Objective meat quality measurements of ham: A practical classification method on the slaughterline

Meat quality is one of the principal problems in Spanish dry cured ham productuon. At the experimental level, there are well developed objective instrumental measurements which can be made on the slaughterline and then, by applying the correct statistical treatment, these measurements can be used to classify hams with an acceptable degree of accuracy. These treatments, however, are not easy to apply in the industry.

In this work, 312 pork carcasses were tested at three industrial abbatoirs. Ham meat quality was determined by internal light scattering (FOP), electrical conductivity (EC) and pH measurements in Semimembranosus (SM) muscle at 45 min and 24 h post mortem. The results obtained were: 21 (6.7%) DFD; 168 (53.9%) slightly DFD; 104 (33.3%) normal; 11 (3.5%) slightly PSE; and 8 (2.6%) PSE.

A simplified method has been developed for classifying hams into quality categories, by deriving a theoretical quality value (Q) based on a simple statistical treatment of values for FOP, EC and pH. The multiple linear regression coefficient of Q was R² = 0.85 (P<0.001) with respect to the experimental variables.     

Improving robustness of industrial object detection by automatic generation of synthetic images from CAD models

Object detection (OD) is used for visual quality control in factories. Images that compose training datasets are often collected directly from the production line and labeled with bounding boxes manually. Such data represent well the inference context but might lack diversity, implying a risk of overfitting. To address this issue, we propose a dataset construction method based on an automated pipeline, which receives a CAD model of an object and returns a set of realistic synthetic labeled images (code publicly available). Our approach can be easily used by non-expert users and is relevant for industrial applications, where CAD models are widely available. We performed experiments to compare the use of datasets obtained by the two different ways—collecting and labeling real images or applying the proposed automated pipeline—in the classification of five different industrial parts. To ensure that both approaches can be used without deep learning expertise, all training parameters were kept fixed during these experiments. In our results, both methods were successful for some objects but failed for others. However, we have shown that the combined use of real and synthetic images led to better results. This finding has the potential to make industrial OD models more robust to poor data collection and labeling errors, without increasing the difficulty of the training process.     

A quantitative approach to ranking corporate law precedents in the Brazilian Superior Court of Justice

This paper aims to contribute to the goal of finding influential legal precedents by quantitative methods. A lot of work has been made in this direction worldwide, especially in the context of common law jurisdictions. However, this type of work is extremely scarce in the Brazilian literature. In addition, our work also contributes to the research of network analysis and the law by applying these methods to unprecedented amount of data and narrowing our inquiry to a single law area, corporate law. Furthermore, whereas most of the literature applying network analysis to judicial decisions had access to readily available data on the citations to precedent within each ruling, our raw data was nothing but the full text of decisions. We focus on data produced by the Superior Court of Justice (STJ), the highest court in Brazil for matters of federal law, including statutory interpretation of civil, criminal and corporate law. The Court issued an astonishing 282040 opinions tagged as related to corporate law between 2008 and 2018. This amount of cases is unparalleled internationally for superior courts and for studies in network analysis and law. In our results, we rank precedents quantitatively based on the citations they receive and make. We also qualitatively analyze some of the results, especially related to groups identified in the network with the Modularity algorithm. Our findings also reveal that corporate law jurisprudence in the STJ is quantitatively dominated by a few legal issues around one single theme that is only tangentially related to corporate law. That is, a type of contract used for the expansion of telephone landlines, which also allowed the consumer to become a shareholder of the telecommunication company. This comparison is especially pertinent because the utter lack of data on the quantitative weight of STJ precedents means the national literature has been operating in a void of objective measurements, one which has been filled with cherry-picked rulings and subjective ranking criteria.

     

The Genetic Heterogeneity among Different Mouse Strains Impacts the Lung Injury Potential of Multiwalled Carbon Nanotubes

Genetic variation constitutes an important variable impacting the susceptibility to inhalable toxic substances and air pollutants, as reflected by epidemiological studies in humans and differences among animal strains. While multiwalled carbon nanotubes (MWCNTs) are capable of causing lung fibrosis in rodents, it is unclear to what extent the genetic variation in different mouse strains influence the outcome. Four inbred mouse strains, including C57Bl/6, Balb/c, NOD/ShiLtJ, and A/J, to test the pro‐fibrogenic effects of a library of MWCNTs in vitro and in vivo are chosen. Ex vivo analysis of IL‐1β production in bone marrow‐derived macrophages (BMDMs) as molecular initiating event (MIE) is performed. The order of cytokine production (Balb/c > A/J > C57Bl/6 > NOD/ShiLtJ) in BMDMs is also duplicated during assessment of IL‐1β production in the bronchoalveolar lavage fluid of the same mouse strains 40 h after oropharyngeal instillation of a representative MWCNT. Animal test after 21 d also confirms a similar hierarchy in TGF‐β1 production and collagen deposition in the lung. Statistical analysis confirms a correlation between IL‐1β production in BMDM and the lung fibrosis. All considered, these data demonstrate that genetic background indeed plays a major role in determining the pro‐fibrogenic response to MWCNTs in the lung.     

Hybrid Nanoscopy of Hybrid Nanomaterials

The combination of complementary techniques to characterize materials at the nanoscale is crucial to gain a more complete picture of their structure, a key step to design and fabricate new materials with improved properties and diverse functions. Here it is shown that correlative atomic force microscopy (AFM) and localization‐based super‐resolution microscopy is a useful tool that provides insight into the structure and emissive properties of fluorescent β‐lactoglobulin (βLG) amyloid‐like fibrils. These hybrid materials are made by functionalization of βLG with organic fluorophores and quantum dots, the latter being relevant for the production of 1D inorganic nanostructures templated by self‐assembling peptides. Simultaneous functionalization of βLG fibers by QD655 and QD525 allows for correlative AFM and two‐color super‐resolution fluorescence imaging of these hybrid materials. These experiments allow the combination of information about the topography and number of filaments that compose a fibril, as well as the emissive properties and nanoscale spatial distribution of the attached fluorophores. This study represents an important step forward in the characterization of multifunctionalized hybrid materials, a key challenge in nanoscience.     

Lateral Magnetically Modulated Multilayers by Combining Ion Implantation and Lithography

The combination of lithography and ion implantation is demonstrated to be a suitable method to prepare lateral multilayers. A laterally, compositionally, and magnetically modulated microscale pattern consisting of alternating Co (1.6 µm wide) and Co‐CoO (2.4 µm wide) lines has been obtained by oxygen ion implantation into a lithographically masked Au‐sandwiched Co thin film. Magnetoresistance along the lines (i.e., current and applied magnetic field are parallel to the lines) reveals an effective positive giant magnetoresistance (GMR) behavior at room temperature. Conversely, anisotropic magnetoresistance and GMR contributions are distinguished at low temperature (i.e., 10 K) since the O‐implanted areas become exchange coupled. This planar GMR is principally ascribed to the spatial modulation of coercivity in a spring‐magnet‐type configuration, which results in 180° Néel extrinsic domain walls at the Co/Co‐CoO interfaces. The versatility, in terms of pattern size, morphology, and composition adjustment, of this method offers a unique route to fabricate planar systems for, among others, spintronic research and applications.     

Quantification of different effects occurring during fatigue tests on bituminous mixtures

Quantification of different effects (nonlinearity, heating, thixotropy, and fatigue) occurring during fatigue tests on bituminous mixtures is presented in this paper. A focus is given on the nonlinearity phenomenon. Continuous fatigue tests and a test with specific protocol (called fatigue tests to estimate biasing effects) were performed in tension/compression mode on cylindrical samples of the same material. The analysis of results reveals that reversible effects (nonlinearity, heating, and thixotropy) are important (more than 90% decrease at 100,000 cycles for a strain amplitude of 100 μm/m at 10 Hz) and cannot be ignored when interpreting classical fatigue tests. The nonlinearity effects respect the time‐temperature superposition principle, and they are more pronounced at “high” temperature (at the same frequency). Direction of nonlinearity curve in the Cole‐Cole axes is shown to be independent of temperature and frequency for the considered range.