bluuebunny/crossref_metadata_2025 huggingface dataset:
Life Cycle Assessment of Advanced Building Components towards NZEBs
Authors: Antypa Despoina , Petrakli Foteini , Gkika Anastasia , Voigt Pamela , Kahnt Alexander , Böhm Robert , Suchorzewski Jan , Araújo Andreia , Sousa Susana , Koumoulos Elias P.
Published: December 2022

The building sector accounts for 40% of the total energy consumed in Europe at annual basis, together with the relevant Greenhouse Gas (GHG) emissions. In order to mitigate these impacts, the concept and establishment of the Nearly Zero Energy Buildings (NZEBs) is under continuous and intensive research. In fact, as the energy used for buildings’ operation becomes more efficient, impacts resulting from the buildings’ embodied energy become of more importance. Therefore, the selection of building materials and components is of high significance, as these affect the energy performance and potential environmental impacts of the building envelopes. The objective of this study is to perform a preliminary Life Cycle Assessment (LCA) on advanced multifunctional building components, aiming to achieve lower embodied emissions in NZEBs. The advanced components analyzed are composite panels for facade elements of building envelopes, providing thermal efficiency. The design of sustainable building envelope systems is expected to upgrade the overall environmental performance of buildings, including the NZEBs. The findings of this study constitute unambiguous evidence on the need for further research on this topic, as substantial lack of data concerning embodied impacts is presented in literature, adding to the growing discussion on NZEBs at a whole life cycle perspective across Europe. This research has shown that the electricity required from the manufacturing phase of the examined building components is the main contributor to climate change impact and the other environmental categories assessed. Sensitivity analysis that has been performed indicated that the climate change impact is highly depended on the electricity grid energy mix across Europe. Taking into account the current green energy transition by the increase of the renewable energy sources in electricity production, as well as the future upgrade of the manufacturing processes, it is expected that this climate change impact will be mitigated. Finally, the comparison between the CLC thermal insulator and other foam concretes in literature showed that the materials of the building components examined do not present any diversions in terms of environmental impact.
Selection and Quantification of Best Water Quality Indicators Using UAV-Mounted Hyperspectral Data: A Case Focusing on a Local River Network in Suzhou City, China
Authors: Zhang Dingyu , Zeng Siyu , He Weiqi
Published: December 2022

Hyperspectral imaging performed by Unmanned Aerial Vehicles (UAVs) has proven its potential in environmental surveillances, especially in the field of water quality monitoring. In this study, three polynomial forms of inversion models for six water quality indicators were specified, with different numbers of spectral reflectance (1/2/3) as independent variables. Each model was designed with seven parameters, and the differential evolution algorithm was used to optimize the parameters by minimization of the mean absolute percentage error (MAPE) between the retrieval results and field observations. Hyperspectral data from a (UAV)-mounted imager and the corresponding river water quality measurements were obtained in a case area in Suzhou City, China. Both MAPE and the coefficient of certainty (R2) are used to evaluate the model performance. All the models are useable, with an MAPE range of 3–18% and an R2 range of 0.65–0.94, while the retrieval accuracy is more indicator-dependent and two nitrogen-related indicators have the lowest MAPE of around 5%. Considering the MAPE during model training and verification, the two-band model structure is more robust than the single- or three-band structures. It is certain that such a data-driven approach for large-scale, continuous, and multiple-indicator monitoring with considerable accuracy could facilitate water quality management.
The Usage of MALL in Learners’ Readiness to Speak English
Authors: Zhen Ling Sue , Hashim Harwati
Published: December 2022

Having proficiency in English macro skills has been of foremost importance among English language learners to have a sustainable education. Evidently, knowing English corresponds with being able to articulate the language. However, many language learners still struggle to successfully master speaking skills. Previous studies advocated mobile-assisted language learning (MALL) as an innovative pedagogical practice that has the potential to be utilized in the acquisition of the speaking skills. Nevertheless, current studies that specify the usage of MALL in the readiness of speaking English are still limited. Therefore, this paper plans to fill in the gap by propounding a systematic review of published studies from the year 2013 to 2022 that are relevant to the implementation of MALL in the readiness to speak English. The findings of this review indicated that the usage of MALL fosters affective variables such as motivation, self-confidence, less anxiety, and learners’ control in the readiness of speaking skills, but most of the reviewed studies’ focal point were on older or adult learners, which created a gap in the literature. Hence, this requires the study of the usage of MALL in primary and secondary levels of education for the benefits of English language learners of all ages in the acquisition of speaking English.
Evaluation of the Ground Settlement in an Urban Area Resulting from a Small Curvature Tunneling Construction
Authors: Tang Lixian , Zhou Qiang , Wang Shoulong , Yao Wenjie , Zhang Bowei , Xiang Ke , Satyanaga Alfrendo , Tao Jin
Published: December 2022

The transportation system is one of the major infrastructures in urban areas, and it serves 56% of the world’s population. Nowadays, metro lines are developing fast in urban areas. Due to the restrictions of urban fields, metro lines are usually not planned straight, and a curved line is required to connect stations in different locations in a city. As a result, small curvature tunnels are commonly constructed in urban areas. The tunneling construction in a city area may cause ground settlement, which is sensitive to surrounding buildings and underground utilities. The aim of this study is to explore the impact of curvature alignment on the ground settlement. In this paper, ground settlements induced by small curvature shield tunneling were evaluated by using a numerical analysis. A total of six cases were selected for the analysis. The results obtained from the numerical simulations were compared with Peck’s equation. It is observed that Peck’s equation can be used for the estimation of the maximum settlement. However, the ground settlements on both sides of the central axis of the curved tunnel are asymmetrical, and Peck’s equation, which provides a symmetrical settlement, may not be applicable in the case of small curvature tunnels.
Influence of Seed Treated by Plasma Activated Water on the Growth of Lactuca sativa L.
Authors: Romanjek Fajdetić Nataša , Benković-Lačić Teuta , Mirosavljević Krunoslav , Antunović Slavica , Benković Robert , Rakić Mario , Milošević Slobodan , Japundžić-Palenkić Božica
Published: December 2022

The aim of this work was to determine if PAW (Plasma Activated Water) seed treatment and growing conditions could have positive effects on lettuce seedlings and growth. The paper presents the results of a pot experiment on lettuce (Lactuca sativa L.) cultivation in greenhouse and field conditions after seed treatment with PAW. The experiment was conducted in two consecutive seasons in 2021 and 2022 and the following growth parameters were measured: head mass, rosette height, rosette width, number of leaves, root mass and root length. As a result of the study, it was found that lettuces grown in the greenhouse from PAW treated seeds had higher results in the first measurement for both cultivars (mass 32.26%, diameter 19.01%, number of leaves 13.49% and height 24.01%), while there were no statistically significant effects on the root system. The lowest results were obtained in untreated and field-grown plants. In addition, plant dry matter was measured and it was found that plants grown from PAW treated seeds had a higher percentage of dry matter (11.51% in 2021, and 11.58% in 2022). It was also found that cultivation in greenhouse resulted in a better quality of plants than the cultivation in the open field.
Effects of Humidification with NaCl Solution Mist on Electrochemical Characteristics of Polymer Electrolyte Membrane Fuel Cells
Authors: Yoo Ho Jun , Cho Gu Young
Published: December 2022

This study examined the effects of mist generated from NaCl solution on the electrochemical properties of polymer electrolyte membrane fuel cells. Mist-containing Na+ and Cl- ions were generated using a custom-made mist generator. The current density-voltage-power density curves and electrochemical impedance spectroscopy of fuel cells were systematically achieved. Furthermore, long-term stability experiments were carried out using chronoamperometry mode for 20 h with deionized water and NaCl solution. After the chronoamperometry measurement, the regeneration of fuel cells was performed with deionized water. The effects of regeneration methods on the performance of the fuel cell were evaluated. Due to the internally produced H2O, constant voltage regeneration was more effective than open circuit voltage regeneration.
Dynamic Load Balancing Techniques in the IoT: A Review
Authors: Kanellopoulos Dimitris , Sharma Varun
Published: December 2022

The Internet of things (IoT) extends the Internet space by allowing smart things to sense and/or interact with the physical environment and communicate with other physical objects (or things) around us. In IoT, sensors, actuators, smart devices, cameras, protocols, and cloud services are used to support many intelligent applications such as environmental monitoring, traffic monitoring, remote monitoring of patients, security surveillance, and smart home automation. To optimize the usage of an IoT network, certain challenges must be addressed such as energy constraints, scalability, reliability, heterogeneity, security, privacy, routing, quality of service (QoS), and congestion. To avoid congestion in IoT, efficient load balancing (LB) is needed for distributing traffic loads among different routes. To this end, this survey presents the IoT architectures and the networking paradigms (i.e., edge–fog–cloud paradigms) adopted in these architectures. Then, it analyzes and compares previous related surveys on LB in the IoT. It reviews and classifies dynamic LB techniques in the IoT for cloud and edge/fog networks. Lastly, it presents some lessons learned and open research issues.
Flow-Based IDS Features Enrichment for ICMPv6-DDoS Attacks Detection
Authors: Elejla Omar E. , Anbar Mohammed , Hamouda Shady , Belaton Bahari , Al-Amiedy Taief Alaa , Hasbullah Iznan H.
Published: December 2022

Internet Protocol version 6 (IPv6) and its core protocol, Internet Control Message Protocol version 6 (ICMPv6), need to be secured from attacks, such as Denial of Service (DoS) and Distributed DoS (DDoS), in order to be reliable for deployment. Several Intrusion Detection Systems (IDSs) have been built and proposed to detect ICMPv6-based DoS and DDoS attacks. However, these IDSs suffer from several drawbacks, such as the inability to detect novel attacks and a low detection accuracy due to their reliance on packet-based traffic representation. Furthermore, the existing IDSs that rely on flow-based traffic representation use simple heuristics features that do not contribute to detecting ICMPv6-based DoS and DDoS attacks. This paper proposes a flow-based IDS by enriching the existing features with a set of new features to improve the detection accuracy. The flow consists of packets with similar attributes (i.e., packets with the same source and destination IP address) and features that can differentiate between normal and malicious traffic behavior, such as the source IP address’s symmetry and the whole flow’s symmetry. The experimental results reveal that the enriched features significantly improved the IDS’s detection accuracy by 16.02% and that the false positive rate decreased by 19.17% compared with state-of-the-art IDSs.
Geodesic (in) Completeness in General Metric Frames
Authors: Rubakov Valery A. , Wetterich Christof
Published: December 2022

The geometric concept of geodesic completeness depends on the choice of the metric field or “metric frame”. We develop a frame-invariant concept of “generalised geodesic completeness” or “time completeness”. It is based on the notion of physical time defined by counting oscillations for some physically allowed process. Oscillating solutions of wave functions for particles with varying mass permit the derivation of generalised geodesics and the associated notion of completeness. Time completeness involves aspects of particle physics and is no longer a purely geometric concept.
Application of DNA Coding, the Lorenz Differential Equations and a Variation of the Logistic Map in a Multi-Stage Cryptosystem
Authors: Gabr Mohamed , Younis Hana , Ibrahim Marwa , Alajmy Sara , Khalid Ijaz , Azab Eman , Elias Rimon , Alexan Wassim
Published: December 2022

The need for information security has become urgent due to the constantly changing nature of the Internet and wireless communications, as well as the daily generation of enormous volumes of multimedia. In this paper, a 3-stage image cryptosystem is developed and proposed. A tan variation of the logistic map is utilized to carry out deoxyribonucleic acid (DNA) encoding in the first stage. For the second encryption stage, the numerical solution of the Lorenz differential equations and a linear descent algorithm are jointly employed to build a robust S-box. The logistic map in its original form is utilized in the third stage. Diffusion is guaranteed through the first and third encryption stages, while confusion is guaranteed through the application of the S-box in the second encryption stage. Carrying out both confusion- and diffusion-inducing stages results in encrypted images that are completely asymmetric to their original (plain) counterparts. An extensive numerical analysis is carried out and discussed, showcasing the robustness and efficacy of the proposed algorithm in terms of resistance to visual, statistical, entropy, differential, known plaint text and brute-force attacks. Average values for the computed metrics are: Information entropy of 7.99, MSE of 9704, PSNR of 8.3 dB, MAE of 80.8, NPCR of 99.6 and UACI of 33. The proposed algorithm is shown to exhibit low computational complexity, encrypting images at an average rate of 1.015 Mbps. Moreover, it possesses a large key space of 2372, and is demonstratd to successfully pass all the tests of the NIST SP 800 suite. In order to demonstrate the superior performance of the proposed algorithm, a comparison with competing image encryption schemes from the literature is also provided.
Stable Many-Body Resonances in Open Quantum Systems
Authors: Peña Rubén , Kyaw Thi Ha , Romero Guillermo
Published: December 2022

Periodically driven quantum many-body systems exhibit novel nonequilibrium states, such as prethermalization, discrete time crystals, and many-body localization. Recently, the general mechanism of fractional resonances has been proposed that leads to slowing the many-body dynamics in systems with both U(1) and parity symmetry. Here, we show that fractional resonance is stable under local noise models. To corroborate our finding, we numerically study the dynamics of a small-scale Bose–Hubbard model that can readily be implemented in existing noisy intermediate-scale quantum (NISQ) devices. Our findings suggest a possible pathway toward a stable nonequilibrium state of matter, with potential applications of quantum memories for quantum information processing.
A Wolf Pack Optimization Algorithm Using RASGS and GBA for Multi-Modal Multi-Objective Problems
Authors: Wang Huibo , Wang Dongxing
Published: December 2022

To address multi-modal multi-objective problems (MMOPs), this paper proposes a wolf pack optimization algorithm using random adaptive-shrinking grid search (RASGS) and raid towards global best archive (GBA) for MMOPs. Firstly, RASGS with logical symmetry was adopted to enhance the exploitation of the algorithm in the local area as well as locate a larger number of Pareto-optimal solutions. Moreover, with the help of an existing sorting method composed of the non-dominated sorting scheme and special crowding distance (SCD), the GBA strategy was employed to obtain and maintain the historical global optimal solution of the population as well as induce the population to explore better solutions. The experimental results indicate that the proposed method has obvious superior performance compared with the existing related algorithms.
Research on the Effectiveness of Deep Learning−Based Agency Cost Suppression Strategy: A Case Study of State−Owned Enterprises in Mainland China
Authors: Zhai Dongxue , Zhao Xuefeng , Bai Yanfei , Wu Delin
Published: December 2022

The mixed ownership reform aims to improve the property rights structure of the state−owned enterprises (SOEs) and reduce agency costs, and the current mixed reform strategies mainly include equity blending by introducing external non−state capital, executive assignments, and employee stock ownership. In this paper, 953 valid data of A−shares listed in Shanghai and Shenzhen from 2008 to 2020 are used as samples to construct the indicators of mixed reform strategy by the literature statistics method. After obtaining multiple impact indicators, the regression impact model of corporate agency cost suppression strategy is constructed by MATLAB software using a machine learning algorithm. On this basis, the performance of multiple machine learning algorithms is compared, and it is found that the integrated optimization−based bag−boosting model is used to study the effect of hybrid reform strategy to reduce the agency costs of SOEs, and the proportional setting of indicators when the effect is optimal is also explored. Finally, the laws of different influencing factors on the agency costs of enterprises are explored separately by the eigenvalue method. The results of the study show that the proportion of shareholding of the first largest non−state shareholder is sin−functional with the agency costs of SOEs when non−state majority shareholders are introduced into SOEs’ equity mix, and the agency costs tend to decrease after SOEs become privately held enterprises. The greater the number and proportion of supervisors appointed by non−state shareholders, the greater the supervisory restraint effect on SOE managers and the better the effect of suppressing agency costs. The participation of non−state−owned shareholders in the company’s business decisions by appointed executives and the special resource advantages of SOEs intensify the occurrence of the self−interest of appointed executives and the increase of agency costs of SOEs. The implementation of an employee stock ownership plan plays the role of employee supervision and restraint on SOE managers, which reduces the agency costs of SOEs. Based on this, it can provide support for the government to improve the hybrid reform policy and promote the process layer by layer, and also provide theoretical reference for SOEs to deepen the equity mix, incentivize employee shareholding, and empower non−state shareholders to govern and thus reduce agency costs.
A Time Series Model Based on Deep Learning and Integrated Indicator Selection Method for Forecasting Stock Prices and Evaluating Trading Profits
Authors: Cheng Ching-Hsue , Tsai Ming-Chi , Chang Chin
Published: December 2022

A stock forecasting and trading system is a complex information system because a stock trading system needs to be analyzed and modeled using data science, machine learning, and artificial intelligence. Previous time series models have been widely used to forecast stock prices, but due to several shortcomings, these models cannot apply all available information to make a forecast. The relationship between stock prices and related factors is nonlinear and involves nonstationary fluctuations, and accurately forecasting stock prices is not an easy task. Therefore, this study used support vector machines (linear and radial basis functions), gene expression programming, multilayer perceptron regression, and generalized regression neural networks to calculate the importance of indicators. We then integrated the five indicator selection methods to find the key indicators. Next, we used long short-term memory (LSTM) and gated recurrent units (GRU) to build time series models for forecasting stock prices and compare them with the listing models. To evaluate the effectiveness of the proposed model, we collected six different stock market data from 2011 to 2019 to evaluate their forecast performance based on RMSE and MAPE metrics. It is worth mentioning that this study proposes two trading policies to evaluate trading profits and compare them with the listing methods, and their profits are pretty good to investors. After the experiments, the proposed time series model (GRU/LSTM combined with the selected key indicators) exhibits better forecast ability in fluctuating and non-fluctuating environments than the listing models, thus presenting an effective reference for stakeholders.
A New Perspective on the Textile and Apparel Industry in the Digital Transformation Era
Authors: Akhtar Waleed Hassan , Watanabe Chihiro , Tou Yuji , Neittaanmäki Pekka
Published: December 2022

The textile and apparel (fashion) industry has been influenced by developments in societal socio-cultural and economic structures. Due to a change in people’s preferences from economic functionality to supra-functionality beyond economic value, the fashion industry is at the forefront of digitalization. The growing digitalization in the fashion industry corresponds to digital fashion, which can satisfy the rapid shift in consumers’ preferences. This paper explores the evolving con-cept of innovations in digital fashion in the textile and apparel industry. Specifically, it centers on the evaluation of Amazon’s digital fashion initiatives, which have made the platform the United States’ top fashion retailer. An analysis of the business model of Amazon’s digital fashion business showed that with the advancements in artificial intelligence (AI) powered by advanced Amazon Web Services (AWS), Amazon has introduced novel digital solutions for the fashion industry, such as advanced digital fashions (ADFs), on-demand manufacturing, neo-luxury, and, ultimately, cloud-based digital fashion platforms, that is, a supra-omnichannel, where all stakeholders are integrated, and their activities are visible in real time. This can be attributed to the learning orchestration externality strategy. This study concludes that with the advancement of digital innovations, Amazon has fused a self-propagating function that advances digital solutions. This study shows that Amazon is the largest R&D company. Its R&D process is based on users’ knowledge gained by their participation through AWS-driven ICT tools. This promotes a culture of experimentation in the development of user-driven innovations. Such innovations have further advanced the functionality of AWS in data analysis and business solutions. This dynamism promotes the development of soft innovation resources and revenue streams. These endeavors are demonstrated in a model, and their reliability is validated through an empirical analysis focused on the emergence of ADF solutions. Therefore, based on an analysis of the development trajectories of Amazon’s digital fashion technologies, such as ADFs, on-demand manufacturing, and neo-luxury, insightful suggestions and a framework for solutions beyond e-commerce are provided.
Studying Respiratory Symptoms Related to Swimming Pools Attendance in Young Athletes: The SPHeRA Study
Authors: Zaccarin Matteo , Zanni Stefano , Gallè Francesca , Protano Carmela , Valeriani Federica , Liguori Giorgio , Romano Spica Vincenzo , Vitali Matteo
Published: December 2022

This study investigates the prevalence of respiratory symptoms and the training factors possibly associated with them in a sample of young Italian competitive swimmers. A questionnaire about training information and symptoms was administered to participants during the winter and summer 2021 training seasons. In total, 396 athletes took part in the study. In the winter training subgroup (n = 197), we found significant associations between increasing training hours per session and the presence of nasal congestion/rhinorrhoea (OR = 3.10; p = 0.039) and cough (OR = 3.48; p = 0.015). Total training hours per week were significantly associated with nasal congestion/rhinorrhoea (OR = 1.12; p = 0.010). In the summer group (n = 199), the same factors were not associated with respiratory symptoms. Having an allergy was significantly related to nasal congestion/rhinorrhea in both the logistic models (model 1 OR = 2.69, p = 0.013; model 2 OR = 2.70, p = 0.012), while having asthma significantly increased the risk of coughing (OR = 3.24, p = 0.033). The kind of environment (indoor or outdoor facilities) did not affect the studied symptoms either in summer or winter. Further investigations are needed to better understand the mechanisms involved in the development of respiratory symptoms in swimmers, particularly on how inflammation and remodelling develop and which environmental conditions can favour these processes.
Enzymatic Biotransformation of 13-desmethyl Spirolide C by Two Infaunal Mollusk Species: The Limpet Patella vulgata and the Cockle Cerastoderma edule
Authors: Rossignoli Araceli E. , Lamas Juan Pablo , Mariño Carmen , Martín Helena , Blanco Juan
Published: December 2022

The presence of a 13-desmethyl Spirolide C isomer (Iso-13-desm SPX C) is very common in some infaunal mollusks in Galicia contaminated with this toxin. Its possible origin by biological transformation was investigated by incubating homogenates of the soft tissues of limpets and cockles spiked with 13-desmethyl Spirolide C (13-desm SPX C). The involvement of an enzymatic process was also tested using a raw and boiled cockle matrix. The enzymatic biotransformation of the parent compound into its isomer was observed in the two species studied, but with different velocities. The structural similarity between 13-desm SPX C and its isomer suggests that epimerization is the most likely chemical process involved. Detoxification of marine toxins in mollusks usually implies the enzymatic biotransformation of original compounds, such as hydroxylation, demethylation, or esterification; however, this is the first time that this kind of transformation between spirolides in mollusks has been demonstrated.
Molecular Diversity of Linear Peptides Revealed by Transcriptomic Analysis of the Venom Gland of the Spider Lycosa poonaensis
Authors: Megaly Alhussin Mohamed Abdelhakeem , Miyashita Masahiro , Abdel-Wahab Mohammed , Nakagawa Yoshiaki , Miyagawa Hisashi
Published: December 2022

Spider venom is a complex mixture of bioactive components. Previously, we identified two linear peptides in Lycosa poonaensis venom using mass spectrometric analysis and predicted the presence of more linear peptides therein. In this study, a transcriptomic analysis of the L. poonaensis venom gland was conducted to identify other undetermined linear peptides in the venom. The results identified 87 contigs encoding peptides and proteins in the venom that were similar to those in other spider venoms. The number of contigs identified as neurotoxins was the highest, and 15 contigs encoding 17 linear peptide sequences were identified. Seven peptides that were representative of each family were chemically synthesized, and their biological activities were evaluated. All peptides showed significant antibacterial activity against Gram-positive and Gram-negative bacteria, although their selectivity for bacterial species differed. All peptides also exhibited paralytic activity against crickets, but none showed hemolytic activity. The secondary structure analysis based on the circular dichroism spectroscopy showed that all these peptides adopt an amphiphilic α-helical structure. Their activities appear to depend on the net charge, the arrangement of basic and acidic residues, and the hydrophobicity of the peptides.
Ultraviolet and X-ray Light-Curves of Novae Observed by the Neil Gehrels Swift Observatory
Authors: Page Kim L. , Kuin N. Paul M. , Osborne Julian P.
Published: December 2022

With rapid response capabilities, and a daily planning of its observing schedule, the Neil Gehrels Swift Observatory is ideal for monitoring transient and variable sources. Here we present a sample of the 12 novae with the most detailed ultraviolet (UV) follow-up by Swift—the first uniform analysis of such UV light-curves. The fading of these specific light-curves can be modelled as power-law decays (plotting magnitude against log time), showing that the same physical processes dominate the UV emission for extended time intervals in individual objects. After the end of the nuclear burning interval, the X-ray emission drops significantly, fading by a factor of around 10–100. The UV changes, however, are of a lower amplitude, declining by 1–2 mag over the same time period. The UV light-curves typically show a break from flatter to steeper around the time at which the X-ray light-curve starts a steady decline from maximum, ∼0.7–1.3 TSSSend. Considering populations of both classical and recurrent novae, and those with main sequence or giant companions, we do not find any strong differences in the UV light-curves or their evolution, although the long-period recurrent novae are more luminous than the majority of the classical novae.
Vaccination against Borna Disease: Overview, Vaccine Virus Characterization and Investigation of Live and Inactivated Vaccines
Authors: Dürrwald Ralf , Kolodziejek Jolanta , Oh Djin-Ye , Herzog Sibylle , Liebermann Heinrich , Osterrieder Nikolaus , Nowotny Norbert
Published: December 2022

(1) Background: Vaccination of horses and sheep against Borna disease (BD) was common in endemic areas of Germany in the 20th century but was abandoned in the early 1990s. The recent occurrence of fatal cases of human encephalitis due to Borna disease virus 1 (BoDV-1) has rekindled the interest in vaccination. (2) Methods: The full genomes of the BD live vaccine viruses “Dessau” and “Giessen” were sequenced and analyzed for the first time. All vaccination experiments followed a proof-of-concept approach. Dose-titration infection experiments were performed in rabbits, based on both cell culture- and brain-derived viruses at various doses. Inactivated vaccines against BD were produced from concentrated cell culture supernatants and investigated in rabbits and horses. The BoDV-1 live vaccine “Dessau” was administered to horses and antibody profiles were determined. (3) Results: The BD live vaccine viruses “Dessau” and “Giessen” belong to clusters 3 and 4 of BoDV-1. Whereas the “Giessen” virus does not differ substantially from field viruses, the “Dessau” virus shows striking differences in the M gene and the N-terminal part of the G gene. Rabbits infected with high doses of cell-cultured virus developed neutralizing antibodies and were protected from disease, whereas rabbits infected with low doses of cell-cultured virus, or with brain-derived virus did not. Inactivated vaccines were administered to rabbits and horses, following pre-defined vaccination schemes consisting of three vaccine doses of either adjuvanted or nonadjuvanted inactivated virus. Their immunogenicity and protective efficacy were compared to the BD live vaccine “Dessau”. Seventy per cent of horses vaccinated with the BD live vaccine “Dessau” developed neutralizing antibodies after vaccination. (4) Conclusion: Despite a complex evasion of immunological responses by bornaviruses, some vaccination approaches can protect against clinical disease. For optimal effectiveness, vaccines should be administered at high doses, following vaccination schemes consisting of three vaccine doses as basic immunization. Further investigations are necessary in order to investigate and improve protection against infection and to avoid side effects.
U5 snRNP Core Proteins Are Key Components of the Defense Response against Viral Infection through Their Roles in Programmed Cell Death and Interferon Induction
Authors: Boudreault Simon , Lemay Guy , Bisaillon Martin
Published: December 2022

The spliceosome is a massive ribonucleoprotein structure composed of five small nuclear ribonucleoprotein (snRNP) complexes that catalyze the removal of introns from pre-mature RNA during constitutive and alternative splicing. EFTUD2, PRPF8, and SNRNP200 are core components of the U5 snRNP, which is crucial for spliceosome function as it coordinates and performs the last steps of the splicing reaction. Several studies have demonstrated U5 snRNP proteins as targeted during viral infection, with a limited understanding of their involvement in virus–host interactions. In the present study, we deciphered the respective impact of EFTUD2, PRPF8, and SNRNP200 on viral replication using mammalian reovirus as a model. Using a combination of RNA silencing, real-time cell analysis, cell death and viral replication assays, we discovered distinct and partially overlapping novel roles for EFTUD2, PRPF8, and SNRNP200 in cell survival, apoptosis, necroptosis, and the induction of the interferon response pathway. For instance, we demonstrated that EFTUD2 and SNRNP200 are required for both apoptosis and necroptosis, whereas EFTUD2 and PRPF8 are required for optimal interferon response against viral infection. Moreover, we demonstrated that EFTUD2 restricts viral replication, both in a single cycle and multiple cycles of viral replication. Altogether, these results establish U5 snRNP core components as key elements of the cellular antiviral response.
Induction of Multiple Immune Signaling Pathways in Gryllodes sigillatus Crickets during Overt Viral Infections
Authors: Duffield Kristin R. , Foquet Bert , Stasko Judith A. , Hunt John , Sadd Ben M. , Sakaluk Scott K. , Ramirez José L.
Published: December 2022

Despite decades of focus on crickets (family: Gryllidae) as a popular commodity and model organism, we still know very little about their immune responses to microbial pathogens. Previous studies have measured downstream immune effects (e.g., encapsulation response, circulating hemocytes) following an immune challenge in crickets, but almost none have identified and quantified the expression of immune genes during an active pathogenic infection. Furthermore, the prevalence of covert (i.e., asymptomatic) infections within insect populations is becoming increasingly apparent, yet we do not fully understand the mechanisms that maintain low viral loads. In the present study, we measured the expression of several genes across multiple immune pathways in Gryllodes sigillatus crickets with an overt or covert infection of cricket iridovirus (CrIV). Crickets with overt infections had higher relative expression of key pathway component genes across the Toll, Imd, Jak/STAT, and RNAi pathways. These results suggests that crickets can tolerate low viral infections but can mount a robust immune response during an overt CrIV infection. Moreover, this study provides insight into the immune strategy of crickets following viral infection and will aid future studies looking to quantify immune investment and improve resistance to pathogens.
ViralVar: A Web Tool for Multilevel Visualization of SARS-CoV-2 Genomes
Authors: Alisoltani Arghavan , Jaroszewski Lukasz , Godzik Adam , Iranzadeh Arash , Simons Lacy M. , Dean Taylor J. , Lorenzo-Redondo Ramon , Hultquist Judd F. , Ozer Egon A.
Published: December 2022

The unprecedented growth of publicly available SARS-CoV-2 genome sequence data has increased the demand for effective and accessible SARS-CoV-2 data analysis and visualization tools. The majority of the currently available tools either require computational expertise to deploy them or limit user input to preselected subsets of SARS-CoV-2 genomes. To address these limitations, we developed ViralVar, a publicly available, point-and-click webtool that gives users the freedom to investigate and visualize user-selected subsets of SARS-CoV-2 genomes obtained from the GISAID public database. ViralVar has two primary features that enable: (1) the visualization of the spatiotemporal dynamics of SARS-CoV-2 lineages and (2) a structural/functional analysis of genomic mutations. As proof-of-principle, ViralVar was used to explore the evolution of the SARS-CoV-2 pandemic in the USA in pediatric, adult, and elderly populations (n > 1.7 million genomes). Whereas the spatiotemporal dynamics of the variants did not differ between these age groups, several USA-specific sublineages arose relative to the rest of the world. Our development and utilization of ViralVar to provide insights on the evolution of SARS-CoV-2 in the USA demonstrates the importance of developing accessible tools to facilitate and accelerate the large-scale surveillance of circulating pathogens.
The Optimized γ-Globin Lentiviral Vector GGHI-mB-3D Leads to Nearly Therapeutic HbF Levels In Vitro in CD34+ Cells from Sickle Cell Disease Patients
Authors: Drakopoulou Ekati , Georgomanoli Maria , Lederer Carsten , Panetsos Fottes , Kleanthous Marina , Voskaridou Ersi , Valakos Dimitrios , Papanikolaou Eleni , Anagnou Nicholas
Published: December 2022

We have previously demonstrated that both the original γ-globin lentiviral vector (LV) GGHI and the optimized GGHI-mB-3D LV, carrying the novel regulatory elements of the 3D HPFH-1 enhancer and the 3’ β-globin UTR, can significantly increase HbF production in thalassemic CD34+ cells and ameliorate the disease phenotype in vitro. In the present study, we investigated whether the GGHI-mB-3D vector can also exhibit an equally therapeutic effect, following the transduction of sickle cell disease (SCD) CD34+ cells at MOI 100, leading to HbF increase coupled with HbS decrease, and thus, to phenotype improvement in vitro. We show that GGHI-mB-3D LV can lead to high and potentially therapeutic HbF levels, reaching a mean 2-fold increase to a mean value of VCN/cell of 1.0 and a mean transduction efficiency of 55%. Furthermore, this increase was accompanied by a significant 1.6-fold HbS decrease, a beneficial therapeutic feature for SCD. In summary, our data demonstrate the efficacy of the optimized γ-globin lentiviral vector to improve the SCD phenotype in vitro, and highlights its potential use in future clinical SCD trials.
A Novel Rhabdovirus Associated with the Idaho Population of Potato Cyst Nematode Globodera pallida
Authors: Kud Joanna , Dahan Jennifer , Orellana Gardenia E. , Dandurand Louise-Marie , Karasev Alexander V.
Published: December 2022

Globodera pallida, a potato cyst nematode (PCN), is a quarantine endoparasitic pest of potato (Solanum tuberosum) in the US due to its effects on yield and quality of potato tubers. A new rhabdovirus, named potato cyst nematode rhabdovirus (PcRV), was revealed and characterized in the G. pallida populations collected in Idaho through use of high-throughput sequencing (HTS) and RT-PCR and found to be most closely related to soybean cyst nematode rhabdovirus (ScRV). PcRV has a 13,604 bp long, single-stranded RNA genome encoding five open reading frames, including four rhabdovirus-specific genes, N, P, G, and L, and one unknown gene. PcRV was found present in eggs, invasive second-stage juveniles, and parasitic females of G. pallida, implying a vertical transmission mode. RT-PCR and partial sequencing of PcRV in laboratory-reared G. pallida populations maintained over five years suggested that the virus is highly persistent and genetically stable. Two other Globodera spp. reproducing on potato and reported in the US, G. rostochiensis and G. ellingtonae, tested negative for PcRV presence. To the best of our knowledge, PcRV is the first virus experimentally found infecting G. pallida. Based on their similar genome organizations, the phylogeny of their RNA-dependent RNA polymerase domains (L gene), and relatively high identity levels in their protein products, PcRV and ScRV are proposed to form a new genus, provisionally named “Gammanemrhavirus”, within the family Rhabdoviridae.
Monkeypox Disease (MPOX) Perceptions among Healthcare Workers versus General Population during the First Month of the WHO Alert: Cross-Sectional Survey in Saudi Arabia
Authors: Temsah Mohamad-Hani , Aljamaan Fadi , Alenezi Shuliweeh , Abouammoh Noura , Alhasan Khalid , Dasuqi Shereen A. , Alhaboob Ali , Hamad Mohammed A. , Halwani Rabih , Alrabiaah Abdulkarim , Alsubaie Sarah , Alshahrani Fatimah S. , AlZamil Fahad , Memish Ziad A. , Barry Mazin , Al-Tawfiq Jaffar A.
Published: December 2022

Background: Monkeypox disease (MPOX) recently re-emerged in May 2022, causing international outbreaks in multiple non-endemic countries. This study demonstrates a novel comparison between the knowledge and perceptions of Saudi healthcare workers (HCWs) and the general public regarding MPOX. Methods: An online survey, conducted from 27 May to 5 June 2022, assessing participants’ MPOX and monkeypox virus (MPV) knowledge in terms of transmission, vaccination, isolation precautions, and their attitudes toward seeking more information. Results: A total of 1546 members of the public and 1130 HCWs completed the survey. Briefly, 61.3% of the public and 74.2% of HCWs showed interest in seeking more information about MPOX. Both groups had average overall mean MPOX knowledge scores. Members of the public holding university degrees and those showing high levels of worry regarding MPOX had significantly higher knowledge scores. However, HCWs showed a poor vaccination knowledge score, while only 57% recognized that MPOX can present similarly to COVID-19 in the early stages. Female HCWs and those with high self-rated MPOX awareness had significantly high knowledge scores. HCWs in secondary and tertiary centers had significantly higher knowledge scores. Conclusion: Both groups showed a decent attitude in terms of seeking more MPOX knowledge, which correlated positively with their worry about and awareness of the disease. These observations are mostly as a consequence of the ongoing COVID-19 pandemic, which encouraged the public and HCW to acquire more information about any novel emerging disease. Policymakers should make the most of this attitude in their awareness campaigns to prevent the spread of the disease and encourage vaccination in cases where it is needed. The knowledge gaps among HCWs were most evident in terms of clinical presentation and vaccinations; this problem needs addressing if we are to avoid further emerging MPOX cases.
Comparison of General Anxiety among Healthcare Professionals before and after COVID-19 Vaccination
Authors: Badami Zohair , Mustafa Hareem , Maqsood Afsheen , Aijaz Soha , Altamash Sara , Lal Abhishek , Saeed Sara , Ahmed Naseer , Yousofi Rahima , Heboyan Artak , Karobari Mohmed
Published: December 2022

Vaccination plays a crucial role in controlling the rate of coronavirus transmission and infectivity. Healthcare professionals are, in fact, at the greatest risk of contracting coronavirus due to their proximity and prolonged exposure to infected patients; this certitude alone enhances the stress and anxiety among patients and professionals alike. In this study, we aimed to assess the levels of anxiety experienced by healthcare professionals in their practices before and after getting vaccinated. This cross-sectional study was carried out in 2021. An electronic survey was distributed among the non-vaccinated and vaccinated healthcare workers. The survey consisted of the following parts: demographic characteristics, coronavirus-related questions, questions related to the specific field of healthcare professions, general anxiety questions, and working-hour-related questions. The Modified General Anxiety Scale (GAD-7) was used along with the paired t-test, Mann–Whitney U test, and Spearmen’s test for comparison. p ≤ 0.05 was considered statistically significant. A total of 798 healthcare professionals participated in the study. In this study, the majority of participants were females, with 598 (74.9%) being between the ages of 21 and 30, and 646 (80.9%) participants were graduates, with the majority being dentists. Non-vaccinated healthcare professionals had severe anxiety (30.9%), whereas, in vaccinated participants, anxiety levels were minimal (56.9%). A statistically significant correlation was discovered when comparing the scores of the vaccinated and non-vaccinated individuals as well as when comparing the professions of vaccinated participants, whereas no association was found with the gender and education level of participants. Vaccination is necessary for all entitled individuals to control the spread of coronavirus. It was discovered that there was an increase in anxiety levels before the vaccination was introduced. The anxiousness was greatly lessened following mass immunizations. Our research will help to raise public awareness of stigmatized mental health disorders in the healthcare industry.
Seasonal and Spatial Variability of Dissolved Nutrients in the Yenisei River
Authors: Tokareva Irina V. , Prokushkin Anatoly S.
Published: December 2022

The accelerated rates of warming in high latitudes lead to permafrost degradation, enhance nutrient cycling and intensify the transport of terrestrial materials to the Arctic rivers. The quantitative estimation of riverine nutrient flux on seasonal and spatial scales is important to clarify the ongoing changes in land–ocean connectivity in the Arctic domain. This study is focused on a multiyear (2015–2021) analysis of concentrations of dissolved nutrients in the Yenisei River. Applying stationary water sampling, we studied seasonal variations in concentrations of phosphate, nitrate, nitrite and ammonia ions in the Yenisei River in the upper (56.0° N), middle (60.9° N) and lower (67.4° N) sections of the river. The waters of the upper river section demonstrated significant and steady nutrient enrichment throughout the hydrological year, reflecting the influence of the Krasnoyarsk reservoir. The downstream reaches of the Yenisei River had more apparent seasonal patterns of nutrient concentrations. Particularly, winter-season nutrient levels in the middle and lower river sections were the highest during the hydrological year and close to the upper section. At snowmelt, and especially the summer–fall seasons, all inorganic nutrient concentrations dropped dramatically after the inflow of the Angara River. On the other hand, the peak nitrite content observed during the early spring flood was most pronounced in the lower section of the river basin, reflecting the specific characteristics of the nitrogen cycle in permafrost soils. The spring flood plays the major role in the annual nutrient fluxes, except for nitrates, for which the maximum occurred in the winter season. The summer–fall season, despite its duration and considerable water runoff, demonstrated the lowest fluxes of dissolved inorganic phosphorus and nitrogen in comparison to other periods of the hydrological year, suggesting strong biological uptake and chemostasis.