Bounded Littlewood identities for cylindric Schur functions

The identities which are in the literature often called ``bounded Littlewood identities" are determinantal formulas for the sum of Schur functions indexed by partitions with bounded height. They have interesting combinatorial consequences such as connections between standard Young tableaux of bounded height, lattice walks in a Weyl chamber, and noncrossing matchings. In this paper we prove affine analogs of the bounded Littlewood identities. These are determinantal formulas for sums of cylindric Schur functions. We also study combinatorial aspects of these identities. As a consequence we obtain an unexpected connection between cylindric standard Young tableaux and $r$-noncrossing and $s$-nonnesting matchings.Comment: 56 pages, 17 figures, title change

Performance Evaluation of Autonomous Driving Control Algorithm for a Crawler-Type Agricultural Vehicle Based on Low-Cost Multi-Sensor Fusion Positioning

The agriculture sector is currently facing the problems of aging and decreasing skilled labor, meaning that the future direction of agriculture will be a transition to automation and mechanization that can maximize efficiency and decrease costs. Moreover, interest in the development of autonomous agricultural vehicles is increasing due to advances in sensor technology and information and communication technology (ICT). Therefore, an autonomous driving control algorithm using a low-cost global navigation satellite system (GNSS)-real-time kinematic (RTK) module and a low-cost motion sensor module was developed to commercialize an autonomous driving system for a crawler-type agricultural vehicle. Moreover, an autonomous driving control algorithm, including the GNSS-RTK/motion sensor integration algorithm and the path-tracking control algorithm, was proposed. Then, the performance of the proposed algorithm was evaluated based on three trajectories. The Root Mean Square Errors (RMSEs) of the path-following of each trajectory are calculated to be 9, 7, and 7 cm, respectively, and the maximum error is smaller than 30 cm. Thus, it is expected that the proposed algorithm could be used to conduct autonomous driving with about a 10 cm-level of accuracy. © 2020 by the authors.1

Syndecan transmembrane domain specifically regulates downstream signaling events of the transmembrane receptor cytoplasmic domain

Despite the known importance of the transmembrane domain (TMD) of syndecan receptors in cell adhesion and signaling, the molecular basis for syndecan TMD function remains un-known. Using in vivo invertebrate models, we found that mammalian syndecan-2 rescued both the guidance defects in C. elegans hermaphrodite-specific neurons and the impaired development of the midline axons of Drosophila caused by the loss of endogenous syndecan. These compensatory ef-fects, however, were reduced significantly when syndecan-2 dimerization-defective TMD mutants were introduced. To further investigate the role of the TMD, we generated a chimera, 2eTPC, com-prising the TMD of syndecan-2 linked to the cytoplasmic domain of platelet-derived growth factor receptor (PDGFR). This chimera exhibited SDS-resistant dimer formation that was lost in the corre-sponding dimerization-defective syndecan-2 TMD mutant, 2eT(GL)PC. Moreover, 2eTPC specifically enhanced Tyr 579 and Tyr 857 phosphorylation in the PDGFR cytoplasmic domain, while the TMD mutant failed to support such phosphorylation. Finally, 2eTPC, but not 2eT(GL)PC, induced phosphorylation of Src and PI3 kinase (known downstream effectors of Tyr 579 phosphorylation) and promoted Src-mediated migration of NIH3T3 cells. Taken together, these data suggest that the TMD of a syndecan-2 specifically regulates receptor cytoplasmic domain function and subsequent downstream signaling events controlling cell behavior. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.1

Production and inventory control of auto parts based on predicted probabilistic distribution of inventory

Bayesian networks are probabilistic models used for prediction and decision making under uncertainty. The delivery quantity, the production quantity, and the inventory are changing according to various unexpected events. Then the prediction of a production inventory is required to cope with such irregular fluctuations. This paper considers a production adjustment method for an automobile parts production process by using a dynamic Bayesian network. All factors that may influence the production quantity, the delivery quantity, and the inventory quantity will be handled. This study also provides a production schedule algorithm that sequentially adjusts the production schedule in order to guarantee that all deadlines are met. Furthermore, an adjusting rule for the production quantities is provided in order to maintain guaranteed delivery

Binary Mixtures of Some Active Pharmaceutical Ingredients with Fatty Alcohols—The Criteria of Successful Eutectic Formation and Dissolution Improvement

Pharmaceutical eutectics are solid mixtures, where the crystals of active pharmaceutical ingredients (APIs) are finely divided in the phase-separated microstructures. The size reduction makes the eutectic formation a viable option to improve the dissolution rate of the poorly soluble APIs. In the present study, ibuprofen, naproxen, and sorafenib were investigated in terms of their phase behaviors with fatty alcohols, such as tetradecanol, octadecanol, and docosanol. Among the studied APIs, only ibuprofen was able to form eutectics with the fatty alcohols, and this was in agreement with the feasibility prediction based on the van ’t Hoff equation and solubility parameters. In vitro release behavior was significantly improved for the ibuprofen/octadecanol eutectic mixture, although the practical insolubility of octadecanol in water was the opposite of the outstanding hydrophilicity of usual eutectic formers. The feasibility prediction and the choice of eutectic formers in the present study will be useful in advancing the utility of the pharmaceutical eutectics

Luteolin Shifts Oxaliplatin-Induced Cell Cycle Arrest at G₀/G₁ to Apoptosis in HCT116 Human Colorectal Carcinoma Cells

Certain antioxidative flavonoids are known to activate nuclear factor E2-related factor 2 (Nrf2), a transcription factor that regulates cellular antioxidants and detoxifying response and is reportedly highly activated in many types of cancers. Few studies on the potential undesired effects of flavonoid intake during chemotherapy have been conducted, yet Nrf2 activators could favor cancer cell survival by attenuating chemotherapeutic efficiency. This study aimed to examine if luteolin, an Nrf2 activator, hinders chemotherapeutic activity of oxaliplatin, a potent anticancer agent for colorectal cancer, in HCT116 cells. Luteolin treatment strongly increased the transcriptional activity of the antioxidant response element in HCT116 cells and induced the protein expression of heme oxygenase-1, which were indicative of its Nrf2-inducing potential. Intriguingly, 25 μM luteolin reduced cell viability through apoptotic induction, which was intensified in p53-expressing cells while 1 μM oxaliplatin caused cell cycle arrest at G0/G1-phase via the p53/p21-dependent mechanism. Moreover, luteolin treatment was found to reduce oxaliplatin-treated p53-null cell viability and colony counts further, thereby demonstrating an additional effect of luteolin in the killing of human colorectal tumor HCT116 cells not expressing functional p53 protein. The findings suggest that luteolin can induce p53-mediated apoptosis regardless of oxaliplatin treatment and may eliminate oxaliplatin-resistant p53-null colorectal cells

Acceptance of an Informational Antituberculosis Chatbot Among Korean Adults: Mixed Methods Research

BackgroundTuberculosis (TB) is a highly infectious disease. Negative perceptions and insufficient knowledge have made its eradication difficult. Recently, mobile health care interventions, such as an anti-TB chatbot developed by the research team, have emerged in support of TB eradication programs. However, before the anti-TB chatbot is deployed, it is important to understand the factors that predict its acceptance by the population. ObjectiveThis study aims to explore the acceptance of an anti-TB chatbot that provides information about the disease and its treatment to people vulnerable to TB in South Korea. Thus, we are investigating the factors that predict technology acceptance through qualitative research based on the interviews of patients with TB and homeless facility personnel. We are then verifying the extended Technology Acceptance Model (TAM) and predicting the factors associated with the acceptance of the chatbot. MethodsIn study 1, we conducted interviews with potential chatbot users to extract the factors that predict user acceptance and constructed a conceptual framework based on the TAM. In total, 16 interviews with patients with TB and one focus group interview with 10 experts on TB were conducted. In study 2, we conducted surveys of potential chatbot users to validate the extended TAM. Survey participants were recruited among late-stage patients in TB facilities and members of web-based communities sharing TB information. A total of 123 responses were collected. ResultsThe results indicate that perceived ease of use and social influence were significantly predictive of perceived usefulness (P=.04 and P<.001, respectively). Perceived usefulness was predictive of the attitude toward the chatbot (P<.001), whereas perceived ease of use (P=.88) was not. Behavioral intention was positively predicted by attitude toward the chatbot and facilitating conditions (P<.001 and P=.03, respectively). The research model explained 55.4% of the variance in the use of anti-TB chatbots. The moderating effect of TB history was found in the relationship between attitude toward the chatbot and behavioral intention (P=.01) and between facilitating conditions and behavioral intention (P=.02). ConclusionsThis study can be used to inform future design of anti-TB chatbots and highlight the importance of services and the environment that empower people to use the technology

Effects of El Niño/La Niña on the Number of Imported Shigellosis Cases in the Republic of Korea, 2004–2017

Shigellosis is a major diarrheal disease in low- and middle-income countries. Although the incidence of such diseases in South and Southeast Asia has been associated with climate fluctuations linked to the El Ni&ntilde;o&ndash;Southern Oscillation (ENSO), the impact of ENSO on shigellosis infections remains unknown. Data reported to being infected with shigellosis while traveling abroad from 2004 to 2017 were obtained from the Korea Centers for Disease Control and Prevention. We investigated the relationship between the Oceanic Ni&ntilde;o Index (ONI) and Indian Ocean Dipole Mode Index and the relative risk of shigellosis in outbound travelers using distributed lag linear and non-linear models. From 2004 to 2017, 87.1% of imported shigellosis was infected in South and Southeast Asian countries. The relative risk of imported shigellosis infection in outbound travelers increased as the ONI decreased. In the association with the five-month cumulative ONI, the relative risk of infection continuously increased as the La Ni&ntilde;a index gained strength. Climate fluctuations associated with the La Ni&ntilde;a phenomenon in South and Southeast Asian countries can lead to issues in sanitation and water safety. Our findings suggest that the decreasing trend in the ONI is associated with an increased incidence of shigellosis in these countries