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Institutional discovery environments now serve as central resource databases for researchers in the academic environment. Over the last several decades, there have been numerous discovery layer research inquiries centering primarily on user satisfaction measures of discovery system effectiveness. This study focuses on the creation of a largely automated method for evaluating discovery layer quality, utilizing the bibliographic sources from student research projects. Building on past research, the current study replaces a semiautomated Excel Fuzzy Lookup Add-In process with a fully scripted R-based approach, which employs the stringdist R package and applies the Jaro-Winkler distance metric as the matching evaluator. The researchers consider the error rate incurred by relying solely on an automated matching metric. They also use Open Refine for normalization processes and package the tools together on an OSF site for other institutions to use. Since the R-based approach does not require special processing or time and can be reproduced with minimal effort, it will allow future studies and users of our method to capture larger sample sizes, boosting validity. While the assessment process has been streamlined and shows promise, there remain issues in establishing solid connections between research paper bibliographies and discovery layer use. Subsequent research will focus on creating alternatives to paper titles as search proxies that better resemble genuine information-seeking behavior and comparing undergraduate and graduate student interactions within discovery environments. [ABSTRACT FROM AUTHOR]

Background: Recommended since 2012 by the World Health Organization (WHO), seasonal malaria chemoprevention (SMC) is a community-based intervention to prevent malaria in children in African regions where malaria transmission follows a seasonal pattern. Following the publication of consolidated WHO guidelines for malaria, SMC is expected to reach more children in new geographies in future years. Though SMC has been shown to reduce malaria-related morbidity and mortality, there is potential for quality improvement of the intervention implementation. Assisted by ten quality standards from a framework developed by Malaria Consortium, this paper aims to better understand the quality of SMC implementation and identify potential barriers to quality delivery of SMC. Methods: A qualitative thematic analysis on data collected after the annual SMC rounds implemented in Burkina Faso and Chad in 2019 was conducted. Sixteen focus group discussions conducted with caregivers and community distributors were analysed. Three selected quality standards for SMC delivery; planning and enumeration; community engagement; and administration of SMC medicines provided overarching quality themes under which subthemes were identified. Results: Eight subthemes relating to the three quality standards were identified. Although SMC was well accepted by communities in both settings, common barriers to the quality delivery of SMC were identified including difficulty ensuring adherence to the SMC administration protocol; difficulties reaching mobile populations; concerns around adverse drug reactions; rumours, and concerns about SMC safety; and community distributors' working conditions. Context-specific barriers included: the suboptimal timeliness of the SMC round in Burkina Faso, and the lack of involvement of female caregivers in mobilization activities in Chad. Conclusion: In the context of increased adoption of SMC, this paper provides relevant insights and recommendations for the improved implementation of SMC programmes. These include the integration of strategies addressing communities' concerns around adverse drug reactions, gender-specific mobilization strategies, and attention to community distributors' working conditions. It also highlights the importance and utility of further, robust research on the quality of SMC delivery. [ABSTRACT FROM AUTHOR]

Cooperation among kin is common in animal societies. Kin groups may form by individuals directly discriminating relatives based on kin recognition cues, or form passively through natal philopatry and limited dispersal. We describe the genetic landscape for a primitively eusocial wasp, Polistes dominula, and ask whether individuals choose cooperative partners that are nearby and/or that are genetic relatives. Firstly, we genotyped an entire sub-population of 1361 wasps and found genetic structuring on an extremely fine scale: the probability of finding genetic relatives decreases exponentially within just a few meters of an individual’s nest. At the same time, however, we found a lack of genetic structuring between natural nest aggregations within the population. Secondly, in a separate dataset where ~2000 wasps were genotyped, we show that wasps forced experimentally to make a new nest choice tended to choose new nests near to their original nests, and that these nests tended to contain some full sisters. However, a significant fraction of wasps chose nests that did not contain sisters, despite sisters being present in nearby nests. Although we cannot rule out a role for direct kin recognition or natal nest-mate recognition, our data suggest that kin groups may form via a philopatric rule-of-thumb, whereby wasps simply select groups and nesting sites that are nearby. The result is that most subordinate helpers obtain indirect fitness benefits by breeding cooperatively. [ABSTRACT FROM AUTHOR]

In a previous paper (Feng et al., J. Differential Equations (2023)), we studied a seasonally interactive model between closed seasons and open seasons with Michaelis-Menten type harvesting, in which we assumed that the harvesting quantity was relatively large (0 < κ = l G c E < 1) and obtained a length threshold of the closed season T ¯ ⁎ depending on the harvesting parameter and the seasonal fluctuation period. It was shown that the origin is globally asymptotically stable if and only if T ¯ ≤ T ¯ ⁎ , and there exists a unique globally asymptotically stable T -periodic solution if and only if T ¯ > T ¯ ⁎. In this paper, we continue to investigate the periodic dynamics of this model when the harvesting quantity is relatively small (κ = l G c E ≥ 1). By finding another smaller length threshold T ¯ ⁎ ∈ (0 , T ¯ ⁎) , we determine the number of periodic solutions and study their stability, which imply the occurrence of bifurcation of periodic solutions. Our results demonstrate that designing the closed harvesting season properly can prevent the species from extinction. Moreover, by comparing with the continuous harvesting model and combining the results in our previous paper and this article, we provide a complete understanding on the global dynamics for the periodic switching model. Some numerical simulations are also carried out to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we investigated Cold Air Outbreaks (CAOs) in Hungary using temperature data from ten weather stations located near populous Hungarian cities. Our main motivation for performing this research was the fact that in this rapidly changing climate, these events continue to represent a threat to infrastructure and human life, such as the outbreaks experienced in early 2021 (e.g., Texas, USA) and late 2022 (Winter Storm Elliott). In addition, no comprehensive study of CAOs in Hungary has been conducted using station data. The definition of CAO used in this paper is that the daily mean temperature had to be in the lower 10th percentile of the daily climatology for five consecutive days, and we allowed a maximum two-day gap between periods matching the criteria above, after which we merged events together. We found that the number of CAOs in Hungary decreased considerably in recent decades (due to increasing mean temperatures), and the climates of the investigated stations became increasingly homogenous. Developing our understanding of CAOs around the world is important because, due to climate change, their seasonal distribution may change in a way that negatively impacts our life and economy. [ABSTRACT FROM AUTHOR]

The Snow Cover Service Value (SCSV) is an important component of the ecological assets of the Qinghai–Tibet Plateau (QTP). Exploring the SCSVs on the QTP is the key to maintaining the functions of climate regulators and Asian water towers, and it is also an important theoretical basis for maintaining the ecological security of ecological barrier areas. Using multi-source data such as daily and monthly observation data sets and related statistical yearbooks, an evaluation framework for the SCSVs on the QTP was constructed for the first time. The results showed that the average annual SCSV of the QTP from 2001 to 2020 was 6.99 trillion yuan, and the average annual climate regulation value was 5.81 trillion yuan, which was the most important SCSV. The Inner Plateau Basin, the Brahmaputra Basin, and the Yangtze Basin had the highest SCSVs, while the Yellow Basin had the lowest unit SCSV, where it was the most vulnerable area of snow cover resources on the QTP, and the SCSV of the Yellow Basin was significantly correlated with rainfall. The correlation between the SCSV and the temperature in the Indus and Ganges Basins was significant. The freshwater supply value of the snow in the Indus Basin and Tarim Basin was found to be able to reach 30% of the whole year in June, where it would be necessary to pay attention to the risk of flooding caused by snowmelt during the melting period. Finally, this paper discussed the strategies for the protection and development of snow resources in each basin based on the spatial distribution characteristics, seasonal variation characteristics, and influencing factors of the SCSVs. The research can provide reference for the rational allocation of snow resources and ecological protection on the QTP. [ABSTRACT FROM AUTHOR]

Flash drought is characterized by rapid onset and short-duration drought conditions caused by a combination of factors, including high evaporation, high temperature, and prolonged periods of little to no precipitation, leading to a sudden and severe decrease in soil moisture levels. In comparison to conventional drought, it is more susceptible to the effects of global warming and has the potential to become a common drought phenomenon in the coming years, necessitating further research. In this paper, we focused on flash drought events, specifically in forest parts of northeastern China that are included within the Greater Khingan Mountains (GKM), Lesser Khingan Mountains (LKM), and Changbai Mountains (CM), using daily soil moisture data as well as SPOT- VEGETATION NDVI satellite data from 2000 to 2020 and determined their impact on the forest NDVI. Our major findings are as follows. (1) The forest within GKM had the maximum area being affected by flash drought events. (2) The frequency ranged from 1 to 2 times, whereas the total duration varied between 20 and 55 days over the study area in a 21-year period. (3) Flash drought was most common in the plant-growing seasons. (4) The flash drought events had a negative influence on the forest NDVI. Our study contributes to a deeper understanding of the flash drought dynamics in forest areas of northeast China for flash drought monitoring, prediction, and management strategies in this region. [ABSTRACT FROM AUTHOR]

Vitamin D regulates not only bone metabolism but also many other processes, including the functioning of lymphocytes. Human T cells have a nuclear receptor for vitamin D (VDR). Studies to date have shown significant seasonal variations in conventional T cell populations in humans living in temperate climates. Objectives. The aim of the current paper was an assessment of seasonal changes of γδ T and iNKT cells in healthy individuals. Material and methods. Peripheral blood was drawn from healthy volunteers – approx. 20 a month – and an additional cohort of 20 volunteers donated blood four times, once every four months. Percentages of γδ T and iNKT cells was assessed with flow cytometry. Results. A pronounced accumulation of iNKT cells was noted in spring, the differences in γδ T cells were less notable. Vitamin D significantly hampers γδ T proliferation in vitro. Conclusions. In the presented article, we show seasonal variability within two populations of unconventional T lymphocytes – γδ T and iNKT. [ABSTRACT FROM AUTHOR]

A long-standing problem in meteor science has been the persistent presence of bias in the measured value of atmospheric scale heights obtained from radio meteor echoes. A common practice of fitting a linear function for bias correction follows the assumption that the systematic bias is devoid of seasonal asymmetry. This would be true if the mass and the velocity distribution of meteoroids remain invariant, both spatially and temporally. But so far no such convincing evidence has been published. On the contrary, fundamental arguments suggest that a universal mass function of radio meteoroids is counterintuitive. This parameter cannot remain invariant due to the intrinsic variability in the meteor response function resulting from the Earth's motion on the plane of ecliptic. In this paper, we show that an inverse relation exists between the width of meteor height distribution, expressed in unit of atmospheric scale height, and the exponent of the mass function. The overall mean of this exponent for the Sodankylä radar is |$1.91 \pm 0.02$|⁠ , modulated by a seasonal variation from the mean of the order of |$\sim \pm 0.1$|⁠. The stated inverse relation is applied to correct for the effect of mass distribution on the height distribution. Allowing for variable mass correction effectively removes the non-linear bias in the measured scale heights in the meteor ionization region. [ABSTRACT FROM AUTHOR]

Simple Summary: Since the 1990s, the golden cuttlefish (Sepia esculenta) has become the dominant cuttlefish fisheries target in the seas around China. In this paper, we aim to determine the current resource status and spatio-seasonal variation in the population in the East China Sea region. We found more juveniles at latitudes of 27.50–28.00° N and 29.00° N and more subadult individuals at 28.50° N in autumn, exhibiting different growth rates and resource densities. In addition, we found the majority of the catches were composed of parent groups in spring, while in autumn, the majority of the catches were composed of juvenile groups. We concluded that the subadult groups might have dispersed widely for feeding and growth along the latitude of 30.00° N and to the south in summer, and the southern area of the Yangtze River extending north was the spawning ground in spring. The groups of S. esculenta preferred to stay in areas with a stable water temperature of ~20.00 °C, and many S. esculenta juveniles might have adapted to endure the negative influence of the low oxygen content in summer. The depth range of the S. esculenta population was 10.00–133.00 m from spring to autumn, but this shrank to 66.00–107.00 m in winter. The golden cuttlefish (Sepia esculenta) is an important cephalopod species with a lifespan of approximately one year. The species plays a crucial role in marine ecological support services and is commercially valuable in fisheries. In the seas around China, this species has emerged as the main target for cuttlefish fisheries, replacing Sepiella maindroni since the 1990s. Variations in oceanographic conditions associated with global warming could significantly impact the temporal-spatial distribution of the species. In this study, we performed bottom trawling surveys with four cruises during 2018–2019 in the East China Sea region to determine the current resource status and seasonal-spatial variations in S. esculenta. We found that the average individual weight (AIW) values were 4.87 and 519.00 g/ind at stations located at 30.50° N, 124.00° E and 30.50° N, 124.50° E, respectively, with the aggregation of larvae and parent groups in spring. The species was not distributed north of 32.00° N in summer. The catch per unit effort by weight (CPUEw) value decreased in the order of 2772.50→2575.20→503.29→124.36 g/h, corresponding to latitudes of 34.50° N→34.00° N→33.50° N→32.50° N 121.50° E in autumn. The most suitable fishing areas were the south of the East China Sea region in spring; the south of the East China Sea region extending to the center and outer parts of the East China Sea region in summer; the south of the Yellow Sea close to the Haizhou Bay fishing ground and the forbidden fishing line region of the Lusi and Dasha fishing grounds in autumn; and the south and center of the East China Sea region in winter. The most suitable sea bottom temperature (SBT) values from spring to winter were 14.76–20.53 °C, 19.54–22.98 °C, 11.79–17.64 °C, and 16.94–20.36 °C, respectively. The most suitable sea bottom salinity (SBS) values were 31.53–34.80‰ in spring, 32.95–34.68‰ in summer, 31.51–34.77‰ in autumn, and 33.82–34.51‰ in winter. We concluded the following: (1) the southern and northern areas of the East China Sea region are spawning and nursery grounds, respectively, in spring; (2) the central distribution is located at a latitude of 28.00° N in autumn and winter; and (3) the southern area of the Yangtze River to the north is a spawning ground in spring, and the areas located at 29.00–34.50° N, 124.00–124.50° E, and 28.00–30.50° N, 125.50–126.50° E are nursery grounds. The results of this study provide useful guidance for appropriate fisheries management, thereby avoiding a collapse in the S. esculenta population, which has been experienced in other species in this area. [ABSTRACT FROM AUTHOR]

The paper researches water quality, supply and management system assessment problems of the Montenegrin costal region. A significant problem is generated by seasonal tourism, the main branch of Montenegrin costal economy. The selected performance indicators model has been tested in the water supply system of the city Herceg Novi, as a representative experimental system for the Montenegrin costal area. The city Herceg Novi has 33.000 permanent residents and around 80.000 individual consumers during the summer touristic season. The research activities are based on the seasonal parameters defined by the monitored performance indicators of the water supply system. The study depicts the developed indicators performance model based on the obtained experimental monitoring data. Within the experimental analytical research performance an indicator matrix was established. The coastal area of Montenegro is experiencing over 50 % of water loss. Structure developed in the model applies the performance indicators and results in systematic losses reduction. The model takes into account the principle of seasonality, and the existence of two completely different periods of the year. This type of the experimental research with testing in situ was for the first time performed and implemented in the costal Adriatic region of Montenegro. [ABSTRACT FROM AUTHOR]

The present study majorly focused on the degree of rainfall alteration (DIRA) using an indicator-based novel approach. Most of the previous works majorly focused on only magnitude parameters for measuring monthly rainfall change; however, alteration may also come from other relevant aspects like frequency, timing, rate of change, and duration of rainfall. The present paper considered 33 indicators to assess alterations in rainfall, encompassing various such aspects. Subsequently, it computed the degrees of rainfall alteration categorized as low, moderate, and high range of variability (RVA). This computation was based on the gridded rainfall data endorsed by the Indian Meteorological Department (IMD). Getis-ord was applied to compute the significance of rainfall patterns. The study revealed that middle RVA-based DIRA is low (< 0.33) in the case of magnitude indicators across IMD-defined meteorological sub-divisions, but moderate DIRA (0.33–0.67) was detected in some parts in the case of rate of change, frequency, duration, and timing indicators. This change was detected rather high (moderate to high) over wider parts of India (six and sixteen sub-divisions) in the case of low and high DIRA. In monsoon and post-monsoon seasons, north-eastern hilly hot spots (95–99% level) were weakened, while it was found enhanced in north-western India. A new rainfall hot spot (95%) was identified in Odisha, Telangana, and Vidarbha transition in 1991–2021. Taking into account the notable success achieved through the IRA approach, the study strongly recommends its application across various related domains. [ABSTRACT FROM AUTHOR]

Solar-heating technology is a promising solution to help China achieve the "3060 double carbon" target as soon as possible. Seasonal thermal storage (STS) can effectively solve the mismatch problem of solar-heating systems between the supply and demand of thermal energy. Due to the instability of solar radiation resources and the heat demand, it is necessary to analyze the dynamic response characteristics and operation strategy optimization of the system in different operation stages. Yet, related studies are still scarce. The aim of this paper is to study the switching mechanism of the operation modes and the transitive relation of the system energy in different operation stages based on a pilot solar-heating system with STS in Huangdicheng, northern China. The impacts of different heating strategies on the system performance were also analyzed with a dynamic simulated method in TRNSYS. The results showed that the solar fraction of the system reached 89.4% in the third year, which was 3.6% higher than that in the first year. The quality–quantity heating operation strategies are effective ways to improve the discharge efficiency of the STS and the system performance without a heat pump. The electricity consumption of the pump on the heating side could be significantly reduced by 44.6% compared with the quality control. Ultimately, the findings in this paper are valuable for the optimization of the operation of solar-heating systems. [ABSTRACT FROM AUTHOR]

Background: Quad bikes are popular recreational, four-wheeled bikes in the Middle East. Injury prevention programs targeting quad bike crashes in the United Arab Emirates (UAE) need evidence about the risk factors and behaviours associated with these crashes in the target population. This is a protocol for a study aiming to investigate quad bike rider behaviours and to assess the risk factors associated with related injuries in the UAE. Methods: This is a cross-sectional observational study aiming to describe a seasonal sport in a desert environment. With an estimated sample size of 451, the survey will follow a three-stage, location-based sampling strategy using the line-transect method. A sampling frame of desert locations with high injury incidences was developed, using Dubai ambulance injury records. Further expansion of the sampling frame was participatory, involving police, enthusiasts, emergency responders and gas station employees. The data collection will be limited to the winter months in fifteen high-injury desert locations across three major Emirates in the UAE. Trained researchers will observe the riders directly in the desert to note their riding habits, followed by a researcher-administered interview on riding and injury history. The interviews will be administered in Arabic and English using Qualtrics software on handheld tablets with offline and online entry mode. In addition, paper-based entry with the same format will be used as a contingency in busy quad bike locations. Conclusion: The objective of this study protocol is to develop a comprehensive survey that will furnish substantial evidence for the formulation of effective injury prevention strategies. To enhance the credibility of the recorded riding behaviors, field observations will be employed. The uniqueness of this study lies in its innovative sampling strategy, custom-tailored to accommodate the highly mobile and transient population of desert bikers in the UAE. [ABSTRACT FROM AUTHOR]

This paper deals with the issue of modelling the volatility of futures prices in agricultural markets. We develop a multi-factor model in which the stochastic volatility dynamics incorporate a seasonal component. In addition, we employ a maturity-dependent damping term to account for the Samuelson effect. We give the conditions under which the volatility dynamics are well defined and obtain the joint characteristic function of a pair of futures prices. We then derive the state-space representation of our model in order to use the Kalman filter algorithm for estimation and prediction. The empirical analysis is carried out using daily futures data from 2007 to 2019 for corn, cotton, soybeans, sugar and wheat. In-sample, the seasonal models clearly outperform the nested non-seasonal models in all five markets. Out-of-sample, we predict volatility peaks with high accuracy for four of these five commodities. [ABSTRACT FROM AUTHOR]

Rainfall, with its intensity, duration, and seasonal distribution, is among the main factors causing soil erosion, which is a widespread environmental problem in Bulgaria. Rainfall erosivity shows the potential of precipitation to generate erosion processes and is an essential indicator of the climate vulnerability of a region. This paper aims to evaluate rainfall erosivity in a part of the Eastern Rhodopes Mountains, an area that is characterised by high-intensity erosion processes and high erosion risk. Local peculiarities of rainfall erosivity were revealed by the calculation of some precipitation indices based on the monthly precipitation for the period 2000–2021, such as the precipitation concentration index (PCI), Angot precipitation index, Fournier index (FI), and modified Fournier index (MFI). The analysis of the extremely wet and extremely dry months at the annual and seasonal (October–March and April–September) levels was performed to evaluate the susceptibility to erosion. The results from the study show that rainfall erosivity in the studied area varies from low to moderate in the northern part of the study area and from high to very high in the south. According to the MFI, high and very high erosivities have been observed mainly since 2012. The erosivity increases from north to south, to the area with a complex relief, where the combination of orography and atmospheric circulation make favourable conditions for the occurrence of extreme precipitation. The analyses of the calculated indices show that the precipitations in most of the studied area generally have from a low to a moderate erosivity, but this does not exclude the occurrence of cases with high and very high erosivities, which are characteristic of recent years and are related to the increase in annual precipitations and extreme precipitation months. The results of this study can contribute to the development and implementation of measures and preventive activities for the reduction and possible elimination of the negative impacts of extreme precipitation. [ABSTRACT FROM AUTHOR]

In the present paper, the response of the ionospheric Total Electron Content (TEC) at low latitudes during several geomagnetic storms occurring in different seasons of the year is investigated. In the analysis of the ionospheric response, the following three geomagnetic events were selected: (i) 23–24 April 2023; (ii) 22–24 June 2015 and (iii) 16 December 2006. Global TEC data were used, with geographic coordinates recalculated with Rawer's modified dip (modip) latitude, which improved the accuracy of the representation of the ionospheric response at low and mid-latitudes. By decomposition of the zonal distribution of the relative deviation of the TEC values from the hourly medians, the spatial distribution of the anomalies, the dependence of the response on the local time and their evolution during the selected events were analyzed. As a result of the study, it was found that the positive response (i.e., an increase in electron density relative to quiet conditions) in low latitudes occurs at the modip latitudes 30° N and 30° S. An innovative result related to the observed responses during the considered events is that they turn out to be relatively stationary. The longitude variation in the observed maxima changes insignificantly during the storms. Depending on the season, there is an asymmetry between the two hemispheres, which can be explained by the differences in the meridional neutral circulation in different seasons. [ABSTRACT FROM AUTHOR]

Background: Adaptation to climate change (CC) is a priority for Small Island Developing States (SIDS) in the Caribbean, as these countries and territories are particularly vulnerable to climate-related events. Primary health care (PHC) is an important contributor to CC adaptation. However, knowledge on how PHC is prepared for CC in Caribbean SIDS is very limited. The aim of this paper is to discuss health system adaptation to climate change, with a focus on PHC. Methods: We explored the perspectives of PHC professionals in Dominica on PHC adaptation to climate change. Focus group discussions (FGDs) were conducted in each of the seven health districts in Dominica, a Caribbean SIDS, between November 2021 and January 2022. The semi-structured interview guide was based on the Essential Public Health Functions: assessment, access to health care services, policy development and resource allocation. Data coding was organized accordingly. Results: Findings suggest that health care providers perceive climate change as contributing to an increase in NCDs and mental health problems. Climate-related events create barriers to care and exacerbate the chronic deficiencies within the health system, especially in the absence of high-level policy support. Healthcare providers need to take a holistic view of health and act accordingly in terms of disease prevention and health promotion, epidemiological surveillance, and ensuring the widest possible access to healthcare, with a particular focus on the environmental and social determinants of vulnerability. Conclusion: The primary health care system is a key stakeholder in the design and operationalization of adaptation and transformative resilience. The Essential Public Health Functions should integrate social and climate and other environmental determinants of health to guide primary care activities to protect the health of communities. This study highlights the need for improved research on the linkages between climate events and health outcomes, surveillance, and development of plans informed by contextual knowledge in the SIDS. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a two-species competition model with seasonal succession and different harvesting strategies. We aim to comprehend the impact of the proportion of good season on species competition outcomes and harvesting practices. For the case of weak harvest, we establish proportion thresholds for the good season for the species. Based on these threshold settings, we determine conditions for the existence and uniqueness of two semi-trivial periodic solutions and the existence, uniqueness and stability of positive periodic solutions under certain conditions. Numerical simulations and brief discussions are presented to validate our theoretical findings. [ABSTRACT FROM AUTHOR]

This paper aims to compare the seasonal and diurnal feeding behaviour of cows and calves at Neudamm Farm in central Namibia. Seasonal bite rates of cows, diurnal bites of cows and calves, and diet composition and preference were assessed and compared. Ten cows and ten calves were followed and observed from a distance, in the morning and in the afternoon. The observations were done on the same cows during the wet and dry seasons while calves were only observed during the wet season. The number of bites taken by each animal within a continuous period of 5 minutes was recorded. Herbaceous plant inventory was done in the foraging area using a step-point method. Each herbaceous plant intercepted was assessed for evidence of grazing and its life form was recorded. Bite rates were compared between morning and afternoon, and between seasons using a two-sample t-test. Preference for life forms and species were tested using a Chi-Square test. The morning bite rate of 38 bites/minute of cows during the wet season was significantly higher than that of the morning dry season of 34.9 bites/minute. This is attributed to the high abundance of nutritious forage resources during the wet season when animals did not have to do much searching compared to the dry season. Afternoon bite rates of cows did not significantly differ between seasons. Morning bite rates were significantly lower in the mornings than in the afternoons in winter. This was because cold morning temperatures slowed down animal feeding rates but increased with the progression of the day. Bite rates of calves did not significantly differ between morning and afternoon during the wet season because they were still learning to forage while being dependent on the mothers for milk. Cattle preferred Schmidtia pappophoroides, Eragrostis trichophora, Heteropogon contortus and Eragrostis nindensis due to their palatability and high grazing value. Nidorella resedifolia, despite being very abundant, was avoided because it contains a toxic alkaloid. [ABSTRACT FROM AUTHOR]

This paper compiles the data regarding the first occurrence of Oithona davisae and O. atlantica in NW Spain, which is supported by morphological and molecular analysis. Additionally, we investigated the seasonal dynamics of the invasive O. davisae, revealing that its abundance is conditioned by upwelling-downwelling patterns in the Rías Baixas of Galicia. Temperature was the most correlated factor, with higher abundances in upwelling relaxation-downwelling events. More studies in long-term zooplankton dynamics and molecular analysis are needed to determine if O. davisae is displacing other native species of the same genus, such as O. atlantica, in Galician waters. [ABSTRACT FROM AUTHOR]

Using an aerosol–climate coupled model, this paper has investigated the changes in distributions of anthropogenic and natural particles due to 4 × CO2-induced global warming, under the low emission scenario of Representative Concentration Pathway 4.5 (RCP4.5). Special attention is paid to the seasonal variations of aerosol size modes. With rising CO2 levels, surface warming, and changes in atmospheric circulations and hydrologic cycles are found during both summer (JJA) and winter (DJF). For anthropogenic particles, changes in fine anthropogenic particulate matter (PM2.5, particles with diameters smaller than 2.5 μm) decrease over high-latitude regions and increase over the tropics in both DJF and JJA. Global mean column concentrations of PM2.5 decrease by approximately 0.19 mg m−2, and concentrations of coarse anthropogenic particles (CPM, particles with diameters larger than 2.5 μm) increase by 0.005 mg m−2 in JJA. Changes in anthropogenic particles in DJF are similar to those in JJA, but the magnitudes of maximum regional changes are much smaller than those in JJA. The coarse anthropogenic particles (CPM, particles with diameters larger than 2.5 μm) increase over northern Africa and the Arabian Peninsula during JJA, whereas changes in anthropogenic CPM during DJF are minimal. During both JJA and DJF, changes in anthropogenic CPM are about two orders of magnitude smaller than those of anthropogenic PM2.5. Enhanced wet deposition by large-scale precipitation under rising CO2-induced surface warming is the critical factor affecting changes in anthropogenic particles. For natural particles, the distribution of change in the natural PM2.5 burden is similar to that of natural CPM, but much larger than natural CPM during each season. Both natural PM2.5 and CPM burdens increase over northern Africa and the Arabian Peninsula during JJA, but decrease over most of the continental regions during DJF. Changes in surface wind speed, divergence/convergence of surface wind, and precipitation are primary reasons for the variation of natural particles. [ABSTRACT FROM AUTHOR]

Excessive settlements or failure of piles observed in some Brazilian unsaturated soil sites indicates that the shaft resistance can vary with the seasonal variability of top soil water content, especially in the case of foundations of transmission towers or installed at the periphery of buildings, situations in which the soil is more susceptible to suction fluctuation due to the higher exposure to rainfall action. The objective of the research described in this paper was to provide field evidence with the purpose of alerting practising engineers and to help researchers to better understand the contribution of matric suction on pile capacity. For this aim, the seasonal variability of the shaft resistance of Continuous Flight Auger (CFA) piles in a typical Brazilian unsaturated tropical soil was evaluated by performing axial tensile load tests on eight instrumented CFA piles in different periods of the year. Soil suction was monitored throughout the period of tests, and the results indicate that the shaft resistance of the pile upper part varies considerably during the year and tends to decrease with decreasing soil suction. This work provides valuable insights into the application of unsaturated soil mechanics, which is usually disconnected to classical geotechnical practice. [ABSTRACT FROM AUTHOR]

In recent years, numerous ancient landslides initially triggered by historic earthquakes on the eastern Tibetan Plateau have been reactivated by fault activity and heavy rainfall, causing severe human and economic losses. Previous studies have indicated that short-term heavy rainfall plays a crucial role in the reactivation of ancient landslides. However, the deformation behavior and reactivation mechanisms of seasonal rainfall-induced ancient landslides remain poorly understood. In this paper, taking the Dandu ancient landslide as an example, field investigations, ring shear experiments, and interferometric synthetic aperture radar (InSAR) deformation monitoring were performed. The cracks in the landslide, formed by fault creeping and seismic activity, provide pathways for rainwater infiltration, ultimately reducing the shear resistance of the slip zone and causing reactivation and deformation of the Dandu landslide. The deformation behavior of landslides is very responsive to seasonal rainfall, with sliding movements beginning to accelerate sharply during the rainy season and decelerating during the dry season. However, this response generally lags by several weeks, indicating that rainfall takes time to infiltrate into the slip zone. These research results could help us better understand the reactivation mechanism of ancient landslides triggered by seasonal rainfall. Furthermore, these findings explain why many slope failures take place in the dry season, which typically occurs approximately a month after the rainy season, rather than in the rainy season itself. [ABSTRACT FROM AUTHOR]

Wave energy has emerged as a focal point in marine renewable energy research. Accurate prediction of wave power plays a pivotal role in enhancing power supply reliability. This paper introduces an innovative wave power prediction method that combines seasonal–trend decomposition using LOESS (STL) with a dual-channel Seq2Seq model. The decomposition model addresses the issue of component redundancy in current input decomposition methods, thereby uncovering key components. The prediction model improves upon the limitations of current prediction models that directly concatenate multiple features, allowing for a more detailed consideration of both trend and periodic features. The proposed approach begins by decomposing the power sequence based on tidal periods and optimal correlation criteria, effectively extracting both trend and periodic features. Subsequently, a dual-channel Seq2Seq model is constructed. The first channel employs temporal pattern attention to capture the trend and stochastic fluctuation information, while the second channel utilizes multi-head self-attention to further enhance the extraction of periodic components. Model validation is performed using data from two ocean buoys, each with a five-year dataset. The proposed model achieves an average 2.45% reduction in RMSE compared to the state-of-the-art method. Both the decomposition and prediction components of the model contribute to this increase in accuracy. [ABSTRACT FROM AUTHOR]

A model‐circulation increment‐based dynamic statistical technique (MIDST) is proposed in this paper to improve the prediction of summer rainfall over southern China (SC) where quite low prediction skills have been found in the Beijing Climate Center Climate System Model version 1.1 with a moderate resolution (BCC_CSM1.1m). The results show that BCC_CSM1.1m can hardly represent the variability of the summer rainfall anomaly and its year‐to‐year increment over SC, and the skillful predictions are mostly confined over the middle reaches of the Yangtze River. Using the dynamic model output and statistical method, the MIDST is established to capture the coupled modes between the year‐to‐year increments of the summer rainfall anomaly and the associated simultaneous three‐dimensional coupled air‐sea circulation predictors. The cross‐validation indicates that the prediction skills of the MIDST are evidently improved for both the summer rainfall increment prediction and summer rainfall anomaly prediction compared with the direct BCC_CSM1.1m prediction. The skillful prediction can persist for long forecast leads over most regions except southwestern China. As the major predictability source of seasonal prediction, the intense response to changes in the circulation related to the El Niño‐Southern Oscillation (ENSO) is well captured, and thus, the performance improvement of the MIDST is primarily due to its more realistic representation of the incremental circulation related to the ENSO. [ABSTRACT FROM AUTHOR]

It has been widely recognized that tropical cyclone (TC) genesis requires favorable large‐scale environmental conditions. Based on these linkages, numerous efforts have been made to establish an empirical relationship between seasonal TC activities and large‐scale environmental favorability in a quantitative way, which lead to conceptual functions such as the TC genesis index. However, due to the limited amount of reliable TC observations and complexity of the climate system, a simple analytic function may not be an accurate portrait of the empirical relationship between TCs and their ambiences. In this research, we use convolution neural networks (CNNs) to disentangle this complex relationship. To circumvent the limited amount of seasonal TC observation records, we implement transfer‐learning technique to train ensemble of CNNs first on suites of high‐resolution climate model simulations with realistic seasonal TC activities and large‐scale environmental conditions, and then on a state‐of‐the‐art reanalysis from 1950 to 2019. The trained CNNs can well reproduce the historical TC records and yields significant seasonal prediction skills when the large‐scale environmental inputs are provided by operational climate forecasts. Furthermore, by inputting the ensemble CNNs with 20th century reanalysis products and Phase 6 of the Coupled Model Intercomparison Project (CMIP6) simulations, we investigated TC variability and its changes in the past and future climates. Specifically, our ensemble CNNs project a decreasing trend of global mean TC activity in the future warming scenario, which is consistent with our future projections using high‐resolution climate model. Plain Language Summary: Tropical cyclones (TCs) require favorable large‐scale environmental conditions to form. Pioneer studies show that these conducive conditions include warm sea surface temperatures (SSTs), sufficient low‐level vorticities and mid‐level humilities, as well as weak‐to‐moderate vertical wind shears. Several follow‐up studies have focused on improving the empirical linkage between number of TC and environmental conditions and developed sets of TC genesis index based on conventional statistical methods. Although these indices can capture climatology of TC genesis spatial distributions and seasonal variation reasonably well, their representations of interannual TC variability are degraded. With the aim to better represent TC interannual variability and long‐term trend using large‐scale environmental conditions, we trained ensembles of convolution neural networks (CNNs) based on the combination of observations and large sets of high‐resolution dynamical climate simulations. The trained CNNs perform significantly well in capturing observed TC interannual‐to‐multidecadal variability and are broadly applicable to many areas of seasonal TC activities. Using a deep learning technique, this paper introduces a new potential avenue to improve our understanding of TC variability and future changes. Key Points: Ensemble convolutional neural networks (CNNs) are trained to emulate seasonal tropical cyclone (TC) activity using environmental factorsThe trained CNNs can be utilized to study seasonal TC variability, and their changes in the past, current and future climatesSkillful seasonal TC predictions can be made using CNN‐based statistical‐dynamical hybrid framework [ABSTRACT FROM AUTHOR]

The El Niño Southern Oscillation (ENSO) is a major influence on interannual variability of rainfall in stations in the tropical southwest Pacific. Predictions of seasonal rainfall, especially a season or two ahead, are of great value to these countries. This paper therefore examines the correlations over ~ 60 years between seasonal rainfall and 8 ENSO indicators at 16 island stations, allowing for lead times. The results show the influence on rainfall of the position and movement of the South Pacific Convergence Zone (SPCZ) during ENSO events, and that the Southern Oscillation Index (SOI), the sea surface temperature anomaly in the central Pacific (Niño 3.4), and the warm water volume in the eastern Pacific (WWV1) have longer lead times compared to most other ENSO indicators. These indicators can therefore be used with confidence in SCOPIC, a widely used statistical tool for prediction of seasonal rainfall. (As global climate models generally have systematic errors in their depiction of the SPCZ, they cannot yet be used directly to reliably predict seasonal rainfall in this region.) For several sites near the SPCZ, we find that a moderately good forecast of rainfall in both spring and summer can be made from indicators measured in June–July (i.e., 3–6 months in advance.) [ABSTRACT FROM AUTHOR]

Predicting drought severity is essential for drought management and early warning systems. Although numerous physical model-based and data-driven methods have been put forward for drought prediction, their abilities are largely constrained by data requirements and modeling complexity. There remains a challenging task to efficiently predict categorial drought, especially for the U.S. Drought Monitor (USDM). Aiming at this issue, multiple Markov chains for USDM-based categorial drought prediction are successfully proposed and evaluated in this paper. In particular, this study concentrated on how the Markov order, step size, and training set length affected prediction accuracy (PA). According to experiments from 2000 to 2021, it was found that the 1-step and first-order Markov models had the best accuracy in predicting droughts up to 4 weeks ahead. The PA steadily dropped with increasing step size, and the average accuracy at monthly scale was 88%. In terms of seasonal variability, summer (July-August) had the lowest PA while winter had the highest (January-February). In comparison with the western region, the PA in the eastern United States is 25% higher. Moreover, the length of the training set had an obvious impact on the PA of the model. The PA in 1-step prediction was 87% and 78% under 20- and 5-yr training sets, respectively. The results of the study showed that Markov models predicted categorical drought with high accuracy in the short term and showed different performances on time and space scales. Proper use of Markov models would help disaster managers and policy makers to put mitigation policies and measures into practice. [ABSTRACT FROM AUTHOR]

This paper presents a novel method for finding features in the analysis of variable distributions stemming from time series. We apply the methodology to the case of submitted and accepted papers in peer-reviewed journals. We provide a comparative study of editorial decisions for papers submitted to two peer-reviewed journals: the Journal of the Serbian Chemical Society (JSCS) and this MDPI Entropy journal. We cover three recent years for which the fate of submitted papers—about 600 papers to JSCS and 2500 to Entropy—is completely determined. Instead of comparing the number distributions of these papers as a function of time with respect to a uniform distribution, we analyze the relevant probabilities, from which we derive the information entropy. It is argued that such probabilities are indeed more relevant for authors than the actual number of submissions. We tie this entropy analysis to the so called diversity of the variable distributions. Furthermore, we emphasize the correspondence between the entropy and the diversity with inequality measures, like the Herfindahl-Hirschman index and the Theil index, itself being in the class of entropy measures; the Gini coefficient which also measures the diversity in ranking is calculated for further discussion. In this sample, the seasonal aspects of the peer review process are outlined. It is found that the use of such indices, non linear transformations of the data distributions, allow us to distinguish features and evolutions of the peer review process as a function of time as well as comparing the non-uniformity of distributions. Furthermore, t- and z-statistical tests are applied in order to measure the significance (p-level) of the findings, that is, whether papers are more likely to be accepted if they are submitted during a few specific months or during a particular "season"; the predictability strength depends on the journal. [ABSTRACT FROM AUTHOR]

Background: Phlebotomus (Paraphlebotomus) sergenti is a widespread proven vector of Leishmania pathogens causing anthroponotic cutaneous leishmaniasis (ACL), due to L. tropica, in the old world. The activity of P. (Par.) sergenti is seasonal and sensitive to general variations in climate. Phenological data sets can thus provide a baseline for continuing investigations on P. (Par.) sergenti population dynamics that may impact future leishmaniasis transmission and control scenarios. Methods/Principal finding: A systematic review of the seasonality of P. (Par.) sergenti was undertaken globally. Sixty-eight scientific papers were identified, and data were extracted from 35 ones, with informative data on sand fly seasonal dynamics on trapping performed from 1992 to December 2021 on 63 sites from 12 countries. Morocco, Saudi Arabia, Iraq, Iran, Pakistan, Palestine, Turkey, Spain, Portugal, Italy, Cyprus, and Georgia. The data extracted from the literature survey were further normalized. Our analysis recorded that the highest P.(Par.) sergenti activity occurs during the hot and dry seasons, primarily in July and August, whatever the location studied. We noticed a relationship between the latitude of sites and sand fly presence (from early April to June) and the type of density trend, varying from a single peak to multiple peaks. On a geographical scale, P. (Par.) sergenti concentrates between 32–37° in latitude in a large interval following the longitude and the highest number of sites with high P. (Par.) sergenti activity is located at the latitude 32°. We also quoted a similar seasonal dynamic and geographic distribution with Phlebotomus (Phlebotomus) papatasi, a proven vector of L. major that causes cutaneous infection. No apparent risk for ACL occurred from December to March, at least in the years and geographic areas considered in this survey. Altogether, knowing that high P. (Par.) sergenti activity would be linked with an increased risk of leishmaniasis transmission, and our study provides information that can be used for control programs on ACL transmission. Conclusions: Despite variations, we found a relatively homogeneous pattern of P. (Par.) sergenti potential behavior in sites whose data are published. A higher risk for L. tropica transmission was identified in the June-October period. Still, such risk was not equally distributed throughout the area since density waves of adults occurred earlier and were more frequent in some territories, like Saudi Arabia. Author summary: Phlebotomus (Paraphlebotomus) sergenti is the most widespread vector of Leishmania pathogens causing anthroponotic cutaneous leishmaniasis (ACL) in the old world. This paper undertook a systematic review of seasonality on a global geographical scale. This systematic analysis allowed us to identify 608 scientific papers, 35 of which 63 sites were explored in 12 countries from 1992 to December 2021. In the current review, Iran (Southern Asia) is the most influential country regarding the number of studies published on P. (Par.) sergenti seasonality with available data. Furthermore, the highest P. (Par.) sergenti activity occurs in all studied locations during the hot and dry periods (with a density that peaked during the hot season, primarily in July and August). Strikingly, we recorded a similar seasonal dynamic and geographic distribution with Phlebotomus papatasi, a proven vector of L. major causing cutaneous leishmaniasis. On a geographical scale, sites with P. (Par.) sergenti activity concentrate between 32–37° in latitude in a large interval following the longitude, with the highest number of sites with high P. (Par.) sergenti activity is located at the latitude 32°. Altogether, knowing that high P. (Par.) sergenti activity would be linked with an increased risk of leishmaniasis transmission. Our study provides information that can be used for control programs on ACL transmission. [ABSTRACT FROM AUTHOR]

In this paper, we establish and study a novel predator–prey model that incorporates: (i) the migration of prey between breeding and non-breeding regions; (ii) the refuge effect of prey; and (iii) the reduction in prey pulse birth rate, in the form of a fear effect, in the presence of predators. Applying the Floquet theory and the comparison theorem of impulsive differential equations, we obtain the sufficient conditions for the stability of the prey-extinction periodic solution and the permanence of the system. Furthermore, we also study the case where the prey population does not migrate. Sufficient conditions for the stability of the prey-extinction periodic solution and the permanence are also established, and the threshold for extinction and permanence of the prey population is obtained. Finally, some numerical simulations are provided to verify the theoretical results. These results provide a theoretical foundation for the conservation of biodiversity. [ABSTRACT FROM AUTHOR]

This paper analyzes the effect of the Australian High (AH) on the seasonal phase locking of Indian Ocean Dipole (IOD) events. The anomalous strong AH associated with the positive phase of the Antarctic Oscillation can cause significant easterly wind anomalies and northward cross‐equatorial flow over the western Maritime Continent (MC) by strengthening the Australian winter monsoon during May–August. The AH‐associated easterly anomalies and northward cross‐equatorial flow can create thermodynamic air‐sea feedback and contribute to a significant cooling anomaly in the western MC and the tropical eastern Indian Ocean. Without considering the effect of ENSO, these processes contribute to the occurrence of positive IOD events, which begin in early summer, peak in late summer, and decay rapidly thereafter. The effect of ENSO can extend the peak period of IOD into the boreal autumn of that year. An anomalous weak AH corresponds to the occurrence and seasonal phase locking of negative IOD events. Through combined empirical orthogonal function analysis, we find that the effect of the AH can well explain the seasonal phase locking of 34 IOD events (40 in total), which provides an important theoretical basis for the prediction of IOD events. Plain Language Summary: Seasonal phase locking is a critical characteristic of typical Indian Ocean Dipole (IOD) events. The IOD usually develops in boreal summer, peaks in autumn, and decays rapidly in winter. Note that the Australian High (AH) plays a key role on the seasonal phase locking of IOD events. It is found that The anomalous strong AH associated with the positive phase of the Antarctic Oscillation (AAO) can cause significant easterly wind anomalies and northward cross‐equatorial flow over the western Maritime Continent by strengthening the Australian winter monsoon during May–August. Key Points: Investigate the effect of Australian High (AH) the on the seasonal phase locking of Indian Ocean Dipole eventsThe Antarctic Oscillation can strengthen AH and Australian winter monsoonThe AH induced easterlies and cross‐equatorial flow contribute to a significant cooling anomaly in the tropical eastern Indian Ocean [ABSTRACT FROM AUTHOR]

This paper studies the spatiotemporal variability of the IRt index (defined as the difference between the percentage of precipitation corresponding to warm days and cold days in year t) calculated at 35 stations in the Iberian Peninsula during 1951–2019. Spatial variability is estimated using cluster analysis (Euclidean distance, Ward's method), which allows regionalization of the data set for each year's season. For each cluster, the < IR > index is defined as the average of the indexes corresponding to each cluster element. The temporal evolution of the < IR > indices is analyzed by studying the appearance of trends using the Mann–Kendall test and the possible existence of various subperiods using the cumulative sum of deviations and the t-test for the difference between the means. The role of EA, EA/WR, NAO, SCAN and WeMO teleconnection patterns in modulating the relationship between temperature and precipitation is analyzed by applying multiple regression analysis. The results show a trend towards positive (or less negative) values in the relationship between temperatures and precipitation (of varying magnitude depending on the region and season) and the contribution of atmospheric dynamics to these changes. [ABSTRACT FROM AUTHOR]

Owing to probabilistic uncertainties associated with seasonal forecasts, especially over areas such as southern Africa where forecast skill is limited, non-climatologists and users of such forecasts frequently prefer them to be presented or distributed in terms of the likelihood (expressed as a probability) of certain categories occurring or thresholds being exceeded. Probabilistic forecast verification is needed to verify such forecasts. Whilst the resulting verification statistics can provide clear insights into forecast attributes, they are often difficult to understand, which might hinder forecast uptake and use. This problem can be addressed by issuing forecasts with some understandable evidence of skill, with the purpose of reflecting how similar forecasts may have performed in the past. In this paper, we present a range of different probabilistic forecast verification scores, and determine if these statistics can be readily compared to more commonly known and understood ‘ordinary’ correlations between forecasts and their associated observations – assuming that ordinary correlations are more intuitively understood and informative to seasonal forecast users. Of the range of scores considered, the relative operating characteristics (ROC) was found to be the most intrinsically similar to correlation. [ABSTRACT FROM AUTHOR]

The Western Ghats (WG) is one of the important biodiversity hotspots and rainfall intense regions in south Asia. In this paper, the long-term trend analysis is carried out during southwest monsoon rainfall over different latitudinal regions of the WG. Further, the gridded daily rainfall data (0.25 × 0.25 spatial grid resolution) is classified into six intensity bins: dry, low, moderate, heavy, very heavy, and extreme, from 1951 to 2015. A detailed trend and variability analysis of rainfall and its frequency in different intensity bins along with their relative contribution were carried out. The results of different rainfall intensity bins depict that the moderate and low intensity bins contribute a maximum share in seasonal rainfall with 45% and 20%, respectively, from the 30% and 50% rainy days in all the regions. Heavy and very heavy intensity bins together contribute about 30% of the seasonal rainfall from about 9% rainy days. Extreme intensity bin recorded an alarming share of 6% with only 1% rainy day occurrences. In general, the relative contribution shows an ascending pattern of moderate, low, very heavy, heavy, extreme, and dry intensity bins. A decreasing trend in rainfall was observed in heavy and very heavy intensity bins, while other intensity bins illustrated mixed trends in different study regions. Extreme rainfall events marked a major shift upward in the WG region during the study period. Overall, our result portrays a negative trend in rainfall during the southwest monsoon season over all the study regions during the study period. [ABSTRACT FROM AUTHOR]

This paper proposes a selection strategy for determining the optimal capacity and location of a static synchronous compensator (STATCOM) device under intermittent output variations of renewable energy sources using a multi-objective cuckoo search (MOCS) algorithm. The impact of seasonal output variations on the location and capacity of the STATCOM devices was analyzed based on the daily output variations of the wind turbines. Three objective functions were considered to determine the optimal location and capacity of the STATCOM devices: (1) minimizing the system line losses, (2) minimizing the transient voltage indicators, and (3) minimizing the total cost of the STATCOM capacity. MOCS was combined with the Pareto front to determine the non-dominated solution sets for the four seasons. The Manhattan distance method was used to select the most suitable installation locations and capacities within a specified time interval. Power flow calculations were performed using DIgSILENT Power Factory 2021 and MATLAB R2021b. To validate the proposed method, a test experiment was conducted using an IEEE 39 bus system. [ABSTRACT FROM AUTHOR]

This paper aimed to characterise Brazilian participation in the Summer Paralympic Games between 1972-2020 and relate it to the historical-national, political and Brazilian Paralympic Committee's strategic plan for the paralympic cycles. This paper also intended to compare Brazilian's results with the best-ranked countries in Rio 2016. Until 2020, the Brazilian delegation was represented by 774 athletes, 251 of whom were medalists (70.9% men and 29.1% women) in 17 different sports, four collective and thirteen individuals. Regarding disability type, 64.9% of the medalist athletes have a physical impairment, 32.3% visual impairment and 2.8% intellectual impairment. During the analysed period, Brazil won 373 medals: 109 gold (29.2%), 132 silver (35.4%) and 132 bronze (35.4%). In conclusion, it is possible to highlight that the improvement in public policies, strategic plans and investments has favoured Brazilian's results. In the last four Paralympic cycles, Brazil could consolidate itself, winning the largest number of medals in 2016 and reaching third place in accumulated growth (3.2%) between 1988-2020, surpassed only by China and Ukraine. [ABSTRACT FROM AUTHOR]

Condensation and sublimation of ices at the surface of the planet is a key part of both the Martian H2O and CO2 cycles, either from a seasonal or diurnal aspect. While most of the ice is located within the polar caps, surface frost is known to be formed during nighttime down to equatorial latitudes. Here, we use data from the Emirates Mars Infrared Spectrometer onboard the Emirates Mars Mission to monitor the diurnal and seasonal evolution of the ices at the surface of Mars over almost one Martian year. The unique local time coverage provided by the instrument allows us to observe the apparition of equatorial CO2 frost in the second half of the Martian night around the equinoxes, to its sublimation at sunrise. Plain Language Summary: The H2O and CO2 ices that form at the surface on Mars play an important role in the exchange between the atmosphere and the surface of the planet. While most of the ice is located within the two polar caps that grew and shrink seasonally, ice is also known to condensate as surface frost during the night and sublimate during the day. This nighttime surface frost deposition can be observed even at equatorial latitudes. In this paper we use data from the Emirates Mars Infrared Spectrometer onboard the Emirates Mars Mission to detect the H2O and CO2 ices at the surface of the planet at all local times over almost one Martian Year, which allows us to monitor both the seasonal and diurnal evolution of the distribution of ices at the surface of Mars. We observe that nighttime CO2 frost forms at equatorial latitudes in the second half of the night to disappear at sunrise around the Martian equinoxes. Key Points: We monitor the seasonal growth and retreat of both polar caps over MY 36We monitor the presence of CO2 ice on the surface of Mars over MY 36, through the season and through all times of dayCO2 ice appears at the surface at equatorial latitudes during the second half of the night around the equinoxes [ABSTRACT FROM AUTHOR]

This paper presents an analysis of future precipitation patterns over the Lake Victoria Basin, East Africa, using bias-corrected CMIP6 model projections. A mean increase of about 5% in mean annual (ANN) and seasonal [March–May (MAM), June–August (JJA), and October–December (OND)] precipitation climatology is expected over the domain by mid-century (2040–2069). The changes intensify towards the end of the century (2070–2099) with an increase in mean precipitation of about 16% (ANN), 10% (MAM), and 18% (OND) expected, relative to the 1985–2014 baseline period. Additionally, the mean daily precipitation intensity (SDII), the maximum 5-day precipitation values (RX5Day), and the heavy precipitation events—represented by the width of the right tail distribution of precipitation (99p–90p)—show an increase of 16%, 29%, and 47%, respectively, by the end of the century. The projected changes have a substantial implication for the region—which is already experiencing conflicts over water and water-related resources. [ABSTRACT FROM AUTHOR]

To accurately predict the time series of energy data, an optimized Hausdorff fractional grey seasonal model was proposed based on the complex characteristics of seasonal fluctuations and local random oscillations of seasonal energy data. This paper used a new seasonal index to eliminate the seasonal variation of the data and weaken the local random fluctuations. Furthermore, the Hausdorff fractional accumulation operator was introduced into the traditional grey prediction model to improve the weight of new information, and the particle swarm optimization algorithm was used to find the nonlinear parameters of the model. In order to verify the reliability of the new model in energy forecasting, the new model was applied to two different energy types, hydropower and wind power. The experimental results indicated that the model can effectively predict quarterly time series of energy data. Based on this, we used China's quarterly natural gas production data from 2015 to 2021 as samples to forecast those for 2022–2024. In addition, we also compared the proposed model with the traditional statistical models and the grey seasonal models. The comparison results showed that the new model had obvious advantages in predicting quarterly data of natural gas production, and the accurate prediction results can provide a reference for natural gas resource allocation. [ABSTRACT FROM AUTHOR]

Four years of Indian Institute of Tropical Meteorology lightning location network lightning observation data are used to determine the seasonal and spatial (over different geographical locations) distribution of the ratio of intra‐cloud (IC) lightning to cloud‐to‐ground (CG) lightning in thunderstorms over the Indian subcontinent. The ratio is high (6–10) in the northwestern parts and low (0.5–3.5) in the northeastern parts. No prominent latitudinal variation of the IC to CG ratio exists, but a climatological seasonal variability exists over all regions. In the pre‐monsoon season (March–May), the mean ratio is observed to be 3.81 with a standard deviation of 0.79, and during the monsoon season (June–September), a value of 3.04 with a standard deviation of 0.50. Although convective available potential energy is the regulating factor, little dependency has been found between the ratio of IC to CG lightning (IC:CG ratio) and the total flash rate (f), as well as with cold cloud depths. The ratio is observed to be proportional to the total flash rate as f0.61. The cold cloud depth is most prominently linked with the regional and seasonal IC:CG ratio. The implication of these observed results has the importance of separating CG lightning flash from total and can be used in numerical models to give a proper prediction of CG lightning in hazard mitigation. Plain Language Summary: Pre‐monsoon thunderstorms exhibit more intra‐cloud (IC) discharge than monsoonal thunderstorms; hence, the IC:cloud‐to‐ground (CG) ratio is also high in pre‐monsoon. In this paper, we have shown that CG lightning is approximately 20% of total lightning in pre‐monsoon whereas 25% of total lightning in monsoon all over the Indian region. A stronger vertical updraft associated with high convective available potential energy enhances the cold cloud depth. It may expand the mixed phase region, which can broaden and uplift the size of the upper positive charge center inside a thunderstorm. In contrast, the middle negative charge center remains at the same temperature level. Therefore, this process may enhance IC discharge between the upper positive charge center and the middle negative charge center, increasing the IC:CG ratio of a thunderstorm. Key Points: The mean intra‐cloud:cloud‐to‐ground (IC:CG) ratio remains high in the Pre‐monsoon season compared to the Monsoon season over the Indian land massThe high cold cloud depth associated with stronger updrafts expand the mixed‐phase region and increases the IC flash rate and IC:CG ratioHigh flash rate associated with high IC flash occurrences is also responsible for a high IC:CG ratio [ABSTRACT FROM AUTHOR]

Describing the acoustic repertoire of cetaceans is necessary to understand the functionality of their sounds and the effect anthropogenic pressures have on animals living in a marine environment. This study provides a description of the acoustic repertoire of bottlenose dolphins (Tursiops truncatus) in the Cres-Lošinj archipelago based on continuous 24-h recordings collected from two monitoring stations, both inside and outside the Natura 2000 Site of Community Importance, during an 8-day period in March/April 2020 and a 13-day period in July/August 2020. A total of 1008 h were visually and aurally analyzed to identify vocalizations and investigate diel and seasonal patterns in their parameters. Furthermore, sound pressure levels were calculated for the low (63 Hz–2 kHz) and high (2 kHz–20 kHz) frequency range. Bottlenose dolphins in the Cres-Lošinj archipelago were found to produce whistles, chirps, low frequency narrow-band sounds, burst pulse sounds, and echolocation clicks showing that dolphins are present at both monitoring stations, during both diel and seasonal periods, in a comparable manner. This paper also provides evidence that whistles, chirps, and low frequency narrow-band sounds change their parameters in relation to the background noise in the area, that varies according to diel and seasonal patterns. This suggests a vocal plasticity in the species and a coping strategy to avoid masking of relevant acoustic signals for the local population in the Cres-Lošinj archipelago. [ABSTRACT FROM AUTHOR]

Previous work on ocean acidification highlighted contrasting response between marine species and population. This so-called species-specific response was hypothesized to be partly a consequence of local adaptation to the present range of natural variability in the carbonate chemistry. Under that hypothesis, species tolerance threshold should be correlated to its environmental pH niche. This paper aims to evaluate shell growth rate of Hexaplex trunculus, an important predatory gastropod in benthic communities of Mali Ston Bay. A long-term experiment (310 days) was designed to test a range of pH treatments covering present and future pH levels relevant in the context of future ocean acidification (7.95-7.22 pHT ) at the sampling site. Sex had an effect on the shell growth rate irrespective of pH, and was only significant after 236 days. As growth rate in all pH treatments followed seasonal patterns correlating to changes in seawater temperature, the data were divided into 3 time periods. A positive relationship between shell growth rate (SGR, mm day-1) and pH was observed for the period 1-59 days (temperature ranging between 26.5 & 18.8 °C), whereas SGR decreased significantly with pH for the following period (60-236 days, temperature ranging between 20.6 & 8.5 °C). After 236 days (temperature ranging between 27.5 & 14.1 °C), there was no significant difference in SGR among pH. Similar temperature was experienced between the first and third period and the difference in response could be explained as a consequence of an acute negative response versus a longer exposure indicating possible potential for acclimation. Our results highlight the modulating effect of temperature and the importance of long-term experiments to better assess impacts of ocean acidification on marine organisms. [ABSTRACT FROM AUTHOR]

Energy shortage has always been a problem that the world needs to face. The combined cooling, heating, and power (CCHP) system, as a multi-level energy utilization system that can provide cooling, heating, and electric energy simultaneously, is considered to have good development prospects in alleviating energy problems. In addition, because of the rapid development of electric vehicles (EVs), using EVs as power supply devices has become a hot topic of research. In this paper, EVs are combined with the CCHP system as new power supply equipment, and the influence of the season on the user's cooling, heating, and power demand is considered. Aiming at the minimum economic cost, the system is optimized by using the PSO algorithm in two operating modes: following electricity load (FEL) and following thermal load (FTL). The final results show that the participation of EVs can reduce costs in both operating modes, especially in FTL mode, which can reduce costs by 4.58%, 13.61%, 12.74%, and 3.57% in spring, summer, autumn, and winter, respectively. In addition, the FEL mode is more economical in spring and winter, and the FTL mode is more economical in summer and winter. In addition, the C O 2 emissions in FEL mode are always less than in FTL mode. [ABSTRACT FROM AUTHOR]

In this paper, we formulate a seasonally interactive model between closed seasons and open seasons with Michaelis-Menten type harvesting based on some management and capture methods of renewable resources. It is assumed that the population growth obeys the logistic equation in closed seasons and is captured following Michaelis-Menten type response function in open seasons. We define a length threshold of the closed season T ¯ ⁎ , which depends on the harvesting parameter. Under the extinct condition of the corresponding continuous harvesting model, by setting the closed season, theoretical results show that the origin is globally asymptotically stable if and only if T ¯ ≤ T ¯ ⁎ , and there exists a unique globally asymptotically stable T -periodic solution if and only if T ¯ > T ¯ ⁎. In particular, under the critical conditions on special harvest parameters, it is found that the T -periodic solution still exists as long as an arbitrary positive close season is formulated. Numerical examples are carried out to confirm the obtained theoretical results. Brief conclusions and discussions on our findings are also provided. [ABSTRACT FROM AUTHOR]

Rainfall onset dates (ROD), rainfall cessation dates (RCD) and length of rainy season (LRS) are crucial for crop production and food security in Eastern Africa yet scantily documented. This paper seeks to investigate the spatial patterns of these parameters. Data used are Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS v2.0) and National Oceanic and Atmospheric Administration (NOAA) gridded temperature. Threshold of 1 mm for rainy day, 20 mm over 5 days with at least 3 rain days and dry spell not exceeding 7 days in the next 21 days were used to determine RODs. The Potential Evapotranspiration (PET) and Water Balance (WB) criteria were computed to determine RCDs. The differences between ROD and RCD were used in calculating LRS. The results showed early rainfall cessation over more than 30 counties in Kenya lead to shortened rainy season by 10–20 days during MAM season. Similarly, 20–40 days early onset dates are observed in most counties in upper Nile, Unity, and Jonglei states in South Sudan, while 20–40 days delayed rainfall onset was observed in Khartoum and southern parts of Nile state western Darfur, eastern and Aljazeera states in Sudan, most parts of Ethiopia and Eritrea districts during JJA season. Highlands of western and Nyanza region in Kenya, most parts of Uganda observed rainfall onset by March and no sign of cessation before November. Early cessation over northern Uganda districts was behind shortened LRS, furthermore, the early RODs over western and southwestern Uganda districts increased LRS. Prolonged dry conditions over northern Sudan, southeastern parts of South Sudan, northern Kenya, central Somalia, northern Darfour, Kordofan and northern parts of Sudan exacerbated by significant delayed onset and early cessation of rainfall. These findings are important for rain-fed agricultural planning and food security in the IGAD region of Eastern Africa. [ABSTRACT FROM AUTHOR]

Accurate medium- and long-term power load forecasting is of great significance for the scientific planning and safe operation of power systems. Monthly power load has multiscale time series correlation and seasonality. The existing models face the problems of insufficient feature extraction and a large volume of prediction models constructed according to seasons. Therefore, a hybrid feature pyramid CNN-LSTM model with seasonal inflection month correction for medium- and long-term power load forecasting is proposed. The model is constructed based on linear and nonlinear combination forecasting. With the aim to address the insufficient extraction of multiscale temporal correlation in load, a time series feature pyramid structure based on causal dilated convolution is proposed, and the accuracy of the model is improved by feature extraction and fusion of different scales. For the problem that the model volume of seasonal prediction is too large, a seasonal inflection monthly load correction strategy is proposed to construct a unified model to predict and correct the monthly load of the seasonal change inflection point, so as to improve the model's ability to deal with seasonality. The model proposed in this paper is verified on the actual power data in Shaoxing City. [ABSTRACT FROM AUTHOR]