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Nur wenige Studien haben bis dato untersucht, wie Holocaust-Organisationen soziale Medien in ihrer Öffentlichkeits- und Bildungsarbeit einsetzen. Diese Studie präsentiert die Resultate einer Literaturrecherche zur Nutzung von sozialen Medien für die Holocaust-Gedenkarbeit und -Erziehung sowie die Ergebnisse einer quantitativen Vorstudie zur Twitter-Nutzung von sechs Holocaust-Museen und -Organisationen in Deutschland und Italien.

We are proud to present the proceedings of the Fourth International Conference on Smart Learning Ecosystems and Regional Developments (SLERD 2019). Following a successful first edition in the East of Europe--Timisoara, Romania (2016)--a second edition in the West--Aveiro, Portugal (2017)--and a third edition in the North--Aalborg, Denmark (2018)--the fourth edition was in the South --Rome, Italy (2019)--covering all four cardinal points of the old continent. This fourth edition was co-organized by ASLERD, in collaboration with the Institute of Educational Technology of the National Research Council of Italy, Quasar Design University, ISIA Rome, and the University of Rome Tor Vergata's SPFS Department with the endorsement of the Ph.D. program in cultural heritage, learning and territory, in May 22-24, 2019.The conference welcomed researchers and practitioners from all over the world involved in the development of smart learning ecosystems, as engines of social innovation and territorial development. At the core, the adjective smart comprises terms like intelligent, purpose oriented, supportive, artful, clever and the like. Thus, smart does not necessarily include the usage of technology (neither does it exclude technology!). Smart is referred to learning ecosystems in ASLERD and SLERD contexts and, thus, does not simply mean "technology enhanced" (to include expert systems or AI). The smartness is a more complex multilayered construct related to the well-being of the players operating in the ecosystems that hopefully are also in relation to the territory (see Declaration of Timisoara, the Wikipedia page ofASLERD1, the proceedings of the previous SLERD conferences published by Springer and the special issues (N.16, N.17, N.20, N.27, N.31, N.35 and N.39 in preparation) devoted to SLERD by IxD&A Journal). Smartness is affected by the improvement of any relevant aspects of the learning processes and ecosystem functioning, especially if connected with territorial development and social innovation. Technologies are in this sense mediators. Hopefully, they should be included but they are not a "sine qua non". The achievement of the learning ecosystems' smartness is a process that needs a long-term vision, multidisciplinary competences, an attitude to understand people and contexts and to mediate point of views and a dynamic resilience to keep on track to achieve, step by step, the foreseen goals: in short, a design literacy from which emerge projects and processes capable to reify them, all aimed at achieving a people-centered smart education, social innovation and territorial development. Overall, we received 31 unique submissions from 18 countries, demonstrating the global interest for this research area and for the SLERD 2019 conference. Out of the total submissions, after a rigorous double-blind peer review and meta-review process, we accepted 12 full papers and 7 short papers. Additionally, we included five extended abstracts to show the breadth of the work in this research community. To complement the oral presentations of the papers, the SLERD 2019 program also included presentations of the best ideas from the 2019 international and local student contests (not included in these proceedings). These competitions challenged local and international students to propose ideas and proofs of concept/prototypes to make learning ecosystems smarter. The selected scientific papers aim to understand, conceive and promote innovative human-centric design and development methods, education/training practices, informal social learning and citizen-driven policies. The papers are organized mirroring the main conference sessions in six themes, namely (1) the virtue of design and that of technological environments; (2) schools: evaluation and design; (3) toward future technological tools and environments;(4) learning ecosystems and regional development; (5) schools: technologies and contexts; and (6) disabilities and interaction. SLERD 2019 contributes to foster the social innovation sectors, identifying and discussing ICT and economic development and deployment strategies alongside new policies for smarter proactive citizens. The proceedings are relevant to both researchers and policy makers. In summary, SLERD 2019 offered an exciting program that provided an excellent overview of the state of the art in smart learning ecosystems and was an occasion for bringing research forward and creating new networks. We are very proud of the final selection of papers, which would not have been possible without the effort and support of our excellent Conference and Program Committees, including more than50 international researchers. We would like to thank all the ones who, in different roles, have contributed their time to organize the event with enthusiasm and commitment.

Background: Chronic kidney disease has emerged as a strong cardiovascular risk factor, and in many current guidelines, it is already considered as a coronary heart disease (CHD) equivalent. Routinely, creatinine has been used as the main marker of renal function, but recently, cystatin C emerged as a more promising marker. The aim of this study was to assess the comparative cardiovascular and mortality risk of chronic kidney disease (CKD) using cystatin C-based and creatinine-based equations of the estimated glomerular filtration rate (eGFR) in participants of population-based and disease cohorts.Methods: The present study has been conducted within the BiomarCaRE project, with harmonized data from 20 population-based cohorts (n = 76,954) from 6 European countries and 3 cardiovascular disease (CVD) cohorts (n = 4982) from Germany. Cox proportional hazards models were used to assess hazard ratios (HRs) for the various CKD definitions with adverse outcomes and mortality after adjustment for the Systematic COronary Risk Evaluation (SCORE) variables and study center. Main outcome measures were cardiovascular diseases, cardiovascular death, and all-cause mortality.Results: The overall prevalence of CKD stage 3–5 by creatinine- and cystatin C-based eGFR, respectively, was 3.3% and 7.4% in the population-based cohorts and 13.9% and 14.4% in the disease cohorts. CKD was an important independent risk factor for subsequent CVD events and mortality. For example, in the population-based cohorts, the HR for CVD mortality was 1.72 (95% CI 1.53 to 1.92) with creatinine-based CKD and it was 2.14 (95% CI 1.90 to 2.40) based on cystatin-based CKD compared to participants without CKD. In general, the HRs were higher for cystatin C-based CKD compared to creatinine-based CKD, for all three outcomes and risk increased clearly below the conventional threshold for CKD, also in older adults. Net reclassification indices were larger for a cystatin-C based CKD definition. Differences in HRs (between the two CKD measures) in the disease cohorts were less pronounced than in the population-based cohorts.Conclusion: CKD is an important risk factor for subsequent CVD events and total mortality. However, point estimates of creatinine- and cystatin C-based CKD differed considerably between low- and high-risk populations. Especially in low-risk settings, the use of cystatin C-based CKD may result in more accurate risk estimates and have better prognostic value.

We are proud to present the proceedings of the Fourth International Conference on Smart Learning Ecosystems and Regional Developments (SLERD 2019). Following a successful first edition in the East of Europe--Timisoara, Romania (2016)--a second edition in the West--Aveiro, Portugal (2017)--and a third edition in the North--Aalborg, Denmark (2018)--the fourth edition was in the South --Rome, Italy (2019)--covering all four cardinal points of the old continent. This fourth edition was co-organized by ASLERD, in collaboration with the Institute of Educational Technology of the National Research Council of Italy, Quasar Design University, ISIA Rome, and the University of Rome Tor Vergata's SPFS Department with the endorsement of the Ph.D. program in cultural heritage, learning and territory, in May 22-24, 2019.

Objective: Classical robust optimization (cRO) in intensity-modulated proton therapy (IMPT) considers isocenter position and particle range uncertainties; anatomical robust optimization (aRO) aims to consider additional non-rigid positioning variations. This work compares the influence of different uncertainty sources on the robustness of cRO and aRO IMPT plans for head and neck squamous cell carcinoma (HNSCC). Methods: Two IMPT plans were optimized for twenty HNSCC patients who received weekly control CTs (cCT): cRO, using solely the planning CT, and aRO, including two additional cCTs. The robustness of the plans in terms of clinical target volume (CTV) coverage and organ at risk (OAR) sparing was analyzed considering stepwise the influence of (1) non-rigid anatomical variations given by the weekly cCT, (2) with fraction-wise added rigid random setup errors and (3) additional systematic proton range uncertainties. Results: cRO plans presented significantly higher nominal CTV coverage but are outperformed by aRO plans when considering non-rigid anatomical variations only, as cRO and aRO plans presented a median target coverage (D98%) decrease for the low-risk/high-risk CTV of 1.8/1.1 percentage points (pp) and -0.2pp/-0.3pp, respectively. Setup and range uncertainties had larger influence on cRO CTV coverage, but led to similar OAR dose changes in both plans. Considering all error sources, 10/2 cRO/aRO patients missed the CTV coverage and a limited number exceeded some OAR constraints in both plans. Conclusions: Non-rigid anatomical variations are mainly responsible for critical target coverage loss of cRO plans, whereas the aRO approach was robust against such variations. Both plans provide similar robustness of OAR parameters. Advances in knowledge: The influence of different uncertainty sources was quantified for robust IMPT HNSCC plans.

Purpose/Objective Classical robust optimization considers uncertainties in patient setup and particle range. Usually plan robustness is evaluated from calculation of perturbed dose distributions based on the planning CT, without considering potential anatomical changes that may occur during the treatment course. Our aim was to compare the overall plan robustness of classical robust optimization (cRO) with the recently proposed anatomical robust optimization (aRO) based on an integral multi-scenario evaluation, considering all types of uncertainties including anatomical variations. Material/Methods Datasets for 20 head and neck cancer patients, including a planning CT and weekly control CTs, were analyzed. Two intensity-modulated proton therapy (IMPT) plans were calculated: cRO, using solely the planning CT, and aRO, including additionally the first two control CTs in the plan optimization. For the robustness analysis, perturbed dose distributions with random setup uncertainties and fixed range uncertainty values of -3.5%, 0% and +3.5% were generated, drawing for each fraction n a random number from a Gaussian distribution around 0 mm with a standard deviation of 2.5 mm for the isocenter shift in each cardinal direction (xn, yn, zn). Moreover, in each fraction n the correspondent weekly control CT was used to consider the anatomical changes during therapy. 33 single-fraction perturbed doses were calculated and summed to generate a perturbed whole-treatment dose distribution. The procedure was repeated 10 times for each of the three range uncertainty values, resulting in 30 perturbed dose distributions per plan (Figure 1). Results Both nominal plans fulfilled the clinical objective for target coverage (D98% ≥ 95% of the prescribed dose). The median values calculated from the 30 perturbed dose distributions for each patient showed a reduction in the target coverage for the cRO plan, with mean (minimum) values of 94.9% (88.1%) and 95.4% (89.3%) for the low- and high-risk CTV, respectively, in comparison with 96.6% (92.0%) and 96.8% (93.6%), respectively, for aRO (Figure 2a). The variation in CTV coverage between the 30 scenarios, i.e. the width of the perturbed dose distributions, was found to be larger for cRO plans, with median (maximum) values of 1.9 (8.3) and 1.4 (5.6) for low- and high-risk CTV, respectively, in comparison with 1.4 (3.4) and 0.9 (5.2) for aRO plans, respectively. Moreover, the cRO case showed reduced robustness in comparison with aRO for some patients, where certain scenarios violate the clinical objective, as shown in Figure 2b. Conclusion Anatomical robust optimization showed superior plan robustness in comparison with the classical approach in a comprehensive multi-scenario evaluation. Anatomical variations play an important role in the overall plan robustness together with setup and range uncertainties, therefore their effect should not be underestimated or neglected.

Classical robust optimization considers uncertainties in patient setup and particle range. Usually plan robustness is evaluated from calculation of perturbed dose distributions based on the planning CT, without considering potential anatomical changes that may occur during the treatment course. Our aim was to compare the overall plan robustness of classical robust optimization (cRO) with the recently proposed anatomical robust optimization (aRO) based on an integral multi-scenario evaluation, considering all types of uncertainties including anatomical variations.

Purpose/Objective Robust optimization in proton therapy considers uncertainties in patient setup and particle range during the plan optimization. In general, however, anatomical changes occurring during the treatment course, potentially causing a degradation of the plan quality, are neglected. The aim of this study was to quantify the influence of these changes on the dose distribution for patients with bilateral head and neck cancer (HNC). Material/Methods Datasets from 20 HNC patients, consisting of a planning CT and weekly control CTs (cCT), were analyzed. Intensity-modulated proton therapy (IMPT) plans with minimax robust optimization were calculated, accounting 3 mm and 3.5% for setup and range uncertainty, respectively. Prescribed doses to the low- and high-risk clinical target volume (CTV) were 57 and 70 Gy(RBE), respectively, delivered in 33 fractions. The organs at risk (OAR) spinal cord, brainstem, parotid glands, larynx, pharyngeal constrictor and esophageal inlet muscle were considered for plan optimization. Weekly cumulative doses, taking the anatomical variations of the cCTs into account, were compared with the nominal plan. When a reduction in target coverage and/or increased dose to OARs was detected, a plan adaptation was performed on the cCT where the dose degradation was observed. Furthermore, for these patients an additional robust plan was calculated, taking also anatomical changes from the first two cCTs into account in the robust optimization. It was evaluated if a subsequent plan adaptation would still be necessary. Results Nominal plans fulfilled the clinical specifications of D98% ≥ 95% of the prescribed dose to the CTVs (range 96.58-98.81% for low-risk CTV and 96.83-98.76% for high-risk CTV). During the treatment course, anatomical changes lead to reduced weekly cumulative D98% values in five patients (25%; minimum 90.17% for low-risk CTV and 89.19% for high-risk CTV). Doses in OARs remained below the clinical constrains during the treatment course. One treatment adaptation was performed for each of these five patients, which allowed a target coverage improvement (range 97.68-99.72% for low-risk CTV and 95.89-98.46% for high-risk CTV). Total cumulative doses including adaptation were acceptable (range 96.67-98.37% for low-risk CTV and 95.11-97.39% for high-risk CTV, see Figure 1a). The results for the more sophisticated robust plan, considering the first two cCTs, were diverse: whereas plan adaption became obsolete in one patient, the total cumulative dose would, without adaptation, still have been below clinical constraints in another (Figure 1b and 2). Conclusion In a substantial number of patients, robust optimization only is not sufficient to account for anatomical changes occurring during the treatment course, resulting in severe target coverage degradation. Assessment of the cumulative weekly doses allowed detection of target coverage loss. The importance of frequent in-treatment imaging is underlined.

Purpose or Objectives The success of light ion radiotherapy is crucially sensitive to daily setup variation and anatomic changes. Irradiation of the esophagus, in particular, suffers from significant target mobility [1]. Since its commissioning, the proton facility at our institute has been using daily kV imaging for patient setup based on bony anatomy, supplemented with in-room dual-energy CT scans as needed. We assessed target positioning with the aid of kV-visible fiducial markers placed around esophageal tumors by tracking their displacement from the planned location throughout treatment. Materials and Methods Five patients with esophageal cancer scheduled for neoadjuvant (4) or definite (1) radiochemotherapy using protons (all male; age 52-64 years; tumor of the middle or lower third of the esophagus; mean GTV: 24 ml) underwent endoscopic ultrasound-guided trans-esophageal placement of gold fiducial markers (VisiCoilTM, IBA Dosimetry, Belgium; diameter 0.35 mm, lengths 5 or 10 mm) demarcating the proximal and distal tumor borders. Pairs of orthogonal kV images taken in treatment position were retrieved for 104/110 fractions. Markers were manually located in the images and their position in 3D determined by triangulation [2]. Vertebral landmarks were similarly reconstructed and used to register kV imaging to the planning CTs. Triangulation errors were estimated per marker from the geometrical compatibility of image point pairs with single 3D points. All calculations were carried out in custom software based on SciPy [3]. Results Marker implantation proceeded without complications and placement of the distal marker was hindered by an obstructing tumor in one case only. All but one marker remained stable throughout treatment, and their visibility in kV images was generally limited, but sufficient. Marker-induced dose perturbations were not clinically relevant. Figure 1 shows example triangulation results for one patient. Overall the standard deviation [inter-quartile range] of the distributions of marker excursions was 2.6 [2.1], 1.8 [2.0], and 3.1 [3.6] mm in the lateral, sagittal, and longitudinal directions, respectively. A Friedman test failed to reveal significant differences between the directions (p>0.7). Inter-marker distances varied by a few mm during treatment with no discernible trend. Triangulation errors ranged from 0.9 to 7.1 mm. One notable instance of marker-indicated target displacement by 26 mm was observed (Fig. 2). This prompted the acquisition of a control CT in treatment position, which revealed an overlap of the planned and actual GTVs of merely 4% (Jaccard index 0.02). The dosimetric impact would have been a reduction of the mean and near-min (D98%) doses by 6% and 47%, respectively. Conclusion Exclusive reliance on bony anatomy for positioning of esophageal cancer patients cannot prevent occasional target misalignments. Gold fiducials (e.g., VisiCoilTM) and daily kV imaging are valuable tools for target-centric setup verification.

Purpose or Objective In patients with locally advanced unresectable pancreatic cancer, neoadjuvant or primary radiochemotherapy (RCT) are alternative treatment options. Today, treatment outcome after RCT is poor, in part due to radiosensitive organs at risk (OARs) limiting the prescribed dose to the target volume. Proton beam techniques enable delivering high radiation doses to the target volume while sparing OARs. In this in-silico feasibility study, we assessed different strategies for dose escalation to 66Gy(RBE) using a simultaneous integrated boost technique and robust multi-field optimized intensity modulated (rMFO-IMPT) pencil beam scanned protons and evaluated their robustness. Material and Methods For each of six pancreatic cancer patients, four different rMFO-IMPT plans were optimized on free-breathing treatment planning CTs using the RayStation treatment planning system (V5.99, RaySearch Laboratories AB, Sweden). These planning strategies consisted of equally-weighted beams: (S1) two posterior oblique (PO) beams, (S2) lateral right beam and left PO beam, (S3) two PO beams plus right non-coplanar beam, and (S4) three non-coplanar beams. At least 95% of 66Gy(RBE) in 30 fractions was prescribed to 95% of the boost volume (GTV), and 51Gy(RBE) was prescribed to 95% of the CTV (GTV with margin and elective volume). A dose fall-off range of 10 mm around the GTV was preset, and setup and range uncertainty parameters of 3 mm and of 3.5% for GTV and CTV coverage were chosen, respectively. The OAR dose constraints adhered to local guidelines and QUANTEC. For each patient and planning strategy, conformity and homogeneity index (CI, HI) of target doses as well as doses to GTV, CTV, and OARs were calculated. Together with additional robustness evaluations of the worst-case scenarios (±3 mm, ±3.5%) the best planning strategy for dose escalation was sought for. Results All nominal plans reached the prescribed dose to the GTV and CTV (Fig. 1a). The CI of all planning strategies was similar (mean CI: 0.6-0.7) even though S3 and S4 were more homogeneous. In some patients, S1 was associated with excess dose to the kidneys (Fig. 1b). Radiation doses (D2%, V45Gy) to the duodenum exceeded the constraints since that OAR was next to or within the target volume, while for the remaining gastrointestinal organs radiation doses were similar for the different strategies and within preset limits (Fig. 1c, d). Overall, S3 and S4 showed the best dose distribution for all OARs. Robustness evaluation of all plans revealed that in total only 38% of the D95% values (S1: 31%, S2: 31%, S3: 39%, S4: 51%) in the worst-case scenarios fulfilled the dose requirement for the GTV leading to an insufficient robustness. Conversely, more than 90% of the D95% values to the CTV were robust against uncertainties, with S3 being most robust (97%). Conclusion Disregarding the inter- and intra-fractional organ motion, dose escalation is possible using robust MFO-IMPT plans with three beams, of which at least one non-conformal.