bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neuroinflammation and neurodegeneration following traumatic brain injuries
Authors: Boulton Matthew , Al-Rubaie Ali 
Published: May 2024

Abstract
Traumatic brain injuries (TBI) commonly occur following head trauma. TBI may result in short- and long-term complications which may lead to neurodegenerative consequences, including cognitive impairment post-TBI. When investigating the neurodegeneration following TBI, studies have highlighted the role reactive astrocytes have in the neuroinflammation and degeneration process. This review showcases a variety of markers that show reactive astrocyte presence under pathological conditions, including glial fibrillary acidic protein (GFAP), Crystallin Alpha-B (CRYA-B), Complement Component 3 (C3) and S100A10. Astrocyte activation may lead to white-matter inflammation, expressed as white-matter hyperintensities. Other white-matter changes in the brain following TBI include increased cortical thickness in the white matter. This review addresses the gaps in the literature regarding post-mortem human studies focussing on reactive astrocytes, alongside the potential uses of these proteins as markers in the future studies that investigate the proportions of astrocytes in the post-TBI brain has been discussed. This research may benefit future studies that focus on the role reactive astrocytes play in the post-TBI brain and may assist clinicians in managing patients who have suffered TBI.
An in-depth analysis of the hydrodynamic behaviour of a high-rate lamellar DAF tank by means of CFD simulations
Authors: Hlukhov Dmytro , Larraona Gorka S. , Rivas Alejandro , Ramos Juan Carlos 
Published: May 2024

AbstractThis research is based on computational fluid dynamics simulations of water and microbubble flow within the tank of a lamellar DAF (L-DAF) clarification system operating under high-rate DAF conditions (12–30 m/h). Firstly, performance of the DAF tank with lamellae was evaluated under two operating conditions in which the flow was either short-circuited or stratified in the absence of lamellae. In addition, the improvement in bubble removal efficiency achieved by the incorporation of lamellae in each scenario was assessed. Secondly, an in-depth analysis was conducted of the flow that develops in the separation zone as a result of placing the lamella pack in that part of the tank. The significant density difference that the lamellae cause to exist between the bubble blanket and clarified water below is responsible for the complex three-dimensional flow observed between the two regions. Analysis of this flow showed a previously undescribed mechanism in which the density gradient plays a crucial role in preventing bubbles from passing through the lamellae and ultimately escaping with the effluent. Finally, the effect of hydraulic loading on the bubble removal efficiency of the L-DAF tank under consideration was researched, and it was found that an L-DAF with a height/length ratio of 0.72 is able to operate at hydraulic loading close to 30 m/h, evidencing good debubbling performance.
Water in nigella oil microemulsion for enhanced oral bioavailability of linagliptin
Authors: Eid Rania K. , Arafa Mona F. , El Maghraby Gamal M. 
Published: May 2024

AbstractLinagliptin is hydrophilic antidiabetic with poor oral bioavailability due to poor permeability and pre-systemic metabolism. The objective was to assess w/o microemulsion for enhanced oral bioavailability of linagliptin. Nigella oil was used as oily phase based on its reported antidiabetic effect. Isopropyl myristate (IPM) or capryol were combined with nigella oil to impart intestinal membrane permeabilizing abilities. Pseudoternary phase diagrams were constructed utilizing nigella oil in presence and absence of isopropyl myristate or capryol as oily phase using Tween 60 as surfactant. W/O microemulsion formulations were selected from the constructed phase diagrams and linagliptin was loaded in the internal aqueous phase at a concentration of 0.5 mg/ml. The prepared formulations were physically evaluated and linagliptin in vitro release was monitored. Eventually, the in vivo hypoglycemic effect was assessed using diabetic rats. The developed microemulsions were of w/o type and exhibited Newtonian flow behavior with nigella/capryol microemulsion recording the lowest viscosity. The recorded droplet size values were 104.9, 121.2 and 86.4 nm for nigella, nigella/IPM and nigella/capryol microemulsions, respectively. All microemulsion formulations showed slower drug release rate compared with aqueous suspension with nigella/capryol microemulsion showing the highest release rate compared to other microemulsions. Release data from microemulsion best fitted to Higuchi model. In vivo oral hypoglycemic activity measurement reflected a more intensified hypoglycemic effect with rapid onset after oral ingestion of microemulsion compared to linagliptin dispersion. Nigella oil/IPM-based microemulsion was ranked as the most effective. The investigation highlighted the feasibility of w/o microemulsion for enhanced oral bioavailability of hydrophilic drugs like linagliptin.
Graphical abstract
Modelling the Response of Timber Beams Under Fire
Authors: Khelifa Mourad , Thi Van Diem , Oudjène Marc , Khennane Amar , El Ganaoui Mohammed , Rogaume Yann 
Published: May 2024

AbstractA fundamental requirement for analysing timber structures under fire is to consider the degradation of material properties with temperature. Therefore, the objective of this study is to propose a model that accounts for the variation of the thermo-physical properties, the development of char, and its evolution with temperature. This model integrates a sequential coupling of heat transfer analysis with structural response. The degradation of the material properties is accounted for through the regulatory approach recommended in Eurocode 5. The stress analysis employs an elasto-plastic model with nonlinear isotropic hardening. Implementation of the model is achieved within the Abaqus suite of finite element software using external subroutines. The model's predictions align well with experimental data, accurately reproducing both thermal and structural responses. Specifically, the model accurately predicts temperature profiles, displacements, and the depth of the charred layer, which initiates above 300 °C. Additionally, for rectangular sections, it was observed that exposure of all faces to fire results in a non-rectangular residual section. Furthermore, employing the temperature-dependent thermal property curves suggested by EC5 yields satisfactory results when predicting the fire resistance of softwood timber structures.
Investigating the influence of clustering techniques and parameters on a hybrid PSO-driven ANFIS model for electricity prediction
Authors: Oladipo Stephen , Sun Yanxia , Amole Abraham Olatide 
Published: May 2024

AbstractThe availability of reliable electrical power, which is essential for a comfortable lifestyle worldwide, requires realistic power usage projections for electric utilities and policymakers, leading to the adoption of machine learning-based modelling tools due to the limitations of traditional power usage projection approaches. However, successful modeling of power usage in neuro-fuzzy models depends on the optimal selection of hyper-parameters. Consequently, this research looked at the major impact clustering methods and hyper-parameter modifications on a particle swarm optimization (PSO)-based adaptive neuro-fuzzy inference system (ANFIS) model. The study examined two distinct clustering methods and other key hyperparameters such as the number of clusters and cluster radius, resulting in a total of 10 sub-models. The performance of the developed models was assessed using four widely recognized performance indicators: root mean square error, mean absolute percentage error (MAPE), mean absolute error (MAE), and coefficient of variation of the root mean square error (CVRMSE). Additionally, the robustness of the optimal sub-model was evaluated by comparing it with other hybrid models based on three different PSO variants. The results revealed that the combination of the ANFIS approach and PSO, specifically with two clusters, yielded the most accurate forecasting scheme with the optimal values for MAPE (7.7778%), MAE (712.6094), CVRMSE (9.5464), and RMSE (909.4998).
Self-Adaptive Incremental PCA-Based DBSCAN of Acoustic Features for Anomalous Sound Detection
Authors: Tan Xiao , Yiu Siu Ming 
Published: May 2024

AbstractIn modern industry, maintaining continuous machine operations is important for improving production efficiency and reducing costs. Therefore, the smart technology of acoustic monitoring to detect anomalous machine conditions earlier before breakdowns works as part of predictive maintenance and is applied not only in industry fault detection but also in safety monitoring and surveillance systems. This paper proposes a self-adaptive unsupervised machine learning algorithm with dimension-reduction technology to detect anomalous sounds after extracting acoustic machine features. Technically, the automatic EPS calculation algorithm-based genetic algorithm optimizes the automatic clustering algorithm’s configuration for incremental principal component analysis and density-based spatial clustering algorithms with noise. IPCA is enhanced by the sequential Karhunen–Loeve (SKL) algorithm, and the condensation algorithm works as the second layer of the algorithm to reduce the number of effective components. This architecture could select an optimized set of parameters based on different test environments and keeps performance quality with fewer computational requirements. In the experiments, 228 sets of normal sounds and 100 sets of anomaly sounds are used. The sound files are collected from the same machine type (stepper motors) at a real plant site. We compare the proposed algorithm with K-means++, one-class SVM, agglomerative clustering, DCGAN and DCNN-Autoencoder, and this new algorithm performs best, with an AUC of 0.84 and the shortest execution time. The algorithm is generic and can be applied to detect anomalies in machines to provide early warning to people to avoid serious accidents or disasters.
Exploring the key factors influencing the actual usage of digital tax platforms
Authors: Abu-Silake Samar Abdallah , Alshurafat Hashem , Alaqrabawi Merwiey , Shehadeh Maha 
Published: May 2024

AbstractIn this groundbreaking study, we explore the behavioral determinants critical to the acceptance and effective utilization of Jordan's digital tax platform among taxpayers. Utilizing an unprecedented combination of frameworks from the Technology Acceptance Model (TAM), Social Capital Theory (SCT), and Theory of Reasoned Action (TRA), this study pioneers a unique integrated approach. Data gathered through questionnaires across Jordan's multiple governorates lay the groundwork for this analysis. Employing the sophisticated Partial Least Squares Structural Equation Modeling (PLS-SEM) within SPSS, our results uncover the profound impact of both social factors (trust, subjective norms) and technological attributes (perceived ease, utility), as conceptualized in TAM, SCT, and TRA. This research is distinct in its focus on Jordan, providing new insights into the nexus of tax compliance and technology adoption, a relatively uncharted area in existing literature.
Fly into the light: eliminating Drosophila melanogaster with chlorophyllin-based Photodynamic Inactivation
Authors: Fellner Andreas , Bresgen Nikolaus , Fefer Michael , Liu Jun , Plaetzer Kristjan 
Published: May 2024

AbstractFruit flies spoil crops in agricultural settings. As conventional pesticides may generate negative off-target effects on humans or the environment, existing treatment methods need eco-friendly and safe alternatives. Photodynamic Inactivation (PDI) is based on the photosensitizer-mediated and light-induced overproduction of reactive oxygen species in targets. We here explore the potential of PDI for the control of fruit fly pests. Drosophila melanogaster serves as well-established model organism in this study. Two distinct experimental approaches are presented: the feed assay, in which fruit flies are provided with sodium magnesium chlorophyllin (Chl, approved as food additive E140) along with sucrose (3%) as their food, and the spray assay, where the photosensitizer is sprayed onto the insects. We show that PDI based on Chl can induce moribundity rates of Drosophila melanogaster of more than 99% with 5 mM Chl and LED illumination (395 nm, 8 h incubation in the dark, radiant exposure 78.9 J/cm2) with the feed assay. If the radiant exposure is doubled to 157.8 J/cm2, 88% of insects are killed by PDI based on 1 mM Chl. The photoactive compound is also effective if presented on strawberries without addition of sucrose with somewhat lower moribundity (71% at 5 mM Chl). Spraying Chl onto insects is less effective than feeding the photosensitizer: 5 mM Chl resulted in 79.5% moribundity (drug to light interval 8 h, radiant exposure 78.9 J/cm2), but if 5 h of sun light (532 J/cm2) and overnight (14 h) dark incubation is used for activation of Chl, more than 95% of insects are killed. As conclusion, Chl serves as effective photoinsecticide against Drosophila melanogaster if a drug to light interval of 8 h is maintained. Feeding the photoactive compound together with sucrose is more effective than spraying it onto insects and increasing the radiant exposure allows for lowering the photosensitizer concentration. Photodynamic Inactivation might therefore represent an eco-friendly addition to the farmers armamentarium against (semi-transparent) insects.
Graphical abstract
Efficacy of herbal extracts in the management of cactus pest, Dactylopius opuntiae (Hemiptera: Dactylopiidae) in Tigray Region, Ethiopia
Authors: Zeweld Sisay Weldegebriel , Ayimut Kiros Meles , Hiben Mebrahtom Gebrelibanos 
Published: May 2024

AbstractCactus (Opuntia ficus-indica) is a drought-resistant plant and the source of food and income for many farmers during the rainy season, and the only option to feed livestock during the dry seasons, especially in the southern part of the Tigray region of Ethiopia. The region is currently suffering from a damaging parasitoid of cactus called Dactylopius opuntiae- ficus biotype. An experimental study was conducted from August 2022 to February 2023 to investigate the efficacy of herbal extracts against cochineal insects. The experiment was conducted on the insecticidal property of methanol extracts of Solanum linnaenum, Euphorbia tirucalli, Nerium oleander, Tephrosia vogelii, Calpurnia aurea, Argemone Mexicana, Datura stramonium and Ricinus communis. Herbs were extracted, and their efficacy and LC50 were determined. Phytochemical screening for secondary metabolites was performed. There was a statistically significant difference in the mean mortality of insects across the levels of the herbs (F (8, 71) = 57.812, p = 0.0001, ƞ2 = 0.867) and the experimental extract concentrations (F (1, 71) = 4198.3, p = 0.0001, ƞ2 = 0.983). The individual extracts of S. linnaenum and N. oleander caused average mortality rates of 99.3% and 97.4%, respectively, at 5% extract concentration. Tannins and saponins were the major metabolites found in the extracts. The present study demonstrated the promising insecticidal efficacy of herbal extracts against the damaging cacti pest D. opuntia-ficus biotype, providing insights into sustainable pest control strategies for protecting vital cactus resources in the Tigray region.
Anchoring Sovereignty in Space: Documenting Places of Wichita Community Building in the Twentieth Century
Authors: Bethke Brandi , Trabert Sarah , McAdams Gary 
Published: May 2024

AbstractThe Wichita and Affiliated Tribes have a long history of occupation in what is now known as Oklahoma. This includes evidence of habitations along Camp Creek and Sugar Creek near Anadarko in Caddo County. Here Wichita peoples camped, built grass houses and arbors, and held social gatherings leading up to and following the passing of the General Allotment Act in 1887. After allotment, communal camp and dance grounds were especially important focal points for community building. These places, such as the ichaskhah camp and dance ground discussed in this article, are critical to understanding the multigenerational connections between ancestral and living Wichita peoples. This history is also important to the community today. However, archaeological research of the Allotment period is exceptionally rare in this region. By using collaborative and Indigenous archaeological methodologies, this work documents the complexities of these places, challenging traditional assumptions of allotment-era cultural loss and assimilation.
Overcoming intergovernmental data sharing challenges with federated learning
Authors: Sprenkamp Kilian , Delgado Fernández Joaquín , Eckhardt Sven , Zavolokina Liudmila 
Published: May 2024

Abstract
Intergovernmental collaboration is needed to address global problems. Modern solutions to these problems often include data-driven methods like artificial intelligence (AI), which require large amounts of data to perform well. As AI emerges as a central catalyst in deriving effective solutions for global problems, the infrastructure that supports its data needs becomes crucial. However, data sharing between governments is often constrained due to socio-technical barriers such as concerns over data privacy, data sovereignty issues, and the risks of information misuse. Federated learning (FL) presents a promising solution as a decentralized AI methodology, enabling the use of data from multiple silos without necessitating central aggregation. Instead of sharing raw data, governments can build their own models and just share the model parameters with a central server aggregating all parameters, resulting in a superior overall model. By conducting a structured literature review, we show how major intergovernmental data-sharing challenges listed by the Organisation for Economic Co-operation and Development can be overcome by utilizing FL. Furthermore, we provide a tangible resource implementing FL linked to the Ukrainian refugee crisis that can be utilized by researchers and policymakers alike who want to implement FL in cases where data cannot be shared. Enhanced AI while maintaining privacy through FL thus allows governments to collaboratively address global problems, positively impacting governments and citizens.
Rao-Blackwellized particle smoothing for simultaneous localization and mapping
Authors: Kok Manon , Solin Arno , Schön Thomas B. 
Published: May 2024

AbstractSimultaneous localization and mapping (SLAM) is the task of building a map representation of an unknown environment while at the same time using it for positioning. A probabilistic interpretation of the SLAM task allows for incorporating prior knowledge and for operation under uncertainty. Contrary to the common practice of computing point estimates of the system states, we capture the full posterior density through approximate Bayesian inference. This dynamic learning task falls under state estimation, where the state-of-the-art is in sequential Monte Carlo methods that tackle the forward filtering problem. In this paper, we introduce a framework for probabilistic SLAM using particle smoothing that does not only incorporate observed data in current state estimates, but it also backtracks the updated knowledge to correct for past drift and ambiguities in both the map and in the states. Our solution can efficiently handle both dense and sparse map representations by Rao-Blackwellization of conditionally linear and conditionally linearized models. We show through simulations and real-world experiments how the principles apply to radio (Bluetooth low-energy/Wi-Fi), magnetic field, and visual SLAM. The proposed solution is general, efficient, and works well under confounding noise.
ON HOMOMORPHISM GRAPHS
Authors: Brandt Sebastian , Chang Yi-Jun , Grebík Jan , Grunau Christoph , Rozhoň Václav , Vidnyánszky Zoltán 
Published: May 2024

Abstract
We introduce new types of examples of bounded degree acyclic Borel graphs and study their combinatorial properties in the context of descriptive combinatorics, using a generalization of the determinacy method of Marks [Mar16]. The motivation for the construction comes from the adaptation of this method to the

$\mathsf {LOCAL}$

model of distributed computing [BCG+21]. Our approach unifies the previous results in the area, as well as produces new ones. In particular, strengthening the main result of [TV21], we show that for

$\Delta>2$

, it is impossible to give a simple characterization of acyclic

$\Delta $

-regular Borel graphs with Borel chromatic number at most

$\Delta $

: such graphs form a

$\mathbf {\Sigma }^1_2$

-complete set. This implies a strong failure of Brooks-like theorems in the Borel context.
Follow the Giver: Is Chinese MNEs’ Investment in Africa Linked to Official Aid?
Authors: Chen Xuanjin , Ghorbani Majid , Xie Zhenzhen 
Published: May 2024

AbstractDoes Chinese aid to African countries trigger Chinese foreign direct investment? Bridging the literature on the impact of foreign aid on foreign direct investment (FDI) and that on state ownership, we consider FDI by China's state-owned enterprises (SOEs) compared with that of its privately owned enterprises (POEs) and find FDI by the former is more likely to follow Chinese governmental aid to Africa. Borrowing from institutional theory, we posit that FDI by SOEs follows political imperatives while FDI by POEs pursues market motives. Using data from multiple sources on 3,760 Chinese FDI projects in Africa between 2001 and 2015, we find a correlation between SOE FDI and government aid than that of POEs; that aid has a greater impact on the probability of FDI when the policies of the host country and those of China are in sync, especially in the case of SOEs; and that in low-investment-risk countries the link between aid and investment is weakened, especially in the case of POEs. The results are robust and consistent across different measures and analyses. We contribute to the literature on the relationship between aid and FDI, as well as to that on varieties of capitalism.