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A facile strategy for tuning the density of surface-grafted biomolecules for melt extrusion-based additive manufacturing applications

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Bio-Design and manufacturing 2024年第3期7卷 277-291页

作者： I.A.O.Beeren G.Dos Santos P.J.Dijkstra c.mota J.Bauer H.Ferreira Rui L.reis N.Neves S.camarero-Espinosa m.B.Baker L.moroni Department of complex Tissue Regeneration MERLN Institute for Technology-Inspired Regenerative MedicineMaastricht University6229 ER MaastrichtThe Netherlands 3B’s Research Group I3Bs–Research Institute on BiomaterialsBiodegradables and BiomimeticsHeadquarters of the European Institute of Excellence on Tissue Engineering and Regenerative MedicineUniversity of MinhoAveParkZona Industrial da Gandra4805-017 BarcoGuimarãesPortugal IcVS/3B’s-PT Government Associate Laboratory 4806-909 Braga/GuimarãesPortugal POLYmAT University of the Basque Country UPV/EHU20018 Donostia/San SebastiánSpain IKERBASQUE Basque Foundation for Science48009 BilbaoSpain

melt extrusion-based additive manufacturing(mE-Am)is a promising technique to fabricate porous scaffolds for tissue engi-neering ***,most synthetic semicrystalline polymers do not possess the intrinsic biological activity required to control cell *** of biomolecules on polymeric surfaces of Am scaffolds enhances the bioactivity of a construct;however,there are limited strategies available to control the surface ***,we report a strategy to tune the surface density of bioactive groups by blending a low molecular weight poly(ε-caprolactone)5k(PcL5k)containing orthogonally reactive azide groups with an unfunctionalized high molecular weight PcL75k at different *** porous three-dimensional(3D)scaf-folds were then fabricated using a high weight percentage(75 wt.%)of the low molecular weight PcL *** a proof-of-concept test,we prepared films of three different mass ratios of low and high molecular weight polymers with a thermopress and reacted with an alkynated fluorescent model compound on the surface,yielding a density of 201-561 pmol/cm^(2).Subsequently,a bone morphogenetic protein 2(BmP-2)-derived peptide was grafted onto the films comprising different blend compositions,and the effect of peptide surface density on the osteogenic differentiation of human mesenchymal stromal cells(hmScs)was *** two weeks of culturing in a basic medium,cells expressed higher levels of BmP receptor II(BmPRII)on films with the conjugated *** addition,we found that alkaline phosphatase activity was only significantly enhanced on films contain-ing the highest peptide density(i.e.,561 pmol/cm^(2)),indicating the importance of the surface *** together,these results emphasize that the density of surface peptides on cell differentiation must be considered at the cell-material ***,we have presented a viable strategy for mE-Am community that desires to tune the bulk and surface functionality via blending of(m

关键词： Additive manufacturing Blending Surface functionalization Surface density click chemistry Human

Adsorption of yttrium(Y^(3+)) and concentration of rare earth elements from phosphogypsum using chitin and chitin aerogel

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Journal of Rare Earths 2024年第4期42卷 775-782页

作者： Glaydson S.dos reis Diana Pinto Sabrina F.Lütke Eder c.Lima Luis F.O.Silva Irineu A.S.De Brum Guilherme L.Dotto Department of Forest Biomaterials and Technology Biomass Technology centre Swedish University of Agricultural SciencesUmeaE13Swedn Universidad De La costa Calle 58#55-66080002BarranquillaAtlanticoColombia Research Group on Adsorptive and catalytic Process Engineering(ENGEPAc) Federal University of Santa MariaAv.Roraima100079705900Santa MariaRSBrazil Institute of chemistry Federal University of Rio Grande do Sul90040060Porto AlegreBrazil

chitin powder and chitin-aerogel were prepared from shrimp wastes and used to uptake Y^(3+)from aqueous solutions and concentrate this rare earth element from phosphogypsum(PG).chitin aerogel displays a specific surface area of 945 m^(2)/g,while chitin powder is 3.6 m^(2)/g,which largely influences its adsorption *** the adsorption in synthetic solutions,the effect of pH on Y^(3+)removal is strong for chitin powder *** contrast,no big pH influence was detected for chitin *** interactions and chelation can highlight the proposed mechanism of Y^(3+)on chitin adsorbents for the powder and ***,in addition to these interactions,pore filling/pore diffusion is the main mechanism of Y^(3+)removal in the chitin *** aerogel is efficient in concentrating 8 times the Y^(3+)from PG,a very complex *** complex chitin aerogel-Y^(3+)can be a secondary source of rare earth elements for other applications.

关键词： Rare earths Sustainable material chitin powder chitin porous aerogel Yttrium adsorption and recovery

consumer transparency in the production chain for plant varieties produced using new genomic techniques

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aBIOTEcH 2024年第2期5卷 239-246页

作者： J.m.Lukasiewicz c.c.m.van de Wiel L.A.P.Lotz m.J.m.Smulders Wageningen University&Research P.O.Box 386NL-6700 AJ WageningenThe Netherlands

Plants edited with new genomic techniques(NGTs)currently fall under the Genetically modified Organisms Directive(2001/18/Ec)in the European *** the proposal of the European commission,NGT plants are partially exempted from the regulations of this *** proposal makes a distinction between two categories of NGT plants:NGT-1 and ***-1 category plants are considered equal to plants obtained through conventional breeding *** plants will not be labelled for the consumer,although they will be labelled as ***-2 category plants may be labelled with additional information as a positive *** of seeds of varieties made with gene editing,but not the products,would mean that most steps in the production chain are transparent,but not the last step towards ***“right to know”and increasing knowledge of gene-edited food is a common theme in food labelling towards ***,we describe current labelling regimes and registers and how these may be applied to provide transparency on gene-edited products to ***,we also look into consumer studies,which indicate a greater acceptance of gene-edited food among consumers,especially when additional benefits such as sustainability are mentioned.

关键词： Labelling New genomic techniques consumer transparency Plant products

Unravelling cOVID-19 waves in Rio de Janeiro city:Qualitative insights from nonlinear dynamic analysis

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Infectious Disease modelling 2024年第2期9卷 314-328页

作者： Adriane S.reis Laurita dos Santos Américo cunha Jr Thaís c.R.O.Konstantyner Elbert E.N.macao Institute of Science and Technology Federal University of São PauloSão Josédos CamposSPBrazil Physics Institute University of São PauloSão PauloSPBrazil Scientific and Technological Institute Universidade BrasilSão PauloSPBrazil Department of Applied mathematics Rio de Janeiro State UniversityRio de JaneiroRJBrazil Paulista School of medicine Federal University of São PauloSão PauloSPBrazil

Since the cOVID-19 pandemic was first reported in 2019,it has rapidly spread around the *** countries implemented several measures to try to control the virus *** healthcare system and consequently the general quality of life population in the cities have all been significantly impacted by the coronavirus *** different waves of contagious were responsible for the increase in the number of cases that,unfortunately,many times lead to *** this paper,we aim to characterize the dynamics of the six waves of cases and deaths caused by cOVID-19 in Rio de Janeiro city using techniques such as the Poincaréplot,approximate entropy,second-order difference plot,and central tendency *** results reveal that by examining the structure and patterns of the time series,using a set of non-linear techniques we can gain a better understanding of the role of multiple waves of cOVID-19,also,we can identify underlying dynamics of disease spreading and extract meaningful information about the dynamical behavior of epidemiological time *** findings can help to closely approximate the dynamics of virus spread and obtain a correlation between the different stages of the disease,allowing us to identify and categorize the stages due to different virus variants that are reflected in the time series.

关键词： cOVID-19 Nonlinear analysis Poincaréplot central tendency measure

metabolic disease and the liver: A review

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World Journal of Hepatology 2024年第1期16卷 33-40页

作者： márcia Vargas Sheila de castro cardoso Toniasso Patricia G Riedel camila Pereira Baldin Francielle Lopes dos reis Robson martins Pereira maria carlota Borba Brum Dvora Joveleviths mario reis Alvares-da-Silva Program of Graduate Science in Gastroenterology and Hepatology Federal University of Rio Grande do SulPorto Alegre 90040-060Rio Grande do SulBrazil School of medicine Federal University of Rio Grande do SulPorto Alegre 90040-060Brazil Program of Graduate Science in Gastroenterology and Hepatology Clinicas Hospital of Porto AlegrePorto Alegre 90410000Brazil medicine Faculty Federal University of Rio Grande do Sul Federal University of Rio Grande do SulPorto Alegre 90040-060Brazil Division of Gastroenterology and Hepatology Clinicas Hospital of Porto AlegrePorto Alegre 90035007Brazil

metabolic dysfunction-associated steatotic liver disease(mASLD)is the most common liver disease worldwide,with an estimated prevalence of 31%in Latin *** presence of metabolic comorbidities coexisting with liver disease varies substantially among *** is acknowledged that obesity is boosting the type 2 diabetes mellitus“epidemic,”and both conditions are significant contributors to the increasing number of patients with *** steatohepatitis represents a condition of chronic liver inflammation and is considered the most severe form of *** diagnosis is based on the presence of steatosis,noninvasive scores and altered liver *** scores of liver fibrosis,such as serum biomarkers,which should be used in primary care to rule out advanced fibrosis,are simple,inexpensive,and widely ***,guidelines from international hepatology societies recommend using noninvasive strategies to simplify case finding and management of high-risk patients with mASLD in clinical ***,there is no definite pharmacological treatment for the *** public health policies to treat patients with risk factors for mASLD prevention is essential.

关键词： Nonalcoholic fatty liver disease Primary care metabolic risk Liver metabolism

mulberry Biomass-Derived Nanomedicines mitigate colitis through Improved Inflamed mucosa Accumulation and Intestinal microenvironment modulation

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Research 2024年第1期2023卷 791-807页

作者： Wenjing Yang Ya ma Haiting Xu Zhenhua Zhu Jiaxue Wu cheng Xu Wei Sun Erhu Zhao min Wang Rui L.reis Subhas c.Kundu Xiaoxiao Shi Bo Xiao State Key Laboratory of Silkworm Genome Biology College of SericultureTextileand Biomass SciencesSouthwest UniversityChongqing 400715China chongqing Key Laboratory of Soft-matter material chemistry and Function manufacturing Faculty of Materials and EnergySouthwest UniversityChongqing 400715China Department of Gastroenterology The First Affiliated Hospital of Nanchang UniversityNanchang 330006China Bs Research Group I3Bs—Research Institute on BiomaterialsBiodegradables and BiomimeticsUniversity of MinhoHeadquarters of the European Institute of Excellence on Tissue Engineering and Regenerative MedicineAveParkBarco 4805-017GuimaraesPortugal IcVS/3B’s-PT Government Associate Laboratory BragaGuimarãesPortugal

The therapeutic outcomes of conventional oral medications against ulcerative colitis(Uc)are restricted by inefficient drug delivery to the colitis mucosa and weak capacity to modulate the inflammatory ***,a fluorinated pluronic(FP127)was synthesized and employed to functionalize the surface of mulberry leaf-derived nanoparticles(mLNs)loading with resveratrol nanocrystals(RNs).The obtained FP127@RN-mLNs possessed exosome-like morphologies,desirable particle sizes(around 171.4 nm),and negatively charged surfaces(−14.8 mV).The introduction of FP127 to RN-mLNs greatly improved their stability in the colon and promoted their mucus infiltration and mucosal penetration capacities due to the unique fluorine effect.

关键词： fluorine sizes Biomass

Performance of evolutionary optimized machine learning for modeling total organic carbon in core samples of shale gas fields

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Petroleum 2024年第1期10卷 150-164页

作者： Leonardo Goliatt c.m.Saporetti L.c.Oliveira E.Pereira Department of computational and Applied mechanics Federal University of Juiz de ForaJuiz de ForaBrazil Department of computational modeling Polytechnic InstituteRio de Janeiro State UniversityNova FriburgoBrazil Petrobras Rio de JaneiroBrazil Department of Stratigraphy and Paleontology Rio de Janeiro State UniversityRio de JaneiroBrazil

Rock samples'TOc content is the best indicator of the organic matter in source *** origin rock samples’analysis is used to calculate it manually by *** method requires time and resources because it relies on samples from many well intervals in source ***,research has been done to aid this *** learning algorithms can estimate total organic carbon instead of well logs and stratigraphic *** light of these efforts,the current work present a study on automating the total organic carbon estimation using machine learning approaches improved by an evolutionary methodology to give the model flexibility and *** algorithms,differential evolution,particle swarm optimization,grey wolf optimization,artificial bee colony,and evolution strategies were used to improve machine learning models to predict *** six metaheuristics were integrated into four machine learning methods:extreme learning machine,elastic net linear model,linear support vector regression,and multivariate adaptive regression *** samples from the YuDong-Nan shale gas field,located in the Sichuan basin,were used to evaluate the hybrid *** findings show that combining machine learning models with an evolutionary algorithms in a hybrid fashion produce flexible models that accurately predict *** results show that,independent of the metaheuristic used to guide the model selection,optimized extreme learning machines attained the best performance scores according to six *** hybrid models can be used in exploratory geological research,particularly for unconventional oil and gas resources.

关键词： Total organic carbon Hybrid models Automated machine learning Evolutionary algorithms Geology

An improved pulse coupled neural networks model for semantic IoT

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Digital communications and Networks 2024年第3期10卷 557-567页

作者： Rong ma Zhen Zhang Yide ma Xiping Hu Edith c.H.Ngai Victor c.m.Leung School of Information Science and Engineering Lanzhou UniversityLanzhou 730000China School of medical Technology Beijing Institute of TechnologyBeijing100081China Department of Electrical and Electronic Engineer The University of Hong KongHong Kong 999077China college of computer Science and Software Engineering Shenzhen UniversityShenzhen 518060China Department of Electrical and computer Engineering the University of British ColumbiaVancouverBC V6T 1Z4Canada

In recent years,the Internet of Things(IoT)has gradually developed applications such as collecting sensory data and building intelligent services,which has led to an explosion in mobile data ***,with the rapid development of artificial intelligence,semantic communication has attracted great attention as a new communication ***,for IoT devices,however,processing image information efficiently in real time is an essential task for the rapid transmission of semantic *** the increase of model parameters in deep learning methods,the model inference time in sensor devices continues to *** contrast,the Pulse coupled Neural Network(PcNN)has fewer parameters,making it more suitable for processing real-time scene tasks such as image segmentation,which lays the foundation for real-time,effective,and accurate image ***,the parameters of PcNN are determined by trial and error,which limits its *** overcome this limitation,an Improved Pulse coupled Neural Networks(IPcNN)model is proposed in this *** IPcNN constructs the connection between the static properties of the input image and the dynamic properties of the neurons,and all its parameters are set adaptively,which avoids the inconvenience of manual setting in traditional methods and improves the adaptability of parameters to different types of *** segmentation results demonstrate the validity and efficiency of the proposed self-adaptive parameter setting method of IPcNN on the gray images and natural images from the matlab and Berkeley Segmentation *** IPcNN method achieves a better segmentation result without training,providing a new solution for the real-time transmission of image semantic information.

关键词： Internet of things(IoT) Semantic information Real-time application Improved pulse coupled neural network Image segmentation

Optimization of a photovoltaic-battery system using deep reinforcement learning and load forecasting

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Energy and AI 2024年第2期16卷 168-183页

作者： António corte Real G.Pontes Luz J.m.c.Sousa m.c.Brito S.m.Vieira IDmEc Instituto Superior TécnicoUniversidade de LisboaLisboa1049-001Portugal Instituto Dom Luiz Faculdade de CiênciasUniversidade de LisboaCampo Grande1749-016LisboaPortugal

Home Energy management Systems(HEmS)are increasingly relevant for demand-side management at the residential level by collecting data(energy,weather,electricity prices)and controlling home appliances or storage *** control can be performed with classical models that find optimal solutions,with high real-time computational cost,or data-driven approaches,like Reinforcement Learning,that find good and flexible solutions,but depend on the availability of load and generation data and demand high computational resources for *** this work,a novel HEmS is proposed for the optimization of an electric battery operation in a real,online and data-driven environment that integrates state-of-the-art load forecasting combining cNN and LSTm neural networks to increase the robustness of *** Reinforcement Learning agents are trained with different algorithms(Double DQN,Dueling DQN,Rainbow and Proximal Policy Optimization)in order to minimize the cost of electricity purchase and to maximize photovoltaic self-consumption for a PV-Battery residential *** show that the best Reinforcement Learning agent achieves a 35%reduction in total cost when compared with an optimization-based agent.

关键词： Energy management system Deep reinforcement learning Demand-side management Load forecasting Deep learning Energy storage systems