Validation of scientific topic models using graph analysis and corpus metadata

Probabilistic topic modeling algorithms like Latent Dirichlet Allocation (LDA) have become powerful tools for the analysis of large collections of documents (such as papers, projects, or funding applications) in science, technology an innovation (STI) policy design and monitoring. However, selecting an appropriate and stable topic model for a specific application (by adjusting the hyperparameters of the algorithm) is not a trivial problem. Common validation metrics like coherence or perplexity, which are focused on the quality of topics, are not a good fit in applications where the quality of the document similarity relations inferred from the topic model is especially relevant. Relying on graph analysis techniques, the aim of our work is to state a new methodology for the selection of hyperparameters which is specifically oriented to optimize the similarity metrics emanating from the topic model. In order to do this, we propose two graph metrics: the first measures the variability of the similarity graphs that result from different runs of the algorithm for a fixed value of the hyperparameters, while the second metric measures the alignment between the graph derived from the LDA model and another obtained using metadata available for the corresponding corpus. Through experiments on various corpora related to STI, it is shown that the proposed metrics provide relevant indicators to select the number of topics and build persistent topic models that are consistent with the metadata. Their use, which can be extended to other topic models beyond LDA, could facilitate the systematic adoption of this kind of techniques in STI policy analysis and design.

     

Blends of Bio-Based Poly(Limonene Carbonate) with Commodity Polymers

In this study, blends of the bio-based poly(limonene carbonate) (PLimC) with different commodity polymers are investigated in order to explore the potential of PLimC toward generating more sustainable polymer materials by reducing the amount of petro- or food-based polymers. PLimC is employed as minority component in the blends. Next to the morphology and thermal properties of the blends the impact of PLimC on the mechanical properties of the matrix polymers is studied. The interplay of incompatibility and zero-shear melt viscosity contrast determines the blend morphology, leading for all blends to a dispersed droplet morphology for PLimC. Blends with polymers of similar structure to PLimC (i.e., aliphatic/aromatic polyester) show the best performance with respect to mechanical properties, whereas blends with polystyrene or poly(methyl methacrylate) are too brittle and polyamide 12 blends show very low elongations at break. In blends with Ecoflex (poly(butylene adipate-co-terephthalate)) and Arnitel EM400 (copoly(ether ester)) with poly(butylene terephthalate) hard and polytetrahydrofuran soft segments) a threefold increase in E-modulus can be achieved, while keeping the elongation at break at reasonable high values of ≈200%, making these blends highly interesting for applications.     

Optimized Biocatalytic Synthesis of 2-Selenopyrimidine Nucleosides by Transglycosylation**

Selenium-modified nucleosides are powerful tools to study the structure and function of nucleic acids and their protein interactions. The widespread application of 2-selenopyrimidine nucleosides is currently limited by low yields in established synthetic routes. Herein, we describe the optimization of the synthesis of 2-Se-uridine and 2-Se-thymidine derivatives by thermostable nucleoside phosphorylases in transglycosylation reactions using natural uridine or thymidine as sugar donors. Reactions were performed at 60 or 80 °C and at pH 9 under hypoxic conditions to improve the solubility and stability of the 2-Se-nucleobases in aqueous media. To optimize the conversion, the reaction equilibria in analytical transglycosylation reactions were studied. The equilibrium constants of phosphorolysis of the 2-Se-pyrimidines were between 5 and 10, and therefore differ by an order of magnitude from the equilibrium constants of any other known case. Hence, the thermodynamic properties of the target nucleosides are inherently unfavorable, and this complicates their synthesis significantly. A tenfold excess of sugar donor was needed to achieve 40−48 % conversion to the target nucleoside. Scale-up of the optimized conditions provided four Se-containing nucleosides in 6–40 % isolated yield, which compares favorably to established chemical routes.     

Multi-objective particle swarm optimisation based integrated production inventory routing planning for efficient perishable food logistics operations

Sustainable and efficient food supply chain has become an essential component of one’s life. The model proposed in this paper is deeply linked to people's quality of life as a result of which there is a large incentive to fulfil customer demands through it. This proposed model can enhance food quality by making the best possible food quality accessible to customers, construct a sustainable logistics system considering its environmental impact and ensure the customer demand to be fulfilled as fast as possible. In this paper, an extended model is examined that builds a unified planning problem for efficient food logistics operations where four important objectives are viewed: minimising the total expense of the system, maximising the average food quality along with the minimisation of the amount of CO₂ emissions in transportation along with production and total weighted delivery lead time minimisation. A four objective mixed integer linear programming model for intelligent food logistics system is developed in the paper. The optimisation of the formulated mathematical model is proposed using a modified multi-objective particle swarm optimisation algorithm with multiple social structures: MO-GLNPSO (Multi-Objective Global Local Near-Neighbour Particle Swarm Optimisation). Computational results of a case study on a given dataset as well as on multiple small, medium and large-scale datasets followed by sensitivity analysis show the potency and effectiveness of the introduced method. Lastly, there has been a scope for future study displayed which would lead to the further progress of these types of models.     

Deliberately Losing Control of C−H Activation Processes in the Design of Small-Molecule-Fragment Arrays Targeting Peroxisomal Metabolism

Combined photochemical arylation, “nuisance effect” (S_NAr) reaction sequences have been employed in the design of small arrays for immediate deployment in medium-throughput X-ray protein–ligand structure determination. Reactions were deliberately allowed to run “out of control” in terms of selectivity; for example the ortho-arylation of 2-phenylpyridine gave five products resulting from mono- and bisarylations combined with S_NAr processes. As a result, a number of crystallographic hits against NUDT7, a key peroxisomal CoA ester hydrolase, have been identified.     

Microtubule Destabilizing Sulfonamides as an Alternative to Taxane-Based Chemotherapy

Pan-Gyn cancers entail 1 in 5 cancer cases worldwide, breast cancer being the most commonly diagnosed and responsible for most cancer deaths in women. The high incidence and mortality of these malignancies, together with the handicaps of taxanes—first-line treatments—turn the development of alternative therapeutics into an urgency. Taxanes exhibit low water solubility that require formulations that involve side effects. These drugs are often associated with dose-limiting toxicities and with the appearance of multi-drug resistance (MDR). Here, we propose targeting tubulin with compounds directed to the colchicine site, as their smaller size offer pharmacokinetic advantages and make them less prone to MDR efflux. We have prepared 52 new Microtubule Destabilizing Sulfonamides (MDS) that mostly avoid MDR-mediated resistance and with improved aqueous solubility. The most potent compounds, N-methyl-N-(3,4,5-trimethoxyphenyl-4-methylaminobenzenesulfonamide 38, N-methyl-N-(3,4,5-trimethoxyphenyl-4-methoxy-3-aminobenzenesulfonamide 42, and N-benzyl-N-(3,4,5-trimethoxyphenyl-4-methoxy-3-aminobenzenesulfonamide 45 show nanomolar antiproliferative potencies against ovarian, breast, and cervix carcinoma cells, similar or even better than paclitaxel. Compounds behave as tubulin-binding agents, causing an evident disruption of the microtubule network, in vitro Tubulin Polymerization Inhibition (TPI), and mitotic catastrophe followed by apoptosis. Our results suggest that these novel MDS may be promising alternatives to taxane-based chemotherapy in chemoresistant Pan-Gyn cancers.     

ProVoc: An app to train vocabulary depth in order to foster children's reading comprehension

Many studies have demonstrated the crucial role of vocabulary in predicting reading performance in general. More recent work has indicated that one particular facet of vocabulary (its depth) is more closely related to language comprehension, especially inferential comprehension. On this basis, we developed a training application to specifically improve vocabulary depth. The objective of this study was to test the effectiveness of a mobile application designed to improve vocabulary depth. The effectiveness of this training was examined on 3rd and 4th grade children's vocabulary (breadth and depth), decoding and comprehension performances. A randomized waiting-list control paradigm was used in which an experimental group first received the intervention during the first 4 weeks (between pretest and post-test1), thereafter, a waiting control group received the training for the next 4 weeks (between postest1 and posttest2). Results showed that the developed application led to significant improvements in terms of vocabulary depth performance, as well as a significant transfer effect to reading comprehension. However, we did not observe such a beneficial effect on either vocabulary breadth or written word identification. These results are discussed in terms of the links between vocabulary depth and comprehension, and the opportunities the app presents for remedying language comprehension deficits in children.     

A local and global tour on MOMoT

Software and Systems Modeling - Many model transformation scenarios require flexible execution strategies as they should produce models with the highest possible quality. At the same time,...     

One-Pot Methods for the Protection and Assembly of Sugars

In recent years, there has been rapid expansion of glycan synthesis, fueled by the recognition that the structural complexity of sugars translates to a myriad of biological functions. Such chemical syntheses involve many challenges, mostly due to the regio- and stereochemical aspects of glycosidic bond formation. One-pot strategies were developed to assist in attaining faster and more economical access to the glycan constructs. In this front, achievements in protecting group manipulation, glycosylation, and combinations of these have been reported. Protecting group manipulations in one pot take advantage of the reaction compatibility of commonly used transformations, many of which occur in high regioselectivity. Sequential glycosylations, on the other hand, rely on leaving group orthogonalities and reactivity tuning, as well as the preactivation technique. Altogether, these approaches offer attractive means to the much needed glycan structures and, consequently, help usher in advances in glycoscience.     

Makespan minimization with OR-precedence constraints

We consider a variant of the NP-hard problem of assigning jobs to machines to minimize the completion time of the last job. Usually, precedence constraints are given by a partial order on the set of jobs, and each job requires all its predecessors to be completed before it can start. In this paper, we consider a different type of precedence relation that has not been discussed as extensively and is called OR-precedence. In order for a job to start, we require that at least one of its predecessors is completed—in contrast to all its predecessors. Additionally, we assume that each job has a release date before which it must not start. We prove that a simple List Scheduling algorithm due to Graham (Bell Syst Tech J 45(9):1563–1581, 1966) has an approximation guarantee of 2 and show that obtaining an approximation factor of \(4/3 - \varepsilon \) is NP-hard. Further, we present a polynomial-time algorithm that solves the problem to optimality if preemptions are allowed. The latter result is in contrast to classical precedence constraints where the preemptive variant is already NP-hard. Our algorithm generalizes previous results for unit processing time jobs subject to OR-precedence constraints, but without release dates. The running time of our algorithm is \(O(n^2)\) for arbitrary processing times and it can be reduced to O(n) for unit processing times, where n is the number of jobs. The performance guarantees presented here match the best-known ones for special cases where classical precedence constraints and OR-precedence constraints coincide.