Miracle-dz/UniFAR-FTUs huggingface dataset:
Submarine Rescue Decompression Procedure from Hyperbaric Exposures up to 6 Bar of Absolute Pressure in Man: Effects on Bubble Formation and Pulmonary Function

Recent advances in submarine rescue systems have allowed a transfer under pressure of crew members being rescued from a disabled submarine. The choice of a safe decompression procedure for pressurised rescuees has been previously discussed, but no schedule has been validated when the internal submarine pressure is significantly increased i.e. exceeding 2.8 bar absolute pressure. This study tested a saturation decompression procedure from hyperbaric exposures up to 6 bar, the maximum operating pressure of the NATO submarine rescue system. The objective was to investigate the incidence of decompression sickness (DCS) and clinical and spirometric indices of pulmonary oxygen toxicity. Two groups were exposed to a Nitrogen-Oxygen atmosphere (pO2 = 0.5 bar) at either 5 bar (N = 14) or 6 bar (N = 12) for 12 h followed by 56 h 40 min resp. 60 h of decompression. When chamber pressure reached 2.5 bar, the subjects breathed oxygen intermittently, otherwise compressed air. Repeated clinical examinations, ultrasound monitoring of venous gas embolism and spirometry were performed during decompression. During exposures to 5 bar, 3 subjects had minor subjective symptoms i.e. sensation of joint discomfort, regressing spontaneously, and after surfacing 2 subjects also experienced joint discomfort disappearing without treatment. Only 3 subjects had detectable intravascular bubbles during decompression (low grades). No bubbles were detected after surfacing. About 40% of subjects felt chest tightness when inspiring deeply during the initial phase of decompression. Precordial burning sensations were reported during oxygen periods. During decompression, vital capacity decreased by about 8% and forced expiratory flow rates decreased significantly. After surfacing, changes in the peripheral airways were still noticed; Lung Diffusion for carbon monoxide was slightly reduced by 1% while vital capacity was normalized. The procedure did not result in serious symptoms of DCS or pulmonary oxygen toxicity and may be considered for use when the internal submarine pressure is significantly increased.
One piece DLFT automotive running boards

Decoma International has developed a one piece composite running board utilizing Composite Products' patented Advantage inline compounding technology. Running boards are currently in production on the F250/350 Regular, Super and Crew cabs, Explorer and Mountaineer vehicles. The replacement of the 43 piece metal and plastic assembly translates into a running board that meets or exceeds performance requirements at a significant cost savings to the OEM at half the weight. Composite Products, Inc. has commercialized this in-line compounding technology to produce long fiber thermoplastic composite solutions for various automotive applications. Advantage systems continuously compound thermoplastic resin with fiber reinforcements such as chopped fiber glass, carbon or natural fibers to produce finished composites with outstanding toughness and excellent exterior appearance characteristics.
Slow Motor Responses to Visual Stimuli of Low Salience in Autism

ABSTRACT The authors studied 2 tasks that placed differing demands on detecting relevant visual information and generating appropriate gaze shifts in adults and children with and without autism. In Experiment 1, participants fixated a cross and needed to make large gaze shifts, but researchers provided explicit instructions about shifting. Children with autism were indistinguishable from comparison groups in this top-down task. In Experiment 2 (bottom-up), a fixation cross remained or was removed prior to the presentation of a peripheral target of low visual salience. In this gap–effect experiment, children with autism showed lengthened reaction times overall but no specific deficit in overlap trials. The results show evidence of a general deficit in manual responses to visual stimuli of low salience and no evidence of a deficit in top-down attention shifting. Older children with autism appeared able to generate appropriate motor responses, but stimulus-driven visual attention seemed impaired.
Predicting Free-Space Occupancy on Novel Artificial Structures by an Invasive Intertidal Barnacle Using a Removal Experiment

Artificial structures can create novel habitat in the marine environment that has been associated with the spread of invasive species. They are often located in areas of high disturbance and can vary significantly in the area of free space provided for settlement of marine organisms. Whilst correlation between the amount of free space available and recruitment success has been shown in populations of several marine benthic organisms, there has been relatively little focus on invasive species, a group with the potential to reproduce in vast numbers and colonise habitats rapidly. Invasion success following different scales of disturbance was examined in the invasive acorn barnacle, Austrominius modestus , on a unique art installation located in Liverpool Bay. Population growth and recruitment success were examined by comparing recruitment rates within disturbance clearings of 4 different sizes and by contrasting population development with early recruitment rates over a 10 week period. Disturbed areas were rapidly recolonised and monocultures of A . modestus formed within 6 weeks. The size of patch created during disturbance had no effect on the rate of recruitment, while a linear relationship between recruit density and patch size was observed. Density-dependent processes mediated initial high recruitment resulting in population stability after 8-10 weeks, but densities continued to greatly exceed those reported in natural habitats. Given that artificial structures are likely to continue to proliferate in light of climate change projections, free-space is likely to become more available more frequently in the future supporting the expansion of fast-colonising species.
DCDistance: A Supervised Text Document Feature extraction based on class labels

Text Mining is a field that aims at extracting information from textual data. One of the challenges of such field of study comes from the pre-processing stage in which a vector (and structured) representation should be extracted from unstructured data. The common extraction creates large and sparse vectors representing the importance of each term to a document. As such, this usually leads to the curse-of-dimensionality that plagues most machine learning algorithms. To cope with this issue, in this paper we propose a new supervised feature extraction and reduction algorithm, named DCDistance, that creates features based on the distance between a document to a representative of each class label. As such, the proposed technique can reduce the features set in more than 99% of the original set. Additionally, this algorithm was also capable of improving the classification accuracy over a set of benchmark datasets when compared to traditional and state-of-the-art features selection algorithms.
Deep Semantic Hashing with Generative Adversarial Networks

Hashing has been a widely-adopted technique for nearest neighbor search in large-scale image retrieval tasks. Recent research has shown that leveraging supervised information can lead to high quality hashing. However, the cost of annotating data is often an obstacle when applying supervised hashing to a new domain. Moreover, the results can suffer from the robustness problem as the data at training and test stage may come from different distributions. This paper studies the exploration of generating synthetic data through semi-supervised generative adversarial networks (GANs), which leverages largely unlabeled and limited labeled training data to produce highly compelling data with intrinsic invariance and global coherence, for better understanding statistical structures of natural data. We demonstrate that the above two limitations can be well mitigated by applying the synthetic data for hashing. Specifically, a novel deep semantic hashing with GANs (DSH-GANs) is presented, which mainly consists of four components: a deep convolution neural networks (CNN) for learning image representations, an adversary stream to distinguish synthetic images from real ones, a hash stream for encoding image representations to hash codes and a classification stream. The whole architecture is trained end-to-end by jointly optimizing three losses, i.e., adversarial loss to correct label of synthetic or real for each sample, triplet ranking loss to preserve the relative similarity ordering in the input real-synthetic triplets and classification loss to classify each sample accurately. Extensive experiments conducted on both CIFAR-10 and NUS-WIDE image benchmarks validate the capability of exploiting synthetic images for hashing. Our framework also achieves superior results when compared to state-of-the-art deep hash models.
Ferumoxytol-enhanced magnetic resonance imaging in acute myocarditis

Objectives Ultrasmall superparamagnetic particles of iron oxide (USPIO)-enhanced MRI can detect tissue-resident macrophage activity and identify cellular inflammation within tissues. We hypothesised that USPIO-enhanced MRI would provide a non-invasive imaging technique that would improve the diagnosis and management of patients with acute myocarditis. Methods Ten volunteers and 14 patients with suspected acute myocarditis underwent T2, T2* and late gadolinium enhancement (LGE) 3T MRI, with further T2* imaging at 24 hours after USPIO (ferumoxytol, 4 mg/kg) infusion, at baseline and 3 months. Myocardial oedema and USPIO enhancement were determined within areas of LGE as well as throughout the myocardium. Results Myocarditis was confirmed in nine of the 14 suspected cases of myocarditis. There was greater myocardial oedema in regions of LGE in patients with myocarditis when compared with healthy volunteer myocardium (T2 value, 57.1±5.3 vs 46.7±1.6 ms, p<0.0001). There was no demonstrable difference in USPIO enhancement between patients and volunteers even within regions displaying LGE (change in R2*, 35.0±15.0 vs 37.2±9.6 s−1, p>0.05). Imaging after 3 months in patients with myocarditis revealed a reduction in volume of LGE, a reduction in oedema measures within regions displaying LGE and improvement in ejection fraction (mean −19.7 mL, 95% CI (−0.5 to −40.0)), −5.8 ms (−0.9 to −10.7) and +6% (0.5% to 11.5%), respectively, p<0.05 for all). Conclusion In patients with acute myocarditis, USPIO-enhanced MRI does not provide additional clinically relevant information to LGE and T2 mapping MRI. This suggests that tissue-resident macrophages do not provide a substantial contribution to the myocardial inflammation in this condition. Clinical trial registration NCT02319278; Results.
Stress field and propagation trend of crack tip in tenon of nickel-based single crystal superalloys turbine blade

A rate-dependent crystal slip finite element program was used to analyze the crack characteristic in tenon of nickel-based single crystal superalloys turbine blade,while the influence of crystallographic orientations was also taken into account.The Mises stress distributions of crack tip in tenon under isotropic condition combined with {001},{011}, {111}crystal orientations were researched.Then the crack propagation trend was examined. The results show that:significant stress concentration and relatively large stress gradient occur in the crack tip with orientations of{001}[110],{011}[110],{111}[110]. The maximum stress value appears at the crack tip.Crack propagation trend varies with different crystallographic orientations.Under{001}[110],{011}[110],{111}[110]conditions,the crack propagation angle is 45°,54.7°,90°,respectively.It is clear that crystallographic orientation has significant influence on crack propagation trend of nickel-based single crystal superalloys turbine blade.
Reforestation Sites Show Similar and Nested AMF Communities to an Adjacent Pristine Forest in a Tropical Mountain Area of South Ecuador

Arbuscular mycorrhizae are important for growth and survival of tropical trees. We studied the community of arbuscular mycorrhizal fungi in a tropical mountain rain forest and in neighbouring reforestation plots in the area of Reserva Biológica San Francisco (South Ecuador). The arbuscular mycorrhizal fungi were analysed with molecular methods sequencing part of the 18 S rDNA. The sequences were classified as Operational Taxonomic Units (OTUs). We found high fungal species richness with OTUs belonging to Glomerales, Diversisporales and Archaeosporales. Despite intensive sampling, the rarefaction curves are still unsaturated for the pristine forest and the reforestation plots. The communities consisted of few frequent and many rare species. No specific interactions are recognizable. The plant individuals are associated with one to ten arbuscular mycorrhizal fungi and mostly with one to four. The fungal compositions associated with single plant individuals show a great variability and variety within one plant species. Planted and naturally occurring plants show high similarities in their fungal communities. Pristine forest and reforestation plots showed similar richness, similar diversity and a significantly nested structure of plant-AMF community. The results indicate that small-scale fragmentation presently found in this area has not destroyed the natural AMF community, at least yet. Thus, the regeneration potential of natural forest vegetation at the tested sites is not inhibited by a lack of appropriate mycobionts.
Quantifying the Structure of Free Association Networks Across the Life Span

We investigate how the mental lexicon changes over the life span using free association data from over 8,000 individuals, ranging from 10 to 84 years of age, with more than 400 cue words per age group. Using network analysis, with words as nodes and edges defined by the strength of shared associations, we find that associative networks evolve in a nonlinear (U-shaped) fashion over the life span. During early life, the network converges and becomes increasingly structured, with reductions in average path length, entropy, clustering coefficient, and small world index. Into late life, the pattern reverses but shows clear differences from early life. The pattern is independent of the increasing number of word types produced per cue across the life span, consistent with a network encoding an increasing number of relations between words as individuals age. Lifetime variability is dominantly driven by associative change in the least well-connected words.
Hot cracking behaviour and susceptibility of extra high purity type 310 stainless steels

Recent progress in the refining technology has enabled the production of highly pure commercial stainless steels. The hot cracking behaviour of these stainless steels was investigated with respect to type 310 stainless steel. For comparison, four types of 310 stainless steels with various amounts of minor and impurity elements such as C, P and S were used. The purity of type 310 stainless steels used was enhanced in the order of type 310<type 310S<type 310ULC<type 310EHP steels. The hot cracking susceptibility was evaluated by the transverse Varestraint test. Two types of hot cracks occurred in these steels by Varestraint test; solidification and ductility-dip cracks. The solidification cracking susceptibility was significantly reduced as the amount of C, P and S decreased, and that in type 310EHP steel reached a level so low that solidification cracking did not occur in practical welding. On the other hand, the ductility-dip cracking susceptibility adversely increased as the purity of the steels was enhanced. However, the ductility-dip cracking susceptibility of type 310EHP steel was sufficiently low as not to yield ductility-dip cracking in practical multipass welding. The experimental and numerical analyses on the solidification brittle temperature range have revealed that the reduced solidification cracking susceptibility upon decreasing the amount of C, P and S in stainless steel can be attributed to the reduced BTR due to the suppression of minor and impurity elements, such as C, P and S, in the finally solidified liquid film between the dendrite.
Susceptibility to Oxidative Stress Is Determined by Genetic Background in Neuronal Cell Cultures

Abstract Traumatic brain injury (TBI) leads to a deleterious and multifactorial secondary inflammatory response in the brain. Oxidative stress from the inflammation likely contributes to the brain damage although it is unclear to which extent. A largely unexplored approach is to consider phenotypic regulation of oxidative stress levels. Genetic polymorphism influences inflammation in the central nervous system and it is possible that the antioxidative response differs between phenotypes and affects the severity of the secondary injury. We therefore compared the antioxidative response in inbred rat strains dark agouti (DA) to piebald viral glaxo (PVG). DA has high susceptibility to inflammatory challenges and PVG is protected. Primary neuronal cell cultures were exposed to peroxynitrite (ONOO−), nitric oxide (NO), superoxide (O2−), and 4-hydroxynonenal (4-HNE). Our findings demonstrated a phenotypic control of the neuronal antioxidative response, specific to manganese O2− dismutase (MnSOD). DA neurons had increased levels of MnSOD, equal levels of peroxiredoxin 5 (PRDX5), decreased oxidative stress markers 3-nitrotyrosine (3-NT) and 4-HNE and decreased neuronal death detected by lactate dehydrogenase (LDH) release after 24 h, and higher oxidative stress levels by CellROX than PVG after 2 h. It is possible that DA neurons had a phenotypic adaptation to a fiercer inflammatory environment. ONOO− was confirmed as the most powerful oxidative damage mediator, while 4-HNE caused few oxidative effects. Inducible NO synthase (iNOS) was not induced, suggesting that inflammatory, while not oxidative stimulation was required. These findings indicate that phenotypic antioxidative regulation affects the secondary inflammation, which should be considered in future individualized treatments and when evaluating antioxidative pharmacological interventions.
Perspectives from the Third International Summit on Medical Nutrition Education and Research

Nutrition is an important component of public health and health care, including in education and research, and in the areas of policy and practice. This statement was the overarching message during the third annual International Summit on Medical Nutrition Education and Research, held at Wolfson College, University of Cambridge, United Kingdom, in August 2017. This summit encouraged attendees to think more broadly about the impact of nutrition policy on health and communities, including the need to visualize the complete food system from “pre-farm to post-fork. ” Evidence of health issues related to food and nutrition were presented, including the need for translation of knowledge into policy and practice. Methods for this translation included the use of implementation and behavior change techniques, recognizing the needs of health-care professionals, policy makers, and the public. In all areas of nutrition and health, clear and effective messages, supported by open data, information, and actionable knowledge, are also needed along with strong measures of impact centered on an ultimate goal: to improve nutritional health and wellbeing for patients and the public.
Preoperative Neutrophil-to-Lymphocyte Ratio and Neutrophilia Are Independent Predictors of Recurrence in Patients with Localized Papillary Renal Cell Carcinoma

Objective. To evaluate the role of preoperative neutrophil-to-lymphocyte ratio (NLR) and absolute neutrophil count (ANC) in patients' prognosis with localized papillary renal cell carcinoma (pRCC). Methods. Data from 218 localized pRCC patients (T1-3 N0/+ M0), operated between 1991 and 2011 at two centers, were evaluated retrospectively. Univariable and multivariable analyses using the Cox regression model were performed to determine the associations of NLR and ANC with recurrence-free survival (RFS). Prognostic accuracy was evaluated with the Harrell concordance index. Results. The 5-year RFS rate was 87.0%. Multivariable analysis identified increased NLR (≥3.6) and ANC (≥5300/μL) as independent prognostic factors for RFS (hazard ratio (HR) = 4.01, P = 0.018) and (HR = 4.71, P = 0.045). The final model built by the addition of NLR or ANC improved predictive accuracy (c-index: 0.824, 0.842) compared with the clinicopathological base model (c-index: 0.800), which included TNM stage and tumor necrosis. Conclusions. The NLR and ANC appear to be independent prognostic factors for RFS after surgery for localized pRCC. They significantly increase the accuracy of established prognostic factors. Therefore, we recommend adding NLR and ANC to traditional prognostic model, which may improve its predictive accuracy.
Effects of inoculation timing on symptom development in Ulmus americana L.

Field inoculation trials are an important component of screening American elms (Ulmus americana) for levels of resistance to Dutch elm disease. A major concern in screening is variability in disease ratings from year to year. Previous studies have demonstrated that timing of inoculation can have a significant impact on disease susceptibility. In this study, trees were inoculated in the main stem using a drill method of inoculation. A recently collected isolate of Ophiostoma novo-ulmi with known pathogenicity was used for inoculations. Three different inoculation times were examined: early (May 26), mid (June 23), and late (August 4) season. Trees were assessed for wilt symptoms at 2, 4, 6, and 8 weeks post inoculation using a disease severity scale of 1-6. The trees in the early season inoculation group had the highest mean disease severity ratings at 4, 6, and 8 weeks post inoculation (WPI), while the late season inoculation group had the lowest disease rating at every time point as well as the smallest area under the disease progress curve. Scientists evaluating American elms for resistance to Dutch elm disease should avoid late season inoculations due to reduced disease susceptibility.
Multi-fault diagnosis for rolling bearing based on double parallel extreme learning machine & kurtosis spectral entropy

In this paper, double parallel feedforward extreme learning machine (DP-ELM) model and kurtosis spectral entropy (KSE) are proposed for the early weak multi-fault diagnosis for rolling bearing. Extreme learning machine (ELM) has been widely used as a fast classification model. But a key problem for ELM is to reduce the impact of random variables and it can't make full use of the direct and indirect information among different layers. To solve the problems, a connection is built between the input layer and the output layer. That is, the output layer receives information not only from the hidden layer but also directly from the input layer. And a set of the input layer weights and the hidden layer thresholds will be chosen analytically by founding the best accuracy. Meanwhile, feature extraction is the prerequisite for classification. In order to improve the accuracy of the multi-fault classification, this paper applies the kurtosis spectral entropy (KSE) algorithm to get the useful features from the vibration signals. Then the eigenvalues are input into the DP-ELM model for pattern recognition. In this paper, two sets of rolling bearing data at different speed are used to test. And each set of data includes six different states. Compared with ELM, back propagation neuron network (BP) and radial basis function (RBF), the experimental results show that, with as few as possible of the hidden nodes, the improved method used in this paper ensures a short learning time that it might learn hundreds of times faster than BP method, and obviously increases the accuracy at a degree. Finally, 10 times 10-fold-cross-validation are used to prove the effectiveness.