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Today, the global food security is one of the most pressing issues for humanity, and, according to Food and Agriculture Organisation (FAO), the increasing demand for food is likely to grow by 70% until 2050. In this current condition and future scenario, the agricultural production is a critical factor for global food security and for facing the food security challenge, with specific reference to many African countries, where a large quantities of rice are imported from other continents. According to FAO, to face the Africa’s inability to reach self-sufficiency in rice, it is urgent “to redress to stem the trend of over-reliance on imports and to satisfy the increasing demand for rice in areas where the potential of local production resources is exploited at very low levels” The present study was undertaken to design a new method for land evaluation based on soil quality indicators and remote sensing data, to assess and map soil suitability for rice crop. Results from the investigations, performed in some areas in the northern part of the Nile Delta, were compared with the most common approaches, two parametric (the square root, Storie methods) and two qualitative (ALES and MicrioLEIS) methods. From the qualitative point of view, the results showed that: (i) all the models provided partly similar outputs related to the soil quality assessments, so that the distinction using the crop productivity played an important role, and (ii) outputs from the soil suitability models were consistent with both the satellite Sentinel-2 Normalize Difference Vegetation Indices (NDVI) during the crop growth and the yield production. From the quantitative point of view, the comparison of the results from the diverse approaches well fit each other, and the model, herein proposed, provided the highest performance. As a whole, a significant increasing in R2 values was provided by the model herein proposed, with R2 equal to 0.92, followed by MicroLES, Storie, ALES and Root as R2 with value equal to 0.87, 0.86, 0.84 and 0.84, respectively, with increasing percentage in R2 equal to 5%, 6% and 8%, respectively. Furthermore, the proposed model illustrated that around (i) 44.44% of the total soils of the study area are highly suitable, (ii) 44% are moderately suitable, and (iii) approximately 11.56% are unsuitable for rice due to their adverse physical and chemical soil properties. The approach herein presented can be promptly re-applied in arid region and the quantitative results obtained can be used by decision makers and regional governments.

Air pollution is a major issue all over the world because of its impacts on the environment and human beings. The present review discussed the sources and impacts of pollutants on environmental and human health and the current research status on environmental pollution forecasting techniques in detail; this study presents a detailed discussion of the Artificial Intelligence methodologies and Machine learning (ML) algorithms used in environmental pollution forecasting and early-warning systems; moreover, the present work emphasizes more on Artificial Intelligence techniques (particularly Hybrid models) used for forecasting various major pollutants (e.g., PM2.5, PM10, O3, CO, SO2, NO2, CO2) in detail; moreover, focus is given to AI and ML techniques in predicting chronic airway diseases and the prediction of climate changes and heat waves. The hybrid model has better performance than single AI models and it has greater accuracy in prediction and warning systems. The performance evaluation error indexes like R2, RMSE, MAE and MAPE were highlighted in this study based on the performance of various AI models.

In this study, the characterization of several bacterial diseases affecting silver birch (Betula pendula Roth.), common ash (Fraxinus excelsior L.), white poplar (Populus alba L.), and white willow (Salix alba L.) in Ukraine were described. The typical symptoms, features of pathogenesis, and characteristics of the causative agents of the most common bacterial diseases of these tree species were shown. The following types of bacterioses were noted to be especially dangerous, namely, bacterial wetwood, fire blight, bacterial canker, and tuberculosis. Bacterial necrosis of the bark was a less dangerous disease. At the same time, all of the listed types of bacterioses were registered within the forest areas of the investigated region. The study revealed that bacterial wetwood of birch and poplar was caused by Lelliottia nimipressuralis; the bacterial canker of poplar is Pseudomonas syringae (Pseudomonas syringae f. populi and Pseudomonas cerasi); the fire poplar blight is caused by Pseudomonas cerasi (P. syringae); the common ash tuberculosis is caused by Pseudomonas syringae pv. savastanoi; and the bacterial wilt of the willow is caused by Brenneria salicis. The phenomenon of the introduction of microorganisms of different functional orientations as well as the formation of conditions for their activity in the rhizosphere of plants have been studied. In the future, it will provide the development of effective methods for the rapid identification of causative agents of bacterioses and plant protection measures based on multi-functional microbiological preparations based on highly effective strains of microorganisms.

Road traffic crashes represent a substantial global public health issue. In Saudi Arabia, which is the focus area of this research, road traffic crashes kill over 130,000 people annually, accounting for almost 5% of deaths in that country. A cross-sectional study with 316 participants holding a valid Saudi driver’s license was conducted via the internet from December 2019 to March 2020 to collect information about the prevalence of risky driving habits among Saudi drivers. The sample was predominantly men and aged between 20 and 39, which is representative of the population of drivers in Saudi Arabia. Drivers generally reported engaging in safe behaviors, although they did state that they drove above the legal speed limit, drove aggressively around slow drivers, and became distracted while driving with some frequency. Multivariate analyses suggested men took more risks than women and younger drivers took more risks than older ones. We conclude that the behavior among drivers in Saudi Arabia generally matches those in other cultures and countries, with men and young adults taking the most risks while driving. Preventative strategies should be developed and implemented in Saudi Arabia.

Agriculture is increasingly facing major challenges such as climate change, scarcity of natural resources and changing societal demands. To tackle these challenges there is a pressing need to evolve towards more sustainable agricultural practices. As a result, sustainability stands among the most relevant topics in agricultural research worldwide, and Spain is no exception. Agricultural sustainability has been analysed in Spain mainly at a national and farm scale. This contribution aims at assessing agricultural sustainability in Spain at a provincial scale, allowing the scrutiny of regional variability induced by the existing differences in extension, relevance and policies of the agricultural activity at this level. The sustainability assessment performed is based on a selection of twenty-two indicators covering the three classical dimensions of sustainability—environmental, economic and social. The methodology implemented is based on normalising and aggregating selected indicators according to three composite indicators for the fifty Spanish provinces. Numerous statistical and cartographic sources are used. Cluster analysis establishes four different groups of provinces according to their performance in terms of agricultural sustainability. Higher economic sustainability in provincial agriculture seems to be mostly associated with more intensive use of agricultural labour and agricultural machinery and faster wealth growth. Social sustainability seems to be linked to greater diversification of economic activities and to quality productions under Protected Designations of Origin (PDO) and Protected Geographical Indications (PGI). Best environmental sustainability is achieved where extension of agricultural land is larger, less agricultural area is burned, and carbon stock and sequestration by agricultural ecosystems is better. It is expected that the results could improve the policy coherence and decision-making for more sustainable agricultural systems in Spanish regions.

(1) Background: the purpose of this study was a preliminary analysis of current methods of online teaching at the Faculty of Medical Sciences, University of Kragujevac, Republic of Serbia, in order to define the attitudes of biomedical students about education during the COVID-19 pandemic and to validate of the education medical questionnaire (eMedQ), a new tool for the assessment of the students’ perceptions about digital education. (2) Methods: this was a qualitative cross-sectional observational study that used the originally developed 45-item questionnaire (eMedQ) as an assessment instrument conducted on biomedical students (n = 209) of all study years at the Faculty of Medical Sciences, University of Kragujevac (Republic of Serbia), during winter semester or between September 2021 and January 2022. (3) Results: In this study, a Cronbach’s alpha value of 0.904 was obtained, which indicated good internal consistency; the correlation matrix revealed many coefficients greater than 0.3, denoting high correlations between the items. The Kaiser–Meyer–Olkin measure of sampling adequacy was 0.866 and Bartlett’s test of sphericity was significant (p < 0.001). The PCA revealed the presence of seven components with characteristic values over one, while three factors explained the highest percentage of variance. (4) Conclusions: this research developed and validated a new tool for evaluation of biomedical student perceptions about digital education.

The purpose of this study was to examine the vegetation dynamics of various lawn grass species in the city of Apatity, Murmansk region, when exposed to anthropogenic and atmospheric pollution impacts. The dust concentration in the atmospheric air was recorded, its mineralogical analysis was carried out, and the dynamics of the development of various lawn types under the anthropogenic load was studied. Cases of exceeding the MPC of dust particles in the atmospheric air were recorded. Nepheline grains were found in the dust samples, which is indicative of pollution migration from the nearby tailings storage facility. It was shown that lawns are able to grow intensively in severe climatic conditions and under the influence of mining and processing enterprises.

Fruits are commonly used, fresh or processed, to prepare different industrial products with superior nutritional and health-promoting properties. Currently, the demand for processed fruit products has motivated the rapid growth of the fruit processing industries, persuading them to produce an enormous amount of by-products with less utilization. Furthermore, people's shifting dietary habits and lack of awareness of nutritional properties result in an avoidable load of fruit by-products. The knowledge of the value of by-products urges exploration with proper documentation, emphasizing the health benefits of some such products. Hence, this review is prepared by carefully analyzing the recent literature on industrial applications of fruit by-products and their nutritional and health-promoting properties. The use of fruit by-products in food industries for various purposes has been reported in the past and has been reviewed and described here. Fruit by-products are a good source of nutrients and bioactive components, including polyphenols, dietary fibers, and vitamins, implying that they could have an important role for novel, value-added functional food properties. Furthermore, fruit by-products are used as the substrate for the production of organic acids, essential oils, enzymes, fuel, biodegradable packaging materials, and preservatives.