Miracle-dz/UniFAR-FTUs huggingface dataset:
Time to Seek Care and Hospital Length of Stay Among Older Adults With Acute Coronary Syndrome During the COVID-19 Pandemic

The prevalence of prehospital delay is high among older adults with acute coronary syndrome (ACS). The current study aimed to examine the associated factors of prehospital delay among patients with ACS during the COVID-19 pandemic. This cross-sectional study was conducted on a convenience sample of 300 older adults with ACS admitted to the emergency department in Jordan. Data were collected from June 1 to September 1, 2020. Bivariate and multivariate analyses were used to explore the predictors of prehospital delay. Being widowed, educational level, pain intensity, the gradual onset of ACS symptoms, symptoms lasting for more than 30 minutes, patients’ feeling anxious about their ACS symptoms, patients’ perceiving their symptoms to be particularly dangerous, history of myocardial infarction (MI), and mode of transportation were associated with the time taken before seeking emergency care. Significant predictors of time to seek help were chief complaint of chest pain or palpitations, abrupt onset of symptoms, the associated symptom of vertigo, and a higher number of chronic illnesses; they explained about 17.9% of the variance in the time to seek care. The average time to seek care among patients with ACS during the COVID-19 pandemic was found to be longer than the average time reported by studies conducted prior the pandemic. Improved understanding of the associations between prehospital delay is crucial for optimal ACS patient outcomes under the impacts of the COVID-19 pandemic.
A Case of Post-COVID-19–Associated Paracentral Acute Middle Maculopathy and Giant Cell Arteritis-Like Vasculitis

Abstract: A 47-year-old man with a history of COVID-19 infection 2 months before presentation, presented with a scotoma of the paracentral visual field of the right eye. After thorough testing and evaluation, a diagnosis of paracentral acute middle maculopathy (PAMM) was established. Two months later, the patient developed temporal headache and jaw claudication. High-dose steroids were initiated, and workup for giant cell arteritis (GCA) was undertaken. The patient experienced resolution of the symptoms within 24 hours of steroid initiation. ESR, CRP, and temporal artery biopsy results were normal, although all were obtained more than 2 weeks after steroid initiation. To the best of our knowledge, our patient represents the first individual to date to potentially implicate COVID-19 in both small and large vessel vasculitis in the ophthalmic setting.
Time-of-flight and noise-correlation-inspired algorithms for full-field shear-wave elastography using digital holography

Abstract. Significance: Quantitative stiffness information can be a powerful aid for tumor or fibrosis diagnosis. Currently, very promising elastography approaches developed for non-contact biomedical imaging are based on transient shear-waves imaging. Transient elastography offers quantitative stiffness information by tracking the propagation of a wave front. The most common method used to compute stiffness from the acquired propagation movie is based on shear-wave time-of-flight calculations. Aim: We introduce an approach to transient shear-wave elastography with spatially coherent sources, able to yield full-field quantitative stiffness maps with reduced artifacts compared to typical artifacts observed in time-of-flight. Approach: A noise-correlation algorithm developed for passive elastography is adapted to spatially coherent narrow or any band sources. This noise-correlation-inspired (NCi) method is employed in parallel with a classic time-of-flight approach. Testing is done on simulation images, experimental validation is conducted with a digital holography setup on controlled homogeneous samples, and full-field quantitative stiffness maps are presented for heterogeneous samples and ex-vivo biological tissues. Results: The NCi approach is first validated on simulations images. Stiffness images processed by the NCi approach on simulated inclusions display significantly less artifacts than with a time-of-flight reconstruction. The adaptability of the NCi algorithm to narrow or any band shear-wave sources was tested successfully. Experimental testing on homogeneous samples demonstrates similar values for both the time-of-flight and the NCi approach. Soft inclusions in agarose sample could be resolved using the NCi method and feasibility on ex-vivo biological tissues is presented. Conclusions: The presented NCi approach was successful in computing quantitative full-field stiffness maps with narrow and broadband source signals on simulation and experimental images from a digital holography setup. Results in heterogeneous media show that the NCi approach could provide stiffness maps with less artifacts than with time-of-flight, demonstrating that a NCi algorithm is a promising approach for shear-wave transient elastography with spatially coherent sources.
Effect and mechanism of propranolol on promoting osteogenic differentiation and early implant osseointegration

The present study aimed to investigate the effect of β-receptor blocker propranolol on early osseointegration of pure titanium implants and the underlying molecular regulatory mechanisms. An implant osseointegration model using the tibial metaphysis of New Zealand rabbits was established. The rabbits were divided into control and low-, medium- and high-dose propranolol groups. The formation of implant osseointegration was detected by X-ray scanning. Mesenchymal stem cells (MSCs) and osteoblasts (OBs) were isolated and cultured in vitro, isoproterenol was supplemented to simulate sympathetic action and propranolol was subsequently administrated. The effect of propranolol on cell proliferation and osteogenic differentiation were assessed by EdU, flow cytometry, alizarin red staining and alkaline phosphatase (ALP) detection. The expression levels of bone morphogenetic protein (BMP)2, RUNX family transcription factor (RunX)2, collagen (COL)-1, osteocalcin (OCN) and β2-adrenergic receptor (AR) were detected by immunofluorescence, reverse transcription-quantitative PCR and western blot assay. Propranolol effectively promoted implant osseointegration in vivo, facilitated proliferation of OBs, inhibited proliferation of MSCs and enhanced osteogenic differentiation of OBs and MSCs. The calcium content and ALP activity of cells treated with propranolol were markedly higher than in the control group. Propranolol also elevated mRNA and protein expression levels of BMP2, RunX2, COL-1 and OCN in tissue and cells, and decreased the expression of β2-AR. The present study demonstrated that the β-receptor blocker propranolol promoted osteogenic differentiation of OBs and MSCs and enhanced implant osseointegration. The present study provided a novel insight into the application and regulatory mechanisms of propranolol.
Recent increase in pertussis incidence in Korea: an age-period-cohort analysis

OBJECTIVES Pertussis or whooping cough—one of the most contagious diseases—is caused by the Gram-negative bacterium Bordetella pertussis. Despite a high vaccination rate, Korea recently experienced a resurgence of pertussis. This study explores patterns and possible explanations for this resurgence through an age-period-cohort analysis. METHODS Using secondary data from the infectious disease portal of the Korea Disease Control and Prevention Agency and the Korea Statistical Information Service of Statistics Korea, this study analyzed the incidence of pertussis in Korea to determine which factors contributed to the recent increase using an age-period-cohort model. RESULTS Analysis of the age effect indicated that the age group most vulnerable to pertussis was 0-year to 2-year-olds. Analysis of the period effect showed a sharp increase in the incidence rate after 2016. Analysis of the cohort effect showed a significant decrease in incidence beginning with the 1955 birth cohort, with the risk increasing again with the 2000s birth cohort. CONCLUSIONS Previous studies have suggested 3 main possible explanations for our results. First, the increased incidence rate can be attributed to contact rates. Second, the rate of immunity through natural exposure has decreased due to the low number of circulating pathogens, in turn affecting the trend of infection. Lastly, variations in pathogens may have also contributed to the increase in incidence. Given that the most significant increase in incidence was observed among infants younger than 1 year old, sufficient maternal immunity must be prioritized to provide passive immunity to newborns via the placenta.
Positive-word stimuli via a smartphone application have no immediate-term effects on multi-directional reach ability in standing position: a randomized controlled trial

Abstract Objectives The purpose of the study was to examine the immediate-term effect of positive-word stimuli via a smartphone application on the multi-directional reach ability in standing position in young adults. Methods This study was an immediate-term, assessor-blinded, two-arm, parallel-group, randomized controlled trial among young adults recruited from one university in Japan. Participants were randomly assigned to the experimental group or control group using a computer-based random number-generating programme. Participants of the experimental group used an application on iPhone and watched 3-min videos displaying positive-word stimuli. This application repeatedly displayed positive-word stimuli every 5 s. The participants of the control group used an application on iPhone and watched the same videos as in the experimental group. However, a positive-word stimulus did not appear in the videos. The primary outcome was the multi-directional reach test (MDRT) from baseline to immediately after the intervention protocol. Results Among the 62 randomized participants (experimental group, n = 31; control group, n = 31), 62 (100%) completed the MDRT immediately after the intervention protocol. There were no differences in mean group change values in MDRT between the experimental and control groups. Conclusions Among young adults, positive-word stimuli via a smartphone application did not significantly improve multi-directional reach ability in standing position. These findings do not support the superiority of this intervention among young adults. Trial Registration: Clinicaltrials.gov, NCT03546218. Registered 6 June 2018, https://clinicaltrials.gov/ct2/show/NCT03546218 KEY MESSAGES In our study, among young adults, positive-word stimuli via an SPSRS application did not significantly improve the multi-directional reach ability in the standing position. These findings do not support the superiority of this intervention among young adults.
Altering the Multimodal Resonance in Ultrathin Silicon Ring for Tunable THz Biosensing

A technique is implemented for altering the multimodal resonance generated in an ultrathin silicon ring resonator-based terahertz (THz) absorber. The absorber provides the dual-band resonance with the excitation of magnetic and electric dipole in the lower and upper band, respectively. The field of magnetic and electric dipoles is altered using a non-resonant graphene ring placed in the center of the generated dipolar arrangement and the tunability and perfect absorption is achieved. A circuit model is prepared using transmission line method and absorber operation is verified. The proposed absorber can be utilized as a biosensor for the detection of malaria virus and glucose percentage in water. The sensor offers highest sensitivity as 0.29 and 0.27 THz per thickness unit change and quality factor as 117.53 and 245 in the lower and upper band, respectively during the sensing of analyte thickness. Also, it offers the sensitivity as 0.20 and 0.10 THz per refractive index unit change and quality factor as 105.28 and 211.84 in the lower and upper band, respectively during refractive index sensing. Moreover, the structure remains insensitive to polarization angle of the incident electromagnetic wave.
Increasing the Utility of the Comprehensive Assessment of Psychopathic Personality–Lexical Rating Scale (CAPP-LRS): Instrument Adaptation and Simplification

The Comprehensive Assessment of Psychopathic Personality–Lexical Rating Scale (CAPP-LRS) is a self-report instrument designed to index psychopathy according to the CAPP psychopathy framework. Developed with the expressed goal of advancing the state of knowledge regarding the specific features of psychopathy, the CAPP model and associated instruments have garnered increasing attention and support in the field. Despite the conceptual strength of the CAPP model, the advanced lexical structure of its primary research tool (the CAPP-LRS) has led researchers to question the utility of the instrument for use with some populations of interest (e.g., forensic/correctional and adolescent/young adult samples). The aim of the present work was to address this issue by creating a lexically simplified, though functionally equivalent, version of the CAPP-LRS to increase accessibility to critically relevant populations. A set of two studies (N = 602) describes the adaptation protocol and the initial validation of the modified instrument.
Common and unique structural plasticity after left and right hemisphere stroke

Strokes to the left and right hemisphere lead to distinctive behavioral profiles. Are left and right hemisphere strokes (LHS and RHS) associated with distinct or common poststroke neuroplasticity patterns? Understanding this issue would reveal hemispheric neuroplasticity mechanisms in response to brain damage. To this end, we investigated poststroke structural changes (2 weeks to 3 months post-onset) using longitudinal MRI data from 69 LHS and 55 RHS patients and 31 demographic-matched healthy control participants. Both LHS and RHS groups showed statistically common plasticity independent of the lesioned hemisphere, including 1) gray matter (GM) expansion in the ipsilesional and contralesional precuneus, and contralesional superior frontal gyrus; 2) GM shrinkage in the ipsilesional medial orbital frontal gyrus and middle cingulate cortex. On the other hand, only RHS patients had significant GM expansion in the ipsilesional medial superior and orbital frontal cortex. Importantly, these common and unique GM changes post-stroke largely overlapped with highly-connected cortical hub regions in healthy individuals. Moreover, they correlated with behavioral recovery, indicating that post-stroke GM volumetric changes in cortical hubs reflect compensatory rather than maladaptive mechanisms. These results highlight the importance of structural neuroplasticity in hub regions of the cortex, along with the hemispheric specificity, for stroke recovery.
Dual Graph Reasoning Unit for Brain Tumor Segmentation

With the rapid development of deep learning, many fully automatic segmentation models are developed to solve the challenge of brain tumor segmentation. However, few methods focus on the rich relational information and contextual dependencies in multimodal MR images. In this paper, we propose a novel approach, called Dual Graph Reasoning Unit (DGRUnit), for brain tumor segmentation. The proposed method consists of two parallel modules, a spatial reasoning module, and a channel reasoning module. The spatial reasoning module maps the original features to an embedding spatial node space and employs the graph convolutional network (GCN) to capture long-range relations between different regions in the spatial dimension. Similar to the spatial reasoning module, the channel reasoning module adopts the graph attention network (GAT) to model the rich contextual interdependencies between different channels with similar semantics representing. To demonstrate the effectiveness of our proposed method, we integrate both modules into a Nested U-net. Experimental results show that our approach achieve significant improvement on brain tumor segmentation task compared to several state-of-the-art methods.
Reduced-Complexity Greedy Distributed Information Bottleneck Algorithm

This paper addresses a distributed sensing scenario, widely known as the Chief Executive Officer (CEO) problem. Considering the logarithmic loss distortion measure, the distributed scalar compression can be optimized using an information bottleneck (IB) approach. The recently proposed Greedy Distributed IB (GDIB) algorithm optimizes all quantizers successively exploiting the statistics of previously designed quantizers as side-information. It was shown, that jointly optimizing the scalar quantizers results in a significant performance improvement compared to individual scalar optimization without side-information. However, processing the side-information becomes a major bottleneck as the memory complexity grows exponentially with the network size. This paper proposes a sequential compression scheme in order to compress this side-information to ensure feasibility even for larger networks. The compression is performed again by means of the information bottleneck method. Presented simulation results show that despite the compression of side-information the overall loss in relevant information can be made sufficiently small.
Rovers Localization by using 3D-to-3D and 3D-to-2D Visual Odometry

Space robotic systems have been playing a crucial role in planetary exploration missions, expanding our access to harsh and hostile environments in the Solar System. Rovers' activities are still mainly controlled through ground operations, and our goal is to develop autonomous systems for navigation and path planning. The position estimates obtained by processing Wheel Odometry (WO) data induce significant errors because of wheels' loss of traction that is caused by, for example, high-slippage terrains (e.g., sandy-loose soils, steep slopes). Our work is focused on the implementation of a localization software based on Visual Odometry (VO). This is a technique developed for the estimation of rovers' position and attitude by using stereo images captured during the vehicle's motion. To determine the attainable accuracy of our software, we carried out a set of numerical simulations through a digitally-reproduced Martian-like environment. The results show that the algorithm allows reconstructing the rover's trajectory with higher accuracies compared to the localization system requirements of the NASA Mars Exploration Rovers (i.e., 10% error over a 100-m traverse [1]).
Multi-coil array for long-distance cross-well electromagnetic detection

Cross-well electromagnetic detection technology is an important geophysical exploration method, which is widely used in oil and gas development, underground resource acquisition and engineering environmental geophysical prospecting. At present, some scholars have developed relatively mature cross-well electromagnetic logging tools that can realize long-distance oil and gas logging. However, these tools are bulky and complicated to operate, so they are not suitable for small-diameter wells. Therefore, this paper proposes a multi-coil array probe for cross-well electromagnetic to realize the long-distance detection of small-diameter wells. The probe is mainly composed of the transmitter coil and the receiver coil. It is small in size, easy to carry, and can achieve high-power transmission and high-sensitivity reception. According to simulation and experimental results, the research can achieve long-distance detection up to 300 meters.
Deep Object-Centric Pooling in Convolutional Neural Network for Remote Sensing Scene Classification

Remote sensing imagery typically comprises successive background contexts and complex objects. Global average pooling is a popular choice to connect the convolutional and fully connected (FC) layers for the deep convolution network. This article equips the networks with another pooling strategy, namely the deep object-centric pooling (DOCP), to pool convolutional features considering the location of an object within the scene image. The proposed DOCP network structure consists of the following two steps: inferring object's location and separately pooling the foreground and background features to generate an object-level representation. Specifically, a spatial context module is presented to learn the location of the object of interest in the scene image. Then, the convolutional feature maps are pooled separately in the foreground and background of the object. Finally, the FC layer concatenates these pooled features and is followed by a batch normalization layer, a dropout layer, and a softmax layer. Two challenging datasets are employed to validate our approach. The experimental results demonstrate that the proposed DOCP-net can outperform the corresponding pooling methods and achieve a better classification performance than other pretrained convolutional neural network-based scene classification methods.
Crack Segmentation for Low-Resolution Images using Joint Learning with Super- Resolution

This paper proposes a method for crack segmentation on low-resolution images. Detailed cracks on their high-resolution images are estimated by super resolution from the low-resolution images. Our proposed method*1optimizes super-resolution images for the crack segmentation. For this method, we propose the Boundary Combo loss to express the local details of the crack. Experimental results demonstrate that our method outperforms the combinations of other previous approaches.
Optimal Multi-Objective Resource Allocation for D2D Underlaying Cellular Networks in Uplink Communications

In this paper, we study a resource allocation problem in orthogonal frequency division multiple access (OFDMA)-based Device-to-Device (D2D) communications. To this end, we propose a multi-objective optimization problem (MOOP) framework, which jointly maximizes the sum rate of D2D users (DUs) and cellular users (CUs) in uplink communications and minimizes the total transmit power. The proposed problem formulation takes into account the minimum data-rates and the maximum transmitted power budget for both DUs and CUs. We transform this MOOP into a single-objective optimization problem (SOOP) using the weighted sum method and then propose an approach to solve this SOOP via a monotonic approach yielding an efficient optimal solution. Furthermore, a suboptimal solution based on the successive convex approximation (SCA) is presented to compromise complexity and performance gain. This is done to reveal that the proposed suboptimal solution closely approaches an optimal solution through simulation analysis. Numerical results unveil an interesting tradeoff between D2Ds CUs and demonstrate the superiority of our proposed solution compared to other baseline schemes.
Ultrafast laser source for nonlinear imaging and spectroscopy with high energy sub-100 fs pulses

A diode-pumped femtosecond laser oscillator producing <100 fs pulses with high pulse energy was demonstrated. The laser was based on the Yb:CALGO crystal and produced 91 fs pulses with 750 mW of average output power. The laser operated at 27 MHz and produced pulses with 28 nJ of energy corresponding to >300 kW of peak power. Such a high peak power performance with <100 fs pulses make this source an excellent platform for fluorescence lifetime imaging, supercontinuum generation, multiphoton imaging or seeding of amplifiers.