Myopericytoma is a benign tumor with the most common presentation as a well-circumscribed, slow-growing mass. It is frequently misdiagnosed as a sarcoma. We presented a 23-year-old patient with a history of a sciatic pain of the right leg. A careful physical examination discovered tumor-like mass in the posterior part of the thigh. Neurological finding showed a reduction of myotatic reflexes on the right leg with a weaker muscle strength on the right leg. The right leg musculature was slightly hypotrophic in the range of 2-3 cm comparing to left leg. Initially electrophysiological and radiological diagnostic with magnetic resonance imaging (MRI) of the lumbar spine, pelvis and thighs were normal. Magnetic resonance imaging of the right thigh discovered a slow growing 2.1 × 3.8 cm sized mass that was initially described by radiologist as a neurinoma. Patient was admitted to department of neurosurgery and operated on for a tumor removal. Tumor was located intimately to femur and sciatic nerve and after careful dissection completely removed. Patient was doing well after surgery and discharge after three days from the hospital. In the postoperative period the symptoms disappeared. Histopathology showed a myopericitoma. Postoperative MRI after three months of follow up showed no tumor residues, and after 6 and 12 months there was no tumor recurrence. Myopericytoma behave in a benign fashion, but, because local recurrences and rarely metastases may occur in atypical and malignant neoplasms, a careful follow-up after radical resection is recommended.

ABSTRACT A novel, efficient method to account for multivariate probability density functions (PDFs) in the context of the flamelet generated manifolds (FGM) approach in a large eddy simulation (LES) framework is presented and discussed. It consists of applying the ‘Correlation Set by Simulated Annealing (CSSA)’ algorithm on univariate samples of each control variable to recombine them into multivariate samples in joint space, while accounting for the needed covariances. This is done on the fly and on a cell-by-cell basis. Thereby, the assumption of statistical independence of the control variables has been relaxed. The PDF is represented in a discrete manner and the integration is replaced through ensemble averaging. Consequently, the shape of the PDF no longer appears in the look-up table. The algorithm has been validated in the context of LES calculations of two configurations. Compared to a conventional pre-integrated FGM approach, the required CPU time has increased only modestly.

Petri nets are a formalism for modelling and reasoning about the behaviour of distributed systems. Recently, a reversible approach to Petri nets, Reversing Petri Nets (RPN), has been proposed, allowing transitions to be reversed spontaneously in or out of causal order. In this work we propose an approach for controlling the reversal of actions of an RPN, by associating transitions with conditions whose satisfaction/violation allows the execution of transitions in the forward/reversed direction, respectively. We illustrate the framework with a model of a novel, distributed algorithm for antenna selection in distributed antenna arrays.

Distributed antenna selection for distributed massive multiple input multiple output (MIMO) communication systems reduces computational complexity compared to centralized approaches, and provides high fault tolerance while retaining diversity and spatial multiplexity. We propose a novel distributed algorithm for antenna selection and show its advantage over existing centralized and distributed solutions. The proposed algorithm is shown to perform well with imperfect channel state information, and to execute a small number of simple computational operations per node, converging fast to a steady state. We base it on reversing Petri nets, a variant of Petri nets inspired by reversible computation, capable of both forward and backward execution while obeying conservation laws.

Recent advances in neuroscience have revealed many principles about neural processing. In particular, many biological systems were found to reconfigure/recruit single neurons to generate multiple kinds of decisions. Such findings have the potential to advance our understanding of the design and optimization process of artificial neural networks. Previous work demonstrated that dense neural networks are needed to shape complex decision surfaces required for AI-level recognition tasks. We investigate the ability to model high dimensional recognition problems using single or several neurons networks that are relatively easier to train. By employing three datasets, we test the use of a population of single neuron networks in performing multi-class recognition tasks. Surprisingly, we find that sparse networks can be as efficient as dense networks in both binary and multi-class tasks. Moreover, single neuron networks demonstrate superior performance in binary classification scheme and competing results when combined for multi-class recognition.

The problem related to the inadequate position of workers during lifting heavy loads is the everyday life of many environments, such as industrial halls or warehouses, which often results in the deepening of the worker's spine load problem. An analysis of such a workplace was carried out in this paper. The workloads at specific body zones were determined, whether they were within the prescribed limits or exceeded it, and on that basis a redesign of the workspace was made in accordance to the anthropological values of the model.

Aim of the research was measuring the heat transfer coefficient of the external walls at the Mechanical Engineering Faculty building with heat flow method, in order to obtain the real value of heat transfer coefficient. After performing the measuring according to the ISO 9869 for in-situ measurement, the average measured heat transfer coefficient was 0.23 W/m2K, which is lower value compared to the calculated one, 0.33 W/m2K, according to the program (KiExpert). Difference between values is the result of limitations in selection of materials and because heat accumulation in building elements is not sufficiently considered in algorithms of the program.

Background: Despite being considered as a distinct diagnostic category in the current ILAR classification criteria, Juvenile Psoriasic Arthritis (JPsA) is known to be a heterogeneous clinical entity, with growing evidence suggesting at least two age-based distinct subgroups(1) Objectives: To identify and characterize subgroups of patients classified as JPsA according to the ILAR criteria and their possible differences in outcomes. Methods: Cross-sectional data from patients enrolled in The EPidemiology, treatment and Outcome of Childhood Arthritis (EPOCA) study and classified as JPsA according to ILAR criteria (n=308) were analyzed. Latent class analysis (LCA) was used to identify subgroups of subjects with similar profiles ILAR criteria for JPsA (presence at onset of psoriasis, dactylitis, nail changes, first-degree relative with psoriasis) and age of arthritis onset. Multinomial logistic regression (three-step method) was performed to explore differences across the obtained classes in clinical-laboratoristic features at onset and outcomes measures collected at visit, namely JADAS scores, VAS-measured Pain, Overall Well-Being (PGA) Pediatric Rheumatology Quality of Life Scale (PRQL). In patients with disease duration more than 2 years (n=233), the relation with Articular and Extraarticular Juvenile Arthritis Damage Index (JADI) was also assessed. Results: LCA revealed 5 classes: 1) late-onset patients with psoriasis, characterized by higher frequency of axial involvement at visit (n = 121); 2) early-onset patients with psoriasis, more likely to be ANA-positive (n = 66); 3) young females with dactylitis at onset and family history of psoriasis, more likely to present with symmetric joint involvement (n = 62); 4) subjects with nail changes and family history of psoriasis(n=34); 5) patients exhibiting dactylitis and nail changes at onset, mostly males, with higher rates of HLA-B27 positivity, small joint involvement and enthesitis at visit (n = 25). Class 1 is associated with higher scores of JADAS10, pain, PGA and JQ; these group also shows higher JADI-A than Class 3. Extraarticular damage is worst for Class 2 subjects. Conclusion: The data driven clustering approach revealed several subgroups, confirming the heterogeneity of JPSA in a multinational cohort. Later-onset subjects with psoriasis have more aggressive disease, being clearly distinct from early-onset ANA-positive patients with psoriasis. The results suggest the need to revise the current classification in order to identify groups that may benefit from different therapeutic choices. References [1] Stoll ML, Nigrovic PA. Clin Dev Immunol. 2006;13(2–4):377–80. Disclosure of Interests: Hala Etayari: None declared, Arūnė Ramanauskiene: None declared, Alessandra Alongi: None declared, Yaryna Boyko: None declared, Yosef Uziel: None declared, Tadej Avcin: None declared, Pierre Quartier Consultant for: AbbVie, Chugai-Roche, lilly, Novartis, Novimmune, Sanofi, and SOBI, Consultant for: AbbVie, Chugai-Roche, Lilly, Novartis, Novimmune, Sanofi, and SOBI, Speakers bureau: AbbVie, BMS, Chugai-Roche, Novartis, Pfizer, and SOBI, Speakers bureau: AbbVie, BMS, Chugai-Roche, Novartis, Pfizer, and SOBI, Nicolino Ruperto Grant/research support from: The Gaslini Hospital, where NR works as full-time public employee, has received contributions (> 10.000 USD each) from the following industries in the last 3 years: BMS, Eli-Lilly, GlaxoSmithKline, F Hoffmann-La Roche, Janssen, Novartis, Pfizer, Sobi. This funding has been reinvested for the research activities of the hospital in a fully independent manner, without any commitment with third parties., Consultant for: Received honoraria for consultancies or speaker bureaus (< 10.000 USD each) from the following pharmaceutical companies in the past 3 years: Ablynx, AbbVie, Astrazeneca-Medimmune, Biogen, Boehringer, Bristol-Myers Squibb, Eli-Lilly, EMD Serono, GlaxoSmithKline, Hoffmann-La Roche, Janssen, Merck, Novartis, Pfizer, R-Pharma, SanofiServier, Sinergie, Sobi and Takeda., Speakers bureau: Received honoraria for consultancies or speaker bureaus (< 10.000 USD each) from the following pharmaceutical companies in the past 3 years: Ablynx, AbbVie, Astrazeneca-Medimmune, Biogen, Boehringer, Bristol-Myers Squibb, Eli-Lilly, EMD Serono, GlaxoSmithKline, Hoffmann-La Roche, Janssen, Merck, Novartis, Pfizer, R-Pharma, SanofiServier, Sinergie, Sobi and Takeda., Angelo Ravelli Grant/research support from: Angelini, AbbVie, Bristol-Myers Squibb, Johnson & Johnson, Novartis, Pfizer, Reckitt Benkiser, and Roche, Consultant for: Angelini, AbbVie, Bristol-Myers Squibb, Johnson & Johnson, Novartis, Pfizer, Reckitt Benkiser, and Roche, Speakers bureau: Angelini, AbbVie, Bristol-Myers Squibb, Johnson & Johnson, Novartis, Pfizer, Reckitt Benkiser, and Roche, Alessandro Consolaro Grant/research support from: AbbVie, Pfizer,

9574 Background: The introduction of immune checkpoint inhibitors (ICIs) or therapies targeting the MAPK-pathway (MAPKis) has significantly improved clinical outcomes in metastatic melanoma patients. Still, a large proportion of the patients become resistant to therapy and there is a need for treatment predictive biomarkers. The aim of this study was to analyze the treatment predictive biomarkers based on the plasma proteome of patients with metastatic melanoma treated with ICIs or MAPKis. Methods: We analyzed serial plasma samples from 48 patients with metastatic melanoma collected; 24 patients were treated with ICIs and with MAPKis, respcetively. A non-biased, high-resolution isoelectric focusing of peptides-liquid chromatography-mass spectrometry (HiRIEFLC-MS/MS)-based method, and with proximity ligation assays (PEA) targeting 92 immuno-oncology-related proteins were used.We analyzed the change in protein levels during treatment with a paired t-test, and their association with progression free survival (PFS) with Cox proportional hazards models. Results: HiRIEFLC-MS/MS detected 1,835 proteins.We detected statistically-significant log2-fold-changes in 109 protein levels out of 1,160 proteins tested (not corrected for multiple testing). PDCD-1 had the highest log2-fold change (FC = 1.27) after treatment (p = 0.02). After stratifying for treatment type, PDCD-1 levels increased in patients treated with ICIs (FC = 2.13, p= 0.0008), but not in MAPKis-treated patients. PEA analyses confirmed this observation. The PEA panel showed association between 44 proteins and shorter PFS (pcoefficient <0.05, pLRT<0.05, qLRT<0.05), among them: LGALS1, CSF1, VEGFA, CASP8, CCL2, TNFSF14, ANGPT2, IL10, IL6, and ADGRG1. Of these, increase in plasma levels during treatment of LGALS1, CCL2 and ADGRG1 were associated with longer PFS. HiRIEF LC-MS/MS detected 69 proteins associated with PFS (pcoefficient< 0.05, pLRT< 0.05, qLRT < 0.05). Conclusions: By using HiRIEFLC-MS/MS, we could detect putative treatment predictive proteins in plasma from patients with metastatic melanoma treated with ICIs or MAPKis. Our findings require further validation.

In 2018, Croatia reported the largest outbreak of West Nile virus (WNV) infections as well as the re-occurrence of human Usutu virus (USUV) infections. For the first time, fatal WNV and USUV infections were detected in wild birds. We analysed epidemiological characteristics and molecular epidemiology of WNV and USUV infections detected during 2018 transmission season. From April to November, 178 patients with neuroinvasive disease and 68 patients with febrile disease were tested for WNV and USUV. Viral RNA was detected in cerebrospinal fluid (CSF) and urine samples using a real-time RT-PCR. Positive samples were tested by nested RT-PCR and nucleotide sequencing. IgM/IgG antibodies were detected in serum/CSF samples using ELISA with confirmation of cross-reactive samples by virus neutralization test (VNT). WNV neuroinvasive disease was confirmed in 54 and WNV fever in seven patients from 10 continental Croatian counties. Areas affected in 2018 were those in which cases occurred in previous seasons, while in three areas human cases were reported for the first time. Phylogenetic analysis of six strains from patients residing in different geographic areas showed circulation of WNV lineage 2. In three patients, neuroinvasive USUV infection was confirmed by RT-PCR or VNT. Sequence analysis of one detected strain revealed USUV Europe 2 lineage. During the same period, a total of 2,574 horse and 1,069 poultry serum samples were tested for WNV antibodies using ELISA. Acute asymptomatic WNV infection (IgM antibodies) was documented in 20/0.7% horses. WNV IgG antibodies were found in 307/11.9% horses and in 125/12.7% poultry. WNV RNA was detected in two goshawks and USUV RNA was detected in one blackbird from north-western Croatia. In the Zagreb area, 3,670 female mosquitoes were collected. One Culex pipiens pool collected in July tested positive for USUV RNA. Our results highlight the importance of continuous multidisciplinary 'One health' surveillance of these emerging arboviruses.

In order to be used for skill development and skill maintenance, virtual environments require accurate simulation of the physical phenomena involved in the process of the task being trained. The accuracy needs to be conveyed in a multimodal fashion with varying parameterisations still being quantified, and these are a function of task, prior knowledge, sensory efficacy and human perception. Virtual reality (VR) has been integrated from a didactic perspective in many serious games and shown to be effective in the pedological process. This paper interrogates whether didactic processes introduced into a VR serious game, by taking advantage of augmented virtuality to modify game attributes, can be effective for both beginners and experts to a task. The task in question is subjective performance in a clay pigeon shooting simulation. The investigation covers whether modified game attributes influence skill and learning in a complex motor task and also investigates whether this process is applicable to experts as well as beginners to the task. VR offers designers and developers of serious games the ability to provide information in the virtual world in a fashion that is impossible in the real world. This introduces the question of whether this is effective and transfers skill adoption into the real world and also if a-priori knowledge influences the practical nature of this information in the pedagogic process. Analysis is conducted via a between-subjects repeated measure ANOVA using a 2×2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2 \times 2$$\end{document} factorial design to address these questions. The results show that the different training provided affects the performance in this task (N=57\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N=57$$\end{document}). The skill improvement is still evidenced in repeated measures when information and guidance is removed. This effect does not exist under a control condition. Additionally, we separate by an expert and non-expert group to deduce if a-priori knowledge influences the effect of the presented information, it is shown that it does not.