Miracle-dz/UniFAR-FTUs huggingface dataset:
Benefical effects of lycopene against contrast medium-induced oxidative stress, inflammation, autophagy, and apoptosis in rat kidney

Currently, the number of imaging and interventional procedures that use contrast agents (CAs) is gradually increasing. Contrast-induced nephropathy (CIN) is the most important CA-related complication. Oxidative stress plays a significant role in its pathophysiology. Lycopene (LPN) is a natural substance with strong antioxidant capacity. The present study aimed to investigate the potential preventive effects of LPN against CIN. In total, 28 male Wistar albino rats were divided into 4 groups with 7 rats in each group; the groups include normal control group, LPN only group at a dose of 4 mg/kg/day for 10 days, CIN group by administering 10 mg/kg furosemide IM + 10 mg/kg indomethacin IP + 10 ml/kg iomeprol IV following 24-h dehydration, and CIN + LPN group. There were statistically significant increase in urea, creatinine, and malondialdehyde levels (p < 0.001, for all) but a significant decrease in glutathione, superoxide dismutase, catalase, and glutathione peroxidase levels (p < 0.001, for all) in the CIN group compared with the control group. On histological examination, a significant increase of infiltrated inflammatory cells and necrotic degenerative changes were observed in the CIN group and the immunohistochemical examination revealed a significant increase in inflammation (inducible nitric oxide synthase), autophagy (LC3/B), and apoptosis (cleaved caspase 3) in the CIN group compared with the control group (p < 0.05, for all). Significant improvements in these unfavorable parameters were observed with CIN + LPN group compared with the CIN only group. In conclusion, the favorable effects of LPN as an anti-inflammatory, antiautophagic, and antiapoptotic agent in an experimental model of CIN have been demonstrated.
Online Detection and Classification of Dynamic Hand Gestures with Recurrent 3D Convolutional Neural Networks

Automatic detection and classification of dynamic hand gestures in real-world systems intended for human computer interaction is challenging as: 1) there is a large diversity in how people perform gestures, making detection and classification difficult, 2) the system must work online in order to avoid noticeable lag between performing a gesture and its classification, in fact, a negative lag (classification before the gesture is finished) is desirable, as feedback to the user can then be truly instantaneous. In this paper, we address these challenges with a recurrent three-dimensional convolutional neural network that performs simultaneous detection and classification of dynamic hand gestures from multi-modal data. We employ connectionist temporal classification to train the network to predict class labels from inprogress gestures in unsegmented input streams. In order to validate our method, we introduce a new challenging multimodal dynamic hand gesture dataset captured with depth, color and stereo-IR sensors. On this challenging dataset, our gesture recognition system achieves an accuracy of 83:8%, outperforms competing state-of-the-art algorithms, and approaches human accuracy of 88:4%. Moreover, our method achieves state-of-the-art performance on SKIG and ChaLearn2014 benchmarks.
Enicostemma littorale prevents tumor formation in 7,12-dimethylbenz(a)anthracene-induced hamster buccal pouch carcinogenesis

Oral cancer is one of the most common malignancies worldwide, and India has recorded the highest annual incidence of oral cancer in comparison with other countries. Altered lipid peroxidation and antioxidant status along with defect in detoxification cascade have been implicated in the pathogenesis of several cancers including oral cancer. The aim of this study was to investigate the chemopreventive potential of ethanolic extract of Enicostemma littorale leaves (ElELet) in 7,12-dimethylbenz(a)anthracene (DMBA)-induced hamster buccal pouch carcinogenesis. Oral tumor was developed in the buccal pouches of male golden Syrian hamsters by painting with 0.5% DMBA three times a week for 14 weeks. We observed 100% tumor formation with increase in tumor volume and tumor burden in the hamsters treated with DMBA alone. Imbalance in phase I (cytochrome P450 and cytochrome b5) and phase II (glutathione reductase, glutathione-S-transferase, glutathione, and Deoxythymidine-diaphorase (DT)-diaphorase) detoxification agents and lipid peroxidation by-products (thiobarbituric acid reactive substances) and antioxidant (superoxide dismutase, catalase, glutathione peroxidase, and vitamins E and C) status was noticed in hamsters treated with DMBA alone. Oral administration of ElELet at a dose of 250 mg/kg body weight to hamsters treated with DMBA significantly prevented both precancerous and cancerous lesions in the oral cavity. ElELet modulated the status of phase I and II detoxification agents and antioxidants in favor of the suppression of oral carcinogenesis. This study thus suggests that E. littorale might have inhibited the oral carcinogenesis in DMBA-treated hamsters through its antioxidant potential. The present findings are also substantiated by histological studies during DMBA-induced oral carcinogenesis.
Traffic Reduction in Packet Switched Networked Control Systems Using Deadband Error Modulation

This paper introduces a novel traffic reduction method for Networked Control Systems (NCS) called Deadband Error Modulation (DEM). The deadband modifies the periodic dynamics of Delta Modulation (DM) based techniques such as our previously proposed Event Triggered Adaptive Differential Modulation (ETADM). Like ETADM it can be used for encoding individual scalar elements of a vector (i.e., the state vector or control input). It is also robust to bounded packet drops.
Exponential Stability Analysis of Sampled-Data ODE–PDE Systems and Application to Observer Design

A small-gain approach is presented for analyzing exponential stability of a class of (dynamical) hybrid systems. The systems considered in the paper are composed of finite-dimensional dynamics, represented by a linear ordinary differential equation (ODE), and infinite-dimensional dynamics described by a parabolic partial differential equation (PDE). Exponential stability is established under conditions involving the maximum allowable sampling period (MASP). This new stability result is shown to be useful in the design of sampled-output exponentially convergent observers for linear systems that are described by an ODE–PDE cascade. The new stability result also proves to be useful in designing practical approximate observers involving no PDEs.
Comparison of cytotoxicity test models for evaluating resin-based composites

Objectives: This study compared different cytotoxicity test models for evaluating resin-based composites (RBCs) and assessed the biocompatibility of standard and bulk-fill RBCs. Methods: A standard (spectrum TPH) and a bulk-fill (smart dentin replacement (SDR)) RBC were selected. Disc-shaped specimens (7 mm diameter) of 2 and 4 mm thickness were polymerized for 20 s with a LED curing light of 700 mW/cm2 irradiance. The specimens (n = 5) were subjected to micro-hardness testing and three cytotoxicity test models (direct contact, indirect contact and extract tests) with the established L-929 cell line. Hardness ratios of top and bottom surfaces of specimens were computed to assess the effectiveness of cure. For the direct and indirect contact tests, the cells were stained and zones of inhibition were analyzed after material contact for 24 h. For the extract test, cells were exposed to extracts for 24 h, and cell viability was measured. Data was analyzed using analysis of variance/Scheffe’s post hoc test and Pearson’s correlation (p < 0.05). Results: The lowest mean hardness ratio and highest cytotoxicity were observed for TPH at 4 mm. At 4-mm thickness, SDR was found to be biocompatible with all three models. Correlations between hardness ratio and cell viability ranged from r = 0.89–0.96 for the various tests. A significant correlation (r = 0.97) was also observed between the three test models. Conclusion: Our data indicated consistency between direct contact, indirect contact and extract test models for cytotoxicity testing of RBCs. Bulk placement and curing at 4 mm for the bulk-fill RBC evaluated did not result in undue cytotoxicity.
The effect of acute ophiobolin A treatment on HO-mediated inflammatory processes

Many microbial and plant-derived metabolites contribute to the production of inflammatory mediators and the expression of pro-inflammatory molecules. Ophiobolin A (OPA) is a fungal secondary metabolite produced by Bipolaris species. The aim of our study was to examine the acute effects of this compound on inflammatory processes. Male Wistar rats were treated with 5% ethanol, 0.01 mg/kg OPA, 0.1 mg/kg OPA and 1.0 mg/kg OPA per os. After 24 h of the administrations, inflammatory mediators such as interleukin-6 (IL-6), tumour necrosis factor-alpha (TNF-α) and myeloperoxidase (MPO) enzyme as well as heme oxygenase (HO) activity were measured in both plasma and cardiac tissue, along with serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST). We found that OPA caused a significant elevation in the concentrations of IL-6 and TNF-α, increased MPO activity and decreased HO enzyme activity in the plasma. While OPA induces inflammation in the plasma, it did not change the level of inflammatory mediators in the cardiac tissue and the concentrations of serum ALT and AST. Our findings indicate that rapid release of inflammatory mediators by OPA promotes systemic inflammation. However, this acute OPA treatment does not show toxic effects on the cardiac tissue and the concentrations of liver enzymes.
The Effects of a Probiotic Milk Product Containing Lactobacillus casei Strain Shirota on the Defecation Frequency and the Intestinal Microflora of Sub-optimal Health State Volunteers: A Randomized Placebo-controlled Cross-over Study

Forty healthy individuals with a low defecation frequency were selected, and the effects of intake of a fermented milk beverage that contains Lactobacillus casei strain Shirota (LcS) at 4 x 10 9 bacteria/bottle for 2 weeks (1 bottle/day) on the defecation frequency and intestinal microflora were evaluated by the placebo-controlled double-blind cross-over scheme. Defecation frequency both in times per week and days per week significantly increased in the LcS beverage period compared with the frequency before the beginning of intake. The differences were more notable in those with a stronger tendency to constipation (frequency of defecation before intake ≤ 4.0 times/week, n=21), and the frequency of defecation in the LcS beverage period was significantly higher than in the placebo period. The stool smell and feeling of completion of voiding improved significantly in the LcS beverage period compared with the placebo period, and in those with a stronger tendency to constipation, the stools were significantly softened compared with the state before intake. The number of bifidobacteria and their percentage in the total number of fecal bacteria in the LcS beverage period increased significantly compared with the levels before intake and were significantly higher than the values in the placebo period. No marked change due to the intake of the LcS beverage was observed in the other components of the microflora, the organic acid contents, stool pH, water content, or contents of putrefactive metabolites. These results suggest that intake of the probiotic fermented milk beverage conditions the intestines by improving the state of bowel movements and stool quality and increasing the fecal population level of bifidobacteria.
Hierarchical Multimodal Metric Learning for Multimodal Classification

Multimodal classification arises in many computer vision tasks such as object classification and image retrieval. The idea is to utilize multiple sources (modalities) measuring the same instance to improve the overall performance compared to using a single source (modality). The varying characteristics exhibited by multiple modalities make it necessary to simultaneously learn the corresponding metrics. In this paper, we propose a multiple metrics learning algorithm for multimodal data. Metric of each modality is a product of two matrices: one matrix is modality specific, the other is enforced to be shared by all the modalities. The learned metrics can improve multimodal classification accuracy and experimental results on four datasets show that the proposed algorithm outperforms existing learning algorithms based on multiple metrics as well as other approaches tested on these datasets. Specifically, we report 95.0% object instance recognition accuracy, 89.2% object category recognition accuracy on the multi-view RGB-D dataset and 52.3% scene category recognition accuracy on SUN RGB-D dataset.
New State and Measurement Models for Endo-Atmospheric Tracking of Ballistic Targets using Seeker Measurements

Two state models and a measurement model for estimation of relative kinematics using measurements from RF seekers are proposed. The state vector for the first state model includes the acceleration of the target along with target-interceptor relative position and velocity in the state vector. In the other state model, the jerk of the target is also included among the state variables. Both models also include the ratio of the air density and the ballistic coefficient and its time derivatives as elements of the state vector to account for the aerodynamic drag in the endo-atmospheric phase. Such formulations obviate the need for assuming empirical models of air density and drag coefficient. In the proposed measurement model, the line of sight (LOS) angle is derived from the seeker measurements of LOS rate and gimbal angle and used for measurement update of the state estimator. This reduces the dimension of the measurement vector and obviates the need for modeling the dynamics of the seeker tracking and the stabilization loop. Performance results of the proposed methods have been compared with a well- known model from the literature under closed-loop guidance employing the augmented proportional navigation (APN) law for endo-atmospheric ballistic target tracking. It is clearly seen that the proposed methods yield more accurate estimates of target acceleration in terms of reduced mean error and a more favourable cumulative distribution of miss distances that effectively increase the probability of hit for a given warhead lethality radius.
Single-Cell RNAseq analysis of infiltrating neoplastic cells at the migrating front of human glioblastoma

Glioblastoma is the most common primary brain cancer in adults and is notoriously difficult to treat due to its diffuse nature. We performed single-cell RNAseq on 3589 cells in a cohort of four patients. We obtained cells from the tumor core as well as surrounding peripheral tissue. Our analysis revealed cellular variation in the tumor’s genome and transcriptome, We were able to identify infiltrating neoplastic cells in regions peripheral to the core lesions. Despite the existence of significant heterogeneity among neoplastic cells, we found that infiltrating GBM cells share a consistent gene signature between patients, suggesting a common mechanism of infiltration. Additionally, in investigating the immunological response to the tumors, we found transcriptionally distinct myeloid cell populations residing in the tumor core and the surrounding peritumoral space. Our data provide a detailed dissection of GBM cell types, revealing an abundance of novel information about tumor formation and migration.
An Algorithm for the Fine Estimation of Polynomial-Phase Signals

To precisely estimate the parameters of polynomial-phase signals (PPSs), we adopt a recently-proposed algorithm for sinusoid frequency estimation. The algorithm is combined with the Wigner distribution to estimate the instantaneous frequency of linear FM signals and with the high-order ambiguity function to estimate parameters of higher order PPSs. Both Gaussian and non-Gaussian noises are considered in simulations, which show that the algorithm converges within two iterations and approach achievable limits for the considered techniques.
Sparsity-based autofocus for undersampled synthetic aperture radar

Motivated by the field of compressed sensing and sparse recovery, nonlinear algorithms have been proposed for the reconstruction of synthetic-aperture-radar images when the phase history is undersampled. These algorithms assume exact knowledge of the system acquisition model. In this paper we investigate the effects of acquisition-model phase errors when the phase history is undersampled. We show that the standard methods of autofocus, which are used as a postprocessing step on the reconstructed image, are typically not suitable. Instead of applying autofocus in postprocessing, we propose an algorithm that corrects phase errors during the image reconstruction. The performance of the algorithm is investigated quantitatively and qualitatively through numerical simulations on two practical scenarios where the phase histories contain phase errors and are undersampled.
Controlling spacecraft landings with constantly and exponentially decreasing time-to-contact

Two bioinspired landing strategies are studied. Both strategies enforce a constant ventral optic flow with constantly decreasing time-to-contact or exponentially decreasing time-to-contact. Until now these strategies have only been studied assuming the visual quantities to be known, i.e., without sensor noise and delay. In this study, the control laws executing the aforementioned landing strategies are studied both theoretically and empirically, taking into account the actual extraction of the visual cues from images.
P112 Speech And Language Therapy By Skype™ For Vocal Cord Dysfunction And Chronic Cough

Introduction The Airways Service at Royal Preston Hospital receives tertiary referrals from across the UK. When a diagnosis of vocal cord dysfunction (VCD) or chronic cough is made and speech and language therapy (SLT) required, patients undergo weekly therapy (minimum four sessions), which some may struggle to attend due to pre-existing commitments and/or travel time. As SLT typically does not require ‘hands-on’ therapy we felt that Skype™ videoconferencing may be a useful mode of treatment delivery. We present our initial experience of this service. Methods A six-month pilot was completed whereby patients were offered SLT over Skype. Prior to therapy all patients were seen by the respiratory consultant and speech and language therapist for assessment and flexible laryngoscopy. Patients required confidential webcam access and proficiency. Symptom questionnaires were completed pre and post therapy (for VCD the 12 item VCDQ; for chronic cough the 19-item LCQ), and patient satisfaction questionnaires and flexible laryngoscopy performed post therapy. Results Eleven people have completed SLT over Skype™ to date, and all demonstrated improvement in symptoms following therapy. Patients with VCD showed a decrease in score on the VCDQ from median (range) 48 (12–53) pre therapy to 40 (7–42) post therapy [minimal clinical important difference (MCID) 5]. Patients with chronic cough showed an increase on the LCQ from median (range) 6.4 (4.6–8.2) pre therapy to 12.2 (10–14.6) post therapy (MCID 1.3). Improvements in laryngeal tension and sensitivity were noted in all cases. All patients gave positive feedback in their patient satisfaction questionnaire scoring “very satisfied” or greater. On three occasions Skype connection problems delayed sessions by a few days. Conclusions Virtual consultations provide the opportunity to treat patients in a more time efficient and practical way, and improvements in patient-reported symptoms and laryngeal appearances were similar to those of patients attending therapy sessions in chest clinic. This data gives support to pursue formalised tariffs for a specialised telehealth service. We feel that Skype should continue as a regular therapy option for patients and other members of the multi-disciplinary team (MDT) should consider this method of therapy delivery.
PHTLS: BASIC AND ADVANCED PREHOSPITAL TRAUMA LIFE SUPPORT, 4TH EDITION

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Frequency-Domain Range Sidelobe Correction in Stretch Processing for Wideband LFM Radars

High linearity and low noise are important conditions for high-resolution imaging in wideband linear frequency modulation (LFM) radar systems, where stretch processing is commonly adopted. However, in practice, hardware may introduce amplitude and phase distortions to radar signals. The distortions will increase the range sidelobes (RSLs) of the dechirped returns and cause the decline of imaging quality. Traditional time-domain RSL correction methods are greatly influenced by time delay and can only be used in a small range window. To solve the problem, we propose a novel frequency-domain RSL correction (FDRC) method in this paper. For FDRC, we first multiply the extracted distortion and the stretched return by a baseband LFM signal and then perform the correction in the frequency domain. Both theoretical and simulation results show that the proposed method provides equivalent performances in RSLs compared to other existing distortion correction methods in a large range window. Besides, the proposed method can be much easily implemented in practical radar systems.
Thorough Understanding Property of Bistatic Forward-Looking High-Speed Maneuvering Platform SAR

This paper investigates a new and special imaging mode, bistatic forward-looking high-speed maneuvering platform synthetic aperture radar, in which both platforms travel curvilinear trajectories with high velocities and accelerations. A thorough understanding of its new properties of motion, 2-D resolution, and echo signal coupling is given. Applicability of gradient method neglecting time dependence of gradient to this special configuration is addressed. Moreover, 2-D coupling characteristic of echo signal at different imaging distances is investigated.
Clinical reasoning in medicine and nursing: Decision making versus problem solving

The clinical reasoning process includes two broad components: (a) problem solving (searching for the one “right”; answer) and (b) decision making (selecting from several possibilities). Each component requires considerable knowledge and skill; decision making also requires that the values assigned to each potential outcome be ascertained and used. We present a framework for the clinical encounter, with particular emphasis on treatment selection. We then note evidence, including three studies conducted by our research group, to support the view that clinical problem solving is based primarily on pattern recognition following data gathering, rather than on a deterministic rule‐based approach. We suggest that a pattern recognition approach, which stresses the importance of a knowledge base as opposed to a set of learned skills, implies a strong potential role for the computer in both medical practice and medical education.