Classification of petroleum origin and integrity by FTIR by FJ. Guzmán-Osorio, VI. Domínguez-Rodríguez, RH. Adams, CE. Lobato-García, A. Guerrero-Peña, JR. Barajas-Hernández

“…The canonic functions derived from the discriminate analysis had correlation coefficients of 0.994, 0.900, and 0.867, among the variables studied and the classification factor. …”
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IRAQ'S AGRICULTURAL ECONOMY AND THE REALITY OF THE VARIABLRS AND THE RESULTS OBJECTIVE CURRICULUM AND QUANTITATIVE ANALYSIS FOR THE PERIOD (1990-2011) by Salim Al-Nuaimy, Mahasen. M Al-Jeboury

“…The research aims to formulate sober policies and practical actions contribute to adjust the course of the agricultural sector and to achieve its goals, which will make it easier to raise production and productivity, Variables of agricultural sector were agricultural work, capital accumulation agricultural, technical mechanism, technical chemical, agricultural loans, agricultural export, import of agricultural, national income, domestic consumption, the cultivatedareas, that have been expressed as (policies of productivity and investment, marketing and price) where its impact was deare on the growth of the agricultural sector and overall productivity during (1990-2010) and the development process and increase production and productivity in the agricultural sector associated with economic, social and institutional multiple and overlapping factors that effects the forms and varying proportions in its impact on agricultural output, which had been measured under function producing an aggregate of variables agricultural policy and its contribution to productivity growth as well as measuring productivity elements total (TFP) by using index (Malmaquist) depending on the (DEAP). …”
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Quality control of DEMs using check surfaces by Francisco Javier Ariza-López, José Rodríguez-Avi

“…This paper proposes the use of check surfaces or ‘patches’ for the assessment of Digital Elevation Model (DEM) elevations and derived variables (e.g. slope and aspect). We work with grid-type DEMs, and the patches are implemented through square windows of different sizes. …”
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Neuroscience-informed nomogram model for early prediction of cognitive impairment in Parkinson's disease by Sudharshan Putha, Swaroop Reddy Gayam, Bhavani Prasad Kasaraneni, Krishna Kanth Kondapaka, Sateesh Kumar Nallamala, Praveen Thuniki

“…The least absolute shrinkage and selection operator (LASSO) algorithm was applied to identify highly correlated clinical variables influencing cognitive function. Subsequently, these variables were integrated into a visualized nomogram model to facilitate early prediction of cognitive impairment (CI) risk. …”
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Allometric equation for estimating aboveground biomass of Acacia-Commiphora forest, southern Ethiopia by Wondimagegn Amanuel, Chala Tadesse, Moges Molla, Desalegn Getinet, Zenebe Mekonnen

“…Data was transformed to logarithmic functions and multiple linear regression techniques were used to develop model to estimate aboveground biomass (AGB). …”
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A Brief Political Economy of Energy Subsidies in the Middle East and North Africa by Laura El-Katiri, Bassam Fattouh

“…While it is clear that energy subsidy reform will not be the only variable at play, its potential socio-economic dividends are important factors for enabling some common regional objectives—sustainable fiscal policies, fiscal space to invest in key areas, and a more efficient and equitable distribution of scarce resources—to be achieved, helping to promote a more stable political status quo in the long term. …”
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Optimizing switching sequences in AC-AC converters for enhanced safety and performance in conveyor systems by Velmurugan Dhandapani, Gopinath Balasubramanian

“…Industrial systems require optimized control to maintain efficiency under variable loads. Fault conditions influence power stability and overall system functionality. …”
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Classification of Biological Data using Deep Learning Technique by Azha Javed, Muhammad Javed Iqbal

“…Previous work failed to properly address issues related to the classification of biological sequences i.e. protein including efficient encoding of variable length biological sequence data and implementation of deep learning based neural network models to enhance the performance of classification/ recognition systems. …”
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Haemodynamics-driven developmental pruning of brain vasculature in zebrafish. by Qi Chen, Luan Jiang, Chun Li, Dan Hu, Ji-wen Bu, David Cai, Jiu-lin Du

“…The brain blood vasculature consists of a highly ramified vessel network that is tailored to meet its physiological functions. How the brain vasculature is formed has long been fascinating biologists. …”
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Interpretable machine learning for predicting isolated basal septal hypertrophy. by Lei Gao, Boyan Tian, Qiqi Jia, Xingyu He, Guannan Zhao, Yueheng Wang

“…This is a common echocardiographic finding with a prevalence of approximately 7-20%, which may indicate early structural and functional remodeling of the left ventricle in certain pathologies. …”
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Validation and Discriminant Analysis of the Athens Insomnia Scale in Older Adults by Huseyin Elbi, Melike Batum, Ece Ozlem Oztürk, Merve Vatansever Balcan, Ayşin Kisabay Ak, Hikmet Yilmaz, Omer Aydemir

“…The internal consistency of the AIS was assessed using the Cronbach alpha coefficient. For validity analyses, the scale's structure validity was evaluated using confirmatory factor analysis (CFA). …”
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Correlation between Electrochemical Relaxations and Morphologies of Conducting Polymer Dendrites by Antoine Baron, Enrique H. Balaguera, Sébastien Pecqueur

“…Correlations are established between dispersive capacitances of dendritic morphologies and growth duration, independently from exogenous physical variables: distance, evaporation or aging. Deviation of the anomalous capacitance from the conventional Debye dielectric relaxation can be programmed, as the growth controls the dispersion coefficient of the dendrite's constant-phase elements relaxation. …”
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A DQN-Based Algorithm for Operational Optimization of Freight Trains in Long Steep Downhill Sections by HE Zhiyu, LI Yinan, LI Hui, JI Zhijun

“…The study employed the batch collection of training samples utilizing experience replay and a double-network mechanism, along with the preprocessing of neural network state inputs, and the investigation into feasible regions within the action space using a variable ε-greedy strategy. A loss function based on the value function was then constructed, and network parameters were updated iteratively by a batch gradient descent method. …”
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AngleCam: Predicting the temporal variation of leaf angle distributions from image series with deep learning by Teja Kattenborn, Ronny Richter, Claudia Guimarães‐Steinicke, Hannes Feilhauer, Christian Wirth

“…The plausibility of the predicted leaf angle time series was underlined by its close relationship with environmental variables related to transpiration. The evaluations confirm that AngleCam is a robust and efficient method to track leaf angles under field conditions. …”
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Long-term evolution of the calibration constant on a mobile water vapour Raman lidar by P. Chazette, J. Totems, F. Laly

“…We note that the use of ground-based measurements does not introduce any more uncertainty in the lidar calibration coefficient than vertical profiles obtained by radiosondes or airborne means. …”
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Evaluation of oral health-related quality of life in burn survivors: A cross-sectional study by Hetal Amipara, Rakesh Kain, Shalabh Kumar

“…Purpose: The face, crucial to identity, is susceptible to the functional and psychological impact of burn injuries. …”
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Effect of Gratitude on Mental Health with Mediating Role of Positive and Negative Affect by Malihe Shakerifard, Ali Mohamadzadeh Ebrahimi, Tayebe Rahimi Pordanjani

“…Findings: There was a significant correlation between all variables of the research (p<0.01). The model had a good fit with some modification. …”
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Predicting Kinematic Viscosity and Cetane Number of Diesel- Biodiesel Blend Using Neural Network and Empirical Models by M. yari, Gh. Moradi, M. Abdolmaleki, Sh. Bashiri

“…This study tries to estimate two substantial properties of blend, i.e. kinemattic viscosity (KV) and cetane number (CN), through neural network (NN) and empirical models which use pure properties of biodiesel (kinematic viscosity, boiling point, evaporation point, flash point, pour point, heat of combustion, cloud point, and specific gravity) as independent variables. In this regard, a three-layer feed-forward network with varying input parameters, training algorithms, transfer functions, and hidden neurons has been examined to predict the KV and CN of the diesel-biodiesel blend. …”
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Exercise, Training &amp; Health by Mentz L, Winkert K, Schlegel S, Rohlmann F, Steinacker JM, Treff G

“…To this end, we evaluated it during rowing ergometer testing in elite rowers.Methods: Twenty-three elite rowers of the German National squad (10 female; age: 24.53.5 years) performed an incremental step test on a C2 rowing-ergometer modified with an external reference system (REF) allowing evaluation of stroke-to-stroke variability during rowing ergometer testing.Results: The coefficient of variation (CV) for PREF was 4.7% (95% CI [4.3, 5.3]). …”
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On the approximation of sum of lognormal for correlated variates and implementation. by Asyraf Nadia Mohd Yunus, Nora Muda, Abdul Rahman Othman, Sonia Aïssa

“…In probabilistic modeling across engineering, finance, and telecommunications, sums of lognormal random variables frequently occur, yet no closed-form expression exists for their distribution. …”
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