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AI-Driven Decentralized IoT for Secure and Scalable Healthcare
No full textAI Innovations in the IoT for Real-Time Patient Monitoring On one hand, the current traditional centralized healthcare architecture poses numerous issues, including data privacy, delay, and security. Here, we present an AI-enabled decentralized IoT architecture to address such challenges during a pandemic and critical care settings. This work presents our architecture to enhance the effectiveness of the current available federated learning, blockchain, and edge computing approach, maximizing data privacy, minimizing latency, and improving other general system metrics. Experimental results demonstrate transaction latency, energy consumption, and data throughput orders of magnitude lower than competitive cloud solutions
Characterization of Double Injection Hydrogen Jet using Acetone-PLIF in a Constant Volume Chamber
No full textAs global warming intensifies, hydrogen is recognized as a viable alternative to conventional fossil fuels thanks to its potential for clean combustion. However, the direct application of hydrogen in internal combustion engines remains challenging due to the lack of detailed knowledge in the mixture formation process. A crucial aspect is understanding the mixture distribution of hydrogen, which significantly impacts combustion efficiency and pollutant formation. This study investigates the effect of double injection on the mixing behavior of hydrogen using Planar Laser-induced Fluorescence (PLIF). Simultaneously, Schlieren imaging was carried out to validate the PLIF measurements and confirm for any slipping between the acetone and hydrogen. The imaging results demonstrated a strong correlation between the PLIF and Schlieren images, confirming that the acetone-doped PLIF effectively captures the hydrogen jet structure with minimal interference from hydrogen’s high diffusivity. These results suggest that this approach can reliably measure the qualitative distribution of the hydrogen mixture. Furthermore, the optimization of double injection parameters demonstrates the potential to form a flammable mixture near the spark plug by promoting jet area expansion
Local nutrient addition drives plant diversity losses but not biotic homogenization in global grasslands
Get PDFNutrient enrichment typically causes local plant diversity declines. A common but untested expectation is that nutrient enrichment also reduces variation in nutrient conditions among localities and selects for a smaller pool of species, causing greater diversity declines at larger than local scales and thus biotic homogenization. Here we apply a framework that links changes in species richness across scales to changes in the numbers of spatially restricted and widespread species for a standardized nutrient addition experiment across 72 grasslands on six continents. Overall, we find proportionally similar species loss at local and larger scales, suggesting similar declines of spatially restricted and widespread species, and no biotic homogenization after 4 years and up to 14 years of treatment. These patterns of diversity changes are generally consistent across species groups. Thus, nutrient enrichment poses threats to plant diversity, including for widespread species that are often critical for ecosystem functions
Refining Control, Charging, and Battery Chemistry for CO2 e Savings in Heavy-Duty Off-Road Plug-In Series Hybrid
No full textWith current and future regulations continuing to drive reductions in carbon dioxide equivalent (CO2e) emissions in the on-road industry, the off-road industry is also likely to be regulated for fuel and CO2e savings. This work focuses on converting a heavy-duty off-road material handler from a conventional diesel powertrain to a plug-in series hybrid, achieving a 49% fuel reduction and 29% CO2e reduction via simulation. Control strategies were refined for energy savings, including a regenerative braking strategy to increase regenerative braking and a load-following hydraulic strategy to decrease electrical energy consumption. The load-following hydraulic control shuts off the hydraulic electric machine when it is not needed—an approach not previously seen in a load-sensing, pressure-compensated system. These strategies achieved a 24.1% fuel savings, resulting in total savings of 61% in fuel and 41% in CO2e in the plug-in series compared to the conventional machine. Beyond control strategies, this study evaluated battery chemistry and charging strategy refinements for total cost of ownership (TCO) and lifetime CO2e. LFP batteries emerged as the most cost-effective and least emitting due to their longer lifespan, which reduced replacement frequency. Charging comparisons showed that Level 2 charging (L2C) typically resulted in lower TCO but higher lifetime CO2e than DC fast charging (DCFC). DCFC costs were heavily influenced by local demand charges, and DCFC emissions were heavily influenced by local grid emissions
Bayesian Analysis of Longitudinal Ordinal Data with Missing Values Using Multivariate Probit Models
No full textIn this paper, we propose efficient Bayesian methods to analyze longitudinal ordinal data with missing values using multivariate probit models. Longitudinal ordinal data with substantial missing values are ubiquitous in many scientific fields. Specifically, we develop the Markov chain Monte Carlo (MCMC) sampling methods based on the non-identifiable multivariate probit models and further compare their performance with the one based on the identifiable multivariate probit models. We carried out our investigation through simulation studies, which show that the proposed methods can handle substantial missing values and the method with marginalizing the redundant parameters based on the non-identifiable model outperforms the others in the mixing and convergences of the MCMC sampling components. We then present an application using data from the Russia Longitudinal Monitoring Survey-Higher School of Economics (RLMS-HSE)
ThermalTrack Dataset- Training Images- Fused RGB LWIR- sequence 7
Get PDFWe present a wheel track detection system that leverages RGB- Thermal (RGB-T) imaging, where thermal channels reveal critical temperature differentials between compacted tracks and loose snow- tracks exhibit higher thermal inertia and lower reflectivity, emitting stronger radiation signatures even in visually homogeneous conditions. By fusing these distinctive thermal patterns with RGB spatial information, our method reliably identifies navigable tracks, enabling robust path-following in complete white-out conditions where snow textures and terrain features become indistinguishable
Boron nitride nanosheets, quantum dots, and dots: Synthesis, properties, and biomedical applications
Get PDFThis review examines three aspects of hexagonal boron nitride (h-BN) nanomaterials: properties, synthesis methods, and biomedical applications. We focus the scope of review on three types of h-BN nanostructures: boron nitride nanosheets (BNNSs, few-layered h-BN, larger than ∼100 nm in lateral dimensions), boron nitride quantum dots (BN QDs, smaller than ∼10 nm in all dimensions, with inherent excitation-dependent fluorescence), and boron nitride dots (BN dots, smaller than ∼10 nm in all dimensions, wide bandgap without noise fluorescence). The synthesis methods of BNNSs, BN QDs, and BN dots are summarized in top-down and bottom-up approaches. Future synthesis research should focus on the scalability and the quality of the products, which are essential for reproducible applications. Regarding biomedical applications, BNNSs were used as nanocarriers for drug delivery, mechanical reinforcements (bone tissue engineering), and antibacterial applications. BN QDs are still limited for non-specific bioimaging applications. BN dots are used for the small dimension to construct high-brightness probes (HBPs) for gene sequence detections inside cells. To differentiate from other two-dimensional materials, future applications should focus on using the unique properties of BN nanostructures, such as piezoelectricity, boron neutron capture therapy (BNCT), and their electrically insulating and optically transparent nature. Examples would be combining BNCT and chemo drug delivery using BNNSs, and using BN dots to form HBPs with enhanced fluorescence by preventing fluorescence quenching using electrically insulating BN dots
Environmental Life Cycle Assessment of Class A Biosolids Production Using Conventional and Low-Cost, Low-Tech Processes at Small Water Resource Recovery Facilities
Get PDFProducing Class A biosolids that can be distributed or land-applied without restriction is a beneficial way to reuse wastewater treatment solids. For small water resource recovery facilities (WRRFs) in particular, low-cost, low-tech (LCLT) processes may be an appealing alternative to conventional technologies for producing Class A biosolids, such as processes to further reduce pathogens (PFRPs). Conventional Class A biosolids treatment processes tend to be energy-intensive and involve complex equipment and operations. However, a systematic comparison of the overall sustainability of conventional processes and LCLT alternatives for producing Class A biosolids to aid decision makers in selecting treatment processes is not readily available. Therefore, this study used life cycle assessments to compare five Class A biosolids treatment processes, including three conventional processes—Composting, Direct Heat Drying, and temperature-phased anaerobic digestion (TPAD)—and two LCLT processes—Air Drying, and long-term Lagoon Storage followed by Air Drying—on the basis of their environmental impacts. The environmental impacts were normalized to facilitate a comparison of the processes. The results indicate that Composting and Direct Heat Drying had the most significant environmental impacts, primarily from the biogenic emissions during Composting and the natural gas requirements for Direct Heat Drying. In comparison, TPAD and Air Drying had the lowest environmental impacts, and Lagoon Storage had intermediate impacts. Thus, LCLT processes may be more sustainable than some, but not all, conventional PFRPs
EXPLORING THE ROLE OF BRAIN-DERIVED EXTRACELLULAR VESICLES IN SALT-SENSITIVE HYPERTENSION
No full textHypertension is a leading risk factor for cardiovascular disease worldwide. Among its various contributing factors, unhealthy lifestyle preferences, particularly excessive salt consumption, significantly elevate the risk of hypertension in salt-sensitive individuals. Growing evidence suggests that the brain plays a crucial role in hypertension through overactive endocrine and autonomic responses. Within the brain, the hypothalamic paraventricular nucleus (PVN), an important region in the control of blood pressure (BP), has been recognized as a key driver in hypertension. PVN dysfunction, characterized by inflammation, oxidative stress, enhanced arginine vasopressin (AVP) release, activation of the renin-angiotensin system (RAS), and overactivity of pre-sympathetic neurons, has been implicated in hypertension progression. Recently, extracellular vesicles (EVs), known for mediating intercellular communication by transporting various bioactive cargo, have been linked to hypertension development. However, the role of brain-derived EVs in salt-sensitive hypertension, particularly in relation to PVN dysfunction, remains largely unknown. Study 1 highlighted the acute effects of brain-derived EVs from hypertensive salt-sensitive rats in primary neuronal cultures and brain PVN. Isolated EVs significantly induced neuroinflammation and oxidative stress in the PVN as well as circumventricular organ lamina terminalis. Study 2 explored the long-term effects of central administration of brain-derived EVs from salt-sensitive hypertensive rats on BP regulation. Isolated EVs alone did not increase BP, but sufficient to increase PVN neural activity, enhanced AVP production and induced oxidative stress. Enhanced neural activity and AVP production was also found in the supraoptic nucleus (SON). With combination of high salt, brain-derived EVs from hypertensive rats increased BP, along with elevated water intake and urine output in rats. Study 3 investigated the role of EVs in regulating the RAS within the PVN, with a primary focus on the angiotensin II type 1 receptor (AT1R), a key receptor component of the RAS. Loading small interfering RNA targeting AT1R into brain-derived EVs from hypertensive rats abolished the EV-induced increase in BP and reduced mitochondrial reactive oxygen species (mtROS) accumulation in AT1R+ cells. Collectively, this work uncovered a novel role of brain-derived EVs in salt-sensitive hypertension and highlighted the potential of EV-based drug delivery systems for hypertension treatment
Evaluation of 3D ROS-based Simultaneous Localization and Mapping Under Noisy Conditions for Uncrewed Surface Vessels Navigation
Get PDFAccurate mapping is crucial for the safe operation of Uncrewed Surface Vessels (USV), especially when relying on 3D LiDAR sensors, which are susceptible to noise from factors like water spray and turbulent surface conditions. This paper investigates the performance of two prominent 3D LiDAR mapping algorithms---HDL graph SLAM and Point LIO---when subjected to injected noise models that mimic real-world maritime disturbances. By introducing controlled noise into the sensor data, we evaluate how each algorithm maintains mapping accuracy under degraded conditions. Quantitative metrics such as Structural Similarity Index Measure (SSIM) and Intersection over Union (IoU) are utilized to assess and compare the robustness of the generated maps. The study will highlight the open-source ROS mapping algorithms strengths and limitations in noisy environments. These findings aim to inform the development of more robust mapping strategies, ultimately enhancing the reliability and safety of USV navigation in challenging maritime settings