A Scientific and Economic View on Collaboration, Balancing vs. Sharing

There is a class of artifacts bodies and their science, also known as 3M & I-bodies in 2008, which consist of human, material/machine, monetary and informational components. For multi-body systems, the paper discusses and develops the scientific and economic fundamentals of the Follett-like classification as domination, compromise, integration and sharing in 2-center conflict types (Matsui, 1983). That is, the mathematical view is based on the Venn diagram of sets in mathematics, the physical view is based on the principle of the lever in Archimedes’ work, and the economical view is based on the profit (specific gravity) and Matsui’s equation. From a systematic view composed of these, it is obtained that the integration pursues the maximization of intersection (compromise) in the two-center, whereas the sharing pursues the minimization of intersection (compromise) in field. When the marginal (maximal) profit is the same, both are pointed out to be similar on the relation of classical Nash’s solution and duality; the scientific and economic findings will contribute to the advance of the coming society and its visibility and harmony in collaboration vs. sharing

Radiotherapy for cancer using X-ray fluorescence emitted from iodine

Radiation treatment is popular and the apparatus is already available in many hospitals. Conventional radiation treatment by itself is not sufficient to achieve complete cure. Therefore, radiosensitizers have been developed to enhance the therapeutic effects of the treatment. The concept of radiosensitization with high-Z-elements was first considered many decades ago. However, radiosensitizers are not commonly used in the clinical setting. Here, we propose a radiotherapy method that utilizes fluorescent X-ray emissions from iodine. This approach should achieve a greater therapeutic effect than that of conventional radiotherapy treatments. In our radiotherapy, iomeprol was used as the iodine-donor. The X-ray apparatus with copper and aluminum filters could be used for the X-ray irradiation, the apparatus is not needed for exclusive use. The X-ray apparatus is only required to prepare the copper and aluminum filters. As proof-of-concept, we show that tumor growth was attenuated using this treatment with iomeprol

Counterfactual Explanation of Brain Activity Classifiers Using Image-To-Image Transfer by Generative Adversarial Network

Deep neural networks (DNNs) can accurately decode task-related information from brain activations. However, because of the non-linearity of DNNs, it is generally difficult to explain how and why they assign certain behavioral tasks to given brain activations, either correctly or incorrectly. One of the promising approaches for explaining such a black-box system is counterfactual explanation. In this framework, the behavior of a black-box system is explained by comparing real data and realistic synthetic data that are specifically generated such that the black-box system outputs an unreal outcome. The explanation of the system's decision can be explained by directly comparing the real and synthetic data. Recently, by taking advantage of advances in DNN-based image-to-image translation, several studies successfully applied counterfactual explanation to image domains. In principle, the same approach could be used in functional magnetic resonance imaging (fMRI) data. Because fMRI datasets often contain multiple classes (e.g., multiple behavioral tasks), the image-to-image transformation applicable to counterfactual explanation needs to learn mapping among multiple classes simultaneously. Recently, a new generative neural network (StarGAN) that enables image-to-image transformation among multiple classes has been developed. By adapting StarGAN with some modifications, here, we introduce a novel generative DNN (counterfactual activation generator, CAG) that can provide counterfactual explanations for DNN-based classifiers of brain activations. Importantly, CAG can simultaneously handle image transformation among all the seven classes in a publicly available fMRI dataset. Thus, CAG could provide a counterfactual explanation of DNN-based multiclass classifiers of brain activations. Furthermore, iterative applications of CAG were able to enhance and extract subtle spatial brain activity patterns that affected the classifier's decisions. Together, these results demonstrate that the counterfactual explanation based on image-to-image transformation would be a promising approach to understand and extend the current application of DNNs in fMRI analyses

Development of ethnographic digital collections

Περιέχει το πλήρες κείμενοΟι λαογραφικές συλλογές αποτελούν πολύτιμη πηγή μελέτης, εξερεύνησης και αξιολόγησης των εθνικών στερεοτύπων των διαφόρων διαμερισμάτων μιας χώρας, δεδομένου ότι στις συλλογές είναι καταχωρημένα ανόθευτα και πηγαία τα εγχώρια εθνοχαρακτηριστικά τους. Κατά κύριο λόγο η λαογραφία αναφέρεται στους μύθους, τα τραγούδια, τη μουσική, τα έθιμα, τη χειροτεχνία, την ενδυμασία, την αρχιτεκτονική και την προφορική παράδοση μιας κοινότητας. Η ιδιαιτερότητα και η ποικιλία ενός τομέα όπως της λαογραφίας δικαιολογεί απόλυτα την ύπαρξη συλλογών και υπο-συλλογών σύνθετης δομής και σημασιολογίας, όπως αυτές που αναφέρουμε παραπάνω. Επομένως η ανάπτυξη ψηφιακών συλλογών απαιτεί τη διατήρηση των στοιχείων που χρειάζονται για: (α) την περιγραφή του περιεχομένου της κάθε συλλογής χωριστά και (β) τη σωστή απεικόνιση της δομής των αντικειμένων στο εσωτερικό αυτής. Στόχος της εργασίας αυτής είναι η παρουσίαση μιας μεθοδολογίας για την ανάπτυξη ενός περιγραφικού μοντέλου μεταδεδομένων για λαογραφικές συλλογές. Το μοντέλο θα αποτελέσει βασικό εργαλείο για την περιγραφή του ψηφιοποιημένου λαογραφικού υλικού, την πρόσβαση σε αυτό από κατανεμημένους χρήστες και φυσικά την επικοινωνία του με άλλα συστήματα. Επιπλέον θα συμβάλλει στη διασύνδεση σύνθετων συλλογών και των αντικειμένων που περιλαμβάνουν είτε σημασιολογικά, είτε χρονικά, είτε θεματικά είτε με οποιονδήποτε άλλο τρόπο απαιτεί η φύση των συλλογών και οι ανάγκες των χρηστών

Use of Recombinant Endolysin to Improve Accuracy of Group B Streptococcus Tests

Group B Streptococcus (GBS) causes serious neonatal infection via vertical transmission. The prenatal GBS screening test is performed at the late stage of pregnancy to avoid risks of infection. In this test, enrichment culture is performed, followed by GBS identification. Selective medium is used for the enrichment; however, Enterococcus faecalis, which is a potential contaminant in swab samples, can interfere with the growth of GBS. Such bacterial contamination can lead to false-negative results. Endolysin, a bacteriophage-derived enzyme, degrades peptidoglycan in the bacterial cell wall; it is a promising antimicrobial agent for selectively eliminating specific bacterial genera/species. In this study, we used the recombinant endolysin EG-LYS, which is specific to E. faecalis; the endolysin potentially enriched GBS in the selective culture. First, in the false-negative model (coculture of GBS and E. faecalis, which disabled GBS detection in the subsequent GBS identification test), EG-LYS treatment at 0.1 mg/ml improved GBS detection. Next, we used 548 vaginal swabs to test the efficacy of EG-LYS treatment in improving GBS detection. EG-LYS treatment (0.1 mg/ml) increased the GBS-positive ratio to 17.9%, compared to 15.7% in the control (phosphate-buffered saline [PBS] treatment). In addition, there were an increased number of GBS colonies under EG-LYS treatment in some samples. The results were supported by the microbiota analysis of the enriched cultures. In conclusion, EG-LYS treatment of the enrichment culture potentially improves the accuracy of the prenatal GBS screening test

Thiamine tetrahydrofurfuryl disulfide promotes voluntary activity through dopaminergic activation in the medial prefrontal cortex

A physically active lifestyle is associated with better health in body and mind, and it is urgent that supporting agents for such lifestyles be developed. In rodents, voluntary locomotor activity as an active physical behavior may be mediated by dopaminergic neurons (DNs). Thiamine phosphate esters can stimulate DNs, and we thus hypothesized that thiamine tetrahydrofurfuryl disulfide (TTFD), a thiamine derivative, promotes locomotor activity via DNs in rats. Acute i.p. administration of TTFD enhanced rat locomotor activity in a normal cage. In vivo microdialysis revealed that TTFD-enhanced locomotor activity was synchronized with dopamine release in the medial prefrontal cortex (mPFC). Antagonism of the dopamine D1 receptor, but not D2 receptor, in the mPFC fully suppressed TTFD-enhanced locomotor activity. Finally, we found a TTFD dose-dependent increase in voluntary wheel running. Our findings demonstrate that DNs in the mPFC mediates TTFD-enhanced locomotor activity, suggesting the potential of TTFD to induce active physical behavior