Search Results (12)

The photovoltaic literature contains a wide range of methods for translating the I–V curves of a solar device to other conditions of irradiance and cell temperature, different from those under which the measurements were performed. Some of these translation methods are included as part of the International Standard IEC 60891. In this paper, these techniques are classified, reviewed, and implemented to perform a deep comparative analysis between them and to discuss their suitability for converting the I–V curves of photovoltaic modules under different scenarios of irradiance and temperature. From the analysis conducted, it can be seen that the interpolation method proposed in IEC 60891 achieves accurate results when it is applied to correct small and medium irradiance and temperature gaps. If no interpolation is possible and for large irradiance corrections, other procedures described in IEC 60891 can be applied. However, certain explicit methods based on the single-diode model or on the double-diode model can overcome the most well-known approaches proposed by the standard. Full article

The use of photovoltaic (PV) panels in interior spaces is expected to increase due to the proliferation of low-power sensor devices in the IoT domain. PV models are critical for estimating the I–V curves that define their performance at various light intensities. These models and the extraction of their parameters have been extensively studied under outdoor conditions, but their indoor illumination performance is less studied. With respect to the latter, several studies have used the parameter-scaling technique. However, the model’s accuracy degrades when the light level decreases. In this study, we propose a simple PV modeling technique that can be applied at various illuminance levels by only using characteristic points (short-circuit current, open-circuit voltage, and maximum-power voltage points) at a reference illumination level. The model uses the characteristic point translation technique to translate the reference characteristic points to other operating conditions. Then, parameter extraction technique is used to extract the model’s parameters. The proposed model’s accuracy is verified using two commercial PV panels and different indoor lighting technologies. The results indicate that the proposed model outperforms the other examined works in terms of accuracy, with an average improvement of 15.75%. Full article

Background: Current prostate cancer evaluation can be inaccurate and burdensome. Quantitative evaluation of Magnetic Resonance Imaging (MRI) sequences non-invasively helps prostate tumor assessment. However, including Dynamic Contrast Enhancement (DCE) in the examined MRI sequence set can add complications, inducing possible side effects from the IV placement or injected contrast material and prolonging scanning time. More accurate quantitative MRI without DCE and artificial intelligence approaches are needed. Purpose: Predict the risk of developing Clinically Significant (Insignificant) prostate cancer CsPCa (CiPCa) and correlate with the International Society of Urologic Pathology (ISUP) grade using processed Signal to Clutter Ratio (SCR) derived from spatially registered bi-parametric MRI (SRBP-MRI) and thereby enhance non-invasive management of prostate cancer. Methods: This pilot study retrospectively analyzed 42 consecutive prostate cancer patients from the PI-CAI data collection. BP-MRI (Apparent Diffusion Coefficient, High B-value, T2) were resized, translated, cropped, and stitched to form spatially registered SRBP-MRI. Efficacy of noise reduction was tested by regularizing, eliminating principal components (PC), and minimizing elliptical volume from the covariance matrix to optimize the SCR. MRI guided biopsy (MRBx), Systematic Biopsy (SysBx), combination (MRBx + SysBx), or radical prostatectomy determined the ISUP grade for each patient. ISUP grade ≥ 2 (<2) was judged as CsPCa (CiPCa). Linear and logistic regression were fitted to ISUP grade and CsPCa/CiPCa SCR. Correlation Coefficients (R) and Area Under the Curves (AUC) for Receiver Operator Curves (ROC) evaluated the performance. Results: High correlation coefficients (R) (>0.55) and high AUC (=1.0) for linear and/or logistic fit from processed SCR and z-score for SRBP-MRI greatly exceed fits using prostate serum antigen, prostate volume, and patient age (R ~ 0.17). Patients assessed with combined MRBx + SysBx and from individual MRI scanners achieved higher R (DR = 0.207+/−0.118) than all patients used in the fits. Conclusions: In the first study, to date, spectral approaches for assessing tumor aggressiveness on SRBP-MRI have been applied and tested and achieved high values of R and exceptional AUC to fit the ISUP grade and CsPCA/CiPCA, respectively. Full article

The aim of this study was to investigate the usefulness of radiomics in the absence of well-defined standard guidelines. Specifically, we extracted radiomics features from multicenter computed tomography (CT) images to differentiate between the four histopathological subtypes of non-small-cell lung carcinoma (NSCLC). In addition, the results that varied with the radiomics model were compared. We investigated the presence of the batch effects and the impact of feature harmonization on the models’ performance. Moreover, the question on how the training dataset composition influenced the selected feature subsets and, consequently, the model’s performance was also investigated. Therefore, through combining data from the two publicly available datasets, this study involves a total of 152 squamous cell carcinoma (SCC), 106 large cell carcinoma (LCC), 150 adenocarcinoma (ADC), and 58 no other specified (NOS). Through the matRadiomics tool, which is an example of Image Biomarker Standardization Initiative (IBSI) compliant software, 1781 radiomics features were extracted from each of the malignant lesions that were identified in CT images. After batch analysis and feature harmonization, which were based on the ComBat tool and were integrated in matRadiomics, the datasets (the harmonized and the non-harmonized) were given as an input to a machine learning modeling pipeline. The following steps were articulated: (i) training-set/test-set splitting (80/20); (ii) a Kruskal–Wallis analysis and LASSO linear regression for the feature selection; (iii) model training; (iv) a model validation and hyperparameter optimization; and (v) model testing. Model optimization consisted of a 5-fold cross-validated Bayesian optimization, repeated ten times (inner loop). The whole pipeline was repeated 10 times (outer loop) with six different machine learning classification algorithms. Moreover, the stability of the feature selection was evaluated. Results showed that the batch effects were present even if the voxels were resampled to an isotropic form and whether feature harmonization correctly removed them, even though the models’ performances decreased. Moreover, the results showed that a low accuracy (61.41%) was reached when differentiating between the four subtypes, even though a high average area under curve (AUC) was reached (0.831). Further, a NOS subtype was classified as almost completely correct (true positive rate ~90%). The accuracy increased (77.25%) when only the SCC and ADC subtypes were considered, as well as when a high AUC (0.821) was obtained—although harmonization decreased the accuracy to 58%. Moreover, the features that contributed the most to models’ performance were those extracted from wavelet decomposed and Laplacian of Gaussian (LoG) filtered images and they belonged to the texture feature class.. In conclusion, we showed that our multicenter data were affected by batch effects, that they could significantly alter the models’ performance, and that feature harmonization correctly removed them. Although wavelet features seemed to be the most informative features, an absolute subset could not be identified since it changed depending on the training/testing splitting. Moreover, performance was influenced by the chosen dataset and by the machine learning methods, which could reach a high accuracy in binary classification tasks, but could underperform in multiclass problems. It is, therefore, essential that the scientific community propose a more systematic radiomics approach, focusing on multicenter studies, with clear and solid guidelines to facilitate the translation of radiomics to clinical practice. Full article

The potential effect of intravenous administration of glutamate on the ovarian activity and the LH secretion pattern, considering the anestrous yearling goat as an animal model, were assessed. In late April, yearling goats (n = 20) were randomly assigned to either (1) Glutamate supplemented (GLUT; n = 10, Live Weight (LW) = 29.6 ± 1.02 kg, Body Condition (BCS) = 3.4 ± 0.2 units; i.v. supplemented with 7 mg GLUT kg⁻¹ LW) or (2) Non-supplemented (CONT; n = 10; LW = 29.2 ± 1.07 kg, BCS = 3.5 ± 0.2 units; i.v. saline). The oats were estrus-synchronized; blood sampling (6 h × 15 min) was carried out for LH quantification. Response variables included pulsatility (PULSE), time to first pulse (TTFP), amplitude (AMPL), nadir (NAD), and area under the curve (AUC) of LH. Ovaries were ultra-sonographically scanned to assess ovulation rate (OR), number of antral follicles (AF), and total ovarian activity (TOA = OR + AF). LH-PULSE was quantified with the Munro algorithm; significant treatment x time interactions were evaluated across time. The variables LW and BCS did not differ (p > 0.05) between the experimental groups. Nevertheless, OR (1.77 vs. 0.87 ± 0.20 units), TOA (4.11 vs. 1.87 ± 0.47 units) and LH-PULSE (5.0 vs. 2.2 pulses 6 h-1) favored (p < 0.05) to the GLUT group. Our results reveal that targeted glutamate supplementation, the main central nervous system neurotransmitter, arose as an interesting strategy to enhance the hypothalamic–hypophyseal–ovarian response considering the anestrous-yearling goat as an animal model, with thought-provoking while promising translational applications. Full article

The identification of actual photovoltaic (PV) model parameters under real operating condition is a crucial step for PV engineering. An accurate and trusted model depends mainly on the accuracy of the model parameters. In this paper, an accurate and enhanced methodology is intended for PV module parameters extraction in outdoor conditions. The proposed methodology combines numerical methods and analytical formulations of the one diode model to derive the five unknown parameters in any operating condition of irradiance and temperature. First, the measured I-V curves at a random weather condition are translated to standard test conditions (i.e., G = 1000 W/m², T = 25 °C), using translation equations. The second step consists of using an optimization algorithm namely the moth flame algorithm (MFO) to find out the five parameters at standard test conditions. Analytical formulations, at a random irradiance and temperature, are then used to express the unknown parameters at any irradiance and temperature. The proposed approach is validated under outdoor conditions against measured I-V curves at different irradiances and temperatures. The validation has also been performed under dynamic operation where the measured maximum power point coordinates (MPP) are compared to the predicted maximum power points. The obtained results from the adopted hybrid methodology confirm the accuracy of the parameter extraction procedure. Full article

Early detection of colorectal cancer (CRC) is the most important factor in deciding its prognosis, so the need to develop an accurate screening test is a must. P-element induced wimpy testis (PIWI) RNA-823 (piR-823) is one of the first piRNAs recognized to be linked to malignancy. We aimed to investigate the expression levels of piR-823 in both serum and tissues of colorectal cancer patients and the ability to use its serum level as a non-invasive diagnostic biomarker to detect colorectal cancer. We determined piR-823 expression levels in 84 serum samples of CRC patients, 75 serum samples of healthy controls, and biological specimens obtained from the 84 patients with colorectal cancer from both the tumor tissues and the normal neighboring tissues using quantitative real-time reverse transcriptase-PCR. We showed that piR-823 had significantly higher serum and tissue expression levels in CRC patients compared to the controls. We observed a significant positive correlation between piR-823 serum levels and the staging of CRC, with significantly higher levels exhibiting advanced stages of CRC (III and IV). This translates into poorer differentiation and lymph node metastasis. The receiver operating characteristic curve (ROC curve) test showed 83.3% sensitivity and 89.3% specificity at a cut-off value of >5.98-fold change, with an area under the curve of 0.933 (p < 0.0001) concerning the ability of piR-823 in diagnosing patients with colorectal carcinoma. piR-823 expression is upregulated in colorectal cancer patients’ serum and tissues, and it can be used as a diagnostic noninvasive biomarker for CRC. Full article

This work presents an adjustable large-scale solar simulator based on metal halide lamps. The design procedure is described with regards to the construction and spatial arrangement of the lamps and the designed optical system. Rotation and translation of the lamp array allow setting the direction and the intensity of the luminous flux on the horizontal plane. To validate the built model, irradiance nonuniformity and temporal instability tests were carried out assigning Class A, B, or C for each test, according to the International Electrotechnical Commission (IEC) standards requirements. The simulator meets the Class C standards on a 200 × 90 cm test plane, Class B on 170 × 80 cm, and Class A on 80 × 40 cm. The temporal instability returns Class A results for all the measured points. Lastly, a PV panel is characterized by tracing the I–V curve under simulated radiation, under outdoor natural sunlight, and with a numerical method. The results show a good approximation. Full article

Silica nanosprings (NS) were coated with gallium nitride (GaN) by high-temperature atomic layer deposition. The deposition temperature was 800 °C using trimethylgallium (TMG) as the Ga source and ammonia (NH₃) as the reactive nitrogen source. The growth of GaN on silica nanosprings was compared with deposition of GaN thin films to elucidate the growth properties. The effects of buffer layers of aluminum nitride (AlN) and aluminum oxide (Al₂O₃) on the stoichiometry, chemical bonding, and morphology of GaN thin films were determined with X-ray photoelectron spectroscopy (XPS), high-resolution x-ray diffraction (HRXRD), and atomic force microscopy (AFM). Scanning and transmission electron microscopy of coated silica nanosprings were compared with corresponding data for the GaN thin films. As grown, GaN on NS is conformal and amorphous. Upon introducing buffer layers of Al₂O₃ or AlN or combinations thereof, GaN is nanocrystalline with an average crystallite size of 11.5 ± 0.5 nm. The electrical properties of the GaN coated NS depends on whether or not a buffer layer is present and the choice of the buffer layer. In addition, the IV curves of GaN coated NS and the thin films (TF) with corresponding buffer layers, or lack thereof, show similar characteristic features, which supports the conclusion that atomic layer deposition (ALD) of GaN thin films with and without buffer layers translates to 1D nanostructures. Full article

Overexpression of monocarboxylate transporters (MCTs) has been shown for a variety of human cancers (e.g., colon, brain, breast, and kidney) and inhibition resulted in intracellular lactate accumulation, acidosis, and cell death. Thus, MCTs are promising targets to investigate tumor cancer metabolism with positron emission tomography (PET). Here, the organ doses (ODs) and the effective dose (ED) of the first ¹⁸F-labeled MCT1/MCT4 inhibitor were estimated in juvenile pigs. Whole-body dosimetry was performed in three piglets (age: ~6 weeks, weight: ~13–15 kg). The animals were anesthetized and subjected to sequential hybrid Positron Emission Tomography and Computed Tomography (PET/CT) up to 5 h after an intravenous (iv) injection of 156 ± 54 MBq [¹⁸F]FACH. All relevant organs were defined by volumes of interest. Exponential curves were fitted to the time–activity data. Time and mass scales were adapted to the human order of magnitude and the ODs calculated using the ICRP 89 adult male phantom with OLINDA 2.1. The ED was calculated using tissue weighting factors as published in Publication 103 of the International Commission of Radiation Protection (ICRP103). The highest organ dose was received by the urinary bladder (62.6 ± 28.9 µSv/MBq), followed by the gall bladder (50.4 ± 37.5 µSv/MBq) and the pancreas (30.5 ± 27.3 µSv/MBq). The highest contribution to the ED was by the urinary bladder (2.5 ± 1.1 µSv/MBq), followed by the red marrow (1.7 ± 0.3 µSv/MBq) and the stomach (1.3 ± 0.4 µSv/MBq). According to this preclinical analysis, the ED to humans is 12.4 µSv/MBq when applying the ICRP103 tissue weighting factors. Taking into account that preclinical dosimetry underestimates the dose to humans by up to 40%, the conversion factor applied for estimation of the ED to humans would rise to 20.6 µSv/MBq. In this case, the ED to humans upon an iv application of ~300 MBq [¹⁸F]FACH would be about 6.2 mSv. This risk assessment encourages the translation of [¹⁸F]FACH into clinical study phases and the further investigation of its potential as a clinical tool for cancer imaging with PET. Full article

Tumors lack a well-regulated vascular supply of O₂ and often fail to balance O₂ supply and demand. Net O₂ tension within many tumors may not only depend on O₂ delivery but also depend strongly on O₂ demand. Thus, tumor O₂ consumption rates may influence tumor hypoxia up to true anoxia. Recent reports have shown that many human tumors in vivo depend primarily on oxidative phosphorylation (OxPhos), not glycolysis, for energy generation, providing a driver for consumptive hypoxia and an exploitable vulnerability. In this regard, IACS-010759 is a novel high affinity inhibitor of OxPhos targeting mitochondrial complex-I that has recently completed a Phase-I clinical trial in leukemia. However, in solid tumors, the effective translation of OxPhos inhibitors requires methods to monitor pharmacodynamics in vivo. Herein, ¹⁸F-fluoroazomycin arabinoside ([¹⁸F]FAZA), a 2-nitroimidazole-based hypoxia PET imaging agent, was combined with a rigorous test-retest imaging method for non-invasive quantification of the reversal of consumptive hypoxia in vivo as a mechanism-specific pharmacodynamic (PD) biomarker of target engagement for IACS-010759. Neither cell death nor loss of perfusion could account for the IACS-010759-induced decrease in [¹⁸F]FAZA retention. Notably, in an OxPhos-reliant melanoma tumor, a titration curve using [¹⁸F]FAZA PET retention in vivo yielded an IC₅₀ for IACS-010759 (1.4 mg/kg) equivalent to analysis ex vivo. Pilot [¹⁸F]FAZA PET scans of a patient with grade IV glioblastoma yielded highly reproducible, high-contrast images of hypoxia in vivo as validated by CA-IX and GLUT-1 IHC ex vivo. Thus, [¹⁸F]FAZA PET imaging provided direct evidence for the presence of consumptive hypoxia in vivo, the capacity for targeted reversal of consumptive hypoxia through the inhibition of OxPhos, and a highly-coupled mechanism-specific PD biomarker ready for translation. Full article

In eukaryotes, cellular functions are tightly controlled by diverse post-translational modifications (PTMs) of proteins. One such PTM affecting many proteins is the deimination of arginine to citrulline. This process, called citrullination is catalyzed by a group of hydrolases called protein arginine deiminases (PADs), of which five isoforms have been identified. Hypercitrullination, as a result of increased PAD expression or activity, is associated with autoimmune diseases e.g., rheumatoid arthritis, lupus, Alzheimer’s disease, ulcerative colitis, multiple sclerosis, and certain cancers. Three common single nucleotide polymorphisms (SNPs) in the PADI4 gene have been described, namely rs874881, rs11203366, and rs11203367, which are thought to affect PAD4 expression and activity. We here compared the suitability of four methods for the screening of SNPs in the PADI4 gene: (i) SYBR-green based real-time polymerase chain reaction followed by high resolution melting curve analysis (HRM-PCR); (ii) PCR followed by detection of restriction fragment length polymorphisms (PCR-RFLP); (iii) conventional tetra-primer amplification refractory mutation system PCR (ARMS-PCR); and (iv) real-time PCR based on the one-step ARMS-PCR. Of these, ARMS-PCR proved to be the most suitable method regarding handling, duration, and cost of experiments. Using the method with SYBR-green based real-time PCR reagents further diminished handling steps and thus potential sources of error. Full article