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Soil organic carbon stocks in native forest of Argentina:a useful surrogate for mitigation and conservation planning under climate variability

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Ecological Processes 2024年第1期13卷 3-24页

作者： Pablo L.Peri Juan Gaitán matías mastrangelo marcelo Nosetto Pablo E.Villagra Ezequiel Balducci martín Pinazo Roxana P.Eclesia Alejandra Von Wallis Sebastián Villarino Francisco Alaggia marina González Polo Silvina manrique Pablo A.meglioli Julián Rodríguez-Souilla martín mónaco Jimena E.Chaves Ariel medina Ignacio Gasparri Eugenio Alvarez Arnesi maría Paula Barral Axel von müller Norberto m.Pahr Josefina Uribe Echevarria Pedro Fernández marina morsucci Dardo López Juan manuel Cellini Leandro Alvarez Ignacio Barberis Hernán Colomb Ludmila La manna Sebastián Barbaro Cecilia Blundo Ximena Sirimarco Laura Cavallero Gualberto Zalazar Guillermo martínez Pastur Instituto Nacional de Tecnología Agropecuaria (INTA) Universidad Nacional de la Patagonia Austral (UNPA) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Universidad Nacional de Luján Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Grupo de Estudio de Agroecosistemas y Paisajes Rurales (GEAP) Universidad Nacional de Mar del Plata Consejo Nacional de Investigaciones Científicas y Técnicas(CONICET ) CCT San Luis Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Instituto Argentino de Nivología Glaciología y Ciencias Ambientales (IANIGLA) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Universidad Nacional de Cuyo Instituto de Investigaciones en Biodiversidad y medioambiente (INIBIOmA) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Instituto de Investigaciones en Energía No Convencional CCT Salta-JujuyConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Laboratorio de Recursos Agroforestales Centro Austral de Investigaciones Científicas (CADIC) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Dirección Nacional de Bosques Ministerio de Ambiente y Desarrollo Sostenible de la Nación Instituto de Ecología Regional Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET )Universidad Nacional de Tucumán Universidad Nacional de Rosario Instituto de Investigaciones en Ciencias Agrarias de Rosario Centro Científico Tecnológico CONICET Grupo de Estudio de Agroecosistemas y Paisajes Rurales (GEAP) Universidad Nacional de Mar del Plata Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Laboratorio de Investigaciones en maderas (LImAD) Universidad Nacional de La Plata (UNLP) Administración de Parques Nacionales (APN) Parque Nacional Los Alerces Centro de Estudios Ambientales Integrados (CEAI) Universidad Nacional de la Patagonia San Juan Bosco (UNPASJB) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET )

Background The nationally determined contribution（NDC） presented by Argentina within the framework of the Paris Agreement is aligned with the decisions made in the context of the United Nations Framework Conven-tion on Climate Change（UNFCCC） on the reduction of emissions derived from deforestation and forest degradation, as well as forest carbon conservation（REDD+）. In addition, climate change constitutes one of the greatest threats to forest biodiversity and ecosystem services. However, the soil organic carbon（SOC） stocks of native forests have not been incorporated into the Forest Reference Emission Levels calculations and for conservation planning under cli-mate variability due to a lack of information. The objectives of this study were:（i） to model SOC stocks to 30 cm of native forests at a national scale using climatic, topographic and vegetation as predictor variables, and（ii） to relate SOC stocks with spatial–temporal remotely sensed indices to determine biodiversity conservation concerns due to threats from high inter-annual climate *** We used 1040 forest soil samples（0–30 cm） to generate spatially explicit estimates of SOC native forests in Argentina at a spatial resolution of approximately 200 m. We selected 52 potential predictive environmental covari-ates, which represent key factors for the spatial distribution of SOC. All covariate maps were uploaded to the Google Earth Engine cloud-based computing platform for subsequent modelling. To determine the biodiversity threats from high inter-annual climate variability, we employed the spatial–temporal satellite-derived indices based on Enhanced Vegetation Index（EVI） and land surface temperature（LST） images from Landsat *** SOC model（0–30 cm depth） prediction accounted for 69% of the variation of this soil property across the whole native forest coverage in Argentina. Total mean SOC stock reached 2.81 Pg C（2.71–2.84 Pg C with a probability of 90%） for a total area of 460,790 km2,

关键词： Soil organic carbon Biodiversity Native forest Climate change mitigation modelling Resilience

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Effects of Spark Energy on Spark Plug Fault Recognition in a Spark Ignition Engine

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Energy Engineering 2022年第1期119卷 189-199页

作者： A.A.Azrin I.m.Yusri m.H.mat Yasin A.Zainal Faculty of mechanical and Automotive Engineering Technology Universiti Malaysia PahangPekan26600Malaysia Centre for Automotive Engineering Universiti Malaysia PahangPekan26600Malaysia Automotive Technology Center(ATeC) Politeknik Sultan Mizan Zainal AbidinDungun23000Malaysia Automotive Engineering Department Education Engineering FacultyUniversitas Negeri YogyakartaYogyakarta55281Indonesia

The increasing demands for fuel economy and emission reduction have led to the development of lean/diluted combustion strategies for modern Spark Ignition(SI)*** new generation of SI engines requires higher spark energy and a longer discharge duration to improve efficiency and reduce the ***,the increased spark energy gives negative impacts on the ignition system which results in deterioration of the spark ***,a numerical model was used to estimate the spark energy of the ignition system based on the breakdown *** trend of spark energy is then recognized by implementing the classification *** features were identified from the Information Gain(IG)scoring of the statistical analysis.k-Nearest Neighbor(KNN),Artificial Neural Network(ANN),and SupportVector machine(SVm)models were studied to identify the best classifier for the classification *** all classifiers,the entire featured dataset was randomly divided into standardized parameter values of training and testing data sets with the ratio of 70-30 for each *** was shown in the study that the KNN classifier acquired the highest Classification Accuracy(CA)of 94.1%compared to ANN and SVm that score 77.3%and 87.9%on the test data,respectively.

关键词： Spark energy numerical model breakdown voltage fault recognition classification

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Electrochemical Formation of Polypyrrole-carboxymethylcellulose Conducting Polymer Composite Films

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Journal of materials Science & Technology 2005年第5期21卷 661-665页

作者： H.N.m.Ekramul mahmud Anuar Kassim Zulkarnain Zainal Wan mahmood mat Yunus Faculty of Science Universiti Putra Malaysia43400 Serdang SelangorMalaysiaFaculty of Science Universiti Putra Malaysia43400 Serdang SelangorMalaysiaFaculty of Science Universiti Putra Malaysia43400 Serdang SelangorMalaysiaFaculty of Science Universiti Putra Malaysia43400 Serdang SelangorMalaysia

The electrochemical preparation of polypyrrole-carboxymethylcellulose （PPY-CmC） conducting polymer composite films on indium tin oxide （ITO） glass electrode from an aqueous solution containing pyrrole monomer, ptoluenesulfonate electrolyte and carboxymethylcellulose insulating polymer is reported. The characterization by Fourier transform infrared spectroscopy （FT-IR） shows that carboxymethylcellulose （CmC） has been successfully incorporated into polypyrrole structure forming PPY-CmC polymer composite films. The conductivity of the prepared composite films was found to increase with increaseing CmC concentration in pyrrole solution, The optical microscopic results show the influence of CmC concentration in the pyrrole solution over the morphological changes of the prepared films. The dynamic mechanical analysis （DmA） on the prepared PPY-CmC film reveals the higher plastic property of the PPY-CmC composite film.

关键词： Conducting polymer Polypyrrole Carboxymethylcellulose

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OffSig-SinGAN: A Deep Learning-Based Image Augmentation model for Offline Signature Verification

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Computers, materials & Continua 2023年第7期76卷 1267-1289页

作者： m.muzaffar Hameed Rodina Ahmad Laiha mat Kiah Ghulam murtaza Noman mazhar Faculty of Computer Science and Information Technology University of MalayaKuala Lumpur46400Malaysia Department of Computer Science Bahauddin Zakariya UniversityMultan60000Pakistan Department of Computer Science Sukkur Institute of Business Administration UniversitySukkur65200Pakistan

Offline signature verification(OfSV)is essential in preventing the falsification of *** learning(DL)based OfSVs require a high number of signature images to attain acceptable ***,a limited number of signature samples are available to train these models in a real-world *** researchers have proposed models to augment new signature images by applying various ***,on the other hand,have used human neuromotor and cognitive-inspired augmentation models to address the demand for more signature ***,augmenting a sufficient number of signatures with variations is still a challenging *** study proposed OffSig-SinGAN:a deep learning-based image augmentation model to address the limited number of signatures problem on offline signature *** proposed model is capable of augmenting better quality signatures with diversity from a single signature image *** is empirically evaluated on widely used public datasets;*** quality of augmented signature images is assessed using four metrics like pixel-by-pixel difference,peak signal-to-noise ratio(PSNR),structural similarity index measure(SSIm),and frechet inception distance(FID).Furthermore,various experiments were organised to evaluate the proposed image augmentation model’s performance on selected DL-based OfSV systems and to prove whether it helped to improve the verification accuracy *** results showed that the proposed augmentation model performed better on the GPDSsyntheticSignature dataset than other augmentation *** improved verification accuracy rate of the selected DL-based OfSV system proved the effectiveness of the proposed augmentation model.

关键词： Signature forgery detection offline signature verification deep learning image augmentation generative adversarial networks

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An Insight into the Structural, Electronic and Transport Characteristics of XIn_(2)S_(4) (X = Zn, Hg) Thiospinels using a Highly Accurate All-Electron FP-LAPW+Lo method

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Chinese Physics Letters 2013年第7期30卷 205-209页

作者： masood Yousaf m.A.Saeed Ahmad Radzi mat Isa H.A.Rahnamaye Aliabad m.R.Sahar Department of Physics Faculty of ScienceUniversiti Teknologi MalaysiaSkudai-81310JohorMalaysia Department of Physics Hakim Sabzevari UniversityIran

The highly accurate full-potential linearized augmented plane wave plus local orbital method is employed to calculate the structural,electronic and transport properties of HgIn_(2)S_(4) and ZnIn_(2)S_(4).For ZnIn_(2)S_(4),the calculated In–S bond length is in good agreement with the experimental *** moduli results suggest that ZnIn_(2)S_(4) can afford more compressional effects than HgIn_(2)S_(4).The present study confirms that both HgIn_(2)S_(4) and ZnIn_(2)S_(4) are indirect band gap materials with band gap values of 0.705 eV and 1.533 eV *** localized region existing in the most bottom valance band of both materials splits into states by 1 eV energy difference under the spin orbital coupling *** plots of charge density predict that chemical bonding in these compounds is a mixture of ionic and covalent *** mass results reveal that mobility of charge carriers in ZnIn_(2)S_(4) is greater than that in HgIn_(2)S_(4).

关键词： effect. orbital charge

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An Improved Study of Electronic Band Structure and Optical Parameters of X-Phosphides (X=B, Al, Ga, In) by modified Becke-Johnson Potential

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Communications in Theoretical Physics 2012年第11期58卷 777-784页

作者： masood Yousaf m.A. Saeed R. Ahmed m.m. Alsardia Ahmad Radzi mat Isa A. Shaari Physics Department Faculty of ScienceUniversiti Teknologi MalaysiaUTM Skudai81310 JohorMalaysia

We report the electronic band structure and optical parameters of X-Phosphides （X=B, AI, Ga, In） by first-principles technique based on a new approximation known as modified Becke-Johnson （roB J）. This potential is considered more accurate in elaborating excited states properties of insulators and semiconductors as compared to LDA and GGA. The present calculated band gaps values of BP, AlP, GaP, and InP are 1.867 eV, 2.268 eV, 2.090 eV, and 1.377 eV respectively, which are in close agreement to the experimental results. The band gap values trend in this study is as： E9 （mBJ-GGA/LDA）〉 E9 （GGA）〉 Eg （LDA）. Optical parametric quantities （dielectric constant, refractive index, reflectivity and optical conductivity） which based on the band structure are aiso presented and discussed. BP, AlP, GaP, and InP have strong absorption in between the energy range 4-9 eV, 4-7 ev, 3-7 eV, and 2-7 eV respectively. Static dielectric constant, static refractive index and coefficient of reflectivity at zero frequency, within mBJ-GGA, are also calculated. BP, AIP, GaP, and InP show significant optical conductivity in the range 5.2-10 eV, 4.3-8 eV, 3.5- 7.2 eV, and 3.2-8 eV respectively. The present study endorses that the said compounds can be used in opto-electronic applications, for different energy ranges.

关键词： DFT FP-LAPW + lo mBJ-GGA optical properties electronic structure

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Electronic Band Structure and Optical Parameters of Spinel Snmg_(2)O_(4) by modified Becke–Johnson Potential

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Chinese Physics Letters 2012年第10期29卷 193-197页

作者： masood Yousaf m.A.Saeed Ahmad Radzi mat Isa Amiruddin Shaari H.A.Rahnamaye Aliabad Physics Department Faculty of ScienceUniversiti Teknologi MalaysiaSkudai-81310JohorMalaysia Department of Physics Hakim Sabzevari UniversityIran

The electronic band structure and optical parameters of Snmg_(2)O_(4) are investigated by the first-principles technique based on a new potential approximation known as modified Becke–Johnson(mBJ).The direct band gap values by LDA,GGA and EV-GGA are underestimated significantly as compared to mBJ-GGA,which generally provides the results comparable to the experimental ***,the present band gap value(4.85 eV)using mBJ-GGA is greatly enhanced to the previous value by EV-GGA(2.823 eV).The optical parametric quantities(dielectric constant,index of refraction,reflectivity,optical conductivity and absorption coefficient)relying on the band structure are presented and *** first critical point(optical absorption's edge)in Snmg_(2)O_(4) occurs at about 4.85 eV.A strong absorption region is observed,extending between 5.4 eV to 25.0 *** Snmg_(2)O_(4),static dielectric constantε1(0),static refractive index n(0),and the magnitude of the coefficient of reflectivity at zero frequency R(0)are 2.296,1.515 and 0.0419,*** optoelectronic properties indicate that this material can be successfully used in optical devices.

关键词： absorption reflectivity dielectric

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Predicting grain size-dependent superplastic properties in friction stir processed ZK30 magnesium alloy with machine learning methods

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Journal of magnesium and Alloys 2024年第5期12卷 1931-1943页

作者： Farid Bahari-Sambran Fernando Carreno C.m.Cepeda-Jiménez Alberto Orozco-Caballero Physical metallurgy Department CENIM-CSICAv.Gregorio del Amo 828040 MadridSpain Department of mechanical Engineering Chemistry and Industrial DesignPolytechnic University of MadridRonda de Valencia 328012MadridSpain

The aim of this work is to predict,for the first time,the high temperature flow stress dependency with the grain size and the underlaid deformation mechanism using two machine learning models,random forest(RF)and artificial neural network(ANN).With that purpose,a ZK30 magnesium alloy was friction stir processed(FSP)using three different severe conditions to obtain fine grain microstructures(with average grain sizes between 2 and 3μm)prone to extensive superplastic *** three friction stir processed samples clearly deformed by grain boundary sliding(GBS)deformation mechanism at high *** maximum elongations to failure,well over 400% at high strain rate of 10^(-2)s^(-1),were reached at 400℃ in the material with coarsest grain size of 2.8μm,and at 300℃ for the finest grain size of 2μ***,the superplastic response decreased at 350℃ and 400℃ due to thermal instabilities and grain coarsening,which makes it difficult to assess the operative deformation mechanism at such *** work highlights that the machine learning models considered,especially the ANN model with higher accuracy in predicting flow stress values,allow determining adequately the superplastic creep behavior including other possible grain size scenarios.

关键词： machine learning Artificial intelligence magnesium alloys Superplasticity Friction stir processing Grain coarsening

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A statistical model to predict total column ozone in Peninsular malaysia

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Frontiers of Earth Science 2016年第1期10卷 63-73页

作者： K. C. TAN H. S. LIm m. Z. mat JAFRI School of Physics Universiti Sains Malaysia Penang 11800 Malaysia

This study aims to predict monthly columnar ozone in Peninsular malaysia based on concentrations of several atmospheric gases. Data pertaining to five atmo- spheric gases （CO2, 03, CH4, NO2, and H2O vapor） were retrieved by satellite scanning imaging absorption spectro- metry for atmospheric chartography from 2003 to 2008 and used to develop a model to predict columnar ozone in Peninsular malaysia. Analyses of the northeast monsoon （NEm） and the southwest monsoon （SWm） seasons were conducted separately. Based on the Pearson correlation matrices, columnar ozone was negatively correlated with HzO vapor but positively correlated with COz and NO2 during both the NEm and SWm seasons from 2003 to 2008. This result was expected because NO/is a precursor of ozone. Therefore, an increase in columnar ozone concentration is associated with an increase in NO2 but a decrease in H/O vapor. In the NEm season, columnar ozone was negatively correlated with H20 （-0.847）, NO2 （0.754）, and CO2 （0.477）; columnar ozone was also negatively but weakly correlated with CH4 （-0.035）. In the SWm season, columnar ozone was highly positively correlated with NO2 （0.855）, CO2 （0.572）, and CH4（0.321） and also highly negatively correlated with H2O（-0.832）. Both multiple regression and principal component analyses were used to predict the columnar ozone value in Peninsular malaysia. We obtained the best-fitting regression equations for the columnar ozone data using four independent variables. Our results show approxi- mately the same R value （≈0.83） for both the NEm and SWm seasons.

关键词： ozone SCIAmACHY principal componentanalysis Peninsular malaysia

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A Review of Smart Contract Blockchain Based on multi-Criteria Analysis:Challenges and motivations

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Computers, materials & Continua 2023年第5期75卷 2833-2858页

作者： Norah m.Alshahrani m.L.mat Kiah B.B.Zaidan A.H.Alamoodi Abdu Saif Department of Computer System&Technology Faculty of Computer Science&ITUniversity of MalayaLembah Pantai50603Kuala LumpurMalaysia Department of Computer Science Applied CollageKing Khalid UniversityP.O.Box 62569AbhaSaudi Arabia Future Technology Research Center National Yunlin University of Science and Technology123 University RoadSection 3DouliouYunlin64002Taiwan Department of Computing Faculty of ArtsComputing and Creative Industry(FSKIK)Universiti Pendidikan Sultan IdrisTanjung MalimMalaysia Department of Electrical Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur50603Malaysia

A smart contract is a digital program of transaction protocol(rules of contract)based on the consensus architecture of *** contracts with Blockchain are modern technologies that have gained enormous attention in scientific and practical applications.A smart contract is the central aspect of a blockchain that facilitates blockchain as a platformoutside the cryptocurrency *** development of blockchain technology,with a focus on smart contracts,has advanced significantly in recent ***,research on the smart contract idea has weaknesses in the implementation sectors based on a decentralized network that shares an identical *** paper extensively reviews smart contracts based on multi-criteria analysis,challenges and ***,implementing blockchain in multicriteria research is required to increase the efficiency of interaction between users via supporting information exchange with high *** blockchain in the multi-criteria analysis is necessary to increase the efficiency of interaction between users via supporting information exchange and with high confidence,detecting malfunctioning,helping users with performance issues,reaching a consensus,deploying distributed solutions and allocating plans,tasks and joint *** smart contract with decision-making performance,planning and execution improves the implementation based on efficiency,sustainability and ***,the uncertainty and supply chain performance lead to improved users’confidence in offering new solutions in exchange for problems in smart *** includes code analysis and performance,while development performance can be under development.

关键词： Blockchain smart contract mCDm mADm

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