bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gestaltungs- und Evaluationsmöglichkeiten von Multimediaanwendungen zur Unterstützung der Betreuung von Menschen mit leichter Demenz
Authors: von Bosse Alexa , Bejan Alexander , Wessel Max , Kunze Christophe 
Published: January 2024

Zusammenfassung
Hintergrund
Zur kognitiv-körperlichen Aktivierung von Menschen mit Demenz (MMD) im stationären Setting stehen vielfältige, zielgruppenspezifisch konzipierte touchbasierte Multimedia-Anwendungen zur Verfügung, die auch tatsächlich in der Praxis genutzt werden. Im Vergleich dazu ist der Einsatz vergleichbarer Anwendungen in der Häuslichkeit bislang gering ausgeprägt.

Ziel und Methodik
Die vorliegende Studie untersucht anhand von 11 leitfadengestützten Expert*inneninterviews sowohl Gestaltungsoptionen und Anforderungen an Anwendungsinhalte als auch Anforderungen an Studiendesigns zu Wirksamkeitsnachweisen touchbasierter Multimedia-Anwendungen für MMD und ihre pflegenden Angehörigen (PA).

Ergebnisse
Es zeigt sich eine große Übereinstimmung bezüglich allgemeiner Anforderungskriterien an touchbasierte Multimedia-Anwendungen – die Akzeptanz ist in hohem Maße von Nutzungskompetenzen, Nutzungspraktiken, Erfahrungen sowie Anreizstrukturen abhängig. Auf der anderen Seite liegen heterogene Meinungen zur inhaltlich-strukturellen Ausgestaltung touchbasierter Multimedia-Anwendungen für MMD vor. Lebensqualität wird als elementarer Evaluationsparameter von Multimedia-Anwendungen genannt.

Diskussion
Individuell stark variierende Lebensumstände von MMD und ihren PA sowie mangelnde Zugangsmöglichkeiten und fehlende Passgenauigkeit der Multimedia-Anwendungen können ursächlich für ihren bislang geringen Einsatz insbesondere in der Häuslichkeit sein. Tagesabhängige Leistungsfähigkeiten und individuelle Krankheitsverläufe stellen besondere Anforderungen an die wissenschaftliche Evaluation und an Wirksamkeitsnachweise touchbasierter Multimedia-Anwendungen dar.
Occupational injuries in orthopedic and trauma surgeons in Austria
Authors: Clar Clemens , Koutp Amir , Leithner Andreas , Leitner Lukas , Puchwein Paul , Vielgut Ines , Sadoghi Patrick 
Published: January 2024

Abstract
Background
The aim of this study was to investigate the frequency and type of injuries during the career of orthopedic and trauma surgeons in Austria. The hypothesis was that the percentage of occupational injuries among orthopedic and trauma surgeons aligns with the incidence reported in the United States, thus indicating the need for a workplace prevention program.

Methods
A web-based survey was created to collect all necessary data and was sent to all orthopedic and trauma surgeons in Austria via e-mail. Relevant parameters included the surgeons’ age, work experience, severity of pain, type of injury, and current pain. Descriptive and explorative statistical analysis was performed.

Results
A web-based survey was sent to 1122 board-certified orthopedic surgeons and residents in Austria via e-mail. In total, the response rate was 135 (12%). Seventy-two surgeons (54%) had suffered from one or more occupational injuries during their career. We detected a significant raise of occupational injuries related to the work life duration in which operations were performed and the prevalence of injuries. Most injuries of surgeons were reported between 21 and 30 years of their professional life. According to the frequency at different locations, the distribution in descending order was 25% with injuries of the hand, 22% of finger(s), 12% of the foot, 10% of the spine, 2% of the neck, 3% of the head, and 2% of the abdomen. A causality of incapacity to work through injuries at the workplace was given as 4%. Four percent stated a sick leave of at least 3 weeks. In 7% of the facilities, there was no optimization of preventive measures following an occupational injury. We found no correlation of injuries and resident status.

Conclusion
Orthopedic surgeons in Austria show a high incidence of occupational injuries in line with the findings of colleagues from the United States. The impact on the health system consists of absenteeism in the workplace of highly specialized health service providers as well as the incapacity to work of a high quality, highly trained workforce of at least 4%. With more preventive measures and more attention and care in the rehabilitation phase after such injuries, a positive effect could be achieved. We believe that residents should be specifically trained on how to avoid such injuries.
The m6A demethylase FTO targets POLQ to promote ccRCC cell proliferation and genome stability maintenance
Authors: He Yichen , Chen Yimeng , Li Zhengsheng , Wu Changping 
Published: January 2024

Abstract
Background and aim
As the first identified m6A demethylase, FTO has been implicated in the progression of various cancers. However, the specific mechanism of FTO in clear cell renal cell carcinoma (ccRCC) remains incompletely understood. In this study, we aimed to explore the potential molecular mechanisms influencing the progression of ccRCC.

Methods
We initially assessed the expression of FTO in tumor and adjacent tissues using TCGA database, RT-qPCR, and Western blot. We then conducted CCK-8, cell cycle analysis, and colony formation assay to investigate the impact of FTO on ccRCC cell proliferation. MeRIP-seq and RNA-seq were employed to identify potential downstream targets of FTO in ccRCC, and these findings were further validated through dual-luciferase reporter assays and MeRIP-qPCR. Then, DNA damage and cell death were assessed separately through gammaH2AX immunofluorescence detection and the LIVE/DEAD Fixable Dead Cell Stain assay, respectively. Subsequently, we identified downstream pathways influenced by FTO's regulation of POLQ through TCGA database analysis and GSEA enrichment analysis. Validation was carried out through Western blot.

Results
FTO is highly expressed in ccRCC tissues and cell lines. Furthermore, ROC curve demonstrates that FTO contributes to the diagnosis of ccRCC. FTO modulates m6A modification, consequently influencing the expression of POLQ, thus facilitating cell proliferation and maintaining genome stability in ccRCC.

Conclusion
FTO could potentially serve as a diagnostic marker for ccRCC. FTO promotes the progression of ccRCC by regulating m6A modification, making the inhibition of FTO a potential novel therapeutic strategy in ccRCC.
Prognosis and immunotherapy response prediction based on M2 macrophage-related genes in colon cancer
Authors: Xu Xiaochen , Zhang Xinwen , Kou Ruilong , Liu Yihao , Chen Siqi , Li Zuguo , Jian Zhiyuan , wang Zhenran 
Published: January 2024

Abstract
Background
M2 macrophage were revealed to play a crucial role in immune evasion and immunotherapies. This study aims to explore the potential significance of M2 macrophage-related genes in colon adenocarcinoma (COAD) by analysizing the transcriptome data in a comprehensive way.

Methods
We collected RNA-sequencing (RNA-seq) data of COAD from The Cancer Genome Atlas (TCGA) and Gene Expression Ominibus (GEO) databases. We calculated the immune infiltration scores of every sample using CIBERSORT algorithm. Through weighted gene co-expression network analysis (WGCNA), we picked out M2 macrophage-related genes. With these genes we screened out prognosis related genes which were utilized to construct a signature to assess the prognosis of patients. To extend the potential application of the signature, we also calculated the correlations with immune infiltration. Finally, we applied techniques such as quantitative reverse transcription polymerase chain reaction (qRT–PCR) and immunoblotting (Western Blotting) to validate the RNF32 gene in cellular in vitro assays.

Results
Seven M2 macrophage-related genes signature was constructed, which was an excellent prognostic predictor in two independent groups. The high-risk group showed lower immune infiltration and poorer response to immunotherapies than those of the low-risk group. The cell vitro experiments showed that the expression level of RNF32 was upregulated in colon cancer cell lines compared with normal cell lines. Moreover, we found that RNF32 may promote the proliferation, migration and invasion of cancer cells in vitro by inhibiting apoptosis.

Conclusion
A novel M2 macrophage-related gene signature affects the prognosis and immune characteristics of colon cancer.
Prediction of positive pulmonary nodules based on machine learning algorithm combined with central carbon metabolism data
Authors: Liu Jian-jun , Shen Wen-bin , Qin Qi-rong , Li Jian-wei , Li Xue , Liu Meng-yu , Hu Wen-lei , Wu Yue-yang , Huang Fen 
Published: January 2024

Abstract
Background
Lung cancer causes a huge disease burden, and early detection of positive pulmonary nodules (PPNs) as an early sign of lung cancer is extremely important for effective intervention. It is necessary to develop PPNs risk recognizer based on machine learning algorithm combined with central carbon metabolomics.

Methods
The study included 2248 participants at high risk for lung cancer from the Ma'anshan Community Lung Cancer Screening cohort. The Least Absolute Shrinkage and Selection Operator (LASSO) was used to screen 18 central carbon-related metabolites in plasma, recursive feature elimination (RFE) was used to select all 42 features, followed by five machine learning algorithms for model development. The performance of the model was evaluated using area under the receiver operator characteristic curve (AUC), accuracy, precision, recall, and F1 scores. In addition, SHapley Additive exPlanations (SHAP) was performed to assess the interpretability of the final selected model and to gain insight into the impact of features on the predicted results.

Results
Finally, the two prediction models based on the random forest (RF) algorithm performed best, with AUC values of 0.87 and 0.83, respectively, better than other models. We found that homogentisic acid, fumaric acid, maleic acid, hippuric acid, gluconic acid, and succinic acid played a significant role in both PPNs prediction model and NPNs vs PPNs model, while 2-oxadipic acid only played a role in the former model and phosphopyruvate only played a role in the NPNs vs PPNs model. This model demonstrates the potential of central carbon metabolism for PPNs risk prediction and identification.

Conclusion
We developed a series of predictive models for PPNs, which can help in the early detection of PPNs and thus reduce the risk of lung cancer.
Auf dem Weg zum Fahrradland – Barrieren von Nichtradfahrer*innen identifizieren und überwinden
Authors: Popp Monika , Rau Henrike , Mahne-Bieder Johannes 
Published: January 2024

ZusammenfassungDie Steigerung des Fahrradverkehrs wird als wichtiger Baustein bei der Transformation hin zu einer nachhaltigen Mobilität gesehen. Der Nationale Radverkehrsplan 3.0 setzt hier unter dem Titel „Fahrradland Deutschland 2030“ ein deutliches Ziel. Die bisherige Fahrradförderung zeigt bisher allerdings nur punktuelle Erfolge: Der durchschnittliche Anteil der Fahrten mit dem Fahrrad ist in Deutschland in den letzten 20 Jahren kaum gestiegen und insbesondere der Anteil der Nichtradfahrer*innen konnte nicht reduziert werden. Im Vergleich zu sogenannten Fahrradnationen wie den Niederlanden ist der Anteil der Personen in Deutschland, die nur selten oder gar nicht Rad fahren, außerdem sehr hoch, was ein klares Hemmnis für die Mobilitätswende darstellt. Das Projekt RadAktiv hat deswegen Radfahrer*innen und Nichtradfahrer*innen systematisch verglichen und Barrieren der Radnutzung identifiziert. Die Studie basiert auf qualitativen Interviews sowie einer deutschlandweiten repräsentativen Befragung (n = 5002). Die größten Unterschiede zwischen Radfahrer*innen und Nichtradfahrer*innen wurden im Bereich der Mobilitätssozialisation und in der Einschätzung der Alltagstauglichkeit des Fahrrads als Verkehrsmittel identifiziert. Außerdem wurde eine Klassifizierung der Nichtradfahrer*innen vorgenommen, die anhand der Aktivierbarkeit drei Typen und ihre spezifischen Barrieren beschreibt: Beinahe-Radfahrer*innen, Radskeptiker*innen und Radverweigerer*innen. Aus den Ergebnissen wurden typspezifische Maßnahmen zur Aktivierung von Nichtradfahrer*innen abgeleitet. Neben Infrastrukturmaßnahmen, die bereits im Fokus vieler Förderanstrengungen stehen, müssen dabei zukünftig auch soziale und kulturelle Gründe für das Nichtradfahren stärkere Berücksichtigung finden. Eine zielgruppengerechte und typenspezifische Kommunikation bezüglich der Vorteile des Fahrrads, die Stärkung einer fahrradfreundlichen Mobilitätskultur sowie die explizite Anerkennung der lebensweltlichen Bedingungen und Erfahrungen verschiedener Typen von Nichtradfahrer*innen stellen dabei vielversprechende Ansätze dar.
Basic method for water detection in LiPF6-based electrolytes
Authors: Šimek Antonín , Kazda Tomáš , Báňa Jiří , Čech Ondřej 
Published: January 2024

AbstractThis paper investigates the effect of water content on lithium-ion battery electrolytes with particular emphasis on the degradation of lithium hexafluorophosphate, a commonly used salt in commercial electrolytes. The study addresses various degradation mechanisms caused by water in a battery system. In addition, the research utilizes electrochemical techniques to detect water and associated changes in electrochemical performance of the cell. The electrochemical water detection method investigated is very fast. The lower detection limit was not tested, but contamination of 250 ppm can be reliably detected. It can be used, for example, in experimental research to determine the purity and quality of the electrolyte used.
Graphical abstract
A multi-method investigation of the permeability structure of brittle fault zones with ductile precursors in crystalline rock
Authors: Osten Julian , Schaber Tom , Gaus Garri , Hamdi Pooya , Amann Florian , Achtziger-Zupančič Peter 
Published: January 2024

AbstractBrittle faults and fault zones are among the most hydraulically active elements in predominantly impermeable crystalline host rock. They pose a significant challenge to underground infrastructure like nuclear waste repositories. Brittle fault zones frequently occur along pre-existing ductile shear zones as they introduce weakness planes in the rock.Four brittle fault zones of ductile origin were analyzed in the Rotondo Granite at the “BedrettoLab” in the Swiss Central Alps. Scanline mapping, rock sampling and permeability measurements using three different methods provide detailed insights into the heterogeneous fault zone architecture and hydrogeology. Average intact rock permeability is in the range of 10−19 to 10−17 m2. Fluid flow is channeled into single open or partially mineralized fractures of, at point-scale, up to 10−14 m2, demonstrated by selective gas probe permeameter measurements and borehole hydraulic testing. Reduced permeabilities have been measured in close proximity to these permeable features, indicating alteration of and around the fracture walls.
Distinguishing between Crohn’s disease and ulcerative colitis using deep learning models with interpretability
Authors: Maurício José , Domingues Inês 
Published: January 2024

AbstractCrohn’s disease and ulcerative colitis are two chronic diseases that cause inflammation in the tissues of the entire gastrointestinal tract and are described by the term inflammatory bowel disease. Gastroenterologists find it difficult to evaluate endoscopic images to recognise the characteristics of the two chronic diseases. Therefore, this work aims to build a dataset with images of Crohn’s disease and ulcerative colitis (collected from the public datasets LIMUC, HyperKvasir and CrohnIPI) and train deep learning models (five CNNs and six ViTs) to develop a tool capable of helping doctors to distinguish the type of inflammatory bowel disease. In addition, as these architectures will be too heavy to work in a hospital context, in this work, we are looking to use knowledge distillation to create lighter and simpler architectures with the same precision as the pre-trained architectures used in this study. During this process, it is important to evaluate and interpret the pre-trained architectures before the distillation process, and the architectures resulting from knowledge distillation to ensure that we can maintain performance and that the information learnt by both architectures are similar. It is concluded that is possible to reduce 25x the number of parameters while maintaining good performance and reducing the inference time by 5.32 s. Allied with this, through the interpretability of the models was concluded that both before and after the knowledge distillation are possible to identify ulcers, bleeding situations, and lesions caused by the inflammation of the disease.
Fully immersive learning with virtual reality for assessing students in art history
Authors: Cecotti Hubert , Huisinga Laura , Peláez Luis Gordo 
Published: January 2024

AbstractImmersive learning systems using consumer grade headsets for virtual reality (VR) software can now reach the classroom. VR represents an important step toward situated learning for bringing realistic experiences to show to students different types of content the way it appears in real life. With the three-dimensional effect, it adds an immersive dimension that can bring the student into a unique environment that is directly connected to the learning content. While VR experiences can be helpful in educational settings, they must satisfy the learning objectives of the course and the specific needs of the students. In this paper, we propose a customizable VR application for displaying paintings for their analysis, and their associated questions designed for instructors in art history. To improve the accessibility and adaptivity to instructors and specific learning materials, we propose the definition of the paintings’ characteristics and the questionnaires associated with the paintings in the JSON open-standard file format, facilitating application changes without any prior programming knowledge. We compare the proposed VR modality with a web-based application on a computer desktop with 35 undergraduate students with art history experience. In both modalities, we assess the workload and usability; the VR sickness symptoms and the motivation in the VR condition. The results indicate better usability and lower workload with the VR condition. While there are no differences in terms of students’ performance for answering the questions, 77% of students prefer the VR condition. The Reduced Instructional Materials Motivation Survey shows a high motivation in the student population. Finally, the system evaluation supports the conclusion that the proposed VR system can be deployed in the art history classroom as the system has a high usability and medium workload.
Allometric equations to calculate living and dead fuel loads in Mediterranean species
Authors: Deltell Leyre , Santana Victor Manuel , Jaime Baeza M. 
Published: January 2024

AbstractDetermining the structure and fuel load is key to know the flammability of vegetation in the Mediterranean Basin where forest fires are frequent. Determine which plant structural variable is best related to living and dead fuel to develop allometric equations in nine species in the Western Mediterranean Basin. In the east of the Iberian Peninsula (Valencia Province), we measured four structural variables (basal stem diameter, height, maximum diameter and perpendicular diameter) that were related, by means of allometric equations, to the living and dead fuel separated into different size classes. We also analyze fuel changes across developmental states of the studied species, and the vertical distribution of dead fuel. General equations that consider all development states can be used to determine living fuel. However to obtain dead fuel, we recommend using specific equations for each development state and fuel fraction for better accuracy. The basal stem diameter was the best structural variable in almost all cases for estimating fuel in the studied species. Dead fuel load throughout species’ ontological development is a key factor to manage Mediterranean plant communities.
Characterizing Socioecological Markers of Differentiated HIV Risk Among Men Who Have Sex with Men in Indonesia
Authors: Nevendorff Laura , Pedrana Alisa , Bourne Adam , Traeger Michael , Sindunata Eric , Reswana Wawa A. , Alharbi Rosidin M. , Stoové Mark 
Published: January 2024

AbstractHIV prevention programs typically focus on changing individuals’ risk behaviors, often without considering the socioecological factors that can moderate this risk. We characterized HIV risk among men who have sex with men (MSM) in Indonesia (n = 1314) using latent class analysis and used multinomial logistic regression to identify latent class relationships with demographics, social/sexual networks, and community-level socioecological indicators of HIV risk. Three HIV risk latent classes were identified—“Sexually Moderate” (n = 333), “Sexual Explorative” (n = 575), and “Navigating Complexities” (n = 406). Using “Sexually Moderate” (lowest risk) as the reference group, MSM in the “Sexual Explorative” class had additional social/sexual network-level risks (meeting partner(s) using both online and offline methods [RR = 3.8; 95%CI 1.7–8.6] or general social media and gay-specific online platforms [RR = 2.6; 95%CI 1.9–3.6] to meet partners, group sex [RR = 10.9; 95%CI 4.5–25.4], transactional sex [RR = 1.6; 95%CI 1.2–2.2]), and community-level risks (experiencing homosexual-related assaults [RR = 1.4; 95%CI 1.1–1.9]). MSM in the “Navigating Complexities” class had additional social/sexual network-level risks (low social support [RR = 1.6; 95%CI 1.1–2.5], less disclosure of their sexuality [RR = 1.4; 95%CI 1.0–1.9]) and community-level risks (higher internalized homonegativity scores [RR = 1.2; 95%CI 1.1–1.4], ever experiencing homosexual-related assaults [RR = 1.4:95%CI 1.1–1.9], less exposure to HIV/STI health promotion [RR = 0.7; 95%CI 0.5–0.9], attending STI-related services in the past 6 months [RR = 0.6; 95%CI 0.4–0.8]). Co-occurring individual and socioecological risk recommend holistic HIV prevention strategies tailored to consider the social and structural conditions of MSM in Indonesia are needed.
Finding the input features that reduce the entropy of a neural network’s prediction
Authors: Amanova Narbota , Martin Jörg , Elster Clemens 
Published: January 2024

AbstractIn deep learning-based image classification, the entropy of a neural network’s output is often taken as a measure of its uncertainty. We introduce an explainability method that identifies those features in the input that impact most this uncertainty. Learning the corresponding features by straightforward backpropagation typically leads to results that are hard to interpret. We propose an extension of the recently proposed oriented, modified integrated gradients (OMIG) technique as an alternative to produce perturbations of the input that have a visual quality comparable to explainability methods from the literature but marks features that have a substantially higher impact on the entropy. The potential benefits of the modified OMIG method are demonstrated by comparison with current state-of-the-art explainability methods on several popular databases. In addition to a qualitative analysis of explainability results, we propose a metric for their quantitative comparison, which evaluates the impact of identified features on the entropy of a prediction.