bluuebunny/crossref_metadata_2025 huggingface dataset:
The Social Justice Impact of the Transit-Oriented Development
Authors: Kim Seunghoon
Published: December 2020

Transit-oriented development (TOD) is often considered a solution for automobile dependency in the pursuit of sustainability. Although TOD has shown various benefits as sustainable development and smart growth, there are potential downsides, such as transit-induced gentrification (TIG). Even if there were no displacement issues with TIG, existing residents could be disadvantaged by a TOD due to affordability problems. This study focuses on these potential affordability issues and aims to evaluate the effects of TOD using residents’ discretionary income (DI) as an indicator of affordability. The light rail transit-oriented development (LRTOD) in Phoenix, AZ, is selected because of the timing of the introduction of development and the simplicity of the light rail transit line. In order to counteract problems induced by a non-random location of TODS, propensity score matching is used. The results indicate that LRTOD can give benefit to all TOD residents. Moreover, the effects of LRTOD on discretionary income of various types of households are not statistically significantly different. We have identified the different magnitudes of the effects of TOD between propensity score matching (PSM)-controlled and uncontrolled models. These indicate the existence of the selection bias of TOD implementation, justifying the adoption of the PSM method.
Plastics Recycling with Tracer-Based-Sorting: Challenges of a Potential Radical Technology
Authors: Gasde Johannes , Woidasky Jörg , Moesslein Jochen , Lang-Koetz Claus
Published: December 2020

To improve the recycling quality of plastics packaging and achieve high recycling rates new identification and sorting technologies are required. Tracer-based-sorting (TBS) is an innovative identification technology based on fluorescent tracers and a corresponding detection unit. TBS can be considered a radical technology change towards a circular economy for plastics and to support sustainability as it has the potential to render several established sorting and/or recycling steps obsolete. This article shows which drivers and barriers are perceived by stakeholders with regard to the implementation of TBS in the market and how challenges are addressed responsibly in the early phases of the innovation process. Influencing external factors and framework conditions of TBS are identified and suitable business models for TBS in a circular economy are discussed. Further, practical recommendations on how to optimize technology and market development for TBS are provided. To obtain these results a mixed method approach of integrated innovation and sustainability analysis, external environment analysis (PESTEL analysis), and business model development approaches was chosen. The research results can be understood as a practical contribution towards a responsible and sustainable implementation of a radical technology-based innovation for a circular economy of plastics.
Building a Theoretical Framework for Corporate Sustainability
Authors: Sanchez-Planelles Joaquin , Segarra-Oña Marival , Peiro-Signes Angel
Published: December 2020

Literature about sustainability and sustainable businesses has become a large field of study during the last years. This field is growing so fast that there are sub-areas or bodies of literature within the sustainability which scopes with clear boundaries between each other. This has caused the apparition of several methodologies and tools for turning traditional companies into sustainable business models. This paper aims to develop the descriptive stage of the theory building process through a careful review of literature to create the first phase of a theory about corporate sustainability. It provides the following classification of concepts retrieved from the observation of the state of art: holistic sustainability, sustainable business models, sustainable methodologies, sustainable operations, and sustainability-oriented innovation. In addition, it seeks to establish relationships between the sustainable concepts and the expected outcomes that their implementation can generate among companies and organizations. Finally, it gives an overview of possibilities for managers that want to embed sustainability in their firms and clear paths of research for keeping the building of the theory about corporate sustainability as a process of constant iteration and improvement.
Lesson Learned from the Power of Open Data: Resolving the Mask Shortage Problem Caused by COVID-19 in South Korea
Authors: Kim Haklae
Published: December 2020

COVID-19 is spreading globally and causing severe damage across different sectors including social culture, politics, and economy. Governments worldwide are responding in various ways to prevent the spread of COVID-19 and to protect the health and safety of citizens. South Korea is escaping the crisis through rapid and early inspection with ICT technology, isolation for confirmed cases, and transparency and communication through public–private partnerships. This paper presents how face mask shortages can be managed through the disclosure of government data and with effective online services. This study shows how South Korea enhances government transparency and that combining open data with ICT technologies can effectively solve social problems during the COVID-19 pandemic.
Protection of Children in Difficulty in China during the COVID-19 Pandemic
Authors: Zhao Fang , Zhu Ning , Hämäläinen Juha
Published: December 2020

This study investigated the resilience of the Chinese child protection system in responding to the special needs of children in difficulty under the specific circumstances caused by the COVID-19 pandemic. This study applied qualitative document analysis of child protection administrative documents, in-depth interviews with 13 child protection professionals, and an in-depth case study of 14 children living in difficulty, complemented by relevant information available in the media. The results indicate that there are good policies in China’s child protection services but the organizational and functional fragmentation complicates implementation, suggesting a need for the development of bottom-up practices. The essential conclusion supported by these results is that the child protection system should be regarded and developed as a systematic project combining the legal, policymaking, and professional systems of child welfare services as well as governmental and non-governmental forces. As the COVID-19 pandemic has raised awareness of the need to develop the field of child protection holistically as an integrated system in terms of social sustainability in China, an international literature-based comparison indicates that the pandemic has also raised similar political awareness in other countries.
Development and Evaluation of Combined Adaptive Neuro-Fuzzy Inference System and Multi-Objective Genetic Algorithm in Energy, Economic and Environmental Life Cycle Assessments of Oilseed Production
Authors: Mousavi-Avval Seyed Hashem , Rafiee Shahin , Mohammadi Ali
Published: December 2020

Energy consumption, economics, and environmental impacts of canola production were assessed using a combined technique involving an adaptive neuro-fuzzy inference system (ANFIS) and a multi-objective genetic algorithm (MOGA). Data were collected from canola farming enterprises in the Mazandaran province of Iran and were used to test the application of the combined modeling algorithms. Life cycle assessment (LCA) for one ha functional unit of canola production from cradle to farm gate was conducted in order to evaluate the impacts of energy, materials used, and their environmental emissions. MOGA was applied to maximize the output energy and benefit-cost ratio, and to minimize environmental emissions. The combined ANFIS–MOGA technique resulted in a 6.2% increase in energy output, a 144% rise in the benefit-cost ratio, and a 19.8% reduction in environmental emissions from the current canola production system in the studied region. A comparison of ANFIS–MOGA with the data envelopment analysis approach was also conducted and the results established that the former is a better system than the latter because of its ability to generate optimum conditions that allow for the assessment of a combination of parameters such as energy, economic, and environmental impacts of agricultural production systems.
Prediction of Potential Evapotranspiration Using Temperature-Based Heuristic Approaches
Authors: Adnan Rana Muhammad , Heddam Salim , Yaseen Zaher Mundher , Shahid Shamsuddin , Kisi Ozgur , Li Binquan
Published: December 2020

The potential or reference evapotranspiration (ET0) is considered as one of the fundamental variables for irrigation management, agricultural planning, and modeling different hydrological pr°Cesses, and therefore, its accurate prediction is highly essential. The study validates the feasibility of new temperature based heuristic models (i.e., group method of data handling neural network (GMDHNN), multivariate adaptive regression spline (MARS), and M5 model tree (M5Tree)) for estimating monthly ET0. The outcomes of the newly developed models are compared with empirical formulations including Hargreaves-Samani (HS), calibrated HS, and Stephens-Stewart (SS) models based on mean absolute error (MAE), root mean square error (RMSE), and Nash-Sutcliffe efficiency. Monthly maximum and minimum temperatures (Tmax and Tmin) observed at two stations in Turkey are utilized as inputs for model development. In the applications, three data division scenarios are utilized and the effect of periodicity component (PC) on models’ accuracies are also examined. By importing PC into the model inputs, the RMSE accuracy of GMDHNN, MARS, and M5Tree models increased by 1.4%, 8%, and 6% in one station, respectively. The GMDHNN model with periodic input provides a superior performance to the other alternatives in both stations. The recommended model reduced the average error of MARS, M5Tree, HS, CHS, and SS models with respect to RMSE by 3.7–6.4%, 10.7–3.9%, 76–75%, 10–35%, and 0.8–17% in estimating monthly ET0, respectively. The HS model provides the worst accuracy while the calibrated version significantly improves its accuracy. The GMDHNN, MARS, M5Tree, SS, and CHS models are also compared in estimating monthly mean ET0. The GMDHNN generally gave the best accuracy while the CHS provides considerably over/under-estimations. The study indicated that the only one data splitting scenario may mislead the modeler and for better validation of the heuristic methods, more data splitting scenarios should be applied.
From Transdisciplinary Research to Transdisciplinary Education—The Role of Schools in Contributing to Community Well-Being and Sustainable Development
Authors: Kubisch Susanne , Parth Sandra , Deisenrieder Veronika , Oberauer Karin , Stötter Johann , Keller Lars
Published: December 2020

This article looks at transdisciplinary research and discusses the possibilities of translating this concept into a new type of education, which we will call Transdisciplinary Education. Following the adoption of the Sustainable Development Goals by the community of states, there has been increased international recognition of education as being a key driver for sustainable development. Considering the global grand challenges of the 21st century, the integration of Education for Sustainable Development at all school levels ought to be prioritized in order to empower young people to contribute to sustainable development. Collaborating with out-of-school partners and doing research on real-world problems within their lifeworld, help students develop the competences necessary for responsible citizenship, while at the same time contributing to community well-being. Both concepts transdisciplinary research and Transdisciplinary Education acknowledge the responsibility of addressing social relevant problems and the significant role of those who are and who will be affected by these challenges. The project Science Education for Action and Engagement Towards Sustainability (SEAS) aims at analyzing different partnerships between schools and out-of-school institutions in European countries. By comparing the collaborative formats and providing a concept and method pool for educators, SEAS targets facilitating the integration of Transdisciplinary Education in formal schooling in the future. This article gives insights into the Austrian research-education collaboration k.i.d.Z.21. Drawing on experiences of k.i.d.Z.21 and taking up characteristics of transdisciplinary research, opportunities and challenges of integrating Transdisciplinary Education in formal schooling are discussed.
Analysis on Operation Modes of Residential BESS with Balcony-PV for Apartment Houses in Korea
Authors: Eum Jiyoung , Kim Yongki
Published: December 2020

The integration of battery energy storage systems (BESS) with renewable energy is a potential solution to address the disadvantages of renewable energy systems, which is irregular and intermittent power. In particular, residential BESS is advancing in numerous countries. The residential BESS connected to the photovoltaic system (PV) can store the PV power in the battery through charging, and supply the PV power, which was stored in the battery, to the load through discharging when there is no PV power. Therefore, the utilization of residential BESS with PV reduces the daily electric power consumption and the electricity bills that households have to charge. However, it is understood that there is no case of installing and using residential BESS in Korea yet. Most residential houses in Korea are apartment houses, and thus residential BESS can be used with balcony PV. This paper presents operation modes of residential BESS with balcony PV for apartment houses. The BESS capacity was estimated by considering the balcony PV capacity, which can be installed in households, and power consumption. The applicability of the residential BESS was analyzed through performance and economics evaluation under current and various conditions. The operation modes of BESS were divided into four types according to PV power supply priority and battery charging source, and a test took place in a demonstration house. The risk of fully discharging the battery has been discovered when PV power is first charged to the battery or when only PV power is charged with the battery. As a result, preferential charging of the battery with PV power and then with PV and grid power was found to be the most optimal operation mode. In addition, additional functions were proposed for residential BESS in apartment households. The results will contribute to effective application of residential BESS with balcony PV in the near future.
A Review of Climate Economic Models in Malaysia
Authors: Rao Thirupathi , Mustapa Siti Indati
Published: December 2020

This paper presents a review of literature on the development of climate economy models in Malaysia from 1988 to 2020. The type of climate economic models used in Malaysia and their attributes were analyzed. The key attributes reviewed include functions, capability, the various approaches, types of Greenhouse gas (GHG) emissions, and various sectors included in the modelling. The review analysis revealed that climate economic modelling in Malaysia can be categorized into two groups namely Input-Output (I-O) table and Social Accounting Matrix (SAM) models as well as the Integrated Assessment Models (IAM). Both groups of climate economic models complement each other in functional capability to do top-down or bottom-up as well as short-term and long-term analysis. The key contribution of this review is in discovering three key gap clusters that exist in climate economic modelling in Malaysia. These gaps include the coverage on types of GHGs, disclosing the GHG sector’s coverage in the modelling, and the discovering of the exclusion of climate damage functions as well as the unavailability of customized functions to suit Malaysia’s climate and geography. These three key gaps need to be urgently addressed for effective policy interventions in Malaysia and to meet the global goals of the Paris Agreement.
Asymmetric Cryptosystem on Matrix Algebra over a Chain Ring
Authors: Yumman Muzna , Shah Tariq , Hussain Iqtadar
Published: December 2020

The revolutionary idea of asymmetric cryptography brings a fundamental change to our modern communication system. However, advances in quantum computers endanger the security of many asymmetric cryptosystems based on the hardness of factoring and discrete logarithm, while the complexity of the quantum algorithm makes it hard to implement in many applications. In this respect, novel asymmetric cryptosystems based on matrices over residue rings are in practice. In this article, a novel approach is introduced. Despite the matrix algebra M(k,ℤn), the matrix algebra M(k,Rn′), Rn′ = ℤ2[w]⟨wn−1⟩ as the chain ring is considered. In this technique, instead of exponentiation, the inner product automorphisms the use for key generation. The chain ring provides computational complexity to its algorithm, which improves the strength of the cryptosystem. However, the residue ring endangers the security of the original cryptosystem, while it is hard to break using Rn′. The structure of the chain ring deals with the binary field ℤ2, which simplifies its calculation and makes it capable of efficient execution in various applications.
Study on Fault Diagnosis Method of Planetary Gearbox Based on Turn Domain Resampling and Variable Multi-Scale Morphological Filtering
Authors: Liu Tongtong , Cui Lingli , Zhang Chao
Published: December 2020

The turn domain resampling (TDR) method is proposed in the paper on the basis of the existing angle domain resampling for solving the problem of non-fixed fault frequency under variable working conditions. TDR can select the appropriate sampling order according to the influence of frequency conversion, which avoided the error caused by the spline interpolation method. It can provide accurate parameters for the subsequent calculation of the equivalent frequency order. Variable multi-scale morphological filtering (VMSMF) method is proposed for the purpose of further reducing the interference of noise in resampling signal to feature extraction. VMSMF adaptively selects structural elements according to the parameter change of impact signal to make its scale more targeted. It only needs to calculate once using the optimal structural unit for a particular impact, and the filtering accuracy and operating efficiency have been greatly improved. The main steps of this article are as follows. First, the TDR is used to resample the original signal as to get the resampling signal which is still submerged by the strong noise. In the second step, VMSMF is used to filter the resampling signal to obtain the signal with less noise interference. Finally, the fault characteristics of the filtering signal was extracted and compared with the possible fault frequency calculated by the sampling parameters provided by resampling, so as to determine the fault type of the planetary gearbox. By analyzing the simulation signal and the experimental signal respectively, this method can find out the corresponding fault characteristics effectively.
Singularities in Euler Flows: Multivalued Solutions, Shockwaves, and Phase Transitions
Authors: Lychagin Valentin , Roop Mikhail
Published: December 2020

In this paper, we analyze various types of critical phenomena in one-dimensional gas flows described by Euler equations. We give a geometrical interpretation of thermodynamics with a special emphasis on phase transitions. We use ideas from the geometrical theory of partial differential equations (PDEs), in particular symmetries and differential constraints, to find solutions to the Euler system. Solutions obtained are multivalued and have singularities of projection to the plane of independent variables. We analyze the propagation of the shockwave front along with phase transitions.
A Chirality Chain in Phenylglycine, Phenylpropionic Acid, and Ibuprofen
Authors: Brunner Henri , Tsuno Takashi , Balázs Gábor
Published: December 2020

Our strategy to analyze the structures of natural amino acids with respect to the interaction of three different elements of chirality within the molecules was applied to the non-natural amino acid (S)-α-phenylglycine, its analogue (S)-α-phenylpropionic acid, and the drug (S)-ibuprofen. The three chirality elements are the configuration at Cα, the conformation at the Cα-C’ bond, and the distortion of the planar carboxylic group to a flat asymmetric tetrahedron. In all three compounds, a given (S) configuration at Cα predominantly induces (M) conformation at the Cα-C’ bond, which in turn preferentially distorts the carboxylic group to a tetrahedron with (R) configuration. Both steps of this chirality chain display high selectivities. Due to varying co-crystallization partners, in all the structures the molecules are in different environments with respect to packing and hydrogen bonding. Nevertheless, the structural pattern and the diaselectivities of the chirality chain persist. For phenylglycine, DFT (Density Functional Theory) calculations confirm the structural results.
Recognition of Crack-Rubbing Coupling Fault of Bearing under High Water Pressure Based on Polar Symmetry Mode Decomposition
Authors: Huang Jiuzhou , Hua Wen , Xie Tianzhou , Yao Yanchao , Dong Shiming
Published: December 2020

The precision of current research on fault recognition of marine bearing remains to be improved. Therefore, a recognition method of crack-rubbing coupling fault of bearing under high water pressure based on polar symmetry mode decomposition is proposed in this article. The structure of marine bearing was analyzed, and the system was divided into several subsystems. Then, the nonlinearity relationship among the subsystems was confirmed. One subsystem was used to represent other subsystems, which was imported into the kinetic equation to obtain the equation after dimensionality reduction. According to the results of dimensionality reduction, the features of signal were measured from time domain, energy, and entropy. Meanwhile, the interior features of signal were extracted. Based on the feature extraction, the classifier of probabilistic neural network was introduced. The signal was recognized, and the recognition results were output via the training of signal sample data. Experimental results show that the method has better dimensionality reduction effect and high recognition precision. The method is practical.
Application of Artificial Intelligence (AI) for Sustainable Highway and Road System
Authors: Arifuzzaman Md , Aniq Gul Muhammad , Khan Kaffayatullah , Hossain S. M. Zakir
Published: December 2020

There are several environmental factors such as temperature differential, moisture, oxidation, etc. that affect the extended life of the modified asphalt influencing its desired adhesive properties. Knowledge of the properties of asphalt adhesives can help to provide a more resilient and durable asphalt surface. In this study, a hybrid of Bayesian optimization algorithm and support vector regression approach is recommended to predict the adhesion force of asphalt. The effects of three important variables viz., conditions (fresh, wet and aged), binder types (base, 4% SB, 5% SB, 4% SBS and 5% SBS), and Carbon Nano Tube doses (0.5%, 1.0% and 1.5%) on adhesive force are taken into consideration. Real-life experimental data (405 specimens) are considered for model development. Using atomic force microscopy, the adhesive strength of nanoscales of test specimens is determined according to functional groups on the asphalt. It is found that the model predictions overlap with the experimental data with a high R2 of 90.5% and relative deviation are scattered around zero line. Besides, the mean, median and standard deviations of experimental and the predicted values are very close. In addition, the mean absolute Error, root mean square error and fractional bias values were found to be low, indicating the high performance of the developed model.
MQC-MB: Multiphoton Quantum Communication Using Multiple-Beam Concept in Free Space Optical Channel
Authors: Harun Nur Ziadah , Zukarnain Zuriati Ahmad , Hanapi Zurina Mohd , Ahmad Idawaty , Khodr Majed F.
Published: December 2020

Multiphoton Quantum Key Distribution (QKD) has recently been proposed to exchange the secret keys using the rotational of polarization over a multi-stage protocol. It has the ability to outperform the weaknesses of a single photon QKD by improving the generation of key rate and distance range. This paper investigates the theoretical aspects of multiphoton QKD protocol’s performance over free space optic (FSO) networks. The most common setup for quantum communication is the single-beam approach. However, the single-beam setup has limitations in terms of high geometrical loss. In this paper, the symmetry multiple-beam for quantum communication which is called as Multiphoton Quantum Communication-Multiple Beam (MQC-MB) is proposed to transmit the multiphoton from the sender to the receiver in order to minimize the impact of geometrical loss that is faced by the single-beam setup. The analysis was carried out through mathematical analysis by establishing the FSO quantum model with the effects of atmospheric and geometrical loss as well as considering atmospheric turbulence modeled by log-normal distribution. The design criteria of FSO, such as the transmitter, receiver, beam divergence, and diameter of apertures, are analytically investigated. The numerical results demonstrate that the MQC-MB outperforms the single-beam in terms of reducing channel loss by about 8 dB and works well under strong turbulence channel. Furthermore, the MQC-MB reduces the quantum bit error rate (QBER) and improves the secret key rate (SKR) as compared to the single-beam system even though the distance between the sender and receiver increases.
Intrinsic Decoherence and Recurrences in a Large Ferromagnetic F = 1 Spinor Bose–Einstein Condensate
Authors: Sandoval-Santana Juan Carlos , Zamora-Zamora Roberto , Paredes Rosario , Romero-Rochín Victor
Published: December 2020

Decoherence with recurrences appear in the dynamics of the one-body density matrix of an F=1 spinor Bose–Einstein condensate, initially prepared in coherent states, in the presence of an external uniform magnetic field and within the single mode approximation. The phenomenon emerges as a many-body effect of the interplay of the quadratic Zeeman effect, which breaks the rotational symmetry, and the spin-spin interactions. By performing full quantum diagonalizations, a very accurate time evolution of large condensates is analyzed, leading to heuristic analytic expressions for the time dependence of the one-body density matrix, in the weak and strong interacting regimes, for initial coherent states. We are able to find accurate analytical expressions for both the decoherence and the recurrence times, in terms of the number of atoms and strength parameters, which show remarkable differences depending on the strength of the spin-spin interactions. The features of the stationary states in both regimes are also investigated. We discuss the nature of these limits in light of the thermodynamic limit.
Road Surface Profile Synthesis: Assessment of Suitability for Simulation
Authors: Lenkutis Tadas , Čerškus Aurimas , Šešok Nikolaj , Dzedzickis Andrius , Bučinskas Vytautas
Published: December 2020

Vibration analysis plays an essential role to enhance the design of the vehicle, related to its comfort and safety level. It is useful to determine the relations between the road profile or its characteristics to the particular properties of vehicles and evaluate the dynamic response to the applied road profile. During the design stage, the simulation of vehicle suspension requires an input of road surface for the initial dynamic load. Therefore, an artificial road profile, created according to a specific methodology, is a key to overall research success. It is possible to generate an artificial road profile using several mathematical methods. This paper is dedicated to analyzing and comparing the usability and ISO-compatibility of three methods: White noise filtration, sinusoidal approximation, and moving average of white noise. Furthermore, we modified the sinusoidal approximation, additionally using a windowing function, thus removing sharp jumps in a generated road profile. Each analyzed method has its advantages and disadvantages, therefore, proper choice in profile generation was a goal of the provided analysis. We defined that the moving average of white noise filtration method has the highest implementation perspectives due to the best compliance to the desired ISO-defined road profile shape and independence from simulation velocity.
Interferon-α2b Treatment for COVID-19 Is Associated with Improvements in Lung Abnormalities
Authors: Zhou Qiong , MacArthur Michael , He Xinliang , Wei Xiaoshan , Zarin Payam , Hanna Bola , Wang Zi-Hao , Xiang Xuan , Fish Eleanor
Published: December 2020

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes coronavirus disease 2019 (COVID-19), a lung disease that may progress to systemic organ involvement and in some cases, death. The identification of the earliest predictors of progressive lung disease would allow for therapeutic intervention in those cases. In an earlier clinical study, individuals with moderate COVID-19 were treated with either arbidol (ARB) or inhaled interferon (IFN)-α2b +/−ARB. IFN treatment resulted in accelerated viral clearance from the upper airways and in a reduction in the circulating levels of the inflammatory biomarkers IL-6 and C-reactive protein (CRP). We have extended the analysis of this study cohort to determine whether IFN treatment had a direct effect on virus-induced lung abnormalities and also to ascertain whether any clinical or immune parameters are associated with worsening of lung abnormalities. Evidence is provided that IFN-α2b treatment limits the development of lung abnormalities associated with COVID-19, as assessed by CT images. Clinical predictors associated with worsening of lung abnormalities include low CD8+ T cell numbers, low levels of circulating albumin, high numbers of platelets, and higher levels of circulating interleukin (IL)-10, IL-6, and C-reactive protein (CRP). Notably, in this study cohort, IFN treatment resulted in a higher percentage of CD8+ T cells, lower tumor necrosis factor (TNF)-α levels and, as reported earlier, lower IL-6 levels. Independent of treatment, age and circulating levels of albumin and CRP emerged as the strongest predictors of the severity of lung abnormalities.
Plant-Based Drugs and Vaccines for COVID-19
Authors: Mahmood Nasir , Nasir Sarah Bushra , Hefferon Kathleen
Published: December 2020

The coronavirus SARS-CoV-2 has turned our own health and the world economy upside down. While several vaccine candidates are currently under development, antivirals with the potential to limit virus transmission or block infection are also being explored. Plant production platforms are being used to generate vaccines and antiviral proteins inexpensively and at mass scale. The following review discusses the biology and origins of the current coronavirus pandemic, and describes some of the conventional, synthetic, and plant-based approaches to address the challenge that it presents to our way of life.
Nano-TiO2 Phototoxicity in Fresh and Seawater: Daphnia magna and Artemia sp. as Proxies
Authors: Soler de la Vega Ana C. , Cruz-Alcalde Alberto , Sans Mazón Carmen , Barata Martí Carlos , Diaz-Cruz M. Silvia
Published: December 2020

Nowadays, the industry is quite commonly using nanoparticles of titanium dioxide (nTiO2) especially in sunscreens, due to its higher reflective index in comparison to micron size TiO2. Its high demand causes its widespread environmental occurrence, thus damaging the environment. The aquatic ecosystems are the most vulnerable to contamination by nTiO2. Like other engineered nanoparticles, nTiO2 has demonstrated generation of reactive oxygen species (ROS) and reactive halogen species (RHS) in the aquatic environment under UV radiation. This study investigated the toxicity of nTiO2 towards two aquatic indicator organisms, one from freshwater (Daphnia magna) and the other from seawater (Artemia sp.), under simulated solar radiation (SSR). Daphnia magna and Artemia sp. were co-exposed in 16 h SSR and 8 h darkness cycles to different concentrations of nTiO2. The estimated EC50 at 48 h for D. magna was 3.16 mg nTiO2/L, whereas for A. sp. no toxic effects were observed. When we exposed these two organisms simultaneously to 48 h of prolonged SSR using higher nTiO2 concentrations, EC50 values of 7.60 mg/L and 5.59 mg/L nTiO2 for D. magna and A. sp., respectively, were obtained. A complementary bioassay was carried out with A. sp., by exposing this organism to a mixture of nTiO2 and organic UV filters (benzophenone 3 (oxybenzone, BP3), octocrylene (OC), and ethyl 4-aminobenzoate (EtPABA)), and then exposed to SSR. The results suggested that nTiO2 could potentially have negative impacts on these organisms, also this work outlines the different characteristics and interactions that may contribute to the mechanisms of environmental (in salted and freshwater) phototoxicity of nTiO2 and UV radiation, besides their interaction with organic compounds.
Using 2D HEC-RAS Modeling and Embankment Dam Break Scenario for Assessing the Flood Control Capacity of a Multi-Reservoir System (NE Romania)
Authors: Urzică Andrei , Mihu-Pintilie Alin , Stoleriu Cristian Constantin , Cîmpianu Cătălin Ioan , Huţanu Elena , Pricop Claudiu Ionuţ , Grozavu Adrian
Published: December 2020

Using hydraulic modeling techniques (e.g., one-dimensional/two-dimensional (1D/2D) hydraulic modeling, dam break scenarios) for extracting the flood settings is an important aspect of any action plan for dam failure (APDF) and flood mitigation strategy. For example, the flood hydraulic models and dam break scenario generated based on light detection and ranging (LiDAR)-derived digital elevation models (DEMs) and processed in the dedicated geographic information systems (GIS) and hydraulic modeling software (e.g., HEC-RAS—Hydrologic Engineering Center River Analysis System, developed by USACE HEC, Davis, CA, USA) can improve the flood hazard maps in case of potentially embankment dam failure. In this study, we develop a small-scale conceptual approach using 2D HEC-RAS software according to the three embankment dam break scenarios, LiDAR data (0.5 m spatial resolution), and 2D hydraulic modeling for the Başeu multi-reservoir system which belongs to the Başeu River (NE Romania) including R1—Cal Alb reservoir, R2—Movileni reservoirs, R3—Tătărăşeni reservoirs, R4—Negreni reservoirs, and R5—Hăneşti reservoirs. In order to test the flood control capacity of the Bașeu multi-reservoir system, the Cal Alb (R1) dam break scenario (piping failure) was taken into account. Three 2D stream flow modeling configurations based on R1 inflow rate with a 1% (100 year), 0.5% (500 year), and 0.1% (1000 year) recurrence interval and the water volume which can be accumulated with that specific inflow rate (1% = 10.19 × 106 m3; 0.5% = 12.39 × 106 m3; 0.1% = 17.35 × 106 m3) were computed. The potential flood wave impact was achieved on the basis of different flood severity maps (e.g., flood extent, flood depth, flood velocity, flood hazard) generated for each recurrence interval scenario and highlighted within the built-up area of 27 settlements (S1–S27) located downstream of R1. The results showed that the multi-reservoir system of Bașeu River has an important role in flood mitigation and contributes to the APDF in the context of climate change and the intensification of hydrological hazard manifestation in northeastern Romania.
Comparing Trace Elements (As, Cu, Ni, Pb, and Zn) in Soils and Surface Waters among Montane, Upland Watersheds and Lowland, Urban Watersheds in New England, USA
Authors: Richardson Justin B.
Published: December 2020

Trace element biogeochemistry from soils to rivers is important for toxicity to aquatic ecosystems. The objective of this study was to determine whether trace element exports in contrasting watersheds are controlled by their abundance in soil, current land uses in the watershed, or geologic processes. Upland soils and river water samples were collected throughout the Deerfield watershed in southern Vermont and western Massachusetts and in the Quinebaug and Shetucket watersheds of eastern Connecticut. Soil concentrations were only an important predictor for dissolved Fe export, but no other trace element. Soil pH was not correlated with normalized dissolved exports of trace elements, but DOC was correlated with normalized dissolved Pb and Ni exports. The limited spatial and depth of soil sampling may have contributed to the poor correlation. Surprisingly, linear regressions and principal component analysis showed that human development was associated with higher soil trace metal concentrations but not significantly correlated with dissolved trace elements export. Instead, forest abundance was a strong predictor for lower Cu, Pb, and Zn soil concentrations and lower As, Fe, Ni and Pb dissolved exports across the watersheds. Dissolved exports of Al, K, and Si suggest that enhanced mineral dissolution in the montane watersheds was likely an important factor for matching or exceeding normalized pollutant trace element exports in more urbanized watersheds. Further studies are needed to evaluate subsurface/hyporheic controls as well as soil–surface water interface to quantify exchange and transport.
Pressure Fluctuations in the Spatial Hydraulic Jump in Stilling Basins with Different Expansion Ratio
Authors: Hassanpour Nasrin , Hosseinzadeh Dalir Ali , Bayon Arnau , Abdollahpour Milad
Published: December 2020

Pressure fluctuations are a key issue in hydraulic engineering. However, despite the large number of studies on the topic, their role in spatial hydraulic jumps is not yet fully understood. The results herein shed light on the formation of eddies and the derived pressure fluctuations in stilling basins with different expansion ratios. Laboratory tests are conducted in a horizontal rectangular flume with 0.5 m width and 10 m length. The range of approaching Froude numbers spans from 6.4 to 12.5 and the channel expansion ratios are 0.4, 0.6, 0.8, and 1. The effects of approaching flow conditions and expansion ratios are thoroughly analyzed, focusing on the dimensionless standard deviation of pressure fluctuations and extreme pressure fluctuations. The results reveal that these variables show a clear dependence on the Froude number and the distance to the hydraulic jump toe. The maximum values of extreme pressure fluctuations occur in the range 0.609<X<3.385, where X is dimensionless distance from the toe of the hydraulic jump, which makes it highly advisable to reinforce the bed of stilling basins within this range.
Macroscopic Lattice Boltzmann Method
Authors: Zhou Jian Guo
Published: December 2020

The lattice Boltzmann method (LBM) is a highly simplified model for fluid flows using a few limited fictitious particles. It has been developed into a very efficient and flexible alternative numerical method in computational physics, demonstrating its great power and potential for resolving more and more challenging physical problems in science and engineering covering a wide range of disciplines such as physics, chemistry, biology, material science and image analysis. The LBM is implemented through the two routine steps of streaming and collision using the three parameters of the lattice size, particle speed and collision operator. A fundamental question is if the two steps are integral to the method or if the three parameters can be reduced to one for a minimal lattice Boltzmann method. In this paper, it is shown that the collision step can be removed and the standard LBM can be reformulated into a simple macroscopic lattice Boltzmann method (MacLAB). This model relies on macroscopic physical variables only and is completely defined by one basic parameter of the lattice size δx, bringing the LBM into a precise “lattice” Boltzmann method. The viscous effect on flows is naturally embedded through the particle speed, making it an ideal automatic simulator for fluid flows. Three additional advantages compared to the existing LBMs are that: (i) physical variables can directly be retained as the boundary conditions; (ii) much less computational memory is required; and (iii) the model is unconditionally stable. The findings are demonstrated and confirmed with numerical tests including flows that are independent of and dependent on fluid viscosity, 2D and 3D cavity flows and an unsteady Taylor–Green vortex flow. This provides an efficient and powerful model for resolving physical problems in various disciplines of science and engineering.
Assessing Reservoir Performance under Climate Change. When Is It Going to Be Too Late If Current Water Management Is Not Changed?
Authors: Chadwick Cristián , Gironás Jorge , Barría Pilar , Vicuña Sebastián , Meza Francisco
Published: December 2020

Climate change is modifying the way we design and operate water infrastructure, including reservoirs. A particular issue is that current infrastructure and reservoir management rules will likely operate under changing conditions different to those used in their design. Thus, there is a big need to identify the obsolescence of current operation rules under climate change, without compromising the proper treatment of uncertainty. Acknowledging that decision making benefits from the scientific knowledge, mainly when presented in a simple and easy-to-understand manner, such identification—and the corresponding uncertainty—must be clearly described and communicated. This paper presents a methodology to identify, in a simple and useful way, the time when current reservoir operation rules fail under changing climate by properly treating and presenting its aleatory and epistemic uncertainties and showing its deep uncertainty. For this purpose, we use a reliability–resilience–vulnerability framework with a General Circulation Models (GCM) ensemble under the four Representative Concentration Pathways (RCP) scenarios to compare the historical and future long-term reservoir system performances under its current operation rule in the Limarí basin, Chile, as a case study. The results include percentiles that define the uncertainty range, showing that during the 21st century there are significant changes at the time-based reliability by the 2030s, resilience between the 2030s and 2040s, volume-based reliability by the 2080s, and the maximum failure by the 2070s. Overall, this approach allows the identification of the timing of systematic failures in the performance of water systems given a certain performance threshold, which contributes to the planning, prioritization and implementation timing of adaptation alternatives.
Optimization of an Autochthonous Bacterial Consortium Obtained from Beach Sediments for Bioremediation of Petroleum Hydrocarbons
Authors: Perdigão Rafaela , Almeida C. Marisa R. , Santos Filipa , Carvalho Maria F. , Mucha Ana P.
Published: December 2020

Oil spill pollution remains a serious concern in marine environments and the development of effective oil bioremediation techniques are vital. This work is aimed at developing an autochthonous hydrocarbon-degrading consortium with bacterial strains with high potential for hydrocarbons degradation, optimizing first the growth conditions for the consortium, and then testing its hydrocarbon-degrading performance in microcosm bioremediation experiments. Bacterial strains, previously isolated from a sediment and cryopreserved in a georeferenced microbial bank, belonged to the genera Pseudomonas, Rhodococcus and Acinetobacter. Microcosms were assembled with natural seawater and petroleum, for testing: natural attenuation (NA); biostimulation (BS) (nutrients addition); bioaugmentation with inoculum pre-grown in petroleum (BA/P) and bioaugmentation with inoculum pre-grown in acetate (BA/A). After 15 days, a clear blending of petroleum with seawater was observed in BS, BA/P and BA/A but not in NA. Acetate was the best substrate for consortium growth. BA/A showed the highest hydrocarbons degradation (66%). All bacterial strains added as inoculum were recovered at the end of the experiment. This study provides an insight into the capacity of autochthonous communities to degrade hydrocarbons and on the use of alternative carbon sources for bacterial biomass growth for the development of bioremediation products to respond to oil spills.
Contrasting the Optical Characterization of Dissolved Organic Matter in Water and Sediment from a Nascent River-Type Lake (Chongqing, China)
Authors: Niu Fengxia , Ji Fangying , Zhang Qian , Shen Qiushi
Published: December 2020

Carbon cycling in rivers is altered by the creation of impoundments through dam construction. This paper seeks to identify the source and composition of dissolved organic matter (DOM) in both water and sediment in Lake Longjing by contrasting the optical characterization of DOM. By comparing the dissolved organic carbon (DOC) concentrations, we show that the sediment (53.7 ± 16.6 mg/L) acts as a DOC source to the overlying water (23.1 ± 1.4 mg/L). The estimated DOC flux in the original reservoir region (88.3 mg m−2 d−1) is higher than that in the newly submerged region (26 mg m−2 d−1), whereas the latter has larger contribution to the DOC annual load because of its larger sediment area. Spectroscopic analysis suggested that pore waters had higher aromaticity and lower proportion of fresh DOM than those in surface waters and benthic overlying waters. Through Parallel Factor Analysis, four fluorescent components were identified, i.e., two terrestrial humic-like components, one protein-like, and one microbial humic-like. Spearman correlation and Non-Metric-Multidimensional Scaling (NMDS) analysis manifested that fluorescent DOM in surface sediments is mainly contributed by autochthonous source, the others by allochthonous source. Due to the high sensitivity of the fluorescent intensity of the protein-like component, it is a useful indicator to reveal the changes of source of DOM.
eNaBLe, an On-Line Tool to Evaluate Natural Background Levels in Groundwater Bodies
Authors: Parrone Daniele , Frollini Eleonora , Preziosi Elisabetta , Ghergo Stefano
Published: December 2020

Inorganic compounds in groundwater may derive from both natural processes and anthropogenic activities. The assessment of natural background levels (NBLs) is often useful to distinguish these sources. The approaches for the NBLs assessment can be classified as geochemical (e.g., the well-known pre-selection method) or statistical, the latter involving the application of statistical procedures to separate natural and anthropogenic populations. National Guidelines for the NBLs assessment in groundwater have been published in Italy (ISPRA 155/2017), based mainly on the pre-selection method. The Guidelines propose different assessment paths according to the sample size in spatial/temporal dimension and the type of the distribution of the pre-selected dataset, taking also into account the redox conditions of the groundwater body. The obtained NBLs are labelled with a different confidence level in function of number of total observations/monitoring sites, extension of groundwater body and aquifer type (confined or unconfined). To support the implementation of the Guidelines, the on-line tool evaluation of natural background levels (eNaBLe), written in PHP and using MySQL as DBMS (DataBase Management System), has been developed. The main goal of this paper is to describe the functioning of eNaBLe and test the tool on a case study in central Italy. We calculated the NBLs of As, F, Fe and Mn in the southern portion of the Mounts Vulsini groundwater body, within the volcanic province of Latium (Central Italy), also separating the reducing and oxidizing facies. Specific results aside, this study allowed to verify the functioning and possible improvements of the online tool and to identify some criticalities in the procedure NBLs assessment at the groundwater body scale