bluuebunny/crossref_metadata_2025 huggingface dataset:
MultiRPN-DIDNet: Multiple RPNs and Distance-IoU Discriminative Network for Real-Time UAV Target Tracking
Authors: Zhuo Li , Liu Bin , Zhang Hui , Zhang Shiyu , Li Jiafeng
Published: July 2021

Target tracking in low-altitude Unmanned Aerial Vehicle (UAV) videos faces many technical challenges due to the relatively small sizes, various orientation changes of the objects and diverse scenes. As a result, the tracking performance is still not satisfactory. In this paper, we propose a real-time single-target tracking method with multiple Region Proposal Networks (RPNs) and Distance-Intersection-over-Union (Distance-IoU) Discriminative Network (DIDNet), namely MultiRPN-DIDNet, in which ResNet50 is used as the backbone network for feature extraction. Firstly, an instance-based RPN suitable for the target tracking task is constructed under the framework of Simases Neural Network. RPN is to perform bounding box regression and classification, in which channel attention mechanism is integrated to improve the representative capability of the deep features. The RPNs built on the Block 2, Block 3 and Block 4 of ResNet50 output their own Regression (Reg) coefficients and Classification scores (Cls) respectively, which are weighted and then fused to determine the high-quality region proposals. Secondly, a DIDNet is designed to correct the candidate target’s bounding box finely through the fusion of multi-layer features, which is trained with the Distance-IoU loss. Experimental results on the public datasets of UAV20L and DTB70 show that, compared with the state-of-the-art UAV trackers, the proposed MultiRPN-DIDNet can obtain better tracking performance with fewer region proposals and correction iterations. As a result, the tracking speed has reached 33.9 frames per second (FPS), which can meet the requirements of real-time tracking tasks.
Measuring the Contribution of Leaves to the Structural Complexity of Urban Tree Crowns with Terrestrial Laser Scanning
Authors: Arseniou Georgios , MacFarlane David W. , Seidel Dominik
Published: July 2021

Trees have a fractal-like branching architecture that determines their structural complexity. We used terrestrial laser scanning technology to study the role of foliage in the structural complexity of urban trees. Forty-five trees of three deciduous species, Gleditsia triacanthos, Quercus macrocarpa, Metasequoia glyptostroboides, were sampled on the Michigan State University campus. We studied their structural complexity by calculating the box-dimension (Db) metric from point clouds generated for the trees using terrestrial laser scanning, during the leaf-on and -off conditions. Furthermore, we artificially defoliated the leaf-on point clouds by applying an algorithm that separates the foliage from the woody material of the trees, and then recalculated the Db metric. The Db of the leaf-on tree point clouds was significantly greater than the Db of the leaf-off point clouds across all species. Additionally, the leaf removal algorithm introduced bias to the estimation of the leaf-removed Db of the G. triacanthos and M. glyptostroboides trees. The index capturing the contribution of leaves to the structural complexity of the study trees (the ratio of the Db of the leaf-on point clouds divided by the Db of the leaf-off point clouds minus one), was negatively correlated with branch surface area and different metrics of the length of paths through the branch network of the trees, indicating that the contribution of leaves decreases as branch network complexity increases. Underestimation of the Db of the G. triacanthos trees, after the artificial leaf removal, was related to maximum branch order. These results enhance our understanding of tree structural complexity by disentangling the contribution of leaves from that of the woody structures. The study also highlighted important methodological considerations for studying tree structure, with and without leaves, from laser-derived point clouds.
Detection of Spatial and Temporal Patterns of Liana Infestation Using Satellite-Derived Imagery
Authors: Chandler Chris J. , van der Heijden Geertje M. F. , Boyd Doreen S. , Foody Giles M.
Published: July 2021

Lianas (woody vines) play a key role in tropical forest dynamics because of their strong influence on tree growth, mortality and regeneration. Assessing liana infestation over large areas is critical to understand the factors that drive their spatial distribution and to monitor change over time. However, it currently remains unclear whether satellite-based imagery can be used to detect liana infestation across closed-canopy forests and therefore if satellite-observed changes in liana infestation can be detected over time and in response to climatic conditions. Here, we aim to determine the efficacy of satellite-based remote sensing for the detection of spatial and temporal patterns of liana infestation across a primary and selectively logged aseasonal forest in Sabah, Borneo. We used predicted liana infestation derived from airborne hyperspectral data to train a neural network classification for prediction across four Sentinel-2 satellite-based images from 2016 to 2019. Our results showed that liana infestation was positively related to an increase in Greenness Index (GI), a simple metric relating to the amount of photosynthetically active green leaves. Furthermore, this relationship was observed in different forest types and during (2016), as well as after (2017–2019), an El Niño-induced drought. Using a neural network classification, we assessed liana infestation over time and showed an increase in the percentage of severely (>75%) liana infested pixels from 12.9% ± 0.63 (95% CI) in 2016 to 17.3% ± 2 in 2019. This implies that reports of increasing liana abundance may be more wide-spread than currently assumed. This is the first study to show that liana infestation can be accurately detected across closed-canopy tropical forests using satellite-based imagery. Furthermore, the detection of liana infestation during both dry and wet years and across forest types suggests this method should be broadly applicable across tropical forests. This work therefore advances our ability to explore the drivers responsible for patterns of liana infestation at multiple spatial and temporal scales and to quantify liana-induced impacts on carbon dynamics in tropical forests globally.
Dependence of CWSI-Based Plant Water Stress Estimation with Diurnal Acquisition Times in a Nectarine Orchard
Authors: Park Suyoung , Ryu Dongryeol , Fuentes Sigfredo , Chung Hoam , O’Connell Mark , Kim Junchul
Published: July 2021

Unmanned aerial vehicle (UAV) remote sensing has become a readily usable tool for agricultural water management with high temporal and spatial resolutions. UAV-borne thermography can monitor crop water status near real-time, which enables precise irrigation scheduling based on an accurate decision-making strategy. The crop water stress index (CWSI) is a widely adopted indicator of plant water stress for irrigation management practices; however, dependence of its efficacy on data acquisition time during the daytime is yet to be investigated rigorously. In this paper, plant water stress captured by a series of UAV remote sensing campaigns at different times of the day (9h, 12h and 15h) in a nectarine orchard were analyzed to examine the diurnal behavior of plant water stress represented by the CWSI against measured plant physiological parameters. CWSI values were derived using a probability modelling, named ‘Adaptive CWSI’, proposed by our earlier research. The plant physiological parameters, such as stem water potential (ψstem) and stomatal conductance (gs), were measured on plants for validation concurrently with the flights under different irrigation regimes (0, 20, 40 and 100 % of ETc). Estimated diurnal CWSIs were compared with plant-based parameters at different data acquisition times of the day. Results showed a strong relationship between ψstem measurements and the CWSIs at midday (12 h) with a high coefficient of determination (R2 = 0.83). Diurnal CWSIs showed a significant R2 to gs over different levels of irrigation at three different times of the day with R2 = 0.92 (9h), 0.77 (12h) and 0.86 (15h), respectively. The adaptive CWSI method used showed a robust capability to estimate plant water stress levels even with the small range of changes presented in the morning. Results of this work indicate that CWSI values collected by UAV-borne thermography between mid-morning and mid-afternoon can be used to map plant water stress with a consistent efficacy. This has important implications for extending the time-window of UAV-borne thermography (and subsequent areal coverage) for accurate plant water stress mapping beyond midday.
Review of Capacitive Touchscreen Technologies: Overview, Research Trends, and Machine Learning Approaches
Authors: Nam Hyoungsik , Seol Ki-Hyuk , Lee Junhee , Cho Hyeonseong , Jung Sang Won
Published: July 2021

Touchscreens have been studied and developed for a long time to provide user-friendly and intuitive interfaces on displays. This paper describes the touchscreen technologies in four categories of resistive, capacitive, acoustic wave, and optical methods. Then, it addresses the main studies of SNR improvement and stylus support on the capacitive touchscreens that have been widely adopted in most consumer electronics such as smartphones, tablet PCs, and notebook PCs. In addition, the machine learning approaches for capacitive touchscreens are explained in four applications of user identification/authentication, gesture detection, accuracy improvement, and input discrimination.
Temporal Alignment of Dual Monitor Accelerometry Recordings
Authors: Brønd Jan Christian , Pedersen Natascha Holbæk , Larsen Kristian Traberg , Grøntved Anders
Published: July 2021

Combining accelerometry from multiple independent activity monitors worn by the same subject have gained widespread interest with the assessment of physical activity behavior. However, a difference in the real time clock accuracy of the activity monitor introduces a substantial temporal misalignment with long duration recordings which is commonly not considered. In this study, a novel method not requiring human interaction is described for the temporal alignment of triaxial acceleration measured with two independent activity monitors and evaluating the performance with the misalignment manually identified. The method was evaluated with free-living recordings using both combined wrist/hip (n = 9) and thigh/hip device (n = 30) wear locations, and descriptive data on initial offset and accumulated day 7 drift in a large-scale population-based study (n = 2513) were calculated. The results from the Bland–Altman analysis show good agreement between the proposed algorithm and the reference suggesting that the described method is valid for reducing the temporal misalignment and thus reduce the measurement error with aggregated data. Applying the algorithm to the n = 2513 samples worn for 7-days suggest a wide and substantial issue with drift over time when each subject wears two independent activity monitors.
An Approximation for Metal-Oxide Sensor Calibration for Air Quality Monitoring Using Multivariable Statistical Analysis
Authors: Sales-Lérida Diego , Bello Alfonso J. , Sánchez-Alzola Alberto , Martínez-Jiménez Pedro Manuel
Published: July 2021

Good air quality is essential for both human beings and the environment in general. The three most harmful air pollutants are nitrogen dioxide (NO2), ozone (O3) and particulate matter. Due to the high cost of monitoring stations, few examples of this type of infrastructure exist, and the use of low-cost sensors could help in air quality monitoring. The cost of metal-oxide sensors (MOS) is usually below EUR 10 and they maintain small dimensions, but their use in air quality monitoring is only valid through an exhaustive calibration process and subsequent precision analysis. We present an on-field calibration technique, based on the least squares method, to fit regression models for low-cost MOS sensors, one that has two main advantages: it can be easily applied by non-expert operators, and it can be used even with only a small amount of calibration data. In addition, the proposed method is adaptive, and the calibration can be refined as more data becomes available. We apply and evaluate the technique with a real dataset from a particular area in the south of Spain (Granada city). The evaluation results show that, despite the simplicity of the technique and the low quantity of data, the accuracy obtained with the low-cost MOS sensors is high enough to be used for air quality monitoring.
Negative Index Metamaterial Lens for Subwavelength Microwave Detection
Authors: Datta Srijan , Mukherjee Saptarshi , Shi Xiaodong , Haq Mahmood , Deng Yiming , Udpa Lalita , Rothwell Edward
Published: July 2021

Metamaterials are engineered periodic structures designed to have unique properties not encountered in naturally occurring materials. One such unusual property of metamaterials is the ability to exhibit negative refractive index over a prescribed range of frequencies. A lens made of negative refractive index metamaterials can achieve resolution beyond the diffraction limit. This paper presents the design of a metamaterial lens and its use in far-field microwave imaging for subwavelength defect detection in nondestructive evaluation (NDE). Theoretical formulation and numerical studies of the metamaterial lens design are presented followed by experimental demonstration and characterization of metamaterial behavior. Finally, a microwave homodyne receiver-based system is used in conjunction with the metamaterial lens to develop a far-field microwave NDE sensor system. A subwavelength focal spot of size 0.82λ was obtained. The system is shown to be sensitive to a defect of size 0.17λ × 0.06λ in a Teflon sample. Consecutive positions of the defect with a separation of 0.23λ was resolvable using the proposed system.
Design and Analysis of Electrodes for Electrostimulation (TENS) Using the Technique of Film Printing and Embroidery in Textiles
Authors: Skrzetuska Ewa , Michalak Daria , Krucińska Izabella
Published: July 2021

This article describes the development of transcutaneous nerve stimulating electrodes (TENS) by means of electrically conductive ink and conductive yarn. The scope of work covered a selection of three types of knitwear with a similar surface weight with different raw material composition. Stimulating electrodes were made by means of film printing and machine embroidery. The electrodes were verified after friction tests, washing, and mechanical deformation. Each process was followed by a check of the resistive properties and assessment of the sensations in order to evaluate their performance. Tests of the surface resistance of research materials confirmed the possibility of preparing textile electrodes for electrostimulation with the use of the film-printing technique and machine embroidery. Resistance of the electrodes made on all types of substrates ranged from approximately 1.00 × 10−2 Ω to around 2.00 × 102 Ω, while the electrodes are commercially available at the level of approximately 3.5 × 105 Ω. This paper underpins the validation of the conclusion that operational processes do not adversely affect the functioning of the developed textile electrodes.
Ultrasonic Propagation in Liquid and Ice Water Drops. Effect of Porosity
Authors: Mendonck Michiel , Aparicio Sofía , González Díaz Cristóbal , Hernández Margarita G. , Muñoz Caro Guillermo M. , Anaya José Javier , Cazaux Stéphanie
Published: July 2021

This work studies ultrasonic propagation in liquid and ice water drops. The effect of porosity on attenuation of ultrasonic waves in the drops is also explored. The motivation of this research was the possible application of ultrasonic techniques to the study of interstellar and cometary ice analogs. These ice analogs, made by vapor deposition onto a cold substrate at 10 K, can display high porosity values up to 40%. We found that the ultrasonic pulse was fully attenuated in such ice, and decided to grow ice samples by freezing a liquid drop. Several experiments were performed using liquid or frozen water drops with and without pores. An ultrasonic pulse was transmitted through each drop and measured. This method served to estimate the ultrasonic velocity of each drop by measuring drop size and time-of-flight of ultrasonic transmission. Propagation of ultrasonic waves in these drops was also simulated numerically using the SimNDT program developed by the authors. After that, the ultrasonic velocity was related with the porosity using a micromechanical model. It was found that a low value of porosity in the ice is sufficient to attenuate the ultrasonic propagation. This explains the observed lack of transmission in porous astrophysical ice analogs.
Weakly Supervised Crop Area Segmentation for an Autonomous Combine Harvester
Authors: Kim Wan-Soo , Lee Dae-Hyun , Kim Taehyeong , Kim Hyunggun , Sim Taeyong , Kim Yong-Joo
Published: July 2021

Machine vision with deep learning is a promising type of automatic visual perception for detecting and segmenting an object effectively; however, the scarcity of labelled datasets in agricultural fields prevents the application of deep learning to agriculture. For this reason, this study proposes weakly supervised crop area segmentation (WSCAS) to identify the uncut crop area efficiently for path guidance. Weakly supervised learning has advantage for training models because it entails less laborious annotation. The proposed method trains the classification model using area-specific images so that the target area can be segmented from the input image based on implicitly learned localization. This way makes the model implementation easy even with a small data scale. The performance of the proposed method was evaluated using recorded video frames that were then compared with previous deep-learning-based segmentation methods. The results showed that the proposed method can be conducted with the lowest inference time and that the crop area can be localized with an intersection over union of approximately 0.94. Additionally, the uncut crop edge could be detected for practical use based on the segmentation results with post-image processing such as with a Canny edge detector and Hough transformation. The proposed method showed the significant ability of using automatic perception in agricultural navigation to infer the crop area with real-time level speed and have localization comparable to existing semantic segmentation methods. It is expected that our method will be used as essential tool for the automatic path guidance system of a combine harvester.
Lidar–Camera Semi-Supervised Learning for Semantic Segmentation
Authors: Caltagirone Luca , Bellone Mauro , Svensson Lennart , Wahde Mattias , Sell Raivo
Published: July 2021

In this work, we investigated two issues: (1) How the fusion of lidar and camera data can improve semantic segmentation performance compared with the individual sensor modalities in a supervised learning context; and (2) How fusion can also be leveraged for semi-supervised learning in order to further improve performance and to adapt to new domains without requiring any additional labelled data. A comparative study was carried out by providing an experimental evaluation on networks trained in different setups using various scenarios from sunny days to rainy night scenes. The networks were tested for challenging, and less common, scenarios where cameras or lidars individually would not provide a reliable prediction. Our results suggest that semi-supervised learning and fusion techniques increase the overall performance of the network in challenging scenarios using less data annotations.
Rapid and Sensitive Inhibitor Screening Using Magnetically Modulated Biosensors
Authors: Roth Shira , Danielli Amos
Published: July 2021

Inhibitor screening is an important tool for drug development, especially during the COVID-19 pandemic. The most used in vitro inhibitor screening tool is an enzyme-linked immunosorbent assay (ELISA). However, ELISA-based inhibitor screening is time consuming and has a limited dynamic range. Using fluorescently and magnetically modulated biosensors (MMB), we developed a rapid and sensitive inhibitor screening tool. This study demonstrates its performance by screening small molecules and neutralizing antibodies as potential inhibitors of the interaction between the spike protein 1 (S1) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the angiotensin-converting enzyme 2 (ACE2) receptor. The MMB-based assay is highly sensitive, has minimal non-specific binding, and is much faster than the commonly used ELISA (2 h vs. 7–24 h). We anticipate that our method will lead to a remarkable advance in screening for new drug candidates.
Micro, Small, and Medium Enterprises’ Business Vulnerability Cluster in Indonesia: An Analysis Using Optimized Fuzzy Geodemographic Clustering
Authors: Caraka Rezzy Eko , Kurniawan Robert , Nasution Bahrul Ilmi , Jamilatuzzahro Jamilatuzzahro , Gio Prana Ugiana , Basyuni Mohammad , Pardamean Bens
Published: July 2021

The COVID-19 pandemic has caused effects in many sectors, including in businesses and enterprises. The most vulnerable businesses to COVID-19 are micro, small, and medium enterprises (MSMEs). Therefore, this paper aims to analyze the business vulnerability of MSMEs in Indonesia using the fuzzy spatial clustering approach. The fuzzy spatial clustering approach had been implemented to analyze the social vulnerability to natural hazards in Indonesia. Moreover, this study proposes the Flower Pollination Algorithm (FPA) to optimize the Fuzzy Geographically Weighted Clustering (FGWC) in order to cluster the business vulnerability in Indonesia. We performed the data analysis with the dataset from Indonesia’s national socioeconomic and labor force survey (SUSENAS and SAKERNAS). We first compared the performance of FPA with traditional FGWC, as well as several known optimization algorithms in FGWC such as Artificial Bee Colony, Intelligent Firefly Algorithm, Particle Swarm Optimization, and Gravitational Search Algorithm. Our results showed that FPAFGWC has the best performance in optimizing the FGWC clustering result in the business vulnerability context. We found that almost all of the regions in Indonesia outside Java Island have vulnerable businesses. Meanwhile, in most of Java Island, particularly the JABODETABEK area that is the national economic backbone, businesses are not vulnerable. Based on the results of the study, we provide the recommendation to handle the gap between the number of micro and small enterprises (MSMEs) in Indonesia.
Fragility Analyses of Bridge Structures Using the Logarithmic Piecewise Function-Based Probabilistic Seismic Demand Model
Authors: Zhao Yinghao , Hu Hesong , Bai Lunhua , Tang Mengxiong , Chen Hang , Su Dingli
Published: July 2021

Seismic fragility analysis is an efficient method to evaluate the structural failure probability during earthquake events. Among the existing fragility analysis methods, the probabilistic seismic demand model (PSDM) and the joint probabilistic seismic demand model (JPSDM) are generally used to compute the component and system fragility, respectively. However, the statistical significance behind the parameters related to the current PSDM and JPSDM are not comparable. Aside from that, when calculating the system fragility, the Monte Carlo sampling (MCS) method is time-consuming. To solve the two flaws, in this paper, the logarithm piecewise functions were used to generate the PSDM and the JPSDM, and the MCS was replaced by the univariate conditioning approximation (UCA) method. The concepts and application procedures of the proposed fragility analysis methods were elaborated first. Then, the UCA method was illustrated in detail. Finally, fragility curves of a steel arch truss case study bridge were generated by the proposed method. The research results indicate the following: (1) the proposed methods unify the data sources and statistical significance of the parameters used in the PSDM and the JPSDM; (2) the logarithmic piecewise function-based PSDM sensitively reflects the changing trend of the component’s demand with the fluctuation of the seismic intensity measure; (3) under transverse seismic waves, major injuries happen on the side bearings of the bridge, while slight damage may occur on each pier, and as the seismic intensity measure increases, the side bearings are more likely to be damaged; (4) for the severe damage and the absolute damage of the studied bridge, the system fragility curves are closer to the upper failure bounds; and (5) compared with the MSC method, the accuracy of the UCA method can be guaranteed with less calculation time.
Assessment of Ionomic, Phenolic and Flavonoid Compounds for a Sustainable Management of Xylella fastidiosa in Morocco
Authors: El Handi Kaoutar , Hafidi Majida , Habbadi Khaoula , El Moujabber Maroun , Ouzine Mohamed , Benbouazza Abdellatif , Sabri Miloud , Achbani El Hassan
Published: July 2021

Morocco belongs to the countries ranked at a high-risk level for entry, establishment, and spread of Xylella fastidiosa, which has recently re-emerged as a plant pathogen of global importance causing olive quick decline syndrome (OQDS). Symptomatic infection by X. fastidiosa leads to devastating diseases and important economic losses. To prevent such losses and damages, countries without current outbreaks like Morocco need to first understand their host plant responses to X. fastidiosa. The assessment of the macro and micro-elements content (ionome) in leaves can give basic and useful information along with being a powerful tool for the sustainable management of diseases caused by this devastating pathogen. Herein, we compare the leaf ionome of four important autochthonous Moroccan olive cultivars (‘Picholine Marocaine’, ‘Haouzia’, ‘Menara’, and ‘Meslalla’), and eight Mediterranean varieties introduced in Morocco (‘Arbequina’, ‘Arbosana’, ‘Leccino’, ‘Ogliarola salentina’, ‘Cellina di Nardo’, ‘Frantoio’, ‘Leucocarpa’, and ‘Picholine de Languedoc’), to develop hypotheses related to the resistance or susceptibility of the Moroccan olive trees to X. fastidiosa infection. Leaf ionomes, mainly Ca, Cu, Fe, Mg, Mn, Na, Zn, and P, were determined using inductively coupled plasma optical emission spectroscopy (ICP-OES). These varieties were also screened for their total phenolics and flavonoids content. Data were then involved in a comparative scheme to determine the plasticity of the pathogen. Our results showed that the varieties ‘Leccino’, ’Arbosana’, ‘Arbequina’ consistently contained higher Mn, Cu, and Zn and lower Ca and Na levels compared with the higher pathogen-sensitive ‘Ogliarola salentina’ and ‘Cellina di Nardò’. Our findings suggest that ‘Arbozana’, ‘Arbiquina’, ‘Menara’, and ‘Haouzia’ may tolerate the infection by X. fastidiosa to varying degrees, provides additional support for ‘Leccino’ having resistance to X. fastidiosa, and suggests that both ‘Ogliarola salentina’ and ‘Cellina di Nardö’ are likely sensitive to X. fastidiosa infection.
Food Connects Washington DC in 2050—A Vision for Urban Food Systems as the Centerpieces of a Circular Economy
Authors: Stuiver Marian , O’Hara Sabine
Published: July 2021

This article presents a vision for an urban food system in Washington DC in 2050 that serves as the centerpiece of a circular economy for the capital region of the United States. Food serves as the connecting link for an inclusive, adaptive, and resilient urban economy embedded in the region. This food economy values natural resources, cultural diversity, and commitment to nature-based innovations. The vision is the result of a three-pronged methodology of: (1) community engagement; (2) a thoughtful, process-focused transformation; and (3) the scaling up of existing urban food initiatives. We argue that small, hyperlocal, neighborhood-based initiatives can become crucial game changers and catalysts of change for entire neighborhoods, cities, and regions. Therefore, we propose a design-based approach to advance our 2050 vision of a circular food system. Our design-based approach consists of three building blocks: (A) systems thinking; (B) the ability to manage wins and tradeoffs; and (C) transitional leadership and cooperation. We explain these building blocks and the way in which they are incorporated in the 2050 vision of Washington DC. We further argue that the food economy is an ideal sector to embark on such a design-based approach due to its systemic nature, its critical position as an indispensable economic sector, and the complex connections it brings to multiple other sectors of the economy. An urban food system can therefore offer the ideal starting point for a transition towards a circular economy.
Supplying Personal Protective Equipment to Intensive Care Units during the COVID-19 Outbreak in Colombia. A Simheuristic Approach Based on the Location-Routing Problem
Authors: Martínez-Reyes Andrés , Quintero-Araújo Carlos L. , Solano-Charris Elyn L.
Published: July 2021

The coronavirus disease 2019, known as COVID-19, has generated an imminent necessity for personal protective equipment (PPE) that became essential for all populations and much more for health centers, clinics, hospitals, and intensive care units (ICUs). Considering this fact, one of the main issues for cities’ governments is the distribution of PPE to ICUs to ensure the protection of medical personnel and, therefore, the sustainability of the health system. Aware of this challenge, in this paper, we propose a simheuristic approach for supplying personal protective equipment to intensive care units which is based on the location-routing problem (LRP). The objective is to provide decision makers with a decision support tool that considers uncertain demands, distribution cost, and reliability in the solutions. To validate our approach, a case study in Bogotá, Colombia was analyzed. Computational results show the efficiency of the usage of alternative safety stock policies to face demand uncertainty in terms of both expected stochastic costs and reliabilities.
Digitally-Enabled Crop Disorder Management Process Based on Farmer Empowerment for Improved Outcomes: A Case Study from Sri Lanka
Authors: Sivagnanasundaram Janagan , Goonetillake Jeevani , Buhary Rifana , Dharmawardhana Thushara , Weerakkody Renuka , Gunapala Rukmali , Ginige Athula
Published: July 2021

We have developed a system facilitated by a mobile artefact to effectively identify crop disorder incidents and manage them using recommended control measures. This work overcomes the limitations of the existing attempts by using digital technology to empower farmers to identify crop disorders rather than replace them with automated techniques. Our approach empowers farmers by providing the information in context for them to identify crop disorders. The developed solution can identify most of the crop disorders instantaneously, irrespective of the crop or other factors that make crop disorder identification complicated. For the rest, it provides a mechanism to carry out a manual identification with the help of subject experts. The solution was deployed among paddy farmers in Sri Lanka to understand how well this could assist them in identifying and managing crop disorders. The system was able to identify 70.8% of the crop disorder incidents reported by the farmers and provided them with the relevant control measures. Farmers’ perceptions of various usability aspects of the solution revealed that the application of agrochemicals and expenses associated with agrochemicals were significantly reduced. It was also observed that the yield quality and quantity and overall revenue have increased compared to the previous seasons.
Life Cycle Assessment of Nitrogen Circular Economy-Based NOx Treatment Technology
Authors: Xue Mianqiang , Lin Bin-Le , Tsunemi Kiyotaka , Minami Kimitaka , Nanba Tetsuya , Kawamoto Tohru
Published: July 2021

Humans are significantly perturbing the global nitrogen cycle, leading to excess reactive nitrogen in the environment. Nitrogen oxides as a key reactive nitrogen species are mainly controlled by selective non-catalytic reduction and selective catalytic reduction. Converting nitrogen oxides to ammonia, defined as ReNOx, emerges as an alternative method under a disparate design concept. However, little is known about its overall environmental performance. In this study, we conducted for the first time a life cycle assessment of ReNOx. Compared with the eco-index in the condition of 200 °C with a conversion rate of 95%, it would increase substantially in the condition of 160 °C with a conversion rate of 80% and in the case without a sound NH3 treatment. Feedstock format change, adsorption material performance deterioration, and recovery rate decline would increase the eco-index by 8%, 12%, and 18%, respectively. The eco-index was decreased by 31% in the optimized scenario with a renewable energy source and an increased conversion rate. The environmental impacts were compared with traditional methods at impact, damage, and eco-index levels. Finally, the implications on process arrangement in the flue gas system, the externality for power generation, and the contribution to the nitrogen circular economy were examined. The results can serve as a reference for its developers to improve the technology from the environmental perspective.
Construction Schedule Risk Assessment and Management Strategy for Foreign General Contractors Working in the Ethiopian Construction Industry
Authors: Cheng Min-Yuan , Darsa Mohammadzen Hasan
Published: July 2021

Construction project schedule delay is a worldwide concern and especially severe in the Ethiopian construction industry. This study developed a Construction Schedule Risk Assessment Model (CSRAM) and a management strategy for foreign general contractors (FGCs). 94 construction projects with schedule delay were collected and a questionnaire survey of 75 domain experts was conducted to systematically select 22 risk factors. In CSRAM, the artificial neural network (ANN) inference model was developed to predict the project schedule delay. Integrating it with the Garson algorithm (GA), the relative weights of risk factors with rankings were calculated and identified. For comparison, the Relative Importance Index (RII) method was also applied to rank the risk factors. Management strategies were developed to improve the three highest-ranked factors identified using the GA (change order, corruption/bribery, and delay in payment), and the RII (poor resource management, corruption/bribery, and delay in material delivery). Moreover, the improvement results were used as inputs for the trained ANN to conduct a sensitivity analysis. The findings of this study indicate that improvements in the factors that considerably affect the construction schedule can significantly reduce construction schedule delays. This study acts as an important reference for FGCs who plan to enter or work in the Ethiopian construction industry.
Peat Land Oil Palm Farmers’ Direct and Indirect Benefits from Good Agriculture Practices
Authors: Awang Abd Hair , Rela Iskandar Zainuddin , Abas Azlan , Johari Mohamad Arfan , Marzuki Mohammad Effendi , Mohd Faudzi Mohd Noor Ramdan , Musa Adri
Published: July 2021

With economically unsustainable metroxylon sagu (sago palms) found in peat lands, small scale farmers are gradually converting their land to oil palm cultivation. Good agriculture practices (GAP) were inculcated to peat land farmers to ensure that the environmental ecosystem is conserved and oil palm productivity is enhanced, along with the farmer’s well-being. The present study examined the effect of GAP on farm performance and the perceived economic well-being of the peat land oil palm farmers. We interviewed randomly selected farmers with assistance from a locally trained native enumerator to complete the survey questionnaire. We conducted partial least square structural equation modeling (PLS-SEM) to incorporate direct and indirect benefits on farmers’ economic well-being to estimate the significance of GAP. The empirical results show that GAP have direct positive effects on farm performance. Such practices lead to significant positive impacts on the economic well-being of peat land oil palm farmers. This solid evidence makes it much easier for small-scale farmers to convert from conventional farming to environmentally friendly farming, and ensures safe and healthy oil palm cultivation.
Stimulation of Employees’ Green Creativity through Green Transformational Leadership and Management Initiatives
Authors: Mansoor Adil , Farrukh Muhammad , Lee Jong-Keon , Jahan Sarwat
Published: July 2021

Drawing upon the componential theory of creativity and social information processing theory, this research elucidates how and why the synergy of green HR practices and green strategies stimulate green creativity. It also explores the possible mediation effect of green transformational leadership (TFL) on the relationship between organizational interventions and green creativity. Survey questionnaires were used to collect data from managers working in large manufacturing firms. The structural equation modeling technique was applied to test the hypothesized relationships. Findings of research revealed that green management initiatives and green TFL stimulate green creativity. Moreover, the intervening impact of green TFL on the relationship between the aforementioned relationships was also established. Policymakers should devise green strategies and provide support to green HR practices for the stimulation of green creativity, whereas HR managers must ensure the compatibility of HR functions with corresponding organizational green strategies. Employees involved in green creative behaviors should be rewarded and retained. Training must be provided in order to keep employees abreast of the latest practices for environment conservation. Furthermore, managers should exhibit a green TFL style to advance green management initiatives and fuel green creativity among employees. This study highlights the significance of the synergy between green HR practices and the firm’s green strategies to stimulate employees’ green creativity. Furthermore, green management initiatives were also found to be the contextual precursor of green TFL, which enhances our understanding of the green TFL style. Lastly, the mediation effect of green TFL implies that it can serve as a proximal HR outcome to implement the organizational green agenda.
Evaluation of Suitable Mixture of Water and Air for Processing Tomato in Drip Irrigation in Xinjiang Oasis
Authors: Wei Chilin , Zhu Yan , Zhang Jinzhu , Wang Zhenhua
Published: July 2021

Aerated irrigation (AI) has emerged as a method to mitigate rhizosphere hypoxia caused by wetting front with sub-surface drip irrigation (SDI). Increasing oxygen in processing tomato’s root zone is beneficial to the improvement of the rhizosphere gas environment, crop growth, yield and quality. The relationship between aerated irrigation and irrigation quantity is not clear. A total of eight treatments, including four irrigation levels (4950 m3 hm−2 (W1), 4750 m3 hm−2 (W2), 4500 m3 hm−2 (W3), 4050 m3 hm−2 (W4)) in combination with aerated irrigation (A2) and non-aerated irrigation (A1) were used to investigate the effects of aerated irrigation on the physiological characteristics and yield of processing tomatoes under mulched drip irrigation in Xinjiang, China. The effects of aerated irrigation on plant height, stem diameter, leaf area index and dry matter, photosynthesis, fluorescence, fruit quality and yield of processing tomatoes were studied. The results showed that plant height, stem diameter, biomass accumulation and leaf area index of processing tomatoes under aerated irrigation were increased by 10.2%, 7.3%, 12.5% and 6.2% under the W1, W2, W3 and W4 conditions (p < 0.05), respectively, compared with non-aerated irrigation. Yield and the content of Vitamin C and soluble solids under aerated irrigation was 9.71%, 5.59% and 5.68% (p < 0.05) higher than that under conventional irrigation, respectively, and the sugar-acid under aerated irrigation decreased by 0.5%. Through principal component analysis, W2A2 treatment had a higher score according to the yield index (per fruit weight, fruit number per plant) and quality index (Vitamin C, soluble solids, sugar-acid ratio) than the other treatments. The results show that aerated irrigation is feasible under the existing mulched drip irrigation in Xinjiang and, in this experiment, W2A2 treatment was the most suitable planting mode.
Electroweak Effects in e+e−→ZH Process
Authors: Arbuzov Andrej , Bondarenko Serge , Kalinovskaya Lidia , Sadykov Renat , Yermolchyk Vitaly
Published: July 2021

Electroweak radiative corrections to the cross-section of the process e+e−→ZH are considered. The complete one-loop electroweak radiative corrections are evaluated with the help of the SANC system. Higher-order contributions of the initial-state radiation are computed in the QED structure function formalism. Numerical results are produced by a new version of the ReneSANCe event generator and MCSANCee integrator for the conditions of future electron-positron colliders. The resulting theoretical uncertainty in the description of this process is estimated.
Firewall from Effective Field Theory
Authors: Ho Pei-Ming , Yokokura Yuki
Published: July 2021

For an effective field theory in the background of an evaporating black hole with spherical symmetry, we consider non-renormalizable interactions and their relevance to physical effects. The background geometry is determined by the semi-classical Einstein equation for an uneventful horizon where the vacuum energy–momentum tensor is small for freely falling observers. Surprisingly, after Hawking radiation appears, the transition amplitude from the Unruh vacuum to certain multi-particle states grows exponentially with time for a class of higher-derivative operators after the collapsing matter enters the near-horizon region, despite the absence of large curvature invariants. Within the scrambling time, the uneventful horizon transitions towards a firewall, and eventually the effective field theory breaks down.
Chk1 and the Host Cell DNA Damage Response as a Potential Antiviral Target in BK Polyomavirus Infection
Authors: Hainley Lydia E. , Hughson Martina S. , Narendran Amithi , Smith Ralph , Arthur Justin , Hayner-Buchan Alida , Conti David J. , Lehman John M. , Friedrich Thomas D.
Published: July 2021

The human BK polyomavirus (BKPyV) is latent in the kidneys of most adults, but can be reactivated in immunosuppressed states, such as following renal transplantation. If left unchecked, BK polyomavirus nephropathy (PyVAN) and possible graft loss may result from viral destruction of tubular epithelial cells and interstitial fibrosis. When coupled with regular post-transplant screening, immunosuppression reduction has been effective in limiting BKPyV viremia and the development of PyVAN. Antiviral drugs that are safe and effective in combating BKPyV have not been identified but would be a benefit in complementing or replacing immunosuppression reduction. The present study explores inhibition of the host DNA damage response (DDR) as an antiviral strategy. Immunohistochemical and immunofluorescent analyses of PyVAN biopsies provide evidence for stimulation of a DDR in vivo. DDR pathways were also stimulated in vitro following BKPyV infection of low-passage human renal proximal tubule epithelial cells. The role of Chk1, a protein kinase known to be involved in the replication stress-induced DDR, was examined by inhibition with the small molecule LY2603618 and by siRNA-mediated knockdown. Inhibition of Chk1 resulted in decreased replication of BKPyV DNA and viral spread. Activation of mitotic pathways was associated with the reduction in BKPyV replication. Chk1 inhibitors that are found to be safe and effective in clinical trials for cancer should also be evaluated for antiviral activity against BKPyV.
Mathematical Modelling of the Molecular Mechanisms of Interaction of Tenofovir with Emtricitabine against HIV
Authors: Iannuzzi Sara , von Kleist Max
Published: July 2021

The combination of the two nucleoside reverse transcriptase inhibitors (NRTI) tenofovir disoproxil fumarate (TDF) and emtricitabine (FTC) is used in most highly active antiretroviral therapies for treatment of HIV-1 infection, as well as in pre-exposure prophylaxis against HIV acquisition. Administered as prodrugs, these drugs are taken up by HIV-infected target cells, undergo intracellular phosphorylation and compete with natural deoxynucleoside triphosphates (dNTP) for incorporation into nascent viral DNA during reverse transcription. Once incorporated, they halt reverse transcription. In vitro studies have proposed that TDF and FTC act synergistically within an HIV-infected cell. However, it is unclear whether, and which, direct drug–drug interactions mediate the apparent synergy. The goal of this work was to refine a mechanistic model for the molecular mechanism of action (MMOA) of nucleoside analogues in order to analyse whether putative direct interactions may account for the in vitro observed synergistic effects. Our analysis suggests that depletion of dNTP pools can explain apparent synergy between TDF and FTC in HIV-infected cells at clinically relevant concentrations. Dead-end complex (DEC) formation does not seem to significantly contribute to the synergistic effect. However, in the presence of non-nucleoside reverse transcriptase inhibitors (NNRTIs), its role might be more relevant, as previously reported in experimental in vitro studies.
Environmental Surveillance for Risk Assessment in the Context of a Phase 2 Clinical Trial of Type 2 Novel Oral Polio Vaccine in Panama
Authors: Rojas-Bonilla Magda , Coulliette-Salmond Angela , Belgasmi Hanen , Wong Kimberly , Sayyad Leanna , Vega Everardo , Grimoldi Fabian , Oberste M. , Rüttimann Ricardo
Published: July 2021

Environmental surveillance was recommended for risk mitigation in a novel oral polio vaccine-2 (nOPV2) clinical trial (M5-ABMG) to monitor excretion, potential circulation, and loss of attenuation of the two nOPV2 candidates. The nOPV2 candidates were developed to address the risk of poliovirus (PV) type 2 circulating vaccine-derived poliovirus (cVDPV) as part of the global eradication strategy. Between November 2018 and January 2020, an environmental surveillance study for the clinical trial was conducted in parallel to the M5-ABMG clinical trial at five locations in Panama. The collection sites were located upstream from local treatment plant inlets, to capture the excreta from trial participants and their community. Laboratory analyses of 49 environmental samples were conducted using the two-phase separation method. Novel OPV2 strains were not detected in sewage samples collected during the study period. However, six samples were positive for Sabin-like type 3 PV, two samples were positive for Sabin-like type 1 PV, and non-polio enteroviruses NPEVs were detected in 27 samples. One of the nOPV2 candidates has been granted Emergency Use Listing by the World Health Organization and initial use started in March 2021. This environmental surveillance study provided valuable risk mitigation information to support the Emergency Use Listing application.