Quasi-compactons in inverted nonlinear photonic crystals

We study large-amplitude one-dimensional solitary waves in photonic crystals featuring competition between linear and nonlinear lattices, with minima of the linear potential coinciding with maxima of the nonlinear pseudopotential, and vice versa (inverted nonlinear photonic crystals, INPhCs), in the case of the saturable self-focusing nonlinearity. Such crystals were recently fabricated using a mixture of SU-8 and Rhodamine-B optical materials. By means of numerical methods and analytical approximations, we find that large-amplitude solitons are broad sharply localized stable pulses (quasi-compactons, QCs). With the increase of the totalpower, P, the QC's centroid performs multiple switchings between minima and maxima of the linear potential. Unlike cubic INPhCs, the large-amplitude solitons are mobile in the medium with the saturable nonlinearity. The threshold value of the kick necessary to set the soliton in motion is found as a function of P. Collisions between moving QCs are considered too.Comment: 11 pages, 8 figures, Physical Review A, in pres

A Real-Time Monitoring System of Industry Carbon Monoxide Based on Wireless Sensor Networks

Carbon monoxide (CO) burns or explodes at over-standard concentration. Hence, in this paper, a Wifi-based, real-time monitoring of a CO system is proposed for application in the construction industry, in which a sensor measuring node is designed by low-frequency modulation method to acquire CO concentration reliably, and a digital filtering method is adopted for noise filtering. According to the triangulation, the Wifi network is constructed to transmit information and determine the position of nodes. The measured data are displayed on a computer or smart phone by a graphical interface. The experiment shows that the monitoring system obtains excellent accuracy and stability in long-term continuous monitoring

Learning Deep Features for Scene Recognition using Places Database

Scene recognition is one of the hallmark tasks of computer vision, allowing definition of a context for object recognition. Whereas the tremendous recent progress in object recognition tasks is due to the availability of large datasets like ImageNet and the rise of Convolutional Neural Networks (CNNs) for learning high-level features, performance at scene recognition has not attained the same level of success. This may be because current deep features trained from ImageNet are not competitive enough for such tasks. Here, we introduce a new scene-centric database called Places with over 7 million labeled pictures of scenes. We propose new methods to compare the density and diversity of image datasets and show that Places is as dense as other scene datasets and has more diversity. Using CNN, we learn deep features for scene recognition tasks, and establish new state-of-the-art results on several scene-centric datasets. A visualization of the CNN layers' responses allows us to show differences in the internal representations of object-centric and scene-centric networks.National Science Foundation (U.S.) (Grant 1016862)United States. Office of Naval Research. Multidisciplinary University Research Initiative (N000141010933)Google (Firm)Xerox CorporationGrant TIN2012-38187-C03-02United States. Intelligence Advanced Research Projects Activity (United States. Air Force Research Laboratory Contract FA8650-12-C-7211

All-trans-Retinoic Acid Ameliorated High Fat Diet-Induced Atherosclerosis in Rabbits by Inhibiting Platelet Activation and Inflammation

Background. All-trans-retinoic acid (atRA) is effective for many proliferative diseases. We investigated the protective effects of atRA against atherosclerosis. Methods. Rabbits were randomly allocated to receive basal diet or an HFD for 4 weeks. HFD group then received rosuvastatin (3 mg/day), atRA (5 mg/kg/day), or the same volume of vehicle, respectively, for next 8 weeks. Results. HFD group showed increases in plasma lipids and aortic plaque formation. P-selectin expression and fibrinogen binding on platelets or deposition on the intima of the aorta also increased significantly as did the levels of TNF-α, IL-6, and fibrinogen in plasma. After 8 weeks of treatment with atRA, there was a significant decrease in plasma lipids and improvement in aortic lesions. AtRA also inhibited the expression of P-selectin and fibrinogen binding on platelets and deposition on the intima of the aorta. Conclusion. AtRA can ameliorate HFD-induced AS in rabbits by inhibiting platelet activation and inflammation

Effects of applying EGR with split injection strategy on combustion performance and knock resistance in a spark assisted compression ignition (SACI) engine

Spark assisted compression ignition (SACI) is a proven method for extending the load range and controlling the combustion phase of homogeneous charge compression ignition (HCCI) while maintaining high thermal efficiency. However, the occurrence of abnormal combustion, such as knock, limits the improvement of efficiency in SACI combustion. In this study, the effects of a coupling strategy, which combines internal/external exhaust gas recirculation (i & e-EGR) and split injection, on knock suppression in SACI mode were investigated in a high-compression-ratio, single-cylinder gasoline engine with a fully variable valve system. During the experiment, the mass of intake air remained constant while e-EGR was added. The results show that the coupling strategy combines the advantages of e-EGR and split injection, providing an effective method for resisting knock and improving engine efficiency. The results also demonstrate that applying e-EGR to SACI combustion significantly decreases the knock intensity by effectively reducing the in-cylinder temperature. In addition, the effect of split injection on knock suppression is related to the initial in-cylinder temperature and fuel stratification. With high initial in-cylinder temperature, the relationship between knock probability and split injection timing is non-monotonic. However, with low initial in-cylinder temperature, the capacity of resisting knock monotonically increases with the delay of secondary injection timing

Experimental analysis of super-knock occurrence based on a spark ignition engine with high compression ratio

The super-knock phenomenon is a major obstacle for further improving the power density in SI engines. The objective of this paper is to experimentally investigating the mechanism involved in the occurrence of super-knock. In this work, a high compression ratio (CR = 13) coupled with advanced spark timings were employed to achieving intense or critical thermal-dynamic conditions to easily inducing the super-knock. The results show that super-knock can originate from spark ignition, which is different from previous results regarding pre-ignition. Changing the spark timing super-knock can be induced with very high pressure oscillation at the present high compression ratio. The high compression ratio could generate sufficiently high thermal-dynamic conditions to inducing the abnormal combustion. In this research, four combustion phenomena were observed. The present work indicates that there is a nonlinear relationship between knock intensity and knocking onset in terms of pressure profiles at different cycles. The super-knock or knock phenomena were dominantly induced by spark ignition, which were controlled by the pre-ignition after several cycles. Finally, the analysis of the mechanism of super-knock with severe pressure oscillation was employed based on the thermal explosion theory and cavity resonances. There are two possible auto-ignition combustion modes that can induce the intense pressure oscillation

Demand response from the control of aggregated inverter air conditioners

Inverter air conditioners (ACs) account for a large proportion of air conditioning loads in many countries and, thus, contribute significantly to the peak loads in these areas, especially in summer. On the other hand, as an important category of thermostatically controlled load with thermal energy storage capability, inverter ACs also have the potential to provide considerable flexibility for electric power systems that are faced with increasing challenges posed by high penetration of renewable power generation. This paper focuses on the demand response from the control of the aggregated inverter ACs for load reduction. A virtual energy storage system (VESS) model that encapsulates the room with an inverter AC was established based on the electric model of an inverter AC and the thermodynamic model of a room. Based on the VESS model, a virtual state of charge (VSOC) priority-based load reduction control method with temperature holding and linear recovery strategies was proposed. The VSOC priority based control was designed to decrease the negative impact of load reduction on customers’ thermal comfort from the perspective of the whole AC population. The temperature holding strategy was designed to reduce the electric power of an AC while ensuring that the indoor temperature is always below the allowable limit. The linear recover strategy was proposed to reduce the load rebound after load reduction. Four cases were studied regarding the operation and load reduction of the 100 inverter ACs, and the simulation results verified the models established and the effectiveness and advantages of the proposed load reduction control method

Probing NaCl hydrate formation from aqueous solutions by Terahertz Time-Domain Spectroscopy

The cooling-induced formation of hydrate in aqueous NaCl solutions was probed using terahertz time-domain spectroscopy (THz-TDS). It was found that the NaCl hydrate formation is accompanied with emergence of four new absorption peaks at 1.60, 2.43, 3.34 and 3.78 THz. Combining the X-ray diffraction measurement with the solid-state based density functional theory (DFT) calculations, we assign the observed terahertz absorption peaks to the vibrational modes of the formed NaCl⋅2H2O hydrate during cooling. This work dedicates THz-TDS based analysis great potential in studying ionic hydrate and the newly revealed collective vibrational modes could be the sensitive indicators to achieve quantitative analysis in phase transitions and lattice dynamics