Novel passive localization algorithm based on double side matrix-restricted total least squares

AbstractIn order to solve the bearings-only passive localization problem in the presence of erroneous observer position, a novel algorithm based on double side matrix-restricted total least squares (DSMRTLS) is proposed. First, the aforementioned passive localization problem is transferred to the DSMRTLS problem by deriving a multiplicative structure for both the observation matrix and the observation vector. Second, the corresponding optimization problem of the DSMRTLS problem without constraint is derived, which can be approximated as the generalized Rayleigh quotient minimization problem. Then, the localization solution which is globally optimal and asymptotically unbiased can be got by generalized eigenvalue decomposition. Simulation results verify the rationality of the approximation and the good performance of the proposed algorithm compared with several typical algorithms

Catalytic difunctionalization of unactivated alkenes with unreactive hexamethyldisilane through regeneration of silylium ions

A metal‐free, intermolecular syn‐addition of hexamethyldisilane across simple alkenes is reported. The catalytic cycle is initiated and propagated by the transfer of a methyl group from the disilane to a silylium‐ion‐like intermediate, corresponding to the (re)generation of the silylium‐ion catalyst. The key feature of the reaction sequence is the cleavage of the Si−Si bond in a 1,3‐silyl shift from silicon to carbon. A central intermediate of the catalysis was structurally characterized by X‐ray diffraction, and the computed reaction mechanism is fully consistent with the experimental findings.TU Berlin, Open-Access-Mittel - 201

Water pollutant fingerprinting tracks recent industrial transfer from coastal to inland China: a case study

In recent years, China’s developed regions have transferred industries to undeveloped regions. Large numbers of unlicensed or unregistered enterprises are widespread in these undeveloped regions and they are subject to minimal regulation. Current methods for tracing industrial transfers in these areas, based on enterprise registration information or economic surveys, do not work. The authors have developed an analytical framework combining water fingerprinting and evolutionary analysis to trace the pollution transfer features between water sources. We collected samples in Eastern China (industrial export) and Central China (industrial acceptance) separately from two water systems. Based on the water pollutant fingerprints and evolutionary trees, we traced the pollution transfer associated with industrial transfer between the two areas. The results are consistent with four episodes of industrial transfers over the past decade. The results also show likely types of the transferred industries - electronics, plastics, and biomedicines - that contribute to the water pollution transfer

The occurrence and potential health risk of microcystins in drinking water of rural areas in China.

Large-scale use of nitrogen and phosphorus fertilizers in agricultural production, environmental pollution and climate warming cause frequent algal blooms and the generation of algal toxins in water bodies in China. Algal pollution is increasing and microcystins (MCs) are detectable in both surface and ground water in China at sub- μg/L and μg/L levels. Toxicological studies show that microcystins have hepatic and  renal toxicity, genotoxicity, tumor-promoting effects, neurotoxicity, reproductive and developmental toxicity. Epidemiological evidence from China further reveals that chronic exposure to MCs through drinking water and liver cancer are positively correlated and demonstrate that MCs in drinking water are a main risk factor in liver cancer. Effectively controlled water pollution, reduced sewage discharge, and enhanced wastewater treatments are pivotal measures to control algal pollution and toxins in the drinking water of rural China

Imaging of brain function based on the analysis of functional connectivity - imaging analysis of brain function by fMRI after acupuncture at LR3 in healthy individuals

Objective: This Study observed the relevant brain areas activated by acupuncture at the Taichong acupoint (LR3) and analyzed the functional connectivity among brain areas using resting state functional magnetic resonance imaging (fMRI) to explore the acupoint specificity of the Taichong acupoint.Methods: A total of 45 healthy subjects were randomly divided into the Taichong (LR3) group, sham acupuncture group and sham acupoint group. Subjects received resting state fMRI before acupuncture, after true (sham) acupuncture in each group. Analysis of changes in connectivity among the brain areas was performed using the brain functional connectivity method.Results: The right cerebrum temporal lobe was selected as the seed point to analyze the functional connectivity. It had a functional connectivity with right cerebrum superior frontal gyrus, limbic lobe cingulate gyrus and left cerebrum inferior temporal gyrus (BA 37), inferior parietal lobule compared by before vs. after acupuncture at LR3, and right cerebrum sub-lobar insula and left cerebrum middle frontal gyrus, medial frontal gyrus compared by true vs. sham acupuncture at LR3, and right cerebrum occipital lobe cuneus, occipital lobe sub-gyral, parietal lobe precuneus and left cerebellum anterior lobe culmen by acupuncture at LR3 vs. sham acupoint.Conclusion: Acupuncture at LR3 mainly specifically activated the brain functional network that participates in visual function, associative function, and emotion cognition, which are similar to the features on LR3 in tradition Chinese medicine. These brain areas constituted a neural network structure with specific functions that had specific reference values for the interpretation of the acupoint specificity of the Taichong acupoint.Keywords: acupuncture, Taichong(LR3), functional magnetic resonance imaging (fMRI), functional connectivit

Error-aware Quantization through Noise Tempering

Quantization has become a predominant approach for model compression, enabling deployment of large models trained on GPUs onto smaller form-factor devices for inference. Quantization-aware training (QAT) optimizes model parameters with respect to the end task while simulating quantization error, leading to better performance than post-training quantization. Approximation of gradients through the non-differentiable quantization operator is typically achieved using the straight-through estimator (STE) or additive noise. However, STE-based methods suffer from instability due to biased gradients, whereas existing noise-based methods cannot reduce the resulting variance. In this work, we incorporate exponentially decaying quantization-error-aware noise together with a learnable scale of task loss gradient to approximate the effect of a quantization operator. We show this method combines gradient scale and quantization noise in a better optimized way, providing finer-grained estimation of gradients at each weight and activation layer's quantizer bin size. Our controlled noise also contains an implicit curvature term that could encourage flatter minima, which we show is indeed the case in our experiments. Experiments training ResNet architectures on the CIFAR-10, CIFAR-100 and ImageNet benchmarks show that our method obtains state-of-the-art top-1 classification accuracy for uniform (non mixed-precision) quantization, out-performing previous methods by 0.5-1.2% absolute

Modeling of Causes of Sina Weibo Continuance Intention with Mediation of Gender Effects

Sina Weibo is a Twitter-like social networking site and one of the most popular microblogging services in China. This study aims to examine the factors that influence the intentions of users to continue using this site. This paper synthesizes the expectation confirmation model (ECM), constructs of habit and perceived critical mass, and the gender effect to construct a theoretical model to explain and predict these user intentions. The model is then tested via an online survey of 498 Sina Weibo users and partial least squares (PLS) modeling. The results indicate that the continuance intention of users is directly predicted by their perceived usefulness of the service (β=0.299), their satisfaction (β=0.208), and their habits (β=0.389), which jointly explain 65.9% of the variance in intention. In addition to the effects of these predictors on the continuance intentions of Sina Weibo users, an assessment of the moderating effect of gender suggests that habit plays a more important role for females than for males in continuance intention, but perceived usefulness seems to be more important for males than for females. The implications of these findings are then discussed