A community food environment plays an essential role in explaining the healthy life-style patterns of its community members. However, there is a lack of compelling quantitative approaches to evaluate these environments. This study introduces and validates a new tool named the Facility List Coder (FLC), whose purpose is to assess food environments based on data sources and classification algorithms. Using the case of Mataró (Spain), we randomly selected 301 grids areas (100 m2) where we conducted street audits in order to physically identify all the facilities by name, address and type. Then, audit-identified facilities were matched with those automatically-identified and were classified using the FLC in order to determine its quality. Our results suggest that automatically-identified and audit-identified food environments have a high level of agreement. The ICC estimates and their respective 95% confidence intervals for the overall sample, yield the result “excellent” (ICC ≥ 0.9) for the level of reliability of the FLC.

This article proposes a monitoring system that allows to track transitions between different stages in the berry harvesting process (berry picking, waiting for transport, transport, and arrival to the packing) solely using information from temperature and vibration sensors located in the basket. The monitoring system assumes a characterization of the process based on Hidden Markov Models and uses the Viterbi algorithm to perform inference and estimate the most likely state trajectory. The obtained state trajectory estimate is then used to compute a potential damage indicator in real-time. The proposed methodology does not require information about the weight of the basket to identify each of the different stages, which makes it effective and more efficient than other alternatives available in the industry.

A method is developed to identify molecular scaffolds potentially active against the Mycobacterium tuberculosis complex (MTBC). A structurally heterogeneous set of compounds active against MTBC was used to obtain a structural pattern model based on structural invariants. This model was statistically validated through a Leave-n-Out test. It successfully discriminated between active or inactive compounds over 86% in database sets and was also able to select new active chemical structures in external databases. The selection of new substituted pyrimidines, pyrimidones and triazolo[1,5-a]pyrimidines was particularly interesting because these structures could provide new scaffolds in this field. The seven selected candidates were synthesized and six of them showed activity in vitro.

A single-center, randomized, double-blind, placebo-controlled clinical trial with two arms was conducted in 71 healthy subjects suffering from sleep disturbances, which were treated with a dietary supplement based on an extract of Aloysia citrodora (or Lippia citriodora, lemon verbena) (n = 33) for 90 days. Subjects in the placebo group (n = 38) received capsules of microcrystalline and maltodextrin with the same organoleptic properties. Between-group significant differences in favor of the experimental group were found in the visual analogue scale (VAS) score rating sleep quality; overall score, sleep latency and sleep efficiency of the Pittsburg Sleep Quality Index (PSQI); and sleep latency, sleep efficiency, wakefulness after sleep onset and duration of awakening assessed by actigraphy. Plasma nocturnal melatonin levels also increased significantly in the experimental group. Changes in anthropometric parameters and physical activity levels were not found. This study shows that the administration of a dietary supplement comprised lemon verbena administered for 3 months was associated with a significant improvement of sleep quality as compared with placebo in a population of healthy subjects with sleep problems. Improvements were also apparent at the mid-study visit after 45 days of supplementation.