Dense Groups Research Articles

A Multi-Active and Multi-Passive Sensor Fusion Algorithm for Multi-Target Tracking in Dense Group Clutter Environments

Multi-target tracking (MTT) of multi-active and multi-passive sensor (MAMPS) systems in dense group clutter environments is facing significant challenges in measurement fusion. Due to the difference in measurement information characteristics in MAMPS fusion, it is difficult to effectively correlate and fuse different types of sensors’ measurements, leading to difficulty in taking full advantage of various types of sensors to improve target tracking accuracy. To this end, we present a novel MAMPS fusion algorithm, which is based on centralized measurement association fusion (MAF) and distributed deep neural network (DNN) track fusion, named the MAMPS-MAF-DNN algorithm. Firstly, to reduce the impact of the dense group clutter, a clutter pre-processing algorithm is elaborated, which combines the advantages of the CFDP (cluster by finding density peaks) and double threshold screening algorithms. Then, for the single-active and multi-passive sensor (SAMPS) system, a centralized MAF algorithm based on angle information is developed, called the SAMPS-MAF algorithm. Finally, the SAMPS-MAF algorithm is extended to the MAMPS system within the DNN framework, and the complete MAMPS-MAF-DNN algorithm is proposed. Experimental results indicate that, compared to the existing MAF and covariance intersection (CI) fusion algorithms, the proposed MAMPS-MAF-DNN algorithm can fully combine the advantages of multi-active and multi-passive sensors, efficiently reduce the computational complexity, and obviously improve the tracking accuracy.

Synthesis of an Ag-based metal–organic framework for effective capture of iodine pollutants

The effective capture of radioiodine exhausted from nuclear power plants, is of paramount importance for the radioactivity control and remediation tasks. Herein, a robust metal–organic framework Ag-Tipe integrating with open Ag+ metal sites and imidazole groups is designed for efficient capture of I2 and CH3I. The dense imidazolium groups are expected to interact with the I2 through charge transfer, enhancing the binding affinity and trapping CH3I as a reactant in the methylation reaction. In addition, the fully open silver metal center in Ag-Tipe can coordinate with iodine species to form AgI. Therefore, the Ag-Tipe exhibits high I2 and CH3I uptake capacities of 3.31 and 0.55 g/g at 75 °C, respectively. The density functional theory (DFT) calculations reveal that the I2 and CH3I binding energy at different sites in Ag-Tipe follows the order Ag > imidazole > benzene ring. This work demonstrates the important role of the binding site of the adsorbent in achieving high I2/CH3I trapping performance.

Fast unfolding of communities in large networks: 15 years later

Abstract The Louvain method was proposed 15 years ago as a heuristic method for the fast detection of communities in large networks. During this period, it has emerged as one of the most popular methods for community detection: the task of partitioning vertices of a network into dense groups, usually called communities or clusters. Here, after a short introduction to the method, we give an overview of the different generalizations, modifications and improvements that have been proposed in the literature, and also survey the quality functions, beyond modularity, for which it has been implemented. Finally, we conclude with a discussion on the limitations of the method and perspectives for future research.

LRSDet: lightweight remote sensing target detection network with local-global information awareness and rapid sample assignment

Abstract With the rapid development of aerospace and unmanned aerial vehicles, using neural networks for object detection in optical remote sensing images (O-RSI) has encountered heightened challenges. The optical remote sensing images have the characteristics of complex geometric scenes, dense groups of objects, and significant multi-scale variations of objects; researchers need to use more complex models to achieve higher accuracy. However, this complexity also brings challenges to the application of lightweight scenes. Therefore, to cope with the trade-off challenge between model complexity and detection accuracy, we propose a lightweight network model LRSDet in this study. The model integrates local and global information processing mechanisms and introduces a fast positive sample assignment strategy to adapt to resource-constrained embedded and mobile platforms. By constructing a lightweight feature extraction network and a lightweight path aggregation network and incorporating the ESM-Attention module, the feature extraction capability of the model in complex remote sensing scenarios is significantly improved. In addition, the application of a dynamic soft threshold strategy further optimizes the positive sample selection process and improves the detection efficiency of the model. Experimental on the O-RSI datasets DIOR, NWPU VHR-10, and RSOD, while analyzing model real-time performance on aerial video and embedded devices, outperforming other state-of-the-art methods.

High-performance proton exchange membrane derived from N-heterocycle poly(aryl ether sulfone)s with ether-free hydrophilic blocks and exhibiting good stability and proton-conducting performance

The trade-off issue between proton conduction properties and stability is a constraint on the commercial application of non-fluorinated proton exchange membranes for fuel cells. To alleviate the issue, the multi-block N-heterocycle poly(aryl ether sulfone)s with ether-free hydrophilic blocks (b-SPDPESs), which is composited by diphenyl sulfone moieties and biphthalazindione structures with dense pendant benzenesulfonic groups, are developed to prepare high-performance membranes. The self-assembly effect of block copolymers not only improves the membrane stability but also constructs regular proton conduction channels. Moreover, the conduction channel consists of hydrophilic blocks without ether bonds, which effectively improves the tolerance of the membrane to radicals. The hydrogen-bond network between sulfonic groups and N-heterocycles in the channel improves the proton conduction efficiency, inhibits the swelling of the membrane, and improves the stability of the membrane. As a result, the swelling degree of b-SPDPESs membrane is only 15.8 %, the proton conductivity is as high as 238 mS cm−1, the membrane aging broken time at 80 °C is between 4 and 6.6 h, and the fuel cells loading the membranes and feeding with hydrogen and air perform the max power density of between 0.65 and 1.25 W cm−2. Modulating the sequence structure of chains and constructing multiblock polymers containing ether-free N-heretrocyclic blocks with sulfonic groups improve the stability of membranes while ensuring their proton conductivity.

UAV Swarm Target Identification and Quantification Based on Radar Signal Independency Characterization

Radar surveillance of noncooperative UAV swarm is challenging and is involved in many critical surveillance scenarios. The multimodality property of dynamic UAV swarm targets presents larger radar signature complexity and elevates the radar detection difficulty. The swarm unit number ambiguity from dense UAV grouping also inhibits radar monitoring accuracy. Inspired by the coherent integration essence of swarm target signals, this paper proposes a radar signal processing framework based on complex valued independent component analysis (cICA) for swarm target identification and quantification. The target detection threshold is determined from pure clutter signals after cICA processing. A customized clustering algorithm is applied on independent components for swarm target quantification. Target detection and quantification methods are verified with various multimodality UAV swarm flight plans. The results indicate that the detection performance of the proposed method is comparable with conventional CFAR algorithms with better stability performance. The target quantification procedure could estimate swarm unit numbers with acceptable numerical deviations. More discussions are given on the relevance between quantification accuracy and swarm configurations with respect to signal independency mechanisms. Efficiency discussions reveal the bottleneck of the proposed method for future optimization works.

Evaluation of droplet deposition parameters based on the Genetic-Otsu algorithm.

Pesticide spraying is a cost-effective way to control crop pests and diseases. The effectiveness of this method relies on the deposition and distribution of the spray droplets within the targeted application area. There is a critical need for an accurate and stable detection algorithm to evaluate the liquid droplet deposition parameters on the water-sensitive paper (WSP) and reduce the impact of image noise. This study acquired 90 WSP samples with diverse coverage through field spraying experiments. The droplets on the WSP were subsequently isolated, and the coverage and density were computed, employing the fixed threshold method, the Otsu threshold method, and our Genetic-Otsu threshold method. Based on the benchmark of manually measured data, an error analysis was conducted on the accuracy of three methods, and a comprehensive evaluation was carried out. The relative error results indicate that the Genetic-Otsu method proposed in this research demonstrates superior performance in detecting droplet coverage and density. The relative errors of droplet density in the sparse, medium, and dense droplet groups are 2.7%, 1.5%, and 2.0%, respectively. The relative errors of droplet coverage are 1.5%, 0.88%, and 1.2%, respectively. These results demonstrate that the Genetic-Otsu algorithm outperforms the other two algorithms. The proposed algorithm effectively identifies small-sized droplets and accurately distinguishes the multiple independent contours of adjacent droplets even in dense droplet groups, demonstrating excellent performance. Overall, the Genetic-Otsu algorithm offered a reliable solution for detecting droplet deposition parameters on WSP, providing an efficient tool for evaluating droplet deposition parameters in UAV pesticide spraying applications.

Dense pedestrian face detection in complex environments

To address the problem of dense crowd face detection in complex environments, this paper proposes a face detection model named Deep and Compact Face Detection (DCFD), which adopts an improved lightweight EfficientNetV2 network to replace the backbone network of RetinaFace. A large kernel attention mechanism is introduced to address the face detection task more accurately. The backbone network, an improved efficient channel attention (ECA) mechanism, is added to further improve the algorithm performance. The feature fusion module is an improved neural architecture search feature pyramid network (NAS-FPN) that significantly improves the face detection accuracy in different scenes. To balance the training process of positive and negative samples, we use the focus loss function to replace the traditional cross-entropy loss function. In different environments, the DCFD algorithm has shown efficient face detection performance. This algorithm provides not only a feasible and effective solution for solving the problem of face detection in dense groups but also an important basis for improving the accuracy of face detection models in practical applications.

GAP: A group-based automatic pruning algorithm via convolution kernel fusion

In recent years, the deployment and operation of convolution neural networks on edge devices with limited computing capabilities have become increasingly challenging due to the large network structure and computational cost. Currently, the mainstream structured pruning algorithms mainly compress the network at the filter or layer level. However, these methods introduce too much human intervention with large granularities, which may lead to unpredictable performance after compression. In this paper, we propose a group-based automatic pruning algorithm(GAP) via kernel fusion to automatically search for the optimal pruning structure in a more fine-grained manner. Specifically, we first adopt a novel nonlinear dimensionality reduction clustering algorithm to divide the filters of each convolution layer into groups of equal size. Afterwards, we encode the mutual distribution similarity of the kernels within each group, and its KL divergence is employed as an importance indicator to determine the retained kernel groups through weighted fusion. Subsequently, we introduce an intelligent searching module that automatically explore and optimize the pruned structure of each layer. Finally, the pruned filters are permutated to form a dense group convolution and fine-tuned. Sufficient experiments show that, on two image classification datasets, for five advanced CNN models, our GAP algorithm outperforms most extant SOTA schemes, reduces artificial intervention, and enables efficient end-to-end training of compact models.

Three‐Component Allylic Alkylation Reaction of α‐Diazo Ketones with Water and Allyl Carbonates for Construction of Homoallylic Alcohols

AbstractA three‐component allylic alkylation reaction of α‐diazo ketones, water and allyl carbonate under the cooperative catalysis of Rh2(OAc)4, Pd2(dba)3 and Brønsted acid was disclosed. This method provides an expeditious access to α‐keto homoallylic alcohols in good to high yields. Controlled experiments support that the transformations proceed through cross‐interception of two active intermediates Pd‐allyl species and enol intermediates derived from oxonium ylides. Moreover, synthetic transformations of the generated products enable the creation of motifs enriched with dense functional groups, underscoring their potential as valuable building blocks.

Relationship between Volpara Density Grade and Compressed Breast Thickness in Japanese Patients with Breast Cancer.

High breast density found using mammographs (MGs) reduces positivity rates and is considered a risk factor for breast cancer. Research on the relationship between Volpara density grade (VDG) and compressed breast thickness (CBT) in the Japanese population is still lacking. Moreover, little attention has been paid to pseudo-dense breasts with CBT < 30 mm among high-density breasts. We investigated VDG, CBT, and apparent high breast density in patients with breast cancer. Women who underwent MG and breast cancer surgery at our institution were included. VDG and CBT were measured. VDG was divided into a non-dense group (NDG) and a dense group (DG). This study included 419 patients. VDG was negatively correlated with CBT. The DG included younger patients with lower body mass index (BMI) and thinner CBT. In the DG, patients with CBT < 30 mm had lower BMI and higher VDG; however, no significant difference was noted in the positivity rate of the two groups. Younger women tend to have higher breast density, resulting in thinner CBT, which may pose challenges in detecting breast cancer on MGs. However, there was no significant difference in the breast cancer detection rate between CBT < 30 mm and CBT ≥ 30 mm.

Weak dimension of power series rings over valuation rings

We examine the power series ring R[[X]] over a valuation ring R of rank 1, with proper, dense value group. We give a counterexample to Hilbert's syzygy theorem for R[[X]], i.e. an R[[X]]-module C that is flat over R and has flat dimension at least 2 over R[[X]], contradicting a previously published result. The key ingredient in our construction is an exploration of the valuation theory of R[[X]]. We also use this theory to give a new proof that R[[X]] is not a coherent ring, a fact which is essential in our construction of the module C.

Integrating and Dividing in a Late Bronze Age Society: Internal Organization of Settlements of the Tisza Site Group in the Southern Carpathian Basin, 1600–1200 b.c.

ABSTRACT Recent research in the later Bronze Age of the southern Carpathian Basin has revealed an extensive network of large, often-enclosed settlements. Within this network, a particularly dense group of sites has recently been characterized: the Tisza Site Group (TSG). Building on advances in inter-site relations in recent research, we explore social organization within settlements using five case studies from different parts of this network. Using a multi-proxy approach of satellite imagery, systematic surface survey, and geophysical prospection, we studied the distribution of archaeological features and surface traces of activity within the enclosed space. Results indicate that sites in the TSG shared a common ethos regarding the use of space and the role of the built environment that was specific to LBA occupation of this landscape. Activity areas with domestic assemblages distributed in low-density relative to the enclosed space indicates settlement and specialist subsistence activities took place in parallel.

P-183 Cleavage patterns combined with fusion status at the compacting stage contribute to the selective single blastocyst transplantation

Abstract Study question To investigate the impact of various cleavage patterns combined with fusion status at the compacting stage on the chromosome ploidy of blastocysts and possible reasons. Summary answer It can be inferred that in single blastocyst transfer without PGT-A, the normal cleavage incomplete compacted embryo can be selected as a last resort. What is known already Previous research has shown that embryos with abnormal cleavage patterns possess lower developmental potential; however, once a blastocyst is formed, its chromosomal euploidy is not necessarily inferior to that of embryos with normal cleavage. It is possible that these embryos undergo self-repair through unfused cells during the compactification stage. The question remains: what is the chromosomal ploidy of embryos with normal cleavage that have unfused cells or fragments at the compacting stage? Is it similar to the chromosomal ploidy of embryos with abnormal cleavage that have unfused cells at the compacting stage? This study aims to provide clarity. Study design, size, duration We conducted a retrospective analysis on 600 PGT-A cycles at our reproductive center from January 2020 to August 2022. A total of 2,250 blastocysts that underwent biopsy and PGT-A testing were included in our analysis. Of these, 475 blastocysts underwent single blastocyst transfer. Participants/materials, setting, methods We classified the embryos into four groups based on their cleavage patterns and fusion status at the compacting stage: normal cleavage complete compacting group (n = 1128), normal cleavage incomplete compacting group (n = 735), abnormal cleavage incomplete compacting group (n = 371), and abnormal cleavage complete compacting group (n = 16). We compared the chromosomal ploidy of four groups, as well as the composition of aneuploidy. We also compared live birth outcomes among the four groups following euploidy thawed single blastocyst transfer. Main results and the role of chance The chromosomal euploidy rates were 55.59%, 50.61%, 59.57%, and 62.5% in the normal cleavage complete compacting group, normal cleavage incomplete compacting group, abnormal cleavage incomplete compacting group, and abnormal cleavage complete compacting group, respectively. There was a significant difference in euploidy rates between the normal cleavage incomplete dense group and the abnormal cleavage incomplete dense group (P = 0.026). Additionally, there was a significant difference in chromosome deletion rates in abnormal chromosomes between the normal cleavage incomplete compacting group (23.95%) and the abnormal cleavage incomplete compacting group (15.63%) (P = 0.005). When thawing and transferring euploid single blastocysts, there was no significant difference in live birth outcomes among the four groups (P = 0.984).In early normal cleavage embryos, if there are unfused cells or fragments at the compacting stage, the ratio of chromosomal abnormalities increases, possibly due to chromosomal loss during the compacting stage. In contrast, abnormal cleavage embryos had an increased euploidy rate once they formed usable blastocysts. The live birth outcomes of abnormal cleavage diploid blastocysts are comparable to those of normal cleavage diploid blastocysts. Limitations, reasons for caution The limitation of this study is a retrospective study with a small sample size. The conclusions of the studies need to be validated in larger-scale prospective studies. Wider implications of the findings Embryologists prefer normal cleavage embryos over abnormal cleavage embryos, and this study found that the low euploidy ratio of normal cleavage incomplete compacting embryos can help guide the screening of single blastocyst transfer without PGT-A. Trial registration number not applicable

Dense tumor‐infiltrating lymphocytes (TILs) in liver metastasis from colorectal cancer are related to improved overall survival

AbstractBackground and ObjectivesTumor‐infiltrating lymphocytes (TILs) represent a host‐tumor interaction, frequently signifying an augmented immunological response. Nonetheless, implications with survival outcomes in patients with colorectal carcinoma liver metastasis (CRLM) warrant rigorous validation. The objective was to demonstrate the association between TILs and survival in patients with CRLM.MethodIn a retrospective evaluation conducted in a single institution, we assessed all patients who underwent hepatectomy due to CRLM between 2014 and 2018. Comprehensive medical documentation reviews were executed. TILs were assessed by a liver pathologist, blinded to the clinical information, in all surgical slides.ResultsThis retrospective cohort included 112 patients. Median overall survival (OS) was 58 months and disease‐free survival (DFS) was 12 months for the entire cohort. Comparison between groups showed a median OS of 81 months in the dense TILs group and 40 months in the weak/absent group (p = 0.001), and DFS was 14 months versus 9 months (p = 0.041). Multivariable analysis showed that TILs were an independent predictor of OS (HR 1.95; p = 0.031).ConclusionsDense TILs are a pivotal prognostic indicator, correlating with enhanced OS. Including TILs information in histopathological evaluations should refine the clinical decision‐making process for this group of patients.

Self-organized vortex phases and hydrodynamic interactions in Bos taurus sperm cells.

Flocking behavior is observed in biological systems from the cellular to superorganismal length scales, and the mechanisms and purposes of this behavior are objects of intense interest. In this paper, we study the collective dynamics of bovine sperm cells in a viscoelastic fluid. These cells appear not to spontaneously flock, but transition into a long-lived flocking phase after being exposed to a transient ordering pulse of fluid flow. Surprisingly, this induced flocking phase has many qualitative similarities with the spontaneous polar flocking phases predicted by Toner-Tu theory, such as anisotropic giant number fluctuations and nontrivial transverse density correlations, despite the induced nature of the phase and the clearly important role of momentum conservation between the swimmers and the surrounding fluid in these experiments. We also find a self-organized global vortex state of the sperm cells, and map out an experimental phase diagram of states of collective motion as a function of cell density and motility statistics. We compare our experiments with a parameter-matched computational model of persistently turning active particles and find that the experimental order-disorder phase boundary as a function of cell density and persistence time can be approximately predicted from measures of single-cell properties. Our results may have implications for the evaluation of sample fertility by studying the collective phase behavior of dense groups of swimming sperm.

Standing balance recovery strategies of young adults in a densely populated environment following external perturbations

The recovery strategies used by young adults to maintain standing balance following external force-controlled perturbations in densely populated group formations was investigated in this work. In particular, the moment of step initiation as well and the characteristics of the first recovery steps and hand-raising were studied here. The experimental data considered in this work are part of a larger dataset relying on a new experimental paradigm inspired by Feldmann and Adrian (2023). In this experiment, 20 participants (8 females, 12 males, 24.8±3.7yo) equipped with motion capture suits were asked to stand in tightly packed formation before receiving a force-controlled perturbation. In total, four group configurations and two interpersonal distancing conditions have been investigated here. The standing balance recovery strategies observed in this dense groups experiment were then compared with the observed behaviour of single individuals following external perturbations (Chatagnon et al., 2023). Results suggest that the moment of initiation for recovery steps was affected by the initial interpersonal distancing conditions. The first recovery steps within the studied dense groups were observed to be slower, smaller and more dispersed than those of single individuals for comparable level of perturbation intensity. However, the relationship between the average speed of first recovery steps and the length of these steps remained similar to the one of single individuals. This suggests that the first recovery step duration remained almost constant during both the dense groups experiment and the experiment with single individuals. Finally, we observed a significant occurrence of participants raising their hands, as physical interactions played an important role in this dense groups experiment. This behaviour was mainly observed to be initiated before recovery steps.

Improved Design and Simulation of an Integrated Ridge-Breaking Earth Cultivator for Ratoon Sugarcane Fields

Ridge-breaking earth cultivation is a new agronomic technology that simplifies and efficiently cultivates ratoon sugarcane. However, traditional cultivators cannot adapt to the distribution of residual stumps, inter-row specifications, and hardened clay soil. This results in substandard soil fragmentation, poor ridge quality, and reduced operational reliability. To address these issues, this article proposes an integrated earth cultivator structure capable of breaking ridges, loosening soil, and raising ridges simultaneously. It is designed to enhance the breaking of tillage layers and the filling of ridges through the coordinated action of multiple soil-engaging components. The effects of pre-loosening by the ridge-breaking plow, high-energy crushing, and throwing by the spirally arranged dense rotary blade group, and soil gathering by the deflector are comprehensively utilized. Additionally, lateral pushing by the ridging plough is employed. Discrete element and finite element simulation results show that densely toothed blades can improve soil supply capacity and structural reliability. This is achieved by increasing the amount of soil throwback and reducing concentrated stress levels. Soil fragmentation rate (SFR) and ridge height (RH) were further used as indicators. Field experiments were conducted to study the effects of operating parameters on breaking and ridging performance. The optimal parameter solution was determined as a forward speed of 0.85 m·s−1 and rotary speed of 289.7 r·min−1. With this adaptive configuration, SFR and RH were improved by 12.4% and 38.5%, respectively, compared with conventional earth cultivators. Additionally, the RSM value of rotary tillage power (Pr) was reduced by 39.6%. Improvements in crushing hardened fields, constructing ridges, and reducing cutting energy consumption have proven effective. This study can provide a reference for the development of earth cultivators based on new agronomy and specific field characteristics.

Diamino-functionalized metal-organic framework for selective capture of gold ions

Adsorptive recovery of valuable gold (Au) ions from wastes is vital but still challenged, especially regarding adsorption capacity and selectivity. A novel M − 3,5-DABA metal-organic framework (MOF) adsorbent was prepared via anchoring 3,5-diaminobenzoic acid (3,5-DABA) molecule in the MOF-808 matrix. Benefiting from the positive charge property, dense amino groups (3.2 mmol g−1) and high porosity, the adsorption capacity of M − 3,5-DABA reaches 1391.5 mg g−1 (pH = 2.5) and adsorption equilibrium is attained in 5 min. This amino-based material shows excellent selectivity towards various metal ions, evading the poor selectivity problem of classical thiol groups (e.g. for Ag+, Cu2+, Pb2+ and Hg2+ ions). In addition, the regeneration was easily achieved via using a hydrochloric acid-thiourea eluent. Experimental analysis and density functional theory (DFT) calculation show the amino group works as a reductant for Au(III) ions and meanwhile acts as an active site for adsorbing Au(III) ions together with the μ-OH group. Thus, M − 3,5-DABA can act as a potential adsorbent for Au(III) ions, and our work offers a viable strategy to construct novel MOF-based adsorbents.

From the grave to the lab: evaluation of archaeological human bone preservation based on micro-computed tomography analysis

Timely understanding of the preservation status of archaeological human bones is the foundation for conducting scientific archaeological work. This paper applies Micro-CT technology to analyze the microscopic preservation status of ancient human femora unearthed from the Rui State site in Liangdai Village, Hancheng, Shaanxi, the Chejiasi Cemetery in Baoji, and the Ouerping Cemetery in Xizhou Village, Yushe, Shanxi, and obtained imaging results and cortical bone porosity (Ct.Po), bone volume fraction (BV/TV), and bone density (BMD) parameters for 9 samples. The results show that the poorly preserved fragile group has lower Ct.Po, BV/TV, and BMD, and macroscopically presents fragile and porous features; while the well-preserved dense group has relatively higher Ct.Po, BV/TV, and BMD, and macroscopically appears solid and dense. This study employs Micro-CT technology to analyze the micro-preservation status of human bones from historical periods, confirming the effectiveness of this technology in revealing the microstructure of ancient human bones, and providing a reference for establishing a human bone preservation status evaluation system.