Evidence of fluid evolution of Baoshan Cu−Pb−Zn polymetallic deposit: Constraints from in-situ sulfur isotope and trace element compositions of pyrite

In-situ LA-ICP-MS and S isotopes of pyrite from the Baoshan Cu polymetallic deposit were conducted to investigate the ore-forming process and the enrichment mechanism of elements. Three generations of pyrite (Py I, Py II, and Py III) in the skarn-type ores and pyrite in the carbonate-hosted sulfide ores from central, western, and northern (C_Py, W_Py, and N_Py) mining districts are selected for comparison. Compared with Py I and Py III, the contents of most elements in Py II are apparently higher. The As and Se contents are high within a wide range and are decoupled in the growth band of the C_Py. The highest As, Se, and Pb contents were found in W_Py and N_Py. These results indicate the drastic changes in the temperature and fluid mixing during the mineralization. The occurrence of fluctuation and change in temperature and f(O₂) was triggered by intermittent pulses of magmatic-hydrothermal fluids, mixing with meteoric water, and water−rock interactions. The sulfur isotopes of all species of pyrite indicated the magmatic source. The change in the f(O₂) conditions caused slight differences in the sulfur isotope compositions. Consequently, a metallogenic model was proposed to explain the ore-forming processes.     

跨行政区游憩空间柔性一体化研究 ——以高莱茵河沿岸地区为例

随着城市化与区域一体化的迅速发展,不同行政区之间的联动关系越来越紧密,这种联动关系在城市各功能空间的设计上有所体现,更渗透到了与市民息息相关的游憩空间建构之中。受制于行政管理等方面的原因,在跨行政区的游憩空间一体化实施过程中,往往会采取一系列柔性措施。以欧洲高莱茵河沿岸地区为研究对象,分析高莱茵河沿岸地区游憩空间的发展与现状,总结其游憩空间体系的构建特点,为中国跨城市河流沿岸的游憩空间柔性一体化建构提供策略与建议。     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).     

Removing data and using metafounders alleviates biases for all traits in Lacaune dairy sheep predictions

Bias in dairy genetic evaluations, when it exists, has to be understood and properly addressed. The origin of biases is not always clear. We analyzed 40 yr of records from the Lacaune dairy sheep breeding program to evaluate the extent of bias, assess possible corrections, and emit hypotheses on its origin. The data set included 7 traits (milk yield, fat and protein contents, somatic cell score, teat angle, udder cleft, and udder depth) with records from 600,000 to 5 million depending on the trait, ～1,900,000 animals, and ～5,900 genotyped elite artificial insemination rams. For the ～8% animals with missing sire, we fit 25 unknown parent groups. We used the linear regression method to compare “partial” and “whole” predictions of young rams before and after progeny testing, with 7 cut-off points, and we obtained estimates of their bias, (over)dispersion, and accuracy in early proofs. We tried (1) several scenarios as follows: multiple or single trait, the “official” (routine) evaluation, which is a mixture of both single and multiple trait, and “deletion” of data before 1990; and (2) several models as follows: BLUP and single-step genomic (SSG)BLUP with fixed unknown parent groups or metafounders, where, for metafounders, their relationship matrix gamma was estimated using either a model for inbreeding trend, or base allele frequencies estimated by peeling. The estimate of gamma obtained by modeling the inbreeding trend resulted in an estimated increase of inbreeding, based on markers, faster than the pedigree-based one. The estimated genetic trends were similar for most models and scenarios across all traits, but were shrunken when gamma was estimated by peeling. This was due to shrinking of the estimates of metafounders in the latter case. Across scenarios, all traits showed bias, generally as an overestimate of genetic trend for milk yield and an underestimate for the other traits. As for the slope, it showed overdispersion of estimated breeding values for all traits. Using multiple-trait models slightly reduced the overestimate of genetic trend and the overdispersion, as did including genomic information (i.e., SSGBLUP) when the gamma matrix was estimated by the model for inbreeding trend. However, only deletion of historical data before 1990 resulted in elimination of both kind of biases. The SSGBLUP resulted in more accurate early proofs than BLUP for all traits. We considered that a snowball effect of small errors in each genetic evaluation, combined with selection, may have resulted in biased evaluations. Improving statistical methods reduced some bias but not all, and a simple solution for this data set was to remove historical records.     

Breeding schemes with optimum-contribution selection or truncation selection for beef cattle destined for use on dairy females

We tested the hypothesis that the size of a beef cattle population destined for use on dairy females is smaller under optimum-contribution selection (OCS) than under truncation selection (TRS) at the same genetic gain (ΔG) and the same rate of inbreeding (ΔF). We used stochastic simulation to estimate true ΔG realized at a 0.005 ΔF in breeding schemes with OCS or TRS. The schemes for the beef cattle population also differed in the number of purebred offspring per dam and the total number of purebred offspring per generation. Dams of the next generation were exclusively selected among the one-year-old heifers. All dams were donors for embryo transfer and produced a maximum of 5 or 10 offspring. The total number of purebred offspring per generation was: 400, 800, 1,600 or 4,000 calves, and it was used as a measure of population size. Rate of inbreeding was predicted and controlled using pedigree relationships. Each OCS (TRS) scheme was simulated for 10 discrete generations and replicated 100 (200) times. The OCS scheme and the TRS scheme with a maximum of 10 offspring per dam required approximately 783 and 1,257 purebred offspring per generation to realize a true ΔG of €14 and a ΔF of 0.005 per generation. Schemes with a maximum of 5 offspring per dam required more purebred offspring per generation to realize a similar true ΔG and a similar ΔF. Our results show that OCS and multiple ovulation and embryo transfer act on selection intensity through different mechanisms to achieve fewer selection candidates and fewer selected sires and dams than under TRS at the same ΔG and a fixed ΔF. Therefore, we advocate the use of a breeding scheme with OCS and multiple ovulation and embryo transfer for beef cattle destined for use on dairy females because it is favorable both from an economic perspective and a carbon footprint perspective.     

Structure–Function Relationship of Retinal Ganglion Cells in Multiple Sclerosis

The retinal ganglion cells (RGC) may be considered an easily accessible pathophysiological site of degenerative processes in neurological diseases, such as the RGC damage detectable in multiple sclerosis (MS) patients with (HON) and without a history of optic neuritis (NON). We aimed to assess and interrelate RGC functional and structural damage in different retinal layers and retinal sites. We included 12 NON patients, 11 HON patients and 14 healthy controls for cross-sectional multifocal pattern electroretinography (mfPERG) and optical coherence tomography (OCT) measurements. Amplitude and peak times of the mfPERG were assessed. Macula and disc OCT scans were acquired to determine macular retinal layer and peripapillary retinal nerve fiber layer (pRNFL) thickness. In both HON and NON patients the foveal N2 amplitude of the mfPERG was reduced compared to controls. The parafoveal P1 peak time was significantly reduced in HON only. For OCT, parafoveal (pfGCL) and perifoveal (pGCL) ganglion cell layer thicknesses were decreased in HON vs. controls, while pRNFL in the papillomacular bundle sector (PMB) showed reductions in both NON and HON. As the mfPERG derived N2 originates from RGC axons, these findings suggest foveal axonal dysfunction not only in HON, but also in NON patients.     

Prediction of mode I fracture toughness of rock using linear multiple regression and gene expression programming

Prediction of mode I fracture toughness (K_IC) of rock is of significant importance in rock engineering analyses. In this study, linear multiple regression (LMR) and gene expression programming (GEP) methods were used to provide a reliable relationship to determine mode I fracture toughness of rock. The presented model was developed based on 60 datasets taken from the previous literature. To predict fracture parameters, three mechanical parameters of rock mass including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and elastic modulus (E) have been selected as the input parameters. A cluster of data was collected and divided into two random groups of training and testing datasets. Then, different statistical linear and artificial intelligence based nonlinear analyses were conducted on the training data to provide a reliable prediction model of K_IC. These two predictive methods were then evaluated based on the testing data. To evaluate the efficiency of the proposed models for predicting the mode I fracture toughness of rock, various statistical indices including coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE) were utilized herein. In the case of testing datasets, the values of R², RMSE, and MAE for the GEP model were 0.87, 0.188, and 0.156, respectively, while they were 0.74, 0.473, and 0.223, respectively, for the LMR model. The results indicated that the selected GEP model delivered superior performance with a higher R² value and lower errors.     

催化共振光散射法测定空气中痕量甲醛的研究

吖啶橙分子聚集体微粒可在513nm波长处出现最大的共振光散射强度(RLS)。在稀硫酸介质中,甲醛能催化溴酸钾氧化吖啶橙的反应,促使其RLS强度减弱。在最佳实验条件下,甲醛质量浓度ρ在0.020～0.25μg/mL的范围内与△I值呈良好的线性关系,线性回归方程为△I=1113.99ρ+49.23,线性相关系数r为0.9986。本法与国标法进行对照,在置信度等于95%时,用Cochran检验,两种方法间不存在显著性差异,方法操作简单、灵敏度高,用于室内外空气中甲醛测定,结果满意。     

危废填埋场地下水环境影响评价研究

危险废物具有各种危害性,不仅对人体健康有着威胁,对于环境治理来说也有着极大的消极影响。就目前来说,虽然安全填埋技术已经较为成熟,但在实际实施过程中还是容易出现渗漏事故,渗漏液在地下容易穿透防渗层,从而影响地下水,所以这也是我们需要重视的问题之一。     

Bioinspired Triboelectric Soft Robot Driven by Mechanical Energy

A sustainable power source is a key technical challenge for practical applications of electrically responsive soft robots, especially the required voltage is over several thousand volts. Here, a practicable new technology, triboelectric soft robot (TESR) system with the primary characteristics of power source from mechanical energy, is developed. At its heart is TESR with bioinspired architectures made of soft-deformable body and two triboelectric adhesion feet, which is driven and accurately controlled through triboelectric effect, while reaching maximum crawling speeds of 14.9 mm s⁻¹ on the acrylic surface. The characteristics of the TESR, including displacement and force, are tested and simulated under the power of a rotary freestanding triboelectric nanogenerator (RF-TENG). Crawling of TESR is successfully realized on different materials surfaces and different angle slopes under the driven of RF-TENG. Furthermore, a real-time visual monitoring platform, in which TESR carries a micro camera to transmit images in a long narrow tunnel, is also achieved successfully, indicating that it can be used for fast diagnosis in an area inaccessible to human beings in the future. This study offers a new insight into the sustainable power source technologies suitable for electrically responsive soft robots and contributes to expanding the applicability of TENGs.