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.

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.

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.

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.

Accelerated Sequential Deposition Reaction via Crystal Orientation Engineering for Low-Temperature,High-Efficiency Carbon-Electrode CsPbBr_(3) Solar Cells

Low-temperature,ambient processing of high-quality CsPbBr_(3)films is demanded for scalable production of efficient,low-cost carbon-electrode perovskite solar cells(PSCs).Herein,we demonstrate a crystal orientation engineering strategy of PbBr_(2)precursor film to accelerate its reaction with CsBr precursor during two-step sequential deposition of CsPbBr_(3)films.Such a novel strategy is proceeded by adding CsBr species into PbBr_(2)precursor,which can tailor the preferred crystal orientation of PbBr_(2)film from[020]into[031],with CsBr additive staying in the film as CsPb_(2)Br_(5)phase.Theoretical calculations show that the reaction energy barrier of(031)planes of PbBr_(2)with CsBr is lower about 2.28 eV than that of(O2O)planes.Therefore,CsPbBr_(3)films with full coverage,high purity,high crystallinity,micro-sized grains can be obtained at a low temperature of 150℃.Carbon-electrode PSCs with these desired CsPbBr_(3)films yield the record-high efficiency of 10.27%coupled with excellent operation stability.Meanwhile,the 1 cm^(2)area one with the superior efficiency of 8.00%as well as the flexible one with the champion efficiency of 8.27%and excellent mechanical bending characteristics are also achieved.

Alleviating the anisotropic microstructural change and boosting the lithium ions diffusion by grain orientation regulation for Ni-rich cathode materials

Generally,layered Ni-rich cathode materials exhibit the morphology of polycrystalline secondary sphere composed of numerous primary particles.While the arrangement of primary particles plays a very important role in the properties of Ni-rich cathodes.The disordered particle arrangement is harmful to the cyclic performance and structural stability,yet the fundamental understanding of disordered structure on the structural degradation behavior is unclarified.Herein,we have designed three kinds of LiNi_(0.83)Co_(0.06)Mn_(0.11)O_(2) cathode materials with different primary particle orientations by regulating the precursor coprecipitation process.Combining finite element simulation and in-situ characterization,the Li^(+)transport and structure evolution behaviors of different materials are unraveled.Specifically,the smooth Li^(+)diffusion minimizes the reaction heterogeneity,homogenizes the phase transition within grains,and mitigates the anisotropic microstructural change,thereby modulating the crack evolution behavior.Meanwhile,the optimized structure evolution ensures radial tight junctions of the primary particles,enabling enhanced Li^(+)diffusion during dynamic processes.Closed-loop bidirectional enhancement mechanism becomes critical for grain orientation regulation to stabilize the cyclic performance.This precursor engineering with particle orientation regulation provides the useful guidance for the structural design and feature enhancement of Ni-rich layered cathodes.

Laser-Constructing 3D Copper Current Collector with Crystalline Orientation Selectivity for Stable Lithium Metal Batteries

The practical application of lithium(Li)metal anodes in high-capacity batteries is impeded by the formation of hazardous Li dendrites.To address this challenge,this research presents a novel methodology that combines laser ablation and heat treatment to precisely induce controlled grain growth within laser-structured grooves on copper(Cu)current collectors.Specifically,this approach enhances the prevalence of Cu(100)facets within the grooves,effectively lowering the overpotential for Li nucleation and promoting preferential Li deposition.Unlike approaches that modify the entire surface of collectors,our work focuses on selectively enhancing lithiophilicity within the grooves to mitigate the formation of Li dendrites and exhibit exceptional performance metrics.The half-cell with these collectors maintains a remarkable Coulombic efficiency of 97.42%over 350 cycles at 1 mA cm^(−2).The symmetric cell can cycle stably for 1600 h at 0.5 mA cm^(−2).Furthermore,when integrated with LiFePO4 cathodes,the full-cell configuration demonstrates outstanding capacity retention of 92.39%after 400 cycles at a 1C discharge rate.This study introduces a novel technique for fabricating selective lithiophilic three-dimensional(3D)Cu current collectors,thereby enhancing the performance of Li metal batteries.The insights gained from this approach hold promise for enhancing the performance of all laser-processed 3D Cu current collectors by enabling precise lithiophilic modifications within complex structures.

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.

An Expert System to Detect Political Arabic Articles Orientation Using CatBoost Classifier Boosted by Multi-Level Features

The number of blogs and other forms of opinionated online content has increased dramatically in recent years.Many fields,including academia and national security,place an emphasis on automated political article orientation detection.Political articles(especially in the Arab world)are different from other articles due to their subjectivity,in which the author’s beliefs and political affiliation might have a significant influence on a political article.With categories representing the main political ideologies,this problem may be thought of as a subset of the text categorization(classification).In general,the performance of machine learning models for text classification is sensitive to hyperparameter settings.Furthermore,the feature vector used to represent a document must capture,to some extent,the complex semantics of natural language.To this end,this paper presents an intelligent system to detect political Arabic article orientation that adapts the categorical boosting(CatBoost)method combined with a multi-level feature concept.Extracting features at multiple levels can enhance the model’s ability to discriminate between different classes or patterns.Each level may capture different aspects of the input data,contributing to a more comprehensive representation.CatBoost,a robust and efficient gradient-boosting algorithm,is utilized to effectively learn and predict the complex relationships between these features and the political orientation labels associated with the articles.A dataset of political Arabic texts collected from diverse sources,including postings and articles,is used to assess the suggested technique.Conservative,reform,and revolutionary are the three subcategories of these opinions.The results of this study demonstrate that compared to other frequently used machine learning models for text classification,the CatBoost method using multi-level features performs better with an accuracy of 98.14%.

Construction of Oriented Structure in Inner Surface of Small-Diameter Artificial Blood Vessels:A Review

There is an urgent need for small-diameter artificial blood vessels in clinic.Physical,chemical and biological factors should be integrated to avoid thrombosis and intimal hyperplasia after implantation and to promote successful fabrication of small-diameter artificial blood vessels.From a physical perspective,the internal oriented structures of natural blood vessels plays an important role in guiding the directional growth of cells,improving the blood flow environment,and promoting the regeneration of vascular tissue.In this review,the effects of the oriented structures on cells,including endothelial cells(ECs),smooth muscle cells(SMCs)and stem cells,as well as the effect of the oriented structures on hemodynamics and vascular tissue remodeling and regeneration are introduced.Various forms of oriented structures(fibers,grooves,channels,etc.)and their construction methods are also reviewed.Conclusions and future perspectives are given.It is expected to give some references to relevant researches.

Integrating Virtual Reality and Energy Analysis with BIM to Optimize Window-to-Wall Ratio and Building’s Orientation for Age-in-Place Design at the Conceptual Stage

This study unfolds an innovative approach aiming to address the critical role of building design in global energy consumption, focusing on optimizing the Window-to-Wall Ratio (WWR), since buildings account for approximately 30% of total energy consumed worldwide. The greatest contributors to energy expenditure in buildings are internal artificial lighting and heating and cooling systems. The WWR, determined by the proportion of the building’s glazed area to its wall area, is a significant factor influencing energy efficiency and minimizing energy load. This study introduces the development of a semi-automated computer model designed to offer a real-time, interactive simulation environment, fostering improving communication and engagement between designers and owners. The said model serves to optimize both the WWR and building orientation to align with occupants’ needs and expectations, subsequently reducing annual energy consumption and enhancing the overall building energy performance. The integrated model incorporates Building Information Modeling (BIM), Virtual Reality (VR), and Energy Analysis tools deployed at the conceptual design stage, allowing for the amalgamation of owners’ inputs in the design process and facilitating the creation of more realistic and effective design strategies.

Exploring heteroepitaxial growth and electrical properties of α-Ga_(2)O_(3) films on differently oriented sapphire substrates

This study explores the epitaxial relationship and electrical properties of α-Ga_(2)O_(3) thin films deposited on a-plane, mplane, and r-plane sapphire substrates. We characterize the thin films by X-ray diffraction and Raman spectroscopy, and elucidate thin film epitaxial relationships with the underlying sapphire substrates. The oxygen vacancy concentration of α-Ga_(2)O_(3) thin films on m-plane and r-plane sapphire substrates are higher than α-Ga_(2)O_(3) thin film on a-plane sapphire substrates. All three thin films have a high transmission of over 80% in the visible and near-ultraviolet regions, and their optical bandgaps stay around 5.02–5.16 eV. Hall measurements show that the α-Ga_(2)O_(3) thin film grown on r-plane sapphire has the highest conductivity of 2.71 S/cm, which is at least 90 times higher than the film on a-plane sapphire. A similar orientation-dependence is seen in their activation energy as revealed by temperature-dependent conductivity measurements, with 0.266, 0.079, and 0.075eV for the film on a-, m-, r-plane, respectively. The origin of the distinct transport behavior of films on differently oriented substrates is suggested to relate with the distinct evolution of oxygen vacancies at differently oriented substrates. This study provides insights for the substrate selection when growing α-Ga_(2)O_(3) films with tunable transport properties.

Object-Oriented Modeling of the Variation of Acceleration and Deceleration Characteristics in Relation to Speed Bands for Railway Vehicles

Automated operation and artificial intelligence technology have become essential for ensuring the safety, efficiency, and punctuality of railways, with applications such as ATO (Automatic Train Operation). In this study, the authors propose a method to efficiently simulate the kinematic characteristics of railroad vehicles depending on their speed zone. They utilized the function overloading function supported by a programming language and applied the fourth-order Lunge-Kutta method for dynamic simulation. By constructing an object model, the authors calculated vehicle characteristics and TPS and compared them with actual values, verifying that the developed model represents the real-life vehicle characteristics accurately. The study highlights potential improvements in automated driving and energy consumption optimization in the railway industry.

Integration of Transport and Land Use Planning by Transit-Oriented Development for Economic Sustainability of the Standard Gauge Railway Projects in Tanzania

Tanzania is one of the countries in Africa that has engaged in the projects for construction of the electrified Standard Gauge Railway (SGR). However, lack of integration of transportation and land-use planning threatens economic sustainability of the SGR project. This study was carried out for the purpose of finding-out how transportation can be integrated with land-use planning for economic sustainability of the project. The study was carried-out by using qualitative research approach through demonstration as case study. Findings show that construction of the SGR is not integrated with land-use planning around the stations and along the SGR corridor. It is concluded that economic sustainability of the SGR projects can be achieved by integration of transport and land-use planning. As demonstrated, it is recommended to deliberate for integration of transportation and land-use planning in the SGR projects of which the prime land within Transit Stations can be efficiently used by using Transit Oriented Development and secure more land for production activities around the Transit Stations and along the SGR corridor.

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.

基于SPI-RRV指数中国气象干旱及其风险时空演变特征研究

为全面揭示变化环境下我国多维气象干旱特征,耦合气象干旱指数(SPI)和可靠性-回弹性-脆弱性(RRV)指数,提出了一种基于SPI-RRV指数的干旱风险评价方法,定量评价了中国气象干旱及其风险的时空演变特征。结果表明:SPI-RRV指数具有特征稳定和时空可比性强的特点,能够较为准确地评估气象干旱风险时空演变特征;南方平均干旱栅格比、干旱月占比和频次大于北方,湿润区和半湿润区干旱历时短、烈度大,半干旱区和干旱区干旱历时长、烈度相对较小;干旱高风险区转移具有显著年代际变化规律,空间上从西北向西南地区转移。