bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ensemble approach for network threat detection and classification on cloud computing
Authors: Krishnaveni S. , Prabakaran S. 
Published: May 2019

SummaryAs Network traffic rises and attacks become more widespread and complicated, we must come across Innovative ways to enrich Intrusion Detection Systems in Cloud Computing. This paper proposes the Ensemble approaches for Network Intrusion Detection and Classification in Cloud. The major aids of the Ensemble Learning to improve the outcome of each Machine Learning Algorithms and to get a robust Classifier. Real Time Malicious Network Streams Samples were collected using Honeynet, which is deployed on cloud environment. We use supervised learning and Unsupervised learning algorithms for classifying the known malicious network streams and unknown malicious streams. Network related attacks can be segregated into four classes, namely, Denial of service (DOS), User to root (U2 R), Remote to local (R2L), and probe, and the vital constraints that must be overcome with the end goal to build efficient Intelligent Intrusion Detection. The motivation behind the proposed work is to enhance the accuracy rate with response time. The outcome obtained from the Ensemble method has better accuracy rate compared to the SVM, Naive Bayes, and Logistic regression method.
Continuous‐Flow Oxidation of HMF to FDCA by Resin‐Supported Platinum Catalysts in Neat Water
Authors: Liguori Francesca , Barbaro Pierluigi , Calisi Nicola 
Published: May 2019

AbstractThe oxidation reaction of 5‐hydroxymethylfurfural to the bioplastic monomer 2,5‐furandicarboxylic acid over heterogenous resin‐supported Pt catalysts was investigated in detail, under continuous flow, base‐free conditions, and in neat water. The product was continuously obtained in 99 % yield by running the reaction at 120 °C, 303 s residence time, 1.2 mL min−1 O2 flow rate, and 7.7 bar O2 pressure. The product was isolated with a high space‐time‐yield of 46.0 g L−1 h−1 without purifications or acid/base treatments.
Using alpha, beta, and zeta diversity in describing the health of stream‐based benthic macroinvertebrate communities
Authors: Simons Ariel Levi , Mazor Raphael , Stein Eric D. , Nuzhdin Sergey 
Published: May 2019

AbstractEcological monitoring of streams has frequently focused on measures describing the taxonomic, and sometimes functional, α diversity of benthic macroinvertebrates (BMIs) within a single sampled community. However, as many ecological processes effectively linkBMIstream communities there is a need to describe groups of communities using measures of regional diversity. Here we demonstrate a role for incorporating both a traditional pairwise measure of community turnover, β diversity, in assessing community health as well as ζ diversity, a more generalized framework for describing similarity between multiple communities. Using 4,395 samples ofBMIstream communities in California, we constructed a model using measures of α, β, and ζ diversity, which accounted for 71.7% of among‐watershed variation in the mean health of communities, as described by the California Streams Condition Index (CSCI). We also investigated the use of ζ diversity in assessing models of stochastic vs. niche assembly across communities ofBMIs within watersheds, with the niche assembly model found to be the likelier of the two.
Postrelease monitoring habitat selection by reintroduced burchell's zebra and blue wildebeest in southern Mozambique
Authors: Mandlate Luís Comissário , Cuamba Ezidio da Lucia , Rodrigues Flávio H. G. 
Published: May 2019

AbstractAimIn Africa, reintroduction of wild animal species to conservation areas is a common practice, for the recovery or restoration of populations. Effective monitoring of reintroduced species requires understanding of basic ecological requirements such as habitat selection of these species in the new environment. Therefore, the present study investigated the habitat selection of zebra and wildebeest following their reintroduction into Maputo Special Reserve, south Mozambique, and we use binary logistic analyses to investigate the relative influence of biotic and abiotic factors in determining the habitat use.LocationMaputo Special Reserve, south Mozambique.MethodsWe conducted the study from July 2016 to June 2017. The data were collected by direct observation, driving the vehicle along the reserve's roads that covered the vegetation communities where zebras and wildebeest are known to commonly occur. Habitat selection was calculated using selection indices (Manly's alpha), and binary logistic analyses were used to investigate the relative influence of biotic and abiotic factors in determining the habitat use.ResultsThe arboreal savanna was the preferred habitat by both herbivore species. Habitat use of zebra appeared to be strongly determined by characteristics such as high grass cover, high grass greenness, and distance to water, while the habitat use by wildebeest, was strongly affected by grass height.Main conclusionsBoth zebra and wildebeest prefer arboreal savanna, forage selection likely drove preference of this habitat. Greater grass cover and greater percentage greenness of the grass both significantly increased the odds of zebra use of habitat, whereas the odds of use decreased with increases in distance to water, meaning an opportunity to ingest large amounts of grass biomass with higher quality, and this opportunity decreases with increasing in distance to water. Grass height was in the highest‐ranking model predicting habitat use by wildebeest, and during the dry season the use of habitat increased with increasing grass height, suggesting that selecting areas with tall grasses by wildebeest equated to choosing areas with higher grass quantity, as the food intake rate increases with grass height.
Give chance a chance: from coexistence to coviability in biodiversity theory
Authors: Jeltsch Florian , Grimm Volker , Reeg Jette , Schlägel Ulrike E. 
Published: May 2019

AbstractA large part of biodiversity theory is driven by the basic question of what allows species to coexist in spite of a confined number of niches. A substantial theoretical background to this question is provided by modern coexistence theory (MCT), which rests on mathematical approaches of invasion analysis to categorize underlying mechanisms into factors that reduce either niche overlap (stabilizing mechanisms) or the average fitness differences of species (equalizing mechanisms). While MCT has inspired biodiversity theory in the search for these underlying mechanisms, we feel that the strong focus on coexistence causes a bias toward the most abundant species and neglects the plethora of species that are less abundant and often show high local turnover. Given the more stochastic nature of their occurrence, we advocate a complementary cross‐level approach that links individuals, small populations, and communities and explicitly takes into account (1) a more complete inclusion of environmental and demographic stochasticity affecting small populations, (2) intraspecific trait variation and behavioral plasticity, and (3) local heterogeneities, interactions, and feedbacks. Focusing on mechanisms that drive the temporary coviability of species rather than infinite coexistence, we suggest a new approach that could be dubbed coviability analysis (CVA). From a modeling perspective, CVA builds on the merged approaches of individual‐based modeling and population viability analysis but extends them to the community level. From an empirical viewpoint, CVA calls for a stronger integration of spatiotemporal data on variability and noise, changing drivers, and interactions at the level of individuals. The resulting large volumes of data from multiple sources could be strongly supported by novel techniques tailored to the discovery of complex patterns in high‐dimensional data. By complementing MCT through a stronger focus on the coviability of less common species, this approach can help make modern biodiversity theory more comprehensive, predictive, and relevant for applications.
The amphibian‐killing fungus in a biodiversity hotspot: identifying and validating high‐risk areas and refugia
Authors: Bacigalupe Leonardo D. , Vásquez Inao A. , Estay Sergio A. , Valenzuela‐Sánchez Andrés , Alvarado‐Rybak Mario , Peñafiel‐Ricaurte Alexandra , Cunningham Andrew A. , Soto‐Azat Claudio 
Published: May 2019

AbstractAmphibian chytridiomycosis, due to infection with the fungusBatrachochytrium dendrobatidis(Bd), has been associated with the alarming decline and extinction crisis of amphibians worldwide. It is essential for conservation management to identify regions with high or low suitability forBd. We use a species distribution model to estimate the environmental suitability ofBdin the Chilean Winter Rainfall–Valdivian Forest biodiversity hotspot. Fourteen environmental variables were used as predictors in the statistical modeling (Maxent, generalized linear models, random forest) which also included 56 independentBd+ localities. High‐risk areas (i.e., suitability above a defined threshold) were validated through prospective field surveys conducted in 2017. As results from Maxent, which only uses presence data, were the only results retained, refugia (i.e., suitability below a defined threshold) were validated with theBdabsences (N = 12) used in the GLM and RF modeling. Our results showed that (1) suitability forBdincreased with human footprint and with shorter distances to urban centers and water bodies and decreased with elevation; (2) climate was not a major factor shaping the current distribution ofBd; and (3) the model predicted high‐risk and refugia areas fairly well. Surveys of 24 new localities in high‐risk areas confirmed that 23 wereBd+; hence, these areas warrant consideration for long‐termBdsurveillance, population monitoring, and disease mitigation. In addition, five localities with apparentBdabsence were found in the predicted high‐risk areas. Our models showed that refugia can exist near high‐risk areas andBd+ sites. Four localities with apparentBdabsence were located within the refugia predicted by the model. PreventingBdtransmission to such refugia is of paramount importance for persistence ofBd‐susceptible amphibian populations. The identification and validation through prospective field surveys of high‐risk areas and refugia are imperative to develop strategies to prevent further arrival and establishment ofBdand also, by identifying amphibian species or populations of conservation concern in such areas, will help to guide specific actions to reduce the biodiversity loss caused by chytridiomycosis.
Inferring critical thresholds of ecosystem transitions from spatial data
Authors: Majumder Sabiha , Tamma Krishnapriya , Ramaswamy Sriram , Guttal Vishwesha 
Published: May 2019

AbstractEcosystems can undergo abrupt transitions between alternative stable states when the driver crosses a critical threshold. Dynamical systems theory shows that when ecosystems approach the point of loss of stability associated with these transitions, they take a long time to recover from perturbations, a phenomenon known as critical slowing down. This generic feature of dynamical systems can offer early warning signals of abrupt transitions. However, these signals are qualitative and cannot quantify the thresholds of drivers at which transition may occur. Here, we propose a method to estimate critical thresholds from spatial data. We show that two spatial metrics, spatial variance and autocorrelation of ecosystem state variable, computed along driver gradients can be used to estimate critical thresholds. First, we investigate cellular‐automaton models of ecosystem dynamics that show a transition from a high‐density state to a bare state. Our models show that critical thresholds can be estimated as the ecosystem state and the driver values at which spatial variance and spatial autocorrelation of the ecosystem state are maximum. Next, to demonstrate the application of the method, we choose remotely sensed vegetation data (Enhanced Vegetation Index, EVI) from regions in central Africa and northeast Australia that exhibit alternative states in woody cover. We draw transects (8 × 90 km) that span alternative stable states along rainfall gradients. Our analyses of spatial variance and autocorrelation of EVI along transects yield estimates of critical thresholds. These estimates match reasonably well with those obtained by an independent method that uses large‐scale (250 × 200 km) spatial data sets. Given the generality of the principles that underlie our method, our method can be applied to a variety of ecosystems that exhibit alternative stable states.
Essential role of IκBNS for in vivo CD4+ T‐cell activation, proliferation, and Th1‐cell differentiation during Listeria monocytogenes infection in mice
Authors: Frentzel Sarah , Katsoulis‐Dimitriou Konstantinos , Jeron Andreas , Schmitz Ingo , Bruder Dunja 
Published: May 2019

AbstractAcquisition of effector functions in T cells is guided by transcription factors, including NF‐κB, that itself is tightly controlled by inhibitory proteins. The atypical NF‐κB inhibitor, IκBNS, is involved in the development of Th1, Th17, and regulatory T (Treg) cells. However, it remained unclear to which extend IκBNS contributed to the acquisition of effector function in T cells specifically responding to a pathogen during in vivo infection. Tracking of adoptively transferred T cells in Listeria monocytogenes infected mice antigen‐specific activation of CD4+ T cells following in vivo pathogen encounter to strongly rely on IκBNS. While IκBNS was largely dispensable for the acquisition of cytotoxic effector function in CD8+ T cells, IκBNS‐deficient Th1 effector cells exhibited significantly reduced proliferation, marked changes in the pattern of activation marker expression, and reduced production of the Th1‐cell cytokines IFN‐γ, IL‐2, and TNF‐α. Complementary in vitro analyses using cells from novel reporter and inducible knockout mice revealed that IκBNS predominantly affects the early phase of Th1‐cell differentiation while its function in terminally differentiated cells appears to be negligible. Our data suggest IκBNS as a potential target to modulate specifically CD4+ T‐cell responses.
Cognitive Internet of Vehicles and disaster management: A proposed architecture and future direction
Authors: Arooj Ansif , Farooq Muhammad Shoaib , Umer Tariq , Shan Rafi Us 
Published: May 2019

AbstractHistorically, the vehicle has just been a component of the human ambulatory system and slave to the commands of driving force. However, recent advancement in technologies such as 5G wireless systems, cloud/edge computing, machine learning, artificial intelligence, and deep learning have opened the new paradigm of the Cognitive Internet of Vehicles (CIoV). The network of heterogeneous intelligent vehicles, not only having the social interaction capabilities but also have the ability to visualize, capture, and disseminate information to dynamic cognitive engines for identifying and analyzing different patterns and prediction of optimized outcomes. From secure navigation to traffic control, transportation security for pollution control has advocated plausible applications in real‐time operations of Internet of Vehicles in humanitarian operations. Proceeding this research, this paper aimed to propose a state‐of‐the‐art architecture based on CIoV for identifying emerging capabilities of available technologies to observe, detect, and mitigate natural disasters, and to develop the CIoV ecosystem for processing the global scale data for intelligent decision making and better service provisioning in natural disaster management.
Physical activity and incident dementia in older Japanese adults: The Okayama study
Authors: Liu Yangyang , Mitsuhashi Toshiharu , Yamakawa Michiyo , Sasai Megumi , Tsuda Toshihide , Doi Hiroyuki , Hamada Jun 
Published: May 2019

ObjectiveTo evaluate the association between regular physical activity and the risk of incident dementia in older Japanese adults.MethodsThis was a retrospective cohort study performed in Okayama City, Japan. Overall, 51 477 older Japanese adults were followed from 2008 to 2014. A health checkup questionnaire was used to assess regular physical activity. The Dementia Scale of long‐term care insurance was used as a measure of incident dementia. Cox proportional hazard models were used to calculate adjusted hazard ratios, with their 95% confidence intervals, for the incidence of dementia across the categories of physical activity.ResultsDuring a 7‐year follow‐up, 13 816 subjects were considered as having incident dementia. Compared with participants who performed physical activity less than or equal to one time per week, the multivariate adjusted hazard ratio values (95% confidence intervals) for participants who performed physical activity greater than or equal to two times per week but not every day and those who performed physical activity every day were 0.79 (0.75‐0.84) and 0.94 (0.89‐0.98), respectively. The interaction of physical activity and sex was statistically significant (P < .01). In subgroup analysis, the multivariate‐adjusted hazard ratio values (95% confidence intervals) remained low, at 0.76 (0.70‐0.84) in males and 0.81 (0.76‐0.87) in females who performed physical activity greater than or equal to two times per week but not every day; they were 0.82 (0.76‐0.89) in males and 1.01 (0.95‐1.07) in females who performed physical activity every day.ConclusionsRegular physical activity could reduce the risk of incident dementia in older Japanese adults, except females who performed physical activity every day.
Beyond the cost‐effectiveness acceptability curve: The appropriateness of rank probabilities for presenting the results of economic evaluation in multiple technology appraisal
Authors: Epstein David 
Published: May 2019

AbstractThe cost‐effectiveness acceptability curve (CEAC) shows the probability that an option ranks first for net benefit. Where more than two options are under consideration, the CEAC offers only a partial picture of the decision uncertainty. This paper discusses the appropriateness of showing the full set of rank probabilities for reporting the results of economic evaluation in multiple technology appraisal (MTA). A case study is used to illustrate the calculation of rank probabilities and associated metrics, based on Monte Carlo simulations from a decision model. Rank probabilities are often used to show uncertainty in the results of network meta‐analysis, but until now have not been used for economic evaluation. They may be useful decision‐making tools to complement the CEAC in specific MTA contexts.
Microwave‐Assisted Synthesis and Transformations of Cationic CpRu(II)(naphthalene) and CpRu(II)(naphthoquinone) Complexes
Authors: Bocekova‐Gajdošíkova Eva , Epik Bugra , Chou Jingyu , Akiyama Katsuhiro , Fukui Nobuaki , Guénée Laure , Kündig E. Peter 
Published: May 2019

AbstractDetails of the direct synthesis of cationic Ru(II)(η5‐Cp)(η6‐arene) complexes from ruthenocene using microwave heating are reported. Developed for the important catalyst precursor [Ru(II)(η5‐Cp)(η6‐1‐4,4a,8a‐naphthalene)][PF6] reaction time could be shortened from three days to 15 min. The method was extended to [Ru(II)(η6‐benzene)(η5‐Cp)][PF6], [Ru(II)(η5‐Cp)(η6‐toluene)][PF6], [Ru(II)(η5‐Cp)(η6‐mesitylene)][PF6], [Ru(II)(η5‐Cp)(η6‐hexamethylbenzene)][PF6], [Ru(II)(η5Cp)(η6‐indane)][PF6], [Ru(II)(η5‐Cp)(η6‐2,6‐dimethylnaphthalene)][PF6], and [Ru(II)(η5‐Cp)(η6‐pyrene)][PF6]. 1‐methylnaphthalene and 2,3‐dimethylnaphthalene afforded mixtures of regioisomeric complexes. [Ru(Cp)(CH3CN)3][PF6], derived from the naphthalene precursor provided access to the cationic RuCp complexes of naphthoquinone, tetralindione, 1,4‐dihydroxynaphthalene, and 1,4‐dimethoxynaphthalene. Reduction of the tetralindione complex afforded selectively the endo,endo diol derivative. X‐Ray structures of five complexes are reported.
Validation of AIST-SHANEL Model Based on Spatiotemporally Extensive Monitoring Data of Linear Alkylbenzene Sulfonate in Japan: Toward a Better Strategy on Deriving Predicted Environmental Concentrations
Authors: Nishioka Tohru , Iwasaki Yuichi , Ishikawa Yuriko , Yamane Masayuki , Morita Osamu , Honda Hiroshi 
Published: May 2019

Abstract
Strategies for deriving predicted environmental concentrations (PECs) using environmental exposure models have become increasingly important in the environmental risk assessment of chemical substances. However, many strategies are not fully developed owing to uncertainties in the derivation of PECs across spatially extensive areas. Here, we used 3-year environmental monitoring data (river: 11 702 points; lake: 1867 points; sea: 12 points) on linear alkylbenzene sulfonate (LAS) in Japan to evaluate the ability of the National Institute of Advanced Industrial Science and Technology (AIST)-Standardized Hydrology-Based Assessment Tool for the Chemical Exposure Load (SHANEL) model developed to predict chemical concentrations in major Japanese rivers. The results indicate that the estimation ability of the AIST-SHANEL model conforms more closely to the actual measured values in rivers than it does for lakes and seas (correlation coefficient: 0.46; proportion within the 10× factor range: 82%). In addition, the 95th percentile, 90th percentile, 50th percentile, and mean values of the distributions of the measured values (14 µg/L, 8.2 µg/L, 0.88 µg/L, and 3.4 µg/L, respectively) and estimated values (19 µg/L, 13 µg/L, 1.4 µg/L, and 4.2 µg/L, respectively) showed high concordance. The results suggest that AIST-SHANEL may be useful in estimating summary statistics (e.g., 95th and 90th percentiles) of chemical concentrations in major rivers throughout Japan. Given its practical use and high accuracy, these environmental risk assessments are suitable for a wide range of regions and can be conducted using representative estimated values, such as the 95th percentile. Integr Environ Assess Manag 2019;15:750–759. © 2019 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
Spectroelectrochemistry of Quantum Dots
Authors: Garoz‐Ruiz Jesus , Perales‐Rondon Juan V. , Heras Aranzazu , Colina Alvaro 
Published: May 2019

AbstractSpectroelectrochemistry (SEC) is a set of techniques with many advantages in the study and characterization of materials. Although SEC has not yet been widely used to study quantum dots (QDs), the information extracted from SEC experiments about these nanostructures is very useful. Most of the works that use SEC to study QDs are high‐quality pieces of research. This review intends to show how to perform SEC in an easy way and what information can be obtained using these techniques. Most of the examples shown in this review are related to semiconductor and carbon QDs. After a brief introduction, some optoelectronic properties of QDs and the main SEC techniques are described. The capabilities of SEC for the study of QDs are illustrated with examples extracted from literature. Finally, the needs of SEC to become a user‐friendly technique and its evolution to become more powerful are commented in the last section of the review.