Distribution of Caustic-Crossing Intervals for Galactic Binary-Lens Microlensing Events

Detection of caustic crossings of binary-lens gravitational microlensing events is important because by detecting them one can obtain useful information both about the lens and source star. In this paper, we compute the distribution of the intervals between two successive caustic crossings, $f(t_{\rm cc})$, for Galactic bulge binary-lens events to investigate the observational strategy for the optimal detection and resolution of caustic crossings. From this computation, we find that the distribution is highly skewed toward short $t_{\rm cc}$ and peaks at $t_{\rm cc}\sim 1.5$ days. For the maximal detection of caustic crossings, therefore, prompt initiation of followup observations for intensive monitoring of events will be important. We estimate that under the strategy of the current followup observations with a second caustic-crossing preparation time of $\sim 2$ days, the fraction of events with resolvable caustic crossing is $\sim 80$. We find that if the followup observations can be initiated within 1 day after the first caustic crossing by adopting more aggressive observational strategies, the detection rate can be improved into $\sim 90$.Comment: total 6 pages, including 5 Figures and no Table, submitted to MNRA

Decomposed Temporal Dynamic CNN: Efficient Time-Adaptive Network for Text-Independent Speaker Verification Explained with Speaker Activation Map

Temporal dynamic models for text-independent speaker verification extract consistent speaker information regardless of phonemes by using temporal dynamic CNN (TDY-CNN) in which kernels adapt to each time bin. However, TDY-CNN shows limitations that the model is too large and does not guarantee the diversity of adaptive kernels. To address these limitations, we propose decomposed temporal dynamic CNN (DTDY-CNN) that makes adaptive kernel by combining static kernel and dynamic residual based on matrix decomposition. The baseline model using DTDY-CNN maintained speaker verification performance while reducing the number of model parameters by 35% compared to the model using TDY-CNN. In addition, detailed behaviors of temporal dynamic models on extraction of speaker information was explained using speaker activation maps (SAM) modified from gradient-weighted class activation mapping (Grad-CAM). In DTDY-CNN, the static kernel activates voiced features of utterances, and the dynamic residual activates unvoiced high-frequency features of phonemes. DTDY-CNN effectively extracts speaker information from not only formant frequencies and harmonics but also detailed unvoiced phonemes' information, thus explaining its outstanding performance on text-independent speaker verification.Comment: Submitted to InterSpeech 202

Functional neural differentiation of human adipose tissue-derived stem cells using bFGF and forskolin

<p>Abstract</p> <p>Background</p> <p>Adult mesenchymal stem cells (MSCs) derived from adipose tissue have the capacity to differentiate into mesenchymal as well as endodermal and ectodermal cell lineage <it>in vitro</it>. We characterized the multipotent ability of human adipose tissue-derived stem cells (hADSCs) as MSCs and investigated the neural differentiation potential of these cells.</p> <p>Results</p> <p>Human ADSCs from earlobe fat maintained self-renewing capacity and differentiated into adipocytes, osteoblasts, or chondrocytes under specific culture conditions. Following neural induction with bFGF and forskolin, hADSCs were differentiated into various types of neural cells including neurons and glia <it>in vitro</it>. In neural differentiated-hADSCs (NI-hADSCs), the immunoreactivities for neural stem cell marker (nestin), neuronal markers (Tuj1, MAP2, NFL, NFM, NFH, NSE, and NeuN), astrocyte marker (GFAP), and oligodendrocyte marker (CNPase) were significantly increased than in the primary hADSCs. RT-PCR analysis demonstrated that the mRNA levels encoding for ABCG2, nestin, Tuj1, MAP2, NFL, NFM, NSE, GAP43, SNAP25, GFAP, and CNPase were also highly increased in NI-hADSCs. Moreover, NI-hADSCs acquired neuron-like functions characterized by the display of voltage-dependent tetrodotoxin (TTX)-sensitive sodium currents, outward potassium currents, and prominent negative resting membrane potentials under whole-cell patch clamp recordings. Further examination by RT-PCR showed that NI-hADSCs expressed high level of ionic channel genes for sodium (SCN5A), potassium (MaxiK, Kv4.2, and EAG2), and calcium channels (CACNA1C and CACNA1G), which were expressed constitutively in the primary hADSCs. In addition, we demonstrated that Kv4.3 and Eag1, potassium channel genes, and NE-Na, a TTX-sensitive sodium channel gene, were highly induced following neural differentiation.</p> <p>Conclusions</p> <p>These combined results indicate that hADSCs have the same self-renewing capacity and multipotency as stem cells, and can be differentiated into functional neurons using bFGF and forskolin.</p

Materialization of single multicomposite nanowire: entrapment of ZnO nanoparticles in polyaniline nanowire

We present materialization of single multicomposite nanowire (SMNW)-entrapped ZnO nanoparticles (NPs) via an electrochemical growth method, which is a newly developed fabrication method to grow a single nanowire between a pair of pre-patterned electrodes. Entrapment of ZnO NPs was controlled via different conditions of SMNW fabrication such as an applied potential and mixture ratio of NPs and aniline solution. The controlled concentration of ZnO NP results in changes in the physical properties of the SMNWs, as shown in transmission electron microscopy images. Furthermore, the electrical conductivity and elasticity of SMNWs show improvement over those of pure polyaniline nanowire. The new nano-multicomposite material showed synergistic effects on mechanical and electrical properties, with logarithmical change and saturation increasing ZnO NP concentration

Development of PIM components for robot surgery

In this study, the micro forcep of end-effector for robot surgery was produced by powder injection molding. The 17-4PH stainless steel powder and binder system based on a wax-polymer were mixed to fabricate the feedstock. The optimum solid loading (vol. %) was determined by the torque rheometer experiments. After injection molding, debinding and sintering were carried out, final product having small and regular patterns was produced.

Frequency Dynamic Convolution: Frequency-Adaptive Pattern Recognition for Sound Event Detection

2D convolution is widely used in sound event detection (SED) to recognize 2D patterns of sound events in time-frequency domain. However, 2D convolution enforces translation-invariance on sound events along both time and frequency axis while sound events exhibit frequency-dependent patterns. In order to improve physical inconsistency in 2D convolution on SED, we propose frequency dynamic convolution which applies kernel that adapts to frequency components of input. Frequency dynamic convolution outperforms the baseline model by 6.3% in DESED dataset in terms of polyphonic sound detection score (PSDS). It also significantly outperforms dynamic convolution and temporal dynamic convolution on SED. In addition, by comparing class-wise F1 scores of baseline model and frequency dynamic convolution, we showed that frequency dynamic convolution is especially more effective for detection of non-stationary sound events. From this result, we verified that frequency dynamic convolution is superior in recognizing frequency-dependent patterns as non-stationary sound events show more intricate time-frequency patterns.Comment: Submitted to INTERSPEECH 202

Simulation of Flood Propagation Due to Levee Break Using the Cartesian Cut Cell Method

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Trends and Associated Factors of Use of Opioid, Heroin, and Cannabis Among Patients for Emergency Department Visits in Nevada: 2009–2017

To examine trends and contributing factors of opioid, heroin, and cannabis-associated emergency department (ED) visits in Nevada. The 2009 to 2017 Nevada State ED database (n = 7,950,554 ED visits) were used. Use of opioid, heroin, and cannabis, respectively, was identified by the International Classification of Diseases, 9th & 10th Revisions. Three multivariable models, one for each of the 3 dependent variables, were conducted. Independent variables included year, insurance status, race/ethnicity, use of other substance, and mental health conditions. The number of individuals with opioid, heroin, cannabis-associated ED visits increased 3%, 10%, and 23% annually from 2009 to 2015, particularly among 21 to 29 age group, females, and African Americans. Use of other substance (odds ratio [OR] = 3.91; 95% confidence interval [CI] = 3.84, 3.99; reference - no use of other substance), mental health conditions (OR = 2.48; 95% CI = 2.43, 2.53; reference – without mental health conditions), Medicaid (OR = 1.41; 95% CI = 1.38, 1.44; reference – non-Medicaid), Medicare (OR = 1.44; 95% CI = 1.39, 1.49; reference – non-Medicare) and uninsured patients (OR = 1.52; 95% CI = 1.49, 1.56; reference - insured) were predictors of all three substance-associated ED visits. With a steady increase in trends of opioid, heroin, and cannabis-associated ED visits in recent years, the main contributing factors include patient sociodemographic factors, mental health conditions, and use of other substances

Numerical simulation on the two-phase flow pattern in the loop heat pipe with r-134a

This paper discusses the two-phase flow pattern in the loop heat pipe with R-134a. A computational fluid dynamics (CFD) study was carried out using ANSYS FLUENT. VOF model was used to simulate interface between vapor and liquid phase of R- 134a. A UDF was used to model evaporation and condensation mass transfer between two phases. For the simulation of increase of pressure in the loop heat pipe, the ideal gas law was considered when modelling the density of vapor. The numerically calculated temperatures in this paper and Fadhl’s calculated temperatures and experimentally measured temperatures matched very well [2]. The maximum difference between the calculated and Fadhl’s temperature data is 2.4 %. The bubble figure in the loop heat was observed with time passed in this paper.Papers presented at the 13th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Portoroz, Slovenia on 17-19 July 2017 .International centre for heat and mass transfer.American society of thermal and fluids engineers