Efficient Design of Pruned Convolutional Neural Networks on FPGA

Journal of Signal Processing Systems - Convolutional Neural Networks (CNNs) have improved several computer vision applications, like object detection and classification, when compared to other...     

Development of a Topical Insulin Polymeric Nanoformulation for Skin Burn Regeneration: An Experimental Approach

Insulin is a peptide hormone with many physiological functions, besides its use in diabetes treatment. An important role of insulin is related to the wound healing process—however, insulin itself is too sensitive to the external environment requiring the protective of a nanocarrier. Polymer-based nanoparticles can protect, deliver, and retain the protein in the target area. This study aims to produce and characterize a topical treatment for wound healing consisting of insulin-loaded poly-DL-lactide/glycolide (PLGA) nanoparticles. Insulin-loaded nanoparticles present a mean size of approximately 500 nm and neutral surface charge. Spherical shaped nanoparticles are observed by scanning electron microscopy and confirmed by atomic force microscopy. SDS-PAGE and circular dichroism analysis demonstrated that insulin preserved its integrity and secondary structure after the encapsulation process. In vitro release studies suggested a controlled release profile. Safety of the formulation was confirmed using cell lines, and cell viability was concentration and time-dependent. Preliminary safety in vivo assays also revealed promising results.     

SOKNL: A novel way of integrating K-nearest neighbours with adaptive random forest regression for data streams

Data Mining and Knowledge Discovery - Most research in machine learning for data streams has focused on classification algorithms, whereas regression methods have received a lot less attention....     

Effect of RF magnetron sputtering parameters on the optimization of the discharge capacity of ternary lithium oxide thin films

Journal of Materials Science: Materials in Electronics - The increasing demand for lithium-ion batteries has stimulated the investigation of new compounds in order to reduce the costs and the...     

Rheokinematics for product development—Formulation screening in rotational rheometers

Product formulations for industrial processes are typically developed at laboratory scale. However, the mixing conditions are not easily mimicked in the laboratory. A rotational device is proposed in this study as a fast laboratory-scale formulation development, which enables mimicking the mixing conditions in the industrial process. The geometrical configurations of the rotational device are from rheometry devices (plate-plate and cone-plate). The main advantages of this method are the small amounts of raw materials and shorter testing times. This methodology is applied to an industrial case study, the reaction injection molding (RIM) process. The mixing length scales evolution in the rotational rheometer were matched to those in RIM machines. The main novelty of this study is the introduction of a protocol that bridges the processing conditions at laboratory using small amounts of raw materials to high throughput continuous flow reactors.     

Nanocomposite powders of hydroxyapatite-graphene oxide for biological applications

The repair of bone fractures is a clinical challenge for patients with impaired healing, such as osteoporosis. Currently, different strategies have been developed to design new biomaterials, enhancing their interactions with biological systems and conducting the cellular behavior in the desired direction to help fracture healing. In the present work, hydroxyapatite-graphene oxide (HA-GO) nanocomposites were produced and the morphological and physicochemical influences of the addition of 0.5 wt%, 1.0 wt% and 1.5 wt% of GO to HA were observed. FEG-SEM and TEM analyses of HA-GO nanocomposites showed HA nanoparticles adhered to the surface of the GO sheets, suggesting an effective method to form nanostructured graphene-based biomaterials. As confirmation, physicochemical analyses by Raman, FTIR and TGA demonstrated a strong affinity between HA and GO, according to the increase of concentration from 0.5 wt% to 1.5 wt% GO in the HA-GO nanocomposites. Also, in order to evaluate the HA-GO nanocomposites behavior under biological microenvironment, in vitro bioactivity and indirect cytotoxicity tests were performed. FEG-SEM analyses confirmed the positive results for the bioactivity properties of HA-GO nanocomposite and indirect cytotoxicity demonstrated that even with a decrease in the hDPSCs viability and proliferation, when increasing to 1.5 wt% of GO concentration, high level of cell viability was exhibited by HA-GO nanocomposites. These biological results suggested the 0.5 wt% HA-GO nanocomposite as a potential bioactive bone graft and a promising biomaterial for bone tissue regeneration, when compared to the pure HA.     

Touch sensor and photovoltaic characteristics of CuSbS2 thin films

Spin-coated chalcostibite CuSbS₂ thin films (≈500 nm thick) were fabricated and the influence of the drying temperature on the structural, morphological, optical and thermoelectric properties of the films was investigated. Crystalline phase-pure chalcostibite has been obtained for the films dried at 180 °C and 210 °C, while below 180 °C these films are partially amorphous. Surprisingly, at drying temperature of 240 °C, a Cu_xS secondary phase appeared. The increase of the drying temperature leads to the increase of the particle size and the decrease of the optical band gap, which is interesting for optoelectronic applications. The highest power factor value was achieved for the film dried at 210 °C, due to the inexistence of secondary phases, which allowed realizing a stable thermoelectric touch sensor with a V_signal/_noise of 5. In addition, this film was tested as a photovoltaic (PV) device and a power conversion efficiency (PCE) of 0.030% with an open-circuit voltage (V_OC) of 0.36 V, a short-circuit current density (J_SC) of 0.278 mAcm^?2 and a fill factor (FF) of 0.27 were obtained. Therefore, this work evidences a pathway toward developing bi-functional devices with simultaneously thermoelectric touch sensor and photovoltaic functions.     

An automated treatment planning strategy for highly noncoplanar radiotherapy arc trajectories

Radiation therapy is a technology-driven cancer treatment modality that has experienced significant advances over the last decades, due to multidisciplinary contributions that include engineering and computing. Recent technological developments allow the use of noncoplanar volumetric modulated arc therapy (VMAT), one of the most recent photon treatment techniques, in clinical practice. In this work, an automated noncoplanar arc trajectory optimization framework designed in two modular phases is presented. First, a noncoplanar beam angle optimization algorithm is used to obtain a set of noncoplanar irradiation directions. Then, anchored in these directions, an optimization strategy is proposed to compute an optimal arc trajectory. The computational experiments considered a pool of twelve difficult head-and-neck tumor cases. It was possible to observe that, for some of these cases, the optimized noncoplanar arc trajectories led to significant treatment planning quality improvements, when compared with coplanar VMAT treatment plans. Although these experiments were done in a research environment treatment planning software (matRad), the conclusions can be of interest for a clinical setting: automated procedures can simplify the current treatment workflow, produce high-quality treatment plans, making better use of human resources and allowing for unbiased comparisons between different treatment techniques.