Transfer Probability Research Articles

Cooperative antibiotic resistance facilitates horizontal gene transfer

The rise of β-lactam resistance among pathogenic bacteria, due to the horizontal transfer of plasmid-encoded β-lactamases, is a current global health crisis. Importantly, β-lactam hydrolyzation by β-lactamases, not only protects the producing cells but also sensitive neighboring cells cooperatively. Yet, how such cooperative traits affect plasmid transmission and maintenance is currently poorly understood. Here we experimentally show that KPC-2 β-lactamase expression and extracellular activity were higher when encoded on plasmids compared with the chromosome, resulting in the elevated rescue of sensitive non-producers. This facilitated efficient plasmid transfer to the rescued non-producers and expanded the potential plasmid recipient pool and the probability of plasmid transfer to new genotypes. Social conversion of non-producers by conjugation was efficient yet not absolute. Non-cooperative plasmids, not encoding KPC-2, were moderately more competitive than cooperative plasmids when β-lactam antibiotics were absent. However, in the presence of a β-lactam antibiotic, strains with non-cooperative plasmids were efficiently outcompeted. Moreover, plasmid-free non-producers were more competitive than non-producers imposed with the metabolic burden of a plasmid. Our results suggest that cooperative antibiotic resistance especially promotes the fitness of replicons that transfer horizontally such as conjugative plasmids.

A Time-Dependent-Density-Functional-Theory Study of Charge Transfer Processes of Li2+ Colliding with Ar in the MeV Region

We study charge transfer of a multi-electron collision system Li2+ + Ar using the time-dependent density functional theory non-adiabatically coupled to the molecular dynamics. By implementing the particle number projection method, the single- and double-charge transfer cross sections are extracted at MeV energies, which are in good agreement with the experimental data available. The analysis of charge transfer probabilities shows that for energies higher than 1.0 MeV, the single-charge transfer occurs for a broader range of impact parameters, while the double-charge transfer is dominated by close collisions. To gain the population of captured electrons on the projectile, we compute the orbital projection probabilities. It is found that the electrons of the Ar atom will most possibly transfer to the 2p orbitals of the Li2+, and only a small portion of captured electrons distribute on the s orbitals. This work verifies the capability of the present methodology in dealing with charge transfer in dressed ion collisions at MeV energies.

An Ant Colony Optimization-Simulated Annealing Algorithm for Solving a Multiload AGVs Workshop Scheduling Problem with Limited Buffer Capacity

In this paper, we address a multiload AGVs workshop scheduling problem with limited buffer capacity. This has important theoretical research value and significance in the manufacturing field in considering the efficient multiload AGVs widely used today, and in the limited buffer area in production practice. To minimize the maximum completion time, an improved ant colony optimization-simulated annealing algorithm based on a multiattribute dispatching rule is proposed. First, we introduce a multiattribute dispatching rule, which combines two attributes, delivery completion time and input queue through dynamic weights that are determined by the information about the system, using the multiattribute dispatching rule to construct the initial solution. Then, with the ant colony optimization-simulated annealing algorithm as the basic framework, we propose a method for calculating transfer probability based on the multiattribute dispatching rule, which obtains heuristic information through the proposed rule. Further, we propose a path branch mechanism and dynamic equilibrium mechanism, aiming to efficiently construct the ant path and dynamically adjust ant path distribution. We propose a key job strategy and design a 2-opt neighborhood search method based on key jobs. Data experiments demonstrate the multiattribute dispatching rule is superior over other heuristic dispatching rules; the algorithm improvement strategies proposed are effective when used simultaneously or separately. Further, the proposed algorithm in this paper is superior over other heuristic algorithms and adapts to all kinds of instances.

Probability of charge transport through al/GaAs interfaces system using quantum model

The focus of this paper is on the investigation and the understanding of transition probability of charge at the metal/semiconductor interface depending on the calculation of the rate constant. For this system we can suppose two localized quantum vector states system with a conduction electron state vector l 〉 interacting with an acceptor state vector l 〉 of electron in band of metal with the interacting described by the coupling matrix element. Expression of rate constant of charge transfer for metal/semiconductor system derived upon the quantum model and perturbation theory for transition between l 〉 and I state when the coupling matrix element coefficient smaller than . The probability of the charge transfer rate constant for the metal/semiconductor interface in this context, is basically defined as a relatively to potential barrier between a metal and a semiconductor The probability of charge transfer rate constant evaluated with reorganization energy using a matlap program. Theoretical results obtained for our mode show that the probability of charge transfer is more probable with decreasing the reorganization energy.

Characteristics and Optimization Strategies of A* Algorithm and Ant Colony Optimization in Global Path Planning Algorithm

A* algorithm and ant colony optimization (ACO) are more widely used in path planning among global path planning algorithms. The optimization process is analyzed and summarized from the principles and characteristics of the two algorithms, A* algorithm is mainly optimized in terms of point selection and improvement of heuristic function; and ACO is mainly investigated in terms of transfer probability and pheromone positive feedback for improvement and optimization. Taking a single algorithm solving complex optimization problems difficulties into consideration, a splitting strategy can be used. So that local path or intelligent path optimization algorithms are incorporated in global path planning to improve search efficiency and optimization quality.

Geo-Economic Analysis Based on an Improved Ant Colony Optimization

This paper addresses the optimal path selection problem for economic corridors, which is a significant issue in the field of geo-economics. The paper has utilized the spatiotemporal characteristics of geo-economics and identified the development needs in this field to propose an improved ant colony optimization (ACO) strategy. The proposed strategy focuses on enhancing the heuristic function, functional area setting, and pheromone updating strategy. The heuristic factors and transfer probabilities have been improved to couple the path nature, which were based on an analysis of the factors that influence geo-economics. This improvement enhances the applicability of the ACO to path selection problems in macrospace. Additionally, the paper has differentiated the priority of path nodes by setting functional areas, which adds directionality to path selection. The improved ACO has been applied to analyze the optimal path in macroscopic economic space. The experimental validation was conducted in the Indo-Pacific region and economic corridors in China within this region, and corresponding potential geo-economic hubs were analyzed. The experimental results were validated using the Mann−Whitney U test and an evaluation method based on path effectiveness. The feasibility and objectivity of the proposed method were verified. This research provides a valuable exploration of the problem of path selection in macrospace and time and provides decision aid for the construction and adjustment development of a country’s geo-economic relations in a given region. It is a technical reference for establishing sustainable development strategies and national and regional economic planning. Overall, this work contributes significantly to the field of geo-economics and demonstrates the effectiveness of the proposed method through experimental validation.

Visible and mid-infrared spectral features of Dy3+: SrF2 and Dy3+/Y3+: SrF2 crystals

In this work, Dy3+: SrF2 and Dy3+/Y3+: SrF2 crystals have been grown successfully by the Bridgman-Stockbarger method, and their absorption spectra, visible and mid-infrared (MIR) emission spectra, as well as fluorescence decay curves were analyzed. The advantages of co-doping Y3+ ions on the yellow and MIR emissions of Dy3+ ions were investigated. The intensity of yellow emission in the doubly-doped crystal is ∼ 4 times stronger than that of the singly-doped crystal. The absorption cross-section (0.782 × 10−21 cm2) at 452 nm and emission cross-section (1.156 × 10−21cm2) at 573 nm of Dy3+/Y3+: SrF2 crystal is higher than that of Dy3+: SrF2 crystal related values. Also, compared to Dy3+: SrF2 crystal, the emission cross-section (3.55 × 10−21 cm2) at 2880 nm and fluorescence decay time (1.062 ms) of Dy3+/Y3+: SrF2 crystal are found to be higher. When co-doped Y3+ ions, the distance between Dy3+ ions increased leading to the reduction of cross-relaxation and resonant energy transfer probabilities while enhancing the intensities of yellow and MIR emissions. From all the optical results, it can be inferred that Dy3+: SrF2 and Dy3+/Y3+: SrF2 crystals are potential materials to simultaneously realize yellow and MIR lasing action.

Resource Optimization for Multi-Unmanned Aerial Vehicle Formation Communication Based on an Improved Deep Q-Network.

With the widespread application of unmanned aerial vehicle (UAV) formation technology, it is very important to maintain good communication quality with the limited power and spectrum resources that are available. To maximize the transmission rate and increase the successful data transfer probability simultaneously, the convolutional block attention module (CBAM) and value decomposition network (VDN) algorithm were introduced on the basis of a deep Q-network (DQN) for a UAV formation communication system. To make full use of the frequency, this manuscript considers both the UAV-to-base station (U2B) and the UAV-to-UAV (U2U) links, and the U2B links can be reused by the U2U communication links. In the DQN, the U2U links, which are treated as agents, can interact with the system and they intelligently learn how to choose the best power and spectrum. The CBAM affects the training results along both the channel and spatial aspects. Moreover, the VDN algorithm was introduced to solve the problem of partial observation in one UAV using distributed execution by decomposing the team q-function into agent-wise q-functions through the VDN. The experimental results showed that the improvement in data transfer rate and the successful data transfer probability was obvious.

GA-ENs: A novel drug–target interactions prediction method by incorporating prior Knowledge Graph into dual Wasserstein Generative Adversarial Network with gradient penalty

Bipartite graph-based drug–target interactions (DTIs) prediction methods are commonly limited by the sparse structure of the graph, resulting in acquiring suboptimal node feature representations. In addition, these defective node features will also interfere with the representation quality of corresponding edge features. To alleviate the sparsity of bipartite graph and get better node representation, according to the prior Knowledge Graph (KG), we developed a novel prediction model based on Variational Graph Auto-Encoder (VGAE) combined with our proposed dual Wasserstein Generative Adversarial Network with gradient penalty strategy (dual-WGAN-GP) for generating edge information and augmenting their representations. Specifically, GA-ENs first utilized dual-WGAN-GP to fill possible edges by a prior KG containing various molecular associations knowledge when constructing a bipartite graph of known DTIs. Moreover, we utilized the KG transfer probability matrix to redefine the drug–drug and target–target similarity matrix, thus constructing the final graph adjacent matrix. Combining graph adjacent matrix with node features, we learn node representations by VGAE and augment them by utilizing dual-WGAN-GP again, thus obtaining final edge representations. Finally, a fully connected network with three layers was designed to predict potential DTIs. Extensive experiment results show that GA-ENs has excellent performance for DTIs prediction and could be a supplement tool for practical DTIs biological screening.

Improving O&M decision tools for offshore wind farm vessel routing by incorporating weather uncertainty

AbstractThe growth of offshore wind farms depends significantly on how well offshore wind turbines (OWTs) are operated and maintained in the long term. The operation and maintenance (O&M) activities for offshore wind are relatively more challenging due to uncertain environmental conditions than onshore and due to this, vessel routing for offshore on‐site repair is remain complex and unreliable. Here, an improved data‐driven decision tool is proposed to robust the vessel routing for O&M tasks under numerous environmental conditions. A novel data‐driven technique based on operational datasets is presented to incorporate weather uncertainties, such as wind speed, wave period and wave height (significantly influence offshore crew repair works), into the O&M decision‐making process. Results show: (1) The inclusion of weather conditions improves the O&M model uncertainty and accuracy, (2) the implementation of a model allowing weather conditions to evolve has been added to vary the probabilities of successful transfers throughout the day, and (3) the reduction of risk of transfer failure by 15%. These conclusions are further supported by the performance error metrics and uncertainty calculations. Last but not least, by generating a variety of policies for consideration, this tool gave wind turbine operators a systematic and transparent way to evaluate trade‐offs and enable choices pertaining to offshore O&M. The full paper highlights the strengths and weaknesses of the proposed technique for offshore vessel routing as well as how the environmental conditions affect them.

A Study of Fractional-Order Memristive Ant Colony Algorithm: Take Fracmemristor into Swarm Intelligent Algorithm

As the fourth fundamental circuit element, the memristor may execute computations while storing data. Fracmemristor takes advantage of the fractional calculate’s long-term memory, non-locality, weak singularity, and the memristor’s storage–computational integration. Since the physical structure of the fracmemristor is similar to the topology of the ant transfer probability flow in ACO, we propose the fractional-order memristive ant colony algorithm (FMAC), which uses the fracmemristor physical system to record the probabilistic transfer information of the nodes that the ant will crawl through in the future and pass it to the current node of the ant, so that the ant acquires the ability to predict the future transfer. After instigating the optimization capabilities with TSP, we discovered that FMAC is superior to PACO-3opt, the best integer-order ant colony algorithm currently available. FMAC operates substantially more quickly than the fractional-order memristor ant colony algorithm due to the transfer probability prediction module based on the physical fracmemristor system (FACA).

RETRACTED ARTICLE: Research on reliability evolutionary optimization of relays device based on Multi-Markov model

As a critical component of the present day power system, a few studies have been conducted on the optimization and future prediction for quality reliability of relay protection devices during their production stage of intelligent testing. Therefore, in this study, a Markov model of multimodal hierarchical spatial states is proposed (1) to calculate the stationary probability and comprehensive availability of different spatial state transfers (2) to predict the quality reliability of the device during production intelligence testing and (3) to infer and calculated the integrated availability of the relay protection device for its future operation during testing. Statistical results from the theoretical findings of this study are highly relevant when compared to the actual operation of relay protection device systems. The correctness of the model calculation method proposed in this study is verified, which provides a feasible method for reliability assessment of relay protection device intelligence tests. In addition, it was also found that the failure rate of the device internal module CPU has a relatively large impact on the comprehensive availability. It is therefore recommended to focus on CPU module detection and timely replacement during the maintenance cycle of on-site operations and maintenance. Finally, the CPU module failure rate threshold for production intelligence testing was amended, which is a valuable indicator for the evolutionary optimization of quality problems in actual smart manufacturing and testing.

Spatiotemporal heterogeneity and decoupling decomposition of industrial carbon emissions in the Yangtze River Delta urban agglomeration of China.

The objective of this study is to identify the spatiotemporal change law and the leading factors of industrial carbon emission decoupling. Based on the industrial carbon emission level of the Yangtze River Delta urban agglomeration (YRDUA) from 2006 to 2020, the spatiotemporal heterogeneity was explored with the help of the spatial Markov chain, the Tapio decoupling model was used to analyze its decoupling state from the industrial economy, and its driving factors were decomposed using the Kaya identity and logarithmic mean Divisia index (LMDI) model. The results show that (1) in 51.9% of the YRDUA's cities, the industrial carbon emission situation was stable, the emission reduction observation area (medium carbon) occupied a dominant position, and the emission reduction key area (relatively high carbon) gradually decreased. (2) Industrial carbon emissions had spatial overflow and path dependency characteristics, and the probability of carbon emission type transfer maintaining the original state reached 80.0%. From 2006 to 2011, the average probability of the downward migration of high-carbon cities was 5.0%. From 2011 to 2020, the average probability of the upward transfer of low-carbon cities was 9.4%. (3) The negative decoupling rate of carbon emissions in the YRDUA experienced a transition from 3.7% to 44.4% and then back to 7.4%, showing spatial imbalance. Unsatisfactory decoupling cities were concentrated along the Yangtze River and in coastal areas. (4) The promoting efficiency of energy intensity, carbon emission coefficient, and employment structure was gradually strengthened, and the carbon-increasing effect of labor input was gradually weakened. (5) The decoupling mode of heavy difficult cities is dominated by the three-factor balanced type, which is jointly affected by industrial production, labor input, and carbon emission coefficient. The findings in this study can provide inspiration for industrial carbon emission reduction in megalopolises.

Spatiotemporal Dynamic Distribution, Regional Differences and Spatial Convergence Mechanisms of Carbon Emission Intensity: Evidence from the Urban Agglomerations in the Yellow River Basin.

Low-carbon transition is of great importance in promoting the high-quality and sustainable development of urban agglomerations in the Yellow River Basin (YRB). In this study, the spatial Markov chain and Dagum's Gini coefficient are used to describe the distribution dynamics and regional differences in the carbon emission intensity (CEI) of urban agglomerations in the YRB from 2007 to 2017. Additionally, based on the spatial convergence model, this paper analyzed the impact of technological innovation, industrial structure optimization and upgrading, and the government's attention to green development on the CEI's convergence speed for different urban agglomerations. The research results show that: (1) The probability of adjacent type transfer, cross-stage transfer, and cross-space transfer of the CEI of urban agglomerations in the YRB is small, indicating that the overall spatiotemporal distribution type of CEI is relatively stable. (2) The CEI of urban agglomerations in the YRB has decreased significantly, but the spatial differences are still significant, with a trend of continuous increase, and regional differences mainly come from the differences between urban agglomerations. (3) Expanding innovation output, promoting the optimization and upgrading of industrial structure, and enhancing the government's attention to green development has a significant positive effect on the convergence rate of the CEI of urban agglomerations in the YRB. This paper holds that implementing differentiated emission reduction measures and actively expanding regional collaborative mechanisms will play an important role in reducing the spatial differences in carbon emissions in urban agglomerations in the YRB, realizing the goals of peak carbon and carbon neutrality.

Spatial‐temporal response capability probabilistic evaluation method of electric vehicle aggregator based on trip characteristics modelling

AbstractAccurately evaluating the response capability of electric vehicles (EVs) is very important for an EV aggregator (EVA) to formulate reasonable bidding strategies in ancillary service markets. Most of the methods proposed in the existing literature only evaluate EVs’ temporal response capability while ignoring their spatial distribution. In addition, the evaluation results provided by the existing methods are typically deterministic, which fails to characterize the uncertainty of EV trip. The above two issues pose high risk of economic loss for the EVA. To this end, a probabilistic evaluation method of spatial‐temporal response capability for EVA is proposed in this paper. The gravity model is adopted to calculate a spatial transfer probability matrix describing EV owners’ trip characteristics between different areas at each time in a region which is divided into several different areas according to the evaluation requirements. Then, the trip chains of EVs are modelled based on the spatial transfer probability matrix, and the states of charge (SOCs) of EVs are tracked in the process. The spatial‐temporal response capability of EVA is evaluated based on charging–discharging states and states of charge of EVs, and the probabilistic evaluation results of response capability are obtained by multiple Monte Carlo simulations. The effectiveness of the proposed method is verified on a real dataset from San Francisco, CA, USA.

IATLR: Improved ACO and TOPSIS-Based Layering Routing Protocol for Underwater Acoustic Networks

Aiming at the challenges of underwater acoustic networks (UANs) such as low bandwidth, long propagation delay, dynamic network topology, and energy limitation, an improved ant colony optimization (IACO) and technique for order preference by similarity to an ideal solution (TOPSIS)-based layering routing (IATLR) protocol for UANs is proposed. In the IATLR protocol, the transfer probability of the ant colony optimization (ACO) is optimized by comprehensively considering multiple factors such as energy consumption, propagation distance, and forwarding angle. Moreover, the ACO is improved and the optimized ACO is combined with the TOPSIS method by using the pheromone concentration of ACO as the decision basis of TOPSIS. Furthermore, the multifactor decision ranking of the TOPSIS method is optimized by the transfer probability of the ACO. Consequently, the best next-hop node is determined. In addition, the energy consumption is balanced through the whole network by the node silence mechanism in the IATLR protocol. Simulation results show that the IATLR protocol has significant advantages compared with the depth-based routing for underwater sensor networks (DBR), layer-based energy-efficient routing (LEER), and depth and distance based layering routing protocol for underwater sensor networks (DDLR) routing protocols in terms of packet delivery rate (PDR), energy consumption, and end-to-end delay (EED). The PDR increases by 5%–30%, the EED decreases by about 1–7 s, and the average energy consumption (AEC) reduces by 0.5–6 J.

Debris Collision Risk Analysis Following Simulated Cislunar Spacecraft Explosions

This research simulates spacecraft explosions in cislunar space and analyzes the resulting risk to other notional spacecraft. Three case studies are considered, which include simulations of spacecraft explosions during Earth–moon Hohmann transfers, along the manifold of the Earth–moon Lagrange point, and at the stable and Earth–moon Lagrange points. Debris from the explosions is propagated using a four-body dynamical model that incorporates the gravitational forces of the Earth, moon, and sun. Finally, the risk to nearby cislunar spacecraft is quantified using two different models for the vulnerability of spacecraft to debris, which include a logistic vulnerability model that incorporates only debris particle mass and a ballistic limit vulnerability model that incorporates both particle mass and velocity. The results from each model are compared to evaluate their application to cislunar debris scenarios. The results of this study showed potential debris hazards to spacecraft near Earth from a mishap during an Earth–moon transfer and hazard probabilities to nearby cislunar spacecraft on the order of from Lagrange point mishaps. Overall, research into cislunar debris propagation enhances operational planning outside the traditional near-Earth paradigm of spacecraft mission operations and increases understanding of the debris-related consequences of mishaps within this orbital regime.

Fidelity of counting the transferred electrons in a GaAs-based monolithic single-electron pump and transistor system with a charge-lock feedback circuit

We developed an electron-counting technique for a self-referenced single-electron quantized current source of a single-electron-pump system and investigated the fidelity of our whole measurement process, including single-electron pumping and electron counting by a single-electron transistor (SET) with a charge-lock feedback loop. The device was fabricated monolithically using a two-dimensional electron system of a GaAs/AlGaAs hetero-junction. In addition to the probability of single-electron transfer, we also measured the current noise spectrum of the SET, from which its charge noise power Sq was derived. The results show that the estimated charge noise of 2.2 ×10−4 e/Hz for a semiconductor-based SET is comparable to that of metallic SETs.

Preparation, structure and luminescent properties of P2O5–Gd2O3–Ga2O3–NaF–ZnO glasses co-doped with Tb3+ and Sm3+

White light-emitting diodes have been intensively explored as a technique of green energy-conversion in recent decades. In this work, a unique Tb3+/Sm3+ co-doped P2O5–Gd2O3–Ga2O3–NaF–ZnO glass consisting of Q0, Q1 and Q2 units was successfully synthesized. The DSC curves demonstrated that the glass stability gradually deteriorated with the increase of Sm3+ contents. The emission spectra exhibited the energy transfer from Dy3+ to Tb3+ ions, and the energy transfer efficiency and probability grew monotonously with the increase of Sm3+ contents. With the help of temperature-dependent emission spectra, the glasses were validated to be thermally stable. The fluorescence curves and Inokuti-Hirayama model demonstrated that the dominant mechanism in the energy transfer process was electric dipole-quadrupole interaction. In addition. the white-light emission with suitable chromaticity coordinates and CCTs could be obtained by adjusting the contents of the sensitizer and activator for PGGNZ glasses. All investigations revealed the potential application of Tb3+/Sm3+ co-doped glasses in optical device applications.

A tipping point of spreading viruses: Estimating the risk of household contact transmission of COVID-19

COVID-19 infection has been reported to be caused by droplet and contact infection. This paper proposes a model that visualizes the risk of contact infection to family members when viruses spread to various items at home. Behavior data after returning home are extracted from a questionnaire-based survey of home behavior to design the agent-based model. The data tables of contact behavior are created, including the room-to-room transfer probability table, the conditional probability table, and the contact probability table. The material transfer efficiency table is also created by measuring the virus transmission rate after contact with droplets in a virus experiment laboratory. In the experiment, the synthetic agent created from the acquired data probabilistically performs movement and contact behavior after returning home and reproduces the state in which the virus attached to the hand or belongings, when going out, propagates to objects at home. Next, we examine the risk of a second family member returning home. As a result, virus-attached contacts within around 30 minutes after returning home are widely confirmed around the entrance and kitchen, suggesting the effectiveness of early hand-washing behavior. And the experiment shows that even if the first person returning home disinfects their hands inside the entrance, the virus remains in a part of the entrance, and the virus is spread inside the room by the second person returning home.