3D Printing and Nanotechnology: A Multiscale Alliance in Personalized Medicine

3D printing and nanotechnology have been two important tools in the development of therapeutic approaches for personalized medicine. More recently, their alliance has been improved in an effort to build innovative, versatile, multifunctional, and/or smart medical and pharmaceutical products. Therefore, an extensive review about scientific studies that ally 3D printing and nanomaterials in the development of new approaches for pharmaceutical and medical applications for the treatment and prevention of diseases is presented here. The articles are classified into five categories according to their main application: Cell growth and tissue engineering, antimicrobial, drug delivery, stimulus-response, and theranostics. Semisolid extrusion, inorganic nanoparticles, and cell growth and tissue engineering are the most reported 3D printing technique, type of nanomaterial, and application, respectively. The increase in papers dedicated to these areas is also notable, especially in the 2019 and 2020, when semisolid extrusion became the most used technique, overcoming fused deposition modelling. In fact, this review highlights that the possibility of an alliance between 3D printing and nanotechnology for the production of multiscale materials is undoubtedly a great opportunity for knowledge and innovation in the pharmaceutical and medical area.     

Diagnosis of learner dropout based on learning styles for online distance learning

The amount of data generated by computer systems in Online Distance Learning (ODL) contains rich information. One example of this information we define as the Learner Learning Trail (LLT), which is the sequence of interactions between the students and the virtual environment. Another example is the Learner Learning Style (LLS), which is associated with the student behavior and choices during the learning process. This information can be used to identify learner behavior and learning style. We perceived, after the study of related literature, that the research field of learner diagnosis for ODL does not apply the conjoint use of LLT and LLS. In this article, we propose a model capable of integrating data generated from the behavior of students in ODL with cognitive aspects of them, such as their Learning Styles, by crossing LLT with LLS. We also propose the CPAD method (Collect, Preprocessing, Analysis, Diagnosis), which is implemented by collecting the raw data regarding learning activities, preprocessing the data into structured time sequences, analyzing the sequences regarding the learning styles and using this analysis to diagnose the learner behavior. We selected the dropout to investigate, once the dropout rate in ODL is a real problem in universities around the world. In addition, the dropout is a student decision which can be associated with previous students behaviors. We performed a study with 202 learners to evaluate if learning styles are capable of explaining aspects of the student behavior. The results suggest that Sequential/Global learning style dimension is more capable of explaining the dropout than the other dimensions. Also, we performed four classification experiments to verify how the dimensions of Felder-Silverman Learning Style Model influence the learner diagnosis. We perceived that the Sequential/Global dimension could provide a higher accuracy average with lower variation independently of the diagnosis technique.     

Bandwidth Aspects in Second Generation Current Conveyors

This paper discusses bandwidth problems associated with second-generation current conveyors (CCII). In particular, our work is centered in high-capacitance applications, and has been oriented for wireless optical links and applied physics. We discuss techniques for improving bandwidth in these CCIIs, and develop a new CCII structure with larger bandwidth than traditional circuits. These circuits are then compared in terms of their noise and dynamic range characteristics. A test circuit was developed to verify these different bandwidth behaviors.     

Environmentally Friendly Graphene Inks for Touch Screen Sensors

Graphene-based materials have attracted significant attention in many technological fields, but scaling up graphene-based technologies still faces substantial challenges. High-throughput top-down methods generally require hazardous, toxic, and high-boiling-point solvents. Here, an efficient and inexpensive strategy is proposed to produce graphene dispersions by liquid-phase exfoliation (LPE) through a combination of shear-mixing (SM) and tip sonication (TS) techniques, yielding highly concentrated graphene inks compatible with spray coating. The quality of graphene flakes (e.g., lateral size and thickness) and their concentration in the dispersions are compared using different spectroscopic and microscopy techniques. Several approaches (individual SM and TS, and their combination) are tested in three solvents (N-methyl-2-pyrrolidone, dimethylformamide, and cyrene). Interestingly, the combination of SM and TS in cyrene yields high-quality graphene dispersions, overcoming the environmental issues linked to the other two solvents. Starting from the cyrene dispersion, a graphene-based ink is prepared to spray-coat flexible electrodes and assemble a touch screen prototype. The electrodes feature a low sheet resistance (290 Ω □⁻¹) and high optical transmittance (78%), which provide the prototype with a high signal-to-noise ratio (14 dB) and multi-touch functionality (up to four simultaneous touches). These results illustrate a potential pathway toward the integration of LPE-graphene in commercial flexible electronics.     

Estimation of breast tumor thermal properties using infrared images

The major goal of this paper is to help detect breast cancer early based on infrared images. Some procedures, protocols and numerical simulations were developed or performed. Two different issues are presented. The first is the development of a standardized protocol for the acquisition of breast thermal images including the design, construction and installation of mechanical apparatus. The second part is related to the greatest difficulty for the numerical computation of breast temperature profiles that is caused by the uncertainty of the real values of the thermophysical parameters of some tissues. Then, a methodology for estimating thermal properties based on these infrared images is presented. The commercial software FLUENT^TM was used for the numerical simulation. A Sequential Quadratic Programming (SQP) method was used to solve the inverse problem and to estimate the thermal conductivity and blood perfusion of breast tissues. The results showed that it is possible to estimate the thermophysical properties using the thermography. The next stage will be to use the geometry of a real breast for the numerical simulation in conjunction with a linear mapping of the temperatures measured over the breast volume.     

MESFET DC model parameter extraction using Quantum Particle Swarm Optimization

This paper presents two techniques for DC model parameter extraction for a Gallium Arsenide (GaAs) based MEtal Semiconductor Field Effect Transistor (MESFET) device. The proposed methods uses Particle Swarm Optimization (PSO) and Quantum Particle Swarm Optimization (QPSO) methods for optimizing the difference between measured data and simulated data. Simulated data are obtained by using four different popular DC models. These techniques avoid complex computational steps involved in traditional parameter extraction techniques. The performance comparison in terms of quality of solution and execution time of classical PSO and QPSO to extract the model parameters are presented. The validity of this approach is verified by comparing the simulated and measured results of a fabricated GaAs MESFET device with gate length of 0.7 μm and gate width of 600 μm (4 × 150). Simulation results indicate that both the technique based on PSO and QPSO accurately extracts the model parameters of MESFET.     

Identity-based key management in mobile ad hoc networks: techniques and applications [dependability in the ubiquitous wireless access]

Security is one of the major issues in MANETs. Their natural characteristics make them vulnerable to numerous severe attacks. It is widely acknowledged that cryptography provides a set of strong techniques against most vulnerabilities. Several cryptographic mechanisms for MANETs can be found in the literature. Among them, identity-based cryptographic mechanisms and key management schemes are proposed to simplify key management and to reduce the memory storage cost. This article presents the most important ID-based key management schemes, discussing their approaches, strengths, and weaknesses, and comparing their main features. It also presents the main IDbased key management application fields on MANETs. In this way it can be useful for users and researchers as a starting point on ID-based key management and its possible uses in MANETs.     

A multimode CMOS PA with a single propagation path

Analog Integrated Circuits and Signal Processing - In this paper a four mode 130 nm RF CMOS power amplifier (PA) in a single propagation path topology is presented and evaluated with IEEE...