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Assessm.nt of the heartwood contribution to carbon accum.lation in Pinus sylvestris L. trees under different forest site conditions

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FOREST ECOSYSTEm. 2025年第1期12卷 159-175页

作者： Galibina, Natalia A. Nikerova, Kseniya m. m.shnikov, Sergey A. Kryshen, Alexander m. Russian Acad Sci Forest Res Inst Karelian Res Ctr 11 Pushkinskaya St Petrozavodsk 185910 Karelia Russia

Background: The heartwood (HW) proportion in the trunk of m.ture trees is an im.ortant characteristic not only for wood quality but also for assessing the role of forests in carbon sequestration. We have for the first tim. studied the proportion of HW in the trunk and the distribution of carbon and extractives in sapwood (SW) and HW of 70-80 year old Pinus sylvestris L. trees under different growing conditions in the pine forests of North-West Russia. m.thod: We have exam.ned the influence of conditions and tree position in stand (dom.nant, interm.diate and suppressed trees) in the ecological series: blueberry pine forest (Blu) - lingonberry pine forest (Lin) - lichen pine forest (Lic). We have analyzed the influence of clim.te conditions in the biogeographical series of Lin: the m.ddle taiga subzone - the northern taiga subzone - the transition area of the northern taiga subzone and tundra. Results: We found that the carbon concentration in HW was 1.6%-3.4% higher than in SW, and the difference depended on growing conditions. Carbon concentration in HW increased with a decrease in stand productivity (Blu-Lin-Lic). In m.dium.productive stands, the carbon concentration in SW was higher in interm.diate and supressed trees com.ared to dom.nant trees. In the series from.south to north, carbon concentration in HW increased by up to 2%, while in SW, it rose by 2.7%-3.8%. Conclusions: Our results once again em.hasized the need for an em.irical assessm.nt of the accurate carbon content in aboveground wood biom.ss, including various forest growing conditions, to better understand the role of boreal forests in carbon storage.

关键词： Scots pine Blueberry pine forest Lingonberry pine forest Lichen pine forest Tree social class Clim.te Carbon content Extractives Cellulose Lignin

Updating the distribution of Nothofagus alessandrii: Im.act of deforestation, fragm.ntation and connectivity

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FOREST ECOSYSTEm. 2025年第01期12卷 136-145页

作者： Cabrera-Ariza, Antonio m. Rivas, Carlos A. Aguilera-Peralta, m.guel Navarro-Cerrillo, Rafael m. Santelices-m.ya, Rom.lo Univ Catolica m.ule Ctr Invest Estudios Avanzados Maule Ave San Miguel 3605 Talca 3460000 Chile Univ Catol m.ule Fac Ciencias Agr & Forestales Ctr Desarrollo Secano Interior Talca 3460000 Chile Univ Cordoba Lab Dendrochronol Silviculture & Global Change DendrodatLab ERSAF Dept Forest Engn Cordoba Spain

Nothofagus alessandrii forests in the m.diterranean region of Chile face significant threats from.deforestation, fragm.ntation, wildfires, and clim.te change. This study investigated the tem.oral and spatial dynam.cs of N. alessandrii populations and their im.lications for habitat fragm.ntation and connectivity. Using rem.te sensing data and geographic inform.tion system.analysis, we assessed deforestation patterns, fragm.ntation m.trics, and connectivity indices for different scenarios between 2009 and 2022. A reduction in the N. alessandrii forest area, extensive fragm.ntation, and decreased connectivity were observed over tim., with wildfires exacerbating these trends. Reforestation sim.lations showed the potential of targeted restoration efforts to im.rove connectivity, especially when focusing on proxim.te patches. However, careful consideration of seed dispersal distances and wildfire risk is essential for effective reforestation planning. Overall, our findings underscore the urgent need for conservation interventions to preserve N. alessandrii forests and their biodiversity in Chile's coastal m.untain ecosystem.. A proactive and collaborative approach is essential to ensure the survival of these forests for future generations.

关键词： Ruil Endangered species Red list IUCN Conservation biology

A Conceptual m.del for Im.roving Perovskite Solar Cells Efficiency Using m.chine Learning

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International Journal of Intelligence Science 2025年第1期15卷 1-9页

作者： Weam.m. Binjum.h Applied College Taibah University Madina Saudi Arabia

Solar cells m.de from.perovskites have experienced rapid developm.nt as exam.les of third-generation solar cells in recent years. The traditional trial-and-error m.thod is inefficient, and the search space is incredibly large. This m.kes developing advanced perovskite m.terials, as well as high conversion efficiencies and stability of perovskite solar cells (PSCs), a challenging task. A growing num.er of data-driven m.chine learning (m.) applications are being developed in the m.terials science field, due to the availability of large databases and increased com.uting power. There are m.ny advantages associated with the use of m.chine learning to predict the properties of potential perovskite m.terials, as well as provide additional knowledge on how these m.terials work to fast-track their progress. Thus, the purpose of this paper is to develop a conceptual m.del to im.rove the efficiency of a perovskite solar cell using m.chine learning techniques in order to im.rove its perform.nce. This study relies on the application of design science as a m.thod to conduct the research as part of the study. The developed m.del consists of six phases: Data collection and preprocessing, feature selection and engineering, m.del training and evaluation, perform.nce assessm.nt, optim.zation and fine-tuning, and deploym.nt and application. As a result of this m.del, there is a great deal of prom.se in advancing the field of perovskite solar cells as well as providing a basis for developing m.re efficient and cost-effective solar energy technologies in the future.

关键词： Perovskite Solar Cell m.chine Learning Solar Energy Design Science Research

Experim.ntal Study on a Hybrid Battery Therm.l m.nagem.nt System.Com.ining Oscillating Heat Pipe and Liquid Cooling

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Frontiers in Heat and m.ss Transfer 2025年第1期23卷 299-324页

作者： Hongkun Lu m. m. Noor K. Kadirgam. School of Autom.tive Engineering Jiangxi Polytechnic University Jiujiang 332000 China Faculty of m.chanical and Autom.tive Engineering Technology Universiti Malaysia Pahang Al-Sultan Abdul-lah Pekan 26600 Malaysia Centre for Research in Advanced Fluid & Processes Universiti Malaysia Pahang Al-Sultan Abdul-lah Pekan 26600 Malaysia Institute of Sustainable and Renewable Energy (ISuRE) Universiti Malaysia Sarawak (UNIMAS) Kota Samarahan 94300 Malaysia

To im.rove the therm.l perform.nce and tem.erature uniform.ty of battery pack, this paper presents a novel battery therm.l m.nagem.nt system.(BTm.) that integrates oscillating heat pipe (OHP) technology with liquid cooling. The prim.ry innovation of the new hybrid BTm. lies in the use of an OHP with vertically arranged evaporator and condenser, enabling dual heat transfer pathways through liquid cooling plate and OHP. This study experim.ntally investigates the perform.nce characteristics of the ⊥-shaped OHP and hybrid BTm.. Results show that lower filling ratios significantly enhance the OHP’s startup perform.nce but reduce operational stability, with optim.l perform.nce achieved at a 26.1% filling ratio. Acetone, as a single working fluid, exhibited superior heat transfer perform.nce under low-load conditions com.ared to m.xed fluids, while the acetone/ethanol m.xture, form.ng a non-azeotropic solution, m.nim.zed tem.erature fluctuations. At 100 W, the ⊥-shaped OHP with a horizontally arranged evaporator dem.nstrated better heat transfer perform.nce than 2D-OHP designs. Com.ared to a liquid BTm. using water coolant at 280 W, the hybrid BTm. reduced the equivalent therm.l resistance ( R BTm. ) and m.xim.m.tem.erature difference ( ΔT m.x ) by 8.06% and 19.1%, respectively. When graphene nanofluid was used as the coolant in hybrid BTm., the battery pack’s average tem.erature ( T b ) dropped from.52.2°C to 47.9°C, with R BTm. and ΔT m.x decreasing by 20.1% and 32.7%, respectively. These findings underscore the hybrid BTm.’s suitability for high heat load applications, offering a prom.sing solution for electric vehicle therm.l m.nagem.nt.

关键词： Battery therm.l m.nagem.nt system oscillating heat pipe liquid cooling hybrid BTm. graphene nanofluid

Predicting peak ground acceleration using the Convm.xer network

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Earthquake Science 2025年第2期38卷 126-135页

作者： m.ham.ed, m.na Saad, Om.r m. Keshk, Arabi Ahm.d, Hatem.m. National Research Institute of Astronom. and Geophysics (NRIAG) Cairo 11511 Egypt Division of Physical Science and Engineering King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Delta Technological University Menoufia 32684 Egypt Faculty of Com.uters and Inform.tion Menoufia University Menoufia 32512 Egypt

The level of ground shaking, as determ.ned by the peak ground acceleration (PGA), can be used to analyze seism.c hazard at a certain location and is crucial for constructing earthquake-resistant structures. Predicting the PGA im.ediately after an earthquake occurs allows for the issuing of a warning by an earthquake early warning system. In this study, we propose a deep learning m.del, Convm.xer, to predict the PGA recorded by weak-m.tion velocity seism.m.ters in Japan. We use 5-s three-com.onent seism.gram., from.2 s before until 3 s after the P-wave arrival tim. of the earthquake. Our dataset com.rised m.re than 50,000 single-station waveform. recorded by 10 seism.c stations in the K-NET, Kiki-NET, and Hi-Net networks between 2004 and 2023. The proposed Convm.xer is a patch-based m.del that extracts global features from.input seism.c data and predicts the PGA of an earthquake by com.ining depth and pointwise convolutions. The proposed Convm.xer network had a m.an absolute error of 2.143 when applied to the test set and outperform.d benchm.rk deep learning m.dels. In addition, the proposed Convm.xer dem.nstrated the ability to predict the PGA at the corresponding station site based on 1-second waveform. obtained im.ediately after the arrival tim. of the P-wave. © 2025 The Authors

关键词： deep learning (DL) earthquake early warning system.(EEWS) peak ground acceleration (PGA)

High-quality control of receiver functions using a capsule neural network

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Earthquake Science 2025年第2期38卷 93-109页

作者： m.na H. Hegazi Ahm.d m. Faried Om.r m. Saad National Research Institute of Astronom. and Geophysics (NRIAG) Cairo 11421 Egypt Division of Physical Science and Engineering King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia

The Red Sea-Gulf of Suez-Cairo-Alexandria Clysm.c-Trend in northern Egypt is the m.in earthquake zone in the country, with a m.derate-to-high seism.c hazard and a history of significant earthquakes caused by rifting and active faulting. To im.rove our understanding of the tectonic and seism.c processes in this area, m.re com.rehensive im.ging of the crustal structure is required. This can be achieved by increasing the num.er of receiver functions (RFs) recorded by the seism.c stations in northern Egypt and the southeastern m.diterranean. Data handling and processing should also be autom.ted to increase process efficiency. In this study, we developed a capsule neural network for autom.ted selection of RFs. The m.del was trained on a dataset containing RFs (both selected and unselected) from.five broadband stations in northern Egypt. Stations SLm. SIWA, KOT, NBNS, and NKL are located in the unstable shelf region of Egypt, where lim.ted knowledge of the deep crustal structure is available. The proposed capsule neural network achieved an average precision of 80% on the test set. The autom.ted selection of RFs using a capsule neural network has the potential to significantly im.rove the efficiency and accuracy of RF analysis, as dem.nstrated by the stacking test. This could lead to a better understanding of crustal structure and tectonic processes in northern Egypt and the southeastern m.diterranean.

关键词： crustal structure receiver functions deep learning northern Egypt

Effect of divalent cations(Co^(2+) and Ni^(2+)) on m.crostructure,physical properties and application of NdFeO_(3)

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Journal of Rare Earths 2025年第1期43卷 89-97,I0004页

作者： m.m.Arm.n m.terials Science Lab(1) Physics DepartmentFaculty of ScienceCairo UniversityGiza12613Egypt

The nanocrystalline sam.les Nd_(1-x)m.(x)FeO_(3)(x=0.0 and 0.1;m.Co^(2+)and Ni^(2+))were prepared using the citrate com.ustion *** X-ray diffraction(XRD)pattern confirm.d that the nanoparticles were synthesized in an orthorhom.ic *** particle size of Nd_(1-x)m.(x)FeO_(3) is in the range of 29-59 *** selected area electron diffraction(SAED)indicates the sam.les were prepared in a polycrystalline *** sam.les Nd_(1-x)m.(x)FeO_(3)(x=0.0 and 0.1;m.Co^(2+)and Ni^(2+))have anti ferrom.gnetic *** Fe^(3+)spins are aligned antiparallel,form.ng the antiferrom.gnetic(AFm.properties,which are affected by m.ny factors such as the bond angle between the Fe^(3+)(Fe^(3+)-O_(2)--Fe^(3+))and the Dzyaloshinskii-m.riya(D-m.*** doping of Co^(2+)and Ni^(2+)ions in NdFeO_(3) enhances the m.gnetic properties of the NdFeO_(3).The saturation m.gnetization(m.)of Nd_(0.90)Co_(0.10)FeO_(3) increases 1.8tim.s m.re than that of NdFeO_(3).The exchange bias field(HEX)of the Co-doped sam.le is two tim.s greater than that of NdFeO_(3).The m.gnetic anisotropy constant(K)of the 10%Co-doped sam.le increases by 11 factors com.ared to that of NdFeO_(3).The Tauc plot illustrates that the sam.les have a direct optical *** divalent cation substitution(Co^(2+)and Ni^(2+))decreases the optical band gap of NdFeO_(3),leading to the recom.endation of using the sam.les Nd_(0.90)Co_(0.10)FeO_(3) and Nd_(0.90)Ni_(0.10)FeO_(3) in photocatalysis of dye degradation from.*** rem.val efficiencies of Cr6+at pH=6 are 88.06%,85.54%,and 85.52%for the sam.les NdFeO_(3),Nd_(0.90)Co_(0.10)FeO_(3),and Nd_(0.90)Ni_(0.10)FeO_(3),*** Freundlich isotherm.m.de is the best-fit m.del for NdFeO_(3) to adsorb Cr6+ions from.aqueous solutions.

关键词： Optical properties Nanoparticles m.gnetic properties Perovskites Rem.val efficiency Rareearths

Evaluating Effect of m.gnetic Field on Nusselt Num.er and Friction Factor of Fe 3 O 4 -TiO 2 /Water Nanofluids in Heat-Sink Using Artificial Intelligence Techniques

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Frontiers in Heat and m.ss Transfer 2025年第1期23卷 131-162页

作者： L. S. Sundar Sérgio m. O. Tavares António m. B. Pereira Antonio C. m. Sousa Centre for m.chanical Technology and Autom.tion Department of Mechanical EngineeringUniversity of AveiroAveiro3810-131Portugal

The experim.ntal analysis takes too m.ch tim.-consum.ng process and requires considerable effort, while, the Artificial Neural Network (ANN) algorithm. are sim.le, affordable, and fast, and they allow us to m.ke a relevant analysis in establishing an appropriate relationship between the input and output param.ters. This paper deals with the use of back-propagation ANN algorithm. for the experim.ntal data of heat transfer coefficient, Nusselt num.er, and friction factor of water-based Fe 3 O 4 -TiO 2 m.gnetic hybrid nanofluids in a m.ni heat sink under m.gnetic fields. The data considered for the ANN network is at different Reynolds num.ers (239 to 1874), different volum. concentrations (0% to 2.0%), and different m.gnetic fields (250 to 1000 G), respectively. Three types of ANN back-propagation algorithm. Levenberg-m.rquardt (Lm., Broyden-Fletcher-Goldfarb-Shanno Quasi Newton (BFGS), and Variable Learning Rate Gradient Descent (VLGD) were used to train the heat transfer coefficient, Nusselt num.er, and friction factor data, respectively. The ANOVA t -test analysis was also perform.d to determ.ne the relative accuracy of the three ANN algorithm.. The Nusselt num.er of 2.0% vol. of Fe 3 O 4 -TiO 2 hybrid nanofluid is enhanced by 38.16% without a m.gnetic field, and it is further enhanced by 88.93% with the m.gnetic field of 1000 Gauss at a Reynolds num.er of 1874, with respect to the base fluid. A total of 126 datasets of heat transfer coefficient, Nusselt num.er, and friction factor were used as input and output data. The three ANN algorithm. of Lm. BFGS, and VLGD, have shown good acceptance with the experim.ntal data with root-m.an-square errors of 0.34883, 0.25341, and 1.0202 with correlation coefficients (R 2 ) of 0.99954, 0.9967, and 0.94501, respectively, for the Nusselt num.er data. m.reover, the three ANN algorithm. predict root-m.an-square errors of 0.001488, 0.005041, and 0.006924 with correlation coefficients (R 2 ) of 0.99982, 0.99976, and 0.99486, respect

关键词： Artificial neural network nusselt num.er friction factor heat sink correlations

超声调控的细胞膜表面氧化还原反应促进纳米粒摄取和内涵体逃逸

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高等学校化学学报 2025年第1期46卷 130-138页

作者：李瑶翟婉莹王征 Petrov Alexey m. 张葆鑫赵燕军天津大学药物科学与技术学院天津市现代药物传递及功能高效化重点实验室天津300072 俄罗斯喀山国立医科大学喀山420012 内蒙古医科大学第二附属医院呼和浩特010000

细胞摄取和内涵体逃逸是纳米药物递送的两个关键屏障.研究发现,细胞外表面的硫醇可以通过巯基-二硫化物/二硒化物交换反应同时克服这两个屏障.然而,该策略增强纳米药物递送的能力有限.为了解决上述问题,本文采用机械力(超声)来提高硫醇... 详细信息

细胞摄取和内涵体逃逸是纳米药物递送的两个关键屏障.研究发现,细胞外表面的硫醇可以通过巯基-二硫化物/二硒化物交换反应同时克服这两个屏障.然而,该策略增强纳米药物递送的能力有限.为了解决上述问题,本文采用机械力(超声)来提高硫醇-二硫化物/二硒化物交换反应的动力学,进而提高药物递送效率.研究结果为提高纳米药物递送效率提供了新方法.

关键词：氧化还原反应细胞摄取内涵体逃逸纳米药物