A Study on Edible Polymer Films for Food Packaging Industry: Current Scenario and Advancements

Over the past two decades, food packaging and packaging industry have paid close attention to create biodegradable and edible polymer films and coatings. In a broad way, edible polymers emerged as a new class of materials that garnered significant properties due to their advantages over synthetic petroleum-based films. When compared to conventional packaging materials, edible polymer films can fundamentally simplify products, improving their potential to be recycled. This work aims to give readers a thorough introduction to edible polymer films, by discussing present research trends, classification, functionality and composition, fabrication, and characterization. The work also emphasizes the advantages and disadvantages of edible polymer films based on meat, poultry, dairy products, fruits, nuts, and vegetables

An efficient image retrieval scheme for colour enhancement of embedded and distributed surveillance images

From the past few years, the size of the data grows exponentially with respect to volume, velocity, and dimensionality due to wide spread use of embedded and distributed surveillance cameras for security reasons. In this paper, we have proposed an integrated approach for biometric-based image retrieval and processing which addresses the two issues. The first issue is related to the poor visibility of the images produced by the embedded and distributed surveillance cameras, and the second issue is concerned with the effective image retrieval based on the user query. This paper addresses the first issue by proposing an integrated image enhancement approach based on contrast enhancement and colour balancing methods. The contrast enhancement method is used to improve the contrast, while the colour balancing method helps to achieve a balanced colour. Importantly, in the colour balancing method, a new process for colour cast adjustment is introduced which relies on statistical calculation. It adjusts the colour cast and maintains the luminance of the image. The integrated image enhancement approach is applied to the enhancement of low quality images produced by surveillance cameras. The paper addresses the second issue relating to image retrieval by proposing a content-based image retrieval approach. The approach is based on the three features extraction methods namely colour, texture and shape. Colour histogram is used to extract the colour features of an image. Gabor filter is used to extract the texture features and the moment invariant is used to extract the shape features of an image. The use of these three algorithms ensures that the proposed image retrieval approach produces results which are highly relevant to the content of an image query, by taking into account the three distinct features of the image and the similarity metrics based on Euclidean measure. In order to retrieve the most relevant images, the proposed approach also employs a set of fuzzy heuristics to improve the quality of the results further. The result

Predicting seizure outcome of vagus nerve stimulation using MEG-based network topology

Vagus nerve stimulation (VNS) is a low-risk surgical option for patients with drug resistant epilepsy, although it is impossible to predict which patients may respond to VNS treatment. Resting-state magnetoencephalography (rs-MEG) connectivity analysis has been increasingly utilized to investigate the impact of epilepsy on brain networks and identify alteration of these networks after different treatments; however, there is no study to date utilizing this modality to predict the efficacy of VNS treatment. We investigated whether the rs-MEG network topology before VNS implantation can be used to predict efficacy of VNS treatment. Twenty-three patients with epilepsy who had MEG before VNS implantation were included in this study. We also included 89 healthy control subjects from the Human Connectome Project. Using the phase-locking value in the theta, alpha, and beta frequency bands as a measure of rs-MEG functional connectivity, we calculated three global graph measures: modularity, transitivity, and characteristic path length (CPL). Our results revealed that the rs-MEG graph measures were significantly heritable and had an overall good test-retest reliability, and thus these measures may be used as potential biomarkers of the network topology. We found that the modularity and transitivity in VNS responders were significantly larger and smaller, respectively, than those observed in VNS non-responders. We also observed that the modularity and transitivity in three frequency bands and CPL in delta and beta bands were significantly different in controls than those found in responders or non-responders, although the values of the graph measures in controls were closer to those of responders than non-responders. We used the modularity and transitivity as input features of a naïve Bayes classifier, and achieved an accuracy of 87% in classification of non-responders, responders, and controls. The results of this study revealed that MEG-based graph measures are reliable biomarkers, and that these measures may be used to predict seizure outcome of VNS treatment Keywords: Vagus nerve stimulation (VNS), Seizure outcome, VNS efficacy, Magnetoencephalography (MEG), Functional connectivity, Phase-locking value (PLV), Graph measures, Human connectome project (HCP

Identifying seizure onset zone from electrocorticographic recordings: A machine learning approach based on phase locking value

Purpose Using a novel technique based on phase locking value (PLV), we investigated the potential for features extracted from electrocorticographic (ECoG) recordings to serve as biomarkers to identify the seizure onset zone (SOZ). Methods We computed the PLV between the phase of the amplitude of high gamma activity (80–150 Hz) and the phase of lower frequency rhythms (4–30 Hz) from ECoG recordings obtained from 10 patients with epilepsy (21 seizures). We extracted five features from the PLV and used a machine learning approach based on logistic regression to build a model that classifies electrodes as SOZ or non-SOZ. Results More than 96% of electrodes identified as the SOZ by our algorithm were within the resected area in six seizure-free patients. In four non-seizure-free patients, more than 31% of the identified SOZ electrodes by our algorithm were outside the resected area. In addition, we observed that the seizure outcome in non-seizure-free patients correlated with the number of non-resected SOZ electrodes identified by our algorithm. Conclusion This machine learning approach, based on features extracted from the PLV, effectively identified electrodes within the SOZ. The approach has the potential to assist clinicians in surgical decision-making when pre-surgical intracranial recordings are utilized

Electroencephalographic patterns during sleep in children with chromosome 15q11.2-13.1 duplications (Dup15q).

Our objective was to define the EEG features during sleep of children with neurodevelopmental disorders due to copy number gains of 15q11-q13 (Dup15q). We retrospectively reviewed continuous EEG recordings of 42 children with Dup15q (mean age: eight years, 32 with idic15), and data collected included background activity, interictal epileptiform discharges, sleep organization, and ictal activity. Three patterns were recognized: Pattern 1: Alpha–delta sleep was noted in 14 children (33%), not associated with any clinical changes. Pattern 2: Electrical status epilepticus in sleep was noted in 15 children (35%), all diagnosed with treatmentresistant epilepsy. Thirteen of the 15 children had clinical seizures. Pattern 3: Frequent bursts of high amplitude bifrontal predominant, paroxysmal fast activity (12–15 Hz) during non-REM sleep was noted in 15 children (35%). All 15 children had treatment-resistant epilepsy. This is the first report of electroencephalographic patterns during sleep of children with Dup15q reporting alpha-delta rhythms, CSWS, and high amplitude fast frequencies. Alpha-delta rhythms are described in children with dysautonomia and/or mood disorders and CSWS in children with developmental regression. The significance of these findings in cognitive function and epilepsy for the children in our cohort needs to be determined with follow-up studies

West syndrome: a comprehensive review

Since its first clinical description (on his son) by William James West (1793-1848) in 1841, and the definition of the classical triad of (1) infantile spasms; (2) hypsarrhythmia, and (3) developmental arrest or regression as "West syndrome", new and relevant advances have been recorded in this uncommon disorder. New approaches include terminology of clinical spasms (e.g., infantile (IS) vs. epileptic spasms (ES)), variety of clinical and electroencephalographic (EEG) features (e.g., typical ictal phenomena without EEG abnormalities), burden of developmental delay, spectrum of associated genetic abnormalities, pathogenesis, treatment options, and related outcome and prognosis. Aside the classical manifestations, IS or ES may present with atypical electroclinical phenotypes (e.g., subtle spasms; modified hypsarrhythmia) and may have their onset outside infancy. An increasing number of genes, proteins, and signaling pathways play crucial roles in the pathogenesis. This condition is currently regarded as a spectrum of disorders: the so-called infantile spasm syndrome (ISs), in association with other causal factors, including structural, infectious, metabolic, syndromic, and immunologic events, all acting on a genetic predisposing background. Hormonal therapy and ketogenic diet are widely used also in combination with (classical and recent) pharmacological drugs. Biologically targeted and gene therapies are increasingly studied. The present narrative review searched in seven electronic databases (primary MeSH terms/keywords included West syndrome, infantile spasms and infantile spasms syndrome and were coupled to 25 secondary clinical, EEG, therapeutic, outcomes, and associated conditions terms) including MEDLINE, Embase, Cochrane Central, Web of Sciences, Pubmed, Scopus, and OMIM to highlight the past knowledge and more recent advances