bluuebunny/crossref_metadata_2025 huggingface dataset:
Review: Application of Artificial Intelligence in Phenomics
Authors: Nabwire Shona , Suh Hyun-Kwon , Kim Moon S. , Baek Insuck , Cho Byoung-Kwan
Published: June 2021

Plant phenomics has been rapidly advancing over the past few years. This advancement is attributed to the increased innovation and availability of new technologies which can enable the high-throughput phenotyping of complex plant traits. The application of artificial intelligence in various domains of science has also grown exponentially in recent years. Notably, the computer vision, machine learning, and deep learning aspects of artificial intelligence have been successfully integrated into non-invasive imaging techniques. This integration is gradually improving the efficiency of data collection and analysis through the application of machine and deep learning for robust image analysis. In addition, artificial intelligence has fostered the development of software and tools applied in field phenotyping for data collection and management. These include open-source devices and tools which are enabling community driven research and data-sharing, thereby availing the large amounts of data required for the accurate study of phenotypes. This paper reviews more than one hundred current state-of-the-art papers concerning AI-applied plant phenotyping published between 2010 and 2020. It provides an overview of current phenotyping technologies and the ongoing integration of artificial intelligence into plant phenotyping. Lastly, the limitations of the current approaches/methods and future directions are discussed.
Novel Feature-Extraction Methods for the Estimation of Above-Ground Biomass in Rice Crops
Authors: Jimenez-Sierra David Alejandro , Correa Edgar Steven , Benítez-Restrepo Hernán Darío , Calderon Francisco Carlos , Mondragon Ivan Fernando , Colorado Julian D.
Published: June 2021

Traditional methods to measure spatio-temporal variations in above-ground biomass dynamics (AGBD) predominantly rely on the extraction of several vegetation-index features highly associated with AGBD variations through the phenological crop cycle. This work presents a comprehensive comparison between two different approaches for feature extraction for non-destructive biomass estimation using aerial multispectral imagery. The first method is called GFKuts, an approach that optimally labels the plot canopy based on a Gaussian mixture model, a Montecarlo-based K-means, and a guided image filtering for the extraction of canopy vegetation indices associated with biomass yield. The second method is based on a Graph-Based Data Fusion (GBF) approach that does not depend on calculating vegetation-index image reflectances. Both methods are experimentally tested and compared through rice growth stages: vegetative, reproductive, and ripening. Biomass estimation correlations are calculated and compared against an assembled ground-truth biomass measurements taken by destructive sampling. The proposed GBF-Sm-Bs approach outperformed competing methods by obtaining biomass estimation correlation of 0.995 with R2=0.991 and RMSE=45.358 g. This result increases the precision in the biomass estimation by around 62.43% compared to previous works.
Fault Diagnosis of Brake Train Based on Multi-Sensor Data Fusion
Authors: Jin Yongze , Xie Guo , Li Yankai , Zhang Xiaohui , Han Ning , Shangguan Anqi , Chen Wenbin
Published: June 2021

In this paper, a fault diagnosis method is proposed based on multi-sensor fusion information for a single fault and composite fault of train braking systems. Firstly, the single mass model of the train brake is established based on operating environment. Then, the pre-allocation and linear-weighted summation criterion are proposed to fuse the monitoring data. Finally, based on the improved expectation maximization, the braking modes and braking parameters are identified, and the braking faults are diagnosed in real time. The simulation results show that the braking parameters of systems can be effectively identified, and the braking faults can be diagnosed accurately based on the identification results. Even if the monitoring data are missing or abnormal, compared with the maximum fusion, the accuracies of parameter identifications and fault diagnoses can still meet the needs of the actual systems, and the effectiveness and robustness of the method can be verified.
Terra Preta Properties in Northwestern Amazonia (Colombia)
Authors: Orozco-Ortiz Juan Manuel , Peña-Venegas Clara Patricia , Bauke Sara Louise , Borgemeister Christian , Mörchen Ramona , Lehndorff Eva , Amelung Wulf
Published: June 2021

Whereas many researchers still approach Terra Preta (TP) as a soil category, new evidence suggests that TP refers to a directional grading of soil property changes (i.e., color, pH, nutrients, etc.) within human-made soils, originating from human activities in pre-Columbian times. Currently, most TP research focuses on the Brazilian part of the Amazon basin, but only little information is available on TP soils in the Colombian Amazon. Here, we sampled four TP and surrounding soils in the Colombian Amazon region at different soil depths and analyzed them for (i) general soil properties such as color, pH and texture, (ii) soil organic carbon and black carbon (BC) contents, the latter using benzene polycarboxylic acids as molecular marker, (iii) phosphorus availability based on sequential fractionation, and (iv) microbial residue contents using amino sugars. Our data from Colombia’s middle Caquetá River and Leticia confirmed that SOC, BC, and total P were present in significantly higher concentrations in the TP areas than the surrounding soils, while pH values and microbial residue contents were unchanged. The enrichment of P forms comprised both easily extractable and stable P pools, which both dominated to a different degree, both in TP and adjacent soils. The different degree of SOC, BC and P enrichment suggests different amounts of waste disposal by the ancient populations at different TP sites, now warranting further research for reconstructing ancient population sizes from TP chemical analyses.
Trends in Ecosystem Services across Europe Due to Land-Use/Cover Changes
Authors: Schirpke Uta , Tasser Erich
Published: June 2021

The growing pressure on society due to global change requires better integration of ecosystem services (ES) into decision-making. Despite a growing number of ES assessments, Europe-wide information on recent changes of multiple ES is still rare. This study aimed at analysing changes in ES values between 2000 and 2018 across Europe based on land use/land cover (LULC) distribution. We mapped 19 ES for 52 ecoregions and identified six major groups of ecoregions with similar LULC distribution and trends. Our results indicated that provisioning ES mainly increased in the forest-dominated region (G2), decreasing in the near-natural grassland region (G1), the region with agricultural mixed systems (G3), and the intensively-used steppic region (G6). Regulating ES slightly decreased in G1 and G6, but increased in G2 and the wetland-dominated region (G5). Cultural ES had generally low negative trends for most ecoregions. In addition, our results revealed ecoregions with differing trends in ES that could be related to specific socioeconomic developments. Our findings provide spatial and quantitative information that can be used for policy development at European national and regional levels—as well as for monitoring of ES.
The Sustainability of Waste Management Models in Circular Economies
Authors: Avilés-Palacios Carmen , Rodríguez-Olalla Ana
Published: June 2021

The circular economy (CE) is considered a key economic model to meet the challenge of sustainable development. Strenous efforts are focused on the transformation of waste into resources that can be reintroduced into the economic system through proper management. In this way, the linear and waste-producing value chain problems are solved, making them circular, and more sustainable solutions are proposed in those chains already benefiting from circular processes, so that waste generation and waste are reduced on the one hand, and on the other, the non-efficient consumption of resources decreases. In the face of this current tide, there is another option that proposes a certain nuance, based on the premise that, although circular systems promote sustainability, it does not mean that they are in themselves sustainable, given that, in the first place, the effects of CE on sustainable development are not fully known and, on the other hand, the CE model includes the flow of materials, with only scant consideration of the flow of non-material resources (water, soil and energy). This paper aims to contrast both currents from an empirical viewpoint. To achieve this, a sustainability analysis of the circular waste management systems measured through a sustainability indicator, the carbon footprint (CF), as a main sustainable indicator in climate change action, is carried out. A crucial difference between circular models that promote waste management and those that do not is found in the collective systems of extended producer responsibility (or CPR). One of the most efficient recycling processes in Europe, waste tire management, has been chosen. Thus, the aim is to verify the sense of including environmental sustainability indicators, as CF, in the process of these systems. A sustainability management model (SBA) applies to End-of Life tire collection systems (ELT). This model is based on the accumulation of environmental impacts through the activities that generate them. To be transparent, this study requires a publicly recognized CF, so the study is focused on SIGNUS, the main Spanish waste tires CPR. The results achieved allow us to conclude that CF is much lower using CPR than non-linear processes. Despite the role that CPR have in the management and use of waste as secondary raw material, it is a priority to focus efforts on their redesign in order to reduce waste. In terms of circular economy, all actions are necessary in order to achieve system efficiencies, even when externalities occur in this process.
Pre-Service Teachers’ Perceptions of Emotions and Self-Regulatory Learning in Emergency Remote Learning
Authors: Kohnke Lucas , Zou Di , Zhang Ruofei
Published: June 2021

This study explored emotions and self-regulatory learning in postgraduate students, forced to transition to emergency remote teaching, at a Hong Kong university after the start of the academic semester. Self-regulation is a critical factor for successful online learning, and emotions are important antecedents of self-regulated learning. The study adopted a two-phase research design, with an initial online questionnaire (n = 52) followed by semi-structured interviews (n = 16) to gain a rich and holistic understanding of students’ experiences. Our findings indicate that: (1) locating a suitable location to attend online classes and sharing problems with classmates were the two most frequently self-regulatory learning strategies employed by students; (2) students experienced some enjoyment attending online classes but experienced increased pressure and time commitment to complete assigned work; (3) students found online learning to lack a sense of community, making it challenging to interact with classmates. The findings suggest teachers need to incorporate various synchronous and asynchronous collaborative activities, and they need to increase their own and students’ presence online to motivate and facilitate effective teaching and learning.
Heat Transfer Measurement within Green Roof with Incinerated Municipal Solid Waste Aggregates
Authors: Kazemi Mostafa , Courard Luc , Hubert Julien
Published: June 2021

A green roof is composed of a substrate and drainage layers which are fixed on insulation material and roof structure. The global heat resistance (Rc) within a green roof is affected by the humidity content of the substrate layer in which the coarse recycled materials can be used. Moreover, the utilization of recycled coarse aggregates such as incinerated municipal solid waste aggregate (IMSWA) for the drainage layer would be a promising solution, increasing the recycling of secondary resources and saving natural resources. Therefore, this paper aims to investigate the heat transfer across green roof systems with a drainage layer of IMSWA and a substrate layer including recycled tiles and bricks in wet and dry states according to ISO-conversion method. Based on the results, water easily flows through the IMSWAs with a size of 7 mm. Meanwhile, the Rc-value of the green roof system with the dry substrate (1.26 m2 K/W) was 1.7 times more than that of the green roof system with the unsaturated substrate (0.735 m2 K/W). This means that the presence of air-spaces in the dry substrate provided more heat resistance, positively contributing to heat transfer decrease, which is also dependent on the drainage effect of IMSWA. In addition, the Rc-value of the dry substrate layer was about twice that of IMSWA as the drainage layer. No significant difference was observed between the Rc-values of the unsaturated substrate layer and the IMSWA layer.
Behind the Targets? The Case for Coherence in a Multi-Scalar Approach to Carbon Action Plans in the Transport Sector
Authors: Marsden Greg , Anable Jillian
Published: June 2021

The Paris Agreement requires radical action across all policy sectors and at all scales of government. This paper argues that without a clear framework for sectoral budget setting which takes account of interactions across spatial scales, incoherent and inadequate policy responses will result. Using a case study of the transport sector within the UK, which has committed to a zero carbon pathway in law, we look at three key elements which have to be considered in setting out a new framework: budget coherence, accounting coherence and policy coherence. Using top-down and bottom-up examples emerging from practices today in the UK, we demonstrate that there are no ‘optimal’ solutions but a set of choices, all of which appear to be better than the patchwork of approaches emerging in the absence of a framework. A multi-scalar approach is essential as transport crosses spatial boundaries and the policy system places different levers at different scales. Transparency will be beneficial for honesty with the public and the difficult politics this rapid transition necessitates. It will also mitigate against blame shifting across governments between and within scales and the resultant inaction which characterized the previous decade of supposed ‘climate action’.
Social, Economic, and Institutional Configurations of the Industrial Symbiosis Process: A Comparative Analysis of the Literature and a Proposed Theoretical and Analytical Framework
Authors: Faria Emilia , Caldeira-Pires Armando , Barreto Cristiane
Published: June 2021

This paper aims at comparatively analyzing the IS process in three remarkable empirical cases. Ostrom’s Institutional Analysis and Development framework and its categories for analysis are used to understand each process. A theoretical and analytical framework is proposed based on a survey of contextual elements that shaped the behavior of organizations towards Industrial Symbiosis practices. The results show that although there was no clear, linear order in which the actors developed symbiotic relationships, the decisions related to Industrial Symbiosis are shaped by a similar set of variables. These variables range from technical and economic aspects, such as the diversity of industries and the viability of exchanges, to social and institutional aspects, encompassing critical environmental issues; bilateral agreements; collective engagement; trust to build cooperative relationships; communication and information sharing strategies; integrated regulatory framework at three levels; congruence between government and company actions to create a cooperative environment; and governance structures involving local government, companies, research and development institutions, and a coordinating entity or the champion. This framework may serve as a reference for diagnostic analyses assessing aspects that can be improved wherein Industrial Symbiosis is already underway. It may also be useful in prescriptive analyses assessing the potential for implementing IS.
Data-Driven Public R&D Project Performance Evaluation: Results from China
Authors: Li Hongbo , Yao Bowen , Yan Xin
Published: June 2021

In public R&D projects, to improve the decision-making process and ensure the sustainability of public investment, it is indispensable to effectively evaluate the project performance. Currently, public R&D project management departments and various academic databases have accumulated a large number of project-related data. In view of this, we propose a data-driven performance evaluation framework for public R&D projects. In our framework, we collect structured and unstructured data related to completed projects from multiple websites. Then, these data are cleaned and fused to form a unified dataset. We train a project performance evaluation model by extracting the project performance information implicit in the dataset based on multi-classification supervised learning algorithms. When facing a new project that needs to be evaluated, its performance can be automatically predicted by inputting the characteristic information of the project into our performance evaluation model. Our framework is validated based on the project data of the National Natural Science Foundation of China (NSFC) in terms of four performance measures (i.e., Accuracy, Recall, Precision, F1 score). In addition, we provide a case study that applies our framework to evaluate the project performance in the logistics and supply chain area of NSFC. In conclusion, this paper contributes to the body of knowledge in sustainability by developing a data-driven method that equips the decision-maker with an automated project performance evaluation tool to make sustainable project decisions.
An Optimization Scheme of Balancing GHG Emission and Income in Circular Agriculture System
Authors: Hang Sheng , Li Jing , Xu Xiangbo , Lyu Yun , Li Yang , Gong Huarui , Xu Yan , Ouyang Zhu
Published: June 2021

With the rapid development of circular agriculture in China, balancing agricultural income and environmental impact by adjusting the structure and scale of circular agriculture is becoming increasingly important. Agriculture is a major source of greenhouse gas and income earned from agriculture drives sustainable agricultural development. This paper built a multi-objective linear programming model based on greenhouse gas emission and agricultural product income and then optimized the structure and scale of circular agriculture using Beiqiu Farm as a case study. Results showed that greenhouse gas emission was mainly from manure management in livestock industry. While the agriculture income increased by 64% after optimization, GHG emission increased by only 12.3%. The optimization made full use of straw, manure and fodder, but also minimized soil nitrogen loss. The results laid a generalized guide for adjusting the structure and scale of the planting and raising industry. Measures for optimizing the management of manure were critical in achieving low agricultural carbon emissions in future agricultural development efforts.
Clustering of EU Countries by the Level of Circular Economy: An Object-Oriented Approach
Authors: Gomonov Konstantin , Ratner Svetlana , Lazanyuk Inna , Revinova Svetlana
Published: June 2021

In order to effectively regulate the circular economy (CE) at the national and international levels, it is essential to have a unified and informative system of indicators for monitoring the progress in the CE. The lack of standard indicators for measuring the progress of cyclicality leads to contradictions and misunderstandings, which is a problem for the implementation of CE strategies. This paper aims to adapt dynamic clustering approaches to solving strategic management problems of circular production and consumption processes. To achieve this goal, the authors performed the following tasks: (1) tested clustering algorithms by ranking EU countries by the level of development of the circular economy; (2) identified the approach that allows the best classification of EU countries, considering changes in the indicators of the level of CE development in 2000–2019 (dynamic classification); (3) developed a software module using python libraries to classify and visualize the results. The results illustrate that the k-means algorithm has a good discriminatory ability in division of all countries of the training sample (EU countries) into several clusters with different dynamics in the development of the CE. The best quality of classification is obtained by the indicator “Generation of municipal waste per capita”; satisfactory quality of the classification is obtained by the indicator “Generation of waste excluding major mineral wastes per GDP unit”. The study results demonstrate the fundamental applicability of the object-oriented and classical statistical approach to solving strategic management problems of the CE and their potential effectiveness in terms of the clarity and information content of reflecting cyclical processes.
Data-Driven Methodology for Sustainable Urban Mobility Assessment and Improvement
Authors: Šoštarić Marko , Vidović Krešimir , Jakovljević Marijan , Lale Orsat
Published: June 2021

The transport system is sensitive to external influences generated by various economic, social and environmental changes. The society and the environment are changing extremely fast, resulting in the need for rapid adjustment of the transport system. Traffic system management, especially in urban areas, is a dynamic process, which is why transport planners are in need of a proven and validated methodology for fast and efficient transport data collection, fusion and analytics that will be used in sustainable urban mobility policy creation. The paper presents a development of a methodology in data rich reality that combines traditional and novel data science approach for transport system analysis and planning. The result is overall process consisting of 150 steps from first desktop research to final solution development. It enables urban mobility stakeholders to identify transport problems, analyze the urban mobility situation and to propose dedicated measures for sustainable urban mobility strengthening. The methodology is based on a big data research and analysis on anonymized big data sets originating from mobile telecommunication network, where the extraction of mobility data from the big dataset is the most innovative part of the proposed process. The extracted mobility data were validated through a “conventional” field research. The methodology was, for additional testing, applied in a pilot study, performed in the City of Rijeka in Croatia. It resulted in a set of alternative measures for modal shift from passenger cars to sustainable mobility modes, that were validated by the local public and urban mobility stakeholders.
Study of the Tourism Competitiveness Model of the World Economic Forum Using Rasch’s Mathematical Model: The Case of Portugal
Authors: Martínez-González José Alberto , Díaz-Padilla Vidina Tais , Parra-López Eduardo
Published: June 2021

In this paper, the potential of the World Economic Forum (WEF) model to analyze tourism competitiveness is studied. The study aims to analyze the WEF model’s validity, reliability and dimensionality. It attempts to determine the WEF model’s potential for studying tourism destinations’ competitiveness in an integrated context. Finally, using the WEF model, Portugal’s competitiveness is analyzed in an integrated and benchmarking context. The methodology used in this study is the Rasch mathematical model, a methodology that has been effectively demonstrated in social sciences. Competitiveness data from the latest available WEF Travel and Tourism Competitiveness Report (TTCR-2019) has been used. The results show that the WEF model is statistically valid and reliable for studying competitiveness in tourism. Likewise, the WEF model’s high potential for the joint study of competitiveness and individual countries in an integrated and benchmarking context is confirmed. The study facilitates the development of policies to improve tourism competitiveness.
Particle Flow Simulation of the Strength and Failure Characteristics of a Layered Composite Rock-Like Sample with a Single Hole
Authors: Wang Guozhu , Wang Yu , Song Lei , Shi Hao , Zhang Mingwei , Yuan Guotao , Xu Qiangguo , Xu Guangda , Zhang Weiqian , Gao Jianjun
Published: June 2021

Layered rock masses with holes are common in nature. Their mechanical behavior plays an important role in the safety and stability of engineering structures. However, previous studies have concentrated on a single lithological layer, and few studies have reported on the mechanical behavior of layered rock masses with holes. Based on the concept of symmetry, uniaxial compression tests and numerical simulations were performed on rock-like specimens with three layers and a hole in the interlayer. The hole was in the center of the sample and was symmetrical up and down. The influence of the thickness and strength of the interlayer on the mechanical behavior and failure processes of the layered rock masses with holes was investigated. The results show that the peak strength and elastic modulus were associated with the thickness and strength of the interlayer. Three failure modes were observed in the specimens, which were not only related to the thickness and strength of the interlayer, but also affected by the presence of the hole. When the thickness of the interlayer is small, mainly a single failure mode was observed (tensile failure or shear failure). However, when the interlayer was thick, the failure mode was tension-shear mixed failure. The failure mechanism of the specimens was primarily crack propagation at the edge of the hole. These research results can provide a basis for site selection, and the design of surrounding rock protection and support parameters, and thus have important practical significance for improving surrounding rock stability and ensuring construction safety.
Ordered Structures of Polynomials over Max-Plus Algebra
Authors: Wang Cailu , Xia Yuanqing , Tao Yuegang
Published: June 2021

The ordered structures of polynomial idempotent algebras over max-plus algebra are investigated in this paper. Based on the antisymmetry, the partial orders on the sets of formal polynomials and polynomial functions are introduced to generate two partially ordered idempotent algebras (POIAs). Based on the symmetry, the quotient POIA of formal polynomials is then obtained. The order structure relationships among these three POIAs are described: the POIA of polynomial functions and the POIA of formal polynomials are orderly homomorphic; the POIA of polynomial functions and the quotient POIA of formal polynomials are orderly isomorphic. By using the partial order on formal polynomials, an algebraic method is provided to determine the upper and lower bounds of an equivalence class in the quotient POIA of formal polynomials. The criterion for a formal polynomial to be the minimal element of an equivalence class is derived. Furthermore, it is proven that any equivalence class is either an uncountable set with cardinality of the continuum or a finite set with a single element.
The Antiviral Effect of the Chemical Compounds Targeting DED/EDh Motifs of the Viral Proteins on Lymphocytic Choriomeningitis Virus and SARS-CoV-2
Authors: Ngwe Tun Mya Myat , Morita Kouichi , Ishikawa Takeshi , Urata Shuzo
Published: June 2021

Arenaviruses and coronaviruses include several human pathogenic viruses, such as Lassa virus, Lymphocytic choriomeningitis virus (LCMV), SARS-CoV, MERS-CoV, and SARS-CoV-2. Although these viruses belong to different virus families, they possess a common motif, the DED/EDh motif, known as an exonuclease (ExoN) motif. In this study, proof-of-concept studies, in which the DED/EDh motif in these viral proteins, NP for arenaviruses, and nsp14 for coronaviruses, could be a drug target, were performed. Docking simulation studies between two structurally different chemical compounds, ATA and PV6R, and the DED/EDh motifs in these viral proteins indicated that these compounds target DED/EDh motifs. The concentration which exhibited modest cell toxicity was used with these compounds to treat LCMV and SARS-CoV-2 infections in two different cell lines, A549 and Vero 76 cells. Both ATA and PV6R inhibited the post-entry step of LCMV and SARS-CoV-2 infection. These studies strongly suggest that DED/EDh motifs in these viral proteins could be a drug target to combat two distinct viral families, arenaviruses and coronaviruses.
TASPERT: Target-Specific Reverse Transcript Pools to Improve HTS Plant Virus Diagnostics
Authors: Espindola Andres S. , Sempertegui-Bayas Daniela , Bravo-Padilla Danny F. , Freire-Zapata Viviana , Ochoa-Corona Francisco , Cardwell Kitty F.
Published: June 2021

High-throughput sequencing (HTS) is becoming the new norm of diagnostics in plant quarantine settings. HTS can be used to detect, in theory, all pathogens present in any given sample. The technique’s success depends on various factors, including methods for sample management/preparation and suitable bioinformatic analysis. The Limit of Detection (LoD) of HTS for plant diagnostic tests can be higher than that of PCR, increasing the risk of false negatives in the case of low titer of the target pathogen. Several solutions have been suggested, particularly for RNA viruses, including rRNA depletion of the host, dsRNA, and siRNA extractions, which increase the relative pathogen titer in a metagenomic sample. However, these solutions are costly and time-consuming. Here we present a faster and cost-effective alternative method with lower HTS-LoD similar to or lower than PCR. The technique is called TArget-SPecific Reverse Transcript (TASPERT) pool. It relies on pathogen-specific reverse primers, targeting all RNA viruses of interest, pooled and used in double-stranded cDNA synthesis. These reverse primers enrich the sample for only pathogens of interest. Evidence on how TASPERT is significantly superior to oligodT, random 6-mer, and 20-mer in generating metagenomic libraries containing the pathogen of interest is presented in this proof of concept.
How Do Enveloped Viruses Exploit the Secretory Proprotein Convertases to Regulate Infectivity and Spread?
Authors: Seidah Nabil G. , Pasquato Antonella , Andréo Ursula
Published: June 2021

Inhibition of the binding of enveloped viruses surface glycoproteins to host cell receptor(s) is a major target of vaccines and constitutes an efficient strategy to block viral entry and infection of various host cells and tissues. Cellular entry usually requires the fusion of the viral envelope with host plasma membranes. Such entry mechanism is often preceded by “priming” and/or “activation” steps requiring limited proteolysis of the viral surface glycoprotein to expose a fusogenic domain for efficient membrane juxtapositions. The 9-membered family of Proprotein Convertases related to Subtilisin/Kexin (PCSK) serine proteases (PC1, PC2, Furin, PC4, PC5, PACE4, PC7, SKI-1/S1P, and PCSK9) participate in post-translational cleavages and/or regulation of multiple secretory proteins. The type-I membrane-bound Furin and SKI-1/S1P are the major convertases responsible for the processing of surface glycoproteins of enveloped viruses. Stefan Kunz has considerably contributed to define the role of SKI-1/S1P in the activation of arenaviruses causing hemorrhagic fever. Furin was recently implicated in the activation of the spike S-protein of SARS-CoV-2 and Furin-inhibitors are being tested as antivirals in COVID-19. Other members of the PCSK-family are also implicated in some viral infections, such as PCSK9 in Dengue. Herein, we summarize the various functions of the PCSKs and present arguments whereby their inhibition could represent a powerful arsenal to limit viral infections causing the present and future pandemics.
The Bacteriophage pEp_SNUABM_08 Is a Novel Singleton Siphovirus with High Host Specificity for Erwinia pyrifoliae
Authors: Kim Sang Guen , Roh Eunjung , Park Jungkum , Giri Sib Sankar , Kwon Jun , Kim Sang Wha , Kang Jeong Woo , Lee Sung Bin , Jung Won Joon , Lee Young Min , Cho Kevin , Park Se Chang
Published: June 2021

Species belonging to the genus Erwinia are predominantly plant pathogens. A number of bacteriophages capable of infecting Erwinia have been used for the control of plant diseases such as fire blight. Public repositories provide the complete genome information for such phages, which includes genomes ranging from 30 kb to 350 kb in size. However, limited information is available regarding bacteriophages belonging to the family Siphoviridae. A novel lytic siphophage, pEp_SNUABM_08, which specifically infects Erwinia pyrifoliae, was isolated from the soil of an affected apple orchard in South Korea. A comprehensive genome analysis was performed using the Erwinia-infecting siphophage. The whole genome of pEp_SNUABM_08 comprised 62,784 bp (GC content, 57.24%) with 79 open reading frames. The genomic characteristics confirmed that pEp_SNUABM_08 is a singleton lytic bacteriophage belonging to the family Siphoviridae, and no closely related phages have been reported thus far. Our study not only characterized a unique phage, but also provides insight into the genetic diversity of Erwinia bacteriophages.
RETRACTED: The Safety of COVID-19 Vaccinations—We Should Rethink the Policy
Authors: Walach Harald , Klement Rainer , Aukema Wouter
Published: June 2021

Background: COVID-19 vaccines have had expedited reviews without sufficient safety data. We wanted to compare risks and benefits. Method: We calculated the number needed to vaccinate (NNTV) from a large Israeli field study to prevent one death. We accessed the Adverse Drug Reactions (ADR) database of the European Medicines Agency and of the Dutch National Register (lareb.nl) to extract the number of cases reporting severe side effects and the number of cases with fatal side effects. Result: The NNTV is between 200–700 to prevent one case of COVID-19 for the mRNA vaccine marketed by Pfizer, while the NNTV to prevent one death is between 9000 and 50,000 (95% confidence interval), with 16,000 as a point estimate. The number of cases experiencing adverse reactions has been reported to be 700 per 100,000 vaccinations. Currently, we see 16 serious side effects per 100,000 vaccinations, and the number of fatal side effects is at 4.11/100,000 vaccinations. For three deaths prevented by vaccination we have to accept two inflicted by vaccination. Conclusions: This lack of clear benefit should cause governments to rethink their vaccination policy.
Impact of Transcriptome and Gut Microbiome on the Response of HIV-1 Infected Individuals to a Dendritic Cell-Based HIV Therapeutic Vaccine
Authors: Pastor-Ibáñez Roque , Díez-Fuertes Francisco , Sánchez-Palomino Sonsoles , Alcamí Jose , Plana Montserrat , Torrents David , Leal Lorna , García Felipe
Published: June 2021

Therapeutic vaccines based on dendritic cells offer a good approach to HIV-specific T-cell responses and partial control of the viral load after antiretroviral therapy interruption. The aim of the present study was to identify mRNA expression profiles and to assess the impact of the gut microbiome composition for predicting the viral load control after antiretroviral therapy interruption. We enrolled 29 patients to receive either placebo or a monocyte-derived dendritic cell vaccine. Patients with a decrease in their viral load of >0.5 log10 copies/mL by 12 weeks after antiretroviral therapy interruption were considered responders. In total, 66 genes were considered differentially expressed between responders and non-responders. Enrichment analysis revealed several upregulated pathways involved in the host defense response to a virus via the type I interferon signaling pathway. Regarding the gut microbiota, responders showed enriched levels of Bacteroidetes (p < 0.005) and Verrucomicrobia (p = 0.017), while non-responders were enriched with Tenericutes (p = 0.049) and Actinobacteria (p < 0.005). We also found important differences at the genus level. However, we did not discover any effect of the dendritic cell vaccine on the transcriptome or the gut microbiota. An alternative analysis did characterize that the microbiota from responders were associated with the metabolic production of short-chain fatty acids, which are key metabolites in the regulation of intestinal homeostasis. The evidence now consistently shows that short-chain fatty acid depletion occurs in HIV-infected individuals receiving antiretroviral treatment.
Characteristics of Healthcare Workers Vaccinated against Influenza in the Era of COVID-19
Authors: Della Polla Giorgia , Licata Francesca , Angelillo Silvia , Pelullo Concetta Paola , Bianco Aida , Angelillo Italo Francesco
Published: June 2021

Understanding the potential impact of COVID-19 on receiving influenza vaccination among healthcare workers (HCWs) is of utmost importance. The purposes of the present cross-sectional study were to describe the characteristics and to explore the predictors of receiving influenza vaccination among a large cohort of Italian HCWs in hospital settings. Information was collected through an anonymous questionnaire from December 2020 through January 2021. General and practice characteristics, perceived risk of seasonal influenza, attitudes towards efficacy and safety of influenza vaccination, and reasons behind the decision to be vaccinated against influenza were explored. Fewer than half (46.2%) of HCWs agreed that influenza is a serious illness and perceived the risk of getting infected with influenza, and concerns about the safety of the vaccination were significant positive predictors. Fewer than half of the respondents were not concerned at all about the efficacy (48.6%) and safety (49.8%) of influenza vaccination, and 51.9% reported that they have not received a seasonal influenza vaccine during the previous season. The most mentioned reason for receiving the influenza vaccine in the current season was that influenza and COVID-19 share some similar symptoms. Study results will aid policymakers in developing vaccination education programs, promotion of trust to address negative misconceptions, and to achieve future high coverage among this high-risk group.
Genetic Analysis Reveals Differences in CD8+ T Cell Epitope Regions That May Impact Cross-Reactivity of Vaccine-Induced T Cells against Wild-Type Mumps Viruses
Authors: Kaaijk Patricia , Emmelot Maarten E. , Kerkhof Jeroen , van Els Cécile A.C.M. , Meiring Hugo D. , de Wit Jelle , Bodewes Rogier
Published: June 2021

Nowadays, mumps is re-emerging in highly vaccinated populations. Waning of vaccine-induced immunity plays a role, but antigenic differences between vaccine and mumps outbreak strains could also contribute to reduced vaccine effectiveness. CD8+ T cells play a critical role in immunity to viruses. However, limited data are available about sequence variability in CD8+ T cell epitope regions of mumps virus (MuV) proteins. Recently, the first set of naturally presented human leukocyte antigen Class I (HLA-I) epitopes of MuV was identified by us. In the present study, sequences of 40 CD8+ T cell epitope candidates, including previously and newly identified, obtained from Jeryl–Lynn mumps vaccine strains were compared with genomes from 462 circulating MuV strains. In 31 epitope candidates (78%) amino acid differences were detected, and in 17 (43%) of the epitope candidates the corresponding sequences in wild-type strains had reduced predicted HLA-I-binding compared to the vaccine strains. These findings suggest that vaccinated persons may have reduced T cell immunity to circulating mumps viruses due to antigenic differences.
Participation of High School Students in Authentic Science and Engineering Experiences with a University-Based Water Research Team
Authors: Alsultan Jawaher , Henderson Michelle , Feldman Allan , Rice Madison , Yang Xia , Kahler Jordin , Ergas Sarina J. , Ghebremichael Kebreab
Published: June 2021

The lack of readily available sources of potable water is major problem in many parts of the world. This project engaged high school (HS) students in authentic and meaningful science and engineering activities to teach them about the lack and poor quality of potable water in many regions and how they can be addressed through the use of point of use (POU) treatments, such as biosand filters (BSFs). The HS students’ activities paralleled those of USF students, including research question development and BSF design, construction, operation, and monitoring. An ethnographic approach was utilized by incorporating participant observation, collection and review of artifacts, and interviews. It was found that the project’s focus on the need to provide potable water in the developing world provided authenticity and meaningfulness to the HS students, which encouraged their participation in activities and the learning of science and engineering practices. The HS students reported an awareness of the differences between this project and their regular science classes. The project had a positive impact on their perceptions of themselves as scientists and their interest in STEM careers. The HS students’ results were useful to the university-based research. In addition, the USF students gained teaching experience while investigating research questions in a low-stakes environment.
Differences in Reference Evapotranspiration Variation and Climate-Driven Patterns in Different Altitudes of the Qinghai–Tibet Plateau (1961–2017)
Authors: Liu Yuan , Yao Xiaolei , Wang Qianyang , Yu Jingshan , Jiang Qi , Jiang Weiwei , Li Luyi
Published: June 2021

Reference evapotranspiration (ET0) in the hydrological cycle is one of the processes that is significantly affected by climate change. The Qinghai–Tibet Plateau (QTP) is universally recognized as a region that is sensitive to climate change. In this study, an area elevation curve is used to divide the study area into three elevation zones: low (below 2800 m), medium (2800–3800 m) and high (3800–5000 m). The cumulative anomaly curve, Mann–Kendall test, moving t-test and Yamamoto test results show that a descending mutation occurred in the 1980s, and an ascending mutation occurred in 2005. Moreover, a delay effect on the descending mutation in addition to an enhancement effect on the ascending mutation of the annual ET0 were coincident with the increasing altitude below 5000 m. The annual ET0 series for the QTP and different elevation zones showed an increasing trend from 1961 to 2017 and increased more significantly with the increase in elevation. Path analysis showed that the climate-driven patterns in different elevation zones are quite different. However, after the ascending mutations occurred in 2005, the maximum air temperature (Tmax) became the common dominant driving factor for the whole region and the three elevation zones.
In Situ Monitoring of a Eutrophicated Pond Revealed Complex Dynamics of Nitrogen and Phosphorus Triggered by Decomposition of Floating-Leaved Macrophytes
Authors: Yi Cuiyu , Li Jiafeng , Zhang Chenrong , Pan Fan , Zhou Changfang
Published: June 2021

To explore the influence of the decomposition of aquatic macrophytes on water quality in eutrophicated aquatic ecosystems and the interacting environmental factors that trigger nitrogen (N) and phosphorus (P) dynamics, a suburban pond with floating-leaved macrophytes (Pond A) as well as another nearby newly dug pond without any obvious aquatic macrophytes (Pond B) were studied. N and P levels together with a series of parameters relating to biomass, water and sediments were monitored during a period of 84 d that covered the entire decomposition process of plants. The results show that the decomposition of aquatic macrophytes can be divided into two phases, with the first phase having a faster decomposition rate and the second phase, a slower one. With the decomposition of biomass, the dissolved oxygen (DO), oxidation-reduction potential (ORP), and pondus hydrogenii (pH) of the water body increased, whereas the permanganate index (CODMn) decreased. Significantly higher levels of total phosphorus in both water and sediment (TPW and TPS) were detected in Pond A with macrophytes; TPW increased quickly during the first phase of biomass decomposition but decreased in the second phase, and TPS remained relatively stable during the first phase but increased slowly in the second phase. Total nitrogen in both water and sediment (TNW and TNS) was also significantly higher in Pond A but remained relatively stable. A structural equation model revealed that the decomposition of aquatic macrophytes, could, directly and indirectly, influence N and P cycles in an aquatic ecosystem through the regulation of pH and DO. Our study indicate that the decomposition of biomass exerted a greater influence on P than on N. Besides the direct release of P from decaying biomass, which caused a significant increase of P in water body, changes of DO and ORP and the subsequent redox state of the whole system during the process also indirectly affected the deposition and dissolution of P between sediment and water. P was the decisive factor that caused endogenous eutrophication in ponds containing aquatic macrophytes.
HydroMet: A New Code for Automated Objective Optimization of Hydrometeorological Thresholds for Landslide Initiation
Authors: Conrad Jacob L. , Morphew Michael D. , Baum Rex L. , Mirus Benjamin B.
Published: June 2021

Landslide detection and warning systems are important tools for mitigation of potential hazards in landslide prone areas. Traditionally, warning systems for shallow landslides have been informed by rainfall intensity-duration thresholds. More recent advances have introduced the concept of hydrometeorological thresholds that are informed not only by rainfall, but also by subsurface hydrological measurements. Previously, hydrometeorological thresholds have been shown to improve capabilities for forecasting shallow landslides, and they may ultimately be adapted to more generalized landslide forecasting. We present HydroMet, a code developed in Python by the U.S. Geological Survey, which allows users to guide the automated estimation of hydrometeorological thresholds for a site or area of interest, with the flexibility to select preferred threshold variables for the antecedent hydrologic conditions and the triggering meteorological conditions. Users can import hydrologic time-series data, including rainfall, soil-water content, and pore-water pressure, along with the times of known landslide occurrences, and then conduct objective optimization of warning thresholds using receiver operating characteristics. HydroMet presents many additional options, including selecting the threshold formula, the timescale of possible threshold variables, and the skill statistics used for optimization. Users can develop dual-stage thresholds for watch and warning alerts, with a lower, risk-averse threshold to avoid missed alarms and a less conservative threshold to minimize false alarms. Users may also choose to split their inventory data into calibration and evaluation subsets to independently evaluate the performance of optimized thresholds. We present output and applications of HydroMet using monitoring data from landslide-prone areas in the U.S. to demonstrate its utility and ability to produce thresholds with limited missed and false alarms for informing the next generation of reliable landslide warning systems.