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Recent research on a special type of sexual reproduction and zygospore formation in Zygnematophyceae, the sister group of land plants, is summarized. Within this group, gamete fusion occurs by conjugation. Zygospore development in Mougeotia, Spirogyra and Zygnema is highlighted, which has recently been studied using Raman spectroscopy, allowing chemical imaging and detection of changes in starch and lipid accumulation. Three-dimensional reconstructions after serial block-face scanning electron microscopy (SBF-SEM) or focused ion beam SEM (FIB-SEM) made it possible to visualize and quantify cell wall and organelle changes during zygospore development. The zygospore walls undergo strong modifications starting from uniform thin cell walls to a multilayered structure. The mature cell wall is composed of a cellulosic endospore and exospore and a central mesospore built up by aromatic compounds. In Spirogyra, the exospore and endospore consist of thick layers of helicoidally arranged cellulose fibrils, which are otherwise only known from stone cells of land plants. While starch is degraded during maturation, providing building blocks for cell wall formation, lipid droplets accumulate and fill large parts of the ripe zygospores, similar to spores and seeds of land plants. Overall, data show similarities between streptophyte algae and embryophytes, suggesting that the genetic toolkit for many land plant traits already existed in their shared algal ancestor. This article is part of the theme issue 'The evolution of plant metabolism'. [ABSTRACT FROM AUTHOR]

Introduction: Point-of-care (POC) manufacturing of chimeric antigen receptor (CAR) modified T cell has expanded rapidly over the last decade. In addition to the use of CD19 CAR T cells for hematological diseases, there is a growing interest in targeting a variety of tumor-associated epitopes. Methods: Here, we report the manufacturing and characterization of autologous anti-CD20 CAR T cells from melanoma patients within phase I clinical trial (NCT03893019). Using a second-generation lentiviral vector for the production of the CD20 CAR T cells on the CliniMACS Prodigy®. Results: We demonstrated consistency in cell composition and functionality of the products manufactured at two different production sites. The T cell purity was >98.5%, a CD4/CD8 ratio between 2.5 and 5.5 and transduction rate between 34% and 61% on day 12 (harvest). Median expansion rate was 53-fold (range, 42-65-fold) with 1.7-3.8×109 CAR T cells at harvest, a sufficient number for the planned dose escalation steps (1×105/kg, 1×106/kg, 1×107/kg BW). Complementary research of some of the products pointed out that the CAR+ cells expressed mainly central memory T-cell phenotype. All tested CAR T cell products were capable to translate into T cell activation upon engagement of CAR target cells, indicated by the increase in pro-inflammatory cytokine release and by the increase in CAR T cell amplification. Notably, there were some interindividual, cell-intrinsic differences at the level of cytokine release and amplification. CAR-mediated T cell activation depended on the level of CAR cognate antigen. Discussion: In conclusion, the CliniMACS Prodigy® platform is well suited for decentralized POC manufacturing of anti-CD20 CAR T cells and may be likewise applicable for the rapid and automated manufacturing of CAR T cells directed against other targets. [ABSTRACT FROM AUTHOR]

Current cable-road layouts for timber harvesting in steep terrain are often based on either manual planning or automated layouts generated from low-resolution GIS data, limiting potential benefits and informed decision-making. In this paper, we present a novel approach to improve cable-road design using multi-objective optimization based on realistic cable-road representations. We systematically compare the effectiveness of single-objective and multi-objective optimization methods for generating layouts using these representations. We implement and evaluate the performance of a weighted single-objective approach, the AUGMECON2 and NSGA-II multi-objective methods in comparison to a layout manually created by a forestry expert, taking into account installation costs, harvesting volumes, residual stand damage and lateral yarding workload. In addition to implementing the first linear programming multi-objective optimization for realistic cable-road representations by adapting AUGMECON2, we also present the first implementation of a multi-objective genetic algorithm (NSGA-II) with simulated annealing for this purpose and evaluate their respective strengths. We find that the use of multi-objective optimization provides advantages in terms of cost-effective, balanced and adaptable cable-road layouts while allowing economic and environmental considerations to be incorporated into the design phase. [ABSTRACT FROM AUTHOR]

Introduction: Point-of-care (POC) manufacturing of chimeric antigen receptor (CAR) modified T cell has expanded rapidly over the last decade. In addition to the use of CD19 CAR T cells for hematological diseases, there is a growing interest in targeting a variety of tumor-associated epitopes. Methods: Here, we report the manufacturing and characterization of autologous anti-CD20 CAR T cells from melanoma patients within phase I clinical trial (NCT03893019). Using a second-generation lentiviral vector for the production of the CD20 CAR T cells on the CliniMACS Prodigy®. Results: We demonstrated consistency in cell composition and functionality of the products manufactured at two different production sites. The T cell purity was >98.5%, a CD4/CD8 ratio between 2.5 and 5.5 and transduction rate between 34% and 61% on day 12 (harvest). Median expansion rate was 53-fold (range, 42-65-fold) with 1.7-3.8×109 CAR T cells at harvest, a sufficient number for the planned dose escalation steps (1×105/kg, 1×106/kg, 1×107/kg BW). Complementary research of some of the products pointed out that the CAR+ cells expressed mainly central memory T-cell phenotype. All tested CAR T cell products were capable to translate into T cell activation upon engagement of CAR target cells, indicated by the increase in pro-inflammatory cytokine release and by the increase in CAR T cell amplification. Notably, there were some interindividual, cell-intrinsic differences at the level of cytokine release and amplification. CAR-mediated T cell activation depended on the level of CAR cognate antigen. Discussion: In conclusion, the CliniMACS Prodigy® platform is well suited for decentralized POC manufacturing of anti-CD20 CAR T cells and may be likewise applicable for the rapid and automated manufacturing of CAR T cells directed against other targets. [ABSTRACT FROM AUTHOR]

Introduction: Point-of-care (POC) manufacturing of chimeric antigen receptor (CAR) modified T cell has expanded rapidly over the last decade. In addition to the use of CD19 CAR T cells for hematological diseases, there is a growing interest in targeting a variety of tumor-associated epitopes. Methods: Here, we report the manufacturing and characterization of autologous anti-CD20 CAR T cells from melanoma patients within phase I clinical trial (NCT03893019). Using a second-generation lentiviral vector for the production of the CD20 CAR T cells on the CliniMACS Prodigy®. Results: We demonstrated consistency in cell composition and functionality of the products manufactured at two different production sites. The T cell purity was >98.5%, a CD4/CD8 ratio between 2.5 and 5.5 and transduction rate between 34% and 61% on day 12 (harvest). Median expansion rate was 53-fold (range, 42-65-fold) with 1.7-3.8×109 CAR T cells at harvest, a sufficient number for the planned dose escalation steps (1×105/kg, 1×106/kg, 1×107/kg BW). Complementary research of some of the products pointed out that the CAR+ cells expressed mainly central memory T-cell phenotype. All tested CAR T cell products were capable to translate into T cell activation upon engagement of CAR target cells, indicated by the increase in pro-inflammatory cytokine release and by the increase in CAR T cell amplification. Notably, there were some interindividual, cell-intrinsic differences at the level of cytokine release and amplification. CAR-mediated T cell activation depended on the level of CAR cognate antigen. Discussion: In conclusion, the CliniMACS Prodigy® platform is well suited for decentralized POC manufacturing of anti-CD20 CAR T cells and may be likewise applicable for the rapid and automated manufacturing of CAR T cells directed against other targets. [ABSTRACT FROM AUTHOR]

Summary: The association between nightmare frequency (NMF) and suicidal ideation (SI) is well known, yet the impact of the COVID‐19 pandemic on this relation is inconsistent. This study aimed to investigate changes in NMF, SI, and their association during the COVID‐19 pandemic. Data were collected in 16 countries using a harmonised questionnaire. The sample included 9328 individuals (4848 women; age M[SD] = 46.85 [17.75] years), and 17.60% reported previous COVID‐19. Overall, SI was significantly 2% lower during the pandemic vs. before, and this was consistent across genders and ages. Most countries/regions demonstrated decreases in SI during this pandemic, with Austria (−9.57%), Sweden (−6.18%), and Bulgaria (−5.14%) exhibiting significant declines in SI, but Italy (1.45%) and Portugal (2.45%) demonstrated non‐significant increases. Suicidal ideation was more common in participants with long‐COVID (21.10%) vs. short‐COVID (12.40%), though SI did not vary by COVID‐19 history. Nightmare frequency increased by 4.50% during the pandemic and was significantly higher in those with previous COVID‐19 (14.50% vs. 10.70%), during infection (23.00% vs. 8.10%), and in those with long‐COVID (18.00% vs. 8.50%). The relation between NMF and SI was not significantly stronger during the pandemic than prior (rs = 0.18 vs. 0.14; z = 2.80). Frequent nightmares during the pandemic increased the likelihood of reporting SI (OR = 1.57, 95% CI 1.20–2.05), while frequent dream recall during the pandemic served a protective effect (OR = 0.74, 95% CI 0.59–0.94). These findings have important implications for identifying those at risk of suicide and may offer a potential pathway for suicide prevention. [ABSTRACT FROM AUTHOR]

As launch capabilities and interest in Cislunar missions expand for commercial, government, and military actors alike, so grows the necessity for a robust architecture in the Cislunar region for conducting Space Domain Awareness (SDA). Among the numerous objectives associated with constructing a robust Cislunar SDA architecture, of particular interest is creating an architecture that is cost effective for both architecture users and maintainers. This paper builds on previous work of using reinforcement learning methods to solve the multi-objective Cislunar architecture design problem by modeling a cooperative architecture user that seeks to maximize detectability by the architecture while minimizing total delta-v needed to do so. We also introduce a novel clustering method by which architectures explored during optimization are be grouped together, allowing us to better understand how observers must work in concert to produce optimal results. Through the interactions between the cooperative agent and architectures, we can further our understanding of the architecture design process while gaining insights into the fundamental qualities of a robust Cislunar architecture. [ABSTRACT FROM AUTHOR]

The authors introduce a novel framework that integrates federated learning with Graph Neural Networks (GNNs) to classify diseases, incorporating Human-in-the-Loop methodologies. This advanced framework innovatively employs collaborative voting mechanisms on subgraphs within a Protein-Protein Interaction (PPI) network, situated in a federated ensemble-based deep learning context. This methodological approach marks a significant stride in the development of explainable and privacy-aware Artificial Intelligence, significantly contributing to the progression of personalized digital medicine in a responsible and transparent manner. [ABSTRACT FROM AUTHOR]

Background: Exploring clinical trial data using alternative methods may enhance original study's findings and provide new insights. The SOAP II trial has been published more than 10 years ago; but there is still some speculation that some patients may benefit from dopamine administration for shock management. We aimed to reanalyse the trial under different approaches and evaluate for heterogeneity in treatment effect (HTE). Methods: All patients enrolled in SOAP II were eligible for reanalysis. We used a variety of methods including the win-ratio (WR), a Bayesian reanalysis stratified according to shock type, and both a risk-based and effect-based explorations for HTE. The methods were applied to different endpoints, including a hierarchy of death, new use of renal-replacement therapy (RRT), and new-onset arrhythmia; 28-day mortality; a composite endpoint (mortality, new use of RRT, and new-onset arrhythmia), and days alive and free of ICU at 28-days (DAFICU28). Results: A total of 1679 patients were included (average age was 64.9 years, 57% male, 62% with septic and 17% with cardiogenic shock). All analysis favoured norepinephrine over dopamine. Under the WR approach, dopamine had fewer wins compared to norepinephrine (WR 0.79; 95% confidence intervals [CI] 0.68–0.92; p = 0.003), evident in both cardiogenic and septic shock subgroups. The Bayesian reanalysis for type of shock showed, for dopamine, a probability of harm of 0.95 for mortality, > 0.99 probability of harm for composite endpoint, and 0.91 probability of harm for DAFICU28. The fewer DAFICU28 with dopamine was more apparent in those with cardiogenic shock (0.92). Under the risk-based HTE, there was a high probability that dopamine resulted fewer DAFICU28 in the highest quartile of predicted mortality risk. The effect-based HTE assessment model did not recommended dopamine over norepinephrine for any combination of possible modifiers including age, type of shock, presence of cardiomyopathy, and SOFA score. Receiving dopamine when the effect-based model recommended norepinephrine was associated with an absolute increase in composite endpoint of 6%. Conclusion: The harm associated with the use of dopamine for the management of shock appears to be present in both septic and cardiogenic shock patients. There was no suggestion of any subgroup in which dopamine was found to be favourable over norepinephrine. [ABSTRACT FROM AUTHOR]

We present an economic and straightforward method to introduce 13C-19F spin systems into the deuterated aromatic side chains of phenylalanine as reporters for various protein NMR applications. The method is based on the synthesis of [4-13C, 2,3,5,6-2H4] 4-fluorophenylalanine from the commercially available isotope sources [2-13C] acetone and deuterium oxide. This compound is readily metabolized by standard Escherichia coli overexpression in a glyphosate-containing minimal medium, which results in high incorporation rates in the corresponding target proteins. [ABSTRACT FROM AUTHOR]

Copyright of Monatsschrift Kinderheilkunde is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Large language models, e.g., Chat Generative Pre-Trained Transformer (also known as ChatGPT), are currently contributing enormously to making artificial intelligence even more popular, especially among the general population. However, such chatbot models were developed as tools to support natural language communication between humans. Problematically, it is very much a "statistical correlation machine" (correlation instead of causality), and there are indeed ethical concerns associated with the use of AI language models including ChatGPT, such as bias, privacy, and abuse. This paper highlights specific ethical concerns about ChatGPT and articulates key challenges when ChatGPT is used in various applications. Practical recommendations for different stakeholders of ChatGPT are also proposed that can serve as checklist guidelines for those applying ChatGPT in their applications. These best practice examples are expected to motivate the ethical use of ChatGPT. [ABSTRACT FROM AUTHOR]

Introduction: Dementia, depression, and cardiovascular disease are major public health concerns for older adults, requiring early intervention. This study investigates whether a virtual reality cognitive remediation program (VR-CR) can improve cognitive function and depressive symptoms in older adults, and determines the necessary sample size for future studies. Integrated VR and CR interventions have shown promising outcomes in older adults with neurodegenerative and mental health disorders. Methods: This secondary analysis of a randomized controlled trial involves adults aged 58–75 years with bipolar disorder, excluding those with acute episodes, epilepsy, or severe eye diseases. The experimental group received standard treatment plus VR-CR, while the control group received only standard treatment. Results: No baseline differences were found between the experimental and control groups. No significant improvement was observed in the overall cognitive function test (p = 0.897) or in depressive symptoms (p = 0.322). A phase III efficacy study requires a sample size of 28 participants (alpha = 0.05, beta = 0.20). Conclusions: VR-CR can potentially treat depressive symptoms in adults and older adults, but the results support conducting phase III studies to further investigate these outcomes. However, the improvement in cognitive performance in the elderly is less pronounced than in younger individuals. [ABSTRACT FROM AUTHOR]

In recent decades, a noticeable trend has emerged in medical and dental schools to adjust their curricula to promote learning strategies and habits geared towards long-term knowledge retention. This systematic review therefore sought to examine whether different teaching methods influence students’ preferred learning approaches (deep, strategic, and surface approach) and indirectly affect their academic performance. Furthermore, it provides a comprehensive overview of the inconsistencies evident in previous literature regarding the relationship between learning approaches and academic performance of medical and dental students. A thorough search across eight databases yielded 49 relevant studies published between the years 2000 and 2023. The majority of studies revealed that whilst deep and strategic learners tend to excel at medical or dental school, surface learners appear to struggle under intense workload and pressure. Hence, a common consensus emerged amongst the existing literature that there is a relative benefit in attempting to guide students towards deep and strategic learning habits and to minimise surface-related learning strategies. However, results also conveyed that merely modifying the teaching methods used in medical and dental schools has limited merit. As such, the results emphasised the lack of a ‘one-size-fits-all’ teaching method. Common factors influencing learning approaches were subsequently identified, and based on these findings, an outlook was put forth to integrate a cognitive neuroscience approach into higher education. These directions for future investigations aim to help students reach their full potential by understanding the processes underlying efficient learning and by being mindful of respective encouraging and discouraging factors. [ABSTRACT FROM AUTHOR]

Background: Utilization by low acuity patients contributes to emergency department (ED) crowding. Both knowledge deficits about adequate care levels and access barriers in primary care are important promoters of such presentations. Concurrently, not having a general practitioner (GP) increases the likelihood of low-acuity ED utilization. This pilot study thus investigated feasibility, acceptance, and potential effects of an ED-delivered intervention for low-acuity patients with no regular primary care provider, consisting of an educational leaflet on acute care options and an optional GP appointment scheduling service. Methods: Low-acuity ED consulters not attached to a GP were given an information leaflet about alternative care offers for acute health problems and offered optional personal appointment scheduling at a local GP practice. Patients were surveyed on demographics, medical characteristics, health care utilization, valuation of the intervention, and reasons for not being attached to a GP and visiting the ED. A follow-up survey was conducted after twelve months. Trends in health and health care utilization were evaluated. Results: Between December 2020 and April 2022, n = 160 patients were enrolled, n = 114 were followed up. The study population was characterized by young age (mean 30.6 years) and predominantly good general health. Besides good health, personal mobility was a central reason for not being attached to a GP, but general preference for specialists and bad experiences with primary care were also mentioned. Most frequently stated motives for the ED consultation were subjective distress and anxiety, a belief in the superiority of the hospital, and access problems in primary care. The interventional offers were favorably valued, 52.5% (n = 84) accepted the GP appointment scheduling service offer. At follow-up, GP utilization had significantly increased, while there were no significant changes regarding utilization of other providers, including ED. An additional practice survey showed a 63.0% take-up rate for the appointment service. Conclusions: With this pilot study, we were able to show that a personalized appointment scheduling service seems to be a promising approach to promote GP attachment and increase primary care utilization in patients without a regular GP in a highly urbanized setting. Further larger-scale studies are needed to investigate potential quantitative effects on ED visits. Trial Registration: German Clinical Trials Register (DRKS00023480); date 2020/11/27. [ABSTRACT FROM AUTHOR]

This article introduces a new basis for optimising cable corridor layouts in timber extraction on steep terrain by using a digital twin of a forest. Traditional approaches for generating cable corridor layouts rely on less accurate contour maps, which can lead to layouts which rely on infeasible supports, undermining confidence in the generated layouts. We present a detailed simulational approach which uses high-resolution tree maps and digital terrain models to compute realistic representations of all possible cable corridors in a given terrain. We applied established methods in forestry to compute feasible cable corridors in a designated area, including rope deflection, determining sufficient tree anchors and placing intermediate supports where necessary. The proposed individual cable corridor trajectories form the foundation for an optimised overall layout that enables a reduction of installation and operation costs and promotes sustainable timber extraction practices on steep terrain. As a next step we aim to mathematically optimise the layout of feasible cable corridors based on multiple criteria (cost, ergonomic aspects, ecological aspects), and integrate the results into an user-friendly workflow. [ABSTRACT FROM AUTHOR]

Tau seed amplification assays (SAAs) directly measure the seeding activity of tau and would therefore be ideal biomarkers for clinical trials targeting seeding-competent tau in Alzheimer's disease (AD). However, the precise relationship between tau seeding measured by SAA and the levels of pathological forms of tau in the AD brain remains unknown. We developed a new tau SAA based on full-length 0N3R tau with sensitivity in the low fg/ml range and used it to characterize 103 brain samples from three independent cohorts. Tau seeding clearly discriminated between AD and control brain samples. Interestingly, seeding was absent in Progressive Supranuclear Palsy (PSP) putamen, suggesting that our tau SAA did not amplify 4R tau aggregates from PSP brain. The specificity of our tau SAA for AD brain was further supported by analysis of matched hippocampus and cerebellum samples. While seeding was detected in hippocampus from Braak stages I-II, no seeding was present in AD cerebellum that is devoid of tau inclusions. Analysis of 40 middle frontal gyrus samples encompassing all Braak stages showed that tau SAA seeding activity gradually increased with Braak stage. This relationship between seeding activity and the presence of tau inclusions in AD brain was further supported by robust correlations between tau SAA results and the levels of phosphorylated tau212/214, phosphorylated tau181, aggregated tau, and sarkosyl-insoluble tau. Strikingly, we detected tau seeding in the middle frontal gyrus already at Braak stage II-III, suggesting that tau SAA can detect tau pathology earlier than conventional immunohistochemical staining. In conclusion, our data suggest a quantitative relationship between tau seeding activity and pathological forms of tau in the human brain and provides an important basis for further development of tau SAA for accessible human samples. [ABSTRACT FROM AUTHOR]

Pollution by heavy metal ions has a serious impact on human health and the environment, which is why the monitoring of heavy metal ions is of great practical importance. In this work, we describe the development of an electrochemical sensor for the detection of cadmium (Cd2+) involving the doping of porous SiO2 spheres with ZnO nanoparticles. Zinc oxide is chosen as the central dopant in the composite material to increase the conductivity and thus improve the electrochemical detection of Cd2+ ions with the SiO2 spheres. The resulting composite is characterized by electrochemical spectroscopic XRD and microscopic methods. As a result, the developed sensor shows good selectivity towards the targeted Cd2+ ions compared to other divalent ions. After optimization of the experimental conditions, the electrochemical sensor shows two different linear ranges between 2.5 × 10−11 molL−1 to 1.75 × 10−10 molL−1 and 2 × 10−9 molL−1 to 1.75 × 10−9 molL−1, indicating a change from diffusion-controlled to surface-controlled oxidation of Cd2+. A detection limit was reached at 4.4 × 10−11 molL−1. In addition, it offers good repeatability and recovery, and can detect accurate trace amounts of Cd2+ ions in real samples such as tap water or seawater by spiking these samples with known Cd2+ concentrations. This setup also provides satisfactory recovery rates in the range of 89–102%. [ABSTRACT FROM AUTHOR]

The emergence of the COVID-19 pandemic, followed by policy measures to combat the virus, evoked public protest movements world-wide. These movements were formed not only in the virtual world but also through local protest gatherings. In contrast to previous research that studied movements in the virtual world through digital network analysis, this study recognizes the importance of the spatial dimension of social movements through local interaction. We therefore introduce a large-scale spatial–social network analysis of a georeferenced Twitter user network to understand the regional connections and transnational influences of the local movement through the virtual network. Our findings indicate that the virtual social network is distinctly structured along geographic and linguistic boundaries. Furthermore, our analysis of transnational influences reveals that the connections within Austria itself hold greater significance compared to their impact on external regions. [ABSTRACT FROM AUTHOR]

Background: Emergency departments (ED) worldwide have to cope with rising patient numbers. Low-acuity consulters who could receive a more suitable treatment in primary care (PC) increase caseloads, and lack of PC attachment has been discussed as a determinant. This qualitative study explores factors that contribute to non-utilization of general practitioner (GP) care among patients with no current attachment to a GP. Method: Qualitative semi-structured telephone interviews were conducted with 32 low-acuity ED consulters with no self-reported attachment to a GP. Participants were recruited from three EDs in the city center of Berlin, Germany. Data were analyzed by qualitative content analysis. Results: Interviewed patients reported heterogeneous factors contributing to their PC utilization behavior and underlying views and experiences. Participants most prominently voiced a rare need for medical services, a distinct mobility behavior, and a lack of knowledge about the role of a GP and health care options. Views about and experiences with GP care that contribute to non-utilization were predominantly related to little confidence in GP care, preference for directly consulting medical specialists, and negative experiences with GP care in the past. Contrasting their reported utilization behavior, many interviewees still recognized the advantages of GP care continuity. Conclusion: Understanding reasons of low-acuity ED patients for GP non-utilization can play an important role in the design and implementation of patient-centered care interventions for PC integration. Increasing GP utilization, continuity of care and health literacy might have positive effects on patient decision-making in acute situations and in turn decrease ED burden. Trial registration: German Clinical Trials Register: DRKS00023480; date: 2020/11/27. [ABSTRACT FROM AUTHOR]

Forestry work, which is considered one of the most demanding and dangerous professions in the world, is claiming more and more lives. In a country as small as Austria, more than 50 forestry workers are killed in accidents every year, and the number is increasing rapidly. This serves as a catalyst for us to implement more stringent measures for workplace safety in order to achieve the sustainability objective of SDG 3, which focuses on health and well-being. This study contributes to the analysis of occupational accidents and focuses on two large real-world datasets from both the Austrian Federal Forests (ÖBf) and the Austrian Workers' Compensation Board (AUVA). Decision trees, random forests, and fully connected neural networks are used for the analysis. By exploring different interpretation methods, this study sheds light on the decision-making processes ranging from basic association to causal inference and emphasizes the importance of causal inference in providing actionable insights for accident prevention. This paper contributes to the topic of explainable AI, specifically in its application to occupational safety in forestry. As a result, it introduces novel aspects to decision support systems in this application domain. [ABSTRACT FROM AUTHOR]

The Sámi people stand out as the only Indigenous minority in an egalitarian European context, namely the Nordic Countries. Therefore, inequalities that they may face are worth closer inspection. Drawing on the distinction between inequalities among individuals (vertical) and between groups (horizontal), we investigate how different types of inequalities affect the Sámi today. We formulate a series of hypotheses on how social, economic, cultural, and political inequalities are linked with discrimination experience, and test these with original data from a population survey conducted in northern Norway and northern Sweden simultaneously in 2021. The findings show that Sámi ethnic background increases the probability of experiencing discrimination. While individual-level economic inequality is also pertinent, this does not directly materialise as between-group inequality. Instead, minority language use is a strong predictor of discrimination experience, revealing the socio-cultural nature of ethnic inequalities. Cross-country differences are only reflected in the effect of minority language use. [ABSTRACT FROM AUTHOR]

Marker-assisted selection (MAS) plays a crucial role in crop breeding improving the speed and precision of conventional breeding programmes by quickly and reliably identifying and selecting plants with desired traits. However, the efficacy of MAS depends on several prerequisites, with precise phenotyping being a key aspect of any plant breeding programme. Recent advancements in highthroughput remote phenotyping, facilitated by unmanned aerial vehicles coupled to machine learning, offer a non-destructive and efficient alternative to traditional, time-consuming, and labour-intensive methods. Furthermore, MAS relies on knowledge of marker-trait associations, commonly obtained through genome-wide association studies (GWAS), to understand complex traits such as drought tolerance, including yield components and phenology. However, GWAS has limitations that artificial intelligence (AI) has been shown to partially overcome. Additionally, AI and its explainable variants, which ensure transparency and interpretability, are increasingly being used as recognised problem-solving tools throughout the breeding process. Given these rapid technological advancements, this review provides an overview of state-of-theart methods and processes underlying each MAS, from phenotyping, genotyping and association analyses to the integration of explainable AI along the entire workflow. In this context, we specifically address the challenges and importance of breeding winter wheat for greater drought tolerance with stable yields, as regional droughts during critical developmental stages pose a threat to winter wheat production. Finally, we explore the transition from scientific progress to practical implementation and discuss ways to bridge the gap between cuttingedge developments and breeders, expediting MAS-based winter wheat breeding for drought tolerance. [ABSTRACT FROM AUTHOR]

Venus is Earth's closest neighbor, hosting a similar size, density, and location in the Solar System. Due to these similarities, Venus has been suggested as a premier location for particular mission sets to include: near-Venus communications and positioning, navigation, and timing (PNT); planetary science; heliophysics; space weather monitoring; and planetary defense. This paper, for the first time in literature, presents 37 unique planar periodic orbits discovered in the Sun–Venus system that may be used for such missions. The Circular Restricted Three-Body Problem (CR3BP) is the primary dynamical model utilized to generate all periodic orbits in the Sun–Venus system. The discovered orbits are grouped into four categories based on their shape: Near-Venus periodic orbits, Sun–Venus touring periodic orbits, Sun–Venus touring periodic orbits featuring near-Sun flybys, and Sun–Venus touring periodic orbits featuring near-Mercury flybys. Each orbit is discussed in terms of its respective Jacobi constant and stability within the context of the CR3BP. The stability of the orbits provides a preliminary analysis of station-keeping costs related to propellant expenditure, thereby determining the feasibility of implementing these trajectories. Specifically, this research shows that most of the identified orbits possess stability indices below 2, suggesting that minimal propellant is necessary for station-keeping maneuvers to sustain the preferred trajectory. For all orbits, specific initial position and velocity states conditions are provided, accompanied by recommendations for their potential mission applications. This research aims to advance ongoing astrodynamics research by filling a catalog hole and providing a Sun–Venus CR3BP orbit baseline. [ABSTRACT FROM AUTHOR]

Sexual reproduction of Zygnematophyceae by conjugation is a less investigated topic due to the difficulties of the induction of this process and zygospore ripening under laboratory conditions. For this study, we collected field sampled zygospores of Spirogyra mirabilis and three additional Spirogyra strains in Austria and Greece. Serial block-face scanning electron microscopy was performed on high pressure frozen and freeze substituted zygospores and 3D reconstructions were generated, allowing a comprehensive insight into the process of zygospore maturation, involving storage compound and organelle rearrangements. Chloroplasts are drastically changed, while young stages contain both parental chloroplasts, the male chloroplasts are aborted and reorganised as 'secondary vacuoles' which initially contain plastoglobules and remnants of thylakoid membranes. The originally large pyrenoids and the volume of starch granules is significantly reduced during maturation (young: 8 ± 5 µm³, mature: 0.2 ± 0.2 µm³). In contrast, lipid droplets (LDs) increase significantly in number upon zygospore maturation, while simultaneously getting smaller (young: 21 ± 18 µm³, mature: 0.1 ± 0.2 and 0.5 ± 0.9 µm³). Only in S. mirabilis the LD volume increases (34 ± 29 µm³), occupying ~50% of the zygospore volume. Mature zygospores contain barite crystals as confirmed by Raman spectroscopy with a size of 0.02 - 0.05 µm³. The initially thin zygospore cell wall (~0.5 µm endospore, ~0.8 µm exospore) increases in thickness and develops a distinct, electron dense mesospore, which has a reticulate appearance (~1.4 µm) in Spirogyra sp. from Greece. The exo- and endospore show cellulose microfibrils in a helicoidal pattern. In the denser endospore, pitch angles of the microfibril layers were calculated: ~18 ± 3° in S. mirabilis, ~20 ± 3° in Spirogyra sp. from Austria and ~38 ± 8° in Spirogyra sp. from Greece. Overall this study gives new insights into Spirogyra sp. zygospore development, crucial for survival during dry periods and dispersal of this genus. [ABSTRACT FROM AUTHOR]

Copyright of HNO is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Numerical association rule mining (NARM) is a popular method under the umbrella of data mining, focused on finding relationships between attributes in transaction databases. Numerical association rules for time series are a new paradigm that extends the applicability of NARM to the domain of time series. Association rule mining algorithms result in numerous rules, the interpretation of which is sometimes not easy for human experts. Therefore, various visualization methods have been developed to improve the explanation results of the rule mining process. This article is a novel contribution to the development of a new visualization method capable of presenting the association rules for time series developed according to the principles of explainable artificial intelligence. The experiments are conducted in the context of smart agriculture (i.e., agricultural time series data), and show the great potential of the proposed visualization method for the future. [ABSTRACT FROM AUTHOR]

This Call to Action is the eighth and final article in this special issue on Family-Centered Early Intervention (FCEI) for children who are deaf or hard of hearing (DHH) and their families, or FCEI-DHH. Collectively, these articles highlight evidence-informed actions to enhance family well-being and to optimize developmental outcomes among children who are DHH. This Call to Action outlines actionable steps to advance FCEI-DHH supports provided to children who are DHH and their families. It also urges specific actions to strengthen FCEI-DHH programs/services and systems across the globe, whether newly emerging or long-established. Internationally, supports for children who are DHH are often siloed, provided within various independent sectors such as health/medicine, education, early childhood, and social and disability services. With this Call to Action, we urge invested parties from across relevant sectors to join together to implement and improve FCEI-DHH programs/services and systems, build the capacity of early intervention (EI) Providers and other professionals, extend research regarding FCEI-DHH, and fund EI supports, systems, and research, all with the aim of advancing outcomes for families and their children who are DHH. [ABSTRACT FROM AUTHOR]

This article is the sixth in a series of eight articles that comprise a special issue on Family-Centered Early Intervention (FCEI) for children who are deaf or hard of hearing (DHH) and their families, or FCEI-DHH. The Support Principles article is the second of three articles that describe the 10 Principles of FCEI-DHH, preceded by the Foundation Principles , and followed by the Structure Principles , all in this special issue. The Support Principles are composed of four Principles (Principles 3 , 4 , 5 , and 6) that highlight (a) the importance of a variety of supports for families raising children who are DHH; (b) the need to attend to and ensure the well-being of all children who are DHH; (c) the necessity of building the language and communication abilities of children who are DHH and their family members; and (d) the importance of considering the family's strengths, needs, and values in decision-making. [ABSTRACT FROM AUTHOR]

This article is the seventh in a series of eight articles that comprise a special issue on family-centered early intervention for children who are deaf or hard of hearing and their families, or FCEI-DHH. This article, Structure Principles , is the third of three articles (preceded by Foundation Principles and Support Principles) that describe the 10 FCEI-DHH Principles. The Structure Principles include 4 Principles (Principle 7 , Principle 8 , Principle 9 , and Principle 10) that highlight (a) the importance of trained and effective Early Intervention (EI) Providers, (b) the need for FCEI-DHH teams to work collaboratively to support families, (c) the considerations for tracking children's progress through developmental assessment, and (d) the essential role of progress monitoring to continuously improve systems. [ABSTRACT FROM AUTHOR]

This article is the second of eight articles in this special issue on Family-Centered Early Intervention (FCEI) for children who are deaf or hard of hearing (DHH) and their families, or FCEI-DHH. Five foundational values that guide FCEI-DHH are described, providing an evidence-informed, conceptual context for the 10 FCEI-DHH Principles and other articles presented in this issue. These values are applicable for Early Intervention (EI) Providers and other professionals on FCEI teams, as well as for FCEI-DHH programs/services and systems. The five key values include (1) being family-centered, (2) responding to diversity, (3) involving invested parties, especially families and individuals who are DHH, (4) supporting holistic child development, and (5) ensuring fundamental human rights. These evidence-informed values are considered essential to the effective provision of FCEI-DHH supports. [ABSTRACT FROM AUTHOR]

This article is the fifth in a series of eight articles that comprise a special issue on Family-Centered Early Intervention (FCEI) for children who are deaf or hard of hearing (DHH) and their families, or FCEI-DHH. The 10 FCEI-DHH Principles are organized conceptually into three sections (a) Foundation Principles , (b) Support Principles , and (c) Structure Principles. Collectively, they describe the essential Principles that guide FCEI for children who are DHH and their families. This article describes the Foundation Principles (Principles 1 and Principle 2). The Foundation Principles emphasize the essential elements of ensuring that families with children who are DHH can access early intervention (EI) and other appropriate supports, as well as highlight the need for provision of EI that is family-centered. Implementation of these FCEI-DHH Principles is intended to improve the lives and the outcomes of children who are DHH and their families around the globe. [ABSTRACT FROM AUTHOR]

This article is the third in a series of eight articles that comprise this special issue on family-centered early intervention for children who are deaf or hard of hearing and their families (FCEI-DHH). It highlights the origins of FCEI-DHH in Western contexts and well-resourced locations and emphasizes the role of culture(s) in shaping FCEI-DHH. This article also cautions against the direct application of the 10 FCEI-DHH Principles presented in this issue across the globe without consideration of cultural implications. Cultural perceptions of decision-making processes and persons who can be decision-makers in FCEI-DHH are explored. Deaf culture(s) and the benefits of exposure to DHH adults with diverse backgrounds are introduced. Structural inequities that impact families' access to FCEI-DHH programs/services and systems, within and among nations and regions, are noted. The need to consider the cultural influences on families is emphasized; this applies to all levels of FCEI, including the development of systems through implementation of supports. [ABSTRACT FROM AUTHOR]

This article is the first of eight articles in this special issue on Family-Centered Early Intervention (FCEI) for children who are deaf or hard of hearing (DHH), or FCEI-DHH. In 2013, a diverse panel of experts published an international consensus statement on evidence-based Principles guiding FCEI-DHH. Those original Principles have been revised through a coproduction process involving multidisciplinary collaborators and an international consensus panel, utilizing the best available evidence and current understanding of how to optimally support children who are DHH and their families. This revision (referred to as expanded Principles) was motivated by the need to incorporate (a) input from family leaders and DHH leaders, (b) broader international and cultural perspectives, (c) new empirical evidence, and (d) research in human development. This Introduction provides an overview of the rationale, purposes, and main content areas to be addressed throughout the special issue. [ABSTRACT FROM AUTHOR]

This is the fourth article in a series of eight that comprise a special issue on family-centered early intervention (FCEI) for children who are deaf or hard of hearing (DHH) and their families, FCEI-DHH. This article describes the co-production team and the consensus review method used to direct the creation of the 10 Principles described in this special issue. Co-production is increasingly being used to produce evidence that is useful, usable, and used. A draft set of 10 Principles for FCEI-DHH and associated Tables of recommended behaviors were developed using the knowledge creation process. Principles were refined through two rounds of eDelphi review. Results for each round were analyzed using measures of overall group agreement and measures that indicated the extent to which the group members agreed with each other. After Round 2, with strong agreement and low to moderate variation in extent of agreement, consensus was obtained for the 10 Principles for FCEI-DHH presented in this special issue. This work can be used to enhance evolution of FCEI-DHH program/services and systems world-wide and adds to knowledge in improvement science. [ABSTRACT FROM AUTHOR]

The methodologies for orbit maintenance continue to develop as the number of cislunar space missions grows. Many of the studies on stationkeeping within cislunar space assume a fixed number of evenly spaced correction maneuvers or plan maneuvers based on the control methodology and mission constraints. From these studies, the maneuver location and coast duration have been identified as essential design parameters that affect the cost of fuel consumption and aid in understanding when and where maneuvers should be placed. The Cauchy–Green tensor allows the analysis of combinations of these design parameters in the form of stability maps. This manuscript derives a modified Cauchy–Green tensor for one and two impulsive stationkeeping maneuvers. The stability maps obtained from the modified Cauchy–Green tensors are used to determine combinations of maneuver location and coast duration that minimize fuel consumption and the final position and velocity errors. In addition, a guidance policy, dependent on uncertainties and an initial state perturbation, is derived from the two-impulse stationkeeping analysis to determine whether performing a corrective maneuver is more beneficial to the overall system’s performance. The solutions obtained from this analysis yield a tool for mission design that is dependent mainly on the problem dynamics, navigation, and thrust uncertainties. [ABSTRACT FROM AUTHOR]

Photon counters and exposure-based cameras cannot simultaneously provide exquisite temporal and spatial resolution in one sensor. Event (i.e. neuromorphic) cameras provide both. Their potential space domain awareness (SDA) applications include short-arc orbit determination and high frequency light curve analysis. Until now, no dynamic event camera simulations for non-resolved objects have been conducted. In this work, we develop numerical and analytical event camera models to better understand potential applicability to SDA efforts. We approximate the event pixel dynamics as a first order differential equation driven by logarithmic photon flux. Photon arrivals are modeled as a stochastic Poisson process. We consider static point sources with constant and time-varying brightness as well as moving sources. We then compare simulated and real event data, showing clear consistencies. For moving sources, we find that the event structure is sensitive to near-instantaneous rates. This sensitivity could provide significant astrometric advancements. We also explore event camera simulations for sinusoidal mean brightness variations, illustrating the complex dependence of frequency estimates on brightness amplitude, oscillation frequency, and event circuit parameters. The presented models improve our fundamental understanding of event data for non-resolved objects. Also, the analytical moving point source model facilitates event-based observability studies and matched filter template generation for object detection, tracking, and characterization. The sensitivity to target parameters observed for the simulated and real event data demonstrates the great potential of event cameras for high spatio-temporal resolution astrometry and photometry. [ABSTRACT FROM AUTHOR]

Smart forestry, an innovative approach leveraging artificial intelligence (AI), aims to enhance forest management while minimizing the environmental impact. The efficacy of AI in this domain is contingent upon the availability of extensive, high-quality data, underscoring the pivotal role of sensor-based data acquisition in the digital transformation of forestry. However, the complexity and challenging conditions of forest environments often impede data collection efforts. Achieving the full potential of smart forestry necessitates a comprehensive integration of sensor technologies throughout the process chain, ensuring the production of standardized, high-quality data essential for AI applications. This paper highlights the symbiotic relationship between human expertise and the digital transformation in forestry, particularly under challenging conditions. We emphasize the human-in-the-loop approach, which allows experts to directly influence data generation, enhancing adaptability and effectiveness in diverse scenarios. A critical aspect of this integration is the deployment of autonomous robotic systems in forests, functioning both as data collectors and processing hubs. These systems are instrumental in facilitating sensor integration and generating substantial volumes of quality data. We present our universal sensor platform, detailing our experiences and the critical importance of the initial phase in digital transformation—the generation of comprehensive, high-quality data. The selection of appropriate sensors is a key factor in this process, and our findings underscore its significance in advancing smart forestry. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) and especially reinforcement learning (RL) have the potential to enable agents to learn and perform tasks autonomously with superhuman performance. However, we consider RL as fundamentally a Human-in-the-Loop (HITL) paradigm, even when an agent eventually performs its task autonomously. In cases where the reward function is challenging or impossible to define, HITL approaches are considered particularly advantageous. The application of Reinforcement Learning from Human Feedback (RLHF) in systems such as ChatGPT demonstrates the effectiveness of optimizing for user experience and integrating their feedback into the training loop. In HITL RL, human input is integrated during the agent’s learning process, allowing iterative updates and fine-tuning based on human feedback, thus enhancing the agent’s performance. Since the human is an essential part of this process, we argue that human-centric approaches are the key to successful RL, a fact that has not been adequately considered in the existing literature. This paper aims to inform readers about current explainability methods in HITL RL. It also shows how the application of explainable AI (xAI) and specific improvements to existing explainability approaches can enable a better human-agent interaction in HITL RL for all types of users, whether for lay people, domain experts, or machine learning specialists. Accounting for the workflow in HITL RL and based on software and machine learning methodologies, this article identifies four phases for human involvement for creating HITL RL systems: (1) Agent Development, (2) Agent Learning, (3) Agent Evaluation, and (4) Agent Deployment. We highlight human involvement, explanation requirements, new challenges, and goals for each phase. We furthermore identify low-risk, high-return opportunities for explainability research in HITL RL and present long-term research goals to advance the field. Finally, we propose a vision of human-robot collaboration that allows both parties to reach their full potential and cooperate effectively. [ABSTRACT FROM AUTHOR]

Studies on parenting stress (PS) in parents of children with hearing loss (HL) have found relationships between child behavior, language skills and parenting stress. The role of early social communication skills has not been researched before. The aim of this cross-sectional study was to investigate the relationship between child behavior, social communication and PS. The study was performed in a subgroup of a total population sample from the AChild (Austrian Children with Hearing Impairment–Longitudinal Databank) study. Preschool children (n = 81) with all degrees of HL and average cognitive functioning and their families were included, and the Parenting Stress Index (PSI) was used. Through factor component analysis, compound scores for externalizing/internalizing problem behavior and hyperactivity were analyzed. Although mean PS was not elevated, the proportion of those with elevated scores was higher compared with the norm population. There was a strong correlation between child behavior problems and PS (strongest correlation: externalizing problem behavior r = 0.643; p < 0.001). All three problem behaviors accounted for 49.7% of the variance in PS. An indirect effect of social communication on PS was almost completely mediated by problem behavior (especially hyperactivity). The importance of social communication development with respect to problem behavior and PS is highlighted. [ABSTRACT FROM AUTHOR]

Purpose: This contribution explores the underuse of artificial intelligence (AI) in the health sector, what this means for practice, and how much the underuse can cost. Attention is drawn to the relevance of an issue that the European Parliament has outlined as a "major threat" in 2020. At its heart is the risk that research and development on trusted AI systems for medicine and digital health will pile up in lab centers without generating further practical relevance. Our analysis highlights why researchers, practitioners and especially policymakers, should pay attention to this phenomenon. Methods: The paper examines the ways in which governments and public agencies are addressing the underuse of AI. As governments and international organizations often acknowledge the limitations of their own initiatives, the contribution explores the causes of the current issues and suggests ways to improve initiatives for digital health. Results: Recommendations address the development of standards, models of regulatory governance, assessment of the opportunity costs of underuse of technology, and the urgency of the problem. Conclusions: The exponential pace of AI advances and innovations makes the risks of underuse of AI increasingly threatening. [ABSTRACT FROM AUTHOR]

The relationship between the state and traditional governance institutions (TGI) in contemporary politics has recently received increased scholarly attention. Traditional leaders play important roles in elections, public goods provision or conflict resolution in Sub-Saharan Africa. We analyse under what conditions cooperation or conflict emerge between the state and TGI. We contribute to the understanding of state-traditional relations by studying how governments interact simultaneously with varying TGI of different ethnic groups. We compare state-TGI relations for eight traditional polities in Kenya, Namibia, Tanzania, and Uganda, based on extensive fieldwork and interviews with state and traditional authorities, experts and constituents. We study three factors shaping state relations with different TGI: (1) the significance of TGI – both social and organisational – in each country and ethnic group; (2) the institutional similarity of TGI and state; and (3) the integration of TGI – both legal and political. Our analysis shows TGI with social significance and functional organisations challenge the state more frequently. Constitutional ambiguity fosters conflict between TGI and state. For our cases, relations are less conflictive in countries with more democratic governments. The same governments and TGI often simultaneously engage in cooperative and conflictive relations, highlighting that governments rarely pursue uniform policies with all TGI. [ABSTRACT FROM AUTHOR]