bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ag sputter coating of PLLA nonwovens
Authors: Teske Michael , Illner Sabine , Tautorat Carsten , Lebahn Kerstin , Schmidt Wolfram , Senz Volkmar , Grabow Niels 
Published: September 2023

Abstract
Physical vapor deposition (PVD) sputtering is a promising technique for the generation of electrically conductive coatings on complex structured biomaterials, such as nonwovens, that can be used in implants. The ultra-thin coatings can fulfil a variety of purposes, such as drug depot or biosensor. The aim of our studies was to determine the feasibility of generating thin silver (Ag) coatings on complex structured poly-L-lactide (PLLA) nonwovens by sputtering and their morphological characterization. PVD sputter process was performed using a customized plasma chamber and a complex rotation of the tender electrospun PLLA nonwovens. Morphological analysis revealed a promising homogenous Ag coating, representing the structure of the nonwovens.
Enhancement and labelling of OCT images
Authors: Karthik Karri , Mahadevappa Manjunatha 
Published: September 2023

Abstract
Optical Coherence Tomography (OCT) is a noninvasive technique for visualizing retinal cross-sections, assisting in diagnosing and monitoring retinal diseases. This study presents an effective OCT image noise reduction and segmentation method. Due to the high resolution of our primary image database, a visual comparison of filter performance was challenging. To address this, we utilized a high-noise image dataset from Duke University, enabling a better evaluation of noise reduction filters. Our method was compared against eight widely-used image filters, including Gaussian, Low pass,Wavelet domain filtering, Lee filter, Anisotropic diffusion, Bilateral filter, Total variational filter, and BM3D filter. Both visual and quantitative analyses were conducted using no-reference performance parameters, namely Gradient Magnitude Similarity Deviation (GMSD), Standard Deviation of Wavelet Coefficients (SDWC), Focus Measure with Tengrade Variance (FMTV), Perception-based Image Quality Evaluator (PIQE), and Visual Information Fidelity (VIF). The results demonstrated the superiority of our proposed filter in terms of noise reduction performance while maintaining the sharpness of retinal layers. Quantitative analysis revealed notable performance gains, including improvements of 63.27% to 83.24% with GMSD, consistent edge strength enhancement of 9.4% to 9.97% using SDWC, gains in image quality between 51.99% and 54.64% with FMTV, performance improvements ranging from 7.25% to 23.97% in terms of PIQE, and a substantial increase in performance varying from 16.31% to 27.69% when assessing the impact on retinal layer quality using VIF. Using the Kruskal-Wallis test, our proposed noise reduction method shows statistical significance for all quantitative parameters. Additionally, our clustering algorithm effectively separated the foreground, including retinal layers and vitreous detachment, from the background and identified an area representing the region between retinal layers where fluid accumulates. We’ve successfully achieved OCT image enhancement, along with distinct foreground and background segmentation.
Investigation of manufacturing deviations of CPC scaffolds for improving the design process
Authors: Seidler Alexander , Pendzik Martin , Hilbig Arthur , Sembdner Philipp , Holtzhausen Stefan , Paetzold-Byhain Kristin 
Published: September 2023

Abstract
In current implantology, calcium phosphate cement (CPC) is increasingly used. A special focus is given to CPC scaffolds, as they are suitable for cell settlement and growth due to their positive osteoconductive properties. The design of the scaffolds is of decisive importance for this. The value ranges of the geometric parameters of these scaffolds (e.g. path distance, path diameter), which are positive for both cell settlement and cell growth, are very small. Manufacturing deviations therefore have a significant impact on cell settlement and growth. The pasty manufacturing consistency can cause sagging at the path interstices of a layer immediately below, resulting in significant manufacturing deviations. A larger path distance and thus a larger path interstitial space promotes cell settlement, but at the same time increases the risk of CPC path shape inconsistency. This in turn can have a negative effect on cell settlement. Therefore, the aim of this paper is to investigate the discrepancies between the nominal and actual state at a path distance favourable to cell settlement on the basis of manufactured CPC scaffolds. In this context, geometric and manufacturing parameters of the shape deviation are to be identified and constructive design adaptations are to be derived on the basis of these. In addition, the effects of the shape and position deviations on the flow behaviour will be investigated.
Method for fabrication of laser-induced periodic surface structures on vascular stents
Authors: Grossmann Swen , Bohne Eric , Stiehm Michael , Schmitz Klaus-Peter , Siewert Stefan 
Published: September 2023

Abstract
Laser-induced periodic surface structures (LIPSS) provide the possibility to functionalize the surface of various materials, which can be used to control the wettability of metal surfaces or influence cell adhesion. LIPSS thus offer great potential for application on implant surfaces if their fabrication process is compatible with standard implant fabrication techniques. Here we demonstrate an easy-to-use two-step fabrication method for stents with different types of LIPSS. The separation between the fabrication of the stent structure and the surface structuring process allows the implementation of any stent structure finishing technique without affecting the LIPSS. The suggested fabrication method may be a step further in implementing laser machining-based surface functionalization in commercial implants.
Design of a Flexible mechatronic system for mechanical impedance measurement of the wrist as one step towards robotic rehabilitation
Authors: Tortorici Ornella , Abbasimoshaei Alireza , Schilling Arndt F. , Kern Thorsten A. 
Published: September 2023

Abstract
Home rehabilitation is a great complement to inpatient rehabilitation, because it allows for more regular training, especially in rural areas, where the access to physiotherapists is limited. However, unsupervised training carries the risk of deviation from the prescribed protocol. An obvious solution is to introduce a technical means for rehabilitation and continuous monitoring of performance. This paper presents a robotic system for rehabilitation of three degrees of freedom of the wrist independently, implemented with only one actuator, optimizing the design and size of the system. The device provides measurements of joint torque-position dependence, allowing objective assessment of mechanical impedance and range of motion to evaluate the progress of rehabilitation. Derived from research on haptic devices, a measurement method was implemented to measure hand impedance in the high frequency range between 100 and 200 Hz using a combination of exciters and accelerometers in the handles. This allows continuous monitoring of gripping forces without the need for complex contact-based force sensors. In collaboration between the authors’ technical and medical universities, a set of two-level passive and active safety measures was implemented to ensure the safety of the system’s users. Therefore, the presented system shows the potential to evaluate the mechanical impedance of the wrist at both low and high frequencies and to monitor the progress during rehabilitation. In the next step, a baseline of wrist impedance will be measured in a target group of healthy volunteers in order to prepare for studies in motion-restricted subjects.
AUC margin loss for limited, imbalanced and noisy medical image diagnosis – a case study on CheXpert5000
Authors: Ihler Sontje , Kuhnke Felix 
Published: September 2023

Abstract
The AUC margin loss is a valuable loss function for medical image classification as it addresses the problems of imbalanced and noisy labels. It is used by the current winner of the CheXpert competition. The CheXpert dataset is a large dataset (200k+ images), however datasets in the range of 1k-10k medical datasets are much more common. This raises the question if optimizing AUC margin loss also is effective in scenarios with limited data.We compare AUC margin loss optimization to binary cross-entropy on limited, imbalanced and noisy CheXpert5000, a subset of CheXpert dataset. We show that AUC margin loss is beneficial for limited data and considerably improves accuracy in the presence of label noise. It also improves out-of-box calibration.
3D-printed scaffolds with perfusable channels for low-cost large construct 3D cell culture
Authors: Kreuels Klaus , Schemmer Carina , Flesch Maximilian Frederick , Gillner Arnold 
Published: September 2023

Abstract
This study presents a novel approach for threedimensional (3D) cell culture using a two-component system consisting of a 3D-printed scaffold structure combined with a perfusion channel. A polymeric scaffold structure with an overall size of 9 mm x 9 mm x 1 mm composed of a cubic lattice with a web thickness of 200 μm and pore size of 600 μm was 3D-printed using a hot UV-stereolithography (SLA) system. The perfusion channel with an inner diameter of 800 μm and channel wall pores of 300 μm for cell culture medium supply was 3D-printed with the same system and material. Scaffolds were investigated with respect to the printing accuracy by digital microscopy. Cytotoxicity of the materials was assessed using MTT-assay and Live/Dead staining. Scaffold were subsequently seeded with 3T3- fibroblasts within a fibrin-based hydrogel and then conditioned either statically or under passive perfusion using a hydrostatic pressure driven flow system. The results show that the scaffold structure and perfusion channel can be produced with high accuracy and stability allowing a supply of nutrient and oxygen via perfusion channel to the cells within the scaffold. This approach has potential for nutrient supply within larger constructs for tissue engineering and regenerative medicine applications.
Comparing Pertubagens from Differential Gene Expression Data Analysis of ASD using Random Forest and Statistical Test
Authors: Sudharshan Ranga , Sinha Kshitij , Pragya  , Manohari Balachander Gowri , Agastinose Ronickom Jac Fredo 
Published: September 2023

Abstract
Differentially Expressed Genes (DEGs) are treated as candidate biomarkers, and a small set of DEGs might be identified as biomarkers using either biological knowledge or data-driven approaches like machine learning and statistical analysis. In this study, we used a combination of the machine learning algorithm and statistical tests to identify the top 300 genes that are differentially expressed in ASD compared to Typically Developed (TD). Initially, we extracted microarray gene expression data of 15 ASD and 15 TD from NCBI GEO database and used a standard pipeline to preprocess the data. Further, Random Forest (RF) was used to discriminate genes between ASD and TD. We, then analyzed the upregulated and downregulated genes using the logFC value to gain insights into their potential roles in the development of ASD. We further used drug-gene interaction analysis from ConnectivityMap to identify drugs that can inhibit the expression of these genes. Our results show that the proposed RF model yields average 5-fold cross-validation accuracy, sensitivity, and specificity of 96.67%. Further, we obtained precision and F-measure scores of 97.5% and 96.57%, respectively. Our analysis identified several novel genes that are dysregulated in ASD, including genes (such as proliferation-inducing protein 38 and germinal centre expressed transcript 32) involved in synaptic transmission, neural development, and immune function. We also identified several drugs (such as ATPase_Inhibitor, kinase inhibitors, and histone deacetylase inhibitors) that can potentially be used to treat ASD. Our findings provide new insights into the molecular mechanisms of ASD and suggest potential targets for drug development. These findings may lead to new therapeutic approaches for the treatment of ASD.
Deep Learning Based Quality Prediction of Retinal Fundus Images
Authors: Bolla Mounika , Biswas Sria , Palanisamy Rohini 
Published: September 2023

Abstract
The accuracy of diagnosing and monitoring eye diseases using fundus imaging is strongly dependent on the quality of the images. Poor image quality can result in delays or inaccuracies in diagnosis, thus risking patient health. Image quality assessment (IQA) is crucial for regulating retinal imaging quality and assisting in successful diagnoses. In this paper, a learning-based model for evaluating the quality of fundus images is proposed. The EyeQ dataset is selected due to its ease of availability and large collection of images. The images in the dataset are classified into three labels based on their perceptual quality. Label 0 denotes good, 1 denotes fair and 2 denotes poor quality. The ResNet50 deep learning model is fine-tuned with different hyperparameters to develop two models, which are labelled as network-1 and network-2. Network-1 uses the Stochastic Gradient Descent (SGD) optimizer and network-2 utilizes the Adam optimizer. Both networks utilise the Categorical Cross Entropy (CCE) loss function, are trained for 40 epochs and has a learning rate of 1e-3. The performance of the trained models is compared using the accuracy validation curve and the loss validation curve. Network-1 demonstrates an accuracy value of 85.8% with a loss of 0.37 and network-2 achieves an accuracy of 86.2% with a loss of 0.34. The results indicate that network-2 slightly outperforms the performance of the other in terms of accuracy, and should be preferred. Moreover, it is evident that the ResNet50 model is highly adept in appropriate feature extraction and quality evaluation of retinal fundus imaging.
Diagnostics of Multi Drug Resistant Tuberculosis in Chest Radiographs using Local Textures & Extreme Gradient Boosting
Authors: Govindarajan Satyavratan , Manuskandan S. R. , Swaminathan Ramakrishnan 
Published: September 2023

Abstract
This study attempts to detect and differentiate Multi Drug Resistant (MDR) - Tuberculosis (TB) and Drug Sensitive (DS)-TB Chest Radiographs (CXR) using local texture descriptors and Ensemble Learning method. Studies report that CXR images contain likelihood information of the drug resistance which can be utilized computationally. Initially, CXR images are subjected to lung fields segmentation using Reaction Diffusion Level Set method. Further, Local Directional Texture Pattern (LDTP) features are extracted from the segmented lungs to characterize the localized textural variations. Extreme Gradient Boosting (XGBoost) classifier is employed to differentiate DS-TB and MDR-TB images. The obtained results demonstrate the ability of extracted LDTP features to characterize nonspecific textural inhomogeneities in images by operating on its principal directions. XGBoost algorithm provides maximum accuracy of 93% and true positive rate of 94.6% in detecting MDR-TB. As the proposed study differentiates the MDR-TB condition using CXR images, its computerized diagnostics could be used in the early screening and followup of TB ridden patients for public health infection control in any setting.
Double-layer optimal energy management of smart grid incorporating P2P energy trading with smart traction system
Authors: El-Zonkoly Amany 
Published: September 2023

Abstract
Moving towards clean and sustainable transportation system, electrification of railway systems along with the use of electric vehicles (EVs) are of great interest. For economic operation of such systems, the peer-to-peer (P2P) energy trading policy became more applicable. Therefore, this paper proposes a double-layer individual-based optimization algorithm for P2P based optimal energy management (EM) of a smart distribution network incorporating flexible smart railway substation taking into consideration multiple energy sources of the traction system and the wayside distribution network with the integration of both EVs and energy hubs (EHs). For efficient operation of the railway substation, captured regenerative braking energy (RBE) are considered. In addition, photovoltaic (PV) units are used on station’s and platforms’ roof-tops for clean energy generation along with a multistory parking garage of electric vehicles (EVs). The wayside distribution network of district distribution area with flexible loads also contains several energy sources including distributed generation and multiple EHs. Optimal energy management is carried out including optimal demand side management of flexible loads and EHs. The optimization study takes into consideration several operational uncertainties arising from several components of the system. The simulation results show the feasibility of applying the proposed EM algorithm with an improvement of the energy economics of the system. The results show a reduction of 6.5 % in energy cost of the distribution network loads, 48 % in net energy cost of EHs, 70.8 % in net energy cost of EVs, and 59.1 % in the cost of energy bought by the traction substation.
Scopoletin a potential phytochemical therapy for antitubercular treatment drug induced liver injury (ATT-DILI) model in Wistar rats
Authors: Sharma Swati , Sharma Vishal , Taneja Sunil , Alka bhatia  , Anand Aishwarya , Patil Amol N. , Banerjee Dibyajyoti 
Published: September 2023

Abstract

Objectives
The hepatoprotective properties of scopoletin have been explored in carbon tetrachloride (CCl4) induced liver injury but not in drug-induced liver injury (DILI) scenarios. Only N-acetyl-cysteine (NAC) has proven efficacy in DILI treatment. Accordingly, we conducted a study to assess the hepatoprotective action of scopoletin in the anti-tubercular treatment (ATT)-DILI model in Wistar rats, if any.

Methods
A total of 36 rats were evaluated, with six in each group. A 36-day ATT at 100 mg/kg dose for isoniazid, 300 mg/kg for rifampicin and 700 mg/kg for pyrazinamide were fed to induce hepatotoxicity in rats. Group I and II–VI received normal saline and ATT, respectively. Oral scopoletin (1,5 and 10 mg/kg) and NAC 150 mg/kg were administered in groups III, IV, V and VI, respectively, once daily for the last 15 days of the experiment. LFT monitoring was performed at baseline, days 21, 28, and 36. Rats were sacrificed for the histopathology examination.

Results
Aspartate transaminase (AST), alanine transaminase (ALT), alkaline phosphatase (ALP) and bilirubin levels were significantly increased in group II (receiving ATT) compared to normal control on day 28 and day 36 (p<0.05). All three doses of scopoletin and NAC groups led to the resolution of AST, ALT, ALP, and bilirubin changes induced by ATT medications effect beginning by day 28 and persisting on day 36 (p<0.01). An insignificant effect was observed on albumin and total protein levels. The effect was confirmed with antioxidants and histopathology analysis.

Conclusions
The study confirms the hepatoprotective efficacy of scopoletin in a more robust commonly encountered liver injury etiology.
The Lineage of Spiritual Succession of the First Bogd Gegen of Mongolia Zanabazar (1634–1723) in His Secret Namtar and on the Thangka
Authors: Syrtypova Surun-Khanda D. 
Published: September 2023

Abstract
The author compares the data of written and pictorial sources related to the most intimate aspect of the life and work of the great Buddhist master Jebzun Damba Khutukhta Undur Gegen Zanabazar. This is the text of his secret namtar, which in Mongolian is usually called “Prayer for the Links of Rebirth” (Mong.: töröl üye-yin jarbiral). The example of this xylograph is kept in the National Library of Mongolia. The basic source for its creation, obviously, was “Jataka mala sugitikatha”, the Tibetan text on the successive line of Tarantha (1575–1634). And the rarest example of Buddhist Mongolian painting of the 17th century is thangka by Zanabazar “The Perfection of Trikaya”, which was kindly provided to the author by the owner of a private collection, B. Amarsana. The thangka is describing for the first time. A detailed analysis of the characters on the painting with the ritual tradition of the Vajrayana reveals the mysterious details of the spiritual practice of Undur Gegen and sets before us new horizons and questions for an in-depth study of Mongolian Buddhism. A comparative study of visual and verbal sources allows us to speak about the Practice of Long Life by the method of the White Chakrasamvara in the tradition of yogini Niguma by Undur Gegen Zanabazar along with the practice of long life by the method of Buddha Amitayus.
Princesses of the Central Plains Married into the Turkish Khaganate
Authors: Urgunbuyan Baatar 
Published: September 2023

Abstract
This article discusses queens and princesses such as “Princess Yi Cheng”, “Princess Chanle”, “Queen of the Xiang Khatun”, “Princess Yixin”, “Princess Huainan”, “Princess Qianjin”, “Princess Anyi” of Western Wei, Northern Zhou, and Sui who married the Turkish Khaganate. During the rule of the First Turkish Khaganate (552–630), the countries of the Middle Khaganate
The princesses in the story are related to Western Wei, Northern Zhou, Sui and Tang. Also, most of these princesses were the daughters of the Xianbei clan. Therefore, it was not possible to name it after a country or a Chinese princess, so the people of the area were given the title because they are Middle Countries or Southern countries.
gave their daughters to the Turkish kings and nobles and wanted to continue their domination by getting support from the Turkish state even so, their rule couldn’t last for a long time, and their state was not stable, eventually, a new state was established in a short period. Furthermore, the historical and political context of the two countries before and after the arrival of the princesses in the Turkish Khaganate will be briefly described. I wrote extensively about two princesses, Qianjing of Northern Zhou and Yi Cheng of Sui, whose dynasty was destroyed and whose descendants were killed just after they arrived in the Turkish Khaganate. They actively participated in politics to take revenge on the newly established state and to rebuild their old ancestral state. My argument is to clarify how it negatively affected the unity and foreign policy of the Turkish Khaganate.
Dual channel transformation of scalar and vector terahertz beams along the optical path based on dielectric metasurface
Authors: Luo Li , Liu Xiao , Duan Shouxin , Li Hui , Xu Hang , Peng Sui , Liu Bo , Wang Yuting , Wang Lingzhi , Zou Yuxin , Li Jie , Shen Yun , Yao Jianquan 
Published: September 2023

Abstract
The research on terahertz wave manipulation based on metasurfaces has gradually deepened, and the number of functions or electromagnetic control dimensions in a single device is constantly increasing. For the spatial dimension of terahertz field regulation, its design degrees of freedom have been expanded from a single transverse plane to the propagation path. In this paper, we propose a novel circularly polarization multiplexed metasurface for dual channel terahertz wave transmission control. Based on the spatial integration of two heterogeneous meta-atoms, which are spin-decoupled and isotropic, respectively, there are four phase channels that can be used at the same time, thus achieving different switching between vector and scalar beams in different circularly polarization channels along the optical path. For linearly polarized wave incidence, the device exhibits conversion between different vector beams longitudinally. To control more electric field components, we combine focused wavefront design with vector or scalar fields and utilize the focusing induced spin–orbit coupling effect, then complex amplitude switching of longitudinal electric field components is obtained. This article extends the manipulation of terahertz waves along the propagation trajectory based on metasurface from single to dual channel for the first time, providing a reference for the design of multifunctional meta-device in terahertz band.