bluuebunny/crossref_metadata_2025_split huggingface dataset:
A deep learning framework for epileptic seizure detection based on neonatal EEG signals
Authors: Gramacki Artur , Gramacki Jarosław 
Published: July 2022

AbstractElectroencephalogram (EEG) is one of the main diagnostic tests for epilepsy. The detection of epileptic activity is usually performed by a human expert and is based on finding specific patterns in the multi-channel electroencephalogram. This is a difficult and time-consuming task, therefore various attempts are made to automate it using both conventional and Deep Learning (DL) techniques. Unfortunately, authors do not often provide sufficiently detailed and complete information to be able to reproduce their results. Our work is intended to fill this gap. Using a carefully selected 79 neonatal EEG recordings we developed a complete framework for seizure detection using DL approch. We share a ready to use R and Python codes which allow: (a) read raw European Data Format files, (b) read data files containing the seizure annotations made by human experts, (c) extract train, validation and test data, (d) create an appropriate Convolutional Neural Network (CNN) model, (e) train the model, (f) check the quality of the neural classifier, (g) save all learning results.
Freshwater unionid mussels threatened by predation of Round Goby (Neogobius melanostomus)
Authors: Clark Kyle H. , Iwanowicz Deborah D. , Iwanowicz Luke R. , Mueller Sara J. , Wisor Joshua M. , Bradshaw-Wilson Casey , Schill William B. , Stauffer J. R. , Boyer Elizabeth W. 
Published: July 2022

AbstractIndigenous freshwater mussels (Unionidae) are integral to riverine ecosystems, playing a pivotal role in aquatic food webs and providing ecological services. With populations on the decline worldwide, freshwater mussels are of conservation concern. In this study, we explore the propensity of the invasive Round Goby (Neogobius melanostomus) fish to prey upon indigenous freshwater mussels. First, we conducted lab experiments where Round Gobies were given the opportunity to feed on juvenile unionid mussels and macroinvertebrates, revealing rates and preferences of consumption. Several Round Gobies consumed whole freshwater mussels during these experiments, as confirmed by mussel counts and x-ray images of the fishes. Next, we investigated Round Gobies collected from stream habitats of the French Creek watershed, which is renowned for its unique and rich aquatic biodiversity. We developed a novel DNA metabarcoding method to identify the specific species of mussels consumed by Round Goby and provide a new database of DNA gene sequences for 25 indigenous unionid mussel species. Several of the fishes sampled had consumed indigenous mussels, including the Elktoe (non-endangered), Creeper (non-endangered), Long Solid (state endangered), and Rayed Bean (federally endangered) species. The invasive Round Goby poses a growing threat to unionid mussels, including species of conservation concern. The introduction of the invasive Round Goby to freshwaters of North America is shaping ecosystem transitions within the aquatic critical zone having widespread implications for conservation and management.
Heavy metal removal using an advanced removal method to obtain recyclable paper incineration ash
Authors: Kim Hak-Min , Choi Tae-Yeol , Park Min-Ju , Jeong Dae-Woon 
Published: July 2022

AbstractVarious agents, including ethylenediaminetetraacetic acid, oxalic acid, citric acid, and HCl, were applied to remove heavy metals from raw paper incineration ash and render the ash recyclable. Among these prepared agent solutions, ethylenediaminetetraacetic acid showed the highest efficiency for Pb removal, while oxalic acid showed the highest efficiencies for Cu, Cd, and As removal. Additionally, three modes of an advanced removal method, which involved the use of both ethylenediaminetetraacetic acid and oxalic acid, were considered for use at the end of the rendering process. Among these three modes of the advanced removal method, that which involved the simultaneous use of ethylenediaminetetraacetic acid and oxalic acid, i.e., a mixture of both solutions, showed the best heavy metal removal efficiencies. In detail, 11.9% of Cd, 10% of Hg, 28.42% of As, 31.29% of Cu, and 49.19% of Pb were removed when this method was used. Furthermore, the application of these three modes of the advanced removal method resulted in a decrease in the amounts of heavy metals eluted and brought about an increase in the CaO content of the treated incineration ash, while decreasing its Cl content. These combined results enhanced the solidification effect of the treated incineration ash. Thus, it was confirmed that the advanced removal method is a promising strategy by which recyclable paper incineration ash can be obtained.
Comparison of survival between unilocular cystic and purely solid renal cell carcinoma
Authors: Wang Yapeng , Niu Xiaoyu , Wang Lihui , Li Yunlong , Qiao Baoping 
Published: July 2022

AbstractTo evaluate clinicopathological features and survival outcomes of unilocular cystic renal cell carcinoma (ucRCC) compared with purely solid renal cell carcinoma (sRCC), and to evaluate the oncologic aggressiveness of ucRCC. The relevant data of 957 patients with sporadic unilateral renal cell carcinoma (RCC) underwent surgical treatment in 2 institutions from Jan 2014 to Oct 2018 were obtained. We excluded multilocular cystic renal neoplasm of low malignant potential (MCRNLMP), RCC with multilocular cysts and necrotic RCC. 74 ucRCCs were identified by pathology reports. We performed propensity score matching (PSM) and eventually selected 144 sRCCs. The clinicopathological features and survival outcomes were compared properly. After PSM, age, BMI, Charlson Comorbidity Index, and postoperative Chronic Kidney Disease grade were not significantly different. Both overall survival and progression-free survival of ucRCC were significantly better than sRCC by the log-rank test. Twenty-five cases of sRCCs were in the pT3 or pT4 stage, while no pT3 or pT4 tumors were found in ucRCCs. Fuhrman grade and lymphatic metastasis were found to be significant prognostic factors for the overall survival of ucRCC. Unilocular cystic RCC has a lower Fuhrman grade and pathological stage and a better prognosis compared with solid RCC. Patients with ucRCC still probably have lymphatic metastasis at surgery and may have postoperative metastasis, which is different from MCRNLMP. We recommend that the diagnosis of ucRCC should be reflected in pathology report. Different subtype of cystic RCC should be taken into consideration in counseling and management.
A microfluidic diagnostic device with air plug-in valves for the simultaneous genetic detection of various food allergens
Authors: Natsuhara Daigo , Misawa Sae , Saito Ryogo , Shirai Koki , Okamoto Shunya , Nagai Moeto , Kitamura Masashi , Shibata Takayuki 
Published: July 2022

AbstractThe identification of accidental allergen contamination in processed foods is crucial for risk management strategies in the food processing industry to effectively prevent food allergy incidents. Here, we propose a newly designed passive stop valve with high pressure resistance performance termed an “air plug-in valve” to further improve microfluidic devices for the detection of target nucleic acids. By implementing the air plug-in valve as a permanent stop valve, a maximal allowable flow rate of 70 µL/min could be achieved for sequential liquid dispensing into an array of 10 microchambers, which is 14 times higher than that achieved with the previous valve arrangement using single-faced stop valves. Additionally, we demonstrate the simultaneous detection of multiple food allergens (wheat, buckwheat, and peanut) based on the colorimetric loop-mediated isothermal amplification assay using our diagnostic device with 10 microchambers compactly arranged in a 20-mm-diameter circle. After running the assays at 60 °C for 60 min, any combination of the three types of food allergens and tea plant, which were used as positive and negative control samples, respectively, yielded correct test results, without any cross-contamination among the microchambers. Thus, our diagnostic device will provide a rapid and easy sample-to-answer platform for ensuring food safety and security.
A methodology for evaluating digital contact tracing apps based on the COVID-19 experience
Authors: Hernández-Orallo Enrique , Manzoni Pietro , Calafate Carlos T. , Cano Juan-Carlos 
Published: July 2022

AbstractControlling the spreading of infectious diseases has been shown crucial in the COVID-19 pandemic. Traditional contact tracing is used to detect newly infected individuals by tracing their previous contacts, and by selectively checking and isolating any individuals likely to have been infected. Digital contact tracing with the utilisation of smartphones was contrived as a technological aid to improve this manual, slow and tedious process. Nevertheless, despite the high hopes raised when smartphone-based contact tracing apps were introduced as a measure to reduce the spread of the COVID-19, their efficiency has been moderately low. In this paper, we propose a methodology for evaluating digital contact tracing apps, based on an epidemic model, which will be used not only to evaluate the deployed Apps against the COVID-19 but also to determine how they can be improved for future pandemics. Firstly, the model confirms the moderate effectiveness of the deployed digital contact tracing, confirming the fact that it could not be used as the unique measure to fight against the COVID-19, and had to be combined with additional measures. Secondly, several improvements are proposed (and evaluated) to increase the efficiency of digital control tracing to become a more useful tool in the future.
Exploring the operational potential of the forest-photovoltaic utilizing the simulated solar tree
Authors: Um Dan-Bi 
Published: July 2022

AbstractThe aim of this study was to explore the operational potential of forest-photovoltaic by simulating solar tree installation. The forest-photovoltaic concept is to maintain carbon absorption activities in the lower part while acquiring solar energy by installing a photovoltaic structure on the upper part of forest land. This study was conducted by simulating solar tree installation using Google Earth satellite imagery in a mountainous area where an agrophotovoltaic system was already installed. When the simulation results were evaluated based on the installation guideline of the agrophotovoltaic system, it was confirmed that the operational potential of forest-photovoltaic was very high in almost all items of the guideline. Therefore, forest photovoltaic can be a possible alternative with priority in South Korea, where it is challenging to secure spatial competitiveness with a conventional flat fixed panel due to costly land prices. Although South Korea has been selected here as a case study, this discussion can be applied to other countries facing the disturbance risk to the forestry landscape due to solar power projects. To the best of the author's knowledge, this is the world's first study exploring the possibility of the forest-photovoltaic.
A nationwide study of patients operated for cervical degenerative disorders in public and private hospitals
Authors: Danielsen Elisabet , Mjåset Christer , Ingebrigtsen Tor , Gulati Sasha , Grotle Margreth , Rudolfsen Jan Håkon , Nygaard Øystein P. , Solberg Tore K. 
Published: July 2022

AbstractDuring the last decades, there has been an increase in the rate of surgery for degenerative disorders of the cervical spine and in the use of supplementary private health insurance. Still, there is limited knowledge about the differences in characteristics of patients operated in public and private hospitals. Therefore, we aimed at comparing sociodemographic-, clinical- and patient management data on patients operated for degenerative cervical radiculopathy and degenerative cervical myelopathy in public and private hospitals in Norway. This was a cross-sectional study on patients in the Norwegian Registry for Spine Surgery operated for degenerative cervical radiculopathy and degenerative cervical myelopathy between January 2012 and December 2020. At admission for surgery, we assessed disability by the following patient reported outcome measures (PROMs): neck disability index (NDI), EuroQol-5D (EQ-5D) and numerical rating scales for neck pain (NRS-NP) and arm pain (NRS-AP). Among 9161 patients, 7344 (80.2%) procedures were performed in public hospitals and 1817 (19.8%) in private hospitals. Mean age was 52.1 years in public hospitals and 49.7 years in private hospitals (P < 0.001). More women were operated in public hospitals (47.9%) than in private hospitals (31.6%) (P < 0.001). A larger proportion of patients in private hospitals had high education (≥ 4 years of college or university) (42.9% vs 35.6%, P < 0.001). Patients in public hospitals had worse disease-specific health problems than those in private hospitals: unadjusted NDI mean difference was 5.2 (95% CI 4.4 – 6.0; P < 0.001) and adjusted NDI mean difference was 3.4 (95% CI 2.5 – 4.2; P < 0.001), and they also had longer duration of symptoms (P < 0.001). Duration of surgery (mean difference 29 minutes, 95% CI 27.1 – 30.7; P < 0.001) and length of hospital stay (mean difference 2 days, 95% CI 2.3 – 2.4; P < 0.001) were longer in public hospitals. In conclusion, patients operated for degenerative cervical spine in private hospitals were healthier, younger, better educated and more often men. They also had less and shorter duration of symptoms and seemed to be managed more efficiently. Our findings indicate that access to cervical spine surgery in private hospitals could be skewed in favour of patients with higher socioeconomic status.
Selective biofunctionalization of 3D cell-imprinted PDMS with collagen immobilization for targeted cell attachment
Authors: Babaei Mahrokh , Bonakdar Shahin , Nasernejad Bahram 
Published: July 2022

AbstractCell-imprinted polydimethylsiloxane substrates, in terms of their ability to mimic the physiological niche, low microfabrication cost, and excellent biocompatibility were widely used in tissue engineering. Cells inside the mature cells' cell-imprinted PDMS pattern have been shown in previous research to be capable of being differentiated into a specific mature cell line. On the other hand, the hydrophobicity of PDMS substrate leads to weak cell adhesion. Moreover, there was no guarantee that the cells would be exactly located in the cavities of the cells' pattern. In many studies, PDMS surface was modified by plasma treatment, chemical modification, and ECM coating. Hence, to increase the efficiency of cell-imprinting method, the concavity region created by the cell-imprinted pattern is conjugated with collagen. A simple and economical method of epoxy silane resin was applied for the selective protein immobilization on the desired regions of the PDMS substrate. This method could be paved to enhance the cell trapping into the cell-imprinted pattern, and it could be helpful for stem cell differentiation studies. The applied method for selective protein attachment, and as a consequence, selective cell integration was assessed on the aligned cell-imprinted PDMS. A microfluidic chip created the aligned cell pattern. After Ar+plasma and APTES treatment of the PDMS substrate, collagen immobilization was performed. The immobilized collagen was removed by epoxy silane resin stamp from the ridge area where the substrate lacked cell pattern and leaving the collagen only within the patterned areas. Coomassie brilliant blue staining was evaluated for selective collagen immobilization, and the collagen-binding stability was assessed by BCA analysis. MTT assay for the evaluation of cell viability on the modified surface was further analyzed. Subsequently, the crystal violet staining has confirmed the selective cell integration to the collagen-immobilized site on the PDMS substrate. The results proved the successfully selective collagen immobilization on the cell-imprinted PDMS and showed that this method increased the affinity of cells to attach inside the cell pattern cavity.
Research on water meter reading recognition based on deep learning
Authors: Liang Yue , Liao Yiqi , Li Shaobo , Wu Wenjuan , Qiu Taorong , Zhang Weiping 
Published: July 2022

AbstractAt present, there are still many old-fashioned water meters in the society, and the water department needs to send staff to read the water meter after arriving at the scene with a handheld all-in-one machine. However, there are many problems in this manual meter reading method. First, a large number of meter reading work leads to low efficiency of the entire water department, consuming a lot of time and energy, and high labor costs; second, the water meters in natural scenes have problems such as serious dial contamination and other environmental factors that interfere with the meter reading staff, and the results of the meter reader cannot be verified later. In response to these problems, this paper studies a deep learning method for automatic detection and recognition of water meter readings. This paper first introduces the existing in-depth learning models, such as Faster R-CNN, SSD, and YOLOv3. Then two datasets are sorted out, one is the original water table picture dataset, and the other is a dataset cut out from the water meter image with the black bounding box showing the water meter readings. Then two plans are proposed, one is the original water table image dataset, and the other is a dataset cut out from the water meter image with the black bounding box showing the water meter readings. Finally, by comparing the three models from different angles, it is determined that YOLOv3 in the second solution has the best recognition effect, and the accuracy rate reaches 90.61%, which can greatly improve work efficiency, save labor costs, and assist auditors in reviewing the read water meter readings.
Estimation of nutrient loads with the use of mass-balance and modelling approaches on the Wełna River catchment example (central Poland)
Authors: Bojanowski Damian , Orlińska-Woźniak Paulina , Wilk Paweł , Szalińska Ewa 
Published: July 2022

AbstractNitrogen and phosphorus budgeting is considered to be a key tool for policy makers and stakeholders when dealing with nutrient contamination issues, however no unified method has been employed in countries affected by this eutrophication problem. The current study offers a detailed insight into the estimations of nutrient loads and their distribution between different sources for a middle-sized agricultural catchment, with the use of two approaches: mass balance (static) and modelling (dynamic). Both methods revealed similar contributions of analysed nutrient sources, although the final estimates in the chosen calculation profile were divergent due to the various reasons related to the methods’ specificity. The advantages and disadvantages of both approaches have been specified in our study, and a hybrid solution on a local and country wide scale has been proposed.
Deep learning-based defects detection of certain aero-engine blades and vanes with DDSC-YOLOv5s
Authors: Li Xubo , Wang Wenqing , Sun Lihua , Hu Bin , Zhu Liang , Zhang Jincheng 
Published: July 2022

AbstractWhen performed by a person, aero-engine borescope inspection is easily influenced by individual experience and human factors that can lead to incorrect maintenance decisions, potentially resulting in serious disasters, as well as low efficiency. To address the absolute requirements of flight safety and improve efficiency to decrease maintenance costs, it is imperative to realize the intelligent detection of common aero-engine defects. YOLOv5 enables real-time detection of aero-engine defects with a high degree of accuracy. However, the performance of YOLOv5 is not optimal when detecting the same defects with multiple shapes. In this work, we introduce a deformable convolutional network into the structure of YOLOv5s to optimize its performance, overcome the disadvantage of the poor geometric transformability of convolutional neural networks, and enhance the adaptability of feature maps with large differences in the shape features. We also use a depth-wise separable convolution to improve the efficiency of multichannel convolution in extracting feature information from each channel at the same spatial position while reducing the increased computational effort due to the introduction of deformable convolution networks and use k-means clustering to optimize the size of anchor boxes. In the test results, mAP50 reached 83.8%. The detection accuracy of YOLOv5s for common aero-engine defects was effectively improved with only a 7.9% increase in calculation volume. Compared with the metrics of the original YOLOv5s, mAP@50 was improved by 1.9%, and mAP@50:95 was improved by 1.2%. This study highlights the wide application potential of depth science methods in achieving intelligent detection of aero-engine defects. In addition, this study emphasizes the integration of DDSC-YOLOv5s into borescope platforms for scaled-up engine defect detection, which should also be enhanced in the future.
A theoretical investigation of the effect of Ga alloying on thermodynamic stability, electronic-structure, and oxidation resistance of Ti2AlC MAX phase
Authors: Sauceda Daniel , Singh Prashant , Arroyave Raymundo 
Published: July 2022

AbstractWe present a systematic investigation of thermodynamic stability, phase-reaction, and chemical activity of Al containing disordered Ti2(Al-Ga)C MAX phases using machine-learning driven high-throughput framework to understand the oxidation resistance behavior with increasing temperature and exposure to static oxygen. The A-site (at Al) disordering in Ti2AlC MAX (M=Ti, A=Al, X=C) with Ga shows significant change in the chemical activity of Al with increasing temperature and exposure to static oxygen, which is expected to enable surface segregation of Al, thereby, the formation of Al2O3 and improved oxidation resistance. We performed in-depth convex hull analysis of ternary Ti–Al–C, Ti–Ga–C, and Ti–Al–Ga–C based MAX phase, and provide detailed contribution arising from electronic, chemical and vibrational entropies. The thermodynamic analysis shows change in the Gibbs formation enthalpy (ΔGform) at higher temperatures, which implies an interplay of temperature-dependent enthalpy and entropic contributions in oxidation resistance Ga doped Ti2AlC MAX phases. A detailed electronic structure and chemical bonding analysis using crystal orbital Hamilton population method reveal the origin of change in phases stability and in oxidation resistance in disorder Ti2(Al1−xGax)C MAX phases. Our electronic structure analysis correlate well with the change in oxidation resistance of Ga doped MAX phases. We believe our study provides a useful guideline to understand to role of alloying on electronic, thermodynamic, and oxidation related mechanisms of bulk MAX phases, which can work as a precursor to understand oxidation behavior of two-dimensional MAX phases, i.e., MXenes (transition metal carbides, carbonitrides and nitrides).