Design and Realization of On-line Enterprise Office Automation System

AbstractThis paper discusses the online business office automation system development process, office automation system requirement analysis, system function design, database design and implementation of the system is introduced, the system function and database design and realization of the system. Through the system function data flow analysis, get the logical structure of database system, and on this basis, the physical structure of database to create all kinds of information inquiry, update operation

Employment hysteresis in the United States during the COVID-19 pandemic

In this paper, we test the validity of the employment hysteresis hypothesis. For this purpose, we use daily employment data at the national and state levels in the United States from January 8, 2020, to May 30, 2020. We apply the modified version of the Kapetanios-Shin unit root test, along with finite-sample critical values. We find that the employment hysteresis hypothesis is valid in the United States during the COVID-19 era. The validity of the findings does not change when data at the national and state levels are used. The evidence is also valid when the employment levels for all firms and small firms are considered. The results are also robust to employment levels for workers at different income levels and employment in five different sectors

Characterization of Laser-Resistant Port Wine Stain Blood Vessels Using In Vivo Reflectance Confocal Microscopy.

Background and objectivesPort wine stain (PWS) is a congenital vascular malformation of the human skin. Laser is the treatment of choice for PWS. Laser-resistant PWS is one crucial factor accounting for inadequate treatment outcome, which needs to be fully characterized. This study aims to quantitatively characterize the morphology of laser-resistant PWS blood vessels in the upper papillary dermis using in vivo reflectance confocal microscopy (RCM).Study design/materials and methodsA total of 42 PWS subjects receiving laser treatment from August 2016 through July 2018 were enrolled into this study. Thirty-three subjects had facial PWS; nine had extremity PWS. All subject's PWS received multiplex 585/1,064 nm laser treatment. RCM images were taken before and after treatment. The density, diameter, blood flow, and depth of PWS blood vessels were analyzed.ResultsWe found 44.4% PWS on the extremities (four out of nine subjects) were laser-resistant, which was significantly higher (P < 0.001) when compared with those PWS on the face (15.2%, 5 out of 33 subjects). The laser-resistant facial PWS blood vessels had significantly higher blood flow (1.35 ± 0.26 U vs. 0.89 ± 0.22 U, P < 0.001), larger blood vessel diameters (109.60 ± 18.24 µm vs. 84.36 ± 24.04 µm, P = 0.033) and were located deeper in the skin (106.01 ± 13.87 µm vs. 87.82 ± 12.57 µm, P < 0.001) in the skin when compared with laser-responsive PWS on the face. The average PWS blood vessel density (17.01 ± 4.63/mm2 vs. 16.61 ± 4.44/mm2 , P = 0.857) was not correlated to the laser resistance.ConclusionsLaser-resistant PWS blood vessels had significantly higher blood flow, larger diameters, and were located deeper in the skin. RCM can be a valuable tool for a prognostic evaluation on laser-resistant lesions before treatment, thereby providing guidance for tailored laser treatment protocols, which may improve the therapeutic outcome. The limitations for this study include relative small sample size and acquisitions of different blood vessels before and after 2 months of treatment. Lasers Surg. Med. © 2019 Wiley Periodicals, Inc

Dynamic Task Scheduling in Remote Sensing Data Acquisition from Open-Access Data Using CloudSim

With the rapid development of cloud computing and network technologies, large-scale remote sensing data collection tasks are receiving more interest from individuals and small and medium-sized enterprises. Large-scale remote sensing data collection has its challenges, including less available node resources, short collection time, and lower collection efficiency. Moreover, public remote data sources have restrictions on user settings, such as access to IP, frequency, and bandwidth. In order to satisfy users’ demand for accessing public remote sensing data collection nodes and effectively increase the data collection speed, this paper proposes a TSCD-TSA dynamic task scheduling algorithm that combines the BP neural network prediction algorithm with PSO-based task scheduling algorithms. Comparative experiments were carried out using the proposed task scheduling algorithms on an acquisition task using data from Sentinel2. The experimental results show that the MAX-MAX-PSO dynamic task scheduling algorithm has a smaller fitness value and a faster convergence speed

Dummy Molecularly Imprinted Polymers-Capped CdTe Quantum Dots for the Fluorescent Sensing of 2,4,6-Trinitrotoluene

Molecularly imprinted polymers (MIPs) with trinitrophenol (TNP) as a dummy template molecule capped with CdTe quantum dots (QDs) were prepared using 3-aminopropyltriethoxy silane (APTES) as the functional monomer and tetraethoxysilane (TEOS) as the cross linker through a seedgrowth method via a sol gel process (i.e., DMIP@QDs) for the sensing of 2,4,6-trinitrotoluene (TNT) on the basis of electron-transfer-induced fluorescence quenching. With the presence and increase of TNT in sample solutions, a Meisenheimer complex was formed between TNT and the primary amino groups on the surface of the QDs. The energy of the QDs was transferred to the complex, resulting in the quenching of the QDs and thus decreasing the fluorescence intensity, which allowed the TNT to be sensed optically. DMIP@QDs generated a significantly reduced fluorescent intensity within less than 10 min upon binding TNT. The fluorescence-quenching fractions of the sensor presented a satisfactory linearity with TNT concentrations in the range of 0.8-30 mu M, and its limit of detection could reach 0.28 mu M. The sensor exhibited distinguished selectivity and a high binding affinity to TNT over its possibly competing molecules of 2,4-dinitrophenol (DNP), 4-nitrophenol (4-NP), phenol, and dinitrotoluene (DNT) because there are more nitro groups in TNT and therefore a stronger electron-withdrawing ability and because it has a high similarity in shape and volume to TNP. The sensor was successfully applied to determine the amount of TNT in soil samples, and the average recoveries of TNT at three spiking levels ranged from 90.3 to 97.8% with relative standard deviations below 5.12%. The results provided an effective way to develop sensors for the rapid recognition and determination of hazardous materials from complex matrices.Molecularly imprinted polymers (MIPs) with trinitrophenol (TNP) as a dummy template molecule capped with CdTe quantum dots (QDs) were prepared using 3-aminopropyltriethoxy silane (APTES) as the functional monomer and tetraethoxysilane (TEOS) as the cross linker through a seedgrowth method via a sol gel process (i.e., DMIP@QDs) for the sensing of 2,4,6-trinitrotoluene (TNT) on the basis of electron-transfer-induced fluorescence quenching. With the presence and increase of TNT in sample solutions, a Meisenheimer complex was formed between TNT and the primary amino groups on the surface of the QDs. The energy of the QDs was transferred to the complex, resulting in the quenching of the QDs and thus decreasing the fluorescence intensity, which allowed the TNT to be sensed optically. DMIP@QDs generated a significantly reduced fluorescent intensity within less than 10 min upon binding TNT. The fluorescence-quenching fractions of the sensor presented a satisfactory linearity with TNT concentrations in the range of 0.8-30 mu M, and its limit of detection could reach 0.28 mu M. The sensor exhibited distinguished selectivity and a high binding affinity to TNT over its possibly competing molecules of 2,4-dinitrophenol (DNP), 4-nitrophenol (4-NP), phenol, and dinitrotoluene (DNT) because there are more nitro groups in TNT and therefore a stronger electron-withdrawing ability and because it has a high similarity in shape and volume to TNP. The sensor was successfully applied to determine the amount of TNT in soil samples, and the average recoveries of TNT at three spiking levels ranged from 90.3 to 97.8% with relative standard deviations below 5.12%. The results provided an effective way to develop sensors for the rapid recognition and determination of hazardous materials from complex matrices