bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation of Bioimpacts of Metallic and Metallic Oxide Nanostructured Materials: Size, Shape, Chemical Composition, and Surface Functionality: A Review
Authors: Fatehbasharzad Parisa , Fatehbasharzad Pegah , Sillanpää Mika , Shamsi Zahra 
Published: September 2021

AbstractNanotechnology is set to impact a wide range of various fields, including medicine, materials technology, environmental sciences, and engineering/manufacturing. Nanoparticles are categorized depending on their size, composition, shape, and surface functionality. Due to the excessive growth of nanostructured materials (NSMs) in production and industrial applications, human and environmental exposure to them and their possible toxicity issues are inevitable. The main objective of this review is to study NSMs, in particular metallic and metallic oxide nanoparticles, and properties that have a determinative role in their bioimpacts. Nevertheless, the main focus is to provide an overview of NSMs toxicology. Medical and environmental applications of the NSMs are discussed here. Also, key factors on the toxicity of the nanoparticles such as shape, size, chemical composition, and surface functionality are discussed. Finally, toxicity of the nanoparticles is going to be highlighted, and relevant studies are critically compared. This review gives a broad scientific view for improving the functional efficiency of nanomaterials while mitigating their possible adverse and unintended effects on biological systems.
Outcomes of infants born during the first 9 years of CF newborn screening in the United States: A retrospective Cystic Fibrosis Foundation Patient Registry cohort study
Authors: Martiniano Stacey L. , Elbert Alexander A. , Farrell Philip M. , Ren Clement L. , Sontag Marci K. , Wu Runyu , McColley Susanna A. 
Published: September 2021

AbstractIntroductionNewborn screening (NBS) for cystic fibrosis (CF) was implemented in all US states and DC by 2010. This hypothesis‐generating study was designed to form the basis of additional analyses and to plan quality improvement initiatives. The aims were to describe the outcomes of infants with CF born during the first 9 years of universal NBS.MethodsWe included participants in the CF Foundation Patient Registry born 2010–2018 with age of recorded CF diagnosis 0–365 days old. We compared the age of center‐reported diagnosis, age at first CF event (defined as earliest sweat test, clinic visit, or hospitalization), demographics, and outcomes between three cohorts born between 2010–2012, 2013–2015, and 2016–2018.ResultsIn 6354 infants, the median age at first CF event decreased from the first to the third cohort. Weight‐for‐age (WFA) was < 10th percentile in about 40% of infants at the first CF Center visit. Median WFA z‐score at 1–2 years was more than 0 but height‐for‐age (HFA) z‐score was less than 0 through age 5–6 years. The second cohort had a higher HFA z‐score than the first cohort at age 5–6 years. Pseudomonas aeruginosa infection was less common in later cohorts. About 1/3 of infants were hospitalized in the first year of life with no changes over time.ConclusionOver 9 years of CF NBS, median age at first CF event decreased. CF NBS had positive health impacts, but early life nutritional deficits and a high rate of infant hospitalizations persist.
Susceptibility of Demotispa neivai (Coleoptera: Chrysomelidae) to Beauveria bassiana and Metarhizium anisopliae entomopathogenic fungal isolates
Authors: Martínez Luis Carlos , Plata‐Rueda Angelica , Ramírez Augusto , Serrão José Eduardo 
Published: August 2021

AbstractBACKGROUNDThe potential of Beauveria bassiana and Metarhizium anisopliae isolates obtained from naturally infected oil palm pests was evaluated to control Demotispa neivai as an alternative for organophosphate insecticide use in oil palm crops in Latin America. Two B. bassiana (Bb‐0018 and Bb‐0025) and two M. anisopliae (Ma‐0002 and Ma‐0003) isolates were tested against D. neivai adults for hydrophobicity, virulence, survival, adhesion to host cuticle, and mortality in semi‐field conditions.RESULTSConcentration–mortality bioassays demonstrate that isolates had lethal effect on D. neivai adults with Bb‐0025 [median lethal concentration (LC50) = 3.45 × 107 conidia mL−1] and Bb‐0018 (LC50 = 3.75 × 107 conidia mL−1) being the most effective followed by Ma‐0003 (LC50 = 3.38 × 108 conidia mL−1) and Ma‐0002 (5.33 × 108 conidia mL−1). Adult survival was 99% without exposure to fungal isolates, decreasing to 21.65% in insects exposed to Ma‐0002, 19.41% with Ma‐0003, 20.13% with Bb‐0018, and 0.17% with Bb‐0025. Mortality of D. neivai adults caused by the entomopathogenic fungal isolates was similar in both laboratory and semi‐field conditions. Also, vegetative growth of the entomopathogenic fungal isolates was found in infected D. neivai adults in the field.CONCLUSIONOur data suggest that the tested entomopathogenic fungal isolates are effective against D. neivai with potential to be used as biological control agents contributing to the decrease of the use of chemical insecticides to control this oil palm pest. © 2021 Society of Chemical Industry.
Attitudes towards rural migrants and their influence on return migration in China
Authors: Zhou Jing , Tang Shuangshuang 
Published: August 2021

AbstractCompared with the enormous attention paid to the formation of attitudes towards migrants, studies on the social consequences of such attitudes have been insufficient, with the link between attitudes towards migrants and return migration remaining an understudied field both in global and Chinese contexts. Contextual hostility creates social and symbolic barriers in the integration process of migrants and decreases their life satisfaction levels and thus significantly influences many types of migration trajectories. Based on the only available national data for China, this study applies multilevel logistic regression models to examine the relationship betweenlocal‐hukouresidents' attitudes towards migrants and the intention for return migration among rural‐to‐urban migrants while accounting for socio‐economic heterogeneity in migrants. Results reveal that, for all types oflocal‐hukouresidents, their acceptance of migrants as either friends, neighbours, or family members positively relates to the intention for return migration among rural‐to‐urban migrants; by contrast, it is only hostility from native‐bornlocal‐hukouresidents that has a significant and negative effect on rural‐to‐urban migrants, encouraging them to plan to return to their places of origin. Moreover, migrants with different amounts of human capital have varied perceptions of attitudes held bylocal‐hukouresidents, with the younger generation of migrants, highly educated migrants, and business migrants being more sensitive to contextual hostility. Thus, they exhibit a greater tendency towards return migration. This study broadens the understanding of return migration from the perspectives of life satisfaction and psychological integration and suggests creating a more open and friendlier social environment in cities.
Latent space data assimilation by using deep learning
Authors: Peyron Mathis , Fillion Anthony , Gürol Selime , Marchais Victor , Gratton Serge , Boudier Pierre , Goret Gael 
Published: September 2021

AbstractPerforming data assimilation (DA) at low cost is of prime concern in Earth system modeling, particularly in the era of Big Data, where huge quantities of observations are available. Capitalizing on the ability of neural network techniques to approximate the solution of partial differential equations (PDEs), we incorporate deep learning (DL) methods into a DA framework. More precisely, we exploit the latent structure provided by autoencoders (AEs) to design an ensemble transform Kalman filter with model error (ETKF‐Q) in the latent space. Model dynamics are also propagated within the latent space via a surrogate neural network. This novel ETKF‐Q‐Latent (ETKF‐Q‐L) algorithm is tested on a tailored instructional version of Lorenz 96 equations, named the augmented Lorenz 96 system, which possesses a latent structure that accurately represents the observed dynamics. Numerical experiments based on this particular system evidence that the ETKF‐Q‐L approach both reduces the computational cost and provides better accuracy than state‐of‐the‐art algorithms such as the ETKF‐Q.
Density Functional Theory Study of Ultrashort Metal−Metal Distances in Diberyllium Complexes Bearing Carbene Ligands
Authors: Sun Lili 
Published: September 2021

AbstractDiberyllium complexes with ultrashort metal−metal distances (USMMDs, defined asdM−M<1.900 Å) are fascinating for the nature of the valence electronic structure of Be atoms. In this paper a family of diberyllium complexes [L−BeH3Be−L]+(1–7), in which L was anN‐heterocyclic carbene (NHC) or a mesoionic carbene (MIC), were studied by Density Functional Theory (DFT) at the B3LYP/cc‐pVTZ level. It was found that complexes1–7possessed ultrashort Be−Be distances of 1.754 Å–1.779 Å and strong covalent bonds between a Be atom and its adjacent carbene center (Ccarb) at once. Electronic structures and chemical bonding analyses ascribed USMMDs between the Be atoms to the Be−H−Be three‐center two‐electron (3c‐2e) bonds. The strong Be−Ccarbbonds were determined by combining effects of covalent interaction and electrostatic interaction between the Be and the Ccarbatoms. These complexes exhibited a great stability with large highest occupied molecular orbital‐lowest unoccupied molecular orbital (HOMO‐LUMO) gaps, high vertical detachment energies (VDEs) and low vertical electron affinities (VEAs) and are potential targets in future experiments.
Practical Synthesis for N‐doped Carbon Microsphere Coated with Zn0.76Co0.24S Nanoparticles towards High‐performance Supercapacitors
Authors: Zhang Wenjun , Zhou Ting , Hao Yonghao , Wang Zhongbing , Chen Chunnian 
Published: September 2021

AbstractTo meet the market demand for supercapacitors with large capacitance and high stability, we successfully prepared a new type of composit material of N−C@Zn0.76Co0.24S with a hierarchical structure utilizing solvothermal and calcination. The nanostructures and electrochemical properties of the samples were tested and analyzed. By adjusting the mass ratio of the N‐doped carbon microsphere during the process of synthesizing composite materials, a series of comparative materials were obtained. The result of research shows that, when the mass ratio of the N‐doped carbon microsphere in the composite was 55 %, the nanocomposite demonstrated excellent specific capacitance (2033.7 F g−1 at a current density of 1 A g−1) and strong cycle performance (retain 88.4 % after 5000 charge‐discharge cycles), far superior to that of the single metal sulfide coating on N‐doped carbon microsphere. When assembled into N−C@ZCS//AC asymmetric supercapacitor (ASC), the ASC exhibits a large energy density of 79.6 Wh kg−1 while the power density is 799.7 W kg−1, proving the composite materials have positive significance in the application of supercapacitors.
Oxygen Enriched Oxamides and N‐Dinitrated Oxamides: Trinitroethyl Esters, Nitrocarbamates and Nitrates
Authors: Klapötke Thomas M. , Krumm Burkhard , Reith Thomas , Riedelsheimer Christian 
Published: September 2021

AbstractStarting from the readily available starting materials diethyl oxalate, glycine and β‐alanine, some new N‐nitrated oxamides were synthesized. Oxamides formed by condensation reactions were subsequently nitrated to form the corresponding dinitroxamides. These were further converted to the corresponding acid chlorides with the utilization of thionyl chloride. The final reaction of the β‐alanine based dinitroxamide with trinitroethanol generated the energetic target ester in moderate yield and high purity. Additionally, starting from diethyl oxalate and ethanolamine gave access to a nitrocarbamate based on an oxamide. Furthermore, the previously reported compound bis(2‐nitratoethyl) oxamide was synthesized now in a more facile fashion and fully characterized, especially in case of the energetic properties, sensitivities and crystal structure. The compounds were fully analysed by NMR spectroscopy, vibrational analysis and elemental analysis. The heat of formation was calculated with the Gaussian program package and in combination with the experimental density the energetic properties were estimated utilizing the Explo5 computer code.
Explainable models to estimate the effective compressive strength of slab–column joints using genetic programming
Authors: Jeong Hoseong , Choi Seung‐Ho , Han Sun‐Jin , Kim Jae Hyun , Lee Sang‐Hoon , Kim Kang Su 
Published: September 2021

ABSTRACTIn this study, explainable models to predict the effective compressive strength of slab–column joints were proposed using genetic programming (GP). Effective compressive strength test results were collected from the literature, among which 81 were sandwich, corner, and edge columns, 44 were interior columns. With respect to the collected test results, random forest (RF), random forest–recursive feature elimination (RF‐RFE), K‐means clustering and linear regression analysis (KL) were applied to analyze the key features influencing the effective compressive strength. In addition, explainable models to predict the effective compressive strength were derived by using GP. The proposed models were verified by comparing with the existing equations, RF, and artificial neural network (ANN). Using the generative adversarial network (GAN), 20,000 fake data were additionally generated to strengthen the verification stage. The results showed that the proposed models exhibited the lowest root mean squared error (RMSE) among the existing equations, and RMSE of the proposed models was close to that of RF and ANN despite its conciseness.
Geothermal energy resources in Ethiopia: Status review and insights from hydrochemistry of surface and groundwaters
Authors: Burnside Neil , Montcoudiol Nelly , Becker Kerry , Lewi Elias 
Published: September 2021

AbstractEthiopia has an estimated >10,000 MW of geothermal energy potential, more than double its current power generating capacity (4,400 MW). Electricity access stands at 44% of the total population, with 31% in rural areas, so effective development of this low‐carbon resource could make a significant impact to equitable delivery of electricity. However, geothermal energy exploitation must be done responsibly to protect valuable water resources under stress from climate‐change driven drought conditions and competing uses across agricultural, domestic, and industrial sectors. Our review provides progress updates on geothermal developments—which soon aim to deliver more than 1,000 MW of electricity—and performs a high‐level assessment of hydrochemical data for ground and surface waters across Ethiopia. A water quality database was built using publicly available information and three quality control criteria: well‐defined sample location, cation‐anion balance (CAB) of ±10%, and clear fluid type definition. Ethiopia hosts two major geothermal water types, sodium‐alkalinity dominated in the Main Ethiopian Rift and sodium‐chloride dominated in the Afar Depression, separated by sodium‐mixed waters between Dofan‐Fantale and Meteka. H and O stable isotopes suggest a largely meteoric source for geothermal waters, with δ18O enrichment adding to evidence of a high enthalpy resource at Tendaho. Hydrochemical investigations provide critical information for successful delivery of sustainable geothermal energy developments. However, the current lack of data available for Ethiopia poses a significant challenge for completion of predevelopment baselines and ongoing environmental impact assessment. We encourage the release of unpublished findings from private companies and government agencies to build upon our database and demonstrate social and environmental responsibility in the development of Ethiopian geothermal resources.This article is categorized under:
Engineering Water > Methods
Floating wind turbine power performance incorporating equivalent turbulence intensity induced by floater oscillations
Authors: Wen Binrong , Li Zhanwei , Jiang Zhihao , Tian Xinliang , Dong Xingjian , Peng Zhike 
Published: September 2021

AbstractExtensive assessment about the efficiency and quality of the power production is important to the floating wind turbine (FWT) development. The power performance of a wind turbine depends on turbine dynamics, control strategy, and atmospheric conditions. As for FWTs, the additional floater oscillations should be particularly incorporated. In this paper, extensive simulations are conducted for a Spar‐type FWT using the FAST software. The relative wind velocity introduced by floater oscillations and the corresponding power capture mechanisms are analyzed in detail. A concept of equivalent turbulence intensity is proposed to generally describe the intensity of floater oscillation. It is observed to satisfyingly serve as an independent variable for FWT power production. The mapping relationship between the FWT power generation and the equivalent turbulence intensity is constructed. Results show that the FWT output power increases linearly with the equivalent turbulence intensity square in the below‐rated region, while it is well regulated around the rated power by the bladepitch controller in the above‐rated region. The normalized power fluctuation augments linearly with equivalent turbulence intensity over the whole operating wind speeds except the rated‐nearby region. The findings are potentially helpful for the power forecasting, controller development, economical evaluation, and wind farm optimizations.
Remazol Brilliant Blue R (RBBR) dye and phosphate adsorption by calcium alginate beads modified with polyethyleneimine
Authors: Isik Zelal , Saleh Mohammed , Bilici Zeynep , Dizge Nadir 
Published: August 2021

AbstractThis study concerns the preparation of novel adsorbent prepared from calcium alginate bead modified with polyethyleneimine (PEI‐CaAlg). The adsorption capacity of the PEI‐CaAlg was examined by Remazol Brilliant Blue R (RBBR) and phosphate adsorption. PEI‐CaAlg showed high removal efficiencies for RBBR (90.48%) and phosphate (88.10%). The removal of both RBBR and phosphate onto the PEI‐CaAlg followed the Freundlich isotherm and the second‐order model. The adsorption was studied in terms of thermodynamic and found to be feasible and spontaneous in nature. The reusability of the modified alginate beads was also examined up to five cycles. The removal efficiency was 90.48% at the first cycle and decreased to 75.15% at the end of the fourth cycle. The adsorption of color and phosphate from real textile wastewater was also instigated. The removal efficiencies for color and phosphate ions reached 80.24% and 90.00%, respectively. Therefore, the prepared PEI‐CaAlg can be considered as a novel, eco‐friendly, and cost‐effective adsorbent for simultaneous dye and phosphate adsorption.Practitioner Points

This study aims to modify the surface of calcium alginate beads with polyethyleneimine (PEI).
The adsorption of RBBR and phosphate by the modified alginate beads (PEI‐CaAlg) was investigated.
PEI is an organic polymer with a linear/branch shape, which can increase the active sites on the adsorbent surface.
PEI has one nitrogen atom in every three atoms provides a positive charge that can complex with the negatively charged molecules.
The adsorption of RBBR and phosphate were carried out onto PEI‐CaAlg.
Verification of piecewise deep neural networks: a star set approach with zonotope pre-filter
Authors: Tran Hoang-Dung , Pal Neelanjana , Lopez Diego Manzanas , Musau Patrick , Yang Xiaodong , Nguyen Luan Viet , Xiang Weiming , Bak Stanley , Johnson Taylor T. 
Published: August 2021

Abstract
Verification has emerged as a means to provide formal guarantees on
learning-based systems incorporating neural network before using
them in safety-critical applications. This paper proposes a new
verification approach for deep neural networks (DNNs) with piecewise
linear activation functions using reachability analysis. The core of
our approach is a collection of reachability algorithms using star
sets (or shortly, stars), an effective symbolic representation of
high-dimensional polytopes. The star-based reachability algorithms
compute the output reachable sets of a network with a given input
set before using them for verification. For a neural network with
piecewise linear activation functions, our approach can construct
both exact and over-approximate reachable sets of the neural
network. To enhance the scalability of our approach, a star set is
equipped with an outer-zonotope (a zonotope over-approximation of
the star set) to quickly estimate the lower and upper bounds of an
input set at a specific neuron to determine if splitting occurs at
that neuron. This zonotope pre-filtering step reduces significantly
the number of linear programming optimization problems that
must be solved in the analysis, and leads to a reduction in
computation time, which enhances the scalability of the star set
approach. Our reachability algorithms are implemented in a software
prototype called the neural network verification tool, and can
be applied to problems analyzing the robustness of machine learning
methods, such as safety and robustness verification of DNNs. Our
experiments show that our approach can achieve runtimes twenty to
1400 times faster than Reluplex, a satisfiability modulo
theory-based approach. Our star set approach is also less
conservative than other recent zonotope and abstract domain
approaches.
The goldfish Carassius auratus: an emerging animal model for comparative cardiac research
Authors: Filice Mariacristina , Cerra Maria Carmela , Imbrogno Sandra 
Published: August 2021

AbstractThe use of unconventional model organisms is significantly increasing in different fields of research, widely contributing to advance life sciences understanding. Among fishes, the cyprinid Carassius auratus (goldfish) is largely used for studies on comparative and evolutionary endocrinology, neurobiology, adaptive and conservation physiology, as well as for translational research aimed to explore mechanisms that may be useful in an applicative biomedical context. More recently, the research possibilities offered by the goldfish are further expanded to cardiac studies. A growing literature is available to illustrate the complex networks involved in the modulation of the goldfish cardiac performance, also in relation to the influence of environmental signals. However, an overview on the existing current knowledge is not yet available. By discussing the mechanisms that in C. auratus finely regulate the cardiac function under basal conditions and under environmental challenges, this review highlights the remarkable flexibility of the goldfish heart in relation not only to the basic morpho-functional design and complex neuro-humoral traits, but also to its extraordinary biochemical-metabolic plasticity and its adaptive potential. The purpose of this review is also to emphasize the power of the heart of C. auratus as an experimental tool useful to investigate mechanisms that could be difficult to explore using more conventional animal models and complex cardiac designs.