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ObjectiveAlthough seizures are the cardinal feature, epilepsy is associated with other forms of brain dysfunction including impaired cognition, abnormal sleep, and increased risk of developing dementia. We hypothesized that, given the widespread neurologic dysfunction caused by epilepsy, accelerated brain aging would be seen. We measured the sleep-based brain age index (BAI) in a diverse group of patients with epilepsy. The BAI is a machine learning-based biomarker that measures how much the brain activity of a person during overnight sleep deviates from chronological age-based norms.MethodsThis case–control study drew information of age-matched controls without epilepsy from home sleep monitoring volunteers and from non-epilepsy patients with Sleep Lab testing. Patients with epilepsy underwent in-patient monitoring and were classified by epilepsy type and seizure burden. The primary outcomes measured were BAI, processed from electroencephalograms, and epilepsy severity metrics (years with epilepsy, seizure frequency standardized by year, and seizure burden [number of seizures in life]). Subanalyses were conducted on a subset with NIH Toolbox cognitive testing for total, fluid, and crystallized composite cognition.Results138 patients with epilepsy (32 exclusively focal and 106 generalizable [focal seizures with secondary generalization]) underwent in-patient monitoring, and age-matched, non-epilepsy controls were analyzed. The mean BAI was higher in epilepsy patients vs controls and differed by epilepsy type: −0.05 years (controls) versus 5.02 years (all epilepsy, p < 0.001), 5.53 years (generalizable, p < 0.001), and 3.34 years (focal, p = 0.03). Sleep architecture was disrupted in epilepsy, especially in generalizable epilepsy. A higher BAI was positively associated with increased lifetime seizure burden in focal and generalizable epilepsies and associated with lower crystallized cognition. Lifetime seizure burden was inversely correlated with fluid, crystallized, and composite cognition.SignificanceEpilepsy is associated with accelerated brain aging. Higher brain age indices are associated with poorer cognition and more severe epilepsy, specifically generalizability and higher seizure burden. These findings strengthen the use of the sleep-derived, electroencephalography-based BAI as a biomarker for cognitive dysfunction in epilepsy.

Pangolins are the most trafficked mammals in the world and are severely threatened by poaching the loss, degradation, and fragmentation of habitat. In Malaysian Borneo, conservation initiatives for the Sunda pangolin (Manis javanica) are hindered by a paucity of data on their distribution and population size. Using MaxEnt niche modelling and consolidated species location data, we projected the distribution of Sunda pangolins in Sabah. Additionally, we assessed the accessibility of their forest habitats to humans to understand potential threats. Our model indicated that, as of 2015, approximately half of Sabah’s land area (39,530 km²) is suitable for pangolins, with 43% in protected forests, 38% in production forests, and 19% outside of these areas. Alarmingly, our data suggest that nearly all (91%) of these suitable habitats are relatively easily accessible to poachers. Our findings provide a state-level baseline understanding of Sunda pangolin distribution and assess potential threats in Sabah. These can inform short- and long-term conservation management plans for pangolin to safeguard this critically endangered species.

Backgrounds: Sleep disturbances are prevalent among elderly individuals. While polysomnography (PSG) serves as the gold standard for sleep monitoring, its extensive setup and data analysis procedures impose significant costs and time constraints, thereby restricting the long-term application within the general public. Our laboratory introduced an innovative biomarker, utilizing artificial intelligence algorithms applied to PSG data to estimate brain age (BA), a metric validated in cohorts with cognitive impairments. Nevertheless, the potential of exercise, which has been a recognized means of enhancing sleep quality in middle-aged and older adults to reduce BA, remains undetermined. Methods: We conducted an exploratory study to evaluate whether 12 weeks of moderate-intensity exercise can improve cognitive function, sleep quality, and the brain age index (BAI), a biomarker computed from overnight sleep electroencephalogram (EEG), in physically inactive middle-aged and older adults. Home wearable devices were used to monitor heart rate and overnight sleep EEG over this period. The NIH Toolbox Cognition Battery, in-lab overnight polysomnography, cardiopulmonary exercise testing, and a multiplex cytokines assay were employed to compare pre- and post-exercise brain health, exercise capacity, and plasma proteins. Results: In total, 26 participants completed the initial assessment and exercise program, and 24 completed all procedures. Data are presented as mean [lower 95% CI of mean, upper 95% CI of mean]. Participants significantly increased maximal oxygen consumption (Pre: 21.11 [18.98, 23.23], Post 22.39 [20.09, 24.68], mL/kg/min; effect size: −0.33) and decreased resting heart rate (Pre: 66.66 [63.62, 67.38], Post: 65.13 [64.25, 66.93], bpm; effect size: −0.02) and sleeping heart rate (Pre: 64.55 [61.87, 667.23], Post: 62.93 [60.78, 65.09], bpm; effect size: −0.15). Total cognitive performance (Pre: 111.1 [107.6, 114.6], Post: 115.2 [111.9, 118.5]; effect size: 0.49) was significantly improved. No significant differences were seen in BAI or measures of sleep macro- and micro-architecture. Plasma IL-4 (Pre: 0.24 [0.18, 0.3], Post: 0.33 [0.24, 0.42], pg/mL; effect size: 0.49) was elevated, while IL-8 (Pre: 5.5 [4.45, 6.55], Post: 4.3 [3.66, 5], pg/mL; effect size: −0.57) was reduced. Conclusions: Cognitive function was improved by a 12-week moderate-intensity exercise program in physically inactive middle-aged and older adults, as were aerobic fitness (VO2max) and plasma cytokine profiles. However, we found no measurable effects on sleep architecture or BAI. It remains to be seen whether a study with a larger sample size and more intensive or more prolonged exercise exposure can demonstrate a beneficial effect on sleep quality and brain age.

Abstract Sleep electroencephalogram (EEG) signals likely encode brain health information that may identify individuals at high risk for age-related brain diseases. Here, we evaluate the correlation of a previously proposed brain age biomarker, the “brain age index” (BAI), with cognitive test scores and use machine learning to develop and validate a series of new sleep EEG-based indices, termed “sleep cognitive indices” (SCIs), that are directly optimized to correlate with specific cognitive scores. Three overarching cognitive processes were examined: total, fluid (a measure of cognitive processes involved in reasoning-based problem solving and susceptible to aging and neuropathology), and crystallized cognition (a measure of cognitive processes involved in applying acquired knowledge toward problem-solving). We show that SCI decoded information about total cognition (Pearson’s r = 0.37) and fluid cognition (Pearson’s r = 0.56), while BAI correlated only with crystallized cognition (Pearson’s r = − 0.25). Overall, these sleep EEG-derived biomarkers may provide accessible and clinically meaningful indicators of neurocognitive health.

Abstract Plastic pollution is distributed patchily around the world’s oceans. Likewise, marine organisms that are vulnerable to plastic ingestion or entanglement have uneven distributions. Understanding where wildlife encounters plastic is crucial for targeting research and mitigation. Oceanic seabirds, particularly petrels, frequently ingest plastic, are highly threatened, and cover vast distances during foraging and migration. However, the spatial overlap between petrels and plastics is poorly understood. Here we combine marine plastic density estimates with individual movement data for 7137 birds of 77 petrel species to estimate relative exposure risk. We identify high exposure risk areas in the Mediterranean and Black seas, and the northeast Pacific, northwest Pacific, South Atlantic and southwest Indian oceans. Plastic exposure risk varies greatly among species and populations, and between breeding and non-breeding seasons. Exposure risk is disproportionately high for Threatened species. Outside the Mediterranean and Black seas, exposure risk is highest in the high seas and Exclusive Economic Zones (EEZs) of the USA, Japan, and the UK. Birds generally had higher plastic exposure risk outside the EEZ of the country where they breed. We identify conservation and research priorities, and highlight that international collaboration is key to addressing the impacts of marine plastic on wide-ranging species.

Abstract Inactivation of influenza A virus by radiofrequency (RF) energy exposure at levels near Institute of Electrical and Electronics Engineers (IEEE) safety thresholds has been reported. The authors hypothesized that this inactivation was through a structure-resonant energy transfer mechanism. If this hypothesis is confirmed, such a technology could be used to prevent transmission of virus in occupied public spaces where RF irradiation of surfaces could be performed at scale. The present study aims to both replicate and expand the previous work by investigating the neutralization of bovine coronavirus (BCoV), a surrogate of SARS-CoV-2, by RF radiation in 6–12 GHz range. Results showed an appreciable reduction in BCoV infectivity (up to 77%) due to RF exposure to certain frequencies, but failed to generate enough reduction to be considered clinically significant.

Abstract Body condition in pelagic seabirds impacts key fitness‐related traits such as reproductive performance and breeding frequency. Regulation of body condition can be especially important for species with long incubation periods and long individual incubation shifts between foraging trips. Here, we show that body condition of adult Red‐billed Tropicbirds (Phaethon aethereus) at St Helena Island, South Atlantic Ocean, exhibited considerable variation between years (2013–2017) and between different stages of the breeding cycle. Females took the first incubation shift following egg laying, after which males and females alternated incubation shifts of varying length, ranging from

IntroductionAlthough brain magnetic resonance imaging (MRI) is a valuable tool for investigating structural changes in the brain associated with neurodegeneration, the development of non-invasive and cost-effective alternative methods for detecting early cognitive impairment is crucial. The human voice has been increasingly used as an indicator for effectively detecting cognitive disorders, but it remains unclear whether acoustic features are associated with structural neuroimaging.MethodsThis study aims to investigate the association between acoustic features and brain volume and compare the predictive power of each for mild cognitive impairment (MCI) in a large community-based population. The study included participants from the Framingham Heart Study (FHS) who had at least one voice recording and an MRI scan. Sixty-five acoustic features were extracted with the OpenSMILE software (v2.1.3) from each voice recording. Nine MRI measures were derived according to the FHS MRI protocol. We examined the associations between acoustic features and MRI measures using linear regression models adjusted for age, sex, and education. Acoustic composite scores were generated by combining acoustic features significantly associated with MRI measures. The MCI prediction ability of acoustic composite scores and MRI measures were compared by building random forest models and calculating the mean area under the receiver operating characteristic curve (AUC) of 10-fold cross-validation.ResultsThe study included 4,293 participants (age 57 ± 13 years, 53.9% women). During 9.3 ± 3.7 years follow-up, 106 participants were diagnosed with MCI. Seven MRI measures were significantly associated with more than 20 acoustic features after adjusting for multiple testing. The acoustic composite scores can improve the AUC for MCI prediction to 0.794, compared to 0.759 achieved by MRI measures.DiscussionWe found multiple acoustic features were associated with MRI measures, suggesting the potential for using acoustic features as easily accessible digital biomarkers for the early diagnosis of MCI.

Abstract Emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its current worldwide spread have caused a pandemic of acute respiratory disease COVID-19. The virus can result in mild to severe, and even to fatal respiratory illness in humans, threatening human health and public safety. The spike (S) protein on the surface of viral membrane is responsible for viral entry into host cells. The discovery of methods to inactivate the entry of SARS-CoV-2 through disruption of the S protein binding to its cognate receptor on the host cell is an active research area. To explore other prevention strategies against the quick spread of the virus and its mutants, non-equilibrium molecular dynamics simulations have been employed to explore the possibility of manipulating the structure–activity of the SARS-CoV-2 spike glycoprotein by applying electric fields (EFs) in both the protein axial directions and in the direction perpendicular to the protein axis. We have found out the application of EFs perpendicular to the protein axis is most effective in denaturing the HR2 domain which plays critical role in viral-host membrane fusion. This finding suggests that varying irradiation angles may be an important consideration in developing EF based non-invasive technologies to inactivate the virus.

Background Obstructive sleep apnoea (OSA) is associated with increased risk of type 2 diabetes. However, results from large population-based prospective cohort studies are rare. The main aim of the present study was to investigate the relative risk of 8-year incident type 2 diabetes in relation to OSA severity in a prospective cohort study of middle-aged and older adults. Methods A total of 2918 participants (mean age 59 years) of the Korean Genome and Epidemiology Study (KoGES), who underwent home-based overnight polysomnography at baseline examination between 2011 and 2014, were followed up 4-yearly between 2015–2018 and 2019–2021. A total of 1697 participants were present in both follow-ups. After excluding participants who had diabetes at baseline (n=481), a total of 1216 participants were eligible for the analyses. Results OSA at baseline was categorised by apnoea–hypopnoea index levels as non-OSA (0–4.9 events·h−1), mild OSA (5.0–14.9 events·h−1) and moderate–severe OSA (≥15.0 events·h−1). Incident type 2 diabetes was identified at each follow-up. Compared with non-OSA, participants with moderate–severe OSA had 1.5 times higher risk of developing type 2 diabetes at the end of the 8-year follow-up after adjusting for potential covariates (relative risk 1.50, 95% CI 1.02–2.21). In the same analytical models for 4-year relative risk of incident type 2 diabetes, none of the OSA groups were at significantly higher risk compared with the non-OSA group. Conclusion Moderate–severe OSA, a modifiable risk factor, poses a higher risk of incident type 2 diabetes compared with non-OSA over an 8-year period in general middle-aged and older adults.

BackgroundPeople age at different rates. Biological age is a risk factor for many chronic diseases independent of chronological age. A good lifestyle is known to improve overall health, but its association with biological age is unclear.MethodsThis study included participants from the UK Biobank who had undergone 12-lead resting electrocardiography (ECG). Biological age was estimated by a deep learning model (defined as ECG-age), and the difference between ECG-age and chronological age was defined as Δage. Participants were further categorized into an ideal (score 4), intermediate (scores 2 and 3) or unfavorable lifestyle (score 0 or 1). Four lifestyle factors were investigated, including diet, alcohol consumption, physical activity, and smoking. Linear regression models were used to examine the association between lifestyle factors and Δage, and the models were adjusted for sex and chronological age.ResultsThis study included 44,094 individuals (mean age 64 ± 8, 51.4% females). A significant correlation was observed between predicted biological age and chronological age (correlation coefficient = 0.54, P

Abstract Spontaneous synchronization over large networks is ubiquitous in nature, ranging from inanimate to biological systems. In the human brain, neuronal synchronization and de-synchronization occur during sleep, with the greatest degree of neuronal synchronization during slow wave sleep (SWS). The current sleep classification schema is based on electroencephalography and provides common criteria for clinicians and researchers to describe stages of non-rapid eye movement (NREM) sleep as well as rapid eye movement (REM) sleep. These sleep stage classifications have been based on convenient heuristic criteria, with little consideration of the accompanying normal physiological changes across those same sleep stages. To begin to resolve those inconsistencies, first focusing only on NREM sleep, we propose a simple cluster synchronization model to explain the emergence of SWS in healthy people without sleep disorders. We apply the empirical mode decomposition (EMD) analysis to quantify slow wave activity in electroencephalograms, and provide quantitative evidence to support our model. Based on this synchronization model, NREM sleep can be classified as SWS and non-SWS, such that NREM sleep can be considered as an intrinsically bistable process. Finally, we develop an automated algorithm for SWS classification. We show that this new approach can unify brain wave dynamics and their corresponding physiologic changes.

Abstract Bespoke (custom‐built) Raspberry Pi cameras are increasingly popular research tools in the fields of behavioral ecology and conservation, because of their comparative flexibility in programmable settings, ability to be paired with other sensors, and because they are typically cheaper than commercially built models. Here, we describe a novel, Raspberry Pi‐based camera system that is fully portable and yet weatherproof—especially to humidity and salt spray. The camera was paired with a passive infrared sensor, to create a movement‐triggered camera capable of recording videos over a 24‐hr period. We describe an example deployment involving “retro‐fitting” these cameras into artificial nest boxes on Praia Islet, Azores archipelago, Portugal, to monitor the behaviors and interspecific interactions of two sympatric species of storm‐petrel (Monteiro's storm‐petrel Hydrobates monteiroi and Madeiran storm‐petrel Hydrobates castro) during their respective breeding seasons. Of the 138 deployments, 70% of all deployments were deemed to be “Successful” (Successful was defined as continuous footage being recorded for more than one hour without an interruption), which equated to 87% of the individual 30‐s videos. The bespoke cameras proved to be easily portable between 54 different nests and reasonably weatherproof (~14% of deployments classed as “Partial” or “Failure” deployments were specifically due to the weather/humidity), and we make further trouble‐shooting suggestions to mitigate additional weather‐related failures. Here, we have shown that this system is fully portable and capable of coping with salt spray and humidity, and consequently, the camera‐build methods and scripts could be applied easily to many different species that also utilize cavities, burrows, and artificial nests, and can potentially be adapted for other wildlife monitoring situations to provide novel insights into species‐specific daily cycles of behaviors and interspecies interactions.

Sleep medicine is an ambitious cross-disciplinary challenge, requiring the mutual integration between complementary specialists in order to build a solid framework. Although knowledge in the sleep field is growing impressively thanks to technical and brain imaging support and through detailed clinic-epidemiologic observations, several topics are still dominated by outdated paradigms. In this review we explore the main novelties and gaps in the field of sleep medicine, assess the commonest sleep disturbances, provide advices for routine clinical practice and offer alternative insights and perspectives on the future of sleep research.

Abstract The diet of an individual animal is subject to change over time, both in response to short‐term food fluctuations and over longer time scales as an individual ages and meets different challenges over its life cycle. A metabarcoding approach was used to elucidate the diet of different life stages of a migratory songbird, the Eurasian reed warbler (Acrocephalus scirpaceus) over the 2017 summer breeding season in Somerset, the United Kingdom. The feces of adult, juvenile, and nestling warblers were screened for invertebrate DNA, enabling the identification of prey species. Dietary analysis was coupled with monitoring of Diptera in the field using yellow sticky traps. Seasonal changes in warbler diet were subtle, whereas age class had a greater influence on overall diet composition. Age classes showed high dietary overlap, but significant dietary differences were mediated through the selection of prey; (i) from different taxonomic groups, (ii) with different habitat origins (aquatic vs. terrestrial), and (iii) of different average approximate sizes. Our results highlight the value of metabarcoding data for enhancing ecological studies of insectivores in dynamic environments.

The interactions of heart rate variability and respiratory rate and tidal volume fluctuations provide key information about normal and abnormal sleep. A set of metrics can be computed by analysis of coupling and coherence of these signals, cardiopulmonary coupling (CPC). There are several forms of CPC, which may provide information about normal sleep physiology, and pathological sleep states ranging from insomnia to sleep apnea and hypertension. As CPC may be computed from reduced or limited signals such as the electrocardiogram or photoplethysmogram (PPG) vs. full polysomnography, wide application including in wearable and non-contact devices is possible. When computed from PPG, which may be acquired from oximetry alone, an automated apnea hypopnea index derived from CPC-oximetry can be calculated. Sleep profiling using CPC demonstrates the impact of stable and unstable sleep on insomnia (exaggerated variability), hypertension (unstable sleep as risk factor), improved glucose handling (associated with stable sleep), drug effects (benzodiazepines increase sleep stability), sleep apnea phenotypes (obstructive vs. central sleep apnea), sleep fragmentations due to psychiatric disorders (increased unstable sleep in depression).

Technetium (99Tc), a uranium-235 (235U) and plutonium-239 (239Pu) fission product, is a primary risk driver in low level radioactive liquid waste at U.S. Department of Energy sites. Previous studies have shown success in using Zero Valent Iron (ZVI) to chemically reduce and immobilize redox sensitive groundwater contaminants. Batch and column experiments were performed to assess the ability of a novel porous iron composite material (PIC) to immobilize Tc(VII) in comparison with two commercial Fe oxide sorbents and reagent grade ZVI in the presence and absence of NO3−, a competing oxidized species that is often found in high concentrations in liquid nuclear waste. Perrhenate (ReO4−) was used as a non-radioactive chemical analogue for pertechnetate (TcO4−) under both oxic and anoxic test conditions. The PIC powder was the most effective at immobilizing Re(VII) under all batch test conditions. The presence of nitrate (NO3−) slowed the removal of ReO4− from solution, presumably through chemical reduction and precipitation. Even so, the PIC and ZVI were effective at removing both Re(VII) and NO3− completely from solution. Nitrate was reduced to NH3 with very little nitrite (NO2−) buildup during equilibration. Significant Re immobilization was observed in the column tests containing PIC sorbent, even though inlet solutions were in equilibrium with O2. The presence of NO3− hastened Re breakthrough, while NO3− reduction to NH3 was observed. The results suggest that PIC and ZVI would be the most effective at the removal of TcO4− from contaminated groundwater sites. Keywords: Technetium, Rhenium, Nitrate, Zero-valent iron, Permeable reactive barriers, Column experiment

Background Sleep fragmentation and sleep apnea are common in patients with atrial fibrillation (AF). We investigated the impact of radio‐frequency catheter ablation (RFCA) on sleep quality in patients with paroxysmal AF and the effect of a change in sleep quality on recurrence of AF. Methods and Results Of 445 patients who underwent RFCA for paroxysmal AF between October 2007 and January 2017, we analyzed 225 patients who had a 24‐hour Holter test within 6 months before RFCA. Sleep quality was assessed by cardiopulmonary coupling analysis using 24‐hour Holter data. We compared cardiopulmonary coupling parameters (high‐frequency coupling, low‐frequency coupling, very‐low‐frequency coupling) before and after RFCA. Six months after RFCA, the high‐frequency coupling (marker of stable sleep) and very‐low‐frequency coupling (rapid eye movement/wake marker) was significantly increased (29.84%–36.15%; P

Abstract Two species of eagles (Golden and White‐tailed) bred in Wales during prehistoric and historic times and became regionally extinct as breeding species in the mid‐1800s. They are iconic and charismatic, and discussions about reintroducing them back into the Welsh landscape have been ongoing for years. Reintroductions, however, can be risky, costly and/or contentious. To address these concerns, and to judge whether it is appropriate to reintroduce a regionally extinct species; the “International Union for Conservation of Nature (IUCN)” have produced criteria by which a proposed reintroduction can be assessed. A key criterion is that the potential reintroduction location lies within the former range of the species. In this study, we addressed this criterion by assessing the past distributions of Golden and White‐tailed Eagles within Wales. Using historic observational data, fossil/archaeological records and evidence from place‐names in the Welsh language, we demonstrated strong evidence for the presence of both of these eagle species in Wales in pre‐historic and historic times. We used kernel density functions to model the likely core distributions of each species within Wales. The resulting core distributions encompassed much of central and west‐north Wales for both species, with the White‐tailed Eagle exhibiting a wider core distribution extending into south Wales. Our results fill knowledge gaps regarding the historic ranges of both species in Britain, and support the future restoration of either or both species to Wales.

SDNET2018 is an annotated image dataset for training, validation, and benchmarking of artificial intelligence based crack detection algorithms for concrete. SDNET2018 contains over 56,000 images of cracked and non-cracked concrete bridge decks, walls, and pavements. The dataset includes cracks as narrow as 0.06 mm and as wide as 25 mm. The dataset also includes images with a variety of obstructions, including shadows, surface roughness, scaling, edges, holes, and background debris. SDNET2018 will be useful for the continued development of concrete crack detection algorithms based on deep convolutional neural networks (DCNNs), which are a subject of continued research in the field of structural health monitoring. The authors present benchmark results for crack detection using SDNET2018 and a crack detection algorithm based on the AlexNet DCNN architecture. SDNET2018 is freely available at https://doi.org/10.15142/T3TD19.

Steel connections are used to connect between beam and column in steel moment frame structures. As of present time, there is a huge lack of understanding of the performance of steel connections and their response to fire especially the uncontrolled fires. Therefore, in this paper, by using a finite element program ABAQUS and with the static analysis of coupled temperature- displacement and to fully understand the behavior of such connection under the fire scenario, developed a temperature-dependent models for different types of steel connections are implemented. Finite Element Analyses (FEA) of selected experimental models are performed to verify the implementation of these models. Fully detailed, field-variable-dependent conductivity element models of the connections are developed, and analyses are performed to determine the effects of heat on the behavior of the materials in the elastic and plastic areas are considered. Moreover, severe deformation in the nonlinear region was investigated. Keywords: Temperature, Steel connections, Non-linear analysis, Finite element methods

Sleep, a vital process of human being, is carefully orchestrated by the brain and consists of cyclic transitions between rapid eye movement (REM) and non-REM (NREM) sleep. Autonomic tranquility during NREM sleep is characterized by vagal dominance and stable breathing, providing an opportunity for the cardiovascular-neural axis to restore homeostasis, in response to use, distress or fatigue inflicted during wakefulness. Abrupt irregular swings in sympathovagal balance during REM sleep act as phasic loads on the resting cardiovascular system. Any causes of sleep curtailment or fragmentation such as sleep restriction, sleep apnea, insomnia, periodic limb movements during sleep, and shift work, not only impair cardiovascular restoration but also impose a stress on the cardiovascular system. Sleep disturbances have been reported to play a role in the development of stroke and other cardiovascular disorders. This review aims to provide updated information on the role of abnormal sleep in the development of stroke, to discuss the implications of recent research findings, and to help both stroke clinicians and researchers understand the importance of identification and management of sleep pathology for stroke prevention and care.

Abstract Background Umbilical cord blood provides a source of hematopoietic stem cells for transplantation with immunological and availability advantages over conventional bone marrow sources. Limited cell numbers and slower engraftment from umbilical cord blood units has led to the clinical development of immobilised Notch ligand Delta-Like 1 to promote ex vivo expansion of a rapidly engrafting cell population. However, current immobilisation methods are not simple to scale in a controlled manner. Results Delta-Like 1 was immobilised onto streptavidin coated magnetic particles via a heterobifunctionalised polyethylene glycol linker molecule to provide an easily manipulated format of surface protein presentation. CD34+ enriched cord blood cells were treated with Delta-Like 1 immobilised particles, and immunophenotypic markers measured to monitor population distributions using cluster identification, characterization, and regression software. The amenability of the approach to scalability was evaluated in a micro-scale stirred tank bioreactor. Surface concentration of Delta-Like 1 was well controlled used differing stoichiometric reagent ratios. Protein immobilisation was a cost effective process and particles were efficiently removed from the final cell product. Immobilised Delta-Like 1 is functional and stimulates qualitatively similar CD34hi, CD38lo, CD90lo, CD133hi, CD135hi progenitor expansion in both static culture and scalable stirred culture platforms. Conclusions Immobilised Delta-Like 1 in this form has the potential to improve the manufacturing efficiency and control of final ex vivo expanded cell product through compatibility with highly controlled and characterised suspension culture systems.

The resistance of beam-to-column connections to fire is an important consideration for the design of steel moment frames. The authors seek to study the effect of fire on such connections using finite element modeling in ABAQUS. The previously published first part of this paper detailed and validated the simulation technique by comparing model results to experimental results reported elsewhere in the literature. This, the second part of the paper, seeks to demonstrate the performance of four types of connections exposed to thermal loading: (1) bolted end plate, (2) bolted cover plate, (3) bolted tee, and (4) welded cover plate. A numerical study was performed to quantify the effects of thermal loading on beam buckling, displacement, rotation, connection stiffness, and moment-rotation behavior at temperatures between 20 and 900 °C. The bolted end plate connection exhibited the highest resistance to thermal loading with a significantly lower degree of degradation in connection performance compared to the other three connection types. Keywords: Moment connections, Finite element analysis, Bolted tee, Temperature, Cover plate connection

Small unmanned aerial system(s) (sUAS) are rapidly emerging as a practical means of performing bridge inspections. Under the right condition, sUAS assisted inspections can be safer, faster, and less costly than manned inspections. Many Departments of Transportation in the United States are in the early stages of adopting this emerging technology. However, definitive guidelines for the selection of equipment for various types of bridge inspections or for the possible challenges during sUAS assisted inspections are absent. Given the large investments of time and capital associated with deploying a sUAS assisted bridge inspection program, a synthesis of authors experiences will be useful for technology transfer between academics and practitioners. In this paper, the authors list the challenges associated with sUAS assisted bridge inspection, discuss equipment and technology options suitable for mitigating these challenges, and present case studies for the application of sUAS to several specific bridge inspection scenarios. The authors provide information to sUAS designers and manufacturers who may be unaware of the specific challenges associated with sUAS assisted bridge inspection. As such, the information presented here may reveal the demands in the design of purpose-built sUAS inspection platforms.

This paper summarizes the results of traditional image processing algorithms for detection of defects in concrete using images taken by Unmanned Aerial Systems (UASs). Such algorithms are useful for improving the accuracy of crack detection during autonomous inspection of bridges and other structures, and they have yet to be compared and evaluated on a dataset of concrete images taken by UAS. The authors created a generic image processing algorithm for crack detection, which included the major steps of filter design, edge detection, image enhancement, and segmentation, designed to uniformly compare different edge detectors. Edge detection was carried out by six filters in the spatial (Roberts, Prewitt, Sobel, and Laplacian of Gaussian) and frequency (Butterworth and Gaussian) domains. These algorithms were applied to fifty images each of defected and sound concrete. Performances of the six filters were compared in terms of accuracy, precision, minimum detectable crack width, computational time, and noise-to-signal ratio. In general, frequency domain techniques were slower than spatial domain methods because of the computational intensity of the Fourier and inverse Fourier transformations used to move between spatial and frequency domains. Frequency domain methods also produced noisier images than spatial domain methods. Crack detection in the spatial domain using the Laplacian of Gaussian filter proved to be the fastest, most accurate, and most precise method, and it resulted in the finest detectable crack width. The Laplacian of Gaussian filter in spatial domain is recommended for future applications of real-time crack detection using UAS.

Background and Objective Simulated altitude as a model for hypoxia has shown inconsistent results in terms of impaired cognition. We hypothesized that preserved periods of stable sleep even under hypoxia could explain stable cognitive function. Delta spectral power on electroencephalography during stable sleep as well as high frequency coupling on the electrocardiogram-based spectrogram was adopted as measures of sleep quality. Methods Eleven healthy, non-smoking subjects (7 men, 27 ± 1.5 years) were exposed to 9 hours of continuous hypoxia for 13 consecutive nights. Polysomnography was done at baseline and during 3 time points, at night 3, 7, and 14. In each study, delta spectral power was obtained during stable N2 and N3 sleep. Stable sleep was defined when there was no significant fragmentation in electroencephalography and fluctuation in electromyography and cardiorespiratory signals. The time threshold was 2 or 5 continuous minutes for N2 and 2 minutes for N3. The amount of high frequency coupling for the sleep period on the electrocardiogram-based spectrogram was computed. Randomized block ANOVA was used with electroencephalography delta power and high frequency coupling as dependent variables with post hoc Tukey test. Results Delta spectral power during stable sleep was not significantly different across the entire hypoxic exposures (p = 0.98 for N2; p = 0.32 for N3). High frequency coupling was different between pre-exposure and mid-exposure (night 7; 52.5 ± 23.6% vs. 39.0 ± 16.7%, p = 0.02) but returned to the baseline level at the post-exposure (night 14; 45.4 ± 18.2%, p = 0.39). Conclusions Both preservation of the proportion of stable sleep and unchanged delta power during these periods may help explain maintained cognition in conditions of chronic nocturnal hypoxic exposures.

Treatment-emergent central sleep apnea has been referred to as ‘complex sleep apnea’, where apparently obstructive respiratory events convert to central apneas with application of positive airway pressure. Potential contributing factors may include increased propensity for arousals and positive airway pressure-induced reductions in CO2 which amplifies unstable ventilatory control. Here we demonstrate the dramatic beneficial effects of zolpidem and enhanced expiratory rebreathing space on complex sleep apnea, which helps to elude the mechanism of complex sleep apnea.