Search

The goal of this paper is to understand the interplay between seasonality and diapause on the population dynamics of ticks. To analyse this challenge, we study a mathematical model in which the population is divided into two groups: individuals with regular development and individuals undergoing diapause. A key ingredient in the model is that the common birth and death rates depend on time in order to describe the seasonal fluctuations of the environment. From a mathematical point of view, this paper offers a novel methodology to derive criteria of global attraction. In some classical models, we give delay-dependent conditions that cover the best delay-independent criteria of global attraction. We discuss how our approach improves existing results in relevant literature. Moreover, our results are simple and versatile enough to match experimental observations. To illustrate this potential, we analyse our model with parameters coming from real observations. A message of this paper is that seasonality plays a critical role in the population dynamics of ticks. [ABSTRACT FROM AUTHOR]

Maritime transport helps the development of the economy of countries. Improving the current situation in this type of transport requires the application of modern software tools for assessment, analysis and forecasting. The aim of this paper is to suggest an approach for an in-depth analysis of marine traffic near to independent ports. This approach is tested and validated for the Varna and Constanta ports for the period 2004–2021. Data from Eurostat are used. This paper proposes a new methodology for an in-depth analysis and forecasting of marine traffic of independent nearby ports using public data. Correlations, multiple regression, graphical methods, seasonality and trendlines are used to test and validate the proposed methodology. The results show that the proposed methodology may be applied for other independent ports and periods. The results show some interesting facts about the analyzed ports of Varna and Constanta. Our initial assumptions that these two independent ports have similar seasonality is rejected. The novelty of the paper refers to a new methodology for the in-depth analysis and forecasting of marine traffic of independent nearby ports using public data. Using the methodology in this paper (for an in-depth analysis of marine traffic of independent nearby ports) similar research may be done for other nearby ports and periods. Other research may focus on finding the specific types of cargo for each port influencing the differences in seasonality. Nearby ports with separate management may use the proposed methodology for better cargo planning and investment planning. [ABSTRACT FROM AUTHOR]

Learning the dynamics of power prices in a given market is important for a number of players (e.g., producers, consumers, and policy makers) at both macro- and microeconomic levels. This paper analyzes the recent behavior of spot prices in eight Western European countries. The sample period coincides with the COVID-19 pandemic for the most part: it starts in April 2020 and runs until May 2023; it includes the start of the Russia–Ukraine war. We introduce a new model for the hourly spot price of electricity. The deterministic component includes yearly, weekly, and daily seasonalities; the stochastic component accounts for volatility, mean reversion, and discrete jumps. We estimate the model with publicly available hourly data. Regarding the development of the internal market for electricity, we find that core mainland power markets now move closer in step with one another than before, but the integration process of the Iberian Peninsula seems to have kicked into reverse. As for the dynamics of power prices, in the last part of the sample period the speed of reversion falls everywhere, and price volatility increases noticeably; the expected number of jumps per hour decreases, but their average size turns to positive and they become more volatile. [ABSTRACT FROM AUTHOR]

Epidemiological data is the data obtained based on disease, injury or environmental hazard occurrence using the previous data on the epidemic situation. We can use it for analysis and find the trends and patterns. We can use different machine learning models to create a platform that can be used for different time series data. We can rely on the properties of time series data like trends and seasonality and use this for future prediction. Acquiring the dataset is the first step in data preprocessing in machine learning. We have collected the dataset from ourWorldIndia website which is a real-life dataset of covid-19. This paper presents the idea of a dedicated machine learning model to forecast the future using epidemiological data. We have taken a data-set of covid-19 for the prediction of the number of daily cases infected by the coronavirus. Our machine learning model can be applied on the dataset of any country in the world. We have applied it on the dataset of India in the experimentation. Our goal behind this research paper is to give the ML model which can be easily used on any epidemiological data for prediction by analysing the seasonality. [ABSTRACT FROM AUTHOR]

Tropical studies traditionally describe insect diversity variation throughout the year. The temporally structured responses of insect assemblages to climate seasonality vary across ecosystems due to gradients of resource availability and limiting ecological factors. These idiosyncratic responses might be particularly true across the vast geographical range of the Brazilian territory, including various environments that harbor one of the most diverse ant faunas worldwide. This study addressed the relationship between ant diversity and climatic seasonality, performing a quantitative review of the published data on ant diversity collected in Brazil. We investigated the seasonality effect on ant abundance and richness described in the literature in 47 papers published between 2000 and 2018. These studies were developed mainly in the Atlantic Forest biome and collected ants with pitfall traps on the soil/litter stratum. We initially carried out a vote-counting procedure by comparing the number of significant results describing seasonal differences in the ant assemblage. We found that most papers described a similar pattern of ant abundance, richness, and species composition between seasons. However, when we performed a meta-analysis, we observed a clear pattern of higher ant abundance and richness in the wet/summer season compared with the dry/winter season. Our meta-analysis reveals that the ant diversity decreases in the dry season, strongly in the Cerrado biome. Additionally, we point out differences in the sampling effort across biomes, indicating the need for further investments in studies focused on temporal diversity patterns, including seasonal effects, on the insect assemblage in biomes less investigated so far. Abstract in Portuguese is available with online material. [ABSTRACT FROM AUTHOR]

Analyzing seasonality in the modern tourism industry is essential for successful organization and destination management. The purpose of this paper is therefore to provide an in-depth analysis of seasonality in the main destinations in Turkey. The methods used include the seasonal index of the time series model, the seasonality indicator, the Gini coefficient, the Theil index, the Lorenz Curve, and the coefficient of variation. The results suggest that domestic tourism was moderately seasonal, whereas inbound tourism was highly seasonal during 2017–2020. Moreover, capacity utilization on average was approximately half of the relative capacity, which indicates a substantial discrepancy. One of the salient findings of this study is that the novel coronavirus disease has aggravated the seasonal fluctuations in the country's tourism demand. In addition, the paper provides an adjustment to an interpretation of the Gini coefficient. [ABSTRACT FROM AUTHOR]

In this paper, we provide sharp criteria of global attraction for a class of non-autonomous reaction–diffusion equations with delay and Neumann conditions. Our methodology is based on a subtle combination of some dynamical system tools and the maximum principle for parabolic equations. It is worth mentioning that our results are achieved under very weak and verifiable conditions. We apply our results to a wide variety of classical models, including the non-autonomous variants of Nicholson's equation or the Mackey–Glass model. In some cases, our technique gives the optimal conditions for the global attraction. [ABSTRACT FROM AUTHOR]

SYNOPSIS: Exploring mandatory financial reporting frequency changes in the United States from 1954 to 1972, we find that a mandatory increase in reporting frequency is associated with an increase in firms' future earnings response coefficients. This effect is stronger for firms with higher sales seasonality or operating in industries with lower earnings persistence and for firms that provide more voluntary disclosures of forward-looking information after the reporting frequency increase. We also find that investors increase (decrease) the weight on long-term (near-term) earnings when pricing the firm after the reporting frequency increase. Our findings suggest that more frequent mandatory reporting can enhance the ability of investors to predict future earnings by providing additional useful information on future earnings and by triggering more voluntary disclosures. Our study informs the ongoing policy debates on mandatory financial reporting frequency by highlighting the informational benefit of frequent financial reporting for investors. Data Availability: Data are available from public sources identified in the paper. JEL Classifications: G14; M41; M48. [ABSTRACT FROM AUTHOR]

Similarly to other tropical, arid and semi-arid regions of the World, livestock production in the Sahel is based on extensive grazing in rangelands where managing herd mobility (transhumance and nomadism) is key to productivity and sustainability. However, in this region, government planning, impact assessments and climate change adaptation solutions face several methodological limitations and lack of data availability particularly about the feed and forage resources and how there are used by livestock. Existing feed balances at national or regional level in Sub-Saharan Africa are still largely perfectible. To address these limitations, FAO and CIRAD (French Agricultural Research Centre for International Development) have developed a tool called Feed Balance Sheet (FBS) adapted to the Sahelian livestock systems to help countries carry out improved feed balances. This new FBS tool provides the following improvements to existing feed balances in countries: (i) it considers the seasonality of feed availability and quality as well as the seasonality of animal requirements; (ii) it includes protein and energy in addition to dry matter; (iii) it takes into account a wide range of resources, including browsing of woody biomass. This article describes the methodological development and the assumptions underlying this tool, which has already been piloted in 6 countries in Western and Central Africa. It also presents the results from 2 countries (Mali and Chad) and draws conclusions on the tool's relevance and guidance for its application. It can be used to improve the resilience of pastoral communities in the Sahel and better plan responses to droughts and other types of crises. Its use requires dedicated training and partnerships between governments and science organizations for accessing the appropriate input data. Based on the tool's experience in six countries (including 2 for which results are presented in this paper), we have confirmed the key role that CIRAD, FAO and their partners must play during the first few years in coaching the different teams at the country level. [ABSTRACT FROM AUTHOR]

In this paper, the full information about the existence and nonexistence of a time-periodic traveling wave solution of a reaction–diffusion Zika epidemic model with seasonality, which is non-monotonic, is investigated. More precisely, if the basic reproduction number, denoted by R 0 , is larger than one, there exists a minimal wave speed c ∗ > 0 satisfying for each c > c ∗ , the system admits a nontrivial time-periodic traveling wave solution with wave speed c, and for c < c ∗ , there exist no nontrivial time-periodic traveling waves such that if R 0 ⩽ 1 , the system admits no nontrivial time-periodic traveling waves. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Finance & Financial Law / Finanse i Prawo Finansowe is the property of Wydawnictwo Uniwersytetu Lodzkiego and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Standard long memory models are in abundance in the literature today. Selecting the best such a model in terms of capturing key requisite features and trends in data becomes a challenge. This paper addresses the issue through a sequence of Monte Carlo experiments on simulated data and introduces an interval estimate on the asymptotic variance for the long-range dependence parameter of the entire family of standard long memory time series considered within the scope of the study. [ABSTRACT FROM AUTHOR]

In this paper, score-driven time series models are used, in order to provide robust estimates of the seasonal components of Russian rouble (RUB) currency exchange rates for the period of 1999 to 2020. This paper is the first empirical application of score-driven models to the RUB to US dollar (USD) and RUB to Euro (EUR) currency exchange rates in the literature. The model includes score-driven local level, seasonality, and volatility components for a variety of probability distributions: Student's t distribution, skewed generalized t (Skew-Gen-t) distribution, exponential generalized beta distribution of the second kind (EGB2), normal-inverse Gaussian (NIG) distribution, and Meixner (MXN) distribution. The use of the MXN distribution is new in the literature of score-driven seasonality models. We show that the score-driven models of this paper are robust to changes in the currency exchange rate regimes of the Bank of Russia. We find that the annual seasonality of the RUB is significant, and it is in the range of ± 4 % . We review the determinants of the RUB seasonality using data on exports, imports, and primary income from the current account of the Russian Federation. The statistical performances of all score-driven models are superior to the statistical performance of the classical multiplicative seasonal autoregressive integrated moving average (ARIMA) model. Our results may motivate the practical use of score-driven models of the RUB exchange rate seasonality for financing, investment, or policy decisions. [ABSTRACT FROM AUTHOR]

Phenology is the study of timing of periodic activities in biological life cycles. It describes an inherent component of ecosystem dynamics, and shifts in biological activity have been increasingly recognized as an indicator of global change. Although phenology is mainly studied above the ground, major ecosystem processes, such as decomposition, mineralization, and nutrient cycling, are soil‐dependent. Therefore, the phenology of soil organisms is a crucial, but understudied, aspect of terrestrial ecosystem functioning. We performed a systematic review of 96 studies, which reported 228 phenological observations, to evaluate the current knowledge of soil microbial and animal phenology. Despite the increasing number of soil phenology reports, most research is still concentrated in a few countries (centered in the Northern Hemisphere) and taxa (microbiota), with significant gaps in the most diverse regions of the globe (i.e., tropics) and important taxa (e.g., ants, termites, and earthworms). Moreover, biotic predictors (e.g., biodiversity and species interactions) have rarely been considered as possible drivers of soil organisms' phenology. We present recommendations for future soil phenology research based on an evaluation of the reported geographical, taxonomic, and methodologic trends that bias current soil phenology research. First, we highlight papers that depict good soil phenology practice, either regarding the research foci, methodological approaches, or results reporting. Then, we discuss the gaps, challenges, and opportunities for future research. Overall, we advocate that focusing both on highly diverse ecosystems and key soil organisms, while testing for the direct and indirect effects of biodiversity loss and climatic stressors, could increase our knowledge of soil functioning and enhance the accuracy of predictions depicting the effects of global change on terrestrial ecosystem functioning as a whole. [ABSTRACT FROM AUTHOR]

Copyright of European Journal of Development Research is the property of Palgrave Macmillan Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper focuses on seasonal demand swings in the European natural gas market. We quantify and compare the role of different flexibility options (domestic production, gas storage, and pipeline and LNG imports) to assess European demand fluctuations in monthly resolution. We contribute to the existing literature on seasonal flexibility by addressing the problem with a mathematical gas market optimization model. Our paper provides valuable empirical insights into the decline of gas production in northwestern Europe. Furthermore, we focus on how specific flexibility features differ between pipeline supplies and LNG supplies and between gas imports and storage dispatch. In terms of methodology, we construct a bottom-up market optimization model and publish the complete source code (which is uncommon for gas market models). Furthermore, we propose a new metric--the scaled coefficient of variation--to quantify the importance of supply sources for seasonal flexibility provision. [ABSTRACT FROM AUTHOR]

Copyright of Marketing Science & Inspirations is the property of Comenius University in Bratislava, Faculty of Management and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Accounting & Management is the property of Croatian Accountant and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we explore potential surplus modelling improvements by investigating how well the available models describe an insurance risk process. To this end, we obtain and analyse a real-life data set that is provided by an anonymous insurer. Based on our analysis, we discover that both the purchasing process and the corresponding claim process have seasonal fluctuations. Some special events, such as public holidays, also have impact on these processes. In the existing literature, the seasonality is often stressed in the claim process, while the cash inflow usually assumes simple forms. We further suggest a possible way of modelling the dependence between these two processes. A preliminary analysis of the impact of these patterns on the surplus process is also conducted. As a result, we propose a surplus process model which utilises a non-homogeneous Poisson process for premium counts and a Cox process for claim counts that reflect the specific features of the data. [ABSTRACT FROM AUTHOR]

An important issue from the forest fire protection system perspective is forecasting fires and maintaining a high readiness of firefighting units at a low cost. In Poland, the level of fire protection is defined by the degree of forest fire risk, based on forecasts made for 1 March to 30 September, i.e., the risk period (the so-called fire season). In this paper, based on classical statistical and spatial analysis, we positively verify the research hypothesis that the fire season in Poland changes in terms of start and end dates depending on the region. We therefore propose a modification to the forecasting period, adapted to local conditions and calculated annually on the basis of the previous period. Then, using network analysis, we negatively verify the hypothesis that the size of the burned area is related to the distance from fire brigades, which proves that the reasons for such a differentiation in the number of fires should be sought elsewhere than in the system used for allocating fire units. On the basis of cluster analysis, attention is drawn to areas where large fires break out more often. [ABSTRACT FROM AUTHOR]

This paper offers an in-depth exploration of the intricate relationship between environmental factors and autism spectrum disorder (ASD), with a special emphasis on seasonality. It reviews existing research, providing a comprehensive summary of findings and highlighting the multifaceted dimensions of several environmental factors influencing the etiology of ASD. The discussion encompasses various elements, including birth months, maternal health, dietary choices, and vitamin D deficiency, delving into the intricate interplay of seasonality with environmental influences such as viral infections and solar radiation. The present study raises essential questions regarding the timing of environmental influences and the factors contributing to the rising prevalence of ASD. Ultimately, it underscores the need for future epidemiological research to incorporate more extensive investigations of environmental risk factors and employ advanced statistical analyses. This comprehensive overview contributes to a deeper understanding of how environmental factors, particularly seasonality, may be linked to the occurrence of ASD and its increasing prevalence, recognizing the multifaceted and diverse nature of these interactions. [ABSTRACT FROM AUTHOR]

Simple Summary: The paper presents practices related to reproductive management in sheep and goat farms in Greece. It presents descriptive information regarding the practices followed and the predictors associated with them. The results also indicate that various reproductive practices can have significant effects on the production outcomes (milk production, lamb production) in sheep and goat farms. The correct implementation of reproductive management in sheep and goat farms, based on scientific principles and compliance with established regulations, is important for the improvement in the welfare of farm animals and high production outcomes. This paper reports findings regarding patterns of reproductive management in 325 sheep flocks and 119 goat herds throughout Greece. The objectives were to describe the patterns of reproductive management in sheep and goat farms, to highlight factors that were associated with these management patterns and the clinical application of the various reproductive management approaches in the farms and to establish potential associations with production outcomes. The median months of the start of the mating period for adult sheep and goats were May and June, respectively and for ewe lambs and replacement goats these were August and September, respectively. The median duration of the mating period was 2 months for adults and 1 month for replacements. The median ratio of female to male animals was 22:1 and 25:1 in sheep and goat farms, respectively. Control of reproduction was applied in 33.2% and 16.8% of sheep and goat farms, respectively, mostly by intravaginal progestagen sponges and less often by melatonin implants; multivariable analysis indicated five (availability of milking parlour, number of ewes in a farm, number of daily milkings, daily period spent by farmers at the farm, farming tradition in the family) and two (number of daily milkings, availability of milking parlour) predictors in sheep and goat farms, respectively. Pregnancy diagnosis ultrasonographically was performed in 36.6% and 16.8% of sheep and goat farms, respectively; multivariable analysis indicated as significant three (management system applied in farms, age of farmer, farming tradition in the family) and two (management system applied in farms, availability of milking parlour) predictors in sheep and goat farms, respectively. The control of reproduction and pregnancy diagnosis were associated with a higher number of vaccinations during pregnancy: 2.6 and 2.7, respectively, versus 2.2 and 2.1 in farms where they were not performed. The average per farm number of lambs/kids born per female animal was 1.33 ± 0.01 and 1.30 ± 0.02 for sheep and goat farms, respectively; five (control of reproduction, location of the farm, presence of working staff, collaboration with veterinary practice, breed of ewes) and two (control of reproduction, breed of female goats) predictors were identified in sheep and goat farms, respectively, for high numbers of lambs/kids. Lambs/kids were taken away from their dams at the age of 50 and 65 days, respectively. The average culling age (females, males) was 5.9 and 4.4 years and 6.9 and 4.9 years for sheep and goats, respectively. Farmers sourced animals to be used as replacements for those removed from the farm, mostly from the animals in their own farms, considering criteria related to milk production. Finally, the application of the control of reproduction was associated with increased milk production and the number of newborns, whilst an inverse correlation between the culling age of animals and milk production was seen. [ABSTRACT FROM AUTHOR]

This paper presents the first results of analyses carried out using mobile phone data on human presence (residents, commuters, visitors) in the coastal territory of Lecce (Italy). The aim of the research, conducted in the framework of the DAStU Project 'Department of Excellence on Fragile Territories' in collaboration with the Municipality of Lecce, is to provide precise feedback on the actual use of a coastal territory which is mostly inhabited temporarily, marked by unauthorised building, and threatened by various environmental and climate risks. Starting with an acknowledgement of the limits that traditional census and registry data have in detecting the use of territories characterised by seasonal use and informality, the paper analyses the variations in anthropic presence over multiple years and the incidence of permanent residents. The analyses were carried out using mobile positioning data extracted from the TIM Data Visual Insight (DVI) platform and refer to the period between September 2019 and September 2020. The results show evident heterogeneity among the different coastal settlements. In particular, there are substantial differences between the southern marine (San Cataldo, Torre Veneri, Frigole, Montegrappa) and northern ones (Torre Chianca, Spiaggiabella, Torre Rinalda), where the former show a greater presence of stable residents and a less pronounced seasonal fluctuation. These differences are fundamental for urban planning policies to determine in which areas the retreat of the building from the coast could cause more difficulties and inconveniences. [ABSTRACT FROM AUTHOR]

This paper proposes a noncooperative game-based planning method for microgrid (MG) considering the interconnection between developing and developed privately-owned clustered MGs on an island. A noncooperative game with imperfect information is designed to regulate the decision-making in planning and operating strategies for rational MG owners. The optimization models for both developing and developed MGs are presented. Different levels of maturity of MG development are modeled by diverse objective functions and constraints, while the data privacy of privately-owned MGs is preserved through imperfect information and prior beliefs. To tackle the seasonality of renewable energy and load on an island, hydrogen storage is considered in the developing MG on the island. Diagonalization and realization are incorporated to develop an effective solving methodology in searching the mixed strategy equilibrium for each MG. The effectiveness of the proposed method is verified using comprehensive case studies. [ABSTRACT FROM AUTHOR]