Despite the perceived success of educational campaigns and smoking bans in public places in China, the actual effects have not been investigated. This study examines the effects of the two policies by major characteristics of smokers and whether the affected smokers have intention to quit smoking. A cross-sectional survey was conducted in 17 cities in China and 16,616 participants were selected using multistage stratified sampling. Logistic regression models were used to examine the effects of educational campaigns and smoking bans in public places on their intention to quit smoking. Results show that the Chinese government should try every means to build its tobacco control publicity and implement various forms of public educational campaigns to enhance smokers' knowledge of the health consequences of smoking. In addition, China should emphasize the enforcement of the existing smoking prohibitions and regulations by implementing local tobacco control legislation and total prohibitions in all public places and workplaces.

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This paper depends on the panel data of Anhui province and its 17 cities' cigarette sales. First we established three single forecasting models (Holter-Wintel Season product model, Time series model decomposing model and Partial least square regression model), after getting the predicted value of cigarette sales from these single models, we then employ the combination forecasting method based on Time Series method and PLS to predict the province and its 17 cities' cigarette sales of the next year. The results show that the accuracy of prediction is good which could provide a reliable reference to cigarette sales forecasting in Anhui province and its 17 cities.

As significant evidence of ice-rich permafrost degradation due to climate warming, thermokarst lake was developing and undergoing substantial changes. Thermokarst lake was an essential ecosystem component, which significantly impacted the global carbon cycle, hydrology process and the stability of the Qinghai-Tibet Engineering Corridor. In this paper, based on Sentinel-2 (2021) and Landsat (1988-2020) images, thermokarst lakes within a 5,000 m range along both sides of Qinghai-Tibet Highway (QTH) were extracted to analyse their spatio-temporal variations. The results showed that the number and area of thermokarst lake in 2021 were 3,965 and 4,038.6 ha (1 ha = 10,000 m2), with an average size of 1.0186 ha. Small thermokarst lakes (<1 ha) accounted for 85.65% of the entire lake count, and large thermokarst lakes (>10 ha) occupied for 44.92% of the whole lake area. In all sub-regions, the number of small lake far exceeds 75% of the total lake number in each sub-region. R1 sub-region (around Wudaoliang region) had the maximum number density of thermokarst lakes with 0.0071, and R6 sub-region (around Anduo region) had the minimum number density with 0.0032. Thermokarst lakes were mainly distributed within range of 4,300 m~5,000 m a.s.l. (94.27% and 97.13% of the total number and size), on flat terrain with slopes less than 3° (99.17% and 98.47% of the total number and surface) and in the north, south, and southeast aspects (47.06% and 32.99% of the total number and area). Thermokarst lakes were significantly developed in warm permafrost region with mean annual ground temperature (MAGT) > -1.5°C, accounting for 47.39% and 54.38% of the total count and coverage, respectively. From 1988 to 2020, in spite of shrinkage or even drain of small portion of thermokarst lake, there was a general expansion trend of thermokarst lake with increase in number of 195 (8.58%) and area of 1,160.19 ha (41.36%), which decreased during 1988-1995 (-702 each year and -706.27 ha/yr) and then increased during 1995-2020 (184.96-702 each year and 360.82 ha/yr). This significant expansion was attributed to ground ice melting as rising air temperature at a rate of 0.03~0.04℃/yr. Followed by the increasing precipitation (1.76~3.07 mm/yr) that accelerated the injection of water into the lake.

We consider the problem of computing the projection P C u, where u is chosen in a real Hilbert space H arbitrarily and the closed convex subset C of H is the intersection of finite level sets of convex functions given as follows:, where m is a positive integer and c i : H → R is a convex function for i = 1, . . . , m. A relaxed Halpern-type algorithm is proposed for computing the projection P C u in this paper, which is defined by xn , n ≥ 0, where the initial guess x 0 ∈ H is chosen arbitrarily, the sequence (λ n ) is in (0, 1) and (C i n ) is a sequence of half-spaces containing C i for i = 1, . . . , m. Since calculations of the projections onto half-spaces C i n (i = 1, . . . , m; n = 1, 2, . . .) are easy in practice, this algorithm is quite implementable. Strong convergence of our algorithm is proved under some ordinary conditions. Some numerical experiments are provided which show advantages of our algorithm. MSC: 58E35; 47H09; 65J15