6,768 research outputs found
Enhanced photocatalytic degradation of ciprofloxacin over Bi2O3/(BiO)(2)CO3 heterojunctions: Efficiency, kinetics, pathways, mechanisms and toxicity evaluation
In this study, the degradation of antibiotic ciprofloxacin (CIP) over Bi2O3/(BiO)(2)CO3 heterojunctions under simulated solar light irradiation (SSL-Bi2O3/(BiO)(2)CO3) was examined for the first time. The results showed that the Bi2O3/(BiO)(2)CO3 heterojunctions dramatically improved CIP decay efficiency. The effect of parameters showed that the CIP decay was optimized with the Bi2O3/(BiO)(2)CO3 dosage of 0.5 g/L and a wide pH range of 4.0-8.3, based on which, a kinetic model was derived to predict the remaining CIP concentration. It was found that the presence of anions like SO42-, NO3- and HCO3- decelerated the CIP decay, while the co-existence of Cl- accelerated the CIP decay. Six degradation intermediates were identified by ultra-performance liquid chromatography coupled with mass analyzer (UPLC/MS) and ion chromatographic (IC) analysis, and the decay pathways and degradation mechanism of CIP were proposed by combining the experiment data with theoretical calculation of frontier electron densities. Hydroxyl radical's reaction, photo-hole (h(+)) oxidation and reductive defluorination were found to involve in the CIP decay. The efficient alleviation on total organic carbon (TOC) and toxicity indicated that the complete mineralization and de-toxicity are possible by this system with sufficient reaction time
Application-Based Online Traffic Classification with Deep Learning Models on SDN Networks
The traffic classification based on the network applications is one important issue for network management. In this paper, we propose an application-based online and offline traffic classification, based on deep learning mechanisms, over software-defined network (SDN) testbed. The designed deep learning model, resigned in the SDN controller, consists of multilayer perceptron (MLP), convolutional neural network (CNN), and Stacked Auto-Encoder (SAE), in the SDN testbed. We employ an open network traffic dataset with seven most popular applications as the deep learning training and testing datasets. By using the TCPreplay tool, the dataset traffic samples are re-produced and analyzed in our SDN testbed to emulate the online traffic service. The performance analyses, in terms of accuracy, precision, recall, and F1 indicators, are conducted and compared with three deep learning models
Optimum dynamic characteristic control approach for building mass damper design
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142538/1/eqe2995.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142538/2/eqe2995_am.pd
Tailoring excitonic states of van der Waals bilayers through stacking configuration, band alignment and valley-spin
Excitons in monolayer semiconductors have large optical transition dipole for
strong coupling with light field. Interlayer excitons in heterobilayers, with
layer separation of electron and hole components, feature large electric dipole
that enables strong coupling with electric field and exciton-exciton
interaction, at the cost that the optical dipole is substantially quenched (by
several orders of magnitude). In this letter, we demonstrate the ability to
create a new class of excitons in transition metal dichalcogenide (TMD) hetero-
and homo-bilayers that combines the advantages of monolayer- and
interlayer-excitons, i.e. featuring both large optical dipole and large
electric dipole. These excitons consist of an electron that is well confined in
an individual layer, and a hole that is well extended in both layers, realized
here through the carrier-species specific layer-hybridization controlled
through the interplay of rotational, translational, band offset, and
valley-spin degrees of freedom. We observe different species of such
layer-hybridized valley excitons in different heterobilayer and homobilayer
systems, which can be utilized for realizing strongly interacting
excitonic/polaritonic gases, as well as optical quantum coherent controls of
bidirectional interlayer carrier transfer either with upper conversion or down
conversion in energy
Mesoscale regulation of droplet templates to tailor microparticle structures and functions
The hierarchical design of mesoscale structures in droplet templates determines the structure and functionality of the resultant microparticles. In this review, we summarize recent progress on the control of microfluidic emulsion templates for the synthesis of polymeric microparticles with desired functionality and internal structure. We introduce strategies for controlling the morphology and interfacial stability of emulsion templates. These strategies are based on manipulation of the mesoscale structure of amphiphilic molecules and nanoparticles at emulsion-droplet interfaces. We also discuss strategies for controlling the mesoscale structure of microparticles, which involve manipulating the interfacial mass-transfer and chemical reactions during template synthesis. We provide insight on the use of these strategies for the rational design and fabrication of polymeric microparticles with predictable internal structures and functionality at the single-particle level
Electroacupuncture of 2 Hz Has a Rewarding Effect: Evidence from a Conditioned Place Preference Study in Rats
Electroacupuncture (EA) has been used to suppress heroin craving in addicts and the conditioned place preference (CPP) for morphine in the rat. The question remained whether EA by itself will produce some rewarding effect. This was investigated using the CPP procedure in the present study. The results indicated that rats showed a significant preference to the 2 Hz EA-paired compartment. This rewarding effect of EA was prevented by pre-treatment with the opioid receptor antagonist naloxone [2 mg kg−1, intraperitoneally (i.p.)], CB1 cannabinoid antagonist AM251 (3 μg per rat, intracerebroventricularly) or D1 dopamine receptor antagonist SCH23390 (0.1 mg kg−1, i.p.), respectively. TempspacetempspaceIt is concluded that 2 Hz EA is capable of inducing CPP in the rat via the activation of the endogenous opioid-, cannabinoid- and dopamine-systems
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