bluuebunny/crossref_metadata_2025 huggingface dataset:
Manufacturing of a PET Filament from Recycled Material for Material Extrusion (MEX)
Authors: Bustos Seibert Maximilian , Mazzei Capote Gerardo Andres , Gruber Maximilian , Volk Wolfram , Osswald Tim A.
Published: September 2022

Due to its low cost and easy use, the use of material extrusion (MEX) as an additive manufacturing (AM) technology has increased rapidly in recent years. However, this process mainly involves the processing of new plastics. Combining the MEX process with polyethylene terephthalate (PET), which offers a high potential for mechanical and chemical recyclability, opens up a broad spectrum of reutilization possibilities. Turning used PET bottles into printable filament for MEX is not only a recycling option, but also an attractive upcycling scenario that can lead to the production of complex, functional parts. This work analyzes the process of extruding recycled PET bottle flakes into a filament, taking different extrusion screws and extrusion parameters into account. The filament is subsequently processed with MEX into tensile tests. An accompanying thermal, rheological and mechanical characterization of the recycled resin is performed to offer a comparison to the virgin material and a commercially available glycol modified polyethylene terephthalate (PETG) filament. The results show the importance of adequate drying parameters prior to the extrusion and the sensitivity of the material to moisture, leading to degradation. The recycled material is more prone to degradation and presents lower viscosities. Mechanical tests display a higher tensile strength of the recycled and virgin resin in comparison to the PETG. The extrusion of the used PET into a filament and the subsequent printing with the MEX process offers a viable recycling process for the discarded material.
Max Scheler’s Movement of Love and the Object of Religious Experience
Authors: Nyaku Kobla
Published: September 2022

In this paper, I explore the implications of Max Scheler’s concept of the movement of love, and I show that this movement, for him, constitutes not only the core of human nature but also the metaphysical presupposition upon which the nature of the object of religious experience could be understood. I argue that Scheler’s unique way of blending intellectual knowledge of essences and spiritual intuition, i.e., metaphysics and religion, respectively, makes his position extremely interesting for present-day interpretations of religious experiences. The question then is, could religious experiences, such as awe, bliss, reverence, and revelation, be said to be given only in spiritually participating in the movement of love—and could this participation be the defining factor of these experiences?
A Review on Locomotion Mode Recognition and Prediction When Using Active Orthoses and Exoskeletons
Authors: Moreira Luís , Figueiredo Joana , Cerqueira João , Santos Cristina P.
Published: September 2022

Understanding how to seamlessly adapt the assistance of lower-limb wearable assistive devices (active orthosis (AOs) and exoskeletons) to human locomotion modes (LMs) is challenging. Several algorithms and sensors have been explored to recognize and predict the users’ LMs. Nevertheless, it is not yet clear which are the most used and effective sensor and classifier configurations in AOs/exoskeletons and how these devices’ control is adapted according to the decoded LMs. To explore these aspects, we performed a systematic review by electronic search in Scopus and Web of Science databases, including published studies from 1 January 2010 to 31 August 2022. Sixteen studies were included and scored with 84.7 ± 8.7% quality. Decoding focused on level-ground walking along with ascent/descent stairs tasks performed by healthy subjects. Time-domain raw data from inertial measurement unit sensors were the most used data. Different classifiers were employed considering the LMs to decode (accuracy above 90% for all tasks). Five studies have adapted the assistance of AOs/exoskeletons attending to the decoded LM, in which only one study predicted the new LM before its occurrence. Future research is encouraged to develop decoding tools considering data from people with lower-limb impairments walking at self-selected speeds while performing daily LMs with AOs/exoskeletons.
Assessment of Individual-Level Exposure to Airborne Particulate Matter during Periods of Atmospheric Thermal Inversion
Authors: Novak Rok , Robinson Johanna Amalia , Kanduč Tjaša , Sarigiannis Dimosthenis , Kocman David
Published: September 2022

Air pollution exposure is harmful to human health and reducing it at the level of an individual requires measurements and assessments that capture the spatiotemporal variability of different microenvironments and the influence of specific activities. In this paper, activity-specific and general indoor and outdoor exposure during and after a period of high concentrations of particulate matter (PM), e.g., an atmospheric thermal inversion (ATI) in the Ljubljana subalpine basin, Slovenia, was assessed. To this end, personal particulate matter monitors (PPM) were used, worn by participants of the H2020 ICARUS sampling campaigns in spring 2019 who also recorded their hourly activities. ATI period(s) were determined based on data collected from two meteorological stations managed by the Slovenian Environmental Agency (SEA). Results showed that indoor and outdoor exposure to PM was significantly higher during the ATI period, and that the difference between mean indoor and outdoor exposure to PM was much higher during the ATI period (23.0 µg/m3) than after (6.5 µg/m3). Indoor activities generally were associated with smaller differences, with cooking and cleaning even having higher values in the post-ATI period. On the other hand, all outdoor activities had higher PM values during the ATI than after, with larger differences, mostly >30.0 µg/m3. Overall, this work demonstrated that an individual-level approach can provide better spatiotemporal resolution and evaluate the relative importance of specific high-exposure events, and in this way provide an ancillary tool for exposure assessments.
High Sensitivity Cryogenic Temperature Sensors Based on Arc-Induced Long-Period Fiber Gratings
Authors: Ivanov Oleg V. , Caldas Paulo , Rego Gaspar
Published: September 2022

In this paper, we investigated the evolution of the dispersion curves of long-period fiber gratings (LPFGs) from room temperature down to 0 K. We considered gratings arc-induced in the SMF28 fiber and in two B/Ge co-doped fibers. Computer simulations were performed based on previously published experimental data. We found that the dispersion curves belonging to the lowest-order cladding modes are the most affected by the temperature changes, but those changes are minute when considering cladding modes with dispersion turning points (DTP) in the telecommunication windows. The temperature sensitivity is higher for gratings inscribed in the B/Ge co-doped fibers near DTP and the optimum grating period can be chosen at room temperature. A temperature sensitivity as high as −850 pm/K can be obtained in the 100–200 K temperature range, while a value of −170 pm/K is reachable at 20 K.
A Novel Supervised Filter Feature Selection Method Based on Gaussian Probability Density for Fault Diagnosis of Permanent Magnet DC Motors
Authors: Wang Weihao , Lu Lixin , Wei Wang
Published: September 2022

For permanent magnet DC motors (PMDCMs), the amplitude of the current signals gradually decreases after the motor starts. In this work, the time domain features and time-frequency-domain features extracted from several successive segments of current signals make up a feature vector, which is adopted for fault diagnosis of PMDCMs. Many redundant features will lead to a decrease in diagnosis efficiency and increase the computation cost, so it is necessary to eliminate redundant features and features that have negative effects. This paper presents a novel supervised filter feature selection method for reducing data dimension by employing the Gaussian probability density function (GPDF) and named Gaussian vote feature selection (GVFS). To evaluate the effectiveness of the proposed GVFS, we compared it with the other five filter feature selection methods by utilizing the PMDCM’s data. Additionally, Gaussian naive Bayes (GNB), k-nearest neighbor algorithm (k-NN), and support vector machine (SVM) are utilized for the construction of fault diagnosis models. Experimental results show that the proposed GVFS has a better diagnostic effect than the other five feature selection methods, and the average accuracy of fault diagnosis improves from 97.89% to 99.44%. This paper lays the foundation of fault diagnosis for PMDCMs and provides a novel filter feature selection method.
A Graph-Neural-Network-Based Social Network Recommendation Algorithm Using High-Order Neighbor Information
Authors: Yu Yonghong , Qian Weiwen , Zhang Li , Gao Rong
Published: September 2022

Social-network-based recommendation algorithms leverage rich social network information to alleviate the problem of data sparsity and boost the recommendation performance. However, traditional social-network-based recommendation algorithms ignore high-order collaborative signals or only consider the first-order collaborative signal when learning users’ and items’ latent representations, resulting in suboptimal recommendation performance. In this paper, we propose a graph neural network (GNN)-based social recommendation model that utilizes the GNN framework to capture high-order collaborative signals in the process of learning the latent representations of users and items. Specifically, we formulate the representations of entities, i.e., users and items, by stacking multiple embedding propagation layers to recursively aggregate multi-hop neighborhood information on both the user–item interaction graph and the social network graph. Hence, the collaborative signals hidden in both the user–item interaction graph and the social network graph are explicitly injected into the final representations of entities. Moreover, we ease the training process of the proposed GNN-based social recommendation model and alleviate overfitting by adopting a lightweight GNN framework that only retains the neighborhood aggregation component and abandons the feature transformation and nonlinear activation components. The experimental results on two real-world datasets show that our proposed GNN-based social recommendation method outperforms the state-of-the-art recommendation algorithms.
Intelligent Detection of Hazardous Goods Vehicles and Determination of Risk Grade Based on Deep Learning
Authors: An Qing , Wu Shisong , Shi Ruizhe , Wang Haojun , Yu Jun , Li Zhifeng
Published: September 2022

Currently, deep learning has been widely applied in the field of object detection, and some relevant scholars have applied it to vehicle detection. In this paper, the deep learning EfficientDet model is analyzed, and the advantages of the model in the detection of hazardous good vehicles are determined. The adaptive training model is built based on the optimization of the training process, and the training model is used to detect hazardous goods vehicles. The detection results are compared with Cascade R-CNN and CenterNet, and the results show that the proposed method is superior to the other two methods in two aspects of computational complexity and detection accuracy. Simultaneously, the proposed method is suitable for the detection of hazardous goods vehicles in different scenarios. We make statistics on the number of detected hazardous goods vehicles at different times and places. The risk grade of different locations is determined according to the statistical results. Finally, the case study shows that the proposed method can be used to detect hazardous goods vehicles and determine the risk level of different places.
How the Experience Designs of Sustainable Festive Events Affect Cultural Emotion, Travel Motivation, and Behavioral Intention
Authors: Yen Hui-Yun
Published: September 2022

Festivals are an important aspect of cultural design. They not only attract a large number of tourists but are also one of the most direct ways of promoting local culture. This study aimed to discover how festival experiences affect cultural feelings, travel motivations, and behavioral intentions. Based on literature research, theoretical model construction, and analysis, this paper begins with an exploration of the literature and designs a structural model to validate consumers’ expectations and conceptions of the 2021 Tainan Chihsi Festival. A total of 238 residents from Taiwan answered the questionnaire. This study used SEM and ANOVA for data analysis. The impact model of the festival experience design presented here can provide reference standards for in-depth research in related fields. Moreover, cultural emotion is a critical component in designing influential festive event experiences that evoke travel motivations and behavioral intentions. Virtual events can emphasize personal elements and educational content. In-person events can emphasize group interaction and entertainment. A combination of virtual and in-person experiences or personal and group exchanges would be ideal. Organizers should consider including emotional elements in their festive events in addition to originality. The inclusion of cultural elements can also foster “shared” experiences between locals and visitors, diversifying urban landscapes and strengthening community interaction. Organizers can plan festive events that align with consumers’ expectations, distinguish festive events from other community events, and add uniqueness and originality to their events.
Airborne Pollen, Allergens, and Proteins: A Comparative Study of Three Sampling Methods
Authors: Suanno Chiara , Sandrini Silvia , Aloisi Iris , De Nuntiis Paola , Facchini Maria Cristina , Del Duca Stefano , Fernández-González Delia
Published: September 2022

Nowadays, there is a wide range of different methods available for the monitoring of pollen and allergens, but their relative efficiency is sometimes unclear, as conventional pollen monitoring does not thoroughly describe pollen allergenicity. This study aims to evaluate airborne pollen, allergen, and protein levels, associating them with meteorological and chemical parameters. The sampling was performed in Bologna (Italy) during the grass flowering period, with three different devices: a Cyclone sampler (CS), a Dicothomous sampler (DS), and a Berner impactor (BI). Total proteins were extracted from aerosol samples, and grass allergens Phl p 1 and Phl p 5 were quantified by ELISA. Airborne Poaceae pollen concentrations were also evaluated, using a Hirst-type trap. Proteins and allergens collected by CS resulted about ten times higher than those collected by the other two instruments, possibly due to their different cut-offs, while DS and BI results appeared consistent only for the total proteins collected in the fine fraction (1.3 vs. 1.6 μg/m3). Airborne proteins correlated neither with Poaceae pollen nor with its aeroallergens, while aeroallergens correlated with pollen only in the coarse particulate, indicating the presence of pollen-independent aeroallergens in the fine particulate, promoted by high wind speed.
The Plant Species Composition of an Abandoned Meadow as an Element of an Ecosystem Mosaic within an Urban-Industrial Landscape
Authors: Błońska Agnieszka , Chmura Damian , Hutniczak Agnieszka , Wilczek Zbigniew , Jarosz Jacek , Besenyei Lynn , Woźniak Gabriela
Published: September 2022

The absence of traditional management in grasslands is responsible for the consequent changes in plant community species composition and diversity of this habitat in Europe. The common reason for these changes is the spread of expansive native species such as Calamagrostis epigejos (L.) Roth and their subsequent dominance over other component species. The aim of the study was to determine the effect of management treatments (e.g., mowing, harvesting biomass) and their frequency of application (e.g., once or twice a year) on the cover abundance of C. epigejos (L.) Roth and the subsequent changes in component grassland species richness and diversity (Shannon–Wiener index) of an abandoned meadow in Silesia in S. Poland. A difference in species richness was found after five years of mowing, but an increase in species diversity appeared only after seven years of the treatments. Significant increases in species richness and Shannon–Wiener index and a significant decrease in cover abundance of C. epigejos (L.) Roth were recorded after different periods and for different treatments.
Uncovering Inequalities in Food Accessibility between Koreans and Japanese in 1930s Colonial Seoul Using GIS and Open-Source Transport Analytics Tools
Authors: Ha Hui Jeong , Lee Jinhyung , Kim Junghwan , Kim Youngjoon
Published: September 2022

This study aimed to investigate the disparities and inequalities in food accessibility in colonial Seoul (Keijo [京城] in Japanese, and Gyeongseong [경성] in Korean) in the 1930s, using a geographic information system (GIS) and open-source transport analytics tools. We specifically focused on the unique social standing of people in the colonial era, namely colonial rulers (Japanese) vs. subjects (Koreans) and examined whether neighborhoods with larger proportions of colonial rulers had more access to food opportunities. For a comprehensive evaluation, we computed food accessibility by multiple transport modes (e.g., public transit and walking), as well as by different time budgets (e.g., 15 min and 30 min) and considered various sets of food options—including rice, meat, seafood, general groceries, vegetables, and fruits—when measuring and comparing accessibility across neighborhoods in colonial Seoul. We took a novel digital humanities approach by synthesizing historical materials and modern, open-source transport analysis tools to compute cumulative opportunity-based accessibility measures in 1930s colonial Seoul. The results revealed that Japanese-dominant neighborhoods had higher accessibility by both public transit and walking than Korean-dominant neighborhoods. The results further suggest that inequality and disparity in food accessibility is observed not only in contemporary society but also in the 1930s, indicating a historically rooted issue.
A Novel Driver Abnormal Behavior Recognition and Analysis Strategy and Its Application in a Practical Vehicle
Authors: Liu Shida , Wang Xuyun , Ji Honghai , Wang Li , Hou Zhongsheng
Published: September 2022

In this work, a novel driver abnormal behavior analysis system based on practical facial landmark detection (PFLD) and you only look once version 5 (YOLOv5) were developed to solve the recognition and analysis of driver abnormal behaviors. First, a library for analyzing the abnormal behavior of vehicle drivers was designed, in which the factors that cause an abnormal behavior of drivers were divided into three categories according to the behavioral characteristics including natural behavioral factors, unnatural behavioral factors, and passive behavioral factors. Then, different neural network models were established through the representation of the actual scene of the three behaviors. Specifically, the abnormal driver behavior caused by natural behavioral factors was identified by a PFLD neural network model based on facial key point detection, and the abnormal driver behavior caused by unnatural behavioral factors and passive behavioral factors were identified by a YOLOv5 neural network model based on target detection. In addition, in a test of the driver abnormal behavior analysis system in an actual vehicle, the precision rate was greater than 95%, which meets the requirements of practical application.
In Vitro and In Vivo Inhibitory Activities of Selected Traditional Medicinal Plants against Toxin-Induced Cyto- and Entero- Toxicities in Cholera
Authors: Charla Rajitha , Patil Priyanka P. , Bhatkande Arati A. , Khode Nisha R. , Balaganur Venkanna , Hegde Harsha V. , Harish Darasaguppe R. , Roy Subarna
Published: September 2022

Careya arborea, Punica granatum, Psidium guajava, Holarrhena antidysenterica, Aegle marmelos, and Piper longum are commonly used traditional medicines against diarrhoeal diseases in India. This study investigated the inhibitory activity of these plants against cytotoxicity and enterotoxicity induced by toxins secreted by Vibrio cholerae. Cholera toxin (CT) and non-membrane damaging cytotoxin (NMDCY) in cell free culture filtrate (CFCF) of V. cholerae were quantified using GM1 ELISA and cell-based assays, respectively. Hydro-alcoholic extracts of these plants and lyophilized juice of P. granatum were tested against CT-induced elevation of cAMP levels in CHO cell line, binding of CT to ganglioside GM1 receptor and NMDCY-induced cytotoxicity. Significant reduction of cAMP levels in CFCF treated CHO cell line was observed for all extracts except P. longum. C. arborea, P. granatum, H. antidysenterica and A. marmelos showed >50% binding inhibition of CT to GM1 receptor. C. arborea, P. granatum, and P. guajava effectively decreased cytotoxicity and morphological alterations caused by NMDCY in CHO cell line. Further, the efficacy of these three plants against CFCF-induced enterotoxicity was seen in adult mice ligated-ileal loop model as evidenced by decrease in volume of fluid accumulation, cAMP levels in ligated-ileal tissues, and histopathological changes in intestinal mucosa. Therefore, these plants can be further validated for their clinical use against cholera.
Romania, a Harbour of HIV-1 Subtype F1: Where Are We after 33 Years of HIV-1 Infection?
Authors: Preda Mădălina , Manolescu Loredana Cornelia Sabina
Published: September 2022

Infection with the human immunodeficiency virus (HIV) has been a major public health concern worldwide for more than 30 years, including in Romania. The F1 HIV-1 subtype was exported from Angola to Romania most probably because of the two countries’ close political connections. Patients infected with HIV-1 via re-used and improperly sterilized injection equipment and through transfusions of unscreened blood, also known as the “Romanian cohort”, were the most common type of HIV-1 infection in Romania in the early 1990s, when the virus’s presence was recognized. Recently, subtype B started to increase in our country, mostly diagnosed in people using intravenous drugs or in men having sex with men. The evolution of the HIV-1 infection in Romania has been unique, with a dominance of the subtype F1, making it different from other countries in Europe.
An Optimized FI-RSV Vaccine Effectively Protects Cotton Rats and BALB/c Mice without Causing Enhanced Respiratory Disease
Authors: Lin Min , Zhang Wei , Yin Yi-Fan , Si Jun-Yu , Zhang Lu-Jing , Chen Li , Lin Xue , Wang Ying-Bin , Zhang Jun , Zheng Zi-Zheng , Xia Ning-Shao
Published: September 2022

Background: Despite considerable efforts toward vaccine development in past decades, no effective vaccines against respiratory syncytial virus (RSV) are available. Recently, we showed that an optimized formalin concentration can preserve prefusion protein (pre-F) on RSV-infected cells and protect mice against RSV infection without causing enhanced respiratory disease (ERD). Here, we sought to further stabilize pre-F on RSV virions by optimizing the production of FI-RSV. Methods: Freshly produced RSV virions were treated with formalin under different concentrations to obtained an opti-FI-RSV vaccine with high pre-F level. Immunogenicity and safety of opti-FI-RSV were evaluated in Balb/c mice and cotton rats. Results: Using 0.0156–0.1778% formalin, we successfully preserved pre-F on virions. This opti-FI-RSV exhibited improved immunogenicity and efficacy without causing ERD. Surprisingly, opti-FI-RSV, with a pre-F-dominant immunogen, still caused ERD after immunization with a suboptimal dose or when the neutralizing antibody titers declined. ERD was avoided by coadministering opti-FI-RSV with CpG + MPLA adjuvant, which subsequently induced a Th1-biasing immune response and, more importantly, significantly improved antibody avidity. Conclusions: Our study provides a new method to obtain a novel FI-RSV vaccine with a high pre-F level and may provide a reference for developing other inactivated vaccines. Our findings also emphasize that appropriate adjuvants are critical for nonreplicating vaccines.
The Role of Mosquito Hemocytes in Viral Infections
Authors: Cardoso-Jaime Victor , Tikhe Chinmay Vijay , Dong Shengzhang , Dimopoulos George
Published: September 2022

Insect hemocytes are the only immune cells that can mount a humoral and cellular immune response. Despite the critical involvement of hemocytes in immune responses against bacteria, fungi, and parasites in mosquitoes, our understanding of their antiviral potential is still limited. It has been shown that hemocytes express humoral factors such as TEP1, PPO, and certain antimicrobial peptides that are known to restrict viral infections. Insect hemocytes also harbor the major immune pathways, such as JAK/STAT, TOLL, IMD, and RNAi, which are critical for the control of viral infection. Recent research has indicated a role for hemocytes in the regulation of viral infection through RNA interference and autophagy; however, the specific mechanism by which this regulation occurs remains uncharacterized. Conversely, some studies have suggested that hemocytes act as agonists of arboviral infection because they lack basal lamina and circulate throughout the whole mosquito, likely facilitating viral dissemination to other tissues such as salivary glands. In addition, hemocytes produce arbovirus agonist factors such as lectins, which enhance viral infection. Here, we summarize our current understanding of hemocytes’ involvement in viral infections.
Factors Associated with Vaccination Intention against the COVID-19 Pandemic: A Global Population-Based Study
Authors: Huang Junjie , Chan Sze Chai , Ko Samantha , Wang Harry H. X. , Yuan Jacky , Xu Wanghong , Zheng Zhi-Jie , Xue Hao , Zhang Lin , Jiang Johnny Y. , Huang Jason L. W. , Chen Ping , Palaganas Erlinda , Viwattanakulvanid Pramon , Somrongthong Ratana , Caicedo Andrés , Medina-Arellano María de Jesús , Murphy Jill K. , Paredes Maria B. Arteaga , Withers Mellissa , Wong Martin C. S.
Published: September 2022

Several vaccines have been developed for COVID-19 since the pandemic began. This study aimed to evaluate the factors associated with COVID-19 vaccination intention. A global survey was conducted across 26 countries from October, 2020 to December, 2021 using an online self-administered questionnaire. Demographic information, socio-economic status, and clinical information were collected. A logistic regression examined the associations between vaccine intention and factors such as perceptions and the presence of chronic physical and mental conditions. The sample included 2459 participants, with 384 participants (15.7%) expressing lower COVID-19 vaccination intent. Individuals who identified as female; belonged to an older age group; had a higher level of education; were students; had full health insurance coverage; or had a previous history of influenza vaccination were more willing to receive vaccination. Conversely, those who were working part-time, were self-employed, or were receiving social welfare were less likely to report an intention to get vaccinated. Participants with mental or physical health conditions were more unwilling to receive vaccination, especially those with sickle cell disease, cancer history within the past five years, or mental illness. Stronger vaccination intent was associated with recommendations from the government or family doctors. The presence of chronic conditions was associated with lower vaccine intention. Individuals with health conditions are especially vulnerable to health complications and may experience an increased severity of COVID-19 symptoms. Future research should evaluate the effectiveness of interventions targeting the vaccine perceptions and behaviours of at-risk groups. As such, public awareness campaigns conducted by the government and proactive endorsement from health physicians may help improve COVID-19 vaccination intention.
Humoral Immune Response of BNT162b2 and CoronaVac Vaccinations in Hemodialysis Patients: A Multicenter Prospective Cohort
Authors: Clavero Rene , Parra-Lucares Alfredo , Méndez-Valdés Gabriel , Villa Eduardo , Bravo Karin , Mondaca Evelyn , Aranda Josseline , Brignardello Rose , Gajardo Cynthia , Ordenes Angelica , Colombo Evelyn , Tapia Jessica , Etcheverry Andoni , Zúñiga José , Toro Luis
Published: September 2022

The CoronaVac vaccine is the most used anti-SARS-CoV-2 vaccine worldwide. Previous data indicate that this vaccine produces a lower immune response than RNA vaccines such as BNT162b2. End-stage renal disease (ESRD) patients have an increased rate of COVID-19 and a reduced immune response to vaccinations. Currently, there is little data on this population’s immune response induced by CoronaVac. Methods: This study involved a prospective cohort of ESRD patients in chronic hemodialysis who received a two-dose immunization scheme of either CoronaVac (Sinovac Biotech) or BNT162b2 vaccines (Pfizer-BioNTech). We measured the plasma levels of anti-SARS-CoV-2 IgG antibodies. We determined antibody titers before immunization, 2 and 4 months after two doses, plus 4 months after a booster dose. Results: We evaluated 208 patients in three hemodialysis centers. The mean age was 62.6 ± 15.6 years, of whom 91 were female (41.75%). Eighty-one patients (38.94%) received the BNT162b2 vaccine and 127 (61.06%) received the CoronaVac vaccine. Patients who received the BNT162b2 vaccine had a higher humoral response compared to those who received the CoronaVac vaccine (4 months after the second dose: BNT162b2: 88.89%, CoronaVac: 51.97%, p < 0.001; 4 months after the booster: BNT162b2: 98.77%, CoronaVac: 86.61%, p < 0.001). Conclusions: Our results suggest that the CoronaVac vaccine induced a lower humoral response than the BNT162b2 vaccine in ESRD patients on hemodialysis.
Immune Evasion of SARS-CoV-2 Omicron Subvariants
Authors: Ke Hanzhong , Chang Matthew , Marasco Wayne
Published: September 2022

Since the SARS-CoV-2 Omicron variant (B.1.1.529) was declared a variant of concern (VOC) by the WHO on 24 November 2021, it has caused another global surge of cases. With extensive mutations in its spike glycoprotein, Omicron gained substantial capabilities to evade the antiviral immunity provided by vaccination, hybrid immunity, or monoclonal antibodies. The Omicron subvariants BA.1, BA.2, BA.2.12.1, BA.4 and BA.5 extended this immune evasion capability by having additional unique mutations in their respective spike proteins. The ongoing Omicron wave and emergence of new Omicron subvariants leads to additional concerns regarding the efficacy of the current antiviral measurements. To have a better understanding of the Omicron subvariants, this review summarizes reports of the immune evasion of subvariants BA.1, BA.2, BA.2.12.1, BA.4, and BA.5 as well as the molecular basis of immune evasion.
An Immune Response to Heterologous ChAdOx1/BNT162b2 Vaccination against COVID-19: Evaluation of the anti-RBD Specific IgG Antibodies Titers and Interferon Gamma Release Assay (IGRA) Test Results
Authors: Zalewska Marzena , Fus Wiktoria , Konka Adam , Wystyrk Karolina , Bochenek Aneta , Botor Hanna , Fronczek Martyna , Zembala-John Joanna , Adamek Brygida
Published: September 2022

This study aimed to assess the magnitude of anti-SARS-CoV-2 immunoglobulin G (IgG) titers and Interferon-Gamma Release Assay (IGRA) test results following administration of booster BNT162b2 in 48 ChAd-primed participants (vaccination schedule: ChAd/ChAd/BNT). Whole blood samples were collected: first, before and second, 21 days after the booster dose. The IgG level was measured using chemiluminescent immunoassay; the intensity of the T-cell response—IFNγ concentration—was assessed using IGRA test. At 21 days after the booster, all subjects achieved reactive/positive anti-SARS-CoV-2 IgG, and IGRA test results showed a significant increase compared to the results before booster administration. We compared the results before and after the booster between participants with and without prior history of COVID-19. The IFNγ concentrations in both cohorts were higher in convalescents (both before booster and 21 days after). The IgG titers were subtly lower in COVID-19 convalescents than in naïve but without statistical significance. Data on cell-mediated immunity are scarce, especially with regard to the general population. A better understanding of the complexity of the immune response to SARS-CoV-2 could contribute to developing more effective vaccination strategies.
Intranasal Treatment of Ferrets with Inert Bacterial Spores Reduces Disease Caused by a Challenging H7N9 Avian Influenza Virus
Authors: James Joe , Meyer Stephanie M. , Hong Huynh A. , Dang Chau , Linh Ho T. Y. , Ferreira William , Katsande Paidamoyo M. , Vo Linh , Hynes Daniel , Love William , Banyard Ashley C. , Cutting Simon M.
Published: September 2022

Background: Influenza is a respiratory infection that continues to present a major threat to human health, with ~500,000 deaths/year. Continued circulation of epidemic subtypes in humans and animals potentially increases the risk of future pandemics. Vaccination has failed to halt the evolution of this virus and next-generation prophylactic approaches are under development. Naked, “heat inactivated”, or inert bacterial spores have been shown to protect against influenza in murine models. Methods: Ferrets were administered intranasal doses of inert bacterial spores (DSM 32444K) every 7 days for 4 weeks. Seven days after the last dose, the animals were challenged with avian H7N9 influenza A virus. Clinical signs of infection and viral shedding were monitored. Results: Clinical symptoms of infection were significantly reduced in animals dosed with DSM 32444K. The temporal kinetics of viral shedding was reduced but not prevented. Conclusion: Taken together, nasal dosing using heat-stable spores could provide a useful approach for influenza prophylaxis in both humans and animals.
Vaccine-Induced T-Cell and Antibody Responses at 12 Months after Full Vaccination Differ with Respect to Omicron Recognition
Authors: Mai Franz , Volzke Johann , Reisinger Emil C. , Müller-Hilke Brigitte
Published: September 2022

More than a year after the first vaccines against the novel SARS-CoV-2 were approved, many questions still remain about the long-term protection conferred by each vaccine. How long the effect lasts, how effective it is against variants of concern and whether further vaccinations will confer additional benefits remain part of current and future research. For this purpose, we examined 182 health care employees—some of them with previous SARS-CoV-2 infection—12 months after different primary immunizations. To assess antibody responses, we performed an electrochemiluminescence assay (ECLIA) to determine anti-spike IgGs, followed by a surrogate virus neutralization assay against Wuhan-Hu-1 and B.1.1.529/BA.1 (Omicron). T cell response against wild-type and the Omicron variants of concern were assessed via interferon-gamma ELISpot assays and T-cell surface and intracellular cytokine staining. In summary, our results show that after the third vaccination with an mRNA vaccine, differences in antibody quantity and functionality observed after different primary immunizations were equalized. As for the T cell response, we were able to demonstrate a memory function for CD4+ and CD8+ T cells alike. Importantly, both T and antibody responses against wild-type and omicron differed significantly; however, antibody and T cell responses did not correlate with each other and, thus, may contribute differentially to immunity.
Immunogenicity and Safety of COVID-19 Vaccines among People Living with HIV: A Systematic Review and Meta-Analysis
Authors: Kang Liangyu , Shang Weijing , Gao Peng , Wang Yaping , Liu Jue , Liu Min
Published: September 2022

Background: The immunogenicity and safety of COVID-19 vaccines among people living with human immunodeficiency virus (PLWH) are unclear. We aimed to evaluate the immunogenicity and safety of COVID-19 vaccines among PLWH. Methods: We systematically searched PubMed, EMBASE, and Web of Science from 1 January 2020 to 28 April 2022 and included observational studies, randomized clinical trials, and non-randomized clinical trials reporting extractable data about the immunogenicity and safety of COVID-19 vaccines among PLWH. Results: A total of 34 eligible studies covering 4517 PLWH were included. The pooled seroconversion rates among PLWH after the first and second doses were 67.51% (95% confident interval (CI) 49.09–85.93%) and 96.65% (95%CI 95.56–97.75%), respectively. The seroconversion was similar between PLWH and healthy controls after the first (risk ratio (RR) = 0.89, 95%CI 0.76–1.04) and the second (RR = 0.97, 95%CI 0.93–1.00) dose. Moreover, the geometric mean titer (GMT) showed no significant difference between PLWH and healthy controls after the first dose (standardized mean difference (SMD) = 0.30, 95%CI -1.11, 1.70) and the second dose (SMD = -0.06, 95%CI -0.18, 0.05). Additionally, the pooled incidence rates of total adverse events among PLWH after the first and the second dose were 46.55% (95%CI 28.29–64.82%) and 30.96% (95%CI 13.23–48.70%), respectively. There was no significant difference in risks of total adverse events between PLWH and healthy controls after the first (RR = 0.86, 95%CI 0.67–1.10) and the second (RR = 0.88, 95%CI 0.68–1.14) dose. Conclusions: The available evidence suggested that the immunogenicity and safety of COVID-19 vaccines among PLWH were acceptable. There was no significant difference in the seroconversion rates and incidence rates of adverse events of COVID-19 vaccines between PLWH and healthy controls.
Variations of Stable Isotopes in Daily Precipitation in a Monsoon Region
Authors: Li Jie , Pang Zhonghe , Tian Lijun , Zhao Hongyi , Bai Guoying
Published: September 2022

The stable isotopes of hydrogen and oxygen in precipitation provide a useful reference for the study of hydrological processes, but concerns have been raised regarding the established patterns in their variations in a monsoon climate zone. In this study, stable isotopes (δ18O and δ2H) of 539 daily precipitation samples from seven hydrometeorological stations in the Beijing area were used to investigate short-term isotopic variations and the controlling factors at a region with a monsoon climate. The δ18O in the precipitation increases from the northwest to the south, which is controlled by the monsoon from the south and continental moisture from the northwest. Consistently, both the high δ18O values and low deuterium excess values from May to September reveal the impact of the monsoon. The amount effect is significant during the monsoon season. In contrast, the T effect is significant, with a gradient of 0.4‰ per °C during the non-monsoon season. A Rayleigh distillation model indicates that the moisture source and residual vapor fraction are the two most important factors in controlling the δ18O patterns in precipitation in a monsoon region, independent of temperature. The result of this study is helpful for the understanding of the regional atmospheric water cycle.
Artificial Neural Networks and Multiple Linear Regression for Filling in Missing Daily Rainfall Data
Authors: Papailiou Ioannis , Spyropoulos Fotios , Trichakis Ioannis , Karatzas George P.
Published: September 2022

As demand for more hydrological data has been increasing, there is a need for the development of more accurate and descriptive models. A pending issue regarding the input data of said models is the missing data from observation stations in the field. In this paper, a methodology utilizing ensembles of artificial neural networks is developed with the goal of estimating missing precipitation data in the extended region of Chania, Greece on a daily timestep. In the investigated stations, there have been multiple missing data events, as well as missing data prior to their installation. The methodology presented aims to generate precipitation time series based on observed data from neighboring stations and its results have been compared with a Multiple Linear Regression model as the basis for improvements to standard practice. For each combination of stations missing daily data, an ensemble has been developed. According to the statistical indexes that were calculated, ANN ensembles resulted in increased accuracy compared to the Multiple Linear Regression model. Despite this, the training time of the ensembles was quite long compared to that of the Multiple Linear Regression model, which suggests that increased accuracy comes at the cost of calculation time and processing power. In conclusion, when dealing with missing data in precipitation time series, ANNs yield more accurate results compared to MLR methods but require more time for producing them. The urgency of the required data in essence dictates which method should be used.
Enhancing a Multi-Step Discharge Prediction with Deep Learning and a Response Time Parameter
Authors: Thaisiam Wandee , Saelo Warintra , Wongchaisuwat Papis
Published: September 2022

Flood forecasting is among the most important precaution measures to prevent devastating disasters affecting human life, properties, and the overall environment. It is closely involved with precipitation and streamflow data forecasting tasks. In this work, we introduced a multi-step discharge prediction framework based on deep learning models. A simple feature representation technique using a correlation of backward lags was enhanced with a time of concentration (TC) concept. Recurrent neural networks and their variants, coupled with the TC-related features, provided superior performance with over 0.9 Nash–Sutcliffe model efficiency coefficient and substantially high correlation values for multiple forecasted points. These results were consistent among both the Upper Nan and the Loei river basins in Thailand, which were used as case studies in this work.
Soil-Gas Diffusivity-Based Characterization of Variably Saturated Agricultural Topsoils
Authors: Abeysinghe A. M. S. N. , Lakshani M. M. T. , Amarasinghe U. D. H. N. , Li Yuan , Deepagoda T. K. K. Chamindu , Fu Wei , Fan Jun , Yang Ting , Ma Xiaoyi , Clough Tim , Elberling Bo , Smits Kathleen
Published: September 2022

Soil-gas diffusivity and its variation with soil moisture plays a fundamental role in diffusion-controlled migration of climate-impact gases from different terrestrial agroecosystems including cultivated soils and managed pasture systems. The wide contrast in soil texture and structure (e.g., density, soil aggregation) in agriculture topsoils (0–10 cm) makes it challenging for soil-gas diffusivity predictive models to make accurate predictions across different moisture conditions. This study characterized gas diffusivity and gas-phase tortuosity in soils sampled from managed pasture and cultivated sites in Sri Lanka at 0–10 cm depth, together with selected soil-gas diffusivity data from the literature. Soil-gas diffusivity was measured using a one-chamber diffusion apparatus using N2 and O2 as experimental gases. The measured diffusivity, together with literature data representing both intact and repacked soils, were tested against five existing widely known gas diffusivity predictive models. The tested models tended to mischaracterize the two-region behavior in some of the aggregated soils, suggesting the need of soil-specific diffusivity models to better describe gas diffusivity in agricultural soils. We suggested a new parametric two-region model, developed in line with literature-based models, to represent both unimodal and bimodal/two-region behavior of selected soils. The new model statistically outperformed the existing predictive models for both intact and repacked soils and, hence, demonstrated its applicability to better characterize site-specific greenhouse gas emissions under different soil water regimes.
Biomathematical Model for Water Quality Assessment: Macroinvertebrate Population Dynamics and Dissolved Oxygen
Authors: Pineda-Pineda Jair J. , Muñoz-Rojas Jesús , Morales-García Y. Elizabeth , Hernández-Gómez Juan C. , Sigarreta José M.
Published: September 2022

Sustainable water management is important to ensure its availability for future generations. The study of water quality is fundamental for this purpose. Assessing the health of aquatic ecosystems through bioindicators has been shown to be reliable and inexpensive. The objective of this work was to evaluate water quality through a biomathematical model that involves environmental stress indicator organisms and their close relationship with dissolved oxygen. In this direction, a system of differential equations describing the population dynamics of aquatic macroinvertebrates under the influence of dissolved oxygen is proposed. The model is validated by its application in the Coyuca Lagoon, Mexico. Likewise, population changes over time were represented, which allowed us to deduce that the increase or decrease in the aeration/oxygenation rate significantly affects the population dynamics of the bioindicator organisms. In addition, to classify water quality, a one-to-one correspondence was established between water quality and the equilibrium points of the system of differential equations. The results obtained allow inferring that the proposed techniques are useful for the study of water quality since they can predict significant changes in the ecosystem and provide researchers and water managers with tools for decision making.
Species Richness and Diversity of Aquatic Ecosystems: Lessons from a Special Issue
Authors: Kotov Alexey A. , Van Damme Kay
Published: September 2022

Aquatic ecosystems around the world are under increasing pressure from human activities and global warming, either directly or indirectly [...]
Developing a Decision Support Evaluation Model Based on the Matter Element Analysis Method to Optimize the Environmental Flows in Dammed Rivers
Authors: Chen Ang , Wu Miao , Shen Dandan , Song Shuang
Published: September 2022

The large number of dams in the world has caused many ecological problems, especially in ecologically fragile areas. Appropriate environmental flow (e-flows) releases reduce stress on river ecosystems caused by the flow alterations of dams. As e-flow releasing is substantially a decision-making process, it is important to choose the right calculation method in many e-flow assessment frameworks and calculation methods or to select the proper e-flow result from many scenarios. In China, there are government guidelines to assist managers in choosing an e-flow method for their situations, but the technical components of these guidelines are too general and not very specific, even though the coverage of the framework of guidelines is comparatively complete. Thus, a high degree of subjectivity remains in the method selection, and managers are often confused about the different e-flow results and scenarios. A more detailed decision support evaluation (DSE) model which can quantify and compare the results from different calculation methods is therefore needed to provide a basic technical economy evaluation. Based on the relevant policies and the dam priority classification frameworks in China, we propose a DSE model based on the matter element analysis (MEA) method to complement the Chinese e-flow framework. First, the flow regime criteria from the related government guidelines for a variety of conservation objectives are summarized. Secondly, different scenarios of e-flows are calculated based on the formal government guidelines and using the same hydrological database. Finally, the DSE model for assessing the different e-flow scenarios are built and demonstrated. MEA helped to quantify and optimize the different results and reduce the uncertainty. The DSE model presented in this study can be applied to e-flow optimization for all dammed rivers in China and serve as a decision support tool for managers.