The Status of Material Resources for Effective Teaching of Physics in Secondary Schools in Akwa Ibom State of Nigeria

The study investigated the status of material resources for the teaching andlearning of physics in Akwa Ibom State Secondary Schools. It adopted survey design. A sample size of 1400 SS3 Physics students took part in theinvestigation. Mean was used in answering the three research questionsraised to guide the investigation. Findings revealed that some resourcematerials are available and adequate for the teaching and learning ofphysics. The study showed a low frequency of use of the available resourcematerials. Recommendation made was that adequate provision of resourcematerials should be made by state government to schools for meaningfulteaching and learning of physics. Physics teachers should make use ofmaterial resources during lessons

Engineering Biofouling Resistant Materials Through the Systematic Adaptation of Surface Morphology

Abstract With increasing numbers of antimicrobial‐resistant (AMR) bacteria strains, it becomes essential that new and effective routes to minimizing bacterial infection rates are produced. Superhydrophobic materials show to be effective in reducing the attachment of bacteria due to their unique wetting properties which can minimize the points at which bacteria can initially adhere. Here, the impact of surface design on the anti‐biofouling capabilities of superhydrophobic pillared arrays prepared via photolithography is investigated. By systematically varying pillar spacing, insight is gained into the complex nature of superhydrophobic fouling as well as allowing for optimization of the antifouling performance. The optimal material within is achieved at a pillar spacing of 87.5 µm, which shows over a 3‐log (and gt; 99.9%) reduction in bacterial attachment

Activity of a nitric oxide-generating wound treatment system against wound pathogen biofilms

This work was supported by Edixomed Ltd

Non-Negative Local Sparse Coding for Subspace Clustering

Subspace sparse coding (SSC) algorithms have proven to be beneficial to clustering problems. They provide an alternative data representation in which the underlying structure of the clusters can be better captured. However, most of the research in this area is mainly focused on enhancing the sparse coding part of the problem. In contrast, we introduce a novel objective term in our proposed SSC framework which focuses on the separability of data points in the coding space. We also provide mathematical insights into how this local-separability term improves the clustering result of the SSC framework. Our proposed non-linear local SSC algorithm (NLSSC) also benefits from the efficient choice of its sparsity terms and constraints. The NLSSC algorithm is also formulated in the kernel-based framework (NLKSSC) which can represent the nonlinear structure of data. In addition, we address the possibility of having redundancies in sparse coding results and its negative effect on graph-based clustering problems. We introduce the link-restore post-processing step to improve the representation graph of non-negative SSC algorithms such as ours. Empirical evaluations on well-known clustering benchmarks show that our proposed NLSSC framework results in better clusterings compared to the state-of-the-art baselines and demonstrate the effectiveness of the link-restore post-processing in improving the clustering accuracy via correcting the broken links of the representation graph.Comment: 15 pages, IDA 2018 conferenc

Quantum Yield Calculations for Strongly Absorbing Chromophores

This article demonstrates that a commonly-made assumption in quantum yield calculations may produce errors of up to 25% in extreme cases and can be corrected by a simple modification to the analysis.Comment: 3 pages, 2 figures. Accepted by Journal of Fluorescenc

Random qubit-states and how best to measure them

We consider the problem of measuring a single qubit, known to have been prepared in either a randomly selected pure state or a randomly selected real pure state. We seek the measurements that provide either the best estimate of the state prepared or maximise the accessible information. Surprisingly, any sensible measurement turns out to be optimal. We discuss the application of these ideas to multiple qubits and higher-dimensional systems

Acute Ethanol Administration Rapidly Increases Phosphorylation of Conventional Protein Kinase C in Specific Mammalian Brain Regions in Vivo

Background Protein kinase C (PKC) is a family of isoenzymes that regulate a variety of functions in the central nervous system including neurotransmitter release, ion channel activity, and cell differentiation. Growing evidence suggests that specific isoforms of PKC influence a variety of behavioral, biochemical, and physiological effects of ethanol in mammals. The purpose of this study was to determine whether acute ethanol exposure alters phosphorylation of conventional PKC isoforms at a threonine 674 (p-cPKC) site in the hydrophobic domain of the kinase, which is required for its catalytic activity. Methods Male rats were administered a dose range of ethanol (0, 0.5, 1, or 2 g/kg, intragastric) and brain tissue was removed 10 minutes later for evaluation of changes in p-cPKC expression using immunohistochemistry and Western blot methods. Results Immunohistochemical data show that the highest dose of ethanol (2 g/kg) rapidly increases p-cPKC immunoreactivity specifically in the nucleus accumbens (core and shell), lateral septum, and hippocampus (CA3 and dentate gyrus). Western blot analysis further showed that ethanol (2 g/kg) increased p-cPKC expression in the P2 membrane fraction of tissue from the nucleus accumbens and hippocampus. Although p-cPKC was expressed in numerous other brain regions, including the caudate nucleus, amygdala, and cortex, no changes were observed in response to acute ethanol. Total PKC? immunoreactivity was surveyed throughout the brain and showed no change following acute ethanol injection

Interdental and subgingival microbiota may affect the tongue microbial ecology and oral malodour in health, gingivitis and periodontitis.

BACKGROUND AND OBJECTIVE: Oral malodour is often observed in gingivitis and chronic periodontitis patients, and the tongue microbiota is thought to play a major role in malodorous gas production, including volatile sulphur compounds (VSCs) such as hydrogen sulphide (H2 S) and methanethiol (CH3 SH). This study aimed to examine the link between the presence of VSCs in mouth air (as a marker of oral malodour) and the oral bacterial ecology in the tongue and periodontal niches of healthy, gingivitis and periodontitis patients. METHODS: Participants were clinically assessed using plaque index, bleeding on probing (BOP) and periodontal probing depths, and VSC concentrations in their oral cavity measured using a portable gas chromatograph. Tongue scrapings, subgingival and interdental plaque were collected from healthy individuals (n = 22), and those with gingivitis (n = 14) or chronic periodontitis (n = 15). The bacterial 16S rRNA gene region V3-V4 in these samples was sequenced, and the sequences were analysed using the minimum entropy decomposition pipeline. RESULTS: Elevated VSC concentrations and CH3 SH:H2 S were observed in periodontitis compared with health. Significant ecological differences were observed in the tongue microbiota of healthy subjects with high plaque scores compared to low plaque scores, suggesting a possible connection between the microbiota of the tongue and the periodontium and that key dysbiotic changes may be initiated in the clinically healthy individuals who have higher dental plaque accumulation. Greater subgingival bacterial diversity was positively associated with H2 S in mouth air. Periodontopathic bacteria known to be prolific VSC producers increased in abundance on the tongue associated with increased bleeding on probing (BOP) and total percentage of periodontal pockets >6 mm, supporting the suggestion that the tongue may become a reservoir for periodontopathogens. CONCLUSION: This study highlights the importance of the periodontal microbiota in malodour and has detected dysbiotic changes in the tongue microbiota in periodontitis

Comparing computer-generated and pathologist-generated tumour segmentations for immunohistochemical scoring of breast tissue microarrays

BACKGROUND: Tissue microarrays (TMAs) have become a valuable resource for biomarker expression in translational research. Immunohistochemical (IHC) assessment of TMAs is the principal method for analysing large numbers of patient samples, but manual IHC assessment of TMAs remains a challenging and laborious task. With advances in image analysis, computer-generated analyses of TMAs have the potential to lessen the burden of expert pathologist review. METHODS: In current commercial software computerised oestrogen receptor (ER) scoring relies on tumour localisation in the form of hand-drawn annotations. In this study, tumour localisation for ER scoring was evaluated comparing computer-generated segmentation masks with those of two specialist breast pathologists. Automatically and manually obtained segmentation masks were used to obtain IHC scores for thirty-two ER-stained invasive breast cancer TMA samples using FDA-approved IHC scoring software. RESULTS: Although pixel-level comparisons showed lower agreement between automated and manual segmentation masks (κ=0.81) than between pathologists' masks (κ=0.91), this had little impact on computed IHC scores (Allred; [Image: see text]=0.91, Quickscore; [Image: see text]=0.92). CONCLUSIONS: The proposed automated system provides consistent measurements thus ensuring standardisation, and shows promise for increasing IHC analysis of nuclear staining in TMAs from large clinical trials