The complex compositions and large shrinkage of concrete, as well as the strong constraints of the structures, often lead to prominent shrinkage cracking problems in modern concrete structures. This paper first introduces a multi-field (hydro–thermo–hygro–constraint) coupling model with the hydration degree of cementitious materials as the basic state parameter to estimate the shrinkage cracking risk of hardening concrete under coupling effects. Second, three new key technologies are illustrated: temperature rise inhibition, full-stage shrinkage compensation, and shrinkage reduction technologies. These technologies can efficiently reduce the thermal, autogenous, and drying shrinkages of concrete. Thereafter, a design process based on the theoretical model and key technologies is proposed to control the cracking risk index below the threshold value. Finally, two engineering application examples are provided that demonstrate that concrete shrinkage cracking can be significantly mitigated by adopting the proposed methods and technologies.
Irritable bowel syndrome with diarrhea (IBS-D) is chronic intestinal dysfunction with diarrhea and other complicated clinical symptoms, and it has a great impact on the daily life and mental state of patients. Some studies have reported that ingestion of probiotics can significantly alleviate a variety of intestinal diseases. The purpose of this study was to investigate the IBS-D-alleviating effects of a probiotic strain, Lactobacillus plantarum CCFM8610, with multiple health-promoting effects. The study was a 12-week, randomized, double-blind, placebo-controlled, pilot clinical trial. Seventy-five patients were randomly assigned to receive the placebo, oligosaccharides, or L. plantarum CCFM8610 (1 × 1010 colony-forming units (CFU) per day), with a 2-week run-in period, an 8-week intervention period, and a 2-week follow-up observation period. The patients' clinical symptoms and quality of life were examined by the IBS symptom severity scale (IBS-SSS) and the IBS quality of life scale (IBS-QOL). Changes in gut microbiota composition and diversity were measured at the end of the intervention period. The oral administration of L. plantarum CCFM8610 significantly decreased the IBS-SSS and IBS-QOL scores, reduced IBS-D symptom severity, recovered gut microbiota diversity, decreased the relative abundance of bloating-related genus Methanobrevibacter, and increased the relative abundance of butyric acid-producing genera, including Anaerostipes, Anaerotruncus, Bifidobacterium, Butyricimonas, and Odoribacter. These findings suggest that ingestion of L. plantarum CCFM8610 can significantly alleviate clinical symptoms and gut microbiota dysbiosis in IBS-D patients. The IBS-D-alleviating effect of L. plantarum CCFM8610 may be related to the increase in the relative abundance of butyric acid-producing genera in the intestine.
The problem of effluent total nitrogen (TN) at most of the wastewater treatment plants (WWTPs) in China is important for meeting the related water quality standards, even under the condition of high energy consumption. To achieve better prediction and control of effluent TN concentration, an efficient prediction model, based on controllable operation parameters, was constructed in a sequencing batch reactor process. Compared with previous models, this model has two main characteristics: ① Superficial gas velocity and anoxic time are controllable operation parameters and are selected as the main input parameters instead of dissolved oxygen to improve the model controllability, and ② the model prediction accuracy is improved on the basis of a feedforward neural network (FFNN) with algorithm optimization. The results demonstrated that the FFNN model was efficiently optimized by scaled conjugate gradient, and the performance was excellent compared with other models in terms of the correlation coefficient (R). The optimized FFNN model could provide an accurate prediction of effluent TN based on influent water parameters and key control parameters. This study revealed the possible application of the optimized FFNN model for the efficient removal of pollutants and lower energy consumption at most of the WWTPs.