LGC-Net: A Lightweight Gyroscope Calibration Network for Efficient Attitude Estimation

This paper presents a lightweight, efficient calibration neural network model for denoising low-cost microelectromechanical system (MEMS) gyroscope and estimating the attitude of a robot in real-time. The key idea is extracting local and global features from the time window of inertial measurement units (IMU) measurements to regress the output compensation components for the gyroscope dynamically. Following a carefully deduced mathematical calibration model, LGC-Net leverages the depthwise separable convolution to capture the sectional features and reduce the network model parameters. The Large kernel attention is designed to learn the long-range dependencies and feature representation better. The proposed algorithm is evaluated in the EuRoC and TUM-VI datasets and achieves state-of-the-art on the (unseen) test sequences with a more lightweight model structure. The estimated orientation with our LGC-Net is comparable with the top-ranked visual-inertial odometry systems, although it does not adopt vision sensors. We make our method open-source at: https://github.com/huazai665/LGC-Ne

Mutual Information Learned Regressor: an Information-theoretic Viewpoint of Training Regression Systems

As one of the central tasks in machine learning, regression finds lots of applications in different fields. An existing common practice for solving regression problems is the mean square error (MSE) minimization approach or its regularized variants which require prior knowledge about the models. Recently, Yi et al., proposed a mutual information based supervised learning framework where they introduced a label entropy regularization which does not require any prior knowledge. When applied to classification tasks and solved via a stochastic gradient descent (SGD) optimization algorithm, their approach achieved significant improvement over the commonly used cross entropy loss and its variants. However, they did not provide a theoretical convergence analysis of the SGD algorithm for the proposed formulation. Besides, applying the framework to regression tasks is nontrivial due to the potentially infinite support set of the label. In this paper, we investigate the regression under the mutual information based supervised learning framework. We first argue that the MSE minimization approach is equivalent to a conditional entropy learning problem, and then propose a mutual information learning formulation for solving regression problems by using a reparameterization technique. For the proposed formulation, we give the convergence analysis of the SGD algorithm for solving it in practice. Finally, we consider a multi-output regression data model where we derive the generalization performance lower bound in terms of the mutual information associated with the underlying data distribution. The result shows that the high dimensionality can be a bless instead of a curse, which is controlled by a threshold. We hope our work will serve as a good starting point for further research on the mutual information based regression.Comment: 28 pages, 2 figures, presubmitted to AISTATS2023 for reviewin

Actividad antioxidante, fenoles totales y flavonoides totales en extractos de tallos de Jasminum nervosum Lour

Guangxi traditional Chinese Medical University Universidad de Medicina Tradicional China de Guangxi This study evaluated the antioxidant activities of the extracts of Jasminum nervosum Lour. stems along with the effects of different extract solvents on total phenolics (TP), total flavonoids (TF), and antioxidant potential. The antioxidant activity of the extracts was assessed using the following methods: DPPH, ABTS+ both free radicals scavenging assays, and reducing assays. TP and TF were detected by spectrophotometric and HPLC methods. In former methods, the highest amount of TP content was ethy lacetate extract (EAE), expressed as gallic acid equivalents. The greatest TF content was in the n-butanol extract (BE), expressed as lutin equivalents. No significant difference was observed in the TP/TF content between these two extracts. The antioxidant activity and TP/TF content of three extracts seemed to follow the same trend. This implied that there is a good correlation between antioxidant activities and TP/TF content. But in HPLC methods, EAE contained the highest content of lutin and gallic acid, which decreased in the same order of EAE > BE > PE, the rank order of TP/TF content of EAE and BE were different according to antioxidant ability. The overall results showed that the EAE and BE were richer in phenolics and flavonoids than petroleum ether extract (PE), and may represent a good source of antioxidants.Este estudio evaluó las actividades antioxidantes de extractos de tallos de Jasminum nervosum Lour., y el efecto de diferentes disolventes de extracción en los fenoles totales (TP) y flavonoides totales (TF), y su potencial antioxidante. La actividad antioxidante de los extractos fue evaluada usando los siguientes métodos: DPPH, ABTS+ y ensayos reductores. TP y TF fueron detectados por métodos espectroscópicos y por HPLC. Con el primer método, el contenido más alto de TP se obtuvo en el extracto con acetato de etilo (EAE), expresado como equivalentes de ácido gálico. Por su parte, el mayor contenido de TF se obtuvo en el extracto con n-butanol (BE), expresado como equivalentes de luteína. No se observaron diferencias significativas en la relación TP/TF entre los dos extractos. La actividad antioxidante y la relación TP/TF de los tres extractos parecen seguir el mismo comportamiento. Esto implica que hay una buena correlación entre las actividades antioxidantes y la relación TP/TF. Con el método de HPLC, el extracto EAE contenía los más altos contenidos de luteína y ácido gálico, que decrecieron en el mismo orden de EAE > BE > PE, el orden de la relación TP/TF de EAE y BE fueron diferentes de acuerdo a su capacidad antioxidante. En conjunto, los resultados muestran que los extractos de EAE y de BE fueron más ricos en compuestos fenólicos y flavonoides que el extracto de éter (PE), y pueden representar una buena fuente de antioxidantes

A Solar Heating and Cooling System in a Nearly Zero-Energy Building: A Case Study in China

The building sector accounts for more than 40% of the global energy consumption. This consumption may be lowered by reducing building energy requirements and using renewable energy in building energy supply systems. Therefore, a nearly zero-energy building, incorporating a solar heating and cooling system, was designed and built in Beijing, China. The system included a 35.17 kW cooling (10-RT) absorption chiller, an evacuated tube solar collector with an aperture area of 320.6 m2, two hot-water storage tanks (with capacities of 10 m3 and 30 m3, respectively), two cold-water storage tanks (both with a capacity of 10 m3), and a 281 kW cooling tower. Heat pump systems were used as a backup. At a value of 25.2%, the obtained solar fraction associated with the cooling load was close to the design target of 30%. In addition, the daily solar collector efficiency and the chiller coefficient of performance (COP) varied from 0.327 to 0.507 and 0.49 to 0.70, respectively

Embodied greenhouse gas emissions from building China’s large-scale power transmission infrastructure

China has built the world’s largest power transmission infrastructure by consuming massive volumes of greenhouse gas- (GHG-) intensive products such as steel. A quantitative analysis of the carbon implications of expanding the transmission infrastructure would shed light on the trade-offs among three connected dimensions of sustainable development, namely, climate change mitigation, energy access and infrastructure development. By collecting a high-resolution inventory, we developed an assessment framework of, and analysed, the GHG emissions caused by China’s power transmission infrastructure construction during 1990–2017. We show that cumulative embodied GHG emissions have dramatically increased by more than 7.3 times those in 1990, reaching 0.89 GtCO -equivalent in 2017. Over the same period, the gaps between the well-developed eastern and less-developed western regions in China have gradually narrowed. Voltage class, transmission-line length and terrain were important factors that influenced embodied GHG emissions. We discuss measures for the mitigation of GHG emissions from power transmission development that can inform global low-carbon infrastructure transitions.

Antioxidant activity, total phenolic, and total flavonoid of extracts from stems of <i>Jasminum nervosum</i> Lour

Guangxi traditional Chinese Medical University Universidad de Medicina Tradicional China de Guangxi This study evaluated the antioxidant activities of the extracts of <i>Jasminum nervosum</i> Lour. stems along with the effects of different extract solvents on total phenolics (TP), total flavonoids (TF), and antioxidant potential. The antioxidant activity of the extracts was assessed using the following methods: DPPH, ABTS+ both free radicals scavenging assays, and reducing assays. TP and TF were detected by spectrophotometric and HPLC methods. In former methods, the highest amount of TP content was ethy lacetate extract (EAE), expressed as gallic acid equivalents. The greatest TF content was in the n-butanol extract (BE), expressed as lutin equivalents. No significant difference was observed in the TP/TF content between these two extracts. The antioxidant activity and TP/TF content of three extracts seemed to follow the same trend. This implied that there is a good correlation between antioxidant activities and TP/TF content. But in HPLC methods, EAE contained the highest content of lutin and gallic acid, which decreased in the same order of EAE > BE > PE, the rank order of TP/TF content of EAE and BE were different according to antioxidant ability. The overall results showed that the EAE and BE were richer in phenolics and flavonoids than petroleum ether extract (PE), and may represent a good source of antioxidants.<br><br>Este estudio evaluó las actividades antioxidantes de extractos de tallos de <i>Jasminum nervosum</i> Lour., y el efecto de diferentes disolventes de extracción en los fenoles totales (TP) y flavonoides totales (TF), y su potencial antioxidante. La actividad antioxidante de los extractos fue evaluada usando los siguientes métodos: DPPH, ABTS+ y ensayos reductores. TP y TF fueron detectados por métodos espectroscópicos y por HPLC. Con el primer método, el contenido más alto de TP se obtuvo en el extracto con acetato de etilo (EAE), expresado como equivalentes de ácido gálico. Por su parte, el mayor contenido de TF se obtuvo en el extracto con n-butanol (BE), expresado como equivalentes de luteína. No se observaron diferencias significativas en la relación TP/TF entre los dos extractos. La actividad antioxidante y la relación TP/TF de los tres extractos parecen seguir el mismo comportamiento. Esto implica que hay una buena correlación entre las actividades antioxidantes y la relación TP/TF. Con el método de HPLC, el extracto EAE contenía los más altos contenidos de luteína y ácido gálico, que decrecieron en el mismo orden de EAE > BE > PE, el orden de la relación TP/TF de EAE y BE fueron diferentes de acuerdo a su capacidad antioxidante. En conjunto, los resultados muestran que los extractos de EAE y de BE fueron más ricos en compuestos fenólicos y flavonoides que el extracto de éter (PE), y pueden representar una buena fuente de antioxidantes

Evaluation of associations between genetically predicted circulating protein biomarkers and breast cancer risk.

A small number of circulating proteins have been reported to be associated with breast cancer risk, with inconsistent results. Herein, we attempted to identify novel protein biomarkers for breast cancer via the integration of genomics and proteomics data. In the Breast Cancer Association Consortium (BCAC), with 122,977 cases and 105,974 controls of European descendants, we evaluated the associations of the genetically predicted concentrations of >1,400 circulating proteins with breast cancer risk. We used data from a large-scale protein quantitative trait loci (pQTL) analysis as our study instrument. Summary statistics for these pQTL variants related to breast cancer risk were obtained from the BCAC and used to estimate odds ratios (OR) for each protein using the inverse-variance weighted method. We identified 56 proteins significantly associated with breast cancer risk by instrumental analysis (false discovery rate <0.05). Of these, the concentrations of 32 were influenced by variants close to a breast cancer susceptibility locus (ABO, 9q34.2). Many of these proteins, such as insulin receptor, insulin-like growth factor receptor 1 and other membrane receptors (OR: 0.82-1.18, p values: 6.96 × 10-4 -3.28 × 10-8 ), are linked to insulin resistance and estrogen receptor signaling pathways. Proteins identified at other loci include those involved in biological processes such as alcohol and lipid metabolism, proteolysis, apoptosis, immune regulation and cell motility and proliferation. Consistent associations were observed for 22 proteins in the UK Biobank data (p < 0.05). The study identifies potential novel biomarkers for breast cancer, but further investigation is needed to replicate our findings.Includes CRUK and FP7