bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cognitive Deficits in Parkinson's Disease Are Associated with Neuronal Dysfunction and Not White Matter Lesions
Authors: Schröter Nils , Bormann Tobias , Rijntjes Michel , Blazhenets Ganna , Berti Raissa , Sajonz Bastian E.A. , Urbach Horst , Weiller Cornelius , Meyer Philipp T. , Rau Alexander , Frings Lars 
Published: May 2023

AbstractBackgroundCognitive deficits considerably contribute to the patient's burden in Parkinson's disease (PD). While cognitive decline is linked to neuronal dysfunction, the additional role of white matter lesions (WML) is discussed controversially.ObjectiveTo investigate the influence of WML, in comparison to neuronal dysfunction, on cognitive deficits in PD.MethodsWe prospectively recruited patients with PD who underwent neuropsychological assessment using the Mattis Dementia Rating Scale 2 (DRS‐2) or Parkinson Neuropsychometric Dementia Assessment (PANDA) and both MRI and PET with [18F]fluorodeoxyglucose (FDG). WML‐load and PD cognition‐related covariance pattern (PDCP) as a measure of neuronal dysfunction were read out. Relationship between cognitive performance and rank‐transformed WML was analyzed with linear regression, controlling for the patients’ age. PDCP subject scores were investigated likewise and in a second step adjusting for age and WML load.ResultsInclusion criteria were met by 76 patients with a mean (± SD) age of 63.5 ± 9.0 years and disease duration of 10.7 ± 5.4 years. Neuropsychological testing revealed front executive and parietal deficits and a median DRS‐2 score of 137 (range 119–144)/144 and PANDA score of 22 (range 3–30)/30. No association between WML and cognition was observed, whereas PDCP subject scores showed a trend‐level negative correlation with the DRS‐2 (P = 0.060) as well as a negative correlation with PANDA (P = 0.049) which persisted also after additional correction for WML (P = 0.039).ConclusionThe present study indicates that microangiopathic WML do not have a relevant impact on neurocognitive performance in PD whereas neuronal dysfunction does.
Exploring activity landscapes with extended similarity: is Tanimoto enough?
Authors: Dunn Timothy B. , López‐López Edgar , Kim Taewon David , Medina‐Franco José L. , Miranda‐Quintana Ramón Alain 
Published: May 2023

AbstractUnderstanding structure‐activity landscapes is essential in drug discovery. Similarly, it has been shown that the presence of activity cliffs in compound data sets can have a substantial impact not only on the design progress but also can influence the predictive ability of machine learning models. With the continued expansion of the chemical space and the currently available large and ultra‐large libraries, it is imperative to implement efficient tools to analyze the activity landscape of compound data sets rapidly. The goal of this study is to show the applicability of the n‐ary indices to quantify the structure‐activity landscapes of large compound data sets using different types of structural representation rapidly and efficiently. We also discuss how a recently introduced medoid algorithm provides the foundation to finding optimum correlations between similarity measures and structure‐activity rankings. The applicability of the n‐ary indices and the medoid algorithm is shown by analyzing the activity landscape of 10 compound data sets with pharmaceutical relevance using three fingerprints of different designs, 16 extended similarity indices, and 11 coincidence thresholds.
Technical note: The design and validation of a multi‐modality lung phantom
Authors: Bowen Donald L. , Touchet Tyler J. , Maitland Duncan J. , McDougall Mary P. 
Published: May 2023

AbstractBackgroundClinically relevant models that enable certain tasks such as calibration of medical imaging devices or techniques, device validation, training healthcare professionals, and more are vital to research throughout the medical field and are referred to as phantoms. Phantoms range in complexity from a vile of water to complex designs that emulate in vivo properties.PurposeSpecific phantoms that model the lungs have focused on replication of tissue properties but lack replication of the anatomy. This limits the use across multiple imaging modalities and for device testing when anatomical considerations as well as tissue properties are needed. This work reports a lung phantom design utilizing materials that accurately mimic the ultrasound and magnetic resonance imaging (MRI) properties of in vivo lungs and includes relevant anatomical equivalence.MethodsThe tissue mimicking materials were selected based on published studies of the materials, through qualitative comparisons of the materials with ultrasound imaging, and quantitative MRI relaxation values. A PVC ribcage was used as the structural support. The muscle/fat combined layer and the skin layer were constructed with various types of silicone with graphite powder added as a scattering agent where appropriate. Lung tissue was mimicked with silicone foam. The pleural layer was replicated by the interface between the muscle/fat layer and the lung tissue layer, requiring no additional material.ResultsThe design was validated by accurately mimicking the distinct tissue layers expected with in vivo lung ultrasound while maintaining tissue‐mimicking relaxation values in MRI as compared to reported values. Comparisons between the muscle/fat material and in vivo muscle/fat tissue demonstrated a 1.9% difference in T1 relaxation and a 19.8% difference in T2 relaxation.ConclusionsQualitative US and quantitative MRI analysis verified the proposed lung phantom design for accurate modeling of the human lungs.
Prostate perfusion mapping using Fourier‐transform based velocity‐selective arterial spin labeling: Choice of cutoff velocity and comparison with brain
Authors: Liu Dapeng , Zhu Dan , Xu Feng , Sedaghat Farzad , Qin Qin 
Published: May 2023

PurposeTo develop velocity selective arterial spin labeling (VSASL) protocols for prostate blood flow (PBF) and prostate blood volume (PBV) mapping.MethodsFourier‐transform based velocity‐selective inversion and saturation pulse trains were utilized in VSASL sequences to obtain blood flow and blood volume weighted perfusion signal, respectively. Here four cutoff velocities (Vcut = 0.25, 0.50, 1.00, and 1.50 cm/s) for PBF and PBV mapping sequences were evaluated with a parallel implementation in brain for measuring cerebral blood flow (CBF) and cerebral blood volume (CBV) with identical 3D readout. This study was performed at 3T on eight young and middle‐aged healthy subjects comparing both perfusion weighted signal (PWS) and temporal SNR (tSNR).ResultsIn contrast to CBF and CBV, the PWS of PBF and PBV were rather unobservable at Vcut of 1.00 or 1.50 cm/s and both PWS and tSNR of PBF and PBV considerably increased at the lower Vcut, indicating that blood moves much slower in prostate than in brain. Similar to the brain results, the tSNR of PBV‐weighted signal was about two to four times over the corresponding values of PBF‐weighted signal. The results also suggested a trend of reduced vascularity within prostate during aging.ConclusionFor prostate, a low Vcut of 0.25–0.50 cm/s seemed necessary for both PBF and PBV measurements to obtain adequate perfusion signal. As in brain, PBV mapping yielded a higher tSNR than PBF.
Embedded Trefftz discontinuous Galerkin methods
Authors: Lehrenfeld Christoph , Stocker Paul 
Published: May 2023

AbstractIn Trefftz discontinuous Galerkin methods a partial differential equation is discretized using discontinuous shape functions that are chosen to be elementwise in the kernel of the corresponding differential operator. We propose a new variant, the embedded Trefftz discontinuous Galerkin method, which is the Galerkin projection of an underlying discontinuous Galerkin method onto a subspace of Trefftz‐type. The subspace can be described in a very general way and to obtain it no Trefftz functions have to be calculated explicitly, instead the corresponding embedding operator is constructed. In the simplest cases the method recovers established Trefftz discontinuous Galerkin methods. But the approach allows to conveniently extend to general cases, including inhomogeneous sources and non‐constant coefficient differential operators. We introduce the method, discuss implementational aspects and explore its potential on a set of standard PDE problems. Compared to standard discontinuous Galerkin methods we observe a severe reduction of the globally coupled unknowns in all considered cases, reducing the corresponding computing time significantly. Moreover, for the Helmholtz problem we even observe an improved accuracy similar to Trefftz discontinuous Galerkin methods based on plane waves.
Nursing students' learning commitment, self‐efficacy and grit during the COVID 19 pandemic: Quantitative empirical research on adaptation to college life
Authors: Jin Juhyun , An Hyeran 
Published: May 2023

AbstractAimsTo examine the learning commitment, self‐efficacy, grit and adaptation to college life among Korean nursing students, under the prolonged COVID‐19 situation, and identify the factors that affect their adaptation to college life.DesignA cross‐sectional study.MethodsThe participants were 247 nursing students. The instruments used in the study were the Learning Commitment Scale for Adults, Self‐Efficacy Scale, Grit Scale and Campus Life Adaptation Scale (developed for Korean nursing students). A multiple linear regression analysis was conducted using SPSS 23.0.ResultsAdaptation to college life had significant positive correlations with learning commitment, self‐efficacy and grit. Moreover, self‐efficacy and learning commitment were key correlators for adapting to college life.
Efficacy and safety of modified fasting therapy for weight loss in 2054 hospitalized patients
Authors: Liu Taoli , Ye Ziheng , Feng Jiahao , Zhang Li , Chen Hongda , Chen Xianhua , Cai Fangjie , Zhang Gengpeng , Lai Jicai , Ye Zhiyu , Cao Nan , Mo Binyan , Li Zhiling , Wang Ning , Lin Yuejia , Zhang Tingying , Yang Yu , Hu Jianguo , Yan Ling , Zheng Zilong , Song Wei , Liang Haifang , Qin Jian 
Published: May 2023

AbstractObjectiveThe aim of this study was to evaluate the efficacy and safety of modified fasting therapy, and a retrospective study was conducted to analyze changes in clinical indicators of hospitalized fasting patients.MethodsA total of 2054 hospitalized fasting patients were enrolled in this observational study. All participants underwent 7 days of modified fasting therapy. The clinical efficacy biomarkers, safety indicators, and body composition were measured before and after fasting.ResultsThe modified fasting therapy reduced body weight, BMI, abdominal circumference, systolic blood pressure, and diastolic blood pressure significantly. Blood glucose and indicators of body composition were improved to various extents (all p < 0.05). There was a small increase in liver function, kidney function, uric acid, electrolytes, blood count, coagulation, and uric biomarkers. Subgroup analysis results showed that cardiovascular diseases benefited from modified fasting therapy.ConclusionsAt present this study is the largest retrospective population‐based study about modified fasting therapy. The results from 2054 patients showed that the modified fasting therapy lasting 7 days was efficient and safe. It led to improvements in physical health and body weight‐associated indicators, as well as body composition and relevant cardiovascular risk factors.
Assessment and management of iatrogenic withdrawal syndrome and delirium in pediatric intensive care units across Europe: An ESPNIC survey
Authors: Sperotto Francesca , Ramelet Anne‐Sylvie , Daverio Marco , Mondardini Maria Cristina , von Borell Florian , Brenner Sebastian , Tibboel Dick , Ista Erwin , Pokorna Paula , Amigoni Angela ,   The Analgosedation CONSORTIUM on behalf of the Pharmacology Section and the Nurse Science Section of the European Society for Paediatric and Neonatal Intensive Care
Published: May 2023

AbstractIntroductionAnalgesia and sedation are essential for the care of children in the pediatric intensive care unit (PICU); however, when prolonged, they may be associated with iatrogenic withdrawal syndrome (IWS) and delirium. We sought to evaluate current practices on IWS and delirium assessment and management (including non‐pharmacologic strategies as early mobilization) and to investigate associations between the presence of an analgosedation protocol and IWS and delirium monitoring, analgosedation weaning, and early mobilization.MethodsWe conducted a multicenter cross‐sectional survey‐based study collecting data from one experienced physician or nurse per PICU in Europe from January to April 2021. We then investigated differences among PICUs that did or did not follow an analgosedation protocol.ResultsAmong 357 PICUs, 215 (60%) responded across 27 countries. IWS was systematically monitored with a validated scale in 62% of PICUs, mostly using the Withdrawal Assessment Tool‐1 (53%). The main first‐line treatment for IWS was a rescue bolus with interruption of weaning (41%). Delirium was systematically monitored in 58% of PICUs, mostly with the Cornell Assessment of Pediatric Delirium scale (48%) and the Sophia Observation Scale for Pediatric Delirium (34%). The main reported first‐line treatment for delirium was dexmedetomidine (45%) or antipsychotic drugs (40%). Seventy‐one percent of PICUs reported to follow an analgosedation protocol. Multivariate analyses adjusted for PICU characteristics showed that PICUs using a protocol were significantly more likely to systematically monitor IWS (odds ratio [OR] 1.92, 95% confidence interval [CI] 1.01–3.67) and delirium (OR 2.00, 95% CI 1.07–3.72), use a protocol for analgosedation weaning (OR 6.38, 95% CI 3.20–12.71) and promote mobilization (OR 3.38, 95% CI 1.63–7.03).ConclusionsMonitoring and management of IWS and delirium are highly variable among European PICUs. The use of an analgosedation protocol was associated with an increased likelihood of monitoring IWS and delirium, performing a structured analgosedation weaning and promoting mobilization. Education on this topic and interprofessional collaborations are highly needed to help reduce the burden of analgosedation‐associated adverse outcomes.
The effect of foreign knowledge acquisition on international performance: The mediating roles of international orientation and business model innovation
Authors: Adomako Samuel 
Published: May 2023

AbstractResearch on how business model innovation (BMI) in international markets affects international performance continues to proliferate. However, existing research is sparse on primary predictors of this relationship. Drawing upon knowledge creation theory, this article investigates a serial mediation model that supports the role of the indirect effects of foreign knowledge acquisition (FKA) via international orientation (IO) and BMI on international performance. Utilizing time‐lagged survey data from multiple respondents in Ghana (N = 352), the results revealed that high levels of FKA enhance BMI via increased IO, and BMI ultimately improves international performance. Implications relating to theory and practice are discussed.
Development and performance of a machine learning‐based tool that predicts influent flow to a WRF 72 h in advance and integrates with existing wet weather nutrient management protocols
Authors: Bilyk Katya , Roostaei Javad , Bailey Erika 
Published: May 2023

AbstractInfluent flow to the 75 mgd Neuse River Resource Recovery Facility (NRRRF) was modeled using machine learning. The trained model can predict hourly flow 72 h in advance. This model was deployed in July 2020, and has been in operation over two and a half years. The model's mean absolute error in training was 2.6 mgd, and mean absolute error has ranged from 10 to 13 mgd in deployment for any point during the wet weather event when predicting 12 h in advance. As a result of this tool, plant staff have optimized the use of their 32 MG wet weather equalization basin, using it approximately 10 times and never exceeding its volume.Practitioner Points
A machine learning model was developed to predict influent flow to a WRF 72 h in advance.
Selecting the appropriate model, variables, and properly characterizing the system are important considerations in machine learning modeling.
This model was developed using free open source software/code (Python) and deployed securely using an automated Cloud‐based data pipeline.
This tool has been in operation for over 30 months and continues to make accurate predictions.
Machine learning combined with subject matter expertise can greatly benefit the water industry.
Prediction of biogas production in anaerobic digestion of a full‐scale wastewater treatment plant using ensembled machine learning models
Authors: Sun Jiasi , Xu Yanran , Nairat Shaker , Zhou Jianpeng , He Zhen 
Published: May 2023

AbstractAnaerobic digestion (AD) of sludge is a key approach to recover useful bioenergy from wastewater treatment and its stable operation is important to a wastewater treatment plant (WWTP). Because of various biochemical processes that are not fully understood, AD operation can be affected by many parameters and thus modeling AD processes becomes a useful tool for monitoring and controlling their operation. In this case study, a robust AD model for predicting biogas production was developed using ensembled machine learning (ML) model based on the data from a full‐scale WWTP. Eight ML models were examined for predicting biogas production and three of them were selected as metamodels to create a voting model. This voting model had a coefficient of determination (R2) at 0.778 and a root mean square error (RMSE) of 0.306, outperformed individual ML models. The Shapley additive explanation (SHAP) analysis revealed that returning activated sludge and temperature of wastewater influent were important features, although they affected biogas production in different ways. The results of this study have demonstrated the feasibility of using ML models for predicting biogas production in the absence of high‐quality data input and improving model prediction through assembling a voting model.Practitioner Points
Machine learning is applied to model biogas production from anaerobic digesters at a full‐scale wastewater treatment plant.
A voting model is created from selected individual models and exhibits better performance of predication.
In the absence of high quality data, indirect features are identified to be important to predicting biogas production.
Organizational Conflicts in the Adoption of Continuous Software Engineering
Authors: Klotins Eriks , Talbert-Goldstein Elliot 
Published: May 2023

AbstractSoftware is a critical component of nearly every product or service. Improvements in software can lead to substantial competitive advantages. At the same time, software and surrounding engineering teams have become increasingly complex.The adoption of continuous integration and delivery is a recent trend to radically improve software release speed. However, its adoption is far from straightforward. Specifically, rethinking processes, organizational culture, ways of working, and business models require buy-in from diverse stakeholders that may have conflicting objectives. Such situations are explored by organizational conflict research.This paper reports on early lessons from an ongoing research project in continuous software engineering, specifically investigating adoption challenges from an organizational conflict perspective. We identify catalysts, symptoms, and outcomes of organizational conflicts hindering the adoption process.We conclude that predictable conflicts emerge when adopting continuous engineering. Engineers, managers, and other teams can proactively prepare for and allocate resources to resolve them. Proper analysis and management can help avoid wasted time, impeding processes, and frustration.
Versicherungstechnische Risiken in der Berufsunfähigkeitsversicherung
Authors: Strobel Jürgen 
Published: May 2023

ZusammenfassungErstmals nach mehr als zwei Jahrzehnten hat die Deutsche Aktuarvereinigung wieder die Veröffentlichung neuer Rechnungsgrundlagen für die Berufsunfähigkeitsversicherung angekündigt. Dies gibt Anlass, die Entwicklung der relevanten Wahrscheinlichkeiten in den vergangenen Jahrzehnten zu analysieren und insbesondere herauszuarbeiten, welche Einflussfaktoren die Veränderungen bestimmt haben. Mit Blick in die Zukunft können daraus insbesondere Informationen über das Änderungsrisiko gewonnen werden, dem die Rechnungsgrundlagen in dieser Lebensversicherungs-Teilsparte in besonderer Weise unterworfen sind.
Cyber-Kumulrisiko
Authors: Cremer Frank , Materne Stefan 
Published: May 2023

ZusammenfassungWährend die Frequenz und die finanziellen Auswirkungen von Cyber-Schäden immer größere Dimensionen annehmen, haben Versicherer das volle Ausmaß dieses Risikos noch nicht verstanden. Für die Versicherungsbranche nimmt der Aspekt des Kumulrisikos eine zentrale Rolle ein. Aus diesem Grund werden die Bedeutung und Besonderheiten des Cyber-Kumulrisikos erarbeitet und der Status quo gemäß der Diskussion in der Literatur sowie der Erfahrungen aus der Praxis analysiert. Abschließend werden die Grenzen der Versicherbarkeit von Cyber-Kumulrisiken diskutiert, wie auch Möglichkeiten des versicherungstechnischen Risikotransfers.
Steuerrecht und Versicherungswirtschaft − ein Risiko eigener Art
Authors: Axer Jochen 
Published: May 2023

ZusammenfassungVersicherungswirtschaft und Staat versuchen mit unterschiedlichen Mitteln und Ressourcen, Lebensrisiken abzusichern. Fiskalische Belastungen von Versicherungsunternehmen, Vertrieb und Versicherungsnehmern führen zu einer Einengung der privatwirtschaftlich organisierten Risikovorsorge. Besonderheiten der Versicherungsbranche aufgrund ihres in die Zukunft gerichteten Geschäftsmodells bedürfen einer steuerlichen Begleitung, die sich der gesellschaftlichen Funktion und des Geschäftsmodells der Versicherer bewusst ist.Die jeweilige Sachbehandlung berührt ein gesellschaftliches Grundverständnis − nämlich entweder den Menschen eine vorausschauende Eigenvorsorge abzuverlangen und diese dann aber auch zu ermöglichen (ohne dass der Staat zusätzliche unverträgliche Lasten aufbürdet) − oder aber den Staat als permanenten „Retter in der Not“ anzusehen (der dann aber zuständig für alles und jedweden ist). Die Versicherungswirtschaft wird sich immer darum bemühen müssen, ihr privatwirtschaftliches Modell als überlegen und „gerechter“, aber gleichzeitig als die staatliche Absicherung entlastend zu verdeutlichen; die Schnittstelle zur Steuerbelastung wird hierbei jederzeit eine wichtige Rolle spielen.
Optimierung von Testprozessen und Anforderungsmanagement
Authors: Schnur Bernd 
Published: May 2023

ZusammenfassungDie digitale Transformation bedingt nicht nur Veränderungen in den Produkten und Prozessen der Unternehmen, sondern auch in den dabei unterstützenden Informationstechnologien. In diesem Zusammenhang sollten vorhandene Optimierungspotenziale bei der Entwicklung und Einführung neuer Software ausgeschöpft werden. Hier können entsprechende Standards zu Verbesserungen von Aufgaben und Projekten in den Anforderungsphasen sowie beim Testen von Anwendungssystemen beitragen. Die in diesem Kontext bekanntesten Standards sind ISTQB und IREB (einschließlich ihrer Zertifizierungsschemata), mit denen Optimierungspotenziale in den Testprozessen und den Prozessen des Anforderungsmanagements realisiert werden können.
Zum Schluss: Die Arche Noah aus Sicht der Seekaskoversicherung
Authors: Reimers-Rawcliffe Lutz 
Published: May 2023

ZusammenfassungRisiko und Versicherungsbedarf sind durchaus keine neuen Fragestellungen. Daher wurde an dieser Stelle exemplarisch die Arche Noah als ein erstes Anwendungsbeispiel für die Seekaskoversicherung skizziert.