Abstract
Reinforced concrete structures are an essential part of our modern society, and monitoring their structural health is of paramount importance. Early detection of decay allows for the reduction of repair costs and, more importantly, the prevention of catastrophic failure. For this purpose, a single fiber reflectance spectrometer was embedded in cement paste samples for the monitoring of water at the fiber tip through its sensitivity to changes in the refractive index. It monitored the curing of samples with different water-to-cement ratios (w/c), between 0.45 and 0.60, measuring the water exhaust during the hardening of the cement paste. It also measured the capillary coefficient from cement paste samples of 0.50, 0.55 and 0.60 w/c: 0.668 & PLUSMN; 0.002 mm/& RADIC;h, 1.771 & PLUSMN; 0.052 mm/& RADIC;h and 6.360 & PLUSMN; 0.269 mm/& RADIC;h, respectively. The capillary coefficient values agree with gravimetric measurements of sorptivity and are further confirmed through porosity measurements made with a scanning electron microscope. Thus, single fiber reflectance spectroscopy can be a gateway to inexpensively measure the entire life cycle of cement, from its curing until its eventual decay, assessing, in situ, its durability through the capillary coefficient.

Abstract
Relative humidity monitorization is of extreme importance on scientific and industrial applications, and fiber optics-based sensors may provide solutions where other types of sensors have limitations. In this work, fiber optics’ sensors were fabricated by combining Long-Period Fiber Gratings with three different humidity-responding polymers, namely Poly(vinyl alcohol), Poly(ethylene glycol) and Hydromed™ D4. The performance of the multiple sensors was experimentally tested and crossed with numerical simulations, which provide a comparison with the expected response given the optical properties of the materials.

Abstract
Listeria monocytogenes has been referred to as a concern microorganism in cheese making due to its ability to survive and grow in a wide range of environmental conditions, such as refrigeration temperatures, low pH and high salt concentration at the end of the production process. Since cheese may be a potential hazard for consumers, especially high-risk consumers (e.g., pregnant, young children, the elderly, people with medical conditions), efforts of the dairy industry have been aimed at investigating new conservation techniques based on natural additives to meet consumers' demands on less processed foods without compromising the food safety. Thus, the aim of this study was to evaluate the efficacy of Myrtus communis L. (myrtle) and Rosmarinus officinalis L. (rosemary) essential oils (EO) against Listeria monocytogenes ATCC 679 spiked in sheep cheese before ripening. After the cheesemaking process, the samples were stored at 8 degrees C for 2 h, 1 d, 3 d, 14 d and 28 d. The composition of EO was identified by gas chromatography-mass spectrometry (GC-MS) analysis. Constituents such as 1,8-cineole, limonene, methyl-eugenol, alpha-pinene, alpha-terpineol, alpha-terpinolene and beta-pinene were present in both EO, accounting for 44.61% and 39.76% from the total of chemical compounds identified for myrtle and rosemary EO, respectively. According to the chemical classification, both EO were mainly composed of monoterpenes. Minimum inhibitory concentration (MIC) against L. monocytogenes was obtained at 31.25 mu L/mL to myrtle EO and at 0.40 mu L/mL to rosemary EO. Then, cheeses were inoculated with L. monocytogenes (Ca. 6 log CFU/mL) and EO was added at MIC value. The addition of rosemary and myrtle EO displayed lower counts of L. monocytogenes (p < 0.01) (about 1-2 log CFU/g) during the ripening period compared to control samples. Ripening only influences (p < 0.001) the growth of L. monocytogenes in control samples. Since rosemary and myrtle EO do not exert any negative impact on the growth of native microflora (p > 0.05), their use as natural antimicrobial additives in cheese demonstrated a potential for dairy processors to assure safety against L. monocytogenes.

Abstract
Food fraud is a growing problem and happens in many ways including mislabelling. Since lack of consumers' knowledge about mandatory food labeling information and different types of food fraud may impact public health, the present work assesses consumers' knowledge about these issues. Principal component analysis was performed to obtain a smaller number of uncorrelated factors regarding the usefulness and confidence of information displayed in food labels and the perception of food fraud. Results indicated that information displayed in food labels is useful, however the way it is presented may decrease consumer interest and understanding. Regarding respondents' confidence in foodstuffs, over half of them stated that information provided in food labels is reliable. However, a lack of confidence about food composition is observed in those processed foodstuffs such as meat products. Food fraud is recognized by more than half of respondents with a higher perception of those practices that imply a risk to public health than those related to economic motivation. Age and education of consumers influenced the perception of the information displayed in the food labels, their confidence and knowledge about food fraud. Implementation of education programs to increase consumer knowledge about food labelling and fraud is essential. Respondents' perception results could be use as guidelines by the food industry to improve food label design in order to enhance consumer understanding.

Abstract
In this work, a multi-parameter point sensor based on the combination of Fabry-Perot (FP) and the anti-resonant (AR) reflecting guidance in cascade configuration is proposed and experimentally demonstrated. This structure, based on FP interference and AR reflecting guidance, was fabricated with two different air micro-cavities. The attained experimental results showed different strain and temperature sensitivities for the antiresonance contribution. However, when analyzing the FP interference, only strain sensitivity was observed, demonstrating that this air micro-cavity was also insensitive to temperature variations.

Abstract
With the advent of personalized medicine, there is a movement to develop "smaller" and "smarter" microdevices that are able to distinguish similar cancer subtypes. Tumor cells display major differences when compared to their natural counterparts, due to alterations in fundamental cellular processes such as glycosylation. Glycans are involved in tumor cell biology and they have been considered to be suitable cancer biomarkers. Thus, more selective cancer screening assays can be developed through the detection of specific altered glycans on the surface of circulating cancer cells. Currently, this is only possible through time-consuming assays. In this work, we propose the "intelligent" Lab on Fiber (iLoF) device, that has a high-resolution, and which is a fast and portable method for tumor single-cell type identification and isolation. We apply an Artificial Intelligence approach to the back-scattered signal arising from a trapped cell by a micro-lensed optical fiber. As a proof of concept, we show that iLoF is able to discriminate two human cancer cell models sharing the same genetic background but displaying a different surface glycosylation profile with an accuracy above 90% and a speed rate of 2.3 seconds. We envision the incorporation of the iLoF in an easy-to-operate microchip for cancer identification, which would allow further biological characterization of the captured circulating live cells.