Miracle-dz/UniFAR-FTUs huggingface dataset:
IL-17 induces macrophages to M2-like phenotype via NF-κB

Background Tumor-associated macrophage (TAM) is emerging as one of the important complications in cancer promotion. Interleukin-17 (IL-17), a potent pro-inflammatory cytokine, plays an active role in promoting M2 macrophage differentiation (TAMs are M2-like phenotypes). In this study, we aimed to evaluate that IL-17 stimulates key phenotypic and functional signatures of M2 macrophages associated with cancer progression in non-small-cell lung cancer (NSCLC) patients. Patients and methods The markers and cytokines of M2 macrophages were detected in THP-1-derived macrophages and mouse peritoneal macrophages treated with IL-17. The activation of nuclear factor kappa B (NF-κB) and nuclear localization of p65 in IL-17-treated cells were investigated. The BAY11-7082 inhibitor and the siRNA of p65 were used to block the NF-κB activation. A total of 85 patients who underwent surgery for histologically verified NSCLC were enrolled in this study. The expression of IL-17 and M2 macrophage markers were assessed by immunostaining. Survivals were estimated using the Kaplan–Meier method. Results The CD163 and CD206 cell surface markers and transforming growth factor beta (TGF-β), vascular endothelial growth factor (VEGF) and IL-10 of M2 macrophages were significantly increased in IL-17-treated THP-1-derived macrophages in a dose-dependent manner. IL-17 increased the mRNA levels of Arginase I and Fizz1, the phosphorylation of IkBα and nuclear localization of p65 (a subunit of NF-κB). The BAY11-7082 abrogated IL-17-induced CD206 and CD163 expression, TGF-β, VEGF, IL-10, Arginase I and Fizz1 expression and p65 nuclear translocation. Further experiments showed that IL-17 induced the expression of CD206, CD163, Arginase I, Fizz1 and Ym1 in mouse peritoneal macrophages that were inhibited by siRNA of p65. The immunostaining experiments on human NSCLC tissues indicated that high IL-17 expression was significantly correlated with CD163 and c-Maf. The intratumoral IL-17+ CD163+ c-Maf+ cells were associated with NSCLC progression. Conclusion IL-17 stimulated macrophages to M2-like phenotypes via NF-κB activation. IL-17 may be a potential therapeutic target for NSCLC.
Automatic Adjustment of Confidence Values in Self-training Semi-supervised Method

This paper consists of a study in the field of semi-supervised learning and implements changes on the self-training algorithm in order to propose a variation in the rate of inclusion of new observations in the labeled dataset. In order to achieve this goal, three methods (FlexCon-G, FlexCone FlexCon-C) are proposed, which differ in the way that they perform the calculation of a new value for the minimum confidence rate to include new patterns. In order to evaluate the proposed methods, we performed experimentations with 20 datasets with diversified characteristics. Each of them was setup with a different percentage of initially labeled patterns. Each dataset was trained using the Naive Bayes, decision tree and ripper classifiers. Moreover, Friedmann statistical test was applied to provide a statistically significant analysis. The obtained results indicate that the three proposed methods perform better than a self-training method in most cases, pointing to the FlexCon-C method as the most efficient of them.
Provable Robustness of ReLU networks via Maximization of Linear Regions

It has been shown that neural network classifiers are not robust. This raises concerns about their usage in safety-critical systems. We propose in this paper a regularization scheme for ReLU networks which provably improves the robustness of the classifier by maximizing the linear regions of the classifier as well as the distance to the decision boundary. Using our regularization we can even find the minimal adversarial perturbation for a certain fraction of test points for large networks. In the experiments we show that our approach improves upon pure adversarial training both in terms of lower and upper bounds on the robustness and is comparable or better than the state of the art in terms of test error and robustness.
Learn Fast, Forget Slow: Safe Predictive Learning Control for Systems With Unknown and Changing Dynamics Performing Repetitive Tasks

We present a control method for improved repetitive path following for a ground vehicle that is geared toward long-term operation, where the operating conditions can change over time and are initially unknown. We use weighted Bayesian linear regression (wBLR) to model the unknown dynamics, and show how this simple model is more accurate in both its estimate of the mean behavior and model uncertainty than Gaussian process regression and generalizes to novel operating conditions with little or no tuning. In addition, wBLR allows us to use fast adaptation and long-term learning in one unified framework to adapt quickly to new operating conditions and learn repetitive model errors over time. This comes with the added benefit of lower computational cost, longer look-ahead, and easier optimization when the model is used in a stochastic model-predictive controller (MPC). In order to fully capitalize on the long prediction horizons that are possible with this new approach, we use Tube MPC to reduce the growth of predicted uncertainty. We demonstrate the effectiveness of our approach in the experiment on a 900-kg ground robot showing results over 3.0 km of driving with both physical and artificial changes to the robot's dynamics. All of our experiments are conducted using a stereo camera for localization.
Sustained Attention Driving Task Analysis based on Recurrent Residual Neural Network using EEG Data

this paper proposes applying recurrent residual network (RRN) for analyzing electroencephalogram (EEG) data captured during a simulated sustained attention driving task. We first address the suitableness of utilizing residual structure as well as adopting recurrent structure for EEG signal processing. Then based on these descriptions a recurrent residual network is tailored and depicted in detail. Thirdly we use an EEG dataset obtained from a sustained-attention experiment for our model justification. By applying the RRN model to the experimental data and via the competitive result achieved, we demonstrate the elegance of the proposed model. At last, we discuss the characteristics of the learned filters and their interpretations from EEG frequency band perspectives.
Self-Organizing Traffic Flow Prediction with an Optimized Deep Belief Network for Internet of Vehicles

To assist in the broadcasting of time-critical traffic information in an Internet of Vehicles (IoV) and vehicular sensor networks (VSN), fast network connectivity is needed. Accurate traffic information prediction can improve traffic congestion and operation efficiency, which helps to reduce commute times, noise and carbon emissions. In this study, we present a novel approach for predicting the traffic flow volume by using traffic data in self-organizing vehicular networks. The proposed method is based on using a probabilistic generative neural network techniques called deep belief network (DBN) that includes multiple layers of restricted Boltzmann machine (RBM) auto-encoders. Time series data generated from the roadside units (RSUs) for five highway links are used by a three layer DBN to extract and learn key input features for constructing a model to predict traffic flow. Back-propagation is utilized as a general learning algorithm for fine-tuning the weight parameters among the visible and hidden layers of RBMs. During the training process the firefly algorithm (FFA) is applied for optimizing the DBN topology and learning rate parameter. Monte Carlo simulations are used to assess the accuracy of the prediction model. The results show that the proposed model achieves superior performance accuracy for predicting traffic flow in comparison with other approaches applied in the literature. The proposed approach can help to solve the problem of traffic congestion, and provide guidance and advice for road users and traffic regulators.
Comparing Hypothetical and Realistic Privacy Valuations

To protect users' privacy, it is important to understand how they value personal information. Prior work identified how framing effects alter users' valuations and highlighted the difficulty in eliciting real valuations through user studies under hypothetical circumstances. However, our understanding of users' valuations remains limited to specific entities, information types, and levels of realism. We examined the effects of realism and purpose of use on users' valuations of their personal information. Specifically, we conducted an online study in which participants (N=434) were asked to assign monetary value to their personal information in the context of an information marketplace involving different receiving parties, while we experimentally manipulated the level of realism of the scenario and the timing of eliciting valuations. Among our findings is a nuanced understanding of valuation biases, including when they may not apply. For example, we find that, contrary to common belief, participants' valuations are not generally higher in hypothetical scenarios compared to realistic ones. Importantly, we find that while absolute valuations vary greatly between participants, the order in which users prioritize information types (i.e., users' relative valuations of different attributes) remains stable across the levels of realism we study. We discuss how our findings inform system design and future studies.
Evidence-based management of patients with vertigo, dizziness, and imbalance at an Australian metropolitan health service: an observational study of clinical practice

ABSTRACT Aim To determine whether patients presenting to the emergency department (ED) with possible benign paroxysmal positional vertigo (BPPV) are managed in accordance with best practice guidelines, and whether physiotherapists are involved in their care. Design Retrospective observational study. Participants Ninety-six consecutive patients presenting to one of three EDs with vertigo, dizziness or imbalance symptoms documented at triage. Individuals with a clear non-vestibular cause of symptoms were excluded. Outcome Measures Proportional adherence to clinical practice guidelines by medical and physiotherapy clinicians, primary diagnosis, incidence of falls, admission to hospital, and referral to a physiotherapy service. Results Adherence to clinical practice guidelines by both professions was low, with only 25 (26%, 95% CI: 18–36%) and 3 (14%, 95% CI: 4–36%) patients assessed by a medical clinician or physiotherapist, respectively, receiving the gold-standard Dix–Hallpike test. Sixty-four (67%) individuals were given a diagnosis of undifferentiated dizziness. Of the 26 (27%) patients with a primary BPPV diagnosis, only three (12%) were treated with a canalith-repositioning technique, and four (15%) reviewed by a physiotherapist. Conclusion Adherence to best-practice guidelines for the management of BPPV in individuals presenting to the ED is low, and physiotherapists are seldom involved in their management.
Point Cloud Object Recognition using 3D Convolutional Neural Networks

With the advent of RGB-D technology, there was remarkable progress in robotic tasks such as object recognition. Many approaches were developed to handle depth information, but they work mainly on 2.5D representations of the data. Moreover, the 3D-data handling approaches using Convolutional Neural Networks developed so far showed a gap between volumetric CNN and multi-view CNN. Therefore, the use of point clouds for object recognition has not been fully explored. In this work, we propose a Convolutional Neural Network model that extracts 3D features directly from RGB-D data, mixing volumetric and multi-view representations. The neural architecture is kept as simple as possible to assess the benefits of the 3D-data easily. We evaluate our approach with the publicly available Washington Dataset of real RGB-D data composed of 51 categories of household objects and obtained an improvement of around 10% in accuracy over the utilisation of 2D features. This result motivates further investigation when compared to some recently reported results tested on smaller datasets.
Confined Space Incident Reconstruction: The Future Depends on Understanding the Past

Confined Space Incident Reconstruction The Future Depends on Understanding the Past By Neil McManus and Assed N. Haddad The written record is the primary source for acquiring information about confined space incidents. These records contain supposedly factual information, including location, date, time, victim’s age and gender, and a narrative summary. The narrative summary can provide additional specific and interpretive information. Interpretive information requires the application of skill and broad-spectrum knowledge about the circumstances of work. Thus, such information necessarily receives the lowest level of confidence. With care in the manner of performing this inquiry, this information can provide the basis for identifying trends in these events. Also, working on statistical and stochastic data is an important means of transforming data into information, information into knowledge and knowledge into action.
The Jovian Atmospheric Window at 2 . 7 J-Lm : A Search for H 2 S

We have observed the atmospheric transmission window at 2.7 ~m in Jupiter's atmosphere at a spectral resolution of 0.1 cm-l from the Kuiper Airborne Observatory. From our analysis of the CH4 abundance (~ 80 m-am) and the H20 abundance « 0.0125 cm-am) we determined that the penetration depth of solar flux at 2.7 ~m is near the base of the NH3 cloud layer. Our upper limit to H20 at 2.7 ~m and other recent results suggest that photolytic reactions in Jupiter's lower troposphere may not be as significant as was previously thought. Our search for H2S in Jupiter's atmosphere yielded an upper limit of ~ 0.1 cm-am. The corresponding limit to the elemental abundance ratio [S]/[H] was ~ 1.7xlO-8, about 10-3 times the solar value. Upon modeling the abundance and distribution of H2S in Jupiter's atmosphere we concluded that, contrary to expectations, sulfur-bearin9 chromophores are not present in significant amounts in Jupiter's visible clouds. Rather, it appears that most of Jupiter's sulfur is locked up as NH4SH in a lower cloud layer. Alternatively. the global abundance of sulfur in Jupiter may be significantly depleted.
Ulmus laevis in the Iberian Peninsula: a review of its ecology and conservation

Abstract: European white elm (Ulmus laevis Pallas) populations are scarce, small and fragmented in the Iberian Peninsula. Due to these characteristics the indigenous status of the species in the region has been questioned, whilst the species’ role in Iberian riparian forest ecology has been neglected. Herein we review past studies regarding this species’ distribution and ecology in the Iberian Peninsula, with special emphasis on the establishment of conservation priorities. We first present a collection of palaeogeographic, historic and genetic data suggesting that the Iberian Peninsula was a glacial refuge for U. laevis. Secondly, we analyse U. laevis distribution in relation to soil physico- chemical properties and water availability in Spain. Following this, we focus on the reproductive biology of the species, and investigate the effect of masting and empty seed production on predation and regeneration establishment. Finally, based on this knowledge, we propose conservation policies for U. laevis in the Iberian Peninsula.
Botryosphaeriaceae from Eucalyptus plantations and adjacent plants in China

The Botryosphaeriaceae is a species-rich family that includes pathogens of a wide variety of plants, including species of Eucalyptus. Recently, during disease surveys in China, diseased samples associated with species of Botryosphaeriaceae were collected from plantation Eucalyptus and other plants, including Cunninghamina lanceolata, Dimocarpus longan, Melastoma sanguineum and Phoenix hanceana, which were growing adjacent to Eucalyptus. In addition, few samples from Araucaria cunninghamii and Cedrus deodara in two gardens were also included in this study. Disease symptoms observed mainly included stem canker, shoot and twig blight. In this study, 105 isolates of Botryosphaeriaceae were collected from six provinces, of which 81 isolates were from Eucalyptus trees. These isolates were identified based on comparisons of the DNA sequences of the internal transcribed spacer regions and intervening 5.8S nrRNA gene (ITS), and partial translation elongation factor 1-alpha (tef1), β-tubulin (tub), DNA-directed RNA polymerase II subunit (rpb2) and calmodulin (cmdA) genes, the nuclear ribosomal large subunit (LSU) and the nuclear ribosomal small subunit (SSU), and combined with their morphological characteristics. Results showed that these isolates represent 12 species of Botryosphaeriaceae, including Botryosphaeria fusispora, Cophinforma atrovirens, Lasiodiplodia brasiliense, L. pseudotheobromae, L. theobromae and Neofusicoccum parvum, and six previously undescribed species of Botryosphaeria and Neofusicoccum, namely B. pseudoramosa sp. nov., B. qingyuanensis sp. nov., B. wangensis sp. nov., N. hongkongense sp. nov., N. microconidium sp. nov. and N. sinoeucalypti sp. nov. Aside from B. wangensis, C. atrovirens and N. hongkongense, the other nine Botryosphaeriaceae species were isolated from Eucalyptus trees in South China. Botryosphaeria fusispora (26 % of the isolates from Eucalyptus) is the dominant species, followed by L. pseudotheobromae (23 % of the isolates from Eucalyptus). In addition to species found on Eucalyptus trees, we also found B. pseudoramosa on M. sanguineum; B. wangensis on C. deodara; C. atrovirens on D. longan; L. theobromae on C. lanceolata, D. longan and P. hanceana; and N. hongkongense on A. cunninghamii. Pathogenicity tests showed that the 12 species of Botryosphaeriaceae are pathogenic to three Eucalyptus clones and that Lasiodiplodia species are the most aggressive. The results of our study suggest that many more species of the Botryosphaeriaceae remain to be discovered in China. This study also provides confirmation for the wide host range of Botryosphaeriaceae species on different plants.
Beam on beam control: beyond the particle approximation

The all-optical control of the trajectory of a nonlinear optical beam propagating in a nematic liquid crystal cell is studied using a combination of modulation theory and full numerical solutions of the governing nematic equations. In detail, the output position of a signal beam is controlled via its interaction with a second, co-propagating control beam. The input positions of both the signal and control beams are fixed, with the output position of the signal beam determined by the input angle of the control beam. A simple modulation theory based on treating the optical beams as mechanical particles in a potential well is found to give only adequate agreement with numerical solutions. However, extending this modulation theory to include the detailed profiles of the beams, so that the beams are treated as rigid bodies moving in a potential well, leads to simple, extended equations which determine the input angle of the control beam required for a given output position of the signal beam. The predictions of this extended particle theory, or rigid body theory, are compared with full numerical solutions of the nematic equations and excellent agreement is found.
Protocols for Reliable Field Olfactometry Odor Evaluations

Specific gasses (odorants) are often poorly correlated with odors, which require human perception. Thus, olfactometry is used to quantify odors, which commonly contain a complex mixture of offensive compounds. Laboratory-based dynamic olfactometry is expensive and time-consuming, and it is accompanied with sample container/ preservation issues. Field olfactometry provides real-time measurements at lower detection levels, but is influenced by environmental factors. This study explores the use of field olfactometry for quantifying dilutions-to-threshold (D/T) of environmental malodors. Nasal Ranger® Field Olfactometer (NRO) instruments were used to collect 3096 individual D/T observations at livestock facilities in central Pennsylvania. Twelve to 16 observations were collected at each sampling station using multiple assessors, capturing four concurrent readings each. The multiple-assessor repeat observation (MARO) technique revealed that the reproducibility of D/T observations (across assessors) was more precise than replicate observations by individual assessors (repeatability). Observations were significantly (P<0.0001) influenced by odor source distance, wind direction, barometric pressure, and wind velocity. Power analysis showed that the 16-sample MARO using NRO method achieved 95% odor panel confidence with a power value of 0.90 at lower-D/T (2,4) and upper-D/T (30, 60) levels. Mid-range D/T settings of 7 and 15 exhibited the greatest odor panelist variability. This study shows that MARO field olfactometry can reliably estimate odor D/T differences, even with weather variations. It is noteworthy, however, that the greatest numbers of observations (n= 85-91) are needed at D/T levels of 7 to 15 (to achieve 95% confidence), precisely the range used to define nuisance odor conditions in some states.
Clinical presentation and management of neonatal abstinence syndrome: an update

(unported, v3.0) License. The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. Permissions beyond the scope of the License are administered by Dove Medical Press Limited. Information on how to request permission may be found at: http://www.dovepress. com/permissions.php Research and Reports in Neonatology 2014:4 75–86 Research and Reports in Neonatology Dovepress
Clinical and biological aspects of aggressive B-cell non-Hodgkin lymphoma in adolescents and young adults

License. The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. Permissions beyond the scope of the License are administered by Dove Medical Press Limited. Information on how to request permission may be found at: http://www.dovepress. com/permissions.php Clinical Oncology in Adolescents and Young Adults 2015:5 115–126 Clinical Oncology in Adolescents and Young Adults Dovepress