Traffic sign detection using a cascade method with fast feature extraction and saliency test

Automatic traffic sign detection is challenging due to the complexity of scene images, and fast detection is required in real applications such as driver assistance systems. In this paper, we propose a fast traffic sign detection method based on a cascade method with saliency test and neighboring scale awareness. In the cascade method, feature maps of several channels are extracted efficiently using approximation techniques. Sliding windows are pruned hierarchically using coarse-to-fine classifiers and the correlation between neighboring scales. The cascade system has only one free parameter, while the multiple thresholds are selected by a data-driven approach. To further increase speed, we also use a novel saliency test based on mid-level features to pre-prune background windows. Experiments on two public traffic sign data sets show that the proposed method achieves competing performance and runs 27 times as fast as most of the state-of-the-art methods

Reaction mechanism between small-sized Ce clusters and water molecules: An ab initio investigation on Ce\u3csub\u3e\u3ci\u3en\u3c/i\u3e\u3c/sub\u3e+H\u3csub\u3e2\u3c/sub\u3eO

Reactions of small-sized cerium clusters Cen (n = 1–3) with a single water molecule are systematically investigated theoretically. The ground state structures of the Cen/H2O complex and the reaction pathways between Cen + H2O are predicted. Our results show the size-dependent reactivity of small-sized Ce clusters. The calculated reaction energies and reaction barriers indicate that the reactivity between Cen and water becomes higher with increasing cluster size. The predicted reaction pathways show that the single Ce atom and the Ce2 and Ce3 clusters can all easily react with H2O and dissociate the water molecule. Under UV-irradiation, the reaction of a Ce atom with a single H2O molecule may even release an H2 molecule. The reaction of either Ce2 or Ce3 with a single H2O molecule can fully dissociate the H2O into H and O atoms while it is bonded with the Ce cluster. The electronic configuration and oxidation states of the Ce atoms in the products and the higher occupied molecular orbitals are analyzed by using the natural bond orbital (NBO) analysis method, from which the high reactivity between the reaction products of Cen + H2O and an additional H2O molecule is predicted. Our results offer deeper molecular insights into the chemical reactivity of Ce, which could be helpful for developing more efficient Ce-doped or Ce-based catalysts. Includes supplementary materials

Mechanistic study of pressure and temperature dependent structural changes in reactive formation of silicon carbonate

The discovery of the silicon carbonate through chemical reaction between porous SiO2 and gaseous CO2 addressed a long-standing question regarding whether the reaction between CO2 and SiO2 is possible. However, the detailed atomic structure of silicon carbonate and associated reaction mechanism are still largely unknown. We explore structure changes of silicon carbonate with pressure and temperature based on systematic ab initio molecular dynamics simulations. Our simulations suggest that the reaction proceeds at the surface of the porous SiO2. Increasing number of CO2 molecules can take part in the reaction by increasing either the pressure or temperature. The final product of the reaction exhibits amorphous structures, where most C atoms and Si atoms are 3-fold and 6-fold coordinated, respectively. The fraction of differently coordinated C (Si) atoms is pressure dependent, and as a result, the structure of the final product is pressure dependent as well. When releasing the pressure, part of the reaction product decomposes into CO2 molecules and SiO2 tetrahedrons. However more than 50% of C atoms are still in 3-fold coordination, implying that stable silicon carbonate may be obtained via repeated annealing under high pressure. The mechanism underlying this chemical reaction is predicted with two possible reaction pathways identified. Moreover, the reaction transition curve is obtained from the extensive simulation, which can be useful to guide the synthesis of silicon carbonate from the reaction between SiO2 and CO2

Pretrained Language Model based Web Search Ranking: From Relevance to Satisfaction

Search engine plays a crucial role in satisfying users' diverse information needs. Recently, Pretrained Language Models (PLMs) based text ranking models have achieved huge success in web search. However, many state-of-the-art text ranking approaches only focus on core relevance while ignoring other dimensions that contribute to user satisfaction, e.g., document quality, recency, authority, etc. In this work, we focus on ranking user satisfaction rather than relevance in web search, and propose a PLM-based framework, namely SAT-Ranker, which comprehensively models different dimensions of user satisfaction in a unified manner. In particular, we leverage the capacities of PLMs on both textual and numerical inputs, and apply a multi-field input that modularizes each dimension of user satisfaction as an input field. Overall, SAT-Ranker is an effective, extensible, and data-centric framework that has huge potential for industrial applications. On rigorous offline and online experiments, SAT-Ranker obtains remarkable gains on various evaluation sets targeting different dimensions of user satisfaction. It is now fully deployed online to improve the usability of our search engine

Trichostatin A destabilizes HIF-2α through a VHL-independent but proteasome-dependent pathway in cancer cell lines and tumor xenografts

Histone deacetylase (HDACs) inhibitors are a new generation of anti-cancer agents. Little is known regarding the effect of HDAC inhibitors on HIF-2α. The effect of trichostatin A (TSA), a class I/II HDAC inhibitor, on HIF-2α protein expression was investiagted in cancer cell lines and tumor xenografts. Results showed TSA inhibited the HIF-2α protein expression in a dose-dependent manner, which was VHL-independent, but proteasome-dependent in cell lines. In tumor xenografts, TSA inhibited tumor growth and HIF-2α expression. Knocking down of HDAC6 by small RNA interfering decreased HIF-2α protein expression. HDAC6 physically interracted with HIF-2α, and HIF-2α was acetylated by TSA. TSA destabilizes HIF-2α in a proteasome dependent manner, which is unrelated to VHL, suggesting the anticancer effect of TSA is at least partially mediated by its inhibition of HIF-2α, which provides a new insight into the molecular mechanism underlying the anticancer effect of HDAC inhibitors

Mechanism of chip formation and surface-defects in orthogonal cutting of soft-brittle potassium dihydrogen phosphate crystals

Micromachining repair of surface defects on KH2PO4 (KDP) optics is an emerging technique in the construction of Inertial Confinement Fusion facilities for obtaining clean nuclear fusion energy. However, this method is yet facing considerable challenges owing to the soft-brittle nature of single-crystal KDP, hence it is necessary to understand its ductile-regime cutting mechanism to generate crack-free surfaces. This paper seeks to investigate the evolution of different cutting mechanism with the change of uncut chip thickness (UCT) in KDP orthogonal cutting processes. A transition of cutting modes from plastic cutting to shear-crack cutting and then fracture cutting with the rise of UCT has been revealed. To explain these cutting phenomena, a novel theoretical model was proposed by calculating the specific energy dissipation for crack/fracture propagations during cutting processes based on fracture mechanics. This analytical model was well validated by the analysis of cutting forces and machined surface quality. Nevertheless, three kinds of surface defects have been observed, i.e. micro pits, micro craters and edge chipping. These surface defects were caused by tearing and spalling of materials with elastic recovery, crack propagation along cleavage planes with ploughing effect, and the peeling away of large-size fracture, respectively. The presented results of great significance for promoting the application of micromachining processes in future engineering repair of KDP optics

TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios

Multi-object tracking in traffic videos is a crucial research area, offering immense potential for enhancing traffic monitoring accuracy and promoting road safety measures through the utilisation of advanced machine learning algorithms. However, existing datasets for multi-object tracking in traffic videos often feature limited instances or focus on single classes, which cannot well simulate the challenges encountered in complex traffic scenarios. To address this gap, we introduce TrafficMOT, an extensive dataset designed to encompass diverse traffic situations with complex scenarios. To validate the complexity and challenges presented by TrafficMOT, we conducted comprehensive empirical studies using three different settings: fully-supervised, semi-supervised, and a recent powerful zero-shot foundation model Tracking Anything Model (TAM). The experimental results highlight the inherent complexity of this dataset, emphasising its value in driving advancements in the field of traffic monitoring and multi-object tracking.Comment: 17 pages, 7 figure

Nickel-based superalloy architectures with surface mechanical attrition treatment:Compressive properties and collapse behaviour

Surface modifications can introduce natural gradients or structural hierarchy into human-made microlattices, making them simultaneously strong and tough. Herein, we describe our investigations of the mechanical properties and the underlying mechanisms of additively manufactured nickel–chromium superalloy (IN625) microlattices after surface mechanical attrition treatment (SMAT). Our results demonstrated that SMAT increased the yielding strength of these microlattices by more than 64.71% and also triggered a transition in their mechanical behaviour. Two primary failure modes were distinguished: weak global deformation, and layer-by-layer collapse, with the latter enhanced by SMAT. The significantly improved mechanical performance was attributable to the ultrafine and hard graded-nanograin layer induced by SMAT, which effectively leveraged the material and structural effects. These results were further validated by finite element analysis. This work provides insight into collapse behaviour and should facilitate the design of ultralight yet buckling-resistant cellular materials.</p

Two-dimensional monolayer salt nanostructures can spontaneously aggregate rather than dissolve in dilute aqueous solutions

It is well known that NaCl salt crystals can easily dissolve in dilute aqueous solutions at room temperature. Herein, we reported the first computational evidence of a novel salt nucleation behavior at room temperature, i.e., the spontaneous formation of two-dimensional (2D) alkali chloride crystalline/non-crystalline nanostructures in dilute aqueous solution under nanoscale confinement. Microsecond-scale classical molecular dynamics (MD) simulations showed that NaCl or LiCl, initially fully dissolved in confined water, can spontaneously nucleate into 2D monolayer nanostructures with either ordered or disordered morphologies. Notably, the NaCl nanostructures exhibited a 2D crystalline square-unit pattern, whereas the LiCl nanostructures adopted non-crystalline 2D hexagonal ring and/or zigzag chain patterns. These structural patterns appeared to be quite generic, regardless of the water and ion models used in the MD simulations. The generic patterns formed by 2D monolayer NaCl and LiCl nanostructures were also confirmed by ab initio MD simulations. The formation of 2D salt structures in dilute aqueous solution at room temperature is counterintuitive. Free energy calculations indicated that the unexpected spontaneous salt nucleation behavior can be attributed to the nanoscale confinement and strongly compressed hydration shells of ions. Supplementary files, including 6 movies, attached below

Direct Reprogramming of Fibroblasts into Embryonic Sertoli-like Cells by Defined Factors

SummarySertoli cells are considered the “supporting cells” of the testis that play an essential role in sex determination during embryogenesis and in spermatogenesis during adulthood. Their essential roles in male fertility along with their immunosuppressive and neurotrophic properties make them an attractive cell type for therapeutic applications. Here we demonstrate the generation of induced embryonic Sertoli-like cells (ieSCs) by ectopic expression of five transcription factors. We characterize the role of specific transcription factor combinations in the transition from fibroblasts to ieSCs and identify key steps in the process. Initially, transduced fibroblasts underwent a mesenchymal to epithelial transition and then acquired the ability to aggregate, formed tubular-like structures, and expressed embryonic Sertoli-specific markers. These Sertoli-like cells facilitated neuronal differentiation and self-renewal of neural progenitor cells (NPCs), supported the survival of germ cells in culture, and cooperated with endogenous embryonic Sertoli and primordial germ cells in the generation of testicular cords in the fetal gonad