bluuebunny/crossref_metadata_2025 huggingface dataset:
Structural change in city systems evolution
Authors: Andersson Martin , Johansson Börje , Niedomysl Thomas
Published: October 2024

This paper analyzes city system dynamics, based on a theoretical framework relating interaction potentials to agglomeration economies and density externalities. It employs new historical time series data on population size of cities in Sweden over two centuries (1810–2010) and introduces two schematic growth factors: (i) the intra-city potential and (ii) the extra-city potential located in in rings encircling each city. The first factor is measured by each city’s population size, while the second is a vector of distance-discounted population size for each of a city’s urban rings. In this way, we can explain a city’s growth as a function of its interaction potential inside the city, as well as inside the first, second hand third ring. A robust finding is that cities with large ring potentials follow different development paths than those with small ring potentials. We also find clear evidence of structural change between the two centuries 1810–1910 and 1910–2010. In the first period, city growth is positively impacted by the size of the intra-city potential, whereas the same potential dampens or reduces the growth in the second period. Moreover, the ring potentials outside the city tend to switch from having negative growth stimulation in the first period to having positive stimulation in the second period.
Possible protective effect of natural flavanone naringenin-reduced graphene oxide nanosheets on nonalcoholic fatty liver disease
Authors: Abdelmoneim Doaa , Eldomany Ehab B. , El-Adl Mohamed , Farghali Ahmed , El-Sayed Gehad , El-Sherbini El Said
Published: October 2024

Utilizing naringenin as a safe, natural compound for reducing graphene oxide and to determine whether Nar-RGO more effectively mitigates the harmful effects of HFFD-induced NAFLD compared to crude naringenin. Using a straightforward experimental setup, we utilize the bioactive flavonoid naringenin (NAR) as the reducing agent to synthesize naringenin-reduced graphene oxide nanosheets (Nar-RGO). Naringenin loading on graphene oxide was validated using electroscopic methods (SEM and TEM) and zeta potential measurements. Utilization of reduced graphene oxide for naringenin encapsulation resulted in a significant improvement in hepatic steatosis, insulin resistance, oxidative stress, and signs of inflammation in HFFD-induced NAFLD compared to crude naringenin. This study demonstrates that Nar-RGO exhibits significantly greater efficacy compared to free naringenin. Therefore, it can be used as a promising medicine in counteracting high-fat-fructose diet (HFFD)-induced NAFLD.
Long-Term Reproducibility of BMD-Measurements with Clinical QCT Using Simultaneous and Asynchronous Calibration Methods and Different Measurement and Reconstruction Protocols
Authors: du Mont Sophie , Barkmann Reinhard , Damm Timo , Peña Jaime , Reinhold Stefan , Both Marcus , Mainusch Meike , Glüer Claus-Christian
Published: October 2024

Osteoporosis is underdiagnosed and undertreated. To improve timely fracture risk assessment optimized densitometry methods are required such as opportunistic spinal quantitative computed tomography (QCT). However, it is unclear how to best calibrate these scans and correct for potential scanner drift of QCT when used for monitoring bone mineral density (BMD) changes. We compared gold standard simultaneous calibration with asynchronous calibration methods, assessing mid-term (12 weeks) and long-term (1.5 years) reproducibility of BMD measurements. Cortical and trabecular compartments of the European Spine Phantom were studied with ten different protocols including low dose and high resolution (HR)-modes. Based on weekly phantom data, we compared simultaneous calibration to asynchronous single (termed global) or monthly calibration. The accuracy was better for trabecular measurements than for cortical measurements for all calibration methods. Reproducibility was excellent for all methods and slightly better for asynchronous than for simultaneous calibration both for trabecular and cortical bone. For HR protocols, reproducibility was better than for low dose measurements. In trabecular compartments averaged HR-BMD remained stable for global (− 0.1%/year, ns) but not for simultaneous calibration (− 1.5%/year, p < 0.001). No significant drifts could be detected for averaged low dose BMD (− 0.9 to + 0.8%/year) for either calibration method. Our data suggest that with regard to precision and accuracy measurements with asynchronous calibration are suitable for vertebral BMD assessment (no contrast agents) in clinical practice. Regular (e.g., monthly) stability tests using a calibration phantom could assure long term stability of at least 1 year.
Ultrasound innovations in abdominal radiology: techniques and clinical applications in pediatric imaging
Authors: Davis Laura May , Martinez-Correa Santiago , Freeman Colbey W. , Adams Caroline , Sultan Laith R. , Le David Q. , Lemessa Natae , Darge Kassa , Hwang Misun
Published: October 2024

Contrast-enhanced ultrasound, microvascular imaging, elastography, and fat quantification have varying degrees of utility, with some applications in the pediatric setting mirroring that in adults and having unique uses when applied to children in others. This review will present novel ultrasound technologies and the clinical context in which they are applied to the pediatric abdomen. New ultrasound technologies have a broad range of applications in clinical practice and represent a powerful diagnostic tool with the potential to replace other imaging modalities, such as magnetic resonance imaging and computed tomography, in specific cases.
A New Approach with Combined Microneedle and Sublative Fractional Radiofrequency for Photoaging Management: A Clinical, Histometric, and Immunohistochemical Study
Authors: El-Domyati Moetaz , Moawad Osama , Abdel-Wahab Hossam , Behairy Ezzeldin F. , Rezk Ahmed F.
Published: October 2024

Background

Fractional radiofrequency (FRF) has been reported to be effective in improving wrinkles. A combination of microneedle and sublative fractional radiofrequency (SFRF) may have the potential synergy to improve photoaged skin.

Objectives

To evaluate the efficacy and safety of combined microneedle and SFRF in photoaging management.

Methods

This prospective study included 12 subjects with moderate photoaging (skin phototype III–IV). The subjects received three consecutive combined microneedle and sublative FRF at 1-month intervals. Punch biopsies were obtained before and after three months of treatment. Routine H&E, Masson-trichrome, Orcein staining, histometric measurements, as well as Collagen type I and Elastin immunohistochemical staining were performed.

Results

Significant improvement was noticed regarding skin tightening and texture (p < 0.05), rhytides, and volunteers’ satisfaction (p < 0.001). Collagen fibers appeared better organized, with a significant increase in collagen type I (p = 0.001). Meanwhile, normal-appearing elastic fibers were restored, and a significant reduction in abnormal elastin was achieved (p = 0.0005).

Conclusion

Combined microneedle and sublative FRF may provide a new therapeutic approach for photoaged skin.

Level of Evidence II

For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.
Key Chemical Soil Parameters for the Assembly of Rhizosphere Bacteria Associated with Avocado Cv Hass Grafted on Landrace Rootstocks
Authors: Córdoba-Agudelo Mateo , Arboleda-Rivera Juan C. , Borrego-Muñoz David A. , Ramírez-Cuartas Camilo A. , Pérez-Jaramillo Juan E.
Published: October 2024

Avocado cultivation holds significant economic importance in many countries, ranking Colombia as the fifth largest global producer. Particularly, the Hass cultivar plays a pivotal role in Colombia’s avocado industry, especially in the Department of Antioquia, the primary export region. This cultivar is grown under diverse soil and climate conditions and exhibits considerable genetic polymorphism due to the hybridization of varieties of agronomic significance, leading to a diverse array of landrace rootstocks. However, the role of soil conditions and rootstock genotype in structuring rhizosphere bacterial communities is still lacking. In addressing this knowledge gap, we investigated the influence of two soil conditions on the structure of rhizosphere bacterial communities associated with two landrace genotypes of Persea americana cv. Hass, utilizing 16S rRNA sequencing. Notably, no significant differences related to genotypes were observed. This study reports that the rhizosphere bacterial microbiome remains consistent across avocado landrace rootstocks, while variations in key parameters such as phosphorus, pH, Mg, and Ca drive distinct rhizosphere effects. Our results reveal that despite the soils having similar management, increases in these crucial parameters can lead to bacterial communities with lower alpha diversity and a more complex co-occurrence network. In addition, we found substantial variations in beta diversity, bacterial composition, and metagenome predictions between the two farms, underscoring the role of soil variables in shaping the bacterial microbiome. These findings provide valuable insights into the factors influencing the bacterial communities that may play a role in the health and productivity of crops with agro-industrial potential, such as Hass avocado.
Wirksamkeit und Sicherheit der neuen Generation der Excimer-Laser-Trabekulotomie bei einer heterogenen Patientenpopulation – 1-Jahres-Follow-up
Authors: Gniesmer Stefanie , Sonntag Svenja Rebecca , Grisanti Swaantje
Published: October 2024

Hintergrund

Mikroinvasive Verfahren haben sich in der Glaukomchirurgie etabliert und werden bevorzugt für Patienten mit nicht zu niedrigen Zieldruckwerten eingesetzt. Die Excimer-Laser-Trabekulotomie (ELT) stellt einen solchen minimal-invasiven Ansatz dar und kann mit einer Kataraktoperation kombiniert werden.

Ziel der Arbeit

Über 12 Monate wurden die Senkung des intraokularen Drucks (IOD), die Menge der drucksenkenden Lokaltherapie und das Auftreten unerwünschter Ereignisse mit dem neuen EliosTM-Verfahren (Elios Vision GmbH, Germering, Deutschland) anhand von Real-Life-Daten einer heterogenen Patientenpopulation, die eine ELT in Kombination mit einer Kataraktoperation (Phako-ELT) erhielt, analysiert.

Material und Methoden

Es wurden 20 Augen von 13 Patienten, die eine Phako-ELT erhalten haben, retrospektiv analysiert. Nach einer Standardphakoemulsifikation mit Hinterkammerlinsenimplantation wurden mit dem Excimer-Laser 10 Mikrokanäle angelegt. Die Patienten wurden über 12 Monate nachbeobachtet und der IOD, die drucksenkende Lokaltherapie und das Auftreten unerwünschter Ereignisse untersucht.

Ergebnisse

Das Durchschnittsalter lag bei 65 Jahren. Präoperativ betrug der IOD 17,5 (± 5,3) mm Hg. Die IOD-Senkung lag im Mittel bei 4,8 mm Hg (27,4 %, p < 0,001) am ersten postoperativen Tag, 3,2 mm Hg (18,3 %, p = 0,22) nach 6 Monaten und 2,5 mm Hg (14,3 %, p = 0,14) nach 12 Monaten. Die Drucksenker konnten von im Durchschnitt 3,2 (± 1,3) Wirkstoffen präoperativ auf 0,5 (± 0,9) an Tag 1 (p < 0,001), 1,9 (± 1,2) nach 6 Monaten (p = 0,008) und 2,2 (± 1,3) nach 12 Monaten (p = 0,013) reduziert werden.

Diskussion

In der hier untersuchten Kohorte ist die ELT in Kombination mit einer Kataraktoperation ein sicheres, minimal-invasives glaukomchirurgisches Verfahren, welches bei Patienten mit niedrigem Ausgangsdruck 1 Jahr postoperativ noch eine IOD-Senkung von 14,3 % aufweist, bei einer Reduktion der drucksenkenden Medikation um 1 Wirkstoff. Da bei der ELT kein Implantat zum Einsatz kommt und die Bindehaut unangetastet bleibt, sind Folgeeingriffe nicht beeinträchtigt und auch Filterkissenoperationen ohne Weiteres möglich.
A strategy of consistent X-ray and neutron double-difference pair distribution function analysis of nanoparticle dispersions
Authors: Thomä Sabrina L. J. , Neuefeind Joerg , Youngs Tristan G. A. , Zobel Mirijam
Published: October 2024

It has been demonstrated that the X-ray pair distribution function (PDF) formalism allows for the identification of very small signal contributions in multi-component systems by the difference and double-difference PDF (dd-PDF) approach. Due to their stronger interaction with light elements compared to X-rays, neutrons are often beneficial or complementary for the characterization of modern materials. Here, it is demonstrated that the dd-PDF strategy previously developed for X-ray PDF data can successfully be applied to neutron PDF data despite much lower count rates compared to X-rays. The dd-PDF strategy was employed for the investigation of aqueous iron oxide nanoparticle (IONP) dispersions. At the Near and InterMediate Range Order Diffractometer (NIMROD) at ISIS, the IONPs could even be investigated in pure water, whereas at the Nanoscale Ordered Materials Diffractometer (NOMAD) at SNS, heavy water had to be used, but additional information could be retrieved from modelling the data of IONP powder in the dry state and with adsorbed (heavy) water. The simple and robust approach can easily be adapted for the use in other multicomponent systems, like heterogenous catalysts or battery systems.

Graphical Abstract
Unraveling molecular characteristics and tumor microenvironment dynamics of neuroendocrine prostate cancer
Authors: Heimdörfer David , Artamonova Nastasiia , Culig Zoran , Heidegger Isabel
Published: October 2024

Prostate cancer (PCa) is the most prevalent malignancy and the second leading cause of cancer-related deaths among men. While adenocarcinoma of the prostate (adeno-PCa) is well-characterized, neuroendocrine prostate cancer (NEPC) remains poorly understood. Generally, NEPC is a rare but highly aggressive histological variant, however its limited patho-physiological understanding leads to insufficient treatment options associated with low survival rates for NEPC patients. Current treatments for NEPC, including platinum-based therapies, offer some efficacy, but there is a significant need for more targeted approaches. This review summarizes the molecular characteristics of NEPC in contrast to adeno-PCa, providing a comprehensive comparison. A significant portion of the discussion is dedicated to the tumor microenvironment (TME), which has recently been identified as a key factor in tumor progression. The TME includes various cells, signaling molecules, and the extracellular matrix surrounding the tumor, all of which play critical roles in cancer development and response to treatment. Understanding the TME’s influence on NEPC could uncover new avenues for innovative treatment strategies, potentially improving outcomes for patients with this challenging variant of PCa.
Robotic cytoreductive surgery and hyperthermic intraperitoneal chemotherapy: is there a benefit?
Authors: Sparkman Brian K. , Freudenberger Devon C. , Vudatha Vignesh , Trevino Jose G. , Khader Adam , Fernandez Leopoldo J.
Published: October 2024

Background

Open cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC) is a therapeutic option for the management of malignancies with peritoneal carcinomatosis and of peritoneal origin. Robotic surgery shows promise as a minimally invasive approach for select patients. We aimed to evaluate the differences in outcomes between robotic versus open CRS/HIPEC and hypothesized less morbidity and faster recovery in the robotic approach group.

Methods

We conducted a retrospective cohort study from our HIPEC database including all tumor origins. We included patients aged 18–89 years who underwent CRS/HIPEC for curative intent at a single institution between January 1, 2017, and December 31, 2023. Patients were stratified by open versus robotic-assisted surgery. Mann–Whitney U and Fisher Exact tests were used to compare differences in patient characteristics and outcomes.

Results

A total of 111 patients underwent CRS/HIPEC for curative intent, with 95 (85.6%) cases performed open and 16 (14.4%) robotically. The groups were demographically similar, except patients undergoing robotic CRS/HIPEC had a significantly higher median income ($83,845 vs. $70,519, p < 0.001). Rate of comorbidities and cancer type, including appendiceal, colorectal, and ovarian, were the same. The peritoneal carcinomatosis index and completion of cytoreduction score were similar between groups. Robotic approach was associated with statistically significant lower estimated blood loss (113 vs. 400 mL, p < 0.001) and postoperative transfusions (6.3% vs. 23.2%, p = 0.036). Total complications, readmission rates, and 30-day mortality were similar among groups, but the robotic group had a significantly shorter length of stay (5.5 vs. 9 d., p < 0.001).

Conclusion

Robotic CRS/HIPEC holds promise to decrease intraoperative blood loss, blood transfusions, and hospital stay while providing similar immediate postoperative outcomes in select patients. These results should be validated in the setting of a prospective trial and effects on long-term oncologic outcomes should be investigated.
Implicit sensing self-supervised learning based on graph multi-pretext tasks for traffic flow prediction
Authors: Sattarzadeh Ali Reza , Pathirana Pubudu Nishantha , Palaniswami Marimuthu
Published: October 2024

In recent years, spatio-temporal graph neural networks (GNNs) have successfully been used to improve traffic prediction by modeling intricate spatio-temporal dependencies in irregular traffic networks. However, these approaches may not capture the intrinsic properties of traffic data and can suffer from overfitting due to their local nature. This paper introduces the Implicit Sensing Self-Supervised learning model (ISSS), which leverages a multi-pretext task framework for traffic flow prediction. By transforming data into an alternative feature space, ISSS effectively captures both specific and general representations through self-supervised tasks, including contrastive learning and spatial jigsaw puzzles. This enhancement promotes a deeper understanding of traffic features, improved regularization, and more accurate representations. Comparative experiments on six datasets demonstrate the effectiveness of ISSS in learning general and discriminative features in both supervised and unsupervised modes. ISSS outperforms existing models, demonstrating its capabilities in improving traffic flow predictions while addressing challenges associated with local operations and overfitting. Comprehensive evaluations across various traffic prediction datasets, have established the validity of the proposed approach. Unsupervised learning scenarios have shown the improvements in RMSE for the METR-LA and PEMSBAY datasets of 0.39 and 0.35 for location-dependent and location-independent tasks, respectively. In supervised learning scenarios, for the same datasets, the improvements were 1.16 for location-dependent tasks and 0.55 for location-independent tasks.
Leveraging survival analysis in cost-aware deepnet for efficient hard drive failure prediction
Authors: Ahmed Jishan , Green II Robert C.
Published: October 2024

Many real-world datasets, such as those used for failure and anomaly detection, are severely imbalanced, with a relatively small number of failed instances compared to the number of normal instances. To address these issues, this paper leverages the Backblaze hard disk drives (HDDs) data and makes several contributions to hard drive failure prediction. This research explores 1D convolutional neural networks (CNN) to utilize the sequential nature of hard drive sensor data. The performance of 1D CNN models is compared to traditional machine learning (ML) algorithms, such as the synthetic minority over-sampling technique (SMOTE) and weighted logistic regression (WLR), demonstrating superior results, suggesting the potential effectiveness of the proposed approaches. In addition to these efforts, this paper aims to provide a comprehensive understanding of hard drive longevity and the critical factors contributing to their eventual failure through survival analysis. The 1D CNN models employ weighted binary cross-entropy (WCE) loss and modified focal loss (MFL) functions to manage class imbalanced issues commonly observed in hard drive data. The findings suggest that 1D CNN models outperform traditional ML models, with regularization techniques like dropout and early stopping proving effective in controlling overfitting. Notably, the 1D CNN model with WCE loss demonstrated the best overall performance with a

$$G_{mean}$$

G

mean

of 0.692, successfully maximizing the FDR without increasing the FAR. In parallel, the research also employs Cox regression to identify key SMART parameters influencing drive failure. The high concordance index (c-index) of the Cox model (0.958) adds confidence to the insights derived. The research thus sets a solid groundwork for data center management strategies, with a future focus on practical implementation and evaluation of these findings.
Hardware-accelerated neural network model for early prediction of sudden cardiac arrest based on heart rate variability metrics
Authors: Pan Sheng-Yueh , Nguyen Duc Huy , Chao Paul C.-P.
Published: October 2024

Sudden Cardiac Arrest (SCA) constitutes a dire medical condition, marked by the abrupt cessation of effective blood circulation due to the heart's failure to contract properly. This leads to acute circulatory collapse, often culminating in loss of consciousness within an hour and potentially resulting in fatality within minutes if left unattended. Heart rate variability (HRV) serves as a critical biometric, derived from electrocardiogram (ECG) signals with ventricular depolarization waves to further calculate the R-R Intervals (RRIs). These intervals provide the basis for extracting various characteristics of cardiac rhythm, encompassing time-domain, frequency-domain, and nonlinear features. This study presents a neural network-based classification algorithm that leverages HRV metrics to categorize patients into SCA and Normal Sinus Rhythm (NSR) cohorts. The proposed neural network (NN) model showcased impressive results, achieving an accuracy of 96.23%, a sensitivity of 94.35%, and a specificity of 98.12% in detecting SCA, as evaluated through leave-one-subject-out analysis. In order to harness the benefits of hardware acceleration, the algorithm is implemented on a Field-Programmable Gate Array (FPGA). Its computational efficiency is subsequently benchmarked against traditional software-based methodologies. The hardware-level implementation is made possible in Verilog hardware description language (HDL) and was verified successfully with expected performance by register-transfer level (RTL) simulation via Vivado 2020.2.
Virtual thoracoscopic imaging for accurate pulmonary nodule localization: clinical experience
Authors: Kadomatsu Yuka , Nakao Megumi , Okado Shoji , Ueno Harushi , Kato Taketo , Nakamura Shota , Chen-Yoshikawa Toyofumi Fengshi
Published: October 2024

The increasing detection of small pulmonary nodules on computed tomography (CT) warrants simple and effective nodule localization methods. We describe our clinical experience using an experimental computer that displays virtual thoracoscopic images. This device constructs three-dimensional images from preoperative CT scans and simulates the deflated lung parenchyma in the lateral decubitus position. Five patients underwent lung resection using this technology. The device provided images that closely resembled actual thoracoscopic images in all cases. This method addresses the limitations of other localization techniques such as allergic reactions and mechanical marker-related complications. The method only requires preoperative CT images, and the process is semi-automatically performed by specifying the nodule location, thoracoscopic camera insertion site, and camera angle. This study is still in the preliminary phase and has several limitations. However, this method has the potential to accurately predict nodule locations and eliminate the many risks associated with other techniques.
Investigating the Effect of Blurring and Focusing Current in Cochlear Implant Users with the Panoramic ECAP Method
Authors: Garcia Charlotte , Morse-Fortier Charlotte , Guérit François , Hislop Scott , Goehring Tobias , Carlyon Robert P. , Arenberg Julie G.
Published: October 2024

Purpose

For some cochlear implants (CIs), it is possible to focus electrical stimulation by partially returning current from the active electrode to nearby, intra-cochlear electrodes (partial tripolar (pTP) stimulation). Another method achieves the opposite: “blurring” by stimulating multiple electrodes simultaneously. The Panoramic ECAP (PECAP) method provides a platform to investigate their effects in detail by measuring electrically evoked compound action potentials and estimating current spread and neural responsiveness along the length of the CI electrode array. We investigate how sharpening and broadening the electrical current spread are reflected in PECAP estimates.

Methods

PECAP measurements were recorded at most comfortable level in 12 ears of Advanced Bionics CI users. Focused thresholds were also determined. For the electrodes with the highest and lowest focused thresholds, additional PECAP measurements were recorded while stimulating in pTP mode and in “blurred” mode with 3 or 5 adjacent electrodes simultaneously stimulated. Current spread and neural responsiveness were then estimated along the electrode array using PECAP.

Results

PECAP revealed increased current spread estimates across participants for blurred stimulation of the targeted electrodes towards the apex of the cochlea. Variable results for pTP stimulation were found, with two of eight ears appearing to drive a small group-level effect of increased current spread.

Conclusion

When stimulating multiple electrodes simultaneously, PECAP detected localized increases in current spread towards the apex (but not the base) of the cochlea. pTP stimulation showed mixed effects on PECAP current spread estimates. These findings are in line with behavioral speech perception studies and have implications for cochlear implant optimization.
Sweet mama: affiliative interactions are related to the reproductive success of dominant female Alpine marmots (Marmota marmota)
Authors: Matteo Panaccio , von Hardenberg Achaz , Ferrari Caterina
Published: October 2024

Sociality is a complex phenomenon, able to influence multiple traits of an individual life history. In group-living mammals, sociality is likely to play a major role in the reproductive success of individuals. Here we investigate how sociality traits are associated to reproductive success in female Alpine marmots (Marmota marmota), a highly social and cooperative breeding ground squirrel distributed in the European Alps. We used social network analysis to calculate sociality metrics and hurdle generalized linear mixed models (hurdle GLMMs) to model the relationship between sociality metrics and reproductive success of individually tagged female Alpine marmots. Our results showed that centrality of a reproductive female within her social group and the number of social partners are positively related to reproductive success, while agonistic behavior was not related with reproduction. Our results highlight the importance of affiliative interactions with other group members in cooperative breeders, suggesting that in such systems female fitness could be more related to social cohesion than to costs of agonistic behaviors to maintain dominance status.
The stigma of underperformance in assessment and remediation
Authors: Castanelli Damian J. , Molloy Elizabeth , Bearman Margaret
Published: October 2024

The stigma of underperformance is widely acknowledged but seldom explored. ‘Failure to fail’ is a perennial problem in health professions education, and learner remediation continues to tax supervisors. In this study, we draw on Goffman’s seminal work on stigma to explore supervisors’ accounts of judging performance and managing remediation in specialty anesthesia training in Australia and New Zealand. In doing so, we focus on what Goffman calls a “stigma theory” to explain the supervisors’ reported practices. We performed a secondary analysis of nineteen interviews originally gathered using purposive sampling to explore how assessment decisions were made. We conducted a theory-informed thematic analysis of the supervisors’ accounts to identify signifiers of stigma and underlying structures and beliefs. From both deductive and inductive analysis, we developed themes that demonstrate how the stigma of underperformance influences and is induced by supervisors’ reticence to discuss underperformance, their desire to conceal remediation, and their differential treatment of trainees. We also found that accounts of trainees ‘lacking insight’ resembled stigma-induced stereotyping. We argue from our data that our cultural expectations of perfectionism propagate a stigma that undermines our efforts to remediate underperformance and that our remediation practices inadvertently induce stigma. We suggest that a multifaceted approach using both individual and collective action is necessary to change both culture and practice and encourage the normalisation of remediation.
Taking what you get or Getting what you Need: A Qualitative Study on Experiences with Mental Health and Welfare Services in Long-Term Recovery in First-Episode Psychosis
Authors: Åsbø Gina , Haavind Hanne , Kruse Sindre Hembre , Wold Kristin Fjelnseth , Hegelstad Wenche ten Velden , Romm Kristin Lie , Slade Mike , Ueland Torill , Melle Ingrid , Simonsen Carmen
Published: October 2024

How people in long-term recovery (clinical and personal) in first-episode psychosis (schizophrenia and bipolar spectrum disorders) experience the mental health and welfare services they interact with is not frequently studied but has significant implications. We therefore aimed to explore which aspects of these services people with FEP evaluate as important for their long-term recovery. Twenty participants in clinical and/or personal recovery from two Norwegian long-term follow-up studies after FEP (TOP 10-year and TIPS 20-year) were sampled for this interview-based qualitative study. The research-team included service user experience. A deductive analysis based on personal accounts of recovery generated five service aspects. Few specific types of interventions were reported to promote recovery although medications, psychotherapy and employment support were mentioned. Participants valued services based in collaboration and that focused on their resources rather than limitations. The importance of long-term follow-up with a consistent aim was highlighted, as was the inclusion of caregivers and peers. Welfare services contributed to recovery by supporting basic needs and safety, but some experienced social exclusion when not participating in the labor market. This study is unique in exploring the role of services, including welfare, in long-term FEP recovery from service user perspectives. Participants evaluated that services played a more indirect role in long-term recovery by supporting their personal resources, although what they needed from services had frequently not been offered. Their expertise by experience contributes valuable knowledge. Better service coordination and consistent implementation of this knowledge are crucial to support recovery in FEP.
Conjunctive hierarchical secret sharing by finite geometry
Authors: Gyarmati Máté , Ligeti Péter , Sziklai Peter , Takáts Marcella
Published: October 2024

Secret sharing is a general method for distributing sensitive data among the participants of a system such that only a collection of predefined qualified coalitions can recover the secret data. One of the most widely used special cases is threshold secret sharing, where every subset of participants of size above a given number is qualified. In this short note, we propose a general construction for a generalized threshold scheme, called conjunctive hierarchical secret sharing, where the participants are divided into disjoint levels of hierarchy, and there are different thresholds for all levels, all of which must be satisfied by qualified sets. The construction is the first method for arbitrary parameters based on finite geometry arguments and yields an improvement in the size of the underlying finite field in contrast with the existing results using polynomials.
Emotions Represent Evaluative Properties Unconsciously
Authors: Bonard Constant
Published: October 2024

Drawing on affective sciences, I argue that normally elicited emotions involve a component—the appraisal process—that represents evaluative properties unconsciously. More specifically, I argue that, given a substantial agreement in affective sciences about what emotions are, given broadly shared definitions of representation, evaluative properties, and unconsciousness, given how appraisals are conceptualized by most (neuro)psychological theories of emotion, and given empirical evidence about affective states elicited by stimuli perceived unconsciously, we are led to conclude that normally elicited emotions involve a component that represents evaluative properties unconsciously. In the last section, I assess which philosophical theories of emotions are in contradiction with my conclusion, ask whether it implies that emotions represent evaluative properties consciously as well, and discuss how it relates to the debate on unconscious emotions.
Modeling extreme events: Univariate and multivariate data-driven approaches
Authors: Buriticá Gloria , Hentschel Manuel , Pasche Olivier C. , Röttger Frank , Zhang Zhongwei
Published: October 2024

This article summarizes the contribution of team genEVA to the EVA (2023) Conference Data Challenge. The challenge comprises four individual tasks, with two focused on univariate extremes and two related to multivariate extremes. In the first univariate assignment, we estimate a conditional extremal quantile using a quantile regression approach with neural networks. For the second, we develop a fine-tuning procedure for improved extremal quantile estimation with a given conservative loss function. In the first multivariate sub-challenge, we approximate the data-generating process with a copula model. In the remaining task, we use clustering to separate a high-dimensional problem into approximately independent components. Overall, competitive results were achieved for all challenges, and our approaches for the univariate tasks yielded the most accurate quantile estimates in the competition.
Learning Strategies in Mathematics for Related Study Programs Focusing on Cooperative Education in Germany – Viewed from the Perspectives of the Academic Disciplines, Economics and Engineering, as well as Gender
Authors: Wild Steffen , Neef Christoph
Published: October 2024

Cognitive learning strategies are seen as a central element for successful learning. Acquiring knowledge about its worth, can support persons in sophisticated groups in attaining academic success. Consequently, the authors are interested in domain-specific learning strategies for mathematics in the academic disciplines of economics and engineering in cooperative tertiary education, in addition to determining gender-specific preferences for particular learning strategies. Data from a cross-sectional design with N = 565 cooperative students from Germany are used. A 2 × 2 analysis of variance, with one repeated measure, show the impact of academic disciplines and gender on seven specific cognitive learning strategies in mathematics. Taken together, these results show the complexity of cognitive learning strategies in higher education learning.
A transformer-based approach to Nigerian Pidgin text generation
Authors: Garba Kabir , Kolajo Taiwo , Agbogun Joshua B.
Published: October 2024

This paper describes the development of a transformer-based text generation model for Nigerian Pidgin also known as Naijá, a popular language in West Africa. Despite its wide use, Nigerian Pidgin remains under-resourced, particularly in areas related to text generation and natural language processing. These difficulties are primarily due to technological constraints rather than the language’s fundamental attributes. There is currently a demand for Nigerian Pidgin-specific solutions because it is used in everyday communication and has a unique linguistic blend. This paper aims to close this gap by exploring the application of state-of-the-art transformer technology to develop a text generation model for Nigerian Pidgin. This work uses the public Afriberta-corpus dataset to optimize the Generative Pre-trained Transformer (GPT-2) model across a sizeable dataset. The performance evaluators, BLEU and Perplexity metrics provide a detailed breakdown of the model’s text quality and predictive accuracy. Despite the difficulties caused by a limited amount of training data, preliminary evaluations show that the model can generate coherent Nigerian Pidgin text. The performance evaluation yielded perplexity scores of 43.56 for variable target reference length and 43.26 for fixed text length. BLEU scores of 0.15 for fixed max length and 0.56 for variable reference target length. This highlights the quality of generated text and the significant improvement when the generated text length is aligned with the reference target. Our work was benchmarked against African American Vernacular (AAVE) revealing that BLEU scores for AAVE are significantly lower than those for Standard American English, with BLEU given as 0.26. Our Nigerian Pidgin model, with a BLEU score of 0.56, shows a better performance. However, both results suggest that both dialects are challenging for language models. Leveraging the pre-trained transformer-based language model and evaluation metrics, we showcase the model’s capacity for coherent Nigerian Pidgin text generation. For future research, the research work can serve as a good foundation for advancement and progress in the Nigerian Pidgin language generation and other low-resource languages.
Robustness of generative AI detection: adversarial attacks on black-box neural text detectors
Authors: Fishchuk Vitalii , Braun Daniel
Published: October 2024

The increased quality and human-likeness of AI generated texts has resulted in a rising demand for neural text detectors, i.e. software that is able to detect whether a text was written by a human or generated by an AI. Such tools are often used in contexts where the use of AI is restricted or completely prohibited, e.g. in educational contexts. It is, therefore, important for the effectiveness of such tools that they are robust towards deliberate attempts to hide the fact that a text was generated by an AI. In this article, we investigate a broad range of adversarial attacks in English texts with six different neural text detectors, including commercial and research tools. While the results show that no detector is completely invulnerable to adversarial attacks, the latest generation of commercial detectors proved to be very robust and not significantly influenced by most of the evaluated attack strategies.
Def2Vec: you shall know a word by its definition
Authors: Morazzoni Irene , Scotti Vincenzo , Tedesco Roberto
Published: October 2024

Def2Vec introduces a new perspective on building words embeddings by using dictionary definitions. By leveraging term-document matrices derived from dictionary definitions and employing Latent Semantic Analysis (LSA), our method, Def2Vec, yields embeddings characterized by robust performance and adaptability. Through comprehensive evaluations encompassing token classification, sequence classification and semantic similarity, we show empirically how Def2Vec consistently demonstrates competitiveness with established models like Word2Vec, GloVe, and FastText. Notably, our model’s utilization of all the matrices resulting from LSA factorisation facilitates efficient prediction of embeddings for out-of-vocabulary words, given their definition. By effectively integrating the benefits of dictionary definitions with LSA-based embeddings, Def2Vec builds informative semantic representations, all while minimizing data requirements. In this paper, we run different experiment to assess the quality of our embedding model at word level and at sequence level. Our findings contribute to the ongoing evolution of word embedding methodologies by incorporating structured lexical information and enabling efficient embedding prediction.
Preparation and characterization of low loss polyvinyl butyral/barium titanate nanocomposite films for energy storage applications
Authors: Awadallah-F Ahmed , Ali Hussein E. , Zaghlool R. A. , Moghny A. S. Abdel
Published: October 2024

For energy storage applications, attaining high dielectric permittivity as well as low loss factor is the foremost target. This could be accomplished via filling polymer matrices with inorganic filler which is characterized by relatively high dielectric permittivity. In the present study, polyvinyl butyral (PVB) was used as a matrix material for preparing nanocomposite films filled with different weight fractions (2, 5, 10, and 15%) of barium titanate (BaTiO3) using the casting approach. The results show that BaTiO3 (BT) is well incorporated inside the PVB matrix. Although the dielectric permittivity has been decreased from 3.61 to 2.41 at 1 kHz upon filling the PVB matrix with 5 wt. % of BT, the PVB-BT-NPs-5 nanocomposite film shows the lowest loss factor ~ 0.0049, nearly half that for PVB, 0.0092, which implies the increased film ability to keep its stored energy. The PVB-BT-NPs-5 has been irradiated with gamma radiation to investigate its impact on the structure beside its dielectric and thermal properties. The crystallite size of BT has been decreased from 20.64 to 17.77 nm as PVB-BT-NPs-5 nanocomposite film has been irradiated at a dose of 0.5 kGy. The dielectric permittivity has been decreased from 2.41 to 2.37 at 1 kHz, whereas an increase from 0.0049 to 0.0073 in the loss factor is observed. Furthermore, the thermal stability has been decreased due to the deformation induced by gamma rays inside the nanocomposite films. Therefore, these nanocomposite films could be better exploited in energy storage applications in its un-irradiated form.
Enhancing Learning Through Animated Video: An Eye-Tracking Methodology Approach
Authors: Beautemps Jacob , Bresges André , Becker-Genschow Sebastian
Published: October 2024

This study investigates the impact of different animation styles on learning outcomes in physics, with a focus on explanations of the seasons. Using a combination of pre-post performance tests and eye tracking, we compared animations featuring a presenter with pure animations without a person in the frame. The sample consisted of students from a seminar for prospective physics teachers (N = 32, mean age = 23.9, SD = 5.7). The results indicate that while both formats achieved high learning success, the pure animation significantly outperformed the presenter-inclusive format in terms of effect size and in attracting gaze to the key areas of interest (AOIs) essential for understanding the physics of seasons. Intriguingly, specific hand gestures in the animation with a presenter were shown to reverse this effect, substantially increasing gaze attention on relevant AOIs. These findings suggest that specific animation elements can enhance educational efficacy in physics. This understanding has the potential to improve educational animations in media but also traditional teaching in school or university.
Qualitative critical phenomenology
Authors: de Boer Marjolein , Zeiler Kristin
Published: October 2024

Since its inception, phenomenological philosophy has engaged with empirical data of lived experiences. Recently, phenomenological philosophy itself has branched out into performing systematic qualitative research, resulting in a heterogeneous field of qualitative phenomenological philosophy. By introducing and outlining the research approach of ‘Qualitative Critical Phenomenology’ (QCP), this paper shows how one may conduct systemic qualitative research to lived experiences with an explicit phenomenological philosophical aim. In building on insights from various approaches within critical phenomenology, we not only give a stepwise explication of how to do QCP, we also discuss how we reflectively engage with lived experience as a research object and how key phenomenological themes – i.e. varieties of pre-/reflectivity and the phenomenological reduction – matter for designing and conducting a QCP inquiry. As such, we contribute to discussions on critical phenomenology – i.e. why it matters – but also to debates on how qualitative critical phenomenology may provide a critical lens to prevailing socio-cultural norms and their constitutive force in co-shaping perception and experience.
Digital Divide in the European Union: A Typology of EU Citizens
Authors: Gomes Ana , Dias José G.
Published: October 2024

This paper addresses the heterogeneity of the digital divide and internet use among citizens in the 28 European Union (EU) countries (at the time of the survey). Drawing from the Eurobarometer Surveys, three indicators of the digital divide are used to define the groups: frequency of internet access, means of internet access, and online activities. The categorical clustering algorithm identifies six groups of internet users: Non-Users, Basic Users, Information Exchangers, Instrumental Users, Socializers, and Advanced Users, each with distinct socio-demographic profiles. The study reveals significant socio-economic and demographic profiling variables characterizing these patterns, including age, education, gender, occupation, type of community and geographic location. A major digital divide is detected in many countries; Notably, Romania, Greece, and Bulgaria have the largest proportion of Non-Users, emphasizing the need for targeted policy interventions. These results provide crucial insights for the European Commission’s digitization strategy, suggesting that more nuanced and targeted measures are needed to ensure equitable digital access across the EU.
Formal models and justifications of democracy
Authors: Genta Benjamin Santos
Published: October 2024

Recently, some epistemic democrats have taken a result from Hong and Page (Proc Natl Acad Sci 101(46):16385–16389, 2004) to help justify the virtues of deliberative democracy. In this paper, I present novel computational models and show that the result fails to be robust in ways that undermine it as evidence for justifying the virtues of deliberative democracy. In particular, the same model lauded by epistemic deliberative democrats can also be used to support certain kinds of epistocracy.