The majority of people with Autism Spectrum Disorder (ASD) exhibit difficulties in social communication and behavior, which hinder their learning capability, amid others. Among technological solutions for people with ASD, serious games are frequently used to enhance learning of specific skills and instructional contents. However, because of heterogeneity in applications and game design, few studies have investigated their use in training daily activities. This paper presents a 3D personalized serious game we developed and validated to help ASD patients practice with shopping activities. Personalized training is paramount in people with ASD, thus several elements of this game were personalized to improve engagement and therefore the effectiveness of the virtual training. In order to assess the validity of the game, ten subjects (age $\text{11.9} \pm \text{2.7}$, 20% female) with ASD played ten sessions of the serious game, once per week. The participants underwent a real-life experience pre- and post-training in a real-life supermarket. Changes in daily living skills among participants were evaluated through specific tools: a form based on the International Classification of Functioning, Disability and Health for Children and Youth; and the Vineland Adaptive Behavior Scale II. Significant improvements (p$< $0.05) were detected in the main skills trained with the serious game, especially in learning the shopping procedure, directing attention, and problem-solving skills. These findings suggest that personalized serious games can represent a prominent tool to enhance daily living skills, but future work should clinically validate their efficacy.

Performance of neural networks greatly depends on quality, size and balance of training dataset. In a real environment datasets are rarely balanced and training deep models over such data is one of the main challenges of deep learning. In order to reduce this problem, methods and techniques are borrowed from the traditional machine learning. Conversely, generative adversarial networks (GAN) were created and developed, a relatively new type of generative models that are based on game theory and consist of two neural networks, a generator and a discriminator. The generator’s task is to create a sample from the input noise that is based on training data distribution and the discriminator should detect those samples as fake. This process goes through a finite number of iterations until the generator successfully fools the discriminator. When this occurs, sample becomes a part of new (augmented) dataset. Even though the original GAN creates unlabeled samples, variants that soon appeared removed that limitation. Generating artificial data through these networks appears to be a meaningful solution to the imbalance problem since it turned out that artificial samples created by GAN are difficult to differentiate from the real ones. In this manner, new samples of minority class could be created and dataset imbalance ratio lowered.

The aim of the study is to investigate consumer attitudes towards specific Customer Social Responsibility Activities in Bosnia and Herzegovina. In order to support this research, a case study method, combined with qualitative and quantitative research methods (referenced survey) was used. To get an insight into the companies’ perspective, when it comes to an engagement in the employment practices, as an integral part of Corporate Social Responsibility, data regarding “The Most Desirable Employer” project- “Najpoželjniji poslodavac”, organized by Kolektiv d.o.o.-MojPosao.ba, for years 2020, 2019 and 2018 will be analyzed. The study should illustrate the exact scenario of customer loyalty in Bosnia and Herzegovina to the companies included in CSR activities and contribute to an advancement of overall knowledge in the field of CSR in Bosnia and Herzegovina. The directing outcome uncovers those corporate capacities have a critical part in fortifying the relationship between corporate social responsibility drives and customer trust in Bosnia and Herzegovina, in light of the fact that high corporate capacities with professional corporate social responsibility actions lead to high faithfulness of customers. The examination features the meaning of the corporate social responsibility activities, which are obligatory for authoritative achievement and guides the policymakers of companies, supervisors, and researchers.

The European Synchrotron Radiation Facility (ESRF) has recently commissioned the new Extremely Brilliant Source (EBS). The gain in brightness as well as the continuous development of beamline instruments boosts the beamline performances, in particular in terms of accelerated data acquisition. This has motivated the development of new access modes as an alternative to standard proposals for access to beamtime, in particular via the “block allocation group” (BAG) mode. Here, we present the recently implemented “historical materials BAG”: a community proposal giving to 10 European institutes the opportunity for guaranteed beamtime at two X-ray powder diffraction (XRPD) beamlines—ID13, for 2D high lateral resolution XRPD mapping, and ID22 for high angular resolution XRPD bulk analyses—with a particular focus on applications to cultural heritage. The capabilities offered by these instruments, the specific hardware and software developments to facilitate and speed-up data acquisition and data processing are detailed, and the first results from this new access are illustrated with recent applications to pigments, paintings, ceramics and wood.

Simple Summary Head and neck cancer is the sixth most common cancer type worldwide, comprising tumors of the upper aero/digestive tract. Approximately 50% of these cancers originate in the oral cavity. Depending on disease stage, oral cancer patients are treated with single-modality surgery, or in combination with radiotherapy with or without chemotherapy. Despite advances in these modalities, the 5-year survival rate is merely 50%. Therefore, implementation of targeted therapies, directed against signaling molecules, has gained attention. One potential target is the MET protein, which can be present on the surface of cancer cells, orchestrating aggressive behavior. As cancer cells can shed the extracellular part of MET from their surface, it is important to identify for MET positive patients whether they possess the entire and/or only the intracellular part of the receptor to assess whether targeted therapies directed against the extracellular, intracellular, or both parts of MET need to be implemented. Abstract The receptor tyrosine kinase MET has gained attention as a therapeutic target. Although MET immunoreactivity is associated with progressive disease, use of targeted therapies has not yet led to major survival benefits. A possible explanation is the lack of companion diagnostics (CDx) that account for proteolytic processing. During presenilin-regulated intramembrane proteolysis, MET’s ectodomain is shed into the extracellular space, which is followed by γ-secretase-mediated cleavage of the residual membranous C-terminal fragment. The resulting intracellular fragment is degraded by the proteasome, leading to downregulation of MET signaling. Conversely, a membrane-bound MET fragment lacking the ectodomain (MET-EC-) can confer malignant potential. Use of C- and N-terminal MET monoclonal antibodies (moAbs) has illustrated that MET-EC- occurs in transmembranous C-terminal MET-positive oral squamous cell carcinoma (OSCC). Here, we propose that ectodomain shedding, resulting from G-protein-coupled receptor transactivation of epidermal growth factor receptor signaling, and/or overexpression of ADAM10/17 and/or MET, stabilizes and possibly activates MET-EC- in OSCC. As MET-EC- is associated with poor prognosis in OSCC, it potentially has impact on the use of targeted therapies. Therefore, MET-EC- should be incorporated in the design of CDx to improve patient stratification and ultimately prolong survival. Hence, MET-EC- requires further investigation seen its oncogenic and predictive properties.