bluuebunny/crossref_metadata_2025 huggingface dataset:
Key Drivers and Skills Needed for Innovative Companies Focused on Sustainability
Authors: Grigorescu Adriana , Maer-Matei Monica Mihaela , Mocanu Cristina , Zamfir Ana-Maria
Published: December 2019

Sustainable innovation at a company level drives economic, environmental and social improvement at a national level. Recent evidence has shown that businesses have increased the managerial attention and investments dedicated to sustainability. This paper aims to identify the most important drivers supporting companies to develop innovation activities oriented towards making the business models more sustainable. We explore microdata from the 2016 Innobarometer “EU Business Innovation Trends” (Flash Eurobarometer 433), covering 8635 companies from 29 countries. Using statistical classification methods, we identify the most important factors that are related to innovation activities that have the potential to shape the efficiency of raw material usage and environmental protection. The most relevant factors emphasized by our analysis are: innovation performance of the country (innovation), percentage of the company turnover invested in innovation activities, percentage of total turnover invested in acquisition of machines, equipment, software or licenses, percentage of total turnover invested in company reputation and branding, including web design, percentage of total turnover invested in software development.. Also, our analysis highlights the skills that are needed the most by companies in order to support their innovation activities targeting sustainability. Our results are useful for better understanding the attention that is given to sustainability by innovative companies, and what the main factors that boost innovation dedicated to sustainability are.
Classifying Dams for Environmental Flow Implementation in China
Authors: Chen Ang , Wu Miao , McClain Michael E.
Published: December 2019

The implementation of environmental flows is of the utmost importance for ecosystem protection and restoration in dammed rivers. A key challenge in optimizing dam regulation is the uncertainty of the ecohydrology relationship between flow release and ecological response. In the present paper, we develop a framework of dam classification to organize the categories of the ecohydrology relationship for implementing environmental flows. Dams are classified from three major categories that differ in dam properties, hydrological alteration, and downstream hydrobiological diversities based on the relationship of hydrology and ecology. Finally, 773 dams in China are screened and ranked into four classes involving a great diversity of environmental flow components. A classification of dams that utilizes the implementation of environmental flows is presented. (1) Class 1 includes dams with rare and endangered fish species in the downstream. It is the category with the highest priority for environmental flow releases and regulation, requiring continuous flow and flood pulse components for fish spawning and migration. (2) Class 2 includes dams with significant hydrological alteration in the downstream. It is the category with second priority for environmental flow releases and regulation, requiring natural hydrological regimes simulation or complete flow component recovery for optimizing the flow duration curve and mitigating adverse impacts of dam operation. (3) Class 3 includes dams with a high degree of regulation where there is urgency for environmental flow releases and regulation, requiring that minimum flow is guaranteed by cascade reservoir regulation. (4) Class 4 includes dams with a low degree of regulation where there is less urgency for environmental flow releases and regulation. This classification method is important for future research, including environmental flow release regulation and the effectiveness evaluation of environmental flow adaptive management. It will be useful for guiding the implementation of environmental flows.
Channel Structure Strategies of Supply Chains with Varying Green Cost and Governmental Interventions
Authors: Yang Deyan , Wang Jinyong , Song Dongping
Published: December 2019

Environmental concerns make enterprises pay more attention to green manufacturing. The emerging green supply chain inevitably will compete with the traditional supply chain. In order to evaluate the competitiveness of supply chains and the impact on channel structure strategy, we develop four game models for two competing supply chains according to their channel structure strategies. Green marginal manufacturing cost, demand sensitivity of green level, and governmental interventions are considered. We study how retail prices, green levels, and profits are influenced by channel structure choice and governmental interventions. Analytical results indicate that the substitutability of products affects channel structure strategy. When the substitutability of products is relatively low, centralization–centralization is the unique Nash equilibrium. However, when the substitutability of products is relatively high, both centralization–centralization and decentralization–decentralization are the Nash equilibriums. Centralization–centralization is a prisoner dilemma, while decentralization–decentralization can make the green supply chain achieve optimal profit. Then, the green marginal manufacturing cost and demand sensitivities of the green level play important but different roles in channel structure strategy of the competing supply chains. Further, whether Nash equilibriums are the optimal strategy depends on governmental intervention. Relatively severe governmental intervention might realize a relatively higher green level, but may not always achieve the lowest retail price for the green supply chain. However, a relatively moderate governmental intervention might achieve a relatively lower green level.
Smart Techniques in Urban Planning: An Insight to Ruled-Based Design
Authors: Pisano Carlo , De Luca Giuseppe , Shirvani Dastgerdi Ahmadreza
Published: December 2019

In the last decades, the ideology of managing the city form and performance through pre-determined plans has gradually lost its validity. Some contemporary urban planning theories suggest the application of smart design techniques for managing urban complexity. However, the proposed approach has partially been experienced in practice, and more research on how to integrate them into urban planning is needed. This study aims to present an insight into the rule-based design as a smart design technique for a shift from pre-determined urban plans to design rules. The methodology is based on a comparative analysis between the experiments of some cases in the north of Europe. Research findings highlight that the capacity to deliver variety with harmony, the distinction between the roles of code writer and building designer, the potential to support the implementation process and to prescribe specific qualities, both for the spatial and organizational purposes, are significant factors for the integration of smart design techniques to urban planning.
Energy Recovery from Wastewater: A Study on Heating and Cooling of a Multipurpose Building with Sewage-Reclaimed Heat Energy
Authors: Cecconet Daniele , Raček Jakub , Callegari Arianna , Hlavínek Petr
Published: December 2019

To achieve technically-feasible and socially-desirable sustainable management of urban areas, new paradigms have been developed to enhance the sustainability of water and its resources in modern cities. Wastewater is no longer seen as a wasted resource, but rather, as a mining ground from which to obtain valuable chemicals and energy; for example, heat energy, which is often neglected, can be recovered from wastewater for different purposes. In this work, we analyze the design and application of energy recovery from wastewater for heating and cooling a building in Brno (Czech Republic) by means of heat exchangers and pumps. The temperature and the flow rate of the wastewater flowing in a sewer located in the proximity of the building were monitored for a one-year period, and the energy requirement for the building was calculated as 957 MWh per year. Two options were evaluated: heating and cooling using a conventional system (connected to the local grid), and heat recovery from wastewater using heat exchangers and coupled heat pumps. The analysis of the scenarios suggested that the solution based on heat recovery from wastewater was more feasible, showing a 59% decrease in energy consumption compared to the conventional solution (respectively, 259,151 kWh and 620,475 kWh per year). The impact of heat recovery from wastewater on the kinetics of the wastewater resource recovery facility was evaluated, showing a negligible impact in both summer (increase of 0.045 °C) and winter conditions (decrease of 0.056 °C).
Attitudes toward Residential Trees and Awareness of Tree Services and Disservices in a Tropical City
Authors: Olivero-Lora Sofia , Meléndez-Ackerman Elvia , Santiago Luis , Santiago-Bartolomei Raúl , García-Montiel Diana
Published: December 2019

Attitudes toward urban residential trees and awareness of their ecosystem services and disservices may play an important role in management decisions of private residential green spaces with important consequences to urban sustainability. In 2011, 397 household surveys were conducted in six locations of the Río Piedras Watershed (San Juan, Puerto Rico) to evaluate residents’ attitudes toward residential and neighborhood trees and their association with household socio-demographic factors, how awareness of services and disservices relate to the spatial proximity of trees (home versus neighborhood), and whether attitudes are associated with yard management (tree abundance). Most residents self-reported positive attitudes toward trees in general and these appeared to be more frequent than self-reported negative attitudes. Respondents recognized more tree services (emphasizing shade, lower temperature, food, and ornamental/aesthetics) and fewer disservices (emphasizing maintenance hardship, property damage, and power line obstruction). Not all tree services and disservices were equally recognized, and differences in the spatial context of trees and residents may contribute to the variation in residents’ awareness of tree ecosystem services or disservices. Variation in positive attitudes partially explained the current variation in yard tree abundance, along with residents’ age, housing tenure, yard size, and watershed location. Results have direct implications for urban forest planning and management in residential contexts.
Geodesign Process Analytics: Focus on Design as a Process and Its Outcomes
Authors: Cocco Chiara , Rezende Freitas Christian , Mourão Moura Ana Clara , Campagna Michele
Published: December 2019

This paper argues that the opportunities offered by currently available collaborative Planning Support Systems (PSS) are useful not only for applying a systems approach and coordinating actors in the planning process, but also for tracking the evolution of design alternatives toward a final plan. The availability of process log-data in the latest PSS opens new paths for understanding (geo)design dynamics. With the aim of taking full advantage of this new data source, a novel Geodesign Process Analytics is described in detail from log-data extraction and pre-processing methods and tools to the development of the set of spatial, performance, temporal and design evolution indicators. The study also demonstrates how the proposed measures are appropriate for display in a dynamic dashboard, making available a real-time process analysis tool to the team coordinators, thus supporting their leading role in facilitating the geodesign process. The research assumptions were tested using the Geodesignhub PSS and data from a geodesign study developed within the International Geodesign Collaboration.
Performance Analysis and Optimization of Central Receiver Solar Thermal Power Plants for Utility Scale Power Generation
Authors: R. P. Praveen
Published: December 2019

The paper puts forth the design, performance analysis, and optimization of a 100 MWe central receiver solar thermal power plant with thermal energy storage capability, which can be utilized effectively to meet the renewable energy targets of the Kingdom of Saudi Arabia (KSA). In this paper, three representative sites in KSA are selected for analysis as these sites experience an annual average direct normal irradiance (DNI) of more than 5.5 kWh/m2/day. The optimization approach presented in this work aims to arrive at the best possible design parameters that suit a particular location in accordance with its DNI profile. From the analysis, an annual energy of 559.61 GWh can be generated in Yanbu with eight hours of thermal energy storage, 18.19% plant efficiency, and a capacity factor of 61.1%. The central receiver plant in Abha would be able to offer an annual energy of 536.31 GWh with the highest plant efficiency of 18.97% and a capacity factor of 60.7%. The performance of the proposed design in the two locations of Yanbu and Abha fares better when compared to the operational plant data of central receiver plant in Crescent Dunes. Based on the findings, the proposed 100 MWe central receiver Solar thermal power plants can be effectively implemented in KSA to meet the energy demands of the region.
A Balance Interface Design and Instant Image-based Traffic Assistant Agent Based on GPS and Linked Open Data Technology
Authors: Chen Fu-Hsien , Yang Sheng-Yuan
Published: December 2019

Taiwan is a highly informational country, and a robust traffic network is not only critical to the national economy, but is also an important infrastructure for economic development. This paper aims to integrate government open data and global positioning system (GPS) technology to build an instant image-based traffic assistant agent with user-friendly interfaces, thus providing more convenient real-time traffic information for users and relevant government units. The proposed system is expected to overcome the difficulty of accurately distinguishing traffic information and to solve the problem of some road sections not providing instant information. Taking the New Taipei City Government traffic open data as an example, the proposed system can display information pages at an optimal size on smartphones and other computer devices, and integrate database analysis to instantly view traffic information. Users can enter the system without downloading the application and can access the cross-platform services using device browsers. The proposed system also provides a user reporting mechanism, which informs vehicle drivers on congested road sections about road conditions. Comparison and analysis of the system with similar applications shows that although they have similar functions, the proposed system offers more practicability, better information accessibility, excellent user experience, and approximately the optimal balance (a kind of symmetry) of the important items of the interface design.
Existence of Small-Energy Solutions to Nonlocal Schrödinger-Type Equations for Integrodifferential Operators in ℝN
Authors: Lee Jun Ik , Kim Yun-Ho , Lee Jongrak
Published: December 2019

We are concerned with the following elliptic equations: ( − Δ ) p , K s u + V ( x ) | u | p − 2 u = λ f ( x , u ) in R N , where ( − Δ ) p , K s is the nonlocal integrodifferential equation with 0 < s < 1 < p < + ∞ , s p < N the potential function V : R N → ( 0 , ∞ ) is continuous, and f : R N × R → R satisfies a Carathéodory condition. The present paper is devoted to the study of the L ∞ -bound of solutions to the above problem by employing De Giorgi’s iteration method and the localization method. Using this, we provide a sequence of infinitely many small-energy solutions whose L ∞ -norms converge to zero. The main tools were the modified functional method and the dual version of the fountain theorem, which is a generalization of the symmetric mountain-pass theorem.
Effects of Machine Learning Approach in Flow-Based Anomaly Detection on Software-Defined Networking
Authors: Dey Samrat Kumar , Rahman Md. Mahbubur
Published: December 2019

Recent advancements in software-defined networking (SDN) make it possible to overcome the management challenges of traditional networks by logically centralizing the control plane and decoupling it from the forwarding plane. Through a symmetric and centralized controller, SDN can prevent security breaches, but it can also bring in new threats and vulnerabilities. The central controller can be a single point of failure. Hence, flow-based anomaly detection system in OpenFlow Controller can secure SDN to a great extent. In this research, we investigated two different approaches of flow-based intrusion detection system in OpenFlow Controller. The first of which is based on machine-learning algorithm where NSL-KDD dataset with feature selection ensures the accuracy of 82% with random forest classifier using the gain ratio feature selection evaluator. In the later phase, the second approach is combined with a deep neural network (DNN)-based intrusion detection system based on gated recurrent unit-long short-term memory (GRU-LSTM) where we used a suitable ANOVA F-Test and recursive feature elimination selection method to boost classifier output and achieve an accuracy of 88%. Substantial experiments with comparative analysis clearly show that, deep learning would be a better choice for intrusion detection in OpenFlow Controller.
Identities and Computation Formulas for Combinatorial Numbers Including Negative Order Changhee Polynomials
Authors: Kim Daeyeoul , Simsek Yilmaz , So Ji Suk
Published: December 2019

The purpose of this paper is to construct generating functions for negative order Changhee numbers and polynomials. Using these generating functions with their functional equation, we prove computation formulas for combinatorial numbers and polynomials. These formulas include Euler numbers and polynomials of higher order, Stirling numbers, and negative order Changhee numbers and polynomials. We also give some properties of these numbers and polynomials with their generating functions. Moreover, we give relations among Changhee numbers and polynomials of negative order, combinatorial numbers and polynomials and Bernoulli numbers of the second kind. Finally, we give a partial derivative of an equation for generating functions for Changhee numbers and polynomials of negative order. Using these differential equations, we derive recurrence relations, differential and integral formulas for these numbers and polynomials. We also give p-adic integrals representations for negative order Changhee polynomials including Changhee numbers and Deahee numbers.
Lie Symmetry Analysis of Burgers Equation and the Euler Equation on a Time Scale
Authors: Liu Mingshuo , Dong Huanhe , Fang Yong , Zhang Yong
Published: December 2019

As a powerful tool that can be used to solve both continuous and discrete equations, the Lie symmetry analysis of dynamical systems on a time scale is investigated. Applying the method to the Burgers equation and Euler equation, we get the symmetry of the equation and single parameter groups on a time scale. Some group invariant solutions in explicit form for the traffic flow model simulated by a Burgers equation and Euler equation with a Coriolis force on a time scale are studied.
Real-Time Control for the EHU Stellarator
Authors: Garrido Izaskun , Maseda Javier , Martija Itziar , Garrido Aitor J.
Published: December 2019

At present, two main magnetic confinement fusion devices exist: tokamaks and stellarators. Moreover, stellarators have been demonstrated to be a good alternative to tokamaks, due to their ability to operate in continuous mode, which eventually translates into a higher commercial profitability. In stellarators, the magnetic confinement of the plasma is achieved exclusively by the coils, thus no electric current through the plasma is needed. In particular, this article presents the Columbia Non-Neutral Torus stellarator that is located in the Automatic Control Group of Euskal Herriko Unibertsitatea (EHU). This EHU stellarator maintains symmetry in its structure due to the topology of the mesh that is formed by its coils. A cornerstone of future fusion reactors is to obtain real-time control that enables a sustained reaction. In this article, a control-oriented model for the installed magnetic confinement coils is presented. The model is based on matrices that preserve symmetry, which is defined from physical principles and then validated by different sets of experimental data. Then, based on this model, a novel predictive control suited to this particular model with symmetric objective function is implemented in the numerical simulations, and its response is compared to that of traditional controllers. Finally, this control is implemented in a real plant and the satisfactory experiment results provide validation of both the numerical model and proposed controller.
Use of Nonconventional Dispersion Measures to Improve the Efficiency of Ratio-Type Estimators of Variance in the Presence of Outliers
Authors: Naz Farah , Nawaz Tahir , Pang Tianxiao , Abid Muhammad
Published: December 2019

The use of auxiliary information in survey sampling to enhance the efficiency of the estimators of population parameters is a common phenomenon. Generally, the ratio and regression estimators are developed by using the known information on conventional parameters of the auxiliary variables, such as variance, coefficient of variation, coefficient of skewness, coefficient of kurtosis, or correlation between the study and auxiliary variable. The efficiency of these estimators is dubious in the presence of outliers in the data and a nonsymmetrical population. This study presents improved variance estimators under simple random sampling without replacement with the assumption that the information on some nonconventional dispersion measures of the auxiliary variable is readily available. These auxiliary variables can be the inter-decile range, sample inter-quartile range, probability-weighted moment estimator, Gini mean difference estimator, Downton’s estimator, median absolute deviation from the median, and so forth. The algebraic expressions for the bias and mean square error of the proposed estimators are obtained and the efficiency conditions are derived to compare with the existing estimators. The percentage relative efficiencies are used to numerically compare the results of the proposed estimators with the existing estimators by using real datasets, indicating the supremacy of the suggested estimators.
Parametric Jensen-Shannon Statistical Complexity and Its Applications on Full-Scale Compartment Fire Data
Authors: Mitroi-Symeonidis Flavia-Corina , Anghel Ion , Minculete Nicușor
Published: December 2019

The order/disorder characteristics of a compartment fire are researched based on experimental data. From our analysis performed by new, pioneering methods, we claim that the parametric Jensen-Shannon complexity can be successfully used to detect unusual data, and that one can use it also as a means to perform relevant analysis of fire experiments. Thoroughly comparing the performance of different algorithms (known as permutation entropy and two-length permutation entropy) to extract the probability distribution is an essential step. We discuss some of the theoretical assumptions behind each step and stress that the role of the parameter is to fine-tune the results of the Jensen-Shannon statistical complexity. Note that the Jensen-Shannon statistical complexity is symmetric, while its parametric version displays a symmetric duality due to the a priori probabilities used.
Solitonic Fixed Point Attractors in the Complex Ginzburg–Landau Equation for Associative Memories
Authors: Pyrkov Alexey N. , Byrnes Tim , Cherny Valentin V.
Published: December 2019

It was recently shown that the nonlinear Schrodinger equation with a simplified dissipative perturbation features a zero-velocity solitonic solution of non-zero amplitude which can be used in analogy to attractors of Hopfield’s associative memory. In this work, we consider a more complex dissipative perturbation adding the effect of two-photon absorption and the quintic gain/loss effects that yields the complex Ginzburg–Landau equation (CGLE). We construct a perturbation theory for the CGLE with a small dissipative perturbation, define the behavior of the solitonic solutions with parameters of the system and compare the solution with numerical simulations of the CGLE. We show, in a similar way to the nonlinear Schrodinger equation with a simplified dissipation term, a zero-velocity solitonic solution of non-zero amplitude appears as an attractor for the CGLE. In this case, the amplitude and velocity of the solitonic fixed point attractor does not depend on the quintic gain/loss effects. Furthermore, the effect of two-photon absorption leads to an increase in the strength of the solitonic fixed point attractor.
Research on the Detection Method of Implicit Self Symmetry in a High-Level Semantic Model
Authors: Wang Chao
Published: December 2019

In order to improve the accuracy of semantic model intrinsic detection, a skeleton-based high-level semantic model intrinsic self-symmetry detection method is proposed. The semantic analysis of the model set is realized by the uniform segmentation of the model within the same style, the component correspondence of the model between different styles, and the shape content clustering. Based on the results of clustering analysis, for a given three-dimensional (3D) point cloud model, according to the curve skeleton, the skeleton point pairs reflecting the symmetry between the model surface points are obtained by the election method, and the symmetry is extended to the model surface vertices according to these skeleton point pairs. With the help of skeleton, the symmetry of the point cloud model is obtained, and then the symmetry region of point cloud model is obtained by the symmetric correspondence matrix and spectrum method, so as to realize the intrinsic symmetry detection of the model. The experimental results show that the proposed method has the advantages of less time, high accuracy, and high reliability.
MICKEY 2.0.85: A Secure and Lighter MICKEY 2.0 Cipher Variant with Improved Power Consumption for Smaller Devices in the IoT
Authors: Alamer Ahmed , Soh Ben , Brumbaugh David E.
Published: December 2019

Lightweight stream ciphers have attracted significant attention in the last two decades due to their security implementations in small devices with limited hardware. With low-power computation abilities, these devices consume less power, thus reducing costs. New directions in ultra-lightweight cryptosystem design include optimizing lightweight cryptosystems to work with a low number of gate equivalents (GEs); without affecting security, these designs consume less power via scaled-down versions of the Mutual Irregular Clocking KEYstream generator—version 2-(MICKEY 2.0) cipher. This study aims to obtain a scaled-down version of the MICKEY 2.0 cipher by modifying its internal state design via reducing shift registers and modifying the controlling bit positions to assure the ciphers’ pseudo-randomness. We measured these changes using the National Institutes of Standards and Testing (NIST) test suites, investigating the speed and power consumption of the proposed scaled-down version named MICKEY 2.0.85. The (85) refers to the new modified bit-lengths of each MICKEY 2.0 register. The results show that it is faster, requires less power, and needs fewer GEs. The proposed variant will enhance the security of applications, such asRadio-frequency identification (RFID) technology, sensor networks, and in Internet of things (IoT) in general. It also will enhance research on the optimization of existing lightweight cryptosystems.
Research on Spectrum Optimization Technology for a Wireless Communication System
Authors: Liu Mingxin , Xue Wei , Jia Peisong , Makarov Sergey B. , Li Beiming
Published: December 2019

In this study, the principle of minimum spectral energy leakage is applied, and the mathematical model is also established by the general function through adding different constraints. To allow the target baseband signal to have a high-quality time-domain representation, it is assumed that the baseband signal is an even function. The time-domain waveform has symmetry about the y-axis, and the objective function is obtained by Fourier series approximation. The frequency-domain characteristics of the baseband signals are obtained by adding the energy limitation condition and the boundary restriction condition. Limit a point at the appropriate position of the main lobe of the normalized energy spectral density function, and at the same time, limit the appropriate point at the first side lobe. The changes of the points modified the whole characteristic of the frequency-domain. To more conveniently compare the characteristics of the signal under different constraints, according to the symmetry of the frequency-domain of the signal, the normalized energy spectrum main lobe energy ratio is defined as a parameter, and thereby the spectral performance of the signal is discriminated by the size of this parameter. Through comparative analysis, the signal with the frequency-domain restriction conditions added has a larger normalized energy spectrum main lobe energy ratio. With increasing roll-off factor n, the energy ratio of the main energy spectrum of the normalized spectrum increases accordingly, i.e., the energy leakage is effectively suppressed. The baseband signal can be considered more suitable as a modern wireless communication system and can be obtained by adding a suitable restriction condition and establishing a model with a general function.
Viscosity Approximation Methods for a General Variational Inequality System and Fixed Point Problems in Banach Spaces
Authors: Wang Yuanheng , Pan Chanjuan
Published: December 2019

In Banach spaces, we study the problem of solving a more general variational inequality system for an asymptotically non-expansive mapping. We give a new viscosity approximation scheme to find a common element. Some strong convergence theorems of the proposed iterative method are obtained. A numerical experiment is given to show the implementation and efficiency of our main theorem. Our results presented in this paper generalize and complement many recent ones.
Zearalenone Induces Endoplasmic Reticulum Stress and Modulates the Expression of Phase I/II Enzymes in Human Liver Cells
Authors: Yoon Jee Eun , Lee Kwang Yong , Seok Jin Sil , Cheng Wei Nee , Kwon Hyuk Cheol , Jeong Chang Hee , Han Sung Gu
Published: December 2019

Zearalenone (ZEN) is a mycotoxin produced by Fusarium species; however, its mechanisms of action in human livers have not been fully elucidated. Thus, we investigated the toxic mechanisms of ZEN in human liver cells. HepG2 cells were treated with ZEN (0–40 μg/mL) for up to 24 h. A significant decrease in cell viability was observed after treatment with 20 and 40 μg/mL of ZEN, including a significant increase in apoptosis and reactive oxygen species production. ZEN increased GRP78 and CHOP, and eIF2α phosphorylation, indicating ER stress; elevated transcription of the autophagy-associated genes, beclin1 and LC3, and translation of LC3; and increased phase I metabolism by increasing PXR and CYP3A4. The protein expression level of CYP3A4 was higher with ZEN treatment up to 20 μg/mL, but remained at the control level after treatment with 40 μg/mL ZEN. In phase II metabolism, Nrf2 activation and UGT1A expression were increased with ZEN treatment up to 20 μg/mL. Treating cells with an ER stress inhibitor alleviated ZEN-induced cell death and autophagy, and inhibited the expression of phase I/II enzymes. Overall, high ZEN concentrations can modulate the expression of phase I/II enzymes via ER stress and reduced protein levels in human liver cells.
Fumagillin, a Mycotoxin of Aspergillus fumigatus: Biosynthesis, Biological Activities, Detection, and Applications
Authors: Guruceaga Xabier , Perez-Cuesta Uxue , Abad-Diaz de Cerio Ana , Gonzalez Oskar , Alonso Rosa M. , Hernando Fernando Luis , Ramirez-Garcia Andoni , Rementeria Aitor
Published: December 2019

Fumagillin is a mycotoxin produced, above all, by the saprophytic filamentous fungus Aspergillus fumigatus. This mold is an opportunistic pathogen that can cause invasive aspergillosis, a disease that has high mortality rates linked to it. Its ability to adapt to environmental stresses through the production of secondary metabolites, including several mycotoxins (gliotoxin, fumagillin, pseurotin A, etc.) also seem to play an important role in causing these infections. Since the discovery of the A. fumigatus fumagillin in 1949, many studies have focused on this toxin and in this review we gather all the information currently available. First of all, the structural characteristics of this mycotoxin and the different methods developed for its determination are given in detail. Then, the biosynthetic gene cluster and the metabolic pathway involved in its production and regulation are explained. The activity of fumagillin on its target, the methionine aminopeptidase type 2 (MetAP2) enzyme, and the effects of blocking this enzyme in the host are also described. Finally, the applications that this toxin and its derivatives have in different fields, such as the treatment of cancer and its microsporicidal activity in the treatment of honeybee hive infections with Nosema spp., are reviewed. Therefore, this work offers a complete review of all the information currently related to the fumagillin mycotoxin secreted by A. fumigatus, important because of its role in the fungal infection process but also because it has many other applications, notably in beekeeping, the treatment of infectious diseases, and in oncology.
Potential of Matrix Metalloproteinase Inhibitors for the Treatment of Local Tissue Damage Induced by a Type P-I Snake Venom Metalloproteinase
Authors: Preciado Lina María , Pereañez Jaime Andrés , Comer Jeffrey
Published: December 2019

Snake bite envenoming is a public health problem that was recently included in the list of neglected tropical diseases of the World Health Organization. In the search of new therapies for the treatment of local tissue damage induced by snake venom metalloproteinases (SVMPs), we tested the inhibitory activity of peptidomimetic compounds designed as inhibitors of matrix metalloproteinases on the activities of the SVMP Batx-I, from Bothrops atrox venom. The evaluated compounds show great potential for the inhibition of Batx-I proteolytic, hemorrhagic and edema-forming activities, especially the compound CP471474, a peptidomimetic including a hydroxamate zinc binding group. Molecular dynamics simulations suggest that binding of this compound to the enzyme is mediated by the electrostatic interaction between the hydroxamate group and the zinc cofactor, as well as contacts, mainly hydrophobic, between the side chain of the compound and amino acids located in the substrate binding subsites S1 and S1 ′ . These results show that CP471474 constitutes a promising compound for the development of co-adjuvants to neutralize local tissue damage induced by snake venom metalloproteinases.
Herpesviruses and the Unfolded Protein Response
Authors: Johnston Benjamin P. , McCormick Craig
Published: December 2019

Herpesviruses usurp cellular stress responses to promote viral replication and avoid immune surveillance. The unfolded protein response (UPR) is a conserved stress response that is activated when the protein load in the ER exceeds folding capacity and misfolded proteins accumulate. The UPR aims to restore protein homeostasis through translational and transcriptional reprogramming; if homeostasis cannot be restored, the UPR switches from “helper” to “executioner”, triggering apoptosis. It is thought that the burst of herpesvirus glycoprotein synthesis during lytic replication causes ER stress, and that these viruses may have evolved mechanisms to manage UPR signaling to create an optimal niche for replication. The past decade has seen considerable progress in understanding how herpesviruses reprogram the UPR. Here we provide an overview of the molecular events of UPR activation, signaling and transcriptional outputs, and highlight key evidence that herpesviruses hijack the UPR to aid infection.
Removal of Microcystis aeruginosa through the Combined Effect of Plasma Discharge and Hydrodynamic Cavitation
Authors: Maršálek Blahoslav , Maršálková Eliška , Odehnalová Klára , Pochylý František , Rudolf Pavel , Stahel Pavel , Rahel Jozef , Čech Jan , Fialová Simona , Zezulka Štěpán
Published: December 2019

Cyanobacterial water blooms represent toxicological, ecological and technological problems around the globe. When present in raw water used for drinking water production, one of the best strategies is to remove the cyanobacterial biomass gently before treatment, avoiding cell destruction and cyanotoxins release. This paper presents a new method for the removal of cyanobacterial biomass during drinking water pre-treatment that combines hydrodynamic cavitation with cold plasma discharge. Cavitation produces press stress that causes Microcystis gas vesicles to collapse. The cyanobacteria then sink, allowing for removal by sedimentation. The cyanobacteria showed no signs of revitalisation, even after seven days under optimal conditions with nutrient enrichment, as photosynthetic activity is negatively affected by hydrogen peroxide produced by plasma burnt in the cavitation cloud. Using this method, cyanobacteria can be removed in a single treatment, with no increase in microcystin concentration. This novel technology appears to be highly promising for continual treatment of raw water inflow in drinking water treatment plants and will also be of interest to those wishing to treat surface waters without the use of algaecides.
Assessing Changes of Water Yield in Qinghai Lake Watershed of China
Authors: Lian Xi-hong , Qi Yuan , Wang Hong-wei , Zhang Jin-long , Yang Rui
Published: December 2019

Water yield is an important ecosystem service, which is directly related to human welfare and affects the sustainable development. Using the integrated valuation of environmental services and tradeoffs model (InVEST model), we simulated the dynamic change of water yield in Qinghai lake watershed, Qinghai, China, and verified the simulation results. This paper emphatically explored how precipitation change and land use/land cover change (LUCC) affected the change of water yield on the spatial and temporal scales. Before 2004, the areas of cultivated land and unused land showed a dramatic increasing tendency, while forestland and water area presented a decreasing trend. After 2004 cultivated land changed slowly, unused land decreased. Grassland revealed a general trend of decline during 1977–2018, while built-up land basically presented a linear increase. The results show that water yield fluctuated and increased during 1977–2018. From 1977 to 2000, the mean water yield in each sub-watershed showed an increasing trend and afterward a decreasing one. After 2000, the sub-watersheds basically showed an increasing tendency. There was a strong correlation, with a correlation coefficient of 0.954 ** (** correlation is significant at the 0.01 level), between precipitation and water yield. Land use/land cover change can change the hydrological state of infiltration, evapotranspiration, and water retention. Meanwhile, the correlation between built-up land and water yield was the highest, with a correlation coefficient of 0.932, followed by forestland, with a correlation coefficient of 0.897. Through the analysis of different scenarios, we found that compared with land use/land cover change, precipitation played a more dominant role in affecting water yield.
The Use of a Microscale Physical Model to Simulate Bankfull Discharge in the Lower Reaches of the Yellow River
Authors: Zhang Xue , Chen Minghong , Wu Pengxiang , Xin Fengmao
Published: December 2019

Microscale physical models (MSPMs) were once widely used in flood planning in large basins. They fell out of favor but are now being used again. This paper explores the benefits of using such a model for understanding a flood problem on the Lower Yellow River (LYR). We constructed an indoor MSPM of a nearly 800-km reach of the LYR. The model had different scales in the longitudinal, transverse, and vertical directions, and we adjusted the slope of the model. Meanwhile, a real-time water level monitoring system and an automatic flow control system were built on the MSPM to automatically control hydrodynamic testing. Through several discharge experiments, bankfull discharge for multiple MSPM sections was obtained and compared with measured data from the corresponding hydrological section of the prototype during the early flood season of 2016. The comparison demonstrated good linear correlation. The analysis of model similarity showed that although there was some deviation in gravity similarity between the MSPM and the prototype, the model discharge scale derived from resistance similarity adequately described the relationship between the model and the prototype bankfull discharge. Further analysis of the relationship between the model and the prototype bankfull discharge revealed that a split-line line may be better than a single regression line. A MSPM could reproduce the bankfull discharge of the LYR with the nearly 800-km reach in the laboratory which is impossible for a small distortion rate physical model, and obtain a result close to that of the assimilated numerical model.
Column Experiments on Sorption Coefficients and Biodegradation Rates of Selected Pharmaceuticals in Three Aquifer Sediments
Authors: Kiecak Aleksandra , Breuer Friederike , Stumpp Christine
Published: December 2019

The presence of pharmaceuticals in the environment, and in groundwater, has been recognized as a great environmental concern. Biodegradation and sorption are the main processes leading to the removal of contamination from the water phase. The aim of this study was to determine the transport processes of selected pharmaceuticals (antipyrine, atenolol, carbamazepine, caffeine, diclofenac, ketoprofen, sulfamethoxazole) in selected sediments (coarse sand, medium sand, sandy loam) in laboratory experiments. Moreover, the impact of flow velocities on the sorption and degradation rates of the selected compounds was studied. Column experiments were performed at three flow velocities, under abiotic and biotic conditions, applying conservative (bromide) and reactive tracers (pharmaceuticals). From the breakthrough curves, retardation factors and degradation rates were determined and the influence of variable flow conditions on transport parameters was evaluated. Low observed concentrations and recoveries of atenolol indicated a strong influence of sorption on its transport. Diclofenac, caffeine, and carbamazepine were also affected by sorption but to a lesser extent. Sulfamethoxazole, ketoprofen, and antipyrine were recovered nearly completely, indicating an almost conservative transport behavior. Biodegradation was small for all the compounds, as the results from biotic and abiotic column experiments were similar. Transport of the tested pharmaceuticals was not influenced by different flow velocities, as similar modelled degradation rates and retardation factors were found for all tested flow velocities.
Design of a Smart System for Rapid Bacterial Test
Authors: Patil Rajshree , Levin Saurabh , Rajkumar Samuel , Ajmal Tahmina
Published: December 2019

In this article, we present our initial findings to support the design of an advanced field test to detect bacterial contamination in water samples. The system combines the use of image processing and neural networks to detect an early presence of bacterial activity. We present here a proof of concept with some tests results. Our initial findings are very promising and indicate detection of viable bacterial cells within a period of 2 h. To the authors’ knowledge this is the first attempt to quantify viable bacterial cells in a water sample using cell splitting. We also present a detailed design of the complete system that uses the time lapse images from a microscope to complete the design of a neural network based smart system.
Gully Head-Cut Distribution Modeling Using Machine Learning Methods—A Case Study of N.W. Iran
Authors: Arabameri Alireza , Chen Wei , Blaschke Thomas , Tiefenbacher John P. , Pradhan Biswajeet , Tien Bui Dieu
Published: December 2019

To more effectively prevent and manage the scourge of gully erosion in arid and semi-arid regions, we present a novel-ensemble intelligence approach—bagging-based alternating decision-tree classifier (bagging-ADTree)—and use it to model a landscape’s susceptibility to gully erosion based on 18 gully-erosion conditioning factors. The model’s goodness-of-fit and prediction performance are compared to three other machine learning algorithms (single alternating decision tree, rotational-forest-based alternating decision tree (RF-ADTree), and benchmark logistic regression). To achieve this, a gully-erosion inventory was created for the study area, the Chah Mousi watershed, Iran by combining archival records containing reports of gully erosion, remotely sensed data from Google Earth, and geolocated sites of gully head-cuts gathered in a field survey. A total of 119 gully head-cuts were identified and mapped. To train the models’ analysis and prediction capabilities, 83 head-cuts (70% of the total) and the corresponding measures of the conditioning factors were input into each model. The results from the models were validated using the data pertaining to the remaining 36 gully locations (30%). Next, the frequency ratio is used to identify which conditioning-factor classes have the strongest correlation with gully erosion. Using random-forest modeling, the relative importance of each of the conditioning factors was determined. Based on the random-forest results, the top eight factors in this study area are distance-to-road, drainage density, distance-to-stream, LU/LC, annual precipitation, topographic wetness index, NDVI, and elevation. Finally, based on goodness-of-fit and AUROC of the success rate curve (SRC) and prediction rate curve (PRC), the results indicate that the bagging-ADTree ensemble model had the best performance, with SRC (0.964) and PRC (0.978). RF-ADTree (SRC = 0.952 and PRC = 0.971), ADTree (SRC = 0.926 and PRC = 0.965), and LR (SRC = 0.867 and PRC = 0.870) were the subsequent best performers. The results also indicate that bagging and RF, as meta-classifiers, improved the performance of the ADTree model as a base classifier. The bagging-ADTree model’s results indicate that 24.28% of the study area is classified as having high and very high susceptibility to gully erosion. The new ensemble model accurately identified the areas that are susceptible to gully erosion based on the past patterns of formation, but it also provides highly accurate predictions of future gully development. The novel ensemble method introduced in this research is recommended for use to evaluate the patterns of gullying in arid and semi-arid environments and can effectively identify the most salient conditioning factors that promote the development and expansion of gullies in erosion-susceptible environments.