Efficient removal of U(VI) from wastewater by a sponge-like 3D porous architecture with hybrid electrospun nanofibers

Removal of uranium(VI)from nuclear wastewater is urgent due to the global nuclear energy exploitation.This study synthesized novel sponge-like 3D porous materials for enhanced uranium adsorption by combining electrospinning and fibrous freeze-shaping techniques.The materials possessed an organic-inorganic hybrid architecture based on the electrospun fibers of polyacrylonitrile(PAN)and SiO_(2).As a sup-porting material,the surface of fibrous SiO_(2) could be further functionalized by cyano groups via(3-cyanopropyl)triethoxysilane.All the cyano groups were turned into amidoxime(AO)groups to obtain a amidoxime-functionalized sponge(PAO/SiO_(2)-AO)through the subsequent ami-doximation process.The proposed sponge exhibited enhanced uranium adsorption performance with a high removal capacity of 367.12 mg/g,a large adsorption coefficient of 4.0×10^(4)mL/g,and a high removal efficiency of 97.59%.The UO_(2)^(2+)adsorption kinetics perfectly conformed to the pseudo-second-order reaction.The sorbent also exhibited an excellent selectivity for UO_(2)^(2+) with other interfering metal ions.2023 Hohai University.Production and hosting by Elsevier B.V.

Research on Interpolation Method for Missing Electricity Consumption Data

Missing value is one of the main factors that cause dirty data.Without high-quality data,there will be no reliable analysis results and precise decision-making.Therefore,the data warehouse needs to integrate high-quality data consistently.In the power system,the electricity consumption data of some large users cannot be normally collected resulting in missing data,which affects the calculation of power supply and eventually leads to a large error in the daily power line loss rate.For the problem of missing electricity consumption data,this study proposes a group method of data handling(GMDH)based data interpolation method in distribution power networks and applies it in the analysis of actually collected electricity data.First,the dependent and independent variables are defined from the original data,and the upper and lower limits of missing values are determined according to prior knowledge or existing data information.All missing data are randomly interpolated within the upper and lower limits.Then,the GMDH network is established to obtain the optimal complexity model,which is used to predict the missing data to replace the last imputed electricity consumption data.At last,this process is implemented iteratively until the missing values do not change.Under a relatively small noise level(α=0.25),the proposed approach achieves a maximum error of no more than 0.605%.Experimental findings demonstrate the efficacy and feasibility of the proposed approach,which realizes the transformation from incomplete data to complete data.Also,this proposed data interpolation approach provides a strong basis for the electricity theft diagnosis and metering fault analysis of electricity enterprises.

Development of in situ characterization techniques in molecular beam epitaxy

Ex situ characterization techniques in molecular beam epitaxy(MBE)have inherent limitations,such as being prone to sample contamination and unstable surfaces during sample transfer from the MBE chamber.In recent years,the need for improved accuracy and reliability in measurement has driven the increasing adoption of in situ characterization techniques.These techniques,such as reflection high-energy electron diffraction,scanning tunneling microscopy,and X-ray photoelectron spectroscopy,allow direct observation of film growth processes in real time without exposing the sample to air,hence offering insights into the growth mechanisms of epitaxial films with controlled properties.By combining multiple in situ characterization techniques with MBE,researchers can better understand film growth processes,realizing novel materials with customized properties and extensive applications.This review aims to overview the benefits and achievements of in situ characterization techniques in MBE and their applications for material science research.In addition,through further analysis of these techniques regarding their challenges and potential solutions,particularly highlighting the assistance of machine learning to correlate in situ characterization with other material information,we hope to provide a guideline for future efforts in the development of novel monitoring and control schemes for MBE growth processes with improved material properties.

Intelligent In-Vehicle Safety System Based on Yolov5

In order to reduce the occurrence of traffic accidents and assist drivers to avoid dangerous driving. This paper presents a smart in-vehicle safety system that utilises the Yolov5 algorithm. Yolov5 algorithm is used to anticipate driver fatigue and distraction behaviours, and remind drivers to pay attention to safe driving in time. The system continuously splits the frames and analyses the frame content through the video feedback from the front camera, compared to the traditional machine learning, Yolov5’s mosaic data is enhanced, resulting in a batch size enhancement of 92.3%, and it also uses the Drop Block mechanism to prevent overfitting. The hardware of this system uses STM32 microcontroller and uses system DMA interrupt control and buzzer alarm device to warn about dangerous driving behaviour.

Prediction of Wordle Scores Based on ARIMA and LSTM Models

This paper examines the effectiveness of the Differential autoregressive integrated moving average (ARIMA) model in comparison to the Long Short Term Memory (LSTM) neural network model for predicting Wordle user-reported scores. The ARIMA and LSTM models were trained using Wordle data from Twitter between 7th January 2022 and 31st December 2022. User-reported scores were predicted using evaluation metrics such as MSE, RMSE, R2, and MAE. Various regression models, including XG-Boost and Random Forest, were used to conduct comparison experiments. The MSE, RMSE, R2, and MAE values for the ARIMA(0,1,1) and LSTM models are 0.000, 0.010, 0.998, and 0.006, and 0.000, 0.024, 0.987, and 0.013, respectively. The results indicate that the ARIMA model is more suitable for predicting Wordle user scores than the LSTM model.

A Study on the Integration of Culture Industry and Tourism Industry--A Case Study of Yancheng City in Jiangsu Province

On the basis of the domestic and foreign research results,combined with the reality of Yancheng,this paper puts forward that spatial layout is the key,the development of tourist product is the crux,the brand image is the core,and regional cooperation is the main way of development.

Marginal weakening promoted rift propagation of the Petermann Ice Shelf in northwestern Greenland from 2016 to 2022

Ice-shelf rifts are precursors of glacier calving, and thus they serve as indicators of ice shelf instability, especially under oceanic and atmospheric warming conditions. Therefore, understanding the dynamic processes underlying rift propagation and the associated damage mechanisms is essential to evaluate ice-shelf instability and to predict glacier calving. In this study, we investigated the effect of marginal weakening on rift propagation on the ice shelf of the Petermann Glacier, among the largest in Greenland, during 2016-2022. First, we analyzed satellite optical images to monitor rift growth(length and width) by tracking the tip trajectory of three large rifts identified on the Petermann Ice Shelf. Then, we estimated rift depth using ArcticDEM and ICESat-2 data. Our results indicated consistent increases of the rift widths and depths over the study period, with mean values of 133 m·a^(-1) and 0.3 m·a^(-1), respectively. We also combined remote-sensing observations with an ice-sheet numerical model to calculate the stress and damage fields on the Petermann Ice Shelf and to assess the ice shelf margin stability and strength. We determined that damage and lateral shear in the fracture zone degraded ice shelf integrity by decreasing the contact length with the fjord wall. In conclusion, marginal weakening effectively promoted rift propagation on the Petermann Ice Shelf, increasing the risk of future glacier calving.

Effects of Polysaccharides from Enteromorpha prolifera on Hepatorenal Syndrome in Mice

[Objectives]This study was conducted to evaluate the protective effect of polysaccharides from Enteromorpha prolifera(PEP)on mice with hepatorenal syndrome induced by carbon tetrachloride.[Methods]A mouse hepatorenal syndrome model was induced by carbon tetrachloride.The serum levels of lipid,total antioxidant capacity,liver and kidney function,pathological changes of liver and kidney were selected to clarity the effectiveness of PEP on hepatorenal syndrome in mice.[Results]PEP effectively lowered the serum levels of lipid,increased total antioxidant capacity,improved liver and kidney injury,and alleviated pathological changes of liver and kidney of mice induced by carbon tetrachloride.[Conclusions]PEP has a potent preventive effect on hepatorenal syndrome induced by carbon tetrachloride in mice,which provides theoretical support for future clinical application of PEP.

Fecal DNA metabarcoding reveals the dietary composition of wintering Red-crowned Cranes(Grus japonensis)

Understanding the diet of threatened wildlife is vital for species-specific conservation and habitat management measures.The Red-crowned Crane(Grus japonensis)is a vulnerable bird distributed in Northeast Asia.Previous dietary studies of this bird focused mainly on its plant food composition based on field observations and microhistological identification.Herein,a total of 45 fecal samples were collected in November,December and January(15 fecal samples each month)from wintering cranes,and then subjected to a high throughput sequencing meta-barcoding approach to determine the primary plant(rbcL)and animal(COI)food items in their diet.A total of 230 operational taxonomic units(OTUs)of plant foods and 371 OTUs of animal foods were obtained.The main plant foods in the wintering period were Miscanthus,Zea,and Hordeum genera,which were similar to those in the breeding and the migration periods.Both agricultural and natural plants were detected,indicating a relatively broad dietary niche for this crane species.However,the main animal foods were representatives of Theridiidae,Megascolecidae,and Agelenidae,in sharp contrast to previous studies.The higher number of small terrestrial arthropods in animal foods might be due to the indirect intake of plants.The composition of both plant and animal foods in the diet showed the highest diversity in December,while it was homogeneous in January.The plant of Zea genus became the main source of nutrition in late winter,as supplementary feeding was performed in the reserve,which could help Red-crowned Cranes to get through the cold season.The results obtained in this work would contribute to the development of effective conservation strategies for the Red-crowned Crane.

A Novel Method for Diagnosis of Breast Cancer Tumors Based on Random Forest

GLOBOCAN 2020 cancer data shows that female breast cancer has become the most common cancer over lung cancer for the first time. As a disease threatening the life safety of women all over the world, how to improve the accuracy of breast cancer diagnosis and help patients get treatment as early as possible is of great importance. This paper introduces a new random forest-based breast cancer diagnosis method (NRFM), using the average radius, average texture, average circumference and other 30 indicators in the nucleus of breast mass as characteristics, to diagnose the benign and malignant breast cancer. NRFM proposed to randomly miss a certain percentage of breast cancer data, using random forest regression to fill in the experiment proved that using the method proposed in this paper, when the proportion of missing data reached 50%, the accuracy of breast cancer diagnosis will be as high as 96.85%. Experiments show that NRFM is easy to understand, convenient to operate, and has practical application value, which can assist doctors to improve the accuracy of breast cancer diagnosis.

On a Class of Semigroup Graphs

Let G = Γ(S) be a semigroup graph, i.e., a zero-divisor graph of a semigroup S with zero element 0. For any adjacent vertices x, y in G, denote C(x,y) = {z∈V(G) | N (z) = {x,y}}. Assume that in G there exist two adjacent vertices x, y, a vertex s∈C(x,y) and a vertex z such that d (s,z) = 3. This paper studies algebraic properties of S with such graphs G = Γ(S), giving some sub-semigroups and ideals of S. It constructs some classes of such semigroup graphs and classifies all semigroup graphs with the property in two cases.

A DFT-based Quantum Theoretic QSAR Study of Nitrobenzenes' Toxicity to Tetrahymena Pyriformis

In this study,DFT-B3LYP level of theory with the 6-311G basis set was used to calculate a set of molecular descriptors of 36 nitrobenzenes.Quantitative structure-activity relationship（QSAR） models of the toxicity（pIGC50） of 36 nitrobenzenes were established using some of the following calculated descriptors：HOMO energy（EHOMO）,LUMO energy（ELUMO）,the difference between LUMO and HOMO energy values（ΔE=ELUMO–EHOMO）,average polarizability（P）,dipole moment（μ）,molecular volume（V） and the charge of nitro group（Q-NO2）.The QSAR models obtained by employing stepwise multiple regression techniques are aimed at correlating the structures with their reported experimental toxicity values. Among the models presented in this study, statistically the most significant one is a two-parameter linear equation with the correlation coefficient （R2） of 0.896 and cross-validated correlation coefficient （R2cv） of 0.878. To further validate the predictive ability of the resulting model, external validation was carried out with R2~xt and Q^2,ext values of 0.894, 0.900, 0.909, 0.874, 0.885 and 0.903, respectively. This study also reconstructed the obtained models using AMl-based calculated descriptors to demonstrate the superiority of DFT over AM1 for quantum calculations of mechanical descriptors. The results were discussed in the light of the main factors that influence the toxicity of nitrobenznenes.

Development and transition of spiral wave in the coupled Hindmarsh-Rose neurons in two-dimensional space

The dynamics and the transition of spiral waves in the coupled Hindmarsh-Rose （H-R） neurons in two-dimensional space are investigated in the paper. It is found that the spiral wave can be induced and developed in the coupled HR neurons in two-dimensional space, with appropriate initial values and a parameter region given. However, the spiral wave could encounter instability when the intensity of the external current reaches a threshold value of 1.945. The transition of spiral wave is found to be affected by coupling intensity D and bifurcation parameter r. The spiral wave becomes sparse as the coupling intensity increases, while the spiral wave is eliminated and the whole neuronal system becomes homogeneous as the bifurcation parameter increases to a certain threshold value. Then the coupling action of the four sub-adjacent neurons, which is described by coupling coefficient D＇, is also considered, and it is found that the spiral wave begins to breakup due to the introduced coupling action from the sub-adjacent neurons （or sites） and together with the coupling action of the nearest-neighbour neurons, which is described by the coupling intensity D.

Further Results on Delay-distribution-dependent Robust Stability Criteria for Delayed Systems

This paper concerns the robust stability analysis of uncertain systems with time delays as random variables drawn from some probability distribution. The delay-distribution-dependent criteria for the exponential stability of the original system in mean square sense are achieved by Lyapunov functional method and the linear matrix inequality （LMI） technique. The proposed approach involves neither free weighting matrices nor any model transformation, and it shows that the new criteria can provide less conservative results than some existing ones. Numerical examples are given to demonstrate the effectiveness and the benefits of the proposed method.

Ultralight Magnetic and Dielectric Aerogels Achieved by Metal-Organic Framework Initiated Gelation of Graphene Oxide for Enhanced Microwave Absorption

The development of a convenient methodology for synthesizing the hierarchically porous aerogels comprising metal–organic frameworks(MOFs)and graphene oxide(GO)building blocks that exhibit an ultralow density and uniformly distributed MOFs on GO sheets is important for various applications.Herein,we report a facile route for synthesizing MOF/reduced GO(rGO)aerogels based on the gelation of GO,which is directly initiated using MOF crystals.Free metal ions exposed on the surface of MIL-88A nanorods act as linkers that bind GO nanosheets to a three-dimensional porous network via metal–oxygen covalent or electrostatic interactions.The MOF/rGOderived magnetic and dielectric aerogels Fe_(3)O_(4)@C/rGO and Ni-doped Fe_(3)O_(4)@C/rGO show notable microwave absorption(MA)performance,simultaneously achieving strong absorption and broad bandwidth at low thickness of 2.5(-58.1 dB and 6.48 GHz)and 2.8 mm(-46.2 dB and 7.92 GHz)with ultralow filling contents of 0.7 and 0.6 wt%,respectively.The microwave attenuation ability of the prepared aerogels is further confirmed via a radar cross-sectional simulation,which is attributed to the synergistic effects of their hierarchically porous structures and heterointerface engineering.This work provides an effective pathway for fabricating hierarchically porous MOF/rGO hybrid aerogels and offers magnetic and dielectric aerogels for ultralight MA.

Pressure-controlled terahertz filter based on 1D photonic crystal with a defective semiconductor

The tunable terahertz（THz） filter has been designed and studied, which is composed of 1D photonic crystal（PC） containing a defect layer of semiconductor Ga As. The analytical solution of 1D defective PC（1DDPC） is deduced based on the transfer matrix method, and the electromagnetic plane wave numerical simulation of this 1DDPC is performed by using the finite element method. The calculated and simulated results have confirmed that the filtering transmittance of this 1DDPC in symmetric structure of air/（Si/SiO_2）~N/GaAs/（SiO_2/Si）~N/air is far higher than in asymmetric structure of air/（Si/SiO_2）~N/GaAs/（Si/SiO_2）~N/air, where the filtering frequency can be tuned by the external pressure. It can provide a feasible route to design the external pressure-controlled THz filter based on 1DPC with a defective semiconductor.

Research on Comparison of Enterprise Financing Efficiency under Layered Background

This paper takes the innovative enterprises with substantial financing in2014-2016 as the research sample,uses the foundation layer enterprises under the same conditions as the contrast,and uses the data envelopment analysis to do empirical research. By comparing the comprehensive technical efficiency,pure technical efficiency and scale efficiency of the sample enterprises and the controlled enterprises,and through the analysis of slack variables of non DEA efficient enterprises,the reasons for the low efficiency and the improvement direction are pointed out. The results show that the financing efficiency of innovation layer enterprises is obviously higher than that of the underlying enterprises,and the financing efficiency has also improved in recent years,but there are still unstable factors,main problem of which is poor operating capacity of funds.

Complex dynamics analysis of impulsively coupled Duffing oscillators with ring structure

Impulsively coupled systems are high-dimensional non-smooth systems that can exhibit rich and complex dynamics.This paper studies the complex dynamics of a non-smooth system which is unidirectionally impulsively coupled by three Duffing oscillators in a ring structure.By constructing a proper Poincare map of the non-smooth system,an analytical expression of the Jacobian matrix of Poincare map is given.Two-parameter Hopf bifurcation sets are obtained by combining the shooting method and the Runge-Kutta method.When the period is fixed and the coupling strength changes,the system undergoes stable,periodic,quasi-periodic,and hyper-chaotic solutions,etc.Floquet theory is used to study the stability of the periodic solutions of the system and their bifurcations.

Stable adaptive fuzzy control of nonlinear systems using small-gain theorem and LMI approach

A new design scheme of stable adaptive fuzzy control for a class of nonlinear systems is proposed in this paper.The T-S fuzzy model is employed to represent the systems.First,the concept of the so-called parallel distributed compensation （PDC） and linear matrix inequality （LMI） approach are employed to design the state feedback controller without considering the error caused by fuzzy modeling.Sufficient conditions with respect to decay rate α are derived in the sense of Lyapunov asymptotic stability.Finally,the error caused by fuzzy modeling is considered and the input-to-state stable （ISS） method is used to design the adaptive compensation term to reduce the effect of the modeling error.By the small-gain theorem,the resulting closed-loop system is proved to be input-to-state stable.Theoretical analysis verifies that the state converges to zero and all signals of the closed-loop systems are bounded.The effectiveness of the proposed controller design methodology is demonstrated through numerical simulation on the chaotic Henon system.