterial strains were also analyzed to investigate the prevalence of factors that may indicate adaptation to unsupportive environmental conditions and could have any significance in further identification of E. coli. Of the strains that had been initially identified as E. coli with culture-based methods, 36–81% were classified as E. coli with the use of selected techniques. The value of Cohen’s kappa revealed the highest degree of agreement between the results of 16S rRNA gene sequencing, the results obtained in the MALDI Biotyper system, and the results of the analysis based on the presence of the yaiO gene. The results of this study could help in the selection of more accurate and reliable methods which can be used in a preliminary screening and more precise identification of E. coli isolated from environmental samples.
Internalised Weight Stigma Mediates Relationships Between Perceived Weight Stigma and Psychosocial Correlates in Individuals Seeking Bariatric Surgery: a Cross-sectional Study
Authors: Bidstrup Hugh , Brennan Leah , Hindle Annemarie , Kaufmann Leah , de la Piedad Garcia Xochitl 
Published: September 2022

Abstract
Purpose
Research suggests that internalised weight stigma may explain the relationship between perceived weight stigma and adverse psychological correlates (e.g. depression, disordered eating, body image disturbances). However, few studies have assessed this mechanism in individuals seeking bariatric surgery, even though depression and disordered eating are more common in this group than the general population.

Materials and Methods
We used data from a cross-sectional study with individuals seeking bariatric surgery (n = 217; 73.6% female) from Melbourne, Australia. Participants (Mage = 44.1 years, SD = 11.9; MBMI = 43.1, SD = 7.9) completed a battery of self-report measures on weight stigma and biopsychosocial variables, prior to their procedures. Bias-corrected bootstrapped mediations were used to test the mediating role of internalised weight stigma. Significance thresholds were statistically corrected to reduce the risk of Type I error due to the large number of mediation tests conducted.

Results
Controlling for BMI, internalised weight stigma mediated the relationship between perceived weight stigma and psychological quality of life, symptoms of depression and anxiety, stress, adverse coping behaviours, self-esteem, exercise avoidance, some disordered eating measures and body image subscales, but not physical quality of life or pain.

Conclusion
Although the findings are cross-sectional, they are mostly consistent with previous research in other cohorts and provide partial support for theoretical models of weight stigma. Interventions addressing internalised weight stigma may be a useful tool for clinicians to reduce the negative correlates associated with weight stigma.

Graphical abstract