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Abstracts: An on-site, sensitive, and cost-effective method for determining aflatoxin B1 (AFB1) in rice samples is proposed, combining magnetic solid phase extraction (MSPE) and time-resolved fluorescence immunochromatography (TRFICA) techniques. Cost-effective rice husks were carbonized and combined with nanomaterials to make magnetic nanocomposites that acted as effective adsorbents in MSPE. Under optimal conditions, the entire process was completed in 15 min with a visual detection limit of 0.16 μg/kg. Recoveries ranged from 85.2 % to 109.4 %, with intra- and inter-day precisions below 11.5 %. The proposed MSPE-TRFICA method offers a viable alternative for the rapid and highly sensitive quantitative detection of AFB1 for quality assurance.

The red imported fire ants (RIFAs) are a globally important invasive pest that severely affects the ecosystem and human health, and its current control is primarily through chemical pesticides. However, the extensive use of chemical pesticides causes environmental problems, and alternative strategies for controlling this pest are being explored. In our study, we aimed to design a deep eutectic solvent (DES)–CaCO3 system in which RIFAs were used as target insects to increase the lethal activity and behavioural regulation effects on RIFAs via contact and feeding. Indoxacarb (IDC) was made into DESs with three fatty acids, oleic acid (OA), linoleic acid (LA), and linolenic acid (LNA), which showed a significant increase in lethal activity against worker ants compared with IDC. OA@IDC@CaCO3, LA@IDC@CaCO3, and LNA@IDC@CaCO3 nanoparticles were prepared via interfacial precipitation. Characterization of the structures of the three pesticide-carrying nanoparticles revealed that all three fatty acid eutectic solvents formed spherical CaCO3 nanoparticles, with average particle sizes between 0.59 and 0.90 μm, which increased with increasing degree of fatty acid unsaturation. The pesticide loading ranged from 2.13 %⁓3.43 %, and the surfaces were all positively charged and well dispersed. OA@IDC@CaCO3 was relatively more effective and was able to dramatically inhibit the abandonment and foraging behaviours of RIFAs, prolong the time required for these behaviours, and decrease the number of feeding worker ants and the amount of food consumed. OA@IDC@CaCO3 was subsequently compounded with diatomaceous earth (DA), and spiked into baits, which significantly increased the contact and feeding activity of worker ants, inhibited the feeding, digging, and corpse-discarding behaviours of RIFAs. In the field trial, the combined control effect of the DA + OA@IDC@CaCO3 group was 83.38 %, which was greater than the 69.65 % of the commercial agent control group. In this study, IDC bait was co-prepared by using acid as a comelting solvent, CaCO3 as a coating, and DA as a pesticide adjuvant, which improved the activity against RIFAs, prolonged the holding period of IDC, and improved the prevention and control of RIFAs. Therefore, our research provides a simple and feasible approach for designing and constructing novel nanopesticides for RIFAs control.

Abstract A fast, simple, and sensitive analytic method was proposed for the simultaneous quantification of aflatoxins (AFTs) and capsaicinoids in vegetable oils by immunomagnetic sorbent coupled with ultra‐performance liquid chromatography coupled with tandem mass spectrometry. The immunomagnetic solid phase extraction (IMSPE) sorbents were synthesized with the monoclonal antibodies via cyanogen bromide magnetic sorbents, which could modify the surface magnetic sorbents under mild synthetic condition. The IMSPE procedure had the following aspects such as ease manipulation, easy disperse, quick isolation, eco‐friendly, and cost‐effective. The major conditions of IMSPE procedure were systemically studied, and the optimized pretreatment was accomplished in 15 min avoding complicated condition or sophisticated equipment. Excellent linearities were achieved by the correlation (R2) more than 0.9983. The limits of quantifications of all analytes ranged from 0.03 to 0.20 µg kg−1, and the recoveries were satisfactory ranging from 75.7% to 124.0% with the intra‐day and inter‐day precisions less than 10.1%. Additionally, the proposed method was used to analyze AFTs and capsaicinoids in retail oil samples. Overall, 25% of soybean and peanut oils and 12.5% of corn and blended oil were detected with AFTs, and no capsaicinoid was found. The content of AFTs was under the MRLs set by EU and China regulation for food quality and safety. The validated results indicated that this method could be utilized for a rapid, efficient, and accurate quantification of AFTs and capsaicinoids in complex lipid‐based matrix.

The limited availability of thermal infrared (TIR) training samples leads to suboptimal target representation by convolutional feature extraction networks, which adversely impacts the accuracy of TIR target tracking methods. To address this issue, we propose an unsupervised cross-domain model (UCDT) for TIR tracking. Our approach leverages labeled training samples from the RGB domain (source domain) to train a general feature extraction network. We then employ a cross-domain model to adapt this network for effective target feature extraction in the TIR domain (target domain). This cross-domain strategy addresses the challenge of limited TIR training samples effectively. Additionally, we utilize an unsupervised learning technique to generate pseudo-labels for unlabeled training samples in the source domain, which helps overcome the limitations imposed by the scarcity of annotated training data. Extensive experiments demonstrate that our UCDT tracking method outperforms existing tracking approaches on the PTB-TIR and LSOTB-TIR benchmarks.

IntroductionGerminated brown rice is a functional food with a promising potential for alleviating metabolic diseases. This study aimed to explore the hypolipidemic effects of autoclaving-treated germinated brown rice (AGBR) and the underlying mechanisms involving gut microbiota.MethodsDietary intervention with AGBR or polished rice (PR) was implemented in patients with hyperlipidemia for 3 months, and blood lipids were analyzed. Nutritional characteristics of AGBR and PR were measured and compared. Additionally, 16S rDNA sequencing was performed to reveal the differences in gut microbiota between the AGBR and PR groups.ResultsAGBR relieves hyperlipidemia in patients, as evidenced by reduced levels of triglycerides, total cholesterol, low-density lipoprotein cholesterol, and apolipoprotein-B, and elevated levels of high-density lipoprotein cholesterol and apolipoprotein-A1. In terms of nutrition, AGBR had significantly higher concentrations of free amino acids (10/16 species), γ-aminobutyric acid, resistant starch, soluble dietary fiber, and flavonoids (11/13 species) than PR. In addition, higher microbial abundance, diversity, and uniformity were observed in the AGBR group than in the PR group. At the phylum level, AGBR reduced Firmicutes, Proteobacteria, Desulfobacterota, and Synergistota, and elevated Bacteroidota and Verrucomicrobiota. At the genus level, AGBR elevated Bacteroides, Faecalibacterium, Dialister, Prevotella, and Bifidobacterium, and reduced Escherichia-Shigella, Blautia, Romboutsia, and Turicibacter.DiscussionAGBR contributes to the remission of hyperlipidemia by modulating the gut microbiota.

Hyperlipidemia is a frequent metabolic disorder that is closely associated with diet. It is believed that brown rice, containing the outer bran layer and germ, is beneficial for the remission of hyperlipidemia. This study established a rat model of hyperlipidemia by feeding a high-fat diet. The hypolipidemic potential of germinated brown rice (Gbrown) and germinated black rice (a germinated black-pigmented brown rice, Gblack) were explored in the model rats, mainly in the aspects of blood lipids, lipases, apolipoproteins, and inflammation. The gut microbiota in hyperlipidemic rats receiving diverse dietary interventions was determined by 16S rDNA sequencing. The results showed that the intervention of Gbrown/Gblack alleviated the hyperlipidemia in rats, evidenced by decreased TC, TG, LDL-C, and apolipoprotein B, and increased HDL-C, HL, LPL, LCAT, and apolipoprotein A1. Gbrown/Gblack also weakened the inflammation in hyperlipidemia rats, evidenced by decreased TNF-α, IL-6, and ET-1. In addition, 16S rDNA sequencing revealed that the diet of Gbrown/Gblack elevated the abundance and diversity of gut microbiota in hyperlipidemia rats. At the phylum level, Gbrown/Gblack decreased Firmicutes, increased Bacteroidetes, and decreased the F/B ratio in hyperlipidemia rats. At the genus level, Gbrown/Gblack decreased Streptococcus and increased Ruminococcus and Allobaculum in hyperlipidemia rats. Some differential microbial genera relating to lipid metabolism were also determined, such as the Lachnospira and Ruminococcus in the Gblack group, and the Phascolarctobacterium, Dorea, Turicibacter, and Escherichia-Shigella in the Gbrown group. Notably, the beneficial effect of Gblack was stronger than Gbrown. To sum up, the dietary interventions of Gbrown/Gblack contributed to the remission of hyperlipidemia by alleviating the dysbiosis of gut microbiota.

Human liver tissue is composed of heterogeneous mixtures of different cell types and their cellular stoichiometry can provide information on hepatic physiology and disease progression. Deconvolution algorithms for the identification of cell types and their proportions have recently been developed for transcriptomic data. However, no method for the deconvolution of bulk proteomics data has been presented to date. Here, we show that proteomes, which usually contain less data than transcriptomes, can provide useful information for cell type deconvolution using different algorithms. We demonstrate that proteomes from defined mixtures of cell lines, isolated primary liver cells, and human liver biopsies can be deconvoluted with high accuracy. In contrast to transcriptome-based deconvolution, liver tissue proteomes also provided information about extracellular compartments. Using deconvolution of proteomics data from liver biopsies of 56 patients undergoing Roux-en-Y gastric bypass surgery we show that proportions of immune and stellate cells correlate with inflammatory markers and altered composition of extracellular matrix proteins characteristic of early-stage fibrosis. Our results thus demonstrate that proteome deconvolution can be used as a molecular microscope for investigations of the composition of cell types, extracellular compartments, and for exploring cell-type specific pathological events. We anticipate that these findings will allow the refinement of retrospective analyses of the growing number of proteome datasets from various liver disease states and pave the way for AI-supported clinical and preclinical diagnostics.

A novel penalty contact constitution was developed to replicate the hysteresis memory effect observed in contact interfaces. On this basis, a refined finite element analysis (FEA) was performed to study the stick–slip friction contact behavior of bolted joint interfaces. The analysis was validated by comparing it with the experimental hysteresis loops in the literature. The simulated hysteresis loops were subsequently used to identify four parameters of the Iwan model. Additionally, the effects of bolt clamping, friction coefficient, and excitation amplitude were individually examined. It was found that the deterioration in bolt clamping performance resulted in a decrease in both the equivalent joint stiffness and energy dissipation. Similarly, the reduction in the friction coefficient yielded a comparable impact. Furthermore, the identified model parameters of critical stick–slip force and displacement exhibited a quasi-linear relationship to the bolt preload and friction coefficient.

Deploying reconfigurable intelligent surface (RIS) to enhance wireless transmission is a promising approach. In this paper, we investigate large-scale multi-RIS-assisted multi-cell systems, where multiple RISs are deployed in each cell. Different from the full-buffer scenario, the mutual interference in our system is not known a priori, and for this reason we apply the load coupling model to analyze this system. The objective is to minimize the total resource consumption subject to user demand requirement by optimizing the reflection coefficients in the cells. The cells are highly coupled and the overall problem is non-convex. To tackle this, we first investigate the single-cell case with given interference, and propose a low-complexity algorithm based on the Majorization-Minimization method to obtain a locally optimal solution. Then, we embed this algorithm into an algorithmic framework for the overall multi-cell problem, and prove its feasibility and convergence to a solution that is at least locally optimal. Simulation results demonstrate the benefit of RIS in time-frequency resource utilization in the multi-cell system.

This paper considers the motion energy minimization problem for a robot that uses millimeter-wave (mm-wave) communications assisted by an intelligent reflective surface (IRS). The robot must perform tasks within given deadlines, and it is subject to quality of service (QoS) constraints. This problem is crucial for fully automated factories governed by the binomial of autonomous robots and new generations of mobile communications, i.e., 5G and 6G. In this new context, robot energy efficiency and communication reliability remain fundamental problems that couple in optimizing robot trajectory and communication QoS. More precisely, to account for the mutual dependency between robot position and communication QoS, robot trajectory and beamforming at the IRS and access point all need to be optimized. We present a solution that can decouple the two problems by exploiting mm-wave channel characteristics. Then, a closed-form solution is obtained for the beamforming optimization problem, whereas the trajectory is optimized by a novel successive-convex optimization-based algorithm that can deal with abrupt line-of-sight (LOS) to non-line-of-sight (NLOS) transitions. Specifically, the algorithm uses a radio map to avoid obstacles and poorly covered areas. We prove that the algorithm can converge to a solution satisfying the Karush-Kuhn-Tucker conditions. The simulation results show a fast convergence rate of the algorithm and a dramatic reduction of the motion energy consumption with respect to methods that aim to find maximum-rate trajectories. Moreover, we show that passive IRSs represent a powerful solution to improve the radio coverage and motion energy efficiency of robots.

This paper describes the design of a low-noise, high-speed readout-integrated circuit for use in InGaAs infrared focal plane arrays, and analyzes the working principle and noise index of the pixel circuit in detail. The design fully considers the dynamic range, noise, and power consumption of the pixel circuit in which a capacitance transimpedance amplifier structure is adopted as the input stage circuit, and chip fabrication via an XFAB 0.18 µm CMOS process is successfully realized. The ROIC adopts monolithic integration and implements various functions, such as windowing, subsampling, and different integration and readout modes. The ROIC reached an array scale of 32 × 32, a frame rate of 100 Hz, and a readout rate of 20 Mbps with an analog power consumption of less than 52 mW. The measurement results show that the input reference noise can be reduced to 143 e- via the CDS, and the fully customized scheme has certain advantages in the research of high-performance ROICs.

Abstract We consider leveraging the joint potential of non‐orthogonal multiple access (NOMA) and traffic offloading to benefit cell‐edge users in multi‐cell scenarios. We formulate the edge‐driven throughput maximisation problem where both the offloading decision and resource allocation are to be optimised, accounting for the impact of the inter‐cell interference on the decoding order in NOMA. The inter‐cell interference is not given constants as it is influenced by resource allocation. Therefore the non‐orthogonal multiple access (NOMA) decoding order is not known a priori. We explore the problem by decomposing it into two subproblems. By analysis of structural properties, we derive algorithm modules which interact iteratively for reciprocity, forming the overall algorithm. Numerical results show that the proposed scheme considerably improves the cell‐edge throughput, compared with the conventional scheme of orthogonal multiple access without traffic offloading.

Biochar is important for soil improvement, fertilizer innovation, and greenhouse gas reduction. In this paper, Mg-modified biochar was prepared from rice and corn straw and mixed with soil at a 1% (w/w) addition in an indoor soil simulation experiment to study the effect of Mg-modified biochar on the chemical properties of acidic soil. The results showed that the addition of Mg-modified biochar reduced soil acidity and improved soil fertility. Compared with the control group, the Mg-modified biochar treatment significantly increased the concentrations of available potassium, available phosphorus, total phosphorus, organic carbon and exchangeable calcium and magnesium in the soil, and effectively increased the concentration of total nitrogen. Rice straw Mg-modified biochar treatment was more effective in increasing the soil-available potassium, available phosphorus, total phosphorus and exchangeable magnesium concentration, while corn straw Mg-modified biochar was more effective in increasing the soil organic carbon and exchangeable calcium concentration. In addition, the high pyrolysis temperature of Mg-modified biochar was more effective in promoting the soil-available potassium, available phosphorus and total nitrogen concentration, while the low pyrolysis temperature of Mg-modified biochar was more effective in promoting soil alkaline nitrogen, exchangeable calcium and magnesium.

Abstract Background Deep vein thrombosis (DVT) is associated with stroke. Here, we hypothesize that genes associated with DVT may also play roles in the development of stroke. Methods we firstly conducted large-scale literature based disease-gene relationship data analysis to explore the genes implicated with DVT and stroke. Further, a mega-analysis was conducted for each of these genes that were linked to DVT but not stroke, using 11 independent stroke RNA expression datasets (176 stroke cases and 102 healthy controls). Then, a multiple linear regression (MLR) model was employed to study possible influential factors on the gene expression levels in stroke. After that, a functional pathway analysis was performed to identify the potential biological linkage between stroke and the target genes suggested by mega-analysis. Results Over 81.10% genes implicated with DVT also suggested an association with stroke. Among the 24 DVT-specific genes, one DVT-inhibiting gene, SP1, presented significantly increased expression in stroke (LFC = 1.34, p-value = 0.0045). Pathway analysis showed that SP1 may play a therapeutic role in post-stroke patients by promoting multiple of stroke-inhibitors. Moreover, geographical region was indicated as an influential factor on the expression levels of SP1 in stroke samples (p-value = 0.037). Conclusion Our results suggested that DVT inhibitor SP1 could be a novel therapeutic target gene for post-stroke treatment. Further study of the potential relations between SP1 and stroke was guaranteed.

Content caching at the edge of network is a promising technique to alleviate the burden of backhaul networks. In this paper, we consider content caching along time in a base station with limited cache capacity. As the popularity of contents may vary over time, the contents of cache need to be updated accordingly. In addition, a requested content may have a delivery deadline within which the content needs to be obtained. Motivated by these, we address optimal scheduling of content caching in a time-slotted system under delivery deadline and cache capacity constraints. The objective is to minimize a cost function that captures the load of backhaul links. For our optimization problem, we prove its NP-hardness via a reduction from the Partition problem. For problem solving, via a mathematical reformulation, we develop a solution approach based on repeatedly applying a column generation algorithm and a problem-tailored rounding algorithm. In addition, two greedy algorithms are developed based on existing algorithms from the literature. Finally, we present extensive simulations that verify the effectiveness of our solution approach in obtaining near-to-optimal solutions in comparison to the greedy algorithms. The solutions obtained from our solution approach are within 1.6% from global optimality.

In the areas of catalysis and renewable energy conversion, the development of active and stable electrocatalysts continues to be a highly desirable and crucial aim. Single-atom catalysts (SACs) provide isolated active sites, high selectivity, and ease of separation from reaction systems, becoming a rapidly evolving research field. Unfortunately, the real roles and key factors of the supports that govern the catalytic properties of SACs remain uncertain. Herein, by means of the density functional theory calculations, in the Au/WSSe SAC, built by filling the single Au atom at the S vacancy site in WSSe monolayer, we find that the powerful binding between the single Au atom and the support is induced by the Au d and W d orbital hybridization, which is caused by the electron transfer between them. The extra tensile strain could further stabilize the Au/WSSe by raising the transfer electron and enhancing the orbital hybridization. Moreover, by dint of regulating the antibonding strength between the single Au atom and H atom, the extra tensile strain is capable of changing the electric-catalytic hydrogen evolution reaction (HER) performance of Au/WSSe as well. Remarkably, under the 1% tensile strain, the reaction barrier (0.06 eV) is only one third of that of free state. This theoretical work not only reveals the bonding between atomic sites and supports, but also opens an avenue to improve the electric-catalytic performance of SACs by adjusting the bonding with outer factors.

Humans cannot perceive the minimal level of difference in the pixel variation. To overcome the problem, the concept of just-noticeable difference (JND) was proposed. JND measures the minimal amount that must be changed for the variation to be detectable by humans. However, JND characteristics were not considered in the traditional perceptual measurements. In this paper, we provide a comprehensive survey of the latest JND-related studies. First, we provide an extensive overview of JND models. JND models comprise human visual system characteristics and masking effects. Next, we introduce the applications of JND models in the perceptual quality evaluation and video compression coding, especially in applying machine-learning techniques to JND prediction. In addition to a thorough summary of the recent progress and applications of JND, we summarize some unsolved technical challenges. We believe that our overview and findings can provide some insights into the related issues and future research directions in video coding.

We investigate the effect of bursty traffic in a long term evolution (LTE) and Wi-Fi aggregation (LWA)-enabled network. The LTE base station routes packets of the same IP flow through the LTE and Wi-Fi links independently. We motivate the use of superposition coding at the LWA-mode Wi-Fi access point (AP) so that it can serve LWA users and Wi-Fi users simultaneously. A random access protocol is applied in such system, which allows the native-mode AP to access the channel with probabilities that depend on the queue size of the LWA-mode AP to avoid impeding the performance of the LWA-enabled network. We analyze the throughput of the native Wi-Fi network and the delay experienced by the LWA users, accounting for the native-mode AP access probability, the traffic flow splitting between LTE and Wi-Fi, and the operating mode of the LWA user with both LTE and Wi-Fi interfaces. Our results show some fundamental tradeoffs in the throughput and delay behavior of LWA-enabled networks, which provide meaningful insight into the operation of such aggregated systems.

In the present work, a rapid, accurate, and cost-effective method was developed for the simultaneous quantification of aflatoxins and benzo(a)pyrene in lipid matrices, using solid-phase extraction (SPE) via humic acid-bonded silica (HAS) sorbents, followed by high-performance liquid chromatography coupled with photochemical post-column reactor fluorescence spectroscopy (HPLC–PHRED–FLD) analysis. The major parameters of extraction efficiency and HPLC–PHRED–FLD analysis were investigated and this method was fully validated. The limits of quantification and the limits of detection were 0.05–0.30 and 0.01–0.09 µg kg−1, respectively. The recoveries were 66.9%–118.4% with intra-day and inter-day precision less than 7.2%. The results of 80 oil samples from supermarkets indicated a high occurrence of BaP, and most of concentrations were within the requirements of EU and China food safety regulations. This is the first utilization of HAS–SPE HPLC–PHRED–FLD to simultaneously analyze the occurrence of aflatoxins and benzo(a)pyrene in vegetable oils.

Myoglobin is a key chemical component that determines meat’s color and affects consumers’ purchase intentions. In this work, we firstly identified the promoter sequence of the Mb gene from the primary assembly of high-throughput genome sequencing in pigs, and predicted its potential transcription factors by LASAGNA. Through the data mining of the mRNA expression profile of longissimus dorsi muscle of different pig breeds, we constructed a hierarchical interplay network of Mb-TFs (Myoglobin-Transcription Factors), consisting of 16 adaptive transcription factors and 23 secondary transcription factors. The verification of gene expression in longissimus dorsi muscle showed that the Mb mRNA and encoded protein were significantly (p < 0.05) more abundant in Bama pigs than Yorkshire pigs. The qRT-PCR (Real-Time Quantitative Reverse Transcription PCR) validation on genes of the Mb-TFs network showed that FOS, STAT3, STAT1, NEFL21, NFE2L2 and MAFB were significant positive regulatory core transcription factors of Mb-TFs network in Bama pigs, whereas ATF3 was the secondary transcription factor most responsible for the activation of the above transcription factors. Our study provides a new strategy to unravel the mechanism of pork color formation, based on public transcriptome and genome data analysis.

Abstract Background A gasotransmitter hydrogen sulfide (H2S) plays an important physiological and pathological role in cardiovascular system. Ischemic post-conditioning (PC) provides cardioprotection in the young hearts but not in the aged hearts. Exogenous H2S restores PC-induced cardioprotection by inhibition of mitochondrial permeability transition pore opening and oxidative stress and increase of autophagy in the aged hearts. However, whether H2S contributes to the recovery of PC-induced cardioprotection via down-regulation of endoplasmic reticulum stress (ERS) in the aged hearts is unclear. Methods The aged H9C2 cells (the cardiomyocytes line) were induced using H2O2 and were exposed to H/R and PC protocols. Cell viability was observed by CCK-8 kit. Apoptosis was detected by Hoechst 33342 staining and flow cytometry. Related protein expressions were detected through Western blot. Results In the present study, we found that 30 μM H2O2 induced H9C2 cells senescence but not apoptosis. Supplementation of NaHS protected against H/R-induced apoptosis, the expression of cleaved caspase-3 and cleaved caspase-9 and the release of cytochrome c. The addition of NaHS also counteracted the reduction of cell viability caused by H/R and decreased the expression of GRP 78, CHOP, cleaved caspase-12, ATF 4, ATF 6 and XBP-1 and the phosphorylation of PERK, eIF 2α and IRE 1α. Additionally, NaHS increased Bcl-2 expression. PC alone did not provide cardioprotection in H/R-treated aged cardiomyocytes, which was significantly restored by the supplementation of NaHS. The beneficial role of NaHS was similar to the supply of 4-PBA (an inhibitor of ERS), GSK2656157 (an inhibitor of PERK), STF083010 (an inhibitor of IRE 1α), respectively, during PC. Conclusion Our results suggest that the recovery of myocardial protection from PC by exogenous H2S is associated with the inhibition of ERS via down-regulating PERK-eIF 2α-ATF 4, IRE 1α-XBP-1 and ATF 6 pathways in the aged cardiomyocytes.

The deformation of Muzhailing deep tunnel is about 2.3 m in the process of construction, which is difficult to be controlled by the traditional “anchor-grouting integration” support system. This paper deeply analyzes the geological characteristics, rock mechanics characteristics, and surrounding rock failure characteristics of Muzhailing tunnel. The deformation mechanism and the failure of the support system are analyzed through the numerical simulation, theoretical analysis, and field test. The authors propose support measures suitable for Muzhailing tunnel based on the analysis results. The maximum buried depth is 600 m, and the engineering rock mass at the depth has nonlinear physical and mechanical phenomenon. The maximum principal stress of Muzhailing tunnel is 25.7 MPa, which belongs to high-stress joint swelling soft rock tunnel. The NPR cable can achieve large deformation under the condition of constant support resistance. The authors put forward the coupling support mode of “NPR cable + steel arch frame + concrete,” which is based on the idea of transforming the composite deformation mechanism to a single type. The stress concentration appears in the range of 12 m in the surrounding rock circle, and the lateral and vertical stress distributions are relatively symmetrical after the improved support. The circumferential strain of the surrounding rock is greatly reduced, and the range of strain is reduced by 10%. The field monitoring results show that the new support system can well control the large soft rock deformation of Muzhailing tunnel (0.5 m). The support strategy proposed can effectively control the large deformation and promote the formation of new support concept for deep tunnel.

In this paper, we analyze the probabilistic cooperation of a full-duplex relay in a multiuser random-access network. The relay is equipped with on/off modes for the receiver and the transmitter independently. These modes are modeled as probabilities by which the receiver and the transmitter are activated. We provide analytical expressions for the performance of the relay queue, such as arrival and service rates, stability conditions, and the average queue size. We optimize the relay's operation setup to maximize the network-wide throughput while, simultaneously, we keep the relay's queue stable and lower the relay's receptions and transmissions. Furthermore, we study the effect of the SINR threshold and the self-interference coefficient on the per-user and network-wide throughput. For low SINR threshold, we show under which circumstances it is beneficial to switch off the relay completely, or switch off the relay's receiver only.

We investigate several important properties of an Adaptive Energy Detector (AED), which is originally proposed according to the Generalized Likelihood Ratio Test (GLRT), under the assumption that the signal steering vector is completely unknown. We show that the AED coincides with the Rao and Wald tests. We also give the exact statistical distribution, according to which one can easily derive the Probabilities of Detection (PD) and False Alarm (PFA), and we use the AED to design a parametrically tunable signal-mismatch detector. Compared to existing tunable detectors, the novel tunable detector is more flexible in governing the rejection of the mismatched signal; moreover, for the matched signal, the tunable detector can provide a higher PD than existing detectors. Two scalars, called the tunable parameters, control this functionality.

In wireless networks, the notion of compatible set refers to a set of radio links that can be simultaneously active with a tolerable interference. Finding a compatible set with maximum weighted revenue from the parallel transmissions is an important optimization subproblem for resource management in wireless networks. For this subproblem, two basic ways of expressing the signal-to-interference-plus-noise-ratio within integer programming are used, differing in the number of variables and the quality of the upper bound given by their linear relaxations. To our knowledge, there is no systematic study comparing the effectiveness of these two approaches to the compatible set optimization problem. The contribution of the article is twofold. First, we present a comparison of the two basic approaches, and, second, we introduce matching inequalities that improve the upper bounds achievable with the two basic approaches. The matching inequalities are generated within the branch-and-cut process using a minimum odd-cut generation procedure based on the Gomory–Hu tree algorithm. The article presents results of a numerical study illustrating our statements and findings.

Many downscaling techniques have been developed in the past few years for projection of station-scale hydrological variables from large-scale atmospheric variables to assess the hydrological impacts of climate change. To improve the simulation accuracy of downscaling methods, the Bayesian Model Averaging (BMA) method combined with three statistical downscaling methods, which are support vector machine (SVM), BCC/RCG-Weather Generators (BCC/RCG-WG), and Statistics Downscaling Model (SDSM), is proposed in this study, based on the statistical relationship between the larger scale climate predictors and observed precipitation in upper Hanjiang River Basin (HRB). The statistical analysis of three performance criteria (the Nash-Sutcliffe coefficient of efficiency, the coefficient of correlation, and the relative error) shows that the performance of ensemble downscaling method based on BMA for rainfall is better than that of each single statistical downscaling method. Moreover, the performance for the runoff modelled by the SWAT rainfall-runoff model using the downscaled daily rainfall by four methods is also compared, and the ensemble downscaling method has better simulation accuracy. The ensemble downscaling technology based on BMA can provide scientific basis for the study of runoff response to climate change.

Increasing evidence has suggested that microRNAs (miRNAs) play an important role in the initiation and progression of hepatocellular carcinoma (HCC). Here, we identified a novel tumor suppressive miRNA, miR-377, and investigated its role in HCC. The expression of miR-377 in HCC tissues and cell lines was detected by real-time reverse-transcription PCR. The effects of miR-377 on HCC cell proliferation and invasion were also investigated. Western blot and luciferase reporter assay were used to identify the direct and functional target of miR-377. The expression of miR-377 was markedly downregulated in human HCC tissues and cell lines. MiR-377 can dramatically inhibit cell growth and invasion in HCC cells. Subsequent investigation revealed that T lymphoma invasion and metastasis 1 (TIAM1) was a direct and functional target of miR-377 in HCC cells. Overexpression of miR-377 impaired TIAM1-induced promotion of proliferation and invasion in HCC cells. Finally, miR-377 is inversely correlated with TIAM1 expression in human HCC tissues. These findings reveal that miR-377 functions as a tumor suppressor and inhibits the proliferation and invasion of HCC cells by targeting TIAM1, which may consequently serve as a therapeutic target for HCC patients.