Establishment and verification of novel TNM staging system for lung mucinous adenocarcinoma.

BACKGROUND: Lung adenocarcinoma is a high-mortality rate cancer. Within this category, Lung mucinous adenocarcinoma (LMAC) is a rare and distinct subtype of lung adenocarcinoma necessitating further investigation. The study was launched to compare the difference of survival features between LMAC and lung non-mucinous adenocarcinoma (LNMAC) and to investigate the significance and demand for developing a new staging system tailored to LMAC. METHODS: This retrospective study assessed the suitableness of the current staging system for LMAC. It compared the overall survival (OS) between LMAC and LNMAC from 2004 to 2020 (LNMAC: 160,387; LMAC: 6,341) and instituted a novel classification framework for LMAC based on US population. Verification group consisting of patients from two Chinese medical centers from 2010 to 2018 (n = 392) was set to ascertain the applicability of this novel system. The primary endpoint was OS. To minimize the bias, propensity score match (PSM) was employed. Survival analysis and Log-rank test were executed to explore the survival features of LMAC. RESULTS: The results indicated that the existed staging system was not suitable for LMAC. Patients diagnosed with LMAC exhibited a superior OS compared to those with LNMAC in stage IA2 (P < 0.0001), IA3 (P < 0.0001), IB (P = 0.0062), IIA (P = 0.0090), IIB (P = 0.0005). In contrast, a worse OS in stage IVA (P = 0.0103) was found in LMAC patients. The novel classification system proposed for LMAC proved to be highly applicable and demonstrated substantial efficacy, as confirmed by the verification group. CONCLUSION: The newly established classification system was more effective for LMAC, but it necessitates large-scale verification to confirm its applicability and reliability.

Cs4 Zn5 P6 S18 I2 : the Largest Birefringence in Chalcohalide Achieved by Highly Polarizable Nonlinear Optical Functional Motifs.

Chalcohalides not only keep the balance between the nonlinear optical (NLO) coefficient and wide band gap, but also provide a promising solution to achieve sufficient birefringence for phase-matching ability in NLO crystals. In this study, a novel chalcohalide, Cs4 Zn5 P6 S18 I2 (1) is successfully synthesized, by incorporating the highly electropositive Cs and the large electronegative I element into the zinc thiophosphate. Its 3D open framework features an edge-shared by distorted [ZnS4 ], ethanol-like [P2 S6 ], and unusual [ZnS2 I2 ] polyhedrons, which is inconsistent with the soft-hard-acids-bases theory. Remarkably, compound 1 simultaneously exhibits the large second-harmonic generation (SHG, 1.1×AgGaS2 , @1.3 µm) and a wide band gap (3.75 eV) toward a high laser-induced damage threshold (16.7×AgGaS2 , @1.06 µm), satisfying the rigorous requirements for a prominent infrared NLO material with concurrent SHG intensity (≥0.5×AGS) and band gap (≥3.5 eV). Moreover, to the best of the knowledge, the experimental result shows that phase 1 has the largest birefringence (0.108, @546 nm) in chalcohalide and meets phase-matching behavior demand originating from the polarizable anisotropy of NLO-functional motifs. This finding may provide great opportunities for designing birefringent chalcohalides.

AIn4S6Cl (A = Rb and Cs) and Pb5Sn3Q10Cl2 (Q = S and Se): quaternary chalcohalides with mixed anionic coordination exhibit photocurrent responses.

Mixed-anionic compounds have caught considerable attention due to their flexible coordination manners and abundant physical properties. Four new chalcohalides RbIn4S6Cl (1), CsIn4S6Cl (2), Pb5Sn3S10Cl2 (3) and Pb5Sn3Se10Cl2 (4) were successfully obtained by the high-temperature halide salt flux method. Compounds 1 and 2 have layered structures that consist of octahedral InS6 and aliovalent-anionic InS3Cl units. Compounds 3 and 4 feature 3-D structural frameworks built by [Pb4SnQ8Cl4]6- and [PbSn2Q6]2- (Q = S and Se) polyhedral chains, in which partial Pb2+ cations are coordinated by Q2- and Cl- anions. Compounds 1-4 have optical band gaps close to the wavelength range of visible light and exhibit significant photocurrent responses of 28.75 nA cm-2, 55.12 nA cm-2, 19.58 mA cm-2, and 36.12 µA cm-2 with on/off ratios 30.0, 2.5, 15.7 and 2.6, respectively, implying their potential for photovoltaic applications. To the best of our knowledge, compound 3 has the largest photocurrent response among all non-oxides. In addition, the activation energies of 1-4 are well below 0.3 eV, which makes these compounds interesting for potential applications in electrochemical devices. This work sheds light on the exploration of promising photocurrent response materials in the mixed-anionic compound system.

[Detecting the moisture content of forest surface soil based on the microwave remote sensing technology.] / 基于微波遥感技术探测森林地表土壤含水率.

The moisture content of forest surface soil is an important parameter in forest ecosystems. It is practically significant for forest ecosystem related research to use microwave remote sensing technology for rapid and accurate estimation of the moisture content of forest surface soil. With the aid of TDR-300 soil moisture content measuring instrument, the moisture contents of forest surface soils of 120 sample plots at Tahe Forestry Bureau of Daxing'anling region in Heilongjiang Province were measured. Taking the moisture content of forest surface soil as the dependent variable and the polarization decomposition parameters of C band Quad-pol SAR data as independent variables, two types of quantitative estimation models (multilinear regression model and BP-neural network model) for predicting moisture content of forest surface soils were developed. The spatial distribution of moisture content of forest surface soil on the regional scale was then derived with model inversion. Results showed that the model precision was 86.0% and 89.4% with RMSE of 3.0% and 2.7% for the multilinear regression model and the BP-neural network model, respectively. It indicated that the BP-neural network model had a better performance than the multilinear regression model in quantitative estimation of the moisture content of forest surface soil. The spatial distribution of forest surface soil moisture content in the study area was then obtained by using the BP neural network model simulation with the Quad-pol SAR data.

[The characteristics of microstructure and chemical compositions of K-feldspar, sphene and zircon with zoning structure].

K-feldspar, sphene and zircon in quartz monzonite from Shahewan, south Qinling, showing strong zoning structure. Characteristics of microstructure and chemical compositions of K-feldspar, sphene and zircon with zoning structure were investigated using advanced instruments of electron probe micro analyses equipped with wavelength dispersive spectrometer (EPM-WDS), scanning electron microscopy with energy dispersive spectrometer (SEM-EDS) and laser ablation--inductively coupled plasma--mass spectrometry (LA-ICP-MS). Our study suggests that K+ could be substituted by small amounts of Na+, Ca2+, Ba2+, Fe2+ and Ce3+. Ca2+ in sphene could be replaced by V3+, Ce3+, Ba2+ and Ti4+ could be substituted by both Fe2+ and Al3+. Zircon contains trace elements like Fe, Th, U, Nb, Ta, Y, Hf, Yb and Pb. Concentration of Si, Al, K, Ca, Na, Mg and Ba in K-feldspar ranked from high to low, among which the contents of K and Na are negatively correlated, the lighter part of BSE images featuring K-feldspar is attributed to comparably higher Ba content, additionally, Si and K contents are elevated while Na content decreased rimward. Ca, Si, Ti, Ba, V, Ce, Al and Fe concentration listed downward, among which higher iron content corresponds to brighter portion of BSE images. Element concentration of zircon could be ranked from high to low as Zr, Si, Nd, Ce, Hf, U, Pb and Th, in which Hf and Zr exhibit negatively correlated. Zr concentration increased while Hf, U and Th concentration decreased from core to rim.

[Inversion of vegetation canopy's chlorophyll content based on airborne hyperspectral image].

By using the airborne hyperspectral remote sensing data of Liangshui National Nature Reserve in Yichun of Heilongjiang Province, Northeast China, 15 spectral parameters including red edge area, triangular vegetation index, and normalized difference vegetation index, etc. were extracted, and in combining with 5 geographical parameters including slope, aspect, elevation, canopy density and total vegetation coverage, and by using SPAD-502, the vegetation canopy's relative chlorophyll content in the reserve were measured, with the correlations of the leaf spectral reflectivity, its first-order derivative and other deformations with the SPAD value analyzed. A prediction model for relative chlorophyll content was established by adopting the kernel-based partial least-squares regression, and a quantitative estimation of the vegetation canopy's relative chlorophyll content in the study area was carried out with the established model. The results showed that the model performed best when the sections were three and the principle components were ten. The co-efficient of determination of the model was R2 = 0.855, the mean absolute percent error was 9.6%, and the prediction precision was 89.7%.

[Forest carbon rates at different scales in Northeast China forest area].

To accurately estimate forest carbon storage is of significance in researching terrestrial ecosystem carbon cycle and global change. Based on the survey data from the representative plots in Northeast China forest area (Da Xing' an Mountains, Xiao Xing' an Mountains, Zhangguangcai Mountains and Changbai Mountains) in 2007 and 2008 and the inventory data in the same period, and by using the models for estimating ground tree biomass, shrub biomass, and grass biomass and the Multi N/C 3000 for measuring forest carbon rate in laboratory, this paper calculated the forest biomass and carbon storage in the forest area, and analyzed the variation and stability of the forest carbon rates at different scales. There was an obvious difference in the carbon rates among tree organs, being the highest in leaf (0.4448), followed by in branch (0.4422), bark (0.4398), and trunk (0.4351). In Changbai and Zhangguangcai Mountains, coniferous forest had a higher carbon rate than broad-leaved forest; whereas in Daxing' an and Xiaoxing' an mountains, it was in adverse. In Northeast China forest area, the forest carbon rates were relatively stable, with a total value of 0.44.

[Quantitative driving analysis of forest biomass changes in Changbai Mountain forest region].

Based on the forest inventory data and single tree biomass model, the forest biomass in the sampling plots in Changbai Mountain forest region was calculated, and, by using the estimated forest biomass from four periods' remote sensing data and based on high accuracy remote sensing models, the changes of regional forest biomass were analyzed. In the meanwhile, the driving factors such as meteorological factors, management factors, and socio-economic factors that caused forest biomass change were selected by bootstrap method, and the driving model of forest biomass change in different time period was set up by using partial least-squares method. The Variable Importance in Projection (VIP) values representing the importance of each of the factors affecting the forest biomass change in study region were calculated. The results showed that the influence of human activity factors (VIP values) on Changhai Mountain forest biomass changes was less than that of natural factors, suggesting that the national forest protection policy for forest regions had played an obvious role. Our research broadened the content of forest biomass change driving analysis, and the introduction of calculating VIP value, which can quantitatively represent the influence of driving factors to forest biomass change, provided a new way for the quantitative analysis on forest biomass change.

[Forest canopy leaf area index in Maoershan Mountain: ground measurement and remote sensing retrieval].

Leaf area index (LAI) is one of the most important structural parameters of terrestrial ecosystem, while the remote sensing retrieval and the ground optical instrument measurement and based on canopy gap model are the effective approaches to rapidly obtain LAI. However, these two approaches can only acquire effective LAI (LAI(e)), due to the clumping of vegetation canopy. Taking the experimental forest farm of Northeast Forestry University at Maoershan Mountain in Heilongjiang Province of Northeast China as study site, this paper measured the forest canopy LAI(e) by LAI2000, and estimated the LAI by the combination of TRAC (tracing radiation and architecture of canopies) measurement of foliage clumping index. A LAI remote sensing retrieval model was constructed through the analysis of the relationships between different vegetation indices calculated from Landsat5-TM and measured LAI(e). The results showed that at the study site, the LAI of broad leaved forests was close to the LAI(e), but the LAI of needle leaved forests was 27% larger than the LAI(e). Reduced simple ratio index (RSR) had the highest relationship with measured LAI(e) (R2 = 0.763, n = 23), which could be used as the best predictor of LAI. The LAI at study site increased rapidly with increasing elevation when the elevation was below 400 m, but had a slow increase when the elevation was from 400 m to 750 m. When the elevation was above 750 m, the LAI decreased. There was a significant correlation between the forest canopy LAI and aboveground biomass.

A low-noise low-power amplifier for implantable device for neural signal acquisition.

This paper presents a low-noise low-power amplifier for implantable device for neural signal acquisition. By operating MOS transistors in the subthreshold region, smaller low-frequency noise and lower power consumption can be achieved. A low power, low-noise common-drain buffer and a low-noise, high-linearity, low pass filter are used for high frequency noise filtering. Post-layout simulation shows the input referred noise of the system is 2.19microVrms from 10Hz to 10 KHz, power consumption is 55.8microW, and the NEF is 2.53. The amplifier was fabricated using a TSMC 0.18microm 1P6M CMOS process. Simulation results show that this low-noise, low-power amplifier is suitable for implantable device applications.

[Effects of topographic correction on remote sensing estimation of forest biomass].

Based on four commonly used models (Cosine model, C model, C + SCS model, and Minnaert model), the topographic effects in Landsat-5 image of Maoershan region in Heilongjiang Province acquired on July 21, 2007 were calibrated on the platform of IDL language. The 4 models were validated from the aspects of visual differences and quantitative statistical features of the images. After the correlation analysis on the corrected remote sensing data and the forest biomass data, the biomass retrieving models were constructed. Furthermore, the effects of different topographic factors on the estimation of forest biomass were studied. The results showed that due to its liner presumption, the topographic correction combined with K-T transformation was not suitable for forest biomass estimation, and the correlations between the remote sensing data and the forest biomass fluctuated significantly. The parameters of the transformation needed to be adjusted in accordance with the information of land surface. The information content of vegetation index was significantly increased after topographic correction, and the correlation between vegetation index and forest biomass was enhanced greatly. Among the four models, Cosine model over-corrected the shaded areas in image, C model and C + SCS model had good correction performance by using semi-empirical parameters, while Minnaert model decreased the error of biomass estimation and improved the precision of remote sensing retrieving models effectively.

[Remote sensing quantitative retrieval of soil water content in desertification region].

An empirical model was set up by using TM data to get the reflectance of the earth surface in Naiman Banner of Kerqin Sandy Land, and the influence of vegetation on the pixel reflectance was eliminated by optical vegetation coverage model. The regression model between soil water content and earth surface reflectance was set up to retrieve soil water content, and the accuracy of the retrieved results were validated by in situ data. The results showed that the theoretical and practical precision was 81.81% and 92.17%, respectively, suggesting that the remote sensing quantitative retrieval of soil water content was scientifically available.