Drishti Paint 3.2:a new open-source tool for both 2D and 3D segmentation

X-ray computed tomography(CT)has been an important technology in paleontology for several decades.It helps researchers to acquire detailed anatomical structures of fossils non-destructively.Despite its widespread application,developing an efficient and user-friendly method for segmenting CT data continues to be a formidable challenge in the field.Most CT data segmentation software operates on 2D interfaces,which limits flexibility for real-time adjustments in 3D segmentation.Here,we introduce Curves Mode in Drishti Paint 3.2,an open-source tool for CT data segmentation.Drishti Paint 3.2 allows users to manually or semi-automatically segment the CT data in both 2D and 3D environments,providing a novel solution for revisualizing CT data in paleontological studies.

Enhancing MXene-based supercapacitors:Role of synthesis and 3D architectures

MXene has been the limelight for studies on electrode active materials,aiming at developing supercapacitors with boosted energy density to meet the emerging influx of wearable and portable electronic devices.Despite its various desirable properties including intrinsic flexibility,high specific surface area,excellent metallic conductivity and unique abundance of surface functionalities,its full potential for electrochemical performance is hindered by the notorious restacking phenomenon of MXene nanosheets.Ascribed to its two-dimensional(2D)nature and surface functional groups,inevitable Van der Waals interactions drive the agglomeration of nanosheets,ultimately reducing the exposure of electrochemically active sites to the electrolyte,as well as severely lengthening electrolyte ion transport pathways.As a result,energy and power density deteriorate,limiting the application versatility of MXene-based supercapacitors.Constructing 3D architectures using 2D nanosheets presents as a straightforward yet ingenious approach to mitigate the fatal flaws of MXene.However,the sheer number of distinct methodologies reported,thus far,calls for a systematic review that unravels the rationale behind such 3D MXene structural designs.Herein,this review aims to serve this purpose while also scrutinizing the structure–property relationship to correlate such structural modifications to their ensuing electrochemical performance enhancements.Besides,the physicochemical properties of MXene play fundamental roles in determining the effective charge storage capabilities of 3D MXene-based electrodes.This largely depends on different MXene synthesis techniques and synthesis condition variations,hence,elucidated in this review as well.Lastly,the challenges and perspectives for achieving viable commercialization of MXene-based supercapacitor electrodes are highlighted.

3D and 2D topographic correction to estimated geothermal gradient from the base of gas hydrate stability zone in the Andaman Forearc Basin

Methane gas hydrate related bottom-simulating reflectors(BSRs)are imaged based on the in-line and cross-line multi-channel seismic(MCS)data from the Andaman Forearc Basin.The depth of the BSR depends on pressure and temperature and pore water salinity.With these assumptions,the BSR depth can be used to estimate the geothermal gradient(GTG)based on the availability of in-situ temperature measurements.This calculation is done assuming a 1D conductive model based on available in-situ temperature measurement at site NGHP-01-17 in the study area.However,in the presence of seafloor topography,the conductive temperature field in the subsurface is affected by lateral refraction of heat,which focuses heat in topographic lows and away from topographic highs.The 1D estimate of GTG in the Andaman Forearc Basin has been validated by drilling results from the NGHP-01 expedition.2D analytic modeling to estimate the effects of topography is performed earlier along selected seismic profiles in the study area.The study extended to estimate the effect of topography in 3D using a numerical model.The corrected GTG data allow us to determine GTG values free of topographic effect.The difference between the estimated GTG and values corrected for the 3D topographic effect varies up to~5℃/km.These conclude that the topographic correction is relatively small compared to other uncertainties in the 1D model and that apparent GTG determined with the 1D model captures the major features,although the correction is needed prior to interpreting subtle features of the derived GTG maps.

“Blocking and rebalance”mechanism-guided design strategies of bimetallic doped 2D a-phosphorus carbide as efficient catalysts for N_(2) electroreduction

Compared to single atom catalysts(SACs),the introduction of dual atom catalysts(DACs)has a significantly positive effect on improving the efficiency in the electrocatalytic nitrogen reduction reaction(NRR)which provides an environmental alternative to the Haber-Bosch process.However,the research on the mechanism and strategy of designing bimetallic combinations for better performance is still in its early stages.Herein,based on"blocking and rebalance"mechanism,45 combinations of bimetallic pair dopedα-phosphorus carbide(TM_(A)TM_(B)@PC)are investigated as efficient NRR catalysts through density functional theory and machine learning method.After a multi-step screening,the combinations of TiV,TiFe,MnMo,and FeW exhibit highly efficient catalytic performance with significantly lower limiting potentials(-0.17,-0.18,-0.14,and-0.30 V,respectively).Excitingly,the limiting potential for CrMo and CrW combinations is 0 V,which are considered to be extremely suitable for the NRR process.The mechanism of"blocking and rebalance"is revealed by the exploration of charge transfer for phosphorus atoms in electron blocking areas.Moreover,the descriptorφis proposed with machine learning,which provides design strategies and accurate prediction for finding efficient DACs.This work not only offers promising catalysts TM_(A)TM_(B)@PC for NRR process but also provides design strategies by presenting the descriptorφ.

Efficient single-pixel imaging encrypted transmission based on 3D Arnold transformation

Single-pixel imaging(SPI)can transform 2D or 3D image data into 1D light signals,which offers promising prospects for image compression and transmission.However,during data communication these light signals in public channels will easily draw the attention of eavesdroppers.Here,we introduce an efficient encryption method for SPI data transmission that uses the 3D Arnold transformation to directly disrupt 1D single-pixel light signals and utilizes the elliptic curve encryption algorithm for key transmission.This encryption scheme immediately employs Hadamard patterns to illuminate the scene and then utilizes the 3D Arnold transformation to permutate the 1D light signal of single-pixel detection.Then the transformation parameters serve as the secret key,while the security of key exchange is guaranteed by an elliptic curve-based key exchange mechanism.Compared with existing encryption schemes,both computer simulations and optical experiments have been conducted to demonstrate that the proposed technique not only enhances the security of encryption but also eliminates the need for complicated pattern scrambling rules.Additionally,this approach solves the problem of secure key transmission,thus ensuring the security of information and the quality of the decrypted images.

Enriched Constant Elements in the Boundary Element Method for Solving 2D Acoustic Problems at Higher Frequencies

The boundary element method(BEM)is a popular method for solving acoustic wave propagation problems,especially those in exterior domains,owing to its ease in handling radiation conditions at infinity.However,BEM models must meet the requirement of 6–10 elements per wavelength,using the conventional constant,linear,or quadratic elements.Therefore,a large storage size of memory and long solution time are often needed in solving higher-frequency problems.In this work,we propose two new types of enriched elements based on conventional constant boundary elements to improve the computational efficiency of the 2D acoustic BEM.The first one uses a plane wave expansion,which can be used to model scattering problems.The second one uses a special plane wave expansion,which can be used tomodel radiation problems.Five examples are investigated to showthe advantages of the enriched elements.Compared with the conventional constant elements,the new enriched elements can deliver results with the same accuracy and in less computational time.This improvement in the computational efficiency is more evident at higher frequencies(with the nondimensional wave numbers exceeding 100).The paper concludes with the potential of our proposed enriched elements and plans for their further improvement.

Remote sensing image encryption algorithm based on novel hyperchaos and an elliptic curve cryptosystem

Remote sensing images carry crucial ground information,often involving the spatial distribution and spatiotemporal changes of surface elements.To safeguard this sensitive data,image encryption technology is essential.In this paper,a novel Fibonacci sine exponential map is designed,the hyperchaotic performance of which is particularly suitable for image encryption algorithms.An encryption algorithm tailored for handling the multi-band attributes of remote sensing images is proposed.The algorithm combines a three-dimensional synchronized scrambled diffusion operation with chaos to efficiently encrypt multiple images.Moreover,the keys are processed using an elliptic curve cryptosystem,eliminating the need for an additional channel to transmit the keys,thus enhancing security.Experimental results and algorithm analysis demonstrate that the algorithm offers strong security and high efficiency,making it suitable for remote sensing image encryption tasks.

Enhancing Human Action Recognition with Adaptive Hybrid Deep Attentive Networks and Archerfish Optimization

In recent years,wearable devices-based Human Activity Recognition(HAR)models have received significant attention.Previously developed HAR models use hand-crafted features to recognize human activities,leading to the extraction of basic features.The images captured by wearable sensors contain advanced features,allowing them to be analyzed by deep learning algorithms to enhance the detection and recognition of human actions.Poor lighting and limited sensor capabilities can impact data quality,making the recognition of human actions a challenging task.The unimodal-based HAR approaches are not suitable in a real-time environment.Therefore,an updated HAR model is developed using multiple types of data and an advanced deep-learning approach.Firstly,the required signals and sensor data are accumulated from the standard databases.From these signals,the wave features are retrieved.Then the extracted wave features and sensor data are given as the input to recognize the human activity.An Adaptive Hybrid Deep Attentive Network(AHDAN)is developed by incorporating a“1D Convolutional Neural Network(1DCNN)”with a“Gated Recurrent Unit(GRU)”for the human activity recognition process.Additionally,the Enhanced Archerfish Hunting Optimizer(EAHO)is suggested to fine-tune the network parameters for enhancing the recognition process.An experimental evaluation is performed on various deep learning networks and heuristic algorithms to confirm the effectiveness of the proposed HAR model.The EAHO-based HAR model outperforms traditional deep learning networks with an accuracy of 95.36,95.25 for recall,95.48 for specificity,and 95.47 for precision,respectively.The result proved that the developed model is effective in recognizing human action by taking less time.Additionally,it reduces the computation complexity and overfitting issue through using an optimization approach.

Case Report: Rhupus (The Association of Systemic Lupus Erythematosus and Rheumatoid Arthritis): About 2 Cases

Introduction: The association of systemic lupus erythematosus and rheumatoid arthritis (rhupus) is a rare clinical condition. Throughout the world, 287 cases of Rhupus have been described. We report two new observations of two patients who presented predominantly distal erosive polyarthritis with positive anti-Sm antibodies in one case and SmRNP in the other case. Observations: Case 1: 37 years old patient, with a recent diagnosis of pulmonary tuberculosis. She has since 8 months an inflammatory, bilaterally and symmetrical polyarthralgia without deformation or ankylosing synovitis, associated with malar erythema without other abnormalities. Immunological tests showed: positive Rheumatoid factor at 158 IU/ml, positive Anti-CCP at 550 IU/ml, and positivity of antinuclear at 1/1280 nuclear fluorescence with a strong presence of anti-Sm >8 IU/ml. The diagnosis of rhupus was concluded, without serious visceral involvement. Case 2: A 28-year-old patient, married with 3 children, with bilateral, symmetrical, deforming and chronic polyarthritis affecting large and small joints, which had been evolving for over 5 years without cutaneous abnormality associated. Paraclinical investigations showed: a biological inflammatory syndrome. Immunology was positive, with rheumatoid factors at 78 IU/ml, anti-CCP at 561 IU/ml, antinuclear antibodies at 1/1280 with positive anti-SmRNP and anti-SSA/Ro52, and a positive direct Coombs test. Joint ultrasound revealed tenosynovitis of the extensors and common flexors of the fingers, erosions and synovitis of multiple PPIs. The diagnosis of rhupus was based on the presence of 10 ACR criteria for RA and 8 ACR/EULAR 2019 criteria for SLE. Conclusion: Rheumatoid arthritis is a rare autoimmune disease combining features of both systemic lupus erythematosus and rheumatoid arthritis in the same patient, often sequentially. Despite a growing number of case reports and series, a consensus on the classification of SLE arthritis is still lacking, and diagnostic criteria for rhupus do not exist. These cases of rhupus must be recognized, as the vital and/or functional prognosis may be different from SLE alone or isolated RA.

Application of Digital Technology in Road and Bridge Design

With the development and progress of science and technology,road and bridge design has experienced rapid development,from the initial manual drawing design to the popularity of Computer-Aided Design(CAD),and then to today’s digital software design era.Early designers relied on hand-drawn paper design forms which was time-consuming and error-prone.Digital support for road and bridge design not only saves the design time but the design quality has also achieved a qualitative leap.This paper engages in the application of digital technology in road and bridge design,to provide technical reference for China’s road and bridge engineering design units,to promote the popularity of Civil3D and other advanced design software in the field of engineering design and development,ultimately contributing to the sustainable development of China’s road and bridge engineering.

Detection of Burned Areas through Spectral Indices Analysis of Sentinel-2A Satellite Images in the Abokouamékro Wildlife Reserve (Central, Côte D’Ivoire)

In Côte d’Ivoire, the recurring and unregulated use of bushfires, which cause ecological damage, presents a pressing concern for the custodians of protected areas. This study aims to enhance our comprehension of the dynamics of burnt areas within the Abokouamékro Wildlife Reserve (AWR) by employing the analysis of spectral indices derived from satellite imagery. The research methodology began with the calculation of mean indices and their corresponding spectral sub-indices, including NDVI, SAVI, NDWI, NDMI, BAI, NBR, TCW, TCG, and TCB, utilizing data from the Sentinel-2A satellite image dated January 17, 2022. Subsequently, a fuzzy classification model was applied to these various indices and sub-indices, guided by the degree of membership α, with the goal of effectively distinguishing between burned and unburned areas. Following the classification, the accuracies of the classified indices and sub-indices were validated using the coordinates of 100 data points collected within the AWR through GPS technology. The results revealed that the overall accuracy of all indices and sub-indices declines as the degree of membership α decreases from 1 to 0. Among the mean spectral indices, NDVI-mean, SAVI-mean, NDMI-mean exhibited the highest overall accuracies, achieving 97%, 95%, and 90%, respectively. These results closely mirrored those obtained by sub-indices using band 8 (NDVI-B8, SAVI-B8, and NDMI-B8), which yield respective overall accuracies of 93%, 92%, and 89%. At a degree of membership α = 1, the estimated burned areas for the most effective indices encompassed 2144.38 hectares for NDVI-mean, 1932.14 hectares for mean SAVI-mean, and 4947.13 hectares for mean NDMI-mean. A prospective approach involving the amalgamation of these three indices could have the potential to yield improved outcomes. This study could be a substantial contribution to the discrimination of bushfires in Côte d’Ivoire.

Highly Efficient Aligned Ion‑Conducting Network and Interface Chemistries for Depolarized All‑Solid‑State Lithium Metal Batteries

Improving the long-term cycling stability and energy density of all-solid-state lithium(Li)-metal batteries(ASSLMBs)at room temperature is a severe challenge because of the notorious solid–solid interfacial contact loss and sluggish ion transport.Solid electrolytes are generally studied as two-dimensional(2D)structures with planar interfaces,showing limited interfacial contact and further resulting in unstable Li/electrolyte and cathode/electrolyte interfaces.Herein,three-dimensional(3D)architecturally designed composite solid electrolytes are developed with independently controlled structural factors using 3D printing processing and post-curing treatment.Multiple-type electrolyte films with vertical-aligned micro-pillar(p-3DSE)and spiral(s-3DSE)structures are rationally designed and developed,which can be employed for both Li metal anode and cathode in terms of accelerating the Li+transport within electrodes and reinforcing the interfacial adhesion.The printed p-3DSE delivers robust long-term cycle life of up to 2600 cycles and a high critical current density of 1.92 mA cm^(−2).The optimized electrolyte structure could lead to ASSLMBs with a superior full-cell areal capacity of 2.75 mAh cm^(−2)(LFP)and 3.92 mAh cm^(−2)(NCM811).This unique design provides enhancements for both anode and cathode electrodes,thereby alleviating interfacial degradation induced by dendrite growth and contact loss.The approach in this study opens a new design strategy for advanced composite solid polymer electrolytes in ASSLMBs operating under high rates/capacities and room temperature.

Silent information regulator sirtuin 1 ameliorates acute liver failure via the p53/glutathione peroxidase 4/gasdermin D axis

BACKGROUND Acute liver failure(ALF)has a high mortality with widespread hepatocyte death involving ferroptosis and pyroptosis.The silent information regulator sirtuin 1(SIRT1)-mediated deacetylation affects multiple biological processes,including cellular senescence,apoptosis,sugar and lipid metabolism,oxidative stress,and inflammation.AIM To investigate the association between ferroptosis and pyroptosis and the upstream regulatory mechanisms.METHODS This study included 30 patients with ALF and 30 healthy individuals who underwent serum alanine aminotransferase(ALT)and aspartate aminotransferase(AST)testing.C57BL/6 mice were also intraperitoneally pretreated with SIRT1,p53,or glutathione peroxidase 4(GPX4)inducers and inhibitors and injected with lipopolysaccharide(LPS)/D-galactosamine(D-GalN)to induce ALF.Gasdermin D(GSDMD)^(-/-)mice were used as an experimental group.Histological changes in liver tissue were monitored by hematoxylin and eosin staining.ALT,AST,glutathione,reactive oxygen species,and iron levels were measured using commercial kits.Ferroptosis-and pyroptosis-related protein and mRNA expression was detected by western blot and quantitative real-time polymerase chain reaction.SIRT1,p53,and GSDMD were assessed by immunofluorescence analysis.RESULTS Serum AST and ALT levels were elevated in patients with ALF.SIRT1,solute carrier family 7a member 11(SLC7A11),and GPX4 protein expression was decreased and acetylated p5,p53,GSDMD,and acyl-CoA synthetase long-chain family member 4(ACSL4)protein levels were elevated in human ALF liver tissue.In the p53 and ferroptosis inhibitor-treated and GSDMD^(-/-)groups,serum interleukin(IL)-1β,tumour necrosis factor alpha,IL-6,IL-2 and C-C motif ligand 2 levels were decreased and hepatic impairment was mitigated.In mice with GSDMD knockout,p53 was reduced,GPX4 was increased,and ferroptotic events(depletion of SLC7A11,elevation of ACSL4,and iron accumulation)were detected.In vitro,knockdown of p53 and overexpression of GPX4 reduced AST and ALT levels,the cytostatic rate,and GSDMD expression,restoring SLC7A11 depletion.Moreover,SIRT1 agonist and overexpression of SIRT1 alleviated acute liver injury and decreased iron deposition compared with results in the model group,accompanied by reduced p53,GSDMD,and ACSL4,and increased SLC7A11 and GPX4.Inactivation of SIRT1 exacerbated ferroptotic and pyroptotic cell death and aggravated liver injury in LPS/D-GalNinduced in vitro and in vivo models.CONCLUSION SIRT1 activation attenuates LPS/D-GalN-induced ferroptosis and pyroptosis by inhibiting the p53/GPX4/GSDMD signaling pathway in ALF.

Automatic modulation recognition of radio fuzes using a DR2D-based adaptive denoising method and textural feature extraction

The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-noise ratio(SNR)of such environments is usually low,which makes it difficult to implement accurate recognition of radio fuzes.To solve the above problem,a radio fuze automatic modulation recognition(AMR)method for low-SNR environments is proposed.First,an adaptive denoising algorithm based on data rearrangement and the two-dimensional(2D)fast Fourier transform(FFT)(DR2D)is used to reduce the noise of the intercepted radio fuze intermediate frequency(IF)signal.Then,the textural features of the denoised IF signal rearranged data matrix are extracted from the statistical indicator vectors of gray-level cooccurrence matrices(GLCMs),and support vector machines(SVMs)are used for classification.The DR2D-based adaptive denoising algorithm achieves an average correlation coefficient of more than 0.76 for ten fuze types under SNRs of-10 d B and above,which is higher than that of other typical algorithms.The trained SVM classification model achieves an average recognition accuracy of more than 96%on seven modulation types and recognition accuracies of more than 94%on each modulation type under SNRs of-12 d B and above,which represents a good AMR performance of radio fuzes under low SNRs.

Jetting-based bioprinting:process,dispense physics,and applications

Jetting-based bioprinting facilitates contactless drop-on-demand deposition of subnanoliter droplets at well-defined positions to control the spatial arrangement of cells,growth factors,drugs,and biomaterials in a highly automated layer-by-layer fabrication approach.Due to its immense versatility,jetting-based bioprinting has been used for various applications,including tissue engineering and regenerative medicine,wound healing,and drug development.A lack of in-depth understanding exists in the processes that occur during jetting-based bioprinting.This review paper will comprehensively discuss the physical considerations for bioinks and printing conditions used in jetting-based bioprinting.We first present an overview of different jetting-based bioprinting techniques such as inkjet bioprinting,laser-induced forward transfer bioprinting,electrohydrodynamic jet bioprinting,acoustic bioprinting and microvalve bioprinting.Next,we provide an in-depth discussion of various considerations for bioink formulation relating to cell deposition,print chamber design,droplet formation and droplet impact.Finally,we highlight recent accomplishments in jetting-based bioprinting.We present the advantages and challenges of each method,discuss considerations relating to cell viability and protein stability,and conclude by providing insights into future directions of jetting-based bioprinting.

MXene-Based Elastomer Mimetic StretchableSensors: Design, Properties, and Applications

Flexible sensors based on MXene-polymer composites are highly prospective for next-generation wearable electronics used in human-machine interfaces.One of the motivating factors behind the progress of flexible sensors is the steady arrival of new conductive materials.MXenes,a new family of 2D nanomaterials,have been draw-ing attention since the last decade due to their high electronic conduc-tivity,processability,mechanical robustness and chemical tunability.In this review,we encompass the fabrication of MXene-based polymeric nanocomposites,their structure-property relationship,and applications in the flexible sensor domain.Moreover,our discussion is not only lim-ited to sensor design,their mechanism,and various modes of sensing platform,but also their future perspective and market throughout the world.With our article,we intend to fortify the bond between flexible matrices and MXenes thus promoting the swift advancement of flexible MXene-sensors for wearable technologies.

Vitamin D,selenium,and antidiabetic drugs in the treatment of type 2 diabetes mellitus with Hashimoto's thyroiditis

BACKGROUND Diabetes and thyroiditis are closely related.They occur in combination and cause significant damage to the body.There is no clear treatment for type-2 diabetes mellitus(T2DM)with Hashimoto's thyroiditis(HT).While single symptomatic drug treatment of the two diseases is less effective,combined drug treatment may improve efficacy.AIM To investigate the effect of a combination of vitamin D,selenium,and hypoglycemic agents in T2DM with HT.METHODS This retrospective study included 150 patients with T2DM and HT treated at The Central Hospital of Shaoyang from March 2020 to February 2023.Fifty patients were assigned to the control group,test group A,and test group B according to different treatment methods.The control group received low-iodine diet guidance and hypoglycemic drug treatment.Test group A received the control treatment plus vitamin D treatment.Test group B received the group A treatment plus selenium.Blood levels of markers of thyroid function[free T3(FT3),thyroid stimulating hormone(TSH),free T4(FT4)],autoantibodies[thyroid peroxidase antibody(TPOAB)and thyroid globulin antibody(TGAB)],blood lipid index[low-density lipoprotein cholesterol(LDL-C),total cholesterol(TC),triacylglycerol(TG)],blood glucose index[fasting blood glucose(FBG),and hemoglobin A1c(HbA1c)]were measured pre-treatment and 3 and 6 months after treatment.The relationships between serum 25-hydroxyvitamin D3[25(OH)D3]level and each of these indices were analyzed.RESULTS The levels of 25(OH)D3,FT3,FT4,and LDL-C increased in the order of the control group,test group A,and test group B(all P<0.05).The TPOAB,TGAB,TC,TG,FBG,HbA1c,and TSH levels increased in the order of test groups B,A,and the control group(all P<0.05).All the above indices were compared after 3 and 6 months of treatment.Pre-treatment,there was no divergence in serum 25(OH)D3 level,thyroid function-related indexes,autoantibodies level,blood glucose,and blood lipid index between the control group,test groups A and B(all P>0.05).The 25(OH)D3 levels in test groups A and B were negatively correlated with FT4 and TGAB(all P<0.05).CONCLUSION The combination drug treatment for T2DM with HT significantly improved thyroid function,autoantibody,and blood glucose and lipid levels.

Two-dimensional MOF-based materials:Preparations and applications as electrodes in Li-ion batteries

Two-dimensional(2D)metal-organic frameworks(MOFs)are rapidly emerging as a unique class of mushrooming family of 2D materials offering distinctive features,such as hierarchical porosity,extensive surface area,easily available active sites,and versatile,adaptable structures.These promising characteristics have positioned them as highly appealing alternatives for a wide range of applications in energy storage technologies,including lithium batteries.Nevertheless,the poor conductivity and limited stability of 2D MOFs have limited their real applications in electrochemical energy storage.These limitations have therefore warranted ongoing research to enhance the performance of 2D MOFs.Given the significance of 2D MOF-based materials as an emerging class of advanced materials,a multitude of strategy has been devised to address these challenges such as synthesizing 2D conductive MOFs and derivatives along with 2D MOF hybridization.One promising approach involves the use of 2D MOF derivatives,including transition metal oxides,which due to their abundant unsatu rated active metal sites and shorter diffusion paths,offer superior electrochemical performance.Additionally,by combining pristine 2D MOFs with other materials,hybrid 2D MOF materials can be created.These hybrids,with their enhanced stability and conductivity,can be directly utilized as active materials in lithium batteries.In the present review,we categorize 2D MOF-based materials into three distinct groups:pristine 2D MOFs,2D MOFderived materials,and 2D MOF hybrid materials.The synthesis methods for each group,along with their specific applications as electrode materials in lithium-ion batteries,are discussed in detail.This comprehensive review provides insights into the potential of 2D MOFs while highlighting the opportunities and challenges that are present in this evolving field.

Exceptional Performance of 3D Additive Manufactured NiFe Phosphite Oxyhydroxide Hollow Tubular Lattice Plastic Electrode for Large-Current-Density Water Oxidization

In this article,we report a 3D NiFe phosphite oxyhydroxide plastic electrode using high-resolution digital light processing(DLP)3D-printing technology via induced chemical deposition method.The as-prepared 3D plastic electrode exhibits no template requirement,freedom design,low-cost,robust,anticorrosion,lightweight,and micro-nano porous characteristics.It can be drawn to the conclusion that highly oriented open-porous 3D geometry structure will be beneficial for improving surface catalytic active area,wetting performance,and reaction–diffusion dynamics of plastic electrodes for oxygen evolution reaction(OER)catalysis process.Density functional theory(DFT)calculation interprets the origin of high activity of NiFe(PO_(3))O(OH)and demonstrates that the implantation of the–PO_(3)can effectively bind the 3d orbital of Ni in NiFe(PO_(3))O(OH),lead to the weak adsorption of intermediate,make electron more active to improve the conductivity,thereby lowing the transform free energy of*O to*OOH.The water oxidization performance of as-prepared 3D NiFe(PO_(3))O(OH)hollow tubular(HT)lattice plastic electrode has almost reached the state-of-the-art level compared with the as-reported large-current-density catalysts or 3D additive manufactured plastic/metal-based electrodes,especially for high current OER electrodes.This work breaks through the bottleneck that plagues the performance improvement of low-cost high-current electrodes.

Spheroid construction strategies and application in 3D bioprinting

Tissue engineering has been striving toward designing and producing natural and functional human tissues.Cells are the fundamental building blocks of tissues.Compared with traditional two-dimensional cultured cells,cell spheres are threedimensional(3D)structures that can naturally form complex cell–cell and cell–matrix interactions.This structure is close to the natural environment of cells in living organisms.In addition to being used in disease modeling and drug screening,spheroids have significant potential in tissue regeneration.The 3D bioprinting is an advanced biofabrication technique.It accurately deposits bioinks into predesigned 3D shapes to create complex tissue structures.Although 3D bioprinting is efficient,the time required for cells to develop into complex tissue structures can be lengthy.The 3D bioprinting of spheroids significantly reduces the time required for their development into large tissues/organs during later cultivation stages by printing them with high cell density.Combining spheroid fabrication and bioprinting technology should provide a new solution to many problems in regenerative medicine.This paper systematically elaborates and analyzes the spheroid fabrication methods and 3D bioprinting strategies by introducing spheroids as building blocks.Finally,we present the primary challenges faced by spheroid fabrication and 3D bioprinting with future requirements and some recommendations.