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Transcranial direct current stimulation (tDCS) has been proposed as a new treatment in major depressive disorder (MDD). This is a fully remote, multisite, double-blind, placebo-controlled, randomized superiority trial of 10-week home-based tDCS in MDD. Participants were 18 years or older, with MDD in current depressive episode of at least moderate severity as measured using the Hamilton Depression Rating Scale (mean = 19.07 ± 2.73). A total of 174 participants (120 women, 54 men) were randomized to active (n= 87, mean age = 37.09 ± 11.14 years) or sham (n= 87, mean age = 38.32 ± 10.92 years) treatment. tDCS consisted of five sessions per week for 3 weeks then three sessions per week for 7 weeks in a 10-week trial, followed by a 10-week open-label phase. Each session lasted 30 min; the anode was placed over the left dorsolateral prefrontal cortex and the cathode over the right dorsolateral prefrontal cortex (active tDCS 2 mA and sham tDCS 0 mA, with brief ramp up and down to mimic active stimulation). As the primary outcome, depressive symptoms showed significant improvement when measured using the Hamilton Depression Rating Scale: active 9.41 ± 6.25 point improvement (10-week mean = 9.58 ± 6.02) and sham 7.14 ± 6.10 point improvement (10-week mean = 11.66 ± 5.96) (95% confidence interval = 0.51–4.01, P= 0.012). There were no differences in discontinuation rates. In summary, a 10-week home-based tDCS treatment with remote supervision in MDD showed high efficacy, acceptability and safety. ClinicalTrials.gov registration: NCT05202119

The main drawbacks of blood-contacting metallic devices are corrosion and thrombus formation on the surface, so polymeric coatings have been proposed to improve its hemocompatibility. Sulfated chitosan (SC) was obtained from natural chitosan (NC) reaction with chlorosulfonic acid to be used as a coating for metallic surfaces. The sulfated chitosan showed no platelet aggregation, an extended clotting time, and non-toxicity to rat fibroblast L929 cells. In this study, stainless steel (SS) and titanium alloys modified with TiO2nanotube (NTT) growth received a NC and SC coating. The titanium surface coated with sulfated chitosan presented the lowest percentage of platelet coverage area. Sulfated chitosan proved to be a promising material for use as a coating for metallic surfaces applied for cardiovascular devices.

As adsorbents directly interact with the biological fluid, they can induce normal physiological mechanisms for repairing body functionality. As a result, biopolymers are widely used as natural and biocompatible alternatives to synthetic adsorbents for establishing body homeostasis in medical treatment. In this regard, relevant properties of carbohydrate-based bioactive adsorbents can be tailored to contribute to the design of safer coatings surfaces for implant devices. This review explores the most common polysaccharide-based polymers applicable in blood-contacting devices for treating degenerative diseases, wound healing, and developing anti-thrombogenic surfaces. Furthermore, challenges and limitations of blood-contacting devices that must still be tackled and strategies to enhance their hemocompatibility are described to encourage their prospective use.

This paper presents as a contribution a fast and systematic approach for the estimation of mechanical parameters of switched reluctance motor drives based on the particle swarm optimization (PSO) algorithm. The proposal is straightforward, successfully avoiding the use of traditional cumbersome and time-consuming tests, sophisticated observers and even the need to design additional controllers. Considering the data from only a current controlled step response, the procedure enables fast offline parameter estimation, based on a minimum squared error metric. Experimental results are provided to demonstrate the effectiveness of the proposed approach, showing that the estimated parameters can be satisfactorily used for control design and lead to suitable simulation responses that match the measured experimental data.

•The modified impact of fatigue scale (MFIS) applied by telephone showed adequate validity.•The MFIS applied by telephone showed adequate reliability.•A change of more than 2 points demonstrates a change in the impact of fatigue.

Chitosan is an exciting alternative for the development of coating-surfaces due to its large action spectrum against pathogenic microorganisms. However, to produce a stable coating with effective antibacterial action, a compromise between deacetylation degree (DD) and molecular weight (MW) is essential. Four chitosan samples were characterized regarding Mw and DD and correlated with the minimum and bactericide concentrations against E. coli, P. aeruginosa,and S. aureus. CHI80MW (79.7% DD and 7.0 × 105Da) showed the best antibacterial effect and was selected to functionalize polytetrafluoroethylene (PTFE) surfaces by plasma. CHI80MW was grafted onto the PTFE surfaces using two different spacer molecules: poly(ethylene glycol) bis (carboxymethyl) ether (PEG) and poly(ethylene-alt-maleic anhydride) (PA). PTFE-Plasma-PA-CHI80MW exhibited a coating with more attached chitosan and better antibacterial action if compared to PTFE-Plasma-PEG-CHI80MW: after 8 h, PTFE-Plasma-PEG-CHI80MW presented a bacterial reduction of 25-30% for the three bacterial strains, and PTFE-Plasma-PA-CHI80MW reduced them to 77-90%. Moreover, cytotoxicity tests showed that PTFE-Plasma-PA-CHI80MW samples were compatible with human fibroblasts.

This paper presents a sensorless control strategy for non-sinusoidal permanent magnet synchronous machines (PMSM) based on a positive sequence detector + phase-locked loop (PSD+PLL) approach. The non-sinusoidal characteristic of the back-EMF results in oscillations when the speed and position are estimated through conventional methods. The proposed approach estimates the back-EMF using a Luenberger observer on stationary reference frame. Furthermore, a PSD is built using a dual second-order generalized integrator (DSOGI), which is tuned in the synchronous frequency estimated by the PLL and is employed to calculate the observed back-EMF fundamental component. Thus, it is possible to re-reduce the back-EMF harmonic content through the proposed scheme. The PLL is adjusted by a PI mechanism and the gain design is performed using pole-placement. The design analysis is also presented and the constrains regarding the PLL natural frequency and damping ratio are investigated. Simulation and experimental results demonstrate that the proposed sensorless control scheme allows the position and speed to be properly estimated even in a machine with non-sinusoidal back-EMF.

(R,S)-ketamine (ketamine) and its enantiomer (S)-ketamine (esketamine) can produce rapid and substantial antidepressant effects. However, individual response to ketamine/esketamine is variable, and there are no well-accepted methods to differentiate persons who are more likely to benefit. Numerous potential peripheral biomarkers have been reported, but their current utility is unclear. We conducted a systematic review/meta-analysis examining the association between baseline levels and longitudinal changes in blood-based biomarkers, and response to ketamine/esketamine. Of the 5611 citations identified, 56 manuscripts were included (N= 2801 participants), and 26 were compatible with meta-analytical calculations. Random-effect models were used, and effect sizes were reported as standardized mean differences (SMD). Our assessments revealed that more than 460 individual biomarkers were examined. Frequently studied groups included neurotrophic factors (n= 15), levels of ketamine and ketamine metabolites (n= 13), and inflammatory markers (n= 12). There were no consistent associations between baselinelevels of blood-based biomarkers, and response to ketamine. However, in a longitudinalanalysis, ketamine responders had statistically significant increases in brain-derived neurotrophic factor (BDNF) when compared to pre-treatment levels (SMD [95% CI] = 0.26 [0.03, 0.48], p= 0.02), whereas non-responders showed no significant changes in BDNF levels (SMD [95% CI] = 0.05 [−0.19, 0.28], p= 0.70). There was no consistent evidence to support any additional longitudinal biomarkers. Findings were inconclusive for esketamine due to the small number of studies (n= 2). Despite a diverse and substantial literature, there is limited evidence that blood-based biomarkers are associated with response to ketamine, and no current evidence of clinical utility.

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18–75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted “brain age” and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen’s d= 0.14, 95% CI: 0.08–0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Dysfunction in a wide array of systems—including the immune, monoaminergic, and glutamatergic systems—is implicated in the pathophysiology of depression. One potential intersection point for these three systems is the kynurenine (KYN) pathway. This study explored the impact of the prototypic glutamatergic modulator ketamine on the endogenous KYN pathway in individuals with bipolar depression (BD), as well as the relationship between response to ketamine and depression-related behavioral and peripheral inflammatory markers. Thirty-nine participants with treatment-resistant BD (23 F, ages 18–65) received a single ketamine infusion (0.5 mg/kg) over 40 min. KYN pathway analytes—including plasma concentrations of indoleamine 2,3-dioxygenase (IDO), KYN, kynurenic acid (KynA), and quinolinic acid (QA)—were assessed at baseline (pre-infusion), 230 min, day 1, and day 3 post-ketamine. General linear models with restricted maximum likelihood estimation and robust sandwich variance estimators were implemented. A repeated effect of time was used to model the covariance of the residuals with an unstructured matrix. After controlling for age, sex, and body mass index (BMI), post-ketamine IDO levels were significantly lower than baseline at all three time points. Conversely, ketamine treatment significantly increased KYN and KynA levels at days 1 and 3 versus baseline. No change in QA levels was observed post-ketamine. A lower post-ketamine ratio of QA/KYN was observed at day 1. In addition, baseline levels of proinflammatory cytokines and behavioral measures predicted KYN pathway changes post ketamine. The results suggest that, in addition to having rapid and sustained antidepressant effects in BD participants, ketamine also impacts key components of the KYN pathway.

This paper proposes a fast adaptive parameter estimation method for maximum torque per ampere control (MTPA) of interior permanent magnet synchronous motor (IPMSM) drives. The adaptive features that enable fast parameter estimation are investigated, and an adaptive observer with a structure capable of achieving fast estimation is proposed. A cascade adaptive observer design strategy is presented in order to obtain the benefit of fast estimation from the proposed adaptive scheme. The MTPA is achieved through the solution of the stator current optimization problem combined with the IPMSM estimated parameters. Simulation and experimental results are provided in order to validate the proposed fast estimation adaptive MTPA algorithm.

The permanent magnet synchronous machines have been used in a wide variety of industrial and commercial applications. The back-EMF waveform of these machines can be sinusoidal or non-sinusoidal. A well-known example for non-sinusoidal machine is the brushless DC drive, in which the machine presents a trapezoidal back-EMF. This machine can be driven by a conventional six-step strategy or could be driven through vector control schemes. However, classic field-oriented control techniques using the Park transformation, could result in torque oscillations. A solution widely employed in the literature is the use of extended control techniques, which uses the information of the back-EMF to perform the reference frame transformations. In addition, the back-EMF information is essential for implementing algorithms of speed and rotor position estimation. In this context, this paper presents a systematic gain design methodology of back-EMF observers for non-sinusoidal PMSM. The observer gains are designed using pole placement technique and a straightforward guideline for gains selection is presented. The discrete-time analysis is performed in order to deal with applications using microprocessors. The proposed observer is compared with a Luenberger observer. Simulation and experimental results corroborate the proposed methodology and demonstrate the observer robustness.

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI?=?63.47–67.00, ROC-AUC?=?71.49%, 95% CI?=?69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI?=?56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa?=?0.83, 95% CI?=?0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.

This study evaluates the influence of the presence of oxygenated groups created onto the surface of activated carbon (AC) on its ability to disperse platinum (Pt) or palladium (Pd) particles and on its catalytic performance to drive the transformation of glycerol into lactic acid. AC pretreatment consisted of oxidation in the presence of HNO3aqueous solutions conducted at 50, 70, and 90 °C, aiming at creating oxygenated groups on the support surface. The catalytic activities of Pt/AC and Pd/AC catalysts were evaluated in the production of lactic acid from both glycerol and crude glycerin. Lower-temperature pretreatments provided catalytic supports showing higher metal uptakes together with similar catalytic activity conversion and yield for both metals (5% Pt/AC and 10% Pd/AC). The catalysts were stable in five reaction cycles, and only negligible activity loss was detected.

This paper proposes a gain design methodology for adaptive observers applied to the estimation of rotor speed of permanent magnet synchronous machines (PMSM). First, a disturbance observer is used for estimation of the back-electromotive force (back-EMF) and avoid undesired nonlinearities in the adaptive observer design. The rotor speed is estimated by a back-EMF adaptive observer based on the PMSM linear model in stationary frame. Both feedback and adaptive gains are analyzed considering the full system in state space form. A pole placement technique is used to design the adaptive and feedback gains, and the mathematical behavior of the speed estimator is obtained. The desired pole locations of the observer are discussed aiming the implementation of a sensorless control scheme. Simulation and experimental results are presented to validate the proposed gain design method.

This paper investigates the digital redesign of proportional integral (PI) controllers implemented under a delay of one sampling period. The usual digital redesign based on state matching cannot be directly applied here. The digital control gains are obtained by means of linear matrix inequalities that minimize the $${\mathcal {H}}_{\infty }$$H∞norm associated with an error signal defined as the difference between the closed-loop system with continuous-time controller and the closed-loop system with the discrete-time controller implemented under the delay. Three synthesis conditions are given, exploring extra matrix variables and suitable matrix structures to provide more efficient redesigns that can deal even with large control delays in the implementation of the redesigned controller. As a contribution, the proposed conditions provide a theoretical guarantee that digital PIs, operating under delay, will perform very close to originally designed continuous-time PIs. A numerical example illustrates the efficiency of the proposed conditions, and a practical application for permanent magnet synchronous motor speed regulation shows good experimental results, illustrating the viability of the proposal.

The main objective of this study was to assess the kinetics of the deterioration of blends of babassu and castor biodiesel. The biodiesel samples were synthesized by catalytic transesterification and characterized for their main physical properties such as kinematic viscosity, density, acid number, ester content, and oxidation stability. Thermal profiles were carried out using the Differential Scanning Calorimetry technique as presented in the American Society for Testing and Materials (ASTM) E537 standard. Kinetic parameters were obtained using ASTM E2041 standard (Borchardt–Daniels method), following a statistical treatment from the ASTM E1970 standard. Among all samples, the pure castor biodiesel sample showed the highest extrapolated onset temperature (Ts), 214.92 °C, and lowest reaction rate [k(T)], 1.02 × 10−3min−1, indicating that this sample is more resistant to oxidation. On the other hand, the blend with the babassu/castor biodiesel mass ratio of 75/25 was the most prone to oxidize. Thus, castor biodiesel may be used as an additive to improve the oxidative stability of other sources of biodiesel, including babassu biodiesel.

Bipolar disorder is a chronic and recurrent illness characterized by depressive and manic episodes. Proton magnetic resonance spectroscopy (1H-MRS) studies have demonstrated glutamate (Glu) system abnormalities in BD, but it is unclear how Glu varies among mood states and how medications modulate it. The objective of this study was to investigate the influence of mood stabilizers on anterior cingulate cortex Glu levels using 1H-MRS during euthymia.

Recent studies have reported on the development of low-cost dressings that can deliver bioactive compounds to wounds, improving patients' quality of life. Our previous study successfully developed alginate-based single and bilayer membranes for slow release of simvastatin. This work aims to develop a new alginate bilayer dressing composed of membranes with different porosities and enhanced properties for sustained simvastatin delivery. These membranes were prepared by two drying processes; convection solvent evaporation and lyophilization, which are essential for modulating porosity and simvastatin release. The membranes were characterized using physical-chemical, thermal, morphological and mechanical analyses. Simvastatin release was accomplished using Franz's diffusion cells. The membranes' shelf-life and cytotoxicity were evaluated using human keratinocytes. Differences in membrane porosity influenced the morphological features of the membranes and their physical barrier properties. In vitrorelease studies showed that the bilayer membranes can sustain longer drug release than the single-layer membrane, which may benefit long-term treatment. Of interest, a more porous bottom layer allowed a faster simvastatin release during the first 6 h than a denser bottom layer. The shelf life analysis showed that, after 6 months, all membranes maintained around 98% of the initial drug content without changing their visual appearance. A cell viability assay showed that simvastatin-loaded alginate membranes are non-cytotoxic.

This paper presents an Atkinson Cycle mechanisms classification. The proposed classification is based on mechanism theory, dividing the mechanisms into two main classes and eight subclasses. The reconfigurability of Atkinson Cycle mechanisms is discussed as well as the mechanism characteristics for each class. This classification was applied to the engines found in bibliography and patent survey. Both surveys were necessary to yield a complete state of the art, regarding not only academic but also technological advances. These surveys and the Atkinson Cycle engine classification expose the wide window of opportunities for engine development. The use of reconfigurable Atkinson Cycle engines can be a powerful tool to develop more efficient vehicles.

The enumeration of kinematic chains for epicyclic gear trains allows obtaining all the possible configurations from specified structural characteristics. However, the more complex becomes the desired structure, the greater the number of options to analyse in order to select the most suitable one, therefore, it is necessary a criterion to reduce this range of choices. The variety of kinematic chains and the concept of minimal sets can be used for this purpose. This paper enumerates the kinematic chains with zero variety for epicyclic gear trains with one and two degrees of freedom, and with up to four independent loops. Some epicyclic gear trains generated from the chains belonging to minimal sets are presented afterward, and the advantages of using zero variety chains are discussed.

In this paper, the influence of load distribution on the stability of heavy articulated vehicles is analyzed. In general, heavy articulated vehicles have low performance with respect to stability analysis, being the focus of many studies in literature. Several characteristics of the vehicles have been analyzed to determine their influence on the vehicle stability calculation; however, load distribution is rarely analyzed. To conduct this research, the Davies method is used to obtain the static of the mechanism that represent the last trailer of the vehicle. Using this method, the longitudinal, lateral and vertical displacements of the center of gravity (CG) are investigated, and a sensitivity analysis is made. Finally, a numerical case study is showed and the results of this study demonstrate that the load distribution has important role on the static rollover threshold (SRT) calculation.

This article presents a method for the dimensional synthesis of the rack-and-pinion steering mechanism by optimization technique based on a novel synthesis equation. The proposed kinematic model allows obtaining a polynomial synthesis equation to formulate the objective function as a sum of squares. Then, the computation of the objective function derivatives is straightforward compared to existing formulations. Finally, the application of the proposed method is shown through a numerical example implemented in Matlab®.

This paper proposes a composite control strategy which combines a discrete-time sliding mode controller with a disturbance observer aiming to decouple current control of vector oriented induction motor drives. The stator current control is carried out through an indirect field orientation in a dqreference frame rotating at synchronous speed. The cross-coupling variables of the induction motor stator currents at synchronous reference frame are modeled as disturbances, and these values are estimated using a discrete-time disturbance observer. The digital implementation delay was included in the plant model formulation, resulting in a control law suitable to direct implementation in microcontrollers and digital signal processors. Then, the nominal and decoupled part of the induction machine model is used for the design of the sliding mode controller, and the additional variables are modeled as disturbances. The cross-coupling variables are observed and used in the control law. The convergence analysis is presented in discrete-time domain. Simulation and experimental results are presented to validate the theoretical analysis, and they show the good performance of the proposed method.

Both bipolar disorder (BD) and major depressive disorder (MDD) have high morbidity and share a genetic background. Treatment options for these mood disorders are currently suboptimal for many patients; however, specific genetic variables may be involved in both pathophysiology and response to treatment. Agents such as the glutamatergic modulator ketamine are effective in treatment-resistant mood disorders, underscoring the potential importance of the glutamatergic system as a target for improved therapeutics. Here we review genetic studies linking the glutamatergic system to the pathophysiology and therapeutics of mood disorders. We screened 763 original genetic studies of BD or MDD that investigated genes encoding targets of the pathway/mediators related to the so-called tripartite glutamate synapse, including pre- and post-synaptic neurons and glial cells; 60 papers were included in this review. The findings suggest the involvement of glutamate-related genes in risk for mood disorders, treatment response, and phenotypic characteristics, although there was no consistent evidence for a specific gene. Target genes of high interest included GRIA3 and GRIK2 (which likely play a role in emergent suicidal ideation after antidepressant treatment), GRIK4 (which may influence treatment response), and GRM7 (which potentially affects risk for mood disorders). There was stronger evidence that glutamate-related genes influence risk for BD compared with MDD. Taken together, the studies show a preliminary relationship between glutamate-related genes and risk for mood disorders, suicide, and treatment response, particularly with regard to targets on metabotropic and ionotropic receptors.