Designing a Heat Sink for Lithium-ion Battery Packs in Electric Vehicles

This report addresses the concepts and implementation of fluid cooled heat sink designs for an electric or hybrid vehicle battery. To determine the battery’s temperature and heat flux profile, testing was performed by measuring these values at multiple locations on a lithium-ion pouch battery using heat flux sensors and thermocouples during the charge and discharge cycles of the battery. Once the data was collected and analyzed, trendlines were fit to the heat flux data then used to create equations for the heat flux profile during the discharging stage. Each equation represented a specific region on the battery geometry. Four heat sink designs were modeled in COMSOL Multiphysics to optimize cooling. The third model concept (Model 3) was chosen as the best model because it cooled the battery to the lowest temperature with the lowest pressure drop

Identifying TBI Physiological States by Clustering Multivariate Clinical Time-Series Data

Determining clinically relevant physiological states from multivariate time series data with missing values is essential for providing appropriate treatment for acute conditions such as Traumatic Brain Injury (TBI), respiratory failure, and heart failure. Utilizing non-temporal clustering or data imputation and aggregation techniques may lead to loss of valuable information and biased analyses. In our study, we apply the SLAC-Time algorithm, an innovative self-supervision-based approach that maintains data integrity by avoiding imputation or aggregation, offering a more useful representation of acute patient states. By using SLAC-Time to cluster data in a large research dataset, we identified three distinct TBI physiological states and their specific feature profiles. We employed various clustering evaluation metrics and incorporated input from a clinical domain expert to validate and interpret the identified physiological states. Further, we discovered how specific clinical events and interventions can influence patient states and state transitions.Comment: 10 pages, 7 figures, 2 table

A Self-Supervised Learning-based Approach to Clustering Multivariate Time-Series Data with Missing Values (SLAC-Time): An Application to TBI Phenotyping

Self-supervised learning approaches provide a promising direction for clustering multivariate time-series data. However, real-world time-series data often include missing values, and the existing approaches require imputing missing values before clustering, which may cause extensive computations and noise and result in invalid interpretations. To address these challenges, we present a Self-supervised Learning-based Approach to Clustering multivariate Time-series data with missing values (SLAC-Time). SLAC-Time is a Transformer-based clustering method that uses time-series forecasting as a proxy task for leveraging unlabeled data and learning more robust time-series representations. This method jointly learns the neural network parameters and the cluster assignments of the learned representations. It iteratively clusters the learned representations with the K-means method and then utilizes the subsequent cluster assignments as pseudo-labels to update the model parameters. To evaluate our proposed approach, we applied it to clustering and phenotyping Traumatic Brain Injury (TBI) patients in the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study. Our experiments demonstrate that SLAC-Time outperforms the baseline K-means clustering algorithm in terms of silhouette coefficient, Calinski Harabasz index, Dunn index, and Davies Bouldin index. We identified three TBI phenotypes that are distinct from one another in terms of clinically significant variables as well as clinical outcomes, including the Extended Glasgow Outcome Scale (GOSE) score, Intensive Care Unit (ICU) length of stay, and mortality rate. The experiments show that the TBI phenotypes identified by SLAC-Time can be potentially used for developing targeted clinical trials and therapeutic strategies.Comment: Submitted to the Journal of Biomedical Informatic

Light Therapy Device for Entrainment of Circadian Rhythm Desynchronization in Microgravity

The circadian rhythm is an internal process of the brain that regulates the sleep-wake cycle. Outside environmental factors can affect the circadian rhythm such as light and dark. In microgravity, astronauts witness the sun rise and set approximately 16 times per day. A disruption (desynchronization) of the circadian rhythm may then occur, with some astronauts reporting to be less alert and unable to sufficiently complete tasks. PURPOSE: To design, fabricate, and test a pair of glasses that emit blue wavelengths of light peripheral to the eyes, for set periods of time, which may promote alertness in astronauts. METHODS: The custom fitted glasses were originally designed in three-dimensional modeling software (Solidworks Premium, Waltham, MA). Components of the glasses included: frames, an Arduino Nano circuit board, tactile button switch, inductive charging components and battery, a wireless charging transmitter, and blue LEDs. The glasses emit 1000 lux at approximately 468 nm wavelength of blue light. The glasses were programmed using C++ to allow the user to wear the glasses for 30 minutes with an automatic timer to turn off the lights upon completion of the session. When fully charged, the battery can sustain a total of 8 sessions with each lasting 30 minutes. To further assess the functionality of the glasses, brainwaves measured via electroencephalography (EEG) and reaction time measured via the psychomotor vigilance test (PVT) were collected before, immediately after, and one hour after a 30-min trial session while wearing the glasses in the “on” position. For one week prior to testing, participants emulated the sleep schedule of astronauts, including a strict adherence to 6.5 hours of sleep each night. Naps, caffeine, and sleep medications were also avoided during this time. RESULTS: For EEG data, morphology of beta wave activation in the frontal lobe noticeably changed after light exposure to a more jagged shape with higher frequency and lower amplitude. The control waveform and the waveform measured before light therapy exhibited greater intermixed frequencies of lower value. With regard to reaction time, when light exposure was administered on test days, participants exhibited faster reaction time responses immediately after (374.2 ± 58.1 msec) and 1-hour post (372.7 ± 65.9 msec) compared to before (530.4 ± 120.4 msec) the glasses were worn. CONCLUSION: Blue light exposure integrated into a customized pair of glasses may elicit faster response times and promote greater levels of alertness both immediately after wearing the glasses for 30 min, and one hour after the glasses have been removed

Terminal spreading depolarization and electrical silence in death of human cerebral cortex

Objective: Restoring the circulation is the primary goal in emergency treatment of cerebral ischemia. However, better understanding of how the brain responds to energy depletion could help predict the time available for resuscitation until irreversible damage and advance development of interventions that prolong this span. Experimentally, injury to central neurons begins only with anoxic depolarization. This potentially reversible, spreading wave typically starts 2 to 5 minutes after the onset of severe ischemia, marking the onset of a toxic intraneuronal change that eventually results in irreversible injury. Methods: To investigate this in the human brain, we performed recordings with either subdural electrode strips (n = 4) or intraparenchymal electrode arrays (n = 5) in patients with devastating brain injury that resulted in activation of a Do Not Resuscitate–Comfort Care order followed by terminal extubation. Results: Withdrawal of life‐sustaining therapies produced a decline in brain tissue partial pressure of oxygen (ptiO2) and circulatory arrest. Silencing of spontaneous electrical activity developed simultaneously across regional electrode arrays in 8 patients. This silencing, termed “nonspreading depression,” developed during the steep falling phase of ptiO2 (intraparenchymal sensor, n = 6) at 11 (interquartile range [IQR] = 7–14) mmHg. Terminal spreading depolarizations started to propagate between electrodes 3.9 (IQR = 2.6–6.3) minutes after onset of the final drop in perfusion and 13 to 266 seconds after nonspreading depression. In 1 patient, terminal spreading depolarization induced the initial electrocerebral silence in a spreading depression pattern; circulatory arrest developed thereafter. Interpretation: These results provide fundamental insight into the neurobiology of dying and have important implications for survivable cerebral ischemic insults. Ann Neurol 2018;83:295–31

What Should a Clinician Do When Spreading Depolarizations are Observed in a Patient?

Abstract: The International Conference on Spreading Depolarizations (iCSD) held in Boca Raton, Florida, in the September of 2018 devoted a section to address the question, “What should a clinician do when spreading depolarizations are observed in a patient?” Discussants represented a wide range of expertise, including neurologists, neurointensivists, neuroradiologists, neurosurgeons, and pre-clinical neuroscientists, to provide both clinical and basic pathophysiology perspectives. A draft summary of viewpoints offered was then written by a multidisciplinary writing group of iCSD members, based on a transcript of the session. Feedback of all discussants was formally collated, reviewed, and incorporated into the final document which was subsequently approved by all authors

Is pentobarbital safe and efficacious in the treatment of super-refractory status epilepticus: a cohort study

Introduction: Seizures refractory to third-line therapy are also labeled super-refractory status epilepticus (SRSE). These seizures are extremely difficult to control and associated with poor outcome. We aimed to characterize efficacy and side-effects of continuous infusions of pentobarbital (cIV-PTB) treating SRSE. Methods: We retrospectively reviewed continuous electroencephalography (cEEG) reports for all adults with RSE treated with cIV-PTB between May 1997 and April 2010 at our institution. Patients with post-anoxic SE and those receiving cIV-PTB for reasons other than RSE were excluded. We collected baseline information, cEEG findings, side-effects and functional outcome at discharge and one year. Results: Thirty one SRSE patients treated with cIV-PTB for RSE were identified. Mean age was 48 years old (interquartile range (IQR) 28,63), 26% (N = 8) had a history of epilepsy. Median SE duration was 6.5 days (IQR 4,11) and the mean duration of cIV-PTB was 6 days (IQR 3,14). 74% (N = 23) presented with convulsive SE. Underlying etiology was acute symptomatic seizures in 52% (N = 16; 12/16 with encephalitis), remote 30% (N = 10), and unknown 16% (N = 5). cIV-PTB controlled seizures in 90% (N = 28) of patients but seizures recurred in 48% (N = 15) while weaning cIV-PTB, despite the fact that suppression-burst was attained in 90% (N = 28) of patients and persisted >72 hours in 56% (N = 17). Weaning was successful after adding phenobarbital in 80% (12/15 of the patients with withdrawal seizures). Complications during or after cIV-PTB included pneumonia (32%, N = 10), hypotension requiring pressors (29%, N = 9), urinary tract infection (13%, N = 4), and one patient each with propylene glycol toxicity and cardiac arrest. One-third (35%, N = 11) had no identified new complication after starting cIV-PTB. At one year after discharge, 74% (N = 23) were dead or in a state of unresponsive wakefulness, 16% (N = 5) severely disabled, and 10% (N = 3) had no or minimal disability. Death or unresponsive wakefulness was associated with catastrophic etiology (p = 0.03), but none of the other collected variables. Conclusions: cIV-PTB effectively aborts SRSE and complications are infrequent; outcome in this highly refractory cohort of patients with devastating underlying etiologies remains poor. Phenobarbital may be particularly helpful when weaning cIV-PTB

Mitigating Complex Dust Foregrounds in Future Cosmic Microwave Background Polarization Experiments

archiveprefix: arXiv primaryclass: astro-ph.CO slaccitation: %%CITATION = ARXIV:1709.07897;%%archiveprefix: arXiv primaryclass: astro-ph.CO slaccitation: %%CITATION = ARXIV:1709.07897;%%archiveprefix: arXiv primaryclass: astro-ph.CO slaccitation: %%CITATION = ARXIV:1709.07897;%%P.B.’s research was supported by an appointment to the NASA Postdoctoral Program at the Jet Propulsion Laboratory, California Institute of Technology, administered by Universities Space Research Association under contract with NAS