Numerical simulation and experimental study of PbWO4/EPDM and Bi2WO6/EPDM for the shielding of {\gamma}rays

The MCNP5 code was employed to simulate the {\gamma}ray shielding capacity of tungstate composites. The experimental results were applied to verify the applicability of the Monte Carlo program. PbWO4 and Bi2WO6 were prepared and added into ethylene propylene diene monomer (EPDM) to obtain the composites, which were tested in the {\gamma}ray shielding. Both the theoretical simulation and experiments were carefully chosen and well designed. The results of the two methods were found to be highly consistent. In addition, the conditions during the numerical simulation were optimized and double-layer {\gamma}ray shielding systems were studied. It was found that the {\gamma}-ray shielding performance can be influenced not only by the material thickness ratio but also by the arrangement of the composites.Comment: 8 pages,7 figures,Submitted to Chin.Phy.

Association of lipid profiles and the ratios with arterial stiffness in middle-aged and elderly Chinese

BACKGROUND: Serum lipids and the ratios are known to be associated with the cardiovascular diseases (CVD). However, the associations of serum lipids and the ratios related to arterial stiffness are unclear. We sought to compare the strength of these serum lipids and the ratios with arterial stiffness assessing by brachial-ankle pulse wave velocity (baPWV) in the middle-aged and elderly Chinese subjects. METHODS: A total number of 1133 Chinese aged from 50 to 90 years old were recruited from Shanghai downtown district. The serum lipids, baPWV and major cardiovascular risk factors of the participants were measured. RESULTS: Participants with high baPWV exhibited higher levels of non-HDL-c, TC/HDL-c, TG/HDL-c, LDL-c/HDL-c, and non-HDL-c/HDL-c, while HDL-c worked in the opposite direction (all P<0.05). In addition, TC, TG, LDL-c, non-HDL-c, TC/HDL-c, TG/HDL-c, LDL-c/HDL-c, and non-HDL-c/HDL-c had a positive relationship with the baPWV value, while HDL-c was on the contrary (all P <0.05). Finally, individuals with high non-HDL-c/HDL-c (OR 1.71, 95% CI 1.06-2.55, P = 0.013) and low HDL-c (OR 0.57, 95% CI 0.35-0.96, P = 0.024) were seem to be at high risk of arterial stiffness. CONCLUSIONS: As a risk indicator, non-HDL-c/HDL-c, which could be readily obtained from routine serum lipids, was significantly associated with baPWV. Non-HDL-c/HDL-c was superior to traditional lipid variables for estimating arterial stiffness in the middle-aged and elderly Chinese population

Determination of the stretch tensor for structural transformations

The transformation stretch tensor plays an essential role in the evaluation of conditions of compatibility between phases and the use of the Cauchy-Born rule. This tensor is difficult to measure directly from experiment. We give an algorithm for the determination of the transformation stretch tensor from x-ray measurements of structure and lattice parameters. When evaluated on some traditional and emerging phase transformations the algorithm gives unexpected results.Comment: 3 figures, 1 tabl

Coordinated Target Tracking by Distributed Unscented Information Filter in Sensor Networks with Measurement Constraints

Tracking a target in a cluttered environment is a representative application of sensor networks. In this paper, we develop a distributed approach to estimate the motion states of a target using noisy measurements. Our method consists of two parts. In first phase, using the unscented sigma-point transformation techniques and information filter framework, a class of algorithms denoted as unscented information filters was developed to estimate the states of a target to be tracked. These techniques exhibit robustness and accuracy of sigma-point filters for nonlinear dynamic inference while being as easily fused as the information filters. In the second phase, we proposed a novel consensus protocol which allows each sensor node to find a consistent estimate of the value of the target. Under this protocol, the final estimate of the value of the target at each time step is iteratively updated only by fusing the neighbors’ measurements when one sensor node is out of the measurement scope of the target. Performance of the distributed unscented information filter is demonstrated and discussed on a target tracking task

A Multimodal In Vitro Diagnostic Method for Parkinson's Disease Combining Facial Expressions and Behavioral Gait Data

Parkinson's disease (PD), characterized by its incurable nature, rapid progression, and severe disability, poses significant challenges to the lives of patients and their families. Given the aging population, the need for early detection of PD is increasing. In vitro diagnosis has garnered attention due to its non-invasive nature and low cost. However, existing methods present several challenges: 1) limited training data for facial expression diagnosis; 2) specialized equipment and acquisition environments required for gait diagnosis, resulting in poor generalizability; 3) the risk of misdiagnosis or missed diagnosis when relying on a single modality. To address these issues, we propose a novel multimodal in vitro diagnostic method for PD, leveraging facial expressions and behavioral gait. Our method employs a lightweight deep learning model for feature extraction and fusion, aimed at improving diagnostic accuracy and facilitating deployment on mobile devices. Furthermore, we have established the largest multimodal PD dataset in collaboration with a hospital and conducted extensive experiments to validate the effectiveness of our proposed method

Optimizing the test locations and replicates in multi‐environmental cotton registration trials in southern Xinjiang, China

Multi-environment trials are routinely conducted around the world to select superior cultivars; the numbers of replicates and locations remains insufficiently studied despite their effects on trial efficiency and cost. The objective of the present study was to compensate for the mentioned lack by dealing with the specific case of cotton in arid conditions of China and by estimating the optimal numbers of locations and/or replicates in a more comprehensive way than implemented so far, i.e. optimizing with regard jointly to three criteria, namely, genotype ranking, location evaluation and environment investigation. Trial heritability and the optimal numbers of locations and replicates were estimated through adapted genotype plus genotype by environment (GGE) biplot analysis from data of cotton variety registration trials in the fringes of the Taklimakan Desert in Southern Xinjiang in China over the 2011–2020 period when three replicate trials were generally conducted in nine locations. Despite the identification of two mega-environments (MEs) through LG (location grouping) biplot analysis, our study showed robust results of genotype ranking, correlation among test locations, and location grouping that were not affected by reducing the number of replicates. It was concluded that two replicates (instead of three) were sufficient for reliable genotype evaluation, test location evaluation and ME classification in the studied trial scheme. The implied savings justifies similar study on other schemes

Anthropogenic impacts on multiple facets of macroinvertebrate α and β diversity in a large river-floodplain ecosystem

AbstractAnthropogenic disturbances have become one of the primary causes of biodiversity decline in freshwater ecosystems. Beyond the well-documented loss of taxon richness in increasingly impacted ecosystems, our knowledge on how different facets of α and β diversity respond to human disturbances is still limited. Here, we examined the responses of taxonomic (TD), functional (FD) and phylogenetic (PD) α and β diversity of macroinvertebrate communities to human impact across 33 floodplain lakes surrounding the Yangtze River. We found that most pairwise correlations between TD and FD/PD were low and non-significant, whereas FD and PD metrics were instead positively and significantly correlated. All facets of α diversity decreased from weakly to strongly impacted lakes owing to the removal of sensitive species harboring unique evolutionary legacies and phenotypes. By contrast, the three facets of β diversity responded inconsistently to anthropogenic disturbance: while FDβ and PDβ showed significant impairment in moderately and strongly impacted lakes as a result of spatial homogenization, TDβ was lowest in weakly impacted lakes. The multiple facets of diversity also responded differently to the underlying environmental gradients, re-emphasizing that taxonomic, functional and phylogenetic diversities provide complementary information on community dynamics. However, the explanatory power of our machine learning and constrained ordination models was relatively low and suggests that unmeasured environmental features and stochastic processes may strongly contribute to macroinvertebrate communities in floodplain lakes suffering from variable levels of anthropogenic degradation. We finally suggested guidelines for effective conservation and restoration targets aimed at achieving healthier aquatic biotas in a context of increasing human impact across the ‘lakescape’ surrounding the Yangtze River, the most important being the control of nutrient inputs and increased spatial spillover effects to promote natural metasystem dynamics.Abstract Anthropogenic disturbances have become one of the primary causes of biodiversity decline in freshwater ecosystems. Beyond the well-documented loss of taxon richness in increasingly impacted ecosystems, our knowledge on how different facets of α and β diversity respond to human disturbances is still limited. Here, we examined the responses of taxonomic (TD), functional (FD) and phylogenetic (PD) α and β diversity of macroinvertebrate communities to human impact across 33 floodplain lakes surrounding the Yangtze River. We found that most pairwise correlations between TD and FD/PD were low and non-significant, whereas FD and PD metrics were instead positively and significantly correlated. All facets of α diversity decreased from weakly to strongly impacted lakes owing to the removal of sensitive species harboring unique evolutionary legacies and phenotypes. By contrast, the three facets of β diversity responded inconsistently to anthropogenic disturbance: while FDβ and PDβ showed significant impairment in moderately and strongly impacted lakes as a result of spatial homogenization, TDβ was lowest in weakly impacted lakes. The multiple facets of diversity also responded differently to the underlying environmental gradients, re-emphasizing that taxonomic, functional and phylogenetic diversities provide complementary information on community dynamics. However, the explanatory power of our machine learning and constrained ordination models was relatively low and suggests that unmeasured environmental features and stochastic processes may strongly contribute to macroinvertebrate communities in floodplain lakes suffering from variable levels of anthropogenic degradation. We finally suggested guidelines for effective conservation and restoration targets aimed at achieving healthier aquatic biotas in a context of increasing human impact across the ‘lakescape’ surrounding the Yangtze River, the most important being the control of nutrient inputs and increased spatial spillover effects to promote natural metasystem dynamics

CIM-MLC: A Multi-level Compilation Stack for Computing-In-Memory Accelerators

In recent years, various computing-in-memory (CIM) processors have been presented, showing superior performance over traditional architectures. To unleash the potential of various CIM architectures, such as device precision, crossbar size, and crossbar number, it is necessary to develop compilation tools that are fully aware of the CIM architectural details and implementation diversity. However, due to the lack of architectural support in current popular open-source compiling stacks, existing CIM designs either manually deploy networks or build their own compilers, which is time-consuming and labor-intensive. Although some works expose the specific CIM device programming interfaces to compilers, they are often bound to a fixed CIM architecture, lacking the flexibility to support the CIM architectures with different computing granularity. On the other hand, existing compilation works usually consider the scheduling of limited operation types (such as crossbar-bound matrix-vector multiplication). Unlike conventional processors, CIM accelerators are featured by their diverse architecture, circuit, and device, which cannot be simply abstracted by a single level if we seek to fully explore the advantages brought by CIM. Therefore, we propose CIM-MLC, a universal multi-level compilation framework for general CIM architectures. We first establish a general hardware abstraction for CIM architectures and computing modes to represent various CIM accelerators. Based on the proposed abstraction, CIM-MLC can compile tasks onto a wide range of CIM accelerators having different devices, architectures, and programming interfaces. More importantly, compared with existing compilation work, CIM-MLC can explore the mapping and scheduling strategies across multiple architectural tiers, which form a tractable yet effective design space, to achieve better scheduling and instruction generation results.Comment: 16 pages, 22 figure

Seismic analysis of fault damage zones in the northern Tarim Basin (NW China):Implications for growth of ultra-deep fractured reservoirs

Understanding fault damage zone is of significant importance for the characterization and modeling of ultra-deep (greater than 6000 m) fractured reservoirs. However, seismic detection of fracture networks in deep fault zone it is still challenging. For this contribution, we propose a seismic Tensor Thickness Method for optimal imaging of the ultra- strike-slip fault damage zones in the Tarim Basin. The results show reasonable distinction through seismic methods of boundary of fault damage zones in carbonate host rock that is consistent with the fractured reservoirs constrained from borehole data. In addition, this study suggests that fault damage zones in ultra deep settings exhibit width ranging 100–800 m, with a linear correlation between fault damage zone width and throw. Isolated fault zones are characterized with linear relationship between the width and displacement of the strike-slip fault zones, but the abnormally wide fault damage zone is likely attributed to fault interaction and overlapping. The results of this work are applicable for fractured reservoir characterization in deep and tight carbonate rocks elsewhere

Cross-sectional analysis of serum calcium levels for associations with left ventricular hypertrophy in normocalcemia individuals with type 2 diabetes

BACKGROUND: Left ventricular hypertrophy (LVH) is prevalent in patients with type 2 diabetes mellitus (T2DM). Recent studies show that an increase in albumin-adjusted serum calcium level is associated with an elevated risk of T2DM. We speculate that increased serum calcium levels in T2DM patients are related to LVH prevalence. METHODS: In this echocardiographic study, 833 normocalcemia and normophosphatemia patients with T2DM were enrolled. The associations between serum calcium and metabolic parameters, left ventricular mass index (LVMI), as well as the rate of LVH were examined using bivariate linear correlation, multivariate linear regression and logistic regression, respectively. The predictive performance of serum calcium for LVH was evaluated using the area under the receiver operating characteristic curve (AUC). RESULTS: Patients with LVH have significantly higher serum calcium than those without LVH. Serum calcium was positively associated with total cholesterol, triglycerides, low-density lipoprotein cholesterol, serum uric acid, HOMA-IR and fasting plasma glucose. Multivariate linear regression analysis demonstrated that serum calcium was independently associated with LVMI (p < 0.001). In comparison with patients in the lowest serum calcium quartile, the odds ratio (OR) for LVH in patients in the highest quartile was 2.909 (95% CI 1.792-4.720; p < 0.001). When serum calcium was analyzed as a continuous variable, per 1 mg/dl increase, the OR (95% CI) for LVH was [2.400 (1.552-3.713); p < 0.001]. Serum calcium can predict LVH (AUC = 0.617; 95% CI (0.577-0.656); p < 0.001). CONCLUSIONS: Albumin-adjusted serum calcium is associated with an increased risk of LVH in patients with T2DM