Miracle-dz/UniFAR-FTUs huggingface dataset:
Successful treatment of a critically ill patient with acute respiratory distress syndrome from COVID-19 using mechanical ventilation strategy with low levels of positive end-expiratory pressure

Abstract Introduction: Acute respiratory distress syndrome (ARDS) secondary to COVID-19 is different from the ARDS caused by other infections. Conventional mechanical ventilation strategies using high levels of PEEP may not be beneficial and can even be harmful to patient with ARDS from COVID-19. So the ventilation strategies should be adjusted in order to improve the pulmonary ventilation function and oxygenation status, and outcomes of the patient. Patient concerns: Herein, we present a 76-year-old male patient with ARDS secondary to COVID-19. We describe our experience with mechanical ventilation strategy and the changes in respiratory mechanics in the patient during treatment. Diagnosis: The patient had tested positive for coronavirus (COVID-19) in nucleic acid test. Chest CT showed multiple ground glass shadows in both lungs. Interventions: The patient received mechanical ventilation with low tidal volume and low PEEP. Outcomes: After treatment, the patients condition, as well as oxygenation status was improved, and he tested negative for the coronavirus several times. Conclusion: This case demonstrated that the low tidal volume with low levels of PEEP ventilation strategy may be more suitable for ARDS from COVID-19.
Metabolomic Analysis of the Ameliorative Effect of Enhanced Proline Metabolism on Hypoxia-Induced Injury in Cardiomyocytes

Background Coronary heart disease is currently the leading cause of death in humans. Its poor prognosis and high mortality are associated with myocardial ischemia, which leads to metabolic disorder-related cardiomyocyte apoptosis and reactive oxygen species (ROS) production. Previous cardiovascular metabolomics studies in humans and mice have shown that proline metabolism is severely altered after cardiomyocyte hypoxia. Proline dehydrogenase (PRODH) is located on the inner mitochondrial membrane and is an enzyme that catalyzes the first step of proline catabolism, which plays an important role in improving the cellular redox state. In vitro oxygen-glucose deprivation can mimic in vivo myocardial ischemic injury. This study is aimed at investigating whether enhancing proline metabolism by overexpressing PRODH can ameliorate hypoxia-induced injury in cardiomyocytes and to reveal the related altered metabolites and mechanistic pathway via untargeted metabolomics analysis. Methods and Results First, through public database analysis and RT-qPCR and western blot analyses in a cardiomyocyte hypoxia model, we found that the expression of the proline-degrading enzyme PRODH was downregulated after myocardial infarction and hypoxia exposure. Second, LDH assays, terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL), DHE staining, flow cytometric apoptosis analysis with DCFH and Annexin V-FITC/PI, and western blot analysis were used to assess the injury level in cardiomyocytes. Enhanced proline metabolism induced by PRODH overexpression reduced the levels of reactive oxidative stress and apoptosis, whereas PRODH knockdown had the opposite effects. Third, untargeted metabolomics analysis revealed that the protective effect was associated with significant changes in metabolism linked to sphingolipid signaling pathways, unsaturated fatty acid biosynthesis, phosphocreatine, glutathione disulfide, aminoacyl-tRNA biosynthesis, and ABC transporters. Conclusions Our study demonstrated a protective effect of enhanced proline metabolism in cardiomyocytes under hypoxia, providing a novel strategy for exploring new treatments for coronary heart disease.
Acute Effects of Whole-Body Vibration Exercises at 2 Different Frequencies Versus an Aerobic Exercise on Some Cardiovascular, Neuromotor and Musculoskeletal Parameters in Adult Patients With Obesity

Whole-body vibration exercise (WBVE), a nonimpact, viable and safe type of exercise, has been reported to be useful in the physical rehabilitation of obesity. Aim of the study was to compare the acute effects of WBVE with a session of walking and running (AER) on cardiovascular, neuromotor and musculoskeletal parameters in obese subjects. Sixteen adult obese subjects performed 3 tests (WBVE at 30 and 45 Hz, AER) randomly in different days. An increase in heart rate was recorded after AER and 45 Hz WBVE (p < 0.001), while only AER increased systolic (p = 0.003) and diastolic blood pressure (p = 0.004) and ratings of perceived exertion (p < 0.001). All 3 exercises determined lactate increase [AER p < 0.001, 45 Hz (p = 0.04), 30 Hz (p = 0.03) WBVE] and sit-and-reach (AER p = 0.002, 45 and 30 Hz WBVE p < 0.001) and fingertip-to-floor improvements (AER p = 0.003, 30 and 45 Hz WBVE p < 0.001), while only 30 Hz WBVE determined improvement in stair climbing test (p < 0.05). Considering the lack of effects of 30 Hz WBVE on the cardiovascular system and fatigue and its positive effect on flexibility and muscle power, this procedure can be considered an appropriate exercise protocol for the obese population.
Multiple Irrelevant Duration Information Affects the Perception of Relevant Duration Information: Interference With Selective Processing of Duration

In the human visual environment, the ability to perceive only relevant duration is important for various activities. However, a relatively small number of studies have investigated how humans process multiple durations, in comparison with the processing of one or two durations. We investigated the effects of multiple irrelevant durations on the perception of relevant duration. In four behavioral experiments, the participants were instructed to pay attention to a target stimulus while ignoring the distractors; then, they reproduced the target duration. We manipulated three aspects of the distractors: number, duration range, and cortical distance to the target. The results showed that the presence of multiple irrelevant durations interfered with the processing of relevant duration in terms of the mean perceived duration and the variability of the perceived duration. The interference was directional; that is, longer (shorter) irrelevant durations made the reproduced durations longer (shorter). Moreover, the interference was not likely to depend on the cortical distance between the target and the distractors, suggesting an involvement of relatively higher cortical areas. These results demonstrate that multiple irrelevant duration information affects the temporal processing of relevant duration information and suggest that multiple independent clocks assigned to each of the durations may not exist.
COVID-19 and the Central Dogma: an Activity To Improve Student Learning and Engagement†

The Central Dogma of molecular biology describes the transfer of genetic information within organisms and is a core concept in the biological sciences. However foundational, the Central Dogma is often misrepresented when taught in introductory college biology courses. In particular, the Central Dogma is often taught with a requisite DNA step, an incorrect conception that omits the possibility of RNA-based molecular systems, such as SARS-CoV-2, the causative agent of COVID-19. In this new contribution, we offer a practical way to clarify correct conceptions and make them immediately relevant through COVID-19. In this new digital ‘sorting cards’ activity, students collaboratively synthesize and map their knowledge of core molecular biology. Building off of the typically-presented concepts of the Central Dogma, we also introduce two sorting card “expansion packs” for double-stranded DNA viruses and single-stranded RNA viruses. We provide activity templates for all sets of cards using a free web-based collaborative platform suitable for sudden shifts to online learning (as in our implementation), pre-planned online learning, and in-person classes. While truly hands-on activities can be difficult to replicate in the context of online learning, the use of collaborative websites and creative freedom in this activity encourages student engagement in and ownership of their learning.
The miR-146a SNP Rs2910164 and miR-155 SNP rs767649 Are Risk Factors for Non-Small Cell Lung Cancer in the Iranian Population

Background Lung cancer is one of the leading causes of death worldwide. MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression and may act as both tumor suppressors and as oncogenes. The presence of single nucleotide polymorphisms (SNPs) inside the miRNA genomic region could affect target miRNA maturation, expression, and binding to its target mRNA and contribute to cancer development. Previous studies on the SNPs Rs2910164 in miR-146a and Rs767649 in miR-155 showed association with non-small cell lung cancer (NSCLC) development. Thus, the aim of this study was to detect any correlation between those SNPs in Iranian NSCLC patients. Methods In a small cohort study, 165 NSCLC patients and 147 noncancer controls were enrolled between Apr 2015 and Sep 2019 at the Masih Daneshvari Hospital, Tehran, Iran. Allele frequencies from the genomic DNA of blood cells were studied using PCR-RFLP and their association with the risk of lung cancer was evaluated. Results The rs2910164C allele (OR = 1.56, 95% CI = 1.10–2.21, p = 0.012) and CC genotype (OR = 2.93, 95% CI = 1.07–7.9, p = 0.034, respectively) were associated with a significantly increased risk for lung cancer compared to that for the GG genotype. When patients were stratified according to smoking exposure, no association with rs2910164 variants was found. The AT genotype (OR = 0.57, 95% CI = 0.33–0.99, p = 0.048) and the A allele frequency (OR = 0.58, 95% CI = 0.35–0.98, p = 0.043) in rs767649 were lower in NSCLC patients in comparison with the control group. In addition, the rs767649 AT genotype frequency in smoking controls was higher than in smoking NSCLC patients (OR = 0.44, 95% CI = 0.21–0.90, p = 0.024). No association was found between rs2910164 and rs767649 variants and stage or type of NSCLC. Conclusion Our finding suggests that miR-146a rs2910164 and miR-155 rs767649 polymorphisms may be considered as genetic risk factors for the susceptibility to NSCLC in the Iranian population. However, a larger multicenter study across Iran is needed to confirm these findings.
Reducing human exposure to arsenic, and simultaneously increasing selenium and zinc intake, by substituting non-aromatic rice with aromatic rice in the diet

Hundreds of millions of people world-wide are exposed to high concentrations of the toxic element arsenic (As) through drinking water and consumption of certain foods, especially rice. In this study Inductively Coupled Plasma Mass Spec- troscopy (ICP-MS) was used to analyse rice from the greater Sylhet region of Bangladesh which has relatively lower ground- water As concentrations. Different varieties of rice were analysed for inorganic-As (i-As) and other elements (Cd, Mn, Pb, Se and Zn) in order to identify rice with low As content and higher essential element (Zn and Se) content. Sylheti non-aromatic rice showed lower As concentration (27.1-174.1 µg/kg) compared to non-aromatic rice from other regions of Bangladesh. Fur- thermore, aromatic rice from Sylhet had the lowest As content (10.1 µg/kg) and the highest Se content (341 µg/kg) compared to non-aromatic rice. Approximately 70% of the total As in Sylheti rice was i-As and parboiled rice contained the highest i-As (90%) compared to other rice varieties. Aromatic rice generally contained lower concentrations of toxic elements (As, Cd, Pb) and higher concentrations of essential elements (Se, Zn) compared to non-aromatic rice. For someone consuming 500 g of non-aromatic or aromatic rice from Sylhet, the daily intake of As from consumption of rice would be reduced by approximately 48% and 69%, respectively, compared to non-aromatic rice from other parts of Bangladesh thus far investigated. Also the daily intake of As from consumption of aromatic rice is 40% lower compared to non-aromatic rice sourced from the Sylhet region. The daily intake of Se and Zn from consumption of rice would be increased by 46% and 23%, respectively, for someone con- suming aromatic rice instead of non-aromatic rice from Sylhet. This study reveals that consuming certain types of aromatic rice can potentially not only reduce exposure to As but also increase the daily intake of Se and Zn in Bangladeshis. This type of rice could also be used in infant foods instead of rice with higher As concentration.
Transcriptomic Analysis of circRNAs in the Peripheral Blood of Nonarteritic Anterior Ischemic Optic Neuropathy

The aim of the study is to explore the expression profile variation of circular RNAs (circRNAs) in the peripheral blood of subjects with nonarteritic anterior ischemic optic neuropathy (NAION) and without NAION, to analyze the differential expression results, and to predict the role of circRNAs in disease development, providing novel ideas and methods for treatment and diagnosis. High-throughput sequencing to explore the expression profiles of RNAs in the peripheral blood of 6 NAION patients and 5 healthy controls was applied. Quality control obtained the advanced data from the original data by ticking out the unqualified data. Then, cluster analysis, volcano plot, coexpression network, and protein-protein interaction network (PPI) were performed. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were used to analyze the whole expressed genes. Lastly, the quantitative real-time Polymerase Chain Reaction (qRT-PCR) was used to verify those significantly differentially expressed circRNAs and do some bioinformatics analysis and prediction in 12 NAION patients and 12 controls. There were significant differences in the expression of 49 circRNAs in the peripheral blood of NAION patients, in which there were 24 upregulations and 25 downregulations (variation folds > 2 and P < 0.05), and it was confirmed that hsa_circ_0005583, hsa_circ_0003922, hsa_circ_0002021, and hsa_circ_0000462 were significantly downregulated (variation folds > 2 and P < 0.05), especially hsa_circ_0005583 which was the most significantly changed one (P < 0.001), and are related to processes such as neurodegeneration, oxidative stress, immunity, and metabolism. The expression profile of circRNAs in the peripheral blood of NAION patients is significantly changed, enriching our understanding of the disease.
An example in homotopy theory

PROPOSITION. There exist two CW-complexes X, Y and a map f:X ->• Y such that (i) the map f is essential, (ii) the restriction of f to any finite-dimensional skeleton X is inessential, and (iii) Y is finite-dimensional. In our example, X is the suspension of infinite complex projective space CP°°. Y has the homotopy type of a countable wedge of 4-spheres, but we shall present Y in a different way, so as to facilitate description of the map/. We first make a ' telescope' T as follows. Take a countable union of copies of the product of the 3-sphere S with the unit interval / = [0,1]. Glue the end S x 1 of the ith. copy to the end *Sf+1 x 0 of the (i+ l)th copy by identifying each point (x, 1) with (gt(x),0), where gi:S ^#? +1 is a map of degree (i+ 1). The resulting space T is thus a Moore space Y(Q, 3), where Q is the additive group of rationals; if st is the homology class of S , st generates the integer subgroup Z ^ Q and ŝ = (i + 1) si+1.
Creation of Quaternary Stereogenic Centers via Copper-Catalyzed Asymmetric Conjugate Addition of Alkenyl Alanes to α,β-Unsaturated Cyclic Ketones

SimplePhos ligands proved to be very powerful ligands in the generation of quaternary stereogenic centers by Michael addition of alkenyl-aluminum reagents to cyclic enones. Using commercially available and easily accessible alkenylbromides as alane precursors the present procedure offers a facile access to β-alkenyl-substituted cyclohexanones with high enantioselectivities up to 96%.
G-RCN: Optimizing the Gap between Classification and Localization Tasks for Object Detection

Multi-task learning is widely used in computer vision. Currently, object detection models utilize shared feature map to complete classification and localization tasks simultaneously. By comparing the performance between the original Faster R-CNN and that with partially separated feature maps, we show that: (1) Sharing high-level features for the classification and localization tasks is sub-optimal; (2) Large stride is beneficial for classification but harmful for localization; (3) Global context information could improve the performance of classification. Based on these findings, we proposed a paradigm called Gap-optimized region based convolutional network (G-RCN), which aims to separating these two tasks and optimizing the gap between them. The paradigm was firstly applied to correct the current ResNet protocol by simply reducing the stride and moving the Conv5 block from the head to the feature extraction network, which brings 3.6 improvement of AP70 on the PASCAL VOC dataset and 1.5 improvement of AP on the COCO dataset for ResNet50. Next, the new method is applied on the Faster R-CNN with backbone of VGG16,ResNet50 and ResNet101, which brings above 2.0 improvement of AP70 on the PASCAL VOC dataset and above 1.9 improvement of AP on the COCO dataset. Noticeably, the implementation of G-RCN only involves a few structural modifications, with no extra module added.
Design of an Optoelectronically Innervated Gripper for Rigid-Soft Interactive Grasping

Over the past few decades, efforts have been made towards robust robotic grasping, and therefore dexterous manipulation. The soft gripper has shown their potential in robust grasping due to their inherent properties-low, control complexity, and high adaptability. However, the deformation of the soft gripper when interacting with objects bring inaccuracy of grasped objects, which causes instability for robust grasping and further manipulation. In this paper, we present an omni-directional adaptive soft finger that can sense deformation based on embedded optical fibers and the application of machine learning methods to interpret transmitted light intensities. Furthermore, to use tactile information provided by a soft finger, we design a low-cost and multi degrees of freedom gripper to conform to the shape of objects actively and optimize grasping policy, which is called Rigid-Soft Interactive Grasping. Two main advantages of this grasping policy are provided: one is that a more robust grasping could be achieved through an active adaptation; the other is that the tactile information collected could be helpful for further manipulation.
A Bayesian approach to deconvolution in well test analysis.

In petroleum well test analysis, deconvolution is used to obtain information about the reservoir system. This information is contained in the response function, which can be estimated by solving an inverse problem in the pressure and flow rate measurements. Our Bayesian approach to this problem is based upon a parametric physical model of reservoir behaviour, derived from the solution for fluid flow in a general class of reservoirs. This permits joint parametric Bayesian inference for both the reservoir parameters and the true pressure and rate values, which is essential due to the typical levels of observation error. Using a set of flexible priors for the reservoir parameters to restrict the solution space to physical behaviours, samples from the posterior are generated using MCMC. Summaries and visualisations of the reservoir parameters' posterior, response, and true pressure and rate values can be produced, interpreted, and model selection can be performed. The method is validated through a synthetic application, and applied to a field data set. The results are comparable to the state of the art solution, but through our method we gain access to system parameters, we can incorporate prior knowledge that excludes non-physical results, and we can quantify parameter uncertainty.
Dimmer: Self-Adaptive Network-Wide Flooding with Reinforcement Learning

The last decade saw an emergence of Synchronous Transmissions (ST) as an effective communication paradigm in low-power wireless networks. Numerous ST protocols provide high reliability and energy efficiency in normal wireless conditions, for a large variety of traffic requirements. Recently, with the EWSN dependability competitions, the community pushed ST to harsher and highly-interfered environments, improving upon classical ST protocols through the use of custom rules, hand-tailored parameters, and additional retransmissions. The results are sophisticated protocols, that require prior expert knowledge and extensive testing, often tuned for a specific deployment and envisioned scenario. In this paper, we explore how ST protocols can benefit from self-adaptivity; a self-adaptive ST protocol selects itself its best parameters to (1) tackle external environment dynamics and (2) adapt to its topology over time. We introduce Dimmer as a self-adaptive ST protocol. Dimmer builds on LWB and uses Reinforcement Learning to tune its parameters and match the current properties of the wireless medium. By learning how to behave from an unlabeled dataset, Dimmer adapts to different interference types and patterns, and is able to tackle previously unseen interference. With Dimmer, we explore how to efficiently design AI-based systems for constrained devices, and outline the benefits and downfalls of AI-based low-power networking. We evaluate our protocol on two deployments of resource-constrained nodes achieving 95.8 % reliability against strong, unknown WiFi interference. Our results outperform baselines such as non-adaptive ST protocols (~27%) and PID controllers, and show a performance close to hand-crafted and more sophisticated solutions, such as Crystal (~99 %).
Efficient Reservoir Management through Deep Reinforcement Learning

Dams impact downstream river dynamics through flow regulation and disruption of upstream-downstream linkages. However, current dam operation is far from satisfactory due to the inability to respond the complicated and uncertain dynamics of the upstream-downstream system and various usages of the reservoir. Even further, the unsatisfactory dam operation can cause floods in downstream areas. Therefore, we leverage reinforcement learning (RL) methods to compute efficient dam operation guidelines in this work. Specifically, we build offline simulators with real data and different mathematical models for the upstream inflow, i.e., generalized least square (GLS) and dynamic linear model (DLM), then use the simulator to train the state-of-the-art RL algorithms, including DDPG, TD3 and SAC. Experiments show that the simulator with DLM can efficiently model the inflow dynamics in the upstream and the dam operation policies trained by RL algorithms significantly outperform the human-generated policy.
Photoluminescent Polymer/Quantum Dot Composite Nanoparticles

Core−shell CdS/SiO2 nanoparticles were prepared and modified with the atom transfer radical polymerization (ATRP) initiator 3-(2-bromopropionyloxy)propyl dimethylethoxysilane (BIDS). The initiator-modified nanoparticles were then used as macroinitiators for the polymerization of methyl methacrylate (MMA) catalyzed by NiBr2(PPh3)2. These hybrid polymer/inorganic nanoparticles could be cast into films that retained the photoluminescence of the precursor CdS nanoparticles and showed even dispersal of the CdS/SiO2 cores throughout the PMMA matrix. These hybrid nanoparticles are versatile structures: their films can be processed from solution and show uniform dispersion of the inorganic phase throughout the host organic matrix on the microscopic level. These nanoparticles also have components whose structures and compositions can be altered to introduce new properties to the material (i.e., the luminescence of the inorganic core or the conductivity of the polymer arms) and to allow for self-assembly of the ma.