The resilience of interdependent transportation networks under targeted attack

Modern world builds on the resilience of interdependent infrastructures characterized as complex networks. Recently, a framework for analysis of interdependent networks has been developed to explain the mechanism of resilience in interdependent networks. Here we extend this interdependent network model by considering flows in the networks and study the system's resilience under different attack strategies. In our model, nodes may fail due to either overload or loss of interdependency. Under the interaction between these two failure mechanisms, it is shown that interdependent scale-free networks show extreme vulnerability. The resilience of interdependent SF networks is found in our simulation much smaller than single SF network or interdependent SF networks without flows.Comment: 5 pages, 4 figure

Seismic Data Interpolation based on Denoising Diffusion Implicit Models with Resampling

The incompleteness of the seismic data caused by missing traces along the spatial extension is a common issue in seismic acquisition due to the existence of obstacles and economic constraints, which severely impairs the imaging quality of subsurface geological structures. Recently, deep learning-based seismic interpolation methods have attained promising progress, while achieving stable training of generative adversarial networks is not easy, and performance degradation is usually notable if the missing patterns in the testing and training do not match. In this paper, we propose a novel seismic denoising diffusion implicit model with resampling. The model training is established on the denoising diffusion probabilistic model, where U-Net is equipped with the multi-head self-attention to match the noise in each step. The cosine noise schedule, serving as the global noise configuration, promotes the high utilization of known trace information by accelerating the passage of the excessive noise stages. The model inference utilizes the denoising diffusion implicit model, conditioning on the known traces, to enable high-quality interpolation with fewer diffusion steps. To enhance the coherency between the known traces and the missing traces within each reverse step, the inference process integrates a resampling strategy to achieve an information recap on the former interpolated traces. Extensive experiments conducted on synthetic and field seismic data validate the superiority of our model and its robustness on various missing patterns. In addition, uncertainty quantification and ablation studies are also investigated.Comment: 14 pages, 13 figure

Ultrasound radiomics nomogram for predicting large-number cervical lymph node metastasis in papillary thyroid carcinoma

PurposeTo evaluate the value of preoperative ultrasound (US) radiomics nomogram of primary papillary thyroid carcinoma (PTC) for predicting large-number cervical lymph node metastasis (CLNM).Materials and methodsA retrospective study was conducted to collect the clinical and ultrasonic data of primary PTC. 645 patients were randomly divided into training and testing datasets according to the proportion of 7:3. Minimum redundancy-maximum relevance (mRMR) and least absolution shrinkage and selection operator (LASSO) were used to select features and establish radiomics signature. Multivariate logistic regression was used to establish a US radiomics nomogram containing radiomics signature and selected clinical characteristics. The efficiency of the nomogram was evaluated by the receiver operating characteristic (ROC) curve and calibration curve, and the clinical application value was assessed by decision curve analysis (DCA). Testing dataset was used to validate the model.ResultsTG level, tumor size, aspect ratio, and radiomics signature were significantly correlated with large-number CLNM (all P< 0.05). The ROC curve and calibration curve of the US radiomics nomogram showed good predictive efficiency. In the training dataset, the AUC, accuracy, sensitivity, and specificity were 0.935, 0.897, 0.956, and 0.837, respectively, and in the testing dataset, the AUC, accuracy, sensitivity, and specificity were 0.782, 0.910, 0.533 and 0.943 respectively. DCA showed that the nomogram had some clinical benefits in predicting large-number CLNM.ConclusionWe have developed an easy-to-use and non-invasive US radiomics nomogram for predicting large-number CLNM with PTC, which combines radiomics signature and clinical risk factors. The nomogram has good predictive efficiency and potential clinical application value

Drude Conductivity of Dirac Fermions in Graphene

Electrons moving in graphene behave as massless Dirac fermions, and they exhibit fascinating low-frequency electrical transport phenomena. Their dynamic response, however, is little known at frequencies above one terahertz (THz). Such knowledge is important not only for a deeper understanding of the Dirac electron quantum transport, but also for graphene applications in ultrahigh speed THz electronics and IR optoelectronics. In this paper, we report the first measurement of high-frequency conductivity of graphene from THz to mid-IR at different carrier concentrations. The conductivity exhibits Drude-like frequency dependence and increases dramatically at THz frequencies, but its absolute strength is substantially lower than theoretical predictions. This anomalous reduction of free electron oscillator strength is corroborated by corresponding changes in graphene interband transitions, as required by the sum rule. Our surprising observation indicates that many-body effects and Dirac fermion-impurity interactions beyond current transport theories are important for Dirac fermion electrical response in graphene

Coxsackievirus A6 Induces Cell Cycle Arrest in G0/G1 Phase for Viral Production

Recent epidemiological data indicate that outbreaks of hand, foot, and mouth disease (HFMD), which can be categorized according to its clinical symptoms as typical or atypical, have markedly increased worldwide. A primary causative agent for typical HFMD outbreaks, enterovirus 71 (EV71), has been shown to manipulate the cell cycle in S phase for own replication; however, it is not clear whether coxsackievirus (CVA6), the main agent for atypical HFMD, also regulates the host cell cycle. In this study, we demonstrate for the first time that CVA6 infection arrests the host cell cycle in G0/G1-phase. Furthermore, synchronization in G0/G1 phase, but not S phase or G2/M phase, promotes viral production. To investigate the mechanism of cell cycle arrest induced by CVA6 infection, we analyzed cell cycle progression after cell cycle synchronization at G0/G1 or G2/M. Our results demonstrate that CVA6 infection promotes G0/G1 phase entry from G2/M phase, and inhibits G0/G1 exit into S phase. In line with its role to arrest cells in G0/G1 phase, the expression of cyclinD1, CDK4, cyclinE1, CDK2, cyclinB1, CDK1, P53, P21, and P16 is regulated by CVA6. Finally, the non-structural proteins of CVA6, RNA-dependent RNA polymerase 3D and protease 3C , are demonstrated to be responsible for the G0/G1-phase arrest. These findings suggest that CVA6 infection arrested cell cycle in G0/G1-phase via non-structural proteins 3D and 3C, which may provide favorable environments for virus production

Electrical Control of Plasmon Resonance with Graphene

Surface plasmon, with its unique capability to concentrate light into sub-wavelength volume, has enabled great advances in photon science, ranging from nano-antenna and single-molecule Raman scattering to plasmonic waveguide and metamaterials. In many applications it is desirable to control the surface plasmon resonance in situ with electric field. Graphene, with its unique tunable optical properties, provides an ideal material to integrate with nanometallic structures for realizing such control. Here we demonstrate effective modulation of the plasmon resonance in a model system composed of hybrid graphene-gold nanorod structure. Upon electrical gating the strong optical transitions in graphene can be switched on and off, which leads to significant modulation of both the resonance frequency and quality factor of plasmon resonance in gold nanorods. Hybrid graphene-nanometallic structures, as exemplified by this combination of graphene and gold nanorod, provide a general and powerful way for electrical control of plasmon resonances. It holds promise for novel active optical devices and plasmonic circuits at the deep subwavelength scale

Intraband Optical Transitions in Graphene

Abstract: We measured tunable interband and intraband transitions in graphene using infrared spectroscopy. Graphene electrons have strong intraband absorption at terahertz frequency range. The absorption spectra are described by a Drude-like frequency dependence

A Tunable Phonon-Exciton Fano System in Bilayer Graphene

Interference between different possible paths lies at the heart of quantum physics. Such interference between coupled discrete and continuum states of a system can profoundly change its interaction with light as seen in Fano resonance. Here we present a unique many-body Fano system composed of a discrete phonon vibration and continuous electron-hole pair transitions in bilayer graphene. Mediated by the electron-phonon interactions, the excited state is described by new quanta of elementary excitations of hybrid phonon-exciton nature. Infrared absorption of the hybrid states exhibit characteristic Fano lineshapes with parameters renormalized by many-body interactions. Remarkably, the Fano resonance in bilayer graphene is continuously tunable through electrical gating. Further control of the phonon-exciton coupling may be achieved with an optical field exploiting the excited state infrared activity. This tunable phonon-exciton system also offers the intriguing possibility of a 'phonon laser' with stimulated phonon amplification generated by population inversion of band-edge electrons.Comment: 21 pages, 3 figure

Discriminative Semantic Feature Pyramid Network with Guided Anchoring for Logo Detection

Logo detection is a technology that identifies logos in images and returns their locations. With logo detection technology, brands can check how often their logos are displayed on social media platforms and elsewhere online and how they appear. It has received a lot of attention for its wide applications across different sectors, such as brand identity protection, product brand management, and logo duration monitoring. Particularly, logo detection technology can offer various benefits for companies to help brands measure their logo coverage, track their brand perception, secure their brand value, increase the effectiveness of their marketing campaigns and build brand awareness more effectively. However, compared with the general object detection, logo detection is more challenging due to the existence of both small logo objects and large aspect ratio logo objects. In this paper, we propose a novel approach, named Discriminative Semantic Feature Pyramid Network with Guided Anchoring (DSFP-GA), which can address these challenges via aggregating the semantic information and generating different aspect ratio anchor boxes. More specifically, our approach mainly consists of two components, namely Discriminative Semantic Feature Pyramid (DSFP) and Guided Anchoring (GA). The former is proposed to fuse semantic features into low-level feature maps to obtain discriminative representation of small logo objects, while the latter is further integrated into DSFP to generate large aspect ratio anchor boxes for detecting large aspect ratio logo objects. Extensive experimental results on four benchmarks demonstrate the effectiveness of the proposed DSFP-GA. Moreover, we further conduct visual analysis and ablation studies to illustrate the strength of the proposed DSFP-GA when detecting both small logo objects and large aspect logo objects

Mineralogy and Chemistry of Sulfides from the Longqi and Duanqiao Hydrothermal Fields in the Southwest Indian Ridge

Recent investigations found that hydrothermal activity and sulfide mineralization occurs along the Southwest Indian Ridge (SWIR). The Longqi and Duanqiao hydrothermal fields between 49° E and 53° E of the SWIR are two prospective mineralization areas discovered by Chinese scientists. With the aim to determine the mineralogical and chemical characteristics of sulfide minerals, we have conducted detailed studies for samples from the two areas using an optical microscope, X‐ray diffractometer, scanning electron microscope, and electron microprobe. The mineralization processes in the Longqi area are divided into three main stages: (1) the low‐medium‐temperature stage: colloform pyrite (Py I) + marcasite → euhedral pyrite (Py II), (2) the high‐temperature stage: isocubanite (±exsolved chalcopyrite) + pyrrhotite → coarse‐grained chalcopyrite (Ccp I), and (3) the medium–low‐temperature stage: sphalerite + fine‐grained chalcopyrite inclusions (Ccp II) → aggregates of anhedral pyrite (Py III) ± marcasite → Fe‐oxide (‐hydroxide) + amorphous silica. The mineralization processes in the Duanqiao area are divided into two main stages: (1) the medium–high‐temperature stage: subhedral and euhedral pyrite (Py I′) → coarse‐grained chalcopyrite (Ccp I′) and (2) the medium–low‐temperature stage: sphalerite → fine‐grained chalcopyrite (Ccp II′) + chalcopyrite inclusions (Ccp II′) → silica‐cemented pyrite (Py II′) + marcasite → Fe‐oxide + amorphous silica. We suggest that the fine‐grained chalcopyrite inclusions in sphalerite from Longqi and Duanqiao were formed by co‐precipitation and replacement mechanisms, respectively. Primary sphalerites from both fields are enriched in Fe (avg. 5.84 wt% for the Longqi field vs. avg. 3.69 wt% for the Duanqiao field), Co (avg. 185.56 ppm for the Longqi field vs. 160.53 ppm for the Duanqiao field), and Cd (avg. 1950 ppm for the Longqi field vs. avg. 525.26 ppm for the Duanqiao field). Cu contents in pyrite from the Duanqiao field (Py I′: avg. 849.23 ppm and Py II′: avg. 1191.11 ppm) tend to be higher than those from the Longqi field (Py I: avg. 26.67 ppm, Py II: avg. 445 ppm, and Py III: avg. 179.29 ppm). Chalcopyrite from both fields is enriched in Zn (Ccp I: avg. 3226.67 ppm, Ccp II: avg. 9280 ppm, Ccp I′: avg. 848 ppm, Ccp II′ (inclusions): avg. 1098 ppm, and Ccp II′ (fine‐grained): avg. 1795 ppm). The varying contents of Zn in the different pyrite and chalcopyrite generations may result from the zone refining process. An integrated study of the mineralogy and mineralogical chemistry suggests that the hydrothermal fluids of the Longqi area are likely conditioned with higher temperatures and relatively lower fO2 and fS2 than those of the Duanqiao area, but in contrast to the former, the latter is much affected by the compositions of the surrounding rocks