WLAN与2G/3G移动网络的集成

本文介绍了WLAN与2G/3G移动网络集成的两个标准,即3GPPR6中定义的WLAN与WCDMA的集成,以及UMA定义的WLAN与GSM/GPRS的集成。

5G/5G-Advanced/6G接入网安全技术演进及内生安全

网络安全技术在无线通信技术的演进中不断增强。介绍了现有5G网络的安全技术方案,并结合5G行业应用需求,探讨了5G-Advanced增强安全技术。立足于万物智能互联愿景,从海量设备连接、智能运维、人工智能/机器学习、区块链方面分析了内生安全技术。认为内生安全是6G网络安全研究的热点,轻量化是6G内生安全的主要特征之一。

Prevalence of Severe Anemia (Hb ≤ 5 g/dl) in Non-Dialyzed Chronic Renal Failure Patients in the Nephrology and Hemodialysis Department of Point G University Hospital

Introduction: Chronic renal failure (CRF) is defined as glomerular filtration rate (GFR) less than 60 ml/min/1.73m2 for at least three (3) months. Anemia is one of its most common complications. Anemia increases the risk factor for cardiovascular mortality by 18% per gram of hemoglobin loss. Objectives: To determine the prevalence and characteristics of this severe anemia, to determine the indications for transfusion, the complications related to this anemia, the evolution and the prognosis of these patients. Materials and Methods: This was a descriptive study with retrospective data collection over 18 months (January 1, 2017 to June 30, 2018) that included hospitalized CRF patients. Were included, non-dialyzed chronic renal failure patients with Hb ≤ 5 g/dl hospitalized during the said period. Not included were chronic renal failure patients with an Hb level ≥ 5 g/dl, those followed up and/or hospitalized outside the study period. Results: Among 1176 patients, 26 had severe anemia (Hb level ≤ 5 g/dl) on CRF, a prevalence of 2.21%. The mean age was 40 years ± 32.62 with extremes of 15 and 67 years. Seventeen women and 9 men. The etiology of chronic renal failure (CRF) was hypertensive vascular nephropathy in 50% of cases. CRF was end-stage in 18 patients (69.2%). The mean hemoglobin level was 4.10 g/dl ± 0.64 with extremes of 2 and 5 g/dl. The anemia was microcytic hypochromic in 50% and aregenerative (96.2%). The main symptoms were asthenia in 20 cases (76.9%), dizziness in 20 cases (76.9%), exertional dyspnea in 19 cases (73.1%). Signs of cardiac decompensation (n = 12) were jugular turgor 10 cases (38.5%), hepato-jugular reflux 06 cases (23.1%), mitral insufficiency murmur 06 cases (23.1%). The main complication was left ventricular hypertrophy 17 cases (77.3%). There was no correlation between anemia and sex (p = 0.291), age (p = 0.778), malaria (p = 0.158), etiology of CRF (p = 0.26). The evolution after treatment of anemia was favorable in 19 patients (73.1%), unfavorable in 02 patients (7.7%) and 05 deaths (19.2%). The deaths were of cardiovascular cause: left ventricular insufficiency 04 cases, stroke 01 case. Conclusion: Anemia is frequent in patients with chronic renal failure and remains an important risk factor for cardiovascular disease and poor general condition.

Hybrid Metamodeling/Metaheuristic Assisted Multi-Transmitters Placement Planning

With every passing day,the demand for data traffic is increasing,and this urges the research community not only to look for an alternating spectrum for communication but also urges radio frequency planners to use the existing spectrum efficiently.Cell sizes are shrinking with every upcoming communication generation,which makes base station placement planning even more complex and cumbersome.In order to make the next-generation cost-effective,it is important to design a network in such a way that it utilizes the minimum number of base stations while ensuring seamless coverage and quality of service.This paper aims at the development of a new simulation-based optimization approach using a hybrid metaheuristic and metamodel applied in a novel mathematical formulation of the multi-transmitter placement planning(MTPP)problem.We first develop a new mathematical programming model for MTPP that is flexible to design the locations for any number of transmitters.To solve this constrained optimization problem,we propose a hybrid approach using the radial basis function(RBF)metamodel to assist the particle swarm optimizer(PSO)by mitigating the associated computational burden of the optimization procedure.We evaluate the effectiveness and applicability of the proposed algorithm by simulating the MTPP model with two,three,four and five transmitters and estimating the Pareto front for optimal locations of transmitters.The quantitative results show that almost maximum signal coverage can be obtained with four transmitters;thus,it is not a wise idea to use higher number of transmitters in the model.Furthermore,the limitations and future works are discussed.

不依赖GNSS的输电线路双端行波故障测距

双端行波故障测距技术是实现输电线路快速故障恢复的有效手段。传统双端行波测距方法依赖全球卫星导航系统(global navigation satellite system,GNSS)同步线路两侧采样数据,存在信号误差、丢失等风险。基于行波的传播时延和时移不变性,该文提出一种不依赖GNSS的双端行波故障测距方案。理论层面,定量分析时间同步误差及其对故障前工频方向行波相角关系的影响,推导证明通过本地计算方向行波相量进行双端故障测距的可行性。算法层面,首先,通过小波变换检测故障初始行波到达时间;其次,通过对故障前工频方向行波的傅里叶变换求解附加相角差,进而完成双端测距。仿真结果表明,在考虑电压互感器传变特性的条件下,所提方案在不同故障情况、采样频率和噪声干扰等影响下均保持了良好的测距性能。由于无须增设GNSS、硬件时间戳等辅助硬件设备,所提方案便于现存设备的技术更新与工程应用。

基于提升距离保护适应性的改进VSG控制策略研究

随着新能源的大规模并网,新能源虚拟同步发电机(VSG)控制技术得到广泛应用。针对现有VSG控制下传统距离保护动作失效的问题,提出1种基于提升距离保护适应性的改进VSG控制策略。首先,对传统距离保护失效的原理进行分析;然后,以减小故障点两侧电流相位差为控制目标,通过定量设计VSG内环控制中的虚拟阻抗值,实现对换流器输出故障电流特性的主动控制;最后,在Matlab/Simulink中搭建新能源并网交流线路发生短路故障时的仿真模型。仿真分析表明,所提改进VSG控制策略能有效支撑传统距离保护的动作可靠性。

探索6G无线系统设计

1当前6G发展处于技术研发的关键阶段,当前,5G已经在全球范围内实现大规模商用,6G作为新一代综合性信息基础设施,将突破传统移动通信范畴,实现通信与感知、计算、人工智能等深度融合,具备空天地海一体化的全球覆盖能力,将在5G“万物互联”基础上进一步实现“万物智联”。根据移动通信产业发展规律,6G发展大致可分为三个阶段,2020至2024年是6G概念形成、技术突破阶段,形成愿景需求及概念,深入研究移动通信基础理论,实现关键核心技术突破,为6G国际标准奠定技术基础。2025至2029年是国际标准化研制阶段,形成6G技术方案和架构,完成6G国际标准研制。2026至2030年是产业研发阶段,全面推进产业研发,构建完整产业生态,适时启动6G商用。

医院药学指南制定中的证据与推荐意见GRADE系统评级方法及应用

目前,国际上存在多种证据与推荐意见分级系统,对临床医务工作者阅读指南证据和推荐意见造成困扰。证据推荐分级的评估、制定与评价(GRADE)系统目前是全球使用最为广泛的证据与推荐意见分级系统,本文简单地介绍GRADE系统证据质量评级及影响推荐意见形成的4个主要因素,并结合中国医院药学界发起制定的、在国际上发表的几部药学指南举例阐述,以帮助临床医务工作者了解GRADE系统,以批判性思维运用指南证据和推荐意见指导临床实践行为。

Using deep neural networks coupled with principal component analysis for ore production forecasting at open-pit mines

Ore production is usually affected by multiple influencing inputs at open-pit mines.Nevertheless,the complex nonlinear relationships between these inputs and ore production remain unclear.This becomes even more challenging when training data(e.g.truck haulage information and weather conditions)are massive.In machine learning(ML)algorithms,deep neural network(DNN)is a superior method for processing nonlinear and massive data by adjusting the amount of neurons and hidden layers.This study adopted DNN to forecast ore production using truck haulage information and weather conditions at open-pit mines as training data.Before the prediction models were built,principal component analysis(PCA)was employed to reduce the data dimensionality and eliminate the multicollinearity among highly correlated input variables.To verify the superiority of DNN,three ANNs containing only one hidden layer and six traditional ML models were established as benchmark models.The DNN model with multiple hidden layers performed better than the ANN models with a single hidden layer.The DNN model outperformed the extensively applied benchmark models in predicting ore production.This can provide engineers and researchers with an accurate method to forecast ore production,which helps make sound budgetary decisions and mine planning at open-pit mines.

Adult neurogenesis:a real hope or a delusion?

Adult neurogenesis,the process of creating new neurons,involves the coordinated division,migration,and differentiation of neural stem cells.This process is restricted to neurogenic niches located in two distinct areas of the brain:the subgranular zone of the dentate gyrus of the hippocampus and the subventricular zone of the lateral ventricle,where new neurons are generated and then migrate to the olfactory bulb.Neurogenesis has been thought to occur only during the embryonic and early postnatal stages and to decline with age due to a continuous depletion of neural stem cells.Interestingly,recent years have seen tremendous progress in our understanding of adult brain neurogenesis,bridging the knowledge gap between embryonic and adult neurogenesis.Here,we discuss the current status of adult brain neurogenesis in light of what we know about neural stem cells.In this notion,we talk about the importance of intra cellular signaling molecules in mobilizing endogenous neural stem cell prolife ration.Based on the current understanding,we can declare that these molecules play a role in targeting neurogenesis in the mature brain.However,to achieve this goal,we need to avoid the undesired proliferation of neural stem cells by controlling the necessary checkpoints,which can lead to tumorigenesis and prove to be a curse instead of a blessing or hope.

A single micro-LED manipulation system based on micro-gripper

Micro-LEDs(μLEDs)have advantages in terms of brightness,power consumption,and response speed.In addition,they can also be used as micro-sensors implanted in the body via flexible electronic skin.One of the key techniques involved in the fabrication ofμLED-based devices is transfer printing.Although numerous methods have been proposed for transfer printing,improving the yield ofμLED arrays is still a formidable task.In this paper,we propose a novel method for improving the yield ofμLED arrays transferred by the stamping method,using an innovative design of piezoelectrically driven asymmetric micro-gripper.Traditional grippers are too large to manipulateμLEDs,and therefore two micro-sized cantilevers are added at the gripper tips.AμLED manipulation system is constructed based on the micro-gripper together with a three-dimensional positioning system.Experimental results using this system show that it can be used successfully to manipulateμLED arrays.

Strain-dependent alpha-synuclein spreading in Parkinson's disease and multiple system atrophy

Parkinson's disease(PD) and atypical Parkinsonian syndromes,such as multiple system atrophy(MSA) and Dementia with Lewy bodies,are neurodegenerative movement disorders characterized by the accumulation of alphasynuclein(a-syn) aggregates.These a-syn aggregates propagate throughout the brain in a prion-like manner,where pathological a-syn recruits endogenous a-syn to form insoluble aggregates.Oligomeric forms representing intermediates on the way to insoluble aggregates result in the most pronounced neurotoxic effects.

Tumor necrosis factor-alpha, transforming growth factor-beta, degree of lower urinary tract symptoms as predictors of erectile dysfunction in benign prostatic hyperplasia patients

Objective: Erectile dysfunction (ED) is a condition of insufficient penile erection, consistently or recurrently, for sexual activity. Tumor necrosis factor-alpha (TNF-α) induces transforming growth factor-beta (TGF-β), which causes the transition of epithelial cells into mesenchymal cells that affect ED. This study aimed to evaluate the roles of TNF-α, TGF-β, degree of lower urinary tract symptoms, and prostatic volume for the presence of ED in benign prostatic hyperplasia (BPH) patients.Methods: Our study performed an analytic observational retrospective cohort study using secondary data from four hospitals in Bali, Indonesia, including medical records and other administrative data. The sample was BPH patients with several history qualifications.Results: Our sample was 83 respondents, ranging from 50 years to 80 years, 61 respondents with ED and 22 with non-ED. The International Prostate Symptom Score showed a significant result, which indicates that ED is more common in patients with higher International Prostate Symptom Score (p=0.002). Moreover, the TNF-α of ≥43.9 pg/mg and TGF-β of ≥175.8 pg/mL were significantly associated with the presence of ED in BPH patients (p<0.0001). Despite these results, prostate volume is not significant with ED (p=0.947).Conclusion: TNF-α, TGF-β, and lower urinary tract symptoms severity can predict the occurrence of ED in BPH, while prostatic volume was not significant.

Targeting gut microbiota in osteoporosis:impact of the microbial based functional food ingredients

Osteoporosis is the most common bone disorder,characterized by low bone mineral density and microarchitectural deterioration of the bone tissue,which increases the susceptibility to fracture.In the past decade,emerging research findings reported the implication of gut microbiota on bone health and osteoporosis pathology.Osteoporotic patients or individuals with a lower bone mineral density exhibit an alteration of the gut microbiota at several taxonomic levels.Additional reports demonstrate that gut microbiota regulates bone metabolism through the modulation of the gut function(mineral availability and absorption,gut integrity),the immune system,and the endocrine system.Thus,based on the vital role of gut microbiota on bone health,it has emerged as a novel therapeutic target for the prevention of bone loss and the treatment of osteoporosis.Microbial-based functional food ingredients,such as probiotics,prebiotics,synbiotics,and fermented foods,have been developed to alter the gut microbiota composition and function and thus,to provide benefits to the host bone health.Despite promising initial results,microbial-based therapies are still under investigation.Moreover,additional animal studies and clinical trials are needed to understand the interactions between gut microbiota and bone metabolism before further applications.

Ultrathin Zincophilic Interphase Regulated Electric Double Layer Enabling Highly Stable Aqueous Zinc‑Ion Batteries

The practical application of aqueous zinc-ion batteries for large-grid scale systems is still hindered by uncontrolled zinc dendrite and side reactions.Regulating the elec-trical double layer via the electrode/electrolyte interface layer is an effective strategy to improve the stability of Zn anodes.Herein,we report an ultrathin zincophilic ZnS layer as a model regu-lator.At a given cycling current,the cell with Zn@ZnS electrode displays a lower potential drop over the Helmholtz layer(stern layer)and a suppressed diffuse layer,indicating the regulated charge distribution and decreased electric double layer repulsion force.Boosted zinc adsorption sites are also expected as proved by the enhanced electric double-layer capacitance.Consequently,the symmetric cell with the ZnS protection layer can stably cycle for around 3,000 h at 1 mA cm^(-2) with a lower overpotential of 25 mV.When coupled with an I2/AC cathode,the cell demonstrates a high rate performance of 160 mAh g^(-1) at 0.1 A g^(-1) and long cycling stability of over 10,000 cycles at 10 A g^(-1).The Zn||MnO_(2) also sustains both high capacity and long cycling stability of 130 mAh g^(-1) after 1,200 cycles at 0.5 A g^(-1).

Nitrogen mineralization in the oldest climax communities in the eastern Mediterranean region

In this study,we investigated how tree species affect N mineralization in connection to some soil properties and seconder metabolite levels of litter,in the soil of the old-est native forest communities.In the oldest pure communi-ties of Pinus nigra(PN),Fagus orientalis(FO),and Abies bornmuelleriana(AB)in the mountain range of Mount Uludağ,Bursa,Turkey,annual net yield and N mineraliza-tion in the 0-5-and 5-20-cm soil layers were determined in a field incubation study over 1 year.Sampling locations were chosen from 1300 to 1600 m a.s.l.,and moisture content(%),pH,water-holding capacity(%),organic C,total N,and C/N ratio,and annual net mineral N yield of the soil and hydro-lyzed tannic acid and total phenolic compounds in litter were compared for these forest communities.F.orientalis had the highest annual net Nmin yield(43.9±4.8 kg ha^(-1) a^(-1)),P.nigra the lowest(30.5±4.2 kg ha^(-1) a^(-1)).Our findings show that in the oldest forest ecosystems,the seasonal soil moisture content and tree species play an essential role in N cycling and that hydrolyzed tannic acids and total phenolic compounds effectively control N turnover.Tannic acid and total phenolics in the litter were found to inhibit nitrification,but total phenolics were found to stimulate ammonification.

A novel approach to the dynamic response analysis of Euler-Bernoulli beams resting on a Winkler soil model and subjected to impact loads

This work presents a novel approach to the dynamic response analysis of a Euler-Bernoulli beam resting on a Winkler soil model and subjected to an impact loading.The approach considers that damping has much less importance in controlling the maximum response to impulsive loadings because the maximum response is reached in a very short time,before the damping forces can dissipate a significant portion of the energy input into the system.The development of two sine series solutions,relating to different types of impulsive loadings,one involving a single concentrated force and the other a distributed line load,are presented.This study revealed that when a simply supported Euler-Bernoulli beam,resting on a Winkler soil model,is subject to an impact load,the resulting vertical displacements,bending moments and shear forces produced along the span of the beam are considerably affected.In particular,the quantification of this effect is best observed,relative to the corresponding static solution,via an amplification factor.The computed impact amplification factors,for the sub-grade moduli used in this study,were in magnitude greater than 2,thus confirming the multiple-degree-of-freedom nature of the problem.

Bayesian Filtering for High-Dimensional State-Space Models With State Partition and Error Compensation

In the era of exponential growth of data availability,the architecture of systems has a trend toward high dimensionality,and directly exploiting holistic information for state inference is not always computationally affordable.This paper proposes a novel Bayesian filtering algorithm that considers algorithmic computational cost and estimation accuracy for high-dimensional linear systems.The high-dimensional state vector is divided into several blocks to save computation resources by avoiding the calculation of error covariance with immense dimensions.After that,two sequential states are estimated simultaneously by introducing an auxiliary variable in the new probability space,mitigating the performance degradation caused by state segmentation.Moreover,the computational cost and error covariance of the proposed algorithm are analyzed analytically to show its distinct features compared with several existing methods.Simulation results illustrate that the proposed Bayesian filtering can maintain a higher estimation accuracy with reasonable computational cost when applied to high-dimensional linear systems.

Transurethral prostate surgery in prostate cancer patients: A population-based comparative analysis of complication and mortality rates

Objective:Prostate cancer(PCa)patients might experience lower urinary tract symptoms as those diagnosed with benign prostatic hyperplasia(BPH).Some of them might be treated for their lower urinary tract symptoms instead of PCa.We aimed to test the effect of PCa versus BPH on surgical outcomes after transurethral prostate surgery,namely complication and mortality rates.Methods:Within the American College of Surgeons National Surgical Quality Improvement Program database(2011-2016),we identified patients who underwent transurethral resection of the prostate,photoselective vaporization,or laser enucleation.Patients were stratified according to postoperative diagnosis(PCa vs.BPH).Univariable and multivariable logistic regression models evaluated the predictors of perioperative morbidity and mortality.A formal test of interaction between diagnosis and surgical technique used was performed.Results:Overall,34542 patients were included.Of all,2008(5.8%)had a diagnosis of PCa.The multivariable logistic regression model failed to show statistically significant higher rates of postoperative complications in PCa patients(odds ratio:0.9,95%confidence interval:0.7-1.1;p=0.252).Moreover,similar rates of perioperative mortality(p=0.255),major acute cardiovascular events(p=0.581),transfusions(p=0.933),and length of stay of more than or equal to 30 days(p=0.174)were found.Additionally,all tests failed to show an interaction between post-operative diagnosis and surgical technique used.Conclusion:Patients diagnosed with PCa do not experience higher perioperative morbidity or mortality after transurethral prostate surgery when compared to their BPH counterparts.Moreover,the diagnosis seems to not influence surgical technique outcomes.

The acceleration of a high-charge electron bunch to 10 GeV in a 10-cm nanoparticle-assisted wakefield accelerator

An intense laser pulse focused onto a plasma can excite nonlinear plasma waves.Under appropriate conditions,electrons from the background plasma are trapped in the plasma wave and accelerated to ultra-relativistic velocities.This scheme is called a laser wakefield accelerator.In this work,we present results from a laser wakefield acceleration experiment using a petawatt-class laser to excite the wakefields as well as nanoparticles to assist the injection of electrons into the accelerating phase of the wakefields.We find that a 10-cm-long,nanoparticle-assisted laser wakefield accelerator can generate 340 pC,10±1.86 GeV electron bunches with a 3.4 GeV rms convolved energy spread and a 0.9 mrad rms divergence.It can also produce bunches with lower energies in the 4–6 GeV range.