Miracle-dz/UniFAR-FTUs huggingface dataset:
Water drinking during aerobic exercise improves the recovery of non-linear heart rate dynamics in coronary artery disease: crossover clinical trial

Introduction The post-exercise recovery is a period of vulnerability of the cardiovascular system in which autonomic nervous system plays a key role in cardiovascular deceleration. It is already known that individuals with coronary artery disease (CAD) are at greater risk due to delayed vagal reactivation in this period. Water ingestion has been studied as a strategy to improve autonomic recovery and mitigate the risks during recovery. However, the results are preliminary and need further confirmation. Therefore, our aim was to investigate the influence of individualized water drinking on the non-linear dynamics of heart rate during and after aerobic exercise in CAD subjects. Methods 30 males with CAD were submitted to a control protocol composed of initial rest, warming up, treadmill exercise, and passive recovery (60 min). After 48 hours they performed the hydration protocol, composed of the same activities, however, with individualized water drinking proportional to the body mass lost in the control protocol. The non-linear dynamics of heart rate were assessed by indices of heart rate variability extracted from the recurrence plot, detrended fluctuation analysis, and symbolic analysis. Results and discussion During exercise, the responses were physiological and similar in both protocols, indicating high sympathetic activity and reduced complexity. During recovery, the responses were also physiological, indicating the rise of parasympathetic activity and the return to a more complex state. However, during hydration protocol, the return to a more complex physiologic state occurred sooner and non-linear HRV indices returned to resting values between the 5th and 20th minutes of recovery. In contrast, during the control protocol, only a few indices returned to resting values within 60 minutes. Despite that, differences between protocols were not found. We conclude that the water drinking strategy accelerated the recovery of non-linear dynamics of heart rate in CAD subjects but did not influence responses during exercise. This is the first study to characterize the non-linear responses during and after exercise in CAD subjects.
Investigating the causal association of postpartum depression with cerebrovascular diseases and cognitive impairment: a Mendelian randomization study

Background Postpartum depression (PPD) is considered the most widespread puerperium complication. The associations of major depressive disorder with certain types of cerebrovascular diseases and cognitive function have been proposed, but the potential causal effects of PPD on these phenotypes are still unknown. Methods A Mendelian randomization (MR) research design with various methods (e.g., inverse-variance weighted method and MR pleiotropy residual sum and outlier test) was adopted to establish a causal relationship between PPD with cerebrovascular diseases and cognitive impairment. Results No causal relationship between PPD with carotid intima media thickness and cerebrovascular diseases (i.e., stroke, ischemic stroke, and cerebral aneurysm) was found. However, MR analyses indicated a causal association between PPD and decreased cognitive function (P = 3.55 × 10−3), which remained significant even after multiple comparison corrections using the Bonferroni method. Sensitivity analyses using weighted median and MR-Egger methods indicated a consistent direction of the association. Conclusion The causal association between PPD and cognitive impairment indicates that cognitive impairment is a critical aspect of PPD and thus cannot be regarded as an epiphenomenon. Addressing cognitive impairment and lessening the symptoms associated with PPD independently play significant roles in the treatment of PPD.
Aortic dissection induced by vascular endothelial growth factor inhibitors

Vascular endothelial growth factor (VEGF) contributes to angiogenesis and vasculogenesis. The occurrence and progression of tumors are accompanied by angiogenesis. Vascular endothelial growth factor inhibitors (VEGFI) have been used in anti-tumor treatment. However, aortic dissection (AD) is one of the VEGFI-associated adverse reactions with cute onset, rapid progression, and high case fatality rate. We collected case reports of VEGFI related to aortic dissection in PubMed and CNKI (China National Knowledge Infrastructure) from inception to 28 April 2022. Seventeen case reports were selected. The medication included sunitinib, sorafenib, pazopanib, axitinib, apatinib, anlotinib, bevacizumab, and ramucirumab. This review discusses the pathology, risk factors, diagnosis, and treatment of AD. Vascular endothelial growth factor inhibitors are related to aortic dissection. Although current literature lacks clear statistical evidence on the population, we offer points to encourage further confirmation of the best methods of care for these patients.
Oxytocin administration is a potential tool for behavioral management in felids

Living in a group setting is essential for the health and wellbeing of social carnivores; however, the managed formation of captive groups of territorial animals can be challenging because of the risk of aggression, injury, and even death. Numerous laboratory and clinical studies have implicated oxytocin in the formation of social bonds. Previously, we have shown that oxytocin (OT) administration reduced social vigilance in African lions. Here, we describe a series of case reports in which OT administration was used to facilitate social bonding in both familiar and unfamiliar conspecific pairs and groups of African lions and tigers, and we provide qualitative descriptions of the study animals’ behaviors before and after treatment. We hypothesized that the repeated intranasal administration of oxytocin over a period of 6–8 weeks would facilitate (1) the bonding process during introductions of unfamiliar individuals and (2) reconciliation between paired individuals that had developed ongoing negative social relationships. Following OT treatment, positive social interactions were either observed for the first time or were restored in all seven study groups.
Is increased myocardial triglyceride content associated with early changes in left ventricular function? A 1H-MRS and MRI strain study

Background Type 2 diabetes (T2D) and obesity induce left ventricular (LV) dysfunction. The underlying pathophysiological mechanisms remain unclear, but myocardial triglyceride content (MTGC) could be involved. Objectives This study aimed to determine which clinical and biological factors are associated with increased MTGC and to establish whether MTGC is associated with early changes in LV function. Methods A retrospective study was conducted using five previous prospective cohorts, leading to 338 subjects studied, including 208 well-phenotyped healthy volunteers and 130 subjects living with T2D and/or obesity. All the subjects underwent proton magnetic resonance spectroscopy and feature tracking cardiac magnetic resonance imaging to measure myocardial strain. Results MTGC content increased with age, body mass index (BMI), waist circumference, T2D, obesity, hypertension, and dyslipidemia, but the only independent correlate found in multivariate analysis was BMI (p=0.01; R²=0.20). MTGC was correlated to LV diastolic dysfunction, notably with the global peak early diastolic circumferential strain rate (r=-0.17, p=0.003), the global peak late diastolic circumferential strain rate (r=0.40, p<0.0001) and global peak late diastolic longitudinal strain rate (r=0.24, p<0.0001). MTGC was also correlated to systolic dysfunction via end-systolic volume index (r=-0.34, p<0.0001) and stroke volume index (r=-0.31, p<0.0001), but not with longitudinal strain (r=0.009, p=0.88). Interestingly, the associations between MTGC and strain measures did not persist in multivariate analysis. Furthermore, MTGC was independently associated with LV end-systolic volume index (p=0.01, R²=0.29), LV end-diastolic volume index (p=0.04, R²=0.46), and LV mass (p=0.002, R²=0.58). Conclusions Predicting MTGC remains a challenge in routine clinical practice, as only BMI independently correlates with increased MTGC. MTGC may play a role in LV dysfunction but does not appear to be involved in the development of subclinical strain abnormalities.
Cooperative, Connected and Automated Mobility Service Continuity in a Cross-Border Multi-Access Edge Computing Federation Scenario

The paradigm shift in transportation systems towards Cooperative, Connected and Automated Mobility (CCAM) aims to improve vehicle maneuverability, reduce pollution, and increase safety. CCAM is primarily responsible for ensuring the best mobility environment, making it one of the main trends in the automotive industry. However, taking advantage of CCAM in Cross-Border Corridors (CBCs) faces many challenges, which go beyond infrastructure deployment cost, and all of which are related to supporting Service Continuity (SC) for mobile users, especially in light of the diversity of territories, network coverage areas, international roaming agreements, and type of cooperative maneuvers. As a solution to these challenges, the paper proposes and implements a new architecture for CCAM SC in CBCs that combines a federation of Multi-access Edge Computing (MEC) concepts to maintain SC.
Serum amyloid A and metabolic disease: evidence for a critical role in chronic inflammatory conditions

Serum amyloid A (SAA) subtypes 1–3 are well-described acute phase reactants that are elevated in acute inflammatory conditions such as infection, tissue injury, and trauma, while SAA4 is constitutively expressed. SAA subtypes also have been implicated as playing roles in chronic metabolic diseases including obesity, diabetes, and cardiovascular disease, and possibly in autoimmune diseases such as systemic lupus erythematosis, rheumatoid arthritis, and inflammatory bowel disease. Distinctions between the expression kinetics of SAA in acute inflammatory responses and chronic disease states suggest the potential for differentiating SAA functions. Although circulating SAA levels can rise up to 1,000-fold during an acute inflammatory event, elevations are more modest (∼5-fold) in chronic metabolic conditions. The majority of acute-phase SAA derives from the liver, while in chronic inflammatory conditions SAA also derives from adipose tissue, the intestine, and elsewhere. In this review, roles for SAA subtypes in chronic metabolic disease states are contrasted to current knowledge about acute phase SAA. Investigations show distinct differences between SAA expression and function in human and animal models of metabolic disease, as well as sexual dimorphism of SAA subtype responses.
Role of automated detection of respiratory related heart rate changes in the diagnosis of sleep disordered breathing

Study objectives The objective of this study was to determine whether electrocardiogram (ECG) and heart rate accelerations that occur in the vicinity of respiratory events could predict the severity of sleep-disordered breathing (SDB). Methods De-identified polysomnogram (NPSG) recordings from 2091 eligible participants in the Sleep Heart Health Study (SHHS) were evaluated after developing and validating an automated algorithm using an initial set of recordings from 1,438 participants to detect RR interval (RRI) dips in ECG and heart rate accelerations from pulse rate signal. Within-subject comparisons were made between the apnea-hypopnea index (AHI) and both the total RRI dip index (total RRDI) and total heart rate acceleration index (total HRAI). Results The estimated AHIs using respiratory-related HRAI correlated with NPSG AHI both in the unadjusted and adjusted model (B: 0.83 and 0.81, respectively P < 0.05). Respiratory-related HRAI had a strong agreement with NPSG AHI (intraclass correlation coefficient-ICC: 0.64, whereas respiratory-related RRDI displayed weaker agreement and ICC: 0.38). Further assessment of respiratory-related HRAI (≥5 events/h) showed a strong diagnostic ability (78, 87, 81, and 56% agreement for traditional AHI cutoffs 5, 10, 15, and 30 events/h, respectively). At the AHI cutoff of 5 events/h the receiver operating curves (ROC) revealed an area under the curve (AUCs) of 0.90 and 0.96 for RE RRDI and RE HRAI respectively. Conclusion The automated respiratory-related heart rate measurements derived from pulse rate provide an accurate method to detect the presence of SDB. Therefore, the ability of mathematical models to accurately detect respiratory-related heart rate changes from pulse rate may enable an additional method to diagnose SDB.
Research on tetrahedron fission topology in three dimensional network-on-chip

: This paper aims to research the tetrahedron fission topology that is a new type of three dimensional Network-on-Chip topology, gives generation process of topology and the design of encoding and routing. Through a three dimensional extension of the gpNoCsim which is a simulator on chip network, the simulation experiment of the tetrahedron fission topology is conducted. The simulation results show, tetrahedron fission topology can achieve lower average latency and fewer average hops than Mesh under uniform traffic pattern, When the injection rate is 0.02, comparing with Mesh, the average latency degrades by 16.8 % and the average hops decrease 5.5% ; Under localized traffic pattern, the average delay of tetrahedral fission topology and the average hops are significantly improved when the injection rate is greater than 0.008, Comparing with Mesh , tetrahedron fission leads to 18.7% decrease of the average latency and 9.6% decrease of the average hops when the injection rate is 0.014. It is shown that the tetrahedron fission topology can be used in the design of three dimensional Network-on-Chip topology.
Phase Transitions in Model Active Systems

Phase Transitions in Model Active Systems A dissertation presented to the Faculty of the Graduate School of Arts and Sciences of Brandeis University, Waltham, Massachusetts by Gabriel S. Redner The amazing collective behaviors of active systems such as bird flocks, schools of fish, and colonies of microorganisms have long amazed scientists and laypeople alike. Understanding the physics of such systems is challenging due to their far-from-equilibrium dynamics, as well as the extreme diversity in their ingredients, relevant timeand length-scales, and emergent phenomenology. To make progress, one can categorize active systems by the symmetries of their constituent particles, as well as how activity is expressed. In this work, we examine two categories of active systems, and explore their phase behavior in detail. First, we study systems of self-propelled spherical particles moving in two dimensions. Despite the absence of an aligning interaction, this system displays complex emergent dynamics, including phase separation into a dense active solid and dilute gas. Using simulations and analytic modeling, we quantify the phase diagram and separation kinetics. We show that this nonequilibrium phase transition is analogous to an equilibrium vapor-liquid system, with binodal and spinodal curves and a critical point. We also characterize the dense active solid phase, a unique material which exhibits the structural signatures of a crystalline solid near the crystal-hexatic transition point, as well as anomalous dynamics including superdiffusive motion on intermediate timescales. We also explore the role of interparticle attraction in this system. We demonstrate that attraction drastically changes the phase diagram, which contains two distinct phaseseparated regions and is reentrant as a function of propulsion speed. We interpret this comvi plex situation with a simple kinetic model, which builds from the observed microdynamics of individual particles to a full description of the macroscopic phase behavior. We also study active nematics, liquid crystals driven out of equilibrium by energydissipating active stresses. The equilibrium nematic state is unstable in these materials, leading to beautiful and surprising behaviors including the spontaneous generation of topological defect pairs which stream through the system and later annihilate, yielding a complex, seemingly chaotic dynamical steady-state. Here, we describe the emergence of order from this chaos in the form of previously unknown broken-symmetry phases in which the topological defects themselves undergo orientational ordering. We have identified these defect-ordered phases in two realizations of an active nematic: first, a suspension of extensile bundles of microtubules and molecular motor proteins, and second, a computational model of extending hard rods. We will describe the defect-stabilized phases that manifest in these systems, our current understanding of their origins, and discuss whether such phases may be a general feature of extensile active nematics.
Compensating for colour artefacts in the design of technical kaleidoscopes

In computer graphics and related fields, bidirectional texture function (BTF) is used for realistic and predictive rendering. BTF allows for the capture of fine appearance effects such as self-shadowing, inter-reflection and subsurface scattering needed for true realism when used in rendering algorithms. The goal of current research is to get a surface representation indistinguishable from the real world. We developed, produced and tested a portable instrument for BTF acquisition based on kaleidoscopic imaging. Here we discuss the colour issues we experienced after the initial tests. We show that the same colour balance cannot be applied to the whole picture as the spectral response of the instrument varies with the position in the image. All optical elements were inspected for their contributions to the spectral behaviour of the instrument. The off-the-shelf parts were either measured or the manufacturer’s data were considered. The custom made mirrors’ spectral reflectivity was simulated. The mathematical model of the instrument was made. We found a way how to implement all these contributions to the image processing pipeline. In this way, a correct white balance for each individual pixel in the image is found and applied, allowing for a more faithful colour representation. Also proposed is an optimized dielectric protective layer for the kaleidoscope’s mirrors.
Atmospheric Diffusion Shown on a Distance-Neighbour Graph

If the diffusivity K of a substance whose mass per volume of atmosphere is χ be defined by an equation of Fick’s type ū ∂ χ /∂ x + v - ∂ χ /∂ y + w - ∂ χ /∂ z + ∂ χ /∂ t = ∂/∂ x (K ∂ χ /∂ x ) + ∂/∂ y (K ∂ χ /∂ y ) ∂/∂ z (K ∂ χ /∂ z ), (1) x , y , z , t being Cartesian co-ordinates and time, ū , v -, w - being the components of mean velocity, then the measured values of K have been found to be 0·2 cm.2 sec. -1 in capillary tubes (Kaye and Laby’s Tables), 105 cm.2 sec. -1 when gusts are smoothed out of the mean wind (Akerblom, G. I. Taylor, Hesselberg, etc.), 108 cm.2 sec. -1 when the means extend over a time comparable with 4 hours (L. F. Richardson and D. Proctor), 1011 cm.2 sec. -1 when the mean wind is taken to be the general circulation characteristic of the latitude (Defant). Thus the so-called constant K varies in a ratio of 2 to a billion. The present paper records an attempt to comprehend all this range of diffusivity in one coherent scheme. Lest the method which I shall adopt should strike the reader as queer and roundabout, I wish to justify it by showing first why some known methods are in difficulties.
High dimensional data clustering by partitioning the hypergraphs using dense subgraph partition

Due to the curse of dimensionality, traditional clustering methods usually fail to produce meaningful results for the high dimensional data. Hypergraph partition is believed to be a promising method for dealing with this challenge. In this paper, we first construct a graph G from the data by defining an adjacency relationship between the data points using Shared Reverse k Nearest Neighbors (SRNN). Then a hypergraph is created from the graph G by defining the hyperedges to be all the maximal cliques in the graph G. After the hypergraph is produced, a powerful hypergraph partitioning method called dense subgraph partition (DSP) combined with the k-medoids method is used to produce the final clustering results. The proposed method is evaluated on several real high-dimensional datasets, and the experimental results show that the proposed method can improve the clustering results of the high dimensional data compared with applying k-medoids method directly on the original data.
Normal forms for parabolic partial differential equations

We begin a study of normal form theorems for parabolic partial differential equations. We show that despite the presence of resonances one can construct a partial normal form for perturbations of the Ginzburg-Landau equation. The normal form transformation is expressed in terms of singular integral operators, whose behavior can be controlled in the appropriate function spaces
One-step deterministic generation of N-atom Greenberger–Horne–Zeilinger states in separate coupled cavities via quantum Zeno dynamics

We propose an efficient scheme for deterministic generating -atom Greenberger–Horne–Zeilinger (GHZ) states in separate coupled cavities connected by optical fibers based on quantum Zeno dynamics only by one-step manipulation. Firstly, we discuss the generation of three-atom GHZ states in separate cavities. Then, the scheme is directly generalized to -atom case without increasing new operations in experiment. The influence of decoherence induced by atomic spontaneous emission and the fibers and cavities losses is discussed by numerical calculation. The results show that the scheme is insensitive to the optical fibers decay due to a tiny excitation probability of the optical fibers during the operation.
Metalized Polymer-Film Capacitors Health Estimation for Three-Phase DC to AC Converters with Artificial Intelligences

Metalized polymer-film capacitors have attained a unique role amongst numerous types of capacitors due to their self-healing ability. However, owing to the increasing usage of converters for transmissions in networks, it is necessary to enhance stability to certify the safety of system operations. Thus, a monitoring process that enables predictive maintenance is essential for evaluating the health status to ensure the stability of electrical systems. This study presents a condition monitoring strategy that utilizes frequency signal analysis to identify capacitor health in a three-phase AC-DC converter. Capacitor current is analyzed using the discrete wavelet transform and normalized by indexes, which is used as input of learning algorithms. A number of indexes, such as root-mean-squared value, variance, average, and median, are behaved as the inputs of artificial intelligent models to examine the film capacitor's factors. The estimated parameters verify that applying the discrete wavelet transform conjoined with indexes for capacitor current provides an excellent accuracy of about 99.85%. This study provides comprehensive insights into film capacitor monitoring using advanced techniques and is expected to be informative for monitoring film capacitors in practical applications.