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Abstract Background We aimed to investigate the post-cessation T2DM risk in male NAFLD and NAFLD-free smokers in a 7-year cohort study. Methods The study population was male adults who underwent annual health checkups in a 7-year cohort study. Recent quitters were categorized into four groups based on their weight gain during follow-up:

To meet the demand of accurate water level prediction of the reservoir in Liuxihe River Basin, this paper proposes an improved long short-term memory (LSTM) neural network based on the Bayesian optimization algorithm and wavelet decomposition coupling. Based on the improved model, the water levels of Liuxihe Reservoir and Huanglongdai Reservoir are simulated and predicted by the 1 h prediction length, and the prediction accuracy of the improved model is verified separately by the 3, 6 and 12 h prediction lengths. The results show that: first, Bayesian optimization coupling can significantly reduce the average absolute error and root mean square error of the model and improve the overall prediction accuracy, but this algorithm is insufficient in the optimization of model extremum; Wavelet decomposition coupling can significantly reduce the outliers in model prediction and improve the accuracy of extremum, but it plays relatively weaker role in the overall optimization of the model. Second, by the prediction lengths of 1, 3, 6 and 12 h, the improved model based on the LSTM neural network and coupled with Bayesian optimization and wavelet decomposition is superior to Bayesian optimization and wavelet decomposition coupling model in overall prediction accuracy and prediction accuracy of extremum. HIGHLIGHTS Quantifying the impacts of coupling model on reservoir water level.; Proposing an improved prediction model for long short-term memory neural network.; Quantifying the impacts of different input characteristics on the model.;

Compound flooding from rainfall and storm tides is prone to occur in coastal cities. The identification of them is essential for controlling urban flooding. First, the dependence between rainfall and storm tides is quantified by Kendall's τ, Spearman's ρ, and tail dependence coefficient. Then, a bivariate copula-based probability distribution model is built to calculate the joint and conditional probability of rainfall and storm tides. Finally, MK and SQMK methods are employed to detect the trends of the dependence and joint probability. The results show that: (1) The dependence between strong rainfall and corresponding storm tides is much higher than that of small rainfall and storm tides, and the effect of tropical cyclones may be one of the reasons. (2) The dependence between rainfall and storm tides is the largest in October and the smallest in July. More attention should be paid to the compound flooding caused by rainfall and storm tides in October for Haikou. (3) The upper tail dependence coefficient of the rainfall and storm tides is significantly greater than the lower tail dependence coefficient and exhibits a significant positive trend. The results can provide additional insights into the effect of rainfall and storm tides for coastal flood management. HIGHLIGHTS The compound effects of rainfall and storm tides were investigated from different perspectives.; Trends of the compound risk were analyzed by the copula and Mann–Kendall method.; Significant increasing trends of joint probability were detected after 1988–1992.; Compound event of rainfall and storm tides is more likely to occur when a high storm tide event has occurred.;

Abstract Impulse noise (IN) widely exists in many communication systems, which seriously affects the performance of OFDM communication systems. A joint channel and IN estimation method based on all subcarriers is designed. This method uses a sparse Bayesian learning (SBL) algorithm incorporating forward–backward Kalman filter (FB-Kalman) to tackle the problem of joint channel and IN estimation and data detection for OFDM systems. Firstly, the channel impulse response and IN are regarded as unknown sparse vectors, and a SBL framework using all subcarriers is proposed to estimate the unknown vector. The SBL theory is used based on the prior distribution of variables, and then the forward–backward joint system is established, which applies the data detection simultaneously. We also propose the FB-Kalman implementation algorithm by using the expectation maximization updates. Explicit expressions of mean and covariance matrix of the posterior distribution are derived in the E-step. Simulation results show that the proposed algorithm improves the normalized mean square error and bit error rate performance of OFDM system in the presence of IN communication environment.

Under normal conditions, heat shock proteins work in unison through dynamic protein interactions collectively referred to as the “chaperome.” Recent work revealed that during cellular stress, the functional interactions of the chaperome are modified to form the “epichaperome,” which results in improper protein folding, degradation, aggregation, and transport. This study is the first to investigate this novel mechanism of protein dishomeostasis in traumatic brain injury (TBI). Male and female adult, Sprague-Dawley rats received a lateral controlled cortical impact (CCI) and the ipsilateral hippocampus was collected 24 h 1, 2, and 4 weeks after injury. The epichaperome complex was visualized by measuring HSP90, HSC70 and HOP expression in native-PAGE and normalized to monomeric protein expression. A two-way ANOVA examined the effect of injury and sex at each time-point. Native HSP90, HSC70 and HOP protein expression showed a significant effect of injury effect across all time-points. Additionally, HSC70 and HOP showed significant sex effects at 24 h and 4 weeks. Altogether, controlled cortical impact significantly increased formation of the epichaperome across all proteins measured. Further investigation of this pathological mechanism can lead to a greater understanding of the link between TBI and increased risk of neurodegenerative disease and targeting the epichaperome for therapeutics.

Aroma is a critical component of the flavor and quality of beverages. Among the volatile chemicals responsible for fragrance perception, sulfur compounds are unique odorants due to their extremely low odor threshold. Although trace amounts of sulfur compounds can enhance the flavor profile of beverages, they can lead to off-odors. Sulfur compounds can be formed via Maillard reaction and microbial metabolism, imparting coffee aroma and altering the flavor of beverages. In order to increase the understanding of sulfur compounds in the field of food flavor, 2-furfurylthiol (FFT) was chosen as a representative to discuss the current status of their generation, sensory impact, enrichment, analytical methods, formation mechanisms, aroma deterioration, and aroma regulation. FFT is comprehensively reviewed, and the main beverages of interest are typically baijiu, beer, wine, and coffee. Challenges and recommendations for FFT are also discussed, including analytical methods and mechanisms of formation, interactions between FFT and other compounds, and the development of specific materials to extend the duration of aroma after release.

Moist-induced electricity generators (MEGs) that harvest electric energy from water or moist has been considered as an efficient and sustainable technique to meet the increasingly serious energy crisis. However, the low output performance, non-degradability and complicated preparation processes of current MEGs have hindered their practical application. Herein, we report a highly-efficient, green and easily fabricated wood-derived moist-induced electricity generator (WMEG) by simply soaking natural wood in the Chinese ink. The generated electricity based on streaming potential comes from when water molecules flow through the charged channel surface of ink-coated wood driven by capillary force and evaporation. As a result, a continuous open-circuit voltage of about 250 mV was achieved from a single WMEG under ambient conditions, and the electrical signal could maintain stale for over 72 h. Moreover, the power output performance of the obtained wood generator can be enhanced by simple series or parallel connection for practical applications, and an electronic calculator can be powered by six-series-connected devices. This current study provides insights for the development of low-cost and sustainable MEGs without complex chemical reaction.

The rich impulsive noise in the power line channel poses a huge challenge to the design of MIMO-OFDM transceiver.To solve this problem, a design scheme that can jointly estimate the channel and impulsive noise was proposed, which exploited the parametric sparsity of the classical multipath model and the sparsity of the time domain impulsive noise.In this scheme, the unknown channel model parameters and the impulsive noise were jointly regarded as a sparse vector.By observing the spatial correlation of MIMO system, a compressed sensing model based on multiple measurement vectors was constructed.The multiple response sparse Bayesian learning theory was introduced to jointly estimate the MIMO channel parameters and impulsive noise.The simulation results show that, compared with the traditional receiver scheme that considers MIMO channel estimation and impulsive noise suppression separately, the receiver proposed has a significant improvement in channel estimation performance and bit error rate performance.

Aiming at the impulsive noise occurring in MIMO-OFDM systems， a joint channel and impulsive noise estimation method based on the multiple measurement vector compressed sensing theory was proposed.The channel impulse response and the impulsive noise were combined to form a row sparse matrix to be estimated， and a multiple measurement vector compressed sensing model based on all subcarriers was constructed.As the measurement matrix was partially unknown due to the presence of unknown transmitted symbols in data tones， the multiple response sparse Bayesian learning theory and expectation maximization framework were adopted to jointly estimate the channel impulse response， the impulsive noise， and the data symbols which were regarded as unknown parameters.Compared with the existing methods， the proposed method not only utilizes all subcarriers but also does not use any a priori information of the channel and impulsive noise.The simulation results show that the proposed method achieves significant improvement on the channel estimation and bit error rate performance.

Abstract Background Artificial intelligence (AI) assistance has been considered as a promising way to improve colonoscopic polyp detection, but there are limited prospective studies on real‐time use of AI systems. Methods We conducted a prospective, multicenter, randomized controlled trial of patients undergoing colonoscopy at six centers. Eligible patients were randomly assigned to conventional colonoscopy (control group) or AI‐assisted colonoscopy (AI group). AI assistance was our newly developed AI system for real‐time colonoscopic polyp detection. Primary outcome is polyp detection rate (PDR). Secondary outcomes include polyps per positive patient (PPP), polyps per colonoscopy (PPC), and non‐first polyps per colonoscopy (PPC‐Plus). Results A total of 2352 patients were included in the final analysis. Compared with the control, AI group did not show significant increment in PDR (38.8% vs. 36.2%, p = 0.183), but its PPC‐Plus was significantly higher (0.5 vs. 0.4, p

This study aims to fully explore the influence of rock joint roughness in the slope stability analysis of an open mine. Therefore, based on the least squares parameter estimation method, a generalized shear strength parameter coupling roughness, which is used to evaluate a slope design, was established by a matching formula reflecting the relationship between the roughness coefficient and the shear strength parameter. Firstly, to verify and calibrate the model, physical direct shear tests were conducted on serrated rock joints, and the effect of roughness was analyzed qualitatively. The results show that an increase in tooth height increases the internal friction angle but decreases cohesion. Therefore, the rock joint direct shear test numerical model by PFC-2D was established and compared with the physical test curve, effectively verifying its correctness. The relationship between cohesion c and internal friction angle φ with roughness coefficient JRC was further quantified, and the new model was then fitted to characterize the relationship between roughness and shear strength parameters. This method is applied to the design optimization of an open pit mine slope. The new parameters are input to GeoSMA-3D, which is used to search for the key block of a bedding slope on an open-pit mine, to optimize the design of the slope.

Background and aim: Previous observational studies have suggested a paradoxical relationship between iron status and the risk of non-alcoholic fatty liver disease (NAFLD). Observed associations in these epidemiological studies fail to show sequential temporality and suffer from problems of confounding. Therefore, we performed a bidirectional two-sample Mendelian randomization (MR) to evaluate the relationship between serum iron status and NAFLD. Methods: The inverse weighted method (IVW) meta-analysis with the fixed-effect model was the main method to estimate the relationship between iron status, including serum ferritin, iron, transferrin saturation (TSAT) and total iron-binding capacity (TIBC), and NAFLD. Weighted median, penalized weighted median, and MR Robust Adjusted Profile Score (MR RAPS) methods were used as additional analyses. Sensitivity analyses were performed with Cochran’s Q test, MR–Egger regression, Steiger filtering, and the MR PRESSO test. Results: Iron status, including serum ferritin, iron, and TSAT, was associated with an increased risk of NAFLD (odds ratio (OR) (95% confidence interval (CI)): 1.25 (1.06, 1.48); 1.24 (1.05, 1.46), 1.16 (1.02, 1.31), respectively). In contrast, minimal effects of NAFLD on serum ferritin, iron, TSAT, and TIBC were observed (OR (95% CI): 1.01 (1.00, 1.02), 1.01 (1.00, 1.02), 1.03 (1.01, 1.05), 1.03 (1.01, 1.05), respectively). Conclusions: Our findings corroborated the causal associations between serum ferritin, iron, TSAT, and NAFLD, which might suggest the potential benefits of iron-related therapy. In addition, NAFLD might, in turn, slightly affect iron homeostasis indicated as serum ferritin, iron, TSAT, and TIBC, but this needs to be further confirmed.

The application of cooperative multicast in a non-orthogonal multiple access (NOMA) system and its performances was studied where a mixed service scenario consisting of a number of the multicast users and one unicast user was employed.In such a system,a cooperative relay path selection strategy was used and a best channel conditioned multicast user was selected as relay user to relay the unicast user’s signal.The unicast user outage probability and the relay user’s capacity in closed-form were then derived.Mont Carlo simulation results validate the analysis and show that the proposed scheme significantly enhances outage probability for unicast user while maintaining the same ergodic capacity for the relay user.

Impulsive noise interference can seriously affect the performance of underwater acoustic communication systems.An impulsive noise suppression method based on regularized threshold iteration was presented.Firstly,the null subcarrier matrix was used to separate impulsive noise from Gaussian white noise and useful signals.Then,based on the theory of compressed sensing,the impulsive noise estimation problem was transformed into a regularization problem by introducing a threshold iteration,and the impulsive noise was estimated by using a threshold function to obtain the estimated value of the impulsive noise.Finally,the estimated impulsive noise was subtracted from the received signal.The simulation results show that the proposed method can effectively reduce the bit error rate (BER) and mean square error (MSE),and improve the reliability of signal transmission in underwater acoustic communication environment.

A novel cooperative location method based on time-of-arrival in wireless senor networks was proposed. Firstly, the optimization problem for the target location was established. Secondly, the mixed semi-positive definite and second-order cone relaxation techniques were used to convert the original non-convex problem into a convex optimization problem. In this way, a fast suboptimal solution to the original problem was obtained. Finally, computer simulations show that the proposed method has lower root mean square error (RMSE) which is closer to the Cramer-Rao lower bound (CRB).

This paper investigates the resource allocation problem in device-to-device (D2D) communications underlaying a non-orthogonal multiple access (NOMA)-based cellular network with energy harvesting, where the energy harvesting-powered D2D communications share the downlink resources of the cellular network. To fully exploit the high-data-rate D2D links in this system, a two-phase framework is proposed for D2D users. In particular, the D2D users harvest energy from the base station (BS) in the first phase and then transmit their own information using the harvested energy in the second one. Meanwhile, the D2D communications could cause severe interference to cellular users (CUs) and hence probably ruin the SIC decoding order of the CUs. To deal with this issue, joint power allocation and time scheduling scheme is proposed to maximize the throughput of the D2D links while guaranteeing the quality of service (QoS) for each CU. Through rigorous derivation, the optimal power control and time scheduling parameters are analyzed to simplify the optimization problem formulation. The closed-form optimal solution is derived in some cases. In other cases, a gradient-based algorithm is employed to find an appropriate sub-optimal solution. The simulation results are demonstrated to validate the superiority of the proposed scheme over the conventional orthogonal multiple access (OMA) scheme.

The impulsive noise can deteriorate sharply the performance of orthogonal frequency division multiplexing (OFDM) systems. In this paper, we propose a novel joint channel impulse response estimation and impulsive noise mitigation algorithm based on compressed sensing theory. In this algorithm, both the channel impulse response and the impulsive noise are treated as a joint sparse vector. Then, the sparse Bayesian learning framework is adopted to jointly estimate the channel impulse response, the impulsive noise, and the data symbols, in which the data symbols are regarded as unknown parameters. The Cramér-Rao Bound is derived for the benchmark. Unlike the previous impulsive noise mitigation methods, the proposed algorithm utilizes all subcarriers without any a priori information of the channel and impulsive noise. The simulation results show that the proposed algorithm achieves significant performance improvement on the channel estimation and bit error rate performance.

In this paper, the target node localization problems based on hybrid RSS-AOA measurements in both noncooperative and cooperative three-dimensional (3-D) wireless sensor networks (WSNs) are discussed. By using novel error approximate expressions for both received signal strength (RSS) and angle-of-arrival (AOA) measurement models, new estimators based on the least squares (LS) criterion are proposed. These estimators can be transformed into mixed semi-definite programming (SDP) and second-order cone programming (SOCP) problems by applying convex relaxation techniques. In addition, the closed-form Cramer-Rao lower bound (CRLB) of the estimator on hybrid measurements in cooperative WSNs is also derived. Theoretical analysis and simulation results show that the Root Mean Square Error (RMSE) of the proposed hybrid RSS-AOA estimators is lower than that of the discussed estimators in both noncooperative and cooperative cases.

Helicobacter pylori (H. pylori) is proved to be the main pathogenic agent of various diseases, including chronic gastritis, gastric ulcer, duodenal ulcer, and gastric cancer. In addition, chronic cholecystitis and cholelithiasis are common worldwide, which are supposed to increase the total mortality of patients. Epidemiologic evidence on the relationship between H. pylori infection of the gallbladder and chronic cholecystitis/cholelithiasis still remains unclear. We conducted a systematic review and meta-analysis of overall studies to investigate the relationship between H. pylori infection of the gallbladder and chronic cholecystitis/cholelithiasis. Two researchers searched PubMed, Embase, and Cochrane Library databases to obtain all related and eligible studies published before July 2020. The pooled odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were calculated by the random-effects model. Subgroup analysis, heterogeneity, publication bias, and sensitivity analysis were also conducted. Twenty studies were included in the meta-analysis, involving 1735 participants and 1197 patients with chronic cholecystitis/cholelithiasis. Helicobacter species infection of the gallbladder was positively correlated with increased risk of chronic cholecystitis and cholelithiasis, especially H. pylori (OR = 3.05; 95% CI, 1.81–5.14; I2 = 23.5%). Besides, country-based subgroup analysis also showed a positive correlation between the gallbladder H. pylori positivity and chronic cholecystitis/cholelithiasis risk. For Asian and non-Asian country studies, the ORs were 4.30 (95% CI, 1.76–10.50; I2 = 37.4%) and 2.13 (95% CI, 1.23–3.70; I2 = 0.0%), respectively. The association was more obvious using the bile sample and urease gene primer. In conclusion, this meta-analysis provided evidence that there is a positive correlation between H. pylori infection in the gallbladder and increased risk of chronic cholecystitis and cholelithiasis.

A novel time-of-arrival–based localization algorithm in mixed line-of-sight/non-line-of-sight environments is proposed. First, an optimization problem of target localization in the known distribution of line-of-sight and non-line-of-sight is established, and mixed semi-definite and second-order cone programming techniques are used to transform the original problem into a convex optimization problem which can be solved efficiently. Second, a worst-case robust least squares criterion is used to form an optimization problem of target localization in unknown distribution of line-of-sight and non-line-of-sight, where all links are treated as non-line-of-sight links. This problem is also solved using the similar techniques used in the known distribution of line-of-sight and non-line-of-sight case. Finally, computer simulation results show that the proposed algorithms have better performance in both the known distribution and the unknown distribution of line-of-sight and non-line-of-sight environments.

Abstract In this paper, we consider the joint design of precoding matrices at both the source and relay nodes in a multi-relay system based on perfect and imperfect channel information, and propose the novel relay selection scheme based on log-likelihood ratio (LLR). Moreover, the symbol error rate (SER) for relay selection system based on proposed scheme is analyzed. At first, we design the combined precoding matrices based on respectively the maximum signal-to-noise ratio (SNR) with perfect channel state information (CSI) and the minimum SER of the single-relay system with imperfect CSI. Using decomposition of matrices, the joint design problems are solved with a two-step method, i.e., the first step is to determine the optimal direction of the precoding matrices, and the second step is to transform the optimization problem into two kinds of independent sub-problems which can be solved in lower complexity. Then, different from traditional relay selection based on signal-to-noise ratio, the relay node with the maximum LLR is chosen. Simulation results show the proposed selection scheme based on LLR is superior to the scheme based on SNR in the SER performance. Furthermore, the multi-relay system using the precoding matrices joint space-time coding technology can improve SER performance of the system effectively compared with only space-time coding or only precoding system.

Aiming at the impulsive noise occurring in OFDM systems,an impulsive noise mitigation algorithm based on compressed sensing theory was proposed.The proposed algorithm firstly treated the channel impulse response and the impulsive noise as a joint sparse vector by exploiting the sparsity of both them.Then the sparse Bayesian learning framework was adopted to jointly estimate the channel impulse response,the impulsive noise and the data symbols,in which the data symbols were regarded as unknown parameters.Compared with the existing impulsive noise mitigation methods,the proposed algorithm not only utilized all subcarriers but also did not use any a priori information of the channel and impulsive noise.The simulation results show that the proposed algorithm achieves significant improvement on the channel estimation and bit error rate performance.

In this paper, we address the target device localization problem in the asynchronous networks. For the purpose of saving power resources, the target device is not synchronized with the anchor nodes, but is only required to listen to the signals transmitted from the anchors, which, however, introduces two extra nuisance parameters: the target's clock skew and clock offset. By transforming the time-of-arrival measurements into time-difference-of-arrival measurements, the clock offset of the target's clock is eradicated. However, there still exists the unknown clock skew, which may degrade the localization performance. Since the range of the clock skew is usually known as a priori, we assume that it follows a uniform distribution within this range. By doing so, we take it as a part of measurement noise and estimate the target node position only. To estimate the target node position, we formulate a fractional programming problem and further show that it can be solved by solving one single mixed semidefinite and second-order cone program (SD/SOCP). Simulation results illustrate the superior performance of the proposed method over the existing methods.

In this paper, we consider the received signal strength-based cooperative localization problem in both known and unknown transmit power of target nodes. For the case of known transmit power, we treat the transmit power as a constant and derive a novel non-convex weighted least squares estimator which can be transformed into a second-order cone programming (SOCP) problem for reaching an efficient solution. For the case of unknown transmit power, we treat the transmit power as an additional unknown parameter and propose a hybrid maximum likelihood-SOCP algorithm to alternatively estimate the target node locations and transmit power. Simulation results confirm the effectiveness of the proposed methods in all considered settings.

In underlay cognitive radios, the primary-channel gain from a primary transmitter to a primary receiver (PU-Rx) and the cross-channel gain from a cognitive transmitter (SU-Tx) to the PU-Rx are crucial for the SU-Tx in controlling its transmit power when sharing spectrum with primary users (PUs). However, the non-cooperation between PUs and secondary users (SUs) makes it difficult for the SU-Tx to acquire the primary-channel and cross-channel gains, in particular when the channel reciprocity is not applicable. Most existing works focus on cross-channel gain estimation and are often based on the channel reciprocity. In this paper, we propose a scheme where the SU-Tx relays primary signals and transmits its own signals to the secondary receiver during the phase of channel gain estimation. Then, an estimation method is developed, which enables the SU-Tx to acquire the primary-channel and cross-channel gains simultaneously. The performance of the proposed estimator is analyzed. Numerical simulations are provided to validate the theoretical analysis and demonstrate the superior performance of the proposed method compared with state-of-the-art methods.

This paper concerns covariance matrix-based spectrum sensing over frequency-selective channels. The impact of frequency-selective channels on the covariance matrix of received signals is analyzed in frequency domain, and it is shown that the phases of channel spectra degrade the performance of covariance matrix-based detectors. To overcome this problem, we propose a new detector which employs only the magnitude spectra of received signals and therefore achieves considerable performance gain. Theoretical performance, in terms of the false-alarm and detection probabilities of the proposed detector, is analyzed. Simulation results verify our theoretical analyses and demonstrate the superior performance of the proposed detector.

Focusing on the impulsive noise mitigation in underwater acoustic communication,an impulsive noise mitigation method based on iteration adaptive approach was proposed.Firstly,by utilizing the orthogonality of the subcarriers in OFDM system,both the impulsive noise and background noise were separated from the signals.Then null tones matrix was used to construct a steering matrix and get the impulsive noise interference covariance matrix.Furthermore,a cost function based on weighted least squares approach was proposed and a close form expression for the impulsive noise was derived.Finally,the impulsive noise was mitigated by substracting the estimation of the impulse noise in the received signal.Simulation results show that the proposed algorithm can reduce the bit error rate (BER) efficiently and provide better performance,especially in high signal to impulsive noise ratio (SINR) case.

Aiming at the problem of the influence of multipath channel and impulse noise on the performance of power line carrier communication system,a transceiver scheme for power line communication system was proposed which could effectively combat the influence of multipath channel and impulse noise.Firstly,the power line channel impulse response and the impulsive noise in the time domain were jointly viewed as a sparse vector.Then,the sparse Bayesian learning theory was adopted to estimate the power line channel and impulse noise jointly.The impulse noise was removed and the channel gain was compensated at the receiver.The simulation result shows that the proposed receiver scheme has better performance than traditional receiver considering channel estimation and impulse noise suppression separately.

Abstract This paper proposes an inter-frame dynamic double threshold (IF-DDT) spectrum sensing algorithm in order to improve the sensing performance based on energy detection (ED) in cognitive radios (CRs). Based on both the activity model of the primary user (PU) and the sensing mechanism of the secondary user (SU), the proposed algorithm exploits the relationship between two adjacent sensing frames and designs dynamic double thresholds for each sensing frame to enhance spectrum sensing performance when the received energy cannot give a reliable local decision. The detection probability and false alarm probability of the proposed sensing scheme are analyzed, and an algorithm for searching the optimal dynamic double thresholds is derived with very low complexity according to the Neyman-Pearson (NP) test criterion. Theoretical analysis and simulation results show that the proposed algorithm outperforms the ED algorithm.

The influence of residual black liquor in pulp on wastewater pollution after the bleaching process was studied. The results show that the CODCr in bleaching effluent has a remarkable linearity with bleaching loss of pulps without residual black liquor. For pulps with some residual black liquor, more than 34% of the overall CODCr is produced by the residual black liquor. It follows that more effective washing to reduce the residual black liquor is an appropriate way to control the pollutant discharges from pulp and paper mill industry.

Wideband distributed cooperative spectrum sensing based on compressed sensing can not only reduce high sampling rate,but also improve the spectrum sensing performance in low signal to noise ratio environment.In order to further enhance the spectrum sensing performance,a wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization was proposed.In this algorithm,the next iterative reconstruction weights were determined according to the current iterative reconstructed spectrum signal,which can encourage the sub-band occupied by primary user to generate signal value and decrease the likelihood of incorrect reconstruction.Simulation results show that the proposed algorithm can not only increases the spectral reconstruction accuracy,but also reduces time and communication costs of the sensing process,and improves the spectrum sensing performance.

The performance of power line communication systems is seriously affected by impulsive noise.The compressed sensing theory has been applied for estimation in view of the sparse property of impulsive noise in the time domain.A compressed sensing method based on the iterative hard thresholding was proposed to estimate the impulsive noise.Firstly,the thresholding value was updatedby iteration,and then the thresholding function was used to estimate the impulsive noise.Finally,the impulsive noise was cancelled by subtracting the estimation value from the received signal.Simulation results show that the proposed method can efficiently estimate the impulsive noise and promote the performance bothinmean square error and signal to noise ratio.

To improve the reliability of spectrum sensing in cognitive radio system,a new cooperation spectrum sensing algorithm was proposed.In this algorithm,the property of the low probability between adjacent frames of the states change was used and then the decision was made by combing the energy value of the current sensing frame with that of the neighboring frame.Therefore,the proposed algorithm could decrease the miss detection probability in case of the instantaneous signal energy dropping when primary user used the licensed spectrum.Furthermore,theoretical expressions for detection probability and false alarm probability were derived.Finally,theoretical analysis and simulation results verify that the detection performance of the proposed algorithm is better than that of cooperative spectrum sensing which is based on the classical energy detection.

An orthogonal design was used to study three factors—melting temperature, time, and solid-liquid ratio—and how they affected the dissolution rate of eucalyptus powder. The optimum solution conditions were 170 °C, 20 min, and a solid-liquid ratio of 1:25. Composition analysis of the residue indicated that, in the dissolving process, acid-insoluble lignin was converted into acid-soluble lignin, and a part of the lignin was degraded or modified. After dissolution, the crystalline structure of cellulose deteriorated, the relative crystallinity decreased, and the crystal form changed from type I into amorphous. Wood powder degradation occurred during dissolution, and a higher dissolution rate led to greater degradation. In a low-temperature environment below 225 °C, the residue thermal stability decreased slightly with increasing dissolution rates, but it greatly improved in a high-temperature environment of 225 to 600 °C.

In order to explore the potential application of green solvent ionic liquids (ILs) in the kraft pulping process, eucalyptus wood was pretreated by [Mmim]DMP before normal pulping. The results showed that materials pretreated shortly by the ionic liquid had a higher yield and viscosity coupled with a lower potassium permanganate value and residual lignin content in the pulp, as a result of the cooking process. It was also inferred that alkaline [Mmim]DMP pretreatment could dissolve lignin effectively from fiber to result in a stronger binding force and more entangled properties. Paper tensile and burst strength were improved by about 40% and 60%, respectively. These results provide a new way for eucalyptus to be utilized in the kraft pulping process.

For the rate maximization problem in OFDM decode-and-forward relay system，a resource allocation algorithm based on the multi-relay forwarding was proposed. In the algorithm，the same subcarrier could be forwarded by multiple relays，and the base station could use the subcarriers that are not occupied by relays to transmit new symbols in the second phase. To reduce the computational complexity，the information transmission mode and the optimal relay set that assisting the transmission under relay mode were determined first，then the original problem was transformed into a dual problem to achieve the joint optimization solution of subcarrier-pairing and power allocation. Simulation results show that the proposed algorithm can achieve a higher system capacity.

Wideband spectrum sensing technology based on compressed sensing can effectively reduce the high sampling rate and the complexity of spectrum sensing.During the sensing process,in order to enhance the reconstruction performance of the spectrum signal,a modified OMP sub-band matching selection algorithm for wideband spectrum reconstruction based on the prior knowledge of boundary information and the block sparse characteristics of wideband frequency signal was proposed.This method can reduce the number of iterations in spectrum reconstruction with OMP algorithm and enhance stability of spectrum reconstruction.Simulation results show that the proposed method can not only improve the accuracy of spectrum reconstruction,but also effectively shorten spectrum sensing timeand achieve better wideband spectrum sensing performance.

The influences of stock consistency on the kappa number, residual alkali of pulp, flow direction of lignin, chemical oxygen demand, oxidation with dichromate (CODCr), and five-day biochemical oxygen demand (BOD5) in effluents were investigated in a washing process. Compared with 15% stock consistency, 35% stock consistency could lead to a decrease of at least 25% in the consumption of washing water while cutting 75.27% and 46.29% of CODCr and BOD5 in washing effluents, respectively. Moreover, the residual lignin in effluents were reduced greatly from 39.35 g·t-1 to 12.76 g·t-1, which will be beneficial to treatment of washing and bleaching effluent. All the results showed that a higher stock consistency in the washing process could decrease the consumption of washing water, the generation of pollution, and the toxicity in bleaching effluent.

Received signal strength–based target localization methods normally employ radio propagation path loss model, in which the log-normal shadowing noise is generally assumed to follow a zero-mean Gaussian distribution and is uncorrelated. In this article, however, we represent the simplified additive noise by the spatially correlated log-normal shadowing noise. We propose a new convex localization estimator in wireless sensor networks by using received signal strength measurements under spatially correlated shadowing environment. First, we derive a new non-convex estimator based on weighted least squares criterion. Second, by using the equivalence of norm, the derived estimator can be reformulated as its equivalent form which has no logarithm in the objective function. Then, the new estimator is relaxed by applying efficient convex relaxation that is based on second-order cone programming and semi-definite programming technique. Finally, the convex optimization problem can be efficiently solved by a standard interior-point method, thus to obtain the globally optimal solution. Simulation results show that the proposed estimator solves the localization problem efficiently and is close to Cramer–Rao lower bound compared with the state-of-the-art approach under correlated shadowing environment.

Alkalinity determination is of crucial significance for the applications of basic ionic liquids with imidazolyl. In this work, the ionization constant pKb value and acid function H- values of ionic liquids synthesized were calculated by pH method and UV spectrum-Hammett method. The dissolution ratio of biomass in these ionic liquids was measured at different temperatures. Finally, the relationship between the alkalinity and structure of these ionic liquids was discussed, and the relationship between the alkalinity of ionic liquid and the dissolution mechanism biomass was also discussed. The results show that the basicity of carboxylate ionic liquids is determined mainly by their anions, whereas cations take some finely tuned roles. Furthermore, cations and anions are equally important and are involved in dissolution mechanisms.

For the resource allocation in OFDMA MIMO relay downlink system,a quality of service aware resource allocation scheme with low complexity under total power constraint was proposed.First,under the assumption of equal power allocation,a selective priority factor was chosen for the relay selecting and subcarrier allocation.The relay selection and subcarriers allocation were carried out depending on the priority factor.Then the optimal power allocation was implemented through convex optimization algorithm.Numerical results show that the proposed scheme can not only achieve the higher capacity of system,but also guarantee the quality of service for each user.

Processing convenience and paper-sizing flexibility frequently require the delivery of alkenylsuccinic anhydride oil as emulsion. The shelf life of the oil is achieved kinetically, in most cases via the addition of surfactants such as cationic starch or a synthetic polymer, which are the subject of increasing scrutiny with regard to their environmental impact. The modification of montmorillonite nanoparticle with sodium fluoride was found to decrease the interfacial tension between dodecenylsuccinic anhydride (DDSA) and aqueous dispersion and to change the wettability of montmorillonite, which benefits the preparation of DDSA-in-water emulsions with enhanced stability, small droplet size, and improved hydrolysis resistance. Adjusting the pH and particle concentration of aqueous solution effectively improved the stability of DDSA emulsion. Catastrophic phase inversion from w/o (water-in-oil) to o/w (oil-in-water) was investigated by monitoring the variation of emulsion conductivity with increasing oil volume fraction. Evidence of the transition from loose particle-film to compact particle shell upon introduction of salt was found, as predicted theoretically for charged particles adsorbed on interfaces. Particulate interfacial films built by SFMMT nanoparticles protected DDSA droplets from aggregation and formed a honeycomb structure. Salt in the DDSA emulsification process restrained the hydrolytic action of DDSA effectively and sustained the sizing performance of DDSA even 5 h after the emulsion preparation.

Existing resource allocation algorithms can't balance system capacity and fairness well when the channel state information is imperfect. In order to solve this problem, a fair resource allocation algorithm was proposed to maximize the system ergodic capacity, while the fairness could be adjusted flexibly by introducing the fairness relaxation factor. In order to reduce the complexity in the use of dual optimization method for solving the lagrange operator process, an iteration searching method in the same layer was proposed to replace the traditional multi-layer iteration searching method. Simulation results show that the proposed algorithm can effectively maximize the system ergodic capacity and guarantee the fairness, while the computational complexity was reduced significantly.

Caveolin1 (CAV1) is involved in lipid homeostasis and endocytosis, but little is known about the significance of CAV1 in the pathogenesis and development of nonalcoholic fatty liver disease (NAFLD). This study aimed to determine the role of CAV1 in NAFLD.Expression of CAV1 in the in vitro and in vivo models of NAFLD was analyzed. The effects of CAV1 knockdown or overexpression on free fatty acid (FFA)-induced lipid accumulation in L02 cells and AML12 cells were determined. CAV1 knockout (CAV1-KO) mice and their wild-type (WT) littermates were subjected to a high fat diet (HFD) for 4 weeks, and the functional consequences of losing the CAV1 gene and its subsequent molecular mechanisms were also examined.Noticeably, CAV1 expression was markedly reduced in NAFLD. CAV1 knockdown led to the aggravation of steatosis that was induced by FFA in both L02 cells and AML12 cells, while CAV1 overexpression markedly attenuated lipid accumulation in the cells. Consistent with CAV1 repression in the livers of HFD-induced mice, the CAV1-KO mice exhibited more severe hepatic steatosis upon HFD intake. In addition, increased cholesterol levels and elevated transaminases were detected in the plasma of CAV1-KO mice. The protein expression of SREBP1, a key gene involved in lipogenesis, was augmented following CAV1 suppression in FFA-treated hepatocytes and in the livers of HFD-fed CAV1-KO mice.CAV1 serves as an important protective factor in the development of NAFLD by modulating lipid metabolism gene expression.

Autoimmune pancreatitis (AIP) is a special type of chronic pancreatitis, which may be misdiagnosed as pancreatic carcinoma. This study aims to verify new biomarkers for AIP and propose a serological pattern to differentiate AIP from pancreatic adenocarcinoma with routinely performed tests. In this study, data of serum samples were collected and compared between 25 patients with AIP and 100 patients with pancreatic carcinoma. Receiver operating characteristic analysis and logistic regression was performed to evaluate the diagnostic effect of serum parameters in differentiating AIP from pancreatic carcinoma alone or in combination. Among several serum markers observed in the two groups, carbohydrate antigen 19-9 (Ca19-9), globulin, eosinophils and hemoglobin were selected as the independent markers. Serum levels of Globulin, Eosinophil percentage in AIP group were significantly higher than in pancreatic cancer group (P

For the power minimization problem in multi-user cooperative relay communications,a resource allocation algorithm based on joint subcarrier pairing and assignment was proposed.Firstly,according to the average channel gain and the target rates of user,the assignment of subcarrier numbers was addressed.Then,in order to choose the subcarrier with best channel condition,a multi-user iterative algorithm for joint subcarrier pairing and assignment was proposed,which could achieve the subcarrier pairing in the cooperative transmissions and virtual pairing in the direct transmission,respectively.Finally,the power allocation was conducted by the water-filling algorithm,so that each user could use the minimum power for transmission.The simulation results indicate that the proposed algorithm can conduct subcarrier pairing and assignment effectively to minimize the total transmission power while meeting the users' target rate requirement.

Existing algorithms couldn't balance system capacity and high fairness well,so a multi-user rate adaptive allocation algorithm was proposed to maximize the capacity of OFDMA system under proportional fairness.Improved maximize the minimum（max-min）user rate model was proposed,the current user was allocated the highest efficiency subcarrier according to the channel efficiency control parameter.If some allocated subcarrier's channel gain was lower than the threshold value,which would be reallocated to another user whose channel gain was highest.Power allocation model was converted into expression of water-filling line; every user's power allocation was resolved according to the resolved water-filling line.Simulation results and analysis show that the proposed scheme can achieve higher capacity and perfect fairness in a variety of SNR cases,while requiring slightly less computation.

Ozonation was used for tertiary treatment of hardwood KP bleaching effluent. The objectives were to investigate the performance of ozonation on reduction of recalcitrant COD and color in the biologically treated effluent and to investigate the change in biodegradability of the effluent during the ozonation process. The results indicate that COD removal was enhanced by increasing solution pH and temperature, but that the recalcitrant COD was not completely removed from the effluent due to ozone-resistant substances that remain in the effluent after ozonation treatment. Ozonation of the effluent was more effective for decoloration than for COD removal. The highest decoloration efficiency and COD reduction were 99% and 55% at pH 11.7 and 25 °C. It was observed that the biological oxygen demand (BOD5) and BOD/COD ratio were 93 mg/L and 0.40, after 30 min of ozonation, which was an increase of up to 102% and 185%, indicating enhanced biodegradability of the effluent after ozonation treatment. This obvious increase in biodegradability implies that the ozone-resistant substances can be decomposed by ozonation to produce compounds that are more biodegradable.

Carboxymethyl lignin nanospheres (CLNPs) were synthesized by a two-step method using microwave irradiation and antisolvent. The morphology and structure of CLNPs were characterized by 31P-NMR, FTIR, and SEM, and the results showed that they had an average diameter of 73.9 nm, a surface area of 8.63 m2 or 3.2 times larger than the original lignin, and abundant carboxyl functional groups of 1.8 mmol/g. The influence of dosage, pH, contact time, and concentration on the adsorption of metal ions onto CLNPs were analyzed, and the maximum adsorption capacity of CLNPs for Pb(II) was found to be 333.26 mg/g, which is significantly higher than other lignin-based adsorbents and conventional adsorbents. Adsorption kinetics and isotherms indicated that the adsorption of lead ions in water onto CLNPs followed the pseudo-second-order model based on monolayer chemisorption mechanism. The main chemical interaction between CLNPs and lead ions was chelation. CLNPs also showed an excellent recycling performance, with only 27.0% adsorption capacity loss after 10 consecutive adsorption−desorption cycles.