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Beam splitting of high-order Gaussian (HOG) beams increases the channel capacity and improves the processing speed of the incoming information. Here a novel all-optical tunable multi-port HOG beam splitter under a periodic dielectric atomic structure is proposed and demonstrated. The original HOG beam is replicated in the output beams. A distinguishable five-port output beam is observed in the experiment, which is beneficial for high-speed optical communications. By tuning the optical properties of this periodic dielectric structure, the spatial position and intensity distribution of each output port are precisely controllable. The splitting ratio δ can be finely adjusted in the range 0 – 4.8. This work provides a new approach for multi-port HOG beam splitters and the basis for all-optical communication.

All-optical devices used to process optical signals without electro-optical conversion plays a vital role in the next generation of optical information processing systems. We demonstrate an efficient all-optical modulator that utilizes a periodic dielectric atomic lattice produced in a gas of 85Rb vapor. Four orders of diffraction patterns are observed when a probe laser is passed through the lattice. The frequency shift of the peak of each diffraction order can be tuned by adjusting the control laser power and two-photon detuning, enabling this device to be used as a multi-channel all-optical modulator. Both theoretical simulations and experimental results demonstrate that this modulator can operate over a frequency band extending from about 0 to 60 MHz. This work may pave the way for studying quantum information processing and quantum networking proposed in atomic ensembles.

In the case of modern multiple power generation modes parallel, thermal power often needs to cooperate with new energy power generation for peak shaving operation, which leads to frequent load changes in thermal power plants, and it is necessary to establish new boiler models quickly and accurately. In this paper, an asymmetric PSO-BP neural network modeling method is proposed to solve this problem. According to the boiler mechanism principle, the non directly related network connection key is removed, and the network structure under different working conditions is unified, and the particle swarm optimization algorithm is adopted to optimize it. Compared with the traditional neural network, the asymmetric PSO-BP neural network model has smaller prediction error and higher stability, which can improve the accuracy of boiler modeling, and lay a foundation for the boiler online modeling when the load changes rapidly.

A novel tunable all-optical grating is realized experimentally in a

Electromagnetically induced grating (EIG) is extensively investigated as an artificial periodic structure in recent years owed to its simple reconfiguration and flexible adjustability. We report the experimental observation of EIG in cold rubidium atoms. The coupling and probe lasers are corresponding to the 5S1/2&minus, 5P1/2 and 5S1/2&minus, 5P3/2 transitions of a V-type electromagnetically induced transparency (EIT) configuration, respectively. A clear spatial intensity distribution of the probe laser with distinguished third-order diffraction pattern is recorded to character the EIG. The influence of the pertinent experimental parameters, such as coupling laser intensity and two-photon detuning on the diffraction pattern is investigated in detail. This is the first observation in visual form of the EIG in cold rubidium atoms. These results may potentially provide a nondestructive method to image cold atoms and pave the way for investigating non-Hermitian physics and the control of light dynamics.

A novel tunable all-optical grating is realized experimentally in a V + Ξ configuration coherent rubidium thermal vapor. This new energy level structure employs a Rydberg level as the uppermost level and contains two typical electromagnetically induced transparency energy level configurations with the same probe field. Compared with the traditional V-type three-level grating, a significant improvement of the diffraction efficiency of this novel grating was observed. Its improvement was then also demonstrated experimentally by the transition spectrum and theoretically by a comprehensive simulation. The diffraction efficiency gain introduced by the control laser field was tuned with several experimental parameters, such as the atomic density and the control field intensity. And the maximum enhancement rate of first-order diffraction efficiency is proved to be as high as 30%. Such a novel all-optical tunable grating promises to be the new driving force in the advancement of all-optical communications and information technology.

Ethopharmacological relevance Sea buckthorn ( Hippophae rhamnoides L.) berries have been traditionally used to treat gastric disorders, cardiovascular problems, and liver injuries in oriental medicinal system. This study aimed to explore the protective effects and mechanisms of the polysaccharide extracts of Sea buckthorn (HRP) berries against lipopolysaccharide (LPS) and d-galactosamine hydrochloride (d-GalN)-induced acute liver failure in mice. Materials and methods HRP was isolated by hot-water extraction and characterized by HPLC and infrared spectrum analysis. The total carbohydrate, uronic acid and protein contents of HRP were measured by a spectrophotometric method. Mice were orally administrated with HRP (50, 100, 200 mg/kg) once daily for 14 consecutive days prior to the challenge with LPS (50 μg/kg) and d-GalN (300 mg/kg). Animals of positive control group were intraperitoneally injected with dexamethasone (10 mg/kg). Mice were sacrificed at 8 h after LPS/d-GalN injection. Results Pretreatment with HRP significantly inhibited LPS/d-GalN-induced increases in serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels, which were accompanied by alleviated liver injuries and reduced production of tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β). HRP was also found to reduce malondialdehyde (MDA) content and to restore superoxide dismutase (SOD) and glutathione peroxidase (GSH-PX) activities. Furthermore, HRP supplementation dose-dependently inhibited the expression of Toll-like receptor 4 (TLR4), phosphorylated extracellular signal-regulated kinase (p-ERK), phosphorylated c-Jun N-terminal kinase (p-JNK), and phosphorylated mitogen activated protein kinase 38 (p–p38 MAPK) in the liver of LPS/d-GalN challenged mice. Pretreatment with HRP also inhibited LPS/d-GalN-induced activation and translocation of nuclear factor-κB (NF-κB). Conclusions This study indicates that pretreatment with HRP protects against LPS/d-GalN-induced liver injury in mice via suppressing the TLR4-NF-κB signaling pathway. Sea buckthorn may be a hopeful drug for prevention of acute live injury.

With the tremendous growth in wireless network deployment and increasing use of mobile devices, e.g., smartphones and tablets, improving energy efficiency in such devices, especially with communication driven workloads, is critical to providing a satisfactory user experience. Studies show that signal strength plays an important role on energy consumption of cellular data communications. While energy consumption can be minimized by accurately predicting signal strengths and reacting to it in real-time, the dynamic nature of wireless environments makes signal strengths highly unpredictable. In this paper, after analyzing in detail the signal strength variation and its impact on energy consumption, we propose to use crowdsourcing approach to optimize mobile devices’ energy efficiency by utilizing signal strength traces reported/shared by other users/devices in cellular networks. Via a comprehensive measurement study, we observe that signal strength traces collected from different devices are pseudo-identical, and they even exhibit similar threshold-based behaviors in the relationship between signal strength and device power consumption. Based on our observations, we propose a predictive scheduling algorithm that: (i) selects the right set of signal strength traces based on its location, (ii) applies a filter to smooth out signal strengths and hide abrupt changes, (iii) digitizes the signal strength to “good” and “bad” areas, and (iv) schedules transmissions based on power-throughput characteristics to optimize the transmission energy efficiency. To demonstrate the efficacy of the proposed algorithms, we prototype the crowdsourcing-based predicative scheduling algorithm on Android-based smartphones. Our experiment results from real-life driving tests demonstrate that, by leveraging others’ signal traces, mobile devices can save energy up to 35 percent compared to the conventional opportunistic scheduling, i.e., schedule transmissions only based on instantaneous channel conditions.

In this study, the directional luminescent quantum dot (QD)-layered double hydroxide (LDH) assembly was fabricated by embedding the trace QDs onto the exterior surface of the organo-modified LDHs. It was found that this novel nanomaterial was able to extraordinarily improve an ultra-weak chemiluminescence (CL) emission from peroxynitrous acid (ONOOH). The enhanced CL emission was attributed to the electrostatic concentration of peroxynitrite (ONOO−) onto the orderly surface of the QD-organo-modified LDHs as well as the hydrophobic microenvironment of the organo-LDHs, facilitating the production of superoxide radical ( O2−) and hydroxyl radical ( OH). In addition, the CL intensity increased with increasing the concentration of nitrite in a wide range of 1.0–1000 μM with a detection limit of 0.3 μM (S/N = 3). Therefore, the proposed method was applied for the selective and sensitive detection of nitrite in sausage samples. Recoveries from spiked real samples were in the range of 96–103%. The results of the proposed method for sensing nitrite in real samples were agreed with those obtained by the standard spectrophotometric method.

In this work, we fabricate an oriented luminescent quantum dot (QD)-layered double hydroxide (LDH) nanocomposite material by the highly orderly and alternate assembly of trace CdTe QDs in dodecylbenzene sulfonate bilayer bunches on the organo-modified LDH exterior surfaces. Interestingly, the novel QD-LDH nanocomposites can remarkably amplify chemiluminescence (CL) of the luminol-H2O2 system, which is attributed to an inhibition of QD oxidation by H2O2, an increase in the radiative decay rate, and an inhibition in the nonradiative relaxation of QDs. In addition, a novel flow-through column-based CL resonance energy transfer is fabricated using luminol as energy donors and the solid luminescent QD-LDH nanocomposites as energy acceptors for signal amplification. The applicability of this flow-through column is evaluated by determining H2O2 using luminol-H2O2 CL system. The CL intensity exhibits a stable response to H2O2 over a concentration range from 0.5 to 60 μM with a detection limit as low as 0.3 μM. Finally, the proposed method has been successfully applied to detect H2O2 in snow samples, and the results agreed with those obtained by the standard spectrophotometric method. Our findings indicate that the new luminescent QD-LDH nanocomposite material would be used for high throughput screening of complex systems with different sized QDs.

In this study, we sought to find the effects and mechanisms of probiotic Lactobacillus casei Zhang (L. casei Zhang) on the pro-inflammatory cytokine production and hepatic inflammatory response in a rat model of acute liver failure induced by lipopolysaccharide (LPS) and d-galactosamine (GalN). Male Wistar rats were orally administrated with or without L. casei Zhang for 30 days prior to challenge with LPS and GalN. Dexamethasone administrated group serving as a positive anti-inflammation control. Serum, intestinal and liver samples were collected 8 h after LPS/GalN challenge for histological, molecular and biochemical analysis. LPS/GalN challenge alone resulted in significantly increased production of endotoxin, tumor necrosis factor-α (TNF-α), interleukin-1 beta (IL-1β) and nitric oxide as compared to the normal control rats. Pretreatment with L. casei Zhang not only reduced these changes, but also attenuated hepatic inflammation as shown by improved histological assessment, decreased myeloperoxidase activity and reduced expression of IL-1β and inducible nitric oxide synthase in the liver. L. casei Zhang supplementation significantly inhibited LPS/GalN-triggered phosphorylation of ERK, JNK and p-38 MAPK, but increased the expression of TLR2, TLR9 and PPAR-γ. Moreover, L. casei Zhang treatment prevented intestinal injury and modulated the intestinal ecology by increasing the fecal Lactobacillus and Bifidobacterium levels. Probiotic L. casei Zhang reduces LPS/GalN-induced pro-inflammatory cytokine and hepatic inflammation through modulating the TLR-MAPK-PPAR-γ signaling pathways and intestinal microbiota.

So-called confinement effects at the interface of nanomaterials could spring up unique properties in catalytical activities and optical amplifiers. There is apparently no good reason to disregard confinement effect-amplified chemiluminescence (CL). In this work, confinement effects were first introduced into CL field using cetyltrimethylammonium bromide (CTAB) bilayer aggregates confined at the interface of the CTAB-carbon dots, which were prepared by one-step microwave irradiation using glycerol as carbon source in the presence of CTAB. Interestingly, it was found that the CTAB bilayer confined at the interface of carbon dots can amplify H2O2 induced ultraweak CL emissions, such as the Co(II)-triggered Fenton-like reaction, the peroxynitrous acid (ONOOH) system, and the peroxymonocarbonate (HCO4(-)) system. The study of fluorescent properties of the as-prepared CTAB-carbon dots and the comparison with the CL efficiency of their analogues indicated that the CTAB bilayer confined in carbon dots could act as a special micelle microenvironment, helping the access of reactive intermediates to the central carbon core. Our findings opened up new possibilities in confinement-enhanced CL emissions.

In this work, we utilized the nonionic fluorosurfactant-capped gold nanoparticles (GNPs) as a novel chemiluminescence (CL) probe for the determination of trace bisphenol A. Bisphenol A can induce a sharp decrease in CL intensity from the GNP-Co(2+)-peroxymonocarbonate (HCO4(-)) system. Under the selected experimental conditions, a linear relationship was obtained between the CL intensity and the logarithm of concentration of bisphenol A in the range of 0.05-50 μM (R(2) = 0.9936), and the detection limit at a signal-to-noise ratio of 3 for bisphenol A was 10 nM. The applicability of the proposed method has been validated by determining bisphenol A in real polycarbonate samples with satisfactory results. The recoveries for bisphenol A in spiked samples were found to be between 94.4% and 105.0%. The relative standard deviation (RSD) for 12 repeated measurements of 0.5 μM bisphenol A was 2.2%. The proposed method described herein was simple, selective and obviated the need of extensive sample pretreatment.

This demo presents an image retrieval system named RoboGene using multi-level log-based relevance feedback scheme. By analyzing previous users' perception on the content of images stored in user log, MLLR ranks the images with stronger log-based relevance to current user's positive feedback higher than those with weaker relevance. The final rank of images returned by RoboGene is the combination of rank of log-based relevance and that of low-level features.

Relevance feedback has been shown as a powerful tool to improve the retrieval performance of content-based image retrieval (CBIR). However, the feedback iteration process is tedious and time-consuming. History log consists of valuable information about previous users' perception of the content of image and such information can be used to accelerate the feedback iteration process and enhance the retrieval performance. In this paper, a novel algorithm to collect and compute the log-based relevance of the images is proposed. We utilize the multi-level structure of log-based relevance and fully mine previous users' perception of content of images in log. Experimental results show that our algorithm is effective and outperforms previous schemes.

The cellular network bandwidth increases significantly in the past few years, stimulated by many popular network-intensive applications, such as video streaming and cloud storage usages. Meanwhile, more and more users enjoy the multitasking feature of mobile devices and concurrently run a number of applications. Given these two trends and the fact that extended battery life remains to be a critical factor for small form factor devices, e.g. smartphones and tablets, it is imperative to understand the energy impact of multiple applications running concurrently on such platforms.In this paper, we characterize and understand the energy and performance impact of concurrent applications via a comprehensive set of carefully designed experiments. Specifically, we focus on network-intensive applications since most usage models today are driven by always-on communication activities. We make several significant contributions to shed light on understanding the energy behavior of concurrent applications. Firstly, we find out that running multiple network-intensive applications concurrently can significantly improve energy efficiency, up to 2.2X compared to running them separately. Secondly, we observe that power consumption from CPU and System on Chip (SoC) are the primary culprits of power dynamic for network-intensive applications; while communication components, including Network Interface Card (NIC), poses very little power consumption variation with different throughput. Thirdly, we investigate, in detail, the significant impact of signal strength on the energy consumption and throughput performance. Our findings and analysis can be applied to provide helpful guidance for a wide range of research aiming to optimize mobile device energy efficiency, e.g. transmission scheduling and protocol design in cellular networks.