bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evidence for a sensitive period of plasticity in brown adipose tissue during early childhood among indigenousSiberians
Authors: Levy Stephanie B. , Klimova Tatiana M. , Zakharova Raisa N. , Fedorov Afanasiy I. , Fedorova Valentina I. , Baltakhinova Marina E. , Leonard William R. 
Published: April 2021

AbstractObjectivesEvolutionary theorists have debated the adaptive significance of developmental plasticity in organisms with long lifespans such as humans. This debate in part stems from uncertainty regarding the timing of sensitive periods. Does sensitivity to environmental signals fluctuate across development or does it steadily decline? We investigated developmental plasticity in brown adipose tissue (BAT) among indigenous Siberians in order to explore the timing of phenotypic sensitivity to cold stress.MethodsBAT thermogenesis was quantified using infrared thermal imaging in 78 adults (25 men; 33 women). Cold exposure during gestation, infancy, early childhood, middle childhood, and adolescence was quantified using: (1) the average ambient temperature across each period; (2) the number of times daily temperature dropped below −40°F during each period. We also assessed past cold exposure with a retrospective survey of participation in outdoor activities.ResultsAdult BAT thermogenesis was significantly associated with the average temperature (p = 0.021), the number of times it was below −40°F (p = 0.026), and participation in winter outdoor activities (p = 0.037) during early childhood.ConclusionsOur results suggest that early childhood represents an important stage for developmental plasticity, and that culture may play a critical role in shaping the timing of environmental signals. The findings highlight a new pathway through which the local consequences of global climate change may influence human biology, and they suggest that ambient temperature may represent an understudied component of the developmental origins of health and disease.
Rheological, thermal and morphological properties of polyethylene terephthalate/polyamide 6/rice husk ash composites
Authors: de Matos Costa Anna Raffaela , Lima Juliana Cysneiros , dos Santos Raquel , Barreto Lhaira Souza , Henrique Mariana Alves , de Carvalho Laura Hecker , de Almeida Yêda Medeiros Bastos 
Published: April 2021

AbstractThis work deals with the rheological, morphological, and thermal properties of composites having poly(ethylene terephthalate) (PET), polyamide‐6 (PA6), and their blends as matrices, and rice husk ash (RHA) as a filler. The study determines the effect of composition on the change in viscosity and rate of degradation during processing in a torque rheometer. Our data indicates that thermal stability and degradation during processing depend on matrix composition and filler concentration. SEM micrographs show both partial adhesion of the filler to the matrices and filler pullout. Optical microscopy shows particle agglomeration and that agglomerate size increased with filler content. FTIR investigates the shifting of absorption bands of PET/PA6 composite after the addition of RHA and attributes the selective dispersion of RHA to the formation of hydrogen bonds. Our data supports the idea that filler employed here is an option to develop polymer composites with improved properties.
Enhanced Peroxidase‐mimicking Activity of Plasmonic Gold‐modified Mn3O4 Nanocomposites through Photoexcited Hot Electron Transfer
Authors: Han Xiaoxuan , Liu Rong , Zhang Hui , Zhou Quan , Feng Wei , Hu Ke 
Published: April 2021

AbstractEnzyme‐mimicking artificial nanomaterials often termed nanozymes have broad applications in many fields, including biosensing, pollutant degradation and cancer diagnosis. Herein, we introduce a plasmonic gold nanoparticle‐modified Mn3O4 nanozyme (Mn3O4‐Au). Visible or near infrared light excitation into the plasmonic absorption band of the surface‐bound gold nanoparticles enhances the catalytic oxidation of tetramethylbenzidine (TMB). The mechanism of light‐enhanced peroxidase activity is proposed based on the Mn3O4 conduction band mediated hot electron transfer from photoexcited gold nanoparticles to H2O2 which undergoes further oxygen‐oxygen bond cleavage to yield hydroxyl radical. The surface decoration of plasmonic gold nanoparticles endows Mn3O4‐Au to be a light‐regulated nanozyme.
Influence of Intermolecular Hydrogen Bonding Interactions on the Electrocatalytic Reduction of CO2 to CO by 6,6′‐Amine Substituted Rhenium Bipyridine Complexes
Authors: Hellman Ashley N. , Haiges Ralf , Marinescu Smaranda C. 
Published: April 2021

AbstractThe introduction of biologically inspired motifs into electrocatalysts is an attractive strategy for efficiently transforming harmful fossil fuel combustion products such as carbon dioxide into useful chemical fuels. Herein, we present a series of Re(bpy)(CO)3Cl electrocatalysts with pendant primary, secondary, and tertiary amines with the aim of determining the effect of available pendant protons on the reduction of CO2 to CO. Cyclic voltammetry studies indicate that the availability of pendant protons leads to intermolecular hydrogen bonding interactions, altering the electrochemical behavior of the complexes. Further, controlled potential electrolysis studies show a clear trend in the catalytic activity of these complexes based on the availability of pendant protons. For the NMe2‐substituted complex with no pendant protons, the Faradaic efficiency (FE) remains quite stable with changing potential (41–65 % FECO), but for the NH2‐substituted complex with maximum available pendant protons, the FECO increases with more negative potentials, peaking at 83 % FECO. Together with the formation of H2 by the NH2‐substituted Re(bpy)(CO)3Cl complex, this suggests a change in electrocatalytic behavior due to the intermolecular hydrogen bonding interactions that occur with additional pendant protons.
Electrochemical Reduction of 4‐Nitrobenzyl Phenyl Thioether for Activation and Capture of CO2
Authors: Mena Silvia , Louault Cyril , Mesa Verónica , Gallardo Iluminada , Guirado Gonzalo 
Published: April 2021

AbstractIn this work, a new simple molecule, 4‐nitrobenzyl phenyl thioether (1), is prepared and used for controlling and tuning CO2 reactivity in function of the electrode potential. The first part of the study is devoted to determining the electrochemical reduction mechanism of 1 in N,N‐dimethylformamide under nitrogen. The compound shows a first reversible one‐electron transfer process, whereas the reaction cleavage of the C−S bond takes place after a second electron transfer process through a stepwise mechanism (thermodynamic and kinetic parameters are conveniently determined). In the second part of the study, the inert atmosphere was replaced by a CO2 atmosphere. At low potential values, compound 1 acts as a redox mediator that allows the reduction of CO2 at ca. −1.2 V vs. SCE. The electrochemical generation of 12− at more negative potential values leads to a C−S bond cleavage reaction that yields the corresponding nitrobenzyl and thiosulfate anions, which react with CO2. The nitro aromatic anion derivative makes it possible to obtain electrocarboxylated derivatives, whereas the thiophenolate anion captures CO2 reversibly. Hence, this research opens a new way of tuning and controlling the reaction processes associated with CO2 from homogenous catalysis at low negative potentials, to electrocarboxylation processes passing to CO2 reversible electrochemically triggered adsorption processes.
How professional engineers can contribute to attraction and retention of minority groups into the engineering profession through equity, diversity, inclusion, and decolonization efforts
Authors: Vandenberghe Jessica 
Published: April 2021

AbstractDiversity leads to innovation, better project delivery efficiency, and improved quality management in terms of technical engineering work. Current statistics show that there is still underrepresentation of minority groups such as females in the Science, Technology, Engineering, and Mathematics (STEM) fields, implying that diversity amongst engineering companies and within the profession is still low. In order to support diversity within the engineering workforce, inclusivity and equitable practises are key to encourage attraction and retention, along with understanding decolonization. Professional engineers have an ethical obligation to contribute both through personal and professional development of skills that will build inclusive organizational cultures and to influence equitable policies and practises.
Autoantibodies against complement component C1q in systemic lupus erythematosus
Authors: Trendelenburg Marten 
Published: April 2021

AbstractSystemic lupus erythematosus (SLE) is the archetype of a systemic autoimmune disease, but the multifaceted pathogenic mechanisms leading to inflammation and organ damage are not fully understood. Homozygous deficiency of complement C1q, the first component of the classical pathway of complement, is strongly associated with the development of SLE, thus pointing at a primarily protective role of C1q. However, while most SLE patients do not have hereditary C1q deficiency, there is indirect evidence for the importance of C1q in the inflammatory processes of the disease, including hypocomplementemia as a result of activation via the classical pathway, deposition of C1q in affected tissues and the occurrence of autoantibodies against C1q (anti‐C1q). The growing body of knowledge on anti‐C1q led to the establishment of a biomarker that is used in the routine clinical care of SLE patients. Exploring the binding characteristics of anti‐C1q allows to understand the mechanisms, that lead to the expression of relevant autoantigenic structures and the role of genetic as well as environmental factors. Lastly, the analysis of the pathophysiological consequences of anti‐C1q is of importance because C1q, the target of anti‐C1q, is a highly functional molecule whose downstream effects are altered by the binding of the autoantibody. This review summarises current study data on anti‐C1q and their implications for the understanding of SLE.
Exposure to air pollution and COVID-19 severity: A review of current insights, management, and challenges
Authors: Ali Nurshad , Fariha Khandaker A. , Islam Farjana , Mishu Moshiul A. , Mohanto Nayan C. , Hosen Mohammad J. , Hossain Khaled 
Published: April 2021

Abstract
Several epidemiological studies have suggested a link between air pollution and respiratory tract infections. The outbreak of coronavirus disease 2019 (COVID-19) poses a great threat to public health worldwide. However, some parts of the globe have been worse affected in terms of prevalence and deaths than others. The causes and conditions of such variations have yet to be explored. Although some studies indicated a possible correlation between air pollution and COVID-19 severity, there is yet insufficient data for a meaningful answer. This review summarizes the impact of air pollution on COVID-19 infections and severity and discusses the possible management strategies and challenges involved. The available literature investigating the correlation between air pollution and COVID-19 infections and mortality are included in the review. The studies reviewed here suggest that exposure to air pollution, particularly to PM2.5 and NO2, is positively correlated with COVID-19 infections and mortality. Some data indicate that air pollution can play an important role in the airborne transmission of SARS-CoV-2. A high percentage of COVID-19 incidences has been reported in the most polluted areas, where patients needed hospital admission. The available data also show that both short-term and long-term air pollution may enhance COVID-19 severity. However, most of the studies that showed a link between air pollution and COVID-19 infections and mortality did not consider potential confounders during the correlation analysis. Therefore, more specific studies need to be performed focusing on some additional confounders such as individual age, population density, and pre-existing comorbidities to determine the impact of air pollution on COVID-19 infections and deaths. Integr Environ Assess Manag 2021;17:1114–1122. © 2021 SETAC
KEY POINTS
COVID-19 infections and mortality are more frequent in highly air polluted areas. PM2.5 and NO2 are more closely correlated with COVID-19 infections and mortality than other air pollutants. Air pollution can play an important role in the airborne transmission of SARS-CoV-2. More specific studies are needed focusing on additional confounders in exploring the interactions between air pollution and SARS-CoV-2 and their adverse effects on human health.
A framework for evaluating island restoration performance: A case study from the Chesapeake Bay
Authors: Davis Jenny , Whitfield Paula , Szimanski Danielle , Golden Becky R. , Whitbeck Matt , Gailani Joe , Herman Brook , Tritinger Amanda , Dillon Sally C. , King Jeffrey 
Published: April 2021

Abstract
The use of natural habitats for coastal protection (also known as Nature-Based Solutions or NBS) in place of engineered structures like breakwaters and seawalls can yield a wide range of ecological and economic benefits. Despite these advantages, NBS are not commonly implemented for shoreline protection due to uncertainty over the amount of protection afforded by each unique feature and how protective capacity and ecological benefits are likely to change over time as NBS mature and adapt to changing environmental drivers. Here, we highlight the recent restoration of Swan Island in the Chesapeake Bay, Maryland, USA, and the collaborative approach used to evaluate post-construction performance, as a framework for quantitative evaluation of NBS projects. At Swan Island, 60 000 cubic yards of dredged sediment were used to elevate and restore the island's footprint with an emphasis on increasing its protective and ecological benefits and long-term resilience to sea-level rise. Five entities have leveraged resources to quantify the benefits and efficacy of island restoration by conducting pre- and post-restoration monitoring, which supports the development of an integrated, simulation model that includes three “measured” system parameters: wave height, vegetative biomass, and island profile (i.e., elevations). The model will be used to predict island performance under a range of different system scenarios and used to inform adaptive management options. Results will demonstrate the efficacy of leveraging natural and engineered processes to restore island systems while providing a framework for quantifying NBS. Integr Environ Assess Manag 2022;18:42–48. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by US Government employees and their work is in the public domain in the USA.
KEY POINTS
Evaluations of NBS performance at the scale of the individual project are needed to address uncertainties about when and where natural solutions can afford adequate levels of coastal protection. A consistent approach to NBS project evaluation will help to foster confidence in the use of natural approaches.
A machine learning classification approach based glioma brain tumor detection
Authors: Mathiyalagan Gomathi , Devaraj Dhanasekaran 
Published: April 2021

AbstractThis article develops a computer aided fully automated method for detecting and classifying the glioma brain magnetic resonance imaging (MRI) using machine learning classification approach. The noise contents in source brain MRI image are detected and removed using ridgelet filter and then the edges in noise removed image are detected using fuzzy logic and then contrast adaptive local histogram equalization is applied on the edge detected brain image for enhancing the edge pixels. The Gabor transformation is applied on the enhanced brain image and the features are computed from this transformed image. The computed features are optimized using feature optimization technique genetic algorithm (GA) and the optimized features are classified using adaptive neurofuzzy inference system (ANFIS) classification method, which classifies the source brain MRI image into either glioma or non‐glioma brain image. Finally, fuzzy C means algorithm is applied on the glioma brain image to segment the tumor regions. The segmented tumor regions in glioma brain image is compared with manually tumor segmented brain image in order to evaluate the performance efficiency of the proposed system and the simulation results shows that the proposed works in this article achieves optimum performance with state of the art methods.
Discovery of a complex sclerotized sperm pump in Monotomidae (Coleoptera): Functional morphology and phylogenetic value
Authors: Jałoszyński Paweł , Ruta Rafał 
Published: April 2021

AbstractIn insects, a long ductus ejaculatorius surrounded by a muscular sheath transfers seminal fluids and sperms from the testes into the male copulatory organ, the aedeagus. In several unrelated coleopteran families, a section of the ductus has evolved to form a specialized pumping organ. The most complex forms of this “sperm pump” was known in Lepiceridae and two subfamilies of evolutionary distant Staphylinidae; in these groups two sclerotized funnels situated on ends of the sperm pump provide attachment sites for a remarkably robust compressor muscle. A sperm pump with two funnels and a previously unknown spiral ridge, representing the most complex sperm pumping apparatus among Coleoptera, is for the first time reported to occur in the superfamily Cucujoidea, family Monotomidae. The compressor muscle is particularly large, and the pump shows features more advanced than those in any other beetle. Not the entire section between funnels is compressed, but only a pair of specialized thin‐walled, unsclerotized and resilin‐rich regions within the pump. The spiral ridge stores mechanical energy to decompress the pump when the muscle relaxes, and provides a sclerotized scaffold for the entire structure. The pumps do not occur in all Monotomidae, but seem to be restricted to the subfamily Monotominae. Two distinct forms were found, each in a different tribe (with one notable exception;Mimemodeshaving a sperm pump typical of Monotomini, not Europini). Moreover, the shapes of the pumps were found to be species‐specific. The phylogenetic value of this structure is discussed, as sperm pumps may help defining monophyletic lineages within this poorly studied family. An evolutionary scenario for a development of sperm pumps in Coleoptera from an undifferentiated ductus ejaculatorius to the most complex “monotomid form” is proposed, assuming several distinct stages exemplified by structures found in other beetle families.
Station‐based non‐linear regression downscaling approach: A new monthly precipitation downscaling technique
Authors: Shen Zexi , Zhang Qiang , Singh Vijay P. , Sun Peng , He Chunyang , Cheng Changxiu 
Published: April 2021

ABSTRACTStatistical downscaling is an effective way to downscale General Circulation Model (GCM) outputs to a finer temporal and spatial scale. Here, we proposed and trained a new station‐based non‐linear regression downscaling (SNRD) approach, and quantitatively demonstrated its better performance than linear regression model. In addition, we also compared the SNRD method with the Bias Correction Spatial Disaggregation (BCSD) method, which has been widely applied on downscaling precipitation. Results indicated that RMSEs and residuals of the BCSD method are 4.6–31 times as ones of SNRD in each region of China during validation period (2004–2015). Besides, with historical in‐situ observed monthly mean precipitation as the benchmark, SNRD downscaled model modified the over‐estimation (1.25–2 times as observed precipitation) flaw of BCSD model in rainy season (June–August) of China, which could provide assistance on the further researches on drought events in rainy season in future. Further, we also surprisingly found that the 2,500 m was the threshold height for statistical downscaling models. Both BCSD and SNRD downscaled precipitation displayed more steadily and accurately above 2,500 m, since there are less intense human activities in China. Thus, we recommend further studies should fully consider the height element in downscaling models to improve the accuracies.
A real‐time interactive rendering method for 360° tabletop integral imaging 3D display
Authors: Ma Xiao‐Ming , Xing Yan , Zheng Jia‐Chen , Li Xiao‐Wei , Wang Qiong‐Hua 
Published: April 2021

AbstractIn this paper, a rendering method for interactive tabletop integral imaging 3D display is proposed to present interactive 3D graphics to users 360° around the display in real‐time. By transforming the viewpoint plane and the elemental image array (EIA) plane with a parallel backward ray‐tracing technique according to the recognized gestures, a high‐efficient rendering for interactive 3D contents can be achieved, thus, the 3D graphics can be manipulated to be displayed on the tabletop in real‐time. Compared with the previous methods that all viewpoint images should be generated first, the proposed method can generate the interactive EIAs that contain all viewpoint information directly, which makes the interactive rendering more efficient. A gesture‐based interactive tabletop integral imaging 3D display prototype is built using an 8‐K (7680 × 4320) pixel resolution LCD. Experimental results show that the proposed interactive rendering method can achieve a short response time of less than 40 ms and high recognition accuracy of over 95% for different spatial hand gestures.
A nonintrusive nonlinear model reduction method for structural dynamical problems based on machine learning
Authors: Kneifl Jonas , Grunert Dennis , Fehr Joerg 
Published: April 2021

AbstractModel order reduction (MOR) has become one of the most widely used tools to create efficient surrogate models for time‐critical applications. For nonlinear models, however, linear MOR approaches are only practicable to a limited extent. Nonlinear approaches, on the contrary, often require intrusive manipulations of the used simulation code. Hence, nonintrusive MOR approaches using classic model order reduction along with machine learning (ML) algorithms can provide remedy. Such approaches have drawn a lot of attention in the recent years. They rely on the idea to learn the dynamics not in a high dimensional but in a reduced space, that is, they predict the discrete sequence of reduced basis' coefficients. Open questions are the suitability of such methods in the field of structural dynamics and the best choice of the used ML algorithm. Both are addressed in this article in addition to the integration of the methodology into a modular and flexible framework that can effortless be adapted to various requirements. By applying the methodology to a dynamic mechanical system, accurate surrogate models are received, which can speed up the simulation time significantly, while still providing high‐quality state approximations.