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With the aggressive and amazing scaling of the feature size of semiconductors, hotspot detection has become a crucial and challenging problem in the generation of optimized mask design for better printability. Machine learning techniques, especially deep learning, have attained notable success on hotspot detection tasks. However, most existing hotspot detectors suffer from suboptimal performance due to two-stage flow and less efficient representations of layout features. What is more, most works can only solve simple benchmarks with apparent hotspot patterns like ICCAD 2012 Contest benchmarks. In this paper, we firstly develop a new end-to-end hotspot detection flow where layout feature embedding and hotspot detection are jointly performed. An attention mechanism-based deep convolutional neural network is exploited as the backbone to learn embeddings for layout features and classify the hotspots simultaneously. Experimental results demonstrate that our framework achieves accuracy improvement over prior arts with fewer false alarms and faster inference speed on much more challenging benchmarks.

Motivation Recombination is one of the essential genetic processes for sexually reproducing organisms, which can happen more frequently in some regions, called recombination hotspots. Although several factors, such as PRDM9 binding motifs, are known to be related to the hotspots, their contributions to the recombination hotspots have not been quantified, and other determinants are yet to be elucidated. Here, we propose a computational method, RHSNet, based on deep learning and signal processing, to identify and quantify the hotspot determinants in a purely data-driven manner, utilizing datasets from various studies, populations, sexes and species. Results RHSNet can significantly outperform other sequence-based methods on multiple datasets across different species, sexes and studies. In addition to being able to identify hotspot regions and the well-known determinants accurately, more importantly, RHSNet can quantify the determinants that contribute significantly to the recombination hotspot formation in the relation between PRDM9 binding motif, histone modification and GC content. Further cross-sex, cross-population and cross-species studies suggest that the proposed method has the generalization power and potential to identify and quantify the evolutionary determinant motifs. Availability and implementation https://github.com/frankchen121212/RHSNet. Supplementary information Supplementary data are available at Bioinformatics online.

Due to the long latency of accessing services from cloud datacenters, mobile edge computing (MEC) has been proposed to provide the capability of cloud computing in close proximity to mobile users. Mobile devices can offload computation-intensive applications to MEC servers to achieve better performance and reduce power consumption. Owing to user mobility, workloads of MEC servers would vary severely to cause imbalanced loads and incur hotspot servers. Previous studies of power saving and hotspot management apply mechanisms for cloud datacenters to MEC servers, but these studies may not be suitable for MEC servers due to the limited computation and communication capacity. We are motivated to propose a scheme, complementary offloading for hotspot mitigation (COHM), for MEC. COHM consists of mechanisms for MEC servers with different states, namely busy, idle, and available. These mechanisms jointly consider the computation tasks for MEC servers with different states to mitigate hotspots. The simulation results show that COHM can decrease the number of hotspot servers without degrading the quality of service for applications.

As the circuit feature size continuously shrinks down, hotspot detection has become a more challenging problem in modern DFM flows. Developed deep learning techniques have recently shown their superiorities on hotspot detection tasks. However, existing hotspot detectors can only handle defect detection from one small layout clip each time, thus may be very time-consuming when dealing with a large full-chip layout. In this paper, we develop a new end-to-end framework that can detect multiple hotspots in a large region at a time and promise a better hotspot detection performance. We design a joint auto-encoder and inception module for efficient feature extraction. A two-stage classification and regression framework is designed to detect hotspot with progressive accurate localization, which provides a promising performance improvement. Experimental results show that our framework enables a significant speed improvement over existing methods with higher accuracy and fewer false alarms.

The Mascarene Islands in the western Indian Ocean, encompassing La Réunion, Mauritius, and Rodrigues, are the recent (, Geochimica et Cosmochimica Acta, 355, ISSN:0016-7037, ISSN:1872-9533

With the rapid increase of solar module wattage from about 300 W to above 650 W, it is important to study the impact of high wattage on the hot spot risk. In this paper we use finite element analysis (FEA) and experiments to analyze the effects of various designs on the hot spot temperature of high wattage solar modules. Design factors include cell size (156.75 mm, 166 mm, 182 mm and 210 mm), the number of cells per bypass diode and cell shape (full cell, half cell and one-third cells). The simulation data is in good agreement with the experiment, and shows a clear trend: increasing the number of cells per bypass diode increases the hotspot temperature at most, increasing cell size leads to a moderate but considerate increase, and cutting a cell into smaller pieces lowers the hot spot temperature under certain conditions. The developed thermal balance model shows that the change in the power density and effective thermal resistance at the hotspot cells are the keys to the trend. This research proves the effectiveness of using finite element analysis (FEA) to study the hotspot risk, and points out a new direction for how to control the hotspot risk of high wattage solar modules with larger solar cells.

The alkalinity of ocean island basalts (OIB), which form by upwelling thermo-chemical instabilities in the mantle, is often associated with the degree of melting. Yet it remains to be tested if alkalinity and the degree of melting are systematically associated with enriched mantle components. The Tasmantid Seamounts, which are fossil remnants of the Tasmantid mantle plume, comprise a north-south age-progressive submarine volcanic chain in the Coral and Tasman Seas East of Australia. Dredged seafloor lavas from nine seamounts along the seamount chain, ranging in age from 50 to 6.5 Ma, show a dichotomy in alkalinity, similar to those observed in other hotspot areas such as Hawai’i or Pitcairn. In radiogenic Sr-Nd-Hf-Pb isotope systematics, Tasmantid Seamount lavas form a continuum between EM1 and PREMA and are thus part of the prevalent EM1-PREMA association in the Pacific. However, their radiogenic Pb isotope systematics mark the Tasmantid plume as an individuum with no resemblance to any other plume. In stable Fe isotopes (expressed as δ57FePrim, which is the Fe isotopic composition calculated to primitive lavas along a liquid line of descent) alkali basalts are, on average, isotopically heavier than tholeiitic lavas, ranging in δ57FePrim from +0.10 to +0.21‰, unrelated to radiogenic isotope systematics, but with co-variations of δ57FePrim and Ti* (which is the primitive melt Ti content). These systematics point towards residual garnet as a key factor and thus indicate a solely petrologic relation between degrees of melting and Fe isotopes. Tholeiitic lavas exhibit a near-depleted mantle like isotopic composition (ranging in δ57FePrim from −0.01 to +0.22‰, median at δ57FePrim + 0.04‰), yet with values of up to δ57FePrim + 0.22‰ that require an isotopically heavy source of unknown origin. The lack of systematics between alkalinity and radiogenic isotope signatures indicates that temperature is the likely driving force for variable melting degrees in some samples over others. Based on these observations, we surmise that tholeiitic lavas form in the plume centre whereas alkaline lavas form at the cooler rim of the conduit. Mixing between melts and associated enriched components in the Tasmantid mantle plume may occur but, at least for alkaline lavas, only on a small scale.

Background and aims – We here describe two new species of Eremitis from Bahia, Brazil, and compare them with morphologically similar species. We also provide illustrations, photos, a distribution map, and notes on habitat and conservation status of the new species.Material and methods – This study was based on fieldwork, analysis of herbarium specimens, and literature review. Specimens collected were analyzed and photographed during fieldwork and observed in cultivation in a greenhouse. The conservation assessment is based on field observations and spatial analyses, following the IUCN guidelines and criteria.Results – Eremitis clarkiae sp. nov. occurs in southern Bahia and has been collected only twice, in the municipality of Floresta Azul. The new species is similar to E. jardimii and E. robusta, both also endemic to Bahia, but can be distinguished by several vegetative and reproductive structures longer than those observed in these species, such as leafy culms, ligules, decumbent culm inflorescences, and pedicels of the staminate spikelets of the staminate whorls. Eremitis vinacea sp. nov. was collected in three localities in southern Bahia, but only the type population was found during recent field trips, in the municipality of Camacã. It is similar to E. afimbriata, a species endemic to Espírito Santo state, being differentiated by its leaf sheaths with persistent fimbriae (vs absent), leaf blades with green adaxial surface (vs bluish green with a blue iridescence), and a single inflorescence on decumbent culms (vs multiple). Both new species are endemic to the Bahian Coastal Forests subregion and should be considered Critically Endangered (CR), according to the IUCN guidelines and criteria.

Previous work shows that auto-ignition propagation modes for strong knocking in engines are dominated by both chemical reactivity and energy density. To clarify the unique role of energy density and chemical reactivity, hotspot auto-ignition induced reaction wave propagation was investigated using direct numerical simulations, addressing the detonation regime in the detonation peninsula. Different operating conditions and mixture components were employed to design specific chemical reactivity and energy density under engine-relevant conditions. Various auto-ignition propagation modes were quantitatively investigated. The results show that unified standards for detonation development and high-accuracy excitation time are necessary for constructing a detonation peninsula. Energy density promotes detonation development and broadens the detonation regime, especially at large hotspot sizes. Meanwhile, there are positive correlations between peak pressure and energy density during detonation development, and the pressure peak can reach an amplitude beyond detonation equilibrium pressure. Furthermore, the improvement in chemical reactivity suppresses detonation development at small hotspot sizes while promoting detonation development at large hotspot sizes. But the variations in chemical reactivity caused by thermal effects show a greater significance than by fuel properties. Besides, obvious distinctions in peak pressure can be identified with the variations of reactivity gradient, and the amplitude always attains the maximum level just when detonation occurs at the edge of the hotspot. Underlying reasons are ascribed to the initial non-uniform distribution of energy density within the hotspot. Meanwhile, the reactivity progress of the remaining mixtures also affects energy density outside the hotspot.

The details and mechanisms for Neogene river reorganization in the U.S. Pacific Northwest and northern Rocky Mountains have been debated for over a century with key implications for how tectonic and volcanic systems modulate topographic development. To evaluate paleo-drainage networks, we produced an expansive data set and provenance analysis of detrital zircon U-Pb ages from Miocene to Pleistocene fluvial strata along proposed proto-Snake and Columbia River pathways. Statistical comparisons of Miocene-Pliocene detrital zircon spectra do not support previously hypothesized drainage routes of the Snake River. We use detrital zircon unmixing models to test prior Snake River routes against a newly hypothesized route, in which the Snake River circumnavigated the northern Rocky Mountains and entered the Columbia Basin from the northeast prior to incision of Hells Canyon. Our proposed ancestral Snake River route best matches detrital zircon age spectra throughout the region. Furthermore, this northerly Snake River route satisfies and provides context for shifts in the sedimentology and fish faunal assemblages of the western Snake River Plain and Columbia Basin through Miocene–Pliocene time. We posit that eastward migration of the Yellowstone Hotspot and its effect on thermally induced buoyancy and topographic uplift, coupled with volcanic densification of the eastern Snake River Plain lithosphere, are the primary mechanisms for drainage reorganization and that the eastern and western Snake River Plain were isolated from one another until the early Pliocene. Following this basin integration, the substantial increase in drainage area to the western Snake River Plain likely overtopped a bedrock threshold that previously contained Lake Idaho, which led to incision of Hells Canyon and establishment of the modern Snake and Columbia River drainage network.

Shale gas has enormous potential and has become a hotspot in recent decades. To exploit shale gas, a variety of working fluids (drilling fluid, fracturing fluid, etc.) have to be applied in drillin...

Hotspot is one form of utilizing Wireless LAN technology that can be used to access internet services and is usually found in public areas such as libraries, campus internet parks, or offices. Aspects that need to be considered in hotspots to make users feel comfortable is security then at the provider side, the aspect that needs to be considered is the regulation of bandwidth allocation to optimize the data transfer speeds that the network and to prevent the possibility of dense network traffic. RADIUS server is one type of server that can be used at hotspots to secure hotspots because it supports various types of encryption. In this study, optimization of the settings for hotspot network bandwidth is optimized by integrating the RADIUS server with RouterOS. Bandwidth allocation management is done by determining the active time of a user account and set quotas hotspot uploads and downloads for the account. The results obtained from this study indicate that when a hotspot user account has passed the active time or has passed the upload quota and the download given, the account will be deleted from the list of hotspot user accounts or disabled.

The Tonga subduction zone in the south-west Pacific is the fastest convergent plate boundary in the world with the most active mantle seismicity. This zone shows unique tectonic features including Samoan volcanic lineament of plume-driven origin near the northern rim of the Tonga subducting slab. The proximity of the Samoa hotspot to the slab is enigmatic and invokes debates on interactions between the Samoa plume and the Tonga subduction. Based on long-term observations of intermediate and deep-focus Tonga earthquakes reported in the Global Centroid Moment Tensor (CMT) catalog, we provide novel detailed imaging of this region. Accurate traveltime residua of the P- and S-waves recorded at two nearby seismic stations of the Global Seismographic Network are inverted for the P- and S-wave velocities and their ratio and reveal their pronounced lateral variations. In particular, they differ for the southern and northern parts of the Tonga subduction region. While no distinct anomalies are detected in the southern Tonga segment, striking low-velocity anomalies associated with a high Vp/Vs ratio are observed in the northern Tonga segment close to the Samoa plume. These anomalies spread through the whole upper mantle down to depths of ~ 600 km. Together with the fast extension of the northern back-arc Lau Basin, slab deformation and geochemical enrichment in the northern Tonga region, they trace deep-seated magmatic processes and evidence an interaction of the Tonga subduction with the Samoa plume.

An exomoon on a non perfectly circular orbit experiences tidal heating that is capable to significantly contribute to the thermal brightness of the moon. Here we argue that the thermal heat is unevenly distributed on the moon's surface, the emission of the tidal heat is limited to a few hot spots on the surface. A well-known example is the tidally heated Io. Due to their significantly increased temperature, the hot spots enhance the energy emission in thermal wavelengths. We made simulations using Monte-Carlo method to examine this contribution, and to predict about the possible detectability of such a spotted exomoon. We found that in the case of large, Earth sized companions to jupiters around red dwarf stars exhibit a thermal flux that enables the direct detection of the moon, due to its photometric signal that can exceed $\approx$100 ppm in the most favourable configurations., Accepted by MNRAS, 16 pages

In recent years, exploration and development of deep shale gas (at a burial depth of 3, 500-4, 500 m) has become a hotspot in the industry. However, the state of gas storage and transporting mechanism for deep shale gas under high pressure and temperature have not been thoroughly explored, compared with its shallower counterpart. A numerical model for deep shale gas recovery considering multi-site non-isothermal excess adsorption has been established and applied using Finite Element Method. Results from the simulation reveal the following. (1) Excess desorption significantly impacts early-stage performance of deep shale gas well; the conventional way for shallower shale gas development, in which the density of adsorbed gas is not distinguished from that of free gas, overestimates the gas in place (GIP). (2) Although thermal stimulation can speed up the desorption and transporting of deep shale gas, the incremental volume of produced gas, which is impacted not only by seepage velocity but also density of gas, is insignificant, far from expectation. Only an additional 2.03% of cumulative gas would be produced under treatment temperature of 190 °C and initial reservoir temperature of 90 °C in a period of 5 years. (3) Matrix porosity, which can be measured on cores in laboratory and/or estimated by using well logging and geophysical data, is the most favorable parameter for deep shale gas recovery. With 60% increase in matrix porosity, an extra 67.25% shale gas on a daily base would be recovered even after 5-year depletion production; (4) Production rate for gas wells in shale reservoirs at 3, 500 m and 4, 500 m deep would be raised by 5.4% in a 5-year period if the depth of target interval would increase by 340 m without thermal treatment according to the numerical model proposed in the study. The paper provides a novel framework for optimizing deep shale gas development and clarifying some misunderstandings on adsorption behaviors associated with relatively high pressure and temperature.

The residual anomaly of GECO model-derived gravity data has been enhanced using first vertical derivative, tilt derivative and balanced horizontal derivative for delineation of structural and tectonic features over the Bay of Bengal (BOB). Entire BOB basin is classified in eastern, central and western basins for analysis of the delineated lineaments to understand the tectonic setting. It is observed that major lineament trends in the western and central basins are N–S, NE–SW, and in the eastern basin N–S, NNE–SSW, while prominent lineament trend for the entire BOB basin is in N–S direction. The statistical analysis of the lineament attributes, viz. lineament density, circular standard deviation, circular variance for the lineaments, reveals that the crust under the central basin has experienced the maximum tectonic disturbances followed by the western and the eastern basins. Euler depth solutions for structural index (SI) zero estimate the possible source depths of the lineaments as (i) 3.0–9.0 km (possibly top sedimentary layer), (ii) 9.0–18.0 km (possibly intermediate sedimentary layer), (iii) 18.0–24.0 km (possibly upper crustal layer), (iv) 24.0–33.0 km (possibly lower crustal layer) and (v) 33.0–64.0 km (possibly associated with Lithosphere). Power spectral analysis and 2D forward modelling indicate that sediment thickness varies from 2.0 to 17.0 km; crustal thickness varies from 4.0 to 16.0 km, and Moho varies from 10 to 34 km depth over the BOB. The present study confirms that the origin of the 85°E ridge is due to the sagging of ridge crust into the mantle lithosphere, whereas the NER has a hotspot origin.

The northeastern United States (NEUS) and the adjacent Northwest Atlantic Shelf (NWS) have emerged as warming hotspots, but the connection between them remains unexplored. Here we use gridded observational and reanalysis datasets to show that the twentieth-century surface air temperature increase along the coastal NEUS is exceptional on the continental and hemispheric scale and is induced by a combination of two factors: the sea surface temperature (SST) increase in the NWS associated with a weakening Atlantic Meridional Overturning Circulation (AMOC), and atmospheric circulation changes associated with a more persistent positive North Atlantic Oscillation. These connections are important because AMOC slowdown and NWS warming are projected to continue. A survey of climate model simulations indicates that realistic SST representation at high spatial resolution might be a minimum requirement to capture the observed pattern of coastal warming, suggesting that prior projection-based assessments may not have captured key features in this populous region. The coastal northeastern United States is a warming hotspot, and observations identify a slower Atlantic overturning circulation and a positive North Atlantic Oscillation phase as drivers. Analysis suggests that low horizontal resolution probably hampers models’ ability to capture the spatial pattern of enhanced warming.

The study aimed at using Moderate Resolution Imaging Spectroradiometer (MODIS-Terra) to investigate long-term spatial and temporal aerosol variations over Zambia during 2000–2020. Based on data availability, ground truthing for MODIS-Terra was done over Mongu in western Zambia using Aerosol Robotic Network (AERONET) data for 2001–2009. The correlation coefficient between MODIS-Terra and AERONET is 0.42 and statistically significant at 95% confidence level. The aerosol optical depth at 550nm (AOD550) and Angstrom exponent (AE470-870) annual mean spatial distribution indicates high and moderate to low patterns explaining distinct features of aerosol loadings from different areas over Zambia. Generally, the AOD550 and AE470-870 spatial gradient values increase from southern to northern Zambia explaining fine mode particles mainly produced by local intensive anthropogenic and urban/small and large-scale industrial emission activities in the cities. Seasonal climatology reveals that highest AOD550 is observed during SON, followed by JJA, DJF, with the lowest recorded during MAM. It is also observed from AE470-870 that fine particles are prominent during JJA and SON. The insignificant decreasing (increasing) trend of AOD550 is revealed over Mwinilunga, Misamfu, Mfuwe, Choma, and Kabwe (Mongu). Further results showed that fire hotspot density intensifies over central parts of Africa, including Zambia from June to November. Moreover, the 5-day air mass back trajectory analysis suggests that aerosol sources over Zambia are associated with short- and long-distance ranges from East Africa, Congo Basin, Madagascar, and Atlantic and Indian oceans with diverse transport pathways in different seasons. These findings may help enhance a better understanding of climatic effects and atmospheric aerosol sources in Zambia.

Microwave ovens function through the emission of electromagnetic waves, which reflect off the walls of the cavities causing local fluctuations to the electromagnetic field. In multimode cavities, multiple hotspots are generated due to the presence of various nodes, causing the localized overheat. Understanding the location of the hotspots is important to improve the heating efficiency and homogeneity of the microwave. This work aimed to propose an innovative technique for mapping the hotspots inside the multimode cavities microwave, using a resistive sheet made of polypropylene and activated carbon in contents of 5, 10 and 20%. To validate the experimental mapping technique, numerical simulations were used to predict the electromagnetic fields inside the cavity, and the simulations were then compared to the experimental result. The numeric models were validated through the experimentally determined output power. The experimental mapping results showed it was possible to reproduce clear and easy identifiable hotspots in different heights inside cavities using resistive sheets with activated carbon contents of 10 and 20%. The numerical simulations showed results for the output power that were statistically equal to the experimental results, validating its application for the prediction of the electromagnetic and thermo fields. Comparing the experimental and numerical mapping of the hotspots, a consistent match was verified between the generated profiles. Thus, the developed mapping technique managed to predict adequately the hotspots inside microwave cavities, which is useful for applications such as scale-ups and the optimization of industrial cavities.

Understanding the dynamics of the greater Yellowstone region requires constraints on deformation spanning million year to decadal timescales, but intermediate-scale (Quaternary) records of erosion and deformation are lacking. The Upper Snake River drainage crosses from the uplifting region that encompasses the Yellowstone Plateau into the subsiding Snake River Plain and provides an opportunity to investigate a transect across the trailing margin of the hotspot. Here, we present a new chronostratigraphy of fluvial terraces along the lower Hoback and Upper Snake Rivers and measure drainage characteristics through Alpine Canyon interpreted in the context of bedrock erodibility. We attempt to evaluate whether incision is driven by uplift of the Yellowstone system, subsidence of the Snake River Plain, or individual faults along the river's path. The Upper Snake River in our study area is incising at roughly 0.3 m/k.y. (300 m/m.y.), which is similar to estimates from drainages at the leading eastern margin of the Yellowstone system. The pattern of terrace incision, however, is not consistent with widely hypothesized headwater uplift from the hotspot but instead is consistent with downstream baselevel fall as well as localized deformation along normal faults. Both the Astoria and Hoback faults are documented as active in the late Quaternary, and an offset terrace indicates a slip rate of 0.25–0.5 m/k.y. (250–500 m/m.y.) for the Hoback fault. Although tributary channel steepness corresponds with bedrock strength, patterns of χ across divides support baselevel fall to the west. Subsidence of the Snake River Plain may be a source of this baselevel fall, but we suggest that the closer Grand Valley fault system could be more active than previously thought.

Regardless of the doubt caused by some rounds on the impossibility of earthquake forecast, more and more countries, even at the highest governmental levels, realize that doing nothing is the ostrich position of dread before the real difficulties associated with the creation of a real forecasting system. Nigeria in times past was believed to be aseismic. However, the seismic record of Nigeria from 1933-2021 have demonstrated in contrast to the idea, numerous quakes have been recorded in Nigeria throughout the years. With the development of observation techniques and theoretical knowledge of geochemistry, geochemical observation of faults gas has become a hotspot once more in recent years. Rn, Hg, H2, etc., are used for geochemical observations. 222Rn has a half-life of 3.825 days, a magnitude 5.0 earthquake will be detected through precursory phenomena at a distance not greater than 142 km. Mercury and other elements are used as important detectors for earthquake prediction and they play an important role in revealing the relationship between fluid in the fault zone and the occurrence of earthquakes, the range for a magnitude 5.0 earthquake is limited to 200 km. Hydrogen concentrations have been monitored for precursory variations in many fault systems, using either discrete sampling and laboratory analysis or continuous monitoring of ground gas, using hydrogen-sensitive fuel cells. Precursory changes in groundwater chemistry are often attributed to the mixing of fluids from two or more chemically distinct aquifers, the physical mechanism responsible for the mixing of fluids is, however, not well established.

One of the provinces in Indonesia that experiences forest and land fires every year is Aceh Province. Aceh Barat District is one of the districts in Aceh Province where forest and land fires occur every dry season. Forest and land fires prevention can be done by utilizing hotspot data for analysis using geographic information systems (GIS). This research aims to analyze the distribution of hotspots and the correlation between rainfall and hotspots as an indicator of the occurrence of forest and land fires in West Aceh Regency in 2014-2019. This research uses MODIS LAPAN hotspots data, land cover distribution maps, peat land distribution maps, administrative maps and rainfall data from BMKG. The correlation between rainfall data and hotspot data was carried out by the bivariate pearson correlation test. The resuls of the research found that there were 576 hotspots in West Aceh Regency from 2014-2019. The district with the highest number of hotspots is in Samatiga District, namely 131 hotspots. The most dominant hotspots are in the peatland cover, as much as 64% and in the swamp scrub land cover area with 126 hotspots. Correlation test results show that rainfall with a negative correlation, that the decrease in rainfall is followed by an increase in hotspots. Keywords: Aceh Barat, fires, GIS, hotspot, rainfall

Waingapu is one of the areas in Nusa Tenggara Timur Province which often suffered from savanna fires. Savanna fires prevention can be done by utilizing hotspot data for analysis using Geographic Information System (GIS). The climate is one of factors influence the occurrence of savanna fires in Waingapu. The purpose of this study was to analyze the relationship between precipitation, SST anomalies, and the occurrences of savanna fires in Waingapu. This research was conducted on February April 2021 at the Forest and Land Fires Laboratory, Department of Silviculture, Faculty of Forestry and Environment, IPB University. The data used are MODIS and VIIRS hotspot data, daily precipitation data and SST 3.4 anomaly data. The results showed that precipitation was inversely related to hotspots with a negative correlation value. SST anomaly is inversely related to precipitation a negative correlation value. While the SST anomaly with hotspots is directly proportional with a positive correlation value. Keywords: climate, hotspot, Geographic Information System (GIS), Waingapu

The increasing frequency of heat waves (HW) in many parts of the world is emerging as one of the climatic vulnerabilities across the world resulting in elevated thermal stress and high mortality. With increase in HW intensity, frequency and duration at global level, India has seen several major HW events in the last decade. HW conditions have mostly been studied by analysing ground-based observations; however, this approach lacks information on spatial variability at the local scale, which is not adequate to identify HW risk and vulnerability hotspots. In this study, gridded analysis of spatio-temporal variability of HW indices has been carried out by utilising freely available Moderate Resolution Imaging Spectrometer (MODIS) Land Surface Temperature (LST) data on Google Earth Engine (GEE) platform in the Indo-Gangetic Plains of India. HW indices to analyse duration, frequency and intensity of HW have been identified and further computed on a grid size of 10 km*10 km area. HW risk and vulnerability hotspot in the study region have been identified by spatial modelling of HW indices, LULC change and population density. The HW risk and vulnerability hotspot layer identified NCT Delhi and its surrounding region at the highest risk of HW with high vulnerability. A strong positive correlation of variability of HW indicators with increasing built-up shows that built-up surfaces affect strongly the HW conditions.

For a given set of spatial locations (e.g., criminal activities, disease outbreak, etc.), circular hotspot detection (CHD) identifies circular zones (or hotspots) of significantly high concentration of activity points in the given space. Furthermore, the prevalence of activities inside these zones is considerably higher than outside them. CHD is essential for numerous societal applications, including criminology, epidemiology, etc. The existing methods for CHD consider one of the given activity points as the center of the circular zone (or hotspot). Hence, these methods are incapable of ignoring small gaps (like mountains, rivers, etc.) in the spatial contiguity of hotspots and are not geographically robust. Geographically robust CHD (GR-CHD) requires enumeration of those candidate circles where the hotspot center is not necessarily an activity point. Unfortunately, this enumeration unreasonably increases the enumerated circles and makes GR-CHD a computationally expensive problem. Therefore, in this paper, GR-CHD is modeled as a single-objective optimization problem. Further, three swarm intelligence (SI) algorithms, namely particle swarm optimization, grey wolf optimizer, and salp swarm algorithm, are applied to the proposed model to detect geographically robust hotspots. Finally, the performances of the presented SI-based schemes and state-of-the-art cubic grid circle (CGC) algorithm have been compared. They are evaluated over the controlled synthetic datasets and the crime dataset of Chicago city for the year 2019. The obtained results indicate that the computational times required by the SI-based schemes are significantly less than the CGC algorithm. Also, the quality of hotspots detected by SI-based algorithms is either improved or at par with the CGC algorithm.

Background: The genus Quercus has a keystone role in the temperate forests in the northern hemisphere; thus this offers an interesting opportunity to use it as a model to know altitudinal species richness patterns which could be used in further studies and projects in biodiversity conservation. Questions: It is possible to detect an altitudinal gradient based on the genus Quercus distribution? What climatic variables are most important in the altitudinal distribution of the genus Quercus ? Study site: The physiographic province of Sierra Madre del Sur (SMS) located southwest of Mexico. Methods: Based on 3,267 herbarium registers of 61 species, a data matrix was created with the presence/absence of each species in altitudinal intervals of 100 m. Then a similarity matrix was obtained using the Sorensen-Dice index in the R software. Through a discriminant analysis, we evaluated for environmental differences among the altitudinal zones previously obtained through a cluster analysis. Results: We found three altitudinal zones, each one defined by exclusive species, and two important species turnover points. The species richness distribution showed a hump-shaped pattern along the altitudinal gradient. The overall model was highly significant, evidencing the existence of different temperature and precipitation regimes throughout the altitudinal distribution of oaks species in SMS. Conclusions: The altitudinal distribution of oak species in the SMS is not homogeneous and is restricted mainly due to differences in the precipitation and temperature regimes. The altitudinal distribution pattern found in this study could be explained considering ecological and historical factors.

A number of studies have revealed the effects of several meteorological factors on the concentration of ambient particulate matter (PM). However, the corresponding non-linear and lagged effects of those variables on PM concentration remain unclear. This study aimed to explore the effect of meteorological variables and fire hotspot counts on PM concentration in the northern part of Thailand using the two-stage approach. In the first stage, combination of log-linear regression model and distributed lag non-linear model was used to estimate province-specific effect of meteorological factors and fire hotspots on PM2.5 and PM10 adjusting by confounders. In the second stage, the multivariate meta-analysis was applied to pool province-specific estimate, and the results showed that the negative associations of temperature, relative humidity, wind speed, and rainfall with PM2.5 and PM10 were observed, while air pressure and fire hotspot was positively associated with PM. Moreover, the effects of temperature, relative humidity, wind speed, rainfall, and fire hotspot on PM2.5 and PM10 were lasted for 5–8 days, whereas those of air pressure were peaked at lag 7 days and become attenuated toward the null afterward. In conclusion, results from this study could contribute a better understanding on the effects of meteorological variables and fire hotspots on PM concentration and induce the development of more tailored air pollution mitigation strategies depending on weather conditions.

Spatially varying diesel locomotive fuel use and emission rates (FUERs) are needed to accurately quantify local emission hotspots and their health impacts. However, existing locomotive FUER data are typically not spatially resolved or representative of real-world locomotive operation. Therefore, existing data are of limited use in quantifying the spatial variability in real-world FUERs. The objectives of this work are to quantify spatial variability in locomotive FUERs and identify factors differentiating hotspots from non-hotspots. FUERs were measured based on real-world measurements conducted for the Piedmont passenger rail service using a portable emission measurement system. FUERs were quantified based on 0.25 mile track segments on the Piedmont route. Hotspots were defined as segments in the top quintile of segment-average FUERs. On average, hotspots contributed 40-50% to trip fuel use and emissions. Hotspots were typically associated with low-to-medium speed, and high acceleration and grade. In contrast, non-hotspots were associated with high speed, and low acceleration and grade. Hotspots were typically located near populated areas and, thus, may exacerbate air pollutant exposure. The method demonstrated here can be applied to other passenger train services to assess key trends in hotspot locations and factors that explain the occurrence of hotspots.

Objective: This study is aimed at interpreting geochemical and geophysical data of 4 locations in Gujarat, India to understand the subsurface geothermal hotspot locations. Methods: CG-5 gravimeter was used to collect the gravity data. Data corrections were done to obtain a complete Bouguer anomaly. The depth of the dense bodies was calculated using Euler deconvolution. Also, the geochemical classification of physiochemical properties of geothermal spring waters of the locations was evaluated to assess their possible applications. Findings: In the sample region, the complete Bouguer anomaly analysis ranges between 1.99 mGal-2.23 mGal. The Euler deconvolution produced depth solutions ranging from 100 to 450 meters, which were mostly found near gravity highs, and the presence of deep structures can be deduced. These deep structures are translated as dense intruding bodies trapped by an overlying cap rock. The Geochemical analysis was done of the four samples. Based on the results of various plots such as Ternary, Durov, Piper, Stiff, the waters are graded as cationic with Na+K and anionic with Cl+SO4. The sample waters indicate suitability for drinking and irrigation at some locations. Finding these hotspots and exploiting them is of importance for these areas which are dealing with the acute water crisis. Novelty: Euler deconvolution of gravity data was first time applied for subtle geothermal trap identification in Saurashtra and Cambay basins. It has been established through this study that surface manifestation of these subtle traps are the hot springs. Systematic geochemical characterization of the hot springs progressed the nascent geothermal energy research of India. Keywords: Bouguer anomaly; Heat source; Geothermal energy; Geochemical analysis; Hot spring; water analysis

Infrared small-target detection of a low signal-to-noise ratio (SNR) has been an important research hotspot. Small targets lack texture and detailed information; in addition, the background tends t...

The Galapagos Islands are a global hotspot of environmental change. However, despite their potentially major repercussions, little is known about current and expected changes in regional terrestrial climate variables and sea surface temperatures (SST). Here, by analysing existing meteorological observations and secondary datasets, we find that the Islands have warmed by about 0.6 °C since the early 1980s, while at the same time becoming drier. In fact, the onset of the wet season is currently delayed 20 days. This drying trend may reverse, however, given that future climate projections for the region suggest mean annual precipitation may increase between 20 and 70%. This would also be accompanied by more extreme wet and hot conditions. Further, we find that regional SST has increased by 1.2 °C over the last two decades. These changes will, in turn, translate into deterioration of marine ecosystems and coral, proliferation of invasive species, and damages to human water, food, and infrastructure systems. Future projections, however, may be overestimated due to the poor capacity of climatic models to capture Eastern-Pacific ENSO dynamics. Our findings emphasize the need to design resilient climate adaptation policies that will remain robust in the face of a wide range of uncertain and changing climatic futures.

El Nino-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) can reduce the amount of rainfall in Indonesia. The previous study found that ENSO and IOD derived from the OISST dataset have an association with hotspots in Indonesia, especially in southern Sumatra dan Kalimantan. But the correlation results are still too small, and the correlation strength between regions has not been analyzed. Therefore, this study quantifies the association of the estimated ENSO and IOD derived from the ERA5 dataset on hotspots in Indonesia based on a Heterogeneous Correlation Map (HCM) and analyzes the correlation strength between regions in Indonesia. We use a singular value decomposition method to quantify this HCM. Besides OISST, ERA5 is an estimation data often used for weather forecast analysis. Therefore, this study quantifies the association of the estimated ENSO and IOD derived from the ERA5 dataset on hotspots in Indonesia based on a Heterogeneous Correlation Map (HCM) and analyzes the correlation strength between regions in Indonesia. Based on variance explained and correlation strength, the hotspot in Indonesia is more sensitive to ENSO and IOD derived from ERA5 than OISST. Consequently, the ERA5 data more useful to statistical analysis that requiring a substantial correlation.

Elevated reactive nitrogen (Nr) deposition is a concern for alpine ecosystems, and dry NH3 deposition is a key contributor. Understanding how emission hotspots impact downwind ecosystems through dry NH3 deposition provides opportunities for effective mitigation. However, direct NH3 flux measurements with sufficient temporal resolution to quantify such events are rare. Here, we measured NH3 fluxes at Rocky Mountain National Park (RMNP) during two summers and analyzed transport events from upwind agricultural and urban sources in northeastern Colorado. We deployed open-path NH3 sensors on a mobile laboratory and an eddy covariance tower to measure NH3 concentrations and fluxes. Our spatial sampling illustrated an upslope event that transported NH3 emissions from the hotspot to RMNP. Observed NH3 deposition was significantly higher when backtrajectories passed through only the agricultural region (7.9 ng m–2 s–1) versus only the urban area (1.0 ng m–2 s–1) and both urban and agricultural areas (2.7 ng m–2 s–1). Cumulative NH3 fluxes were calculated using observed, bidirectional modeled, and gap-filled fluxes. More than 40% of the total dry NH3 deposition occurred when air masses were traced back to agricultural source regions. More generally, we identified that 10 (25) more national parks in the U.S. are within 100 (200) km of an NH3 hotspot, and more observations are needed to quantify the impacts of these hotspots on dry NH3 deposition in these regions.

The Galapagos Archipelago is the surface expression of an active hotspot or long-lived mantle plume. The Archipelago consists of a group of 13 main islands which are located in the eastern central Pacific Ocean about 1,000 km west of the northern edge of the South American continent, east of the East Pacific Rise and south of the Galapagos spreading center. Because of the large distance to the nearest continental land mass, Galapagos can be seen as an almost isolated sedimentary system. A provenance study conducted on samples collected from seventeen beaches on eleven islands, demonstrates that mineral grains and particles were derived from weathering of predominantly basaltic rocks and were transported within the islands, between the islands or inside the coastal area around the Archipelago. The exclusion of external sources allows advanced studies about erosion processes, transport pathways of particles and the accumulation of autochthonous sediments. The combined usage of optical particle size and shape analysis with RAMAN spectroscopy allows a successful spatial delimitation of host rocks and a reconstruction of transport pathways. The analyzed samples can be subdivided into three groups: 1) Type-A sediments: fine-grained and sampled on beaches of the oldest islands in the eastern part of Galapagos. The composition of volcanic minerals corresponds to the alkaline character of the basaltic source rocks. 2) Type-B: well sorted sediments characterized by medium-grained olivine, pyroxene, plagioclase and even a small amount of quartz grains. The islands of this group are located in the central region of the Archipelago. 3) Type-C samples: olivine and pyroxene are the predominant volcanic minerals. These samples indicate bimodal, coarse-grained size distributions and large proportions of pumice and are found in Floreana in the south and the youngest islands Isabela and Fernandina in the west of Galapagos.

A wave resource characterization was performed for the southern coast of Alaska based on a 32-year hindcast covering the period from 1979 to 2010. The characterization closely followed International Electrotechnical Commission (IEC) Technical Specifications. An unstructured-grid Simulating WAves Nearshore (SWAN) model, which had an approximate spatial resolution of 300 m within 30 km from the nearest shoreline, was developed. Extensive model validation and error characterization was performed. The model was found to perform well with an average absolute percent error of 8.6% in significant wave height, averaged over 18 buoys. Statistics for the six IEC wave resource parameters were calculated and aggregated at 20 km from shore to quantify the incident wave power and its variability at a regional scale. The southern coast of the Aleutian Archipelago was found to have the most available wave energy in the region. A nearshore resource assessment was performed by evaluating resource hotspots located 1 km from shore. More than 28% of the nearshore stations analyzed had an Optimum Hotspot Identifier value of at least 5 [kW/m] at diverse water depths, thereby positioning Alaska as a promising location for wave energy development.

Plant hotspot areas are the areas that are very rich in plant species diversity. These areas have a priority for conservation. To highlight the plant diversity for nature conservation purposes a case study in Al Baha region, Saudi Arabia is presented, in which the importance of the natural vegetation and flora of one of the hotspot areas of Saudi Arabia is evaluated through the explanation of its natural plant species. A survey study has been conducted in an area of 167.6 km2, a 97 sample each with 20X20 m were laid out covering the whole ecological zones of the study site. Data of flora, vegetation cover and topography were gathered from each sample site. The study revealed about 319 plant species belonging to 228 genera and 75 families. Two species were found endemic to Saudi Arabia, 14 were endemics to Arabian Peninsula, and five were regional endemics that are only found in East Africa and Arabian Peninsula, while 39 species are rare and endangered.

Deep-sea fishes have long captured our imagination with striking adaptations to life in the mysterious abyss, raising the possibility that this cold, dark ocean region may be a key hub for physiological and functional diversification. We explore this idea through an analysis of body shape evolution across ocean depth zones in over 3000 species of marine teleost fishes. We find that the deep ocean contains twice the body shape disparity of shallow waters, driven by elevated rates of evolution in traits associated with locomotion. Deep-sea fishes display more frequent adoption of forms suited to slow and periodic swimming, whereas shallow living species are concentrated around shapes conferring strong, sustained swimming capacity and manoeuvrability. Our results support long-standing impressions of the deep sea as an evolutionary hotspot for fish body shape evolution and highlight that factors like habitat complexity and ecological interactions are potential drivers of this adaptive diversification.

The existence of mantle plumes was first proposed in the 1970s to explain intra-plate, hotspot volcanism, yet owing to difficulties in resolving mantle upwellings with geophysical images and discrepancies in interpretations of geochemical and geochronological data, the origin, dynamics and composition of plumes and their links to plate tectonics are still contested. In this Review, we discuss progress in seismic imaging, mantle flow modelling, plate tectonic reconstructions and geochemical analyses that have led to a more detailed understanding of mantle plumes. Observations suggest plumes could be both thermal and chemical in nature, can attain complex and broad shapes, and that more than 18 plumes might be rooted in regions of the lowermost mantle. The case for a deep mantle origin is strengthened by the geochemistry of hotspot volcanoes that provide evidence for entrainment of deeply recycled subducted components, primordial mantle domains and, potentially, materials from Earth’s core. Deep mantle plumes often appear deflected by large-scale mantle flow, resulting in hotspot motions required to resolve past tectonic plate motions. Future research requires improvements in resolution of seismic tomography to better visualize deep mantle plume structures at smaller than 100-km scales. Concerted multi-proxy geochemical and dating efforts are also needed to better resolve spatiotemporal and chemical evolutions of long-lived mantle plumes. Mantle plumes are an integral aspect of Earth’s convection system, yet, difficulty in imaging mantle upwellings led to controversies surrounding their origin, dynamics and composition. This Review synthesizes geophysical, geodynamic and geochemical constraints on mantle plumes and their importance in the Earth system.

The acoustic black hole (ABH) structure has gradually become a research hotspot in recent years due to its ascendant capacity of vibration attenuation and energy accumulation. To further improve the performance of vibration and noise reduction, the ultra-low frequency broadband gap of a one-dimensional structure embedded ABHs with power-law material properties is investigated in this paper. Based on the Euler-Bernoulli theory, the Transfer Matrix Method (TMM) is used to establish the dynamic model of the dual power-law ABH (DP-ABH) beam. The band structure results obtained by TMM and the finite element method are compared with each other to verify the ultra-low broadband gap of the structure. Comparison with the traditional ABH show that the ultra-low frequency performance of the DP-ABH is due to the enhanced local resonator properties with reduction of dual power-law local stiffness. Parameter analysis served as a guide for optimization is carried out and a method of combining NSGA-II and TMM is applied to optimize the ABH section with full parameters, to consider a trade-off between lower bandgaps and higher stiffness. The investigation shows that the ultra-low broadband gaps of the periodic DP-ABHs structure, which meets adequate stiffness requirements, can be designed by optimized configuration.

Large igneous provinces (LIPs) are commonly associated with mass extinctions. However, the precise relations between LIPs and their impacts on biodiversity is enigmatic, given that they can be asynchronous. It has been proposed that the environmental impacts are primarily related to sill emplacement. Therefore, the structure of LIPs' magma storage system is critical because it dictates the occurrence and timing of mass extinction. We use surface-wave tomography to image the lithosphere under the Permian Emeishan large igneous province (ELIP) in southwestern China. We find a northeast-trending zone of high shear-wave velocity (Vs) and negative radial anisotropy (Vsv > Vsh; v and h are vertically and horizontally polarized S waves, respectively) in the crust and lithosphere. We rule out the possibilities of rifting or orogenesis to explain these seismic characteristics and interpret the seismic anomaly as a mafic-ultramafic, dike-dominated magma storage system of the ELIP. We further propose that the anomaly represents a hidden hotspot track that was emplaced before the ELIP eruption. A zone of higher velocity but less-negative radial anisotropy, on the hotspot track but to the northeast of the eruption center in the Panxi region, reflects an elevated proportion of sills emplaced at the incipient stage of the ELIP. Liberation of poisonous gases by the early sill intrusions explains why the mid-Capitanian global biota crisis preceded the peak ELIP eruption by 2–3 m.y.

To evaluate the mercury sources and its transportation mechanism from a global hotspot region (the Ganga Alluvial Plain, northern India), two sets of time-series samples of shallow groundwater (n = 31) and river water (n = 31) were collected in alternate days, from the Behta River Basin, in July and August 2019. The estimation of total dissolved mercury was performed by using the Flow Injection Atomic Absorption Spectroscopy-Mercury Hydride System. The mercury concentrations ranged high (> 1400 ng/L), in the three orders of magnitude, emphasizing the importance of mercury transportation, through the unconfined alluvial aquifer system, linked with the monsoon precipitation. In July, the accumulative intensity of monsoon precipitation favored the increasing mercury concentrations in the river water, as well as, in the groundwater. The infiltration of mercury contaminated water is the prominent hydrological process accountable for the peaked mercury concentration (above the World Health Organization’s drinking water standard of 1000 ng/L) in the river basin. In August, about 67% of the collected samples reported base-level mercury concentrations. Temporal variations of mercury concentration in the groundwater and the river water showed significantly higher values in July, than in August. These results illustrate the importance of the interaction between the monsoon precipitation, and anthropogenic mercury, in the river basin, for the riverine and groundwater mercury transportation as the fundamental hydraulic control. The present study underscores the significance of monsoon precipitation on the groundwater transportation of global mercury cycling by the Ganga River.

Thermography is a non-invasive and promising clinical method widely being used in screening of breast cancer. Breast thermal images show the heat distribution, depicting the manifestation of cancerous lesions with hot regions. Accurate segmentation of these hotspots is very vital in determining the severity of the lesions, localization and treatment regimen. In this work, color segmentation based on superpixel scheme is proposed to extract the hotspots from breast thermal images. Here, we employ the most recently proposed Gaussian mixture model superpixels, featuring semantically defined boundaries to segment the hotspots with ease. The proposed system tested with a standard dataset exhibits best performance, evaluated with various statistical metrics. It demonstrates very high segmentation accuracy around 99.84%. Visual analyses and statistical comparisons with ground truth images establish the superiority of proposed system over existing methods. Proposed method could increase diagnostic accuracies of breast cancer and increase the abnormality detection in early stage.

Currently, there is no precise information on the degree of transformation of Tropical Andes hotspot landscape and native ecosystems due to the intensification of agricultural and urban land-use. Proper knowledge of these changes would provide crucial information for planning conservation strategies. We evaluated the impact of the intensification of agricultural and urban land-use on the Inter-Andean Dry Forest and Tropical Montane Forest, both of which are categorized as Critically Endangered, and the state of the landscape in the High Rio Guayllabamba watershed, Ecuador, during the periods 1991–2005 and 2005–2017. The evaluation was carried out using Landsat satellite images of 30 x 30 m pixels and landscape metrics. We found an advanced state of landscape transformation. Since the 1990s, the loss of both ecosystems was largely caused by the conversion of forest to agriculture, resulting in substantial changes in the spatial configuration of these ecosystems. From 1991 to 2017, 19.8 % and 16.1 % of Inter-Andean Dry Forest and Tropical Montane Forest respectively, were converted to agriculture. The loss of Inter-Andean Dry Forest was 28 % and the number of forest patches increased by more than 150%. The loss of Tropical Montane Forest was 16.5 % and the number of forest patches increased by more than 300 %. The largest loss and fragmentation of forest cover occurred from 1991 to 2005. We suggested planning landscape-scale conservation, using the patch-corridor-matrix model. This model is appropriate given the current configuration of the landscape studied, with Inter-Andean Dry Forest and Tropical Montane Forest restricted to small patches sparsely distributed across the landscape.

The Alps are an important hotspot of species diversity and endemism, as well as a presumed glacial refugium of several species’ groups including land snails. The recent ranges of Alpine endemics are well known, but their fluctuations during the postglacial period mirroring local climate changes are understudied. By analysing five Late Glacial and Holocene mollusc successions from two areas in the southernmost part of the Bohemian Massif (Czech Republic) situated about 100 km north of the Alps, we reveal details of these fluctuations. The Alpine endemic rocky dweller Chilostoma achates had reached the southern part of the Bohemian Massif already in the Late Glacial and disappeared in the Mid-Holocene canopy forest optimum. On the contrary, the northern boundaries of Alpine canopy forest epigeic snails extended further north than today at the turn of the Middle and Late-Holocene, pointing to a more favourable forest microclimate. The earliest known occurrences of several temperate canopy forest central European species, especially Causa holosericea and Discus perspectivus, imply the role of different areas in the Alps as their glacial refugia.