Tetrahedral homonuclear tetrameric species are neutral or ionic tetrahedra of chemical elements, true molecular tetrahedra in strict geometrical sense. The aim of this work was to find all true ...elemental tetrahedra experimentally determined as stable and capable of being transferred from one medium/condition to another, to rationalize their structures and properties, and seek their technological significance. A database of elemental tetrahedra was built based on reliable literature, and a dataset of molecular descriptors was generated. Correlation analysis, hierarchical cluster analysis, principal component analysis, and some regression analysis were carried out. Twelve chemical elements from Groups 13 – 15 have tetrahedral species: anions E48– (Al, Ga, In, Tl), anions E44– (Si, Ge, Sn, Pb), neutral molecules E4 (P, As, Sb), and cations E4+ (P, As, Sb, Bi). These species appear in 39 forms, such as gas phase, solid Zintl phases, thin films, Zintl phase ammoniates, and cage compounds, among others. Zintl phases and forms of P4 and As4 are important for synthesis of new materials, chemical reactions, and other applications. Data compression has shown that the true tetrahedral species are a three-dimensional phenomenon, and that true tetrahedra can be distinguished from fictive tetrahedra. Grouping of the tetrahedra according to their periodic groups, charges, frequency, and diversity class values, tetrahedral size, and metallic character, were observed. Empirical rules for species size and principal components were established for true tetrahedra. Most descriptors are parabolic functions of the class variable. True tetrahedral species partly remain a puzzle and should be further investigated.
Sumpor je najzastupljeniji mikroelement u ljudskom tijelu, u obliku mnogobrojnih ne samo organskih već i anorganskih spojeva s različitim ulogama. Ovim pregledom prikazani su anorganski spojevi ...sumpora iz klase endogenih tiocianatnih spojeva u ljudskom organizmu. Ta se klasa izvodi iz tiocianatnog aniona SCN– ponajprije enzimskim i neenzimskim reakcijama u stanicama ili izvanstaničnom prostoru. SCN– nastaje detoksikacijom endogenih ili egzogenih cianida, djelovanjem endogene bakterijske flore, metabolizmom cianogene hrane ili industrijskom intoksikacijom. Opisani su molekulski i ionski spojevi: tiocianska, izotiocianska, hipotiocianska, (cianido-C)sulfinska i (cianido-C)sulfonska kiselina; soli tih kiselina i aniona 1,2,3-tricianotrisulfida(1–) s najzastupljenijim kationima u organizmu (Na+, K+, Ca2+ i Mg2+); cianotiocianat i bis(cianido-C)sumpor(S-S) (tiocianogen). Anioni i molekule jesu endogene reaktivne sumporove vrste sa svojstvima pseudohalogena. Nalaze se u značajnim koncentracijama u tjelesnim tekućinama, gdje imaju zaštitne uloge – detoksikacijsku (uklanjanju cianid) i antimikrobne uloge (mikrobicidno i mikrobiostatski djeluju na razne bakterije, na neke viruse, gljivice i parazite). Metabolički su povezani s endogenim okso spojevima sumpora u ljudskom tijelu. Može se očekivati da će istraživanja o opisanoj klasi sumpornih spojeva razjasniti u bliskoj budućnosti njihove molekulske mehanizme djelovanja u ljudskom tijelu.
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Sumpor je nakon kalcija i fosfora najzastupljeniji element u ljudskom tijelu, gdje se nalazi u mnogobrojnim anorganskim i organskim spojevima, a u vrlo malim količinama i u elementarnom stanju. U ...ovom pregledu prikazani su anorganski spojevi sumpora iz klase endogenih okso-spojeva u ljudskom organizmu, koji ponajprije nastaju enzimskim i neenzimskim biosintetskim putevima u stanicama ili izvanstaničnom prostoru. Opisani su sulfati, tiosulfati, μ-disulfido-bis(trioksosulfati)(2–) (tetrationati), sulfiti, hidrogensulfiti, sulfonati i disulfiti najzastupljenijih metala u organizmu (Na+, K+, Ca2+ i Mg2+) i sumporov dioksid. Anioni i SO2 jesu endogene neradikalske sumporove vrste koje se nalaze u znatnim koncentracijama u tjelesnim tekućinama, gdje imaju zasebne fiziološke, patološke, metaboličke, detoksikacijske i druge uloge. Međusobno su povezani metaboličkim putevima sumporovih spojeva. Dok je sulfatni ion redovit sastojak elektrolita i izvor sumpora, tiosulfatni ion ima brojne zaštitne funkcije i važan je metabolit, a anioni nastali reakcijom SO2 i vode također su važni metabolički međuprodukti. Novijim istraživanjima prepoznate su uloge sumporova dioksida kao nove signalne molekule i aniona μ-disulfido-bis(trioksosulfata)(2–), kao metabolita koji se stvara tijekom upale crijeva. Istraživanja o opisanoj klasi sumporovih spojeva i njihovoj važnosti za ljudski organizam očito nisu završena i mogu još donijeti važne i neočekivane spoznaje.
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Quo Vaditis, Scientia et Educatio? Kiralj, Rudolf
Radovi Zavoda za znanstvenoistraživački i umjetnički rad u Bjelovaru,
2023, 2023-00-00, Letnik:
17, Številka:
17
Journal Article, Paper
Recenzirano
Odprti dostop
Exponential growth of human knowledge i.e. of science and technology, becomes uncontrollable and more and more is in disagreement with linear biological development of humans. This work makes ...assessment of the impact of the exponential growth to education in terms of bibliometric analyses of university textbooks and case studies of visual nature in chemistry. Various bibliometric descriptors (number of pages, number of editions with years, font size, and maximum number of characters) were determined for books studied from 12 diverse areas of knowledge, and from 14 branches of chemistry. Case studies in chemistry (spherical harmonics, nucleophilic substitution reactions, and nucleic acid bases) were illustrated using modern calculation and visualization software and chemical databases. All textbooks studied exhibit the increase in the quantity of matter. There are several increase types, linear, parabolic, oscillating and others, visible when analyzing No. pages versus time scatterplots. Other descriptors show that some increase is always present. Increased rates from the first to the last edition of textbooks are higher in chemistry than in general knowledge. Converting them into additional time to study textbooks, they range from about 10 minutes to 100 minutes per day. This means students have to spend in general over 2 hours more, and in chemistry 2 4 hours per day more than their colleagues who had the first edition textbooks. The three case studies in chemistry indicate that many outdated misconceptions are not erased using modern computer technology, what makes studying textbooks more difficult. Textbooks systematically omit high quality computer-generated plots of various functions and molecular structures and instead, prefer using inaccurate schematic and artistic presentations. Such situation, in spite of the exponential growth of science and technology, persists for decades, coexisting with good calculation and plotting software and chemical databases. Remedies for this situation are not simple and they include radical changes of textbooks for a whole course.
Students’ honesty is a key element in the context of academic honesty, when taking into consideration that the share of academically educated persons is in permanent increase. Students are the future ...moving power of the society; they are the part of the population that will significantly influence the society on the whole and its socio-economic development, including the younger generations. The paper analyses eight groups of data on the constant growth of students’ dishonesty in the world, and particularly in the USA, the United Kingdom and Sweden. Over the last two decades, a significant increase has been recorded. The situation in Croatia has been compared with these trends on the basis of the data gained by studying various sources from literature and the internet, as well as several estimates. As a result, the following students’ dishonesty indices have been defined: average (IC0) and maximal (IC1) cheating at exams, and average (IP0) and maximal (IP1) plagiarism. The indices mainly follow global trends, whilst over the last two decades, the average percentage of students engaging in dishonest activities has been alarmingly high: 64 % (IC0); 76 % (IC1); 33 % (IP0) and 77 % (IP1). Data according to five socio-economic indices have been collected and estimated: GDP (gross domestic product per capita), HDI (human development index), GII (global innovation index), CPI (corruption perception index), and EI (education index). By the means of weighing correlation and regression, it has been determined that IC0, IC1, IP0 and IP1 are different indices; that IP0 and IP1 do not correlate well with time and the socio-economic variables due to an insufficient quantity of data on students’ plagiarism; that IC0 and IC1 correlate well with time, GDP, HDI and EI. Furthermore, IC0 and IC1 have modestly decreased over the last several years; and IP0 and IP1 have demonstrated no decrease at all. The dependence of IC0 and IC1 on GDP, HDI and EI has been presented by two sigmoid curves, with a minor increase around 1980, and a major around 2010. Since students’ dishonesty and its growth have been socially determined, the culture itself ought to be changed – from the culture of profit, competition and success to the culture of knowledge and responsibility, with pronounced social and moral components of the socio-economic development.
Four Quantitative Structure–Activity Relationship (QSAR) models were constructed for a set of 32 and 16 HIV-1 protease inhibitors in the training and external validation sets, respectively, using the ...biological activity and molecular descriptors from the literature. Two QSAR models were based on Support Vector Machines methods (SVM): Support Vector Regression (SVR) and Least-Squares Support Vector Machines (LS-SVM) models. The other two models were an ordinary Partial Least Squares (PLS) and Ordered Predictors Selection-based PLS (OPS-PLS). The SVR and LS-SVM models showed to be somewhat better than the PLS model in external validation and leave-
N-out crossvalidation. SVR and LS-SVM were better than OPS-PLS in external validation, but showed equal performance in leave-
N-out crossvalidation. However, despite of their high predictive ability, the SVM models failed in
y-randomization, which did not happen with the PLS and OPS-PLS models. The OPS-PLS model was the only one that undoubtedly showed satisfactory performance both in prediction and all validations. The selection of inhibitors by the SVM-based models and variable selection by the OPS-PLS model were rationalized by means of Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA). Lagrange multipliers from the SVR and LS-SVM models were explained for the first time in terms of molecular structures, descriptors, biological activity and principal components. Some unresolved difficulties in practical usage of SVM in QSAR and QSPR were pointed out. The presented validation and interpretation of SVR and LS-SVM models is a proposal for future investigations about SVM applications in QSAR and QSPR, valid for any modeling and validation condition of the final regression equations.
Sign change problem (SCP) in multivariate Quantitative Structure-Activity/Property Relationships (QSAR/QSPR) is the inconsistency in the direction of association between molecular descriptors and the ...dependent variable. Sign change is observed when the signs of the elements of the reference vector (correlation vector for the data set obtained from variable selection) are compared to the signs of the elements of all correlation and regression vectors related to a model. SCP check in this work, named Integral SCP (ISCP) check, is established to be a general effective anti-SCP procedure, consisting of five check levels. Twelve diverse QSAR/QSPR data sets from literature were tested, and performance of data sets, models and descriptors was assessed by qualitative labeling systems. Most data sets and models did not have satisfactory performance, what is discussed in terms possible data and model remedy. Keywords: sign change, direction of association between two variables, correlation, molecular descriptor, dependent variable, multivariate model
Four quantitative structure-activity relationships (QSAR) and quantitative structure-property relationship (QSPR) data sets were selected from the literature and used to build regression models with ...75, 56, 50 and 15 training samples. The models were validated by leave-one-out crossvalidation, leave-N-out crossvalidation (LNO), external validation, y-randomization and bootstrapping. Validations have shown that the size of the training sets is the crucial factor in determining model performance, which deteriorates as the data set becomes smaller. Models from very small data sets suffer from the impossibility of being thoroughly validated, failure and atypical behavior in certain validations (chance correlation, lack of robustness to resampling and LNO), regardless of their good performance in leave-one-out crossvalidation, fitting and even in external validation. A simple determination of the critical Nin LNO has been introduced by using the limit of 0.1 for oscillations in Q², quantified as the variation range in single LNO and two standard deviations in multiple LNO. It has been demonstrated that it is sufficient to perform 10 -25 y-randomization and bootstrap runs for a typical model validation. The bootstrap schemes based on hierarchical cluster analysis give more reliable and reasonable results than bootstraps relying only on randomization of the complete data set. Data quality in terms of statistical significance of descriptor -yrelationships is the second important factor for model performance.Variable selection that does not eliminate insignificant descriptor - yrelationships may lead to situations in which they are not detected during model validation, especially when dealing with large data sets.
Even small areas as Bjelovar-Bilogora County (BBC) are affected by increasing local and regional pollution. A large variety of organic compounds exists in all parts of the atmosphere, waters and ...soil, accumulates in living organisms and on anthropogenic objects. This work investigates organic pollutants in BBC in relation to their spread, behavior and chemical properties, based on literature data in absence of experimental measurements. More than 230 organic pollutants were identified in BBC: simple compounds, benzene derivatives, polycyclic aromatic hydrocarbons, polychlorinated and other biphenyls, polychlorinated dibenzo-p-dioxins and dibenzofurans, halogenated alkanes and alkenes, diverse pesticides and antimicrobials. Geographic distribution of organic pollutants was investigated in relation to population density, agricultural activity, position of volatile organic compounds emitters, annual traffic data, and night sky brightness levels as light pollution. It is visible that towns and larger villages as well as main roads are emitters of various organic pollutants and smog generators, whilst typically rural regions are more characterized by pesticides pollution. Three examples for QSPR (Quantitative Structure-Property Relationship) are described and investigated in terms of their statistics (sign change problem) and chemical interpretability: 1) a partial least squares (PLS) regression model for boiling point of polycyclic aromatic hydrocarbons; 2) a multiple linear regression (MLR) model for micellar phase-water partition coefficient of diverse solutes; 3) a MLR model for bioconcentration factor of nonpolar organic compounds. Several samples in the models were already identified as existing pollutants in BBC. Models 2) and 3) failed in the sign check, for which explanations are given and remedies are proposed.
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