bluuebunny/crossref_metadata_2025_split huggingface dataset:
Response to “Impact of Zeolite Structure on Entropic–Enthalpic Contributions to Alkane Monomolecular Cracking: An IR Operando Study”
Authors: Janda Amber , Lin Li‐Chiang , Vlaisavljevich Bess , Van der Mynsbrugge Jeroen , Bell Alexis T. 
Published: May 2019

AbstractThis is a response to the paper published by S. A. Kadam, H. Li, R. F. Wormsbacher, A. Travert, Chem. Eur. J. 2018, 24, 5489. Key consistencies between our reported results and those reported in this work are also highlighted.
Antibody–Prodrug Conjugates with KSP Inhibitors and Legumain‐Mediated Metabolite Formation
Authors: Lerchen Hans‐Georg , Stelte‐Ludwig Beatrix , Berndt Sandra , Sommer Anette , Dietz Lisa , Rebstock Anne‐Sophie , Johannes Sarah , Marx Leo , Jörißen Hannah , Mahlert Christoph , Greven Simone 
Published: May 2019

AbstractInvited for the cover of this issue is the group of Hans‐Georg Lerchen and colleagues from Bayer AG R&D Pharmaceuticals. The image, provided by J. Franz and graphic designers from The New Atlantic (Cologne), depicts a cartoon representation of the legumain‐mediated cleavage of the peptide cap within the lysosome. Read the full text of the article at 10.1002/chem.201900441.
Ersatzkältemittel ohne Kompromisse
Authors: Förster Janko 
Published: May 2019

AbstractAb dem Jahr 2020 gilt die nächste Stufe der EU Kältemittelregelung/F‐Gase‐Verordnung (EU) Nr. 517/2014 für fluorierte Treibhausgase. Das verschärft die Auflagen für Hersteller von Anlagen mit FKW‐Kältemitteln deutlich und bedeutet neue Anforderungen für Betreiber von Bestandsanlagen hinsichtlich ihrer Prüf‐ und Dokumentationspflichten. Darüber hinaus ist abzusehen, dass sich bisher oft eingesetzte Kältemittel knapper und teurer werden.
Practical Considerations in Particle and Object Tracking and Analysis
Authors: Aaron Jesse , Wait Eric , DeSantis Michael , Chew Teng‐Leong 
Published: May 2019

AbstractThe rapid advancement of live‐cell imaging technologies has enabled biologists to generate high‐dimensional data to follow biological movement at the microscopic level. Yet, the “perceived” ease of use of modern microscopes has led to challenges whereby sub‐optimal data are commonly generated that cannot support quantitative tracking and analysis as a result of various ill‐advised decisions made during image acquisition. Even optimally acquired images often require further optimization through digital processing before they can be analyzed. In writing this article, we presume our target audience to be biologists with a foundational understanding of digital image acquisition and processing, who are seeking to understand the essential steps for particle/object tracking experiments. It is with this targeted readership in mind that we review the basic principles of image‐processing techniques as well as analysis strategies commonly used for tracking experiments. We conclude this technical survey with a discussion of how movement behavior can be mathematically modeled and described. © 2019 by John Wiley & Sons, Inc.
Parallel simulation of the synchronization of heterogeneous cells in the sinoatrial node
Authors: Nicolás Mata Aurelio , Román Alonso Graciela , López Garza Gabriel , Godinez Fernández José Rafael , Castro García Miguel Alfonso , Castellanos Ábrego Norma Pilar 
Published: May 2019

SummaryThe cells of the sinoatrial node (SAN) are self‐excitable entities that show a coupled electrical pattern that consists of the synchronized activation of action potentials that determine the heart rate. To accurately describe the behavior of cell membrane proteins, theoretical biophysicists have devoted themselves to the study of the electrical activity of individual cells, which involves solving a large number of coupled differential equations. This computational limitation makes the modeling of a large number of cells unattainable, since the intracellular distribution of Ca2+ must be considered and this fact increases in grand extent the number of differential equations involved. In this work, we explore different parallel architectures (using OpenMP, MPI, and CUDA libraries) to show advances in the computational modeling and simulation of the SAN using a multicellular array in which the cells are endowed of heterogeneous conductances and are electrically coupled, considering a variable connectivity among them.
Haloperidol‐Induced Preclinical Tardive Dyskinesia Model in Rats
Authors: Guzen Fausto Pierdoná , Cavalcanti José Rodolfo Lopes de Paiva , Cavalcanti Diogo Manuel Lopes de Paiva , de Sales Luma Gabrielle Praxedes , da Silva Monalisa Stefany Martins , da Silva Aline Naiara Azevedo , Pinheiro Francisco Irochima , de Araújo Dayane Pessoa 
Published: May 2019

AbstractHaloperidol is a first‐generation antipsychotic used in the treatment of psychoses, especially schizophrenia. This drug acts by blocking dopamine D2 receptors, reducing psychotic symptoms. Notwithstanding its benefits, haloperidol also produces undesirable impacts, in particular extrapyramidal effects such as tardive dyskinesia (TD), which limit the use of this and related drugs. TD is characterized by repetitive involuntary movements occurring after chronic exposure therapy with haloperidol. Symptoms most commonly manifest in the orofacial area and include involuntary movements, tongue protrusion, pouting lips, chewing in the absence of any object to chew, and facial grimacing. The most serious aspect of TD is that it may persist for months or years after drug withdrawal and is irreversible in some patients. This unit, aimed at facilitating the study of TD, describes methods to induce TD in rats using haloperidol, as well as procedures for evaluating the animals's TD‐related symptoms. © 2019 by John Wiley & Sons, Inc.
Responses of a native plant species from invaded and uninvaded areas to allelopathic effects of an invader
Authors: Lyytinen Anne , Lindström Leena 
Published: May 2019

AbstractInvaders exert new selection pressures on the resident species, for example, through competition for resources or by using novel weapons. It has been shown that novel weapons aid invasion but it is unclear whether native species co‐occurring with invaders have adapted to tolerate these novel weapons. Those resident species which are able to adapt to new selective agents can co‐occur with an invader while others face a risk of local extinction. We ran a factorial common garden experiment to study whether a native plant species, Anthriscus sylvestris, has been able to evolve a greater tolerance to the allelochemicals exerted by the invader, Lupinus polyphyllus. Lupinus polyphyllus produces allelochemicals which potentially act as a novel, strong selective agent on A. sylvestris. We grew A. sylvestris seedlings collected from uninvaded (naïve) and invaded (experienced) sites growing alone and in competition with L. polyphyllus in pots filled with soil with and without activated carbon. Because activated carbon absorbs allelochemicals, its addition should improve especially naïve A. sylvestris performance in the presence of the invader. To distinguish the allelochemicals absorption and fertilizing effects of activated carbon, we grew plants also in a mixture of soil and fertilizer. A common garden experiment indicated that the performances of naïve and experienced A. sylvestris seedlings did not differ when grown with L. polyphyllus. The addition of activated carbon, which reduces interference by allelochemicals, did not induce differences in their performances although it had a positive effect on the aboveground biomass of A. sylvestris. Together, these results suggest that naïve and experienced A. sylvestris plants tolerated equally the invader L. polyphyllus and thus the tolerance has not occurred over the course of invasion.
Phytoplankton functional composition shows higher seasonal variability in a large shallow lake after a eutrophic past
Authors: Pálffy Károly , Vörös Lajos 
Published: May 2019

AbstractEutrophication is a well‐known problem of global proportions with some easily recognizable and potentially harmful effects on aquatic habitats, but our knowledge on the underlying associated changes in ecosystem functioning is rather limited. Relevant studies suggest that seasonal variability in the functional composition of phytoplankton shows an increase as eutrophication progresses. The aim of the present study was to test this hypothesis through the assessment of long‐term changes in the functional diversity and composition of phytoplankton in a large shallow lake situated in Central Europe with a history of dramatic changes in trophic state. Contrary to our expectations, results have shown that the maximum range of compositional variability had a significant negative correlation with the summer biomass maxima. On the other hand, average seasonal variability measured as annual beta diversity exhibited an increasing trend throughout the years from the period of early eutrophication to the recent period of reoligotrophication, seemingly following a decline in functional richness and a long‐term rise in annual mean water temperature. The enhanced variability in phytoplankton succession implies that all the ecosystem processes connected to the phytoplankton follow more complex seasonal dynamics. Besides changing community structure, trophic state also seems to be an important factor in setting the limits to compositional changes during the annual cycle, whereas long‐term warming is likely to enhance instability in the phytoplankton. The trajectories of these two factors and the changes in seasonal succession indicate a lake in transition, urging more in‐depth research efforts to understand the impact of climate change on this specific ecosystem, and raise the question of whether the observed changes can also occur in other similar aquatic systems.
Savanna canopy trees under fire: long‐term persistence and transient dynamics from a stage‐based matrix population model
Authors: Werner Patricia A. , Peacock Stephanie J. 
Published: May 2019

AbstractFire is a major disturbance driving the dynamics of the world's savannas. Almost all fires are set by humans who are increasingly altering fire timing and frequency on every continent. The world's largest protected areas of savannas are found in monsoonal northern Australia. These include relatively intact, tall, open forests where traditional indigenous fire regimes have been largely replaced in the past half century by contemporary patterns with trees experiencing fire as often as three out of five years. Eucalypt canopy trees form the basic structure of these savannas and changes to the canopy due to fire regimes cascade to affect other plants and animals. In this study, we used data from nearly three decades of field studies on the effects of fire on individual trees to define eight life‐history stages and to calculate transition rates among stages. We developed a stage‐based matrix population model that explicitly considers how fire season and understory influence growth, survival, and recruitment for each life‐history stage. Long‐term population growth rates and transient population dynamics were calculated under five different fire regimes, each in two understory types, using both deterministic and stochastic simulations of seasonal timing of fires. We found that fire was necessary for long‐term persistence of eucalypt canopy tree populations but, under annual fires, most populations did not survive. Population persistence was highly dependent on fire regime (fire season and frequency) and understory type. A stochastic model tended to yield higher population growth rates than the deterministic model with regular, periodic fires, even under the same long‐term frequency of fires. Transient population dynamics over 100 yr also depended on fire regime and understory, with implications for savanna physiognomy and management. Model predictions were tested in an independent data set from a 21‐yr longitudinal field study in Kakadu National Park. This study is a novel and integrative contribution to our understanding of fire in savanna biomes regarding the potential for long‐term persistence and transient dynamics of savanna canopy tree populations. The model is relatively simple, generalizable, and adaptable for further investigations of the population dynamics of savanna trees under fire.
Interspecific prey neighborhoods shape risk of predation in a savanna ecosystem
Authors: Ng'weno Caroline C. , Ford Adam T. , Kibungei Alfred K. , Goheen Jacob R. 
Published: May 2019

AbstractThe vulnerability of an individual to predation depends on the availability of other prey items in the surrounding environment. Interspecific prey aggregations or “neighborhoods” may therefore affect an individual's vulnerability to predation. We examined the influence of prey neighborhood structure (i.e., the densities and identities of prey neighborhoods) on spatial variation in predation in a multi‐prey system with a primary apex predator. We combinedGPSlocations of lions (Panthera leo), kill‐site surveys, and spatially explicit density estimates of five species of ungulates for which a significant level of predation was attributable to lions. In addition to the dual influence of predator activity and vegetation, predation risk was attributable to the structure of prey neighborhoods for at least two of the five species of prey. Along with traditionally recognized components of predation (the rate of predator–prey encounters and prey catchability), we encourage ecologists to consider how prey neighborhood structure influences spatial variation in predation risk.
Chemical synthesis of materials based on calcium zirconate for solid oxide fuel cells (SOFC)
Authors: Vieira Bruno M. , Nadaleti Willian C. , Almeida Suelen R. , Eliker Carolina , da Silva Cava Sergio , Raubach Cristiane W. , de Sousa Vania C. 
Published: May 2019

AbstractFuel cells allow the production of energy from a clean electrochemical reaction. Among various types, the solid oxide fuel cell (SOFC) operates at high temperatures, allowing the conversion of hydrogen fuel into electricity, where water is generated as a by‐product. Strontium‐doped lanthanum manganite (La1‐xSrxMnO3, LSM) is commonly used as a cathodic material in traditional high‐temperature solid oxide fuel cells. Nowadays, the operating temperature of SOFCs should be reduced to 600–800°C due to improved fine electrolyte production techniques and the use of some intermediate temperature electrolytes. The LSM is not a suitable cathode for SOFCs operating in this temperature range, since it does not have a high enough conductivity and its electrochemical activity is very low as well. In this article, the performance improvement of LSM is described by mixing with calcium zirconate. The composite ceramic materials CaZrO3−La0.6Sr0.4MnO3, CaZrO3−NiO, and CaZrO3 were synthesized by combustion method, for application as a SOFC single cell. The results prove that the synthesized materials have potential to be used in a SOFC cell. At 800°C, was confirmed the CaZrO3 formation. Through Electrochemical impedance spectroscopy, the analysis presented low activation energy and the materials have been demonstrated to be compatible, an important fact to construct a suitable SOFC cell. The obtained activation energy was 0.90, 0.85, and 0.51 eV for the electrolyte, the anode and the cathode, respectively.
The utility of an automated and ambulatory device for detecting and differentiating epileptic and psychogenic non‐epileptic seizures
Authors: Naganur Vaidehi D. , Kusmakar Shitanshu , Chen Zhibin , Palaniswami Marimuthu S. , Kwan Patrick , O'Brien Terence J. 
Published: May 2019

AbstractObjectiveAccurate differentiation between epileptic seizures (ES) and psychogenic non‐epileptic seizures (PNES) can be challenging based on history alone. Inpatient video EEG monitoring (VEM) is often needed for a definitive diagnosis. However, VEM is highly resource intensive, is of limited availability, and cannot be undertaken over long periods. Previous research has shown that time‐frequency analysis of accelerometer data could be utilized to differentiate between ES and PNES. Using a seizure detection and classification algorithm, we sought to examine the diagnostic utility of an automated analysis with an ambulatory accelerometer.MethodsA wrist‐worn device was used to collect accelerometer data from patients during VEM admission, for diagnostic evaluation of convulsive seizures. An automated process, that involved the use of K‐means clustering and support vector machines, was used to detect and classify each seizure as ES or PNES. The results were compared with VEM diagnoses determined by epileptologists blinded to the accelerometer data.ResultsTwenty‐four convulsive seizures, consisting of at least 20 seconds of sustained continuous activity, recorded from 11 patients during inpatient VEM (13 PNES from five patients and 11 ES from six patients) were included for analysis. The automated system detected all convulsive seizures (ES, PNES) from >661 hours of recording with 67 false alarms (2.4 per 24 hours). The sensitivity and specificity for classifying ES from PNES were 72.7% and 100%, respectively. The positive and negative predictive values for classifying PNES were 81.3% and 100%, respectively. There was no significant difference between the classification results obtained from the automation process and the VEM diagnoses.SignificanceThis automated system can potentially provide a wearable out‐of‐hospital seizure diagnostic monitoring system.
A semantic data lake framework for autonomous fault management in SDN environments
Authors: Benayas Fernando , Carrera Álvaro , García‐Amado Manuel , Iglesias Carlos A. 
Published: May 2019

AbstractFault Management is a vital issue for any network operator since the beginning of the telecommunications era. As networks have become more and more complex, their management systems are crucial for any operator company. In this ecosystem, the Software‐Defined Networking (SDN) approach has appeared as a possible solution for different networking issues. The flexibility provided by SDN to the network management enables a great dynamism in the configuration of network devices. However, this feature introduces the cost of a potential increase in failures because every modification introduced on the control plane is a new possibility for failures to appear and cause a decrement of the quality for offered services. Because of the growing pace of the networks, the classical approach is not feasible to cope that dynamism. Increasing the number of human operators in charge of the fault management process would increase the operation cost dramatically. Thus, this paper presents an approach to apply machine learning over a big data framework for an autonomous fault management process in SDN networks. In this paper, we present a Semantic Data Lake framework for a self‐diagnosis service, which is deployed on top of an SDN management platform. Moreover, we have developed a prototype of the proposed service with different diagnosis models for SDN networks. Models and algorithms have been evaluated showing good results.
Resource allocation in PD‐NOMA–based mobile edge computing system: Multiuser and multitask priority
Authors: Paymard Pouria , Mokari Nader 
Published: May 2019

AbstractMobile edge computing (MEC) is a new network architecture concept that enables cloud computing capabilities at the edge of the cellular network, and hence, MEC has the ability to process the computation tasks in close proximity to the network edge. In this paper, we consider a multiuser MEC system with multiple computation tasks such that each computation task is independent with different priorities. For this purpose, we devise a novel multiuser, multitask, and nonpreemptive priority M/G/1 queuing model in the MEC server environment. In doing so, we propose a priority‐based task scheduling policy that aims to maximize the profit of mobile network operator by jointly optimizing service rate, transmit power, and subcarrier allocation with satisfying power and delay constraints. This is necessary to handle the physical channel opportunities to obtain higher spectral efficiency in the proposed task offloading scheme. In this line, we also consider power‐domain nonorthogonal multiple access (PD‐NOMA) technique. Numerical results show that, by using the Priority queuing in PD‐NOMA‐SCA and Priority queuing in PD‐NOMA‐matching schemes, the performance can be improved considerably compared to No‐priority queuing in OMA‐SCA and No‐priority queuing in OMA‐matching, eg, the Priority queuing in PD‐NOMA‐SCA scheme improves nearly 54% compared to the No‐priority queuing in OMA‐SCA scheme. It is noteworthy that the performance gap between exhaustive search and the Priority queuing in PD‐NOMA‐SCA scheme is nearly 7%.
Lowering greenhouse gas (GHG) emissions: techno‐economic analysis of biomass conversion to biofuels and value‐added chemicals
Authors: Sharma Anita , Jakhete Akshay , Sharma Abhishek , Joshi Jyeshtharaj B. , Pareek Vishnu 
Published: May 2019

AbstractIt is important for researchers to look at alternative fuels to reduce dependence on fossil fuels as a primary source of energy, to protect the environment, and to reduce greenhouse‐gas emissions. An alternative fuel has to be environment friendly and economically viable, both in terms of production and suitability for the modern world. Fuel derived from biomass has long been viewed as a potential replacement. First‐generation biomass‐derived fuels such as bioethanol and biodiesel have already been competing with conventional fuels, assisted by legislation. This review paper assesses the feasibility of adapting and incorporating second‐generation advanced biofuel production technology for the thermochemical conversion of biomass to produce alternative fuels. The conversion technologies considered here are pyrolysis and gasification, and their potential has been examined using techno‐economic assessment (TEA). A brief overview of different business models that can be incorporated during TEA has also been discussed. Techno‐economic assessment data help in determining costs of technologies if they are employed on a commercial scale, especially in terms of per unit cost of product. The review has compiled the technical and economic data available for assessing the types and combination of processes that can assist competitiveness in the existing market. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd.
A review of geochemical–mechanical impacts in geological carbon storage reservoirs
Authors: Akono Ange‐Therese , Druhan Jennifer L. , Dávila Gabriela , Tsotsis Theodore , Jessen Kristian , Fuchs Samantha , Crandall Dustin , Shi Zhuofan , Dalton Laura , Tkach Mary K. , Goodman Angela L. , Frailey Scott , Werth Charles J. 
Published: May 2019

AbstractGeological carbon storage (GCS) refers to the technology of capturing man‐made carbon dioxide (CO2) emissions, typically from stationary power sources, and storing such emissions in deep underground reservoirs. GCS is an approach being explored globally as a defense mechanism against climate change projections, although it is not without its critics. An important focus has been recently placed on understanding the coupling between rock–fluid geochemical alterations and mechanical changes for CO2 storage schemes in saline aquifers. This article presents a review of the current state of knowledge regarding CO2‐induced geochemical reactions in subsurface reservoirs, and their potential impact on mechanical properties and microseismic events at CO2 storage sites. This review focuses, in particular, on the current state of the art in fluid–rock interactions within the GCS context. Key issues to be addressed include geochemical reactions and the alteration of transport and mechanical properties. Specific review topics include the swelling of clays, the prediction of dissolution and precipitation reaction rates, CO2‐induced changes in porosity and permeability, constitutive models of chemo–mechanical interactions in rock, and correlations between geochemical reactions and induced seismicity. The open questions in the field are emphasized, and new research needs are highlighted. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd.