Assessing the dynamic behavior of wsn motes and rfid semi-passive tags for temperature monitoring.

A notorious advantage of wireless transmission is a significant reduction and simplification in wiring and harness. There are a lot of applications of wireless systems, but in many occasions sensor nodes require a specific housing to protect the electronics from hush environmental conditions. Nowadays the information is scarce and nonspecific on the dynamic behaviour of WSN and RFID. Therefore the purpose of this study is to evaluate the dynamic behaviour of the sensors. A series of trials were designed and performed covering temperature steps between cold room (5 °C), room temperature (23 °C) and heated environment (35 °C). As sensor nodes: three Crossbow motes, a surface mounted Nlaza module (with sensor Sensirion located on the motherboard), an aerial mounted Nlaza where the Sensirion sensor stayed at the end of a cable), and four tags RFID Turbo Tag (T700 model with and without housing), and 702-B (with and without housing). To assess the dynamic behaviour a first order response approach is used and fitted with dedicated optimization tools programmed in Matlab that allow extracting the time response (?) and corresponding determination coefficient (r2) with regard to experimental data. The shorter response time (20.9 s) is found for the uncoated T 700 tag which encapsulated version provides a significantly higher response (107.2 s). The highest ? corresponds to the Crossbow modules (144.4 s), followed by the surface mounted Nlaza module (288.1 s), while the module with aerial mounted sensor gives a response certainly close above to the T700 without coating (42.8 s). As a conclusion, the dynamic response of temperature sensors within wireless and RFID nodes is dramatically influenced by the way they are housed (to protect them from the environment) as well as by the heat released by the node electronics itself; its characterization is basic to allow monitoring of high rate temperature changes and to certify the cold chain. Besides the time to rise and to recover is significantly different being mostly higher for the latter than for the former

High risk and probability of progression to osteoporosis at 10 years in HIV-infected individuals: the role of PIs

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Journal of antimicrobial chemotherapy following peer review. The version of record Negredo, E., Langohr, K., Bonjoch, A., Perez, N., Estany, C., Puig, J., Echevarría, P., Clotet, B., Gómez Melis, G. High risk and probability of progression to osteoporosis at 10 years in HIV-infected individuals: the role of PIs. "Journal of antimicrobial chemotherapy", 1 Setembre 2018, vol. 73, núm. 9, p. 2452-2459 is available online at: https://academic.oup.com/jac/article-abstract/73/9/2452/5026321.Peer ReviewedPostprint (author's final draft

The counteractive effect of the sensor housing on the unit sensitivity across a series of dynamic temperature profiles.

The advantages of wireless sensing implemented on the cold chain of fresh products are well known. These sensor systems consist of a combination of delicate internal electronic circuitry enclosed in a special housing unit. Manufacturers however are presented with the challenge that the housing required to withstand the harsh environment in which the sensors are being used all too often take from the functionality of the sensor. Therefore the target of this study is to determine the dynamic behavior and the counteractive effects of the sensor housing on temperature recording accuracy in the wireless nodes of Wireless Sensor Network (WSN) and Radio Frequency Identification (RFID) semi-passive tags. Two kind of semi-passive Turbo Tags were used (T700 and T702-B), which consisted of sensors with and without a cover, and two kind of WSN nodes, IRIS (sensors Intersema and Sensirion soldered in the motherboard) and NLAZA (Sensirion in a cable and soldered to the motherboard). To recreate the temperature profiles the devices were rotated between a cold room(5 ºC) through a ambient room(23 ºC) to a heated environment (35ºC) and vice versa. Analysis revealed the differences between housing and no housing are 308.22s to 21.99s respectively in the step from 5 to 35 ºC. As is demonstrated in these experiments the influence of the housing significantly hinders sensor accuracy

Detection of cold chain breaks using partial least squares-class modelling based on biogenic amine profiles in tuna

The maintenance of the cold chain is essential to ensure foodstuff conformity and safety. However, gaps in the cold chain may be expected so designing analytical methods capable to detect cold chain breaks is a worthwhile issue. In this paper, the possibility of using the amount of nine biogenic amines (BAs) determined in Thunnus albacares by HPLC-FLD for detecting cold chain breaks is approached. Tuna is stored at 3 different temperature conditions for 8 storage periods. The evolution of the content of BAs is analyzed through parallel factor analysis (PARAFAC), in such a way that storage temperature, BAs and storage time profiles are estimated. PARAFAC has made it possible to observe two spoilage routes with different relative evolution of BAs. In addition, it has enabled to estimate the storage time, by considering the three storage temperatures, with errors of 0.5 and 1.0 days in fitting and in prediction, respectively. Furthermore, a class-modelling technique based on partial least squares is sequentially applied to decide, from the amount of BAs, if there has been a cold chain break. Firstly, samples stored at 25 °C are statistically discriminated from those kept at 4 °C and −18 °C; next, frozen samples are distinguished from those refrigerated. In the first case, the probabilities of false non-compliance and false compliance are almost zero, whereas in the second one, both probabilities are 10%. Globally, the results of this work have pointed out the feasibility of using the amount of BAs together with PLS-CM to decide if the cold chain has been maintained or not.Agencia Estatal de Investigación of Spanish Ministerio de Economía, Industria y Competitividad, Gobierno de España [project CTQ2017-88894-R] and Consejería de Educación de la Junta de Castilla y León [project BU012P17] both co-financed with European Regional Development Fun

Economically motivated food fraud and adulteration in Brazil: incidents and alternatives to minimize occurrence.

Made available in DSpace on 2018-08-15T00:33:32Z (GMT). No. of bitstreams: 1 ID443532018v83n8p2028JFoodSci.pdf: 310812 bytes, checksum: 8c4b14317218e9bbc886899fa22311e4 (MD5) Previous issue date: 2018-08-14bitstream/item/181446/1/ID44353-2018v83n8p2028JFoodSci.pd

Emerging targets for addiction neuropharmacology: From mechanisms to therapeutics

Drug abuse represents a considerable burden of disease and has enormous economic impacts on societies. Over the years, few medications have been developed for clinical use. Their utilization is endowed with several limitations, including partial efficacy or significant side effects. On the other hand, the successful advancement of these compounds provides an important proof of concept for the feasibility of drug development programs in addiction. In recent years, a wealth of information has been generated on the psychological mechanisms, genetic or epigenetic predisposing factors, and neurobiological adaptations induced by drug consumption that interact with each other to contribute to disease progression. It is now clear that addiction develops through phases, from initial recreational use to excessive consumption and compulsive drug seeking, with a shift from positive to negative reinforcement driving motivated behaviors. A greater understanding of these mechanisms has opened new vistas in drug development programs. Researchers' attention has been shifted from investigation of classical targets associated with reward to biological substrates responsible for negative reinforcement, impulse loss of control, and maladaptive mechanisms resulting from protracted drug use. From this research, several new biological targets for the development of innovative therapies have started to emerge. This chapter offers an overview of targets currently under scrutiny for the development of new medications for addiction. This work is not exhaustive but rather it provides a few examples of how this research has advanced in recent years by virtue of studies carried out in our laboratory

Digital technology enablers for resilient and customer driven food value chains

Food production chains have to respond to disrupted global markets and dynamic customer demands. They are coming under pressure to move from a supply to a demand-driven business model. The inherent difficulties in the lifecycle management of food products, their perishable nature, the volatility in global and regional supplier and customer markets, and the mix of objective and subjective drivers of customer demand and satisfaction, compose a challenging food production landscape. Businesses need to navigate through dynamically evolving operational risks and ensure targeted performance in terms of supply chain resilience and agility, as well as transparency and product assurance. While the industrial transition to digitalised and automated food production chains is seen as a response to such challenges, the contribution of industry 4.0 technology enablers towards this aim is not sufficiently well understood. This paper outlines the key features of high performing food production chains and performs a mapping between them and enabling technologies. As digitalisation initiatives gain priority, such mapping can help with the prioritisation of technology enablers on delivering key aspects of high performing food production chains

A Genetic Animal Model of Alcoholism for Screening Medications to Treat Addiction

The purpose of this review is to present up-to-date pharmacological, genetic, and behavioral findings from the alcohol-preferring P rat and summarize similar past work. Behaviorally, the focus will be on how the P rat meets criteria put forth for a valid animal model of alcoholism with a highlight on its use as an animal model of polysubstance abuse, including alcohol, nicotine, and psychostimulants. Pharmacologically and genetically, the focus will be on the neurotransmitter and neuropeptide systems that have received the most attention: cholinergic, dopaminergic, GABAergic, glutamatergic, serotonergic, noradrenergic, corticotrophin releasing hormone, opioid, and neuropeptide Y. Herein, we sought to place the P rat's behavioral and neurochemical phenotypes, and to some extent its genotype, in the context of the clinical literature. After reviewing the findings thus far, this chapter discusses future directions for expanding the use of this genetic animal model of alcoholism to identify molecular targets for treating drug addiction in general