Effect Of Spread Research Articles

Cooperative control of environmental extremes by artificial intelligent agents.

Humans have been able to tackle biosphere complexities by acting as ecosystem engineers, profoundly changing the flows of matter, energy and information. This includes major innovations that allowed to reduce and control the impact of extreme events. Modelling the evolution of such adaptive dynamics can be challenging, given the potentially large number of individual and environmental variables involved. This article shows how to address this problem by using fire as the source of extreme events. We implement a simulated environment where fire propagates on a spatial landscape, and a group of artificial agents learn how to harvest and exploit trees while avoiding the damaging effects of fire spreading. The agents need to solve a conflict to reach a group-level optimal state: while tree harvesting reduces the propagation of fires, it also reduces the availability of resources provided by trees. It is shown that the system displays two major evolutionary innovations that end up in an ecological engineering strategy that favours high biomass along with the suppression of large fires. The implications for potential artificial intelligence management of complex ecosystems are discussed.

Prediction of ILI following the COVID-19 pandemic in China by using a partial differential equation

Abstract The COVID-19 outbreak has significantly disrupted the lives of individuals worldwide. Following the lifting of COVID-19 interventions, there is a heightened risk of future outbreaks from other circulating respiratory infections, such as influenza-like illness (ILI). Accurate prediction models for ILI cases are crucial in enabling governments to implement necessary measures and persuade individuals to adopt personal precautions against the disease. This paper aims to provide a forecasting model for ILI cases with actual cases. We propose a specific model utilizing the partial differential equation (PDE) that will be developed and validated using real-world data obtained from the Chinese National Influenza Center. Our model combines the effects of transboundary spread among regions in China mainland and human activities’ impact on ILI transmission dynamics. The simulated results demonstrate that our model achieves excellent predictive performance. Additionally, relevant factors influencing the dissemination are further examined in our analysis. Furthermore, we investigate the effectiveness of travel restrictions on ILI cases. Results can be used to utilize to mitigate the spread of disease.

Prioritising non-native fish species for management actions in three Polish rivers using the newly developed tool-dispersal-origin-status-impact scheme.

Biological invasions are a major threat to global biodiversity, with freshwater ecosystems being among the most susceptible to the successful establishment of non-native species and their respective potential impacts. In Poland, the introduction and spreading of non-native fish has led to biodiversity loss and ecosystem homogenisation. Our study applies the Dispersal-Origin-Status-Impact (DOSI) assessment scheme, which is a population-level specific assessment that integrates multiple factors, including dispersal mechanisms, origin, status, and impacts, providing a nuanced framework for assessing invasion risks at local and regional levels. We used this tool to evaluate the risks associated with non-native fish species across three major Polish rivers (Pilica, Bzura, and Skrwa Prawa) and to prioritise them for management actions. Using DOSI, we assessed eight non-native species identified in the three studied rivers: seven in both Pilica and Bzura and four in Skrwa Prawa. The DOSI assessment scheme identified high variability in the ecological impacts and management priorities among the identified non-native species. Notably, species such as the Ponto-Caspian gobies exhibited higher risk levels due to their rapid spread and considerable ecological effects, contrasting with other species that demonstrated lower impact levels and, hence, received a lower priority for intervention. The adoption of the DOSI scheme in three major rivers in Poland has provided valuable insights into the complexities of managing biological invasions, suggesting that localised, detailed assessments are crucial for effective conservation strategies and highlighting the importance of managing non-native populations locally.

A new look at the finance–environment nexus: How yield spread affects environmental quality in the United States

AbstractEnhancing environmental quality is currently a key focus for policymakers. Furthermore, researchers are also prioritizing the investigation of novel variables that can influence environmental quality. The yield spread is commonly used as a leading indicator for business cycles in the macro‐finance literature, providing information about future expectations regarding business cycles. The yield spread also presents information about the borrowing costs of firms. None of the existing studies in the environmental economics literature has tested the impact of the yield spread on environmental quality, implying the level of the yield spread has not been considered a variable that can influence environmental quality. This study aims to fill this gap by providing evidence on the effect of yield spread (between 2‐ and 10‐year government bonds) on environmental quality in the United States from June 1976 to September 2023. The results indicate that an increase in the yield spread leads to a rise in environmental destruction. These results suggest two considerable consequences. First, optimistic expectations today lead to the overuse of resources and environmental destruction. Second, firms' higher borrowing costs may be forcing them to use less environmentally friendly production methods to offset more expensive financing costs and increase their profits. This study asserts that companies should enhance their environmental sensitivity, and policymakers should adopt a more proactive stance, based on the results of this study and other research that demonstrates the detrimental impacts of environmental regulation violations and poor environmental performances on companies' stock prices and financial performances.

Image quality improvement in single plane-wave imaging using deep learning

In ultrasound image diagnosis, single plane-wave imaging (SPWI), which can acquire ultrasound images at more than 1000 fps, has been used to observe detailed tissue and evaluate blood flow. SPWI achieves high temporal resolution by sacrificing the spatial resolution and contrast of ultrasound images. To improve spatial resolution and contrast in SPWI, coherent plane-wave compounding (CPWC) is used to obtain high-quality ultrasound images, i.e., compound images, by coherent addition of radio frequency (RF) signals acquired by transmitting plane waves in different directions. Although CPWC produces high-quality ultrasound images, their temporal resolution is lower than that of SPWI. To address this problem, some methods have been proposed to reconstruct a ultrasound image comparable to a compound image from RF signals obtained by transmitting a small number of plane waves in different directions. These methods do not fully consider the properties of RF signals, resulting in lower image quality compared to a compound image. In this paper, we propose methods to reconstruct high-quality ultrasound images in SPWI by considering the characteristics of RF signal of a single plane wave to obtain ultrasound images with image quality comparable to CPWC. The proposed methods employ encoder–decoder models of 1D U-Net, 2D U-Net, and their combination to generate the high-quality ultrasound images by minimizing the loss that considers the point spread effect of plane waves and frequency spectrum of RF signals in training. We also create a public large-scale SPWI/CPWC dataset for developing and evaluating deep-learning methods. Through a set of experiments using the public dataset and our dataset, we demonstrate that the proposed methods can reconstruct higher-quality ultrasound images from RF signals in SPWI than conventional method.

The Mpox outbreak is a public health emergency of international concern: Implications for mental health and global preparedness.

The Mpox, a zoonotic viral disease that has historically affected Central and West Africa, has been declared a Public Health Emergency of International Concern by the World Health Organization. Rapid transmission and recent dissemination in Africa may imply significant challenges to global health, including mental health. We reviewed the mental health implications of the Mpox outbreak according to the published literature. We also discussed the psychological effects of the global spreading of this infection and public health preparedness strategies. Key areas of intervention may include the epidemiological surveillance, vaccine development, and mental health strategies. The Mpox outbreak calls for a robust global preparedness to address potential health emergencies. Strengthening epidemiological surveillance, ensuring equitable vaccine distribution, and building resilient public health infrastructure are crucial. Additionally, addressing mental health consequences may require immediate, intermediate, and long-term strategies, including telepsychiatry, stress management training, and the integration of mental health into primary care.

Controllable Contact-Destructive Hydrogel Actuators.

Constructing hydrogels with spatially heterogeneous structures are crucial for unlocking novel applications. To this end, selectively removing a specific portion of hydrogels by facile and intricate destructive strategies is worth exploring. Herein, a "contact-destructive" hydrogel actuator is presented, composed of a dynamic hydrogel network doped with hydrophilic polyethylene glycol (PEG). The destructive behavior of the hydrogel actuator is attributed to the surface tension-induced spreading effect and the enhanced water absorption due to the additive PEG. Parameters that act on these mechanisms are used to control the destruction of the hydrogel. During the destructive process, the hydrogel actuator exhibits locomotion routes predetermined by the graphic pattern with the aid of 3D printing. Additionally, such self-destructive behavior can be terminated by UV light irradiation when PEG is replaced with poly(ethylene glycol) diacrylate (PEGDA). Significantly, diverse applications including controllable 3D structures collapse, self-erasing, and on-demand cell release, are realized with such self-destructive hydrogel. These results demonstrate that the present hydrogel has great values in soft robotics, anti-counterfeiting, controlled drug delivery, and other related fields.

An examination of the relationship between risk perceptions, cultural-religious beliefs and coping during COVID-19 pandemic control in South Asian countries: a systematic review

BackgroundCovid 19 was declared as a public health emergency by the World Health Organisation (WHO) due to its rapid spread and catastrophic effects on health. It affected around 119 M people with mortality rate of 0.27% worldwide, including South-Asians. This review aims to understand the risk perceptions, cultural religious beliefs and the coping mechanisms of South Asians during the Covid 19 pandemic.MethodsWe conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The following search engines were used: Medline, Cochrane Library, PsycINFO, CINAHL, and Web of Science. Included studies investigated perceptions and opinions of individuals on knowledge, risk and protective factors, native faith based practices, and attitudes towards the COVID-19 pandemic.ResultsThe database search produced 282 articles to screen. The final narrative synthesis included five studies comprising of 13,476 participants from Pakistan, India, Nepal, and Bangladesh. Ten studies, comprising 7,893 participants, were eligible and included for meta-analysis. The overall pooled prevalence with maximum heterogeneity for correct knowledge of symptoms, hand washing or use of sanitizers, face masking use of herbal or traditional remedies and physical distancing or avoidance of contact was reported through meta-analysis.ConclusionThe review brings forth a useful comparison of individual and cultural differences in KAP, risk perceptions and coping strategies. This review highlights the need for and importance of tailored information dissemination, culturally sensitive risk communication, targeted educational interventions, community engagement and empowerment, policy, and infrastructure improvements, as well as continued research and data collection. By addressing these implications, efforts to mitigate the impact of COVID-19 can be more effective and equitable across diverse populations.Prospero registrationCRD42021246475.

Monetary policy reaction function: A Bayesian analysis for the BRICS.

This study estimates the monetary policy reaction function (MPRF) in a Dynamic Stochastic General Equilibrium (DSGE) framework using Bayesian analysis for the emerging economies. DSGE models are suitable for the policy analysis because of their simplicity and prominent role of forward-looking variables. This is a pioneer study investigating the combined effects of credit spreads, fiscal imbalances, and monetary autonomy on interest rates for BRICS member countries. Using real data for the period 1970-2021, the posterior estimates confirm that both credit spread and fiscal imbalance significantly contribute to fluctuations in output, inflation, and interest rates in all the sample economies. The estimates show that fluctuations in the inflation rate are due to supply shocks. The empirical estimates also reveal that fiscal imbalances shock significantly affect output in Brazil, India, and South Africa, whereas, based on real data inflation and interest rate are significantly affected by fiscal imbalance shocks in China and South Africa. Yet, the findings suggest that the effects of various shocks on output and interest rates vary across countries.

Estimation of Electron Drift Mobility along the <i>c</i>-Axis in 4H-SiC by Using Vertical Schottky Barrier Diodes

Electron mobility along the c-axis is the most important in SiC because the current flows along this direction in vertical SiC devices. However, previous reports on the drift mobility along the c-axis are still limited because of the difficulty of sample preparation or analysis. In this study, the authors presented the method to estimate the electron drift mobility of a lightly-doped epitaxial layer by using SiC(0001) vertical Schottky barrier diodes (SBDs). For the analyses, the effects of current spreading and series resistance were carefully considered based on experimental results obtained from SBDs with various device parameters, leading to a more accurate estimation. The mobility along the c-axis was obtained as 1070 ± 290 cm2/Vs for a donor density of 1 × 1015 cm-3, and it was compared with the results by Hall effect measurement.

A numerical and experimental approach to blast protection with fluids, effect of impulse spreading

In the face of rapidly evolving challenges, new protection techniques against blast waves generated by high explosive detonations must be identified. The protection of vehicle floors is particularly relevant, especially against improvised explosive devices (IED), as these are challenging to detect. In this paper, investigations on fluid-filled sacrificial claddings are presented. Classical sacrificial claddings aim at limiting the deflection of the target by dissipating the blast wave energy through the core plastic or brittle deformation. On the contrary, fluid-filled sacrificial claddings are systems which aim at limiting the deflection of the target by extracting energy from the system and modifying the load distribution on the target. A new experimental set-up, designed for this investigation, is presented. Based on pressure signals, high speed-imaging and numerical simulations on LS-DYNA, it is shown that the ability to extract energy from the system is directly linked to the freedom of displacement of the fluid. It is also shown that at the same time, higher fluid displacement and well-designed boundary conditions lead to higher impulse spreading on the target.

LLMv2: A Language Model with Holistic Hidden Markov Models and Machine Learning for Fake News Detection

The usage of social media has expanded in recent years, allowing them to get news from around the world at any time. This in turn, is questioning the authenticity of the news that is being spread both globally and locally. Fake news such as misinformation, gossips is widely disseminated on social media having a negative impact on society and lives of the people. As a result, much study is being is carried out in order to detect them. The data can be clustered into smaller groups based on the type of news using a few learning approaches. A novel method has been proposed for prediction of the authenticity of the news of the LIAR dataset [1] using Logistic Regression and a boosting algorithm eXtreme Gradient Boosting (XGBoost) for efficacy, computational pace and performance of the model. This method detects fake news by analyzing the semantic and syntactic connections between sentences. Various graphs (like heat maps, bar charts) are plotted to show the distribution of the authenticity of news and also to compare the predicted result with the actual one. The proposed strategy addresses the effects of the hoax's global spread. People are hungry for information to defend themselves and others in a community where humans are confronting large-scale risks from harms. Some key traits such as Sentimental features, Content-based features, Frequency features, and Hybrid features (combinations of two or more features) are incorporated for early prediction of fake news spread via social media. The liar dataset is used to train the method and tested for accurate results. The experimental accuracy is found out to be 98%. Key Words: fake news detection, social media, logistic regression, XG boost, natural language processing

Heat spreading effect on the optimal geometries of cooling structures in a manifold heat sink

Embedded cooling is a promising solution to address thermal challenges of power electronics. The present work investigates heat spreading effect on the optimal geometries of cooling structures within a single-phase manifold heat sink in laminar regime by integration of topology optimization (TO) and Bayesian optimization (BO). Such integration is for the manual parameter tuning issue in the density-based TO of conjugate heat transfer, and the TO process is accelerated by using a dual-level simulator and the optimality criteria optimizer combined with the stochastic gradient descent method. The heat spreading effect significantly alters the optimal geometries, due to the change of thermal resistance constitutions. Physical analyses on the BO-TO-generated geometries give two guidelines for improving the cooling structures here: (a) Heat source-coolant distance should increase properly for narrow heating area and small Biot number; (b) Highly-thermal-conductivity solid can be filled into low-velocity regions directly connecting to hot area. As an example, a fabrication-friendly cooling structure is devised in the case of concentrating heating following these guidelines, avoiding the computationally-expensive optimization process and the over-complicated geometries. The CFD simulations show this design can significantly reduce the thermal resistance with minor increase of pressure loss as the Reynold number from 50 to 300.

Theoretical and Practical Considerations of Spatially Offset Raman Spectroscopy (SORS) and Micro-SORS.

Spatially offset Raman spectroscopy (SORS) is typically used to non-invasively investigate stratified samples that possess features on a millimeter scale, whereas micro-SORS usually deals with micrometer-thick layered samples. However, there are many instances where these boundaries are intertwined, sometimes indicating the possibility of using both techniques as well as circumstances that present mutual exclusion to their applicability. The aim of this study is to establish an application protocol that provides better insight into their suitability for deployment in various scenarios. The differences and similarities between the two approaches are investigated highlighting their strengths and limitations considering both theoretical and practical aspects. Diverse available parameters entail prospects and restrictions of both techniques and give rise to specific instrumental effects, namely, the overlap between the collection and excitation areas, the percentage of collected area for a given spatial offset, and the accuracy in the definition of the spatial offset (spread effect). These aspects are studied and exemplified on mockup samples relevant to the field of cultural heritage. The samples are characterized by high compositional complexity comprising features ranging from micrometer to millimeter scales. The conclusions reached are also relevant to other scientific areas such as biomedical, forensic, or energy harvest.

Enhancing the dissemination of Cantonese Opera among youth via Bilibili: a study on intangible cultural heritage transmission

Intangible cultural heritage is an invaluable treasure for all human beings worldwide. In 2009, the United Nations Educational, Scientific and Cultural Organization (UNESCO) inscribed the Chinese Cantonese Opera, also known as Yueju in Chinese Pinyin, on the Representative List of Intangible Cultural Heritage of Humanity. The awareness of inheriting Yueju is not uncommon, but advancing methods to involve more young generations in this art form is still necessary. In this study, we focused on Yueju videos on Bilibili, a cultural community and video website popular among the younger generation. Through quantitative and qualitative research, we explored the types of Yueju videos that would have a significant spreading effect. The 1916 Bilibili videos related to Yueju were collected using Python crawler technology. We analyzed each video using seventeen variables. The elaboration likelihood model (ELM) forms the theoretical foundation of this research. We constructed the Yueju transmission model with two persuasive routes based on this model. The research methods mainly comprised regression analysis, multi-factor ANOVA, and analytic hierarchy process (AHP). We invited thirty-one experts to assess the importance hierarchy of those video factors and calculate the weight coefficient using AHP. This study demonstrated the central route concerning the causal relationship between video recognition and spreading effect through regression analysis. Additionally, this research identified the optimal combination of 8 video factors using multi-factor ANOVA in the peripheral route. In this study, we focused on the niche of Yueju video transmission on Bilibili. This research utilized the ELM and hybrid methods to obtain the statistical results. Then, we developed appropriate macro-level and micro-level strategies for transmitting Yueju culture, particularly those aimed at the younger generation.

Three-dimensional theory of superradiant free-electron lasers

The solitonlike superradiant regime of free-electron lasers (FEL) offers a promising path towards ultrashort pulses, beyond the natural limit dictated by the bandwidth of the high-gain FEL instability. In this work we present a three-dimensional theory of the superradiant regime, including the effects of beam emittance and energy spread. Our work takes advantage of recent developments in nonlinear FEL theory to provide a fully analytical description of solitonlike superradiance. Our theory proves the existence of a diffraction-dominated steady-state regime in which the superradiant peak power grows indefinitely while leaving the pulse duration and on-axis intensity almost unchanged. These results are in excellent agreement with three-dimensional simulations and are supported by recent experimental results at the Linac Coherent Light Source. This work advances nonlinear FEL theory and provides a theoretical framework for the next generation of attosecond x-ray FELs. Published by the American Physical Society 2024

Dextractor:Deformation Extractor Framework for Monitoring-Based Ground Radar

The radio frequency (RF) data generated from a single-chip millimeter-wave (mmWave) ground-based multi-input multi-output (GB-MIMO) radar can provide a highly robust, precise measurement for deformation in harsh environments, overcoming challenges such as different lighting and weather conditions. Monitoring deformation is significant for safety factors in different applications, such as detecting and monitoring the ground stability of underground mines. However, radar images can experience different types of clutter and artifacts besides the spreading effects caused by the side lobes, resulting in the foremost challenge of suppressing clutter and monitoring deformation.In the state of the art, the introduced frameworks usually include many filters proposed for different types of noise, with commercial systems typically using an amplitude threshold. This paper proposes a framework for monitoring the deformation, where the essential process is to apply a data-driven threshold to the amplitude heatmap, detect the deformation, and eliminate noise. The proposed threshold is an iterative approach based on radar imagery statistics, and it performs well for the collected dataset. The principal advantage of our proposed framework is simplicity, reducing the burden of using different filters. We can consider the dynamic threshold based on data statistics as a data-driven machine learning tool. The results show promising performance for our method in monitoring the deformation and removing clutter compared to the benchmark method.

Tell me what to do first: how behavioural skills drive users’ intention to adopt online health information

PurposeTo gain a deeper understanding of users’ health information adoption and to promote the effectiveness of health information spread in the context of online limited information, this paper aims to examine how the information-motivation-behavioural (IMB) skills model can be used to organize online health information by experimenting how different IMB elements (information, motivation and behavioural skills) affect users’ intention to adopt health information.Design/methodology/approachThe authors conducted an experiment with 48 participants who received health articles with various combinations and sequences of IMB elements, analysing the impact on information adoption intention to share and practice. The authors also examined the mediation effect of information usefulness and the moderating effect of perceived health status.FindingsThe authors found that: users’ adoption intention of information was influenced by the order of used IMB elements, not the number of elements used; users were more likely to adopt information that started with behavioural skills rather than the model-prescribed IMB sequence; and perceived usefulness mediated the relationship between IMB elements and users’ adoption intention, which means users with different levels of health status all pay more attention to information usefulness and practicability.Originality/valueThe study contributes to research on health communication by showing how the IMB model can be applied online to enhance the effectiveness of health information dissemination. It can also help online health communities arrange more effective and engaging health messages to promote users’ willingness to adopt.

Women Education During Crisis: How Do Cosmetic and Health Industries Educate Women for Covid-19 Resilience and Provide Basis for Mitigation Education?

COVID-19 virus has been putting many people's health in peril and causing social anxiety, insecurity, and mayhem. It has become a public enemy. Collaboration between all sectors and community involvement are required to control the spread and negative effects of COVID-19. The beauty industry has emerged as one of several crucial sectors in the fight against COVID-19 Because they can make hand sanitizers, cleansers, hand gel, and lotions in large quantities that can protect the community and encourage community to stay healthy. This research explores the roles played by some locally produced beauty products in Indonesia in empowering women and girls to protect themselves from COVID-19. The study uses qualitative research methods. It examines ten cosmetics companies and incorporates interpretative analysis and web content analysis. The study examines the data from the perspective of community education and humanities. According to the study, the beauty industries typically employ three major strategies to educate their female and young girl customers. The first educational strategy is promoting self-health protection to make wellness and health goods. The second approach involves teaching women new healthy routines, safe, healthy makeup practices, and strict mask wearing and health plan implementation. The third strategy involves taking part in social educational activities that support and promote social skills among women and girls, such as empathy, care, and support. The study shows that women education is not only the responsibility of educational institutions, but also the business or industries sectors.

Analyzing Covid-19 Pandemic Through Cases and Spillover Effect: Cross Wavelet Transformation of Mobility in the Countries

AbstractThis research examines the relationship between daily Covid-19 cases and public mobility for six different places, where mobility can be high, in Brazil, the UK, and the USA. We tried to show how the spreading effect of infectious diseases occurs in places where human mobility is intense. The data consists of daily data covering the periods from 28/02/2020 to 08/02/2021, which includes the database of Our World in Data and Google Mobility Reports. Basically, there is a positive correlation between mobility and case numbers. Results in the paper differ from country to country. That is to say, mobility in grocery stores and pharmacies can be said to have an impact on the number of cases in all three countries. Brazil is the country where mobility in parks has the strongest impact. The country which has the lowest frequency in retail outlets is America.