Utilization of waste materials to improve asphalt mixtures performance

This study aims to develop an innovative bitumen with large quantities of waste materials to improve asphalt mixtures performance. Different amounts of waste motor oil and waste HDPE were added to a new bitumen. The bitumen modified with 10% of waste motor oil and 5% of HDPE showed promising characteristics (high softening point temperatures and penetration slightly higher than the conventional bitumen). After the selection of the most promising modified bitumen, three asphalt mixtures were produced with different bitumens (namely conventional bitumen, commercial modified bitumen and the selected modified bitumen). Beyond that, this modified bitumen improved some mechanical characteristics of the asphalt mixture where it was used, in comparison to conventional and modified asphalt mixtures.

Hair coloration by gene regulation: fact or fiction?

The unravelling of hair pigmentation genetics and robust delivery systems to the hair follicle (HF) will allow the development of a new class of colouring products. The challenge will be changing hair colour from inside out by safely regulating the activity of target genes through the specific delivery of synthetic/natural compounds, proteins, genes, or small RNAs.

Relationship between galactomannan structure and physicochemical properties of films produced thereof

In this work five sources of galactomannans, Adenanthera pavonina, Cyamopsis tetragonolobus, Caesalpinia pulcherrima, Ceratonia siliqua and Sophora japonica, presenting mannose/galactose ratios of 1.3, 1.7, 2.9, 3.4 and 5.6, respectively, were used to produce galactomannan-based films. These films were characterized in terms of: water vapour, oxygen and carbon dioxide permeabilities (WVP, O 2 P and CO 2 P); moisture content, water solubility, contact angle, elongation-at-break (EB), tensile strength (TS) and glass transition temperature (T g ). Results showed that films properties vary according to the galactomannan source (different galactose distribution) and their mannose/galactose ratio. Water affinity of mannan and galactose chains and the intermolecular interactions of mannose backbone should also be considered being factors that affect films properties. This work has shown that knowing mannose/galactose ratio of galactomannans is possible to foresee galactomannan-based edible films properties.

Neural correlates of face familiarity in institutionally reared children with distinctive, atypical social behavior

Although the impact of early adverse experience on neural processing of face familiarity has been studied, research has not taken into account disordered child behavior. This work compared the neural processing of familiar versus strangers' faces in 47 institutionalized children with a mean age of 54 months to determine the effects of (a) the presence versus absence of atypical social behavior and (b) inhibited versus indiscriminant atypical behavior. Results revealed a pattern of cortical hypoactivation in institutionalized children manifesting atypical social behavior and that inhibited children displayed larger neural response to a caregiver's face than to the stranger's, while indiscriminant children did not discriminate between stimuli. These findings suggest that neural correlates of face familiarity are associated with social functioning in institutionalized children.

UV-visible scanning spectrophotometry and chemometric analysis as tools for carotenoids analysis in cassava genotypes (Manihot esculenta Crantz)

In this study, the metabolomics characterization focusing on the carotenoid composition of ten cassava (Manihot esculenta) genotypes cultivated in southern Brazil by UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography was performed. Cassava roots rich in -carotene are an important staple food for populations with risk of vitamin A deficiency. Cassava genotypes with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The data set was used for the construction of a descriptive model by chemometric analysis. The genotypes of yellow-fleshed roots were clustered by the higher concentrations of cis--carotene and lutein. Inversely, cream-fleshed roots genotypes were grouped precisely due to their lower concentrations of these pigments, as samples rich in lycopene (redfleshed) differed among the studied genotypes. The analytical approach (UV-Vis, HPLC, and chemometrics) used showed to be efficient for understanding the chemodiversity of cassava genotypes, allowing to classify them according to important features for human health and nutrition.

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Electrically tunable resonant scattering in fluorinated bilayer graphene

Adatom-decorated graphene offers a promising new path towards spintronics in the ultrathin limit. We combine experiment and theory to investigate the electronic properties of dilutely fluorinated bilayer graphene, where the fluorine adatoms covalently bond to the top graphene layer. We show that fluorine adatoms give rise to resonant impurity states near the charge neutrality point of the bilayer, leading to strong scattering of charge carriers and hopping conduction inside a field-induced band gap. Remarkably, the application of an electric field across the layers is shown to tune the resonant scattering amplitude from fluorine adatoms by nearly twofold. The experimental observations are well explained by a theoretical analysis combining Boltzmann transport equations and fully quantum-mechanical methods. This paradigm can be generalized to many bilayer graphene-adatom materials, and we envision that the realization of electrically tunable resonance may be a key advantage in graphene-based spintronic devices.

Electronic transport across linear defects in graphene

We investigate the low-energy electronic transport across grain boundaries in graphene ribbons and infinite flakes. Using the recursive Green’s function method, we calculate the electronic transmission across different types of grain boundaries in graphene ribbons. We show results for the charge density distribution and the current flow along the ribbon. We study linear defects at various angles with the ribbon direction, as well as overlaps of two monolayer ribbon domains forming a bilayer region. For a class of extended defect lines with periodicity 3, an analytic approach is developed to study transport in infinite flakes. This class of extended grain boundaries is particularly interesting, since the K and K0 Dirac points are superposed.

Solving large 0–1 multidimensional knapsack problems by a new simplified binary artificial fish swarm algorithm

The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.

Multi-stacks of epitaxial GeSn self-assembled dots in Si: Structural analysis

We report on the growth and structural and morphologic characterization of stacked layers of self-assembled GeSn dots grown on Si (100) substrates by molecular beam epitaxy at low substrate temperature T = 350 °C. Samples consist of layers (from 1 up to 10) of Ge0.96Sn0.04 self-assembled dots separated by Si spacer layers, 10 nm thick. Their structural analysis was performed based on transmission electron microscopy, atomic force microscopy and Raman scattering. We found that up to 4 stacks of dots could be grown with good dot layer homogeneity, making the GeSn dots interesting candidates for optoelectronic device applications.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Eco-friendly luminescent hybrid materials based on EuIII and LiI co-doped chitosan

Biopolymer-based materials have been of particular interest as alternatives do synthetic polymers due to their low toxicity, biodegradability and biocompatibility. Among them, chitosan is one of the most studied ones and has recently been investigated for the application as solid state polymer electrolytes. Furthermore, it can serve as a host for luminescent species such as rare earth ions, giving rise to materials with increased functionality, of particular interest for electrochemical devices. In this study, we investigate chitosan based luminescent materials doped wit Eu3+ and Li+ triflate salts from the structural, photophysical and conductivity points of view. Because the host presents a broad emission band in the blue to green, while Eu3+ emits in the red, fine tuning of emission colour and/or generation of white light is possible by optimizing composition and excitation scheme. Europium lifetimes (5D0) are in the range 270 – 350 µs and quantum yields are as high as 2%. Although Li+ does not interfere with the luminescent properties, it grants ion-conducting properties to the material suggesting that a combination of both properties could be further explored in multifunctional device.

Early holocenic and historic mtDNA african signatures in the iberian peninsula: The andalusian region as a paradigm

Determining the timing, identity and direction of migrations in the Mediterranean Basin, the role of "migratory routes" in and among regions of Africa, Europe and Asia, and the effects of sex-specific behaviors of population movements have important implications for our understanding of the present human genetic diversity. A crucial component of the Mediterranean world is its westernmost region. Clear features of transcontinental ancient contacts between North African and Iberian populations surrounding the maritime region of Gibraltar Strait have been identified from archeological data. The attempt to discern origin and dates of migration between close geographically related regions has been a challenge in the field of uniparental-based population genetics. Mitochondrial DNA (mtDNA) studies have been focused on surveying the H1, H3 and V lineages when trying to ascertain north-south migrations, and U6 and L in the opposite direction, assuming that those lineages are good proxies for the ancestry of each side of the Mediterranean. To this end, in the present work we have screened entire mtDNA sequences belonging to U6, M1 and L haplogroups in Andalusians--from Huelva and Granada provinces--and Moroccan Berbers. We present here pioneer data and interpretations on the role of NW Africa and the Iberian Peninsula regarding the time of origin, number of founders and expansion directions of these specific markers. The estimated entrance of the North African U6 lineages into Iberia at 10 ky correlates well with other L African clades, indicating that U6 and some L lineages moved together from Africa to Iberia in the Early Holocene. Still, founder analysis highlights that the high sharing of lineages between North Africa and Iberia results from a complex process continued through time, impairing simplistic interpretations. In particular, our work supports the existence of an ancient, frequently denied, bridge connecting the Maghreb and Andalusia.

Monocarboxylate transport inhibition potentiates the cytotoxic effect of 5-fluorouracil in colorectal cancer cells

Cancer cells rely mostly on glycolysis to meet their energetic demands, producing large amounts of lactate that are extruded to the tumour microenvironment by monocarboxylate transporters (MCTs). The role of MCTs in the survival of colorectal cancer (CRC) cells is scarce and poorly understood. In this study, we aimed to better understand this issue and exploit these transporters as novel therapeutic targets alone or in combination with the CRC classical chemotherapeutic drug 5-Fluorouracil. For that purpose, we characterized the effects of MCT activity inhibition in normal and CRC derived cell lines and assessed the effect of MCT inhibition in combination with 5-FU. Here, we demonstrated that MCT inhibition using CHC (a-cyano-4-hydroxycinnamic acid), DIDS (4,4'-diisothiocyanatostilbene-2,2'-disulphonic acid) and quercetin decreased cell viability, disrupted the glycolytic phenotype, inhibited proliferation and enhanced cell death in CRC cells. These results were confirmed by specific inhibition of MCT1/4 by RNA interference. Notably, we showed that 5-FU cytotoxicity was potentiated by lactate transport inhibition in CRC cells, either by activity inhibition or expression silencing. These findings provide novel evidence for the pivotal role of MCTs in CRC maintenance and survival, as well as for the use of these transporters as potential new therapeutic targets in combination with CRC conventional therapy.

Electronic structure and optical signatures of semiconducting transition metal dichalcogenide nanosheets

CONSPECTUS: Two-dimensional (2D) crystals derived from transition metal dichalcogenides (TMDs) are intriguing materials that offer a unique platform to study fundamental physical phenomena as well as to explore development of novel devices. Semiconducting group 6 TMDs such as MoS2 and WSe2 are known for their large optical absorption coefficient and their potential for high efficiency photovoltaics and photodetectors. Monolayer sheets of these compounds are flexible, stretchable, and soft semiconductors with a direct band gap in contrast to their well-known bulk crystals that are rigid and hard indirect gap semiconductors. Recent intense research has been motivated by the distinct electrical, optical, and mechanical properties of these TMD crystals in the ultimate thickness regime. As a semiconductor with a band gap in the visible to near-IR frequencies, these 2D MX2 materials (M = Mo, W; X = S, Se) exhibit distinct excitonic absorption and emission features. In this Account, we discuss how optical spectroscopy of these materials allows investigation of their electronic properties and the relaxation dynamics of excitons. We first discuss the basic electronic structure of 2D TMDs highlighting the key features of the dispersion relation. With the help of theoretical calculations, we further discuss how photoluminescence energy of direct and indirect excitons provide a guide to understanding the evolution of the electronic structure as a function of the number of layers. We also highlight the behavior of the two competing conduction valleys and their role in the optical processes. Intercalation of group 6 TMDs by alkali metals results in the structural phase transformation with corresponding semiconductor-to-metal transition. Monolayer TMDs obtained by intercalation-assisted exfoliation retains the metastable metallic phase. Mild annealing, however, destabilizes the metastable phase and gradually restores the original semiconducting phase. Interestingly, the semiconducting 2H phase, metallic 1T phase, and a charge-density-wave-like 1T' phase can coexist within a single crystalline monolayer sheet. We further discuss the electronic properties of the restacked films of chemically exfoliated MoS2. Finally, we focus on the strong optical absorption and related exciton relaxation in monolayer and bilayer MX2. Monolayer MX2 absorbs as much as 30% of incident photons in the blue region of the visible light despite being atomically thin. This giant absorption is attributed to nesting of the conduction and valence bands, which leads to diversion of optical conductivity. We describe how the relaxation pathway of excitons depends strongly on the excitation energy. Excitation at the band nesting region is of unique significance because it leads to relaxation of electrons and holes with opposite momentum and spontaneous formation of indirect excitons.