bluuebunny/crossref_metadata_2025 huggingface dataset:
The prevalence of grandparental childcare in Europe: a research update
Authors: Zanasi Francesca , Arpino Bruno , Bordone Valeria , Hank Karsten
Published: September 2023

We investigate (a) how the proportion of European grandparents providing childcare changed over a period of 15 years, (b) how these proportions differ by gender and education, and (c) how countries not covered in earlier analyses fit into previously identified regional patterns of grandparental childcare in Europe. Using data from Waves 1, 2, and 8 of the Survey of Health, Ageing and Retirement in Europe (SHARE), our descriptive analysis provides estimates of the prevalence and intensity of grandparental childcare in 26 European countries as well as of the changes therein over time and across socio-demographically defined groups. Overall, the prevalence and intensity of grandparental childcare in Europe has remained fairly stable over time, with minor increases. Proportions of grandparents providing any childcare strongly vary, however, across countries (from 24 to 60%). Grandmothers are generally more likely to provide childcare than grandfathers, while differences based on educational levels are less clear-cut. Central and southeastern Europe, representing the bulk of the ‘new’ countries in the analysis, exhibit patterns of grandparental childcare closely resembling those observed in Mediterranean countries. Our analysis revealed an overall stability over time rather than change in grandparents’ provision of childcare in Europe, with substantial variations across welfare state regimes and within countries when accounting for grandparents’ gender and educational levels. Including countries that had previously been excluded from other studies challenges the ‘narrative’ that has emerged around a negative macrolevel association between the provision of extensive and intensive grandparental childcare.
A synergistic effect of fibrous carboxymethyl cellulose with equine collagen improved the hemostatic properties of freeze-dried wound dressings
Authors: Sedlář M. , Kacvinská K. , Fohlerová Z. , Izsák D. , Chalupová M. , Suchý P. , Dohnalová M. , Sopuch T. , Vojtová L.
Published: September 2023

Bleeding is one of the most commonly occurring injuries; it can be painful and even life-threatening condition. The hemostats are substances that promote blood clotting and fasten hemostasis. In this paper, we evaluated the hemostatic effect of freeze-dried wound dressings based on equine collagen, porcine collagen, fibrous carboxymethyl cellulose (CMC) and their mixtures. The wound dressings were investigated for their morphological structure, chemical structure, absorption properties, in vitro hemostasis, cytotoxicity assay and lastly, for in vivo hemostasis. We have found out that adding fibrous CMC into collagen-based hemostatic wound dressings creates a strong synergistic effect, which significantly improves absorption capacity by almost doubling it, as well as supports clotting time. Based on the in vivo studies on partial nephrectomy in rats, the time needed for achieving hemostasis was significantly lower due to the synergy of collagen and CMC. Our materials were compared to the commonly used hemostatic sealing patch on the market (Tachosil) during the in vivo testing, and sample of a mixture of equine collagen and CMC showed better hemostatic efficacy.

Graphical abstract
Norwegian higher education futures
Authors: Bleiklie Ivar
Published: September 2023

The paper deals with the future of Norwegian higher education as part of a Nordic project on higher education futures. To identify future scenarios for Norwegian higher education (HE), the paper uses the theoretical lens of historical institutionalism to focus on scenario building. Like in the other Nordic countries, Norwegian HE and research are characterized by easily accessible and free public HE provision, high participation rates, and a high level of investment in HE and research. However, the question is this: If we look back at the development of Norwegian HE the last decades, to what extent can we expect present developments to persist and to what extent can we expect more or less sharp breaks and deviations from past and present developments? Departing from an institutionalist position, two historically grounded visions and related scenarios are identified: an academic excellence scenario and a national service scenario. The scenarios reflect tensions between different visions of the shape, emphasis, and orientation of HE and research. The empirical focus is on the developments of HE along five dimensions: growth, systemic integration, academic drift, labor market relevance, and governance. First, the conceptual approach is presented, outlining the use of scenarios and an institutionalist approach to thinking about the future of HE. Secondly, the paper outlines the five trends regarding past and ongoing developments. Third, some ideas about future developments are outlined, before the conclusion is drawn.
SAWIT: A small-sized animal wild image dataset with annotations
Authors: Nguyen Thi Thu Thuy , Eichholtzer Anne C. , Driscoll Don A. , Semianiw Nathan I. , Corva Dean M. , Kouzani Abbas Z. , Nguyen Thanh Thi , Nguyen Duc Thanh
Published: September 2023

Computer vision has found many applications in automatic wildlife data analytics and biodiversity monitoring. Automating tasks like animal recognition or animal detection usually require machine learning models (e.g., deep neural networks) trained on annotated datasets. However, image datasets built for general purposes fail to capture realistic conditions of ecological studies, and existing datasets collected with camera-traps mainly focus on medium to large-sized animals. There is a lack of annotated small-sized animal datasets in the field. Small-sized animals (e.g., small mammals, frogs, lizards, arthropods) play an important role in ecosystems but are difficult to capture on camera-traps. They also present additional challenges: small animals can be more difficult to identify and blend more easily with their surroundings. To fill this gap, we introduce in this paper a new dataset dedicated to ecological studies of small-sized animals, and provide benchmark results of computer vision-based wildlife monitoring. The novelty of our work lies on SAWIT (small-sized animal wild image dataset), the first real-world dataset of small-sized animals, collected from camera traps and in realistic conditions. Our dataset consists of 34,434 images and is annotated by experts in the field with object-level annotations (bounding boxes) providing 34,820 annotated animals for seven animal categories. The dataset encompasses a wide range of challenging scenarios, such as occlusions, blurriness, and instances where animals blend into the dense vegetation. Based on the dataset, we benchmark two prevailing object detection algorithms: Faster RCNN and YOLO, and their variants. Experimental results show that all the variants of YOLO (version 5) perform similarly, ranging from 59.3% to 62.6% for the overall mean Average Precision (mAP) across all the animal categories. Faster RCNN with ResNet50 and HRNet backbone achieve 61.7% mAP and 58.5% mAP respectively. Through experiments, we indicate challenges and suggest research directions for computer vision-based wildlife monitoring. We provide both the dataset and the animal detection code at https://github.com/dtnguyen0304/sawit.
Urokinase-Type Plasminogen Activator Receptor (uPAR) Expression and [64Cu]Cu-DOTA-AE105 uPAR-PET/CT in Patient-Derived Xenograft Models of Oral Squamous Cell Carcinoma
Authors: Lawaetz Mads , Binderup Tina , Christensen Anders , Juhl Karina , Lelkaitis Giedrius , Lykke Eva , Knudsen Line , von Buchwald Christian , Kjaer Andreas
Published: September 2023

Purpose

[64Cu]Cu-DOTA-AE105 urokinase-type plasminogen activator receptor (uPAR)-PET/CT is a novel and promising imaging modality for cancer visualization, although it has not been tested in head and neck cancer patients nor in preclinical models that closely resemble these heterogenous tumors, i.e., patient-derived xenograft (PDX) models. The aim of the present study was to establish and validate oral squamous cell carcinoma (OSCC) PDX models and to evaluate [64Cu]Cu-uPAR-PET/CT for tumor imaging in these models.

Procedures

PDX flank tumor models were established by engrafting tumor tissue from three patients with locally advanced OSCC into immunodeficient mice. [64Cu]Cu-DOTA-AE105 was injected in passage 2 (P2) mice, and [64Cu]Cu-uPAR-PET/CT was performed 1 h and 24 h after injection. After the last PET scan, all animals were euthanized, and tumors dissected for autoradiography and immunohistochemical (IHC) staining.

Results

Three PDX models were established, and all of them showed histological stability and unchanged heterogenicity, uPAR expression, and Ki67 expression through passages. A significant correlation between uPAR expression and tumor growth was found. All tumors of all models (n=29) showed tumor uptake of [64Cu]Cu-DOTA-AE105. There was a clear visual concordance between the distribution of uPAR expression (IHC) and [64Cu]Cu-DOTA-AE105 uptake pattern in tumor tissue (autoradiography). No significant correlation was found between IHC (H-score) and PET-signal (SUVmax) (r=0.34; p=0.07).

Conclusions

OSCC PDX models in early passages histologically mimic donor tumors and could serve as a valuable platform for the development of uPAR-targeted imaging and therapeutic modalities. Furthermore, [64Cu]Cu-uPAR-PET/CT showed target- and tumor-specific uptake in OSCC PDX models demonstrating the diagnostic potential of this modality for OSCC patients.
Associations between environmental heavy metals exposure and preserved ratio impaired spirometry in the U.S. adults
Authors: Chen Chen , Zhang Shunan , Yang Ting , Wang Chen , Han Guiling
Published: September 2023

We examined 9556 individuals aged 18 to 79 years who had information on spirometry testing and heavy metals and used multivariable logistic or linear regression to evaluate associations between serum levels of cadmium, lead, and mercury and PRISm and lung function in U.S. adults, which were conducted first in all participants, and then separately in never/former smokers and current smokers. The overall prevalence of PRISm was 7.02%. High levels of serum cadmium were significantly associated with PRISm in all individuals, no matter in never/former smokers (quartile 4 vs 1, the OR = 2.517, 95% CI = 1.376–4.604, p-trend = 0.0077) and current smokers (quartile 4 vs 1, the OR = 2.201, 95% CI = 1.265–3.830, p-trend = 0.0020). Serum lead and mercury were not significantly correlated with PRISm, regardless of smoking status. Serum cadmium was strongly correlated with lower FEV1/FVC, regardless of smoking status. Besides, serum cadmium was also significantly related to lower FVC % predicted in never/former smokers and lower FEV1% predicted in current smokers. Serum lead was strongly correlated with lower FVC % predicted and FEV1/FVC in all individuals and never/former smokers. And serum mercury was significantly associated with decrements in FVC % predicted in all individuals and current smokers. These findings demonstrate that serum cadmium is associated with a higher risk of PRISm and lower lung function, with the most significant effect on FEV1/FVC in particular. Our results also indicate that exposure to lead and mercury negatively affects lung function in never/former smokers and current smokers, respectively.
Induction of proteasomal activity in mammalian cells by lifespan-extending tRNA synthetase inhibitors
Authors: Mariner Blaise L. , Rodriguez Antonio S. , Heath Olivia C. , McCormick Mark A.
Published: September 2023

We have recently shown that multiple tRNA synthetase inhibitors can greatly increase lifespan in multiple models by acting through the conserved transcription factor ATF4. Here, we show that these compounds, and several others of the same class, can greatly upregulate mammalian ATF4 in cells in vitro, in a dose dependent manner. Further, RNASeq analysis of these cells pointed toward changes in protein turnover. In subsequent experiments here we show that multiple tRNA synthetase inhibitors can greatly upregulate activity of the ubiquitin proteasome system (UPS) in cells in an ATF4-dependent manner. The UPS plays an important role in the turnover of many damaged or dysfunctional proteins in an organism. Increasing UPS activity has been shown to enhance the survival of Huntington’s disease cell models, but there are few known pharmacological enhancers of the UPS. Additionally, we see separate ATF4 dependent upregulation of macroautophagy upon treatment with tRNA synthetase inhibitors. Protein degradation is an essential cellular process linked to many important human diseases of aging such as Alzheimer’s disease and Huntington’s disease. These drugs’ ability to enhance proteostasis more broadly could have wide-ranging implications in the treatment of important age-related neurodegenerative diseases.
Sex differences in biological aging and the association with clinical measures in older adults
Authors: Phyo Aung Zaw Zaw , Fransquet Peter D. , Wrigglesworth Jo , Woods Robyn L. , Espinoza Sara E. , Ryan Joanne
Published: September 2023

Females live longer than males, and there are sex disparities in physical health and disease incidence. However, sex differences in biological aging have not been consistently reported and may differ depending on the measure used. This study aimed to determine the correlations between epigenetic age acceleration (AA), and other markers of biological aging, separately in males and females. We additionally explored the extent to which these AA measures differed according to socioeconomic characteristics, clinical markers, and diseases. Epigenetic clocks (HorvathAge, HannumAge, PhenoAge, GrimAge, GrimAge2, and DunedinPACE) were estimated in blood from 560 relatively healthy Australians aged ≥ 70 years (females, 50.7%) enrolled in the ASPREE study. A system-wide deficit accumulation frailty index (FI) composed of 67 health-related measures was generated. Brain age and subsequently brain-predicted age difference (brain-PAD) were estimated from neuroimaging. Females had significantly reduced AA than males, but higher FI, and there was no difference in brain-PAD. FI had the strongest correlation with DunedinPACE (range r: 0.21 to 0.24 in both sexes). Brain-PAD was not correlated with any biological aging measures. Significant correlations between AA and sociodemographic characteristics and health markers were more commonly found in females (e.g., for DunedinPACE and systolic blood pressure r = 0.2, p < 0.001) than in males. GrimAA and Grim2AA were significantly associated with obesity and depression in females, while in males, hypertension, diabetes, and chronic kidney disease were associated with these clocks, as well as DunedinPACE. Our findings highlight the importance of considering sex differences when investigating the link between biological age and clinical measures.
Learning during a pandemic: an Activity Theory analysis of the challenges experienced by Aotearoa/New Zealand university students
Authors: Gedera Dilani , Forbes Dianne , Brown Cheryl , Hartnett Maggie , Datt Ashwini
Published: September 2023

The worldwide disruption of higher education during the Covid-19 pandemic has been studied from the viewpoints of institutions and teachers, with some attention to students’ health and learning challenges. Attempts to theorise the diverse and conflicting challenges faced by students learning online during the pandemic have been limited. It is helpful to analyse students’ experiences as part of an activity system in order to unravel the system’s elements and determine contradictions that occur. This study adopted a mixed methods approach to investigate students’ online learning experiences at all eight New Zealand universities during the pandemic. Data obtained via a large-scale online survey, followed by focus groups and individual interviews, is presented in light of an Activity Theory framework. Findings show that students’ key challenges were associated with new tools and technologies, lack of interaction and social connection, lack of routine and space, and clashing commitments due to multiple roles and responsibilities. Contradictions can be a driving force for change and development in teaching and learning contexts. We conclude with recommendations for tertiary institutions, teachers, learning designers and students to inform future learning and teaching plans.
Rearrangement Events on Circular Genomes
Authors: Stevenson Joshua , Terauds Venta , Sumner Jeremy
Published: September 2023

Early literature on genome rearrangement modelling views the problem of computing evolutionary distances as an inherently combinatorial one. In particular, attention is given to estimating distances using the minimum number of events required to transform one genome into another. In hindsight, this approach is analogous to early methods for inferring phylogenetic trees from DNA sequences such as maximum parsimony—both are motivated by the principle that the true distance minimises evolutionary change, and both are effective if this principle is a true reflection of reality. Recent literature considers genome rearrangement under statistical models, continuing this parallel with DNA-based methods, with the goal of using model-based methods (for example maximum likelihood techniques) to compute distance estimates that incorporate the large number of rearrangement paths that can transform one genome into another. Crucially, this approach requires one to decide upon a set of feasible rearrangement events and, in this paper, we focus on characterising well-motivated models for signed, uni-chromosomal circular genomes, where the number of regions remains fixed. Since rearrangements are often mathematically described using permutations, we isolate the sets of permutations representing rearrangements that are biologically reasonable in this context, for example inversions and transpositions. We provide precise mathematical expressions for these rearrangements, and then describe them in terms of the set of cuts made in the genome when they are applied. We directly compare cuts to breakpoints, and use this concept to count the distinct rearrangement actions which apply a given number of cuts. Finally, we provide some examples of rearrangement models, and include a discussion of some questions that arise when defining plausible models.
Computed Tomography-derived intratumoral and peritumoral radiomics in predicting EGFR mutation in lung adenocarcinoma
Authors: Shang Youlan , Chen Weidao , Li Ge , Huang Yijie , Wang Yisong , Kui Xiaoyan , Li Ming , Zheng Hairong , Zhao Wei , Liu Jun
Published: September 2023

Objective

To investigate the value of Computed Tomography (CT) radiomics derived from different peritumoral volumes of interest (VOIs) in predicting epidermal growth factor receptor (EGFR) mutation status in lung adenocarcinoma patients.

Materials and methods

A retrospective cohort of 779 patients who had pathologically confirmed lung adenocarcinoma were enrolled. 640 patients were randomly divided into a training set, a validation set, and an internal testing set (3:1:1), and the remaining 139 patients were defined as an external testing set. The intratumoral VOI (VOI_I) was manually delineated on the thin-slice CT images, and seven peritumoral VOIs (VOI_P) were automatically generated with 1, 2, 3, 4, 5, 10, and 15 mm expansion along the VOI_I. 1454 radiomic features were extracted from each VOI. The t-test, the least absolute shrinkage and selection operator (LASSO), and the minimum redundancy maximum relevance (mRMR) algorithm were used for feature selection, followed by the construction of radiomics models (VOI_I model, VOI_P model and combined model). The performance of the models were evaluated by the area under the curve (AUC).

Results

399 patients were classified as EGFR mutant (EGFR+), while 380 were wild-type (EGFR−). In the training and validation sets, internal and external testing sets, VOI4 (intratumoral and peritumoral 4 mm) model achieved the best predictive performance, with AUCs of 0.877, 0.727, and 0.701, respectively, outperforming the VOI_I model (AUCs of 0.728, 0.698, and 0.653, respectively).

Conclusions

Radiomics extracted from peritumoral region can add extra value in predicting EGFR mutation status of lung adenocarcinoma patients, with the optimal peritumoral range of 4 mm.
Endogeneity of marketing variables in multicategory choice models
Authors: Hruschka Harald
Published: September 2023

A regressor is endogenous if it is correlated with the unobserved residual of a model. Ignoring endogeneity may lead to biased coefficients. We deal with the omitted variable bias that arises if firms set marketing variables considering factors (demand shocks) that researchers do not observe. Whereas publications on sales response or brand choice models frequently take the potential endogeneity of marketing variables into account, multicategory choice models provide a different picture. To consider endogeneity in multicategory choice models, we follow a two-step Gaussian copula approach. The first step corresponds to an individual-level random coefficient version of the multivariate logit model. We analyze yearly shopping data for one specific grocery store, referring to 29 product categories. If the assumption of a Gaussian correlation structure is met, the copula approach indicates the endogeneity of a category-specific marketing variable in about 31% of the categories. The majority of marketing variables rated as endogenous are positively correlated with the omitted variable, implying that ignoring endogeneity leads to an overestimation of the coefficients of the respective marketing variable. Finally, we investigate whether taking endogeneity into account by the copula approach leads to different managerial implications. In this regard, we demonstrate that for our data ignoring endogeneity often suggests a level of marketing activity that is too high.
Production of Metallic Tungsten and Tungsten Carbide from Natural Wolframite and Scheelite via Sulfide Chemistry
Authors: Boury Charles , Green Sierra R. , Allanore Antoine
Published: September 2023

The development of sulfide-based chemistry and physical separation in the last decade opens new processes to produce metals at the industrial scale. Herein, a new route to produce metallic tungsten and tungsten carbides particles from natural wolframite (Fe,Mn)WO4 and scheelite CaWO4 is presented. Sulfidation of mineral concentrates breaks the tungstate crystal structure into a mix of sulfides, in particular tungsten disulfide WS2. The thermal instability of WS2 at high temperature allows for its subsequent, selective, thermal reduction to tungsten particles at around 1500 °C. Similar thermal reduction in the presence of carbon result in the production of tungsten carbides, WC and W2C, obtained at around 1250 °C. The other major components of the sulfidized concentrate remain un-reduced under the proposed conditions, demonstrating selective reduction of WS2 as a possible new route for W recovery. Similar findings are reported for the carburization of WS2.
When and how should low acyl gellan gum be added to the protein blends to improve meat analogue texture?
Authors: Dinani Somayeh Taghian , Broekema Nicole Louise , Boom Remko Marcel , van der Goot Atze Jan
Published: September 2023

The addition of hydrocolloids to protein blends may improve the formation of structure of products formed upon heating and shearing, and thus could be valuable in developing better meat analogues. In this study, the effects of adding one particular hydrocolloid, and the use of calcium chloride (CaCl2) as a solidifying agent were evaluated on the macrostructure, microstructure, and the mechanical properties of pea protein isolate (PPI) and wheat gluten blends (WG) (ratio 1:1, 40 wt%), when using shearing and heating as formation process. The addition of low acyl gellan gum was shown to result in better internal structure, such as oriented fibrousness, but only when the low acyl gellan gum was added together with the WG after first allowing hydration of the PPI in a CaCl2 solution. The material was markedly stronger and tougher both parallel and perpendicular to the shearing direction. The influence of the sequence of addition indicates that the interactions between the different components before and during heating and shearing are non-equilibrium and that therefore the preparation procedure of the initial dough is just as important as the composition and the settings of the heating and shearing process itself.
Comparison of the effects of extraction method and solvents on biological activities of phytochemicals from selected violet and blue pigmented flowers
Authors: Żbik Klara , Onopiuk Anna , Szpicer Arkadiusz , Kurek Marcin
Published: September 2023

The flowers of many plant species are characterized by intense color and richness of bioactive compounds. They can be their valuable and curious sources that are worth extracting with the highest possible efficiency. The study compares the effects of different extraction methods and ultrasound (US) treatment on the physicochemical properties of dried petals of Malva sylvestris (MS), Clitoria ternatea (CT), Centaurea cyanus (CC), and Trifolium pratense (TP). The petals were ground and then extracted by three methods: (1) with H2O, (2) with 70% methanol, (3) with 70% methanol + acetic acid solvents, additionally used US. Measured: color parameters in CIEL*a*b* system; total antioxidant activity (TAA) referred to the 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radicals activity; total phenolic content (TPC) by the Folin-Ciocâlteu method; total anthocyanin content (TAC) by the pH differential method. No specific differences in color parameters founded. The highest TAA (in % of DPPH reductive- MS: 87.86; CT: 62.56; CC: 72.04; TP: 82.99), TPC (in mg gallic acid equivalent/100 g of sample- MS: 1072.86; CT: 849.85; CC: 912.07; TP: 873.77), and TAC (in mg of cyanidin-3-glucoside/100 g of sample- MS: 747.79; CT: 226.46; CC: 267.53; TP: 234.77) was reached by method (3). US treatment increased the effect.
Long-Term Results of Laparoscopic Sleeve Gastrectomy: a Review of Studies Reporting 10+ Years Outcomes
Authors: Vitiello Antonio , Abu-Abeid Adam , Dayan Danit , Berardi Giovanna , Musella Mario
Published: September 2023

Laparoscopic sleeve gastrectomy (LSG) is the most commonly performed bariatric procedure worldwide. Systematic search of Pubmed, Cochrane, and Embase was performed in order to find all the articles reporting 10+ years of LSG results. Eleven studies including 1020 patients met the inclusion criteria. Overall weighted mean %TWL was 24.4% (17–36.9%), and remission rates from TD2M to HTN were 45.6% (0–94.7%) and 41.4% (0–78.4%), respectively. De novo GERD had an overall prevalence of 32.3% (21.4–58.4%), and five cases (0.5%) of Barrett’s disease were reported. Revisional surgery was required for 19.2% (1–49.5%) of patients, Roux-en-Y gastric bypass being the most common secondary procedure.
A Multi-Yield-Surface Plasticity State-Based Peridynamics Model and its Applications to Simulations of Ice-Structure Interactions
Authors: Song Ying , Zhang Luwen , Li Shaofan , Li Yunbo
Published: September 2023

Due to complex mesoscopic and the distinct macroscopic evolution characteristics of ice, especially for its brittle-to-ductile transition in dynamic response, it is still a challenging task to build an accurate ice constitutive model to predict ice loads during ship-ice collision. To address this, we incorporate the conventional multi-yield-surface plasticity model with the state-based peridynamics to simulate the stress and crack formation of ice under impact. Additionally, we take into account of the effects of inhomogeneous temperature distribution, strain rate, and pressure sensitivity. By doing so, we can successfully predict material failure of isotropic freshwater ice,iceberg ice, and columnar saline ice. Particularly, the proposed ice constitutive model is validated through several benchmark tests, and proved its applicability to model ice fragmentation under impacts, including drop tower tests and ballistic problems. Our results show that the proposed approach provides good computational performance to simulate ship-ice collision.
Scale Effect of a Kappel Tip-Rake Propeller
Authors: Chen Chen-Wei , Chen Xupeng , Zhou Zhaoye , Chen Liwan
Published: September 2023

In this paper, the scale effect of Kappel tip-rake propellers with different end plate designs was studied using computational fluid dynamics. Given the base size of the mesh and the appropriate numerical model for the determined simulation, the open-water performance of three Kappel propellers with different bending degrees of the end plate at different scales was calculated. Comparing the scale effect of these propellers, the scale effect of the torque coefficient of a Kappel propeller is more intense than that of the conventional propeller. In addition, the scale effect of the torque coefficient is strong when the bending degree of the end plate increases, dwarfing the scale effect on the thrust coefficient. Following the research on the scale effect of the wake field for the Kappel propeller, the laws that reveal the influence of the scale on the wake field were summarized; that is, the high-speed zone in the wake relatively expands with the increase of the scale in company with a trend of tip cross flow. The research reveals the basic variation trend and rule of the open-water performance and wake distribution for the Kappel propeller under different scales within the Reynolds number range of 4.665×105−8.666×107 considering γ transition, as well as the characteristic differences between the Kappel propellers with different end plate designs, which will be of great significance to its optimization design and application to marine vehicles of different scales.
Low-cost fabrication and physicochemical characterization of ZnFe2O4 nanoparticles as an efficient multifunctional inorganic pigment
Authors: Sayed Mostafa A. , Abdelmaksoud W. M. A. , Teleb Said M. , El-Din Adel M. , Abo-Aly Mohamed M.
Published: September 2023

The pursuit of low-cost manufacturing of newly effective pigments is a pressing economic need. Thus, in this work, low-cost ZnFe2O4 spinel nanoparticles (ZF-NPs) with an average diameter of 20 nm were successfully synthesized using a simple sol–gel method, which can be extended for large-scale fabrication of a reddish nano pigment. TGA/DTA, XRD, DRS, HRTEM, and SEM/EDX investigations were used to characterize the as-prepared product. The color of synthesized NPs was studied using CIE L*a*b* colorimetric method with color coordinates of L* = 41.7, a* = 72.2, and b* = 48.8. The newly developed pigment was examined to be superior to the traditional pigment (M6001/Fe2O3: L* = 30.4, a* = 42.16, and b* = 45.7). After that, the synthesized nano pigment was integrated into both ink and paint formulations as a multifunctional coating. The inclusion of synthesized nano pigment in metal coating printing ink formulation was done to produce a good alternative and cost-effective substitute for the commercially available pigment used in the inks industry. Also, the effect of the fabricated nanoparticles on corrosion resistance and thermal stability of epoxy-based paint formulations was evaluated using different standard tests. Therefore, the ZnFe2O4 pigment should be applied as a highly efficient inorganic nano pigment.
Automated volumetric assessment of pituitary adenoma
Authors: Da Mutten Raffaele , Zanier Olivier , Ciobanu-Caraus Olga , Voglis Stefanos , Hugelshofer Michael , Pangalu Athina , Regli Luca , Serra Carlo , Staartjes Victor E.
Published: September 2023

Purpose

Assessment of pituitary adenoma (PA) volume and extent of resection (EOR) through manual segmentation is time-consuming and likely suffers from poor interrater agreement, especially postoperatively. Automated tumor segmentation and volumetry by use of deep learning techniques may provide more objective and quick volumetry.

Methods

We developed an automated volumetry pipeline for pituitary adenoma. Preoperative and three-month postoperative T1-weighted, contrast-enhanced magnetic resonance imaging (MRI) with manual segmentations were used for model training. After adequate preprocessing, an ensemble of convolutional neural networks (CNNs) was trained and validated for preoperative and postoperative automated segmentation of tumor tissue. Generalization was evaluated on a separate holdout set.

Results

In total, 193 image sets were used for training and 20 were held out for validation. At validation using the holdout set, our models (preoperative / postoperative) demonstrated a median Dice score of 0.71 (0.27) / 0 (0), a mean Jaccard score of 0.53 ± 0.21/0.030 ± 0.085 and a mean 95th percentile Hausdorff distance of 3.89 ± 1.96./12.199 ± 6.684. Pearson’s correlation coefficient for volume correlation was 0.85 / 0.22 and −0.14 for extent of resection. Gross total resection was detected with a sensitivity of 66.67% and specificity of 36.36%.

Conclusions

Our volumetry pipeline demonstrated its ability to accurately segment pituitary adenomas. This is highly valuable for lesion detection and evaluation of progression of pituitary incidentalomas. Postoperatively, however, objective and precise detection of residual tumor remains less successful. Larger datasets, more diverse data, and more elaborate modeling could potentially improve performance.
On increasing the contribution of locally produced fresh foods to school meals in the Caribbean
Authors: Fair Oacia , Hickey Gordon M. , Ville Arlette Saint , Phillip Leroy E.
Published: September 2023

The rising prevalence of childhood overweight and obesity within the Caribbean is a major public health and policy concern because obese children are at risk of developing non-communicable diseases (NCDs) later in life. Throughout the Caribbean Community (CARICOM), children are consuming unhealthy diets, characterized by energy-dense, processed and ultra-processed foods, sugar sweetened beverages, and limited quantities of fruits and vegetables. Community-based school meal programmes (SMPs) have been identified as useful vehicles to address unhealthy eating among children, and “farm-to-school” approaches have the potential to increase the availability of locally grown nutritious produce, while supporting local agriculture and reducing the region’s reliance on food imports. This paper seeks to better understand the barriers to enhancing community-based school feeding value-chains in the CARICOM, by focusing on the Eastern Caribbean Island of Nevis where there is an interest in developing farm-to-school value chains. Using key informant interviews combined with focus groups with actors along the local food value chain, we identify the following barriers to an effective community-based SMP: a lack of communication and an absence of contractual agreements between local farmers and the SMP administration; generally low levels of child acceptance of school meals containing fresh vegetables; and limited intersectoral coordination and collaboration among SMP stakeholders and local farmers. Using social network analysis, we further discuss limitations in group organization and coordination among local farmers and opportunities for SMP improvement. The results point to the need for more integrative public policy development and greater community engagement to coordinate and strengthen the farm-to school approach to school feeding.
Text mining of veterinary forums for epidemiological surveillance supplementation
Authors: Munaf Samuel , Swingler Kevin , Brülisauer Franz , O’Hare Anthony , Gunn George , Reeves Aaron
Published: September 2023

Web scraping and text mining are popular computer science methods deployed by public health researchers to augment traditional epidemiological surveillance. However, within veterinary disease surveillance, such techniques are still in the early stages of development and have not yet been fully utilised. This study presents an exploration into the utility of incorporating internet-based data to better understand smallholder farming communities within the UK, by using online text extraction and the subsequent mining of this data. Web scraping of the livestock fora was conducted, with text mining and topic modelling of data in search of common themes, words, and topics found within the text, in addition to temporal analysis through anomaly detection. Results revealed that some of the key areas in pig forum discussions included identification, age management, containment, and breeding and weaning practices. In discussions about poultry farming, a preference for free-range practices was expressed, along with a focus on feeding practices and addressing red mite infestations. Temporal topic modelling revealed an increase in conversations around pig containment and care, as well as poultry equipment maintenance. Moreover, anomaly detection was discovered to be particularly effective for tracking unusual spikes in forum activity, which may suggest new concerns or trends. Internet data can be a very effective tool in aiding traditional veterinary surveillance methods, but the requirement for human validation of said data is crucial. This opens avenues of research via the incorporation of other dynamic social media data, namely Twitter, in addition to location analysis to highlight spatial patterns.
Selecting an appropriate machine-learning model for perovskite solar cell datasets
Authors: Salah Mohamed M. , Ismail Zahraa , Abdellatif Sameh
Published: September 2023

Utilizing artificial intelligent based algorithms in solving engineering problems is widely spread nowadays. Herein, this study provides a comprehensive and insightful analysis of the application of machine learning (ML) models to complex datasets in the field of solar cell power conversion efficiency (PCE). Mainly, perovskite solar cells generate three datasets, varying dataset size and complexity. Various popular regression models and hyperparameter tuning techniques are studied to guide researchers and practitioners looking to leverage machine learning methods for their data-driven projects. Specifically, four ML models were investigated; random forest (RF), gradient boosting (GBR), K-nearest neighbors (KNN), and linear regression (LR), while monitoring the ML model accuracy, complexity, computational cost, and time as evaluating parameters. Inputs' importance and contribution were examined for the three datasets, recording a dominating effect for the electron transport layer's (ETL) doping as the main controlling parameter in tuning the cell's overall PCE. For the first dataset, ETL doping recorded 93.6%, as the main contributor to the cell PCE, reducing to 79.0% in the third dataset.
Evaluation of the antibacterial activity of cinnamon essential oil and its individual compounds on Aggregatibacter actinomycetemcomitans isolated from black extrinsic tooth stain: an in vitro study
Authors: Lotfy W. A. , Matar M. A. , Alkersh B. M.
Published: September 2023

Aim

Black extrinsic tooth stain (BETS) is a health challenge that commonly affects children. Aggregatibacter actinomycetemcomitans (Aa) presents in higher prevalence within the polymicrobial community of BETS. In this study, the anti-planktonic and anti-sessile activities of cinnamon essential oil (CEO) and its individual compounds against Aa were evaluated. The preventive effect of CEO and its active substances on BETS formation was also studied in vitro.

Methods

Aa was isolated from a preschool child with BETS and was identified based on the morphological characteristics, MALDI-TOF mass spectroscopy and 16S rRNA sequencing. The effect of CEO and its individual compounds on the growth kinetics of planktonic and sessile Aa cells as well as their antibacterial efficacy and their rate of bacterial killing were examined. The preventive effect of CEO and its active substances on the formation of BETS was evaluated using an ex vivo model. The data were analysed using one-way analysis of variance (ANOVA) and the significance level was set at p < 0.05.

Results

Out of eight individual compounds of CEO, only eugenol, cinnamaldehyde and α-methyl cinnamaldehyde showed anti-Aa activities. The values of the minimum inhibitory concentrations (MICs) were in the following order: CEO (421.5 mg/ml) > α-methyl cinnamaldehyde (26.37 mg/ml) > cinnamaldehyde (0.209 mg/ml) > eugenol (0.052 mg/ml). CEO, eugenol, cinnamaldehyde and α-methyl cinnamaldehyde, respectively, exhibited two-, four-, four- and eightfold increase of sessile MIC compared to their planktonic MIC. The growth kinetics of both planktonic and sessile Aa in the presence of CEO, eugenol, cinnamaldehyde and α-methyl cinnamaldehyde revealed a complete inhibition at the MICs and 5.3%–37.4% biofilm inhibition at sub-MICs. The time-killing study demonstrated that CEO, eugenol and cinnamaldehyde were capable of reducing the survival rate of both planktonic and sessile Aa cells after 15–20 and 25–30 min, respectively. However, α-methyl cinnamaldehyde showed a superior anti-planktonic to anti-biofilm activity. The daily incorporation of CEO, eugenol and cinnamaldehyde at their MICs for 14 days totally prevented the formation of BETS in the ex vivo model; however, in the case of α-methyl cinnamaldehyde, BETS was visually detectable after 10 days.

Conclusion

CEO and its individual compounds have marked antibacterial activity against Aa. The effective results against planktonic and sessile Aa within reasonable time indicate that they can be used to prevent BETS.
Link prediction for ex ante influence maximization on temporal networks
Authors: Yanchenko Eric , Murata Tsuyoshi , Holme Petter
Published: September 2023

Influence maximization (IM) is the task of finding the most important nodes in order to maximize the spread of influence or information on a network. This task is typically studied on static or temporal networks where the complete topology of the graph is known. In practice, however, the seed nodes must be selected before observing the future evolution of the network. In this work, we consider this realistic ex ante setting where p time steps of the network have been observed before selecting the seed nodes. Then the influence is calculated after the network continues to evolve for a total of $$T>p$$

T
>
p

time steps. We address this problem by using statistical, non-negative matrix factorization and graph neural networks link prediction algorithms to predict the future evolution of the network, and then apply existing influence maximization algorithms on the predicted networks. Additionally, the output of the link prediction methods can be used to construct novel IM algorithms. We apply the proposed methods to eight real-world and synthetic networks to compare their performance using the susceptible-infected (SI) diffusion model. We demonstrate that it is possible to construct quality seed sets in the ex ante setting as we achieve influence spread within 87% of the optimal spread on seven of eight network. In many settings, choosing seed nodes based only historical edges provides results comparable to the results treating the future graph snapshots as known. The proposed heuristics based on the link prediction model are also some of the best-performing methods. These findings indicate that, for these eight networks under the SI model, the latent process which determines the most influential nodes may not have large temporal variation. Thus, knowing the future status of the network is not necessary to obtain good results for ex ante IM.
The politics of decolonising the curriculum through adopting mother tongue instruction in a South African historically disadvantaged university setting
Authors: Nyoni Phefumula
Published: September 2023

This paper focuses on the dynamics of decolonising the curriculum by adopting mother tongue language as a medium for instruction in South African universities. There has been growing criticism on the slow pace of decoloniality within university spaces amid mounting challenges of lack of development in society. The paper speaks to the experiences of historically disadvantaged universities regarding adopting mother tongue instruction, especially considering the complexities and contradictions posed by institutional culture and epistemological traditions. The paper presents insights into how a decolonial perspective can assist in ridding African universities of epistemological and pedagogical practices that hinder decolonial efforts and broader societal development. The paper focuses on the synergies between mother tongue instruction and curriculum transformation in light of the contradictions associated with the use of the mother tongue that could enhance students’ epistemic access and success. It thus presents opportunities and controversies surrounding the introduction of the language policy, especially among historically disadvantaged universities. A Kaupapa Māori approach philosophical lens of reimagination evoked during the 1980s revolution becomes a central theoretical framework. It helps understand how indigenous philosophies can be essential in decolonising African knowledge and epistemological traditions. In this regard, the paper concludes that applying the Kaupapa Māori approach—and in particular, the principle of reimagination on the curriculum transformation in African universities (especially the formerly disadvantaged ones)—can propel a decolonial drive. The paper resulted from experiential knowledge and observations, informal interviews targeting students and scholars and empirical evidence from previous studies.
Deep-learning for automated markerless tracking of infants general movements
Authors: Abbasi H. , Mollet S. R. , Williams S. A. , Lim L. , Battin M. R. , Besier T. F. , McMorland A. J. C.
Published: September 2023

The presence of abnormal infant General Movements (GMs) is a strong predictor of progressive neurodevelopmental disorders, including cerebral palsy (CP). Automation of the assessment will overcome scalability barriers that limit its delivery to at-risk individuals. Here, we report a robust markerless pose-estimation scheme, based on advanced deep-learning technology, to track infant movements in consumer mobile device video recordings. Two deep neural network models, namely Efficientnet-b6 and resnet-152, were trained on manually annotated data across twelve anatomical locations (3 per limb) in 12 videos from 6 full-term infants (mean age = 17.33 (SD 2.9) wks, 4 male, 2 female), using the DeepLabCut™ framework. K-fold cross-validation indicates the generalization capability of the deep-nets for GM tracking on out-of-domain data with an overall performance of 95.52% (SD 2.43) from the best performing model (Efficientnet-b6) across all infants (performance range: 84.32–99.24% across all anatomical locations). The paper further introduces an automatic, unsupervised strategy for performance evaluation on extensive out-of-domain recordings through a fusion of likelihoods from a Kalman filter and the deep-net. Findings indicate the possibility of establishing an automated GM tracking platform, as a suitable alternative to, or support for, the current observational protocols for early diagnosis of neurodevelopmental disorders in early infancy.