Voice of Climate: Focus on GGDP

Green development has become a global goal for sustainable development. However, traditional GDP is unable to eff ectively refl ect the level of economic growth of an economy, let alone consider its relationship with the natural environment and ecosystems. Regarding the fi rst issue, this paper proposes a suitable GGDP calculation method, which includes traditional GDP, the value of natural resource depletion, the value of environmental pollution, as well as the benefi ts of resource and environmental improvement. We use partial least squares regression analysis (PLS) to model and accurately quantify the impact of GGDP variables on climate response indicators. The results show that the selected GGDP method can signifi cantly correlate and refl ect climate change. Regarding the second issue, this paper uses dynamic multivariate time series models (ARIMAX) and vector error correction models (VECM) to predict the impact of China’s climate mitigation. Cointegration tests were performed to determine the long-term equilibrium relationship among these indicators, and residual stationary white noise tests were conducted. The future 10-year GGDP was estimated using the quadratic curve estimation method, and future changes in climate indicators for the next 10 years were predicted using a multivariate time series model. The research fi ndings indicate that using GGD P instead of GDP has a positive impact on global climate mitigation

Guidelines for Adapting Structural Family Therapy Approach for Immigrant Generation East Asian American Families

The author developed detailed guidelines for adapting the structural family therapy approach for therapists who work with immigrant east Asian American families. Due to different acculturation levels among family members, immigrant parents often have conflicts with their children, which have become an important reason why Asian American families seek mental health services. The review of both traditional east Asian family-related cultural values and European American cultural values illustrates the parenting emphases that vary to a great extent between these two broad cultural groups. The widely accepted child development theories, parenting theories, and family therapy approaches were developed primarily based on European American populations. Asian American parenting approaches are often regarded as less favorable when they are evaluated using the Western parenting standards. However, many studies indicated that the traditional Asian American parenting approaches, including the parents\u27 emphasis on respect for elders, interdependency, self-control, and education, did not impact the children negatively. Studies suggested reduced treatment effectiveness when therapists treat east Asian families using Western developed family therapy approaches, such as structural family therapy, without adaption. The author adapted each structural family technique for immigrant east Asian family by incorporating their traditional parenting values into the standard techniques

Evolution of conditional cooperation in collective-risk social dilemma with repeated group interactions

The evolution and long-term sustenance of cooperation has consistently piqued scholarly interest across the disciplines of evolutionary biology and social sciences. Previous theoretical and experimental studies on collective risk social dilemma games have revealed that the risk of collective failure will affect the evolution of cooperation. In the real world individuals usually adjust their decisions based on environmental factors such as risk intensity and cooperation level. However, it is still not well understood how such conditional behaviors affect the evolution of cooperation in repeated group interactions scenario from a theoretical perspective. Here, we construct an evolutionary game model with repeated interactions, in which defectors decide whether to cooperate in subsequent rounds of the game based on whether the risk exceeds their tolerance threshold and whether the number of cooperators exceeds the collective goal in the early rounds of the game. We find that the introduction of conditional cooperation strategy can effectively promote the emergence of cooperation, especially when the risk is low. In addition, the risk threshold significantly affects the evolutionary outcomes, with a high risk promoting the emergence of cooperation. Importantly, when the risk of failure to reach collective goals exceeds a certain threshold, the timely transition from a defective strategy to a cooperative strategy by conditional cooperators is beneficial for maintaining high-level cooperation.Comment: Accepted by Proceedings of the Royal Society B-Biological Science

Mendelian randomization analysis to elucidate the causal relationship between small molecule metabolites and ovarian cancer risk

BackgroundSmall molecule metabolites are potential biomarkers for ovarian cancer. However, the causal relationship between small molecule metabolites and ovarian cancer remains unclear.MethodsSingle nucleotide polymorphisms (SNPs) correlated with 53 distinct small molecule metabolites were identified as instrumental variables (IVs) from comprehensive genome-wide association studies. Aggregate data encompassing 25,509 cases of ovarian cancer and 40,941 controls of European descent were procured from the Ovarian Cancer Association Consortium. To evaluate causative associations, four Mendelian randomization techniques—including inverse-variance weighted, weighted median, maximum likelihood, and MR-Egger regression—were employed.ResultsIn total, 242 SNPs were delineated as IVs for the small molecule metabolites under consideration. A significant association with the overarching risk of ovarian cancer was observed for six distinct metabolites. Hexadecenoylcarnitine and methioninesulfoxide were associated with a 32% and 31% reduced risk, respectively. Fifteen metabolites were linked to subtype ovarian cancers. For instance, both methionine sulfoxide and tetradecanoyl carnitine exhibited an inverse association with the risk of clear cell and high-grade serous ovarian cancers. Conversely, tryptophan demonstrated a 1.72-fold elevated risk for endometrioid ovarian cancer.ConclusionThis study identified several metabolites with putative causal effects on ovarian cancer risk using Mendelian randomization analysis. The findings provide insight into the etiological role of small molecule metabolites and highlight potential early detection biomarkers for ovarian cancer. Subsequent investigations are imperative to corroborate these findings and elucidate the underlying pathophysiological mechanisms

DSGN++: Exploiting Visual-Spatial Relation for Stereo-based 3D Detectors

Camera-based 3D object detectors are welcome due to their wider deployment and lower price than LiDAR sensors. We revisit the prior stereo modeling DSGN about the stereo volume constructions for representing both 3D geometry and semantics. We polish the stereo modeling and propose our approach, DSGN++, aiming for improving information flow throughout the 2D-to-3D pipeline in the following three main aspects. First, to effectively lift the 2D information to stereo volume, we propose depth-wise plane sweeping (DPS) that allows denser connections and extracts depth-guided features. Second, for better grasping differently spaced features, we present a novel stereo volume -- Dual-view Stereo Volume (DSV) that integrates front-view and top-view features and reconstructs sub-voxel depth in the camera frustum. Third, as the foreground region becomes less dominant in 3D space, we firstly propose a multi-modal data editing strategy -- Stereo-LiDAR Copy-Paste, which ensures cross-modal alignment and improves data efficiency. Without bells and whistles, extensive experiments in various modality setups on the popular KITTI benchmark show that our method consistently outperforms other camera-based 3D detectors for all categories. Code will be released at https://github.com/chenyilun95/DSGN2

Efficient Procedures of Sensitivity Analysis for Structural Vibration Systems with Repeated Frequencies

Derivatives of eigenvectors with respect to structural parameters play an important role in structural design, identification, and optimization. Particularly, calculation of eigenvector sensitivity is considered when the eigenvalues are repeated. A relaxation factor embedded in the combined approximations (CA) method makes it effective to the structural response at various modified designs. The proposed method is feasible after overcoming the defection of irreversibility of the characteristic matrix. Numerical examples show that it is easy to implement the computational procedure, and the method presented in this paper is efficient for the general linear vibration damped systems with repeated frequencies

Image feature recognition and gas permeability prediction of Gaomiaozi bentonite based on digital images and machine learning

Gas permeability, which is measured mainly through gas permeability experiments, is a critical technical index in many engineering fields. In this study, permeability is firstly calculated based on information from a digital image and an improved permeability prediction model. The calculated results are experimentally verified. Subsequently, a self-developed image-processing program is used to extract feature parameters from a scanning electron microscopy image. Meanwhile, an extreme learning machine algorithm is used to input the image feature parameters obtained using the image-processing program into the extreme learning machine algorithm for machine learning. Additionally, we compare several typically used machine learning algorithms, which confirmed the reliability and accuracy of our algorithm. The best activation function can be obtained by comparing the predicted permeability using an appropriate number of neuron nodes. Experimental results show that the program can accurately identify the features of the microscopy image. Combining the program with an extreme learning machine neural network algorithmgas permeability results to be obtained with high accuracy. This method yields good predictions of permeability in certain cases and has been adapted to other geomaterials.Cited as: Liu, J., Ma, S., Shen, W., Zhou, J., Hong, Y. Image feature recognition and gas permeability prediction of Gaomiaozi bentonite based on digital images and machine learning. Advances in Geo-Energy Research, 2022, 6(4): 314-323. https://doi.org/10.46690/ager.2022.04.0

The Impact of Wire Stent Fabrication Technique on the Performance of Stent Placement

Braided wire stents demonstrate distinct characteristics compared to welded ones. In this study, both braided and welded wire stents with the same nominal dimensions were crimped inside a sheath and then deployed into a stenosed artery using finite element analysis. The braided wire stent was generated by overlapping wires to form crisscross shape. A welded wire stent was created by welding the intersection points of wires to avoid sliding between wires. The effect of fabrication technique on mechanical behavior of Nitinol wire stents was evaluated. The results showed that relative sliding between wires reduced the deformation of the braided stent, which led to less radial strength than the welded one; therefore, the deployed braided stent was more conformed to the anatomic shape of the lesion and much less efficient for restoring the patency of the stenotic artery. Post balloon-dilation was commonly used to improve its performance in terms of lumen gain and deployed shape of the stent. On the contrary, the welded wire stent exhibited a high capacity for pushing the occlusion outward. It reached an approximately uniform shape after deployment. The welded joints caused larger deformation and high strain on the stent struts, which indicate a potential earlier failure for the welded stent. In addition, higher contact pressure at the stent-lesion interface and higher arterial stresses were observed in the artery supported by the welded stent. The peak stress concentration may increase the occurrence of neointimal hyperplasia

Oxidation of copper electrodes on flexible polyimide substrates for non-enzymatic glucose sensing

The integration of non-enzymatic glucose sensing entities into device designs compatible with industrial production is crucial for the broad take-up of non-invasive glucose sensors. Copper and its oxides have proven to be promising candidates for electrochemical glucose sensing. They can be fabricated in situ enabling integration with standard copper metallisation schemes for example in printed circuit boards (PCBs). Here, copper oxide electrodes are prepared on flexible polyimide substrates through direct annealing of patterned electrode structures. Both annealing temperature and duration are tuned to optimise the sensor surface for optimum glucose detection. A combination of microscopy and spectroscopy techniques is used to follow changes to the surface morphology and chemistry under the varying annealing conditions. The observed physico-chemical electrode characteristics are directly compared with electrochemical testing of the sensing performance, including chronoamperommetry and interference experiments. A clear influence of both aspects on the sensing behaviour is observed and an anneal at 250 °C for 8 h is identified as the best compromise between sensor performance and low interference from competing analytes