bluuebunny/crossref_metadata_2025 huggingface dataset:
Grassland Use Intensity Classification Using Intra-Annual Sentinel-1 and -2 Time Series and Environmental Variables
Authors: Potočnik Buhvald Ana , Račič Matej , Immitzer Markus , Oštir Krištof , Veljanovski Tatjana
Published: July 2022

Detailed spatial data on grassland use intensity is needed in several European policy areas for various applications, e.g., agricultural management, supporting nature conservation programs, improving biodiversity strategies, etc. Multisensory remote sensing is an efficient tool to collect information on grassland parameters. However, there is still a lack of studies on how to process, combine, and implement large radar and optical image datasets in a joint observation framework to map grassland types on large heterogeneous study areas. In our study, we assessed the usefulness of 2521 Sentinel-1 and 586 Sentinel-2 satellite images and topographic data for mapping grassland use intensity. We focused on the distinction between intensively and extensively managed permanent grassland in a large heterogeneous study area in Slovenia. We provided dense Satellite Image Time Series (SITS) for 2017, 2018 and 2019 to identify important differences, e.g., management practices, between the two grassland types analysed. We also investigated the effectiveness of combining two different remote-sensing products, the optical Normalised Difference Vegetation Index (NDVI) and radar coherence. Grassland types were distinguished using an object-based approach and the Random Forest classification. With the use of SITS only, the models achieved poor performance in the case of cloudy years (2018). However, the performance improved with additional features (environmental variables). The feature selection method based on Mean Decrease Accuracy (MDA) provided a deeper insight into the high-dimensional multisensory SITS. It helped select the most relevant features (acquisition dates, environmental variables) that distinguish between intensive and extensive grassland types. The addition of environmental variables improved the overall classification accuracy by 7–15%, while the feature selection additionally improved the final overall classification accuracy (using all available features) by 2–3%. Although the reference dataset was limited (1259 training samples), the final overall classification accuracy was above 88% in all years analysed. The results show that the proposed Random Forest classification using combined multisensor data and environmental variables can provide better and more stable information on grasslands than single optical or radar data SITS on large heterogeneous areas. Therefore, a combined approach is recommended to distinguish different grassland types.
Spatiotemporal Modeling of Zoonotic Arbovirus Transmission in Northeastern Florida Using Sentinel Chicken Surveillance and Earth Observation Data
Authors: Campbell Lindsay P. , Guralnick Robert P. , Giordano Bryan V. , Sallam Mohamed F. , Bauer Amely M. , Tavares Yasmin , Allen Julie M. , Efstathion Caroline , Bartlett Suzanne , Wishard Randy , Xue Rui-De , Allen Benjamin , Tressler Miranda , Qualls Whitney , Burkett-Cadena Nathan D.
Published: July 2022

The irregular timing and spatial variation in the zoonotic arbovirus spillover from vertebrate hosts to humans and livestock present challenges to predicting spillover occurrence over time and across broader geographic areas, compromising effective prevention and control strategies. The objective of this study was to quantify the effects of the landscape composition and configuration and dynamic weather events on the 2018 spatiotemporal distribution of eastern equine encephalitis virus (EEEV) (Togaviridae, Alphavirus) and West Nile virus (WNV) (Flaviviridae, Flavivirus) sentinel chicken seroconversion in northeastern Florida. We used a modeling framework that explicitly accounts for joint spatial and temporal effects and incorporates key EO (Earth Observation) information on the climate and landscape in order to more accurately quantify the environmental effects on the transmission to sentinel chickens. We investigated the environmental effects using Bernoulli generalized linear mixed effects models (GLMMs), including a site-level random effect, and then added spatial random effects and spatiotemporal random effects in subsequent runs. The models were executed using an integrated nested Laplace approximation (INLA) and a stochastic partial differential equation (SPDE) approach in R-INLA. The GLMMs that included a spatiotemporal random effect performed better relative to models that included only spatial random effects and also performed better than non-spatial models. The results indicated a strong spatiotemporal structure in the seroconversion for both viruses, but EEEV exhibited a more punctuated and compact structure at the beginning of the sampling season, while WNV exhibited a more gradual and diffuse structure across the study area toward the end of the sampling season. The percentage of cypress–tupelo wetland land cover within 3500 m of coop sites and the edge density of the forest land cover within 500 m had a strong positive effect on the EEEV seroconversion, while the best fitting model for WNV was the intercept-only model with spatiotemporal random effects. The lagged climatic variables included in our study did not have a strong effect on the seroconversion for either virus when accounting for temporal autocorrelation, demonstrating the utility of capturing this structure to avoid type I errors. The predictive accuracy for out-of-sample data for the EEEV seroconversion demonstrates the potential to develop a framework that incorporates temporal dynamics in order to better predict arbovirus transmission.
On-Orbit Calibration of the KBR Antenna Phase Center of GRACE-Type Gravity Satellites
Authors: Huang Zhiyong , Li Shanshan , Huang Lingyong , Fan Diao
Published: July 2022

The coordinates of the KBR (K-band ranging system) antenna phase center of GRACE-type gravity satellites in the satellite Science Reference Frame should be precisely known, and the determination accuracy should reach 0.3 mrad in the Y (pitch) and Z (yaw) directions. Due to the precision limitation of ground measurement and the change of space environment during orbit, the KBR antenna phase center changes. In order to obtain more accurate KBR antenna phase center coordinates, it is necessary to maneuver the satellite to achieve the on-orbit calibration of the KBR antenna phase center. Based on the in-orbit calibration data of KBR of GRACE-FO satellites, a new method is proposed to estimate the antenna phase center of KBR using the inter-satellite range acceleration as the observation value. The antenna phase center of KBR is solved by the robust estimation method, and the obtained calibration results are better than 72 μm in the Y and Z directions and better than 1.3 mm in the X direction, which is 50% better than the least squares estimation algorithm. The accuracy of KBR calibration results obtained by using the data of positive maneuvers or mirror (negative) maneuvers, respectively, does not meet 0.3 mrad. It is shown that mirror maneuvers are required for KBR calibration of a GRACE-type gravity satellite to obtain antenna phase center estimation results that meet the accuracy requirements. The calibration algorithm proposed in this paper can provide reference for KBR antenna phase center calibration of Chinese GRACE-type gravity satellites.
Use of Virtual Reality to Increase Awareness of Line-of-Sight Hazards around Industrial Equipment
Authors: Gauthier Sara , Leduc Mallorie , Perfetto Sara J. , Godwin Alison
Published: July 2022

Impaired operator line of sight has been implicated in several pedestrian–equipment accidents and fatalities in the mining industry. Existing training methods for conveying visibility information lack worker engagement and may be insufficient to capture the dynamic, three-dimensional nature of blind spots around industrial equipment. The present study utilized a custom virtual reality experience intended to shift the way in which visibility information is presented. Visibility knowledge, confidence levels and safe pedestrian behaviors around the load-haul-dump vehicle were examined among participants in control and experimental (virtual reality and conventional training) groups (n = 72). Results demonstrate that the virtual reality intervention was not effective for increasing visibility knowledge and safe pedestrian behaviors relative to controls, although the performances of the virtual reality and conventional training groups were comparable. A discrepancy was identified in the perceived versus actual visibility knowledge and safe pedestrian behaviors at the rear of the load-haul-dump vehicle among the virtual reality training group. The findings suggest poor knowledge transfer between the three-dimensional virtual reality experience and the two-dimensional visibility plot used. The work also speaks to the importance of emphasizing rear-facing visibility deficits around machinery within industry safety training materials.
Effects of Interrupted Daily Routine Due to COVID-19 on Circadian Chronotype and Leisure Time Physical Activity
Authors: Renziehausen Justine M. , Fukuda David H.
Published: July 2022

Circadian chronotype is dependent on many factors including age, physical activity participation, eating and sleeping patterns, and typical schedule. Recently, the COVID-19 pandemic resulted in schedule changes for most individuals. Therefore, the purpose of this study is to examine whether sport participation influences circadian chronotype and physical activity and whether COVID-19 restrictions have impacted chronotype scores. Briefly, 128 physically active males (n = 62) and females (n = 66) between 18 and 55 years old (24.7 ± 7.1) completed a survey consisting of demographics information, the Morningness–Eveningness Questionnaire (MEQ), and the Godin Leisure Time Physical Activity Scale (LTPA). Participants were asked to answer relevant questions about their habits/preferences before and after COVID-19-related restrictions were implemented. MEQ scores categorized individuals into morning (MT), intermediate (IT), and evening (ET) chronotypes. Three-way (pre-COVID-19 chronotype x sport participation x time) repeated measures ANOVA was conducted to evaluate differences in MEQ and LTPA. A significant main effect of time was found for MEQ (p = 0.018) and LTPA (p = 0.002), indicating changes following COVID-19. A significant time x chronotype interaction was shown for MEQ (p < 0.001) with MT (p < 0.001), IT (p = 0.044), and ET (p = 0.044) individuals indicating chronotype-specific changes following COVID-19. LTPA was decreased and MEQ scores changed following COVID-19, with shifts toward IT scores.
Acute Effect of Upper-Lower Body Super-Set vs. Traditional-Set Configurations on Bar Execution Velocity and Volume
Authors: Peña García-Orea Guillermo , Rodríguez-Rosell David , Segarra-Carrillo Daniel , Da Silva-Grigoletto Marzo Edir , Belando-Pedreño Noelia
Published: July 2022

This study aimed to compare the effect on bar execution velocity and number of repetitions between two velocity-based resistance training protocols only differing in the set configuration of the full-squat (SQ) and bench-press (BP) exercises. Moderately strength-trained men were assigned to a traditional (TS, n = 9)- or an alternating-set (AS, n = 10) configuration group to perform four testing sessions against different relative loads (55–60–65–70% 1RM). Relative load, magnitude of intra-set velocity loss (%VL), number of sets, inter-set recovery time, and exercise order were matched for both groups in each session. Mean propulsive velocity of the first repetition (MPVfirst), average number of repetitions per set (NRS), total number of repetitions (TNR), and total training time per session (TT) were measured. No significant differences between training conditions were observed for any relative load in MPVfirst, NRS, and TNR in both exercises. The TS group completed a significantly higher number of repetitions (p < 0.05) at faster velocities (MPV > 0.9–1.1 m·s−1) in the SQ. In conclusion, training sessions performing AS between SQ and BP exercises with moderate relative loads and %VL result in similar bar execution velocity and volume, but in a more time-efficient manner, than the traditional approach.
Semiparametric Survival Analysis of 30-Day Hospital Readmissions with Bayesian Additive Regression Kernel Model
Authors: Chakraborty Sounak , Zhao Peng , Huang Yilun , Dey Tanujit
Published: July 2022

In this paper, we introduce a kernel-based nonlinear Bayesian model for a right-censored survival outcome data set. Our kernel-based approach provides a flexible nonparametric modeling framework to explore nonlinear relationships between predictors with right-censored survival outcome data. Our proposed kernel-based model is shown to provide excellent predictive performance via several simulation studies and real-life examples. Unplanned hospital readmissions greatly impair patients’ quality of life and have imposed a significant economic burden on American society. In this paper, we focus our application on predicting 30-day readmissions of patients. Our survival Bayesian additive regression kernel model (survival BARK or sBARK) improves the timeliness of readmission preventive intervention through a data-driven approach.
Phenotypic Variability of Wheat and Environmental Share in Soil Salinity Stress [3S] Conditions
Authors: Banjac Borislav , Mladenov Velimir , Petrović Sofija , Matković-Stojšin Mirela , Krstić Đorđe , Vujić Svetlana , Mačkić Ksenija , Kuzmanović Boris , Banjac Dušana , Jakšić Snežana , Begić Danilo , Šućur Rada
Published: July 2022

Through choosing bread wheat genotypes that can be cultivated in less productive areas, one can increase the economic worth of those lands, and increase the area under cultivation for this strategic crop. As a result, more food sources will be available for the growing global population. The phenotypic variation of ear mass and grain mass per ear, as well as the genotype × environment interaction, were studied in 11 wheat (Triticum aestivum L.) cultivars and 1 triticale (Triticosecale W.) cultivar grown under soil salinity stress (3S) during three vegetation seasons. The results of the experiment set on the control variant (solonetz) were compared to the results obtained from soil reclaimed by phosphogypsum in the amount of 25 t × ha−1 and 50 t × ha−1. Using the AMMI analysis of variance, there was found to be a statistically significant influence of additive and non-additive sources of variation on the phenotypic variation of the analyzed traits. Although the local landrace Banatka and the old variety Bankut 1205 did not have high enough genetic capacity to exhibit high values of ear mass, they were well-adapted to 3S. The highest average values of grain mass per ear and the lowest average values of the coefficient of variation were obtained in all test variants under microclimatic condition B. On soil reclaimed by 25 t × ha−1 and 50 t × ha−1 of phosphogypsum, in microclimate C, the genotypes showed the highest stability. The most stable genotypes were Rapsodija and Renesansa. Under 3S, genotype Simonida produced one of the most stable reactions for grain mass per ear.
Port Cities Creative Heritage Enhancement (PCCHE) Scenario Approach: Culture and Creativity for Sustainable Development of Naples Port
Authors: Daldanise Gaia , Clemente Massimo
Published: July 2022

In the international debate, creative and cultural responses to climate change and environmental sustainability are increasing in policies and practices. Creativity and cultural heritage enhancement can guide the definition of new trajectories of sustainable urban development, particularly in port-city interaction areas. In Europe, port-city interaction areas have been transformed into laboratories of cultural and creative experimentation for the sustainable management of cultural heritage and the urban quality of public spaces. Starting from the studies developed on the main measurement frameworks of creative cities and sustainable development policies, the paper aims to investigate the possibility of developing a “Port-cities Creative Heritage Enhancement” approach to assess and plan possible cultural and creative transformations of historical-architectural buildings, industrial archaeology, and symbolic urban spaces in the port-city interaction areas of Naples.
Study of the Air Leakage Mechanism and the Suitable Gas Drainage Volume with the Upper Tunnel
Authors: Zhang Chao , Chu Tingxiang , Liu Shanjun , Ni Xin
Published: July 2022

Gas drainage in an upper tunnel effectively prevents the gas overrun of the working face. However, the upper tunnel gas drainage quickly leads to air leakage and increases the risk of spontaneous coal combustion in the goaf. To reveal the influence of an upper tunnel gas drainage on the spontaneous combustion of coal in the goaf, the formation of an air leakage channel, the gas emission, and the distribution of the intuitive combustion danger area were studied through a numerical simulation and field measurement. The results indicated that the effective drainage section of the upper tunnel was behind the working face within a certain distance, and the air leakage mode presented the stereoscopic air leakage characteristics of high and low positions coexisting in the goaf. The spontaneous combustion danger area distribution increased gradually with the gas drainage volume increasing. However, the gas concentration in the upper corner decreased with the extraction quantity. Then a safe gas drainage volume was determined by comparing and analyzing the coal gas emission and spontaneous combustion with different extraction quantities.
Effect of the Matrix Dam in the Paddy Field Drainage Ditch on Water Purification Based on the Physical Model Test
Authors: Liu Haisheng , Yang Hao , Shang Honghua , Su Fangli , Ji Changzhi , Cheng Jing
Published: July 2022

(1) Setting a matrix dam in the paddy field drainage ditch has been recognized as an effective method to lower the velocity of water discharged from a paddy field in the drainage ditch, which can improve the purification efficiency of the drainage ditch for nitrogen and phosphorus pollutants, but the specific placement and thickness of the matrix dam have not been supported due to the insufficient research results. (2) Three thicknesses of the matrix dam were set in three locations of the physical model of the drainage ditch. By measuring the flow rate and water level in different sections, the optimal layout location and thickness of the matrix dam were determined. (3) When the matrix dam was located in section 1-1, the flow rate from sections A-A to C1-C1 was reduced by 0.159 m/s; when the matrix dam was located in section 2-2, the flow rate was reduced by 0.331 m/s; when the matrix dam was located in section 3-3, the flow rate was reduced by 0.360 m/s. (4) We concluded that the optimal design position of the matrix dam was section 3-3, 9.2 m from the entrance of the water flume, and the optimal design thickness was 0.3 m.
Coevolution between Terraced Landscapes and Rural Communities: An Integrated Approach Using Expert-Based Assessment and Evaluation of Winegrowers’ Perceptions (Northwest Piedmont, Italy)
Authors: Pomatto Enrico , Devecchi Marco , Larcher Federica
Published: July 2022

Terraced landscapes are characterized by many features but are also threatened by abandonment, with the loss of the historical landscape and increased hydrogeological risk. In this research, we developed an innovative integrated approach using expert-based assessment and evaluation of winegrowers’ perceptions to investigate the coevolution between terraced landscapes and rural communities. The aims were as follows: (i) to identify the historical landscape elements, (ii) to identify the landscape dynamics, and (iii) to analyze winegrowers’ perceptions about the historical landscape elements and future development prospects. The methodology was applied to a terraced vineyard landscape (545 ha) located in Piedmont (Italy). The expert-based assessment included historical analyses and field surveys. To evaluate winegrowers’ perceptions, an online questionnaire was used to understand their perceptions about the landscape’s historical elements and dynamics. The results suggest that unique historical landscape elements and traditional practices (vine pergolas supported by stone columns) are conserved in the area, but also highlight some dynamics, including new vine-breeding techniques (espaliers) and new land uses (olive groves, meadows, and woodland). Winegrowers (n = 49) recognized as identity elements the same identified as historical by experts. Regarding future prospects, almost all winegrowers preferred the conservation of vineyards and pergolas. The research methodology was able to show the mutual link between terraced landscapes and rural communities in coevolutionary terms and could be replicated in similar contexts. According to the winegrowers’ awareness, future planning strategies will have to support dynamic conservation of the landscape.
Predicting Pavement Structural Condition Using Machine Learning Methods
Authors: Ahmed Nazmus Sakib , Huynh Nathan , Gassman Sarah , Mullen Robert , Pierce Charles , Chen Yuche
Published: July 2022

State departments of transportation recognize the need to incorporate pavement structural condition in their pavement performance models and/or decision processes used to select candidate projects for preservation, rehabilitation, or reconstruction at the network level. However, pavement structural condition data are costly to obtain. To this end, this paper develops and evaluates the effectiveness of two machine learning methods, Random Forest (RF) and eXtreme Gradient Boosting (XGBoost), for predicting a flexible pavement’s structural condition. The aim is to be able to predict whether a pavement section’s structural condition is poor or not based on Annual Average Daily Traffic (AADT), truck percentage, and speed limit. The structural condition of a pavement is considered poor if the Surface Curvature Index (SCI12) is above 3.3. The models are developed using 950 miles of Traffic Speed Deflectometer (TSD) data collected along 8 primary routes in South Carolina. The performance of the machine learning models was compared with that of a logistic regression model. When the trained models are applied to the test data, the prediction results indicated that the XGBoost and RF models outperform the logistic regression model by 12% and 8%, respectively. XGBoost outperformed RF by 4%. With XGBoost found to be the best among the three models evaluated, its performance was examined using other poor structural condition threshold values; its prediction accuracy is found to be robust across the different scenarios. AADT and truck percentages are found to be significant factors whereas speed limit has no effect on a pavement’s structural condition.
Design Aspects in Repairability Scoring Systems: Comparing Their Objectivity and Completeness
Authors: Dangal Sagar , Faludi Jeremy , Balkenende Ruud
Published: July 2022

The Circular Economy Action Plan adopted by the European Commission aims to keep value in products as long as possible through developing product-specific requirements for durability and repairability. In this context, various scoring systems have been developed for scoring product repairability. This study assessed the objectivity and completeness of six major repair scoring systems, to see what further development may be required to make them policy instruments for testing product repairability. Completeness of the scoring systems was assessed by comparing them to the latest literature on what design features and principles drive product repairability. Objectivity was determined by assessing whether the scoring levels in each criterion were clearly defined with a quantifiable and operator-independent testing method. Results showed that most of the criteria in the scoring systems were acceptably objective and complete. However, improvements are recommended: The health and safety criterion lacked objectivity and has not yet been fully addressed. Further research is required to expand the eDiM database, and to identify whether the additional accuracy provided by eDiM compared to disassembly step compensates for the increased difficulty in testing. Finally, assessment of reassembly and diagnosis should be expanded. Addressing these gaps will lead to the development of a scoring system that could be better used in policymaking, and for assessment by consumer organizations, market surveillance authorities, and other interested stakeholders, to promote the repairability of products.
The Attitudes of K–12 Schools’ Teachers in Serbia towards the Potential of Artificial Intelligence
Authors: Kuleto Valentin , Ilić Milena P. , Bucea-Manea-Țoniş Rocsana , Ciocodeică David-Florin , Mihălcescu Horia , Mindrescu Veronica
Published: July 2022

Similar to so many other aspects of modern life, education is gradually being automated by technological means. The software, apps, systems, platforms, and digital devices that permeate modern education are inextricably linked to these automated processes. One of the primary goals of automation has always been to improve quality and efficiency by reducing the number of human repetitive tasks based on machine learning (ML) algorithms and applications that facilitate the automation of decision-making of artificial intelligence (AI). Thus, computers and robots are predictable and do exactly what they are programmed to do. It is impossible for a computer’s memory or processing power to become “tired” because machines never rest, and now some activities can be automated, thanks to advances in artificial intelligence. Schools nowadays have software that analyses data and makes decisions based on the data rather than relying solely on human analysts regarding repetitive administrative tasks. The exploratory research within the K–12 group of teachers from LINK Educational Alliance from Serbia was performed on 109 persons to identify the genuine knowledge about AI and the potential for automatisation of work processes. Based on the teachers’ opinions regarding opportunities brought about by AI in K–12 schools, we analysed their implications in implementing AI in the educational process in K–12 education.
Distance Education for Basic Surgical Skills Using Homemade Tools—DIY Methods for Emergency Situations
Authors: Schlégl Ádám Tibor , Pintér Zsolt Balázs , Kovács Anna , Kopjár Eszter , Varga Péter , Kardos Dániel , Berner-Juhos Krisztina , Maróti Péter , Füzesi Zsuzsanna
Published: July 2022

The aim of our research was to establish a reproducible curriculum that offers the possibility to gain basic surgical skills (knot tying, suturing, laparoscopy basics) through distance education in emergency situations by using tools available in the household. Forty-six volunteering third- and fourth-year medical students were involved in the study. The distance education system was set up using homemade or easily obtainable tools (an empty can, shoe box, sponge, etc.) to teach surgical knotting, suturing, and basic laparoscopic skills. The reachable learning objectives were contrasted with the original course plan. Feedback from the students has been collected. The students’ results were compared to the regular course of the previous years. Seventy-nine percent of the original learning objectives could be reached completely, and 15% partially. The necessary tools were available for 82% of the students. The students evaluated the course for 4.26 in general and 4.86 considering the circumstances (on a 5-level-scale). The homemade trainers were assessed over four as an acceptable substitution. Students’ exam results decreased only by 7% compared to the previous two years. Basic surgical skills can be educated with acceptable efficiency and student satisfaction using distance teaching and homemade tools. This is the first study where not only the simulators but the surgical instruments were replaced with household tools and evaluated by a reproducible curriculum.
Impact of the Digital Economy on the Carbon Emissions of China’s Logistics Industry
Authors: Li Juan , Wang Qinmei
Published: July 2022

As a new type of economy, the digital economy has become an important driver of economic changes and the direction of future economic development, as well as an important way to reduce carbon emissions in the logistics industry. Promoting carbon emissions reduction in the logistics industry with the digital economy has great practical significance. This paper analyzes the mechanism through which the digital economy impacts carbon emissions of the logistics industry, and then, based on provincial panel data from 2005 to 2019 in China, a nonlinear regression model and a quantile regression model are used to empirically test the digital economy’s impact on the carbon emissions of the logistics industry. The results show that there is a U-shaped correlation between the digital economy and carbon emissions of China’s logistics industry, and it is in the first half of the U-shaped correlation. The development of the digital economy has both a significant inhibitory and evolutionary effect on the carbon emissions of the logistics industry. With the increase in quantiles, the marginal impact of digital economy development on carbon emission reduction in China’s logistics industry decreases.
Research on Linear Combination Models of BDS Multi-Frequency Observations and Their Characteristics
Authors: Guo Zhongchen , Yu Xuexiang , Hu Chao , Jiang Chuang , Zhu Mingfei
Published: July 2022

The linear combination of multi-frequency carrier-phase and pseudorange observations can form the combined observations with special properties. The type and number of combined frequencies will directly affect the characteristics of the combined observations. BDS-2 and BDS-3 broadcast three and five signals, respectively, and the study of their linear combination is of great significance for precision positioning. In this contribution, the linear combination form of multi-frequency carrier-phase observations in cycles and meters is sorted out. Seven frequency combination modes are formed, and some special combinations for positioning are searched. Then, based on the principle of minimum combined noise, a simpler search method for the optimal real coefficients of ionosphere-free (IF) combination based on the least squares (LS) principle is proposed. The general analytical expressions of optimal real coefficients for multi-frequency geometry-based and ionosphere-free (GBIF), geometry-free and ionosphere-free (GFIF), and pseudorange multipath (PMP) combinations with the first-order ionosphere delay taken into account are derived. And the expression derivation process is given when both the first-order and second-order ionospheric delays are eliminated. Based on this, the characteristics of the optimal real coefficient combination in various modes are compared and discussed. The various combinations reflect that the accuracy of the combined observations from dual-frequency (DF) to five-frequency (FF) is gradually improving. The combination coefficient becomes significantly larger after taking the second-order ionospheric delay into account. In addition, the combined accuracy of BDS-3 is better than that of BDS-2. When only the first-order ionosphere is considered, the combination attribute of (B1C, B1I, B2a) is the best among the triple-frequency (TF) combinations of BDS-3. When both the first-order and second-order ionospheric delays are considered, the (B1C, B3I, B2a) combination is recommended.
Abusive Supervision Impact on Employees’ Creativity: A Mediated-Moderated Perspective
Authors: Hussain Iftikhar , Ali Shahab , Shahzad Farrukh , Irfan Muhammad , Wan Yong , Fareed Zeeshan , Sun Li
Published: July 2022

The drive for the current study was to describe the findings carried out to understand abusive supervision and employees’ creativity in business organizations. This research investigated the effect of abusive supervision on employees’ creativity. The influence of employment insecurity as a mediating variable and the moderating role of locus of control has also been examined. The study was based on Hobfoll’s conservation of resources theory. The data were collected using a self-administered questionnaire from 500 employees working in different business organizations in Pakistan. To analyze the data, the study employed path analytic approaches using multilevel modeling in Mplus 7.1. The empirical analysis has confirmed that abusive supervision and employment insecurity have a significant negative impact on employees’ creativity. Employment infectivity partially mediates the effect of abusive supervision on employees’ creativity. Moderation analysis was performed and established that the locus of control moderates the effect of abusive supervision on employment insecurity as well as the effect of employment insecurity on employees’ creativity. The current research has contributed towards developing a better understanding of the studied variables, i.e., abusive supervision, employment insecurity, locus of control, and employees’ creativity. To the best of authors’ knowledge these variables have been studied together here for the first time. The study also forwarded practical recommendations for managers and entrepreneurs.
Montgomery Identity and Ostrowski-Type Inequalities for Generalized Quantum Calculus through Convexity and Their Applications
Authors: Kalsoom Humaira , Vivas-Cortez Miguel , Abidin Muhammad Zainul , Marwan Muhammad , Khan Zareen A.
Published: July 2022

The celebrated Montgomery identity has been studied extensively since it was established. We found a novel version of the Montgomery identity when we were working inside the framework of p- and q-calculus. We acquire a Montgomery identity through a definite (p,q)-integral from these results. Consequently, we establish specific Ostrowski-type (p,q)-integral inequalities by using Montgomery identity. In addition to the well-known repercussions, this novel study provides an opportunity to set up new boundaries in the field of comparative literature. The research that is being proposed on the (p,q)-integral includes some fascinating results that demonstrate the superiority and applicability of the findings that have been achieved. This highly successful and valuable strategy is anticipated to create a new venue in the contemporary realm of special relativity and quantum theory. These mathematical inequalities and the approaches that are related to them have applications in the areas that deal with symmetry. Additionally, an application to special means is provided in the conclusion.
Nanomaterial Ecotoxicology in the Terrestrial and Aquatic Environment: A Systematic Review
Authors: Gambardella Chiara , Pinsino Annalisa
Published: July 2022

This systematic review analyzes the studies available on the ecotoxicity of nanomaterials (NMs) in the environment to understand where future research should be addressed for achieving Agenda 2030 goals on sustainable development and environmental safety. We discuss the status of NMs ecotoxicological effects across different organisms that are representative of all natural environments (land, air, water). A total of 1562 publications were retrieved from the Web of Science (all databases) by using the search criteria “nanomaterials” and “ecotoxicology”; among them, 303 studies were included in the systematic review because they met any of the following criteria: (i) focalize on both search criteria; (ii) deal with terrestrial, or aquatic environment; (iii) address models (organisms, cells) for the nano environmental risk assessment and exposure. The knowledge gaps are identified together with novel insights that need to be further investigated to better understand the ecotoxicological environmental impacts of NMs.
Gambierdiscus and Its Associated Toxins: A Minireview
Authors: Wang Da-Zhi , Xin Ye-Hong , Wang Ming-Hua
Published: July 2022

Gambierdiscus is a dinoflagellate genus widely distributed throughout tropical and subtropical regions. Some members of this genus can produce a group of potent polycyclic polyether neurotoxins responsible for ciguatera fish poisoning (CFP), one of the most significant food-borne illnesses associated with fish consumption. Ciguatoxins and maitotoxins, the two major toxins produced by Gambierdiscus, act on voltage-gated channels and TRPA1 receptors, consequently leading to poisoning and even death in both humans and animals. Over the past few decades, the occurrence and geographic distribution of CFP have undergone a significant expansion due to intensive anthropogenic activities and global climate change, which results in more human illness, a greater public health impact, and larger economic losses. The global spread of CFP has led to Gambierdiscus and its toxins being considered an environmental and human health concern worldwide. In this review, we seek to provide an overview of recent advances in the field of Gambierdiscus and its associated toxins based on the existing literature combined with re-analyses of current data. The taxonomy, phylogenetics, geographic distribution, environmental regulation, toxin detection method, toxin biosynthesis, and pharmacology and toxicology of Gambierdiscus are summarized and discussed. We also highlight future perspectives on Gambierdiscus and its associated toxins.
Development and Clinical Applications of a 5-Plex Real-Time RT-PCR for Swine Enteric Coronaviruses
Authors: Zhu Jin-Hui , Rawal Gaurav , Aljets Ethan , Yim-Im Wannarat , Yang Yong-Le , Huang Yao-Wei , Krueger Karen , Gauger Phillip , Main Rodger , Zhang Jianqiang
Published: July 2022

A PEDV/PDCoV/TGEV/SADS-CoV/XIPC 5-plex real-time RT-PCR was developed and validated for the simultaneous detection and differentiation of four swine enteric coronaviruses (PEDV, PDCoV, TGEV and SADS-CoV) in one PCR reaction (XIPC serves as an exogenous internal positive control). The 5-plex PCR had excellent analytical specificity, analytical sensitivity, and repeatability based on the testing of various viral and bacterial pathogens, serial dilutions of virus isolates, and in vitro transcribed RNAs. The 5-plex PCR had comparable diagnostic performance to a commercial PEDV/TGEV/PDCoV reference PCR, based on the testing of 219 clinical samples. Subsequently, 1807 clinical samples collected from various U.S. states during 2019–2021 were tested by the 5-plex PCR to investigate the presence of SADS-CoV in U.S. swine and the frequency of detecting swine enteric CoVs. All 1807 samples tested negative for SADS-CoV. Among the samples positive for swine enteric CoVs, there was a low frequency of detecting TGEV, an intermediate frequency of detecting PDCoV, and a high frequency of detecting PEDV. Although there is no evidence of SADS-CoV presence in the U.S. at present, the availability of the 5-plex PCR will enable us to conduct ongoing surveillance to detect and differentiate these viruses in swine samples and other host species samples as some of these coronaviruses can cause cross-species infection.
The T Cell Epitope Landscape of SARS-CoV-2 Variants of Concern
Authors: Tennøe Simen , Gheorghe Marius , Stratford Richard , Clancy Trevor
Published: July 2022

During the COVID-19 pandemic, several SARS-CoV-2 variants of concern (VOC) emerged, bringing with them varying degrees of health and socioeconomic burdens. In particular, the Omicron VOC displayed distinct features of increased transmissibility accompanied by antigenic drift in the spike protein that partially circumvented the ability of pre-existing antibody responses in the global population to neutralize the virus. However, T cell immunity has remained robust throughout all the different VOC transmission waves and has emerged as a critically important correlate of protection against SARS-CoV-2 and its VOCs, in both vaccinated and infected individuals. Therefore, as SARS-CoV-2 VOCs continue to evolve, it is crucial that we characterize the correlates of protection and the potential for immune escape for both B cell and T cell human immunity in the population. Generating the insights necessary to understand T cell immunity, experimentally, for the global human population is at present a critical but a time consuming, expensive, and laborious process. Further, it is not feasible to generate global or universal insights into T cell immunity in an actionable time frame for potential future emerging VOCs. However, using computational means we can expedite and provide early insights into the correlates of T cell protection. In this study, we generated and revealed insights on the T cell epitope landscape for the five main SARS-CoV-2 VOCs observed to date. We demonstrated using a unique AI prediction platform, a significant conservation of presentable T cell epitopes across all mutated peptides for each VOC. This was modeled using the most frequent HLA alleles in the human population and covers the most common HLA haplotypes in the human population. The AI resource generated through this computational study and associated insights may guide the development of T cell vaccines and diagnostics that are even more robust against current and future VOCs, and their emerging subvariants.
Nanoparticle- and Microparticle-Based Vaccines against Orbiviruses of Veterinary Importance
Authors: Jiménez-Cabello Luis , Utrilla-Trigo Sergio , Barreiro-Piñeiro Natalia , Pose-Boirazian Tomás , Martínez-Costas José , Marín-López Alejandro , Ortego Javier
Published: July 2022

Bluetongue virus (BTV) and African horse sickness virus (AHSV) are widespread arboviruses that cause important economic losses in the livestock and equine industries, respectively. In addition to these, another arthropod-transmitted orbivirus known as epizootic hemorrhagic disease virus (EHDV) entails a major threat as there is a conducive landscape that nurtures its emergence in non-endemic countries. To date, only vaccinations with live attenuated or inactivated vaccines permit the control of these three viral diseases, although important drawbacks, e.g., low safety profile and effectiveness, and lack of DIVA (differentiation of infected from vaccinated animals) properties, constrain their usage as prophylactic measures. Moreover, a substantial number of serotypes of BTV, AHSV and EHDV have been described, with poor induction of cross-protective immune responses among serotypes. In the context of next-generation vaccine development, antigen delivery systems based on nano- or microparticles have gathered significant attention during the last few decades. A diversity of technologies, such as virus-like particles or self-assembled protein complexes, have been implemented for vaccine design against these viruses. In this work, we offer a comprehensive review of the nano- and microparticulated vaccine candidates against these three relevant orbiviruses. Additionally, we also review an innovative technology for antigen delivery based on the avian reovirus nonstructural protein muNS and we explore the prospective functionality of the nonstructural protein NS1 nanotubules as a BTV-based delivery platform.
Computer Vision Based Deep Learning Approach for the Detection and Classification of Algae Species Using Microscopic Images
Authors: Abdullah  , Ali Sikandar , Khan Ziaullah , Hussain Ali , Athar Ali , Kim Hee-Cheol
Published: July 2022

The natural phenomenon of harmful algae bloom (HAB) has a bad impact on the quality of pure and freshwater. It increases the risk to human health, water bodies and overall aquatic ecosystem. It is necessary to continuously monitor and perform proper action against HAB. The inspection of algae blooms by using conventional methods, like algae detection under microscopes, is a difficult, expensive, and time-consuming task, however, computer vision-based deep learning models play a vital role in identifying and detecting harmful algae growth in aquatic ecosystems and water reservoirs. Many studies have been conducted to address harmful algae growth by using a CNN based model, however, the YOLO model is considered more accurate in identifying the algae. This advanced deep learning method is extensively used to detect algae and classify them according to their corresponding category. In this study, we used various versions of the convolution neural network (CNN) based on the You Only Look Once (YOLO) model. Recently YOLOv5 has been getting more attention due to its performance in real-time object detection. We performed a series of experiments on our custom microscopic images dataset by using YOLOv3, YOLOv4, and YOLOv5 to detect and classify the harmful algae bloom (HAB) of four classes. We used pre-processing techniques to enhance the quantity of data. The mean average precision (mAP) of YOLOv3, YOLOv4, and YOLO v5 is 75.3%, 83.0%, and 91.0% respectively. For the monitoring of algae bloom in freshwater, computer-aided based systems are very helpful and effective. To the best of our knowledge, this work is pioneering in the AI community for applying the YOLO models to detect algae and classify from microscopic images.
Occurrence and Reduction of Shiga Toxin-Producing Escherichia coli in Wastewaters in the Kathmandu Valley, Nepal
Authors: Sthapit Niva , Malla Bikash , Tandukar Sarmila , Ghaju Shrestha Rajani , Thakali Ocean , Sherchand Jeevan B. , Haramoto Eiji , Kazama Futaba
Published: July 2022

Inadequately treated effluents discharged from wastewater treatment plants (WWTPs) severely affect the environment and the surrounding population. This study analyzed the presence of the Shiga toxin-producing Escherichia coli (STEC) genes, stx1, and stx2, and the E. coli gene, sfmD, in municipal WWTP A (n = 11) and B (n = 11) where the reductions were also evaluated; hospitals (n = 17), sewage treatment plants (STPs) (n = 4) and non-functional WWTPs (not-working WWTPs) (n = 5) in the Kathmandu Valley, Nepal. The sfmD gene was detected in 100% of the samples in WWTPs, hospitals, and not-working WWTPs and 50% of STP samples. The highest detection of stx1 and stx2 was shown in the WWTP influents, followed by WWTP effluents, not-working WWTP wastewater, hospital wastewater, and STP wastewater. Log10 reduction values of sfmD, stx1, and stx2 in WWTP A were 1.7 log10, 1.7 log10, 1.4 log10, whereas those in WWTP B were 0.5 log10, 0.6 log10, 0.5 log10, respectively, suggesting the ineffective treatment of STEC in the wastewater in the Kathmandu Valley. The high concentrations of the stx genes in the wastewaters suggest the increasing presence of aggressive STEC in the Kathmandu Valley, which should be a major public health concern.
INFLUENCE OF CREEP ON THE STRESS-STRAIN STATE OF REINFORCED CONCRETE MULTISTORY BUILDINGS
Authors:   National Research Moscow State University of Civil Engineering, DOMAROVA E.V.
Published: July 2022

With long-term action of the load in concrete and reinforced concrete, an increase in inelastic deformations occurs, which is associated with the creep of concrete. The viscous properties of any concrete are determined by its measure of creep and creep coefficient. Modern software systems make it possible to calculate structures taking into account the rheological properties of concrete. To analyze the stress-strain state of a multi-storey building, taking into account the long-term deformation of concrete, a 45-storey model of a frame building was calculated. The creep characteristics of concrete were set according to Eurocode 2. The results of the calculation showed that the creep of concrete during its long-term deformation leads to a redistribution of forces in the building elements, an increase in floor slab deflections and an increase in the buckling of eccentrically compressed elements. A comparative analysis of the creep coefficients of high-strength concretes according to Eurocode 2 and SP 63.13330.2018 was carried out, which showed the need for an experimental study of the values specified in SP 63.13330.2018 due to a single coefficient for concretes of class B60-B100.