Results of Proficiency Testing for Trichinella in Poland, 2015–2019

Trichinellosis is a zoonotic meat-borne disease caused by the nematodes of the genus Trichinella. Meat containing live Trichinella larvae is a source of infection. The examination of meat for Trichinella was introduced in 1869, but the digestion method for this did not appear in Poland until the late 1970s. Nowadays, the meat of all food animals susceptible to Trichinella spp. is examined in the frame of official post mortem control with the digestion method. The majority of laboratories in Poland meet the requirements of the ISO/IEC 17025 Standard (352 field laboratories). Laboratory personnel participate in quality control programs. This paper presents the results of proficiency tests (PTs) organized within 2015–2019 in Poland. Over this period, the laboratories examined 7580 samples (contamination levels: zero, one, three, and five larvae). Each laboratory was provided with a set of samples (one negative and three positive). Over 95% of the samples were considered correct in qualitative assessments, though the results of the quantitative evaluations were slightly lower, with 89% of samples being considered correct. Based on a sample evaluation, 88% of laboratories passed the PT comparison. A slight decrease was observed in the examination of samples spiked with five larvae, and great progress was achieved in samples containing three larvae. Low levels of sample contamination are sought after in laboratories but may make evaluations difficult. For this reason, we must consider increasing the number of larvae added to the samples in the next PTs.

Reference-guided structure-aware deep sketch colorization for cartoons

Digital cartoon production requires extensive manual labor to colorize sketches with visually pleasant color composition and color shading. During colorization, the artist usually takes an existing cartoon image as color guidance, particularly when colorizing related characters or an animation sequence. Reference-guided colorization is more intuitive than colorization with other hints, such as color points or scribbles, or text-based hints. Unfortunately, reference-guided colorization is challenging since the style of the colorized image should match the style of the reference image in terms of both global color composition and local color shading. In this paper, we propose a novel learning-based framework which colorizes a sketch based on a color style feature extracted from a reference color image. Our framework contains a color style extractor to extract the color feature from a color image, a colorization network to generate multi-scale output images by combining a sketch and a color feature, and a multi-scale discriminator to improve the reality of the output image. Extensive qualitative and quantitative evaluations show that our method outperforms existing methods, providing both superior visual quality and style reference consistency in the task of reference-based colorization.

A software toolkit for modeling human sentence parsing: An approach using continuous-time, discrete-state stochastic dynamical systems

We present a new software toolkit for implementing a broad class oftheories of sentence processing. In this framework, processing a word ina sentence is viewed as a continuous-time random walk through a set ofdiscrete states that encode information about the emerging structure of thesentence so far. The state space includes one or more special absorbingstates, which, when reached, indicate the decision to move on to the nextword of the sentence. This setup allows us to ask how how long it takesto reach an absorbing state and what the probability of reaching this stateis. We summarize a number of important statistics that can be directlyrelated to human reading times and comprehension question performance.To illustrate the use of the toolkit, we model two types of garden paths,local coherence effects, and the ambiguity advantage using three qualitativelydifferent theories of sentence processing. While the modeler must still makedefensible theoretical and implementation choices, this framework representsan improvement over the descriptive, paper-pencil modeling that is thenorm in psycholinguistics by facilitating quantitative evaluations of modelperformance and laying the groundwork for Bayesian fitting of free parametersin a model. An open-source Python package is provided.

Valuing Domestic Transport Infrastructure: A View from the Route Choice of Exporters

A key input to quantitative evaluations of transport infrastructure projects is their impact on transport costs. We propose a new method of estimating this impact relying on widely accessible customs data: by using the route choice of exporters. We combine our method with a spatial equilibrium model to study the effects of the massive expressway construction in China between 1999 and 2010. We find transport costs are 20% lower on expressways than on regular roads. The expressways construction increases aggregate exports by 10% and domestic trade by 14%. It generates 5.1% welfare gains, implying a 150% net return to investment.

The Efficiency of Biocidal Silica Nanosystems for the Conservation of Stone Monuments: Comparative In Vitro Tests against Epilithic Green Algae

In the last decade, worldwide research has focused on innovative natural biocides and the development of organic and inorganic nanomaterials for long-lasting reliability. In this work, the biocide effects of two different biocides encapsulated in two different silica nanosystems for a multifunctional coating have been performed through in vitro tests, by using Chlorococcum sp. as a common stone biodeteriogen. Zosteric sodium salt (ZS), a green biocide, was compared with the commercial biocide, 2-mercaptobenzothiazole (MBT), widely used in the treatment of cultural heritage. The analyzed systems are the following: silica nanocapsules (NC) and silica nanoparticles (MNP) not loaded with biocides, two nanosystems loaded with ZS and MBT, and free biocides. The qualitative and quantitative evaluations of biocide efficiency were performed periodically, analyzing pigment autofluorescence to discriminate between active and inactive/dead cells. The analyses showed multiple differences. All the nanocontainers presented an initial reduction in chlorophyll’s autofluorescence. For the free biocide, the results highlighted higher efficiency for MBT than ZS. Finally, the nanosystems loaded with the different biocides highlighted a higher activity for nanocontainers loaded with the commercial biocide than the green product, and better efficiency for MNP in comparison with NC.

Retrieval from software libraries for bug localization

This retrospective on our 2011 MSR publication starts with the research milieu that led to the work reported in our paper. We brie y review the competing ideas of a decade ago that could be applied to solving the problem of identifying the les in a software library related to a query. We were especially interested in nding out if the more complex text retrieval methods of that time would be e ective in the software context. A surprising conclusion of our paper was that the reality was exactly the opposite: the more traditional simpler methods outperformed the complex methods. In addition to this surprising result, our paper was also the rst to report what was considered at that time a large-scale quantitative evaluation of the IR-based approaches to automatic bug localization. Over the years, such quantitative evaluations have become the norm. We believe that these contributions were largely responsible for the popularity of this paper in the research literature.

Comparison of bias and resolvability in single-cell and single-transcript methods

Single-cell and single-transcript measurement methods have elevated our ability to understand and engineer biological systems. However, defining and comparing performance between methods remains a challenge, in part due to the confounding effects of experimental variability. Here, we propose a generalizable framework for performing multiple methods in parallel using split samples, so that experimental variability is shared between methods. We demonstrate the utility of this framework by performing 12 different methods in parallel to measure the same underlying reference system for cellular response. We compare method performance using quantitative evaluations of bias and resolvability. We attribute differences in method performance to steps along the measurement process such as sample preparation, signal detection, and choice of measurand. Finally, we demonstrate how this framework can be used to benchmark different methods for single-transcript detection. The framework we present here provides a practical way to compare performance of any methods.