Study of validity of the single-diode model for solar cells by I–V curves parameters extraction using a simple numerical method

The I–V measurement of solar cells is one of the most employed electrical characterization techniques in the photovoltaics research field due to the valuable information one can obtain from such a curve. Parameters like Voc, Isc and the maximum power can be easily observed at a glance. Furthermore, additional information can be extracted by a more exhaustive analysis involving the equivalent electrical circuit of a solar cell which is based on ideal electrical components with a well-defined behavior. This equivalent circuit is typically assumed to be formed by a current source in parallel with a single diode and a shunt resistor, connected to a series resistor. However, this model does not take into account the separate contributions of the different carrier transport mechanisms in solar cells; for example, carrier diffusion and recombination-generation in the depletion region. Therefore, the single diode model may not be suitable in many practical cases. In this work, a simple numerical method was developed to extract the parameters for both single diode and double diode models from experimental I–V curves of solar cells. The developed numerical algorithm was applied to extract the parameters for a published benchmark solar cell which has been used for testing this kind of algorithms. The extracted parameters using our simple method are comparable with other more sophisticated and computer power demanding algorithms. Thereafter, we applied the developed algorithm to extract the single-diode parameters from simulated “experimental” I–V curves, where two carrier transport mechanisms are present, trying to understand under what conditions the single diode approximation would provide meaningful parameters for such experimental curves. It is shown that the extracted parameters can vary strongly, particularly for the dark saturation current and ideality factor, without much variation of the root mean square error between the experimental data and the model, causing these values to be unreliable and its physical interpretation misleading. We show that the same algorithm can be applied to a double diode (two exponentials) model providing physically meaningful parameters without much computing power requirements. In summary, there is no further justification for using a single diode model to interpret the experimental I–V curves of real solar cells.     

Brain Proteome and Behavioural Analysis in Wild Type,BDNF+/− and BDNF−/− Adult Zebrafish (Danio rerio) Exposed to Two Different Temperatures

Experimental evidence suggests that environmental stress conditions can alter the expression of BDNF and that the expression of this neurotrophin influences behavioural responses in mammalian models. It has been recently demonstrated that exposure to 34 °C for 21 days alters the brain proteome and behaviour in zebrafish. The aim of this work was to investigate the role of BDNF in the nervous system of adult zebrafish under control and heat treatment conditions. For this purpose, zebrafish from three different genotypes (wild type, heterozygous BDNF^+/− and knock out BDNF^−/−) were kept for 21 days at 26 °C or 34 °C and then euthanized for brain molecular analyses or subjected to behavioural tests (Y-maze test, novel tank test, light and dark test, social preference test, mirror biting test) for assessing behavioural aspects such as boldness, anxiety, social preference, aggressive behaviour, interest for the novel environment and exploration. qRT-PCR analysis showed the reduction of gene expression of BDNF and its receptors after heat treatment in wild type zebrafish. Moreover, proteomic analysis and behavioural tests showed genotype- and temperature-dependent effects on brain proteome and behavioural responding. Overall, the absent expression of BDNF in KO alters (1) the brain proteome by reducing the expression of proteins involved in synapse functioning and neurotransmitter-mediated transduction; (2) the behaviour, which can be interpreted as bolder and less anxious and (3) the cellular and behavioural response to thermal treatment.     

An adaptive interface‐enriched generalized FEM for the treatment of problems with curved interfaces

An adaptive refinement scheme is presented to reduce the geometry discretization error and provide higher‐order enrichment functions for the interface‐enriched generalized FEM. The proposed method relies on the h‐adaptive and p‐adaptive refinement techniques to reduce the discrepancy between the exact and discretized geometries of curved material interfaces. A thorough discussion is provided on identifying the appropriate level of the refinement for curved interfaces based on the size of the elements of the background mesh. Varied techniques are then studied for selecting the quasi‐optimal location of interface nodes to obtain a more accurate approximation of the interface geometry. We also discuss different approaches for creating the integration sub‐elements and evaluating the corresponding enrichment functions together with their impact on the performance and computational cost of higher‐order enrichments. Several examples are presented to demonstrate the application of the adaptive interface‐enriched generalized FEM for modeling thermo‐mechanical problems with intricate geometries. The accuracy and convergence rate of the method are also studied in these example problems. Copyright © 2015 John Wiley & Sons, Ltd.     

Synthesis of Four Steroidal Carbamates with Antitumor Activity against Mouse Colon Carcinoma CT26WT Cells: In Vitro and In Silico Evidence

Colorectal cancer (CRC) is one of the most lethal cancers worldwide. If detected on time, surgery can expand life expectations of patients up to five more years. However, if metastasis has grown deliberately, the use of chemotherapy can play a crucial role in CRC control. Moreover, the lack of selectivity of current anticancer drugs, plus mutations that occur in cancerous cells, demands the development of new chemotherapeutic agents. Several steroids have shown their potentiality as anticancer agents, while some other compounds, such as Taxol and its derivatives bearing a carbamate functionality, have reached the market. In this article, the synthesis, characterization, and antiproliferative activity of four steroidal carbamates on mouse colon carcinoma CT26WT cells are described. Carbamate synthesis occurred via direct reaction between diosgenin, its B-ring modified derivative, and testosterone with phenyl isocyanate under a Brønsted acid catalysis. All obtained compounds were characterized by ¹H and ¹³C Nuclear Magnetic Resonance (NMR), High Resolution Mass Spectroscopy (HRMS); their melting points are also reported. Results obtained from antiproliferative activity assays indicated that carbamates compounds have inhibitory effects on the growth of this colon cancer cell line. A molecular docking study carried out on Human Prostaglandin E Receptor (EP4) showed a high affinity between carbamates and protein, thus providing a valuable theoretical explanation of the in vitro results.     

Topological map-based approach for localization and mapping memory optimization

Robotics in agriculture faces several challenges, such as the unstructured characteristics of the environments, variability of luminosity conditions for perception systems, and vast field extensions. To implement autonomous navigation systems in these conditions, robots should be able to operate during large periods and travel long trajectories. For this reason, it is essential that simultaneous localization and mapping algorithms can perform in large-scale and long-term operating conditions. One of the main challenges for these methods is maintaining low memory resources while mapping extensive environments. This work tackles this issue, proposing a localization and mapping approach called VineSLAM that uses a topological mapping architecture to manage the memory resources required by the algorithm. This topological map is a graph-based structure where each node is agnostic to the type of data stored, enabling the creation of a multilayer mapping procedure. Also, a localization algorithm is implemented, which interacts with the topological map to perform access and search operations. Results show that our approach is aligned with the state-of-the-art regarding localization precision, being able to compute the robot pose in long and challenging trajectories in agriculture. In addition, we prove that the topological approach innovates the state-of-the-art memory management. The proposed algorithm requires less memory than the other benchmarked algorithms, and can maintain a constant memory allocation during the entire operation. This consists of a significant innovation, since our approach opens the possibility for the deployment of complex 3D SLAM algorithms in real-world applications without scale restrictions.     

Hydrophobization of hair to improve the interfacial adhesion between hair and high-density polyethylene

Concerned about environmental pollution, and aware of the comfort that polyethylene provides for daily human life, this work sought to replace a percentage of high-density polyethylene (HDPE) with human or bovine hair. Hair is natural, abundant, light weight, non-toxic, and disposed of as garbage. The main disadvantage of natural composites is the interfacial adhesion. To increase the interfacial adhesion between hair and HDPE, stearic acid or oleic acid was chemically anchored on the hair surface, which leads to an improved contact angle hysteresis and hydrophobicity. Dynamic-mechanical properties of the composites were investigated focusing on the type of carboxylic acid used (stearic or oleic acid), hair length, hair type (human or bovine) and amount of hair used in the composite. Taking 40°C as a reference, using 15% of hair with a length of 1 ± 0.15 mm, the highest storage modulus value was obtained with HDPE with human hair modified with oleic acid, exceeding the value of the storage modulus of HDPE by 67.64%. Increasing storage modulus on composites indicates of interfacial interaction and chemical affinity improvement between hair and polyethylene.     

A self-training automatic infant-cry detector

Neural Computing and Applications - Infant cry is one of the first distinctive and informative life signals observed after birth. Neonatologists and automatic assistive systems can analyse infant...