bluuebunny/crossref_metadata_2025 huggingface dataset:
Human Resource Management and Institutional Resilience during the COVID-19 Pandemic—A Case Study from the Westfjords of Iceland
Authors: Jóhannsdóttir Lára , Cook David , Kendall Sarah , Latapí Mauricio , Chambers Catherine
Published: December 2022

Human resource management (HRM) is challenging in times of crisis, more so than when there is a stable business environment. Consequently, the overall aim of the study is to identify the preparedness, transition process, learning, and growth that businesses in the Westfjords region experienced because of the COVID-19 pandemic. In total, 42 semi-structured interviews were conducted with various members of the society, such as health authorities, healthcare workers, staff of a university center, social workers, and business owners, to gain as broad of an understanding of the local impacts as possible, as well as the coping strategies that emerging or were employed. The model employed for the analysis is an organizational resilience and organizational coping strategies model, which considers both the pre- and post-crisis situation. The core components of this model—anticipate and plan, manage and survive, and learn and grow—were the themes that were used in the thematic analysis of the interviews presented in the results. The findings of the study suggest that the preparedness aspect of the model employed, namely anticipate and plan, was negligible, as institutions were neither very ready for disruption prior to the crisis, nor had plans in place to deal with such a situation. Despite the lack of pre-crisis anticipation and planning mechanisms, examples of how institutions managed and coped during the pandemic were evident in the data. Also, during the crisis, some institutions managed to not just learn and grow, but, through adaptation to the situation, they were able to thrive. The findings also suggest both positive and negative aspects to HRM in public and private institutions. The implications of the study are theoretical in cases of alteration to the analytical model employed, practical in the case of coping mechanisms and practical solutions suggested, and have policy relevance, as the study emphasizes the importance of integrating flexible approaches to national mandates, thus enabling local conditions to be taken into account.
Distributed Fuzzy Clustering Analysis of Time-Lapse Electrical Resistivity Tomography for Water Inrush Monitoring in Coal Mines
Authors: Herui Zhang , Guolin Wang , Xiaozhen Teng , Xiaohui Zheng
Published: December 2022

The majority of water inrush accidents in coal mines are caused by mining engineering activities. To avoid water inrush accidents, the Time-lapse Electrical Resistivity Tomography (TLERT) is applied to monitor water migration in fractured zone. A great challenge for the application of TLERT monitoring is the huge and numerous time series data sets generated by monitoring systems, which are difficult to process manually. This research proposed a distributed fuzzy clustering algorithm based on kernel function estimation to analyze TLERT images automatically. The resistivity date can be classified with different cluster centroids. The fuzzy c-means algorithm was chosen to display resistivity change. The algorithm was validated using a floor water inrush model. The results indicate that the water migration in the fractured zone can be monitored automatically and the edge of the resistivity changing area can be shown clearly.
CA Energy Saving Joint Resource Optimization Scheme Based on 5G Channel Information Prediction of Machine Learning
Authors: Liu Junxia , Liu Wen
Published: December 2022

Carrier aggregation (CA) is considered as a key enabling technology to provide higher rates for users in LTE/5G networks. However, the increased transmission rate is accompanied by higher energy consumption. The existing CA energy efficiency resource optimization allocation scheme in 5G does not fully consider the following two issues, namely, the impact of delayed channel state information feedback on the rationality of resource allocation and the increasing in energy consumption caused by frequent switching of component carriers (CCs) by narrowband users; this paper proposed a CA energy-efficient joint resource optimization allocation (PEJA) scheme based on channel information prediction. The proposed scheme (PEJA) fully considers the above two issues. Firstly, the algorithm of random forest predicting channel state information is designed. On the basis, the CA energy-efficient joint resource optimization allocation (PEJA) scheme based on channel information prediction is proposed. The simulation results show that the proposed algorithm PEJA has a higher energy efficiency and throughput than the comparison algorithm under different numbers of users and different transmission powers. The PEJA algorithm is more energy efficient than the PEJA-NC algorithm, which does not consider the CC handover of narrowband users. To sum up, the proposed PEJA energy-efficient resource allocation scheme maximizes system energy efficiency and achieves a higher throughput.
Cost–Benefit Analysis of Unconventional Arterial Intersection Designs: Cairo as a Case Study
Authors: Shokry Sherif , Tanaka Shinji , Wahaballa Amr M.
Published: December 2022

Due to their innovative treatment, Unconventional Arterial Intersection Designs (UAIDs) have been developed to alleviate congestion at conventional signalized intersections, in an effort towards the sustainable development of crowded capitals. A methodological framework for economic assessment, however, has not been investigated properly for such designs, particularly under mixed traffic environments. This article aims to outline a methodological framework that can be followed for the socio-economic assessment of such designs. A cost–benefit analysis approach was developed to figure out the different determinants of costs and benefits of an overpass interchange (as a widespread treatment) and two selected UAIDs (as alternative measures). The two studied UAID schemes in this article are Continuous Flow Intersection (CFI) and Restricted Crossing U-Turn (RCUT). Seeking credible results, a set of three signalized intersections in downtown Cairo, Egypt was selected as a proof-of-concept for the developed method. PTV-VISSIM, a simulation-based platform, was utilized to estimate the benefits gained by road users. Our research objectives were to identify, evaluate, and compare the economic feasibility of the different alternatives. Compared to the overpass intersection, we found that the CFI and RCUT designs ensure higher economic efficiency, while mitigating congestion at conventional signalized intersections under heterogeneous traffic conditions.
Negative Organizations and [Negative] Powerful Relationships and How They Work against Innovation—Perspectives from Millennials, Generation Z and Other Experts
Authors: Au-Yong-Oliveira Manuel
Published: December 2022

Negative organizations, where powerful people manage to keep a negative strategy in place, one which does not benefit the firm but perpetuates their power, is a reality discussed herein. Positive organizations, led by positive leaders who do not feel threatened by brilliant employees who have brilliant ideas, may be less prominent than we think and should not be taken for granted. Following thirty years of working in organizations, both large and small, the author has come to realize that the status quo tends to be very strong, and that innovating and disrupting that balance is not only dangerous but seldom succeeds. More research is necessary in this field to prove this theory right. This article aims to point readers and researchers in the right direction and to challenge one to think just how negative organizations may be. The article is based on the experience of the author; on a look at the case of Nokia (the former handheld mobile phone division), seen to be a negative organization; as well as on in-depth personal interviews with three experts (a purposive sample) on the topic of positive versus negative organizations; and, finally, the results of two surveys (n = 116—millennials; and n = 115—Generation Z) are shared. A total of 94.8% of the Generation Z respondents (109 respondents in total) believe negative organizations to exist (where the status quo may prevail over innovative individuals and innovation to the detriment of the global organizational strategy), which is seen to be very encouraging for this research study.
Creation of a Mobile Application for Navigation for a Potential Use of People with Visual Impairment Exercising the NTRIP Protocol
Authors: Beltrán-Iza Emilio Alejandro , Noroña-Meza Cristian Oswaldo , Robayo-Nieto Alexander Alfredo , Padilla Oswaldo , Toulkeridis Theofilos
Published: December 2022

The global navigation satellite systems (GNSS) have become important in conjunction with the advancement of technology, in order to improve the accuracy of positioning and navigation on mobile devices. In the current project, a mobile application for navigation using the network transport of restricted test case modeling (RTCM) via internet protocol (NTRIP) was developed, and it has been focused on the autonomous mobility of people with visual disabilities. This occurred through a web viewer that stores the base cartography in a genome database (GDB). Such information is integrated into the application interface with Java Script language within the Android Studio platform, with a personalized design. This incorporates a screen reader for selection, navigation and direction of destinations, in addition to an early warning system for obstacles. Additionally, a differential position correction was implemented using the BKG Ntrip Client (BNC) software, for the adjustment of coordinates with the precise point positioning (PPP) method through streams in the format of RTCM with casters EPEC3, IGS03 and BCEP00BKG0. The evaluation of the application was performed using the National Standard for Spatial Data Accuracy (NSSDA), establishing 30 control points. These were obtained through the fast static method, in order to compare the horizontal accuracy of the observations in static and navigation modes between high-end and mid-range mobile devices.
Price Prediction and Classification of Used-Vehicles Using Supervised Machine Learning
Authors: Bukvić Lucija , Pašagić Škrinjar Jasmina , Fratrović Tomislav , Abramović Borna
Published: December 2022

Due to the large growth in the number of cars being bought and sold, used-car price prediction creates a lot of interest in analysis and research. The availability of used cars in developing countries results in an increased choice of used vehicles, and people increasingly choose used vehicles over new ones, which causes shortages. There is an important need to explore the enormous amount of valuable data generated by vehicle sellers. All sellers usually have the imminent need of finding a better way to predict the future behavior of prices, which helps in determining the best time to buy or sell, in order to achieve the best profit. This paper provides an overview of data-driven models for estimating the price of used vehicles in the Croatian market using correlated attributes, in terms of production year and kilometers traveled. In order to achieve this, the technique of data mining from the online seller “Njuškalo” was used. Redundant and missing values were removed from the data set during data processing. Using the method of supervised machine learning, with the use of a linear regression algorithm for predicting the prices of used cars and comparing the accuracy with the classification algorithm, the purpose of this paper is to describe the state of the vehicle market and predict price trends based on available attributes. Prediction accuracy increases with training the model with the second data set, where price growth is predicted by linear regression with a prediction accuracy of 95%. The experimental analysis shows that the proposed model predicts increases in vehicle prices and decreases in the value of vehicles regarding kilometers traveled, regardless of the year of production. The average value of the first data set is a personal vehicle with 130,000 km traveled and a price of EUR 10,000. The second set of data was extracted 3 months after the previously analyzed set, and the average price of used vehicles increased by EUR 1391 per vehicle. On the other hand, average kilometers traveled decreased by 8060 km, which justifies the increase in prices and validates the training models. The price and vehicle type are features that play an important role in predicting the price in a second-hand market, which seems to be given less importance in the current literature of prediction models.
Green Bond Issuance and Peer Firms’ Green Innovation
Authors: Wu Xia , Bu Danlu , Lian Jun , Bao Yanping
Published: December 2022

Based on the realistic background of the rapid development of China’s green bond market, this paper uses the data of China’s non-financial listed companies from 2010 to 2020 to examine the impact of green bond issuance on peer firms’ green innovation. The results show that the issuance of corporate green bonds can significantly promote the quantity and quality of peer firms’ green innovation, and this promotion effect is sustainable. The heterogeneity test shows that when the issuer of green bonds is an industry leader or the issuer is highly concerned by the media, the green innovation promotion effect of peer firms is more significant. Similarly, when the issuer and the peer firm are close competitors or in the same board network, the peer firm has a higher level of green innovation. It is further found that the green innovation behavior adopted by peer firms can significantly improve their environmental performance. The article indicates that the issuance of corporate green bonds can produce a good spillover effect of green innovation in the industry, which is conducive to China’s strategic goal of “carbon neutrality, carbon emission peak”.
Influencing Factors of Usage Intention of Metaverse Education Application Platform: Empirical Evidence Based on PPM and TAM Models
Authors: Wang Gaofeng , Shin Changhoon
Published: December 2022

We explored the influencing factors of the usage intention of a metaverse education application platform that directly influence the optimization of its service function, improve the usage intention, and realize the promotion and application of metaverse technology in the education domain. Based on the characteristics of the metaverse education application platform, we integrated the PPM (push–pull–mooring) model and the TAM (technology acceptance model) to construct the model of influencing factors of usage intention. Ultimately, 275 valid questionnaires were collected through expert demonstration, pre-investigation, formal investigation, and other processes. In addition, our paper used the SEM (structural equation model) and fsQCA (fuzzy-set qualitative comparative analysis) to analyze the influencing factors of user willingness and their configuration paths. The study found that personalized learning, contextualized teaching, perceived usefulness, perceived ease of use, social needs, and social impact play significant positive roles in the willingness to use the metaverse education platform. Meanwhile, the obtained findings show that the experience-led community-driven mode, personality-led community-driven mode, and social-led utility-driven mode serve as potential guidelines for usage intention enhancement.
A Study on Spatial Accessibility of the Urban Stadium Emergency Response under the Flood Disaster Scenario
Authors: Wang Yiche , Li Hai , Shi Yong , Yao Qian
Published: December 2022

In the context of global climate change and the rapid development of the sports industry, increasingly frequent flooding has become a significant challenge for Chinese cities today and one of the hot issues in risk management for sports events. In order to reveal the impact of flooding on the spatial accessibility of emergency response to stadiums in the central urban area within the outer ring of Shanghai, this article evaluates the accessibility of medical emergency services in the central urban area under the impact of flooding based on flood scenario simulations and GIS network analysis. Results show that under the different flooding scenarios, as the intensity of flooding increases, urban road traffic in flood-prone areas is blocked by ponding, and some stadiums are inaccessible to emergency vehicles. The scope of emergency response services for some medical institutions along the Huangpu River is significantly reduced, while emergency response times for stadiums in the riverside area are delayed considerably. Some stadiums are unable to access emergency medical services. The study’s results can offer a case reference for upgrading the level of emergency management of stadiums under urban-scale flooding and optimizing the quality of regional medical emergency services.
Firewall Anomaly Detection Based on Double Decision Tree
Authors: Lin Zhiming , Yao Zhiqiang
Published: December 2022

To solve the problems regarding how to detect anomalous rules with an asymmetric structure, which leads to the firewall not being able to control the packets in and out according to the administrator’s idea, and how to carry out an incremental detection efficiently when the new rules are added, anomaly detection algorithms based on an asymmetric double decision tree were considered. We considered the packet filter, the most common and used type of First Matching Rule, for the practical decision space of each rule and the whole policy. We adopted, based on the asymmetric double decision tree detection model, the policy equivalent decision tree and the policy decision tree of anomalies. Therefore, we can separate the policy’s effective decision space and the anomalous decision space. Using the separated decision trees can realize the optimization of the original policy and the faster incremental detection when adding new rules and generating a detailed report. The simulation results demonstrate that the proposed algorithms are superior to the other decision tree algorithms in detection speed and can achieve incremental detection. The results demonstrate that our approach can save about 33% of the time for complete detection compared with the other approaches, and the time of incremental anomaly detection compared to complete detection is about 90% of the time saved in a complex policy.
Approximation by Operators for the Sheffer–Appell Polynomials
Authors: Jeelani Mdi , Alnahdi Abeer
Published: December 2022

In this paper, we introduce a generalization of the Kantrovich–Stancu-type Szasz operator asymmetry with hybrid families of special polynomials. Additionally, we construct certain positive linear operators together with the Sheffer–Appell polynomial sequences and then obtain the properties of convergence and the order of convergence, which is symmetric to these operators. For applications, we consider certain explicit examples including mixed-type special polynomials.
Exploiting Asymmetric EEG Signals with EFD in Deep Learning Domain for Robust BCI
Authors: Huang Binwen , Xu Haiqin , Yuan Miao , Aziz Muhammad Zulkifal , Yu Xiaojun
Published: December 2022

Motor imagery (MI) is a domineering paradigm in brain–computer interface (BCI) composition, personifying the imaginary limb motion into digital commandments for neural rehabilitation and automation exertions, while many researchers fathomed myriad solutions for asymmetric MI EEG signals classification, the existence of a robust, non-complex, and subject-invariant system is far-reaching. Thereupon, we put forward an MI EEG segregation pipeline in the deep-learning domain in an effort to curtail the existing limitations. Our method amalgamates multiscale principal component analysis (MSPCA), a novel empirical Fourier decomposition (EFD) signal resolution method with Hilbert transform (HT), followed by four pre-trained convolutional neural networks for automatic feature estimation and segregation. The conceived architecture is validated upon three binary class datasets: IVa, IVb from BCI Competition III, GigaDB from the GigaScience repository, and one tertiary class dataset V from BCI competition III. The average 10-fold outcomes capitulate 98.63%, 96.33%, and 89.96%, the highest classification accuracy for the aforesaid datasets accordingly using the AlexNet CNN model in a subject-dependent context, while in subject-independent cases, the highest success score was 97.69%, outperforming the contemporary studies by a fair margin. Further experiments such as the resolution scale of EFD, comparison with other signal decomposition (SD) methods, deep feature extraction, and classification with machine learning methods also accredits the supremacy of our proposed EEG signal processing pipeline. The overall findings imply that pre-trained models are reliable in identifying EEG signals due to their capacity to maintain the time-frequency structure of EEG signals, non-complex architecture, and their potential for robust classification performance.
A Recognition Method of Ancient Architectures Based on the Improved Inception V3 Model
Authors: Wang Xinyang , Li Jiaxun , Tao Jin , Wu Ling , Mou Chao , Bai Weihua , Zheng Xiaotian , Zhu Zirui , Deng Zhuohong
Published: December 2022

Traditional ancient architecture is a symbolic product of cultural development and inheritance, with high social and cultural value. An automatic recognition model of ancient building types is one possible application of asymmetric systems, and it will be of great significance to be able to identify ancient building types via machine vision. In the context of Chinese traditional ancient buildings, this paper proposes a recognition method of ancient buildings, based on the improved asymmetric Inception V3 model. Firstly, the improved Inception V3 model adds a dropout layer between the global average pooling layer and the SoftMax classification layer to solve the overfitting problem caused by the small sample size of the ancient building data set. Secondly, migration learning and the ImageNet dataset are integrated into model training, which improves the speed of network training while solving the problems of the small scale of the ancient building dataset and insufficient model training. Thirdly, through ablation experiments, the effects of different data preprocessing methods and different dropout rates on the accuracy of model recognition were compared, to obtain the optimized model parameters. To verify the effectiveness of the model, this paper takes the ancient building dataset that was independently constructed by the South China University of Technology team as the experimental data and compares the recognition effect of the improved Inception V3 model proposed in this paper with several classical models. The experimental results show that when the data preprocessing method is based on filling and the dropout rate is 0.3, the recognition accuracy of the model is the highest; the accuracy rate of identifying ancient buildings using our proposed improved Inception V3 model can reach up to 98.64%. Compared with other classical models, the model accuracy rate has increased by 17.32%, and the average training time has accelerated by 2.29 times, reflecting the advantages of the model proposed in this paper. Finally, the improved Inception V3 model was loaded into the ancient building identification system to prove the practical application value of this research.
Phase Sensitivity Improvement in Correlation-Enhanced Nonlinear Interferometers
Authors: Liang Xinyun , Yu Zhifei , Yuan Chun-Hua , Zhang Weiping , Chen Liqing
Published: December 2022

Interferometers are widely used as sensors in precision measurement. Compared with a conventional Mach–Zehnder interferometer, the sensitivity of a correlation-enhanced nonlinear interferometer can break the standard quantum limit. Phase sensitivity plays a significant role in the enhanced performance. In this paper, we review improvement in phase estimation technologies in correlation-enhanced nonlinear interferometers, including SU(1,1) interferometer and SU(1,1)-SU(2) hybrid interferometer, and so on, and the applications in quantum metrology and quantum sensing networks.
Taking Sides: Asymmetries in the Evolution of Human Brain Development in Better Understanding Autism Spectrum Disorder
Authors: Leisman Gerry , Melillo Robert , Melillo Ty , Machado Calixto , Machado-Ferrer Yanin , Chinchilla Mauricio , Carmeli Eli
Published: December 2022

Confirmation from structural, functional, and behavioral studies agree and suggest a configuration of atypical lateralization in individuals with autistic spectrum disorders (ASD). It is suggested that patterns of cortical and behavioral atypicality are evident in individuals with ASDs with atypical lateralization being common in individuals with ASDs. The paper endeavors to better understand the relationship between alterations in typical cortical asymmetries and functional lateralization in ASD in evolutionary terms. We have proposed that both early genetic and/or environmental influences can alter the developmental process of cortical lateralization. There invariably is a “chicken or egg” issue that arises whether atypical cortical anatomy associated with abnormal function, or alternatively whether functional atypicality generates abnormal structure.
Techno-Economic Analysis of a Seasonal Thermal Energy Storage System with 3-Dimensional Horizontally Directed Boreholes
Authors: Beaufait Robert , Villasmil Willy , Ammann Sebastian , Fischer Ludger
Published: December 2022

Geothermal energy storage provides opportunities to store renewable energy underground during summer for utilization in winter. Vertically oriented systems have been the standard when employing boreholes as the means to charge and discharge the underground. Horizontally oriented borehole storage systems provide an application range with specific advantages over vertically oriented systems. They are not limited to the surface requirements needed for installation with vertical systems and have the potential to limit storage losses. Horizontal systems can be incorporated into the built environment and utilize underground storage sites below existing infrastructure. An experimental study examines configurations using a mix of renewable energy (photovoltaic panels) and grid energy to charge a storage system during summer for use during winter. A comparison of five different borehole configurations at three different loading temperatures was composed using an experimentally validated numerical model. The horizontal systems studied and analyzed in this work showed improved performance with scale and charging temperature. This paper supports further exploration into specific use cases for horizontal borehole thermal energy storage systems and suggests applications which would take advantage of better performance at scale.
Reducing Virus Transmission from Heating, Ventilation, and Air Conditioning Systems of Urban Subways
Authors: Nazari Ata , Hong Jiarong , Taghizadeh-Hesary Farzad , Taghizadeh-Hesary Farhad
Published: December 2022

Aerosols carrying the virus inside enclosed spaces is an important mode of transmission for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as supported by growing evidence. Urban subways are one of the most frequented enclosed spaces. The subway is a utilitarian and low-cost transit system in modern society. However, studies are yet to demonstrate patterns of viral transmission in subway heating, ventilation, and air conditioning (HVAC) systems. To fill this gap, we performed a computational investigation of the airflow (and associated aerosol transmission) in an urban subway cabin equipped with an HVAC system. We employed a transport equation for aerosol concentration, which was added to the basic buoyant solver to resolve the aerosol transmission inside the subway cabin. This was achieved by considering the thermal, turbulent, and induced ventilation flow effects. Using the probability of encountering aerosols on sampling surfaces crossing the passenger breathing zones, we detected the highest infection risk zones inside the urban subway under different settings. We proposed a novel HVAC system that can impede aerosol spread, both vertically and horizontally, inside the cabin. In the conventional model, the maximum probability of encountering aerosols from the breathing of infected individuals near the fresh-air ducts was equal to 51.2%. This decreased to 3.5% in the proposed HVAC model. Overall, using the proposed HVAC system for urban subways led to a decrease in the mean value of the probability of encountering the aerosol by approximately 84% compared with that of the conventional system.
T Cells Contribute to Pathological Responses in the Non-Targeted Rat Heart following Irradiation of the Kidneys
Authors: Lenarczyk Marek , Alsheikh Ammar J. , Cohen Eric P. , Schaue Dörthe , Kronenberg Amy , Geurts Aron , Klawikowski Slade , Mattson David , Baker John E.
Published: December 2022

Heart disease is a significant adverse event caused by radiotherapy for some cancers. Identifying the origins of radiogenic heart disease will allow therapies to be developed. Previous studies showed non-targeted effects manifest as fibrosis in the non-irradiated heart after 120 days following targeted X-irradiation of the kidneys with 10 Gy in WAG/RijCmcr rats. To demonstrate the involvement of T cells in driving pathophysiological responses in the out-of-field heart, and to characterize the timing of immune cell engagement, we created and validated a T cell knock downrat on the WAG genetic backgrou nd. Irradiation of the kidneys with 10 Gy of X-rays in wild-type rats resulted in infiltration of T cells, natural killer cells, and macrophages after 120 days, and none of these after 40 days, suggesting immune cell engagement is a late response. The radiation nephropathy and cardiac fibrosis that resulted in these animals after 120 days was significantly decreased in irradiated T cell depleted rats. We conclude that T cells function as an effector cell in communicating signals from the irradiated kidneys which cause pathologic remodeling of non-targeted heart.
Effect of Low-Molecular Organic Acids on the Migration Characteristics of Nickel in Reclaimed Soil from The Panyi Mine Area in China
Authors: Zheng Yonghong , Lu Jiangwei , Zhang Zhiguo , Li Yating , Tan Yuning , Cai Weiqing , Ma Chengnan , Chen Fangling
Published: December 2022

This study investigated the effects of low molecular weight organic acids (citric acid and malic acid) on the migration properties of nickel in soil. A reclaimed soil sample was obtained from the Panyi Mine in Huainan City, China. The effects of adding different concentrations of Ni, citric acid (CA) and malic acid (MA) were assessed on the migration and transformation of soil Ni forms. The results showed: (1) An increase in soil Ni activity with increasing Ni concentrations. (2) An increased proportion of exchangeable forms of Ni in soil with increased malic acid and citric acid concentrations, effectively promoting Ni mobility. In addition, the active Ni fraction in reclaimed soil increased significantly with increasing concentrations of citric and malic acid. The nickel activation effect of citric acid was found to be higher than that of malic acid. (3) The activation effect of organic acids on Ni weakened with aging, exhibiting a gradual transformation from the loosely bound form of Ni, to the strongly bound form. The results of this study provide a theoretical basis for improving the effectiveness and efficiency of the phytoremediation techniques used for the treatment of Ni-polluted soils.
Fatal Methanol Poisoning Caused by Drinking Industrial Alcohol: Silesia Region, Poland, April–June 2022
Authors: Tomsia Marcin , Głaz Małgorzata , Nowicka Joanna , Cieśla Julia , Sosnowski Maciej , Chełmecka Elżbieta
Published: December 2022

Methanol poisonings caused by drinking industrial alcohol remain a severe problem worldwide. Education on types of alcohol and their harmfulness and legal regulations limiting the industrial alcohol trade seem to be the keys to reducing the number of poisonings. Methanol distribution in different tissues after absorption is not well understood. This research aimed to quantify the methanol and formic acid distribution in body fluids and tissue material in post-mortem samples collected from 19 fatal victims of massive intoxication with industrial alcohol in the Silesia Region (Poland) who died between April and June 2022. The samples were analyzed using a gas chromatography–flame ionization detector (GC-FID), and correlation coefficients for methanol and formic acid were determined. The results show a wide distribution of methanol and formic acid in human post-mortem biological fluids (blood, urine, vitreous humor, bile, and cerebrospinal fluid) and tissues (muscle, kidney, liver, spleen, lung, and brain). The strongest correlation for methanol concentration in blood and body fluids/tissues was obtained in the cerebrospinal fluid (r = 0.997) and for formic acid in muscle tissue (r = 0.931). The obtained results may be a valuable tool in toxicological analysis and improve medical standards of early diagnosis and targeted treatment.
Comparative Analysis of Aristolochic Acids in Aristolochia Medicinal Herbs and Evaluation of Their Toxicities
Authors: Zhang Shu-Han , Wang Yun , Yang Jing , Zhang Dan-Dan , Wang Yan-Lei , Li Shu-Hui , Pan Ying-Ni , Zhang Hua-Min , Sun Yi
Published: December 2022

Aristolochic acids (AAs) are a group of nitrophenanthrene carboxylic acids present in many medicinal herbs of the Aristolochia genus that may cause irreversible hepatotoxicity, nephrotoxicity, genotoxicity and carcinogenicity. However, the specific profile of AAs and their toxicity in Aristolochia plants, except for AAs Ι and ΙΙ, still remain unclear. In this study, a total of 52 batches of three medicinal herbs belonging to the Aristolochia family were analyzed for their AA composition profiles and AA contents using the UPLC-QTOF-MS/MS approach. The studied herbs were A. mollissima Hance (AMH), A. debilis Sieb.etZucc (ADS), and A. cinnabaria C.Y.Cheng (ACY). Chemometrics methods, including PCA and OPLS-DA, were used for the evaluation of the Aristolochia medicinal herbs. Additionally, cytotoxicity and genotoxicity of the selected AAs and the extracts of AMH and ADS were evaluated in a HepG2 cell line using the MTT method and a Comet assay, respectively. A total of 44 AAs, including 23 aristolochic acids and 21 aristolactams (ALs), were detected in A. mollissima. Moreover, 41 AAs (23 AAs and 18 ALs) were identified from A. debilis Sieb, and 45 AAs (29 AAs and 16 ALs) were identified in A. cinnabaria. Chemometrics results showed that 16, 19, and 22 AAs identified in AMH, ADS, and ACY, respectively, had statistical significance for distinguishing the three medicinal herbs of different origins. In the cytotoxicity assay, compounds AL-BΙΙ, AAΙ and the extract of AMH exhibited significant cytotoxicities against the HepG2 cell line with the IC50 values of 0.2, 9.7 and 50.2 μM, respectively. The results of the Comet assay showed that AAΙ caused relatively higher damage to cellular DNA (TDNA 40–95%) at 50 μM, while AAΙΙ, AMH and ADS extracts (ranged from 10 to 131 μM) caused relatively lower damage to cellular DNA (TDNA 5–20%).
Potential Endocrine Disruption of Cyanobacterial Toxins, Microcystins and Cylindrospermopsin: A Review
Authors: Casas-Rodriguez Antonio , Cameán Ana M. , Jos Angeles
Published: December 2022

Microcystins (MCs) and cylindrospermopsin (CYN), although classified as hepatotoxins and cytotoxins, respectively, have been shown to also induce toxic effects in many other systems and organs. Among them, their potential endocrine disruption (ED) activity has been scarcely investigated. Considering the increasing relevance of ED on humans, mammals, and aquatic organisms, this work aimed to review the state-of-the-art regarding the toxic effects of MCs and CYN at this level. It has been evidenced that MCs have been more extensively investigated than CYN. Reported results are contradictory, with the presence or absence of effects, but experimental conditions also vary to a great extent. In general, both toxins have shown ED activity mediated by very different mechanisms, such as estrogenic responses via a binding estrogen receptor (ER), pathological changes in several organs and cells (testis, ovarian cells), and a decreased gonad-somatic index. Moreover, toxic effects mediated by reactive oxygen species (ROS), changes in transcriptional responses on several endocrine axes and steroidogenesis-related genes, and changes in hormone levels have also been reported. Further research is required in a risk assessment frame because official protocols for assessment of endocrine disrupters have not been used. Moreover, the use of advanced techniques would aid in deciphering cyanotoxins dose-response relationships in relation to their ED potential.
Comparative Analysis of Tomato Brown Rugose Fruit Virus Isolates Shows Limited Genetic Diversity
Authors: Abrahamian Peter , Cai Weili , Nunziata Schyler O. , Ling Kai-Shu , Jaiswal Namrata , Mavrodieva Vessela A. , Rivera Yazmín , Nakhla Mark K.
Published: December 2022

Tomato is an important vegetable in the United States and around the world. Recently, tomato brown rugose fruit virus (ToBRFV), an emerging tobamovirus, has impacted tomato crops worldwide and can result in fruit loss. ToBRFV causes severe symptoms, such as mosaic, puckering, and necrotic lesions on leaves; other symptoms include brown rugose and marbling on fruits. More importantly, ToBRFV can overcome resistance in tomato cultivars carrying the Tm-22 locus. In this study, we recovered ToBRFV sequences from tomato seeds, leaves, and fruits from the U.S., Mexico, and Peru. Samples were pre-screened using a real-time RT-PCR assay prior to high-throughput sequencing. Virus draft genomes from 22 samples were assembled and analyzed against more than 120 publicly available genomes. Overall, most sequenced isolates were similar to each other and did not form a distinct population. Phylogenetic analysis revealed three clades within the ToBRFV population. Most of the isolates (95%) clustered in clade 3. Genetic analysis revealed differentiation between the three clades indicating minor divergence occurring. Overall, pairwise identity showed limited genetic diversity among the isolates in this study with worldwide isolates, with a pairwise identity ranging from 99.36% and 99.97%. The overall population is undergoing high gene flow and population expansion with strong negative selection pressure at all ToBRFV genes. Based on the results of this study, it is likely that the limited ToBRFV diversity is associated with the rapid movement and eradication of ToBRFV-infected material between countries.
In Vitro Diagnostic Assay to Detect SARS-CoV-2-Neutralizing Antibody in Patient Sera Using Engineered ACE-2 Mini-Protein
Authors: Pereira de Jesus Bruna Andersen , Gomes Anderson Albino , Clark Alex E. , Rodrigues Tayse Andrade , Ledgerwood-Lee Melissa , Van Zant Westley , Brickner Howard , Wang Meiqiao , Blum David L. , Cassera Maria B. , Carlin Aaron F. , Aronoff-Spencer Eliah S. , da Silva Gustavo Felippe , Magalhães Maria de Lourdes Borba , Ray Partha
Published: December 2022

The recent development and mass administration of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) vaccines allowed for disease control, reducing hospitalizations and mortality. Most of these vaccines target the SARS-CoV-2 Spike (S) protein antigens, culminating with the production of neutralizing antibodies (NAbs) that disrupt the attachment of the virus to ACE2 receptors on the host cells. However, several studies demonstrated that the NAbs typically rise within a few weeks after vaccination but quickly reduce months later. Thus, multiple booster administration is recommended, leading to vaccination hesitancy in many populations. Detecting serum anti-SARS-CoV-2 NAbs can instruct patients and healthcare providers on correct booster strategies. Several in vitro diagnostics kits are available; however, their high cost impairs the mass NAbs diagnostic testing. Recently, we engineered an ACE2 mimetic that interacts with the Receptor Binding Domain (RBD) of the SARS-2 S protein. Here we present the use of this engineered mini-protein (p-deface2 mut) to develop a detection assay to measure NAbs in patient sera using a competitive ELISA assay. Serum samples from twenty-one patients were tested. Nine samples (42.8%) tested positive, and twelve (57.1%) tested negative for neutralizing sera. The data correlated with the result from the standard commercial assay that uses human ACE2 protein. This confirmed that p-deface2 mut could replace human ACE2 in ELISA assays. Using bacterially expressed p-deface2 mut protein is cost-effective and may allow mass SARS-CoV-2 NAbs detection, especially in low-income countries where economical diagnostic testing is crucial. Such information will help providers decide when a booster is required, reducing risks of reinfection and preventing the administration before it is medically necessary.
Advanced Nanomedicine for High-Risk HPV-Driven Head and Neck Cancer
Authors: Xu Qiang , Chen Ye , Jin Yuan , Wang Zhiyu , Dong Haoru , Kaufmann Andreas M. , Albers Andreas E. , Qian Xu
Published: December 2022

The incidence of high-risk Human Papillomavirus (HR-HPV)-driven head and neck squamous cell carcinoma (HNSCC) is on the rise globally. HR-HPV-driven HNSCC displays molecular and clinical characteristics distinct from HPV-uninvolved cases. Therapeutic strategies for HR-HPV-driven HNSCC are under investigation. HR-HPVs encode the oncogenes E6 and E7, which are essential in tumorigenesis. Meanwhile, involvement of E6 and E7 provides attractive targets for developing new therapeutic regimen. Here we will review some of the recent advancements observed in preclinical studies and clinical trials on HR-HPV-driven HNSCC, focusing on nanotechnology related methods. Materials science innovation leads to great improvement for cancer therapeutics including HNSCC. This article discusses HPV-E6 or -E7- based vaccines, based on plasmid, messenger RNA or peptide, at their current stage of development and testing as well as how nanoparticles can be designed to target and access cancer cells and activate certain immunology pathways besides serving as a delivery vehicle. Nanotechnology was also used for chemotherapy and photothermal treatment. Short interference RNA targeting E6/E7 showed some potential in animal models. Gene editing by CRISPR-CAS9 combined with other treatments has also been assessed. These advancements have the potential to improve the outcome in HR-HPV-driven HNSCC, however breakthroughs are still to be awaited with nanomedicine playing an important role.
Point-of-Care Testing for Sensitive Detection of the African Swine Fever Virus Genome
Authors: Elnagar Ahmed , Blome Sandra , Beer Martin , Hoffmann Bernd
Published: December 2022

African swine fever (ASF) is a contagious viral hemorrhagic disease that affects domestic pigs and wild boar. The disease is notifiable to the World Organization of Animal Health (WOAH), and causes significant deaths and economic losses. There is currently no fully licensed vaccine available. As a result, early identification of the causative agent, ASF virus (ASFV), is crucial for the implementation of control measures. PCR and real-time PCR are the WOAH-recommended standard methods for the direct detection of ASFV. However, under special field conditions or in simple or remote field laboratories, there may be no sophisticated equipment or even stable electricity available. Under these circumstances, point-of-care systems can be put in place. Along these lines, a previously published, rapid, reliable, and electricity-free extraction method (TripleE) was used to isolate viral nucleic acid from diagnostic specimens. With this tool, nucleic acid extraction from up to eight diagnostic samples can be realized in one run in less than 10 min. In addition, the possibility of completely omitting viral DNA extraction was analyzed with so-called direct real-time PCR protocols using ASFV original samples diluted to 1:40 in RNase-free water. Furthermore, three real-time PCR cyclers, developed for use under field conditions (IndiField, Liberty16 and UF-300 GenecheckerTM), were comparatively applied for the sensitive high-speed detection of ASFV genomes, with overall PCR run times between 20 and 54 min. Depending on the viral DNA extraction/releasing method used and the point-of-care cycler applied, a total time for detection of 30 to 60 min for up to eight samples was feasible. As expected, the limitations in analytical sensitivity were positively correlated to the analysis time. These limitations are acceptable for ASFV diagnostics due to the expected high ASFV genome loads in diseased animals or carcasses.
Knowledge, Attitudes, and Behaviors Regarding Lyme Borreliosis Prevention in the Endemic Area of Northeastern Poland
Authors: Wozinska Marta , Toczylowski Kacper , Lewandowski Dawid , Bojkiewicz Ewa , Sulik Artur
Published: December 2022

(1) Background: The incidence of Lyme borreliosis (LB) is increasing in Europe. The new LB vaccine is still in clinical development, thus the dissemination of knowledge about the disease is essential. We assessed the knowledge, attitudes and preventive practices (KAP) against tick-borne diseases (TBDs) of people living in the endemic area in northeastern Poland. (2) Methods: We surveyed 406 adults using a 37-item anonymous paper survey. The data were analyzed with regression models. (3) Results: The two most popular knowledge sources were the Internet and doctors, selected by 77.8% and 53.4%, respectively. Respondents felt moderately knowledgeable about TBDs and tick bite prophylaxis (median scores 5/10, and 6/10, respectively), considered TBDs to be a significant health threat (median 8/10), attributed high risk to tick mouthparts remaining in the skin after tick removal (median 10/10), and shared multiple misconceptions regarding LB transmission, symptoms, and management. General knowledge scores (GKS) about TBDs and tick protection practices scores (TPS) were moderate (65.0%; IQR, 55.8–71.7%, 63.6%; 54.5–72.7%, respectively). Only 48.0% had a positive attitude towards TBE vaccination. A recent tick-bite was associated with higher GKS (OR, 2.55; 95% CI, 1.27–5.10; p = 0.008), higher TPS (OR 4.76, 95% CI, 2.0–11.1; p < 0.001), and a positive attitude towards TBE vaccine (OR 2.10, 1.07–4.10, p = 0.030). A positive vaccine attitude was also associated with obtaining TBD knowledge from doctors and other verified sources (OR, 2.654, 1.66–4.23; p < 0.001). Age, place of residence, and frequent exposure to ticks in green areas were not associated with GKS, TPS, nor vaccine attitude. (4) Conclusions: Increased risk perceptions are associated with adoption of behaviors preventing TBDs. Medical professionals play an important role in communicating knowledge about TBDs. There is a need to revise current communication strategies with respect to tick bites and prevention of LB and other TBDs.