The use of information systems for logistics and supply chain management in South East Europe: Current status and future direction

This research aims to investigate the current status and future direction of the use of information systems for logistics and supply chain management (LSCM) in South East Europe. The objectives are threefold: (1) to identify major challenges and developments on the use of information systems for LSCM by enterprises, (2) to examine the actual level of satisfaction of current policy on LSCM, and (3) to reveal the actual need of enterprises in South East Europe on effective use of information systems for LSCM. Mixed methodology of literature review and questionnaire survey is adopted in this research. Data collected from 79 enterprises are analysed using descriptive analysis in SPSS. The findings suggest that enterprises in Albania, Bulgaria, Greece, Former Yugoslav Republic of Macedonia (FYROM), Romania, and Serbia and Montenegro, face similar challenges but all are in different stages of developments of LSCM. Their use of information systems explains their heavy focus on supply chain partnership and weakness in demand chain partnership. Major findings suggest that companies and governments alike in that region do not seem to be ready for playing a significant and demanding role in global supply chains. Current deficiencies, including limited abilities in building valuable forward relations, weak strategic planning and organisation, and infrastructural problems, are major obstacles for fast development in LSCM. At the same time though, traces of changing mentalities do exist, setting the ground for improved performance and ultimately for a better position in global business

Implementing a system to evaluate quality assurance in rehabilitation in Greece.

BACKGROUND: Use of a widely accepted quality assurance tool is an essential procedure of effective and result-oriented quality management in the rehabilitation sector, and generally in health care and social services, but is still lacking in Greece. OBJECTIVE: This study aims to explore to what extent a Quality Assurance System in Rehabilitation (QASR) in the Greek setting could respond to the needs for quality evaluation of the facilities for people with a disability and to discuss possibilities of its use in rehabilitation organizations, sites and hospitals. METHODS: The European Quality in Social Services (EQUASS) Assurance self-assessment questionnaire was officially translated and used as the basis for the new tool, which consisted of 110 questions in 11 sections on development and 6 questions on its evaluation. This tool was tested in 15 specialized centers. RESULTS: The study received a high (93.75%) response rate. Overall score ranged from 11% to one perfect 100%; 53.3% of the facilities fell short of the preset qualification standards, while 4 (26.7%) were qualified for level-1 accreditation. Evaluation of the QASR questionnaire for the function of the rehabilitation facilities for the disabled was extremely positive. CONCLUSIONS: The EQUASS assurance-based Greek QASR has received proper attention in its first implementation and it was shown promising to assess the needs of sites that would like to improve their services. The next steps are to establish its validity and reliability so that it can significantly emerge as the standard system for guiding policy in the rehabilitation sector in Greece

Neuroscience and CSR : using EEG for assessing the effectiveness of branded videos related to environmental issues

The majority of studies evaluating the effectiveness of branded CSR campaigns are concentrated and base their conclusions on data collection through self-reporting questionnaires. Although such studies provide insights for evaluating the effectiveness of CSR communication methods, analysing the message that is communicated, the communication channel used and the explicit brain responses of those for whom the message is intended, they lack the ability to fully encapsulate the problem of communicating environmental messages by not taking into consideration what the recipients’ implicit brain reactions are presenting. Therefore, this study aims to investigate the effectiveness of CSR video communications relating to environmental issues through the lens of the recipients’ implicit self, by employing neuroscience-based assessments. For the examination of implicit brain perception, an electroencephalogram (EEG) was used, and the collected data was analysed through three indicators identified as the most influential indicators on human behaviour. These three indicators are emotional valence, the level of brain engagement and cognitive load. The study is conducted on individuals from the millennial generation in Thessaloniki, Greece, whose implicit brain responses to seven branded commercial videos are recorded. The seven videos were a part of CSR campaigns addressing environmental issues. Simultaneously, the self-reporting results from the participants were gathered for a comparison between the explicit and implicit brain responses. One of the key findings of the study is that the explicit and implicit brain responses differ to the extent that the CSR video communications’ brain friendliness has to be taken into account in the future, to ensure success. The results of the study provide an insight for the future creation process, conceptualisation, design and content of the effective CSR communication, in regard to environmental issues

Random forest feature selection, fusion and ensemble strategy: combining multiple morphological MRI measures to discriminate among healthy elderly, MCI, cMCI and Alzheimer's disease patients: from the Alzheimer's disease neuroimaging initiative (ADNI) database

Background In the era of computer-assisted diagnostic tools for various brain diseases, Alzheimer’s disease (AD) covers a large percentage of neuroimaging research, with the main scope being its use in daily practice. However, there has been no study attempting to simultaneously discriminate among Healthy Controls (HC), early mild cognitive impairment (MCI), late MCI (cMCI) and stable AD, using features derived from a single modality, namely MRI. New method Based on preprocessed MRI images from the organizers of a neuroimaging challenge,3 we attempted to quantify the prediction accuracy of multiple morphological MRI features to simultaneously discriminate among HC, MCI, cMCI and AD. We explored the efficacy of a novel scheme that includes multiple feature selections via Random Forest from subsets of the whole set of features (e.g. whole set, left/right hemisphere etc.), Random Forest classification using a fusion approach and ensemble classification via majority voting. From the ADNI database, 60 HC, 60 MCI, 60 cMCI and 60 CE were used as a training set with known labels. An extra dataset of 160 subjects (HC: 40, MCI: 40, cMCI: 40 and AD: 40) was used as an external blind validation dataset to evaluate the proposed machine learning scheme. Results In the second blind dataset, we succeeded in a four-class classification of 61.9% by combining MRI-based features with a Random Forest-based Ensemble Strategy. We achieved the best classification accuracy of all teams that participated in this neuroimaging competition. Comparison with existing method(s) The results demonstrate the effectiveness of the proposed scheme to simultaneously discriminate among four groups using morphological MRI features for the very first time in the literature. Conclusions Hence, the proposed machine learning scheme can be used to define single and multi-modal biomarkers for AD

Prokineticin-1 (PROK1) modulates interleukin (IL)-11 expression via prokineticin receptor 1 (PROKR1) and the calcineurin/NFAT signalling pathway

Prokineticin-1 (PROK1) is a multifunctional secreted protein which signals via the G-protein coupled receptor, PROKR1. Previous data from our laboratory using a human genome survey microarray showed that PROK1–prokineticin receptor 1 (PROKR1) signalling regulates numerous genes important for establishment of early pregnancy, including the cytokine interleukin (IL)-11. Here, we have shown that PROK1–PROKR1 induces the expression of IL-11 in PROKR1 Ishikawa cells and first trimester decidua via the calcium–calcineurin signalling pathway in a guanine nucleotide-binding protein (Gq/11), extracellular signal-regulated kinases, Ca2+ and calcineurin–nuclear factor of activated T cells dependent manner. Conversely, treatment of human decidua with a lentiviral miRNA to abolish endogenous PROK1 expression results in a significant reduction in IL-11 expression and secretion. Importantly, we have also shown a regulatory role for the regulator of calcineurin 1 isoform 4 (RCAN1-4). Overexpression of RCAN1-4 in PROKR1 Ishikawa cells using an adenovirus leads to a reduction in PROK1 induced IL-11 indicating that RCAN1-4 is a negative regulator in the calcineurin-mediated signalling to IL-11. Finally, we have shown the potential for both autocrine and paracrine signalling in the human endometrium by co-localizing IL-11, IL-11Rα and PROKR1 within the stromal and glandular epithelial cells of non-pregnant endometrium and first trimester decidua. Overall we have identified and characterized the signalling components of a novel PROK1–PROKR1 signalling pathway regulating IL-11

Severe paraneoplastic hypoglycemia secondary to a gastrointestinal stromal tumour masquerading as a stroke

We report the case of a 70-year-old previously healthy female who presented acutely to the Accident and Emergency department with left-sided vasomotor symptoms including reduced muscle tone, weakness upon walking and slurred speech. Physical examination confirmed hemiparesis with VIIth nerve palsy and profound hepatomegaly. A random glucose was low at 1.7 mmol/l, which upon correction resolved her symptoms. In hindsight, the patient recalled having had similar episodes periodically over the past 3 months to which she did not give much attention. While hospitalized, she continued having episodes of symptomatic hypoglycaemia during most nights, requiring treatment with i.v. dextrose and/or glucagon. Blood tests including insulin and C-peptide were invariably suppressed, in correlation with low glucose. A Synacthen stimulation test was normal (Cort (0′) 390 nmol/l, Cort (30′) 773 nmol/l). A computed tomography scan showed multiple lobulated masses in the abdomen, liver and pelvis. An ultrasound guided biopsy of one of the pelvic masses was performed. Immunohistochemistry supported the diagnosis of a gastrointestinal stromal tumour (GIST) positive for CD34 and CD117. A diagnosis of a non islet cell tumour hypoglycaemia (NICTH) secondary to an IGF2 secreting GIST was confirmed with further biochemical investigations (IGF2=96.5 nmol/l; IGF2:IGF1 ratio 18.9, ULN <10). Treatment with growth hormone resolved the patient's hypoglycaemic symptoms and subsequent targeted therapy with Imatinib was successful in controlling disease progression over an 8-year observation period

New High-Speed a-Si/c-Si- and a-SiC/c-Si-Based Switches

The electrical and optical characteristics of the new high-speed Al/a-Si/c-Si(p)/c-Si(n+)/Al and Al/a- SiC/c-Si(p)/c-Si(n+)/Al optically controlled switches are presented in this paper. These switches exhibit the lowest ever reported values of rise and fall times, for this kind of switches, of about 3ns. They also exhibit a temperature and light reversibly controlled forward breakover voltage (VBF), together with high values of light triggering sensitivity

Quantitative identification of functional connectivity disturbances in neuropsychiatric lupus based on resting-state fMRI: a robust machine learning approach

Neuropsychiatric systemic lupus erythematosus (NPSLE) is an autoimmune entity comprised of heterogenous syndromes affecting both the peripheral and central nervous system. Research on the pathophysiological substrate of NPSLE manifestations, including functional neuroimaging studies, is extremely limited. The present study examined person-specific patterns of whole-brain functional connectivity in NPSLE patients (n = 44) and age-matched healthy control participants (n = 39). Static functional connectivity graphs were calculated comprised of connection strengths between 90 brain regions. These connections were subsequently filtered through rigorous surrogate analysis, a technique borrowed from physics, novel to neuroimaging. Next, global as well as nodal network metrics were estimated for each individual functional brain network and were input to a robust machine learning algorithm consisting of a random forest feature selection and nested cross-validation strategy. The proposed pipeline is data-driven in its entirety, and several tests were performed in order to ensure model robustness. The best-fitting model utilizing nodal graph metrics for 11 brain regions was associated with 73.5% accuracy (74.5% sensitivity and 73% specificity) in discriminating NPSLE from healthy individuals with adequate statistical power. Closer inspection of graph metric values suggested an increased role within the functional brain network in NSPLE (indicated by higher nodal degree, local efficiency, betweenness centrality, or eigenvalue efficiency) as compared to healthy controls for seven brain regions and a reduced role for four areas. These findings corroborate earlier work regarding hemodynamic disturbances in these brain regions in NPSLE. The validity of the results is further supported by significant associations of certain selected graph metrics with accumulated organ damage incurred by lupus, with visuomotor performance and mental flexibility scores obtained independently from NPSLE patients. View Full-Text Keywords: neuropsychiatric systemic lupus erythematosus; rs-fMRI; graph theory; functional connectivity; surrogate data; machine learning; visuomotor ability; mental flexibilit