Efficient flexible dye-sensitized solar cells from rear illumination based on different morphologies of titanium dioxide photoanode

The TiO_(2) with nanoparticles(NPs),nanowires(NWs),nanorods(NRs)and nanotubes(NTs)structures were prepared by using a in-situ hydrothermal technique,and then proposed as a photoanode for flexible dye-sensitized solar cell(FDSSC).The influences of the morphology of TiO_(2) on the photovoltaic performances of FDSSCs were investigated.Under rear illumination of 100 mW·cm^(−2),the power conversion efficiencies of FDSSCs achieved 6.96%,7.36%,7.65%,and 7.83%with the TiO_(2) photoanodes of NPs,NWs,NRs,and NTs and PEDOT counter electrode.The FDSSCs based on TiO_(2) NRs and NTs photoanodes have higher short circuit current densities and power conversion efficiencies than that of the others.The enhanced power conversion efficiency is responsible for their nanotubes and rod-shaped ordered structures,which are more beneficial to transmission of electron and hole in semiconductor compared to the TiO_(2) nanoparticles and nanowires disordered structure.

Guidelines on clinical research evaluation of artificial intelligence in ophthalmology(2023)

With the upsurge of artificial intelligence(AI)technology in the medical field,its application in ophthalmology has become a cutting-edge research field.Notably,machine learning techniques have shown remarkable achievements in diagnosing,intervening,and predicting ophthalmic diseases.To meet the requirements of clinical research and fit the actual progress of clinical diagnosis and treatment of ophthalmic AI,the Ophthalmic Imaging and Intelligent Medicine Branch and the Intelligent Medicine Committee of Chinese Medicine Education Association organized experts to integrate recent evaluation reports of clinical AI research at home and abroad and formed a guideline on clinical research evaluation of AI in ophthalmology after several rounds of discussion and modification.The main content includes the background and method of developing this guideline,an introduction to international guidelines on the clinical research evaluation of AI,and the evaluation methods of clinical ophthalmic AI models.This guideline introduces general evaluation methods of clinical ophthalmic AI research,evaluation methods of clinical ophthalmic AI models,and commonly-used indices and formulae for clinical ophthalmic AI model evaluation in detail,and amply elaborates the evaluation methods of clinical ophthalmic AI trials.This guideline aims to provide guidance and norms for clinical researchers of ophthalmic AI,promote the development of regularization and standardization,and further improve the overall level of clinical ophthalmic AI research evaluations.

The effect of gravity on self-similarity of Worthington jet after water entry of a two-dimensional wedge

The effect of gravity on the self-similarity of jet shape at late stage of Worthington jet development is investigated by experiment in the study.In addition,the particle image velocimetry(PIV)method is introduced to analyze the development of flow field.There is a linear scaling regarding the axial velocity of the jet and the scaling coefficient increases with the Froude number.

Engineering Multi‑field‑coupled Synergistic Ion Transport System Based on the Heterogeneous Nanofluidic Membrane for High‑Efficient Lithium Extraction

The global carbon neutrality strategy brings a wave of rechargeable lithium‐ion batteries technique development and induces an ever-growing consumption and demand for lithium(Li).Among all the Li exploitation,extracting Li from spent LIBs would be a strategic and perspective approach,especially with the low energy consumption and eco-friendly membrane separation method.However,current membrane separation systems mainly focus on monotonous membrane design and structure optimization,and rarely further consider the coordination of inherent structure and applied external field,resulting in limited ion transport.Here,we propose a heterogeneous nanofluidic membrane as a platform for coupling multi-external fields(i.e.,lightinduced heat,electrical,and concentration gradient fields)to construct the multi-field-coupled synergistic ion transport system(MSITS)for Li-ion extraction from spent LIBs.The Li flux of the MSITS reaches 367.4 mmol m^(−2)h^(−1),even higher than the sum flux of those applied individual fields,reflecting synergistic enhancement for ion transport of the multi-field-coupled effect.Benefiting from the adaptation of membrane structure and multi-external fields,the proposed system exhibits ultrahigh selectivity with a Li^(+)/Co^(2+)factor of 216,412,outperforming previous reports.MSITS based on nanofluidic membrane proves to be a promising ion transport strategy,as it could accelerate ion transmembrane transport and alleviate the ion concentration polarization effect.This work demonstrated a collaborative system equipped with an optimized membrane for high-efficient Li extraction,providing an expanded strategy to investigate the other membrane-based applications of their common similarities in core concepts.

Smart palm-size optofluidic hematology analyzer for automated imaging-based leukocyte concentration detection

A critical function of flow cytometry is to count the concentration of blood cells,which helps in the diagnosis of certain diseases.However,the bulky nature of commercial flow cytometers makes such tests only available in hospitals or laboratories,hindering the spread of point-of-care testing(POCT),especially in underdeveloped areas.Here,we propose a smart Palm-size Optofluidic Hematology Analyzer based on a miniature fluorescence microscope and a microfluidic platform to lighten the device to improve its portability.This gadget has a dimension of 35×30×80 mm and a mass of 39 g,less than 5%of the weight of commercially available flow cytometers.Additionally,automatic leukocyte concentration detection has been realized through the integration of image processing and leukocyte counting algorithms.We compared the leukocyte concentration measurement between our approach and a hemocytometer using the Passing-Bablok analysis and achieved a correlation coefficient of 0.979.Through Bland-Altman analysis,we obtained the relationship between their differences and mean measurement values and established 95%limits of agreement,ranging from−0.93×10^(3)to 0.94×10^(3)cells/μL.We anticipate that this device can be used widely for monitoring and treating diseases such as HIV and tumors beyond hospitals.

A theoretical insight about co-pyrolysis reaction of natural gas and coal

The co-pyrolysis of natural gas and coal is a promising way for the production of acetylene due to its high efficiency for energy and hydrogen utilization.This work investigated the thermodynamics for the copyrolysis reaction of natural gas and coal using density functional theory.The favorable reaction conditions are presented in the form of phase diagrams.The calculation results show that the extra amount of methane may benefit the production of acetylene in the co-pyrolysis reaction,and the C/H ratio of 1:1,temperature around 3000 K and pressure at 0.1 MPa are most favorable.The results would provide basic data for related industrial process for the production of acetylene.

Trade-offs between ion-conducting and mechanical properties: The case of polyacrylate electrolytes

Polymer electrolytes(PEs)have been long recognized as the key materials to enable energy-dense batteries and render flexible energy devices practically viable,owing to their chemical and mechanical reliability.However,much of their promise is yet to be realized.The roomtemperature ion conductivity of existing PEs still falls short of the implementation criterion of 10^(-4) S cm^(-1) on the promise of acceptable mechanical properties,thereby precluding their practical application.The twin but inversely related duties of polymers,that is,functioning as both an ion-conducting medium and a structural backbone,underlie this issue but are less elucidated systematically.The polyacrylate(PA)family is among promising polymer matrices on account of ester polarity,electrode compatibility,chemical tunability,and mechanical durability.The extensive applicability of PA in plasticized gels,dry solids,and emerging composites makes PA-based PEs representative to illustrate the trade-off between ion conduction and mechanical strength.We herein seek to outline the stated long-standing conflict exemplified by PA-based PEs,focusing on crucial strategies toward balancing and reconciling the two mutually exclusive properties,with the intention of offering designing guidelines for next-generation PEs.

Non-invasive assessment for intratumoural distribution of interstitial fluid flow

Interstitial fluid plays a vital role in drug delivery and tumour treatment.However,few non-invasive measurement methods are available for measuring low-velocity biological fluid flow.Therefore,this study aimed to develop a novel technology called interstitial flow velocity-MRI.The interstitial flow velocity-MRI sequence consists of a dual inversion recovery preparation and an improved stimulated echo sequence(ISTE)combined with phase-contrast MRI.A homemade flow phantom was used to assess the feasibility and sensitivity of interstitial flow velocity-MRI.In addition,xenografts of female BALB/c mouse models of 4T1 breast cancer administered losartan(40 mg/kg)or saline(n?6)were subjected to imaging on a 7.0 T scanner to assess the in vivo interstitial fluid flow velocity.The results showed a significant correlation(P<0.001)between the theoretical velocities and velocities measured using the flow phantom.Interstitial flow velocity-MRI could detect a velocity as low as 10.21±2.65 mm/s with a spatial resolution of 0.313 mm.The losartan group had a lower mean interstitial fluid velocity than the control group(85±16 vs 113±24 mm/s).In addition,compared to the saline treatment,losartan treatment reduced the proportion of collagen fibres by 10%and 12%in the Masson and Sirius red staining groups,respectively.Interstitial flow velocity-MRI has the potential to determine interstitial fluid flow velocity non-invasively and exhibits an intuitive velocity map.

Research on Facial Fatigue Detection of Drivers with Multi-feature Fusion

In order to solve the shortcomings of current fatigue detection methods such as low accuracy or poor real-time performance,a fatigue detection method based on multi-feature fusion is proposed.Firstly,the HOG face detection algorithm and KCF target tracking algorithm are integrated and deformable convolutional neural network is introduced to identify the state of extracted eyes and mouth,fast track the detected faces and extract continuous and stable target faces for more efficient extraction.Then the head pose algorithm is introduced to detect the driver’s head in real time and obtain the driver’s head state information.Finally,a multi-feature fusion fatigue detection method is proposed based on the state of the eyes,mouth and head.According to the experimental results,the proposed method can detect the driver’s fatigue state in real time with high accuracy and good robustness compared with the current fatigue detection algorithms.

A Spectral Convolutional Neural Network Model Based on Adaptive Fick’s Law for Hyperspectral Image Classification

Hyperspectral image classification stands as a pivotal task within the field of remote sensing,yet achieving highprecision classification remains a significant challenge.In response to this challenge,a Spectral Convolutional Neural Network model based on Adaptive Fick’s Law Algorithm(AFLA-SCNN)is proposed.The Adaptive Fick’s Law Algorithm(AFLA)constitutes a novel metaheuristic algorithm introduced herein,encompassing three new strategies:Adaptive weight factor,Gaussian mutation,and probability update policy.With adaptive weight factor,the algorithmcan adjust theweights according to the change in the number of iterations to improve the performance of the algorithm.Gaussianmutation helps the algorithm avoid falling into local optimal solutions and improves the searchability of the algorithm.The probability update strategy helps to improve the exploitability and adaptability of the algorithm.Within the AFLA-SCNN model,AFLA is employed to optimize two hyperparameters in the SCNN model,namely,“numEpochs”and“miniBatchSize”,to attain their optimal values.AFLA’s performance is initially validated across 28 functions in 10D,30D,and 50D for CEC2013 and 29 functions in 10D,30D,and 50D for CEC2017.Experimental results indicate AFLA’s marked performance superiority over nine other prominent optimization algorithms.Subsequently,the AFLA-SCNN model was compared with the Spectral Convolutional Neural Network model based on Fick’s Law Algorithm(FLA-SCNN),Spectral Convolutional Neural Network model based on Harris Hawks Optimization(HHO-SCNN),Spectral Convolutional Neural Network model based onDifferential Evolution(DE-SCNN),SpectralConvolutionalNeuralNetwork(SCNN)model,and SupportVector Machines(SVM)model using the Indian Pines dataset and PaviaUniversity dataset.The experimental results show that the AFLA-SCNN model outperforms other models in terms of Accuracy,Precision,Recall,and F1-score on Indian Pines and Pavia University.Among them,the Accuracy of the AFLA-SCNN model on Indian Pines reached 99.875%,and the Accuracy on PaviaUniversity reached 98.022%.In conclusion,our proposed AFLA-SCNN model is deemed to significantly enhance the precision of hyperspectral image classification.

Depth-Guided Vision Transformer With Normalizing Flows for Monocular 3D Object Detection

Monocular 3D object detection is challenging due to the lack of accurate depth information.Some methods estimate the pixel-wise depth maps from off-the-shelf depth estimators and then use them as an additional input to augment the RGB images.Depth-based methods attempt to convert estimated depth maps to pseudo-LiDAR and then use LiDAR-based object detectors or focus on the perspective of image and depth fusion learning.However,they demonstrate limited performance and efficiency as a result of depth inaccuracy and complex fusion mode with convolutions.Different from these approaches,our proposed depth-guided vision transformer with a normalizing flows(NF-DVT)network uses normalizing flows to build priors in depth maps to achieve more accurate depth information.Then we develop a novel Swin-Transformer-based backbone with a fusion module to process RGB image patches and depth map patches with two separate branches and fuse them using cross-attention to exchange information with each other.Furthermore,with the help of pixel-wise relative depth values in depth maps,we develop new relative position embeddings in the cross-attention mechanism to capture more accurate sequence ordering of input tokens.Our method is the first Swin-Transformer-based backbone architecture for monocular 3D object detection.The experimental results on the KITTI and the challenging Waymo Open datasets show the effectiveness of our proposed method and superior performance over previous counterparts.

Plasmon-enhanced nanosoldering of silver nanoparticles for high-conductive nanowires electrodes

The silver nanowires(Ag NWs)electrodes,which consist of incompact Ag nanoparticles(NPs)formed by multi-photon photoreduction,usually have poor conductivities.An effective strategy for enhancing conductivity of the Ag NWs elec-trodes is plasmon-enhanced nanosoldering(PLNS)by laser irradiation.Here,plasmon-enhanced photothermal effect is used to locally solder Ag NPs and then aggregates of these NPs grow into large irregular particles in PLNS process.Fi-nite element method(FEM)simulations indicate that the soldering process is triggered by localized surface plasmon-in-duced electric field enhancement at“hot-spots”.The effectiveness of PLNS for enhancing conductivity depends on laser power density and irradiation time.By optimizing the conditions of PLNS,the electrical conductivity of Ag NWs is signific-antly enhanced and the conductivityσs is increased to 2.45×107 S/m,which is about 39%of the bulk Ag.This PLNS of Ag NWs provides an efficient and cost-effective technique to rapidly produce large-area metal nanowire electrodes and capacitors with high conductivity,excellent uniformity,and good flexibility.

Phylogenetic relationships of the zokor genus Eospalax(Mammalia,Rodentia,Spalacidae)inferred from whole-genome analyses,with description of a new species endemic to Hengduan Mountains

Zokors in the genus Eospalax,which are endemic to northern and western China,are subterranean rodents that inhabit various niches,including grasslands,high-altitude meadows,forests,and farmlands.Six species in Eospalax were described a century ago but their taxonomy and phylogeny remain controversial.In this study,we performed high-depth whole-genome sequencing of 47 zokor samples,comprising all six previously described species.Genomic analyses revealed a reliable and robust phylogeny of Eospalax and supported the validity of the six named species.According to the inferred phylogenetic relationships,Eospalax first divergent into two clades in the early Pliocene(ca.4.68 million years ago(Ma)),one inhabiting the highaltitude Qinghai-Xizang(Tibet)Plateau(QTP)and adjacent regions,and the another inhabiting the lowaltitude Loess Plateau and Qinling-Daba Mountains.The most recent divergences occurred between E.baileyi and E.smithii and between E.rufescens and E.rothschildi in the late Pliocene(ca.2.09 and 2.19 Ma,respectively).We also collected specimens of zokors in the southern Hengduan Mountains(Muli County,Sichuan Province),far from the known distributions of all other zokors.Morphological and molecular analyses strongly suggested that the specimens represent a new species,formally described here as Eospalax muliensis sp.nov.The new species belongs to the high-altitude clade and diverged from closely related species(ca.4.22 Ma)shortly after the first divergence in Eospalax.Interestingly,Eospalax muliensis sp.nov.possesses more supposedly plesiomorphic characters,suggesting a possible origin of the genus in the Hengduan Mountains.

Parameter optimization of control system design for uncertain wireless power transfer systems using modified genetic algorithm

The closed-loop wireless power transfer(WPT)system can realize constant voltage output in the presence of perturbation.However,the parameter design of the controller is a difficult problem.The traditional trial-and-error method is time-consuming and difficult to find optimal parameters.A parameter optimization strategy of control systems for uncertain WPT systems using the modified genetic algorithm(MGA)is proposed.Firstly,because the system has different characteristics at different periods,the simulation process is divided into three stages.The first one is the start-up stage,in which we mainly consider the overshoot and the rate of the voltage rise.The second one is the tracking stage,in which the tracking time and switching loss are mainly considered.The third one is the stabilisation stage,in which the steady-state error and switching loss are mainly considered.Secondly,three cost functions are designed according to the characteristics of the three stages,and then the optimal controller parameters of each stage are obtained by using MGA.Finally,the effectiveness of the proposed method is verified by simulation.The optimization results show that compared with the previous parameter optimization method,the optimal controller parameters obtained by the proposed method make the WPT system achieve better performance.

Demands and technical developments of clinical flow cytometry with emphasis in quantitative,spectral,and imaging capabilities

As the gold-standard method for single-cell analysis,flow cytometry enables high-throughput and multiple-parameter characterization of individual biological cells.This review highlights the demands for clinical flow cytometry in laboratory hematology(e.g.,diagnoses of minimal residual disease and various types of leukemia),summarizes state-of-the-art clinical flow cytometers(e.g.,FACSLyricTMby Becton Dickinson,DxFLEX by Beckman Coulter),then considers innovative technical improvements in flow cytometry(including quantitative,spectral,and imaging approaches)to address the limitations of clinical flow cytometry in hematology diagnosis.Finally,driven by these clinical demands,future developments in clinical flow cytometry are suggested.

Preface to the Special Issue of Photocatalysis for Solar Fuels

As natural photosynthesis does, direct conversion of solar energy into the storable form of chemical energy is an intriguing technology for solar energy utilization. Due to increasing concerns of energy and environmental problems caused by the consumption of fossil fuels, production of chemical solar fuels (such as hydrogen, methanol or methane,etc) by artificial photosynthesis, namely photocatalytic splitting of water or reduction of CO2, has been a hot research topic in recent years.

The effect of protic ionic liquids incorporation on CO_(2) separation performance of Pebax-based membranes

The separation of carbon dioxide(CO_(2))is of great importance for environment protection and gas resource purification.The ionic liquids(ILs)-based gas separation membrane provides a new chance for efficient CO_(2)separation,while high permeability and selectivity of membranes is a great challenge.In this study,the influence of two protic ILs with different anion([TMGH][Im]and[TMGH][PhO])on the CO_(2)separation performance of the prepared ILs/Pebax blended membranes were systematically investigated at different temperature.The results showed the CO_(2)permeability exhibits the rising trend for ILs/Pebax blended membranes with the increment of IL content.Especially,the[TMGH][Im]with low viscosity and high CO_(2)absorption capacity leads to the blended membranes showing better CO_(2)permeability and ideal CO_(2)selectivity than that of membranes with[TMGH][PhO]at high IL content.Besides,with operating temperature increasing,the gas permeability of 20%(mass)[TMGH][Im]/Pebax blended membrane increases due to the decreasing viscosity of IL and the rising chain mobility of polymer.Inversely,the gas selectivity shows decreasing trend because CO_(2)absorption capacity obviously decreased at higher temperature.

A novel microfluidic flow-cytometry for counting numbers of single-cell β-actins

As a house keeping protein with stable expressions, β-actin is used as a loading control in normalization of western blotting. However, the actual numbers of β-actins at the single-cell level remain elusive. Based on a homedeveloped flow cytometry, single-cell numbers of β-actin from 8 cell types(subtypes) and 2 tumour patient samples were quantified as 9.62 ± 4.29 × 105(A549, Ncell= 14,242), 6.46 ± 3.34 × 105(Hep G2, Ncell= 35,932),1.58 ± 0.90 × 106(MCF 10 A, N6 cell= 16,650), 1.08 ± 0.48 × 10(HeLa, Ncell= 26,151), 7.60 ± 4.34 × 105(PC3, Ncell= 11,922), 1.10 ± 0.72 × 106(SACC-83, Ncell= 13,616), 8.58 ± 4.54 × 105(CAL 27, Ncell= 7271),9.00 ± 4.69 × 105(CAL 27-LN2, Ncell= 6222), 8.26 ± 4.48 × 105(Oral Tumour Patient I, Ncell= 359), and8.19 ± 5.12 × 105(Oral Tumour Patient II, Ncell= 175), and were analyzed by statistical approaches including one-way analysis of variance, neural network based pattern recognition and Bayesian estimation, with varied expressions of β-actins among different cell types located. The dataset reported in this study may serve as a reference in future studies of quantitative protein analysis.

Dynamic mode decomposition and reconstruction of transient cavitating flows around a Clark-Y hydrofoil

The transient cavitating flow around the Clark-Y hydrofoil is numerically investigated by the dynamic mode decomposition with criterion.Based on the ranking dominant modes,frequencies of the first four modes are in good accordance with those obtained by fast Fourier transform.Furthermore,the cavitating flow field is reconstructed by the first four modes,and the dominant flow features are well captured with the reconstructed error below 12%when compared to the simulated flow field.This paper offers a reference for observing and reconstructing the flow fields,and gives a novel insight into the transient cavitating flow features.

Flat soliton microcomb source

Mode-locked microcombs with flat spectral profiles provide the high signal-to-noise ratio and are in high demand for wavelength division multiplexing(WDM)-based applications,particularly in future high-capacity communication and parallel optical computing.Here,we present two solutions to generate local relatively flat spectral profiles.One microcavity with ultra-flat integrated dispersion is pumped to generate one relatively flat single soliton source spanning over 150 nm.Besides,one extraordinary soliton crystal with single vacancy demonstrates the local relatively flat microcomb lines when the inner soliton spacings are slightly irregular.Our work paves a new way for soliton-based applications owing to the relatively flat spectral characteristics.