Autonomic Measures Research Articles

Brief communication: Accurate and autonomous snow water equivalent measurements using a cosmic ray sensor on a Himalayan glacier

Abstract. We analyze snow water equivalent (SWE) measurements from a cosmic ray sensor (CRS) on the lower accumulation area of Mera Glacier (central Himalaya, Nepal) between November 2019 and November 2021. The CRS aligned well with field observations and revealed accumulation in pre-monsoon and monsoon observations, followed by ablation in post-monsoon and winter observations. COSIPY simulations suggest significant surface melting, water percolation, and refreezing within the snowpack, consistent with CRS observations yet liable to be missed by surface mass balance surveys. We conclude that CRS can be used to determine mass fluxes in various climatic settings, but the interpretation of the total changes in SWE needs complementary measurements and model analysis to determine the share of specific mass fluxes, such as melt and refreezing.

Effects of levodopa/carbidopa intestinal gel infusion on autonomic symptoms in advanced Parkinson's disease: a systematic review.

Autonomic failure has a major impact on the quality of life of individuals with Parkinson's disease(PD), especially in advanced stages of the disease. Levodopa/carbidopa intestinal gel (LCIG) infusion is a well-established treatment for advanced PD with severe motor fluctuations and provides substantial benefit in managing some non-motor symptoms (NMS), such as sleep, fatigue, and neuropsychiatric issues. The effect of LCIG on autonomic symptoms is by contrastnot well known. Here we performed a systematic review on the influence of LCIG therapy on autonomic dysfunction in PD individuals. Following the PRISMA guidelines, we systematically searched for studies that included autonomic outcome measures in LCIG-treated PD individuals, limiting the search to articles written in English and published between January 2005 and June 2023. We evaluated improvement, stability, or worsening of gastrointestinal, urinary, and cardiovascular symptoms at six different timepoints according to clinimetric scale changes compared to baseline. Data on autonomic adverse events (AEs) possibly related to LCIG treatment were also collected. Of the 1476 studies identified in the initial search, 16 ultimately met the inclusion criteria and underwent quality assessment and data extraction, with data from 1361 PD patients (18.3months mean follow-up). Thirteen studies reported improvement or stability of gastrointestinal, urinary, and cardiovascular symptoms over the interventional period. One study found a worsening of cardiovascular symptoms and two of urological symptoms. Regarding safety, seven studies reported gastrointestinal (8.4%), urinary (0.5%), and cardiovascular (1.1%) autonomic LCIG-related AEs. LCIG infusion may help toreduce the burden ofautonomic symptoms in advanced PD. Prospective studies specifically addressing the effect of LCIG on autonomic function in advanced PD are warranted.

Assessing the impacts of climate change on high mountain land-based livelihoods: An empirical investigation in District Nagar, Gilgit-Baltistan, Pakistan

Land-based livelihoods in Pakistan's high mountain regions are highly vulnerable to climate change due to the complex interactions between people and their natural environment. This study uses a mixed-method approach to explore how climate change affects land-based livelihoods in the high mountain Nagar District, Pakistan. Data were collected using a structured household survey of 430 randomly selected farmers, supplemented by focus group discussions and key informant interviews. The findings reveal that 87.7 % of farmers have observed negative impacts of climate change, such as increased crop diseases, reduced water for irrigation, and lower crop yields. Bivariate results indicate that factors related to farming practices, such as farming experience and cropping zones, significantly influence farmers' perceptions of impacts. The study emphasizes the urgent need for targeted government intervention and agricultural planning to boost the resilience of farmers in Nagar District. It calls for improved irrigation, crop disease management, and support tailored to high-mountain farming practices. The research highlights the importance of developing adaptation strategies to protect vulnerable farming communities from climate change impacts and supports the need for effective autonomous adaptation measures. This research contributes to a better understanding of climate change impacts on high-mountain agriculture and emphasizes the need to safeguard vulnerable farming communities.

Direct measurement and compensation of contour errors for profile grinding

Profile grinding is widely used for precision machining of curved parts, such as tools and molds. Traditional methods are manual-dependent and struggle with autonomous measurement and compensation of contour errors. This paper introduces a novel method for the direct measurement and compensation of contour errors in large-size profile grinding. A new image stitching algorithm for complex smooth curves is proposed, enabling robust image registration in low-feature regions. Furthermore, an approach for on-machine sub-pixel detection of contour errors is investigated, and an in-situ compensation algorithm for contour errors is designed. Experimental results show that the proposed method achieves high-precision stitching with minimal overlap, significantly improving contour error measurement. The compensation algorithm optimizes the tool path and implement the online compensation of the full contour errors during secondary machining, effectively improving the machining accuracy of curve parts. Additionally, a negative correlation between the number of image stitches and machining accuracy is revealed, and the possible explanations are discussed. The impact of various factors on machining accuracy will be further investigated in future studies.

Autonomous solar measurement system for sustainable solar energy

Autonomous solar measurement system for sustainable solar energy

Application scenarios and opportunities of autonomous pass-by measurements

Traditionally, pass-by measurements of vehicles were performed manually along the roadside. Recent developments allow for such measurements to be performed autonomously. Without the labour-intensive need of a measurement engineer at the spot, a variety of new applications for pass-by measurements become apparent. Beyond the application of the standardized SPB-measurement, a continuous and autonomous measurement of single vehicles can be used to detect high noise emitters. E.g., so-called posers or motorcycles increase the annoyance of inhabitants significantly. The detection of these single events is an important step to advance noise protection. Furthermore, the steady collection of data leads to numerous opportunities to describe and categorize vehicle and road noise. It can be used to further investigate the change of the acoustic properties of the roads in detail as well as those of the vehicles. The ongoing electrification of the vehicle fleet and the resulting changes in the noise behaviour can be scientifically tracked in real time. This progression affects next to the engine type (and sound) also the driving behaviour, the used tyres on the vehicle, and more. A continuous collection of pass-by measurements will deliver an increased understanding of the different influential factors of the vehicle-road-interaction.

Has the German vehicle fleet become quieter? - Results of a measurement campaign using SPB and CPX measurements

In the past, the German Environment Agency has carried out several measurement campaigns to determine the noise behavior of the German vehicle fleet. The aim of the current project was to identify any trends in comparison to previous campaigns. Autonomous pass-by measurements were carried out at 30 locations throughout Germany in accordance with DIN EN ISO 11819-1 (SPB) with the aim of recording at least 1000 vehicles per location. As the road surface influences the pass-by noise, near-field measurements according to DIN EN ISO 11819-2 (CPX) were carried out to determine the homogeneity of the road surface at each measurement location. In parallel to the CPX measurements, texture measurements according to DIN EN ISO 13473 were carried out to quantify the relevant geometric parameters of the road surface. The presentation describes the methodology of these measurements and presents the final results including a comparison with data from the 2012 and 2002 measurement campaigns.

Effect of Prior Moderate Aerobic Exercise to Prolonged Sitting on Peripheral and Central Cardiovascular Measures in Young Women.

Prolonged sitting is a risk factor for cardiovascular disease (CVD). We examined whether moderate aerobic exercise prior to prolonged sitting (EX + SIT) has protective effects on peripheral and central cardiovascular and autonomic measures. Young women (n = 26; 23.4 ± 4.3 years old; BMI = 23.1 ± 4.3) completed two sessions in random order: (1) EX + SIT, which consisted of 25 min of moderate aerobic exercise followed by a 3 h prolonged sitting bout, and (2) a 3 h prolonged sitting bout only (SIT-only). Seated peripheral and central blood pressure (BP), pulse wave velocity (PWV), and heart rate variability (HRV) were measured at baseline and after 1 h, 2 h, and 3 h of sitting. Generalized linear mixed models with random effects examined the effects of conditions (i.e., EX + SIT vs. SIT) on BP, PWV, and HRV while adjusting for baseline values. Only peripheral and central diastolic BP (β = 2.18; p = 0.016 and β = 1.99; p = 0.034, respectively) were significantly lower in the EX + SIT condition compared to the SIT-only condition. No differences were detected in other BP, PWV, or HRV variables between the two conditions (p > 0.05 for all). Performing moderate aerobic exercise in the morning before engaging in prolonged sitting bouts may reduce some of the prolonged-sitting-induced cardiovascular impairments in young women. Further research is needed to confirm these findings in males and middle-aged/older adults.

Flexible, Multifunctional, and Durable MXene/CeO2/Cellulose Nanofibers for Efficient Energy Conversion‐Storage Capacity Toward Self‐Powered Monitoring of Ammonia

AbstractThe appeal of wearable gas sensors for Internet of Things (IoTs) necessitates flexible sensory units along with sustainable source of energy supply. The key factors required for emergence of these devices are choice of electroactive materials, flexibility, skin‐compatibility, and robustness against harsh environment. Considering this, the multifunctional MXene/CeO2 composites reinforced with electrospun cellulose nanofibers are constructed and investigated for energy conversion, energy storage, and gas sensing applications. Among the synthesized composites, MXene/CeO2 (10 wt%) coated onto cellulose nanofibers outperformed triboelectric nanogenerator (TENG) with open‐circuit voltage of 160 V and supercapacitor (SC) specific capacitance of 388.98 F g−1 and sensing response of 212% toward 10 ppm NH3. The fabricated devices show promising outlooks against practical challenges of influence of humid conditions and different bending states. Lastly, the self‐chargeable device is integrated and the practical implications of charging of SC through TENG and its utilization in sensor powering is demonstrated. The above findings are expected to contribute significantly in envisioning development of wearable health monitors, combining the flexibility features and facilitating autonomous measurements of NH3 pollutant and biomarker.

A Fusion Tracking Algorithm for Electro-Optical Theodolite Based on the Three-State Transition Model.

This study presents a novel approach to address the autonomous stable tracking issue in electro-optical theodolite operating in closed-loop mode. The proposed methodology includes a multi-sensor adaptive weighted fusion algorithm and a fusion tracking algorithm based on a three-state transition model. A refined recursive formula for error covariance estimation is developed by integrating attenuation factors and least squares extrapolation. This formula is employed to formulate a multi-sensor weighted fusion algorithm that utilizes error covariance estimation. By assigning weighted coefficients to calculate the residual of the newly introduced error term and defining the sensor's unique states based on these coefficients, a fusion tracking algorithm grounded on the three-state transition model is introduced. In cases of interference or sensor failure, the algorithm either computes the weighted fusion value of the multi-sensor measurement or triggers autonomous sensor switching to ensure the autonomous and stable measurement of the theodolite. Experimental results indicate that when a specific sensor is affected by interference or the off-target amount cannot be extracted, the algorithm can swiftly switch to an alternative sensor. This capability facilitates the precise and consistent generation of data, thereby ensuring the stable operation of the tracking system. Furthermore, the algorithm demonstrates robustness across various measurement scenarios.

Lost at sea: Impact of an ocean survival experience on psychological, physiological and cognitive abilities (RAD'LÔ)

Survival in an extreme environment places high physiological and cognitive demands on the individual. These environments are characterized by specific stimuli, including unusual sensory stimulation and uncertainty, which induce intense stress. Thus, the aims of this study are: i) to evaluate the impact of a five-day survival at sea simulation on human adaptive capacities, based on the assessment of psychological, cognitive, physiological, and sensorial measures; and ii) to assess recovery. Twenty-one healthy participants were enrolled in a 5-day simulation onboard a lifeboat or an inflatable raft. Psychological, physiological, sensory, and cognitive measurements were recorded before leaving (baseline), at the end of the experiment (post) and during the week that followed (recovery). Our results are unequivocal. The harshness of the environment affected the majority of the organism's responses. On the cognitive level, performance significantly deteriorated. On the psychological level, there was low mood, a decrease in subjective exteroceptive acuity and sleep disorders, increased energy, and less perceived stress. On the physiological level, a decline was recorded with respect to autonomous nervous system measurements. On the sensory level, we observed a state of hypervigilance and hypersensitivity to stimuli from the external environment. Proprioception was deeply impacted. Moreover, at recovery, many individuals did not fully recover or deteriorated further, especially regarding sleep, interoceptive abilities and sensory distortion. It appears that participants entered a state of psychological hibernation, associated with increased physical and cognitive load, and sensory hypervigilance. These results raise the question of the risks that may be incurred during future long-term space missions, as astronauts will have to maintain their cognitive performance at a high level to be able to respond to environmental demands and remain alive. It is essential to continue to explore countermeasures that will support adaptation in future spacecraft crew.

An approach to the detection of pain from autonomic and cortical correlates

ObjectiveTo assess the value of combining brain and autonomic measures to discriminate the subjective perception of pain from other sensory-cognitive activations. Methods20 healthy individuals received 2 types of tonic painful stimulation delivered to the hand: electrical stimuli and immersion in 10 Celsius degree (°C) water, which were contrasted with non-painful immersion in 15 °C water, and stressful cognitive testing. High-density electroencephalography (EEG) and autonomic measures (pupillary, electrodermal and cardiovascular) were continuously recorded, and the accuracy of pain detection based on combinations of electrophysiological features was assessed using machine learning procedures. ResultsPainful stimuli induced a significant decrease in contralateral EEG alpha power. Cardiac, electrodermal and pupillary reactivities occurred in both painful and stressful conditions. Classification models, trained on leave-one-out cross-validation folds, showed low accuracy (61–73%) of cortical and autonomic features taken independently, while their combination significantly improved accuracy to 93% in individual reports. ConclusionsChanges in cortical oscillations reflecting somatosensory salience and autonomic changes reflecting arousal can be triggered by many activating signals other than pain; conversely, the simultaneous occurrence of somatosensory activation plus strong autonomic arousal has great probability of reflecting pain uniquely. SignificanceCombining changes in cortical and autonomic reactivities appears critical to derive accurate indexes of acute pain perception.

Autonomous ground vehicle gravity anomaly measurement and dynamic error compensation

Abstract To address the issue that dynamic gravity anomaly measurement is overly dependent on GNSS and can’t be measured autonomously at this stage, this paper proposes an autonomous ground vehicle dynamic gravity anomaly measurement method based on a strapdown inertial navigation system (SINS), odometer (OD), barometer and platform gravimeter. The SINS/OD /barometer integrated navigation solution delivers high-precision navigation parameters, completes the calculation of correction terms, and performs the autonomous dynamic gravity anomaly measurement combined with the primary measurement results of the platform gravimeter. Numerical calculations provide the requirements for the application of the proposed method, and the cut-off frequency for extracting gravity anomalies is 0.02 Hz, as determined by power spectral density analysis. In order to further improve the measurement accuracy and account for dynamic errors caused by vehicle maneuvering, a long-short-term memory (LSTM) model of recurrent neural network (RNN) is introduced. A series of experiments under multiple circumstances with repeated lines were conducted in Tianjin, China, and the static measurements along the line were taken using CG-5 to provide true values of gravity anomalies. The results demonstrate that the autonomous measurement scheme can achieve accuracy comparable to GNSS-assisted, and that dynamic error compensation algorithm based on LSTM improves the dynamic gravity measurements accuracy significantly without sacrificing the spatial resolution of gravity anomalies.

Precise and efficient measurement of tibial slope on magnetic resonance imaging (MRI): two novel autonomous pipelines by traditional and deep learning algorithms.

The measurement of posterior tibial slopes (PTS) can aid in the screening and prevention of anterior cruciate ligament (ACL) injuries and improve the success rate of some other knee surgeries. However, the circle method for measuring PTS on magnetic resonance imaging (MRI) scans is challenging and time-consuming for most clinicians to implement in practice, despite being highly repeatable. Currently, there is no automated measurement scheme based on this method. To enhance measurement efficiency, consistency, and reduce errors resulting from manual measurements by physicians, this study proposes two novel, precise, and computationally efficient pipelines for autonomous measurement of PTS. The first pipeline employs traditional algorithms with experimental parameters to extract the tibial contour, detect adhesions, and then remove these adhesions from the extracted contour. A cyclic process is employed to adjust the parameters adaptively and generate a better binary image for the following tibial contour extraction step. The second pipeline utilizes deep learning models for classifying MRI slice images and segmenting tibial contours. The incorporation of deep learning models greatly simplifies the corresponding steps in pipeline 1. To evaluate the practical performance of the proposed pipelines, doctors utilized MRI images from 20 patients. The success rates of pipeline 1 for central, medial, and lateral slices were 85%, 100%, and 90%, respectively, while pipeline 2 achieved success rates of 100%, 100%, and 95%. Compared to the 10 minutes required for manual measurement, our automated methods enable doctors to measure PTS within 10 seconds. These evaluation results validate that the proposed pipelines are highly reliable and effective. Employing these tools can effectively prevent medical practitioners from being burdened by monotonous and repetitive manual measurement procedures, thereby enhancing both the precision and efficiency. Additionally, this tool holds the potential to contribute to the researches regarding the significance of PTS, particularly those demanding extensive and precise PTS measurement outcomes.

Autonomic and Enteric Profiling May Help Predict Response to Diverse Obesity Therapies.

Changes in autonomic (ANS) and enteric nervous systems (ENS) may be involved in pathogenesis of obesity. We hypothesized that baseline autonomic and enteric parameters may predict outcomes of diverse obesity therapies. We studied ANS and ENS physiology in 37 patients (8 male, 29 female, age 45years, weight 129.7kg) at 4 centers in patients undergoing medical (9: low-calorie diet) versus invasive (22: 16 sleeve, 6 bypass) and semi-invasive (6: 2 band, 2 high energy stimulation, 2 aspiration) weight loss therapies. Weight loss was reported as percent weight loss from baseline to latest values at 1year and in some up to 5years; classified as < or > /= 20% for each group. ANS testing included sympathetic adrenergic function by measuring reflex vasoconstriction and postural adjustment ratio. ENS was measured non-invasively using cutaneous low-resolution electrogastrogram. Percent weight loss was greater with the invasive (28.5%) than semi-invasive (9.1%) or non-invasive low-calorie diet (4.4%) (p < .001). Percent weight loss at 1year (and up to 5years) corresponded to the adrenergic measure of postural adjustment ratio (r = .42, p = .012), total pulse amplitude at rest (r = .56, p < .001), and electrogastrogram standing-to-rest difference (r = .33, p = .056). Baseline autonomic and enteric function measures correspond to percentage with loss in this pilot study using diverse weight loss methods. Autonomic and enteric profiling has potential clinical use for evaluation and treatment of obesity but needed larger controlled trials.

The Influence of Seasonal Effects on Railway Vertical Track Modulus

Adequate vertical track support is essential for safe and efficient railway operations. Insufficient support leads to distorted track geometry, increased dynamic loads, component stress, poor ride quality, rolling stock damage, and derailment risks. Current inspection practices focus on assessing the condition of the track components and geometry, rather than the root causes of degradation. To improve this condition, this study presents the use of a methodology that utilizes an autonomous vertical track deflection measurement system mounted on a loaded rail car (36 tonnes/axle) to support track maintenance decisions in a heavy haul railroad located in southeast Brazil. The system continuously measured substructure stiffness along the railway line. Over one year, data were collected from over 8000 km of track. The study highlighted seasonal effects on track degradation over time, identifying areas with significant deflections and high deflection rates, which contribute to issues such as differential settlement and reduced lifespan of track components. Additionally, the study revealed seasonal effects, with deflections peaking during wet weather and decreasing during dry cycles. A method to classify weak track areas was developed, facilitating monitoring and enabling more effective maintenance planning, contributing to the reduction of overall track maintenance costs and enhancing safety and operational efficiency.

Emotional and Cognitive "Route" in Decision-Making Process: The Relationship between Executive Functions, Psychophysiological Correlates, Decisional Styles, and Personality.

Studies on decision-making have classically focused exclusively on its cognitive component. Recent research has shown that a further essential component of decisional processes is the emotional one. Indeed, the emotional route in decision-making plays a crucial role, especially in situations characterized by ambiguity, uncertainty, and risk. Despite that, individual differences concerning such components and their associations with individual traits, decisional styles, and psychophysiological profiles are still understudied. This pilot study aimed at investigating the relationship between individual propensity toward using an emotional or cognitive information-processing route in decision-making, EEG and autonomic correlates of the decisional performance as collected via wearable non-invasive devices, and individual personality and decisional traits. Participants completed a novel task based on realistic decisional scenarios while their physiological activity (EEG and autonomic indices) was monitored. Self-report questionnaires were used to collect data on personality traits, individual differences, and decisional styles. Data analyses highlighted two main findings. Firstly, different personality traits and decisional styles showed significant and specific correlations, with an individual propensity toward either emotional or cognitive information processing for decision-making. Secondly, task-related EEG and autonomic measures presented a specific and distinct correlation pattern with different decisional styles, maximization traits, and personality traits, suggesting different latent profiles.

Approaches to studying emotion using physiological responses to spoken narratives: A scoping review.

Narratives are effective tools for evoking emotions, and physiological measurements provide a means of objectively assessing emotional reactions - making them a potentially powerful pair of tools for studying emotional processes. However, extent research combining emotional narratives and physiological measurement varies widely in design and application, making it challenging to identify previous work, consolidate findings, and design effective experiments. Our scoping review explores the use of auditory emotional narratives and physiological measures in research, examining paradigms, study populations, and represented emotions. Following the PRISMA-ScR Checklist, we searched five databases for peer-reviewed experimental studies that used spoken narratives to induce emotion and reported autonomic physiological measures. Among 3466 titles screened and 653 articles reviewed, 110 studies were included. Our exploration revealed a variety of applications and experimental paradigms; emotional narratives paired with physiological measures have been used to study diverse topics and populations, including neurotypical and clinical groups. Although incomparable designs and sometimes contradictory results precluded general recommendations as regards which physiological measures to use when designing new studies, as a whole, the body of work suggests that these tools can be valuable to study emotions. Our review offers an overview of research employing narratives and physiological measures for emotion study, and highlights weaknesses in reporting practices and gaps in our knowledge concerning the robustness and specificity of physiological measures as indices of emotion. We discuss study design considerations and transparent reporting, to facilitate future using emotional narratives and physiological measures in studying emotions.

Automated transient grating spectroscopy mapping and signal control for large samples.

We present developments for the mapping of large areas using transient grating spectroscopy (TGS) that allow for smoother, larger, autonomous measurements of material samples. The addition of a precise linear stage in the direction parallel to laser sampling coupled with signal optimizing control allows for hands free, self-correcting measurements. In addition, the simplification of the sample holding design to a form that is small enough to mount directly to the linear stage exhibits a straightforward, low-cost solution for automated TGS applications. This capability is demonstrated by taking large uninterrupted maps of gradient wafers, and the results are validated on calibrated tungsten samples and control TGS samples from gradient wafers.

Preterm Infant's Heart Rate Variability Near Birth Predicts Autonomic Symptoms at Age 3 to 5 Years.

Aims To describe the autonomic function of premature infants born between 28 and 32 weeks of gestation, without medical risk factors, at the age of 3 to 5 years and to assess whether it's possible to predict the appearance of autonomic deficits in these children at this age range. Methods This follow-up study included 40 out of 55 premature infants born between weeks 28 and 32 during 2018 to 2020. During 2022 to 2023 parents were asked to report on medical and developmental follow-up and treatment, functional characteristics of the autonomic system, and the age at which walking was achieved. Results Approximately 27% of the participants (11 out of 40) presented autonomic symptoms at 3 to 5 years of age. A predictive relationship was noted between the function of the heart rate control system near birth and the presence of autonomic dysfunctions at ages 3 to 5. Fourteen of 40 children received neurodevelopmental treatments. However, children with autonomic symptoms were not treated for their symptoms. Conclusion These preliminary findings provide valuable insights into the autonomic function of children born premature and the potential predictive relationship between early autonomic measures and later autonomic dysfunctions. It also highlights the need for increased awareness and intervention strategies for addressing autonomic issues in premature infants to support their overall well-being.