bluuebunny/crossref_metadata_2025 huggingface dataset:
An MDS-based unifying approach to time series K-means clustering: application in the dynamic time warping framework
Authors: Vera J. Fernando , Angulo José M.
Published: May 2023

Partitioning algorithms, and in particular K-means clustering, are widely used in time series analysis. K-means clustering is intrinsically related to the use of the Euclidean distance as a measure of dissimilarity. When other dissimilarity measures, such as dynamic time warping, are involved, K-means clustering is usually replaced by the optimisation of a sums-of-the-stars clustering criterion, giving rise to an algorithm other than that of K-means, such as K-medoids. Another common restriction in the implementation of K-means concerns the need to estimate the average as the cluster prototype, which may represent a drawback for this method in time series when elastic measures such as dynamic time warping are used. In this paper, we propose a multidimensional scaling based K-means clustering algorithm that enables the use of K-means clustering together with any dissimilarity measure, and in particular with dynamic time warping, without requiring us to estimate cluster prototypes for the time series. This procedure is a true K-means clustering algorithm that searches for the partition in an equivalent auxiliary configuration, usually in a dimension lower than the time series length. The approach proposed is of particular interest when dynamic time warping is used in the analysis of series of unequal length and/or when some data are missing, and hence Euclidean distances cannot be used. The performance of our procedure is tested by conducting an extensive Monte Carlo experiment, comparing the results with those obtained by K-medoids. The procedure is also illustrated with the analysis of carbon dioxide emissions from 133 countries.
A non-local quasi-linear ground state representation and criticality theory
Authors: Fischer Florian
Published: May 2023

We study energy functionals associated with quasi-linear Schrödinger operators on infinite weighted graphs, and develop a ground state representation. Using the representation, we develop a criticality theory, and show characterisations for a Hardy inequality to hold true. As an application, we show a Liouville comparison principle.
Forest GUMP: a tool for verification and explanation
Authors: Murtovi Alnis , Bainczyk Alexander , Nolte Gerrit , Schlüter Maximilian , Steffen Bernhard
Published: May 2023

In this paper, we present Forest GUMP (for Generalized, Unifying Merge Process) a tool for verification and precise explanation of Random forests. Besides pre/post-condition-based verification and equivalence checking, Forest GUMP also supports three concepts of explanation, the well-known model explanation and outcome explanation, as well as class characterization, i.e., the precise characterization of all samples that are equally classified. Key technology to achieve these results is algebraic aggregation, i.e., the transformation of a Random Forest into a semantically equivalent, concise white-box representation in terms of Algebraic Decision Diagrams (ADDs). The paper sketches the method and demonstrates the use of Forest GUMP along illustrative examples. This way readers should acquire an intuition about the tool, and the way how it should be used to increase the understanding not only of the considered dataset, but also of the character of Random Forests and the ADD technology, here enriched to comprise infeasible path elimination. As Forest GUMP is publicly available all experiments can be reproduced, modified, and complemented using any dataset that is available in the ARFF format.
First three years of the international verification of neural networks competition (VNN-COMP)
Authors: Brix Christopher , Müller Mark Niklas , Bak Stanley , Johnson Taylor T. , Liu Changliu
Published: May 2023

This paper presents a summary and meta-analysis of the first three iterations of the annual International Verification of Neural Networks Competition (VNN-COMP), held in 2020, 2021, and 2022. In the VNN-COMP, participants submit software tools that analyze whether given neural networks satisfy specifications describing their input-output behavior. These neural networks and specifications cover a variety of problem classes and tasks, corresponding to safety and robustness properties in image classification, neural control, reinforcement learning, and autonomous systems. We summarize the key processes, rules, and results, present trends observed over the last three years, and provide an outlook into possible future developments.
Field Testing the “Avoid the Needle” Intervention for Persons at Risk for Transitioning to Injecting Drug Use in Tallinn, Estonia and New York City, USA
Authors: Jarlais Don C Des , McKnight Courtney , Weng Chenziheng Allen , Feelemyer Jonathan , Tross Susan , Raag Mait , Org Greete , Talu Ave , Uuskula Anneli
Published: May 2023

This study aimed to field tested the “Avoid the Needle” (AtN) intervention to reduce transitions from non-injecting to injecting drug use in two different epidemiological settings. Respondent driven sampling was used to recruit current non-injecting drug users (NIDUs) in Tallinn, Estonia in 2018-19 and in New York City (NYC) in 2019-20. Both persons who had never injected and persons who had previously injected but not in the last 6 months were eligible; a structured interview was administered, a blood sample collected, and the intervention administered by trained interventionists. We recruited 19 non-injectors from Tallinn and 140 from NYC. Participants in Tallinn were younger and had begun using drugs at earlier ages than participants in NYC. The primary drugs used in Tallinn were amphetamine, fentanyl, and opioid analgesics, while in NYC they were heroin, cocaine, speedball, and fentanyl. Six-month follow-up data were obtained from 95% of participants in Tallinn. The study was interrupted by COVID-19 lockdown in NYC, but follow-up data were obtained from 59% of participants. There were minimal transitions to injecting: 1/18 in Tallinn and 0/83 in NYC. There were significant declines in the frequencies of using readily injectable drugs (fentanyl, amphetamine, heroin, cocaine) from baseline to follow-up in both sites (Cochran-Armitage tests for trend, χ2 = 21.3, p < 0.001 for New York City; and χ2 = 3.9, p = 0.048 for Tallinn). Reducing transitions into injecting is a potentially very important method for reducing HIV transmission and other harms of drug use. Further investigation and implementation of AtN type interventions is warranted.
Optimal selection and investment-allocation decisions for sustainable supplier development practices
Authors: Bai Chunguang , Govindan Kannan , Dhavale Dileep
Published: May 2023

Organization’s sustainability performance is influenced by its suppliers’ sustainability performance. This relationship makes sustainable supplier development a strategic competitive option for a buyer or focal organization. When considering sustainable supplier development practices (SSDPs) adoption, organizations have to balance and consider their limited financial resources and operational constraints. It becomes necessary to both select the best SSDPs set and investment allocation among the selected SSDP set such that the organization can maximize overall sustainability performance level. In this paper, an integrated formal modeling methodology using DEMATEL, the NK model, and multi-objective linear programming model is used support this objective. The proposed methodology is evaluated in a practical sustainable supply chain field study of an equipment manufacturing company in China. Through case study, we found that the interdependency among SSDPs must be considered in SSDPs selection and investment allocation problem. Theoretical, managerial and methodology implications, conclusions, and directions for future research are also presented.
Frequency Analysis of EEG Microstate Sequences in Wakefulness and NREM Sleep
Authors: Wiemers Milena C. , Laufs Helmut , von Wegner Frederic
Published: May 2023

The majority of EEG microstate analyses concern wakefulness, and the existing sleep studies have focused on changes in spatial microstate properties and on microstate transitions between adjacent time points, the shortest available time scale. We present a more extensive time series analysis of unsmoothed EEG microstate sequences in wakefulness and non-REM sleep stages across many time scales. Very short time scales are assessed with Markov tests, intermediate time scales by the entropy rate and long time scales by a spectral analysis which identifies characteristic microstate frequencies. During the descent from wakefulness to sleep stage N3, we find that the increasing mean microstate duration is a gradual phenomenon explained by a continuous slowing of microstate dynamics as described by the relaxation time of the transition probability matrix. The finite entropy rate, which considers longer microstate histories, shows that microstate sequences become more predictable (less random) with decreasing vigilance level. Accordingly, the Markov property is absent in wakefulness but in sleep stage N3, 10/19 subjects have microstate sequences compatible with a second-order Markov process. A spectral microstate analysis is performed by comparing the time-lagged mutual information coefficients of microstate sequences with the autocorrelation function of the underlying EEG. We find periodic microstate behavior in all vigilance states, linked to alpha frequencies in wakefulness, theta activity in N1, sleep spindle frequencies in N2, and in the delta frequency band in N3. In summary, we show that EEG microstates are a dynamic phenomenon with oscillatory properties that slow down in sleep and are coupled to specific EEG frequencies across several sleep stages.
“Do Something Simple for the Climate”: How Collective Counter-Conduct Reproduces Consumer Responsibilization
Authors: Döbbe Friederike , Cederberg Emilia
Published: May 2023

This paper studies consumers’ reactions and resistance to being responsibilized for making climate-friendly food choices. While resistance to consumer responsibilization has been studied from an individual experiential perspective, we examine its collective characteristics. We do this by tracing the controversial marketing campaign of a Swedish poultry producer, encouraging consumers to “do something simple for the climate” by eating chicken rather than beef. In our analysis of social media comments and formal complaints to the consumer protection authority, we mobilize Foucault’s notion of counter-conduct to analyse subtle forms of resistance to consumer responsibilization. We identified four interrelated yet distinct forms of consumer counter-conduct: challenging truth claims, demanding ‘more,’ constructing ‘the misled consumer,’ and rejecting vilification. By theorizing these counter-conducts, we demonstrate how consumers collectively contested both the means and ends of responsibilization—but not the underlying premise of individualized responsibility. Thus, our study helps to explain how consumers’ resistance reproduces, rather than undermines, responsibilization.
Fidelity and Clinical Competence in Providing Illness Management and Recovery: An Explorative Study
Authors: Roosenschoon Bert-Jan , van Weeghel Jaap , Deen Mathijs L. , van Esveld Emmie W. , Kamperman Astrid M. , Mulder Cornelis L.
Published: May 2023

Illness Management and Recovery (IMR) is a psychosocial intervention supporting people with serious mental illnesses. In this study, 15 IMR groups were assessed for fidelity and clinician competency to establish the implementation level of all IMR elements and explore complementarity of the IMR Treatment Integrity Scale (IT-IS) to the standard IMR Fidelity Scale. Use of the IT-IS was adapted, similar to the IMR Fidelity Scale. Descriptive statistics were applied. Implementation success of IMR elements varied widely on the IMR Fidelity Scale and IT-IS (M = 3.94, SD = 1.13, and M = 3.29, SD = 1.05, respectively). Twelve IMR elements (60%) were well-implemented, whereas eight (40%) were implemented insufficiently, including some critical cognitive-behavioral techniques (e.g., role-playing). The scales appeared largely complementary, though strongly correlated (r (13) = 0.74, p = 0.002). Providing all IMR elements adequately requires a variety of clinical skills. Specific additional training and supervision may be necessary.
A Gibbs sampler for multi-species occupancy models
Authors: Clark Allan Ernest , Altwegg Res
Published: May 2023

Multi-species occupancy (MSO) models use detection-nondetection data from species observed at different locations to estimate the probability that a particular species occupies a particular geographical region. The models are particularly useful for estimating the occupancy probabilities associated with rare species since they are seldom observed when undertaking field surveys. In this paper, we develop Gibbs sampling algorithms that can be used to fit various Bayesian MSO models to detection-nondetection data. Bayesian analysis of these models can be undertaken using statistical packages such as JAGS, Stan, and NIMBLE. However, since these packages were not developed specifically to fit occupancy models, one often experiences long run-times when undertaking analysis. However, we find that these packages that were not developed specifically to fit MSO models are less efficient than our special-purpose Gibbs sampling algorithms.
Residential proximity to petrol stations and risk of childhood leukemia
Authors: Malavolti Marcella , Malagoli Carlotta , Filippini Tommaso , Wise Lauren A , Bellelli Alessio , Palazzi Giovanni , Cellini Monica , Costanzini Sofia , Teggi Sergio , Vinceti Marco
Published: May 2023

Petrol stations emit benzene and other contaminants that have been associated with an increased risk of childhood leukemia. We carried out a population-based case-control study in two provinces in Northern Italy. We enrolled 182 cases of childhood leukemia diagnosed during 1998–2019 and 726 age- and sex-matched population controls. We geocoded the addresses of child residences and 790 petrol stations located in the study area. We estimated leukemia risk according to distance from petrol stations within a 1000 m buffer and amount of supplied fuel within a buffer of 250 m from the child’s residence. We used conditional logistic regression models to approximate risk ratios (RRs) and 95% confidence intervals (CIs) for associations of interest, adjusted for potential confounders. We also modeled non-linear associations using restricted cubic splines. In secondary analyses, we restricted to acute lymphoblastic leukemia (ALL) cases and stratifed by age (<5 and ≥5 years). Compared with children who lived≥1000 m from a petrol station, the RR was 2.2 (95% CI 0.5–9.4) for children living<50 m from nearest petrol station. Associations were stronger for the ALL subtype (RR=2.9, 95% CI 0.6–13.4) and among older children (age≥5 years: RR=4.4, 95% CI 0.6–34.1; age<5 years: RR=1.6, 95% CI 0.1–19.4). Risk of leukemia was also greater (RR=1.6, 95% CI 0.7–3.3) among the most exposed participants when assigning exposure categories based on petrol stations located within 250 m of the child’s residence and total amount of gasoline delivered by the stations. Overall, residence within close proximity to a petrol station, especially one with more intense refueling activity, was associated with an increased risk of childhood leukemia, though associations were imprecise.
Reclassification of two germline DICER1 splicing variants leads to DICER1 syndrome diagnosis
Authors: Apellaniz-Ruiz Maria , Sabbaghian Nelly , Chong Anne-Laure , de Kock Leanne , Cetinkaya Semra , Bayramoğlu Elvan , Dinjens Winand N. M. , McCluggage W. Glenn , Wagner Anja , Yilmaz Aslihan Arasli , Foulkes William D.
Published: May 2023

DICER1 syndrome is an inherited condition associated with an increased risk of developing hamartomatous and neoplastic lesions in diverse organs, mainly at early ages. Germline pathogenic variants in DICER1 cause this condition. Detecting a variant of uncertain significance in DICER1 or finding uncommon phenotypes complicate the diagnosis and can negatively impact patient care. We present two unrelated patients suspected to have DICER1 syndrome. Both females (aged 13 and 15 years) presented with multinodular goiter (thyroid follicular nodular disease) and ovarian tumours. One was diagnosed with an ovarian Sertoli-Leydig cell tumour (SLCT) and the other, with an ovarian juvenile granulosa cell tumour, later reclassified as a retiform variant of SLCT. Genetic screening showed no germline pathogenic variants in DICER1. However, two potentially splicing variants were found, DICER1 c.5365-4A>G and c.5527+3A>G. Also, typical somatic DICER1 RNase IIIb hotspot mutations were detected in the thyroid and ovarian tissues. In silico splicing algorithms predicted altered splicing for both germline variants and skipping of exon 25 was confirmed by RNA assays for both variants. The reclassification of the ovarian tumour, leading to recognition of the association with DICER1 syndrome and the characterization of the germline intronic variants were all applied to recently described DICER1 variant classification rules. This ultimately resulted in confirmation of DICER1 syndrome in the two teenage girls.
What is a Complex System, After All?
Authors: Estrada Ernesto
Published: May 2023

The study of complex systems, although an interdisciplinary endeavor, is considered as an integrating part of physical sciences. Contrary to the historical fact that the field is already mature, it still lacks a clear and unambiguous definition of its main object of study. Here, I propose a definition of complex systems based on the conceptual clarifications made by Edgar Morin about the bidirectional non-separability of parts and whole produced by the nature of interactions. Then, a complex system is defined as the system where there is a bidirectional non-separability between the identities of the parts and the identity of the whole. Thus, not only the identity of the whole is determined by the constituent parts, but also the identity of the parts are determined by the whole due to the nature of their interactions. This concept allows, as shown in the paper, to derive some of the main properties that such systems must have as well as to propose its mathematical formalization.
Callous-Unemotional Traits in Adolescents' Daily Life: Associations with Affect and Emotional and Conduct Problems
Authors: Goulter Natalie , Cooke Eric M. , Zheng Yao
Published: May 2023

Intensive longitudinal methods (e.g., daily diary) inform understanding of dynamic processes by parsing within-person state-like fluctuations from stable between-person trait-like differences. In this exploratory study, we investigated whether self-reported callous-unemotional (CU) traits (callousness, uncaring) demonstrated daily fluctuations, as well as whether daily CU traits were associated with multiple forms of daily emotional and behavioral functioning. A sample of 99 adolescents (55.8% female; Mage = 14.60 years) provided baseline information and completed a naturalistic 30-day diary reporting on CU traits, positive and negative affect, and emotional and conduct problems in their daily lives. Dynamic structural equation modeling revealed that many CU traits items showed within-person autoregressive and cross-lagged links; however, there was substantial between-person variation in within-person fluctuations across items. At the subscale level, cross-day associations were observed between callousness and uncaring, conduct problems and uncaring, positive affect and callousness, negative affect and emotional problems, and emotional problems and negative affect. By harnessing intensive longitudinal data, our findings provide preliminary state-level evidence of CU traits, as well as functional information with regards to CU traits and emotional and behavioral problems in daily life. We consider the implications of our findings in terms of informing future CU traits intensive longitudinal evaluations.
Participatory Methods to Engage Autistic People in the Design of Digital Technology: A Systematic Literature Review
Authors: Maun Rachael , Fabri Marc , Trevorrow Pip
Published: May 2023

Purpose

Many technology designers strive to involve end users in the design process, aiming to produce better outcomes. However, designers may struggle to engage autistic users effectively due to a lack of understanding of autistic characteristics and preferences. This systematic literature review aimed to identify how autistic adolescents and adults can best be engaged in effective participatory design activities.

Methods

Seven databases were searched for articles reporting technology design involving autistic people, returning 276 results. Using the PRISMA approach, 258 were excluded due to not meeting the inclusion criteria. The remaining 18 articles were then quality assessed.

Results

A thematic analysis revealed five core themes: (1) Engagement: the importance of investment in, and ownership of, the design process to create engagement, (2) Relationships: building relationships through collaboration and careful facilitation, (3) Skills development: the development of personal skills such as teamwork, design and self-advocacy in order to grow confidence, (4) Structure: providing context and structure to make the design experience feel safe and predictable, and (5) Support: the importance of support and consideration of individual needs as well as discouraging negative behaviours.

Conclusion

Valuing participants as equal partners in design emerged as an, arguably, universal principle. The specific needs and preferences of autistic people must be understood and respected by designers. This goes beyond obvious accommodations such as providing a quiet and safe environment, and requires a deeper, more personal engagement with the individuals and their interests. We provide tangible recommendations for increasing engagement and aiding the design process.
Collaborative robots in manufacturing and assembly systems: literature review and future research agenda
Authors: Keshvarparast Ali , Battini Daria , Battaia Olga , Pirayesh Amir
Published: May 2023

Nowadays, considering the constant changes in customers’ demands, manufacturing systems tend to move more and more towards customization while ensuring the expected reactivity. In addition, more attention is given to the human factors to, on the one hand, create opportunities for improving the work conditions such as safety and, on the other hand, reduce the risks brought by new technologies such as job cannibalization. Meanwhile, Industry 4.0 offers new ways to facilitate this change by enhancing human–machine interactions using Collaborative Robots (Cobots). Recent research studies have shown that cobots may bring numerous advantages to manufacturing systems, especially by improving their flexibility. This research investigates the impacts of the integration of cobots in the context of assembly and disassembly lines. For this purpose, a Systematic Literature Review (SLR) is performed. The existing contributions are classified on the basis of the subject of study, methodology, methodology, performance criteria, and type of Human-Cobot collaboration. Managerial insights are provided, and research perspectives are discussed.
A Primal-Dual Finite Element Method for Scalar and Vectorial Total Variation Minimization
Authors: Hilb Stephan , Langer Andreas , Alkämper Martin
Published: May 2023

Based on the Fenchel duality we build a primal-dual framework for minimizing a general functional consisting of a combined$$L^1$$L1and$$L^2$$L2data-fidelity term and a scalar or vectorial total variation regularisation term. The minimization is performed over the space of functions of bounded variations and appropriate discrete subspaces. We analyze the existence and uniqueness of solutions of the respective minimization problems. For computing a numerical solution we derive a semi-smooth Newton method on finite element spaces and highlight applications in denoising, inpainting and optical flow estimation.
Training for Supervisors to Improve Sustainable Employment of Employees with a work Disability: A Longitudinal Effect and Process Evaluation from an Intervention Study with Matched Controls
Authors: Schaap Rosanne , Coenen Pieter , Zwinkels Wim , de Wolff Marianne , Hazelzet Astrid , Anema Johannes
Published: May 2023

Purpose

Supervisors play a crucial role in sustainable employment of employees with a work disability. The ‘Mentorwijs’ (literal translation: Mentorwise) training was developed to train supervisors in knowledge, attitudes and skills needed to guide these employees. This study evaluated the effect of ‘Mentorwijs’ on employees’ employment and supervisors’ behavioral outcomes.

Methods

Register- and questionnaire data were obtained from 73 employees and 1,526 matched controls to measure employment (≥ 1/month, ≥ 12 h/week and ≥ 3 consecutive months (≥ 1 h/month)) during a 12-month follow-up period. Questionnaire data were obtained from 127 supervisors who followed the ‘Mentorwijs’ training, to assess their knowledge, self-efficacy, intention to adopt and applied behaviors.

Results

Employment for ≥ 1 h/month did not significantly improve after 3 (β = 0.05; CI=-0.07-0.16), 6 (β = 0.07; CI=-0.04-0.18), 9 (β = 0.08; CI=-0.02-0.18) and 12 (β = 0.01; CI=-0.08-0.10) months among employees whose supervisors followed ‘Mentorwijs’ compared to those who did not. Significant effects were found after 8 months (β = 0.11; CI = 0.01–0.21). Comparable effects were found for employment ≥ 12 hour/week and ≥ 3 consecutive months (≥ 1 hour/month). Supervisors’ knowledge and self-efficacy significantly improved as a result of ‘Mentorwijs’, but no effects were found for intention to adopt and applied behaviors.

Conclusions

‘Mentorwijs’ is a promising training to improve the guidance of employees with a work disability. Further research is needed to examine how long-term effects of ‘Mentorwijs’ on employment can be sustained.
Thermal properties of spark plasma sintered Inconel 625 modified by titanium zirconium mixed carbide
Authors: Rutkowski Paweł , Huebner Jan , Graboś Adrian , Kata D. , Pasiut Katarzyna , Handke Bartosz , Nieroda Paweł
Published: May 2023

Nickel-based superalloys are an important group of advanced engineering materials used for high-temperature and/or corrosive environments. Lately, in order to improve their mechanical properties, carbide reinforcement is added to a metal matrix, creating composites of improved hardness, shear resistance, or tensile resistance. In order to preserve the wide applicability of those materials, thermal properties, and corrosion resistance must also be evaluated. Presented research evaluated the thermal properties of Inconel 625—(Ti,Zr)C0.85 composites obtained at 1000 °C by spark plasma sintering process. Sinters containing 5–20 mass% of carbide phases were initially characterized in terms of their density, phase composition, and microstructure. A thorough examination of their thermal properties included: dilatometry, laser flash analysis, and differential scanning calorimetry. Conducted experiments revealed that a growing amount of carbide reinforcement decreased the thermal diffusivity and conductivity of samples. Other materials had a nonlinear correlation with that parameter. Performed analysis allowed to make an initial evaluation of oxidation resistance at 800 °C. It was shown that above 5 mass% addition of (Ti,Zr)C0.85 there is a considerable mass gain change shown by samples during the first hour of oxidation before passive layers were created. Suitable chemical reactions were predicted in order to describe the oxidation process of obtained composites.
Big Science, Big Trouble? Understanding Conflict in and Around Big Science Projects and Networks
Authors: Rüland Anna-Lena
Published: May 2023

Many Big Science projects and networks experience conflict. A plethora of disciplines have examined conflict causes in science collaboration and Big Science, contributing to a more nuanced understanding of why conflicts emerge. Yet, so far, there is no theoretical model that explains which mechanisms connect conflict cause and outbreak in Big Science. Drawing on interdisciplinary literature on science collaboration and Big Science as well as on scholarship on strategic action fields (SAFs), I address this blind spot by proposing a model that outlines which mechanisms induce and fuel conflict in Big Science projects and networks. Five interlinked mechanisms – attribution of threat or opportunity, mobilization of resources, coalition-building, boundary deactivation and innovative action – are central to it. Tracing these mechanisms in conflictual episodes which emerged in three typical, yet most-different, Big Science cases – the International Experimental Thermonuclear Reactor (ITER), the Human Brain Project (HBP) and the Thirty Meter Telescope (TMT) – this study also provides a proof of concept for the model.
Two-sample test for ambivalent subset relationship in fuzzy set qualitative comparative analysis
Authors: Veri Francesco
Published: May 2023

In fuzzy set qualitative comparative analysis (fsQCA), ambivalent subset relationships (ASR), occur when solution term X is in subset relation with the outcome Y and its absence ~ Y, leading to false-positive results. While ASR can be empirically detected in small-N and medium-N cases through in-depth case knowledge, it is challenging to identify them in large-N case designs. QCA parameters such as proportion reduction inconsistency (PRI) and consistency are commonly used to identify simultaneous subset relationships (SSR), but they are not specifically designed to detect ASR. To address this issue, this article introduces the DTS test, a new test based on two-sample statistics. The DTS test identifies distributional convergence between a solution term’s empirical cumulative distribution function (eCDF) and an eCDF of solution formulas with asymptotic ASR characteristics. By comparing empirical solutions’ patterns with spurious artificially built solutions' patterns, the DTS test reduces the risk of causal fallacies in interpreting the empirical results. Overall, the DTS test provides a valuable tool for identifying and addressing potential ASR bias in fsQCA, particularly in large-N case designs.
Mental health-related quality of life in mothers of children with surgically repaired congenital heart disease: a 13-year longitudinal study
Authors: Ehrler Melanie , Wettach Corina , Beck Ingrid , Valsangiacomo Buechel Emanuela R. , Latal Beatrice , Landolt Markus A.
Published: May 2023

Aims

Having a child with congenital heart disease (CHD) can affect parental health-related quality of life (HR-QoL). We investigated the long-term trajectories of mental HRQoL (m-HRQoL) in mothers of children with CHD and examined risk factors for persistent low m-HRQoL.

Methods

One hundred twenty-five mothers of children with CHD completed a standardized questionnaire on m-HRQoL (mental subscale SF-12) after the children’s first open-heart surgery and subsequently when the children were 1, 4, 6, 10, and 13 years old. A z-score for m-HRQoL was calculated with national norms. Latent class growth analysis (LCGA) was used to identify subgroups of mothers with regards to their m-HRQoL trajectories over time. Regression analysis investigated predictors for chronically low m-HRQoL.

Results

Compared to norms, mothers of children with CHD had significantly lower m-HRQoL immediately after open-heart surgery (β = −0.30 (CI-95: −0.44, −0.15)). Subsequently, m-HRQoL increased to a normal level (m-HRQoL compared to the norm from 1 to 13 years: β ranges between 0.05 and 0.27). LCGA revealed two distinct groups of m-HRQoL trajectories: A group with normal m-HRQoL (75% of mothers, means z-scores range between − 0.76 and 0.62) and a group with chronically low m-HRQoL (25% of mothers, mean z-scores range between −1.32 and −0.10). Chronically, low m-HRQoL was associated with poorer social support (OR = 3.39 (CI-95: 1.40, 8.49), p = 0.008) but not with parental education, migration background, number of open-heart surgeries, diagnosis of a univentricular CHD, or low IQ.

Conclusion

A quarter of mothers of children with CHD have chronically low m-HRQoL throughout their child’s development, especially those mothers with poor social support. Further studies of family-oriented approaches are needed to identify and support these mothers and reinforce parental well-being.
Spatiotemporal variation in water availability drives insect community dynamics in an urban riparian zone
Authors: Bonfoey Alyssa , Padda Sugjit Singh , Stahlschmidt Zachary
Published: May 2023

Water bodies can mitigate urban heat island effects and allow terrestrial animals to access water during periods of insufficient precipitation. Because precipitation is expected to become increasingly scarce in many global regions, urban riparian areas in drylands may yield important insight into the dynamic role of water in terrestrial animal communities. Here, we first investigated the role of spatiotemporal variability in water availability in insect biomass and biodiversity in an urban riparian area—particularly, whether seasonality modulates the spatial effects of water availability. High water availability was characterized spatially by proximity to a river, and temporally by high-precipitation seasons. Second, we investigated whether the relationship between biomass and biodiversity shifts due to variation in water availability. We determined the biomass and biodiversity of an insect community across a riparian zone in Stockton, CA, USA, an urban drylands area characterized by hot, dry summers and cool, wet winters. Time (seasonality exhibiting dramatic variation in precipitation) exerted strong effects on ecological indices and a biodiversity-biomass relationship. Space (proximity to a fixed water source) had more modest effects on the community, and there was some evidence that space and time modulated the effects of one another on the community. Urban animal community dynamics may be more sensitive to larger-scale climate patterns than to local, landscape-level factors, and covariation between biomass and biodiversity may be influenced by resource (water) availability. Studying insect communities in the riparian zones of urban drylands may be critical to understanding how animal communities respond to a warmer, drier climate.
Brief report first report of the in vitro ovicidal activity of camel milk and its fractions on zoonotic-liver fluke (Fasciola gigantica) eggs
Authors: Awad Dina A.B. , Eldiarby Amany S. , Abdallah Mona , Hamad Ahmed , Gawad Samah M. Abdel
Published: May 2023

Fasciola gigantica is one of the worldwide parasites that cause livestock and human illnesses. Chemotherapy is now the primary therapeutic option for its treatment. Drug abuse has led to the emergence of drug-resistant strains. As a result, there is an urgent need to discover natural and efficient anthelmintics against Fasciola spp. The study aims to evaluate the ovicidal activities of camel milk and its fractions on F. gigantica eggs. In the in vitro assay of F. gigantica eggs were submitted to different concentrations (0.5% and 1%) of camel milk fractions; Camel Milk Whey (CMW), Camel Milk Casein (CMC), and Skimmed Camel Milk (SCM) as well as a positive control (PC) of Nitroxynil (100 mg/ml) and a negative control (NC) with physiological saline. The Egg Hatching Assay (EHA) results showed that camel milk fractions exhibited ovicidal activity, especially CMW, and CMC, which showed 97.58 ± 0.58 and 96.9 ± 1.99 ovicidal activity, respectively, at a concentration of 1% after 15 days of treatment compared to PC, which exhibited 91.75 ± 4.95 ovicidal activity. The egg hatching ratios were 1.67% and 2.33% for CMW and CMC, respectively, compared to 70.17% for the NC and 6% for the PC. The LC50 values for CMW and CMC on the 15th day of treatment were 0.20 and 9.13, respectively. From the results above, we can infer that camel milk and its fractions are promising as a new alternative for fascioliasis control.
A stepwise approach for Scenario-based Inventory Modelling for Prospective LCA (SIMPL)
Authors: Langkau Sabine , Steubing Bernhard , Mutel Christopher , Ajie Maulana Permana , Erdmann Lorenz , Voglhuber-Slavinsky Ariane , Janssen Matty
Published: May 2023

Purpose

In prospective life cycle assessment (pLCA), inventory models represent a future state of a production system and therefore contain assumptions about future developments. Scientific quality should be ensured by using foresight methods for handling these future assumptions during inventory modelling. We present a stepwise approach for integrating future scenario development into inventory modelling for pLCA studies.

Methods

A transdisciplinary research method was used to develop the SIMPL approach for scenario-based inventory modelling for pLCA. Our interdisciplinary team of LCA and future scenario experts developed a first draft of the approach. Afterwards, 112 LCA practitioners tested the approach on prospective case studies in group work projects in three courses on pLCA. Lessons learned from application difficulties, misunderstandings and feedback were used to adapt the approach after each course. After the third course, reflection, discussion and in-depth application to case studies were used to solve the remaining problems of the approach. Ongoing courses and this article are intended to bring the approach into a broader application.

Results and discussion

The SIMPL approach comprises adaptations and additions to the LCA goal and scope phase necessary for prospective inventory modelling, particularly the prospective definition of scope items in reference to a time horizon. Moreover, three iterative steps for combined inventory modelling and scenario development are incorporated into the inventory phase. Step A covers the identification of relevant inventory parameters and key factors, as well as their interrelations. In step B, future assumptions are made, by either adopting them from existing scenarios or deriving them from the available information, in particular by integrating expert and stakeholder knowledge. Step C addresses the combination of assumptions into consistent scenarios using cross-consistency assessment and distinctness-based selection. Several iterations of steps A–C deliver the final inventory models.

Conclusion

The presented approach enables pLCA practitioners to systematically integrate future scenario development into inventory modelling. It helps organize possible future developments of a technology, product or service system, also with regard to future developments in the social, economic and technical environment of the technology. Its application helps to overcome implicit bias and ensures that the resulting assessments are consistent, transparently documented and useful for drawing practically relevant conclusions. The approach is also readily applicable by LCA practitioners and covers all steps of prospective inventory modelling.
Causal reasoning with causal graphs in educational technology research
Authors: Weidlich Joshua , Hicks Ben , Drachsler Hendrik
Published: May 2023

Researchers tasked with understanding the effects of educational technology innovations face the challenge of providing evidence of causality. Given the complexities of studying learning in authentic contexts interwoven with technological affordances, conducting tightly-controlled randomized experiments is not always feasible nor desirable. Today, a set of tools is available that can help researchers reason about cause-and-effect, irrespective of the particular research design or approach. This theoretical paper introduces such a tool, a simple graphical formalism that can be used to reason about potential sources of bias. We further explain how causal graphs differ from structural equation models and highlight the value of explicit causal inference. The final section shows how causal graphs can be used in several stages of the research process, whether researchers plan to conduct observational or experimental research.
Quaternionic phase and axis/colour retrieval
Authors: Zimmermann Martha L. , Bernstein Swanhild , Heise Bettina
Published: May 2023

We demonstrate a quaternion-based phase and axis retrieval algorithm and a quaternionic realization of the Gerchberg–Saxton method, particularly suitable for RGB images. The RGB image is represented here as quaternion-valued image in polar form with the components quaternionic magnitude, axis and phase. We discuss their importance and relations in spatial and Fourier domain. We illustrate three versions of retrieval: the quaternionic phase only, the axis only and the joint phase and axis retrieval algorithm derived from the classical Gerchberg–Saxton algorithm. We discuss how the retrieval results are influenced by the choice of the Fourier axis of the quaternionic Fourier transform. Finally, we show that by including more constraints and prior knowledge, respectively, the retrieval can be improved.
Temporary Employment of First-Generation Migrants in the Netherlands
Authors: Boffi Giacomo
Published: May 2023

The Netherlands is the European country that has undergone the highest increase in temporary jobs in the last decade. These occupations are characterized by a low level of job security and, in the case of older workers, may lead to social exclusion and higher welfare dependence. Using the LISS panel data (2008–2019) for the resident population of the Netherlands, this paper establishes an innovative link between migration background and temporary employment. First, it is investigated whether first-generation migrants (western and non-western) are more likely to be temporarily employed than Dutch-born natives. Besides, it is explored whether higher education, language problems, and active social contacts influence this relationship. The findings show that non-western migrants are more likely to be temporarily employed than both western migrants and Dutch-born natives. Language problems are the main moderator increasing migrants’ probability of being temporarily employed, while higher education and active social contacts appear not to be significant.
Inactivation of zearalenone (ZEN) and deoxynivalenol (DON) in complete feed for weaned piglets: Efficacy of ZEN hydrolase ZenA and of sodium metabisulfite (SBS) as feed additives
Authors: Dänicke Sven , Carlson Linn , Heymann Ann-Katrin , Grümpel-Schlüter Angelika , Doupovec Barbara , Schatzmayr Dian , Streit Barbara , Kersten Susanne , Kluess Jeannette
Published: May 2023

Female pigs respond sensitive both to DON and ZEN with anorexia and endocrine disruption, respectively, when critical diet concentrations are exceeded. Therefore, the frequent co-contamination of feed by DON and ZEN requires their parallel inactivation. The additive ZenA hydrolyzes ZEN while SBS inactivates DON through sulfonation. Both supplements were simultaneously added (+, 2.5 g SBS and 100 U ZenA/kg) to a control diet (CON−, 0.04 mg DON and < 0.004 mg ZEN/kg; CON+, 0.03 mg DON and < 0.004 mg ZEN/kg) and a Fusarium toxin contaminated diet (FUS−, 2.57 mg DON and 0.24 mg ZEN/kg; FUS+, 2.04 mg DON and 0.24 mg ZEN/kg). The 4 diets were fed to 20 female weaned piglets each (6 kg initial body weight) for 35 days; the piglets were sacrificed thereafter for collecting samples. Supplements improved performance and modified metabolism and hematology independent of dietary DON contamination. The mechanisms behind these changes could not be clarified and require further consideration. SBS reduced DON concentration in feed by approximately 20% and to the same extent in blood plasma and urine suggesting that no further DON sulfonate formation occurred in the digestive tract before absorbing DON in the upper digestive tract or that additionally formed DON sulfonates escaped absorption. DON sulfonates were detected in feces suggesting that unabsorbed DON sulfonates reached feces and/or that unabsorbed DON was sulfonated in the hindgut. The observed reduction rate of 20% was evaluated to be insufficient for feeding practice. Galenic form of SBS added to dry feed needs to be improved to support the DON sulfonation in the proximal digestive tract.ZenA was active in the digestive tract as demonstrated by the presence of its hydrolyzed none-estrogenic reaction products hydrolyzed ZEN (HZEN) and decarboxylated and hydrolyzed ZEN (DHZEN) both in feces, systemic circulation, and urine of group FUS+ compared to group FUS−. The presence of these hydrolysis products was paralleled by a significant decrease in high-estrogenic ZEN concentrations which, in turn, was related to a decrease in relative weights of uteri and ovaries when compared to group FUS−. Thus, ZenA was proven to be effective; both in terms of biomarkers and biological effects.
Being certain about uncertainties: a robust evaluation method for high-dose-rate prostate brachytherapy treatment plans including the combination of uncertainties
Authors: Kennedy Andrew C. , Douglass Michael J. J. , Santos Alexandre M. C.
Published: May 2023

In high-dose-rate (HDR) prostate brachytherapy the combined effect of uncertainties cause a range of possible dose distributions deviating from the nominal plan, and which are not considered during treatment plan evaluation. This could lead to dosimetric misses for critical structures and overdosing of organs at risk. A robust evaluation method to assess the combination of uncertainties during plan evaluation is presented and demonstrated on one HDR prostate ultrasound treatment plan retrospectively. A range of uncertainty scenarios are simulated by changing six parameters in the nominal plan and calculating the corresponding dose distribution. Two methods are employed to change the parameters, a probabilistic approach using random number sampling to evaluate the likelihood of variation in dose distributions, and a combination of the most extreme possible values to access the worst-case dosimetric outcomes. One thousand probabilistic scenarios were run on the single treatment plan with 43.2% of scenarios passing seven of the eight clinical objectives. The prostate D90 had a standard deviation of 4.4%, with the worst case decreasing the dose by up to 27.2%. The urethra D10 was up to 29.3% higher than planned in the worst case. All DVH metrics in the probabilistic scenarios were found to be within acceptable clinical constraints for the plan under statistical tests for significance. The clinical significance of the results from the robust evaluation method presented on any individual treatment plan needs to be compared in the context of a historical data set that contains patient outcomes with robustness analysis data to ascertain a baseline acceptance.
A Variance Partitioning Multi-level Model for Forest Inventory Data with a Fixed Plot Design
Authors: Marques Isa , Wiemann Paul F. V. , Kneib Thomas
Published: May 2023

Forest inventories are often carried out with a particular design, consisting of a multi-level structure of observation plots spread over a larger domain and a fixed plot design of exact observation locations within these plots. Consequently, the resulting data are collected intensively within plots of equal size but with much less intensity at larger spatial scales. The resulting data are likely to be spatially correlated both within and between plots, with spatial effects extending over two different areas. However, a Gaussian process model with a standard covariance structure is generally unable to capture dependence at both fine and coarse scales of variation as well as for their interaction. In this paper, we develop a computationally feasible multi-level spatial model that accounts for dependence at multiple scales. We use a data-driven approach to determine the weight of each spatial process in the model to partition the variability of the measurements. We use simulated and German small tree inventory data to evaluate the model’s performance.Supplementary material to this paper is provided online.