[Monitoring and Analysis of the Spatio-temporal Change Characteristics of the PM2.5 Concentration Over Beijing-Tianjin-Hebei and Its Surrounding Regions Based on Remote Sensing].

To analyze the spatial and temporal variation characteristics of PM2.5 in Beijing-Tianjin-Hebei and its surrounding regions, a 1 km resolution AOT product was retrieved from MODIS data and the remote sensing inversion of the PM2.5 concentration in Beijing-Tianjin-Hebei and its surrounding regions was realized using the geographically weighted regression model. On this basis, the synthesis results of multi-timescale PM2.5 concentrations were verified and analyzed. Finally, the spatial and temporal variation characteristics of PM2.5 in Beijing-Tianjin-Hebei and its surrounding regions between 2016 and 2017 were compared and analyzed using different time scales. The results show that the verification of the PM2.5 concentration products of the average daily, monthly, and annual averages are in general good. The larger the time scale is, the better is the PM2.5 effect of the remote sensing estimation. The relative accuracy of the annual average PM2.5 products is higher than 80%. However, the precision of the PM2.5 remote sensing results for 2016 and 2017 is relatively close (at the same time scales). The PM2.5 distribution in Beijing-Tianjin-Hebei and its surrounding regions shows a seasonal variation (winter > autum ≈ spring > summer). The spatial distribution is high in the southern but low in the northern part. Compared with 2016, the average PM2.5 concentration decreased by~9.2% in 2017. The area with high values was significantly reduced. High PM2.5 concentrations occurred in November and December and low concentrations were observed in August. The PM2.5 concentration change between 2017 and 2016 is closely related to the comprehensive control crucial action and specific inspection activities of air pollution in 2017, which indirectly account for the effect of the reduction of the atmospheric pollution.

Wavelength-dependent backscattering measurements for quantitative monitoring of apoptosis, part 1: early and late spectral changes are indicative of the presence of apoptosis in cell cultures.

Apoptosis, a form of programmed cell death with unique morphological and biochemical features, is dysregulated in cancer and is activated by many cancer chemotherapeutic drugs. Noninvasive assays for apoptosis in cell cultures can aid in screening of new anticancer agents. We have previously demonstrated that elastic scattering spectroscopy can monitor apoptosis in cell cultures. In this report we present data on monitoring the detailed time-course of scattering changes in a Chinese hamster ovary (CHO) and PC-3 prostate cancer cells treated with staurosporine to induce apoptosis. Changes in the backscattering spectrum are detectable within 10 min, and continue to progress up to 48 h after staurosporine treatment, with the magnitude and kinetics of scattering changes dependent on inducer concentration. Similar responses were observed in CHO cells treated with several other apoptosis-inducing protocols. Early and late scattering changes were observed under conditions shown to induce apoptosis via caspase activity assay and were absent under conditions where apoptosis was not induced. Finally, blocking caspase activity and downstream apoptotic morphology changes prevented late scattering changes. These observations demonstrate that early and late changes in wavelength-dependent backscattering correlate with the presence of apoptosis in cell cultures and that the late changes are specific to apoptosis.

Wavelength-dependent backscattering measurements for quantitative monitoring of apoptosis, part 2: early spectral changes during apoptosis are linked to apoptotic volume decrease.

Elastic scattering spectroscopy (ESS), in the form of wavelength-dependent backscattering measurements, can be used to monitor apoptosis in cell cultures. Early changes in backscattering upon apoptosis induction are characterized by an overall decrease in spectral slope and begin as early as 10 to 15 min post-treatment, progressing over the next 6 to 8 h. The timescale of early scattering changes is consistent with reports of the onset of apoptotic volume decrease (AVD). Modeling cellular scattering with a fixed distribution of sizes and a decreasing index ratio, as well as an increased contribution of the whole cell to cellular scattering, resulting from increased cytoplasmic density, is also consistent with observed spectral changes. Changes in ESS signal from cells undergoing osmotically-induced volume decrease in the absence of apoptosis were similar, but smaller in magnitude, to those of apoptotic cells. Further, blockage of Cl(-) channels, which blocks AVD and delays apoptosis, blocked the early scattering changes, indicating that the early scattering changes during apoptosis result, at least partially, from AVD. Work continues to identify the additional sources of early spectral scattering changes that result from apoptosis induction.

Application of a two-dimensional model for predicting the pressure-flow and compression properties during column packing scale-up.

A two-dimensional model was formulated to describe the pressure-flow behavior of compressible stationary phases for protein chromatography at different temperatures and column scales. The model was based on the assumption of elastic deformation of the solid phase and steady-state Darcy flow. Using a single fitted value for the empirical modulus parameters, the model was applied to describe the pressure-flow behavior of several adsorbents packed using both fluid flow and mechanical compression. Simulations were in agreement with experimental data and accurately predicted the pressure-flow and compression behavior of three adsorbents over a range of column scales and operating temperatures. Use of the described theoretical model potentially improves the accuracy of the column scale-up process, allowing the use of limited laboratory scale data to predict column performance in large scale applications.

Robust speaker's location detection in a vehicle environment using GMM models.

Abstract-Human-computer interaction (HCI) using speech communication is becoming increasingly important, especially in driving where safety is the primary concern. Knowing the speaker's location (i.e., speaker localization) not only improves the enhancement results of a corrupted signal, but also provides assistance to speaker identification. Since conventional speech localization algorithms suffer from the uncertainties of environmental complexity and noise, as well as from the microphone mismatch problem, they are frequently not robust in practice. Without a high reliability, the acceptance of speech-based HCI would never be realized. This work presents a novel speaker's location detection method and demonstrates high accuracy within a vehicle cabinet using a single linear microphone array. The proposed approach utilize Gaussian mixture models (GMM) to model the distributions of the phase differences among the microphones caused by the complex characteristic of room acoustic and microphone mismatch. The model can be applied both in near-field and far-field situations in a noisy environment. The individual Gaussian component of a GMM represents some general location-dependent but content and speaker-independent phase difference distributions. Moreover, the scheme performs well not only in nonline-of-sight cases, but also when the speakers are aligned toward the microphone array but at difference distances from it. This strong performance can be achieved by exploiting the fact that the phase difference distributions at different locations are distinguishable in the environment of a car. The experimental results also show that the proposed method outperforms the conventional multiple signal classification method (MUSIC) technique at various SNRs.