Disseminating knowledge: the effects of digitalised academic discourse on language, genre and identity

In this introduction to the special issue Disseminating knowledge: The effects of digitalised academic discourse in language, genre and identity, the authors discuss the impact that digital technologies and the Web have had on academia. They show how this attests to interrelations between new digital platforms of knowledge creation and dissemination and their use within discourse communities as elements of innovation and change in the shaping and reshaping of existing academic practices. The introduction also discusses the various methodological approaches that have been adopted with a view to investigating digital academic discourse. Exploring some current academic discoursal practices and their specific textual manifestations in the form of digitally-mediated genres, the authors highlight the complexities of the study of digital academic communication

Temperature - Emissivity separation assessment in a sub-urban scenario

In this paper, a methodology that aims at evaluating the effectiveness of different TES strategies is presented. The methodology takes into account the specific material of interest in the monitored scenario, sensor characteristics, and errors in the atmospheric compensation step. The methodology is proposed in order to predict and analyse algorithms performances during the planning of a remote sensing mission, aimed to discover specific materials of interest in the monitored scenario. As case study, the proposed methodology is applied to a real airborne data set of a suburban scenario. In order to perform the TES problem, three state-of-the-art algorithms, and a recently proposed one, are investigated: Temperature-Emissivity Separation'98 (TES-98) algorithm, Stepwise Refining TES (SRTES) algorithm, Linear piecewise TES (LTES) algorithm, and Optimized Smoothing TES (OSTES) algorithm. At the end, the accuracy obtained with real data, and the ones predicted by means of the proposed methodology are compared and discussed

Accuracy of Triple Diagnostic Test in Patients with Thyroid Nodule at Dr. Cipto Mangunkusumo General Hospital

The aim of the study is to evaluate the accuracy of triple diagnostic test on thyroid nodules. The data from patients’ medical records who came to Cipto Mangunkusumo General Hospital for the first time or for evaluation of thyroid nodule and patients who underwent thyroidectomy during 2010 to 2011. Clinical examination was scored by McGill Thyroid Nodule Score. ROC procedure was performed to obtain clinical cut-off scores of diagnosis of Malignant. Ultrasonography (USG) result was considered Malignant for TIRADS 4, 5, and 6. If clinical, USG and histopathology examinations of triple diagnostic give positive results, it will be classified as concordant Malignant whereas if all those three show benign results, the classification is benign. Thyroid carcinoma was found in 134 out of 161 patients with thyroid nodule. There were 84 patients with concordant results for all three elements of the triple test. Out of 84 patients with concordant triple diagnostic results, there were 53 Malignant cases (32.9%) and 31 benign cases (19.3%). Main histopathological findings among patients with thyroid carcinoma was papillary (90.3%), follicular (3%), medullary (0.7%), and anaplastic (6%). The sensitivity and specificity of triple diagnostic was 77% and 94%, with positive predictive value of 98%, negative predictive value of 51,6% and accuracy of 80.9%. Combination of clinical findings, USG, and FNAB gave Malignant probability of 92%, better than combination of clinical findings and USG (81.6%) or clinical findings and FNAB (87%). Triple diagnostic cannot be used as an ideal test to replace frozen section examination in managing thyroid nodule. However, in cases with concordant results of each triple diagnostic’s element, the positive predictive value (98%) and Malignant probability (92%) is high. &nbsp

Statistical analysis of hyper-spectral data: a non-Gaussian approach

We investigate the statistical modeling of hyper-spectral data. The accurate modeling of experimental data is critical in target detection and classification applications. In fact, having a statistical model that is capable of properly describing data variability leads to the derivation of the best decision strategies together with a reliable assessment of algorithm performance. Most existing classification and target detection algorithms are based on the multivariate Gaussian model which, in many cases, deviates from the true statistical behavior of hyper-spectral data. This motivated us to investigate the capability of non-Gaussian models to represent data variability in each background class. In particular, we refer to models based on elliptically contoured (EC) distributions. We consider multivariate EC-t distribution and two distinct mixture models based on EC distributions. We describe the methodology adopted for the statistical analysis and we propose a technique to automatically estimate the unknown parameters of statistical models. Finally, we discuss the results obtained by analyzing data gathered by the multispectral infrared and visible imaging spectrometer (MIVIS) sensor

T cell subpopulations in the physiopathology of fibromyalgia : Evidence and perspectives

Fibromyalgia is one of the most important \u201crheumatic\u201d disorders, after osteoarthritis. The etiology of the disease is still not clear. At the moment, the most defined pathological mechanism is the alteration of central pain pathways, and emotional conditions can trigger or worsen symptoms. Increasing evidence supports the role of mast cells in maintaining pain conditions such as musculoskeletal pain and central sensitization. Importantly, mast cells can mediate microglia activation through the production of proinflammatory cytokines such as IL-1\u3b2, IL-6, and TNF\u251. In addition, levels of chemokines and proinflammatory cytokines are enhanced in serum and could contribute to inflammation at systemic level. Despite the well-characterized relationship between the nervous system and inflammation, the mechanism that links the different pathological features of fibromyalgia, including stress-related manifestations, central sensitization, and dysregulation of the innate and adaptive immune responses is largely unknown. This review aims to provide an overview of the current understanding of the role of adaptive immune cells, in particular T cells, in the physiopathology of fibromyalgia. It also aims at linking the latest advances emerging from basic science to envisage new perspectives to explain the role of T cells in interconnecting the psychological, neurological, and inflammatory symptoms of fibromyalgia

FAKTOR DETERMINAN PENGUNGKAPAN SUKARELA OLEH YAYASAN DI INDONESIA

The purpose of this study was to determine the effect of donations, restricted funds, organizational size, and age of the organization age on the voluntary disclosure of the foundation. All foundations in Indonesia are the population in this study. The sample of this research is foundations in Indonesia that submit financial reports via the internet between 2013-2019 and have complete data. Based on these criteria, 114 financial reports were obtained as the research sample. The results of this study prove that restricted funds and organizational size have a significant positive effect on voluntary disclosure, while the donations and age of the organization have no significant positive effect on voluntary disclosure. The implication of this research is that funders must consider the restricted funds and the size of the organization to assess the prospects of the foundation. In addition, the foundation must increase voluntary disclosure to be more transparent in providing information about its foundation. With transparency, the foundation will more easily get the trust to receive funds that are beneficial to the foundation's survival

Cross-immunization against respiratory coronaviruses may protect children from SARS-CoV2: more than a simple hypothesis?

In January 2020, a new coronavirus was identified as responsible for a pandemic acute respiratory syndrome. The virus demonstrated a high infectious capability and not-neglectable mortality in humans. However, similarly to previous SARS and MERS, the new disease COVID-19 caused by SARS-CoV-2 seemed to relatively spare children and younger adults. Some hypotheses have been proposed to explain the phenomenon, including lower ACE2 expression in children, cross-immunization from measles/rubella/mumps and BCG-vaccination, as well as the integrity of respiratory mucosa. Herein, we hypothesize that an additional mechanism might contribute to children\u2019s relative protection from SARS-CoV-2, the cross-immunization conferred by previous exposures to other common respiratory coronaviruses. To support our hypothesis, we show a statistically significant similarity in genomic and protein sequences, including epitopes for B- and T-cell immunity, of SARS-CoV-2 and the other beta coronaviruses. Since these coronaviruses are highly diffused across pediatric populations, cross-reactive immunity might reasonably induce an at least partial protection from SARS-CoV-2 in children

Differences in osteoimmunological biomarkers predictive of psoriatic arthritis among a large Italian cohort of psoriatic patients

(1) Background: In literature it is reported that 20\u201330% of psoriatic patients evolve to psoriatic arthritis over time. Currently, no specific biochemical markers can either predict progression to psoriatic arthritis or response to therapies. This study aimed to identify osteoimmunological markers applicable to clinical practice, giving a quantitative tool for evaluating pathological status and, eventually, to provide prognostic support in diagnosis. (2) Methods: Soluble (serum) bone and cartilage markers were quantified in 50 patients with only psoriasis, 50 psoriatic patients with psoriatic arthritis, and 20 healthy controls by means of multiplex and enzyme-linked immunoassays. (3) Results: Differences in the concentrations of matrix metalloproteases (MMPs), tissue inhibitors of metalloproteinases (TIMPs), receptor activator of nuclear factor kappa-B-ligand (RANK-L), procollagen type I N propeptide (PINP), C-terminal telopeptide of type I collagen (CTx-I), dickkopf-related protein 1 (DKK1), and sclerostin (SOST) distinguished healthy controls from psoriasis and psoriatic arthritis patients. We found that MMP2, MMP12, MMP13, TIMP2, and TIMP4 distinguished psoriasis from psoriatic arthritis patients undergoing a systemic treatment, with a good diagnostic accuracy (Area under the ROC Curve (AUC) > 0.7). Then, chitinase-3-like protein 1 (CHI3L1) and MMP10 distinguished psoriasis from psoriatic arthritis not undergoing systemic therapy and, in the presence of onychopathy, MMP8 levels were higher in psoriasis than in psoriatic arthritis. However, in these latter cases, the diagnostic accuracy of the identified biomarkers was low (0.5 < AUC < 0.7). (4) Conclusions. By highlighting never exploited differences, the wide osteoimmunological biomarkers panel provides a novel clue to the development of diagnostic paths in psoriasis and psoriasis-associated arthropathic disease