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The present study aimed to compare the ability of the GLIM criteria, PG-SGA and mPG-SGA to diagnose malnutrition and predict survival among Chinese lung cancer (LC) patients. This was a secondary analysis of a multicenter, prospective, nationwide cohort study, 6697 LC inpatients were enrolled between July 2013 and June 2020. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), area under the curve (AUC), and quadratic weighted Kappa coefficients were calculated to compare the ability to diagnose malnutrition. There were 754 patients who underwent follow-up for a median duration of 4.5 years. The associations between the nutritional status and survival were analyzed by the Kaplan-Meier method and multivariable Cox proportional hazard regression models. The median age of LC patients was 60 (53, 66), and 4456 (66.5%) were male. There were 617 (9.2%), 752 (11.2%), 1866 (27.9%), and 3462 (51.7%) patients with clinical stage Ⅰ, Ⅱ, Ⅲ, and Ⅳ LC, respectively. Malnutrition was present in 36.1%–54.2% (as evaluated using different tools). Compared with the PG-SGA (used as the diagnostic reference), the sensitivity of the mPG-SGA and GLIM was 93.7% and 48.3%; the specificity was 99.8% and 78.4%; and the AUC was 0.989 and 0.633 (P < 0.001). The weighted Kappa coefficients were 0.41 for the PG-SGA vs. GLIM, 0.44 for the mPG-SGA vs. GLIM, and 0.94 for the mPG-SGA vs PG-SGA in patients with stage Ⅰ-Ⅱ LC. These values were respectively 0.38, 0.39, and 0.93 in patients with stage Ⅲ-Ⅳ of LC. In a multivariable Cox analysis, the mPG-SGA (HR = 1.661, 95%CI = 1.348–2.046, P < 0.001), PG-SGA (HR = 1.701, 95%CI = 1.379–2.097, P < 0.001) and GLIM (HR = 1.657, 95%CI = 1.347–2.038, P < 0.001) showed similar death hazard ratios. The mPG-SGA provides nearly equivalent power to predict the survival of LC patients as the PG-SGA and the GLIM, indicating that all three tools are applicable for LC patients. The mPG-SGA has the potential to be an alternative replacement for quick nutritional assessment among LC patients. [ABSTRACT FROM AUTHOR]

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Adaptive help-seeking as a learning strategy can influence learners' learning outcomes. Learners in online learning environments need more self-regulation and especially more help-seeking strategies. A systematic review was conducted to explore help-seeking strategies in online learning environments. A search on help-seeking strategies in online environments in Educational Research Information Center (ERIC) and PsycInfo yielded 36 peer-reviewed articles that met the inclusion criteria for this study. Karabenick and Knapp's categories of help-seeking (formal help-seeking, informal help-seeking, instrumental activities, lowering performance aspirations, and altering goals) were used to review the strategies employed by students in online learning. The results show that there is an extreme lack of research on learners' psychological decision-making process when they lower performance aspirations or alter their goals. Moreover, most studies focus on the learners' formal and informal help-seeking behaviors in online settings. Since much research has been limited to small case studies that are not always generalizable, future studies are encouraged to include more instructional contexts and personal variables like gender, age, educational background, and mastery of computer skills. To avoid biases that may occur in self-reporting studies, recommendations are made for future studies that use more subjective methods to trace their actual help-seeking behaviors. [ABSTRACT FROM AUTHOR]

Copyright of Revista Brasileira de Medicina do Esporte is the property of Redprint Editora Ltda. 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.)

With the continuous development of China's sustainable economy, the cultural tourism industry, as the tertiary industry, has developed rapidly and become the most important high growth field of economic development. At present, industrial clusters are obvious. The rapid development of industrial clusters will inevitably brings about the unreasonable exploitation of resources and the destruction of ecological environment. How to reasonably evaluate the green and high-quality development of cultural tourism integration industrial cluster has become the focus of attention. In view of the above problems, in this paper, the theoretical basis of cultural tourism integration and the classification of industrial clusters are systemically analyzed. Moreover, the development degree of cultural tourism integration industrial clusters through location entropy is proposed, and the evaluation of green development of cultural tourism integration industrial clusters is conducted. Based on the evaluation of the development levels of tourism industry, green tourism resources and ecological environment governance, the comprehensive evaluation method is used to evaluate the green development level. Furthermore, taking the A City in the northern China as an example, the development mode of the cultural tourism integrated industrial cluster is analyzed, and the changes of tourism income and annual GDP of the A City from 2009 to 2019 are calculated. The results show that the location entropy of the cultural tourism integrated industrial cluster of the A City increases from 1.1 in 2009 to 9.12 in 2019, showing an increasing trend year by year. Using the comprehensive evaluation method, it can be found that the evaluation scores of the tourism industry development, green tourism resource and ecological environment governance levels show an increasing trend year by year, and the comprehensive scores have increased from 5.33 in 2009 to 86.42 in 2019. It fully shows that the green development of the industrial clusters in the A city shows a good development trend and can promotes the sustainable development of urban economy well. [ABSTRACT FROM AUTHOR]

Causal inference regarding a hypothesized mediation mechanism relies on the assumptions that there are no omitted pretreatment confounders (i.e., confounders preceding the treatment) of the treatment-mediator, treatment-outcome, and mediator-outcome relationships, and there are no posttreatment confounders (i.e., confounders affected by the treatment) of the mediator-outcome relationship. It is crucial to conduct a sensitivity analysis to determine if a potential violation of the assumptions would easily change analytic conclusions. This article proposes a simulation-based method to assess the sensitivity to unmeasured pretreatment confounding, assuming no posttreatment confounding. It allows one to (a) quantify the strength of an unmeasured pretreatment confounder through its conditional associations with the treatment, mediator, and outcome; (b) simulate the confounder from its conditional distribution; and (c) finally assess its influence on both the point estimation and estimation efficiency by comparing the results before and after adjusting for the simulated confounder in the analysis. The proposed sensitivity analysis strategy can be implemented for any causal mediation analysis method. It is applicable to both randomized experiments and observational studies and to mediators and outcomes of different scales. A visualization tool is provided for vivid representations of the sensitivity analysis results. An R package mediationsens has been developed for researchers to implement the proposed method easily (https://cran.r-project.org/web/packages/mediationsens/index.html). [ABSTRACT FROM AUTHOR]

Although many studies have been recently performed on fertility-sparing treatments in patients with endometrial cancer (EC) and endometrial atypical hyperplasia (EAH), most of the corresponding studies were retrospective and small sample research. However, it is essential to more thoroughly assess the necessity of hysterectomy in EC patients using current accumulated experience. With the development of machine learning (ML), it has been gradually integrated into oncologic research but seldom applied to predict the efficacy of hysterectomy due to an insufficient number of patients who did not undergo hysterectomy, leading to a learning imbalance. Thus, the commonly used machine learning models cannot provide satisfying performance. In this study, we aimed to develop ML models to predict whether hysterectomy is necessary for EC patients and help gynecologists determine the possibility of fertility-preserving treatment in EC patients. A clinical dataset of 1534 women with EC was analyzed. The Borderline-SMOTE algorithm was employed to solve imbalanced learning issues. Then, the Adaptive Boosting (AdaBoost) algorithm, which is less susceptible to overfitting than other machine learning algorithms, was used to build a high-performance ensemble classification model. The findings indicated that the method outperformed conventional machine learning models and provided a realistic strategy to make fertility-preserving treatment decisions. The proposed model provides a platform for physicians to precisely predict the efficacy of fertility-sparing therapy in EC patients, allows gynecologists to select the optimal treatment for a patient, and reduces resource waste and risks of overtreatment. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the effect of the salinity of saline-sodic soils on the structural characteristics of humic acid (HA) in soil aggregates of various grain sizes. Saline-sodic soils in the Songnen Plain with light, moderate and high salinity, referred to as Light Saline(LS), Middle Saline(MS), and Heavy Saline(HS) soils, respectively, were collected and fractionated into > 2 mm, 2-0.25 mm, 0.250.053 mm and < 0.053 mm grain-size fractions by wet sieving. HA was extracted and qualitatively characterized by a variety of means, including infrared (IR) spectra, fluorescence spectra and thermodynamic properties. The results showed that (1) the content of the water-stable aggregate of < 0.25 mm grain size (micro-aggregate) was greater than 75% in each soil sample, regardless of soil salinity; (2) total organic carbon (TOC) content was higher in the < 0.053 mm grain-size fraction than in any other grainsize fraction; (3) the ratio of the summed intensities of HA IR peaks at 2920 cm-1 and 2850 cm-1 to the intensity of the HA peak at 1720 cm-1 and at 1620 cm-1, which were respectively referred to as (2920+2850)/1720 and (2920+2850)/1620 for simplicity, decreased in the order of Light Saline(LS) > Middle Saline(MS) > Heavy Saline(HS); (4) the intensity of fluorescence peaks D, C and A decreased in the order of LS > MS > HS, and peak D was the highest of the three HA peaks for each grain-size fraction of LS soils; (5) the high-temperature to moderate-temperature heat loss ratio of HA extracted from different saline-sodic soils decreased in the order of HS > MS > LS; and (6) for soil micro-aggregates (< 0.25 mm), the high-temperature to moderate- temperature heat release ratio, the high-temperature heat release, the high-temperature weight loss, and the high-temperature to moderate-temperature weight loss ratio all decreased in the order of HS > MS > LS. The findings provide basic data for the improvement and utilization of saline-sodic soils in the Songnen Plain. [ABSTRACT FROM AUTHOR]

This paper investigates the risk assessment method of electrical fires of high-rise buildings based on hybrid decision models considering asymmetric proximity. Based on the occurrence mechanism of electrical fires in high-rise buildings, a four-level evaluation index system considering the disaster causing body, fire site environment, affected body, and fire driving factors is established based on FP growth mining association rules, and the risk grade is divided further. An improved DEMATEL+ANP index weight assignment method for balancing the interaction relationship between indexes is proposed, and a hybrid decision model for electrical fire risk assessment in high-rise buildings, taking further account of asymmetric proximity and improved evidence cloud theory. Combined with specific examples, the effectiveness of the proposed building electrical fire risk assessment method is verified. This method can better balance each risk evaluation index, fully considering the fuzziness and randomness in the electrical fire risk assessment of high-rise buildings, and improve the accuracy and applicability of electrical fire risk assessment. [ABSTRACT FROM AUTHOR]

In order to explore the response mechanism of photosynthesis in castor leaves to greenhouse effect, a pot experiment was conducted to analyze the effects of increasing temperature (28°C) and CO2 concentration (550 ppm) on the photosynthetic parameters and photosynthetic pigments contents of castor, a famous oil seed crop over the world. The results showed that in the short term stress, it was not conducive to plant growth and development that only warming inhibited photosynthesis and transpiration of castor leaves. The increasing concentration of CO2 could promote the photosynthesis of castor leaves, which increased its photosynthetic rate and transpiration, and was beneficial to accelerate the growth rate of castor. The interactive effects of increasing temperature and CO2 concentration not only promoted photosynthesis and transpiration of castor, but also increased the content of pigments that used to absorb and transfer light energy, synthesized more organic matter and improved castor quality. However, the interactions had no significant effects on the growth of this species. This study has important theoretical significance for in-depth understanding of castor's response to global change, and for its further use. [ABSTRACT FROM AUTHOR]

The electrical fire risk of high-rise buildings remains high, which has threatened people's lives and property safety for a long time. Therefore, accurately evaluating the electrical fire risk and identifying the risk factors is vital for formulating proper electrical fire prevention measures. This paper proposes a two-level assessment method of electrical fire risk of high-rise buildings based on interval TOPSIS method. Firstly, the electrical fire data and expert evaluation opinions are queried, and the improved Delphi method is used to obtain the two-level index framework of electrical fire risk assessment. Then, the interval analytic hierarchy process is used to determine the weight coefficient of electrical fire risk index of high-rise buildings. Finally, the risk index factors are sorted in combination with interval TOPSIS method. After verification, it is found that the sequence of electrical fire risk factors of high-rise buildings is the chain reaction of inflammables and explosives (accounting for 27.9%), the fire caused by electrical lines (accounting for 22.07%), and the fire caused by electrical equipment (accounting for 20.89%), where the overload risk factor accounts for the largest proportion in the sub-indicators. [ABSTRACT FROM AUTHOR]

Postearthquake building damage assessment requires professional judgment; however, there are factors such as high workload and human error. Making use of Terrestrial Laser Scanning data, this paper presents a method for seismic damage information extraction. This new method is based on principal component analysis calculating the local surface curvature of each point in the point cloud. Then use the nearest point angle algorithm, combined with the data features of the actual measured value to identify point cloud seismic information, and filter the points that tend to the plane by setting the threshold value. Based on the statistical analysis of the normal vector, the raw point cloud data are deplanarized to obtain the preliminary results of seismic damage information. The density clustering algorithm is used to denoise the initially extracted seismic damage information. Ultimately, we can obtain the distribution patterns and characteristics of cracks in the walls of the building. The extraction result of the seismic damage information point cloud data is compared with the photos collected at the site, showing that the algorithm steps successfully identify the crack and shed wall skin information recorded in the site photos (identification rate: 95%). Point cloud distribution maps of cracked and shed siding areas determine quantitative information on seismic damage, providing a higher level of performance and detail than direct contact measurements. [ABSTRACT FROM AUTHOR]

The rate of recurrence and metastasis of non-small cell lung cancer after radical resection is still very high. The risk factors for recurrence and metastasis have been extensively studied, but the dynamic pattern of postoperative recurrence hazard over time is relatively lacking. The dynamic recurrence hazard rate curve is applied to describe the rate of recurrence at any point time among the "at-risk" patients. In this article, by reviewing the previous literature, the characteristics of the dynamic recurrence and metastasis pattern after radical resection of non-small cell lung cancer and the clinical factors affecting the recurrence and metastasis pattern are summarized, in order to screen out specific populations with high recurrence risk and give them personalized follow-up strategy and diagnosis and treatment. [ABSTRACT FROM AUTHOR]

The optimal thresholds to define a survival-related low fat mass index (FMI) in Asian oncology populations remains largely unknown. This study sought to derive the sex-specific FMI cutoffs and analyze the independent and joint associations of a low FMI, handgrip weakness, and the Global Leadership Initiative on Malnutrition (GLIM)-defined malnutrition with cancer survival. We performed a multicenter cohort study including 2376 patients with cancer. The FMI was measured by bioelectrical impedance analysis and the best thresholds were determined using an optimal stratification (OS) method. Low handgrip strength (HGS) and malnutrition were defined based on the Asian Working Group for Sarcopenia 2019 framework and the GLIM, respectively. The associations of a low FMI, handgrip weakness and malnutrition with survival were estimated independently and jointly by calculating multivariable-adjusted hazard ratios (HRs). The study enrolled 1303 women and 1073 men with a mean age of 57.7 years and a median follow-up of 1267 days. The OS-defined FMI cutoffs were <5 kg/m2 in women and <7.7 kg/m2 in men. A low FMI, low HGS and malnutrition were identified in 1188 (50%), 1106 (46.5%) and 910 (38.3%) patients, respectively. A low FMI was adversely associated with the nutritional status, physical performance, quality of life and hospitalization costs. A low FMI (HR = 1.50, 95%CI = 1.16 to 1.92) and malnutrition (HR = 1.31, 95%CI = 1.08 to 1.59) were independently associated with mortality. Overall, the FMI plus GLIM-defined malnutrition showed the maximal joint prognostic impact, and patients with a combined low FMI and malnutrition had the worst survival (HR = 1.93, 95%CI = 1.48 to 2.52). Low FMI-indicated fat depletion outperforms and strengthens the prognostic value of handgrip weakness and GLIM-defined malnutrition for cancer survival. These findings indicate the importance of including fat mass assessment during routine cancer care to help guide strategies to optimize survival outcomes. [ABSTRACT FROM AUTHOR]