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Background: The accurate identification and evaluation of lymph nodes by CT images is of great significance for disease diagnosis, treatment, and prognosis. Purpose: To assess the lymph nodes' segmentation, size, and station by artificial intelligence (AI) for unenhanced chest CT images and evaluate its value in clinical scenarios. Material and methods: This retrospective study proposed an end-to-end Lymph Nodes Analysis System (LNAS) consisting of three models: the Lymph Node Segmentation model (LNS), the Mediastinal Organ Segmentation model (MOS), and the Lymph Node Station Registration model (LNR). We selected a healthy chest CT image as the template image and annotated 14 lymph node station masks according to the IASLC to build the lymph node station mapping template. The exact contours and stations of the lymph nodes were annotated by two junior radiologists and reviewed by a senior radiologist. Patients aged 18 and above, who had undergone unenhanced chest CT and had at least one suspicious enlarged mediastinal lymph node in imaging reports, were included. Exclusions were patients who had thoracic surgeries in the past 2 weeks or artifacts on CT images affecting lymph node observation by radiologists. The system was trained on 6725 consecutive chest CTs that from Tianjin Medical University General Hospital, among which 6249 patients had suspicious enlarged mediastinal lymph nodes. A total of 519 consecutive chest CTs from Qilu Hospital of Shandong University (Qingdao) were used for external validation. The gold standard for each CT was determined by two radiologists and reviewed by one senior radiologist. Results: The patient-level sensitivity of the LNAS system reached of 93.94% and 92.89% in internal and external test dataset, respectively. And the lesion-level sensitivity (recall) reached 89.48% and 85.97% in internal and external test dataset. For man–machine comparison, AI significantly apparently shortened the average reading time (p < 0.001) and had better lesion-level and patient-level sensitivities. Conclusion: AI improved the sensitivity lymph node segmentation by radiologists with an advantage in reading time. [ABSTRACT FROM AUTHOR]

With the advancement of medical technology, the previous biomedical material platforms have been unable to meet the increasingly diverse application requirements, and the emergence of poly(2-oxazoline)s provides an opportunity to develop the next generation of biomedical materials. The highly tunable structure and function of poly(2-oxazoline)s, with excellent physical and biological properties, have shown great potential for application in the initial exploratory work. Currently, there are a lot of applied studies related to the water solubility, invisibility, and thermoresponsive of poly(2-oxazoline)s, mainly focused on drug delivery, protein modification, gene carriers, anti-fouling interface, cell sheet engineering, and hydrogel. This paper describes the preparation and physicochemical properties of poly(2-oxazoline)s and reviews the recent applications of poly(2-oxazoline)s in the biomedical field. [ABSTRACT FROM AUTHOR]

Electrocatalytic water splitting to produce hydrogen is a promising route to provide green hydrogen on a large scale. To explore non-noble metal electrocatalysts with high performance is still a challenge. Herein, a one-step electrodeposition way is developed to construct the heterostructural (NiO-La2O3)/(Ni-La)/NiO/Ni electrocatalysts on Ni foam. The dark Ni-La coating was prepared by co-electrodeposition from an aqueous solution containing LaCl3 and NiCl2 with a molar concentration ratio of 1:5. Among these heterostructural Ni-based electrocatalysts, an excellent HER activity is achieved: an overpotential of 22 mV at the current density of 10 mA cm−2 in 1 M KOH solution. It is demonstrated that the introduction of La significantly reduces the overpotential for HER. The higher the La content in the Ni-La coating of these electrocatalysts, the better the electrocatalytic HER performance was exhibited. This work provides a facile and inexpensive route to prepare Ni-La coating on electrodes in an aqueous solution. [ABSTRACT FROM AUTHOR]

Cross-Domain Few-Shot Learning (CD-FSL) aims at recognizing unseen classes from target domains that vastly differ from training classes from source domains, utilizing only a few labeled samples. However, the substantial domain disparities between target and source domains pose huge challenges to few-shot generalization. To resolve domain disparities, we propose HybridPrompt, a novel architecture for Domain-Aware Prompting that integrates a variety of cross-domain learned prompts as knowledge experts for CD-FSL. The proposed method enjoys several merits. First, to encode knowledge from diverse source domains, several Domain Prompts are introduced to capture domain-specific knowledge. Subsequently, to facilitate the cross-domain transfer of valuable knowledge, a Transferred Prompt is specifically tailored for each target task by retrieving highly relevant Domain Prompts based on domain properties. Finally, to complement insufficient transferred information, an Adaptive Prompt is learned to incorporate additional target characteristics for model adaptation. Consequently, the collaboration of these three types of prompts contributes to a hybridly prompted model that achieves domain-aware encoding, transfer, and adaptation, thereby enhancing adaptability on unseen domains. Extensive experimental results on the Meta-Dataset benchmark demonstrate that our method achieves superior performance against state-of-the-art methods. The source code is available at https://github.com/Jamine-W/HybridPrompt. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) transition metal dichalcogenide (TMD) has emerged as an effective optoelectronics material due to its novel optical properties. Understanding the role of defects in exciton kinetics is crucial for achieving high-efficiency TMD devices. Here, we observe defects induced anomalous power dependence exciton dynamics and spatial distribution in hexagonal heterogeneous WS2. With transient absorption microscopy study, we illustrate that these phenomena originate from the competition between radiative and defect-related non-radiative decays. To understand the physics behind this, a decay model is introduced with two defect-related channels, which demonstrates that more excitons decay through non-radiative channels in the dark region than the bright region. Our work reveals the mechanisms of anomalous exciton kinetics by defects and is instrumental for understanding and exploiting excitonic states in emerging 2D semiconductors. [ABSTRACT FROM AUTHOR]

A novel copper immobilized on biomimetic assembled carboxymethylcellulose/calcium carbonate hybrid (CuII@CMC/CaCO3) as an efficient heterogeneous catalyst for the synthesis of 1,2,3-triazoles has been described herein. The fabrication of CuII@CMC/CaCO3 is accomplished through a bioinspired mineralization process using sodium carboxymethylcellulose (CMC-Na) as the template and ion exchange agent, while the metathesis, nucleation, assemble, hybridization, and immobilization of Cu(II) occurred by successful treatment with CaCl2, Na2CO3, and CuSO4 in water at room temperature. The resultant CuII@CMC/CaCO3 hybrid was well characterized by various analyses such as FT-IR, XRD, SEM, EDX, EDX-mapping, TEM, and TGA techniques. In the presence of low copper loading of CuII@CMC/CaCO3 hybrid, benzylic halides, azide, and alkynes proceeded smoothly to afford 1,4-disubstituted 1,2,3-triazoles in high yields. The catalyst can be conveniently recovered from the reaction mixture by filter and reused for at least 5 consecutive runs with a slight drop in its catalytic activity. The remarkable activity and stability of the catalyst may be attributed to the coordination of both carboxyl and hydroxyl groups of the hybrid of CMC/CaCO3. [ABSTRACT FROM AUTHOR]

Developing new cabbage varieties resistant to head splitting and cabbage fusarium wilt (CFW) has become a high priority in breeding programs. To rapidly obtain resistant inbred lines, 230 doubled haploid (DH) lines were generated with an isolated microspore culture system from the crosses of two inbred lines, 23–457 (highly susceptible to both head splitting and CFW) and 88–54 (highly resistant to both head splitting and CFW). On the basis of field trials and a molecular marker assay, four elite DH lines (D29, D70, D120, and D162) were selected. These elite DH lines were crossed with elite cabbage inbred lines to generate more than 60 hybrids. An evaluation of the hybrids in the field indicated that five hybrids were highly resistant to both head splitting and CFW. These five hybrids also exhibited good agronomic traits. The resistant hybrids may be useful for controlling head splitting and CFW in the field. Our results also suggest that the application of an isolated microspore culture system and marker-assisted selection represents a rapid and efficient way of enhancing the resistance to head splitting and CFW in cabbage. [ABSTRACT FROM AUTHOR]

In this paper, we proposed a novel multi-modal max-margin supervised topic model (MMSTM) for social event analysis by jointly learning the representation together with the classifier in a unified framework. Compared with existing methods, the proposed MMSTM model has several advantages. (1) The proposed model can utilize the classifier as the regularization term of our model to jointly learn the parameters in the generative model and max-margin classifier, and use the Gibbs sampling to learn parameters of the representation model and max-margin classifier by minimizing the expected loss function. (2) The proposed model is able to not only effectively mine the multi-modal property by jointly learning the latent topic relevance among multiple modalities for social event representation, but also exploit the supervised information by considering a discriminative max-margin classifier for event classification to boost the classification performance. (3) In order to validate the effectiveness of the proposed model, we collect a large-scale real-world dataset for social event analysis, and both qualitative and quantitative evaluation results have demonstrated the effectiveness of the proposed MMSTM. [ABSTRACT FROM AUTHOR]

A bifunctional acid-base catalyst of CeIII immobilized on ethylenediamine (EDA)-grafted poly(vinyl chloride) (PVC) has been prepared by a simple approach. First, PVC was treated with EDA to afford aminated poly(vinyl chloride) (PVC-EDA). Thereafter, the PVC-EDA were used in the mobilization of CeCl3 to obtain a bifunctional catalyst (PVC-EDA-CeIII) in which a harmonious coexistence of Lewis acid (Ce3+) sites and Lewis base (amine) moieties on PVC was achieved. The obtained PVC-EDA-CeIII complex was characterized by EA, ICP-AES, FT-IR, SEM, EDS, TGA, and DTG techniques. The as-prepared catalyst can efficiently catalyze the one-pot four-component reactions of aromatic aldehydes, malononitrile, ethyl acetoacetate, and hydrazine in ethanol under mild conditions to afford polyfunctionalized 1,4-dihydropyrano[2,3-c]pyrazoles with excellent yields. The high catalytic performance of the PVC-EDA-CeIII bifunctional catalyst is attributed to a synergistic effect of Lewis acid sites (CeIII) and Lewis base sites (amino moieties). The significant features of the present protocol are environmentally benign, simple operation, short reaction time, high yields, and without chromatographic separation. Moreover, the catalyst can easily be separated by simple filtration and reused for five runs without obvious decline or losing its catalytic activity. [ABSTRACT FROM AUTHOR]

The present study was designed to investigate the effects of pilose antler peptide (PAP) on lipopolysaccharide (LPS)-induced lung injury. BalB/c mice intraperitoneally received PAP (10 and 20 mg/kg) or dexamethasone (2 mg/kg) 1 h prior to intratracheal instillation of LPS. PAP significantly decreased lung wet-to-dry weight (W/D) ratio and lung myeloperoxidase (MPO) activity and restored LPS-induced lung histopathological changes. PAP also increased super oxide dismutase (SOD) level and inhibited malondialdehyde (MDA) content and levels of pro-inflammatory cytokines including tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6) in bronchoalveolar lavage fluid (BALF) in LPS-stimulated mice. Furthermore, we demonstrated that PAP inhibited Rho/NF-κB pathway in LPS-induced mice. Our experimental results indicated that the protective mechanism of PAP might be attributed partly to the inhibition of Rho/NF-κB pathway. [ABSTRACT FROM AUTHOR]

Cerium(IV) carboxymethylcellulose (CMC −Ce) was found to be a highly efficient, eco-friendly and recyclable heterogeneous catalyst for the synthesis of 2,4,6-triarylpyridine derivatives in excellent yields via one-pot multicomponent reaction of various benzaldehydes, acetophenones, and ammonium acetate under solvent-free condition. Moreover, the present protocol has the merits of easy work-up, short reaction times, and high yields. [ABSTRACT FROM AUTHOR]

Feature-based object matching is a fundamental problem for many applications in computer vision, such as object recognition, 3D reconstruction, tracking, and motion segmentation. In this work, we consider simultaneously matching object instances in a set of images, where both inlier and outlier features are extracted. The task is to identify the inlier features and establish their consistent correspondences across the image set. This is a challenging combinatorial problem, and the problem complexity grows exponentially with the image number. To this end, we propose a novel framework, termed Robust Object Matching using Low-rank constraint (ROML), to address this problem. ROML optimizes simultaneously a partial permutation matrix (PPM) for each image, and feature correspondences are established by the obtained PPMs. Two of our key contributions are summarized as follows. (1) We formulate the problem as rank and sparsity minimization for PPM optimization, and treat simultaneous optimization of multiple PPMs as a regularized consensus problem in the context of distributed optimization. (2) We use the alternating direction method of multipliers method to solve the thus formulated ROML problem, in which a subproblem associated with a single PPM optimization appears to be a difficult integer quadratic program (IQP). We prove that under wildly applicable conditions, this IQP is equivalent to a linear sum assignment problem, which can be efficiently solved to an exact solution. Extensive experiments on rigid/non-rigid object matching, matching instances of a common object category, and common object localization show the efficacy of our proposed method. [ABSTRACT FROM AUTHOR]

China has become the largest producer of crude steel in the world since 1996, which places the country under huge pressure in terms of resources, energy, and the environment. Examining the driver of steel demand is of great significance to the structural adjustment and sustainable development of the steel industry. The researchers calculate the steel demand in China from 2000 to 2009 based on three sinks (steel stock, export, and loss) by taking the four stages of steel life cycle (production, fabrication and manufacturing, use, and waste management and recycling) as the study object. The researchers conclude that addition to in-use stock is the main driver of steel demand and that the 10-year average addition to inuse stock accounted for 77% of the steel sinks, in which 55% of the addition occurs in the building sector, and the steel for this segment is of low strength with large consumption. Based on the analysis of existing policies, the researchers propose that the steel demand structure will develop toward diversification and that the building sector will realize the upgrade of products as soon as possible to improve construction quality. Under the pressure of rising cost for imported resources, the export ratio of steel products should be controlled appropriately. Thus, recycling economy should be developed to reduce steel losses. [ABSTRACT FROM AUTHOR]

Paeoniflorin has been demonstrated to exert anti-inflammatory and immunomodulatory effects in the animal study. In this study, we investigated immunoregulatory effects of paeoniflorin on anti-asthmatic effects and underlying mechanisms. Asthma model was established by ovalbumin-induced. A total of 50 mice were randomly assigned to five experimental groups: control, model, dexamethasone (2 mg/kg), and paeoniflorin (10 and 20 mg/kg). Airway resistance (Raw) were measured by the forced oscillation technique; histological studies were evaluated by the hematoxylin and eosin (HE) staining; Th1/Th2 cytokines were evaluated by enzyme-linked immunosorbent assay (ELISA); Th1/Th2 cells were evaluated by flow cytometry (FCM); and GATA3 and T-bet were evaluated by Western blot. Our study demonstrated that, compared with model group, paeoniflorin inhibited ovalbumin (OVA)-induced increases in Raw and eosinophil count; interleukin (IL)-4, IgE levels were recovered in bronchoalveolar lavage fluid compared; increased IFN-γ level in bronchoalveolar lavage fluid; histological studies demonstrated that paeoniflorin substantially inhibited OVA-induced eosinophilia in lung tissue and lung tissue compared with model group. Flow cytometry studies demonstrated that paeoniflorin can regulate Th1/Th2 balance. These findings suggest that paeoniflorin may effectively ameliorate the progression of asthma and could be used as a therapy for patients with allergic asthma. [ABSTRACT FROM AUTHOR]

China has developed more than 20 water pollution control plans for river basins (RBWPs) since 1996. However, the implementation has generally lagged. This paper proposes a three-step, post-evaluation methodology to analyze the implementation result of a RBWP and its influential factors. First, a multi-attribute evaluation method based on an index system is established to score the enforcement results of a RBWP. Indicators measure how well a RBWP has achieved its objectives, which include water quality compliance, pollution load control, project construction, financial inputs, and related management requirements. Second, an interpretive structural model is used to detect the significant factors that affect RBWP implementation. This model can effectively analyze the cause-effect chain and hierarchical relationship among variables. Five groups of factors were identified, namely, plan preparation, water resource endowment, policy, institution, and management. Both qualitative and quantitative methods are employed in the third step to evaluate the extent to which these factors have influenced the execution result of a RBWP, including pre-post contrast, scenario analysis, and correlation analysis. This research then post-evaluated the implementation of the Huai River Basin water pollution control plans (HRBWPs) over a period of 10 years as a case study. Results showed that the implementation of the H-RBWPs was unsatisfactory during 2001-2005, although it improved during 2006-2010. The poor execution of these plans was partially caused by the underestimation of regional economic development in combination with ineffective industrial structure adjustment policies. Therefore, this case study demonstrates the feasibility and flexibility of the proposed post-evaluation methodology. [ABSTRACT FROM AUTHOR]

In this work, the anti-asthma potential of platycodin D (PLD) was studied by investigation of its effect to suppress airway inflammation, a murine model of asthma and the possible mechanisms. A total of 50 mice were randomly assigned to five experimental groups: control, ovalbumin (OVA), OVA+ dexamethasone (2 mg/kg) and OVA + PLD (40, 80 mg/kg). Airway resistance (Raw) were measured; airway histological studies were evaluated by the hematoxylin and eosin (HE) staining; interleukin-4 (IL-4), interleukin-5(IL-5), and interleukin-13 in bronchoalveolar lavage fluid (BALF) were evaluated by enzyme-linked immunosorbent assay (ELISA); NF-κBp65, p-NF-κBp65, p-IKKα, IKKα, p-IKKβ, p-IкBα, and IкBα of airway were measured by Western blotting. Our study demonstrated that PLD inhibited OVA-induced increases in Raw and eosinophil count in airway; IL-4, IL-5, and IL-13 were recovered in BALF. Histological studies demonstrated that PLD substantially inhibited OVA-induced eosinophilia in airway tissue. Western blotting studies demonstrated that PLD substantially inhibited NF-κB pathway. These findings suggest that PLD may effectively ameliorate the progression of asthma and could be used as a therapy for patients with allergic asthma. [ABSTRACT FROM AUTHOR]

Tracking multiple objects is critical to automatic video content analysis and virtual reality. The major problem is how to solve data association problem when ambiguous measurements are caused by objects in close proximity. To tackle this problem, we propose a multiple information fusion-based multiple hypotheses tracking algorithm integrated with appearance feature, local motion pattern feature and repulsion-inertia model for multi-object tracking. Appearance model based on HSV-local binary patterns histogram and local motion pattern based on optical flow are adopted to describe objects. A likelihood calculation framework is proposed to incorporate the similarities of appearance, dynamic process and local motion pattern. To consider the changes in appearance and motion pattern over time, we make use of an effective template updating strategy for each object. In addition, a repulsion-inertia model is adopted to explore more useful information from ambiguous detections. Experimental results show that the proposed approach generates better trajectories with less missing objects and identity switches. [ABSTRACT FROM AUTHOR]

The bag-of-words (BOW) based methods are widely used in image classification. However, huge number of visual information is omitted inevitably in the quantization step of the BOW. Recently, NBNN and its improved methods like Local NBNN were proposed to solve this problem. Nevertheless, these methods do not perform better than the state-of-the-art BOW based methods. In this paper, based on the advantages of BOW and Local NBNN, we introduce a novel locality discriminative coding (LDC) method. We convert each low level local feature, such as SIFT, into code vector using the Local Feature-to-Class distance other than by k-means quantization. After coding, sum-pooling combined with SPM is used to construct a single feature representation vector for each image. Extensive experimental results on several challenging benchmark datasets show that our LDC method outperforms six state-of-the-art image classification methods. [ABSTRACT FROM AUTHOR]

Object tracking is the process of determining the states of a target in consecutive video frames based on properties of motion and appearance consistency. In this paper, we propose a consistent low-rank sparse tracker (CLRST) that builds upon the particle filter framework for tracking. By exploiting temporal consistency, the proposed CLRST algorithm adaptively prunes and selects candidate particles. By using linear sparse combinations of dictionary templates, the proposed method learns the sparse representations of image regions corresponding to candidate particles jointly by exploiting the underlying low-rank constraints. In addition, the proposed CLRST algorithm is computationally attractive since temporal consistency property helps prune particles and the low-rank minimization problem for learning joint sparse representations can be efficiently solved by a sequence of closed form update operations. We evaluate the proposed CLRST algorithm against $$14$$ state-of-the-art tracking methods on a set of $$25$$ challenging image sequences. Experimental results show that the CLRST algorithm performs favorably against state-of-the-art tracking methods in terms of accuracy and execution time. [ABSTRACT FROM AUTHOR]

Crop residues are an important biomass, and are significant in the sustainable development of China. This paper uses the Grey-Markov modeling approach, the cost-benefit analysis method, and the constraint optimization method to establish the potential of crop residue recycling in China (CRRC) using a bottom-up analysis. Taking 2010 as the baseline year, the CRRC model is used to determine the quantity trends of crop residue resources, simulating the recycling potential and selecting key crop residue recycling technologies for operation between 2010 and 2030. The results illustrate that the total residue output from different crops will gradually increase to 1062 million tons in 2030. The proportion of crop residue for field burning is expected to decrease as a result of guidance and support from the government. Market mechanisms are also improving the development of the crop residue recycling industry. The economic benefit of crop residue recycling is expected to be worth 132 billion CNY in 2030 according to technology structure options. Key crop residue recycling technologies preferred such as liquefaction, amination, silo, co-firing straw power and composting will account for more than 85% of the total benefits. [ABSTRACT FROM AUTHOR]

In this study, a novel artificial hybrid vesicle, nano silver particles decorated cerasome were fabricated through sol-gel and self-assemble methods as well as in situ reduction. Samples were characterized in terms of hydrodynamic size and surface morphology via dynamic light scattering as well as scanning and transmission electron microscopies. Analysis through energy dispersive X-ray spectrometer proved the existence of silver particles. Due to the high morphological stability of cerasome, Silver nanoparticles with a size of about 5-10 nm can be deposited on the surface without any stabilizers. The UV spectra revealed a single symmetric extinction peak at 406 nm, confirming the spherical shape of the synthesized silver nanoparticles. Several reducing agents were screened before confirming sodium borohydride (NaBH). Comparison of different NaBH/lipid ratios (K) was then carried out in order to ascertain its effect. Investigation of the stability of this hybrid vesicles was carried out, indicating that it can be stored at 4 °C for at least 3 months without any morphological change. Results demonstrated that this hybrid vesicle has excellent morphological stability, which impart it significant potential for various applications such as being an antibacterial material and a radio sensitization agent. [ABSTRACT FROM AUTHOR]

A probability risk assessment was undertaken to study the individual and combined ecological risks induced by six polycyclic aromatic hydrocarbons (PAHs) both in surface water and sediment from southwestern catchments of the Bohai Sea, China. The actual measured PAH concentrations in water and sediment were compared with toxicity effect data (the 10th percentile of predicted no effect concentration) to calculate the risk quotients (RQs) for an individual PAH. The equilibrium partitioning method was applied to estimate toxicity data in sediment. A method based on the equivalent concentration concept was proposed and applied to assess the combined ecological risk of multiple PAHs. Monte Carlo simulation and bootstrap technique were utilized to calculate the distribution of RQs and associated uncertainties. The ecological safety level was defined by RQ ≤ 1. Results indicated that both in water and sediment, fluoranthene and pyrene posed the highest risks, whereas acenaphthene and fluorene posed negligible risks. Naphthalene and phenanthrene did not pose risks to the ecological community in surface water but had relatively higher risks in sediment. The median RQs of combined risk in surface water and sediment were 0.934 and 2.42, and the probabilities of RQ > 1 were up to 0.473 and 0.599, respectively, which were much higher than the individual compound acting alone. The risk level in sediment was quite higher than in surface water probably owing to the non-equilibrium distribution between two phases, which suggested that local authorities should focus more on sediment quality management. [ABSTRACT FROM AUTHOR]

Given the statistical gaps in material flow among provinces in China, a method was introduced to estimate regional physical imports and exports (RPIE), which includes international and interregional imports/exports. This method uses provincial monetary inputoutput tables (MIOT) and international trade statistics. A coefficient matrix representing correlations between monetary value and physical mass for years 2000-2009 was obtained based on a detailed commodity classification and 22 material production sectors in MIOT. With the coefficient matrix as reference, RPIE was measured. Pilot calculation of both regional physical trade balance and domestic material consumption, as well as a brief analysis of these methods, were conducted using 2002 data. [ABSTRACT FROM AUTHOR]

To improve material efficiency, industrial structure optimization becomes a focal point in Chinese industrial and environmental policies. It is crucial to cluster economic sectors and determine their priority for industrial and environmental policy implementation. Integrating a set of criteria, a hybrid input-output model and the hierarchical cluster analysis, this study clusters China's economic sectors and determines their priority on a life cycle basis. China's economic sectors are clustered into three clusters. Industrial structure changes (industrial policy) should encourage the development of sectors in cluster 1 and limit the development of sectors in cluster 2. Technology development and materials recycling (two environmental policies) should mainly focus on sectors in clusters 1 and 2. Future industrial policies in China should limit the development of two sectors named Manufacture of metal products and Extraction of petroleum and natural gas. Instead of limiting some industries by command-and-control, the best policy option is to remedy environmental standards and law enforcement. Enterprises belonging to the identified key sectors from the viewpoint of direct production impacts should be concerned to achieve enterprise sustainability. To achieve sustainable production chains, the identified key sectors from the viewpoint of accumulative production impacts should be concerned. For sustainable consumption, the identified key sectors from the viewpoint of consumption impacts should be concerned to transform consumption styles. Most of environmental pressure can be alleviated not only by technical improvements and material recycling, but also by the development of economic sectors in cluster 1. [ABSTRACT FROM AUTHOR]

In this paper, we formulate object tracking in a particle filter framework as a structured multi-task sparse learning problem, which we denote as Structured Multi-Task Tracking (S-MTT). Since we model particles as linear combinations of dictionary templates that are updated dynamically, learning the representation of each particle is considered a single task in Multi-Task Tracking (MTT). By employing popular sparsity-inducing $$\ell _{p,q}$$ mixed norms $$(\text{ specifically} p\in \{2,\infty \}$$ and $$q=1),$$ we regularize the representation problem to enforce joint sparsity and learn the particle representations together. As compared to previous methods that handle particles independently, our results demonstrate that mining the interdependencies between particles improves tracking performance and overall computational complexity. Interestingly, we show that the popular $$L_1$$ tracker (Mei and Ling, IEEE Trans Pattern Anal Mach Intel 33(11):2259-2272, ) is a special case of our MTT formulation (denoted as the $$L_{11}$$ tracker) when $$p=q=1.$$ Under the MTT framework, some of the tasks (particle representations) are often more closely related and more likely to share common relevant covariates than other tasks. Therefore, we extend the MTT framework to take into account pairwise structural correlations between particles (e.g. spatial smoothness of representation) and denote the novel framework as S-MTT. The problem of learning the regularized sparse representation in MTT and S-MTT can be solved efficiently using an Accelerated Proximal Gradient (APG) method that yields a sequence of closed form updates. As such, S-MTT and MTT are computationally attractive. We test our proposed approach on challenging sequences involving heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that S-MTT is much better than MTT, and both methods consistently outperform state-of-the-art trackers. [ABSTRACT FROM AUTHOR]

Four new phenoxy imino compounds were synthesized, and the solid-state structures of 1– 3 were determined by single-crystal X-ray diffraction study, giving crystallographic data as follows. 2-Acetyl-6-[1-(2,6-diisopropylphenylimino)ethyl]-4-methylphenol ( 1): a = 13.5893(5) Å, b = 10.5781(4) Å, c = 15.6778(4) Å, β = 113.1804(18)○, P21/c. 2,6-[1-(2,6-Diisopropylphenylimino)ethyl]-4-methylphenol ( 2): a = 12.1909(5) Å, b = 16.3324(6) Å, c = 15.9456(7) Å, β = 96.990(2)○, P21/c. 2-Acetyl-6-[1-(4-bromine-2,6-dimethylphenylimino)ethyl]-4-methylphenol ( 3): a = 7.5337(4) Å, b = 10.0457(5) Å, c = 12.6163(4) Å, α = 90.139(3)○, β = 104.003(3)○, γ = 106.485(2)○, P−1. Their molecular structures show that the 2,6-substituted phenyl ring is located approximately orthogonal to the hydroxyphenyl ring with the dihedral angle varying from 85.2○ to 101.4○. [ABSTRACT FROM AUTHOR]

A new flavone C-glycoside, 5,7-dihydroxy-4′-methoxy-8-C-[2″-(2″′-methylbutyryl)]-β-D-glucopyranosyl flavone ( 1), was isolated from the rhizomes of Cyperus rotundus. Its chemical structure was elucidated on the basis of UV, IR, MS, and NMR spectroscopic analyses. Compound 1 showed moderate inhibitory activity against MRB in the test, with an IC value of approximately 56.03 μM. [ABSTRACT FROM AUTHOR]

Generalization across various forgeries and robustness against corruption are pressing challenges of forgery detection. Although previous works boost generalization with the help of data augmentations, they rarely consider the robustness against corruption. To tackle these two issues of generalization and robustness simultaneously, in this paper, we propose a novel forgery detection generative adversarial network (FD-GAN), which consists of two generators (a blend-based generator and a transfer-based generator) and a discriminator. Concretely, the blend-based generator and the transfer-based generator can adaptively create challenging synthetic images with more flexible strategies to improve generalization. Besides, the discriminator is designed to judge whether the input is synthetic and predicts the manipulated regions with a collaboration of spatial and frequency branches. And the frequency branch utilizes Low-rank Estimation algorithms to filter out adversarial corruption in the input for robustness. Furthermore, to present a deeper understanding of FD-GAN, we apply theoretical analysis on forgery detection, which provides some guidelines on data augmentations for improving generalization and mathematical support for robustness. Extensive experiments demonstrate that FD-GAN exhibits better generalization and robustness. For example, FD-GAN outperforms 14 existing methods on 3 benchmarks in generalization evaluation, and it separately improves the performance against 6 kinds of adversarial attacks and 7 types of distortions by 16.2% and 2.3% on average in robustness evaluation. [ABSTRACT FROM AUTHOR]

Modern deep neural networks are prone to learn domain-dependent shortcuts and thus usually suffer from severe performance degradation when tested in unseen target domains due to their poor ability of out-of-distribution generalization, which significantly limits the real-world applications. The main reason is the domain shift lying in the large distribution gap between source and unseen target data. To this end, this paper takes a step towards training robust models for domain generalizable visual tasks, which mainly focuses on learning domain-invariant visual representation to alleviate the domain shift. Specifically, we first propose an effective Hierarchical Visual Transformation (HVT) network to (1) first transform the training sample hierarchically into new domains with diverse distributions from three levels: Global, Local, and Pixel, (2) then maximize the visual discrepancy between the source domain and new domains, and minimize the cross-domain feature inconsistency to capture domain-invariant features. Besides, we further enhance the HVT network by introducing the environment-invariant learning. To be specific, we enforce the invariance of the visual representation across automatically inferred environments by minimizing invariant learning loss that considers the weighted average of environmental losses. In this way, we can prevent the model from relying on the spurious features for prediction, thus helping the model to effectively learn domain-invariant representation and narrow the domain gap in various visual matching and recognition tasks, such as stereo matching, pedestrian retrieval, and image classification. We term our extended HVT as EHVT to show distinction. We integrate our EHVT network into different models and evaluate its effectiveness and compatibility on several public benchmark datasets. Extensive experiments clearly show that our EHVT can substantially enhance the generalization performance in various tasks. Our codes are available at https://github.com/cty8998/EHVT-VisualDG. [ABSTRACT FROM AUTHOR]