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This paper aims at the comparison of diversity of the seasonality of unemployment on the labour markets of the West Pomeranian Voivodeship. Analyses concerned the monthly and yearly fluctuations in seasonal unemployment. This paper has also attempted to verify whether on the studied markets there occur dependencies between the number of the unemployed and the number of the seasonally unemployed. The analysis concerned all communes in the West Pomeranian Voivodeship based on the adopted classification of administrative division into rural communes, urban and rural communes, and urban communes. Data applied in the research concerned the monthly number of the unemployed in general from the period of January 2001-December 2015 obtained from the Voivodeship Labour Office in Szczecin. Seasonal components of unemployment were distinguished with the Census X-12 ARIMA algorithm. [ABSTRACT FROM AUTHOR]

Machine learning (ML) has been utilized to predict climatic parameters, and many successes have been reported in the literature. In this paper, we scrutinize the effectiveness of five widely used ML algorithms in the monthly prediction of seasonal climatic parameters using monthly image data. Specifically, we quantify the predictive performance of these algorithms applied to five climatic parameters using various combinations of features. We compare the predictive accuracy of the resulting trained ML models to that of basic statistical estimators that are computed directly from the training data. Our results show that ML never significantly outperforms the statistical baseline, and underperforms for most feature sets. Unlike previous similar studies, we provide error bars for the relative performance of different predictors based on jackknife estimates applied to differences in predictive error magnitudes. We also show that the practice of shuffling data sequences which was employed in some previous references leads to data leakage, resulting in over-estimated performance. Ultimately, the paper demonstrates the importance of using well-grounded statistical techniques when producing and analyzing the results of ML predictive models. [ABSTRACT FROM AUTHOR]

Humidity is one of the most significant climate factors influencing destination decisions and the distribution pattern of vacationers during various seasons. This variable influences the benefit of day-to-day travel industry activities and keeps up the destination competitiveness. In this paper, the univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) model has been applied to conjecture month-to-month humidity for Bangladesh mainstream tourist spots up to the year 2025. Later, the influence of humidity on tourist arrival that contributes to the national economy was also assessed usi ng the Seasonal Analysis of Covariance (SANCOVA) model. Our findings indicate that the Bangladesh tourism industry is more vulnerable to seasonal variation, and this seasonality has a 72% effect on tourist arrival and a 58% effect on overall humidi ty. The findings suggest that if per unit humidity in seasonality increases, then the tourism indus try income will increase by approximately 59.463 thousand Taka (Bangladesh currency) in every season. [ABSTRACT FROM AUTHOR]

Understanding the temporal dynamics and drivers of dissolved inorganic nitrogen (DIN) and dissolved inorganic phosphorus (DIP) provides a critical link to better management of nutrient‐related impacts such as eutrophication and harmful algal blooms (HABs). DIN and DIP are a primary control on persistent eutrophication and HABs in the Pacific Northwest (PNW). An understudied phenomenon, this paper examines multi‐decadal trends in DIN and DIP concentrations and loads, and their relationships to climatic and hydrologic factors (e.g., stream and air temperature, discharge, precipitation) in the PNW. Dissolved constituents act as a broad sentinel of linkages between watershed and in‐stream mechanisms such as nitrification, denitrification, nutrient use efficiency, evapotranspiration, hydrologic connectivity, groundwater extraction, irrigation, and land uses. As opposed to the total N and P often used in individual, autochthonous, lentic systems, DIN and DIP are used here as measures of multiscaled processes in allochthonous lotic systems with diverse flow paths. Time‐series data from public agencies were used for up to 20 years in river outlets from the Willamette, Salmon, Spokane, and Yakima watersheds. Seasonal Mann Kendall (SMK) tests suggest significant decreasing multi‐decadal trends in DIN and DIP loads for three out of four watersheds (for DIN, SMK = −0.104; for DIP, SMK = −0.081, −0.181, and −0.213), significant decreasing trends in DIN concentrations for one of the four watersheds (SMK = −0.144), and significant decreasing trends in DIP concentrations in three of the four watersheds (SMK = −0.120, −0.135, and −0.157). Multivariate regressions found significant relationships for concentrations, loads, and ratios when regressed against stream and air temperatures, precipitation, and discharge (16 significant regressions, with adjusted R2 values between 0.016 and 0.65). Highlights of these regression results are as follows: (1) precipitation, discharge, and water and air temperatures help to explain DIN and DIP concentrations and loads, (2) changes in DIN concentrations are sensitive to more hydroclimatic variables than DIP concentrations, and (3) DIP concentrations are positively correlated with stream temperature while DIP loads are negatively correlated with stream temperature. Furthermore, seasonal changes in nutrients — and their potential to alter aquatic productivity during a year — has received little attention in the literature. Regressions established significant seasonality or monthly variation of DIN and DIP concentrations and loads in all four watersheds (20 significant regressions, with adjusted R2 values between 0.038–0.65). Nutrient thresholds of DIN (0.3–0.5 mg/L) and DIP (0.05–0.005 mg/L) concentrations were used to analyze N‐ and P‐limitation. P‐limitation is known to occur in lakes, and N‐limitation is known to occur in rivers. Surprisingly, except for one watershed (Salmon), nutrient concentrations for both DIN and DIP in all watersheds were shown to be above the limitation thresholds across multiple seasons. In certain situations, such as where significant decreasing trends continue, the DIN:DIP ratio suggests seasonal switching between N‐ and P‐limited could create ideal conditions for HABs. The findings of this study have important implications for water resource management issues such as agriculture, land use development, fish populations, timber harvests, water quality, and public health. [ABSTRACT FROM AUTHOR]

This paper aims to determine the possible impact of the seasonality of agricultural production on the prices of these products. Three main products were analysed, the majority of which are wheat, maize and sunflower production. With the help of national databases, product prices were analysed quantitatively and qualitatively, as well as statistically, over the last 5 years by calendar month. A series of researches have been carried out on the data, such as: analysing the dynamics of both annual and monthly prices, as well as determining the correlations between the price level for these products and the calendar month to which these prices refer. Following this analysis, the third-degree polynomial regression equations were determined, showing that product prices follow a sinuous trend, with high prices in the first part of the year, when supply is running out, then, during the harvesting period, there is a drop in price, given the sudden increase in supply on the market, and in the last months of the calendar year, the highest prices are recorded, given the additional cost of storing production following the harvesting campaign. [ABSTRACT FROM AUTHOR]

Seasonal variations in agriculture is a major contributor to undernutrition in many agrarian economies. While recent studies have highlighted the role of markets in improving nutrition, the relative importance of markets in smoothing food consumption across seasons remains largely unexamined. Using data from Sierra Leone, this paper analyses whether access to local food markets mitigates seasonal fluctuations in household dietary diversity and food security. Our results confirm that agricultural seasonality imposes significant fluctuations on household dietary diversity and food security. Households, especially those in rural areas, are found to experience significant deteriorations in dietary diversity and food security during the lean season. Most importantly, the results also show that households with better market access consume more diverse diets and are more food secure in both lean and non-lean seasons than remoter households. An important policy implication of these results is that market-based interventions aimed at strengthening market access through improved market infrastructure and roads can significantly contribute to year-long food consumption smoothing, improved dietary diversity and overall food and nutrition security. [ABSTRACT FROM AUTHOR]

A coincidence in the timing of floods and their drivers can be used as a proxy for the causality of flood generation. Here, we investigate the relationship between the seasonality of floods, maximum annual rainfall, and maximum annual soil moisture data of 886 basins in Brazil for 1980–2015 to shed light on process controls of flood generation. Floods tend to occur at the same time of year as soil moisture peaks and lag behind rainfall peaks by 3 weeks. In Amazonia, central and northern Brazil, flood timing is more correlated with the timing of soil moisture peaks than with that of rainfall peaks, which is interpreted as resulting from high subsurface water storage capacities. In southern and southeastern Brazil, on the other hand, flood timing is highly correlated with both soil moisture and rainfall because of low subsurface water storage capacities. These findings can support flood forecasting and climate impact studies. Plain Language Summary: In warm regions, floods are usually generated by a combination of intense rainfall and wet soils. In this paper, we analyze the average timing within the year of floods, extreme rainfall, and soil moisture to elucidate how floods come about in the main Brazilian rivers. We find that in some regions, such as Amazonia and central Brazil, floods tend to occur when soils are wet. In other regions, such as southern Brazil, floods tend to occur when rainfall is most extreme. We believe that these differences are related to differences in the soil water storage capacity. The understanding of the regional importance of each of these components helps increase the efficiency of flood prevention measures and climate change adaptation. Key Points: Flood peaks tend to occur at the same time of year as annual soil moisture peaks and lag behind annual rainfall peaks by 3 weeksFlood seasonality is linked mainly with soil moisture peaks in Amazonia and central Brazil, where soil storage capacity is highFlood timing is highly correlated with rainfall and soil moisture peaks in the south and southeast, where soil storage capacity is low [ABSTRACT FROM AUTHOR]

As the impacts of the anthropocene intensifies, there is an increasing need to understand how these changes affect both daily and sub‐daily stream flow variability, timing and flow quantities, as these are some of the most influential drivers of spatial and temporal dynamics of stream biota. In this paper, long‐term changes in flow patterns of a strategic water source area (Luvuvhu catchment) in an arid region of southern Africa were quantified, focusing on the relation between daily and sub‐daily flow and its potential impact on fish biota of the catchment. Long‐term temporal trends in stream flow were modelled using generalized least squares (GLS), while sub‐daily and daily mean flow of the same stations were compared using a suite of metrics. Periods of similar stream flow patterns were identified using K‐means cluster analysis. A spreadsheet rule‐based model was developed linking fish communities to streamflow patterns, providing a predictive framework for fish assemblage responses to stream flow classes. Long‐term reduction in flow in the Luvuvhu catchment has a strong seasonal component, with significant decreases during the wet season, not linked to long‐term rainfall patterns. The flow regime of the Luvuvhu river system has become more variable over time. Several sub‐daily flow metrics were positively related to daily flow metrics. Oscillating flow conditions and the loss of intermediate‐flow states may permanently exclude certain fish flow guilds. However, temporal partitioning is only evident when sub‐daily metrics are considered, highlighting their importance for assessing ecological resilience. [ABSTRACT FROM AUTHOR]

Media impact has significant effect on reducing the disease prevalence, meanwhile sanitation and awareness can control the epidemic by reducing the growth rate of bacteria and direct contacts with infected individuals. In this paper, we investigate the impacts of media and sanitation coverage on the dynamics of epidemic outbreak. We observe that the growth rate of social media advertisements carries out a destabilizing role, while the system regains stability if the baseline number of social media advertisements exceeds a certain threshold. The dissemination of awareness among susceptibles first destabilizes and then stabilizes the system. The disease can be wiped out if the baseline level of awareness or the rate of spreading global information about the disease and its preventive measures is too high. We obtain an explicit expression for the basic reproduction number ℛ 0 and show that ℛ 0 < 1 leads to the total eradication of infection from the region. To capture a more realistic scenario, we construct the forced delay model by seasonally varying the growth rate of social media advertisements and incorporating the time lag involved in reporting of total infective cases to the policy makers. Seasonal pattern in the growth rate of social media advertisements adds complexity to the system by inducing chaotic oscillations. For gradual increase in the delay in reported cases of infected individuals, the nonautonomous system switches finitely many times between periodic and chaotic states. [ABSTRACT FROM AUTHOR]

The aim of this paper is to construct a forecasting model oriented on predicting basic macroeconomic variables, namely: the GDP growth rate, the unemployment rate, and the consumer price inflation. In order to select the set of the best regressors, Bayesian Averaging of Classical Estimators (BACE) is employed. The models are atheoretical (i.e. they do not reflect causal relationships postulated by the macroeconomic theory) and the role of regressors is played by business and consumer tendency survey-based indicators. Additionally, survey-based indicators are included with a lag that enables to forecast the variables of interest (GDP, unemployment, and inflation) for the four forthcoming quarters without the need to make any additional assumptions concerning the values of predictor variables in the forecast period. Bayesian Averaging of Classical Estimators is a method allowing for full and controlled overview of all econometric models which can be obtained out of a particular set of regressors. In this paper authors describe the method of generating a family of econometric models and the procedure for selection of a final forecasting model. Verification of the procedure is performed by means of out-of-sample forecasts of main economic variables for the quarters of 2011. The accuracy of the forecasts implies that there is still a need to search for new solutions in the atheoretical modelling. [ABSTRACT FROM AUTHOR]

The nighttime light (NTL) remote-sensing data have been widely applied in several applications for analyzing the urbanization process. The relationship between NTL intensity and human activity becomes a solid foundation for the applications using NTL data. However, there is no research, so far, revealing how the human activity seasonality could impact the seasonal change of NTL intensity. In this paper, a comparative analysis, box plot, and random forest algorithm were applied to NTL remote-sensing data and points of interest (POIs) data within Shanghai, China. The results show that in spring and autumn, the NTL is much brighter than that in summer and winter, especially within high human activity density area. The NTL intensity can be partly (approximately 40%) explained as the joint effects of the five POI categories. By analyzing the contributions of each POI category to NTL intensity, we found that the National Polar-Orbiting Partnership-Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) could be used to dig more information about gross domestic product (GDP) and traffic-based applications with consideration of NTL seasonality. [ABSTRACT FROM AUTHOR]

This paper examines the relationships among maize prices for four countries to determine if newly emerging exporters, Brazil and Ukraine, influence the international price of maize. Our work focuses on each market's participation in the price discovery process rather than trying to determine a price leader. We find that the United States plays the largest role in price discovery, followed by Argentina, Brazil, and Ukraine. We also search for export thresholds and find that Ukraine's contribution to price discovery rises slightly when an export threshold of 2.3 million tons is reached. No export thresholds were found for Brazil. Export thresholds for Argentina were found but only have a minor impact on price relationships. We also found that price relationships vary considerably across seasons of the year. [ABSTRACT FROM AUTHOR]

Citizens increasingly dispose their waste at household waste recycling centres (HWRC). To enhance the collection of recyclables materials, local authorities and waste management companies invest considerable resources in planning. While the planning of these centres requires a comprehensive understanding of collected solid waste, only limited studies have consistently investigated waste data from HWRC. To fill this knowledge gap, historical data for HWRC from the Greater Copenhagen, Central Zealand, Silkeborg and Djursland in Denmark were analysed with regards to temporal and geographical variation. The results showed the mass of collected waste varies seasonally; this trend was consistently seen during the period 2010–2016. Moreover, the data revealed that the total waste collected was principally driven by the number of visitors. The geometric bar plot and ternary plot depicted an increase in the percentage of recyclable materials, whereas the percentage of incinerated waste decreased during the period 2010–2016. The waste characterisation study indicated that about 7% of small miscellaneous combustible waste was brought in black plastic bag, although these bags were forbidden; the results suggest that the percentage of misplaced recyclable materials could considerably decrease if citizens bring their waste in clear plastic bags. • The core findings of the paper: • Solid waste collected at recycling centres shows a seasonal pattern. • The number of visitors affected significantly the mass of waste collected. • Ternary plot enables to compares waste composition between 36 recycling centres. • Despite the ban, 7% of waste was brought in black plastic bags. [ABSTRACT FROM AUTHOR]

The paper presents a discussion on an opinion about the stability margin towards an emergency in local climate dynamics from the bifurcation analysis viewpoint. With this purpose we propose to attract the practice-oriented bifurcation analysis, where the conflict-of-units between notions used to understand natural evolution processes and notions used to describe desirable artificial regimes is resolved by integrating analytics on the basis of modified bifurcation diagrams. The discussion focuses on the phenomenon of interannual temperature variability, where local annual maximums and minimums are analyzed with daily details in both time and temperature coordinates. This phenomenon is considered via the probable, periodical and regulator conceptions. Advantages of the regulator conception are verified by results of processing the data of temperature meteorological observations on daily means over the last 135 years. This conception is based on the HDS-hypothesis, in accordance to which local climate dynamics is determined by the natural competition between the amplitude quantization (restricted by the temperature Hysteresis) and time quantization (caused by the Double Synchronization). Thus an alternation between three elementary processes with the same period (year) and different patterns of annual warming–cooling cycles is supposed as a typical behavior for local climate systems, and the idea on high-dynamic local climate ensembles is developed instead of the conventional opinion on quasi-static local climate norms. Mechanisms of temperature changes due to abrupt shifts (so-called change-points) of the HDS-regulator parameters are distinguished from mechanisms of temperature changes due to bifurcations. The notion of a stability margin is used as a distance to an emergency and is visualized in the parametrical space. So, in spite of the mechanisms of temperature changes with/without bifurcations are different, their conflict-free sewing becomes conceptually possible in the context of the stability margin towards emergencies determined relatively bifurcation boundaries in the parametrical space. Since the discussed dynamics is not supposed to exist in terms of the traditional estimations concerning the observed local climate changes, then we believe that the paper would be interesting for scientists in the field of bifurcation analysis as well as for scientists and specialists, activity areas of which relate to the contemporary challenges connected with climate changes. [ABSTRACT FROM AUTHOR]

This paper summarizes results from Passenger Origin-Destination Simulator (PODS) research on how dynamic user influence performs under seasonality and system volatility. We explore the revenue results for two different dynamic user influence (UI) strategies—unbiased and biased high-under varying demand levels, with and without hybrid forecasting, under either strong-positive or weak-positive correlation of demand. In short, dynamic UI seeks to emulate revenue management (RM) analysts' attempts to positively influence the RM system. In this study, we use a large "international" network with 572 O-D markets and four different airlines competing for passengers, including a low-cost carrier. The revenue results show that out of 224 individual experiments, we only found eight cases (less than 4%) where there was not a revenue improvement over the comparable base case without dynamic UI. This is a ringing endorsement of the use of dynamic UI, independent of demand level, or forecasting strategy. [ABSTRACT FROM AUTHOR]

Time series is a collection of observations made at regular time intervals and its analysis refers to problems in correlations among successive observations. Time series analysis is applied in all areas of statistics but some of the most important include macroeconomic and financial time series. In this paper we are testing forecasting capacity of the time series analysis to predict tourists' trends and indicators. We found evidence that the time series models provide accurate extrapolation of the number of guests, quarterly for one year in advance. This is important for appropriate planning for all stakeholders in the tourist sector. Research results confirm that moving average model for time series data provide accurate forecasting the number of tourist guests for the next year. [ABSTRACT FROM AUTHOR]

Seasonality, a distinctive feature of the tourism and hospitality industry, refers to the temporal imbalance in tourism demand at a destination. In order to address this issue, the tourism literature often suggests that tourism operators cooperate with each other to create marketing synergies, and that destinations should develop a variety of products and services to cater for different market segments. However, there are limited studies that examine the practicality of these suggestions in the context of small and medium businesses in rural areas. This study addresses this gap via an investigation of the phenomenon of seasonality and its implications for rural tourism destinations. Semi-structured interviews were carried out with 16 local tourism operators and stakeholders in South Gippsland (Victoria, Australia). A key finding revealed in this study is that tourism operators' views towards seasonality and their own mitigation efforts are not necessarily synonymous; hence, this paper speaks to the challenges rural tourism destinations encounter when attempting to take a collective and collaborative approach to seasonality. The paper concludes with recommendations for rural tourism organisations to assist small and medium operators to manage and mitigate the impacts of seasonality. [ABSTRACT FROM AUTHOR]

As part of the Census Bureau’s effort to prove the operational feasibility of the American Community Survey (ACS), the Bureau contracted with local experts to conduct comparative analyses of the 1999–2001 ACS estimates with the 2000 Census data for various test counties. One of the goals of the ACS is to replace the decennial census long form. The resulting research papers analyzed various quality measures (response rates, allocation rates, and so on), conceptual differences in the two instruments, and statistical reliability in an effort to add to our assessment of the ACS as an adequate replacement instrument for collecting long form data. This paper discusses the results of these four research efforts and presents conclusions and recommendations for further Census Bureau action and research. The quality of traditional long form data, the importance of accurate population estimates and an accurate Master Address File (MAF), and continued research on the quality of small area data are discussed. [ABSTRACT FROM AUTHOR]

State‐of‐the‐art flood hazard maps in coastal cities are often obtained from simulating coastal or pluvial events separately. This method does not account for the seasonality of flood drivers and their mutual dependence. In this article, we include the impact of these two factors in a computationally efficient probabilistic framework for flood risk calculation, using Ho Chi Minh City (HCMC) as a case study. HCMC can be flooded subannually by high tide, rainfall, and storm surge events or a combination thereof during the monsoon or tropical cyclones. Using long gauge observations, we stochastically model 10,000 years of rainfall and sea level events based on their monthly distributions, dependence structure and cooccurrence rate. The impact from each stochastic event is then obtained from a damage function built from selected rainfall and sea level combinations, leading to an expected annual damage (EAD) of $1.02 B (95th annual damage percentile of $2.15 B). We find no dependence for most months and large differences in expected damage across months ($36–166 M) driven by the seasonality of rainfall and sea levels. Excluding monthly variability leads to a serious underestimation of the EAD by 72–83%. This is because high‐probability flood events, which can happen multiple times during the year and are properly captured by our framework, contribute the most to the EAD. This application illustrates the potential of our framework and advocates for the inclusion of flood drivers' dynamics in coastal risk assessments. Plain Language Summary: In coastal cities, floods can result from different drivers such as intense rainfall and extreme sea levels. In order to estimate the expected annual damage (EAD) from flooding, it is important to correctly quantify the chance of these events happening and their impacts. Commonly, only the maximum value for a flood driver each year is taken, ignoring its seasonality; and these maxima are assumed to either never or always happen at the same time of the year. These assumptions become problematic when pluvial and coastal floods can occur at different times of the year and sometimes at the same time, such as in Ho Chi Minh City (HCMC). In this paper, we develop a framework to account for the seasonality of flood drivers and their mutual dependencies. Using statistical and hydrodynamic modeling, we generate the equivalent of 10,000 years of rainfall and sea level events and estimate their impact. We find the EAD for HCMC to be $1.02 B. Neglecting the seasonality of rainfall and sea level leads to an underestimation of the EAD by 72–83%. This application illustrates the potential of our framework and advocates for the inclusion of flood drivers' dynamics in coastal risk assessments. Key Points: We develop a flood risk framework based on monthly time series that includes the seasonality and the dependence between flood driversNot accounting for seasonality underestimates the expected annual damage (EAD) in Ho Chi Minh City by 72–83%Rainfall and storm surge are independent for most months but, under the assumption of full correlation, EAD would increase by 15% [ABSTRACT FROM AUTHOR]

Understanding market integration has greatly benefited from analysing and comparing variations in price transmissions. An important source of variation in agricultural markets is seasonal changes in production, consumption and transaction costs. A key factor driving seasonality in agricultural price is temperature, as supply and demand changes are triggered by seasonal temperature differences. In this paper, we study the seasonal variations in vertical price transmission focusing on the asymmetric price adjustment to analyse changes in the market interactions between the stages of the value chain. Our data reveal significant transitory effects of temperature on the price transmission process. Results of a panel threshold model suggest that the farm–wholesale price adjustments to deviations from the market equilibrium are more symmetric at higher temperatures. However, we do not find an effect of temperature on the wholesale–retail price relationship. Our findings can be rationalised with wholesalers making use of their market power to extend their margins in the upstream chain. Wholesaler market power is lower during warm periods, and price adjustment is more symmetric. Concerning the Iranian poultry value chain, our findings imply that temperature‐related differences in market interactions should be considered in formulating policy interventions. [ABSTRACT FROM AUTHOR]

Copyright of Dela is the property of University of Ljubljana, Faculty of Philosophy / Univerza v Ljubljani, Filozofska Fakulteta 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 investigate the combined effects of fear, prey refuge and additional food for predator in a predator–prey system with Beddington type functional response. We observe oscillatory behaviour of the system in the absence of fear, refuge and additional food whereas the system shows stable dynamics if anyone of these three factors is introduced. After analysing the behaviour of system with fear, refuge and additional food, we find that the system destabilizes due to fear factor whereas refuge and additional food stabilize the system by killing persistent oscillations. We extend our model by considering the fact that after sensing the chemical/vocal cue, prey takes some time for assessing the predation risk. The delayed system shows chaotic dynamics through multiple stability switches for increasing values of time delay. Moreover, we see the impact of seasonal change in the level of fear on the delayed as well as non-delayed system. [ABSTRACT FROM AUTHOR]

Fear of predation may assert privilege to prey species by restricting their exposure to potential predators, meanwhile it can also impose costs by constraining the exploration of optimal resources. A predator–prey model with the effect of fear, refuge, and hunting cooperation has been investigated in this paper. The system's equilibria are obtained and their local stability behavior is discussed. The existence of Hopf-bifurcation is analytically shown by taking refuge as a bifurcation parameter. There are many ecological factors which are not instantaneous processes, and so, to make the system more realistic, we incorporate three discrete time delays: in the effect of fear, refuge and hunting cooperation, and analyze the delayed system for stability and bifurcation. Moreover, for environmental fluctuations, we further modify the delayed system by incorporating seasonality in the fear, refuge and cooperation. We have analyzed the seasonally forced delayed system for the existence of a positive periodic solution. In the support of analytical results, some numerical simulations are carried out. Sensitivity analysis is used to identify parameters having crucial impacts on the ecological balance of predator–prey interactions. We find that the rate of predation, fear, and hunting cooperation destabilizes the system, whereas prey refuge stabilizes the system. Time delay in the cooperation behavior generates irregular oscillations whereas delay in refuge stabilizes an otherwise unstable system. Seasonal variations in the level of fear and refuge generate higher periodic solutions and bursting patterns, respectively, which can be replaced by simple 1-periodic solution if the cooperation and fear are also allowed to vary with time in the former and latter situations. Higher periodicity and bursting patterns are also observed due to synergistic effects of delay and seasonality. Our results indicate that the combined effects of fear, refuge and hunting cooperation play a major role in maintaining a healthy ecological environment. [ABSTRACT FROM AUTHOR]

AbstractAccording to archaeological data, Otaria flavescens and Arctocephalus australis were exploited at the mouth of the Santa Cruz River by hunter-gatherers in the late Holocene. These studies suggest the past existence of reproductive colonies from where individuals of different ages were taken, highlighting the offspring available in the austral summer. This paper presents new information on sex, age, and season of death based on the study of teeth growth layers and rings recorded on canines of both species recovered in three archaeological sites located in Punta Entrada, on the southern bank of Santa Cruz River. The results confirm that otariids were captured in the austral summer and show that winter and spring were also important seasons. Prey included females, pups, and adult males captured according to the abundance of each age group at different seasons of the year. These data are in agreement with those obtained from other lines of evidence, such as osteometry and sclerochronology, which indicate this sector of the Patagonian coast was occupied recurrently to hunt otariids as one of the main resources taken by hunter-gatherers when visiting Punta Entrada at different times of the year. [ABSTRACT FROM AUTHOR]

The innovations of battery and charging technologies facilitate worldwide bus electrification, which can conserve energy and reduce emissions. The emergence of wireless power transfer technology offers the potential to alleviate bus range anxiety. This paper constructs the layout models of static wireless and centralized charging stations based on the seasonal differences associated with battery capacities and passenger flow, which aims to obtain the bus charging station layout scheme of the lowest cost. Then, the heuristic algorithm is utilized to solve the layout models as the mixed linear programming problem. This study results confirm that the combined layout of static wireless and centralized charging stations is more advantageous than a single model. Finally, the required fixed cost of supporting bus system operation is explored for future capital reserves. [ABSTRACT FROM AUTHOR]

Due to technological change and growing digitalization of the workplaces, the post-pandemic economic recovery offers opportunities for workers to upgrade their industry-specific skills in different sectors, including tourism, where an increasing shortage in the seasonal tier of the labor market is emerging. Various barriers have been identified as key factors preventing both tourism firms from implementing skill development interventions, and workers from co-investing in training. An under-investigated possible barrier is women's occupational segregation, both horizontal and vertical. This paper looks at the former type of segregation, the most frequent in the tourism industry, by showing that this condition penalizes women's willingness to invest in specific training. Data come from a dedicated survey administered to a sample of seasonal employees who worked in the Rimini Province (Italy) during the summer of 2019 and applies a twofold regression analysis followed by an Oaxaca-Blinder decomposition. Our findings contribute to the debate on gender equality in the tourism industry and on the gendered impact of COVID-19 on workers' careers. [ABSTRACT FROM AUTHOR]

Copyright of lnternational Journal of Geography & Geography Education is the property of Marmara University 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.)

Leaves of European larch, silver birch, and bilberry were sampled 5–7 times per growing season in 2010–2019 in a locality near the city of Litvínov in the Krušné Hory Mts. (Ore Mts.) near the Czech/German border. The locality is characterised by a large amount of plant-available Mn because of acidic soils in the study area. All three investigated plants at the studied site acquired manganese concentrations close to the definition of hyperaccumulation (ca. 10,000 mg kg−1). This paper presents the most detailed collection of plant material for the characterisation of seasonal dynamics of Mn concentrations in the foliage of the three studied plants under field conditions and compares this information with that in published studies. Time (day in the year or day in the growing season) and cumulative precipitation anomalies were major and minor variables, respectively, explaining Mn dynamics in leaves, while temperature and insolation anomalies were not significant. The three investigated species showed plant-specific Mn acquisition rates in the growing season and specific effects of precipitation. Seasonal dynamics must be considered if plant leaves are used for environmental monitoring. [ABSTRACT FROM AUTHOR]

Background: Although Plasmodium falciparum transmission frequently exhibits seasonal patterns, the drivers of malaria seasonality are often unclear. Given the massive variation in the landscape upon which transmission acts, intra-annual fluctuations are likely influenced by different factors in different settings. Further, the presence of potentially substantial inter-annual variation can mask seasonal patterns; it may be that a location has "strongly seasonal" transmission and yet no single season ever matches the mean, or synoptic, curve. Accurate accounting of seasonality can inform efficient malaria control and treatment strategies. In spite of the demonstrable importance of accurately capturing the seasonality of malaria, data required to describe these patterns is not universally accessible and as such localized and regional efforts at quantifying malaria seasonality are disjointed and not easily generalized. Methods: The purpose of this review was to audit the literature on seasonality of P. falciparum and quantitatively summarize the collective findings. Six search terms were selected to systematically compile a list of papers relevant to the seasonality of P. falciparum transmission, and a questionnaire was developed to catalogue the manuscripts. Results and discussion: 152 manuscripts were identified as relating to the seasonality of malaria transmission, deaths due to malaria or the population dynamics of mosquito vectors of malaria. Among these, there were 126 statistical analyses and 31 mechanistic analyses (some manuscripts did both). Discussion: Identified relationships between temporal patterns in malaria and climatological drivers of malaria varied greatly across the globe, with different drivers appearing important in different locations. Although commonly studied drivers of malaria such as temperature and rainfall were often found to significantly influence transmission, the lags between a weather event and a resulting change in malaria transmission also varied greatly by location. Conclusions: The contradicting results of studies using similar data and modelling approaches from similar locations as well as the confounding nature of climatological covariates underlines the importance of a multi-faceted modelling approach that attempts to capture seasonal patterns at both small and large spatial scales. [ABSTRACT FROM AUTHOR]

The paper addresses the problem of change inhibitors in textile and apparel companies. The textile and apparel industry is characterized by high dynamics of sector-specific change, the cyclic nature of its processes, and by changing fashion trends. Companies that change more slowly than their environment are characterized by inertia. The objective of the paper is to identify the factors inhibiting restructuring change in textile and apparel enterprises. The first part of the paper discusses the theoretical aspects of change inhibitors, placing them in the context of the theory of the population ecology approach and the notion of organizational inertia, that refer to the issues of restructuring change inhibitors. The second part offers an empirical illustration of change inhibitors. The study employs a quantitative approach. A linear regression equation is used to determine the factors most strongly inhibiting restructuring change in textile and apparel enterprises. The main inhibitors of restructuring change in the textile and apparel industry are identified. [ABSTRACT FROM AUTHOR]

Human populations are not static or uniformly distributed across space and time. This consideration has a notable impact on natural hazard analyses which seek to determine population exposure and risk. This paper focuses on the coupling of population and environmental models to address the effect of seasonally varying populations on exposure to flood risk. A spatiotemporal population modelling tool, SurfaceBuilder247, has been combined with LISFLOOD-FP flood inundation model outputs for a study area centred on the coastal resort town of St Austell, Cornwall, United Kingdom (UK). Results indicate strong seasonal cycles in populations and their exposure to flood hazard which are not accounted for in traditional population datasets and flood hazard assessments. Therefore, this paper identifies and demonstrates considerable enhancements to the current handling of spatiotemporal population variation within hazard exposure assessment and disaster risk management. [ABSTRACT FROM AUTHOR]

The economic policy directly related to employment and labour force aims the economic growth and the increase of the living standard using the best the capacities of economy: increasing productivity, reducing unemployment, using a larger proportion of working time. This paper aimed to use the statistical and econometric techniques to test and reveal trends in the evolution of the quarterly employment rate in agriculture, and on this basis to extrapolate the investigated characteristic. [ABSTRACT FROM AUTHOR]

The paper presents the results of a study on the collective gardening and dacha movement in the suburban area of Perm. The term "gardening and dacha formations," which combines different types of citizen collective gardening, truck farming, and dacha associations is proposed and substantiated. Such collective formations represent special territorial communities. They exist outside of work time within a limited space, mainly outside the urban environment; they are characterized by seasonal activity and have a particular interaction with the surrounding territory. A methodology for identifying such formations has been developed, their number and features have been revealed, and their territorial distribution has been analyzed. It has been established that most dachas of Perm residents are located in the suburban Perm municipal district. In other areas close to Perm, there are also dachas of other residents of the territory. The paper determines the different territorial levels of gardening and dacha formations, which reflect the features of their interaction with each other and with the nearby territory: site, garden, set, cluster, and area. The factors of the distribution of gardening and dacha formations over the territory are distinguished, and their location is considered, making allowance for the geographic features of Perm krai. The features of gardening and dacha areas specific to the region are identified. [ABSTRACT FROM AUTHOR]

The analysis of atmospheric particles (aerosols) is of special interest due to their potential effects on human health and other applications. In this paper the climatic and seasonal effects on aerosols have been characterized in Tucumán city (26°50' S, 65° 13' W, 450 masl), Argentina, for the 2006–2013 period. The atmospheric aerosols in Tucumán city result from both stationary and mobile sources such as: industrial activity of sugar cane and alcohol distilleries, paper industry, biomass burning (mainly sugarcane waste crop and grasslands), household waste burning and transport emissions. The peak of industrial activity is seasonal, coincident with the austral winter (July-August-September), when accumulation of particles in the lower atmosphere occurs. In this region, there are no studies like the present one that evaluate, using “in situ" equipment, the temporal variation of aerosols and its causes, by applying modern analytical techniques. A continuous volumetric and isokinetic sampler of Hirst type (Burkard), was used for atmospheric particle sampling, in weekly records between 2006 and 2013. The particle concentration (number of particles per cubic meter) showed an increasing trend in the studied period. The monthly variation of: the particle concentration; the aerosol optical thickness at a wavelength of 550 nm (AOD550) obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard Aqua (NASA) satellite, and the AOD from different aerosol tracers (black and organic carbon, sea salt, sulfates, dust) obtained from the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2), were also analyzed. The temporal variation in particle concentration was explained mostly by wind direction, while the corresponding variation for AOD550(MODIS) was explained by temperature and seasonality (as by-product of climatic variation and anthropogenic particle emission sources). The variation in the AOD550(MERRA-2) data series were explained by temperature, humidity, precipitation, and seasonality, with less effect of wind speed and direction. Particle concentration, AOD550(MODIS), and AOD550(MERRA-2) were highly variable. The cross-correlation between AOD550(MODIS) and AOD550(MERRA-2) time series was significantly positive at lag zero. Other contribution was the determination of the space-time distribution of aerosols on a monthly basis considering AOD550 MODIS (3 km × 3 km) data. The present study suggests that these variables are affected by temperature and wind dynamics driven by seasonal and high-order autoregressive non-linear processes. [ABSTRACT FROM AUTHOR]

This paper presents key findings from an 'immersion' that was undertaken in August 2017 on Paquetá and surrounding islands within the Amazon region of Brazil. In this research, immersion is understood as active participation in peoples' lives over a period of time and supported by other methods including observation, semi-structured interviews and co-mapping. This research adapted the urban metabolism concept commonly used to assess levels of sustainability and resilience, for application to the context of peripheral river islands located in the Tocantins river near the Brazilian city of Belém. It specifically focuses on factors that impact on people's behaviour in relation to water management, or what is described here as the 'island water metabolism'. This includes geographic, seasonal, local governance and social dimensions as well as dependence on the rising and falling tides of the river. [ABSTRACT FROM AUTHOR]

People’s health, mood, and activities are closely related to their environment and the seasons. Countries at extreme latitudes (e.g., Sweden, U.K., and Norway) experience huge variations in their light levels, impacting the population’s mental state, well-being and energy levels. Advanced sensing technologies on smartphones enable nonintrusive and longitudinal monitoring of user states. The collected data make it possible for healthcare professionals and individuals to diagnose and rectify problems caused by seasonality. In this paper, we present a personal mobile sensing system that exploits technologies on smartphones to efficiently and accurately detect the light exposure, mood, and activity levels of individuals. We conducted a 2-year experiment with many users to test the functionality and performance of our system. The results show that we can obtain accurate light exposure estimation by opportunistically measuring light data on smartphones, tracking both personal light exposure and the general seasonal trends. An optional questionnaire also provides insight into the correlation between a user’s mood and energy level. Our system is able to inform users how little light they are experiencing in the winter time. It can also correlate light exposure data with reduced mood and energy, and provide quantitative measurements for lifestyle changes. [ABSTRACT FROM PUBLISHER]

In tourism, and not only, the phenomenon of seasonality has negative influences both on the stability of the labor force and on the uniformity of the incomes of the local and regional communities. Starting from this consideration, the paper presents and analyzes the characteristics of the number of tourists' overnight stays in the reception structures with accommodation functions in the Center development area. After a regional analysis, the paper focuses on the evolution of the number of overnight stays of foreign tourists on types of reception structure with accommodation functions. The conclusions highlight, on the one hand, the increase in the phenomenon of seasonality and on the other hand the changes in the weights of the types of tourist accommodation structure in the total overnight stays of the foreign tourists during January 2010 - January 2018. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive spatiotemporal analysis of precipitation patterns over the territory of the Czech Republic for the 1961–2019 period. Monthly, seasonal and annual series of precipitation totals and numbers of precipitation days were calculated for four altitudinal groups and the entire Czech Republic, based upon the daily precipitation totals recorded by 531 rain‐gauge stations run by the Czech Hydrometeorological Institute. Analysis of series of monthly, seasonal and annual precipitation totals revealed relatively stable fluctuations, while linear trends remained largely insignificant. However, wavelet analysis indicated significant interannual variability on a timescale of 4–8‐years in seasonal and annual series. The minimum in annual variation tended to appear in February (also in January and, at higher altitudes in particular, in April) with the maximum favouring July (but also June and August). The relative proportions of annual totals taken up by winter precipitation increased with altitude, while the proportions for summer precipitation decreased with altitude. Linear trends in the numbers of precipitation days exhibited the most pronounced decreases from April to June, reflected in negative precipitation trends in April–June and positive in July–September. The results obtained are also presented in the broader (central) European context. [ABSTRACT FROM AUTHOR]

The low profitability of regional airports is a major impediment to the development of regional aviation. Without subsidies, regional airports struggle to subsist financially. This paper elucidates the various revenue and expenditure heads of Indian airports and discusses the financial status of regional airports. This study also uses panel data from 42 Indian regional airports from 2014–2015 to 2018–2019 to examine the effect of possible determinants on regional airport profits and revenue. Applying Hausman-Taylor regression, the findings indicate that regional airports can expand their profits and revenue primarily by increasing domestic and international passenger flow. Lower levels of seasonality contribute to the airport revenue. Airport capacity utilisation has a favourable and considerable impact on airport profits but not airport revenue. Civil enclaves were found to be profitable. Additionally, the research findings emphasise the unpredictable nature of low-cost carriers and provide managerial implications to policymakers and regional airport operators. • This paper highlights the financial status of regional airports in India. • Lower levels of seasonality contribute to airport revenue. • Airport capacity utilisation has a favourable and considerable impact on airport profits. • Civil enclaves are found to be profitable. • The unpredictable nature of low-cost carriers is emphasised. [ABSTRACT FROM AUTHOR]

According to the definition of the UNWTO, one of the pillars of smart tourism research is the context of seasonality. Based on this approach, the authors aimed to reveal the results of the extent to which field-specific literature addresses this issue. However, regarding the concept of smart tourism, the authors of this study have shown a lack of attention to the relationship between these two logically related areas of tourism research: seasonality and smart tourism. Thus, the study proposed a new approach and possible research directions in connection with seasonality research in the context of smart tourism. [ABSTRACT FROM AUTHOR]

Using maize prices data from Tanzania's National Bureau of Statistics from 2002 through 2017, this paper analyses the impacts of export bans and seasonality on spatial domestic price transmission between deficit markets and the surplus Sumbawanga market; using a vector error correction (VEC) model with export ban and seasonality dummy variables. Results show that 45% of deficit markets converged in the long-run with the Sumbawanga market, with a significant negative sign at 10% level. Moreover, 64% of market pairs negatively impacted spatial domestic price transmission, while seasonality had significant impacts on the same between market pairs. A Granger causality suggests that 63%, 27%, and 10% of market pairs were bidirectional, unidirectional and no causality, respectively. Thus, government policies should incline towards increaseing maize production rather than imposing ad-hoc export bans, improving storage facilities, and mitigating climate changes to insulate seasonality: all of which will--through market mechanism--moderate consumer prices and ensure profitability among maize sellers. [ABSTRACT FROM AUTHOR]