Dynamic Partitioning Research Articles

Cluster Partition Method of Large-Scale Grid-Connected Distributed Generations considering Expanded Dynamic Time Scenarios

The reasonable clustering of large-scale distributed generations (DGs) can optimize the scheduling control and operation monitoring of the power grid, which ensures the orderly and efficient integration of DGs into the power system. In this article, the influence of internal and external flexible resources is considered in the DG cluster partition, and the comprehensive performance indexes with expanded dynamic time scenario are proposed to realize the dynamic cluster partition. Firstly, the active and reactive power balance indexes considering the flexible resources are derived, which forms the comprehensive index together with the structure index. Then, the comprehensive index is expanded to the dynamic forms, which reflects the real-time cluster performance, and the cluster partition method is given with the genetic algorithm. Finally, the effectiveness verification of the proposed cluster partition method is carried out with the 14- and 33-bus systems.

Subcellular regulation of glucose metabolism through multienzyme glucosome assemblies by EGF–ERK1/2 signaling pathways

A multienzyme metabolic assembly for human glucose metabolism, namely the glucosome, has been previously demonstrated to partition glucose flux between glycolysis and building block biosynthesis in an assembly size-dependent manner. Among three different sizes of glucosome assemblies, we have shown that large-sized glucosomes are functionally associated with the promotion of serine biosynthesis in the presence of epidermal growth factor (EGF). However, due to multifunctional roles of EGF in signaling pathways, it is unclear which EGF-mediated signaling pathways promote these large glucosome assemblies in cancer cells. In this study, we used Luminex multiplexing assays and high-content single-cell imaging to demonstrate that EGF triggers temporal activation of extracellular signal-regulated kinases 1/2 (ERK1/2) in Hs578T cells. Subsequently, we found that treatments with a pharmacological inhibitor of ERK1/2, SCH772984, or short-hairpin RNAs targeting ERK1/2 promote the dissociation of large-sized assemblies to medium-sized assemblies in Hs578T cells. In addition, our Western blot analyses revealed that EGF treatment does not increase the expression levels of enzymes that are involved in both glucose metabolism and serine biosynthesis. The observed spatial transition of glucosome assemblies between large and medium sizes appears to be mediated by the degree of dynamic partitioning of glucosome enzymes without changing their expression levels. Collectively, our study demonstrates that EGF–ERK1/2 signaling pathways play an important role in the upregulation of large-sized glucosomes in cancer cells, thus functionally governing the promotion of glycolysis-derived serine biosynthesis.

An Improved Physical Model of Power Diode in the Rectifier Circuit

Considering the weakness of the conventional physical model of power diodes in the rectifier design, an improved lumped-charge model is presented in this article to achieve both high accuracy and high efficiency in the simulation of power electronic equipment. To improve the convergence of the physical model simulation in the rectifier circuit, the transmission-line theory is implemented in the model. Furthermore, a dynamic partition method is implemented in the model to achieve high accuracy of the transient characteristics of the diode during the level transition of the rectifier, with reducing the number of numerical solutions through reallocation of computing resources. Compared with the conventional model, the simulation error is decreased. This successfully adopts the physical model to realize both equipment-level simulation and high accuracy of device simulation in the design of the rectifier and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$RC$ </tex-math></inline-formula> snubber circuit. The experimental results show that the error of the proposed model is less than 10% and 5% the minimum, which is a maximum 30% decreasing compared with that of the conventional model. The half-cycle ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$500~{\mu \text {s}}$ </tex-math></inline-formula> ) simulation of the rectifier circuit with 10 and 20 power diodes cost 18 and 33 s.

CASHT: Contention Analysis in Shared Hierarchies with Thefts

Cache management policies should consider workloads’ contention behavior when managing a shared cache. Prior art makes estimates about shared cache behavior by adding extra logic or time to isolate per workload cache statistics. These approaches provide per-workload analysis but do not provide a holistic understanding of the utilization and effectiveness of caches under the ever-growing contention that comes standard with scaling cores. We present Contention Analysis in Shared Hierarchies using Thefts, or CASHT, 1 a framework for capturing cache contention information both offline and online. CASHT takes advantage of cache statistics made richer by observing a consequence of cache contention: inter-core evictions, or what we call THEFTS. We use thefts to complement more familiar cache statistics to train a learning model based on Gradient-boosting Trees (GBT) to predict the best ways to partition the last-level cache. GBT achieves 90+% accuracy with trained models as small as 100 B and at least 95% accuracy at 1 kB model size when predicting the best way to partition two workloads. CASHT employs a novel run-time framework for collecting thefts-based metrics despite partition intervention, and enables per-access sampling rather than set sampling that could add overhead but may not capture true workload behavior. Coupling CASHT and GBT for use as a dynamic policy results in a very lightweight and dynamic partitioning scheme that performs within a margin of error of Utility-based Cache Partitioning at a 1/8 the overhead.

Dynamic trait-niche relationships shape niche partitioning across habitat transformation gradients

Multidimensional approaches examining complex trait-niche relationships are crucial to understand community assembly. This is particularly important across habitat transformation gradients because specialists are progressively substituted by generalists and, despite increasing functional homogenization, in both specialist and generalist communities niche partitioning is apparent. Here, in line with the continuum hypothesis, we expected that divergent trait-niche relationships would arise in passerine assemblages across the natural-to-urban transformation gradient. More specifically, we expected that traits linking form to function would be more important in less transformed habitats, while population density and traits linked to dispersal and dominance would predominate in more transformed habitats. Accordingly, we found that beak length and its interaction with tarsus length correlated significantly with isotopic niches in natural and rural habitats, where specialists predominate. Conversely, body size and aggressiveness only showed significant relationships with isotopic niches with increasing habitat transformation, where generalists prevail. Interestingly, we recorded a mix of these processes in rural habitats, which acted as a frontier between these two domains. Our study is thus important in showing that a complex combination of morphological and behavioral traits determine niche characteristics, and that these relationships are dynamic across habitat transformation gradients.

Dynamic Zoning and Collaborative Control of Autonomous Region of an Active Distribution Network Based on Synchronous Measurement Information

With the continuous access of distributed power to the active distribution network, the voltage overrun at key load nodes is easy to occur, which will affect the safe operation of the active distribution network. Therefore, the dynamic partition and collaborative control method of autonomous region of active distribution network based on synchronous measurement information are studied, so as to rationally dynamically partition the active distribution network, effectively coordinate the voltage control of each partition, and ensure the safe operation of distribution network. Synchronous phasor measuring device is used to collect node voltage related information of distribution network. Based on the collected information and the eigenroots of the electrical distance matrix, the number of larger eigenroots, namely the optimal dynamic partition number, is determined. Ward distance clustering algorithm is used to complete the dynamic partition of distribution network. After the completion of dynamic partition, for the nodes with the most serious voltage overlimit in each partition, the collaborative control of the voltage in each partition is completed according to the eventdriven mode. The experimental results show that the proposed method can be used to dynamically partition the autonomous regions of active distribution network and ensure that the reactive power reserve margin of each region is higher than the minimum standard. This method can effectively control the voltage of each node, and the control time is short and the active power loss is less.

Optimal Data Placement and Replication Approach for SIoT with Edge

Social networks (SNs) are sources with extreme number of users around the world who are all sharing data like images, audio, and video to their friends using IoT devices. This concept is the so-called Social Internet of Things (SIot). The evolving nature of edge-cloud computing has enabled storage of a large volume of data from various sources, and this task demands an efficient storage procedure. For this kind of large volume of data storage, the usage of data replication using edge with geo-distributed cloud service area is suited to fulfill the user’s expectations with low latency. The major issue is the way to store the data and replicate these large data items optimally and allocate the request from the data center efficiently. For efficient storage of these data, we use edge server, which is part of the cloud server, in this study. Thus, the data are distributed and stored with quick access, which will reduce the latency with response. The proposed data placement approach learns with machine learning (ML) algorithm called radial basis kernel function assisted with support vector machine (RBF-SVM) to classify the data center for storing the user and friend’s data from the SIoT devices. These learning algorithms will be used to predict the workload of the data stored in the data center as either edge or cloud depending on the existing time slots. The data placement with dynamic nature is also optimized using the proposed dynamic graph partitioning (GP) method to meet the individual user’s demand of low latency with minimum costs. This way will keep the SIoT data placement efficient and effective over time. Accordingly, this proposed data placement and replication approach introduces three kinds of innovations compared with the existing data placement approach. (i) Rather than storing the user data in a single cloud, this study uses the edge server closest to the SIoT devices for faster access with reduced response time. (ii) The classification algorithm called RBF-SVM is used to find storage for user for reducing data replication. (iii) Dynamic GP is introduced for data placement with reduced latency and minimum cost to fulfil the dynamic nature of the SN. The simulation result of this approach obtains reduced latency of 130 ms and minimum cost compared with those of the existing data placement approaches. Therefore, our proposed data placement with ML-based learning on edge provides promising results in terms of efficiency, effectiveness, and performance with reduced latency and minimum cost.

The Thermodynamic Formalism and the Central Limit Theorem for Stochastic Perturbations of Circle Maps with a Break

Let $T\in C^{2+\varepsilon}(S^{1}\setminus\{x_{b}\})$, $\varepsilon&gt;0$, be an orientation preserving circle homeomorphism with rotation number $\rho_{T}=[k_{1},k_{2},\ldots,k_{m},1,1,\ldots]$, $m\geq 1$, and a single break point $x_{b}$. Stochastic perturbations $\overline{z}_{n+1}=T(\overline{z}_{n})+\sigma\xi_{n+1}$, $\overline{z}_{0}:=z\in S^{1}$ of critical circle maps have been studied some time ago by Diaz-Espinoza and de la Llave, who showed for the resulting sum of random variables a central limit theorem and its rate of convergence. Their approach used the renormalization group technique. We will use here Sinai’s et al. thermodynamic formalism approach, generalised to circle maps with a break point by Dzhalilov et al., to extend the above results to circle homemorphisms with a break point. This and the sequence of dynamical partitions allows us, following earlier work of Vul at al., to establish a symbolic dynamics for any point ${z\in S^{1}}$ and to define a transfer operator whose leading eigenvalue can be used to bound the Lyapunov function. To prove the central limit theorem and its convergence rate we decompose the stochastic sequence via a Taylor expansion in the variables $\xi_{i}$ into the linear term $L_{n}(z_{0})=\xi_{n}+\sum\limits_{k=1}^{n-1}\xi_{k}\prod\limits_{j=k}^{n-1}T^{% \prime}(z_{j})$, ${z_{0}\in S^{1}}$ and a higher order term, which is possible in a neighbourhood $A_{k}^{n}$ of the points $z_{k}$, ${k\leq n-1}$, not containing the break points of $T^{n}$. For this we construct for a certain sequence $\{n_{m}\}$ a series of neighbourhoods $A_{k}^{n_{m}}$ of the points $z_{k}$ which do not contain any break point of the map $T^{q_{n_{m}}}$, $q_{n_{m}}$ the first return times of $T$. The proof of our results follows from the proof of the central limit theorem for the linearized process.

Steganalysis of Compressed Speech Based on Association Rule Mining

Currently, steganography based on compressed speech streams is gathering more and more attention. Meanwhile, it poses a huge threat to cyber security. As a counter technique, steganalysis can detect whether an illegal secret message is embedded in a compressed speech. To further improve the detection performance of current methods, a novel steganalysis method based on codeword association rule mining (CARM) is proposed in this paper. Firstly, we analyzed the spatiotemporal relationships between codewords in compressed speech. Secondly, the steganography-sensitivity codeword association rule base in training set was built based on the confidence change of codeword association rules before and after steganography. Thirdly, the steganography characteristic index and the corresponding dynamic partition threshold in validation set were computed to determine whether the compressed speech segment contains covert communication or not. Finally, comprehensive experiments were conducted to evaluate the performance of the proposed CARM steganalysis method under various conditions, including different association rule patterns, whether to use dynamic partition threshold, different embedding rates, different speech lengths, etc. The experimental results verify that CARM can achieve better performance than the comparison methods. In addition, the detection accuracy of CARM method can be improved significantly by using dynamic partition threshold at low embedding rates.

The dynamic partitioning of airborne phthalates in indoor environment: effects of ventilation

Low energy consumption buildings with strong air tightness such as passive buildings are the development trend in the world. However, ventilation directly affects the emission and dynamic transport of indoor phthalates. A transient partition model considering the dynamic behavior of size-resolved particle was utilized to investigate the influence of ventilation on the airborne Di-2-ethylhexyl phthalate (DEHP). The air exchange rate (a) was set to 0.15 h-1, 0.3 h-1, 0.6 h-1, 2h-1 for the different conditions. The predicted gas-phase concentration of DEHP in the initial 70 days is unaffected for different a and constant hms, whereas it raises until the a increases to 2 h-1. The equilibrium gas-phase concentration decreases from 0.257 to 0.203 μg/m3. Meanwhile, the higher a also reduced the particle-phase concentration of DEHP. Furthermore, the changes of airborne DEHP were analyzed by considering the impact of a on hms caused by ventilation. The results indicates that more ventilation leads to higher gas-phase concentration for the whole stage. The gas-phase concentration at equilibrium increases from 0.237 to 0.440 μg/m3. The total airborne (gas-phase + particle-phase) concentration decreases with the higher ventitation rate, which indicates that the ventitation has a positive effect on indoor airborne DEHP.

Realization of quenching & dynamic partitioning on large-size parts

ABSTRACT Small components can obtain microstructure of martensite and stable retained austenite (RA) by quenching and traditional partitioning (Q&P) process, thereby demonstrating excellent performances. However, the Q&P is difficult to be realized in large-size parts with complicated multiple microstructures, especially the big property differences from surface to working depth. A novel dynamic quenching–partitioning process for large products was developed by water spraying and critical bainite transformation kinetics was taken into consideration in this process. Typical as-treated microstructure is composed of triplex phases mainly including martensite, bainite and RA. Good combination of strength and toughness have been gained because of multiphase structure and film RA between bainite plate by it. Corresponding ultimate tensile strength and impact energy are 1363 MPa and 81 J at 10 mm depth from the surface as well as 1182 MPa and 65 J at 50 mm depth, respectively, keeping high strength level of over 1100 MPa and demonstrating relatively low gradients. Simulation results also showed that spraying parameters can adjust temperature variation and phase transformation near the surface, realizing the novel process in large-size parts. And it is suitable for multiphase steels, providing a new idea for large-size parts with energy and cost savings.

Dissipativity analysis for Takagi–Sugeno fuzzy system with time-varying delays and stochastic packet dropouts

The dissipative stability analysis of Takagi–Sugeno fuzzy system (TSFS) is the focus of this paper via taking the effects of both delays and packet dropouts. The novel augmented Lyapunov–Krasovskii functional (LKF) is proposed via utilizing the delay-dependent matrix, which provides the information of the delay derivative bounds. By applying the dynamic delay partition method, the delay interval is divided into several variable subintervals, which takes full advantage of time-varying delay information. In addition, the randomly occurring asynchronous or synchronous controllers are put forward to enhance the design flexibility and control performance. On the basis of the new augmented LKF and improved boundary techniques, the sufficient asymptotic stability condition is derived in the form of linear matrix inequalities (LMIs). Subsequently, numerical examples are addressed to certify the feasibility and advantage of the put forward methodology.

Analytical model of workpiece temperature in axial ultrasonic vibration-assisted milling in situ TiB2/7050Al MMCs

In recent years, as a new method developed for machining difficult-to-cut materials, ultrasonic vibration-assisted machining technology has been attracting more and more attentions due to its superior properties in reducing cutting temperature. However, analytical models revealing the mechanism and predicting the cutting temperature for ultrasonic vibration-assisted machining are still needed to be developed. In this paper, an analytical model was established to predict the workpiece temperature for ultrasonic vibration-assisted milling of in situ TiB2/Al MMCs. The heat intensity would be directly determined by the cutting force which was significantly influenced by the ultrasonic vibration motion. Meanwhile, the moving heat source theory was applied for calculating dynamic heat flux and partition ratio. Besides, material properties, tool geometry, cutting parameters, and vibration parameters were taken into account for workpiece temperature modeling. Finally, the developed analytical temperature model was validated by milling experiments with and without ultrasonic vibration on in situ TiB2/7050Al metal matrix composites. The relative errors between model prediction results and experiments were smaller than 17%, indicating that the proposed model could provide workpiece temperature prediction reliably and accurately. Furthermore, the established analytical model could be used not only in ultrasonic vibration-assisted milling but also in conventional milling for the metal matrix composites.

MapReduce-Based Dynamic Partition Join with Shannon Entropy for Data Skewness

Join operations of data sets play a crucial role in obtaining the relations of massive data in real life. Joining two data sets with MapReduce requires a proper design of the Map and Reduce stages for different scenarios. The factors affecting MapReduce join efficiency include the density of the data sets and data transmission over clusters like Hadoop. This study aims to improve the efficiency of MapReduce join algorithms on Hadoop by leveraging Shannon entropy to measure the information changes of data sets being joined in different MapReduce stages. To reduce the uncertainty of data sets in joins through the network, a novel MapReduce join algorithm with dynamic partition strategies called dynamic partition join (DPJ) is proposed. Leveraging the changes of entropy in the partitions of data sets during the Map and Reduce stages revises the logical partitions by changing the original input of the reduce tasks in the MapReduce jobs. Experimental results indicate that the entropy-based measures can measure entropy changes of join operations. Moreover, the DPJ variant methods achieved lower entropy compared with the existing joins, thereby increasing the feasibility of MapReduce join operations for different scenarios on Hadoop.

The integration of urban streetscapes provides the possibility to fully quantify the ecological landscape of urban green spaces: A case study of Xi’an city

Urban green space is the critical composition of urban ecosystem, which provides numerous ecosystem services for urban residents, and has great value. The optimization of urban green landscape aesthetics can improve the health level of the city and enhance the enjoyment of the people. In this research, we calculated two kinds of ecological indices based on deep learning semantic recognition and multispectral remote sensing, and proposed a set of integrated multi-dimensional urban green ecological indicators, which can be used to evaluate the value of urban green ecological landscape aesthetics. These two kinds of ecological indices represent the landscape characteristics of urban green space from the perspective of overlooking and the perspective of looking around respectively. And then the regionalization method based on dynamic constraint aggregation cluster and partition (RECDAP) is used to identify the ecological homogeneous area of urban block. The results indicated that first, there are spatial differences in pedestrian perception of urban vegetation, and high-perception areas are mainly distributed in schools, parks and internal roads in large communities. Second, the green cover based on overlooking view is also mainly distributed in schools, parks, large communities and other places. Finally, the integration of indicators proves that human perception of urban green space landscape aesthetics cannot be ignored. The homogeneous areas provide a new reference for urban managers and designers to create and maintain urban green space. The addition of streetscape provides a possibility for a more objective and comprehensive evaluation of the aesthetic value of urban green space landscape, so that people can better understand the dynamic role of green space in the urbanization and human health. Public managers and urban green designers can use the ecological indices system to optimize and maintain urban vegetation by taking ecologically homogeneous areas as units.

Electron Spin Echo Envelope Modulation Spectroscopy Reveals How Adenosylcobalamin-Dependent Lysine 5,6-Aminomutase Positions the Radical Pair Intermediates and Modulates Their Stabilities for Efficient Catalysis

Electron spin echo envelope modulation (ESEEM) spectroscopy reveals several interactions that serve to weaken the Co–C5′ bond, through stabilization of the cleaved state, thereby facilitating the 5′-deoxyadenosyl (5′-dAdo•) radical formation in unlabeled and 15N-labeled lysine 5,6-aminomutase. In the first place, we show that the CoII–His133β interaction enhances the spin delocalization from CoII to the α-axial ligand, reducing the 5′-dAdo•–CoII recombination probability in situ and allowing nascent 5′-dAdo• to migrate toward the substrate. Next, using [5′-2H]-deoxyadenosylcobalamin, we show that the C5′ methyl group of 5′-dAdoH is at closest contact with the substrate radical. In the case of 5′-dAdo•, this would allow the 5′-methylene radical to be rapidly quenched by H-transfer from the substrate. Finally, we show that the spin density is transferred noncovalently from the substrate radical to the adenine N7 of 5′-dAdoH. In the one-radical substrate–5′-dAdo•–product H-exchange triad, which is central in the mechanism of action of B12 enzymes, such transfer would promote the forward H-transfer reaction by dynamically lowering the free energy of the substrate radical, thereby facilitating its formation and quenching of 5′-dAdo•. In the reverse H-transfer reaction following the 1,2-rearrangement, the reversibility of the noncovalent spin transfer allows the product radical to restore full radical character to reform 5′-dAdo• and a diamagnetic product. The role of dynamical and reversible spin partitioning as a mechanism for modulating the radical stability is likely common in B12 enzymes. This study leads to a better comprehension about how an enzyme controls the reaction trajectory of 5′-dAdo• exquisitely with specificity. The ESEEM results support the positioning of the interacting partners in the catalytic form of lysine 5,6-aminomutase obtained by modeling.

Towards a digital twin for characterising natural source zone depletion: A feasibility study based on the Bemidji site

Natural source zone depletion (NSZD) of light non-aqueous phase liquids (LNAPLs) may be a valid long-term management option at petroleum impacted sites. However, its future long-term reliability needs to be established. NSZD includes partitioning, biotic and abiotic degradation of LNAPL components plus multiphase fluid dynamics in the subsurface. Over time, LNAPL components are depleted and those partitioning to various phases change, as do those available for biodegradation. To accommodate these processes and predict trends and NSZD over decades to centuries, for the first time, we incorporated a multi-phase multi-component multi-microbe non-isothermal approach to representatively simulate NSZD at field scale. To validate the approach we successfully mimic data from the LNAPL release at the Bemidji site. We simulate the entire depth of saturated and unsaturated zones over the 27 years of post-release measurements. The study progresses the idea of creating a generic digital twin of NSZD processes and future trends. Outcomes show the feasibility and affordability of such detailed computational approaches to improve decision-making for site management and restoration strategies. The study provided a basis to progress a computational digital twin for complex subsurface systems.

Cold-induced Arabidopsis FRIGIDA nuclear condensates for FLC repression

Plants use seasonal temperature cues to time the transition to reproduction. In Arabidopsis thaliana, winter cold epigenetically silences the floral repressor locus FLOWERING LOCUS C (FLC) through POLYCOMB REPRESSIVE COMPLEX 2 (PRC2)1. This vernalization process aligns flowering with spring. A prerequisite for silencing is transcriptional downregulation of FLC, but how this occurs in the fluctuating temperature regimes of autumn is unknown2–4. Transcriptional repression correlates with decreased local levels of histone H3 trimethylation at K36 (H3K36me3) and H3 trimethylation at K4 (H3K4me3)5,6, which are deposited during FRIGIDA (FRI)-dependent activation of FLC7–10. Here we show that cold rapidly promotes the formation of FRI nuclear condensates that do not colocalize with an active FLC locus. This correlates with reduced FRI occupancy at the FLC promoter and FLC repression. Warm temperature spikes reverse this process, buffering FLC shutdown to prevent premature flowering. The accumulation of condensates in the cold is affected by specific co-transcriptional regulators and cold induction of a specific isoform of the antisense RNA COOLAIR5,11. Our work describes the dynamic partitioning of a transcriptional activator conferring plasticity in response to natural temperature fluctuations, thus enabling plants to effectively monitor seasonal progression.

Sign Detection and Signed Integer Comparison for the 3-Moduli Set {2^n±1,2^(n+k)}

Comparison, division and sign detection are considered complicated operations in residue number system (RNS). A straightforward solution is to convert RNS numbers into binary formats and then perform complicated operations using conventional binary operators. If efficient circuits are provided for comparison, division and sign detection, the application of RNS can be extended to the cases including these operations.For RNS comparison in the 3-moduli set , we have only found one hardware realization. In this paper, an efficient RNS comparator is proposed for the moduli set which employs sign detection method and operates more efficient than its counterparts. The proposed sign detector and comparator utilize dynamic range partitioning (DRP), which has been recently presented for unsigned RNS comparison. Delay and cost of the proposed comparator are lower than the previous works and makes it appropriate for RNS applications with limited delay and cost.

Study on Microstructures and Properties of Low-Carbon-Steel Heavy Plate Treated by Quenching and Dynamic Partitioning

Study on Microstructures and Properties of Low-Carbon-Steel Heavy Plate Treated by Quenching and Dynamic Partitioning