bluuebunny/crossref_metadata_2025_split huggingface dataset:
Variances in Smoking Expectancies Predict Moment-to-Moment Smoking Behaviors in Everyday Life
Authors: Halliday Deanna M. , Zawadzki Matthew J. , Song Anna V. 
Published: April 2024

Abstract
Background
Many policy decisions about tobacco control are predicated on rational choice models, which posit (1) that smokers are aware of the risks of cigarettes and (2) that perceived risks have a consistent influence on continued smoking behavior. However, research shows that beliefs about smoking may be vulnerable to changes in internal and external contexts.

Methods
Using ecological momentary assessment, we tested this by measuring how smokers’ (N = 52) beliefs about smoking varied over time. Four times per day over 1 week, participants responded to measures of smoking intentions, risk perceptions, mood and social outcome expectancies, and internal and external contextual factors.

Results
We analyzed this data using multilevel modeling, finding that both smoking intentions, risk perceptions, and expectancies differed between participants as well as between moments.

Conclusion
Risk perceptions and mood expectancies were a significant predictor of intentions to smoke in the next 30 min, illustrating the importance of these beliefs in decisional processes. This study was preregistered at the Open Science Foundation: https://osf.io/wmv3s/?view_only=71ad66d3ce3845fcb3bf2b9860d820c9. Our analytic plan was not preregistered.
Room to Improve: Predictors of Attendance and Outcomes Within Mindfulness-Enhanced Behavioral Parent Training
Authors: Donovan Mark O. , Barkus Emma , Herbert Jane S. , Pickard Judy A. 
Published: April 2024

Abstract
Objectives
Parents across a broad sociodemographic spectrum struggle with their children’s difficult behaviors and need effective and engaging interventions. We developed a mindfulness-enhanced behavioral parent training group program (MeBPT) aiming to be more inclusive and enable positive outcomes. This study investigated whether MeBPT can meet diverse needs across child, parent, family, and program-delivery factors, and explored whether improvements in parent-rated child behavior are predicted by changes in mindful parenting, parenting approach, or both.

Method
Participants were 338 parents of 3- to 12-year-old children presenting with externalizing problems to a university clinic in regional Australia. Factors that significantly correlated with improvements in parent and child outcomes or attendance were included in regression analyses.

Results
Improved parent-rated child behavior was predicted by change in mindful parenting (p = 0.019) but not parenting approach (p = 0.305). Attendance was high across all factors, and particularly for older parents. Improvements in parent well-being, approach, mindfulness, and child behavior were similarly large for families across child and family characteristics. Low-income families exhibited less improvement in parental well-being (p = 0.012), although demonstrated similar improvements in child behavior, parenting approach, and mindful parenting. Families with more severe problems at baseline showed largest gains (p < 0.002). Parental self-awareness and acceptance were important change agents.

Conclusions
MeBPT appears effective across various sociodemographic backgrounds and is particularly beneficial for families presenting with more severe behavioral problems. Controlled research with ethnically diverse families is needed to confirm the benefits of MeBPT and to allow examination of mediators and moderators.
Rediscovery of small-scale fisheries in the era of crises
Authors: Salmi Pekka , Setälä Jari , Saarni Kaija 
Published: April 2024

AbstractThis article analyses the role of small-scale fisheries in the era of crises that increase fisheries’ vulnerability. Crises may also trigger a reconsideration of the value of small-scale fisheries. Thus, our main research questions are twofold: 1) How do the recent crises directly affect small-scale fisheries? and 2) What are the opportunities for reinventing the societal and environmental benefits of small-scale fisheries? Answers to the research questions are based on a selection of interviews, email inquiry, research articles and reports in the context of Finnish small-scale fisheries. By focusing on these fisheries, operated in a Northern European welfare state, we study the potential that the new turbulent and uncertain circumstances could lead to acknowledgement of the multifunctional character of small-scale fisheries. The results show that climate change, Covid-19 pandemic and Russian invasion of Ukraine have challenged the resilience of Finnish small-scale fishing livelihood, albeit moderately. The prospects for new policies triggered by these crises stem from acknowledgement of small-scale fisheries’ contribution to food security, environmental benefits and short supply chains. The best way to secure fish-based food security and sustainability during crises, is to keep the fishing sector and the production and distribution chains vital in normal conditions. We conclude that in a society like Finland the rediscovery of small-scale fisheries’ future necessitates wide societal and political discussion about the pros and cons of the livelihood, together with inclusive governance that recognizes the multifunctional roles of small-scale fisheries in the era of crises.
Serum carnosinase 1, an early indicator for incident microalbuminuria in type 1 diabetes
Authors: Qiu Jiedong , Yard Benito A. , Krämer Bernhard K. , Bilo Henk J. G. , Kannt Aimo , van Goor Harry , van Dijk Peter R. 
Published: April 2024

Abstract
Aims
Carnosinase (CN1) polymorphisms have been linked to diabetic kidney disease (DKD), as CN1 degrades dipeptides which scavenge oxidative metabolites and prevent the formation of advanced glycation end-products. In this work, we studied the association between serum CN1, the systemic redox status and long-term renal outcome in type 1 diabetes.

Methods
Serum CN1 was measured in a prospective type 1 diabetes cohort (n = 218) with a 16-year follow-up. A total of 218 patients treated at the Diabetes Outpatient Clinic of the Weezenlanden Hospital (nowadays Isala Hospital, Zwolle, The Netherlands) were included in this analysis. We assessed whether serum CN1 was associated with renal function and development of DKD as well as other diabetic complications.

Results
At baseline, age, systemic redox status and N-terminal pro brain-natriuretic peptide (NT-proBNP) were associated with serum CN1 concentration (p < 0.05). During follow-up, CN1 concentration in the middle tertile was associated with less incident microalbuminuria (odds ratio = 0.194, 95% C.I.: 0.049—0.772, p = 0.02) after adjustment for age, systemic redox status, NT-proBNP and sex.

Discussion
Serum CN1 could predict incident microalbuminuria and may be used as a novel parameter to identify patients at risk for DKD.
Balance Board Math: Exploring the Sense of Balance as a Basis for Functions and Graphing and Number Line Concepts
Authors: Tancredi Sofia 
Published: April 2024

AbstractCan math concepts be experienced through the sensory modality of balance? Balance Board Math (BBM) is a set of pedagogical math activities designed to instantiate mathematical concepts through stimulation to the vestibular sense: an organ in the inner ear that detects our bodily balance and orientation. BBM establishes the different ways children spontaneously rock and move as the basis for inclusively exploring mathematical concepts together across diverse sensory profiles. I describe two activity sets where students explore focal concepts by shifting their balance on rockable balance boards: “the Balance Number Line,” using analog materials to foster understandings of the number line and negative numbers, and “Balance Graphing,” using sensors and a digital display to foster exploration of functions and graphing concepts, including the parameters of trigonometric functions and function addition. I outline proposed ways that engaging with concepts through balance-activating movement can change learners’ mathematical thinking and learning.
The Impact of Subway Station Proximity on Apartment Prices in Shiraz
Authors: Kashkooli Hamed Najafi , Hajipoor Khalil , Arasteh Mojtaba , Soltani Ali 
Published: April 2024

AbstractProximity to public transportation, such as subway stations is often considered as one of the main factors affecting urban land value and housing prices. However, the magnitude and direction of this impact may vary depending on the context and characteristics of each city. This paper aims to investigate the effect of subway station proximity on apartment prices in Shiraz, a major city in Iran with a population of over 1.8 million people. Using a hedonic price model and regression technique, we analyzed a dataset of 128 apartment transactions, controlling for apartment size, location, age, and other characteristics. The results differ from previous studies which suggested being closer to the transit station affects the property price due to accessibility. The findings suggest that distance to subway stations has an insignificant effect on apartment prices in Shiraz, with property size, location, and age being key determinants of apartment prices. The possible reasons for this result were discussed and recommendations were made for the development of further studies.
Building a Fully-Automatized Active Learning Framework for the Semantic Segmentation of Geospatial 3D Point Clouds
Authors: Kölle Michael , Walter Volker , Sörgel Uwe 
Published: April 2024

AbstractIn recent years, significant progress has been made in developing supervised Machine Learning (ML) systems like Convolutional Neural Networks. However, it’s crucial to recognize that the performance of these systems heavily relies on the quality of labeled training data. To address this, we propose a shift in focus towards developing sustainable methods of acquiring such data instead of solely building new classifiers in the ever-evolving ML field. Specifically, in the geospatial domain, the process of generating training data for ML systems has been largely neglected in research. Traditionally, experts have been burdened with the laborious task of labeling, which is not only time-consuming but also inefficient. In our system for the semantic interpretation of Airborne Laser Scanning point clouds, we break with this convention and completely remove labeling obligations from domain experts who have completed special training in geosciences and instead adopt a hybrid intelligence approach. This involves active and iterative collaboration between the ML model and humans through Active Learning, which identifies the most critical samples justifying manual inspection. Only these samples (typically $$\ll 1{\%}$$

≪
1
%

of Passive Learning training points) are subject to human annotation. To carry out this annotation, we choose to outsource the task to a large group of non-specialists, referred to as the crowd, which comes with the inherent challenge of guiding those inexperienced annotators (i.e., “short-term employees”) to still produce labels of sufficient quality. However, we acknowledge that attracting enough volunteers for crowdsourcing campaigns can be challenging due to the tedious nature of labeling tasks. To address this, we propose employing paid crowdsourcing and providing monetary incentives to crowdworkers. This approach ensures access to a vast pool of prospective workers through respective platforms, ensuring timely completion of jobs. Effectively, crowdworkers become human processing units in our hybrid intelligence system mirroring the functionality of electronic processing units.
Is sarcopenia a real concern in ankylosing spondylitis? A systematic literature review
Authors: Ceolin Chiara , Papa Mario Virgilio , Scagnellato Laura , Doria Andrea , Sergi Giuseppe , Ramonda Roberta 
Published: April 2024

Abstract
Purpose
Sarcopenia is a condition defined as loss of muscle mass and strength, associated with poor functional performance and disability. Sarcopenia can be exacerbated or worsened in presence of inflammation, sedentary lifestyle and cytokine imbalance, thus it frequently occurs in people affected by rheumatic diseases. This systematic literature review aims to explore the association between sarcopenia and spondyloarthritis (SpA) and its most frequent manifestation, i.e. ankylosing spondylitis (AS).

Methods
The Scopus, PubMed, and Web of Science databases were searched for articles on muscle mass, muscle strength and axial SpA, from any date to November 2023. Only studies written in English were considered. The methodological quality of the studies included in the review was evaluated using the Newcastle–Ottawa Scales for observational studies and for case–control studies.

Results
190 papers were retrieved from the searches, 14 of which met the inclusion criteria. Rather than diagnosis of sarcopenia, pre-sarcopenia or probable sarcopenia were frequent in people with AS, with a great reduction especially of muscle strength. The pre-sarcopenia status appears to be related to high AS disease activity, suggesting that chronic inflammation resulting in pain, less movement and decreased physical activity could play a role in the muscle heath of AS patients.

Conclusions
Our review confirms the existence of an association between AS and loss of muscle strength—likely sarcopenia—already at a young age. Preventive and early strategies should be adopted to ensure successful aging for individuals with AS.
Optimization of barrel temperature and feed moisture content for better physicochemical and sensory properties of extruded snacks from blends of finger millet, sweet potato, and soybean composite flour using response surface methodology
Authors: Mohammed Ibrahim , Forsido Sirawdink Fikreyesus , Kuyu Chala G. 
Published: April 2024

AbstractExtruded snacks are commonly made with cereals with good expansion properties but low in essential nutrients such as protein and vitamins. The incorporation of legume and vegetable crops into cereal improves the nutritional value of cereal-based extruded snacks. This study aimed to develop a nutrient-rich optimized extruded snack by incorporating orange-fleshed sweet potato, finger millet, and soybean flour. The extrusion processing conditions were barrel temperature (90–130 °C) and feed moisture content (20–26%). Thirteen treatment combinations were generated for this experiment using a face-centered central composite design. Standard methods were used to evaluate the effect of barrel temperature and feed moisture content on extruded snacks' nutritional, anti-nutritional, physical, functional, and sensory acceptability. The data were analyzed, and processing conditions were optimized using the response surface methodology of Design Expert software version 13. Multiple regression analysis showed significant effects (p < 0.05) of the independent variables on moisture, protein, fat, beta-carotene, bulk density (BD), hardness, expansion ratio (ER), water absorption index (WAI), water solubility index (WSI), and overall acceptability of the extrudates. The optimum response of 14.06% protein, 3.26% ash, 69.12% carbohydrate, 6.477 mg/100 g beta-carotene, 0.36 g/ml bulk density, 2.72 Expansion ratio, 87.28 N hardness, 4.34 g/g Water absorption index, 22.34% Water solubility index, and overall acceptability of 3.30 was achieved at an optimal barrel temperature of 114.5 °C and feed moisture content of 20%. The obtained result suggests that barrel temperature and feed moisture content had a significant influence (p < 0.05) on the measured quality properties of the extrudates.
A comprehensive review of phytochemicals of Withania somnifera (L.) Dunal (Solanaceae) as antiviral therapeutics
Authors: Ozeer Fathima Zahraa , Nagandran Saraswathi , Wu Yuan Seng , Wong Ling Shing , Stephen Annatasha , Lee Michelle Felicia , Kijsomporn Jureerat , Guad Rhanye Mac , Batumalaie Kalaivani , Oyewusi Habeebat Adekilekun , Verma Amita , Yadav Ekta , Afzal Sheryar , Sekar Mahendran , Subramaniyan Vetriselvan , Fuloria Neeraj Kumar , Fuloria Shivkanya , Sarker Md. Moklesur Rahman 
Published: April 2024

AbstractViruses have caused millions and billions of infections and high mortality rates without successful immunization due to a lack of antiviral drugs approved for clinical use. Therefore, the discovery of novel antiviral drugs is impertinent and natural products are excellent alternative sources. Withania somnifera (L.) Dunal (Solanaceae) is recognized as one of the most significant herbs in the Ayurvedic system and it had been utilized in various biological actions for more than 3000 years. This review aimed to discuss the therapeutic effects and associated molecular mechanisms of Withania somnifera (WS) and its phytochemicals, withanolides against various viruses in preclinical and clinical settings towards developing potential inhibitors which could target virus proteins or their respective host cell receptors. WS was reported to attenuate coronavirus disease 2019 (COVID-19), serve as a potential ligand against the herpes simplex virus (HSV) DNA polymerase, suppress Alzheimer’s disease progression by inhibiting the cytotoxicity induced by the human immunodeficiency virus 1 (HIV-1)-activated beta-amyloid (Aβ), and attenuate the neuraminidase activity of H1N1 influenza. WS root extracts have also reduced the mortality rates and stress levels in tilapia infected with tilapia lake virus (TiLV), and stimulated antiviral nitric oxide formation in chicks infected with infectious bursal disease (IBD). With increasing evidence from previous literatures, further in vitro and in vivo investigations of WS against other viral infections may provide promising results.
Graphical Abstract
PLA-HA/Fe3O4 magnetic nanoparticles loaded with curcumin: physicochemical characterization and toxicity evaluation in HCT116 colorectal cancer cells
Authors: Bourang Shima , Asadian Sina , Noruzpour Mehran , Mansuryar Atefeh , Azizi Solmaz , Ebrahimi Hossein Ali , Amani Hooshyar Vahid 
Published: April 2024

AbstractColorectal cancer (CRC) is the third most common, harmful, and universal cancer and the second lethal type. This paper discusses the therapeutic potential of curcumin, a significant curcuminoid found in the substructure of plant Curcuma longa (turmeric), against CRC. Curcumin has the ability to disrupt a variety of cellular signaling pathways and has been validated in several preclinical and clinical studies, but suffers from low solubility and bioavailability. Despite the widespread use of curcumin (CU) against colorectal cancer, it presents limitations, such as low solubility and bioavailability. Due to these drawbacks, researchers focused on new methods to carry CU into cells to overcome the limits of treatments with CU. One of the leading solutions is bioanalytical methods, which are based on using CU in combination with nanoparticles, especially magnetic nanoparticles, which cause the targeted transfer of the drug to cancer cells. To address these issues, PLA-HA/Fe3O4 magnetic nanoparticles were synthesized and loaded with curcumin. The average size and zeta potential of the nanoparticles and the magnetic properties were measured. The drug encapsulation efficiency and cumulative release of curcumin from the nanoparticles under acidic and neutral pH (4.8, 6, and 7.4) values were evaluated, as well as the cytotoxic effect of the nanoparticles on HCT116 colorectal cancer cells. According to the results of DLS and TEM analysis, PLA/Fe3O4/curcumin nanoparticles had a spherical structure with an average size of 208 Å ± 12.8 nm and a Zeta potential of − 18 (mV). The drug encapsulation efficiency in PLA-HA/Fe3O4 nanoparticles was 24.8 ± 4.6 percent. The drug's release rate was influenced by acidic and neutral pH levels. After 14 days, the highest release rate was 98% at pH 4.8 and over 94% at pH 6 (typical of cancer cells). In contrast, the drug's release at pH 7.4 (typical of healthy cells) after 14 days was only 59%. The results demonstrated that nanoparticles have a high degree of biocompatibility and the ability to carry Curcumin medications. HCT116 cells with 200 μg/ml PLA-HA/Fe3O4/Curcumin nanoparticles have 58.63 ± 3.7% percent cell viability. Ultimately, PLA-HA, Fe3O4, and Curcumin's physicochemical characteristics and impact on cell viability render them valuable instruments for precisely delivering drugs to colorectal cancer cells. The PLA-HA/Fe3O4–curcumin nanoparticles demonstrated a well-targeted drug delivery system for upcoming colorectal cancer treatments, as evidenced by their strong cytotoxic effects on colorectal cancer cells and negligible toxicity towards non-cancerous cells.
Graphical abstract
A feasibility study on the adoption of a generative denoising diffusion model for the synthesis of fundus photographs using a small dataset
Authors: Kim Hong Kyu , Ryu Ik Hee , Choi Joon Yul , Yoo Tae Keun 
Published: April 2024

AbstractThe generative diffusion model has been highlighted as a state-of-the-art artificial intelligence technique for image synthesis. Here, we show that a denoising diffusion probabilistic model (DDPM) can be used for a domain-specific task generating fundus photographs based on a limited training dataset in an unconditional manner. We trained the DDPM based on U-Net backbone architecture, which is the most popular form of the generative diffusion model. After training, serial multiple denoising U-Nets can generate FPs using random noise seeds. A thousand healthy retinal images were used to train the diffusion model. The input image size was set to a pixel resolution of 128 × 128. The trained DDPM successfully generated synthetic fundus photographs with a resolution of 128 × 128 pixels using our small dataset. We failed to train the DDPM for 256-by-256-pixel images due to the limited computation capacity using a personal cloud platform. In a comparative analysis, the progressive growing generative adversarial network (PGGAN) model synthesized more sharpened images than the DDPM in the retinal vessels and optic discs. The PGGAN (Frechet inception distance [FID] score: 41.761) achieved a better FID score than the DDPM (FID score: 65.605). We used a domain-specific generative diffusion model to synthesize fundus photographs based on a relatively small dataset. Because the DDPM has disadvantages with a small dataset, including difficulty in training and low image quality compared with generative adversarial networks such as PGGAN, further studies are needed to improve diffusion models for domain-specific medical tasks with small numbers of samples.
Fejér–Riesz factorization in the QRC-subalgebra and circularity of the quaternionic numerical range
Authors: van der Merwe Alma , van Straaten Madelein , Woerdeman Hugo J. 
Published: April 2024

AbstractWe provide a characterization when the quaternionic numerical range of a matrix is a closed ball with center 0. The proof makes use of Fejér–Riesz factorization of matrix-valued trigonometric polynomials within the algebra of complex matrices associated with quaternion matrices.