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Background: Teleophthalmology is a validated method for diabetic eye screening that is underutilized in U.S. primary care clinics. Even when made available to patients, its long-term effectiveness for increasing screening rates is often limited. Introduction: We hypothesized that a stakeholder-based implementation program could increase teleophthalmology use and sustain improvements in diabetic eye screening. Materials and Methods: We used the NIATx Model to test a stakeholder-based teleophthalmology implementation program, I-SITE at one primary care clinic (Main) and compared teleophthalmology use and diabetic eye screening rates with those of other primary care clinics (Outreach) within a U.S. multipayer health system where teleophthalmology was underutilized. Results: Teleophthalmology use increased post-I-SITE implementation (odds ratio [OR] = 5.73 [p < 0.001]), and was greater at the Main than at the Outreach clinics (OR = 10.0 vs. 1.69, p < 0.001). Overall diabetic eye screening rates maintained an increase from 47.4% at baseline to 60.2% and 64.1% at 1 and 2 years post-I-SITE implementation, respectively (p < 0.001). Patients who were younger (OR = 0.98 per year of age, p = 0.02) and men (OR = 1.98, p = 0.002) were more likely to use teleophthalmology than in-person dilated eye examinations for diabetic eye screening. Discussion: Our stakeholder-based implementation program achieved a significant increase in overall teleophthalmology use and maintained increased post-teleophthalmology diabetic eye screening rates. Conclusion: Stakeholder-based implementation may increase the long-term reach and effectiveness of teleophthalmology to reduce vision loss from diabetes. Our approach may improve integration of telehealth interventions into primary care.

We thank the participants in the \Stealth Physics at LHCb" workshop, held in Santiago de Compostela in February 2020 [333], for many fruitful discussions and for triggering many ideas that were developed here. We also thank the LHC Long-Lived Particle community, and the LPCC LHC Long-lived Particle and Dark Matter working groups for fostering and nurturing the interest in the ideas here discussed. We kindly acknowledge Vladimir Gligorov, Stephen Farry and Niels Tuning for kindly reading and providing comments to this document. This work has been supported by MINECO (Spain) through the Ramón y Cajal program RYC-2016- 20073 and by XuntaGAL under the ED431F 2018/01 project. It has also received nancial support from XuntaGAL (Centro singular de investigación de Galicia accreditation 2019-2022), by European Union ERDF, by the \María de Maeztu" Units of Excellence program MDM-2016-0692 and the Spanish Research State Agency, and by the Generalitat Valenciana (Spain) through the plan GenT program (CIDEGENT/2019/068)., In this paper, we describe the potential of the LHCb experiment to detect Stealth physics. This refers to dynamics beyond the Standard Model that would elude searches that focus on energetic objects or precision measurements of known processes. Stealth signatures include long-lived particles and light resonances that are produced very rarely or together with overwhelming backgrounds. We will discuss why LHCb is equipped to discover this kind of physics at the Large Hadron Collider and provide examples of well-motivated theoretical models that can be probed with great detail at the experiment., MINECO (Spain) through the Ram on y Cajal program RYC-2016- 20073, XuntaGAL under the ED431F 2018/01 project, XuntaGAL (Centro singular de investigaci on de Galicia accreditation 2019-2022), European Union ERDF, María de Maeztu" Units of Excellence program MDM-2016-0692, Spanish Research State Agency, Generalitat Valenciana (Spain) through the plan GenT program (CIDEGENT/2019/068)

A computational approach is presented to estimate the in vivo magnitude and spatial distribution of mechanical material properties of soft tissues. This strategy utilizes an optimization-ty...

A design concept for shape-changing smart material tiles for applications in environmentally responsive building facades is presented. In particular, the application considered is a tile that would change the shape of the building surface to favorably affect the interaction with solar irradiance. A lab-scale prototype system for smart material tiles composed of 3D printed thermally responsive shape memory polymer (SMP) and utilizing localized thermal material activation and uniform pressure actuation is examined. Tests utilizing the prototype tile are used to create and validate a computational (finite element) representation of the adaptive surface tile system. Toward developing this computational representation, a strategy is presented to determine and validate the material parameters for the 3D printed SMP by matching the tile shape predicted by the numerical model to the tile shape measured experimentally. This numerical representation was then implemented into a computational approach to explore the design space for this adaptive tile to have an effect on the solar irradiance on a building surface. More specifically, a series of numerical examples are considered that determine the location and size of material activation that minimize the area of the tile exposed to solar irradiance. Results indicate that the adaptive tile can change the surface of a structure to considerably improve the structure’s interaction with solar irradiance. Additionally, the importance of the control strategy for a multi-tile system was displayed, particularly with respect to the capability to significantly reduce the energy cost and affect the solar irradiance to a higher degree by accounting for neighboring tile interaction.

Objective Diabetic retinopathy remains the leading cause of blindness among working-age U.S. adults largely due to low screening rates. Rural populations face particularly greater challenges to screening because they are older, poorer, less insured, and less likely to receive guideline-concordant care than those in urban areas. Current patient education efforts may not fully address multiple barriers to screening faced by rural patients. We sought to characterize contextual factors affecting rural patient adherence with diabetic eye screening guidelines. Research design and methods We conducted semi-structured interviews with 29 participants (20 adult patients with type 2 diabetes and 9 primary care providers) in a rural, multi-payer health system. Both inductive and directed content analysis were performed. Results Factors influencing rural patient adherence with diabetic eye screening were categorized as environmental, social, and individual using the Ecological Model of Health. Major themes included limited access to and infrequent use of healthcare, long travel distances to obtain care, poverty and financial tradeoffs, trusting relationships with healthcare providers, family members’ struggles with diabetes, anxiety about diabetes complications, and the burden of diabetes management. Conclusions Significant barriers exist for rural patients that affect their ability to adhere with yearly diabetic eye screening. Many studies emphasize patient education to increase adherence, but current patient education strategies fail to address major environmental, social, and individual barriers. Addressing these factors, leveraging patient trust in their healthcare providers, and strategies targeted specifically to environmental barriers such as long travel distances (e.g. teleophthalmology) may fill crucial gaps in diabetic eye screening in rural communities.

The development and evaluation of a computational approach for optimal design of a smart material shape changing building skin is presented and numerically evaluated. Specifically, a unique shape-based approach is utilized to create an optimization approach to identify the activation and actuation mechanisms to minimize the difference between a desired shape and the estimated morphed shape. Three potential metrics of shape difference are considered and their capability to facilitate an efficient optimization process leading to accurate shape matching is evaluated. Details of the optimal design framework are presented, particularly focusing on the shape difference metrics as well as the strategy to parameterize the activation of the smart material. In particular, the parameterization strategy is a unique approach to easily integrate controllable localized activation within a smart material structure in a generally applicable way that does not limit the design search space. A series of numerical design examples are presented based on the concept of a smart material (e.g., shape memory polymer) shape changing tile that can be activated and actuated in a variety of ways to achieve desirable surface wrinkle patterns. These numerical design examples are applied to both 2D and 3D problems and consider a variety of parameterizations and target shapes. Results indicate that the shape-based approach can consistently determine the mechanisms of morphing needed to accurately match a target shape. Furthermore, it is shown that localized material activation can lead to not only a more accurate shape but also requires less energy and actuation devices to do so.

We discuss how to extract the weak phase alpha from present data on B--> rho+- pi-+ decays. Introducing alpha_{eff} and constraining the difference from alpha using flavor SU(3), one arrives at alpha=(95+- 16) degrees, if a testable assumption of a small relative strong phase between the two relevant tree amplitudes is employed to distinguish between discrete ambiguities. On the long run we advocate the combined fit to B--> rho+- pi-+ and SU(3) related modes. The effect of SU(3) breaking in this approach is expected to be small, because of relatively small penguin pollution.

The present study focuses on fish antibiotics which are an important group of pharmaceuticals used in fish farming to treat infections and, until recently, most of them have been exposed to the environment with very little attention. Information about the environmental behaviour and the description of the environmental fate of medical substances are difficult or expensive to obtain. The experimental information in terms of properties is reported when available, in other cases, it is estimated by standard tools as those provided by the United States Environmental Protection Agency EPISuite software and by custom quantitative structure-activity relationship (QSAR) applications. In this study, a QSAR screening of 15 fish antibiotics and 132 xenobiotic molecules was performed with two aims: (i) to develop a model for the estimation of octanol--water partition coefficient (logP) and (ii) to estimate the relative binding affinity to oestrogen receptor (log RBA) using a model constructed on the activities of 132 xenobiotic compounds. The custom models are based on constitutional, topological, electrostatic and quantum chemical descriptors computed by the CODESSA software. Kohonen neural networks (self organising maps) were used to study similarity between the considered chemicals while counter-propagation artificial neural networks were used to estimate the properties.

We consider the scalar form factor in the weak current matrix element μ|0>, P=π, η, η′. It obtains the contributions from the scalar meson resonance [Formula: see text] and from the scalar projection of the vector meson K*(892) resonance. We analyze decay amplitudes of the Cabibbo suppressed decays D → KP, P=π, η, η′ using the factorization approach. The form factors of the relevant matrix elements are described by assuming the dominance of nearby resonances. The annihilation contribution in these decays arises from the matrix element μ|0>. All the required parameters are experimentally known except the scalar meson [Formula: see text] decay constant. We fit the decay amplitudes and we find that final state interaction improves the agreement with the experimental data. Then we extract bounds on scalar form factor parameters and compare them with the experimental data obtained in the analyses of K→πeνe and K→πμνμ. The same scalar form factor is present in the τ → KPντ decay, with P=π, η, η′. Using the obtained bounds we investigate the significance of the scalar meson form factor in the τ→ KPντ, P=π, η, η′ decay rates and spectra. We find that the [Formula: see text] scalar meson dominates in the τ→Kη′ντ decay spectrum.

ICP-AES was used for the quantitative determination of copper and copper accompanying elements (As, Ag, Bi, Co, Fe, Mn, Ni, Pb, Sb, Sn, Zn) that are present as impurities in plano-convex ingots from seven late bronze age hoards in Slovenia. Principal component analysis (PCA) was used for multi-dimensional data evaluation and for visualisation of ingots as points in reduced two-dimensional space. From the analytical and PCA results, it has been concluded that iron as well as arsenic, and to a less extent nickel and antimony, are the most relevant variables for differentiation between ingots. Furthermore, on the basis of PCA results, the relationship between object position in two-dimensional space and its elemental composition has been established. The information obtained by PCA transformation allowed us to make some hypotheses about the possible multi-stage smelting process and about ore types used in ancient copper production. We also show that, in general, there are no significant differences among the copper ingots from different Slovenian locations.

Summary. Recent obstetrical practice trends in 12 countries were surveyed. There was a 3-fold difference in caesarean section rates and a 10-fold difference in instrumental vaginal delivery rates among countries. There was a net increase in the caesarean section rate of all countries over the study period and a net decrease in the instrumental vaginal delivery rate of some countries. There was a decrease in the caesarean section rate during the last year of observation in Australia, Denmark and Finland. In general, countries with high caesarean rates also had high instrumental vaginal delivery rates. There was no consistent relationship between use of caesarean section and use of instrumental vaginal delivery, although in several countries increasing use of caesarean section was accompanied by decreasing use of instrumental vaginal delivery. Oxytocin use rates were associated positively with instrumental delivery but not with caesarean section rates. While it was not possible to determine the proportions of women who received appropriate obstetrical care, we can infer that a significant proportion of interventions were unnecessary or only marginally beneficial. Continued increases in rates of obstetrical intervention are unlikely to result in improvements in birth outcome overall and may pose a risk to mothers and their newborns.

The separation and determination of the major carboxylic acids in wine by liquid chromatography were optimized by using the modelling surface response method. The chromatographic response function was used as a criterion to obtain an optimum peak separation with the minimum analysis time accepted. The starting mobile phase composition (% methanol) and the change in the solvent strength of the mobile phase during the analysis time were considered as experimental parameters. Malic, tartaric, acetic, lactic, succinic and citric acid were determined by linear gradient elution of their phenacyl bromide derivatives. The optimized method was applied to a red wine sample.

A program for modeling, validation, prediction and graphic display of data is reported. The package is useful for dealing with responses that area function of a reduced number of variables. Implementation of user-defined models is easy and several very general equations can be selected. The structure of the program is shown and the use of the different modules is explained. Two typical, applications based on distinct mathematical models are shown.

The hardware and software requirements for intelligent analytical instruments are discussed. Existing technology in both fields allows the production of a new generation of instruments that can learn from their own operation and even transfer the acquired knowledge to machines of a later generation. The hardware needed is a processor with the power of at least the Intel 80386 processor, 4–5 Mbyte RAM, storage equivalent to a 1.6-Gbyte hard disk and a special encode/decode processor for compressing complex instrumental information. This hardware can support the transmission, transformation, storage and handling of about 100 000 complex measurements (up to 3 kbyte of numbers per measurement) and a knowledge base of about the same size. In this context, the space for software can be neglected or, in the case of neural networks, the “software” can be hardwired. At preent, there are two different approaches to handling the required amount of data, extracting vital information, and acquiring (in close cooperation with experts) new knowledge. The first is neural networks and the second is hierarchical clustering. It is argued that combination of both methods forms a very powerful basis for software development in intelligent instruments.

A topical spot-on solution was developed for treating pets that contained of active ingredients metaflumizone and amitraz and intended for use as an ectoparasiticide. The formulation vehicle system was designed by balancing the following three attributes of various solvents: evaporation/drying, surface spreading, and percutaneous absorption. The solvents were selected by evaluating the solubilization capacity of individual solvents with respect to the above active ingredients. The evaporation rates of various solvent systems were then determined. The visual observations of the treatment sites was also performed a day after treating the dogs to understand the cosmetic effect of various solvent systems. The lead formulations dried off within a day after application with no noticeable residue at the treatment site, while others produced appreciable powdery residue or a large wet and oily spot. The stability of the lead formulations was also evaluated over 2 years to demonstrate a 2-year shelf life of this product.

Objectives: This study sought to investigate gender-related differences in patients with atrial fibrillation (AF) in Europe. Background: Gender-related differences may play a significant role in AF. Methods: We analyzed the data of 5,333 patients (42% female) enrolled in the Euro Heart Survey on Atrial Fibrillation. Results: Compared with men, the women were older, had a lower quality of life (QoL), had more comorbidities, more often had heart failure (HF) with preserved left ventricular systolic function (18% vs. 7%, p < 0.001), and less often had HF with systolic dysfunction (17% vs. 26%, p < 0.001). Among patients with typical AF symptoms (56% of women, 49% of men), there was no gender-related difference in the choice of rate or rhythm control. Among patients with atypical or no symptoms (44% of women, 51% of men), women less frequently underwent rhythm control (39% vs. 51%, p < 0.001) than did men. Women underwent less electrical cardioversion (22% vs. 28%, p < 0.001). Prescription of oral anticoagulants was identical (65%) in both genders. One-year outcome was similar except that women had a higher chance for stroke (odds ratio 1.83 in multivariable regression analysis, p = 0.019). Conclusions: Women with AF had more comorbidities, more HF with preserved systolic function, and a lower QoL than men. In the large group with atypical or no symptoms, women were treated appropriately more conservatively with less rhythm control than men. Women had a higher chance for stroke. Long-term QoL changes and other morbidities and mortality were similar. © 2007 American College of Cardiology Foundation.

Isospin-breaking in $B\ensuremath{\rightarrow}\ensuremath{\pi}\ensuremath{\pi}$ caused by ${\ensuremath{\pi}}^{0}\ensuremath{-}\ensuremath{\eta}\ensuremath{-}{\ensuremath{\eta}}^{\ensuremath{'}}$ mixing is studied in a model-independent way using flavor SU(3). Measured branching ratios for ${B}^{+}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{0},{B}^{+}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{+}{\ensuremath{\eta}}^{{(}^{\ensuremath{'}})}$ and ${B}^{0}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{0}{\ensuremath{\eta}}^{{(}^{\ensuremath{'}})}$ imply an uncertainty in $\ensuremath{\alpha}$ smaller than $1.4\ifmmode^\circ\else\textdegree\fi{}$. We find a negligible effect of ${\ensuremath{\pi}}^{0}\ensuremath{-}\ensuremath{\eta}\ensuremath{-}{\ensuremath{\eta}}^{\ensuremath{'}}$ mixing on $\ensuremath{\alpha}$ in $B\ensuremath{\rightarrow}\ensuremath{\rho}\ensuremath{\pi}$. Characterizing the effect of ${\ensuremath{\rho}}^{0}\ensuremath{-}\ensuremath{\omega}$ mixing in $B\ensuremath{\rightarrow}\ensuremath{\rho}\ensuremath{\rho}$ and in $B\ensuremath{\rightarrow}\ensuremath{\rho}\ensuremath{\pi}$ by the two-pion invariant mass dependence, we point out a way of constraining this effect experimentally or eliminating it altogether. We show that a model-independent shift in $\ensuremath{\alpha}$ caused by electroweak penguin amplitudes in $B\ensuremath{\rightarrow}\ensuremath{\pi}\ensuremath{\pi}$, $B\ensuremath{\rightarrow}\ensuremath{\rho}\ensuremath{\rho}$ and $B\ensuremath{\rightarrow}\ensuremath{\rho}\ensuremath{\pi}$ is the same, $\ensuremath{\Delta}{\ensuremath{\alpha}}_{\mathrm{EWP}}=(1.5\ifmmode\pm\else\textpm\fi{}0.3)\ifmmode^\circ\else\textdegree\fi{}$. Other sources of isospin-breaking in these processes are briefly discussed.

We consider large interconnected networks that operate under a user-provider paradigm (such as IP over SONET) where networks from different layers are in different administrative domains. In such a relationship, the overall network survivability can benefit from a limited sharing of network management data between networks of different layers. The paper proposes a multi-layered alarm management framework in such a setting. The alarm manager uses a finite state machine to represent an alarm instance with state transitions triggered as a result of the correlation of multiple alarms. We present a constructive argument to demonstrate the correctness of the finite state machine. Alarm correlation is handled by a rule-based reasoning engine. The set of correlation rules and corresponding actions depends on the definition of alarms that can enter the system. Therefore, based on the multi-layered paradigm and the inclusion of a performance management agent, three alarm categories are created: provider network alarms; user network alarms; predictive alarms.

Global perinatal mortality figures show that of the 132 million births per year, there are between 6 and 7 million perinatal deaths. While 90% of these births are in less developed countries, perinatal deaths take 98% of the global share. These statistics show on average the rates as they were in England during the 1930s. The most common recorded medical causes of perinatal deaths are also similar in the less developed countries, and the common denominators are early childbearing, poor maternal health and above all, the lack of appropriate and quality services. Although life-saving practices for most infants have been known for decades, currently a third of mothers still have no access to services during pregnancy, and almost half do not have access to services for childbirth. There are enormous variations both among and within countries. It takes innovation to find the best fit between the needs of women and infants and resources. A health worker with excellent knowledge and skills is the key resource and the best investment. The cost is moderate, and the investment pays a high dividend in improved health of both the mother and her baby, and better health for the next generation at lower cost.

A quantitative structure-selectivity relationships of series of structurally diverse α 1 -adrenergic antagonists was performed by using counter-propagation neural network (CP-ANN). The theoretical molecular descriptors have been calculated and selected using CODESSA program. The results obtained for a highly non-congeneric set of molecules have confirmed the potential of use of CP-ANN approach in prediction of relative activity (selectivity) of α 1 -adrenergic antagonists.

The Kohonen neural networks were chosen to prepare a relevant model for fast selection of the most suitable phase equilibrium method(s) to be used in efficient vaporliquid chemical process design and simulation. They were trained to classify the objects of the study (the known physical properties and parameters of samples) into none, one or more possible classes (possible methods of phase equilibrium) and to estimate the reliability of the proposed classes (adequacy of different methods of phase equilibrium). Out of the several ones the Kohonen network architecture yielding the best separation of clusters was chosen. Besides the main Kohonen map, maps of physical properties and parameters, and phase equilibrium probability maps were obtained with horizontal intersections of the neural network. A proposition of phase equilibrium methods is represented with the trained neural network.

We point out that the decay mode D^0 -> K^0 \bar{K^0} has no factorizable contribution. In the chiral perturbation language, treating D^0 as heavy, the O(p) contribution is zero. We calculate the nonfactorizable chiral loop contributions of order O(p^3). Then, we use a heavy-light type chiral quark model to calculate nonfactorizable tree level terms, also of order O(p^3), proportional to the gluon condensate. We find that both the chiral loops and the gluon condensate contributions are of the same order of magnitude as the experimental amplitude.

The decay mode D^0 -> K^0 \bar{K^0} has no factorizable contribution. We calculate the nonfactorizable chiral loop contributions of order O(p^3)and then we use a heavy-light type chiral quark model to calculate nonfactorizable tree level terms, also of order O(p^3), proportional to the gluon condensate. Calculated chiral loops and the gluon condensate contributions are of the same order of magnitude as the experimental amplitude.

In the paper Kohonen neural network as an alternative tool for fast selection of suitable physical property estimation method that is very important for efficient chemical process design and simulation is described. Neural networks should advice appropriate methods of phase equilibrium estimation on the basis of known physical properties. In other words, they should classify objects into none, one or more possible classes (possible methods of phase equilibrium) and estimate the reliability of the proposed classes (adequacy of different methods of phase equilibrium). From among several different artificial neural networks, Kohonen neural networks were chosen as the most appropriate for the specific problem. Probability maps for each specific phase equilibrium method were obtained as a result. The analysis of the results confirmed that the hypothesis to use Kohonen networks for separation of the classes was correct.

The two-hybrid system has proved to be a facile method for detecting and analyzing protein-protein interactions. An expanded application of this system, protein linkage mapping, provides a means of identifying interactions on a global scale and should prove a powerful tool in analyzing whole genomes as their sequences become available. To overcome some of the inherent difficulties in such a large-scale approach, we have constructed a set of new strains and vectors that will allow for more efficient screening. The strains contain a GAL1-URA3 reporter for positive and negative selection, as well as a UAS(G)-lacZ reporter. The strains are of opposite mating types, permitting libraries present in one strain to be easily screened against a second library in the companion strain. We also constructed a family of CEN-based vectors for expression of both Gal4 DNA-binding and activation domain fusions. These plasmids include a hemagglutinin epitope tag and different polylinkers to increase the ease of subcloning. CEN-based vectors are maintained at 1-2 copies per cell, limiting the number of individual cells containing multiple plasmids that can confuse further analyses, and ensuring that fusions are not expressed at toxic levels. Using these vectors, both homo- and heterodimeric interactions resulted in up to 10-fold higher reporter gene transcription than obtained with 2micro;-based plasmids, despite significantly lower protein levels. In addition to protein linkage mapping, these reagents should be generally useful in standard two-hybrid applications.

The goals and limitations of some clustering methods are briefly reviewed. In order to avoid the usual methods which are very demanding on computer time and space, a new scheme is proposed for updating (generation) of, and retrieval from, large data bases organized as binary trees. The method is based on calculation of three distances at any given vertex l on the level n, A(l,n) instead of two. The respective distances d1(X,Al), d2(X,Ar), d3(AlAr) are calculated between the input vector X and the left and right descendant of the vertex A(l,n), Al and Ar, respectively. The advantage of the method compared to the standard clustering methods or formation of hierarchal trees is that the required memory or computational time is reduced from N2 to approximately N log N (N is the number of clustering objects).

A new method for the estimation of the atomic-orbital (AO) potentials in infinite systems is suggested. Using this method the potentials of carbon AO's in graphite, of nitrogen and boron AO's in boron nitride, and of aluminum and nitrogen AO's in aluminum nitride were determined. The energy gap in boron nitride calculated by this method (4.4 eV) is in good agreement with the experimental value of 4.3 eV.

A link between a substructure searching system and a 13C NMR data base has been established and permits the retrieval and examination of the chemical shifts associated with specific substructures. The means by which these searches are accomplished is described and the results from the searches are presented and discussed. The system is interactive, and can be used to locate in the data base the chemical shifts of carbon atoms in precisely defined environments. Alternatively, it may be used to learn the range of the chemical shifts possessed by particular types of carbon atoms, such as N-methyl or O-methyl carbons.

The problems of preprocessing of 13C-n.m.r. spectra for hierarchical clustering are discussed. Encoding of the spectra in nonequidistant intervals is proposed. To establish the optimal intervals, a Simplex method with variable-sized movements is used. The optimized parameter is the amount of information contained in the first two coordinates of the transforms, obtained by the application of principal component analysis to the 13C-n.m.r. spectra. The spectra encoded in optimized intervals are used for automated structure elucidation, based on a hierarchical organization of a collection of more than 2000 assigned13C-n.m.r. spectra. The hierarchical trees needed for the library search and prediction of some structural features were generated by a 3-distances clustering method. The retrieval and predictive abilities of the system are discussed.

The fast Fourier transform algorithm is applied to a collection of infrared spectra and the advantages of transformed spectra are discussed in detail. The truncation of the transformed spectra permits a reduction of the computer space needed for the storage of the data collection, and greatly accelerates the computer manipulation of full curve spectra. The latter aspect is particularly important in analysis of mixtures where the identification of components from the spectrum of the unknown mixture is based on “distance” or similarity calculations between the original spectrum of the mixture and any of the possible combination of components. Special emphasis in this calculation was given to the quantitative estimation of the ratio of components in the mixture. Some examples of the procedure for the analysis of mixtures from a collection of 104 infrared spectra of surfactants are discussed in detail.

It has been shown that the 5,6-double bond steroidal thiazolidines can be N-acylated if there is no substituent in the 4'-position on the thiazolidine ring; substituents in the 4'-position of the thiazolidine sterically hinder acylation. On the other hand, the 4,5-double bond steroidal thiazolidine isomers decomposed on attempted acylation. The lability of these 4,5-double bond isomers was attributed to the contribution of a hyperconjugative resonance form to the structure of the 4,5-double bond isomers.

The generation of a hierarchical tree of 500 infrared spectra, using the recently proposed fractal or 3-distances-clustering method is described and discussed. The objects of clustering are infrared spectra of polymer compounds which are represented as sets of 80 complex Fourier coefficients, obtained by fast Fourier transformation of digitized absorbance spectra. The generated hierarchical tree, with a maximum height of 20 and an average height of 12 levels, yields a very satisfactory clustering scheme with respect to the structure of the compounds involved. In addition to very good clustering, a 100% retrieval (prediction) ability was obtained. This was achieved by the use of an iterative procedure after the initial tree had been generated. Additionally, the tree was tested with 240 infrared spectra of different compounds which were taken into account during the generation of the tree. The retrieval success of these test runs is discussed with respect to the structural similarity of the compounds to which the “unknown” spectra were linked.

A computer program that uses on-line generated substructures of organic compounds as input and retrieves the corresponding distributions of 13C-n.m.r. chemical shifts is described and discussed. The procedure of creating the substructures and the main features of the retrieval philosophy are outlined. One search is worked out in detail to demonstrate the ability of the system.

The total energy surface of the (Si2O7)6− ion is calculated from the bend and torsion angles in the SiOSi axis. The results are discussed and compared with the experimental data. The ab initio calculation of (SiO4)4−, as well as the calculation of the charge distributions for all species were made and discussed.

The library search applied as a tool for the fast retrieval of chemical information is described in detail. The advantages, problems, and solutions for different types of data collection and banks (spectral collections, numeric data, textual data, chemical structures) associated with the use of the library search are outlined and discussed.

A conventional infrared spectra collection was converted into computer-readable form. The data format is selected to allow for minimal storage requirements, easy handling, and reconstruction of the source curve.

The magnetic moment μeff and spectroscopic g factor of powdered Ni3TeO6 were measured and found to be μeff = (3.17 ± 0.01) B. M. and g = 2.26 ± 0.02. With a simple LCAO Mo treatment it was shown that the influence of the actual ligand field at a Ni(II) ion, which has C3v symmetry, differs very little from the influence of a cubic octahedral field.