Structural Investigation and Molecular Modeling Studies of Strobilurin-Based Fungicides Active against the Rice Blast Pathogen Pyricularia oryzae

The increasing emergence of fungicide-resistant pathogens requires urgent solutions for crop disease management. Here, we describe a structural investigation of new fungicides obtained by combining strobilurin and succinate dehydrogenase inhibitor pharmacophores. We identified compounds endowed with very good activity against wild-type Pyricularia oryzae, combined in some cases with promising activity against strobilurin-resistant strains. The first three-dimensional model of P. oryzae cytochrome bc1 complex containing azoxystrobin as a ligand was developed. The model was validated with a set of commercially available strobilurins, and it well explains both the resistance mechanism to strobilurins mediated by the mutation G143A and the activity of metyltetraprole against strobilurin-resistant strains. The obtained results shed light on the key recognition determinants of strobilurin-like derivatives in the cytochrome bc1 active site and will guide the further rational design of new fungicides able to overcome resistance caused by G143A mutation in the rice blast pathogen.     

Simultaneous measurement of light transmission and heat flow in a modified differential scanning calorimeter

A commercial DSC cell has been modified to allow simultaneous measurement of heat flow and light transmission. A special fiber optic probe capable of transmitting and receiving light is located immediately above the sample. The sample is held in a reflective aluminum pan during the measurement. Maximum optical signal intensity is recorded when the sample becomes completely transparent. The light from the probe will pass through the sample, reflect off the bottom of the pan, and then pass up through the sample again and back into the probe. The method was developed to augment the normal DSC heat-flow measurement. We find that the additional optical information is useful in elucidating the nature of thermal transitions in polymeric materials. Any transition, physical or chemical, that is accompanied by an appreciable change in optical transmission can be studied by this technique. The probe is useful even in investigations where only the optical signal is desired, because one can make use of the temperature programming and data aquisition capabilities of the DSC instrument. The presence of the probe tip near the sample does not seriously degrade the heat-flow signal. Good calorimetric accuracy is maintained, albeit some baseline curvature is introduced. Several applications of the technique are described. These include melting and crystallization of polymers, solubility behavior of polymer–polymer and polymer–additive blends, and sintering of polymer particles during oxidative degradation.     

Guanine and plasmid DNA binding of mono- and trinuclear fac-[Re(CO)3]+ complexes with amino acid ligands

We have synthesized and fully characterized four new complexes comprising the fac-[Re(CO)3]+ moiety and the ligands NH3, L-proline (Pro), or N,N-dimethylglycine (dmGly). The reaction of [Re(H2O)3(CO)3]+ with the two amino acids gives trinuclear complexes of general formula [Re(L)(CO)3]3 (where L = amino acid). We have studied the in vitro behavior of these compounds with guanine and DNA in order to understand whether the cytotoxicity exhibited by certain rhenium complexes based on the fac-[Re(CO)3]+ core is due to the formation of nucleobase complexes and inter- or intrastrand links between DNA bases. We have performed model studies with guanine and studied the structural effects induced by different rhenium(I) tricarbonyl complexes on PhiX174 plasmid DNA by electrophoretic methods. Our results show that rhenium complexes with two available coordination sites interact with plasmid DNA to form a stable adduct that is likely to involve two bases.     

EDT Method for Multiple Labelled Objects Subject to Tied Distances

Machine Intelligence Research - The success of new scientific areas can be assessed by their potential for contributing to new theoretical approaches aligned with real-world applications. The...     

Assessing the impact of real-time machine translation on multilingual meetings in global software projects

Communication in global software development is hindered by language differences in countries with a lack of English speaking professionals. Machine translation is a technology that uses software to translate from one natural language to another. The progress of machine translation systems has been steady in the last decade. As for now, machine translation technology is particularly appealing because it might be used, in the form of cross-language chat services, in countries that are entering into global software projects. However, despite the recent progress of the technology, we still lack a thorough understanding of how real-time machine translation affects communication. In this paper, we present a set of empirical studies with the goal of assessing to what extent real-time machine translation can be used in distributed, multilingual requirements meetings instead of English. Results suggest that, despite far from 100 % accurate, real-time machine translation is not disruptive of the conversation flow and, therefore, is accepted with favor by participants. However, stronger effects can be expected to emerge when language barriers are more critical. Our findings add to the evidence about the recent advances of machine translation technology and provide some guidance to global software engineering practitioners in regarding the losses and gains of using English as a lingua franca in multilingual group communication, as in the case of computer-mediated requirements meetings.     

SOA-enabled compliance management: instrumenting, assessing, and analyzing service-based business processes

Facilitating compliance management, that is, assisting a company’s management in conforming to laws, regulations, standards, contracts, and policies, is a hot but non-trivial task. The service-oriented architecture (SOA) has evolved traditional, manual business practices into modern, service-based IT practices that ease part of the problem: the systematic definition and execution of business processes. This, in turn, facilitates the online monitoring of system behaviors and the enforcement of allowed behaviors—all ingredients that can be used to assist compliance management on the fly during process execution. In this paper, instead of focusing on monitoring and runtime enforcement of rules or constraints, we strive for an alternative approach to compliance management in SOAs that aims at assessing and improving compliance. We propose two ingredients: (i) a model and tool to design compliant service-based processes and to instrument them in order to generate evidence of how they are executed and (ii) a reporting and analysis suite to create awareness of a company’s compliance state and to enable understanding why and where compliance violations have occurred. Together, these ingredients result in an approach that is close to how the real stakeholders—compliance experts and auditors—actually assess the state of compliance in practice and that is less intrusive than enforcing compliance.     

A kernel-based framework for image collection exploration

While search engines have been a successful tool to search text information, image search systems still face challenges. The keyword-based query paradigm used to search in image collection systems, which has been successful in text retrieval, may not be useful in scenarios where the user does not have the precise way to express a visual query. Image collection exploration is a new paradigm where users interact with the image collection to discover useful and relevant pictures. This paper proposes a framework for the construction of an image collection exploration system based on kernel methods, which offers a mathematically strong basis to address each stage of an image collection exploration system: image representation, summarization, visualization and interaction. In particular, our approach emphasizes a semantic representation of images using kernel functions, which can be seamlessly harnessed across all system components. Experiments were conducted with real users to verify the effectiveness and efficiency of the proposed strategy.     

Multi-target tracking on confidence maps: An application to people tracking

We propose a generic online multi-target track-before-detect (MT-TBD) that is applicable on confidence maps used as observations. The proposed tracker is based on particle filtering and automatically initializes tracks. The main novelty is the inclusion of the target ID in the particle state, enabling the algorithm to deal with unknown and large number of targets. To overcome the problem of mixing IDs of targets close to each other, we propose a probabilistic model of target birth and death based on a Markov Random Field (MRF) applied to the particle IDs. Each particle ID is managed using the information carried by neighboring particles. The assignment of the IDs to the targets is performed using Mean-Shift clustering and supported by a Gaussian Mixture Model. We also show that the computational complexity of MT-TBD is proportional only to the number of particles. To compare our method with recent state-of-the-art works, we include a postprocessing stage suited for multi-person tracking. We validate the method on real-world and crowded scenarios, and demonstrate its robustness in scenes presenting different perspective views and targets very close to each other.