bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tumor-skin invasion is a reliable risk factor for poor prognosis in superficial soft tissue sarcomas
Authors: Iwai Tadashi , Hoshi Manabu , Oebisu Naoto , Takada Naoki , Ban Yoshitaka , Nakamura Hiroaki 
Published: September 2022

IntroductionSuperficial soft tissue sarcomas are often left untreated unless they invade the skin and skin ulcers manifest. Progressive sarcomas frequently result in dismal oncological outcomes despite multidisciplinary treatment. This study aimed to identify prognostic factors for superficial soft tissue sarcomas.Materials and methodsThis study retrospectively analyzed the clinicopathological data of 82 patients with superficial soft tissue sarcomas treated between August 2003 and December 2020 at our institution. A superficial soft tissue sarcoma was defined if the percentage of the area occupied by the tumor in the assessed region (skin, subcutaneous) was more than 50%. Age, sex, location, tumor size, tumor-skin invasion, tumor grade, and distant metastasis at initial diagnosis were evaluated as potential prognostic factors. Cox proportional hazards regression models were used to identify the prognostic factors. Five-year survival rates were assessed by the Kaplan-Meier method.ResultsThe mean follow-up time was 60.1 months. The 5-year overall survival, 5-year local recurrence-free survival, and 5-year metastasis survival rates were 76.4%, 60.6%, and 71.0%, respectively. Univariate analysis showed significant relationships between poor prognosis and tumor size ≥5 cm, distant metastasis at initial diagnosis, and tumor-skin invasion. In the multivariate analysis, only the tumor-skin invasion was associated with worse overall survival.ConclusionsSuperficial soft tissue sarcomas have biologically been considered a separate category due to their better prognosis. In this study, the tumor-skin invasion was the only significant factor associated with a poor prognosis. Therefore, all superficial soft tissue sarcomas without tumor-skin invasion should be treated as early as possible.
Better insights into wood-based panel production
Authors: Bär Jan , Ramesh Santhosh Balaji , Schleissinger Florian , Woll Jürgen 
Published: September 2022

Abstract
Dieffenbacher has developed a completely new software platform for the digitalization of wood-based panel production plants. The name of the Platform is EVORIS. This article explains how smart data processing in production, with the help of artificial intelligence and machine learning, delivers transparency to production processes and helps operators and technologists to produce smarter. Furthermore, experiences in working methods, the development process, AI engineering and, above all, lessons learnt from theory vs. practice are illustrated.
3D printed microfluidic modules: passive mixers and cells encapsulation in alginate
Authors: Dalcanale Federico , Caj Michaela , Schuler Felix , Ganeshanathan Kireedan , Suter-Dick Laura 
Published: September 2022

Abstract
passive mixers and droplet generation microfluidic chip modules were designed and manufactured using a commercial SLA 3D-printer. The mixing modules were designed specifically for 3D-printing and evaluated using FEM modeling. The co-flow droplet generator was used for cancer cells encapsulation and drug potency evaluation.
Micro-computed tomography and brightness-mode ultrasound show air entrapments inside tablets
Authors: Carlson Craig S. , Hannula Markus , Postema Michiel 
Published: September 2022

Abstract
Controlled disintegration of pharmaceutical tablets has been of interest for consistency checks and drug delivery. Under sonication, tablet disintegration is accelerated. This acceleration has been attributed to the existence of microscopic air pockets inside compacted tablets. In this study, we investigated the existence of such pockets by subjecting tablets to micro-computed tomography. In addition, we subjected tablets from the same batch to sonography. The tablets were measured to have an ultrasonic swelling rate of 162±16 μms−1. The micro-computed tomography images showed air pockets of up to 9 μm in diameter, some of which were visibly connected to each other. The brightness-mode images showed scattering from inside the tablets, suggesting cavitation activity. We conclude that, inside the tablets investigated, microscopic air entrapments exist, whose pulsations are detectable with brightness-mode ultrasound.
Steerable Flexible Laparoscope to Facilitate Camera Guidance During Minimally Invasive Procedures
Authors: Schäfer Max B. , Waltner Madeleine , Giacoppo Giuliano A. , Pott Peter P. 
Published: September 2022

Abstract
In conventional laparoscopy, the field of view of the surgeon is limited. Angled laparoscopes enable the observation of surrounding structures, however, to change the viewing perspective on a specific object, permanent repositioning and rotation of the shaft is required. In this paper, a demonstrator of a steerable flexible laparoscope is presented, enabling the user to intuitively adjust the perspective onto an object by means of a single control element. The laparoscope provides a viewing angle of ± 50° at 50 mm working distance. In first tests, the presented laparoscope showed advantages regarding intuitiveness of the control, easier handling, and improved depth perception.
On the use of singular value decomposition for QRS detection and ECG denoising
Authors: Schanze Thomas 
Published: September 2022

Abstract
QRS detection is a pre-processing step to detect the heartbeat in an electrocardiogram (ECG) for subsequent rhythm classification. However, measured ECG waveforms may differ as a result of intrinsic variability or due to artefacts or noise. If the signals are distorted, then this often leads to difficulties in QRS detection. Of course, a high QRS detection performance is an important part of an ECG analysis algorithm, and furthermore, it must work even for highly noisy signals. Singular value decompositon (SVD) is the factorization of a matrix into the product three matrices. SVD allows us to find important components of data and, thus, can be used for dimension reduction or denoising. We introduce SVD based methods for QRS detection and ECG denoising, especially for short unknown signal segments, and show application results.
Acquisition and Processing of Biomedical Data for Outpatient Care in Rural Areas
Authors: Keil Alexander , Hahn Kai , Brombach Nick , Brück Rainer , Farhan Nabeel , Gaus Olaf 
Published: September 2022

Abstract
Acquisition of medical data such as blood pressure, ECG, pulse, and other values is currently often carried out in doctor’s offices by physicians or medical staff. This requires valuable time of patients as well as of practices’ personel and can deliver specific data only of the time of the visit. In this paper we describe a different approach. Patients measure their biomedical vital data at home. Therefore a technical infrastructure together with a workflow were developed and applied within a current project with patients in a rural area. Vital data is transferred via smartphone apps to a cloud environment where doctors can easily access and assess the data.
A Large-scale Virtual Patient Cohort to Study ECG Features of Interatrial Conduction Block
Authors: Bender Jule , Nagel Claudia , Fröhlich Jonathan , Wieners Christian , Dössel Olaf , Loewe Axel 
Published: September 2022

Abstract
Interatrial conduction block refers to a disturbance in the propagation of electrical impulses in the conduction pathways between the right and the left atrium. It is a risk factor for atrial fibrillation, stroke, and premature death. Clinical diagnostic criteria comprise an increased P wave duration and biphasic P waves in lead II, III and aVF due to retrograde activation of the left atrium. Machine learning algorithms could improve the diagnosis but require a large-scale, well-controlled and balanced dataset. In silico electrocardiogram (ECG) signals, optimally obtained from a statistical shape model to cover anatomical variability, carry the potential to produce an extensive database meeting the requirements for successful machine learning application. We generated the first in silico dataset including interatrial conduction block of 9,800 simulated ECG signals based on a bi-atrial statistical shape model. Automated feature analysis was performed to evaluate P wave morphology, duration and P wave terminal force in lead V1. Increased P wave duration and P wave terminal force in lead V1 were found for models with interatrial conduction block compared to healthy models. A wide variability of P wave morphology was detected for models with interatrial conduction block. Contrary to previous assumptions, our results suggest that a biphasic P wave morphology seems to be neither necessary nor sufficient for the diagnosis of interatrial conduction block. The presented dataset is ready for a classification with machine learning algorithms and can be easily extended.
Development of an AI-supported exercise therapy for advanced cancer patients
Authors: Wichum Felix , De Lazzari Nico , Götte Miriam , David Corinna , Wiede Christian , Seidl Karsten , Tewes Mitra 
Published: September 2022

Abstract
Exercise therapy is able to reduce symptom burden in advanced cancer patients (ACP). However, ACP daily form differs between days e.g. tumor and therapy induced. We included five ACP to classify individual exercise capacity due to cardiovascular parameters. Features are extracted from the electrocardiogram and then processed with a neural network after feature selection. Results indicate a high classification quality with an F1 score up to 0.95 ± 0.05. Including neuronal networks for training control can potentially help to manage exercise intensity ideal.
Continuous error processing during a closed-loop 2D tracking task
Authors: Pulferer Hannah S. , Müller-Putz Gernot R. 
Published: September 2022

Abstract
The usefulness of error-related potentials (ErrPs) for control in non-invasive Brain-Computer interface (BCI) research has been established over the last decades. To continuously correct for erroneous action of an end effector (e.g., robot arm) in a BCI however, these neural correlates relating only to the discrete perception of errors remain problematic. Using a pre-recorded dataset offering feedback in a 2D tracking task in different correct or erroneous conditions, we analyzed whether error processing during continuous feedback can be observed from the electroencephalogram (EEG). Within this dataset comprising 30 sessions of recordings, we were able to detect significant differences between correct and erroneous conditions. Furthermore, minimal significant difference between two erroneous conditions is reported, confirming the direct connection between error and cognitive response.
Explaining and Evaluating Deep Tissue Classification by Visualizing Activations of Most Relevant Intermediate Layers
Authors: Mohammed Aliya , Geppert Carol , Hartmann Arnd , Kuritcyn Petr , Bruns Volker , Schmid Ute , Wittenberg Thomas , Benz Michaela , Finzel Bettina 
Published: September 2022

Abstract
Deep Learning-based tissue classification may support pathologists in analyzing digitized whole slide images. However, in such critical tasks, only approaches that can be validated by medical experts in advance to deployment, are suitable. We present an approach that contributes to making automated tissue classification more transparent. We step beyond broadly used visualizations for last layers of a convolutional neural network by identifying most relevant intermediate layers applying Grad-CAM. A visual evaluation by a pathologist shows that these layers assign relevance, where important morphological structures are present in case of correct class decisions. We introduce a tool that can be easily used by medical experts for such validation purposes for any convolutional neural network and any layer. Visual explanations for intermediate layers provide insights into a neural network’s decision for histopathological tissue classification. In future research also the context of the input data must be considered.
Development of a pain journal for chronic pain management and remote monitoring
Authors: Le Van Hoang , Zeiner Klaus , Kampusch Stefan 
Published: September 2022

Abstract
Chronic pain is a global health problem, having a tremendous effect on the quality-of-life (QoL) of patients. Monitoring the outcome of a specific therapy and the condition of the patient is of utter importance for effective pain management. A smartphone application was developed for comprehensive pain management in chronic pain patients. It allows patients to enter and keep track of their health related QoL, pain, and medication intake in an easy, fast, and regular daily routine. The app was built based on standardized questionnaires and the needs of pain specialists and patients assessed via a brief survey in a small target group. The survey showed an unmet need for applications in clinical practice, which enable comprehensive monitoring of QoL, pain, therapeutic progress, and thus allow for patient engagement and overall improved pain management. Beneficially, patients can share their reported outcome measures gathered via the app with their pain specialist via PDF exports for remote monitoring. The smartphone app has been realized and is currently evaluated in beta tests. The easy, comprehensible, and routine assessment of the patient’s condition, combined with a future integration into an online therapy management system, may further advance pain management in chronic pain patients.
Using a single inertial sensor to control exergames for children with cerebral palsy
Authors: Mittag Christina , Waldheim Vivian , Krause Axel , Seel Thomas 
Published: September 2022

Abstract
Introduction: Children with cerebral palsy (CCP) benefit from intensive arm training. Exergames that can be played at home offer the possibility to increase the frequency of therapy but require reliable and accurate real-time motion tracking via easy-to-use sensors in unsupervised settings and magnetically disturbed environments. Method: We propose an inertial-sensor-based method with a single sensor on the wrist for real-time tracking of the inclination of the forearm. The control parameter of the game was validated with an optical marker-based ground truth system. Results: First experiments with a therapist performing training movements in a healthy and simulated spastic manner show that the forearm inclination well captures the motion dynamics. The accuracy of the inertial-sensor-based measurement is validated with respect to the reference system in three healthy subjects. Orientation offsets between the inertial sensor and the forearm marker set in the range of 2° ̶ 6° and dynamic measurement errors about 3.1° were obtained. Conclusion: This work demonstrates that the proposed method is suitable for real-time control of exergames of CCP. The validation with an optical reference system showed that the forearm inclination can be used as for feedback and therapeutic progress monitoring.
Analysis on the effect of eye globe diameters on the biomechanics of posterior ocular tissues during horizontal adduction
Authors: Goyal Arsh , Kumar Bajpai Saumendra , Swaminathan Ramakrishnan 
Published: September 2022

Abstract
In this work, an attempt has been made to analyze the influence of pathological changes in eye globe dimensions towards the mechanical responses of optic nerve head tissues during eye adductions. For this study, a 3D baseline model geometry of posterior ocular tissues has been constructed. The eye globe diameters of the model are modified to mimic the changes in ocular globe morphology in control, glaucoma, myopia and glaucoma with myopia conditions. Adductions are simulated for each modified model as the rotation of the globe from 1o to 10o in steps of 1o. von Mises strain in lamina cribrosa (LC) and posterior displacement of LC are estimated. Results show that strains developed in LC and its posterior displacement are higher in diseased eyes compared to healthy eyes. It appears that eyes with higher axial length and globe anisotropy are more susceptible to optic nerve head damage. This study might be extended to assess the progression of glaucomatous optic neuropathy.
Ultrasound-Mediated Cavitation of Magnetic Nanoparticles for Drug Delivery Applications
Authors: Huber Christian , George Benedikt , Rupitsch Stefan J. , Ermert Helmut , Ullmann Ingrid , Vossiek Martin , Lyer Stefan 
Published: September 2022

Abstract
Magnetic nanoparticles guided by an external magnetic field can be used to deliver drugs (e.g., chemotherapeutics) to malignant regions (e.g., tumor tissue). Some nonmagnetic, sonosensitive nanoparticles are known to generate cavitation induced by focused ultrasound. This can can be used to monitor spatial/temporal particle distribution and to stimulate local drug release in target regions. Little to nothing is known about the sonosensitivity of magnetic nanoparticles. Therefore, we investigated this physical phenomenon in the present contribution. We showed that certain magnetic nanoparticles have high cavitation potential and are promising for further research in this regard.
Bone ablation using a Ho:YAG laser
Authors: Cetin Cigdem , Drusová Sandra , Hamidi Arsham , Rauter Georg , Cattin Philippe , Zam Azhar , Canbaz Ferda 
Published: September 2022

Abstract
This study aimed to optimize the ablation depth and duration at a fixed energy using a Ho:YAG laser, considering fiber delivery applications. According to the measurements performed with an optical coherence tomography system, we obtained depths of about 1.4 mm with 500 mJ/pulse applied energy when moving the laser along a 1 cm line for 60 s (corresponding to ~50 pulses per position). Coupling this laser into a flexible fiber (θ= 250 μm) will be the next step for future minimal-invasive bone ablation trials. Furthermore, deeper ablation (~1.5 mm) was also achieved with different energy levels on bone samples.
Tiffeneau-Testing by means of a Smart-Shirt
Authors: Laufer Bernhard , Docherty Paul D. , Jalal Nour Aldeen , Krueger-Ziolek Sabine , Hoeflinger Fabian , Reindl Leonhard , Moeller Knut 
Published: September 2022

Abstract
Tiffeneau manoeuvres are an important method in pulmonary function testing of the human lungs and can help to diagnose respiratory obstructions. Data from a motion capture system and a spirometer was used to evaluate Tiffeneau indexes which can theoretically be derived via a Smart-Shirt that incorporates three circumference measurements of the upper body. The mean error was 4.5% regarding the Tiffeneau indexes gained by the spirometer, indicating that clinical diagnosis of obstruction is potentially possible using a Smart-Shirt.
Initial engagement and axial force model for self-tapping bone screws
Authors: Wilkie Jack , Rauter Georg , Möller Knut 
Published: September 2022

Abstract
Correctly torquing bone screws is important for implant fixation longevity and strength. A model-based smart screwdriver has been proposed to regulate torque, however current models ignore axial force and the initial engagement of the screw. This was addressed here by deriving a model based on the concept of a net axial force generated by a difference in contact areas on the inward and outward sides of the screw threads. This force is opposed by the shear strength of the material around the threads. The results of the derivation were able to predict the effects of different axial forces during insertion in relation to the hole material strength. The results may be used to compensate for initial thread breakage in future model-based smart screwdrivers to improve their accuracy.
Determination of free heme in stored red blood cells with an apo-horseradish peroxidase-based assay
Authors: Vijayan Vijith , Greite Robert , Schott Sebastian , Doricic Julian , Madyaningrana Kukuh , Pradhan Pooja , Martens Jörg , Blasczyk Rainer , Janciauskiene Sabina , Immenschuh Stephan 
Published: September 2022

Abstract
Transfusion effectiveness of red blood cells (RBCs) has been associated with duration of the storage period. Storage-dependent RBC alterations lead to hemolysis and release of toxic free heme, but the increase of free heme levels over time is largely unknown. In the current study, an apo-horseradish peroxidase (apoHRP)-based assay was applied to measure levels of free heme at regular intervals or periodically in supernatants of RBCs until a maximum storage period of 42 days. Free heme levels increased with linear time-dependent kinetics up to day 21 and accelerated disproportionally after day 28 until day 42, as determined with the apoHRP assay. Individual time courses of free heme in different RBC units exhibited high variability. Notably, levels of free hemoglobin, an established indicator of RBC damage, and those of total heme increased with continuous time-dependent linear kinetics over the entire 42 day storage period, respectively. Supernatants from RBC units with high levels of free heme led to inflammatory activation of human neutrophils. In conclusion, determining free heme in stored RBCs with the applied apoHRP assay may become feasible for testing of RBC storage quality in clinical transfusion medicine.
Reflections on Lao Sze-Kwang and His Double-Structured “Intra-Cultural” Philosophy of Culture
Authors: Ames Roger T. 
Published: September 2022

AbstractIn his own time, Lao Sze-Kwang formulated his own intra-cultural approach to the philosophy of culture that begins from the interdependence and organic nature of our cultural experience. In this article, I will address three questions: Why did Lao abandon his early reliance on the Hegelian model of philosophy of culture and formulate his own “two-structured” theory? Again, given Lao’s profound commitment and contribution to Chinese philosophy and its future directions, why is it not proper to describe him as a “Chinese philosopher”? And why is the much accomplished Lao Sze-Kwang not installed in the Chinese University of Hong Kong pantheon as yet one more of the great “New Confucian” philosophers that are associated with this institution?
Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration Tool
Authors: Oliveira Alexandre , Cunha Emanuel , Cruz Fernando , Capela João , Sequeira João C. , Sampaio Marta , Sampaio Cláudia , Dias Oscar 
Published: September 2022

Abstract
Genome-scale metabolic models (GEMs) are essential tools for in silico phenotype prediction and strain optimisation. The most straightforward GEMs reconstruction approach uses published models as templates to generate the initial draft, requiring further curation. Such an approach is used by BiGG Integration Tool (BIT), available for merlin users. This tool uses models from BiGG Models database as templates for the draft models. Moreover, BIT allows the selection between different template combinations. The main objective of this study is to assess the draft models generated using this tool and compare them BIT, comparing these to CarveMe models, both of which use the BiGG database, and curated models. For this, three organisms were selected, namely Streptococcus thermophilus, Xylella fastidiosa and Mycobacterium tuberculosis. The models’ variability was assessed using reactions and genes’ metabolic functions. This study concluded that models generated with BIT for each organism were differentiated, despite sharing a significant portion of metabolic functions. Furthermore, the template seems to influence the content of the models, though to a lower extent. When comparing each draft with curated models, BIT had better performances than CarveMe in all metrics. Hence, BIT can be considered a fast and reliable alternative for draft reconstruction for bacteria models.