Search

Information has been uploaded and downloaded through the Internet, day in and day out, ever since we immersed ourselves in the Internet. Data security has become an area demanding high attention, and one of the most efficient techniques for protecting data is data hiding. In recent studies, it has been shown that the indices of a codebook can be reordered to hide secret bits. The hiding capacity of the codeword index reordering scheme increases when the size of the codebook increases. Since the codewords in the codebook are not modified, the visual performance of compressed images is retained. We propose a novel scheme making use of the fundamental principle of the codeword index reordering technique to hide secret data in encrypted images. By observing our experimental results, we can see that the obtained embedding capacity of 197,888 is larger than other state-of-the-art schemes. Secret data can be extracted when a receiver owns a data hiding key, and the image can be recovered when a receiver owns an encryption key. more...

The aim of this study is to evaluate the performance of the Global Climate Model (GCM) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) in historical simulations of temperature and precipitation. The goal is to select the best performing GCMs for future projection of temperature and precipitation in the Second Songhua River Basin under multiple shared socioeconomic pathways (SSPs). Interannual variability skill (IVS) and Taylor diagrams are used to evaluate the spatiotemporal performance of GCMs against temperature and precipitation data published by the China Meteorological Science Commons during 1956–2016. In addition, five relatively independent models are selected to simulate the temperature and precipitation for 2021–2050 using Hierarchical Clustering. The selected models are CMCC-ESM2, EC-Earth3-Veg-LR, IPSL-CM6A-LR, MIROC-ES2L, and MPI-ESM1-2-HR. The projected results find that SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios show an increasing trend of future annual mean temperature and precipitation. However, for annual precipitation, there is a mixed state of increase and decrease among different models on the seasonal scale. In general, future temperature and precipitation changes still show a trend of growth and uneven distribution in the Second Songhua River Basin, which may be further accelerated by human activities. more...

Sensor nodes are critical components of the Internet of Things (IoT). Traditional IoT sensor nodes are typically powered by disposable batteries, making it difficult to meet the requirements for long lifetime, miniaturization, and zero maintenance. Hybrid energy systems that integrate energy harvesting, storage, and management are expected to provide a new power source for IoT sensor nodes. This research describes an integrated cube-shaped photovoltaic (PV) and thermal hybrid energy-harvesting system that can be utilized to power IoT sensor nodes with active RFID tags. The indoor light energy was harvested using 5-sided PV cells, which could generate 3 times more energy than most current studies using single-sided PV cells. In addition, two vertically stacked thermoelectrical generators (TEG) with a heat sink were utilized to harvest thermal energy. Compared to one TEG, the harvested power was improved by more than 219.48%. In addition, an energy management module with a semi-active configuration was designed to manage the energy stored by the Li-ion battery and supercapacitor (SC). Finally, the system was integrated into a 44 mm × 44 mm × 40 mm cube. The experimental results showed that the system was able to generate a power output of 192.48 µW using indoor ambient light and the heat from a computer adapter. Furthermore, the system was capable of providing stable and continuous power for an IoT sensor node used for monitoring indoor temperature over a prolonged period. more...

Disease risk is a persistent problem in domestic cattle farming, while economic traits are the main concern. This study aimed to reveal the epigenetic basis for differences between zebu (Bos indicus) and taurine cattle (Bos taurus) in disease, disease resistance, and economic traits, and provide a theoretical basis for the genetic improvement of domestic cattle. In this study, whole genome bisulfite sequencing (WGBS) was used to analyze the whole-genome methylation of spleen and liver samples from Yunnan zebu and Holstein cattle. In the genome-wide methylation pattern analysis, it was found that the methylation pattern of all samples was dominated by the CG type, which accounted for >94.9%. The DNA methylation levels of different functional regions and transcriptional elements in the CG background varied widely. However, the methylation levels of different samples in the same functional regions or transcriptional elements did not differ significantly. In addition, we identified a large number of differentially methylation region (DMR) in both the spleen and liver groups, of which 4713 and 4663 were annotated to functional elements, and most of them were annotated to the intronic and exonic regions of genes. GO and KEGG functional analysis of the same differentially methylation region (DMG) in the spleen and liver groups revealed that significantly enriched pathways were involved in neurological, disease, and growth functions. As a result of the results of DMR localization, we screened six genes (DNM3, INPP4B, PLD, PCYT1B, KCNN2, and SLIT3) that were tissue-specific candidates for economic traits, disease, and disease resistance in Yunnan zebu. In this study, DNA methylation was used to construct links between genotypes and phenotypes in domestic cattle, providing useful information for further screening of epigenetic molecular markers in zebu and taurine cattle. more...

As a critical physical parameter in the sea–air interface, sea surface temperature (SST) plays a crucial role in the sea–air interaction process. The SST diurnal cycle is one of the most critical changes that occur in the various time scales of SST. Currently, accurate simulation and prediction of SST diurnal cycle amplitude remain challenging. The application of machine learning in marine environment research, simulation, and prediction has received increasing attention. In this study, a regression prediction model for SST diurnal cycle amplitude was constructed based on TOGA/COARE buoy-observed data and an extreme gradient boosting algorithm (XGBoost). The XGBoost algorithm was also optimized using label distribution smoothing (LDS) to respond to the problem of uneven cycle amplitude size distribution. The results showed that the LDS-XGB model outperformed various empirical models and other machine learning models in terms of prediction error and prediction accuracy while effectively improving the data imbalance problem without losing model accuracy and achieving accurate and efficient predictions of the SST diurnal cycle amplitude. This work is a good demonstration of the integration of marine science and machine learning, which indicates that machine learning plays an important role in the model parametrizations and understanding the mechanisms. more...

Using the rock mechanics test (RMT) and acoustic emission acquisition system (DS9), based on the energy principle, uniaxial compression, uniaxial cyclic loading, and unloading tests are used to study the energy transformation characteristics of the process of sandstone absorbing axial strain energy, accumulating and releasing elastic strain energy, plastic deformation, and crack extension dissipation energy. The study results show the increase of loading rate, rock fracture surface increases, number of fragments increases, and size of fragments decreases; the sandstone damage process causes: shear damage to tensile shear damage and then splitting damage for change; the input energy and elastic energy increase nonlinearly with an increase of stress, and the dissipative energy is larger at the beginning of loading. After a small decrease, it enters the nonlinear growth stage, and the input energy density grows the fastest. The elastic energy density is the second fastest, and the dissipative energy density grows the slowest; with an increase of loading rate, in any deformation stage, the elastic energy density and dissipation energy density are increased, proportion of elastic energy density is decreased, and proportion of dissipation energy density is increased. Near the peak stress stage, the proportion of elastic energy decreases, and the proportion of dissipative energy increases; the damage variable stress curve of sandstone is “weakly concave”, which is consistent with the logistic function, and the damage evolution process has chaotic dynamics properties; the acoustic emission energy of sandstone in cyclic loading and unloading test has a similar variation with the theoretical calculation of dissipated energy. The cumulative energy curve shows a step-up law, and the stress corresponding to the step point is near the historical maximum stress. more...

How to hide messages in digital images so that messages cannot be discovered and tampered with is a compelling topic in the research area of cybersecurity. The interpolation-based reversible data hiding (RDH) scheme is especially useful for the application of medical image management. The biometric information of patients acquired by biosensors is embedded into an interpolated medical image for the purpose of authentication. The proposed scheme classifies pixel blocks into complex and smooth ones according to each block’s dynamic range of pixel values. For a complex block, the minimum-neighbor (MN) interpolation followed by DIM embedding is applied, where DIM denotes the difference between the block’s interpolated pixel values and the maximum pixel values. For a smooth block, the block mean (BM) interpolation is followed by a prediction error histogram (PEH) embedding and a difference expansion (DE) embedding is applied. Compared with previous methods, this adaptive strategy ensures low distortion due to embedding for smooth blocks while it provides a good payload for complex blocks. Our scheme is suitable for both medical and general images. Experimental results confirm the effectiveness of the proposed scheme. Performance comparisons with state-of-the-art schemes are also given. The peak signal to noise ratio (PSNR) of the proposed scheme is 10.32 dB higher than the relevant works in the best case. more...

Animal diseases impose a huge burden on the countries where diseases are endemic. Conventional control strategies of vaccines and veterinary drugs are to control diseases from a pharmaceutical perspective. Another alternative approach is using pre-existing genetic disease resistance or tolerance. We know that the Yunling goat is an excellent local breed from Yunnan, southwestern China, which has characteristics of strong disease resistance and remarkable adaptability. However, genetic information about the selection signatures of Yunling goats is limited. We reasoned that the genes underlying the observed difference in disease resistance might be identified by investigating selection signatures between two different goat breeds. Herein, we selected the Nubian goat as the reference group to perform the population structure and selection signature analysis by using RAD-seq technology. The results showed that two goat breeds were divided into two clusters, but there also existed gene flow. We used Fst (F-statistics) and π (pi/θπ) methods to carry out selection signature analysis. Eight selected regions and 91 candidate genes were identified, in which some genes such as DOK2, TIMM17A, MAVS, and DOCK8 related to disease and immunity and some genes such as SPEFI, CDC25B, and MIR103 were associated with reproduction. Four GO (Gene Ontology) terms (GO:0010591, GO:001601, GO:0038023, and GO:0017166) were associated with cell migration, signal transduction, and immune responses. The KEGG (Kyoto Encyclopedia of Genes and Genomes) signaling pathways were mainly associated with immune responses, inflammatory responses, and stress reactions. This study preliminarily revealed the genetic basis of strong disease resistance and adaptability of Yunling goats. It provides a theoretical basis for the subsequent genetic breeding of disease resistance of goats. more...

Climate change can impact the yield and water footprint of crops. Therefore, assessing such impacts carries great significance for regional water and food security. This study validated and verified the variety parameters of winter wheat for the Decision Support System for Agrotechnology Transfer (DSSAT) model, using the long-term (1993–2013) growth and yield data observed from six agricultural experiment stations in the Haihe River Basin (HRB), China. The growth process was simulated under three representative concentration pathways (RCPs), named RCP2.6, RCP4.5, and RCP8.5—climate scenarios driven by the HadGEM2-ES model. The variety parameters of winter wheat showed high accuracy in the simulation of the anthesis and maturity dates, and could be used for long-term prediction of the growth process. The trends of climate change had positive impacts on the water footprint of winter wheat but adverse impacts on the yield. The growing period was shortened by 3.6 days, 4.7 days, and 5.0 days per decade in the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, due to the rapid accumulation of heat. The yield would be increased in lower emissions scenarios (17% in RCP2.6), but decreased in high-emissions scenarios due to high temperatures, which may restrict the growth of wheat. The water footprint was decreased by 10%, 11%, and 13% in the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, indicating that the water-use efficiency could be improved in the future. The results showed broad application prospects of the DSSAT model in simulating the response of crop growth to climate change. more...

Pixel value ordering and prediction error expansion (PVO+PEE) is a very successful reversible data hiding (RDH) scheme. A series of studies were proposed to improve the performance of the PVO-based scheme. However, the embedding capacity of those schemes is quite limited. We propose a two-step prediction-error-triplet expansion RDH scheme based on PVO. A three-dimensional state transition map for the prediction-error triplet is also proposed to guide the embedding of the two-step scheme. By properly designing the state transitions, the proposed scheme can embed secret data or expand without embedding by modifying just a single entry of the triplet. The experimental results show that the proposed scheme significantly enlarges the embedding capacity of the PVO-based scheme and further reduces the distortion due to embedding. more...

Previous studies have shown that Yunnan humped cattle have higher disease resistance than pure taurine cattle, such as Holsteins. However, there exists limited information about the molecular genetic basis underlying disease resistance differences between them. The objective of this study was to compare differentially expressed genes (DEGs) in the liver and spleen tissues of Holstein and Yunnan humped cattle through comparative transcriptome analysis, using RNA-sequencing. In total, 1564 (647 up- and 917 down-regulated genes) and 1530 (716 up- and 814 down-regulated genes) DEGs were obtained in the liver and spleen tissues of Holstein and Yunnan humped cattle comparison groups, respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the DEGs were mainly associated with the RIG-I signaling pathway, immune responses, major histocompatibility complex (MHC) class I protein complex and complement activation, human T-cell lymphotropic virus type-I (HTLV-I) infection. Some genes related to immune function, such as C1QB, CD55, MASP2, C4BPA, MAVS, NOD2, and CD46, were up-regulated in Yunnan humped cattle, while C2, SERPING1, SERPINE1, TIRAP, TLR2, and TLR6 were down-regulated. The expression levels of 11 selected DEGs, analyzed by quantitative reverse-transcription polymerase chain reaction (RT-qPCR), were consistent with the deep sequencing results by RNA-sequencing. Our results will provide a scientific basis and key technical support for disease-resistant breeding of domestic cattle. more...

A new elastoplastic J 2 -flow models with thermal effects is proposed toward simulating thermo-coupled finite deformation behaviors of shape memory polymers. In this new model, an elastic potential evolving with development of plastic flow is incorporated to characterize the stress-softening effect at unloading and, moreover, thermo-induced plastic flow is introduced to represent the strain recovery effect at heating. It is shown that any given test data for both effects may be accurately simulated by means of direct and explicit procedures. Numerical examples for model predictions compare well with test data in literature. more...