Fast data processing method for multispectral radiation thermometry based on Euclidean distance optimization.

This study presents a fast and accurate data processing method for multispectral radiation thermometry that can accurately measure the true temperature of steel materials without requiring a priori emissivity model. The method generates a temperature matrix by inputting emissivity values at different wavelengths and selects a reference vector from the matrix. Then, it rearranges the temperature matrices at other wavelengths and calculates the Euclidean distance between each column element of the rearranged matrix and the reference vector. The method uses an unconstrained optimization technique to minimize the Euclidean distance and obtain the true temperature and emissivity of the object simultaneously. We evaluate the performance of the method by simulation and experiment in the response band of 1.4 ∼ 2.5 µm and temperature range of 873 ∼ 1173 K. The simulation results indicate that the relative error of the inverted temperature is within 0.229%, and the average computation time is less than 112.301 ms. The experimental results show that the maximum temperature error during the measurement process is 0.813%. Our method provides a feasible and efficient solution for real-time temperature measurement of steel materials.

Approach to multispectral thermometry with Planck formula and hybrid metaheuristic optimization algorithm.

Accurate temperature measurement has significant implications for product quality, industrial process control, and scientific research. As a non-contact temperature measurement method with broad application prospects, multispectral thermometry still poses significant challenges in data processing. Currently, most multispectral thermometry methods use the Wien approximation equation to construct the objective function. However, the use of the Wien approximation equation is conditional and generally applicable only to low temperatures or short wavelengths. In this paper, what we believe is a new data processing model of multispectral thermometry is established based on the Planck formula; Additionally, a feasible region constraint method is proposed to constrain the emissivity range; By utilizing a hybrid metaheuristic optimization algorithm based on differential evolution (DE) and multi-population genetic (MPG) algorithms, the simulation results of six different models and experimental results of silicon carbide demonstrate that the proposed algorithm achieves an average relative error in temperature measurement within 0.42% and a random relative error within 0.79%. The average computation time for each temperature inversion is approximately 0.26 seconds. The accuracy and efficiency of the algorithm ensure that it can be applied to real-time temperature measurement in industrial field.

Efficacy and safety of agomelatine versus SSRIs/SNRIs for post-stroke depression: a systematic review and meta-analysis of randomized controlled trials.

Agomelatine is effective in the treatment of depression, but its effect for post-stroke depression (PSD) remains unclear. This study was conducted to compare the efficacy and safety of agomelatine versus SSRIs/SNRIs in treating PSD. We systematically searched Embase, PubMed, Cochrane Library, WanFang Data, China National Knowledge Infrastructure, and Cqvip databases for double-blind randomized controlled studies comparing the efficacy and safety of agomelatine versus SSRIs/SNRIs for PSD until December 2022. The primary efficacy endpoint was the Hamilton Depression Rating Scale (HAMD) score, and the primary safety endpoint was the incidence of overall adverse reactions. Nine studies comprising 857 patients with PSD were included. After 6-12 weeks of treatment, the HAMD score ( P  = 0.16) and the overall response rates ( P  = 0.20) in the agomelatine group were comparable to that in the SSRIs/SNRIs group. Participants treated with agomelatine achieved higher Barthel Index scores compared with the SSRIs/SNRIs group ( P  = 0.02). There was a significantly lower incidence of overall adverse reactions ( P  = 0.008) and neurological adverse reactions ( P  < 0.0001) in the agomelatine group. The efficacy of agomelatine for treating PSD is probably comparable to that of SSRIs/SNRIs, and it may improve stroke outcomes with better safety.

Certification of stroke centers at primary hospitals and the improvement of thrombolysis n South China during 2020-2022.

INTRODUCTION: IVT use declined globally in 2020 due to the Corona Virus Disease 2019 (COVID-19) pandemic, but it increased in South China. This study was conducted to evaluate the association of establishing Stroke Prevention Centers (SPCs) at primary hospitals with IVT increase in South China. MATERIALS AND METHODS: We conducted a longitudinal observational study across 336 hospitals in 114 areas in South China during 2020-2022. Data regarding certified stroke centers, IVT volumes, and IVT rates were collected. Correlations between IVT rates and the number or density of stroke centers were accessed. IVT use was compared among areas with different levels of stroke centers or on different certification process. RESULTS: During 2020-2022, there were 83, 125, and 152 stroke centers, with 26, 65, and 92 SPCs, respectively. IVT therapies were 12,795, 17,266, and 20,411, representing a 29.8% increase/year (all p < 0.001). IVT rates increased from 7.2% in 2020 to 8.8% and 10.4% in 2021 and 2022, demonstrating a 22.2% increase/year (all p < 0.001). IVT rates correlated with the number and density of SPCs (all p < 0.05). IVT rates were higher in areas equipped with SPCs than in those without stroke centers (all p < 0.05). IVT rates consistently increased during the SPC certification process from 1 year before through the certification and subsequent maintenance (both p < 0.05). DISCUSSION AND CONCLUSION: Well-organised SPCs and IVT therapy demonstrated substantial increase during the 3-year period. Certification of SPCs at primary hospitals is associated with improved IVT therapy in South China even with city lockdown during COVID-19 pandemic.