Developed Model Research Articles

Intelligent diagnostic model for pterygium by combining attention mechanism and MobileNetV2

AIM: To evaluate the application of an intelligent diagnostic model for pterygium. METHODS: For intelligent diagnosis of pterygium, the attention mechanisms—SENet, ECANet, CBAM, and Self-Attention—were fused with the lightweight MobileNetV2 model structure to construct a tri-classification model. The study used 1220 images of three types of anterior ocular segments of the pterygium provided by the Eye Hospital of Nanjing Medical University. Conventional classification models—VGG16, ResNet50, MobileNetV2, and EfficientNetB7—were trained on the same dataset for comparison. To evaluate model performance in terms of accuracy, Kappa value, test time, sensitivity, specificity, the area under curve (AUC), and visual heat map, 470 test images of the anterior segment of the pterygium were used. RESULTS: The accuracy of the MobileNetV2+Self-Attention model with 281 MB in model size was 92.77%, and the Kappa value of the model was 88.92%. The testing time using the model was 9ms/image in the server and 138ms/image in the local computer. The sensitivity, specificity, and AUC for the diagnosis of pterygium using normal anterior segment images were 99.47%, 100%, and 100%, respectively; using anterior segment images in the observation period were 88.30%, 95.32%, and 96.70%, respectively; and using the anterior segment images in the surgery period were 88.18%, 94.44%, and 97.30%, respectively. CONCLUSION: The developed model is lightweight and can be used not only for detection but also for assessing the severity of pterygium.

PBPK Modeling of Entrectinib and Its Active Metabolite to Derive Dose Adjustments in Pediatric Populations Co-Administered with CYP3A4 Inhibitors.

Physiologically based pharmacokinetic (PBPK) models of entrectinib and its equipotent metabolite, M5, were established in healthy adult subjects and extrapolated to pediatric patients to predict increases in steady-state systemic exposure on co-administration of strong and moderate CYP3A4 inhibitors (itraconazole at 5 mg/kg, erythromycin at 7.5-12.5 mg/kg and fluconazole at 3-12 mg/kg, respectively). Adult model establishment involved the optimization of fraction metabolized by CYP3A4 (0.92 for entrectinib and 0.98 for M5) using data from an itraconazole DDI study. This model captured well the exposure changes of entrectinib and M5 seen in adults co-administered with the strong CYP3A4 inducer rifampicin. In pediatrics, reasonable prediction of entrectinib and M5 pharmacokinetics in ≧2 year olds was achieved when using the default models for physiological development and enzyme ontogenies. However, a two to threefold misprediction of entrectinib and M5 exposures was seen in <2 year olds which may be due to missing mechanistic understanding of gut physiology and/or protein binding in very young children. Model predictions for ≧2 year olds showed that entrectinib AUC(0-t) was increased by approximately sevenfold and five to threefold by strong and high-moderate and low-moderate CYP3A4 inhibitors, respectively. Based on these victim DDI predictions, dose adjustments for entrectinib when given concomitantly with strong and moderate CYP3A4 inhibitors in pediatric subjects were recommended. These simulations informed the approved entrectinib label without the need for additional clinical pharmacology studies.

Conformational Dynamics and Molecular Characterization of Alsin MORN Monomer and Dimeric Assemblies.

Despite the ubiquity of membrane occupation recognition nexus (MORN) motifs across diverse species in both eukaryotic and prokaryotic organisms, these protein domains remain poorly characterized. Their significance is underscored in the context of the Alsin protein, implicated in the debilitating condition known as infantile-onset ascending hereditary spastic paralysis (IAHSP). Recent investigations have proposed that mutations within the Alsin MORN domain disrupt proper protein assembly, precluding the formation of the requisite tetrameric configuration essential for the protein's inherent biological activity. However, a comprehensive understanding of the relationship between the biological functions of Alsin and its three-dimensional molecular structure is hindered by the lack of available experimental structures. In this study, we employed and compared several protein structure prediction algorithms to identify a three-dimensional structure for the putative MORN of Alsin. Furthermore, inspired by experimental pieces of evidence from previous studies, we employed the developed models to predict and investigate two homo-dimeric assemblies, characterizing their stability. This study's insights into the three-dimensional structure of the Alsin MORN domain and the stability dynamics of its homo-dimeric assemblies suggest an antiparallel linear configuration stabilized by a noncovalent interaction network.

Microfluidic system for generating a three-dimensional (3D) vascularized islet-on-a-chip model

Diabetes is a disease associated with the insufficiency of pancreatic endocrine part, consisting mainly of pancreatic islets. Currently, diabetes is considered the fastest growing civilization disease. Globally, over 440 million people suffer from diabetes, and it is estimated that this number will increase to 700 million by 2045. Pancreatic islets are complex, highly vascularized mini-organs, and only the development of a fully functional vascularized pancreatic islet model could lead to the progress of knowledge about diabetes evolution, new therapeutic strategies, and the islet generation for applications in regenerative medicine. Therefore, the main goal of our study was to develop a microfluidic system for the simultaneous culture of two three-dimensional (3D) research models. The device presented in this article was used to simultaneously culture a model of a blood vessel composed of endothelial cells (HUVEC) developed using the Viscous Finger Patterning (VFP) technique and a model of the pancreatic islet, which was developed using a co-culture of α and β cells. During the research, device production method was optimized, and for this purpose, the most precise micro-milling technique was compared with the rapid prototyping technique - 3D printing. The spatial arrangement of cells in the developed models, their morphology, and viability were visualized using fluorescence staining and confocal microscopy analysis. This article presents preliminary research to develop a long-term culture of a complex model imitating the connection between the microvessel and the pancreatic islet, which in the future will be used to develop new therapeutic strategies or generate fully functional islets.

Symbolic recording of signalling and cis-regulatory element activity to DNA.

Measurements of gene expression or signal transduction activity are conventionally performed using methods that require either the destruction or live imaging of a biological sample within the timeframe of interest. Here we demonstrate an alternative paradigm in which such biological activities are stably recorded to the genome. Enhancer-driven genomic recording of transcriptional activity in multiplex (ENGRAM) is based on the signal-dependent production of prime editing guide RNAs that mediate the insertion of signal-specific barcodes (symbols) into a genomically encoded recording unit. We show how this strategy can be used for multiplex recording of the cell-type-specific activities of dozens to hundreds of cis-regulatory elements with high fidelity, sensitivity and reproducibility. Leveraging signal transduction pathway-responsive cis-regulatory elements, we also demonstrate time- and concentration-dependent genomic recording of WNT, NF-κB and Tet-On activities. By coupling ENGRAM to sequential genome editing via DNA Typewriter1, we stably record information about the temporal dynamics of two orthogonal signalling pathways to genomic DNA. Finally we apply ENGRAM to integratively record the transient activity of nearly 100 transcription factor consensus motifs across daily windows spanning the differentiation of mouse embryonic stem cells into gastruloids, an in vitro model of early mammalian development. Although these are proof-of-concept experiments and much work remains to fully realize the possibilities, the symbolic recording of biological signals or states within cells, to the genome and over time, has broad potential to complement contemporary paradigms for how we make measurements in biological systems.

The development and utilization of shale oil and gas resources in China and economic analysis of energy security under the background of global energy crisis

AbstractThe key scientific problem to be solved in this paper is the optimal development and utilization model and the economic evaluation model of China's land-phase shale oil and gas resources, and the purpose of the research is to promote the large-scale commercial development and utilization of China's shale oil and gas resources, and to safeguard China's oil and gas energy security and the sustainable development of the economy. The article proposes to adopt the small surface element volume method (oil content rate method) to evaluate the pure shale oil resources, adopt the Cobb–Douglas production function model as the optimization model to measure the boundary production capacity of shale oil and gas, construct the optimal development and utilization model for shale oil and gas resources considering the five first-level safeguard indexes, namely, science and technology (A), capital (K), talents (L), reserves (S) and ecological environment (E), and establish the basic constraint model for the optimal development and utilization of shale oil and gas resources. The basic constraint model, as well as the evaluation model of economic coefficients for the development and utilization of shale oil and gas resources were established. The pure shale oil resources are mainly calculated based on the movable oil content of shale. In the paper, the S1 of normal pyrolysis (300 °C) is regarded as movable oil, and the sum of S1 and evaporated hydrocarbon (light hydrocarbon) loss is the movable oil content of shale. The integrated geological-physical exploration-engineering comprehensive evaluation of China’s land-phase shale oil-rich and high-yielding “sweet spot” is an important prerequisite for the realization of shale oil and gas resources to build production scale and effective development, and the least-squares method is used to estimate the average production function, the distance to the maximum value of the residuals, and the boundary capacity production function. The average production function and residual maximum distance are estimated by the least squares method, and the production function of the boundary capacity is derived, and the quotient of the boundary capacity and the actual capacity is calculated to get the capacity utilization rate, which can be used to analyze the potential of future shale oil and gas growth. The development of shale oil and gas resources in a target block requires comprehensive consideration of the first-level guarantee indicators such as science and technology (A), capital (K), talents (L), reserves (S) and ecological environment (E), as well as more than 10 s-level indicators and a number of third-level indicators, in order to ensure that the oil companies maximize their profits by organizing the development and production. The economic coefficient can be expressed as the ratio of economically recoverable resources to geological reserves. The larger the economic coefficient for the development and utilization of shale oil and gas resources is, the better the economy of the area is, and the larger the proportion of shale oil and gas resources that can be exploited. There is little special literature on the optimal development and utilization model of shale oil and gas resources and energy security among many research results at home and abroad. The evaluation of pure shale oil using the small surface element volume method (oil content rate method) and the construction of the boundary capacity calculation model, the optimal development of the basic constraints model and the economic evaluation model that we have determined, although they can not yet fully cover all the links and factors related to the development and utilization of shale oil and gas resources, are not yet fully covered by our research work. However, our research work has given the model more geological and economic theoretical connotations, and provided an economic basis and technical reference for the large-scale and commercial development and utilization of shale oil and gas resources as an effective alternative to oil imports.

Prediction of adolescent idiopathic scoliosis with machine learning algorithms using brain volumetric measurements.

It is known that neuroanatomical and neurofunctional changes observed in the brain, brainstem and cerebellum play a role in the etiology of adolescent idiopathic scoliosis (AIS). This study aimed to investigate whether volumetric measurements of brain regions can be used as predictive indicators for AIS through machine learning techniques. Patients with a severe degree of curvature in AIS (n = 32) and healthy individuals (n = 31) were enrolled in the study. Volumetric data from 169 brain regions, acquired from magnetic resonance imaging (MRI) of these individuals, were utilized as predictive factors. A comprehensive analysis was conducted using the twelve most prevalent machine learning algorithms, encompassing thorough parameter adjustments and cross-validation processes. Furthermore, the findings related to variable significance are presented. Among all the algorithms evaluated, the random forest algorithm produced the most favorable results in terms of various classification metrics, including accuracy (0.9083), AUC (0.993), f1-score (0.970), and Brier score (0.1256). Additionally, the most critical variables were identified as the volumetric measurements of the right corticospinal tract, right corpus callosum body, right corpus callosum splenium, right cerebellum, and right pons, respectively. The outcomes of this study indicate that volumetric measurements of specific brain regions can serve as reliable indicators of AIS. In conclusion, the developed model and the significant variables discovered hold promise for predicting scoliosis development, particularly in high-risk individuals.

Artificial Neural Network Models for Solution Concentration Measurement during Cooling Crystallization of Ceritinib

The development of a quantitative in-line UV spectroscopic method for monitoring of solute concentration during the crystallization process of the active pharmaceutical ingredient (API), ceritinib is described. The method is based on artificial neural networks (ANN). A seeded cooling crystallization process of ceritinib from tetrahydrofuran was studied as a model system. The model was constructed from collected ATR-UV spectra and temperature records within the metastable zone. The collected spectra were preprocessed with the first derivative using the Savitzky-Golay filter. ANN models with different architectures were created and the optimal architecture was chosen based on the root mean square error of prediction (RMSEP) criterion. In addition, ANN models were compared with the models obtained by the linear partial least squares regression (PLSR). Due to the nonlinear relationship in the data set, ANN models predict the solution concentration with higher accuracy compared to linear models. The developed models were successfully used in real-time solution concentration measurement during ceritinib crystallization along with a supersaturation control module developed in-house.

Pengembangan Media Video Pembelajaran pada Mata Pelajaran Sejarah Kebudayaan Islam untuk Siswa Kelas VII MTSN

This research aims to produce learning video media for SKI Class VII MTsN subjects that are valid and practical. This type of research is development research, known as Research and Development (R&amp;D), using the 4-D development model. The development procedure in this research consists of 4 stages, namely, (1) Define, (2) Design, (3) Develop, (4) Disseminate. The product validity test was carried out by 3 validators, namely 1 material validator and 2 media validators. Product trials were carried out on class VII students at MTsN 5 Tanah Datar with the aim of finding out the practicality of the product being developed. The results of material validation by material expert validators obtained an average of 4.94 in the "very valid" category. The results of the media validator assessment with validator I obtained an average of 4.93 in the "very valid" category and the validation results with validator II obtained an average of 4.93 in the "very valid" category. This learning multimedia is said to be practical based on the results of the practicality test with an average of 4.5. Based on the results of the validity test and practicality test, it can be concluded that learning multimedia in PAI subjects for class IV elementary school is suitable for use in learning

An Investigation of Shaft Voltage in Synchronous Generators Under SAGE and Variable Load Condition

Abstract Synchronous generators are widely used in power generation systems. Static air-gap eccentricity (SAGE) often occurs in synchronous generators due to the component wear over prolonged operation. This paper presents a comprehensive mathematical model specifically tailored for SAGE fault, incorporating for the influence of stator slotting. The study thoroughly examines the impacts of both eccentricity and varying loads on the shaft voltage using the developed model. Furthermore, a novel method for detecting SAGE is introduced, leveraging the mathematical model of shaft voltage. This detection method proves effective for identifying eccentricity in synchronous generators across different load conditions by reasonably combining shaft voltage and phase current. The mathematical model of shaft voltage and the proposed detection method are validated through three-dimensional finite-element calculations and experimental studies. The work is helpful to manage and predict the shaft voltage. This paper contributes to the prevention of shaft voltage damage and real-time monitoring of the SAGE fault in synchronous generators.

Model of non-equilibrium near-cathode plasma layers for simulation of ignition of high-pressure arcs on cold refractory cathodes

The introduction of secondary ion-electron emission into an approximate model of non-equilibrium plasma layers on hot (thermionic) cathodes of high-pressure arc discharges allows extending the model to low cathode surface temperatures. Analysis of evaluation results shows that the extended model describes glow-like discharges on cold cathodes and thermionic arc discharges on hot cathodes, as it should. In the course of glow-to-arc transitions on cold cathodes, a transient regime occurs where a hot arc spot has just formed and a significant fraction of the current still flows to the cold surface outside the spot, so that the near-cathode voltage continues to be high. The power input in the near-cathode layer is very high in this regime, and so is the electron temperature in the near-cathode region. The mean free path for collisions between the atoms and the ions in these conditions exceeds the thickness of the layer where the ion current to the cathode is generated. A new method for evaluation of the ion current under such conditions is implemented. The developed model is applicable for cathode surface temperatures below the boiling point of the cathode material and may be used for multidimensional simulations of ignition of high-current arcs on refractory cathodes.

Form Uncertainty to Sustainable Decision-Making: A Novel MIDAS–AM–DeepAR-Based Prediction Model for E-Commerce Industry Development

Global efforts to build sustainable e-commerce ecosystems through various prediction tools have suffered due to uncertainty in politics, the economy, and the environment. This paper proposes a new integrative prediction model to track the sustainable development of e-commerce. Using US e-commerce data, this study explores the prediction accuracy of the mixed data sampling (MIDAS) model in combination with the attention mechanism (AM) approach, analyzing the performance differences between the model’s before and after improvements. More so, the paper evaluates the performance of the new prediction approach against other competing models using the prediction accuracy metric, the probability interval test, and the Diebold and Mariann (DM) test methods. The results indicate that the introduction of the MIDAS and the AM approaches allows the prediction model to fully utilize the effective information of the mixed-frequency data while simultaneously capturing the differences in the importance of the variables in terms of their time series and the non-linear relationship of the learning variables, thereby positively influencing the economic prediction of the e-commerce industry. Second, the proposed prediction model combines the ability of long-term and short-term high-precision prediction and performs multi-step probability prediction on the development of the e-commerce industry. It can better track abnormal changes in macroeconomic indicators and fit their fluctuation trends. Third, based on the results of the three evaluation indicators, the MIDAS–AM–Deep autoregressive recurrent neural network (DeepAR) model achieves optimal prediction accuracy, allowing it to provide more timely, accurate, and comprehensive predictions for e-commerce management decisions when macroeconomic conditions are undergoing significant transformations.

Stochastic journeys of cell progenies through compartments and the role of self-renewal, symmetric and asymmetric division

Division and differentiation events by which cell populations with specific functions are generated often take place as part of a developmental programme, which can be represented by a sequence of compartments. A compartment is the set of cells with common characteristics; sharing, for instance, a spatial location or a phenotype. Differentiation events are transitions from one compartment to the next. Cells may also die or divide. We consider three different types of division events: (i) where both daughter cells inherit the mother’s phenotype (self-renewal), (ii) where only one of the daughters changes phenotype (asymmetric division), and (iii) where both daughters change phenotype (symmetric division). The self-renewal probability in each compartment determines whether the progeny of a single cell, moving through the sequence of compartments, is finite or grows without bound. We analyse the progeny stochastic dynamics with probability generating functions. In the case of self-renewal, by following one of the daughters after any division event, we may construct lifelines containing only one cell at any time. We analyse the number of divisions along such lines, and the compartment where lines terminate with a death event. Analysis and numerical simulations are applied to a five-compartment model of the gradual differentiation of hematopoietic stem cells and to a model of thymocyte development: from pre-double positive to single positive (SP) cells with a bifurcation to either SP4 or SP8 in the last compartment of the sequence.

Improving Children’s Services Engagement of Fathers in Child Protection: Logic Model for an Organisational Development and Staff Training Intervention

AbstractThere is a long-standing and ongoing problem of practice with at-risk families in child welfare work focusing primarily on mothers and failing to properly engage fathers. The article describes a child welfare innovation from the UK designed to tackle this issue—the ISAFE (Improving Safeguarding through Audited Father-Engagement) intervention, developed by The Fatherhood Institute and The Children’s Social Care Research and Development Centre (CASCADE) at Cardiff University and based on two previous separate interventions which had positive initial evaluations. ISAFE combines in-service social work practitioner training with other elements of organisational development to improve the engagement of fathers. Activities targeting organisational culture are case file audits, identification and training of team champions, and a webinar for service leaders. The practitioner training involves both awareness raising about the importance of engaging men and skills development via an introduction to motivational interviewing. ISAFE’s theory of change is summarised in the form of a logic model. Limitations of the intervention and its evaluation are discussed.

Lithofacies, Facies Association, and Depositional Environment of 34-1, 33-6, and 33-4 Sandstone, Wida Field, Gita Member, Talang Akar Formation, Asri Basin, Offshore Southeast Sumatra

Three Gita Member reservoirs 34-1, 33-6, and 33-4 produce from solution gas drive with rapid pressure decline and low recovery factor. After successful oil production enhancements through waterflooding injections prompt the need for a reservoir model in further field development. Before such models were built reservoir characterization was carried out to determine facies and depositional environment for facies modeling. The study integrated core, wireline log, petrophysical logs, seismic attribute, petrography, etc. Next, well correlation was carried out to distribute stratigraphic markers. Finally, seismic attribute and well correlation were integrated to construct pie chart and depositional environment map. External geometry from seismic attribute revealed distributary channel with point bars which act as reservoir and consist of medium-fine grained planar tabular cross bedding sandstone, mud drapes sandstone, and ripple-wavy lamination sandstone. The wireline log showed fining-upward pattern and core displayed abundant channel rip up clasts, sharp or erosional contact with underlying lithology. Frequent mud drapes found within channel sandstone indicate tidal influence in proximity to marine environment probably in lower delta plain. Channels are trending west-east (34-1) and north-south (33-6 and 33-4). Other facies associations are shallow marine, swamp, interdistributary bay, and tidally influenced interdistributary bay. Shallow marine FA consists of skeletal limestone (Lm), calcareous mudstone, and calcareous sandstone (Sc). Rootlet mudstone (Fb) and interlamination of carbonaceous mudstone with very fine-grain sandstone (Fl) formed interdistributary bay FA. Swamp FA consists of coal and coaly mudstone. Tidally influenced interdistributary bay FA consists of carbonaceous laminated mudstone high in carbon (Flb), intensely bioturbated carbonaceous mudstone (Flb), very finely laminated mudstone-very fine grain sandstone (Fl) and black fissile shale (Fm).

Novel Inhibitor of Keap1-Nrf2 Protein–Protein Interaction Attenuates Osteoclastogenesis In Vitro and Prevents OVX-Induced Bone Loss In Vivo

Keap1 interacts with Nrf2 by assisting in its ubiquitination and subsequent proteolysis. By preventing ROS accumulation during RANKL-induced osteoclastogenesis, Nrf2 activation can prevent the differentiation of osteoclasts. Additionally, inhibiting the Keap1-Nrf2 PPI can be an effective strategy for triggering Nrf2 to regulate oxidative stress. Structure-based virtual screening was performed to discover a potentially novel Keap1-Nrf2 PPI inhibitor wherein KCB-F06 was identified. The inhibitory effects of KCB-F06 on osteoclastogenesis were investigated in vitro through TRAP staining and bone resorption assays. An ovariectomy-induced osteoporosis mouse model was applied to evaluate KCB-F06’s therapeutic effects in vivo. Lastly, the underlying mechanisms were explored using real-time PCR, Western blotting, and co-IP assays. KCB-F06 was discovered as a novel Keap1-Nrf2 PPI inhibitor. As a result, the expression of antioxidants (HO-1 and NQO1) was suppressed, hence reducing ROS accumulation during osteoclastogenesis. Subsequently, this caused the inactivation of RANKL-induced IKB/NF-kB signaling. This eventually led to the downregulation of osteoclast-specific proteins including NFATc1, which is an essential transcription factor for osteoclastogenesis. These results demonstrated that Nrf2 activation in osteoclasts is a valuable tool for osteoclastic bone loss management. In addition, KCB-F06 presents as an alternative candidate for treating osteoclast-related bone diseases and as a novel small molecule that can serve as a model for further Keap1-NRF2 PPI inhibitor development.

Bioengineered Silk Protein-Based 3D In Vitro Models for Tissue Engineering and Drug Development: From Silk Matrix Properties to Biomedical Applications.

3D in vitro model has emerged as a valuable tool for studying tissue development, drug screening, and disease modeling. 3D systems can accurately replicate tissue microstructures and physiological features, mirroring the in vivo microenvironment departing from conventional 2D cell cultures. Various 3D in vitro models utilizing biomacromolecules like collagen and synthetic polymers have been developed to meet diverse research needs andaddress the complex challenges of contemporary research. Silk proteins, bearing structural and functional similarities to collagen, have been increasingly employed to construct advanced 3D in vitro systems, surpassing the limitations of 2D cultures. This review examines silk proteins' composition, structure, properties, and functions, elucidating their role in 3D in vitro models. Furthermore, recent advances in biomedical applications involving silk-based organoid models are discussed. In particular, the unique physiological attributes of silk matrix constituents in in vitro tissue constructs are highlighted, providing a meticulous evaluation of their importance. Additionally, it outlines the current research hurdles and complexities while contemplating future avenues, thereby paving the way for developing complex and biomimetic silk protein-based microtissues.

Development of an Online Nursing Leadership Program for Global Health in the Western Pacific Region

Background and Objective. Global health highlights the transnational determinants, issues, and possible solutions for improving health outcomes. Addressing global health issues requires population-based approaches coupled with individualized healthcare across settings, including strategies for achieving health equity. Designing and implementing global health solutions requires competent nurse leaders who can facilitate multi-disciplinary collaborations, engage in policy development, and lead advocacies that support the global health agenda. Thus, this paper examined the stakeholder perspectives that informed the development of a leadership program on global health for nurse leaders in the Western Pacific Region (WPR). Methods. The study used a descriptive qualitative approach to generate key recommendations for a context-appropriate, multi-country capacity-building program for nurse leaders on global health. The Analysis Design, Development, Implementation, and Evaluation (ADDIE) model and reflexive approach were employed to guide the development of the training design. Twenty-five nurse leaders from World Health Organization Collaborating Centers (WHO-CC) in the Western Pacific participated. Qualitative data were collected from participant feedback and post-activity sessions throughout program implementation. Results. Thematic analysis of stakeholder data revealed that the program (1) capitalized on equipping nurseleaders with the concepts related to global health and developing competencies in leadership, policyengagement, and advocacy; (2) ensured learning strategies by having participants from varied contextsand experiences; and (3) reflected on the strengths and limitations of the use of the online platform. Conclusion. This paper contributed to the growing literature on global health and programs that supportaddressing global health issues. The findings underscored the urgent need to capacitate nurses in leadershippositions who contribute to addressing emerging issues in global health. The paper recommended improvements in the design and implementation of the Global Health Nursing Leadership Program to engage more nurse leaders across the region and enhance content and delivery.

Analytical modelling of the linear transverse flux permanent magnet motor using magnetic equivalent circuit method

AbstractThe authors propose an analytical modelling approach for the linear transverse flux permanent magnet motor using the magnetic equivalent circuit method. The main focus of this study is to predict the phase flux‐linkage characteristic of the motor. Essential equations required for implementation of the model and how to solve it are described clearly so that someone can use it easily. A typical motor is selected to apply the proposed model and simulation results, including static characteristics of flux‐linkage and thrust, are presented. To validate the developed analytical model, the discussed motor is also analysed with 3D finite element method using MAXWELL software and the obtained simulation results are compared to each other.

Modeling Normal and Abnormal Circuit Development with Recurrent Neural Networks.

Neural development must construct neural circuits that can perform the computations necessary for survival. However, many theoretical models of development do not explicitly address the computational goals of the resulting networks, or computations that evolve in time. Recurrent neural networks (RNNs) have recently come to prominence as both models of neural circuit computation and building blocks of powerful artificial intelligence systems. Here, we review progress in using RNNs for understanding how developmental processes lead to effective computations, and how abnormal development disrupts these computations.