184 research outputs found
Deep Reinforcement Learning-Based Channel Allocation for Wireless LANs with Graph Convolutional Networks
Last year, IEEE 802.11 Extremely High Throughput Study Group (EHT Study
Group) was established to initiate discussions on new IEEE 802.11 features.
Coordinated control methods of the access points (APs) in the wireless local
area networks (WLANs) are discussed in EHT Study Group. The present study
proposes a deep reinforcement learning-based channel allocation scheme using
graph convolutional networks (GCNs). As a deep reinforcement learning method,
we use a well-known method double deep Q-network. In densely deployed WLANs,
the number of the available topologies of APs is extremely high, and thus we
extract the features of the topological structures based on GCNs. We apply GCNs
to a contention graph where APs within their carrier sensing ranges are
connected to extract the features of carrier sensing relationships.
Additionally, to improve the learning speed especially in an early stage of
learning, we employ a game theory-based method to collect the training data
independently of the neural network model. The simulation results indicate that
the proposed method can appropriately control the channels when compared to
extant methods
Thompson Sampling-Based Channel Selection through Density Estimation aided by Stochastic Geometry
We propose a sophisticated channel selection scheme based on multi-armed bandits and stochastic geometry analysis. In the proposed scheme, a typical user attempts to estimate the density of active interferers for every channel via the repeated observations of signal-to-interference power ratio (SIR), which demonstrates the randomness induced by randomized interference sources and fading effects. The purpose of this study involves enabling a typical user to identify the channel with the lowest density of active interferers while considering the communication quality during exploration. To resolve the trade-off between obtaining more observations on uncertain channels and using a channel that appears better, we employ a bandit algorithm called Thompson sampling (TS), which is known for its empirical effectiveness. We consider two ideas to enhance TS. First, noticing that the SIR distribution derived through stochastic geometry is useful for updating the posterior distribution of the density, we propose incorporating the SIR distribution into TS to estimate the density of active interferers. Second, TS requires sampling from the posterior distribution of the density for each channel, while it is significantly more complicated for the posterior distribution of the density to generate samples than well-known distribution. The results indicate that this type of sampling process is achieved via the Markov chain Monte Carlo method (MCMC). The simulation results indicate that the proposed method enables a typical user to determine the channel with the lowest density more efficiently than the TS without density estimation aided by stochastic geometry, and ε-greedy strategies
Isotopic analysis of Ni, Cu, and Zn in freshwater for source identification
Nickel (Ni), copper (Cu), and zinc (Zn) are commonly used in human activities and pollute aquatic environments including rivers and oceans. Recently, Ni, Cu, and Zn isotope ratios have been measured to identify their sources and cycles in environments. We precisely determined the Ni, Cu, and Zn isotope ratios in rain, snow, and rime collected from Uji City and Mt. Kajigamori in Japan, and investigated the potential of isotopic ratios as tracers of anthropogenic materials. The isotope and elemental ratios suggested that road dust is the main source of Cu in most rain, snow, and rime samples and that some of the Cu may originate from fossil fuel combustion. Zinc in the rain, snow, and rime samples may be partially attributed to Zn in road dust. Zinc isotope ratios in the Uji rain samples are lower than those in the road dust, which would be emitted via high temperature processes. Nickel isotope ratios are correlated with V/Ni ratios in the rain, snow, and rime samples, suggesting that their main source is heavy oil combustion. Furthermore, we analyzed water samples from the Uji and Tawara Rivers and the Kakita River spring in Japan. Nickel and Cu isotope ratios in the river water samples were significantly heavier than those in rain, snow, and rime samples, while Zn isotope ratios were similar. This is attributed to isotopic fractionation of Cu and Ni between particulate-dissolved phases in river water or soil
近赤外線スペクトロスコピィを用いた成人期注意欠如・多動症の前頭前野における血液動態反応の低下
AIM: Recent developments in near-infrared spectroscopy (NIRS) have enabled non-invasive clarification of brain functions in psychiatric disorders. In pediatric attention-deficit hyperactivity disorder (ADHD), reduced prefrontal hemodynamic responses have been observed with NIRS repeatedly. However, there are few studies of adult ADHD by multi-channel NIRS. Therefore, in this study, we used multi-channel NIRS to examine the characteristics of prefrontal hemodynamic responses during the Stroop Color-Word Task (SCWT) in adult ADHD patients and in age- and sex-matched control subjects. METHODS: Twelve treatment-naïve adults with ADHD and 12 age- and sex-matched healthy control subjects participated in the present study after giving consent. We used 24-channel NIRS to measure the oxygenated hemoglobin (oxy-Hb) changes at the frontal lobes of participants during the SCWT. We compared the oxy-Hb changes between adults with ADHD and control subjects by t-tests with Bonferroni correction. RESULTS: During the SCWT, the oxy-Hb changes observed in the ADHD group were significantly smaller than those in the control group in channels 11, 16, 18, 21, 22, 23, and 24, corresponding to the prefrontal cortex. At channels 16, 21, 23, and 24 of the ADHD group, there were negative correlations between the symptomatic severity and the oxy-Hb changes. CONCLUSION: The present study suggests that adults with ADHD have reduced prefrontal hemodynamic response as measured by NIRS.博士(医学)・乙第1422号・平成30年11月30日© 2018 The Authors. Psychiatry and Clinical Neurosciences © 2018 Japanese Society of Psychiatry and NeurologyThis is the pre-peer reviewed version of the following article: [https://onlinelibrary.wiley.com/doi/full/10.1111/pcn.12643], which has been published in final form at [https://doi.org/10.1111/pcn.12643]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions
Quantitative evaluation of protocorm growth and fungal colonization in Bletilla striata (Orchidaceae) reveals less-productive symbiosis with a non-native symbiotic fungus
Quantitative evaluation of symbiotic cells in Pecteilis radiata protocorm. (a) Symbiotic cells with hyphal coils in P. radiata protocorm. Scale bars, 50Â Îźm. (b) Ratio of the number of symbiotic cells at each stage in a symbiotic protocorm. Each value represents the average number of symbiotic cells in ten protocorms. The experiments were repeated six times with similar results. (PDF 959Â kb
Aluminium reduces sugar uptake in tobacco cell cultures: a potential cause of inhibited elongation but not of toxicity
Aluminium is well known to inhibit plant elongation, but the role in this inhibition played by water relations remains unclear. To investigate this, tobacco (Nicotiana tabacum L.) suspension-cultured cells (line SL) was used, treating them with aluminium (50 μM) in a medium containing calcium, sucrose, and MES (pH 5.0). Over an 18 h treatment period, aluminium inhibited the increase in fresh weight almost completely and decreased cellular osmolality and internal soluble sugar content substantially; however, aluminium did not affect the concentrations of major inorganic ions. In aluminium-treated cultures, fresh weight, soluble sugar content, and osmolality decreased over the first 6 h and remained constant thereafter, contrasting with their continued increases in the untreated cultures. The rate of sucrose uptake, measured by radio-tracer, was reduced by approximately 60% within 3 h of treatment. Aluminium also inhibited glucose uptake. In an aluminium-tolerant cell line (ALT301) isogenic to SL, all of the above-mentioned changes in water relations occurred and tolerance emerged only after 6 h and appeared to involve the suppression of reactive oxygen species. Further separating the effects of aluminium on elongation and cell survival, sucrose starvation for 18 h inhibited elongation and caused similar changes in cellular osmolality but stimulated the production of neither reactive oxygen species nor callose and did not cause cell death. We propose that the inhibition of sucrose uptake is a mechanism whereby aluminium inhibits elongation, but does not account for the induction of cell death
Phosphorylation of the RSRSP stretch is critical for splicing regulation by RNA-Binding Motif Protein 20 (RBM20) through nuclear localization
RBM20 is a major regulator of heart-specific alternative pre-mRNA splicing of TTN encoding a giant sarcomeric protein titin. Mutation in RBM20 is linked to autosomal-dominant familial dilated cardiomyopathy (DCM), yet most of the RBM20 missense mutations in familial and sporadic cases were mapped to an RSRSP stretch in an arginine/serine-rich region of which function remains unknown. In the present study, we identified an R634W missense mutation within the stretch and a G1031X nonsense mutation in cohorts of DCM patients. We demonstrate that the two serine residues in the RSRSP stretch are constitutively phosphorylated and mutations in the stretch disturb nuclear localization of RBM20. Rbm20 S637A knock-in mouse mimicking an S635A mutation reported in a familial case showed a remarkable effect on titin isoform expression like in a patient carrying the mutation. These results revealed the function of the RSRSP stretch as a critical part of a nuclear localization signal and offer the Rbm20 S637A mouse as a good model for in vivo study
ACE2 knockout hinders SARS-CoV-2 propagation in iPS cell-derived airway and alveolar epithelial cells
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, continues to spread around the world with serious cases and deaths. It has also been suggested that different genetic variants in the human genome affect both the susceptibility to infection and severity of disease in COVID-19 patients. Angiotensin-converting enzyme 2 (ACE2) has been identified as a cell surface receptor for SARS-CoV and SARS-CoV-2 entry into cells. The construction of an experimental model system using human iPS cells would enable further studies of the association between viral characteristics and genetic variants. Airway and alveolar epithelial cells are cell types of the lung that express high levels of ACE2 and are suitable for in vitro infection experiments. Here, we show that human iPS cell-derived airway and alveolar epithelial cells are highly susceptible to viral infection of SARS-CoV-2. Using gene knockout with CRISPR-Cas9 in human iPS cells we demonstrate that ACE2 plays an essential role in the airway and alveolar epithelial cell entry of SARS-CoV-2 in vitro. Replication of SARS-CoV-2 was strongly suppressed in ACE2 knockout (KO) lung cells. Our model system based on human iPS cell-derived lung cells may be applied to understand the molecular biology regulating viral respiratory infection leading to potential therapeutic developments for COVID-19 and the prevention of future pandemics
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