Population Analysis Methods Research Articles

A new approach to assessing and forecasting the stock of sprat in the Baltic Sea in modern conditions

The aim of this article: analysis of information and software for forecasting of the Baltic Sea sprat stock Sprattus sprattus balticus at 22–32 ICES subdivisions in the context of the suspension of Russia’s activities in the International Council for the Exploration of the Sea (ICES).Methods used: The data of estimates of sprat abundance and biomass by hydroacoustic methods, commercial and biostatistical characteristics of the species were used to assess the stock and predict its catch in the Baltic Sea. Estimation of the sprat stock was carried out using the traditional method of virtual population analysis (VPA) adjusted according to the method of extended survival analysis (XSA) using the internationally approved VPA module software within the framework of ICES and the R software environment. The recruitment calibration program RCT3 (Recruitment calibration) was used for the abundance of recruitment (age 1 year) according to XSA and forecast. A multivariate short-term forecast was carried out at different levels of development of the total allowable catch (TAC) under the MFDP program (Multi Fleet Deterministic Projection). As an alternative, the domestic software «KAFKA» was tested.Novelty: for the first time, estimates of the sprat stock were made in the conditions of limited access of Russian specialists to primary data in ICES in full.Result: modern methodological and informational support of scientific research in the Baltic Sea in the conditions of the suspension of the activities of Russian experts in ICES makes it possible to obtain information in the minimum necessary amount for assessing the stock of sprat and predicting its catch. Modeling with the «KAFKA» software showed satisfactory results.Practical significance: The current level of information support for forecasting the state of the stock and catch of sprat in the Baltic Sea will allow solving a complex of problems of managing this resource in modern conditions.

Population analysis and the effects of Gaussian basis set quality and quantum mechanical approach: main group through heavy element species.

Atomic charge and its distribution across molecules provide important insight into chemical behavior. Though there are many studies on various routes for the determination of atomic charge, there are few studies that examine the broader impact of basis set and quantum method used over many types of population analysis methods across the periodic table. Largely, such a study of population analysis has focused on main-group species. In this work, atomic charges were calculated using several population analysis methods including orbital-based methods (Mulliken, Löwdin, and Natural Population Analysis), volume-based methods (Atoms-in-Molecules (AIM) and Hirshfeld), and potential derived charges (CHELP, CHELPG, and Merz-Kollman). The impact of basis set and quantum mechanical method choices upon population analysis has been considered. The basis sets utilized include Pople (6-21G**, 6-31G**, 6-311G**) and Dunning (cc-pVnZ, aug-cc-pVnZ; n = D, T, Q, 5) basis sets for main group molecules. For the transition metal and heavy element species examined, relativistic forms of the correlation consistent basis sets were used. This is the first time the cc-pVnZ-DK3 and cc-pwCVnZ-DK3 basis sets have been examined with respect to their behavior across all levels of basis sets for atomic charges for an actinide. The quantum methods chosen include two density functional (PBE0 and B3LYP), Hartree-Fock, and second-order Møller-Plesset perturbation theory (MP2) approaches.

Validation of valence bond and molecular orbital models in analyzing the anionic hyperconjugation effect on the stability of alkyl and fluorinated carbanions in gaseous phase

AbstractIn this paper, the anionic hyperconjugation occurring in alkyl and fluorinated carbanions in the gaseous phase is examined at density functional theory (DFT) at the level of theory B3LYP/6‐31++G (d,p) with empirical dispersion‐GD3 theory. First, a contribution of this study is to confirm that the C‐H bond in (CH3)3C‐H (isobutane) is more acidic than the C‐H bonds in CH3CH2‐H (ethane) and (CH3)2CH‐H (propane) based on a comparison of conjugate base stability. Also, the natural population analysis (NPA) and CHELPG methods are well‐performed for calculating charge distribution on carbon atoms, and in contrast, the Mulliken population is better for hydrogen atoms to describe the anionic hyperconjugation in the valence bond (VB) model. The molecular orbital model accounts for the stability order of alkyl and perfluorinated carbanions through the number, strength, and overlap geometry between the lone electron pair on carbon atom and the vicinal σ*C‐H/σ*C‐F orbitals. On the other hand, the utility of VB theory becomes invalid because of the strong inductive effect of the fluorine element and the steric repulsion among CF3 groups in perfluorinated carbanions. Also, the hybridization of the carbon atom holding the lone electron pair can become more s‐character or p‐character dependent on the size of surrounding groups.

Conservation Biology of Endangered Wild Walnut in Tianshan Valley, Xinjiang

Wild walnut belongs to the walnut family in Tianshan Valley of Xinjiang. Tertiary tree species in Central Asia and endangered plant under state protection. Its main distribution areas are as far as the Western Tianshan Mountains and Pamir-Alai Mountains of the former Soviet Union, and it is only distributed in Dekuztala County of Xinjiang, China. It is of great scientific value to study the origin and evolution of cultivated walnut, paleofloristic changes, paleogeography, Tertiary and Quaternary climatic changes. Due to the narrow distribution of wild walnut in Xinjiang, harsh desert conditions, climate change, human disturbance, habitat fragmentation and other factors, wild walnut in Xinjiang is facing the risk of extinction, and it is urgent to carry out research on conservation biology and conservation genetics. In this paper, floristic, community and plant population research and analysis methods were adopted [1][6]. In this paper, the floristic composition, plant ecological type structure, plant climate and soil water characteristics of wild walnut community, age structure of wild walnut population, fluctuation cycle and evolution trend of population age composition, population growth characteristics, phenotypic plasticity of seeds and compound leaves, and biomass allocation were analyzed comprehensively in Xinjiang Nature Reserve. And put forward scientific protection countermeasures.

Rapid Nondestructive Detection of Chlorophyll Content in Muskmelon Leaves under Different Light Quality Treatments

In order to select the light quality suitable for plant growth, a quantitative detection model of chlorophyll content in muskmelon leaves was established to monitor plant growth quickly and accurately. In the paper, muskmelon “Boyang 91” was used as the experimental material, and six different light proportion treatments were set up. Through measuring plant height, stem diameter, number of leaves, nodes, and other growth indicators, in addition to leaf chlorophyll content, the response difference of muskmelon to different light qualities was explored in a plant factory. The hyperspectral imaging technology was used to establish the prediction model for the chlorophyll content of muskmelon. The original spectrum was preprocessed and optimized by five pretreatments, and then the characteristic wavelengths were extracted by six methods. Partial least squares regression (PLSR), least squares support vector machine (LSSVM), and convolutional neural network (CNN) were established for optimal feature wavelength. The results showed that the plant height and stem diameter of the T3 treatment were higher than those of other treatments, and their values were 14.48 (cm) and 5.02 (mm), respectively. The chlorophyll content of the T3 treatment was the highest, and its value was 40.16 (mg/g), which was higher than that of other treatments. Through comprehensive analysis, the T3 treatment (light ratio: 6R/1B/2W, light quantum flux: 360 μmol/(m2·s), photoperiod: 12 h) was optimal. Meanwhile, the average spectral reflectance data of 216 leaf samples were extracted, and the S-G preprocessing method was selected to preprocess the original spectral data (Rc = 0.860, RMSEC = 1.806; Rcv = 0.790, RMSECV = 2.161). By comparing and analyzing the correlation coefficients and root mean square errors of six feature wavelength extraction methods, it was concluded that the variable combination population analysis (VCPA) method had the best model effect for feature wavelength extraction (RP = 0.824, RMSEP = 1.973). Ten characteristic wavelengths ( 396, 409, 457, 518, 532, 565, 687, 691, 701, and 705 nm) extracted by the VCPA method were used to establish the chlorophyll content prediction model, and the chlorophyll content prediction model of S-G-VCPA-CNN had the best performance (Rc = 0.9151, RMSEC = 1.445; Rp = 0.811, RMSEP = 2.055). The results of this study provide data support and a theoretical basis for screening the light ratio of other crops, and also present technical support for online monitoring of crop growth in plant factories.

Predicting IoT failures with Bayesian workflow

IoT networks are so voluminous that they cannot be treated as individual devices, but as populations. Main aim of the paper is to create a comprehensive method for predicting failures taking device variance into consideration. We propose using data fusion of happenstance observations (resets and failures) to better estimate device parameters. We propose using methods of population analysis in Bayesian statistics to estimate failure times investigating only a part of the population. For this purpose, we use multilevel hierarchical Bayesian model and provide it with post stratification. We propose model assumptions, construct the model and evaluate it, and perform computations using Hamiltonian Monte Carlo. This method is known as the Bayesian workflow. We have analyzed three different models showing that, in case of small device variance, it can be ignored, or at least compensated, while significant differences require hierarchical modeling. We also show that hierarchical model shows significant robustness to a small amount of data. We have shown attractiveness of Bayesian approach to modeling failures of IoT devices. Ability to diagnose and tune models, and assure their computational fidelity is a great advantage of Bayesian workflow.

A Quantum Mechanical Viewpoint on Structural Stability of the Smallest Hydrated Sulfate Cluster [SO4(H2O)3]2-

Being the most kosmotropic type anion, SO 4 2 - shows a very strong affinity towards sequential hydration, and hence undergoes immediate stabilization via differently sized hydrated clusters [SO 4 (H 2 O) n ] 2− , n ≤ 80 in solution state. Interestingly, the smallest yet stable hydrated cluster detected through the advanced experimental techniques is [SO 4 (H 2 O) 3 ] 2− with hydration number n = 3. Despite its ubiquity in many sulfate enriched aqueous systems, the concerned electronic structure and structural stability reported so far are mostly based on the position of atomic nuclei in the theoretically produced low energy molecular geometry, which is, however, not regarded as a quantitative approach for depicting chemical bonding and structural entity in respect to electron density distributions around atoms and bonds between the atoms. In this study, the molecular orbitals (MOs) and Mulliken population analysis methods are used to extract chemical bond related information of [SO 4 (H 2 O) 3 ] 2− from its DFT derived molecular wavefunctions ( ) and then total molecular electron density surface (TMEDS), MOs iso-surfaces, and contour lines are deeply analyzed prior to describe how these EDSs actually provide detailed insights into the orbital interactions, atomic bonding, and structural stability. It is found that [SO 4 (H 2 O) 3 ] 2− ion stabilizes with (a) a closed 3D structural entity and a realistic distribution of electron cloud around the specific atoms and bonds, (b) a delocalized type electron density, and (c) an orbital type bonding interaction between the atoms. Besides these, a quantitatively measured electron amplitudes and the specific type bonding interactions make that hydrated structure quantum mechanically feasible.

Variable selection for the determination of the soluble solid content of potatoes with surface impurities in the visible/near-infrared range

Non-destructive quality assessment of the inner content of potatoes is a key challenge in automatic grading of agricultural quality, especially when potatoes have surface impurities. This study compares different partial least-square regression (PLSR) models for the prediction of soluble solid content (SSC) of potatoes under conditions of surface cleanliness and surface impurities. Smoothing and spectral preprocessing with first-order derivatives and variable sorting for normalization (VSN) can effectively eliminate spectral noise. Variable selection algorithms were used to extract effective variables in order to further optimise the prediction models. The results showed that the method of the variable combination population analysis—iteratively retains informative variables (VCPA-IRIV) is the best method for selecting valid variables, and that the 35-variable VCPA-IRIV-PLSR prediction model could predict the potato SSC with a predictive correlation coefficient ( R p ), root-mean-square error of prediction ( RMSE P ), and residual predictive deviation ( RPD ) values of 0.831, 0.461 ○ Brix and 1.798, respectively. Therefore, the experimental results show the feasibility and applicability of the proposed SSC prediction method for potatoes with surface impurities using near-infrared spectroscopy. • Non-destructive detection of uncleaned potatoes (with surface impurities). • Good PLSR prediction model of potato SSC based on surface impurities. • Processing spectral data with multiple preprocessing algorithms to eliminate noise. • Proposed optimised variable selection algorithms for effective wavelength selection. • Application of VCPA-IRIV algorithm.

Study of Reactivity and Molecular Stability by the Density Functional Theory Method on 2,3-Dihydro -1H-Perimidine: Comparative Analysis

Numerous studies have been carried out on the structure of 2,3-dihydro-1H-perimidine substituted as compounds with various biological activities. Researchers have found that these compounds exhibit characteristics potentially useful in medicinal chemistry research and have many therapeutic applications. In this work, we carried out a study using descriptors of the conceptual DFT in order to determine the atoms responsible for the chelation of certain metals (zinc, copper, iron ...) in order to propose new stable molecules complexed with these metals. Calculations were performed to determine the local reactivity of substituted 2,3-dihydro-1H-perimidine using Fukui functions by the Natural Population Analysis method. Overall parameters were also determined to predict the relative stability and reactivity of substituted 2,3-dihydro-1H-perimidine. This work was carried out at the calculation level B3LYP / 6-311G (d, p). Compound 2 with an energy difference from the frontier orbitals of ΔEgap = 4.031 eV is the most polarizable. Also, the study of frontier orbitals locates HOMO on the function of substituted 2,3-dihydro-1H-perimidine. Analysis of local reactivity indices as well as of the dual descriptor revealed that nitrogen N17 and N19 are the most favorable sites for electrophilic attack.

Theoretical studies on the products formed by cerium atom reacting with XF3 (X = N, P and As)

The possible products (CeXF3, XCeF3, FXCeF2 and F2XceF, X = N, P and As) formed by Ce atom reacting with XF3 were studied by ab initio methods, and the bonding properties of these molecules were studied by atoms-in-molecule (AIM), Fuzzy bond order (FBO), natural population analysis (NPA) and Pipek-Mezey localized orbital methods. For CeXF3, the thermodynamic stability of nitride is the lowest, followed by arsenide, while that of phosphide is the highest. However, the case of other compounds (XCeF3, FXCeF2 and F2XCeF) is the opposite of CeXF3. The AIM results indicate that most of XCe, XF and CeF bonds exhibit mainly closed-shell interaction characteristics and also have partial covalent characteristics. The CeF1 (or F2) bond in F2XCeF shows closed-shell interaction characteristics due to the agnostic interaction, and the stability of the XCeF1 (or F2) ring is weak because the BCP is closed to the RCP.

Quantitative Detection of Acid Value During Edible Oil Storage by Raman Spectroscopy: Comparison of the Optimization Effects of BOSS and VCPA Algorithms on the Characteristic Raman Spectra of Edible Oils

Acid value is one of the crucial indicators reflecting the quality of edible oil during storage. This study proposed a quantitative detection method for edible oil acid value during storage based on reduced Raman spectral characteristics. First, the Raman spectra of edible oil samples from different storage periods were collected, and the original spectra were preprocessed using Savitzky-Golay smoothing (SG smoothing), multiple scattering correction (MSC), adaptive iteratively reweighted penalized least squares (airPLS) combined with normalization. Then, bootstrap soft shrinkage (BOSS) and variable combination population analysis (VCPA) methods based on model population analysis (MPA) strategy were introduced to optimize Raman spectral characteristics. Finally, the SVM prediction model based on the optimized characteristic Raman shifts was established to realize the quantitative detection of edible oil acid value during storage. The results showed that compared with the full-spectrum SVM model, the BOSS-SVM and VCPA-SVM models had no overfitting during the training process, and the VCPA-SVM model obtained the best generalization performance, and its $$ {R}_{\mathrm{P}}^2 $$ and RMSEP in the prediction set were 0.932 and 0.153, respectively. This study sufficiently demonstrated that the SVM model integrated with the characteristic Raman shifts which were optimized by the BOSS and VCPA was a promising tool to monitoring the acid value in edible oil during the storage, and the characteristic Raman shifts of Raman spectra optimized by the VCPA was of more interpretation and pertinence.

Insights into the Chemical Bonding in Microhydrated Protons from Molecular Orbital and Population Analysis Methods

Research works related to investigate molecular electronic structures and thermodynamic stabilities simply by looking into the position of concerned atomic nuclei in the theoretically optimized molecular geometries do not give quantitative picture of the chemical bonding in respect to electron density distributions around atoms and bonds between the atoms. Therefore, total molecular electron density surfaces, and molecular orbitals (MOs) iso-surfaces & contours must be analyzed deeply while interpreting chemical bonds and electronic interactions quantum mechanically. In this paper, how these electron density surfaces (EDSs) actually provide meaningful explanation to the orbital interactions and atomic bonding in microhydrated protons: Hydronium (H 3 O + ), Zundel (H 5 O 2 + ), and Eigen (H 9 O 4 + ), and their overviews are reported briefly. The MOs and Mulliken population analysis methods are used to extract their chemical bond related information from their own DFT derived molecular wavefunctions ( ), and then all the EDSs are examined thoroughly. The MOs analysis reveals that the total molecular electron density surface of each cation defines a closed 3D structural entity plus an exact distribution of electron cloud around the specific bonds, the iso-surface of each MO displays a delocalized type electron density properly along with approximating a region in which bonding electrons are likely to be found and confirming orbital type interactions in atomic bonding, and the contour lines of all the MOs measure the electron amplitudes quantitatively. Additionally, the Mulliken derived partial atomic charge value on each atom of them quantify and compare specific bonding interactions numerically.

The Status of the Stock and the Current Fishery for the Atka Mackerel, Pleurogrammus monopterygius (Pallas, 1810), in the Olyutorsky–Navarin Area, Bering Sea

The dynamics of the Atka mackerel stock in the Olyutorsky–Navarin area in 1994–2019 is inferred from bottom-trawl surveys, fishery statistics, open-access NOAA data, and the results of simulation by the method of virtual population analysis. After the period of low stock in the mid-1990s, the abundance of the Atka mackerel group in the area increased sharply to a maximum in 2006–2008, when the spawning biomass was estimated at approximately 9500 t and the fishery biomass at 14 000 t. In 2008, the stock showed a tendency to decrease; by 2013, the spawning stock decreased to 3600 t and the fishery stock to 5600 t; subsequently, there was a period of stabilization at a low level with a slight tendency to further reduction. One of the possible causes of the sharp increase in the Atka mackerel stock in the 2000s could be the increased transport of juveniles of strong year-classes from the main spawning grounds off the Aleutian Islands with their subsequent settlement on available parts of the shelf off Cape Olyutorsky. The development of the Atka mackerel fishery in the Olyutorsky–Navarin area in 1994–2019 had a pattern similar in general to the stock dynamics. Until 1995, no more than an average of 100 t were caught per year; in 2006–2010, the average annual catch increased to 790 t; in 2011–2015, it increased to 1150 t; and in 2016–2019, the catch again decreased to 950 t. Due to the emerging trend of a general reduction in the stock of the Aleutian population, this low level of catches in the Olyutorsky–Navarin area is expected to continue in the coming years.

Hydrogen Bond Studies in Interact 6-Mercaptopurine with its Receptor Hypoxanthine-Guanine Phosphoribosyltransferase

Objective: The aim of this study was to study some properties of the pharmaceutical compound (6-mercaptopurine) a number of theoretical methods were carried out to calculate their molecular energy, the length of the bonds and angles, in addition to their chemical forms and the binding sites with the enzyme as important anti-cancer inhibitors. Methods: The intramolecular hydrogen bond, molecular structure, and vibrational frequencies of 6- Mercaptopurine have been investigated by means of density functional (DFT and AM1) methods with 6-311++G basis. Results: The nature of these interactions, known as resonance assisted hydrogen bonds, has been discussed. As a geometrical indicator of a local aromaticity, the geometry-based HOMA index has been applied. Additionally, the linear correlation coefficients between substituent constants and selected parameters in R position have been calculated. Conclusion: The results show that the hydrogen bond strength is mainly governed by the resonance variations inside the chelate ring induced by the substituent groups. The topological properties of the electron density distributions for 6- MP H...N intra molecular bridges have been analyzed .Finally, the natural population analysis methods has been used to evaluate the hydrogen bonding interactions.

Early determination of mildew status in storage maize kernels using hyperspectral imaging combined with the stacked sparse auto-encoder algorithm

The early detection the mildew status of maize kernels caused by fungal infection during storage is essential. Hyperspectral imaging (HSI) combined with the deep stacked sparse auto-encoders (SSAE) algorithm was employed to recognize the early mildewed degree of kernels. HSI data of kernels were collected in the spectral range of 400–1000 nm and the mildew status was classified into four grades (health, mild mildew, moderate mildew, and heavy mildew) using the measured fungal spores as the reference. The nonlinear features of the spectra were represented using the SSAE network, and the key wavelengths were selected by variable combination population analysis and random frog methods, which were combined with four classifiers-Softmax, kernel extreme learning machine (KELM), ELM, and support vector machine-to establish models for identifying the mildew grades of kernels. The comparative results indicated that SSAE combined with KELM classifier to build the SSAE-KELM model had better identification ability than other models with high total correct recognition rate of 97.36% and 96.84% for the training and testing sets, respectively. The sensitivity and specificity were 0.92–1. The different grades were visualized on the images of maize kernels based on pixels-level and object-level. The current results demonstrated that HSI with SSAE-KELM model performed well in the early detection of mildew status of maize kernel, and can be applied as the reference method for batch and online detection of mildew kernels to improve grain storage security.

Advances in genome-wide association studies of complex traits in rice.

Genome-wide association studies (GWAS), genetic surveys of the whole genome to detect variants associated with a trait in natural populations, are a powerful approach for dissecting complex traits. This genetic mapping approach has been applied in rice over the last 10years. During the last decade, GWAS was used to identify the loci underlying tens of rice traits, and several important genes were detected in GWAS and further confirmed in follow-up functional experiments. In this review, we present an overview of the whole process in a typical GWAS, including population design, genotyping, phenotyping and analysis methods. Recent advances in rice GWAS are also provided, including several examples of the functional characterization of candidate genes. The possible breakthroughs of rice GWAS in the next decade are discussed with regard to their application in breeding, the consideration of epistatic interactions and in-depth functional annotations of DNA elements and genetic variants throughout the rice genome.

Quantum chemical analysis of reaction indices and reaction path for drug molecules

We performed a quantum chemical study on evaluating chemical reactivity for drug molecules in Cytochrome P450 (CYP) metabolic reaction. In this study, we focused on two insights for analysing the chemical reactivity: one is the Fukui reaction indices for a molecule, and the other is the minimum energy paths of hydrogen transition reaction between drug molecule and FeO-Porphyrin ring part on the CYP metabolic reaction. The Fukui indices are obtained numerically by using the familiar population analysis method in quantum chemical calculations. We performed the assessments of some population analyses to clarify the numerical behaviour clearly and then evaluated the potential of the reactivity of drug molecule. On the other hand, in the analysis of the minimum energy path for the CYP metabolic reaction, we performed the nudged elastic band (NEB) calculations for the hydrogen transition reaction in the first step of the CYP metabolic reaction. We report the findings for the reactivity from the Fukui indices method and also show the NEB results for the reaction paths.

Construction, characteristics and high throughput molecular screening methodologies in some special breeding populations: a horticultural perspective

Advanced marker technologies are widely used for evaluation of genetic diversity in cultivated crops, wild ancestors, landraces or any special plant genotypes. Developing agricultural cultivars requires the following steps: (i) determining desired characteristics to be improved, (ii) screening genetic resources to help find a superior cultivar, (iii) intercrossing selected individuals, (iv) generating genetically hybrid populations and screening them for agro-morphological or molecular traits, (v) evaluating the superior cultivar candidates, (vi) testing field performance at different locations, and (vii) certifying. In the cultivar development process valuable genes can be identified by creating special biparental or multiparental populations and analysing their association using suitable markers in given populations. These special populations and advanced marker technologies give us a deeper knowledge about the inherited agronomic characteristics. Unaffected by the changing environmental conditions, these provide a higher understanding of genome dynamics in plants. The last decade witnessed new applications for advanced molecular techniques in the area of breeding,with low costs per sample. These, especially, include next-generation sequencing technologies like reduced representation genome sequencing (genotyping by sequencing, restriction site-associated DNA). These enabled researchers to develop new markers, such as simple sequence repeat and single- nucleotide polymorphism, for expanding the qualitative and quantitative information onpopulation dynamics. Thus, the knowledge acquired from novel technologies is a valuable asset for the breeding process and to better understand the population dynamics, their properties, and analysis methods.

Estimation of Otolithes ruber stock with virtual population analysis in the Northwest area of the Persian Gulf

Stock assessment of Otolithes ruber was carried out using Virtual Population Analysis (VPA) method in the coastal waters of Northwest Persian Gulf. Catch and length frequency data during 2002-2012 were converted to age frequency. The maximum of stock number and biomass were observed in age group 1 and 2 respectively. The minimum of stock number and biomass were observed age group 6. The maximum and minimum of catch number were in age group 2 and 6 respectively. The maximum and minimum of weight were in age group 3 and 1 respectively. The maximum and minimum of instantaneous fishing mortality were in age group 4 and 1 respectively. The maximum of fishing mortality was estimated in 2010-2011 and minimum was in 2002-2003 and 2008-2009. During 2011-2012 the stock number and biomass were estimated 29558 (*103) specimen, 7302 ton and the catch number and weight were calculated 7562 (*103), 2364 ton and fishing mortality was obtained 0.47 per year. The calculated parameters showed over-exploitation in age-groups 3 and 4. To preserve stocks and to guarantee sustainable exploitation, the prevention of increasing fishing efforts and the control of fishing activities are crucial.

Atomic Charges in Describing Properties of Aromatic Molecules.

The performance of four frequently employed population analysis methods is assessed by comparisons with experimentally derived properties of monosubstituted benzene derivatives. The analysis is based on the expected dependence between site reactivities and electron densities at the respective ring carbon atoms. The correspondence between charges obtained from Mulliken, NPA, Hirshfeld, and QTAIM approaches and the σ0m and σ0p aromatic substituent constants is examined. The series of molecules investigated includes benzene and 18 monosubstituted derivatives. The atomic charges are derived using the B3LYP, ωB97X-D density functional, and MP2 MO methods combined with the 6-311++G(3df,2pd) basis set. A quantitative correspondence between Hirshfeld charges and σ0 constants is established. Application of Møller-Plesset second-order perturbation theory (MP2) wave functions appears to be essential in obtaining a more realistic electron density distribution. NPA and QTAIM charges provide in most cases a satisfactory description of the substituent effects. The net transfer of charges between substituents and the aromatic ring is assessed.