Temporary Hot Spots Research Articles

Temporal dynamics of faster neo-Z evolution in butterflies.

The faster-Z/X hypothesis predicts that sex-linked genes should diverge faster than autosomal genes. However, studies across different lineages have shown mixed support for this effect. So far, most analyses have focused on old and well-differentiated sex chromosomes, but less is known about the divergence of more recently acquired neo-sex chromosomes. In Lepidoptera (moths and butterflies), Z-autosome fusions are frequent, but the evolutionary dynamics of neo-Z chromosomes have not been explored in detail. Here, we analyzed the faster-Z effect in Leptidea sinapis, a butterfly with three Z chromosomes. We show that the neo-Z chromosomes have been acquired stepwise, resulting in strata of differentiation and masculinization. While all Z chromosomes showed evidence of the faster-Z effect, selection for genes on the youngest neo-Z chromosome (Z3) appears to have been hampered by a largely intact, homologous neo-W chromosome. However, the intermediately aged neo-Z chromosome (Z2), which lacks W gametologs, showed fewer evolutionary constraints, resulting in particularly fast evolution. Our results therefore support that neo-sex chromosomes can constitute temporary hot-spots of adaptation and divergence. The underlying dynamics are likely causally linked to shifts in selective constraints, evolution of gene expression, and degeneration of W-linked gametologs which gradually expose Z-linked genes to selection.

Deep Reinforcement Learning-based Mining Task Offloading Scheme for Intelligent Connected Vehicles in UAV-aided MEC

The convergence of unmanned aerial vehicle (UAV)-aided mobile edge computing (MEC) networks and blockchain transforms the existing mobile networking paradigm. However, in the temporary hotspot scenario for intelligent connected vehicles (ICVs) in UAV-aided MEC networks, deploying blockchain-based services and applications in vehicles is generally impossible due to its high computational resource and storage requirements. One possible solution is to offload part of all the computational tasks to MEC servers wherever possible. Unfortunately, due to the limited availability and high mobility of the vehicles, there is still lacking simple solutions that can support low-latency and higher reliability networking services for ICVs. In this article, we study the task offloading problem of minimizing the total system latency and the optimal task offloading scheme, subject to constraints on the hover position coordinates of the UAV, the fixed bonuses, flexible transaction fees, transaction rates, mining difficulty, costs and battery energy consumption of the UAV. The problem is confirmed to be a challenging linear integer planning problem, we formulate the problem as a constrained Markov decision process. Deep Reinforcement Learning (DRL) has excellently solved sequential decision-making problems in dynamic ICVs environment, therefore, we propose a novel distributed DRL-based P-D3QN approach by using Prioritized Experience Replay strategy and the dueling double deep Q-network (D3QN) algorithm to solve the optimal task offloading policy effectively. Finally, experiment results show that compared with the benchmark scheme, the P-D3QN algorithm can bring about 26.24% latency improvement and increase about 42.26% offloading utility.

In-situ thermography revealing the evolution of internal short circuit of lithium-ion batteries

The demand for lithium-ion batteries is ever increasing while its safety is arousing great public concerns. The feature of a defective cell that may evolve to catastrophic failure is difficult to characterize, given the observation of the cell's internal structure is hard to make. Herein, this paper proposes a new method using thermography to characterize the evolution process from internal short circuit to thermal runaway inside a lithium-ion cell. The spatial and temporal temperature variation around the initiation point of the internal short circuit as well as the voltage and surface temperature are recorded in high frequency. The internal short circuit is triggered by the magnet and wax. The results show that the aluminum-anode-type internal short circuit can lead to thermal runaway by a sequence of the hot spot, gas generation, and combustion. Inadequate internal short circuit heat generation contributes to a temporary hot spot that gradually cools down to ambient temperature. Thermal runaway tends to occur when the hot spot above 150 °C reaches the area of 50 mm2 and the majority of the exothermic side reaction heat in the hot spot area is released within ca. 2s. These results are expected to guide the design of safer lithium-ion batteries.

UAV-assisted cooperative offloading energy efficiency system for mobile edge computing

Reliable communication and intensive computing power cannot be provided effectively by temporary hot spots in disaster areas and complex terrain ground infrastructure. Mitigating this has greatly developed the application and integration of UAV and Mobile Edge Computing (MEC) to the Internet of Things (IoT). However, problems such as multi-user and huge data flow in large areas, which contradict the reality that a single UAV is constrained by limited computing power, still exist. Due to allowing UAV collaboration to accomplish complex tasks, cooperative task offloading between multiple UAVs must meet the interdependence of tasks and realize parallel processing, which reduces the computing power consumption and endurance pressure of terminals. Considering the computing requirements of the user terminal, delay constraint of a computing task, energy constraint, and safe distance of UAV, we constructed a UAV-Assisted cooperative offloading energy efficiency system for mobile edge computing to minimize user terminal energy consumption. However, the resulting optimization problem is originally nonconvex and thus, difficult to solve optimally. To tackle this problem, we developed an energy efficiency optimization algorithm using Block Coordinate Descent (BCD) that decomposes the problem into three convex subproblems. Furthermore, we jointly optimized the number of local computing tasks, number of computing offloaded tasks, trajectories of UAV, and offloading matching relationship between multi-UAVs and multiuser terminals. Simulation results show that the proposed approach is suitable for different channel conditions and significantly saves the user terminal energy consumption compared with other benchmark schemes.

Energy-Efficient Communications in Unmanned Aerial Relaying Systems

Due to flexible deployment and low cost, an unmanned aerial relaying (UAR) system has been considered as a promising aerial communication platform to complement current terrestrial infrastructure in some scenarios like temporary hotspots, disaster areas, and complex terrains. However, practical UAR systems may not be able to provide ubiquitous and high-quality wireless connections, mainly due to the limited on-board energy of unmanned aerial vehicles (UAVs). Consequently, the UAVs are unable to hover in the sky for a long time, thus having to land frequently for energy replenishment. To save UAVs' energy, we propose a joint communication and placement design for energy-efficient communications in a multi-hop UAR system. Specifically, we formulate the Energy Consumption Rate minimization problem, called ECR, by jointly considering routing, data rate, transmission power, and UAV position. Since ECR is a non-convex nonlinear programming, we propose an iterative optimization method to solve ECR iteratively by first reducing ECR into two sub-problems ECR-C and ECR-P and then solving them sequentially at an iteration. Specifically, we develop an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula> -bounded approximation algorithm to solve ECR-C with a performance guarantee, and reformulate ECR-P as a global consensus optimization problem solved by an ADMM (alternating direction method of multipliers) method. Particularly, all UAVs locally update their own positions in parallel, reducing the computation and implementation complexity significantly. Extensive simulation results show the energy efficiency improvement by up to 20% compared with other existing algorithms.

Dramatic temporal variations in methane levels in black bloom prone areas of a shallow eutrophic lake

Global lakes serve as a key natural source of methane (CH4) and suffer from increasing hypoxia due to unprecedented anthropogenic activities and climate change. A black bloom is a temporary hypoxia triggered by a longstanding algal bloom, which facilitates CH4 production by creating reducing conditions and abundant algae-sourced organic carbon. One-year investigations were conducted to examine temporal CH4 dynamics in the water and sediment pore water in black bloom prone areas (BBPAs) in Lake Taihu, China, where there had been at least two recorded black bloom events. The CH4 in the water changed significantly with time (p < 0.001), with the highest concentrations appearing in warm months when an abnormal lower dissolved oxygen content was observed at different sites, which were one to two orders of magnitude higher than other months. Compared with the control site, there were significantly higher CH4 concentrations in BBPA waters (p < 0.001), which was consistent with the higher CH4 in the sediment pore water. Methane dynamics in the water showed significant positive correlations with temperature, total phosphorus, total nitrogen, ammonia-N, and soluble reactive phosphorus (p < 0.05), but showed a significant inverse correlation with dissolved oxygen (p < 0.01). Redundancy analysis indicated dissolved oxygen made the largest contribution to CH4 dynamics in the BBPAs. A significant increase in the CH4 in water will turn BBPAs into temporary hot spots with substantial CH4 emissions with the appearance of black blooms. The results provide new insights into understanding future CH4 dynamics under globally prevailing algal blooms and climate change.

Energy Efficiency and Hover Time Optimization in UAV-Based HetNets

In this article, we investigate the downlink performance of a three-tier heterogeneous network (HetNet). The objective is to enhance the edge capacity of a macro cell by deploying unmanned aerial vehicles (UAVs) as flying base stations and small cells (SCs) for improving the capacity of indoor users in scenarios such as temporary hotspot regions or during disaster situations where the terrestrial network is either insufficient or out of service. UAVs are energy-constrained devices with a limited flight time, therefore, we formulate a two layer optimization scheme, where we first optimize the power consumption of each tier for enhancing the system energy efficiency (EE) under a minimum quality-of-service (QoS) requirement, which is followed by optimizing the average hover time of UAVs. We obtain the solution to these nonlinear constrained optimization problems by first utilizing the Lagrange multipliers method and then implementing a sub-gradient approach for obtaining convergence. The results show that through optimal power allocation, the system EE improves significantly in comparison to when maximum power is allocated to users (ground cellular users or connected vehicles). The hover time optimization results in increased flight time of UAVs thus providing service for longer durations.

A Reappraisal of Seismicity Recorded During the 1996 Gjálp Eruption, Iceland, in Light of the 2014–2015 Bárðarbunga–Holuhraun Lateral Dike Intrusion

This study performs a reanalysis of the seismicity recorded during the 1996 Gjalp eruption that occurred at NW Vatnajokull, Iceland. The seismicity was recorded by the temporary HOTSPOT network consisting of 30 three-component broadband stations. In total 301 events were identified between 29 September and 12 October and their phases were manually picked. A velocity model was estimated from P-phase travel times by using VELEST. Events were first located using the algorithm NONLINLOC in order to obtain absolute locations. Precise relative locations were obtained with HYPODD by utilizing catalog and cross-correlation differential travel times. Results show that events clustered first along the SW rim of the Barðarbunga caldera and later along the Gjalp fissure, with most hypocentral depths located between 3 and 8 km. Waveforms of the 10 largest events that followed the Barðarbunga earthquake were inverted in order to obtain moment tensors. For all events we found that the deviatoric moment tensor fits the data better than pure double-couple or full moment tensor solutions. Events along the Barðarbunga caldera exhibited reverse focal mechanisms, while those at the Gjalp fissure exhibited mostly strike-slip faulting. Seismic velocity variations calculated using ambient noise interferometry, point to the possibility that a small subglacial eruption occurred at Barðarbunga before the main earthquake. This removed melt from the magma chamber causing its roof to collapse, and also resulted in the lateral migration of magma towards the Gjalp fissure. The 2014–2015 Barðarbunga–Holuhraun eruption shares common characteristics with the 1996 Gjalp eruption, although the size of the latter was much smaller.

The impact of cattle dung pats on earthworm distribution in grazed pastures

BackgroundGrazed grassland management regimes can have various effects on soil fauna. For example, effects on earthworms can be negative through compaction induced by grazing animals, or positive mediated by increases in sward productivity and cattle dung pats providing a food source. Knowledge gaps exist in relation to the behaviour of different earthworm species i.e. their movement towards and aggregation under dung pats, the legacy effects of pats and the spatial area of recruitment. The present study addressed these knowledge gaps in field experiments, over 2 years, using natural and simulated dung pats on two permanent, intensively grazed pastures in Ireland.ResultsDung pats strongly affected spatial earthworm distribution, with up to four times more earthworms aggregating beneath pats, than in the control locations away from pats. In these earthworm communities comprising 11 species, temporally different aggregation and dispersal patterns were observed, including absence of individual species from control locations, but no clear successional responses. Epigeic species in general, but also certain species of the anecic and endogeic groups were aggregating under dung. Sampling after complete dung pat disappearance (27 weeks after application) suggested an absence of a dung pat legacy effect on earthworm communities. Based on species distributions, the maximum size of the recruitment area from which earthworms moved to pats was estimated to be 3.8 m2 per dung pat. Since actual grazing over 6 weeks would result in the deposition of about 300 dung pats per ha, it is estimated that a surface area of 1140 m2 or about 11% of the total grazing area can be influenced by dung pats in a given grazing period.ConclusionsThis study showed that the presence of dung pats in pastures creates temporary hot spots in spatial earthworm species distribution, which changes over time. The findings highlight the importance of considering dung pats, temporally and spatially, when sampling earthworms in grazed pastures. Published comparisons of grazed and cut grasslands probably reached incorrect conclusions by ignoring or deliberately avoiding dung pats. Furthermore, the observed intense aggregation of earthworms beneath dung pats suggests that earthworm functions need to be assessed separately at these hot spots.

Early Warning System for Temporary Crime Hot Spots

We investigate the potential for preventing crimes at temporary hot spots in addition to chronic hot spots. Using data on serious violent crimes from Pittsburgh, Pennsylvania, we investigate an early warning system (EWS) for starting/stopping police deployments at temporary hot spots in coordination with constant prevention work at chronic hot spots. We estimate chronic hot spots using kernel density smoothing. We use simple rules for detecting flare-ups of temporary hot spots, predicting their persistence, deploying police, and stopping deployments. We also consider a combination program including the hottest chronic hot spots, with EWS applied to remaining areas. Using 2000–2010 data, we run computational experiments varying the size of chronic hot spots and varying rule thresholds to tune the EWS. Tradeoff curves with percentage of crimes exposed to prevention versus percentage area of the city with crime prevention workload provide tools for coordinating chronic and temporary hot spot programs. The combination program is the most efficient, equitable, and responsive program. After first allocating police prevention resources to the hottest chronic hot spots, the marginal benefits of adding more chronic hot spot area is not as high as adding temporary hot spots. Chronic hot spots are limited to large commercial and adjoining residential areas. Temporary hot spots are widely scattered throughout Pittsburgh. Temporary hot spots exist outside of chronic hot spots and are targets for prevention as supplements to chronic hot spots. A combination program targeting both chronic and temporary hot spots is recommended.

Thermal windows on the trunk of hauled-out seals: hot spots for thermoregulatory evaporation?

Seals have adapted to the high heat transfer coefficient in the aquatic environment by effective thermal insulation of the body core. While swimming and diving, excess metabolic heat is supposed to be dissipated mainly over the sparsely insulated body appendages, whereas the location of main heat sinks in hauled-out seals remains unclear. Here, we demonstrate thermal windows on the trunk of harbour seals, harp seals and a grey seal examined under various ambient temperatures using infrared thermography. Thermograms were analysed for location, size and development of thermal windows. Thermal windows were observed in all experimental sessions, shared some common characteristics in all seals and tended to reappear in similar body sites of individual seals. Nevertheless, the observed variations in order and location of appearance, number, size and shape of thermal windows would imply no special anatomical site for this avenue of heat loss. Based on our findings, we suggest that, in hauled-out seals, heat may be transported by blood flow to a small area of the wet body surface where the elevation of temperature facilitates evaporation of water trapped within the seals' pelages due to increased saturation vapour pressure. The comparatively large latent heat necessary for evaporation creates a temporary hot spot for heat dissipation.

Adaptive Distributed Dynamic Channel Allocation for Wireless Networks

Channel allocation schemes in a mobile computing (wireless) environment can be either static or dynamic. Static allocation offers negligible channel acquisition time and zero message complexity and works well at a low system load; the performance steadily decreases as system load increases since many calls are dropped. In the case of even temporary hot spots many calls may be dropped by a heavily loaded switching station even when there are enough idle channels in the interference region of that station. On the other hand, dynamic schemes provide better utilization of the channels at higher loads albeit at the cost of higher channel acquisition time and some additional control messages. Our purpose in the present paper is to propose a combined channel allocation scheme so that each switching station can tune to its own load independent of other stations in its interference region; the objective is to minimize the call drop rate and at the same time maintain a minimum average channel acquisition time and minimum control message complexity.