RESUMEN
Defect inspection of existing buildings is receiving increasing attention for digitalization transfer in the construction industry. The development of drone technology and artificial intelligence has provided powerful tools for defect inspection of buildings. However, integrating defect inspection information detected from UAV images into semantically rich building information modeling (BIM) is still challenging work due to the low defect detection accuracy and the coordinate difference between UAV images and BIM models. In this paper, a deep learning-based method coupled with transfer learning is used to detect defects accurately; and a texture mapping-based defect parameter extraction method is proposed to achieve the mapping from the image U-V coordinate system to the BIM project coordinate system. The defects are projected onto the surface of the BIM model to enrich a surface defect-extended BIM (SDE-BIM). The proposed method was validated in a defect information modeling experiment involving the No. 36 teaching building of Nantong University. The results demonstrate that the methods are widely applicable to various building inspection tasks.
RESUMEN
Schizophrenia is a chronic mental disorder primarily treated with antipsychotics, which have limited efficacy for negative symptoms. This study aims to evaluate the effectiveness and feasibility of exercise interventions as adjuncts to pharmacotherapy through a meta-analysis, providing valuable insights for rational intervention design. Four databases were searched, and randomized controlled trials with no language restrictions published up to March 27, 2023, were included. The primary outcome indicator was the Positive and Negative Symptom Scale (PANSS) total score along with its three sub-scales. Secondary outcomes included the Scale for Assessment of Negative Symptoms (SANS) and Body Mass Index (BMI), which were used to assess the efficacy of aerobic exercise interventions in patients with schizophrenia. Subgroup analyses were conducted to explore the impact of intervention duration and total weekly exercise time, while treatment feasibility was assessed through adherence rates. A total of 17 publications involving 973 patients with schizophrenia were deemed eligible and included in the analysis. Compared to other forms of adjunctive interventions, the network meta-analysis of 12 PANSS-based studies revealed that adjunctive aerobic exercise interventions were the most effective in reducing overall PANSS scores in patients with schizophrenia, with statistically significant pooled results (MD = -4.84, 95% CI: -5.72, -3.96). Both the PANSS negative symptom subscale (MD = -2.11, 95% CI: -3.26, -0.95) and SANS (MD = -9.11, 95% CI: -11.94, -6.27) indicated that adjunctive aerobic exercise interventions effectively alleviate negative symptoms. Subgroup meta-analysis indicated that 2-3 month interventions involving 100-220 min of exercise per week were the most effective. Additionally, adherence to the adjunctive aerobic exercise regimen was found to be comparable to that of conventional treatment alone. Aerobic exercise interventions, as adjunctive therapy, are an effective measure for reducing PANSS scores in patients with schizophrenia, contributing to the alleviation of both the positive and negative symptoms, and patients demonstrated strong adherence to aerobic exercise.
RESUMEN
The wavelet-domain Hidden Markov Tree Model can properly describe the dependence and correlation of fundus angiographic images' wavelet coefficients among scales. Based on the construction of the fundus angiographic images Hidden Markov Tree Models and Gaussian Mixture Models, this paper applied expectation-maximum algorithm to estimate the wavelet coefficients of original fundus angiographic images and the Bayesian estimation to achieve the goal of fundus angiographic images denoising. As is shown in the experimental result, compared with the other algorithms as mean filter and median filter, this method effectively improved the peak signal to noise ratio of fundus angiographic images after denoising and preserved the details of vascular edge in fundus angiographic images.
RESUMEN
OBJECTIVE: To observe the effect of Gengnianchun Recipe (GNC) on bone mineral density (BMD), bone biomechanical parameters and serum lipid level in the bilaterally ovariectomized (OVX) rats and to explore the prophylactic and therapeutic action of GNC on ovariectomy induced osteoporosis and hyperlipidemia. METHODS: OVX SD rats, 10 - 12 months old, were divided into different groups and fed with GNC 2 g/d, GNC 1 g/d and Nilestriol 0.125 mg/week, respectively for 4 months to observe the change of BMD and bone biomechanical parameters of the lumbar vertebrae, and the serum levels of total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C), and to compare the effect of the two drugs on the morphology of the uterus. RESULTS: There was marked reduction in BMD and biomechanical parameters in lumbar vertebrae (P < 0.01) and increase of serum TC and LDL-C levels (P < 0.01) in rats after OVX. GNC or Nilestriol significantly improved the decreased BMD and biomechanical parameters of the lumbar vertebrae (P < 0.05 or P < 0.01), and reduced the serum TC and LDL-C levels (P < 0.01). In the Nilestriol group, the wet weight of uterus got increased obviously (P < 0.01), the number of uterine glands increased, uterine columnar epithelium thickened, and the mitotic figures in the epithelial stroma and myointimal cells augmented. But no such effect in wet weight and morphology of uterus was found in the GNC group. CONCLUSION: GNC could increase the BMD and biomechanical parameters of the lumbar vertebrae, reduce the serum TC and LDL-C levels, yet produce no adverse reaction in stimulating proliferation and hypertrophy of uterus.