Linear Scaling Method Research Articles

CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations.

CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It is especially aimed at massively parallel and linear-scaling electronic structure methods and state-of-the-art ab initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post-Hartree-Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension.

Shape model constrained scaling improves repeatability of gait data

Decisions made by gait researchers in the generation of kinematic or musculoskeletal models are a potential source of variation between researchers, leading to variable model outcomes. Statistical shape models can accurately predict bone geometry and have the potential to improve the repeatability of clinical gait analysis. The purpose of this study was to determine if using a shape model to scale segment length and joint centre locations would improve repeatability of kinematic and kinetic gait data, compared to linear scaling methods. Five participants completed a motion capture experiment, including a standing static trial and walking at a self-selected speed. Anatomical landmarks from the static trial were used by five experienced researchers to generate kinematic models using two methods; (1) linear scaling in OpenSim, and (2) shape-model scaling using our ‘MAP Client’ scale tool. The resulting models were used to perform an inverse kinematic and inverse dynamic analysis on the walking trials, and variation between researchers was analysed by comparing outputs from the same motion capture trial using different models. Higher variability between researchers was observed in joint angles (P < 0.001), joint moments (P < 0.005), and joint powers (P < 0.005) when using linear scaling, compared to shape-model scaling. Variation was at least three times as large for linearly-scaled models compared to shape-model scaled models. We have identified that linear scaling can lead to substantial variability in gait data across researchers, even with the same experimental data. Using a shape model to scale musculoskeletal models results in repeatable kinematic and kinetic gait data.

The Predictive Value of Glomerular Filtration Rate-Based Scaling of Pediatric Clearance and Doses for Drugs Eliminated by Glomerular Filtration with Varying Protein-Binding Properties.

IntroductionFor drugs eliminated by glomerular filtration (GF), clearance (CL) is determined by GF rate (GFR) and the unbound fraction of the drug. When predicting CL of GF-eliminated drugs in children, instead of physiologically based pharmacokinetic (PBPK) methods that consider changes in both GFR and protein binding, empiric bodyweight-based methods are often used. In this article, we explore the predictive value of scaling using a GFR function, and compare the results with linear and allometric scaling methods for drugs with different protein-binding properties.MethodsFirst, different GFR maturation functions were compared to identify the GFR function that would yield the most accurate GFR predictions across the pediatric age range compared with published pediatric inulin/mannitol CL values. Subsequently, the accuracy of pediatric CL scaling using this GFR maturation function was assessed and compared with PBPK CL predictions for hypothetical drugs binding, to varying extents, to serum albumin or α-acid glycoprotein across the pediatric age range. Additionally, empiric bodyweight-based methods were assessed.ResultsThe published GFR maturation functions yielded comparable maturation profiles, with the function reported by Salem et al. leading to the most accurate predictions. On the basis of this function, GFR-based scaling yields reasonably accurate (percentage prediction error ≤ 50%) pediatric CL values for all drugs, except for some drugs highly bound to AGP in neonates. Overall, this method was more accurate than linear or 0.75 allometric bodyweight-based scaling.ConclusionWhen scaling CL and dose by GFR function, maturational changes in plasma protein concentrations impact GF minimally, making this method a superior alternative to empiric bodyweight-based scaling.Electronic supplementary materialThe online version of this article (10.1007/s40262-020-00890-2) contains supplementary material, which is available to authorized users.

Spatio-temporal evaluation of various global circulation models in terms of projection of different meteorological drought indices

During the coming years, a dramatic increase is expected in the number of drought events mainly due to climate change. In this study, the spatio-temporal variations of duration and intensity of drought events during two 30-year periods in the future (2040–2069 and 2070–2099) together with the reference period (1971–2000) were investigated based on the impacts of climate change. Three drought indices including the Standardized Precipitation Index, the China Z Index, and the Statistical Z Score were calculated from the dynamically downscaled precipitation data from the outputs of GFDL-ESM2M, HadGEM2-ES, and MPI-ESM-MR general circulation models (GCMs) under RCP4.5 and RCP8.5 scenarios over the Western Black Sea (WBS) and the Euphrates–Tigris (ET) basins in Turkey. The biases in the GCMs' precipitation were corrected using the linear scaling method. Additionally, the Mann–Kendall trend test was adapted to the values of drought indices to detect the trend. The results of the study showed that there is no meaningful variation between the different drought indices and also the outputs of various GCMs in terms of drought properties. On the other hand, based on the drought indices values calculated from the outputs of all GCMs, it was found that drought duration and intensity will increase during the current century. Additionally, it was concluded that by taking the spatial distribution of drought properties over the basins into the account, there is a slight relationship between the geographical elevation and drought properties over the WBS and the ET basins.

Effect of Computed Tomography Slice Thickness on Calculated Coronary Artery Calcium Score in the Assessment of Possible Radiation Induced Cardiac Toxicity

Studies have suggested that the occurrence of radiation induced cardiac toxicity in breast cancer patients is significantly higher in women with pre-existing cardiac risk factors. Therefore, it is important to quantify the relationship between radiation induced cardiac toxicity and a measurable level of pre-existing cardiac risk such as the patient’s coronary artery calcium Agatston score. To assess the extent of coronary artery calcium present in the walls of patients’ coronary arteries before they received treatment, Agatston scores may be calculated using thoracic CT scans acquired for external beam radiotherapy planning. However, these planning CT scans can vary in slice thickness and resolution, thus complicating the calculation of calcium scores using scans with slice thicknesses other than the 3mm routinely employed for traditional Agatston scoring. The objective of this project is to quantify the effect of varying CT scan slice thickness in the calculation of coronary artery calcium scores so that a method of standardization might be developed. This is accomplished through the design, fabrication, and scanning of an anthropomorphic phantom featuring calcium inserts of varying sizes. Analysis of how the scores change with increasing slice thickness is used to construct a simple linear scaling method of standardization which corrects for varying slice thickness and the resulting partial volume distortions. A linear scaling method was successfully validated for the calculation of coronary artery calcium Agatston scores across a range of slice thicknesses increasing from 0.625 mm to 5 mm. Scaling is applied by multiplying the score by the slice thickness and dividing by 3 mm. This method is potentially applicable in any clinical or research endeavour which calls for retroactive cardiac calcium quantification. With a simple linear scaling method, external beam radiation therapy planning CT scans with slice thicknesses ranging from 0.625 mm to 5 mm can be used to calculate coronary artery calcium Agatston scores and thereby measure a patient’s level of cardiac risk before treatment.

Reconstruction of the lower limb bones from digitised anatomical landmarks using statistical shape modelling

BackgroundBone shapes strongly influence force and moment predictions of kinematic and musculoskeletal models used in motion analysis. The precise determination of joint reference frames is essential for accurate predictions. Since clinical motion analysis typically does not include medical imaging, from which bone shapes may be obtained, scaling methods using reference subjects to create subject-specific bone geometries are widely used. Research questionThis study investigated if lower limb bone shape predictions from skin-based measurements, utilising an underlying statistical shape model (SSM) that corrects for soft tissue artefacts in digitisation, can be used to improve conventional linear scaling methods of bone geometries. MethodsSSMs created from 35 healthy adult femurs and tibiae/fibulae were used to reconstruct bone shapes by minimising the distance between anatomical landmarks on the models and those digitised in the motion laboratory or on medical images. Soft tissue artefacts were quantified from magnetic resonance images and then used to predict distances between landmarks digitised on the skin surface and bone. Reconstruction results were compared to linearly scaled models by measuring root mean squared distances to segmented surfaces, calculating differences of commonly used anatomical measures and the errors in the prediction of the hip joint centre. ResultsSSM reconstructed surface predictions from varying landmark sets from skin and bone landmarks were more accurate compared to linear scaling methods (2.60–2.95 mm vs. 3.66–3.87 mm median error; p < 0.05). No significant differences were found between SSM reconstructions from bony landmarks and SSM reconstructions from digitised landmarks obtained in the motion lab and therefore reconstructions using skin landmarks are as accurate as reconstructions from landmarks obtained from medical images. SignificanceThese results indicate that SSM reconstructions can be used to increase the accuracy in obtaining bone shapes from surface digitised experimental data acquired in motion lab environments.

Highly Efficient, Linear-Scaling Seminumerical Exact-Exchange Method for Graphic Processing Units.

We present a highly efficient and asymptotically linear-scaling graphic processing unit accelerated seminumerical exact-exchange method (sn-LinK). We go beyond our previous central processing unit-based method (Laqua, H.; Kussmann, J.; Ochsenfeld, C. J. Chem. Theory Comput. 2018, 14, 3451-3458) by employing our recently developed integral bounds (Thompson, T. H.; Ochsenfeld, C. J. Chem. Phys. 2019, 150, 044101) and high-accuracy numerical integration grid (Laqua, H.; Kussmann, J.; Ochsenfeld, C. J. Chem. Phys. 2018, 149, 204111). The accuracy is assessed for several established test sets, providing errors significantly below 1mEh for the smallest grid. Moreover, a comprehensive performance analysis for large molecules between 62 and 1347 atoms is provided, revealing the outstanding performance of our method, in particular, for large basis sets such as the polarized quadruple-zeta level with diffuse functions.

Spectroscopic, quantum chemical, QTAIM analysis, molecular dynamics simulation, docking studies and solvent effect of pyridin-2-yl oxyacetic acid herbicide and its derivatives

The density functional theory calculations and spectroscopic characterization (FTIR, FT- Raman, 1H, 13C NMR and ultraviolet–visible) of the herbicide compound Triclopyr (TCP) on monomeric and dimeric model is carried out. Its computational results are correlated with two pyridine derivative compounds FPA and FOP. The specific solvent effect of monomer with water complexes (TCPW, FPAW and FOPW) formed by hydrogen bonding interactions are investigated at the B3LYP 6-311G (d,p) level. Potential energy surface (PES) scanning of above compounds has been performed to discover the most stable conformer. The distribution of the vibrational bands are carried out with the help of normal coordinate analysis (NCA) and the resulting harmonic wavenumbers are scaled by using Wavenumber–Linear Scaling (WLS) method. The nature of inter and intramolecular hydrogen bonds are analyzed using NBO, QTAIM and Hirshfeld surface analysis. Furthermore herbicidal activity is confirmed on the compounds with molecular docking studies and molecular dynamic simulations (MDS).

Large-scale excited-state calculation using dynamical polarizability evaluated by divide-and-conquer based coupled cluster linear response method.

This study attempted to propose an efficient scheme at the coupled cluster linear response (CCLR) level to perform large-scale excited-state calculations of not only local excitations but also nonlocal ones such as charge transfers and transitions between delocalized orbitals. Although standard applications of fragmentation techniques to the excited-state calculations brought about the limitations that could only deal with local excitations, this study solved the problem by evaluating the excited states as the poles of dynamical polarizability. Because such an approach previously succeeded at the time-dependent density functional theory level [H. Nakai and T. Yoshikawa, J. Chem. Phys. 146, 124123 (2017)], this study was considered as an extension to the CCLR level. To evaluate the dynamical polarizability at the CCLR level, we revisited three equivalent formulas, namely, coupled-perturbed self-consistent field (CPSCF), random phase approximation (RPA), and Green's function (GF). We further extended these formulas to the linear-scaling methods based on the divide-and-conquer (DC) technique. We implemented the CCLR with singles and doubles (CCSDLR) program for the six schemes, i.e., the standard and DC-type CPSCF, RPA, and GF. Illustrative applications of the present methods demonstrated the accuracy and efficiency. Although the standard three treatments could exactly reproduced the conventional frequency-domain CCSDLR results, their computational costs were commonly higher than that of the conventional ones due to large amount of computations for individual frequencies of the external electric field. The DC-type treatments, which approximately reproduced the conventional results, could achieve quasilinear scaling computational costs. Among them, DC-GF was found to exhibit the best performance.

Типология сельских территорий по уровню развития инженерной инфраструктуры

The relevance of the study is that the poor quality and fragmentary engineering arrangement of rural settlements negatively affects the demographics of rural areas. The aim of the study is to develop a comprehensive methodology for assessing the impact of the state of engineering infrastructure of rural settlements on the demography of rural territories, which is an integral indicator of the proposed rural population density. The paper proposes a method for a comprehensive assessment of rural areas by the level of development of engineering infrastructure. The composite index of rural engineering infrastructure development aggregates seven private statistical indicators calculated for each region of Russia in 2018 and normalized using the linear scaling method. The main difference between the author’s method and the previously conducted research is the combination of the results of ranking Russian regions by the level of development of engineering infrastructure in rural areas with grouping by the density of the rural population. The novelty of the proposed approach is associated with the formation of two-dimensional groupings of rural areas, where population density is regarded as the primary grouping characteristics, and the level of development of engineering infrastructure as a secondary grouping characteristic that gave the possibility to evaluate the correlation between the level of development of social and engineering infrastructure of rural territories and their people. The results of the correlation analysis indicate a moderate relationship between the density of the rural population and the level of development of engineering infrastructure in rural areas. In practical terms, the typology formed serves as an objective basis for identifying and comparing growth points and priorities for sustainable spatial development of rural territories in the future, which creates prerequisites for the unification of state approaches to strategic planning and management of socio-economic development of rural territories of the Russian Federation and regions. The directions of further research are related to the development of the proposed approach in terms of comprehensive coverage of other components of socio-economic development of rural areas (demography, economy, agriculture, social infrastructure) for a more complete assessment of their impact on the rural population density.

Multi-Scale CNN for Fine-Grained Image Recognition

Most conventional fine-grained image recognitions are based on a two-stream model of object-level and part-level CNNs, where the part-level CNN is responsible for learning the object-parts and their spatial relationships. To train the part-level CNN, we first need to separate parts from an object. However, there exist sub-level objects with no distinctive and separable parts. In this paper, a multi-scale CNN with a baseline Object-level and multiple Part-level CNNs is proposed for the fine-grained image recognition with no separable object-parts. The basic idea to train different CNNs of the multi-scale CNNs is to adopt different scales in resizing the training images. That is, the training images are resized such that the entire object appears as much as possible for the Object-level CNN, while only a local part of the object is to be included for the Part-level CNN. This scale-specific image resizing approach requires a scale-controllable parameter in the image resizing process. In this paper, a scale-controllable parameter is introduced for the linear-scaling and random-cropping method. Also, a line-based image resizing method with a scale-controllable parameter is employed for the part-level CNNs. The proposed multi-scale CNN is applied to a food image classification, which belongs to a fine-grained classification problem with no separable object-parts. Experimental results on the public food image datasets show that the classification accuracy improves substantially when the predicted scores of the multi-scale CNN are fused together. This reveals that the object-level and part-level CNNs work harmoniously in differentiating subtle differences of the sub-level objects.

Vibrational spectra, hydrogen bonding analysis and herbicidal activity study of mefenacet: A DFT approach

Abstract The present study aims to provide deeper knowledge of structural, spectroscopic conformational analysis and herbicidal activity of the rice paddy herbicide Mefenacet on monomeric (MM) and dimeric (MD) model. The specific solvent effect of MM with water molecule (MM-H2O) has been investigated at the B3LYP/6-311G (d,p) level in order to observe the hydrogen bonding interaction. The fundamental modes of vibration are addressed by experimental FT-IR (400-4000 cm−1) and FT-Raman (50-3500 cm−1) techniques. The vibrational spectrum is performed with normal coordinate analysis (NCA) and the wavenumbers are scaled by using Wavenumber–Linear Scaling (WLS) method in order to identify the herbicidal active mode of vibration. Additionally, Quantum Theory of Atoms in Molecules (QTAIM) describing the electronic structure of the monomer and dimer molecules by means of various topological parameters to scrutinize the herbicidal active region. Potential energy surface (PES) scanning of MM with eight different dihedral angles has been performed to discover the most stable conformer, which leads to the herbicidal activity. The UV and global reactivity descriptors have also been carried out to check the herbicidal activity. Hirshfeld surface analysis of MD is done to confirm the existence of intermolecular interactions. Docking studies are performed to predict the herbicidal active site. Moreover, the stability of MM has been evaluated via Molecular Dynamic Simulations (MDS).

Assessment of Future Climate Change Projections Using Multiple Global Climate Models

Nowadays, the hydrological cycle which alters river discharge and water availability is affected by climate change. Therefore, the understanding of climate change is curial for the security of hydrologic conditions of river basins. The main purpose of this study is to assess the projections of future climate across the Upper Ayeyarwady river basin for its sustainable development and management of water sector for this area. Global Ten climate Models available from CMIP5 represented by the IPCC for its fifth Assessment Report were bias corrected using linear scaling method to generate the model error. Among the GCMs, a suitable climate model for each station is selected based on the results of performance indicators (R2 and RMSE). Future climate data are projected based on the selected suitable climate models by using future climate scenarios: RCP2.6, RCP4.5, and RCP8.5. According to this study, future projection indicates to increase in precipitation amounts in the rainy and winter season and diminishes in summer season under all future scenarios. Based on the seasonal temperature changes analysis for all stations, the future temperature are predicted to steadily increase with higher rates during summer than the other two seasons and it can also be concluded that the monthly minimum temperature rise is a bit larger than the maximum temperature rise in all seasons.

Stochastic Vertex Corrections: Linear Scaling Methods for Accurate Quasiparticle Energies.

New stochastic approaches for the computation of electronic excitations are developed within the many-body perturbation theory. Three approximations to the electronic self-energy are considered: G0W0, G0W0tc, and G0W0tcΓX. All three methods are formulated in the time domain, and the latter two incorporate nonlocal vertex corrections. In the case of G0W0tcΓX, the vertex corrections are included both in the screened Coulomb interaction and in the expression for the self-energy. The implementation of the three approximations is verified by comparison to deterministic results for a set of small molecules. The performance of the fully stochastic implementation is tested on acene molecules, C60 and PC60BM. The vertex correction appears crucial for the description of unoccupied states. Unlike conventional (deterministic) approaches, all three stochastic methods scale linearly with the number of electrons.

A Linear-Scaling Method for Noncovalent Interactions: An Efficient Combination of Absolutely Localized Molecular Orbitals and a Local Random Phase Approximation Approach.

A novel method for the accurate and efficient calculation of interaction energies in weakly bound complexes composed of a large number of molecules is presented. The new ALMO+RPAd method circumvents the prohibitive scaling of coupled cluster singles and doubles while still providing similar accuracy across a diverse range of weakly bound chemical systems. Linear-scaling procedures for the Fock build are given utilizing absolutely localized molecular orbitals (ALMOs), resulting in the a priori exclusion of basis set superposition errors. A bespoke data structure and algorithm using density fitting are described, leading to linear scaling for the storage and computation of the two-electron integrals. Electron correlation is included through a new, linear-scaling pairwise local random phase approximation approach, including exchange interactions, and decomposed into purely dispersive excitations (RPAxd). Collectively, these allow meaningful decomposition of the interaction energy into physically distinct contributions: electrostatic, polarization, charge transfer, and dispersion. Comparison with symmetry-adapted perturbation theory shows good qualitative agreement. Tests on various dimers and the S66 benchmark set demonstrate results within 0.5 kcal mol-1 of coupled cluster singles and doubles results. On a large cluster of water molecules, we achieve calculations involving over 3500 orbital and 12,000 auxiliary basis functions in under 10 min on a single CPU core.

Selection of general circulation models for the projections of spatio-temporal changes in temperature of Borneo Island based on CMIP5

A study has been conducted to evaluate the changes in temperature of Borneo Island for different representative concentration pathway (RCP) scenarios through statistical downscaling of an ensemble of general circulation models (GCMs) selected using entropy-based methods. A combination of past-performance and envelope approaches was used for the selection of GCM ensemble from a pool of 20 Coupled Model Intercomparison Project Phase 5 (CMIP5) GCMs. Ranking of the GCMs was done separately at each grid point by using three entropy-based feature selection methods. Climate Research Unit (CRU) gridded temperature data was used as dependent variable and the simulated temperature of different GCMs for the period 1961–2005 was used as independent variable for the selection of GCMs. The scores obtained by the GCMs at different CRU grids were aggregated using compromise programming method and then ranked for entire Borneo Island using group decision-making method. Linear scaling method was applied to remove the biases in GCMs, followed by random forest (RF)–based regression method to generate multi-model ensemble projections. The results revealed that FIO-ESM, MRI-CGCM3, GFDL-CM3, and IPSL-CM5A-MR are the most suitable GCMs for the projection of temperature in the study area. The projection of temperature using the selected GCMs indicated increase in temperature in the Borneo Island, particularly in the southwest regions. The minimum temperature was projected to increase more (3.3 to 4.7 °C) compared with maximum temperature (3.0 to 4.6 °C) and thus, the diurnal temperature range (DTR) was projected to decrease gradually until the end of the twenty-first century. Increase in average and maximum temperatures was projected more during the southwest (SW) monsoon compared with the northeast (NE) monsoon. The study indicated that large increase in temperature and decrease in DTR would have significant impact on ecology and bio-environment of the island which have one of the dense ecological diversities in the world.

Evaluation and application of a SWAT model to assess the climate change impact on the hydrology of the Himalayan River Basin

The water resources of Tamor River Basin in the eastern Himalayas of Nepal is heavily tapped for agricultural water use and hydropower production. Several studies show that the hydrology of the Himalayan River Basins is vulnerable to climate change. Topographical variations, data scarcity and its complex climate have always been barriers to achieving realistic simulation of the hydrological regime in the Himalayan River Basins, and the Tamor River Basin is no different. In hydrological response unit (HRU) based models, fixing the number of HRUs and sub-basins has a tendency towards confusion. This is especially true in regions with altitudinal and climatic variations. Therefore, this study aims to evaluate the SWAT model performance uncertainty associated with the number of sub-basins, HRUs, and elevation bands and quantify the impact of climate change on streamflows in the Tamor River Basin. Future climate scenarios were developed for three different time frames, the 2030s, 2060s, and 2080s, based on an ensemble of Coupled Model Intercomparison Project Phase 5 (CMIP5) and four Regional Climate Models (RCMs) under the Representative Concentration Pathways (RCP4.5 and RCP8.5) scenarios. The linear scaling method (LSM) of bias correction was used to bias-correct the climate data and then fed into the SWAT model to simulate the future streamflows of the basin. An increase in the annual average maximum temperature (+4 °C) and minimum temperature (+5.5 °C), and a decrease in precipitation (−4.5%) is projected by the end of the twenty-first century under RCP8.5 scenarios. The study found that the future climate could decrease the streamflow by over 8.5% during the twenty-first century under RCP8.5 scenarios. The results show elevation bands (EBs) to be more significant compared to HRUs and sub-basins (SBs) in getting a robust hydrological model in the Himalayan region. The estimates prepared in this study would be beneficial for hydropower developers, planners and policymakers, and water resource managers in developing adaptation strategies to offset the negative impact of climate change in the Tamor River Basin.

Evaluation of precipitation measurements methods under field conditions during a summer season: A comparison of the standard rain gauge with a weighable lysimeter and a piezoelectric precipitation sensor

Current precipitation measurements are conducted largely by simple automatic rain gauges. Despite being error-prone and sometimes of questionable accuracy, the procedure is still widely used. In recent years new possibilities have emerged, which are based on different measuring principles. Although the application of alternative devices is increasing, its use in research is limited. In this study, precipitation measurements by different devices were compared, and systematic errors caused by individual characteristics were corrected. Data were collected by means of a monitoring network, which included a piezoelectric precipitation sensor mounted at 2.3 m, a standard tipping bucket at 1 m, and a weighable gravitation lysimeter at ground level. As measurements at ground level are considered as optimum, the records of the lysimeter were thereby determined as a reference. The results showed that precipitation measured by elevated rain gauges differed in total between −6.8% and +35% compared to rainfall measured by the lysimeter. The records correlated well, but the analyses indicated a strong influence of the precipitation intensity on the recorded amount of precipitation. The deviations between values of the rain gauges and those of the lysimeter increased with rainfall intensity. In general, the tipping bucket demonstrated negative error values and indicated an underestimation of precipitation compared to records at ground level, whereas the piezoelectric precipitation sensor showed an overestimation by highly positive error values. A subsequent precipitation correction through the linear scaling method improved significantly the raw data of the rain gauges.

Structural activity (monomer and dimer), spectroscopic analysis, chemical reactivity, fungicidal activity and molecular dynamics simulation of phenyl benzamide fungicides: A combined experimental and theoretical approach

The present study aims to provide deeper knowledge of the structural activity, spectroscopic analysis, chemical reactivity and fungicidal activity of phenyl benzamide fungicides: flutolanil and mepronil based on monomer and dimer model with the aid of experimental and computational methods. The distribution of the vibrational bands are carried out with the help of normal coordinate analysis (NCA). The resulting harmonic wavenumbers are scaled by using Wavenumber Linear Scaling method (WLS). The nature of the hydrogen bonds are characterized by NBO analysis. The evaluated HOMO and LUMO energies indicate the chemical stability of the molecules. The time dependent density functional theory is used to find the various electronic transitions and their nature within the molecule. The molecular orbital contributions are studied by using TDOS spectral analysis. The molecular electrostatic potential (MESP) and global reactivity descriptor parameters are also performed. The 1H and 13C NMR spectra are recorded. The stable conformers of flutolanil and mepronil have been identified by potential energy surface scan analysis. The binding affinity and hydrogen bond interaction between the selected compounds and the target protein are evaluated using molecular docking studies. The pose with highest interaction energy and hydrogen bond interaction is further analyzed using molecular dynamics studies to understand the effect of ligands on conformational changes of protein and the stability of protein ligand complex. The invitro analysis has been performed against two fungal pathogens, Aspergillus niger and Candida albicans.

Deep Binary Reconstruction for Cross-Modal Hashing

To satisfy the huge storage space and organization capacity requirements in addressing big multimodal data, hashing techniques have been widely employed to learn binary representations in cross-modal retrieval tasks. However, optimizing the hashing objective under the necessary binary constraint is truly a difficult problem. A common strategy is to relax the constraint and perform individual binarizations over the learned real-valued representations. In this paper, in contrast to conventional two-stage methods, we propose to directly learn the binary codes, where the model can be easily optimized by a standard gradient descent optimizer. However, before that, we present a theoretical guarantee of the effectiveness of the multimodal network in preserving the inter- and intra-modal consistencies. Based on this guarantee, a novel multimodal deep binary reconstruction model is proposed, which can be trained to simultaneously model the correlation across modalities and learn the binary hashing codes. To generate binary codes and to avoid the tiny gradient problem, a novel activation function first scales the input activations to suitable scopes and, then, feeds them to the tanh function to build the hashing layer. Such a composite function is named adaptive tanh . Both linear and nonlinear scaling methods are proposed and shown to generate efficient codes after training the network. Extensive ablation studies and comparison experiments are conducted for the image2text and text2image retrieval tasks; the method is found to outperform several state-of-the-art deep-learning methods with respect to different evaluation metrics.