Synthesis and Structure of [NbCl3{[NPPh2(C5H4)]2Fe}]: The First Structurally Characterised Complex Containing a Chelating Di(phosphaneiminato) Ligand

Reaction of [Fe{(C₅H₄)PPh₂=NSiMe₃}₂] with niobium pentachloride affords the chelate complex [NbCl₃{[NPPh₂(C₅H₄)]₂Fe}].     

Design of SARS-CoV-2 Main Protease Inhibitors Using Artificial Intelligence and Molecular Dynamic Simulations

Drug design is a time-consuming and cumbersome process due to the vast search space of drug-like molecules and the difficulty of investigating atomic and electronic interactions. The present paper proposes a computational drug design workflow that combines artificial intelligence (AI) methods, i.e., an evolutionary algorithm and artificial neural network model, and molecular dynamics (MD) simulations to design and evaluate potential drug candidates. For the purpose of illustration, the proposed workflow was applied to design drug candidates against the main protease of severe acute respiratory syndrome coronavirus 2. From the ∼140,000 molecules designed using AI methods, MD analysis identified two molecules as potential drug candidates.     

Sensitizer-controlled photochemical reactivity via upconversion of red light

By combining the energy input from two red photons, chemical reactions that would normally require blue or ultraviolet irradiation become accessible. Key advantages of this biphotonic excitation strategy are that red light usually penetrates deeper into complex reaction mixtures and causes less photo-damage than direct illumination in the blue or ultraviolet. Here, we demonstrate that the primary light-absorber of a dual photocatalytic system comprised of a transition metal-based photosensitizer and an organic co-catalyst can completely alter the reaction outcome. Photochemical reductions are achieved with a copper(i) complex in the presence of a sacrificial electron donor, whereas oxidative substrate activation occurs with an osmium(ii) photosensitizer. Based on time-resolved laser spectroscopy, this changeover in photochemical reactivity is due to different underlying biphotonic mechanisms. Following triplet energy transfer from the osmium(ii) photosensitizer to 9,10-dicyanoanthracene (DCA) and subsequent triplet–triplet annihilation upconversion, the fluorescent singlet excited state of DCA triggers oxidative substrate activation, which initiates the cis to trans isomerization of an olefin, a [2 + 2] cycloaddition, an aryl ether to ester rearrangement, and a Newman–Kwart rearrangement. This oxidative substrate activation stands in contrast to the reactivity with a copper(i) photosensitizer, where photoinduced electron transfer generates the DCA radical anion, which upon further excitation triggers reductive dehalogenations and detosylations. Our study provides the proof-of-concept for controlling the outcome of a red-light driven biphotonic reaction by altering the photosensitizer, and this seems relevant in the greater context of tailoring photochemical reactivities.

Triplet–triplet annihilation upconversion enables oxidative activation of substrates that would normally require blue or green light irradiation. Photocatalysis experiments are complemented by in-depth laser spectroscopic investigations.     

A rotation method which gives linear estimates for powers of the Ahlfors–Beurling operator

In [O. Dragičević, A. Volberg, Sharp estimate of the Ahlfors–Beurling operator via averaging martingale transforms, Michigan Math. J. 51 (2) (2003) 415–435] the Ahlfors–Beurling operator T was represented as an average of two-dimensional martingale transforms. The same result can be proven for powers Tⁿ. Motivated by [T. Iwaniec, G. Martin, Riesz transforms and related singular integrals, J. Reine Angew. Math. 473 (1996) 25–57], we deduce from here that Tⁿ_p are bounded from above by Cnp^*, . We further improve this estimate to obtain the optimal behaviour of the L^p norms in question.     

Informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography and high-resolution mass spectrometry (GCxGC-HRMS)

This paper describes informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution mass spectrometry (HRMS). GCxGC-HRMS analysis produces large data sets that are rich with information, but highly complex. The size of the data and volume of information requires automated processing for comprehensive cross-sample analysis, but the complexity poses a challenge for developing robust methods. The approach developed here analyzes GCxGC-HRMS data from multiple samples to extract a feature template that comprehensively captures the pattern of peaks detected in the retention-times plane. Then, for each sample chromatogram, the template is geometrically transformed to align with the detected peak pattern and generate a set of feature measurements for cross-sample analyses such as sample classification and biomarker discovery. The approach avoids the intractable problem of comprehensive peak matching by using a few reliable peaks for alignment and peak-based retention-plane windows to define comprehensive features that can be reliably matched for cross-sample analysis. The informatics are demonstrated with a set of 18 samples from breast-cancer tumors, each from different individuals, six each for Grades 1-3. The features allow classification that matches grading by a cancer pathologist with 78% success in leave-one-out cross-validation experiments. The HRMS signatures of the features of interest can be examined for determining elemental compositions and identifying compounds.     

Semi-Classical Green Kernel Asymptotics for the Dirac Operator

We consider a semi-classical Dirac operator in d ∈ ? spatial dimensions with a smooth potential whose partial derivatives of any order are bounded by suitable constants. We prove that the distribution kernel of the inverse operator evaluated at two distinct points fulfilling a certain hypothesis can be represented as the product of an exponentially decaying factor involving an associated Agmon distance and some amplitude admitting a complete asymptotic expansion in powers of the semi-classical parameter. Moreover, we find an explicit formula for the leading term in that expansion.     

Carnap,Goguen, and the Hyperontologies: Logical Pluralism and Heterogeneous Structuring in Ontology Design

This paper addresses questions of universality related to ontological engineering, namely aims at substantiating (negative) answers to the following three basic questions: (i) Is there a ‘universal ontology’?, (ii) Is there a ‘universal formal ontology language’?, and (iii) Is there a universally applicable ‘mode of reasoning’ for formal ontologies? To support our answers in a principled way, we present a general framework for the design of formal ontologies resting on two main principles: firstly, we endorse Rudolf Carnap’s principle of logical tolerance by giving central stage to the concept of logical heterogeneity, i.e. the use of a plurality of logical languages within one ontology design. Secondly, to structure and combine heterogeneous ontologies in a semantically well-founded way, we base our work on abstract model theory in the form of institutional semantics, as forcefully put forward by Joseph Goguen and Rod Burstall. In particular, we employ the structuring mechanisms of the heterogeneous algebraic specification language HetCasl for defining a general concept of heterogeneous, distributed, highly modular and structured ontologies, called hyperontologies. Moreover, we distinguish, on a structural and semantic level, several different kinds of combining and aligning heterogeneous ontologies, namely integration, connection, and refinement. We show how the notion of heterogeneous refinement can be used to provide both a general notion of sub-ontology as well as a notion of heterogeneous equivalence of ontologies, and finally sketch how different modes of reasoning over ontologies are related to these different structuring aspects.