bluuebunny/crossref_metadata_2025 huggingface dataset:
A Machine Learning Model Based on GRU and LSTM to Predict the Environmental Parameters in a Layer House, Taking CO2 Concentration as an Example
Authors: Chen Xiaoyang , Yang Lijia , Xue Hao , Li Lihua , Yu Yao
Published: December 2023

In a layer house, the CO2 (carbon dioxide) concentration above the upper limit can cause the oxygen concentration to be below the lower limit suitable for poultry. This leads to chronic CO2 poisoning in layers, which manifests as listlessness, reduced appetite, weak constitution, decreased production performance, and weakened resistance to disease. Regulating ventilation may ensure a suitable CO2 concentration in layer houses. Predicting the changes in CO2 concentration and regulating the CO2 concentration in advance are key to ensuring healthy large-scale breeding of layers. In recent years, machine learning and deep learning methods have been increasingly applied to this field. A CO2 prediction model for layer house is proposed based on a GRU (gated recurrent unit) and LSTM (long short-term memory). The temperature, humidity, and CO2 were determined as inputs to the model by the correlation coefficient. The datasets of the experimental layer house were continuously measured during June–July 2023, using a self-developed environmental monitor, and the monitored data were used as samples for model inputs. There were 22,000 time series data in the datasets. In this study, multivariate time series data were standardized via data pre-processing to improve model training. GRU and LSTM models were constructed. The models were trained using a training set. Then, these trained models were used to provide predictions on a test set. The prediction errors were calculated using the true values of the test set and the predicted values provided by the models. To test the performance of the model and accuracy of the predictions, predictions were made for different numbers of datasets. The results demonstrated that the combined prediction model had good generalization, stability, and convergence with high prediction accuracy. Due to the structure of the model, the stability of the LSTM model was higher than that of the GRU model, and its prediction accuracy and speed were lower than those of the GRU model. When the datasets of the GRU model were 15,000 to 17,000, The MAE of the GRU was 70.8077 to 126.7029 ppm, and the prediction time of the GRU is 16 to 24 ms. When the LSTM model’s datasets were 15,000–20,000, the MAE of LSTM was 78.8596 to 136.0896 ppm, and the prediction time of the GRU was 17 to 26 ms.
A Touch on Musical Innovation: Exploring Wearables and Their Impact on New Interfaces for Musical Expression
Authors: Wexler David , Yip Joanne , Lee Ka-Po , Li Xiaolu , Wong Yiu-Hong
Published: December 2023

This paper explores the innovative concept of using wearable technologies as a medium for musical expression. Special emphasis is placed on a unique wearable device equipped with motion, touch, and acceleration sensors, which can be used as a wrist strap, hand strap, or surface drum pad. The aim is to create a new musical instrument that simplifies music learning and expression and makes them more intuitive. The wearable device contains 32 individual touch-sensitive pressure sensors, a nine-axis inertial-measurement-unit motion sensor, and various light-emitting diode and vibrational haptic-feedback components. The inclusion of tactile and intuitive features in the wearable device enhances the musical experience of users by enabling engaging interaction. Consequently, it is believed that this groundbreaking technology has significant potential to contribute to the field of music, providing musicians with a versatile and intuitive instrument that facilitates their creative expression.
Interacting Multiple Model Estimators for Fault Detection in a Magnetorheological Damper
Authors: Lee Andrew Sanghyun , Wu Yuandi , Gadsden Stephen Andrew , AlShabi Mohammad
Published: December 2023

This paper proposes a novel estimator for the purpose of fault detection and diagnosis. The interacting multiple model (IMM) strategy is effective for estimating the behaviour of systems with multiple operating modes. Each mode corresponds to a distinct mathematical model and is subject to a filtering process. This paper applies various model-based filters in combination with the IMM strategy. One such estimator employs the recently introduced extended sliding innovation filter (ESIF) known as the IMM-ESIF. The ESIF is an extension of the sliding innovation filter for nonlinear systems based on the sliding mode concept. In the presence of modeling uncertainties, the ESIF has been proven to be more robust compared to methods such as the extended Kalman filter (EKF). The novel IMM-ESIF strategy is also compared with the IMM strategy, which incorporates the unscented Kalman filter (UKF), referred to herein as IMM-UKF. While EKF uses Taylor series approximation to linearize the system model, the UKF uses sigma point to calculate the system’s mean and covariance. The methods were applied to an experimental magnetorheological (MR) damper setup, which was designed for testing control and estimation theory. Magnetorheological dampers exhibit a diverse array of applications in the automotive and aerospace sectors, with particular relevance to attenuating vibrations through adaptive suspension systems. Applied to a magnetorheological (MR) damper with distinct operating modes determined by the damper’s current, the results showcase the effectiveness of IMM-ESIF. In mixed operational conditions, IMM-ESIF demonstrates a notable 80% to 90% reduction in estimation error compared to its counterparts. Furthermore, it exhibits a 4% to 5% enhancement in correctly classifying operational modes, establishing IMM-ESIF as a promising and efficient alternative for adaptive estimation in electromechanical systems. The improved accuracy in estimating the system’s behaviour, even amidst uncertainties and mixed operational scenarios, signifies the potential of IMM-ESIF to significantly enhance the overall robustness and efficiency of estimations.
Reuse Distance-Aided Resource Selection Mechanisms for NR-V2X Sidelink Communication
Authors: Yin Jicheng , Hwang Seung-Hoon
Published: December 2023

Cellular vehicle-to-everything (C-V2X) facilitates direct communication between vehicles and other user equipment (UE) to improve the efficiency of the Internet of vehicles communication through sidelink. In addition, in the new radio vehicle-to-everything (NR-V2X) Mode 2, users can automatically select resources using the conventional sensing-based semi-persistent scheduling (SB-SPS) resource selection algorithm. This mechanism allows users to generate a list of available resources after a sensing window, after which the users can randomly select resources, and the resource can be used continuously over multiple periods before reselection. However, during the sensing window, neighbors may generate a similar list of available resources, and random selection may lead to resource conflicts. This phenomenon may lead to deteriorated communication performance and increased latency due to incorrect reception. Therefore, this paper proposes a reuse distance-aided resource selection (RD-RS) method which integrates resource reuse distance judgement with SB-SPS to mitigate resource conflicts and interference caused by random selection. Moreover, the reuse distance judgement is performed before the final resource selection, and whether the user will select the current resource depends on the reuse distance between that user and other occupiers. Furthermore, the performance of the proposed scheme is compared with other algorithms. Simulation results show that the proposed RD-RS not only achieves a higher packet reception ratio (PRR) but also effectively reduces the inter-packet gap (IPG). Moreover, in specific scenarios, the proposed method outperforms conventional schemes by 9% in terms of PRR and 70% in terms of Range.
Composition of Essential Oils from Fruits of Peucedanum longifolium and Rhizomatophora aegopodioides (Apiaceae) with Regard to Other Related Taxa—A Chemometric Approach
Authors: Ušjak Ljuboš , Niketić Marjan , Petrović Silvana
Published: December 2023

The aim of this work was to investigate the composition of essential oils isolated from fruits of Peucedanum longifolium, and Rhizomatophora aegopodioides (a species which was previously placed in the genus Peucedanum), as well as to compare the obtained results to those available for other previously investigated related species (including taxa which are also, according to some authors, excluded from the genus Peucedanum). Essential oils were obtained via hydrodistillation in a Clevenger-type apparatus and their composition was analyzed using GC-FID and GC-MS. To compare these data to those of previously investigated taxa, a chemometric approach was applied; the data were analyzed using multivariate statistical methods: non-metric multidimensional scaling (nMDS) and hierarchical cluster analysis. The most abundant in P. longifolium essential oil were monoterpenes (79.7%), mostly α-phellandrene (26.2%), β-phellandrene + limonene (21.0%) and myrcene (9.5%), followed by sesquiterpenes (18.3%), mostly germacrene B (9.5%). On the other hand, dominant in R. aegopodioides essential oil were non-terpenic aliphatic hydrocarbons (46.1%), mainly n-undecane (16.5%) and n-nonane (11.3%). In addition, this essential oil also contained a notable quantity of sesquiterpenes (25.1%), with (E)-sesquilavandulol being the most abundant (10.0%). The results of multivariate statistics revealed a clear separation of the essential oil composition of R. aegopodioides and P. longifolium, as well as of P. longifolium and P. officinale. The clustering of the samples of most of the taxa that do not belong to the Peucedanum in the narrow sense (sensu stricto) was also observed, which is in accordance with their recent inclusion in separate genera.
Sports Participation and Osteoarthritis in Females: A Systematic Review
Authors: Brent Magnus , Brent Mikkel Bo
Published: December 2023

Sports participation and the risk of osteoarthritis (OA) have been a concern for decades. Few research efforts have been dedicated to clarify this issue for females, although they are considered at greater risk of developing OA than males. In contrast, several reviews have established an association between sports participation and OA for males. The aim of the systematic review was to assess the association between OA and participation in popular sports for females. PubMed, Embase, and Google Scholar were searched and yielded 578 articles. Nine eligible studies were included and covered ballet (age range: 19–54 years), running or tennis (age range: 40–65 years), Olympic sports (age range: not specified), volleyball (age range: 16.0 ± 0.8 to 46.8 ± 5.1 years), and cross-country skiing (age range: 15 to ≥60 years). For females, participating in sports at an elite level was associated with a higher risk of OA and an increased need for surgical treatment. At non-elite level, it was associated with a higher risk of OA, but it did not materialize to an increased risk for surgical treatment. Few studies compared females and males, and these studies suggested that sex did not affect the risk of developing OA from participating in sports. Nevertheless, to isolate the precise effect of sports participation on the development of OA remains difficult as injuries are common among athletes and are independently associated with an increased risk of OA.
The Mediating Impact of Innovation Types in the Relationship between Innovation Use Theory and Market Performance
Authors: Chen Shieh-Liang , Chen Kuo-Liang
Published: December 2023

The ultimate goal of innovation is to improve performance. But if people’s needs and uses are ignored, innovation will only be a formality. In the past, research on innovation mostly focused on technology, processes, business models, services, and organizations. The measurement of innovation focuses on capabilities, processes, results, and methods, but there has always been a lack of pre-innovation measurements and tools. This study is the first to use the innovation use theory proposed by Christensen et al. combined with innovation types, and it uses the measurement focus on the early stage of innovation as a post-innovation performance prediction. This study collected 590 valid samples and used SPSS and the four-step BK method to conduct regression analysis and mediation tests. The empirical results obtained the following: (1) a confirmed model and scale of the innovation use theory; (2) that three constructs of innovation use theory have an impact on market performance; and (3) that innovation types acting as mediators will improve market performance. This study establishes an academic model of the innovation use theory to provide a clear scale tool for subsequent research. In practice, it can first measure the direction of innovation and performance prediction, providing managers with a reference when developing new products and applying market strategies.
Vulnerability and Inner Areas in Italy—“Should Young Stay or Should Young Go”? A Survey in the Molise Region
Authors: Grignoli Daniela , D’Ambrosio Mariangela , Boriati Danilo
Published: December 2023

This article explores the depopulation phenomenon in the context of the Molise region, an Inner Area in the south of Italy, considering it as an indicator of emerging social vulnerability. In particular, this paper presents the results of a quantitative study conducted in Molise on a non-probabilistic sample composed of 89 respondents through an online self-administered semi-structured questionnaire. This research may contribute to stimulating reflection on social vulnerability studies by explaining that, in the age of complexity, societies, although simple, are not builders of social capital capable of protecting against social vulnerability. In particular, the data reveal that more than 2/3 of the sample (+75%) do not participate in community activities (events at volunteer centers; civic and political activities; and events youth aggregation centers). For this reason, it is important to improve solidarity, which is the core of new strategies of proximity welfare that help to reduce depopulation.
Enhancing Anaerobic Biodegradation of Phenanthrene in Polluted Soil by Bioaugmentation and Biostimulation: Focus on the Distribution of Phenanthrene and Microbial Community Analysis
Authors: Xue Hanhan , Shi Yongsen , Qiao Junpeng , Li Xiaoqian , Liu Rutao
Published: December 2023

The remediation of polycyclic aromatic hydrocarbon (PAH)-contaminated soils has received much attention in recent years, and most of the contaminated sites are in anaerobic environments, such as deep soils and flooded soils. We simulated the natural flooded soil environment, selected phenanthrene (PHE) as a model PAH contaminant, and designed batch experiments run for 63 days to comprehensively investigate the effects of the combined addition of anaerobic sludge and granular biochar on microbial community and function and the anaerobic biodegradation of PHE. Firstly, the residue, distribution, and removal of PHE in the flooded soil environment were quantified for each group. Secondly, the effects of bioaugmentation of soil indigenous microorganisms by the addition of anaerobic activated sludge and biostimulation of biochar on the removal of PHE from the soil were analyzed against each other. Lastly, the changes in the structure of the microbial community under the effect of bioaugmentation and biostimulation were illustrated by sequencing analyses. The results of this study showed that the removal efficiency of PHE reached 72.0% after the addition of anaerobic activated sludge. The incorporation of anaerobic activated sludge and biochar resulted in a 25.3% increase in PHE removal compared to a single soil, suggesting that the combination of bioaugmentation and biostimulation can have a synergistic effect on the anaerobic biodegradation of PHE in contaminated soils. The results of sequencing analysis further indicated that the introduction of an exogenous microbial community changed the dominant genera associated with PHE degradation and introduced methanogenic archaea, which enriched the metabolic pathways of the carbon cycle in the system. On this basis, the addition of biochar resulted in higher anaerobic microbial community diversity, functional dominant species were enriched, and the direct interspecies electron transfer (DIET) process between electroactive bacteria (Bacteroides, f_Geobacteraceae) and Methanosaeta was facilitated, which accelerated the degradation of PHE by anaerobic microbial communities. The results of this study provide regulatory tools and basic data support for enhanced bioremediation of PAHs in flooded soils.
How Is the Utilities Sector Contributing to Building a Sustainable Future? A Systematic Literature Review of Sustainability Practices
Authors: D’Amore Gabriella , Testa Maria , Lepore Luigi
Published: December 2023

Utilities have a key role in the transition to a more economically and socially sustainable future. Driven by pressures from investors, regulators, government and society, companies across all sectors are setting bold ambitions for sustainability. However, they strongly depend on the utility industry meeting their own sustainability goals. Despite the relevance of their role, the determinants and obstacles to the adoption of sustainability practices by utility companies have been little investigated by scholars. This article aims to bridge this gap through a systematic literature review of 72 articles published from 1990 to 2023 in the accounting and management fields. After the analysis of bibliometric data and keywords used for science mapping, this study developed an in-depth review of the literature. Five different clusters, corresponding to the main research topics on which management and accounting literature has focused over the last 30 years, were identified. The results highlight that the expanding regulation and institutional pressures coming from governments, financial investors, consumers and society represent the primary factors that are driving utility companies toward sustainability. However, there are still several obstacles preventing utility companies from radically changing their business models, including the high costs associated with the technological and process innovations required. This study offers theoretical and practical contributions and policy implications. It contributes to systematizing literature on this topic, evidencing existing gaps and future research guidelines. It also outlines some managerial propositions that may be useful for practitioners, governments and policymakers.
Augmented Reality in A Sustainable Engineering Design Context: Understanding Students’ Collaboration and Negotiation Practices
Authors: Beheshti Mobina , Yujin Kang Eunice , Yan Shulong , Louime Emanuel , Hancock Caitlyn , Hira Avneet
Published: December 2023

This study reports on the use of augmented reality (AR) within the context of sustainable engineering design education. The objective of this study is to understand students’ collaboration and negotiation practices in a sustainable engineering design context using AR. The technology used in this study includes MERGE Cube (a physical cube that acts as a digital canvas for AR) and CoSpaces Edu (an online platform for students to build 3D creations and animate them with code). There have been 48 instances of student participation from upper elementary to middle school in four iterations of this study since February 2022. The research was conducted based on a design-based research methodology, and the data was collected through qualitative methods and analyzed using the intra-action analysis method. This study’s outcome revealed that interactions among participant dyads and with the technology shed light on distinct dynamics within collaborative sustainability-oriented learning and design processes. These diverse interactions collectively emphasize the multifaceted nature of collaborative design, where individual experiences, communication styles, and technological proficiency all play integral roles in shaping the collaborative process. In addition, the results of our research showed that the complexities inherent in negotiating ownership and collaboration dynamics are influenced by individual attitudes, timing of involvement, and previous experiences. Given the importance of collaboration in achieving sustainability-oriented goals, these findings are relevant to the field of sustainable engineering education, especially when working with younger children.
An Analysis of Recreational and Leisure Areas in Polish Counties with the Use of Geographically Weighted Regression
Authors: Nalej Marta , Lewandowicz Elżbieta
Published: December 2023

Recreational and leisure areas play a special role. These areas mitigate or eliminate the disadvantages of living in large cities, enhance the quality of life in small towns, and support sustainability. The aim of this study was to analyze the share of recreational and leisure areas in Polish counties in 2022. In Poland, recreational and leisure areas constitute a separate land-use category in cadastral registers. Annual cadastral data from the Land and Building Register at county level (in tabular form) were the main source of data for the study. The analysis revealed that the share of recreational and leisure areas was higher in counties situated in western and south-western Poland, as well as in cities. The spatially varied influence of socioeconomic factors on the share of recreational and leisure areas in Polish counties in 2002 was determined with the use of the local Moran’s I statistic and geographically weighted regression (GWR). The study confirmed that population density was significantly related to the share of recreational and leisure areas in Polish counties. The impact of the remaining socioeconomic factors associated with spatial and economic development varied across regions. The study also revealed that, in addition to the current socioeconomic determinants, the share of recreational and leisure areas in Polish counties was also influenced by historical factors and the counties’ development since their establishment.
Research Trends in Learning Needs Assessment: A Review of Publications in Selected Journals from 1997 to 2023
Authors: Choi Hee Jun , Park Ji Hye
Published: December 2023

This study analyzes existing research on learning needs assessments to identify key insights into the discipline and propose implications for future studies. Eighty-nine SSCI journal articles from 1997 to 2023 were reviewed. The findings are as follows. Firstly, concerning the nature of learning needs, prominent fields identified included education, social welfare, medicine and nursing, business, and psychology. Research identifying the learning needs of medical staff was the most prevalent, followed by K–12 teachers, lifelong learners without professional goals, university faculty, and social workers. Notably, Europe and North America were the primary research regions. Secondly, researchers mostly employed quantitative data, then combined methodologies, and qualitative data. Numerous studies involved only target learners in their needs assessments, with fewer involving stakeholders. Many studies did not employ multi-faceted approaches combining different source inputs or incorporating complementary needs assessment methods. Future needs assessment studies should involve diverse individuals and integrate indicators such as relevant test results or performance appraisal outcomes to obtain more trustworthy data for the needs assessment process. Most studies containing quantitative analysis components used mean values to determine learning needs. The ranked discrepancy model is recommended when conducting ordinal surveys for learning needs assessment to avoid misinterpretations and inaccurate conclusions.
Assessing the Importance of the Marine Chokepoint: Evidence from Tracking the Global Marine Traffic
Authors: Wang Xue , Du Debin , Peng Yan
Published: December 2023

The significance of international maritime chokepoints and the exploration of their safety and security are intricately linked to the expansion of the maritime economy, the maintenance of political and social stability, and the safeguarding of state interests. Limited efforts have been dedicated to comprehensively assessing the extent of chokepoints’ influence or establishing a global ranking of their importance using dependable maritime data. In light of the growing significance of oceans and seas in the realms of economy and society, there is a pressing need to afford heightened attention to the importance of chokepoints. In this paper, 15 critical chokepoints from around the world are studied, and the method of Location Quotient is used to calculate the influence of their radiation range utilizing the Automatic Identification System (AIS); this study charts the worldwide spatial and temporal dimensions of maritime transport spanning from 2012 to 2022. The conclusion of this study reveals the following key findings: (1) Maritime shipping trajectories exhibit fluctuating growth over time, with traffic hotspots predominantly located in continental border zones, gradually decreasing from the equator toward the poles; (2) The regions with active maritime traffic do not exhibit a positive correlation with the hotspots; instead, there is a pattern of “strong in the north, weak in the south, strong in the east, weak in the west”; (3) The Strait of Gibraltar and the Strait of Malacca are identified as the globally most strategically valuable straits for maritime shipping; (4) There is significant variation in the influence range of strategic passages, and countries with mutual dependencies may have competitive relationships.
Introduction to a Novel End-of-the-Year Special Issue of Surgeries
Authors: Sier Cornelis F. M.
Published: December 2023

Dear readers, authors, reviewers, and editors of Surgeries, [...]
Big Bang Nucleosynthesis Constraints and Indications for Beyond Standard Model Neutrino Physics
Authors: Kirilova Daniela , Panayotova Mariana , Chizhov Emanuil
Published: December 2023

We use Big Bang Nucleosynthesis (BBN) to probe Beyond Standard Model physics in the neutrino sector. Recently, the abundances of primordially produced light elements D and He-4 were determined from observations with better accuracy. The good agreement between the theoretically predicted abundances of primordially produced light elements and those derived from observations allows us to update the BBN constraints on Beyond Standard Model (BSM) physics. We provide numerical analysis of several BSM models of BBN and obtain precise cosmological constraints and indications for new neutrino physics. Namely, we derive more stringent BBN constraints on electron neutrino–sterile neutrino oscillations corresponding to 1% uncertainty of the observational determination of the primordial He-4. The cosmological constraints are obtained both for the zero and non-zero cases of the initial population of the sterile neutrino state. Then, in a degenerate BBN model with neutrino νe↔νs oscillations, we analyze the change in the cosmological constraints in case lepton asymmetry L is big enough to suppress oscillations. We obtain constraints on the lepton asymmetry L. We discuss a possible solution to the dark radiation problem in degenerate BBN models with νe↔νs oscillations in case L is large enough to suppress neutrino oscillations during the BBN epoch. Interestingly, the required value of L for solving the DR problem is close to the value of L indicated by the EMPRESS experiment, and also it is close to the value of lepton asymmetry that is necessary to relax Hubble tension.
On Normed Algebras and the Generalized Maligranda–Orlicz Lemma
Authors: Cichoń Mieczysław , Cichoń Kinga
Published: December 2023

In this paper, we discuss some extensions of the Maligranda–Orlicz lemma. It deals with the problem of constructing a norm in a subspace of the space of bounded functions, for which it becomes a normed algebra so that the norm introduced is equivalent to the initial norm of the subspace. This is done by satisfying some inequality between these norms. We show in this paper how this inequality is relevant to the study of operator equations in Banach algebras. In fact, we study how to equip a subspace of the space of bounded functions with a norm equivalent to a given one so that it is a normed algebra. We give a general condition for the construction of such norms, which allows us to easily check whether a space with a given norm is an algebra with a pointwise product and the consequences of such a choice for measures of noncompactness in such spaces. We also study quasi-normed spaces. We introduce a general property of measures of noncompactness that allows the study of quadratic operator equations, prove a fixed-point theorem suitable for such problems, and complete the whole with examples and applications.
Revitalizing Skin Repair: Unveiling the Healing Power of Livisin, a Natural Peptide Calcium Mimetic
Authors: Zhan Xuehui , Wang Danni , Wang Hanfei , Chen Hui , Wu Xinyi , Li Tao , Qi Junmei , Chen Tianbao , Wu Di , Gao Yitian
Published: December 2023

When the skin is damaged, accelerating the repair of skin trauma and promoting the recovery of tissue function are crucial considerations in clinical treatment. Previously, we isolated and identified an active peptide (livisin) from the skin secretion of the frog Odorrana livida. Livisin exhibited strong protease inhibitory activity, water solubility, and stability, yet its wound-healing properties have not yet been studied. In this study, we assessed the impact of livisin on wound healing and investigated the underlying mechanism contributing to its effect. Our findings revealed livisin effectively stimulated the migration of keratinocytes, with the underlying mechanisms involved the activation of CaSR as a peptide calcium mimetic. This activation resulted in the stimulation of the CaSR/E-cadherin/EGFR/ERK signaling pathways. Moreover, the therapeutic effects of livisin were partially reduced by blocking the CaSR/E-cadherin/EGFR/ERK signaling pathway. The interaction between livisin and CaSR was further investigated by molecular docking. Additionally, studies using a mouse full-thickness wound model demonstrated livisin could accelerate skin wound healing by promoting re-epithelialization and collagen deposition. In conclusion, our study provides experimental evidence supporting the use of livisin in skin wound healing, highlighting its potential as an effective therapeutic option.
Generation and Characterization of a Multi-Functional Panel of Monoclonal Antibodies for SARS-CoV-2 Research and Treatment
Authors: Patterson Lila D. , Dubansky Benjamin D. , Dubansky Brooke H. , Stone Shannon , Kumar Mukesh , Rice Charles D.
Published: December 2023

The Coronavirus disease 2019 (COVID-19) pandemic caused by Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) is an ongoing threat to global public health. To this end, intense efforts are underway to develop reagents to aid in diagnostics, enhance preventative measures, and provide therapeutics for managing COVID-19. The recent emergence of SARS-CoV-2 Omicron variants with enhanced transmissibility, altered antigenicity, and significant escape of existing monoclonal antibodies and vaccines underlines the importance of the continued development of such agents. The SARS-CoV-2 spike protein and its receptor binding domain (RBD) are critical to viral attachment and host cell entry and are primary targets for antibodies elicited from both vaccination and natural infection. In this study, mice were immunized with two synthetic peptides (Pep 1 and Pep 2) within the RBD of the original Wuhan SARS-CoV-2, as well as the whole RBD as a recombinant protein (rRBD). Hybridomas were generated, and a panel of three monoclonal antibodies, mAb CU-P1-1 against Pep 1, mAb CU-P2-20 against Pep 2, and mAb CU-28-24 against rRBD, was generated and further characterized. These mAbs were shown by ELISA to be specific for each immunogen/antigen. Monoclonal antibody CU-P1-1 has limited applicability other than in ELISA approaches and basic immunoblotting. Monoclonal antibody CU-P2-20 is shown to be favorable for ELISA, immunoblotting, and immunohistochemistry (IHC), however, not live virus neutralization. In contrast, mAb CU-28-24 is most effective at live virus neutralization as well as ELISA and IHC. Moreover, mAb CU-28-24 is active against rRBD proteins from Omicron variants BA.2 and BA.4.5 as determined by ELISA, suggesting this mAb may neutralize live virus of these variants. Each of the immunoglobulin genes has been sequenced using Next Generation Sequencing, which allows the expression of respective recombinant proteins, thereby eliminating the need for long-term hybridoma maintenance. The synthetic peptides and hybridomas/mAbs and quantitative antigen-binding data are under the intellectual property management of the Clemson University Research Foundation, and the three CDRs have been submitted as an invention disclosure for further patenting and commercialization.
Identification of Putative Novel Rotavirus H VP7, VP4, VP6 and NSP4 Genotypes in Pigs
Authors: Ferrari Elena , Vignola Greta , Bertasio Cristina , Chiapponi Chiara , Alborali Giovanni Loris , Martella Vito , Boniotti Maria Beatrice
Published: December 2023

Rotavirus H (RVH) has been detected in humans, pigs and bats. Recently, RVH infections were reported in different porcine farms worldwide, suggesting epidemiological relevance. However, to date, the genome information of RVH strains has been limited due to the scarcity of deposited sequences. This study aimed to characterize the VP7, VP4, VP6 and NSP4 genes of RVHs from 27 symptomatic pigs, in Italy, between 2017 and 2021. RVH genes were amplified via RT-PCR using specific primers, and the amplicons were sequenced. By coupling the data generated in this study with the sequences available in the databases, we elaborated a classification scheme useful to genotype the VP7, VP4, VP6 and NSP4 genes. The nucleotide identity and phylogenetic analyses unveiled an impressive genetic heterogeneity and allowed the classification of the Italian RVH strains into 12G (VP7), 6P (VP4), 8I (VP6) and 8E (NSP4) genotypes, of which 6I, 5E and the totality of the G and P genotypes were of novel identification. Our data highlight the high genetic variability of the RVH strains circulating in pigs and underline the importance of a robust classification system to track the epidemiology of RVHs.
Serological and Molecular Characterization of Occult HBV Infection in Blood Donors from South Italy
Authors: Damiani Alessia Sticchi , Holzmayer Vera , Galli Claudio , De Nuzzo Mariangela , Anderson Mark , Cloherty Gavin , Di Renzo Nicola
Published: December 2023

Despite good vaccine coverage and careful blood donor selection policies, hepatitis B virus (HBV) is still the most frequent viral infection among blood donors (BDs) in Italy, mostly in the occult form (OBI). We studied the virological features of OBI in BDs from South Italy by serology, molecular testing for HBV-DNA, and sequencing for HBV genotypes and mutations. One hundred and two samples from 95 BDs (22.1% first time, 87.9% regular, median age 57 years) positive for HBV-DNA and negative for HBsAg were retrospectively analyzed. HBV biomarkers were detected in 96.9% (anti-HBc in 44.2%, anti-HBc plus anti-HBs in 49.5%, anti-HBs alone in 3.2%). No risk factor was declared by 45.3% of donors. HBV-DNA levels were very low (median: 7 IU/mL). All samples harbored HBV genotype D and single or multiple mutations in the S gene were found in 28/36 sequences analyzed and in 75% of donors. Mutations were unrelated to gender, donor group or serological patterns. An HBsAg assay with enhanced sensitivity was positive in samples from seven donors (7.4%), two of which negative for HBV-DNA by real-time PCR. OBI still represents a risk for HBV transmission from blood donations; screening by highly sensitive serological and molecular assays is warranted.
Antiviral Activity of Ailanthone from Ailanthus altissima on the Rice Stripe Virus
Authors: Tan Qingwei , Zhu Jianxuan , Ju Yuanyuan , Chi Xinlin , Cao Tangdan , Zheng Luping , Chen Qijian
Published: December 2023

Rice stripe disease caused by the rice stripe virus (RSV), which infects many Poaceae species in nature, is one of the most devastating plant viruses in rice that causes enormous losses in production. Ailanthone is one of the typical C20 quassinoids synthesized by the secondary metabolism of Ailanthus altissima, which has been proven to be a biologically active natural product with promising prospects and great potential for use as a lead structure for pesticide development. Based on the achievement of the systemic infection and replication of RSV in Nicotiana benthamiana plants and rice protoplasts, the antiviral properties of Ailanthone were investigated by determining its effects on viral-coding RNA gene expression using reverse transcription polymerase chain reaction, and Western blot analysis. Ailanthone exhibited a dose-dependent inhibitory effect on RSV NSvc3 expression in the assay in both virus-infected tobacco plants and rice protoplasts. Further efforts revealed a potent inhibitory effect of Ailanthone on the expression of seven RSV protein-encoding genes, among which NS3, NSvc3, NS4, and NSvc4 are the most affected genes. These facts promoted an extended and greater depth of understanding of the antiviral nature of Ailanthone against plant viruses, in addition to the limited knowledge of its anti-tobacco mosaic virus properties. Moreover, the leaf disc method introduced and developed in the study for the detection of the antiviral activity of Ailanthone facilitates an available and convenient screening method for anti-RSV natural products or synthetic chemicals.
How to Break through the Bottlenecks of in Ovo Vaccination in Poultry Farming
Authors: Li Xuefeng , Liu Xiaoxiao , Cui Lu , Liu Zheyi , Zhang Yu , Li Hai
Published: December 2023

Poultry farming is one of the pillar industries of global animal husbandry. In order to guarantee production, poultry are frequently vaccinated from the moment they are hatched. Even so, the initial immunity of chicks is still very poor as they are in the “window period” of immune protection. In ovo vaccination pushes the initial immunization time forward to the incubation period, thereby providing earlier immune protection for chicks. In ovo vaccination is currently a research hotspot of poultry disease prevention and control, which is in line with the intensification of poultry production. However, the vaccines currently available for in ovo vaccination are limited and cannot meet the needs of industrial development, so how to efficiently activate the adaptive immune response of chicken embryos becomes the key to restrict product development and technological progress of in ovo vaccination. Its breakthrough, to a large extent, depends on systematic illustration of the mechanism underlying the adaptive immune response post immunization. Clarification of this issue will provide us with theoretical support and potential solutions for the development of novel vaccines for in ovo vaccination, the augmentation of efficacy of current vaccines and the optimization of immune programs.
Outer Membrane Vesicles from Acinetobacter baumannii: Biogenesis, Functions, and Vaccine Application
Authors: Weng Zheqi , Yang Ning , Shi Shujun , Xu Zining , Chen Zixu , Liang Chen , Zhang Xiuwei , Du Xingran
Published: December 2023

This review focuses on Acinetobacter baumannii, a Gram-negative bacterium that causes various infections and whose multidrug resistance has become a significant challenge in clinical practices. There are multiple bacterial mechanisms in A. baumannii that participate in bacterial colonization and immune responses. It is believed that outer membrane vesicles (OMVs) budding from the bacteria play a significant role in mediating bacterial survival and the subsequent attack against the host. Most OMVs originate from the bacterial membranes and molecules are enveloped in them. Elements similar to the pathogen endow OMVs with robust virulence, which provides a new direction for exploring the pathogenicity of A. baumannii and its therapeutic pathways. Although extensive research has been carried out on the feasibility of OMV-based vaccines against pathogens, no study has yet summarized the bioactive elements, biological activity, and vaccine applicability of A. baumannii OMVs. This review summarizes the components, biogenesis, and function of OMVs that contribute to their potential as vaccine candidates and the preparation methods and future directions for their development.
Towards Optimisation of Microalgae Cultivation through Monitoring and Control in Membrane Photobioreactor Systems
Authors: Mora-Sánchez Juan Francisco , Ribes Josep , González-Camejo Josué , Seco Aurora , Ruano María Victoria
Published: December 2023

This research lays a foundation for optimised membrane photobioreactor performance and introduces novel control parameters crucial for advancing microalgae cultivation techniques and promoting environmental sustainability. Particularly, this study presents an innovative solids retention time (SRT) controller designed for a pilot-scale membrane photobioreactor. Employing a fuzzy-logic knowledge-based approach, this controller uses the first derivative of pH data dynamics (pH′) as an input variable, directly correlated with nitrogen recovery rate and biomass productivity when normalised by average light irradiance (I2). Through a feedback mechanism, it regulates daily SRT variations, ensuring stable reactor operation, optimal volatile suspended solids concentration, efficient nitrogen removal, and enhanced biomass productivity. Normalised nitrogen recovery rate, considering solar light irradiance and volatile suspended solids concentration, increased by 51% compared to previous studies employing fixed SRT and hydraulic retention time (HRT). Combining this SRT controller with a previously studied HRT controller could potentially amplify biomass productivity efficiency. In addition, controlling or not controlling the HRT and SRT are assessed in terms of filtration performance and GHG emissions. Finally, a new dissolved-oxygen-based parameter shows promise for continuous microalgae culture control.
‘Squeezing Out’ the Nile Delta’s Drainage Water to Irrigate Egypt’s Desert Land
Authors: Tawfik Mohamed , Hoogesteger Jaime , Moussa Moustafa , Hellegers Petra
Published: December 2023

Egypt’s quota of Nile River water has been constant since the 1950s, despite the continual agricultural land expansion. To facilitate land reclamation, Egypt has reallocated Nile water from downstream users, mostly smallholders in the ‘old lands’ of the Delta. As water demands have grown, more attention has gone to the reuse of waste/drainage water as a reliable source for irrigated agriculture in the “old lands”. Recently, new mega plants for drainage water treatment have been built to promote reclamation of ‘new lands’ in desert-front governorates located outside the Nile Delta. Through these plants and the related water conveyance infrastructure, drainage water from the ‘old lands’ is now being collected, treated, and reallocated to these newly reclaimed areas. This article scrutinizes this transformation of access to drainage water, examining who benefits and what implications it holds for smallholder farmers in the old lands. The analysis suggests that waste/drainage water reclamation schemes do not tap into unused water but actually risk depriving smallholders in the Nile Delta of water access. It argues that more attention should be given to existing informal reuse arrangements and that smallholders’ access to water is guaranteed in light of new drainage water reuse projects.
Assessment of Physicochemical Parameters by Remote Sensing of Bacalar Lagoon, Yucatán Peninsula, Mexico
Authors: Hernández-Martínez José Luis , Perera-Burgos Jorge Adrián , Acosta-González Gilberto , Alvarado-Flores Jesús , Li Yanmei , Leal-Bautista Rosa María
Published: December 2023

Remote sensing is an invaluable research tool for the analysis of marine and terrestrial water bodies. However, it has some technical limitations in waters with oligotrophic conditions or close to them due to the low spectral response of some water parameters to the signal from the sensors to be used. In this work, we use remote sensing to evaluate a set of water quality parameters (dissolved oxygen, total dissolved solids, oxidation–reduction potential, electrical conductivity, salinity, and turbidity) in the Bacalar Lagoon, located in the Mexican Caribbean, which has experienced in recent years a dramatic change from its natural oligotrophic condition to mesotrophic and eutrophic due to anthropogenic contamination. This was accomplished through the correlation and linear regression analysis between reflectance images processed from Landsat 8 and Sentinel 2, with in situ measurements for each physicochemical parameter considered, and the development of statistical models to predict their values in places where only the reflectance values were available. The results of this work indicate the feasibility of using remote sensing to monitor electrical conductivity, salinity, turbidity, and total dissolved solids since their predicted values agree with those reported at various sites within this lagoon.
Multi-Station Hydrological Modelling to Assess Groundwater Recharge of a Vast Semi-Arid Basin Considering the Problem of Lack of Data: A Case Study in Seybouse Basin, Algeria
Authors: Inan Cagri Alperen , Maoui Ammar , Lucas Yann , Duplay Joëlle
Published: December 2023

Water resource management scenarios have become more crucial for arid to semi-arid regions. Their application prerequisites rigorous hydrological modelling approaches since data are usually exposed to uncertainties and inaccuracies. In this work, Soil Water Assessment Tool (SWAT), an open source semi-distributed, continuous-time, process-based physical hydrological model is used to model hydrological processes and eventually calculate groundwater recharge estimations in Seybouse basin, Northeast Algeria. The model uses estimated rainfall to calibrate the model with observed discharge from hydrometric stations. Model calibration and validation are performed over four hydrometric stations located in the basin. Uncertainty analysis and sensitivity analysis supported the calibration period. SUFI-2 algorithm is used for uncertainty estimations along with a global sensitivity analysis prior to calibration simulations. Simulated flood hydrographs showed generally good accuracy with few misfits on the peaks. The model obtained satisfactory and consistent calibration and validation results for which the Nash score varied from 0.5 to 0.7 for calibration and from −0.1 to 0.6 for validation and R2 from 0.6 to 0.7 for calibration and 0.03 to 0.8 for validation. Moreover, estimated water budget values show strong similarities with the observed values found in the literature. The present work shows that the rigorously calibrated and validated SWAT model can simulate hydrological processes as well as major high and low flows using estimated rainfall data.