bluuebunny/crossref_metadata_2025_split huggingface dataset:
Template-Based Image Reconstruction Facing Different Topologies
Authors: Neumayer Sebastian , Topalovic Antonia 
Published: February 2024

AbstractThe reconstruction of images from measured data is an increasing field of research. For highly under-determined problems, template-based image reconstruction provides a way of compensating for the lack of sufficient data. A caveat of this approach is that dealing with different topologies of the template and the target image is challenging. In this paper, we propose a LDDMM-based image-reconstruction model that resolves this issue by adding a source term. On the theoretical side, we show that the model satisfies all criteria for being a well-posed regularization method. For the implementation, we pursue a discretize-then-optimize approach involving the proximal alternating linearized minimization algorithm, which is known to converge under mild assumptions. Our simulations with both artificial and real data confirm the robustness of the method, and its ability to successfully deal with topology changes even if the available amount of data is very limited.
Enhancing the Sustainability of Poly(Lactic Acid) (PLA) Through Ketene-Based Chain Extension
Authors: Alkan Goksu Yonca 
Published: February 2024

AbstractThe widespread utilization of nonrenewable fossil-based polymers has led to significant environmental damage. Bio-based Poly(lactic acid) (PLA) has garnered substantial academic and industrial interest in the last two decades due to its advantageous characteristics for food packaging applications. Nonetheless, the improper disposal of PLA continues to contribute to the plastic waste problem. PLA recycling mainly involves thermal processes, facing challenges due to PLA’s limited stability. This study aims to enhance PLA’s molecular weight and melt viscosity by using chain extenders to increase its degree of branching. A modular chain extender capable of thermally forming highly reactive ketene intermediates is employed to react with PLA’s hydroxyl and carboxyl end groups in a single step. For this purpose, copolymers of styrene and 2,2,5-trimethyl-5-(4-vinylbenzyl)-1,3-dioxane-4,6-dione were synthesized using free radical polymerization and characterized through 1H-NMR, TGA, and DSC analyses. The chemical interaction between these chain extenders and molten PLA was also explored, resulting in increased PLA molecular weight and higher melting temperature (Tm), reaching 155.1 for PLA_2.5CE2. Additionally, the branching introduced through this process led to a notable increase in the UV absorption of PLA, suggesting potential applications in the packaging industry. The chemical tunability of this functional ketene-based chain extender holds promise for tailoring PLA’s structure for diverse applications, further advancing its sustainability and utility.
Graphical Abstract
A population pharmacokinetics model of balovaptan to support dose selection in adult and pediatric populations
Authors: Schaedeli Stark Franziska , Chavanne Clarisse , Derks Michael , Jolling Koen , Lagraauw Hendrik Maxime , Lindbom Lars , Prins Klaas , Silber Baumann Hanna E. 
Published: February 2024

AbstractBalovaptan is a brain-penetrating vasopressin receptor 1a antagonist previously investigated for the core symptoms of autism spectrum disorder (ASD). A population pharmacokinetic (PK) model of balovaptan was developed, initially to assist clinical dosing for adult and pediatric ASD studies and subsequently for new clinical indications including malignant cerebral edema (MCE) and post-traumatic stress disorder. The final model incorporates one-compartment disposition and describes time- and dose-dependent non-linear PK through empirical drug binding and a gut extraction component with turnover. An age effect on clearance observed in children was modeled by an asymptotic function that predicts adult-equivalent exposures at 40% of the adult dose for children aged 2–4 years, 70% for 5–9 years, and at the full adult dose for ≥ 10 years. The model was adapted for intravenous (IV) balovaptan dosing and combined with in vitro and ex vivo pharmacodynamic data to simulate brain receptor occupancy as a guide for dosing in a phase II trial of MCE prophylaxis after acute ischemic stroke. A sequence of three stepped-dose daily infusions of 50, 25 and 15 mg over 30 or 60 min was predicted to achieve a target occupancy of ≥ 80% in ≥ 95% of patients over a 3-day period. This model predicts both oral and IV balovaptan exposure across a wide age range and will be a valuable tool to analyze and predict its PK in new indications and target populations, including pediatric patients.
A method to predict connectivity for nomadic waterbird species from tracking data
Authors: Nicol Sam , Lloyd-Jones Luke , McGinness Heather M. 
Published: February 2024

Abstract
Context
Nomadic waterbird species move erratically, which makes it difficult to predict site use and connectivity over time. This is particularly pertinent for long-distance movements, during which birds may move between sites hundreds to thousands of kilometres apart.

Objectives
This study aimed to understand how landscape and weather influence long-distance waterbird movements, to predict the probability of connectivity between locations and forecast short-term movements for a nomadic species, the straw-necked ibis (Threskiornis spinicollis) in Australia’s Murray–Darling basin.

Methods
We used 3.5 years of satellite tracking data together with high-resolution landscape and weather variables to model the expected distance travelled under environmental scenarios for long-distance movements. We generated least-cost paths between locations of interest and simulated the probability that birds could exceed the least cost-distance as a measure of connectivity. We also generated short-term forecasts (1–3 days; conditional on departure) of the probability of bird occurrence at a location given the expected environmental conditions.

Results
Our results suggested that wind is the dominant predictor of distance travelled during long-distance movements, with significant but smaller effects from month. Birds travelled further when wind benefit was higher and during summer. Further work is required to validate our forecasts of bird positions over short time periods.

Conclusions
Our method infers the predictors of poorly understood movements of nomadic birds during flight. Understanding how partial migrants use landscapes at large scales will help to protect birds and the landscapes where they live.
A fault detection strategy for an ePump during EOL tests based on a knowledge-based vibroacoustic tool and supervised machine learning classifiers
Authors: Borriello Pasquale , Tessicini Fabrizio , Ricucci Giuseppe , Frosina Emma , Senatore Adolfo 
Published: February 2024

AbstractThis paper presents a methodology for identifying faulty components in an electric pump during the end-of-line test based on accelerations and pressure pulsation data used to train an ensemble learning algorithm based on supervised machine learning classifiers. Despite various quality control measures in pump manufacturing, some out-of-tolerance components can pass through and end up on the assembly line, potentially leading to premature failure or abnormal noise during real-field operation. Because of the high impact, it is very important to put in place actions to mitigate the risk of delivering non-conform units, even if properly working in terms of pressure-flow rate performances. In this paper, an innovative knowledge-based vibroacoustic tool together with a machine learning built-in Python® library have been used to post-process acceleration and pressure pulsations data to generate features, which are then used to train, and test several supervised machine learning algorithms. The ensemble learning algorithm combines the best classifiers to identify healthy electric pump units with high accuracy, achieving above 95% accuracy in an experimental test campaign carried out on eighty electric pumps. Results are compared using principal component analysis for dimensionality reduction, and a sensor sensitivity study is conducted.
Trajectory-based alignment for optical see-through HMD calibration
Authors: Chen Lingling , Zhao Shaohua , Chen Wei , Shi Zhongchen , Xie Liang , Yan Ye , Yin Erwei 
Published: February 2024

AbstractIn order to align the virtual and real content precisely through augmented reality devices, especially in optical see-through head-mounted displays (OST-HMD), it is necessary to calibrate the device before using it. However, most existing methods estimated the parameters via 3D-2D correspondences based on the 2D alignment, which is cumbersome, time-consuming, theoretically complex, and results in insufficient robustness. To alleviate this issue, in this paper, we propose an efficient and simple calibration method based on the principle of directly calculating the projection transformation between virtual space and the real world via 3D-3D alignment. The proposed method merely needs to record the motion trajectory of the cube-marker in the real and virtual world, and then calculate the transformation matrix between the virtual space and the real world by aligning the two trajectories in the observed view. There are two advantages associated with the proposed method. First, the operation is simple. Theoretically, the user only needs to perform four alignment operations for calibration without changing the rotation variation. Second, the trajectory can be easily distributed throughout the entire observation view, resulting in more robust calibration results. To validate the effectiveness of the proposed method, we conducted extensive experiments on our self-built optical see-through head-mounted display (OST-HMD) device. The experimental results show that the proposed method can achieve better calibration results than other calibration methods.
Real-time diabetic foot ulcer classification based on deep learning & parallel hardware computational tools
Authors: Fadhel Mohammed A. , Alzubaidi Laith , Gu Yuantong , Santamaría Jose , Duan Ye 
Published: February 2024

AbstractMeeting the rising global demand for healthcare diagnostic tools is crucial, especially with a shortage of medical professionals. This issue has increased interest in utilizing deep learning (DL) and telemedicine technologies. DL, a branch of artificial intelligence, has progressed due to advancements in digital technology and data availability and has proven to be effective in solving previously challenging learning problems. Convolutional neural networks (CNNs) show potential in image detection and recognition, particularly in healthcare applications. However, due to their resource-intensiveness, they surpass the capabilities of general-purpose CPUs. Therefore, hardware accelerators such as application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), and graphics processing units (GPUs) have been developed. With their parallelism efficiency and energy-saving capabilities, FPGAs have gained popularity for DL networks. This research aims to automate the classification of normal and abnormal (specifically Diabetic Foot Ulcer—DFU) classes using various parallel hardware accelerators. The study introduces two CNN models, namely DFU_FNet and DFU_TFNet. DFU_FNet is a simple model that extracts features used to train classifiers like SVM and KNN. On the other hand, DFU_TFNet is a deeper model that employs transfer learning to test hardware efficiency on both shallow and deep models. DFU_TFNet has outperformed AlexNet, VGG16, and GoogleNet benchmarks with an accuracy 99.81%, precision 99.38% and F1-Score 99.25%. In addition, the study evaluated two high-performance computing platforms, GPUs and FPGAs, for real-time system requirements. The comparison of processing time and power consumption revealed that while GPUs outpace FPGAs in processing speed, FPGAs exhibit significantly lower power consumption than GPUs.
Irrigation Water Management in a Water-Scarce Environment in the Context of Climate Change
Authors: Gabr Mohamed Elsayed , Awad Ahmed , Farres Hesham N. 
Published: February 2024

AbstractClimate change has a considerable impact on irrigated agriculture, which is vital for food and fiber production. In this study, in the context of climate change, simulation model CROPWAT 8 was employed to compute the reference evapotranspiration, and net irrigation water requirement for wheat, barley, maize, sugar beet, potato, tomato, and date palm. In addition, the WaterGEMS model was utilized to design a new sprinkler irrigation system to run long-term simulations of hydraulic behavior within pressurized pipe networks to irrigate 43 acres for two arid sites (Siwa Oasis and West Elminya fields) inside the 1.5-million-acre groundwater irrigation project in the Egyptian western desert. Five scenarios for climate change were employed in the current (1991–2023), representative concentration path (RCP) 8.5 greenhouse gas emission scenarios for the 2040s, 2060s, 2080s, and 2100s. Mean ETo values for the current scenario show 4.56 and 5.7 mm for the Siwa Oasis and West Elminya fields, respectively. The climate changes cause an increase of the reference evapotranspiration by 4.6, 5.9, 9.4, and 12.7% for RCP: 8.5 greenhouse gas emissions for the 2040s, 2060s, 2080s, and 2100s scenarios, respectively, for the Siwa Oasis field. On the other hand, an increased ratio for the reference evapotranspiration by 4.2, 5.4, 8.6, and 11.6% was observed for the scenarios in the West Elminya field, respectively. The designed sprinkler system indicated a capacity of 111.4 m3 h−1 and 167 m3 h−1 for Siwa and West Elminya fields, respectively. The study suggests using crop patterns for wheat, barley, potato, and sugar beet to save irrigation water.
Graphical abstract
Performance Evaluation of Spectral Efficiency Hybrid Precoding and Combining Algorithm for Millimeter Wave -MIMO Systems
Authors: Samir Youstina Nagy , Nafea Hala B. , Zaki Fayez Wanis 
Published: February 2024

AbstractMultiple input multiple output (MIMO) system with Millimeter Wave spectrum is currently used in most wireless applications and all cellular system to provides high data rates. with using large antenna array which is possible by decrease the wavelength to achieve high beamforming gain and improve the spectral efficiency. in this paper, used low complexity with hybrid precoding at the transmitting side and combining at the receiver side with limited feedback system, by using the concept of orthogonal matching pursuit (OMP) in single and multi-user cases, and compared the results with analog only beasmstring. The results of simulation showed that when used Minimum Mean Square Error (MMSE) precoders performed better than other hybrid precoding approaches, in addition the MMSE hybrid precoding /combining technique offers higher spectral efficiency compared with analog only beamstring.
How to explain social innovation in elderly care services: The role of for-profit and non-profit social enterprises
Authors: Guzmán Carmen , Santos Francisco J. , Savall Teresa 
Published: February 2024

AbstractSocial innovation and social enterprise are two major factors in addressing the challenges of population ageing since both are aimed at solving social problems. One of these challenges involves providing quality care services for the elderly. However, few studies have analysed how social enterprises can promote or manage social innovations in this sector. This research therefore studies said relationship, paying particular attention to the for-profit and non-profit nature of social enterprises. Specifically, to test the hypotheses, we use data from a survey of nursing homes in southern Spain, where care services are expanding with the support of welfare state social policies. The results show that non-profit social enterprises tend to develop more social innovations in care services, and that the social mission and participative governance positively influence the implementation of social innovations in this activity sector. Consequently, implications for social policies are suggested to better meet the needs of the elderly.
Counterexamples to the MMP for 1-foliations in positive characteristic
Authors: Bernasconi Fabio 
Published: February 2024

AbstractWe show that many statements of the Minimal Model Program, including the cone theorem, the base point free theorem and the existence of Mori fibre spaces, fail for 1-foliated surface pairs $$(X,\mathcal {F})$$

(
X
,
F
)

with canonical singularities in characteristic $$p>0$$

p
>
0

.
A practical tool to enable Indigenous enterprise planning and development grounded in culture
Authors: Maclean Kirsten , Rist Phil , Rassip Whitney , Prudames Nicole 
Published: February 2024

AbstractGlobally, Indigenous people seek to develop sustainable livelihood options that enable them to practice their culture, look after their traditional estates and generate economic development outcomes for their wider community. Enterprise development can and may provide one such pathway. However, challenges can arise with regard to reconciling the core drivers of ‘economic development’ with aspirations to practice and preserve culture. Current enterprise development approaches and models do not always suit Indigenous contexts. In this paper, we present a practical tool to enable Indigenous leaders, their partners, and others, to consider enterprise development options grounded in culture that may generate multiple benefits including economic outcomes. Our tool combines critical review of alternative development models, with empirical research to outline a set of foundational principles, building blocks and potential enterprise development options. We apply the practical tool to a case study of a nascent enterprise from the northern Australia Indigenous-led bush products sector. The case study illustrates how enterprise development planning is integral and discussions should consider how to enable cultural governance, protection of Indigenous cultural and intellectual property, potential benefits and sharing, access to resources, as well as the ‘building blocks’ for enterprise development and consideration of different enterprise approaches. The practical tool aims to ensure development pathways build on local economies and ecologies, do not compromise culture and recognise the influence of extra-local political economies on lived experiences and outcomes.
Tadpoles Develop Elevated Heat Tolerance in Urban Heat Islands Regardless of Sex
Authors: Bókony Veronika , Balogh Emese , Ujszegi János , Ujhegyi Nikolett , Szederkényi Márk , Hettyey Attila 
Published: February 2024

AbstractThe ability of wildlife to endure the effects of high temperatures is increasingly important for biodiversity conservation under climate change and spreading urbanization. Organisms living in urban heat islands can have elevated heat tolerance via phenotypic or transgenerational plasticity or microevolution. However, the prevalence and mechanisms of such thermal adaptations are barely known in aquatic organisms. Furthermore, males and females can differ in heat tolerance, which may lead to sex-biased mortality, yet it is unknown how sex differences in thermal biology influence urban phenotypic divergence. To address these knowledge gaps, we measured critical thermal maxima (CTmax) in male and female agile frog (Rana dalmatina) tadpoles captured from warm urban ponds and cool woodland ponds, and in a common-garden experiment where embryos collected from both habitat types were raised in the laboratory. We found higher CTmax in urban-dwelling tadpoles compared to their counterparts living in woodland ponds. This difference was reversed in the common-garden experiment: tadpoles originating from urban ponds had lower CTmax than tadpoles originating from woodland ponds. We found no effect of sex on CTmax or its difference between habitats. These results demonstrate that aquatic amphibian larvae can respond to the urban heat island effect with increased heat tolerance similarly to other, mostly terrestrial taxa studied so far, and that phenotypic plasticity may be the main driver of this response. Our findings also suggest that heat-induced mortality may be independent of sex in tadpoles, but research is needed in many more taxa to explore potentially sex-dependent urban thermal responses.
Movement efficiency in survivors of childhood acute lymphoblastic leukemia: a report from the St. Jude lifetime cohort study
Authors: Onerup Aron , Mirzaei S. Sedigheh , Wogksch Matthew D. , Goodenough Chelsea G. , Lambert Genevieve , Sapkota Yadav , Mulrooney Daniel A. , Hudson Melissa M. , Jacola Lisa M. , Ness Kirsten K. 
Published: February 2024

Abstract
Purpose
Movement efficiency, a measure of neuromuscular biomechanics, may be modified by physical activity. We aimed to assess the risk of and risk factors for low movement efficiency in survivors of childhood acute lymphoblastic leukemia (ALL).

Methods
Participants underwent an assessment of activity energy expenditure (AEE) with actigraphy, and the gold standard doubly labeled water, where the differences between elimination rates of oxygen and hydrogen from body water are evaluated over a week. Movement efficiency was assessed using the raw residuals of a linear regression between AEEs from accelerometers and doubly labeled water. Elastic-net logistic regressions were used to identify demographic, treatment, and functional variables associated with movement efficiency.

Results
The study cohort included 256 non-cancer controls and 302 ALL survivors (48% female), categorized as efficient (N = 24), normal (N = 245), or inefficient (N = 33) based on their movement efficiency. There was no difference in the odds for poor movement efficiency between survivors (n = 33, 10.9%) compared to controls (n = 23, 9.0%, odds ratio [OR]: 1.19, 95% confidence interval [CI]: 0.67, 2.10; p = 0.55). In survivors, neuropathy was associated with a higher risk of being inefficient compared to efficient (OR 4.30, 95% CI 1.03–17.96), while obesity (≥ 30 kg/m2) had a protective association (OR 0.18, 95% CI 0.04–0.87).

Conclusions
Neuropathy was associated with a higher risk of poor movement efficiency in survivors of childhood ALL.

Implications for cancer survivors
These results further highlight impairments associated with treatment-induced neuropathy in survivors of childhood ALL.
Reversible Elevation of Tryptase Over the Individual's Baseline: Why is It the Best Biomarker for Severe Systemic Mast Cell Activation and MCAS?
Authors: Valent Peter , Akin Cem , Arock Michel 
Published: February 2024

Abstract
Purpose of Review
Mast cell (MC) activation syndromes (MCAS) are conditions defined by recurrent episodes of severe systemic anaphylaxis or similar systemic events triggered by MC-derived mediators that can be measured in biological fluids. Since some symptoms of MC activation may occur due to other, non-MC etiologies and lead to confusion over diagnosis, it is of crucial importance to document the involvement of MC and their products in the patients´ symptomatology.

Recent Findings
The most specific and generally accepted marker of severe systemic MC activation is an event-related, transient increase in the serum tryptase level over the individual baseline of the affected individual. However, baseline concentrations of serum tryptase vary among donors, depending on the genetic background, age, kidney function, and underlying disease. As a result, it is of critical importance to provide a flexible equation that defines the diagnostic increase in tryptase qualifying as MCAS criterion in all patients, all situations, and all ranges of baseline serum tryptase. In 2012, the consensus group proposed the 120% + 2 ng/ml formula, which covers the great majority of groups, including cases with low, normal, or elevated basal serum tryptase level.

Summary
This formula has been validated in subsequent studies and has proven to be a robust and consistent diagnostic criterion of MCAS. The present article is discussing the impact of this formula and possible limitations as well as alternative markers and mediators that may be indicative of MCAS.