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Due to the insufficient consideration of population distribution differences in existing site selection research, as well as the difficulty in meeting the needs of population refuge under the condition of dam-break floods, the site selection plan is insufficient. The population distribution was simulated by using land-use and land-cover change (LUCC) and nighttime light data, and the number and distribution of the affected population were determined based on the simulation results of dam-break floods. On the basis of screening qualified candidate shelters, the effective capacity and accessibility information under normal weather and extreme rainfall conditions were analyzed and quantified. A multi-objective site selection model was built by comprehensively considering factors such as population transfer efficiency, construction cost and capacity limitations of shelters. The NSGA-II algorithm was used to solve the final site selection plan. The method was applied to the Dafangying Reservoir in Hefei City, Anhui Province. The results show that the overall average relative error (MRE) of population simulation. for 35 downstream streets is 11.16%, which has high fitting precision and can truly reflect the distribution of population. The number of qualified refuge candidate shelters screened under normal weather scenarios is 352, and the number of refuge sites retained under extreme rainfall weather is 266. Population distribution and weather factors have significant effects on the choice of refuge. The population distribution and weather factors have a significant impact on the selection of shelters and the allocation of evacuees. [ABSTRACT FROM AUTHOR]

Background: Pyrilla perpusilla (Walker) is an important pest of sugarcane ecosystem in the Tarai region of Uttarakhand state of India. The study focused on investigating the population dynamics of Pyrilla (sugarcane leaf hopper) and its parasitoids under the natural field conditions. Results: During the study, two important parasitoids, viz., Fulgoraecia Melanoleuca, a nymphal/adult parasitoid (Lepidoptera: Epipyropidae), and Cheiloneurus pyrillae, an egg parasitoid (Hymenoptera: Encyrtidae), were found associated with the sugarcane leaf hopper. The peak mean population of ecto-parasitoid, F. melanoleuca cocoon, was observed in November 2022–23 and 2023–24. The morning hour relative humidity showed a negative significant relation with the cocoon population. The maximum parasitization of nymphs and adults Pyrilla was found to be 46.7 and 46.0%, respectively, from September to October during 2022–23 and 2023–24 crop seasons, after that the declining trend in parasitization by F. melanoleuca was observed. An increasing trend was recorded in egg parasitization in July, when the maximum mean population density of Pyrilla egg batches (2.28 /leaf), nymphs (4.75/leaf) and adults (4.58/leaf) was found. Temperature and relative humidity had significant correlations with Pyrilla egg batches. Conclusion: Overall, the study outlines the presence of Pyrilla and its naturally occurring parasitoids in the sugarcane ecosystem, along with the effects of weather conditions on Pyrilla's population density and the parasitization rates of the parasitoids. The peak activity period of pest and its parasitoids was reported from September to November. Weather factors such as temperature ranging from 16 to 37.25 °C and relative humidity (62.7–93.8%) played a significant role in affecting their density and parasitization. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Plant Protection & Pathology is the property of Egyptian National Agricultural Library (ENAL) 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.)

Abstract Background Pyrilla perpusilla (Walker) is an important pest of sugarcane ecosystem in the Tarai region of Uttarakhand state of India. The study focused on investigating the population dynamics of Pyrilla (sugarcane leaf hopper) and its parasitoids under the natural field conditions. Results During the study, two important parasitoids, viz., Fulgoraecia Melanoleuca, a nymphal/adult parasitoid (Lepidoptera: Epipyropidae), and Cheiloneurus pyrillae, an egg parasitoid (Hymenoptera: Encyrtidae), were found associated with the sugarcane leaf hopper. The peak mean population of ecto-parasitoid, F. melanoleuca cocoon, was observed in November 2022–23 and 2023–24. The morning hour relative humidity showed a negative significant relation with the cocoon population. The maximum parasitization of nymphs and adults Pyrilla was found to be 46.7 and 46.0%, respectively, from September to October during 2022–23 and 2023–24 crop seasons, after that the declining trend in parasitization by F. melanoleuca was observed. An increasing trend was recorded in egg parasitization in July, when the maximum mean population density of Pyrilla egg batches (2.28 /leaf), nymphs (4.75/leaf) and adults (4.58/leaf) was found. Temperature and relative humidity had significant correlations with Pyrilla egg batches. Conclusion Overall, the study outlines the presence of Pyrilla and its naturally occurring parasitoids in the sugarcane ecosystem, along with the effects of weather conditions on Pyrilla’s population density and the parasitization rates of the parasitoids. The peak activity period of pest and its parasitoids was reported from September to November. Weather factors such as temperature ranging from 16 to 37.25 °C and relative humidity (62.7–93.8%) played a significant role in affecting their density and parasitization.

This article examines the impact of meteorological conditions represented by ambient temperature, ambient humidity, wind speed, and daily precipitation sum on the reliability of low-voltage cable lines. Cable line reliability is crucial to the stability and safety of power systems. Failure of cable lines can lead to power outages. This can cause serious economic and social consequences, as well as threaten human safety, especially in the public sector and critical infrastructure. In addition, any interruption of cable lines generates costs related to repairs, operational losses, and possible contractual penalties. This is why it is so important to investigate the causes of power equipment failures. Many power system failures are caused by weather factors. The main purpose of this article is to quantify the actual impact of weather conditions on the performance and reliability of power equipment in distribution networks. Reliability indicators (failure rate, failure duration, restoration rate, and failure coefficient) for low-voltage cable lines were calculated as a function of weather conditions. Empirical values of the indicators were determined based on many years of observations of power lines operating in the Polish power system. An analysis of the conformity of their empirical distribution with the assumed theoretical model was also conducted. By quantifying the impact of specific weather factors on the operation of power equipment, it becomes possible to identify the ranges in which failures are most likely.

Since its initial outbreak in Korea in 2015, fire blight has consistently emerged annually. Fire blight out-breaks usually begin in May, peak in June, and decline in July in Korea. In this study, we analyzed cases that exhibit a distinct pattern of disease occurrence based on yearly weather conditions from 2020 to 2023. In 2020, fire bight disease occurrence began in late May. Although the disease incidence started late by the low temperatures in April, which caused flowering period delayed, the incidence increased significantly due to the high risk of blossom infection. In 2021, the first outbreak began in late April because the flower infection started in early April. In 2022, despite the high blossom infection risk during the flowering period in April and the high incidence of fire blight in May, the incidence decreased sharply from June due to the low rainfall in May. In 2023, due to torrential rains and hail in late June, the incidence of fire blight increased even in July. Considering the weather factors that affect the increase of fire blight disease, it is suggested that control measures to prevent the fire blight infection should be carried out before and after wind-driven rains.

Distributed photovoltaic power stations have advantages such as local direct power supply and reduced transmission energy consumption, and whose demands are constantly being developed. Conducting research on medium- and long-term distributed photovoltaic prediction will have significant value for applications such as the electricity trade market, power grid operation, and the planning of new power stations. Due to characteristics such as long time dependence, disperse power stations, and strong randomness, making accurate and stable predictions becomes very difficult. In this research, we propose a multiple time series feature and multiple-model fusion-based ensemble learning model for medium- and long-term distributed photovoltaic power prediction (M2E-DPV). Considering the wave influence and the differences in distributions in different areas of photovoltaic power, multiple feature combinations are designed to increase feature expression ability and adaptability. Based on the boost ensemble learning model, trained on a single model of different time scale features, the optimal scoring strategy is used for multiple model fusion in the rolling prediction process, and finally, time-segmented probabilistic correction is performed. The experiment results show the effectiveness of the M2E-DPV under multiple feature combinations and multi-model fusion strategies. The average MAPE, R2, and ACC indicators are 0.15, 0.96, and 0.91, respectively. Compared with other methods, there is a significant improvement, indicating that the prediction ability of the model framework proposed in this paper is advanced and robust. [ABSTRACT FROM AUTHOR]

Rompin has played an active role in Malaysia's rice production for several decades. However, rice production faces a threat, particularly from the hemipteran insect pests. There is limited documentation on the abundance of these insects and their relationship with weather factors. Therefore, this study aimed to determine the abundance of hemipterans in different growth stages and to understand the effects of weather factors on their population in rice fields. The study was conducted in farmers' rice fields in Rompin, Pahang, Malaysia, during the main and off-season rice planting. Sweep nets, yellow sticky traps, and yellow pan traps were utilized in each plot. Trapped insects were identified based on the rice planting seasons and growth stages. The trends of weather factors such as rainfall, temperature, light intensity, and wind speed were analysed and correlated with insect abundance. A total of 23 023 individuals belonging to six families and eleven species of the hemipteran order were recorded. Nine of these species were pests, namely Leptocorisa oratorius (Fabricius) (2.05%), Maiestas dorsalis (Motschulsky) (41.93%), Nephotettix virescens (Distant) (1.52%), Nephotettix nigropictus (Stål) (0.03%), Scotinophara sp. (4.92%), Nilaparvata lugens (Stål) (28.18%), Sogatella furcifera (Horváth) (17.75%), Nezara viridula (Linnaeus) (0.01%) and Scotinophara coarctata (Fabricius) (2.88%). The other two species were predators, Cyrtorhinus lividipennis (Reuter) (0.55%) and Polytoxus fuscovittatus (Stål) (0.19%). Maiestas dorsalis, N. lugens, S. furcifera, and Scotinophara sp. were found in significantly (df=10, F=5.707, P<0.01) higher numbers and exceptionally high during rice's late vegetative and early reproductive stages. The maximum temperature significantly (R²>0.5 & P<0.05) increased during the main season, while wind speed increased significantly (R²>0.5 & P<0.05) during the offseason. Wind speed significantly positive correlated (r>0.5 & P<0.05) with N. virescens, S. furcifera, L. oratorius, and Scotinophara sp. On the other hand, rainfall exhibited a significant negative correlation (r>-0.5 &P<0.05) with L. oratorius. Various pest species and their high populations in this study pose a significant threat to plants due to their preferences for different plant parts and strata. [ABSTRACT FROM AUTHOR]

This study analyzes the impact of weather factors on the resilience of airport flight operations, focusing on flight performance, economic outcomes, and transportation capacity. A Kolmogorov–Arnold Network (KAN) model was employed to identify key weather variables and establish the relationship between these factors and airport operational resilience. Xi'an Xianyang International Airport was used as a case study, with the weights of various routes determined using grey relational analysis, considering average daily flight volume, flight distance, and airport flow stability indicators. Flight operation records and weather data were utilized to assess the influence of critical weather factors on key operational resilience metrics. The findings reveal that routes in economically developed areas exert a more pronounced effect on flow stability. Temperature and wind speed emerged as the most influential factors, with importance values of 0.35 and 0.32, respectively, about flight operations and economic performance. Furthermore, changes in wind direction and wind speed had the greatest impact on transportation capacity, with importance values of 0.7 and 0.65, respectively. These results highlight the need for special attention to weather factors such as temperature and wind speed during flight scheduling and risk assessment to ensure operational safety, efficiency, and economic viability. [ABSTRACT FROM AUTHOR]

Light-emitting diodes have been beneficial for plant growth, especially for microgreens in countries with low radiation, greenhouses, and chambers. However, information about how plants respond to additional light-emitting diode lighting after 12 hours of sunlight exposure in tropical areas is limited. This study examines the effects of long-duration light-emitting diodes on mustard greens in Kien Giang province, Vietnam (105°14'33.21" E; 9°91'41.13" N). The trials were conducted in the greenhouse for two growing seasons with a completely randomized design, including 0, 2, 4, and 6 hours of assembled light-emitting diodes lighting and 4 hours of commercial light-emitting diodes lighting after 6 pm, with three replications. Results showed that weather factors in season 2 favorably influenced mustard's growth. At 4 hours of lighting, commercial light-emitting diodes showed a higher chlorophyll index, flowering time, flowering rate, leaf number, and absolute growth rate of leaf number but less leaf and fresh shoot weight than assembled light-emitting diodes. Four hours of assembled light-emitting diodes positively affected most mustard growth, while 6 hours of assembled light-emitting diodes were superior for flowering aspects. Adding 4 hours of light-emitting diodes could increase leafy yield and shorten the harvesting time of mustard greens grown in greenhouses under tropical conditions. [ABSTRACT FROM AUTHOR]

This article examines the impact of meteorological conditions represented by ambient temperature, ambient humidity, wind speed, and daily precipitation sum on the reliability of low-voltage cable lines. Cable line reliability is crucial to the stability and safety of power systems. Failure of cable lines can lead to power outages. This can cause serious economic and social consequences, as well as threaten human safety, especially in the public sector and critical infrastructure. In addition, any interruption of cable lines generates costs related to repairs, operational losses, and possible contractual penalties. This is why it is so important to investigate the causes of power equipment failures. Many power system failures are caused by weather factors. The main purpose of this article is to quantify the actual impact of weather conditions on the performance and reliability of power equipment in distribution networks. Reliability indicators (failure rate, failure duration, restoration rate, and failure coefficient) for low-voltage cable lines were calculated as a function of weather conditions. Empirical values of the indicators were determined based on many years of observations of power lines operating in the Polish power system. An analysis of the conformity of their empirical distribution with the assumed theoretical model was also conducted. By quantifying the impact of specific weather factors on the operation of power equipment, it becomes possible to identify the ranges in which failures are most likely. [ABSTRACT FROM AUTHOR]

The article presents a study on the influence of weather factors (ambient temperature) on the operational reliability of overhead low-voltage power lines with bare conductors. A method for determining the average failure intensity, average failure duration, average renewal intensity, and failure rate of overhead low-voltage power lines with bare conductors as a function of ambient temperature is presented. Based on many years of observations of power lines operated in electric power distribution networks in Poland, the empirical values of the above-mentioned reliability indicators were determined. An analysis of empirical distribution compliance with the assumed theoretical model was also carried out. The reliability studies conducted showed that the highest failure intensity of the considered power lines occurred at temperatures commonly found in Poland. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Southeast University / Dongnan Daxue Xuebao is the property of Journal of Southeast University Editorial Office 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.)

As part of a concerted research effort to design management strategies for an economic insect pest of cashew (Anacardium occidentale L.), viz., Analeptes trifasciata Fabricius (Coleoptera: Cerambycidae), also known as the stem girdler, it became necessary to understand the biotic and abiotic factors influencing its population fluctuation. The population dynamics of A. trifasciata and its relationship with crop phenology (flushing, senescence, flower initiation, fruit development and maturation stages) and weather factors (average temperature, relative humidity and rainfall) were investigated from 2017 to 2019 at the cashew orchard of Cocoa Research Institute of Nigeria (CRIN), Ibadan, Nigeria. Observations were recorded at monthly intervals for the duration. The period of incidence was from May to December. Peak abundance, which coincided with the wet season as well as senescence and flower initiation stages, were not significantly correlated. Adult abundance of A. trifasciata was conspicuously low during the fruit development and maturation stages, this stage coincided with the peak of the dry season. However, there was no significant correlation between the pest abundance and crop phenological stages. The male to female ratio was 1:0.81 (÷2 =1.313, df =1, p =0.252). The abundance of A. trifasciata significantly but negatively correlated (r = -0.73) with temperature. Relative humidity (r = 0.30) and rainfall (r = 0.24) showed non-significant association with stem-girdler population. Our findings indicated that temperature is the major predictor of A. trifasciata population fluctuation irrespective of the phenological stage. These findings can be useful for developing a forecasting model for its early detection and appropriate management. [ABSTRACT FROM AUTHOR]

In this paper, a data-driven framework aimed at investigating how weather factors affect the spatio-temporal patterns of air traffic flow in the terminal maneuvering area (TMA) is presented. The framework mainly consists of three core modules, namely, trajectory structure characterization, flow pattern recognition, and association rule mining. To fully characterize trajectory structure, abnormal trajectories and typical operations are sequentially extracted based on a deep autoencoder network with two specially designed loss functions. Then, using these extracted elements as basic components to further construct and cluster per-hour-level descriptions of airspace structure, the spatio-temporal patterns of air traffic flow can be recognized. Finally, the association rule mining technique is applied to find sets of weather factors that often appear together with each flow pattern. Experimental analysis is demonstrated on two months of arrival flight trajectories at Hong Kong International Airport (HKIA). The results clearly show that the proposed framework effectively captures spatial anomalies, fine-grained trajectory structures, and representative flow patterns. More importantly, it also reveals that those flow patterns with non-conforming behaviors result from complex interactions of various weather factors. The findings provide valuable insights into the causal relationships between weather factors and changes in flow patterns, greatly enhancing the situational awareness of TMA. [ABSTRACT FROM AUTHOR]

Urban site analysis includes tangible factors such as the physical site features and intangible factors as the sensory site features like odors affect the inhabited area in the site. Environmental and chemical studies have much greater attention and studies to the odor effects in urban areas than urban designers. This paper aims to provide a validated and applicable method for urban designers in odor measurement. The objective of this research is to present the various methods of measuring odors adopted in chemical and environmental studies to achieve an applicable odor measurement method in the urban design field. The odor measurement tools are usually dedicated to measuring odor concentration at the odor source or at the receptor location that are used in chemical and environmental studies. However, in urban design studies the odor measurement could be performed using a method called citizen science considering the FIDOL factor to evaluate the odor nuisance including odor frequency, intensity, duration, offensiveness, location, and hedonic tone. This research conducts a case study in Tripoli city and determines Tripoli landfill as a significant odor source that affects people in their inhabited areas. A questionnaire was distributed in the affected area by the odor source, and the respondents of the inhabitants ensured that the summer season is the most season that they can feel the odor in their places associated with the wind direction. The results ensure that the citizen science method in measuring odors is validated, applicable, and available for urban designers to detect and estimate the affected area by odor source. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Plant Protection & Pathology is the property of Egyptian National Agricultural Library (ENAL) 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.)

Background. Enzymomycotic depletion of grain leads to a significant decrease in the dry matter mass of the grain, as the intensity of respiration increases, protein substances break down, enzymes (in particular, α-amylase) pass from the adsorbed form to the water-soluble one, and their activity increases sharply. One of the consequences of this is the intensive amylolysis of starch, which means a significant deterioration in the technological indicators of the quality of grain and seeds. Materials and Methods. This study gives a thorough description of the process of enzymomycotic depletion of grain of soft winter wheat (Triticum aestivum L.), sowing rye (Secale cereale L.), winter triticale (Triticosecale Witt.) depending on abiotic factors and the sources of resistance to ear diseases 4, 8, 12 days after the onset of full ripeness in the conditions of the western forest-steppe of Ukraine (2019–2021). Research methods – general scientific, field, measurement and weight, mathematical and statistical. Results and Discussion. According to the obtained results, the dependence of enzymomycotic depletion of grain on abiotic factors was established. The development of ear diseases depended both on weather factors and on the ecological plasticity of the cultivar. The highest percentage of the distribution of ear sepsoria was observed on the 12th day after the onset of full ripeness: wheat – 3.3 %, rye – 2.4 %, triticale – 1.9 %, fusarium, respectively 2.4 %, 1.9 %, 1 %, 8 %. The loss of dry matter in the weight of 1000 grains depended on the ecotype of the cultivar and the duration of the grain stan­ding time 4, 8, and 12 days after full ripeness. Conclusion. The following cultivars were most resistant to EMDG: Oberih Myronivsky (wheat), Kobza (rye), Obrij Myronivsky (triticale); their base seed production profitability rates being 75.1 %, 116.6 %, and 146.8 %, respectively. The results of the study can be used in the selection of varieties of winter grain crops resistant to enzymomycotic grain depletion for the western forest-steppe and Polissya zones of Ukraine, where breeding work on these crops is not carried out and agricultural producers purchase seeds of new varieties from the originating institutions of the central forest-steppe to introduce them into production.

This study analyzes the impact of weather factors on the resilience of airport flight operations, focusing on flight performance, economic outcomes, and transportation capacity. A Kolmogorov–Arnold Network (KAN) model was employed to identify key weather variables and establish the relationship between these factors and airport operational resilience. Xi’an Xianyang International Airport was used as a case study, with the weights of various routes determined using grey relational analysis, considering average daily flight volume, flight distance, and airport flow stability indicators. Flight operation records and weather data were utilized to assess the influence of critical weather factors on key operational resilience metrics. The findings reveal that routes in economically developed areas exert a more pronounced effect on flow stability. Temperature and wind speed emerged as the most influential factors, with importance values of 0.35 and 0.32, respectively, about flight operations and economic performance. Furthermore, changes in wind direction and wind speed had the greatest impact on transportation capacity, with importance values of 0.7 and 0.65, respectively. These results highlight the need for special attention to weather factors such as temperature and wind speed during flight scheduling and risk assessment to ensure operational safety, efficiency, and economic viability.

Copyright of Journal of Plant Protection & Pathology is the property of Egyptian National Agricultural Library (ENAL) 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 the recent past, exotic whiteflies viz., Aleurodicus rugioperculatus, Paraleyrodes bondari, Paraleyrodes minei and Aleurotrachelus atratus are infesting coconut plantations in India. Based on the damage potential, the predominant species are the rugose spiralling whitefly, A. rugioperculatus and the Bondars nesting whitefly, P. bondari. A study was undertaken to determine the seasonal incidence and population dynamics of these in the new invasion region at Karungalakudi block of Madurai district from 33rd standard meteorological week (SMW) of 2021 to 32nd SMW of 2022. The results indicated that A. rugioperculatus incidence rose considerably from the first week of April (10.9 adults/leaflet) to third week of May (8.3 adults/leaflet; while P. bondari reached maximum during the third week of March (71.99 adults/leaflet) and extended up to first week of June (67.57 adults/leaflet) coinciding with summer months with high temperature and limited precipitation. Subsequently, their incidence declined with the onset of north east monsoon coupled with parasitism by Encarsia guadeloupae and predation by chrysopids from thirdweek of August to fourth-week of December in 2021. The extent of parasitism by E. guadeloupae on A. rugioperculatus nymphs was positively correlated and ranged from 40% (third week of August, 33rd SMW, 2021) to 84% (second week of June 2022, 24th SMW). Chrysopids revealed a highly significant positive correlation with the incidence. [ABSTRACT FROM AUTHOR]

The article presents a study on the influence of weather factors (ambient temperature) on the operational reliability of overhead low-voltage power lines with bare conductors. A method for determining the average failure intensity, average failure duration, average renewal intensity, and failure rate of overhead low-voltage power lines with bare conductors as a function of ambient temperature is presented. Based on many years of observations of power lines operated in electric power distribution networks in Poland, the empirical values of the above-mentioned reliability indicators were determined. An analysis of empirical distribution compliance with the assumed theoretical model was also carried out. The reliability studies conducted showed that the highest failure intensity of the considered power lines occurred at temperatures commonly found in Poland.

In this paper, a data-driven framework aimed at investigating how weather factors affect the spatio-temporal patterns of air traffic flow in the terminal maneuvering area (TMA) is presented. The framework mainly consists of three core modules, namely, trajectory structure characterization, flow pattern recognition, and association rule mining. To fully characterize trajectory structure, abnormal trajectories and typical operations are sequentially extracted based on a deep autoencoder network with two specially designed loss functions. Then, using these extracted elements as basic components to further construct and cluster per-hour-level descriptions of airspace structure, the spatio-temporal patterns of air traffic flow can be recognized. Finally, the association rule mining technique is applied to find sets of weather factors that often appear together with each flow pattern. Experimental analysis is demonstrated on two months of arrival flight trajectories at Hong Kong International Airport (HKIA). The results clearly show that the proposed framework effectively captures spatial anomalies, fine-grained trajectory structures, and representative flow patterns. More importantly, it also reveals that those flow patterns with non-conforming behaviors result from complex interactions of various weather factors. The findings provide valuable insights into the causal relationships between weather factors and changes in flow patterns, greatly enhancing the situational awareness of TMA.

There has been an insurgence of allergic respiratory diseases such as asthma and rhinitis in industrialized countries in the last few decades as a result of the interaction between air pollutants and pollen, which has become a global and dramatic health problem. Air pollutants such as nitrogen dioxide, sulfur dioxide, ozone, and carbon dioxide affect the physical, chemical and biological properties of pollen such as the pollen content, production, and allergenicity, exacerbating symptoms in vulnerable subjects. When investigating these interactions and their effects, the environmental impact of climate change, weather variables and urbanization should be taken into account as well as the pollen species, type of pollutant, conditions of exposure, and individual susceptibility. Up to 25% of asthma adult cases are work-related, because several categories of workers in different sectors are exposed to aeroallergens and outdoor air pollutants. Thus, in this study, we evaluated the significant impacts of occupational allergies on worker's health and quality of life. In summary, to assess the effect of interactions between air pollutants and pollen on public and occupational health, all the factors that play a role in this context will be investigated, including environmental factors, individual susceptibility in relation to pollen species, type of pollutants, and conditions of exposure. [ABSTRACT FROM AUTHOR]

This paper presents the models developed for the short-term forecasting of energy production by photovoltaic panels. An analysis of a set of weather factors influencing daily energy production is presented. Determining the correlation between the produced direct current (DC) energy and the individual weather parameters allowed the selection of the potentially best explanatory factors, which served as input data for the neural networks. The forecasting models were based on MLP and Elman-type networks. An appropriate selection of structures and learning parameters was carried out, as well as the process of learning the models. The models were built based on different time periods: year-round, semi-annual, and seasonal. The models were developed separately for monocrystalline and amorphous photovoltaic modules. The study compared the models with the predicted and measured insolation energy. In addition, complex forecasting models were developed for the photovoltaic system, which could forecast DC and AC energy simultaneously. The complex models were developed according to the rules of global and local modeling. The forecast errors of the developed models were included. The smallest values of the DC energy forecast errors were achieved for the models designed for summer forecasts. The percentage forecast error was 1.95% using directly measured solar irradiance and 5. 57% using predicted solar irradiance. The complex model for summer forecasted the AC energy with an error of 1.86%. [ABSTRACT FROM AUTHOR]

This research aims to determine the types of thunderstorms formed in the thickness of the cloud (determine the Dry adiabatic lapse rate (DALR) and Environmental lapse rate (ELR)) in the case of precipitation during the day. Data were taken by Temperature, Dew point, Atmospheric Pressure, and Height from re-analysis by the (ECMWF) for the heights (0-18000) m, the levels of pressure (1000-100) mbar, low cloud cover data, and the characteristic days ((18, 24, 27) February, 28 April, and 25 November) of the year 2018 for Baghdad station were chosen to obtain the largest possible number of clouds and their diversity to use them in calculating the cloud cover and weather stability in terms of calculating the daily change, temperature, dew point in addition to calculating the low cloud cover with altitude and atmospheric instability. The Sigma Plot program was used in this research to determine the base of clouds and thunderstorms. The change in temperature, Dew point, clouds base, and altitude was determined, then the cloud thickness, types, and classification were calculated. The clouds found are strong thunderstorm clouds characterized by thickness and height, such as the clouds of Nimbostratus (Ns) and Cumulonimbus (Cb). [ABSTRACT FROM AUTHOR]

Population fluctuation of the most abundant mite species inhabiting mango, Mangifera indica L. (Anacardiaceae), as one of the important fruit trees at Qalyubia governorate, Egypt was studied from August 2020 to September 2022. Results indicated the occurrence of 19 mite species from 18 genera in 10 families. Mango bud mite, Aceria mangiferae Sayed, mango rust mite, Metaculus mangiferae (Attiah) and tetranychid mite, Oligonychus mangiferus (Rahman & Sapra) have become important pests on "Naomi" mango cultivar. While, the mango leaf coating mite, Aceria aegyptindicae Elhalawany, Amrine & Ueckermann and Cisaberoptus kenyae Keifer are important pests on "Heidi" cultivar. Aceria mangiferae has two peaks (in mid and late November, and late May and early-June) on buds of "Naomi" cultivar during the two successive seasons. Metaculus mangiferae has two peaks on leaves (in mid-October and late May) in the first season and (in late November and May) in the second season. Oligonychus mangiferus was recorded in high numbers in spring and autumn on "Naomi" cultivar during the two collection seasons. Aceria aegyptindicae and C. kenyae have two peaks (in late November and mid-February) in the first season, and (in early December and late April) in the second season on "Heidi" cultivar. Predacious mites are following their associated phytophagous prey with a lag in time. The population of phytophagous mites was significantly affected by combined weather factors and plant age than weather factors alone. Results indicated 'Heidi' is resistant to infestation with A. mangiferae, and susceptible to both A. aegyptindicae and C. kenyae. However, 'Naomi' is susceptible to the first pest and resistant to latter two pests. The changes in the nutritional value of the host plant are more effective on mite population fluctuation than weather factors. [ABSTRACT FROM AUTHOR]

Summary: Due to the rapid development of satellite laser communication technology, free‐space optical (FSO) links present a promising alternative to traditional radio frequency (RF) links. In this paper, taking the influence of weather factors into consideration, we investigate the performance of the hybrid FSO/RF links where the feeder link operates in the FSO band and the user link operates in the hybrid FSO/RF band. Specifically, the FSO feeder link is modeled by the gamma–gamma distribution in the presence of beam wander and pointing error, and the detection method adopts either the intensity modulation with direct intensity (IM/DD) or heterodyne detection. The RF user link is assumed to follow the shadowed Rician model. In addition, in order to improve the transmission rate of the link under the time‐varying satellite–terrestrial channel, a rate adaptation scheme is proposed. The performance of the system under study is evaluated in terms of the outage probability, average bit error rate (BER), and average transmission rate. Our results provide some important insights, for example, (1) due to the constraints of the feeder link and weather factors, there is an upper limit on the outage performance and bit error rate of the hybrid link; (2) the adaptive transmission strategy can significantly improve the transmission rate of the link compared with traditional design. [ABSTRACT FROM AUTHOR]

Lane departure crashes account for approximately 34% of all roadway crashes and over 70% of all roadway fatalities in Maine. Despite an 18% decrease in average daily traffic volume, the half of the year with colder weather, from November to April, comprises over 64% of the yearly lane-departure crashes. The purpose of this study is to explore to what extent seasonal (i.e., winter vs. non-winter) and monthly weather variations impact lane departure crashes on rural Maine roads. We used a negative binomial model with panel data to analyze monthly crashes on Interstates, minor arterials, major collectors, and minor collectors from 2015 to 2019 for winter and non-winter periods. The data include monthly average daily traffic, geometric characteristics, and weather variables. The research results indicate that the seasonal variability as reflected in various weather variables significantly impact the frequency of lane-departure crashes during the winter period. The marginal effect analysis shows that as the number of days with more than 1 inch of snowfall, or rainfall increases by 1%, the average number of lane-departure crashes increases approximately by 0.51% and 0.09% on Interstate roadways, respectively. [ABSTRACT FROM AUTHOR]

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The incidence of aphid Aphis craccivora Koch in Indian bean Lablab purpureus (L.) reached its peak during 2nd week of January (2nd SMW) with 25.27 aphids/twig of 10 cm. Maximum incidence of jassid Empoasca kerri Pruthi (8.20/leaf) and whitefly Bemisia tabaci (Gennadius) (7.12/leaf) was observed during 4th week of December (52nd SMW). The thrips Megalurothrips distalis Karny started appearing from 4th week of November (48th SMW) reaching its peak (10.35/flower) during 1st SMW. Maximum larval counts of Helicoverpa armigera (Hubner) (5.79/plant) was observed during 2nd week of January (2nd SMW), while in case of Maruca vitrata Geyer (7.21/plant) it was during 2nd week of January (2nd SMW). Maximum and minimum temperature showed significant negative influence on the incidence of all these pests; and morning relative humidity showed significant negative effect on all except M. distalis. While morning vapour pressure showed significant negative influence on the incidence of all pests except E. kerri and B. tabaci. [ABSTRACT FROM AUTHOR]

Thermal-Energy-Storage Air-Conditioning (TES-AC), a sustainable form of Air-Conditioning (AC) operates by storing thermal energy as chilled water when energy demand is low during nighttime. Later it uses the stored thermal energy during the daytime to cool the indoor air of the building the next day. However, the stored thermal energy in the form of water in the tanks of the chiller plant might be affected by external weather factors. It is essential to understand whether there is a relation between external weather conditions and water consumption in the TES-AC system. Without verifying the relation, applying computational intelligence for Thermal-Energy-Storage (TES) in Heating, Ventilation, and Air Conditioning (HVAC) would not be appropriate. However, not much research has focused on applying such techniques in HVAC for facility management and maintenance. Moreover, identifying these features by discovering the relation between weather and water consumption is a crucial part to apply computational intelligence such as machine learning techniques for predictive maintenance of this facility as it heavily relies on water volume for TES-AC charging. During warmer weather, the stored thermal energy might have an effectual loss due to evaporation which would mean more water consumption by TES-AC for cooling. Hence, this research investigates whether external weather data has any effect on the water consumption of TES-AC and discusses how external weather may affect the water consumption of TES-AC and if it is important to factor it in whilst utilizing computational intelligence for charging load prediction of TES-AC.

Extreme climate and uncertainties in environmental changes have caused tourists to change their travel behaviors, and further affected the tourism value of tourism attractions. This study assessed the changes in the tourism value considering different climate change scenarios. Firstly, this study utilized meteorological data and number of tourists from the past decade to estimate the number of future tourists of 14 national forest parks in Taiwan. Questionnaire survey was conducted to investigate the travel durations of tourists; and the travel cost method was used to estimate the future tourism value. Then, the changes in the total value of each national forest park in Taiwan due to climate change were calculated. The results indicated that in national forest parks in Taiwan, the number of tourists and temperature increase were positively correlated, and the future tourism value decline because the recreation time in most national forest parks under climate change will decline. This study calculated the total changes in the future (from 2020 to 2100) tourism value of 14 national forest parks in Taiwan under climate change, and the maximum value reaches NT$183.473 billion. Under Scenario RCP 8.5, the tourism value is higher than that under Scenario RCP 2.6. Also, regarding time sequence, under Scenario RCP 8.5, the degree of decrease in tourism value in each area were smaller than those under Scenario RCP 2.6; in some areas, the tourism value increased. National forest park managers should promptly propose relevant adaptive policies to reduce the damage of climate change to tourism value.

Late blight, caused by Phytophthora infestans, is a major disease of the potato crop with a strong negative impact on tuber yield and tuber quality. The control of late blight in conventional potato production systems is often through weekly application of prophylactic fungicides, moving away from a sustainable production system. In support of integrated pest management practices, machine learning algorithms were proposed as tools to forecast aerobiological risk level (ARL) of Phytophthora infestans (>10 sporangia/m3) as inoculum to new infections. For this, meteorological and aerobiological data were monitored during five potato crop seasons in Galicia (northwest Spain). Mild temperatures (T) and high relative humidity (RH) were predominant during the foliar development (FD), coinciding with higher presence of sporangia in this phenological stage. The infection pressure (IP), wind, escape or leaf wetness (LW) of the same day also were significantly correlated with sporangia according to Spearman's correlation test. ML algorithms such as random forest (RF) and C5.0 decision tree (C5.0) were successfully used to predict daily sporangia levels, with an accuracy of the models of 87% and 85%, respectively. Currently, existing late blight forecasting systems assume a constant presence of critical inoculum. Therefore, ML algorithms offer the possibility of predicting critical levels of Phytophthora infestans concentration. The inclusion of this type of information in forecasting systems would increase the exactitude in the estimation of the sporangia of this potato pathogen. [ABSTRACT FROM AUTHOR]

Simple Summary: Despite traditional reports on the ability of female dromedaries to modulate pregnancy length in response to environmental conditions, no empirical study has been developed. According to the present results, female dromedaries would adjust the onset of parturition to give birth around darker and, therefore, safer nights since social communication and interaction between congeners are increased under dim light conditions, mostly mediated by hormonal signals. Furthermore, the time of delivery, a highly energy-demanding process, may also be modulated by mean wind speed and its transient increases since these weather variables affect the thermal comfort and, thus, the heat transfer between an animal and its environment and the individual energy budget. Gravid females may be more energetically compromised when the offspring is a male; hence, the onset of parturition for the newborns of the male sex will be more probable to occur on slightly brighter nights and when mean wind speed is lower when compared to their female counterparts. Such specific phenology would favor a proper multisensory interaction between the mother and the more immature male young at neonatal stages so that thermoregulatory demands are minimized for these reproductive tasks, and then the fitness of parents and the survival of offspring are improved. Given energy costs for gestating and caring for male offspring are higher than those of female newborns, external environmental conditions might be regarded as likely to affect the timing of delivery processes differentially depending on the sex of the newborn calf to be delivered. The aim of the present paper is to evaluate the association between environmental stressors such as the moon phase and weather-related factors and the onset of labor in female dromedaries. A binary logistic regression model was developed to find the most parsimonious set of variables that are most effective in predicting the probability for a gravid female dromedary to give birth to a male or a female calf, assuming that higher gestational costs and longer labor times are ascribed to the production of a male offspring. Although the differences in the quantitative distribution of spontaneous onset of labor across lunar phases and the mean climate per onset event along the whole study period were deemed nonsignificant (p > 0.05), a non-negligible prediction effect of a new moon, mean wind speed and maximum wind gust was present. At slightly brighter nights and lower mean wind speeds, a calf is more likely to be male. This microevolutionary response to the external environment may have been driven by physiological and behavioral adaptation of metabolic economy and social ecology to give birth to cooperative groups with the best possible reduction of thermoregulatory demands. Model performance indexes then highlighted the heterothermic character of camels to greatly minimize the impact of the external environment. The overall results will also enrich the general knowledge of the interplay between homeostasis and arid and semi-arid environments. [ABSTRACT FROM AUTHOR]