Optimization of microwave-assisted extraction of hydrophilic and lipophilic antioxidants from a surplus tomato crop by response surface methodology

Tomato is the second most important vegetable crop worldwide and a rich source of industrially interesting antioxidants. Hence, the microwave-assisted extraction of hydrophilic (H) and lipophilic (L) antioxidants from a surplus tomato crop was optimized using response surface methodology. The relevant independent variables were temperature (T), extraction time (t), ethanol concentration (Et) and solid/liquid ratio (S/L). The concentration-time response methods of crocin and β-carotene bleaching were applied, since they are suitable in vitro assays to evaluate the antioxidant activity of H and L matrices, respectively. The optimum operating conditions that maximized the extraction were as follows: t, 2.25 min; T, 149.2 ºC; Et, 99.1 %; and S/L, 45.0 g/L for H antioxidants; and t, 15.4 min; T, 60.0 ºC; Et, 33.0 %; and S/L, 15.0 g/L for L antioxidants. This industrial approach indicated that surplus tomatoes possess a high content of antioxidants, offering an alternative source for obtaining natural value-added compounds. Additionally, by testing the relationship between the polarity of the extraction solvent and the antioxidant activity of the extracts in H and L media (polarity-activity relationship), useful information for the study of complex natural extracts containing components with variable degrees of polarity was obtained.

Microwave-assisted extraction of phenolic acids and flavonoids and production of antioxidant ingredients from tomato: a nutraceutical-oriented optimization study

The production of natural extracts requires suitable processing conditions to maximize the preservation of the bioactive ingredients. Herein, a microwave-assisted extraction (MAE) process was optimized, by means of response surface methodology (RSM), to maximize the recovery of phenolic acids and flavonoids and obtain antioxidant ingredients from tomato. A 5-level full factorial Box-Behnken design was successfully implemented for MAE optimization, in which the processing time (t), temperature (T), ethanol concentration (Et) and solid/liquid ratio (S/L) were relevant independent variables. The proposed model was validated based on the high values of the adjusted coefficient of determination and on the non-significant differences between experimental and predicted values. The global optimum processing conditions (t=20 min; T=180 ºC; Et=0 %; and S/L=45 g/L) provided tomato extracts with high potential as nutraceuticals or as active ingredients in the design of functional foods. Additionally, the round tomato variety was highlighted as a source of added-value phenolic acids and flavonoids.

Path relinking for the fixed spectrum frequency assignment problem

International audience

I. Quantal effects in biochemical cooperativity and a proposed mechanism for the differentiation of calcium signaling in synaptic plasticity. II. Evolutionary algorithms for the optimization of methods in computational chemistry

In Part 1 of this thesis, we propose that biochemical cooperativity is a fundamentally non-ideal process. We show quantal effects underlying biochemical cooperativity and highlight apparent ergodic breaking at small volumes. The apparent ergodic breaking manifests itself in a divergence of deterministic and stochastic models. We further predict that this divergence of deterministic and stochastic results is a failure of the deterministic methods rather than an issue of stochastic simulations.

Ergodic breaking at small volumes may allow these molecular complexes to function as switches to a greater degree than has previously been shown. We propose that this ergodic breaking is a phenomenon that the synapse might exploit to differentiate Ca$^{2+}$ signaling that would lead to either the strengthening or weakening of a synapse. Techniques such as lattice-based statistics and rule-based modeling are tools that allow us to directly confront this non-ideality. A natural next step to understanding the chemical physics that underlies these processes is to consider \textit{in silico} specifically atomistic simulation methods that might augment our modeling efforts.

In the second part of this thesis, we use evolutionary algorithms to optimize \textit{in silico} methods that might be used to describe biochemical processes at the subcellular and molecular levels. While we have applied evolutionary algorithms to several methods, this thesis will focus on the optimization of charge equilibration methods. Accurate charges are essential to understanding the electrostatic interactions that are involved in ligand binding, as frequently discussed in the first part of this thesis.

Mayaro virus and dengue virus 1 and 4 natural infection in culicids from Cuiabá, state of Mato Grosso, Brazil

This study aimed to verify the diversity of Culicidae species and their frequency of infection with flaviviruses and alphaviruses in Cuiabá, state of Mato Grosso, Brazil. Mosquitoes were captured with Nasci aspirators and hand net in 200 census tracts, identified alive at species level and pooled in one-20 (11,090 mosquitoes, 14 species). Female pools (n = 610) were subjected to multiplex seminested-reverse transcription-polymerase chain reaction (RT-PCR) for 11 flavivirus and five alphavirus. Positive pools were tested by single RT-PCR followed by nucleotide sequencing, by RT-PCR for E1 gene [Mayaro virus (MAYV)] and by inoculation in Vero cells (MAYV) or C6/36 cells (flaviviruses). One/171 Aedes aegypti was positive for dengue virus (DENV)-1, 12/403 Culex quinquefasciatus , and four/171 Ae. aegypti for MAYV, which was isolated from two pools containing two nonengorged females of Ae. aegypti and two of Cx. quinquefasciatus. DENV-4 was detected in 58/171 pools of Ae. aegytpi, 105/403 Cx. quinquefasciatus, two/five Psorophora sp., two/11 Psorophora varipes / Psorophora albigenu , one/one Sabethes chloropterus , two/five Culex bidens / Culex interfor , and one/one Aedes sp. DENV-4 was isolated from two pools containing three and 16 nonengorged Cx. quinquefasciatus females. Phylogenetic analysis revealed MAYV belongs to genotype L, clustering with human samples of the virus previously identified in the city. Cuiabá has biodiversity and ecosystem favourable for vector proliferation, representing a risk for arbovirus outbreaks.

Sparse time-frequency data analysis : a multi-scale approach

In this work, we further extend the recently developed adaptive data analysis method, the Sparse Time-Frequency Representation (STFR) method. This method is based on the assumption that many physical signals inherently contain AM-FM representations. We propose a sparse optimization method to extract the AM-FM representations of such signals. We prove the convergence of the method for periodic signals under certain assumptions and provide practical algorithms specifically for the non-periodic STFR, which extends the method to tackle problems that former STFR methods could not handle, including stability to noise and non-periodic data analysis. This is a significant improvement since many adaptive and non-adaptive signal processing methods are not fully capable of handling non-periodic signals. Moreover, we propose a new STFR algorithm to study intrawave signals with strong frequency modulation and analyze the convergence of this new algorithm for periodic signals. Such signals have previously remained a bottleneck for all signal processing methods. Furthermore, we propose a modified version of STFR that facilitates the extraction of intrawaves that have overlaping frequency content. We show that the STFR methods can be applied to the realm of dynamical systems and cardiovascular signals. In particular, we present a simplified and modified version of the STFR algorithm that is potentially useful for the diagnosis of some cardiovascular diseases. We further explain some preliminary work on the nature of Intrinsic Mode Functions (IMFs) and how they can have different representations in different phase coordinates. This analysis shows that the uncertainty principle is fundamental to all oscillating signals.

Frequency of metabolic syndrome in women treated at the Menopause Clinic of the “Dr. José Eleuterio González” University Hospital of the UANL in Northeastern Mexico

Objectives: To determine the frequency of metabolic syndrome (MS) in patients with menopause, and to compare the incidence of MS between surgical and natural menopause. Methods: This was an observational, longitudinal, descriptive, retrospective, unblinded study of cases seen at the Menopause Clinic of the University Hospital “Dr. José eleuterio González” of the Universidad Autónoma de Nuevo León from March 2009 to December 2011. The frequency of MS was determined based on Adult Treatment Panel III (ATPIII) classiication. Results: at the end of the study, 391 patients were evaluated. The mean age was 50.1 years. We found a frequency of MS of 38.1%, the risk factor most often found was low HDL cholesterol (62.5%), followed by obesity (46.5%), hypercholesterolemia (42.3%), hyperglycemia (11.5%), and hypertension (7.7%). The incidence of natural and surgical menopause was 37.6% vs. 39.2% respectively; however, the result was not statistically signiicant (p = 0.093). Conclusions: Patients with menopause are at increased risk of developing MS. it is important to detect MS early in this of patients, when they have one risk factor to avoid complications which may trigger the syndrome. We recommend screening for MS during perimenopause, in order to detect and try to delay it in a timely manner and recommend primary prevention (diet and exercise), or secondary prevention in cases with one or more risk factors.

Frequency of metabolic syndrome in women treated at the Menopause Clinic of the “Dr. José Eleuterio González” University Hospital of the UANL in Northeastern Mexico

Objectives: To determine the frequency of metabolic syndrome (MS) in patients with menopause, and to compare the incidence of MS between surgical and natural menopause. Methods: This was an observational, longitudinal, descriptive, retrospective, unblinded study of cases seen at the Menopause Clinic of the University Hospital “Dr. José eleuterio González” of the Universidad Autónoma de Nuevo León from March 2009 to December 2011. The frequency of MS was determined based on Adult Treatment Panel III (ATPIII) classiication. Results: at the end of the study, 391 patients were evaluated. The mean age was 50.1 years. We found a frequency of MS of 38.1%, the risk factor most often found was low HDL-cholesterol (62.5%), followed by obesity (46.5%), hypercholesterolemia (42.3%), hyperglycemia (11.5%), and hypertension (7.7%). The incidence of natural and surgical menopause was 37.6% vs. 39.2% respectively; however, the result was not statistically signiicant (p = 0.093). Conclusions: Patients with menopause are at increased risk of developing MS. it is important to detect MS early in this of patients, when they have one risk factor to avoid complications which may trigger the syndrome. We recommend screening for MS during perimenopause, in order to detect and try to delay it in a timely manner and recommend primary prevention (diet and exercise), or secondary prevention in cases with one or more risk factors.

A natural extension of the classical envelope theorem in vector differential programming

The aim of this paper is to extend the classical envelope theorem from scalar to vector differential programming. The obtained result allows us to measure the quantitative behaviour of a certain set of optimal values (not necessarily a singleton) characterized to become minimum when the objective function is composed with a positive function, according to changes of any of the parameters which appear in the constraints. We show that the sensitivity of the program depends on a Lagrange multiplier and its sensitivity.

Development of Physics-based Models and Design Optimization of Power Electronic Conversion Systems

The main objective for physics based modeling of the power converter components is to design the whole converter with respect to physical and operational constraints. Therefore, all the elements and components of the energy conversion system are modeled numerically and combined together to achieve the whole system behavioral model. Previously proposed high frequency (HF) models of power converters are based on circuit models that are only related to the parasitic inner parameters of the power devices and the connections between the components. This dissertation aims to obtain appropriate physics-based models for power conversion systems, which not only can represent the steady state behavior of the components, but also can predict their high frequency characteristics. The developed physics-based model would represent the physical device with a high level of accuracy in predicting its operating condition. The proposed physics-based model enables us to accurately develop components such as; effective EMI filters, switching algorithms and circuit topologies [7]. One of the applications of the developed modeling technique is design of new sets of topologies for high-frequency, high efficiency converters for variable speed drives. The main advantage of the modeling method, presented in this dissertation, is the practical design of an inverter for high power applications with the ability to overcome the blocking voltage limitations of available power semiconductor devices. Another advantage is selection of the best matching topology with inherent reduction of switching losses which can be utilized to improve the overall efficiency. The physics-based modeling approach, in this dissertation, makes it possible to design any power electronic conversion system to meet electromagnetic standards and design constraints. This includes physical characteristics such as; decreasing the size and weight of the package, optimized interactions with the neighboring components and higher power density. In addition, the electromagnetic behaviors and signatures can be evaluated including the study of conducted and radiated EMI interactions in addition to the design of attenuation measures and enclosures.

Physics-Based Modeling of Power System Components for the Evaluation of Low-Frequency Radiated Electromagnetic Fields

The low-frequency electromagnetic compatibility (EMC) is an increasingly important aspect in the design of practical systems to ensure the functional safety and reliability of complex products. The opportunities for using numerical techniques to predict and analyze system’s EMC are therefore of considerable interest in many industries. As the first phase of study, a proper model, including all the details of the component, was required. Therefore, the advances in EMC modeling were studied with classifying analytical and numerical models. The selected model was finite element (FE) modeling, coupled with the distributed network method, to generate the model of the converter’s components and obtain the frequency behavioral model of the converter. The method has the ability to reveal the behavior of parasitic elements and higher resonances, which have critical impacts in studying EMI problems. For the EMC and signature studies of the machine drives, the equivalent source modeling was studied. Considering the details of the multi-machine environment, including actual models, some innovation in equivalent source modeling was performed to decrease the simulation time dramatically. Several models were designed in this study and the voltage current cube model and wire model have the best result. The GA-based PSO method is used as the optimization process. Superposition and suppression of the fields in coupling the components were also studied and verified. The simulation time of the equivalent model is 80-100 times lower than the detailed model. All tests were verified experimentally. As the application of EMC and signature study, the fault diagnosis and condition monitoring of an induction motor drive was developed using radiated fields. In addition to experimental tests, the 3DFE analysis was coupled with circuit-based software to implement the incipient fault cases. The identification was implemented using ANN for seventy various faulty cases. The simulation results were verified experimentally. Finally, the identification of the types of power components were implemented. The results show that it is possible to identify the type of components, as well as the faulty components, by comparing the amplitudes of their stray field harmonics. The identification using the stray fields is nondestructive and can be used for the setups that cannot go offline and be dismantled

Simultaneous optimization of colloidal stability and interfacial charge transfer efficiency in photocatalytic Pt/CdS nanocrystals

Colloidal stability and efficient interfacial charge transfer in semiconductor nanocrystals are of great importance for photocatalytic applications in aqueous solution since they provide long-term functionality and high photocatalytic activity, respectively. However, colloidal stability and interfacial charge transfer efficiency are difficult to optimize simultaneously since the ligand layer often acts as both a shell stabilizing the nanocrystals in colloidal suspension and a barrier reducing the efficiency of interfacial charge transfer. Here, we show that, for cysteine-coated, Pt-decorated CdS nanocrystals and Na2SO3 as hole scavenger, triethanolamine (TEOA) replaces the original cysteine ligands in situ and prolongs the highly efficient and steady H2 evolution period by more than a factor of 10. It is shown that Na2SO3 is consumed during H2 generation while TEOA makes no significant contribution to the H2 generation. An apparent quantum yield of 31.5%, a turnover frequency of 0.11 H2/Pt/s, and an interfacial charge transfer rate faster than 0.3 ps were achieved in the TEOA stabilized system. The short length, branched structure and weak binding of TEOA to CdS as well as sufficient free TEOA in the solution are the keys to enhancing colloidal stability and maintaining efficient interfacial charge transfer at the same time. Additionally, TEOA is commercially available and cheap, and we anticipate that this approach can be widely applied in many photocatalytic applications involving colloidal nanocrystals.

Informational masking and the effects of differences in fundamental frequency and fundamental-frequency contour on phonetic integration in a formant ensemble

This study explored the effects on speech intelligibility of across-formant differences in fundamental frequency (ΔF0) and F0 contour. Sentence-length speech analogues were presented dichotically (left=F1+F3; right=F2), either alone or—because competition usually reveals grouping cues most clearly—accompanied in the left ear by a competitor for F2 (F2C) that listeners must reject to optimize recognition. F2C was created by inverting the F2 frequency contour. In experiment 1, all left-ear formants shared the same constant F0 and ΔF0F2 was 0 or ±4 semitones. In experiment 2, all left-ear formants shared the natural F0 contour and that for F2 was natural, constant, exaggerated, or inverted. Adding F2C lowered keyword scores, presumably because of informational masking. The results for experiment 1 were complicated by effects associated with the direction of ΔF0F2; this problem was avoided in experiment 2 because all four F0 contours had the same geometric mean frequency. When the target formants were presented alone, scores were relatively high and did not depend on the F0F2 contour. F2C impact was greater when F2 had a different F0 contour from the other formants. This effect was a direct consequence of the associated ΔF0; the F0F2 contour per se did not influence competitor impact.

Antimicrobial resistance in indicator Escherichia coli isolates from free-ranging livestock and sympatric wild ungulates in a natural environment (Northeastern Spain)

Antimicrobial resistance was assessed in indicator Escherichia coli isolates from free-ranging livestock and sympatric wild boar (Sus scrofa) and Iberian ibex (Capra pyrenaica) in a National Game Reserve in northeastern Spain. The frequency of antimicrobial resistance was low (0% to 7.9%). However, resistance to an extended-spectrum cephalosporin and fluoroquinolones was detected.

Frequency adjustable MEMS vibration energy harvester

Ambient mechanical vibrations offer an attractive solution for powering the wireless sensor nodes of the emerging "Internet-of-Things". However, the wide-ranging variability of the ambient vibration frequencies pose a significant challenge to the efficient transduction of vibration into usable electrical energy. This work reports the development of a MEMS electromagnetic vibration energy harvester where the resonance frequency of the oscillator can be adjusted or tuned to adapt to the ambient vibrational frequency. Micro-fabricated silicon spring and double layer planar micro-coils along with sintered NdFeB micro-magnets are used to construct the electromagnetic transduction mechanism. Furthermore, another NdFeB magnet is adjustably assembled to induce variable magnetic interaction with the transducing magnet, leading to significant change in the spring stiffness and resonance frequency. Finite element analysis and numerical simulations exhibit substantial frequency tuning range (25% of natural resonance frequency) by appropriate adjustment of the repulsive magnetic interaction between the tuning and transducing magnet pair. This demonstrated method of frequency adjustment or tuning have potential applications in other MEMS vibration energy harvesters and micromechanical oscillators.