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Bolstering low-income students' postsecondary participation is important to remediate these students' disadvantages and to improve society's overall level of education. Recent research has demonstrated that secondary schools vary considerably in their tendencies to send students to postsecondary education, but existing research has not systematically identified the school characteristics that explain this variation. Identifying these characteristics can help improve low-income students' postsecondary outcomes. We identify relevant characteristics using population-level data from Wisconsin, a mid-size state in the United States. We first show that Wisconsin's income-based disparities in postsecondary participation are wide, even net of academic achievement. Next, we show that several geographic characteristics of schools help explain between-secondary school variation in low-income students' postsecondary outcomes. Finally, we test whether a dense set of school organisational features explain any remaining variation. We find that these features explain virtually no variation in secondary schools' tendencies to send low-income students to postsecondary education. [For the corresponding grantee submission, see ED623645.]

Racialized tracking is central to sociological explanations for racially stratified educational outcomes. However, school officials' decision-making is of debated importance for explaining racialized tracking. We contribute to this literature by examining the effects of schools' enrollment policies for Advanced Placement (AP) courses. Using a unique combination of school survey data and administrative data from Wisconsin, we examine what happens to racial inequality in AP participation when school officials enforce performance-based selection criteria, which we call "course gatekeeping." We find that course gatekeeping has racially disproportionate effects. Although racialized differences in prior achievement partially explain the especially large negative effects among students of color, course gatekeeping produces Black-white and Hispanic-white disparities in participation even among students with similar, relatively low prior achievement. We further find that course gatekeeping has longer-run effects, particularly discouraging Black and Asian or Pacific Islander students from attending highly selective four-year colleges.

In 2015, Wisconsin began mandating the ACT college entrance exam and the WorkKeys career readiness assessment. With population-level data and several quasi-experimental designs, we assess how this policy affected college attendance. We estimate a positive policy effect for middle/high-income students, no effect for low-income students, and greater effects at high schools that had lower ACT participation before the policy. We further find little evidence that being deemed college-ready by one's ACT scores or career-ready by one's WorkKeys scores affects college attendance probabilities. Pragmatically, the findings highlight the policy's excellence and equity consequences, which are complex given that the policy has principally helped advantaged students. Theoretically, the findings shed light on students' (dis)inclinations to update educational beliefs in light of new signals. [For the corresponding grantee submission, see ED624339.]

Abstract Glial Fibrillary Acidic Protein (GFAP) and Ubiquitin C-terminal hydrolase (UCH-L1) have been FDA-approved for clinical use in mild and moderate traumatic brain injury (TBI). Understanding sex differences in their diagnostic accuracy over time will help inform clinical practice. We sought to evaluate the sex differences in the temporal profile of GFAP and UCH-L1 in a large cohort of trauma patients presenting to the emergency department. To compare the biomarkers’ diagnostic accuracy in male versus female patients for detecting mild TBI (MTBI), and traumatic intracranial lesions on head CT. This prospective cohort study enrolled female and male adult trauma patients presenting to a Level 1 Trauma Center. All patients underwent rigorous screening to determine whether or not they had experienced a MTBI. Of 3025 trauma patients assessed, 1030 met eligibility criteria and 446 declined. Initial blood samples were obtained in 584 patients enrolled within 4 h of injury. Repeated blood sampling was conducted at 4, 8, 12, 16, 24, 36, 48, 60, 72, 84, 96, 108, 120, 132, 144, 156, 168, and 180-h post-injury. The main outcomes included the diagnostic accuracy in detection of MTBI and traumatic intracranial lesions on head CT scan. A total of 1831 samples were drawn in 584 patients over 7 days, 362 (62%) were male and 222 (38%) were female. The pattern of elevation was similar in both sexes. Although the pattern of elevation was similar between male and female for both biomarkers, male patients had significantly higher concentrations of UCH-L1 compared to female patients at several timepoints post-injury, particularly within 24 h of injury. There were no significant differences in diagnostic accuracy for detecting MTBI or for detecting CT lesions between male and female patients at any timepoint for both GFAP and UCH-L1. Although patterns of GFAP and UCH-L1 release in trauma patients over a week post-injury was similar between the sexes, there were significantly higher concentrations of UCH-L1 in males at several timepoints post-injury. Despite this, the overall diagnostic accuracies of both GFAP and UCH-L1 over time for detecting MTBI and CT lesions were not significantly different between male and female trauma patients.

Small wind turbines offer a complement to photovoltaic systems and are becoming an interesting solution in the wake of rising energy prices. The measurement results indicate that some locations on and around the building are not suited for installing wind turbines, while others show increased wind potential. Due to limited space, rooftop mounting is an interesting alternative to free mounting on a mast from a technical point of view. For this reason, the influence of roof shapes on the flow on and behind the building was measured and the performance of two different types of small wind turbines was investigated. The turbines assessed in the project are VertikonM with a vertical axis and helix-shaped rotor blades, and Superwind 1250 wind turbine with a horizontal axis and centrifugal force pitch control. The results showed that there is an average increase in wind speed of 0.2 m/s on gable roofs at hub height (7 m). In comparison, there is an increase of 0.4 m/s on flat roofs at hub height (7 m). In relation to the performance of the turbines, high turbulence on the roof seems to cancel out this effect. The performance of the horizontal axis small wind turbine has not increased in comparison with gable roof and free-standing mast. For the vertical-axis turbine, a power increase by a factor of 2.23 was achieved between free-standing mast and gable roof. Vertical wind flow above the gable roof was identified as the main cause for power increase. The experiment was conducted on the Lichtenegg energy research park (Lower Austria) and its results make it possible to better identify all effects that affect the turbine output power

Coal has been one of the main fuels used in Europe. Its decreasing role due to the ongoing transformation of the energy system will create significant socio-economic challenges. The switch into renewable energy systems could be an alternative to maintain jobs and economic activities within the affected regions. Biomass use and bioenergy can play an important role in the energy transition. Instead of energy crops, forest and agricultural residues should be used as biogenic energy sources in the future to avoid impacts on land use and food security. The main objective of this article is to investigate the biomass potential of a coal region and to provide scenarios for the future development of bioenergy production. Due to the changing framework conditions and, as a result, the different biomass focuses, previous bioenergy potential estimates must be reviewed. The methods for determining the potential of biomass for energy production was used for Lusatia (in German: Lausitz), the second largest coal region in Germany. These methods can also be applied in other regions. As a first step, the regional status quo assessment of cultivated areas and yields had decisive relevance for calculating biomass potential ranges. In a second step, the current bioenergy facilities in the region were identified, with a focus on power and heat production. The third step was the estimation of future regional bioenergy use. Therefore, the regional potential was gathered with the generally supra-regional framework conditions. For this purpose, national scenario studies were used, which contain the relevant target values and framework conditions. Two scenarios were developed for future bioenergy estimations: a conservative path based on the current policies and a progressive path, derived from the goal of climate neutrality by 2045. The results show a qualitative comparison among both scenarios and the previously determined potential ranges. Bioenergy can probably contribute to achieving climate neutrality with an increase in wood-fired systems, while agricultural bioenergy potential is likely to decline. In the discussion section, however, the uncertainty of these results is pointed out, as future use of bioenergy will be heavily influenced by the regulatory framework, competition with material use and the influences of climate change.

Abstract Background Pathogen identification in clinical routine is based on the cultivation of microbes with subsequent morphological and physiological characterisation lasting at least 24 hours. However, early and accurate identification is a crucial requisite for fast and optimally targeted antimicrobial treatment. Molecular biology based techniques allow fast identification, however discrimination of very closely related species remains still difficult. Results A molecular approach is presented for the rapid identification of pathogens combining PCR amplification with microarray detection. The DNA chip comprises oligonucleotide capture probes for 25 different pathogens including Gram positive cocci, the most frequently encountered genera of Enterobacteriaceae, non-fermenter and clinical relevant Candida species. The observed detection limits varied from 10 cells (e.g. E. coli) to 105 cells (S. aureus) per mL artificially spiked blood. Thus the current low sensitivity for some species still represents a barrier for clinical application. Successful discrimination of closely related species was achieved by a signal pattern recognition approach based on the k-nearest-neighbour method. A prototype software providing this statistical evaluation was developed, allowing correct identification in 100 % of the cases at the genus and in 96.7 % at the species level (n = 241). Conclusion The newly developed molecular assay can be carried out within 6 hours in a research laboratory from pathogen isolation to species identification. From our results we conclude that DNA microarrays can be a useful tool for rapid identification of closely related pathogens particularly when the protocols are adapted to the special clinical scenarios.

Preoperative implantation of an intra-aortic balloon pump has been shown to reduce mortality in high-risk cardiac surgery cases. However, one main contraindication for its use is severe aortic regurgitation. We describe a case of safe and beneficial use in a patient presenting with moderate to severe aortic regurgitation and highly reduced ejection fraction undergoing aortic valve replacement.

The final goal of all industrial machine learning (ML) projects is to develop ML products and rapidly bring them into production. However, it is highly challenging to automate and operationalize ML products and thus many ML endeavors fail to deliver on their expectations. The paradigm of Machine Learning Operations (MLOps) addresses this issue. MLOps includes several aspects, such as best practices, sets of concepts, and development culture. However, MLOps is still a vague term and its consequences for researchers and professionals are ambiguous. To address this gap, we conduct mixed-method research, including a literature review, a tool review, and expert interviews. As a result of these investigations, we contribute to the body of knowledge by providing an aggregated overview of the necessary principles, components, and roles, as well as the associated architecture and workflows. Furthermore, we provide a comprehensive definition of MLOps and highlight open challenges in the field. Finally, this work provides guidance for ML researchers and practitioners who want to automate and operate their ML products with a designated set of technologies.

Bolstering low-income students’ postsecondary participation is important to remediate these students’ disadvantages and to improve society’s overall level of education. Recent research has demonstrated that secondary schools vary considerably in their tendencies to send students to postsecondary education, but existing research has not systematically identified the school characteristics that explain this variation. Identifying these characteristics can help improve low-income students’ postsecondary outcomes. We identify relevant characteristics using population-level data from Wisconsin, a mid-size state in the United States. We first show that Wisconsin’s income-based disparities in postsecondary participation are wide, even net of academic achievement. Next, we show that several geographic characteristics of schools help explain between-secondary school variation in low-income students’ postsecondary outcomes. Finally, we test whether a dense set of school organisational features explain any remaining variation. We find that these features explain virtually no variation in secondary schools’ tendencies to send low-income students to postsecondary education.

The topic of biochar carbon removal (BCR), which refers to the pyrolysis of biomass, is increasingly being discussed as a potential solution for the long-term removal of carbon dioxide from the atmosphere. However, BCR technology assessments in Germany, which are used as the basis for strategic decision-making, are often limited to woody biomass as an input material and are based on old data. Consequently, this study focuses on BCR from forest residues, straw and sewage sludge and assesses its contribution to negative emissions under current techno-economic framework conditions. Using life cycle assessment and annuity method, as well as complementary stakeholder engagement formats, the study provides a comprehensive analysis of BCR pathways in Germany based on an empirical, up-to-date data basis. The results highlight the environmental advantages of BCR, particularly in reducing greenhouse gas emissions compared to the conventional treatment of residues. The economic feasibility of BCR is uncertain, with profitability dependent on plant scale, biomass type and the integration of energy co-products. Stakeholder insights underscore the necessity for supportive policies and investment in BCR technology to enhance scalability. This interdisciplinary approach enriches the discourse on BCR’s role in achieving carbon neutrality and offers a robust data foundation for future evaluations.