An Ensemble Multilabel Classification for Disease Risk Prediction

It is important to identify and prevent disease risk as early as possible through regular physical examinations. We formulate the disease risk prediction into a multilabel classification problem. A novel Ensemble Label Power-set Pruned datasets Joint Decomposition (ELPPJD) method is proposed in this work. First, we transform the multilabel classification into a multiclass classification. Then, we propose the pruned datasets and joint decomposition methods to deal with the imbalance learning problem. Two strategies size balanced (SB) and label similarity (LS) are designed to decompose the training dataset. In the experiments, the dataset is from the real physical examination records. We contrast the performance of the ELPPJD method with two different decomposition strategies. Moreover, the comparison between ELPPJD and the classic multilabel classification methods RAkEL and HOMER is carried out. The experimental results show that the ELPPJD method with label similarity strategy has outstanding performance

A Novel Deep Neural Network Model for Multi-Label Chronic Disease Prediction

Chronic diseases are one of the biggest threats to human life. It is clinically significant to predict the chronic disease prior to diagnosis time and take effective therapy as early as possible. In this work, we use problem transform methods to convert the chronic diseases prediction into a multi-label classification problem and propose a novel convolutional neural network (CNN) architecture named GroupNet to solve the multi-label chronic disease classification problem. Binary Relevance (BR) and Label Powerset (LP) methods are adopted to transform multiple chronic disease labels. We present the correlated loss as the loss function used in the GroupNet, which integrates the correlation coefficient between different diseases. The experiments are conducted on the physical examination datasets collected from a local medical center. In the experiments, we compare GroupNet with other methods and models. GroupNet outperforms others and achieves the best accuracy of 81.13%

Existence and Iteration of Positive Solutions for Multipoint Boundary Value Problems Dependence on the First Order Derivative with One-Dimensional p-Laplacian

Abstract In this paper, we study the existence of monotone positive solutions for the following nonlinear m-point singular boundary value problem with p-Laplacian operator. The main tool is the monotone iterative technique. We obtain not only the existence of positive solutions for the problem, but also establish iterative schemes for approximating solution. Mathematics Subject Classification: 34B1

Effect of regenerator on the direct steam generation solar power system characterized by prolonged thermal storage and stable power conversion

The direct steam generation (DSG) solar power system using two stage accumulators and cascade steam-organic Rankine cycle (RC-ORC) has remarkably enlarged storage capacity. It can facilitate stable power generation and address the challenges of conventional DSG systems. Regenerator is generally an issue worthy of discussion in organic Rankine cycle (ORC) systems. However, its influence on the newly proposed DSG system has not been investigated yet and is expected to be appreciable. Introducing a regenerator affects not only the ORC efficiency, RC-ORC efficiency, heat exchanger area, but also heat storage capacity, discharge duration, discharge efficiency, aperture area of collectors and the net profit (ΔP). Detailed performance comparison between the DSG systems without/with regenerator is carried out in this paper. The results indicate that at a given power output, aperture area is reduced by the regenerator especially for MM, R365mfc and pentane due to the increment in ORC, RC-ORC and discharge efficiencies, as well as the decrement in heat input. Discharge duration is shortened by 0.01–1.78 h depending on ORC fluids. R365mfc exhibits the maximum ΔP (4.19∼6.48 million USD), followed by MM and pentane. On the contrary, ΔP is negative for benzene (−5.61∼-4.31 million USD)

What influenced the lesion patterns and hemodynamic characteristics in patients with internal carotid artery stenosis? A retrospective study

•Blood perfusion influences ischemic lesions in patients with of ICAS.•Communicating arteries influence intracranial blood flow.•TCD was a convenient and rapid tool to assess cerebral blood flow

Effects of nitrogen addition and plant litter manipulation on soil fungal and bacterial communities in a semiarid sandy land

The plant and soil microbial communities are influenced by variability in environmental conditions (e.g., nitrogen addition); however, it is unclear how long-term nitrogen addition and litter manipulation affect soil microbial communities in a semiarid sandy grassland. Therefore, we simulated the impact of N addition and litter manipulation (litter removal, litter doubling) on plant and soil microbial communities in Horqin grassland, northern China through an experiment from 2014 to 2019. Our results revealed that in the case of non-nitrogen (N0), litter manipulation significantly reduced vegetation coverage (V) (p < 0.05); soil bacterial communities have higher alpha diversity than that of the fungi, and the beta diversity of soil fungi was higher than that of the bacteria; soil microbial alpha diversity was significantly decreased by nitrogen addition (N10) (p < 0.05); N addition and litter manipulation had significantly interactive influences on soil microbial beta diversity, and litter manipulation (C0 and C2) had significantly decreased soil microbial beta diversity (p < 0.05) in the case of nitrogen addition (N10) (p < 0.05). Moreover, bacteria were mostly dominated by the universal phyla Proteobacteria, Actinobacteria, and Acidobacteria, and fungi were only dominated by Ascomycota. Furthermore, the correlation analysis, redundancy analysis (RDA), and variation partitioning analysis indicated that the soil fungi community was more apt to be influenced by plant community diversity. Our results provide evidence that plant and soil microbial community respond differently to the treatments of the 6-year N addition and litter manipulation in a semiarid sandy land

An Ensemble Multilabel Classification for Disease Risk Prediction

It is important to identify and prevent disease risk as early as possible through regular physical examinations. We formulate the disease risk prediction into a multilabel classification problem. A novel Ensemble Label Power-set Pruned datasets Joint Decomposition (ELPPJD) method is proposed in this work. First, we transform the multilabel classification into a multiclass classification. Then, we propose the pruned datasets and joint decomposition methods to deal with the imbalance learning problem. Two strategies size balanced (SB) and label similarity (LS) are designed to decompose the training dataset. In the experiments, the dataset is from the real physical examination records. We contrast the performance of the ELPPJD method with two different decomposition strategies. Moreover, the comparison between ELPPJD and the classic multilabel classification methods RAkEL and HOMER is carried out. The experimental results show that the ELPPJD method with label similarity strategy has outstanding performance

miR-17-5p and miR-106a are involved in the balance between osteogenic and adipogenic differentiation of adipose-derived mesenchymal stem cells

AbstractMesenchymal stem cells (MSCs) can differentiate into several distinct cell types, including osteoblasts and adipocytes. The balance between osteogenic and adipogenic differentiation is disrupted in several osteogenic-related disorders, such as osteoporosis. So far, little is known about the molecular mechanisms that drive final lineage commitment of MSCs. In this study, we revealed that miR-17-5p and miR-106a have dual functions in the modulation of human adipose-derived mesenchymal stem cells (hADSCs) commitment by gain- and loss-of-function assays. They could promote adipogenesis and inhibit osteogenesis. Luciferase reporter assay, western blot and ELISA suggested BMP2 was a direct target of miR-17-5p and miR-106a. Downregulation of endogeneous BMP2 by RNA interference suppressed osteogenesis and increased adipogenesis, similar to the effect of miR-17-5p and miR-106a upregulation. Moreover, the inhibitory effects of miR-17-5p on osteogenic and adipogenic differentiation of hADSCs could be reversed by BMP2 RNA interference. In conclusion, miR-17-5p and miR-106a regulate osteogenic and adipogenic lineage commitment of hADSCs by directly targeting BMP2, and subsequently decreased osteogenic TAZ, MSX2 and Runx2, and increased adipogenic C/EBPα and PPARγ

Research status and development trend of compressed air energy storage in abandoned coal mines

Compressed air energy storage (CAES) has the advantages of low construction cost, small equipment footprint, long storage cycle and environmental protection. Exploring the development of CAES technology in underground space is one of the innovative approaches to achieve China’s “dual-carbon” goal. Underground energy storage reservoirs can be classified into salt caverns, aquifers, depleted oil and gas fields, abandoned coal mines, and caverns. With the increasing number of abandoned coal mines in China, the direct closure of resource-depleted coal mines not only cause a significant waste of underground space resources, but also induce a series of safety, environmental and other issues. Therefore, utilizing the underground space of abandoned coal mines as CAES reservoirs holds great application prospects. The analysis shows that, ① There is a large amount of usable space in abandoned coal mines, and eight reuse modes of underground space in abandoned coal mines have been summarized: agricultural and forestry land, construction land, site greening, watershed utilization, water-heat combination, wetland park, mine park, and space reuse. ② The research on CAES in abandoned coal mines in China started late, the basic theoretical research is weak, the key technologies is immature, and geological conditions in coal mines are complex, the relevant applications of basic research is insufficient, and the commercialization, large-scale promotion and application have not yet been achieved. ③ Three key technologies are summarized and proposed to cope with the CAES in abandoned coal mines, i.e., the evaluation method of site selection for the construction of abandoned coal mine energy storage reservoirs, the key technology for the sealing of abandoned coal mine energy storage reservoirs, and the stability and safety evaluation of abandoned coal mine energy storage reservoirs. A flowchart for siting the construction of CAES reservoirs in abandoned coal mines has been established

Contamination and mobile colistin resistance gene analysis for Salmonella isolated from retail chickens in Ji'nan

ObjectiveTo investigate the contamination of Salmonella in retail chickens in Ji’nan city from 2020 to 2021， and to explore the prevalence of the mobile colistin resistance gene （mcr） among these Salmonella isolates.MethodsFrom December 2020 to November 2021， 260 retail chicken samples were collected in Ji’nan City， and Salmonella was isolated and confirmed according to GB 4789.4—2016 “National food standard - Food microbiological examination： Salmonella”. Serotype identification and mcr gene screening were performed for all Salmonella isolates by polymerase chain reaction （PCR）. The drug resistance of mcr gene-positive strains was tested by micro-broth dilution method.ResultsA total of 61 in 260 retail chicken samples were positive for Salmonella detection with the contamination rate of 23.46% （61/260）. The highest contamination rate was 53.33% （32/60） for samples collected in autumn. One hundred and three Salmonella strains were isolated， 56 of which were Salmonella Enteritidis， accounting for 54.37% （56/103）. Two Salmonella Indiana， isolated from two separate chicken wing samples collected from different regions， were positive for mcr-1 gene， with a positive rate of 1.94% （2/103）. Antimicrobial susceptibility testing revealed that both of the two mcr-1-harboring Salmonella Indiana were multi-drug resistant， and one of them was concurrently resistant to all 12 categories of tested drugs， including carbapenems and polymyxins.ConclusionThere was a certain degree of Salmonella contamination in retail chickens in Jinan from 2020 to 2021， and the contamination rate of the samples collected in autumn was higher than in any other seasons. Salmonella Enteritidis was the predominant serotype. It should be of concern that a Salmonella isolate carried mcr-1 gene with severe multidrug resistance to both colistin and carbapenems， indicating that the surveillance for Salmonella in the whole chain of chicken production should be strengthened continuously， to provide important basic data for the prevention and control of foodborne diseases