Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical and epidemiological features of acute intestinal infections with hemorragic colitis in children

Aim. To study the clinical and epidemiological features of acute intestinal infections associated with hemorrhagic colitis in children. Methods. The clinical and epidemiological features of hemorrhagic colitis were studied in 70 children with acute intestinal infections aged from 1 month to 14 years who were admitted to the Infectious Diseases Hospital in Kazan, Russia. The following stool tests were performed: single bacteriology test for pathogenic and conditionally pathogenic microbiota, rotavirus antigen detection by latex agglutination, campylobacter DNA detection by polymerase chain reaction and microscopy to detect protozoa. Results. Hemorrhagic colitis was present mainly in infants (56 children, 80%), the main reasons for hemorrhagic colitis were: Salmonella enteritidis - 12 (17.1%) children, Campylobacter - 6 (8.6%) children, Klebsiella pneumoniae - 6 (8.6%) children. There were single cases of hemorrhagic colitis associated with Shigella, Enterobacter, S. aureus, Ps. aeruguinosa and E. hystolitica. The diagnosis of Campylobacter infection was based on the detection of the DNA but not the bacteria itself like in other acute intestinal infections. The majority of hemorrhagic colitis cases (52 children, 74.3%) were registered in spring and summertime. Hemorrhagic colitis was moderately severe and manifested as traces of blood and mucus in stool. Hemorrhagic colitis usually lasted up to 3 days in majority of children. Conclusion. The main reasons for acute intestinal infections associated with hemorrhagic colitis were: Salmonella enteritidis, Campilobacter and Klebsiella pneumonia, hemorrhagic colitis was most common in infants in spring and summertime.
Ethanol Inhibits Cytokine-Induced iNOS and sPLA2 in Immortalized Astrocytes: Evidence for Posttranscriptional Site of Ethanol Action

Chronic and excessive ethanol consumption is known to alter neuron and glial cell functions in the central nervous system (CNS). Astrocytes comprise the major cell type in the brain. These immune active cells are capable of responding to proinflammatory cytokines and endotoxins, which stimulate transcriptional pathways leading to induction of genes, including the inducible nitric oxide synthase (iNOS) and secretory phospholipase A2 (sPLA2). In this study, we investigate the effects of ethanol on cytokine-induced iNOS and sPLA2 in immortalized astrocytes (DITNC). When DITNC cells were exposed to ethanol (0–200 mM) for 4 h prior to subsequent stimulation with cytokines for 16 h, NO production decreased with increasing ethanol concentrations starting from 50 mM. At ethanol concentrations higher than 100 mM, ethanol also inhibited cytokine-induced sPLA2 release into the culture medium. The inhibitory effect of ethanol on NO production corresponds well with the decrease in iNOS protein and NOS enzyme activity, but not with iNOS and sPLA2 mRNA nor binding of NF-ĸB to DNA. The inhibition of cytokine-induced NO production by ethanol was also dependent on the time of ethanol exposure to the cells, but addition of acetaldehyde up to 200 µM did not elicit any changes. Taken together, these results provide evidence for a posttranscriptional mode of ethanol action on the cytokine induction pathway for NO production in astrocytes.
Effect of Quercetin on RAC1 Gene Expression as a Marker of Metastasis in Cervical Cancer Cells

Background:: Cancer metastasis is the most important cause of cancer death and different treatment strategies have targeted on preventing the occurrence of metastasis. Quercetin is a flavonoid and widely used as an antioxidant and recent studies have discovered its anticancer and antiproliferative capabilities. Rac1 is protein known to involve in tumor invasion and metastases. Objectives:: In this study, we investigated the effect of quercetin on expression of Rac1 protein. Materials and Methods:: In this experimental study, HeLa cells were treated with quercetin at 2 concentrations (20 and 40 μM) for 24 hours and then cell lysate was assessed by Western blotting analysis to investigate the impact of quercetin on expression of Rac1 protein. Results:: Quercetin significantly decreased Rac1 expression of HeLa cells assessed by western blotting, in dose-dependent manners (P < 0.05). Conclusions:: This study showed that quercetin decreased Rac1 expression as a marker of metastasis in cervical cancer cells. Therefore, the quercetin may provide an effective new strategy to reduce of tumor metastasis.
Feasibility and reproducibility of muscular strength measures in gymnastics-specific body positions using hand-held dynamometry

This study aimed to determine feasibility and reproducibility of muscular strength measurements in young gymnasts, using hand-held dynamometry in gymnastics-specific body positions. A group of 32 male and female young gymnasts 8-11 years-old, performed different strength tests using a Nicholas Manual Muscle Tester (NMMT). The measurements were collected in 4 major muscle groups (shoulder flexors and extensors, hip flexors and extensors) at 22 different joint angular positions, with the active elbow or knee joint in full extension. The maximal strength was obtained by placing the NMMT in a distal forearm or shank position, with the gymnast in supine or prone position stabilized on a vault. A Myrin goniometer, attached on the sagittal plane near elbow or knee joint, was used to specify the shoulder and hip joint angular positions. In the majority of the measurements (18 out of 22 angular positions) the intra-class correlation coefficients revealed a good level of test-retest reliability (R = 0.80-0.88). In four cases (3 in shoulder flexors and 1 in shoulder extensors) intra-class reliability was fair, with R-values ranging from 0.70 to 0.78. The low coefficients of variation and standard errors of measurements affirmed the reproducibility of measurements. In conclusion, this study showed the feasibility and the reproducibility of shoulder and hip flexor and extensor muscles maximal strength measurements using NMMT in gymnastics-based settings.
Molecular Detection of Late-Onset Neonatal Sepsis in Premature Infants Using Small Blood Volumes: Proof-of-Concept

Background: Conventional blood culture is still the gold standard for sepsis diagnosis but results are not immediately available and pathogens are only detected in approximately 25% of cases. New molecular assays for the detection of blood stream pathogens are promising diagnostic tools. Objectives: The aim of the study was to adapt and evaluate a multiplex PCR system using 100 µl blood. -Methods: 46 blood specimens of very low birth weight infants (818 ± 242 g) with suspected sepsis were analyzed using the Roche SeptiFast MGRADE PCR with a modified DNA extraction protocol and software handling tool for decreased blood volume requirements. Results: In the non-infected group, 5/21 infants had a positive PCR result with coagulase-negative staphylococci. All pathogens detected in the blood culture positive group (n = 15) were also detected by PCR. In addition, 4/6 patients had a positive PCR result in the clinical sepsis group (clinical and laboratory signs of sepsis but negative blood culture). Overall, the PCR was demonstrated to have a higher sensitivity (90.5%; 95%CI 68.2-98.3%) in comparison to blood culture (71.4%; 95%CI 47.7-87.8%) including clinical sepsis cases, even though it had a lower specificity (80.0%; 95%CI 58.7-92.4% versus 100.0%; 95%CI 83.4-100.0%). Conclusions: These first data demonstrate the usability and potential benefit of this multiplex PCR using a modified DNA extraction for the rapid detection of nosocomial sepsis in preterm infants in addition to blood culture.
Visual Measurement Integrity Monitoring for UAV Localization

Unmanned aerial vehicles (UAVs) have increasingly been adopted for safety, security, and rescue missions, for which they need precise and reliable pose estimates relative to their environment. To ensure mission safety when relying on visual perception, it is essential to have an approach to assess the integrity of the visual localization solution. However, to the best of our knowledge, such an approach does not exist for optimization-based visual localization. Receiver autonomous integrity monitoring (RAIM) has been widely used in global navigation satellite systems (GNSS) applications such as automated aircraft landing. In this paper, we propose a novel approach inspired by RAIM to monitor the integrity of optimization-based visual localization and calculate the protection level of a state estimate, i.e. the largest possible translational error in each direction. We also propose a metric that quantitatively evaluates the performance of the error bounds. Finally, we validate the protection level using the EuRoC dataset and demonstrate that the proposed protection level provides a significantly more reliable bound than the commonly used 3σ method.
5G QoS: Impact of Security Functions on Latency

Network slicing is considered a key enabler to 5th Generation (5G) communication networks. Mobile network operators may deploy network slices—complete logical networks customized for specific services expecting a certain Quality of Service (QoS). New business models like Network Slice-as-a-Service offerings to customers from vertical industries require negotiated Service Level Agreements (SLA), and network providers need automated enforcement mechanisms to assure QoS during instantiation and operation of slices. In this paper, we focus on ultra-reliable low-latency communication (URLLC). We propose a software architecture for security functions based on off-the-shelf hardware and open-source software and demonstrate, through a series of measurements, that the strict requirements of URLLC services can be achieved. As a real-world example, we perform our experiments using the intrusion prevention system (IPS) Snort to demonstrate the impact of security functions on latency. Our findings lead to the creation of a model predicting the system load that still meets the URLLC latency requirement. We fully disclose the artifacts presented in this paper including pcap traces, measurement tools, and plotting scripts at https://gallenmu.github. io/low-latency.
Modeling the Occurrence of Events Subject to a Reporting Delay via an EM Algorithm

A delay between the occurrence and the reporting of events often has practical implications such as for the amount of capital to hold for insurance companies, or for taking preventive actions in case of infectious diseases. The accurate estimation of the number of incurred but not (yet) reported events forms an essential part of properly dealing with this phenomenon. We review the current practice for analysing such data and we present a flexible regression framework to jointly estimate the occurrence and reporting of events from data at daily level. By linking this setting to an incomplete data problem, estimation is performed by the expectation-maximization algorithm. The resulting method is elegant, easy to understand and implement, and provides refined forecasts on a daily level. The proposed methodology is applied to a European general liability portfolio in insurance.
Generalized permutahedra: Minkowski linear functionals and Ehrhart positivity

We characterize all signed Minkowski sums that define generalized permutahedra, extending results of Ardila–Benedetti–Doker (Discrete Comput. Geom. 43 (2010), no. 4, 841–854). We use this characterization to give a complete classification of all positive, translation‐invariant, symmetric Minkowski linear functionals on generalized permutahedra. We show that they form a simplicial cone and explicitly describe their generators. We apply our results to prove that the linear coefficients of Ehrhart polynomials of generalized permutahedra, which include matroid polytopes, are non‐negative, verifying conjectures of De Loera–Haws–Köppe (Discrete Comput. Geom. 42 (2009), no. 4, 670–702) and Castillo–Liu (Discrete Comput. Geom. 60 (2018), no. 4, 885–908) in this case. We also apply this technique to give an example of a solid‐angle polynomial of a generalized permutahedron that has negative linear term and obtain inequalities for beta invariants of contractions of matroids.
Neural Population Coding for Effective Temporal Classification

Neural encoding plays an important role in faithfully describing the temporally rich patterns, whose instances include human speech and environmental sounds. To classify such spatio-temporal patterns with the Spiking Neural Networks (SNNs), how these patterns are encoded has a direct impact on the complexity of the task. In this paper, we study several existing temporal and population coding schemes in speech and audio recognition. We show that, with population neural coding, the encoded patterns are linearly separable using the Support Vector Machine (SVM). We note that the population neural coding effectively project the temporal information into the spatial domain, thus improving linear separability of the patterns. We achieve an accuracy of 95% and 100% on TIDIGITS and RWCP datasets respectively with SVM classifier. We further implement the Tempotron as an SNN-based classifier on the same datasets and achieve similar results. The study suggests that an effective neural coding scheme is just as important as the classifier.
High contrast dual-mode optical and 13C magnetic resonance imaging in diamond particles

Author(s): Lv, X; Walton, JH; Druga, E; Wang, F; Aguilar, A; McKnelly, T; Nazaryan, R; Liu, FL; Wu, L; Shenderova, O; Vigneron, DB; Meriles, CA; Reimer, JA; Pines, A; Ajoy, A | Abstract: Multichannel imaging -- the ability to acquire images of an object through more than one imaging mode simultaneously -- has opened interesting new perspectives in areas ranging from astronomy to medicine. Visible optics and magnetic resonance imaging (MRI) offer complementary advantages of resolution, speed and depth of penetration, and as such would be attractive in combination. In this paper, we take first steps towards marrying together optical and MR imaging in a class of biocompatible particulate materials constructed out of diamond. The particles are endowed with a high density of quantum defects (Nitrogen Vacancy centers) that under optical excitation fluoresce brightly in the visible, but also concurrently electron spin polarize. This allows the hyperpolarization of lattice 13C nuclei to make the particles over three-orders of magnitude brighter than in conventional MRI. Dual-mode optical and MR imaging permits immediate access to improvements in resolution and signal-to-noise especially in scattering environments. We highlight additional benefits in background-free imaging, demonstrating lock-in suppression by factors of 2 and 5 in optical and MR domains respectively. Ultimate limits could approach as much as two orders of magnitude in each domain. Finally, leveraging the ability of optical and MR imaging to simultaneously probe Fourier-reciprocal domains (real and k-space), we elucidate the ability to employ hybrid sub-sampling in both conjugate spaces to vastly accelerate dual-image acquisition, by as much as two orders of magnitude in practically relevant sparse-imaging scenarios. This is accompanied by a reduction in optical power by the same factor. Our work suggests interesting possibilities for the simultaneous optical and low-field MR imaging of targeted diamond nanoparticles.
3D Printed Actuators: Reversibility, Relaxation, and Ratcheting

Additive manufacturing strives to combine any combination of materials into 3D functional structures and devices, ultimately opening up the possibility of 3D printed machines. It remains difficult to actuate such devices, thus limiting the scope of 3D printed machines to passive devices or necessitating the incorporation of external actuators that are manufactured differently. Here, 3D printed hybrid thermoplast/conducter bilayers are explored, which can be actuated by differential heating caused by externally controllable currents flowing through their conducting faces. The functionality of such actuators is uncovered and it is shown that they allow to 3D print, in one pass, simple flexible robotic structures that propel forward under step‐wise applied voltages. Moreover, exploiting the thermoplasticity of the nonconducting plastic parts at elevated temperatures, it is shown that how strong driving leads to irreversible deformations—a form of 4D printing—which also enlarges the range of linear response of the actuators. Finally, it is shown that how to leverage such thermoplastic relaxations to accumulate plastic deformations and obtain very large deformations by alternatively driving both layers of a bilayer; this is called ratcheting. The strategy is scalable and widely applicable, and opens up a new approach to reversible actuation and irreversible 4D printing of arbitrary structures and machines.
Subword ELMo

Embedding from Language Models (ELMo) has shown to be effective for improving many natural language processing (NLP) tasks, and ELMo takes character information to compose word representation to train language models.However, the character is an insufficient and unnatural linguistic unit for word representation.Thus we introduce Embedding from Subword-aware Language Models (ESuLMo) which learns word representation from subwords using unsupervised segmentation over words.We show that ESuLMo can enhance four benchmark NLP tasks more effectively than ELMo, including syntactic dependency parsing, semantic role labeling, implicit discourse relation recognition and textual entailment, which brings a meaningful improvement over ELMo.
Actuation response model from sparse data for wall turbulence drag reduction

We compute, model, and predict drag reduction of an actuated turbulent boundary layer at a momentum thickness based Reynolds number of Re{\theta} = 1000. The actuation is performed using spanwise traveling transversal surface waves parameterized by wavelength, amplitude, and period. The drag reduction for the set of actuation parameters is modeled using 71 large-eddy simulations (LES). This drag model allows to extrapolate outside the actuation domain for larger wavelengths and amplitudes. The modeling novelty is based on combining support vector regression for interpolation, a parameterized ridgeline leading out of the data domain, scaling from Tomiyama and Fukagata (2013), and a discovered self-similar structure of the actuation effect. The model yields high prediction accuracy outside the training data range.
The solution of the Cauchy problem for the two-dimensional transport equation on a rotating plane.

The limiting case of the system of equations of two-dimensional gas dynamics in the presence of the Coriolis force, which can be obtained under the assumption of a small pressure, is considered. With this approach, the equation for the velocity vector (transport equation) is split off from the system and can be solved separately. Using the method of stochastic perturbation along characteristics, we obtain an explicit asymptotic representation of a smooth solution of transport equations and analyze the process of formation of singularities of solution using a specific example. It is concluded that the presence of the Coriolis force prevents the singularities formation.
Achieving Phase Coherency and Gain Stability in Active Antenna Arrays for Sub-6 GHz FDD and TDD FD-MIMO: Challenges and Solutions

Full-dimension MIMO (FD-MIMO) using planar active antenna systems (AAS) is considered a critical technology for fifth-generation (5G) cellular systems to improve network capacity. An AAS is typically subject to hardware impairments that negatively impact network capacity. Hence, this article focuses on impairments that cause phase and magnitude errors between radio frequency (RF) chains and shows why they are particularly difficult to avoid in practical AAS. Although previous investigations show these impairments to degrade performance, they are not useful in deriving measurable impairment margins for practical FD-MIMO deployments. Knowing impairment limits are critical for system designers to make hardware design tradeoffs such as AAS configuration, component selection, implementation complexity, and cost. Moreover, it also helps set conformance limits for critical lab verification. Therefore, the paper first investigates the impact of the impairments and derives their practical limits for FD-MIMO by explicitly considering the cumulative effects of the channel model, inter-cell interference, link adaptation, and channel aging due to feedback delays. It is shown that a lower number of digitized RF chains can be a better choice under lower impairments. Next, the sources of impairments are investigated by using measurements carried out in the lab and the field during live operation in a commercial LTE network. Phase drift from local oscillators (LO) and internal temperature variations are identified as two significant sources. The tradeoffs and shortcomings of some of the existing solutions in massive MIMO literature are discussed. Finally, in order to address the shortcomings, a novel and practical coherent LO distribution architecture and array calibration mechanism are proposed. This solution is shown to be applicable to both TDD and FDD FD-MIMO. Measurement results are provided to prove the high degree of coherency and stability achieved on a unique array architecture called high definition active antenna system (HDAAS).
King’s Research

Models of coupled phase oscillators are used to describe a wide variety of phenomena in neuroimaging. These models typically rest on the premise that oscillator dynamics do not evolve beyond their respective limit cycles, and hence that interactions can be described purely in terms of phase differences. Whilst mathematically convenient, the restrictive nature of phase-only models can limit their explanatory power. We therefore propose a generalisation of dynamic causal modelling that incorporates both phase and amplitude. This allows for the separate quanti ﬁ cations of phase and amplitude contributions to the connectivity between neural regions. We show, using model-generated data and simulations of coupled pendula, that phase-amplitude models can describe strongly coupled systems more effectively than their phase-only counterparts. We relate our ﬁ ndings to four metrics commonly used in neuroimaging: the Kuramoto order parameter, cross-correlation, phase-lag index, and spectral entropy. We ﬁ nd that, with the exception of spectral entropy, the phase-amplitude model is able to capture all metrics more effectively than the phase-only model. We then demonstrate, using local ﬁ eld potential recordings in rodents and functional magnetic resonance imaging in macaque monkeys, that amplitudes in oscillator models play an important role in describing neural dynamics in anaesthetised brain states.
On sets of commuting and anticommuting Paulis

In this work we study the structure and cardinality of maximal sets of commuting and anticommuting Paulis in the setting of the abelian Pauli group. We provide necessary and sufficient conditions for anticommuting sets to be maximal, and present an efficient algorithm for generating anticommuting sets of maximum size. As a theoretical tool, we introduce commutativity maps, and study properties of maps associated with elements in the cosets with respect to anticommuting minimal generating sets. We also derive expressions for the number of distinct sets of commuting and anticommuting abelian Paulis of a given size.