bluuebunny/crossref_metadata_2025 huggingface dataset:
Mind the gap: Early-career teachers’ level of preparedness, professional development, working conditions, and feelings of distress
Authors: Admiraal Wilfried , Kittelsen Røberg Karl-Ingar , Wiers-Jenssen Jannecke , Saab Nadira
Published: July 2023

In the first years of a teaching career, teachers experience high levels of distress, and the attrition rate appears to be high. Early-career teachers do not always feel well prepared for their job and feel insufficient support during their first experiences as a teacher. Induction programs, professional development, and school support could equip early-career teachers with the additional teaching repertoire they need and improve their well-being. The current study aimed to contribute insights into the importance of the level of preparedness, professional development, and working conditions for early-career teachers’ well-being. Based on multi-level regression analysis of TALIS 2018 data of more than 77,000 teachers in 24 European countries, the impact of the level of preparedness, professional development, and working conditions have been examined on teachers’ feelings of distress during their first years of teaching. Early-career teachers have been divided into two groups: novice teachers (with no more than 2 years of teaching experience) and advanced beginners (with between 2 and 5 years of teaching experience). These two groups were compared with mid-and late-career teachers (with more than 5 years of teaching experience). Level of preparedness and professional development variables were only weakly related to teachers’ feelings of distress, whereas working conditions were strongly related to early-career teachers’ feelings of distress. In particular, high workload and classroom discipline issues were strongly and positively related to teachers’ feelings of distress. Differences between the two early-career teacher groups and the group of mid- and late-career teachers were marginal. Yet, additional research is needed into the quality and the variety of initial teacher education and induction programs to come to more rigorous conclusions about the potential effects of different programs.
The role of confidence in knowledge ascriptions: an evidence-seeking approach
Authors: Francis Kathryn B. , Beaman C. Philip
Published: July 2023

Two methods have been used in the investigation of the stakes-sensitivity of knowledge as it occurs in ordinary language: (a) asking participants about the truth or acceptability of knowledge ascriptions and (b) asking participants how much evidence someone needs to gather before they know that something is the case. This second, “evidence-seeking”, method has reliably found effects of stakes-sensitivity while the method of asking about knowledge ascriptions has not. Consistent with this pattern, in Francis et al. (Ergo, 2019), we found evidence of scalar stakes effects using an evidence-seeking approach. Whilst we found this evidence across several cases using both negative (“don’t know”) and positive (“know”) polarities, there remain questions about the directness of the relationship between stakes and knowledge ascriptions; it is possible that stakes are affecting knowledge by affecting the confidence of the attributor. For example, Bach (in: Peter & Preyer, 2005) has argued that knowledge attributions do not track truth attributions but rather thresholds for doxastic confidence. To investigate the role of confidence in knowledge ascriptions, we use our existing paradigm (Francis et al., 2019) but include measures of both participant and protagonist confidence. As far as we are aware, this is the first empirical investigation of the role of confidence in stakes effects on knowledge that incorporates an evidence-seeking approach using several scenarios. Overall, across both positive (“know”) and negative (“don’t know”) polarity conditions, we find further evidence of a stakes effect on knowledge using an evidence-seeking paradigm. However, and importantly, we do not find evidence that changes in participant confidence partially or fully mediate the stakes effect on knowledge.
Selenium preserves cytosolic-Ca2+ homeostasis in olive callus cells during oxidative stress
Authors: Del Pino Alberto M. , Regni Luca , Reale Lara , Micheli Maurizio , Datti Alessandro , Proietti Primo , Palmerini Carlo A.
Published: July 2023

Selenium (Se) is not essential for plant nutrition, however, growing evidence suggests a role of this element against oxidative stress. Here, we investigated the antioxidant effect of Se in an experimental system consisting of suspensions of olive callus cells exposed to hydrogen peroxide. Due to the disruptive capacity of oxidative stress on cytosolic Ca2+ homeostasis, Se treatments were simply and effectively assessed with cytosolic Ca2+ measurements. Se did not alter cell morphology, nor interfered with fluorometric determinations, suggesting a suitable model for monitoring alterations of cytosolic Ca2+. Furthermore, we used thapsigargin (TG), a known inhibitor of the Ca2+-ATPases of the endoplasmic reticulum, to establish whether Se had a specific impact on oxidative stress. We found that Se antagonized H2O2-mediated perturbations of cytosolic Ca2+, but was unable to offset TG-mediated disruptions. We conclude that Se merits consideration in strategies designed to tackle abiotic stress leading to oxidative insults.
Supporting AI-powered real-time cyber-physical systems on heterogeneous platforms via hypervisor technology
Authors: Cittadini Edoardo , Marinoni Mauro , Biondi Alessandro , Cicero Giorgiomaria , Buttazzo Giorgio
Published: July 2023

The heavy use of machine learning algorithms in safety-critical systems poses serious questions related to safety, security, and predictability issues, requiring novel architectural approaches to guarantee such properties. This paper presents an architecture solution that leverages heterogeneous platforms and virtualization technologies to support AI-powered applications consisting of modules with mixed criticalities and safety requirements. The hypervisor exploits the security features of the Xilinx ZCU104 MPSoCs to create two isolated execution environments: a high performance domain running deep learning algorithms under the Linux operating system and a safety-critical domain running control and monitoring functions under the freeRTOS real-time operating system. The proposed approach is validated by a use case consisting of an unmanned aerial vehicle capable of tracking moving targets using a deep neural network accelerated on the FGPA available on the platform.
FluidFlower Benchmark: Lessons Learned from the Perspective of Subsurface Simulation
Authors: Wapperom Michiel , Tian Xiaoming , Novikov Aleks , Voskov Denis
Published: July 2023

In this work, we describe our decisions made to perform the FluidFlower simulation study and discuss various aspects of the benchmark that are different from our usual subsurface simulation practice. We will discuss the impact of various modeling choices on the outcomes of the simulation models, such as gridding, discretization, and solver strategies, and the lessons learned, taking into account the different conditions of the FluidFlower study compared to conditions commonly dealt with in subsurface simulation. We will start with a brief description of the DARTS framework utilized for compositional simulation, the thermodynamic and physical modeling related to the atmospheric $$\text{ CO}_{2}$$

CO
2

-brine system, and the modeling workflow used in our benchmark submission. Additionally, we describe a custom nonlinear solver developed for the atmospheric benchmark conditions to improve convergence including the linear solver strategy since our default two-stage preconditioner does not perform effectively. To make meaningful comparisons between each of the modeling choices, we define a baseline model which is a simplified version of our setup in the main FluidFlower benchmark. The baseline model is then used to study the effect of Cartesian and unstructured meshes and a two-point flux approximation compared with a multi-point flux approximation for capturing the physics at play. We conclude our work with lessons learned and future recommendations.
Molecular Classification and Antimicrobial Profiles of Chlorination-Resistant Escherichia Coli at Wastewater Treatment Plant in the North West Province of South Africa
Authors: Makuwa S. , Green E. , Tlou M. , Ndou B. , Fosso-Kankeu E.
Published: July 2023

The resistance of different pathogenic variants of E. coli to antibiotics, is a health concern globally. The study assessed the resistance of 90 E. coli isolates that survived chlorination at a Wastewater Treatment Plant (WWTP) in North West, South Africa (NW-SA), to 12 different antibiotics using the Kirby-Bauer disk diffusion method. The study further assessed the diarrheagenic pathotypes origin of the isolates. The molecular characterization revealed diarrheagenic E. coli pathotypes ranged as follows: Enteroaggregative E. coli (EAEC) 16 (17.78%), Enteroinvasive E. coli (EIEC) 6 (6.67%), Enterotoxigenic E. coli (ETEC) 5 (5.56%) and Enteropathogenic E. coli (EPEC) 3 (3.33%). A high degree of resistance was observed against sulphamethoxazol (92.22%), while lower resistance was observed against Kanamycin (3.33%), chloramphenicol (5.56%) and ciprofloxacin (6.67%). Multiple drug resistance of three and more antibiotics was observed in 81.11% of the E. coli isolates. The detected diarrheagenic E. coli pathotypes showed multiple resistance to different studied antibiotics with Multiple Antibiotic Resistance Indexing (MARI) equal to 0.9 for EIEC and EAEC respectively, followed by ETEC at 0.8 and EPEC at 0.2. The study reveals that the wastewater effluent from the studied plant serves as an important reservoir for the distribution of antibiotic resistant diarrheagenic E. coli pathotypes and other potential pathogens to the aquatic milieu, thus confirming potential risk to public health.
Resting-state fractal brain connectivity is associated with impaired cognitive performance in healthy aging
Authors: Czoch Akos , Kaposzta Zalan , Mukli Peter , Stylianou Orestis , Eke Andras , Racz Frigyes Samuel
Published: July 2023

Aging affects cognitive functions even in the absence of ongoing pathologies. The neurophysiological basis of age-related cognitive decline (CD), however, is not completely understood. Alterations in both functional brain connectivity and in the fractal scaling of neuronal dynamics have been linked to aging and cognitive performance. Recently, fractal connectivity (FrC) has been proposed — combining the two concepts — for capturing long-term interactions among brain regions. FrC was shown to be influenced by increased mental workload; however, no prior studies investigated how resting-state FrC relates to cognitive performance and plausible CD in healthy aging. We recruited 19 healthy elderly (HE) and 24 young control (YC) participants, who underwent resting-state electroencephalography (EEG) measurements and comprehensive cognitive evaluation using 7 tests of the Cambridge Neurophysiological Test Automated Battery. FrC networks were reconstructed from EEG data using the recently introduced multiple-resampling cross-spectral analysis (MRCSA). Elderly individuals could be characterized with increased response latency and reduced performance in 4–4 tasks, respectively, with both reaction time and accuracy being affected in two tasks. Auto- and cross-spectral exponents — characterizing regional fractal dynamics and FrC, respectively, — were found reduced in HE when compared to YC over most of the cortex. Additionally, fractal scaling of frontoparietal connections expressed an inverse relationship with task performance in visual memory and sustained attention domains in elderly, but not in young individuals. Our results confirm that the fractal nature of brain connectivity — as captured by MRCSA — is affected in healthy aging. Furthermore, FrC appears as a sensitive neurophysiological marker of age-related CD.
Spatial Statistical Analysis of Shipwreck Sites: A Methodological Proposal
Authors: Santos Joel , Bettencourt José
Published: July 2023

Spatial statistical analysis is almost absent from research on underwater archaeological contexts. However, the information obtained using this approach would allow the reconstruction of depositional dynamics and the exploration of distribution patterns related to the ships’ on-board organization. This paper proposes a six-step methodology that will contribute to reducing the current gap in the use of spatial statistical analysis of shipwreck sites. This methodology will be tested in two distinct case studies, the Uluburun and the Tortugas wrecks, showing that the same protocol can be useful in the interpretation of different shipwrecks, in sites with a coherent distribution during their formation process. Using statistical tools, this methodology will strengthen context awareness, confirming, refuting, or adding new perspectives to previous interpretations. Finally, the way the framework was built will allow its replication in other sites.
Sustainable coatings based on core–shell pigments to enhance antibacterial and other beneficial paper properties
Authors: Mohamed M. G. , Ahmed N. M. , Samir M.
Published: July 2023

Paper manufacturers are constantly looking for new methods to improve coated paper properties. Pigments are encountered in paper coatings to add new functions. For example, titanium dioxide (TiO2 ) and talc are considered among the best-known pigments used in paper coating and manufacturing due to their whiteness and other beneficial properties. Nevertheless, talc has a weak dispersion during which its particles agglomerate, and this disadvantage needs to be overcome before its application which means higher cost. Therefore, in this work, a core–shell technique is used to modify the talc surface and enhance its dispersion in order to promote its use in improving the properties of the paper. Core–shell pigments are composed of a thin shell of (nano- and micronized) titanium dioxide precipitated on talc particles. These prepared talc/TiO2 core–shell pigments were characterized using various techniques such as XRF, SEM, and TEM, and then they were incorporated in paper coatings to evaluate their effect on the different properties of the coated papers. The results showed that nano-talc/TiO2 with the obtained unique chemical and morphological structure has improved the physical, mechanical, and optical properties of the coated papers besides improving their antimicrobial activity, especially when compared to papers coated with micronized talc/TiO2.
Building and Maintaining Self-Efficacy Beliefs: A Study of Entry-Level Vocational Education and Training Teachers
Authors: Gagnon Nathalie , Dubeau Annie
Published: July 2023

New vocational education and training (VET) teachers in Quebec (Canada), as in other countries (e.g., France, the Netherlands, Norway, Sweden, Switzerland, the United States), face specific challenges and experience an atypical process of entry into the teaching profession. In addition to the known professional induction challenges, which requires numerous adjustments in terms of organizational integration and socialization as well as on a personal level, new VET teachers also experience a major professional and identity transition: they shift from experts in their field to novices in the teaching field. Moreover, as they are not generally trained in pedagogy, new teachers must enroll in a mandatory teaching bachelor’s program once they are fully in charge of a class and its educational responsibilities. This complex process calls for a closer look at ways to facilitate their induction experience. Specifically, because it is closely related to motivation, engagement, and performance, this study focuses on their perceived self-efficacy as teachers. This study focused on 21 new VET teachers in the francophone province of Quebec, Canada, and aim to identify different strategies through which they succeeded in developing and maintaining their self-efficacy: strategies related to 1) the work of teaching, 2) mobilization of resources, 3) professional development, and 4) attitudes and well-being at work. These strategies allow us to gain a deeper understanding of previously unexplored aspects of the reality of these teachers, and to propose avenues for the development of interventions targeting their needs.
Nonexistence of solutions to fractional parabolic problem with general nonlinearities
Authors: Zhang Lihong , Liu Yuchuan , Nieto Juan J. , Wang Guotao
Published: July 2023

In this content, we investigate a class of fractional parabolic equation with general nonlinearities $$\begin{aligned} \frac{\partial z(x,t)}{\partial t}-(\Delta +\lambda )^{\frac{\beta }{2}}z(x,t)=a(x_{1})f(z), \end{aligned}$$

∂
z
(
x
,
t
)

∂
t

-

(
Δ
+
λ
)

β
2

z

(
x
,
t
)

=
a

(

x
1

)

f

(
z
)

,

where a and f are nondecreasing functions. We first prove that the monotone increasing property of the positive solutions in $$x_{1}$$

x
1

 direction. Based on this, nonexistence of the solutions are obtained by using a contradiction argument. We believe these new ideas we introduced will be applied to solve more fractional parabolic problems.
Optimisation of seat reservations on trains to minimise transfer distances
Authors: Weicker Karsten
Published: July 2023

This paper introduces a novel optimisation problem motivated by the real-world application of transferring between trains. The driving idea is to minimise the walking distances of all transferring passengers by optimising the assignment of passengers to railcarriages in the seat reservation process. The focus of this work is on formalising and modelling the problem, which has not been studied before. It aims to provide a framework for future considerations. We present three versions of the problem with increasing difficulty: one-train-one-station, one-train-many-stations, and a general problem with multiple trains and stations. Since the simplest version of the problem is a pure assignment problem in the form of minimum-cost bipartite matching, our problem modelling and algorithmic solution approach remain closely related to maxflow problems as they represent a proven method for assignment problems. However, even the one-train-many-stations problem cannot be solved by transforming it into a standard maximum-flow problem. The main result shown is the NP-hardness of the general problem.
A Review on Monitoring of Organic Pollutants in Wastewater Using Electrochemical Approach
Authors: Idris Azeez Olayiwola , Orimolade Benjamin , Dennany Lynn , Mamba Bhekie , Azizi Shohreh , Kaviyarasu K. , Maaza Malik
Published: July 2023

This review focuses on monitoring selected organic contaminants utilising an electrochemistry technique due to intrinsic benefits such as simplicity, portability, cost, and improved sensitivity. Because the presence of organic pollutants in water causes a variety of health issues such as tumour, headaches, tiredness, and developmental abnormalities, it is critical to explore an effective approach to quantifying these contaminants in various matrices. Although remarkable results have been documented in the use of conventional techniques in the quantification of organic pollutants, owing to high costs, longer pre-concentration steps and analysis times, high power consumption, and the need for sophisticated skilled personnel, their applications for monitoring organic pollutants on-site have been hampered. The electrochemistry approach has emerged to address the difficulties that have hindered the use of traditional approaches for quantifying organic contaminants in water. Thus, the purpose of this review is to examine the concept of employing electrochemistry techniques to determine organic contaminants in various matrixes, and various recommendations for future research have been highlighted.

Graphical Abstract

This diagram illustrates the steps involved in creating a sensor utilising nanomaterial and connected to a three-electrode system. The nanomaterial is immobilised onto the surface of the working electrode. A suitable potentiostat is then employed to generate the current signal of the reaction between the sensor and the desired analyte.
Vegetable substrates as an alternative for the inclusion of lactic acid bacteria with probiotic potential in food matrices
Authors: Bernal-Castro Camila , Espinosa-Poveda Elpidia , Gutiérrez-Cortés Carolina , Díaz-Moreno Consuelo
Published: July 2023

Vegetable substrates are food matrices with micronutrients, antioxidants, and fiber content with a high potential for bioprocesses development. In addition, they have been recognized as essential sources of a wide range of phytochemicals that, individually or in combination, can act as bioactive compounds with potential benefits to health due to their antioxidant and antimicrobial activity and recently due to their status as prebiotics in the balance of the human intestinal microbiota. This systematic review explores the benefits of lactic fermentation of plant matrices such as fruits, vegetables, legumes, and cereals by bacteria with probiotic potential, guaranteeing cell viability (106–107 CFU/mL) and generating bioactive metabolic products for modulation of the gut microbiome.
Surgical treatment of tracheal stenosis during Covid-19 era: a single-center experience and lessons learnt on the field
Authors: Bacchin Diana , Aprile Vittorio , Lenzini Alessandra , Korasidis Stylianos , Mastromarino Maria Giovanna , Picchi Alessandro , Fanucchi Olivia , Ribechini Alessandro , Ambrogi Marcello Carlo , Lucchi Marco
Published: July 2023

SARS-CoV2 outbreak led to several healthcare system challenges, especially concerning respiratory support to Covid-19 patients. In the first 2 years of pandemic (2020–2021), we assisted to a marked increase of post-invasive mechanical ventilation (IMV) tracheal stenosis incidence, many of them requiring surgical treatment, namely resection and primary end-to-end anastomosis. Our aim is to describe our experience during the abovementioned biennium, focusing on postoperative outcomes of patients who have had Covid-19 (“post-Covid”). We retrospectively collected pre-, intra- and postoperative data on all patients who underwent tracheal surgery for benign stenosis in our Unit from May 2020 to October 2021, including previous Covid-19. Comparison between “post-Covid-19” and “non-Covid-19” groups’ outcomes was then performed. Patients were 9 males and 6 females, and mean age was 57.4 ± 13.21 years. Nine patients had previous Covid-19 (60%). All patients underwent multidisciplinary preoperative evaluation. Almost every operation was conducted by cervicotomy, and the mean length of the resected specimen was 23.9 ± 6.5 mm. Postoperative complications were: dysphonia (3 cases), wound infection (1), bleeding (1), ab-ingestis pneumonia (1), anastomosis dehiscence (2), and stenosis recurrence (1). Thirty-day mortality rate was 6.7% (1 patient). No significant differences between “post-Covid-19” and “non-Covid-19” groups were identified. Pathology revealed, in 5 “post-Covid-19” patients, signs of vasculitis or perivascular inflammatory infiltrate. Tracheal stenosis’ surgical treatment has always been known as a challenging procedure because of high perioperative morbidity and mortality rates. Our experience shows that previous Covid-19 and ongoing pandemic did not significantly affect perioperative outcomes of patients who underwent tracheal resection and primary end-to-end anastomosis in a high-volume Center and after multidisciplinary workup.

Graphical abstract
Blow-up solutions of damped Klein–Gordon equation on the Heisenberg group
Authors: Ruzhansky Michael , Sabitbek Bolys
Published: July 2023

We prove the blow-up of solutions of the semilinear damped Klein–Gordon equation in a finite time for arbitrary positive initial energy on the Heisenberg group. This work complements the paper Ruzhansky and Tokmagambetov (J Differ Equ 265(10):5212–5236, 2018), where the global in time well-posedness was proved for the small energy solutions.
A Bayesian actor-oriented multilevel relational event model with hypothesis testing procedures
Authors: Vieira Fabio , Leenders Roger , McFarland Daniel , Mulder Joris
Published: July 2023

Relational event network data are becoming increasingly available. Consequently, statistical models for such data have also surfaced. These models mainly focus on the analysis of single networks; while in many applications, multiple independent event sequences are observed, which are likely to display similar social interaction dynamics. Furthermore, statistical methods for testing hypotheses about social interaction behavior are underdeveloped. Therefore, the contribution of the current paper is twofold. First, we present a multilevel extension of the dynamic actor-oriented model, which allows researchers to model sender and receiver processes separately. The multilevel formulation enables principled probabilistic borrowing of information across networks to accurately estimate drivers of social dynamics. Second, a flexible methodology is proposed to test hypotheses about common and heterogeneous social interaction drivers across relational event sequences. Social interaction data between children and teachers in classrooms are used to showcase the methodology.
Development of a practical guideline for person centred goal setting in geriatric rehabilitation: a participatory action research
Authors: Wattel Elizabeth M. , de Groot Aafke J. , Deetman-van der Breggen Sacha , Bonthuis Robin , Jongejan Niels , Tol-Schilder Marina M. R. , van der Wouden Johannes C. , Gobbens Robbert
Published: July 2023

Purpose

To improve goal setting in Geriatric Rehabilitation (GR), by developing an evidence-based practical guideline for patient-centred goal setting.

Methods

Participatory action research (PAR) in a cyclical process, with GR professionals as co-researchers. Each cycle consisted of five phases: problem analysis, literature review, development, practical experience, feedback & evaluation. The evaluation was based on video recordings of goal setting conversations, and on oral and written feedback of the GR professionals who tested the guideline.

Results

In two PAR-cycles the guideline was developed, consisting of eight recommendations for setting and using goals, and of practical advices elaborating three of the recommendations, concerning conversational skills specific for goal setting conversations. After the second cycle the research team concluded that the guideline was feasible in daily practice and effective when used consciously.

Conclusion

In this study, a practical guideline for setting and using goals in GR was developed. GR teams can improve their patient centred working with goals by discussing the recommendations in their team and choosing the recommendations to work on. This can be supported by the development of an interdisciplinary training. The effect on quality of care should be subject to further investigation.
Low-Frequency Ultrawide Band Gap Study of Symmetric Conical Scatterer Phononic Crystal
Authors: Tang Rongjiang , Lu Taoqi , Zheng Weiguang
Published: July 2023

Purpose

One of the key challenges in the research of phononic crystals is achieving small-size control of large wavelengths, which means obtaining low-frequency band gaps with relatively small lattice dimensions. Previous studies have mostly been unsatisfactory in this regard. To obtain lower starting frequencies and more satisfactory band gap widths, this work presents a novel design for a phononic crystal structure.

Design Approach

The proposed phononic crystal consists of a silicon rubber connecting plate, an epoxy resin substrate, and tungsten metal cone scatterers. Through finite element method (FEM) calculations and analysis, we have successfully achieved an ultrawide band gap. To delve further into the origin of the ultra-wideband gap in a newly conceived phononic crystal, the vibrational modes of this crystal were carefully studied.

Findings

This work has successfully achieved an ultrawide band gap with a width ranging from 122.47 to 4360.2 in the case of a lattice constant of a = 8.5 mm. It was found that the low-frequency ultra-wideband gap cannot be obtained without the presence of silicone rubber. Furthermore, an equivalent spring model was developed, and the accuracy of this model was successfully validated through meticulous calculations. At last, It is found that d1, d4, h1, and h3 have the most pronounced effect on the ultrawide bandgap, and the intrinsic reason is the fact that they determine the geometric structure of the silicone rubber connection plate.

Research Limitations/implications

Due to the chosen research method of finite element analysis, the study results may vary depending on the different mesh discretizations, but this type of error is small and can be ignored.

Practical Implications

This work provides a new design solution for phononic crystal miniaturization.

Originality/value

Compared with previous reports, the new phonon crystals designed in this paper have smaller size, lower starting frequency, and wider band gap.
Energy consumption forecast in peer to peer energy trading
Authors: Hassan Hend G. , Shahin Ahmed A. , Ziedan Ibrahim E.
Published: July 2023

This study predicts future values of energy consumption demand from a novel dataset that includes the energy consumption during COVID-19 lockdown, using up-to-date deep learning algorithms to reduce peer-to-peer energy system losses and congestion. Three learning algorithms, namely Random Forest (RF), Bi-LSTM, and GRU, were used to predict the future values of a building’s energy consumption. The results were compared using the RMSE and MAE evaluation metrics. The results show that predicting the future energy demand with accurate results is achievable, and that Bi-LSTM and GRU perform better, especially when trained as univariate models with only the energy consumption values and no other features included.
Demography as a Field: Where We Came From and Where We Are Headed
Authors: Pesando Luca Maria , Dorélien Audrey , St-Denis Xavier , Santos Alexis
Published: July 2023

This essay provides a series of reflections on the current state of demography as seen by four early-career researchers who are actively engaged in aspects of the discipline as varied as research, teaching, mentorship, data collection efforts, policy making, and policy advising. Despite some claims that the discipline is weakening, we showcase the great potential of the field and outline promising pathways and novel directions for the future. In so doing, we critically assess recent innovations in data quality and availability, stressing the need to “revolutionize” the way that demographic methods are taught by adopting a viewpoint that more closely reflects the rapidly changing, or “fast,” nature of global social phenomena such as conflict-related displacements, environmental disasters, migration streams, pandemics, and evolving population policies. We conclude by discussing the relevance of careful demographic analyses for policy making, stressing three main points: (i) the need to make demography more visible and understandable to the public eye; (ii) the importance of engaging and co-creating with local communities to “break” the academic bubble; and (iii) the urge to counteract the spread of misinformation—a phenomenon that has become even more visible in the aftermath of the COVID-19 outbreak.
AI-enabled strategies for climate change adaptation: protecting communities, infrastructure, and businesses from the impacts of climate change
Authors: Jain Harshita , Dhupper Renu , Shrivastava Anamika , Kumar Deepak , Kumari Maya
Published: July 2023

Climate change is one of the most pressing global challenges we face today. The impacts of rising temperatures, sea levels, and extreme weather events are already being felt around the world and are only expected to worsen in the coming years. To mitigate and adapt to these impacts, we need innovative, data-driven solutions. Artificial intelligence (AI) has emerged as a promising tool for climate change adaptation, offering a range of capabilities that can help identify vulnerable areas, simulate future climate scenarios, and assess risks and opportunities for businesses and infrastructure. With the ability to analyze large volumes of data from climate models, satellite imagery, and other sources, AI can provide valuable insights that can inform decision-making and help us prepare for the impacts of climate change. However, the use of AI in climate change adaptation also raises important ethical considerations and potential biases that must be addressed. As we continue to develop and deploy these solutions, it is crucial to ensure that they are transparent, fair, and equitable. In this context, this article explores the latest innovations and future directions in AI-enabled climate change adaptation strategies, highlighting both the potential benefits and the ethical considerations that must be considered. By harnessing the power of AI for climate change adaptation, we can work towards a more resilient, sustainable, and equitable future for all.
An integrative approach for the analysis of risk and health across the life course: challenges, innovations, and opportunities for life course research
Authors: Zuber Sascha , Bechtiger Laura , Bodelet Julien Stéphane , Golin Marta , Heumann Jens , Kim Jung Hyun , Klee Matthias , Mur Jure , Noll Jennie , Voll Stacey , O’Keefe Patrick , Steinhoff Annekatrin , Zölitz Ulf , Muniz-Terrera Graciela , Shanahan Lilly , Shanahan Michael J. , Hofer Scott M.
Published: July 2023

Life course epidemiology seeks to understand the intricate relationships between risk factors and health outcomes across different stages of life to inform prevention and intervention strategies to optimize health throughout the lifespan. However, extant evidence has predominantly been based on separate analyses of data from individual birth cohorts or panel studies, which may not be sufficient to unravel the complex interplay of risk and health across different contexts. We highlight the importance of a multi-study perspective that enables researchers to: (a) Compare and contrast findings from different contexts and populations, which can help identify generalizable patterns and context-specific factors; (b) Examine the robustness of associations and the potential for effect modification by factors such as age, sex, and socioeconomic status; and (c) Improve statistical power and precision by pooling data from multiple studies, thereby allowing for the investigation of rare exposures and outcomes. This integrative framework combines the advantages of multi-study data with a life course perspective to guide research in understanding life course risk and resilience on adult health outcomes by: (a) Encouraging the use of harmonized measures across studies to facilitate comparisons and synthesis of findings; (b) Promoting the adoption of advanced analytical techniques that can accommodate the complexities of multi-study, longitudinal data; and (c) Fostering collaboration between researchers, data repositories, and funding agencies to support the integration of longitudinal data from diverse sources. An integrative approach can help inform the development of individualized risk scores and personalized interventions to promote health and well-being at various life stages.
How AI developers can assure algorithmic fairness
Authors: Xivuri Khensani , Twinomurinzi Hosanna
Published: July 2023

Artificial intelligence (AI) has rapidly become one of the technologies used for competitive advantage. However, there are also growing concerns about bias in AI models as AI developers risk introducing bias both unintentionally and intentionally. This study, using a qualitative approach, investigated how AI developers can contribute to the development of fair AI models. The key findings reveal that the risk of bias is mainly because of the lack of gender and social diversity in AI development teams, and haste from AI managers to deliver much-anticipated results. The integrity of AI developers is also critical as they may conceal bias from management and other AI stakeholders. The testing phase before model deployment risks bias because it is rarely representative of the diverse societal groups that may be affected. The study makes practical recommendations in four main areas: governance, social, technical, and training and development processes. Responsible organisations need to take deliberate actions to ensure that their AI developers adhere to fair processes when developing AI; AI developers must prioritise ethical considerations and consider the impact their models may have on society; partnerships between AI developers, AI stakeholders, and society that might be impacted by AI models should be established; and AI developers need to prioritise transparency and explainability in their models while ensuring adequate testing for bias and corrective measures before deployment. Emotional intelligence training should also be provided to the AI developers to help them engage in productive conversations with individuals outside the development team.
Different approaches to the moral status of AI: a comparative analysis of paradigmatic trends in Science and Technology Studies
Authors: Redaelli Roberto
Published: July 2023

The exponential progress of AI systems today compels scientists and philosophers to redefine their conceptual frameworks to better understand the nature of these new technologies and their moral status. Among the various theories that are used to respond to the challenges posed by intelligent systems are instrumentalism, Socio-technical Systems Theory (STST) and Mediation Theory (MT), all widely adopted in the field of Science and Technology Studies (STS). This paper intends to present the main features of these theories and provide a comparative analysis of them in order to assess their contribution to the process of understanding the moral status of artificial intelligence. Our investigation intends to show how (1) instrumentalism is inadequate to account for the moral status of AI, (2) STST, while helping to highlight the link between AI, society and morality, lends itself to the criticism of anthropocentrism, (3) MT in its Latourian version has the merit of highlighting the active character of technological artefacts and thus of artificial intelligence in the moral sphere. However, the principle of symmetry it proposes poses the problem of the de-accountability of the human agent. (4) MT in its postphenomenological form seems to partially resolve the problem of moral responsibility, but the opacity of the terminology it employs exposes it to various criticisms. In light of these results, we intend to show how an understanding of the moral status of intelligent systems cannot be based on the diametrically opposed positions that consider technologies either morally neutral or else moral agents similar to humans, whereas particularly useful elements can be found in STST and in postphenomenological MT.
The road to greater well-being: exploring the impact of an undergraduate positive education course on university students’ well-being
Authors: Pastore Olivia L. , McAllister Sarah , Fortier Michelle
Published: July 2023

The profile of subjective well-being (SWB) in university students is perturbing in many respects. Indeed, university students are in need of tools to combat stress and promote SWB now more than ever given the adverse repercussions of the COVID-19 pandemic. Positive education could serve as a SWB tool to help university students deal with academic, personal, and global stressors. While a number of studies have quantitatively reported the impact of positive education on student SWB, few have considered students’ experiences and perceptions of changes in their SWB as a result of taking a positive education course. Therefore, the purpose of this study was to qualitatively explore university students’ experiences in a positive education course and their perceptions of its influence on their SWB immediately after taking the course. Undergraduate students (n = 17) who had taken a positive education course during the Winter term of 2020 (January–April) were recruited via volunteer sampling. Data were collected by means of semi-structured interviews and analyzed using reflexive thematic analysis. Analyses revealed that the course improved the students’ SWB, self-compassion, mindfulness, and optimism. Mechanisms such as greater self-reflection, implementation of intentional positive activities, and big picture thinking underlie these reported improvements. Our findings support positive education’s effectiveness in enhancing student SWB and expand on the current literature by proposing novel mechanisms linking positive education to enhanced student SWB, self-compassion, mindfulness, and optimism.
The Ethics of Sharing: Privacy, Data, and Common Goods
Authors: Søe Sille Obelitz , Mai Jens-Erik
Published: July 2023

Given the concerns about big tech’s hoarding of data, creation of profiles, mining of data, and extrapolation of new knowledge from their data warehouses, there is a need and interest in devising policies and regulations that better shape big tech's influence on people and their lives. One such proposal is to create data commons. In this paper, we examine the idea of data commons as well as the concept of sharing in relation to the concept of personal data. We argue that personal data are different in nature from the objects of classical commons wherefore the logic of “sharing is caring” is flawed. We, therefore, develop an ethics of sharing taking privacy into account as well as the idea that sometimes the right thing to do is not sharing. This ethics of sharing is based in a proposal to conceptualize data commons as MacIntyrean practices and Wittgensteinian forms of life.
Infectious disease physician characteristics and prescription of meropenem in the hospital
Authors: Challener Douglas , O’Horo John , Tande Aaron J.
Published: July 2023

Objective:

Physician characteristics may be correlated with medical treatment decisions and patient outcomes. This study examined the correlations between characteristics of infectious disease (ID) physicians and the use of the restricted antimicrobial meropenem.

Design:

This was a retrospective cohort study following 27 attending ID physicians for 5 years at a large academic medical center.

Methods:

All inpatient ID clinical encounters between 2013 and 2018 were assessed for physician and patient characteristics, including patient Charlson Comorbidity Index, patient sex, ID service seeing the patient, physician career stage, physician training location, and physician sex. Adjusted and unadjusted odds ratios were calculated for the receipt of meropenem on the same day as an ID clinical note.

Results:

Between 2013 and 2018, meropenem was administered on the same day as 9046 (11.1%) of 81,787 inpatient ID encounters. After adjustment for patient and practice-specific factors, physician career stage was associated with administration of meropenem. Patients seen by mid-career and late-career ID physicians were more likely to receive meropenem than those seen by early-career physicians (aOR 1.22 95% confidence interval [CI 1.13–1.31 and aOR 1.17 95% CI 1.10–1.25, respectively).

Conclusions:

ID provider characteristics may help target future antimicrobial stewardship program interventions.
Obstetrical Outcomes of Patients with Epilepsy in a Canadian Tertiary Care Center (2014–2020)
Authors: Hébert Julien , Iyengar Yajur , Ng Sharon , Liao Jenny , Snelgrove John W. , Bui Esther
Published: July 2023

Background:

There is a paucity of data on the obstetrical outcomes of Canadian pregnant patients with epilepsy, which may differ from the average Canadian pregnancy and from other populations of pregnant patients with epilepsy.

Methods:

Pregnant patients with epilepsy were identified from a prospectively collected database of patients seen at the maternal-fetal medicine obstetrics program of Mount Sinai Hospital (Toronto, Canada) between January 1, 2014, and November 20, 2020. Pregnancy, delivery, and neonatal outcome data were retrieved from this database and described using 95% binomial confidence intervals. Comparisons of obstetrical outcomes over the same period among the Canadian population average, obtained from publicly available national health data, were done using one-proportion Z-tests for nominal variables and one-sample t-tests for continuous variables.

Results:

In total, 282 pregnancies, from 224 patients, were included, which resulted in 274 live births. Mean maternal age was 32.8 years (s.d.= 4.6; population average [μ] = 30.9;p< 0.01), and 53% were primiparous (CI95%= 49%–61%; μ = 43%;p< 0.01). The observed rates of obstetrical complications were gestational hypertension 9% (CI95%=6%–13%; μ=7%; p=0.19), gestational diabetes 5% (CI95%= 3%–8%; μ = 9%;p= 0.02), cesarean section 44% (CI95%= 38%–50%; μ = 28%;p< 0.01), postpartum hemorrhage 5% (CI95%= 3%–8%; μ = 0.5%;p< 0.01), stillbirth 1% (CI95%= 0%–2%; μ=1%;p> 0.99), and prematurity 9% (CI95%= 6%–13%; μ = 8%;p= 0.44).

Conclusion:

In this cohort of Canadian pregnant patients with epilepsy from an urban tertiary care center, observed rates of obstetrical complications were rare and no higher than in the Canadian population over the same period, with the exception of cesarean section and postpartum hemorrhage. Future prospective studies that include primary care and rural settings are needed to increase the generalizability of those results.
Neural prediction model for transition onset of a boundary layer in presence of two-dimensional surface defects
Authors: Rouviere Adrien , Pascal Lucas , Méry Fabien , Simon Ehouarn , Gratton Serge
Published: July 2023

Predicting the laminar to turbulent transition is an important aspect of computational fluid dynamics because of its impact on skin friction. Traditional transition prediction methods such as local stability theory or the parabolized stability equation method do not allow for the consideration of strongly non-parallel boundary layer flows, as in the presence of surface defects (bumps, steps, gaps, etc.). A neural network approach, based on an extensive database of two-dimensional incompressible boundary layer stability studies in the presence of gap-like surface defects, is used. These studies consist of linearized Navier–Stokes calculations and provide information on the effect of surface irregularity geometry and aerodynamic conditions on the transition to turbulence. The physical and geometrical parameters characterizing the defect and the flow are then provided to a neural network whose outputs inform about the effect of a given gap on the transition through the

${\rm \Delta} N$

method (where N represents the amplification of the boundary layer instabilities).