Search results for " Mach"
showing 10 items of 1388 documents
A Novel Border Identification Algorithm Based on an “Anti-Bayesian” Paradigm
2013
Published version of a chapter in the book: Computer Analysis of Images and Patterns. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-40261-6_23 Border Identification (BI) algorithms, a subset of Prototype Reduction Schemes (PRS) aim to reduce the number of training vectors so that the reduced set (the border set) contains only those patterns which lie near the border of the classes, and have sufficient information to perform a meaningful classification. However, one can see that the true border patterns (“near” border) are not able to perform the task independently as they are not able to always distinguish the testing samples. Thus, researchers have worked on thi…
On Detection of Network-Based Co-residence Verification Attacks in SDN-Driven Clouds
2017
Modern cloud environments allow users to consume computational and storage resources in the form of virtual machines. Even though machines running on the same cloud server are logically isolated from each other, a malicious customer can create various side channels to obtain sensitive information from co-located machines. In this study, we concentrate on timely detection of intentional co-residence attempts in cloud environments that utilize software-defined networking. SDN enables global visibility of the network state which allows the cloud provider to monitor and extract necessary information from each flow in every virtual network in online mode. We analyze the extracted statistics on d…
Kick Detection and Influx Size Estimation during Offshore Drilling Operations using Deep Learning
2019
An uncontrolled or unobserved influx or kick during drilling has the potential to induce a well blowout, one of the most harmful incidences during drilling both in regards to economic and environmental cost. Since kicks during drilling are serious risks, it is important to improve kick and loss detection performance and capabilities and to develop automatic flux detection methodology. There are clear patterns during a influx incident. However, due to complex processes and sparse instrumentation it is difficult to predict the behaviour of kicks or losses based on sensor data combined with physical models alone. Emerging technologies within Deep Learning are however quite adapt at picking up …
Effect of various dentin disinfection protocols on the bond strength of resin modified glass ionomer restorative material.
2017
Background Disinfection of dentin surface prior to any restorative therapy is important for the longevity of the treatment rendered. However, these dentin disinfection methods should itself not interfere with the adhesion of the restorative material. Therefore the aim of this study was to determine the effect of various dentin disinfection protocols on the shear bond strength (SBS) of resin modified glass ionomer cement (RMGIC). Material and methods The occlusal surface of 40 extracted premolars were trimmed to obtain a flat dentinal surface and was randomly divided into four groups. CTRL was the control group; NaOCl was 1% sodium hypochlorite disinfection group; CHX was 2% chlorhexidine di…
Mutant p53 induces Golgi tubulo-vesiculation driving a prometastatic secretome
2020
TP53 missense mutations leading to the expression of mutant p53 oncoproteins are frequent driver events during tumorigenesis. p53 mutants promote tumor growth, metastasis and chemoresistance by affecting fundamental cellular pathways and functions. Here, we demonstrate that p53 mutants modify structure and function of the Golgi apparatus, culminating in the increased release of a pro-malignant secretome by tumor cells and primary fibroblasts from patients with Li-Fraumeni cancer predisposition syndrome. Mechanistically, interacting with the hypoxia responsive factor HIF1α, mutant p53 induces the expression of miR-30d, which in turn causes tubulo-vesiculation of the Golgi apparatus, leading …
A Pan-Cancer Approach to Predict Responsiveness to Immune Checkpoint Inhibitors by Machine Learning
2019
Immunotherapy by using immune checkpoint inhibitors (ICI) has dramatically improved the treatment options in various cancers, increasing survival rates for treated patients. Nevertheless, there are heterogeneous response rates to ICI among different cancer types, and even in the context of patients affected by a specific cancer. Thus, it becomes crucial to identify factors that predict the response to immunotherapeutic approaches. A comprehensive investigation of the mutational and immunological aspects of the tumor can be useful to obtain a robust prediction. By performing a pan-cancer analysis on gene expression data from the Cancer Genome Atlas (TCGA, 8055 cases and 29 cancer types), we …
Mass Spectrometry Imaging Differentiates Chromophobe Renal Cell Carcinoma and Renal Oncocytoma with High Accuracy
2020
Background: While subtyping of the majority of malignant chromophobe renal cell carcinoma (cRCC) and benign renal oncocytoma (rO) is possible on morphology alone, additional histochemical, immunohistochemical or molecular investigations are required in a subset of cases. As currently used histochemical and immunohistological stains as well as genetic aberrations show considerable overlap in both tumors, additional techniques are required for differential diagnostics. Mass spectrometry imaging (MSI) combining the detection of multiple peptides with information about their localization in tissue may be a suitable technology to overcome this diagnostic challenge. Patients and Methods: Formalin…
The Active Inference Approach to Ecological Perception: General Information Dynamics for Natural and Artificial Embodied Cognition
2018
The emerging neurocomputational vision of humans as embodied, ecologically embedded, social agents – who shape and are shaped by their environment – offers a golden opportunity to revisit and revise ideas about the physical and information-theoretic underpinnings of life, mind, and consciousness itself. In particular, the active inference framework (AIF) makes it possible to bridge connections from computational neuroscience and robotics/AI to ecological psychology and phenomenology, revealing common underpinnings and overcoming key limitations. AIF opposes the mechanistic to the reductive, while staying fully grounded in a naturalistic and information theoretic foundation, using the princi…
In Situ Representations and Access Consciousness in Neural Blackboard or Workspace Architectures
2018
Phenomenal theories of consciousness assert that consciousness is based on specific neural correlates in the brain, which can be separated from all cognitive functions we can perform. If so, the search for robot consciousness seems to be doomed. By contrast, theories of functional or access consciousness assert that consciousness can be studied only with forms of cognitive access, given by cognitive processes. Consequently, consciousness and cognitive access cannot be fully dissociated. Here, the global features of cognitive access of consciousness are discussed based on neural blackboard or (global) workspace architectures, combined with content addressable or "in situ" representations as …
Anxiolytic effects of muscarinic acetylcholine receptors agonist oxotremorine in chronically stressed rats and related changes in BDNF and FGF2 level…
2017
Rationale: In depressive disorders, one of the mechanisms proposed for antidepressant drugs is the enhancement of synaptic plasticity in the hippocampus and cerebral cortex. Previously, we showed that the muscarinic acetylcholine receptor (mAChR) agonist oxotremorine (Oxo) increases neuronal plasticity in hippocampal neurons via FGFR1 transactivation. Objectives: Here, we aimed to explore (a) whether Oxo exerts anxiolytic effect in the rat model of anxiety-depression-like behavior induced by chronic restraint stress (CRS), and (b) if the anxiolytic effect of Oxo is associated with the modulation of neurotrophic factors, brain-derived neurotrophic factor (BDNF) and fibroblast growth factor-2…