bluuebunny/crossref_metadata_2025 huggingface dataset:
Correlations between Contrast-Enhanced Ultrasound Imaging and Histopathological Results in Salivary Gland Lesions
Authors: Krupa Karolina , Wieczorek Patryk , Scrinscaia Olga , Puzio Anna , Kozłowski Zbigniew , Pietruszewska Wioletta , Stefańczyk Ludomir
Published: November 2022

The purpose of this study was to search for correlations between contrast-enhanced ultrasound (CEUS) imaging and histopathological results in salivary gland lesions and to determine the accuracy of CEUS in the preoperative differentiation of salivary gland tumours according to postoperative histopathological results. The study included 54 consecutive patients with 63 salivary gland lesions who underwent CEUS examination prior to surgical treatment at the Department of Otolaryngology, Medical University of Łódź (Poland) in 2019–2022. The accuracy of CEUS in differential diagnostics of salivary gland lesions was later verified against final histological diagnosis. Among 63 salivary gland lesions, 26 were categorized as malignant or with malignant potential, and 37 were benign. There was a correlation between professional photographs of CEUS imaging and microscope slides containing postoperative specimens. A strong heterogeneous enhancement was observed mainly in benign lesions, with while weak heterogeneity mostly among the malignant or with malignant potential lesions. A pattern of contrast enhancement in specific structures reflected histopathological images. These results suggest that contrast-enhanced ultrasonography is a promising tool for the preoperative diagnostics of salivary gland lesions.
Post-Mortem Interval and Microbiome Analysis through 16S rRNA Analysis: A Systematic Review
Authors: Tozzo Pamela , Amico Irene , Delicati Arianna , Toselli Federico , Caenazzo Luciana
Published: November 2022

The determination of the Post-Mortem Interval (PMI) is an issue that has always represented a challenge in the field of forensic science. Different innovative approaches, compared to the more traditional ones, have been tried over the years, without succeeding in being validated as successful methods for PMI estimation. In the last two decades, innovations in sequencing technologies have made it possible to generate large volumes of data, allowing all members of a bacterial community to be sequenced. The aim of this manuscript is to provide a review regarding new advances in PMI estimation through cadaveric microbiota identification using 16S rRNA sequencing, in order to correlate specific microbiome profiles obtained from different body sites to PMI. The systematic review was performed according to PRISMA guidelines. For this purpose, 800 studies were identified through database searching (Pubmed). Articles that dealt with PMI estimation in correlation with microbiome composition and contained data about species, body site of sampling, monitoring time and sequencing method were selected and ultimately a total of 25 studies were considered. The selected studies evaluated the contribution of the various body sites to determine PMI, based on microbiome sequencing, in human and animal models. The results of this systematic review highlighted that studies conducted on both animals and humans yielded results that were promising. In order to fully exploit the potential of the microbiome in the estimation of PMI, it would be desirable to identify standardized body sampling sites and specific sampling methods in order to align data obtained by different research groups.
Artificial Intelligence in Lung Cancer Imaging: Unfolding the Future
Authors: Cellina Michaela , Cè Maurizio , Irmici Giovanni , Ascenti Velio , Khenkina Natallia , Toto-Brocchi Marco , Martinenghi Carlo , Papa Sergio , Carrafiello Gianpaolo
Published: November 2022

Lung cancer is one of the malignancies with higher morbidity and mortality. Imaging plays an essential role in each phase of lung cancer management, from detection to assessment of response to treatment. The development of imaging-based artificial intelligence (AI) models has the potential to play a key role in early detection and customized treatment planning. Computer-aided detection of lung nodules in screening programs has revolutionized the early detection of the disease. Moreover, the possibility to use AI approaches to identify patients at risk of developing lung cancer during their life can help a more targeted screening program. The combination of imaging features and clinical and laboratory data through AI models is giving promising results in the prediction of patients’ outcomes, response to specific therapies, and risk for toxic reaction development. In this review, we provide an overview of the main imaging AI-based tools in lung cancer imaging, including automated lesion detection, characterization, segmentation, prediction of outcome, and treatment response to provide radiologists and clinicians with the foundation for these applications in a clinical scenario.
Diagnostic Value of Superb Microvascular Imaging in Differentiating Benign and Malignant Breast Tumors: A Systematic Review and Meta-Analysis
Authors: Feng Jiaping , Lu Jianghao , Jin Chunchun , Chen Yihao , Chen Sihan , Guo Guoqiang , Gong Xuehao
Published: November 2022

Purpose: We performed a systematic review and meta-analysis of studies that investigated the diagnostic performance of Superb Microvascular Imaging (SMI) in differentiating between benign and malignant breast tumors. Methods: Studies published between January 2010 and March 2022 were retrieved by online literature search conducted in PubMed, Embase, Cochrane Library, Web of Science, China Biology Medicine Disc, China National Knowledge Infrastructure, Wanfang, and Vip databases. Pooled sensitivity, specificity, and diagnostic odd ratios were calculated using Stata software 15.0. Heterogeneity among the included studies was assessed using I2 statistic and Q test. Meta-regression and subgroup analyses were conducted to investigate potential sources of heterogeneity. Influence analysis was conducted to determine the robustness of the pooled conclusions. Deeks’ funnel plot asymmetry test was performed to assess publication bias. A summary receiver operating characteristic curve (SROC) was constructed. Results: Twenty-three studies involving 2749 breast lesions were included in our meta-analysis. The pooled sensitivity and specificity were 0.80 (95% confidence interval [CI], 0.77–0.84, inconsistency index [I2] = 28.32%) and 0.84 (95% CI, 0.79–0.88, I2 = 89.36%), respectively. The pooled diagnostic odds ratio was 19.95 (95% CI, 14.84–26.82). The area under the SROC (AUC) was 0.85 (95% CI, 0.81–0.87). Conclusion: SMI has a relatively high sensitivity, specificity, and accuracy for differentiating between benign and malignant breast lesions. It represents a promising supplementary technique for the diagnosis of breast neoplasms.
Cardiac Magnetic Resonance in Fabry Disease: Morphological, Functional, and Tissue Features
Authors: Aquaro Giovanni Donato , De Gori Carmelo , Faggioni Lorenzo , Parisella Maria Luisa , Aringhieri Giacomo , Cioni Dania , Lencioni Riccardo , Neri Emanuele
Published: November 2022

Fabry disease (FD) is an X-linked inheritable storage disease caused by a deficiency of alpha-galactosidase causing lysosomal overload of sphingolipids. FD cardiomyopathy is characterized by left ventricular (LV) hypertrophy and should be considered in differential diagnosis with all the other causes of LV hypertrophy. An early diagnosis of FD is very important because the enzyme replacement therapy (ERT) may change the fate of patients by blocking both cardiac and systemic involvement and improving prognosis. Diagnosis may be relatively easy in young patients with the typical signs and symptoms of FD, but in male patients with late onset of disease and in females, diagnosis may be very challenging. Morphological and functional aspects are not specific to FD, which cannot be diagnosed or excluded by echocardiography. Cardiac magnetic resonance (CMR) with tissue characterization capability is an accurate technique for the differential diagnosis of LV hypertrophy. The finding of decreased myocardial T1 value in LV hypertrophy is specific to FD. Late gadolinium enhancement (LGE) is found in the late stage of the disease, but it is useful to predict the cardiac response to ERT and to stratify the prognosis.
Significance of Machine Learning for Detection of Malicious Websites on an Unbalanced Dataset
Authors: Ul Hassan Ietezaz , Ali Raja Hashim , Ul Abideen Zain , Khan Talha Ali , Kouatly Rand
Published: November 2022

It is hard to trust any data entry on online websites as some websites may be malicious, and gather data for illegal or unintended use. For example, bank login and credit card information can be misused for financial theft. To make users aware of the digital safety of websites, we have tried to identify and learn the pattern on a dataset consisting of features of malicious and benign websites. We treated the problem of differentiation between malicious and benign websites as a classification problem and applied several machine learning techniques, for example, random forest, decision tree, logistic regression, and support vector machines to this data. Several evaluation metrics such as accuracy, precision, recall, F1 score, and false positive rate, were used to evaluate the performance of each classification technique. Since the dataset was imbalanced, the machine learning models developed a bias during training toward a specific class of websites. Multiple data balancing techniques, for example, undersampling, oversampling, and SMOTE, were applied for balancing the dataset and removing the bias. Our experiments showed that after balancing the data, the random forest algorithm using the oversampling technique showed the best results in all evaluation metrics for the benign and malicious website feature dataset.
Pulmonary Granulomas and Mycobacterial Infection: Concordance between the Results of Special Stains Performed on Lung Tissue Sections and Tissue Cultures
Authors: Bahmad Hisham F. , Azimi Roshanak , Kilinc Ekim , Tuda Claudio , Vincentelli Cristina
Published: November 2022

Background: The most common cause of infectious pulmonary granulomas worldwide is Mycobacterium tuberculosis. The diagnosis is based on clinical presentation, histopathologic findings, detection of acid-fast bacilli (AFB) in tissue or sputum using special stains, and/or isolation of mycobacteria in cultures or via PCR-based methods. Different studies have shown that high levels of discrepancy exist between these diagnostic approaches in lung tissue specimens. Objective: To assess the degree of concordance between the results of special stains and cultures on lung tissue specimens in the diagnosis of mycobacterial infections. Methodology: Eighty-seven patients with a diagnosis of granulomas (necrotizing and non-necrotizing) on lung tissue specimens were identified. Cohen’s kappa was used to measure the general concordance between the results of the histopathological examination (special stains) and bacteriological tissue cultures. Results: With Kinyoun acid-fast stains, 8/48 (16.7%) cases were positive for AFB. With FITE stains, 10/57 (17.5%) cases were positive for AFB. There was strong agreement between Kinyoun acid-fast and FITE stains (Kappa = 0.806; p-value < 0.001). Tissue cultures were performed on 38/87 cases (43.7%), and 10/38 (26.3%) of the cultures were positive for mycobacteria. There was no concordance between Kinyoun acid-fast stains or FITE stains and tissue cultures results. Conclusion: Our observations represent an initial step in the process of reviewing the two methods used at our institution to diagnose mycobacterial infections on lung tissue specimens and highlight the need of incorporating more advanced diagnostic methods such as PCR to confirm mycobacterial infections and improve patient management. Importantly, species-level identification of mycobacteria is necessary to guide treatment.
Conflict Dynamics in Scale-Free Networks with Degree Correlations and Hierarchical Structure
Authors: Jacobo-Villegas Eduardo , Obregón-Quintana Bibiana , Guzmán-Vargas Lev , Liebovitch Larry S.
Published: November 2022

We present a study of the dynamic interactions between actors located on complex networks with scale-free and hierarchical scale-free topologies with assortative mixing, that is, correlations between the degree distributions of the actors. The actor’s state evolves according to a model that considers its previous state, the inertia to change, and the influence of its neighborhood. We show that the time evolution of the system depends on the percentage of cooperative or competitive interactions. For scale-free networks, we find that the dispersion between actors is higher when all interactions are either cooperative or competitive, while a balanced presence of interactions leads to a lower separation. Moreover, positive assortative mixing leads to greater divergence between the states, while negative assortative mixing reduces this dispersion. We also find that hierarchical scale-free networks have both similarities and differences when compared with scale-free networks. Hierarchical scale-free networks, like scale-free networks, show the least divergence for an equal mix of cooperative and competitive interactions between actors. On the other hand, hierarchical scale-free networks, unlike scale-free networks, show much greater divergence when dominated by cooperative rather than competitive actors, and while the formation of a rich club (adding links between hubs) with cooperative interactions leads to greater divergence, the divergence is much less when they are fully competitive. Our findings highlight the importance of the topology where the interaction dynamics take place, and the fact that a balanced presence of cooperators and competitors makes the system more cohesive, compared to the case where one strategy dominates.
Inclusion and Deaf and Hard of Hearing Students: Finding Asylum in the LRE
Authors: Silvestri Julia A. , Hartman Maria C.
Published: November 2022

The movement towards inclusive public education for deaf and hard of hearing children (DHH) has steadily gathered momentum during the last fifty years. Both within the United States and abroad, inclusive public education has been facilitated through legislative action with varied results. Varied interpretation of inclusion policy, notably the “Least Restrictive Environment” (LRE) clause of the Individuals with Disabilities Education Act in the United States, an emphasis on assimilation, and a default preference for auditory-oral communication have often resulted in isolating and inaccessible experiences for DHH students in the mainstream. The purpose of this article is to review theory and research on effective practices in inclusion for DHH students. The research is summarized with respect to accessibility, social-emotional considerations, and language policy. It is often asserted that communication access and cultural identity are major factors that impact the successful inclusion of these students with bicultural identity related to greater wellbeing. Deaf schools may be the LRE placement option for some students and source of resource and support for DHH students and educators in all settings. The authors suggest that a shift towards a more inclusive experience in mainstream settings is emerging through the use of Universal Design for Learning (UDL), classroom technology, and culturally responsive education that integrates sign language and Deaf culture to foster bicultural identities. Strategies for effective inclusion include co-enrollment, deaf awareness programming, and consistent policy that equalizes the status of sign languages. Future research is recommended in effective practices in auditory and visual accommodations, integration of technology in K-12 classrooms, and the relation of policy to practice in inclusive education for DHH students.
Admission Grades as Predictors of Medical Students’ Academic Performance: A Cross-Sectional Study from Saudi Arabia
Authors: Hendi Ali , Mahfouz Mohammed S. , Alqassim Ahmad Y. , Makeen Anwar , Somaili Mohammed , Shami Mohammed O. , Names Abdellh A. , Darraj Alaa , Kariri Areej , Ashiri Asma , Alhazmi Abdulaziz H.
Published: November 2022

Background: Admission to medical school is competitive, and different countries use various tests in addition to high school grades to minimize selection bias. A few studies have been conducted to evaluate the usefulness of these tests as predictors for students’ academic performance. In this article, we aimed to assess factors that influenced students’ grades in medical school. Methods: A cross-sectional study included all students who graduated from the Faculty of Medicine at Jazan University between 2018 and 2020. Scores of the included participants were extracted from the registry of Jazan University, and additional questions about study habits were completed by the included students. Descriptive, univariate, and multivariate analyses were performed for the factors that impacted academic performance. Results: There were 331 included candidates, and the majority of them were female (53%). About 60% of the participants were medical residents at the time of the study, and 40% were interns. Univariate and multivariate analyses indicated that grades in high school and the pre-requisite tests were positively associated with students’ academic performance. Further, studying more than two hours per day was positively correlated with better grades in medical school. Conclusion: Scores of the admission tests can serve as predictors for student performance in medical school. National studies are deemed essential to evaluate additional admission tests for medical school, an action that would minimize selection bias.
Internet Risk Perception: Development and Validation of a Scale for Adults
Authors: Torres-Hernández Norma , García-Martínez Inmaculada , Gallego-Arrufat María-Jesús
Published: November 2022

Despite the importance of Internet risk perception, no instrument currently exists that measures this awareness in the Spanish population. The goal of this study was to provide information on studies of the validity and reliability of the Internet Risk Perception (IRP) Scale for adult Spanish citizens. We began with a literature review and validation using a mixed panel with 20 participants. We analyzed the degree to which the subjects agreed or disagreed with the criteria evaluated, including contributions for improving the instrument, and performed a pilot test with 517 adults aged 18 to 77. Construct reliability and validity were analyzed using various statistical analyses. The results from the confirmatory factor analysis showed a sufficient accuracy of the data with parameters that indicated an excellent fit for all items. The Spanish version of the scale for adults is a reliable and valid instrument for use in studies that investigate Internet risk perception in people over 18 years of age.
Double Polar Codes for Joint Source and Channel Coding
Authors: Dong Yanfei , Niu Kai
Published: November 2022

In this paper, we design a joint source and channel coding (JSCC) framework combining the source polar coding and the channel polar coding. The source is first compressed using a polar code (PC), and source check decoding is employed to construct an error set containing the index of all source decoding errors. Then, the proposed JSCC system employs another PC or systematic PC (SPC) to protect the compressed source and the error set against noise, which is called double PC (D-PC) or systematic double PC (SD-PC), respectively. For a D-PC JSCC system, we prove a necessary condition for the optimal mapping between the source PC and the channel PC. On the receiver side, by introducing the joint factor graph representation of the D-PC and SD-PC, we propose two joint source and channel decoders: a joint belief propagation (J-BP) decoder, and a systematic joint belief propagation (SJ-BP) decoder. In addition, a biased extrinsic information transfer (B-EXIT) chart is developed for various decoders as a theoretical performance evaluation tool. Both B-EXIT and simulation results show that the performance of the proposed JSCC scheme has no error floor and outperforms the turbo-like BP decoder.
Research on Small Acceptance Domain Text Detection Algorithm Based on Attention Mechanism and Hybrid Feature Pyramid
Authors: Liu Mingzhu , Li Ben , Zhang Wei
Published: November 2022

In the traditional text detection process, the text area of the small receptive field in the video image is easily ignored, the features that can be extracted are few, and the calculation is large. These problems are not conducive to the recognition of text information. In this paper, a lightweight network structure on the basis of the EAST algorithm, the Convolution Block Attention Module (CBAM), is proposed. It is suitable for the spatial and channel hybrid attention module of text feature extraction of the natural scene video images. The improved structure proposed in this paper can obtain deep network features of text and reduce the computation of text feature extraction. Additionally, a hybrid feature pyramid + BLSTM network is designed to improve the attention to the small acceptance domain text regions and the text sequence features of the region. The test results on the ICDAR2015 demonstrate that the improved construction can effectively boost the attention of small acceptance domain text regions and improve the sequence feature detection accuracy of small acceptance domain of long text regions without significantly increasing computation. At the same time, the proposed network constructions are superior to the traditional EAST algorithm and other improved algorithms in accuracy rate P, recall rate R, and F-value.
Comparative Evaluation of the Performance of ZigBee and LoRa Wireless Networks in Building Environment
Authors: Liu Zhibin , Li Yuxin , Zhao Liang , Liang Ruobing , Wang Peng
Published: November 2022

ZigBee and LoRa are communication technologies widely used in the application of the Internet of things (IoT), especially in the field of smart building environmental monitoring. The main purpose of this study is to compare and analyze the transmission performance of ZigBee and LoRa wireless communication networks in the building. Through two indicators of packet loss rate (PLR) and round-trip time (RTT), this paper discusses in detail the transmission performance of ZigBee and LoRa technologies in whole buildings under the same working conditions. We set up three experimental scenarios of line-of-sight, horizontal and vertical to evaluate the communication performance of these two networks by changing the baud rate and packet length, and cost and power consumption were considered. Experiments have shown that LoRa networks outperform ZigBee networks in most cases and are the best choice for building communication networks. The experimental results provide basic data support and engineering reference for the application of these two technologies in buildings, especially for the deployment of communication networks throughout buildings. The innovation and contribution of this paper are to discuss the effect of packet length, baud rate, distance, and different locations within a building on the performance of ZigBee and LoRa transmissions, using RTT and PLR as metrics through three experimental scenarios.
A Coverage Hole Patching Algorithm for Heterogeneous Wireless Sensor Networks
Authors: Lu Xinmiao , Wei Yuhan , Wu Qiong , Yang Cunfang , Li Dongyuan , Zhang Liyu , Zhou Ying
Published: November 2022

The improvement of coverage is a critical issue in the coverage hole patching of sensors. Traditionally, VOPR and VORCP algorithms improve the coverage of the detection area by improving the original VOR algorithm, but coverage hole patching algorithms only target homogeneous networks. In the real world, however, the nodes in the wireless sensor network (WSN) are often heterogeneous, i.e., the sensors have different sensing radii. The VORPH algorithm uses the VOR in a hybrid heterogeneous network and improves the original algorithm. The patched nodes are better utilized, and the detection range is enlarged. However, the utilization rate of the patched nodes is not optimized, making it impossible to patch the coverage holes to the maximum degree. In the environment of hybrid heterogeneous WSN, we propose a coverage hole patching algorithm with a priority mechanism. The algorithm determines the patching priority based on the size of the coverage holes, thereby improving network coverage, reducing node redundancy, and balancing resource allocation. The proposed algorithm was compared under the same environment by simulation and analysis. The results show that our algorithm is superior to the traditional coverage hole patching algorithms in coverage rate, and can reduce node redundancy.
Heat Conduction with Krylov Subspace Method Using FEniCSx
Authors: Kumar Varun , Chandan K. , Nagaraja K. V. , Reddy M. V.
Published: November 2022

The study of heat transfer deals with the determination of the rate of heat energy transfer from one system to another driven by a temperature gradient. It can be observed in many natural phenomena and is often the fundamental principle behind several engineering systems. Heat transfer analysis is necessary while designing any product. The most common numerical method used to analyze heat transfer is the finite element method. This paper uses the finite element method to demonstrate steady and transient heat conduction in a three-dimensional bracket. The goal here was to determine the temperature distribution and rate of heat flow in the solid. This is crucial in designing machine elements as they are subjected to various thermal loads during operation and also due to fluctuations in the surrounding environmental conditions. The temperature significantly affects stress, displacements, and volumetric strains. Thus, to analyze thermal stresses induced in a machine element, it is necessary to find the temperature field first. The thermal analysis was performed using the open-source package FEniCSx on Python. The program was run using a preconditioned Krylov subspace method for higher-order function spaces. The Krylov subspace solver drastically reduces computational time. The time taken for the execution of each order was recorded and presented.
A Survey of Diagnostic and Condition Monitoring of Metal Oxide Surge Arrester in the Power Distribution Network
Authors: Ranjbar Behnam , Darvishi Ali , Dashti Rahman , Shaker Hamid Reza
Published: November 2022

Metal oxide surge arresters (MOSAs) are a popular solution for dealing with overvoltages due to lightning and switching in power distribution networks. As a result, a MOSA’s performance and longevity have a significant impact on the quality of energy and the frequency of outages. A MOSA performance is determined by several elements such as leakage current, partial discharge, and thermal image measured in various ways. In this study, different techniques for diagnostic and condition monitoring of MOSAs are discussed, and each method’s advantages and disadvantages are investigated. Additionally, the results of practical tests on two 20 kV healthy and degraded MOSAs are investigated and compared.
The Balance and Optimization Model of Coal Supply in the Flow Representation of Domestic Production and Imports: The Ukrainian Case Study
Authors: Bilan Tetiana , Kaplin Mykola , Makarov Vitaliy , Perov Mykola , Novitskii Ihor , Zaporozhets Artur , Havrysh Valerii , Nitsenko Vitalii
Published: November 2022

The successful supply of an economy with coal fuel, for a country that carries out its large-scale extraction and import, is a complex production and logistics problem. Violations of the usual supply scheme in conditions of crises in the energy markets, international conflicts, etc., lead to the problem of simultaneous restructuring of the entire supply scheme. This requires changes in the directions and capacities of domestic production and imports. In this article, the above problem is solved by the economic and mathematical model of production type. The developed model includes subsystems of domestic production and import supply. The results of modeling economy supply with thermal coal for different values of demand are given. The model was used to determine the amounts of coal production for Ukraine with the structure of the coal industry of 2021 and under the condition of anthracite consumers’ transformation to the high volatile coal. Simulations have shown that eliminating the use of anthracite requires the modernization of existing coal mines. Under those conditions, the import of high volatile coal will amount to 3.751 million tons in 2030 and 11.8 million tons in 2035. The amounts of coking coal imports will be 5.46 million tons, 5.151 million tons, and 7.377 million tons in 2025, 2030, and 2035, respectively.
Experimental Study on Damage Fracture Law of Coal from Solid-Propellant Blasting
Authors: Chu Huaibao , Yu Mengfei , Sun Bo , Yan Shaoyang , Wei Haixia , Zhang Guangran , Wang Donghui , Xu Jie
Published: November 2022

The low permeability of coal seams has always been the main bottleneck restricting coalbed methane drainage. In this paper, a coal seam anti-reflection technology with solid-propellant blasting was proposed, and the composition and proportion of the solid propellants were determined based on the principle of oxygen balance. The authors designed a solid-propellant blasting damage fracture experiment of simulation coal, tested the impact pressure on a blast hole wall, measured the ultrasonic wave velocity, explosive strain and crack propagation velocity, and then revealed the blasting damage fracture process and mechanism of coal based on the experimental results and damage fracture mechanics theory. The history curve of impact pressure time can be divided into three processes including the slow pressurization process, dramatic increase process, and nonlinear pressure relief process. The pressure distribution along the whole blasting hole was uneven, and the peak pressure was relatively small, but the pressure action time was long. The damage and fracture process of coal solid-propellant blasting can be divided into two stages including the rapid damage fracture development stage and the stable slow damage fracture development stage. Firstly, the explosion stress wave produced and rapidly accelerated the radial cracks extension; secondly, the cracks slowly expanded over a large area by the combined effects of the high-pressure gases, the gas, and the original rock stress.
Investigation of Effects of Different High Voltage Types on Dielectric Strength of Insulating Liquids
Authors: Atalar Fatih , Ersoy Aysel , Rozga Pawel
Published: November 2022

Liquid dielectrics are different from each other, but are used to perform the same tasks in high-voltage electrical equipment, especially transformers. In similar conditions, the insulation performance of transformer oils under different types of voltage will provide dielectric resistance. In this study, three different dielectric liquids applied in transformers, namely mineral oil, natural ester and synthetic ester, were tested. Tests under AC and negative DC voltage were performed at electrode gaps of 2.5 mm, 2 mm and 1 mm using disk and VDE type electrodes as per ASTM D1816-84A and ASTM D877-87 standards, respectively. In turn, the impulse voltage tests were performed under an electrode configuration suggested by the IEC 60897 standard. The current data of 500 ms prior to breakdown under AC electrical field stress was decomposed using the empirical mode decomposition (EMD) and variational mode decomposition (VMD) methods. These analyses were conducted before the full electrical breakdown. Although synthetic ester has the highest dielectric strength under AC and negative DC electrical field stress, mineral oil has been assessed to be the most resistant liquid dielectric at lightning impulse voltages. In addition, stabilization of mineral oil under AC and negative DC voltage was also seen to be good with the help of calculated standard deviation values. However, synthetic ester has a significant advantage, especially in terms of dielectric performance, over mineral oil in spite of the stability of mineral oil. This indicates that liquid dielectric selection for transformers must be carried out as a combined evaluation of multiple parameters.
Synthesis of Micron-Sized LiNi0.8Co0.1Mn0.1O2 and Its Application in Bimodal Distributed High Energy Density Li-Ion Battery Cathodes
Authors: Lin Chia-Hsin , Parthasarathi Senthil-Kumar , Bolloju Satish , Abdollahifar Mozaffar , Weng Yu-Ting , Wu Nae-Lih
Published: November 2022

The uniform and smaller-sized (~3 μm) LiNi0.8Co0.1Mn0.1O2 (SNCM) particles are prepared via a fast nucleation process of oxalate co-precipitation, followed by a two-step calcination procedure. It is found that the fast nucleation by vigorous agitation enables us to produce oxalate nuclei having a uniform size which then grow into micron-particles in less than a few minutes. The impacts of solution pH, precipitation time, calcination temperature, and surface modification with ZrO2 on the structural, morphological, and electrochemical properties of SNCM are systematically examined to identify the optimal synthetic conditions. A novel bimodal cathode design has been highlighted by using the combination of the SNCM particles and the conventional large (~10 μm) LiNi0.83Co0.12Mn0.05O2 (LNCM) particles to achieve the high volumetric energy density of cathode. The volumetric discharge capacity is found to be 526.6 mAh/cm3 for the bimodal cathode L80% + S20%, whereas the volumetric discharge capacity is found to be only 480.3 and 360.6 mAh/cm3 for L100% and S100% unimodal, respectively. Moreover, the optimal bi-modal cathode delivered higher specific energy (622.4 Wh/kg) and volumetric energy density (1622.6 Wh/L) than the L100% unimodal (596.1 Wh/kg and 1402.1 Wh/L) cathode after the 100th cycle. This study points to the promising utility of the SNCM material in Li-ion battery applications.
Gasification of Solid Recovered Fuels with Variable Fractions of Polymeric Materials
Authors: Alves Octávio , Calado Luís , Panizio Roberta M. , Nobre Catarina , Monteiro Eliseu , Brito Paulo , Gonçalves Margarida
Published: November 2022

Gasification is a promising thermochemical technology used to convert waste materials into energy with the introduction of low amounts of an oxidant agent, therefore producing an environmental impact that is lower when compared to incineration and landfilling. Moreover, gasification allows a sustainable management of wastes and reduces the use of fossil fuels responsible for the increment of greenhouse gases. This work aimed to perform gasification tests with solid recovered fuels (SRF) containing organic fractions mainly retrieved from construction and demolition wastes to assess the potential for energy conversion. Tests were conducted in a pilot-scale downdraft gasifier (maximum feedstock input of 22 kg/h) at c.a. 800 °C, using SRF samples containing different proportions of polymeric wastes ranging between 0 and 20 wt %. Gas and chars obtained as by-products were analysed to evaluate their properties and to establish valid pathways for their valorisation. The addition of polymeric wastes reduced char production but rose both tar and HCl concentrations in the gas. The SRF with 10 wt % of polymeric wastes generated the best results, producing the highest calorific value for the gas (3.5 MJ/Nm3) and the highest cold-gas efficiency (45%). Possible char applications include their use as catalysts for tar decomposition, or as an additive in construction materials. Gasification can therefore be considered a valid solution for the energetic valorisation of these SRFs.
Outdoor Insulation and Gas-Insulated Switchgears
Authors: Fofana Issouf , Brettschneider Stephan
Published: November 2022

With the growth of the world’s population and faster-developing industries, larger amounts of electric energy are needed [...]
Hate and False Metaphors: Implications to Emerging E-Participation Environment
Authors: Alathur Sreejith , Chetty Naganna , Pai Rajesh R. , Kumar Vishal , Dhelim Sahraoui
Published: November 2022

This study aims to investigate the effect of metaphorical content on e-participation in healthcare. With this objective, the study assesses the awareness and capability of e-participants to navigate through healthcare metaphors during their participation. Healthcare-related e-participation data were collected from the Twitter platform. Data analysis includes (i) awareness measurements by topic modelling and sentiment analysis and (ii) participation abilities by problem-based learning models. Findings show that a lack of effort to validate metaphors harms e-participation levels and awareness, resulting in a problematic health environment. Exploring metaphors in these intricate forums has the potential to enhance service delivery. Improving web service delivery requires valuable input from stakeholders on the application of metaphors in the health domain.
Privacy Goals for the Data Lifecycle
Authors: Henriksen-Bulmer Jane , Yucel Cagatay , Faily Shamal , Chalkias Ioannis
Published: November 2022

The introduction of Data Protection by Default and Design (DPbDD) brought in as part of the General Data Protection Regulation (GDPR) in 2018, has necessitated that businesses review how best to incorporate privacy into their processes in a transparent manner, so as to build trust and improve decisions around privacy best practice. To address this issue, this paper presents a 7-stage data lifecycle, supported by nine privacy goals that together, will help practitioners manage data holdings throughout data lifecycle. The resulting data lifecycle (7-DL) was created as part of the Ideal-Cities project, a Horizon-2020 Smart-city initiative, that seeks to facilitate data re-use and/or repurposed. We evaluate 7-DL through peer review and an exemplar worked example that applies the data lifecycle to a real-time life logging fire incident scenario, one of the Ideal-Cities use cases to demonstrate the applicability of the framework.
Special Issue on Security and Privacy in Blockchains and the IoT
Authors: Stach Christoph
Published: November 2022

The increasing digitalization in all areas of life is leading step-by-step to a data-driven society [...]
Retail Central Bank Digital Currencies (CBDC), Disintermediation and Financial Privacy: The Case of the Bahamian Sand Dollar
Authors: Wenker Kilian
Published: November 2022

The fast-growing, market-driven demand for cryptocurrencies worries central banks, as their monetary policy could be completely undermined. Central bank digital currencies (CBDCs) could offer a solution, yet our understanding of their design and consequences is in its infancy. This non-technical paper examines how The Bahamas has designed the Sand Dollar, the first real-world instance of a retail CBDC. It contrasts the Sand Dollar with definition-based specifications. The author then develops a scenario analysis to illustrate commercial bank risks. In this process, the central bank becomes a deposit monopolist, leading to high funding risks, disintermediation risks, and solvency risks for the commercial banking sector. This paper argues that restrictions and caps will be the new specifications of a regulatory framework for CBDCs if disintermediation in the banking sector is to be prevented. The anonymity of CBDCs is identified as a comparative disadvantage that will affect their adoption. These findings provide insight into governance problems facing central banks and coherently lead to the design of the Sand Dollar. This paper concludes by suggesting that combating cryptocurrencies is a task that cannot be solved by a CBDC.
The Complete Mitochondrial Genome of Hyotissa hyotis (Bivalvia: Gryphaeidae) Reveals a Unique Gene Order within Ostreoidea
Authors: Li Fengping , Fan Mingfu , Wang Shunshun , Gu Zhifeng , Wang Aimin , Liu Chunsheng , Yang Yi , Liu Shikai
Published: November 2022

The mitochondrial (mt) genome is an important tool when studying the evolution of metazoan animals. The oyster family Gryphaeidae, together with Ostreidae, is one of the two extant taxa of superfamily Ostreoidea. Up until now, the available mitochondrial genomes of oysters were all limited to family Ostreidae. In the present study, the first complete mtDNA of family Gryphaeidae represented by Hyotissa hyotis was sequenced and compared with other available ostreoid mtDNA. The mtDNA of H. hyotis is 22,185 bp in length, encoding 13 protein-coding-genes (PCGs), two ribosomal RNA (rRNA) and 23 transfer RNA (tRNA) genes. Within all the intergenic regions that range from 2 to 1528 bp, two large non-coding regions were identified. The first large non-coding region, located between Cox1 and trnA, contains 1528 nucleotides, while the second one is 1191 bp in length and positioned between Cytb and Nad2. The nucleotide composition of the whole mtDNA is A + T biased, accounting for 59.2%, with a negative AT skew value of −0.20 and a positive GC skew value of 0.33. In contrast to the mtDNA of Ostreidae, neither the split of rrnL nor rrnS was detected in that of H. hyotis. The duplication of trnW of H. hyotis was also discovered for the first time within Ostreoidea. The gene order of H. hyotis is quite different from those of ostreids, indicating extensive rearrangements within superfamily Ostreoidea. The reconstructed phylogeny supported H. hyotis as sister to Ostreidae, with the latter clade formed by Ostrea + (Saccostrea + Crassostrea). This study could provide important information for further understanding the mitochondrial evolution of oysters.
Fatty Acid and Micronutrient Profile of Longissimus Lumborum from Red Angus and Red Angus x Akaushi Cattle Finished on Grass or Grain
Authors: Krusinski Lucas , Maciel Isabella C. F. , Sergin Selin , Goeden Travis , Schweihofer Jeannine P. , Singh Sukhdeep , Rowntree Jason E. , Fenton Jenifer I.
Published: November 2022

Cattle diet and breed modify the nutritional profile of beef. The objective of this study was to compare the fatty acid (FA) and micronutrient profiles of Red Angus (RA) and RA x Akaushi (AK) crossbreed steers fed either a grass or grain diet. This two-year study randomly assigned steers to the diets using a 2 × 2 factorial experiment. FAs and micronutrients were analyzed. Diet effect was the strongest with grass-finished beef being higher in n-3 polyunsaturated FAs (p < 0.001), conjugated linoleic acid (p < 0.05), vaccenic acid (p < 0.05), iron (p < 0.001), and vitamin E (p < 0.001) compared to grain-finished beef. Breed effects were observed for lauric and myristic acids (p < 0.05), selenium (p < 0.05), and zinc (p < 0.01) with AK containing more of these compounds than RA. Diet × breed effects were non-existent. These results indicate that diet has a stronger influence than breed on modifying the nutritional profile of beef. Because of a more favorable FA and antioxidant profile, consumption of grass-finished beef could benefit human health.
Allergenicity Alleviation of Bee Pollen by Enzymatic Hydrolysis: Regulation in Mice Allergic Mediators, Metabolism, and Gut Microbiota
Authors: Tao Yuxiao , Zhou Enning , Li Fukai , Meng Lifeng , Li Qiangqiang , Wu Liming
Published: November 2022

Bee pollen as a nutrient-rich functional food has been considered for use as an adjuvant for chronic disease therapy. However, bee pollen can trigger food-borne allergies, causing a great concern to food safety. Our previous study demonstrated that the combined use of cellulase, pectinase and papain can hydrolyze allergens into peptides and amino acids, resulting in reduced allergenicity of bee pollen based on in vitro assays. Herein, we aimed to further explore the mechanisms behind allergenicity alleviation of enzyme-treated bee pollen through a BALB/c mouse model. Results showed that the enzyme-treated bee pollen could mitigate mice scratching frequency, ameliorate histopathological injury, decrease serum IgE level, and regulate bioamine production. Moreover, enzyme-treated bee pollen can modulate metabolic pathways and gut microbiota composition in mice, further supporting the alleviatory allergenicity of enzyme-treated bee pollen. The findings could provide a foundation for further development and utilization of hypoallergenic bee pollen products.
Ethanolic Cashew Leaf Extract: Antimicrobial Activity, Mode of Action, and Retardation of Spoilage Bacteria in Refrigerated Nile Tilapia Slices
Authors: Sinlapapanya Pitima , Sumpavapol Punnanee , Nirmal Nilesh , Zhang Bin , Hong Hui , Benjakul Soottawat
Published: November 2022

Phenolic compounds from cashew (Anacardium occidentale L.) leaves were extracted using ethanol with the aid of ultrasonication. Three independent variables, including ultrasound amplitude, time, and ethanol concentration, were used for response surface methodology (RSM) along with the central composite design (CCD). Under the optimized condition (70% amplitude; 40 min; 80% ethanol), the extraction yield and total phenolic contents were 24.50% and 431.16 mg GAE/g dry extract, respectively. Cashew leaf extract (CLE) had the lower minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) against Shewanella sp. than P. aeruginosa. The release of K+ and Mg2+ ions from damaged cell membranes with a coincidental decrease of TTC dehydrogenase activity were augmented when treated with CLE. In addition, scanning electron microscopic (SEM) image revealed deformations and perforation of cell walls of bacteria treated with CLE. The dominant compounds in CLE were amentoflavone, quercetin, and its glycosides. Based on microbial challenge test, the growth of P. aeruginosa and Shewanella sp. inoculated in tilapia slices were inhibited by CLE at 400 and 600 ppm within 15 days of refrigerated storage.
A Method for Capture and Detection of Crop Airborne Disease Spores Based on Microfluidic Chips and Micro Raman Spectroscopy
Authors: Zhang Xiaodong , Bian Fei , Wang Yafei , Hu Lian , Yang Ning , Mao Hanping
Published: November 2022

Airborne crop diseases cause great losses to agricultural production and can affect people’s physical health. Timely monitoring of the situation of airborne disease spores and effective prevention and control measures are particularly important. In this study, a two-stage separation and enrichment microfluidic chip with arcuate pretreatment channel was designed for the separation and enrichment of crop disease spores, which was combined with micro Raman for Raman fingerprinting of disease conidia and quasi identification. The chip was mainly composed of arc preprocessing and two separated enriched structures, and the designed chip was numerically simulated using COMSOL multiphysics5.5, with the best enrichment effect at W2/W1 = 1.6 and W4/W3 = 1.1. The spectra were preprocessed with standard normal variables (SNVs) to improve the signal-to-noise ratio, which was baseline corrected using an iterative polynomial fitting method to further improve spectral features. Raman spectra were dimensionally reduced using principal component analysis (PCA) and stability competitive adaptive weighting (SCARS), support vector machine (SVM) and back-propagation artificial neural network (BPANN) were employed to identify fungal spore species, and the best discrimination effect was achieved using the SCARS-SVM model with 94.31% discrimination accuracy. Thus, the microfluidic-chip- and micro-Raman-based methods for spore capture and identification of crop diseases have the potential to be precise, convenient, and low-cost methods for fungal spore detection.