This paper develops a distributed dictionary learning algorithm for sparse representation of the data distributed across nodes of sensor networks, where the sensitive or private data are stored or ...there is no fusion center or there exists a big data application. The main contributions of this paper are: 1) we decouple the combined dictionary atom update and nonzero coefficient revision procedure into two-stage operations to facilitate distributed computations, first updating the dictionary atom in terms of the eigenvalue decomposition of the sum of the residual (correlation) matrices across the nodes then implementing a local projection operation to obtain the related representation coefficients for each node; 2) we cast the aforementioned atom update problem as a set of decentralized optimization subproblems with consensus constraints. Then, we simplify the multiplier update for the symmetry undirected graphs in sensor networks and minimize the separable subproblems to attain the consistent estimates iteratively; and 3) dictionary atoms are typically constrained to be of unit norm in order to avoid the scaling ambiguity. We efficiently solve the resultant hidden convex subproblems by determining the optimal Lagrange multiplier. Some experiments are given to show that the proposed algorithm is an alternative distributed dictionary learning approach, and is suitable for the sensor network environment.
Objective To explore the association between circadian syndrome (CircS) and Metabolic Syndrome (MetS) with psoriasis. Compare the performance of MetS and CircS in predicting psoriasis. Methods An ...observational study used data from the NHANES surveys conducted in 2005–2006 and 2009–2014. We constructed three multiple logistic regression models to investigate the relationship between MetS, CircS, and their components with psoriasis. The performance of MetS and CircS in predicting psoriasis was compared using five machine-learning algorithms, and the best-performing model was explained via SHAP. Then, bidirectional Mendelian randomization analyses with the inverse variance weighted (IVW) as the primary method were employed to determine the causal effects of each component. Result A total of 9,531 participants were eligible for the study. Both the MetS (OR = 1.53, 95%CI: 1.07–2.17, P = 0.02) and CircS (OR = 1.40, 95%CI: 1.02–1.91, P = 0.039) positively correlated with psoriasis. Each CircS algorithmic model performs better than MetS, with Categorical Features+Gradient Boosting for CircS (the area under the precision-recall curve = 0.969) having the best prediction effect on psoriasis. Among the components of CircS, elevated blood pressure, depression symptoms, elevated waist circumference (WC), and short sleep contributed more to predicting psoriasis. Under the IVW methods, there were significant causal relationships between WC (OR = 1.52, 95%CI: 1.34−1.73, P = 1.35e-10), hypertension (OR = 1.68, 95%CI: 1.19−2.37, P = 0.003), depression symptoms (OR = 1.39, 95%CI: 1.17−1.65, P = 1.51e-4), and short sleep (OR = 2.03, 95%CI: 1.21–3.39, p = 0.007) with psoriasis risk. Conclusion CircS demonstrated superior predictive ability for prevalent psoriasis compared to MetS, with elevated blood pressure, depression symptoms, and elevated WC contributing more to the prediction.
With the acceleration of urbanization, the demand for land due to urban large-scale construction and development is increasing. Coastal reclamation (CR) is a prevailing approach to tackle the ...contradiction between coastal land shortage and the growing demand for living space for human beings. Enormous social and economic benefits are derived from CR, while at the same time bringing a series of environmental problems. Since the beginning of the 21st century, this oceanic-oriented development has become more frequent. Therefore, the considerable economic and ecological trade-offs of reclamation activities must be analyzed to enable targeted land use decisions. By comprehensively evaluating the natural conditions of the sea area, including geology, topography, hydrology, ecology, and social and economic conditions, this study established an environmental capacity assessment system (ECAS) based on water environmental capacity for assessment of the potential environmental impact resulting from CR. According to the water quality status and positions of CR in Haizhou Bay, the environmental capacities of four major pollutants were calculated to forecast the suitable area of CR. The results indicated that these reclamation projects had notable negative effects on the environmental capacity of the four major pollutants. The order of pollutants according to their harm on seawater quality is: PO4-P > NH4-N > NOX-N > COD. In three reclamation alternative scenarios, scenario 3 led to the minimum negative impacts on the environmental capacity, scenario 2 followed, and scenario 1 had the worst result. Hence, scenario 3 was the optimal reclamation scenario, under which the suitable area of CR in Haizhou Bay was found to be 83 km2. This study provides a scientific reference for the effective management of coastal reclamation and future environmental impact research when new CR is proposed, as well as sustainable urban development.
•Combined genetic algorithm and machine learning for optimization.•Proposed the advantage interval of three kinds of CTPC systems.•Proposed a novel goal-oriented design method for CPC systems.
The ...CO2 power cycle (CPC) system is an efficient and environmentally friendly method for waste heat recovery (WHR). However, the traditional design and optimization process of a CPC system is very complex and time-consuming. This paper proposes a novel goal-oriented design method based on machine-learning methods for quickly designing an optimized CPC system with given performance indicators. And taking the design of the CO2 transcritical power cycle (CTPC) system for internal combustion engines (ICEs) as an example. Firstly, the net output power and the total cost of the system prediction models are trained by simulated data. Then the multi-objective optimization of the system is carried out by using the genetic algorithm coupled with the prediction models, and the optimization results are used to train a classification model. Finally, the given target indicators are input into the classification model for goal-oriented designing and getting the optimal configuration. The results of the goal-oriented design validation show that the goal-oriented design method can design the CTPC system well. And, once the classification model is trained, the CTPC system's future goal-oriented design process only needs to be calculated once, significantly reducing design time. In conclusion, the goal-oriented design method based on machine-learning proposed is a novel and promising method. This is a technology that combines computer science and energy science and can provide users with a quick and reliable CPC system design method.
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The Fangji Dihuang formulation (FJDHF) is a widely recognized Traditional Chinese Medicine (TCM) formula that consists of five plant drugs: Stephaniae Tetrandrae Radix, Cinnamomi Ramulus, Rehmanniae ...Radix, Saposhnikoviae Radix, and Glycyrrhiza Urensis Fisch. This formulation has been known to exhibit clinical therapeutic effects in the treatment of inflammatory skin diseases. However, there is a lack of pharmacological research on its anti-atopic dermatitis (AD) activity.
To investigate the potential anti-AD activity of FJDHF, DNCB was used to induce AD-like skin inflammation in the back of mice. Following successful modeling, the mice were administered FJDHF orally. The extent of the inflammatory skin lesions was recorded at day 4, 7, 14 and 28. UHPLC-Q-Exactive Orbitrap MS was used to identify and match the compounds present in FJDHF with ITCM, TCMIP and TCMSID. In silico predictions of potential target proteins of the identified compounds were obtained from SwishTargetPrediction, ITCM and TargetNet databases. AD-related genes were identified from GSE32924 data set, and FJDHF anti-AD hub genes were identified by MCODE algorithm. ClueGo enrichment analysis was employed to identify the core pathway of FJDHF's anti-AD effect. To further investigate the anti-AD effect of FJDHF, single-cell RNA sequencing data set (GSE148196) from AD patients was analyzed to determine the target cells and signaling pathways of FJDHF in AD. Finally, rt-PCR, flow cytometry, and mouse back skin RNA sequencing were utilized to validate our findings.
FJDHF was found to be effective in improving the degree of the AD-like lesions in the mice. Network pharmacological analysis revealed the core pathway of FJDHF to be the IL-17 signaling pathway, which is interactively associated with cytokines. Single-cell RNA sequencing analysis suggested that FJDHF may play an anti-AD role by influencing dendritic cells. Flow cytometry and rt-PCR results showed that FJDHF can reduce the influence of AD sample of IL-4, IFN-γ and the expression of IL-17. The RNA sequencing of mouse back skin also confirmed our conclusion.
FJDHF may inhibit DNCB-induced AD-like skin inflammation in mice by inhibiting the IL-17 signaling pathway. Thus, FJDHF can be considered as a potential therapeutic agent for AD.
The supercritical CO2 (sCO2) power cycle could improve efficiencies for a wide range of thermal power plants. The sCO2 turbine generator plays an important role in the sCO2 power cycle by directly ...converting thermal energy into mechanical work and electric power. The operation of the generator encounters challenges, including high temperature, high pressure, high rotational speed, and other engineering problems, such as leakage. Experimental studies of sCO2 turbines are insufficient because of the significant difficulties in turbine manufacturing and system construction. Unlike most experimental investigations that primarily focus on 100 kW‐ or MW‐scale power generation systems, we consider, for the first time, a small‐scale power generator using sCO2. A partial admission axial turbine was designed and manufactured with a rated rotational speed of 40,000 rpm, and a CO2 transcritical power cycle test loop was constructed to validate the performance of our manufactured generator. A resistant gas was proposed in the constructed turbine expander to solve the leakage issue. Both dynamic and steady performances were investigated. The results indicated that a peak electric power of 11.55 kW was achieved at 29,369 rpm. The maximum total efficiency of the turbo‐generator was 58.98%, which was affected by both the turbine rotational speed and pressure ratio, according to the proposed performance map.
In response to climate change, the supercritical CO2 (sCO2) power cycle has been studied worldwide and considered the next generation of power generation technology. Most of the study is focused on theoretical analysis, and the experimental investigation of a CO2 power cycle is insufficient. In addition, the power capacity is usually between 0.1 and 10 MW, and the limited literature pays attention to the 10 kW sCO2 turbine expander and its performance that can be widely used in distributed energy systems, transportation, and waste heat recovery area. We try to fill in the gaps. Limited literature studies pay attention to the experimental analysis of a 10 kW sCO2 turbo‐generator and its performance. We also try to fill the gaps.
There has been increasing concern that the overuse of antibiotics in livestock farming is contributing to the burden of antimicrobial resistance in people. Farmed animals in Europe and North America, ...particularly pigs, provide a reservoir for livestock‐associated methicillin‐resistant Staphylococcus aureus (LA‐MRSA ST398 lineage) found in people. This study is designed to investigate the contribution of MRSA from Chinese pig farms to human infection. A collection of 483 MRSA are isolated from 55 farms and 4 hospitals in central China, a high pig farming density area. CC9 MRSA accounts for 97.2% of all farm isolates, but is not present in hospital isolates. ST398 isolates are found on farms and hospitals, but none of them formed part of the “LA‐MRSA ST398 lineage” present in Europe and North America. The hospital ST398 MRSA isolate form a clade that is clearly separate from the farm ST398 isolates. Despite the presence of high levels of MRSA found on Chinese pig farms, the authors find no evidence of them spilling over to the human population. Nevertheless, the ST398 MRSA obtained from hospitals appear to be part of a widely distributed lineage in China. The new animal‐adapted ST398 lineage that has emerged in China is of concern.
Zoonotic transmission of methicillin‐resistant Staphylococcus aureus (MRSA) is a significant problem and adds to the burden on antibiotic resistance in human healthcare. However, population‐level genomic studies reveal a separate MRSA population between farmed pigs and people in central China, a high pig farming density area.
We developed a multiplex PCR-based reverse line blot assay to identify 23 pneumococcal serotypes represented in the polysaccharide vaccine, using 334 well-characterized isolates, representing all 90 ...serotypes, and 268 "unknowns." The assay identified all target serotypes, but 11, which cross-react with 1 to 4 nonvaccine serotypes, could be distinguished using serotype-specific antisera.
We evaluated a combined panfungal PCR-reverse line blot (RLB) hybridization assay based on internal transcribed spacer 1 (ITS1) and ITS2 region polymorphisms to identify 159 Candida, Cryptococcus ...neoformans, and Aspergillus isolates (22 species). Its utility to identify fungal pathogens directly from 27 clinical specimens was also determined. ITS sequence analysis was performed to resolve discrepant identifications or where no RLB result was obtained. Species-specific ITS2- and ITS1-based probes correctly identified 155 of 159 isolates (98%) and 149 (93.7%) isolates, respectively. All strains were unambiguously differentiated with the exception of cross-reactivity between the Candida norvegensis probe and Candida haemulonii DNA product. Species identification of the pathogen was made for all 21 specimens (sensitivity of 100%) where species-specific probes were included in the RLB; however, there was no ITS2 probe-based hybridization signal for two specimens. Results were concordant with the culture results for 18 (85.7%) specimens. The assay was able to provide species identification in the absence of a culture result (two specimens) and to detect mixed infection (one specimen). The results indicate that the RLB assay is capable of reliably detecting yeasts and Aspergillus spp. in clinical specimens and that the incorporation of both ITS1- and ITS2-targeted probes is required for optimal sensitivity. The test has potential utility in the early diagnosis of invasive fungal infection, since "fungal" DNA was detected in all 27 specimens. Prior to incorporation of probes to detect other fungal species, ITS sequencing may be performed to achieve species identification.
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