bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Optimal Model for Medical Text Classification Based on Adaptive Genetic Algorithm
Authors: Ben Abdennour Ghada , Gasmi Karim , Ejbali Ridha 
Published: July 2024

AbstractAutomatic text classification, in which textual data is categorized into specified categories based on its content, is a classic issue in the science of Natural Language Processing. In recent years, there has been a notable surge in research on medical text classification due to the increasing availability of medical data like patient medical records and medical literature. Machine learning and statistical methods, such as those used in medical text classification, have proven to be highly efficient for these tasks. However, a significant amount of manual labor is still required to categorize the extensive dataset utilized for training. Recent research have demonstrated the effectiveness of pretrained language models, including machine learning models, in reducing the time and effort required for feature engineering by medical experts. However, there is no statistically significant enhancement in performance when directly applying the machine learning model to the classification task. In this paper, we present a hybrid machine learning model that combines individual traditional algorithms augmented by a genetic algorithm. However, the improved model is designed to enhance performance by optimizing the weight parameter. In this context, the best single model demonstrated commendable accuracy. In addition, when applying the hybridization approach and optimizing the weight parameters, the results were substantially enhanced. The results underscore the superiority of our augmented hybrid model over individual traditional algorithms. We conduct experiments using two distinct types of datasets: one comprising medical records, such as the Heart Failure Clinical Record and another consisting of medical literature, such as PubMed 20k RCT. So, the objective is to clearly showcase the effectiveness of our approach by highlighting the significant enhancements in accuracy, precision, F1-score and Recall achieved through our improved model.
Filtering of 3D point clouds using maximum likelihood algorithm
Authors: Salah Mahmoud , Farhan Magda , Basha Ali , Sherif Mohamed 
Published: July 2024

AbstractRecently, the 3D point cloud (PC) has become more popular as an innovative object representation. However, there is usually noise and outliers in the raw point cloud. It is essential to eliminate the noise from the point cloud and outlier data while maintaining the features and finer details intact. This paper presents a comprehensive method for filtering and classification point clouds using a maximum likelihood algorithm (ML). TOPCON GLS-2000 3D terrestrial laser scanners (TLS) have been used to collect the 3D PC data set; the scan range is up to 350 m. About 30 m apart from the study area. ScanMaster software has been used to import, view, and filter point cloud information. The position information of the points is linked with the training point cloud and the filtered point cloud to derive the nonlinear model using MATLAB software. To evaluate the quality of the denoising results, two error metrics have been used: the average angle (δ) and distance (Dmean) between the ground truth point and the resulting point. The experimental findings demonstrate that the suggested approach can effectively filter out background noise while improving feature preservation. The filtering and classifying technique is more effective and efficient compared to the selected filtering methods when applied to 3D point clouds containing a large number of points and a variety of natural characteristics.
“In Silico” prediction of antibiotics biodegradation by Ganoderma lucidum GILCC 1 laccase
Authors: Mora-Gamboa María P. C. , Ardila-Leal Leidy D. , Galindo Johan F. , Poutou-Piñales Raúl A. , Quevedo-Hidalgo Balkys E. 
Published: July 2024

AbstractAntibiotics present a pressing environmental challenge as emerging pollutants due to their persistence and role in promoting antibiotic-resistant bacteria. To model the utilization of Ganoderma lucidum GlLCC1 laccase in degrading antibiotics, a 3D homology model of GILCC1, based on Lentinus tigrinus mushroom laccase, was utilized. Five broad-spectrum WHO-designated antibiotics with molecular weights between 100 and 500 Da were selected. Molecular dynamics simulations were conducted at pH 3.0 and 7.0 to evaluate the interactions between GILCC1 and antibiotics in a TIP3P water box, with system behaviour assessed at 300 °K using an NPT assembly. ABTS (2,2ʹ-Azino-bis (3-ethylbenzthiazoline-6-sulfonic Acid)) served as the comparison molecule. The binding free energy indicated a strong affinity between 3D GILCC1 and various ligands. At pH 3.0, GILCC1 exhibited significant Gibbs free energy (ΔG), indicating a high affinity for Levofloxacin (LVX; −8.2 kcal mol−1), Sulfisoxazole (SFX; −7.8 kcal mol−1), Cefuroxime (CXM; −7.5 kcal mol−1), Cephradine (CFD; −7. 5 kcal mol−1), ABTS (−7.6 kcal mol−1), and Tetracycline (TE; −7.5 kcal mol−1), attributed to pocket topology and interactions such as hydrogen bonds and van der Waals forces. Electron transfer in GILCC1 involved a chain of residues, including His395 and Phe239. Although the affinity decreased at pH 7.0, the potential of GILCC1 to degrade antibiotics remained plausible. This study accurately predicted the behaviour of the laccase-antibiotic system, providing atomic-level insights into molecular interactions and emphasizing the importance of experimental assays and assessments of antibiotic degradation in wastewater, considering various chemical compounds. The use of ABTS as a mediator was suggested to enhance molecule affinity.
Graphical abstract
Microstructure, mechanical and tribological properties of AA5083-TiO2 nanocomposite by multi-pass friction stir processing
Authors: Karmiris-Obratański Panagiotis , Papantoniou Ioannis G. , Leszczyńska-Madej Beata 
Published: July 2024

AbstractThis study examines the impact of Friction Stir Processing (FSP) with TiO2 nanoparticle incorporation on the microstructural, mechanical, and tribological properties of AA5083 Metal Matrix Composites (MMCs). It offers a detailed analysis of the alterations in the alloy’s characteristics due to FSP. Microstructural examination was conducted using optical microscopy (OM) and scanning electron microscopy (SEM). Significant findings include the microstructural refinement where TiO2 nanoparticle addition during FSP shrank the grain size from 20 to 3 µm after one pass, which then rose to 7 µm following four passes. Mechanical properties, specifically microhardness and tensile strength, were assessed. Results indicated that after four FSP passes, the material can reach a yield strength of 192 MPa and an ultimate tensile strength (UTS) of 359 MPa, alongside a consistent microhardness of 103 HV0.1. Furthermore, it was observed that increasing FSP passes enhances energy absorption, although it remains lower than that of the base material. Analysis of fracture and wear mechanisms has led to the conclusion that with more passes, fracture mechanisms transition to a mix of ductile and brittle behaviors, and the friction coefficient decreases by up to 22.95%.
The use of artificial intelligence to advance sustainable supply chain: retrospective and future avenues explored through bibliometric analysis
Authors: Zejjari Ibtissam , Benhayoun Issam 
Published: July 2024

AbstractKeeping up with the hastily growing economy implies undergoing unremitting transformation permanently. In the field of supply chain, such progress can only be guaranteed via the exploration of new horizons and innovative solutions in response to the constraints of the global market. Emerging technologies, particularly artificial intelligence, offer promising avenues for enhancing supply chain processes, with sustainability ascending as a critical consideration. Despite the recent surfacing of AI-driven applications, scant attention has been devoted to exploring their full potential within supply chain operations, particularly in conjunction with SDGs. Recognizing the untapped opportunities presented by the implementation of AI for a sustainable supply chain this study undertakes a bibliometric analysis of 236 research papers sourced from the Web of science database. The analysis utilizes R language BiblioShiny to examine the extracted papers, and dissect patterns, trends, and relationships among key concepts and themes as well as prominent topics, impactful authors, and leading journals and countries in this domain. The findings reveal substantial growth in research related to SCM, AI, and sustainability as the UK leads this field of study with 132 articles followed by India, China and the USA. Eventually, the National University of Singapore came first in terms of paper affiliations, followed by De La Salle University, and London Metropolitan University. These results only prove that sustainability is becoming more critical in the equation of AI-driven supply chains especially with the current socio-political and economic circumstances, constituting a solid base for further academic research and more innovations in the managerial and business-related policies in this field.
Are the key welfare models effective for exotic pet animals?
Authors: Warwick Clifford , Steedman Catrina , Jessop Mike , Grant Rachel 
Published: July 2024

AbstractThe Five Freedoms, Five Domains, Five Welfare Needs, and other similar models or principles, are key aspirational or outcome-led frameworks aimed at safeguarding animals under human custodianship, and are widely used in legislation, guidance documents, and protocols. We aimed to investigate the effectiveness of these animal welfare models as intended protections. Our study considered three informational tiers of relevance for guidance: Tier 1, key welfare models and principles governing legislation; Tier 2, formal secondary guidance; and Tier 3, welfare outcomes. We conducted a literature review of key welfare models, as well as reports of persistent animal welfare problems associated with exotic pets, and collated available examples of relevant legislation and their implementation. Of the 91 studied regions that adopted animal welfare models, the following were directly or closely aligned with: Five Freedoms n = 64, Five Welfare Needs n = 26, Five Domains n = 1. We identified the following numbers of welfare concerns for animals kept in trade and private home situations: invertebrates n = 21, fishes n = 27, amphibians n = 26, reptiles n = 43, birds n = 22, mammals n = 43. Despite the frequent adoption of one or other model or principle, animal welfare concerns and problems were regularly identified in relation to both commercial and home environments across all animal classes. We recommend that animal welfare is assigned priority over traditional pet selling or keeping practices through the adoption of modernised animal welfare models, underpinned by evolving scientific knowledge and precautionary principles, that aim to promote animal-centric preferred life quality.
Optimal drift rate control and two-sided impulse control for a Brownian system with the long-run average criterion
Authors: Cao Ping , Wang Xiaodao , Yao Dacheng 
Published: July 2024

AbstractIn this paper, we consider a joint drift rate control and two-sided impulse control problem in which the system manager adjusts the drift rate as well as the instantaneous relocation for a Brownian motion, with the objective of minimizing the total average state-related cost and control cost. The system state can be negative. Assuming that instantaneous upward and downward relocations take a different cost structure, which consists of both a setup cost and a variable cost, we prove that the optimal control policy takes an $\left\{ {\!\left( {{s^{\ast}},{q^{\ast}},{Q^{\ast}},{S^{\ast}}} \right),\!\left\{ {{\mu ^{\ast}}(x)\,:\,x \in [ {{s^{\ast}},{S^{\ast}}}]} \right\}} \right\}$ form. Specifically, the optimal impulse control policy is characterized by a quadruple $\left( {{s^{\ast}},{q^{\ast}},{Q^{\ast}},{S^{\ast}}} \right)$, under which the system state will be immediately relocated upwardly to ${q^{\ast}}$ once it drops to ${s^{\ast}}$ and be immediately relocated downwardly to ${Q^{\ast}}$ once it rises to ${S^{\ast}}$; the optimal drift rate control policy will depend solely on the current system state, which is characterized by a function ${\mu ^{\ast}}\!\left( \cdot \right)$ for the system state staying in $[ {{s^{\ast}},{S^{\ast}}}]$. By analyzing an associated free boundary problem consisting of an ordinary differential equation and several free boundary conditions, we obtain these optimal policy parameters and show the optimality of the proposed policy using a lower-bound approach. Finally, we investigate the effect of the system parameters on the optimal policy parameters as well as the optimal system’s long-run average cost numerically.
Pyramid diffractive optical networks for unidirectional image magnification and demagnification
Authors: Bai Bijie , Yang Xilin , Gan Tianyi , Li Jingxi , Mengu Deniz , Jarrahi Mona , Ozcan Aydogan 
Published: July 2024

AbstractDiffractive deep neural networks (D2NNs) are composed of successive transmissive layers optimized using supervised deep learning to all-optically implement various computational tasks between an input and output field-of-view. Here, we present a pyramid-structured diffractive optical network design (which we term P-D2NN), optimized specifically for unidirectional image magnification and demagnification. In this design, the diffractive layers are pyramidally scaled in alignment with the direction of the image magnification or demagnification. This P-D2NN design creates high-fidelity magnified or demagnified images in only one direction, while inhibiting the image formation in the opposite direction—achieving the desired unidirectional imaging operation using a much smaller number of diffractive degrees of freedom within the optical processor volume. Furthermore, the P-D2NN design maintains its unidirectional image magnification/demagnification functionality across a large band of illumination wavelengths despite being trained with a single wavelength. We also designed a wavelength-multiplexed P-D2NN, where a unidirectional magnifier and a unidirectional demagnifier operate simultaneously in opposite directions, at two distinct illumination wavelengths. Furthermore, we demonstrate that by cascading multiple unidirectional P-D2NN modules, we can achieve higher magnification factors. The efficacy of the P-D2NN architecture was also validated experimentally using terahertz illumination, successfully matching our numerical simulations. P-D2NN offers a physics-inspired strategy for designing task-specific visual processors.
Parthanatos initiated by ROS-induced DNA damage is involved in intestinal epithelial injury during necrotizing enterocolitis
Authors: Xu Lingqi , Ma Shurong , Qu Minhan , Li Na , Sun Xu , Wang Tingting , Chen Lulu , Zhu Jie , Ding Yifang , Gong Yuan , Hu Fangjie , Dong Zhenzhen , Zhang Rui , Wang Jiang Huai , Wang Jian , Zhou Huiting 
Published: July 2024

AbstractNecrotizing enterocolitis (NEC) involves intestinal epithelial damage and inflammatory response and is associated with high morbidity and mortality in infants. To improve therapeutic prospects, elucidating underlying molecular mechanisms of intestinal epithelial damage during NEC is of the essence. Poly (ADP-ribose) polymerase 1 (PARP1)-dependent parthanatos is a programmed inflammatory cell death. In the present study, the presence of parthanatos-associated proteins PARP1 and poly (ADP-ribose) (PAR), along with high expression of DNA damage-associated biomarkers, 8-hydroxy-2’-deoxyguanosine (8-OHdG) and phosphorylation of histone H2AX (γH2AX), were discovered in the intestinal tissues of NEC infants. Additionally, the upregulated expression of PARP1 and PAR in NEC intestinal tissues correlated distinctly with clinical indices indicative of NEC incidence and severity. Furthermore, we demonstrated that inhibiting the expression of parthanatos-associated proteins, by either pharmacological blockage using 3-aminobenzamide (3-AB), an inhibitor of PARP1, or genetic knockout using Parp1-deficient mice, resulted in substantial improvements in both histopathological severity scores associated with intestinal injury and inflammatory reactions. Moreover, in an in vitro NEC model, reactive oxygen species (ROS)-induced DNA damage promoted the formation of PAR and nuclear translocation of apoptosis-inducing factor (AIF), thus activating PARP1-dependent parthanatos in Caco-2 cells and human intestinal organoids. Our work verifies a previously unexplored role for parthanatos in intestinal epithelial damage during NEC and suggests that inhibition of parthanatos may serve as a potential therapeutic strategy for intervention of NEC.
Cohort study of cardiovascular safety of different COVID-19 vaccination doses among 46 million adults in England
Authors: Ip Samantha , North Teri-Louise , Torabi Fatemeh , Li Yangfan , Abbasizanjani Hoda , Akbari Ashley , Horne Elsie , Denholm Rachel , Keene Spencer , Denaxas Spiros , Banerjee Amitava , Khunti Kamlesh , Sudlow Cathie , Whiteley William N. , Sterne Jonathan A. C. , Wood Angela M. , Walker Venexia ,   the CVD-COVID-UK/COVID-IMPACT Consortium,   the Longitudinal Health and Wellbeing COVID-19 National Core Study
Published: July 2024

AbstractThe first dose of COVID-19 vaccines led to an overall reduction in cardiovascular events, and in rare cases, cardiovascular complications. There is less information about the effect of second and booster doses on cardiovascular diseases. Using longitudinal health records from 45.7 million adults in England between December 2020 and January 2022, our study compared the incidence of thrombotic and cardiovascular complications up to 26 weeks after first, second and booster doses of brands and combinations of COVID-19 vaccines used during the UK vaccination program with the incidence before or without the corresponding vaccination. The incidence of common arterial thrombotic events (mainly acute myocardial infarction and ischaemic stroke) was generally lower after each vaccine dose, brand and combination. Similarly, the incidence of common venous thrombotic events, (mainly pulmonary embolism and lower limb deep venous thrombosis) was lower after vaccination. There was a higher incidence of previously reported rare harms after vaccination: vaccine-induced thrombotic thrombocytopenia after first ChAdOx1 vaccination, and myocarditis and pericarditis after first, second and transiently after booster mRNA vaccination (BNT-162b2 and mRNA-1273). These findings support the wide uptake of future COVID-19 vaccination programs.
Phosphorylation of PFKL regulates metabolic reprogramming in macrophages following pattern recognition receptor activation
Authors: Wang Meiyue , Flaswinkel Heinrich , Joshi Abhinav , Napoli Matteo , Masgrau-Alsina Sergi , Kamper Julia M. , Henne Antonia , Heinz Alexander , Berouti Marleen , Schmacke Niklas A. , Hiller Karsten , Kremmer Elisabeth , Wefers Benedikt , Wurst Wolfgang , Sperandio Markus , Ruland Jürgen , Fröhlich Thomas , Hornung Veit 
Published: July 2024

AbstractInnate immune responses are linked to key metabolic pathways, yet the proximal signaling events that connect these systems remain poorly understood. Here we show that phosphofructokinase 1, liver type (PFKL), a rate-limiting enzyme of glycolysis, is phosphorylated at Ser775 in macrophages following several innate stimuli. This phosphorylation increases the catalytic activity of PFKL, as shown by biochemical assays and glycolysis monitoring in cells expressing phosphorylation-defective PFKL variants. Using a genetic mouse model in which PFKL Ser775 phosphorylation cannot take place, we observe that upon activation, glycolysis in macrophages is lower than in the same cell population of wild-type animals. Consistent with their higher glycolytic activity, wild-type cells have higher levels of HIF1α and IL-1β than PfklS775A/S775A after LPS treatment. In an in vivo inflammation model, PfklS775A/S775A mice show reduced levels of MCP-1 and IL-1β. Our study thus identifies a molecular link between innate immune activation and early induction of glycolysis.
Catalytic enantioselective nitrone cycloadditions enabling collective syntheses of indole alkaloids
Authors: Tian Xiaochen , Xuan Tengfei , Gao Jingkun , Zhang Xinyu , Liu Tao , Luo Fengbiao , Pang Ruochen , Shao Pengcheng , Yang Yun-Fang , Wang Yang 
Published: July 2024

AbstractTetrahydro-β-carboline skeletons are prominent and ubiquitous in an extraordinary range of indole alkaloid natural products and pharmaceutical compounds. Powerful synthetic approaches for stereoselective synthesis of tetrahydro-β-carboline skeletons have immense impacts and have attracted enormous attention. Here, we outline a general chiral phosphoric acid catalyzed asymmetric 1,3-dipolar cycloaddition of 3,4-dihydro-β-carboline-2-oxide type nitrone that enables access to three types of chiral tetrahydro-β-carbolines bearing continuous multi-chiral centers and quaternary chiral centers. The method displays different endo/exo selectivity from traditional nitrone chemistry. The distinct power of this strategy has been illustrated by application to collective and enantiodivergent total syntheses of 40 tetrahydro-β-carboline-type indole alkaloid natural products with divergent stereochemistry and varied architectures.
Dual roles of microbes in mediating soil carbon dynamics in response to warming
Authors: Qin Shuqi , Zhang Dianye , Wei Bin , Yang Yuanhe 
Published: July 2024

AbstractUnderstanding the alterations in soil microbial communities in response to climate warming and their controls over soil carbon (C) processes is crucial for projecting permafrost C-climate feedback. However, previous studies have mainly focused on microorganism-mediated soil C release, and little is known about whether and how climate warming affects microbial anabolism and the subsequent C input in permafrost regions. Here, based on a more than half-decade of in situ warming experiment, we show that compared with ambient control, warming significantly reduces microbial C use efficiency and enhances microbial network complexity, which promotes soil heterotrophic respiration. Meanwhile, microbial necromass markedly accumulates under warming likely due to preferential microbial decomposition of plant-derived C, further leading to the increase in mineral-associated organic C. Altogether, these results demonstrate dual roles of microbes in affecting soil C release and stabilization, implying that permafrost C-climate feedback would weaken over time with dampened response of microbial respiration and increased proportion of stable C pool.