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This paper investigates the optimal planning of microgrids including the hydrogen energy system through mixed-integer linear programming model. A real case study is analyzed by extending the only microgrid lab facility in Austria. The case study considers the hydrogen production via electrolysis, seasonal storage and fueling station for meeting the hydrogen fuel demand of fuel cell vehicles, busses and trucks. The optimization is performed relative to two different reference cases which satisfy the mobility demand by diesel fuel and utility electricity based hydrogen fuel production respectively. The key results indicate that the low emission hydrogen mobility framework is achieved by high share of renewable energy sources and seasonal hydrogen storage in the microgrid. The investment optimization scenarios provide at least 66% and at most 99% carbon emission savings at increased costs of 30% and 100% respectively relative to the costs of the diesel reference case (current situation). • A MILP model for renewable based hydrogen production, seasonal storage and mobility. • A real case study is analyzed by extending a microgrid lab facility in Austria. • Multiple investment optimization scenarios relative to two distinct reference cases. • CO 2 reduction by at least 66% and at most 99% relative to the diesel reference case. • Introducing carbon prices to bridge the cost gap between hydrogen and diesel fuel. [ABSTRACT FROM AUTHOR]

Currently, many Microgrid projects remain financially uncertain and not bankable for institutional investors due to major challenges in existing planning and design methods that require multiple, complex steps and software tools. Existing techniques treat every Microgrid project as a unique system, resulting in expensive, non-standardized approaches and implementations which cannot be compared. That is, it is not possible to correlate the results from different planning methods performed by different project developers and/or engineering companies. This very expensive individual process cannot guarantee financial revenue streams, cannot be reliably audited, impedes pooling of multiple Microgrid projects into a financial asset class, nor does it allow for wide-spread and attractive Microgrid and Distributed Energy Resource projects deployment. Thus, a reliable, integrated, and streamlined process is needed that guides the Microgrid developer and engineer through conceptual design, engineering, detailed electrical design, implementation, and operation in a standardized and data driven approach, creating reliable results and financial indicators that can be audited and repeated by investors and financers. This article describes the steps and methods involved in creating bankable Microgrids by relying on an integrated Microgrid planning software approach that unifies proven technologies and tested planning methods, researched and developed by the United States National Laboratory System as well as the US Department of Energy, to reduce design times. [ABSTRACT FROM AUTHOR]

In developing countries, mini-grids are seen as an important option to improve electrification rates in rural areas. In order to be successful, mini-grids face issues of operation and sizing of generation capacities. Current studies on the optimal sizing of mini-grids do not include capacity expansion feedbacks regarding the operator's or investor's long-term economic performance on growth in electricity usage, e.g. gap between demand and supply impacting the operator's income. Using a System Dynamics model, this paper compares the impact from two capacity expansion strategies on rural mini-grid operator's long-term economic performance. The two capacity expansion strategies are: a strategy with minimized costs and a strategy where only diesel power is allowed. Research shows that a cost-minimized capacity expansion strategy might not be the most beneficial solution for the operator's long term financial performance. Specifically, the high investment costs prohibit the implementation of the cost-minimized expansion strategy. In addition, the diesel-only expansion strategy suffers from high operational costs, which creates long-term challenges as the share of diesel increase. Therefore, the timeline of the investments and when to implement different strategies is important, creating a benefit for a System Dynamics approach. [ABSTRACT FROM AUTHOR]

Optimal microgrid design is a challenging problem, especially for multi-energy microgrids with electricity, heating, and cooling loads as well as sources, and multiple energy carriers. To address this problem, this paper presents an optimization model formulated as a mixed-integer linear program, which determines the optimal technology portfolio, the optimal technology placement, and the associated optimal dispatch, in a microgrid with multiple energy types. The developed model uses a multi-node modeling approach (as opposed to an aggregate single-node approach) that includes electrical power flow and heat flow equations, and hence, offers the ability to perform optimal siting considering physical and operational constraints of electrical and heating/cooling networks. The new model is founded on the existing optimization model DER-CAM, a state-of-the-art decision support tool for microgrid planning and design. The results of a case study that compares single-node vs. multi-node optimal design for an example microgrid show the importance of multi-node modeling. It has been shown that single-node approaches are not only incapable of optimal DER placement, but may also result in sub-optimal DER portfolio, as well as underestimation of investment costs. [ABSTRACT FROM AUTHOR]

Summary Samans et al. (2014) reported the enrichment of nucleosomes in human and bovine spermatozoa at centromere repeats and retrotransposon sequences such as LINE-1 and SINE. We demonstrate here that nucleosomal enrichments at repetitive sequences as reported result from bioinformatic analyses that make redundant use of sequencing reads that map to multiple locations in the genome. To illustrate that this computational approach is flawed, we observed comparable artificial enrichments at repetitive sequences when aligning control genomic DNA or simulated reads of uniform genome coverage. These results imply that the main conclusions of the article by Samans et al. (2014) are confounded by an inappropriate computational methodology used to analyze the primary data. [ABSTRACT FROM AUTHOR]

The stem cell zinc finger 1 (SZF1)/ZNF589 protein belongs to the large family of Krüppel-associated box domain–zinc finger (KRAB-ZNF) transcription factors, which are present only in higher vertebrates and epigenetically repress transcription by recruiting chromatin-modifying complexes to the promoter regions of their respective target genes. Although the distinct biological functions of most KRAB–ZNF proteins remain unknown, recent publications indicate their implication in fundamental processes, such as cell proliferation, apoptosis, differentiation, development, and tumorigenesis. SZF1/ZNF589 was first identified as a gene with SZF1-1 isoform specifically expressed in CD34 + hematopoietic cells, strongly suggesting a role in epigenetic control of gene expression in hematopoietic stem/progenitor cells (HSPCs). However, the function of SZF1/ZNF589 in hematopoiesis has not yet been elucidated. Our study reveals SZF1/ZNF589 as a gene with a human-specific nucleotide DNA-change, conferring potential species-specific functional properties. Through shRNA-mediated loss-of-function experiments, we found that changes in expression of fundamental apoptosis-controlling genes are induced on SZF1/ZNF589 knockdown, resulting in inhibited growth of hematopoietic cell lines and decreased progenitor potential of primary human bone marrow CD34 + cells. Moreover, we found that the SZF1/ZNF589 gene is differentially regulated during hypoxia in CD34 + HSPCs in a cytokine-dependent manner, implicating its possible involvement in the maintenance of the hypoxic physiologic status of hematopoietic stem cells. Our results establish the role of SZF1/ZNF589 as a new functional regulator of the hematopoietic system. [ABSTRACT FROM AUTHOR]

Microgrids are an increasingly common component of the evolving electricity grids with the potential to improve local reliability, reduce costs, and increase penetration rates for distributed renewable generation. The additional complexity of microgrids often leads to increased investment costs, creating a barrier for widespread adoption. These costs may result directly from specific needs for islanding detection, protection systems and power quality assurance that would otherwise be avoided in simpler system configurations. However, microgrids also facilitate additional value streams that may make up for their increased costs and improve the economic viability of microgrid deployment. This paper analyses the literature currently available on research relevant to value streams occurring in microgrids that may contribute to offset the increased investment costs. A review on research related to specific microgrid requirements is also presented. [ABSTRACT FROM AUTHOR]

Summary Aging is driven by changes of the epigenetic state that are only partially understood. We performed a comprehensive epigenomic analysis of the pancreatic β cell, key player in glucose homeostasis, in adolescent and very old mice. We observe a global methylation drift resulting in an overall more leveled methylome in old β cells. Importantly, we discover targeted changes in the methylation status of β cell proliferation and function genes that go against the global methylation drift, are specific to β cells, and correlate with repression of the proliferation program and activation of metabolic regulators. These targeted alterations are associated with specific chromatin marks and transcription factor occupancy in young β cells. Strikingly, we find β cell function improved in aged mice, as predicted by the changes in methylome and transcriptome. Thus, aging of terminally differentiated cells in mammals is not always coupled to functional decline. [ABSTRACT FROM AUTHOR]

Distributed energy resources gain an increased importance in commercial and industrial building design. Combined heat and power (CHP) units are considered as one of the key technologies for cost and emission reduction in buildings. In order to make optimal decisions on investment and operation for these technologies, detailed system models are needed. These models are often formulated as linear programming problems to keep computational costs and complexity in a reasonable range. However, CHP systems involve variations of the efficiency for large nameplate capacity ranges and in case of part load operation, which can be even of non-linear nature. Since considering these characteristics would turn the models into non-linear problems, in most cases only constant efficiencies are assumed. This paper proposes possible solutions to address this issue. For a mixed integer linear programming problem two approaches are formulated using binary and Special-Ordered-Set (SOS) variables. Both suggestions have been implemented into the optimization model DER–CAM to simulate investment decisions of CHP micro-turbines and CHP fuel cells with variable efficiencies. The approaches have further been applied successfully in a case study with four different commercial buildings. Comparison of the results between the standard version and the new approaches indicate that total annual system costs remain almost unchanged. System performance is subject to change and storage technologies become more important. Part load operation has mainly been found important for fuel cell units. The micro-turbine is found almost exclusively in full load, thus rendering the application of the new approaches for this technology unnecessary for the considered unit sizes and building types. The approach using binary variables was the most promising method to model variable efficiencies in terms of computational costs and results. It should especially be considered for specific fuel cell technologies. Further investigation on the impacts of this approach on the prediction of fuel cell and micro-turbine performance is suggested. [ABSTRACT FROM AUTHOR]

Thermal energy storage (TES) and distributed generation technologies, such as combined heat and power (CHP) or photovoltaics (PV), can be used to reduce energy costs and decrease CO 2 emissions from buildings by shifting energy consumption to times with less emissions and/or lower energy prices. To determine the feasibility of investing in TES in combination with other distributed energy resources (DER), mixed integer linear programming (MILP) can be used. Such a MILP model is the well-established Distributed Energy Resources Customer Adoption Model (DER-CAM); however, it currently uses only a simplified TES model to guarantee linearity and short run-times. Loss calculations are based only on the energy contained in the storage. This paper presents a new DER-CAM TES model that allows improved tracking of losses based on ambient and storage temperatures, and compares results with the previous version. A multi-layer TES model is introduced that retains linearity and avoids creating an endogenous optimization problem. The improved model increases the accuracy of the estimated storage losses and enables use of heat pumps for low temperature storage charging. Results indicate that the previous model overestimates the attractiveness of TES investments for cases without possibility to invest in heat pumps and underestimates it for some locations when heat pumps are allowed. Despite a variation in optimal technology selection between the two models, the objective function value stays quite stable, illustrating the complexity of optimal DER sizing problems in buildings and microgrids. [ABSTRACT FROM AUTHOR]

Abstract: Load balancing in electricity grids becomes a more sophisticated problem by the increased availability of time-varying stochastic supply of electricity from conversion of renewable resources like wind or sunlight. Due to the fact that large quantities of electrical energy cannot be stored easily, demand side management by shifting electrical loads is one attempt to cope with this problem. In this paper we discuss and compare two types of control signals to use the thermal storage of electrical household appliances as balancing power. As the system of our research consists of a high number of controllable refrigerators with independent parameters and behaviour, we investigate the synergetic behaviour by a simulation model. For this objective we analyze a simulation model of controllable refrigerators with respect to their ability to shift their energy demand depending on parameterized external signals. We show that both types of control signals can be used for short term reserves with delivery within 15min of time, but they differ in possible shapes of the resulting load curves and in the reaction time of the controlled system. In addition to the simulation model we develop a model of the synergetic behaviour of an ensemble of refrigerators'' reaction on control signals. This mathematical model predicts the electricity demand of ensembles of controlled appliances. As it reduces the simulation model''s complexity it could be used in a sophisticated control strategy, e.g. in a model predictive control approach. The general attempt to integrate the load shift potential of cooling devices into the control of an electricity grid can probably be transferred to other electrical appliances with thermal storage capacities. [Copyright &y& Elsevier]

• Resource and load intra-hour variability is overlooked in microgrid optimizations. • Novel framework which includes intra-hour variability in economic optimization. • Approach is agnostic to intra-hour timescale. • 98.2% less runtime than traditional approaches with high optimality. The intra-hour intermittency of solar energy and demand introduce significant design challenges for microgrids. To avoid costly energy shortfalls and mitigate outage probability, islanded microgrids must be designed with sufficient distributed energy resources (DER) to meet demand and fulfill the energy and power balance. To avoid excessive runtime, current design tools typically only utilize hourly data. As such, the variable nature of solar and demand is often overlooked. Thus, DER designed based on hourly data may result in significant energy shortfalls when deployed in real-world conditions. This research introduces a new, fast method for optimizing DER investments and performing dispatch planning to consider intra-hour variability. A novel set of constraints which operate on intra-hour data are implemented in a mixed-integer-linear-program microgrid investment optimization. Variability is represented by the single worst-case intra-hour fluctuation. This allows for fast optimization times compared to other approaches tested. Applied to a residential microgrid case study with 5-minute intra-hour resolution, this new method is shown to maintain optimality within 2% and reduce runtime by 98.2% compared to full-scale-optimizations which consider every time-step explicitly. Applicable to a variety of technologies and demand types, this method provides a general framework for incorporating intra-hour variability into microgrid design. [ABSTRACT FROM AUTHOR]

Local and renewable energy communities show a high potential for the efficient use of distributed energy technologies at regional levels according to the Clean Energy Package of the European Union. However, until now there are only limited possibilities to bring such energy communities into reality because of several limitation factors. Challenges are already encountered during the planning phase since a large number of decision variables have to be considered depending on the number and type of community participants and distributed technologies. This paper overcomes these challenges by establishing a mixed-integer linear programming based optimal planning approach for renewable energy communities. A real case study is analyzed by creating an energy community testbed with a leading energy service provider in Austria. The case study considers nine energy community members of a municipality in Austria, distributed photovoltaic systems, energy storage systems, different electricity tariff scenarios and market signals including feed-in tariffs. The key results indicate that renewable energy communities can significantly reduce the total energy costs by 15% and total carbon dioxide emissions by 34% through an optimal selection and operation of the energy technologies. In all the optimization scenarios considered, each community participant can benefit both economically and ecologically. • Novel optimization strategies for renewable energy communities in microgrids. • Advanced mixed-integer linear programming model with 8760-hour time horizon. • A real Austrian case study with nine community participants and six scenarios. • Renewable energy transfer with different tariff scenarios and market signals. • Reduction of community costs by 15% and community carbon emissions by 34%. [ABSTRACT FROM AUTHOR]

Abstract: Within recent years, energy policies have imposed a number of targets at European and national level for rational use of energy (RUE), renewable energy sources (RES) and related CO2 reductions. As a result, a wide variety of policy instruments is currently implemented and hence the question arises: how can these instruments be designed in a way to reach the maximum policy target with the minimum public money spent? The objective of this paper is to derive a methodology for obtaining efficient policy portfolios promoting sustainable energy systems depending on the policy target and show corresponding results from case studies in Austria, Germany and Poland. The investigations were carried out by application of Invert simulation tool, a computer model developed for simulating the impacts of various promotion schemes for renewable and efficient energy systems. With this tool, the CO2 reductions and related public expenses have been calculated for various policy mixes. In the building-related energy sector, it turned out that in all investigated regions support schemes for supply side measures are the most cost-efficient instruments. However, their potential is restricted and for achieving higher levels of CO2 reduction, promotion of demand side measures is indispensable. The paper shows that for a comprehensive comparison of policy portfolios, there are always two dimensions to be considered: efficiency and effectiveness. The more effective, i.e. the higher the implementation rate of a scheme, the more essential becomes the efficiency criteria. [Copyright &y& Elsevier]

Abstract: Most data mining techniques have rarely been used in ecology. To address the specific needs of scientists analysing data from a plant trait database developed during the LEDA project, a web-based data mining tool has been developed. This paper presents the DIONE data miner and the project it has been developed in. It addresses the nature of plant trait data from a data mining perspective and points out problems that arise when preparing data for this process. The availability of a large amount of high quality data is an essential prerequisite for successful data mining. To ensure this, a software aided reviewing process has been integrated into the LEDA Traitbase system. The process enables third-party contributors to easily commit their data to LEDA, while assuring adherence of the data to the LEDA standard. The paper concludes with information about data mining results on plant trait data achieved so far and gives an outlook on the applicability of data mining to the fields of ecology. [Copyright &y& Elsevier]

The optimal design of microgrids with thermal energy system requires optimization techniques that can provide investment and scheduling of the technology portfolio involved. In the modeling of such systems with seasonal storage capability, the two main challenges include the low temporal resolution of available data and the non-linear cost versus capacity relationship of solar thermal and heat storage technologies. This work overcomes these challenges by developing two different optimization models based on mixed-integer linear programming with objectives to minimize the total energy costs and carbon dioxide emissions. Piecewise affine functions are used to approximate the non-linear cost versus capacity behavior. The developed methods are applied to the optimal planning of a case study in Austria. The results of the models are compared based on the accuracy and real-time performance together with the impact of piecewise affine cost functions versus non-piecewise affine fixed cost functions. The results show that the investment decisions of both models are in good agreement with each other while the computational time for the 8760-h based model is significantly greater than the model having three representative periods. The models with piecewise affine cost functions show larger capacities of technologies than non-piecewise affine fixed cost function based models. • Two different models with varying time steps to optimize costs and carbon emissions. • Modeling of non-linear cost functions into piecewise affine cost functions. • Austrian microgrid study with eight scenarios in residential heating sector. • Piecewise affine cost functions have high impact on results in carbon reduction. • Reduction of carbon emissions by 77% with seasonal thermal storage capability. [ABSTRACT FROM AUTHOR]

• Introduces novel hybrid techno-economic optimization method for distributed energy systems and microgrids. • Method guarantees result feasibility, especially during outage and islanded situations. • Compares to the state-of-art approach in literature. • Introduces novel state-of-charge constraint for reduced models to approximate multiple outage days. • Method shown to produce significant runtime savings with high optimality and robustness. Recently, researchers have begun to study hybrid approaches to Microgrid techno-economic planning, where a reduced model optimizes the DER selection and sizing is combined with a full model that optimizes operation and dispatch. Though providing significant computation time savings, these hybrid models are susceptible to infeasibilities, when the size of the DER is insufficient to meet the energy balance in the full model during macrogrid outages. In this work, a novel hybrid optimization framework is introduced, specifically designed for resilience to macrogrid outages. The framework solves the same optimization problem twice, where the second solution using full data is informed by the first solution using representative data to size and select DER. This framework includes a novel constraint on the state of charge for storage devices, which allows the representation of multiple repeated days of grid outage, despite a single 24-h profile being optimized in the representative model. Multiple approaches to the hybrid optimization are compared in terms of their computation time, optimality, and robustness against infeasibilities. Through a case study on three real Microgrid designs, we show that allowing optimizing the DER sizing in both stages of the hybrid design, dubbed minimum investment optimization (MIO), provides the greatest degree of optimality, guarantees robustness, and provides significant time savings over the benchmark optimization. [ABSTRACT FROM AUTHOR]

Abstract: Objective: Social networking sites such as Facebook are popular avenues of social discourse among adolescents and young adults, allowing for communication through photographs, videos, and chat features. These websites are also emerging as portals for health-centered support groups, bringing together people with common medical conditions. Adolescents with tracheostomies represent a special and vulnerable patient population. Our aim was to determine whether this particular group of patients found Facebook to be a suitable environment in which to network with other users with tracheostomies. Methods: We used our institution''s tracheostomy database to obtain a list of all patients between ages of 11–18. We identified 33 patients in this category, and completed a chart review to determine their medical diagnoses as well as age at trach placement. We determined that of these 33 patients, 24 had severe neurocognitive delays that would render them unable to participate in the study. We contacted the remaining nine subjects and obtained appropriate consent for their participation in the study. Results: Of the nine subjects with tracheostomies who completed our survey, four were actively involved with the Facebook community. Two of the four subjects regularly connected with people that they had not met in person, and all four subjects shared the fact that they had a tracheostomy with the Facebook community. Three of the four subjects posted pictures of themselves with their trach sites visible. Finally, three of the four subjects stated that they met and communicated with other Facebook members with tracheostomies. Conclusions: Social networking sites such as Facebook appear to offer an appropriate avenue for adolescents with tracheostomies to network with other users with tracheostomies. Further studies are warranted to assess the reach and social impact of these networking sites as portals of health-centered support groups, however, social networking sites and the cyberspace community may be a promising source of support for adolescents with tracheotomies. [Copyright &y& Elsevier]

• Discusses dearth of efficient multiyear optimization approaches in literature. • Uses historic and forecasted data to show need for multiyear optimization approach. • Introduces novel and fast multiyear optimization approach. • Compares with standard literature approaches, showcasing significant time savings. • Discusses impact of forecasting error on the approaches. With energy systems, the problem of economic planning is decisive in the design of a low carbon and resilient future grid. Although several tools to solve the problem already exist in literature and industry, most tools only consider a single "typical year" while providing investment decisions that last around a quarter of a century. In this paper, we introduce why such an approach is limited and derive two approaches to correct this. The first approach, the Forward-Looking model, assumes perfect knowledge and makes investment decisions based on the full planning horizon. The second novel approach, the Adaptive method, solves the optimization problem in single year iterations, making incremental investment decisions that are dependant on previous years, with only knowledge of the current year. Comparing the two approaches on a realistic microgrid, we find little difference in investment decisions (maximum 21% difference in total cost over 20 years), but large differences in optimization time (up to 12000% time difference). We close the paper by discussing implications of forecasting errors on the microgrid planning process, concluding that the Adaptive approach is a suitable choice. [ABSTRACT FROM AUTHOR]

Objective: To determine the effects of nodal yield on survival in early stage oral cavity squamous cell carcinoma (OCSCC) in the context of primary tumor depth of invasion (DOI).Materials and Methods: Patients with early-stage clinically node-negative OCSCC who underwent upfront surgery at the primary site were identified using the National Cancer Database between 2004 and 2015.Results: There were 3384 patients with <4 mm DOI and 1387 patients with ≥4 mm DOI identified. Management of the neck included observation (40%), END with <18 nodes harvested ± postoperative radiation (ND < 18, 16%), and END with ≥18 nodes harvest ± postoperative radiation (ND ≥ 18, 44%). When adjusted for relevant covariates, ND ≥ 18 demonstrated statistically significant improvements in overall survival for both DOI < 4 mm and ≥4 mm (DOI < 4 mm: HR 0.67, 95%CI 0.54-0.85; DOI ≥ 4 mm: HR 0.47, 95%CI 0.34-0.64). However, ND < 18 showed no significant difference from observation of the neck regardless of DOI (DOI < 4 mm: HR 0.82, 95%CI 0.63-1.07; DOI ≥ 4 mm: HR 0.72, 95%CI 0.51-1.03). Of patients undergoing END, the most significant factors associated with obtaining a nodal yield of 18 or more were age less than 40 years (HR 2.58, 95%CI 1.84-3.63) and treatment at an academic facility (HR 2.47, 95%CI 2.06-2.96).Conclusions: END with 18 or more nodes is associated with improved survival outcomes in patients with early stage OCSCC regardless of DOI. END with less than 18 nodes, however, does not appear significantly different than observation of the neck alone. Achieving a lymph node yield of 18 or more is multifactorial and includes both patient and provider factors. [ABSTRACT FROM AUTHOR]

Background During the last years, molecular genetic data are increasingly used as prognostic and predictive factors in acute myeloid leukemia (AML). The molecular genetic profile permits a rapid risk categorization and beyond that a prediction of differential treatment efficacy of post-remission chemotherapy versus an allogeneic hematopoietic cell transplantation (HCT) in specific subgroups. Methods The aim of this study was to evaluate cost-effectiveness of two different strategies of risk categorization (conventional cytogenetic diagnostics (CCD) versus molecular genetic diagnostics (MGD)) in patients with AML, using a decision-analytic state-transition model. The model is run as (Monte Carlo) microsimulation in which individuals pass through in cycles with a cycle length of one month and a time horizon of ten years. Findings Results show that on average, individuals within the MGD group generated about US$ 32,000 higher costs but survived about seven months longer than individuals within the CCD group. This leads to an Incremental Cost-Effectiveness Ratio (ICER) of about US$ 4928 per survived month. Interpretation With a GDP (Gross Domestic Product) of US$ 26,467 (€ 33,630) per capita in Germany in 2012, the base-case ICER of US$ 4928 per survived month projected to US$ 59,136 per survived year is in between the simple GDP and the three times GDP per capita. [ABSTRACT FROM AUTHOR]

Microgrids can integrate variable renewable energy sources into the energy system by controlling flexible assets locally. However, as the energy system is dynamic, an effective microgrid controller must be able to receive feedback from the system in real-time, plan ahead and take into account the active electricity tariff, to maximize the benefits to the operator. These requirements motivate the use of optimization-based control methods, such as Model Predictive Control to optimally dispatch flexible assets in microgrids. However, the major bottleneck to achieve maximum benefits with these methods is their predictive accuracy. This paper addresses this bottleneck by developing a novel multi-step forecasting method for a Model Predictive Control framework. The presented methods are applied to a real test-bed of a renewable energy community in Austria, where its operational costs and CO 2 emissions are benchmarked with those of a rule-based control strategy for Flat, Time-of-Use, Demand Charge and variable energy price tariffs. In addition, the impact of forecast errors and electric battery capacity on energy community operational savings are examined. The key results indicate that the proposed controller can outperform a rule-based dispatch strategy by 24.7% in operational costs and by 8.4% in CO 2 emissions through optimal operation of flexibilities if it has perfect foresight. However, if the controller is deployed in a realistic environment, where forecasts for electrical load and PV generation are required, the same savings are reduced to 3.3% for cost and 7.3% for CO 2 , respectively. In such environments, the proposed controller performs best in highly dynamic tariffs such as Time-of-Use and Real-time pricing rates, achieving real cost savings of up to 6.3%. These results show that the profitability of optimization-based control of microgrids is threatened by forecast errors. This motivates future research on control strategies that compensate for forecast errors in real-world operation and more accurate forecasting methods. [Display omitted] • Advanced microgrid controller framework based on Model Predictive Control. • Novel method for multi-step-ahead time series forecasting. • A real Austrian test-bed with multiple operational optimization scenarios. • Comprehensive economic analysis considering forecast errors and multiple battery sizes. • Reduction of operational costs by 6% and carbon emissions by 7% [ABSTRACT FROM AUTHOR]

Summary: Ineffective haematopoiesis with peripheral cytopenias despite normo- or hypercellular bone marrow is the hallmark of the myelodysplastic syndromes especially in the low-risk subgroups. It is caused by increased secretion of inhibitory cytokines in the marrow through a yet unresolved pathophysiological mechanism. Immunoinhibitory or modulatory therapy aims at restoring haematopoiesis by reversing these inhibitory processes and includes antithymocyte globulin (ATG), ciclosporin A (CSA), direct TNF-inhibitors and lenalidomide. Although not yet approved for clinical use, ATG therapy improves mono-, bi- and trilineage cytopenias in around 35–40% of low-risk MDS patients usually after a single treatment course. Highest response rates are seen in younger patients, those with a shorter duration of the disease and low transfusion requirement, with hypocellular bone marrow or with thrombocytopenia. The presence of the HLA-DR15 (DR2) genotype is an additional parameter predicting a response. In contrast, differentiation defects with an increased blast cell percentage or sideroachrestic changes characterize the poor responders. A simple scoring system, using age, duration of transfusion dependency, and HLA-DR15 status, has been developed and allows identifying patients with a high, intermediate, or low probability of response to treatment with ATG. Other immunosuppressive agents which can also induce responses, e.g. CSA, have been combined with ATG, but have not yet been fully evaluated for their potential role in the treatment of MDS. Lenalidomide has a superior efficacy in the 5q-syndrome, but also some efficacy in the other low-risk MDS patients. Further clinical trials are needed to define the potential of immunosuppressive/modulatory treatment in MDS. [Copyright &y& Elsevier]

Distributed power systems in the U.S. and globally are evolving to provide reliable and clean energy to consumers. In California, existing regulations require significant increases in renewable generation, as well as identification of customer-side Distributed Energy Resources (DER) controls, communication technologies, and standards for interconnection with the electric grid systems. As DER deployment expands, customer-side DER control and optimization will be critical for system flexibility and demand response (DR) participation, which improves the economic viability of DER systems. Current DER systems integration and communication challenges include leveraging the existing DER and DR technology and systems infrastructure, and enabling optimized cost, energy and carbon choices for customers to deploy interoperable grid transactions and renewable energy systems at scale. This paper presents a cost-effective solution to these challenges by exploring communication technologies and information models for DER system integration and interoperability. This system uses open standards and optimization models for resource planning based on dynamic -pricing notifications and autonomous operations within various domains of the smart grid energy system. It identifies architectures and customer engagement strategies in dynamic DR pricing transactions to generate feedback information models for load flexibility, load profiles, and participation schedules. The models are tested at a real site in California—Fort Hunter Liggett (FHL). The results for FHL show that the model fits within the existing and new DR business models and networked systems for transactive energy concepts. Integrated energy systems, communication networks, and modeling tools that coordinate supply-side networks and DER will enable electric grid system operators to use DER for grid transactions in an integrated system. [ABSTRACT FROM AUTHOR]

Highlights: [•] DER potentially competitive in both economic and CO2 emissions abatement terms. [•] DER more competitive in commercial buildings, in warmer areas of the U.S. [•] Structure of electricity/NG tariffs drive DER attractiveness, more so than climate. [•] High spark spreads lead to increased economic attractiveness of DER. [ABSTRACT FROM AUTHOR]

Highlights: [•] We simulated chilled water thermal energy storage (TES) under diverse conditions. [•] TES systems reduced annual electricity cost by 5–15% across four locations. [•] TES systems also reduced peak electricity demand by 13–30% across locations. [•] Optimally sized TES systems were compared to simple, heuristically sized systems. [•] Optimization is critical to TES sizing when tariff and load drivers less present. [ABSTRACT FROM AUTHOR]

P-selectin and its receptor P-selectin glycoprotein ligand-1 (PSGL-1) mediate adhesion between leukocytes, tumor cells (including leukemias and lymphomas), and platelets, and play an important role in hematopoiesis, T cell activation, and cancer growth and metastasis. As microparticles (MPs) are released from activated or apoptotic cells, there should be significant numbers of circulating PSGL-1–bearing MPs in the blood of patients undergoing allogeneic stem cell transplantation (alloSCT). We enumerated PSGL-1–expressing MPs in plasma samples from 30 consecutive patients with hematologic disorders at different time points during the course of alloSCT by flow cytometry and analyzed their relation to cell counts, patient characteristics, and clinical outcome. Median follow-up time of surviving patients was 1,772 days (range 1272–1981 days). Nineteen patients (63.3%) died, 10 due to progression of disease (33.3%). The PSGL-1 MPs significantly declined during conditioning therapy but increased again after transfusion of donor cells and even more at the time of engraftment. Numbers >250/μL after graft transfusion were associated with a shorter time to engraftment for patients receiving fresh peripheral stem cell grafts (median, 15 vs. 21 days; p = 0.049). Furthermore, low PSGL-1 MP values at those two time points were associated with a higher risk of progress/relapse in univariate analysis (p = 0.008–0.014; hazard ratio [HR] = 15.0–42.0) with cumulative incidences at 5 years of 81.8% versus 28.6% and 85.7% versus 20.0%, respectively. In conclusion, PSGL-1 microparticles show a characteristic course during alloSCT and their possible association with relapse/progress requires further evaluation of the PSGL-1/P-selectin interaction in leukemias and lymphomas. [ABSTRACT FROM AUTHOR]

Summary: Genomic imprinting regulates parental-specific expression of particular genes and is required for normal mammalian development. How imprinting is established during development is, however, largely unknown. To address this question, we studied the mouse Kcnq1 imprinted cluster at which paternal-specific silencing depends on expression of the noncoding RNA Kcnq1ot1. We show that Kcnq1ot1 is expressed from the zygote stage onward and rapidly associates with chromatin marked by Polycomb group (PcG) proteins and repressive histone modifications, forming a discrete repressive nuclear compartment devoid of RNA polymerase II, a configuration also observed at the Igf2r imprinted cluster. In this compartment, the paternal Kcnq1 cluster exists in a three-dimensionally contracted state. In vivo the PcG proteins Ezh2 and Rnf2 are independently required for genomic contraction and imprinted silencing. We propose that the formation of a parental-specific higher-order chromatin organization renders imprint clusters competent for monoallelic silencing and assign a central role to PcG proteins in this process. [Copyright &y& Elsevier]

Abstract: Antigenic cross-reactivity has been described between the venom allergen (antigen 5) and mammalian testis proteins. Based on an allergen database we have previously shown that allergens can be represented by allergen motifs. A motif group was found containing venom antigen 5 sequences from different vespids. Using an optimized amino acid profile based on antigen 5 sequences for searching cross-reactive proteins, three human semen proteins belonging to the family of cysteine-rich secretory proteins (hCRISP) were found in the Swiss Protein database. To analyze antigenic cross-reactivity between antigen 5 and hCRISPs, antigen 5 from yellow jacket venom (Ves v 5) and two hCRISPs (CRISP-2 and -3) were chosen and produced as recombinant proteins in E. coli. A correlation was found between antibodies reacting with rVes v 5 and rhCRISP-2, -3 in a small human sera population indicating the presence of cross-reactive antibodies in human serum. Using intravenous immunoglobulin (IVIg), a therapeutic multidonor IgG preparation, cross-reactive antibodies were isolated that recognize rVes v 5, hCRISP-2 and -3 suggesting the presence of common epitopes between Ves v 5 and hCRISPs. However this cross-reactivity seems not to be linked to allergy to wasp venom as we could show no correlation between increasing CAP-class IgE level to wasp venom and IgG to sperm extract and hCRISPs. These data suggest that higher sensitization to wasp venom does not induce more antibodies against autoantigens and might not represent a higher risk to develop autoantibodies leading to infertility. [Copyright &y& Elsevier]

Abstract: We have recently shown that the majority of allergens can be represented by allergen motifs. This observation prompted us to experimentally investigate the synthesized peptides corresponding to the in silico motifs with regard to potential IgE binding and cross-reactions with allergens. Two motifs were selected as examples to conduct in vitro studies. From the first motif, derived from allergenic MnSOD sequences, the motif stretch of the allergen Asp f 6 was selected and synthesized as a peptide (MnSOD Mot). The corresponding full-length MnSOD was also expressed in Escherichia coli and both were compared for IgE reactivity with sera of patients reacting to the MnSOD of Aspergillus fumigatus or Malassezia sympodialis. For the second motif, the invertebrate tropomyosin sequences were aligned and a motif consensus sequence was expressed as a recombinant protein (Trop Mot). The IgE reactivity of Trop Mot was analyzed in ELISA and compared to that of recombinant tropomyosin from the shrimp Penaeus aztecus (rPen a 1) in ImmunoCAP. MnSOD Mot was weakly recognized by some of the tested sera, suggesting that the IgE binding epitopes of a multimeric globular protein such as MnSOD cannot be fully represented by a motif peptide. In contrast, the motif Trop Mot showed the same IgE reactivity as shrimp full-length tropomyosin, indicating that the major allergenic reactivity of a repetitive structure such as tropomyosin can be covered by a motif peptide. Our results suggest that the motif-generating algorithm may be used for identifying major IgE binding structures of coiled-coil proteins. [Copyright &y& Elsevier]

Abstract: Reversible figures such as the Necker cube make up a well-known class of visual phenomena in which an invariant stimulus pattern gives rise to at least two different perceptual interpretations. Former EEG studies of our research group demonstrated a reversal-related delta response and a frontal enhancement of gamma activity during multistable perception which has been interpreted as signaling attentional top-down processes. The aim of the present study was to investigate the functional involvement of delta and gamma activity in top-down processes more explicitly by asking 21 healthy participants to bring the reversal rate under voluntary control during viewing of the Necker cube. Slowing down the reversal rate should be accomplished by focussing attention to the currently perceived alternative while speeding up should be accomplished by shifting attention as rapidly as possible from one perspective to the other. EEG was recorded from frontal, central, parietal, and occipital locations of both hemispheres. The data was analysed on the single-sweep level in the delta and gamma frequency range. The results showed that both delta response and gamma power were larger during slowing down than speeding up the reversal rate. These findings may indicate that more attentional resources have to be allocated by the cognitive system in order to prevent a reversal by means of focussed attention than to initiate a reversal by attentional shifts. [Copyright &y& Elsevier]

Abstract: We have previously isolated anti-FcεRIα autoantibodies from phage libraries of healthy donors and urticaria patients. Strikingly, the same antibody, LTMα15, was isolated from both libraries. Sequence analysis revealed a germline configuration of the LTMα15 variable heavy (VH) chain with a slightly mutated variable light (VL) chain supporting its classification as a natural autoantibody. Distribution analysis of anti-FcεRIα autoantibodies by functional or serological tests delivered conflicting data. For this reason we have developed a new real-time PCR to analyse the distribution of LTMα15VH in healthy donors and urticaria patients. Our new bioinformatic program permitted the design of a minor groove binder (MGB) TaqMan probe that specifically detected the LTMα15VH. We were able to demonstrate a broad range of rearranged VH gene copy number without any correlation to the state of health. Monitoring LTMα15VH gene copy number in a single donor over a period of 70 days revealed a time-related fluctuation of circulating B cells carrying LTMα15VH. We propose that our real-time PCR may serve as a model for the quantification of natural antibody sequences at a monoclonal level. [Copyright &y& Elsevier]

Oral involvement of chronic graft-versus-host disease (GvHD) is a most distressing and disabling complication of hematopoietic cell transplantation, for which systemic immunosuppression as well as topical corticosteroid treatment may offer only limited symptomatic relief. Here we report encouraging preliminary results with the application of tacrolimus (FK-506) as a 0.1% ointment in three patients with severe oral chronic GvHD, heavily pretreated without success, who experienced rapid, consistent, complete or at least marked, subjective and objective improvement with topical tacrolimus. [Copyright &y& Elsevier]

• Overall outcomes of patients allografted for BC CML remain poor in the TKI era. • Survival after alloSCT for BC CML depends on the pretransplant remission status. • Conventional prognostic factors remain outcome determinants for BC CML in remission. • UD transplant is associated with better LFS in patients with active BC at alloSCT. The prognosis of patients with blast crisis (BC) chronic myeloid leukemia (CML) is still dismal. Allogeneic stem cell transplantation represents the only curative treatment option, but data on transplant outcomes are scarce. We therefore conducted a retrospective, registry-based study of adult patients allografted for BC CML, focusing on patients with active disease at transplant and pretransplant prognostic factors. One hundred seventy patients allografted for BC CML after tyrosine kinase inhibitor pretreatment between 2004 and 2016 were analyzed. Before transplant, 95 patients were in remission, whereas 75 patients had active BC. In multivariable analysis of the entire cohort, active BC at transplant was the strongest factor associated with decreased overall survival (hazrd ratio, 1.87; P =.010) and shorter leukemia-free survival (LFS; hazard ratio, 1.69; P =.017). For patients with BC in remission at transplant, advanced age (≥45 years), lower performance status (≤80%), longer interval from diagnosis BC to transplant (>12 months), myeloablative conditioning, and unrelated donor (UD) transplant were risk factors for inferior survival. In patients with active BC, only UD transplant was significantly associated with prolonged LFS and trended toward improved overall survival. In summary, survival of patients allografted for BC CML was strongly dependent on pretransplant remission status. In patients with remission of BC, conventional prognostic factors remained the major determinants of outcome, whereas in those with active BC at transplant, UD transplant was associated with prolonged LFS in our study. [ABSTRACT FROM AUTHOR]

• First-line treatment is applied relatively homogeniously among German, Austrian, and Swiss transplant centers except initial treatment of progressive onset. • Second-line treatment varies considerably with new agents entering clinic through the last 10 years. • Even in the presence of evidence clinical practice in treatment of lung manifestations varies considerably. Chronic graft-versus-host disease (cGVHD) remains the leading cause of late morbidity and mortality. Despite the growing number of treatment options in cGVHD, evidence remains sparse. The German-Austrian-Swiss GVHD Consortium performed a survey on clinical practice in treatment of cGVHD among transplant centers in Germany, Austria, and Switzerland in 2009 and 2018 and compared the results. The survey performed in 2009 contained 20 questions on first-line treatment and related issues and 4 questions on second-line scenarios followed by a survey on all systemic and topic treatment options known and applied, with 31 of 36 transplant centers (86%) responding. The survey in 2018 repeated 7 questions on first-line treatment and 3 questions on second-line scenarios followed by an updated survey on all current systemic treatment options known and applied, with 29 of 66 centers (43%) responding. In summary, the results show a large overlap of first-line treatment practice between centers and the 2 surveys because of a lack of new data that changes practice, except significant heterogeneity of treatment of cGVHD progressive onset type, which can be explained by the lack of trials focusing on this high-risk entity. In contrast, treatment options applied to second-line therapy vary considerably, with new agents like ibrutinib and ruxolitinib entering clinical practice. Moreover, treatment of bronchiolitis obliterans syndrome demonstrates heterogeneity in applied therapeutic options and sequence because of a lack of controlled data and different conclusions from already existing evidence. In summary, the survey results demonstrate an increasing number of treatment options applied to cGVHD accompanied by a significant heterogeneity in second-line treatment and underline the urgent need for clinical trials and registry analyses on rare entities with high mortality like progressive onset type and lung involvement of cGVHD. [ABSTRACT FROM AUTHOR]

The eukaryotic genome is organized to enable the precise regulation of gene expression. This organization is established as the embryo transitions from a fertilized gamete to a totipotent zygote. To understand the factors and processes that drive genomic organization, we focused on the pioneer factor GAGA factor (GAF) that is required for early development in Drosophila. GAF transcriptionally activates the zygotic genome and is localized to subnuclear foci. This non-uniform distribution is driven by binding to highly abundant GA repeats. At GA repeats, GAF is necessary to form heterochromatin and silence transcription. Thus, GAF is required to establish both active and silent regions. We propose that foci formation enables GAF to have opposing transcriptional roles within a single nucleus. Our data support a model in which the subnuclear concentration of transcription factors acts to organize the nucleus into functionally distinct domains essential for the robust regulation of gene expression. [Display omitted] • The GAF unstructured polyQ domain is not required for localizing to nuclear foci • The GAF DBD is necessary and sufficient for localization to condensed nuclear foci • GAF subnuclear foci correspond to heterochromatic AAGAG satellite repeats • GAF is required for heterochromatin formation and silencing of satellite repeats Gaskill et al. demonstrate that in addition to the previously identified role of the pioneer factor GAF in activating the initial zygotic transcription in Drosophila , GAF is required to establish silencing of highly abundant AAGAG satellite repeats. This silencing occurs in subnuclear GAF foci established through DNA binding. [ABSTRACT FROM AUTHOR]

Complete donor chimerism is strongly associated with complete remission after allogeneic stem cell transplantation (allo-SCT) in patients with hematologic malignancies. Donor-derived allo-immune responses eliminate the residual host hematopoiesis and thereby mediate the conversion to complete donor chimerism. Recently, cytomegalovirus (CMV) reactivation was described to enhance overall T cell reconstitution, to increase graft-versus-host disease incidence, and to reduce the leukemia relapse risk. However, the link between CMV and allo-immune responses is still unclear. Here, we studied the relationship between CMV-specific immunity, overall T cell reconstitution, and residual host chimerism in 106 CMV-seropositive patients transplanted after reduced-intensity conditioning including antithymocyte globulin. In accordance with previous reports, the recovery of CMV-specific cytotoxic T cells (CMV-CTLs) was more frequent in CMV-seropositive recipients (R) transplanted from CMV-seropositive than from seronegative donors (D). However, once CMV-CTLs were detectable, the reconstitution of CMV-specific CTLs was comparable in CMV R+/D– and R+/D+ patients. CD3 + and CD8 + T cell reconstitution was significantly faster in patients with CMV-CTLs than in patients without CMV-CTLs both in the CMV R+/D– and R+/D+ setting. Moreover, CMV-CTL numbers correlated with CD3 + and CD8 + T cell numbers in both settings. Finally, presence of CMV-CTLs was associated with low host chimerism levels 3 months after allo-SCT. In conclusion, our data provide a first indication that CMV-CTLs in CMV-seropositive patients might trigger the reconstitution of T cells and allo-immune responses reflected by the conversion to complete donor chimerism. [ABSTRACT FROM AUTHOR]

Molecular genetics may influence outcome for patients with myelofibrosis. To determine the impact of molecular genetics on outcome after allogeneic stem cell transplantation, we screened 169 patients with primary myelofibrosis (n = 110), post-essential thrombocythemia/polycythemia vera myelofibrosis (n = 46), and myelofibrosis in transformation (n = 13) for mutations in 16 frequently mutated genes. The most frequent mutation was JAK2V617F (n = 101), followed by ASXL1 (n = 49), calreticulin (n = 34), SRSF2 (n = 16), TET2 (n = 10), U2AF1 (n = 11), EZH2 (n = 7), MPL (n = 6), IDH2 (n = 5), IDH1 (n = 4), and CBL (n = 1). The cumulative incidence of nonrelapse mortality (NRM) at 1 year was 21% and of relapse at 5 years 25%. The 5-year rates progression-free (PFS) and overall survival (OS) were and 56%, respectively. In a multivariate analysis CALR mutation was an independent factor for lower NRM (HR, .415; P  = .05), improved PFS (HR, .393; P  = .01), and OS (HR, .448; P  = .03). ASXL1 and IDH2 mutations were independent risk factors for lower PFS (HR, 1.53 [ P  = .008], and HR, 5.451 [ P  = .002], respectively), whereas no impact was observed for “triple negative” patients. Molecular genetics, especially CALR , IDH2 , and ASXL1 mutations, may thus be useful to predict outcome independently from known clinical risk factors after allogeneic stem cell transplantation for myelofibrosis. [ABSTRACT FROM AUTHOR]