bluuebunny/crossref_metadata_2025_split huggingface dataset:
Public sector entrepreneurship: an integrative review
Authors: Vivona Roberto , Clausen Tommy H. , Gullmark Petter , Cinar Emre , Demircioglu Mehmet Akif 
Published: September 2024

AbstractPublic sector entrepreneurship (PSE) has emerged as a vital field, exploring how public servants leverage opportunities to create public value amidst unprecedented and unpredictable challenges in governance. This article navigates the expansive landscape of PSE literature, consolidating diverse theoretical perspectives and fragmented knowledge into a cohesive framework. Through an integrative and systematic review of 100 articles, we identify PSE as a multi-level phenomenon characterized by a context-dependent combination of proactivity, innovation, and risk-taking, that serves to drive change and renewal, promote resilient organizations, and resourcefully exploit opportunities for public value creation, with the ultimate aim of achieving positive societal and environmental outcomes. By proposing an analytical framework that embraces the fluid nature of PSE and integrating diverse perspectives, this study enriches our understanding of the intersection between entrepreneurship and public administration. It advocates for a nuanced, sector-specific approach to PSE, laying a solid foundation for further advancements in the field.
Comparative Evaluation of Commercial Filters and Ultrafiltration for Concentrating Cryptosporidium Oocysts and Giardia Cysts from Water Samples
Authors: Al Mshelesh Hayder , Bridle Helen , Vesey Graham 
Published: September 2024

AbstractThis review of literature analyses the effectiveness of three commercially available filters, namely the Pall Envirochek filters, IDEXX FiltaMax, and Whatman flatbed membrane, in the process of concentrating Cryptosporidium oocysts and Giardia cysts from water samples. Moreover, several research studies investigated the possibility of using ultrafiltration filters as an affordable substitute for pathogen concentration, and their efficacy for protozoa is reviewed here and compared against the existing commercial filter options. Because of the differences in sampling procedures, no one method for concentrating these protozoa consistently outperforms others. This comparative article summarises our current understanding of the recent water sampling techniques to concentrate waterborne protozoans and highlights the remaining knowledge gaps. While ultrafiltration is a financially practical alternative for the concentration of pathogens, this paper highlights that further investigation is required to optimise their efficacy, particularly for low numbers of oocysts and cysts. These insights play a substantial role in providing information for advancing enhanced water sampling and treatment systems, reducing the dangers connected with waterborne protozoans, and ensuring the protection of public health.
Accelerating FLAIR imaging via deep learning reconstruction: potential for evaluating white matter hyperintensities
Authors: Nishioka Noriko , Shimizu Yukie , Kaneko Yukio , Shirai Toru , Suzuki Atsuro , Amemiya Tomoki , Ochi Hisaaki , Bito Yoshitaka , Takizawa Masahiro , Ikebe Yohei , Kameda Hiroyuki , Harada Taisuke , Fujima Noriyuki , Kudo Kohsuke 
Published: September 2024

Abstract

Purpose
To evaluate deep learning-reconstructed (DLR)–fluid-attenuated inversion recovery (FLAIR) images generated from undersampled data, compare them with fully sampled and rapidly acquired FLAIR images, and assess their potential for white matter hyperintensity evaluation.

Materials and methods
We examined 30 patients with white matter hyperintensities, obtaining fully sampled FLAIR images (standard FLAIR, std-FLAIR). We created accelerated FLAIR (acc-FLAIR) images using one-third of the fully sampled data and applied deep learning to generate DLR–FLAIR images. Three neuroradiologists assessed the quality (amount of noise and gray/white matter contrast) in all three image types. The reproducibility of hyperintensities was evaluated by comparing a subset of 100 hyperintensities in acc-FLAIR and DLR–FLAIR images with those in the std-FLAIR images. Quantitatively, similarities and errors of the entire image and the focused regions on white matter hyperintensities in acc-FLAIR and DLR–FLAIR images were measured against std-FLAIR images using structural similarity index measure (SSIM), regional SSIM, normalized root mean square error (NRMSE), and regional NRMSE values.

Results
All three neuroradiologists evaluated DLR–FLAIR as having significantly less noise and higher image quality scores compared with std-FLAIR and acc-FLAIR (p < 0.001). All three neuroradiologists assigned significantly higher frontal lobe gray/white matter visibility scores for DLR–FLAIR than for acc-FLAIR (p < 0.001); two neuroradiologists attributed significantly higher scores for DLR–FLAIR than for std-FLAIR (p < 0.05). Regarding white matter hyperintensities, all three neuroradiologists significantly preferred DLR–FLAIR (p < 0.0001). DLR–FLAIR exhibited higher similarity to std-FLAIR in terms of visibility of the hyperintensities, with 97% of the hyperintensities rated as nearly identical or equivalent. Quantitatively, DLR–FLAIR demonstrated significantly higher SSIM and regional SSIM values than acc-FLAIR, with significantly lower NRMSE and regional NRMSE values (p < 0.0001).

Conclusions
DLR–FLAIR can reduce scan time and generate images of similar quality to std-FLAIR in patients with white matter hyperintensities. Therefore, DLR–FLAIR may serve as an effective method in traditional magnetic resonance imaging protocols.
Localizing structural damage based on auto-regressive with exogenous input model parameters and residuals using a support vector machine based learning approach
Authors: Gunes Burcu 
Published: September 2024

AbstractMachine learning algorithms operating in an unsupervised fashion has emerged as promising tools for detecting structural damage in an automated fashion. Its essence relies on selecting appropriate features to train the model using the reference data set collected from the healthy structure and employing the trained model to identify outlier conditions representing the damaged state. In this paper, the coefficients and the residuals of the autoregressive model with exogenous input created using only the measured output signals are extracted as damage features. These features obtained at the baseline state for each sensor cluster are then utilized to train the one class support vector machine, an unsupervised classifier generating a decision function using only patterns belonging to this baseline state. Structural damage, once detected by the trained machine, a damage index based on comparison of the residuals between the trained class and the outlier state is implemented for localizing damage. The two-step damage assessment framework is first implemented on an eight degree-of-freedom numerical model with the effects of measurement noise integrated. Subsequently, vibration data collected from a one-story one-bay reinforced concrete frame inflicted with progressive levels of damage have been utilized to verify the accuracy and robustness of the proposed methodology.
Wiener-Hopf Indices of Unitary-Valued Functions on the Imaginary Axis
Authors: Frazho A. E. , Ran A. C. M. , van Schagen F. 
Published: September 2024

AbstractThis paper is concerned with the Wiener-Hopf indices of unitary-valued rational matrix functions on the imaginary axis. These indices play a role in the Fredholm theory for Wiener-Hopf integral operators. Our main result gives formulas for the Wiener-Hopf indices in terms of the matrices appearing in realizations of the factors in a Douglas-Shapiro-Shields factorization of the unitary-valued function. Two approaches to this problem are presented: one direct approach using operator theoretic methods, and a second approach using the Cayley transform which allows to use results for an analogous problem regarding unitary-valued functions on the unit circle and corresponding Toeplitz operators.
Can Physicochemical Properties Alter the Potency of Aeroallergens? Part 1 – Aeroallergen Protein Families
Authors: Teixeira Carla S. S. , Carriço-Sá Bruno , Villa Caterina , Mafra Isabel , Costa Joana 
Published: September 2024

Abstract
Purpose of Review
Respiratory allergies are non-communicable diseases caused by the hypersensitivity of the immune system to environmental aeroallergens. The culprits are aero-transported proteins eliciting respiratory symptoms in sensitized/allergic individuals. This review intends to provide a holistic overview on the categorization of aeroallergens into protein families (Part 1) and to exploit the impact of physicochemical properties on inhalant protein allergenicity (Part 2). This first part will focus particularly on aeroallergen organization into families and how this classification fits their physicochemical properties.

Recent Findings
Aeroallergen classification into protein families facilitates the identification of common physicochemical properties, thus aiding a better comprehension of known allergens, while predicting the behavior of novel ones. The available online databases gathering important features of aeroallergens are currently scarce.

Summary
Information on distinct aeroallergen classification is still lacking, as data is dispersed and often outdated, hampering an efficient evaluation of new aeroallergens.
Innovations in Imaging: 18F-Fluorodeoxyglucose PET/CT for Assessment of Cardiovascular Infection and Inflammation
Authors: Trivedi Siddharth J , Bourque Jamieson M 
Published: September 2024

Abstract
Purpose of review
18F-Fluorodeoxyglucose positron emission tomography (PET) combined with computed tomography (CT), referred to as 18F-FDG PET/CT, plays a significant role in the diagnosis and management of patients with systemic infectious and inflammatory conditions. This review provides an overview of 18F-FDG PET/CT in systemic infectious and inflammatory conditions, including infective endocarditis (IE), cardiac implantable electrical device (CIED)/left ventricular assist device (LVAD) infection, sarcoidosis, and large-vessel vasculitis (LVV).

Recent Findings
This review highlights the past and present literature in the increasing role of 18F-FDG PET/CT in cardiovascular inflammation and infection, including diagnostic and prognostic findings.

Summary
They key aspects of this paper are to highlight the importance of 18F-FDG PET/CT in cardiovascular infection and inflammation, and to provide illustrations of how it can contribute to patient diagnosis and management.
Long-term experience with octreotide and lanreotide for the treatment of gastroenteropancreatic neuroendocrine tumors
Authors: Kiesewetter Barbara , Pflüger Friedrich Franz , Melhorn Philipp , Mazal Peter , Raderer Markus 
Published: September 2024

Abstract
Introduction
The somatostatin analogs (SSA) octreotide and lanreotide are a mainstay in the treatment of neuroendocrine tumors (NET). The two pivotal trials differed considerably in terms of patient characteristics and are not directly comparable. Further comparative data are lacking.

Methods
This retrospective chart review study included patients with gastroenteropancreatic NET grade 1 or 2 who were treated with octreotide LAR or lanreotide autogel. The main aim was to compare the two SSA based on progression-free survival (PFS) and overall survival (OS) from treatment start.

Results
In total, 129 patients were analyzed, 60% (n = 77) had a small intestinal NET and 31% (n = 40) a pancreatic NET. Histologically, 34% (n = 44) had NET G1, 55% (n = 71) a NET G2, and 11% (n = 14) a NET G1/G2 unclassified. Lanreotide was used in 90 patients (70%) and octreotide in 39 patients (30%). Overall, the median PFS was 32.2 months (95% CI 23.0–42.9 months). No PFS difference (p = 0.8) was observed between lanreotide (29.8 months, 95% CI 18.7–48.5 months) and octreotide (36.0 months, 95% CI 23.2–68.2 months). Median OS from treatment start was calculated at 93.5 months (95% CI 71.1–132.9 months). Again, the median OS following lanreotide (113.4 months, 95% CI 62.3–NA months) or after octreotide (90.3 months, 95% CI 71.1–NA months) did not differ significantly (p > 0.9).

Conclusions
Our long-term experience with octreotide and lanreotide in NET did not reveal differences in antitumor effectiveness. This is consistent with previous reports and might suggest that both SSA can be used interchangeably if needed.
Leukocyte Extracellular Vesicles Predict Progression of Systolic Dysfunction in Heart Failure with Mildly Reduced Ejection Fraction (LYCHEE) – A Prospective, Multicentre Cohort Study
Authors: Gąsecka Aleksandra , Siniarski Aleksander , Duchnowski Piotr , Stępień Konrad , Błażejowska Ewelina , Gajewska Magdalena , Karaban Kacper , Porębska Kinga , Reda Aleksandra , Rogula Sylwester , Rolek Bartosz , Słupik Dorota , Gozdowska Roksana , Kleibert Marcin , Zajkowska Dominika , Grąt Michał , Grabowski Marcin , Filipiak Krzysztof J. , van der Pol Edwin , Nieuwland Rienk 
Published: September 2024

AbstractRisk stratification in heart failure with mildly-reduced ejection fraction (HFmrEF) remains challenging. We evaluated the predictive value of advanced glycation end products (AGEs) and plasma concentrations of extracellular vesicles (EVs) for the systolic and diastolic dysfunction progression in HFmrEF patients. Skin AGE accumulation was measured using AGE Reader. Plasma EV concentrations were measured using flow cytometry. Among 74 patients enrolled, 13 (18%) had systolic dysfunction progression and 5 (7%) had diastolic dysfunction progression during 6.5 months follow-up. Leukocyte EVs concentrations were higher in patients with systolic dysfunction progression (p = 0.002) and predicted the progression with 75.0% sensitivity and 58.3% specificity, independent of other clinical variables (OR 4.72, 95% CI 0.99–22.31). Skin AGE levels and concentrations of other EV subtypes were not associated with systolic or diastolic dysfunction progression. Increased leukocyte EVs concentrations are associated with 4.7-fold higher odds of systolic dysfunction progression in HFmrEF patients.
Graphical Abstract
AGE – advanced glycation end products, HFmrEF – heart failure with mildly reduced ejection fraction, ECHO – echocardiography, EV – extracellular vesicles
Navigating Business Model Redesign: The Compass Method for Identifying Changes to the Operating Model
Authors: Lara Machado Paola , van de Ven Montijn , Aysolmaz Banu , Turetken Oktay , vom Brocke Jan 
Published: September 2024

AbstractIn today’s dynamic business environment, organizations constantly change their business models to respond to emerging digital technologies and shifting customer expectations. It is a fundamental challenge to translate these changes into the organization’s operating model. When organizations redesign their business models, significant adjustments to the operating model and its underlying business processes are necessary to ensure the effective delivery of the value proposition to customers. Existing research falls short in detailing how changes to the business model at the tactical level impact the operating model at the operational level. To address this gap, this paper introduces the Compass Method. This method provides guidance for decision-makers at the tactical and operational levels in identifying necessary changes to their operating model using a set of operating model design cards. The method has been developed following the design science research methodology and is grounded in extant knowledge from both business model research and process management research. Three rounds of design and evaluation of the method were completed in multiple settings. The study contributes to the understanding of the relationship between business models, operating models, and business processes, paving the way for the development of complementary methods and tools to further investigate this relationship.
Non-HACEK gram-negative bacilli infective endocarditis: data from a retrospective German cohort study
Authors: Dörfler Juliane , Grubitzsch Herko , Schneider-Reigbert Matthias , Pasic Miralem , Pfäfflin Frieder , Stegemann Miriam , Sander Leif E. , Kurth Florian , Lingscheid Tilman 
Published: September 2024

Abstract

Purpose
Infective endocarditis caused by non-HACEK gram-negative bacilli (GNB-IE) is rare but associated with significant morbidity and case fatality. Evidence on optimal treatment and management is limited. We aimed to describe the characteristics and management of GNB-IE patients, investigating factors associated with disease acquisition and unfavorable outcomes.

Methods
We conducted a retrospective descriptive single-center study (tertiary care and referral hospital) between 2015 and 2021, including adult patients with definite GNB-IE. We reviewed demographic, clinical and microbiological data, focusing on predisposing factors, clinical outcomes and 1-year mortality.

Results
Of 1093 patients with probable or definite IE, 19 patients (median age 69 years) had definite GNB-IE, with an increasing incidence throughout the study period. Median age-adjusted Charlson Comorbidity Index score was 4 points. Prosthetic valve IE (PVIE) was present in 7/19 (37%) patients. Nosocomial acquisition occurred in 8/19 (42%) patients. Escherichia coli and Klebsiella pneumoniae were the most common pathogens. Beta-lactam (BL) based combination therapy was applied in 12/19 (63%) patients (58% BL + fluoroquinolone, 42% BL + aminoglycoside). Cardiac surgery was required in 8/19 (42%) patients (PVIE 71%, native valve IE 25%), primarily for embolism prevention and heart failure. Complications occurred in 14/19 (74%) patients. The in-hospital mortality rate was 21% (4/19); the one-year mortality rate was 44% (7/16). One-year mortality did not significantly differ between patients who underwent cardiac surgery and patients managed with anti-infective treatment alone (p = 0.633).

Conclusions
GNB-IE affects elderly patients with high comorbidity levels and recent health-care exposure. GNB-IE was associated with high complication rates and high mortality.
N-AquaRAM: A Cost-Efficient Deep Learning Accelerator for Real-Time Aquaponic Monitoring
Authors: Siddique Ali , Iqbal Muhammad Azhar , Sun Jingqi , Zhang Xu , Vai Mang I. , Siddique Sunbal 
Published: September 2024

AbstractAquaponics is an emerging area of agricultural sciences that combines aquaculture and hydroponics in a symbiotic way to increase crop production. Though it offers a lot of advantages over traditional techniques, including chemical-free and soil-less farming, its commercial application suffers from some problems such as the lack of experienced manpower. To operate a stable smart aquaponic system, it is critical to estimate the fish size properly. In this context, the use of dedicated hardware for real-time aquaponic monitoring can greatly resolve the issue of inexperienced handlers. In this article, we present a complete methodology to train a deep neural network to perform fish size estimation in real time. To achieve high accuracy, a novel implementation of swish function is presented. This novel version is far more hardware efficient than the original one, while being extremely accurate. Moreover, we present a deep learning accelerator that can classify 40 million fish samples in a second. The dedicated real-time system is about 1600 times faster than the one based on general-purpose computers. The proposed neuromorphic accelerator consumes about 2600 slice registers on a low-end model of Virtex 6 FPGA series.
Unveiling Disparities: Analyzing Hispanic Inclusion in Liver Cancer Research Databases in the United States
Authors: Figueroa Gabriela Arroyo , Greten Tim F. , Bonilla Cecilia Monge 
Published: September 2024

AbstractPrimary liver cancer, including hepatocellular carcinoma and intrahepatic cholangiocarcinoma was the sixth leading cause of cancer death in the United States in 2023. Hispanic people constitute approximately 19% of the nation’s total population according to the US Census. Hispanic patients have the highest relative incidence rates of liver cancer compared to non-Hispanic Whites and non-Hispanic Blacks, a disparity frequently overlooked in cancer research. In this study, our primary objective was to analyze the potential underrepresentation of Hispanic individuals in liver cancer research databases. We identified databases that had liver cancer-specific studies and be population-based in the United States. Our search yielded 7 cancer genomic databases, which were analyzed according to incidence percentages across ethnicity and race categories. Our study included 3104 patients; ethnic data was not reported for 13.1% (n = 406) of the patients. Samples were predominantly from individuals who identified as Not Hispanic (81.0%), Hispanic individuals represented 5.9%. Race was reported as follows: non-Hispanic Whites (61.0%), Asians (22.0%), non-Hispanic Blacks (5.4%), Other (3.1%), Native American/American Indian/Alaska Native (0.4%), Pacific Islander/Native Hawaiian (0.2%) and not reported (7.9%). These findings collectively underscore significant disparities in the representation of ethnic and racial groups, particularly Hispanics. Given the present racial and ethnic demographics of the US population and the projected surge in the Hispanic population in forthcoming years, it becomes imperative to address health disparities that may worsen without efforts to enhance proper inclusion in cancer research.
Young Doctors Program-Colorado: An Elective Elementary School Program to Improve Health Literacy, Utilization of the Healthcare System, and Osteopathic Awareness
Authors: Sposet Samantha , Fabich Riley , McEchron Matthew 
Published: September 2024

AbstractThe Young Doctors Program (YDP) is a “mini medical school” series for fifth-grade elementary children. The YDP was designed and led by medical students in the Academic Medicine and Leadership Track at the Rocky Vista University College of Osteopathic Medicine in Colorado. The curriculum of the program was designed around the State of Colorado Learning Standards with the purpose of educating students about emergencies and common ailments in five body systems (cardiovascular, respiratory, gastrointestinal, musculoskeletal, and renal) while also providing exposure to healthcare as a profession. YDP provides children with insights into the healthcare system, an introduction to osteopathic medicine, and it enhances community outreach. This article provides a framework for the semester-long YDP curriculum as well as our final event which synthesizes learned information using standardized patients. We describe successes including community outreach and healthcare exposure in the elementary school, and challenges initiating connections with local schools and funding. Future goals include expanding outreach to other fifth-grade schools as well as growth to different age levels. Authors plan to pursue IRB approval for research to examine the benefits and efficacy of the YDP.