bluuebunny/crossref_metadata_2025 huggingface dataset:
Mapping Residential Vacancies with Multisource Spatiotemporal Data: A Case Study in Beijing
Authors: Li Xiaoting , Gong Peng
Published: January 2022

China has undergone rapid urbanization in the past few decades, and it has been accompanied by overdevelopment. Residential vacancies caused by overdevelopment result in a waste of resources and generate greenhouse gases associated with land surface changes. Due to the poor spatial resolution and limited availability of data, previous studies performed analyses at low resolutions at the county scale, thus lacking spatial detail. In addition, they used complicated subjective indicators difficult to apply to cities of various sizes across China. To understand the detailed spatial pattern of residential vacancies in megacities, we designed a more generally applicable approach with multisource high-resolution spatiotemporal data and tested it in Beijing, the capital of China. At first, a statistical regression with features derived from multisource data was used. Then, the predicted values of the regression function were used as standard heat values, and the observed heat value in each unit was divided by the corresponding standard heat value. Next, residential vacancies were estimated by calculating the quantiles of these division results in all analysis units. This approach requires no prior knowledge or complicated indicators and can be easily applied across cities in China, which is beneficial for development planning at the provincial and national levels.
Visualization-Driven Time-Series Extraction from Wearable Systems Can Facilitate Differentiation of Passive ADL Characteristics among Stroke and Healthy Older Adults
Authors: John Joby , Soangra Rahul
Published: January 2022

Wearable technologies allow the measurement of unhindered activities of daily living (ADL) among patients who had a stroke in their natural settings. However, methods to extract meaningful information from large multi-day datasets are limited. This study investigated new visualization-driven time-series extraction methods for distinguishing activities from stroke and healthy adults. Fourteen stroke and fourteen healthy adults wore a wearable sensor at the L5/S1 position for three consecutive days and collected accelerometer data passively in the participant’s naturalistic environment. Data from visualization facilitated selecting information-rich time series, which resulted in classification accuracy of 97.3% using recurrent neural networks (RNNs). Individuals with stroke showed a negative correlation between their body mass index (BMI) and higher-acceleration fraction produced during ADL. We also found individuals with stroke made lower activity amplitudes than healthy counterparts in all three activity bands (low, medium, and high). Our findings show that visualization-driven time series can accurately classify movements among stroke and healthy groups using a deep recurrent neural network. This novel visualization-based time-series extraction from naturalistic data provides a physical basis for analyzing passive ADL monitoring data from real-world environments. This time-series extraction method using unit sphere projections of acceleration can be used by a slew of analysis algorithms to remotely track progress among stroke survivors in their rehabilitation program and their ADL abilities.
Patient Specific Numerical Modeling for Renal Blood Monitoring Using Electrical Bio-Impedance
Authors: Al-harosh Mugeb , Chernikov Egor , Shchukin Sergey
Published: January 2022

Knowledge of renal blood circulation is considered as an important physiological value, particularly for fast detection of acute allograft rejection as well as the management of critically ill patients with acute renal failure. The electrical impedance signal obtained from kidney with an appropriate electrode system and optimal electrode system position regarding to the kidney projection on skin surface reflects the nature of renal blood circulation and tone of renal blood vessels. This paper proposes a specific numerical modelling based on prior information from MRI-data. The numerical modelling was conducted for electrical impedance change estimation due to renal blood distribution. The proposed model takes into the account the geometrical and electrophysiological parameters of tissues around the kidney as well as the actual blood distribution within the kidney. The numerical modelling had shown that it is possible to register the electrical impedance signal caused by renal blood circulation with an electrode system commensurate with the size of kidney, which makes it possible to reduce the influence of surrounding tissues and organs. Experimental studies were obtained to prove the numerical modelling and the effectiveness of developed electrode systems based on the obtained simulation results. The obtained electrical impedance signal with the appropriate electrode system shows very good agreement with the renal blood change estimated using Doppler ultrasound. For the measured electrical impedance signal, it is possible to obtain the amplitude-time parameters, which reflect the hemodynamic characteristics of the kidneys and used in diagnostics, which is the subject of further research.
A Probabilistic Approach to Estimating Allowed SNR Values for Automotive LiDARs in “Smart Cities” under Various External Influences
Authors: Meshcheryakov Roman , Iskhakov Andrey , Mamchenko Mark , Romanova Maria , Uvaysov Saygid , Amirgaliyev Yedilkhan , Gromaszek Konrad
Published: January 2022

The paper proposes an approach to assessing the allowed signal-to-noise ratio (SNR) for light detection and ranging (LiDAR) of unmanned autonomous vehicles based on the predetermined probability of false alarms under various intentional and unintentional influencing factors. The focus of this study is on the relevant issue of the safe use of LiDAR data and measurement systems within the “smart city” infrastructure. The research team analyzed and systematized various external impacts on the LiDAR systems, as well as the state-of-the-art approaches to improving their security and resilience. It has been established that the current works on the analysis of external influences on the LiDARs and methods for their mitigation focus mainly on physical (hardware) approaches (proposing most often other types of modulation and optical signal frequencies), and less often software approaches, through the use of additional anomaly detection techniques and data integrity verification systems, as well as improving the efficiency of data filtering in the cloud point. In addition, the sources analyzed in this paper do not offer methodological support for the design of the LiDAR in the very early stages of their creation, taking into account a priori assessment of the allowed SNR threshold and probability of detecting a reflected pulse and the requirements to minimize the probability of “missing” an object when scanning with no a priori assessments of the detection probability characteristics of the LiDAR. The authors propose a synthetic approach as a mathematical tool for designing a resilient LiDAR system. The approach is based on the physics of infrared radiation, the Bayesian theory, and the Neyman–Pearson criterion. It features the use of a predetermined threshold for false alarms, the probability of interference in the analytics, and the characteristics of the LiDAR’s receivers. The result is the analytical solution to the problem of calculating the allowed SNR while stabilizing the level of “false alarms” in terms of background noise caused by a given type of interference. The work presents modelling results for the “false alarm” probability values depending on the selected optimality criterion. The efficiency of the proposed approach has been proven by the simulation results of the received optical power of the LiDAR’s signal based on the calculated SNR threshold and noise values.
Analysis of the Results of the Borowiec SLR Station (7811) for the Period 1993–2019 as an Example of the Quality Assessment of Satellite Laser Ranging Stations
Authors: Schillak Stanisław , Lejba Paweł , Michałek Piotr , Suchodolski Tomasz , Smagło Adrian , Zapaśnik Stanisław
Published: January 2022

This paper presents the results of an orbital analysis of satellite laser ranging data performed by the Borowiec SLR station (7811) in the period from July 1993 to December 2019, including the determination of the station positions and velocity. The analysis was performed using the GEODYN-II orbital program for the independent monthly orbital arcs from the results of the LAGEOS-1 and LAGEOS-2 satellites. Each arc was created from the results of the laser observations of a dozen or so selected stations, which were characterized by a large number of normal points and a good quality of observations. The geocentric and topocentric coordinates of the station were analyzed. Factors influencing the uncertainty of the measurements were determined: the number of the normal points, the dispersion of the normal points in relation to the orbits, and the long-term stability of the systematic deviations. The position leap at the end of 2002 and its interpretation in ITRF2014 were analyzed. The 3D stability of the determined positions throughout the period of study was equal to 12.7 mm, with the uncertainty of determination being at the level of 4.3 mm. A very high compliance of the computed velocity of the Borowiec SLR station (24.9 mm/year) with ITRF2014 (25.0 mm/year) was found.
An Arithmetic-Trigonometric Optimization Algorithm with Application for Control of Real-Time Pressure Process Plant
Authors: Devan P. Arun Mozhi , Hussin Fawnizu Azmadi , Ibrahim Rosdiazli B. , Bingi Kishore , Nagarajapandian M. , Assaad Maher
Published: January 2022

This paper proposes a novel hybrid arithmetic–trigonometric optimization algorithm (ATOA) using different trigonometric functions for complex and continuously evolving real-time problems. The proposed algorithm adopts different trigonometric functions, namely sin, cos, and tan, with the conventional sine cosine algorithm (SCA) and arithmetic optimization algorithm (AOA) to improve the convergence rate and optimal search area in the exploration and exploitation phases. The proposed algorithm is simulated with 33 distinct optimization test problems consisting of multiple dimensions to showcase the effectiveness of ATOA. Furthermore, the different variants of the ATOA optimization technique are used to obtain the controller parameters for the real-time pressure process plant to investigate its performance. The obtained results have shown a remarkable performance improvement compared with the existing algorithms.
A Smart Colorimetric Platform for Detection of Methanol, Ethanol and Formic Acid
Authors: Sha Mizaj Shabil , Maurya Muni Raj , Geetha Mithra , Kumar Bijandra , Abdullah Aboubakr M. , Sadasivuni Kishor Kumar
Published: January 2022

Carbon dioxide (CO2) is a greenhouse gas in the atmosphere and scientists are working on converting it to useful products, thereby reducing its quantity in the atmosphere. For converting CO2, different approaches are used, and among them, electrochemistry is found to be the most common and more efficient technique. Current methods for detecting the products of electrochemical CO2 conversion are time-consuming and complex. To combat this, a simple, cost-effective colorimetric method has been developed to detect methanol, ethanol, and formic acid, which are formed electrochemically from CO2. In the present work, the highly efficient sensitive dyes were successfully established to detect these three compounds under optimized conditions. These dyes demonstrated excellent selectivity and showed no cross-reaction with other products generated in the CO2 conversion system. In the analysis using these three compounds, this strategy shows good specificity and limit of detection (LOD, ~0.03–0.06 ppm). A cost-effective and sensitive Internet of Things (IoT) colorimetric sensor prototype was developed to implement these dyes systems for practical and real-time application. Employing the dyes as sensing elements, the prototype exhibits unique red, green, and blue (RGB) values upon exposure to test solutions with a short response time of 2 s. Detection of these compounds via this new approach has been proven effective by comparing them with nuclear magnetic resonance (NMR). This novel approach can replace heavy-duty instruments such as high-pressure liquid chromatography (HPLC), gas chromatography (G.C.), and NMR due to its extraordinary selectivity and rapidity.
The Organization of Animal Protection Investigations and the Animal Harm Spectrum: Canadian Data, International Lessons
Authors: Coulter Kendra
Published: January 2022

This paper offers the first overview of the Canadian animal cruelty investigations landscape. First, the public and private sector organizations responsible for enforcement are explained, followed by examination of the implications of this patchwork for reporting suspected cruelty. Key statistical data are presented about the types of issues and cases and investigator responses. Initial recommendations are then proposed, and the value of the animal harm spectrum is discussed, including how it can be mobilized to strengthen the operations of animal protection work and animal welfare policy across nations.
An Application of Natural Language Processing to Classify What Terrorists Say They Want
Authors: Bridgelall Raj
Published: January 2022

Knowing what perpetrators want can inform strategies to achieve safe, secure, and sustainable societies. To help advance the body of knowledge in counterterrorism, this research applied natural language processing and machine learning techniques to a comprehensive database of terrorism events. A specially designed empirical topic modeling technique provided a machine-aided human decision process to glean six categories of perpetrator aims from the motive text narrative. Subsequently, six different machine learning models validated the aim categories based on the accuracy of their association with a different narrative field, the event summary. The ROC-AUC scores of the classification ranged from 86% to 93%. The Extreme Gradient Boosting model provided the best predictive performance. The intelligence community can use the identified aim categories to help understand the incentive structure of terrorist groups and customize strategies for dealing with them.
Evaluation of Ecosystem Services in Mining Basins: An Application in the Piedmont Region (Italy)
Authors: Assumma Vanessa , Bottero Marta , Caprioli Caterina , Datola Giulia , Mondini Giulio
Published: January 2022

Mining activities impact on the territorial system in various ways, affecting its environmental and socio-economic components. Specific evaluation tools can support decision-making processes in the context of the sustainable planning and management of mining activities. Within the evaluation procedures of mining activities, a growing interest in the analysis of Ecosystem Services (ES) is emerging. ES refer to the benefits that the natural system delivers to society, linking the health of ecosystems and human well-being. Starting from a real-world case related to the adoption of the Regional Plan of Mining Activities (PRAE) of the Piedmont region (Northern Italy), the paper aims to explore the ES valuation by considering three different mining quarries. The state of the art of the basins is compared with alternative planning scenarios from the point of view of the ES produced. The valuation is developed through GIS and the Simulsoil software, detecting the biophysical benefits produced and estimating their economic performance. The simulation results can be used to support the formulation of planning strategies, estimating the trade-offs in terms of competitive land-use values. The study also demonstrates that the integration of ES into Strategic Environmental Assessment (SEA) can produce a comprehensive impact assessment of a mining project, guaranteeing the protection and valorisation of the environmental system.
Mining-Induced Anthropogenic Transformations of the Wielka Kopa Massif—Case Study of Rudawy Janowickie, the Sudetes
Authors: Duchnowska Magdalena
Published: January 2022

The article presents a detailed description of the transformation of the terrain relief due to long-lasting underground and surface mining activity in the Wielka Kopa massif at Rudawy Janowickie (the Western Sudetes mountains). It includes both the anthropogenic forms and secondary transformations of these forms due to natural land-shaping processes, ongoing after mining had been discontinued. The location deserves special attention, as it shows particularly significant mining-induced relief transformations, whose scale can be compared to those of the Walbrzych hard coal basin and the Turoszow lignite basin. The presented object is also an important historical heritage and deserves special attention due to its high research, didactic and tourism potential. The article offers a description of the characteristics and a classification of the anthropogenic forms in the area of Wielka Kopa, which are hoped to serve as an aid in planning future actions related to the revitalization of the area and also as an example for future descriptions of other closed mining facilities.
Does Culture Matter? Measuring Cross-Country Perceptions of CSR Communication Campaigns about COVID-19
Authors: Colleoni Elanor , Romenti Stefania , Valentini Chiara , Badham Mark , Choi Sung In , Kim Sungsu , Jin Yan
Published: January 2022

The COVID-19 pandemic has brought several challenges to businesses and societies. In response, many corporations have supported local communities and authorities in the management of the pandemic. Although these initiatives, which can be considered forms of corporate social responsibility (CSR), were highly coupled with explicit CSR communication campaigns, little is known about whether these campaigns were effective. Previous research indicates that culture can shape people’s perceptions of CSR initiatives and communications, suggesting that businesses pay attention to careful consideration of cultural norms for effective CSR communication. However, the COVID-19 pandemic as a new CSR setting may challenge earlier findings. This study empirically investigates whether three cultural factors (individualism/collectivism, uncertainty avoidance, and power distance) affect public perceptions measured as recall of and favorability towards corporate COVID-19 response initiatives across six countries. Findings from a representative survey of adults across these countries show that respondents in individualistic and collectivistic countries recall these CSR communication campaigns about these corporate COVID-19 response initiatives quite differently, and these are related to differences in power distance and uncertainty avoidance. However, no difference was found in overall corporate favorability, indicating that cultural factors did not affect levels of favorability towards such initiatives. This, we argue, can be explained by the global dimension of the COVID-19 pandemic, which is the context of these CSR initiatives. This study contributes to CSR communication literature with empirical findings from a global pandemic setting. It offers businesses and managers empirical grounds to understand the communicative impact of COVID-19 response initiatives, which can inform future CSR actions.
Factors Affecting Zoo Visitors’ Conservation Beliefs and Knowledge of Large Carnivores in 2009 and a Dozen Years Later
Authors: Oražem Vesna , Majić Skrbinšek Aleksandra , Šorgo Andrej , Tomažič Iztok
Published: January 2022

Teaching in a formal learning environment mainly focuses on gaining knowledge, and scarcely on the development of pro-environmental attitudes. Knowledge can also be gained in informal learning institutions, such as zoos, and their potential use in general public education should not be neglected. This paper explores factors influencing the conservation beliefs of zoo visitors about brown bears, grey wolves, and Eurasian lynx. The study undertaken in Zoo Ljubljana (Slovenia) consisted of surveys performed in 2009 (n = 613) and in 2021 (n = 257). The levels of knowledge and education influenced both supporting and opposing beliefs about the three large carnivore species. The gender factor was less uniform: both supporting and opposing beliefs about lynx were demonstrated, but only opposing beliefs about brown bear and wolf. The study indicates that knowledge has the most significant influence on conservation beliefs, thus highlighting the importance of educational and communication activities in management and conservation actions regarding large carnivore species. The varied gender influence suggests that species-specific educational activities should be encouraged.
Determinants of Sustainable Cross-Border Cooperation: A Structural Model for the Hungarian Context Using the PLS-SEM Methodology
Authors: Khmeleva Galina Anatolievna , Kurnikova Marina Viktorovna , Nedelka Erzsébet , Tóth Balázs István
Published: January 2022

The importance of this research stems from the need to ensure the sustainability of cross-border cooperation through a better understanding of its determinants and causal relationships. While having common features and patterns, cross-border cooperation is always expressed through the relations of specific countries and peoples. Therefore, based upon the PLS-SEM methodology, the authors consider the fundamental factors influencing the external cooperation of Hungary’s transboundary regions. The advantage of the PLS-SEM method is that it enables researchers to simultaneously identify and approximate hidden connections between input data and to construct a regression model describing the relationship between input data. Despite widespread application in economic studies, the authors have not found the use of PLS-SEM for studying cross-border cooperation issues in the current scientific literature. The authors have built a model to assess the hidden factors of cross-border cooperation and to identify the indirect influence of certain factors. The novelty of the research is to identify the determinants of sustainable cross-border cooperation and the relationship between them in a multi-level system of cross-border interaction between businesses, people, and the State. In the Hungarian context, transport infrastructure and business travel are shown to have a direct positive impact on cross-border cooperation. For the first time, tourism and socio-economic conditions have been shown to have powerful but indirect impacts. This work could be the beginning of gathering new evidence on the determinants and causation of cross-border cooperation in the context of other countries. An important finding of the study is the growing importance of indicators of the new, post-industrial economy. As for recommendations, the authors focus on state, regional, and municipal support measures, awareness of the possibilities of cross-border cooperation, the need to develop e-commerce, and alternative energy as a modern basis for converting Hungary’s cross-border position into a competitive advantage.
The Long-Standing Issue of Mobility at the Olympics: From Host Cities to Host Regions in the Ongoing Case Study of Milan–Cortina 2026
Authors: Lopes dos Santos Gustavo , Macário Rosário , Delaplace Marie , Di Vita Stefano
Published: January 2022

Due to public opposition against the unsustainability of hosting the Olympic Games, the International Olympic Committee adopted Olympic Agenda 2020 to adjust the event requirements to address modern society’s sustainability concerns. Since its implementation, the Agenda has driven important changes regarding the planning and organization of the Olympics, including the possibility of regions being hosts. This allows the sprawl of Olympic venues over larger territories, theoretically facilitating the alignment of event requirements with the needs of the intensively growing contemporary urban areas. However, the larger the host territory, the more complex becomes its mobility planning, as transport requirements for participants still have to be fulfilled, and the host populations still expect to inherit benefits from any investments made. The objective of this paper is to identify and discuss new challenges that such modifications bring for mega-event mobility planning. First, based on the academic literature of case studies of previous Olympic cities, a theoretical framework to systematize the mobility problem at the Olympic Games is proposed for further validation, identifying the dimensions of the related knowledge frames. Second, the mobility planning for the case study of the first ever Olympic region—the Milan–Cortina 2026 Winter Games—is described. Using this case study, the proposed framework is then extrapolated for cases of Olympic regions in order to identify any shifts in the paradigm of mobility planning when increasing the spatial scale of Olympic hosts. Conclusions indicate that, if properly addressed, unsustainability might be mitigated in Olympic regions, but mega-event planners will have to consider new issues affecting host communities and event stakeholders.
Plant Nutrition under Climate Change and Soil Carbon Sequestration
Authors: Elbasiouny Heba , El-Ramady Hassan , Elbehiry Fathy , Rajput Vishnu D. , Minkina Tatiana , Mandzhieva Saglara
Published: January 2022

The climate is one of the key elements impacting several cycles connected to soil and plant systems, as well as plant production, soil quality, and environmental quality. Due to heightened human activity, the rate of CO2 is rising in the atmosphere. Changing climatic conditions (such as temperature, CO2, and precipitation) influence plant nutrition in a range of ways, comprising mineralization, decomposition, leaching, and losing nutrients in the soil. Soil carbon sequestration plays an essential function—not only in climate change mitigation but also in plant nutrient accessibility and soil fertility. As a result, there is a significant interest globally in soil carbon capture from atmospheric CO2 and sequestration in the soil via plants. Adopting effective management methods and increasing soil carbon inputs over outputs will consequently play a crucial role in soil carbon sequestration (SCseq) and plant nutrition. As a result, boosting agricultural yield is necessary for food security, notoriously in developing countries. Several unanswered problems remain regarding climate change and its impacts on plant nutrition and global food output, which will be elucidated over time. This review provides several remarkable pieces of information about the influence of changing climatic variables on plant nutrients (availability and uptake). Additionally, it addresses the effect of soil carbon sequestration, as one of climate change mitigations, on plant nutrition and how relevant management practices can positively influence this.
Exploiting the Pascal Distribution Series and Gegenbauer Polynomials to Construct and Study a New Subclass of Analytic Bi-Univalent Functions
Authors: Amourah Ala , Frasin Basem Aref , Ahmad Morad , Yousef Feras
Published: January 2022

In the present analysis, we aim to construct a new subclass of analytic bi-univalent functions defined on symmetric domain by means of the Pascal distribution series and Gegenbauer polynomials. Thereafter, we provide estimates of Taylor–Maclaurin coefficients a2 and a3 for functions in the aforementioned class, and next, we solve the Fekete–Szegö functional problem. Moreover, some interesting findings for new subclasses of analytic bi-univalent functions will emerge by reducing the parameters in our main results.
Analysis of Control Methods for the Traction Drive of an Alternating Current Electric Locomotive
Authors: Goolak Sergey , Tkachenko Viktor , Šťastniak Pavol , Sapronova Svitlana , Liubarskyi Borys
Published: January 2022

The analysis of operating conditions of traction drives of electric locomotives with asynchronous traction motors has been carried out. It was found that during operation in the output converter of an asynchronous motor, defects may occur, which leads to asymmetric modes of its operation. Models of a traction drive of an electric locomotive with asynchronous motors with scalar and vector control of the output converter are proposed, taking into account asymmetric operating modes. As a result of the simulation, the starting characteristics of the traction drive were obtained for various control methods both in normal and emergency modes of the drive. For the drive-in emergency mode, the following cases were investigated: the balance of the converter output voltages and the turn-to-turn circuit of 10% of phase A winding of the motor stator; imbalance of the output voltages of the inverter and an intact motor; imbalance of the output voltages of the converter and interturn short circuit of 10% of phase A winding of the motor stator. Comparison of the simulation results have shown that in emergency modes in the traction drive, the torque ripple on the motor shaft in the drive with vector control is 13% less, and in scalar control, the phase current unbalance coefficient is 22% less. The results of this work can be used to study the influence of the output converter control methods on the energy efficiency indicators of the traction drive of an AC electric locomotive.
Short-Term Energy Forecasting Using Machine-Learning-Based Ensemble Voting Regression
Authors: Phyo Pyae-Pyae , Byun Yung-Cheol , Park Namje
Published: January 2022

Meeting the required amount of energy between supply and demand is indispensable for energy manufacturers. Accordingly, electric industries have paid attention to short-term energy forecasting to assist their management system. This paper firstly compares multiple machine learning (ML) regressors during the training process. Five best ML algorithms, such as extra trees regressor (ETR), random forest regressor (RFR), light gradient boosting machine (LGBM), gradient boosting regressor (GBR), and K neighbors regressor (KNN) are trained to build our proposed voting regressor (VR) model. Final predictions are performed using the proposed ensemble VR and compared with five selected ML benchmark models. Statistical autoregressive moving average (ARIMA) is also compared with the proposed model to reveal results. For the experiments, usage energy and weather data are gathered from four regions of Jeju Island. Error measurements, including mean absolute percentage error (MAPE), mean absolute error (MAE), and mean squared error (MSE) are computed to evaluate the forecasting performance. Our proposed model outperforms six baseline models in terms of the result comparison, giving a minimum MAPE of 0.845% on the whole test set. This improved performance shows that our approach is promising for symmetrical forecasting using time series energy data in the power system sector.
Evaluation of the Bioelectrochemical Approach and Different Electron Donors for Biological Trichloroethylene Reductive Dechlorination
Authors: Dell’Armi Edoardo , Rossi Marta Maria , Taverna Lucia , Petrangeli Papini Marco , Zeppilli Marco
Published: January 2022

Trichloroethylene (TCE) and more in general chlorinated aliphatic hydrocarbons (CAHs) can be removed from a contaminated matrix thanks to microorganisms able to perform the reductive dechlorination reaction (RD). Due to the lack of electron donors in the contaminated matrix, CAHs’ reductive dechlorination can be stimulated by fermentable organic substrates, which slowly release molecular hydrogen through their fermentation. In this paper, three different electron donors constituted by lactate, hydrogen, and a biocathode of a bioelectrochemical cell have been studied in TCE dechlorination batch experiments. The batch reactors evaluated in terms of reductive dechlorination rate and utilization efficiency of the electron donor reported that the bio-electrochemical system (BES) showed a lower RD rate with respect of lactate reactor (51 ± 9 µeq/d compared to 98 ± 4 µeq/d), while the direct utilization of molecular hydrogen gave a significantly lower RD rate (19 ± 8 µeq/d), due to hydrogen low solubility in liquid media. The study also gives a comparative evaluation of the different electron donors showing the capability of the bioelectrochemical system to reach comparable efficiencies with a fermentable substrate without the use of other chemicals, 10.7 ± 3.3% for BES with respect of 3.5 ± 0.2% for the lactate-fed batch reactor. This study shows the BES capability of being an alternative at classic remediation approaches.
A Note on Singularity Avoidance in Fourth-Order Gravity
Authors: Fabbri Luca
Published: January 2022

We consider the fourth-order differential theory of gravitation to treat the problem of singularity avoidance: studying the short-distance behaviour in the case of black-holes and the big-bang we are going to see a way to attack the issue from a general perspective.
Impact of Molecular Modification on the Efficiency of Recombinant Baculovirus Vector Invasion to Mammalian Cells and Its Immunogenicity in Mice
Authors: Zheng Hao , Pan Yong , Wang Xiong , Tian Weibin , Yao Lunguang , Sun Jingchen
Published: January 2022

The baculovirus display system (BDS), an excellent eukaryotic surface display technology that offers the advantages of safety, efficiency, and economy, is widely used in biomedicine. A previous study using rBacmid-Δgp64-ires-gp64 expressed in low copy numbers of the gp64 gene achieved high-efficiency expression and co-display of three fluorescent proteins (GFP, YFP, and mCherry). However, low expression of GP64 in recombinant baculoviruses also reduces the efficiency of recombinant baculovirus transduction into mammalian cells. In addition, the baculovirus promoter has no expression activity in mammalian cells and thus cannot meet the application requirements of baculoviral vectors for the BDS. Based on previous research, this study first determined the expression activity of promoters in insect Spodoptera frugiperda 9 cells and mammalian cells and successfully screened the very early promoter pie1 to mediate the co-expression of multiple genes. Second, utilizing the envelope display effect of the INVASIN and VSVG proteins, the efficiency of transduction of recombinant baculovirus particles into non-host cells was significantly improved. Finally, based on the above improvement, a recombinant baculovirus vector displaying four antigen proteins with high efficiency was constructed. Compared with traditional BDSs, the rBacmid-Δgp64 system exhibited increased display efficiency of the target protein by approximately 3-fold and induced an approximately 4-fold increase in the titer of serum antibodies to target antigens in Bal B/c mice. This study systematically explored the application of a new multi-gene co-display technology applicable to multi-vaccine research, and the results provide a foundation for the development of novel BDS technologies.
Understanding Rhinovirus Circulation and Impact on Illness
Authors: Esneau Camille , Duff Alexandra Cate , Bartlett Nathan W.
Published: January 2022

Rhinoviruses (RVs) have been reported as one of the main viral causes for severe respiratory illnesses that may require hospitalization, competing with the burden of other respiratory viruses such as influenza and RSV in terms of severity, economic cost, and resource utilization. With three species and 169 subtypes, RV presents the greatest diversity within the Enterovirus genus, and despite the efforts of the research community to identify clinically relevant subtypes to target therapeutic strategies, the role of species and subtype in the clinical outcomes of RV infection remains unclear. This review aims to collect and organize data relevant to RV illness in order to find patterns and links with species and/or subtype, with a specific focus on species and subtype diversity in clinical studies typing of respiratory samples.
Detection of Enterovirus D68 in Wastewater Samples from the UK between July and November 2021
Authors: Tedcastle Alison , Wilton Thomas , Pegg Elaine , Klapsa Dimitra , Bujaki Erika , Mate Ryan , Fritzsche Martin , Majumdar Manasi , Martin Javier
Published: January 2022

Infection with enterovirus D68 (EV-D68) has been linked with severe neurological disease such as acute flaccid myelitis (AFM) in recent years. However, active surveillance for EV-D68 is lacking, which makes full assessment of this association difficult. Although a high number of EV-D68 infections were expected in 2020 based on the EV-D68′s known biannual circulation patterns, no apparent increase in EV-D68 detections or AFM cases was observed during 2020. We describe an upsurge of EV-D68 detections in wastewater samples from the United Kingdom between July and November 2021 mirroring the recently reported rise in EV-D68 detections in clinical samples from various European countries. We provide the first publicly available 2021 EV-D68 sequences showing co-circulation of EV-D68 strains from genetic clade D and sub-clade B3 as in previous years. Our results show the value of environmental surveillance (ES) for the early detection of circulating and clinically relevant human viruses. The use of a next-generation sequencing (NGS) approach helped us to estimate the prevalence of EV-D68 viruses among EV strains from other EV serotypes and to detect EV-D68 minor variants. The utility of ES at reducing gaps in virus surveillance for EV-D68 and the possible impact of nonpharmaceutical interventions introduced to control the COVID-19 pandemic on EV-D68 transmission dynamics are discussed.
Persistent T-Cell Reactivity in a Seronegative Patient after SARS-CoV-2 Infection and One Vaccination
Authors: Andreas Nico , Weis Sebastian , Kolanos Steffi , Baumgart Sabine , Kamradt Thomas , Pletz Mathias W.
Published: January 2022

We present here a 64-year-old male participant of the CoNAN study who experienced a PCR-confirmed mild SARS-CoV-2 infection but did not develop any measurable antibody response. Additionally, after vaccination with ChAdOx1 (AstraZeneca, Cambridge, UK) 11 months later, no antibodies were detected in six serological tests three weeks after the vaccination. When we assessed T-helper (Th) cell immunity, SARS-CoV-2-specific Th cells produced detectable amounts of IFNγ and TNF six weeks after the infection. A robust T-cell immunity remained detectable at least until six months after the infection and was boosted by the vaccination thereafter. This case report points out that an assessment of a prior infection or a vaccine response based solely on antibody detection might have limitations in individual patients.
Benign Fasciculation Syndrome and Migraine Aura without Headache: Possible Rare Side Effects of the BNT162b2 mRNA Vaccine? A Case Report and a Potential Hypothesis
Authors: Salai Grgur , Bilic Ervina , Primorac Dragan , Lakusic Darija Mahovic , Bilic Hrvoje , Lazibat Ines , Grgurevic Lovorka
Published: January 2022

The BNT162b2 (Pfizer BioNTech) mRNA vaccine is an effective vaccine against COVID-19 infection. Here, we report an adverse event following immunization (AEFI) in a 48-year-old female patient who presented with fasciculations, migraine auras without headaches and in an increased discomfort of previously present palpitations, as well as excitation and insomnia. Her fasciculations were intermittently present until the time this paper was written, starting from the 6th day post-vaccination; they changed localization and frequency, but most commonly they were generalized, affecting almost all muscle groups. The patient also suffered from two incidents of migraine auras with visual kaleidoscope-like phenomena without headaches a few months after the vaccination. These symptoms were considered to be AEFI and no causal relation with the vaccine could be proven.
Childhood Immunisation Coverage during the COVID-19 Epidemic in Italy
Authors: Sabbatucci Michela , Odone Anna , Signorelli Carlo , Siddu Andrea , Silenzi Andrea , Maraglino Francesco Paolo , Rezza Giovanni
Published: January 2022

The COVID-19 pandemic has affected national healthcare systems worldwide, with around 282 million cumulative confirmed cases reported in over 220 countries and territories as of the end of 2021. The Italian National Health System was heavily affected, with detrimental impacts on preventive service delivery. Routine vaccination services were disrupted across the country during the first months of the pandemic, and both access to and demand for vaccines have decreased during the pandemic. In many cases, parents preferred to postpone scheduled appointments for routine paediatric vaccinations because of stay-at-home orders or fear of COVID-19 infection when accessing care. The objective of the current study was to assess the routine childhood vaccine coverage (VC) rates during the COVID-19 epidemic in Italy. We compared 2020 and 2019 VC by age group and vaccine type. The Italian Ministry of Health collected anonymised and aggregated immunisation national data through the local health authorities (LHAs). Results were considered statistically significant at a two-tailed p-value ≤ 0.05. VC rates for mandatory vaccinations decreased in 2020 compared to 2019 (range of VC rate decrease: −1% to −2.7%), while chicken pox increased (+2.2%) in 7-year-old children. Recommended vaccinations were moderately affected (range of VC rate decrease in 2020 vs. 2019: −1.4% to −8.5%), with the exception of anti-HPV in males, Men ACWY, and anti-rotavirus vaccination (VC increase 2020 vs. 2019: +1.8%, +4.7% and +9.4%, respectively). In the COVID-19 era, the implementation of coherent, transparent, and effective communication campaigns and educational programs on safe childhood vaccinations, together with the increase in the number of healthcare staff employed, is essential to support strategies to reinforce vaccination confidence and behaviour, thus avoiding health threats due to VPD during and beyond COVID-19 times.
Coprostanol as a Population Biomarker for SARS-CoV-2 Wastewater Surveillance Studies
Authors: Reynolds Liam J. , Sala-Comorera Laura , Khan Mohd Faheem , Martin Niamh A. , Whitty Megan , Stephens Jayne H. , Nolan Tristan M. , Joyce Eadaoin , Fletcher Nicola F. , Murphy Cormac D. , Meijer Wim G.
Published: January 2022

Wastewater surveillance is a cost-effective tool for monitoring SARS-CoV-2 transmission in a community. However, challenges remain with regard to interpretating such studies, not least in how to compare SARS-CoV-2 levels between different-sized wastewater treatment plants. Viral faecal indicators, including crAssphage and pepper mild mottle virus, have been proposed as population biomarkers to normalise SARS-CoV-2 levels in wastewater. However, as these indicators exhibit variability between individuals and may not be excreted by everyone, their utility as population biomarkers may be limited. Coprostanol, meanwhile, is a bacterial metabolite of cholesterol which is excreted by all individuals. In this study, composite influent samples were collected from a large- and medium-sized wastewater treatment plant in Dublin, Ireland and SARS-CoV-2 N1, crAssphage, pepper mild mottle virus, HF183 and coprostanol levels were determined. SARS-CoV-2 N1 RNA was detected and quantified in all samples from both treatment plants. Regardless of treatment plant size, coprostanol levels exhibited the lowest variation in composite influent samples, while crAssphage exhibited the greatest variation. Moreover, the strongest correlations were observed between SARS-CoV-2 levels and national and Dublin COVID-19 cases when levels were normalised to coprostanol. This work demonstrates the usefulness of coprostanol as a population biomarker for wastewater surveillance studies.
Managing Apparent Loss and Real Loss from the Nexus Perspective Using System Dynamics
Authors: Choi Seo Hyung , Shin Bongwoo , Shin Eunher
Published: January 2022

When water utilities establish water loss control programs, they traditionally focus on apparent loss rather than real loss when considering economic feasibility in the water sector. There is an urgent need for new management approaches that can address complex relationships and ensure the sustainability of natural resources among different sectors. This study suggests a novel approach for water utilities to manage water losses from the water-energy (WE) Nexus perspective. The Nexus model uses system dynamics to simulate twelve scenarios with the differing status of water loss and energy intensities. This analysis identifies real loss as one of the main causes of resource waste and an essential factor from the Nexus perspective. It also demonstrates that the energy intensity of each process in the urban water system has a significant impact on resource use and transfer. The consumption and movement of resources can be quantified in each process involved in the urban water system to distinguish central and vulnerable processes. This study suggests that the Nexus approach can strongly contribute to quantifying the use and movement of resources between water and energy sectors and the strategic formulation of sustainable and systematic water loss management strategies from the Nexus perspective.
Study of the sensitivity and specificity of smell and taste disorders as a predictive factor of SARS-CoV-2 infection among primary care healthcare professionals: a retrospective observational study
Authors: Ruiz-Comellas Anna , Roura Poch Pere , Sauch Valmaña Glòria , Guadalupe-Fernández Víctor , Mendioroz Peña Jacobo , Miró Catalina Queralt , Vidal-Alaball Josep , Ramirez-Morros Anna
Published: January 2022

Background

Among the manifestations of COVID-19 are taste and smell disorders (TSDs).

Aim

To evaluate the sensitivity and specificity of TSDs and other associated symptoms to estimate predictive values for determining SARS-CoV-2 infection.

Design & setting

A retrospective observational study of healthcare professionals in Catalonia, Spain.

Method

A study of the sensitivity and specificity of TSDs has been carried out using the polymerase chain reaction (PCR) test for the diagnosis of SARS-CoV-2 as the gold standard value. Logistic regressions adjusted for age and sex were performed to identify additional symptoms that might be associated with COVID-19.

Results

The results are based on 226 healthcare workers with clinical symptoms suggestive of COVID-19, 116 with positive PCR and 110 with negative PCR. TSDs had an odds ratio (OR) of 12.4 (95% confidence interval [CI] = 6.3 to 26.2), sensitivity 60.3% and specificity 89.1%. In the logistic regression model, the association of TSD, fever or low-grade fever, shivering, dyspnoea, arthralgia, and myalgia obtained an area under the curve (AUC) of 85.7% (95% CI = 80.7 % to 90.7 %), sensitivity 82.8 %, specificity 80.0%, and positive predictive values 81.4% and negative 81.5%.

Conclusion

TSDs are a strong predictor of COVID-19. The association of TSD, fever, low-grade fever or shivering, dyspnoea, arthralgia, and myalgia correctly predicts 85.7% of the results of the COVID-19 test.