Honeys from the Argentine Phytogeographic Provinces Chaqueña and Monte in Catamarca and La Rioja by Aimará Ayelen Poliero, Inés Aubone, Marisa Amadei Enghelmayer, Valeria Soledad Rosso, Sandra Rosa Fuselli, Rosa Maria Alonso-Salces

“… The characterization of the Argentinean honeys from the vegetation units (VU) of the Phytogeographical Provinces located in Catamarca and La Rioja was performed by the analysis used for honey quality control: sugar profile, free acidity, pH, electrical conductivity (EC), color and contents of moisture, ash, total soluble solids and hydroxymethylfurfural. …”
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Hydrologic responses of watershed assessment to land cover and climate change using soil and water assessment tool model by R.C.C. Puno, G.R. Puno, B.A.M. Talisay

“…The increase of forest vegetation resulted in a minimal decrease in baseflow and surface runoff. …”
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Application of the ESTARFM algorithm for fusing Sentinel-2 and MODIS NDSI series in the eastern Qilian Mountains by Hui Guo, Xiaoyan Wang, Zhiqi Ouyang, Siyong Chen, Tao Che, Zhaojun Zheng

“…New hydrological insights: Most fusion studies have focused on algorithm development and applied these algorithms to vegetation phenology. Our findings show that using ESTARFM could increase the accuracy of snow cover monitoring in mountainous areas. …”
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A comprehensive environmental index for monitoring ecological quality of typical alpine wetlands in Central Asia by Jiudan Zhang, Junli Li, Changming Zhu, Anming Bao, Amaury Frankl, Philippe De Maeyer, Tim Van de Voorde

“…Meanwhile, improvements were also observed in hydrological conditions, vegetation vitality, and aboveground biomass, coupled with a reduction in wetland landscape fragmentation, improving ecological stability. …”
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Land cover classification for Siberia leveraging diverse global land cover datasets by Munseon Beak, Kazuhito Ichii, Yuhei Yamamoto, Ruci Wang, Beichen Zhang, Ram C. Sharma, Tetsuya Hiyama

“…However, in warm summer climates, precipitation plays a critical role in vegetation distribution. The more accurate and detailed land cover created in this study enhances the reliability of analyses in Siberia and fosters a deeper understanding of the impact of the carbon cycle.…”
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Agro-Morphological Characterization of Kenyan Slender Leaf (Crotalaria brevidens and C. ochroleuca) Accessions by Fridah A. Mwakha, Bernard M. Gichimu, Johnstone O. Neondo, Peter K. Kamau, Eddy O. Odari, Joshua K. Muli, Nancy L. M. Budambula

“…Slender leaf (Crotalaria spp) is among the indigenous and underutilized vegetables in Kenya whose production is limited to the Western and Coastal regions of the country. …”
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Permafrost Dynamics Observatory: 3. Remote Sensing Big Data for the Active Layer, Soil Moisture, and Greening and Browning by Elizabeth Wig, Kevin Schaefer, Roger Michaelides, Richard Chen, Leah K. Clayton, Brittany Fager, Lingcao Huang, Andrew D. Parsekian, Howard Zebker, Yingtong Zhang, Yuhuan Zhao

“…All permafrost variables show statistically significant differences from one land cover type to another; in particular, cropland has thicker active layers and developed land has lower seasonal subsidence than most other land cover types, potentially related to disturbance and permafrost thaw. While vegetation browning is not strongly associated with any of the measured permafrost variables, more greening is associated with less subsidence and ALT and with higher bulk soil VWC.…”
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Statewide Forest Canopy Cover Mapping of Florida Using Synergistic Integration of Spaceborne LiDAR, SAR, and Optical Imagery by Monique Bohora Schlickmann, Inacio Thomaz Bueno, Denis Valle, William M. Hammond, Susan J. Prichard, Andrew T. Hudak, Carine Klauberg, Mauro Alessandro Karasinski, Kody Melissa Brock, Kleydson Diego Rocha, Jinyi Xia, Rodrigo Vieira Leite, Pedro Higuchi, Ana Carolina da Silva, Gabriel Maximo da Silva, Gina R. Cova, Carlos Alberto Silva

“…This study demonstrates the potential of integrating multiple remote sensing datasets to produce accurate vegetation maps, supporting forest management and sustainability efforts in Florida.…”
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Impact of Irrigation Regimes on Growth and Postharvest Quality of Pomegranates (Punica granatum L.) under Conditions of Newly Reclaimed Land by Magdi A.A. Mousa, Adel D. Al-Qurashi, Omer H.M. Ibrahim, Kamal A.M. Abo-Elyousr, Ahmed M.K. Abdel Aal, Abdel-Fattah M. El-Salhy, Tarek K.H. El-Bolok, Mohamed A.H. Ali, Esmat F. Ali, Eman A.A. Abou-Zaid

“…Results revealed that applying irrigation at a rate of 75% enhanced fruit quality and yield, mitigated sun sting and cracking, and improved vegetative growth. Moreover, water use efficiency (WUE) was increased, which was reflected in the increase of the percentage of commercial and marketing fruits and decreased production costs when applying 75% of the water ration, which maintains soil and natural resources for sustainable agriculture.…”
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Impact of lifestyle factors on oral cancer risk and prevention: Oral cancer epidemiology by Iadalin Ryntathiang, N. Aravindha Babu, Silambarasan Tamil Selvan, Mukesh Kumar Dharmalingam Jothinathan

“…Nutrients represent, among other factors, oral cancer risk, which is demonstrated in epidemiology data by the protective effects of fruits and vegetables and the possible risks of high-meat diets. …”
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Identifying Optimal Variables to Predict Soil Organic Carbon in Sandy, Saline, and Black Soil Regions: Remote Sensing, Terrain, or Climate Factors? by Liping Wang, Huanjun Liu, Xiang Wang, Xiaofeng Xu, Liyuan He, Chong Luo, Yong Li, Xinle Zhang, Deqiang Zang, Shufeng Zheng, Xiaodan Mei

“…Our results indicated that (1) climate factors, particularly mean annual precipitation and mean annual temperature, were the most effective predictors in SOC mapping across sandy, saline, and black soil regions, as indicated by their significant contribution to RF model performance (R² > 0.63); (2) followed by climate factors, the Transformed Vegetation Index (TVI) was consistently identified as the most influential variable for SOC prediction among spectral indexes in all three regions; (3) a local regression method based on RF models showed good performance compared to a global model; (4) desertification and salinization were the main reasons for the spatial differences in AH and DM&LD, respectively. …”
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A global gross primary productivity of sunlit and shaded canopies dataset from 2002 to 2020 via embedding random forest into two-leaf light use efficiency modelZenodo by Zhilong Li, Ziti Jiao, Ge Gao, Jing Guo, Chenxia Wang, Sizhe Chen, Zheyou Tan

“…This GPP product provides a data basis for improving our understanding of the dynamics of global vegetation productivity and its interactions with the changes in environmental conditions.…”
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The assessment of dairy goats’ welfare in alpine summer ranges by Manuela Renna, Benedetta Torsiello, Silvana Mattiello, Luca Battaglini, Monica Battini

“…These indicators were collected from a distance, and with limited visibility due to adverse weather conditions, thick vegetation cover or rocky areas, thus explaining the unacceptable reliability. …”
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Sistemas Fisiográficos del Área Natural Protegida "Valle Cretácico"; Provincia de Río Negro by Nora Romina Solorza, Marcos Damián Mare

“…The physiographic systems study shows that there is a marked susceptibility to the erosion processes increase, especially gully erosion. The natural vegetation, as a consequence of its physiognomic characteristics adapted to semiarid and mesothermal climate and of the historical social land use overloading , currently presents a low coverage, associated with low levels of soil aggregation. …”
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Componentes y Dinámica Natural del Ambiente - Ciudad de Neuquén- by Olga Capua, Elsie Marcela Jurio

“…Además, la baja cobertura vegetal y la características propias de los suelos propician la acción directa del viento sobre la superficie favoreciendo los procesos de erosión -deflación, abrasión y atrición- y acumulación eólicos. …”
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Prediction of Winter Wheat Parameters with Planet SuperDove Imagery and Explainable Artificial Intelligence by Gabriele De Carolis, Vincenzo Giannico, Leonardo Costanza, Francesca Ardito, Anna Maria Stellacci, Afwa Thameur, Sergio Ruggieri, Sabina Tangaro, Marcello Mastrorilli, Nicola Sanitate, Simone Pietro Garofalo

“…Different machine learning (ML) algorithms were trained and compared using spectral band data and calculated vegetation indices (VIs) as predictors. Model performance was assessed using R² and RMSE. …”
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Deep Brain Stimulation in the treatment of disorders of consciousness by Joanna Olszak, Karolina Zalewa, Lidia Bartoszek, Dominika Orłowska, Wojciech Kapłan, Mikołaj Poleszczuk, Karol Poleszczuk, Alicja Milewska, Anna Czuba, Marta Kaus

“… Introduction and Purpose  Disorders of consciousness, such as the vegetative state (VS) and minimally conscious state (MCS), are significant neurological conditions where patients exhibit limited or no awareness of their surroundings. …”
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Study on the effects of land use transformation on habitat quality and its driving mechanisms: a case study of the Qin-Mang River Basin by Jiwei Zhao, Luyao Wang, Dong Jia, Yaowen Wang

“…The HQ index decreased from 0.3409 in 1992 to 0.2896 in 2022, with a significant increase in spatial heterogeneity. Altitude, vegetation coverage, temperature, precipitation, and slope are the main driving factors influencing HQ, with natural factors dominating, but human activities gradually playing an increasingly significant role. …”
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Dietary phytochemicals alleviate the premature skin aging: A comprehensive review by Harpreet Singh, Y.T. Kamal, Jessica Pandohee, Arun Kumar Mishra, Aritra Biswas, Sourav Mohanto, Arvind Kumar, Sagnik Nag, Amrita Mishra, Mhaveer Singh, Himanshu Gupta, Hitesh Chopra

“…Dietary phytochemicals, present in fruits, vegetables, and other plant-derived meals, have gained interest due to their efficiency to eradicate free radicals and lowering the release of inflammatory mediators which accounts for premature skin aging. …”
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First insights into the spatio-temporal ecology of sympatric large carnivores in Niokolo-Koba National Park, Senegal by Robin Horion, Zoe Woodgate, Marine Drouilly

“…Spotted hyaena site use was positively associated with leopard relative abundance index and negatively associated with normalized difference vegetation index, whereas only distance to the nearest road influenced leopard site use. …”
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