一种改进Oriented RepPoints的遥感图像有向目标检测

为解决Oriented RepPoints算法在遥感图像有向目标检测中因遥感图像背景干扰信息较多和目标尺度大小不一所导致的检测精度不高、易漏检误检等问题,提出一种改进Oriented RepPoints的遥感图像有向目标检测方法MA-RPDet(Mixed Attention RepPoints Detector).首先,采用了PVTv2作为主干网络,该网络利用线性空间缩减自注意力机制提取出更具局部连续性的特征图,并保持与卷积运算类似的线性复杂度.其次,在特征融合阶段设计了串联性混合注意力模块,进一步强化了重要特征,促进了多尺度特征的高效交互.最后,引入平滑GIoU损失函数对模型学习策略进行优化,提高了检测精度.在两个遥感图像目标检测数据集DOTA和HRSC2016上的实验结果表明,所提方法的检测精度mAP分别达到了77.19%和90.3%,均高于其他对比算法,证明了本文方法的有效性.

基于改进Oriented R-CNN的旋转框麦穗检测与计数模型

为对干扰、遮挡等复杂的田野环境中麦穗进行精准定位与计数,该研究提出了一种改进的Oriented R-CNN麦穗旋转框检测与计数方法,首先在主干网络中引入跨阶段局部空间金字塔(spatial pyramid pooling cross stage partial networks,SPPCSPC)模块扩大模型感受野,增强网络感知能力;其次,在颈网络中结合路径聚合网络(PANet,path aggregation network)和混合注意力机制(E2CBAM,efficient two convolutional block attention module),丰富特征图包含的特征信息;最后采用柔性非极大值抑制算法(Soft-NMS,soft-non maximum suppression)优化预测框筛选过程。试验结果显示,改进的模型对复杂环境中的麦穗检测效果良好。相较原模型,平均精确度均值mAP提高了2.02个百分点,与主流的旋转目标检测模型Gliding vertex、R3det、Rotated Faster R-CNN、S2anet和Rotated Retinanet相比,mAP分别提高了4.99、2.49、3.94、2.25和4.12个百分点。该研究方法利用旋转框准确定位麦穗位置,使得框内背景区域面积大幅度减少,为实际观察麦穗生长状况和统计数量提供了一种有效的方法。

Three-dimensionally oriented organization of hexagonal MIL-96 microplates toward superior film microstructure

Preferential orientation control of metal—organic framework(MOF)films is advantageous for maximizing pore uniformity and minimizing grain-boundary defects.Nonetheless,the preparation of MOF films with both in-plane and out-of-plane orientations remains a grand challenge.In this study,we reported the preparation of three-dimensionally oriented MIL-96 layers through combining morphology control of MIL-96 seeds with addition of polyvinylpyrrolidone surfactants and arachidonic acids.The three-dimensionally oriented MIL-96 film was readily obtained through in-plane epitaxial growth.It is anticipated that the aforementioned protocol can be effective for obtaining diverse MOF films with a three-dimensionally oriented organization.

Self-assembly of perovskite nanocrystals:From driving forces to applications

Self-assembly of metal halide perovskite nanocrystals(NCs)into superlattices can exhibit unique collective properties,which have significant application values in the display,detector,and solar cell field.This review discusses the driving forces behind the self-assembly process of perovskite NCs,and the commonly used self-assembly methods and different self-assembly structures are detailed.Subsequently,we summarize the collective optoelectronic properties and application areas of perovskite superlattice structures.Finally,we conclude with an outlook on the potential issues and future challenges in developing perovskite NCs.

Alcohol solvent effect on the self-assembly behaviors of lignin oligomers

The interactions between lignin oligomers and solvents determine the behaviors of lignin oligomers self-assembling into uniform lignin nanoparticles(LNPs).Herein,several alcohol solvents,which readily interact with the lignin oligomers,were adopted to study their effects during solvent shifting process for LNPs’production.The lignin oligomers with widely distributed molecular weight and abundant guaiacyl units were extracted from wood waste(mainly consists of pine wood),exerting outstanding self-assembly capability.Uniform and spherical LNPs were generated in H_(2)O-n-propanol cosolvent,whereas irregular LNPs were obtained in H_(2)O-methanol cosolvent.The unsatisfactory self-assembly performance of the lignin oligomers in H_(2)O-methanol cosolvent could be attributed to two aspects.On one hand,for the initial dissolution state,the distinguishing Hansen solubility parameter and polarity between methanol solvent and lignin oligomers resulted in the poor dispersion of the lignin oligomers.On the other hand,strong hydrogen bonds between methanol solvent and lignin oligomers during solvent shifting process,hindered the interactions among the lignin oligomers for self-assembly.

Chitosan/Sodium Alginate Multilayer pH-Sensitive Films Based on Layer-by-Layer Self-Assembly for Intelligent Packaging

The abuse of plastic food packaging has brought about severe white pollution issues around the world.Developing green and sustainable biomass packaging is an effective way to solve this problem.Hence,a chitosan/sodium alginate-based multilayer film is fabricated via a layer-by-layer(LBL)self-assembly method.With the help of superior interaction between the layers,the multilayer film possesses excellent mechanical properties(with a tensile strength of 50 MPa).Besides,the film displays outstanding water retention property(blocking moisture of 97.56%)and ultraviolet blocking property.Anthocyanin is introduced into the film to detect the food quality since it is one natural plant polyphenol that is sensitive to the pH changes ranging from 1 to 13 in food when spoilage occurs.It is noted that the film is also bacteriostatic which is desired for food packaging.This study describes a simple technique for the development of advanced multifunctional and fully biodegradable food packaging film and it is a sustainable alternative to plastic packaging.

Hollow tubes constructed by carbon nanotubes self-assembly for CO_(2) capture

Carbon nanotubes(CNTs)have garnered significant attention in the fields of science,engineering,and medicine due to their numerous advantages.The initial step towards harnessing the potential of CNTs involves their macroscopic assembly.The present study employed a gentle and direct self-assembly technique,wherein controlled growth of CNT sheaths occurred on the metal wire’s surface,followed by etching of the remaining metal to obtain the hollow tubes composed of CNTs.By controlling the growth time and temperature,it is possible to alter the thickness of the CNTs sheath.After immersing in a solution containing 1 g/L of CNTs at 60℃ for 24 h,the resulting CNTs layer achieved a thickness of up to 60μm.These hollow CNTs tubes with varying inner diameters were prepared through surface reinforcement using polymers and sacrificing metal wires,thereby exhibiting exceptional attributes such as robustness,flexibility,air tightness,and high adsorption capacity that effectively capture CO_(2) from the gas mixture.

A Non-parametric Gradient-Based Shape Optimization Approach for Solving Inverse Problems in Directed Self-Assemblyof Block Copolymers

We consider the inverse problem of finding guiding pattern shapes that result in desired self-assembly morphologies of block copolymer melts.Specifically,we model polymer selfassembly using the self-consistent field theory and derive,in a non-parametric setting,the sensitivity of the dissimilarity between the desired and the actual morphologies to arbitrary perturbations in the guiding pattern shape.The sensitivity is then used for the optimization of the confining pattern shapes such that the dissimilarity between the desired and the actual morphologies is minimized.The efficiency and robustness of the proposed gradient-based algorithm are demonstrated in a number of examples related to templating vertical interconnect accesses(VIA).

Confined cobalt single-atom catalysts with strong electronic metal-support interactions based on a biomimetic self-assembly strategy

Designing high-performance and low-cost electrocatalysts for oxygen evolu-tion reaction(OER)is critical for the conversion and storage of sustainable energy technologies.Inspired by the biomineralization process,we utilized the phosphorylation sites of collagen molecules to combine with cobalt-based mononuclear precursors at the molecular level and built a three-dimensional(3D)porous hierarchical material through a bottom-up biomimetic self-assembly strategy to obtain single-atom catalysts confined on carbonized biomimetic self-assembled carriers(Co SACs/cBSC)after subsequent high-temperature annealing.In this strategy,the biomolecule improved the anchoring efficiency of the metal precursor through precise functional groups;meanwhile,the binding-then-assembling strategy also effectively suppressed the nonspecific adsorption of metal ions,ultimately preventing atomic agglomeration and achieving strong electronic metal-support interactions(EMSIs).Experimental characterizations confirm that binding forms between cobalt metal and carbonized self-assembled substrate(Co–O_(4)–P).Theoretical calculations disclose that the local environment changes significantly tailored the Co d-band center,and optimized the binding energy of oxygenated intermediates and the energy barrier of oxygen release.As a result,the obtained Co SACs/cBSC catalyst can achieve remarkable OER activity and 24 h durability in 1 M KOH(η10 at 288 mV;Tafel slope of 44 mV dec-1),better than other transition metal-based catalysts and commercial IrO_(2).Overall,we presented a self-assembly strategy to prepare transition metal SACs with strong EMSIs,providing a new avenue for the preparation of efficient catalysts with fine atomic structures.

Layer by Layer Self-assembly Fiber-based Flexible Electrochemical Transistor

Poly(3,4-ethylenedioxyethiophene)-polystyrene sulfonic acid(PEDOT:PSS)/polyallyl dimethyl ammonium chloride modified reduced graphene oxide(PDDA-rGO)was layer by layer self-assembled on the cotton fiber.The surface morphology and electric property was investigated.The results confirmed the dense membrane of PEDOT:PSS and the lamellar structure of PDDA-rGO on the fibers.It has excellent electrical conductivity and mechanical properties.The fiber based electrochemical transistor(FECTs)prepared by the composite conductive fiber has a maximum output current of 8.7 mA,a transconductance peak of 10 mS,an on time of 1.37 s,an off time of 1.6 s and excellent switching stability.Most importantly,the devices by layer by layer self-assembly technology opens a path for the true integration of organic electronics with traditional textile technologies and materials,laying the foundation for their later widespread application.

Oriented Bounding Box Object Detection Model Based on Improved YOLOv8

In the study of oriented bounding boxes(OBB)object detection in high-resolution remote sensing images,the problem of missed and wrong detection of small targets occurs because the targets are too small and have different orientations.Existing OBB object detection for remote sensing images,although making good progress,mainly focuses on directional modeling,while less consideration is given to the size of the object as well as the problem of missed detection.In this study,a method based on improved YOLOv8 was proposed for detecting oriented objects in remote sensing images,which can improve the detection precision of oriented objects in remote sensing images.Firstly,the ResCBAMG module was innovatively designed,which could better extract channel and spatial correlation information.Secondly,the innovative top-down feature fusion layer network structure was proposed in conjunction with the Efficient Channel Attention(ECA)attention module,which helped to capture inter-local cross-channel interaction information appropriately.Finally,we introduced an innovative ResCBAMG module between the different C2f modules and detection heads of the bottom-up feature fusion layer.This innovative structure helped the model to better focus on the target area.The precision and robustness of oriented target detection were also improved.Experimental results on the DOTA-v1.5 dataset showed that the detection Precision,mAP@0.5,and mAP@0.5:0.95 metrics of the improved model are better compared to the original model.This improvement is effective in detecting small targets and complex scenes.

Estimation of cancer cell migration in biomimetic random/oriented collagen fiber microenvironments

Increasing data indicate that cancer cell migration is regulated by extracellular matrixes and their surrounding biochemical microenvironment,playing a crucial role in pathological processes such as tumor invasion and metastasis.However,conventional two-dimensional cell culture and animal models have limitations in studying the influence of tumor microenvironment on cancer cell migration.Fortunately,the further development of microfluidic technology has provided solutions for the study of such questions.We utilize microfluidic chip to build a random collagen fiber microenvironment(RFM)model and an oriented collagen fiber microenvironment(OFM)model that resemble early stage and late stage breast cancer microenvironments,respectively.By combining cell culture,biochemical concentration gradient construction,and microscopic imaging techniques,we investigate the impact of different collagen fiber biochemical microenvironments on the migration of breast cancer MDA-MB-231-RFP cells.The results show that MDA-MB-231-RFP cells migrate further in the OFM model compared to the RFM model,with significant differences observed.Furthermore,we establish concentration gradients of the anticancer drug paclitaxel in both the RFM and OFM models and find that paclitaxel significantly inhibits the migration of MDA-MB-231-RFP cells in the RFM model,with stronger inhibition on the high concentration side compared to the low concentration side.However,the inhibitory effect of paclitaxel on the migration of MDA-MB-231-RFP cells in the OFM model is weak.These findings suggest that the oriented collagen fiber microenvironment resembling the late-stage tumor microenvironment is more favorable for cancer cell migration and that the effectiveness of anticancer drugs is diminished.The RFM and OFM models constructed in this study not only provide a platform for studying the mechanism of cancer development,but also serve as a tool for the initial measurement of drug screening.

Analysis of the Effect of Problem-Oriented Nursing Intervention on Patients with Lower Extremity Arteriosclerosis Obliterans in Vascular Surgery

Objective: To analyze the effect of problem-oriented nursing intervention on patients with lower extremity arteriosclerosis obliterans (ASO) in vascular surgery. Methods: The clinical data of 128 patients with lower extremity ASO in vascular surgery were selected and randomly divided into groups A and B, with 64 cases each. Group A is the control group, and Group B is the observation group. Group A received the routine nursing intervention, and Group B received the problem-oriented nursing intervention. The compliance, self-care ability, psychological state, quality of life, and nursing satisfaction of the two groups of patients were evaluated based on various indicators. Results: After the intervention, the evaluation of self-care ability (ESCA) score of the patients in Group B was higher than that of Group A, and the symptom checklist-90 (SCL-90) score was lower than that of Group A. The differences were significant (t = 10.019, t = 3.118, P < 0.01). After the intervention, the World Health Organization Quality of Life Brief (WHOQOL-BREF) index scores of the two groups increased and the increase in Group B was significantly higher than Group A (P < 0.001). The compliance rate of Group B (62/ 96.88%) was higher than that of Group A (52/ 81.25%), and the difference was extremely significant (χ2 = 8.020, P < 0.01). Conclusion: Problem-oriented nursing intervention for patients with lower extremity ASO in vascular surgery improved the patient’s self-care ability, and quality of life, reduced the patient’s negative emotions, and enhanced their overall satisfaction.

Intervention Effect of Lower Limb Rehabilitation Robot with Task-Oriented Training on Stroke Patients and Its Influence on KFAROM Score

Objective: To explore the effect of lower limb rehabilitation robot combined with task-oriented training on stroke patients and its influence on KFAROM score. Methods: 100 stroke patients with hemiplegia admitted to our hospital from January 2023 to December 2023 were randomly divided into two groups, the control group (50 cases) was given task-oriented training assisted by nurses, and the observation group (50 cases) was given lower limb rehabilitation robot with task-oriented training. Lower limb balance, lower limb muscle strength, motor function, ankle function, knee flexion range of motion and walking ability were observed. Results: After treatment, the scores of BBS, quadriceps femoris and hamstrings in the observation group were significantly higher than those in the control group (P Conclusion: In the clinical treatment of stroke patients, the combination of task-oriented training and lower limb rehabilitation robot can effectively improve the lower limb muscle strength, facilitate the recovery of balance function, and have a significant effect on the recovery of motor function, which can improve the walking ability of stroke patients and the range of motion of knee flexion, and achieve more ideal therapeutic effectiveness.

An Approach to Detect Structural Development Defects in Object-Oriented Programs

Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detection approaches, ranging from traditional heuristic algorithms to machine learning methods, are used to identify these defects. Ensemble learning methods have strengthened the detection of these defects. However, existing approaches do not simultaneously exploit the capabilities of extracting relevant features from pre-trained models and the performance of neural networks for the classification task. Therefore, our goal has been to design a model that combines a pre-trained model to extract relevant features from code excerpts through transfer learning and a bagging method with a base estimator, a dense neural network, for defect classification. To achieve this, we composed multiple samples of the same size with replacements from the imbalanced dataset MLCQ1. For all the samples, we used the CodeT5-small variant to extract features and trained a bagging method with the neural network Roberta Classification Head to classify defects based on these features. We then compared this model to RandomForest, one of the ensemble methods that yields good results. Our experiments showed that the number of base estimators to use for bagging depends on the defect to be detected. Next, we observed that it was not necessary to use a data balancing technique with our model when the imbalance rate was 23%. Finally, for blob detection, RandomForest had a median MCC value of 0.36 compared to 0.12 for our method. However, our method was predominant in Long Method detection with a median MCC value of 0.53 compared to 0.42 for RandomForest. These results suggest that the performance of ensemble methods in detecting structural development defects is dependent on specific defects.

Method of Establishing Object-Oriented System Structure for Decision Support System

In order to solve existing problems about the method of establishing traditional system structure of decision support system(DSS), O S chart is applied to describe object oriented system structure of general DSS, and a new method of eight specific steps is proposed to establish object oriented system structure of DSS by using the method of O S chart, which is applied successfully to the development of the DSS for the energy system ecology engineering research of the Wangheqiu country. Supplying many scientific effective computing models, decision support ways and a lot of accurate reliable decision data, the DSS plays a critical part in helping engineering researchers to make correct decisions. Because the period for developing the DSS is relatively shorter, the new way improves the efficiency of establishing DSS greatly. It also makes the DSS of system structure more flexible and easy to expand.

Structure-oriented edge-preserving smoothing based on accurate estimation of orientation and edges

In this paper, we present a new method for reducing seismic noise while preserving structural and stratigraphic discontinuities. Structure-oriented edge-preserving smoothing requires information such as the local orientation and edge of the reflections. The information is usually estimated from seismic data with full frequency bandwidth. When the data has a very low signal to noise ratio （SNR）, the noise usually reduces the estimation accuracy. For seismic data with extremely low SNR, the dominant frequency has higher SNR than other frequencies, so it can provide orientation and edge information more reliably than other frequencies. Orientation and edge are usually described in terms of apparent reflection dips and coherence differences, respectively. When frequency changes, both dip and coherence difference change more slowly than the seismogram itself. For this reason, dip and coherence estimated from dominant frequency data can approximately represent those of other frequency data. Ricker wavelet are widely used in seismic modeling. The Marr wavelet has the same shape as Ricker wavelets in both time and frequency domains, so the Marr wavelet transform is selected to divide seismic data into several frequency bands. Reflection apparent dip as well as the edge information can be obtained by scanning the dominant frequency data. This information can be used to selectively smooth the frequency bands （dominant, low, and high frequencies） separately by structure-oriented edge-preserving smoothing technology. The ultimate noise-suppressed seismic data is the combination of the smoothed frequency band data. Application to synthetic and real data shows the method can effectively reduce noise, preserve edges, improve trackable reflection continuity, and maintain useful information in seismic data.

一种基于组件的aspect-oriented编程框架

面向方面的编程(AOP:aspect-oriented programming)是一种新的编程技术.它引进了aspect,将影响多个模块的行为封装到一个可重用模块中,允许程序员对横切(crosscutting concerns)进行模块化,从而消除了面向对象编程(OOP:object-oriented programming)引起的代码混乱和分散问题.本文讨论了在服务体模型上实现的一种aspect-oriented编程框架.这个编程框架使用aspect组件,定义了对OOP语言的扩展,可方便将模块化的aspect代码扩展到源程序中,解决了OOP模型在这方面的不足.

Modeling of Intelligent Integrated Network Management System Using Object Oriented Approach *

The concept of intelligent integrated network management (IINM) is briefly introduced. In order to analyze, design and implement IINM successfully, object oriented approach is testified to be an effective and efficient way. In this paper, object oriented technique is applied to the structural model of IINM system, The Domain object class and the MU object class are used to represent the manager and the managed resources. Especially, NM IA is introduced which is a special object class with intelligent behaviors to manage the resources efficiently.

Oriented quantum coalgebra structure on the tensor product of an oriented quantum coalgebra with itself

Oriented quantum algebras （coalgebras） are generalizations of quasitriangular Hopf algebras （coquasitriangular Hopf algebras） and account for regular isotopy invariants of oriented 1-1 tangles, oriented knots and links. Let （H, or, D, U） be an oriented quantum coalgebra over the field k. Then （H×H, φ, D×D, U× U） is a trivial oriented quantum coalgebra structure on the tensor product of coalgebra H with itself, where φ （a × b, c × d） = σ-（ a, c）σ （b, d）. This paper presents the oriented quantum coalgebra structure （ H×H, σ, D×D, U× U） on coalgebra H× H, where σ（ a × b, c× d） = σ ^-1 （ d1, a1 ） σ（ a2, c1 ） σ^-1 （ d2, b1 ） σ（ b2, c2 ）. So a nontrivial oriented quantum coalgebra structure is obtained and it is dual to Radford＇s results in the paper ＂On the tensor product of an oriented quantum algebra with itself＂ published in 2007. Theoretically, the results of this paper are important in constructing the invariants of oriented knots and links.