Sunny Weather Research Articles

Регуляция соковыделения при подсочке березы Betula pendula Roth

The study showed a correlation between the intensity of sap release by birch trees and the trunk diameter, degree of crown development, and tree age. In addition to the characteristics of trees, sap release intensity also depended on weather conditions and tapping methods. The study object was a mature birch stand with blueberry ground cover (Kirishi forestry unit of the Leningrad region, Russia). The composition of the stand consisted of birch (65 %), spruce (21 %), aspen (8 %), alder (3 %), elm (2 %), and maple (1 %); the basal area was 0.6. The projective cover was 0.73. The average age, diameter and height were 76 yrs, 25.0 cm and 24.3 m, respectively. Tapping was carried out by the closed method. The tapping channels were 30–40 cm above the root neck. The intensity of sap release was found to depend on the number of channels and their location. The maximum intensity of sap release from one tapping channel was 285 mL/h, depending on the trunk diameter and tree age. The intensity of sap release varied throughout the day: it increased in the morning and early afternoon (until 1–2 pm), and decreased in the late afternoon. At night, sap release intensity was the lowest, or it stopped completely regardless of the tree's age, degree of crown development, and trunk diameter. At the average daily temperature between +3 and +6 °С in moky weather, each tree produced 0.54–1.37 L of sap per day, and at a higher temperature in sunny weather, 2.50–6.22 L per day. The higher the air and soil temperatures, the more intense the sap release. At the air temperature of –3.0 °С, the sap freezes. When the average daily air temperature stays above +10.0 °С for several days, the sap begins to ferment. For citation: Gryazkin A.V., Danilov D.A., Zaytsev D.A., Hoang Minh Anh, Thanh Tran Trung. Regulation of Sap Release when Tapping Betula pendula Roth. Lesnoy Zhurnal = Russian Forestry Journal, 2023, no. 4, pp. 180–189. (In Russ.). https://doi.org/10.37482/0536-1036-2023-4-180-189

Sparse Adversarial Unsupervised Domain Adaptation With Deep Dictionary Learning for Traffic Scene Classification

In recent years, the accurate recognition of traffic scenes has played a key role in autonomous vehicle operations. However, most works in this area do not address the domain shift issue where the classification performance is degraded when the distribution of the source and target images are different due to weather changes. Also, lack of sparsity of current studies results in sample complexity and overfitting issues. To mitigate these challenges, this paper proposes a novel Sparse Adversarial Domain Adaptation (SADA) model for traffic scene classification. Our objective is to learn a scene classifier on a source domain with sunny weather and transfer its knowledge to a target domain with different weather (i.e., cloudy, rainy, and snowy) to enhance the classification performance on the target. First, a sparse representation is learned from the source traffic scenes via nonlinear dictionary learning in the latent space of a deep classifier. Then, a conditional generative adversarial network is devised to capture the distribution of the source sparse codes. Finally, a domain invariant sparse feature extractor is developed via a minimax game to align the sparse codes of the target domain images with the source; hence, providing domain adaptation for traffic scene classification using a deep neural network. Experimental results on a real-world dataset collected by the Honda Research Institute (HRI) indicate the superior performance of the proposed SADA compared to current traffic scene classification methods and state-of-the-art domain adaptation frameworks.

Design and Performance of Solar-Powered Surveillance Robot for Agriculture Application

Agriculture can benefit from robotics technology to overcome the drawback of limited human labor working in this sector. One of the robot applications in agriculture is a surveillance robot to monitor the condition. This paper describes a surveillance robot that is powered by a capacitor bank charged by a mini solar panel. The solar-powered robot is well-suited for deployment in open agricultural areas in Indonesia, where the irradiance is high. This potential is excellent for generating electricity and charging electric vehicles, such as those used in agriculture. The surveillance robot developed and tested in this study has been successfully deployed in an agriculture-like setting with all-terrain contours and the capacity to avoid obstacles. During high irradiance sunny weather, the shortest charging time was 2 hours. Hence, the proposed technology is effective for designing a surveillance robot for agricultural applications.

Learning from the Past: The Impacts of Economic Crises on Energy Poverty Mortality and Rural Vulnerability

The summer-dominated Mediterranean island of Cyprus is often considered in the contexts of beach tourism, sunny weather, and different types of business economic activities and services. In terms of its climatic conditions, extreme heat and mild winters characterise the island; yet, recent evidence has shown that winter poses a significant threat to public health. Its excess winter mortality is amongst the highest in Europe and there is an increased risk of energy-poverty-related mortality compared to total mortality. This study is an extension of previous research, with the objective of further scrutinizing the shift observed between urban and rural energy poverty mortality in the time of a severe nationwide financial crisis. Mortality and temperature data for the period of 2008–2018, as well as macroeconomic indicators, were investigated through a linear regression analysis. The results indicated that the declining economic situation of the island severely hit rural areas, with a significant increase in energy-poverty-related mortality, while urban areas were more resilient to this. There are three existing challenges linked to energy poverty: low incomes, high energy prices, and poor building energy efficiency. In Cyprus, all three coincide and are aggravated in times of crisis, creating conditions of extreme vulnerability for populations already in a disadvantaged position. This study’s motivation was to highlight the intense vulnerability associated with crises in Cyprus, and its outcomes call for higher levels of support at such times, especially when it comes to rural populations.

A comprehensive evaluation of water spray system on transparent roof towards optimal operation schedule

Indoor overheating induced by transparent roofs sharply increases the building energy consumption. Water spray offers a potential solution but requiring effective strategy to balance cooling effects and cost-effectiveness. Aiming at a spray system installed on transparent roof (63.2 × 24.6 m) of a mixed-use building in Guangzhou, China, this study provides a comprehensive evaluation of multiple strategies including continuous and intermittent operation with different spray/interval time. In sunny weather, continuous spray reduces the exterior, interior surface temperature, and long-wave radiation by 17.5 °C, 9.6 °C, and 66.3 W/m2, respectively. Besides, the indoor air temperature, globe temperature, and mean radiant temperature are also lowered by 4.4, 5.2, and 5.7 °C, respectively. Comparatively, the intermittent spray produces worse cooling effect, the reduction of exterior, interior surface temperature, and long-wave radiation are 9.4–15.9 °C, 4.1–7.8 °C, and 24.1–47.7 W/m2, respectively. The intermittent operating conditions, sorted according to the exterior surface temperature reduction, are ranked as 30/10 > 20/10 > 10/10 > 10/50 > 10/20 min, with the cooling effect not decreasing linearly with interval time, but increasing monotonically with spray time. The air conditioning electricity saved by continuous spray is higher than that by intermittent spray, but the water pump electricity and water consumptions are higher as well. Technical-economy evaluation indicates that water consumption is primary cost factor in spray systems and intermittent spray with 10/50 min is the optimal scenario. This study provides insights into the economical and efficient operation of transparent roof spray system, and lays a foundation for its smart control.

Prevalence and Associated Factors of Vitamin D Deficiency in High Altitude Region in Saudi Arabia: Three-Year Retrospective Study.

Vitamin D has many functions in the human body, and its deficiency is associated with skeletal and non-skeletal diseases. Vitamin D deficiency (blood level of 25 (OH) vitamin D < 20 ng/mL) has been reported worldwide, including Kingdom of Saudi Arabia (KSA). Its prevalence and associated factors vary according to KSA region. Therefore, this study aimed to explore the prevalence and risk factors of vitamin D deficiency in the Taif region of KSA. This retrospective study included patients who attended outpatient clinics at the Alameen General Hospital from 2019 to 2021. Demographic, clinical, and laboratory data were collected using a hospital software system. The study included 2153 patients and vitamin D deficiency was diagnosed in 900 (41.8%) of whom were diagnosed with vitamin D deficiency. It was more common in males (P=0.021), younger age (<0.001), and in patients without comorbidities. There was a positive correlation between 25 (OH) vitamin D levels and blood cholesterol, high-density lipoprotein, calcium, and vitamin B12 levels. In the binary logistic regression analysis, age was the most significant predictor (P<0.001), followed by the absence of thyroid disease (P=0.012) and asthma (P=0.030). Vitamin D deficiency is common in the Saudi population despite sunny weather in KSA. It is more prevalent among males, younger individuals, and those without comorbidities such as thyroid diseases and asthma.

Contrasting Drought Propagation Into the Terrestrial Water Cycle Between Dry and Wet Regions

AbstractDrought's intensity and duration have increased in many regions over the last decades. However, the propagation of drought‐induced water deficits through the terrestrial water cycle is not fully understood at a global scale. Here we study responses of monthly evaporation (ET) and runoff to soil moisture droughts occurring between 2001 and 2015 using independent gridded datasets based on machine learning‐assisted upscaling of satellite and in‐situ observations. We find that runoff and ET show generally contrasting drought responses across climate regimes. In wet regions, runoff is strongly reduced while ET is decoupled from soil moisture decreases and enhanced by sunny and warm weather typically accompanying soil moisture droughts. In drier regions, ET is reduced during droughts due to vegetation water stress, while runoff is largely unchanged as precipitation deficits are typically low in these regions and ET decreases are buffering runoff reductions. While these water flux drought responses are controlled by the large‐scale climate regimes, they are additionally modulated by local vegetation characteristics. Land surface models capture the observed water cycle responses to drought in the case of runoff, but not for ET where the ET deficit (surplus) is overestimated (underestimated), related to a misrepresentation of the general soil moisture‐evaporation interplay. In summary, our study illustrates how the joint analysis of machine learning‐enhanced Earth observations can advance the understanding of global eco‐hydrological processes, as well as the validation of land surface models.

Factors Influencing Motorists' Injury Severities: An Empirical Assessment of Crashes in District Peshawar, Pakistan

Travelling in a motor car is a popular mode of conveyance across Pakistan. Similarly, motorists constitute about 66% of total registered cars in Peshawar District which observed a 200% increase from 2006 to 2016. The current research estimates a Random Parameter Logit (RPL) Model by heterogeneousness means &amp; variations in order to identify various parameters that contribute to the motorists' brutality of injury. The effects of motorist traits, temporal characteristics, motor vehicle features, roadway attributes, weather characteristics and effects of speed limits were predominantly considered for this analysis. Generally, typical approximation results show that the chance and severity of injuries increase for accidents including young drivers, winter indicators, and crashes that occurred between 10 AM-02 PM. Likewise, minor wound smashes are more likely to involve senior drivers, occurring during sunny weather, in the autumn season and in the month of August. Safety measures are suggested based on the findings of this research study to improve professional's motorist safety e.g. educating drivers about traffic rules and safety, zero tolerance for driving without a valid license, and enforcing speed limits on the roads. The results of this study will help in formulating strategies to improve motorists' safety.

3D-гидродинамическое моделирование потоков СО2 и CH4 в приземном слое атмосферы (На примере лесного участка «Рошни-Чу»)

Introduction: The aim of this study is to evaluate the spatial variability of carbon dioxide (CO2) and methane (CH4) fluxes at the reference site "Roshni-Chu" of the carbon measurement megasites of the Chechen Republic using modeling experiments with in-situ measurements and remote sensing data. Methods and materials: Measurements of carbon dioxide (CO2) and methane (CH4) fluxes at the soil surface at the "Roshni Chu" forest site in the mountainous forest region of the Chechen Republic were conducted using a dynamic closed chamber connected to a portable gas analyzer G4301 (Picarro, USA). Leaf photosynthesis and respiration parameters of the main edificators and sub-edificators of premontane broadleaf forests were measured using the portable photosynthetic system LI-6800 (LI-COR, USA). Landsat 8 data were used to produce digital maps of surface topography and Nor-malized Difference Vegetation Index (NDVI). A 3D process-based atmospheric transfer model was chosen to describe the spatial variability of carbon dioxide and methane fluxes within the atmospheric boundary layer. The model is based on a one-and-a-half closure scheme for the Navier-Stokes and continuity equations, solved using Reynolds averaging and the Bussiness conjecture. Results: It was shown that a three-dimensional (3D) mathematical transfer models based on the solution of the equations of thermo-hydrodynamics are among the most effective methods for estimating vertical and horizontal fluxes of greenhouse gases in the atmosphere, taking into account the heterogeneous vegetation structure and surface topography. Based on the modeling results, maps of spatial distribution of turbulent exchange coefficient and horizontal wind speed at 5 m height, and maps of spatial distribution of CO2 and CH4 methane fluxes at 5, 25 and 50 m height were created. It was revealed that the "Roshni-Chu" forest area serves as a CO2 sink from the atmosphere under warm sunny weather in summer. The greatest uptake is detected near the local elevations. The fluxes of CH4 are almost negative, the lowest values of CH4 uptake are connected with uneven topography and are observed in small depressions between the hills. Conclusions: Based on the study of the wind field and the greenhouse gas fluxes at the carbon experimental site "Roshni-Chu" in the Chechen Republic, a significant spatial heterogeneity of the vertical CO2 and CH4 fluxes was revealed. The model approach, together with field measurements and remote sensing data, can be very effective for assessing the spatial heterogeneity of greenhouse gas fluxes at sites with non-uniform topography and vegetation. The method of modeling the spatial distribution of CO2 and CH4 fluxes within the atmospheric boundary layer can be used in different forest regions of the North Caucasus to describe the regional greenhouse gas balance.

Reasons for shortening snow cover duration in the Western Sudetes in light of global climate change

AbstractThis article discusses the reasons for shortening snow cover duration in the Western Sudetes, considering local changes in: air temperature; amount and type of precipitation; sunshine duration and atmospheric circulation leading to changes in the number of days with snow cover and its depth; and its start and end dates. All factors were linked to the exposure and relief of the study area. The analysis was made for the winter seasons (Nov–Apr) 1961/1962–2020/2021. It was found that the primary reasons for the shortening of snow cover duration in the Western Sudetes are: a multi‐year increase in air temperature and sunshine duration; changes in precipitation patterns—a decrease in the proportion of solid precipitation, changes in atmospheric circulation—including an increase in anticyclonic circulation types with sunny weather, especially in April (snow cover disappears in most of the elevation profile of the Sudetes); and less cyclonic weather types. The above factors synergistically affect the lower snow depth, and fewer days with solid precipitation, which promotes its faster spring ablation. In the subsequent 30 years (climatological norms), there is a successive shortening in its duration. On the snow cover start dates, there are no clear trends in the direction and rate of change. On end dates, negative trends are observed, in most cases statistically significant. The rate of change for the end dates of snow cover is about twice as high as the start dates. The rate of decline in snow cover is higher at stations at similar altitudes with northern macro‐exposure than southern. The results correspond with other studies from Europe and the world on the earlier disappearance of snow cover. They confirm the successive global warming and shortening snow cover duration, especially evident in the last few decades.

A Comparative Study of Abnormal Heating Composite Insulators.

The abnormal heating of composite insulators on transmission lines frequently occurs, seriously threatening the power grid's safe and stable operation. For different types of abnormal heating composite insulators, undifferentiated replacement wastes a lot of labor and material resources. This study explores the abnormal heating composite insulators under different environmental humidity and wind speed conditions. The heating and discharge of composite insulators are observed, and the heating range, heating shape, and temperature rise (ΔT) are analyzed. The abnormal heating of the sheath-aging composite insulator is related to the aging of the silicone rubber and the environmental humidity. The partial discharge caused by the core rod's defect is the primary source of the temperature rise in the decay-like insulator. The heating range of the contaminated insulator is connected to the environmental humidity, and the ΔT increases with the salt density. The ΔT and heating range of the three types of abnormal heating increase with the ambient humidity. The heating phenomenon under low humidity is an important characteristic that distinguishes decay-like and contaminated insulators from sheath-aging insulators. Therefore, the on-site infrared inspection should be carried out in sunny and windless weather to prevent the impact of high humidity and wind speed on infrared temperature measurement.

Comparative Experimental Investigation on Front Cooling for Tempered Glass Photovoltaic Thermal System

ABSTRACT Photovoltaic (PV) technology that converts solar energy into electricity is projected to play a significant role in renewable development in Malaysia. However, its electrical efficiency decreases with the increase in cell temperature. Therefore, a photovoltaic thermal (PV/T) system uses water to boost electrical efficiency by cooling PV cells. The PV/T system, on the other hand, is the combination of solar PV and solar thermal collector (STC) to simultaneously produce electricity and heated flowing fluid. This research study fabricated monocrystalline and polycrystalline PV panels with tempered glass and epoxy lamination to compare with front flow cooling PV/T systems using similar panels. The experiment with real-time data recording on power output and surface temperature was performed at Wisma R&D, the University of Malaya, during clear sunny weather in Kuala Lumpur, Malaysia. The highest daily electrical efficiency for Monocrystalline PV/T is 16.05%, while Polycrystalline PV/T produces 15% efficiency at a flow rate of 1.3 LPM. In comparison, monocrystalline and polycrystalline PVs have an average electrical efficiency of 14.54% and 13.80%, respectively. The highest thermal efficiency for Monocrystalline and Polycrystalline PV/T was 41.26% and 47.71% at a flow rate of 0.8 LPM. Monocrystalline PV/T has the best electrical efficiency, whereas Polycrystalline PV/T is the best for thermal efficiency.

Evaluating and Analyzing the Solar Public Street Lighting Utilization: A Case Study in Manokwari

Public Street Lighting (PSL) is one of the complementary road buildings used to illuminate the road. Solar Public Street Lighting (SPSL) is used in several places in Indonesia. Based on the background above, the objectives of this study are (1) to obtain the results of technical analysis of SPSL, (2) to obtain the results of economic analysis of SPSL development using investment schemes. The research was conducted in Manokwari Regency, West Papua. The research data were obtained from the results of measurements on solar panels to solar charge controllers and measurements from solar charge controllers to batteries in sunny, cloudy or rainy weather conditions from 08:00 WIT to 17:00 WIT. Economic analysis is carried out to obtain the parameters of Net Present Value (NPV), and Benefit Cost Ratio (B/C Ratio) with discount rates of 10% and 0%. The results showed that (1) based on technical analysis SPSL in Manokwari Regency has met public street lighting standards, in accordance with the Minister of Transportation Regulation No. 27 of 2018 concerning street lighting equipment. (2) An economic analysis shows that the development of SPSL with investment schemes is not feasible because the NPV value &lt; 0 with an IRR of 10%, and a B/C Ratio of &lt; 1. The construction of SPSL is economically feasible if the calculation of 0% IRR with the price of electricity per kWh reaches a value of IDR 14,411.32 or approximately ten times the price of Non-Subsidized PLN kWh electricity which is worth IDR 1,444.70.

The Impact of In-Vehicle Traffic Lights on Driving Characteristics in the Presence of Obstructed Line-of-Sight

In-vehicle traffic lights (IVTLs) have been identified as a potential means of eco-driving. However, the extent to which they influence driving characteristics in the event of obstructed on-road traffic lights (ORTLs) has yet to be fully examined. Firstly, the situation of partially deployed IVTLs in both vehicles was analyzed to identify the factors that affect driving characteristics. Through the following distance model, relative vehicle speed, acceleration and deceleration, and following distance were recognized as the contributing factors. The evaluation indicators for driving characteristics were thereby further established. Then, a hardware-in-the-loop simulation platform was built using PreScan 8.5-MATLAB/Simulink R2018b joint simulation software and a Logitech G29 device. IVTLs were implemented using modules in the joint simulation software. Finally, under the scenarios of obstructed ORTLs and various deployment conditions of IVTLs, the original data were collected from 50 experimental subjects with simulated driving. The subjects included 25 males and 25 females, all of whom were non-professional drivers, with ages ranging from 20 to 40 years old. The conclusion was reached that IVTLs could improve driving comfort by approximately 10% in sunny weather (p = 0.008 &lt; 0.05, p = 0.023 &lt; 0.05; p = 0.046 &lt; 0.05, p = 0.001 &lt; 0.05), driving maneuverability by approximately 30% in foggy weather (p = 0.033 &lt; 0.05), and driving safety by approximately 50% in the ORTLs obstructed by a truck scenario (p = 0.019 &lt; 0.05). In general, even if only one vehicle was equipped with IVTLs, certain gain effects on the driving characteristics of both vehicles could still be provided.

Heat and mass transfer analysis and optimization of passive interfacial solar still

Due to the fast thermal response and high solar energy efficiency, the passive interfacial solar still has become a reliable scheme for distributed water supply. In this paper, the thermodynamic performance of the interfacial solar still under different structures and operating conditions is studied experimentally, which provides an optimization direction for strengthening the distillation process. Firstly, based on the different Ra numbers, the calculation correlations for diffusion and convective mass transfer in the air interlayer were established to accurately predict the thermodynamic model of the interfacial distillation process. Then, the temperature distribution of the condenser and the growth process of condensate droplets were analyzed with the constant evaporation temperature. Simultaneously, the influence of different condensing structures and external variables on the heat transfer performance was compared. The results show that the interfacial still could obtain maximum evaporation heat under the vertical operation condition. When the evaporation temperature is 70 °C, the temperature difference between the wick evaporator and condenser can be increased by 49.5 %, after coupling a finned condenser with the aspect ratio of 7.2. In addition, a narrower interlayer spacing and a larger evaporation temperature could bring a higher equivalent heat transfer rate and evaporation efficiency. In a sunny weather, the interfacial solar still coupled with an extended condenser can reach a 4.81 kg/m2/day water yield and a 0.486 daily gained output ratio under 1 cm interlayer spacing.

Experimental investigation on indoor thermal environment improvement and energy-saving of electrochromic window under Singapore's tropical climate

This study aims at analyzing the thermal performance improvement of a gray tintable electrochromic window (EC window) under Singapore's tropical climate. Two climate chambers were experimentally studied, one with a double-glazed EC window and another with a single-glazing window, the most common in the considered region, as the reference. The indoor thermal environment and air conditioning energy consumption were compared respectively to investigate the thermal performance improvement of the EC window. The results, under the sunny outdoor weather condition, showed that the EC window could achieve an interior surface temperature reduction of 4.4 °C under the tinted state and 3.0 °C under the clear state, compared to the reference window. Moreover, the bleached EC window achieved up to 37% improvement in peak Predicted Mean Vote (PMV) over the reference window, while the fully tinted EC window achieved a 50% improvement in peak PMV. Finally, the EC window under the fully tinted state could achieve up to 19% energy savings compared to the reference window. Using the EC window under Singapore's tropical climate can improve the occupant thermal comfort during the daytime and reduce air conditioning energy consumption.

Design of pliek-u dryer using Dafa-type solar energy

One of the food diversification strategies of coconut commodity is to process it into Pliek U. Pliek U is a typical food of the Province of Aceh, Indonesia, which in its processing stage requires a drying process. So far, Pliek U drying process is often conducted conventionally through direct drying (sun drying), so that Pliek U produced is susceptible to dust and other dirt contamination. This research aimed to design a Pliek U dryer using Dafa type solar energy. The Dafa type solar energy dryer used a turbine ventilator with a vertical axis wind turbine equipped with two solar collectors. This turbine had a simple shape and construction and was arranged like the letter S. While the two parts of the solar collector were used to collect energy from the sun directly. In the experiment, the blank test was carried out in the time range, namely from 10.20 am to 04.50 pm in sunny weather, with an interval of 30 minutes for each temperature data recording. The empty test results of the Dafa type solar energy dryer showed that the average shelf temperature was 44.21 °C, the collector temperature was 45.64 °C, and the ambient temperature was 31.14 °C. This initial test revealed that the performance ability of the tool was very effective in maintaining temperature during the drying process, so that further tests using materials for drying Pliek U may be carried out.

A Reinforcement Learning Approach for Integrating an Intelligent Home Energy Management System with a Vehicle-to-Home Unit

These days, users consume more electricity during peak hours, and electricity prices are typically higher between 3:00 p.m. and 11:00 p.m. If electric vehicle (EV) charging occurs during the same hours, the impact on residential distribution networks increases. Thus, home energy management systems (HEMS) have been introduced to manage the energy demand among households and EVs in residential distribution networks, such as a smart micro-grid (MG). Moreover, HEMS can efficiently manage renewable energy sources, such as solar photovoltaic (PV) panels, wind turbines, and vehicle energy storage. Until now, no HEMS has intelligently coordinated the uncertainty of smart MG elements. This paper investigated the impact of PV solar power, MG storage, and EVs on the maximum solar radiation hours. Several deep learning (DL) algorithms were utilized to account for the uncertainties. A reinforcement learning home centralized photovoltaic (RL-HCPV) scheduling algorithm was developed to manage the energy demand between the smart MG elements. The RL-HCPV system was modelled according to several constraints to meet household electricity demands in sunny and cloudy weather. Additionally, simulations demonstrated how the proposed RL-HCPV system could incorporate uncertainty, and efficiently handle the demand response and how vehicle-to-home (V2H) can help to level the appliance load profile and reduce power consumption costs with sustainable power production. The results demonstrated the advantages of utilizing RL and V2H technology as potential smart building storage technology.

METHOD OF COUNTING OBJECTS IN AN ORCHARD IN REAL TIME

The paper proposes a novel method for counting apples in an orchard using unmanned aerial vehicles (UAVs), also known as drones. The authors acknowledge that traditional methods of counting apples are time-consuming and labor-intensive and therefore propose a more efficient and accurate solution using a group of drones equipped with high-resolution cameras. The proposed method involves using a convolutional neural network (CNN) called YOLOv5-v1 to detect and count the apples in the images captured by the drones. YOLOv5-v1 was trained using a dataset of annotated images of apples in different lighting conditions and orientations and was found to be highly accurate in identifying and counting apples in test images. The proposed method was tested on two different orchards and was highly accurate. Specifically, the results of the experimental studies show that the model accuracy was: i) in sunny weather – 92.11%, ii) in cloudy weather – 90.76%, and iii) in sunny weather, but with high shading – 82.69%. Such results indicate that under sunny and overcast weather conditions with a low level of shade, the proposed approach demonstrates high accuracy and reliability in real-time operation. At the same time, it should be noted that due to the presence of significant visual noise in the orchard, such as the covering of fruits by leaves and branches, the efficiency of the UAV group and the automated system, in general, cannot be 100% fulfilled in natural conditions, which can serve as a promising task for further of research. Overall, the proposed method of counting structural objects provides an efficient and accurate solution for counting apples in orchards, which could save time and resources for farmers. The use of UAVs and CNNs in agriculture is a promising area of research, and this paper presents a practical application of these technologies in fruit counting.

Investigating the impact of air pollution in selected African developing countries.

Air pollution is a major challenge faced by most countries due to the continuous quest of industrialization leading to a high pollution, which Africa is not an exception. Nowadays countries are trying to regulate their carbon emission by transitioning from traditional methods to modern technologies. However, measures to reduce environmental pollution due to carbon emissions and PM2.5 do not receive rational attention and represent a serious threat to the continent. The aim of this study is to investigate the impact of the adoption of green innovation technologies on carbon and particulate matter (PM2.5) emission reduction in some of the most polluted African countries and its effect on the economic growth from 2000 to 2019. We based on cross-sectional dependency analysis, unit root test, and other robust tests for the data analysis since they are best fit and accurate for the data interpretation. The short- and long-term CS-ARDL empirical evidence showed a negative and significant impact of the adoption of green energy technology innovation on carbon and particulate matter emissions, implying that the adoption of green energy technology significantly reduces the emission of carbon and PM2.5 emissions. However, the results show that the use of non-renewable energies has a negative effect on environmental sustainability since it increases carbon and particle matter emissions. There is a need for the selected African countries to efficiently adopt ecofriendly technologies to reduce their carbon and PM2.5 emissions and take advantage of natural resources such as the constant sunny weather to implement the installation of solar panels as a source of energy and other technologies. Various recommendations have been made to effectively reduce CO2 and particulate matter emissions; future studies should be conducted on the implementation of the recommended policies.