Multivariate Aggregated NOMA for Resource Aware Wireless Network Communication Security

NonorthogonalMultiple Access(NOMA)is incorporated into the wireless network systems to achieve better connectivity,spectral and energy effectiveness,higher data transfer rate,and also obtain the high quality of services(QoS).In order to improve throughput and minimum latency,aMultivariate Renkonen Regressive Weighted Preference Bootstrap Aggregation based Nonorthogonal Multiple Access(MRRWPBA-NOMA)technique is introduced for network communication.In the downlink transmission,each mobile device’s resources and their characteristics like energy,bandwidth,and trust are measured.Followed by,the Weighted Preference Bootstrap Aggregation is applied to recognize the resource-efficient mobile devices for aware data transmission by constructing the different weak hypotheses i.e.,Multivariate Renkonen Regression functions.Based on the classification,resource and trust-aware devices are selected for transmission.Simulation of the proposed MRRWPBA-NOMA technique and existing methods are carried out with different metrics such as data delivery ratio,throughput,latency,packet loss rate,and energy efficiency,signaling overhead.The simulation results assessment indicates that the proposed MRRWPBA-NOMA outperforms well than the conventional methods.

CONSERVATIVE ESTIMATING FUNCTION IN THE NONLINEAR REGRESSION MODEL WITH AGGREGATED DATA

The purpose of this paper is to study the theory of conservative estimating functions in nonlinear regression model with aggregated data. In this model, a quasi-score function with aggregated data is defined. When this function happens to be conservative, it is projection of the true score function onto a class of estimation functions. By constructing, the potential function for the projected score with aggregated data is obtained, which have some properties of log-likelihood function.

Wavelet-Aggregated Signal in Earthquake Prediction

The concept of aggregated signal is introduced. Quantitatively, an aggregated signal can be defined as the scalar signal: it accumulates in its own variations only those spectral components that are presented simultaneously in each scalar time series of the multidimensional signal to be analyzed. Moreover, an algorithm of aggregation is proposed to suppress the spectral components that are present in any of the scalar components but absent in others (these components can be called local disturbance signals, for instance of technogenic nature). The main purpose of constructing the aggregated signal is to make clearer the common tendency of low-frequency data-flow in geophysical networks, which indicates an increase in collective behavior.It is known that almost all models of the process of earthquake preparation have pointed out an increase in collective behavior of components of geophysical fields in the region of preparation when the coming geocatastrophe has entered its long- and mid-term stages.

THE INFLUENCE OF HEAT TREATMENT ON STRUCTURES OF THE AGGREGATED STATE OF POLYAMIDE-1010

The structural parameters of the aggregated state of polyamide （PA）-1010 annealedat various temperatures were computed by means of the desmearing intensity from SmallAngle X-ray Scattering （SAXS） measurements and by using the concept of the distance dis-tribution function. The results indicated that the structural parameters of the aggregatedstate were strongly dependent upon heat treatment conditions and the maximum valuesof the structural parameters were obtained for the samples annealed at T = 175℃. Theparticle size Z annealed at different temperature was ranged between 8.1--12.8nm, and thevalues of the distance distribution function Pmax（Z） were obtained when Z = 4.0--6.8nm.Using one dimension electron density correlation function （1D EDCF） method long period（L） and thickness of the lamellar （d0） were estimated and were found to increase with theincrease of the degree of crystallinity.

Aggregated morphodynamic modelling of tidal inlets and estuaries

Aggregation is used to represent the real world in a model at an appropriate level of abstraction.We used the convection-diffusion equation to examine the implications of aggregation progressing from a three-dimensional(3D)spatial description to a model representing a system as a single box that exchanges sediment with the adjacent environment.We highlight how all models depend on some forms of parametric closure,which need to be chosen to suit the scale of aggregation adopted in the model.All such models are therefore aggregated and make use of some empirical relationships to deal with sub-scale processes.One such appropriately aggregated model,the model for the aggregated scale morphological interaction between tidal basin and adjacent coast(ASMITA),is examined in more detail and used to illustrate the insight that this level of aggregation can bring to a problem by considering how tidal inlets and estuaries are impacted by sea level rise.

COMMUNITY ANALYSIS OF AGGREGATED BACTERIA IN SOUTHERN LAKE BAIKAL

[KG(0.01mm]This study focuses on the community structure of aggregated bacteria in Lake Baikal and relationships with free-living bacteria. Fluorescent in situ hybridization (FISH) methods were used in samples of bacteria taken in April, 2001. Bacterial counts of free-living bacteria by DAPI staining ranged from 0.2×10 6 to 3.2×10 6 cells·mL -1, decreasing with depth, whereas aggregated bacterial numbers dramatically increased with depth, ranging from 0.4×10 4 to 3.3×10 4 cells·mL -1. Ratios of EUB probe binding cells to DAPI counts ranged from 52.3 to 74.1% in free-living bacteria and from 39.6 to 66.7% in aggregated bacteria, respectively. Community composition of aggregated bacteria was very different from free-living bacteria, especially at 25m depth where highest phytoplankton numbers were observed. The vertical profile of aggregated bacteria community was very characteristic. Beta-Proteobacteria increased with depth down to 100m. At 250m, gamma-Proteobacteria was 44% of DAPI bound cells, while other groups were less than 1%. We conclude that community structures of free-living and aggregated bacteria were different, and they may sustain the ecosystem in independent ways.

Component Carrier Selection and Beamforming on Carrier Aggregated Channels in Heterogeneous Networks

In this paper, component carrier selection and beamforming on carrier aggregated channels in Heterogeneous Networks are proposed. The scheme jointly selects the component carrier and precoding (i.e. beamforming) vectors with the cooperation of the other cells to deal with the interference between Macro cell and Pico cell. The component carrier selection and beamforming is achieved by optimizing the multi-cell downlink throughput. This optimization results in shutting down a subset of the component carrier in order to allow for a perfect interference removal at the receive side in the dense low power node deployment scenario. Additionally, algorithm based on Branch and Bound Method is used to reduce the search complexity of the algorithm. Simulation results show that the proposed scheme can achieve high cell-average and cell-edge throughput for the Pico cell in the Heterogeneous Networks.

Effects of Conservation Tillage on Total and Aggregated Soil Organic Carbon in the Andes

Many Andisols of the Andes have been disturbed by traditional potato-based rotation agriculture disrupting soil structure, water retention capacity and organic matter content. This study was undertaken to investigate the contribution of conservation farming technology or reduced tillage in potato-based rotations in the Colombian Andes in order to rehabilitate total and aggregated soil organic C in disturbed organic matter-rich Andisols. Soils were sampled from farms with 7-year of reduced tillage and farms with conventional farming practices. Ultrasound energy was applied to samples to disrupt aggregation and total soil C was determined in order to investigate the amount of carbon held inside the aggregates of different soil size classes. Results indicated that reduced tillage in potato-based crop rotations increased the soil C concentration and average C content in the whole profile (≈117 cm depth) by 50 and 33% (1636 t C ha?1 vs. 1224 t C ha?1), respectively, as compared to conventional farming practices. Carbon content increased 177% in the subsoil (A2 horizon, 78 -117 cm depth, from 215 to 596 t?ha?1), although most of the soil C was in the A1 horizon (between 0 -78 cm average thickness, 1097 t?ha?1). These increases show that reduced tillage enhances C stores in Andisols which are already high in organic matter. In addition, C in aggregates represented more than 80% of the total organic matter and it was positively affected by conservation practices. The C increase was preferential in the smaller macroaggregates (

Mixed Contiguous and Aggregated Spectrum Allocation Algorithm for CR based TD-LTE System

Cognitive Radio (CR) is a promising technology to increase the efficiency of spectrum by opportunistic access. However, in many cases the sensed spectrum is so broken that it cannot be utilized sufficiently with traditional continuous spectrum allocation strategy. Spectrum aggregation can make full use of narrow spectrum fragments while the overhead it brings may reduce the overall performance of the system. This paper proposes a Mixed Contiguous and Aggregated Spectrum Allocation (MixCASA) algorithm for CR based TD-LTE Networks. This algorithm combines contiguous with discontiguous spectrum allocation together in order to guarantee the feasibility and efficiency of system. Simulation results show that the MixCASA algorithm can increase the number of allocated channels, and reduce the overhead brought by excessive spectrum aggregation as well.

Grain erosion wear properties and grinding performance of porous aggregated cubic boron nitride abrasive wheels

Cubic boron nitride(cBN)superabrasive grinding wheels exhibit unique advantages in the grinding of difficult-to-cut materials with high strength and toughness,such as titanium alloys and superalloys.However,grinding with multilayered metallic cBN superabrasive wheels faces problems in terms of grain wear resistance,the chip storage capability of the working layers and the stability and controllability of the dressing process.Therefore,in this work,novel metallic cBN superabrasive wheels with aggregated cBN(AcBN)grains and open pore structures were fabricated to improve machining efficiency and surface quality.Prior to the grinding trials,the airborne abrasive blasting process was conducted and the abrasive blasting parameters were optimized in view of wear properties of cBN grains and metallic matrix materials.Subsequently,the comparative experiments were performed and then the variations in grinding force and force ratio,grinding temperature,tool wear morphology and ground surface quality of the multilayered AcBN grinding wheels were investigated during machining Ti-6Al-4V alloys.In consideration of the variations of grain erosion wear volume and material removal rate per unit of pure metallic matrix materials as the abrasive blasting parameters changes,the optimal abrasive blasting parameters were identified as the SiC abrasive mesh size of 60#and the abrasive blasting distance and time of 60 mm and 15 s,respectively.The as-developed AcBN grains exhibited better fracture toughness and impact resistance than monocrystalline cBN(McBN)grains because of the existence of metal-bonded materials amongst multiple cBN particles that decreased crack propagation inside whole grains.The metallic porous AcBN wheels had lower grinding forces and temperature and better ground surface quality than vitrified McBN wheels due to the constant layer-by-layer exposure of cBN particles in the working layer of AcBN wheels.

Optimized Dispatching Method for Flexibility Improvement of AC-MTDC Distribution Systems Considering Aggregated Electric Vehicles

With the increasing use of renewable resources and electric vehicles(EVs), the variability and uncertainty in their nature put forward a high requirement for flexibility in AC distribution system incorporating voltage source converter(VSC) based multi-terminal direct current(MTDC) grids. In order to improve the capability of distribution systems to cope with uncertainty, the flexibility enhancement of AC-MTDC distribution systems considering aggregated EVs is studied. Firstly, the charging and discharging model of one EV is proposed considering the users' demand difference and traveling needs. Based on this, a vehicle-to-grid(V2G) control strategy for aggregated EVs to participate in the flexibility promotion of distribution systems is provided. After that, an optimal flexible dispatching method is proposed to improve the flexibility of power systems through cooperation of VSCs, controllable distributed generations(CDGs), aggregated EVs, and energy storage systems(ESSs). Finally, a case study of an AC-MTDC distribution system is carried out. Simulation results show that the proposed dispatching method is capable of effectively enhancing the system flexibility, reducing renewable power curtailment, decreasing load abandonment, and cutting down system cost.

Aggregated carbon dots-loaded macrophages treat sepsis by eliminating multidrug-resistant bacteria and attenuating inflammation

Sepsis,caused by uncontrollable infection and inflammatory response,leads to more than 30 million infected patients and results in high morbidity worldwide every year.Currently,no efficient approaches have been developed for sepsis therapy due to antimicrobial resistance and inflammatory storm.Here,we report macrophages loaded with aggregated carbon dots(ACDs)in the lysosome,termed MCDs,to treat sepsis in immunosuppressive mice.The ACDs are constructed by negative CDs and amine-abundant polyethyleneimine(PEI),enabling them to bear the strong antibacterial ability and enhanced photoluminescent efficacy.The ACDs are specifically located in the macrophage lysosomes,efficiently enhancing the multidrug-resistant bacteria-killing ability of MCDs.More importantly,the MCDs possess superior anti-inflammatory effects such as reducing the number of pro-inflammatory(M1)and stimulating anti-inflammatory(M2)macrophages.These effects upregulate the inflammatory cytokines(TNF-α,IL-1β,IL-4,and IL-10),ultimately resulting in increased sepsis survival.Our work provides an intelligent approach to overcoming multidrug-resistant bacteria-induced infection from sepsis patients and paves a new avenue on employing nanoparticle-loaded cells for combating inflammation-related infection.

A novel forecasting approach to schedule aggregated electric vehicle charging

To be able to schedule the charging demand of an electric vehicle fleet using smart charging,insight is required into different charging session characteristics of the considered fleet,including the number of charging sessions,their charging demand and arrival and departure times.The use of forecasting techniques can reduce the uncertainty about these charging session characteristics,but since these characteristics are interrelated,this is not straightforward.Remarkably,forecasting frameworks that cover all required characteristics to schedule the charging of an electric vehicle fleet are absent in scientific literature.To cover this gap,this study proposes a novel approach for forecasting the charging requirements of an electric vehicle fleet,which can be used as input to schedule their aggregated charging demand.In the first step of this approach,the charging session characteristics of an electric vehicle fleet are translated to three parameter values that describe a virtual battery.Subsequently,optimal predictor variable and hyperparameter sets are determined.These serve as input for the last step,in which the virtual battery parameter values are forecasted.The approach has been tested on a real-world case study of public charging stations,considering a high number of predictor variables and different forecasting models(Multivariate Linear Regression,Random Forest,Artificial Neural Network and k-Nearest Neighbors).The results show that the different virtual battery parameters can be forecasted with high accuracy,reaching R^(2) scores up to 0.98 when considering 400 charging stations.In addition,the results indicate that the forecasting performance of all considered models is somehow similar and that only a low number of predictor variables are required to adequately forecast aggregated electric vehicle charging characteristics.

Extension of Paraconsistent Many-Valued Similarity Method to Group Decision

The Paraconsistent Many-Valued Similarity (PMVS) method for multi-attribute decision making will be incomplete as a decision model if it is not extended to the realm of group decision-making. Therefore, in this article, our primary objective is to show how the paraconsistent many-valued similarity method can be used to solve group decision-making problems involving choice making or ranking of a finite set of decision alternatives. Moreover, since weights are very important parameters in multi-attribute decision-making, we have introduced the Borda rule to calculate the weights of experts and that of every criterion under consideration. To demonstrate how the proposed method works, a numerical example on energy sources of an economy from the points of view of a group of experts is investigated. Further, we compare the results of this new approach with that of fuzzy TOPSIS group decision-making method to illustrate the robustness and effectiveness of the former.

Impacts of Aggregation Methods and Trophospecies Number on the Structure and Function of Marine Food Webs

Aggregation of species with similar ecological properties is one of the effective methods to simplify food web researches.However,species aggregation will affect not only the complexity of modeling process but also the accuracy of models’outputs.Selection of aggregation methods and the number of trophospecies are the keys to study the simplification of food web.In this study,three aggregation methods,including taxonomic aggregation(TA),structural equivalence aggregation(SEA),and self-organizing maps(SOM),were analyzed and compared with the linear inverse model–Markov Chain Monte Carlo(LIM-MCMC)model.Impacts of aggregation methods and trophospecies number on food webs were evaluated based on the robustness and unitless of ecological net-work indices.Results showed that aggregation method of SEA performed better than the other two methods in estimating food web structure and function indices.The effects of aggregation methods were driven by the differences in species aggregation principles,which will alter food web structure and function through the redistribution of energy flow.According to the results of mean absolute percentage error(MAPE)which can be applied to evaluate the accuracy of the model,we found that MAPE in food web indices will increase with the reducing trophospecies number,and MAPE in food web function indices were smaller and more stable than those in food web structure indices.Therefore,trade-off between simplifying food webs and reflecting the status of ecosystem should be con-sidered in food web studies.These findings highlight the importance of aggregation methods and trophospecies number in the analy-sis of food web simplification.This study provided a framework to explore the extent to which food web models are affected by dif-ferent species aggregation,and will provide scientific basis for the construction of food webs.

Small molecules to target tau amyloid aggregation

Protein aggregation has been linked with many neurodegenerative diseases,such as Alzheimer’s disease(AD)or Parkinson’s disease.AD belongs to a group of heterogeneous and incurable neurodegenerative disorders collectively known as tauopathies.They comprise frontotemporal dementia,Pick’s disease,or corticobasal degeneration,among others.The symptomatology varies with the specific tau protein variant involved and the affected brain region or cell type.However,they share a common neuropathological hallmark-the formation of proteinaceous deposits named neurofibrillary tangles.Neurofibrillary tangles,primarily composed of aggregated tau(Zhang et al.,2022),disrupt normal neuronal functions,leading to cell death and cognitive decline.

Mechanical Behavior Based on Aggregates Microstructure of Ultra-high Performance Concrete

We developed ultra-high performance concrete(UHPC)incorporating mullite sand and brown corundum sand(BCS),and the quartz sand UHPC was utilized to prepare for comparison.The properties of compressive strength,elastic modulus,ultrasonic pulse velocity,flexural strength,and toughness were investigated.Scanning electron microscopy and nanoindentation were also conducted to reveal the underlying mechanisms affecting macroscopic performance.Due to the superior interface bonding properties between mullite sand and matrix,the compressive strength and flexural toughness of UHPC have been significantly improved.Mullite sand and BCS aggregates have higher stiffness than quartz sand,contributing to the excellent elastic modulus exhibited by UHPC.The stiffness and volume of aggregates have a more significant impact on the elastic modulus of UHPC than interface performance,and the latter contributes more to the strength of UHPC.This study will provide a reference for developing UHPC with superior elastic modulus for structural engineering.

Straw return increases crop production by improving soil organic carbon sequestration and soil aggregation in a long-term wheat-cotton cropping system

Straw return is a promising strategy for managing soil organic carbon(SOC)and improving yield stability.However,the optimal straw return strategy for sustainable crop production in the wheat(Triticum aestivum L.)-cotton(Gossypium hirsutum L.)cropping system remains uncertain.The objective of this study was to quantify the long-term(10 years)impact of carbon(C)input on SOC sequestration,soil aggregation and crop yields in a wheat-cotton cropping system in the Yangtze River Valley,China.Five treatments were arranged with a single-factor randomized design as follows:no straw return(Control),return of wheat straw only(Wt),return of cotton straw only(Ct),return of 50%wheat and 50%cotton straw(Wh-Ch)and return of 100%wheat and 100%cotton straw(Wt-Ct).In comparison to the Control,the SOC content increased by 8.4 to 20.2%under straw return.A significant linear positive correlation between SOC sequestration and C input(1.42-7.19 Mg ha^(−1)yr^(−1))(P<0.05)was detected.The percentages of aggregates of sizes>2 and 1-2 mm at the 0-20 cm soil depth were also significantly elevated under straw return,with the greatest increase of the aggregate stability in the Wt-Ct treatment(28.1%).The average wheat yields increased by 12.4-36.0%and cotton yields increased by 29.4-73.7%,and significantly linear positive correlations were also detected between C input and the yields of wheat and cotton.The average sustainable yield index(SYI)reached a maximum value of 0.69 when the C input was 7.08 Mg ha^(−1)yr^(−1),which was close to the maximum value(SYI of 0.69,C input of 7.19 Mg ha^(−1)yr^(-1))in the Wt-Ct treatment.Overall,the return of both wheat and cotton straw was the best strategy for improving SOC sequestration,soil aggregation,yields and their sustainability in the wheat-cotton rotation system.

Straw mulching alters the composition and loss of dissolved organic matter in farmland surface runoff by inhibiting the fragmentation of soil small macroaggregates

Straw mulching is a widespread practice for reducing the soil carbon loss caused by erosion.However,the effects of straw mulching on dissolved organic matter(DOM)runoff loss from black soil are not well studied.How straw mulching affects the composition and loss of runoff DOM by changing soil aggregates remains largely unclear.Here,a straw mulching treatment was compared to a no mulching treatment(as a control)on sloping farmland with black soil erosion in Northeast China.We divided the soil into large macroaggregates(>2 mm),small macroaggregates(0.25-2 mm),and microaggregates(<0.25 mm).After five rain events,the effects of straw mulching on the concentration(characterized by dissolved organic carbon(DoC)and composition(analyzed by fluorescence spectroscopy)of runoff and soil aggregate DOM were studied.The results showed that straw mulching reduced the runoff amount by 54.7%.Therefore,although straw mulching increased the average DOc concentration in runoff,it reduced the total runoff DOM loss by 48.3%.The composition of runoff DOM is similar to that of soil,as both contain humic-like acid and protein-like components.With straw mulching treatment,the protein-like components in small macroaggregates accumulated and the protein-like components in runoff declined with rain events.Fluorescence spectroscopy technology may help in understanding the hydrological paths of rain events by capturing the dynamic changes of runoff and soil DOM characteristics.A variation partitioning analysis(VPA)indicated that the DOM concentration and composition of microaggregates explained 68.2%of the change in runoff DOM from no mulching plots,while the change in runoff DOM from straw mulching plots was dominated by small macroaggregates at a rate of 55.1%.Taken together,our results demonstrated that straw mulching reduces the fragmentation of small macroaggregates and the loss of microaggregates,thus effecting DOM compositions in soil and reducing the DOM loss in runoff.These results provide a theoretical basis for reducing carbon loss in sloping farmland.

Case Studies of the Microphysical and Kinematic Structure of Summer Mesoscale Precipitation Clouds over the Eastern Tibetan Plateau

Three cases of microphysical characteristics and kinematic structures in the negative temperature region of summer mesoscale cloud systems over the eastern Tibetan Plateau(TP)were investigated using X-band dual-polarization radar.The time-height series of radar physical variables and mesoscale horizontal divergence δderived by quasi-vertical profiles(QVPs)indicated that the dendritic growth layer(DGL,-20°C to-10°C)was ubiquitous,with large-value zones of K_(DP)(specific differential phase),Z_(DR)(differential reflectivity),or both,and corresponded to various dynamic fields(ascent or descent).Ascents in the DGL of cloud systems with vigorous vertical development were coincident with large-value zones of Z_(DR),signifying ice crystals with a large axis ratio,but with no obvious large values of K_(DP),which differs from previous findings.It is speculated that ascent in the DGL promoted ice crystals to undergo further growth before sinking.If there was descent in the DGL,a high echo top corresponded to large values of K_(DP),denoting a large number concentration of ice crystals;but with the echo top descending,small values of K_(DP) formed.This is similar to previous results and reveals that a high echo top is conducive to the generation of ice crystals.When ice particles fall to low levels(-10℃ to 0℃),they grow through riming,aggregation,or deposition,and may not be related to the kinematic structure.It is important to note that this study was only based on a limited number of cases and that further research is therefore needed.