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Physics of porous materials under extreme laser-generated conditions

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Matter and Radiation at Extremes 2024年第3期9卷 1-3页

作者： V.T.Tikhonchuk s.Weber Extreme Light Infrastructure ERIC ELI Beamlines Facility25241 DolníBrezanyCzech Republic CELIA University of Bordeaux33405 TalenceFrance

Porous materials offer unique possibilities for the production of plasmas with controlled density profiles for experiments on laser–matter interaction.They are of growing relevance to many applications,such as inertial confinement fusion,fundamental research,and secondary sources.Understanding the processes of transformation of a porous solid into a plasma is of fundamental interest and is needed for producing materials with desired properties.

关键词： interaction. properties. porous

Elevation transition of aquatic insects closely matches a thermal feature in the Yungas of Northwestern Argentina

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Journal of Mountain science 2024年第2期21卷 433-448页

作者： Alexandra BUITRAGO-GUACANAME Carlos MOLINERI Andrés LIRA-NORIEGA Daniel Andrés DOs sANTOs Neotropical Biodiversity Institute(CONICET-UNT) UNT-DomesHorco Molle S/N4107 TucumánArgentina CONACYT Research Fellow Network of Advanced Molecular StudiesInstitute of Ecology A.COld Road to Coatepec 351El HayaCP 91073XalapaVeracruzMexico Biostatistics Chair Faculty of Natural Sciences and IMLNational University of TucumánSan Miguel de TucumánMiguel Lillo 2054000 TucumánArgentina

Temperature is a key factor that shapes the distribution of organisms.Having knowledge about how species respond to temperature is relevant to devise strategies for addressing the impacts of climate change.Aquatic insects are particularly vulnerable to climate change,yet there is still much to learn about their ecology and distribution.In the Yungas ecoregion of Northwestern Argentina,cold-and warm-adapted species of the orders Ephemeroptera,Plecoptera,and Trichoptera(EPT)are segregated by elevation.We modeled the ecological niche of south American EPT species in this region using available data and projected their potential distribution in geographic space.species were grouped based on their ecogeographic similarity,and we analyzed their replacement pattern along elevation gradients,focusing on the ecotone where opposing thermal preferences converge.Along this interface,we identified critical points where the combined incidence of cold and warm assemblages maximizes,indicating a significant transition zone.We found that the Montane Cloud Forest holds the interface,with a particularly greater suitability at its lower boundary.The main axis of the interface runs in a N-s direction and falls between 14°C-16°C mean annual isotherms.The probability of a particular location within a basin being classified as part of the interface increases as Kira’s warmth index approaches a score around 150.Understanding the interface is critical for defining the thermal limits of species distribution and designing biomonitoring programs.Changes in the location of thermal constants related to mountainous ecotones may cause vertical displacement of aquatic insects and vegetation communities.We have recognized significant temperature thresholds that serve as indicators of suitability for the interface.As global warming is anticipated to shift these indicators,we suggest using them to monitor the imprints of climate change on mountain ecosystems.

关键词： Austral Yungas Ecological Niche Model Ephemeroptera Kira’s warmth index Plecoptera Trichoptera

Insulin therapy in type 2 diabetes: Insights into clinical efficacy, patient-reported outcomes, and adherence challenges

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World Journal of Diabetes 2024年第5期15卷 828-852页

作者： Mahmoud Emad-Eldin Gehan F Balata Eman A Elshorbagy Mona s Hamed Mohamed s Attia Department of Pharmacy Practice Faculty of PharmacyZagazig UniversityZagazig HFQM+872Al-Sharqia GovernorateEgypt Department of Pharmacy Practice Faculty of PharmacyHeliopolis UniversityCairo 44519Egypt Department of Pharmaceutics Faculty of PharmacyZagazig UniversityZagazig 44519Al-Sharqia GovernorateEgypt Department of Internal Medicine Faculty of MedicineZagazig UniversityZagazig 44519Al-Sharqia GovernorateEgypt Department of Community at Faculty of Medicine Zagazig UniversityZagazig 44519Al-Sharqia GovernorateEgypt

Insulin therapy plays a crucial role in the management of type 2 diabetes as the disease progresses.Over the past century,insulin formulations have undergone significant modifications and bioengineering,resulting in a diverse range of available insulin products.These products show distinct pharmacokinetic and pharmacodynamic profiles.Consequently,various insulin regimens have em-erged for the management of type 2 diabetes,including premixed formulations and combinations of basal and bolus insulins.The utilization of different insulin regimens yields disparate clinical outcomes,adverse events,and,notably,patient-reported outcomes(PROs).PROs provide valuable insights from the patient’s perspective,serving as a valuable mine of information for enhancing healthcare and informing clinical decisions.Adherence to insulin therapy,a critical patient-reported outcome,significantly affects clinical outcomes and is influenced by multiple factors.This review provides insights into the clinical effectiveness of various insulin preparations,PROs,and factors impacting insulin therapy adherence,with the aim of enhancing healthcare practices and informing clinical decisions for individuals with type 2 diabetes.

关键词： Adherence Diabetes Insulin Patient-reported outcomes Pharmacokinetic Pharmacodynamic

Explainable Conformer Network for Detection of COVID-19 Pneumonia from Chest CT scan: From Concepts toward Clinical Explainability

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Computers, Materials & Continua 2024年第1期78卷 1171-1187页

作者： Mohamed Abdel-Basset Hossam Hawash Mohamed Abouhawwash s.s.Askar Alshaimaa A.Tantawy Faculty of Computers and Informatics Zagazig UniversityZagazig44519Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of statistics and Operations Research College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

The early implementation of treatment therapies necessitates the swift and precise identification of COVID-19 pneumonia by the analysis of chest CT scans.This study aims to investigate the indispensable need for precise and interpretable diagnostic tools for improving clinical decision-making for COVID-19 diagnosis.This paper proposes a novel deep learning approach,called Conformer Network,for explainable discrimination of viral pneumonia depending on the lung Region of Infections(ROI)within a single modality radiographic CT scan.Firstly,an efficient U-shaped transformer network is integrated for lung image segmentation.Then,a robust transfer learning technique is introduced to design a robust feature extractor based on pre-trained lightweight Big Transfer(BiT-L)and finetuned on medical data to effectively learn the patterns of infection in the input image.secondly,this work presents a visual explanation method to guarantee clinical explainability for decisions made by Conformer Network.Experimental evaluation of real-world CT data demonstrated that the diagnostic accuracy of ourmodel outperforms cutting-edge studies with statistical significance.The Conformer Network achieves 97.40% of detection accuracy under cross-validation settings.Our model not only achieves high sensitivity and specificity but also affords visualizations of salient features contributing to each classification decision,enhancing the overall transparency and trustworthiness of our model.The findings provide obvious implications for the ability of our model to empower clinical staff by generating transparent intuitions about the features driving diagnostic decisions.

关键词： Deep learning COVID-19 multi-modal medical image fusion diagnostic image fusion

Understanding the corrosion and bio-corrosion behaviour of Magnesium composites – a critical review

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Journal of Magnesium and Alloys 2024年第3期12卷 890-939页

作者： Prithivirajan sekar s.K.Panigrahi Department of Mechanical Engineering Indian Institute of Technology MadrasChennai600036India Applied Magnesium Research Center Center of Excellence in Materials and Manufacturing for Futuristic MobilityIndian Institute of Technology MadrasChennai600036India

Realising the potential of Magnesium(Mg),several globally leading ventures have invested in the Mg industry,but their relatively poor corrosion resistance is a never ending saga till date.The corrosion and bio-corrosion behaviour of Mg has gained research attention and still remains a hot topic in the application of automobile,aerospace and biomedical industries.The intrinsic high electrochemical nature of Mg limits their utilization in diverse application.This scenario has prompted the development of Mg composites with an aim to achieve superior corrosion and bio-corrosion resistance.The present review enlightens the influence of grain size(Gs),secondary phase,texture,type of matrix and reinforcement on the corrosion and bio-corrosion behaviour of Mg composites.Firstly,the corrosion and bio-corrosion behaviour of Mg composites manufactured by primary and secondary processing routes are elucidated.secondly,the comprehensive corrosion and bio-corrosion mechanisms of these Mg composites are proposed.Thirdly,the individual role of Gs,texture and corrosive medium on corrosion and bio-corrosion behaviour of Mg composites are clarified and revealed.The challenges encountered,unanswered issues in this field are explained in detail and accordingly the scope for future research is framed.The review is presented from basic concrete background to advanced corrosion mechanisms with an aim of creating interest among the readers like students,researchers and industry experts from various research backgrounds.Indeed,the corrosion and bio-corrosion behaviour of Mg composites are critically reviewed for the first time to:(i)contribute to the body of knowledge,(ii)foster research and development,(iii)make breakthrough,and(iv)create life changing innovations in the field of Mg composite corrosion.

关键词： Corrosion Bio corrosion Magnesium alloys Magnesium composites Magnesium implants.

Real-Time Prediction of Urban Traffic Problems Based on Artificial Intelligence-Enhanced Mobile Ad Hoc Networks(MANETs)

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Computers, Materials & Continua 2024年第5期79卷 1903-1923页

作者： Ahmed Alhussen Arshiya s.Ansari Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Information Technology College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

Traffic in today’s cities is a serious problem that increases travel times,negatively affects the environment,and drains financial resources.This study presents an Artificial Intelligence(AI)augmentedMobile Ad Hoc Networks(MANETs)based real-time prediction paradigm for urban traffic challenges.MANETs are wireless networks that are based on mobile devices and may self-organize.The distributed nature of MANETs and the power of AI approaches are leveraged in this framework to provide reliable and timely traffic congestion forecasts.This study suggests a unique Chaotic spatial Fuzzy Polynomial Neural Network(CsFPNN)technique to assess real-time data acquired from various sources within theMANETs.The framework uses the proposed approach to learn from the data and create predictionmodels to detect possible traffic problems and their severity in real time.Real-time traffic prediction allows for proactive actions like resource allocation,dynamic route advice,and traffic signal optimization to reduce congestion.The framework supports effective decision-making,decreases travel time,lowers fuel use,and enhances overall urban mobility by giving timely information to pedestrians,drivers,and urban planners.Extensive simulations and real-world datasets are used to test the proposed framework’s prediction accuracy,responsiveness,and scalability.Experimental results show that the suggested framework successfully anticipates urban traffic issues in real-time,enables proactive traffic management,and aids in creating smarter,more sustainable cities.

关键词： Mobile AdHocNetworks(MANET) urban traffic prediction artificial intelligence(AI) traffic congestion chaotic spatial fuzzy polynomial neural network(CsFPNN)

MAIPFE:An Efficient Multimodal Approach Integrating Pre-Emptive Analysis,Personalized Feature selection,and Explainable AI

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Computers, Materials & Continua 2024年第5期79卷 2229-2251页

作者： Moshe Dayan sirapangi s.Gopikrishnan school of Computer science and Engineering VIT-AP UniversityAmaravathiAndhra Pradesh522241India

Medical Internet of Things(IoT)devices are becoming more and more common in healthcare.This has created a huge need for advanced predictive health modeling strategies that can make good use of the growing amount of multimodal data to find potential health risks early and help individuals in a personalized way.Existing methods,while useful,have limitations in predictive accuracy,delay,personalization,and user interpretability,requiring a more comprehensive and efficient approach to harness modern medical IoT devices.MAIPFE is a multimodal approach integrating pre-emptive analysis,personalized feature selection,and explainable AI for real-time health monitoring and disease detection.By using AI for early disease detection,personalized health recommendations,and transparency,healthcare will be transformed.The Multimodal Approach Integrating Pre-emptive Analysis,Personalized Feature selection,and Explainable AI(MAIPFE)framework,which combines Firefly Optimizer,Recurrent Neural Network(RNN),Fuzzy C Means(FCM),and Explainable AI,improves disease detection precision over existing methods.Comprehensive metrics show the model’s superiority in real-time health analysis.The proposed framework outperformed existing models by 8.3%in disease detection classification precision,8.5%in accuracy,5.5%in recall,2.9%in specificity,4.5%in AUC(Area Under the Curve),and 4.9%in delay reduction.Disease prediction precision increased by 4.5%,accuracy by 3.9%,recall by 2.5%,specificity by 3.5%,AUC by 1.9%,and delay levels decreased by 9.4%.MAIPFE can revolutionize healthcare with preemptive analysis,personalized health insights,and actionable recommendations.The research shows that this innovative approach improves patient outcomes and healthcare efficiency in the real world.

关键词： Predictive health modeling Medical Internet of Things explainable artificial intelligence personalized feature selection preemptive analysis

Provenance and depositional setting of the Late MiocenePleistocene clastic sediments in the eastern Arabian Peninsula and western Iraq using rare earth elements geochemistry

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Acta Geochimica 2024年第2期43卷 399-410页

作者： salih M.Awadh Zinah s.Al-Ankaz Mohanad R.A.Al-Owaidi John s.Armstrong-Altrin Department of Geology College of ScienceUniversity of BaghdadBaghdadIraq Department of Geology College of ScienceUniversity of WasitWasit 52011Iraq Department of Applied Geology College of ScienceUniversity of BabylonBabylon 51001Iraq Unidad de Procesos Oceanicos y Costeros Instituto de Ciencias del Mar y LimnologíaUniversidad Nacional Autonoma de MexicoCiudad Universitaria04510 Mexico CityCDMXMexico Department of Marine sciences Bharathidasan UniversityTiruchirapalliTamil Nadu 620024India

The sandstones of the Late miocene–Pliocene Dibdibba Formation in the Najaf–Karbala Plateau and Basra were examined to determine their source rocks and origin. The rare earth elements(REE) and trace elements(sc, Co, V, and Th) concentrations in these sandstones revealed that they likely derived from a single source. The steep light rare earth elements(LREE) and flat, heavy rare earth element(HREE) patterns, negative Eu anomaly, and high ΣREE contents in sandstones suggest its derivation from a suggests that a passive continental margin environment and originated from felsic source rocks. The average concentration of ΣREE is 93.5 ppm, which is lower than that of the average crustal compositions like Upper Continental Crust and Post Archean Australian shale. The higher proportion of LREE compared to HREE implies that these sandstones were recycled and derived from a distal source. The Th/Co, Th/sc, La/sc, La/Co, Eu/Eu*and(La/Lu)cn elemental ratios indicated that these Late Miocene–Pliocene sandstones were derived from felsic rocks located in the marginal region of the Arabian shield.

关键词： REE Dibdibba formation Clastic sediments Passive continental margin

Optimizing oncolytic virus design:a“swiss army knife”approach to create a systemically delivered therapeutic

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signal Transduction and Targeted Therapy 2024年第5期9卷 1791-1792页

作者： Carolina s.Ilkow John Cameron Bell Ottawa Hospital Research Institute 501 Smyth RoadOttawaONK1H 8L6Canada

In a recent paper published in Nature Biotechnology,Chen et al.1 describe a multiplex oncolytic virus platform that coupled with adoptive T cell therapy could solve the problem of repeat,systemic delivery of virus based therapeutics.It is widely accepted that multi-targeted therapeutic approaches attacking several facets of cancer biology are necessary to effectively deal with the tumor heterogeneity that exists within and between patients.

关键词： therapeutic al. targeted