Intravenous therapy is the standard medical procedure that is used for administering medications directly into the vein. The automated drug infusion devices are designed in such a way that they provide exact medication doses with safety measures included. On the other hand, this is why they must be regularly watched by healthcare providers. This paper introduces a cloud-based IoT drug infusion system that was developed to address remote patient care needs. This system enables remote, accurate, and secure management of medication delivery. Its key contributions include allowing healthcare providers to control and monitor IV infusions remotely while maintaining safety features. The system consists of a microcontroller that is responsible for data processing, a control system that oversees infusion rate regulation, and an IoT-based framework that allows for remote monitoring and alerts via a user-friendly web interface. This new approach to care will therefore improve patient care by providing remote management of medications. Full article

The Youjiang Basin in China is the world’s second-largest concentrated area of Carlin-type Au deposits after Nevada, USA, boasting cumulative Au reserves nearing 1000 t. This study examined the recently unearthed Lintan Carlin-type Au deposit within the Youjiang Basin. Factor analysis and association rule algorithms were used to identify exploration vectors and indicators essential for navigating this promising geological territory. In the Lintan mining area, the geological strata encompass the Triassic Bianyang, Niluo, and Xuman formations comprised clastic rocks, followed by the deeper Permian Wujiaping Formation with massive carbonate rocks. The orebodies are restricted to the F₁₄ inverse fault, cutting through the Xuman Formation, with an additional F₇ fault between the Wujiaping and Xuman formations. A total of 125 rock samples from the F₁₄ fault and a representative cross-section were analyzed for 15 elements (Au, Ag, As, Bi, Cd, Co, Cu, Hg, Mo, Ni, Pb, Sb, Tl, W, and Zn). The elements were divided into four groups based on cluster and factor analysis. Group 1 (Co, Cu, Zn, Ni, Tl, W, and Bi) was mainly enriched in the Xuman, Niluo, and Bianyang formations controlled by sedimentary diagenesis. Group 2 (Au, As, Hg, and Sb) was concentrated in the F₁₄ and F₇ faults, representing Au mineralization. Group 3 (Pb, Ag, and Mo) was mostly enriched near the F₁₄ and F₇ faults, displaying a peripheral halo of Au mineralization, and was probability controlled by ore-forming hydrothermal activities. Group 4 (Cd and Mo) exhibited extreme enrichment along the periphery of the F₇ fault. This pattern indicates the presence of a substantial hydrothermal alteration zone surrounding the fault, likely influenced by ore-forming hydrothermal processes. Additionally, Pb, Ag, Cd, Mo, and W are considered essential indicators for ore formation besides Au, As, Sb, Hg, and Tl. Twelve effective association rules were derived using the association rule algorithm, which can aid in discriminating Au mineralization. The spatial distributions of the 15 elements indicated that the F₁₄ fault is the main ore-bearing fracture zone, while the F₇ fault serves as the ore-conducting structure, channeling ore-forming fluids into the F₁₄ fault. Faults between the Wujiaping and Xuman formations, along with their associated reverse faults, present potential prospecting targets both within and outside the Lintan Au deposit in the Youjiang Basin. Exploration geochemical data can be fully utilized by combining factor analysis and association rule algorithms, offering key guidance for prospecting Carlin-type gold and similar deposits. Full article

This study explores the strategic interactions among the government, growers, and the public within the context of green rice production, employing an evolutionary game theory framework. Recognizing the intricate dynamics of agricultural sustainability, we construct a three-party evolutionary game model to investigate the strategic decision-making processes and stability conditions of each stakeholder. The model assesses how various strategies evolve under the influence of economic incentives, regulatory measures, and public engagement. Through analytical and numerical methods, including stability analysis and MATLAB 2020b simulations, we identify the Evolutionarily Stable Strategies (ESS) that signify sustainable practices in green rice production. The results reveal that as government incentives for green production increase and fines for non-green practices are enforced, the likelihood of growers adopting sustainable practices significantly rises. Furthermore, the strategic enhancement of economic incentives and reputational factors not only bolsters governmental regulatory commitment but also reduces the necessity for public supervision, demonstrating a systemic shift towards self-regulation and market-driven sustainability. The simulations demonstrate the system’s evolution towards a stable state where governmental regulation is fully enforced, growers adopt green production universally, and public supervision becomes redundant. The findings underscore the importance of designing policy interventions that harmonize economic and environmental objectives, suggesting that well-structured incentives and regulatory measures can catalyze the transition towards sustainable agricultural practices. Additionally, our study highlights the pivotal role of establishing effective incentive structures that ensure the economic benefits of green production outweigh the costs, facilitating an autonomous regulatory system. This study contributes to the understanding of how strategic interactions shaped by policy and market forces can foster agricultural sustainability. Full article

In this study, a set of accurate dispersive nonlinear wave equations is established, using the wave velocity and free surface elevation as variables. These equations improve upon previous equations in which the velocity potential is used as a variable by considering the rotational wave motion and by adding a second-order bottom slope term that applies to general situations, allowing the equations to consider the influence of rapidly changing, horizontal, two-dimensional bottom topographies. The problem of the inaccuracy of the integral calculations used in previous equations in nearshore areas is solved by approximating the integral calculations into differential calculations, and a set of coupled wave equations is established by keeping the free surface elevation and the horizontal velocity constant, thus allowing the calculation of nearshore wave-generated currents. The benefits of the current model are confirmed through comparisons with corresponding laboratory experimental findings and are illustrated through a comparison with the numerical outcomes of other pertinent models. Full article

The axiomatic structure of the $\kappa$-statistcal theory is proven. In addition to the first three standard Khinchin–Shannon axioms of continuity, maximality, and expansibility, two further axioms are identified, namely the self-duality axiom and the scaling axiom. It is shown that both the $\kappa$-entropy and its special limiting case, the classical Boltzmann–Gibbs–Shannon entropy, follow unambiguously from the above new set of five axioms. It has been emphasized that the statistical theory that can be built from $\kappa$-entropy has a validity that goes beyond physics and can be used to treat physical, natural, or artificial complex systems. The physical origin of the self-duality and scaling axioms has been investigated and traced back to the first principles of relativistic physics, i.e., the Galileo relativity principle and the Einstein principle of the constancy of the speed of light. It has been shown that the $\kappa$-formalism, which emerges from the $\kappa$-entropy, can treat both simple (few-body) and complex (statistical) systems in a unified way. Relativistic statistical mechanics based on $\kappa$-entropy is shown that preserves the main features of classical statistical mechanics (kinetic theory, molecular chaos hypothesis, maximum entropy principle, thermodynamic stability, H-theorem, and Lesche stability). The answers that the $\kappa$-statistical theory gives to the more-than-a-century-old open problems of relativistic physics, such as how thermodynamic quantities like temperature and entropy vary with the speed of the reference frame, have been emphasized. Full article

In this study, the catchment hydrology cycle analysis tool (CAT) model was used to conduct a comprehensive hydrological analysis of the water balance of agricultural reservoirs. Data from 2010 to 2017, including precipitation, water level data in the reservoir, groundwater usage, and wastewater discharge, were collected and compiled for the upper reaches of the Hantan River Dam. The current conditions and content curves of the 11 reservoirs within the watershed were investigated and recorded. The results were analyzed by simulating three scenarios: treating the entire watershed as 1 unit, dividing the watershed into 5 sub-watersheds according to the standard watershed criteria, and further subdividing it into 27 watersheds, taking into account the presence of agricultural reservoirs. In cases where watershed information is lacking, it is deemed that subdividing the watershed can enhance efficiency. The highest model efficiency was observed in the 27 sub-basins, particularly when accounting for agricultural reservoirs. This study proposed an efficient method for hydrological analysis of watersheds including ungauged areas. Full article

This research investigates the intricate relationship between financial openness, natural resources, and carbon neutrality in the N-11 countries. It provides insights into how environmental tax and innovation can drive carbon neutrality in these nations, thus advancing our understanding of the nexus among financial openness, natural resources, and carbon neutrality. The study aims to offer policymakers perspectives on formulating policies to foster sustainable economic development and environmental conservation in the N-11 nations. The discourse highlights the environmental implications of foreign direct investment (FDI) and trade openness, revealing a complex interplay between economic development, technological innovation, and environmental sustainability. While FDI can facilitate technological transfers and managerial advancements that enhance resource efficiency and promote environmentally friendly practices, its environmental impact varies based on regulatory frameworks and enforcement mechanisms. In countries with weak environmental regulations, FDI may lead to negative outcomes such as pollution hotspots, resource depletion, and ecosystem degradation. Similarly, trade openness can exacerbate environmental degradation through increased production, energy consumption, and waste generation. However, both FDI and trade openness can contribute positively to environmental sustainability when coupled with effective environmental policies, investment in green technology, and the promotion of sustainable practices. Thus, policymakers must strike a balance between economic development and environmental protection by implementing stringent environmental regulations, promoting clean technology transfer, and fostering sustainable development practices domestically and internationally. This research offers valuable insights for policymakers aiming to navigate the complexities of achieving carbon neutrality while ensuring sustainable economic growth in the N-11 countries. Full article

Arteries and veins develop different types of occlusive diseases and respond differently to injury. The biological reasons for this discrepancy are not well understood, which is a limiting factor for the development of vein-targeted therapies. This study contrasts human peripheral arteries and veins at the single-cell level, with a focus on cell populations with remodeling potential. Upper arm arteries (brachial) and veins (basilic/cephalic) from 30 organ donors were compared using a combination of bulk and single-cell RNA sequencing, proteomics, flow cytometry, and histology. The cellular atlases of six arteries and veins demonstrated a 7.8× higher proportion of contractile smooth muscle cells (SMCs) in arteries and a trend toward more modulated SMCs. In contrast, veins showed a higher abundance of endothelial cells, pericytes, and macrophages, as well as an increasing trend in fibroblasts. Activated fibroblasts had similar proportions in both types of vessels but with significant differences in gene expression. Modulated SMCs and activated fibroblasts were characterized by the upregulation of MYH10, FN1, COL8A1, and ITGA10. Activated fibroblasts also expressed F2R, POSTN, and COMP and were confirmed by F2R/CD90 flow cytometry. Activated fibroblasts from veins were the top producers of collagens among all fibroblast populations from both types of vessels. Venous fibroblasts were also highly angiogenic, proinflammatory, and hyper-responders to reactive oxygen species. Differences in wall structure further explain the significant contribution of fibroblast populations to remodeling in veins. Fibroblasts are almost exclusively located outside the external elastic lamina in arteries, while widely distributed throughout the venous wall. In line with the above, ECM-targeted proteomics confirmed a higher abundance of fibrillar collagens in veins vs. more basement ECM components in arteries. The distinct cellular compositions and transcriptional programs of reparative populations in arteries and veins may explain differences in acute and chronic wall remodeling between vessels. This information may be relevant for the development of antistenotic therapies. Full article

Understanding the association between booster vaccination and COVID-19 outcomes can help strengthen post-pandemic messaging and strategies to increase vaccination and reduce severe and long-term consequences of COVID-19. Using the Household Pulse Survey data collected from U.S. adults from 9 December 2022 to 13 February 2023 (n = 214,768), this study assessed the relationship between COVID-19 booster vaccination and COVID-19 outcomes (testing positive for COVID-19, moderate/severe COVID-19, and long COVID). Disparities were found in COVID-19 outcomes (e.g., testing positive for COVID-19, moderate/severe COVID-19, and long COVID) by sociodemographic characteristics, region of residence, food insecurity status, mental health status, disability status, and housing type. Receipt of a COVID-19 booster vaccination was negatively associated with testing positive for COVID-19 (aOR = 0.75, 95%CI: 0.72,0.79), having moderate/severe COVID-19 (aOR = 0.92, 95%CI: 0.88, 0.97), or having long COVID (aOR = 0.86 (0.80, 0.91)). Even among those who tested positive for COVID-19, those who received the booster vaccine were less likely to have moderate/severe COVID-19 and less likely to have long COVID. Communicating the benefits of COVID-19 booster vaccination, integrating vaccination in patient visits, and reducing access barriers can increase vaccination uptake and confidence for all individuals and protect them against the severe negative outcomes of COVID-19. Full article

Unhealthy lifestyle behaviors (ULBs) are common in early adolescence and could be worsened by Attention-Deficit/Hyperactivity Disorder (ADHD), as well as by specific psychosocial factors, such as stress and unbalanced (i.e., too high or low scores of) psychological well-being (PWB) dimensions. This multi-center study aimed to evaluate how interactions between ADHD symptoms and psychosocial factors associated with ULBs (i.e., Allostatic Overload and multidimensional Psychological Well-Being), considered as moderators, could affect the adoption of ULBs during adolescence. A total of 440 fourteen-year-old adolescents were recruited from six upper secondary schools in Bologna and Rome (Italy) and completed self-report questionnaires on ULBs, ADHD, and psychosocial factors. Relations between ADHD symptomatology and specific ULBs (i.e., impaired sleep, problematic Internet use) were moderated by variables deemed as “negative” (i.e., Allostatic Overload) or “positive” (i.e., PWB dimensions of Self-Acceptance, Personal Growth, Positive Relations, Purpose in Life, Environmental Mastery): when the “negative” moderator is absent and the levels of the “positive” moderators are higher, ULBs decrease among students with lower ADHD symptomatology but increase among students with more severe ADHD. Based on ADHD severity, interventions should aim at promoting a state of euthymia, which consists in balanced PWB dimensions and reflects the optimal level of well-being to fulfill one’s own potential and self-realization. Full article

Climate change is dramatically increasing the overall area of saline soils around the world, which is increasing by approximately two million hectares each year. Soil salinity decreases crop yields and, thereby, makes farming less profitable, potentially causing increased poverty and hunger in many areas. A solution to this problem is increasing the salt tolerance of crop plants. Transcription factors (TFs) within crop plants represent a key to understanding salt tolerance, as these proteins play important roles in the regulation of functional genes linked to salt stress. The basic leucine zipper (bZIP) TF has a well-documented role in the regulation of salt tolerance. To better understand how bZIP TFs are linked to salt tolerance, we performed a genome-wide analysis in wheat using the Chinese spring wheat genome, which has been assembled by the International Wheat Genome Sequencing Consortium. We identified 89 additional bZIP gene sequences, which brings the total of bZIP gene sequences in wheat to 237. The majority of these 237 sequences included a single bZIP protein domain; however, different combinations of five other domains also exist. The bZIP proteins are divided into ten subfamily groups. Using an in silico analysis, we identified five bZIP genes (ABF2, ABF4, ABI5, EMBP1, and VIP1) that were involved in regulating salt stress. By scrutinizing the binding properties to the 2000 bp upstream region, we identified putative functional genes under the regulation of these TFs. Expression analyses of plant tissue that had been treated with or without 100 mM NaCl revealed variable patterns between the TFs and functional genes. For example, an increased expression of ABF4 was correlated with an increased expression of the corresponding functional genes in both root and shoot tissues, whereas VIP1 downregulation in root tissues strongly decreased the expression of two functional genes. Identifying strategies to sustain the expression of the functional genes described in this study could enhance wheat’s salt tolerance. Full article

Comprehensive vegetation surveys are crucial for species selection and layout during the restoration of degraded island ecosystems. However, due to the poor accessibility of uninhabited islands, traditional quadrat surveys are time-consuming and labor-intensive, and it is challenging to fully identify the specific species and their spatial distributions. With miniaturized sensors and strong accessibility, high spatial and temporal resolution, Unmanned Aerial Vehicles (UAVs) have been extensively implemented for vegetation surveys. By collecting UAVs multispectral images and conducting field quadrat surveys on Anyu Island, we employ four machine learning models, namely Gradient Boosting Decision Tree (GBDT), Support Vector Machine (SVM), Random Forest (RF) and Multiple Classifier Systems (MCS). We aim to identify the dominant species and analyze their spatial distributions according to spectral characteristics, vegetation index, topographic factors, texture features, and canopy heights. The results indicate that SVM model achieves the highest (88.55%) overall accuracy (OA) (kappa coefficient = 0.87), while MCS model does not significantly improve it as expected. Acacia confusa has the highest OA among 7 dominant species, reaching 97.67%. Besides the spectral characteristics, the inclusion of topographic factors and texture features in the SVM model can significantly improve the OA of dominant species. By contrast, the vegetation index, particularly the canopy height even reduces it. The dominant species exhibit significant zonal distributions with distance from the coastline on the Anyu Island (p < 0.001). Our study provides an effective and universal path to identify and map the dominant species and is helpful to manage and restore the degraded vegetation on uninhabited islands. Full article

The inductive heating of a CMC susceptor for industrial applications can generate very high process temperatures. Thus, the behavior of a silicon carbide-based matrix with carbon-fiber-reinforced carbon (C/C-SiC) as a susceptor is investigated. Specifically, the influence of fiber length and the distribution of carbon fibers in the composite were investigated to find out the best parameters for the most efficient heating. For a multi-factorial set of requirements with a combination of filling levels and fiber lengths, a theoretical correlation of the material structure can be used as part of a digital model. Multi-physical simulation was performed to study the behavior of an alternating magnetic field generated by an inducing coil. The simulation results were verified by practical tests. It is shown that the inductive heating of a C/C-SiC susceptor can reach very high temperatures in a particularly fast and efficient way without oxidizing if it is ensured that a silicon carbide-based matrix completely encloses the fibers. Full article

Thermal comfort is a complex issue in the built environment due to the physiological and psychological differences of each individual in a building. There is a growing worry over the environmental implications of energy use as a result of the warming of the global climate and the growth in the number of instances of extreme weather events. Many review articles have been written, but these reviews have focused on a specific aspect of occupant behavior and thermal comfort. To research the trends of thermal comfort and energy, this research adopted mixed reviews, i.e., quantitative and qualitative, to understand the state-of-the-art factors affecting the thermal comfort of occupants concerning energy, different occupant modeling approaches, functions, and limitations. The in-depth qualitative discussion provides deeper insights into the impacts of occupant behaviors, factors affecting thermal comfort, and occupant behavior modeling approaches. This study classified occupant behaviors into five categories: occupant characteristics, perceptions of the occupant, realistic behaviors, heat gain, and occupant interactions with the system. It also went further to classify the factors affecting the thermal comfort of users based on past works of literature. These include structural, environmental, and human factors. It was concluded that factors that have the most significant impact on energy are human, structural, and environmental factors, respectively. In addition, most of the occupant behavior modeling approaches that have been used in past studies have pros and cons and cannot accurately predict human behaviors because they are stochastic. Future research should be conducted on thermal comfort for different building functions by examining the varied activity intensity levels of users, especially in educational or commercial buildings. Additionally, a proper investigation should be carried out on how thermal insulation of structural members influences thermal comfort. These should be compared in two similar buildings to understand occupant behavioral actions and energy consumption. Full article

Vascular co-option is a consequence of the direct interaction between perivascular cells, known as pericytes (PCs), and glioblastoma multiforme (GBM) cells (GBMcs). This process is essential for inducing changes in the pericytes’ anti-tumoral and immunoreactive phenotypes. Starting from the initial stages of carcinogenesis in GBM, PCs conditioned by GBMcs undergo proliferation, acquire a pro-tumoral and immunosuppressive phenotype by expressing and secreting immunosuppressive molecules, and significantly hinder the activation of T cells, thereby facilitating tumor growth. Inhibiting the pericyte (PC) conditioning mechanisms in the GBM tumor microenvironment (TME) results in immunological activation and tumor disappearance. This underscores the pivotal role of PCs as a key cell in the TME, responsible for tumor-induced immunosuppression and enabling GBM cells to evade the immune system. Other cells within the TME, such as tumor-associated macrophages (TAMs) and microglia, have also been identified as contributors to this immunomodulation. In this paper, we will review the role of these three cell types in the immunosuppressive properties of the TME. Our conclusion is that the cellular heterogeneity of immunocompetent cells within the TME may lead to the misinterpretation of cellular lineage identification due to different reactive stages and the identification of PCs as TAMs. Consequently, novel therapies could be developed to disrupt GBM-PC interactions and/or PC conditioning through vascular co-option, thereby exposing GBMcs to the immune system. Full article

Background: Complex post-traumatic stress disorder (CPTSD) is a severely debilitating recently added symptom cluster in the International Classification of Diseases (ICD-11). So far, only limited information on mental health treatment-uptake and -satisfaction of individuals with CPTSD is available. The aim of this study is to investigate these aspects in a representative sample of the German general population. Methods: Participants completed the International Trauma Questionnaire (ITQ) to identify participants with CPTSD, as well as questionnaires on mental health treatment uptake and satisfaction, adverse childhood experiences, anxiety, depression, working ability, personality functioning, and epistemic trust. Results: Of the included n = 1918 participants, n = 29 (1.5%) fulfilled the criteria for CPTSD. Participants with CPTSD had received mental health treatment significantly more often than participants with PTSD or depression (65.5% vs. 58.8% vs. 31.6%; p = 0.031) but reported significantly less symptom improvement (52.9% vs. 78.0% vs. 80.0%; p = 0.008). Lower levels of epistemic trust were associated with higher CPTSD symptoms (p < 0.001). Conclusions: Our study shows that while the vast majority of individuals with CPTSD had received mental health treatment, subjective symptom improvement rates are not satisfactory. CPTSD was associated with a broad number of comorbidities and impairments in functioning. Lower levels of epistemic trust may partially explain worse treatment outcomes. Full article

Background/Objectives: Although SARS-CoV-2 infection is a significant risk factor for venous thromboembolism (VTE), data on the impact of the use of non-invasive ventilation support (NIVS) to mitigate the risk of VTE during hospitalization are scarce. Methods: Data for 1471 SARS-CoV-2 patients, hospitalized in a single hub during the first pandemic wave, were collected from clinical records, including symptom duration and type, information on lung abnormalities on chest computed tomography (CT), laboratory parameters and the use of NIVS. Determining VTE occurrence during hospital stays was the main endpoint. Results: Patients with VTE (1.8%) had an increased prevalence of obesity (26% vs. 11%), diabetes (41% vs. 21%), higher CHA2DS2VASC score (4, IQR 2–5 vs. 3, IQR 1–4, age- and sex-adjusted, p = 0.021) and cough (65% vs. 44%) and experienced significantly higher rates of NIVS (44% vs. 8%). Using a stepwise multivariate logistic regression model, the prevalence of electrocardiogram abnormalities (odds ratio (OR) 2.722, 95% confidence interval (CI) 1.039–7.133, p = 0.042), cough (OR 3.019, 95% CI 1.265–7.202, p = 0.013), CHA2DS2-VASC score > 3 (OR 3.404, 95% CI 1.362–8.513, p = 0.009) and the use of NIVS (OR 15.530, 95% CI 6.244–38.627, p < 0.001) were independently associated with a risk of VTE during hospitalization. NIVS remained an independent risk factor for VTE even after adjustment for the period of admission within the pandemic wave. Conclusions: Our study suggests that NIVS is a risk factor for VTE during hospitalization in SARS-CoV-2 patients. Future studies should assess the optimal prophylactic strategy against VTE in patients with a SARS-CoV-2 infection candidate to non-invasive ventilatory support. Full article

Situational awareness (SA) is crucial in disaster response, enhancing the understanding of the environment. Social media, with its extensive user base, offers valuable real-time information for such scenarios. Although SA systems excel in extracting disaster-related details from user-generated content, a common limitation in prior approaches is their emphasis on single-modal extraction rather than embracing multi-modalities. This paper proposed a multimodal hierarchical graph-based situational awareness (MHGSA) system for comprehensive disaster event classification. Specifically, the proposed multimodal hierarchical graph contains nodes representing different disaster events and the features of the event nodes are extracted from the corresponding images and acoustic features. The proposed feature extraction modules with multi-branches for vision and audio features provide hierarchical node features for disaster events of different granularities, aiming to build a coarse-granularity classification task to constrain the model and enhance fine-granularity classification. The relationships between different disaster events in multi-modalities are learned by graph convolutional neural networks to enhance the system’s ability to recognize disaster events, thus enabling the system to fuse complex features of vision and audio. Experimental results illustrate the effectiveness of the proposed visual and audio feature extraction modules in single-modal scenarios. Furthermore, the MHGSA successfully fuses visual and audio features, yielding promising results in disaster event classification tasks. Full article

Accurate and stable positioning is significant for vehicle navigation systems, especially in complex urban environments. However, urban canyons and dynamic interference make vehicle sensors prone to disturbance, leading to vehicle positioning errors and even failures. To address these issues, an adaptive loosely coupled IMU/GNSS/LiDAR integrated navigation system based on factor graph optimization with sensor weight optimization and fault detection is proposed. First, the factor nodes and system framework are constructed based on error models of sensors, and the optimization method principle is derived. Second, the interactive multiple-model algorithm based on factor graph optimization (IMMFGO) is utilized to calculate and adjust sensor weights for global optimization, which will reduce the impact of disturbed sensors. Finally, a multi-stage fault detection, isolation, and recovery (MSFDIR) strategy is implemented based on the IMMFGO results and IMU pre-integration measurements, which can detect significant sensor faults and optimize the system structure. Vehicle experiments show that our IMMFGO method generally obtains better performance in positioning accuracy by 23.7% compared to adaptive factor graph optimization (AFGO) methods, and the MSFDIR strategy possesses the capability of fault sensor detection, which provides an essential reference for multi-source vehicle navigation systems in urban canyons. Full article

The design of hydraulic structures in the Arctic is complicated by shallow relief, which cause unique runoff processes that promote snow-damming and refreeze of runoff. We discuss the challenges encountered in modeling snowmelt runoff into two coastal freshwater lagoons in Utqiaġvik, Alaska. Stage-frequency curves with quantified uncertainty were required to design two new discharge gates that would allow snowmelt runoff flows through a proposed coastal revetment. To estimate runoff hydrographs arriving at the lagoons, we modeled snowpack accumulation and ablation using SnowModel which in turn was used to force a physically-based hydraulic runoff model (HEC-RAS). Our results demonstrate the successful development of stage-frequency curves by incorporating a Monte Carlo simulation approach that quantifies the variability in runoff timing and volume. Our process highlights the complexities of Arctic hydrology by incorporating significant delays in runoff onset due to localized snow accumulation and melting processes. This methodology not only addresses the uncertainty in snow-damming and refreeze processes which affect the arrival time of snowmelt inflow peaks, but is also adaptable for application in other challenging environments where secondary runoff processes are predominant. Full article

Defoliation is an inevitable abiotic stress for forage and turf grasses because harvesting, grazing, and mowing are general processes for their production and management. Vegetative regrowth occurs upon defoliation, a crucial trait determining the productivity and persistence of these grasses. However, the information about the molecular regulation of this trait is limited because it is still challenging to perform molecular analyses in forage and turf grasses. Here, we used rice as a model to investigate vegetative regrowth upon defoliation at physiological and molecular levels. This study analyzed stubble and regrown leaves following periodic defoliation using two rice varieties with contrasting regrowth vigor. Vigorous regrowth was associated with maintained chlorophyll content and photosystem II performance; a restricted and promoted mRNA accumulation of sucrose synthase (SUS) I and III subfamilies, respectively; and reduced enzymatic activity of SUS. These results suggest that critical factors affecting vegetative regrowth upon defoliation are de novo carbohydrate synthesis by newly emerged leaves and proper carbohydrate management in leaves and stubble. Physiological and genetic analyses have demonstrated that the reduced sensitivity to and inhibited biosynthesis of cytokinin enhance regrowth vigor. Proper regulation of these metabolic and hormonal pathways identified in this study can lead to the development of new grass varieties with enhanced regrowth vigor following defoliation. Full article