Dynamical Variables Research Articles

Geographical Peculiarities of Pinus sibirica Du Tour Natural Regeneration as Related to its Seed Crops

Forest ecology faces a significant challenge in understanding the dynamics of populations of forest-forming trees during their renewal phase, as it shapes the subsequent development and structure of forest ecosystems. The forest regeneration process relies on the dynamics of the seed yield of the woody plants and the unique characteristics of their distribution. In the case of the Cembrae sp. five-needled pines belonging, which have wingless seeds, their renewal is closely linked to the activities of Nucifraga sp. birds that scatter the seeds to create food reserves in the soil. This research aims to explore the geographical variations of Siberian stone pine (Pinus sibirica Du Tour) natural regeneration as a function of seed abundance. This study was conducted in three Russian mountain regions known for their forests predominated by Pinus sibirica: the Aldan Highlands, the Northern Urals, and the Khamar-Daban Mountains. It was discovered that each region exhibited distinct patterns in both cone yields and Pinus sibirica regeneration. The fluctuations in the thin-billed nutcracker (Nucifraga caryocatactes macrorhynchos Brehm C. L.) populations during the seed harvest season, influenced by the nature of the seed production dynamics in each region, we believed to play a major role in the quantity of Pinus sibirica seedlings appearing in the subsequent year. These findings explain the observed variations in the renewal dynamics of annual emergent seedlings of Pinus sibirica and its reliance on cone yield in the examined regions.

Ultrasound biomicroscopy analysis of ciliary muscle dynamics and its relation to intra-ocular pressure after phacoemulsification in dogs.

This study investigates the relationship between ciliary muscle dynamics, thickness, and the regulation of intraocular pressure (IOP), focusing on the progression of cataracts and changes post-phacoemulsification. It explores how these factors impact canine ocular health, particularly in the context of cataract development and subsequent surgical intervention. Data was collected using Ultrasound Biomicroscopy (UBM) from dogs at the Veterinary Medical Teaching Hospital of Chungbuk National University, Korea. The study involved 57 eyes from 35 dogs, categorized into five groups: 13 normal eyes, 14 with incipient cataracts, 12 with immature cataracts, 6 with mature cataracts, and 12 post-phacoemulsification. UBM measurements assessed various ciliary muscle parameters including ciliary body axial length (CBAXL), ciliary process-sclera angle (CPSA), longitudinal fibers of ciliary muscle thickness (Lf-CMT), and longitudinal and radial fibers of ciliary muscle thickness (LRf-CMT). Findings indicated a decrease in CBAXL and an increase in Lf-CMT as cataracts progressed in severity. Post-phacoemulsification, there was a notable increase in CBAXL and a decrease in CPSA, Lf-CMT, and LRf-CMT, compared to both cataractous and normal eyes. Regression analysis revealed a significant positive association between CBAXL and IOP, alongside a negative association between Lf-CMT and IOP. These findings suggest that variations in ciliary muscle dynamics and thickness, as influenced by cataract progression and phacoemulsification, have distinct impacts on intraocular pressure. The study proposes that phacoemulsification leads to ciliary muscle contraction, causing an inward and anterior movement of the ciliary muscle. This movement results in the narrowing of the ciliary cleft and constriction of the unconventional outflow pathway, potentially causing an increased risk of glaucoma post-surgery. Our research contributes to understanding the anatomical and physiological changes in the canine eye following cataract surgery and underscores the importance of monitoring IOP and ciliary muscle dynamics in these patients.

Machine-learning and mechanistic modeling of metastatic breast cancer after neoadjuvant treatment.

Clinical trials involving systemic neoadjuvant treatments in breast cancer aim to shrink tumors before surgery while simultaneously allowing for controlled evaluation of biomarkers, toxicity, and suppression of distant (occult) metastatic disease. Yet neoadjuvant clinical trials are rarely preceded by preclinical testing involving neoadjuvant treatment, surgery, and post-surgery monitoring of the disease. Here we used a mouse model of spontaneous metastasis occurring after surgical removal of orthotopically implanted primary tumors to develop a predictive mathematical model of neoadjuvant treatment response to sunitinib, a receptor tyrosine kinase inhibitor (RTKI). Treatment outcomes were used to validate a novel mathematical kinetics-pharmacodynamics model predictive of perioperative disease progression. Longitudinal measurements of presurgical primary tumor size and postsurgical metastatic burden were compiled using 128 mice receiving variable neoadjuvant treatment doses and schedules (released publicly at https://zenodo.org/records/10607753). A non-linear mixed-effects modeling approach quantified inter-animal variabilities in metastatic dynamics and survival, and machine-learning algorithms were applied to investigate the significance of several biomarkers at resection as predictors of individual kinetics. Biomarkers included circulating tumor- and immune-based cells (circulating tumor cells and myeloid-derived suppressor cells) as well as immunohistochemical tumor proteins (CD31 and Ki67). Our computational simulations show that neoadjuvant RTKI treatment inhibits primary tumor growth but has little efficacy in preventing (micro)-metastatic disease progression after surgery and treatment cessation. Machine learning algorithms that included support vector machines, random forests, and artificial neural networks, confirmed a lack of definitive biomarkers, which shows the value of preclinical modeling studies to identify potential failures that should be avoided clinically.

Okadaic acid as a major problem for the seafood safety (Mytilus galloprovincialis) and the dynamics of toxic phytoplankton in the Slovenian coastal sea (Gulf of Trieste, Adriatic Sea)

This article presents the first results on shellfish toxicity in the Slovenian sea (Gulf of Trieste, Adriatic Sea) since the analytical methods for the detection of biotoxins (PSP, ASP, DSP and other lipophilic toxins) in bivalve molluscs were included in the national monitoring program in 2013. In addition to toxins, the composition and abundance of toxic phytoplankton and general environmental characteristics of the seawater (surface temperature and salinity) were also monitored.During the 2014–2019 study period, only lipophilic toxins were detected (78 positive tests out of 446 runs), of which okadaic acid (OA) predominated in 97 % of cases, while dinophysistoxin-2 and yessotoxins only gave a positive result in one sampling event each. The number of samples that did not comply with the EC Regulation for the OA group was 17 or 3.8 % of all tests performed, all of which took place from September to November, while a few positive OA tests were also recorded in December, April, and May. This toxicity pattern was consistent with the occurrence pattern of the five most common DSP-producing dinoflagellates, which was supported by the development of warm and thermohaline stratified waters: Dinophysis caudata, D. fortii, D. sacculus, D. tripos and Phalacroma rotundatum. The strong correlation (r = 0.611, p < 0.001) between D. fortii, reaching abundances of up to 950 cells L−1, and OA suggests that D. fortii is the main cause of OA production in Slovenian waters.Strong interannual variations in OA and phytoplankton dynamics, exacerbated by the effects of anthropogenic impacts in this coastal ecosystem, reduce the predictability of toxicity events and require continuous and efficient monitoring. Our results also show that the introduction of the LC-MS/MS method for lipophilic toxins has improved the management of aquaculture activities, which was not as accurate based on mouse bioassays.

Intelligent Structure Identification and Robust Control Implementation

This study outlines a comprehensive strategy for designing and implementing robust controllers tailored for intelligent structures. This study presents a robust control-based structural identification technique that uses the input/output data of the system to construct a state-space mode and frequency domain. To reduce vibrations, a robust controller is created using the control Simulink model. The identification and robust control of smart structures using Simulink involve a combination of system identification techniques and control design within the MATLAB Simulink environment. The key challenge is dealing with uncertainties and variations in system dynamics. Robust control methods have been employed to suppress the vibrations during dynamic disturbances. These methods are important for mechanical systems operating under stochastic loading conditions.

Unsupervised restoration of a complex learned behavior after large-scale neuronal perturbation.

Reliable execution of precise behaviors requires that brain circuits are resilient to variations in neuronal dynamics. Genetic perturbation of the majority of excitatory neurons in HVC, a brain region involved in song production, in adult songbirds with stereotypical songs triggered severe degradation of the song. The song fully recovered within 2 weeks, and substantial improvement occurred even when animals were prevented from singing during the recovery period, indicating that offline mechanisms enable recovery in an unsupervised manner. Song restoration was accompanied by increased excitatory synaptic input to neighboring, unmanipulated neurons in the same brain region. A model inspired by the behavioral and electrophysiological findings suggests that unsupervised single-cell and population-level homeostatic plasticity rules can support the functional restoration after large-scale disruption of networks that implement sequential dynamics. These observations suggest the existence of cellular and systems-level restorative mechanisms that ensure behavioral resilience.

Arterial Lesion Location and Outcomes of Intracranial Atherosclerotic Disease.

Intracranial atherosclerosis is a leading cause of stroke with a high recurrence rate despite treatment. Numerous factors are proposed to influence stroke recurrence due to intracranial atherosclerosis including lesion eccentricity, plaque characteristics, and computational fluid dynamic metrics, such as wall shear stress. An overlooked variable that intrinsically relates to intracranial atherosclerosis is the location of the arterial segment where the lesion occurs. Variations in cerebral blood flow, arterial anatomy, and flow dynamics are likely drivers of initial lesion development and thus likely to influence stroke recurrence. To date, treatment trials of intracranial atherosclerosis have not considered arterial segment lesion location as an independent variable, failing to account for variations in flow dynamics between each artery. There are limited available data on differences between arterial segments, confined to only post hoc analyses. In this review, we summarize available data on such differences between arterial segments. With the limited arterial segment data available, multiple differences in recurrence of stroke in territory of lesion were identified across trials.

Understanding the Saffron Corm Development-Insights into Histological and Metabolic Aspects.

The reproduction of Crocus sativus L., a sterile triploid plant, is carried out exclusively through corms, whose size determines the saffron yield. The development of daughter corms (DC) is supported by photoassimilates supplied by the leaves as well as by the mother corms (MC). While biomass partitioning during DC development is well studied, growth dynamics in terms of cell number and size, the involved meristems, as well as carbohydrate partition and allocation, are not yet fully understood. We conducted a comprehensive study into saffron corm growth dynamics at the macroscopic and microscopic levels. Variations in carbohydrate content and enzymatic activities related to sucrose metabolism in sources and sinks were measured. Two key meristems were identified. One is involved in vascular connections between DC and MC. The other is a thickening meristem responsible for DC enlargement. This research explains how the previously described phases of corm growth correlate with variations in cell division, enlargement dynamics, and carbohydrate partitioning among organs. Results also elucidated that the end of DC growth relates to a significant drop in MC root biomass, limiting the water supply for the DC growth, and establishing the onset of leaf wilting. The lack of starch accumulation in aged leaf cells is noteworthy, as is the accumulation of lipids. We hypothesize a signaling role of sugars in DC growth initiation, stop, and leaf aging. Finally, we established a predominant role of sucrose synthase as a sucrolytic enzyme in the maintenance of the high flux of carbon for starch synthesis in DC. Together, the obtained results pave the way for the definition of strategies leading to better control of saffron corm development.

A Quantitative ABCD Analysis of Factors Driving Share Price Volatility in the Indian Pharmaceutical Sector

Purpose: This research employs an innovative ABCD (Advantages, Benefits, Constraints, and Disadvantages) analysis framework to intricately explore and evaluate the diverse factors influencing share price volatility in the Indian Pharmaceutical Sector. Delving into both individual and systemic characteristics, the study quantitatively assesses the effectiveness of various elements impacting share prices. Each component related to share price movements is meticulously assigned a score or weightage, providing a nuanced understanding of their respective contributions. Design: The researcher utilized focused group interviews to collect participants’ viewpoints on the factors influencing share price dynamics in the Indian pharmaceutical industry. Opinions were obtained through designated measurements, and the collected data underwent subsequent quantitative analysis. Findings: In the specific context of the present study, which focuses on the quantitative ABCD analysis of factors driving share price fluctuations in the Indian pharma industry, the research findings underscore the notable impact of advantageous factors on volatility. The outcome of the ABCD analysis substantiates the effectiveness of the concepts/ideas related to Factors Driving Share Price Volatility in the Indian Pharmaceutical Sector. Originality: This research introduces a novel application of the ABCD analytical paradigm to investigate factors influencing variations in the pricing dynamics of shares in the Indian pharmaceutical industry. While ABCD analysis is prevalent in diverse areas, this study pioneers a unique exploration within the pharmaceutical domain. By identifying and evaluating the crucial elements influencing share prices, this work contributes to the originality of studies in the field, presenting a distinctive approach to understanding the dynamics of the Indian pharmaceutical market. Type of Paper: Empirical Analysis.

Recruitment dynamics of juvenile salmonids: Comparisons among populations and with classic case studies.

Understanding recruitment, the process by which individuals are added to a population or to a fishery, is critical for understanding population dynamics and facilitating sustainable fisheries management. Important variation in recruitment dynamics is observed among populations, wherein some populations exhibit asymptotic productivity and others exhibit overcompensation (i.e., compensatory density-dependence in recruitment). Our ability to understand this interpopulation variability in recruitment patterns is limited by a poor understanding of the underlying mechanisms, such as the complex interactions between density dependence, recruitment, and environment. Furthermore, most studies on recruitment are conducted using an observational design with long time series that are seldom replicated across populations in an experimentally controlled fashion. Without proper replication, extrapolations between populations are tenuous, and the underlying environmental trends are challenging to quantify. To address these issues, we conducted a field experiment manipulating stocking densities of juvenile brook trout Salvelinus fontinalis in three wild populations to show that these neighboring populations-which exhibit divergent patterns of density dependence due to environmental conditions-also have important differences in recruitment dynamics. Testing against four stock-recruitment models (density independent, linear, Beverton-Holt, and Ricker), populations exhibited ~twofold variation in asymptotic productivity, with no overcompensation following a Beverton-Holt model. Although environmental variables (e.g., temperature, pH, depth, substrate) correlated with population differences in recruitment, they did not improve the predictive power in individual populations. Comparing our patterns of recruitment with classic salmonid case studies revealed that despite differences in the shape and parameters of the curves (i.e., Ricker vs. Beverton-Holt), a maximum stocking density of about five YOY fish/m2 emerged. Higher densities resulted in very marginal increases in recruitment (Beverton-Holt) or reduced recruitment due to overcompensation (Ricker).

Accounting intra-annual variability in mortality and recruitment in stock status evaluation of Parapenaeopsis stylifera fishery of north-eastern Arabian Sea under moderate data scenario

Length-based integrated mixed effect (LIME) approach was applied for the assessment of Parapenaeopsis stylifera stock, the most prominent penaeid resource along Gujarat coast. Month was selected as a temporal step size to improve estimate precision and capture intra-annual variation in population dynamics. Catch was provided as an additional input to create a moderate data scenario and reduce bias in estimates of reference indices. The values of key life history priors Linf, K, M, t0, Lm50, Lm95 were 160.59 mm total length (TL), 1.68 yr−1, 2.406 yr−1, −0.01 yr, 89.1 mm TL, 95.06 mm TL, respectively. The LWR was established as W = 0.0117*TL2.652. The estimated SPR ranged between 0.33 and 0.70. The monthly fishing mortality was estimated between 0.06 and 0.31. In 37.5% of the observed month, the fishing mortality was above optimum, which by and large coincides with the peak fishing months. The recruitment is continuous, with a coefficient of variation of only 18.5%. Based on these indices, the stock can be considered as healthy or sustainable. A continuous monitoring and collection of abundance data through experimental surveys are recommended as a future course of action.

Rational design of a near-infrared fluorescent probe for monitoring butyrylcholinesterase activity and its application in development of inhibitors.

Butyrylcholinesterase (BChE) is widely expressed in multiple tissues and has a vital role in several key human disorders, such as Alzheimer's disease and tumorigenesis. However, the role of BChE in human disorders has not been investigated. Thus, to quantitatively detect and visualize dynamical variations in BChE activity is essential for exploring the biological roles of BChE in the progression of a number of human disorders. Herein, based on the substrate characteristics of BChE, we customized and synthesized three near-infrared (NIR) fluorescent probe substrates with cyanine-skeleton, and finally selected a NIR fluorescence probe substrate named CYBA. The CYBA demonstrated a significant increase in fluorescence when interacting with BChE, but mainly avoided AChE. Upon the addition of BChE, CYBA could be specifically hydrolyzed to TBO, resulting in a significant NIR fluorescence signal enhancement at 710nm. Systematic evaluation revealed that CYBA exhibited exceptional chemical stability in complex biosamples and possessed remarkable selectivity and sensitivity towards BChE. Moreover, CYBA was successfully applied for real-time imaging of endogenous BChE activity in two types of nerve-related living cells. Additionally, CYBA demonstrated exceptional stability in the detection of complex biological samples in plasma recovery studies (97.51%-104.01%). Furthermore, CYBA was used to construct a high-throughput screening (HTS) method for BChE inhibitors using human plasma as the enzyme source. We evaluated inhibitory effects of a series of natural products and four flavonoids were identified as potent inhibitors of BChE. Collectively, CYBA can serve as a practical tool to track the changes of BChE activity in complicated biological environments due to its excellent capabilities.

Sex-Related Differences in Shoulder Complex Joint Dynamics Variability During Pediatric Manual Wheelchair Propulsion.

More than 80% of adult manual wheelchair users with spinal cord injuries will experience shoulder pain. Females and those with decreased shoulder dynamics variability are more likely to experience pain in adulthood. Sex-related differences in shoulder dynamics variability during pediatric manual wheelchair propulsion may influence the lifetime risk of pain. We evaluated the influence of sex on 3-dimensional shoulder complex joint dynamics variability in 25 (12 females and 13 males) pediatric manual wheelchair users with spinal cord injury. Within-subject variability was quantified using the coefficient of variation. Permutation tests evaluated sex-related differences in variability using an adjusted critical alpha of P = .001. No sex-related differences in sternoclavicular or acromioclavicular joint kinematics or glenohumeral joint dynamics variability were observed (all P ≥ .042). Variability in motion, forces, and moments are considered important components of healthy joint function, as reduced variability may increase the likelihood of repetitive strain injury and pain. While further work is needed to generalize our results to other manual wheelchair user populations across the life span, our findings suggest that sex does not influence joint dynamics variability in pediatric manual wheelchair users with spinal cord injury.

Multi-rate modulation encoding via unsupervised learning for audio event detection

Technologies in healthcare, smart homes, security, ecology, and entertainment all deploy audio event detection (AED) in order to detect sound events in an audio recording. Effective AED techniques rely heavily on supervised or semi-supervised models to capture the wide range of dynamics spanned by sound events in order to achieve temporally precise boundaries and accurate event classification. These methods require extensive collections of labeled or weakly labeled in-domain data, which is costly and labor-intensive. Importantly, these approaches do not fully leverage the inherent variability and range of dynamics across sound events, aspects that can be effectively identified through unsupervised methods. The present work proposes an approach based on multi-rate autoencoders that are pretrained in an unsupervised way to leverage unlabeled audio data and ultimately learn the rich temporal dynamics inherent in natural sound events. This approach utilizes parallel autoencoders that achieve decompositions of the modulation spectrum along different bands. In addition, we introduce a rate-selective temporal contrastive loss to align the training objective with event detection metrics. Optimizing the configuration of multi-rate encoders and the temporal contrastive loss leads to notable improvements in domestic sound event detection in the context of the DCASE challenge.

Anthropogenic particle concentrations and fluxes in an urban river are temporally variable and impacted by storm events.

Anthropogenic particles (AP), which include microplastics and other synthetic, semisynthetic, and anthropogenically modified materials, are pollutants of concern in aquatic ecosystems worldwide. Rivers are important conduits and retention sites for AP, and time series data on the movement of these particles in lotic ecosystems are needed to assess the role of rivers in the global AP cycle. Much research assessing AP pollution extrapolates stream loads based on single time point measurements, but lotic ecosystems are highly variable over time (e.g., seasonality and storm events). The accuracy of models describing AP dynamics in rivers is constrained by the limited studies that examine how frequent changes in discharge drive particle retention and transport. This study addressed this knowledge gap by using automated, high-resolution sampling to track AP concentrations and fluxes during multiple storm events in an urban river (Milwaukee River) and comparing these measurements to commonly monitored water quality metrics. AP concentrations and fluxes varied significantly across four storm events, highlighting the temporal variability of AP dynamics. When data from the sampling periods were pooled, there were increases in particle concentration and flux during the early phases of the storms, suggesting that floods may flush AP into the river and/or resuspend particles from the benthic zone. AP flux was closely linked to river discharge, suggesting large loads of AP are delivered downstream during storms. Unexpectedly, AP concentrations were not correlated with other simultaneously measured water quality metrics, including total suspended solids, fecal coliforms, chloride, nitrate, and sulfate, indicating that these metrics cannot be used to estimate AP. These data will contribute to more accurate models of particle dynamics in rivers and global plastic export to oceans. PRACTITIONER POINTS: Anthropogenic particle (AP) concentrations and fluxes in an urban river varied across four storm events. AP concentrations and fluxes were the highest during the early phases of the storms. Storms increased AP transport downstream compared with baseflow. AP concentrations did not correlate with other water quality metrics during storms.

Variation in emotion dynamics over time is associated with future relationship outcomes.

Romantic relationships are defined by emotion dynamics, or how the emotions of one partner at a single timepoint can affect their own emotions and the emotions of their partner at the next timepoint. Previous research has shown that the level of these emotion dynamics plays a role in determining the state and quality of the relationship. However, this research has not examined whether the estimated emotion dynamics change over time, and how the change in these dynamics might relate to relationship outcomes, despite changes in dynamics being likely to occur. We examined whether the magnitude of variation in emotion dynamics over time was associated with relationship outcomes in a sample of 148 couples. Time-varying vector autoregressive models were used to estimate the emotion dynamics for each couple, and the average and standard deviation of the dynamics over time was related to relationship quality and relationship dissolution 1-2 years later. Our results demonstrate that certain autoregressive and cross-lagged parameters do show significant variation over time, and that this variation is associated with relationship outcomes. Overall, this study demonstrates the importance of accounting for change in emotion dynamics over time, and the relevance of this change to the prediction of future outcomes.

Small-scale variation of atmospheric dynamics applying chaos theory, case study

Characterization and knowledge of the variability of atmospheric dynamics on a small scale in the city of Riobamba, Ecuador, are achieved through the chaos theory. Meteorological data is taken every hour during four years, including variables such as wind speed, wind direction, incident radiation, temperature, and humidity, from the ESPOCH, SAN JUAN, and QUIMIAG weather stations in the canton of Riobamba. The van Ulden and Hostlang models are used to calculate the Obukhov length, surface heat fluxes, and latent heat flux. The chaos theory is applied to study the variation of atmospheric microdynamics. The Lyapunov coefficients, Kolmogorov-Sinai entropy, and Kaplan-Yorke fractal dimension are determined. Before analysis, noise reduction is necessary due to the lack of correlation, especially in the Obukhov length. This research follows a longitudinal design and employs quantitative and explanatory methods based on data analysis, statistical-mathematical techniques, and inductive-deductive approaches. The results indicate a highly variable system, reflected in a high number of Lyapunov coefficients, fractional dimensions, and entropy variations. The microdynamic parameters exhibit hyperchaotic behavior, as indicated by the presence of more than one positive Lyapunov coefficient. The variables also demonstrate a fractional fractal dimension, highlighting the irregularity in the geometric representation of the system.

Interspecific Variations in the Internal Mercury Isotope Dynamics of Antarctic Penguins: Implications for Biomonitoring.

Mercury (Hg) biomonitoring requires a precise understanding of the internal processes contributing to disparities between the Hg sources in the environment and the Hg measured in the biota. In this study, we investigated the use of Hg stable isotopes to trace Hg accumulation in Adélie and emperor penguin chicks from four breeding colonies in Antarctica. Interspecific variation of Δ199Hg in penguin chicks reflects the distinct foraging habitats and Hg exposures in adults. Chicks at breeding sites where adult penguins predominantly consumed mesopelagic prey showed relatively lower Δ199Hg values than chicks that were primarily fed epipelagic krill. Substantial δ202Hg variations in chick tissues were observed in both species (Adélie: -0.11 to 1.13‰, emperor: -0.27 to 1.15‰), whereas only emperor penguins exhibited the lowest δ202Hg in the liver and the highest in the feathers. Our results indicate that tissue-specific δ202Hg variations and their positive correlations with % MeHg resulted from MeHg demethylation in the liver and kidneys of emperor penguin chicks, whereas Adélie penguin chicks showed different internal responses depending on their exposure to dietary MeHg. This study highlights the importance of considering intra- and interspecific variations in adult foraging ecology and MeHg demethylation when selecting penguin chicks for Hg biomonitoring.

Quality assurance for focused ultrasound-induced blood-brain barrier opening procedure using passive acoustic detection

Focused ultrasound (FUS) combined with microbubbles is a promising technique for noninvasive, reversible, and spatially targeted blood-brain barrier opening, with clinical trials currently ongoing. Despite the fast development of this technology, there is a lack of established quality assurance (QA) strategies to ensure procedure consistency and safety. To address this challenge, this study presents the development and clinical evaluation of a passive acoustic detection-based QA protocol for FUS-induced blood-brain barrier opening (FUS-BBBO) procedure. Ten glioma patients were recruited to a clinical trial for evaluating a neuronavigation-guided FUS device. An acoustic sensor was incorporated at the center of the FUS device to passively capture acoustic signals for accomplishing three QA functions: FUS device QA to ensure the device functions consistently, acoustic coupling QA to detect air bubbles trapped in the acoustic coupling gel and water bladder of the transducer, and FUS procedure QA to evaluate the consistency of the treatment procedure. The FUS device passed the device QA in 9/10 patient studies. 4/9 cases failed acoustic coupling QA on the first try. The acoustic coupling procedure was repeatedly performed until it passed QA in 3/4 cases. One case failed acoustic coupling QA due to time constraints. Realtime passive cavitation monitoring was performed for FUS procedure QA, which captured variations in FUS-induced microbubble cavitation dynamics among patients. This study demonstrated that the proposed passive acoustic detection could be integrated with a clinical FUS system for the QA of the FUS-BBBO procedure. National Institutes of Health R01CA276174, R01MH116981, UG3MH126861, R01EB027223, R01EB030102, and R01NS128461.

A GEO-GEO Stereo Observation of Diurnal Cloud Variations over the Eastern Pacific

Fast atmospheric processes such as deep convection and severe storms are challenging to observe and understand without adequate spatiotemporal sampling. Geostationary (GEO) imaging has the advantage of tracking these fast processes continuously at a cadence of the 10 min global and 1 min mesoscale from thermal infrared (TIR) channels. More importantly, the newly-available GEO-GEO stereo observations from our 3D-Wind algorithm provide more accurate height assignment for atmospheric motion vectors (AMVs) than those from conventional TIR methods. Unlike the radiometric methods, the stereo height is insensitive to radiometric TIR calibration of satellite sensors and can assign the feature height correctly under complex situation (e.g., multi-layer clouds and atmospheric inversion). This paper shows a case study from continuous GEO-GEO stereo observations over the Eastern Pacific during 1–5 February 2023, to highlight diurnal variations of clouds and dynamics in the planetary boundary layer (PBL), altocumulus/congestus, convective outflow and tropical tropopause layer (TTL). Because of their good vertical resolution, the stereo observations often show a wind shear in these cloud layers. As an example, the stereo winds reveal the classic Ekman spiral in marine PBL dynamics with a clockwise (counterclockwise) wind direction change with height in the Northern (Southern) Hemisphere subtropics. Over the Southeastern Pacific, the stereo cloud observations show a clear diurnal variation in the closed-to-open cell transition in the PBL and evidence of precipitation at a lower level from broken stratocumulus clouds.