Simplified Strategies Research Articles

Multiple surrogates in the meta-analytic setting for normally distributed endpoints

The identification of good surrogate endpoints is a challenging endeavour. This may, at least partially, be attributable to the fact that most researchers have focused on the identification of a single surrogate endpoint. It is thus implicitly assumed that the treatment effect on the true endpoint (T) can be accurately predicted based on the treatment effect on one surrogate endpoint (S) only. Given the complex nature of many diseases and the different therapeutic pathways in which a treatment can impact T, this assumption may be too optimistic. For example, in oncology, the effect of a treatment often depends on both the treatment’s efficacy and its toxicity. In the present paper, the meta-analytic framework of Buyse et al. (2000) is extended to the setting where multiple S are considered. To cope with potential model convergence issues that often arise in a meta-analytic framework, several simplified model fitting strategies are proposed. Further, simulation studies are conducted to evaluate the properties of the estimated surrogacy metrics, and the new methodology is applied on a case study in schizophrenia. An online Appendix that details how the analyses can be conducted in practice (using the R package Surrogate) is also provided.

Comparison of Awake Respiratory Control Versus Sleep Obstructive Sleep Apnea Endotypes.

Most approaches to advance simplified physiology-based precision medicine strategies for obstructive sleep apnea (OSA) focus on sleep parameters (i.e., OSA endotypes). However, wakefulness physiology measures can also provide prediction insight for certain OSA therapies yet their relationship with sleep parameters has not been extensively investigated. This study aimed to investigate potential relationships between awake ventilatory control parameters and sleep OSA endotypes and their potential to predict changes in OSA severity with morphine. Data were acquired from a randomised, cross-over trial that investigated effects of morphine versus placebo on OSA severity and underlying mechanisms. Here, awake ventilatory chemoreflex testing prior to overnight polysomnography was compared with direct measures of sleep respiratory control (e.g., hypercapnic ventilatory responses and loop gain) and OSA endotypes during a separate overnight physiology study (pharyngeal critical closure pressure-Pcrit, muscle responsiveness via genioglossus intramuscular electromyography and arousal threshold via epiglottic pressure catheter to transient continuous positive airway pressure reductions). Twenty-one men with OSA completed both study arms. During placebo, 1) awake chemosensitivity correlated with Pcrit (r=0.726, p=0.001), 2) arousal threshold correlated with awake CO2 ventilatory response threshold (r=-0.467, p=0.047) and basal ventilation (r=-0.500, p=0.029). Awake chemosensitivity and Pcrit also correlated with the apnea-hypopnea index (p<0.001) during placebo. Awake chemosensitivity was predictive of changes in OSA severity with morphine(r=-0.535, p=0.013). In conclusion, awake measures of respiratory control are related to physiological endotypes such as airway collapsibility and arousal threshold during sleep and OSA severity. Awake ventilatory chemosensitivity has the best potential to predict changes in OSA severity with morphine.

Distinct Element macro-crack networks for expedited discontinuum seismic analysis of large-scale URM structures

Discontinuum analysis is a powerful tool for the detailed seismic assessment of unreinforced masonry (URM) structures, whose widespread use is however still mostly limited to small-scale assemblies or isolated components. Despite their unique capabilities, including the explicit simulation of separation phenomena, collapses and out-of-plane (OOP) failures that are hardly replicable using traditional continuum solutions, the high computational cost entailed by micro-to-meso-scale discontinuum modelling strategies, which are the standard approaches in applied research, presently prevent their employment for building-scale problems. The few available macro-scale discontinuum models specifically conceived for URM, on the other hand, rely on complex geometrical discretization processes that require costly manual work, as well as on less efficient deformable block formulations. In this paper, a new simplified discontinuum macro-model is presented and validated against full-scale laboratory test outcomes on walls, pier-spandrel systems and building specimens, in addition to various meso-scale numerical results, under either in-plane (IP) or OOP actions, and considering quasi-static (monotonic, cyclic) or dynamic loadings. The proposed simulation technique, implemented in a robust Distinct Element Method (DEM) framework, leverages a semi-automated Equivalent Frame discretization algorithm that idealizes masonry piers, spandrels and nodes as an assembly of interlocked rigid macro-blocks connected by a network of zero-thickness interface springs. The latter are herein demonstrated to effectively replicate URM damage at the component-level through fracture energy contact laws, providing macro-scale yet representative failure patterns, as well as adequate predictions of overall strength and deformation capacities. Results obtained show a good agreement between macro- and more sophisticated meso-scale predictions, as well as with experimental outcomes, albeit dissimilarities among measured and computed force-displacement responses – similarly to other simplified strategies – were detected as vertical overburden increases. Notably, for analogous levels of accuracy, the analysis time required by our new macro-models is up to 150 times lower than its meso-counterparts. The use of the proposed simplified strategy also enabled the satisfactory simulation of the quasi-static cyclic and seismic responses of full-scale building-scale specimens, prohibitive tasks using traditional detailed DEM models, while also being up to 10 times faster than previous deformable macro-models.

Isolation and characterization of a Halomonas species for non-axenic growth-associated production of bio-polyesters from sustainable feedstocks.

The urgent need for renewable replacements for synthetic materials may be addressed through microbial biotechnology. To simplify the large-scale implementation of such bio-processes, robust cell factories that can utilize sustainable and widely available feedstocks are pivotal. To this end, non-axenic growth-associated production could reduce operational costs and enhance biomass productivity, thereby improving commercial competitiveness. Another major cost factor is downstream processing, especially in the case of intracellular products, such as bio-polyesters. Simplified cell-lysis strategies could also further improve economic viability.

Beneficiary appointment and delivery planning in a conflict setting

AbstractIn this study, we explore the challenges faced by humanitarian organizations engaged in relief efforts for internally displaced individuals during armed conflicts. Based on our semistructured interviews with three local nongovernmental organizations (LNGOs) in Syria, we introduce a new appointment scheduling problem to improve decision‐making for aid delivery planning in conflict settings. Operating in a highly resource‐constrained environment, these LNGOs face complexities that necessitate effective decision support tools to streamline supply delivery at relief facilities, where a large number of registered beneficiaries are served. Our proposed appointment scheduling problem aims to optimize the allocation of delivery times for various supplies, taking into account the urgency of needs and operational limitations. We present a heuristic that addresses the complexities of the proposed scheduling problem in a flexible way. The heuristic can accommodate simple rules derived from LNGOs' operational policies on the ground, such as imposing a single visit per beneficiary, delivering a single supply type per day, and preallocating time slots to conflict groups. We present a case study based on the Latakia district of Syria to assess the performance of our heuristic and the effectiveness of simplified delivery strategies. Our results not only showcase the efficiency of the heuristic, but also provide valuable managerial insights. We find that cross‐training of staff is more beneficial when supplies are relatively abundant. Furthermore, the simplified delivery policies are effective in certain conditions contingent upon various factors, including supply scarcity, difficulty of travel, and the level of conflict in the population.

Impact of simplified HCV diagnostic strategies on the HCV epidemic among men who have sex with men in the era of HIV oral pre-exposure prophylaxis in Taiwan: a modelling study.

Simplified hepatitis C virus (HCV) diagnostic strategies have the potential to improve HCV diagnoses and treatment. We aimed to investigate the impact of simplified HCV diagnostic strategies on HCV incidence and its effect on HCV diagnosis and treatment among men who have sex with men (MSM) regardless of HIV status and use of HIV pre-exposure prophylaxis (PrEP) in Taiwan. A compartmental deterministic model was developed to describe the natural history of HCV disease progression, the HCV care cascade and the HIV status and PrEP using among MSM. The model was calibrated to available data for HCV and HIV epidemiology and population demographics in Taiwan. We simulated the epidemic from 2004 and projected the impact of simplified testing strategies on the HCV epidemic among MSM over 2022-2030. Under the current testing approach in Taiwan, total HCV incidence would increase to 12.6 per 1000 person-years among MSM by 2030. Single-visit point-of-care RNA testing had the largest impact on reducing the number of new HCV infections over 2022-2030, with a 31.1% reduction (interquartile range: 24.9%-32.8%). By 2030, single-visit point-of-care HCV testing improved HCV diagnosis to 90.9%, HCV treatment to 87.7% and HCV cure to 81.5% among MSM living with HCV. Compared to status quo, prioritized simplified HCV testing for PrEP users and MSM living with diagnosed HIV had considerable impact on the broader HCV epidemic among MSM. A sensitivity analysis suggests that reinfection risk would have a large impact on the effectiveness of each point-of-care testing scenario. Simplified HCV diagnostic strategies could control the ongoing HCV epidemic and improve HCV testing and treatment among Taiwanese MSM. Single-visit point-of-care RNA testing would result in large reductions in HCV incidence and prevalence among MSM. Efficient risk-reduction strategies will need to be implemented alongside point-of-care testing to achieve HCV elimination among MSM in Taiwan.

Intensive Environmental Sampling and Whole Genome Sequence-based Characterization of Listeria in Small- and Medium-sized Dairy Facilities Reveal Opportunities for Simplified and Size-appropriate Environmental Monitoring Strategies

Small- and medium-sized dairy processing facilities (SMDFs) may face unique challenges with respect to controlling Listeria in their processing environments, e.g., due to limited resources. The aim of this study was to implement and evaluate environmental monitoring programs (EMPs) for Listeria control in eight SMDFs in a ∼1-year longitudinal study; this included a comparison of pre-operation (i.e., after cleaning and sanitation and prior to production) and mid-operation (i.e., at least 4 h into production) sampling strategies. Among 2,072 environmental sponge samples collected across all facilities, 272 (13%) were positive for Listeria. Listeria prevalence among pre- and mid-operation samples (15% and 17%, respectively), was not significantly different. Whole genome sequencing (WGS) performed on select isolates to characterize Listeria persistence patterns revealed repeated isolation of closely related Listeria isolates (i.e., ≤20 high-quality single nucleotide polymorphism [hqSNP] differences) in 5/8 facilities over >6 months, suggesting Listeria persistence and/or reintroduction was relatively common among the SMDFs evaluated here. WGS furthermore showed that for 41 sites where samples collected pre- and mid-operation were positive for Listeria, Listeria isolates obtained were highly related (i.e., ≤10 hqSNP differences), suggesting that pre-operation sampling alone may be sufficient and more effective for detecting sites of Listeria persistence. Importantly, our data also showed that only 1/8 of facilities showed a significant decrease in Listeria prevalence over 1 year, indicating continued challenges with Listeria control in at least some SMDFs. We conclude that options for simplified Listeria EMPs (e.g., with a focus on pre-operation sampling, which allows for more rapid identification of likely persistence sites) may be valuable for improved Listeria control in SMDFs.

Two-dimensional interfacial enhanced CO2 adsorption performance of porous organic amine solids: Structure-activity relationships and DFT calculations

The utilization of inexpensive and efficient amine-functionalized adsorbents has become a research hotspot in post-combustion capture technology. Meanwhile, the structure of the support and the selection of organic amines are the primary considerations affecting the CO2 adsorption performance. Herein, the novel solid amine adsorbent materials with amine-support interfacial effect were successfully synthesized in this study by loading four organic amines (TETA, TEPA, PEHA, and PEI) onto expanded vermiculite (EVMT) support with the layered structure. The results indicated that EVMT-50TETA exhibited superior CO2 adsorption capacity (132.5 mg/g) along with effective regeneration capability. This was attributed to the unique layered structure of EVMT that facilitates the dispersion of TETA on its surface or between layers as well as the formation of hydrogen bonds between surface functional groups (–OH) and amines to enhance the amine-support interfacial interaction. Furthermore, the minimal volume expansion of TETA during CO2 adsorption enables improved diffusion of CO2 in channels and enhanced accessibility to active sites. DFT calculations show higher binding energies and faster CO2 adsorption-diffusion rates between TETA and EVMT support. In situ DRIFTS experiments revealed that the process of CO2 adsorption followed the zwitterion mechanism, in which the zwitterion can be reversibly deprotonated to form ammonium carbamate and carbamic acid. This study provides comprehensive insights into the supports and amines interfacial effects through systematic investigation, offering both simplified synthesis strategies and profound theoretical support for studying solid amine adsorbents.

Numerical analysis of delamination behavior in an impregnated HTS Roebel cable during cooling

The delamination failures of REBCO tapes inside impregnated HTS Roebel cables during cooling have been observed in existing experiments. In this work, the finite element analysis (FEA) based on the cohesive zone model (CZM) is applied to simulate the delamination failure within impregnated Roebel cable during cooling from 300 K to 4.2 K. The modified three-dimensional (3D) Roebel geometric model is adopted. Simplified calculation strategies are developed to reduce the modeling complexity and computational cost. As a result, delamination characteristics observed in previous experiments can be captured based on the numerical simulation. Parametric analyses indicate that the mismatch in thermal expansion between impregnating materials and REBCO tapes has a more severe impact on the delamination than the edge pre-crack during cooling. Meanwhile, the various levels of delamination damage among REBCO tapes are observed, and the effects of delamination strength on the numerical results are discussed.

Indoor Mapping with Entertainment Devices: Evaluating the Impact of Different Mapping Strategies for Microsoft HoloLens 2 and Apple iPhone 14 Pro.

Due to their low cost and portability, using entertainment devices for indoor mapping applications has become a hot research topic. However, the impact of user behavior on indoor mapping evaluation with entertainment devices is often overlooked in previous studies. This article aims to assess the indoor mapping performance of entertainment devices under different mapping strategies. We chose two entertainment devices, the HoloLens 2 and iPhone 14 Pro, for our evaluation work. Based on our previous mapping experience and user habits, we defined four simplified indoor mapping strategies: straight-forward mapping (SFM), left-right alternating mapping (LRAM), round-trip straight-forward mapping (RT-SFM), and round-trip left-right alternating mapping (RT-LRAM). First, we acquired triangle mesh data under each strategy with the HoloLens 2 and iPhone 14 Pro. Then, we compared the changes in data completeness and accuracy between the different devices and indoor mapping applications. Our findings show that compared to the iPhone 14 Pro, the triangle mesh accuracy acquired by the HoloLens 2 has more stable performance under different strategies. Notably, the triangle mesh data acquired by the HoloLens 2 under the RT-LRAM strategy can effectively compensate for missing wall and floor surfaces, mainly caused by furniture occlusion and the low frame rate of the depth-sensing camera. However, the iPhone 14 Pro is more efficient in terms of mapping completeness and can acquire a complete triangle mesh more quickly than the HoloLens 2. In summary, choosing an entertainment device for indoor mapping requires a combination of specific needs and scenes. If accuracy and stability are important, the HoloLens 2 is more suitable; if efficiency and completeness are important, the iPhone 14 Pro is better.

Design of a large-scale model for wind tunnel test of a multiadaptive flap concept

The design and application of morphing systems are ongoing issues compelling the aviation industry. The Clean Sky - program represents the most significant aeronautical research ever launched in Europe on advanced technologies for greening next-generation aircraft. The primary purpose of the program is to develop new concepts aimed at decreasing the effects of aviation on the environment, increasing reliability, and promoting eco-friendly mobility. These ambitions are pursued through research on enabling technologies fostering noise and gas emissions reduction, mainly by improving aircraft aerodynamic performances. Within the Clean Sky framework, a multimodal morphing flap device was designed based on tight industrial requirements and tailored for large civil aircraft applications. The flap is deployed in one unique setting, and its cross section is morphed differently in take-off and landing to get the necessary extra lift for the specific flight phase. Moreover, during the cruise, the tip of the flap is deflected for load control and induced drag reduction. Before manufacturing the first flap prototype, a high-speed (Ma = 0.3), large-scale test campaign (geometric scale factor 1:3) was deemed necessary to validate the performance improvements brought by this novel system at the aircraft level. On the other hand, the geometrical scaling of the flap prototype was considered impracticable due to the unscalability of the embedded mechanisms and actuators for shape transition. Therefore, a new architecture was conceived for the flap model to comply with the scaled dimensions requirements, withstand the relevant loads expected during the wind tunnel tests and emulate the shape transition capabilities of the true-scale flap. Simplified strategies were developed to effectively morph the model during wind tunnel tests while ensuring the robustness of each morphed configuration and maintaining adequate stiffness levels to prevent undesirable deviations from the intended aerodynamic shapes. Additionally, a simplified design was conceived for the flap-wing interface, allowing for quick adjustments of the flap setting and enabling load transmission paths like those arising between the full-scale flap and the wing. The design process followed for the definition of this challenging wind tunnel model has been addressed in this work, covering the definition of the conceptual layout, the numerical evaluation of the most severe loads expected during the test, and the verification of the structural layout by means of advanced finite element analyses.

Speculative ubimus design: Probing the potential for expansion of second-wave ubiquitous music frameworks

This contribution engages with the relationships between field deployments and conceptual underpinnings of ubiquitous music (ubimus) research, to establish a dialog with speculative design. Three cases serve as triggers for a conceptual exercise that points to common threads among ubimus endeavors within three active areas of second-wave ubimus investigations: Emugel, a tool for lite-coding; Ouija, an ecomprovisational artwork; and InMesh, a multimodal installation inspired in the cultural frictions of current Amazonian reality. Lite coding is proposed as a sonic-oriented practice that incorporates simplified semantic strategies to foster knowledge sharing in iterative individual and group-based creative activities. Ouija is an ecomprovisational artwork deployable on the musical internet that highlights the dynamic relationships between fixed and volatile resources in music making. The processes leading to the realization of InMesh furnish an opportunity to probe the limits of repurposed telematic tools for sharing implicit knowledge and hint at potential limitations of multimodal artistic frameworks.

Easy and reliable assessment of the prevalence of porcine post-weaning diarrhoea.

Post-weaning diarrhoea is a condition of increasing importance due to recent restrictions and bans on the preventive use of antimicrobials and medicinal zinc oxide. For various purposes, it is valuable to monitor the occurrence of post-weaning diarrhoea. The aim of this paper was to propose a protocol for easy and reliable assessment of the prevalence of post-weaning diarrhoea within a section of pigs as an alternative to clinical examination of a random sample of pigs. Two datasets were collected in two different observational field investigations, including more than 4000 individual clinical examinations of newly weaned pigs. First we identified a clinical marker for post-weaning diarrhoea. Second, we drew samples by simulation from our two dataset using different simplified sampling strategies and compared these to conventional random sampling strategies. The prediction error for estimates of the diarrhoea prevalence within a section was compared for the different sampling strategies. The study showed that pigs with diarrhoea had an increased risk of displaying diarrheic soiling of the hind part as well as dull, long, and bristly hair coat, and possibly also hollow flanks and a suboptimal body condition score. Diarrheic soiling of the hind part was the best clinical predictor of diarrhoea; our best estimate of the diagnostic sensitivity was 76.1% (95% credible interval: 72.0, 79.8), and the specificity was 97.1% (95% credible interval: 96.5 0.97.7). Diarrheic soiling of the hind is only a valid clinical predictor of diarrhoea for the first 14 days after insertion into the nursery unit. The precision and accuracy of prevalence estimates were similar for haphazard sampling compared to random sampling of the pigs. Likewise, sampling from a restricted number of pens produced prediction errors similar to sampling across all pens. Yet, the study had limitations regarding sample sizes, and furthermore it is difficult to provide certainty for absence of effects. We recommend sampling pigs haphazardly within at least three randomly selected pens for post-weaning diarrhoea prevalence surveys in order to easily obtain a reliable prevalence estimate. Based on our findings, we conclude the paper by proposing a simple four-step protocol for surveys of the within-section prevalence of post-weaning diarrhoea.

Expanding the toolbox of probiotic Escherichia coli Nissle 1917 for synthetic biology.

Escherichia coli Nissle 1917 (EcN) is a probiotic microbe that has the potential to be developed as a promising chassis for synthetic biology applications. However, the molecular tools and techniques for utilizing EcN remain to be further explored. To address this opportunity, the EcN-based toolbox was systematically expanded, enabling EcN as a powerful platform for more applications. First, two EcN cryptic plasmids and other compatible plasmids were genetically engineered to enrich the manipulable plasmid toolbox for multiple gene coexpression. Next, two EcN-based technologies were developed, including the conjugation strategy for DNA transfer, and quantification of protein expression capability. Finally, the EcN-based applications were further expanded by developing EcN native integrase-mediated genetic engineering and establishing an in vitro cell-free protein synthesis (CFPS) system. Overall, this study expanded the toolbox for manipulating and making full use of EcN as a commonly used probiotic chassis, providing several simplified, dependable, and predictable strategies for researchers working in synthetic biology fields.

Rational Simplification of High Fidelity Wind Turbine Models Used for Mooring Analysis

This study investigates the use of simplified turbine modelling in analysis of a soft mooring system (horizontal plane periods > 250 s). Two simplified turbine models are developed, tested and compared to a high fidelity turbine model in a case study of the INO WINDMOOR 12 MW FOWT with a soft mooring system. The chosen simplified modelling strategies are a drag disc model, a de-coupled approach where the aerodynamic loads are pre-calculated in a fixed turbine simulation and a model with reduced degrees-of-freedom. Corrections to the pre-calculated force model is also developed and compared. The results show that the pre-calculated force approach gives better comparisons to the full model than the drag disc model, and that applying a controller correction to account for the wind turbine controller’s response to floater motions improves the predicted response.

Urban Cool Island as a sustainable passive cooling strategy of urban spaces under summer conditions in Mediterranean climate

Rapid urbanization of cities is changing the local climate, resulting in high temperatures and rough, dense urban environments lacking in water and vegetation. Currently, public space is the object of particular attention due to the concern of improving the quality of life on which the feeling of well-being strongly depends. This study focuses on the problem of urban warming. It is interested in evaluating the effect of natural cooling by the plant cover and water in urban spaces and their microclimatic impact on the built environment during the hot period at the level of the city of Jijel with humid climate. More precisely, it aims at comparing in a simplified and synthetic way different strategies proposed in the form of scenarios by the numerical simulation software ENVI-met. Compared to the initial case, the results have confirmed that the blue and green scenarios have produced a coolness island effect and have allowed the mitigation of urban heat islands during the day.

Consecutive engineering of anodic graphene supported cobalt monoxide composite and cathodic nanosized lithium cobalt oxide materials with improved lithium-ion storage performances

Downsizing the electrochemically active materials in both cathodic and anodic electrodes commonly brings about enhanced lithium-ion storage performances. It is particularly meaningful to explore simplified and effective strategies for exploiting nanosized electrode materials in the advanced lithium-ion batteries. In this work, the spontaneous reaction between few-layered graphene oxide (GO) and metallic cobalt (Co) foils in mild hydrothermal condition is for the first time employed to synthesize a reduced graphene oxide (RGO) supported nanosized cobalt monoxide (CoO) anode material (CoO@RGO). Furthermore, the CoO@RGO sample is converted to nanosized lithium cobalt oxide cathode material (LiCoO2, LCO) by taking the advantages of the self-templated effect. As a result, both the CoO@RGO anode and the LCO cathode exhibit inspiring lithium-ion storage properties. In half-cells, the CoO@RGO sample maintains a reversible capacity of 740.6 mAh·g−1 after 300 cycles at the current density of 1000 mA·g−1 while the LCO sample delivers a reversible capacity of 109.1 mAh·g−1 after 100 cycles at the current density of 100 mA·g−1. In the CoO@RGO//LCO full-cells, the CoO@RGO sample delivers a reversible capacity of 553.9 mAh·g−1 after 50 cycles at the current density of 200 mA·g−1. The reasons for superior electrochemical behaviors of the samples have been revealed, and the strategy in this work can be considered to be straightforward and effective for engineering both anode and cathode materials for lithium-ion batteries.

Multi-Objective Deep Reinforcement Learning for Crowd Route Guidance Optimization

In this study, we propose an improved version of Pareto deep Q-network (PDQN), a multi-objective deep reinforcement learning method, and attempt to demonstrate its effectiveness in a real-world problem such as crowd route guidance strategy optimization. Overcrowding during crowd movement can sometimes lead to accidents; therefore, it is imperative to guide crowds to move safely and efficiently. Safety and efficiency are conflicting objectives, and how to dynamically determine guidance can be formulated as a multi-objective sequential decision-making problem. PDQN is suitable for solving these problems, but its applicability to complex real-world problems has not been fully verified. To apply PDQN to real problems, we propose to adjust the parameters of PDQN and improve the action selection criteria during learning. A toy problem and a crowd guidance problem using multi-agent crowd simulation are adopted to evaluate the performance of improved PDQN. Experimental results show that the improved PDQN can search for good strategies compared with the original PDQN and can obtain better strategies than simplified strategies.

An Open-Source Framework for Modeling RC Shear Walls Using Deep Neural Networks

Reinforced concrete (RC) shear walls macroscopic models are simplified strategies able to simulate the complex nonlinear behavior of RC shear walls to some extent, but their efficacy and robustness are limited. In contrast, microscopic models are sophisticated finite element method (FEM) models that are far more accurate and reliable. However, their elevated computational cost turns them unfeasible for most practical applications. In this study, a data-driven surrogate model for analyzing RC shear walls is developed using deep neural networks (DNNs). The surrogate model is trained with thousands of FEM simulations to predict the characteristic curve obtained when a static nonlinear pushover analysis is performed. The surrogate model is extensively tested and found to exhibit a high degree of accuracy in its predictions while being extremely faster than the detailed FEM analysis. The complete framework that made this study possible is provided as an open-source project. The project is developed in Python and includes a parametric FEM model of an RC shear wall in OpenSeesPy, the training and validation of the DNN model in TensorFlow, and an application with an interactive graphical user interface to test the methodology and visualize the results.

Multi-GNSS precise point positioning with predicted orbits and clocks

Global Navigation Satellite Systems (GNSS) Real-time Precise Point Positioning (RT-PPP) strongly relies on the precise satellite orbits and clocks, especially the latter requires high update rate, e.g., five seconds, due to its limited prediction accuracy. Such a high-rate update frequency is a burden to both the data analysis and communicating, and interruption in communicating is almost unavoidable. For the new constellations such as Galileo and BDS-3 with high-stability hydrogen clocks onboard, it is possible to predict satellite clocks to a longer arc. Moreover, recent developments in multi-GNSS ultra-rapid precise orbit determination enables the half-hourly update, ensuring the availability with a prediction arc of 30–60 min. We investigate multi-GNSS RT-PPP using half-hourly predicted products and demonstrate that a 3-D accuracy of 2.9 and 11.3 cm can be achieved for static and simulated kinematic solutions, respectively. We present the different clock prediction accuracies of different types of satellites and propose a satellite-specific weighting strategy in PPP, which exploits the benefits of the satellites of good performance. The method is based on the prediction accuracy of both, satellites and clocks, and shows an improvement of 15 to 60% compared to those without satellite-specific weighting or with simplified weighting strategies. We also demonstrate that Galileo satellites contribute the most in the quad-constellation solution, thanks to the highly stable satellite clocks.