bluuebunny/crossref_metadata_2025 huggingface dataset:
Planning Nature-Based Solutions for Urban Flood Reduction and Thermal Comfort Enhancement
Authors: Majidi Abdul Naser , Vojinovic Zoran , Alves Alida , Weesakul Sutat , Sanchez Arlex , Boogaard Floris , Kluck Jeroen
Published: November 2019

As a consequence of climate change and urbanization, many cities will have to deal with more flooding and extreme heat stress. This paper presents a framework to maximize the effectiveness of Nature-Based Solutions (NBS) for flood risk reduction and thermal comfort enhancement. The framework involves an assessment of hazards with the use of models and field measurements. It also detects suitable implementation sites for NBS and quantifies their effectiveness for thermal comfort enhancement and flood risk reduction. The framework was applied in a densely urbanized study area, for which different small-scale urban NBS and their potential locations for implementation were assessed. The overall results show that the most effective performance in terms of flood mitigation and thermal comfort enhancement is likely achieved by applying a range of different measures at different locations. Therefore, the work presented here shows the potential of the framework to achieve an effective combination of measures and their locations, which was demonstrated on the case of the Sukhumvit area in Bangkok (Thailand). This can be particularly suitable for assessing and planning flood mitigation measures in combination with heat stress reduction.
Sympatric Bat Species Prey Opportunistically on a Major Moth Pest of Pecans
Authors: Braun de Torrez Elizabeth C. , Brown Veronica A. , McCracken Gary F. , Kunz Thomas H.
Published: November 2019

Native predators provide undervalued pest suppression services to agriculture. Studies of pest consumption by insectivorous bats tend to focus upon single species in large, centralized colonies, while bats dispersed in small groups within the agricultural matrix often go unnoticed. Pecan trees, Carya illinoinensis, and the destructive pecan nut casebearer (PNC) moth, Acrobasis nuxvorella, comprise a tightly linked host–parasite system in a widespread agroecosystem native to North America. Here we use a quantitative polymerase chain reaction (qPCR) assay of fecal DNA to document predation on PNC moths by an assemblage of sympatric bat species across episodic peaks in PNC abundance. Although five species of bats consume PNC moths, greater predation by a solitary tree-roosting bat (eastern red bat, Lasiurus borealis) than other species is suggested by a higher frequency of PNC occurrence and quantity of PNC gene copies in fecal samples. Consumption of PNC by bats during all documented peaks in moth activity suggests that predation pressure occurs throughout the PNC season. Our results highlight the need to consider multi-species assemblages and different foraging strategies when assessing pest suppression services, particularly in agroforestry or tree crops. Assessing the diet of only common or easily captured species limits our ability to accurately document pest consumption by bats.
Blockchain in FinTech: A Mapping Study
Authors: Fernandez-Vazquez Simon , Rosillo Rafael , De La Fuente David , Priore Paolo
Published: November 2019

Blockchain is currently one of the most important topics in both the academia and industry world, mainly due to the possible effects that the continuing application of this new technology could have. The adoption of this technology by FinTech companies constitutes the next step towards the expansion of blockchain and its sustainability. The paper conducts a mapping study on the research topics, limitations, gaps and future trends of blockchain in FinTech companies. A total of 49 papers from a scientific database (Web of Science Core Collection) have been analyzed. The results show a deep focus in challenges such as security, scalability, legal and regulatory, privacy or latency, with proposed solutions still to be far from being effective. A vast majority of the research is focused into finance and banking sector, obviating other industries that could play a crucial role in the further expansion of blockchain. This study can contribute to researchers as a starting point for their investigation, as well as a source for recommendations on future investigation directions regarding blockchain in the FinTech sector.
Assessing the Ecological Sensitivity of Coastal Marine Ecosystems: A Case Study in Xiamen Bay, China
Authors: Hu Wenjia , Yu Weiwei , Ma Zhiyuan , Ye Guanqiong , Dang Ersha , Huang Hao , Zhang Dian , Chen Bin
Published: November 2019

Coastal marine ecosystems are sensitive to anthropogenic stressors and environmental change. The Chinese Government proposed an ecosystem-based marine spatial planning scheme called the “Marine Ecological Red Line” (MERL), aimed at protecting ecologically sensitive areas. The assessment and mapping of ecosystem sensitivity provide important tools for regional MERL and setting conservation priorities. In this study, an integrated framework for the comprehensive sensitivity assessment of coastal marine ecosystems was proposed. This framework had two components: endogenous sensitivity and exogenous sensitivity. A weighted summation method was used along with a GIS-based spatial analysis to calculate regional sensitivity quantitatively. Taking Xiamen Bay in China as a case study, the approach integrated spatial data on the distribution of marine habitats and multiple human activities. An index system (including 26 indicators) was established for the case study. Five areas with different levels of sensitivity were delineated. In the study region of 1281 km2, areas with extremely high and high sensitivity covered 87 km2 and 235 km2, respectively, and were hypothesized to be priority areas of conservation and regulation. Areas with the highest sensitivity were located closer to Jiulongjiang Estuary and along the coastline of Xiang’an. Areas with lower sensitivity were also mapped in Tong’an Bay, representing possible areas that could accommodate future industrial or intensive human use. Comparative analyses between endogenous sensitivity and exogenous sensitivity allowed the presence of development-protection conflict zones to be identified. The results provide an important scientific basis for MERL decisions. In addition, targeted management strategies were proposed for Xiamen Bay. This study presents an operational approach to provide relevant scientific knowledge on the process of ecosystem-based marine spatial planning, facilitating policy-making decisions in sustainable coastal and marine management.
The Construction and Evolution of Technological Innovation Ecosystem of Chinese Firms: A Case Study of LCD Technology of CEC Panda
Authors: Gan Jingxian , Qi Yong , Tian Chen
Published: November 2019

With a longitudinal case study on the development of Liquid Crystal Display (LCD) technology of China Electronics (CEC) Panda, this study examined how Chinese firms build their technological innovation ecosystem (TIE). We explored the evolution and the driving mechanisms of TIE. The results of the study found: (1) The enterprise’s motivations for innovation and innovation efficiency can be improved when the core enterprise’s TIE is constructed. (2) The evolution of the enterprise’s TIE undergoes three stages: formation period, incubation period, and development period. (3) The interaction between the external factors from the environment and the internal factors from the agent drives the evolution of the TIE (4). Three types of driving modes develop, depending on the nature of the main factor affecting TIE development: extrapolation drive, hybrid drive, and internal drive.
Knowledge Management and the Sustainable Development of Social Work
Authors: Colnar Simon , Dimovski Vlado , Bogataj David
Published: November 2019

The growing shortage of skilled social workers, accompanied by an ageing population and the increasing number of fragile, elderly individuals that require social services, poses a serious challenge for our society. The magnitude of this problem is seen in the various predictions hypothesizing that, globally, there is likely to be a shortfall of millions of social workers for the successful provision of social services. To make matters worse, there are not enough social work students to fill that void, whereas the existing employee turnover is another serious concern for the social work field. Policy makers in many countries do not yet understand the pattern of growing needs and have no tool to forecast the future increase in educational requirements for creating a pool of adequately skilled social workers. In addition to this, understanding the patterns of workforce entrance and exit for social workers and the dynamics of transition becomes important for national policy and decision makers. In our paper, we build on current research about knowledge management in social work settings to demonstrate that knowledge management can have a positive impact in helping to fulfil the important role of social work in any ageing society. With our research, we contribute to the underdeveloped literature about knowledge management in the public sector and especially in social work settings and to the knowledge-based view of the organization. We present a multiple decrement model of social workers’ entrance and transition from social work student and social worker trainee to fully productive social worker, to their exit, whether by changed profession, retirement or death. We argue that the availability of social workers in a national economy depends on the development and operationalization of appropriate policies, where knowledge management can be influential. Our model allows measuring the quality of the national policy system related to the social work profession, something which has not been achieved yet, and shows how knowledge management solutions can positively influence the whole field of social work. We apply an objective measuring tool, grounded in an already developed actuarial–mathematical method. Our case relies on the collection and analysis of relevant data found in publicly available statistical reports for Slovenia. Existing data enables us to provide assumptions on how to better forecast the transition of social workers.
Can I Sustain My Happiness? A Review, Critique and Research Agenda for Economics of Happiness
Authors: Jain Mansi , Sharma Gagan Deep , Mahendru Mandeep
Published: November 2019

Human beings want to live in a state of happiness and prosperity, but happiness is important not just for the well-being of individuals but for the well-being of society. To ensure the maximization of happiness, it is necessary to consider more than just money, and rather include the right understanding of happiness at the individual level, the family level, the society level, and the environmental (nature) level. This paper contributes to the existing body of knowledge by consolidating the findings of the literature; grouping those into major themes and sub-themes; describing the mechanisms based on the empirical papers by highlighting the independent, dependent, control, and moderating variables, to study the causal relationships between variables under study; proposing an agenda for future research; and informing the policymakers about decisions influencing the human happiness level through legislative rules and regulations. Our results suggest prioritizing the conceptualization of happiness while computing the happiness level at the individual or collective levels. Furthermore, the study recommends governments to establish the conditions enabling individuals to report happiness independently from the political pressure to answer strategically for impressive happiness level figures at the macro level.
Median to Strong Rainfall Intensity Favors Carbon Sink in a Temperate Grassland Ecosystem in China
Authors: Hao Guangcun , Hu Zhongmin , Guo Qun , Di Kai , Li Shenggong
Published: November 2019

Over the past 50 years, rainfall events have made significant alterations to environments due to global warming. The grasslands in arid and semi-arid regions are extremely sensitive to variations in rainfall patterns, which are considered to significantly affect ecosystem functions. In this study, an experiment with varying rainfall sizes and frequencies (0 mm, 2 mm, 5 mm, 10 mm, 20 mm, and 40 mm) was conducted during growing seasons in typical grasslands, to study the effect of changes in rainfall regime on net ecosystem exchange (NEE). Our results indicated that NEE exhibited nonlinear responses to rainfall treatments, and reached its peak under 20 mm in middle growing season. Further, the component fluxes of both NEE (i.e., gross primary productivity (GPP)) and ecosystem respiration (ER) illustrated nonlinear responses to treatment gradient, with peak values at 20 mm and 5 mm, respectively. Based on five-year eddy flux measurements, further analyses demonstrated that GPP and ER increased with increasing soil moisture, and net ecosystem carbon uptake (-1*NEE) was significantly stimulated due to a more enhanced GPP than ER, when soil moisture was above 8%. Additionally, we found that the response of root biomass was different from that of carbon fluxes to changes in rainfall patterns. Overall, these findings highlight the importance of both changes in rainfall regimes in controlling ecosystem C exchange and investigation of the potential threshold for ecosystem function shifts, which are crucial to further understand C cycles in grasslands.
Research of the Operator’s Advisory System Based on Fuzzy Logic for Pelletizing Equipment
Authors: Andriukaitis Darius , Laucka Andrius , Valinevicius Algimantas , Zilys Mindaugas , Markevicius Vytautas , Navikas Dangirutis , Sotner Roman , Petrzela Jiri , Jerabek Jan , Herencsar Norbert , Klimenta Dardan
Published: November 2019

Fertilizer manufacturing in the chemical industry is closely related with agricultural production. More than a half of raw materials for food products are grown by fertilizing plants. The demand of fertilizers has been constantly increasing along the growth of human population. Fertilizer manufacturers face millions of losses each year due to poor quality products. One of the most common reasons is wrong decisions in control of manufacturing processes. Operator’s experience has the highest influence on this. This paper analyzes the pellet measurement data, collected at the fertilizer plant by using indirect measurements. The results of these measurements are used to construct the model of equipment status control, based on the fuzzy logic. The proposed solution allows to respond to changes in production parameters in a 7–10 times faster manner. On average, a manufacturer with production volumes of up to 80 tonnes/hour could have lost about 8400 tonnes/year of high-quality production. The publication seeks symmetry between human and system decision making.
Automatic Registration of Multi-Projector Based on Coded Structured Light
Authors: Zhao Shuaihe , Zhao Mengyi , Dai Shuling
Published: November 2019

Multi-projector display systems are widely used in virtual reality, flight simulators, and other entertainment systems. Geometric distortion and color inconsistency are two key problems to be solved. In this paper a geometric correction principle is theoretically demonstrated and a consistency principle of geometric correction is first proposed. A new method of automatic registration of a multi-projector on a curved screen is put forward. Two pairs of binocular-cameras are used to reconstruct the curved screen. To capture feature points of the curved screen precisely, a group of red-blue coded structured light images is designed to be projected onto the screen. Geometric homography between each projector and the curved screen is calculated to gain a pre-warp template. Work which can gain a seamless display is illustrated by a six-projector system on the curved screen.
Novel Fuzzy Clustering Methods for Test Case Prioritization in Software Projects
Authors: Shrivathsan A. D. , Ravichandran K. S. , Krishankumar R. , Sangeetha V. , Kar Samarjit , Ziemba Pawel , Jankowski Jaroslaw
Published: November 2019

Systematic Regression Testing is essential for maintaining software quality, but the cost of regression testing is high. Test case prioritization (TCP) is a widely used approach to reduce this cost. Many researchers have proposed regression test case prioritization techniques, and clustering is one of the popular methods for prioritization. The task of selecting appropriate test cases and identifying faulty functions involves ambiguities and uncertainties. To alleviate the issue, in this paper, two fuzzy-based clustering techniques are proposed for TCP using newly derived similarity coefficient and dominancy measure. Proposed techniques adopt grouping technology for clustering and the Weighted Arithmetic Sum Product Assessment (WASPAS) method for ranking. Initially, test cases are clustered using similarity//dominancy measures, which are later prioritized using the WASPAS method under both inter- and intra-perspectives. The proposed algorithms are evaluated using real-time data obtained from Software-artifact Infrastructure Repository (SIR). On evaluation, it is inferred that the proposed algorithms increase the likelihood of selecting more relevant test cases when compared to the recent state-of-the-art techniques. Finally, the strengths of the proposed algorithms are discussed in comparison with state-of-the-art techniques.
Some Inequalities Using Generalized Convex Functions in Quantum Analysis
Authors: Vivas-Cortez Miguel J. , Kashuri Artion , Liko Rozana , Hernández Jorge E. Hernández
Published: November 2019

In the present work, the Hermite–Hadamard inequality is established in the setting of quantum calculus for a generalized class of convex functions depending on three parameters: a number in ( 0 , 1 ] and two arbitrary real functions defined on [ 0 , 1 ] . From the proven results, various inequalities of the same type are deduced for other types of generalized convex functions and the methodology used reveals, in a sense, a symmetric mathematical phenomenon. In addition, the definition of dominated convex functions with respect to the generalized class of convex functions aforementioned is introduced, and some integral inequalities are established.
Multiple Mycotoxins Determination in Food by LC-MS/MS: An International Collaborative Study
Authors: Bessaire Thomas , Mujahid Claudia , Mottier Pascal , Desmarchelier Aurélien
Published: November 2019

An intercollaborative study was organized to evaluate the performance characteristics of a liquid chromatography tandem mass spectrometry procedure for the simultaneous determination of 12 mycotoxins in food, which were ochratoxin A, aflatoxins B1, B2, G1, G2, and M1, deoxynivalenol, zearalenone, fumonisins B1 and B2, and T-2 and HT-2 toxins. The method combined the simplicity of the QuEChERS (Quick, Easy, Cheap, Efficient, Rugged and Safe) approach with the efficiency of immunoaffinity column cleanup (the step used to enhance sensitivity and sample cleanup for some matrices only). Twenty-three entities were enrolled and were European reference laboratories for mycotoxin analysis, U.S. and European service laboratories, and Nestlé laboratories. Each participant analyzed 28 incurred and/or spiked blind samples composed of spices, nuts, milk powder, dried fruits, cereals, and baby food using the protocol given. Method performances were assessed according to ISO 5725-2. Relative standard deviations of repeatability and reproducibility and trueness values for each of the 115 mycotoxin/sample combinations ranged from 5% to 23%, 7% to 26%, and 85% to 129%, respectively, in line with requirements defined in EC 401/2006. The overall set of data gathered demonstrated that the method offered a unique platform to ensure compliance with EC 1881/2006 and EC 165/2013 regulations setting maximum limits for mycotoxins in food samples, even at low regulated levels for foods intended for infants and young children. The method was applicable regardless of the food, the regulated mycotoxin, and the concentration level, and thus is an excellent candidate for future standardization.
Characterization of Brain Inflammation, Apoptosis, Hypoxia, Blood-Brain Barrier Integrity and Metabolism in Venezuelan Equine Encephalitis Virus (VEEV TC-83) Exposed Mice by In Vivo Positron Emission Tomography Imaging
Authors: Bocan Thomas M. , Stafford Robert G. , Brown Jennifer L. , Akuoku Frimpong Justice , Basuli Falguni , Hollidge Bradley S. , Zhang Xiang , Raju Natarajan , Swenson Rolf E. , Smith Darci R.
Published: November 2019

Traditional pathogenesis studies of alphaviruses involves monitoring survival, viremia, and pathogen dissemination via serial necropsies; however, molecular imaging shifts this paradigm and provides a dynamic assessment of pathogen infection. Positron emission tomography (PET) with PET tracers targeted to study neuroinflammation (N,N-diethyl-2-[4-phenyl]-5,7-dimethylpyrazolo[1,5-a]pyrimidine-3-acetamide, [18F]DPA-714), apoptosis (caspase-3 substrate, [18F]CP-18), hypoxia (fluormisonidazole, [18F]FMISO), blood–brain barrier (BBB) integrity ([18F]albumin), and metabolism (fluorodeoxyglucose, [18F]FDG) was performed on C3H/HeN mice infected intranasally with 7000 plaque-forming units (PFU) of Venezuelan equine encephalitis virus (VEEV) TC-83. The main findings are as follows: (1) whole-brain [18F]DPA-714 and [18F]CP-18 uptake increased three-fold demonstrating, neuroinflammation and apoptosis, respectively; (2) [18F]albumin uptake increased by 25% across the brain demonstrating an altered BBB; (3) [18F]FMISO uptake increased by 50% across the whole brain indicating hypoxic regions; (4) whole-brain [18F]FDG uptake was unaffected; (5) [18F]DPA-714 uptake in (a) cortex, thalamus, striatum, hypothalamus, and hippocampus increased through day seven and decreased by day 10 post exposure, (b) olfactory bulb increased at day three, peaked day seven, and decreased day 10, and (c) brain stem and cerebellum increased through day 10. In conclusion, intranasal exposure of C3H/HeN mice to VEEV TC-83 results in both time-dependent and regional increases in brain inflammation, apoptosis, and hypoxia, as well as modest decreases in BBB integrity; however, it has no effect on brain glucose metabolism.
New Insights into Parvovirus Research
Authors: Gallinella Giorgio
Published: November 2019

The family Parvoviridae includes an ample and most diverse collection of viruses. Exploring the biological diversity and the inherent complexity in these apparently simple viruses has been a continuous commitment for the scientific community since their first discovery more than fifty years ago. The Special Issue of ‘Viruses’ dedicated to the ‘New Insights into Parvovirus Research’ aimed at presenting a ‘state of the art’ in many aspects of research in the field, at collecting the newest contributions on unresolved issues, and at presenting new approaches exploiting systemic (-omic) methodologies.
A PBMC-Based System to Assess Human T Cell Responses to Influenza Vaccine Candidates In Vitro
Authors: Tapia-Calle Gabriela , Born Philip A. , Koutsoumpli Georgia , Gonzalez-Rodriguez Martin Ignacio , Hinrichs Wouter L. J. , Huckriede Anke L. W.
Published: November 2019

Vaccine development is an expensive and time-consuming process that heavily relies on animal models. Yet, vaccine candidates that have previously succeeded in animal experiments often fail in clinical trials questioning the predictive value of animal models. Alternative assay systems that can add to the screening and evaluation of functional characteristics of vaccines in a human context before embarking on costly clinical trials are therefore urgently needed. In this study, we have established an in vitro system consisting of long-term cultures of unfractionated peripheral blood mononuclear cells (PBMCs) from healthy volunteers to assess (recall) T cell responses to vaccine candidates. We observed that different types of influenza vaccines (whole inactivated virus (WIV), split, and peptide vaccines) were all able to stimulate CD4 and CD8 T cell responses but to different extents in line with their reported in vivo properties. In-depth analyses of different T cell subsets revealed that the tested vaccines evoked mainly recall responses as indicated by the fact that the vast majority of the responding T cells had a memory phenotype. Furthermore, we observed vaccine-induced activation of T follicular helper cells, which are associated with the induction of humoral immune responses. Our results demonstrate the suitability of the established PBMC-based system for the in vitro evaluation of memory T cell responses to vaccines and the comparison of vaccine candidates in a human immune cell context. As such, it can help to bridge the gap between animal experiments and clinical trials and assist in the selection of promising vaccine candidates, at least for recall antigens.
Phosphate Induced Arsenic Mobilization as a Potentially Effective In-Situ Remediation Technique—Preliminary Column Tests
Authors: Maier Martin V. , Wolter Yvonne , Zentler Daniel , Scholz Christian , Stirn Charlotte N. , Isenbeck-Schröter Margot
Published: November 2019

Arsenic (As) contamination of groundwater is commonly remediated by pump and treat. However, this technique is difficult to apply or maintain efficiently because the mobility of arsenic varies depending on the geochemical aquifer conditions. Arsenic interacting with the sediment can cause strong retardation, which is counteracted by ions competing for sedimentary sorption sites like silica, bicarbonate and phosphate. Phosphate competes most effectively with arsenic for sorption sites due to its chemical similarity. To accelerate an ongoing but ineffective pump and treat remediation, we examined the competitive effect of increasing phosphate doses on contaminated aquifer material of different depths and thus under distinct geochemical conditions. In the columns with phosphate addition, significant amounts of arsenic were released rapidly under oxic and anoxic conditions. In all tests, the grade of leaching was higher under anoxic conditions than under oxic conditions. As(III) was the dominant species, in particular during the first release peaks and the anoxic tests. Higher amounts of phosphate did not trigger the arsenic release further and led to a shift of arsenic species. We suggest that the competitive surface complexation is the major process of arsenic release especially when higher amounts of phosphate are used. Commonly arsenic release is described at iron reducing conditions. In contrast, we observed that a change in prevailing redox potential towards manganese reducing conditions in the oxic tests and iron reducing conditions in the anoxic column took place later and thus independently of arsenic release. The reduction of As(V) to As(III) under both redox conditions is presumed to be an effect of microbial detoxification. A loss of sulphate in all columns with phosphate indicates an increased microbial activity, which might play a significant role in the process of arsenic release. Preliminary tests with sediment material from a contaminated site showed that phosphate additions did not change the pH value significantly. Therefore, a release of other metals is not likely. Our results indicate that in-situ application of phosphate amendments to arsenic-contaminated sites could accelerate and enhance arsenic mobility to improve the efficiency of pump and treat remediation without negative side effects. The novelty of this approach is the use of only small amounts of phosphate in order to stimulate microbial activity in addition to surface complexation. Therefore, this method might become an innovative and cost-effective remediation for arsenic contaminated sites.
Correlations of Stormwater Runoff and Quality: Urban Pavement and Property Value by Land Use at the Parcel Level in a Small Sized American City
Authors: Zhou Long
Published: November 2019

As the urban environment keeps growing, stormwater management programs have been adopted to address unregulated nonpoint runoff and pollutants across the world. Extensive studies on stormwater runoff and quality at smaller spatial scales exist, but are rare at larger spatial scales. Using the City of Corvallis, Oregon, a small sized American city, as a test-bed, this study estimates urban stormwater runoff and quality by zoning, which specifies land uses, and by parcel, which defines land ownership using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and high resolution land use and land cover data. The correlations between stormwater runoff volume, stormwater quality, parcel land cover sizes, and values are then analyzed and visualized in RStudio. The results indicate that stormwater runoff and quality are determined by complex biophysical processes, with strong correlations between urban spatial sizes and property values for some land uses being observed. The research results provide suggestions for low impact development applications for different land uses, and the findings in this research can be used to suggest stormwater management policy for various land uses in small sized cities.
Urban Flood Hazard Modeling Using Self-Organizing Map Neural Network
Authors: Rahmati Omid , Darabi Hamid , Haghighi Ali Torabi , Stefanidis Stefanos , Kornejady Aiding , Nalivan Omid Asadi , Tien Bui Dieu
Published: November 2019

Floods are the most common natural disaster globally and lead to severe damage, especially in urban environments. This study evaluated the efficiency of a self-organizing map neural network (SOMN) algorithm for urban flood hazard mapping in the case of Amol city, Iran. First, a flood inventory database was prepared using field survey data covering 118 flooded points. A 70:30 data ratio was applied for training and validation purposes. Six factors (elevation, slope percent, distance from river, distance from channel, curve number, and precipitation) were selected as predictor variables. After building the model, the odds ratio skill score (ORSS), efficiency (E), true skill statistic (TSS), and the area under the receiver operating characteristic curve (AUC-ROC) were used as evaluation metrics to scrutinize the goodness-of-fit and predictive performance of the model. The results indicated that the SOMN model performed excellently in modeling flood hazard in both the training (AUC = 0.946, E = 0.849, TSS = 0.716, ORSS = 0.954) and validation (AUC = 0.924, E = 0.857, TSS = 0.714, ORSS = 0.945) steps. The model identified around 23% of the Amol city area as being in high or very high flood risk classes that need to be carefully managed. Overall, the results demonstrate that the SOMN model can be used for flood hazard mapping in urban environments and can provide valuable insights about flood risk management.
Flood Risk Mapping Worldwide: A Flexible Methodology and Toolbox
Authors: Glas Hanne , Rocabado Ivan , Huysentruyt Steven , Maroy Edith , Salazar Cortez Danitza , Coorevits Kobe , De Maeyer Philippe , Deruyter Greet
Published: November 2019

Flood risk assessments predict the potential consequences of flooding, leading to more effective risk management and strengthening resilience. However, adequate assessments rely on large quantities of high-quality input data. Developing regions lack reliable data or funds to acquire them. Therefore, this research has developed a flexible, low-cost methodology for mapping flood hazard, vulnerability and risk. A generic methodology was developed and customized for freely available data with global coverage, enabling risk assessment worldwide. The default workflow can be enriched with region-specific information when available. The practical application is assured by a modular toolbox developed on GDAL and PCRASTER. This toolbox was tested for the catchment of the river Moustiques, Haiti, for which several flood hazard maps were developed. Then, the toolbox was used to create social, economic and physical vulnerability maps. These were combined with the hazard maps to create the three corresponding flood risk maps. After creating these with the default data, more detailed information, gathered during field work, was added to verify the results of the basic workflow. These first tests of the developed toolbox show promising results. The toolbox allows policy makers in developing countries to perform reliable flood risk assessments and generate the necessary maps.
Long-term Oncologic Outcome of Postoperative Complications After Colorectal Cancer Surgery
Authors: Oh Chang Kyu , Huh Jung Wook , Lee You Jin , Choi Moon Suk , Pyo Dae Hee , Lee Sung Chul , Park Seong Mun , Shin Jung Kyong , Park Yoon Ah , Cho Yong Beom , Yun Seong Hyeon , Kim Hee Cheol , Lee Woo Yong
Published: November 2019

Purpose: The impact of postoperative complications on long-term oncologic outcome after radical colorectal cancer surgery is controversial. The aim of this study was to examine the risk factors and oncologic outcomes of surgery-related postoperative complication groups.Methods: From January 2010 to December 2010, 310 patients experienced surgery-related postoperative complications after radical colorectal cancer surgery. These stage I–III patients were classified into 2 subgroups, minor (grades I, II) and major (grades III, IV) complication groups, according to extended Clavien-Dindo classification system criteria. Clinicopathologic differences between the 2 groups were analyzed to identify risk factors for major complications. The diseasefree survival rates of surgery-related postoperative complication groups were also compared.Results: Minor and major complication groups were stratified with 194 patients (62.6%) and 116 patients (37.4%), respectively. The risk factors influencing the major complication group were pathologic N category and operative method. The prognostic factors associated with disease-free survival were preoperative perforation, perineural invasion, tumor budding, and receiving neoadjuvant therapy. With a median follow-up period of 72.2 months, the 5-year disease-free survival rates were 84.4% in the minor group and 78.5% in the major group, but there was no statistical significance between the minor and major groups (P = 0.392).Conclusion: Advanced cancer and open surgery were identified as risk factors for increased surgery-related major complications after radical colorectal cancer surgery. However, severity of postoperative complications did not affect disease-free survival from colorectal cancer.
Abdominopelvic Actinomycosis Mimicking Peritoneal Carcinomatosis: A Case Report
Authors: Kim Sungjin , Kang Sung Il , Kim Sohyun , Jang Min Hye , Kim Jae Hwang
Published: November 2019

Actinomycosis is a rare chronic bacterial infection primarily caused by Actinomyces israelii. A 47-year-old woman presented to our clinic with a 1-week history of lower abdominal pain. Preoperative imaging studies revealed multiple peritoneal and pelvic masses suggestive of malignancy. The primary tumor could not be identified despite further endoscopic and gynecological evaluation. On exploration for tissue confirmation, excisional biopsies from multiple masses were performed because complete excision was not possible. Histopathological examination confirmed actinomycosis with multiple abscesses, and the patient was treated with antibiotics. We present a case of disseminated peritoneal actinomycosis that mimicked malignant peritoneal carcinomatosis on imaging studies.
PVP-Assisted Synthesis of Self-Supported Ni
2
P@Carbon for High-Performance Supercapacitor
Authors: He Qian , Liu Xiong Xiong , Wu Rui , Chen Jun Song
Published: November 2019

Highly conductive and stable electrode materials are usually the focus of high-performance supercapacitors. In this work, a unique design of Ni
2
P@carbon self-supported composite nanowires directly grown on Ni foam was applied for a supercapacitor. The Co
3
O
4
nanowire array was first synthesized on the Ni foam substrate, and the resulting Ni
2
P@carbon nanocomposite was obtained by hydrothermally coating Co
3
O
4
with the Ni-ethylene glycol complex followed by gaseous phosphorization. We have discovered that the molecular weight of surfactant polyvinylpyrrolidone (PVP) used in the hydrothermal step, as well as the temperature for phosphorization, played very important roles in determining the electrochemical properties of the samples. Specifically, the sample synthesized using PVP with 10 k molecular weight and phosphorized at 300°C demonstrated the best supercapacitive performance among the different samples, with the highest capacitance and most stable cyclic retention. When an asymmetric supercapacitor (ASC) was assembled with this Ni
2
P@carbon sample as the cathode and activated carbon (AC) as the anode, the ASC device showed excellent capacitances of 3.7 and 1.6 F cm
-2
at 2 and 50 mA cm
-2
, respectively, and it kept a high capacitance of 1.2 F cm
-2
after 5000 cycles at a current rate of 25 mA cm
-2
. In addition, the ASC could reach a high energy density of about 122.8 Wh kg
-1
at a power density of 0.15 kW kg
-1
and 53.3 Wh kg
-1
at the highest power density of 3.78 kW kg
-1
. Additionally, this device also had the ability to power up 16 red LEDs effortlessly, making it a strong candidate in electrochemical energy storage for practical usage.
PCR DIAGNOSTICS OF COLLETOTRICHUM COCCODES
IN POTATO LEAVES
Authors: Belov Grigory , Belosohov Arseny , Kutuzova Irina , Kokaeva Ludmila , Elansky Sergey , Zeyruk Vladimir , Derevyagina Marina , Vasilieva Svetlana
Published: November 2019

Colletotrichum coccodes is a plant pathogenic fungus affecting different organs of potato, tomato, and some other plants. The leaf infection with C. coccodes may result in a rapid development of infection nidus and high losses caused by the infection of potato tubers during harvesting. Our study showed the presence of C. coccodes on potato leaves with dry necrotic lesions. The presence of a DNA region specific for C. coccodes was detected in DNA isolated from five potato leaf samples: one from the Northern Ossetia, one from the Kostroma region, and three from the Mari El Republic.
INNOVATION IN COMBINATION WITH DIGITIZATION - THE MOST IMPORTANT DIRECTION OF POSTINDUSTRIAL DEVELOPMENT OF RUSSIA
Authors: Zeldner Alexey
Published: November 2019

The article considers the introduction of modern digital technologies in domestic agriculture. The author insists that innovative activities involving the implementation of the function of science to achieve national strategic goals ultimately ensure the competitiveness of products of domestic industries and enterprises and profit for conducting production on an expanded basis. The implementation of such a policy requires the availability of appropriate investments in order to develop and introduce innovations and digital technologies in the practical activities of enterprises.
Yeşeya:58 Bağlamında Yahudilik, Hristiyanlık ve İslam’da Makbul Orucun Anlamı
Authors: DÖLEK İlbey
Published: November 2019

Makbul orucu, Tanrı’nın
kullarından istediği ve bundan hoşnut olacağı gerçek ya da doğru oruç olarak
tarif etmek mümkündür. Bakara suresi 183. ayette geçen “oruç size farz
kılındığı gibi sizden öncekilere de farz kılınmıştır” ifadesinden hareketle
İslam’dan önce Yahudileri ve Hristiyanları içine alan diğer din mensupları için
de oruç tutmanın emredildiği anlaşılmaktadır. Bu makale, Kuran’ın dışında
Yahudi ve Hristiyan kutsal metinlerinde oruç nasıl anlatılmaktadır? Söz konusu
dinlerin kutsal metinlerinde makbul oruç tasvirleri arasında ne tür benzerlik
ve farklar bulunmaktadır? Tanah’ın Yeşaya Kitabı, 58. bölümündeki “Gerçek
Oruç” bağlamında oruç ibadetinin özünde ne vardır? ve Rab’bin hoşnut
olacağı makbul orucun fenomenolojik anlamda özellikleri nelerdir? sorularına
odaklanmaktadır.  Kadim bir geçmişi olan
oruç ibadetinin gizli ve gösterişten uzak yapılması kutsal metinlerin ortak
tavsiyesidir.  Bunun yanında hem insanın
kendi nefsini terbiye etmede bir araç hem de Tanrı ile olan ilişkisinde
yakınlaşmayı sağlayan bir ibadet olarak orucun, Tanrı katında makbul bir değere
sahip olması için ahkâmı yanında adabının ve esrarının (hikmet) da gözetilmesi
gerektiği kutsal metinlerde ifade edilmektedir.
Weather Prediction using Multiple IoT Based Wireless Sensor
Authors:   P.G. Student, Department of E&TC Engineering, Dr. D. Y. Patil School of Engineering, Charholi(bk), Pune, (MH), India., Sah Heeralal Kumar , Koli Dr. S. M. ,   Professor, Department of E&TC Engineering, Dr. D.Y.Patil School of Engineering, Charholi (Bk), Pune, MH, India.
Published: November 2019

Environmental monitoring has become extremely important due to recent changes in the climate. It is important for ensuring a safe and wealthy life of both humans and artifacts. This field is based on remote sensing and wireless sensor networks for gathering data about the environment. Recent advancements, for example, the vision of the Internet of Things (IoT), the distributed computing model, and digital physical frameworks support the transmission and management of huge amounts of data relating to the trends determined in environmental parameters. In this context, the paper presents three different IoT-based wireless sensors for weather prediction and environmental monitoring: one employing User Datagram Protocol (UDP)-based Wi-Fi communication, second communicating through Wi-Fi and Hypertext Transfer Protocol (HTTP), and a third one using Bluetooth communication. The system consists of three different wireless sensor nodes based on Node-MCU Wi-Fi module or Arduino microcontroller that is connected to the internet, and a firebase cloud server, which provides information storage and delivery to remote clients. In addition, to view the result output in an effective and user friendly manner, MIT App Inventor is used to develop applications for Android phones using a web browser and either an associated phone or the on-screen phone person. The system conducts a lookup table which contains the value of temperature, humidity, real time rain, and a level of carbon monoxide (CO) and are used to predict the current environmental conditions.
Detecting Forged E-Mail using Data Mining Techniques
Authors:   Professor, Department of Computer Science and Engineering, Sreenidhi Institute of Science and Technology, Yamnampet, Ghatkesar, Hyderabad, Telangana, India., Sahoo Dr. Prasanta Kumar , Rajitha Cheguri ,   Department of Computer Science and Engineering, Sreenidhi Institute of Science and Technology, Yamnampet, Ghatkesar, Hyderabad, Telangana, India.
Published: November 2019

In the modern era of computers E-mails is becoming a very important mode of communication for industry, people, and organizations and for the society as a whole. Especially in corporate sectors and business organizations, E mails are widely used for business and personal communication. The feature of E-mails is that, it creates quick, reliable type of communication that’s all free and simply accessible. In spite of so many alternative means of communication such as messages, social networks like WhatsApp, Twitter, and mobile applications, the uses of E-mails continuously growing exponentially. But due to its popularity there are continuously threats and attacks are carried out over E-mails for various gain. The foremost popular attack over the web is phishing mails. Phishers utilize E-mail services quite expeditiously in spite of different detection and hindrance techniques already in situ. Most of the present day phishing attacks use E-mail as the primary carrier. Phishers conceive to fraudulently acquire sensitive information, like usernames, passwords and master card details, by masquerading as a trustworthy entity in transmission. Even though there are a lot of existing techniques offered to notice phishing attacks, every one of them have their own limitations. This research aims to identify the phishing E-mails using classification techniques with a better accuracy. The technique proposed in this research work to classify forged E-mails from the Genuine E-mails and also examines the effectiveness of detection of common user’s phishing E-mails. It provides a great help to the common man by proper detection of phishing attacks and protecting their confidential data.
Hierarchical Energy Efficient Routing in Wireless Sensor Networks and its Challenges
Authors:   Research Scholar, Department of Computer Science and Engineering, I. K. Gujral Punjab Technical University, Jalandhar, Punjab, India., Varun Rajesh Kumar , Gangwar Dr. R. ,   Professor, Department of Computer Science and Engineering, BCET, Gurudaspur, Punjab, India.
Published: November 2019

Wireless sensor network consists of various sensor nodes connected through wireless media. Sensor nodes are tiny devices having lesser energy capabilities. Sensor nodes are either ad-hoc or mobile in their environment. Wireless sensor network route of transmission media is discovered by routing protocols and responsible for secure communication between sensor nodes. Energy is a precious resource of sensor nodes, and the entire lifetime of WSNs is depending on the energy capability of the sensor nodes. The fundamental problem is how to organize topology of WSN for deployed sensor nodes with lesser power consumption as possible. Major problems in wireless sensor networks which consume extra energy are interference, control message overhead, packet delay, unnecessary transmission, and bandwidth utilization. Therefore, energy efficient techniques are needed to overcome these problems. Hierarchical routing is the best routing method for finding optimal path between sensor nodes which enhance the lifetime of the network. This paper focuses towards various hierarchical energy efficient routing in wireless sensor networks and analyzes various features of WSN that should consider during designing of routing protocols.
Technique t o Generate t he Secure Symmetric Key U nder Variable Keys Environment u sing Genetic Algorithm
Authors:   Department of Computer Science and Engineering, National Institute of Technology, Arunachal Pradesh, India,, Chunka* Chukhu , Banerjee Subhasish ,   Department of Computer Science and Engineering, National Institute of Technology, Arunachal Pradesh, India,, Goswami Rajat Subhra ,   Department of Computer Science and Engineering, National Institute of Technology, Arunachal Pradesh, India,
Published: November 2019

The purpose of information security is to protect information or data from misuse, unauthorized access and also to ensure the secured communication between transmitter and receiver. In this regard, one of the primary and foremost necessity is to protect the key by any means and should also be unbreakable. In this context, a mechanism namely, Automatic Variable Key (AVK) has been introduced to maintain the secrecy of the key. However, in this approach the initial key must be established earlier, then only it changes the keys and make unpredictable to guess, for every new block of data transmission. Thus, to overcome from this extra burden of initial distribution of key, we propose a new technique using Artificial Intelligent (AI) in order to generate the initial key automatically using the Genetic Algorithm (GA). We have demonstrated the importance of AI in the area of cryptography by our scheme. A comparative study is also carried out with the existing schemes to prove the proficiency of proposed scheme. Thus, in order to prove the unpredictability among the auto-generated keys, we have verified the randomness with the help of National Institute of Standards Technology (NIST) Test suite.