bluuebunny/crossref_metadata_2025 huggingface dataset:
Seasonal Variability of Diffuse Attenuation Coefficient in the Pearl River Estuary from Long-Term Remote Sensing Imagery
Authors: Yang Chaoyu , Ye Haibin , Tang Shilin
Published: July 2020

We evaluated six empirical and semianalytical models of the diffuse attenuation coefficient at 490 nm (Kd(490)) using an in situ dataset collected in the Pearl River estuary (PRE). A combined model with the most accurate performance (correlation coefficient, R2 = 0.92) was selected and applied for long-term estimation from 2003 to 2017. Physical and biological processes in the PRE over the 14-year period were investigated by applying satellite observations (MODIS/Aqua data) and season-reliant empirical orthogonal function analysis (S-EOF). In winter, the average Kd(490) was significantly higher than in the other three seasons. A slight increasing trend was observed in spring and summer, whereas a decreasing trend was observed in winter. In summer, a tongue with a relatively high Kd(490) was found in southeastern Lingdingyang Bay. In Eastern Guangdong province (GDP), the relatively higher Kd(490) value was found in autumn and winter. Based on the second mode of S-EOF, we found that the higher values in the eastern GDP extended westward and formed a distinguishable tongue in winter. The grey relational analysis revealed that chlorophyll-a concentration (Cchla) and total suspended sediment concentration (Ctsm) were two dominant contributors determining the magnitude of Kd(490) values. The Ctsm-dominated waters were generally located in coastal and estuarine turbid waters; the Cchla-dominated waters were observed in open clear ocean. The distribution of constituents-dominated area was different in the four seasons, which was affected by physical forces, including wind field, river runoff, and sea surface temperature.
Determination of Planetary Boundary Layer height with Lidar Signals Using Maximum Limited Height Initialization and Range Restriction (MLHI-RR)
Authors: Zhong Tianfen , Wang Nanchao , Shen Xue , Xiao Da , Xiang Zhen , Liu Dong
Published: July 2020

The planetary boundary layer height (PBLH) is a vital parameter to characterize the surface convection, which determines the diffusion of air pollutants. The accurate inversion of PBLH is extremely important for the study of aerosol concentrations, in order to predict air quality and provide weather forecast. Aerosol lidar, a powerful remote sensing instrument for detecting the characteristics of atmospheric temporal and spatial evolution, can continuously retrieve the planetary boundary layer (PBL) and obtain high resolution measurements. However, multi-layer conditions, including one or more layers of aerosol, or cloud above the PBL, can seriously interfere the accuracy of PBLH determined by lidar. A new technique of maximum limited height initialization and range restriction (MLHI-RR) is proposed to eliminate the impact of multi-layer conditions on PBLH determination. Four widely used methods for deriving PBLH are utilized, in addition to the MLHI-RR constraint. Comparisons demonstrate that the proposed technique can determine the PBLH in multi-layer conditions with higher accuracy. The proposed technique requires no affiliate information besides lidar signals, which provide a convenient method for PBLH determination under complicated conditions.
Deep Learning with Open Data for Desert Road Mapping
Authors: Stewart Christopher , Lazzarini Michele , Luna Adrian , Albani Sergio
Published: July 2020

The availability of free and open data from Earth observation programmes such as Copernicus, and from collaborative projects such as Open Street Map (OSM), enables low cost artificial intelligence (AI) based monitoring applications. This creates opportunities, particularly in developing countries with scarce economic resources, for large–scale monitoring in remote regions. A significant portion of Earth’s surface comprises desert dune fields, where shifting sand affects infrastructure and hinders movement. A robust, cost–effective and scalable methodology is proposed for road detection and monitoring in regions covered by desert sand. The technique uses Copernicus Sentinel–1 synthetic aperture radar (SAR) satellite data as an input to a deep learning model based on the U–Net architecture for image segmentation. OSM data is used for model training. The method comprises two steps: The first involves processing time series of Sentinel–1 SAR interferometric wide swath (IW) acquisitions in the same geometry to produce multitemporal backscatter and coherence averages. These are divided into patches and matched with masks of OSM roads to form the training data, the quantity of which is increased through data augmentation. The second step includes the U–Net deep learning workflow. The methodology has been applied to three different dune fields in Africa and Asia. A performance evaluation through the calculation of the Jaccard similarity coefficient was carried out for each area, and ranges from 84% to 89% for the best available input. The rank distance, calculated from the completeness and correctness percentages, was also calculated and ranged from 75% to 80%. Over all areas there are more missed detections than false positives. In some cases, this was due to mixed infrastructure in the same resolution cell of the input SAR data. Drift sand and dune migration covering infrastructure is a concern in many desert regions, and broken segments in the resulting road detections are sometimes due to sand burial. The results also show that, in most cases, the Sentinel–1 vertical transmit–vertical receive (VV) backscatter averages alone constitute the best input to the U–Net model. The detection and monitoring of roads in desert areas are key concerns, particularly given a growing population increasingly on the move.
Triple Collocation-Based Assessment of Satellite Soil Moisture Products with In Situ Measurements in China: Understanding the Error Sources
Authors: Wu Xiaotao , Lu Guihua , Wu Zhiyong , He Hai , Scanlon Tracy , Dorigo Wouter
Published: July 2020

With the increasing utilization of satellite-based soil moisture products, a primary challenge is knowing their accuracy and robustness. This study presents a comprehensive assessment over China of three widely used global satellite soil moisture products, i.e., Soil Moisture Active Passive (SMAP), European Space Agency (ESA) Climate Change Initiative (CCI) Soil Moisture, Soil Moisture and Ocean Salinity (SMOS). In situ soil moisture from 1682 stations and Variable Infiltration Capacity (VIC) model are used to evaluate the performance of SMAP_L3, ESA_CCI_SM_COMBINED, SMOS_CATDS_L3 from 31 March 2015 to 3 June 2018. The Triple Collocation (TC) approach is used to minimize the uncertainty (e.g., scale issue) during the validation process. The TC analysis is conducted using three triplets, i.e., [SMAP-Insitu-VIC], [CCI-Insitu-VIC], [SMOS-Insitu-VIC]. In general, SMAP is the most reliable product, reflecting the main spatiotemporal characteristics of soil moisture, while SMOS has the lowest accuracy. The results demonstrate that the overall root mean square error of SMAP, CCI, SMOS is 0.040, 0.028, 0.107 m3m−3, respectively. The overall temporal correlation coefficient of SMAP, CCI, SMOS is 0.68, 0.65, 0.38, respectively. The overall fractional root mean square error of SMAP, CCI, SMOS is 0.707, 0.750, 0.897, respectively. In irrigated areas, the accuracy of CCI is reduced due to the land surface model (which does not consider irrigation) used for the rescaling of the CCI_COMBINED soil moisture product during the merging process, while SMAP and SMOS preserve the irrigation signal. The quality of SMOS is most strongly impacted by land surface temperature, vegetation, and soil texture, while the quality of CCI is the least affected by these factors. With the increase of Radio Frequency Interference, the accuracy of SMOS decreases dramatically, followed by SMAP and CCI. Higher representativeness error of in situ stations is noted in regions with higher topographic complexity. This study helps to provide a guideline for the application of satellite soil moisture products in scientific research and gives some references (e.g., modify data algorithm according to the main error sources) for improving the data quality.
Whitecap Observations by Microwave Radiometers: With Discussion on Surface Roughness and Foam Contributions
Authors: A. Hwang Paul
Published: July 2020

Ocean surface whitecaps manifest surface wave breaking. Most of the whitecap data reported in the literature are based on optical observations through photographic or video recording. The air in whitecaps modifies the dielectric properties of microwave emissions and scattering. Therefore, whitecap information is intrinsic to microwave signals. This paper discusses a method to retrieve the ocean surface whitecap coverage from microwave radiometer signals.
A Machine Learning Approach to Detecting Pine Wilt Disease Using Airborne Spectral Imagery
Authors: Iordache Marian-Daniel , Mantas Vasco , Baltazar Elsa , Pauly Klaas , Lewyckyj Nicolas
Published: July 2020

Pine Wilt Disease is one of the most destructive pests affecting coniferous forests. After being infected by the harmful Bursaphelenchus xylophilus nematode, most trees die within one year. The complex spreading pattern of the disease and the tedious hard labor process of diagnosis involving field wood sampling followed by laboratory analysis call for alternative methods to detect and manage the infected areas. Remote sensing comes naturally into play owing to the possibility of covering relatively large areas and the ability to discriminate healthy from sick trees based on spectral characteristics. This paper presents the development of machine learning classification algorithms for the detection of Pine Wilt Disease in Pinus pinaster, performed in the framework of the European Commission’s Horizon 2020 project “Operational Forest Monitoring using Copernicus and UAV Hyperspectral Data” (FOCUS) in two provinces of central Portugal. Five flight campaigns have been carried out in two consecutive years in order to capture a multitemporal variation of disease distribution. Classification algorithms based on a Random Forest approach were separately designed for the acquired very-high-resolution multispectral and hyperspectral data, respectively. Both algorithms achieved overall accuracies higher than 0.91 in test data. Furthermore, our study shows that the early detection of decaying trees is feasible, even before symptoms are visible in the field.
A Practical Methodology for Generating High-Resolution 3D Models of Open-Pit Slopes Using UAVs: Flight Path Planning and Optimization
Authors: Battulwar Rushikesh , Winkelmaier Garrett , Valencia Jorge , Naghadehi Masoud Zare , Peik Bijan , Abbasi Behrooz , Parvin Bahram , Sattarvand Javad
Published: July 2020

High-resolution terrain models of open-pit mine highwalls and benches are essential in developing new automated slope monitoring systems for operational optimization. This paper presents several contributions to the field of remote sensing in surface mines providing a practical framework for generating high-resolution images using low-trim Unmanned Aerial Vehicles (UAVs). First, a novel mobile application was developed for autonomous drone flights to follow mine terrain and capture high-resolution images of the mine surface. In this article, case study is presented showcasing the ability of developed software to import area terrain, plan the flight accordingly, and finally execute the area mapping mission autonomously. Next, to model the drone’s battery performance, empirical studies were conducted considering various flight scenarios. A multivariate linear regression model for drone power consumption was derived from experimental data. The model has also been validated using data from a test flight. Finally, a genetic algorithm for solving the problem of flight planning and optimization has been employed. The developed power consumption model was used as the fitness function in the genetic algorithm. The designed algorithm was then validated using simulation studies. It is shown that the offered path optimization can reduce the time and energy of high-resolution imagery missions by over 50%. The current work provides a practical framework for stability monitoring of open-pit highwalls while achieving required energy optimization and imagery performance.
Survey of 8 UAV Set-Covering Algorithms for Terrain Photogrammetry
Authors: Hammond Joshua E. , Vernon Cory A. , Okeson Trent J. , Barrett Benjamin J. , Arce Samuel , Newell Valerie , Janson Joseph , Franke Kevin W. , Hedengren John D.
Published: July 2020

Remote sensing with unmanned aerial vehicles (UAVs) facilitates photogrammetry for environmental and infrastructural monitoring. Models are created with less computational cost by reducing the number of photos required. Optimal camera locations for reducing the number of photos needed for structure-from-motion (SfM) are determined through eight mathematical set-covering algorithms as constrained by solve time. The algorithms examined are: traditional greedy, reverse greedy, carousel greedy (CG), linear programming, particle swarm optimization, simulated annealing, genetic, and ant colony optimization. Coverage and solve time are investigated for these algorithms. CG is the best method for choosing optimal camera locations as it balances number of photos required and time required to calculate camera positions as shown through an analysis similar to a Pareto Front. CG obtains a statistically significant 3.2 fewer cameras per modeled area than base greedy algorithm while requiring just one additional order of magnitude of solve time. For comparison, linear programming is capable of fewer cameras than base greedy but takes at least three orders of magnitude longer to solve. A grid independence study serves as a sensitivity analysis of the CG algorithms α (iteration number) and β (percentage to be recalculated) parameters that adjust traditional greedy heuristics, and a case study at the Rock Canyon collection dike in Provo, UT, USA, compares the results of all eight algorithms and the uniqueness (in terms of percentage comparisons based on location/angle metadata and qualitative visual comparison) of each selected set. Though this specific study uses SfM, the principles could apply to other instruments such as multi-spectral cameras or aerial LiDAR.
Polysaccharides as the Sensing Material for Metal Ion Detection-Based Optical Sensor Applications
Authors: Azeman Nur Hidayah , Arsad Norhana , A Bakar Ahmad Ashrif
Published: July 2020

The incorporation of a proper sensing material towards the construction of high selectivity optical sensing devices is vital. Polysaccharides, such as chitosan and carrageenan, are among the bio-based sensing materials that are extensively employed due to their remarkable physicochemical attributes. This paper highlights the critical aspects of the design of suitable polysaccharides for the recognition of specific analytes through physical and chemical modifications of polysaccharide structure. Such modifications lead to the enhancement of physicochemical properties of polysaccharides and optical sensor performance. Chitosan and carrageenan are two materials that possess excellent features which are capable of sensing target analytes via various interactions. The interaction between polysaccharides and analytes is dependent on the availability of functional groups in their structure. The integration of polysaccharides with various optical sensing techniques further improves optical sensor performance. The application of polysaccharides as sensing materials in various optical sensing techniques is also highlighted, particularly for metal ion sensing.
Integrated LTE and Millimeter-Wave 5G MIMO Antenna System for 4G/5G Wireless Terminals
Authors: Iffat Naqvi Syeda , Hussain Niamat , Iqbal Amjad , Rahman MuhibUr , Forsat Masoud , Mirjavadi Seyed Sajad , Amin Yasar
Published: July 2020

This work demonstrates an integrated multiple-input multiple-output (MIMO) antenna solution for Long Term Evolution (LTE) and Millimeter-Wave (mm-wave) 5G wireless communication services. The proposed structure is comprised of a two-element LTE MIMO antenna, and a four-element 5G MIMO configuration with rectangular and circular defects in the ground plane. For experimental validation, the proposed structure is fabricated on a Rogers RO4350B substrate with 0.76 mm thickness. The overall substrate dimensions are 75 mm × 110 mm. The proposed structure is capable of operating at 5.29–6.12 GHz (LTE 46 and 47 bands) and 26–29.5 GHz (5G mm-wave) frequency bands. Additionally, the measured peak gain of 5.13 and 9.53 dB is attained respectively for the microwave and mm-wave antennas. Furthermore, the analysis of the MIMO performance metrics demonstrates good characteristics, and excellent field correlation performance across the operating bands. Furthermore, the analysis of the Specific Absorption Rate (SAR) and Power Density (PD) at the lower frequency band (5.9 GHz) and PD only at mm-Wave frequency band (28 GHz) verifies that the proposed antenna system satisfies the international human safety standards. Therefore, the proposed integrated MIMO antenna configuration ascertains to be a potential contender for the forthcoming communication applications.
Evaluation of Full-Body Gestures Performed by Individuals with Down Syndrome: Proposal for Designing User Interfaces for All Based on Kinect Sensor
Authors: Del Rio Guerra Marta Sylvia , Martin-Gutierrez Jorge
Published: July 2020

The ever-growing and widespread use of touch, face, full-body, and 3D mid-air gesture recognition sensors in domestic and industrial settings is serving to highlight whether interactive gestures are sufficiently inclusive, and whether or not they can be executed by all users. The purpose of this study was to analyze full-body gestures from the point of view of user experience using the Microsoft Kinect sensor, to identify which gestures are easy for individuals living with Down syndrome. With this information, app developers can satisfy Design for All (DfA) requirements by selecting suitable gestures from existing lists of gesture sets. A set of twenty full-body gestures were analyzed in this study; to do so, the research team developed an application to measure the success/failure rates and execution times of each gesture. The results show that the failure rate for gesture execution is greater than the success rate, and that there is no difference between male and female participants in terms of execution times or the successful execution of gestures. Through this study, we conclude that, in general, people living with Down syndrome are not able to perform certain full-body gestures correctly. This is a direct consequence of limitations resulting from characteristic physical and motor impairments. As a consequence, the Microsoft Kinect sensor cannot identify the gestures. It is important to remember this fact when developing gesture-based on Human Computer Interaction (HCI) applications that use the Kinect sensor as an input device when the apps are going to be used by people who have such disabilities.
Hierarchical Anomaly Detection Model for In-Vehicle Networks Using Machine Learning Algorithms
Authors: Park Seunghyun , Choi Jin-Young
Published: July 2020

The communication and connectivity functions of vehicles increase their vulnerability to hackers. The unintended failure and malfunction of in-vehicle systems caused by external factors threaten the security and safety of passengers. As the controller area network alone cannot protect vehicles from external attacks, techniques to analyze and detect external attacks are required. Therefore, we propose a multi-labeled hierarchical classification (MLHC) intrusion detection model that analyzes and detects external attacks caused by message injection. This model quickly determines the occurrence of attacks and classifies the attack using only existing classified attack data. We evaluated the performance of the model by analyzing its learning space. We further verified the model by comparing its accuracy, F1 score and data learning and evaluation times with the two layers multi-class detection (TLMD) and single-layer multi-class classification (SLMC) models. The simulation results show that the MLHC model has the highest F1 score of 0.9995 and is 87.30% and 99.92% faster than the SLMC and TLMD models in terms of detection time, respectively. Consequently, the proposed model can classify both the type and existence or absence of attacks with high accuracy and can be used in interior communication environments of high-speed vehicles with a high throughput.
An Intelligent and Low-Cost Eye-Tracking System for Motorized Wheelchair Control
Authors: Dahmani Mahmoud , Chowdhury Muhammad E. H. , Khandakar Amith , Rahman Tawsifur , Al-Jayyousi Khaled , Hefny Abdalla , Kiranyaz Serkan
Published: July 2020

In the 34 developed and 156 developing countries, there are ~132 million disabled people who need a wheelchair, constituting 1.86% of the world population. Moreover, there are millions of people suffering from diseases related to motor disabilities, which cause inability to produce controlled movement in any of the limbs or even head. This paper proposes a system to aid people with motor disabilities by restoring their ability to move effectively and effortlessly without having to rely on others utilizing an eye-controlled electric wheelchair. The system input is images of the user’s eye that are processed to estimate the gaze direction and the wheelchair was moved accordingly. To accomplish such a feat, four user-specific methods were developed, implemented, and tested; all of which were based on a benchmark database created by the authors. The first three techniques were automatic, employ correlation, and were variants of template matching, whereas the last one uses convolutional neural networks (CNNs). Different metrics to quantitatively evaluate the performance of each algorithm in terms of accuracy and latency were computed and overall comparison is presented. CNN exhibited the best performance (i.e., 99.3% classification accuracy), and thus it was the model of choice for the gaze estimator, which commands the wheelchair motion. The system was evaluated carefully on eight subjects achieving 99% accuracy in changing illumination conditions outdoor and indoor. This required modifying a motorized wheelchair to adapt it to the predictions output by the gaze estimation algorithm. The wheelchair control can bypass any decision made by the gaze estimator and immediately halt its motion with the help of an array of proximity sensors, if the measured distance goes below a well-defined safety margin. This work not only empowers any immobile wheelchair user, but also provides low-cost tools for the organization assisting wheelchair users.
Simulation and Experiment for Growth of High-Quality and Large-Size AlN Seed Crystals by Spontaneous Nucleation
Authors: Qin Zuoyan , Chen Wenhao , Deng Danxia , Sun Zhenhua , Li Baikui , Zheng Ruisheng , Wu Honglei
Published: July 2020

Seed crystals are the prerequisite for the growth of high quality and large size aluminum nitride (AlN) single crystal boules. The physical vapor transport (PVT) method is adopted to grow AlN seed crystal. However, this method is not available in nature. Herein, the temperature field distribution in the PVT furnace was simulated using the numerical analysis method to obtain free-standing and large-size seeds. The theoretical studies indicate that the temperature distribution in the crucible is related to the crucible height. According to the theory of growth dynamics and growth surface dynamics, the optimal thermal distribution was achieved through the design of a specific crucible structure, which is determined by the ratio of top-heater power to main-heater power. Moreover, in our experiment, a sole AlN single crystal seed with a length of 12 mm was obtained on the tungsten (W) substrate. The low axial temperature gradient between material source and substrate can decrease the nucleation rate and growth rate, and the high radial temperature gradient of the substrate can promote the expansion of crystal size. Additionally, the crystallinity of the crystals grown under different thermal field conditions are analyzed and compared. The Raman results manifest the superiority of the thermal inversion method in the growth of high quality AlN single crystal.
TrustWalker: An Efficient Trust Assessment in Vehicular Internet of Things (VIoT) with Security Consideration
Authors: Sohail Muhammad , Ali Rashid , Kashif Muhammad , Ali Sher , Mehta Sumet , Zikria Yousaf Bin , Yu Heejung
Published: July 2020

The Internet of Things (IoT) is a world of connected networks and modern technology devices, among them vehicular networks considered more challenging due to high speed and network dynamics. Future trends in IoT allow these inter networks to share information. Also, the previous security solutions to vehicular IoT (VIoT) much emphasize on privacy protection and security related issues using public keys infrastructure. However, the primary concern about efficient trust assessment, authorized users malfunctioning, and secure information dissemination in vehicular wireless networks have not been explored. To cope with these challenges, we propose a trust enhanced on-demand routing (TER) scheme, which adopts TrustWalker (TW) algorithm for efficient trust assessment and route search technique in VIoT. TER comprised of novel three-valued subjective logic (3VSL), TW algorithm, and ad hoc on-demand distance vector (AODV) routing protocol. The simulated results validate the accuracy of the proposed scheme in term of throughput, packet drop ratio (PDR), and end to end (E2E) delay. In the simulation, the execution time of the TW algorithm is analyzed and compared with another route search algorithm, i.e., Assess-Trust (AT), by considering real-world online datasets such as Pretty Good Privacy and Advogato. The accuracy and efficiency of the TW algorithm, even with a large number of vehicle users, are also demonstrated through simulations.
Information Value-Based Fault Diagnosis of Train Door System under Multiple Operating Conditions
Authors: Kim Seokgoo , Kim Nam Ho , Choi Joo-Ho
Published: July 2020

While there are many data-driven diagnosis algorithms for fault isolation of complex systems, a new challenge arises in the case of multiple operating regimes. In this case, the diagnosis is usually carried out for each regime for better accuracy. However, the problem is that different results can be derived from each regime and they can conflict with each other, which may invalidate the performance of fault diagnosis. To address this challenge, a methodology for selecting the most reliable one among the different diagnostic results is proposed, which combines the Bayesian network (BN) and the information value (IV). The BN is trained for each regime and a conditional probability table is obtained for probabilistic fault diagnosis. The IV is then employed to evaluate the value of several diagnostic results. The proposed approach is applied to the fault diagnosis of a train door system and its effectiveness is proven.
Development of a Dental Implantable Temperature Sensor for Real-Time Diagnosis of Infectious Disease
Authors: Kim Jeffrey J. , Stafford Gery R. , Beauchamp Carlos , Kim Shin Ae
Published: July 2020

Implantable sensors capable of real-time measurements are powerful tools to diagnose disease and maintain health by providing continuous or regular biometric monitoring. In this paper, we present a dental implantable temperature sensor that can send early warning signals in real time before the implant fails. Using a microfabrication process on a flexible polyimide film, we successfully fabricated a multi-channel temperature sensor that can be wrapped around a dental implant abutment wing. In addition, the feasibility, durability, and implantability of the sensor were investigated. First, high linearity and repeatability between electrical resistance and temperature confirmed the feasibility of the sensor with a temperature coefficient of resistance (TCR) value of 3.33 × 10–3/°C between 20 and 100 °C. Second, constant TCR values and robust optical images without damage validated sufficient thermal, chemical, and mechanical durability in the sensor’s performance and structures. Lastly, the elastic response of the sensor’s flexible substrate film to thermal and humidity variations, simulating in the oral environment, suggested its successful long-term implantability. Based on these findings, we have successfully developed a polymer-based flexible temperature sensor for dental implant systems.
The Importance and Prospects of the Use of Algae in Agribusiness
Authors: Piwowar Arkadiusz , Harasym Joanna
Published: July 2020

Agribusiness could be the most promising sector for algae biomass exploitation and popularization. In this paper we summarize the scope of interests in agribusiness which can be fulfilled with algae exploitation. A high growth rate, a high ability to bind carbon dioxide and the potential to accumulate biogenic elements and light metals mean that algae can be used as a raw material for production of biofertilizers, biopesticides, feeds and feed additives. The use of the means of agricultural production based on algae can take place both in organic and conventional agriculture. The development of innovative and low-cost technologies of algae production, including the possibilities of their use in rural areas, provide a basis for changes, improvements and modifications to the existing solutions in the scope of production and use of industrial means of agricultural production. We also show that although there are quite diverse methods of production, and various micro and macro species diversified in chemical content, the economic viability of algae-based agribusiness is still in its infancy. The wide utilization of algae for food product manufacturing opens alternative ways for food acquisition, protecting both the food supply and the planet’s resources. The sustainability aspects of mass algae production implementation seem to be indisputable regarding possible benefits resulting from such technology. The versatility of algae application in food products, along with the very high nutritive and bioactive profile of this ingredient, make this resource of high importance in a low-emission economy.
Warming Increases Nitrous Oxide Emission from the Littoral Zone of Lake Poyang, China
Authors: Cheng Junxiang , Xu Ligang , Jiang Mingliang , Jiang Jiahu , Xu Yanxue
Published: July 2020

Littoral wetlands are globally important for sustainable development; however, they have recently been identified as critical hotspots of nitrous oxide (N2O) emissions. N2O flux from subtropical littoral wetlands remains unclear, especially under the current global warming environment. In the littoral zone of Lake Poyang, a simulated warming experiment was conducted to investigate N2O flux. Open-top chambers were used to raise temperature, and the static chamber-gas chromatograph method was used to measure N2O flux. Results showed that the littoral zone of Lake Poyang was an N2O source, with an average flux rate of 8.9 μg N2O m−2 h−1. Warming significantly increased N2O emission (13.8 μg N2O m−2 h−1 under warming treatment) by 54% compared to the control treatment. N2O flux in the spring growing season was also significantly higher than that of the autumn growing season. In addition, temperature was not significantly related to N2O flux, while soil moisture only explained about 7% of N2O variation. These results imply that N2O emission experiences positive feedback effect on the ongoing warming of the climate, and abiotic factors (e.g., soil temperature and soil moisture) were not main controls on N2O variation in this littoral wetland.
The Effect of Consumer Perception on Food Waste Behavior of Urban Households in China
Authors: Zhang Panpan , Zhang Dan , Cheng Shengkui
Published: July 2020

Food waste has become a global problem, causing widespread concern in all sectors of society. Many scholars and institutions have researched this issue from different perspectives, but theoretical and empirical research on food waste from the perspective of consumer perception is still limited. Therefore, this study constructs a theoretical framework based on food waste behavior of households and empirically analyzes the effect of consumer perception on food waste by 273 Chinese urban households eating at home. The reliable urban household food waste data are based on a combination of household questionnaire surveys, bookkeeping surveys, weighing surveys, and semi-structured interviews in 2018. The survey site is Zhengzhou City in Henan Province. The results show that the higher urban household consumer perception positive index, the smaller the amount of food waste per capita per meal, and the higher urban household consumer perception negative index, the greater the amount of food waste per capita per meal. These results suggest consumer perception affects urban household food waste behavior significantly. We need to encourage consumers to form a joint effort to change consumer perception about food waste in order to reducing food waste.
Energy Consumption Models at Urban Scale to Measure Energy Resilience
Authors: Mutani Guglielmina , Todeschi Valeria , Beltramino Simone
Published: July 2020

Energy resilience can be reached with a secure, sustainable, competitive, and affordable system. In order to achieve energy resilience in the urban environment, urban-scale energy models play a key role in supporting the promotion and identification of effective energy-efficient and low-carbon policies pertaining to buildings. In this work, a dynamic urban-scale energy model, based on an energy balance, has been designed to take into account the local climate conditions and morphological urban-scale parameters. The aim is to present an engineering methodology, applied to clusters of buildings, using the available urban databases. This methodology has been calibrated and optimized through an iterative procedure on 102 residential buildings in a district of the city of Turin (Italy). The results of this work show how a place-based dynamic energy balance methodology can also be sufficiently accurate at an urban scale with an average seasonal relative error of 14%. In particular, to achieve this accuracy, the model has been optimized by correcting the typological and geometrical characteristics of the buildings and the typologies of ventilation and heating system; in addition, the indoor temperatures of the buildings—that were initially estimated as constant—have been correlated to the climatic variables. The proposed model can be applied to other cities utilizing the existing databases or, being an engineering model, can be used to assess the impact of climate change or other scenarios.
Minimum Infective Dose of a Lumpy Skin Disease Virus Field Strain from North Macedonia
Authors: Wolff Janika , Krstevski Kiril , Beer Martin , Hoffmann Bernd
Published: July 2020

Infection with Lumpy Skin Disease virus (LSDV), as well as infections with other Capripox virus species, are described as the most severe pox diseases of production animals and are therefore listed as notifiable diseases under the guidelines of the World Organization for Animal Health (OIE). To our knowledge there is only a single study examining dose dependency, clinical course, viremia, virus shedding, as well as serological response following experimental LSDV “Neethling” inoculation. Here, we inoculated cattle with four different doses of LSDV strain “Macedonia2016”, a recently characterized virulent LSDV field strain, and examined clinical symptoms, viremia, viral shedding, and seroconversion. Interestingly, around 400 cell culture infectious dose50 (CCID50) of LSDV-“Macedonia2016” were sufficient to induce generalized Lumpy Skin Disease (LSD) in two out of six cattle but with a different incubation time, whereas the other animals of this group showed only a mild course of LSD. However, differences in incubation time, viral loads, serology, and in the clinical scoring could not be observed in the other three groups. In summary, we concluded that experimental LSDV infection of cattle with an infectious virus titer of 105 to 106 CCID50/mL of “Macedonia2016” provides a robust and sufficient challenge model for future studies.
Human Papillomavirus Vaccines: An Updated Review
Authors: Cheng Liqin , Wang Yan , Du Juan
Published: July 2020

Human papillomavirus (HPV) vaccines, which were introduced in many countries in the past decade, have shown promising results in decreasing HPV infection and related diseases, such as warts and precancerous lesions. In this review, we present the updated information about current HPV vaccines, focusing on vaccine coverage and efficacy. In addition, pan-gender vaccination and current clinical trials are also discussed. Currently, more efforts should be put into increasing the vaccine’s coverage, especially in low- and middle-income countries. Provision of education on HPV and vaccination is one of the most important methods to achieve this. Vaccines that target HPV types not included in current vaccines are the next stage in vaccine development. In the future, all HPV-related cancers, such as head and neck cancer, and anal cancer, should be tracked and evaluated, especially in countries that have introduced pan-gender vaccination programs. Therapeutic vaccines, in combination with other cancer treatments, should continue to be investigated.
Assessment of vertebral pathology of drivers of vehicles of industrial enterprises
Authors: Shaykhlislamova E. , Vagapova D. , Churmantayeva S. , Berg A.
Published: July 2020

One of the many professional groups employed in many sectors of the economy is truck drivers, whose work is characterized by a complex of adverse production factors, of which physical activity, vibration, adverse microclimate, intensity of work, as a rule, are the main reasons for the formation of diseases of the musculoskeletal system, including vertebrogenic pathology. According to the results of a polyclinic examination of male truck drivers employed at industrial enterprises of the Republic of Bashkortostan, 73.8 % have vertebral diseases of the cervical spine (cervicalgia/cervicobrachialgia) and 89.2 %. — of the lumbosacral one (lumbalgia/ lumbar ischialgia, radiculopathy). An increase in the length of service negatively affects the course of the disease, leading to an increase in the neurological deficit from the reflex stage in the group of people with a work experience of up to 9 years to the compression-radicular stage with an experience of more than 20 years. The data presented indicate the need to develop a set of targeted measures of sanitary-hygienic and medical-rehabilitation nature.
Recombinant cytokines in the treatment of pneumonia. Clinical experience
Authors: Egorova V. , Trofimov V.
Published: July 2020

The article presents experience and clinical and immunological effectiveness of the use of recombinant interleukin-2 (rIL-2) in the treatment and prevention of pneumonia in order to reduce the risk of pneumonia in cerebral strokes and severe exogenous poisoning. Accumulated clinical experience on the use of recombinant interleukin-2 in patients of various age groups indicates the validity and feasibility of including the drug in the basic therapy for severe pneumonia along with antimicrobial chemotherapy in order to normalize immunological parameters, improve clinical course of the disease, achieve timely and complete resolution of the inflammatory process.
Quality of laboratory tests as a basic component of treatment effectiveness
Authors: Silkina Tamara , Petrova Olga
Published: July 2020

The article presents analysis of modern laboratory technologies and requirements for the quality of laboratory tests in the Russian Federation. Basic rules that improve the quality of laboratory tests at the preanalytical, analytical and postanalytical stage are studied on the example of tests in the Laboratory Hemotest. The optimal list of laboratory tests used in the practice of a general practitioner and organizational options for performing laboratory tests, the features of the process that affect the speed of obtaining a result by a doctor in an outpatient setting and in hospital, are presented.
Degradabilidad in situ de la dieta seleccionada por la llama (Lama glama)
Authors: Ponce Quispe Wilson , Merlo Maydana Flavio Eudaldo
Published: July 2020

Por efectos de la degradación y baja producción de pastos naturales, se presume no se cubren los requerimientos nutricionales de la llama. El objetivo de la investigación fue evaluar la degradabilidad in situ de materia seca (DISMS), de proteína bruta (DISPB), fibra detergente neutra (DISFDN) y fibra detergente ácida (DISFDA), de la dieta seleccionada por llamas según meses y tiempos de incubación, en la comunidad Jila Huta Manasaya, Sajama Oruro. Se seleccionaron 4 llamas machos de 3 años de edad, tipo q´ara de 70 kg/llama; de tamas de la comunidad en los que fueron aplicadas mediante cirugía implante de cánulas en el primer compartimento (C1). Las muestras de ingesta colectada a nivel esofágica de llamas pastoreadas en pastizales naturales fueron secadas, molidas, almacenadas 3 g en bolsas Dacron de 1700 poros/cm2 no digeribles, luego incubadas en el C1 durante 0; 6; 12; 24; 36; 48; 72, y 96 horas en los meses de octubre, noviembre y diciembre. Las técnicas de análisis de laboratorio empleadas son el análisis proximal de Weende y análisis de Van Soest. Los datos fueron analizados con arreglo factorial 3*8 en diseño completamente al azar y las diferencias mediante la prueba de comparación de medias de Duncan. Los resultados obtenidos fue la degradabilidad in situ se da en un proceso y velocidad lento en el primer compartimento del estómago de llamas.
Reliability and Validity ofan Adapted QuestionnaireAssessing OccupationalExposures to HazardousChemicals among HealthCare Workers in Bhutan
Authors: Rai Rajni , El-Zaemey Sonia , Dorji Nidup , Fritschi Lin
Published: July 2020

Background: Collection of reliable and valid occupational history data is of utmost importanceto assess work-related exposures and their health effects. Few standardized questionnairesare available for the collection of occupational history data in low-and-middle incomecountries. Objective: To adapt and test a validated questionnaire developed in the United States by theNational Institute of Safety and Health, in order to assess occupational chemical exposuresamong health care workers in Bhutan. Methods: The questionnaire was first adapted to suit the Bhutanese context with the adviceof an expert review committee. 30 health care workers then completed the questionnaire atbaseline and 10–14 days later. Test-retest reliability was assessed by calculating Cohen's κand percentage agreement. Results: The questionnaire had high test-retest reliability. Cohen's κ ranged from 0.61 to1.00, and percentage agreement ranged from 86.7% to 100%. Further adaptations includedomitting questions on chemicals not available in Bhutan. Conclusion: The adapted questionnaire is appropriate for assessing occupational chemicalexposures among health care workers in Bhutan.
Assessment of Bone Turnover Biomarkers in Lead-Battery Workers with Long-Term Exposure to Lead
Authors: Ravibabu Kalahasthi , Barman Tapu , Bagepally Bhavani Shankara
Published: July 2020

Background: The major portion of lead in the body resides in skeletal system. The bone turnover affects the release of lead into the circulation from bones. The bone turnover biomarkers (BTM) in lead-battery workers with long-term exposure to lead have not been explored yet. Objective: To evaluate the BTM (formation and resorption) in lead-battery workers with long-term exposure to lead in lead-battery manufacturing plant. Methods: 176 male lead-exposed workers and 80 matched comparison group were studied. All participants were examined for blood lead levels (BLLs), bone formation biomarkers—serum osteocalcin (OC), alkaline phosphatase (ALP), bone-specific alkaline phosphatase (BALP)—and bone resorption biomarkers—serum pyridinoline (PYD), deoxypyridinoline (DPYD), tartarate-resistant acid phosphatase-5b (TRACP-5b), and urinary hydroxyproline (UHYP). Results: We found a significantly higher bone formation biomarkers such as BALP (p=0.007) and bone resorption biomarkers, eg, PYD (p=0.048), TRCAP-5b (p=0.001), and UHYP (p=0.001) in lead-exposed workers. A significant (p=0.041) negative correlation (ρ -0.128) was noted between BLLs and OC. A significant positive correlation was noted between BLLs and TRACP-5b (ρ 0.176, p=0.005) and UHYP (ρ 0.258, p=0.004). Serum OC (p=0.040) and UHYP (p=0.015) levels changed significantly with BLL level. Bone resorption biomarkers levels—PYD, TRACP-5b, and BALP—were higher among those with higher BLLs levels. The duration of exposure was significantly associated with BALP (p=0.037), DPYD (p=0.016), TRACP5b (p=0.001), and UHYP (p=0.002) levels. Conclusion: Long-term lead exposure affects the bone turnover.
Community-based pandemic preparedness: COVID-19 procedures of a Manitoba First Nation community
Authors: Kyoon-Achan Grace , Write Lynda
Published: July 2020

The COVID-19 pandemic has impacted the Canadian health, social and economic landscape beginning early in 2020. Efforts to stem the viral tide have called into cooperation international, federal, and provincial governments. These governments are drawing on public health and socio-economic measures to prevent outbreaks in some cases and reduce infections and death rates in others. First Nations are a seemingly peripheral part of the general response, with communities being served by Indigenous Services Canada, a federal government institution responsible for First Nations health care. A participant observation process enabled the reporting of the community’s steps in pandemic planning and preparation. We showcase the work being accomplished on the ground in Nisichawayasihk Cree Nation, a community in northern Manitoba. This includes strong local leadership, evidence-based planning and decision-making, pooling and coordinating resources, ongoing communication, traditional medicines and health approaches, planning for mental health supports, ensuring food security and general safety for community members. All levels of community-based leadership along with strong, measured and well-coordinated action are required to prevent the outbreak of viral infections in First Nation communities.
“She completely twisted the body language”: Pandemic, parody, politics, and comedy in the era of coronavirus
Authors: Ogbu Oluchi Gloria
Published: July 2020

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BOARD OF DIRECTORS EFFECTIVENESS CHALLENGE: AN INTROSPECTIVE ON THE GOVERNMENT LINK COMPANIES EXPERIENCE
Authors: Ishak Suraiya , Che Omar Ahmad Raflis
Published: July 2020

The Board of directors represents the essential pillar in the corporate governance system. The Board of directors exerts significant influence in corporate control through the control, service, and strategic roles. This article aims to identify factors that influence the effective function of the corporate boards based on the government link companies (GLCs) experience in Malaysia. This study utilizes an unobtrusive method, which employs publicly available secondary data. The data are obtained from the online publications hit through the keywords of the entity’s name. Two entities, which sparked controversies in Malaysia during the period of mid-2018 until early 2019 are referred to as the observed case for this study. The content analysis on the materials capture a few themes of challenges comprised of (1) patrimonialism within board structure; (2) appointment of individuals of non-expert; (3) exaggerate practices of cross-directorship among GLCs board; (4) dominance influence of chairman onboard activities; and (5) vague board decision-making process. The originality of this study lies in the process that optimizes the strength of the qualitative method to comprehend corporate governance challenges by incorporating a true scenario.