bluuebunny/crossref_metadata_2025_split huggingface dataset:
Urgency of Strengthening Women Participation in The Building of Gender Justice Based Village
Authors: Budoyo Sapto , Hardiyanti Marzellina 
Published: September 2022

Village building is part of national building which is regulated in Law No. 6 Year 2014 on Village. People participation is necessary in the building of villages, including the participation of women which is still considered very low particularly in generating their aspiration to build villages. Therefore, strengthening women participation in village building is necessary so that policies regarding women issues can be well accommodated in order to realize village building which is based on gender justice. Law research method was appllied in this study using literature approach in order to collect accurate data. The result of this study shows that it is necessary to strengthen women participation in village building which is based on gender justice because it is indicated that political law in Indonesia tends to support the issue corcerning legal protection toward women position as citizens. This is regulated in constitutional foundation in Article 27 section (1), Article 28D section (1), and Article 28I section (2) The 1945 Constitution of The Republic of Indonesia and Article 55 No.6 Year 2014 Law on Village. Women representation in villages aims to solve various issues related to women justice particularly on issues around violence cases which seems like a tip of an iceberg and are unresolved. The efforts to strengthen women participation in village building are built through the form of togetherness, growing from root, trust and openness.
The Fulfillment of Rights to Citizenship for Migrant Worker Deportees in Nunukan District
Authors: Mahfud Muh. Afif , Wibawa Kadek Cahya Susila , ALW Lita Tyesta , Saraswati Retno 
Published: September 2022

Rights to Citizenship must be protected because it is the basis to be able to access the other rights. Rights to citizenship of migrant workers in Nunukan District is potentially expired and lost if they do not renew their passports. The same case may occur with illegal migrant workers who stay for 5 years abroad. This article aims to analyze the potential of stateless person in Nunukan District, the effort made by the government to handle the issue, and the ideal construction of legal protection for stateless person. This study applied socio legal approach using primary and secondary data which were collected through interview, observation, and in depth interview. Those data then were analyzed qualitatively. Based on the analysis, it is concluded that: (1) the potential of being stateless person in Nunukan District occurred in migrant workers whose passports were expired for more than 5 years, irregular migrant workers who stayed abroad for more than five years, the descendants or children of migrant workers who were born and were raised in Malaysia; (2) the government prevents the occurrence of stateless person: (a) integrated management of handling migrant workers; (b) sweeping in order to prevent irregular migrant workers; (c) simplifying the issuance of Letter of Arrival of Indonesian Citizen (SKDWNI) and Letter of Overseas Arrival (SKDLN); (3)ideal construction of the protection of right to citizenship for migrant workers is the extension of the scope of migrant workers protection agreement, and the placement of Citizenship and Civil Record Agency officers in order to make the paperwork handling of citizenship document easier.
Strengthening Rembugan as A Mediation Model in The Resolution of River Water Pollution Disputes (A case study in Purbalingga, Central Java, Indonesia).
Authors: Triana Nita , Mukhtar Naqiyah , Izza Farah Nuril , Turistiati Ade Tuti 
Published: September 2022

Purbalingga as an industrial area is prone to pollution that has a detrimental impact on society and the environment. It is necessary to find a way that can bring together the parties involved to peacefully resolve environmental disputes. The purpose of this study is to strengthen rembugan as a mediation model for resolving pollution disputes in the old industrial area. This research is qualitative research with a socio-legal approach, by conceptualizing law as non-doctrinal. The results showed that rembugan is a community culture in dispute resolution that reflects the values of local wisdom possessed by the Purbalingga community, namely the attitude of the parties to accept and use consensus methods in dispute resolution. The purpose of rembugan is to achieve harmony and togetherness. The mediator is the Environment Agency (DLH) and Village Head (Kepala Desa). Strengthening rembugan position in the dispute resolution model is supported by Purbalingga community culture, whose characters are honest, free, open, egalitarian, and accepting of consensus. Strengthening rembugan as a mediation model is also supported by government institutions such as village heads and Environment Agency, and is formally regulated in Law No. 32 of 2009 concerning environmental protection and management.
The why and how of trustworthy AI
Authors: Schmitz Anna , Akila Maram , Hecker Dirk , Poretschkin Maximilian , Wrobel Stefan 
Published: September 2022

Abstract
Artificial intelligence is increasingly penetrating industrial applications as well as areas that affect our daily lives. As a consequence, there is a need for criteria to validate whether the quality of AI applications is sufficient for their intended use. Both in the academic community and societal debate, an agreement has emerged under the term “trustworthiness” as the set of essential quality requirements that should be placed on an AI application. At the same time, the question of how these quality requirements can be operationalized is to a large extent still open.
In this paper, we consider trustworthy AI from two perspectives: the product and organizational perspective. For the former, we present an AI-specific risk analysis and outline how verifiable arguments for the trustworthiness of an AI application can be developed. For the second perspective, we explore how an AI management system can be employed to assure the trustworthiness of an organization with respect to its handling of AI. Finally, we argue that in order to achieve AI trustworthiness, coordinated measures from both product and organizational perspectives are required.
Cold plasma as a fast acting alternative disinfection method
Authors: Buhl Sebastian , Stich Alexander , Clos Dario , Bulitta Clemens 
Published: September 2022

Abstract
Cold plasma disinfection is a cost-efficient and, above all, fast way of disinfecting even complex products. There are already approaches where plasma disinfection is used for wound treatment or hand disinfection. The ionization of a gas results in a number of physical and chemical processes that have a damaging effect on microorganisms. Especially in the field of medical device reprocessing, a tool that can reliably disinfect even very complex products in a short time would be a great asset. In this work, the potential of a newly developed cold plasma disinfection device was tested for the reduction of microbiological contamination and thus the disinfecting effect. In order to examine this microbiological reduction 3D printed scaffolds with contaminated test plates were used. This was done with different concentrations of the bacteria in the cold plasma disinfection process to determine the maximum germ reduction effect. In a first test run, the maximum effect of germ reduction was achieved with log 3.6. By making further changes and increasing the disinfection cycles, it was possible to increase the germ reduction to log 4.7. If these values are confirmed and can be improved by further modifications (e.g. increasing the plasma concentration), cold plasma technology represents a very good alternative to conventional disinfection methods.
First-cycle oscillation excursions of Pickering-stabilised microbubbles subjected to a high-amplitude ultrasound pulse
Authors: Anderton Nicole , Carlson Craig S. , Matsumoto Ryunosuke , Shimizu Ri-ichiro , Poortinga Albert T. , Kudo Nobuki , Postema Michiel 
Published: September 2022

Abstract
Pickering stabilisation is a manufacturing process involving the adsorption of colloidal particles at gas-liquid interfaces. It is used to create the shells of stable, long-lived ultrasound contrast agent microbubbles. The purpose of the present study is to determine whether high-amplitude sonication influences the integrity of Pickering-stabilised shells. To this purpose, Pickering-stabilised microbubbles were subjected to high-speed photography at 10 million frames per second during 1-MHz, 1-MPa sonication. In addition, radial excursions as a function of time were simulated using the Rayleigh-Plesset equation for free gas microbubbles and microbubbles encapsulated by Pickering-stabilised shells of 7.6-Nm−1 stiffness. The maximum expansions observed from camera recordings were either agreeing with those computed for Pickering-stabilised microbubbles or corresponding to greater values. The results indicate that optically identical microbubbles may undergo shell disruption of different severity. We conclude that the disruption occurs during sonication and not prior to it. These findings may aid in the development of Pickering-stabilised agents that facilitate ultrasoundtriggered release.
Monitoring the gelation of gellan gum with torsion rheometry and brightness-mode ultrasound
Authors: Postema Michiel , Gering Christine , Anderton Nicole , Carlson Craig S. , Kellomäki Minna 
Published: September 2022

Abstract
Gellan gum is a hydrogel with several applications in ultrasonic imaging, novel drug delivery, and tissue regeneration. As hydrogels are dynamic entities, their viscocelastic and therefore their acoustic properties change over time, which is of interest to monitor. To determine the speed of sound from brightness-mode images, however, rather large quantities of hydrogel are needed. In this study, we investigated torsion rheometry as a means to determine acoustic properties. Perceived speeds of sound were derived and computed from torsion rheometry measurements of gelating gellan gum mixed with spermidine trihydrochloride crosslinker. For comparison, brightness-mode ultrasonic images were recorded of the same material inside a phantom well. The rheometry data converged to a speed of sound within a standard devitation of the speed of sound measured from the brightness-mode images.We have shown that dynamic acoustic properties of gelating gellan gum can be simulated and experimentally determined using torsion rheometry.
Feature-based Differentiation of Malignant Melanomas, Lesions and Healthy Skin in Multiphoton Tomography Skin Images
Authors: Lange Irene , Prinke Philipp , Klee Sascha , Piaţek Łukasz , Warzecha Marek , Konig Karsten , Haueisen Jens 
Published: September 2022

Abstract
Malignant melanoma is a very aggressive tumour with the ability to metastasize at an early stage. Therefore, early detection is of great importance. Multiphoton tomography is a new non-invasive examination method in the clinical diagnosis of skin alterations that can be used for such early diagnosis. In this paper, a method for automated evaluation of multiphoton images of the skin is presented. The following features at the cellular and subcellular level were extracted to differentiate between malignant melanomas, lesions, and healthy skin: cell symmetry, cell distance, cell density, cell and nucleus contrast, nucleus cell ratio, and homogeneity of cytoplasm. The extracted features formed the basis for the subsequent classification. Two feature sets were used. The first feature set included all the above-mentioned features, while the second feature set included the significantly different features between the three classes resulting from a multivariate analysis of variance. The classification was performed by a Support Vector Machine, the k-Nearest Neighbour algorithm, and Ensemble Learning. The best classification results were obtained with the Support Vector Machine using the first feature set with an accuracy of 52 % and 79.6 % for malignant melanoma and healthy skin, respectively. Despite the small number of subjects investigated our results indicate that the proposed automatic method can differentiate malignant melanoma, lesions, and healthy skin. For future clinical application, an extended study with more multiphoton images is needed.
An online movement and tremor identification algorithm for evaluation during deep brain stimulation
Authors: Bourgeois Frédéric , Pambakian Nicola , Coste Jérôme , Lange Ijsbrand de , Lemaire Jean-Jacques , Schkommodau Erik , Hemm Simone 
Published: September 2022

Abstract
INTRODUCTION: Deep brain stimulation (DBS) is widely used to alleviate symptoms of movement disorders. During intraoperative stimulation the influence of active or passive movements on the neuronal activity is often evaluated but the evaluation remains mostly subjective. The objective of this paper is to investigate the potential of a previously developed Weighted-frequency Fourier Linear combiner and Kalman filter-based recursive algorithm to identify tremor phases and types. METHODS: Ten accelerometer recordings from eight patients were acquired during DBS from which 186 phases were manually annotated into: rest, postural and kinetic phase without tremor, and rest, postural and kinetic phase with tremor. The method first estimates the instantaneous tremor frequency and then decomposes the motion signal into voluntary and tremorous parts. The tremorous part is used to quantify tremor and the voluntary part to differentiate rest, postural and kinetic phases. RESULTS: Instantaneous tremor frequency and amplitude are successfully tracked online. The overall accuracy for tremorous phases only is 89.1% and 76.3% when also non-tremorous phases are considered. Two main misclassification cases are identified and further discussed. CONCLUSION: The results demonstrate the potential of the developed algorithm as an online tremorous movement classifier. It would benefit from a more advanced tremor detector but nevertheless the obtained digital biomarkers offer an evidence-based analysis and could optimize the efficacy of DBS treatment.
Multiple parallel hidden layers autoencoder for denoising ECG signal
Authors: Samann Fars , Schanze Thomas 
Published: September 2022

Abstract
Deep learning with multiple hidden layers denoising autoencoders (MHL-DAE) is commonly used to denoise images and signals through dimension reduction. Here, we explore the potential of multiple parallel hidden layers denoising autoencoder (MPHL-DAE) to denoise complex bio-signals, like electrocardiogram (ECG). A merge layer, e.g., average layer is considered as the output of the proposed model by combining the outputs of the parallel hidden layers. The parallel hidden layers in the coding layer with activation function of different scale a, e.g., are considered to capture distinct features of the input. The lower/upper number of the required hidden neurons of the coding layer are estimated using data driven approach via singular values decomposition (SVD). The results show that the proposed MPHL-DAE model achieve better/similar SNR improvement compared to MHL-DAE with suitable scale for various noise levels respectively.
Wearable Wake-up System for CCHS Patients
Authors: Mayer Juliane , Junger Philipp , Hokenmaier Lukas , Pott Peter P. 
Published: September 2022

Abstract
Congenital Central Hypoventilation Syndrome (CCHS) leads to insufficient breathing especially during sleep. While patients can be ventilated and monitored during the night, adolescents undergo changes in their biorhythm and lifestyle and are at higher risk to inadvertently fall asleep and stop breathing during the day. In this paper, we propose a prototype mobile wake-up device worn behind both ears that constantly measures oxygen saturation and heart rate noninvasively. If a dangerously low level of saturation is detected, it is assumed that the user fell asleep. To wake them, the device issues an acoustic and haptic alarm. The device settings are accessed via a smartphone app. To evaluate the sensor performance, a subject simultaneously wore the prototype behind his ears and a commercial finger pulse oximeter on his hand. Heart rate and blood oxygen saturation were taken for three measurements of few minutes each. Mean absolute error of oxygen saturation was less than 2 % for two data sets and 6.1 %for the third. It is assumed that during this measurement, the device lost contact to the skin. The heart rate measurement showed satisfactory agreement of < 4 % mean average error. In the future, the measurement quality will be improved by calibration and more reliable attachment to the ear and a user study will be conducted in order to evaluate the prototype usability.
Evaluation of the influence of the nasal cavity in flow simulations of the upper airway of a sleep apnea patient
Authors: Zell Fenja , Ibbeken Alina , Hagen Christina , Steffen Armin , Grzyska Ulrike , Frydrychowicz Alex , Buzug Thorsten M. 
Published: September 2022

Abstract
Computational fluid dynamics can be used to analyze the flow pattern and the anatomical predisposition of the airway collapse in patient-specific simulations of sleep apnea patients. Especially the nasal geometry is a major challenge, because of the complex structures and high calculation effort. Due to this limitations the nasal cavity is often excluded. To investigate the influence of the exclusion of the nasal geometry on the flow in the pharynx, four digital models were created. One, which includes the complete nasal structure, and three simplified models, neglecting the nasal geometry using different cutting planes. Airflow simulations using the k-ε turbulence model are performed with an inlet flow rate of 10 l/min. The results show a good agreement of the average velocities. Deviations of the velocity and pressure values occur particularly in the region of the oropharynx and indicate that the type of simplification has a significant influence on the pressure distribution.
A time-resolved fibrosis model – in vitro assessment of antifibrotic implant coatings
Authors: Khaimov Valeria , Strübing Julia , Stahnke Thomas , Grabow Niels , Schmitz Klaus-Peter , Siewert Stefan 
Published: September 2022

Abstract
Wound healing after implant surgery represents a spontaneous repair process that, when disturbed, can lead to a pathological situation known as fibrosis, characterized by excessive proliferation, increased extracellular matrix deposition, and scarring of the tissue. Tissue-specific cell culture models simulating physiological or pathophysiological cell responses are valuable research tools in the field of fibrosis, among others. In such in vitro systems, endpoint measurements are typically used to assess cell viability and/or proliferation. However, this approach is usually time consuming, costly and often leads to the destruction of the sample. Additionally, these conventional in vitro systems provide only a single snapshot of the respective sample at the end of the experiment. Therefore, we aimed to evolve the fibrotic disease in vitro model established by Stahnke et al. To this end, we chose a time-resolved, non-invasive approach based on cell impedance measurements and bright-field microscopy that allows continuous monitoring of the cells. Such measurements can be directly conducted using the xCELLigence RTCA eSight system. This system was used to characterize the cellular responses of the fibrosarcoma cell line HT-1080 and primary fibroblasts isolated from the Tenon’s capsule of human donors to TGF-β1, a key cytokine involved in the pathogenesis of fibrosis. The data shows that compared to Tenon’s fibroblasts the response of HT-1080 cells to TGF- β1 is less pronounced and only detectable within a narrow time frame. Thus, HT-1080 do not appear to be a suitable cell culture model for the assessment of antifibrotic implant coatings.
Automatic detection of foreign objects and contaminants in colonoscopic video data using deep learning
Authors: Kress Veronika , Wittenberg Thomas , Raithel Martin , Bruns Volker , Lehmann Edgar , Eixelberger Thomas , Hackner Ralf 
Published: September 2022

Abstract
Introduction: In the field of colonoscopy results of automated or supporting procedures using medical image processing are often compromised by contaminants such as blood or stool, but also due to medical instruments. Such objects or contaminations often obscure relevant areas or cause disturbances in various algorithms and also prevent physicians from recognizing relevant information in the video-stream. Hence, automatic detection and segmentation of such contaminations is desirable, by obtaining proper segmentation masks to an algorithm yields the possibility to exclude such areas from analysis. Method: We created a training and validation dataset by collecting (and annotating, where necessary) endoscopic video sequences from various public available datasets and a privat collection. An encoder-decoder deep convolutional neural network was trained with this data to predict segmentation masks for blood, stool, medical instruments and other objects. Results: Depending on the class (blood, stool, ... ), we were able to obtain a mean Dice score in the range between 0.88 to 0.93 on the evaluation dataset. Conclusion: The proposed approach hence allows us providing segmentation masks that are able to reduce problems in the subsequent image analysis and also find regions that were not properly observed.
Annotation Efforts in Image Segmentation can be Reduced by Neural Network Bootstrapping
Authors: Rettenberger Luca , Schilling Marcel , Reischl Markus 
Published: September 2022

Abstract
Modern medical technology offers potential for the automatic generation of datasets that can be fed into deep learning systems. However, even though raw data for supporting diagnostics can be obtained with manageable effort, generating annotations is burdensome and time-consuming. Since annotating images for semantic segmentation is particularly exhausting, methods to reduce the human effort are especially valuable. We propose a combined framework that utilizes unsupervised machine learning to automatically generate segmentation masks. Experiments on two biomedical datasets show that our approach generates noticeably better annotations than Otsu thresholding and k-means clustering without needing any additional manual effort. Using our framework, unannotated datasets can be amended with pre-annotations fully unsupervised thus reducing the human effort to a minimum.
Home rehabilitation system for the upper extremity focusing on technology-aided assessment of spasticity
Authors: Panny Matthias , Nagiller Ines , Nagiller Marco , Kim Yeongmi 
Published: September 2022

Abstract
This paper presents a robotic wrist rehabilitation device that facilitates both pronation/supination and flexion/ extension movements. Further, it provides technologyaided assessment capabilities through measurement of joint stiffness, range of motion (ROM) and detection of the catch that is often associated with spasticity. The mechanical and electrical system design, allowing for aforementioned training and assessment capabilities, is presented. An indirect torque measurement via the actuator currents is proposed, which can determine the angle of catch, and compared to the already established methods of using inertial measurement units. The approach is tested using a simplified, mechanical model of the joint catch on the presented device. The results show that the indirect measurement has similar performance of assessing the angle of catch as the inertial data. Therefore, the presented device shows a potential to assess not only stiffness but also the angle of catch without additional sensors.