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Geographic information system (GIS) software has been essential for visualising and determining heating and cooling requirements, sources of industrial excess heat, natural bodies of water, and municipalities. Policymakers highly encourage the use of GIS software at all administrative levels. It is expected that the heating and cooling demand will continue to increase. For a reliable heat and cooling supply, we must identify heat sources that can be used to provide heat or for removing surplus heat. We propose a method for identifying possible heat sources for large heat pumps and chillers that combines geospatial data from administrative units, industrial facilities, and natural bodies of water. Temperatures, capacities, heat source availability, as well as their proximity to areas with high demand density for heating and cooling were considered. This method was used for Estonia, Latvia and Lithuania. Excess heat from heat generation plants and industries, sewage water treatment plants, and natural heat sources such as rivers, lakes and seawater were included. The study’s findings provide an overview of possible industrial and natural heat sources, as well as their characteristics. The potential of the heat sources was analysed, quantified, and then compared to the areas of heating and cooling demand.

Large-scale heat pumps (HPs) and refrigeration plants are essential technologies to decarbonise the heating and cooling sector. District heating and cooling (DHC) can be supplied with low carbon footprint, if power generated from renewable energy sources is used. The simultaneous supply of DHC is often not considered in energy planning, nor the characteristics of the heat source and sink. Simplified approaches may not reveal the true potential of HPs and chillers. In this paper, different heat sources and sinks and their characteristics were considered for the simultaneous supply of DHC based on large-scale HPs and refrigeration plants. An optimization model was developed based on mixed-integer linear programming. The model is able to identify ideal production and storage capacities, heat sources and sinks based on realistic hourly operation profiles. By doing so, it is possible to identify the most economical or sustainable supply of DHC using electricity. The optimization model was applied to the Nordhavn area, a new development district of Copenhagen, Denmark. The results show that a combination of different heat sources and sinks is ideal for the case study. A HP that uses the district cooling network as a heat source to supply DHC was shown to be very efficient and economical. Groundwater and sewage water HPs were proposed for an economical supply of district heating. The Pareto frontier showed that a large reduction in annual CO2 emissions is possible for a relatively small increase in investments.

Excess heat is present in many sectors, and its utilization could reduce the primary energy use and emission of greenhouse gases. This work presents a geographical mapping of excess heat, in which excess heat from the industry and utility sector was distributed to specific geographical locations in Denmark. Based on this mapping, a systematic approach for identifying cases for the utilization of excess heat is proposed, considering the production of district heat and process heat, as well as power generation. The technical and economic feasibility of this approach was evaluated for six cases. Special focus was placed on the challenges for the connection of excess heat sources to heat users. To account for uncertainties in the model input, different methods were applied to determine the uncertainty of the results and the most important model parameters. The results show how the spatial mapping of excess heat sources can be used to identify their utilization potentials. The identified case studies show that it can be economically feasible to connect the heat sources to the public energy network or to use the heat to generate electricity. The uncertainty analysis suggests that the results are indicative and are particularly useful for a fast evaluation, comparison and prioritization of possible matches. The excess heat temperature and obtainable energy price were identified as the most important input parameters.

The paper presents a modelling framework that may be used to plan the integration of large-scale HPs in district heating (DH) areas. By use of the methodology both optimal HP capacities to be installed and optimal choice of heat source to be used during the year are identified by minimizing total cost of ownership including investment and operational costs. The modelling framework uses mixed-integer linear programming and hourly calculations over one year. Seasonal variations of the heat source temperatures, capacity limitations and HP coefficient of performance as well as technical constraints were taken into account. The DH network of Tallinn, Estonia, was used as a case study. Six different heat source types were identified for 13 potential locations of large-scale HPs. The results showed that the integration of large-scale HPs in the DH network of Tallinn is economically feasible. It was found that 122 MW HP capacity could be installed without compromising the operation of sustainable base load units. The heat sources needed for obtaining this solution were sewage water, river water, ambient air, seawater and groundwater. It was further shown that the Lorenz efficiency depends on the variations of heat source temperatures.

The paper presents a modelling framework that may be used to plan the integration of large-scale HPs in district heating (DH) areas. By use of the methodology both optimal HP capacities to be installed and optimal choice of heat source to be used during the year are identified by minimizing total cost of ownership including investment and operational costs. The modelling framework uses mixed-integer linear programming and hourly calculations over one year. Seasonal variations of the heat source temperatures, capacity limitations and HP coefficient of performance as well as technical constraints were taken into account. The DH network of Tallinn, Estonia, was used as a case study. Six different heat source types were identified for 13 potential locations of large-scale HPs. The results showed that the integration of large-scale HPs in the DH network of Tallinn is economically feasible. It was found that 122 MW HP capacity could be installed without compromising the operation of sustainable base load units. The heat sources needed for obtaining this solution were sewage water, river water, ambient air, seawater and groundwater. It was further shown that the Lorenz efficiency depends on the variations of heat source temperatures.

Neutrons, owing to their unique properties, serve as indispensable probes for investigating the structure and dynamics of materials across various length scales. The scientific community utilizing neutron research infrastructures encompasses a diverse range of disciplines, making it challenging to quantify its scientific and societal impact. To address this challenge, we apply Natural Language Processing (NLP) and machine learning techniques to analyze the scientific output of the European neutron science community. Leveraging open-source software toolkits, our method allows for the quantitative assessment of community evolution and research focus. Our analysis reveals consistent growth in the neutron community despite a reduction in sources, underscoring the enduring significance of neutron methods in scientific research. Furthermore, an increase in unique authors and an even distribution of publications across diverse scientific topics highlight the community’s interdisciplinary nature and collaborative spirit. While this study emphasizes neutron scattering, our methodology holds promise for a broad range of scientific communities reliant on Large Research Infrastructures (LRIs), offering opportunities for collaboration, optimization of experimental approaches, and informed decision-making by governmental and funding bodies.

Purpose After vertical parasagittal hemispherotomy a restricted diffusion is often seen ipsilaterally and even distant from the adjacent resection margin. This retrospective cohort study analyses the anatomic site and the time course of the diffusion restriction after vertical parasagittal hemispherotomy. Methods Fifty-nine patients were included into this study, all of them having had one pre-operative and at least one post-operative MRI, including diffusion imaging at b‑values of 0 and 1000 s/mm 2 with a calculated ADC. Results Diffusion restriction occurred exclusively on the operated site in all patients. In the basal ganglia, diffusion restriction was present in 37 of 38 patients at the first postoperative day with a duration of 38 days. In the midbrain, the posterior limb of the internal capsule and the thalamus, a restricted diffusion became postoperatively prominent at day 9 in all three localizations, with a duration of 36, 34 and 36 days, respectively. The incidence of thalamic lesions was lower if a preoperative damage had occurred. Conclusion The restricted diffusion in the basal ganglia resembles direct effects of the operation at its edges, whereas the later appearing diffusion restriction in the midbrain and the posterior limb of the internal capsule rather belong to a degeneration of the descending fibers being transected by the hemispherotomy in the sense of a Wallerian degeneration. The presence of preoperative hemispheric lesions influences the development of diffusion restriction at subacute fiber degeneration.

Background/Aim: Liposarcomas (LS) are one of the most common entities within the heterogenous group of soft tissue sarcomas. The aim of this study was to identify prognostic indicators in patients with LS of the extremities and truncal wall. Patients and Methods: We analysed the influence of potential prognostic factors on local recurrence-free survival (LRFS) and overall survival (OS) in 181 patients who were suitable for surgical treatment with curative intent. Results: The median follow-up period was 7.1 years. The 5-year LRFS and OS rates were 79.1 and 93.3%. The 5-year OS rate was 94.7% in patients with R0-resected primary tumors and 72.7% in patients with R1/R2-status (p=0.023). In multivariate analysis, only histologic grade was found to be an independent prognostic factor of OS. Conclusion: Negative margins were not an independent prognostic factor in our series. Tumor biology reflected by histologic grade dictated the outcome.

The German Association for Psychiatry and Psychotherapy (DGPPN) has committed itself to establish a prospective national cohort of patients with major psychiatric disorders, the so-called DGPPN-Cohort. This project will enable the scientific exploitation of high-quality data and biomaterial from psychiatric patients for research. It will be set up using harmonised data sets and procedures for sample generation and guided by transparent rules for data access and data sharing regarding the central research database. While the main focus lies on biological research, it will be open to all kinds of scientific investigations, including epidemiological, clinical or health-service research.