bluuebunny/crossref_metadata_2025_split huggingface dataset:
Validation of the Quality Analysis of Medical Artificial Intelligence (QAMAI) tool: a new tool to assess the quality of health information provided by AI platforms
Authors: Vaira Luigi Angelo , Lechien Jerome R. , Abbate Vincenzo , Allevi Fabiana , Audino Giovanni , Beltramini Giada Anna , Bergonzani Michela , Boscolo-Rizzo Paolo , Califano Gianluigi , Cammaroto Giovanni , Chiesa-Estomba Carlos M. , Committeri Umberto , Crimi Salvatore , Curran Nicholas R. , di Bello Francesco , di Stadio Arianna , Frosolini Andrea , Gabriele Guido , Gengler Isabelle M. , Lonardi Fabio , Maglitto Fabio , Mayo-Yáñez Miguel , Petrocelli Marzia , Pucci Resi , Saibene Alberto Maria , Saponaro Gianmarco , Tel Alessandro , Trabalzini Franco , Trecca Eleonora M. C. , Vellone Valentino , Salzano Giovanni , De Riu Giacomo 
Published: May 2024

Abstract
Background
The widespread diffusion of Artificial Intelligence (AI) platforms is revolutionizing how health-related information is disseminated, thereby highlighting the need for tools to evaluate the quality of such information. This study aimed to propose and validate the Quality Assessment of Medical Artificial Intelligence (QAMAI), a tool specifically designed to assess the quality of health information provided by AI platforms.

Methods
The QAMAI tool has been developed by a panel of experts following guidelines for the development of new questionnaires. A total of 30 responses from ChatGPT4, addressing patient queries, theoretical questions, and clinical head and neck surgery scenarios were assessed by 27 reviewers from 25 academic centers worldwide. Construct validity, internal consistency, inter-rater and test–retest reliability were assessed to validate the tool.

Results
The validation was conducted on the basis of 792 assessments for the 30 responses given by ChatGPT4. The results of the exploratory factor analysis revealed a unidimensional structure of the QAMAI with a single factor comprising all the items that explained 51.1% of the variance with factor loadings ranging from 0.449 to 0.856. Overall internal consistency was high (Cronbach's alpha = 0.837). The Interclass Correlation Coefficient was 0.983 (95% CI 0.973–0.991; F (29,542) = 68.3; p < 0.001), indicating excellent reliability. Test–retest reliability analysis revealed a moderate-to-strong correlation with a Pearson’s coefficient of 0.876 (95% CI 0.859–0.891; p < 0.001).

Conclusions
The QAMAI tool demonstrated significant reliability and validity in assessing the quality of health information provided by AI platforms. Such a tool might become particularly important/useful for physicians as patients increasingly seek medical information on AI platforms.
The effect of NHFOV on hemodynamics in mild and moderately preterm neonates: a randomized clinical trial
Authors: Farag Marwa Mohamed , Hassan Mohamed Ahmed Amen , Fasseeh Nader Abd EL Moneim , Ghazal Hesham Abd EL Rahim 
Published: May 2024

AbstractThe aim of this study is to study cardio-respiratory effects of nasal high-frequency oscillatory ventilation (NHFOV) vs. NCPAP as an initial mode of ventilation in moderate-late-preterm infants. A randomized controlled trial was conducted in NICU of Alexandria University Maternity Hospital (AUMH). One-hundred late-moderate-preterm infants were randomly assigned to either NHFOV-group (n = 50) or NCPAP-group (n = 50). For both groups, functional echocardiography was performed in the first 24 h to detect hemodynamic changes and respiratory outcome was monitored throughout the hospital stay. The main outcomes were hemodynamic measurements and myocardial function using functional echocardiography of those infants along with the respiratory outcome and complications. Kaplan–Meier survival plot was used representing time course of NCPAP and NHFOV failure. Left ventricular output values were not significantly different in both groups with median 202 ml/kg /min and IQR (176–275) in NCPAP-group and 226 ml/kg/min with IQR (181–286) in NHFOV group. Nevertheless, ejection fraction and fractional shortening were significantly higher in NHFOV-group with P 0.001. The time to weaning, the time to reach 30%-FIO2, the need for invasive ventilation, oxygen support duration, and maximal-FIO2 were significantly more in NCAPAP group. Conclusion: NHFOV is an effective and promising tool of non-invasive-ventilation which can be used as a primary modality of respiratory support in preterm infants with variable forms of respiratory distress syndrome without causing detrimental effect on hemodynamics or significant respiratory complications. Trial registration: NCT05706428 (registered on January 21, 2023).

What is Known:• NHFOV might be beneficial as a secondary mode of ventilation and might have an impact on hemodynamics.

What is New:• NHFOV can be used as an initial mode of ventilation with CDP beyond the reported pressure limits of CPAP without causing neither CO2 retention nor adverse hemodynamic consequences.
Hybrid modeling of an ultracentrifugation process for separation of full and empty adeno-associated virus particles
Authors: De-Luca Riccardo , Pupo-Correia Miguel , Feldhofer Michael , Martins Duarte L. , Umprecht Alexandra , Shahmohammadi Ali , Corona Daniel , von Stosch Moritz 
Published: May 2024

AbstractUltracentrifugation is an attractive method for separating full and empty capsids, exploiting their density difference. Changes of the serotype/capsid, density of loading material, or the genetic information contained in the adeno-associated viruses (AAVs) require the adaptation of the harvesting parameters and the density gradient loaded onto the centrifuge. To streamline these adaptations, a mathematical model could support the design and testing of operating conditions.Here, hybrid models, which combine empirical functions with artificial neural networks, are proposed to describe the separation of full and empty capsids as a function of material and operational parameters, i.e., the harvest model. In addition, critical quality attributes are estimated by a quality model which is operating on top of the harvest model. The performance of these models was evaluated using test data and two additional blind runs. Also, a “what-if” analysis was conducted to investigate whether the models’ predictions align with expectations.It is concluded that the models are sufficiently accurate to support the design of operating conditions, though the accuracy and applicability of the models can further be increased by training them on more specific data with higher variability.
A Tool for the Assessment of Swallowing Safety and Efficiency in Adults: Turkish Adaptation of Boston Residue and Clearance Scale
Authors: Tosun Samet , Topbaş Saime Seyhun , Aksoy Elif 
Published: May 2024

Abstract
The objective of this study was to create a Turkish language adaptation of the Boston Residue and Clearance Scale (BRACS), a validated and reliable tool. The BRACS scale was first translated into Turkish and a Turkish version was subsequently developed. Fiberoptic endoscopic examination of swallowing (FEES) was administered to collect data from 25 dysphagic patients who were hospitalized after a stroke. The recorded films were subjected to editing procedures to ensure their appropriateness for the assessment of swallowing disorders and were then dispatched to a panel of five speech and language therapists for evaluation using the adaptation of the BRACS instrument. The scoring by the experts was evaluated using both explanatory factor analysis (EFA) and confirmatory factor analysis (CFA). Convergent validity, item reliability, and construct (composite) reliability were measured by calculating the average variance extracted (AVE) values. For the 12 location items, EFA revealed 3 main latent factors: the laryngeal vestibule and the oropharynx and hypopharynx. The Turkish BRACS had excellent inter-rater reliability (Krippendorff’s alpha coefficient values ranged from 0.93 to 0.95) and high internal consistency (Cronbach’s alpha values ranged from 0.88 to 0.93). Inter-rater ICCs for the first and second sessions were 0.83 and 0.85, respectively. CFA showed that all fitted criteria reached acceptable or perfect fit levels. The findings indicated that the proposed factor structure was validated. The AVE values are between 0.61 and 0.73 which was taken as evidence of convergent validity. The Turkish adaptation of the BRACS tool demonstrates both reliablity and validity, rendering it a useful and credible tool for assessing residual severity, particularly in clinical settings.
Viable protoplast isolation, organelle visualization and transformation of the globally distributed plant pathogen Phytophthora cinnamomi
Authors: Kharel Aayushree , Rookes James , Ziemann Mark , Cahill David 
Published: May 2024

AbstractPhytophthora cinnamomi is an oomycete plant pathogen with a host range of almost 5000 plant species worldwide and therefore poses a serious threat to biodiversity. Omics technology has provided significant progress in our understanding of oomycete biology, however, transformation studies of Phytophthora for gene functionalisation are still in their infancy. Only a limited number of Phytophthora species have been successfully transformed and gene edited to elucidate the role of particular genes. There is a need to escalate our efforts to understand molecular processes, gene regulation and infection mechanisms of the pathogen to enable us to develop new disease management strategies. The primary obstacle hindering the advancement of transformation studies in Phytophthora is their challenging and unique nature, coupled with our limited comprehension of why they remain such an intractable system to work with. In this study, we have identified some of the key factors associated with the recalcitrant nature of P. cinnamomi. We have incorporated fluorescence microscopy and flow cytometry along with the organelle-specific dyes, fluorescein diacetate, Hoechst 33342 and MitoTracker™ Red CMXRos, to assess P. cinnamomi-derived protoplast populations. This approach has also provided valuable insights into the broader cell biology of Phytophthora. Furthermore, we have optimized the crucial steps that allow transformation of P. cinnamomi and have generated transformed isolates that express a cyan fluorescent protein, with a transformation efficiency of 19.5%. We therefore provide a platform for these methodologies to be applied for the transformation of other Phytophthora species and pave the way for future gene functionalisation studies.
Open vs. robot-assisted preperitoneal inguinal hernia repair. Are they truly clinically different?
Authors: Rodrigues-Gonçalves V. , Verdaguer-Tremolosa M. , Martínez-López P. , Fernandes N. , Bel R. , López-Cano M. 
Published: May 2024

Abstract
Introduction
Inguinal hernia repair lacks a standard repair technique, with laparo-endoscopic and open preperitoneal methods showing similar outcomes. Despite higher costs, the popularity of robotic surgery is on the rise, driven by technological advantages. Controversies persist in comparing open repair techniques with the robotic approach, given contradictory results. The objective of this study was to compare postoperative outcomes, including complications, chronic pain, and recurrence, between open and robotic-assisted preperitoneal inguinal hernia repair.

Methods
This single-center retrospective study encompassed patients undergoing elective inguinal hernia repair in a specialized unit, employing both open preperitoneal and robotic-assisted laparoscopic approaches from September 2018 to May 2023. Comparative analysis of short- and long-term outcomes between these techniques was conducted. Additionally, multivariate logistic regression was employed to explore predictors of postoperative complications.

Results
A total of 308 patients met the inclusion criteria. 198 (64%) patients underwent surgery using an open preperitoneal approach and 110 (36%) using robot-assisted laparoscopy. Patients in the robot-assisted group were younger (P = 0.006) and had fewer comorbidities (P < 0.001). There were no differences between the groups in terms of postoperative complications (P = 0.133), chronic pain (P = 0.463) or recurrence (P = 0.192). Multivariate analysis identified ASA ≥ III (OR, 1.763; 95%CI, 1.068–3.994; P = 0.027) and inguinoscrotal hernias (OR, 2.371, 95%CI, 1.407–3.944; P = 0.001) as risk factors of postoperative complications.

Conclusions
Both open preperitoneal and robotic-assisted laparoscopic approaches show similar outcomes for complications, chronic pain, and recurrence when performed by experienced surgeons. The open preperitoneal approach, with its quicker operative time, may be advantageous for high-comorbidity cases. Treatment choice should consider patient factors, surgeon experience, and healthcare resources.
Tracking and co-location of global point clouds for large-area indoor environments
Authors: Michiels Nick , Jorissen Lode , Put Jeroen , Liesenborgs Jori , Vandebroeck Isjtar , Joris Eric , Van Reeth Frank 
Published: May 2024

AbstractExtended reality (XR) experiences are on the verge of becoming widely adopted in diverse application domains. An essential part of the technology is accurate tracking and localization of the headset to create an immersive experience. A subset of the applications require perfect co-location between the real and the virtual world, where virtual objects are aligned with real-world counterparts. Current headsets support co-location for small areas, but suffer from drift when scaling up to larger ones such as buildings or factories. This paper proposes tools and solutions for this challenge by splitting up the simultaneous localization and mapping (SLAM) into separate mapping and localization stages. In the pre-processing stage, a feature map is built for the entire tracking area. A global optimizer is applied to correct the deformations caused by drift, guided by a sparse set of ground truth markers in the point cloud of a laser scan. Optionally, further refinement is applied by matching features between the ground truth keyframe images and their rendered-out SLAM estimates of the point cloud. In the second, real-time stage, the rectified feature map is used to perform localization and sensor fusion between the global tracking and the headset. The results show that the approach achieves robust co-location between the virtual and the real 3D environment for large and complex tracking environments.
The smart home, a true home? How new technologies disrupt the experience of home for older persons
Authors: Felber Nadine Andrea , Alavi Hamed , Mugellini Elena , Wangmo Tenzin 
Published: May 2024

AbstractSmart home technologies (SHTs) can support older persons to age in place. However, adoption of SHTs remains low among this population. A reason for this is that they are not accustomed to having a home that is technologically enhanced. In this article, we focus on the older persons’ lived experience of “home” and show how SHTs potentially disrupt it. In consulting the currently available literature, both theoretical and empirical, we propose and use the concept of somatic capability assessment (SCA) in the discussion surrounding the design of SHTs for older persons. First, we propose SCA as a concept to grasp how humans take decisions while relying on their physical body, undisturbed by suggestions from technologies. Furthermore, we show that SCA functions best in a familiar and private environment—the home. SHTs have the potential to make the home seem unfamiliar and exposed, precisely through added data and the resulting suggestions, as we show through related empirical studies. Thus, SHTs hold an increased disruptive potential for older persons at home. By introducing SCA into the discussion of SHTs for older persons, and thus paying attention on how SHTs potentially disrupt the experience of home, further advances the ethical discussion on the adequate use and design of technologies in daily life, especially for the group of older persons. Our analysis offers important insights for the design and implementation processes of SHTs for older persons.
Effects of an extreme weather event over reproduction and survival of Great Tits (Parus major) in eastern Spain
Authors: Solís Iris , Álvarez Elena , Barba Emilio 
Published: May 2024

AbstractThe frequency of extreme climatic and weather events has increased since 1950 due to global changes induced by human influence. These events can have significant impacts at the individual, population, and community levels across various taxonomic groups. They can be particularly detrimental to bird populations during their breeding season, affecting specific breeding parameters. This study originated from an exceptionally rare breeding season of a resident Great Tit population recorded in spring 2002 when an unusual mortality of nestlings was observed. We quantified weather conditions (temperature, rainfall) from the end of April, a few days before we started detecting failed nests, and compared them with previous and subsequent years. In early May, when many pairs were incubating or caring for newly hatched chicks, we detected unusually low ambient temperatures and unusually high rainfall. This event likely caused that many first clutches failed completely, and that, compared with previous and subsequent years, fledging and breeding success was relatively low in those which were successful. There was also an increased proportion of replacement clutches that year. Anyway, the overall production of fledglings per breeding pair over the breeding season was 2.39, lower than other years. Although recruitment rate in 2003 was similar to other years, the lower production of fledglings in 2002 probably resulted in a decrease in the number of breeding pairs in the following years.
Measurement of Serum Vitamins B2 and B6 in Patients with Hashimoto’s Thyroiditis by LC–MS/MS Method
Authors: Mikulska-Sauermann Aniceta Ada , Karaźniewicz-Łada Marta , Filipowicz Dorota , Ruchała Marek , Główka Franciszek 
Published: May 2024

AbstractVitamin B2 and vitamin B6 are cofactors and coenzymes in many biochemical reactions, and their sufficient serum concentrations may be crucial for the proper functioning of the thyroid gland. The aim of the study was to develop and validate a novel high-performance liquid chromatography–tandem mass spectrometry (LC–MS/MS) method for the determination of vitamin B2 and vitamin B6 in the serum of patients with Hashimoto’s thyroiditis (HT). Detection of the analytes was performed on a triple-quadrupole MS with multiple reaction monitoring using electrospray ionization. The mobile phase consisted of water and methanol, both containing 0.1% (v/v) formic acid. The analytes were isolated from serum by the one-step sample preparation of the trichloroacetic acid precipitation. Validation parameters, including linearity, accuracy, precision, limits of detection and quantification, and stability, were determined and fulfilled the criteria for analyzing compounds in biological fluids. The method was applied for the determination of the above vitamin concentrations in serum samples of 74 patients with HT and 33 healthy controls. The concentration of vitamin B2 was significantly lower in patients with HT compared to the control group (7.20 ± 7.86 ng/mL vs. 12.03 ± 9.62 ng/mL) and the concentration of vitamin B6 was also lower, but without a statistically significant difference (30.09 ± 19.16 ng/mL vs. 37.29 ± 23.02 ng/mL). We concluded that the vitamins concentration measurement may be helpful in the diagnosis of vitamin deficiencies and the supplementation strategy.
A machine learning approach for package size estimation using UHF RFID interrogation signature
Authors: Vales-Alonso Javier , López-Matencio Pablo 
Published: May 2024

AbstractThis paper introduces a new approach for performing package classification and sizing using Radio-Frequency Identification (RFID) systems. This technique is applicable when packages are labeled with or contain multiple RFID-tagged items. During the interrogation of the tags, received signal strength (RSS) statistics and other information, such as the frame count or the reading time, are collected by the reader and used to predict the package type from a set of candidate classes using an Artificial Neural Network (ANN). The primary challenge lies in acquiring sufficient training data for a target scenario to ensure reliable predictions. To address this, a two-phase training process based on transfer learning is adopted. Initially, a base model is developed using synthetic data generated from a detailed RFID simulator, designed to suit diverse scenarios, establish detailed link budgets, and comprehensively simulate the communication protocols. This model is then refined using a small dataset collected experimentally in the actual scenario. This method was validated in a real testbed with four different package types. The base model was trained using 1000 synthetic samples per package type (4000 in total), whereas the refined model was trained with a dataset consisting of only 25 real interrogation traces (samples) per package type (100 in total). The experimental samples were obtained using a software-defined radio unit, the Ettus B210 Universal Software Radio Peripheral (USRP) platform. This experiment achieved an accuracy of over 92%. In summary, this approach introduces a new feature to existing RFID setups, demonstrating potential for advanced package handling and cost optimization in the logistics sector.
Privacy-preserving visual analysis: training video obfuscation models without sensitive labels
Authors: De Coninck Sander , Wang Wei-Cheng , Leroux Sam , Simoens Pieter 
Published: May 2024

AbstractVisual analysis tasks, including crowd management, often require resource-intensive machine learning models, posing challenges for deployment on edge hardware. Consequently, cloud computing emerges as a prevalent solution. To address privacy concerns associated with offloading video data to remote cloud platforms, we present a novel approach using adversarial training to develop a lightweight obfuscator neural network. Our method focuses on pedestrian detection as an example of visual analysis, allowing the transformation of video frames on the camera itself to retain only essential information for pedestrian detection while preserving privacy. Importantly, the obfuscated data remains compatible with publicly available object detectors, requiring no modifications or significant loss in accuracy. Additionally, our technique overcomes the common limitation of relying on labeled sensitive attributes for privacy preservation. By demonstrating the inability of pedestrian attribute recognition models to detect attributes in obfuscated videos, we validate the efficacy of our privacy protection method. Our results suggest that this scalable approach holds promise for enabling camera usage in video analytics while upholding personal privacy.