Empirical likelihood for spatial cross-sectional data models with matrix exponential spatial specification

In this paper,we study spatial cross-sectional data models in the form of matrix exponential spatial specification(MESS),where MESS appears in both dependent and error terms.The empirical likelihood(EL)ratio statistics are established for the parameters of the MESS model.It is shown that the limiting distributions of EL ratio statistics follow chi-square distributions,which are used to construct the confidence regions of model parameters.Simulation experiments are conducted to compare the performances of confidence regions based on EL method and normal approximation method.

Factors affecting land dissection density in geomorphological regions of China

Land dissection density(LDD)provides morphological evidence regarding prior intense soil erosion and quantifies the distribution of land dissections.A comprehensive understanding of the potential factors influencing the spatial pattern and value of the LDD is vital in geological disasters,soil erosion,and other related domains.Land dissection phenomena in China affects large areas with different morphological,pedological,and climatic characteristics.Prior studies have focused on the potential factors influencing the LDD at a watershed scale.However,these results are insufficient to reflect the status quo of dissection development and its primary influencing factors on a national scale.LDD’s spatial patterns and the dominant factors at a regional scale in millions of square kilometers remain to be ascertained.This study used the geomorphon-based method and the geographical detector model to quantify the spatial pattern of LDD over China and identify the dominant factors affecting this pattern in China’s six first-order geomorphological regions(GR1~GR6).The results yield the following findings:(1)LDD in China ranges from 0~4.55 km/km^(2),which is larger in central and eastern regions than in other regions of China;(2)dominant factors and their dominant risk subcategories vary with each geomorphological region’s primary internal and external forces;(3)the influence of natural factors is more significant on the large regional scale in millions of square kilometers compared to anthropogenic factors;relief degree of land surface(RDLS)is dominant in GR1,GR2,and GR5;the slope is dominant in GR6,soil type is dominant in GR3 and GR4,and lithology plays a critical role in the dominant interactions of GR3,GR4,and GR6;(4)the interactions between factors on LDD’s spatial pattern have a more significant effect than individual factors.

Lycium barbarum glycopeptide(wolfberry extract)slows N-methyl-N-nitrosourea-induced degradation of photoreceptors

Photoreceptor cell degeneration leads to blindness, for which there is currently no effective treatment. Our previous studies have shown that Lycium barbarum(L. barbarum) polysaccharide(LBP) protects degenerated photoreceptors in rd1, a transgenic mouse model of retinitis pigmentosa. L. barbarum glycopeptide(Lb GP) is an immunoreactive glycoprotein extracted from LBP. In this study, we investigated the potential protective effect of Lb GP on a chemically induced photoreceptor-degenerative mouse model. Wild-type mice received the following: oral administration of Lb GP as a protective pre-treatment on days 1–7;intraperitoneal administration of 40 mg/kg N-methylN-nitrosourea to induce photoreceptor injury on day 7;and continuation of orally administered Lb GP on days 8–14. Treatment with Lb GP increased photoreceptor survival and improved the structure of photoreceptors, retinal photoresponse, and visual behaviors of mice with photoreceptor degeneration. Lb GP was also found to partially inhibit the activation of microglia in N-methyl-N-nitrosourea-injured retinas and significantly decreased the expression of two pro-inflammatory cytokines. In conclusion, Lb GP effectively slowed the rate of photoreceptor degeneration in N-methyl-N-nitrosourea-injured mice, possibly through an anti-inflammatory mechanism, and has potential as a candidate drug for the clinical treatment of photoreceptor degeneration.

An artificial intelligence diabetes managgement architecture based on 5G

Along with the development of 5G network and Internet of Things technologies,there has been an explosion in personalized healthcare systems.When the 5G and Artificial Intelligence(Al)is introduced into diabetes management architecture,it can increase the efficiency of existing systems and complications of diabetes can be handled more effectively by taking advantage of 5G.In this article,we propose a 5G-based Artificial Intelligence Diabetes Management architecture(AIDM),which can help physicians and patients to manage both acute complications and chronic complications.The AIDM contains five layers:the sensing layer,the transmission layer,the storage layer,the computing layer,and the application layer.We build a test bed for the transmission and application layers.Specifically,we apply a delay-aware RA optimization based on a double-queue model to improve access efficiency in smart hospital wards in the transmission layer.In application layer,we build a prediction model using a deep forest algorithm.Results on real-world data show that our AIDM can enhance the efficiency of diabetes management and improve the screening rate of diabetes as well.

A Review of Research on Second Language Acquisition from a Positive Psychology Perspective

This paper reviews the research on second language acquisition from the perspective of positive psychology.First,it introduces the background and purpose of the study and discusses the significance of the application of positive psychology in the field of language acquisition.Then,the basic theories of positive psychology,including the core concepts and principles of positive psychology,are summarized.Subsequently,the theory of second language acquisition is defined and outlined,including the definition,characteristics,and related developmental theories of second language acquisition.On this basis,the study of second language acquisition from the perspective of positive psychology is discussed in detail.By combing and synthesizing the literature,this paper summarizes the current situation and trend of second language acquisition research under the perspective of positive psychology and puts forward some future research directions and suggestions.

An Improved Harris Hawk Optimization Algorithm

Aiming at the problems that the original Harris Hawk optimization algorithm is easy to fall into local optimum and slow in finding the optimum,this paper proposes an improved Harris Hawk optimization algorithm(GHHO).Firstly,we used a Gaussian chaotic mapping strategy to initialize the positions of individuals in the population,which enriches the initial individual species characteristics.Secondly,by optimizing the energy parameter and introducing the cosine strategy,the algorithm's ability to jump out of the local optimum is enhanced,which improves the performance of the algorithm.Finally,comparison experiments with other intelligent algorithms were conducted on 13 classical test function sets.The results show that GHHO has better performance in all aspects compared to other optimization algorithms.The improved algorithm is more suitable for generalization to real optimization problems.

Research on the Resistance of Cutting Mechanism of Mining Longitudinal Roadheader

In order to accurately obtain the dynamic characteristics of the cutting mechanism of the mining longitudinal roadheader,combined with the working principle of the mining longitudinal roadheader,the theoretical analysis and derivation are carried out in detail.By using ADAMS to simulate,the resistance curve and torque curve of the cutting mechanism in different directions are obtained.The results show that ADAMS can effectively predict the excavation resistance and torque of the cutting mechanism of mining longitudinal roadheader,which has certain reference value for future optimization design.

Design a Special Fixture for Tractor Lever

Aiming at the problems of long time and poor machining precision in processing the tractor lever workpiece,a special fixture suitable for the tractor lever workpiece is designed by analyzing the processing technology of the lever workpiece,and the workpiece is accurately positioned and tightened under the action of the special fixture.Efficient machining of the workpiece can be achieved by using a drill template.The fixture not only has the advantages of high production efficiency,low cost and high life,but also effectively improves the processing technology of the workpiece,and has certain reference value for the subsequent fixture improvement design.

Hair growth-promotion effects and antioxidant activity of the banana flower extract HappyAngel^(■):double-blind, placebo-controlled trial

Banana flowers contain various bioactive components, including several antioxidants with anti-inflammatory effects. However, it is unclear whether they can reduce and prevent hair loss. This study examines the effect of banana flower extracts on preventing hair loss and strengthening hair roots. The banana flower extract(HappyAngel^(■))was used to treat human hair follicle dermal papilla cells(HFDPCs)and the expression of reactive oxygen species(ROS), dihydrotestosterone(DHT), and hair-related genes(SRD5A1, SRD5A2, AR, and KROX20)were monitored. Fifty subjects were divided into a placebo group and a banana flower group. The experimental group consumed banana flower extract daily for twelve weeks and then underwent hair testing, hair-related genes analysis, collection of hair loss, and questionnaires. The results showed that the banana flower extract significantly increased hair cell growth and decreased the expression of ROS, DHT, and hair follicle growth inhibition-related SRD5A1, SRD5A2, and AR genes, and significantly increased the expression of hair growth-related KROX20 gene in HFDPCs. Consuming banana flower extract for twelve weeks increased the hair root diameter and reduced hair loss and scalp redness compared to the placebo group. Thus, banana flower extract(HappyAngel^(■))can stimulate hair growth and inhibit the activation of hair loss genes.

Mechanical Properties of Self-Compacting Rubberized Concrete with Different Rubber Types under Triaxial Compression

Different rubber aggregates lead to changes in the effect of stress conditions on the mechanical behavior of concrete,and studies on the triaxial properties of self-compacting rubber concrete(SCRC)are rare.In this study,35 cylindrical specimens taking lateral stress and rubber type as variables were prepared to study the fresh properties and mechanical behaviors of SCRC under triaxial compression,where the rubber contains two types,i.e.,380μm rubber powder and 1–4 mm rubber particles,and four contents,i.e.,10%,20%and 30%.The test results demonstrated that SCRC exhibited a typical oblique shear failure mode under triaxial compression and had a more moderate descending branch compared with self-compacting concrete(SCC).The presence of lateral stress can significantly improve the compression properties,including initial elastic modulus,peak stress and peak strain,with an improvement range of 3%–73%for peak stress.While rubber aggregates mainly targeted the deformation abilities and toughness for improvement,and the peak strain improvement ranges were 0.1–3.1 times and 0.1–1.0 times for SCRC containing rubber powder and SCRC containing rubber particles,respectively,relative to SCC.At a high lateral stress of at least 12 MPa,the loss of strength due to the addition of rubber can be controlled within 10%,in which case the content of rubber powder and rubber particles was recommended to be at most 20%and 30%,respectively.Based on the Mohr-Coulomb theory,the failure criteria of SCRC with different rubber types were established.For analysis and design purposes,an empirical model was proposed to predict the stressstrain behavior under triaxial compression,considering the influence of different rubber content and lateral stress.The results obtained in this study can provide a valuable reference for the design and application of self-compacting rubberized concrete in practical projects,especially those involving three-way compression states and requiring high-quality deformation and energy dissipation.

Multi-Feature Fusion Book Recommendation Model Based on Deep Neural Network

The traditional recommendation algorithm represented by the collaborative filtering algorithm is the most classical and widely recommended algorithm in the practical industry.Most book recommendation systems also use this algorithm.However,the traditional recommendation algorithm represented by the collaborative filtering algorithm cannot deal with the data sparsity well.This algorithm only uses the shallow feature design of the interaction between readers and books,so it fails to achieve the high-level abstract learning of the relevant attribute features of readers and books,leading to a decline in recommendation performance.Given the above problems,this study uses deep learning technology to model readers’book borrowing probability.It builds a recommendation system model through themulti-layer neural network and inputs the features extracted from readers and books into the network,and then profoundly integrates the features of readers and books through the multi-layer neural network.The hidden deep interaction between readers and books is explored accordingly.Thus,the quality of book recommendation performance will be significantly improved.In the experiment,the evaluation indexes ofHR@10,MRR,andNDCGof the deep neural network recommendation model constructed in this paper are higher than those of the traditional recommendation algorithm,which verifies the effectiveness of the model in the book recommendation.

Design of Semipersistent Resource Allocation in LTE-V Network

Radio network access technology currently used in 4G/5G is Long Term Evolution-Advanced(LTE-A),which was developed by 3rd Generation Partnership Project(3GPP).Device-to-device(D2D)communication is a technology enabling direct communications among wireless devices without forwarding through an evolved Node B(eNB).Moreover,D2D transmission can support vehicles as a vehicle-to-vehicle(V2V)environment.It is possible to avoid accidents via exchanging movement-related information among vehicles and effectively increase driving safety(and efficiency).However,radio resources are limited in radio networks.A vehicle transmits through D2D in Long Term Evolution-Vehicle(LTE-V)mode-3 standard,and an eNB can allocate the same spectrum radio resources for cellular and V2V links simultaneously.When using the same radio resources,the probability of interference may increase.This study designed a semipersistent resource allocation algorithm based on different cycles in an LTE-V network.Moreover,resource allocation under different cycles was analyzed,and a scheme for resource selection is proposed based on cycle size.The proposed Semi Persistent Gain Aware Resource Allocation(SP-GARA)scheme selects resources based on the expected sum rate of the cycle size and analyzes and discusses the results of the total sum rate at different cycles and speeds for an improved performance.

Lightweight Method for Plant Disease Identification Using Deep Learning

In the deep learning approach for identifying plant diseases,the high complexity of the network model,the large number of parameters,and great computational effort make it challenging to deploy the model on terminal devices with limited computational resources.In this study,a lightweight method for plant diseases identification that is an improved version of the ShuffleNetV2 model is proposed.In the proposed model,the depthwise convolution in the basic module of ShuffleNetV2 is replaced with mixed depthwise convolution to capture crop pest images with different resolutions;the efficient channel attention module is added into the ShuffleNetV2 model network structure to enhance the channel features;and the ReLU activation function is replaced with the ReLU6 activation function to prevent the gen-eration of large gradients.Experiments are conducted on the public dataset PlantVillage.The results show that the proposed model achieves an accuracy of 99.43%,which is an improvement of 0.6 percentage points compared to the ShuffleNetV2 model.Compared to lightweight network models,such as MobileNetV2,MobileNetV3,EfficientNet,and EfficientNetV2,and classical convolutional neural network models,such as ResNet34,ResNet50,and ResNet101,the proposed model has fewer parameters and higher recognition accuracy,which provides guidance for deploying crop pest identification methods on resource-constrained devices,including mobile terminals.

Determination of the early Paleozoic accretionary complex in Southwestern Yunnan, China: Implications for the tectonic evolution of the Proto-Tethys Ocean

Accretionary complex study provides important knowledge on the subduction and the geodynamic processes of the oceanic plate,which represents the ancient ocean basin extinction location.Nevertheless,there exist many disputes on the age,material source,and tectonic attribute of the Lancang Group,located in Southwest Yunnan,China.In this paper,the LA-ICP-MS detrital zircon U‒Pb chronology of nine metamorphic rocks in the Lancang Group was carried out.The U‒Pb ages of the three detrital zircons mainly range from 590-550 Ma,980-910 Ma,and 1150-1490 Ma,with the youngest detrital zircons having a peak age of about 560 Ma.The U‒Pb ages of the six detrital zircons mainly range from 440-460 Ma and 980-910 Ma,and the youngest detrital zircon has a peak age of about 445 Ma.In the Lancang Group,metamorphic acidic volcanic rocks,basic volcanic rocks,intermediate-acid intrusive rocks,and high-pressure metamorphic rocks are exposed in the form of tectonic lens in schist,rendering typical melange structural characteristics of“block+matrix”.Considering regional deformation and chronology,material composition characteristics,and the previous data,this study thinks the Lancang Group may be an early Paleozoic tectonic accretionary complex formed by the eastward subduction of the Changning-Menglian Proto-Tethys Ocean,which provides an important constraint for the Tethys evolution.

Quantum Oblivious Transfer with Reusable Bell State

In cryptography,oblivious transfer(OT)is an important multiparty cryptographic primitive and protocol,that is suitable for many upperlayer applications,such as secure computation,remote coin-flipping,electrical contract signing and exchanging secrets simultaneously.However,some nogo theorems have been established,indicating that one-out-of-two quantum oblivious transfer(QOT)protocols with unconditional security are impossible.Fortunately,some one-out-of-two QOT protocols using the concept of Crepeau’s reduction have been demonstrated not to conform to Lo’s no-go theorem,but these protocols require more quantum resources to generate classical keys using all-or-nothing QOT to construct one-out-of-two QOT.This paper proposes a novel and efficient one-out-of-two QOT which uses quantum resources directly instead of wasting unnecessary resources to generate classical keys.The proposed protocol is not covered by Lo’s no-go theorem,and it is able to check the sender’s loyalty and avoid the attack from the receiver.Moreover,the entangled state of the proposed protocol is reusable,so it can provide more services for the participants when necessary.Compared with otherQOT protocols,the proposed protocol is more secure,efficient,and flexible,which not only can prevent external and internal attacks,but also reduce the required resources and resource distribution time.

Application of Deep Learning to Production Forecasting in Intelligent Agricultural Product Supply Chain

Production prediction is an important factor influencing the realization of an intelligent agricultural supply chain.In an Internet of Things(IoT)environment,accurate yield prediction is one of the prerequisites for achieving an efficient response in an intelligent agricultural supply chain.As an example,this study applied a conventional prediction method and deep learning prediction model to predict the yield of a characteristic regional fruit(the Shatian pomelo)in a comparative study.The root means square error(RMSE)values of regression analysis,exponential smoothing,grey prediction,grey neural network,support vector regression(SVR),and long short-term memory(LSTM)neural network methods were 53.715,6.707,18.440,1.580,and 1.436,respectively.Among these,the mean square error(MSE)values of the grey neural network,SVR,and LSTM neural network methods were 2.4979,31.652,and 2.0618,respectively;and theirRvalues were 0.99905,0.94,and 0.94501,respectively.The results demonstrated that the RMSE of the deep learning model is generally lower than that of a traditional prediction model,and the prediction results are more accurate.The prediction performance of the grey neural network was shown to be superior to that of SVR,and LSTM neural network,based on the comparison of parameters.

Long-term quality-of-care score for predicting the occurrence of acute myocardial infarction in patients with type 2 diabetes mellitus

BACKGROUND Cardiovascular disease(CVD)is the leading cause of death globally,and diabetes mellitus(DM)is a well-established risk factor.Among the risk factors for CVD,DM is a major modifiable factor.In the fatal CVD outcomes,acute myocardial infarction(AMI)is the most common cause of death.AIM To develop a long-term quality-of-care score for predicting the occurrence of AMI among patients with type 2 DM on the basis of the hypothesis that good quality of care can reduce the risk of AMI in patients with DM.METHODS Using Taiwan’s Longitudinal Cohort of Diabetes Patients Database and the medical charts of a medical center,we identified incident patients diagnosed with type 2 DM from 1999 to 2003 and followed them until 2011.We constructed a summary quality-of-care score(with values ranging from 0 to 8)with process indicators(frequencies of HbA1c and lipid profile testing and urine,foot and retinal examinations),intermediate outcome indicators(low-density lipoprotein,blood pressure and HbA1c),and co-morbidity of hypertension.The associations between the score and the incidence of AMI were evaluated using Cox regression models.RESULTS A total of 7351 patients who had sufficient information to calculate the score were enrolled.In comparison with participants who had scores≤1,those with scores between 2 and 4 had a lower risk of developing AMI[adjusted hazard ratio(AHR)=0.71;95% confidence interval(95%CI):0.55-0.90],and those with scores≥5 had an even lower risk(AHR=0.37;95%CI:0.21-0.66).CONCLUSION Good quality of care can reduce the risk of AMI in patients with type 2 DM.The quality-of-care score developed in this study had a significant association with the risk of AMI and thus can be applied to guiding the care for these patients.

Dramatic changes in the horizontal structure of mangrove forests in the largest delta of the northern Beibu Gulf, China

The horizontal structure of mangrove forests is an important characteristic that reflects a significant signal for coupling between mangroves and external drivers.While the loss and gain of mangroves has received much attention,little information about how the horizontal structure of mangrove forests develops from the seedling stage to maturity has been presented.Here,remote sensing images taken over approximately 15 years,UVA images,nutrient elements,sediments,and Aegiceras corniculatum vegetation parameters of the ecological quadrats along the Nanliu Delta,the largest delta of the northern Beibu Gulf in China,are analyzed to reveal changes in the horizontal structure of mangroves and their associated driving factors.The results show that both discrete structures and agglomerated structures can often be found in A.corniculatum seedlings and saplings.However,the combination of seedlings growing into maturity and new seedlings filling in available gaps causes the discrete structure of A.corniculatum to gradually vanish and the agglomerate structure to become stable.The aggregated structure of seedlings,compared to the discrete structure,can enhance the elevation beneath mangroves by trapping significantly more sediments,providing available spaces and conditions for seedlings to continue growing.Furthermore,by catching fine sediments with enriched nutrients,the survival rate of A.corniculatum seedlings in the agglomerated structure can be much higher than that in the discrete structure.Our results highlight the significance of the agglomeration of A.corniculatum,which can be beneficial to coastal mangrove restoration and management.

Dramatical hydro-sedimentary changes induced by bamboo fences over mangrove tidal flat of the largest delta in Beibu Gulf, southwestern China

Mangrove forest is one of the most important ecological and environmental resources by effectively promoting tidal flat deposition and preventing the coastal region from typhoon.However,there have been mass loss of mangrove forests due to anthropogenic activities.It is an urgent need to explore an effective way for mangrove restoration.Here,three rows of bamboo fences with hydro-sedimentary observation set over Aegiceras corniculatum mangrove tidal flat of the Nanliu Delta,the largest delta of Beibu Gulf,China,were conducted to analyze the hydro-sedimentary variations induced by bamboo fences.Results identified that the mean horizontal velocity Um per burst(20 min)decreased by as much as 71%and 40%in comparison with those without bamboo fences in March and November,respectively,when the tidal current entering the bamboo area during flood.The maximum of mean horizontal flow velocity Um-max at bamboo area was 50%–75%of that without bamboo fences during ebb tide.The suspended sediment concentration of bamboo area suggested a maximum reduction of 57%relative to bare flat during flood,and was 80%lower than bare flat at ebb peak.Moreover,the turbulent kinetic dissipationεat flood tide was significantly higher than that at ebb tide,while the bamboo fences greatly increased the turbulent kinetic dissipationεby 2 to 5 times relative to bare flat,resulting in an increase of the bed elevation by inhibiting the sediment incipient motion and intercepting suspended sediment.The siltation rate at the bamboo area was 140%and 29.3%higher than that at the bare flat and the region covered with A.corniculatum,respectively.These results highlight that bamboo fences can effectively attenuate tidal current and thus promote siltation over mangrove flat,which contribute great benefit to mangrove survival.

Effects of substrate on burrowing behavior,feeding physiology,and energy budget of undulated surf clam Paphia undulata

Substrate is an important abiotic factor for burrowing shellfish,as it not only provides them with shelter,but also impose significant effect on their physiological metabolism.However,the physiological responses of burrowing clams within various substrates get less attention due to difficulty in carrying out physiological tests in buried conditions.Consequently,this study investigated the burrowing behavior,feeding physiology and energy budget of Paphia undulata,which is an important aquaculture bivalve species in south China.The clams were exposed to mud and sand substrates with variable physical properties in the laboratory,to determine the suitable substrate conditions for this species.The results showed that the percentage of burrowing clams,digging index,burrowing time,burrowing depth and scope for growth(SFG)were higher in mud substrates with≥40%water content.Likewise,burrowing percentage,digging index,and burrowing depths were higher in substrates with≤40%sand content.Moreover,the burrowing depth had significant effect on the feeding physiology and SFG of P.undulata as clams burrowed at 6.3±1.8 cm had higher clearance rates and SFG as compared to other buried depths.This study further revealed that low water content in the sediment inhibited physiological performances of P.undulata by impairing feeding or absorption,hence reducing the SFG.In conclusion,mud substrate with≥40%water content or with≤40%sand content is suitable for proper burrowing and growth of P.undulata.Our findings therefore provide fundamental knowledge that will be applicable in the improvement of bottom aquaculture and conservation of P.undulata.