bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessment and Prediction of Sea Level Trend in the South Pacific Region
Authors: Raj Nawin , Gharineiat Zahra , Ahmed Abul Abrar Masrur , Stepanyants Yury
Published: February 2022

Sea level rise is an important and topical issue in the South Pacific region and needs an urgent assessment of trends for informed decision making. This paper presents mean sea level trend assessment using harmonic analysis and a hybrid deep learning (DL) model based on the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) technique, Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU) and Neighbourhood Component Analysis (NCA) to build a highly accurate sea level forecasting model for three small islands (Fiji, Marshall Island and Papua New Guinea (PNG)) in the South Pacific. For a 20-year period, the estimated mean sea level rise per year from the harmonic computation is obtained: 112 mm for PNG, 98 mm for Marshall Island and 52 mm for Fiji. The DL procedure uses climate and environment-based remote sensing satellite (MODIS, GLDAS-2.0, MODIS TERRA, MERRA-2) predictor variables with tide gauge base mean sea level (MSL) data for model training and development for forecasting. The developed CEEMDAN-CNN-GRU as the objective model is benchmarked by comparison to the hybrid model without data decomposition, CNN-GRU and standalone models, Decision Trees (DT) and Support Vector Regression (SVR). All model performances are evaluated using reliable statistical metrics. The CEEMDAN-CNN-GRU shows superior accuracy when compared with other standalone and hybrid models. It shows an accuracy of >96% for correlation coefficient and an error of <1% for all study sites.
Beep4Me: Automatic Ticket Validation to Support Fare Clearing and Service Planning
Authors: Tuveri Giovanni , Garau Marco , Sottile Eleonora , Pintor Lucia , Atzori Luigi , Meloni Italo
Published: February 2022

An integrated transport service fare system, supported by an agreement for ticket revenue sharing among service providers, is an essential component to improve the experience of the users who can find single tickets for the integrated transport services they look for. A challenge is to find a model to share the revenue which all providers agree on. A solution is to adopt data-driven approaches where user-generated data are collected to extract information on the extent each transport service was used. This is consistently used. However, it suffers from incomplete data, as not all users always validate their ticket when checking out or when switching lines. We studied all technologies available to support automatic ticket validation in order to record when the users access and exit each service line. The contributions of this work are the following: we give an in-depth description of the inner workings of this novel approach describing how we take advantage of each technology; we present the developed solution (Beep4Me), which adds new functionalities to an existing mobile ticketing platform; and we describe our testing framework, which includes most cases users might encounter during a trip. Our results demonstrate how it is possible to collect key data related to validations which can be used first for clearing purposes and then for network planning/fleet optimization.
Automated Knee MR Images Segmentation of Anterior Cruciate Ligament Tears
Authors: Awan Mazhar Javed , Rahim Mohd Shafry Mohd , Salim Naomie , Rehman Amjad , Garcia-Zapirain Begonya
Published: February 2022

The anterior cruciate ligament (ACL) is one of the main stabilizer parts of the knee. ACL injury leads to causes of osteoarthritis risk. ACL rupture is common in the young athletic population. Accurate segmentation at an early stage can improve the analysis and classification of anterior cruciate ligaments tears. This study automatically segmented the anterior cruciate ligament (ACL) tears from magnetic resonance imaging through deep learning. The knee mask was generated on the original Magnetic Resonance (MR) images to apply a semantic segmentation technique with convolutional neural network architecture U-Net. The proposed segmentation method was measured by accuracy, intersection over union (IoU), dice similarity coefficient (DSC), precision, recall and F1-score of 98.4%, 99.0%, 99.4%, 99.6%, 99.6% and 99.6% on 11451 training images, whereas on the validation images of 3817 was, respectively, 97.7%, 93.8%,96.8%, 96.5%, 97.3% and 96.9%. We also provide dice loss of training and test datasets that have remained 0.005 and 0.031, respectively. The experimental results show that the ACL segmentation on JPEG MRI images with U-Nets achieves accuracy that outperforms the human segmentation. The strategy has promising potential applications in medical image analytics for the segmentation of knee ACL tears for MR images.
Learning to Reason on Tree Structures for Knowledge-Based Visual Question Answering
Authors: Li Qifeng , Tang Xinyi , Jian Yi
Published: February 2022

Collaborative reasoning for knowledge-based visual question answering is challenging but vital and efficient in understanding the features of the images and questions. While previous methods jointly fuse all kinds of features by attention mechanism or use handcrafted rules to generate a layout for performing compositional reasoning, which lacks the process of visual reasoning and introduces a large number of parameters for predicting the correct answer. For conducting visual reasoning on all kinds of image–question pairs, in this paper, we propose a novel reasoning model of a question-guided tree structure with a knowledge base (QGTSKB) for addressing these problems. In addition, our model consists of four neural module networks: the attention model that locates attended regions based on the image features and question embeddings by attention mechanism, the gated reasoning model that forgets and updates the fused features, the fusion reasoning model that mines high-level semantics of the attended visual features and knowledge base and knowledge-based fact model that makes up for the lack of visual and textual information with external knowledge. Therefore, our model performs visual analysis and reasoning based on tree structures, knowledge base and four neural module networks. Experimental results show that our model achieves superior performance over existing methods on the VQA v2.0 and CLVER dataset, and visual reasoning experiments prove the interpretability of the model.
Using Automatic Speech Recognition to Assess Thai Speech Language Fluency in the Montreal Cognitive Assessment (MoCA)
Authors: Kantithammakorn Pimarn , Punyabukkana Proadpran , Pratanwanich Ploy N. , Hemrungrojn Solaphat , Chunharas Chaipat , Wanvarie Dittaya
Published: February 2022

The Montreal cognitive assessment (MoCA), a widely accepted screening tool for identifying patients with mild cognitive impairment (MCI), includes a language fluency test of verbal functioning; its scores are based on the number of unique correct words produced by the test taker. However, it is possible that unique words may be counted differently for various languages. This study focuses on Thai as a language that differs from English in terms of word combinations. We applied various automatic speech recognition (ASR) techniques to develop an assisted scoring system for the MoCA language fluency test with Thai language support. This was a challenge because Thai is a low-resource language for which domain-specific data are not publicly available, especially speech data from patients with MCIs. Furthermore, the great variety of pronunciation, intonation, tone, and accent of the patients, all of which might differ from healthy controls, bring more complexity to the model. We propose a hybrid time delay neural network hidden Markov model (TDNN-HMM) architecture for acoustic model training to create our ASR system that is robust to environmental noise and to the variation of voice quality impacted by MCI. The LOTUS Thai speech corpus was incorporated into the training set to improve the model’s generalization. A preprocessing algorithm was implemented to reduce the background noise and improve the overall data quality before feeding data into the TDNN-HMM system for automatic word detection and language fluency score calculation. The results show that the TDNN-HMM model in combination with data augmentation using lattice-free maximum mutual information (LF-MMI) objective function provides a word error rate (WER) of 30.77%. To our knowledge, this is the first study to develop an ASR with Thai language support to automate the scoring system of MoCA’s language fluency assessment.
Multi-Objective Real-Time Tuning of SVC Used in Electrified Traction Systems
Authors: Bigharaz Mohammad Hossein , Dehcheshmeh Mehdi Amiri , Givi Hadi , Hubálovský Štěpán
Published: February 2022

Electric train system is a very large load for the power network. This load consumes a large amount of reactive power. In addition, it causes a massive unbalance to the network, which results in many problems such as voltage drops, high transmission losses, reduction in the transformer output ability, negative sequence current, mal-operation of protective relays, etc. In this paper, a novel real-time optimization approach is presented to adjust the static VAR compensator (SVC) for the traction system to realize two objectives; current unbalance reduction and reactive power compensation. A multi-objective optimization technique entitled non-dominated sorting genetic algorithm (NSGA-II) is used to fulfill the regarded objectives simultaneously. A comprehensive simulator has been designed for electric train network modeling that is able to adjust the parameters of SVC in an optimum manner at any time and under any circumstances. The results illustrate that the provided method can efficiently reduce the unbalancing in current as well as supply the demanded reactive power with acceptable precision.
Convolutional Blur Attention Network for Cell Nuclei Segmentation
Authors: Thi Le Phuong , Pham Tuan , Hsu Yi-Chiung , Wang Jia-Ching
Published: February 2022

Accurately segmented nuclei are important, not only for cancer classification, but also for predicting treatment effectiveness and other biomedical applications. However, the diversity of cell types, various external factors, and illumination conditions make nucleus segmentation a challenging task. In this work, we present a new deep learning-based method for cell nucleus segmentation. The proposed convolutional blur attention (CBA) network consists of downsampling and upsampling procedures. A blur attention module and a blur pooling operation are used to retain the feature salience and avoid noise generation in the downsampling procedure. A pyramid blur pooling (PBP) module is proposed to capture the multi-scale information in the upsampling procedure. The superiority of the proposed method has been compared with a few prior segmentation models, namely U-Net, ENet, SegNet, LinkNet, and Mask RCNN on the 2018 Data Science Bowl (DSB) challenge dataset and the multi-organ nucleus segmentation (MoNuSeg) at MICCAI 2018. The Dice similarity coefficient and some evaluation matrices, such as F1 score, recall, precision, and average Jaccard index (AJI) were used to evaluate the segmentation efficiency of these models. Overall, the proposal method in this paper has the best performance, the AJI indicator on the DSB dataset and MoNuSeg is 0.8429, 0.7985, respectively.
Addressing Uncertainty by Designing an Intelligent Fuzzy System to Help Decision Support Systems for Winter Road Maintenance
Authors: Hatamzad Mahshid , Polanco Pinerez Geanette , Casselgren Johan
Published: February 2022

One of the main challenges in developing efficient and effective winter road maintenance is to design an accurate prediction model for the road surface friction coefficient. A reliable and accurate prediction model of road surface friction coefficient can help decision support systems to significantly increase traffic safety, while saving time and cost. High dynamicity in weather and road surface conditions can lead to the presence of uncertainties in historical data extracted by sensors. To overcome this issue, this study uses an adaptive neuro-fuzzy inference system that can appropriately address uncertainty using fuzzy logic neural networks. To investigate the ability of the proposed model to predict the road surface friction coefficient, real data were measured at equal time intervals using optical sensors and road-mounted sensors. Then, the most critical features were selected based on the Pearson correlation coefficient, and the dataset was split into two independent training and test datasets. Next, the input variables were fuzzified by generating a fuzzy inference system using the fuzzy c-means clustering method. After training the model, a testing set was used to validate the trained model. The model was evaluated by means of graphical and numerical metrics. The results show that the constructed adaptive neuro-fuzzy model has an excellent ability to learn and accurately predict the road surface friction coefficient.
Political Participation of Young Voters: Tracing Direct and Indirect Effects of Social Media and Political Orientations
Authors: Tariq Rehan , Zolkepli Izzal Asnira , Ahmad Mahyuddin
Published: February 2022

Political participation in Pakistan was expected to rise because of the enormous democratic potential of social media; nevertheless, a drop has been observed following an initial increase. This scenario encourages investigation of the decisive factors that might draw disengaged citizens into participatory politics. Therefore, this study illustrates the results of a Pakistani sample (n = 410) regarding the role of social media in influencing political participation in online and offline platforms. Five variables were examined using partial least squares (PLS) to see how they influenced online and offline political participation. The OSOR model of communication mediation was used for this purpose. Its implications were extended by simultaneously incorporating three outcome orientations—political expression, political efficacy, and partisanship—as mediators. In addition, we included political interest as an antecedent orientation and social media use as stimuli. Online and offline political participation were placed under response as endogenous variables. Our findings acknowledged nine direct and five indirect correlations out of ten direct and six indirect relationships. Political efficacy neither influenced offline political participation nor proved to be a mediator between social media use and offline political participation. We conclude with study implications, limitations, and recommendations for future scholars.
Effects of Plastic versus Straw Mulching Systems on Soil Microbial Community Structure and Enzymes in Strawberry Cultivation
Authors: Muñoz Katherine , Thiele-Bruhn Sören , Kenngott Kilian G. J. , Meyer Maximilian , Diehl Dörte , Steinmetz Zacharias , Schaumann Gabriele E.
Published: February 2022

This study aimed to evaluate changes in abundance, structure, and enzyme activity of the soil microbiome in response to 4 years of mulching using either black polyethylene plastic film (PM) or wheat straw (SM). Soil samples (depth 0–5 and 5–10 cm) were collected from conventional strawberry plots, in two samplings: 1 week prior (S1) and 7 weeks after straw application (S2). Selected soil properties were monitored in each system and the abundance and structure of microbial communities were characterized via phospholipid fatty acid (PLFA) analysis. The investigation of soil microbial functions included activities of the enzymes chitinase, leucine aminopeptidase, and acid phosphatase, as well as function genes involved in nitrogen transformation. Each mulch system resulted in distinct physicochemical properties. In particular, a pH value higher by one-unit under PM (7.6 ± 0.3) compared to SM (6.5 ± 0.3) was observed. Values for SOC, DOC, and total-N were 15%, 22%, and 16% higher in PM than in SM. The microbial biomass (total PLFAs) was 1.5-fold higher in SM compared to PM. The abundance of soil fungi (F) and bacteria (B) increased by 37% and 44% after straw incorporation compared to PM (S2). In particular, Gram-negative bacteria (gr–) increased by twofold in SM. Consequently, wider F:B and gr+:gr– ratios were observed in PM. According to the shifts in microbial abundance, the activity of the enzyme chitinase was lower by 27% in PM, while the activity of the acid phosphatase increased by 32%. Denitrification genes were not affected by the mulching systems. In conclusion, the abundance and structure of the investigated microbial groups and the enzyme activities were strongly influenced by the mulching system. In detail, effects on microbiota were primarily attributed to the altered soil pH and probably the input of degradable organic matter with straw mulching in SM. This resulted in higher abundance of soil microorganisms in SM, although measures within this cultivation system such as fungicide application may have exerted adverse effects on the microbiota.
Responses of Soil Phosphorus Fractions to Land-Use Change in Colombian Amazon
Authors: Chavarro-Bermeo Juan P. , Arruda Bruna , Mora-Motta Dúber A. , Bejarano-Herrera Wilfrand , Ortiz-Morea Fausto A. , Somenahally Anil , Silva-Olaya Adriana M.
Published: February 2022

Intensive land-use change, the overgrazing of pastures, and the poor soil management in the Amazon region induce significant soil chemical degradation, causing alterations in the soil phosphorus (P) dynamics. Here, we studied the changes in P fractions and availability throughout the soil profile along a chronosequence composed of four study areas representing the typical land-use transition from forest to pasture for extensive cattle ranching in the Colombian Amazon region: (i) Forest—Deforested—Pasture 4 years old and Pasture established >25 years after deforestation. Soil samples collected at 0–10, 10–20, 20–30, and 30–40 cm depth were used for the sequential fractionation of P, determination of acid phosphatase activity and soil organic carbon (C) content, and calculation of C:organic P (Po) ratio and P stocks. Our results showed that the land-use change caused a decrease of 31.1% in the fractions of labile inorganic P, with the mineralization of organic P by phosphatase enzyme playing an essential role in the P availability. Although according to the C:Po ratio of the deeper layer the P seems to be sufficient to satisfy the plant needs of all the land uses assessed, the exploitation of soil nutrients in pastures reduced by 6.1% the moderately and non-labile P stock. Given the role of cattle ranching in the economy of tropical countries, it is imperative to adopt strategies of soil P management to improve P-use efficiency, avoiding the degradation of grazing land resources while ensuring the long-term sustainability of rangeland livestock and decrease further deforestation of the Amazon rainforest.
MDPI Sustainability: Special Issue “Innovations in Sustainable Materials and Construction Technologies”
Authors: Gupta Rishi
Published: February 2022

At the time this editorial was being written, the uncertainties induced by the global pandemic were continuing to affect millions of people around the world [...]
How Do New Ventures Implementing Green Innovation Strategy Achieve Performance Growth?
Authors: Zhang Xiue , Meng Qiao , Le Yuan
Published: February 2022

Manufacturing new ventures aiming to realize green innovative development play an essential role in the process of realizing the green transformation of economy and society. However, there is limited research on green manufacturing new ventures, and scholars have different views on whether green innovation strategy can improve new venture performance. This paper attempts to fill this gap by proposing a comprehensive framework of the relationship among green innovation strategy, green knowledge sharing, business model innovation, and new venture performance, based on the natural resource-based view. Through the empirical analysis of 240 sample enterprises in China, the results show that green innovation strategy has a significant positive effect on new venture performance. Green knowledge sharing and business model innovation are the essential paths for new ventures to achieve performance growth. Additionally, green knowledge sharing and business model innovation play a chain mediating role between green innovation strategy and new venture performance. This study suggests directions for manufacturing new ventures implementing a green innovation strategy to enhance performance and establishes a theoretical basis for the green transformation development of China’s economy and society.
The Human’s Comfort Mystery—Supporting Energy Transition with Light-Color Dimmable Room Lighting
Authors: Wenninger Simon , Wiethe Christian
Published: February 2022

The constant increase of intermittent renewable energies in the electricity grid complicates balancing supply and demand. Thus, research focuses on solutions in demand-side management using energy flexibility to resolve this problem. However, the interface between demand-side management and human behavior is often insufficiently addressed, although further potential could be leveraged here. This paper elaborates on the effect of light color on humans’ temperature and comfort perception in connection to energy flexibility. Researchers have found that people perceive blue light as colder and red light as warmer. To this end, we evaluate the effect of light color in a case study for a German industrial facility assuming sector-coupled electric heating. We simulate the entire heating period from October to April in an hourly granularity, using the well-established real options analysis and binomial trees as a decision support system to heuristically minimize energy expenditures by utilizing deferral options when energy prices are high. Our results show a 12.5% reduction in heating costs for sector-coupled electric heating, which extrapolated leads to CO2-eq emission savings of over 34,000 tons per year for the entire German industry, thereby supporting the energy transition.
Exploring the Influence of Culture in the Present and Future of Multicultural Organizations: Comparing the Case of Spain and Latin America
Authors: Rodríguez-Rivero Rocío , Ortiz-Marcos Isabel , Patiño-Arenas Victoria E.
Published: February 2022

The present is bringing about significant change in many aspects of our lives, and this impact has also reached project management. Working with multicultural and virtual teams makes it necessary to review how these teams are managed in order to achieve the expected success of a project. A survey has been designed based on the six cultural dimensions proposed by Hofstede. It was completed by engineering students from Spain and Latin American countries, and defines behaviors associated with each cultural dimension and was personalized for a university context, in which the participants were living. Apart from perceived behaviors, the survey also measures desired ones. Therefore, its analysis makes it possible to detect both the existing differences between students in the countries analyzed, as well as the differences between the current situation and the desired situation perceived by participants. The latter information is relevant for anticipating possible changes in the behavior of teams in multicultural organizations. The results lead us to reflect on the aspects that can help to strengthen teamwork and its management when dealing with multicultural projects, especially those involving professionals from Spain and Latin America.
Sound Design of Guqin Culture: Interactive Art Promotes the Sustainable Development of Traditional Culture
Authors: Shen Danni , Guo Herui , Yu Linghui , Ying Jie , Shen Jie , Ying Shuchen , Bao Defu , Wang Ying
Published: February 2022

Culture, as an intangible piece of heritage, is one of the priorities of sustainable conservation. With the rapid modernization of science and technology, traditional culture that is expressed in the form of sound is facing prominent problems related to inheritance and development. Thinking about how to integrate traditional culture into the daily life of the public is an important way of solving sustainability problems related to traditional culture. This study took Guqin culture as its research object, explored the possibility of using sound as an interactive medium, and considered how to present traditional culture to the public in public space to broaden the inheritance and development mode of Guqin culture. Therefore, this study proposes a public Sound Interaction Design Model oriented to sound and presents a public sound-interactive installation with different levels based on the model. The feasibility of the model is verified through an interactive design evaluation method, and the role of the model in sustainable cultural development is discussed.
Identifying Strengths and Obstacles to Climate Change Adaptation in the German Agricultural Sector: A Group Model Building Approach
Authors: Valencia Cotera Rodrigo , Egerer Sabine , Máñez Costa María
Published: February 2022

In the past 30 years, there has been a significant increase in drought events in Europe. It is expected that climate change will make droughts more frequent and intense. This situation is particularly concerning for areas with no drought management culture. This study focuses on North East Lower Saxony (NELS), an important agricultural region in northern Germany. We implement a novel approach to Group Model Building to assess the preparedness of NELS to deal with climate change and droughts. Our novel approach includes the creation of a preliminary model based on individual interviews and a triangulation of information after the workshop. We conclude that stakeholders are aware of climate change, but insufficient attention is given to adaptive solutions mainly because they require high initial investments. Given its existing political infrastructure, the region has the potential to adjust. With efficient government bodies are already in place, beneficial updates could be made to established water withdrawal regulations.
The Impact of Human Rights Reporting and Presentation Formats on Non-Professional Investors’ Perceptions and Intentions to Invest
Authors: Brink William D. , De Meyst Karen , Eaton Tim V.
Published: February 2022

Compared to other types of sustainability information, it remains uncommon for companies to report human rights information, and critics argue that when companies do report, they often report opportunistically. This is problematic as non-professional investors may rely on this information when making investment decisions. In this study, we use an experiment to examine how non-professional investors react to human rights information presented in varying formats (i.e., numerical, graphs, qualitative) compared to no reporting. Consistent with our expectations, we find that when information is positive, participants do not react to qualitative information. However, they react positively to numerical and graphical information and seem to use a less critical mindset when processing this type of information, which is associated in the literature with an “aura” of accuracy, objectivity, and neutrality. This is problematic because, similar to what is often the case in reality, participants had no certainty about the accuracy of the information. Further, when information is less positive, participants do not react to numerical or graphical information, but they do react negatively to qualitative information, which is more vague and may be perceived as companies trying to obfuscate less positive performance. We offer a critical discussion of our results.
Self-Supervised Human Activity Representation for Embodied Cognition Assessment
Authors: Zaki Zadeh Mohammad , Ramesh Babu Ashwin , Jaiswal Ashish , Makedon Fillia
Published: February 2022

Physical activities, according to the embodied cognition theory, are an important manifestation of cognitive functions. As a result, in this paper, the Activate Test of Embodied Cognition (ATEC) system is proposed to assess various cognitive measures. It consists of physical exercises with different variations and difficulty levels designed to provide assessment of executive and motor functions. This work focuses on obtaining human activity representation from recorded videos of ATEC tasks in order to automatically assess embodied cognition performance. A self-supervised approach is employed in this work that can exploit a small set of annotated data to obtain an effective human activity representation. The performance of different self-supervised approaches along with a supervised method are investigated for automated cognitive assessment of children performing ATEC tasks. The results show that the supervised learning approach performance decreases as the training set becomes smaller, whereas the self-supervised methods maintain their performance by taking advantage of unlabeled data.
Media Exposure, Behavioural Risk Factors and HIV Testing among Women of Reproductive Age in Papua New Guinea: A Cross-Sectional Study
Authors: Adegboye Oyelola A. , Ezechukwu Henry C. , Woodall Hannah , Brough Megan , Robertson-Smith Jodie , Paba Rosella , Czech Geraint , Emeto Theophilus I.
Published: February 2022

Background: Reproductive health remains a major health concern in developing countries such as Papua New Guinea (PNG). The prevalence of human immunodeficiency virus (HIV) in PNG is the highest in the Southern Pacific region, with women having a higher risk of contracting the infection. Hence, there have been several policies aimed at mitigating the spread of the disease. One of these policies include the use of mass media as a health promotion tool to educate the population on the risk of the disease. Therefore, this study aimed at investigating the association of mass media to HIV testing among women. Methods: Data were obtained from the PNG Demographic and Health Survey (DHS) of 2019. A total of 15,005 reproductive-age women was included in this analysis. Results: The results showed that women with low (aOR = 1.63, 95% CI: 1.39, 1.90) and high (aOR = 1.53, 95% CI: 1.36, 1.72) media exposure were more likely to undertake HIV testing compared to those with no media exposure. Compared to no education, women with incomplete primary (aOR = 1.22, 95% CI: 1.06, 1.40), complete primary (aOR = 1.56, 95% CI: 1.30, 1.87), incomplete secondary (aOR = 2.18, 95% CI: 1.85, 2.58), complete secondary (aOR= 2.33, 95% CI: 1.77, 3.09) and higher (aOR = 3.38, 95% CI: 2.57, 4.46) education were more likely to undertake HIV testing. Compared to women with the poorest wealth index, women with richer indexes were more likely to undertake HIV testing. Women living in rural areas were less likely to undertake HIV testing (aOR = 0.72, 95% CI: 0.63, 0.82). However, marital status, knowledge of transmission and religion were not associated with HIV testing. Conclusion: In conclusion, this study provides strong evidence that mass media exposure increases the likelihood of HIV testing in women of reproductive age in PNG. Mass media campaigns would serve as a cost-effective health promotion tool against the spread of disease.
Moonlighting in Rickettsiales: Expanding Virulence Landscape
Authors: Matos Ana Luísa , Curto Pedro , Simões Isaura
Published: February 2022

The order Rickettsiales includes species that cause a range of human diseases such as human granulocytic anaplasmosis (Anaplasma phagocytophilum), human monocytic ehrlichiosis (Ehrlichia chaffeensis), scrub typhus (Orientia tsutsugamushi), epidemic typhus (Rickettsia prowazekii), murine typhus (R. typhi), Mediterranean spotted fever (R. conorii), or Rocky Mountain spotted fever (R. rickettsii). These diseases are gaining a new momentum given their resurgence patterns and geographical expansion due to the overall rise in temperature and other human-induced pressure, thereby remaining a major public health concern. As obligate intracellular bacteria, Rickettsiales are characterized by their small genome sizes due to reductive evolution. Many pathogens employ moonlighting/multitasking proteins as virulence factors to interfere with multiple cellular processes, in different compartments, at different times during infection, augmenting their virulence. The utilization of this multitasking phenomenon by Rickettsiales as a strategy to maximize the use of their reduced protein repertoire is an emerging theme. Here, we provide an overview of the role of various moonlighting proteins in the pathogenicity of these species. Despite the challenges that lie ahead to determine the multiple potential faces of every single protein in Rickettsiales, the available examples anticipate this multifunctionality as an essential and intrinsic feature of these obligates and should be integrated into available moonlighting repositories.
Knowledge, Attitudes, and Practices regarding Soil-Transmitted Helminthiasis among Village Health Volunteers in Nakhon Si Thammarat Province, Thailand: A Cross-Sectional Study
Authors: Narkkul Udomsak , Na-ek Prasit , Kaewkungwal Jaranit , Punsawad Chuchard
Published: February 2022

Soil-transmitted helminth infections are most prevalent in rural populations. Village health volunteers (VHVs) are the key individuals for Thai primary healthcare. Therefore, this study aimed to investigate the knowledge, attitudes, and practices regarding soil-transmitted helminthiasis in VHVs. A questionnaire survey was conducted among 552 VHVs randomly selected from four subdistricts in a southern province of Thailand. Sociodemographic variables and information regarding the knowledge, attitudes, and practices related to soil-transmitted helminthiasis were collected using a structured questionnaire. The results demonstrated that VHVs had poor knowledge (70.47%) and practices (66.49%); however, 69.57% had good attitudes. Most VHVs had inadequate knowledge and practices regarding soil-transmitted helminthiasis. VHVs who had been trained in parasitic infection control measures were 2.18 times more likely to have good knowledge. VHVs with a monthly family income of more than 307 USD were 1.58 times more likely to have a good attitude. VHVs with good knowledge were more likely to have good practices. In conclusion, the development of training programs and health promotion should be considered to enhance the knowledge, attitudes, and practices related to soil-transmitted helminthiasis in VHVs, who are the key individuals for providing health education to community members.
Phenotypic and Genetic Characterization of Aeromonas hydrophila Phage AhMtk13a and Evaluation of Its Therapeutic Potential on Simulated Aeromonas Infection in Danio rerio
Authors: Janelidze Nino , Jaiani Ekaterine , Didebulidze Elene , Kusradze Ia , Kotorashvili Adam , Chalidze Kristine , Porchkhidze Ketevan , Khukhunashvili Tinatin , Tsertsvadze George , Jgenti Dodo , Bajashvili Tamaz , Tediashvili Marina
Published: February 2022

Phage therapy can be an effective alternative to standard antimicrobial chemotherapy for control of Aeromonas hydrophila infections in aquaculture. Aeromonas hydrophila-specific phages AhMtk13a and AhMtk13b were studied for basic biological properties and genome characteristics. Phage AhMtk13a (Myovirus, 163,879 bp genome, 41.21% CG content) was selected based on broad lytic spectrum and physiologic parameters indicating its lytic nature. The therapeutic potential of phage AhMtk13a was evaluated in experimental studies in zebrafish challenged with A. hydrophila GW3-10 via intraperitoneal injection and passive immersion in aquaria water. In experimental series 1 with single introduction of AhMtk13a phage to aquaria water at phage–bacteria ratio 10:1, cumulative mortality 44% and 62% was registered in fish exposed to phage immediately and in 4 h after bacterial challenge, correspondingly, compared to 78% mortality in the group with no added phage. In experimental series 2 with triple application of AhMtk13a phage at ratio 100:1, the mortality comprised 15% in phage-treated group compared to the 55% in the control group. Aeromonas hydrophila GW3-10 was not detectable in aquaria water from day 9 but still present in fish at low concentration. AhMtk13a phage was maintained in fish and water throughout the experiment at the higher concentration in infected fish.
Refined Capsid Structure of Human Adenovirus D26 at 3.4 Å Resolution
Authors: Reddy Vijay S. , Yu Xiaodi , Barry Michael A.
Published: February 2022

Various adenoviruses are being used as viral vectors for the generation of vaccines against chronic and emerging diseases (e.g., AIDS, COVID-19). Here, we report the improved capsid structure for one of these vectors, human adenovirus D26 (HAdV-D26), at 3.4 Å resolution, by reprocessing the previous cryo-electron microscopy dataset and obtaining a refined model. In addition to overall improvements in the model, the highlights of the structure include (1) locating a segment of the processed peptide of VIII that was previously believed to be released from the mature virions, (2) reorientation of the helical appendage domain (APD) of IIIa situated underneath the vertex region relative to its counterpart observed in the cleavage defective (ts1) mutant of HAdV-C5 that resulted in the loss of interactions between the APD and hexon bases, and (3) the revised conformation of the cleaved N-terminal segments of pre-protein VI (pVIn), located in the hexon cavities, is highly conserved, with notable stacking interactions between the conserved His13 and Phe18 residues. Taken together, the improved model of HAdV-D26 capsid provides a better understanding of protein–protein interactions in HAdV capsids and facilitates the efforts to modify and/or design adenoviral vectors with altered properties. Last but not least, we provide some insights into clotting factors (e.g., FX and PF4) binding to AdV vectors.
A Conserved Receptor-Binding Domain in the VP1u of Primate Erythroparvoviruses Determines the Marked Tropism for Erythroid Cells
Authors: Bircher Cornelia , Bieri Jan , Assaraf Ruben , Leisi Remo , Ros Carlos
Published: February 2022

Parvovirus B19 (B19V) is a human pathogen with a marked tropism for erythroid progenitor cells (EPCs). The N-terminal of the VP1 unique region (VP1u) contains a receptor-binding domain (RBD), which mediates virus uptake through interaction with an as-yet-unknown receptor (VP1uR). Considering the central role of VP1uR in the virus tropism, we sought to investigate its expression profile in multiple cell types. To this end, we established a PP7 bacteriophage-VP1u bioconjugate, sharing the size and VP1u composition of native B19V capsids. The suitability of the PP7-VP1u construct as a specific and sensitive VP1uR expression marker was validated in competition assays with B19V and recombinant VP1u. VP1uR expression was exclusively detected in erythroid cells and cells reprogrammed towards the erythroid lineage. Sequence alignment and in silico protein structure prediction of the N-terminal of VP1u (N-VP1u) from B19V and other primate erythroparvoviruses (simian, rhesus, and pig-tailed) revealed a similar structure characterized by a fold of three or four α-helices. Functional studies with simian parvovirus confirmed the presence of a conserved RBD in the N-VP1u, mediating virus internalization into human erythroid cells. In summary, this study confirms the exclusive association of VP1uR expression with cells of the erythroid lineage. The presence of an analogous RBD in the VP1u from non-human primate erythroparvoviruses emphasizes their parallel evolutionary trait and zoonotic potential.
Serum and Fecal Amino Acid Profiles in Cats with Chronic Kidney Disease
Authors: Summers Stacie C. , Quimby Jessica , Blake Amanda , Keys Deborah , Steiner Joerg M. , Suchodolski Jan
Published: February 2022

The purpose of the study was to quantify serum and fecal amino acids (AA) in cats with chronic kidney disease (CKD) and compare to healthy cats. Thirty-five cats with International Renal Interest Society Stage 1–4 CKD and 16 healthy mature adult and senior client-owned cats were included in this prospective cross-sectional study. Sera were analyzed for 25 AA concentrations using an ion exchange chromatography AA analyzer with post column ninhydrin derivatization. Voided fecal samples were analyzed for 22 AA concentrations using liquid chromatography with tandem mass spectrometry. CKD cats had lower serum concentrations of phenylalanine (mean difference ± standard error of the mean: 12.7 ± 4.3 µM; p = 0.03), threonine (29.6 ± 9.2 µM; p = 0.03), tryptophan (18.4 ± 5.4 µM; p = 0.005), serine (29.8 ± 12.6 µM; p = 0.03), and tyrosine (11.6 ± 3.8 µM; p = 0.01) and higher serum concentrations of aspartic acid (4.7 ± 2.0 µM; p = 0.01), β-alanine (3.4 ± 1.2 µM; p = 0.01), citrulline (5.7 ± 1.6 µM; p = 0.01), and taurine (109.9 ± 29.6 µM; p = 0.01) when compared to healthy cats. Fecal AA concentrations did not differ between healthy cats and CKD cats. 3-Methylhistidine-to-creatinine did not differ between healthy cats with and without muscle loss. Cats with CKD IRIS Stages 1–4 have a deranged serum amino acid profile compared to healthy cats.
Varicocele in an Adult Ram: Histopathological Examination and Sperm Quality Evaluation
Authors: Basioura Athina , Brellou Georgia D. , Tsakmakidis Ioannis , Vlemmas Ioannis , Boscos Constantin M. , Giadinis Nektarios
Published: February 2022

Varicocele is a common pathological condition of testis that is related to male fertility problems. A 3-year age Chios ram had an abnormally enlarged scrotal area, was excluded from reproductive duties, and was euthanized with the owners’ permission. The main pathological finding was the presence of bilateral multinodular spermatic cord enlargement with laminated vascular thrombi. Histopathological examination revealed commonly mineralized thrombi within the lumen of veins of the pampiniform plexus, inflammation and testicular degeneration. The epididymides were transported to the laboratory and each cauda region was sliced and washed (8 mL water for injection/epididymis), and the epididymal sperm samples were collected. Sperm motility variables (CASA), viability (eosin-nigrosine), morphology (SpermBlue®), and DNA integrity (Acridine Orange Test, AOT) were assessed. The total and progressive motility were low in semen samples of both sides (30.00% and 1.00% vs. 42.60% and 2.50% for left and right epididymis, respectively). Low viability values were observed for both sides (26.00% vs. 23.00% for left and right epididymis, respectively), while sperm morphological abnormalities were within normal limits. No sperm with DNA damage were detected. The results of this case report indicate that varicocele is associated with testis dysfunction and degradation of ram semen quality, mainly affecting motility and kinematics.
Future Climate-Driven Runoff Change in the Large River Basins in Eastern Siberia and the Far East Using Process-Based Hydrological Models
Authors: Kalugin Andrey
Published: February 2022

The main goal of this study was to obtain new results on the physically based future hydrological consequences of climate change in the Amur, Lena, and Selenga River basins by using data from an ensemble of global climate (general circulation) models (GCMs) as boundary conditions in spatially distributed, process-based runoff formation models. This approach provides a basis for a more detailed comparison of the sensitivity of hydrological systems of neighboring large river basins in Eastern Siberia and the Far East. The greatest increases in annual flow are predicted for the Lena River under Representative Concentration Pathway (RCP) 2.6 and RCP 6.0 by the middle and end of the 21st century and for the Selenga River under RCP 6.0 by the end of the 21st century, while the Amur flow anomalies are close to zero. During the 21st century, the greatest relative changes in river flow are predicted for the spring flood, especially for the Lena and Selenga, under both scenarios. The summer–autumn and winter runoff of the Amur River has a negative change of up to 8% for the two RCPs, and, on the contrary, the anomalies are positive for the Lena and Selenga. Evaluating runoff variations between RCPs, we noted high summer–autumn and winter runoff changes for the Amur River under RCP 6.0 for the future period, a significant increase in anomalies of the spring and winter runoff of the Lena under RCP 6.0 by the end of the 21st century, and a greater prevalence of summer–autumn and winter runoff increase for the Selenga River under RCP 2.6 during the 21st century, but it is especially pronounced by its end.
Water Level Forecasting Using Spatiotemporal Attention-Based Long Short-Term Memory Network
Authors: Noor Fahima , Haq Sanaulla , Rakib Mohammed , Ahmed Tarik , Jamal Zeeshan , Siam Zakaria Shams , Hasan Rubyat Tasnuva , Adnan Mohammed Sarfaraz Gani , Dewan Ashraf , Rahman Rashedur M.
Published: February 2022

Bangladesh is in the floodplains of the Ganges, Brahmaputra, and Meghna River delta, crisscrossed by an intricate web of rivers. Although the country is highly prone to flooding, the use of state-of-the-art deep learning models in predicting river water levels to aid flood forecasting is underexplored. Deep learning and attention-based models have shown high potential for accurately forecasting floods over space and time. The present study aims to develop a long short-term memory (LSTM) network and its attention-based architectures to predict flood water levels in the rivers of Bangladesh. The models developed in this study incorporated gauge-based water level data over 7 days for flood prediction at Dhaka and Sylhet stations. This study developed five models: artificial neural network (ANN), LSTM, spatial attention LSTM (SALSTM), temporal attention LSTM (TALSTM), and spatiotemporal attention LSTM (STALSTM). The multiple imputation by chained equations (MICE) method was applied to address missing data in the time series analysis. The results showed that the use of both spatial and temporal attention together increases the predictive performance of the LSTM model, which outperforms other attention-based LSTM models. The STALSTM-based flood forecasting system, developed in this study, could inform flood management plans to accurately predict floods in Bangladesh and elsewhere.
Assessing Performances of Multivariate Data Assimilation Algorithms with SMOS, SMAP, and GRACE Observations for Improved Soil Moisture and Groundwater Analyses
Authors: Tangdamrongsub Natthachet , Dong Jianzhi , Shellito Peter
Published: February 2022

Multivariate data assimilation (DA) of satellite soil moisture (SM) and terrestrial water storage (TWS) observations has recently been used to improve SM and groundwater storage (GWS) simulations. Previous studies employed the ensemble Kalman approach in multivariate DA schemes, which assumes that model and observation errors have a Gaussian distribution. Despite the success of the Kalman approaches, SM and GWS estimates can be suboptimal when the Gaussian assumption is violated. Other DA approaches, such as particle smoother (PS), ensemble Gaussian particle smoother (EnGPS), and evolutionary smoother (EvS), do not rely on the Gaussian assumption and may be better suited to non-Gaussian error systems. The objective of this paper is to evaluate the performance of these four DA approaches (EnKS, PS, EnGPS, and EvS) in multivariate DA systems by assimilating satellite data from the Soil Moisture and Ocean Salinity (SMOS), Soil Moisture Active Passive (SMAP), and Gravity Recovery And Climate Experiment (GRACE) missions into the Community Atmosphere and Biosphere Land Exchange (CABLE) land surface model. The analyses are carried out in Australia’s Goulburn River catchment, where in situ SM and groundwater data are available to comprehensively validate the DA performance. Results show that all four DA approaches have outstanding performances and improve correlation coefficients of SM and GWS estimates by ~20% and 100%, respectively. The EvS outperforms the others, but its benefit is relatively marginal compared to Gaussian approaches (e.g., EnKS). This is due to the fact that SM and TWS error distributions in this study are close to Gaussian: a suitable condition for, e.g., EnKS, EnGPS. The robust performance of EvS appears to be the optimal approach for jointly assimilating multi-source hydrological observations to improve regional hydrological analyses.