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A conceptual model based on the dynamic interaction between fire, the fuel bed and the surrounding flow to explain the non-monotonic or intermittent behaviour of fires is proposed. According to the model, even in nominally permanent and uniform boundary conditions, the fire-induced flow modifies the geometry of the flame and its rate of spread. After an initial acceleration, there is a reduction in the rate of spread followed by one or more cycles of growth. Carefully controlled experiments of fires in slopes and canyons show that the evolution of fire properties, namely flame angle and rate of spread, have high-frequency oscillations superimposed on the low-frequency fire growth cycle described above.

The aim of the comment is to address the misrepresentations of our work on the Neolithic transitions that are found in a recent article by Manen and coauthors in Radiocarbon. There are a fair number of them as indicated in the comment. The purpose of the comment is (1) to set the record straight, (2) to clarify several misconceptions that have persisted in the literature for some time, and (3) to comment briefly on the convergence between our own recent regional modeling of the spread of early farming along the north coast of the West Mediterranean and the position currently held by Manen and coauthors.

Dataset for submitted paper: Fences foil foragers from fueling forest fires: Can large herbivores alter fire behaviour in coastal eucalypt forests? Contents are R script with relevant excel spreadsheets + appendix

Virus corona telah menjadi pandemi dunia dan sudah menyebar hampir ke seluruh dunia, termasuk Indonesia. Banyak dampak negatif yang diakibatkan oleh penyebaran COVID-19 di Indonesia, sehingga pemerintah mengambil tindakan vaksinasi agar dapat menekan tingkat penyebaran COVID-19. Tanggapan dari masyarakat terhadap tindakan vaksinasi cukup beragam di media sosial Twitter, ada yang mendukung dan ada juga yang tidak setuju. Makalah ini bertujuan untuk mengetahui sentimen masyarakat terhadap tindakan vaksinasi. Data yang digunakan sebanyak 845 tweet, dengan menggunakan dua kata kunci, yaitu “vaksinmerahputih” dan “vaksinsinovac”. Data kemudian dibagi menjadi 253 data latih dan 592 data uji. Klasifikasi dilakukan menggunakan metode SVM dan Naïve Bayes. Hasil klasifikasi dari metode Naïve Bayes mendapatkan rata-rata akurasi 85,59%, sedangkan SMV sebesar 84,41%. Hasil sentimen pada metode Naïve Bayes dengan kata kunci “vaksinsinovac” mendapatkan sentimen positif 66% dan negatif 34%, sedangkan “vaksinmerahputih” memperoleh sentimen positif 89% dan negatif 11%. Metode SVM dengan kata kunci “vaksinsinovac” mendapatkan sentimen positif 96% dan negatif 4%, sedangkan “vaksinmerahputih” mendapatkan sentimen positif 98% dan negatif 2%. Dapat disimpulkan bahwa hasil sentimen masyarakat terhadap tindakan vaksinasi mendapat respons yang positif.

Coronavirus 2019 or Covid-19 is a major problem for health, and it is a global pandemic that has to be controlled. Covid-19 spread so fast to 196 countries, including Indonesia. The government has to study the pattern and predict its spread in order to make policies that will be implemented to tackle the spread of some of the existing data. Therefore this research was conducted as a precautionary measure against the Covid-19 pandemic by predicting the rate of spread of Covid-19. The application of the machine learning method by combining the k-means clustering algorithm in determining the cluster, k-nearest neighbor for prediction and Iterative Dichotomiser (ID3) for mapping patterns is expected to be able to predict the level of spread of Covid-19 in Indonesia with an accuracy rate of 90%. Keywords – machine learning, k-means, k-nearest neighbor, Iterative Dichotomiser

Rangeland scientists have long relied on thermocouples for measuring temperature, especially in agris—in the field, under the extreme conditions of wildland fire. But the electronics required to sense and record thermocouple data remain expensive to both purchase and protect from exposure to heat and flames. Open-source, do-it-yourself (DIY) electronics platforms such as Arduino are increasingly popular among ecologists, and have been shown to perform as well as proprietary commercial systems when recording thermocouple data. The FeatherFlame system is a reliable, low-cost solution to sampling wildland fire, ranging from US$240–490 for 1–6 thermocouple sensors, including all fire protection equipment. The low cost and multi-sensor capacity facilitates spatial replication, which allows fire ecologists to measure and report meaningful data on rate of spread and calculate fire intensity.

To explore the differences in hoarding strategies of rodents for different seeds in various seasons, we labeled and released the seeds of Pinus koraiensis, Corylus mandshurica, Quercus mongolica and Prunus sibirica in temperate forests of Northeast China and investigated the fate of the seeds in spring and autumn. The analysis showed that the hoarding strategies of the rodents varied substantially between seasons. The seeds were consumed faster in the spring than in the autumn. More than 50% of the seeds in the two seasons were consumed by the 16th day. It took 36 days to consume 75% of the seeds in the spring and 44 days in the autumn. The rate of consumption of the seeds in the spring was greater than in the autumn, and the rate of spread of the seeds was greater in the autumn. The distances of removal for the consumption and dispersal of seeds in the spring (3.26 ± 3.21 m and 4.15 ± 3.52 m, respectively) were both shorter than those in the autumn (3.74 ± 3.41 m and 4.87 ± 3.94 m, respectively). In addition, the fate of different seeds varied significantly owing to differences in hoarding strategies. The seeds of the three preferred species, P. koraiensis, C. mandshurica, and Q. mongolica, were quickly consumed. More than 90% of the seeds of these species were consumed. Only 21% of Pr. sibirica seeds were slowly consumed, and the two seasons had the same seed consumption rate patterns: the consumption rate of P. koraiensis seeds was the highest, followed by C. mandshurica, then Q. mongolica, and finally Pr. sibirica. The median removal times of the two seasons were different, but the rules were the same: P. koraiensis was the shortest, followed by C. mandshurica, and the third was Q. mongolica. In both seasons, the most predated in situ seeds were those of P. koraiensis; the most hoarded seeds were those of C. mandshurica, and the most unconsumed seeds were those of Pr. sibirica.

Összefoglaló. Bevezetés: A COVID–19-járvány az egész világon elterjedt. A járvány Európában való első megjelenése során megfigyelhető volt, hogy a terjedés mértéke kisebb azokban az országokban, ahol a tuberkulózis elleni védekezésül kiterjedt BCG-vakcinációt végeznek. Célkitűzés: A jelen munkában olyan összefüggéseket igyekeztünk feltárni, amelyek befolyásolták a járványterjedés paramétereit, különös figyelemmel a BCG-vakcinációs gyakorlatra. Módszerek: A világ összes olyan országára vonatkozóan, ahol megfelelő minőségű statisztikai adatok álltak rendelkezésünkre, vizsgáltuk a járvány terjedésének első hullámát. A mozgóátlagolt járványgörbéken elemeztük a járvány időtartamát, a tetőzés mértékét, a fertőzöttek és a halálesetek egymillió lakosra vetített számát. Figyelembe vettük az országok gazdasági mutatóit (GDP, légi forgalom, a tengeri hajózás mértéke). Statisztikai analízis: A vizsgált paraméterek nem mutattak normális eloszlást, így nemparaméteres próbákkal (rangkorreláció, Kruskal–Wallis ANOVA) statisztikai kapcsolatot kerestünk a járványterjedés mértéke, a BCG-vakcináció és más paraméterek között. Eredmények: A járvány gyorsan elterjedt a világon, de mégis, február első három hetében a terjedésben egy szünet volt megfigyelhető. A járványhullám Európában nagyjából egyszerre ért véget. A járvány által leginkább azok az országok érintettek, ahol nem alkalmaztak rendszeres BCG-vakcinációt, bár a képet bonyolítja, hogy ezek az országok gazdaságilag többnyire fejlettek. A halálozási rátában nem mutatkozott ilyen különbség. Következtetés: Statisztikailag igazolható tény, hogy a vakcinációt végző országokból az első hullám alatt kevesebb fertőzöttet jelentettek; az ok-okozati összefüggés bizonytalan, hiszen az országok múltja, szokásai, társadalmi berendezkedése, gazdasági fejlettsége nem azonos. Eredményeink alátámasztják az összehasonlító kontaktkutatás fontosságát annak tisztázására, hogy a BCG-oltás hogyan befolyásolja az emberek vírussal szembeni érzékenységét, valamint a vírus terjesztésének, továbbadásának képességét. Orv Hetil. 2021; 162(4): 123–134. Summary. Introduction: The new type of coronavirus (SARS-CoV-2) epidemic is widespread throughout the world. During the outbreak of the pandemic in Europe it was revealed that the rate of spread was lower in countries where extensive BCG vaccination is used to protect against tuberculosis. Objective: In the present work, we sought to explore relationships that influenced epidemic spreading parameters, with particular reference to BCG vaccination practice. Methods: We examined the first wave of the spread of the epidemic for all countries in the world where adequate quality statistics were available. We analyzed the duration of the epidemic, the extent of the peak, the number of infected people, and the number of deaths per million inhabitants with the moving average of epidemic curves. We took into account the economic indicators of the countries (GDP, air traffic and extent of maritime shipping). Statistical analysis: The examined parameters did not show a normal distribution, so we looked for a statistical relationship with non-parametric tests (rank correlation, Kruskal–Wallis ANOVA) between the extents of epidemic spread, BCG vaccination and other parameters. Results: The epidemic spread rapidly around the world, but still, in the first three weeks of February, there was a pause in the spread. The first wave of epidemics ended roughly at the same time in Europe. Those countries are the most affected by the epidemic where regular BCG vaccination has not been used, although the picture is complicated by the fact that these countries are mostly economically developed. There was no such difference observable in the mortality rate. Conclusion: Although this work clearly demonstrates that during the first wave of the pandemic, fewer infections were reported worldwide in countries where BCG vaccination is obligatory, however, the causal relationship is uncertain, as the countries’ past, customs, social organization and economic development are different. Our results support the necessity of comparative contact tracing to clarify how BCG vaccination affects people’s susceptibility to this new type of coronavirus as well as their ability to spread and transmit the virus. Orv Hetil. 2021; 162(4): 123–134.

A new instrument to quantify firebrand dynamics during fires with particular focus on those associated with the Wildland-Urban Interface (WUI) has been developed. During WUI fires, firebrands can ignite spot fires, which can rapidly increase the rate of spread (ROS) of the fire, provide a mechanism by which the fire can pass over firebreaks and are the leading cause of structure ignitions. Despite this key role in driving wildfire dynamics and hazards, difficulties in collecting firebrands in the field and preserving their physical condition (e.g. dimensions and temperature) have limited the development of knowledge of firebrand dynamics. In this work we present a new, field-deployable diagnostic tool, an emberometer, designed to provide measurement of firebrand fluxes and information on both the geometry and the thermal conditions of firebrands immediately before deposition by combining a visual and infrared camera. A series of laboratory experiments were conducted to calibrate and validate the developed imaging techniques. The emberometer was then deployed in the field to explore firebrand fluxes and particle conditions for a range of fire intensities in natural pine forest environments. In addition to firebrand particle characterization, field observations with the emberometer enabled detailed time history of deposition (i.e. firebrand flux) relative to concurrent in situ fire behaviour observations. We highlight that deposition was characterised by intense, short duration “showers” that can be reasonably associated to spikes in the average fire line intensity. The results presented illustrate the potential use of an emberometer in studying firebrand and spot fire dynamics.

The aim of this study is to trace the rate of spread of the COVID-19 pandemic and predict the end of the spread of COVID-19 in Bahrain Though the term ‘Corona virus’ hit the headlines from 31 December 2019 and gradually started spreading in leaps and bounds right from January 2020 in Wuhan, China, Bahrain started witnessing cases only in February 2020 With a gradual increase in the number of cases and the number of deaths, the people in Bahrain are deprived of leading a normal routine anymore With the suspension of educational institutes, imposed restrictions on businesses, and the enforced ‘work from home’ on the working class, the COVID-19 has played havoc in the lives of the people residing in Bahrain Extracting the data from web site of Worldometers about the active cases, death cases and recovery cases in Bahrain, and devising a mathematical model, this study traces the spread of the virus for a specified period from 1 March 2020 to 20 September 2020 cumulatively and attempts to predict the rate of spread of the virus using polynomial regression method The proposed prediction of the end of COVID-19 disease in Bahrain will help Bahrain prepare for the post-pandemic scenario keeping in mind the well-being of its residents © 2020, Research Publication All rights reserved

SummaryDrug resistance mutations tend to disrupt key physiological processes, and therefore carry a fitness cost. The size of these fitness costs is a central determinant of the rate of spread of these mutations in natural populations so are important to quantify. Head-to-head competition assays provide a standard approach to measuring differential fitness, and have been used extensively for malaria parasites. These assays typically use standardized culture media, containing RPMI 1640, which has a 1.4 to 5.5-fold (mean: 2.6-fold) higher concentration of amino acids than human blood. In this rich media we predict that fitness costs will be underestimated because resource competition is weak. We tested this prediction using an artemisinin sensitive parasite edited to contain kelch-C580Y or R561H mutations conferring resistance to artemisinin or synonymous control mutations. We examined the impact of these single amino acid mutations on fitness, using replicated head-to head competition experiments conducted in media containing (i) normal RPMI, (ii) modified RPMI with reduced amino acid concentration, (iii) RPMI containing only isoleucine, or (iv) 3-fold diluted RPMI. We found a significant 1.3 to 1.4-fold increase in fitness costs measured in modified and isoleucine-only media relative to normal media, while fitness costs were 2.5-fold higher in diluted media. We conclude that fitness costs are strongly affected by media composition and will be significantly underestimated in normal RPMI. Elevated fitness costs in nature will limit spread of ART-resistance but will also promote evolution of compensatory mutations that restore fitness, and can be exploited to maximize selection in laboratory experiments.

Aim of the study: The objective of this study is to calculate fireline intensity using remote sensing and geographic information systems, to investigate relationship between fireline intensity and VIIRS active fire data, and to develop a practical fireline intensity estimation model.Material and methods: The Visible Infrared Imaging Radiometer Suite (VIIRS) active fire/hotspot data provided by Suomi National Polar Orbiting Partnership (S-NPP) and National Oceanic and Atmospheric Administration (NOAA-20) satellites were used to estimate the rate of fire spread. Fuel consumption was estimated using Sentinel-2 images, stand type maps and surface and available crown fuel loading models for Turkish red pine (Pinus brutia Ten.). The fireline intensity was then calculated using Byram’s (1959) fireline intensity equation.Main results: The results indicated that the number of VIIRS active fire data was well correlated with fireline intensity, rate of fire spread and fuel consumption. The calculated fireline intensity ranged between 175.0 and 47597.2 kW/m with an average value of 9280.4 kW/m. The number of VIIRS active fire data alone explained 72% of the variation in fireline intensity.Highlights: Satellite based products can be effectively used to calculate fireline intensity through estimating rate of fire spread and fuel consumption easily and effectively in burned areas., Çalışmanın amacı: Bu çalışmanın amacı, uzaktan algılama ve coğrafi bilgi sistemlerini kullanarak yangın şiddetini hesaplamak, yangın şiddeti ile VIIRS aktif yangın verileri arasındaki ilişkiyi araştırmak ve pratik olarak kullanılabilecek bir yangın şiddeti tahmin modeli geliştirmektir.Materyal ve yöntem: Yangın yayılma oranını tahmin etmek için Suomi Ulusal Kutup Yörünge Ortaklığı (S-NPP) ve Amerikan Ulusal Okyanus ve Atmosfer Dairesi (NOAA-20) uyduları tarafından sağlanan Görünür Kızılötesi Görüntüleme Radyometre Sensöründen (VIIRS) gelen aktif yangın/sıcak nokta verileri kullanılmıştır. Yanıcı madde tüketimini tahmin etmek için Sentinel-2 görüntüleri, meşcere tipi haritaları ve Kızılçam (Pinus brutia Ten.) için geliştirilmiş ölü örtü ve tepe yanıcı madde miktarı tahmin modelleri kullanılmıştır. Yangın şiddeti değerleri Byram (1959) tarafından geliştirilen denklemle hesaplanmıştır.Temel sonuçlar: VIIRS aktif yangın verileri ile yangın şiddeti, yangın yayılma oranı ve yanıcı madde tüketimi arasında anlamlı pozitif korelasyon elde edilmiştir Yangında hesaplanan yangın şiddeti 175.0 ila 47597.2 kW/m arasında değişmiş, ortalama 9280.4 kW/m olarak hesaplanmıştır. Tek başına VIIRS aktif yangın veri sayısı ile yangın şiddetindeki değişimin %72'sini açıklanabilmiştir. Araştırma vurguları: Uydu tabanlı ürünler, yanan alanlarda yangının yayılma oranı ve yanıcı madde tüketiminin kolay ve etkin bir şekilde tahmin edilmesi yoluyla, yangın şiddetinin hesaplanmasında kullanılabilir.

اعترفت منظمة الصحة العالمية بأن وباء کورونا المستجد (COVID-19) هو جائحة عالمية وبذلک اعتبر هذا الاعتراف واقعة مادية توافرت معها شروط الظرف الاستثنائي من حيث توافر الخطر الجسيم الحال الذي سبب تهديدا للنظام العام الصحي في دولة الکويت مما اقتضت المصلحة العامة في منع انتشار الوباء. ويعد مجلس الوزراء الکويتي هو السلطة المختصة في إصدار التدابير العامة التي تتخذ عدة صور في تقييدها لنشاط الأفراد کالحظر والإذن المسبق والإخطار وتنظيم النشاط. وهي تدابير تؤثر بدورها على بعض الحقوق والحريات لا سيما حرية التنقل وحق التجمع على الرغم من أن قرارات حظر التجوال الکلي والجزئي للسکان کانت مدد متفاوتة وفق ما تقتضيه نسبة حالات الإصابة بالفيروس. وخلصت الدراسة إلى وجوب أن ترتبط القرارات الصادرة بالتدابير العامة بالتناسب مع درجة الخطر الناجم عن انتشار فيروس COVID-19 وضرورة أن تکون تلک التدابير متناسبة بشکل صارم مع المخاطر الصحية التي ينطوي عليها ومناسبة لظروف الزمان والمکان مع عدم المبالغة المستمرة للتهديد الصحي لوباء COVID-19 حتى لا تکون مدعاة لوضع المزيد من القيود على الحريات والحقوق الشخصية. The World Health Organization has recognized that the new Corona epidemic (COVID-19) is a global pandemic, a material event, an exceptional circumstance, and an unexpected serious danger that has caused a threat to the public health system in Kuwait, which necessitated the public interest to prevent the spread of the epidemic. The Kuwaiti Cabinet is the competent authority to issue general measures that restrict freedoms such as prohibition, prior authorization, notification, and regulation of activity. Restricting the right to public meetings and freedom of movement through curfew decisions for the population with the increasing rate of spread of the virus. The study concluded that general measures should be correlated in proportion to the degree of risk resulting from the spread of the COVID-19 virus and strictly proportional to health risks and conditions of time and place, while not exaggerating the continuous health threat of the COVID-19 epidemic in order not to be a cause for placing more restrictions on freedoms and personal rights.

Garden loosestrife (Lysimachia vulgaris L.), is an invasive wetland plant that is subject to management in King County, WA, USA. Large-scale management efforts are generally conducted using herbicides. In this case study, we analyzed 17 yr of monitoring and treatment data in four riparian areas in King County to estimate the rate of spread of L. vulgaris and the efficacy of herbicidal treatments against L. vulgaris populations. In each area, herbicide treatments were applied annually. In three of the areas, the area infested with L. vulgaris did not change over time, while in the fourth area populations of L. vulgaris were spreading at a rate of 0.79 m2 yr−1. There were a greater number of sampled locations infested with L. vulgaris over the 17-yr period, and because populations were either not spreading or spreading slowly, it is possible that populations were becoming more fragmented. There was no relationship between the percentage of the infested area treated with herbicides and the area infested in the following year. However, there was a negative relationship between the area treated and the percent change in the invaded area; specifically, in years when L. vulgaris did not retract over the 17-yr study period.

Respiratory infections are very common and highly contagious. Respiratory infectious diseases affect not only the person infected but also the family members and the society. As medical sciences advance, several diseases have been conquered; however, the impact of novel infectious diseases on the society is enormous. As the clinical presentation of respiratory infections is similar regardless of the pathogen, the causative agent is not distinguishable by symptoms alone. Moreover, it is difficult to develop a cure because of the various viral mutations. Various respiratory infectious diseases ranging from influenza, which threaten the health of mankind globally, to the coronavirus disease 2019, which resulted in a pandemic, exist. Contrary to human expectations that development in health care and improvement in hygiene will conquer infectious diseases, humankind's health and social systems are threatened by novel infectious diseases. Owing to the development of transport and trading activity, the rate of spread of new infectious diseases is increasing. As respiratory infections can threaten the members of the global community at any time, investigations on preventing the transmission of these diseases as well as development of effective antivirals and vaccines are of utmost importance and require a worldwide effort.

Objective: This study aims to forecast the number of deaths and cases in Turkey 150 days after (6 August 2020) the first occurrence of COVID-19 in Turkey. The data used is from 10 March 2020 (the first day has seen of COVID-19 in Turkey) to 15 June 2020 and includes people of all ages from all provinces of Turkey. Material and Method: The relationship between cases, deaths, patients in intensive care units, intubated patients, and recovered patients, which are observations of COVID-19, was examined with a correlation matrix. Afterward, the ARIMA (0,2,4) model to forecast the number of COVID-19 cases in Turkey and the ARIMA(0,3,1) model to forecast the number of COVID-19 deaths in Turkey were established. Result: COVID-19 cases were forecasted that there may be 266.692 cases in Turkey on 6 August in the 1st model. Subsequently, a similar forecast has been made on COVID-19 deaths in Turkey on 6 August in the 2nd model. COVID-19 deaths were forecasted that there may be 5718. The p-values of these parameters of models were observed statistically significant (p

© 2020 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made., Objective: To investigate disease spread in amyotrophic lateral sclerosis (ALS), and determine the influence of lower (LMN) and upper motor neuron (UMN) involvement. Methods: We assessed disease spread in ALS in 1376 consecutively studied patients, from five European centers, applying an agreed proforma to assess LMN and UMN signs. We defined the pattern of disease onset and progression from predominant UMN or lower motor neuron (LMN) dysfunction in bulbar, upper limbs, lower limbs, and thoracic regions Non-linear regression analysis was applied to fit the data to a model that described the relation between two random variables, graphically represented by an inverse exponential curve. We analyzed the probability, rate of spread, and both combined (area under the curve). Results: We found that progression was more likely and quicker to or from the region of onset to close spinal regions. When the disease had a limb onset, bulbar motor neurons were more resistant. Furthermore, in the same time frame more patients progressed from bulbar to lower limbs than vice-versa, whether predominantly UMN or LMN involvement. Patients with initial thoracic involvement had a higher probability for rapid change. The presence of predominant UMN signs was associated with a faster caudal progression. Interpretation: Contiguous progression was leading pattern, and predominant UMN involvement is important in shortening the time for cranial-caudal spread. Our results can best be fitted to a model of independent LMN and UMN degeneration, with regional progression of LMN degeneration mostly by contiguity. UMN lesion causes an acceleration of rostral-caudal LMN loss., This is an EU Joint Programme - Neurodegenerative Disease Research (JPND) project. The project is supported through national funding organizations under the aegis of JPND - www.jpnd.eu. This project was also partially supported by FCT funding to Neuroclinomics2 (PTDC/EEI-SII/1937/2014).

A learning-based wildfire spread model was developed in this study to predict short-term wildfire spread. Real-time rate of spread (RoS) measurement was first conducted by calculating normal movements of fire fronts. Subsequently, machine learning was employed to correlate the local RoS and environmental parameters and predict the RoS in the unburnt area. After that, a narrow-band level-set method was utilized to simulate the evolution of fire front. RoS measurement, machine learning, and level-set method were individually verified with numerically generated fire fronts, and applied in a real scale shrubland fire scenario. Results show that the proposed learning-based method is capable of predicting short-term fire spread without employing an empirical RoS model, which is beneficial for modeling spreading of a real wildfire.

Pandemics have had very important consequences in human history. Lots of people lost their lives and countries have been intensively affected in terms of socioeconomic problems. Unfortunately, avoidance of pandemics and limiting the spread are still currently not always possible. Maybe the most important factor for this is the increasing frequency of traveling. Increasing airline traveling rate also increases the rate of spread. Global organizations like the World Health Organization and United Nations are trying to play a supreme role over the countries. Pandemics do not have borders; therefore, efforts should be given globally, definition of pandemic should be established as soon as possible, and protective measures should be shared with countries. If these are not done, severe health consequences and serious economic problems are inevitable.

This work investigates the fire line evolution in canyon fire spread by analytical and experimental means. The purpose is to understand the mechanism of fire spread acceleration associated with eruptive fire in canyon terrain. A symmetrical model canyon is used for experiments, and in each test the fire is initiated by a point ignition using dead pine needles as the fuels. By experimental observations and data, three distinct types of fire line contour are identified under different central slope angles (the angle between the canyon centerline and the horizontal ground), resulting in different variation modes of rate of spread along the canyon centerline. It is found that the trace of fire head deviates from the line of maximum slope for non-zero central slope angles, and such a deviation increases with increasing central slope angle. The fire spread acceleration associated with eruptive fire occurs when the central slope angle reaches a certain critical value. Experimental data confirm that under higher slope conditions, the significant interaction between the two lateral flame fronts induces marked convective heating ahead of the flame front, which is inferred to be the potential mechanisms of eruptive fire in canyon topography. A model analysis further elucidates how the deflection of the trace of fire head, induced by the fire interaction effect, influences the acceleration of fire spread under higher slope conditions.

Background: In the early phases of the 2019 novel coronavirus (COVID-19) pandemic, health system leaders faced the urgent task of translating the unknown into forecasting models for hospital capacity. Our study objective was to demonstrate the application of a practical, locally informed model to estimate the hospital capacity needed even though the community COVID-19 caseload was unknown. Methods: We developed a susceptible-infected-recovered (SIR) model that was adopted from the University of Pennsylvania COVID-19 Hospital Impact Model for Epidemics and employed at 8 hospitals within Ochsner Health, the largest integrated delivery system in Louisiana, between March 16 and April 15, 2020. Intensive care unit (ICU) admissions of cases in the New Orleans area were used to estimate the community case load when testing was delayed. Results: Initially, the observed ICU census trended near R0=2.0, whereas the ventilator census trended between R0=2.0 and 3.0. After implementing social distancing, both the ICU and ventilator capacity trended toward R0=1.3, while non-ICU medical/surgical beds trended toward R0=1.5. The model accurately predicted peak ICU (n=250) and hospital bed (n=487) usage by April 6, 2020. In response to model trends, Ochsner added 130 ICU beds across its hospitals by opening a new ICU and converting operating rooms and parts of emergency departments to ICU beds. Conclusion: When disease testing is limited or results are delayed, ICU admissions data can inform SIR models of the rate of spread of COVID-19 in a community. Our model used various R0 plots to demonstrate an array of scenarios to guide planning for hospital and political leaders.

Fuel break effectiveness in wildland-urban interface (WUI) is not well understood during downslope wind-driven fires even though various fuel treatments are conducted across the western United States. The aim of this paper is to examine the efficacy of WUI fuel breaks under the influence of strong winds and dry fuels, using the 2018 Camp Fire as a case study. The operational fire growth model Prometheus was used to show: (1) downstream impacts of 200 m and 400 m wide WUI fuel breaks on fire behavior and evacuation time gain; (2) how the downstream fire behavior was affected by the width and fuel conditions of the WUI fuel breaks; and (3) the impacts of background wind speeds on the efficacy of WUI fuel breaks. Our results indicate that WUI fuel breaks may slow wildfire spread rates by dispersing the primary advancing fire front into multiple fronts of lower intensity on the downstream edge of the fuel break. However, fuel break width mattered. We found that the lateral fire spread and burned area were reduced downstream of the 400 m wide WUI fuel break more effectively than the 200 m fuel break. Further sensitivity tests showed that wind speed at the time of ignition influenced fire behavior and efficacy of management interventions.

This dataset contains KML files for wildfires detected from VIIRS across northwestern Europe from 2012 to 2022. Each file contains the fire progression at each satellite overpass. These files were used to detect the rate of spread for each wildfire event to characterize the fire behavior in temperate northwest Europe, a region with limited fire history.

COVID-19 or Novel Coronavirus disease is not only creating a pandemic but also created another kind of problem, initiating a group of wastes, which is also called as COVID-19 waste. COVID-19 waste includes the mask, hand gloves, sanitizer bottles, Personal Protective Equipment (PPE) kits, syringes used to vaccinate people, etc. These wastes are now polluting every continent and ocean. Improper disposal of such wastes may increase the rate of spread of contamination. In this regard, we decided to build up a detection model, which will be able to detect some of the COVID-19 wastes. We considered masks, hand gloves, and syringes as the initial wastes to get detected. We collected the dataset manually, annotated the images with these three classes, then trained different CNN models to compare the accuracies of the models for our dataset. We got the best model to be EfficientDet D0, which gives a mean average precision of 0.82. Further, we have also developed a UI to deploy the model, where general users can upload the images and can detect the wastes, controlling the threshold. This article is protected by copyright. All rights reserved.

Most wildland and prescribed fire spread occurs through ground fuels, and the rate of spread (RoS) in such environments is often summarized with empirical models that assume uniform environmental conditions and produce a unique RoS. On the other hand, representing the effects of local, small-scale variations of fuel and wind experienced in the field is challenging and, for landscape-scale models, impractical. Moreover, the level of uncertainty associated with characterizing RoS and flame dynamics in the presence of turbulent flow demonstrates the need for further understanding of fire dynamics at small scales in realistic settings. This work describes adapted computer vision techniques used to form fine-scale measurements of the spatially and temporally varying RoS in a natural setting. These algorithms are applied to infrared and visible images of a small-scale prescribed burn of a quasi-homogeneous pine needle bed under stationary wind conditions. A large number of distinct fire front displacements are then used statistically to analyze the fire spread. We find that the fine-scale forward RoS is characterized by an exponential distribution, suggesting a model for fire spread as a random process at this scale.

Fire behavior is well described by a fire’s direction, rate of spread, and its energy release rate. Fire intensity as defined by Byram (1959) is the most commonly used term describing fire behavior in the wildfire community. It is, however, difficult to observe from space. Here, we assess fire spread and fire radiative power using infrared sensors with different spatial, spectral and temporal resolutions. The sensors used offer either high spatial resolution (Sentinel-2) for fire detection, but a low temporal resolution, moderate spatial resolution and daily observations (VIIRS), and high temporal resolution with low spatial resolution and fire radiative power retrievals (Meteosat SEVIRI). We extracted fire fronts from Sentinel-2 (using the shortwave infrared bands) and use the available fire products for S-NPP VIIRS and Meteosat SEVIRI. Rate of spread was analyzed by measuring the displacement of fire fronts between the mid-morning Sentinel-2 overpasses and the early afternoon VIIRS overpasses. We retrieved FRP from 15-min Meteosat SEVIRI observations and estimated total fire radiative energy release over the observed fire fronts. This was then converted to total fuel consumption, and, by making use of Sentinel-2-derived burned area, to fuel consumption per unit area. Using rate of spread and fuel consumption per unit area, Byram’s fire intensity could be derived. We tested this approach on a small number of fires in a frequently burning West African savanna landscape. Comparison to field experiments in the area showed similar numbers between field observations and remote-sensing-derived estimates. To the authors’ knowledge, this is the first direct estimate of Byram’s fire intensity from spaceborne remote sensing data. Shortcomings of the presented approach, foundations of an error budget, and potential further development, also considering upcoming sensor systems, are discussed.

Spread F is an ionospheric phenomenon which has been reported and analyzed extensively over equatorial regions. It has also been investigated over midlatitude regions, mostly over the Southern Hemisphere. Over midlatitudes it has, been correlated with geomagnetic activity, travelling ionospheric disturbances (TIDs) and F region uplifts, with Perkins instability proposed as the primary seeding mechanism. The present study deals with the diurnal and seasonal occurrence rate of spread F events observed over two stations at the same longitude namely Nicosia (geographic Lat: 35.29 °N, Long: 33.38 °E) and Moscow (geographic Lat: 55.50 °N, Long: 37.30 °E) during 2009 and 2014 encompassing periods of low, and high solar activity. The main finding of this investigation is the inverse solar cycle and significantly different annual temporal dependence of the spread F occurrence rate over Nicosia and Moscow.

COVID-19 virus, knows as novel coronavirus, spread across the world. The World Health Organization (WHO) marked March 11, 2020 as the day when COVID-19 was declared as pandemic. It was first originated in Wuhan, China. In recent days, Covid-19 impacted various social and economic fields in the world. It is necessary to quantify its spread and make predictions on how it is going to affect the world in coming months. In this paper, our aim is to use linear regression and LSTM algorithms to forecast Covid-19 spread. The objective of this study is to determine if spread can be forecasted to better accuracy using linear regression and LSTM algorithms.

The health organizations around the world are currently facing one of the greatest challenges, to overcome the current global pandemic, COVID-19. It erupted in December 2019, in Wuhan City, China. It spreads rapidly throughout the world within couple of months. In this paper, the data of the COVID-19 have been collected, organized, analyzed and interpreted using the discrete-time model of SIR epidemic model. Moreover, results for several countries from different regions of the world have been obtained. Furthermore, comparative study has been carried out for the countries under consideration. The comparison was performed for the data of different countries on same dates of each month. However, the calculations are carried out for thirteen consecutive weeks, to investigate the rate of spread and the control of the disease in these countries. This guides us to some important concepts like factors favoring the spread of virus and those resisting the spread. Different regions are studied and their data have been evaluated to know which regions are the most effected. This study helps to know the important factors about the behavior of the coronavirus in different environments, such as lockdowns, temperatures, humidity and other restrictions. The proposed concepts and equations can be used to project the upcoming behavior of the pandemic.

Corona Virus (Covid-19) has spread throughout the world, including Indonesia and Bengkulu province. The high spread of cases raises fear and concern in the community, especially those who have not been exposed to clear information about Covid-19. Community understanding and supportive attitudes as well as good preventive measures play an important role in reducing the rate of spread in Bengkulu Province. Effectiveness in reducing the number of cases is very dependent on the cooperation and compliance of the whole community. The purpose of this study was to describe the knowledge, attitudes and practice of the people in Bengkulu Province regarding Covid-19.

The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global health problem that the WHO declared a pandemic. COVID-19 has resulted in a worldwide lockdown and threatened to topple the global economy. The mortality of COVID-19 is comparatively low compared with previous SARS outbreaks, but the rate of spread of the disease and its morbidity is alarming. This virus can be transmitted human-to-human through droplets and close contact, and people of all ages are susceptible to this virus. With the advancements in nanotechnology, their remarkable properties, including their ability to amplify signal, can be used for the development of nanobiosensors and nanoimaging techniques that can be used for early-stage detection along with other diagnostic tools. Nano-based protection equipment and disinfecting agents can provide much-needed protection against SARS-CoV-2. Moreover, nanoparticles can serve as a carrier for antigens or as an adjuvant, thereby making way for the development of a new generation of vaccines. The present review elaborates the role of nanotechnology-based tactics used for the detection, diagnosis, protection, and treatment of COVID-19 caused by the SARS-CoV-2 virus.

In a bid to slow the rate of spread of the virus, the Federal Government of Nigeria, on several occasions, imposed targeted lockdown measures in areas with rapid increase of Covid-19 cases. The states in which the federal government imposed the targeted lockdown included Lagos, Ogun, and the Federal Capital Territory in Abuja. Some States in the country imposed partial lockdown and closure of interstate boarders. Curfews have also been introduced in all the states nationwide. To alleviate the effects of the lockdown, the Federal Government of Nigeria rolled out palliative measures for targeted groups. However, lamentations have trailed the distribution of government palliatives by the masses. Citizens allege that the process of distribution of palliatives had been politicized. Key words: • Corona virus • Covid-19 • Nigeria • Palliatives Copyright © 2020 Eranga. Published by Global Health and Education Projects, Inc. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in this journal, is properly cited.

BACKGROUND: Previous studies analyzed contrast agent spread during cervical interlaminar epidural steroid injections (CILESIs) by using planar fluoroscopy and reported wide variance of the rate of spread to the ventral epidural space (VES). Cross-sectional CT allows for direct viewing of contrast agent in the VES, providing improved spread assessment and thereby informing needle placement decisions when targeting pain generators. PURPOSE: To determine the extent of injectate spread at CT fluoroscopy–guided CILESI, with particular attention to the VES and bilateral neuroforamina, by using cross-sectional CT. MATERIALS AND METHODS: This study reviewed 83 consecutive CT fluoroscopy–guided CILESIs at which a postprocedural cervical spine CT was performed (June 2016 to December 2017). All procedures used the same injectate (2 mL corticosteroid, 3 mL contrast agent). Postprocedural CT scans were reviewed for the presence of contrast within the VES, dorsal epidural space, ipsilateral neuroforamen, and contralateral neuroforamen in every cervical interlaminar level. Descriptive data are presented as frequencies or means. McNemar tests or hierarchical logistic models were used to assess associations between covariates and contrast agent spread to particular locations. RESULTS: The study cohort included 73 individual patients (59% women; 43 of 73) (mean patient age, 57.6 years ± 11.5 [standard deviation]). Mean number of levels of cranial spread were 0.6 level for VES, 1.9 levels for contralateral neuroforamen, 2.1 levels for ipsilateral neuroforamen, and 3 levels for dorsal epidural space. No VES spread in any level was found with 35% (29 of 83) of injections. VES spread was more likely to occur in the level of needle placement (43%; 36 of 83) than in other interlaminar levels (19.5%; 97 of 498; P < .001). Spread was more likely to occur in the neuroforamen ipsilateral to the needle approach compared with contralateral (P < .001). CONCLUSION: Cervical interlaminar epidural steroid injections have injectate spreads with a mean of less than one level cranially in the ventral epidural space (VES) and approximately two levels in the neuroforamen. VES spread occurs more frequently at the level of needle placement and within the ipsilateral neuroforamen. © RSNA, 2019

The aim of this study was to determine the pattern of the spread of antibiotic-resistant E. coli on pig farms in Kupang City by using mapping analysis. Data on E. coli resistance comes from the results of laboratory analysis and as secondary data for spatial analysis. Spatial analysis uses the nearest neighbour index, convex hull and elementary analysis of disease methods. The results of this study have shown a high prevalence of E. coli (85.4%) with clustered distribution patterns and have a wide spread (10920 ha) in the area in Kupang City. MDR E. coli had a moderate prevalence (57.31%) by forming a group spread pattern and a wide spread (7778 Ha) on pig farms in Kupang City. This result encourages prevention and control efforts by all interested parties so that the rate of spread of resistant E. coli can be reduced.

Fire simulators allow predicting fire spread and behavior and some of which in real-time. Both strategies and tactics to suppress wildland fires depend on fire analysis which is generally based on fire simulations that need to be accurate for a proper decision making. However, limitations and assumptions of the fire models and uncertainties in input data may induce errors in the simulated fire growth and, therefore, fire simulations do not always match actual fire spread. In this paper, we show an innovative method implemented in Wildfire Analyst to adjust fire simulations in real-time. The method determines the adjustment factors needed for the optimal rate of spread by fuel model in order to minimize the arrival time error between the simulated fire and a set of control points where the arrival time of the observed (real) fire is known. Two case studies were used to present the method, showing robust results in reducing the error and fitting the simulated fire growth to the real fire spread, with practical real-time implications. The method presented may be solved in real-time and used with any empirical fire propagation.

The rate of fire spread is of paramount interest in order to prevent and control wildland fires. It has been extensively studied under laboratory conditions, but little research has been made regarding the differences between artificially constructed and natural litter. By using a specially designed sampling method, in this study differences in the rate of spread between natural and constructed pine needle litter samples are assessed using a combustion tunnel with controlled wind speed. A total of 68 experiments were conducted with four levels of wind speed and six levels of permeability (five for constructed samples and one for the natural sample). It was found that permeability has a strong influence on the rate of spread when wind speeds are high (2.1–3.6 $${\hbox {m}} \cdot {\hbox {s}}^{-1}$$ ). It was also found that while wind speed and permeability have a strong influence on the rate of spread, their combined effect is not significant. Thus, both variables may be treated independently from one another. Lastly, it was found that constructed samples with permeability of $$1 \times 10^{-7}$$ m $$^2$$ behave similarly to natural samples in terms of the rate of spread. This suggests that it is possible to use constructed samples in the laboratory by matching their permeability, and, thus, obtain realistic values for the rate of fire spread. This could be of use for medium and large scale laboratory tests, where it is not possible to use undisturbed litter samples.

An important property of wildfire behaviour is rate of spread (ROS). The objectives of this study are to evaluate the uncertainty of landscape-scale ROS estimates derived from repetitive airborne thermal infrared (ATIR) georeferenced imagery and the utility of such estimates for understanding fire behaviour and controls on spread rates. Time-sequential ATIR image data were collected for the Cedar, Detwiler, and Rey Fires, which burned in California during summers of 2016 and 2017. We analyse error, uncertainty, and precision of ROS estimates associated with co-location accuracy, delineation of active fire front positions, and generation of fire spread vectors. The major sources of uncertainty influencing accuracy of ROS estimates are co-registration accuracy of sequential image pairs and procedures for delineating active fire front locations and spread vectors between them; none of these were found to be substantial. Median ROS estimates are 11 m min−1 for the Cedar Fire and 8 m min−1 for the Detwiler Fire, both of which burned through mixed shrub and tree areas of the Sierra Nevada foothills and were estimated for downslope spread events. Of the three study fires, the fastest spread rates (average spread of 25 m min−1 with maximum of 39 m min−1) are estimated for the Rey Fire, which burned on variable directional slopes through chaparral shrubland vegetation.

Diaphorina citri Kuwayama (Hemiptera: Liviidae), commonly known as Asian citrus psyllid (ACP), is an invasive insect pest and the vector of the bacterium causing Huanglongbing (HLB), a lethal disease of citrus. In the United States, ACP has been established in all citrus-producing zones, all of which have different environmental conditions. The spread of ACP and, more importantly, HLB, has progressed differently depending on the state, with more rapid spread in Florida and Texas than in California. Climatic variations between the regions are likely a strong factor in the difference in the rate of spread. Despite this, it is unknown how the flight capacity of D. citri is influenced by high temperatures (&gt, 30 °C) and subsequently, low humidity experienced in California but not in Texas or Florida. In this study, by using a custom-made, temperature-controlled flight mill arena, we assessed the effect of high temperatures on the flight capacity and flight propensity of D. citri under low (20–40%) and high (76–90%) relative humidity conditions. We found that temperature and humidity influence the propensity to engage in short or long-distance flight events. Psyllids exposed to temperatures above 43 °C only performed short flights (˂60 s), and a high relative humidity significantly decrease the proportion of long flights (≥60 s) at 26 and 40 °C. The flight capacity for insects who engaged in short and long flights was significantly affected by temperature but not by humidity. For long flyers, temperature (in the 26–43 °C range) was negatively correlated with distance flown and flight duration. The most favorable temperature for long dispersion was 26 °C, with suboptimal temperatures in the range of 32–37 °C and the least favorable temperatures at 40 and 43 °C. In conclusion, D. citri is able to fly in a broad range of temperatures and efficiently fly in high and low humidity. However, temperatures above 40 °C, similar to those experienced in semi-arid environments like Southern California or Arizona, are detrimental for its flight capacity.