An automatic approach to detect skin cancer utilizing active infrared thermography.

Skin cancer is a growing global concern, with cases steadily rising. Typically, malignant moles are identified through visual inspection, using dermatoscopy and patient history. Active thermography has emerged as an effective method to distinguish between malignant and benign lesions.

VIS-NIR hyperspectral imaging and multivariate analysis for direct characterization of pelagic fish species.

The identification of fish species and their physical and chemical characterization play a crucial role in the fishing industry, fish-food research and the management of marine resources. Traditional methods for species identification, such as expert observation, DNA barcoding and meta-barcoding, though effective, require labor-intensive laboratory work. Consequently, there is a pressing need for more objective and efficient methodologies for accurate fish species identification and characterization.

Reduced fertilization supplemented with RGM 2450 and RGM 2529 promotes tomato production in a sustainable way.

The rising demand for vegetables has driven the adoption of greenhouse cultivation to guarantee high yields and quality of fresh produce year-round. Consequently, this elevates the demand for fertilizers, whose costs are progressively escalating. RGM 2450 and RGM 2529 are plant growth-promoting rhizobacteria (PGPR).

Feasibility Study on the Use of Infrared Cameras for Skin Cancer Detection under a Proposed Data Degradation Model.

Infrared thermography is considered a useful technique for diagnosing several skin pathologies but it has not been widely adopted mainly due to its high cost. Here, we investigate the feasibility of using low-cost infrared cameras with microbolometer technology for detecting skin cancer. For this purpose, we collected infrared data from volunteer subjects using a high-cost/high-quality infrared camera.

Digital Classification of Chilean Pelagic Species in Fishing Landing Lines.

Fishing landings in Chile are inspected to control fisheries that are subject to catch quotas. The control process is not easy since the volumes extracted are large and the numbers of landings and artisan shipowners are high. Moreover, the number of inspectors is limited, and a non-automated method is utilized that normally requires months of training.

Genomic and Experimental Analysis of the Biostimulant and Antagonistic Properties of Phytopathogens of and .

The RGM 2450 and RGM 2529 strains were isolated from the rhizosphere of plants presenting resilience to abiotic and biotic stress conditions. To understand the implications of bacteria in resilience, a genomic and experimental analysis was carried out on their biostimulant and phytopathogenic antagonist properties. Genome analyses of both strains indicated that they have the potential to synthesize bioactive compounds such as the battery of non-ribosomal peptides, polyketides, extracellular enzymes and phytohormones.

Genomic and Experimental Analysis of the Insecticidal Factors Secreted by the Entomopathogenic Fungus RGM 2184.

The entomopathogenic fungus strain RGM 2184 can reach a maximum efficacy of 80% against the quarantine pest in field assays. In this study, the RGM 2184 genome was sequenced, and genome mining analyses were performed to predict the factors involved in its insecticidal activity. Additionally, the metabolic profiling of the RMG 2184 culture's supernatants was analyzed by mass spectrometry, and the insecticidal activity from one of these extracts was evaluated in larvae.

: A Biological Control Approach with a Biopesticide Based on Entomopathogenic Fungi in the Winter Season in Chile.

(Denis and Shiffermüller) (Lepidoptera: Tortricidae) is one of the main pests that affect the production and export of table grapes in Chile. Because this pest has quarantine status, the fruit must be fumigated with methyl bromide, which reduces the fruit's export competitiveness in the destination market. In the present study, to help resolve this issue, six native entomopathogenic fungi were identified through multilocus analysis, including three and three .

Improved Antibiotic Detection in Raw Milk Using Machine Learning Tools over the Absorption Spectra of a Problem-Specific Nanobiosensor.

In this article we present the development of a biosensor system that integrates nanotechnology, optomechanics and a spectral detection algorithm for sensitive quantification of antibiotic residues in raw milk of cow. Firstly, nanobiosensors were designed and synthesized by chemically bonding gold nanoparticles (AuNPs) with aptamer bioreceptors highly selective for four widely used antibiotics in the field of veterinary medicine, namely, Kanamycin, Ampicillin, Oxytetracycline and Sulfadimethoxine. When molecules of the antibiotics are present in the milk sample, the interaction with the aptamers induces random AuNP aggregation.

Slight pH Fluctuations in the Gold Nanoparticle Synthesis Process Influence the Performance of the Citrate Reduction Method.

Gold nanoparticles (AuNPs) are currently under intense investigation for biomedical and biotechnology applications, thanks to their ease in preparation, stability, biocompatibility, multiple surface functionalities, and size-dependent optical properties. The most commonly used method for AuNP synthesis in aqueous solution is the reduction of tetrachloroauric acid (HAuCl₄) with trisodium citrate. We have observed variations in the pH and in the concentration of the gold colloidal suspension synthesized under standard conditions, verifying a reduction in the reaction yield by around 46% from pH 5.

An embedded system for image segmentation and multimodal registration in noninvasive skin cancer screening.

We present a heterogeneous architecture for image registration and multimodal segmentation on an embedded system for noninvasive skin cancer screening. The architecture combines Otsu thresholding and the random walker algorithm to perform image segmentation, and features a hardware implementation of the Harris corner detection algorithm to perform region-of-interest detection and image registration. Running on a Xilinx XC7Z020 reconfigurable system-on-a-chip, our prototype computes the initial segmentation of a 400×400-pixel region of interest in the visible spectrum in 12.

Detection theory for accurate and non-invasive skin cancer diagnosis using dynamic thermal imaging.

Skin cancer is the most common cancer in the United States with over 3.5M annual cases. Presently, visual inspection by a dermatologist has good sensitivity (> 90%) but poor specificity (< 10%), especially for melanoma, which leads to a high number of unnecessary biopsies.

A novel approach to study the pMDI plume using an infrared camera and to evaluate the aerodynamic properties after varying the time between actuations.

Plume characteristics, such as temperature and velocity, emitted from pMDIs could significantly affect the dose delivered to the lung. Currently, high speed cameras and thermocouples are used separately to evaluate these parameters. We used a low-noise infrared camera to evaluate both the temperature and velocity of the emitted plume from pMDIs.

Model-based edge detector for spectral imagery using sparse spatiospectral masks.

Two model-based algorithms for edge detection in spectral imagery are developed that specifically target capturing intrinsic features such as isoluminant edges that are characterized by a jump in color but not in intensity. Given prior knowledge of the classes of reflectance or emittance spectra associated with candidate objects in a scene, a small set of spectral-band ratios, which most profoundly identify the edge between each pair of materials, are selected to define a edge signature. The bands that form the edge signature are fed into a spatial mask, producing a sparse joint spatiospectral nonlinear operator.

Data compressive paradigm for multispectral sensing using tunable DWELL mid-infrared detectors.

While quantum dots-in-a-well (DWELL) infrared photodetectors have the feature that their spectral responses can be shifted continuously by varying the applied bias, the width of the spectral response at any applied bias is not sufficiently narrow for use in multispectral sensing without the aid of spectral filters. To achieve higher spectral resolutions without using physical spectral filters, algorithms have been developed for post-processing the DWELL's bias-dependent photocurrents resulting from probing an object of interest repeatedly over a wide range of applied biases. At the heart of these algorithms is the ability to approximate an arbitrary spectral filter, which we desire the DWELL-algorithm combination to mimic, by forming a weighted superposition of the DWELL's non-orthogonal spectral responses over a range of applied biases.

Noise-cancellation-based nonuniformity correction algorithm for infrared focal-plane arrays.

The spatial fixed-pattern noise (FPN) inherently generated in infrared (IR) imaging systems compromises severely the quality of the acquired imagery, even making such images inappropriate for some applications. The FPN refers to the inability of the photodetectors in the focal-plane array to render a uniform output image when a uniform-intensity scene is being imaged. We present a noise-cancellation-based algorithm that compensates for the additive component of the FPN.

Membrane currents in the oocyte of the toad Bufo arenarum.

The amphibian oocyte cell model is widely used for heterologous expression of ionic channels and receptors. Little is known, however, about the physiology of oocyte cell models other than Xenopus laevis. In this study, the two-electrode voltage clamp technique was used to assess the most common electrical patterns of oocytes of the South American toad Bufo arenarum.