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There is a rising need for sensors under an IoT network to identify and monitor the environment as more IoT devices and services are made accessible for use. This movement presents challenges such as the proliferation of data and the scarcity of energy. This research presents a strategy for enhancing the service provision capabilities of WSN-aided IoT applications by combining mobile edge computation with wireless signal and control transmission. In order to reduce overall system energy consumption while maintaining data transmission rate and power needs, a new optimization problem integrating power allocation, CPU frequency, offloading weight factor, and energy harvesting is devised. The non-convex nature of the problem necessitates the development of a novel ideal solution group iterative process optimization model that divides the original problem into multiple subproblems, with each subproblem being optimized in turn. According to the results of simulations with a numerical model, our proposed method consumes considerably less energy than just the two benchmark methodologies.

In this work, the AlCoCrFeNi2.1eutectic high-entropy alloys (EHEAs) were fabricated by laser additive manufacturing and subsequently heat-treated at various temperatures between 800 and 1200 °C to achieve excellent strength-plasticity synergy. The high solidification rate of selective laser melting (SLM) leads to instability of the eutectic growth front, resulting in a typical melt pool morphology of equiaxed and columnar crystals for AlCoCrFeNi2.1. The body-centered cubic (BCC) content of ∼82% in the SLM specimens leads to a higher tensile strength of ∼1175 MPa and poorer plasticity of ∼6.42%. After heat treatment, the BCC transforms to face-centered cubic (FCC) and the microstructure changes to a dendrite containing eutectic lamellar structure. As the temperature increases, Ni–Al aggregates, B2 phase particles precipitate and grow in the BCC matrix. Meanwhile, the uniform heating mode eliminates the orientation of the SLM melt pool structure, reduces the internal stress and dislocation density of the SLM alloy. In addition, high-temperature heating promotes the stable growth of lamellar structure. These combined effects allow the strength-plasticity trade-off to be achieved in the heat-treated specimen. The HT-1200 sample has a strength of 1065 MPa and a ductility of 21.97%.

Biomass is an important indicator in estimating the growth and yield of crops. Mastering the growth state of crops by evaluating and monitoring biomass is crucial. Correlation analysis was used to identify hyperspectral sensitive bands with the best correlation with biomass, and a hyperspectral vegetation index was constructed. Plant height data was coupled with hyperspectral reflectance and vegetation index data, and a biomass inversion model was constructed using partial least squares (PLS), support vector machine (SVM), and random forest (RF) regression analysis. The R2, root mean square error (RMSE), and normalized root mean square error (NRMSE) were calculated to verify the accuracy of the model. Plant height coupled with hyperspectral reflectance and vegetation index data, R2, RMSE, and NRMSE of the biomass model establishment and validation, compared with the hyperspectral data alone, improved model accuracy of the three algorithms for maize (Zea maysL.) biomass inversion coupled with plant height data with the relative improvement in accuracy of 13.58, 9.6, and 1.05%, respectively. Additionally, the model becomes more stable, overcoming the spectral saturation of canopy to a certain extent. It provides supporting information for accurate farmland planning, growth monitoring, and yield estimation. Use of plant height coupled hyperspectral reflectance data to perform the biomass inversion of maize.Development of biomass inversion model.Calculate R2, RMSE, and NRMSE to verify the model accuracy.

Laser powder bed fusion (LPBF) Invar 36 alloy has attracted plenty of attention in cryogenic components or precision instruments due to its low coefficient of thermal expansion in a wide range of temperature. However, the LPBF Invar 36 has a significant anisotropic mechanical property due to the unique columnar grain morphology and pore feature. In this study, the influence of scanning speed on the anisotropic tensile properties were investigated. In this respect, tensile tests of specimens parallel and perpendicular to the building direction with a scanning speed from 200 to 1400 mm/s of LPBF Invar 36 alloy were conducted, and the microstructural influential factors on the anisotropic tensile properties were analyzed. Results show that as the volumetric energy density (VED) increases, the inhomogeneity of grain morphology decreases, while the pore feature changes from the lack-of-fusion (LOF) pore perpendicular to the building direction to the bubble-shaped spherical pore, which is resulted from the collapse of the locking holes. In this case, the grain orientation and size, as well as the dislocation density in the vicinity of pores are influenced by the pore morphology due to different thermal history. On the whole, the increased level of anisotropy in pores are the main reason of the increased level of anisotropy in tensile properties.

Structural variants (SVs), such as deletions (DELs) and insertions (INSs), contribute substantially to pig genetic diversity and phenotypic variation. Using a library of SVs discovered from long-read primary assemblies and short-read sequenced genomes, we map pig genomic SVs with a graph-based method for re-genotyping SVs in 402 genomes. Our results demonstrate that those SVs harboring specific trait-associated genes may greatly shape pig domestication and local adaptation. Further characterization of SVs reveals that some population-stratified SVs may alter the transcription of genes by affecting regulatory elements. We identify that the genotypes of two DELs (296-bp DEL, chr7: 52,172,101–52,172,397; 278-bp DEL, chr18: 23,840,143–23,840,421) located in muscle-specific enhancers are associated with the expression of target genes related to meat quality (FSD2) and muscle fiber hypertrophy (LMOD2and WASL) in pigs. Our results highlight the role of SVs in domestic porcine evolution, and the identified candidate functional genes and SVs are valuable resources for future genomic research and breeding programs in pigs.

ABSTRACTLong non-coding RNAs (lncRNAs) are involved in the process of muscle cell differentiation and play an important role. Previous studies have shown that lncRNA-MEG3 promotes the differentiation of porcine skeletal muscle satellite cells (PSCs), but the regulatory mechanism of MEG3 interaction with target protein has not been well studied. We demonstrated that MEG3 can bind dihydrolipoamide succinyltransferase (DLST) by RNA pull down and RIP-qPCR. Subsequently, knockdown and overexpression experiments showed that DLST promotes PSCs differentiation. Rescue experiments showed that the expression of DLST protein was significantly increased with MEG3 overexpression and decreased with MEG3 knockdown, while its mRNA expression was not changed. Furthermore, we have successfully predicted and validated that the transcription factor myogenic differentiation (MYOD) binds to the MEG3 core promoter though utilizing chromatin immunoprecipitation (CHIP) and luciferase reporter assays. The results indicated that MYOD acts as a transcription factor of MEG3 to promote MEG3 transcription. Knockdown of MEG3 in vivo indicated that MEG3 is involved in skeletal muscle regeneration. It is concluded that MYOD acts as a transcription factor to induce MEG3 expression. MEG3 acts as a molecular scaffold to bind and promote DLST protein expression. This paper provides a new molecular mechanism for MEG3 to promote the differentiation of PSCs.

AbstractIn topic modelling, the main computational problem is to approximate the posterior distribution given an observed collection. Commonly, we must resort to variational methods for approximations; however, we do not know which variational variant is the best choice under certain settings. In this paper, we focus on four topic modelling inference methods, including mean-field variation Bayesian, collapsed variational Bayesian, hybrid variational-Gibbs and expectation propagation, and aim to systematically compare them. We analyse them from two perspectives, i.e. the approximate posterior distribution and the type of -divergence; and then empirically compare them on various data-sets by two popular metrics. The empirical results are almost matching our analysis, where they indicate that CVB0 may be the best variational variant for topic models.

Uncovering genetic variation through resequencing is limited by the fact that only sequences with similarity to the reference genome are examined. Reference genomes are often incomplete and cannot represent the full range of genetic diversity as a result of geographical divergence and independent demographic events. To more comprehensively characterize genetic variation of pigs (Sus scrofa), we generated de novo assemblies of nine geographically and phenotypically representative pigs from Eurasia. By comparing them to the reference pig assembly, we uncovered a substantial number of novel SNPs and structural variants, as well as 137.02-Mb sequences harboring 1737 protein-coding genes that were absent in the reference assembly, revealing variants left by selection. Our results illustrate the power of whole-genome de novo sequencing relative to resequencing and provide valuable genetic resources that enable effective use of pigs in both agricultural production and biomedical research.

It has been widely accepted that sustainable polymers derived from renewable resources are able to replace the short-turnover petroleum-based materials and reduce environmental impact in the future. However, their hydrophilic chemical structures rich with oxygen groups could lead to easy growth of bacteria, which greatly limit their applications in packaging materials. Here, we present an intelligent food-packaging material with sustained-release antibacterial and real-time monitoring ability based on totally biobased contents. In detail, sodium alginate with Artemisia argyiemission oil (encapsulated in gelatin–Arabic gum microcapsules) and citric acid-sourced pH-responsive carbon quantum dots (CQDs) are coated on bamboo cellulose papers. The obtained biobased composite material (almost 100% biocarbon content) with antibacterial ability is able to extend the shelf life of fresh shrimps and can be biodegraded. Moreover, owing to the introduction of CQDs, the composite can rapidly (within 1 s) detect slight pH variations (response pH ∼5, 10–9mol/L of OH–) through an obvious color change (hue value from 305 to 355°). The developed strategy may open up new opportunities in the design of multifunctional biobased composites for intelligent applications.

The aim was to evaluate the risk for major hemorrhage complications (MHC) prior to percutaneous renal biopsy and apply a specific procedure in high-risk patients to decrease their incidence. Hemorrhage complications that required blood transfusion or other interventions were diagnosed as MHC. One retrospective (Group A, n = 1314) and two prospective cohorts (Group B, n = 249 and Group C, n = 422) were involved in the study. Group A was used to establish a risk equation for MHC, Group B to test its performance, and Group C to evaluate the efficacy of the proposed procedure to reduce MHC incidence. Group C was classified, based on the equation, into high-risk (C1) and low-risk (C2) patients, who received different interventions. The intervention in Group C1 consisted of use of 18-gauge needles, a 12-h rest period post-operation, and reptilase injection; in Group C2, 16-gauge needles were used, with a 6-h rest, and no reptilase injection. Group B was also divided into B1 (high-risk) and B2 (low-risk) using the same cut-off, for further comparison. (1) In Group A, 4.8 % of patients experienced MHC and the equation: Logit (PMHC) = 0.022 × mean arterial pressure (mmHg) + 0.216 × bleeding time (min) − 0.011 × eGFR [ml/(min 1.73 m2)] − 0.894 × kidney length (cm) − 2.100 × renal cortical thickness (cm) + 6.225 (cutoff = −1.664) was established. (2) The area under the receiver operating characteristic curve was 0.848 (95 % CI 0.797–0.890) for Group B. (3) MHC occurred in 4.8 and 2.8 % of patients in Group B and C, respectively; Group B1 suffered significantly more frequent gross hematuria, hematoma and MHC than Group C1; however, no significant difference except for large hematoma was found between Groups B2 and C2 for all complications. The equation is reliable to predict the risk for MHC; the interventions proposed can decrease the incidence of MHC in high-risk patients.

AbstractIt is particularly important for the development of agriculture to strengthen the agricultural pests monitoring, prevention and cure. The traditional methods of remote sensing (RS) for agricultural pests monitoring cannot meet the needs of agricultural development, because of their long time-consuming, high cost, and low accuracy. However, Unmanned Aerial Vehicle (UAV) remote sensing, as a new means of remote sensing, is introduced in this paper for agricultural monitoring. UAV has advantages of strong real-time, quickness, convenience, low cost, high accuracy and abundant data. With the great flexibility of UAV remote sensing, it is not only easy to focus on regional and long-term agricultural pests monitoring, but also feasible to provide scientific basis for crop pests control. Thus, it is better to meet the time needs of pests’ control. In the article, Baiyangdian agricultural area is chosen as the study area. It is discussed how to process UAV images rapidly and extract disease crop information, especially which improved scale invariant feature transform (SIFT) algorithm and object-oriented information extraction are used for image-processing. Fortunately, it has been received good results for the local crop pest control in terms of fact of treatment. With the advantages of UAV remote sensing, there is a broad application prospect in precision agriculture.

The article presents the summary of the speech by Li Changchun, member of the Standing Committee of the Political Bureau of the Communist Party of China (CPC) Central Committee, delivered during the awarding ceremony of the 10th China Journalist's Day on November 8, 2009. He spoke about the 60th anniversary of the new China and the role of the news industry. He also pointed out the CPC's good traditions in the media and propaganda work that the news front inherited and advanced.

The pig has a noninvasive epitheliochorial placenta, and trophoblast-endometrial epithelial bilayer development could impact on placental function. This work compared the morphological structures, the cell proliferation status as assessed by Ki67 staining, as well as the location and gene and protein expression of heparanase (HPSE) at the maternal-fetal interface between Yorkshire and Meishan pigs on Days 26, 50, and 95 of gestation. Histomorphometry showed that the widths of placental folds, endometrial stroma, and placental stroma in Meishan pigs were smaller than those in Yorkshire pigs during late gestation, while the complexity and the cell proliferation ability of the folded bilayer were greater in Meishan pigs in this period. The location and expression levels of HPSEmRNA and protein at the maternal-fetal interface were similar between the two breeds during early and midgestation. However, during late gestation, the mRNA and protein levels were higher in Meishan placentae. In addition, the HPSEmRNA was expressed by all the trophoblast cells, and the protein was located both at trophoblast and luminal epithelium cells in Meishan pigs during late gestation, while in Yorkshire pigs, the HPSEmRNA and protein were only identified in trophoblast cells located at the bottom and side of folds. The findings suggest that Meishan pigs may rely more upon the increase in the complexity of the folded bilayer within a reduced placenta to expand the exchange surface area and the HPSE may contribute to the development of the folded bilayer in pigs.

Abstract 4877

Nowadays, massive short texts, such as social media posts and newspaper titles, are available on the Internet. Analyzing these short texts is very significant for many content analysis tasks. However, the commonly used text analysis tools, i.e., topic models, lose effectiveness on short texts because of the sparsity and noise problems. Recent topic models mainly attempt to solve the sparsity problem, but neglect the noise issue. To address this, we propose a common semantics topic model (CSTM) in this paper. The key idea is to introduce a new type of topic, namely common topic, to gather the noise words. The experimental results on real-world datasets indicate that our CSTM outperforms the existing short text topic models on the traditional tasks. [ABSTRACT FROM AUTHOR]