bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reduced Belief Updating in the Context of Depressive Symptoms: An Investigation of the Associations with Interpretation Biases and Self-Evaluation
Authors: Würtz Felix , Kube Tobias , Woud Marcella L. , Margraf Jürgen , Blackwell Simon E. 
Published: January 2024

Abstract
Background
Depressive symptoms are associated with negative expectations and reduced belief updating by positive information. Cognitive immunization, the devaluation of positive information, has been argued to be central in this relationship and predictive processing models suggest that more positive information is associated with greater cognitive immunization.

Methods
In an online experiment, N = 347 healthy participants took part in a performance task with standardized feedback of varying levels of positivity (mild, moderate, extreme). Effects of feedback positivity on cognitive immunization were investigated. Further, depressive symptoms, interpretation bias and participant’s self-evaluation were examined as potential correlates of belief updating.

Results
As expected, participants receiving mildly positive feedback reported a greater amount of cognitive immunization than those receiving moderately positive feedback. However, neither group differed from those receiving extremely positive feedback. Although depressive symptoms did not show the hypothesized association with cognitive immunization, they were associated with a weaker increase in positive expectations following feedback. Exploratory analyses showed associations between self-evaluation and belief updating.

Conclusions
The results suggest that healthy participants engaged in cognitive immunization when feedback was less positive than expected. Depressive symptoms were associated with reduced belief updating, but not with cognitive immunization. Self-evaluation may be a promising factor for future research.
Enhancing historical thinking through learning analytics in Primary Education: A bridge to formative assessment
Authors: Tirado-Olivares Sergio , López-Fernández Carlota , González-Calero José Antonio , Cózar-Gutiérrez Ramón 
Published: January 2024

AbstractHistory teaching from early educational stages not only should assess the student's ability to memorise historical content, but also their ability to think historically. Traditional summative tests do not enable teachers to continuously monitor the progress of students. This study evaluates the effect in history learning of incorporating learning analytics (LA) in terms of academic achievement and self-efficacy. Seventy-six elementary students aged 10–12 years old participated in the study. The results indicate that the integration of LA particularly helped students with low historical knowledge and enabled the prediction of academic achievement, especially in historical thinking. The results also highlight the disparity between students' knowledge and students' self-efficacy during the lessons, and what they demonstrate in exams, indicating the need to incorporate tasks before exams that allow students to identify their limitations and misconceptions. These results suggest that LA in history teaching may provide teachers with useful information for formative assessment.
Menopausal hormone therapy and risk of sarcoidosis: a population-based nested case–control study in Sweden
Authors: Dehara Marina , Kullberg Susanna , Bixo Marie , Sachs Michael C. , Grunewald Johan , Arkema Elizabeth V. 
Published: January 2024

AbstractSarcoidosis incidence peaks in women between 50 and 60 years old, which coincides with menopause, suggesting that certain sex hormones, mainly estrogen, may play a role in disease development. We investigated whether menopausal hormone therapy (MHT) was associated with sarcoidosis risk in women and whether the risk varied by treatment type. We performed a nested case–control study (2007–2020) including incident sarcoidosis cases from the Swedish National Patient Register (n = 2593) and matched (1:10) to general population controls (n = 20,003) on birth year, county, and living in Sweden at the time of sarcoidosis diagnosis. Dispensations of MHT were obtained from the Swedish Prescribed Drug Register before sarcoidosis diagnosis/matching. Adjusted odds ratios (aOR) of sarcoidosis were estimated using conditional logistic regression. Ever MHT use was associated with a 25% higher risk of sarcoidosis compared with never use (aOR 1.25, 95% CI 1.13–1.38). When MHT type and route of administration were considered together, systemic estrogen was associated with the highest risk of sarcoidosis (aOR 1.51, 95% CI 1.23–1.85), followed by local estrogen (aOR 1.25, 95% CI 1.11–1.42), while systemic estrogen-progestogen combined was associated with the lowest risk compared to never users (aOR 1.12, 95% CI 0.96–1.31). The aOR of sarcoidosis did not differ greatly by duration of MHT use. Our findings suggest that a history of MHT use is associated with increased risk of sarcoidosis, with women receiving estrogen administered systemically having the highest risk.
Customer satisfaction in the pet food subscription-based online services
Authors: Lima Diogo , Ramos Ricardo F. , Oliveira Pedro Miguel 
Published: January 2024

AbstractPet food subscription-based online services (SOS) fulfill the demand for pet food that fits pets’ characteristics and health necessities. The present research explores the antecedents of pet food SOS customer satisfaction and its effect on continuance intention, positively moderated by price. 28,786 online reviews from 10 pet food SOS brands were collected from Trustpilot to generate a term-frequency matrix through text mining techniques and used as an input to construct a structural equation model. Results suggest that e-service quality (E-SQ), perceived healthfulness, ingredients and nutritional composition, and packaging positively influence customer satisfaction, subsequently predicting continuance intention. In turn, price was not confirmed as a positive moderating factor in the relationship between customer satisfaction and continuance intention.
Toward the concurrent self-evaluation of solidarity in platform-based development: a case study of discrepancies among technological interpretation in Japan
Authors: Kihira Mariko , Maruyama Yasushi 
Published: January 2024

AbstractModern global agriculture requires an innovative trade-off and balance between crop productivity and environmental sustainability. Determining this balance requires the participatory development of farmers, although this often fails due to discrepancies. In our view, successful participatory development is based on concurrent self-evaluations that enable stakeholders to recognize discrepancies and to fairly and constructively build solidarity. This paper is aimed at identifying discrepancies in the interpretation of technologies using a case study of a multistakeholder platform used for biological soil diagnosis in Hamamatsu city, Japan. A combination of a narrative approach and the application of co-occurrence networks is taken based on the qualitative data for farmers, research experts, research institutions, and governmental agents. The analyses revealed that highly and less engaged farmers, researchers, and local governments have different interpretations of technological perfection, technological uncertainty, and technological perception. These interpretations are associated with engagement. In summary, the cognitive differences among the stakeholders of participatory projects can be objectively assessed in the form of concurrent self-evaluations using the mixed research method proposed in this paper.
Home range and notes about social interactions in the poison frog Phyllobates vittatus (Anura: Dendrobatidae)
Authors: Garrido-Priego Marina , Monge-Velázquez Michelle , Whitworth Andrew , Gomez-Mestre Ivan 
Published: January 2024

AbstractUnderstanding animal movements is vital for gaining insights into species' ecological patterns, habitat preferences, and reproductive strategies. Studies in dendrobatid frogs have revealed that home range behaviours, particularly in species with male parental care, are closely linked to the distribution of reproductive resources. Here we focus on males of the poison frog Phyllobates vittatus, endemic to the southern Pacific of Costa Rica to determine males’ home range size and the degree of overlap between individuals of P. vittatus. Sixteen individuals were tracked using harmonic direction finder over 4–5 days each, revealing an average minimum convex polygon area of 55.7 m2 and a 50% kernel density estimates area of 26.75 m2. Overlapping areas indicated shared home ranges, possibly due to resource distribution. Contrary to prior expectations, we did not observe aggressive encounters between males tracked but we observed one aggressive event between two males carrying tadpoles. Notably, we observed a novel behaviour: a female apparently defending tadpoles from a perceived male intruder. These findings provide important insights into P. vittatus’ behaviour and space use, which are key to developing and implementing conservation strategies, especially considering its vulnerable status and the limited available data on this endemic species.
Assessing Long-Term Excavation Damage in Switzerland’s Bedretto Adit: A Field Investigation in the Northern Section
Authors: Alcaino-Olivares Rodrigo , Paraskevopoulou Chrysothemis , Perras Matthew A. 
Published: January 2024

AbstractThe Bedretto adit, in the Alps of Switzerland, was excavated in 1972–1982 as an auxiliary adit for the main Furka Base Tunnel. The adit is 5218 m long, being excavated mostly in the Rotondo Granite with drill and blast methods to create a horseshoe cross-section. Much of the tunnel has remained unlined and such long observation periods are seldom available since tunnels typically are lined shortly after construction and mines are often closed or backfilled. Previous research in 2004 characterized the depth of failure (DoF) around the adit and found on average a depth of 1.1 ± 0.03 m. A site investigation was carried out in 2017, aimed to measure the DoF through 3D light detection and ranging scanned sections again. The new 3D scans covered a longer section of the tunnel with each scan, up to 6 m in length, compared to the previous laser scans with a single circumferential pass. The results were compared with the data from 2004 and with empirical and numerical prediction curves for Excavation Damage Zone depths. The findings indicate that between 2004 and 2017, the measured DoF generally extended, on average, by 0.1 m, implying that failure has progressed with time. Furthermore, the analysis showed that the volume of failure from 2004 extended up to 1.9 m3/m, and this volume increased to 3.2 m3/m in 2017 on average. The VoF was used as a means to overcome the challenge of comparing past to present scan results, since the exact location of the 2004 measurements were not known. Significant variations in the measured DoF at sections of the adit near faults and below a glacier indicate that these external factors can significantly influence the rock mass behaviour. When comparing the DoF to empirical excavation damage zone prediction intervals, the level of damage at the Bedretto adit is comparable with the outer excavation damage zone. This is a region of isolated micro-cracking, and it conceptually suggests that the continued spalling in the Bedretto adit is the results of crack propagation from initial excavation induced damage that leads to interaction even after 41 years since excavation works ceased.
Unimodular gravity in covariant formalism
Authors: Klusoň J. , Matouš B. 
Published: January 2024

AbstractIn this short note we study unimodular gravity in Weyl-De Donder formalism. We find corresponding Hamiltonian and study consequence of the unimodular constraint on the conjugate covariant momenta. We also find covariant Hamiltonian for Henneaux-Teitelboim unimodular action and study corresponding equations of motion.
Grandparental childcare, family allowances and retirement policies
Authors: Cipriani Giam Pietro , Fioroni Tamara 
Published: January 2024

AbstractThe paper uses an OLG model to study the interaction between policies designed to ensure the sustainability of the pension system, i.e. child allowances and pensions policies, and grandparental childcare. We find that the rise in grandparenting negatively affects the elderly labour supply hampering the impact of pension policies designed to raise the retirement age and lengthen working lives. Then, we introduce child allowances and find that the impact of child allowances on the fertility rate is influenced by the efficiency of grandparenting in reducing child-rearing costs. Child benefits have a positive impact on fertility only if grandparenting is not very effective at reducing childcare costs. This suggests that the role of grandparents in various countries may partly explain the inconsistency in empirical evidence on the relationship between child benefits and fertility rates. The study also finds that child benefits have a positive impact on the elderly labour supply when grandparenting is efficient.
Case study on delivery time determination using a machine learning approach in small batch production companies
Authors: Rokoss Alexander , Syberg Marius , Tomidei Laura , Hülsing Christian , Deuse Jochen , Schmidt Matthias 
Published: January 2024

AbstractDelivery times represent a key factor influencing the competitive advantage, as manufacturing companies strive for timely and reliable deliveries. As companies face multiple challenges involved with meeting established delivery dates, research on the accurate estimation of delivery dates has been source of interest for decades. In recent years, the use of machine learning techniques in the field of production planning and control has unlocked new opportunities, in both academia and industry practice. In fact, with the increased availability of data across various levels of manufacturing companies, machine learning techniques offer the opportunity to gain valuable and accurate insights about production processes. However, machine learning-based approaches for the prediction of delivery dates have not received sufficient attention. Thus, this study aims to investigate the ability of machine learning to predict delivery dates early in the ordering process, and what type of information is required to obtain accurate predictions. Based on the data provided by two separate manufacturing companies, this paper presents a machine learning-based approach for predicting delivery times as soon as a request for an offer is received considering the desired customer delivery date as a feature.
Position and Attitude Tracking Controllers Using Lyapunov Transformations for Quadrotors
Authors: Madeiras João , Cardeira Carlos , Oliveira Paulo 
Published: January 2024

AbstractIn this paper, a novel feedback control strategy for quadrotor trajectory tracking is designed and experimentally tested with proof of exponential stability, using the Lyapunov transformations theory. The controller is derived from an inner-outer loop control structure, namely by considering the position system coupled through an interconnection term with the attitude system. For the design of the position controller, the considered dynamics are worked on the body frame, which is uncommon in the literature, and its synthesis derives from theories such as Pontryagin’s maximum principle, Lyapunov theory, and Linear Quadratic Regulator (LQR), which ensure Input-to-state stability, steady-state optimality, and global exponential stability. The attitude system is based on an error quaternion parameterization via a nonlinear coordinate transformation matrix followed by a state input feedback, rendering the system linear and time-invariant. Under a correct transformation, LQR theory ensures almost exponential stability and steady-state optimality for the overall interconnected closed-loop systems. Experimental and simulation results illustrate the performance of the tracking system onboard a quadrotor.
PANACEA: a neural model ensemble for cyber-threat detection
Authors: AL-Essa Malik , Andresini Giuseppina , Appice Annalisa , Malerba Donato 
Published: January 2024

AbstractEnsemble learning is a strategy commonly used to fuse different base models by creating a model ensemble that is expected more accurate on unseen data than the base models. This study describes a new cyber-threat detection method, called , that uses ensemble learning coupled with adversarial training in deep learning, in order to gain accuracy with neural models trained in cybersecurity problems. The selection of the base models is one of the main challenges to handle, in order to train accurate ensembles. This study describes a model ensemble pruning approach based on eXplainable AI (XAI) to increase the ensemble diversity and gain accuracy in ensemble classification. We base on the idea that being able to identify base models that give relevance to different input feature sub-spaces may help in improving the accuracy of an ensemble trained to recognise different signatures of different cyber-attack patterns. To this purpose, we use a global XAI technique to measure the ensemble model diversity with respect to the effect of the input features on the accuracy of the base neural models combined in the ensemble. Experiments carried out on four benchmark cybersecurity datasets (three network intrusion detection datasets and one malware detection dataset) show the beneficial effects of the proposed combination of adversarial training, ensemble learning and XAI on the accuracy of multi-class classifications of cyber-data achieved by the neural model ensemble.
Re-analyzing ‘say’ complementation: Implications for case theory and beyond
Authors: Major Travis 
Published: January 2024

AbstractThis paper argues based on data from Uyghur (Turkic) that clausal complementation structures involving a special form of the verb ‘say’ are actually adjunct clauses headed by the verb ‘say’ that merge at two heights: VP or TP. I demonstrate that properties unique to ‘say’ as a main verb extend to ‘say’ in these adjunct clauses. Accusative subjects are a primary focus, where it is shown that the re-analysis of clausal complementation has implications for Case Theory in Uyghur and beyond.
Investigating the effects of PTEN mutations on cGAS-STING pathway in glioblastoma tumours
Authors: Dogan Eda , Yildirim Zafer , Akalin Taner , Ozgiray Erkin , Akinturk Nevhis , Aktan Cagdas , Solmaz Asli Ece , Biceroglu Huseyin , Caliskan Kadri Emre , Ertan Yesim , Yurtseven Taskin , Kosova Buket , Bozok Vildan 
Published: January 2024

Abstract
Background
PTEN is a tumour suppressor gene and well-known for being frequently mutated in several cancer types. Loss of immunogenicity can also be attributed to PTEN loss, because of its role in establishing the tumour microenvironment. Therefore, this study aimed to represent the link between PTEN and cGAS-STING activity, a key mediator of inflammation, in tumour samples of glioblastoma patients.

Methods
Tumour samples of 36 glioblastoma patients were collected. After DNA isolation, all coding regions of PTEN were sequenced and analysed. PTEN expression status was also evaluated by qRT-PCR, western blot, and immunohistochemical methods. Interferon-stimulated gene expressions, cGAMP activity, CD8 infiltration, and Granzyme B expression levels were determined especially for the evaluation of cGAS-STING activity and immunogenicity.

Results
Mutant PTEN patients had significantly lower PTEN expression, both at mRNA and protein levels. Decreased STING, IRF3, NF-KB1, and RELA mRNA expressions were also found in patients with mutant PTEN. Immunohistochemistry staining of PTEN displayed expressional loss in 38.1% of the patients. Besides, patients with PTEN loss had considerably lower amounts of IFNB and IFIT2 mRNA expressions. Furthermore, CD8 infiltration, cGAMP, and Granzyme B levels were reduced in the PTEN loss group.

Conclusion
This study reveals the immunosuppressive effects of PTEN loss in glioblastoma tumours via the cGAS-STING pathway. Therefore, determining the PTEN status in tumours is of great importance, like in situations when considering the treatment of glioblastoma patients with immunotherapeutic agents.
Reaction Mechanisms and Plasma-Catalyst Interaction in Plasma-Assisted Oxidation of n-Butane: A Data-Driven Approach
Authors: Reiser D. , von Keudell A. 
Published: January 2024

AbstractExperimental investigations of n-butane oxidation under atmospheric-pressure plasma conditions and in He-dilution have provided detailed information on the power-dependence of the conversion of $$\text {C}_{4}\text {H}_{10}$$

C
4

H
10

into CO and $$\text {CO}_{2}$$

CO
2

at 450 K surface temperature. The rf-plasma discharge has been equipped with a $$\text {MnO}_{2}$$

MnO
2

-catalyst, and a significant impact on the reaction chain due to the presence of the catalyst surface could be observed. We report on ongoing data-based model development. Recently, a reaction kinetic model has been published, which agrees well with the experimental data (Stewig et al. in Plasma Sources Sci Technol 32:105006, 2023). However, that model could not clearly identify the main mechanisms in the interaction of plasma and catalyst. We show that various models can be found that explain the data similarly well. Detailed sensitivity analysis shows that only a maximum of three parameters can be identified in all the models considered for the currently limited data. Despite this limitation, we intend to continue the data analysis using more general models and introduce possible surface effects. Such unified models simultaneously describe the experimental data from both measurements with and without catalyst using a single set of physical parameters. To evaluate the hypotheses, we present numerical results for certain ranges of experimental parameters, which, in a subsequent experimental verification, allows to exclude or confirm one or another model.