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Copyright of Chinese Journal of Inorganic Analytical Chemistry / Zhongguo Wuji Fenxi Huaxue is the property of Beijing Research Institute of Mining & Metallurgy Technology Group and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introduction: The aims of the study were to investigate whether first-dose efficacy can predict third-dose anatomical response and analyze the risk factors for first-dose response of polypoidal choroidal vasculopathy (PCV) patients. Methods: We retrospectively reviewed patients' medical records from 27 centers of China PCV Research Alliance. PCV patients treated with intravitreal injections of conbercept (IVC) based on the 3+ pro re nata regimen (three initial monthly injections, followed by injections as needed) with complete 3-month injection data were included. Response correlations, risk factor associations, changes in central macular thickness (CMT) or best-corrected visual acuity (BCVA), and number of injections in the first year of follow-up were evaluated separately in the pachy-PCV and non-pachy-PCV phenotypes. Results: Overall, 165 eligible patients were included. There was a significant correlation between first-dose and third-dose anatomical response in pachy-PCV or non-pachy-PCV patients (rs = 0.611, p < 0.001; rs = 0.638, p < 0.001). Multivariate analysis revealed associations of good first-dose anatomical response in pachy-PCV patients with baseline CMT with a predicted area under the curve (AUC) of 0.847, while a good response in non-pachy-PCV patients was associated with baseline BCVA, baseline CMT, pigment epithelial detachment (PED) height, higher proportion of intraretinal fluid, and lower PED minimum diameter with a predicted AUC of 0.940. CMT in the good first-dose response group was significantly decreased from baseline at all first-year follow-up visits in both groups (p < 0.001), and mean BCVA was improved in the good versus poor first-dose anatomical response group (5.4 vs. 1.6 ETDRS letters in pachy-PCV, 10.6 vs. 7.4 letters in non-pachy-PCV) after the third injection. No significant difference was observed in the number of injections in the first year of follow-up between different response groups. Conclusion: In PCV patients receiving IVC, the first- and third-dose responses are significantly correlated, and different factors influence the first-dose response in different subtypes of PCV. [ABSTRACT FROM AUTHOR]

目的:调查和分析免疫检查点抑制剂在儿童患者应用中的不良反应。 方法:回顾性调查 2019 年 1 月 1 日至 2022 年 9 月 15 日于该院接受程序性死亡受体 1(PD-1) / 程序性死亡受体配体 1(PD-L1)抑制剂治疗各类恶性实体肿瘤和血液系统肿瘤的 25 例儿童患者(<18 周岁)病历(共 137 次入院记录),记录患儿接受治疗期间发生的所有不良反应信息,并进行严重程度分级、相 关性评价和影响因素分析。 结果:25 例使用 PD-1/ PD-L1 抑制剂的患儿中,16 例患儿合计发生 20 次不良反应。 患儿发生的不良 反应主要为发热(8 例,发生率为 32%)、氨基转移酶升高(3 例,发生率为 12%)和凝血功能障碍(2 例,发生率为 8%),此外还有白 细胞计数降低、咳嗽、皮疹、腹泻、便潜血、乏力及食欲减退(各 1 例,发生率均为 4%)等;其中,1—2 级不良反应 19 次,3—5 级不良 反应共 1 次;相关性为“很可能”的不良反应共 15 次。 4 例患儿在发生不良反应后再次接受治疗,有 2 例出现了新的不良反应。 经分析,并发症涉及 3 个及以上系统对不良反应的发生率有显著影响。 结论:儿童患者使用 PD-1/ PD-L1 抑制剂时,其不良反应 发生情况与成人有所差异,较成人而言需要更多关注。 临床需注意用药监护,提高儿童用药的安全性。 [ABSTRACT FROM AUTHOR]

The study aimed to explore the changes of the photosynthetic performance of Medicago sativa leaves in late autumn by screening alfalfa germplasm materials suitable for planting in Heilongjiang Province. Six Medicago sativa varieties were used as experimental materials. Photosynthetic indexes, including leaf water vapor pressure, stomatal conductance, net photosynthetic rate, transpiration rate and intercellular CO2 concentration, were measured. Excellent Medicago sativa varieties were selected by a membership function evaluation. The results showed that the net photosynthetic rate and water use efficiency of Longmu 801 were the highest. The stomatal conductance and intercellular CO2 concentration of Caoyuan No. 3 were the highest. The transpiration rate of Caoyuan No. 3 and Longmu 801 was significantly higher than that of other varieties (P<0.05). The leaf water vapor pressure of Caoyuan No.3, Longmu 801 and Queen was significantly higher than that of other varieties (P<0.05). Membership functions were used to evaluate the photosynthetic performance of varieties. The photosynthetic performance of Medicago sativa varieties, ranked from high to low, was as follows: Longmu 801 > Caoyuan No.3 > Queen > Concept > Adrenalin > Sardi. The study indicates that Longmu 801 and Caoyuan No.3 have strong photosynthetic performance and were suitable for planting in Heilongjiang. [ABSTRACT FROM AUTHOR]

Foamed concrete, due to its lightweight and high-strength characteristics, offers significant advantages as a roadbed material. However, its mechanical properties are notably influenced by its density and microstructure. Comprehensive research addressing the correlation between the density, mechanical properties, and microstructure of roadbed foamed concrete, especially within real construction scenarios, remains limited. To address this research gap, we undertook compressive strength tests and a set of microstructural analyses on four sets foamed concrete samples of varying densities prepared on-site. The objective was to deeply understand the mechanical and microstructural characterization of roadbed foamed concrete at different densities and correlation Analysis. The findings indicate an exponential correlation between density and compressive strength, most prominently within the density range of 800–1000 kg/m3, accompanied by commendable thermal stability. X-ray Computed Tomography (X-CT) analyses further demonstrate that density increase is pivotal in enhancing the pore structure, thereby achieving lower porosity, fewer detrimental pores, more homogeneous pore distribution, and superior pore sphericity. Scanning Electron Microscopy (SEM) evaluations suggest that enhancing the density of the sample can mitigate the damage to individual pores, reduce internal cavities, and curb initial defects. Furthermore, the pore intersections exhibit a more intact and dense crystalline structure. Upon assessment, we discerned a significant correlation between porosity, compressive strength, and density. The Pearson correlation coefficient (r) between any two of these parameters is notably close to 1 (−1). These research results show that it is feasible to optimize the density of foam concrete to enhance its microstructure and thereby enhance its compressive performance. This provides strong data support for the wider application of foam concrete in roadbed engineering.

Cognitive competency is an essential complement to the existing ship pilot screening system that should be focused on. Situation awareness (SA), as the cognitive foundation of unsafe behaviors, is susceptible to influencing piloting performance. To address this issue, this paper develops an identification model based on random forest- convolutional neural network (RF-CNN) method for detecting at-risk cognitive competency (i.e., low SA level) using wearable EEG signal acquisition technology. In the poor visibility scene, the pilots’ SA levels were correlated with EEG frequency metrics in frontal (F) and central (C) regions, including α/β (p = 0.071 < 0.1 in F and p = 0.042 < 0.05 in C), θ/(α + θ) (p = 0.048 < 0.05 in F and p = 0.026 < 0.05 in C) and (α + θ)/β (p = 0.046 < 0.05 in F and p = 0.012 < 0.05 in C), and then a total of 12 correlation features were obtained based on a 5 s sliding time window. Using the RF algorithm developed by principal component analysis (PCA) for further feature combination, these salient combinations are used as input sets to obtain the CNN algorithm with optimal parameters for identification. The comparative results of the proposed RF-CNN (accuracy is 84.8%) against individual RF (accuracy is 78.1%) and CNN (accuracy is 81.6%) methods demonstrate that the RF-CNN with feature optimization provides the best identification of at-risk cognitive competency (accuracy increases 6.7%). Overall, the results of this paper provide key technical support for the development of an adaptive evaluation system of pilots’ cognitive competency based on intelligent technology, and lay the foundation and framework for monitoring the cognitive process and competency of ship piloting operation in China. [ABSTRACT FROM AUTHOR]

Forest ecological carrying capacity can measure the balance between environmental pollution and forest ecosystems in the process of social development. This paper first selects 17-year panel data of five provinces in southeastern China, and uses the generalized trapezoidal fuzzy number to describe and express them based on the flat peak characteristic of the data itself; Secondly, the generalized Shapley value with the introduction of λ-fuzzy measure is used to measure the correlation between attribute indicators, and the indicator weight is determined by the attributes contribution; Then, an optimal fuzzy measure linear programming model is established based on the similarity, which is used to determine the generalized Shapley value of each attribute indicator. Finally, the λ-Shapley-Choquet integral operator is used for information aggregation and the centroid method is used to rank the comprehensive evaluation values. The results show that the forest ecological carrying capacity of five provinces during 2004-2020 is ranked from high to low as Fujian Province, Jiangxi Province, Zhejiang Province, Guangxi Province, and Guangdong Province. Based on this, it is proposed that strengthening the forest's ecological carrying capacity in southeastern China should be carried out in parallel from two aspects: enriching forest resources and reducing environmental pollution. [ABSTRACT FROM AUTHOR]

The study of tumor microenvironment plays an important role in the treatment of cancer patients. In this paper, intelligent medical Internet of Things technology was used to analyze cancer tumor microenvironment-related genes. Through experiments designed and analyzed cancer-related genes, this study concluded that in cervical cancer, patients with high expression of P16 gene had a shorter life cycle and a survival rate of 35%. In addition, through investigation and interview, it was found that patients with positive expression of P16 and Twist genes had a higher recurrence rate than patients with negative expression of both genes; high expression of FDFT1, AKR1C1, and ALOX12 in colon cancer is associated with short survival; high expressions of HMGCR and CARS1 is associated with longer survival; overexpression of NDUFA12, FD6, VEZT, GDF3, PDE5A, GALNTL6, OPMR1, and AOAH in thyroid cancer is associated with shortened survival; high expressions of NR2C1, FN1, IPCEF1, and ELMO1 is associated with prolonged survival. Among the genes associated with the prognosis of liver cancer, the genes associated with shorter survival period are AGO2, DCPS, IFIT5, LARP1, NCBP2, NUDT10, and NUDT16; the genes associated with longevity are EIF4E3, EIF4G3, METTL1, NCBP1, NSUN2, NUDT11, NUDT4, and WDR4. Depending on the prognostic role of genes in different cancers, they can influence patients to achieve the effect of reducing patients’ symptoms. In the process of disease analysis of cancer patients, this paper uses bioinformation technology and Internet of things technology to promote the development of medical intelligence.

Respiratory monitoring is a significant issue to reduce patient risks and medical staff labor in postoperative care and epidemic infection, particularly after the COVID-19 pandemic. Oximetry is widely used for respiration monitoring in the clinic, but it sometimes fails to capture a low-functional respiratory condition even though a patient has breathing difficulty. Another approach is breathing-sound monitoring, but this is unstable due to the indirect measurement of lung volume. Kobayashi in our team is developing a sensor measuring temporal changes in lung volume with a displacement sensor attached across the sixth and eighth ribs. For processing these respiratory signals, we propose the combination of complex-valued wavelet transform and the correlation among spectrum sequences. We present the processing results and discuss its feasibility to detect a low-functional condition in respiration. The result for detecting low-functional respiration showed good performance with a sensitivity of 0.88 and specificity of 0.88 to 1 in its receiver operating characteristic (ROC) curve.

• Experiments investigate flow condensation heat transfer for vertical and horizontal orientations. • Detailed data reduction and uncertainty analysis presented. • Trends involving flow inertia, body force, and liquid mass fraction presented. • Separated Flow Model predictions for vertical downflow offer reasonable agreement. • Common correlations evaluated for horizontal flow results. The present study aims to better analyze the influence of body force on flow condensation heat transfer by conducting tests at multiple orientations in Earth's gravity. Dielectric FC-72 is condensed in a smooth stainless-steel tube with 7.12 mm diameter and 574.55 mm condensing length by counterflow of cooling water across the outer surface of the tube. Test conditions span FC-72 mass velocities of 50.3–360.3 kg/m2 s, test section inlet pressures of 127.0–132.1 kPa, and test section inlet thermodynamic equilibrium qualities of 0.13–1.15. A subset of data gathered corresponding to axisymmetric, annular condensation heat transfer is identified and a detailed methodology for data reduction to calculate heat transfer coefficient presented. Uncertainty analysis is also presented and indicates channel average heat transfer coefficients are calculated within ±3.6% to ±26.7% (depending on operating conditions). Analysis of parametric trends for condensation heat transfer reveals the dominant influence of mass velocity (flow inertia), secondary influence of vapor mass fraction (thermodynamic equilibrium quality), and strong dependence on orientation (body force) at low mass velocities. At higher mass velocities results for all orientations investigated begin to converge, indicating body force independent annular condensation heat transfer is achieved. Separated Flow Model predictions of vertical downflow condensation heat transfer provide reasonable agreement with experimental results, evidence by a Mean Absolute Error (MAE) of 31.2%. Evaluation of condensation heat transfer correlations for horizontal flow reveal most correlations struggle for cases with high liquid content. Specific correlations are identified for superior accuracy in predicting the measured data. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cognitive competency is an essential complement to the existing ship pilot screening system that should be focused on. Situation awareness (SA), as the cognitive foundation of unsafe behaviors, is susceptible to influencing piloting performance. To address this issue, this paper develops an identification model based on random forest- convolutional neural network (RF-CNN) method for detecting at-risk cognitive competency (i.e., low SA level) using wearable EEG signal acquisition technology. In the poor visibility scene, the pilots' SA levels were correlated with EEG frequency metrics in frontal (F) and central (C) regions, including α/β ( p  = 0.071 < 0.1 in F and p  = 0.042 < 0.05 in C), θ/(α + θ) ( p  = 0.048 < 0.05 in F and p  = 0.026 < 0.05 in C) and (α + θ)/β ( p  = 0.046 < 0.05 in F and p  = 0.012 < 0.05 in C), and then a total of 12 correlation features were obtained based on a 5 s sliding time window. Using the RF algorithm developed by principal component analysis (PCA) for further feature combination, these salient combinations are used as input sets to obtain the CNN algorithm with optimal parameters for identification. The comparative results of the proposed RF-CNN (accuracy is 84.8%) against individual RF (accuracy is 78.1%) and CNN (accuracy is 81.6%) methods demonstrate that the RF-CNN with feature optimization provides the best identification of at-risk cognitive competency (accuracy increases 6.7%). Overall, the results of this paper provide key technical support for the development of an adaptive evaluation system of pilots' cognitive competency based on intelligent technology, and lay the foundation and framework for monitoring the cognitive process and competency of ship piloting operation in China., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Jiang, Chen, Ren and Zhu.)

The study of tumor microenvironment plays an important role in the treatment of cancer patients. In this paper, intelligent medical Internet of Things technology was used to analyze cancer tumor microenvironment-related genes. Through experiments designed and analyzed cancer-related genes, this study concluded that in cervical cancer, patients with high expression of P16 gene had a shorter life cycle and a survival rate of 35%. In addition, through investigation and interview, it was found that patients with positive expression of P16 and Twist genes had a higher recurrence rate than patients with negative expression of both genes; high expression of FDFT1, AKR1C1, and ALOX12 in colon cancer is associated with short survival; high expressions of HMGCR and CARS1 is associated with longer survival; overexpression of NDUFA12, FD6, VEZT, GDF3, PDE5A, GALNTL6, OPMR1, and AOAH in thyroid cancer is associated with shortened survival; high expressions of NR2C1, FN1, IPCEF1, and ELMO1 is associated with prolonged survival. Among the genes associated with the prognosis of liver cancer, the genes associated with shorter survival period are AGO2, DCPS, IFIT5, LARP1, NCBP2, NUDT10, and NUDT16; the genes associated with longevity are EIF4E3, EIF4G3, METTL1, NCBP1, NSUN2, NUDT11, NUDT4, and WDR4. Depending on the prognostic role of genes in different cancers, they can influence patients to achieve the effect of reducing patients' symptoms. In the process of disease analysis of cancer patients, this paper uses bioinformation technology and Internet of things technology to promote the development of medical intelligence., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Ren, Cao, Ma, Li, Xia and Zhao.)

It has been shown that the detection performance can be improved by exploiting the covariance matrix of the channel vector in the distributed MIMO radar. In this paper, we firstly introduce a system model in which the target is modeled as the sum of a finite number of independent scatterers without limitation on transmitter-receiver configurations. Using this system model, we make a detailed analysis of the covariance matrix under various target RCS models. The formula to calculate the elements of covariance matrix for the MIMO radar with arbitrary transmitter-target-receiver collocations is derived. We also propose an approach to evaluate correlations between channels based on the local maximum potential detection and the received signals. This approach makes it possible to predict the detection performance for the actual distributed MIMO radar. The theoretical probability of detection for this approach is developed and validated by simulation. [ABSTRACT FROM AUTHOR]

Respiratory monitoring is a significant issue to reduce patient risks and medical staff labor in postoperative care and epidemic infection, particularly after the COVID-19 pandemic. Oximetry is widely used for respiration monitoring in the clinic, but it sometimes fails to capture a low-functional respiratory condition even though a patient has breathing difficulty. Another approach is breathing-sound monitoring, but this is unstable due to the indirect measurement of lung volume. Kobayashi in our team is developing a sensor measuring temporal changes in lung volume with a displacement sensor attached across the sixth and eighth ribs. For processing these respiratory signals, we propose the combination of complex-valued wavelet transform and the correlation among spectrum sequences. We present the processing results and discuss its feasibility to detect a low-functional condition in respiration. The result for detecting low-functional respiration showed good performance with a sensitivity of 0.88 and specificity of 0.88 to 1 in its receiver operating characteristic (ROC) curve. [ABSTRACT FROM AUTHOR]