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Activated carbon filters are widely used to remove gaseous pollutants in order to guarantee a healthy living environment. The standard method for evaluating the adsorption performance of filters is conducted at ~100 ppm. Although this accelerates the test and avoids the high requirements of the test device, it is still far from the contaminant concentration in the indoor environment, and adsorbents in practical application may show different capabilities. Therefore, this study compared several methods for predicting the adsorption performance of activated carbon and recommended a procedure based on the Wheeler–Jonas model to estimate the breakthrough curve at low concentrations using experimental data at high concentrations. The results showed that the Langmuir model and Wood–Lodewyckx correlation were the most suitable for obtaining the equilibrium adsorption capacity and mass transfer coefficient, which are critical parameters in the Wheeler–Jonas model. The predicted service life was derived from the breakthrough curve. A modification method based on a relationship with inlet gas concentration was proposed to reduce the prediction deviation of the service life. After modification, the maximum deviation was within two hours and the relative deviation was no more than 7%.

Polarization measurements have been widely used to detect aerosol properties by remote sensing in recent decades. To better understand the polarization characteristics of aerosols by lidar, the numerically exact T-matrix method was used to simulate the depolarization ratio (DR) of dust and smoke aerosols at typical laser wavelengths in this study. The results show that the DRs of dust and smoke aerosols have obviously different spectral dependences. Moreover, the ratio of DRs at two wavelengths has an obvious linear relationship with the microphysical properties of aerosols, including aspect ratio, effective radius and complex refractive index. At short wavelengths, we can use it to invert the absorption characteristics of particles, further improving the detection ability of lidar. Comparing the simulation results of different channels, DR, (color ratio) CR and (lidar ratio) LR have a good logarithmic fitting relationship at 532 nm and 1064 nm, which helps to classify the aerosol types. On this basis, a new inversion algorithm, “1β+1α+2δ”, was presented. By this algorithm, the backscattering coefficient (β), extinction coefficient (α), DR (δ) at 532 nm and 1064 nm can be used to expand the range of inversion and compare lidar data with different configurations to obtain more extensive optical characteristics of aerosols. Our study enhances the application of laser remote sensing in aerosol observations more accurately.

Aerosol microphysical properties, such as volume concentration (VC) and effective radius (ER), are of great importance to evaluate their radiative forcing and impacts on climate change. However, range-resolved aerosol VC and ER still cannot be obtained by remote sensing currently except for the column-integrated one from sun-photometer observation. In this study, a retrieval method of range-resolved aerosol VC and ER is firstly proposed based on the partial least squares regression (PLSR) and deep neural networks (DNN), combining polarization lidar and collocated AERONET (AErosol RObotic NETwork) sun-photometer observations. The results show that the measurement of widely-used polarization lidar can be reasonably used to derive the aerosol VC and ER, with the determination coefficient (R2) of 0.89 (0.77) for VC (ER) by use of the DNN method. Moreover, it is proven that the lidar-based height-resolved VC and ER at near-surface are well consistent with independent observations of collocated Aerodynamic Particle Sizer (APS). Additionally, we found that there are significant diurnal and seasonal variations of aerosol VC and ER in the atmosphere at Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL). Compared with columnar ones from the sun-photometer observation, this study provides a reliable and practical way to obtain full-day range-resolved aerosol VC and ER from widely-used polarization lidar observation, even under cloud conditions. Moreover, this study also can be applied to long-term observations by current ground-based lidar networks and spaceborne CALIPSO lidar, aiming to further evaluate aerosol climatic effects more accurately.

The new era requires port sectors cannot only promote economic development, but also need to achieve social harmony and ecological environment protection, which is in accordance with the initiative of ecological civilization construction proposed by the 17th National Congress of the Communist Party of China. Yet most performance-evaluated metrics related to social and environmental dimensions are qualitative not quantitative and hence not easy to be observed imprecisely, which makes it more complex to evaluate the ecological performance of port sectors. To address this issue, this paper introduces uncertainty theory to data envelopment analysis to deal with the imprecise data. Meanwhile, considering that the port industries usually reveal the characteristics of economies of scale and ignoring it would result in incomplete evaluation and wrong decision-making, this paper examines the ecological efficiency of port industries from the two perspectives with both technical efficiency and scale efficiency. Through the empirical analysis of China’s 17 port sectors, two major categories have emerged representing ecological efficiencies at different levels. That is, technically eco-efficient and eco-inefficient ports group as well as scale eco-efficient and eco-inefficient ports group. Moreover, the improvement radii of eco-inefficient port sectors are further calculated by models. The empirical implications can help policymakers to formulate and adjust policies on ecological civilization construction in China’s port industry.

Disinfection byproducts (DBPs) remains an ongoing issue because of their widespread occurrence and toxicity. Various organic substances in Algogenic organic matter (AOM) can produce DBPs in the chlorination process. To provide specific suggestions for the targeted removal of DBP precursors in AOM, the main biochemical components in AOM were qualitatively and quantitatively analyzed. An accurate model for predicting the DBP formation potentials (DBPFPs) of AOM was herein developed based on the dissolved organic carbon of the five main biochemical components in AOM and the DBPFPs of their corresponding surrogates. The contributions of each biochemical component to the three DBP species were evaluated, and the key components were identified. The results showed that lipids, proteins, carbohydrates, humic acid-like substances, and fulvic acid-like substances were the main biochemical components in AOM. Thereof, proteins (71.2 ± 2.1%) and carbohydrates (53.1 ± 2.1%) were the major contributor to the carbon content in intracellular organic matter and extracellular organic matter, respectively. The contribution results of biochemical components to the formation of DBPs showed that proteins were the key contributor to DBPs, suggesting that the targeted removal of proteins before the chlorination process would effectively reduce DBPs from AOM.

In recent years, phishing events occur frequently, and the detection of phishing URL has become a common concern in the field of network security. In previous studies, researchers distinguish phishing URLs from normal URLs by the string characteristics. However, this method is difficult to achieve efficient detection accuracy in the case of attacker's forgery of URL features. In this paper, we propose a phishing URL detection method based on URL content. Firstly, the simple features are used for preliminary screening, and then, the URLs that cannot be distinguished by simple features are input into the simulation environment to obtain the page content. Finally, the method based on CNN is used to detect malicious URLs based on the page content. Experiments show that our method can achieve satisfying detection accuracy.

People spend most of their time indoors. The volatile organic compounds (VOCs) in indoor air represented by toluene inevitably affect people's health. Activated carbon can effectively reduce indoor VOCs pollution. The experiments in the previous studies were carried out at the concentration of tens or hundreds of ppm, which could not reflect the actual adsorption performance of activated carbon in the actual conditions. In this study, a method was proposed to predict breakthrough curve of toluene at ~1 ppm. The method was based on Wheeler-Jonas model, the equilibrium adsorption capacity was predicted by the Freundlich equation, and the adsorption rate constant was obtained by Yoon-Nelson equation. The predicted breakthrough curves were in good agreement with the experimental data in the range of 0.5~4.0 ppm. The adsorption rate constant was predicted using the relationship with inlet concentration of toluene. When the breakout fraction was 20-85%, the relative deviation was 5.54% and 4.08% at 0.5 and 1.0 ppm. This method can predict the adsorption performance and service life of activated carbon for toluene at ppb~ppm level.

Polarization lidar has been widely used in recent decades to observe the vertical structures of aerosols and clouds in the atmosphere. To obtain more information from polarization lidar measurements, we developed a dual-polarization lidar system that can detect polarization measurements simultaneously at both 355 nm and 532 nm. The vertical distributions of atmospheric aerosols and clouds over northern China were successfully observed by the developed lidar. Observational data during two typical cases (dust events and haze episodes) were used for the analysis in this study. The results showed that for dust-dominated aerosols, the depolarization ratio (DR) at 532 nm was larger than that at 355 nm, but that for air pollutants was smaller. Our results also show that dual-polarization measurements can be used to largely improve aerosol classification. Moreover, we found that there is a good relationship between the absorption coefficient of aerosols and the ratio of DRs at 532 nm and 355 nm for dust aerosols. These results confirm that the absorption characteristics of dust aerosols cause a difference in DR at the UV and VIS wavelengths, and implying that aerosol absorption may be determined by polarization lidar at the ultraviolet and visible wavelengths.

Accurate identification of aerosols and cloud from remote sensing observations is of importance for quantitatively evaluating their radiative forcing and related impacts. Even though polarization lidar has exhibited a unique advantage of classifying atmospheric aerosols and clouds over the past several decades, polarization measurements are often achieved at one wavelength (UV or VIS) using laser remote sensing. To better identify the types of aerosols and clouds, we developed a ground-based dual-polarization lidar system that can simultaneously detect polarization measurements at wavelengths of 355 nm and 532 nm. Our results show that the volume depolarization ratios (VDRs) at 355 nm and 532 nm markedly differ for typical types of aerosols and clouds in the atmosphere. For non-spherical particles, the ratio of VDRs at 532 nm and 355 nm are 2.87 ± 1.35 for ice cloud and 1.51 ± 0.29 for dust-dominated aerosols, respectively. However, for spherical particles, the ratios are 0.43 ± 0.26 for water cloud and 0.56 ± 0.05 for air pollutants. Consequently, we proposed a simple reliable method for classifying atmospheric aerosols and clouds from polarization measurements observed by the developed lidar system. The proposed method first distinguishes clouds from aerosols using a combination of the color ratio (CR, 532 nm/355 nm) and attenuated backscattering coefficients (ABC) at 532 nm. Then, subtypes of clouds and aerosols are identified based on the ratio of VDRs at 532 nm and 355 nm. The results showed that dual-polarization lidar measurements can remarkably improve the classification of atmospheric aerosols and clouds, compared with results using a traditional method. This study illustrates that more information on atmospheric aerosols and clouds can be obtained from polarization measurements at multiple wavelengths by active remote sensing.

In the present study, we determined whether ultrasound-targeted microbubble destruction (UTMD) combined with dual targeting of transforming growth factor (TGF)-β1 and tissue inhibitors of metalloproteinase (TIMP) 1 recombinant adeno-associated virus (rAAV) can stabilize atherosclerotic vulnerable plaques. First, we used rabbit model to detect the TGF-β1/TIMP1 virus therapy result. H&E staining was used to evaluate the tissues. The protein levels of TGF-β1 and TIMP1 were detected in rabbit models. The THP-1 cells were induced into macrophages, and transfected with TGF-β1 and TIMP1 rAAV under optimized UTMD. The expression of TGF-β1 and TIMP1 was measured by RT-PCR and western blotting. We found that the apoptotic rates were induced when compared to the control group. The rAAV virus group showed a significant decrease in the p-ERT and p-AKT expression. These data support the hypothesis that TGF-β1 and TIMP1 are crucial in the regulation of atherosclerotic plaques.

In this study, two fullerenes (C60, C70) and their methano-substitutions (PC61BM, PC71BM), as electron transport materials (ETMs) in perovskite solar cells (Pero-SCs), were systematically studied. As being used as ETMs, methanofullerenes, though with lower electron mobility compared to the counterpart pristine fullerenes, lead to higher power conversion efficiencies (PCEs) of Pero-SCs. The difference is likely caused by the fill-out vacancies and smoother morphology of the interfaces between ETM and perovskite layers, as they were prepared by different methods. In addition, compared to C60 and PC61BM, C70 and PC71BM showed priority in terms of short-circuit current density, which should be attributed to fast free charge extraction abilities.

Summary: Background/Objective: The selection of surgical technique in patients with cervical spondylotic myelopathy relies on the surgeon(s) and patients' conditions. The objectives of the study were to test the hypotheses that French-door laminoplasty recovers faster than laminectomy and has good outcome measures. Methods: Data regarding surgical, radiological, and clinical outcome measures of 330 patients with cervical spondylotic myelopathy operated under French-door laminoplasty (fdLP group, n = 110), open-door laminoplasty (odLP group, n = 110), or laminectomy (LC group, n = 110) were collected from the records of institute and analyzed. Results: Patients of fdLP group (p

Skin cancer is one of the most lethal cancers in the world, which is a common type of cancer. And the early diagnosis of it is quite important. Aiming to improve the classification of skin cancer, a modified convolutional neural net- work model is proposed. Firstly, a convolutional layer and a pooling layer is added on the original network, constructed an 8-layer convolutional neural network. And then the network output value and the data label by the backward propagation adjust the network parameters. Lastly, by constantly debugging the network, the best model for the recognition network is selected. The proposed network applied to the dataset consisting of 900 cases of melanoma with the malignancy status pathologically confirmed. The results of the revised network prediction accuracy got 91.92% on training set and 89.5% on test set. The results obtained demonstrate that the proposed method is performant and can be used to predict whether the skin cancer is benign or malignant. With the development of deep learning and the clinical application of medical images, this method is expected to become a diagnostic tool for doctors to diagnose skin cancer.

A methanol-soluble diamine-modified fullerene derivative (denoted as PCBDANI) was applied as an efficient cathode buffer layer (CBL) in planar p-i-n perovskite solar cells (pero-SCs) based on the CH3NH3PbI3– x Cl x absorber. The device with PCBDANI single CBL exhibited significantly improved performance with a power conversion efficiency (PCE) of 15.45%, which is approximately 17% higher than that of the control device without the CBL. The dramatic improvement in PCE can be attributed to the formation of an interfacial dipole at the PCBM/Al interface originating from the amine functional group and the suppression of interfacial recombination by the PCBDANI interlayer. To further improve the PCE of pero-SCs, PCBDANI/LiF double CBLs were introduced between PCBM and the top Al electrode. An impressive PCE of 15.71% was achieved, which is somewhat higher than that of the devices with LiF or PCBDANI single CBL. Besides the PCE, the long-term stability of the device with PCBDANI/LiF double CBLs is also superior to that of the device with LiF single CBL.

The interlayers, including hole transporting layer (HTL) and electron transporting layer (ETL), segregating photoactive layer and the electrodes play an important role in charge extraction and transportation in perovskite solar cells (pero-SCs). Two novel copolymers, PDTSTTz and PDTSTTz-4, for the first time were applied as HTL in the n-i-p type pero-SCs, with the device structure of ITO/compact TiO2/CH3NH3PbI3-xClx/HTL/MoO3/Ag. The highest occupied molecular orbitals (HOMO) levels of PDTSTTz and PDTSTTz-4 exhibit a suitable band alignment with the valence band edge of the perovskite. Both of them lead to improved device performances compared with reference pero-SCs based on P3HT as HTL. To further balance the charge extraction and the diffusion length of charge carriers, pristine C60 was introduced at the cathode side of the pero-SCs, working together with TiO2 as ETL. With insertion of both the HTL and ETL, the performance of pero-SCs was greatly enhanced. The optimized devices exhibited impressive PCEs of 14.4% and 15.8% for devices based on PDTSTTz and PDTSTTz-4. The improved performance is attributed to better light harvest ability, decreased interface resistance and faster decay time due to the introduction of the interlayers.

In this paper, we introduce a room-temperature mixed-solvent-vapor annealing (rtMSVA) method to fabricate high performance perovskite solar cells (pero-SCs) based on MAPbI3−xClx without the need for thermal annealing (TA). An ultra-smooth perovskite thin-film with high crystallinity was obtained by the DMF/CB mixed-solvent (1 : 20, v/v) vapor annealing at room-temperature without TA and the power conversion efficiency (PCE) of the pero-SCs reached 16.4%. More importantly, the reproducibility of the PCEs is quite good among 40 different devices. Furthermore, large active area pero-SCs were fabricated with the rtMSVA method. The PCEs of the pero-SCs based on ITO and flexible PET/Ag mesh electrodes with an active area of 1.21 cm2 reached 11.01% and 7.5%, respectively. We anticipate that rtMSVA would very possibly become a promising crystallization method for the fabrication of large area pero-SCs in the near future.

For perovskite solar cells (Pero-SCs), one of the key issues with respect to the power conversion efficiency (PCE) is the morphology control of the perovskite thin-films. In this study, an easily-accessible additive polyethylenimine (PEI) is utilized to tune the morphology of CH3NH3PbI3-xClx. With addition of 1.00 wt% of PEI, the smoothness and crystallinity of the perovskite were greatly improved, which were characterized by scanning electron microscopy (SEM) and X-ray diffraction (XRD). A summit PCE of 14.07% was achieved for the p-i-n type Pero-SC, indicating a 26% increase compared to those of the devices without the additive. Both photoluminescence (PL) and alternating current impedance spectroscopy (ACIS) analyses confirm the efficiency results after the addition of PEI. This study provides a low-cost polymer additive candidate for tuning the morphology of perovskite thin-films, and might be a new clue for the mass production of Pero-SCs.

Accurate estimation of evapotranspiration (ET), especially at the regional scale, is an extensively investigated topic in the field of water science. The ability to obtain a continuous time series of highly precise ET values is necessary for improving our knowledge of fundamental hydrological processes and for addressing various problems regarding the use of water. This objective can be achieved by means of ET data assimilation based on hydrological modeling. In this paper, a comprehensive review of ET data assimilation based on hydrological modeling is provided. The difficulties and bottlenecks of using ET, being a non-state variable, to construct data assimilation relationships are elaborated upon, with a discussion and analysis of the feasibility of assimilating ET into various hydrological models. Based on this, a new easy-to-operate ET assimilation scheme that includes a water circulation physical mechanism is proposed. The scheme was developed with an improved data assimilation system that uses a distributed time-variant gain model (DTVGM), and the ET-soil humidity nonlinear time response relationship of this model. Moreover, the ET mechanism in the DTVGM was improved to perfect the ET data assimilation system. The new scheme may provide the best spatial and temporal characteristics for hydrological states, and may be referenced for accurate estimation of regional evapotranspiration.

Accurate estimates of evapotranspiration (ET) are important to skillful predictions of runoff, soil moisture and crop productivity. In this study, ET was simulated over three years in China by integrating remotely-sensed data with the simulation model SEBS-China. SEBS-China was developed from the Surface Energy Balance System (SEBS) model that is used to estimate atmospheric turbulent heat fluxes and evaporative fraction through satellite-derived radiation fluxes and land surface temperatures coupled with near-surface meteorological variables. Simulated regional ET was first evaluated using experimental data from the Changbai Mountains and five river basins in China. Average annual simulated ET agreed well with the observed data, based on the detailed results through comparative validation. Regional ET derived from SEBS-China was then compared with the simulated ET from the Common Land Model (CoLM). Both of the models simulated regional ET well, with a few overestimated areas such as in the Qinghai–Tibet Plateau, YanShan and South Daxing'anling Mountains. We conclude that more efficient ET estimation can be achieved through combining remotely-sensed information with land surface models.

Passive remote sensing has been widely used in recent decades to obtain global particulate matter (PM) mass concentration at daytime and under cloud-free condition. In this study, a retrieval method was developed for providing PM (PM10 and PM2.5) mass concentration both at daytime and nighttime using the latest data version (V4.10) from space-borne Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar measurements. The advantage of the method is that PM10 & PM2.5 mass concentrations were obtained for seven aerosol types respectively base on active remote sensing observation at daytime and nighttime, even under cloudy condition. The results show that satellite-based PM mass concentrations are in good agreement with in-situ observations from 1602 ground monitoring sites throughout the world. Moreover, global distributions of PM10 and PM2.5 mass concentration during 2007–2016 were investigated, showing that for Beijing the annual mean PM2.5 mass concentration at nighttime is 11.31% less than those at daytime, however for London is 36.62%. It is suggested that diurnal variations in PM2.5 mass concentration are closely related to human activities. This work provides a reliable high-resolution database for long-term particulate mass concentrations on the global scale, which is of importance to evaluate aerosol impacts on climate, environment as well as ecosystem.

In this paper, triple cathode buffer layers (CBLs) composed of phenyl-C61-butyric acid methyl ester (PCBM), C60, and LiF layers were introduced into the planar p-i-n perovskite solar cells (p-i-n PSCs) with a device structure of ITO/PEDOT:PSS/CH3NH3PbI3-xClx/CBLs/Al. For comparison, a single CBL of PCBM and a double CBL of PCBM/LiF were also investigated in the p-i-n PSCs. On the basis of the PCBM buffer layer, the addition of a thin LiF layer facilitated the charge collection process and led to the dramatic improvement of the power conversion efficiency (PCE) of the PSCs up to 14.69% under an illumination of AM 1.5G, 100 mW/cm(2), which is to date one of the highest efficiencies of the p-i-n PSCs. By further insertion of a C60 layer between PCBM and LiF in the triple CBLs, a PCE of 14.24% was obtained, and more importantly, the PCBM/C60/LiF triple CBLs are very helpful for improving the stability of the devices and making the LiF layer less thickness-sensitive for achieving high performances of the p-i-n PSCs.

Cyclopentadienyliron (CpFe) groups have been successfully attached on the surface of reduced graphene oxide (rG) by a ligand-exchange reaction of ferrocene (Cp2Fe) and rG to produce CpFe-modified reduced graphene oxide (rGFeCp), which exhibits good processability in many organic solvents. In a similar one-pot reaction, graphite was efficiently exfoliated using Cp2Fe as the intercalator to form CpFe-attached free-standing graphene nanosheets (GFeCp, ∼10 layers). Upon pyrolysis and ammonia activation, rGFeCp and GFeCp were converted to iron/nitrogen co-doped porous graphenes, namely, rGFe-800a and GFe-800a, respectively. The obtained rGFe-800a exhibited good electrochemical performance for the oxygen reduction reaction (ORR) under alkaline conditions (0.1 M KOH) with a low half-wave potential at −0.29 V, a dominant four-electron transfer mechanism (n = 3.5 at −1.0 V), and a maximum diffusion-limiting current density of 4.86 mA cm−2. In addition, rGFe-800a showed excellent methanol tolerance, superior to that of commercial 20% Pt/C. The effect of iron/nitrogen co-doping plays a key role in the good ORR activities of the as-prepared materials.

Background and Objectives: The diagnosis of cancer is concerned, and the prediction of cell carcinoma is of great importance for the treatment. Materials and Methods: First, we obtain a series of slices of tumor cell pathology in clinical data, with being followed training sets and test sets gained by adding data model. Then, we design a convolutional neural network training and prediction model. After that, we optimize parameters for training and prediction model, combining experience. Results: In experiment, the accuracy of the model predicting for cell carcinoma is 87.38%. Conclusions: This study provides a reference that predicts the extent of cell carcinoma progression by using deep learning model.

In order to meet the requirements of ultrasound bone density measurement, we proposed a software solution to improve the accuracy and speed of measurement of bone mineral density of the ultrasound bone densitometer. We used a high-speed USB interface chip FT232H, along with a high-speed AD converter chip to calculate speed of sound (SOS), broadband ultrasound attenuation (BUA ) and other bone density parameters in the PC software. This solution improved the accuracy of the measurement data, reduced the measurement time and increased the quality of the displayed image. It is well concluded that the new software can greatly improve the accuracy and transmission speed of bone density measurement data through a high-speed USB interface and a software data processing technology.

The next generation of Augmented Reality (AR) games will require real and virtual objects to coexistin motionin immersive game environments. This will require the illusion that real and virtual objects interact physically together in a plausible way. TheMotion in Augmented Reality Games(MARG) engine described in this paper has been developed to allow these kinds of game environments. The paper describes the design and implementation of the MARG engine and presents two proof-of-concept AR games that have been developed using it. Evaluations of these games have been performed and are presented to show that the MARG engine takes an important step in developing the next generation of motion-rich AR games.