Corporate heritage brand insight from John Lewis

Purpose: This paper studies the relationship between corporate heritage brand identity and customers satisfaction of John Lewis Partnership (JLP) which is one of the most successful British retail heritage brands internationally. We conceptualize and address the key factors of corporate heritage brand identity which includes brand price, quality, design, and symbol. It examines the corporate heritage brand experience of JLP customers through which corporate heritage brand identity influence its customers’ satisfaction. We also established the moderating role of word of mouth (WoM) on these relationships. Design/methodology/approach: An Online and observation surveys targeting over than 6000 customers in some five main cities in England (London, Manchester, Liverpool, Leicester and Southampton) used in this study, A (596) survey success responses collected from JLP stores, shopping centres, and public places within the United Kingdom, in addition to that, approaching all JLP online customers and followers to their social media applications and their website. Findings: The results confirmed the importance of heritage brand identity to reach for a powerful heritage brand satisfaction. The relation becomes stronger once corporate heritage brand experience considered as mediation between identity and satisfaction. Research limitations/implications: This study was implemented on a single at the retail sector in the United Kingdom, were still the management strategy had huge restrictions to represent the heritage identity and involve the academic sector to test it or represent it. Practical implications: The corporate heritage brand identity dimensions that were tested in this study gives the brand managers a clear picture in how to represent their heritage brand to the market, while the negative effect of word of mouth on the relation between the corporate heritage brand identity and brand experience is a reasonable indicator of lack communication between the heritage brand and the customers which need more attention from the heritage corporation to consider to sustain their brand on the market. Originality/value: This paper identifies the distinct characteristics of corporate heritage brand identity dimensions that must be taken into account to get a powerful brand experience and sustain the brand satisfaction on the market. Keywords Corporate heritage brand identity; Corporate heritage brand; Brand strategy; Brand experience; Word of mouth; Satisfaction Paper Type - Research Pape

Spatial Probabilistic Mapping of Biomolecular Ensembles in Tissue via Mass Spectrometry Imaging

Tissues are a major focus of clinical research and histopathological diagnosis for a wide range of diseases. Understanding the complex biomolecular manifestations of disease within tissues by characterizing its morphology and biomolecular information content paves the way for exploring the fundamental mechanisms of pathogenesis and for identifying diagnostic and prognostic biomarkers and potential therapeutic targets. Among the many tissue-investigation techniques, matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has evolved into a label-free core technology for visualization and spatially-resolved ex vivo analysis of biomolecules directly from tissue samples. Ion images, i.e. false color renderings of mass-to-charge ratio (m/z) intervals of interest, are used as the fundamental investigation tool in MALDI-MSI for conveying the spatial distribution of molecules-of-interest (MOIs, e.g., metabolites, drugs, lipids or proteins) within biological tissues that are often compared to external histopathology annotations. They are considered as the gold-standard by MSI researchers against which the biomarker discovery methods are validated. However, the conversion of raw MSI data into ion images for visualization, spatial interpretation and molecular analysis, has not changed since the inception of the technology. Moreover, the generated ion images can be prone to technical artifacts, user input- and user perception-bias. This work introduces a computational framework, moleculaR, which proposes a coherent spatial probabilistic approach for mapping tissue MOIs and allowing for a user-independent spatial visualization and interpretation of MOIs' distribution in tissue samples via MSI. moleculaR uses user-independent assignment of m/z intervals for capturing MOIs based on the device- and measurement-dependent mass resolving power along with Gaussian-weighting of observed peak intensities for improved reliability of metabolite/lipid/drug signals in MSI. Instead of relying on a subjective qualitative judgment of the end-user concerning the observed spatial distribution of an MOI within a tissue sample, moleculaR proposes molecular probabilistic maps (MPMs), which apply pixel-wise spatial significance testing of MOI intensities against a complete spatial randomness (CSR) model inferred from the signal intensities of that same MOI. The framework also allows for spatial statistical comparisons of different tissues (cross-tissue MPMs, or CT-MPMs) and for collective projections of metabolite ensembles onto a single tissue plane, followed by computation of collective projection probabilistic maps (CPPMs). Ultimately, computed "hotspot" and "coldspot" spatial contours provide user-independent and probabilistic localization of tissue areas where an MOI has a statistically significant non-random relative spatial abundance or deficiency, respectively. Furthermore, this work extends the above concept to spatial quantitative mapping in tissues based on drug dilution series proposing a generalized nonlinear calibration model as a replacement for the traditional linear model that could better model drug-intensity response in the presence of noise and technical variability. The framework has been tested and validated on data acquired from various MALDI-MSI instrument platforms featuring different tissue samples including isocitrate dehydrogenase-wild type (IDH-WT) glioblastoma (GB), IDH-WT and -mutant glioma, gastrointestinal stromal tumor (GIST), wild-type mouse brain, porcine liver and APP NL-G-F Alzheimer’s disease mouse model tissue samples in addition to simulation-based experiments mimicking a MALDI-MSI ground-truth which have been developed and utilized to test the proposed workflows. The results highlight moleculaR’s capabilities of i) improving MOI signal reliability, ii) providing objective and data-driven designations of areas which exhibit statistically significant non-random spatial patterns of MOI intensities independent of how an end-user may perceive its (i.e. MOI's) spatial relative abundance or deficiency and iii) enabling spatially-resolved investigation of ion milieus, lipid remodeling pathways or complex scores like the adenylate energy charge within the same image. On the other hand, spatial quantitative mapping based on generalized nonlinear calibration and cross-tissue probabilistic mapping can be used to provide valuable insight into drug-tissue penetration. In particular, spatial quantitative mapping of the drug imatinib in a cohort of GIST tissue samples revealed striking inefficiency in imatinib penetration into GIST liver metastases, despite the abundant imatinib levels beyond the limit of quantification (LOQ) observed within the corresponding healthy liver tissues surrounding the metastatic GIST. In conclusion, the results suggest that moleculaR, with its core concept of spatial probabilistic mapping of biomolecules in tissues, shall replace or complement ion images for the spatial analysis of MOIs because of its valuable benefit of enabling probabilistic localization of non-random patterns of MOI signal intensities and shall further foster the role of MALDI-MSI as a valuable technique for investigating the spatial distribution of biomolecules and drugs in tissue samples. moleculaR has been made available for the scientific community as an open-source R package

An Agglomerative Hierarchical Clustering with Various Distance Measurements for Ground Level Ozone Clustering in Putrajaya, Malaysia

Ground level ozone is one of the common pollution issues that has a negative influence on human health. The key characteristic behind ozone level analysis lies on the complex representation of such data which can be shown by time series. Clustering is one of the common techniques that have been used for time series metrological and environmental data. The way that clustering technique groups the similar sequences relies on a distance or similarity criteria. Several distance measures have been integrated with various types of clustering techniques. However, identifying an appropriate distance measure for a particular field is a challenging task. Since the hierarchical clustering has been considered as the state of the art for metrological and climate change data, this paper proposes an agglomerative hierarchical clustering for ozone level analysis in Putrajaya, Malaysia using three distance measures i.e. Euclidean, Minkowski and Dynamic Time Warping. Results shows that Dynamic Time Warping has outperformed the other two distance measures

Artificial Intelligence and customers service in banking: the bank of the future Monzo

Purpose: Our research studies the impact of artificial intelligence (AI) banking service innovation on Y-generation customers’ lifestyle. Recently financial technology (FinTech) applications have attracted large demand for mobile banking users targeting youth generation by using smartphone apps banking services. This research focuses on the banking service innovation using AI and its impact mobile banking customers, young generation customers in particular. The FinTech applications developers monitored all their customer expenses using these financial wallets to monitor their life-style and daily expenses data. The financial service innovation makes life easier and convenient for customers, but it helps several companies to monitor the youth generation interest and data. These data could have been used in an unethical way without their awareness and consents. There is an urgent requirement to understand this phenomenon and improve more regulations to improve the security and ethical standard for such data and regulate these financial technology wallets. The study considered artificial intelligence security, risk and ethics as a moderator for these relationships. Monzo is one of the famous financial technology platforms which announce that 55K users apply for their wallet in weekly bases, moreover, they are targeting the youth generation. It was founded since 2015 which power progressing business within 2018 and 2019. This case is one of the main popular financial technology platforms in the United Kingdom which this study adopted. More than 1 million new customers join Monzo last year, and the customer deposits increased by 390miion pound with the last year 2018/2019 which reflect the demand from customer side to use such technology. Design/methodology/approach: A research framework was developed based upon thorough literature review on artificial intelligence and banking service innovations. The Data of this study will be targeting on over than 8000 youth users in the United Kingdom using social media platforms such as Facebook, Instagram and Snapchat. Online questionnaires targeted to be active to discover how artificial intelligence financial applications leads to service addiction through social influence and service innovation. The moderating role AI risks and security and AI ethics will also be analysed in this study. Findings: The results will reveal how AI platforms controlled youth generation life-style by attracting them to use such financial wallet. The results will reflect the impact of AI within the coming years on government regulations to avoid any risk and to build security for customer data through having data protection. The results will also be addressing the role of the government and society to control these companies’ data by having an ethical agreement for data protection. Practical implications: The study aims to help the regulators to build rules for avoiding any risk and to have data protection for Y – generation lifestyle expenses. Moreover, to build a rule for Financial Technology companies to protect their data and regulate their service. It will reflect how the government bodies need to control the artificial intelligence of the innovated banking service big data which could use unethically regarding customer lifestyle and personal information’s. Originality/value: This paper designs a conceptual framework to determine how financial technology applications using artificial intelligence techniques could impact Y-generation life-style data. This paper is one of a few studies, which focus on the importance of Fintech AI platforms toward the business environment. At the same time, how AI ethics rules need to be set up by governments to avoid any risk and build data protection for youth generation users. This is an example of a case study that attempts to target Y-generation on daily bases to attract them using such intelligence platform on their daily bases. Keywords: Fin-tech, Artificial intelligence, service addiction, social influence, AI ethics, AI risk and security, Monzo Paper type: Research pape

ETS-1 oncoprotein expression is decreased in aggressive papillary transitional cell carcinoma of the urinary bladder: An immunohistochemical study

Introduction: ETS-1 proto-oncogene is a transcription factor that plays multiple roles in the process of oncogenesis and helps in the process of tumor invasion. ETS-1 oncoprotein correlation with high grade and invasive tumors is controversial; as it is found to be upregulated with some tumors and down regulated with others. Expression of ETS-1 in urinary bladder carcinoma (UBC) and its correlation with tumor differentiation and invasiveness are still under-investigated. So far, there is no reliable prognostic marker has been proved for detection of the tumor progression and recurrence.Objectives: To analyze the correlation between ETS-1 oncoprotein immunohistochemical expression and the different stages and grades of the primary papillary transitional cell carcinoma of the urinary bladder.Patients and methods: This is a retrospective cross sectional study that included archival material from 150 cancer cases and 24 control biopsies.Results: There was a decreased ETS-1 oncoprotein expression with increasing stage and grade of the tumor with a highly significant statistical correlation (P = 0.001). With the quantitative assessment of the immunohistochemical results and using ROC (receiver operating characteristics) curve, cut-off values were found, that were associated with high grade and muscle invasive tumors (≤30% and ≤20%, respectively).Conclusion: ETS-1 oncoprotein is down regulated with high grade and highly invasive urinary bladder papillary transitional cell carcinomas. This oncoprotein may be used as an independent prognostic marker to predict the aggressive papillary transitional carcinomas with high invasive potential. More studies are needed to confirm our results.Keywords: Papillary transitional cell carcinoma; ETS-1; Prognostic marker; Immunohistochemical; Stage; Grad

INHALED TASTE MASKED SPRAY DRIED KETOTIFEN MICROPARTICLES: FORMULATION, CHARACTERIZATION AND IN VITRO PULMONARY DEPOSITION

Objective: Preparation and characterization of inhalable taste masked microparticles (MPs) loaded with the anti-asthmatic bitter drug, ketotifen (KT).Methods: MPs were prepared by a spray-drying technique. The effects of addition of different excipients namely: mannitol, leucine and hyaluronic acid (HA) on the physicochemical properties of KT spray dried powders were determined. Powder taste was evaluated on volunteers. DSC and x-ray diffraction were done to investigate thermal and crystallographic properties of the powders. The surface morphology and shape of KT-loaded hyaluronic acid MPs were examined using scanning electron microscope, in vitro pulmonary deposition and inhalation indices were determined using a twin stage glass impinger (TSI).Results: Leucine improved the powder flow properties. Mannitol, at all tested ratios, produced brownish discoloration in spray dried powders (SDP) upon storage even in dessicator. At a drug to HA ratio of 1:2, the bitter taste of KT had significantly improved besides obtaining a high respirable particle fraction. This selected ratio showed good physicochemical stability for up to 9 mo.Conclusion: The developed KT spray dried particles may offer a good platform for the targeted pulmonary delivery of the drug overcoming the major biological barriers.Keywords: Ketotifen, Microparticles, Pulmonary delivery, Hyaluronic acid, Taste masking, Spray dryin

Sonohysterography for evaluation of endometrial abnormalities associated with tamoxifen therapy for breast cancer

AbstractObjectiveTo evaluate sonohysterography for the diagnosis of endometrial abnormalities in women treated with tamoxifen for breast cancer.Patients and methodsWe assessed 37 women treated with tamoxifen for breast cancer who underwent sonohysterography and correlative endometrial biopsy for evaluation of postmenopausal bleeding or thickened endometrium greater than 8mm. In 14 patients, endometrial biopsy was followed by endovaginal sonography to ensure removal of endometrial pathology. Sonohysterography findings were compared with histopathology results.ResultsSonohysterography findings coincided with histopathology results in 27 of 37 cases including 19 of 23 cases of endometrial polyps, 6 of 8 cases with thickened endometria and two cases had normal endometrium. Sonohysterography findings did not coincide with histopathology in 3 of the 14 cases who underwent endovaginal sonography after endometrial biopsy compared to 7 of the 23 cases who did not undergo such examination and 4 of these missed 7 cases were for endometrial polyps.ConclusionSonohysterography is a useful procedure for the diagnosis of endometrial abnormalities in tamoxifen-treated women. Endometrial abnormalities are better diagnosed on sonohysterography than on endometrial biopsy which has the limitation of some missed endometrial polyps, a problem that may be minimized by performing endovaginal sonography after endometrial biopsy

Strategies to Manage Customer Complaints

Poor customer complaint-handling strategies can negatively affect customer loyalty. Leaders in the pharmaceutical industry who fail to improve complaint-handling strategies can experience a decrease in profitability. Grounded in the double-loop learning theory, the purpose of this qualitative single-case study was to explore effective strategies business leaders use to manage customer complaints in a pharmaceutical company. Participants included six business leaders in Northwest New Jersey, United States, who successfully used strategies to improve customer complaint handling in the pharmaceutical industry. Data were collected from semistructured interviews and company documents relevant to customer complaint handling and were analyzed using thematic data analysis. Two themes emerged: improving the investigation process and organizing the management structure. A key recommendation for business leaders is to focus on organizational learning to improve investigation strategies. The implications for positive social change include the potential to improve the investigation processes and organizational structure, which may improve the health of the population and lead to providing high-quality and low-risk products to patients