bluuebunny/crossref_metadata_2025 huggingface dataset:
Unraveling the Effects of Co-Crystallization on the UV/Vis Absorption Spectra of an N-Salicylideneaniline Derivative. A Computational RI-CC2 Investigation
Authors: Quertinmont Jean , Leyssens Tom , Wouters Johan , Champagne Benoît
Published: October 2020

This work aims at unraveling the effects of co-crystallization on the optical properties of an N-salicylideneaniline-derived molecular switch transforming between an enol and a keto form. This is achieved by way of a two-step multi-scale method where (i) the molecular geometry and unit cell parameters are optimized using a periodic boundary conditions density functional theory method and (ii) the optical properties are computed for a selection of clusters embedded in an array of point-charges that reproduce the crystal field electronic potential. The optical properties (vertical excitation energies and oscillator strengths) are obtained at the RI-CC2/def2-TZVPD level of approximation. This method allows us to decompose the effects of co-crystallization into (i) indirect effects, the geometry changes of the chromophore due to crystal packing with the coformer, and (ii) direct ones, the polarization due to the interacting coformer and to the crystal field. For the former effects, variations of a crucial torsion angle lead to modification of the π-conjugation and therefore to the decrease or increase of the excitation energies. About the latter, they are antagonistic: (i) the coformer is not directly involved in the excitations but its polarization decreases the excitation energies while (ii) the crystal field has the opposite effect. For the co-crystals with succinic and fumaric acids, combining these direct and indirect effects leads to a hypsochromic shift of the first absorption band with respect to the reference crystal, in agreement with experimental data.
Medicinal Potential of Garcinia Species and Their Compounds
Authors: Espirito Santo Bruna Larissa Spontoni do , Santana Lidiani Figueiredo , Kato Junior Wilson Hino , de Araújo Felipe de Oliveira , Bogo Danielle , Freitas Karine de Cássia , Guimarães Rita de Cássia Avellaneda , Hiane Priscila Aiko , Pott Arnildo , Filiú Wander Fernando de Oliveira , Arakaki Asato Marcel , Figueiredo Patrícia de Oliveira , Bastos Paulo Roberto Haidamus de Oliveira
Published: October 2020

Garcinia is a genus of Clusiaceae, distributed throughout tropical Asia, Africa, New Caledonia, Polynesia, and Brazil. Garcinia plants contain a broad range of biologically active metabolites which, in the last few decades, have received considerable attention due to the chemical compositions of their extracts, with compounds which have been shown to have beneficial effects in several diseases. Our work had the objective of reviewing the benefits of five Garcinia species (G. brasiliensis, G. gardneriana, G. pedunculata, G. cambogia, and G. mangstana). These species provide a rich natural source of bioactive compounds with relevant therapeutic properties and anti-inflammatory effects, such as for the treatment of skin disorders, wounds, pain, and infections, having demonstrated antinociceptive, antioxidant, antitumoral, antifungal, anticancer, antihistaminic, antiulcerogenic, antimicrobial, antiviral, vasodilator, hypolipidemic, hepatoprotective, nephroprotective, and cardioprotective properties. This demonstrates the relevance of the genus as a rich source of compounds with valuable therapeutic properties, with potential use in the prevention and treatment of nontransmissible chronic diseases.
Review of the State of the Art of Deep Learning for Plant Diseases: A Broad Analysis and Discussion
Authors: Hasan Reem Ibrahim , Yusuf Suhaila Mohd , Alzubaidi Laith
Published: October 2020

Deep learning (DL) represents the golden era in the machine learning (ML) domain, and it has gradually become the leading approach in many fields. It is currently playing a vital role in the early detection and classification of plant diseases. The use of ML techniques in this field is viewed as having brought considerable improvement in cultivation productivity sectors, particularly with the recent emergence of DL, which seems to have increased accuracy levels. Recently, many DL architectures have been implemented accompanying visualisation techniques that are essential for determining symptoms and classifying plant diseases. This review investigates and analyses the most recent methods, developed over three years leading up to 2020, for training, augmentation, feature fusion and extraction, recognising and counting crops, and detecting plant diseases, including how these methods can be harnessed to feed deep classifiers and their effects on classifier accuracy.
Inverter Efficiency Analysis Model Based on Solar Power Estimation Using Solar Radiation
Authors: Park Chul-Young , Hong Seok-Hoon , Lim Su-Chang , Song Beob-Seong , Park Sung-Wook , Huh Jun-Ho , Kim Jong-Chan
Published: October 2020

The photovoltaic (PV) industry is an important part of the renewable energy industry. With the growing use of PV systems, interest in their operation and maintenance (O&M) is increasing. In this regard, analyses of power generation efficiency and inverter efficiency are very important. The first step in efficiency analysis is solar power estimation based on environment sensor data. In this study, solar power was estimated using a univariate linear regression model. The estimated solar power data were cross-validated with the actual solar power data obtained from the inverter. The results provide information on the power generation efficiency of the inverter. The linear estimation model developed in this study was validated using a single PV system. It is possible to apply the coefficients presented in this study to other PV systems, even though the nature and error rates of the collected data may vary depending on the inverter manufacturer. To apply the proposed model to PV systems with different power generation capacities, reconstructing the model according to the power generation capacity is necessary.
A New Computational Approach to Evaluating Systemic Gene–Gene Interactions in a Pathway Affected by Drug LY294002
Authors: Kim Shinuk
Published: October 2020

In this study, we investigate how drugs systemically affect genes via pathways by integrating information from interactions between chemical compounds and molecular expression datasets, and from pathway information such as gene sets using mathematical models. First, we adopt drug-induced gene expression datasets; then, employ gene set enrichment analysis tools for selecting candidate enrichment pathways; and lastly, implement the inverse algorithm package for identifying gene–gene regulatory networks in a pathway. We tested LY294002-induced datasets of the MCF7 breast cancer cell lines, and found a CELL CYCLE pathway with 101 genes, ERBB signaling pathway consisting of 82 genes, and MTOR pathway consisting of 45 genes. We consider two interactions: quantity strength depending on number of interactions, and quality strength depending on weight of interaction as positive (+) and negative (−) interactions. Our methods revealed ANAPC1-CDK6 (−0.412) and ORC2L- CHEK1(0.951) for the CELL CYCLE pathway; INS-RPS6 (−3.125) and PRKAA2-PRKAA2 (+1.319) for the MTOR pathway; and CBLB-RPS6KB1 (−0.141), RPS6KB1-CBLC (+0.238) for the ERBB signaling pathway to be top quality interactions. Top quantity interactions discovered include 12; the CDC (−,+) gene family for the CELL CYCLE pathway, 20; PIK3 (−), 23; PIK3CG (+) for the MTOR pathway, 11; PAK (−), 10; PIK3 (+) for the ERBB signaling pathway.
Occlusal Load Considerations in Implant-Supported Fixed Restorations
Authors: D’Amico Cesare , Bocchieri Salvatore , Sambataro Sergio , Surace Giovanni , Stumpo Chiara , Fiorillo Luca
Published: October 2020

The advent of new technologies in the field of medicine and dentistry is creating improvements that lead clinicians to have materials and procedures able to improve patients’ quality of life. The aim of this article is to evaluate occlusion load and its consequences on fixed implant-supported prosthesis. New materials have granted clinicians the possibility achieve great aesthetic results in dental prosthesis, and new procedures allow them to standardize and give precise and repeatable results, especially for the functional and long-term stability aspects of products. Some principles should be carefully evaluated and applied to every dental prosthesis; the evaluation of the forces and fitting of meso-structures to dental implants, an aspect that is often not well considered by clinicians, is the main focus of this article.
Classification of Active Fires and Weather Conditions in the Lower Amur River Basin
Authors: Hayasaka Hiroshi , Sokolova Galina V. , Ostroukhov Andrey , Naito Daisuke
Published: October 2020

Most wildland fires in boreal forests occur during summer, but major fires in the lower Amur River Basin of the southern Khabarovsk Krai (SKK) mainly occur in spring. To reduce active fires in the SKK, we carried out daily analysis of MODIS (Moderate Resolution Imaging Spectroradiometer) hotspot (HS) data and various weather charts. HS data of 17 years from 2003 were used to identify the average seasonal fire occurrence. Active fire-periods were extracted by considering the number of daily HSs and their continuity. Weather charts, temperature maps, and wind maps during the top 12 active fire-periods were examined to clarify each fire weather condition. Analysis results showed that there were four active fire-periods that occurred in April, May, July, and October. Weather charts during the top active fire-periods showed active fires in April and October occurred under strong wind conditions (these wind velocities were over 30 km h−1) related to low-pressure systems. The very active summer fire at the end of June 2012 occurred related to warm air mass advection promoted by large westerly meandering. We showed clear fire weather conditions in the SKK from March to October. If a proper fire weather forecast is developed based on our results, more efficient and timely firefighting can be carried out.
InSAR Greece with Parallelized Persistent Scatterer Interferometry: A National Ground Motion Service for Big Copernicus Sentinel-1 Data
Authors: Papoutsis Ioannis , Kontoes Charalampos , Alatza Stavroula , Apostolakis Alexis , Loupasakis Constantinos
Published: October 2020

Advances in synthetic aperture radar (SAR) interferometry have enabled the seamless monitoring of the Earth’s crust deformation. The dense archive of the Sentinel-1 Copernicus mission provides unprecedented spatial and temporal coverage; however, time-series analysis of such big data volumes requires high computational efficiency. We present a parallelized-PSI (P-PSI), a novel, parallelized, and end-to-end processing chain for the fully automated assessment of line-of-sight ground velocities through persistent scatterer interferometry (PSI), tailored to scale to the vast multitemporal archive of Sentinel-1 data. P-PSI is designed to transparently access different and complementary Sentinel-1 repositories, and download the appropriate datasets for PSI. To make it efficient for large-scale applications, we re-engineered and parallelized interferogram creation and multitemporal interferometric processing, and introduced distributed implementations to best use computing cores and provide resourceful storage management. We propose a new algorithm to further enhance the processing efficiency, which establishes a non-uniform patch grid considering land use, based on the expected number of persistent scatterers. P-PSI achieves an overall speed-up by a factor of five for a full Sentinel-1 frame for processing in a 20-core server. The processing chain is tested on a large-scale project to calculate and monitor deformation patterns over the entire extent of the Greek territory—our own Interferometric SAR (InSAR) Greece project. Time-series InSAR analysis was performed on volumes of about 12 TB input data corresponding to more than 760 Single Look Complex Sentinel-1A and B images mostly covering mainland Greece in the period of 2015–2019. InSAR Greece provides detailed ground motion information on more than 12 million distinct locations, providing completely new insights into the impact of geophysical and anthropogenic activities at this geographic scale. This new information is critical to enhancing our understanding of the underlying mechanisms, providing valuable input into risk assessment models. We showcase this through the identification of various characteristic geohazard locations in Greece and discuss their criticality. The selected geohazard locations, among a thousand, cover a wide range of catastrophic events including landslides, land subsidence, and structural failures of various scales, ranging from a few hundredths of square meters up to the basin scale. The study enriches the large catalog of geophysical related phenomena maintained by the GeObservatory portal of the Center of Earth Observation Research and Satellite Remote Sensing BEYOND of the National Observatory of Athens for the opening of new knowledge to the wider scientific community.
UAV-Borne LiDAR Crop Point Cloud Enhancement Using Grasshopper Optimization and Point Cloud Up-Sampling Network
Authors: Chen Jian , Zhang Zichao , Zhang Kai , Wang Shubo , Han Yu
Published: October 2020

Because of low accuracy and density of crop point clouds obtained by the Unmanned Aerial Vehicle (UAV)-borne Light Detection and Ranging (LiDAR) scanning system of UAV, an integrated navigation and positioning optimization method based on the grasshopper optimization algorithm (GOA) and a point cloud density enhancement method were proposed. Firstly, a global positioning system (GPS)/inertial navigation system (INS) integrated navigation and positioning information fusion method based on a Kalman filter was constructed. Then, the GOA was employed to find the optimal solution by iterating the system noise variance matrix Q and measurement noise variance matrix R of Kalman filter. By feeding the optimal solution into the Kalman filter, the error variances of longitude were reduced to 0.00046 from 0.0091, and the error variances of latitude were reduced to 0.00034 from 0.0047. Based on the integrated navigation, an UAV-borne LiDAR scanning system was built for obtaining the crop point. During offline processing, the crop point cloud was filtered and transformed into WGS-84, the density clustering algorithm improved by the particle swarm optimization (PSO) algorithm was employed to the clustering segment. After the clustering segment, the pre-trained Point Cloud Up-Sampling Network (PU-net) was used for density enhancement of point cloud data and to carry out three-dimensional reconstruction. The features of the crop point cloud were kept under the processing of reconstruction model; meanwhile, the density of the crop point cloud was quadrupled.
Photometric Normalization of Chang’e-4 Visible and Near-Infrared Imaging Spectrometer Datasets: A Combined Study of In-Situ and Laboratory Spectral Measurements
Authors: Qi Xiaobin , Ling Zongcheng , Zhang Jiang , Chen Jian , Cao Haijun , Liu Changqing , Qiao Le , Fu Xiaohui , He Zhiping , Xu Rui , Liu Jianzhong , Zou Yongliao
Published: October 2020

Until 29 May 2020, the Visible and Near-Infrared Imaging Spectrometer (VNIS) onboard the Yutu-2 Rover of the Chang’e-4 (CE-4) has acquired 96 high-resolution surface in-situ imaging spectra. These spectra were acquired under different illumination conditions, thus photometric normalization should be conducted to correct the introduced albedo differences before deriving the quantitative mineralogy for accurate geologic interpretations. In this study, a Lommel–Seeliger (LS) model and Hapke radiative transfer (Hapke) model were used and empirical phase functions of the LS model were derived. The values of these derived phase functions exhibit declining trends with the increase in phase angles and the opposition effect and phase reddening effect were observed. Then, we discovered from in-situ and laboratory measurements that the shadows caused by surface roughness have significant impacts on reflectance spectra and proper corrections were introduced. The validations of different phase functions showed that the maximum discrepancy at 1500 nm of spectra corrected by the LS model was less (~3.7%) than that by the Hapke model (~7.4%). This is the first time that empirical phase functions have been derived for a wavelength from 450 to 2395 nm using in-situ visible and near-infrared spectral datasets. Generally, photometrically normalized spectra exhibit smaller spectral slopes, lower FeO contents and larger optical maturity parameter (OMAT) than spectra without correction. In addition, the band centers of the 1 and 2 μm absorption features of spectra after photometric normalization exhibit a more concentrated distribution, indicating the compositional homogeneity of soils at the CE-4 landing site.
UWB-Based Self-Localization Strategies: A Novel ICP-Based Method and a Comparative Assessment for Noisy-Ranges-Prone Environments
Authors: Bonnin-Pascual Francisco , Ortiz Alberto
Published: October 2020

Ultra-Wide-Band (UWB) positioning systems are now a real option to estimate the position of generic agents (e.g., robots) within indoor/GPS-denied environments. However, these environments can comprise metallic structures or other elements which can negatively affect the signal transmission and hence the accuracy of UWB-based position estimations. Regarding this fact, this paper proposes a novel method based on point-to-sphere ICP (Iterative Closest Point) to determine the 3D position of a UWB tag. In order to improve the results in noise-prone environments, our method first selects the anchors’ subset which provides the position estimate with least uncertainty (i.e., largest agreement) in our approach. Furthermore, we propose a previous stage to filter the anchor-tag distances used as input of the ICP stage. We also consider the addition of a final step based on non-linear Kalman Filtering to improve the position estimates. Performance results for several configurations of our approach are reported in the experimental results section, including a comparison with the performance of other position-estimation algorithms based on trilateration. The experimental evaluation under laboratory conditions and inside the cargo hold of a vessel (i.e., a noise-prone scenario) proves the good performance of the ICP-based algorithm, as well as the effects induced by the prior and posterior filtering stages.
Transfer Learning Based Method for Frequency Response Model Updating with Insufficient Data
Authors: Deng Zhongmin , Zhang Xinjie , Zhao Yanlin
Published: October 2020

Finite element model updating precision depends heavily on sufficient vibration feature extraction. However, adequate amount of sample collection is generally time-consuming in frequency response (FR) model updating. Accurate vibration feature extraction with insufficient data has become a significant challenge in FR model updating. To update the finite element model with a small dataset, a novel approach based on transfer learning is firstly proposed in this paper. A readily available fault diagnosis dataset is selected as ancillary knowledge to train a high-precision mapping from FR data to updating parameters. The proposed transfer learning network is constructed with two branches: source and target domain feature extractor. Considering about the cross-domain feature discrepancy, a domain adaptation method is designed by embedding the extracted features into a shared feature space to train a reliable model updating framework. The proposed method is verified by a simulated satellite example. The comparison results manifest that sample amount dependency has prominently lessened this method and the updated model outperforms the method without transfer learning in accuracy with the small dataset. Furthermore, the updated model is validated through dynamic response out of the training set.
Prediction of Sensory Parameters of Cured Ham: A Study of the Viability of the Use of NIR Spectroscopy and Artificial Neural Networks
Authors: Hernández-Ramos Pedro , Vivar-Quintana Ana María , Revilla Isabel , González-Martín María Inmaculada , Hernández-Jiménez Miriam , Martínez-Martín Iván
Published: October 2020

Dry-cured ham is a high-quality product owing to its organoleptic characteristics. Sensory analysis is an essential part of assessing its quality. However, sensory assessment is a laborious process which implies the availability of a trained tasting panel. The aim of this study was the prediction of dry-ham sensory characteristics by means of an instrumental technique. To do so, an artificial neural network (ANN) model for the prediction of sensory parameters of dry-cured hams based on NIR spectral information was developed and optimized. The NIR spectra were obtained with a fiber-optic probe applied directly to the ham sample. In order to achieve this objective, the neural network was designed using 28 sensory parameters analyzed by a trained panel for sensory profile analysis as output data. A total of 91 samples of dry-cured ham matured for 24 months were analyzed. The hams corresponded to two different breeds (Iberian and Iberian x Duroc) and two different feeding systems (feeding outdoors with acorns or feeding with concentrates). The training algorithm and ANN architecture (the number of neurons in the hidden layer) used for the training were optimized. The parameters of ANN architecture analyzed have been shown to have an effect on the prediction capacity of the network. The Levenberg–Marquardt training algorithm has been shown to be the most suitable for the application of an ANN to sensory parameters
The Use of Inertial Measurement Units for the Study of Free Living Environment Activity Assessment: A Literature Review
Authors: Jung Sylvain , Michaud Mona , Oudre Laurent , Dorveaux Eric , Gorintin Louis , Vayatis Nicolas , Ricard Damien
Published: October 2020

This article presents an overview of fifty-eight articles dedicated to the evaluation of physical activity in free-living conditions using wearable motion sensors. This review provides a comprehensive summary of the technical aspects linked to sensors (types, number, body positions, and technical characteristics) as well as a deep discussion on the protocols implemented in free-living conditions (environment, duration, instructions, activities, and annotation). Finally, it presents a description and a comparison of the main algorithms and processing tools used for assessing physical activity from raw signals.
Investigating the Benefits of Vector-Based GNSS Receivers for Autonomous Vehicles under Challenging Navigation Environments
Authors: Elghamrawy Haidy Y. F. , Tamazin Mohamed , Noureldin Aboelmagd
Published: October 2020

There is a growing demand for robust and accurate positioning information for various applications, including the self-driving car industry. Such applications rely mainly on the Global Navigation Satellite System (GNSS), including the Global Positioning System (GPS). However, GPS positioning accuracy relies on several factors, such as satellite geometry, receiver architecture, and navigation environment, to name a few. In urban canyons in which there is a significant probability of signal blockage of one or more satellites and/or interference, the positioning accuracy of scalar-based GPS receivers drastically deteriorates. On the other hand, vector-based GPS receivers exhibit some immunity to momentary outages and interference. Therefore, it is becoming necessary to consider vector-based GPS receivers for several applications, especially safety-critical applications, including next-generation navigation technologies for autonomous vehicles. This paper investigates a vector-based receiver’s performance and compares it to its scalar counterpart in signal degraded conditions. The realistic simulation experiments in this paper are conducted on GPS L1 C/A signals generated using the SpirentTM simulation system to create a fully controlled environment to examine and validate the performance. The results show that the vector tracking system outperforms the scalar tracking in terms of position and velocity estimation accuracy in signal-degraded environments.
Review of Smart City Assessment Tools
Authors: Patrão Carlos , Moura Pedro , Almeida Anibal T. de
Published: October 2020

Today’s cities are estimated to generate 80% of global GDP, covering only about 3% of the land, but contributing to about 72% of all global greenhouse gas emissions. Cities face significant challenges, such as population growth, pollution, congestion, lack of physical and social infrastructures, while trying to simultaneously meet sustainable energy and environmental requirements. The Smart City concept intends to address these challenges by identifying new and intelligent ways to manage the complexity of urban living and implement solutions for multidisciplinary problems in cities. With the increasing number of Smart City projects being implemented around the world, it is important to evaluate their strengths and weaknesses for their future improvement and evolution track record. It is, therefore, crucial to characterize and improve the proper tools to adequately evaluate these implementations. Following the Smart City implementation growth, several Smart City Assessment tools with different indicator sets have been developed. This work presents a literature review on Smart City Assessment tools, discussing their main gaps in order to improve future methodologies and tools. Smart City Assessment can deliver important performance indicators monitoring for the evaluation of multiple benefits for different actors and stakeholders, such as city authorities, investors and funding agencies, researchers, and citizens.
Mothers as Victims of Intimate Partner Violence: The Decision to Leave or Stay and Resilience-Oriented Intervention
Authors: Sani Ana Isabel , Pereira Dora
Published: October 2020

This paper presents a qualitative study to understand the reasons for leaving or staying in an abusive relationship and how this informs planning for psychosocial interventions with victims. We present a study of 15 Portuguese women with children who were victims of intimate partner violence (IPV). The sample consisted of women, helped by a Victim Support Office, who volunteered to participate in a semi-structured interview and whose narrative responses were recorded and transcribed for analysis. The results, organized into two broad categories, reveal that the reasons for staying in the abusive relationship are essentially related to extrinsic factors (e.g., children, the aggressor, society), which reinforces myths (e.g., marriage is for life) and makes it difficult to break the cycle of violence. However, the decision to leave the abusive relationship is also based on the same factors which, when reconceptualized and empowered, contribute to the intrinsic recognition of the problem and the decision-making process. We find that the resilience portfolio model, which focuses on three major factors (self-regulation, interpersonal forces, and construction of meaning), favors the identification of protective factors that can guide interventions for individuals facing situations of adversity such as IPV.
New Ways of Working and Public Healthcare Professionals’ Well-Being: The Response to Face the COVID-19 Pandemic
Authors: López-Cabarcos M. Ángeles , López-Carballeira Analía , Ferro-Soto Carlos
Published: October 2020

This research proposes analyzing the influence of new ways of working (NWW) on healthcare professional’s well-being and how these may affect work performance and public service motivation. These variables and relationships were important before COVID-19 pandemic, and everything points to the fact that during and after the pandemic their importance will be higher. To buffer the potential negative effects of implementing the NWW, both organizations and employees must identify personal (psychological capital) and job resources (inter-role conflict, psychological empowerment, meaning of work) capable of acting as effective moderators to promote employee well-being and avoid negative experiences at work. This paper aims to shed light on new ways of coping and adapting to uncertain job requirements such as those that have arisen during COVID-19. Moreover, it highlights the great changes that public healthcare needs to face to improve the quality of the service offered to society. It is urgent that public administrators and human resources managers design effective strategies and make effective decisions in which employee well-being and service quality are main priorities.
Bridging the Literature Gap: A Framework for Assessing Actor Participation in Participatory Guarantee Systems (PGS)
Authors: Kaufmann Sonja , Hruschka Nikolaus , Vogl Christian R.
Published: October 2020

Participatory guarantee systems (PGS) have become increasingly important for organic quality assurance. PGS are promoted as more suitable than third-party certification (TPC) for smallholder farmers in the Global South. The advocated benefits of PGS include the promotion of organic agriculture, farmer empowerment, and the facilitation of food system sustainability. To deliver these benefits, local actor participation is key. To date, there is still an absence of in-depth studies on participation in PGS in the literature. The aim of this study was to contribute to closing this research gap by (i) conducting a meta-analysis on PGS participation and (ii) presenting a framework for studying actor participation in PGS. A systematic literature review on participation in PGS was carried out, using a framework based on Cohen and Uphoff (1980). The results showed that data on participation in PGS are still fragmented in scientific literature. Quantitative empirical evidence and data on the extent and purpose of participation and actors’ perception of participation, for example, are very scarce or not available at all. This paper argues that a systematic and theory-based approach to further research on participation in PGS is needed for improved understanding and facilitation, and suggests an adapted version of Cohen and Uphoff’s (1980) framework for conducting this research.
3D Numerical Analysis of the Natural Ventilation Behavior in a Colombian Greenhouse Established in Warm Climate Conditions
Authors: Villagran Edwin , Leon Rommel , Rodriguez Andrea , Jaramillo Jorge
Published: October 2020

Global food production and availability in hot climate zones are limited by biotic and abiotic factors that affect agricultural production. One of the alternatives for intensifying agriculture and improving food security in these regions is the use of naturally ventilated greenhouses, an alternative that still requires information that allows technical criteria to be established for decision-making. Therefore, the objective of this work was to study the spatial distribution of temperature and relative humidity inside a greenhouse built in the Colombian Caribbean. The methodological approach included the implementation of an experimentally validated 3D numerical simulation model. The main results obtained allowed to determine that the airflows generated inside the greenhouse had average velocities below 0.5 m/s and were mainly driven by the thermal effect of natural ventilation. It was also found that the gradients generated between the interior of the structure and the exterior environment presented values lower than 2.0 °C for temperature and −6.3% for relative humidity. These values can be considered low in comparison with other structures evaluated in other regions of the world where the gradients can reach values higher than 10 °C and 13% for temperature and relative humidity, respectively.
Evaluation of Construction Cost, Time, and Sustainable Attributes of Drywalls Supported by Resilient Channels
Authors: Kim Kyung Ho , Jeon Jin Yong
Published: October 2020

In this study, a gypsum board wall was developed using resilient channels to improve sound insulation performance, constructability, and economic efficiency; the effect of the application of the developed wall on skyscrapers and long-term housing, one of the main forms of modern buildings, was also comprehensively evaluated. Resilient channels were inserted and fixed to ensure the constructability was suitable for high-rise buildings. In addition, the sound insulation performance, durability of the wall, CO2 emissions, and life-cycle cost (LCC), which are key elements for economic efficiency, constructability, and sustainability, were analyzed. The developed lightweight gypsum board drywall with resilient channels was compared with a concrete wall as well as a double stud gypsum board wall, which has been most widely used among existing drywalls. The sound insulation performance and durability were evaluated in a laboratory, and the other items were evaluated after constructing the walls in a hotel building with an area of 2956 m2. The evaluation results show that the developed wall exhibited a 3 dB higher sound insulation performance than the concrete wall, even though it was thinner by 50 mm, and the wall secured the grade of “severe duty” (SD) based on the BS 5234-2 standard in durability evaluation, indicating that it can sufficiently replace concrete walls. Moreover, when the developed wall was installed in an actual building and compared with a concrete wall, a 14.7% reduction in construction cost, 59% reduction in CO2 emissions, and 30.4% reduction in the LCC of the drywall, considering even the remodeling and dismantling stages of the building, were observed. Therefore, it was proven that the newly developed resilient channel drywall with improved constructability has significant value in terms of sound insulation performance, economic efficiency, safety, and eco-friendliness.
Peculiarities of the Relation between Human and Environmental Wellbeing in Different Stages of National Development
Authors: Ulman Simona-Roxana , Mihai Costica , Cautisanu Cristina
Published: October 2020

The literature formed around the concept of sustainable development emphasizes that its achievement depends on how its dimensions evolve. Considering that the economic dimension is not an end in itself, but a means for achieving the other two dimensions, we concentrated on the relation between environment and society. Using the framework of Sustainable Society Index, we applied path analysis for identifying the effects of human wellbeing components on environmental wellbeing for 71 countries around the world in 2016. The countries were grouped into two groups—factor-driven and innovation-driven economies—according to Global Competitiveness Report. The main results revealed that once the society develops, the pressure upon the environment tends to move from the necessity of offering the basic human needs to the one regarding superior societal needs. While the least developed nations have to pay attention especially to population growth, safe sanitation and health as primary channels of better protecting the environment, in the case of the most developed countries, the main directions of environmental improvement may be education and good governance. Thus, a high environmental concern has to be cultivated in the development process, whichever its stage, but with distinct directions of action, as shown by this study.
A Transportation Network Paradox: Consideration of Travel Time and Health Damage due to Pollution
Authors: Cheng Zhaolin , Zhao Laijun , Li Huiyong
Published: October 2020

In cities with serious air pollution, travel time and health damage significantly affect route choice by travelers (e.g., motorcycle and scooter drivers). Consequently, the classical Braess paradox is no longer realistic because it only considers the traveler’s value of time (VOT). In the current study, we describe a new transportation network paradox that considers both the VOT and the traveler’s perception of pollution damage. To examine the conditions that create the new paradox, we developed a novel method to compute a total comprehensive cost that combines the VOT with health damage. We analyzed the conditions for the new paradox and the system’s performance using a user equilibrium model and system optimization. Furthermore, an improved model is used to analyze how different transport modes influence the Braess paradox. We found that whether the new paradox occurs and the potential improvement of the system’s performance depend on whether the total travel demand falls within critical ranges. The bounds of these ranges depend on the values of the parameters in the function that describes the health damage and the link travel time function. In addition, high health damage significantly affects route choices and traffic flow distribution. This paper presents a new perspective for decision-making by transportation planners and for route choices in cities with serious air pollution.
Improving the Water-Use Efficiency and the Agricultural Productivity: An Application Case in a Modernized Semiarid Region in North-Central Mexico
Authors: González-Trinidad Julián , Júnez-Ferreira Hugo Enrique , Bautista-Capetillo Carlos , Ávila Dávila Laura , Robles Rovelo Cruz Octavio
Published: October 2020

The increasing population demands a greater quantity of food. In order to satisfy the world’s demand, one of the main challenges worldwide consists of modernizing the current irrigation systems. This research shows an experience carried out in a modernized irrigation module in Central-North Mexico following these objectives: to evaluate the impact of the modernization of the irrigation module, to analyze the agricultural productivity, and to assess a group of parameters related with the agricultural production (system conduction and distribution efficiencies, water productivity, among others) and the water volumes after and before the modernization. After a drought period, a methodology was performed in commercial parcels in 2013 to increase the yield of different crops. Some of the activities were: soil leveling, estimation of the soil properties (field capacity, wilting point, bulk density, pH, and organic matter), optimum fertilization applications, use of a model to scheduling irrigation, measure volumes extracted at the parcel level. With the modernization and the method used, around 1800 and 2000 m3 ha−1 were saved with respect to the initial granted volume by the Comisión Nacional del Agua and increase in the global efficiency was also achieved (from 55% to 85%). All crop yields increased, i.e., for corn from 2.5 kg/m3 to 3.8 kg/m3. The impact of modernization accompanied with an effective operation allowed a significant increase of the crop yield and water productivity. Despite a controlled distribution of water being carried out, future research should contemplate free water demand scenarios and automation irrigation for improving the module operation.
Micro-Operating Mechanism Approach
for Regulatory Sandbox Policy Focused on Fintech
Authors: Choi HaeOk , Lee KwangHo
Published: October 2020

To determine the micro-operating mechanism(MoM) of enterprises participating in the regulatory sandbox policy in fintech, this study analyzes the structure of enterprise innovation competencies and derives relevant implications. The results reveal that large, middle-standing, and small and medium-sized enterprises focus on security, infrastructure, and user-related technology development, respectively, to enhance their innovation competencies. The security-related issues considered by large enterprises entail relatively high costs in initial technology development and are closely related to infrastructure building. Large enterprises are focused on developing overall security-related technologies, whereas middle-standing enterprises are striving to develop infrastructure-related technologies, with particular emphasis on elementary technologies. Small and medium-sized enterprises are also making efforts to develop user-centered technologies that can directly be used in fintech. As a method to implement regulatory sandboxes tailored to the needs of participating enterprises in South Korea, this study will help to determine the MoM of such participants and establish strategies to support them sustainably in terms of evidence-based policy.
Lifetime Cadmium Exposure and Mortality for Renal Diseases in Residents of the Cadmium-Polluted Kakehashi River Basin in Japan
Authors: Nishijo Muneko , Nogawa Kazuhiro , Suwazono Yasushi , Kido Teruhiko , Sakurai Masaru , Nakagawa Hideaki
Published: October 2020

Very few studies have investigated the dose–response relationship between external cadmium (Cd) exposure and mortality. We aim to investigate the relationship between lifetime Cd intake (LCd) and mortality in the Cd-polluted Kakehashi River basin in Japan. Mortality risk ratios for a unit of increase of LCd and urinary Cd were analyzed using Cox’s proportional model. LCd was estimated based on residency and Cd in rice produced in their living areas. In men, mortality for all causes was significantly increased for a 10-μg/g Cr increase in urinary Cd, but not for a 1-g increase in LCd. In women, mortality risks for all causes and renal diseases, particularly renal failure, were significantly increased for a 10-μg/g Cr increase in urinary Cd. Similarly, mortality risks for renal diseases and renal failure were significantly increased for a 1-g increase of LCd in women. Comparing the contribution of two exposure markers to increased mortality in women, LCd was more effective for increasing mortality risks for renal diseases and renal failure, while urinary Cd contributed more to increased mortality risk for all causes. LCd may show a better dose–response relationship with mortality risk for renal diseases in women.
Low Prevalence of Leptospira Carriage in Rodents in Leptospirosis-Endemic Northeastern Thailand
Authors: Krairojananan Panadda , Thaipadungpanit Janjira , Leepitakrat Surachai , Monkanna Taweesak , Wanja Elizabeth W. , Schuster Anthony L. , Costa Federico , Poole-Smith B. Katherine , McCardle Patrick W.
Published: October 2020

Leptospirosis is a neglected zoonotic disease affecting mostly the world’s tropical regions. The rural people of northeastern Thailand suffer from a large number of leptospirosis infections, and their abundant rice fields are optimal rodent habitats. To evaluate the contribution of diversity and carriage rate of pathogenic Leptospira in rodent reservoirs to leptospirosis incidence, we surveyed rodents, between 2011 and 2012, in four provinces in northeastern Thailand with the highest incidence rates of human leptospirosis cases. We used lipL32 real-time PCR to detect pathogenic Leptospira in rodent kidneys, partial 16S rRNA gene sequencing to classify the infecting Leptospira species, and whole 16S rDNA sequencing to classify species of isolated Leptospira. Overall prevalence of Leptospira infection was 3.6% (18/495). Among infected rodents, Bandicotaindica (14.3%), Rattusexulans (3.6%), and R. rattus (3.2%) had renal carriage. We identified two pathogenic Leptospira species: L. interrogans (n = 15) and L. borgpetersenii (n = 3). In addition, an L. wolffii (LS0914U) isolate was recovered from the urine of B. indica. Leptospira infection was more prevalent in low density rodent populations, such as B. indica. In contrast, there was a lower prevalence of Leptospira infection in high density rodent populations of R. exulans and R. rattus.
In Vitro and In Vivo Models to Study the Zoonotic Mosquito-Borne Usutu Virus
Authors: Benzarti Emna , Garigliany Mutien
Published: October 2020

Usutu virus (USUV), a mosquito-borne zoonotic flavivirus discovered in South Africa in 1959, has spread to many European countries over the last 20 years. The virus is currently a major concern for animal health due to its expanding host range and the growing number of avian mass mortality events. Although human infections with USUV are often asymptomatic, they are occasionally accompanied by neurological complications reminiscent of those due to West Nile virus (another flavivirus closely related to USUV). Whilst USUV actually appears less threatening than some other emergent arboviruses, the lessons learned from Chikungunya, Dengue, and Zika viruses during the past few years should not be ignored. Further, it would not be surprising if, with time, USUV disperses further eastwards towards Asia and possibly westwards to the Americas, which may result in more pathogenic USUV strains to humans and/or animals. These observations, inviting the scientific community to be more vigilant about the spread and genetic evolution of USUV, have prompted the use of experimental systems to understand USUV pathogenesis and to boost the development of vaccines and antivirals. This review is the first to provide comprehensive coverage of existing in vitro and in vivo models for USUV infection and to discuss their contribution in advancing data concerning this neurotropic virus. We believe that this paper is a helpful tool for scientists to identify gaps in the knowledge about USUV and to design their future experiments to study the virus.
Resident Memory T Cells and Their Effect on Cancer
Authors: Craig Daniel J. , Creeden Justin F. , Einloth Katelyn R. , Gillman Cassidy E. , Stanbery Laura , Hamouda Danae , Edelman Gerald , Dworkin Lance , Nemunaitis John J.
Published: October 2020

Resident memory T (TRM) cells are a unique subset of CD8+ T cells that are present within certain tissues and do not recirculate through the blood. Long term memory establishment and maintenance are dependent on tissue population of memory T cells. They are characterized by dual CD69/CD103 positivity, and play a role in both response to viral infection and local cancer immunosurveillance. Human TRM cells demonstrate the increased expression of adhesion molecules to facilitate tissue retention, have reduced proliferation and produce both regulatory and immune responsive cytokines. TRM cell phenotype is often characterized by a distinct expression profile driven by Runx3, Blimp1, and Hobit transcription factors. The accumulation of TRM cells in tumors is associated with increased survival and response to immunotherapies, including anti-PD-1 and anti-CTLA-4. In this review, we explore potential mechanisms of TRM cell transformation and maintenance, as well as potential applications for the use of TRM cells in both the development of supportive therapies and establishing more accurate prognoses.
Intranasal Immunization of Mice with Multiepitope Chimeric Vaccine Candidate Based on Conserved Autotransporters SigA, Pic and Sap, Confers Protection against Shigella flexneri
Authors: León Yrvin , Zapata Lionel , Molina Raúl E. , Okanovič Gaj , Gómez Leonardo A. , Daza-Castro Carla , Flores-Concha Manuel , Reyes José L. , Oñate Angel A.
Published: October 2020

Shigellosis is a diarrheal disease and the World Health Organization prompts the development of a vaccine against Shigella flexneri. The autotransporters SigA, Pic and Sap are conserved among Shigella spp. We previously designed an in silico vaccine with immunodominat epitopes from those autotransporters, and the GroEL protein of S. typhi as an adjuvant. Here, we evaluated the immunogenicity and protective efficacy of the chimeric multiepitope protein, named rMESF, in mice against lethal infection with S. flexneri. rMESF was administered to mice alone through the intranasal (i.n.) route or accompanied with Complete Freund’s adjuvant (CFA) intradermically (i.d.), subcutaneously (s.c.), and intramuscular (i.m.), as well as with Imject alum (i.m.). All immunized mice increased IgG, IgG1, IgG2a, IgA and fecal IgA titers compared to PBS+CFA and PBS+alum control groups. Furthermore, i.n. immunization of mice with rMESF alone presented the highest titers of serum and fecal IgA. Cytokine levels (IFN-γ, TNF-α, IL-4, and IL-17) and lymphocyte proliferation increased in all experimental groups, with the highest lymphoproliferative response in i.n. mice immunized with rMESF alone, which presented 100% protection against S. flexneri. In summary, this vaccine vests protective immunity and highlights the importance of mucosal immunity activation for the elimination of S. flexneri.