bluuebunny/crossref_metadata_2025_split huggingface dataset:
Social Health and Cognitive Change in Old Age: Role of Brain Reserve
Authors: Marseglia Anna , Kalpouzos Grégoria , Laukka Erika J. , Maddock Jane , Patalay Praveetha , Wang Hui‐Xin , Bäckman Lars , Westman Eric , Welmer Anna‐Karin , Dekhtyar Serhiy ,   the SHARED Consortium
Published: December 2022

ObjectiveIndividual aspects of social health (SH; eg, network, engagement, support) have been linked to cognitive health. However, their combined effect and the role of the structural properties of the brain (brain reserve [BR]) remain unclear. We investigated the interplay of SH and BR on cognitive change in older adults.MethodsWithin the Swedish National Study on Aging and Care–Kungsholmen, 368 dementia‐free adults aged ≥60 years with baseline brain magnetic resonance imaging were followed over 12 years to assess cognitive change. A measure of global cognition was computed at each of the 5 waves of assessment by averaging domain‐specific Z scores for episodic memory, perceptual speed, semantic memory, and letter and category fluency. An SH composite score was computed at baseline by combining leisure activities and social network. BR was proxied by total brain tissue volume (TBTV). Linear mixed models (adjusted for sociodemographic, vascular, and genetic factors) were used to estimate cognitive trajectories in relation to SH and TBTV. Interaction analysis and stratification were used to examine the interplay between SH and TBTV.ResultsModerate–good SH (n = 245; vs poor, β‐slope = 0.01, 95% confidence interval [CI] = 0.002–0.02, p = 0.018) and moderate‐to‐large TBTV (n = 245; vs small, β‐slope = 0.03, 95% CI = 0.02–0.04, p < 0.001) were separately associated with slower cognitive decline. In stratified analysis, moderate–good SH was associated with higher cognitive levels (but not change) only in participants with moderate‐to‐large TBTV (β‐intercept = 0.21, 95% CI = 0.06–0.37, p < 0.01; interaction SH * TBTV, p < 0.05).InterpretationOur findings highlight the interplay between SH and BR that likely unfolds throughout the entire life course to shape old‐age cognitive outcomes. ANN NEUROL 2023;93:844–855
Subsurface Engineering Induced Fermi Level De‐pinning in Metal Oxide Semiconductors for Photoelectrochemical Water Splitting
Authors: Wang Jun , Ni Ganghai , Liao Wanru , Liu Kang , Chen Jiawei , Liu Fangyang , Zhang Zongliang , Jia Ming , Li Jie , Fu Junwei , Pensa Evangelina , Jiang Liangxing , Bian Zhenfeng , Cortés Emiliano , Liu Min 
Published: December 2022

AbstractPhotoelectrochemical (PEC) water splitting is a promising approach for renewable solar light conversion. However, surface Fermi level pinning (FLP), caused by surface trap states, severely restricts the PEC activities. Theoretical calculations indicate subsurface oxygen vacancy (sub‐Ov) could release the FLP and retain the active structure. A series of metal oxide semiconductors with sub‐Ov were prepared through precisely regulated spin‐coating and calcination. Etching X‐ray photoelectron spectroscopy (XPS), scanning transmission electron microscopy (STEM), and electron energy loss spectra (EELS) demonstrated Ov located at sub ∼2–5 nm region. Mott–Schottky and open circuit photovoltage results confirmed the surface trap states elimination and Fermi level de‐pinning. Thus, superior PEC performances of 5.1, 3.4, and 2.1 mA cm−2 at 1.23 V vs. RHE were achieved on BiVO4, Bi2O3, TiO2 with outstanding stability for 72 h, outperforming most reported works under the identical conditions.
Precise Assembly of Polyoxometalates at Single‐cluster Levels
Authors: Liu Qingda , Wang Xun 
Published: December 2022

AbstractPolyoxometalate (POM) clusters with atomic precision structures are promising candidates construct functional nanomaterials via self‐assembly. Non‐covalent interactions at molecular levels can govern the self‐assembly of POM clusters, for which the precise control of POM‐based assemblies can be realized at single‐cluster levels. This mini‐review focuses on the synthesis and properties of POM‐based nanostructures, including amphiphilic POM assemblies and co‐assemblies of POM clusters and other subnanometer building blocks. Several synthetic strategies have been developed for rational control of POM‐based assemblies in terms of morphologies, compositions and properties. 1D subnanometer POM assemblies demonstrate remarkable enhanced mechanical properties due to the topological interactions between nanowires and surroundings. The in‐depth understanding of POM‐based assemblies may help in the design of functional nanomaterials in fundamental perspectives and applications.
Molecular Level Modulation of Anthraquinone‐containing Resorcinol‐formaldehyde Resin Photocatalysts for H2O2 Production with Exceeding 1.2 % Efficiency
Authors: Zhao Chen , Wang Xinyao , Yin Yanfeng , Tian Wenming , Zeng Guang , Li Haitao , Ye Sheng , Wu Limin , Liu Jian 
Published: December 2022

AbstractDesigning polymeric photocatalysts at the molecular level to modulate the photogenerated charge behavior is a promising and challenging strategy for efficient hydrogen peroxide (H2O2) photosynthesis. Here, we introduce electron‐deficient 1,4‐dihydroxyanthraquinone (DHAQ) into the framework of resorcinol‐formaldehyde (RF) resin, which modulates the donor/acceptor ratio from the perspective of molecular design for promoting the charge separation. Interestingly, H2O2 can be produced via oxygen reduction and water oxidation pathways, verified by isotopic labeling and in situ characterization techniques. Density functional theory (DFT) calculations elucidate that DHAQ can reduce the energy barrier for H2O2 production. RF‐DHAQ exhibits excellent overall photosynthesis of H2O2 with a solar‐to‐chemical conversion (SCC) efficiency exceeding 1.2 %. This work opens a new avenue to design polymeric photocatalysts at the molecular level for high‐efficiency artificial photosynthesis.
Modeling wide range of viscoelastic–viscoplastic behavior of AralditeLY564 epoxy using cooperative viscoplasticity theory based on overstress model
Authors: Bakbak Okan , Colak Ozgen 
Published: December 2022

AbstractThe rate‐dependent properties of epoxy (Araldite LY 564) were successfully addressed by dynamic mechanical analysis (DMA), quasi‐static compression tests (strain rates: 1.E‐3, 1.E‐2, and 1.E‐1 /s), Split Hopkinson Pressure Bar (SHPB) testing (strain rates: 875 and 770/s) and stress relaxation experiments (strain levels: 3.16 and 7.15%) are simulated by a micromechanically based constitutive model. The used model is Cooperative‐Viscoplasticity Theory Based on Overstress (VBO) model. The majority of works about modeling polymers are limited to modeling quasi‐static tension‐compression behaviors and predicting elasticity modulus and yield strength. In this work, the effectiveness of the Cooperative‐VBO model is verified and validated by simulating a wide range of material behaviors of Araldite LY 564. Material parameters of the model are determined by using storage modulus obtained from DMA and quasi‐static compression test at a strain rate of 1.E‐1 /s. High strain rate behaviors and stress relaxation behaviors are predicted. The behaviors from quasi‐static to high strain rate, from stress relaxation at different strain levels to storage modulus, respectively, are predicted with a single set of material parameters. Simulation and prediction results revealed the effectiveness of the proposed model.
Population structure and genetic connectivity reveals distinctiveness of Irish harbour seals (Phoca vitulina) and implications for conservation management
Authors: Steinmetz Kristina , Murphy Sinéad , Cadhla Oliver Ó. , Carroll Emma L. , Onoufriou Aubrie B. , Russell Debbie J. F. , Cronin Michelle , Mirimin Luca 
Published: December 2022

Abstract

The identification of discrete intraspecific units, such as genetically informed management units (MUs), is important to effectively develop and implement conservation strategies for protected species. Harbour seals (Phoca vitulina) occurring in Irish waters are currently viewed as a single nationwide panmictic population (and hence MU), although this assumption is not based on any knowledge of population structure because of the lack of available genetic data.
Thus, the present study used mitochondrial control region sequences and between nine and 11 microsatellite loci from harbour seals from Ireland and Northern Ireland (up to n = 123) and adjacent UK/European waters (up to n = 289) to provide insights into the genetic population structure and diversity of harbour seals in the areas studied.
Within the island of Ireland, genetic analyses revealed the presence of three genetically distinct local populations, characterized by high genetic diversity, hereby defined as: East Ireland (EI), North‐west & Northern Ireland (NWNI), and South‐west Ireland (SWI).
Using previously published and newly generated data, a subsequent wider scale analysis revealed that the EI and SWI local populations were genetically distinct from neighbouring UK/European areas, whereas seals from the NWNI area could not be distinguished from a previously identified Northern UK metapopulation. Migration rate estimates showed that NWNI receives migrants from North‐west Scotland, with NWNI acting as a genetic source for both SWI and EI.
The present study provides the most comprehensive genetic assessment of harbour seals in European waters to date, with findings indicating that conservation strategies for harbour seals in Irish waters should be amended to accommodate at least three genetically distinct local populations/MUs. The use of approaches considering both ecological and genetic parameters is recommended for future assessments and delineation of units of ecological relevance for conservation management purposes.
Sufficiency for diagnosability of stochastic discrete‐event systems and a polynomial‐time verification
Authors: Cao Weihua , Liu Fuchun 
Published: December 2022

AbstractThe notion of diagnosability of stochastic discrete‐event systems (SDESs) was introduced in the literature, but the method for verifying the diagnosability of SDESs was exponential. However, is there a sufficient condition of diagnosability of SDESs that can be tested with polynomial method? In this paper, we present a sufficient condition of diagnosability of SDESs based on a constructive testing automaton, and a polynomial method is proposed to test the condition.
The branch‐cut cosmology: evidences and open questions
Authors: Zen Vasconcellos César A. , Hess Peter O. , de Freitas Pacheco José , Hadjimichef Dimiter , Bodmann Benno 
Published: December 2022

AbstractIn this work, we present a brief review of the branch‐cut cosmology as well as we approach topics not yet investigated. Starting with an already explored topic, the theme of the primordial singularity suppression, we approach essential themes for a better understanding of the scope of branch‐cut cosmology. More precisely, based on recent contributions, we advance a better understanding of the branch‐cut scenarios as well as essential topics for modern cosmology such as the flatness, homogeneity, and horizon problems from the classical point of view of the branch‐cut cosmology.
Fine motor skill and expressive language in minimally verbal and verbal school‐aged autistic children
Authors: Butler Lindsay K. , Tager‐Flusberg Helen 
Published: December 2022

AbstractFine motor skill is associated with expressive language outcomes in infants who have an autistic sibling and in young autistic children. Fewer studies have focused on school‐aged children even though around 80% have motor impairments and 30% remain minimally verbal (MV) into their school years. Moreover, expressive language is not a unitary construct, but it is made up of components such as speech production, structural language, and social‐pragmatic language use. We used natural language sampling to investigate the relationship between fine motor and speech intelligibility, mean length of utterance and conversational turns in MV and verbal autistic children between the ages of 4 and 7 while controlling for age and adaptive behavior. Fine motor skill predicted speech production, measured by percent intelligible utterances. Fine motor skill and adaptive behavior predicted structural language, measured by mean length of utterance in morphemes. Adaptive behavior, but not fine motor skill, predicted social‐pragmatic language use measured by number of conversational turns. Simple linear regressions by group corrected for multiple comparisons showed that fine motor skill predicted intelligibility for MV but not verbal children. Fine motor skill and adaptive behavior predicted mean length of utterance for both MV and verbal children. These findings suggest that future studies should explore whether MV children may benefit from interventions targeting fine motor along with speech and language into their school years.
Optimization of feather degradation by a Bacillus thuringiensis isolate using response surface methodology and investigation of the feather protein hydrolysate structure
Authors: Elleboudy Nooran Sherif , Trabik Yossra A. , Aboulwafa Mohammad Mabrouk 
Published: December 2022

AbstractValorization of chicken feather is a long‐sought approach for its sustainable disposal. Being protein rich, hydrolyzed chicken feather has a wide range of applications, not limited to formulation of microbiological culture media, animal feed, and biofertilizers, but extends to synthesis of bioplastic films, cosmetics, and biomedicals. In this study, a potent keratinolytic isolate was recovered from soil and identified by 16S rRNA as Bacillus thuringiensis. Feather degradation by the isolate was optimized through response surface methodology. First, one‐variable‐at‐a‐time technique to assign the factors that affect feather degradation, then Box–Behnken central composite design model were employed. The model, involving three independent variables (initial pH, inoculum size, and concentration of supplementary glucose), was significant (R2 = 0.9716). According to the model, complete feather degradation is obtained at an inoculum size of B. thuringiensis B4 equal to 1 × 1010 CFU/ml, when feather meal broth is supplemented with 1.5% (w/v) glucose and pH adjusted to 8.5. Protein content of the lysate was 327.8 ± 25 μg/ml, and no carbohydrates were detected. SEM/EDX analysis has shown that the hydrolysate consisted mainly of O, P, S, and Se in addition to carbon, while FTIR images assured the presence of carboxyl and amino groups characteristic of peptides and amino acids.
Immobilization of the metagenomic lipase, LipG9, on porous pellets of poly‐hydroxybutyrate produced by the double emulsion solvent evaporation technique
Authors: Richter Jeferson Luiz , Zawadzki Sônia Faria , Alves dos Santos Leandro , Alnoch Robson Carlos , Moure Vivian Rotuno , Mitchell David Alexander , Krieger Nadia 
Published: December 2022

AbstractThis work aimed to produce porous poly‐hydroxybutyrate (PHB) pellets in order to evaluate the pellets as a support for immobilization of the metagenomic lipase, LipG9. Four types of pelletized PHB particles with different morphological characteristics were obtained using the double emulsion and solvent evaporation technique (DESE). The micropores of these PHB pellets had similar average diameters (about 3 nm), but the pellets had different specific surface areas: 11.7 m2 g−1 for the PHB powder, 8.4 m2 g−1 for the control pellets (Ø < 0.5 mm, produced without the pore forming agent), 10.0 m2 g−1 for the small pellets (Ø < 0.5 mm), 9.5 m2 g−1 for the medium pellets (0.5 < Ø < 0.8 mm) and 8.4 m2 g−1 for the large pellets (Ø > 1.4 mm). Purified LipG9 was immobilized by adsorption on these pellets, and the results were compared with those obtained with PHB powder. The highest immobilization yield (83%) was obtained for the medium PHB pellets, followed by large (76%) and small (55%) PHB pellets. The activity of LipG9 immobilized on the pellets, for the synthesis of ethyl oleate in n‐hexane, was highest for the medium pellets (22 U g−1). The immobilization yield was high for PHB powder (99%) but the esterification activity was slightly lower (20 U g−1). These results show that pelletized PHB beads can be used for the immobilization of lipases, with the advantage that pelletized PHB will perform better than PHB powder in large‐scale enzyme bioreactors.
Ultrasensitive green spectrofluorimetric approach for quantification of Hg(II) in environmental samples (water and fish samples) using cysteine@MnO2 dots
Authors: Salman Baher I. , Hassan Yasser F. , Ali Marwa F. B. , Batakoushy Hany A. 
Published: December 2022

AbstractMercury (Hg2+) is a natural element present in foods such as fish, water and soil. Exposure to mercury leads to severe toxic effects on the nervous, digestive, and immune systems. Here, a novel, green, and environmentally friendly fluorescent probe decorated with cysteine/MnO2 quantum dots (Cys@MnO2 QDs) was synthesized. This synthesis was carried out using a simple ultrasound technique with the aid of cysteine for fabricating Cys@MnO2 QDs to estimate Hg levels in fish and water samples. In this morphological study, Cys@MnO2 QDs were fully characterized using high‐resolution transmission electron microscopy, zeta potential analysis, fluorescence, ultraviolet–visible and infrared spectroscopy. The fluorescence of the synthesized Cys@MnO2 QDs was significantly quenched by gradually increasing the Hg(II) concentration. The quenching mechanism based on the Hg–S bonds strengthened the utility of the Cys@MnO2 QDs as a novel luminescent nanoprobe. The estimation of Hg was linear in the concentration range 0.7–100.0 ng mL−1 with a limit of quantitation equal to 0.30 ng mL−1. The Cys@MnO2 QDs are fluorescent probes with various benefits such as speed, ease of use, cost‐ effective, and being environmentally friendly; they are easily applied in food manufacturing and for public health improvement.
Business model innovation for the Sustainable Development Goals
Authors: Rosati Francesco , Rodrigues Vinicius P. , Cosenz Federico , Li‐Ying Jason 
Published: December 2022

AbstractBusiness model innovation can be a key driver to realizing the transformation needed to achieve the United Nations Sustainable Development Goals (SDGs). At the same time, the SDGs can support organizations as they identify and tackle opportunities for business model innovation. This study uses a constructive research method to build a managerial approach that supports business model innovation for the SDGs. The approach helps organizations assess their contribution to the SDGs, explore and prioritize SDG‐oriented business opportunities and risks, and formulate business model innovation strategies accordingly. The proposed approach was developed through participatory action research conducted in collaboration with two companies operating in the medical and educational sectors and then applied to Ørsted, a multinational power company, which is strongly committed to a sustainability‐driven business transformation and aspires to contribute strongly to SDG 7 (Affordable and clean energy) and SDG 13 (Climate action). The study furthers the academic and practical debate on business model innovation for sustainability by providing new academic and practical knowledge on how organizations can use the SDGs to stimulate business model innovations.
How does climate change affect firms' investment efficiency? Evidence from China's listed renewable energy firms
Authors: Yu Shiwei , Zheng Yali , Hu Xing 
Published: December 2022

AbstractImproving the investment efficiency of renewable energy (RE) firms is one of the critical measures for energy low‐carbon transformation and mitigating climate change. To investigate the impact of climate change (greenhouse gas emissions, extreme temperatures, and extreme weather events) on the investment efficiency of RE firms, the present study applied a fixed effect regression model by using the panel data of China's 205 listed non‐hydro RE firms during 2008–2019. The influencing mechanism and the heterogeneity among RE firms are also explored. The results show that (1) CO2 emissions and extreme weather events significantly improve the investment efficiency of RE firms, whereas extreme temperatures' effect is significantly negative. (2) CO2 emissions can promote the investment efficiency of wind and solar firms with environmental responsibility through reducing agency problems and information asymmetry. (3) RE policies play an active role between climate change and investment efficiency of wind and solar energy firms, but the promotion effect is not significant for biomass energy firms. (4) The joint effect of climate change and RE policies on investment efficiency are more prominent for wind and solar energy firms in a low‐marketized environment and state‐owned firms. These results suggest that wind and solar firms should seize market investment opportunities when facing climate change. Besides, policymakers should strengthen market‐oriented construction and improve the completeness of RE policies in low‐marketization areas.
Deep learning‐based multimodal fusion network for segmentation and classification of breast cancers using B‐mode and elastography ultrasound images
Authors: Misra Sampa , Yoon Chiho , Kim Kwang‐Ju , Managuli Ravi , Barr Richard G. , Baek Jongduk , Kim Chulhong 
Published: December 2022

AbstractUltrasonography is one of the key medical imaging modalities for evaluating breast lesions. For differentiating benign from malignant lesions, computer‐aided diagnosis (CAD) systems have greatly assisted radiologists by automatically segmenting and identifying features of lesions. Here, we present deep learning (DL)‐based methods to segment the lesions and then classify benign from malignant, utilizing both B‐mode and strain elastography (SE‐mode) images. We propose a weighted multimodal U‐Net (W‐MM‐U‐Net) model for segmenting lesions where optimum weight is assigned on different imaging modalities using a weighted‐skip connection method to emphasize its importance. We design a multimodal fusion framework (MFF) on cropped B‐mode and SE‐mode ultrasound (US) lesion images to classify benign and malignant lesions. The MFF consists of an integrated feature network (IFN) and a decision network (DN). Unlike other recent fusion methods, the proposed MFF method can simultaneously learn complementary information from convolutional neural networks (CNNs) trained using B‐mode and SE‐mode US images. The features from the CNNs are ensembled using the multimodal EmbraceNet model and DN classifies the images using those features. The experimental results (sensitivity of 100 ± 0.00% and specificity of 94.28 ± 7.00%) on the real‐world clinical data showed that the proposed method outperforms the existing single‐ and multimodal methods. The proposed method predicts seven benign patients as benign three times out of five trials and six malignant patients as malignant five out of five trials. The proposed method would potentially enhance the classification accuracy of radiologists for breast cancer detection in US images.
Theoretical Aspects and Applications of Aqueous Two‐Phase Systems
Authors: Singla Mohit , Sit Nandan 
Published: December 2022

AbstractThe aqueous two‐phase system (ATPS) is commonly known as a technique that yields high‐purity products in a single step. It is particularly advantageous for purifying biomolecules like proteins, nucleic acids, enzymes, viruses etc. Currently, aqueous two‐phase extraction (ATPE), i.e., liquid‐liquid extraction, involves the transfer of the solute from one aqueous phase to another. In ATPE, for recovery of biomolecules, polymer‐polymer and polymer‐salt type systems are used. The most recent developments with respect to recovery of biomolecules by ATPS are reviewed and discussed, covering the mechanism, which controls the phase formation, the conditions of solute partitioning in ATPS processes, and factors influencing the ATPS including concentration and molecular weight (MW) of polymers, types of salt, pH, and temperature. In addition, also the increasing applications of ATPS for the recovery of high‐value bioproducts, the benefits of the ATPS recovery system, and the recent developments of alternative low‐cost ATPS are highlighted.