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Cannabis is an ancient plant that has been used for therapeutic and recreational purposes. Nowadays, industrial hemp, a variety with low concentration of the psychoactive cannabinoid Δ9-tetrahydrocannabinol (THC) and high concentration of non-psychoactive cannabinoids, is getting more and more interest in the food, pharmaceutical, and cosmetic industry. However, cannabis not only contains cannabinoids as bioactive components but also other metabolites like terpenes and phenolic compounds, and the content of these interesting secondary metabolites greatly differs with the genetic variety of the plant. Due to the huge complexity of composition of the cannabis matrix, in this work, a comprehensive two-dimensional liquid chromatography (LC × LC) method has been developed as a very power separation technique coupling a pentafluorophenyl (PFP) and a C18 in the first and second dimensions. Two industrial hemp strains (cookie and gelato) were analyzed to determine the difference in their content of cannabinoids and phenolic compounds. To do this, a new demodulation process was applied for the first time to transform 2D raw data into 1D data which allowed carrying out the chemometric analysis needed to determine the statistical differences between the hemp strains. The cookie strain presented a total of 41 cannabinoid markers, while the gelato strain presented more representative phenolic compounds, in total 24 phenolic compounds were detected as potential markers of this sample. These differences in the chemical composition could determine the industrial destiny of the different hemp strains. Graphical abstract

The marine environment is considered an inexhaustible source of antioxidants. Marine organisms like macro- and microalgae and sponges are excellent sources of phenolic compounds that attract researchers and consumers’ interest. These marine organisms present a complex chemical and nutritional composition, where phenolic compounds are found at much lower concentrations than macronutrients. Therefore, specific extraction strategies should be applied to obtain rich phenolic extracts to establish their chemical composition and biological functionality and develop commercial products. Nowadays, there is a clear trend to apply efficient and green extraction techniques for recovering natural ingredients, like phenolic compounds. One of the most useful and successful strategies is the use of compressed fluids extraction techniques such as supercritical fluid extraction (SFE), gas expanded liquid extraction (GXL), and pressurized liquid extraction (PLE). This chapter describes and discusses the fundamentals of these alternative green techniques and their applications to extract phenolic compounds from marine sources.

The study of the phytochemical composition of seed oils is of upmost importance for the food and cosmetic industries, mainly considering their associated biological properties. Extraction of seed oils using supercritical fluids (SFE) is an ecological and green alternative to conventional extraction processes since it is able to provide with potent bioactive extracts, avoiding degradation and transformation of the compounds present originally in the raw material. The objective of the present work was the extraction of pure fractions of polar lipids and their chemical characterization using chromatographic techniques such as GC-MS and LC-DAD-MS/MS of blackberry (Rubus glaucus) and passion fruit (Passiflora edulis) seed oils extracted by supercritical carbon dioxide. Oleamides derived from oleic acid were identified as the main compounds in both samples; in particular, 9-octadecenamide was the major identified oleamide. Besides, the extract obtained from passion fruit showed to be a source of linoleic acid, while the SFE extract from blackberry presented important concentrations of vanillin. The chemical composition of these seed oils can be of high interest for their further use in cosmetics and food industry., Open Access funding enabled and organized by Projekt DEAL. The authors acknowledge funding from the 2014CD0021 project (I-COOP-AGROFOOD 2014) and AGL2017-89417-R project (Spanish Ministry of Science) and Laboratory Department of Universidad de Nariño (Pasto, Colombia).

The application of atmospheric pressure ionization (API) sources in gas chromatography-mass spectrometry (GC-MS) determinations is becoming more popular since they have shown great capabilities to sort out the main drawbacks of vacuum ionization techniques like electron ionization (EI) and chemical ionization (CI). The development of new API techniques and set-ups have grown in the last decades, opening the field of GC-MS to new applications and facing some of the major issues in current analytical methodologies such as the requirement of a compromise between sensitivity and selectivity. Thus, this review is mainly focused on the use of GC-API-MS in different application fields such as food analysis (food safety and food metabolomics), environmental analysis, clinical analysis, drug and pharmaceutical analysis, and petroleomics, among others. The methodologies have been critically reviewed to compare the performance of different API sources and approaches, highlighting the main contributions to overcoming some of the major limitations of the current methodologies as well as the new perspectives that GC-API-MS might open in the different fields.

The Green Chemistry movement has led the change toward a more sustainable and environmentally benign chemistry industry and has explored new ways to reduce or eliminate the use or generation of hazardous substances from chemical products and processes. In the present chapter several extraction techniques will be seen and their applications to herbs, spices, and by‐products. Among pressurized technologies, supercritical fluid extraction (SFE) and pressurized liquid extraction (PLE) are revised in addition to techniques such as ultrasound‐assisted extraction (UAE), microwave‐assisted extraction (MAE), and enzyme‐assisted extraction (EAE). Moreover, the combination of these techniques for integrated processes will be covered. The reader is invited to learn about the huge potential of these techniques for extraction of high added‐value compounds (with improved bioactivity) while complying with Green Chemistry goals., A.P.S.C. thanks to the Administrative Department of Science, Technology and Innovation COLCIENCIAS (Colombia) for her postdoctoral research fellowship (784-1077 2017). M. H. would like to thank MICINN for his “Ramón y Cajal” research contract. The authors would also like to thank Projects AGL2017-89417-R (MINECO, Spain) and I-LINK1096 (Consejo Superior de Investigaciones Científicas, CSIC), for their financial support.

The use of atmospheric pressure ionization (API) sources has become very popular for gas chromatography-mass spectrometry (GC-MS) determinations. GC-API-MS shows important advantages over traditional vacuum ionization sources such as a lower fragmentation preserving the molecular or quasi-molecular ion, the combination of GC separations with advanced mass spectrometers typically developed for liquid chromatography (LC) systems, a significantly higher sensitivity, or the reduction of costs due to the capability to use the same MS for both LC- and GC- couplings. For these reasons, the development of new API sources and GC-API-MS platforms has exponentially increased during the last years. Thus, this review is mainly focused on the last advances in GC-API-MS instrumentation. New setups and couplings on extensively reported API techniques as well as the development of new API sources for GC-MS coupling are thoroughly discussed. Moreover, novel ionization strategies have been reviewed to overcome some of the drawbacks of GC-API-MS methodologies.

Arginase 1 (Arg1) is a ubiquitous enzyme belonging to the urea cycle that catalyzes the conversion of l-arginine into l-ornithine and urea. In endothelial cells (ECs), Arg1 was proposed to limit the availability of l-arginine for the endothelial nitric oxide synthase (eNOS) and thereby reduce nitric oxide (NO) production, thus promoting endothelial dysfunction and vascular disease. The role of EC Arg1 under homeostatic conditions is in vivo less understood. The aim of this study was to investigate the role of EC Arg1 on the regulation of eNOS, vascular tone, and endothelial function under normal homeostatic conditions in vivo and ex vivo. By using a tamoxifen-inducible EC-specific gene-targeting approach, we generated EC Arg1 KO mice. Efficiency and specificity of the gene targeting strategy was demonstrated by DNA recombination and loss of Arg1 expression measured after tamoxifen treatment in EC only. In EC Arg1 KO mice we found a significant decrease in Arg1 expression in heart and lung ECs and in the aorta, however, vascular enzymatic activity was preserved likely due to the presence of high levels of Arg1 in smooth muscle cells. Moreover, we found a downregulation of eNOS expression in the aorta, and a fully preserved systemic l-arginine and NO bioavailability, as demonstrated by the levels of l-arginine, l-ornithine, and l-citrulline as well as nitrite, nitrate, and nitroso-species. Lung and liver tissues from EC Arg1 KO mice showed respectively increase or decrease in nitrosyl-heme species, indicating that the lack of endothelial Arg1 affects NO bioavailability in these organs. In addition, EC Arg1 KO mice showed fully preserved acetylcholine-mediated vascular relaxation in both conductance and resistant vessels but increased phenylephrine-induced vasoconstriction. Systolic, diastolic, and mean arterial pressure and cardiac performance in EC Arg1 KO mice were not different from the wild-type littermate controls. In conclusion, under normal homeostatic conditions, lack of EC Arg1 expression is associated with a down-regulation of eNOS expression but a preserved NO bioavailability and vascular endothelial function. These results suggest that a cross-talk exists between Arg1 and eNOS to control NO production in ECs, which depends on both L-Arg availability and EC Arg1-dependent eNOS expression.

This work presents a comparative study for the analysis of carbohydrates for four common chromatographic methods, each coupled to mass spectrometry. Supercritical fluid chromatography (SFC), hydrophilic interaction liquid chromatography (HILIC), reversed-phase liquid chromatography (RP-LC) and gas chromatography (GC) with detection by triple quadrupole mass spectrometer (QqQ-MS) are compared. It is shown that gas chromatography and reversed-phase liquid chromatography, each after derivatisation, are superior to the other two methods in terms of separation performance. Furthermore, comparing the different working modes of the mass spectrometer, it can be determined that a targeted analysis, i.e. moving from full scan to single ion monitoring (SIM) and multiple reaction monitoring (MRM), results in an improvement in the sensitivity as well as the repeatability of the method, which has deficiencies especially in the analysis using HILIC. Overall, RP-LC–MS in MRM after derivatisation with 1-phenyl-3-methyl-5-pyrazolone (PMP) proved to be the most suitable method in terms of separation performance, sensitivity and repeatability for the analysis of monosaccharides. Detection limits in the nanomolar range were achieved, which corresponds to a mass concentration in the low µg/L range. The applicability of this method to different biological samples was investigated with various herbal liquors, pectins and a human glycoprotein. Graphical abstract

Cannabis is an ancient plant that has been used for therapeutic and recreational purposes. Nowadays, industrial hemp, a variety with low concentration of the psychoactive cannabinoid Δ

The estimation of the network traffic state, its likely short-term evolution, the prediction of the expected travel times in a network, and the role that mobility patterns play in transport modeling is usually based on dynamic traffic models, whose main input is a dynamic origin–destination (OD) matrix that describes the time dependencies of travel patterns, this is one of the reasons that have fostered large amounts of research on the topic of estimating OD matrices from the available traffic information. The complexity of the problem, its underdetermination, and the many alternatives that it offers are other reasons that make it an appealing research topic. The availability of new traffic data measurements that were prompted by the pervasive penetration of information and communications technology (ICT) applications offers new research opportunities. This study focused on GPS tracking data and explored two alternative modeling approaches regarding how to account for this new information to solve the dynamic origin–destination matrix estimation (DODME) problem, either including it as an additional term in the formulation model or using it in a data-driven modeling method to propose new model formulations. Complementarily, independently of the approach used, a key aspect is the quality of the estimated OD, which, as recent research has made evident, is not well measured by the conventional indicators. This study also explored this problem for the proposed approaches by conducting synthetic computational experiments to control and understand the process.

Since OD matrices are not directly observable, indirect procedures have been developed to estimate OD matrices from traffic data. Traffic management must move toward dynamic traffic assignment models because they capture congestion propagation effects. In this context, dynamic OD matrices are needed. This paper first explores the extension of a conventional bilevel analytical static method to the dynamic context, then analyses the solutions obtained regarding both convergence to measured traffic data and structural similarity to an a priori OD matrix. A simulation optimization technique, SPSA, is then proposed because its flexibility allows inclusion of traffic counts (as in Spiess method) and emerging ICT traffic measurements. The performances of these two types of algorithms are analyzed in detail, focussing on faults of classical convergence measures to obtain an estimated dynamic OD matrix structurally similarity to the a priori OD matrix and pros and cons of variants of selected methods.

The spatial arrangement of a metropolis is of utmost importance to carry out daily activities, which are constrained by space and time. Accessibility is not only shaped by the spatial and temporal dimension, but it is also defined by individual characteristics, such as gender, impairments, or socioeconomic characteristics of the citizens living or commuting in this area. This study analyzes mobility trends and patterns in the metropolitan area of Barcelona before and after the COVID-19 pandemic outbreak, with special emphasis on gender and equality. The study draws on multiple sources of information, however, two main datasets are analyzed: two traditional travel surveys from the transport metropolitan area of Barcelona and two coming from smartphone data. The results show that gender plays a relevant role when analyzing mobility patterns, as already highlighted in other studies, but, after the pandemic outbreak, some population groups were more likely to change their mobility patterns, for example, highly educated population groups and those with higher income. This study also highlights that e-activities may shape new mobility patterns and living conditions for some population segments, but some activities cannot be replaced by IT technologies. For all these reasons, city and transport planning should foster sustainable development policies, which will provide the maximum benefit for society.

The estimation of Origin to Destination (OD) matrices is still object of continuous research interest, but the complexity of the problem, the many alternatives that it offers and the role that mobility patterns represented by ODs play in transport modelling, makes it an appealing research topic, namely in the domain of dynamic approaches. The availability of new traffic measurement due to the pervasive penetration of ICT measurements offers new paths to explore. This paper provides an insight of what can be achieved when, in addition to link flow counts, travel times are considered in the formulation of the Dynamic Origin-Destination Matrix Estimation (DODME). The analysis is conducted with an extension of conventional SPSA and a new hybrid formulation combining analytical and non-analytical formulations. Peer Reviewed Objectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats Sostenibles

Herbal liqueurs are a large group of diverse alcoholic beverages with an ancient tradition produced by maceration of various herbs and spices and are commonly drunken before or after a meal to aid in the digestion because of their potential functional properties. In the presented work, eight different commercial herbal liqueurs were investigated with regard to their composition of phenolic compounds by liquid chromatography ion mobility quadrupole time-of-flight mass spectrometry (LC-IM-QTOF-MS). This multidimensional analytical platform uses all-ion fragmentation for a deep coverage of the foodome. After an extensive data clean-up, 3225 features were found. 213 features were manually annotated due to the absence of databases and software tools able to consider the drift time or Collison Cross Section (CCS) together with high resolution MS/MS spectra for identification. The identified compounds reflected the large variance between the investigated samples and a wealth of potential bioactive compounds that these liqueurs harbor.

Algae have been consumed for many years in Asian countries; at present, its consumption around the world either as food ingredient or directly as food commodity has increased considerably mainly due to the Asian influence and its cuisine, but also because of the growing interest in the beneficial health effects of algae. Although several biological activities have been attributed to different algae compounds such as pigments, lipids, polysaccharides, fiber, proteins or vitamins, in the present review we will highlight the different phenolic compounds present on seaweeds and their important role in the functional and health effects, paying special attention to the antioxidant, anti-proliferative, anti-obesity and antidiabetic activities.

Pressurized liquid extraction using green solvents (ethanol and water) was applied to extract photosynthetic pigments from the microalgae Chlamydomonas sp. An experimental design is employed to determine the effect of the extraction conditions on the extraction yield and the antioxidant capacity of the different extracts determined using 1,1-diphenyl-2-picryl-hydrazyl and TEAC tests. All the extracts show significant antioxidant activity in all assays. Besides, in this work, the carotenoid and chlorophyll composition of the Chlamydomonas extracts was analyzed by HPLC–DAD–APCI–MS/MS for the first time, being the main compounds lutein and pheophythin a´.

At present, there is an increasing demand for natural bioactive compounds able to provide health benefits when included and consumed in a functional food or in a nutraceutical. In this regard, microalgae are promising natural sources with great potential, not only considering that these organisms are largely underexplored, but also because microalgae can be produced at large scale and their chemical composition might be tuned to over-synthesize a particular target compound. The use of advanced sustainable extraction techniques to recover these bioactive compounds is a must nowadays. This work presents an overview on the use of compressed fluid-based extraction techniques to obtain bioactive compounds from microalgae that can be seen also as a first step towards its recovery at larger scale. When relevant, the description of the analytical procedure used to chemically characterize the bioactive compounds is also included.

This study looks into the effect of L2 learning context and different types of L2 exposure on changes in the use of communication strategies (CS). Previous findings on the possible effects of study abroad (SA) experiences on the development of CS do not allow for a clear conclusion on the issue. The present study specifically compares the effects on 65 Spanish undergraduate students with English as an L2 of either four months of SA experience or of AH courses, incorporating an analysis of the type of L2 contact participants engaged in, such as their relationships and leisure activities. This possible effect is measured in terms of development of CS effectiveness over a four-month period. The results suggest that engaging in non-language-oriented organised leisure activities may benefit L2 learners in developing effective CS use, with implications for language teaching and learning in both contexts.

Over the last century, cities have developed as a function of increased usage of automobiles as the standard transport mode. The number of cars increased along with the population as highways and parking spots became essential in city planning. Now, there is more focus on how the existing infrastructure could be used as efficiently as possible rather than increasing capacity by merely building new roads. An important part of traffic planning is a sustainable transport system, which thereby reduces congestion and emissions by using the available capacity in a more efficient way. Traffic simulation models are tools for assessing new mobility solutions and analysing changes in the infrastructure, such as rearranging intersections and building new roads. Transportation is undergoing a profound and significant transformation as it seeks to fulfil the promise of connected mobility for people and goods while limiting its carbon footprint. Physical changes to the road network mean large investments that must be comprehensively considered before acting. Modelling different scenarios of infrastructural changes allows making forecasts without any physical changes. Autonomous vehicles are potentially changing the economics of ownership as well as the use of the transportation networks, which will likely accelerate trends towards greater use of app-based ride hailing and/or sharing by private transportation network companies. American and European cities are seeing a rise in several potential business models with varying degrees of ride sharing and public vs. private involvement in delivering mobility services (MaaS). Implications for transit agencies and mobility service providers must be evaluated, and this can be done by traffic simulation models that provide a model-based framework for evaluating the mobility impact of new services.

The focus of this study was the analysis of the complex chemical composition from different parts of Buddleja davidii, whose species are commonly known as ornamental plants and herbal medicines in many countries. As an herbal medicine, it has been utilized for stroke treatments, headache, wound healing, neurological disorder, etc. However, the understanding of its chemical matrices is still insufficient. Therefore, an online two-dimensional reversed phase liquid chromatography x hydrophilic interaction liquid chromatography (RPLCxHILIC) system coupled with mass spectrometry was applied for further detailed investigation of the chemical constituents in Buddleja dividii. In this two-dimensional liquid chromatography (2D-LC) method, a new at-column dilution (ACD) modulator was introduced in the 2D-LC system to solve the incompatibility problem of the mobile phase between two dimensions, which resulted in a 2D-LC analysis with high orthogonality. For the root extract, as one of the analyzed samples, the optimization of the 1D and 2D gradients was carried out carefully. With this new modulator, much better peak separation and better peak shape were achieved compared to two-dimensional liquid chromatography system using a traditional standard (TS) modulator. With a similar approach, the other four parts of Buddleja davidii were well separated. Comparing the different analyzed parts, flowers and leaves showed the most complex profiles. MS and MS/MS data were obtained successfully, which demonstrated the potential of the proposed RPLCxHILIC-MS system in the constituents’ analysis of herbal medicine. However, due to the lack of reported reference information, 24 compounds could be tentatively identified.

Profiling of the main metabolites from several licorice (Glycyrrhiza glabra) samples collected at different locations is carried out in this work by using comprehensive two-dimensional liquid chromatography (LC × LC) coupled to diode array (DAD) and mass spectrometry (MS) detectors. The optimized method was based on the application of a HILIC-based separation in the first dimension combined with fast RP-based second dimension separation. This set-up was shown to possess powerful separation capabilities allowing separating as much as 89 different metabolites in a single sample. Identification and grouping of metabolites according to their chemical class were achieved using the DAD, MS and MS/MS data. Triterpene saponins were the most abundant metabolites followed by glycosylated flavanones and chalcones, whereas glycyrrhizic acid, as expected, was confirmed as the main component in all the studied samples. LC × LC-DAD-MS/MS was able to resolve these complex licorice samples providing with specific metabolite profiles to the different licorice samples depending on their geographical origin. Namely, from 19 to 50 specific compounds were exclusively determined in the 2D-chromatograms from the different licorice samples depending on their geographical origin, which can be used as a typical pattern that could potentially be related to their geographical location and authentication., M. H. would like to thank MICINN for his “Ramón y Cajal” research contract. The authors would like to thank Project AGL2014-53609-P (MINECO, Spain) for financial support. This work was also funded by Italian Ministry of Research and University (MIUR) and European Commission (Project PON01_00636: Anti-counterfeiting technologies and materials and nanotechnologies for authentication and protection of agrifood excellence – “Fingerimball”).

Modern food analysis is directed to the characterization of as many components as possible in food and food-related materials. The use of –omics technologies within a Foodomics approach requires the use of high throughput analytical techniques able to offer increased resolving power and capability to separate a high number of compounds. From this perspective, two-dimensional liquid chromatography has the potential to unravel very complex food matrices, providing with high resolving power and enhanced identification potential, particularly when coupled to mass spectrometry. This review presents an overview including the most notable two-dimensional liquid chromatography applications developed in the last ten years to study food safety, food quality and the relationship between health and food as well as for the characterization of particular groups of food components within a Foodomics perspective. Moreover, the latest developments and advances, limitations, future evolution and needs related to the use of this technique are critically discussed and commented., Authors thank Project AGL2017-89417-R (MINECO, Spain) for financial support.

© 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ There are presently several companies that provide processed or raw global positioning system (GPS) measurements generated by fleets of commercial vehicles, internet applications or automobile companies. The aim of this paper is to deepen our understanding of GPS data applicability in transportation modelling by providing systematic and quantified insights into the representativeness of collected data in describing individual’ route choices. Unfortunately, real data often contain noise, uncertainty, errors, redundancies or even irrelevant information. Useless models will be obtained when built over incorrect or incomplete data. This is why pre-processing is one of the most critical steps in data analysis. Yet, pre-processing has not been properly systematized, which is why this paper focuses on the necessary steps for pre-processing GPS tracking data together and puts forth a proposal for systematizing it. Furthermore, the aggregation level is at waypoint location for low latency GPS positions along the trip trajectory. Travel time reliability on OD paths is addressed, along with other OD path characteristics. Dense urban networks pose multiple possibilities for route choice, and data from new technologies offers an opportunity to understand route choice behaviour. This research was funded by TRA2016-76914-C3-1-P Spanish R+D Programs and by Secretaria d’Universitats-iRecerca-Generalitat de Catalunya- 2017-SGR- 1749 and Industrial PhD Program 2017 DI 041.

OD matrices that describe mobility patterns provide major input to most transport analysis models. Since OD matrices are not yet directly observable, they are usually estimated indirectly. Data from new sources such as mobile phone records and GPS traces from mobile apps are emerging alternatives that allow for cheaper and timely estimates. However, they are still hindered by weaknesses that must be studied for use as input to transportation models. This paper presents a case study using mobility data from mobile phone records, with the goal of establishing a methodology for validating the obtained OD matrices and generating the appropriate input for traffic assignment models. Spatial and temporal consistency of OD data elaborated from mobile records has been proved to be useful for transportation modelling needs.

Meet-Up is an innovate pilot program for enrolled students at UPC (Universitat Politecnica de Catalunya) with Autism Spectrum Disorder (ASD). UPC is a Technical University one that provides majors in the STEM (Science, Technology, Engineering and Mathematics) area. As part of the UPC Inclusion Program, for the first time an orientation program for students with an ASD was launched on September 2017. Nowadays, colleges and universities are receiving more admission applications from young adults diagnosed with ASD than in the past, because ASD was sometimes confused with other disorders, but since the late 1990s the revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) seems to be an important factor on early diagnosis and intervention of ASD, so many of these students are now in a position to consider enrollment in higher education, which was not a viable option a few years ago. Since lecturers and schools at UPC have little experience of students with these disorders, the program was designed with the support of ASAC (Associacio Asperger de Catalunya) professionals, an Autism Spectrum local organization, and deployed with follow-up sessions conducted by ASAC psychologist team. Follow-up sessions are held at lunchtime, always at the same time and place, in order to provide students and Meet-Up staff with a familiar environment and a relaxed atmosphere conducive to free and open discussion. Finally, we experimented with the use of technology as a tool for cognitive support to help students focus on independence and control in order to reduce stress. In this initial stage, we confined the experience to electronic agendas, a contact list using WhatsApp and access to the virtual campus by means of smartphones. The promotion of the Meet-Up program was highly unsatisfactory in the first edition and a real concern for Meet-Up staff since students were allowed to incorporate ongoing in the course edition. This work presents the design of the initial Meet-Up pilot, the second edition revised program and qualitative results that cover the first edition feedback. Student profiling and initial screening tests (STAI, BDI, EQ and AQ) have been incorporated in the second edition while substantial promotion effort and organization issues have been addressed. First indicators, show a 100% increment in the number of students continuously attending to monthly follow-up sessions.

While optimization models play a key role in transportation analysis, the objective function to be optimized, however, cannot always be defined analytically. It is therefore necessary to resort to non-differentiable optimization methods that usually pivot on evaluating the objective function. Special cases of particular interest are those in Dynamic OD Estimation, which cannot evaluate the objective analytically and thus the formulation falls within the computational framework of Simulation-Optimization. SPSA is not limited to the inputs from conventional traffic counts and can be easily extended to account for the measurements of traffic variables supplied by emerging sensors exploiting Information and Communication Technologies (ICT). Numerical experiments have been conducted with a real network, and the results have been analyzed from two different perspectives: performance and solution quality. This allows understanding the behavior of the SPSA algorithm and new variants, which altogether contribute to the aim of adding ICT measures in the future. Their sensitivity to the initial values, the effect of bounding the variables and scaling techniques are going to be analyzed. This paper will report on the results of the numerical experiments, their analyses, conclusions and further research.

Proanthocyanidins as well as other secondary metabolites present in green cocoa beans were studied thanks to a new method involving the use of on-line comprehensive two-dimensional liquid chromatography coupled to tandem mass spectrometry (LC × LC-MS/MS). In order to enhance the performance of previously developed methodologies, the use of different modulation strategies were explored. Focusing modulation clearly allowed the attainment of higher resolving power and peak capacity compared to non-focusing modulation set-ups. Moreover, the use of active modulation by the addition of a make-up flow efficiently helped to compensate for the solvent strength mismatch produced between dimensions. The optimized method was useful to successfully describe the secondary metabolite composition of green cocoa that was characterized by the presence of 30 main compounds, including 3 xanthines, 2 flavan-3-ols and 24 oligomeric procyanidins with a degree of polymerization up to 12. The obtained results showed that the proanthocyanidins found in the cocoa beans were exclusively B-type procyanidins. The existence of (epi)catechin subunits linked to sugar or galloyl moieties was not observed. The developed method produced a good separation of secondary metabolites allowing an improvement with respect to the available methodologies for the analysis of a complex food sample such as cocoa metabolites in terms of speed of analysis, resolution and peak capacity., S.T.U. wants to thank Colciencias-Colombia for financial support, and Universidad Industrial of Santander (Colombia) and Instituto de Investigación en Ciencias de la Alimentación (CIAL, Spain) for making this work possible. Authors thank Projects AGL2014-53609-P and AGL2017-89417-R (MINECO, Spain) for financial support.

In the present work, the phlorotannin composition of different Sargassum muticum samples collected at different locations along the North Atlantic coasts as well as the bioactivities related to these components were investigated. After pressurized liquid extraction, the samples collected at the extreme locations of a latitudinal gradient from Portugal and Norway, were found to be the richest on total phenols and, particularly, on phlorotannins, containing up to 148.97 and 5.12mg phloroglucinol equivalents g, respectively. The extracts obtained from these locations were further purified and chemically characterized using a modified HILIC×RP-DAD-MS/MS method. The application of this methodology allowed the tentative identification of a great variability of phlorotannins with different degrees of polymerization (from 3 to 11) and structures, determined for the first time in S. muticum. The most-abundant phlorotannins on these samples were fuhalols, hydroxyfuhalols and phlorethols, showing also particularities and important differences depending on the geographical location. Afterwards, the antiproliferative activity of these extracts against HT-29 adenocarcinoma colon cancer cells was studied. Results revealed that the richest S. muticum samples in terms of total phlorotannins, i.e., those from Norway, presented the highest activity, showing a good cytotoxic potential at concentrations in the medium micromolar range., A.P.S.C. thanks to the Administrative Department of Science, Technology and Innovation COLCIENCIAS (Colombia) for her Ph. D. Scholarship. M. H. would like to thank MICINN for his “Ramón y Cajal” research contract. The authors would also like to thank Projects AGL2011-29857-C03-01 (MINECO, Spain) and ALIBIRD-CM, S2013/ABI-2728 (Comunidad de Madrid), Interreg IVB Biotecmar (collect of algae along the Atlantic coasts) and Era-net Seas-era INVASIVES for their financial support.

Cystoseira abies-marina is one of the most important brown algae species found in the Mediterranean Sea and Atlantic Ocean ecosystems and has been reported as a promising source of phenolic compounds, including phlorotannins, with important biological activities. In the present work, the possibility of developing new green processes to eliminate/replace the use of traditional polluting and often toxic solvents to obtain phlorotannin-enriched extracts is explored, looking for higher efficiency and compliance with the rules of green chemistry. The theoretical modelling of the Hansen solubility parameters could provide a useful and accurate estimation for the solvent selection and prediction of the solubility of these natural bioactive compounds. In order to drive the process towards the extraction of the target compounds, the chemical composition of phlorotannins from Cystoseira abies-marina was determined using a comprehensive two-dimensional liquid chromatography (LC × LC-MS/MS) method. Phlorethols, fucols or fucophlorethols containing from 3 to 14 phloroglucinol units (PGU) were tentatively identified. The estimation of Hansen solubility parameters of the most abundant phlorotannins (7 PGU) in some green solvents (ethanol, water, ethyl lactate and CO + ethanol) under sub- and supercritical conditions was carried out to improve their selective extraction and is presented for the first time. According to the theoretical approach, low temperatures of the extraction solvents provide the minimum R (difference in solubility parameter). However, this work experimentally demonstrates that pure ethanol at 100 °C showed the highest selectivity to extract phlorotannins. The Hansen approach proves to be a profitable tool to select a suitable solvent for extraction purposes., A. P. S. C. thanks to the Administrative Department of Science, Technology and Innovation COLCIENCIAS (568-2012) (Colombia) for her PhD Scholarship. The authors want to thank Project AGL2014-53609-P (MINECO, Spain) for the financial support.

The use of floating car data as a particular case of probe vehicle data has been the object of extensive research for estimating traffic conditions, travel times, and origin-to-destination trip matrices. It is based on data collected from a GPS-equipped vehicle fleet or available cell phones. Cooperative cars with vehicle-to-vehicle and vehicle-to-infrastructure communication capabilities represent a step forward, as they also allow tracking of vehicles surrounding the equipped car. This paper presents the results of a limited experiment with a small fleet of cooperative cars in the central business district of Barcelona, Spain, known as L’Eixample District. Data collected from the experiment were used to build and calibrate the emulation of cooperative functions in a microscopic simulation model that captured the behavior of vehicle sensors in Barcelona’s central business district. Such a calibrated model allows emulating fleet data on a large scale that goes far beyond what a small fleet of cooperative vehicles could capture. To determine the traffic state, several approaches were developed for estimating traffic variables—whose accuracy depends on the penetration level of the technology—on the basis of extensions of Edie’s generalized definitions of the fundamental traffic variables with the emulated data.

This innovate practice work-in-progress paper presents a pilot orientation program for students with Autism Spectrum Disorder (ASD), a range of conditions involving serious dysfunctions in aspects of social relationships and learning. Young adults with ASD are more likely than the general population to concentrate on science and engineering, so those who enroll at college tend to choose STEM degrees. However, students with ASD often undergo stress and experience difficulty in the transition to college. For this reason our university considers the necessity for an orientation program to help such students in this challenging situation. In this paper, the authors describe this initiative, known as Meet-Up, and the problems we faced during the pilot program.

Due to its significant amount of antioxidants, durum wheat (Triticum turgidum ssp. durum) could potentially contribute to the protection against a number of chronic diseases, such as diabetes, cardiovascular disease, and cancer. The increasing interest toward healthy food among both consumers and scientists has moved the focus toward the phytochemical content of whole wheat grains. The aim of this study was to identify the phytochemical composition of 22 cultivars belonging to old and modern durum wheat genotypes, including antioxidant capacity (DPPH and FRAP tests). In addition, five phenolic acids involved in the vanillin biosynthesis pathway and in the defence mechanism of plants were screened using UHPLC‐MS/MS. Remarkable quantitative differences in the amount of the five phenolic acids analysed (p < 0.05) were detected among the wheat genotypes investigated. Results showed that among the investigated phenolic compounds, trans‐ferulic acid was the most abundant, ranging from 13.28 to 324.69 μg/g; all the other identified compounds were present at lower concentrations. Moreover, significant differences on the antioxidant activity were observed. Collected data suggested possible differences between biosynthetic pathway of secondary metabolites among durum wheat genotypes.

Phlorotannins are an important class of polyphenolic compounds only found in brown algae. The chemical analysis of these bioactive polyphenols is rather difficult due to the great chemical variability and complexity of the natural composition of these components in algae, forming large phloroglucinol polymers. In the present work, a new approach based on the use of comprehensive 2D LC (LC × LC) is shown to analyze this complex family of compounds. The developed LC × LC methodology is based on the coupling of a hydrophilic-interaction LC (HILIC)-based separation in the first dimension and an RP-based separation in the second dimension. The employment of this online coupling together with DAD and MS/MS allowed the separation and identification of more than 50 compounds in a Cystoseira abies-marina brown alga extract. Phlorotannins containing from 5 to 17 phloroglucinol units were identified in this sample by HILIC × RP-DAD-MS/MS. Besides, using the 2,4-dimethoxybenzaldehyde assay, it was possible to determine that the total amount of phlorotannins present in the extract was 40.2 mg phloroglucinol equivalents per gram of extract. To our knowledge, this work is the first demonstration of the usefulness of HILIC × RP-DAD-MS/MS for the determination of phlorotannins.

For some years now, multidimensional chromatography has been the focus of development in liquid chromatography in order to comprehensively analyze increasingly complex samples. It becomes clear that the molecular composition in biological samples is much more complex than previously assumed. Thus, the manifold variations of multidimensional chromatography allow a deeper understanding of the processes in nature. This review introduces the most important and creative modulators for the realization of two-dimensional liquid chromatography and discusses their advantages and disadvantages. One critical point in 2D-LC is, that the fractions from the 1D are often eluted in an incompatible or non-optimal injection solvent for the 2D, which causes in no or low retention of analytes, loss of separation power or increasing peak broadening in the 2D. Therefore, in this review the modulators are considered with regard to their ability to combine orthogonal separation mechanisms.