Badanie ścieżki handlu uprawnieniami do emisji dwutlenku węgla w Chinach w kontekście tzw. podwójnego węgla

With the continuous development of the global economy, the rapid deterioration of the global ecological environment has caused a huge impact on the future development of the world. In order to solve the problem of global warming and enhance the self-development capacity of all countries, based on the concept of sustainable development, China has set the ambitious goal of dual carbon. To this end, China is actively promoting the establishment of a national carbon emissions trading system.In response to low price competitiveness, such as nonstandard trading system, the influence of the development of the carbon emissions trading system in the future, should not only attach importance to enrich and strengthen the basic function of the carbon market, also continue to carbon pricing system and in-depth reform of the fiscal and taxation system, clear up the thoughts to the carbon market trading rules, is on its relevant rights and obligations, firmly adhere to steadily promote carbon market links between countries. Currently, China’s carbon emission trading is still in its infancy, and its effect is still limited in specific practice. Meanwhile, carbon emission trading markets in developed countries such as the United States and the United Kingdom have begun to implement carbon tariffs and other means to maintain their carbon borders. Therefore, the construction of carbon emission trading is necessary for development, but also for the sustainable development of the country.The lag of China’s carbon emission market leads to the worsening of the problem of carbon excess emissions of industries in the regions not covered, and the increased economic burden caused by the carbon barriers of other countries in foreign trade. Of course, this requires China take the path of sustainable development to continue to strengthen the system construction of carbon emission rights and promote the further optimization of their functions.Wraz z ciągłym rozwojem światowej gospodarki, gwałtowne pogarszanie się globalnego środowiska ekologicznego wywiera ogromny wpływ na przyszły rozwój świata. Aby rozwiązać problem globalnego ocieplenia i zwiększyć zdolność do samorozwoju wszystkich krajów, w oparciu o koncepcję zrównoważonego rozwoju, Chiny postawiły sobie ambitny cel podwójnego węgla. W tym celu Chiny aktywnie promują ustanowienie krajowego systemu handlu uprawnieniami do emisji dwutlenku węgla. W odpowiedzi na niską konkurencyjność cenową, taką jak niestandardowy system handlu, wpływ rozwoju systemu handlu uprawnieniami do emisji dwutlenku węgla w przyszłości powinien nie tylko wzmacniać podstawową funkcję rynku uprawnieniami do emisji dwutlenku węgla, ale także sprzyjać kontynuacji systemu ustalania cen emisji uprawnień do emisji dwutlenku węgla oraz dogłębneie reformy systemu fiskalnego i podatkowego, wyjaśnieniu zasad handlu uprawnieniami do emisji dwutlenku węgla, jego odpowiednich praw i obowiązków oraz stanowczo opowiadać się za stałym promowaniem powiązań między krajami na rynku uprawnień do emisji dwutlenku węgla. Obecnie handel emisjami dwutlenku węgla w Chinach jest wciąż w powijakach, a jego efekt jest nadal ograniczony. Tymczasem rynki handlu emisjami dwutlenku węgla w krajach rozwiniętych, takich jak Stany Zjednoczone i Wielka Brytania, zaczęły wdrażać taryfy węglowe i inne środki utrzymania swoich granic węglowych. Dlatego budowa handlu emisjami dwutlenku węgla jest konieczna dla rozwoju, ale także dla zrównoważonego rozwoju kraju. Opóźnienie rynku emisji dwutlenku węgla w Chinach prowadzi do pogłębienia problemu nadprodukcji węgla przez przemysł i zwiększonego obciążenia ekonomicznego spowodowane go barierami węglowymi innych krajów w handlu zagranicznym. Oczywiście wymaga to od Chin wejścia na ścieżkę zrównoważonego rozwoju, dalszego wzmacniania budowy systemu uprawnień do emisji dwutlenku węgla oraz promowania dalszej optymalizacji ich funkcji

Lorentz Quantum Computer

A theoretical model of computation is proposed based on Lorentz quantum mechanics. Besides the standard qubits, this model has an additional bit, which we call hyperbolic bit (or hybit in short). A set of basic logical gates are constructed and their universality is proved. As an application, a search algorithm is designed for this computer model and is found to be exponentially faster than the Grover's search algorithm

Deformable Kernel Expansion Model for Efficient Arbitrary-shaped Scene Text Detection

Scene text detection is a challenging computer vision task due to the high variation in text shapes and ratios. In this work, we propose a scene text detector named Deformable Kernel Expansion (DKE), which incorporates the merits of both segmentation and contour-based detectors. DKE employs a segmentation module to segment the shrunken text region as the text kernel, then expands the text kernel contour to obtain text boundary by regressing the vertex-wise offsets. Generating the text kernel by segmentation enables DKE to inherit the arbitrary-shaped text region modeling capability of segmentation-based detectors. Regressing the kernel contour with some sampled vertices enables DKE to avoid the complicated pixel-level post-processing and better learn contour deformation as the contour-based detectors. Moreover, we propose an Optimal Bipartite Graph Matching Loss (OBGML) that measures the matching error between the predicted contour and the ground truth, which efficiently minimizes the global contour matching distance. Extensive experiments on CTW1500, Total-Text, MSRA-TD500, and ICDAR2015 demonstrate that DKE achieves a good tradeoff between accuracy and efficiency in scene text detection

An Efficient Imbalance-Aware Federated Learning Approach for Wearable Healthcare with Autoregressive Ratio Observation

Widely available healthcare services are now getting popular because of advancements in wearable sensing techniques and mobile edge computing. People's health information is collected by edge devices such as smartphones and wearable bands for further analysis on servers, then send back suggestions and alerts for abnormal conditions. The recent emergence of federated learning allows users to train private data on local devices while updating models collaboratively. However, the heterogeneous distribution of the health condition data may lead to significant risks to model performance due to class imbalance. Meanwhile, as FL training is powered by sharing gradients only with the server, training data is almost inaccessible. The conventional solutions to class imbalance do not work for federated learning. In this work, we propose a new federated learning framework FedImT, dedicated to addressing the challenges of class imbalance in federated learning scenarios. FedImT contains an online scheme that can estimate the data composition during each round of aggregation, then introduces a self-attenuating iterative equivalent to track variations of multiple estimations and promptly tweak the balance of the loss computing for minority classes. Experiments demonstrate the effectiveness of FedImT in solving the imbalance problem without extra energy consumption and avoiding privacy risks.Comment: submitted to IEEE OJCS in Oct. 2023, under revie

Validation and Application of SMAP SSS Observation in Chinese Coastal Seas

Using sea surface salinity (SSS) from the Soil Moisture Active Passive (SMAP) mission from September 2015 to August 2016, the spatial distribution and seasonal variation in SSS in the Chinese coastal seas were investigated. First, in situ salinity observation over Chinese East Sea was used to validate SMAP observation. Then, the SSS signature of the Yangtze River fresh water was analyzed using SMAP data and the river discharge data. The SSS around the Yangtze River estuary in the Chinese East Sea, the Bohai Sea and the Yellow Sea is significantly lower than that of the open ocean. The SSS of Chinese coastal seas shows significant seasonal variation, and the seasonal variation in the adjacent waters of the Yangtze River estuary is the most obvious, followed by that of the Pearl River estuary. The minimum value of SSS appears in summer while maximum in winter. The root-mean-squared difference of daily SSS between SMAP observation and in situ observation is around 3 psu in both summer and winter, which is much lower than the annual range of SSS variation. The path of fresh water from SMAP and in situ observation is consistent during summer time

A Unified Perspective on Multiple Shooting In Differential Dynamic Programming

Differential Dynamic Programming (DDP) is an efficient computational tool for solving nonlinear optimal control problems. It was originally designed as a single shooting method and thus is sensitive to the initial guess supplied. This work considers the extension of DDP to multiple shooting (MS), improving its robustness to initial guesses. A novel derivation is proposed that accounts for the defect between shooting segments during the DDP backward pass, while still maintaining quadratic convergence locally. The derivation enables unifying multiple previous MS algorithms, and opens the door to many smaller algorithmic improvements. A penalty method is introduced to strategically control the step size, further improving the convergence performance. An adaptive merit function and a more reliable acceptance condition are employed for globalization. The effects of these improvements are benchmarked for trajectory optimization with a quadrotor, an acrobot, and a manipulator. MS-DDP is also demonstrated for use in Model Predictive Control (MPC) for dynamic jumping with a quadruped robot, showing its benefits over a single shooting approach