The Role of Corporate Social Responsibility in Online Identity Construction: An Analysis of turkey's Banking Sector

Cataloged from PDF version of article.This study focuses on Turkey's banking sector and investigates the role of public relations and corporate social responsibility practices in constructing organizational identities through a thematic content analysis of banks' corporate websites. Based on social identity theory, the research reveals that regardless of its core business function, an organization must communicate non-economic social concerns to construct a public identity and gain legitimacy. (C) 2014 Elsevier Inc. All rights reserved

Autologous anti-SOX2 antibody responses reflect intensity but not frequency of antigen expression in small cell lung cancer

Background: Anti-SOX2 antibody responses are observed in about 10 to 20% of small cell lung cancer (SCLC) patients. The aim of this study was to determine whether such responses reflect a particular pattern of SOX2 protein expression in the tumor and whether this pattern associates with clinical outcome. Methods. Paraffin embedded tumor tissues, obtained from SCLC patients who had no evidence of paraneoplastic autoimmune degeneration, were evaluated for SOX2 expression by immunohistochemistry for both intensity and extent of staining. Sera from the same patients were tested for autologous antibodies against recombinant SOX2 by enzyme-linked immunosorbent assay (ELISA). Correlates between overall survival and various clinical parameters including SOX2 staining and serology were determined. Results: SOX2 protein expression was observed in tumor tissue in 89% of patients. Seventeen patients (29%) were seropositive for SOX2 antibodies and, in contrast to SOX2 staining, the presence of antibody correlated with limited disease stage (p = 0.05). SOX2 seropositivity showed a significant association with the intensity of SOX2 staining in the tumor (p = 0.02) but not with the frequency of SOX2 expressing cells. Conclusion: Anti-SOX2 antibodies associate with better prognosis (limited stage disease) while SOX2 protein expression does not; similar to reports from some earlier studies. Our data provides an explanation for this seemingly contrasting data for the first time as SOX2 antibodies can be observed in patients whose tumors contain relatively few but strongly staining cells, thus supporting the possible presence of active immune-surveillance and immune-editing targeting SOX2 protein in this tumor type. © 2014 Atakan et al.; licensee BioMed Central Ltd

Autologous anti-SOX2 antibody responses reflect intensity but not frequency of antigen expression in small cell lung cancer

Cataloged from PDF version of article.Background: Anti-SOX2 antibody responses are observed in about 10 to 20% of small cell lung cancer (SCLC) patients. The aim of this study was to determine whether such responses reflect a particular pattern of SOX2 protein expression in the tumor and whether this pattern associates with clinical outcome. Methods. Paraffin embedded tumor tissues, obtained from SCLC patients who had no evidence of paraneoplastic autoimmune degeneration, were evaluated for SOX2 expression by immunohistochemistry for both intensity and extent of staining. Sera from the same patients were tested for autologous antibodies against recombinant SOX2 by enzyme-linked immunosorbent assay (ELISA). Correlates between overall survival and various clinical parameters including SOX2 staining and serology were determined. Results: SOX2 protein expression was observed in tumor tissue in 89% of patients. Seventeen patients (29%) were seropositive for SOX2 antibodies and, in contrast to SOX2 staining, the presence of antibody correlated with limited disease stage (p = 0.05). SOX2 seropositivity showed a significant association with the intensity of SOX2 staining in the tumor (p = 0.02) but not with the frequency of SOX2 expressing cells. Conclusion: Anti-SOX2 antibodies associate with better prognosis (limited stage disease) while SOX2 protein expression does not; similar to reports from some earlier studies. Our data provides an explanation for this seemingly contrasting data for the first time as SOX2 antibodies can be observed in patients whose tumors contain relatively few but strongly staining cells, thus supporting the possible presence of active immune-surveillance and immune-editing targeting SOX2 protein in this tumor type. © 2014 Atakan et al.; licensee BioMed Central Ltd

Gaining legitimacy through CSR: An analysis of Turkey's 30 largest corporations

Grounded in institutional theory, this study provides an overview of the corporate social responsibility (CSR) initiatives of Turkey's 30 largest corporations through a thematic content analysis. The study focuses on the G-20 member Turkey and investigates the influence of isomorphism mechanisms on the adoption of CSR initiatives in a developing country context. The aim of this study is to integrate Carroll's CSR dimensions, the type of CSR engagement and coercive, mimetic and normative isomorphism mechanisms proposed by institutional theory. Through this integration the study makes a unique contribution to the literature by providing a different perspective. Findings reveal industry characteristics do not influence the selection of CSR initiatives. While business-to-business companies focus on CSR activities linked to their core business functions, business-to-consumer companies focus on CSR initiatives that are more discretionary, varied and philanthropic. In addition, findings show that multinational corporations implement CSR initiatives at the global level rather than focusing on local needs. © 2016 John Wiley & Sons Ltd

An experimental and modeling study on the reactivity of extremely fuel-rich methane/dimethyl ether mixtures

Chemical reactions in stoichiometric to fuel-rich methane/dimethyl ether/air mixtures (fuel air equiva- lence ratio φ=1–20) were investigated by experiment and simulation with the focus on the conversion of methane to chemically more valuable species through partial oxidation. Experimental data from dif- ferent facilities were measured and collected to provide a large database for developing and validating a reaction mechanism for extended equivalence ratio ranges. Rapid Compression Machine ignition delay times and species profiles were collected in the temperature range between 660 and 1052 K at 10 bar and equivalence ratios of φ= 1–15. Ignition delay times and product compositions were measured in a shock tube at temperatures of 630–1500 K, pressures of 20–30 bar and equivalence ratios of φ= 2 and 10. Ad- ditionally, species concentration profiles were measured in a flow reactor at temperatures between 473 and 973 K, a pressure of 6 bar and equivalence ratios of φ= 2, 10, and 20. The extended equivalence ratio range towards extremely fuel-rich mixtures as well as the reaction-enhancing effect of dimethyl ether were studied because of their usefulness for the conversion of methane into chemically valuable species through partial oxidation at these conditions. Since existing reaction models focus only on equivalence ratios in the range of φ= 0.3–2.5, an extended chemical kinetics mechanism was developed that also covers extremely fuel-rich conditions of methane/dimethyl ether mixtures. The measured ignition delay times and species concentration profiles were compared with the predictions of the new mechanism, which is shown to predict well the ignition delay time and species concentration evolution measure- ments presented in this work. Sensitivity and reaction pathway analyses were used to identify the key reactions governing the ignition and oxidation kinetics at extremely fuel-rich conditions

Transfer learning for drug–target interaction prediction

MotivationUtilizing AI-driven approaches for drug–target interaction (DTI) prediction require large volumes of training data which are not available for the majority of target proteins. In this study, we investigate the use of deep transfer learning for the prediction of interactions between drug candidate compounds and understudied target proteins with scarce training data. The idea here is to first train a deep neural network classifier with a generalized source training dataset of large size and then to reuse this pre-trained neural network as an initial configuration for re-training/fine-tuning purposes with a small-sized specialized target training dataset. To explore this idea, we selected six protein families that have critical importance in biomedicine: kinases, G-protein-coupled receptors (GPCRs), ion channels, nuclear receptors, proteases, and transporters. In two independent experiments, the protein families of transporters and nuclear receptors were individually set as the target datasets, while the remaining five families were used as the source datasets. Several size-based target family training datasets were formed in a controlled manner to assess the benefit provided by the transfer learning approach.ResultsHere, we present a systematic evaluation of our approach by pre-training a feed-forward neural network with source training datasets and applying different modes of transfer learning from the pre-trained source network to a target dataset. The performance of deep transfer learning is evaluated and compared with that of training the same deep neural network from scratch. We found that when the training dataset contains fewer than 100 compounds, transfer learning outperforms the conventional strategy of training the system from scratch, suggesting that transfer learning is advantageous for predicting binders to under-studied targets.Availability and implementationThe source code and datasets are available at https://github.com/cansyl/TransferLearning4DTI. Our web-based service containing the ready-to-use pre-trained models is accessible at https://tl4dti.kansil.org

Neuroimaging in cannabis use: a systematic review of the literature

Background We conducted a systematic review to assess the evidence for specific effects of cannabis on brain structure and function. The review focuses on the cognitive changes associated with acute and chronic use of the drug. Method We reviewed literature reporting neuroimaging studies of chronic or acute cannabis use published up until January 2009. The search was conducted using Medline, EMBASE, LILACS and PsycLIT indexing services using the following key words: cannabis, marijuana, delta-9-tetrahydrocannabinol, THC, cannabidiol, CBD, neuroimaging, brain imaging, computerized tomography, CT, magnetic resonance, MRI, single photon emission tomography, SPECT, functional magnetic resonance, fMRI, positron emission tomography, PET, diffusion tensor MRI, DTI-MRI, MRS and spectroscopy. Results Sixty-six studies were identified, of which 41 met the inclusion criteria. Thirty-three were functional (SPECT/PET/fMRI) and eight structural (volumetric/DTI) imaging studies. The high degree of heterogeneity across studies precluded a meta-analysis. The functional studies suggest that resting global and prefrontal blood flow are lower in cannabis users than in controls. The results from the activation studies using a cognitive task are inconsistent because of the heterogeneity of the methods used. Studies of acute administration of THC or marijuana report increased resting activity and activation of the frontal and anterior cingulate cortex during cognitive tasks. Only three of the structural imaging studies found differences between users and controls. Conclusions Functional neuroimaging studies suggest a modulation of global and prefrontal metabolism both during the resting state and after the administration of THC/marijuana cigarettes. Minimal evidence of major effects of cannabis on brain structure has been reporte

Cannabis affects people differently: inter-subject variation in the psychotogenic effects of Δ9-tetrahydrocannabinol: a functional magnetic resonance imaging study with healthy volunteers

Background Cannabis can induce transient psychotic symptoms, but not all users experience these adverse effects. We compared the neural response to Δ9-tetrahydrocannabinol (THC) in healthy volunteers in whom the drug did or did not induce acute psychotic symptoms. Method In a double-blind, placebo-controlled, pseudorandomized design, 21 healthy men with minimal experience of cannabis were given either 10mg THC or placebo, orally. Behavioural and functional magnetic resonance imaging measures were then recorded whilst they performed a go/no-go task. Results The sample was subdivided on the basis of the Positive and Negative Syndrome Scale positive score following administration of THC into transiently psychotic (TP; n=11) and non-psychotic (NP; n=10) groups. During the THC condition, TP subjects made more frequent inhibition errors than the NP group and showed differential activation relative to the NP group in the left parahippocampal gyrus, the left and right middle temporal gyri and in the right cerebellum. In these regions, THC had opposite effects on activation relative to placebo in the two groups. The TP group also showed less activation than the NP group in the right middle temporal gyrus and cerebellum, independent of the effects of THC. Conclusions In this first demonstration of inter-subject variability in sensitivity to the psychotogenic effects of THC, we found that the presence of acute psychotic symptoms was associated with a differential effect of THC on activation in the ventral and medial temporal cortex and cerebellum, suggesting that these regions mediate the effects of the drug on psychotic symptom

A nanocommunication system for endocrine diseases

Nanotechnology is a newand very promising area of research which will allow several new applications to be created in different fields, such as, biological, medical, environmental, military, agricultural, industrial and consumer goods. This paper focuses specifically on nanocommunications, which will allow interconnected devices, at the nano-scale, to achieve collaborative tasks, greatly changing the paradigm in the fields described. Molecular communication is a new communication paradigm which allows nanomachines to exchange information using molecules as carrier. This is the most promising nanocommunication method within nanonetworks, since it can use bio-inspired techniques, inherit from studied biological systems, which makes the connection of biologic and man-made systems a easier process. At this point, the biggest challenges in these type of nanocommunication are to establish feasible and reliable techniques that will allow information to be encoded, and mechanisms that ensure a molecular communication between different nodes. This paper focus on creating concepts and techniques to tackle these challenges, and establishing new foundations on which future work can be developed. The created concepts and techniques are then applied in an envisioned medical application, which is based on a molecular nanonetwork deployed inside the Human body. The goal of this medical application is to automatously monitor endocrine diseases using the benefits of nanonetworks, which in turn connects with the internet, thus creating a Internet of NanoThings system. The concepts and techniques developed are evaluated by performing several simulations and comparing with other researches, and the results and discussions are presented on the later sections of this paper

Flexible energy conversion and storage via high-temperature gas-phase reactions: The piston engine as a polygeneration reactor

Piston engines are typically considered devices converting chemical energy into mechanical power via internal combustion. But more generally, their ability to provide high-pressure and high-temperature conditions for a limited time means they can be used as chemical reactors where reactions are initiated by compression heating and subsequently quenched by gas expansion. Thus, piston engines could be “polygeneration” reactors that can flexibly change from power generation to chemical synthesis, and even to chemical-energy storage. This may help mitigating one of the main challenges of future energy systems – accommodating fluctuations in electricity supply and demand. Investments in devices for grid stabilization could be more economical if they have a second use. This paper presents a systematic approach to polygeneration in piston engines, combining thermodynamics, kinetics, numerical optimization, engineering, and thermo-economics. A focus is on the fuel-rich conversion of methane as a fuel that is considered important for the foreseeable future. Starting from thermodynamic theory and kinetic modeling, promising systems are selected. Mathematical optimization and an array of experimental kinetic investigations are used for model improvement and development. To evaluate technical feasibility, experiments are then performed in both a single-stroke rapid compression machine and a reciprocating engine. In both cases, chemical conversion is initiated by homogeneous-charge compression-ignition. A thermodynamic and thermo-economic assessment of the results is positive. Examples that illustrate how the piston engine can be used in polygeneration processes to convert methane to higher-value chemicals or to take up carbon dioxide are presented. Open issues for future research are addressed