Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlation of Electromagnetic Interference in Inverter and Radio Disturbance on Assessment of Component and Battery Electric Vehicle

Electromagnetic interference generated by the power modules of the inverter in battery electric vehicles causes degradation of the radio broadcasting performance in vehicle antennas. The discrepancies in the input impedance from the inverter between the assessment of the component and vehicle could affect the common mode current. In this study, the correlation between the conducted currents in both the components and the battery electric vehicle was evaluated. In addition, the relationships between the electromagnetic interference in the inverter, the drive shafts, and the interference voltage at the radio antenna cable are also examined. The correlations were investigated experimentally and computationally using the common mode ferrite core and Y capacitance for frequencies ranging from 150 kHz to 30 MHz. The result showed that the common mode current in the vehicle is significant high at 1.2 MHz with only Y capacitance installed in the vehicle (no ferrite core), which was attributable to a lower input impedance from the inverter in the vehicle. In addition, our study demonstrated the strong correlations between the common mode current, the electric field at the drive shaft, and the voltage at the radio antenna. The investigation results provide suggestions for appropriate suppression for the electromagnetic interference at the early design stage of the component, taking into account the gap of the impedance characteristic in the vehicle.
Multi-Intersection Management for Connected Autonomous Vehicles by Reinforcement Learning

The rapid development of connected autonomous vehicles (CAVs) makes it foreseeable that CAVs will dominate future road traffic. To manage CAV traffic, researchers developed a revolutionary paradigm, which uses intelligent intersection managers (IMs) for a finer-grained control of CAVs' cruising at intersections than traditional traffic lights. However, existing IM-based methods mostly focus on optimizing the single-intersection CAV traffic efficiency, without solving the fundamental problem of maximizing the global efficiency of a multi-intersection road network. Therefore, we address such problem by proposing a system architecture that decomposes each IM into an oracle and a valve, where the oracle ensures safe and efficient crossing at individual intersections, and the valve selects some of the approaching CAVs for the oracle to control and postpones the crossing of the unselected ones. We further focus on distributed decision making for the valves, and propose a multi-agent reinforcement learning framework, spatial-aware multi-agent actor-credit (SMAC). Specifically, SMAC integrates a novel credit assignment method that captures agents' spatially decaying influences to stimulate agent cooperation, and a novel graph convolutional mixing network to capture the graph-structured inter-agent relationships in a road network. We conduct extensive experiments on three traffic flow datasets, and show that SMAC outperforms state-of-the-art baselines.
The multi‐instrumented studies of equatorial thermosphere aeronomy scintillation system: Climatology of zonal drifts

A spaced-antenna scintillation system was installed at Ancon, Peru, in May 1994 to measure scintillation of 250-MHz signals from a geostationary satellite by three antennas spaced in the magnetic east-west direction. These measurements were used to establish the climatology of the zonal drift of the irregularities which cause equatorial scintillations. The major objective of this study is to compare this drift climatology to the climatology of zonal neutral wind which is the driver of the equatorial electrodynamics. A comparison of these two climatologies in conjunction with scintillation statistics may provide some clues regarding factors which help or hinder the formation of equatorial spread-F (ESF). With these objectives in mind, the first year's drift and scintillation statistics have been presented as a function of local time, season and magnetic activity and compared with the statistics of ion drift published earlier from incoherent scatter radar observations. The scintillation drift is in good agreement with the Jicamarca radar observations except for the fact that the local time dependence of our drift observations exhibit a broader maximum. The broad maximum may be attributed to lower ion drag experienced in the presence of ESF due to sustained uplifting of the ionosphere. During magnetically active periods, the scintillation drift often exhibits east to west reversals presumably because of the disturbance dynamo effects. The westward drifts during such reversals may be as large as 100 m/s. We have also modeled the zonal drifts as a seasonal basis by using Hedin's neutral wind model and Anderson's fully analytical ionospheric model. The modeled zonal drifts present good quantitative agreement with the drifts obtained with the scintillation technique.
Study of Spacer Layers’ Influence on Current-Voltage Characteristic of Resonant-Tunneling Diode

The influence of spacer layers’ technological errors on resonant-tunneling diodes’ current-voltage characteristic’s peak current’s distribution and an influence of spacer layers’ thickness on resonant-tunneling diodes’ current-voltage characteristics’ direct and reverse branches’ current were studied. The research was conducted using the RTSVAC software package developed by the authors – spacer layers’ thickness’ technological errors’ contribution to the distribution of resonant-tunneling diodes’ peak current has been assessed using a computer statistical experiment. The dispersion of resonant-tunneling diodes’ peak current’s distribution under spacer layers’ thickness’ technological errors’ impact is 18% of the total dispersion under the combined impact of technological errors of all design parameters of resonant-tunneling diodes. It is shown that emitter spacers’ thickness’ variation affects the peak current of resonant-tunneling diodes’ current-voltage characteristics’ direct branch, and varying of collector spacers’ thickness – reverse branch of resonant tunneling-diodes’ current-voltage characteristics.
Acoustic Coupling and Remote Excitation in an Array of Multi-Mode Piezoelectric Micromachined Ultrasonic Transducers

SummaryThis paper investigates acoustic cross-coupling and remote excitation in an array of PMUTs (piezoelectric micromachined ultrasound transducers). Though undesired cross-talk can impact on PMUT array performance, the same can be also employed for remote excitation. The device array under study comprises of 7 PMUTs with constant pitch which is designed and characterized at the fundamental and higher order modes. The insights are employed to demonstrate a remote frequency filter and dual-channel excitation employing acoustic coupling.
Model of dredging impact on Dungeness crab in Grays Harbor, WA

Abstract : The effects of dredging on marine organisms have been an issue for several decades. Studies have shown effects on the composition of infaunal communities, including disruption and subsequent recolonization. Few attempts have been made to develop predictive models of dredging impacts on invertebrates. A few studies have focused specifically on Dungeness crab, primarily in Grays Harbor. The most recent of these studies has been aimed at quantifying crab entrainment and dredging morality rates. The intent of this study was threefold: (1) to predict the numbers of crabs in various age classes that would be entertained and killed during the proposed widening and deepening of the Grays Harbor navigation channel; (2) to use those predictions to forecast losses to the commercial fishery and; (3) to modify both the dredge schedule and types of gear used in various areas (reaches) of the estuary in order to reduce predicted impact to crab.
Cover-runoff equations to improve simulation of runoff in pasture growth models

An Australian native pasture growth–water balance model (GRASP) was modified to include the USDA curve number runoff method from PERFECT, with the aim of providing a more general model than the regionally derived Scanlan runoff approach used previously and to improve runoff and water balance prediction. The modified model was calibrated against measured runoff and soil water data for a range of pasture treatments in Central Queensland. Optimised curve numbers were related to cover; curve number reduced from 97 for bare conditions to a minimum of 57 for 53% cover, with no difference between soils (mudstone or sandstone derived, or eroded phases) or types of cover (grass biomass and litter, or tree litter). In the modified model this equation provides feedback of effects of grazing management and tree density on cover to the water balance. Runoff prediction using the Scanlan runoff sub-model (derived for soils in the Burdekin catchment) was satisfactory (r 2 1:1 = 0.70), indicating that soils at the Central Queensland site had similar runoff responses to those in the Burdekin. Addition of the curve number sub-model improved runoff prediction (r 2 1:1 = 0.87). Adjusting curve number each day according to cover improved runoff predictions for low cover situations where cover varied through time, which is important in degraded pastures. Total soil water prediction was very good using the Scanlan runoff sub-model (r 2 1:1 = 0.88) and slightly improved using the modified model (r 2 1:1 = 0.91). Soil water in the surface layer was predicted well, giving confidence in prediction of soil evaporation. This study provides important new runoff parameter values for modelling water balance and degradation of hard setting soils under pasture. The parameters derived from this study can be used with historical climate data to provide a long-term assessment of effects of grazing management on runoff on such soils. SRn et d r la tu s
Assessment of Alternative Fuels for Sustainable Road Transportation

Naturally, human beings move from one point to the other in search of facilities, socioeconomic fulfillment, livelihoods, and other necessities of life. Road transportation is one of the cost-effective, flexible, and easily accessible forms of transportation, globally. However, the application of fossil-based (FB) fuels for transport vehicles is ineffective, emits toxic gasses, pollutes the air, and exacerbates environmental degradation. The current work assesses the application of clean fuels such as biofuels, natural gas, electricity, propane, and other emerging fuels to replace FB fuels in transport vehicles. Unlike FB fuels, the use of biohydrogen, biomethane, biodiesel, and bioethanol in transport vehicles resulted in emission reduction by 70 %, 63 %, 41 %, and 54 %, respectively, while electric vehicles lower maintenance costs, ensures better engine performance, supports renewable energy integration, and better engine efficiency. The adoption of natural gas and propane as alternative fuel for transport vehicles is cost-effective, minimizes the emission of toxic greenhouse gasses, contributes to net-zero emission in the transport sector, and promotes environmental sustainability. There is a need for targeted financial, infrastructural, and technical investments to further promote the application of these clean fuels for road transport application. More multidisciplinary and innovative studies should be commissioned to unravel novel production, transport, storage, and utilization technologies for renewable fuels in the transport sector. Stakeholders should liaise with governments to enact implementable policies and laws that advance the use of alternative fuel for engine applications. The outcome of the study provides updated information and sensitizes automobile engineers, environmentalists, transport fleet operators, governments, and other stakeholders on the benefits derivable in the adoption of clean fuels as alternatives to FB fuels as transport vehicles fuel.
Dynamic UAV Swarm Confrontation: An Imitation Based on Mobile Adaptive Networks

Cooperative unmanned aerial vehicle (UAV) swarms could expand the mission capability of the single UAV and the overall combat effectiveness. We consider the dynamic scenarios where an UAV swarm confronts multiple maneuvering high-value targets (HVTs) and multiple maneuvering attackers. In such hostile scenarios, each UAV of the UAV swarm would generally strive to survive through collaboratively offending their opponents and self-defense from potential attacks. We consider modeling UAV swarms as biologically inspired mobile adaptive networks to imitate the dynamic confrontations of UAV swarms. It is essential to develop an efficient motion control mechanism underpinned by both target tracking and decision making so as to enhance the capability of UAV swarms. We formulate a distributed modularized framework incorporating collaboratively tracking multiple opponents, making successive and prompt decisions, and controlling motion mechanism for mobile adaptive networks. We develop the diffusion multitask interactive Kalman filter to efficiently track multiple preys (HVTs) and multiple predators (attackers). We further develop the collaborative decision making on prey pursuit or predator evasion such that each UAV would acquire early warnings and predictions of the most hypothetically threatening predators to enhance the effectiveness of self-defense. Moreover, we develop a composite motion control mechanism, such that each UAV would be steered toward the prey or away from any approaching predator in a self-organized manner at a variable speed. The modular design of the proposed framework would promote the affordability and adaptability of UAV swarms. Illustrative simulation results validate the efficacy of the proposed distributed framework and the underlying algorithms.
Magnetotelluric constraints on the tectonic setting of Grenville-aged orogenesis in central Australia

Abstract: Magnetotelluric (MT) data were collected over a 480 km long profile in central Australia, extending from the Mesoarchaean–Palaeoproterozoic Gawler Craton into the Mesoproterozoic–Neoproterozoic Musgrave Province. The two regions have contrasting geological histories and many reconstruction models of Proterozoic Australia propose that they were juxtaposed during the Mesoproterozoic. Despite the significant differences in geological background between the Gawler Craton and the Musgrave Province, the MT data did not image an electrical structure, or any change in electrical character, between them. MT models suggest that southern–central Australia is electrically separated into two parts. The first, comprising the northernmost Gawler Craton and the Musgrave Province, has a 5 km thick layer of moderate resistivity overlying highly resistive crust. The second, comprising the central–northern Gawler Craton, displays moderate resistivity to the base of the crust. The lithospheric mantle underlying both electrical regions is uniformly highly resistive. Our results suggest that the Musgrave Province and Gawler Craton are more closely related than is currently recognized. We propose that the Gawler Craton forms basement to the Musgrave Province and that the Grenvillian Musgrave Orogeny was an intracratonic reworking event that overprinted the older basement.
An Integrated Assessment Framework for Uncertainty Studies in Global and Regional Climate Change: The IGSM-CAM

This paper describes an integrated assessment framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the IGSM-CAM incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from uncertainties intrinsic to the economic model, from parametric uncertainty to uncertainty in future climate policies. Another major feature is the flexibility to vary key climate parameters controlling the climate response: climate sensitivity, net aerosol forcing and ocean heat uptake rate. Thus, the IGSM-CAM is a computationally efficient framework to explore the uncertainty in future global and regional climate change due to uncertainty in the climate response and projected emissions. This study further presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent by 2100) and three sets of climate parameters. The chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century climate change. As such, this study presents new estimates of the 90% probability interval of regional climate change for different emissions scenarios. These results underscore the large uncertainty in regional climate change resulting from uncertainty in climate parameters and emissions, and the statistical uncertainty due to natural variability.
Preliminary analysis of ERS-1 wind scatterometer data over land surfaces

Abstract This Letter presents preliminary observations made with the ERS-1 wind scatterometer over land surfaces. A global backscattering coefficient image, synthesized from the original raw data indicates a strong correlation between the radar signal and the distribution of the main vegetation types throughout the world. In particular, tropical vegetation formations are well identified. The effects of angular and multitemporal variations on the backscattering coefficient σ0 are shown for different terrestrial surfaces. Illustrations are given for the African continent which presents numerous vegetation types along a north-south latitudinal gradient. Results indicate the strong capability of the ERS-1 scatterometer to discriminate and monitor vegetation change at a global scale.
Missing-Modal Face Anti-Spoofing: A Benchmark

Nowadays, face anti-spoofing (FAS) has become a popular and important topic in computer vision, particularly for the security of face recognition systems. As camera manufacturing technology continues to mature, multi-modal FAS research is becoming increasingly common. However, most studies assume complete training and testing data, meaning that RGB, Depth, and IR images are available for all examples. While some research has explored flexible modalities, few methods can handle missing modalities during training, testing, or both, let alone at various levels. The challenge becomes even greater when considering different scenarios of missing modalities. In this paper, we establish the missing-modal vision transformer FAS benchmark (MMV-FAS). Specifically, MMV-FAS uses meta-learning to simulates missing modalities, and realizes the interaction between different modalities though multimodal TokenMix and a shared-parameters vision transformer network. We then evaluate our proposed method on three popular multi-modal FAS datasets: WMCA, CASIA-SURF, and CASIA-SURF CeFA. Our experimental results demontrate that our proposed method exhibits competitive performance.
THE INFLUENCE OF HYDROLOGICAL CONNECTIVITY ON FOOD WEB STRUCTURE IN FLOODPLAIN LAKES

Hydrological connectivity is an important driver of ecosystem structure in floodplain rivers; however, little is known of how hydrological connectivity affects the structure and functioning of food webs in these systems. This study examines aquatic food web structure in 10 floodplain lakes on a dryland river floodplain in eastern Australia across a connectivity gradient. Results for fishes suggest that benthic carbon sources are more important in high connectivity billabongs than in low connectivity billabongs and that pelagic sources are more important in low connectivity billabongs than in high connectivity billabongs. Fishes in less connected billabongs were also found to feed at higher trophic levels than in more connected billabongs. We hypothesize that in high connectivity billabongs, where suitable benthic primary sources are abundant, common fish species such as carp and bony bream feed as detritivores or herbivores; while in low connectivity billabongs, where benthic sources are less abundant, the same species feed as planktivores, insectivores or piscivores. This dietary difference may also be promoted by greater predation efficiency in less structurally complex low connectivity billabongs. The feeding behaviour of these fish species subsequently influences the trophic positions of fishes higher in the food chain and ultimately the total food chain lengths that high and low connectivity billabongs support. The results of this study highlight the importance of hydrological connectivity to the structure of food webs in these systems and the potential for them to be affected by water resource development. Copyright © 2011 John Wiley & Sons, Ltd.
Variability of Conducted Emissions of EV Chargers due to Mutual Effects on a DC Grid

DC grids are becoming a popular choice to cope with highly dynamic and distorting loads, such as electric vehicle chargers that feature significant conducted emissions in the supraharmonic range, on/off load profiles and large power levels (especially for fast charging mode, enabled by connection to a DC grid). One major factor affecting the reliable assessment of emissions in the supraharmonic frequency interval (2 kHz to 150 kHz) is the definition of the supply conditions namely the feeding impedance; in addition, emissions in this frequency range are a mix of differential- and common-mode emissions, with prevalence of the former. It is demonstrated that supply impedance values at the EV charger connection may be highly variable depending on network loading and location of the other connected EV chargers: some scenarios of small and medium extension of the DC network are evaluated, showing peculiar frequency intervals where emissions could vary by as much as 20 dB simply as the consequence of connection and disconnection of other EVs.
A Jaccard Factor-Based Heuristic for the Set k-Cover Problem in Wireless Sensor Networks

The applications of a wireless sensor network rely heavily on the network’s ability to function for an extended period. By separating the sensors into groups, each of which may keep an eye on the entire area of interest and be activated alternately, the system’s lifetime can be maximized. However, determining the most significant number of different sensor covers necessitates solving the NP-complete set k-cover issue. This work presents an improved greedy approach to the set k-cover problem based on the Jaccard Similarity Coefficient. The latter is a statistical method used to understand the similarity and diversity between sample sets. Moreover, the quality of the produced solution is improved by removing duplicate sensors for each set cover. The effectiveness of the proposed approach was compared to some greedy-based methods from the literature based on 1000 widely used benchmark instances. Computational results demonstrate its efficacy in producing high-quality solutions within acceptable computational time, especially when the problem scale increases
FM Noise Measurement of Single-Frequency Lasers

The results of the frequency (FM) noise measurements of single-frequency lasers using the optical heterodyne method are reported. The distributed feedback (DFB) diode lasers, the DFB fiber lasers and two types of the external cavity diode lasers (ECDLs) were studied. The technique is based on the direct measurements of the optical FM noise with RF phase noise analyzer (PNA) and is traceable to primary RF phase noise standards.