United Parcel Service (United States)

Agricultural diversification represents an important strategy for promoting sustainability and resilience in rural regions. Goji berries (Lycium barbarum) have emerged as a promising alternative crop due to their high nutritional and functional potential. In this sense, the search for new crops to diversify the production in southwestern Spain is of main interest for farmers to adapt their productions to consumers claims and to climate change, having alternatives to the classical crops (olives, grapes for wine, etc.). This study evaluated several quality related parameters of three goji berry varieties cultivated in the southwest of Spain. Texture profile analysis (TPA) and puncture tests revealed varietal differences in firmness, cohesiveness, and springiness, influenced by genotype and harvesting time. Other morphological and quality parameters such as moisture, total soluble solids, titratable acidity and color were also affected. Significant differences in antioxidant capacity (ABTS and DPPH assays) were found among the varieties and harvesting times, with NQ7 exhibiting the highest values. Phenolic compounds were identified and quantified by LC–HRMS/MS, detecting 33 compounds, with most belonging to the hydroxycinnamic acids, flavonols and flavanones families. NQ7 presented the highest total phenolic content (74.787 mg/100 g DW), with rutin, coumaric acid derivatives, and naringenin as major contributors. The correlation analysis confirmed a strong relationship between total phenolic content and antioxidant capacity. Overall, the results indicated that goji berries grown in southwestern Spain exhibited favorable quality and bioactive profiles, supporting their suitability for sustainable production and commercialization, including further applications as functional food ingredients.

Roadway surface type classification (e.g., unpaved, asphalt, concrete) is an essential data element for road safety analysis and required as part of the Model Inventory of Roadway Elements (MIRE) Fundamental Data Elements (FDEs). Supplementary guidance issued by the Federal Highway Administration (FHWA) requires detailed surface type classification for the National Highway System (NHS) and roads functionally classified as interstates; however, less detailed surface type attribute group values (i.e., unpaved surface, asphalt pavement, concrete pavement, and other paved surface) are required for all remaining road segments that are not a part of the NHS. As part of a FHWA data analysis technical assistance (DATA) team, the research team worked with the Kansas Department of Transportation (KDOT) to develop a machine learning model capable of initially categorizing roads to reduce the level of effort required to satisfy the full MIRE FDE requirements. The research team conducted a pilot image classification analysis and determined a potential workflow for a broader statewide study area. This paper outlines the pilot methodologies and results. The team developed a support vector machine (SVM) learning model combined with Bayesian statistics that classified roads as paved or unpaved from aerial imagery with an overall model accuracy of 95%.

Abstract We discuss the kinetic theory of stellar systems and two-dimensional vortices and stress their analogies. We recall the derivation of the Landau and Lenard–Balescu equations from the Klimontovich formalism. These equations take into account two-body correlations and are valid at the order 1/N, where N is the number of particles in the system. They have the structure of a Fokker–Planck equation involving a diffusion term and a drift term. The systematic drift of a vortex is the counterpart of the dynamical friction experienced by a star. At equilibrium, the diffusion and the drift terms balance each other establishing the Boltzmann distribution of statistical mechanics. We discuss the problem of kinetic blocking in certain cases and how it can be solved at the order $$1/N^2$$ 1 / N 2 by the consideration of three-body correlations. We also consider the behaviour of the system close to the critical point following a recent suggestion by Hamilton and Heinemann (2023). We present a simple calculation, valid for spatially homogeneous systems with long-range interactions described by the Cauchy distribution, showing how the consideration of the Landau modes regularizes the divergence of the friction by polarization at the critical point. We mention, however, that fluctuations may be very important close to the critical point and that deterministic kinetic equations for the mean distribution function (such as the Landau and Lenard–Balescu equations) should be replaced by stochastic kinetic equations.