Small-drone technology has opened a range of new applications for aerial transportation. These drones leverage the Internet of Things (IoT) to offer cross-location services for navigation. However, they are susceptibl...Small-drone technology has opened a range of new applications for aerial transportation. These drones leverage the Internet of Things (IoT) to offer cross-location services for navigation. However, they are susceptible to security and privacy threats due to hardware and architectural issues. Although small drones hold promise for expansion in both civil and defense sectors, they have safety, security, and privacy threats. Addressing these challenges is crucial to maintaining the security and uninterrupted operations of these drones. In this regard, this study investigates security, and preservation concerning both the drones and Internet of Drones (IoD), emphasizing the significance of creating drone networks that are secure and can robustly withstand interceptions and intrusions. The proposed framework incorporates a weighted voting ensemble model comprising three convolutional neural network (CNN) models to enhance intrusion detection within the network. The employed CNNs are customized 1D models optimized to obtain better performance. The output from these CNNs is voted using a weighted criterion using a 0.4, 0.3, and 0.3 ratio for three CNNs, respectively. Experiments involve using multiple benchmark datasets, achieving an impressive accuracy of up to 99.89% on drone data. The proposed model shows promising results concerning precision, recall, and F1 as indicated by their obtained values of 99.92%, 99.98%, and 99.97%, respectively. Furthermore, cross-validation and performance comparison with existing works is also carried out. Findings indicate that the proposed approach offers a prospective solution for detecting security threats for aerial systems and satellite systems with high accuracy.展开更多
The effect of prenatal exposure to ambient particulate matter(PM)on birth weight varies considerably across studies,and the findings remain inconclusive.In this study,we conducted a meta-analysis to assess the associa...The effect of prenatal exposure to ambient particulate matter(PM)on birth weight varies considerably across studies,and the findings remain inconclusive.In this study,we conducted a meta-analysis to assess the associations between exposure to PM_(2.5) and PM10 and birth weight.A total of 74 studies were identified through searches in Web of Science,PubMed,Embase,and Ovid Medline,as well as manual searches,up to October 2024.We found that for each 10μg/m^(3) increase in PM_(2.5),the risk of low birth weight(LBW)increased significantly during the entire pregnancy(odds ratio[OR]=2.41,95%confidence interval[CI]:1.99–2.91)and in all trimesters.Similarly,for every 10μg/m^(3) increase in PM10 concentration,the risk of LBW increased significantly during the entire pregnancy(OR=1.46,95%CI:1.16–1.84).Subgroup analysis by maternal age for PM_(2.5) showed that mothers aged 30 and above had a significantly higher risk of LBW(OR=3.69,95%CI:2.81–4.84),compared with those under 30.In conclusion,maternal exposure to PM_(2.5) and PM_(10) is associated with an increased risk of LBW across all trimesters.Additionally,mothers aged 30 and above are at a higher risk of LBW,compared with younger mothers.Further research is needed to clarify the biological mechanisms by which PM pollution may contribute to LBW.展开更多
BACKGROUND Beinaglutide,a short-acting glucagon-like polypeptide-1 receptor agonist,has shown variable efficacy in weight reduction and metabolic control in randomized controlled trials(RCTs).AIM To summarize the ther...BACKGROUND Beinaglutide,a short-acting glucagon-like polypeptide-1 receptor agonist,has shown variable efficacy in weight reduction and metabolic control in randomized controlled trials(RCTs).AIM To summarize the therapeutic effects of beinaglutide in patients with overweight/obesity with/without type 2 diabetes.METHODS RCTs involving patients receiving beinaglutide in the intervention arm and placebo or active comparator in the control arm were searched through multiple electronic databases.The change from baseline in body weight was the primary outcome;secondary outcomes included changes in body mass index(BMI),waist circumference(WC),blood pressure,glycemic parameters,lipids,and adverse events(AEs).RevMan web was used to conduct meta-analysis using random-effects models.Outcomes were presented as mean differences(MDs),odds ratios(ORs),or risk ratios(RRs)with 95%confidence intervals(95%CIs).RESULTS Six RCTs(n=800)with mostly some concerns about the risk of bias were included.Over 12-24 weeks,beinaglutide 0.1-0.2 mg thrice daily was superior to the control group in reducing total(MD=-3.25 kg,95%CI:-4.52 to-1.98,I^(2)=84%,P<0.00001)and percent(MD=-4.13%,95%CI:-4.87 to-3.39,I^(2)=54%,P<0.00001)body weight reduction.Beinaglutide also outperformed the control group in achieving weight loss by 5%(OR 4.61)and 10%(OR=5.34).The superiority of beinaglutide vs the control group was also found in reducing BMI(MD=-1.22 kg/m^(2),95%CI:-1.67 to-0.77)and WC(MD=-2.47 cm,95%CI:-3.74 to-1.19]).Beinaglutide and the control group had comparable impacts on blood pressure,glycemic parameters,insulin resistance,hepatic transaminases,and lipid profile.Beinaglutide posed higher risks of treatment discontinuation due to AEs(RR=3.15),nausea(RR=4.51),vomiting(RR=8.19),palpitation(RR=3.95),headache(RR=2.87),and dizziness(RR=6.07)than the control.However,the two groups had identical risks of total and serious AEs,diarrhea,fatigue,and hypoglycemia.CONCLUSION Short-term data from RCTs suggested that beinaglutide causes modest benefits in reducing body weight,BMI,and WC,with no significant difference in glycemic and other metabolic endpoints compared to the control arm.Safety data were consistent with those of the other drugs in the glucagon-like polypeptide-1 receptor agonist class.Larger RCTs are warranted to prove the longer-term metabolic benefits of beinaglutide.展开更多
6G is desired to support more intelligence networks and this trend attaches importance to the self-healing capability if degradation emerges in the cellular networks.As a primary component of selfhealing networks,faul...6G is desired to support more intelligence networks and this trend attaches importance to the self-healing capability if degradation emerges in the cellular networks.As a primary component of selfhealing networks,fault detection is investigated in this paper.Considering the fast response and low timeand-computational consumption,it is the first time that the Online Broad Learning System(OBLS)is applied to identify outages in cellular networks.In addition,the Automatic-constructed Online Broad Learning System(AOBLS)is put forward to rationalize its structure and consequently avoid over-fitting and under-fitting.Furthermore,a multi-layer classification structure is proposed to further improve the classification performance.To face the challenges caused by imbalanced data in fault detection problems,a novel weighting strategy is derived to achieve the Multilayer Automatic-constructed Weighted Online Broad Learning System(MAWOBLS)and ensemble learning with retrained Support Vector Machine(SVM),denoted as EMAWOBLS,for superior treatment with this imbalance issue.Simulation results show that the proposed algorithm has excellent performance in detecting faults with satisfactory time usage.展开更多
With the increasing complexity of vehicular networks and the proliferation of connected vehicles,Federated Learning(FL)has emerged as a critical framework for decentralized model training while preserving data privacy...With the increasing complexity of vehicular networks and the proliferation of connected vehicles,Federated Learning(FL)has emerged as a critical framework for decentralized model training while preserving data privacy.However,efficient client selection and adaptive weight allocation in heterogeneous and non-IID environments remain challenging.To address these issues,we propose Federated Learning with Client Selection and Adaptive Weighting(FedCW),a novel algorithm that leverages adaptive client selection and dynamic weight allocation for optimizing model convergence in real-time vehicular networks.FedCW selects clients based on their Euclidean distance from the global model and dynamically adjusts aggregation weights to optimize both data diversity and model convergence.Experimental results show that FedCW significantly outperforms existing FL algorithms such as FedAvg,FedProx,and SCAFFOLD,particularly in non-IID settings,achieving faster convergence,higher accuracy,and reduced communication overhead.These findings demonstrate that FedCW provides an effective solution for enhancing the performance of FL in heterogeneous,edge-based computing environments.展开更多
In this article, a model of 3-D net is set up by using lumped mass method. Model test results made by Lader and Enerhaug are cited to verify the numerical model. The aim of this paper is to investigate the effects of ...In this article, a model of 3-D net is set up by using lumped mass method. Model test results made by Lader and Enerhaug are cited to verify the numerical model. The aim of this paper is to investigate the effects of weight system on the hydrodynamic behavior of 3-D net of gravity cage in current. Using the 3-D net model, with different styles and masses of weight system, hydrodynamic behavior of gravity cage net in current is simulated. In this article, two styles of common weight system are used, which include： （1） sinker system , （2） bottom collar-sinker system. Under each style, three different masses of weight system are adopted. The numerical results indicate that the bottom collar-sinker system is practically feasible in improving the cage net volume deformation. Results of this study will give references for better knowledge of hydrodynamic behavior of gravity cage.展开更多
Association rules are useful for determining correlations between items. Applying association rules to intrusion detection system (IDS) can improve the detection rate, but false positive rate is also increased. Weight...Association rules are useful for determining correlations between items. Applying association rules to intrusion detection system (IDS) can improve the detection rate, but false positive rate is also increased. Weighted association rules are used in this paper to mine intrustion models, which can increase the detection rate and decrease the false positive rate by some extent. Based on this, the structure of host-based IDS using weighted association rules is proposed.展开更多
Objective To investigate the difference in tumor conventional imaging findings and texture features on T2 weighted images between glioblastoma and primary central neural system(CNS) lymphoma. Methods The pre-operative...Objective To investigate the difference in tumor conventional imaging findings and texture features on T2 weighted images between glioblastoma and primary central neural system(CNS) lymphoma. Methods The pre-operative MRI data of 81 patients with glioblastoma and 28 patients with primary CNS lymphoma admitted to the Chinese PLA General Hospital and Hainan Hospital of Chinese PLA General Hospital were retrospectively collected. All patients underwent plain MR imaging and enhanced T1 weighted imaging to visualize imaging features of lesions. Texture analysis of T2 weighted imaging(T2 WI) was performed by use of GLCM texture plugin of ImageJ software, and the texture parameters including Angular Second Moment(ASM), Contrast, Correlation, Inverse Difference Moment(IDM), and Entropy were measured. Independent sample t-test and Mann-Whitney U test were performed for the between-group comparisons, regression model was established by Binary Logistic regression analysis, and receiver operating characteristic(ROC) curve was plotted to compare the diagnostic efficacy. Results The conventional imaging features including cystic and necrosis changes(P = 0.000), ‘Rosette' changes(P = 0.000) and ‘incision sign'(P = 0.000), except ‘flame-like edema'(P = 0.635), presented significantly statistical difference between glioblastoma and primary CNS lymphoma. The texture features, ASM, Contrast, Correlation, IDM and Entropy, showed significant differences between glioblastoma and primary CNS lympoma(P = 0.006,0.000, 0.002, 0.000, and 0.015 respectively). The area under the ROC curve was 0.671, 0.752, 0.695, 0.720 and 0.646 respectively, and the area under the ROC curve was 0.917 for the combined texture variables(Contrast, cystic and necrosis, ‘Rosette' changes, and ‘incision sign') in the model of Logistic regression. Binary Logistic regression analysis demonstrated that cystic and necrosis changes, ‘Rosette' changes and ‘incision sign' and texture Contrast could be considered as the specific texture variables for the differential diagnosis of glioblastoma and primary CNS lymphoma. Conclusion The texture features of T2 WI and conventional imaging findings may be used to distinguish glioblastoma from primary CNS lymphoma.展开更多
Low molecular weight organic acids （LMWOAs） are prevalent on the earth＇s surface. They are vital intermediate products during metabolic pathways of organic matter and participate in the tricarboxylic acid cycle dur...Low molecular weight organic acids （LMWOAs） are prevalent on the earth＇s surface. They are vital intermediate products during metabolic pathways of organic matter and participate in the tricarboxylic acid cycle during life activities. Photochemical reactions are pivotal for LMWOAs＇ origination and play a large role in determining their diversity and their ultimate fate. Within the long time that organic matter is preserved in sediments, it can be decomposed and converted to release organic and inorganic pollutants as well as C, N, and P nutrients, which are of potential ecological risk in causing secondary pollution to lake water. The sediment pool is a comprehensive and complex compartment closely associated with overlying water by various biochemical processes, during which LMWOAs play critical roles to transport and transform elements. This article elucidates geochemical behaviors of LMWOAs in the surface environment in details, taking natural water, soil, and aerosol as examples, focusing on reviewing research developments on sources and characteristics, migration and mineralization of LMWOAs and relevant environmental effects. Simultaneously, this review article depicts the categories and contents of LMWOAs or their contribution to DOC in environmental media, and evaluates their importance during organic matter early diagenesis. Through concluding and discussing the conversion mechanisms and influencing factors, the next research orientations on LMWOAs in lake ecosystems are determined, mainly concerning relationships with hydrochemical parameters and microorganisms, and interactions with pollutants. This will enrich the knowledge on organic matter degradation and related environmental effects, and help reconstruct a theoretical framework for organic compound succession and influencing factors, providing basic data for lake eutrophication and ecological risk assessment, conducive to better control over water pollution and proper management of water quality.展开更多
The purpose of this systematic review was to identify the effects of weight-lifting or resistance exercise on breast cancer-related lymphedema.Published articles written in English were retrieved from electronic datab...The purpose of this systematic review was to identify the effects of weight-lifting or resistance exercise on breast cancer-related lymphedema.Published articles written in English were retrieved from electronic databases,including ScienceDirect,PubMed,Scopus,and CINAHL databases.Hand-searches for unpublished papers were also completed.Content analysis was used to examine articles that met the inclusion criteria.Among 525 searched papers,15 papers met the inclusion criteria:13 trials evaluated weight-lifting or resistance exercise alone and two trials evaluated weight-lifting or resistance exercise plus aerobic exercise.The results of the review showed that no arm volume change was observed for either exercise modality.In addition,six included studies showed that weight-lifting or resistance exercise did not cause lymphedema or adverse events in patients at risk of breast cancer-related lymphedema.For patients with breast cancer-related lymphedema,six studies reported that change of swelling outcome measures were not significantly different between the weight-lifting or resistance exercise group and the control group.However,three included studies reported that volume of arm was significantly more reduced in the weight-lifting or resistance exercise group than those in the control group.The findings suggest that supervised resistance exercise may be safe,feasible,and beneficial in patients with breast cancer-related lymphedema or at risk for breast cancer-related lymphedema.However,the limitation of small sample size implies that further research is needed to confirm these findings.展开更多
The gear transmission system has been widely applied in mechanical systems,and many high-performance applications of these systems require low weight.With the aid of establishing the optimization model of the gear tra...The gear transmission system has been widely applied in mechanical systems,and many high-performance applications of these systems require low weight.With the aid of establishing the optimization model of the gear transmission system that consists of an objective function and some constraints(for example,the bending stress,the contact stress,the torsional strength,etc.),the optimal weight design of the gear transmission system can be transformed into the optimization problem for the objective function under the constraints.Moreover,both the shaft and the gear of the gear transmission system are considered simultaneously in our design.The hybrid Taguchi-genetic algorithm(HTGA)is employed to find the optimal design variables and the optimal weight of the system.An illustrated example for the single spur gear reducer is given to show that the optimal weight design problem can be successfully solved using the proposed design scheme.It also proves the high efficiency and feasibility of the algorithm in the gear design.展开更多
BACKGROUND With increasing rates of liver transplantation and a stagnant donor pool,the annual wait list removals have remained high.Living donor liver transplantation(LDLT)is an established modality in expanding the ...BACKGROUND With increasing rates of liver transplantation and a stagnant donor pool,the annual wait list removals have remained high.Living donor liver transplantation(LDLT)is an established modality in expanding the donor pool and is the primary method of liver donation in large parts of the world.Marginal living donors,including those with hepatic steatosis,have been used to expand the donor pool.However,due to negative effects of steatosis on graft and recipient outcomes,current practice excludes overweight or obese donors with more than 10%macro vesicular steatosis.This has limited a potentially important source to help expand the donor pool.Weight loss is known to improve or resolve steatosis and rapid weight loss with short-term interventions have been used to convert marginal donors to low-risk donors in a small series of studies.There is,however,a lack of a consensus driven standardized approach to such interventions.AIM To assess the available data on using weight loss interventions in potential living liver donors with steatotic livers and investigated the feasibility,efficacy,and safety of using such donors on the donor,graft and recipient outcomes.The principal objective was to assess if using such treated donor livers,could help expand the donor pool.METHODS We performed a comprehensive literature review and meta-analysis on studies examining the role of short-term weight loss interventions in potential living liver donors with hepatic steatosis with the aim of increasing liver donation rates and improving donor,graft,and recipient outcomes.RESULTS A total of 6 studies with 102 potential donors were included.Most subjects were males(71).All studies showed a significant reduction in body mass index postintervention with a mean difference of-2.08(-3.06,1.10,I2=78%).A significant reduction or resolution of hepatic steatosis was seen in 93 of the 102(91.2%).Comparison of pre-and post-intervention liver biopsies showed a significant reduction in steatosis with a mean difference of-21.22(-27.02,-15.43,I2=56%).The liver donation rates post-intervention was 88.5(74.5,95.3,I2=42%).All donors who did not undergo LDLT had either recipient reasons or had fibrosis/steatohepatitis on post intervention biopsies.Post-operative biliary complications in the intervention group were not significantly different compared to controls with an odds ratio of 0.96[(0.14,6.69),I2=0].The overall post-operative donor,graft,and recipient outcomes in treated donors were not significantly different compared to donors with no steatosis.CONCLUSION Use of appropriate short term weight loss interventions in living liver donors is an effective tool in turning marginal donors to low-risk donors and therefore in expanding the donor pool.It is feasible and safe,with comparable donor,graft,and recipient outcomes,to non-obese donors.Larger future prospective studies are needed.展开更多
Background:Weight-loss-induced fat loss improves cardiometabolic health in individuals with overweight and obesity;however,weight loss can also result in bone loss and increased fracture risk.Weight-loss-induced bone ...Background:Weight-loss-induced fat loss improves cardiometabolic health in individuals with overweight and obesity;however,weight loss can also result in bone loss and increased fracture risk.Weight-loss-induced bone loss may be attenuated with exercise.Our aim was to compare changes in bone mineral density(BMD)in adults with overweight and obesity who undertook diet-induced weight loss alone or in combination with exercise.Methods:We included randomized controlled trials(RCTs)in adults with overweight or obesity(aged-18 years;body mass index-25 kg/m^(2))that prescribed diet-induced weight loss alone or in combination with supervised exercise,and measured any bone structural parameters.Risk of bias was assessed using the Cochrane Risk of Bias tool.Random-effects meta-analyses determined mean changes and net mean differences(95%confidence intervals(95%CIs))in the percentage of areal BMD(aBMD)change between groups.Results:We included 9 RCTs.Diet-induced weight loss led to significant losses in femoral neck aBMD(mean change:-1.73%(95%CI:-2.39%to-1.07%),p<0.001)and total hip aBMD(-2.19%(95%CI:-3.84%to-0.54%),p=0.009).Femoral neck aBMD losses were significantly greater in the diet-induced weight loss group compared to the exercise plus diet-induced weight loss group(net difference:-0.88%(95%CI:-1.73%to-0.03%));however,there were no differences in aBMD changes at any other skeletal site:total hip(-1.96%(95%CI:-4.59%to 0.68%))and lumbar spine(-0.48%(95%CI:-1.81%to 0.86%)).aBMD changes did not differ significantly according to exercise modality(resistance exercise,aerobic exercise,or a combination of the two)during diet-induced weight loss.Conclusion:Diet-induced weight loss led to greater femoral neck bone loss compared to diet-induced weight loss plus exercise.Bone loss at the total hip and lumbar spine was not attenuated by exercise during diet-induced weight loss.The lack of consistent skeletal benefits may be due to the insufficient duration and/or training intensities of most exercise interventions.Additional RCTs with appropriate,targeted exercise interventions should be conducted.展开更多
With the increasing intelligence and integration,a great number of two-valued variables(generally stored in the form of 0 or 1)often exist in large-scale industrial processes.However,these variables cannot be effectiv...With the increasing intelligence and integration,a great number of two-valued variables(generally stored in the form of 0 or 1)often exist in large-scale industrial processes.However,these variables cannot be effectively handled by traditional monitoring methods such as linear discriminant analysis(LDA),principal component analysis(PCA)and partial least square(PLS)analysis.Recently,a mixed hidden naive Bayesian model(MHNBM)is developed for the first time to utilize both two-valued and continuous variables for abnormality monitoring.Although the MHNBM is effective,it still has some shortcomings that need to be improved.For the MHNBM,the variables with greater correlation to other variables have greater weights,which can not guarantee greater weights are assigned to the more discriminating variables.In addition,the conditional P(x j|x j′,y=k)probability must be computed based on historical data.When the training data is scarce,the conditional probability between continuous variables tends to be uniformly distributed,which affects the performance of MHNBM.Here a novel feature weighted mixed naive Bayes model(FWMNBM)is developed to overcome the above shortcomings.For the FWMNBM,the variables that are more correlated to the class have greater weights,which makes the more discriminating variables contribute more to the model.At the same time,FWMNBM does not have to calculate the conditional probability between variables,thus it is less restricted by the number of training data samples.Compared with the MHNBM,the FWMNBM has better performance,and its effectiveness is validated through numerical cases of a simulation example and a practical case of the Zhoushan thermal power plant(ZTPP),China.展开更多
Information feedback strategies can influence the traffic efficiency of intelligent traffic systems greatly.Based on the more practical symmetrical two-route scenario with one entrance and one exit,an improved weighte...Information feedback strategies can influence the traffic efficiency of intelligent traffic systems greatly.Based on the more practical symmetrical two-route scenario with one entrance and one exit,an improved weighted mean velocity feedback strategy（WMVFS） is proposed,which is not sensitive to the precision of global position system（GPS） devices.The applicability of WMVFS to different weight factors,aggressive probabilities,densities of dynamic vehicles,and different two-route scenarios（symmetrical scenario and asymmetrical scenario with a speed limit bottleneck） is analyzed.Results show that WMVFS achieves the best performance compared with three other information feedback strategies when considering the traffic flux and stability.展开更多
This paper explores a highly accurate identification modeling approach for the ship maneuvering motion with fullscale trial. A multi-innovation gradient iterative(MIGI) approach is proposed to optimize the distance me...This paper explores a highly accurate identification modeling approach for the ship maneuvering motion with fullscale trial. A multi-innovation gradient iterative(MIGI) approach is proposed to optimize the distance metric of locally weighted learning(LWL), and a novel non-parametric modeling technique is developed for a nonlinear ship maneuvering system. This proposed method’s advantages are as follows: first, it can avoid the unmodeled dynamics and multicollinearity inherent to the conventional parametric model; second, it eliminates the over-learning or underlearning and obtains the optimal distance metric; and third, the MIGI is not sensitive to the initial parameter value and requires less time during the training phase. These advantages result in a highly accurate mathematical modeling technique that can be conveniently implemented in applications. To verify the characteristics of this mathematical model, two examples are used as the model platforms to study the ship maneuvering.展开更多
In this paper,a novel precoding scheme based on the Gauss-Seidel(GS)method is proposed for downlink massive multiple-input multiple-output(MIMO)systems.The GS method iteratively approximates the matrix inversion and r...In this paper,a novel precoding scheme based on the Gauss-Seidel(GS)method is proposed for downlink massive multiple-input multiple-output(MIMO)systems.The GS method iteratively approximates the matrix inversion and reduces the overall complexity of the precoding process.In addition,the GS method shows a fast convergence rate to the Zero-forcing(ZF)method that requires an exact invertible matrix.However,to satisfy demanded error performance and converge to the error performance of the ZF method in the practical condition such as spatially correlated channels,more iterations are necessary for the GS method and increase the overall complexity.For efficient approximation with fewer iterations,this paper proposes a weighted GS(WGS)method to improve the approximation accuracy of the GS method.The optimal weights that accelerate the convergence rate by improved accuracy are computed by the least square(LS)method.After the computation of weights,the different weights are applied for each iteration of the GS method.In addition,an efficient method of weight computation is proposed to reduce the complexity of the LS method.The simulation results show that bit error rate(BER)performance for the proposed scheme with fewer iterations is better than the GS method in spatially correlated channels.展开更多
In this article, we study positive solutions to the system{Aαu（x） = Cn,αPV∫Rn（a1（x-y）（u（x）-u（y）））/（｜x-y｜n＋α）dy = f（u（x）, Bβv（x） = Cn,βPV ∫Rn（a2（x-y）（v（x）-v（y））/（｜x-y｜n＋β）dy ...In this article, we study positive solutions to the system{Aαu（x） = Cn,αPV∫Rn（a1（x-y）（u（x）-u（y）））/（｜x-y｜n＋α）dy = f（u（x）, Bβv（x） = Cn,βPV ∫Rn（a2（x-y）（v（x）-v（y））/（｜x-y｜n＋β）dy = g（u（x）,v（x））.To reach our aim, by using the method of moving planes, we prove a narrow region principle and a decay at infinity by the iteration method. On the basis of these results, we conclude radial symmetry and monotonicity of positive solutions for the problems involving the weighted fractional system on an unit ball and the whole space. Furthermore, non-existence of nonnegative solutions on a half space is given.展开更多
Objective:To analyze the relationship between body mass index(BMI)before pregnancy and gestational weight gain throughout pregnancy with the incidence of preeclampsia.Methods:This was a systematic review-meta analysis...Objective:To analyze the relationship between body mass index(BMI)before pregnancy and gestational weight gain throughout pregnancy with the incidence of preeclampsia.Methods:This was a systematic review-meta analysis of literature collected from three e-databases:Scopus,PubMed,and Science Direct.Quality assessment was measured with the Effective Public Health Practice Project methods.Meta-analysis was done by calculating the fixed and random-effects of odds ratio(OR)for each BMI category and gestational weight gain as compared with the incidence of preeclampsia.Results:Overweight was associated with a significantly increased risk of preeclampsia(OR=2.152,95%CI 1.363-3.400;P=0.001).Obesity was also associated with a noticeably increased risk of preeclampsia(OR=2.856,95%CI 1.755-4.649;P<0.001).Meanwhile,underweight was associated with a significantly reduced risk of preeclampsia(OR=0.639,95%CI 0.500-0.817;P<0.001)when compared with normal BMI.Pregnant women who gained weight below the standard throughout pregnancy was a protective factor from preeclampsia(OR=0.813,95%CI 0.610-1.083;P=0.157)whereas pregnant women who gained weight above the standard had almost doubled risk of preeclampsia(OR=1.850,95%CI 1.377-2.485;P<0.001).Conclusions:The result of this study affirms the role of overweight-obesity pre-pregnancy,and gestational weight gain above the standard during pregnancy as significant risk factors for developing preeclampsia.展开更多
Memory-based collaborative recommender system (CRS) computes the similarity between users based on their declared ratings. However, not all ratings are of the same importance to the user. The set of ratings each user ...Memory-based collaborative recommender system (CRS) computes the similarity between users based on their declared ratings. However, not all ratings are of the same importance to the user. The set of ratings each user weights highly differs from user to user according to his mood and taste. This is usually reflected in the user’s rating scale. Accordingly, many efforts have been done to introduce weights to the similarity measures of CRSs. This paper proposes fuzzy weightings for the most common similarity measures for memory-based CRSs. Fuzzy weighting can be considered as a learning mechanism for capturing the preferences of users for ratings. Comparing with genetic algorithm learning, fuzzy weighting is fast, effective and does not require any more space. Moreover, fuzzy weightings based on the rating deviations from the user’s mean of ratings take into account the different rating scales of different users. The experimental results show that fuzzy weightings obviously improve the CRSs performance to a good extent.展开更多
文摘Small-drone technology has opened a range of new applications for aerial transportation. These drones leverage the Internet of Things (IoT) to offer cross-location services for navigation. However, they are susceptible to security and privacy threats due to hardware and architectural issues. Although small drones hold promise for expansion in both civil and defense sectors, they have safety, security, and privacy threats. Addressing these challenges is crucial to maintaining the security and uninterrupted operations of these drones. In this regard, this study investigates security, and preservation concerning both the drones and Internet of Drones (IoD), emphasizing the significance of creating drone networks that are secure and can robustly withstand interceptions and intrusions. The proposed framework incorporates a weighted voting ensemble model comprising three convolutional neural network (CNN) models to enhance intrusion detection within the network. The employed CNNs are customized 1D models optimized to obtain better performance. The output from these CNNs is voted using a weighted criterion using a 0.4, 0.3, and 0.3 ratio for three CNNs, respectively. Experiments involve using multiple benchmark datasets, achieving an impressive accuracy of up to 99.89% on drone data. The proposed model shows promising results concerning precision, recall, and F1 as indicated by their obtained values of 99.92%, 99.98%, and 99.97%, respectively. Furthermore, cross-validation and performance comparison with existing works is also carried out. Findings indicate that the proposed approach offers a prospective solution for detecting security threats for aerial systems and satellite systems with high accuracy.
文摘The effect of prenatal exposure to ambient particulate matter(PM)on birth weight varies considerably across studies,and the findings remain inconclusive.In this study,we conducted a meta-analysis to assess the associations between exposure to PM_(2.5) and PM10 and birth weight.A total of 74 studies were identified through searches in Web of Science,PubMed,Embase,and Ovid Medline,as well as manual searches,up to October 2024.We found that for each 10μg/m^(3) increase in PM_(2.5),the risk of low birth weight(LBW)increased significantly during the entire pregnancy(odds ratio[OR]=2.41,95%confidence interval[CI]:1.99–2.91)and in all trimesters.Similarly,for every 10μg/m^(3) increase in PM10 concentration,the risk of LBW increased significantly during the entire pregnancy(OR=1.46,95%CI:1.16–1.84).Subgroup analysis by maternal age for PM_(2.5) showed that mothers aged 30 and above had a significantly higher risk of LBW(OR=3.69,95%CI:2.81–4.84),compared with those under 30.In conclusion,maternal exposure to PM_(2.5) and PM_(10) is associated with an increased risk of LBW across all trimesters.Additionally,mothers aged 30 and above are at a higher risk of LBW,compared with younger mothers.Further research is needed to clarify the biological mechanisms by which PM pollution may contribute to LBW.
文摘BACKGROUND Beinaglutide,a short-acting glucagon-like polypeptide-1 receptor agonist,has shown variable efficacy in weight reduction and metabolic control in randomized controlled trials(RCTs).AIM To summarize the therapeutic effects of beinaglutide in patients with overweight/obesity with/without type 2 diabetes.METHODS RCTs involving patients receiving beinaglutide in the intervention arm and placebo or active comparator in the control arm were searched through multiple electronic databases.The change from baseline in body weight was the primary outcome;secondary outcomes included changes in body mass index(BMI),waist circumference(WC),blood pressure,glycemic parameters,lipids,and adverse events(AEs).RevMan web was used to conduct meta-analysis using random-effects models.Outcomes were presented as mean differences(MDs),odds ratios(ORs),or risk ratios(RRs)with 95%confidence intervals(95%CIs).RESULTS Six RCTs(n=800)with mostly some concerns about the risk of bias were included.Over 12-24 weeks,beinaglutide 0.1-0.2 mg thrice daily was superior to the control group in reducing total(MD=-3.25 kg,95%CI:-4.52 to-1.98,I^(2)=84%,P<0.00001)and percent(MD=-4.13%,95%CI:-4.87 to-3.39,I^(2)=54%,P<0.00001)body weight reduction.Beinaglutide also outperformed the control group in achieving weight loss by 5%(OR 4.61)and 10%(OR=5.34).The superiority of beinaglutide vs the control group was also found in reducing BMI(MD=-1.22 kg/m^(2),95%CI:-1.67 to-0.77)and WC(MD=-2.47 cm,95%CI:-3.74 to-1.19]).Beinaglutide and the control group had comparable impacts on blood pressure,glycemic parameters,insulin resistance,hepatic transaminases,and lipid profile.Beinaglutide posed higher risks of treatment discontinuation due to AEs(RR=3.15),nausea(RR=4.51),vomiting(RR=8.19),palpitation(RR=3.95),headache(RR=2.87),and dizziness(RR=6.07)than the control.However,the two groups had identical risks of total and serious AEs,diarrhea,fatigue,and hypoglycemia.CONCLUSION Short-term data from RCTs suggested that beinaglutide causes modest benefits in reducing body weight,BMI,and WC,with no significant difference in glycemic and other metabolic endpoints compared to the control arm.Safety data were consistent with those of the other drugs in the glucagon-like polypeptide-1 receptor agonist class.Larger RCTs are warranted to prove the longer-term metabolic benefits of beinaglutide.
基金supported in part by the National Key Research and Development Project under Grant 2020YFB1806805partially funded through a grant from Qualcomm。
文摘6G is desired to support more intelligence networks and this trend attaches importance to the self-healing capability if degradation emerges in the cellular networks.As a primary component of selfhealing networks,fault detection is investigated in this paper.Considering the fast response and low timeand-computational consumption,it is the first time that the Online Broad Learning System(OBLS)is applied to identify outages in cellular networks.In addition,the Automatic-constructed Online Broad Learning System(AOBLS)is put forward to rationalize its structure and consequently avoid over-fitting and under-fitting.Furthermore,a multi-layer classification structure is proposed to further improve the classification performance.To face the challenges caused by imbalanced data in fault detection problems,a novel weighting strategy is derived to achieve the Multilayer Automatic-constructed Weighted Online Broad Learning System(MAWOBLS)and ensemble learning with retrained Support Vector Machine(SVM),denoted as EMAWOBLS,for superior treatment with this imbalance issue.Simulation results show that the proposed algorithm has excellent performance in detecting faults with satisfactory time usage.
文摘With the increasing complexity of vehicular networks and the proliferation of connected vehicles,Federated Learning(FL)has emerged as a critical framework for decentralized model training while preserving data privacy.However,efficient client selection and adaptive weight allocation in heterogeneous and non-IID environments remain challenging.To address these issues,we propose Federated Learning with Client Selection and Adaptive Weighting(FedCW),a novel algorithm that leverages adaptive client selection and dynamic weight allocation for optimizing model convergence in real-time vehicular networks.FedCW selects clients based on their Euclidean distance from the global model and dynamically adjusts aggregation weights to optimize both data diversity and model convergence.Experimental results show that FedCW significantly outperforms existing FL algorithms such as FedAvg,FedProx,and SCAFFOLD,particularly in non-IID settings,achieving faster convergence,higher accuracy,and reduced communication overhead.These findings demonstrate that FedCW provides an effective solution for enhancing the performance of FL in heterogeneous,edge-based computing environments.
基金the National High Technology Research and Development Program of China (863 Program, Grant No. 2006AA100301)Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT) (Grant No. IRT0420).
文摘In this article, a model of 3-D net is set up by using lumped mass method. Model test results made by Lader and Enerhaug are cited to verify the numerical model. The aim of this paper is to investigate the effects of weight system on the hydrodynamic behavior of 3-D net of gravity cage in current. Using the 3-D net model, with different styles and masses of weight system, hydrodynamic behavior of gravity cage net in current is simulated. In this article, two styles of common weight system are used, which include： （1） sinker system , （2） bottom collar-sinker system. Under each style, three different masses of weight system are adopted. The numerical results indicate that the bottom collar-sinker system is practically feasible in improving the cage net volume deformation. Results of this study will give references for better knowledge of hydrodynamic behavior of gravity cage.
文摘Association rules are useful for determining correlations between items. Applying association rules to intrusion detection system (IDS) can improve the detection rate, but false positive rate is also increased. Weighted association rules are used in this paper to mine intrustion models, which can increase the detection rate and decrease the false positive rate by some extent. Based on this, the structure of host-based IDS using weighted association rules is proposed.
文摘Objective To investigate the difference in tumor conventional imaging findings and texture features on T2 weighted images between glioblastoma and primary central neural system(CNS) lymphoma. Methods The pre-operative MRI data of 81 patients with glioblastoma and 28 patients with primary CNS lymphoma admitted to the Chinese PLA General Hospital and Hainan Hospital of Chinese PLA General Hospital were retrospectively collected. All patients underwent plain MR imaging and enhanced T1 weighted imaging to visualize imaging features of lesions. Texture analysis of T2 weighted imaging(T2 WI) was performed by use of GLCM texture plugin of ImageJ software, and the texture parameters including Angular Second Moment(ASM), Contrast, Correlation, Inverse Difference Moment(IDM), and Entropy were measured. Independent sample t-test and Mann-Whitney U test were performed for the between-group comparisons, regression model was established by Binary Logistic regression analysis, and receiver operating characteristic(ROC) curve was plotted to compare the diagnostic efficacy. Results The conventional imaging features including cystic and necrosis changes(P = 0.000), ‘Rosette' changes(P = 0.000) and ‘incision sign'(P = 0.000), except ‘flame-like edema'(P = 0.635), presented significantly statistical difference between glioblastoma and primary CNS lymphoma. The texture features, ASM, Contrast, Correlation, IDM and Entropy, showed significant differences between glioblastoma and primary CNS lympoma(P = 0.006,0.000, 0.002, 0.000, and 0.015 respectively). The area under the ROC curve was 0.671, 0.752, 0.695, 0.720 and 0.646 respectively, and the area under the ROC curve was 0.917 for the combined texture variables(Contrast, cystic and necrosis, ‘Rosette' changes, and ‘incision sign') in the model of Logistic regression. Binary Logistic regression analysis demonstrated that cystic and necrosis changes, ‘Rosette' changes and ‘incision sign' and texture Contrast could be considered as the specific texture variables for the differential diagnosis of glioblastoma and primary CNS lymphoma. Conclusion The texture features of T2 WI and conventional imaging findings may be used to distinguish glioblastoma from primary CNS lymphoma.
基金financially supported by the National Natural Sciences Foundation of China(No.41373138,41003055,41261140337)the National Science and Technology Major Special Project(No.2011ZX07212-007)State Key Laboratory of Environmental Geochemistry(No.SKLEG2013404),Institute of geochemistry, Chinese Academy of Sciences
文摘Low molecular weight organic acids （LMWOAs） are prevalent on the earth＇s surface. They are vital intermediate products during metabolic pathways of organic matter and participate in the tricarboxylic acid cycle during life activities. Photochemical reactions are pivotal for LMWOAs＇ origination and play a large role in determining their diversity and their ultimate fate. Within the long time that organic matter is preserved in sediments, it can be decomposed and converted to release organic and inorganic pollutants as well as C, N, and P nutrients, which are of potential ecological risk in causing secondary pollution to lake water. The sediment pool is a comprehensive and complex compartment closely associated with overlying water by various biochemical processes, during which LMWOAs play critical roles to transport and transform elements. This article elucidates geochemical behaviors of LMWOAs in the surface environment in details, taking natural water, soil, and aerosol as examples, focusing on reviewing research developments on sources and characteristics, migration and mineralization of LMWOAs and relevant environmental effects. Simultaneously, this review article depicts the categories and contents of LMWOAs or their contribution to DOC in environmental media, and evaluates their importance during organic matter early diagenesis. Through concluding and discussing the conversion mechanisms and influencing factors, the next research orientations on LMWOAs in lake ecosystems are determined, mainly concerning relationships with hydrochemical parameters and microorganisms, and interactions with pollutants. This will enrich the knowledge on organic matter degradation and related environmental effects, and help reconstruct a theoretical framework for organic compound succession and influencing factors, providing basic data for lake eutrophication and ecological risk assessment, conducive to better control over water pollution and proper management of water quality.
文摘The purpose of this systematic review was to identify the effects of weight-lifting or resistance exercise on breast cancer-related lymphedema.Published articles written in English were retrieved from electronic databases,including ScienceDirect,PubMed,Scopus,and CINAHL databases.Hand-searches for unpublished papers were also completed.Content analysis was used to examine articles that met the inclusion criteria.Among 525 searched papers,15 papers met the inclusion criteria:13 trials evaluated weight-lifting or resistance exercise alone and two trials evaluated weight-lifting or resistance exercise plus aerobic exercise.The results of the review showed that no arm volume change was observed for either exercise modality.In addition,six included studies showed that weight-lifting or resistance exercise did not cause lymphedema or adverse events in patients at risk of breast cancer-related lymphedema.For patients with breast cancer-related lymphedema,six studies reported that change of swelling outcome measures were not significantly different between the weight-lifting or resistance exercise group and the control group.However,three included studies reported that volume of arm was significantly more reduced in the weight-lifting or resistance exercise group than those in the control group.The findings suggest that supervised resistance exercise may be safe,feasible,and beneficial in patients with breast cancer-related lymphedema or at risk for breast cancer-related lymphedema.However,the limitation of small sample size implies that further research is needed to confirm these findings.
基金Supported by the Fundamental Research Funds for the Central Universities(20102080201000085)the National Natural Science Foundation of China(50875189)
文摘The gear transmission system has been widely applied in mechanical systems,and many high-performance applications of these systems require low weight.With the aid of establishing the optimization model of the gear transmission system that consists of an objective function and some constraints(for example,the bending stress,the contact stress,the torsional strength,etc.),the optimal weight design of the gear transmission system can be transformed into the optimization problem for the objective function under the constraints.Moreover,both the shaft and the gear of the gear transmission system are considered simultaneously in our design.The hybrid Taguchi-genetic algorithm(HTGA)is employed to find the optimal design variables and the optimal weight of the system.An illustrated example for the single spur gear reducer is given to show that the optimal weight design problem can be successfully solved using the proposed design scheme.It also proves the high efficiency and feasibility of the algorithm in the gear design.
文摘BACKGROUND With increasing rates of liver transplantation and a stagnant donor pool,the annual wait list removals have remained high.Living donor liver transplantation(LDLT)is an established modality in expanding the donor pool and is the primary method of liver donation in large parts of the world.Marginal living donors,including those with hepatic steatosis,have been used to expand the donor pool.However,due to negative effects of steatosis on graft and recipient outcomes,current practice excludes overweight or obese donors with more than 10%macro vesicular steatosis.This has limited a potentially important source to help expand the donor pool.Weight loss is known to improve or resolve steatosis and rapid weight loss with short-term interventions have been used to convert marginal donors to low-risk donors in a small series of studies.There is,however,a lack of a consensus driven standardized approach to such interventions.AIM To assess the available data on using weight loss interventions in potential living liver donors with steatotic livers and investigated the feasibility,efficacy,and safety of using such donors on the donor,graft and recipient outcomes.The principal objective was to assess if using such treated donor livers,could help expand the donor pool.METHODS We performed a comprehensive literature review and meta-analysis on studies examining the role of short-term weight loss interventions in potential living liver donors with hepatic steatosis with the aim of increasing liver donation rates and improving donor,graft,and recipient outcomes.RESULTS A total of 6 studies with 102 potential donors were included.Most subjects were males(71).All studies showed a significant reduction in body mass index postintervention with a mean difference of-2.08(-3.06,1.10,I2=78%).A significant reduction or resolution of hepatic steatosis was seen in 93 of the 102(91.2%).Comparison of pre-and post-intervention liver biopsies showed a significant reduction in steatosis with a mean difference of-21.22(-27.02,-15.43,I2=56%).The liver donation rates post-intervention was 88.5(74.5,95.3,I2=42%).All donors who did not undergo LDLT had either recipient reasons or had fibrosis/steatohepatitis on post intervention biopsies.Post-operative biliary complications in the intervention group were not significantly different compared to controls with an odds ratio of 0.96[(0.14,6.69),I2=0].The overall post-operative donor,graft,and recipient outcomes in treated donors were not significantly different compared to donors with no steatosis.CONCLUSION Use of appropriate short term weight loss interventions in living liver donors is an effective tool in turning marginal donors to low-risk donors and therefore in expanding the donor pool.It is feasible and safe,with comparable donor,graft,and recipient outcomes,to non-obese donors.Larger future prospective studies are needed.
基金JM is supported by a Research Training Program ScholarshipDS is supported by an Australian National Health and Medical Research Council(NHMRC)RD Wright Biomedical Career Development Fellowship(GNT1123014)an NHMRC Investigator Grant(GNT1174886).
文摘Background:Weight-loss-induced fat loss improves cardiometabolic health in individuals with overweight and obesity;however,weight loss can also result in bone loss and increased fracture risk.Weight-loss-induced bone loss may be attenuated with exercise.Our aim was to compare changes in bone mineral density(BMD)in adults with overweight and obesity who undertook diet-induced weight loss alone or in combination with exercise.Methods:We included randomized controlled trials(RCTs)in adults with overweight or obesity(aged-18 years;body mass index-25 kg/m^(2))that prescribed diet-induced weight loss alone or in combination with supervised exercise,and measured any bone structural parameters.Risk of bias was assessed using the Cochrane Risk of Bias tool.Random-effects meta-analyses determined mean changes and net mean differences(95%confidence intervals(95%CIs))in the percentage of areal BMD(aBMD)change between groups.Results:We included 9 RCTs.Diet-induced weight loss led to significant losses in femoral neck aBMD(mean change:-1.73%(95%CI:-2.39%to-1.07%),p<0.001)and total hip aBMD(-2.19%(95%CI:-3.84%to-0.54%),p=0.009).Femoral neck aBMD losses were significantly greater in the diet-induced weight loss group compared to the exercise plus diet-induced weight loss group(net difference:-0.88%(95%CI:-1.73%to-0.03%));however,there were no differences in aBMD changes at any other skeletal site:total hip(-1.96%(95%CI:-4.59%to 0.68%))and lumbar spine(-0.48%(95%CI:-1.81%to 0.86%)).aBMD changes did not differ significantly according to exercise modality(resistance exercise,aerobic exercise,or a combination of the two)during diet-induced weight loss.Conclusion:Diet-induced weight loss led to greater femoral neck bone loss compared to diet-induced weight loss plus exercise.Bone loss at the total hip and lumbar spine was not attenuated by exercise during diet-induced weight loss.The lack of consistent skeletal benefits may be due to the insufficient duration and/or training intensities of most exercise interventions.Additional RCTs with appropriate,targeted exercise interventions should be conducted.
基金supported by the National Natural Science Foundation of China(62033008,61873143)。
文摘With the increasing intelligence and integration,a great number of two-valued variables(generally stored in the form of 0 or 1)often exist in large-scale industrial processes.However,these variables cannot be effectively handled by traditional monitoring methods such as linear discriminant analysis(LDA),principal component analysis(PCA)and partial least square(PLS)analysis.Recently,a mixed hidden naive Bayesian model(MHNBM)is developed for the first time to utilize both two-valued and continuous variables for abnormality monitoring.Although the MHNBM is effective,it still has some shortcomings that need to be improved.For the MHNBM,the variables with greater correlation to other variables have greater weights,which can not guarantee greater weights are assigned to the more discriminating variables.In addition,the conditional P(x j|x j′,y=k)probability must be computed based on historical data.When the training data is scarce,the conditional probability between continuous variables tends to be uniformly distributed,which affects the performance of MHNBM.Here a novel feature weighted mixed naive Bayes model(FWMNBM)is developed to overcome the above shortcomings.For the FWMNBM,the variables that are more correlated to the class have greater weights,which makes the more discriminating variables contribute more to the model.At the same time,FWMNBM does not have to calculate the conditional probability between variables,thus it is less restricted by the number of training data samples.Compared with the MHNBM,the FWMNBM has better performance,and its effectiveness is validated through numerical cases of a simulation example and a practical case of the Zhoushan thermal power plant(ZTPP),China.
基金Project supported by the Ph. D. Programs Foundation of the Ministry of Education of China （Grant No. 20093108110019）
文摘Information feedback strategies can influence the traffic efficiency of intelligent traffic systems greatly.Based on the more practical symmetrical two-route scenario with one entrance and one exit,an improved weighted mean velocity feedback strategy（WMVFS） is proposed,which is not sensitive to the precision of global position system（GPS） devices.The applicability of WMVFS to different weight factors,aggressive probabilities,densities of dynamic vehicles,and different two-route scenarios（symmetrical scenario and asymmetrical scenario with a speed limit bottleneck） is analyzed.Results show that WMVFS achieves the best performance compared with three other information feedback strategies when considering the traffic flux and stability.
基金financially supported in part by the National High Technology Research and Development Program of China(863Program,Grant No.2015AA016404)the National Natural Science Foundation of China(Grant Nos.51109020,51179019 and 51779029)the Fundamental Research Program for Key Laboratory of the Education Department of Liaoning Province(Grant No.LZ2015006)
文摘This paper explores a highly accurate identification modeling approach for the ship maneuvering motion with fullscale trial. A multi-innovation gradient iterative(MIGI) approach is proposed to optimize the distance metric of locally weighted learning(LWL), and a novel non-parametric modeling technique is developed for a nonlinear ship maneuvering system. This proposed method’s advantages are as follows: first, it can avoid the unmodeled dynamics and multicollinearity inherent to the conventional parametric model; second, it eliminates the over-learning or underlearning and obtains the optimal distance metric; and third, the MIGI is not sensitive to the initial parameter value and requires less time during the training phase. These advantages result in a highly accurate mathematical modeling technique that can be conveniently implemented in applications. To verify the characteristics of this mathematical model, two examples are used as the model platforms to study the ship maneuvering.
基金supported by the MSIT(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2019-2018-0-01423)supervised by the IITP(Institute for Information&communications Technology Promotion)supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2020R1A6A1A03038540).
文摘In this paper,a novel precoding scheme based on the Gauss-Seidel(GS)method is proposed for downlink massive multiple-input multiple-output(MIMO)systems.The GS method iteratively approximates the matrix inversion and reduces the overall complexity of the precoding process.In addition,the GS method shows a fast convergence rate to the Zero-forcing(ZF)method that requires an exact invertible matrix.However,to satisfy demanded error performance and converge to the error performance of the ZF method in the practical condition such as spatially correlated channels,more iterations are necessary for the GS method and increase the overall complexity.For efficient approximation with fewer iterations,this paper proposes a weighted GS(WGS)method to improve the approximation accuracy of the GS method.The optimal weights that accelerate the convergence rate by improved accuracy are computed by the least square(LS)method.After the computation of weights,the different weights are applied for each iteration of the GS method.In addition,an efficient method of weight computation is proposed to reduce the complexity of the LS method.The simulation results show that bit error rate(BER)performance for the proposed scheme with fewer iterations is better than the GS method in spatially correlated channels.
基金Supported by National Natural Science Foundation of China(11771354)
文摘In this article, we study positive solutions to the system{Aαu（x） = Cn,αPV∫Rn（a1（x-y）（u（x）-u（y）））/（｜x-y｜n＋α）dy = f（u（x）, Bβv（x） = Cn,βPV ∫Rn（a2（x-y）（v（x）-v（y））/（｜x-y｜n＋β）dy = g（u（x）,v（x））.To reach our aim, by using the method of moving planes, we prove a narrow region principle and a decay at infinity by the iteration method. On the basis of these results, we conclude radial symmetry and monotonicity of positive solutions for the problems involving the weighted fractional system on an unit ball and the whole space. Furthermore, non-existence of nonnegative solutions on a half space is given.
文摘Objective:To analyze the relationship between body mass index(BMI)before pregnancy and gestational weight gain throughout pregnancy with the incidence of preeclampsia.Methods:This was a systematic review-meta analysis of literature collected from three e-databases:Scopus,PubMed,and Science Direct.Quality assessment was measured with the Effective Public Health Practice Project methods.Meta-analysis was done by calculating the fixed and random-effects of odds ratio(OR)for each BMI category and gestational weight gain as compared with the incidence of preeclampsia.Results:Overweight was associated with a significantly increased risk of preeclampsia(OR=2.152,95%CI 1.363-3.400;P=0.001).Obesity was also associated with a noticeably increased risk of preeclampsia(OR=2.856,95%CI 1.755-4.649;P<0.001).Meanwhile,underweight was associated with a significantly reduced risk of preeclampsia(OR=0.639,95%CI 0.500-0.817;P<0.001)when compared with normal BMI.Pregnant women who gained weight below the standard throughout pregnancy was a protective factor from preeclampsia(OR=0.813,95%CI 0.610-1.083;P=0.157)whereas pregnant women who gained weight above the standard had almost doubled risk of preeclampsia(OR=1.850,95%CI 1.377-2.485;P<0.001).Conclusions:The result of this study affirms the role of overweight-obesity pre-pregnancy,and gestational weight gain above the standard during pregnancy as significant risk factors for developing preeclampsia.
文摘Memory-based collaborative recommender system (CRS) computes the similarity between users based on their declared ratings. However, not all ratings are of the same importance to the user. The set of ratings each user weights highly differs from user to user according to his mood and taste. This is usually reflected in the user’s rating scale. Accordingly, many efforts have been done to introduce weights to the similarity measures of CRSs. This paper proposes fuzzy weightings for the most common similarity measures for memory-based CRSs. Fuzzy weighting can be considered as a learning mechanism for capturing the preferences of users for ratings. Comparing with genetic algorithm learning, fuzzy weighting is fast, effective and does not require any more space. Moreover, fuzzy weightings based on the rating deviations from the user’s mean of ratings take into account the different rating scales of different users. The experimental results show that fuzzy weightings obviously improve the CRSs performance to a good extent.
