Testing for Long-Run Relation between Economic Growth and Export Earnings of Cocoa in Ghana using Co-Integration Techniques

In this study, we explore the causal influence of export earnings of cocoa towards economic growth (i.e., gross domestic product (GDP)). The augmented Dickey–Fuller (ADF) and the Phillips–Perron (PP) unit root tests indicate that the two series are integrated of order one, I (1). The results of the trace and the maxi-eigenvalue cointegration test based on Johansen’s procedure indicate the existence of a cointegration between export earnings of cocoa and GDP. Thus, the two variables of the study have a long-run equilibrium relationship. The vector error correction model of order two, VECM (2), was considered as the “best” model after evaluating other competing models. It is observed that, in the long-run, previous year export earnings of cocoa is positively related to economic growth. In the short run, the results revealed that the previous GDP has positive effect on current GDP; and higher export earnings of cocoa have positive effect on GDP. Feedback causality is observed between economic growth (GDP) and export earnings of cocoa. This suggests a bi-directional causality from export earnings to economic growth (GDP). Keywords: Cointegration, VECM, Johansen, ADF, Causality

Integrating Knowledge Graphs for Analysing Academia and Industry Dynamics

Academia and industry are constantly engaged in a joint effort for producing scientific knowledge that will shape the society of the future. Analysing the knowledge flow between them and understanding how they influence each other is a critical task for researchers, governments, funding bodies, investors, and companies. However, current corpora are unfit to support large-scale analysis of the knowledge flow between academia and industry since they lack of a good characterization of research topics and industrial sectors. In this short paper, we introduce the Academia/Industry DynAmics (AIDA) Knowledge Graph, which characterizes 14M papers and 8M patents according to the research topics drawn from the Computer Science Ontology. 4M papers and 5M patents are also classified according to the type of the author's affiliations (academy, industry, or collaborative) and 66 industrial sectors (e.g., automotive, financial, energy, electronics) obtained from DBpedia. AIDA was generated by an automatic pipeline that integrates several knowledge graphs and bibliographic corpora, including Microsoft Academic Graph, Dimensions, English DBpedia, the Computer Science Ontology, and the Global Research Identifier Database

Heterogeneous inter-organizational social capital: the case of Faraday Partnerships for technology transfer

Given its tripartite impact on society, industry, and university, the phenomenon of university-industry partnership (UIP) has become a valuable research endeavor. However, examining UIP-related literature shows limited understanding from a social capital (SC) perspective, albeit its relevance (as UIP comprises extensive social interaction) and capacity (being an important resource latent in networks system). Likewise, it is noticeable that research on inter-organizational SC has been predominantly conducted from the perspective of homogenous organizations (i.e., have consistent expectation, mission, and culture). However, the perspective of social interaction between heterogeneous organizations (i.e., belong to different sectors thus inherently different) is limited. We address these two gaps by investigating the idiosyncrasy of SC development in the setting of UIP, as a unique context for heterogeneous inter-organizational SC. We contribute to the literature by exposing the various facets of SC dynamics as evolve in this uncommon domain. Also, we identify four factors as moderating the interaction between the three dimensions of SC that eventually influence the dual processes of technology translation and transfer

Promoting Partnership with Traditional Authorities in Development Projects: A Model for Community Infrastructure Project Delivery in Ghana

Promoting partnership with traditional Authority Project (PPTAP) was designed to translate into reality the vision of having our traditional leaders play pivotal roles in community devel­opment. The project was to test the role that chiefs, queen mothers and other opinion leaders could play in the decentralization of community development. In spite of the presence of some challenges with respect to project implementation such as slow pace in the payment of coun­terpart fund contribution, this novelty achieved spectacular successes. This paper discusses the results of a questionnaire survey that looked at the role played by traditional authorities and community involvement in infrastructure development for 40 selected communities in Ashanti region under the PPTAP, with support from the International Development Agency (IDA) of the World Bank and the Government of Ghana. The paper concludes that the inclusion of tradi­tional authorities in beneficiary communities helped in an accurate identification of community needs, minimization of cost incurred and high-quality workmanship as well as strengthened ownership. For community based development, the paper recommends a Tripartite Partnership (TTP), where Traditional Authorities work in tandem with the Public and Private Sector to ensure sustainable national development. PPTAP presents an excellent framework for such TPP arrangements. Keywords: Traditional Authorities, Community Based Project, Infrastructure, Developmen

Resting electrocardiographic and echocardiographic findings in an urban community in the Gambia

The presence of Left Ventricular Hypertrophy (LVH) in a patient with systemic hypertension deserves serious attention and makes its clinical diagnosis a priority. Over the years various criteriahave been proposed for the electrographic (ECG) diagnosis of LVH and the sensitivity and specificity of these criteria have been extensively studied in Caucasians. Recent evidence indicates that they areinapplicable to people of African descent. Unlike echocardiography (ECHO), the ECG is generally available, cheap but has a lower sensitivity in detecting LVH compared to echocardiography. Thisstudy was conducted to evaluate ECG criteria against 2-dimensional (2-D) guided M-mode echocardiography in the diagnosis of LVH in adult Gambians. Secondly, to determine the ECG criteria usingthe Minnesota, Araoye, Sokolow and Lyon or Wolff criteria with the overall best accuracy for the diagnosis of LVH. Two hundred and eight (208) consecutive patients with systemic hypertension (BP.140/90mmHg) with or without treatment and an age matched group of 108 non-hypertensive patients were enrolled from outpatient clinics. A questionnaire was filled. All patients were investigated with 2-D guided M-mode echocardiography and a standard 12-1ead ECG. Anthropometric measurements were also taken. The gold standard was the Penn formula to determine the left ventricular mass index (of 125 g/m2 in males and 110 g/m2 in females as the cut-off for LVH). Using this gold standard the prevalence of echocardiographic LVH was 47.5% and 27.8 % in the hypertensives and non-hypertensives respectively (P 0.05). Sokolow and Lyon criterion had overall best accuracy for the electrocardiographic diagnosis of left ventricular hypertrophyin hypertensives and is further recommended for use as such. But for non-hypertensives, the Wolff criterion had overall best accuracy

ResearchFlow: Understanding the Knowledge Flow between Academia and Industry

Understanding, monitoring, and predicting the flow of knowledge between academia and industry is of critical importance for a variety of stakeholders, including governments, funding bodies, researchers, investors, and companies. To this purpose, we introduce ResearchFlow, an approach that integrates semantic technologies and machine learning to quantifying the diachronic behaviour of research topics across academia and industry. ResearchFlow exploits the novel Academia/Industry DynAmics (AIDA) Knowledge Graph in order to characterize each topic according to the frequency in time of the related i) publications from academia, ii) publications from industry, iii) patents from academia, and iv) patents from industry. This representation is then used to produce several analytics regarding the academia/industry knowledge flow and to forecast the impact of research topics on industry. We applied ResearchFlow to a dataset of 3.5M papers and 2M patents in Computer Science and highlighted several interesting patterns. We found that 89.8% of the topics first emerge in academic publications, which typically precede industrial publications by about 5.6 years and industrial patents by about 6.6 years. However this does not mean that academia always dictates the research agenda. In fact, our analysis also shows that industrial trends tend to influence academia more than academic trends affect industry. We evaluated ResearchFlow on the task of forecasting the impact of research topics on the industrial sector and found that its granular characterization of topics improves significantly the performance with respect to alternative solutions

SUPREME-HN: a retrospective biomarker study assessing the prognostic value of PD-L1 expression in patients with recurrent and/or metastatic squamous cell carcinoma of the head and neck.

BACKGROUND:Programmed cell death ligand-1 (PD-L1) expression on tumor cells (TCs) is associated with improved survival in patients with head and neck squamous cell carcinoma (HNSCC) treated with immunotherapy, although its role as a prognostic factor is controversial. This study investigates whether tumoral expression of PD-L1 is a prognostic marker in patients with recurrent and/or metastatic (R/M) HNSCC treated with standard chemotherapy. METHODS:This retrospective, multicenter, noninterventional study assessed PD-L1 expression on archival R/M HNSCC tissue samples using the VENTANA PD-L1 (SP263) Assay. PD-L1 high was defined as PD-L1 staining of ≥ 25% TC, with exploratory scoring at TC ≥ 10% and TC ≥ 50%. The primary objective of this study was to estimate the prognostic value of PD-L1 status in terms of overall survival (OS) in patients with R/M HNSCC. RESULTS:412 patients (median age, 62.0 years; 79.9% male; 88.2% Caucasian) were included from 19 sites in seven countries. 132 patients (32.0%) had TC ≥ 25% PD-L1 expression; 199 patients (48.3%) and 85 patients (20.6%) had TC ≥ 10% and ≥ 50%, respectively. OS did not differ significantly across PD-L1 expression (at TC ≥ 25% cutoff median OS: 8.2 months vs TC < 25%, 10.1 months, P = 0.55) or the ≥ 10% and ≥ 50% cutoffs (at TC ≥ 10%, median OS: 9.6 months vs TC < 10%, 9.4 months, P = 0.32, and at TC ≥ 50%, median OS 7.9 vs TC < 50%, 10.0 months, P = 0.39, respectively). CONCLUSIONS:PD-L1 expression, assessed using the VENTANA PD-L1 (SP263) Assay, was not prognostic of OS in patients with R/M HNSCC treated with standard of care chemotherapies. Trial registration ClinicalTrials.gov, NCT02543476. Registered September 4, 2015

A review on a deep learning perspective in brain cancer classification

AWorld Health Organization (WHO) Feb 2018 report has recently shown that mortality rate due to brain or central nervous system (CNS) cancer is the highest in the Asian continent. It is of critical importance that cancer be detected earlier so that many of these lives can be saved. Cancer grading is an important aspect for targeted therapy. As cancer diagnosis is highly invasive, time consuming and expensive, there is an immediate requirement to develop a non-invasive, cost-effective and efficient tools for brain cancer characterization and grade estimation. Brain scans using magnetic resonance imaging (MRI), computed tomography (CT), as well as other imaging modalities, are fast and safer methods for tumor detection. In this paper, we tried to summarize the pathophysiology of brain cancer, imaging modalities of brain cancer and automatic computer assisted methods for brain cancer characterization in a machine and deep learning paradigm. Another objective of this paper is to find the current issues in existing engineering methods and also project a future paradigm. Further, we have highlighted the relationship between brain cancer and other brain disorders like stroke, Alzheimer’s, Parkinson’s, andWilson’s disease, leukoriaosis, and other neurological disorders in the context of machine learning and the deep learning paradigm

Factors impacting antiretroviral therapy adherence among human immunodeficiency virus-positive adolescents in Sub-Saharan Africa: a systematic review

© 2018 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.Objectives: Eighty-two percent of human immunodeficiency virus (HIV)–positive adolescents live in Sub-Saharan Africa (SSA). Despite the availability of antiretroviral therapy (ART), adherence levels are suboptimal, leading to poor outcomes. This systematic review investigated factors impacting ART adherence among adolescents in SSA, including religious beliefs and intimate relationships. Methods: A systematic review was conducted between June and August 2016 using eight electronic databases, including Cochrane and PubMed. Published, ongoing and unpublished research, conducted in SSA from 2004 to 2016, was identified and thematic analysis was used to summarise findings. Results: Eleven studies from eight SSA countries, published in English between 2011 and 2016, reported on factors impacting ART adherence among adolescents living with HIV (ALHIV). Forty-four barriers and 29 facilitators to adherence were identified, representing a complex web of factors. The main barriers were stigma, ART side-effects, lack of assistance and forgetfulness. Facilitators included caregiver support, peer support groups and knowledge of HIV status. Conclusions: Stigma reflects difficult relations between ALHIV and their HIV-negative peers and adults. Most interventions target only those with HIV, suggesting a policy shift towards the wider community could be beneficial. Recommendations include engaging religious leaders and schools to change negative societal attitudes. Limitations of the review include the urban settings and recruitment of predominantly vertically infected participants in most included studies. Therefore, the findings cannot be extrapolated to ALHIV residing in rural locations or horizontally infected ALHIV, highlighting the need for further research in those areas.Peer reviewedFinal Accepted Versio

Innovation capacity in the healthcare sector and historical anchors: examples from the UK, Switzerland and the US

Innovation is an integral part of economic development in developed economies. In the post 2008 period, a key policy agenda is that of sustainable development, which calls for innovation in all aspects of value-chains. In this paper, we focus on innovation from the biotech—pharma perspective to see whether or not this will lead to a sustainable future for the regions where there are clusters of firms in this sector. We examine data from a recently completed European Union study of innovation in the Healthcare sector from the UK and Switzerland, countries with an historical base in pharma, to understand how innovation pathways vary at the regional level in the broader life sciences, which incorporate biotech and more. Innovation in the healthcare sector in two regions, Oxfordshire in the UK and Zurich in Switzerland are compared. We contextualize our discussion by drawing on studies that focus on the sector in the US, specifically Boston. The analytical framework comprises three elements: innovation systems and national and regional economic development theories are the first two, followed by approaches which consider organizational or institutional activity. This framework is used to help explain and understand the complexity of how innovation is organized at the sub-national level. The overall context is that it is increasing becoming a condition for government financing of research that it has more immediate application in industry or have the possibility of commercialisation (e.g., translational research)