Repulsion Loss: Detecting Pedestrians in a Crowd

Detecting individual pedestrians in a crowd remains a challenging problem since the pedestrians often gather together and occlude each other in real-world scenarios. In this paper, we first explore how a state-of-the-art pedestrian detector is harmed by crowd occlusion via experimentation, providing insights into the crowd occlusion problem. Then, we propose a novel bounding box regression loss specifically designed for crowd scenes, termed repulsion loss. This loss is driven by two motivations: the attraction by target, and the repulsion by other surrounding objects. The repulsion term prevents the proposal from shifting to surrounding objects thus leading to more crowd-robust localization. Our detector trained by repulsion loss outperforms all the state-of-the-art methods with a significant improvement in occlusion cases.Comment: Accepted to IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 201

AIDA: Legal Judgment Predictions for Non-Professional Fact Descriptions via Partial-and-Imbalanced Domain Adaptation

In this paper, we study the problem of legal domain adaptation problem from an imbalanced source domain to a partial target domain. The task aims to improve legal judgment predictions for non-professional fact descriptions. We formulate this task as a partial-and-imbalanced domain adaptation problem. Though deep domain adaptation has achieved cutting-edge performance in many unsupervised domain adaptation tasks. However, due to the negative transfer of samples in non-shared classes, it is hard for current domain adaptation model to solve the partial-and-imbalanced transfer problem. In this work, we explore large-scale non-shared but related classes data in the source domain with a hierarchy weighting adaptation to tackle this limitation. We propose to embed a novel pArtial Imbalanced Domain Adaptation technique (AIDA) in the deep learning model, which can jointly borrow sibling knowledge from non-shared classes to shared classes in the source domain and further transfer the shared classes knowledge from the source domain to the target domain. Experimental results show that our model outperforms the state-of-the-art algorithms.Comment: 13 pages, 15 figure

Sex plays a role in the construction of epiphytic bacterial communities on the algal bodies and receptacles of Sargassum thunbergii

The community structures of epiphytic bacteria on the surface of macroalgae are closely related to their host algae, but there is a lack of research on the differences between the epiphytic bacterial communities of male and female algae and their reproductive tissues. In this study, high-throughput sequencing was used to compare epiphytic bacterial community structures on the intertidal macroalgae Sargassum thunbergii and their receptacles between male and female samples. The epiphytic bacteria on the male and female algal bodies and receptacles had similar community structures with a large number of shared bacteria, but the samples clearly clustered separately, and the abundances of dominant taxa, specific bacteria, and indicator species differed, indicating that epiphytic bacterial communities differed significantly between the male and female S. thunbergii and their receptacles. In addition, the abundance of many predicted functional genes was significantly different between epiphytic bacteria on male and female algal bodies and receptacles, especially metabolism-related genes, and the abundances of predicted functional genes of epiphytic bacteria were significantly higher on both types of male samples than on female samples. Our study confirmed that the sex of the host algae influenced the epiphytic bacterial community structures on algae and algal reproductive tissues, and this role was mainly related to the host metabolism. The results reveal the role of host plant sex in the formation of epiphytic bacterial communities. These findings are helpful for obtaining an in-depth understanding of the construction mechanism of algae-associated bacteria

Research progress of 3D printed poly (ether ether ketone) in the reconstruction of craniomaxillofacial bone defects

The clinical challenge of bone defects in the craniomaxillofacial region, which can lead to significant physiological dysfunction and psychological distress, persists due to the complex and unique anatomy of craniomaxillofacial bones. These critical-sized defects require the use of bone grafts or substitutes for effective reconstruction. However, current biomaterials and methods have specific limitations in meeting the clinical demands for structural reinforcement, mechanical support, exceptional biological performance, and aesthetically pleasing reconstruction of the facial structure. These drawbacks have led to a growing need for novel materials and technologies. The growing development of 3D printing can offer significant advantages to address these issues, as demonstrated by the fabrication of patient-specific bioactive constructs with controlled structural design for complex bone defects in medical applications using this technology. Poly (ether ether ketone) (PEEK), among a number of materials used, is gaining recognition as a feasible substitute for a customized structure that closely resembles natural bone. It has proven to be an excellent, conformable, and 3D-printable material with the potential to replace traditional autografts and titanium implants. However, its biological inertness poses certain limitations. Therefore, this review summarizes the distinctive features of craniomaxillofacial bones and current methods for bone reconstruction, and then focuses on the increasingly applied 3D printed PEEK constructs in this field and an update on the advanced modifications for improved mechanical properties, biological performance, and antibacterial capacity. Exploring the potential of 3D printed PEEK is expected to lead to more cost-effective, biocompatible, and personalized treatment of craniomaxillofacial bone defects in clinical applications

The effect of online reviews on addressing endogeneity in discrete choice models

This paper investigates the effectiveness of online reviews on addressing price endogeneity issue in an application to consumer demand for smartphone. We consider review variables as the substitutes of unobserved product quality in terms of a scalar variable as seen in previous methods. An aspect-based sentiment classification technique is designed to construct feature-related review variables from millions of review contents. We discuss the performance of review variables both in a hedonic pricing model and a conditional logit discrete choice model. Our results demonstrate that review variables show a good performance either as instruments for price or as explicit control variables in demand models. In detail, the pricing prediction accuracy increases 3.4%, which is considered as a significant improvement in the practice of forecasting. In the discrete choice model, the estimated price coefficient is biased in the positive direction without endogeneity correction. It is adjusted in the expected way after including review variables. The findings indicate that online reviews provide alternative sources of information in dealing with endogeneity in discrete choice models. We also analyze the differences in the preferences and needs of individual consumers to provide some practical implications of marketing

Simulation of Cross-Correlated Random Fields for Transversely Anisotropic Soil Slope by Copulas

Multi-source uncertainties yielded by randomness, spatial variability and cross-correlation of soil parameters severely affect the realization of random fields. However, current studies rarely account for these simultaneously, leading to inevitable bias in random field simulation and subsequent structure analysis. In this paper, copula-based cross-correlated random fields for transversely anisotropic soil slope are proposed. Firstly, based on the traditional probabilistic method and random field theory, the effect of the cross-correlation of soil parameters on the random field is comprehensively analyzed. Then copulas, which mainly characterize the dependent structures of random variables, are further expanded to connect multivariate random fields. Four special algorithms associated with Gaussian, Frank, Plackett and No. 16 copulas are subsequently developed. At last, the performance and effectiveness of copula-based cross-correlated random fields are illustrated by means of assumed and engineering slope cases. The results show that the proposed method is amenable to characterizing spatial variability comprising multiple cross-correlated soil parameters of transversely anisotropic slope. Soil profiles can be represented with a relatively high accuracy. Moreover, the performance of copula-based CCRF is simultaneously governed by margins, cross-correlated coefficients and copulas. The proper selection of these crucial factors can considerably reduce multi-source uncertainties. Overall, the proposed method could provide a useful guideline for accurately modeling cross-correlation random fields of soil slope

Numerical Study on an RBF-FD Tangent Plane Based Method for Convection–Diffusion Equations on Anisotropic Evolving Surfaces

In this paper, we present a fully Lagrangian method based on the radial basis function (RBF) finite difference (FD) method for solving convection–diffusion partial differential equations (PDEs) on evolving surfaces. Surface differential operators are discretized by the tangent plane approach using Gaussian RBFs augmented with two-dimensional (2D) polynomials. The main advantage of our method is the simplicity of calculating differentiation weights. Additionally, we couple the method with anisotropic RBFs (ARBFs) to obtain more accurate numerical solutions for the anisotropic growth of surfaces. In the ARBF interpolation, the Euclidean distance is replaced with a suitable metric that matches the anisotropic surface geometry. Therefore, it will lead to a good result on the aspects of stability and accuracy of the RBF-FD method for this type of problem. The performance of this method is shown for various convection–diffusion equations on evolving surfaces, which include the anisotropic growth of surfaces and growth coupled with the solutions of PDEs

Experimental Study on the Influence of Substrate Properties on Rainfall Infiltration and Runoff from Ecological Slopes

Rain is an important factor influencing the instability of ecological slopes. There is little research on the inherent quantitative influence of substrate properties on slope runoff and water infiltration to support accurate ecological slope protection design. In this paper, the influence of substrate characteristics on slope runoff and water infiltration is quantitatively analyzed by constructing large physical models with different substrate characteristics for artificial rainfall simulations. The experimental results showed that the cumulative runoff volume and slope runoff rate were positively correlated with the cement content and substrate thickness in a 4 h, 60 mm/h artificially simulated rainfall. Specifically, the cumulative runoff volume increased by 2.06% for every 1% increase in cement content, and the cumulative runoff volume increased by 3.93% for every 1 cm increase in substrate thickness. The substrate inhibited the advance of the wetting front, and at different slope locations, the transport rate of the wetting front exhibited a mid-slope > upslope. Moreover, the transport rate of the wetting front showed a non-linear relationship with time as a power function V = a·tb, with the cement content showing a linear relationship with parameters a and b, and the substrate thickness showing a non-linear relationship with parameters a and b. The cumulative infiltration and infiltration rate were negatively correlated with cement content and substrate thickness, as shown by a 2.2% decrease in cumulative infiltration for every 1% increase in cement content and a 4.73% decrease in cumulative infiltration for every 1 cm increase in substrate thickness

Microstructures and properties of nickel-titanium carbide composites fabricated by laser cladding

In this work, Ni/TiC composites were synthesized by the laser cladding technique (LCT). A scanning electron microscope (SEM), X-ray diffractometer (XRD), microhardness meter, electrochemical workstation, and friction and wear tester examined the microstructure, surface morphology, phase structure, microhardness, wear, and corrosion resistances of the Ni/TiC composites. These results indicated the Ni/40TiC composite contained finer equiaxed crystals than the Ni and Ni/20TiC composites. In addition, numerous TiC particles in the Ni/40TiC composite impeded growth of the nickel crystals, which resulted in the fine microstructure of the Ni/40TiC composite. The Ni, Ni/20TiC, and Ni/40TiC composites exhibited face-centered cubic (f c c) lattices. The average microhardness values of the Ni/20TiC and Ni/40TiC composites were approximately 748 HV and 851 HV, respectively. The Ni/40TiC composite had the lowest friction coefficient (0.43) among all three coatings, and only some shallow scratches appeared on the surface of the Ni/40TiC composite. The corrosion potential (E) of Ni/40TiC exceeded the Ni/20TiC composite, and both were larger than the Ni composite, which indicated the Ni/40TiC composite had outstanding corrosion resistance and the Ni composite had poor corrosion resistance. The corrosion current densities (i) of Ni, Ni/20TiC, and Ni/40TiC composites were 5.912, 4.405, and 3.248 μA/cm2, respectively.The research is supported by the National Natural Science Foundation of China (Granted no. 51974089), and the China Scholarship Council (Granted nos. 201908230345, 202008230022)

Development of an endoplasmic reticulum stress-related signature with potential implications in prognosis and immunotherapy in head and neck squamous cell carcinoma

Abstract Background Head and neck squamous cell carcinoma (HNSCC) is a multisite malignancy that responds well to immunotherapy. Despite the initial enthusiasm, the clinical benefits of immunotherapy in HNSCC patients are overall limited. Endoplasmic reticulum stress (ERS) has been indicated to play a key role in the process of anti-tumor immune response mediation. However, ERS-related biomarkers which can accurately predict prognosis and immunotherapy response in HNSCC are still lacking. Methods and results In this study, we identify and validate an ERS-related signature comprises of six genes (ASNS, EXOSC6, BAK1, TPP1, EXOSC8, and TATDN2) that can predict the prognosis of HNSCC patients. GSEA analysis indicates that the ERS-related signature is significantly correlated with tumor immunity in HNSCC. Moreover, the infiltration of naive B cells and CD8 + T cells are significantly diminished in patients with high-risk scores compared to those with low-risk scores, while macrophages and activated mast cells are remarkably enhanced. Furthermore, the ERS-related signature also displays a tremendous potential for predicting immunotherapy response in HNSCC. Conclusions Our study identifies an ERS-related signature that can predict the prognosis of HNSCC patients and highlights its potential value as a predictive biomarker of immunotherapy response, potentially enabling more precise and personalized immunotherapy response and paving the way for further investigation of the prognostic and therapeutic potentials of ERS