Special Section Guest Editorial: Image/Video Quality and System Performance

Rapid developments in display technologies, digital printing, imaging sensors, image processing and image transmission are providing new possibilities for creating and conveying visual content. In an age in which images and video are ubiquitous and where mobile, satellite, and three-dimensional (3-D) imaging have become ordinary experiences, quantification of the performance of modern imaging systems requires appropriate approaches. At the end of the imaging chain, a human observer must decide whether images and video are of a satisfactory visual quality. Hence the measurement and modeling of perceived image quality is of crucial importance, not only in visual arts and commercial applications but also in scientific and entertainment environments. Advances in our understanding of the human visual system offer new possibilities for creating visually superior imaging systems and promise more accurate modeling of image quality. As a result, there is a profusion of new research on imaging performance and perceived quality

Comparative performance between human and automated face recognition systems, using CCTV imagery, different compression levels and scene parameters

In this investigation we identify relationships between human and automated face recognition systems with respect to compression. Further, we identify the most influential scene parameters on the performance of each recognition system. The work includes testing of the systems with compressed Closed-Circuit Television (CCTV) footage, consisting of quantified scene (footage) parameters. Parameters describe the content of scenes concerning camera to subject distance, facial angle, scene brightness, and spatio-temporal busyness. These parameters have been previously shown to affect the human visibility of useful facial information, but not much work has been carried out to assess the influence they have on automated recognition systems. In this investigation, the methodology previously employed in the human investigation is adopted, to assess performance of three different automated systems: Principal Component Analysis, Linear Discriminant Analysis, and Kernel Fisher Analysis. Results show that the automated systems are more tolerant to compression than humans. In automated systems, mixed brightness scenes were the most affected and low brightness scenes were the least affected by compression. In contrast for humans, low brightness scenes were the most affected and medium brightness scenes the least affected. Findings have the potential to broaden the methods used for testing imaging systems for security applications

SYNERGETIC USE OF SENTINEL-1 AND SENTINEL-2 DATA FOR EXTRACTION OF BUILT-UP AREA IN A ROCKY DESERT OASIS, EXAMPLE FOR DRAA TAFILALT, SOUTH-EAST OF MOROCCO

Synthetic Aperture Radar (SAR) is an active remote sensing technique capable of providing high-resolution imagery independent from daytime and to great extent unimpaired by weather conditions. Unlike the passive remote sensing active radars receive its' own reflected signal. Features of received signal make able to obtain additional information about surface objects and covers. Because of signal, double reflecting upon vertical surfaces like walls, it become common to study urbanized areas using SAR data. Because of mostly similar spectral characteristic of the typical buildings' roofs and sandy soils, that are distinguishing for Morocco, classification using visible and NIR multispectral remote sensing data is complicated. Thus, SAR data processing technique is rather useful while application to deserted area studying and urbanized areas identification

A case study in identifying acceptable bitrates for human face recognition tasks

Face recognition from images or video footage requires a certain level of recorded image quality. This paper derives acceptable bitrates (relating to levels of compression and consequently quality) of footage with human faces, using an industry implementation of the standard H.264/MPEG-4 AVC and the Closed-Circuit Television (CCTV) recording systems on London buses. The London buses application is utilized as a case study for setting up a methodology and implementing suitable data analysis for face recognition from recorded footage, which has been degraded by compression. The majority of CCTV recorders on buses use a proprietary format based on the H.264/MPEG-4 AVC video coding standard, exploiting both spatial and temporal redundancy. Low bitrates are favored in the CCTV industry for saving storage and transmission bandwidth, but they compromise the image usefulness of the recorded imagery. In this context, usefulness is determined by the presence of enough facial information remaining in the compressed image to allow a specialist to recognize a person. The investigation includes four steps: (1) Development of a video dataset representative of typical CCTV bus scenarios. (2) Selection and grouping of video scenes based on local (facial) and global (entire scene) content properties. (3) Psychophysical investigations to identify the key scenes, which are most affected by compression, using an industry implementation of H.264/MPEG-4 AVC. (4) Testing of CCTV recording systems on buses with the key scenes and further psychophysical investigations. The results showed a dependency upon scene content properties. Very dark scenes and scenes with high levels of spatial–temporal busyness were the most challenging to compress, requiring higher bitrates to maintain useful information

Therapeutic and immunomodulatory activities of short-course treatment of murine visceral leishmaniasis with KALSOME™10, a new liposomal amphotericin B

Visceral leishmaniasis (VL), a potentially fatal disease, is most prevalent in the Indian subcontinent, East Africa and South America. Since the conventional antileishmanial drugs have many limitations we evaluated a new ergosterol rich liposomal amphotericin B formulation, KALSOME™10 for its leishmanicidal efficacy, tolerability and immunomodulatory activity. Normal healthy mice were treated with 3.5 mg/kg single and 7.5 mg/kg single and double doses ofKALSOME™10. Liver and kidney function tests were performed fourteen days after treatment. Next, normal mice were infected with Leishmania donovani amastigotes. Two months post infection they were treated with the above mentioned doses of KALSOME™10 and sacrificed one month after treatment for estimation of parasite burden in the liver and spleen by Limiting Dilution Assay. Leishmanial antigen stimulated splenocyte culture supernatants were collected for cytokine detection through ELISA. Flow cytometric studies were performed on normal animals treated with KALSOME™10, Amphotericin B (AmB) and AmBiosome to compare their immunomodulatory activities. The drug was found to induce no hepato- or nephrotoxicities at the studied doses. Moreover, at all doses, it led to significant reduction in parasite burden in two month infected BALB/c mice, with 7.5 mg/kg double dose resulting in almost complete clearance of parasites from both liver and spleen. Interestingly, the drug at 7.5 mg/kg double dose could almost completely inhibit the secretion of disease promoting cytokines, IL-10 and TGFβ, and significantly elevate the levels of IFNγ and IL-12, cytokines required for control of the disease. Mice treated with KALSOME™10 showed elevated levels of IFNγ and suppressed IL-10 secretion from both CD4+ and CD8+ subsets of T cells, as well as from culture supernatants of splenocytes, compared to that of normal, AmB and AmBisome treated animal Treatment of infected mice with 7.5 mg/kg double dose of KALSOME™10 was safe and effective in clearing the parasites from the sites of infection. The drug maintains the inherent immunomodulatory activities of AmB by effectively suppressing disease promoting cytokines IL-10 and TGFβ, thereby boosting IL-12 and IFNγ levels. This emphasizes KALSOME™10 as a promising drug alternative for lifelong protection from VL

ASSESSING VEGETATION STRUCTURAL CHANGES IN OASIS AGRO-ECOSYSTEMS USING SENTINEL-2 IMAGE TIME SERIES: CASE STUDY FOR DRÂA-TAFILALET REGION MOROCCO

Nowadays, Moroccan oasis agro-ecosystems are under intense effect of natural and anthropogenic factors. Therefore, this essay proposes to use Leaf Area Index (LAI) to assess the consequences of the oases long-term biodegradation. The index was used as a widely-applied parameter of vegetation structure and an important indicator of plant growth and health. Therefore, a new optical multispectral Sentinel-2 data were used to build a long term LAI time series for the area of the Erfoud and Rissani oases, Errachidia province in Drâa-Tafilalet region in Morocco. Nine images of LAI spatial distribution over the study area were obtained by means of SNAP Biophysical Processor over the period since July 2015 till May 2018. Time series analysis of the resultedmaps has revealed a stable trend towards the average LAI decreasing and vegetation structure simplification as a consequence

Using random forest and decision tree models for a new vehicle prediction approach in computational toxicology

yesDrug vehicles are chemical carriers that provide beneficial aid to the drugs they bear. Taking advantage of their favourable properties can potentially allow the safer use of drugs that are considered highly toxic. A means for vehicle selection without experimental trial would therefore be of benefit in saving time and money for the industry. Although machine learning is increasingly used in predictive toxicology, to our knowledge there is no reported work in using machine learning techniques to model drug-vehicle relationships for vehicle selection to minimise toxicity. In this paper we demonstrate the use of data mining and machine learning techniques to process, extract and build models based on classifiers (decision trees and random forests) that allow us to predict which vehicle would be most suited to reduce a drug’s toxicity. Using data acquired from the National Institute of Health’s (NIH) Developmental Therapeutics Program (DTP) we propose a methodology using an area under a curve (AUC) approach that allows us to distinguish which vehicle provides the best toxicity profile for a drug and build classification models based on this knowledge. Our results show that we can achieve prediction accuracies of 80 % using random forest models whilst the decision tree models produce accuracies in the 70 % region. We consider our methodology widely applicable within the scientific domain and beyond for comprehensively building classification models for the comparison of functional relationships between two variables

Antifungal activity of amphotericin B conjugated to nanosized magnetite in the treatment of paracoccidioidomycosis

This study reports on in vitro and in vivo tests that sought to assess the antifungal activity of a newly developed magnetic carrier system comprising amphotericin B loaded onto the surface of pre-coated (with a double-layer of lauric acid) magnetite nanoparticles. The in vitro tests compared two drugs; i.e., this newly developed form and free amphotericin B. We found that this nanocomplex exhibited antifungal activity without cytotoxicity to human urinary cells and with low cytotoxicity to peritoneal macrophages. We also evaluated the efficacy of the nanocomplex in experimental paracoccidioidomycosis. BALB/c mice were intratracheally infected with Paracoccidioides brasiliensis and treated with the compound for 30 or 60 days beginning the day after infection. The newly developed amphotericin B coupled with magnetic nanoparticles was effective against experimental paracoccidioidomycosis, and it did not induce clinical, biochemical or histopathological alterations. The nanocomplex also did not induce genotoxic effects in bone marrow cells. Therefore, it is reasonable to believe that amphotericin B coupled to magnetic nanoparticles and stabilized with bilayer lauric acid is a promising nanotool for the treatment of the experimental paracoccidioidomycosis because it exhibited antifungal activity that was similar to that of free amphotericin B, did not induce adverse effects in therapeutic doses and allowed for a reduction in the number of applications

TBK1: a new player in ALS linking autophagy and neuroinflammation.

Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disorder affecting motor neurons, resulting in progressive muscle weakness and death by respiratory failure. Protein and RNA aggregates are a hallmark of ALS pathology and are thought to contribute to ALS by impairing axonal transport. Mutations in several genes known to contribute to ALS result in deposition of their protein products as aggregates; these include TARDBP, C9ORF72, and SOD1. In motor neurons, this can disrupt transport of mitochondria to areas of metabolic need, resulting in damage to cells and can elicit a neuroinflammatory response leading to further neuronal damage. Recently, eight independent human genetics studies have uncovered a link between TANK-binding kinase 1 (TBK1) mutations and ALS. TBK1 belongs to the IKK-kinase family of kinases that are involved in innate immunity signaling pathways; specifically, TBK1 is an inducer of type-1 interferons. TBK1 also has a major role in autophagy and mitophagy, chiefly the phosphorylation of autophagy adaptors. Several other ALS genes are also involved in autophagy, including p62 and OPTN. TBK1 is required for efficient cargo recruitment in autophagy; mutations in TBK1 may result in impaired autophagy and contribute to the accumulation of protein aggregates and ALS pathology. In this review, we focus on the role of TBK1 in autophagy and the contributions of this process to the pathophysiology of ALS

Deregulated expression of TANK in glioblastomas triggers pro-tumorigenic ERK1/2 and AKT signaling pathways

Signal transmission by the noncanonical IkappaB kinases (IKKs), TANK-binding kinase 1 (TBK1) and IKKɛ, requires interaction with adapter proteins such as TRAF associated NF-κB activator (TANK). Although increased expression or dysregulation of both kinases has been described for a variety of human cancers, this study shows that deregulated expression of the TANK protein is frequently occurring in glioblastomas (GBMs). The functional relevance of TANK was analyzed in a panel of GBM-derived cell lines and revealed that knockdown of TANK arrests cells in the S-phase and prohibits tumor cell migration. Deregulated TANK expression affects several signaling pathways controlling cell proliferation and the inflammatory response. Interference with stoichiometrically assembled signaling complexes by overexpression or silencing of TANK prevented constitutive interferon-regulatory factor 3 (IRF3) phosphorylation. Knockdown of TANK frequently prevents constitutive activation of extracellular signal-regulated kinases 1 and 2 (ERK1/2). TANK-mediated ERK1/2 activation is independent from the canonical MAP kinase or ERK kinase (MEK) 1/2-mediated pathway and utilizes an alternative pathway that uses a TBK1/IKKɛ/Akt signaling axis, thus identifying a novel pathway suitable to block constitutive ERK1/2 activity.Peer reviewe