A 14-mW PLL-less receiver in 0.18-μm CMOS for Chinese electronic toll collection standard

This is the accepted manuscript version of the following article: Xiaofeng He, et al., “A 14-mW PLL-less receiver in 0.18-μm CMOS for Chinese electronic toll collection standard”, IEEE Transactions on Circuits and Systems II: Express Briefs, Vol. 61(10): 763-767, August 2014. The final published version is available at: http://ieeexplore.ieee.org/document/6871304/ © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The design of a 14-mW receiver without phase-locked loop for the Chinese electronic toll collection (ETC) system in a standard 0.18-μm CMOS process is presented in this brief. Since the previously published work was mainly based on vehicle-powered systems, low power consumption was not the primary goal of such a system. In contrast, the presented system is designed for a battery-powered system. Utilizing the presented receiver architecture, the entire receiver only consumes 7.8 mA, at the supply voltage of 1.8 V, which indicates a power saving of at least 38% compared with other state-of-the-art designs for the same application. To verify the performance, the bit error rate is measured to be better than 10-6, which well satisfies the Chinese ETC standard. Moreover, the sensitivity of the designed receiver can be readjusted to -50 dBm, which is required by the standard.Peer reviewe

Regional correction calibration for OCF precipitation in flood season in Zhejiang Province based on cluster analysis

The forecast of rainstorm in flood season has always been the key and difficult point in the meteorological forecasting operation. First, we used the daily precipitation data from 2 227 meteorological stations in Zhejiang Province from 2016 to 2021 during the flood season (April to October), and divided the precipitation region by applying the K-means clustering algorithm, which employed the Euclidean distance as the similarity measure. Then, the regional correction method is formed by combing the spatial-temporally improved bias correction method and divided regions. Finally, we applied this method to perform the regional correction and validation on the Zhejiang Multi-Model Objective Consensus Forecast (OCF), compared with the overall correction not combined with divided regions.The results are as follows. (1) The K-means clustering algorithm can divide Zhejiang Province into 7 precipitation-similar regions, which show distinct regional characteristics closely related to the topographic features of Zhejiang Province. (2) According to validation during the 2021 flood season, the regional correction performed better than the overall correction in the OCF forecasts.Its main advantages lie in effectively reducing the false alarm of precipitation in the clear-rain forecast and substantially increasing the hit rate (POD) for the heavy rain and above, especially for the rainstorm and above from 0.25 to 0.41. (3) The typical validation show that, for both systematic and convective precipitation, the regional correction can significantly improve the intensity and falling area of precipitation for the rainstorm and above. Especially for the systematic precipitation, the regional correction demonstrated more remarkable effects, which can predict heavy rainstorms

Relationships between Landscape Patterns and Hydrological Processes in the Subtropical Monsoon Climate Zone of Southeastern China

With rapid economic development, extensive human activity has changed landscape patterns (LPs) dramatically, which has further influenced hydrological processes. However, the effects of LPs changes on hydrological processes, especially for the streamflow–sediment relationship in the subtropical monsoon climate zone, have not been reported. In our study, 10 watersheds with different sizes in the subtropical monsoon climate zone of southeastern China were chosen as the study area, and the effect of the 14 most commonly used landscape metrics (LMs) on 4 typical hydrological indices (water yields (WY), the runoff coefficient (RC), the soil erosion modulus (SEM), and the suspended sediment concentration (SSC)) were analyzed based on land use maps and hydrological data from 1990 to 2019. The results reveal that the LP characteristics within the study area have changed significantly. The number of patches and landscape shape indices were significantly positively correlated with watershed size (p &lt; 0.01). For most watersheds, the largest patch index was negatively correlated with WY, RC, and SEM, and the perimeter area fractal dimension was positively correlated with WY, RC, SEM, and SSC. The effects of several LMs on the hydrological indices had scale effects. WY/RC and the interspersion and juxtaposition index were negatively correlated in most larger watersheds but were positively correlated in most smaller watersheds. Similar results were found for Shannon’s diversity/evenness index and SEM. In general, an increase in a small patch of landscape and in landscape diversity would increase WY, the fragmentation of LPs would result in more soil erosion, and LPs would affect the relationship between streamflow and sediment yield. As a result, a proper decrease in landscape fragmentation and physical connectivity in the subtropical monsoon climate zone of southeastern China would benefit soil erosion prevention. These results enhance the knowledge about the relationship between LPs and hydrological processes in the subtropical monsoon climate zone of southeastern China and benefit local water and soil conservation efforts.</p

Hyperspectral band selection using crossover based gravitational search algorithm

Band selection is an important data dimensionality reduction tool in hyperspectral images (HSIs). To identify the most informative subset band from the hundreds of highly corrected bands in HSIs, a novel hyperspectral band selection method using a crossover based gravitational search algorithm (CGSA) is presented in this paper. In this method, the discriminative capability of each band subset is evaluated by a combined optimization criterion, which is constructed based on the overall classification accuracy and the size of the band subset. As the evolution of the criterion, the subset is updated using the V-shaped transfer function based CGSA. Ultimately, the band subset with the best fitness value is selected. Experiments on two public hyperspectral datasets, i.e. the Indian Pines dataset and the Pavia University dataset, have been conducted to test the performance of the proposed method. Comparing experimental results against the basic GSA and the PSOGSA (hybrid PSO and GSA) revealed that all of the three GSA variants can considerably reduce the band dimensionality of HSIs without damaging their classification accuracy. Moreover, the CGSA shows superiority on both the effectiveness and efficiency compared to the other two GSA variants

Lithofacies Characteristics and Sweet Spot Distribution of Lacustrine Shale Oil: A Case Study from the Dongying Depression, Bohai Bay Basin, China

AbstractLacustrine shale is characterized by rapid lithofacies transformation and compositional heterogeneity, which present challenges in shale oil sweet spot evaluation and distribution prediction and should be systematically studied. Field emission-scanning electron microscopy (FE-SEM), low-pressure adsorption isotherm analysis, mercury intrusion porosimetry (MIP), and triaxial compression testing were employed to comprehensively analyze the oil-bearing capacity, reservoir properties, fluidity, and frackability of different lithofacies. Via analyses of mineral composition, total organic carbon (TOC) content, and sedimentary structure, seven lithofacies were identified: organic-rich calcareous shale (L1), organic-rich laminated calcareous mudstone (L2), organic-rich laminated carbonate-bearing mudstone (L3), intermediate-organic laminated calcareous mudstone (L4), organic-poor laminated calcareous mudstone (L5), organic-poor thin-bedded calcareous mudstone (L6), and organic-rich laminated silty mudstone (L7). Considered together, the oil-bearing capacity, reservoir properties, fluidity, and frackability suggested that the L1 and L7 lithofacies were high-quality sweet spots, with satisfactory oil-bearing capacity (TOC&gt;3.5%; S1&gt;10 mgHC/grock), well-developed pores and microfractures, notable fluidity (as indicated by a high oil saturation index value), and suitable brittleness. The sweet spot distribution was predicted according to multiresolution graph-based clustering analysis of well logs. The results indicate that comprehensive research of the key factors for shale oil and lithofacies prediction can promote sweet spot prediction and enhance shale oil exploration

Characterization of LC-MS based urine metabolomics in healthy children and adults

Previous studies reported that sex and age could influence urine metabolomics, which should be considered in biomarker discovery. As a consequence, for the baseline of urine metabolomics characteristics, it becomes critical to avoid confounding effects in clinical cohort studies. In this study, we provided a comprehensive lifespan characterization of urine metabolomics in a cohort of 348 healthy children and 315 adults, aged 1 to 78 years, using liquid chromatography coupled with high resolution mass spectrometry. Our results suggest that sex-dependent urine metabolites are much greater in adults than in children. The pantothenate and CoA biosynthesis and alanine metabolism pathways were enriched in early life. Androgen and estrogen metabolism showed high activity during adolescence and youth stages. Pyrimidine metabolism was enriched in the geriatric stage. Based on the above analysis, metabolomic characteristics of each age stage were provided. This work could help us understand the baseline of urine metabolism characteristics and contribute to further studies of clinical disease biomarker discovery

Emotional intelligence, self-efficacy, english language proficiency and cross cultural adjustment among China self-initiated expatriates in Malaysia

Cross-cultural adjustment (CCA) is a vital part of expatriate accomplishments, it is a kind of adjustment that can be improved by exposing the expatriates to the facts and understanding of norms that is suitable for behaviors that are exhibited in a foreign country by means of cross-cultural adjustment. This research aims to ease interactions between China Self-Initiated Expatriates (SIEs) and national hosts via Emotional Intelligence, Self-efficacy and English language proficiency, thus offering expatriates a vision into the host country’s culture to enhance their understanding of the new environment. Social Cognitive theory suggest that individuals form and display certain behavioral patterns which are categorized into three; personal factors, behavioral factor, and environmental. This current research uses the sample size of 87 SIEs respondents from China mainland which are selected via systematic random sampling. The questionnaire used in this research was a combination of constructed questions and adapted questions from previous studies. The three variables which are Emotional Intelligence, Self-efficacy and English language proficiency, and CCA was analyzed with Pearson correlation and multiple regressions with Statistical Package for Social Science (SPSS). The result was presented in a descriptive and inferential manner. It exhibited that China SIEs in Malaysia were able to adjust well in Malaysia due to good Emotional Intelligence, Self-Efficacy and proficiency in English language. The findings also suggests that Self-Efficacy and Emotional Intelligence contributed significantly to CCA by the China SIEs while English language proficiency was found not to contribute drastically to enhance China expatriates’ adjustment in Malaysia. It is recommended for future research to incorporate bigger sample size to further increase the accuracy of the research

CToMP: A Cycle-task-oriented Memory Protection Scheme for Unmanned Systems

Memory corruption attacks (MCAs) refer to malicious behaviors of system intruders that modify the contents of a memory location to disrupt the normal operation of computing systems, causing leakage of sensitive data or perturbations to ongoing processes. Unlike general-purpose systems, unmanned systems cannot deploy complete security protection schemes, due to their limitations in size, cost and performance. MCAs in unmanned systems are particularly difficult to defend against. Furthermore, MCAs have diverse and unpredictable attack interfaces in unmanned systems, severely impacting digital and physical sectors. In this paper, we first generalize, model and taxonomize MCAs found in unmanned systems currently, laying the foundation for designing a portable and general defense approach. According to different attack mechanisms, we found that MCAs are mainly categorized into two types--return2libc and return2shellcode. To tackle return2libc attacks, we model the erratic operation of unmanned systems with cycles and then propose a cycle-task-oriented memory protection (CToMP) approach to protect control flows from tampering. To defend against return2shellcode attacks, we introduce a secure process stack with a randomized memory address by leveraging the memory pool to prevent Shellcode from being executed. Moreover, we discuss the mechanism by which CToMP resists the ROP attack, a novel variant of return2libc attacks. Finally, we implement CToMP on CUAV V5+ with Ardupilot and Crazyflie. The evaluation and security analysis results demonstrate that the proposed approach CToMP is resilient to various MCAs in unmanned systems with low footprints and system overhead.Comment: This paper has been accepted by SCIENCE CHINA Information Science

Extraction and separation of zinc, lead, silver, and bismuth from bismuth slag

The present paper deals with the extraction and separation of zinc, lead, silver, and bismuth from a refractory bismuth refining slag via a hydrometallurgical route. The process consists of a preliminary leaching of zinc with water, followed by the selective leaching of lead and silver with a calcium chloride solution, leading to the crystallization of lead chloride and the cementation of silver. The diagrams of the total concentrations of [Pb]/[Ag] versus [Cl-] and temperature in the Pb/Ag-Cl-H2O system were drawn, respectively, to determine the optimum concentration of leaching agent and leaching temperature. The potential-pH diagram of the Pb/Ag/Bi-H2O system indicates that the preferential leaching of lead and silver could be achieved. Finally, 98.8% of lead and 90.4% of silver were selectively removed by further leaching the water leaching residue with 400 g/dm3 of CaCl2 solution at pH 4.5 and 80 °C, while only 3.7% of bismuth was leached in this stage. Fifty-nine percent of lead in the leach liquor was separated out as PbCl2 by natural cooling. Ninety-five percent of silver in mother liquor was recovered by cementation with a lead sheet. The depleted CaCl2 solution can be sent to the leaching step again to close the loop