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Decreasing speed and stride length over successive races have been shown to be associated with musculoskeletal injury (MSI) in racehorses, demonstrating the potential for early detection of MSI through longitudinal monitoring of changes in stride characteristics. A machine learning (ML) approach for early detection of MSI, enforced rest, and retirement events using this same horse-level, race-level, and stride characteristic data across all race sectionals was investigated. A CatBoost model using features from the two races prior to an event had the highest classification performance (sensitivity score for MSI, enforced rest and retirement equal to 0.00, 0.58, 0.76, respectively and balanced accuracy score corresponding to 0.44), with scores decreasing for models incorporating windows that included additional races further from the event. Feature importance analysis of ML models demonstrated that retirement was predicted by older age, poor performance, and longer racing career, enforced rest was predicted by younger age and better performance, but was less likely to occur when the stride length is increasing, and MSI predicted by increased number of starters, greater variation in speed and lower percentage of career time at rest. A relatively low classification performance highlights the difficulties in discerning MSI from alternate events using ML. Improved data recording through more thorough assessment and annotation of adverse events is expected to improve the predictability of MSI. [ABSTRACT FROM AUTHOR]

The aim of this study is to evaluate the accuracy of outcome reporting after elective visceral surgery in a low volume district hospital. Outcome measurement as well as transparent reporting of surgical complications becomes more and more important. In the future, financial and personal resources may be distributed due to reported quality and thus, it is in the main interest of healthcare providers that outcome data are accurately collected. Between 10/2020 and 09/2021 postoperative complications during the hospitalisation were recorded using the Clavien–Dindo classification (CDC) and comprehensive complication index by residents of a surgical department in a district hospital. After one year of prospective data collection, data were retrospectively analyzed and re-evaluated for accuracy by senior consultant surgeons. In 575 patients undergoing elective general or visceral surgery interns and residents reported an overall rate of patients with complications of 7.3% (n = 42) during the hospitalization phase, whereas a rate of 18.3% (n = 105) was revealed after retrospective analysis by senior consultant surgeons. Thus, residents failed to report patients with postoperative complications in 60% of cases (63/105). In the 42 cases, in which complications were initially reported, the grading of complications was correct only in 33.3% of cases (n = 14). Complication grades that were most missed were CDC grade I and II. Quality of outcome measurement in a district hospital is poor if done by unexperienced residents and significantly underestimates the true complication rate. Outcome measurement must be done or supervised by experienced surgeons to ensure correct and reliable outcome data. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has been marked by novel viral variants, posing challenges to global public health. Recombination, a viral evolution mechanism, is implicated in SARS-CoV-2's ongoing evolution. The XBB recombinant lineage, known for evading antibody-mediated immunity, exhibits higher transmissibility without increased disease severity. We investigated the prevalence and genomic features of XBB in SARS-CoV-2-positive cases in Rio Grande do Sul (RS), Brazil. We sequenced 357 samples from epidemiological weeks (EW) 47/2022 to 17/2023, and included 389 publicly available sequences. Clinical and epidemiological data were obtained from DATASUS, e-SUS, and SIVEP GRIPE (data recording systems of the Brazilian Ministry of Health). Of these, 143 were classified as XBB and 586 were other Omicron lineages. In March 2023 (EW 10), XBB became dominant, accounting for 83.3% of cases. 97.7% of XBB-infected patients successfully recovered from the infection, with a low mortality rate (2.3%). Even after receiving three vaccine doses and having been previously infected, 59.5% of the patients experienced reinfection with XBB. However, for 54% of the individuals, the interval between their XBB infection and the last vaccine dose exceeded one year, potentially leading to a decline in antibody levels. In addition, we identified 90 mutations in RS circulating XBB, spread throughout the genome, notably in the Spike protein region associated with immune resistance. This study provides insights into the dynamics and impact of a recombinant variant becoming predominant for the first time in the state. Continued surveillance of SARS-CoV-2 genomic evolution is crucial for effective public health management. [ABSTRACT FROM AUTHOR]

This study focused on detecting the reflections of healing and change in cortex activation in full-face transplantation and lesions patients on EEG activity. Face transplant patients have facial lesions before transplantation and, to identify pre-face transplant patients' brain activity in the absence of pre-transplant recordings, we used data obtained from pre-transplant facial lesion patients. Ten healthy, four facial lesion and three full-face transplant patients participated in this study. EEG data recorded for four different sensory stimuli (brush from the right face, right hand, left face, and left-hand regions) were analyzed using wavelet packet transform method. EEG waves were analyzed for standard bands. Our findings indicate significant change in the 2–4 Hz frequency range which may be a result of ongoing or previous cortical reorganization for face lesion and transplant patients. Alterations of the delta wave seen in patients with facial lesion and face transplant can also be explained by the intense central plasticity. Our findings show that the delta band differences might be used as a marker in the evaluation of post-transplant cortical plasticity in the future. [ABSTRACT FROM AUTHOR]

Gait data collection from overweight individuals walking on irregular surfaces is a challenging task that can be addressed using inertial measurement unit (IMU) sensors. However, it is unclear how many IMUs are needed, particularly when body attachment locations are not standardized. In this study, we analysed data collected from six body locations, including the torso, upper and lower limbs, to determine which locations exhibit significant variation across different real-world irregular surfaces. We then used deep learning method to verify whether the IMU data recorded from the identified body locations could classify walk patterns across the surfaces. Our results revealed two combinations of body locations, including the thigh and shank (i.e., the left and right shank, and the right thigh and right shank), from which IMU data should be collected to accurately classify walking patterns over real-world irregular surfaces (with classification accuracies of 97.24 and 95.87%, respectively). Our findings suggest that the identified numbers and locations of IMUs could potentially reduce the amount of data recorded and processed to develop a fall prevention system for overweight individuals. [ABSTRACT FROM AUTHOR]

There is an ongoing debate on the processes producing background seismicity and deformation transients across seismic gaps, i.e., regions that lack historical large-magnitude earthquakes. Essential missing elements are geophysical images that resolve sources of geophysical unrest. Here, we apply seismic scattering and absorption tomography to data recorded during the 2010–2014 seismic sequence within the Mt. Pollino seismic gap region (Southern Italy). The tomographic models show high sensitivity to fluid content, deformed fractured structures, and impermeable layers stopping fluid migrations. They bridge the gaps between geological and geophysical models and provide a highly-resolved image of the source of seismic and deformation unrest within this seismic gap. High absorption topping the western Pollino seismic volume appears pressurized between the low-Vp/Vs and low-scattering San Donato metamorphic core and a deep basement. Absorbing fluids can only migrate laterally to the east, blocked in the west and southwest by deep low-scattering barriers associated with east-dipping faults and to the north and southeast by saturated overpressurized low-scattering basins. This eastern migration is only partially effective, producing seismicity across the lowest boundary of the high-absorption volume. Our results showcase the potential of seismic scattering and absorption when imaging structures causing geophysical unrest processes across fault networks. [ABSTRACT FROM AUTHOR]

Sepsis is a leading cause of mortality and early identification improves survival. With increasing digitalization of health care data automated sepsis prediction models hold promise to aid in prompt recognition. Most previous studies have focused on the intensive care unit (ICU) setting. Yet only a small proportion of sepsis develops in the ICU and there is an apparent clinical benefit to identify patients earlier in the disease trajectory. In this cohort of 82,852 hospital admissions and 8038 sepsis episodes classified according to the Sepsis-3 criteria, we demonstrate that a machine learned score can predict sepsis onset within 48 h using sparse routine electronic health record data outside the ICU. Our score was based on a causal probabilistic network model—SepsisFinder—which has similarities with clinical reasoning. A prediction was generated hourly on all admissions, providing a new variable was registered. Compared to the National Early Warning Score (NEWS2), which is an established method to identify sepsis, the SepsisFinder triggered earlier and had a higher area under receiver operating characteristic curve (AUROC) (0.950 vs. 0.872), as well as area under precision-recall curve (APR) (0.189 vs. 0.149). A machine learning comparator based on a gradient-boosting decision tree model had similar AUROC (0.949) and higher APR (0.239) than SepsisFinder but triggered later than both NEWS2 and SepsisFinder. The precision of SepsisFinder increased if screening was restricted to the earlier admission period and in episodes with bloodstream infection. Furthermore, the SepsisFinder signaled median 5.5 h prior to antibiotic administration. Identifying a high-risk population with this method could be used to tailor clinical interventions and improve patient care. [ABSTRACT FROM AUTHOR]

Surgical data quantification and comprehension expose subtle patterns in tasks and performance. Enabling surgical devices with artificial intelligence provides surgeons with personalized and objective performance evaluation: a virtual surgical assist. Here we present machine learning models developed for analyzing surgical finesse using tool-tissue interaction force data in surgical dissection obtained from a sensorized bipolar forceps. Data modeling was performed using 50 neurosurgery procedures that involved elective surgical treatment for various intracranial pathologies. The data collection was conducted by 13 surgeons of varying experience levels using sensorized bipolar forceps, SmartForceps System. The machine learning algorithm constituted design and implementation for three primary purposes, i.e., force profile segmentation for obtaining active periods of tool utilization using T-U-Net, surgical skill classification into Expert and Novice, and surgical task recognition into two primary categories of Coagulation versus non-Coagulation using FTFIT deep learning architectures. The final report to surgeon was a dashboard containing recognized segments of force application categorized into skill and task classes along with performance metrics charts compared to expert level surgeons. Operating room data recording of > 161 h containing approximately 3.6 K periods of tool operation was utilized. The modeling resulted in Weighted F1-score = 0.95 and AUC = 0.99 for force profile segmentation using T-U-Net, Weighted F1-score = 0.71 and AUC = 0.81 for surgical skill classification, and Weighted F1-score = 0.82 and AUC = 0.89 for surgical task recognition using a subset of hand-crafted features augmented to FTFIT neural network. This study delivers a novel machine learning module in a cloud, enabling an end-to-end platform for intraoperative surgical performance monitoring and evaluation. Accessed through a secure application for professional connectivity, a paradigm for data-driven learning is established. [ABSTRACT FROM AUTHOR]

In the past 2 years, three earthquakes of magnitude 6.0 and above occurred consecutively in Qinghai province, China, i.e., the 22 May 2021 Ms7.4 Maduo, 8 January 2022 Ms6.9 Menyuan, and 26 March 2022 Ms6.0 Delingha earthquakes. The hydrological observation instruments set up by the China Earthquake Administration allow us to study the dynamic processes in the well-aquifer systems during the establishment of criticality. Particularly, the observations played an important role in the prediction of the 8 January 2022 Ms6.9 Menyuan earthquake that was approved by the People's Government of Qinghai province. This work presents the hydrological data recorded by 7 stations to show the short-term anomalies before these earthquakes. To explore the performance of the hydrological observations in detecting earthquakes that occurred on different active tectonic blocks, we calculate the relative amplitudes of the pre-seismic changes. Results indicate that markedly pre-seismic change is found if the observation station and the detection earthquake are on the same block, and moderate change is found if they are on the adjacent blocks, while the precursor is hard to be identified if they are on the separated blocks. The variations in the hydrological responses may be caused by the strength weakening (or dilatancy) of source media. And the increased volumes in the crust can be evidenced by the changes in the geodetic time series in the same neighborhoods and during the same period, augmenting stress loading between the blocks. [ABSTRACT FROM AUTHOR]

The experience of pain has been dissociated into two interwoven aspects: a sensory-discriminative aspect and an affective-motivational aspect. We aimed to explore which of the pain descriptors is more deeply rooted in the human brain. Participants were asked to evaluate applied cold pain. The majority of the trials showed distinct ratings: some were rated higher for unpleasantness and others for intensity. We compared the relationship between functional data recorded from 7 T MRI with unpleasantness and intensity ratings and revealed a stronger relationship between cortical data and unpleasantness ratings. The present study underlines the importance of the emotional-affective aspects of pain-related cortical processes in the brain. The findings corroborate previous studies showing a higher sensitivity to pain unpleasantness compared to ratings of pain intensity. For the processing of pain in healthy subjects, this effect may reflect the more direct and intuitive evaluation of emotional aspects of the pain system, which is to prevent harm and to preserve the physical integrity of the body. [ABSTRACT FROM AUTHOR]

The accelerating growth of seismic unrest before eruptions has been observed at many volcanoes and utilized for eruption forecasts. However, there are still many eruptions for which no precursory unrest has been identified, even at well-monitored volcanoes. The recent eruptions of Shinmoe-dake, Japan, have been another negative example of this kind. Here we present seismological evidence that the eruption preparation had been ongoing at the shallow depths beneath Shinmoe-dake for several months to a year. We investigated the seismic background level (SBL) of eleven-year data recorded around the volcano, including two stations about 1 km from the eruptive crater. We searched for persistent weak signals, focusing on low-amplitude time windows recorded during quiet nighttime. Then the spectra of daily background noise were classified by clustering analysis. The SBL analysis successfully revealed very weak precursory tremors from more than several months before the eruption, and residual tremors to the end of the eruptive period. The precursory signals grew acceleratory in a similar way as is assumed in the material failure forecast method applied to eruption forecasts. However, their growth was significantly slower and longer compared to other cases reported in the literature. Such slow and quiet eruption preparations would not be captured by conventional seismological methods. We expect that long-term SBL analyses on proximal seismic data will help detect early precursors, even at seismically quiet volcanoes, and will also help towards judging the end of an eruptive period. [ABSTRACT FROM AUTHOR]

Based on the temperature data recorded by a mooring system deployed in the northern South China Sea (SCS), this study compares the traditional methods of identifying and extracting internal solitary waves (ISWs): the whole water column isotherm (WCI) method and the single isotherm (SI) method, and proposes a novel method: the temperature superposition (TS) method. Results indicate that the TS method identifies the most ISWs, followed by the WCI method, and the SI method identifies the fewest. When the ISW amplitudes are smaller than 60 m, the TS method can identify the most ISWs. When the ISW amplitudes are greater than 60 m, the number of ISWs identified by the three methods is the same. The TS method removes the internal tides, takes into account the temperature of all depth layers, and amplifies the signal of ISWs to a certain extent, so as to effectively identify ISWs. [ABSTRACT FROM AUTHOR]

To ensure the safety of railroad operations, it is important to monitor and forecast track geometry irregularities. A higher safety requires forecasting with higher spatiotemporal frequencies, which in turn requires capturing spatial correlations. Additionally, track geometry irregularities are influenced by multiple exogenous factors. In this study, a method is proposed to forecast one type of track geometry irregularity, vertical alignment, by incorporating spatial and exogenous factor calculations. The proposed method embeds exogenous factors and captures spatiotemporal correlations using a convolutional long short-term memory. The proposed method is also experimentally compared with other methods in terms of the forecasting performance. Additionally, an ablation study on exogenous factors is conducted to examine their individual contributions to the forecasting performance. The results reveal that spatial calculations and maintenance record data improve the forecasting of vertical alignment. [ABSTRACT FROM AUTHOR]

Although multisensory integration (MSI) has been extensively studied, the underlying mechanisms remain a topic of ongoing debate. Here we investigate these mechanisms by comparing MSI in healthy controls to a clinical population with spinal cord injury (SCI). Deafferentation following SCI induces sensorimotor impairment, which may alter the ability to synthesize cross-modal information. We applied mathematical and computational modeling to reaction time data recorded in response to temporally congruent cross-modal stimuli. We found that MSI in both SCI and healthy controls is best explained by cross-modal perceptual competition, highlighting a common competition mechanism. Relative to controls, MSI impairments in SCI participants were better explained by reduced stimulus salience leading to increased cross-modal competition. By combining traditional analyses with model-based approaches, we examine how MSI is realized during normal function, and how it is compromised in a clinical population. Our findings support future investigations identifying and rehabilitating MSI deficits in clinical disorders. [ABSTRACT FROM AUTHOR]

Estimating deep-time species-level diversification processes remains challenging. Both the fossil record and molecular phylogenies allow the estimation of speciation and extinction rates, but each type of data may still provide an incomplete picture of diversification dynamics. Here, we combine species-level palaeontological (fossil occurrences) and neontological (molecular phylogenies) data to estimate deep-time diversity dynamics through process-based birth–death models for Carcharhiniformes, the most speciose shark order today. Despite their abundant fossil record dating back to the Middle Jurassic, only a small fraction of extant carcharhiniform species is recorded as fossils, which impedes relying only on the fossil record to study their recent diversification. Combining fossil and phylogenetic data, we recover a complex evolutionary history for carcharhiniforms, exemplified by several variations in diversification rates with an early low diversity period followed by a Cenozoic radiation. We further reveal a burst of diversification in the last 30 million years, which is partially recorded with fossil data only. We also find that reef expansion and temperature change can explain variations in speciation and extinction through time. These results pinpoint the primordial importance of these environmental variables in the evolution of marine clades. Our study also highlights the benefit of combining the fossil record with phylogenetic data to address macroevolutionary questions. [ABSTRACT FROM AUTHOR]

Our detailed 3-D seismic tomographic assimilation using high-quality phase arrival time data recorded by the local seismographic network demonstrated that heterogeneities in the crustal faults have contributed significantly to the pop-up tectonics beneath the Shillong Plateau, characterized by high-V and low-σ. The major seismogenic faults, namely, the north-dipping Dapsi thrust in association with Dauki fault in the south and south dipping Brahmaputra fault in the north, located either side of the Shillong Plateau that acted as the causative factors for the pop-up, which attributed to the lithostatic (high-V, low-σ) and sedimentary (low-V, high-σ) load, respectively. Seismicity is found confined to a depth ≤ 60 km. Uneven distribution of structural heterogeneities in the upper crust is responsible for earthquake genesis of varying strengths. It is intriguing to note that high-velocity anomalies and low-ϭ in the uppermost crust, interpreted as the Shillong Plateau that acted as a geometric asperity and the juxtaposition of high-V and low-V became the source zone of the 1897 Shillong earthquake (Ms 8.7) as a novel observation for the region. Structural heterogeneities are distinctly distributed between low-V, high-σ and high-V, low-σ in the lower crust plays a major role for future intense seismogenesis due to differential strain accumulation. [ABSTRACT FROM AUTHOR]

To examine the influence of movement on cerebrospinal fluid (CSF) dynamics, intracranial subdural pressure recordings were taken from sub-adult alligators (Alligator mississippiensis) locomoting on a treadmill. Pressure recordings documenting the cardiac, ventilatory, and barostatic influences on the CSF were in good agreement with previous studies. During locomotion the CSF exhibits sinusoidal patterns of pressure change that spanned a mean amplitude of 56 mm Hg, some 16 × the amplitude of the cardiac-linked pulsations. These sinusoidal CSF pulsations were closely linked to the locomotor kinematics, particularly the lateral oscillations of the alligator's head. Data recorded from the freely moving alligators suggest that fluid inertia, body cavity pressures, and likely other factors all influence the CSF pressure. The clear relationship between movement and CSF pressure described in this study suggests that the paucity of studies examining human CSF dynamics during movement should be addressed. [ABSTRACT FROM AUTHOR]

Examining continuous seismic data recorded by a dense broadband seismic network throughout Taipei shows for the first time, the nature of seismic noise in this highly populated metropolitan area. Using 140 broadband stations in a 50 km × 69 km area, three different recurring, strong noise signals characterized by dominant frequencies of 2–20 Hz, 0.25–1 Hz, and < 0.2 Hz are explored. At frequencies of 2–20 Hz, the seismic noise exhibits daily and weekly variations, and a quiescence during the Chinese New Year holidays. The largest amplitude occurred at a station located only 400 m from a traffic-roundabout, one of the busiest intersections in Taipei, suggesting a possible correlation between large amplitude and traffic flow. The median daily amplitude for the < 0.2 Hz and 0.2–1.0 Hz frequency bands is mostly synchronized with high similarity between stations, indicating that the sources are persistent oceanic or atmospheric perturbations across a large area. The daily amplitude for the > 2 Hz band, however, is low, indicating a local source that changes on shorter length scales. Human activities responsible for the 2–40 Hz energy in the city, we discovered, are able to produce amplitudes approximately 2 to 1500 times larger than natural sources. Using the building array deployed in TAIPEI 101, the tallest building in Taiwan, we found the small but repetitive ground vibration induced by traffic has considerable effect on the vibration behavior of the high-rise building. This finding urges further investigation not only on the dynamic and continuous interaction between vehicles, roads, and buildings, but also the role of soft sediment on such interaction. [ABSTRACT FROM AUTHOR]

Humans interact with other humans at a variety of timescales and in a variety of social contexts. We exhibit patterns of coordination that may differ depending on whether we are genuinely interacting as part of a coordinated group of individuals vs merely co-existing within the same physical space. Moreover, the local coordination dynamics of an interacting pair of individuals in an otherwise non-interacting group may spread, propagating change in the global coordination dynamics and interaction of an entire crowd. Dynamical systems analyses, such as Recurrence Quantification Analysis (RQA), can shed light on some of the underlying coordination dynamics of multi-agent human interaction. We used RQA to examine the coordination dynamics of a performance of "Welcome to the Imagination World", composed for wind orchestra. This performance enacts a real-life simulation of the transition from uncoordinated, non-interacting individuals to a coordinated, interacting multi-agent group. Unlike previous studies of social interaction in musical performance which rely on different aspects of video and/or acoustic data recorded from each individual, this project analyzes group-level coordination patterns solely from the group-level acoustic data of an audio recording of the performance. Recurrence and stability measures extracted from the audio recording increased when musicians coordinated as an interacting group. Variability in these measures also increased, indicating that the interacting ensemble of musicians were able to explore a greater variety of behavior than when they performed as non-interacting individuals. As an orchestrated (non-emergent) example of coordination, we believe these analyses provide an indication of approximate expected distributions for recurrence patterns that may be measurable before and after truly emergent coordination. [ABSTRACT FROM AUTHOR]

In recent years, there has been an emerging interest in the use of claims and electronic health record (EHR) data for evaluation of medical device safety and effectiveness. In Korea, national insurance electronic data interchange (EDI) code has been used as a medical device data source for common data model (CDM). This study performed a preliminary feasibility assessment of CDM-based vigilance. A cross-sectional study of target medical device data in EHR and CDM was conducted. A total of 155 medical devices were finally enrolled, with 58.7% of them having EDI codes. Femoral head prosthesis was selected as a focus group. It was registered in our institute with 11 EDI codes. However, only three EDI codes were converted to systematized nomenclature of medicine clinical terms concept. EDI code was matched in one-to-many (up to 104) with unique device identifier (UDI), including devices classified as different global medical device nomenclature. The use of UDI rather than EDI code as a medical device data source is recommended. We hope that this study will share the current state of medical device data recorded in the EHR and contribute to the introduction of CDM-based medical device vigilance by selecting appropriate medical device data sources. [ABSTRACT FROM AUTHOR]

Identifying sources and sinks of malaria transmission is critical for designing effective intervention strategies particularly as countries approach elimination. The number of malaria cases in Thailand decreased 90% between 2012 and 2020, yet elimination has remained a major public health challenge with persistent transmission foci and ongoing importation. There are three main hotspots of malaria transmission in Thailand: Ubon Ratchathani and Sisaket in the Northeast; Tak in the West; and Yala in the South. However, the degree to which these hotspots are connected via travel and importation has not been well characterized. Here, we develop a metapopulation model parameterized by mobile phone call detail record data to estimate parasite flow among these regions. We show that parasite connectivity among these regions was limited, and that each of these provinces independently drove the malaria transmission in nearby provinces. Overall, our results suggest that due to the low probability of domestic importation between the transmission hotspots, control and elimination strategies can be considered separately for each region. [ABSTRACT FROM AUTHOR]

The analysis of complex mechanisms underlying ventricular fibrillation (VF) and atrial fibrillation (AF) requires sophisticated tools for studying spatio-temporal action potential (AP) propagation dynamics. However, fibrillation analysis tools are often custom-made or proprietary, and vary between research groups. With no optimal standardised framework for analysis, results from different studies have led to disparate findings. Given the technical gap, here we present a comprehensive framework and set of principles for quantifying properties of wavefront dynamics in phase-processed data recorded during myocardial fibrillation with potentiometric dyes. Phase transformation of the fibrillatory data is particularly useful for identifying self-perpetuating spiral waves or rotational drivers (RDs) rotating around a phase singularity (PS). RDs have been implicated in sustaining fibrillation, and thus accurate localisation and quantification of RDs is crucial for understanding specific fibrillatory mechanisms. In this work, we assess how variation of analysis parameters and thresholds in the tracking of PSs and quantification of RDs could result in different interpretations of the underlying fibrillation mechanism. These techniques have been described and applied to experimental AF and VF data, and AF simulations, and examples are provided from each of these data sets to demonstrate the range of fibrillatory behaviours and adaptability of these tools. The presented methodologies are available as an open source software and offer an off-the-shelf research toolkit for quantifying and analysing fibrillatory mechanisms. [ABSTRACT FROM AUTHOR]