bluuebunny/crossref_metadata_2025 huggingface dataset:
Responses of Anammox Granular Sludge to Long-Term Rare Earth Element Feeding: Lanthanum as a Case
Authors: Huang Shuanglei , Wu Daishe
Published: September 2020

A tremendous input of ammonium and rare earth elements (REEs) has entered the surroundings on account of the discharge and leak of leaching agents during rare earth in-suit leaching mining, which has threatened various organisms. Anammox has the potential to release nitrogen contamination, but the potential impacts of REEs on anammox bacteria remain unclear. In this study, La (III) was chosen as a case to explore the long-term impacts on anammox granular sludge. The 5 mg L−1 La (III) which was examined hardly affected the anammox granulates because of the defense of extracellular polymeric substances. The high La concentrations (10–50 mg L−1) caused intercellular accumulation and the significant inhibition of nitrogen removal performance and dehydrogenase activity, especially a decrease in the relative abundance of Ca. Kuenenia. Moreover, it also induced patently oxidative damage and affected cell membrane integrity. Notably, extracellular polymeric substances have a limited defense capability; neither La3+ nor Ca2+/Mg2+ efflux-related genes aggravated the intracellular accumulation of La.
Fishing Livelihoods in the Mackenzie River Basin: Stories of the Délįne Got’ine
Authors: Martin Chelsea , Parlee Brenda , Neyelle Morris
Published: September 2020

Climate change is among the greatest challenges facing Indigenous peoples. The impacts of climate change cannot be understood as only ecological or through models and projections. In this study, narratives from Indigenous peoples provide lived experience and insight of how social and ecological impacts are interconnected. Through collaborative research with the Sahtú Renewable Resources Board in the Northwest Territories Canada in the period 2018–2019, this paper shares the stories of the Délįne Got’ine peoples of Great Bear Lake (GBL), and how warming temperatures in the region impact fishing livelihoods. Specifically, we address the question, “What are the impacts of climate change on the fishing livelihoods of the Délįne Got’ine people?” Narratives from 21 semi-structured interviews reveal insights on six dimensions of fishing livelihoods. Analysis suggests the specific indicators of ecological change of concern to fishers and how those impact livelihoods over the short and long term. Given that the majority of research on climate change involving Indigenous peoples in Canada has focused on the high arctic and marine environments, this work is unique in its focus on the subarctic region and on freshwater ecosystems and livelihoods.
Exploring the Drivers and the Interventions towards Sustainable Food Security in the Food Supply Chain
Authors: Chan Hao Yuan , Abdul Halim-Lim Sarina , Tan Tai Boon , Kamarulzaman Nitty Hirawaty , Jamaludin Adi Ainurzaman , Wan-Mohtar Wan Abd Al Qadr Imad
Published: September 2020

The sustainability of food security is a global concern, and one of the priorities related to it is the ability to identify effective efforts that can protect food security along the food supply chain (FSC). The present study demystifies the relation of sustainability and food security and structurally identifies the sustainable drivers, and the pragmatic interventions that can critically contribute to the sustainability of food security within each stage of the FSC. A systematic review of articles from six databases was implemented. Thematic analysis was engaged to detect the sustainable drivers and interventions practised at each stage in the FSC for food security purposes. Six main themes of the drivers and interventions were derived from the analysis: food security governance involvement, input resource management, output management, information sharing, income, and technology. The result identifies the potential that quality management has on the mediating effect towards sustainable food security, through which a conceptual model for sustainable food security in the FSC was thus developed. It is deduced that mapping and categorizing the drivers and intervention of sustainable food securities could help deepen the understanding of effective and innovative practices towards food security in the FSC.
Scientific Landscape Related to Mapuche Indigenous Peoples and Wallmapu Territory
Authors: Bañales-Seguel Camila , Riquelme Maulén Wladimir , Álvez Amaya , Habit Evelyn
Published: September 2020

Recent international recognition of indigenous peoples, their rights and contributions to solving current challenges has directed academic attention to the way research is conducted in relation to them, what topics are studied, by whom, and using which methodologies. The Mapuche are the most numerous indigenous peoples in South America and have ancestrally inhabited a territory denominated Wallmapu. This study undertook a comprehensive revision and meta-analysis of the scientific literature related to the Mapuche and Wallmapu. Through quantification and visualization of the scientific landscape, the goal was to enhance the understanding of the themes and patterns that have guided research in this field of study. We found 1611 documents in Web of Science and SciELO collections published between 1975 and 2020. Using CiteSpace software, we analyzed the main conceptual hotspots, identified central authors and pivotal works, among other aspects of the scientific knowledge domain. The main research themes found revolve around political and historical aspects of the relationship between Mapuche and the State; ethnobotanical research including plant properties and cultural knowledge transmission; and the indisputable connection between indigenous resistance and environmental depredation. We argue that valuing cultural diversity paves the road for reclaiming indigenous knowledge as a contribution to our understanding of the world.
Estimate of Secondary NO2 Levels at Two Urban Traffic Sites Using Observations and Modelling
Authors: Ghermandi Grazia , Fabbi Sara , Veratti Giorgio , Bigi Alessandro , Teggi Sergio
Published: September 2020

Assessing secondary and primary NO2 in urban areas is important to support carefully designed environmental policies, particularly in areas with recurrent exceedance of NO2 regulatory limits. The share of secondary NO2 was preliminary estimated in intense traffic areas of Modena and Reggio Emilia (Northern Italy) by the combined analysis of regulatory air quality observations at urban traffic and urban background conditions. In addition simulations performed by the Lagrangian particle dispersion models Micro SWIFT SPRAY and the chemical transport model WRF-Chem were performed. The former was applied on the urban area representative of traffic conditions for both cities, in winter. The latter was applied twice in Modena, both with and without urban traffic emissions. Results suggest a large amount of secondary NO2 mainly at the Modena traffic site, and a better representativity of background conditions of the corresponding urban station in Reggio Emilia. NOx levels simulated by WRF-Chem show good results at Modena urban background and performance in line with reference benchmark values in reproducing observed NO2 and NOx concentrations at rural background sites, although a non-negligible bias in simulated urban NO2 remained. Overall the simulation models suggest that contribution to atmospheric NOx by domestic heating or industrial combustion emissions are not as relevant compared to traffic, consistently with the local emission inventory.
Smartphone-Based Participatory Soundscape Mapping for a More Sustainable Acoustic Environment
Authors: Brambilla Giovanni , Pedrielli Francesca
Published: September 2020

The urban environmental planning, a fundamental dynamic process for cities’ sustainability, could benefit from the soundscape approach, dealing with the perception of the acoustic environment in which sound is considered as a resource rather than a waste (noise). Noise and soundscape maps are useful tools for planning mitigation actions and for communication with citizens. Both mappings can benefit from crowdsourcing and participatory sound monitoring that has been made possible due to the large use of internet connections and mobile devices with dedicated apps. This paper is a “scoping review” to provide an overview of the potential, benefits, and drawbacks of participatory noise monitoring in noise and soundscape mapping applications, while also referring to metrological aspects. Gathering perceptual data on soundscapes by using digital questionnaires will likely be more commonly used than printed questionnaires; thus, the main differences between the experimental protocols concern the measurement of acoustic data. The authors propose to classify experimental protocols for in-field soundscape surveys into three types (GUIDE, MONITOR, and SMART) to be selected according to the survey’s objectives and the territorial extension. The main future developments are expected to be related to progress in smartphone hardware and software, to the growth of social networks data analysis, as well as to the implementation of machine learning techniques.
The Production of Sustainable Concrete with the Use of Alternative Aggregates: A Review
Authors: Collivignarelli Maria Cristina , Cillari Giacomo , Ricciardi Paola , Miino Marco Carnevale , Torretta Vincenzo , Rada Elena Cristina , Abbà Alessandro
Published: September 2020

The concrete industry is a core element of the building sector, but it has to deal with the increasing attention on the environmental issues related to the production process: increasing energy efficiency and the adoption of alternative fuels or raw materials represent the most relevant solutions. The present work analyses physical, mechanical, and environmental performances of concrete incorporating residues derived from four main sources (construction and demolition waste, residues from waste treatment, metallurgical industry by-products, and others), as substitutes of either fine or coarse aggregates. Fine aggregates showed the highest number of alternatives and replacement level, with the relevant impact on concrete properties; coarse aggregates, however, always reach a complete replacement, with the exclusion of glass that highly affects the mechanical performance. Construction and metallurgical industry categories are the main sources of alternative materials for both the components, with ceramic and lead slag reaching a full replacement for fine and coarse aggregates.
An Inclusive Approach to Partnerships for the SDGs: Using a Relationship Lens to Explore the Potential for Transformational Collaboration
Authors: Stott Leda , Murphy David F.
Published: September 2020

Partnerships are positioned as critical for the achievement of the Sustainable Development Goals and the United Nations transformational agenda for 2030. The widespread use of terms such as ‘collaboration’, ‘partnership’ and ‘cooperation’ has, however, led to debates about the expectations of such relationships and calls have been made for more rigorous clarification and classification of these related concepts. Drawing upon a comprehensive literature review, we argue in this conceptual paper that the broad spectrum of personal and organizational interactions within, between and across different sectors, domains, disciplines and contexts makes the quest to delineate and categorize these diverse forms of collaboration a seemingly impossible task. We further suggest that such efforts advance a narrow view of partnership as little more than a means to an end, thus limiting understanding of the integrative and intrinsic value of working in this way. We believe that a more inclusive understanding of partnerships may be achieved by exploring them through a relationship lens that acknowledges the importance of inter-personal connections in partnerships more deeply. In doing so, the capacity of partnerships to generate the systemic change that is at the heart of the 2030 Agenda for Sustainable Development may be enhanced and ultimately realized.
Toxic Metal Adsorption from Aqueous Solution by Activated Biochars Produced from Macadamia Nutshell Waste
Authors: Dao Minh Trung , Nguyen T. T. Tram , Nguyen X. Du , La D. Duong , Nguyen D. Duc , Chang S. W. , Chung W. J. , Nguyen Van Khanh
Published: September 2020

Abundantly available biomass wastes from agriculture can serve as effective environmental remediation materials. In this study, activated biochar was fabricated from macadamia nutshell (MCN) through carbonization and chemical modification. The resultant biochars were used as adsorbents to remove toxic metal ions such as Cu2+ and Zn2+ from aqueous solutions. The results showed that the activated MCN biochar has a high adsorption capacity for toxic metal ions. When MCN biochar was activated with K2CO3, the adsorption efficiencies for Cu2+ and Zn2+ were 84.02% and 53.42%, respectively. With H3PO4 activation, the Cu2+- and Zn2+-adsorption performances were 95.92% and 67.41%, respectively. H2O2-modified MCN biochar had reasonable Cu2+- and Zn2+-adsorption efficiencies of 79.33% and 64.52%, respectively. The effects of pH, adsorbent concentration and adsorption time on the removal performances of Cu2+ and Zn2+ in aqueous solution were evaluated. The results exhibited that the activated MCN biochar showed quick adsorption ability with an optimal pH of 4 and 4.5 for both Cu2+ and Zn2+, respectively.
Changes in Energy Supplies in the Countries of the Visegrad Group
Authors: Rokicki Tomasz , Perkowska Aleksandra
Published: September 2020

The main purpose of the work is to identify and present the current situation and changes in the volume of energy supplies in the countries of the Visegrad Group. The specific objectives of the article are to determine the degree of concentration of energy supply sources in the countries of the Visegrad Group, the directions of their changes, types of energy used and changes in this area, establishing the correlation between the volume of energy supplies and changes in the economic situation in V4 countries. The period of research covers the years 1990–2018. The sources of materials were the literature on the subject, with the data from Eurostat. The following methods were used for the analysis and presentation of materials: descriptive, tabular, graphical, dynamics indicators with a constant basis; Gini concentration coefficient; concentration analysis using the Lorenz curve; coefficient of variation; Pearson’s linear correlation coefficient. It was found that, of a high concentration of energy supplies from one or more sources in all countries of the Visegrad Group, the largest was in Poland and the lowest were in Hungary and the Czech Republic. In each of these countries, the economy was transforming and there was also a gradual diversification of energy sources.
Spatio-Temporal Changes of Housing Features in Response to Urban Renewal Initiatives: The Case of Seoul
Authors: Yang Hee Jin
Published: September 2020

Over the past two decades, Seoul has been in a transitional period in terms of urban renewal approaches. Housing is a fundamental element of citizens’ lives and the built landscape, thus, it deserves thoughtful scrutiny. As such, this study empirically investigates the dynamics of the spatial and temporal characteristics of housing stock within the context of new urban renewal policies in Seoul. A fine-grained and multifaceted analysis shows that the supply of new apartments has decreased over time, revealing that denser housing redevelopment in the inner city has become more difficult. In addition, an exploratory spatial data analysis indicates that although spatial clustering of old housing units has been reduced, new housing units have become more spatially distributed and outwardly dispersed over time. Since the physical and locational changes of housing stock are closely related to urban renewal initiatives, this study suggests that the city government needs to incorporate the concept of sustainable urban growth management into its housing supply and renewal policies.
Toward Improving the Prediction Accuracy of Product Recommendation System Using Extreme Gradient Boosting and Encoding Approaches
Authors: Shahbazi Zeinab , Hazra Debapriya , Park Sejoon , Byun Yung Cheol
Published: September 2020

With the spread of COVID-19, the “untact” culture in South Korea is expanding and customers are increasingly seeking for online services. A recommendation system serves as a decision-making indicator that helps users by suggesting items to be purchased in the future by exploring the symmetry between multiple user activity characteristics. A plethora of approaches are employed by the scientific community to design recommendation systems, including collaborative filtering, stereotyping, and content-based filtering, etc. The current paradigm of recommendation systems favors collaborative filtering due to its significant potential to closely capture the interest of a user as compared to other approaches. The collaborative filtering harnesses features like user-profile details, visited pages, and click information to determine the interest of a user, thereby recommending the items that are related to the user’s interest. The existing collaborative filtering approaches exploit implicit and explicit features and report either good classification or prediction outcome. These systems fail to exhibit good results for both measures at the same time. We believe that avoiding the recommendation of those items that have already been purchased could contribute to overcoming the said issue. In this study, we present a collaborative filtering-based algorithm to tackle big data of user with symmetric purchasing order and repetitive purchased products. The proposed algorithm relies on combining extreme gradient boosting machine learning architecture with word2vec mechanism to explore the purchased products based on the click patterns of users. Our algorithm improves the accuracy of predicting the relevant products to be recommended to the customers that are likely to be bought. The results are evaluated on the dataset that contains click-based features of users from an online shopping mall in Jeju Island, South Korea. We have evaluated Mean Absolute Error, Mean Square Error, and Root Mean Square Error for our proposed methodology and also other machine learning algorithms. Our proposed model generated the least error rate and enhanced the prediction accuracy of the recommendation system compared to other traditional approaches.
Collision Free Smooth Path for Mobile Robots in Cluttered Environment Using an Economical Clamped Cubic B-Spline
Authors: Noreen Iram
Published: September 2020

Mobile robots have various applications in agriculture, autonomous cars, industrial automation, planetary exploration, security, and surveillance. The generation of the optimal smooth path is a significant aspect of mobile robotics. An optimal path for a mobile robot is measured by various factors such as path length, path smoothness, collision-free curve, execution time, and the total number of turns. However, most of the planners generate a non-smooth less optimal and linear piecewise path. Post processing smoothing is applied at the cost of increase in path length. Moreover, current research on post-processing path smoothing techniques does not address the issues of post smoothness collision and performance efficiency. This paper presents a path smoothing approach based on clamped cubic B-Spline to resolve the aforementioned issues. The proposed approach has introduced an economical point insertion scheme with automated knot vector generation while eliminating post smoothness collisions with obstacles. It generates C2 continuous path without any stitching point and passes more closely to the originally planned path. Experiments and comparison with previous approaches have shown that the proposed approach generates better results with reduced path length, and execution time. The test cases used for experiments include a simple structure environment, complex un-structured environment, an environment full of random cluttered narrow obstacles, and a case study of an indoor narrow passage.
Prospective Teachers’ Development of Meta-Cognitive Functions in Solving Mathematical-Based Programming Problems with Scratch
Authors: Shahbari Juhaina Awawdeh , Daher Wajeeh , Baya’a Nimer , Jaber Otman
Published: September 2020

Transformations, including symmetry and rotations, are important in solving mathematical problems. Meta-cognitive functions are considered critical in solving mathematical problems. In the current study, we examined prospective teachers’ use of meta-cognitive functions while solving mathematical-based programming problems in the Scratch environment. The study was conducted among 18 prospective teachers, who engaged in a sequence of mathematical problems that utilize Scratch. The data sources included video recordings and solution reports while they performed mathematical problems. The findings indicated that the participants developed their meta-cognitive functions as problem solvers related to both mathematics and programming aspects. The findings also indicated that the participants developed regulation meta-cognitive functions more than awareness and evaluation ones in mathematical and programming aspects.
Enhanced Hand-Oriented Activity Recognition Based on Smartwatch Sensor Data Using LSTMs
Authors: Mekruksavanich Sakorn , Jitpattanakul Anuchit , Youplao Phichai , Yupapin Preecha
Published: September 2020

The creation of the Internet of Things (IoT), along with the latest developments in wearable technology, has provided new opportunities in human activity recognition (HAR). The modern smartwatch offers the potential for data from sensors to be relayed to novel IoT platforms, which allow the constant tracking and monitoring of human movement and behavior. Recently, traditional activity recognition techniques have done research in advance by choosing machine learning methods such as artificial neural network, decision tree, support vector machine, and naive Bayes. Nonetheless, these conventional machine learning techniques depend inevitably on heuristically handcrafted feature extraction, in which human domain knowledge is normally limited. This work proposes a hybrid deep learning model called CNN-LSTM that employed Long Short-Term Memory (LSTM) networks for activity recognition with the Convolution Neural Network (CNN). The study makes use of HAR involving smartwatches to categorize hand movements. Using the study based on the Wireless Sensor Data Mining (WISDM) public benchmark dataset, the recognition abilities of the deep learning model can be accessed. The accuracy, precision, recall, and F-measure statistics are employed using the evaluation metrics to assess the recognition abilities of LSTM models proposed. The findings indicate that this hybrid deep learning model offers better performance than its rivals, where the achievement of 96.2% accuracy, while the f-measure is 96.3%, is obtained. The results show that the proposed CNN-LSTM can support an improvement of the performance of activity recognition.
Dynamic Response of the Newton Voigt–Kelvin Modelled Linear Viscoelastic Systems at Harmonic Actions
Authors: Dobrescu Cornelia
Published: September 2020

The variety of viscoelastic systems and structures, for the most part, is studied analytically, with significant results. As a result of analytical, numerical and experimental research, which was conducted on a larger variety of linear viscoelastic systems and structures. We analyzed the dynamic behavior for the viscoelastic composite materials, anti-vibration viscous-elastic systems consisting of discrete physical devices, road structures consisting of natural soil structures with mineral aggregates and asphalt mixes, and mixed mechanic systems of insulation of the industrial vibrations consisting of elastic and viscous devices. In this context, the compound rheological model can be schematized as being V−(E|V) type of the Newton Voigt–Kelvin model with inertial excited mass, applicable to linear viscoelastic materials.
Parameterized Design and Dynamic Analysis of a Reusable Launch Vehicle Landing System with Semi-Active Control
Authors: Wang Chen , Chen Jinbao , Jia Shan , Chen Heng
Published: September 2020

Reusable launch vehicles (RLVs) are a solution for effective and economic transportation in future aerospace exploration. However, RLVs are limited to being used under simple landing conditions (small landing velocity and angle) due to their poor adaptability and the high rocket acceleration of current landing systems. In this paper, an adaptive RLV landing system with semi-active control is proposed. The proposed landing system can adjust the damping forces of primary strut dampers through semi-actively controlled currents in accordance with practical landing conditions. A landing dynamic model of the proposed landing system is built. According to the dynamic model, an light and effective RLV landing system is parametrically designed based on the response surface methodology. Dynamic simulations validate the proposed landing system under landing conditions including the highest rocket acceleration and the greatest damper compressions. The simulation results show that the proposed landing system with semi-active control has better landing performance than current landing systems that use passive liquid or liquid–honeycomb dampers. Additionally, the flexibility and friction of the structure are discussed in the simulations. Compared to rigid models, flexible models decrease rocket acceleration by 51% and 54% at the touch down moments under these two landing conditions, respectively. The friction increases rocket acceleration by less than 1%. However, both flexibility and friction have little influence on the distance between the rocket and ground, or the compression strokes of the dampers.
Adaptive Mechanism Model for the Prevention of SLA Violation in the Context of COPD Patient Monitoring
Authors: Kouamé Konan-Marcelin , Mcheick Hamid , Ajami Hicham
Published: September 2020

In this paper, we introduce a new kind of Service Level Agreement(SLA) Template to better control dynamically quality of medical monitoring platform service. Our approach is based on Health care system and Health Information Technology (HIT) research area, specifically the field of telemonitoring system for patients who suffer from chronic obstructive pulmonary disease (COPD). According to WHO statistics, COPD is the third leading cause of death worldwide. To this end, several solutions or platforms exist today to monitor COPD. Most of these platforms manage large volume of patient data. This can bring about quality and lost data problems. To address these issues, control mechanisms must be proposed and designed to improve the quality of service (QoS) on these platforms. A platform with continuously monitored QoS can save patients’ lives and reduce data quality risk. In this article, we propose an ontology that uses SLAs data from COPD monitoring platforms with dynamic data from a patient context. We dynamically calculate the number of patient data incidents and the number of service request incidents from two dynamic contexts: SLA and the patient context. If the number of incidents is higher than what is expected in the SLA, then alerts are sent to the interface parties in real time. Finally, the contribution of this article is the proposed virtual SLA template to better control SLA violation and improve quality of medical monitoring platforms services.
Mitigation of Privacy Threats due to Encrypted Traffic Analysis through a Policy-Based Framework and MUD Profiles
Authors: Baldini Gianmarco , Hernandez-Ramos José L. , Nowak Slawomir , Neisse Ricardo , Nowak Mateusz
Published: September 2020

It has been proven in research literature that the analysis of encrypted traffic with statistical analysis and machine learning can reveal the type of activities performed by a user accessing the network, thus leading to privacy risks. In particular, different types of traffic (e.g., skype, web access) can be identified by extracting time based features and using them in a classifier. Such privacy attacks are asymmetric because a limited amount of resources (e.g., machine learning algorithms) can extract information from encrypted traffic generated by cryptographic systems implemented with a significant amount of resources. To mitigate privacy risks, studies in research literature have proposed a number of techniques, but in most cases only a single technique is applied, which can lead to limited effectiveness. This paper proposes a mitigation approach for privacy risks related to the analysis of encrypted traffic which is based on the integration of three main components: (1) A machine learning component which proactively analyzes the encrypted traffic in the network to identify potential privacy threats and evaluate the effectiveness of various mitigation techniques (e.g., obfuscation), (2) a policy based component where policies are used to enforce privacy mitigation solutions in the network and (3) a network node profile component based on the Manufacturer Usage Description (MUD) standard to enable changes in the network nodes in the cases where the first two components are not effective in mitigating the privacy risks. This paper describes the different components and how they interact in a potential deployment scenario. The approach is evaluated on the public dataset ISCXVPN2016 and the results show that the privacy threat can be mitigated significantly by removing completely the identification of specific types of traffic or by decreasing the probability of their identification as in the case of VOIP by 50%, Chat by 40% and Browsing by 33%, thus reducing significantly the privacy risk.
Human Action Recognition Using Bone Pair Descriptor and Distance Descriptor
Authors: Warchoł Dawid , Kapuściński Tomasz
Published: September 2020

The paper presents a method for the recognition of human actions based on skeletal data. A novel Bone Pair Descriptor is proposed, which encodes the angular relations between pairs of bones. Its features are combined with Distance Descriptor, previously used for hand posture recognition, which describes relationships between distances of skeletal joints. Five different time series classification methods are tested. The selection of features, input joints, and bones is performed. The experiments are conducted using person-independent validation tests and a challenging, publicly available dataset of human actions. The proposed method is compared with other approaches found in the literature achieving relatively good results.
A Novel Categorical Approach to Semantics of Relational First-Order Logic
Authors: Schreiner Wolfgang , Steingartner William , Novitzká Valerie
Published: September 2020

We present a categorical formalization of a variant of first-order logic. Unlike other texts on this topic, the goal of this paper is to give a very transparent and self-contained account without requiring more background than basic logic and set theory. Our focus is to show how the semantics of first-order formulas can be derived from their usual deduction rules. For understanding the core ideas, it is not necessary to investigate the internal term structure of atomic formulas, thus we abstract atomic formulas to (syntactically opaque) relations; in this sense, our variant of first-order logic is “relational”. While the derived semantics is based on categorical principles (even the duality that arises from a symmetry between two ways of looking at something where there is no reason to choose one over the other), it is nevertheless “constructive” in that it describes explicit computations of the truth values of formulas. We demonstrate this by modeling the categorical semantics in the RISCAL (RISC Algorithm Language) system which allows us to validate the core propositions by automatically checking them in finite models.
The Asymptotic Approach to the Description of Two-Dimensional Symmetric Soliton Patterns
Authors: Stepanyants Yury
Published: September 2020

The asymptotic approach is suggested for the description of interacting surface and internal oceanic solitary waves. This approach allows one to describe stationary moving symmetric wave patterns consisting of two plane solitary waves of equal amplitudes moving at an angle to each other. The results obtained within the approximate asymptotic theory are validated by comparison with the exact two-soliton solution of the Kadomtsev–Petviashvili equation (KP2-equation). The suggested approach is equally applicable to a wide class of non-integrable equations too. As an example, the asymptotic theory is applied to the description of wave patterns in the 2D Benjamin–Ono equation describing internal waves in the infinitely deep ocean containing a relatively thin one of the layers.
Second-Order Cone Approximation for Voltage Stability Analysis in Direct-Current Networks
Authors: Montoya Oscar Danilo , Gil-González Walter , Molina-Cabrera Alexander
Published: September 2020

In this study, the voltage stability margin for direct current (DC) networks in the presence of constant power loads is analyzed using a proposed convex mathematical reformulation. This convex model is developed by employing a second-order cone programming (SOCP) optimization that transforms the non-linear non-convex original formulation by reformulating the power balance constraint. The main advantage of the SOCP model is that the optimal global solution of a problem can be obtained by transforming hyperbolic constraints into norm constraints. Two test systems are considered to validate the proposed SOCP model. Both systems have been reported in specialized literature with 6 and 69 nodes. Three comparative methods are considered: (a) the Newton-Raphson approximation based on the determinants of the Jacobian matrices, (b) semidefinite programming models, and (c) the exact non-linear formulation. All the numerical simulations are conducted using the MATLAB and GAMS software. The effectiveness of the proposed SOCP model in addressing the voltage stability problem in DC grids is verified by comparing the objective function values and processing time.
The Parotoid Gland Secretion from Peruvian Toad Rhinella horribilis (Wiegmann, 1833): Chemical Composition and Effect on the Proliferation and Migration of Lung Cancer Cells
Authors: Schmeda-Hirschmann Guillermo , de Andrade Jean Paulo , Soto-Vasquez Marilú Roxana , Alvarado-García Paul Alan Arkin , Palominos Charlotte , Fuentes-Retamal Sebastián , Mellado Mathias , Correa Pablo , Urra Félix A.
Published: September 2020

Since Rhinella sp. toads produce bioactive substances, some species have been used in traditional medicine and magical practices by ancient cultures in Peru. During several decades, the Rhinella horribilis toad was confused with the invasive toad Rhinella marina, a species documented with extensive toxinological studies. In contrast, the chemical composition and biological effects of the parotoid gland secretions (PGS) remain still unknown for R. horribilis. In this work, we determine for the first time 55 compounds from the PGS of R. horribilis, which were identified using HPLC-MS/MS. The crude extract inhibited the proliferation of A549 cancer cells with IC50 values of 0.031 ± 0.007 and 0.015 ± 0.001 µg/mL at 24 and 48 h of exposure, respectively. Moreover, it inhibited the clonogenic capacity, increased ROS levels, and prevented the etoposide-induced apoptosis, suggesting that the effect of R. horribilis poison secretion was by cell cycle blocking before of G2/M-phase checkpoint. Fraction B was the most active and strongly inhibited cancer cell migration. Our results indicate that the PGS of R. horribilis are composed of alkaloids, bufadienolides, and argininyl diacids derivatives, inhibiting the proliferation and migration of A549 cells.
Bee Venom Phospholipase A2 Ameliorates Atherosclerosis by Modulating Regulatory T Cells
Authors: Kang Geun-Hyung , Lee Sujin , Choi Da Bin , Shin Dasom , Kim Jahee , Yang HyeJin , Bae Hyunsu
Published: September 2020

Atherosclerosis is a chronic inflammatory disease caused by lipids and calcareous accumulations in the vascular wall due to an inflammatory reaction. Recent reports have demonstrated that regulatory T (Treg) cells have an important role as a new treatment for atherosclerosis. This study suggests that bee venom phospholipase A2 (bvPLA2) may be a potential therapeutic agent in atherosclerosis by inducing Treg cells. We examined the effects of bvPLA2 on atherosclerosis using ApoE-/- and ApoE-/-/Foxp3DTR mice. In this study, bvPLA2 increased Treg cells, followed by a decrease in lipid accumulation in the aorta and aortic valve and the formation of foam cells. Importantly, the effect of bvPLA2 was found to depend on Treg cells. This study suggests that bvPLA2 can be a potential therapeutic agent for atherosclerosis.
Mycotoxin Deoxynivalenol Has Different Impacts on Intestinal Barrier and Stem Cells by Its Route of Exposure
Authors: Hanyu Hikaru , Yokoi Yuki , Nakamura Kiminori , Ayabe Tokiyoshi , Tanaka Keisuke , Uno Kinuko , Miyajima Katsuhiro , Saito Yuki , Iwatsuki Ken , Shimizu Makoto , Tadaishi Miki , Kobayashi-Hattori Kazuo
Published: September 2020

The different effects of deoxynivalenol (DON) on intestinal barrier and stem cells by its route of exposure remain less known. We explored the toxic effects of DON on intestinal barrier functions and stem cells after DON microinjection (luminal exposure) or addition to a culture medium (basolateral exposure) using three-dimensional mouse intestinal organoids (enteroids). The influx test using fluorescein-labeled dextran showed that basolateral DON exposure (1 micromolar (µM) disrupted intestinal barrier functions in enteroids compared with luminal DON exposure at the same concentration. Moreover, an immunofluorescence experiment of intestinal epithelial proteins, such as E-cadherin, claudin, zonula occludens-1 (ZO-1), and occludin, exhibited that only basolateral DON exposure broke down intestinal epithelial integrity. A time-lapse analysis using enteroids from leucine-rich repeat-containing G-protein-coupled receptor 5 (Lgr5)-enhanced green fluorescence protein (EGFP) transgenic mice and 5-ethynyl-2-deoxyuridine (EdU) assay indicated that only the basolateral DON exposure, but not luminal DON exposure, suppressed Lgr5+ stem cell count and proliferative cell ratio, respectively. These results revealed that basolateral DON exposure has larger impacts on intestinal barrier function and stem cells than luminal DON exposure. This is the first report that DON had different impacts on intestinal stem cells depending on the administration route. In addition, RNA sequencing analysis showed different expression of genes among enteroids after basolateral and luminal DON exposure.
Genome Sequence and Characterization of Five Bacteriophages Infecting Streptomyces coelicolor and Streptomyces venezuelae: Alderaan, Coruscant, Dagobah, Endor1 and Endor2
Authors: Hardy Aël , Sharma Vikas , Kever Larissa , Frunzke Julia
Published: September 2020

Streptomyces are well-known antibiotic producers, also characterized by a complex morphological differentiation. Streptomyces, like all bacteria, are confronted with the constant threat of phage predation, which in turn shapes bacterial evolution. However, despite significant sequencing efforts recently, relatively few phages infecting Streptomyces have been characterized compared to other genera. Here, we present the isolation and characterization of five novel Streptomyces phages. All five phages belong to the Siphoviridae family, based on their morphology as determined by transmission electron microscopy. Genome sequencing and life style predictions suggested that four of them were temperate phages, while one had a lytic lifestyle. Moreover, one of the newly sequenced phages shows very little homology to already described phages, highlighting the still largely untapped viral diversity. Altogether, this study expands the number of characterized phages of Streptomyces and sheds light on phage evolution and phage-host dynamics in Streptomyces.
Water Value Flows Upstream
Authors: Savenije Hubert H. G. , van der Zaag Pieter
Published: September 2020

Arjen Hoekstra postulated in 2001 that the value of water accumulates in an upstream direction: water value flows upstream. The ultimate source of this value is the rain. This original idea he used to develop the water value-flow concept. This article shows that the water value-flow concept has much to offer in terms of contemporary challenges. It is fully consistent with the "Five Bellagio Principles on Valuing Water" that the High Level Panel of Water published in 2017, and can make significant contributions to the first four principles. This article also shows that the concept can make many more contributions, including incorporating precipitationsheds, and thus include the source areas of rainfall in valuing water. Yet, until now, this innovative and potentially ground breaking concept has been largely ignored by researchers and practitioners in the fields of water resources management and economics. We conclude that the value-flow concept is a unique and promising framework for the integrated assessment of the value of water within a water resources system or river basin. We suggest that the concept can be enriched by incorporating instream benefits, water quality, as well as social, cultural, and spiritual values. We also suggest to test whether the concept can be usefully applied, and add value, to the emerging fields of socio-hydrology and water accounting.
Water Quality of Freshwater Ecosystems in a Temperate Climate
Authors: Klimaszyk Piotr , Gołdyn Ryszard
Published: September 2020

Water is the substance that made life on Earth possible. It plays a key role in both the individual and population development of all species. Water is also a critical resource for humans as populations continue to grow and climate change affects global and local water cycles. Water is a factor limiting economic development in many regions of the world. Under these conditions, good water quality becomes an extremely important factor that determines its economic utility, including water supply, recreation, and agriculture. Proper water quality maintenance of freshwater ecosystems is also very important for preserving biodiversity. The quality of water depends on many factors, the most important of which are related to human impact on water ecosystems, especially the impact of various pollutants from municipal economy, industry and agriculture. Hydrotechnical changes, such as river damming, drainage processes and water transport between catchments also have a significant impact. Water quality is also dependent on the impact of natural conditions connected, e.g., with climate, catchment, water organisms and their interactions within the food-webs, etc. This Special Issue consists of fourteen original scientific papers concerning different problems associated with the water quality of freshwater ecosystems in a temperate climate. Most of the articles deal with the relations between water quality and the structure of ecosystem biocenoses. The conclusion of these articles confirms the fact that the deterioration of water quality has a direct impact on the quantitative and qualitative structure of biocenoses. This is accompanied by a decline in biodiversity and the disappearance of rare plant and animal species. They also draw attention to the particular importance of internal physical and chemical differentiation within the aquatic ecosystem, both in horizontal and vertical dimensions. The problem of ensuring proper ecological conditions and good quality of water in freshwater aquatic ecosystems is also raised, and methods for the restoration of water bodies are presented. The majority of the research presented in this Special Issue was carried out in Central Europe, and one of the papers concerns the area of West Africa—the edge of temperate climate zone.
The Influence of Grain Size Distribution on the Hydraulic Gradient for Initiating Backward Erosion
Authors: Dirkx Willem-Jan , Beek Rens , Bierkens Marc
Published: September 2020

Backward erosion by piping is one of the processes that threaten the stability of river embankments in the Netherlands. During high river stages, groundwater flow velocities underneath the embankment increase as a result of the steepened hydraulic gradient. If a single outflow point exists or forms, the concentrated flow can entrain soil particles, leading to the formation of a subsurface pipe. The processes controlling this phenomenon are still relatively unknown due to their limited occurrence and because piping is a subsurface phenomenon. To study the initiation of piping, we performed laboratory experiments in which we induced water flow through a porous medium with a vertically orientated outflow point. In these experiments, we explicitly considered grain size variations, thus adding to the existing database of experiments. Our experiments showed that the vertical velocity needed for the initiation of particle transport can be described well by Stokes’ law using the median grain size. We combine this with a novel method to relate bulk hydraulic conductivity to the grain size distribution. This shows that knowledge of the grain size distribution and the location of the outflow point are sufficient to estimate the hydraulic gradient needed to initiate pipe formation in the experiment box.
Effect of Climate Change on a Monolithic Desulphurized Tailings Cover
Authors: Bashir Rashid , Ahmad Fiaz , Beddoe Ryley
Published: September 2020

A soil cover system can be viewed as a thin interface placed between the atmosphere and the underlying waste. Climate is a primary design variable in soil cover design; therefore, climate change poses a number of challenges to design, operation and long-term performance of covers. In this research climate change effects on the hydraulic behavior of soil covers at a Northern Ontario, Canada site were assessed. Covers were analyzed using historical and future climate datasets. Historical climate data were compiled from an Environment Canada weather station near the site. The future climate datasets were sourced for different Global Circulation Models (GCM) for various representative concentration pathways (RCP). The covers at the site were constructed with a single layer of desulphurized tailings. Soil covers were meant to limit oxygen ingress to the underlying reactive tailings by maintaining high water saturation in the covers. Oxygen flux through soil covers for current and future climates were predicted using variably saturated water flow and oxygen transport modeling using the finite element method. The results of this research indicate that the effect of climate change on soil cover depends on the hydraulic properties of the soil cover materials and that of the underlying tailings. The results of this study suggest that the effect of climate change on the coarse tailing covers could be marginal resulting in a maximum increase of 5% in oxygen flux at the cover surface for the future climates in comparison to the base climate. However, in the case of fine tailings covers, increases of up to 65% can be expected.