bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Spectral X-Ray Imaging for Panoramic Dental Images Based on a Simulation Framework
Authors: Berthe Daniel , Kolb Anna , Rabi Abdulrahman , Sellerer Thorsten , Somerkivi Villseveri , Feuerriegel Georg Constantin , Sauter Andreas Philipp , Meurer Felix , Hämisch York , Pantsar Tuomas , Lohman Henrik , Pfeiffer Daniela , Pfeiffer Franz
Published: January 2024

Modern photon counting detectors allow the calculation of virtual monoenergetic or material decomposed X-ray images but are not yet used for dental panoramic radiography systems. To assess the diagnostic potential and image quality of photon counting detectors in dental panoramic radiography, ethics approval from the local ethics committee was obtained for this retrospective study. Conventional CT scans of the head and neck region were segmented into bone and soft tissue. The resulting datasets were used to calculate panoramic equivalent thickness bone and soft tissue images by forward projection, using a geometry like that of conventional panoramic radiographic systems. The panoramic equivalent thickness images were utilized to generate synthetic conventional panoramic radiographs and panoramic virtual monoenergetic radiographs at various energies. The conventional, two virtual monoenergetic images at 40 keV and 60 keV, and material-separated bone and soft tissue panoramic equivalent thickness X-ray images simulated from 17 head CTs were evaluated in a reader study involving three experienced radiologists regarding their diagnostic value and image quality. Compared to conventional panoramic radiographs, the material-separated bone panoramic equivalent thickness image exhibits a higher image quality and diagnostic value in assessing the bone structure $$\left(p<.001\right)$$

p
<
.
001

and details such as teeth or root canals $$\left(p<.001\right)$$

p
<
.
001

. Panoramic virtual monoenergetic radiographs do not show a significant advantage over conventional panoramic radiographs. The conducted reader study shows the potential of spectral X-ray imaging for dental panoramic imaging to improve the diagnostic value and image quality.
Using the Textual Content of Radiological Reports to Detect Emerging Diseases: A Proof-of-Concept Study of COVID-19
Authors: Crombé Amandine , Lecomte Jean-Christophe , Seux Mylène , Banaste Nathan , Gorincour Guillaume
Published: January 2024

Changes in the content of radiological reports at population level could detect emerging diseases. Herein, we developed a method to quantify similarities in consecutive temporal groupings of radiological reports using natural language processing, and we investigated whether appearance of dissimilarities between consecutive periods correlated with the beginning of the COVID-19 pandemic in France. CT reports from 67,368 consecutive adults across 62 emergency departments throughout France between October 2019 and March 2020 were collected. Reports were vectorized using time frequency–inverse document frequency (TF-IDF) analysis on one-grams. For each successive 2-week period, we performed unsupervised clustering of the reports based on TF-IDF values and partition-around-medoids. Next, we assessed the similarities between this clustering and a clustering from two weeks before according to the average adjusted Rand index (AARI). Statistical analyses included (1) cross-correlation functions (CCFs) with the number of positive SARS-CoV-2 tests and advanced sanitary index for flu syndromes (ASI-flu, from open-source dataset), and (2) linear regressions of time series at different lags to understand the variations of AARI over time. Overall, 13,235 chest CT reports were analyzed. AARI was correlated with ASI-flu at lag = + 1, + 5, and + 6 weeks (P = 0.0454, 0.0121, and 0.0042, respectively) and with SARS-CoV-2 positive tests at lag = − 1 and 0 week (P = 0.0057 and 0.0001, respectively). In the best fit, AARI correlated with the ASI-flu with a lag of 2 weeks (P = 0.0026), SARS-CoV-2-positive tests in the same week (P < 0.0001) and their interaction (P < 0.0001) (adjusted R2 = 0.921). Thus, our method enables the automatic monitoring of changes in radiological reports and could help capturing disease emergence.
MRI-Based Machine Learning Fusion Models to Distinguish Encephalitis and Gliomas
Authors: Zheng Fei , Yin Ping , Yang Li , Wang Yujian , Hao Wenhan , Hao Qi , Chen Xuzhu , Hong Nan
Published: January 2024

This paper aims to compare the performance of the classical machine learning (CML) model and the deep learning (DL) model, and to assess the effectiveness of utilizing fusion radiomics from both CML and DL in distinguishing encephalitis from glioma in atypical cases. We analysed the axial FLAIR images of preoperative MRI in 116 patients pathologically confirmed as gliomas and clinically diagnosed with encephalitis. The 3 CML models (logistic regression (LR), support vector machine (SVM) and multi-layer perceptron (MLP)), 3 DL models (DenseNet 121, ResNet 50 and ResNet 18) and a deep learning radiomic (DLR) model were established, respectively. The area under the receiver operating curve (AUC) and sensitivity, specificity, accuracy, negative predictive value (NPV) and positive predictive value (PPV) were calculated for the training and validation sets. In addition, a deep learning radiomic nomogram (DLRN) and a web calculator were designed as a tool to aid clinical decision-making. The best DL model (ResNet50) consistently outperformed the best CML model (LR). The DLR model had the best predictive performance, with AUC, sensitivity, specificity, accuracy, NPV and PPV of 0.879, 0.929, 0.800, 0.875, 0.867 and 0.889 in the validation sets, respectively. Calibration curve of DLR model shows good agreement between prediction and observation, and the decision curve analysis (DCA) indicated that the DLR model had higher overall net benefit than the other two models (ResNet50 and LR). Meanwhile, the DLRN and web calculator can provide dynamic assessments. Machine learning (ML) models have the potential to non-invasively differentiate between encephalitis and glioma in atypical cases. Furthermore, combining DL and CML techniques could enhance the performance of the ML models.
Masticatory Muscles Activation and TMJ Space During Asymmetrically Loaded Jaw Closing
Authors: Angst Lea , Koolstra Jan Harm , Wiedemeier Daniel , Van Sluijs Rachel M. , Pulfer Anina M. , Gallo Luigi M. , Colombo Vera
Published: January 2024

Masticatory muscle activation and temporomandibular joint (TMJ) load generated during asymmetrically loaded jaw closing are largely unknown. Two different strategies were developed to explain how the central nervous system (CNS) generates muscle activation patterns during motion: minimization of joint load (MJL) vs. minimization of muscle effort (MME). The aim of the present study was to investigate, experimentally, the neuromuscular strategy selected by the CNS to coordinate jaw closing in reaction to the application of an external asymmetric load. Masticatory muscle activation was measured with electromyography (EMG) and the minimum intra-articular distance (MID) was assessed by dynamic stereometry to infer joint loading. Ten healthy subjects performed jaw-closing movements against an asymmetric mandibular load set from 0.0 to 2.0 kg in 0.5-kg steps. Recordings were analyzed by exploratory and graphical statistical tools. Moreover, the observed differences in MID and EMG among the various mandibular loads were tested using non-parametric tests for repeated measures data. The ipsilateral-contralateral differences in MID and EMG of the anterior temporalis showed a significant increase (p < 0.001, p = 0.01) with increasing asymmetrical load with both joints being most heavily loaded at 1 kg. EMG signals of the masseter did not change significantly with increasing load. This study is the first to have analyzed the changes in the TMJ intra-articular space during asymmetrically loaded jaw-closing movements, not only three dimensionally and dynamically, but also combined with EMG. Asymmetrical load affected the TMJ space and masticatory muscle activation patterns, primarily resulting in an increased activation of the anterior temporalis muscle. This might suggest the involvement of a control mechanism to protect the joints from overloading. However, the results do not fully support the hypothesis of MJL nor the MME strategy.
Explainable text-based features in predictive models of crowdfunding campaigns
Authors: Pekar Viktor , Candi Marina , Beltagui Ahmad , Stylos Nikolaos , Liu Wei
Published: January 2024

Reward-Based Crowdfunding offers an opportunity for innovative ventures that would not be supported through traditional financing. A key problem for those seeking funding is understanding which features of a crowdfunding campaign will sway the decisions of a sufficient number of funders. Predictive models of fund-raising campaigns used in combination with Explainable AI methods promise to provide such insights. However, previous work on Explainable AI has largely focused on quantitative structured data. In this study, our aim is to construct explainable models of human decisions based on analysis of natural language text, thus contributing to a fast-growing body of research on the use of Explainable AI for text analytics. We propose a novel method to construct predictions based on text via semantic clustering of sentences, which, compared with traditional methods using individual words and phrases, allows complex meaning contained in the text to be operationalised. Using experimental evaluation, we compare our proposed method to keyword extraction and topic modelling, which have traditionally been used in similar applications. Our results demonstrate that the sentence clustering method produces features with significant predictive power, compared to keyword-based methods and topic models, but which are much easier to interpret for human raters. We furthermore conduct a SHAP analysis of the models incorporating sentence clusters, demonstrating concrete insights into the types of natural language content that influence the outcome of crowdfunding campaigns.
A Study of Intermittent Turbulence in Stable Arctic Boundary Layers
Authors: Butterworth Brian J. , de Boer Gijs , Lawrence Dale
Published: January 2024

Polar boundary layers are difficult to model due to the existence of intermittent turbulence within stable layers. Here we present a case study evaluation of coherent structures in a stable boundary layer observed during a series of flights with an uncrewed aircraft system (DataHawk2) on 19 October 2016 at Oliktok Point, Alaska as part of the ERASMUS (Evaluation of Routine Atmospheric Sounding Measurements using Unmanned Systems) field campaign. During a sequence of five flights over a nine-hour period, 57 profiles of atmospheric properties (0–400 m a.g.l) were collected. Turbulence was identified using derived Richardson Number, temperature structure function parameter, and turbulence kinetic energy dissipation. Throughout all flights on this strongly stable day, intermittent turbulence was observed. These turbulent layers showed well-mixed potential temperature profiles embedded within otherwise stable potential temperature profiles; often resulting in a characteristic staircase pattern. Turbulent layers ranged from 1 to 30 m deep, with most individual layers being 1–2 m deep. Vertical propagation velocities of layers in the lower atmosphere were on the order of a few cm s−1, typical of non-convective environments. In different regions of the profile, turbulence was driven by a different balance of buoyancy and shear forces, with turbulence in the near surface environment driven by strong shear forces overcoming strong resistance to buoyancy, while turbulence in elevated layers characterized by weaker shear forces overcoming weaker resistance to buoyancy. We discuss the potential of such datasets for improving subgrid parameterizations of small-scale turbulence embedded within stable boundary layers.
Effect of Small-Scale Topographical Variations and Fetch from Roughness Elements on the Stable Boundary Layer Turbulence Statistics
Authors: Bhimireddy Sudheer R. , Sun Jielun , Wang Junming , Kristovich David A. R. , Hiscox April L.
Published: January 2024

Understanding the influence of roughness and terrain slope on stable boundary layer turbulence is challenging. This is investigated using observations collected from October to November of 2018 during the Stable Atmospheric Variability ANd Transport (SAVANT) field campaign conducted in a shallow sloping Midwestern field. We analyze the turbulence velocity scale and its variation with the mean wind speed using observations up to 10–20 m on four meteorological towers located along a shallow gully. The roughness length for momentum over this complex terrain varied with wind direction from 0.0049 m to a maximum of 0.12 m for winds coming through deciduous trees present in the field. The variation of the turbulence velocity with wind speed shows a transition from a weak wind regime to a stronger wind regime, as reported by past studies. This transition is not observed for winds coming from the tree area, where turbulence is enhanced even for weak wind speeds. For weak stratification and stronger winds, the turbulent velocity scale increased with an increase in roughness while the terrain slope is seen to have a weak influence. The sizes of the dominant turbulent eddies seen from the vertical velocity power spectra are observed to be larger for winds coming through the tree area. The turbulence enhancement by the trees is found to be strong within a fetch distance of 7 times the tree height and not observable at 16 times of the tree height.
Children’s Thoughts on Wonder in Fairy Tales
Authors: Kaliszewska-Henczel Magdalena
Published: January 2024

Fairy tales are a means to introduce the Polish language and social education exercises in Polish kindergartens and schools (early childhood literature education). In their methodological proposals, authors of school handbooks use fairy tales as a medium for teaching moral values. The Goldfish is an example of such an approach (Fałdzińska and Rączyńska, 2017). This article presents the thoughts of children aged six to nine (Polish kindergarten and primary school years one to three) constructed around the fairy tale in question, which, on the one hand, can be understood as a cautionary lesson about the importance of remaining satisfied with one’s station (Tatar 2014), and on the other serves as a meta-tale, exposing a rule of the genre’s poetics (Somoff, 2019). Assuming the role of observer-as-participant, intent on providing interpretations, the author of this study aims to identify children’s categories of wonder occurring in Aleksandr Afanasyev’s The Goldfish (Afanasyev, 1984). It was observed that children reflect on the rules of wonder in fairy tales (as culture-specific texts) and derive social meanings significant from the viewpoint of fairy tale categories. As such, they were not only limited to the lesson of condemning greed, which is often assigned to The Goldfish.
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

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

History 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

Sarcoidosis 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

Pet 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

Modern 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

Understanding 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

The 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

In 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

The 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

Delivery 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

In 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

Ensemble 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

This 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

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

Experimental 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.
Mode Transition Induced by Gas Heating Along the Discharge Channel in Capacitively Coupled Atmospheric Pressure Micro Plasma Jets
Authors: Schulenberg David A. , Vass Máté , Klich Maximilian , Donkó Zoltán , Klotz Jeldrik , Bibinov Nikita , Mussenbrock Thomas , Schulze Julian
Published: January 2024

The effects of neutral gas heating along the direction of the gas flow inside the discharge channel of a parallel plate micro atmospheric pressure plasma jet, the COST-jet, on the spatio-temporal dynamics of energetic electrons are investigated by experiments and simulations. The plasma source is driven by a single frequency sinusoidal voltage waveform at 13.56 MHz in helium with an admixture (0.05–0.2%) of nitrogen. Optical emission spectroscopy measurements are applied to determine the spatio-temporally resolved electron impact excitation dynamics from the ground state into the He I (3s)$$^3$$

3

S$$_1$$

1

state and the rotational temperature of nitrogen molecules at different positions along the direction of the gas flow inside the 30 mm long discharge channel. The gas temperature, which is assumed to be equal to the N$$_2$$

2

rotational temperature, is found to increase along the discharge channel. This effect is attenuated as the nitrogen concentration is increased in the gas mixture, leading to an eventually constant temperature profile. The experimental data also reveal a plasma operating mode transition along the discharge channel from the $$\Omega$$
Ω
- to the Penning-mode and show good agreement with the results of 1d3v kinetic simulations, which spatially resolve the inter-electrode space and use the gas temperature as an input value. The simulations demonstrate that the increase of the gas temperature leads to the observed mode transition. The results suggest the possibility of using the nitrogen admixture and the feed gas temperature as additional control parameters, (i) to tailor the plasma operating mode along the direction of the gas flow so that the production of specific radicals is optimized; and (ii) to control the final gas temperature of the effluent. The latter could be particularly interesting for biological applications, where the upper gas temperature limit is dictated by the rather low thermal damage threshold of the treated material.
Negative Downstream Effects of Alarmist Disinformation Discourse: Evidence from the United States
Authors: Jungherr Andreas , Rauchfleisch Adrian
Published: January 2024

The threat of disinformation features strongly in public discourse, but scientific findings remain conflicted about disinformation effects and reach. Accordingly, indiscriminate warnings about disinformation risk overestimating its effects and associated dangers. Balanced accounts that document the presence of digital disinformation while accounting for empirically established limits offer a promising alternative. In a preregistered experiment, U.S. respondents were exposed to two treatments designed to resemble typical journalistic contributions discussing disinformation. The treatment emphasizing the dangers of disinformation indiscriminately (T1) raised the perceived dangers of disinformation among recipients. The balanced treatment (T2) lowered the perceived threat level. T1, but not T2, had negative downstream effects, increasing respondent support for heavily restrictive regulation of speech in digital communication environments. Overall, we see a positive correlation among all respondents between the perceived threat of disinformation to societies and dissatisfaction with the current state of democracy.
Jesus was a Refugee: Religious Values Framing can Increase Support for Refugees Among White Evangelical Republicans
Authors: DeMora Stephanie L. , Merolla Jennifer L. , Newman Brian , Zechmeister Elizabeth J.
Published: January 2024

We consider how frames highlighting religious values shape opinion among individuals who may experience social identity conflict. White evangelical Republicans have ardently supported Donald Trump’s restrictionist stances towards refugees, yet those partisan policy stances exist in tension with evangelical Christian values emphasizing care for vulnerable strangers. Our pre-registered national experiment tests whether a religious message can move white self-identified evangelical Republicans’ opinions relating to refugees. The pro-refugee Christian values message increases favorable attitudes on some, but not all, measures. The effect is comparatively stronger among those who are more committed to their evangelical identity; unexpectedly, those who identify as strong Republicans are not more resistant to the message. These results demonstrate that moral reframing, which is known to shape attitudes in other domains, can affect self-identified evangelical Republicans’ attitudes on refugees, potentially shifting the national discussion of refugees in the U.S. The finding is all the more significant given highly partisan debates over refugees during the Trump presidency, which may have made partisans’ opinions especially rigid at the time of our experiment. Our results also speak to the relevance of identity strength in conditioning the impact of religious values frames.
Identifying the Impact of Social Capital on Quality of Urban Life (Evidence from Iran)
Authors: Amerian Mohammad
Published: January 2024

In this study we investigated the relationship between social capital (SC) and quality of urban life (QoUL). In fact, by using the concept of SC, we examined accuracy of the causal relationship among the three dimensions of the QoUL (objective, subjective and behavioral). The 22 district of Tehran was our case study. This district officially ran in 2000. The main tool for data collection was questionnaire and its constructs were directly extracted from the literature review. According to Cochran formula a total 384 questionnaire were distributed among participants. The data obtained from the questionnaire were analyzed in SPSS 21 as well as Smart PLS 3. The approach of structural equations modeling (SEM) was employed to confirm or decline our hypotheses. Findings of this study show that SC was positively associated with all three dimensions of QoUL. Also, the high objective QoUL in our sample has created a high subjective QoUL. However, the SQoUL did not lead to high behavioral QoUL. We believe that the low level of SC in the area has led to such a result.
Performative updates and the modeling of speech acts
Authors: Krifka Manfred
Published: January 2024

This paper develops a way to model performative speech acts within a framework of dynamic semantics. It introduces a distinction between performative and informative updates, where informative updates filter out indices of context sets (cf. Stalnaker, Cole (ed), Pragmatics, Academic Press, 1978), whereas performative updates change their indices (cf. Szabolcsi, Kiefer (ed), Hungarian linguistics, John Benjamins, 1982). The notion of index change is investigated in detail, identifying implementations by a function or by a relation. Declarations like the meeting is (hereby) adjourned are purely performative updates that just enforce an index change on a context set. Assertions like the meeting is (already) adjourned are analyzed as combinations of a performative update that introduces a guarantee of the speaker for the truth of the proposition, and an informative update that restricts the context set so that this proposition is true. The first update is the illocutionary act characteristic for assertions; the second is the primary perlocutionary act, and is up for negotiations with the addressee. Several other speech acts will be discussed, in particular commissives, directives, exclamatives, optatives, and definitions, which are all performative, and differ from related assertions. The paper concludes a discussion of locutionary acts, which are modelled as index changers as well, and proposes a novel analysis for the performative marker hereby.
Deep convolutional neural networks are not mechanistic explanations of object recognition
Authors: Grujičić Bojana
Published: January 2024

Given the extent of using deep convolutional neural networks to model the mechanism of object recognition, it becomes important to analyse the evidence of their similarity and the explanatory potential of these models. I focus on one frequent method of their comparison—representational similarity analysis, and I argue, first, that it underdetermines these models as how-actually mechanistic explanations. This happens because different similarity measures in this framework pick out different mechanisms across DCNNs and the brain in order to correspond them, and there is no arbitration between them in terms of relevance for object recognition. Second, the reason similarity measures are underdetermining to a large degree stems from the highly idealised nature of these models, which undermines their status as how-possibly mechanistic explanatory models of object recognition as well. Thus, building models with more theoretical consideration and choosing relevant similarity measures may bring us closer to the goal of mechanistic explanation.
Phenylethanoid glycosides accumulation and antiradical activity of fractionated extracts of Plantago ovata Forssk. callus cultures lines
Authors: Budzianowska Anna , Kikowska Małgorzata , Budzianowski Jaromir
Published: January 2024

The main phenylethanoid glycosides in the Plantago genus are acteoside (verbascoside) and plantamajoside, compounds with broad biological effects. This is a report on Plantago ovata callus induction, proliferation and establishment as well as the content of those phenylethanoids in that cell biomass. In the experimental studies, callus initiated from various seedling explants (roots, hypocotyls and leaves) was cultured on MS (Murashige-Skoog) media augmented with 2,4-D (2,4-dichloroacetic acid) and KIN (kinetin) or NAA (α-naphthaleneacetic acid) and BAP (6-benzylaminopurine). Callus proliferating on MS without NH4NO3 (ammonium nitrate) supplemented with 2,4-D (1.0 mg/l) and KIN (0.5 mg/l or 1.0 mg/l) turned out to be a good growth system for biomass production—mean increase of fresh weigh calculated on three following passages was 9.1 ± 1.8. The phytochemical analyses and antiradical DPPH (1,1-diphenyl-2-picryl-hydrazyl) tests revealed that the antioxidant activity is due to the presence of phenylethanoid glycosides. The quantitative screening of the callus extract by TLC (thin-layer chromatography) video densitometric method showed the highest content of acteoside (9.58 ± 0.75 mg/g dry weight) in root-derived and plantamajoside (8.15 ± 0.81 mg/g d.w.) in hypocotyl-derived callus biomass. In in vitro redifferentiated cultures of P. ovata, compounds with a demonstrated therapeutic effect, can be obtained in a manner that is completely independent of cultivation or harvesting from the wild.

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