Developing countries have common goals of poverty eradication and improving people’s livelihoods. As the largest developing country, China has made remarkable achievements in poverty alleviation ...during the 30 years of reform. Although a targeted poverty alleviation mechanism was established by the Chinese government in 2013, the identification of poor households has been an arduous journey. Based on a total of 688 samples of grassroots officials and 2,621 rural households from 69 village-level divisions in 9 provinces in China, this study conducted cross-validation on the impact of the participation of rural households in the identifying poor households that required government assistance. This was from the perspectives of grassroots officials and rural households. It was investigated whether this participation led to an anomaly between the identification of poor households and the actual situation. Empirical results show that the participation of rural households in appraisals significantly increases the probability of identifying a non-poor household as a poor household (first error) and decreases the probability of failing to identify a poor household as a poor household (second error). As the impact of the first error is greater than that of the second error, the participation of rural households in appraisals has the overall effect of increasing the incorrect registrations of poor households. These results are still valid after addressing the self-selection problem. For other developing countries to successfully apply effort into poverty alleviation, in addition to focusing on increasing farmers’ participation in public affairs, they should prevent any bias that may be caused by farmers’ participation in public affairs; strengthen publicity and guidance; focus on the nurture of officials; perfect top-level design; and set clearer targets for poverty alleviation policies.
This paper presents a theoretical and experimental study on thermal conductivities of silica aerogel, xonotlite-type calcium silicate and xonotlite–aerogel composite insulation material. The ...transmittance spectra of silica aerogel and xonotlite-type calcium silicate samples are obtained through FTIR measurements. The corresponding extinction coefficient spectra of the three materials are then obtained by applying Beer’s law. The thermal conductivities of aerogel, xonotlite-type calcium silicate, and xonotlite–aerogel composite insulation material are measured from 300 to 970
K and from 0.045
Pa to atmospheric pressure with the transient hot-strip (THS) method. The thermal conductivity models developed for coupled heat transfer of gas and solid based on the unit cell method are compared with the experimental measurement results. It is shown that the effective thermal conductivity models matches well with the experimental data. The specific spectral extinction coefficients of xonotlite-type calcium are larger than 10
m
2
kg
−1, and the specific spectral extinction coefficients of aerogel are larger than 7
m
2
kg
−1 over the whole measured spectra. The density of xonotlite-type calcium silicate is the key factor affecting the effective thermal conductivity of xonotlite–aerogel composite insulation material, and the density of aerogel has little influence. The effective thermal conductivity can be lowered greatly by composite of the two materials at an elevated temperature.
Aircraft engine systems are composed of numerous pipelines. It is crucial to regularly inspect these pipelines to detect any damages or failures that could potentially lead to serious accidents. The ...inspection process typically involves capturing complete 3D point clouds of the pipelines using 3D scanning techniques from multiple viewpoints. To obtain a complete and accurate representation of the aircraft pipeline system, it is necessary to register and align the individual point clouds acquired from different views. However, the structures of aircraft pipelines often appear similar from different viewpoints, and the scanning process is prone to occlusions, resulting in incomplete point cloud data. The occlusions pose a challenge for existing registration methods, as they can lead to missing or wrong correspondences. To this end, we present a novel registration framework specifically designed for aircraft pipeline scenes. The proposed framework consists of two main steps. First, we extract the point feature structure of the pipeline axis by leveraging the cylindrical characteristics observed between adjacent blocks. Then, we design a new 3D descriptor called PL-PPFs (Point Line–Point Pair Features), which combines information from both the pipeline features and the engine assembly line features within the aircraft pipeline point cloud. By incorporating these relevant features, our descriptor enables accurate identification of the structure of the engine’s piping system. Experimental results demonstrate the effectiveness of our approach on aircraft engine pipeline point cloud data.
To construct gene co-expression networks, it is necessary to evaluate the correlation between different gene expression profiles. However, commonly used correlation metrics, including both linear ...(such as Pearson's correlation) and monotonic (such as Spearman's correlation) dependence metrics, are not enough to observe the nature of real biological systems. Hence, introducing a more informative correlation metric when constructing gene co-expression networks is still an interesting topic.
In this paper, we test distance correlation, a correlation metric integrating both linear and non-linear dependence, with other three typical metrics (Pearson's correlation, Spearman's correlation, and maximal information coefficient) on four different arrays (macrophage and liver) and RNA-seq (cervical cancer and pancreatic cancer) datasets. Among all the metrics, distance correlation is distribution free and can provide better performance on complex relationships and anti-outlier. Furthermore, distance correlation is applied to Weighted Gene Co-expression Network Analysis (WGCNA) for constructing a gene co-expression network analysis method which we named Distance Correlation-based Weighted Gene Co-expression Network Analysis (DC-WGCNA). Compared with traditional WGCNA, DC-WGCNA can enhance the result of enrichment analysis and improve the module stability.
Distance correlation is better at revealing complex biological relationships between gene profiles compared with other correlation metrics, which contribute to more meaningful modules when analyzing gene co-expression networks. However, due to the high time complexity of distance correlation, the implementation requires more computer memory.
Abstract
O-GlcNAcylation is a conserved post-translational modification that attaches N-acetyl glucosamine (GlcNAc) to myriad cellular proteins. In response to nutritional and hormonal signals, ...O-GlcNAcylation regulates diverse cellular processes by modulating the stability, structure, and function of target proteins. Dysregulation of O-GlcNAcylation has been implicated in the pathogenesis of cancer, diabetes, and neurodegeneration. A single pair of enzymes, the O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA), catalyzes the addition and removal of O-GlcNAc on over 3,000 proteins in the human proteome. However, how OGT selects its native substrates and maintains the homeostatic control of O-GlcNAcylation of so many substrates against OGA is not fully understood. Here, we present the cryo-electron microscopy (cryo-EM) structures of human OGT and the OGT-OGA complex. Our studies reveal that OGT forms a functionally important scissor-shaped dimer. Within the OGT-OGA complex structure, a long flexible OGA segment occupies the extended substrate-binding groove of OGT and positions a serine for O-GlcNAcylation, thus preventing OGT from modifying other substrates. Conversely, OGT disrupts the functional dimerization of OGA and occludes its active site, resulting in the blocking of access by other substrates. This mutual inhibition between OGT and OGA may limit the futile O-GlcNAcylation cycles and help to maintain O-GlcNAc homeostasis.
Because of the unique physical and chemical properties of water, obtaining high-quality underwater images directly is not an easy thing. Hence, recovery and enhancement are indispensable steps in ...underwater image processing and have therefore become research hotspots. Nevertheless, existing image-processing methods generally have high complexity and are difficult to deploy on underwater platforms with limited computing resources. To tackle this issue, this paper proposes a simple and effective baseline named UIR-Net that can recover and enhance underwater images simultaneously. This network uses a channel residual prior to extract the channel of the image to be recovered as a prior, combined with a gradient strategy to reduce parameters and training time to make the operation more lightweight. This method can improve the color performance while maintaining the style and spatial texture of the contents. Through experiments on three datasets (MSRB, MSIRB and UIEBD-Snow), we confirm that UIR-Net can recover clear underwater images from original images with large particle impurities and ocean light spots. Compared to other state-of-the-art methods, UIR-Net can recover underwater images at a similar or higher quality with a significantly lower number of parameters, which is valuable in real-world applications.
This paper studies the thermal radiative transfer in silica aerogel and silica aerogel composite insulation materials (a xonotlite–aerogel composite and a ceramic fiber–aerogel composite). The ...spectral transmittances of silica aerogel, xonotlite-type calcium silicate, and ceramic fiber insulation materials–all considered semi-transparent mediums capable of absorbing, emitting, and scattering thermal radiation–are measured with a Fourier transform infrared spectrometer (FTIR) at different infrared wavelengths ranging from 2.5 to 25μm. The spectral transmittances are used to determine the specific spectral extinction coefficient and the specific Rosseland mean extinction coefficient of each sample. The radiative conductivity of each sample, deduced from the overall thermal conductivity measured using the transient hot-strip (THS) method, is compared against diffusion approximation predictions by using the measured spectral extinction coefficient. The results show that the spectral extinction coefficients of the samples are strongly dependent on the wavelength, particularly in the short wavelength regime (<10μm). The total Rosseland mean extinction coefficients of the samples all decrease with increasing temperature. The radiative conductivities are almost proportional to the cube of temperature, decreasing as sample densities increase.
► Radiative heat transfer is a major heat transfer mechanism for studied materials. ► An FTIR equipment can be used to study radiative properties of insulation material. ► The extinction coefficients of the samples are strongly dependent on wavelength. ► The radiative conductivities are almost proportional to the cube of temperature.
There are no adequate data to determine whether intensity-modulated radiotherapy (IMRT) is superior to three-dimensional conformal radiotherapy (3DCRT) in the treatment of non-small cell lung cancer ...(NSCLC). This meta-analysis was conducted to compare the clinical outcomes of IMRT and 3DCRT in the treatment of NSCLC.
No exclusions were made based on types of study design. We performed a literature search in PubMed, EMBASE and the Cochrane library databases from their inceptions to April 30, 2015. The overall survival (OS) and relative risk (RR) of radiation pneumonitis and radiation oesophagitis were evaluated. Two authors independently assessed the methodological quality and extracted data. Publication bias was evaluated by funnel plot using Egger's test results.
From the literature search, 10 retrospective studies were collected, and of those, 5 (12,896 patients) were selected for OS analysis, 4 (981 patients) were selected for radiation pneumonitis analysis, and 4 (1339 patients) were selected for radiation oesophagitis analysis. Cox multivariate proportional hazards models revealed that 3DCRT and IMRT had similar OS (HR = 0.96, P = 0.477) but that IMRT reduced the incidence of grade 2 radiation pneumonitis (RR = 0.74, P = 0.009) and increased the incidence of grade 3 radiation oesophagitis (RR = 2.47, P = 0.000).
OS of IMRT for NSCLC is not inferior to that of 3DCRT, but IMRT significantly reduces the risk of radiation pneumonitis and increases the risk of radiation oesophagitis compared to 3DCRT.
An outbreak of the so-called Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2), has been spreading rapidly nationwide in China since ...December 2019. Wuhan, Hubei Province, is the hardest-hit region, with a rise in confirmed cases and its hospitals overwhelmed. On 2nd February, 2020, Wuhan began to build a modular hospital to treat patients caught with mild illness. The mobile modular hospital is mainly composed of medical modules, technical support modules, ward units, living support units and transportation capacity under field conditions, and there are complete equipment and specialized personnel to treat patients. Due to the severity and particularity of SARS-CoV-2, taking granted from lessons learnt from mobile modular hospitals, we use the existing large venues to construct a new fixed modular hospital. As patients need to be treated and tested, it is important to develop a clinical laboratory in the modular hospital and ensure biosafety. The construction of a clinical laboratory in the modular hospital is faced with problems such as time pressure, limited site selection, high level of biosafety, lack of experience and so forth. This paper mainly discusses how to construct the clinical laboratory in the modular hospital quickly and safely and put it into use to provide testing service for patients under various limited conditions.
Gene co-expression networks are widely studied in the biomedical field, with algorithms such as WGCNA and lmQCM having been developed to detect co-expressed modules. However, these algorithms have ...limitations such as insufficient granularity and unbalanced module size, which prevent full acquisition of knowledge from data mining. In addition, it is difficult to incorporate prior knowledge in current co-expression module detection algorithms. In this paper, we propose a novel module detection algorithm based on topology potential and spectral clustering algorithm to detect co-expressed modules in gene co-expression networks. By testing on TCGA data, our novel method can provide more complete coverage of genes, more balanced module size and finer granularity than current methods in detecting modules with significant overall survival difference. In addition, the proposed algorithm can identify modules by incorporating prior knowledge. In summary, we developed a method to obtain as much as possible information from networks with increased input coverage and the ability to detect more size-balanced and granular modules. In addition, our method can integrate data from different sources. Our proposed method performs better than current methods with complete coverage of input genes and finer granularity. Moreover, this method is designed not only for gene co-expression networks but can also be applied to any general fully connected weighted network.
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