bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reusable unit process life cycle inventory for manufacturing: high speed laser directed energy deposition
Authors: Ehmsen Svenja , Yi Li , Glatt Moritz , Linke Barbara S. , Aurich Jan C. 
Published: April 2023

AbstractThe unit process life cycle inventory is a modeling approach to estimate the energy demand and resource requirements of a unit process. Thus, a model of the unit process life cycle inventory for a specific manufacturing process can be used for quantifying the environmental impacts of specific products manufactured by that process. Within the approach, reusable models are developed for specific manufacturing processes. In this paper, the development and validation of a unit process life cycle inventory model for high-speed laser directed energy deposition is presented. This additive manufacturing process offers great potential for the industry due to its fast process speed. However, high-speed laser directed energy deposition has a high energy consumption and resource demand. Assessing the energy demand for individual manufactured products is a time-intensive process that requires expert knowledge. Thus, the development of an adaptable unit process life cycle inventory model enables more convenient assessment and improvement of its energy and resource efficiencies for producing different products. For the development of the model, the subsystems of a high-speed laser directed energy deposition machine are analyzed separately, e. g. the laser generator, the trajectory system, the powder feeder, and the suction system. Afterward, the energy and material demand of these subsystems are described in mathematical models. Finally, the model is validated by comparing the energy demands of three demonstration parts, measured by experiments, and predicted by the model.
Experimentelle georeferenzierte Bevölkerungszahl auf Basis der Bevölkerungsfortschreibung und Mobilfunkdaten
Authors: Hadam Sandra 
Published: April 2023

ZusammenfassungKleinräumige und aktuelle Bevölkerungszahlen sind für politische Entscheidungsfindungen unerlässlich. Die Bevölkerungsfortschreibung ermöglicht die Angabe aktueller Einwohnerzahlen auf geografischer Ebene der Gemeinden. Die Einwohnerzahl wird hierbei auf Basis des Zensus 2011 anhand von Angaben der Statistiken zu Geburten und Sterbefällen sowie der Wanderungsstatistik laufend fortgeschrieben. Um den wachsenden Bedarf an kleinräumigeren Bevölkerungszahlen kurzfristig zu decken, wird die Bevölkerungsfortschreibung mit einem neuen experimentellen Lösungsansatz ergänzt.Im Projekt Experimentelle georeferenzierte Bevölkerungszahl auf Basis der Bevölkerungsfortschreibung und Mobilfunkdaten werden im Rahmen eines Verteilungsverfahrens die Ergebnisse der Bevölkerungsfortschreibung von der Gemeindeebene anhand von Mobilfunkdaten bundesweit auf INSPIRE-konforme 1 × 1 km Gitterzellen umverteilt und mittels einer interaktiven Karte frei nutzbar zur Verfügung gestellt. Mobilfunkdaten bieten aufgrund ihres starken Zusammenhangs mit der Bevölkerungsverteilung sowie ihrer hohen zeitlichen und räumlichen Auflösung eine geeignete Datengrundlage für die kleinräumige Verteilung der amtlichen Einwohnerzahl. Auf Basis zusätzlicher Geodaten der deutschen Landesvermessung, wie bspw. dem Landbedeckungsmodell für Deutschland, werden die resultierenden experimentellen georeferenzierten Bevölkerungszahlen auf Plausibilität geprüft und Verbesserungen in der Mobilfunkdatenaufbereitung hergeleitet und umgesetzt. Im Ergebnis resultieren bundesweit experimentelle georeferenzierte Bevölkerungszahlen, die in urbanen, dicht besiedelten Regionen plausibel erscheinen, jedoch im ländlichen, weniger dicht besiedelten Raum zu systematischen Fehlschätzungen neigen.
Job flourishing research: A systematic literature review
Authors: A’yuninnisa Rizqi N. , Carminati Lara , Wilderom Celeste P.M. 
Published: April 2023

AbstractResearch on job flourishing is still in its infancy, relies on a plethora of different theories, and shows inconsistent results, but has already shown numerous beneficial effects on various organizational outcomes. In this state-of-the-art review, we identify the theoretical frameworks used to examine (the dynamics of) job flourishing, including its predictors and outcomes, and offer an integrated approach that is, thus far, missing. We selected and analyzed 40 empirical studies and derived from them a comprehensive multilevel conceptual model with matching propositions. This review extends our current knowledge of organizational psychology literature by suggesting how to combine the evidence obtained so far on how job flourishing arises and unfolds in organizational work contexts and its effects (e.g., on job performance, turnover intention, etc.). Rooted therein, we provide both directions for impactful future research and recommendations for managers on how to foster this desirable mental-health state at work.
The role of 18F-FDG PET/CT in primary cutaneous lymphoma: an educational review
Authors: McDonald Elysia O. , Amanullah Amir A. , Park Peter Sang Uk , Song William , Werner Thomas J. , Alavi Abass , Revheim Mona-Elisabeth 
Published: April 2023

Abstract
Introduction
Primary cutaneous lymphoma (PCL) is a cutaneous non-Hodgkin’s lymphoma that originates in the skin and lacks extracutaneous spread upon initial diagnosis. The clinical management of secondary cutaneous lymphomas is different from that of PCLs, and earlier detection is associated with better prognosis. Accurate staging is necessary to determine the extent of disease and to choose the appropriate treatment. The aim of this review is to investigate the current and potential roles of 18F- fluorodeoxyglucose positron emission tomography–computed tomography (18F-FDG PET/CT) in the diagnosis, staging, and monitoring of PCLs.

Methods
A focused review of the scientific literature was performed using inclusion criteria to filter results pertaining to human clinical studies performed between 2015 and 2021 that analyzed cutaneous PCL lesions on 18F PET/CT imaging.

Results & Conclusion
A review of 9 clinical studies published after 2015 concluded that 18F-FDG PET/CT is highly sensitive and specific for aggressive PCLs and proved valuable for identifying extracutaneous disease. These studies found 18F-FDG PET/CT highly useful for guiding lymph node biopsy and that imaging results influenced therapeutic decision in many cases. These studies also predominantly concluded that 18F-FDG PET/CT is more sensitive than computed tomography (CT) alone for detection of subcutaneous PCL lesions. Routine revision of nonattenuation-corrected (NAC) PET images may improve the sensitivity of 18F-FDG PET/CT for detection of indolent cutaneous lesions and may expand the potential uses of 18F-FDG PET/CT in the clinic. Furthermore, calculating a global disease score from 18F-FDG PET/CT at every follow-up visit may simplify assessment of disease progression in the early clinical stages, as well as predict the prognosis of disease in patients with PCL.
Dissecting Psychiatric Heterogeneity and Comorbidity with Core Region-Based Machine Learning
Authors: Lv Qian , Zeljic Kristina , Zhao Shaoling , Zhang Jiangtao , Zhang Jianmin , Wang Zheng 
Published: April 2023

AbstractMachine learning approaches are increasingly being applied to neuroimaging data from patients with psychiatric disorders to extract brain-based features for diagnosis and prognosis. The goal of this review is to discuss recent practices for evaluating machine learning applications to obsessive-compulsive and related disorders and to advance a novel strategy of building machine learning models based on a set of core brain regions for better performance, interpretability, and generalizability. Specifically, we argue that a core set of co-altered brain regions (namely ‘core regions’) comprising areas central to the underlying psychopathology enables the efficient construction of a predictive model to identify distinct symptom dimensions/clusters in individual patients. Hypothesis-driven and data-driven approaches are further introduced showing how core regions are identified from the entire brain. We demonstrate a broadly applicable roadmap for leveraging this core set-based strategy to accelerate the pursuit of neuroimaging-based markers for diagnosis and prognosis in a variety of psychiatric disorders.
Optimization of Chelating Process of Amino Acids of Leather Waste and Glycine with Different Minerals and Its Relationship with Arthrospira platensis Biological Activities
Authors: Jacob Rania H. , Afify Adel S. , Shanab Sanaa M. M. , Shalaby Emad A. , Hafez Rehab M. 
Published: April 2023

AbstractThere are several factors were taken in consideration such as time, ratio, temperature and pH to improve the chelation process between the amino acids and inorganic ions. The current study aims to optimize the physical factors controlling the synthesis of chelated amino acids with different minerals and to enhance antioxidant and biodiesel production from Arthrospira platensis cultivated in culture enriched with different chelated minerals. In this study; various physical factors such as (ratio of amino acids and minerals; temperature, time and pH) were used for optimization of chelation formation. The blue -green alga Arthrospira platensis was cultivated under different synthesized chelated minerals (T1-T13), the growth rate, antioxidant, antiradical and biodiesel production were determined in all treated alga. The obtained results showed that the optimum conditions for production of chelated amino acid were ratio (2:1 M), temperature at 60 °C, the duration between 4:5 days and the suitable or stability of chelation at pH = 4, Also, the growth rate of A. platensis with Cu-glycinate higher than Cu-leather waste and Zarrouk media. The antioxidant activity results of different extracts of Arthrospira platensis showed that the water extract gave high antioxidant activity against DPPH radical assay than acetone extract in all treatments when compared with untreated culture (Zarrouk’s medium). Arthrospira platensis cultivated on Zarrouk medium supplemented with chelated amino acids with metals was showed an increase in algal pigments and lipids with Mn-LW, Zn-LW and Mg-LW treatments. Also, the results showed that the produced biodiesel was observed with M-LW treatments, which was more than that of glycinate treatments, untreated culture (Zarrouk) and LW biodiesel. Therefore, the highest biodiesel percentages were founded with Zn, Mn and Mg-LW (5.37, 5.25 and 4.86% respectively). The recorded results and material balance data concluded that possibility for use the chelated minerals (glycine and leather wastes) as plant fertilizer in future because its high yield and low fees for production.
Graphical Abstract
Uncertainty from the Aharonov–Vaidman identity
Authors: Leifer Matthew S. 
Published: April 2023

AbstractIn this article, I show how the Aharonov–Vaidman identity $$A\left| \psi \right\rangle = \left\langle A \right\rangle \left| \psi \right\rangle + \Delta A \left| \psi ^{\perp }_A \right\rangle $$

A

ψ

=

A

ψ

+
Δ
A

ψ
A
⊥

can be used to prove relations between the standard deviations of observables in quantum mechanics. In particular, I review how it leads to a more direct and less abstract proof of the Robertson uncertainty relation $$\Delta A \Delta B \ge \frac{1}{2} \left| \left\langle [A,B] \right\rangle \right| $$

Δ
A
Δ
B
≥

1
2

[
A
,
B
]

than the textbook proof. I discuss the relationship between these two proofs and show how the Cauchy–Schwarz inequality can be derived from the Aharonov–Vaidman identity. I give Aharonov–Vaidman based proofs of the Maccone–Pati uncertainty relations and show how the Aharonov–Vaidman identity can be used to handle propagation of uncertainty in quantum mechanics. Finally, I show how the Aharonov–Vaidman identity can be extended to mixed states and discuss how to generalize the results to the mixed case.
The labour market perspective on the role identities of vocational teacher educators: a case study in Malta
Authors: Said Alison 
Published: April 2023

AbstractThe overall purpose of this qualitative study is to gain a deeper understanding of how employers, who represent the Maltese labour market, view the role identities of Vocational Teacher Educators (VTEs). Data were collected through semi-structured interviews, adopting thematic analysis. Findings from this research, where it gives a voice to a group that has too often been neglected in policy and research, may help policymakers in small states to be wary of taking on board concepts related to the roles of VTEs originating from much larger countries and from the mainstream education contexts. Implications on how the relationship between the labour market and VTEs are discussed.
Characterising sediment thickness beneath a Greenlandic outlet glacier using distributed acoustic sensing: preliminary observations and progress towards an efficient machine learning approach
Authors: Booth Adam D. , Christoffersen Poul , Pretorius Andrew , Chapman Joseph , Hubbard Bryn , Smith Emma C. , de Ridder Sjoerd , Nowacki Andy , Lipovsky Bradley Paul , Denolle Marine 
Published: April 2023

AbstractDistributed Acoustic Sensing (DAS) is increasingly recognised as a valuable tool for glaciological seismic applications, although analysing the large data volumes generated in acquisitions poses computational challenges. We show the potential of active-source DAS to image and characterise subglacial sediment beneath a fast-flowing Greenlandic outlet glacier, estimating the thickness of sediment layers to be 20–30 m. However, the lack of subglacial velocity constraint limits the accuracy of this estimate. Constraint could be provided by analysing cryoseismic events in a counterpart 3-day record of passive seismicity through, for example, seismic tomography, but locating them within the 9 TB data volume is computationally inefficient. We describe experiments with data compression using the frequency-wavenumber (f-k) transform ahead of training a convolutional neural network, that provides a ~300-fold improvement in efficiency. In combining active and passive-source and our machine learning framework, the potential of large DAS datasets could be unlocked for a range of future applications.
Bridging the gap between pricing and reserving with an occurrence and development model for non-life insurance claims
Authors: Crevecoeur Jonas , Antonio Katrien , Desmedt Stijn , Masquelein Alexandre 
Published: April 2023

AbstractDue to the presence of reporting and settlement delay, claim data sets collected by non-life insurance companies are typically incomplete, facing right censored claim count and claim severity observations. Current practice in non-life insurance pricing tackles these right censored data via a two-step procedure. First, best estimates are computed for the number of claims that occurred in past exposure periods and the ultimate claim severities, using the incomplete, historical claim data. Second, pricing actuaries build predictive models to estimate technical, pure premiums for new contracts by treating these best estimates as actual observed outcomes, hereby neglecting their inherent uncertainty. We propose an alternative approach that brings valuable insights for both non-life pricing and reserving. As such, we effectively bridge these two key actuarial tasks that have traditionally been discussed in silos. Hereto, we develop a granular occurrence and development model for non-life claims that tackles reserving and at the same time resolves the inconsistency in traditional pricing techniques between actual observations and imputed best estimates. We illustrate our proposed model on an insurance as well as a reinsurance portfolio. The advantages of our proposed strategy are most compelling in the reinsurance illustration where large uncertainties in the best estimates originate from long reporting and settlement delays, low claim frequencies and heavy (even extreme) claim sizes.
Shortcuts for the construction of sub-annual life tables
Authors: Pavía Jose M. , Lledó Josep 
Published: April 2023

AbstractFuelled by the big data explosion, a new methodology to estimate sub-annual death probabilities has recently been proposed, opening new insurance business opportunities. This new approach exploits all the detailed information available from millions of microdata records to develop seasonal-ageing indexes (SAIs) from which sub-annual (quarterly) life tables can be derived from annual tables. In this paper, we explore whether a shortcut could be taken in the estimation of SAIs and (life insurance) sub-annual death rates. We propose three different approximations, in which estimates are attained by using just a small bunch of thousands of data records and assess their impact on several competitive markets defined from an actual portfolio of life insurance policies. Our analyses clearly point to the shortcuts as good practical alternatives that can be used in real-life insurance markets. Noticeably, we see that embracing the new quarterly based approach, even using only an approximation (shortcut), is economically preferable to using the associated annual table, offering a significant competitive advantage to the company adopting this innovation.
249 Addressing Structural Racism Using Community Based System Dynamics
Authors: Gullett Heidi , Brown Gregory , Collins Delores , Mathews Michael , Stange Kurt , Hovmand Peter 
Published: April 2023

OBJECTIVES/GOALS: 1. Describe method of Community Based System Dynamics. 2. Describe CBSD as used in addressing structural racism in a previously redlined community. 3. Review example causal loop diagrams and simulation models developed using CBSD focused on structural racism as a social determinant of health. METHODS/STUDY POPULATION: Community Based System Dynamics (group model building and computer simulation development). Cuyahoga County, Ohio, a previously redlined community of more than 1.2 million people. RESULTS/ANTICIPATED RESULTS: Actionable Community identified leverage points for action to mitigate structural racism. Computer simulation models built on causal loop diagrams built by Community members with loved experience. DISCUSSION/SIGNIFICANCE: Structural and social determinants of health, such as racism, have profound impacts on the health of individuals and populations, however they remain challenging to address in pragmatic ways. CBSD is a novel method to engage community members not proximal to the impact of structural racism in generating maps of the complex, dynamic system they live in.Precision Medicine/Health
437 Novel Targeting of Semaphorin 7a-Mediated Survival Signaling in ER+ Breast Cancer to Mitigate Therapy Resistance
Authors: Steinmetz Rachel , Lyons Traci 
Published: April 2023

OBJECTIVES/GOALS: Estrogen receptor-positive (ER+) breast cancers (BC) comprise >70% of all BC and cause the most BC-related deaths in women worldwide. Despite available therapies against ER+ BC, recurrence often arises due to development of endocrine therapy resistance. Thus, our goal is to identify novel biomarkers that could serve as therapeutic targets for ER+ BC. METHODS/STUDY POPULATION: We have identified a neuroimmune molecule, Semaphorin 7a (SEMA7A), as a potential biomarker for endocrine therapy resistance, relapse, and poor survival in ER+ BC patients. SEMA7A promotes tumor growth, angiogenesis, epithelial-to-mesenchymal transition, metastasis, and endocrine therapy resistance in our pre-clinical models. Specifically, using in vivo models we have shown that SEMA7A+ MCF7 tumors result in lung metastases that do not respond to fulvestrant, in part via downregulation of ER, posing the need to identify novel, druggable targets for SEMA7A+ ER+ BC patients. SEMA7A is a membrane-bound protein that can inhibit tumor cell death via integrin-mediated PI3K/Akt pro-survival signaling. Thus, we hypothesized that SEMA7A+ ER+ BC may be sensitive to PI3K inhibition in combination with fulvestrant. RESULTS/ANTICIPATED RESULTS: Our preliminary studies confirmed that high SEMA7A expression associates with increased phospho-Akt levels and decreased apoptosis of tumor cells in forced suspension conditions. We also observed that human MCF7 ER+ SEMA7A overexpressing (OE) cells are sensitive to the PI3K (P110ï ¡ï€©ï€ inhibitor, Alpelisib. Also, the combination of Alpelisib with fulvestrant inhibited tumor cell viability in MCF7 cells, which was further enhanced in the SEMA7A OE counterparts. The combination also decreased proliferation and tumor sphere formation. There are currently no therapies that directly target SEMA7A, and here I propose an innovative hypothesis that PI3K inhibition will block SEMA7A signaling. DISCUSSION/SIGNIFICANCE: The role of SEMA7A has been studied in several cancer types, but its function in ER+ BC remains less well understood. In future studies, we will explore the mechanisms by which SEMA7A signals in the cell and to promote tumor cell survival. Delineating these mechanisms will help optimize treatment combinations to improve BC patient survival.
A physics-based domain adaptation framework for modeling and forecasting building energy systems
Authors: Xuereb Conti Zack , Choudhary Ruchi , Magri Luca 
Published: April 2023

Abstract
State-of-the-art machine-learning-based models are a popular choice for modeling and forecasting energy behavior in buildings because given enough data, they are good at finding spatiotemporal patterns and structures even in scenarios where the complexity prohibits analytical descriptions. However, their architecture typically does not hold physical correspondence to mechanistic structures linked with governing physical phenomena. As a result, their ability to successfully generalize for unobserved timesteps depends on the representativeness of the dynamics underlying the observed system in the data, which is difficult to guarantee in real-world engineering problems such as control and energy management in digital twins. In response, we present a framework that combines lumped-parameter models in the form of linear time-invariant (LTI) state-space models (SSMs) with unsupervised reduced-order modeling in a subspace-based domain adaptation (SDA) approach, which is a type of transfer-learning (TL) technique. Traditionally, SDA is adopted for exploiting labeled data from one domain to predict in a different but related target domain for which labeled data is limited. We introduced a novel SDA approach where instead of labeled data, we leverage the geometric structure of the LTI SSM governed by well-known heat transfer ordinary differential equations to forecast for unobserved timesteps beyond available measurement data by geometrically aligning the physics-derived and data-derived embedded subspaces closer together. In this initial exploration, we evaluate the physics-based SDA framework on a demonstrative heat conduction scenario by varying the thermophysical properties of the source and target systems to demonstrate the transferability of mechanistic models from physics to observed measurement data.
Active screening and patient-placement and cohort-placement strategies to decrease carbapenem-resistant gram-negative bacilli colonization and infection in pediatric patients: A 5-year retrospective observational study in China
Authors: Yin LJ , He LY , Lu GP , Cao Y , Wang LS , Zhai XW , Wang CQ 
Published: April 2023

AbstractCarbapenem-resistant gram-negative bacilli (CR-GNB) colonization screening was initiated across high-risk departments (PICU, NICU, neonatal wards, and hematology departments) in January 2017, and several CR-GNB cohort and patient-placement strategies were introduced throughout the hospital in January 2018. The colonization and infection rates decreased to varying degrees from 2017 to 2021.