Abstract Schizophrenia frequently follows a chronic relapsing-remitting course, comprising alternating episodes with and without psychotic symptoms (hereafter: psychosis and psychotic remission). One potential neurobiological correlate of this course is aberrant dopamine synthesis and storage (DSS) in the striatum, which can be estimated by 18 F-DOPA positron emission tomography (PET). We hypothesised that striatal DSS in patients with schizophrenia decreases from psychosis to psychotic remission, with lower striatal DSS in patients during psychotic remission compared to healthy subjects. Additionally, we explored whether striatal DSS is associated with psychotic relapse after remission. 18 F-DOPA PET scans and clinical assessments were conducted in 28 patients with schizophrenia at two timepoints, first during psychosis and second during early psychotic remission 6 weeks to 12 months after the first timepoint, as well as in 21 healthy controls, assessed twice in a comparable time interval. The averaged influx constant k i cer as proxy for DSS was calculated for striatal subregions (i.e., nucleus accumbens, caudate, and putamen) using voxel-wise Patlak modelling with a cerebellar reference region. Mixed-effects models and post hoc analyses were used to test for longitudinal changes in k i cer and cross-sectional group differences. An exploratory clinical follow-up 12 months after the second scan was conducted to assess psychotic relapse, and post hoc ANCOVAs were used to test for differences in k i cer at each session between relapsing and non-relapsing patients. K i cer in both caudate and nucleus accumbens significantly changed from psychosis to psychotic remission compared to healthy controls, with a significant longitudinal decrease of caudate k i cer in patients. Furthermore, k i cer in both caudate and accumbens was significantly lower in patients during early psychotic remission compared to controls. At the exploratory clinical follow-up, 32% of patients had experienced a psychotic relapse; they showed higher caudate k i cer compared to non-relapsing patients during psychosis, with no difference during psychotic remission. These findings provide evidence for the link between striatal, particularly caudate, DSS and the relapsing-remitting course of psychotic symptoms in schizophrenia, with lower caudate DSS during early psychotic remission. Data suggest altered striatal dopamine synthesis together with impaired DSS dynamics along the course of psychotic symptoms in schizophrenia.

BACKGROUND: While the last decade of extensive research revealed the prominent role of the claustrum for functions such as attention), it is poorly understood whether the claustrum is relevant for schizophrenia and related cognitive symptoms. We hypothesized that claustrum volumes are lower in schizophrenia and also that potentially lower volumes mediate patients' attention deficits. METHODS: Based on T1-weighted magnetic resonance imaging, advanced automated claustrum segmentation, and attention symbol coding task in 90 patients with schizophrenia and 96 healthy control participants from 2 independent sites, the COBRE open-source database and Munich dataset, we compared total intracranial volume-normalized claustrum volumes and symbol coding task scores across groups via analysis of covariance and related variables via correlation and mediation analysis. RESULTS: Patients had lower claustrum volumes of about 13% (p < .001, Hedges' g = 0.63), which not only correlated with (r = 0.24, p = .014) but also mediated lower symbol coding task scores (indirect effect ab = -1.30 6 0.69; 95% CI, -3.73 to -1.04). Results were not confounded by age, sex, global and claustrum-adjacent gray matter changes, scanner site, smoking, and medication. CONCLUSIONS: Results demonstrate lower claustrum volumes that mediate patients' attention deficits in schizophrenia. Data indicate the claustrum as being relevant for schizophrenia pathophysiology and cognitive functioning.

The current view of neurodevelopment after preterm birth presents a strong paradox: diverse neurocognitive outcomes suggest heterogeneous neurodevelopment, yet numerous brain imaging studies focusing on average dysmaturation imply largely uniform aberrations across individuals. Here we show both, spatially heterogeneous individual brain abnormality patterns but with consistent underlying biological mechanisms of injury and plasticity. Using cross-sectional structural magnetic resonance imaging data from preterm neonates and longitudinal data from preterm children and adults in a normative reference framework, we demonstrate that brain development after preterm birth is highly heterogeneous in both severity and patterns of deviations. Individual brain abnormality patterns are also consistent for their extent and location along the life course, associated with glial cell underpinnings, and plastic for influences of the early social environment. Our findings extend conventional views of preterm neurodevelopment, revealing a nuanced landscape of individual variation, with consistent commonalities between subjects. This integrated perspective implies more targeted theranostic intervention strategies, specifically integrating brain charts and imaging at birth, as well as social interventions during early development.

The industrial sector is a significant energy consumer amidst the ongoing energy transition to renewable energy resources. With the rising penetration of volatile renewable sources, the need for managed electricity consumption, i.e., demand-side management intensifies. However, the participation of incentivized programs is mostly limited to single consumers with a vast electricity consumption. Recent regulatory changes have allowed independent aggregators to participate in the reserve and ancillary market, enabling smaller end-users to contribute. With the numerous demand-side management contribution possibilities, including energy efficiency and demand-response measures, the objective of the study is to systematically categorize demand-side management applications across different industrial sectors and stages. Furthermore, the study aims to analyze interconnections between these objectives, which are predominantly addressed in isolation within the existing research literature. Highlighting the potential in industrial electricity consumption optimization contributes to the United Nations’ sustainable development goals 7, 9, and 13. To structure the application possibilities within the less-energy intensive industry, a systematic mapping study was conducted covering developments from 2012. An initial search was conducted on several literature databases, and structured selection and data extraction were applied. Cited and referenced studies were screened until no more relevant publications were found. Studies show a wide range of application possibilities and were structured and compiled into an application map. Trends show the increasing inclusion of storage devices in recent publications. Application of energy-flexible and energy-efficient objectives shows synergetic effects. A notable lack of studies focusing on ancillary markets within the less energy-intensive industries was discovered.

Value stream mapping is a well-established tool for analyzing and optimizing value streams in production. In its conventional form, it requires a high level of manual effort and is often inefficient in volatile and high-variance environments. The idea of digitizing value stream mapping to increase efficiency has thus been put forward. A common means suggested for digitization is Process Mining, a field related to Data Science and Process Management. Furthermore, adding sustainability aspects to value stream mapping has also been subject to research. Regarding the ongoing climate crisis and companies' endeavors to improve overall sustainability, integrating sustainability into value stream mapping must be deemed equally relevant. This research paper provides an overview of the state of the art of Process Mining-based and sustainability-integrated value stream mapping, proposes a framework for a combined approach, and presents technical details for the implementation of such an approach, including a validation from practice.

An increasing number of renewable energy sources driven by ambitious sustainability efforts is both changing and challenging electricity systems worldwide. Successfully dealing with a variable and highly decentralized electricity supply associated with the rising share of renewable energy sources will be crucial in the near future. This paper investigates the potential of information technology (IT) for regional marketing of energy flexibility from the machine level in factories to the electricity-grid level. In this context, energy flexibility describes the capability to react quickly and cost-efficiently to alternating electricity availability. Based on a literature review of regional marketing mechanisms, existing concepts of IT platforms, and current real-world model regions, this paper aims to apply a holistic research approach to better understand the challenges regarding the energy transition on a regional level and corresponding requirements for IT platforms used for flexibility marketing. The approach allows to identify relevant key challenges and flexibility marketing use cases, attributing core importance to underlying production processes. In particular, target processes for respective use cases are derived based on a description of current regional marketing of demand flexibility. Successful implementation of target processes is required to provide regional energy flexibility via IT platforms. A comparison between current processes and target processes finally allows defining the need for change and development, e.g., of new intelligent interfaces, already during the conceptual test of new IT platforms. The introduced research approach was applied to one exemplary use case within the energy-flexible model region Augsburg of the Kopernikus project SynErgie, Germany. The paper especially illustrates that service-oriented IT platforms simplify the communication process between the relevant players in energy flexibility marketing. Der steigende Anteil erneuerbarer Energien, die durch ehrgeizige Nachhaltigkeitsbem & uuml;hungen vorangetrieben wird, ver & auml;ndert die Elektrizit & auml;tssysteme weltweit und stellt sie gleichzeitig vor neue Herausforderungen. In diesem Artikel wird das Potenzial der Informationstechnologie (IT) f & uuml;r die regionale Vermarktung von Energieflexibilit & auml;t von der Maschinenebene in Fabriken bis hin zur Stromnetzebene untersucht. Energieflexibilit & auml;t beschreibt in diesem Zusammenhang die F & auml;higkeit von Fabriken, schnell und kosteneffizient auf ein fluktuierendes Stromangebot zu reagieren. Basierend auf einer Literaturrecherche zu regionalen Vermarktungsmechanismen, bestehenden Konzepten von IT-Plattformen und realen Modellregionen zielt dieser Beitrag darauf ab, einen ganzheitlichen Forschungsansatz anzuwenden, um die Herausforderungen der Energiewende auf regionaler Ebene und entsprechende Anforderungen an IT-Plattformen zur Flexibilit & auml;tsvermarktung zu durchdringen. Der Ansatz erlaubt es, relevante Schl & uuml;sselherausforderungen und Anwendungsf & auml;lle der Flexibilit & auml;tsvermarktung zu identifizieren, wobei den zugrundeliegenden Produktionsprozessen eine zentrale Bedeutung beigemessen wird. Insbesondere werden Zielprozesse f & uuml;r die jeweiligen Anwendungsf & auml;lle auf der Grundlage einer Beschreibung der regionalen Vermarktung von Nachfrageflexibilit & auml;t abgeleitet. Die erfolgreiche Umsetzung der definierten Soll-Prozesse ist Voraussetzung f & uuml;r die Bereitstellung regionaler Energieflexibilit & auml;t & uuml;ber IT-Plattformen. Der Vergleich zwischen Ist- und Soll-Prozessen erm & ouml;glicht es schlie ss lich, bereits bei der konzeptionellen Erprobung neuer IT-Plattformen den & Auml;nderungs- und Entwicklungsbedarf, z. B. von intelligenten Schnittstellen, zu definieren. Der vorgestellte Forschungsansatz wurde auf einen exemplarischen Anwendungsfall innerhalb der Energieflexiblen Modellregion Augsburg des Kopernikus-Projekts SynErgie angewandt. Der Beitrag verdeutlicht, dass dienstleistungsorientierte IT-Plattformen den Kommunikationsprozess zwischen den relevanten Akteuren im Energieflexibilit & auml;tsmarketing vereinfachen.

Lasting thalamus volume reduction after preterm birth is a prominent finding. However, whether thalamic nuclei volumes are affected differentially by preterm birth and whether nuclei aberrations are relevant for cognitive functioning remains unknown.Using T1-weighted MR-images of 83 adults born very preterm (≤ 32 weeks’ gestation; VP) and/or with very low body weight (≤ 1,500 g; VLBW) as well as of 92 full-term born (≥ 37 weeks’ gestation) controls, we compared thalamic nuclei volumes of six subregions (anterior, lateral, ventral, intralaminar, medial, and pulvinar) across groups at the age of 26 years. To characterize the functional relevance of volume aberrations, cognitive performance was assessed by full-scale intelligence quotient using the Wechsler Adult Intelligence Scale and linked to volume reductions using multiple linear regression analyses.Thalamic volumes were significantly lower across all examined nuclei in VP/VLBW adults compared to controls, suggesting an overall rather than focal impairment. Lower nuclei volumes were linked to higher intensity of neonatal treatment, indicating vulnerability to stress exposure after birth. Furthermore, we found that single results for lateral, medial, and pulvinar nuclei volumes were associated with full-scale intelligence quotient in preterm adults, albeit not surviving correction for multiple hypotheses testing.These findings provide evidence that lower thalamic volume in preterm adults is observable across all subregions rather than focused on single nuclei. Data suggest the same mechanisms of aberrant thalamus development across all nuclei after premature birth.

As sustainability in manufacturing becomes increasingly important, numerous concepts, new technologies, and use cases for improving and assessing sustainability in manufacturing environments are emerging. However, there is a lack of a framework that shows an easy way to identify relevant topics for action in the field of sustainable manufacturing. The purpose of this publication is to provide a structure for the topic of sustainable manufacturing, to contribute to the understanding and classification of ongoing activities, and to identify starting points for future research and development. Within this publication, an extensive literature review is presented. A framework for sustainable manufacturing that acts as a call for action for academia and operations management in the industry alike is derived from this literature review. The framework is intended for Western countries, as, within this framework, aspects such as the elimination of enslaved persons and child labor in production are assumed to be implemented through legal regulations already. Details of the framework are elaborated, and its application is discussed. This publication contributes to a common, clear understanding of sustainability and the different aspects of sustainability in manufacturing.

BACKGROUND AND HYPOTHESIS:Abnormal thalamic nuclei volumes and their link to cognitive impairments have been observed in schizophrenia. However, whether and how this finding extends to the schizophrenia spectrum is unknown. We hypothesized a distinct pattern of aberrant thalamic nuclei volume across the spectrum and examined its potential associations with cognitive symptoms.STUDY DESIGN:We performed a FreeSurfer-based volumetry of T1-weighted brain MRIs from 137 healthy controls, 66 at-risk mental state (ARMS) subjects, 89 first-episode psychosis (FEP) individuals, and 126 patients with schizophrenia to estimate thalamic nuclei volumes of six nuclei groups (anterior, lateral, ventral, intralaminar, medial, and pulvinar). We used linear regression models, controlling for sex, age, and estimated total intracranial volume, both to compare thalamic nuclei volumes across groups and to investigate their associations with positive, negative, and cognitive symptoms.STUDY RESULTS:We observed significant volume alterations in medial and lateral thalamic nuclei. Medial nuclei displayed consistently reduced volumes across the spectrum compared to controls, while lower lateral nuclei volumes were only observed in schizophrenia. Whereas positive and negative symptoms were not associated with reduced nuclei volumes across all groups, higher cognitive scores were linked to lower volumes of medial nuclei in ARMS. In FEP, cognition was not linked to nuclei volumes. In schizophrenia, lower cognitive performance was associated with lower medial volumes.CONCLUSIONS:Results demonstrate distinct thalamic nuclei volume reductions across the schizophrenia spectrum, with lower medial nuclei volumes linked to cognitive deficits in ARMS and schizophrenia. Data suggest a distinctive trajectory of thalamic nuclei abnormalities along the course of schizophrenia.

Background and Hypothesis The cholinergic system is altered in schizophrenia. Particularly, patients' volumes of basal-forebrain cholinergic nuclei (BFCN) are lower and correlated with attentional deficits. It is unclear, however, if and how BFCN changes and their link to cognitive symptoms extend across the schizophrenia spectrum, including individuals with at-risk mental state for psychosis (ARMS) or during first psychotic episode (FEP). Study Design To address this question, we assessed voxel-based morphometry (VBM) of structural magnetic resonance imaging data of anterior and posterior BFCN subclusters as well as symptom ratings, including cognitive, positive, and negative symptoms, in a large multi-site dataset (n = 4) comprising 68 ARMS subjects, 98 FEP patients (27 unmedicated and 71 medicated), 140 patients with established schizophrenia (SCZ; medicated), and 169 healthy controls. Results In SCZ, we found lower VBM measures for the anterior BFCN, which were associated with the anticholinergic burden of medication and correlated with patients' cognitive deficits. In contrast, we found larger VBM measures for the posterior BFCN in FEP, which were driven by unmedicated patients and correlated at-trend with cognitive deficits. We found no BFCN changes in ARMS. Altered VBM measures were not correlated with positive or negative symptoms. Conclusions Results demonstrate complex (posterior vs. anterior BFCN) and non-linear (larger vs. lower VBM) differences in BFCN across the schizophrenia spectrum, which are specifically associated both with medication, including its anticholinergic burden, and cognitive symptoms. Data suggest an altered trajectory of BFCN integrity in schizophrenia, influenced by medication and relevant for cognitive symptoms.

Background:Cocaine use disorder (CUD) is a global health issue with severe behavioral and cognitive sequelae. While previous evidence suggests a variety of structural and age-related brain changes in CUD, the impact on both, cortical thickness and brain age measures remains unclear. Methods:Derived from a publicly available data set (SUDMEX_CONN), 74 CUD patients and 62 matched healthy controls underwent brain MRI and behavioral-clinical assessment. We determined cortical thickness by surface-based morphometry using CAT12 and Brain Age Gap Estimate (BrainAGE) via relevance vector regression. Associations between structural brain changes and behavioral-clinical variables of patients with CUD were investigated by correlation analyses. Results:We found significantly lower cortical thickness in bilateral prefrontal cortices, posterior cingulate cortices, and the temporoparietal junction and significantly increased BrainAGE in patients with CUD [mean (SD) = 1.97 (±3.53)] compared to healthy controls (p < 0.001, Cohen's d = 0.58). Increased BrainAGE was associated with longer cocaine abuse duration. Conclusion:Results demonstrate structural brain abnormalities in CUD, particularly lower cortical thickness in association cortices and dose-dependent, increased brain age.

The modern manufacturingManufacturing industry often relies on complex global supply chainsSupply Chain requiring extensive productionProduction procedures and flexible and robust supply chainSupply Chain management. The more flexible the supply chainSupply Chain, the easier it responds to disruptions. FlexibilityFlexibility, however, comes with a toll, such as environmental impacts and flexibilityFlexibility inherent costs. This study presents a simulationSimulation model based on a robust designDesign frameworkFramework to analyze and overcome these challenges. The model uses a multi-method simulationSimulation approach called ‘processes inside agents’ hybridly combining Discrete Event SimulationDiscrete event simulation and Agent-Based Modeling to investigate an optimum point of flexibilityFlexibility regarding the energy consumed. An enhanced flexibilityFlexibility formula developed reveals the impact of the used flexibilityFlexibility in the supply chainSupply Chain network. The study illustrates that limited flexibility can achieve better results than higher flexibilityFlexibility for lowering the energy consumption per product. The results also demonstrate that no single optimum point of flexibilityFlexibility can generate optimal results for the whole supply chainSupply Chain network. However, there is a local and case-specific optimum point of flexibilityFlexibility for each degree of forecast accuracy.

The ongoing energy transition to renewable energies heavily impacts even non-energy-intensive manufacturing companies (NEIMCs). This progress comes with fluctuations in electricity availability; and ultimately rising costs. Facing the transformation by applying demand-side energy flexibility measures, so far, has considered rather energy-intensive companies while leaving NEIMCs out of focus. Despite their number and economic importance in the European terrain, their demand-side potential is usually underestimated while it may be central to an overall successful adaptation. In this work, energy transition challenges posed to NEIMCs are funneled from several surveys with eight companies in the southern German manufacturing sector. They were evaluated to extract individual requirements for implementing energy-oriented manufacturing; from a NEIMC’s perspective. Experiences from the process industry were adapted custom-oriented to guideline potentially specific solutions for NEIMCs related to the energy transition using IT solutions. More broadly, this approach reflects opportunities and challenges in the NEIMC environment and outlines promising avenues to exploit energy flexibility.

For decades, aberrant dopamine transmission has been proposed to play a central role in schizophrenia pathophysiology. These theories are supported by human in vivo molecular imaging studies of dopamine transmission, particularly positron emission tomography. However, there are several downsides to such approaches, for example limited spatial resolution or restriction of the measurement to synaptic processes of dopaminergic neurons. To overcome these limitations and to measure complementary aspects of dopamine transmission, magnetic resonance imaging (MRI)-based approaches investigating the macrostructure, metabolism, and connectivity of dopaminergic nuclei, i.e., substantia nigra pars compacta and ventral tegmental area, can be employed. In this scoping review, we focus on four dopamine MRI methods that have been employed in patients with schizophrenia so far: neuromelanin MRI, which is thought to measure long-term dopamine function in dopaminergic nuclei; morphometric MRI, which is assumed to measure the volume of dopaminergic nuclei; diffusion MRI, which is assumed to measure fiber-based structural connectivity of dopaminergic nuclei; and resting-state blood-oxygenation-level-dependent functional MRI, which is thought to measure functional connectivity of dopaminergic nuclei based on correlated blood oxygenation fluctuations. For each method, we describe the underlying signal, outcome measures, and downsides. We present the current state of research in schizophrenia and compare it to other disorders with either similar (psychotic) symptoms, i.e., bipolar disorder and major depressive disorder, or dopaminergic abnormalities, i.e., substance use disorder and Parkinson's disease. Finally, we discuss overarching issues and outline future research questions.

With rising energy prices, it becomes increasingly important for industrial companies to consider energy costs in the activity of production planning and control. Reduced energy costs can both be realised through lower consumption and higher energy efficiency. Furthermore, the ability to flexibly consume energy, while adapting consumption to electricity availability or variable energy prices, as often referred to as ‘demand response’, might bring significant benefits. Two important requirements for demand response are the ability to predict consumption and the ability to precisely determine the potential flexible approaches available. For this purpose, a material flow model was implemented that simulates both the production process and the energy consumed by it. This model was parameterised based on real production data and energy consumption. Initial analysis reveals that manufacturing processes generally undergo interruptions, which cannot be predicted at the stage of production planning. These interruptions significantly reduce the accuracy of the model and were considered by means of probability density functions.

The expansion of renewable energies and the concomitant compensatory measures, such as the expansion of the electricity grid, the installation of energy storage facilities, or the flexibilization of demand, lead to a more elaborated energy supply system. Furthermore, the technological development of small power plants has further progressed, and many novel technologies have achieved grid parity. For manufacturing companies, the integration of renewable generation plants at their own site therefore represents a promising strategy for being both technically independent of the electricity grid and autonomous of price policy decisions and volatile market prices. This paper outlines the existing decentralized, renewable power generation technologies, their energetic modeling, and a hybrid optimization methodology for their dimensioning that uses mixed integer linear programming (MILP) and linear programming (LP) problem formulation. Finally, the introduced dimensioning method is applied to an exemplary manufacturing company that is assumed to be in the central part of Germany and located in the metalworking sector. The company has an electricity demand of approximately 20,000 MWh/a. The optimization results in a maximum expansion of PV and the use of CHP to cover the base load leading to a promising energy cost reduction of almost 20%.