Ideal Scenario Research Articles

State Dependency of Dynamic and Thermodynamic Contributions to Effective Precipitation Changes

Abstract Reliable projections of the future hydrological cycle are needed for designing adaptation and mitigation measures under global warming. However, uncertainties in the projected sign and magnitude of effective precipitation changes (precipitation minus evaporation, P − E) remain high. Here, we examine the state dependency of circulation, temperature, and relative humidity contributions to P − E changes in simulations of the Last Glacial Maximum (LGM), mid-Holocene, and abrupt quadrupling of the atmospheric carbon dioxide concentration. To this purpose, we apply a moisture budget decomposition and a thermodynamic scaling approximation to CMIP6/PMIP4 simulations with the Earth system model MPI-ESM1.2. We find that the importance of thermodynamic and dynamic contributions to P − E changes and the patterns of dynamic contributions depend strongly on the underlying forcing. Greenhouse gas forcing leads to a stronger thermodynamic response than dynamic response. The LGM ice sheets yield a large dynamic contribution with zonally heterogeneous patterns. Orbital forcing induces a predominantly dynamic response with a hemispherically antisymmetric structure. We also identify state-invariant features: The importance of temperature and relative humidity contributions to specific humidity changes is consistent across states, and the wet-get-wetter–dry-get-drier paradigm proposed for global warming holds in almost all regions dominated by thermodynamic contributions. By definition, the P − E budget and the respective thermodynamic, dynamic, and transient eddy contributions vanish in the global mean. Moreover, we find that for increasing length scales, the spatial variability of these contributions decays with similar rates. We suggest repeating our analysis for more models and states which could help constrain hydroclimate projections. Significance Statement We aim at improving our understanding of the influence of changes in winds and water vapor on the local balance between precipitation and evaporation. To this end, we compare simulations for two past climate states with an idealized high carbon dioxide concentration scenario. We find characteristics that depend on the underlying state and characteristics that are consistent across states. Our results help to identify what we can learn from past climate states about precipitation changes under future greenhouse gas emission scenarios. So far, we only analyzed simulations from one model. Therefore, we suggest to repeat our analysis with more models and for more past climate states to confirm our results.

Lidocaine Enhanced Antitumor Efficacy and Relieved Chemotherapy-Induced Hyperalgesia in Mice with Metastatic Gastric Cancer.

With the widespread use of lidocaine for pain control in cancer therapy, its antitumor activity has attracted considerable attention in recent years. This paper provides a simple strategy of combining lidocaine with chemotherapy drugs for cancer therapy, aiming to relieve chemotherapy-induced pain and achieve stronger antitumor efficacy. However, there is still a lack of substantial pre-clinical evidence for the efficacy and related mechanisms of such combinations, obstructing their potential clinical application. In this study, we propose intraperitoneal chemotherapy (IPC) against gastric cancer (GC) as an ideal scenario to evaluate the efficacy of a lidocaine/paclitaxel combination. Firstly, we used human GC cells MKN-45-luc to investigate the antitumor activity and related mechanisms of the lidocaine/paclitaxel combination in vitro. Then, we used C57BL/6 mice with intraperitoneal drug suffusion to evaluate the efficacy of lidocaine to suppress paclitaxel-induced hyperalgesia and related mechanisms. Lastly, in BALB/c tumor-bearing nude mice we evaluated the synergistic antitumor activity and pain-relieving effect of the lidocaine/paclitaxel combination. Our results showed enhanced antitumor activity for the lidocaine/paclitaxel combination, which induced apoptosis, inhibited migration, and the invasion of GC cells in a synergistic manner. In animal models, the lidocaine/paclitaxel combination effectively inhibited growth and peritoneal metastasis of the tumor, resulting in prolonged survival time. Meanwhile, lidocaine showed considerable anti-inflammatory activity alongside its anesthetic effect, which, in combination, effectively relieved hyperalgesia induced by paclitaxel. These results suggested that intraperitoneal suffusion with lidocaine/paclitaxel could be a pain-free IPC formulation with enhanced antitumor activity, which could provide a promising treatment for GC with peritoneal metastasis.

Real-time multi-sensor fusion for object detection and localization in self-driving cars: A Carla simulation

Research on integrating camera and LiDAR in self-driving car systems has important scientific significance in the context of developing 4.0 technology and applying artificial intelligence. The research contributes to improving the accuracy in recognizing and locating objects in complex environments. This is an important foundation for further research on optimizing response time and improving the safety of self-driving systems. This study proposes a real-time multi-sensor data fusion method, termed "Multi-Layer Fusion," for object detection and localization in autonomous vehicles. The fusion process leverages pixel-level and feature-level integration, ensuring seamless data synchronization and robust performance under adverse conditions. Experiments conducted on the CARLA simulator. The results show that the method significantly improves environmental perception and object localization, achieving a mean detection accuracy of 95% and a mean distance error of 0.54 meters across diverse conditions, with real-time performance at 30 FPS. These results demonstrate its robustness in both ideal and adverse scenarios

Dynamic coupling of qualitative–quantitative models for operation of water resources based on environmental criteria

Concerning issues include the distribution of scarce water resources, the quality of utilized water, environmental repercussions, and regulations for the sustainable use of water resources. In the management of water resources, optimal qualitative–quantitative exploitation of surface water bodies is regarded as a desirable strategy. The Dez River surface water system from the Dez regulatory dam to Band-e-Ghir is selected in the current paper to create a qualitative–quantitative model that can determine the best exploitation strategies. A dynamic linkage between qualitative and quantitative models is built in order to simulate the current exploitation conditions under the umbrella of the best-case scenario. In this coupled system, hydraulic relationships are established between all of the system’s components. The available data are shared between two models in this structure to simulate the qualitative and quantitative effects of surface water. Then, a new structure is produced to derive the best policies for exploiting the dam and the river by connecting the multi-objective particle swarm optimization algorithm with the qualitative–quantitative coupled model body. The monthly river environmental demand is one of the decision variables in the ideal scenario, and the goals include boosting the percentage of supply demands and minimizing the violation of quality standards. The best-case scenario’s implementation increases the likelihood that all plain demands will be met, regardless of priority. Furthermore, in comparison with the reference scenario, the results of the optimal scenario show that not only are the concentrations of contaminants and qualitative parameters increased, but there are also only minimal violations of the quality and pollution standards of the river water in the majority of river points, particularly in the locations of agricultural withdrawals. The findings demonstrate that using the qualitative–quantitative dynamic relationship between water resources and the development of the coupled model using the NSGA-II algorithm allows us to better plan for the appropriate use of existing water resources by taking into account all stakeholders in such a way that, in addition to meeting needs, maintains the river quality close to standard limits throughout the exploitation period. By using this strategy, users will be informed of the negative effects of their actions, as well as the encroachment on river boundaries and associated consequences.

Sustainability assessment of low-impact development methods for urban stormwater management: A multi-criteria decision-making approach

Low-impact development (LID) methods are used in urban areas as sustainable stormwater management solutions. However, previous studies often lack situational scenario-based assessments and cover a limited range of criteria and indices, overlooking key factors, especially in developing countries facing significant sustainability challenges. This study addresses these gaps by assessing the sustainability of four LID alternatives, including novel combinations of rain barrels (RBs), rain gardens (RGs), permeable pavements (PPs), infiltration trenches (ITs), and vegetative swales (VSs), for inside and outside the house in a case study located in Tehran, Iran. In addition, 22 quantitative/qualitative indices were selected across environmental, social, economic, and technical criteria. The three-phase indices evaluation involved 1) simulating the study area by the stormwater management model (SWMM), 2) collecting quantitative data, and 3) scoring qualitative indices through questionnaires. A modified analytical hierarchy process model was employed to rank LID alternatives in difficult, poor, transition, satisfied, and ideal scenarios. Considering situational scenarios, the results showed that IT and VS for outside the house consistently performed best, adding novel contributions. Sensitivity analysis confirmed the robustness of this finding despite changing criteria weights. This study provides a new framework for urban decision-makers in developing countries to adopt resilient stormwater solutions.

Evidences of radioresistance in Drosophila melanogaster from Northeastern Brazil

Background Ionizing radiation can inflict cellular damage, the severity of which is determined by the dose, exposure duration, and its capacity to penetrate cells. Some studies have demonstrated that genetic and epigenetic mechanisms have enabled organisms to develop adaptive traits and enhance their ability to repair DNA damage. Northeastern Brazil, a region containing rocky outcrops rich in uranium and thorium, is an ideal scenario to study natural radiation and its effects on natural populations. This study presents evidence of radioresistance in the offspring of a natural strain of Drosophila melanogaster resident in the municipality of Cerro Corá (CC-res), an environment with high levels of radon-222. Material and methods Genotoxicity was assessed using the comet assay in offspring of the CC-res and Oregon-R (OR), the control group, both reared under the same laboratory conditions for between 7 and 13 months. The adults and their offspring larvae were exposed to the Cerro Corá environment for 6 days during the dry and wet seasons. Low damage index and frequency were observed only in the CC-res. To confirm the radioresistance, the same strains were exposed after 16 months of cultivation to controlled doses of gamma radiation. Results and conclusions CC-res exhibited significantly lower levels of damage compared to the OR strain, with a clear dose–response effect to the irradiation observed exclusively in the OR group. The results support the occurrence of radioresistance in the CC-res strain and underscore the need for further in vivo studies investigations into the impact of Brazil’s natural environmental radiation.

Inequity Aversion Selection Under Revenue-Sharing in a Reservation Commuting Platform for Urban–Rural Agglomerations

The intelligent design of a transportation system management platform offers a compelling solution for optimizing traffic flow in urban–rural agglomerations. While previous studies have concentrated on the technical aspects of addressing transportation challenges in these areas, there has been a paucity of attention paid to the economic dimensions. This study explores the economic viability of such a system by examining the revenue-sharing mechanism. Moreover, it examines the principal cost elements within the construction context and develops a mathematical model based on game theory and considerations of inequity aversion. A case study of the Guangdong–Hong Kong–Macao Greater Bay Area serves to demonstrate the model’s validity. From the perspective of the service provider, it is advantageous for the provider to pursue fairness, or at the very least, to disregard any unfairness, if the owner pursues absolute fairness. In an ideal scenario, where both parties prioritize fairness, optimal or near-optimal solutions can be reached based on their fairness preferences. This approach allows for the maximization of overall benefits without incurring losses. The research findings not only offer guidance to policymakers in the realm of traffic management but also present novel ideas and methodologies for scholarly exploration in related fields.

Plurilingual Education across Educational Levels – Conceptualization, Curriculum Analysis, and Recommendations for Further Development

In the period 2020-2023, the research and development project Plurilingual Education – Minority and Majority Students' Language Awareness across Educational Levels (PE-LAL) investigated students' language awareness across educational levels in the context of plurilingual education in the mandatory language subjects in primary and lower secondary school (Danish, Danish as a second language, English, French, German) and in Almen Sprogforståelse in upper secondary school. Based on findings from the PE-LAL project, the article focuses on plurilingual education in a Danish educational context. First, the article presents the project's conceptualization of plurilingual education developed through an abductive approach. The conceptualization forms a continuum consisting of three pluralistic approaches and a transversal dimension. Then, based on the conceptualization, the article presents findings from the project's curriculum study showing that plurilingual education is integrated in all language subjects in primary and lower secondary school and in Almen Sprogforståelse in upper secondary school – albert in different ways and with different objectives – leaving the Danish language curriculum with great development potential for plurilingual education. Finally, by drawing on the curriculum findings and other research results from the project, the article concludes with an introduction to the project's Recommendations to strengthen plurilingual education in language subjects in primary and lower secondary school and in Almen Sprogforståelse in upper secondary school in Denmark. The 18 recommendations represent an ideal scenario for how plurilingual education can be strengthened at different levels vertically and horizontally in the Danish educational context, which is why the recommendations address both the macro level (curriculum and teacher education) as well as the meso and micro levels (school, teacher, teaching materials, teaching practice). Each single recommendation is an important contribution to strengthen plurilingual education.

Is There an Optimal Spacer Cation for Two-Dimensional Lead Iodide Perovskites?

Two-dimensional lead iodide perovskites have attracted significant attention for their potential applications in optoelectronic and photonic devices due to their tunable excitonic properties. The choice of organic spacer cations significantly influences the light emission and exciton transport properties of these materials, which are vital for their device performance. In this Perspective, we discuss the impact of spacer cations on lattice dynamics and exciton-phonon coupling, focusing on three representative 2D lead iodide perovskites that exhibit distinct types of structural distortions. Minimizing structural distortions, such as dynamic out-of-plane octahedral tilting and lone pair distortion, appears to be essential for achieving narrow photoluminescence (PL) emission peaks, high PL quantum yields, and rapid exciton diffusion by suppressing exciton-phonon coupling, as demonstrated in 2D perovskites based on phenylethylammonium cation or its derivatives. We propose that designing spacer cations with enhanced intermolecular interactions and denser packing, combined with the close packing of inorganic ions to minimize the motions of both organic and inorganic lattices, would be the ideal scenario for yielding the most favorable optoelectronic properties in these materials.

Mitigating impulsive noise in airborne PLC: Introducing the S-SAMP-PV algorithm for MIMO OFDM systems

Power Line Communication (PLC) offers an efficient solution for data transmission over electrical power lines, presenting a promising avenue for in-flight communication in More Electrical Aircraft (MEA). A significant challenge in airborne PLC is Impulsive Noise (IN), which hampers transmission reliability. Existing noise mitigation methods, while valuable, face limitations in airborne settings due to computational intensiveness and sub-optimal sparse recovery performance. This paper introduces the Structured Sparsity Adaptive Matching Pursuit with Preliminary partial support estimation and Variable step-size (S-SAMP-PV) algorithm, devised for Multiple-Input-Multiple-Output (MIMO) systems. It uniquely pre-estimates partial support of sparse IN signals, enabling adaptive convergence without prior sparsity knowledge. This methodology substantially reduces computational demands, satisfying stringent real-time requirements of airborne applications. In simulation, the S-SAMP-PV algorithm exhibits marked advantages over traditional algorithms such as Orthogonal Matching Pursuit (OMP). Specifically, it realizes an approximate 81.3% reduction in Normalized Mean Square Error (NMSE) and demonstrates around 37% improvement in computational efficiency relative to OMP. Moreover, its Bit Error Rate (BER) performance at high Signal to Noise Ratio (SNR) approaches the ideal scenario where IN is assumed to be perfectly eliminated. These results emphasize the promise of S-SAMP-PV in elevating the performance of airborne PLC systems by efficient IN mitigation.

Stool and blood biomarkers for colorectal cancer management: an update on screening and disease monitoring.

Biomarkers have revolutionized the management of colorectal cancer (CRC), facilitating early detection, prevention, personalized treatment, and minimal residual disease (MRD) monitoring. This review explores current CRC screening strategies and emerging biomarker applications. We summarize the landscape of non-invasive CRC screening and MRD detection strategies, discuss the limitations of the current approaches, and highlight the promising potential of novel biomarker solutions. The fecal immunochemical test remained the cornerstone of CRC screening, but its sensitivity has been improved by assays that combined its performance with other stool analytes. However, their sensitivity for advanced adenomas and the patient compliance both remain suboptimal. Blood-based tests promise to increase compliance but require further refinement to compete with stool-based biomarker tests. The ideal scenario involves leveraging blood tests to increase screening participation, and simultaneously promote stool- and endoscopy-based screening among those who are compliant. Once solely reliant on upfront surgery followed by stage and pathology-driven adjuvant chemotherapy, the treatment of stage II and III colon cancer has undergone a revolutionary transformation with the advent of MRD testing after surgery. A decade ago, the concept of using a post-surgical test instead of stage and pathology to determine the need for adjuvant chemotherapy was disruptive. Today, a blood test may be more informative of the need for chemotherapy than the stage at diagnosis. Biomarker research is not just improving, but bringing a transformative change to CRC clinical management. Early detection is not just getting better, but improving thanks to a multi-modality approach, and personalized treatment plans are not just becoming a reality, but a promising future with MRD testing.

An enhanced dynamic-network-based framework for quantifying and enhancing the resilience of disaster response networks to old communities under rainstorm waterlogging

Developing effective disaster response networks (DRNs) is crucial for mitigating the impacts of rainstorm waterlogging in old communities. Aiming at providing implementable strategies for enhancing DRN resilience, this paper developed an enhanced dynamic network analysis (DNA)-based framework for DRNs utilizing the DNA and CRITIC-VIKOR method. This framework conceptualizes community disaster response as a three-stage ‘agent-information-resource-task’ (A-I-R-T) dynamic network, facilitating a comprehensive understanding of interactions among stakeholders, disaster information, emergency resources, and response tasks. Subsequently, a hybrid evaluation model combining CRITIC and VIKOR methods was established to quantify DRN resilience by assessing deviations from ideal response scenarios. Validated through a case study of the Y community in Xuzhou city of China, the findings reveal significant variations in stakeholder communication effectiveness across different stages of disaster response, with resilience peaking during the function recovery stage at 0.292. This study not only contributes to the body of knowledge in disaster management and resilience theory but also provides actionable strategies for enhancing DRN resilience, thereby contributing to more resilient urban environments.

Hydraulic performance analysis of new versus commercial nozzle design for pressurised porous media filters

AbstractRapid water filtration with pressurised porous media filters is extensively applied in drip irrigation systems. In double-chamber filters, the underdrains are fixed to the base of the inner plate to sustain the media above while draining water. Here, a new underdrain design intended to reduce the filter energy consumption is presented. The main difference with commercial underdrain units corresponds to the distribution of the slots, being in a horizontal plate to uniformise the flow trajectories inside the porous media. Both commercial and new underdrain designs have been tested in laboratory in both filtration and backwashing modes with three media types, two media heights, and superficial velocities ranging from 20 to 120 m h−1. In filtration mode, results indicate that the new design reduces the filter pressure drop by 31% at 60 m h−1 in comparison with the commercial one. The exploration with an analytical model that correctly reproduces the filter pressure drop, reveals that its value at 60 m h−1 is only 15% higher than the ideal scenario (uniform flow throughout the porous media bed). In backwashing mode, the pressure drop in comparison with the commercial design is reduced by 65% at 80 m h−1, while having the same trend for the bed expansion, which is also predicted by a simple analytical expression. Thus, the new underdrain design produces a more homogeneous fluidised regime than the commercial one at low-moderate superficial velocities.

Stability analysis and controller design of the Cooperative Adaptive Cruise Control platoon considering a rate-free time-varying communication delay and uncertainties

In recent years, Cooperative Adaptive Cruise Controls (CACCs) have been increasingly studied as a promising solution to problems such as traffic congestion and pollutant emissions. Despite their potential, the communication delays within CACC systems undermine the effectiveness of regular feedback control method in guaranteeing the fundamental control objective of stability. Considerable research has been conducted to derive stability conditions that account for communication delays. However, the time-varying and rate-free attributes of communication delay make deriving stability conditions highly challenging. To address this, this paper proposes a novel stability condition for the CACC platoon considering a rate-free communication delay using the Lyapunov–Krasovskii Stability Theorem and Schur complement. Additionally, we deduce a robust stability condition that takes into account measure uncertainties. Building on these foundations, a centralized H∞ controller is developed to address rate-free disturbances, ensuring string stability. Furthermore, extensive numerical analyses are conducted to investigate the impact of a rate-free communication delay and measurement uncertainties on tracking performance, transient response, and safety conditions. The results demonstrate that CACCs can effectively track errors and achieve equilibrium if the stability condition is met. Realistic scenarios incorporating rate-free communication delays and measurement uncertainties are associated with diminished tracking performance, transient responses, and safety conditions when compared to ideal scenarios characterized by constant communication delays. Furthermore, the H∞ controller surpasses the regular controller in tracking performance and maintains string stability amidst rate-free communication delays. Specifically, under the H∞ controller, the peak spacing error is reduced to merely 83.68% of that observed with the regular controller. The deployment of the H∞ controller facilitates a significant reduction in settling time (ST) by 90.04% and effectively prevents overshoot, thereby ensuring string stability, in stark contrast to the regular controller, which only achieves a 79.34% reduction in ST and a 5.97% reduction in maximum overshoot. Moreover, the H∞ controller markedly reduces the likelihood of high-risk scenarios in comparison to the regular controller. Moreover, CACCs with access to more distant and abundant information demonstrate superior transient response and safety conditions.

Economic assessment of animal disease burden in Senegalese small ruminants

Small ruminant production in sub-Saharan Africa is limited by a range of constraints, including animal health issues. This study aimed at estimating the impact of these issues on the small ruminant production in Senegal in a holistic manner, using an approach developed by the Global Burden of Animal Diseases (GBADs) programme. The estimation focused on the mixed crop-livestock system, representing a large proportion (>60 %) of the small ruminant population in the country. It was based on existing data collected via a systematic literature review, acquisition of secondary datasets from local stakeholders, and expert elicitation. A dynamic population model was used to calculate the gross margin of the sector under both the current health constraints and an ideal health state, where animals are not exposed to causes of morbidity and mortality. The difference between the current and ideal health scenarios, termed the Animal Health Loss Envelope (AHLE), provides a quantitative measure of the farm-level cost of disease in the system. The all-cause AHLE was estimated at 292 billion FCFA (468 million USD, with 95 % prediction interval 216 – 366 billion FCFA) per year for 2022, for a population of 8.8 million animals. The contribution of Peste des Petits Ruminants (PPR) was modelled separately, as an example of attributing part of the AHLE to a specific disease cause. PPR was estimated to contribute 5 % of the total AHLE. The animal disease burden experienced by Senegalese livestock keepers was largely due to loss in animals and production, with relatively small amounts of animal health expenditure. Implementation of this study contributed to the further development of the GBADs approach. Such estimates can support decision making at all levels, from investment decisions at the international level to local disease awareness campaigns targeting livestock keepers.

Stereoselective Vinylic C−H Addition via Metallaphotoredox Migration

AbstractGeometrically defined allylic alcohols with SE, SZ, RE and RZ stereoisomers serve as valuable intermediates in synthetic chemistry, attributed to the stereoselective transformations enabled by the alkenyl and hydroxyl functionalities. When an ideal scenario presents itself with four distinct stereoisomers as potential products, the simultaneous control vicinal stereochemistry in a single step would offer a direct pathway to any desired stereoisomer. Here, we unveil a metallaphotoredox migration strategy to access stereodefined allylic alcohols through vinylic C−H activation with aldehydes. This method harnesses a chiral nickel catalyst in concert with a photocatalyst to enable a 1,4‐Ni migration by using readily accessible 2‐vinyl iodoarenes as starting materials. The efficacy of this methodology is highlighted by the precise construction of all stereoisomers of allylic alcohols bearing analogous substituents and the efficient synthesis of key intermediates en route to Myristinin family. Experimental and computational studies have shed light on pivotal aspects including the synergy of metal catalysis and photocatalysis, the driving forces behind the migration, and the determination of absolute configuration in the C−H addition process.

Stereoselective Vinylic C-H Addition via Metallaphotoredox Migration.

Geometrically defined allylic alcohols with SE, SZ, RE and RZ stereoisomers serve as valuable intermediates in synthetic chemistry, attributed to the stereoselective transformations enabled by the alkenyl and hydroxyl functionalities. When an ideal scenario presents itself with four distinct stereoisomers as potential products, the simultaneous control vicinal stereochemistry in a single step would offer a direct pathway to any desired stereoisomer. Here, we unveil a metallaphotoredox migration strategy to access stereodefined allylic alcohols through vinylic C-H activation with aldehydes. This method harnesses a chiral nickel catalyst in concert with a photocatalyst to enable a 1,4-Ni migration by using readily accessible 2-vinyl iodoarenes as starting materials. The efficacy of this methodology is highlighted by the precise construction of all stereoisomers of allylic alcohols bearing analogous substituents and the efficient synthesis of key intermediates en route to Myristinin family. Experimental and computational studies have shed light on pivotal aspects including the synergy of metal catalysis and photocatalysis, the driving forces behind the migration, and the determination of absolute configuration in the C-H addition process.

Upside-down Rayleigh-Marchenko: A practical redatuming scheme for seabed seismic acquisitions

Ocean-bottom seismic plays a crucial role in resource exploration and monitoring. However, despite their undoubted potential, the use of coarse receiver geometries poses challenges to accurate wavefield redatuming. This in turn affects the quality of subsequent imaging and reservoir characterization products. We develop a reciprocal version of the Rayleigh-Marchenko (RM) method, called the upside-down RM method, in which all spatial integrals are performed over the (usually much better-sampled) source carpet; this results in a redatuming scheme that naturally accommodates irregular and sparse receiver geometries. Our method requires the availability of multicomponent receivers and either dual sources or a preprocessing step of model-based source deghosting and uses only the down-going component of the receiver-side wavefield; as such, it can be interpreted as a full-wavefield extension of the mirror migration method commonly used in seabed settings. Two synthetic examples are used to showcase the effectiveness of our method, starting from the ideal scenario of finely and regularly sampled source and receiver arrays and subsequently considering different levels of decimation for the receiver geometry. Migrated images as well as common-angle gathers reveal that our method can be used to produce structural and amplitude-friendly imaging outputs with minimal data preprocessing.

Experimental modal identification of a pedestrian bridge through drive-by monitoring integrated with shared-mobility vehicles

In the context of improving resilience in transport infrastructure, an emerging approach of indirect structural health monitoring is gaining attention, known as drive-by monitoring, instrumenting a vehicle with sensors to evaluate the bridges it crosses. However, their effectiveness has predominantly been investigated in ideal scenarios, with actual real-world applications being quite scarce. The research presented in this paper explores the feasibility of combining two routes: (1) fleet emissions reduction and (2) transport resilience enhancement, through drive-by monitoring integrated with shared mobility, including electric mobility scooter and bicycle. The information from drive-by data collected from shared mobility can give valuable information on critical transport infrastructure (e.g., bridges) and such a drive-by database has the potential for network level infrastructure condition assessment. In this paper, two different drive-by roadmaps are investigated subject to the flexibility of the bridges, namely partially or fully drive-by monitoring. To validate the proposed roadmaps, a full-scale pedestrian bridge was chosen for drive-by testing, where smartphone sensors and specialised accelerometers are mounted on shared mobility for data acquisition. Experimental results demonstrate that (i) smartphone sensing can provide data with similar accuracy compared to specialised accelerometers, (ii) bridge frequencies can be easily obtained from temporarily parked shared mobility, with a maximum relative error of 1.05%, (iii) both the bridge frequencies and operational deflection shapes are successfully extracted from the moving shared mobility by using variational mode decomposition and filtering techniques, and shared mobility's GPS data along with moving speeds are collected for potential vehicle positioning and drive-by database updating.

Detectability of Varied Hybridization Scenarios Using Genome-Scale Hybrid Detection Methods

Hybridization events complicate the accurate reconstruction of phylogenies, as they lead to patterns of genetic heritability that are unexpected under traditional, bifurcating models of species trees. This phenomenon has led to the development of methods to infer these varied hybridization events, both methods that reconstruct networks directly, as well as summary methods that predict individual hybridization events from a subset of taxa. However, a lack of empirical comparisons between methods – especially those pertaining to large networks with varied hybridization scenarios – hinders their practical use. Here, we provide a comprehensive review of popular summary methods: TICR, MSCquartets, HyDe, Patterson’s D-Statistic (ABBA-BABA), D3, and Dp. TICR and MSCquartets are based on quartet concordance factors gathered from gene tree topologies and HyDe, Patterson’s D-Statistic, D3, and Dp use site pattern frequencies to identify hybridization events between sets of three taxa. We then use simulated data to address questions of method accuracy and ideal use scenarios by testing methods against complex networks which depict gene flow events that differ in depth (timing), quantity (single vs. multiple, overlapping hybridizations), and rate of gene flow (γ). We find that deeper or multiple hybridization events may introduce noise and weaken the signal of hybridization, leading to higher relative false negative rates across all methods. Despite some forms of hybridization eluding quartet-based detection methods, MSCquartets displays high precision in most scenarios. While HyDe results in high false negative rates when tested on hybridizations involving extinct or unsampled ghost lineages, HyDe is the only method able to identify the direction of hybridization, distinguishing the source parental lineages from recipient hybrid lineages. Lastly, we test the methods on a dataset of ultraconserved elements from the bee subfamily Nomiinae, finding possible hybridization events between clades which correspond to regions of poor support in the species tree estimated in a previous study.