bluuebunny/crossref_metadata_2025 huggingface dataset:
Dietary Germinated Paddy Rice and Stocking Density Affect Egg Performance, Serum Biochemical Properties, and Proteomic and Transcriptomic Response of Laying Hens Exposed to Chronic Heat Stress
Authors: Incharoen Tossaporn , Roytrakul Sittiruk , Likittrakulwong Wirot
Published: December 2021

Germinated paddy rice (GPR) could be a good alternative feed source for poultry with stocking density and heat stress problems. A total of 72 Hy-line Brown laying hens raised under low (LSD, 0.12 m2/bird) and high stocking densities (HSD, 0.06 m2/bird) were investigated. Three dietary GPR levels (0, 74 and 148 g/kg) were used. It was found that average daily feed intake, hen-day egg production, and egg mass significantly decreased in the HSD group. The levels of serum glucose (GLU), phosphorous (P), corticosterone (CORT), total Ig, lysozyme (LZY), and superoxide dismutase activities (SOD) in the HSD group were higher than those in the LSD group. Dietary GPR significantly affected GLU, P, alternative complement haemolytic 50 (ACH50), total Ig, and LZY. Moreover, CORT level significantly decreased in 74 and 148 g/kg dietary GPR groups, whereas SOD significantly increased only in the 148 g/kg dietary GPR group. Serum samples were analyzed using liquid chromatography-tandem mass spectrometry, and 8607 proteins were identified. Proteome analysis revealed 19 proteins which were enriched in different stocking densities and dietary GPR levels. Quantitative real-time reverse transcription-PCR technique was successfully used to verify the differentiated abundant protein profile changes. The proteins identified in this study could serve as appropriate biomarkers.
Utilizing Earth Observations of Soil Freeze/Thaw Data and Atmospheric Concentrations to Estimate Cold Season Methane Emissions in the Northern High Latitudes
Authors: Tenkanen Maria , Tsuruta Aki , Rautiainen Kimmo , Kangasaho Vilma , Ellul Raymond , Aalto Tuula
Published: December 2021

The northern wetland methane emission estimates have large uncertainties. Inversion models are a qualified method to estimate the methane fluxes and emissions in northern latitudes but when atmospheric observations are sparse, the models are only as good as their a priori estimates. Thus, improving a priori estimates is a competent way to reduce uncertainties and enhance emission estimates in the sparsely sampled regions. Here, we use a novel way to integrate remote sensing soil freeze/thaw (F/T) status from SMOS satellite to better capture the seasonality of methane emissions in the northern high latitude. The SMOS F/T data provide daily information of soil freezing state in the northern latitudes, and in this study, the data is used to define the cold season in the high latitudes and, thus, improve our knowledge of the seasonal cycle of biospheric methane fluxes. The SMOS F/T data is implemented to LPX-Bern DYPTOP model estimates and the modified fluxes are used as a biospheric a priori in the inversion model CarbonTracker Europe-CH4. The implementation of the SMOS F/T soil state is shown to be beneficial in improving the inversion model’s cold season biospheric flux estimates. Our results show that cold season biospheric CH4 emissions in northern high latitudes are approximately 0.60 Tg lower than previously estimated, which corresponds to 17% reduction in the cold season biospheric emissions. This reduction is partly compensated by increased anthropogenic emissions in the same area (0.23 Tg), and the results also indicates that the anthropogenic emissions could have even larger contribution in cold season than estimated here.
Fine Classification of Rice Paddy Based on RHSI-DT Method Using Multi-Temporal Compact Polarimetric SAR Data
Authors: Guo Xianyu , Yin Junjun , Li Kun , Yang Jian
Published: December 2021

In recent years, the compact polarimetric (CP) synthetic aperture radar (SAR) has become a hotspot of SAR Earth observation. Meanwhile, CP SAR provides both relatively rich polarization information and large swath-width for rice mapping. Fine classification of rice paddy plays an important role in growth monitoring, pest prevention and yield estimation of rice. In this study, the multi-temporal CP SAR data were firstly simulated by fully polarimetric RADARSAT-2 data, and 22 CP parameters from each of the six temporal CP SAR data were extracted. Then we built a rice height-sensitive index (RHSI). Furthermore, a decision tree (DT) method was established by using the optimal CP parameters based on RHSI. Finally, the classification results of rice paddy based on DT and support vector machine (SVM) methods were compared. Results showed that the RHSI-DT method could obtain better results, with an overall accuracy of 97.94% and a kappa coefficient of 0.973, which was 2% higher and 0.03 larger than those of the SVM method. Besides, we found that the surface scattering of m-χ decomposition (m-χ_s (0627)) and ΔShannon entropy intensity Hi (Hi (1015)-Hi (0627)) were highly effective parameters to distinguish paddies of transplanting hybrid rice (T-H) and direct-sown japonica rice (D-J).
Atmospheric Correction of Airborne Hyperspectral CASI Data Using Polymer, 6S and FLAASH
Authors: Yang Mengmeng , Hu Yong , Tian Hongzhen , Khan Faisal Ahmed , Liu Qinping , Goes Joaquim I. , Gomes Helga do R. , Kim Wonkook
Published: December 2021

Airborne hyperspectral data play an important role in remote sensing of coastal waters. However, before their application, atmospheric correction is required to remove or reduce the atmospheric effects caused by molecular and aerosol scattering and absorption. In this study, we first processed airborne hyperspectral CASI-1500 data acquired on 4 May 2019 over the Uljin coast of Korea with Polymer and then compared the performance with the other two widely used atmospheric correction approaches, i.e., 6S and FLAASH, to determine the most appropriate correction technique for CASI-1500 data in coastal waters. Our results show the superiority of Polymer over 6S and FLAASH in deriving the Rrs spectral shape and magnitude. The performance of Polymer was further evaluated by comparing CASI-1500 Rrs data with those obtained from the MODIS-Aqua sensor on 3 May 2019 and processed using Polymer. The spectral shapes of the derived Rrs from CASI-1500 and MODIS-Aqua matched well, but the magnitude of CASI-1500 Rrs was approximately 0.8 times lower than MODIS Rrs. The possible reasons for this difference were time difference (1 day) between CASI-1500 and MODIS data, higher land adjacency effect for MODIS-Aqua than for CASI-1500, and possible errors in MODIS Rrs from Polymer.
Controlling the Connected Vehicle with Bi-Directional Information: Improved Car-Following Models and Stability Analysis
Authors: Yi Ziwei , Lu Wenqi , Qu Xu , Li Linheng , Mao Peipei , Ran Bin
Published: December 2021

Connected vehicle (CV) technologies are changing the form of traditional traffic models. In the CV driving environment, abundant and accurate information is available to vehicles, promoting the development of control strategies and models. Under these circumstances, this paper proposes a bidirectional vehicles information structure (BDVIS) by making use of the acceleration information of one preceding vehicle and one following vehicle to improve the car-following models. Then, we deduced the derived multiple vehicles information structure (DMVIS), including historical movement information of multiple vehicles, without the acceleration information. Next, the paper embeds the four kinds of basic car-following models into the framework to investigate the stability condition of two structures under the small perturbation of traffic flow and explored traffic response properties with different proportions of forward-looking or backward-looking terms. Under the open boundary condition, simulations on a single lane are conducted to validate the theoretical analysis. The results indicated that BDVIS and the DMVIS perform better than the original car-following model in improving the traffic flow stability, but that they have their own advantages for differently positioned vehicles in the platoon. Moreover, increasing the proportions of the preceding and following vehicles presents a benefit to stability, but if traffic is stable, an increase in any of the parameters would extend the influence time, which reveals that neither β1 or β2 is the biggest the best for the traffic.
A Reinforcement Learning Based Dirt-Exploration for Cleaning-Auditing Robot
Authors: Pathmakumar Thejus , Elara Mohan Rajesh , Gómez Braulio Félix , Ramalingam Balakrishnan
Published: December 2021

Cleaning is one of the fundamental tasks with prime importance given in our day-to-day life. Moreover, the importance of cleaning drives the research efforts towards bringing leading edge technologies, including robotics, into the cleaning domain. However, an effective method to assess the quality of cleaning is an equally important research problem to be addressed. The primary footstep towards addressing the fundamental question of “How clean is clean” is addressed using an autonomous cleaning-auditing robot that audits the cleanliness of a given area. This research work focuses on a novel reinforcement learning-based experience-driven dirt exploration strategy for a cleaning-auditing robot. The proposed approach uses proximal policy approximation (PPO) based on-policy learning method to generate waypoints and sampling decisions to explore the probable dirt accumulation regions in a given area. The policy network is trained in multiple environments with simulated dirt patterns. Experiment trials have been conducted to validate the trained policy in both simulated and real-world environments using an in-house developed cleaning audit robot called BELUGA.
Complex Deep Neural Networks from Large Scale Virtual IMU Data for Effective Human Activity Recognition Using Wearables
Authors: Kwon Hyeokhyen , Abowd Gregory D. , Plötz Thomas
Published: December 2021

Supervised training of human activity recognition (HAR) systems based on body-worn inertial measurement units (IMUs) is often constrained by the typically rather small amounts of labeled sample data. Systems like IMUTube have been introduced that employ cross-modality transfer approaches to convert videos of activities of interest into virtual IMU data. We demonstrate for the first time how such large-scale virtual IMU datasets can be used to train HAR systems that are substantially more complex than the state-of-the-art. Complexity is thereby represented by the number of model parameters that can be trained robustly. Our models contain components that are dedicated to capture the essentials of IMU data as they are of relevance for activity recognition, which increased the number of trainable parameters by a factor of 1100 compared to state-of-the-art model architectures. We evaluate the new model architecture on the challenging task of analyzing free-weight gym exercises, specifically on classifying 13 dumbbell execises. We have collected around 41 h of virtual IMU data using IMUTube from exercise videos available from YouTube. The proposed model is trained with the large amount of virtual IMU data and calibrated with a mere 36 min of real IMU data. The trained model was evaluated on a real IMU dataset and we demonstrate the substantial performance improvements of 20% absolute F1 score compared to the state-of-the-art convolutional models in HAR.
A Critical-Systematic Review of the Interactions of Biochar with Soils and the Observable Outcomes
Authors: Nkoh Jackson Nkoh , Baquy M. Abdulaha-Al , Mia Shamim , Shi Renyong , Kamran Muhammad Aqeel , Mehmood Khalid , Xu Renkou
Published: December 2021

Biochar research has experienced a significant increase in the recent two decades. It is growing quickly, with hundreds of reviews, including meta-analyses, that have been published reporting diverse effects of biochar on soil properties and plant performance. However, an in-depth synthesis of biochar–soil interactions at the molecular level is not available. For instance, in many meta-analyses, the effects of biochar on soil properties and functions were summarized without focusing on the specificity of the biochar and soil properties. When applied to soils, biochar interacts with different soil components including minerals, organic matter, gases, liquids, and nutrients, while it also changes soil microbial community structure and their occurrence. These different interactions modify soil physicochemical properties with consequences for dynamic changes in nutrient availability and, thus, plant performance. This review systematically analyzed biochar effects on soil properties and functions: (a) soil physical properties; (b) chemical properties; (c) biological properties; and (d) functions (plant performance, nutrient cycling, etc.). Our synthesis revealed that the surface properties of biochar (specific surface area and charge) and its associated nutrient content determine its role in the soil. At the same time, the extent of changes depends on soil properties, suggesting that both biochar and soil properties need to be considered for harvesting benefits of biochar application. Altogether, we believe our synthesis will provide a guide for researchers and practitioners for future research as well as large-scale field applications.
Trace Metal Accumulation in Rice Variety Kainat Irrigated with Canal Water
Authors: Khan Zafar Iqbal , Mansha Asim , Saleem Muhammad Hamzah , Tariq Farah , Ahmad Kafeel , Ahmad Tasneem , Farooq Awan Muhammad Umer , Abualreesh Muyassar H. , Alatawi Aishah , Ali Shafaqat
Published: December 2021

Due to the rapid increase in industrial and urban areas, environmental pollution is increasing worldwide, causing unwanted changes in the air, water, and soil at biological, physical, and chemical levels, ultimately causing negative effects for living things. This work was performed in Jhang, Punjab, Pakistan, and examined and measured heavy metal levels in various plant parts of the rice (Oryza sativa) variety Kainat (roots, shoots, and grains) with results been set in relation to the soil around the root area. The samples were taken from five different sites. The mean level of trace metals (mg/kg) in grains was soil-dependent and varied from cadmium (Cd) (2.49–5.52), zinc (Zn) (5.8–10.78), copper (Cu) (4.82–7.85), cobalt (Co) (1.48–6.52), iron (Fe) (8.68–14.73), manganese (Mn) (6.87–13.93), and nickel (Ni) (2.3–8.34). Excluding Cd, the absorption of all metals under inspection was recorded within permissible limits, as recommended by the FAO and WHO. The pollution load index for Cd was highest at all sites. The enrichment coefficient of Co, Cd, and Cu were greater. The bioaccumulation factor at all studied sites was present, in order: Cu ˃ Zn ˃ Fe ˃ Mn ˃ Co ˃ Ni ˃ Cd. The translocation factor was present at five different sites: Mn ˃ Fe ˃ Cu ˃ Zn ˃ Co ˃ Cd ˃ Ni. The health risk index of all inspected metals was lower than 1 and was within safe limits. The higher pollution of Cd suggested maintenance of rice crop is recommended, decreasing health risks in humans.
Determinants of Fixed Asset Investment in the Polish Farms
Authors: Szymańska Elżbieta Jadwiga , Dziwulski Mariusz , Kruszyński Michał
Published: December 2021

The aim of this study was to determine the factors affecting the level of investment activity of agricultural producers in Poland. Detailed studies included 4309 farms that kept accounts within the Farm Accountancy Data Network (FADN) accounting system in the years 2010–2018. The study uses Person’s linear correlation method, the multiple correlation method, and regression analysis. For the regression analysis, both static and dynamic models were applied. The level of expenditure on agricultural investment varied in the surveyed households and showed an upward trend during the years 2010–2018. Studies have shown that the investment activity of Polish farms largely depends on the possibility of raising funds from European Union programs dedicated, inter alia, to the development of agricultural holdings. The regression analysis demonstrated that the principal factors affecting the level of agricultural investment include: the amount of long-term liabilities, the family income of the farm, and the amount of investment subsidies. Preferential loans are an important parameter in a dynamic investment model. This study suggests that agricultural policy factors should be taken into account to ensure the appropriate development of Polish farms.
Social Dynamics Simulation Using a Multi-Layer Network
Authors: Sugiki Nao , Nagao Shogo , Kurauchi Fumitaka , Mutahari Mustafa , Matsuo Kojiro
Published: December 2021

The analysis and evaluation of urban structure are important while considering sustainable urban policies. It is necessary to develop a method that can easily analyze the social dynamics that are the result of changes over time in urban transportation and land use. Therefore, by describing the relationships between various agents in urban areas as a network, it is possible to analyze them by focusing on their structures. However, since there are few existing studies on social dynamics using network-based methods, it is necessary to examine the validity and effectiveness of these methods. The purpose of this study is to examine the possibility of urban analysis and evaluation focusing on the network shape by describing the urban activities and modeling the dynamics with a multilayer network. In particular, we focus on household composition and individual facility access, examine what kind of interpretation is possible for network indicators, and mention the applicability of complex networks to urban analysis. The model was applied to a two-dimensional grid virtual city, and the household composition and individual facility accessibility were quantified using the centrality index.
Use of a Graphic Organiser as a Pedagogical Instrument for the Sustainable Development of EFL Learners’ English Reading Comprehension
Authors: Qi Wenjuan , Jiang Yuhong
Published: December 2021

As a visual teaching tool, a Graphic Organiser aids students by constructing and displaying a graphic of the text’s structure, improving students’ sustainable development in English reading comprehension. However, few studies have investigated sustainable development in English reading comprehension using Graphic Organisers, although they might play a critical role in this. Thus, by adopting the methods of quasi-experimentation, observation and interview, this paper aims to address the following two questions from the perspectives of Schema Theory and Dual Coding Theory: (1) What is the effect of Graphic Organisers implemented in English reading on English as a foreign language (EFL) learners’ sustainable development in English reading comprehension? Is it positive? (2) How do Graphic Organisers affect various groups of EFL learners’ sustainable development in English reading comprehension? One hundred students in an EFL school were chosen as research participants for this experiment, and the whole treatment lasted for three months. The results revealed that the application of Graphic Organisers improved EFL learners’ sustainable development in English reading comprehension overall. In addition, Graphic Organisers benefited EFL learners with a medium reading ability most in their sustainable development of English reading comprehension; Graphic Organisers also made a certain difference for students with low and high reading abilities.
Inter- and Intra-Regional Disparities in Russia: Factors of Uneven Economic Growth
Authors: Timiryanova Venera , Krasnoselskaya Dina , Lakman Irina , Popov Denis
Published: December 2021

Despite the growing body of literature on the dependence of economic growth from different factors, the reasons for uneven growth remain unclear. Within the country, regions have different growth rates in their diverse parts. It is unclear why the same factor could influence municipalities differently. To reveal this reason, we used hierarchical linear modeling with spatial dependence, which allows us to decompose variation into regional and municipal scales and take into account spatial autocorrelation. We conducted our research on data for 2239 municipalities within 85 Russian regions in 2019. Our model incorporates 20 factors of economic growth, with 7 at the municipal scale. Cross-interaction estimates established that factors attributed to the regional level determined the relationship between dependent variables (growth rate of production, growth rate of social benefits, and taxable income) at the municipal level and predictors. The influence of initial level, investments in fixed assets, employment on municipal growth varies greatly depending on such regional determinants as economic structure, innovation, human capital, and inequality. This paper adds to the existing literature on uneven economic growth at a smaller scale (municipality) and at the same time helps to rethink inter- and intra-regional disparities.
The Association of Falls Risk in Older Adults and Their Living Environment: A Case Study of Rural Area, Thailand
Authors: Iamtrakul Pawinee , Chayphong Sararad , Jomnonkwao Sajjakaj , Ratanavaraha Vatanavongs
Published: December 2021

Falls in older adults have become a serious problem and a major cause of home injuries and even deaths. The increasing number of older people that will enter the “older adults” category in a few years’ time calls for an effective plan to mitigate the risk factors to falling. This article reported on our study of the relationship between living environment hazards and fall risk in older adults to reduce and prevent the risk of falling using a specific case of a rural area in Thailand. A site investigation together with a questionnaire survey were conducted in a total of 950 homes of older people who were interviewed in conjunction with authorities from Banphaeo district of Samutsakorn Province, Thailand. Using a multinomial logistic regression model, this research found the following risk of falls based on the categorizations of the calculated risk factors among socio-economic characteristics (sex, age, marital status, income), health status (congenital diseases), and living environment characteristics (toilet availability in bedroom). The analysis identified a multifactorial relationship involving intrinsic and extrinsic factors that determined fall risk among older adults. Based on the findings of the research, risk factors associated with socioeconomic determinants in term of poverty were found as a key barrier in promoting the health and well-being of older adults. We recommend interventions for fall prevention and fall risk-reduction strategies through improvement of the physical environment in the homes of older adults as a proactive measure to lessen the causes of home injuries from falls.
Asymmetric and Symmetric Link between Quality of Institutions and Sectorial Foreign Direct Investment Inflow in India: A Fresh Insight Using Simulated Dynamic ARDL Approach
Authors: Rehman Faheem Ur , Popp József , Ahmad Ejaz , Khan Muhammad Asif , Lakner Zoltán
Published: December 2021

This study explores the bicausality between institutional quality and FDI inflow both aggregated and sector-wise, i.e., the agricultural, manufacturing, and tertiary sectors in the Indian economy, by applying simulated autoregressive distributed lag (SARDL) dynamic new techniques, an extended variant of orthodox ARDL and NARDL. The study confirms that aggregated and sectorial FDI are enhanced by adequate institutional quality, and similarly, FDI promotes quality institutions. The nexus between institutional quality and FDI inflow is an inspiration for India to compete with developed economies by enhancing its institutional quality. The study observes cointegration and bidirectional causality between institutional quality and aggregated FDI.
What Is the Customer Value of the Circular Economy? Cross-Industry Exploration of Diverse Values Perceived by Consumers and Business Customers
Authors: Aarikka-Stenroos Leena , Welathanthri Martina Don , Ranta Valtteri
Published: December 2021

A growing number of companies provide CE products, technologies, services, and solutions, and similarly, an increasing number of researchers have analyzed sustainable and CE business models providing knowledge about CE technology businesses. However, this research has focused almost solely on the providers’ perspective on CE business and offerings, remaining silent on the customer perspective. Therefore, this study contributes by focusing on the customer value of CE innovations and solutions, conducting an explorative qualitative multiple-case investigation among customers of diverse CE businesses, and mapping diverse customer value dimensions, including economic, functional, emotional, and symbolic, and comparing them as perceived by consumer and business customers. The findings show that the functional value of CE offerings dominates. We develop conceptual maps for CE customer value for a theoretical understanding of the CE from the customer perspective and provide insights for managers to assert the value of their CE solutions.
Students’ Interests in Biodiversity: Links with Health and Sustainability
Authors: Franzolin Fernanda , Carvalho Graça S. , Santana Carolina Maria Boccuzzi , Calegari Andreia dos Santos , Almeida Ester Aparecida Ely de , Soares João Paulo Reis , Jorge Jessica , Neves Franciele Dutra das , Lemos Erika Romanholo Silva
Published: December 2021

The COVID-19 pandemic has shown that sustainable actions to preserve biodiversity are critical to preventing new microorganisms from harming human health. In this sense, education and encouraging young people’s interest in local biodiversity are crucial to promoting its preservation and sustainability. This research studied the biodiversity interests of 14–15-year-old students in São Paulo State, focusing on the links between biodiversity and human health. The criterion of maximum variation was used to constitute a heterogeneous sample of students. Students answered a four-point Likert questionnaire. The items in this questionnaire were divided into categories related to the interest of young people in biodiversity, and these were analyzed using descriptive and inferential statistics (Wilcoxon test). Categories of biodiversity linked to “health or human utility” were of higher interest to young people than those with no links to human benefits, such as “diversity of organisms”. These findings, along with the literature, showed that young people are interested in biodiversity issues associated with human health. Therefore, teaching biodiversity should reflect on new possibilities for making a more sustainable environment and promoting social and environmental justice, fundamental aspects of promoting and guaranteeing human health.
Diversity Variation of Silica-Scaled Chrysophytes Related to Differences in Physicochemical Variables in Estuaries of Rivers in an Arctic Watershed
Authors: Bessudova Anna , Gabyshev Viktor , Firsova Alena , Gabysheva Olga , Bukin Yurij , Likhoshway Yelena
Published: December 2021

The present study examined the taxonomic diversity of silica-scaled chrysophytes in the estuaries of the Arctic watershed of Yakutia in the context of global climate change, as these aquatic organisms are highly sensitive to environmental changes. Previously, 41 species of silica-scaled chrysophytes were recorded in the waters of Yakutia. In the present study, we supplemented this list with 55 species. We observed a high species richness (82 taxa) of silica-scaled chrysophytes in the study area. Of these, eight species were recorded in the waters of Russia for the first time. At present, the study area represents the northernmost habitat for most species observed during the study. The diversity of silica-scaled chrysophytes in Arctic rivers is comparable to or even greater than the diversity of chrysophycean flora at the middle latitudes. Most of these chrysophytes are represented by polyzonal and ubiquitous species. During 2008–2010, we noted increased relative numbers of boreal species in northern waters compared with data obtained during the previous 30 years. Overall, the species richness of silica-scaled chrysophytes in the studied rivers increased with increase in water transparency, temperature, and magnesium ion concentration, but decreased with increase in surfactant concentration. The origin of samples from a certain river; distance of the sampling site from the estuary; water temperature, transparency, and colour; and concentration of carbon dioxide, magnesium ions, total iron, surfactants, and oil products affect the species composition of silica-scaled chrysophytes in the study area. Our findings are fundamental to evaluate the current status of Arctic aquatic microflora and its further monitoring in the context of anthropogenic and climatic impacts.
Crude Oil Price Forecast Based on Deep Transfer Learning: Shanghai Crude Oil as an Example
Authors: Deng Chao , Ma Liang , Zeng Taishan
Published: December 2021

Crude oil is an important fuel resource for all countries. Accurate predictions of oil prices have important economic and social values. However, the price of crude oil is highly nonlinear under the influence of many factors, so it is very difficult to predict accurately. Shanghai crude oil futures were officially listed in March 2018. It is of great significance to accurately predict the price of Shanghai crude oil futures for guiding China’s domestic production practice. Forecasting the price of Shanghai crude oil futures is even more difficult because of the lack of price data due to the short listing time. In order to solve this problem, this paper proposes using Long Short-Term Memory Network (LSTM) based on transfer learning to predict the price of crude oil in Shanghai. The basic idea is to take advantage of the correlation between Brent crude oil and Shanghai crude oil, use Brent crude oil for training in the early stage, and then use Shanghai crude oil to fine-tune the network. The empirical results show that the LSTM model based on transfer learning has strong generalization ability and high prediction accuracy.
Morphological Uniqueness: The Concept and Its Relationship to Indicators of Biological Quality of Human Faces from Equatorial Africa
Authors: Kleisner Karel
Published: December 2021

Facial symmetry, averageness, and the level of sex-typical development of dimorphic traits are traditionally associated with various biological quality indicators and should be, therefore, preferred in mate choice. The aim of this study is to propose a concept of morphological uniqueness and uncover its possible associations to putative phenotypic cues of biological quality. In contrast to typicality expressed by averageness, morphological uniqueness quantifies the degree of possessing characteristics unique to particular groups. I employed a combination of geometric morphometric and Bayesian multiple regression to analyze 300 Cameroonian faces, while an additional 1153 faces from eight distinct populations from across four continents were used as a reference sample of the global population to calculate the morphological uniqueness of Cameroonians. I found that morphological uniqueness is positively associated with a feminine facial shape in women and negatively with morphological masculinity in men. Facial symmetry was positively associated with female faces with greater levels of uniqueness; the result for male faces was inconclusive. The faces of both sexes perceived as more attractive had lower levels of morphological uniqueness. Facial distinctiveness showed no relationship to morphological uniqueness in either sex, which indicates that morphological uniqueness and distinctiveness are two complementary approaches to studying facial typicality. In the conclusion, the evolutionary significance of the proposed concept and its potential applicability is discussed.
Evaluation of a Deep Learning Algorithm for Automated Spleen Segmentation in Patients with Conditions Directly or Indirectly Affecting the Spleen
Authors: Meddeb Aymen , Kossen Tabea , Bressem Keno K. , Hamm Bernd , Nagel Sebastian N.
Published: December 2021

The aim of this study was to develop a deep learning-based algorithm for fully automated spleen segmentation using CT images and to evaluate the performance in conditions directly or indirectly affecting the spleen (e.g., splenomegaly, ascites). For this, a 3D U-Net was trained on an in-house dataset (n = 61) including diseases with and without splenic involvement (in-house U-Net), and an open-source dataset from the Medical Segmentation Decathlon (open dataset, n = 61) without splenic abnormalities (open U-Net). Both datasets were split into a training (n = 32.52%), a validation (n = 9.15%) and a testing dataset (n = 20.33%). The segmentation performances of the two models were measured using four established metrics, including the Dice Similarity Coefficient (DSC). On the open test dataset, the in-house and open U-Net achieved a mean DSC of 0.906 and 0.897 respectively (p = 0.526). On the in-house test dataset, the in-house U-Net achieved a mean DSC of 0.941, whereas the open U-Net obtained a mean DSC of 0.648 (p < 0.001), showing very poor segmentation results in patients with abnormalities in or surrounding the spleen. Thus, for reliable, fully automated spleen segmentation in clinical routine, the training dataset of a deep learning-based algorithm should include conditions that directly or indirectly affect the spleen.
Temporal Patterns of Bacterial and Viral Communities during Algae Blooms of a Reservoir in Macau
Authors: Hu Dini , Giesy John P. , Guo Min , Ung Wai Kin , Kong Yijun , Mok Kai Meng , Lee Simon Ming-Yuen
Published: December 2021

Compositions of microbial communities associated with blooms of algae in a storage reservoir in Macau, China were investigated between 2013 and 2016. Algae were enumerated by visible light microscopy. Profiles of organisms in water were examined by 16S rRNA sequences and viral metagenomics, based on next generation sequencing. Results of 16S rRNA sequencing indicated that majority of the identified organisms were bacteria closely related to Proteobacteria, Cyanobacteria, Verrucomicrobia, Bacteroidetes, and Actinobacteria. Metagenomics sequences demonstrated that the dominant virus was Phycodnavirus, accounting for 70% of the total population. Patterns of relative numbers of bacteria in the microbial community and their temporal changes were determined through alpha diversity indices, principal coordinates analysis (PCoA), relative abundance, and visualized by Venn diagrams. Ways in which the bacterial and viral communities are influenced by various water-related variables were elucidated based on redundancy analysis (RDA). Relationships of the relative numbers of bacteria with trophic status in a reservoir used for drinking water in Macau, provided insight into associations of Phycodnavirus and Proteobacteria with changes in blooms of algae.
The Autophagy Cargo Receptor SQSTM1 Inhibits Infectious Bursal Disease Virus Infection through Selective Autophagic Degradation of Double-Stranded Viral RNA
Authors: Xu Chenyang , Li Tongtong , Lei Jing , Zhang Yina , Zhou Jiyong , Hu Boli
Published: December 2021

Selective autophagy mediates the degradation of cytoplasmic cargos, such as damaged organelles, invading pathogens, and protein aggregates. However, whether it targets double-stranded RNA (dsRNA) of intracellular pathogens is still largely unknown. Here, we show that selective autophagy regulates the degradation of the infectious bursal disease virus (IBDV) dsRNA genome. The amount of dsRNA decreased greatly in cells that overexpressed the autophagy-required protein VPS34 or autophagy cargo receptor SQSTM1, while it increased significantly in SQSTM1 or VPS34 knockout cells or by treating wild-type cells with the autophagy inhibitor chloroquine or wortmannin. Confocal microscopy and structured illumination microscopy showed SQSTM1 colocalized with dsRNA during IBDV infection. A pull-down assay further confirmed the direct binding of SQSTM1 to dsRNA through amino acid sites R139 and K141. Overexpression of SQSTM1 inhibited the replication of IBDV, while knockout of SQSTM1 promoted IBDV replication. Therefore, our findings reveal the role of SQSTM1 in clearing viral dsRNA through selective autophagy, highlighting the antiviral role of autophagy in the removal of the viral genome.
Whole Genome Sequencing and Phylogenetic Analysis of Rabies Viruses from Bats in Connecticut, USA, 2018–2019
Authors: Hyeon Ji-Yeon , Risatti Guillermo R. , Helal Zeinab H. , McGinnis Holly , Sims Maureen , Hunt Amelia , Chung David H. , Kim Junwon , Desiato Julia , Lee Dong-Hun
Published: December 2021

We performed whole genome sequencing and genetic characterization of rabies viruses (RABV) detected in bats submitted to the Connecticut Veterinary Medical Diagnostic Laboratory (CVMDL) during 2018–2019. Among 88 bats submitted to CVMDL, six brain samples (6.8%, 95% confidence interval: 1.6% to 12.1%) tested positive by direct fluorescent antibody test. RABVs were detected in big brown bats (Eptesicus fuscus, n = 4), a hoary bat (Lasiurus cinereus, n = 1), and an unidentified bat species (n = 1). Complete coding sequences of four out of six detected RABVs were obtained. In phylogenetic analysis, the RABVs (18-62, 18-4347, and 19-2274) from big brown bats belong to the bats EF-E1 clade, clustering with RABVs detected from the same bat species in Pennsylvania and New Jersey. The bat RABV (19-2898) detected from the migratory hoary bat belongs to the bats LC clade, clustering with the eleven viruses detected from the same species in Arizona, Washington, Idaho, and Tennessee. The approach used in this study generated novel data regarding genetic relationships of RABV variants, including their reservoirs, and their spatial origin and it would be useful as reference data for future investigations on RABV in North America. Continued surveillance and genome sequencing of bat RABV would be needed to monitor virus evolution and transmission, and to assess the emergence of genetic mutations that may be relevant for public health.
Fast and Reliable Identification of Ammonia Phylotypes T1, T2 and T6 Using a Stereomicroscope: Implication for Large-Scale Ecological Surveys and Monitoring Programs
Authors: Pavard Jean-Charles , Richirt Julien , Courcot Lucie , Bouchet Pascal , Seuront Laurent , Bouchet Vincent M. P.
Published: December 2021

Among benthic foraminifera, the genus Ammonia is characterized by high morphological variability which makes it particularly challenging to recognize using traditional morphology-based taxonomy. Despite the joint efforts made by both molecular and morphological taxonomists, it is still hard to identify different phylotypes based on their morphology. A new method was developed recently to discriminate three NE Atlantic phylotypes of Ammonia (T1, T2, and T6). This method is based on two morphometrical parameters using scanning electron microscope (SEM) images (i.e., the average pore diameter and the elevation of sutures on the spiral side), resulting individuals being correctly assigned to their phylotype in more than 90% of cases. In this study, we assess the possibility of implementing these criteria using a stereomicroscope. Phylotype assignations by SEM and stereomicroscopic identifications are in accordance for 62.6% of the scrutinized foraminifera and increase up to 79.5% when only the phylotype T6 is considered. Though the stereomicroscopic identification of Ammonia phylotypes based on these two morphological parameters needs to be cross-validated using molecular tools, this approach noticeably allows the identification of an individual 3 to 7 times faster than using a SEM. The ratio between accuracy and efficiency, an issue that is also attributable to the use of the rose Bengal staining method, suggests prioritizing the use of stereomicroscope identifications in large foraminiferal surveys. Finally, in the context that Ammonia phylotype T6 potentially being an alien species in Europe, this method will help to quickly identify Ammonia phylotypes; hence contributing to monitor the presence of T6 in different regions and then, offering interesting research perspectives to assess the timing and/or the progression of the possible invasion.
Sea Level Prediction Using Machine Learning
Authors: Tur Rifat , Tas Erkin , Haghighi Ali Torabi , Mehr Ali Danandeh
Published: December 2021

Sea level prediction is essential for the design of coastal structures and harbor operations. This study presents a methodology to predict sea level changes using sea level height and meteorological factor observations at a tide gauge in Antalya Harbor, Turkey. To this end, two different scenarios were established to explore the most feasible input combinations for sea level prediction. These scenarios use lagged sea level observations (SC1), and both lagged sea level and meteorological factor observations (SC2) as the input for predictive modeling. Cross-correlation analysis was conducted to determine the optimum input combination for each scenario. Then, several predictive models were developed using linear regressions (MLR) and adaptive neuro-fuzzy inference system (ANFIS) techniques. The performance of the developed models was evaluated in terms of root mean squared error (RMSE), mean absolute error (MAE), scatter index (SI), and Nash Sutcliffe Efficiency (NSE) indices. The results showed that adding meteorological factors as input parameters increases the performance accuracy of the MLR models up to 33% for short-term sea level predictions. Moreover, the results contributed a more precise understanding that ANFIS is superior to MLR for sea level prediction using SC1- and SC2-based input combinations.
Impacts of Land Use Change on Water Quality Index in the Upper Ganges River near Haridwar, Uttarakhand: A GIS-Based Analysis
Authors: Maurya Pradip Kumar , Ali Sk Ajim , Alharbi Raied Saad , Yadav Krishna Kumar , Alfaisal Faisal M. , Ahmad Ateeque , Ditthakit Pakorn , Prasad Shiv , Jung You-Kyung , Jeon Byong-Hun
Published: December 2021

The water quality of rivers is deteriorating due to human interference. It is essential to understand the relationship between human activities and land use types to assess the water quality of a region. GIS is the latest tool for analyzing this spatial correlation. Land use land cover, and change detection are the best illustration for showing the human interactions with land features. This study assessed water quality index of the upper Ganges River near Haridwar, Uttarakhand, and spatially correlated it with changing land use to reach a logical conclusion. In the upper course of Ganges, along a 78-km stretch from Kaudiyala to Bhogpur, water samples were collected from five stations. For water quality index, physicochemical parameters like pH, EC, DO, TDS, CaCO3−, CaCO3, Cl−, Ca2+, Mg2+, Na+, K+, F−, Fe2+ were considered. The results of the spatial analysis were evaluated through error estimation and spatial correlation. The root mean square error between spatial land use and water quality index at the selected sampling sites was estimated to be 0.1443. The spatial correlation between land use change and site-wise differences in water quality index also showed a high positive correlation, with R2 = 0.8455. The degree of positive correlation and root mean square error strongly indicated that the water quality of the river in the upper course of the Ganges is highly impacted by human activities.
Possibility of using recombinant monoclonal antibodies in the treatment of the coronavirus infection
Authors: Klimov Vladimir Anatolievich
Published: December 2021

Monoclonal antibodies are successfully used to treat a number of viral diseases; they are produced by the plasma cells of the human immune system and are the result of a natural humoral response to the ingress of a certain antigen. Antibodies designed to target only one specific protein — in this case, the protein of the virus that causes COVID-19 — are called «monoclonal». Their purpose is to block the COVID-19 virus and prevent its penetration and replication in human cells, and their ultimate focus is on combating infectious manifestations. They are believed to cause fewer undesirable effects than convalescent plasma, which is essentially a complex of polyclonal antibodies and circulating immune complexes. Monoclonal antibodies can be synthesized in the laboratory using the blood serum of patients who have undergone this disease as a starting material. The use of monoclonal antibodies is indicated for patients with a mild and moderate form of the disease at a high risk of progression of the pathological process to a severe degree, which implies the need for hospitalization and a high probability of a fatal outcome.
The use of cardiointervalography in the diagnosis of lesions of the cardiovascular and autonomic nervous system
Authors: Skvortsov Vsevolod Vladimirovich , Skvortsova Ekaterina Mikhailovna , Zadumina Dariya Nikolaevna , Shtonda Daniil Alekseevich
Published: December 2021

Cardiointervalography is a method for assessing the state of the mechanisms of regulation of the physiological functions of the body, used in the diagnosis of lesions of the cardiovascular and autonomic nervous system. The article tells about the main reference points for general practitioners and cardiologists who are faced with the application of this method.
Historical and medical aspects of the formation and development of regional general medical practice
Authors: Kaspruk Lyudmila Ilyinichna
Published: December 2021

The results of the historical and medical analysis of the processes of formation and development of primary care in the Orenburg Region are quite relevant, especially in connection with the renewed demand for resolving urgent issues that have arisen in the system of domestic health care. Consideration of the above aspects on the example of a separate territory, the Orenburg Region, is significant, given that public health care is formed by various structures of territorial systems in the context of demographic, social and economic gradations.
Plantilla Word para manuscritos
Authors: Mestre Gómez Ulises
Published: December 2021

Los autores deberán ajustar sus manuscritos al formato adjunto.