Screening of grapes and wine for azoxystrobin, kresoxim-methyl and trifloxystrobin fungicides by HPLC with diode array detection

The Quinone outside Inhibitors (QoI) are one of the most important and recent fungicide groups used in viticulture and also allowed by Integrated Pest Management. Azoxystrobin, kresoxim-methyl and trifloxystrobin are the main active ingredients for treating downy and powdery mildews that can be present in grapes and wines. In this paper, a method is reported for the analysis of these three QoI-fungicides in grapes and wine. After liquid–liquid extraction and a clean-up on commercial silica cartridges, analysis was by isocratic HPLC with diode array detection (DAD) with a run time of 13 min. Confirmation was by solid-phase micro-extraction (SPME), followed by GC/MS determination. The main validation parameters for the three compounds in grapes and wine were a limit of detection up to 0.073mg kg-1, a precision not exceeding 10.0% and an average recovery of 93% ±38.

Green production of zero-valent iron nanoparticles using tree leaf extracts

The interest in zero-valent iron nanoparticles has been increasing significantly since the development of a green production method in which extracts from natural products or wastes are used. However, this field of application is yet poorly studied and lacks knowledge that allows the full understanding of the production and application processes. The aim of the present work was to evaluate the viability of the utilization of several tree leaves to produce extracts which are capable of reducing iron(III) in aqueous solution to form nZVIs. The quality of the extracts was evaluated concerning their antioxidant capacity. The results show that: i) dried leaves produce extracts with higher antioxidant capacities than non-dried leaves, ii) the most favorable extraction conditions (temperature, contact time, and volume:mass ratio) were identified for each leaf, iii) with the aim of developing a green, but also low-cost,method waterwas chosen as solvent, iv) the extracts can be classified in three categories according to their antioxidant capacity (expressed as Fe(II) concentration): >40 mmol L−1; 20–40 mmol L−1; and 2–10 mmol L−1; with oak, pomegranate and green tea leaves producing the richest extracts, and v) TEManalysis proves that nZVIs (d=10–20 nm) can be produced using the tree leaf extracts.

Application of green zero-valent iron nanoparticles to the remediation of soils contaminated with ibuprofen

Zero-valent iron nanoparticles (nZVIs) are often used in environmental remediation. Their high surface area that is associated with their high reactivity makes them an excellent agent capable of transforming/degrading contaminants in soils and waters. Due to the recent development of green methods for the production of nZVIs, the use of this material became even more attractive. However, the knowledge of its capacity to degrade distinct types of contaminants is still scarce. The present work describes the study of the application of green nZVIs to the remediation of soils contaminated with a common anti-inflammatory drug, ibuprofen. The main objectives of this work were to produce nZVIs using extracts of grape marc, black tea and vine leaves, to verify the degradation of ibuprofen in aqueous solutions by the nZVIs, to study the remediation process of a sandy soil contaminated with ibuprofen using the nZVIs, and to compare the experiments with other common chemical oxidants. The produced nZVIs had nanometric sizes and were able to degrade ibuprofen (54 to 66% of the initial amount) in aqueous solutions. Similar remediation efficiencies were obtained in sandy soils. In this case the remediation could be enhanced (achieving degradation efficiencies above 95%) through the complementation of the process with a catalyzed nZVI Fenton-like reaction. These results indicate that this remediation technology represents a good alternative to traditional and more aggressive technologies.

Multiplexed electrochemical immunosensor for detection of celiac disease serological markers

Celiac disease (CD) is a gluten-induced autoimmune enteropathy characterized by the presence of antibodies against gliadin (AGA) and anti-tissue transglutaminase (anti-tTG) antibodies. A disposable electrochemical dual immunosensor for the simultaneous detection of IgA and IgG type AGA and antitTG antibodies in real patient’s samples is presented. The proposed immunosensor is based on a dual screen-printed carbon electrode, with two working electrodes, nanostructured with a carbon–metal hybrid system that worked as the transducer surface. The immunosensing strategy consisted of the immobilization of gliadin and tTG (i.e. CD specific antigens) on the nanostructured electrode surface. The electrochemical detection of the human antibodies present in the assayed serum samples was carried out through the antigen–antibody interaction and recorded using alkaline phosphatase labelled anti-human antibodies and a mixture of 3-indoxyl phosphate with silver ions was used as the substrate. The analytical signal was based on the anodic redissolution of enzymatically generated silver by cyclic voltammetry. The results obtained were corroborated with commercial ELISA kits indicating that the developed sensor can be a good alternative to the traditional methods allowing a decentralization of the analyses towards a point-of-care strategy.

Detection of ZnS phases in CZTS thin-films by EXAFS

Copper zinc tin sulfide (CZTS) is a promising Earthabundant thin-film solar cell material; it has an appropriate band gap of ~1.45 eV and a high absorption coefficient. The most efficient CZTS cells tend to be slightly Zn-rich and Cu-poor. However, growing Zn-rich CZTS films can sometimes result in phase decomposition of CZTS into ZnS and Cu2SnS3, which is generally deleterious to solar cell performance. Cubic ZnS is difficult to detect by XRD, due to a similar diffraction pattern. We hypothesize that synchrotron-based extended X-ray absorption fine structure (EXAFS), which is sensitive to local chemical environment, may be able to determine the quantity of ZnS phase in CZTS films by detecting differences in the second-nearest neighbor shell of the Zn atoms. Films of varying stoichiometries, from Zn-rich to Cu-rich (Zn-poor) were examined using the EXAFS technique. Differences in the spectra as a function of Cu/Zn ratio are detected. Linear combination analysis suggests increasing ZnS signal as the CZTS films become more Zn-rich. We demonstrate that the sensitive technique of EXAFS could be used to quantify the amount of ZnS present and provide a guide to crystal growth of highly phase pure films.

Detection of quasi-periodic processes in complex systems: how do we quantitatively describe their properties?

It has been shown that in reality at least two general scenarios of data structuring are possible: (a) a self-similar (SS) scenario when the measured data form an SS structure and (b) a quasi-periodic (QP) scenario when the repeated (strongly correlated) data form random sequences that are almost periodic with respect to each other. In the second case it becomes possible to describe their behavior and express a part of their randomness quantitatively in terms of the deterministic amplitude–frequency response belonging to the generalized Prony spectrum. This possibility allows us to re-examine the conventional concept of measurements and opens a new way for the description of a wide set of different data. In particular, it concerns different complex systems when the ‘best-fit’ model pretending to be the description of the data measured is absent but the barest necessity of description of these data in terms of the reduced number of quantitative parameters exists. The possibilities of the proposed approach and detection algorithm of the QP processes were demonstrated on actual data: spectroscopic data recorded for pure water and acoustic data for a test hole. The suggested methodology allows revising the accepted classification of different incommensurable and self-affine spatial structures and finding accurate interpretation of the generalized Prony spectroscopy that includes the Fourier spectroscopy as a partial case.

Low-loss austempered ductile iron gears: experimental evaluation comparing materials and lubricants

An experimental study to evaluate the power dissipation of gears was performed. Three low-loss gear models were manufactured using standard 20° pressure angle tools. Austempered ductile iron (ADI) and 20MnCr5 carburized steel gears were tested in an FZG gear test machine using mineral, ester and polyalphaolephine (PAO)-based oils. The results compare power dissipation, the influence of different tooth flank geometries, materials and lubricants. This work concludes that conventional power-transmission gears can be replaced by these improved and more efficient low–loss models, which can be produced using common tools and that steel gears can be successfully replaced by austempered ductile iron gears.

Low torque loss gears: austempered ductile iron versus carburized steel

Low-loss power transmission gears operate at lower temperature than conventional ones because their teeth geometry is optimized to reduce friction. The main objective of this work is to compare the operating stabilization temperature and efficiency of low-loss austempered ductile iron (ADI) and carburized steel gears. Three different low-loss tooth geometries were adopted (types 311, 411 and 611, all produced using standard 20° pressure angle tools) and corresponding steel and ADI gears were tested in a FZG machine. The results obtained showed that low-loss geometries had a significant influence on power loss, gears 611 generating lower power loss than gears 311. At low speeds (500 and 1000 rpm) and high torque ADI gears generated lower power loss than steel gears. However, at high speed and high torque (high input power and high stabilization temperature) steel gears had better efficiency.

Using mobile device detection approaches to augment the accuracy of web delivery content

Recent studies of mobile Web trends show a continuous explosion of mobile-friendly content. However, the increasing number and heterogeneity of mobile devices poses several challenges for Web programmers who want to automatically get the delivery context and adapt the content to mobile devices. In this process, the devices detection phase assumes an important role where an inaccurate detection could result in a poor mobile experience for the enduser. In this paper we compare the most promising approaches for mobile device detection. Based on this study, we present an architecture for a system to detect and deliver uniform m-Learning content to students in a Higher School. We focus mainly on the devices capabilities repository manageable and accessible through an API. We detail the structure of the capabilities XML Schema that formalizes the data within the devices capabilities XML repository and the REST Web Service API for selecting the correspondent devices capabilities data according to a specific request. Finally, we validate our approach by presenting the access and usage statistics of the mobile web interface of the proposed system such as hits and new visitors, mobile platforms, average time on site and rejection rate.

Using device detection techniques in M-learning scenarios

Recent studies of mobile Web trends show the continued explosion of mobile-friend content. However, the wide number and heterogeneity of mobile devices poses several challenges for Web programmers, who want automatic delivery of context and adaptation of the content to mobile devices. Hence, the device detection phase assumes an important role in this process. In this chapter, the authors compare the most used approaches for mobile device detection. Based on this study, they present an architecture for detecting and delivering uniform m-Learning content to students in a Higher School. The authors focus mainly on the XML device capabilities repository and on the REST API Web Service for dealing with device data. In the former, the authors detail the respective capabilities schema and present a new caching approach. In the latter, they present an extension of the current API for dealing with it. Finally, the authors validate their approach by presenting the overall data and statistics collected through the Google Analytics service, in order to better understand the adherence to the mobile Web interface, its evolution over time, and the main weaknesses.

Sensitive bi-enzymatic biosensor based on polyphenoloxidases–gold nanoparticles–chitosan hybrid film–graphene doped carbon paste electrode for carbamates detection

A bi-enzymatic biosensor (LACC–TYR–AuNPs–CS/GPE) for carbamates was prepared in a single step by electrodeposition of a hybrid film onto a graphene doped carbon paste electrode (GPE). Graphene and the gold nanoparticles (AuNPs) were morphologically characterized by transmission electron microscopy, X-ray photoelectron spectroscopy, dynamic light scattering and laser Doppler velocimetry. The electrodeposited hybrid film was composed of laccase (LACC), tyrosinase (TYR) and AuNPs entrapped in a chitosan (CS) polymeric matrix. Experimental parameters, namely graphene redox state, AuNPs:CS ratio, enzymes concentration, pH and inhibition time were evaluated. LACC–TYR–AuNPs–CS/GPE exhibited an improved Michaelis–Menten kinetic constant (26.9 ± 0.5 M) when compared with LACC–AuNPs–CS/GPE (37.8 ± 0.2 M) and TYR–AuNPs–CS/GPE (52.3 ± 0.4 M). Using 4-aminophenol as substrate at pH 5.5, the device presented wide linear ranges, low detection limits (1.68×10− 9 ± 1.18×10− 10 – 2.15×10− 7 ± 3.41×10− 9 M), high accuracy, sensitivity (1.13×106 ± 8.11×104 – 2.19×108 ± 2.51×107 %inhibition M− 1), repeatability (1.2–5.8% RSD), reproducibility (3.2–6.5% RSD) and stability (ca. twenty days) to determine carbaryl, formetanate hydrochloride, propoxur and ziram in citrus fruits based on their inhibitory capacity on the polyphenoloxidases activity. Recoveries at two fortified levels ranged from 93.8 ± 0.3% (lemon) to 97.8 ± 0.3% (orange). Glucose, citric acid and ascorbic acid do not interfere significantly in the electroanalysis. The proposed electroanalytical procedure can be a promising tool for food safety control.

Utilization of food industry wastes for the production of zero-valent iron nanoparticles

The proper disposal of the several types of wastes produced in industrial activities increases production costs. As a consequence, it is common to develop strategies to reuse these wastes in the same process and in different processes or to transform them for use in other processes. This work combines the needs for new synthesis methods of nanomaterials and the reduction of production cost using wastes from citrine juice (orange, lime, lemon and mandarin) to produce a new added value product, green zero-valent iron nanoparticles that can be used in several applications, including environmental remediation. The results indicate that extracts of the tested fruit wastes (peel, albedo and pulp fractions) can be used to produce zero-valent iron nanoparticles (nZVIs). This shows that these wastes can be an added value product. The resulting nZVIs had sizes ranging from 3 up to 300 nm and distinct reactivities (pulp > peel > albedo extracts). All the studied nanoparticles did not present a significant agglomeration/settling tendency when compared to similar nanoparticles, which indicates that they remain in suspension and retain their reactivity.

Multilayer Perceptron Neural Networks Training Through Charged System Search and its Application for Non-Technical Losses Detection

The non-technical loss is not a problem with trivial solution or regional character and its minimization represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. In this paper, we show how to improve the training phase of a neural network-based classifier using a recently proposed meta-heuristic technique called Charged System Search, which is based on the interactions between electrically charged particles. The experiments were carried out in the context of non-technical loss in power distribution systems in a dataset obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others natureinspired optimization techniques for training neural networks. Thus, it is possible to improve some applications on Smart Grids.

Iron Overload Favors the Elimination of Leishmania

Iron plays a central role in host-parasite interactions, since both intervenients need iron for survival and growth, but are sensitive to iron-mediated toxicity. The host’s iron overload is often associated with susceptibility to infection. However, it has been previously reported that iron overload prevented the growth of Leishmania major, an agent of cutaneous leishmaniasis, in BALB/c mice. In order to further clarify the impact of iron modulation on the growth of Leishmania in vivo, we studied the effects of iron supplementation or deprivation on the growth of L. infantum, the causative agent of Mediterranean visceral leishmaniasis, in the mouse model. We found that dietary iron deficiency did not affect the protozoan growth, whereas iron overload decreased its replication in the liver and spleen of a susceptible mouse strain. The fact that the iron-induced inhibitory effect could not be seen in mice deficient in NADPH dependent oxidase or nitric oxide synthase 2 suggests that iron eliminates L. infantum in vivo through the interaction with reactive oxygen and nitrogen species. Iron overload did not significantly alter the mouse adaptive immune response against L. infantum. Furthermore, the inhibitory action of iron towards L. infantum was also observed, in a dose dependent manner, in axenic cultures of promastigotes and amastigotes. Importantly, high iron concentrations were needed to achieve such effects. In conclusion, externally added iron synergizes with the host’s oxidative mechanisms of defense in eliminating L. infantum from mouse tissues. Additionally, the direct toxicity of iron against Leishmania suggests a potential use of this metal as a therapeutic tool or the further exploration of iron anti-parasitic mechanisms for the design of new drugs.

Iron Metabolism: From Health to Disease

Background Iron is vital for almost all living organisms by participating in a wide range of metabolic processes. However, iron concentration in body tissues must be tightly regulated since excessive iron may lead to microbial infections or cause tissue damage. Disorders of iron metabolism are among the most common human diseases and cover several conditions with varied clinical manifestations. Methods An extensive literature review on the basic aspects of iron metabolism was performed, and the most recent findings on this field were highlighted as well. Results New insights on iron metabolism have shed light into its real complexity, and its role in both healthy and pathological states has been recognized. Important discoveries about the iron regulatory machine and imbalances in its regulation have been made, which may lead in a near future to the development of new therapeutic strategies against iron disorders. Besides, the toxicity of free iron and its association with several pathologies has been addressed, although it requires further investigations. Conclusion This review will provide students in the fields of biochemistry and health sciences a brief and clear overview of iron physiology and toxicity, as well as imbalances in the iron homeostasis and associated pathological conditions.