Search

Abstract The escalating global population and energy demands underscore the critical role of renewable energy sources, particularly solar power, in mitigating environmental degradation caused by traditional fossil fuels. This paper emphasizes the advantages of solar energy, especially photovoltaic (PV) systems, which have become pivotal in hybrid energy systems. However, accurate modelling and identification of PV cell parameters pose challenges, prompting the adoption of meta‐heuristic optimization algorithms. This work explores the limitations of existing algorithms and introduces a novel approach, the bio‐dynamics grasshopper optimization algorithm (BDGOA). The BDGOA addresses deficiencies in both exploration and exploitation phases, exhibiting exceptional convergence speed and efficiency. The algorithm's simplicity, achieved through the implementation of an elimination phase and controlled search space, enhances its performance without intricate calculations. The study evaluates the BDGOA by applying it to identify unknown parameters of five solar modules. The algorithm's effectiveness is demonstrated through the extraction of parameters for RTC France, PWP201, SM55, KC200GT, and SW255 models, validated against experimental data under diverse conditions. The paper concludes with insights into the impact of radiation and temperature on module parameters. The subsequent sections of the paper delve into the intricacies of the PV cell and module model, articulate the formulation of the proposed algorithm, present simulations, and analyse the obtained results. The BDGOA emerges as a promising solution, overcoming the limitations of existing algorithms and contributing significantly to the advancement of accurate and efficient PV cell parameter identification, thereby propelling progress towards a sustainable energy future.

Abstract Understanding tree transpiration variability is vital for assessing ecosystem water‐use efficiency and forest health amid climate change, yet most landscape‐level measurements do not differentiate individual trees. Using canopy temperature data from thermal cameras, we estimated the transpiration rates of individual trees at Harvard Forest and Niwot Ridge. PT‐JPL model was used to derive latent heat flux from thermal images at the canopy‐level, showing strong agreement with tower measurements (R2 = 0.70–0.96 at Niwot, 0.59–0.78 at Harvard at half‐hourly to monthly scales) and daily RMSE of 33.5 W/m2 (Niwot) and 52.8 W/m2 (Harvard). Tree‐level analysis revealed species‐specific responses to drought, with lodgepole pine exhibiting greater tolerance than Engelmann spruce at Niwot and red oak showing heightened resistance than red maple at Harvard. These findings show how ecophysiological differences between species result in varying responses to drought and demonstrate that these responses can be characterized by deriving transpiration from crown temperature measurements.

Abstract Early‐stage estrogen receptor positive and human epidermal growth factor receptor negative (ER+/HER2−) luminal breast cancer (BC) is quite heterogeneous and accounts for about 70% of all BCs. Ki67 is a proliferation marker that has a significant prognostic value in luminal BC despite the challenges in its assessment. There is increasing evidence that spatial colocalization, which measures the evenness of different types of cells, is clinically important in several types of cancer. However, reproducible quantification of intra‐tumor spatial heterogeneity remains largely unexplored. We propose an automated pipeline for prognostication of luminal BC based on the analysis of spatial distribution of Ki67 expression in tumor cells using a large well‐characterized cohort (n = 2,081). The proposed Ki67 colocalization (Ki67CL) score can stratify ER+/HER2− BC patients with high significance in terms of BC‐specific survival (p

Abstract Recent advances in whole‐slide imaging (WSI) technology have led to the development of a myriad of computer vision and artificial intelligence‐based diagnostic, prognostic, and predictive algorithms. Computational Pathology (CPath) offers an integrated solution to utilise information embedded in pathology WSIs beyond what can be obtained through visual assessment. For automated analysis of WSIs and validation of machine learning (ML) models, annotations at the slide, tissue, and cellular levels are required. The annotation of important visual constructs in pathology images is an important component of CPath projects. Improper annotations can result in algorithms that are hard to interpret and can potentially produce inaccurate and inconsistent results. Despite the crucial role of annotations in CPath projects, there are no well‐defined guidelines or best practices on how annotations should be carried out. In this paper, we address this shortcoming by presenting the experience and best practices acquired during the execution of a large‐scale annotation exercise involving a multidisciplinary team of pathologists, ML experts, and researchers as part of the Pathology image data Lake for Analytics, Knowledge and Education (PathLAKE) consortium. We present a real‐world case study along with examples of different types of annotations, diagnostic algorithm, annotation data dictionary, and annotation constructs. The analyses reported in this work highlight best practice recommendations that can be used as annotation guidelines over the lifecycle of a CPath project.

Abstract This study focuses on a zero voltage transition multi‐input quasi‐Z‐source converter (qZSC). This topology can be used for input sources with different voltages and currents to provide a constant output voltage. In the proposed structure, several qZSCs are combined and the output filter of all stages is eliminated. Therefore, the overall number of circuit elements, cost, volume and weight are reduced in comparison with when they are in a separate operation. In this converter, the soft‐switching conditions are provided for all stages by using only one auxiliary circuit. The employed technique provides zero‐voltage zero‐current switching (ZVZCS) and zero‐voltage switching for main switches at turn‐on and turn‐off instants, respectively. The auxiliary switch turns on under zero‐current switching and turns off under ZVZCS. Furthermore, the reverse recovery losses of diodes are reduced. The theoretical foundation of the proposed converter is presented and its performance is simulated by OrCAD software. The obtained results show 3.5% improvement in the efficiency at nominal loads, compared to its hard‐switching counterpart. A dual‐input prototype of the proposed structure is successfully built to support the validity of the theoretical analysis.

This paper proposes a new anisotropic diffusion model in image restoration that is understood from a variational optimization of an energy functional. Initially, a family of new diffusion functions based on cubic Hermite spline is provided for optimal image denoising. After that, the existence and uniqueness of weak solutions for the corresponding Euler–Lagrange equation are proven in an appropriate functional space, and a consistent and stable numerical model is also shown. We complement this work by illustrating some experiments on different actual brain Magnetic Resonance Imaging (MRI) scans, showing the proposed model’s impressive results.

Background. Hydroxychloroquine with or without azithromycin was one of the common therapies at the beginning of the COVID-19 pandemic. They can prolong QT interval, cause torsade de pointes, and lead to sudden cardiac death. We aimed to assess QT interval prolongation and its risk factors in patients who received hydroxychloroquine with or without azithromycin. Methods. This study was a retrospective cohort study. One hundred seventy-two confirmed COVID-19 patients were included in this study, hospitalized at Babol University of Medical Sciences hospitals between March 5, 2020, and April 3, 2020. Patients were divided into two groups: hydroxychloroquine alone and hydroxychloroquine with azithromycin. Electrocardiograms were used for outcome assessment. Results. 83.1% of patients received hydroxychloroquine plus azithromycin vs. 16.9% of patients who received only hydroxychloroquine. The mean age of patients was 59.2±15.4.The mean of posttreatment QTc interval in the monotherapy group was shorter than the mean of posttreatment QTc interval in the combination therapy group, but it had no significant statistical difference (462.5±43.1 milliseconds vs. 464.3±59.1 milliseconds; p=0.488). Generally, 22.1% of patients had a prolonged QTc interval after treatment. Male gender, or baseline QTc≥450 milliseconds, or high-risk Tisdale score increased the likelihood of prolonged QTc interval. Due to QTc prolongation, fourteen patients did not continue therapy after four days. Conclusions. Hospitalized patients treated by hydroxychloroquine with or without azithromycin had no significant difference in prolongation of QT interval and outcome. The numbers of patients with prolonged QT intervals in this study emphasize careful cardiac monitoring during therapy, especially in high-risk patients.

In many references, both the ill-posed and inverse boundary value problems are solved iteratively. The iterative procedures are based on firstly converting the problem into a well-posed one by assuming the missing boundary values. Then, the problem is solved by using either a developed numerical algorithm or a conventional optimization scheme. The convergence of the technique is achieved when the approximated solution is well compared to the unused data. In the present paper, we present a different way to solve an ill-posed problem by applying the localized and space-time localized radial basis function collocation method depending on the problem considered and avoiding the iterative procedure. We demonstrate that the solution of certain ill-posed and inverse problems can be accomplished without iterations. Three different problems have been investigated: problems with missing boundary condition and internal data, problems with overspecified boundary condition, and backward heat conduction problem (BHCP). It has been demonstrated that the presented method is efficient and accurate and overcomes the stability analysis that is required in iterative techniques.

Polyamides (PAs) are one of the most important engineering polymers; however, the difficulty in dissolving them hinders their applications. Formic acid (FA) is the most common solvent for PAs, but it has industrial limitations. In this contribution, we proposed a new solvent system for PAs by replacing a portion of the FA with urea and calcium chloride (FAUCa). Urea imparts the hydrogen bonding and calcium ion from the calcium chloride, as a Lewis acid was added to the system to compensate for the pH decrease due to the addition of urea. The results showed that the proposed solvent (FAUCa) could readily dissolve PAs, resulting in a less decrease in the mechanical properties during the dissolution. The composite prepared using the FAUCa has almost the same properties as the one prepared using the FA solution. The solution was applied on a polyamide 66 fabric to make an all-polyamide composite-coated fabric, which then was characterized. The FAUCa solution had a higher viscosity than the one prepared using the neat FA solvent, which can be an advantage in the applications which need higher viscosity like preparing the all-polyamide composite-coated fabric. A more viscous solution makes a denser coating which will increase the water /gas tightness. In conclusion, using the FAUCa solvent has two merits: (1) replacement of 40% of the FA with less harmful and environmentally friendly chemicals and (2) enabling for the preparation of more viscous solutions, which makes a denser coating.

A 40-year-old man presented with atypical chest pain and fatigue from 15 days ago a suspicious mass in the right ventricle based on a bed side transthoracic echocardiography. Preoperative diagnosis of a cardiac hemangioma comes to mind in a minority of cases. In our case, a cardiac tumor was diagnosed and the vascular nature of the tumor was suggested by vascular blush on the coronary angiography. In addition, right ventriculotomy was the approach of choice in our case because of its inaccessibility and its particular location.

Integration of electronic health records (EHRs) in the national health care systems of low- and middle-income countries (LMICs) is vital for achieving the United Nations Sustainable Development Goal of ensuring healthy lives and promoting well-being for all people of all ages. National EHR systems are increasing, but mostly in developed countries. Besides, there is limited research evidence on successful strategies for ensuring integration of national EHRs in the health care systems of LMICs. To fill this evidence gap, a comprehensive survey of literature was conducted using scientific electronic databases-PubMed, SCOPUS, Web of Science, and Global Health-and consultations with international experts. The review highlights the lack of evidence on strategies for integrating EHR systems, although there was ample evidence on implementation challenges and relevance of EHRs to vertical disease programs such as HIV. The findings describe the narrow focus of EHR implementation, the prominence of vertical disease programs in EHR adoption, testing of theoretical and conceptual models for EHR implementation and success, and strategies for EHR implementation. The review findings are further amplified through examples of EHR implementation in Sierra Leone, Malawi, and India. Unless evidence-based strategies are identified and applied, integration of national EHRs in the health care systems of LMICs is difficult., (© 2019 John Wiley & Sons, Ltd.)