Using Neural Network Classifier Support Vector Machine Regression for the prediction of Melting Point of Drug – like compounds

In our study we use a kernel based classification technique, Support Vector Machine Regression for predicting the Melting Point of Drug – like compounds in terms of Topological Descriptors, Topological Charge Indices, Connectivity Indices and 2D Auto Correlations. The Machine Learning model was designed, trained and tested using a dataset of 100 compounds and it was found that an SVMReg model with RBF Kernel could predict the Melting Point with a mean absolute error 15.5854 and Root Mean Squared Error 19.7576

Agri-environmental evaluation of traditional and alternative corn production systems in Chiapas, Mexico

This study evaluates the effects of environmental variables on traditional and alternative agroecosystems in three Ejidos (communal lands) in the Chiapas rainforest in Mexico. The tests occurred within two seasonal agricultural cycles. In spring-summer, experiments were performed with the traditional slash, fell and burn (S-F-B) system, no-burn systems and rotating systems with Mucuna deeringiana Bort., and in the autumn-winter agricultural cycle, three no-burn systems were compared to evaluate the effect of alternative sowing with corn (no-burn and topological modification of sowing). The results show a high floristic diversity in the study area (S_S = 4 - 23%), with no significant differences among the systems evaluated. In the first cycle, the analysis of the agronomical variables of the corn indicated better properties in the fallowing systems, with an average yield of 1950 kg ha^‑1, but there was variation related to the number of years left fallow. In the second cycle, the yields were positive for the alternative technology (average yield 3100 kg ha^‑1). The traditional S-F-B systems had reduced pests and increased organic matter and soil phosphorous content. These results are the consequence of fallow periods and adaptation to the environment; thus, this practice in the Chiapas rainforest constitutes an ethnocultural reality, which is unlikely to change in the near future if the agrosystems are managed based on historical principles.

Schauder – Zur Dekonstruktion eines Spürens

Zusammenfassung: Ziel der Arbeit ist den Sinn von Schauder philosophisch zu erhellen. An einem Einzelphänomen, wie es so bisher nicht behandelt wurde, wird zugleich das Geflecht von Affekt/Emotion/Gefühl, gestützt auf Hegel, Heidegger, Husserl, Freud und Lacan, in immer neuen Ansätzen kritisch reflektiert und Zug um Zug mit Derrida dekonstruiert. In einem Textverfahren, das sich auch grafisch durch gegenübergestellte Kolumnen auszeichnet, werden heterogene Ansätze zum Sinn von Schauder mit dekonstruktivistischen Einsichten konfrontiert. Die Ansätze, Schauder über Datum, Begriff, Phänomen oder Strukturelement bestimmen zu wollen, durchdringen sich dabei mit denjenigen, die sich einer solchen Bestimmung entziehen (Hegels Negativität, Heideggers Seinsentzug oder Lacans Signifikantenmangel). Am Fokus Schauder, an dem sich das Fiktive einer mit sich selbst identischen Präsenz besonders eindringlich darstellt, werden so spezifische Aporien der Metaphysik der Präsenz entfaltet und die Geschlossenheit logozentristischer Systeme in die Bewegung einer anderen Öffnung und Schließung im Sinn der Schrift bzw. des allgemeinen Textes transformiert. Neben der différance, dem Entzug der Metapher, dem Supplement und dem Gespenstischen stützt sich die Arbeit auf die Iterabilität, bei der im selben Zug die Identität des Sinns gestiftet und zerstreut wird (Dissemination). Im Kapitel Piloerection werden Ambivalenzen und Paradoxien des Schauders am Beispiel von computergestützten empirisch-psychologischen Studien aufgezeigt. Im Kapitel Atopologie des Schauders prädikative, propositionale und topologische Bedingungen zum Sinn von Schauder analysiert und dekonstruiert. Ebenso, im Folgekapitel Etymon, etymologische und technisch-mediale Bedingungen. Im Schlußkapitel Maß, Anmaß, Unmaß der Empfindung des Schauders wird am Beispiel der konkreten Beiträge zum Schauder von Aristoteles, Kant, Fechner, Otto, Klages, Lorenz und Adorno aufgezeigt, dass (1) ein Schauder nicht von einem Außen aus an-gemessen werden kann, (2) sich im Schauder die metaphysische Opposition von Fiktion und Realität in einer Unentscheidbarkeit zerstreut, (3) dass trotz der Heterogenität der Ansätze in diesen Beiträgen eine Komplizenschaft zum Ausdruck kommt: ein Begehren nach Präsenz, das durch den Ausschluß des Anderen zugleich die Gewalt des Einen produziert, (4) dass der Signifikant Schauder, der selbst in Abwesenheit eines Referenten, eines bestimmten Signifikats, einer aktuellen Bedeutungs­intention, eines Sen­ders oder Empfängers funktioniert, als verändertes Zu­rückbleiben eines differenzieller Zeichens betrachtet werden muss, als Effekt von Spuren, die sich nur in ihrem eige­nen Auslöschen ereignen. Die Arbeit schließt mit dem Vorschlag, Spüren jenseits von Arché, Telos oder Eschaton, jenseits eines Phallogozentrismus in der derridaschen Spur zu denken. Nicht zuletzt über diese Pfropfung, wie sie im Französischen [trace] so nicht möglich ist, schließt sie als deutschsprachiger Beitrag an sein Werk an.

A Distributed Model for Mobile Robot Environment-Learning and Navigation

A distributed method for mobile robot navigation, spatial learning, and path planning is presented. It is implemented on a sonar-based physical robot, Toto, consisting of three competence layers: 1) Low-level navigation: a collection of reflex-like rules resulting in emergent boundary-tracing. 2) Landmark detection: dynamically extracts landmarks from the robot's motion. 3) Map learning: constructs a distributed map of landmarks. The parallel implementation allows for localization in constant time. Spreading of activation computes both topological and physical shortest paths in linear time. The main issues addressed are: distributed, procedural, and qualitative representation and computation, emergent behaviors, dynamic landmarks, minimized communication.

Understanding Subsystems in Biology through Dimensionality Reduction, Graph Partitioning and Analytical Modeling

Biological systems exhibit rich and complex behavior through the orchestrated interplay of a large array of components. It is hypothesized that separable subsystems with some degree of functional autonomy exist; deciphering their independent behavior and functionality would greatly facilitate understanding the system as a whole. Discovering and analyzing such subsystems are hence pivotal problems in the quest to gain a quantitative understanding of complex biological systems. In this work, using approaches from machine learning, physics and graph theory, methods for the identification and analysis of such subsystems were developed. A novel methodology, based on a recent machine learning algorithm known as non-negative matrix factorization (NMF), was developed to discover such subsystems in a set of large-scale gene expression data. This set of subsystems was then used to predict functional relationships between genes, and this approach was shown to score significantly higher than conventional methods when benchmarking them against existing databases. Moreover, a mathematical treatment was developed to treat simple network subsystems based only on their topology (independent of particular parameter values). Application to a problem of experimental interest demonstrated the need for extentions to the conventional model to fully explain the experimental data. Finally, the notion of a subsystem was evaluated from a topological perspective. A number of different protein networks were examined to analyze their topological properties with respect to separability, seeking to find separable subsystems. These networks were shown to exhibit separability in a nonintuitive fashion, while the separable subsystems were of strong biological significance. It was demonstrated that the separability property found was not due to incomplete or biased data, but is likely to reflect biological structure.

Lecture notes

Lecture notes in LaTex

Exercise sheet 2 pdf

Exercises and solutions in PDF

Exercise sheet 2

Exercises and solutions in LaTex

Lecture notes pdf

Lecture notes in PDF

Lecture notes pdf

Lecture notes in PDF

Lecture notes

Lecture notes in LaTex

Programming Principles: The Java Library

In this session we point you at the Java Library, and go into some more details on how Strings work. We also introduce the HashMap class (a very useful type of collection).

Self-organized sociopolitical interactions as the best way to achieve organized patterns in human social systems: going beyond the top-down control of classical political regimes

La monografía presenta la auto-organización sociopolítica como la mejor manera de lograr patrones organizados en los sistemas sociales humanos, dada su naturaleza compleja y la imposibilidad de las tareas computacionales de los regímenes políticos clásico, debido a que operan con control jerárquico, el cual ha demostrado no ser óptimo en la producción de orden en los sistemas sociales humanos. En la monografía se extrapola la teoría de la auto-organización en los sistemas biológicos a las dinámicas sociopolíticas humanas, buscando maneras óptimas de organizarlas, y se afirma que redes complejas anárquicas son la estructura emergente de la auto-organización sociopolítica.

The relevance of the Laplacian of intracule and extracule density distributions for analyzing electron-electron interactions in molecules

A topological analysis of intracule and extracule densities and their Laplacians computed within the Hartree-Fock approximation is presented. The analysis of the density distributions reveals that among all possible electron-electron interactions in atoms and between atoms in molecules only very few are located rigorously as local maxima. In contrast, they are clearly identified as local minima in the topology of Laplacian maps. The conceptually different interpretation of intracule and extracule maps is also discussed in detail. An application example to the C2H2, C2H4, and C2H6 series of molecules is presented

Exploring chromium (VI) dioxodihalides chemistry: is density functional theory the most suitable tool?

A comparative systematic study of the CrO2F2 compound has been performed using different conventional ab initio methodologies and density functional procedures. Two points have been analyzed: first, the accuracy of results yielded by each method under study, and second, the computational cost required to reach such results. Weighing up both aspects, density functional theory has been found to be more appropriate than the Hartree-Fock (HF) and the analyzed post-HF methods. Hence, the structural characterization and spectroscopic elucidation of the full CrO2X2 series (X=F,Cl,Br,I) has been done at this level of theory. Emphasis has been given to the unknown CrO2I2 species, and specially to the UV/visible spectra of all four compounds. Furthermore, a topological analysis in terms of charge density distributions has revealed why the valence shell electron pair repulsion model fails in predicting the molecular shape of such CrO2X2 complexes