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Mitochondrial DNA (mtDNA) is particularly vulnerable to somatic mutagenesis. Potential mechanisms include DNA polymerase γ (POLG) errors and the effects of mutagens, such as reactive oxygen species. Here, we studied the effects of transient hydrogen peroxide (H2O2 pulse) on mtDNA integrity in cultured HEK 293 cells, applying Southern blotting, ultra-deep short-read and long-read sequencing. In wild-type cells, 30 min after the H2O2 pulse, linear mtDNA fragments appear, representing double-strand breaks (DSB) with ends characterized by short GC stretches. Intact supercoiled mtDNA species reappear within 2–6 h after treatment and are almost completely recovered after 24 h. BrdU incorporation is lower in H2O2-treated cells compared to non-treated cells, suggesting that fast recovery is not associated with mtDNA replication, but is driven by rapid repair of single-strand breaks (SSBs) and degradation of DSB-generated linear fragments. Genetic inactivation of mtDNA degradation in exonuclease deficient POLG p.D274A mutant cells results in the persistence of linear mtDNA fragments with no impact on the repair of SSBs. In conclusion, our data highlight the interplay between the rapid processes of SSB repair and DSB degradation and the much slower mtDNA re-synthesis after oxidative damage, which has important implications for mtDNA quality control and the potential generation of somatic mtDNA deletions.

Epilepsy and mental retardation are known to be associated with pathogenic mutations in a broad range of genes that are expressed in the brain and have a role in neurodevelopment. Here, we report on a family with three affected individuals whose clinical symptoms closely resemble a neurodevelopmental disorder. Whole-exome sequencing identified a homozygous stop-gain mutation, p.Gln19*, in the BATF2 gene in the patients. The BATF2 transcription factor is predominantly expressed in macrophages and monocytes and has been reported to modulate AP-1 transcription factor-mediated pro-inflammatory responses. Transcriptome analysis showed altered base-level expression of interferon-stimulated genes in the patients’ blood, typical for type I interferonopathies. Peripheral blood mononuclear cells from all three patients demonstrated elevated responses to innate immune stimuli, which could be reproduced in CRISPR–Cas9-generated BATF2−/− human monocytic cell lines. BATF2 is, therefore, a novel disease-associated gene candidate for severe epilepsy and mental retardation related to dysregulation of immune responses, which underscores the relevance of neuroinflammation for epilepsy.

Immune-mediated diarrhea represents a serious complication of checkpoint inhibitor therapy, especially following ipilimumab-based treatment. Efficient diagnosis and control of diarrhea remains an ongoing challenge. We developed an accelerated management paradigm for patients with ipilimumab-induced diarrhea. Patients who developed significant diarrhea (>five loose stools/day) were presumed to be developing immune colitis. Therapy was interrupted and patients were treated with a methylprednisolone dose pack. If diarrhea was not completely resolved, high-dose steroids and infliximab were promptly added. Only non-responding patients underwent further evaluation for infection or other causes of diarrhea. A total of 242 patients were treated with ipilimumab-based regimens. Forty-six developed significant diarrhea (19%) and thirty-four (74.4%) had a rapid resolution of diarrhea following glucocorticosteroid and infliximab treatment. The median time to resolution of diarrhea was only 8.5 ± 16.4 days. Accelerated treatment for presumed immune-mediated diarrhea resulted in the rapid control of symptoms in the majority of patients. There were no intestinal complications or deaths. Immunosuppressive therapy for diarrhea did not appear to decrease the remission rate or survival. After the control of diarrhea, most patients were able to continue their planned immunotherapy. Further testing in 11/46 patients with unresponsive diarrhea revealed additional diagnoses, allowing their treatment to be adjusted.

Nevoid basal-cell carcinoma syndrome (Gorlin syndrome) is characterized by numerous cutaneous basal cell carcinomas mediated by mutations in the hedgehog pathway. Vismodegib or sonidegib represent promising treatment options. We identified 10 Gorlin patients who were treated with sonidegib (n = 6) or vismodegib (n = 4) between March 2012 and March 2022. We analyzed the activity, toxicity, and duration of the response to oral hedgehog inhibitors. The number of new tumors that developed prior to treatment or after treatment as well as the time of response and durability of responses were assessed. All patients achieved a complete remission. With a 30.7 ± 48.4-month median follow-up, the drug treatment significantly reduced the number of new basal cell cancers from a mean of 28.3 ± 24.6 prior to treatment to a mean of 1.4 ± 2.0 during treatment (p = 0.0048). The median time to develop a new basal cell cancer was 47.3 months. Three patients eventually developed localized recurrences. After resection, ongoing treatment suppressed the development of additional lesions. One patient developed numerous new drug-resistant basal cell cancers and died of acute leukemia. Six patients required treatment modifications for toxicity. Sustained hedgehog inhibitor treatment can suppress the progression of both new and existing basal cell carcinomas for an extended period. Drug administration schedule adjustments improved tolerance without altering efficacy, potentially contributing to a prolonged response duration.

As electric vehicle adoption grows, understanding the impact of electric vehicle charging on electricity grids becomes increasingly important. Accurate grid impact modelling requires high-quality charging infrastructure data. This study examined the electric vehicle recharging infrastructure and usage patterns in a region of the Italian Alps over a three-year period from 2021 to 2023. The primary objectives were to analyze the growth and distribution of electric vehicle charging stations, assess energy consumption, and evaluate charging behaviours across various recharging points. The research involved collecting empirical data from 411,800 recharging sessions and simulated data using the emobpy tool to model energy consumption and charging behavior. Key findings reveal a substantial increase in the number of recharging points, from 673 in 2021 to 970 in 2023, with the total energy delivered increasing from 938 MWh in 2021 to 4133 MWh in 2023. The data showed distinct temporal trends: AC points were primarily used during the day, while DC points saw higher usage during morning and late afternoon peaks, aligning with travelling times. The study’s validation of simulation results against empirical data emphasized the importance of high-quality input for accurate grid impact assessments. These findings suggest the necessity for strategic placement of recharging infrastructure and provide practical insights for policymakers, urban planners, and utility companies to support sustainable electric vehicle integration.

Prescriptive analytics plays an important role in decision making in smart factories by utilizing the available data to gain actionable insights. The planning, integration and development of such use cases still poses manifold challenges. Use cases are still being implemented as standalone versions; the existing IT-infrastructure is not fit for integrative bidirectional decision communication, and implementations only reach low technical readiness levels. We propose a reference architecture for the integration of prescriptive analytics use cases in smart factories. The method for the empirically grounded development of reference architectures by Galster and Avgeriou serves as a blueprint. Through the development and validation of a specific IoT-Factory use case, we demonstrate the efficacy of the proposed reference architecture. We expand the given reference architecture for one use case to the integration of a smart factory and its application to multiple use cases. Moreover, we identify the interdependency among multiple use cases within dynamic environments. Our prescriptive reference architecture provides a structured way to improve operational efficiency and optimize resource allocation.

This study aimed to investigate the diagnostic performance of breast mass detection on monoenergetic image data at 40 keV (MonoE40) and on iodine maps (IM) compared with conventional image data (CI). In this prospective single-center case-control study, 50 breast cancer patients were examined using contrast-enhanced dual-layer spectral CT. For qualitative and quantitative comparison of MonoE40 and IM with CI image data, four blinded, independent readers assessed 300 randomized single slices (two slices for each imaging type per case) with or without cancerous lesions for the presence of a breast mass. Detection sensitivity and specificity were calculated and readers rated their subjective diagnostic certainty. For statistical analysis of sensitivity and specificity, a paired t-test and ANOVA were used (significance level p = 0.05). A total of 50 female patients (median age 51 years, range 28–83 years) participated. IM had the highest overall scores in sensitivity and specificity for breast cancer detection, with 0.97 ± 0.06 and 0.95 ± 0.07, respectively, compared with 0.90 ± 0.04 and 0.92 ± 0.06 in CI. MonoE40 yielded a sensitivity of 0.96 ± 0.02 and specificity of 0.94 ± 0.08. All differences in sensitivity and specificity between MonoE or IM and CI were statistically significant (p < 0.001). The superiority of IM sensitivity and specificity was most pronounced in patients with dense breasts. Spectral CT improved the detection of breast cancer with higher sensitivity and specificity compared to conventional image data in our study.

Pulsed electric field (PEF) treatment is known as a method that can intensify heat- and mass-transfer-based processes such as osmotic dehydration, drying, or freeze-drying. However, the literature about its impact on quality of freeze-dried products is limited to a few raw materials. The aim of this study was to analyze the effect of PEF on the cell disintegration index, selected bioactive compounds, and physical quality parameters of freeze-dried pumpkin. The final quality of the freeze-dried product was evaluated by residual moisture content, color analysis, total phenolic content, total carotenoid content, sugars content, and hygroscopic properties. The application of PEF treatment induced the disintegration of pumpkin cells even at low energy input (0.11 kJ/kg), and the saturation level of electroporation was reached after 4 kJ/kg. PEF treatment at 2 kJ/kg allowed 40% more total carotenoids to be retained in comparison to the untreated sample. Furthermore, all PEF-treated freeze-dried pumpkin samples exhibited lower sucrose content but had higher glucose and fructose contents in comparison to the reference samples. However, this effect was more pronounced when the shelf temperature was equal to 40 °C.

Utilizing titanium diboride (TiB2) inoculation for grain-refining purposes is a widely established practice in aluminum casthouses and foundries. Since this inoculation is usually implemented jointly with or between routine melt treatment steps ahead of casting, it is important to know whether and how other melt treatment processes affect the fade of TiB2 particles. For the present study, we investigated the influence of degassing process on the separation behavior of TiB2 particles in aluminum melt. Multiple sampling methods were employed and the samples were analyzed via spectrometer analysis. The removal efficiency of TiB2 during the gas-purging process of 5083 aluminum melt was confirmed to be significant over 10 min of treatment time. The rate at which the TiB2 content decays was found to increase with the impeller rotary speed from 400 rounds per minute (rpm) to 700 rpm. The separation rate of TiB2 particles was obtained to be 0.05–0.08 min−1 by fitting the experimental data. Particle mapping results suggest that the TiB2 particles were separated to a dross layer. The obtained experimental results were used to quantitatively evaluate the conventional deterministic flotation model. The deviation between the conventional model and the experimental data was explained through the entrainment–entrapment (EE) model. Suggestions were made for future analytical and experimental works which may validate the EE model.

Incentive policies play a crucial role in encouraging the adoption of renewable energy sources and energy efficiency measures. This study analyzes and compares the incentives for energy transition in the South Tyrol region of Italy using a marginal abatement cost (MAC) curve constructed with an expert-based approach. The incentives for residential energy efficiency, mobility, and boiler replacement are characterized based on assumptions for costs, energy savings, and parameters. The resulting expert-based MAC curve analysis reveals boiler replacement incentives to be the most cost-effective, yielding CO2 reductions at the lowest cost but with limited potential as the incentive is limited to apartment blocks that are not in district heating areas. Mobility incentives enabling electric vehicle adoption have the highest CO2 reduction potential, albeit at higher costs per ton abated. Residential energy efficiency incentives fall between the two for cost-effectiveness and potential. The MAC curve approach provides a useful comparison of cost-effectiveness versus potential, guiding policy prioritization. This techno-economic assessment methodology can be applied to other regions pursuing energy transition. Overall, a balanced policy mix encompassing transport, buildings, and heating is required for comprehensive low-carbon transition.

Objective: In rare cases, Lyme neuroborreliosis (LNB) can induce cerebral vasculitis leading to severe stenosis of the cerebral vasculature and consecutive ischemia. Therapy is based on anti-biotic treatment of the tick-borne disease, whereas interventional therapeutic options have not been assessed yet. Material and Methods: We report on a patient with LNB and concomitant stenoses and progressive and fatal vasculitis of the cerebral vessels despite all therapeutic efforts by the departments of neurology and interventional neuroradiology. In this context, we also conducted a literature review on endovascular treatment of LNB-associated cerebral ischemia. Results: A 52-year-old female presented with transient neglect and psychomotor slowdown (initial NIHSS = 0). MRI and serology led to the diagnosis of basal meningitis due to LNB with vasculitis of cerebral arteries. Despite immediate treatment with antibiotics and steroids, neurologic deterioration (NIHSS 8) led to an emergency angiography on day 2 after admission. Hemodynamically relevant stenoses of the MCA were treated via spasmolysis and PTA, leading to almost complete neurological recovery. Despite intensified medical treatment, the vasculitis progressed and could only be transiently ameliorated via repetitive spasmolysis. On day 19, she again presented with significant neurologic deterioration (NIHSS 9), and PTA and stenting of the nearly occluded MCA were performed with a patent vessel, initially without hemorrhagic complications. Despite all therapeutic efforts and preserved stent perfusion, vasculitis worsened and the concurrent occurrence of subdural hemorrhage led to the death of the patient. Conclusion: Neuroradiological interventions, i.e., spasmolysis, PTA, and, if necessary, stenting, can and should be considered in cases of LNB-induced vasculitis and stroke that are refractory to best medical treatment alone. Key point: Neuroradiological interventions can be considered in patients with vascular complications of Lyme neuroborreliosis as an additional extension of the primary drug therapy.

Intracranial pressure (ICP) burden or pressure time dose (PTD) is a valuable clinical indicator for pending intracranial hypertension, mostly based on threshold exceedance. Pulse frequency and waveform morphology (WFM) of the ICP signal contribute to PTD. The temporal resolution of the ICP signal has a great influence on PTD calculation but has not been systematically studied yet. Hence, the temporal resolution of the ICP signal on PTD calculation is investigated. We retrospectively analysed continuous 48 h ICP recordings with high temporal resolution obtained from 94 patients at the intensive care unit who underwent neurosurgery due to an intracranial haemorrhage and received an intracranial pressure probe (43 females, median age: 72 years, range: 23 to 88 years). The cumulative area under the curve above the threshold of 20 mmHg was compared for different temporal resolutions of the ICP signal (beat-to-beat, 1 s, 300 s, 1800 s, 3600 s). Events with prolonged ICP elevation were compared to those with few isolated threshold exceedances. PTD increased for lower temporal resolutions independent of WFM and frequency of threshold exceedance. PTDbeat-to-beat best reflected the impact of frequency of threshold exceedance and WFM. Events that could be distinguished in PTDbeat-to-beat became magnified more than 7-fold in PTD1s and more than 104 times in PTD1h, indicating an overestimation of PTD. PTD calculation should be standardised, and beat-by-beat PTD could serve as an easy-to-grasp indicator for the impact of frequency and WFM of ICP elevations on ICP burden.

The transition to sustainable waterways transport is imperative in the face of environmental and climate challenges. Local lakes, often overlooked, play a significant role in regional transportation networks and ecosystems. This study focuses on Orta lake, Italy, and aims to facilitate its transition to sustainable inland waterways transport by substituting its diesel-based fleet with electric vessels. Firstly, a comprehensive market analysis was conducted to understand the available electric vessel models and their technical characteristics. This included parameters such as capacity, range, and charging time. Based on the market analysis, an optimization model was developed to determine the minimum number of electric vessels required to completely replace the existing diesel-based fleet. This model considers various constraints and objectives, such as meeting transport demand, minimizing the number of vessels, and reducing environmental impact. The developed model was then applied to the case study of Orta lake using the collected market data. The results indicate an optimal fleet configuration and provide insights into the feasibility and implications of the transition. This study contributes to the growing body of knowledge on sustainable inland waterways transport and offers a methodology that can be replicated and adapted for other local lakes or maritime settings.

The European Union has seen a strong growth of electric passenger vehicles over the last decade. The steady increase in the number of electric vehicles requires a thorough examination of the current infrastructure and their future development, which are critical to the continuous market growth of this technology. The underdeveloped charging infrastructure is identified as one of the main barriers, next to the purchase price of electric vehicles. Thus, the infrastructure (supply side) and the vehicles (demand side) must coevolve and consider not only the quantitative balance between EVs and charging stations but the interlinkages with social, technical, and economic criteria for the overall system development. In this context, the methods presented in this paper address regional specificities when developing an integrated network of charging infrastructure for private and public passengers transport in an alpine region. The results of the application of the methodology to a mountainous area present the potential for replicability and highlight the importance of considering regional characteristics and of stakeholder involvement.

Public bus decarbonization is increasingly important to address the global issue of climate change. There are several challenges associated with large-scale introduction of zero-emission technologies in public fleets. This is especially the case in an extra-urban context, of mountain regions with challenging weather conditions. In this work the analysis of the state-of-the-art ZEBs, local bus lines, and timetables was performed to understand the best fit of technology—battery electric buses (BEBs) or fuel cell electric buses (FCEBs)—for each line in such a region. Further, a simulation tool was developed to calculate the compatibility of zero-emission technologies with the current needs of the public transportation considering distance, altitude difference, and climate conditions. The results show that a complete switch of the fleet is possible with a slight increase in the number of buses and that there is no clear difference in the distance covered in mountainous areas by BEBs versus FCEBs, but that both technologies can cover similar distances. The tool developed is not limited to bus fleets but can be applied to all kinds of fleets that cover clearly defined daily routes.

Despite the availability and ease of collecting a large amount of free, unlabeled data, the expensive and time-consuming labeling process is still an obstacle to labeling a sufficient amount of training data, which is essential for building supervised learning models. Here, with low labeling cost, the active learning (AL) technique could be a solution, whereby a few, high-quality data points are queried by searching for the most informative and representative points within the instance space. This strategy ensures high generalizability across the space and improves classification performance on data we have never seen before. In this paper, we provide a survey of recent studies on active learning in the context of classification. This survey starts with an introduction to the theoretical background of the AL technique, AL scenarios, AL components supported with visual explanations, and illustrative examples to explain how AL simply works and the benefits of using AL. In addition to an overview of the query strategies for the classification scenarios, this survey provides a high-level summary to explain various practical challenges with AL in real-world settings; it also explains how AL can be combined with various research areas. Finally, the most commonly used AL software packages and experimental evaluation metrics with AL are also discussed.

Checkpoint inhibitor therapy for metastatic melanoma has dramatically improved outcomes. Currently, 20 to 40% of treated patients achieve lengthy remissions. It is not clear whether patients in remission require ongoing therapy or if treatment can be safely discontinued. A retrospective chart review was performed of patients who underwent elective treatment discontinuation after two negative scans three months apart. Of 132 checkpoint inhibitor-treated patients, 46 achieved a complete response (34.8%) and electively discontinued therapy. The progression-free survival was 97.5% at 1 year and 94.7% at 3 years following treatment discontinuation. The median duration of follow-up was 26 months. In total, 4 of 46 individuals (8.7%) eventually relapsed (median time to relapse: 27 months). The median disease-specific survival of the entire cohort was not reached and was 100% at 4 years from the start of therapy. Two patients eventually died, one from melanoma and the other from an unrelated illness. We have identified an elective treatment discontinuation strategy that is generalizable to a variety of checkpoint inhibitor ± targeted therapy regimens. We found that most complete remissions remained durable after elective treatment discontinuation. We hypothesize that this approach could decrease potential drug toxicities, reduce the treatment-related financial burden, and improve patients’ quality of life.

Despite the availability of a large amount of free unlabeled data, collecting sufficient training data for supervised learning models is challenging due to the time and cost involved in the labeling process. The active learning technique we present here provides a solution by querying a small but highly informative set of unlabeled data. It ensures high generalizability across space, improving classification performance with test data that we have never seen before. Most active learners query either the most informative or the most representative data to annotate them. These two criteria are combined in the proposed algorithm by using two phases: exploration and exploitation phases. The former aims to explore the instance space by visiting new regions at each iteration. The second phase attempts to select highly informative points in uncertain regions. Without any predefined knowledge, such as initial training data, these two phases improve the search strategy of the proposed algorithm so that it can explore the minority class space with imbalanced data using a small query budget. Further, some pseudo-labeled points geometrically located in trusted explored regions around the new labeled points are added to the training data, but with lower weights than the original labeled points. These pseudo-labeled points play several roles in our model, such as (i) increasing the size of the training data and (ii) decreasing the size of the version space by reducing the number of hypotheses that are consistent with the training data. Experiments on synthetic and real datasets with different imbalance ratios and dimensions show that the proposed algorithm has significant advantages over various well-known active learners.

Humans learn movements naturally, but it takes a lot of time and training to achieve expert performance in motor skills. In this review, we show how modern technologies can support people in learning new motor skills. First, we introduce important concepts in motor control, motor learning and motor skill learning. We also give an overview about the rapid expansion of machine learning algorithms and sensor technologies for human motion analysis. The integration between motor learning principles, machine learning algorithms and recent sensor technologies has the potential to develop AI-guided assistance systems for motor skill training. We give our perspective on this integration of different fields to transition from motor learning research in laboratory settings to real world environments and real world motor tasks and propose a stepwise approach to facilitate this transition.

Background: During cochlear implantation, the electrode array has significant friction with the sensitive endocochlear lining and causes mutual mechanical trauma while the array is being inserted. Both, the impact of insertion speed on electrode friction and the relationship of electrode insertion force and friction have not been adequately investigated to date. Methods: In this study, friction coefficients between a CI electrode array (31.5 mm) and a tissue simulating the endocochlear lining have been acquired, depending on different insertion speeds (0.1, 0.5, 1.0, 1.5, and 2.0 mm/s). Additionally, the electrode insertion forces during the placing into a scala tympani model were recorded and correlated with the friction coefficient. Results: It was shown that the friction coefficient reached the lowest value at an insertion speed of 0.1 mm/s (0.24 ± 0.13), a maximum occurred at 1.5 mm/s (0.59 ± 0.12), and dropped again at 2 mm/s (0.45 ± 0.11). Similar patterns were observed for the insertion forces. Consequently, a high correlation coefficient (0.9) was obtained between the insertion forces and friction coefficients. Conclusion: The present study reveals a non-linear increase in electrode array friction, when insertion speed raises and reports a high correlation between friction coefficient and electrode insertion force. This dependence is a relevant future parameter to evaluate and reduce cochlear implant insertion trauma. Significance statement: Here, we demonstrated a dependence between cochlear electrode insertion speed and its friction behavior and a high correlation to insertion force. Our study provides valuable information for the evaluation and prevention of cochlear implant insertion trauma and supports the optimization of cochlear electrode arrays regarding friction characteristics.

The U.S. Geological Survey is actively investigating remote sensing of surface velocity and river discharge (discharge) from satellite-, high altitude-, small, unmanned aircraft systems- (sUAS or drone), and permanent (fixed) deployments. This initiative is important in ungaged basins and river reaches that lack the infrastructure to deploy conventional streamgaging equipment. By coupling alternative discharge algorithms with sensors capable of measuring surface velocity, streamgage networks can be established in regions where data collection was previously impractical or impossible. To differentiate from satellite or high-altitude platforms, near-field remote sensing is conducted from sUAS or fixed platforms. QCam is a Doppler (velocity) radar mounted and integrated on a 3DR© Solo sUAS. It measures the along-track surface velocity by spot dwelling in a river cross section at a vertical where the maximum surface velocity is recorded. The surface velocity is translated to a mean-channel (mean) velocity using the probability concept (PC), and discharge is computed using the PC-derived mean velocity and cross-sectional area. Factors including surface-scatterer quality, flight altitude, propwash, wind drift, and sample duration may affect the radar-returns and the subsequent computation of mean velocity and river discharge. To evaluate the extensibility of the method, five science flights were conducted on four rivers of varying size and dynamics and included the Arkansas River, Colorado (CO), USA (two events); Salcha River near Salchaket, Alaska (AK), USA; South Platte River, CO, USA; and the Tanana River, AK, USA. QCam surface velocities and river discharges were compared to conventional streamgaging methods, which represented truth. QCam surface velocities for the Arkansas River, Salcha River, South Platte River, and Tanana River were 1.02 meters per second (m/s) and 1.43 m/s; 1.58 m/s; 0.90 m/s; and 2.17 m/s, respectively. QCam discharges (and percent differences) were 9.48 (0.3%) and 20.3 cubic meters per second (m3/s) (2.5%); 62.1 m3/s (−10.4%); 3.42 m3/s (7.3%), and 1579 m3/s (−18.8%). QCam results compare favorably with conventional streamgaging and are a viable near-field remote sensing technology that can be operationalized to deliver real-time surface velocity, mean velocity, and river discharge, if cross-sectional area is available.

The modeling of energy systems with high penetration of renewables is becoming more relevant due to environmental and security issues. Researchers need to support policy makers in the development of energy policies through results from simulating tools able to guide them. The EPLANopt model couples a multi-objective evolutionary algorithm to EnergyPLAN simulation software to study the future best energy mix. In this study, EPLANopt is applied at country level to the Italian case study to assess the best configurations of the energy system in 2030. A scenario, the result of the optimization, is selected and compared to the Italian integrated energy and climate action plan scenario. It allows a further reduction of CO2 emissions equal to 10% at the same annual costs of the Italian integrated energy and climate action plan scenario. Both these results are then compared to climate change scenarios through the carbon budget indicator. This comparison shows the difficulties to meet the Paris Agreement target of limiting the temperature increase to 1.5 °C. The results also show that this target can only be met through an increase in the total annual costs in the order of 25% with respect to the integrated energy and climate action plan scenario. However, the study also shows how the shift in expenditure from fossil fuels, external expenses, to investment on the national territory represents an opportunity to enhance the national economy.

This study aimed to examine the financing of photovoltaics research and development by analyzing funding from public (European Union and national budgets) and private sources (enterprises), Strategic Energy Technology Plan participating countries being the main focus (European Union Member States plus Norway and Turkey). In the coming years, photovoltaics are expected to heavily contribute towards the achievement of audacious climate and energy objectives. Continuous monitoring of the effects is of great importance to assess a course of action taken at such a large scale. It will be revealed that the distribution of funding provided by national budgets highly concentrates on a few Member States, which is part of a general trend in Research and Development within Europe. Approximately 85% of the current European investment provided by the EU budget is administered in the framework of the Horizon 2020 (2014–2020) program; private investment behaves differently. The European photovoltaics manufacturing market has been obliterated by low-budget imported goods. A major characteristic is that the remaining companies are almost exclusively privately held. Gathering data has consequently been a challenge, as opposed to the readily available public datasets.

The human skin, as the boundary organ between the human body and the environment, is under the constant influence of free radicals (FR), both from the outside in and from the inside out. Carotenoids are known to be powerful antioxidant substances playing an essential role in the reactions of neutralization of FR (mainly reactive oxygen species ROS). Carotenoid molecules present in the tissue are capable of neutralizing several attacks of FR, especially ROS, and are then destroyed. Human skin contains carotenoids, such as α-, γ-, β-carotene, lutein, zeaxanthin, lycopene and their isomers, which serve the living cells as a protection against oxidation. Recent studies have reported the possibility to investigate carotenoids in human skin quickly and non-invasively by spectroscopic means. Results obtained from in-vivo studies on human skin have shown that carotenoids are vital components of the antioxidative protective system of the human skin and could serve as marker substances for the overall antioxidative status. Reflecting the nutritional and stress situation of volunteers, carotenoids must be administered by means of antioxidant-rich products, e.g., in the form of fruit and vegetables. Carotenoids are degraded by stress factors of any type, inter alia, sun radiation, contact with environmental hazards, illness, etc. The kinetics of the accumulation and degradation of carotenoids in the skin have been investigated.

Recently, it has been demonstrated that particulate substances penetrate preferentially into the hair follicles and that the penetration depth depends on the particle size. In the present study, the influence of the vehicle of the particulate substances on the penetration depth was investigated. Four different formulations (ethanolic suspension, aqueous suspension, ethanolic gel and aqueous gel) containing peptide-loaded particles of 1 µm in diameter were prepared and applied on porcine ear skin. After penetration, punch biopsies were taken and the penetration depths of the particles were investigated by laser scanning microscopy. The deepest penetration was achieved with the gel formulations demonstrating an influence of the vehicle on the penetration depth of particulate substances.

CMOS-based devices and the control of the materials properties by nanotechnology enabled significant progresses in the field of metal chemiresistors for gas sensing applications both in terms of miniaturization and performances (e.g., gas sensitivity). In this regard, ink-jet printing is a powerful technique to achieve high-volume production and meet the emerging consumer market demands. The paste formulation is an obvious aspect to consider for achieving a viscosity range suitable for ink-jet printing. More importantly, it is often an underestimated task which impacts the gas response of the resulting chemiresistors in terms of sensitivity, cross-sensitivity and baseline drift. In this manuscript, the effects on the film morphology and gas response upon removing ethyl-cellulose from the paste formulation is reported. Improvements in terms of sensitivity and baseline drift were observed.

Long-term slash-and-burn experiments, when compared with intensive tillage without manuring, resulted in a huge data set relating to potential crop yields, depending on soil quality, crop type, and agricultural measures. Cultivation without manuring or fallow phases did not produce satisfying yields, and mono-season cropping on freshly cleared and burned plots resulted in rather high yields, comparable to those produced during modern industrial agriculture - at least ten-fold the ones estimated for the medieval period. Continuous cultivation on the same plot, using imported wood from adjacent areas as fuel, causes decreasing yields over several years. The high yield of the first harvest of a slash-and-burn agriculture is caused by nutrient input through the ash produced and mobilization from the organic matter of the topsoil, due to high soil temperatures during the burning process and higher topsoil temperatures due to the soil’s black surface. The harvested crops are pure, without contamination of any weeds. Considering the amount of work required to fight weeds without burning, the slash-and-burn technique yields much better results than any other tested agricultural approach. Therefore, in dense woodland, without optimal soils and climate, slash-and-burn agriculture seems to be the best, if not the only, feasible method to start agriculture, for example, during the Late Neolithic, when agriculture expanded from the loess belt into landscapes less suitable for agriculture. Extensive and cultivation with manuring is more practical in an already-open landscape and with a denser population, but its efficiency in terms of the ratio of the manpower input to food output, is worse. Slash-and-burn agriculture is not only a phenomenon of temperate European agriculture during the Neolithic, but played a major role in land-use in forested regions worldwide, creating anthromes on a huge spatial scale.

Renewable energy sources are vital to achieving Europe’s 2030 energy transition goals. Technological innovation, driven by public expenditures on research and development, is a major driver for this change. Thus, an extensive dataset on these expenditures of the European Member States and the European Commission, dating back to the early 1970s, was created. This paper creates predictive scenarios of public investment in renewable energy research and development in Europe based on this historical dataset and current trends. Funding from both, European Member States and the European Commission, between today and 2030 are used in the analysis. The impact on the cumulative knowledge stock is also estimated. Two projection scenarios are presented: (1) business as usual; and (2) an advanced scenario, based on the assumption that the Mission Innovation initiative causes public expenditures to increase in the coming years. Both scenarios are compared to the European 2030 climate and energy framework target sets. Results indicate that Member States in Europe currently tend to fund renewables more than the European Commission, but funding from both sources is expected to increase in the future. Furthermore, the European Commission distributes its funding more equally across the various renewable energy sources than Member States.