Time Epochs Research Articles

The Emotional Impact of COVID-19 News Reporting: A Longitudinal Study Using Natural Language Processing

The emotional impact of the COVID-19 pandemic and ensuing social restrictions has been profound, with widespread negative effects on mental health. We made use of the natural language processing and large-scale Twitter data to explore this in depth, identifying emotions in COVID-19 news content and user reactions to it, and how these evolved over the course of the pandemic. We focused on major UK news channels, constructing a dataset of COVID-related news tweets (tweets from news organisations) and user comments made in response to these, covering Jan 2020 to April 2021. Natural language processing was used to analyse topics and levels of anger, joy, optimism, and sadness. Overall, sadness was the most prevalent emotion in the news tweets, but this was seen to decline over the timeframe under study. In contrast, amongst user tweets, anger was the overall most prevalent emotion. Time epochs were defined according to the time course of the UK social restrictions, and some interesting effects emerged regarding these. Further, correlation analysis revealed significant positive correlations between the emotions in the news tweets and the emotions expressed amongst the user tweets made in response, across all channels studied. Results provide unique insight onto how the dominant emotions present in UK news and user tweets evolved as the pandemic unfolded. Correspondence between news and user tweet emotional content highlights the potential emotional effect of online news on users and points to strategies to combat the negative mental health impact of the pandemic.

The Epoch-State Filter, Revisited

The epoch-state filter is a recursive sequential estimator that maintains its state estimate and associated covariance at a fixed time known as the epoch, avoiding the need to propagate the covariance between measurements. Instead, the filter maps measurement innovations from the measurement time to the epoch time, in a fashion similar to a batch estimator. When process noise is present, the epoch time must follow all but at most the penultimate measurement. Revisiting the topic, this paper contributes several variations, including a factorized form, a factorized information form, and sigma-point versions, and provides a number of clarifying illustrative examples.

Coupling of Zinc Dose to Frequency in a Regularly Recurrent Pattern Shows a Limited Capacity of Excessive Dietary Zinc to Compensate for a Previously Deficient Intake

The impact of feeding a proportional dose of zinc in a regularly recurrent pattern (idiorrhythmic feeding) on body growth of weanling rats was studied to assess the extent to which an intake exceeding the requirement could compensate for a previously deficient intake. The idiorrhythmic regimen (I) was designed so that the overall dose-time equivalent (modulo; Mx) was kept constant over a selected period of time (epoch; E), whereas the actual dose and frequency varied regularly according to a predetermined pattern; that is, I = dnth(Mx)/dnth, where Mx and dnth are the selected dose-time equivalent and the sequential number of zinc-dosing days, respectively. For example, 3 mg Zn·kg-1 diet fed every day (I = 3/1) and 24 mg Zn·kg-1 diet fed 1 d in an 8-d period (7 d of feeding a zinc-deficient diet) (I = 24/8) are dose-time equivalents because they both provide 72 mg Zn·kg-1 over a 24-d E. Modulos of M3, M6, M12 and M24 were used, which provided 3, 6, 12 and 24 mg Zn·kg-1·d-1 dose-time equivalents during a 24-d E. Each modulo had seven analogous idiorrhythms: I = Mx/1, 2Mx/2, 3Mx/3, 4Mx/4, 5Mx/5, 6Mx/6 and 8Mx/8; for example, with 8 Mx/8, 24, 48, 96 or 192 mg Zn·kg-1 diet was fed every 8th d; on the other 7 d a diet without a zinc supplement was fed for M3, M6, M12 and M24, respectively. Zinc dose-rate idiorrhythm generated a complex, gestalt-like, biphasic growth response pattern where an intake of dietary zinc exceeding requirements had either no effect (M3 or average of 3 mg kg-1 diet) or fully compensated for only 1 (M6 and M12 or average of 6 and 12 mg Zn·kg-1 diet) or 2 (M24 or average of 24 mg Zn·kg-1 diet) d.

A time series analysis approach to forecast price fluctuation points

ABSTRACT For manufacturers, material procurement and product sales directly influence cash flows. Buying materials at lower prices and selling products at higher prices is the easiest way to increase revenue. If a company can predict the price fluctuations in materials or products accurately, then it can maximize its profit by taking the appropriate action at the right time. This study proposes a novel price fluctuation forecast model, that is, the price fluctuation point forecast approach (PFPFA), to anticipate price fluctuation points and the degrees of price changes. Price fluctuation data are non-uniform time series. Hence, this study focuses on the quantities that predict price fluctuation points rather than the price fluctuation time epoch. The PFPFA encompasses four models to predict the price fluctuation points and three models to predict the price differences between periods. Thus, for each product, 12 forecast outcomes are possible. Applied to a real-world scenario and compared with exponential smoothing, the PFPFA offers acceptable predictions about price fluctuation points and performs better with regard to the degrees of price changes.

Noise in cesarean deliveries: a comprehensive analysis of noise environments in the Labor and Delivery operating room and evaluation of a visual alarm noise abatement program

Cesarean deliveries are the most common major surgery worldwide. Noise in healthcare settings leads to impaired communication, concentration, and stress among health care providers. Limited information is available about noise at cesarean delivery. Our aim was to achieve a comprehensive analysis of noise that occurs during cesarean deliveries. Sound level meters are used to determine baseline noise levels and to describe the frequency of acute noise that is generated during a cesarean that will cause a human startle response. Secondarily, we will evaluate the effectiveness of a visual alarm system to mitigate excessive noise. We completed a pre-intervention/post-intervention observational study of noise levels during cesarean deliveries before and after introduction of a visual alarm system for noise mitigation between 2/15/2021 to 8/26/2021. There were 156 cases included from each study period. Sound pressure levels were analyzed by overall case median decibel levels and by time epoch for relevant phases of the operation. Rapid increase noise events capable of causing a human startle response, "Startle events" were detected a by retrospective analysis, with quantification for baselines and analysis of frequency by case type. Median noise levels with inter-quartile ranges [I.Q.R.] are presented. Data are compared between epochs and case characteristics with non-parametric two-tailed testing. The median acoustic pressure for all cesarean deliveries was 61.8 [58.8, 65.9] dBA (median [I.Q.R.]). The median dBA for the full case time period was significantly higher during cases with NICU team presence, 62.1 [60.5, 63.9]; neonatal admission to the NICU, 62.0 [60.4, 63.9]; 5-minute APGAR score less than 7, 62.2 [61.1, 64.3]; multiple gestations, 62.6 [62.0, 64.2]; and intraoperative tubal sterilization, 62.8 [61.5, 65.1]. The use of visual alarms was associated with a statistically significant reduction of median noise level by 0.7 dBA, from 61.8 [60.6, 63.5] dBA to 61.1 [59.8, 63.7] dBA, (p<0.001). The noise intensities recorded during cesarean deliveries were commonly at levels that affect communication and concentration, and above the safe levels recommended by the W.H.O. Although noise was reduced by 0.7 dBA, the reduction was not clinically significant to reduce noise a discernible amount (a 3dB change) nor in reducing "startle events". Isolated use of visual alarms during cesarean deliveries is unlikely to be a satisfactory noise mitigation strategy.

Abstract 70: Reducing Onset-to-reperfusion Times Through The Implementation Of A Prehospital Large-vessel Occlusion Bypass Protocol: A Real-world Experience

Introduction: Time to endovascular treatment (EVT) is a major determinant of patient outcomes for large vessel occlusion (LVO) strokes. Delays in interfacility transfers, however, can limit treatment efficacy. The Cincinnati Stroke Triage Assessment Tool (C-STAT) is a pre-hospital screen used to identify patients suspected of having LVOs. In October 2019, the “Oahu LVO Bypass Protocol” was adopted island-wide for all EMS evaluations. In this protocol, patients with C-STAT+ scores bypassed the nearest local hospital and were diverted to a Comprehensive Stroke Center (CSC). Our study aims to identify how this protocol has impacted onset-to-reperfusion times for patients with LVOs. Methods: A retrospective chart review was performed on all patients receiving EVT from January 1 st , 2017 to February 1 st , 2022. Patients were dichotomized into pre and post bypass groups using October 1 st , 2019 as the implementation date. All non-EMS transfers, posterior circulation strokes, and patients &gt;8 hours from symptom onset were excluded from analysis. We compared the two time epochs using descriptive statistics and an interrupted time-series analysis (ITS). Results: During the 5-year study period, 520 patients received EVT at our institution with an average age of 70.6 and median NIHSS of 19. A total of 115 patients met inclusion for the pre-bypass cohort and 172 patients for the post-bypass cohort. Significant reductions were observed in the median times (pre-bypass(min) [IQR] vs. post-bypass(min) [IQR]) from onset-to-CSC arrival (140[65-214] vs. 68[46-157], p&lt;.001) and onset-to-reperfusion (233[167-310] vs. 189[151-250], p=.005) without significant delay in onset-to-tPA time (100[70-169] vs. 88[67-119], p=.121). The proportion of interfacility EVT transfers also declined from 51% to 17% between the pre and post bypass eras (p&lt;0.001). On ITS analysis, the mean and median level of onset-to-CSC arrival times were significantly reduced by 30% and 51%, respectively. This reduction in treatment time was maintained for a 28-month post-bypass period. Conclusion: Implementation of the Oahu LVO bypass protocol shows significant reduction in onset-to-reperfusion times without delays to tPA administration, while also reducing rates of interfacility transfers.

Input Shape Effect on Classification Performance of Raw EEG Motor Imagery Signals with Convolutional Neural Networks for Use in Brain—Computer Interfaces

EEG signals are interpreted, analyzed and classified by many researchers for use in brain-computer interfaces. Although there are many different EEG signal acquisition methods, one of the most interesting is motor imagery signals. Many different signal processing methods, machine learning and deep learning models have been developed for the classification of motor imagery signals. Among these, Convolutional Neural Network models generally achieve better results than other models. Because the size and shape of the data is important for training Convolutional Neural Network models and discovering the right relationships, researchers have designed and experimented with many different input shape structures. However, no study has been found in the literature evaluating the effect of different input shapes on model performance and accuracy. In this study, the effects of different input shapes on model performance and accuracy in the classification of EEG motor imagery signals were investigated, which had not been specifically studied before. In addition, signal preprocessing methods, which take a long time before classification, were not used; rather, two CNN models were developed for training and classification using raw data. Two different datasets, BCI Competition IV 2A and 2B, were used in classification processes. For different input shapes, 53.03-89.29% classification accuracy and 2-23 s epoch time were obtained for 2A dataset, 64.84-84.94% classification accuracy and 4-10 s epoch time were obtained for 2B dataset. This study showed that the input shape has a significant effect on the classification performance, and when the correct input shape is selected and the correct CNN architecture is developed, feature extraction and classification can be done well by the CNN architecture without any signal preprocessing.

Very High Resolution Images and Superpixel-Enhanced Deep Neural Forest Promote Urban Tree Canopy Detection

Urban tree canopy (UTC) area is an important index for evaluating the urban ecological environment; the very high resolution (VHR) images are essential for improving urban tree canopy survey efficiency. However, the traditional image classification methods often show low robustness when extracting complex objects from VHR images, with insufficient feature learning, object edge blur and noise. Our objective was to develop a repeatable method—superpixel-enhanced deep neural forests (SDNF)—to detect the UTC distribution from VHR images. Eight data expansion methods was used to construct the UTC training sample sets, four sample size gradients were set to test the optimal sample size selection of SDNF method, and the best training times with the shortest model convergence and time-consumption was selected. The accuracy performance of SDNF was tested by three indexes: F1 score (F1), intersection over union (IoU) and overall accuracy (OA). To compare the detection accuracy of SDNF, the random forest (RF) was used to conduct a control experiment with synchronization. Compared with the RF model, SDNF always performed better in OA under the same training sample size. SDNF had more epoch times than RF, converged at the 200 and 160 epoch, respectively. When SDNF and RF are kept in a convergence state, the training accuracy is 95.16% and 83.16%, and the verification accuracy is 94.87% and 87.73%, respectively. The OA of SDNF improved 10.00%, reaching 89.00% compared with the RF model. This study proves the effectiveness of SDNF in UTC detection based on VHR images. It can provide a more accurate solution for UTC detection in urban environmental monitoring, urban forest resource survey, and national forest city assessment.

An Anonymous Authentication With Received Signal Strength Based Pseudonymous Identities Generation for VANETs

Our proposed key stream derived from shared key generation process based on received signal strength (RSS) represents pseudonymous identities (PIDs) utilized in an anonymous authentication is obtained through an interactive connection between communicating mobile users and an authorized entity taken over by a Group Manager (GM). This process goal is fetching some credentials in advance, when mobile users actively and anonymously are playing their role in the system. These PIDs could be embedded in the credential equipped to the participating mobile users. They should be usually unique and must be secured from any adversary when doing any either attack or treat. In this paper, our proposed shared key generation derived from RSS between communicating mobile users and GM provides unique PIDs. Then, the embedded PID at an epoch time as a part of mobile users secret key together with credential components are used for signing a message anonymously. Based on PID at epoch time and updated revocation list obtained from GM, verifier user ensures the validity of signature. The measurement scenario of system performance is done by varying the traffic conditions either quiet or crowded to create communication impairment combined with mobile users’ speed varying on 20 km/h, 40 km/h, and 60 km/h respectively. The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ping</i> time interval is varied as well, it is configured to 7 ms, 10 ms, and 20 ms, respectively. Here, the result of evaluation showed that PIDs generation works properly by the number of generated PIDs up to 11 with the highest correlation is achieved up to 0.99. Meanwhile, quantization algorithm works properly for 3000 or more ICMP packets and achieves zero key disagreement rate (KDR). Total signing and verification times are sufficient practical about 90 ms and 100 ms, respectively.

Origin of the philosophy of agricultural farming in Uzbekistan

The human world and its sustainable development is, first of all, the creation of material goods, ensuring a prosperous life and the implementation of creative work, an important component of the life of the state and society, which is the main criterion, the principle of human life and capital. Naturally, the main goal at the level of understanding the policy pursued by the head of our country and its fundamental nature is the formation of the middle stratum and the movement of farming, which is considered its basis, its development based on the requirements of a comprehensive period and time, improvement of organizational and legal foundations, development in harmony with advanced national and foreign experience is an urgent task. From this point of view, the fact that the Andijan Agricultural School and its role in the socio-economic development of our country are great, and its philosophical coverage through the essence of the epoch in space and time is a factor, a guarantee of modern science and sustainable development. This article examines the origin of the philosophy of farming in Uzbekistan. Consequently, the contribution of scientists and their contribution to the farming movement, in particular the Andijan school in increasing the quality and productivity of agricultural products, as well as the peculiarities of agricultural development today have been discussed.

Quality metrics in the management of acute stroke in Greece during the first 5 years of Registry of Stroke Care Quality (RES-Q) implementation.

Establishment of a prospective stroke registry may promote the documentation and improvement of acute stroke care. We present the status of stroke management in Greece using the Registry of Stroke Care Quality (RES-Q) dataset. Consecutive patients with acute stroke were prospectively registered in RES-Q registry by contributing sites in Greece during the years 2017-2021. Demographic and baseline characteristics, acute management, and clinical outcomes at discharge were recorded. Stroke quality metrics, with a specific interest in the association between acute reperfusion therapies and functional recovery in ischemic stroke patients are presented. A total of 3590 acute stroke patients were treated in 20 Greek sites (61% men, median age 64 years; median baseline NIHSS 4; 74% ischemic stroke). Acute reperfusion therapies were administered in almost 20% of acute ischemic stroke patients, with a door to needle and door to groin puncture times of 40 and 64 min, respectively. After adjustment for contributing sites, the rates of acute reperfusion therapies were higher during the time epoch 2020-2021 compared to 2017-2019 (adjusted OR 1.31; 95% CI 1.04-1.64; p < 0.022; Cochran-Mantel-Haenszel test). After propensity-score-matching, acute reperfusion therapies administration was independently associated with higher odds of reduced disability (one point reduction across all mRS scores) at hospital discharge (common OR 1.93; 95% CI 1.45-2.58; p < 0.001). Implementation and maintenance of a nationwide stroke registry in Greece may guide the stroke management planning, so that prompt patient transportation, acute reperfusion therapies, and stroke unit hospitalization become more widely accessible, improving the functional outcomes of stroke patients.

Acoustic positioning of multiple AUVs by an ASV: experimental validation and performance characterisation

Cooperation among heterogeneous marine vehicles can offer several benefits to underwater applications, such as supporting the navigation of submerged robots by leveraging the information available to a surface vehicle. Within such context, this paper describes an acoustic positioning and communication protocol developed for the localisation of multiple Autonomous Underwater Vehicles (AUVs) by means of an Autonomous Surface Vehicle (ASV) equipped with an Ultra-Short BaseLine (USBL) device. To avoid packet collisions, access to the acoustic channel is managed through a time slot division mechanism. Unlike a classical Time Division Multiple Access (TDMA) protocol, the approach considered in this work consists of a centralised scheduling handled by the ASV, in which AUVs are localised at regular time epoch but can transmit only when queried. This allows to prioritise the number of position measurements taken by the ASV and then relayed back to the submerged vehicles, with the final goal of improving the navigation accuracy of the latter. The solution is also designed to handle the latency of acoustic communication and to correctly associate each position measurement with the corresponding acquisition time. Furthermore, it does not require any a priori synchronisation between the clocks of the vehicles involved and ensures complete decoupling between their navigation algorithms. Experimental activities in very-shallow waters, involving an ASV and two target nodes, were carried out to validate the multi-AUVs positioning system and to provide a characterisation of its performance.

Methods for calculating ventilation rates during resuscitation from out-of-hospital cardiac arrest

ObjectiveVentilation control is important during resuscitation from out-of-hospital cardiac arrest (OHCA). We compared different methods for calculating ventilation rates (VR) during OHCA. MethodsWe analyzed data from the Pragmatic Airway Resuscitation Trial, identifying ventilations through capnogram recordings. We determined VR by: 1) counting the number of breaths within a time epoch (“counted” VR), and 2) calculating the mean of the inverse of measured time between breaths within a time epoch (“measured” VR). We repeated the VR estimates using different time epochs (10, 20, 30, 60 sec). We defined hypo- and hyperventilation as VR <6 and >12 breaths/min, respectively. We assessed differences in estimated hypo- and hyperventilation with each VR measurement technique. ResultsOf 3,004 patients, data were available for 1,010. With the counted method, total hypoventilation increased with longer time epochs ([10-s epoch: 75 sec hypoventilation] to [60-s epoch: 97 sec hypoventilation]). However, with the measured method, total hypoventilation decreased with longer time epochs ([10-s epoch: 223 sec hypoventilation] to [60-s epoch: 150 sec hypoventilation]). With the counted method, the total duration of hyperventilation decreased with longer time epochs ([10-s epochs: 35 sec hyperventilation] to [60-s epoch: 0 sec hyperventilation]). With the measured method, total hyperventilation decreased with longer time epochs ([10-s epoch: 78 sec hyperventilation] to [60-s epoch: 0 sec hyperventilation]). Differences between the measured and counted estimates were smallest with a 60-s time epoch. ConclusionsQuantifications of hypo- and hyperventilation vary with the applied measurement methods. Measurement methods are important when characterizing ventilation rates in OHCA.

Peak movement and impact characteristics of different training methods in professional rugby union

ABSTRACT The purpose of this study was to compare the peak periods (1- to 6-minute epochs) for three different training methods (game-based training – GBT; small-sided games – SSG; and conditioning training – CT) in elite male rugby union (RU) players. The peak movement (m·min−1) and impact (impact·min−1) characteristics of 42 players during in-season training were assessed. When comparing between training methods, SSG drills produced the greatest peak movement characteristics for all time epochs (1-minute average peak periods – SSG 195 m·min−1, GBT 160 m·min−1, and CT 144 m·min−1). The peak impact characteristics performed during training were 1–2 impact·min−1 for a 1-minute period and then decreased as the time period increased for all training methods. The greatest distribution of training time occurred at 30–39% (SSG and CT) and 40–49% (GBT) of peak movement intensity, with less than 5% of training performed at or above 80% peak intensity across all drill types. Findings from the current study show that the peak movement periods (m·min−1) in RU training from all three training methods match or exceed those which are previously reported in peak gameplay, yet their ability to replicate peak impact characteristics is questionable.

The relationship between single muscle fibre and voluntary rate of force development in young and old males.

It is suggested that the early phase (< 50ms) of force development during a muscle contraction is associated with intrinsic contractile properties, while the late phase (> 50ms) is associated with maximal force. There are no direct investigations of single muscle fibre rate of force development (RFD) as related to joint-level RFD METHODS: Sixteen healthy, young (n = 8; 26.4 ± 1.5 yrs) and old (n = 8; 70.1 ± 2.8 yrs) males performed maximal voluntary isometric contractions (MVC) and electrically evoked twitches of the knee extensors to assess RFD. Then, percutaneous muscle biopsies were taken from the vastus lateralis and chemically permeabilized, to assess single fibre function. At the joint level, older males were ~ 30% weaker and had ~ 43% and ~ 40% lower voluntary RFD values at 0-100 and 0-200ms, respectively, than the younger ones (p ≤ 0.05). MVC torque was related to every voluntary RFD epoch in the young (p ≤ 0.001), but only the 0-200ms epoch in the old (p ≤ 0.005). Twitch RFD was ~ 32% lower in the old compared to young (p < 0.05). There was a strong positive relationship between twitch RFD and voluntary RFD during the earliest time epochs in the young (≤ 100ms; p ≤ 0.01). While single fibre RFD was unrelated to joint-level RFD in the young, older adults trended (p = 0.052-0.055) towards significant relationships between joint-level RTD and Type I single fibre RFD at the 0-30ms (r2 = 0.48) and 0-50ms (r2 = 0.49) time epochs. Electrically evoked twitches are good predictors of early voluntary RFD in young, but not older adults. Only the older adults showed a potential relationship between single fibre (Type I) and joint-level rate of force development.

Superposed epoch analysis using time-normalization: A Python tool for statistical event analysis

A superposed epoch analysis (SEA) is a simple, yet powerful statistical analysis technique, used to identify patterns in the temporal evolution of observed quantities relative to defined epochs. In some cases, the event duration and time between epochs (epoch length) can be highly variable. If the measured response scales with the event duration or epoch length, then the underlying temporal patterns can be suppressed when analyzed in absolute time. In this article, we describe an adaptation of the traditional SEA, where we apply time-normalization to each event and present a Python package sea_norm which implements the time-normalized SEA. Rather than defining a singular epoch time, a start, epoch, and end time are defined for each event, separating each event into two intervals. For every event, the duration of both intervals is normalized to a common time axis, essentially stretching or compressing each interval, such that each respective epoch interval is the same length for all events. This technique has the advantage of identifying temporal patterns not observed in a traditional SEA. Given a time series, a list of event start, epoch, and end times, and specified binning dimensions the Python package sea_norm returns a time-normalized SEA analysis of the time-series. This technique is widely applicable across the Space Physics field, where events have defined start and end times, and where the response to those events may scale proportionally with event length. We provide examples demonstrating how the SEA code works with one-dimensional and two-dimensional time series, and how users can specify their own statistics to use in the superposed analysis (e.g., percentiles).

Abstract 14850: Effect of Therapeutic-Dose Heparin on Acute Kidney Injury in Non-Critically Ill Hospitalized Patients With Covid-19: The Activ4a and Attac Randomized Trial

Background: Acute kidney injury (AKI) is common in patients with COVID-19 and mediated, in part, by thromboinflammation. In non-critically ill patients with COVID-19, therapeutic-dose anticoagulation with heparin increased the probability of survival to hospital discharge with reduced use of cardiovascular or respiratory organ support. We investigated whether therapeutic-dose heparin reduces the incidence of AKI or death in non-critically ill patients hospitalized for COVID-19. Methods: Non-critically ill patients hospitalized for COVID-19 were enrolled in an open-label, multiplatform randomized trial of therapeutic-dose heparin versus usual-care pharmacologic thromboprophylaxis. The primary endpoint of this analysis was in-hospital diagnosis of AKI or death. AKI was defined as Kidney Disease Improving Global Outcomes stage 2 or 3 AKI (≥2-fold increase in serum creatinine or initiation of renal replacement therapy). A Bayesian statistical model estimated the risk of AKI or death between those randomized to therapeutic-dose anticoagulation versus usual-care thromboprophylaxis, adjusted for age, sex, D-dimer, time epoch, country, site, and platform. Results: Among 1922 enrolled from ACTIV4a and ATTACC, 23 were excluded due to ESRD at enrollment. Baseline or follow-up creatinine was missing for 205 individuals. Among 1694 participants analyzed, median age was 60, 58% were men, and median baseline creatinine was 0.9 mg/dL. The primary endpoint occurred in 83 participants (4.9%); 4.4% assigned to therapeutic-dose heparin and 5.5% assigned to thromboprophylaxis (adjusted relative risk [aRR] 0.72, 95% CrI 0.47-1.10; posterior probability of superiority [defined as relative risk &lt; 1.0] was 93.6%). Therapeutic-dose anticoagulation was associated with a 97.7% probability of superiority to reduce the composite of stage 3 AKI or death (3.1% vs. 4.6%; aRR 0.64, 95% CrI 0.40-0.99) compared to usual-care thromboprophylaxis. Conclusions: Therapeutic-dose anticoagulation with heparin was associated with a high probability of superiority to reduce the incidence of in-hospital stage 3 AKI or death in non-critically ill patients hospitalized for COVID-19, compared with usual-care thromboprophylaxis.

Decline of geomagnetic and ionospheric activity at earthquake during spotless Sun

We investigate the geomagnetic and ionospheric effects of seismic activity during 1954 Sun spotless days (SSL) from 1995 to 2020. Two subsets of earthquakes (EQ) are evaluated for 676 events observed with the depth D1 ≤ 30 km and 1278 events with D2 > 30 km and the total set SSL. Newly developed 1 h geomagnetic index Hpo and the ionospheric WEQ index are used for the comparisons with the daily peak earthquake. The ionosphere WEQ index is derived at the EQ epicenter from JPL GIM-TEC map within the cell of 2.5°×5°, in latitude φ and longitude λ surrounding the epicenter at radius of about 200 km. We use the method of superposed epoch with the zero epoch time t0 taken at EQ to extract peak values of Hpo and WEQ during t0-24 h ≤ t < t0 (preEQ) and t0 < t ≤ t0 + 24 h (postEQ). It is found that the magnitude of Hpo(t0) is less that the both peaks of Hpo(preEQ) and Hpo(postEQ) in 91 % of events independent of EQ’s depth. Similar effect is observed with the peak of the positive/negative ionosphere indices and the absolute values of |W(preEQ)| and |W(postEQ)| the both exceeding |WEQ| in 77 % of events. The seismic activity tends to increase towards the solar minimum when SSLs occur. Our results provide evidence that EQ-related geomagnetic and ionospheric activities experience decline of intensity at the time of EQ under SSL.

Deep and shallow fast embedded capsule networks: going faster with capsules

Capsule Networks (CapsNets) is a great approach for understanding data in the field of computer vision. CapsNets allow a deeper understanding of images compared to the traditional Convolutional Neural Networks. The first test for CapsNet was in digits recognition on the ‘MNIST’ dataset, where it successfully achieved high accuracy. CapsNets are reliable at deciphering overlapping digits. Deep Capsule Networks achieved state-of-the-art accuracy in CIFAR10 which isn’t achieved by shallow capsule networks. Despite all these accomplishments, Deep Capsule Networks are very slow due to the ‘Dynamic Routing’ algorithm. In this paper, Fast Embedded Capsule Network and Deep Fast Embedded Capsule Network are introduced, representing novel capsule network architectures that uses 1D convolution based dynamic routing with a fast element-wise multiplication transformation process. These architectures not only compete with the state-of-the-art methods in terms of accuracy in the capsule domain, but also excels in terms of speed, and reduced complexity. This is shown by the 58% reduction in the number of trainable parameters and 64% reduction in the average epoch time in the training process. Experimental results shows excellent and verified properties.

An increase in relative contribution of compensatory postural adjustments during voluntary movement while standing in adolescents and young adults with bilateral spastic cerebral palsy.

Previous studies have revealed several deficits in anticipatory postural adjustments (APAs) during voluntary movements while standing in individuals with bilateral spastic cerebral palsy (BSCP). However, it remains unclear whether compensatory postural adjustments (CPAs) during movement increase to compensate for APA deficits. We investigated the anticipatory and compensatory activities of postural muscles during voluntary movement while standing in adolescents and young adults with BSCP. The study included seven participants with BSCP with level II on the Gross Motor Function Classification System (GMFCS), seven with BSCP with level III on the GMFCS, and fourteen healthy controls. The participants stood on a force platform and lifted a load under two weight conditions (light and heavy). The electromyographic activities of postural muscles were analyzed at time intervals typical for APAs and CPAs. The percentage of muscle activity in the CPA time epoch against the total muscle activity during the APA and CPA time epochs was higher in the two BSCP groups than in the control group. In the control group, a load-related modulation was observed only in the APA time epoch, whereas in the BSCP-II group, the load-related increase was observed in both the APA and CPA time epochs. No load-related modulations were observed in the BSCP-III group. These findings suggest that adolescents and young adults with BSCP exhibit an increase in the relative contribution of CPAs during voluntary movement and that there exist severity-related differences in the modulation of APAs and CPAs.