Denoising and Trend Terms Elimination Algorithm of Accelerometer Signals

Acceleration-based displacement measurement approach is often used to measure the polish rod displacement in the oilfield pumping well. Random noises and trend terms of the accelerometer signals are the main factors that affect the measuring accuracy. In this paper, an efficient online learning algorithm is proposed to improve the measurement precision of polish rod displacement in the oilfield pumping well. To remove the random noises and eliminate the trend term of accelerometer signals, the ARIMA model and its parameters are firstly derived by using the obtained data of time series of acceleration sensor signals. Secondly, the period of the accelerometer signals is estimated through the Rife-Jane frequency estimation approach based on Fast Fourier Transform. With the obtained model and parameters, the random noises are removed by employing the Kalman filtering algorithm. The quadratic integration of the period is calculated to obtain the polish rod displacement. Moreover, the windowed recursive least squares algorithm is implemented to eliminate the trend terms. The simulation results demonstrate that the proposed online learning algorithm is able to remove the random noises and trend terms effectively and greatly improves the measurement accuracy of the displacement

Chaotic Microcavity Laser with Low threshold and Unidirectional Output

Here we report lasing action in lima\c{c}on-shaped GaAs microdisks with quantum dots (QDs) embedded. Although the intracavity ray dynamics is predominantly chaotic, high-$Q$ modes are concentrated in the region $\chi > \chi_c$ as a result of wave localization. Strong optical confinement by total internal reflection leads to very low lasing threshold. Our measurements show that all the lasing modes have output in the same direction, regardless of their wavelengths and intracavity mode structures. This universal emission direction is determined by directed phase space flow of optical rays in the open chaotic cavity. The divergence angle of output beam is less than 40 degree. The unidirectionality proves to be robust against small deviations of the real cavity shape and size from the designed values.Comment: 12 pages, 4 figure

Infrared Optical Anisotropy in Quasi-1D Hexagonal Chalcogenide BaTiSe3

Polarimetric infrared detection bolsters IR thermography by leveraging the polarization of light. Optical anisotropy, i.e., birefringence and dichroism, can be leveraged to achieve polarimetric detection. Recently, giant optical anisotropy was discovered in quasi-1D narrow-bandgap hexagonal perovskite sulfides, A1+xTiS3, specifically BaTiS3[1,2] and Sr9/8TiS3[3,4]. In these materials, the critical role of atomic-scale structure modulations[4,5] in the unconventional electrical[5,6], optical[7,8], and thermal[7,9] properties raises the broader question of other materials that belong to this family. To address this issue, for the first time, we synthesized high-quality single crystals of a largely unexplored member of the A1+xTiX3 (X = S, Se) family, BaTiSe3. Single-crystal X-ray diffraction determined the room-temperature structure with the P31c space group, which is a superstructure of the earlier reported[10] P63/mmc structure. The crystal structure of BaTiSe3 features antiparallel c-axis displacements similar to BaTiS3,[2] but is of lower symmetry. Polarization-resolved Raman and Fourier transform infrared (FTIR) spectroscopy were used to characterize the optical anisotropy of BaTiSe3, whose refractive index along the ordinary (perpendicular to c) and extraordinary (parallel to c) optical axes was quantitatively determined by combining ellipsometry studies with FTIR. With a giant birefringence {\Delta}n~0.9, BaTiSe3 emerges as a new candidate for miniaturized birefringent optics for mid-wave infrared to long-wave infrared imaging

Astragalus mongholicus Bunge and Curcuma aromatica Salisb. modulate gut microbiome and bile acid metabolism to inhibit colon cancer progression

IntroductionAlterations in the gut microbiome and bile acid metabolism are known to play a role in the development and progression of colon cancer. Medicinal plants like Astragalus mongholicus Bunge and Curcuma aromatica Salisb. (AC) have shown preferable therapeutic effect on cancer therapy, especially digestive tract tumors like colon cancer. However, the precise mechanisms of AC inhibiting colon cancer, particularly in relation to the gut microbiome and bile acid dynamics, are not fully understood.MethodsOur research aimed to investigate the anti-tumor properties of AC in mice with CT26 colon cancer and further investigate its underlying mechanism via intestinal microbiota. The size and pathological changes of solid tumors in colon cancer are used to evaluate the inhibitory effect of AC on colon cancer. Metagenomics and 16s rRNA gene sequencing were employed to clarify the dysbiosis in the gut microbiome of colon cancer and its impact on colon cancer. The levels of bile acids (BAs) in the feces of mice from each group were measured using UPLC-Qtrap-MS/MS.ResultsAC effectively suppressed the growth of colon cancer and reduced histological damage. Notably, AC treatment led to changes in the gut microbiome composition, with a decrease in pathogenic species like Citrobacter and Candidatus_Arthromitus, and an increase in beneficial microbial populations including Adlercreutzia, Lachnospiraceae_UCG-001, and Parvibacter. Additionally, AC altered bile acid profiles, resulting in a significant decrease in pro-carcinogenic bile acids such as deoxycholic acid (DCA) and lithocholic acid (LCA), while increasing the concentration of the cancer-inhibitory bile acid, ursodeoxycholic acid (UDCA). Tracking and analyzing the data, AC may mainly upregulate FabG and baiA genes by increasing the relative abundance of Adlercreutzia and Parvibacter bacteria, which promoting the metabolism of pro-carcinogenic LCA.DiscussionThese findings provide strong evidence supporting the role of AC in regulating gut microbiome-mediated bile acid metabolism, which is crucial in impeding the progression of colon cancer

METTL14 Is a Chromatin Regulator Independent of Its RNA N6-Methyladenosine Methyltransferase Activity

METTL3 and METTL14 are two components that form the core heterodimer of the main RNA m6A methyltransferase complex (MTC) that installs m6A. Surprisingly, depletion of METTL3 or METTL14 displayed distinct effects on stemness maintenance of mouse embryonic stem cell (mESC). While comparable global hypo-methylation in RNA m6A was observed in Mettl3 or Mettl14 knockout mESCs, respectively. Mettl14 knockout led to a globally decreased nascent RNA synthesis, whereas Mettl3 depletion resulted in transcription upregulation, suggesting that METTL14 might possess an m6A-independent role in gene regulation. We found that METTL14 colocalizes with the repressive H3K27me3 modification. Mechanistically, METTL14, but not METTL3, binds H3K27me3 and recruits KDM6B to induce H3K27me3 demethylation independent of METTL3. Depletion of METTL14 thus led to a global increase in H3K27me3 level along with a global gene suppression. The effects of METTL14 on regulation of H3K27me3 is essential for the transition from self-renewal to differentiation of mESCs. This work reveals a regulatory mechanism on heterochromatin by METTL14 in a manner distinct from METTL3 and independently of m6A, and critically impacts transcriptional regulation, stemness maintenance, and differentiation of mESCs

Atom-Specific Probing of Electron Dynamics in an Atomic Adsorbate by Time-Resolved X-Ray Spectroscopy

The electronic excitation occurring on adsorbates at ultrafast timescales from optical lasers that initiate surface chemical reactions is still an open question. Here, we report the ultrafast temporal evolution of x-ray absorption spectroscopy (XAS) and x-ray emission spectroscopy (XES) of a simple well-known adsorbate prototype system, namely carbon (C) atoms adsorbed on a nickel [Ni(100)] surface, following intense laser optical pumping at 400 nm. We observe ultrafast (∼100  fs) changes in both XAS and XES showing clear signatures of the formation of a hot electron-hole pair distribution on the adsorbate. This is followed by slower changes on a few picoseconds timescale, shown to be consistent with thermalization of the complete C/Ni system. Density functional theory spectrum simulations support this interpretation

Atom-Specific Probing of Electron Dynamics in an Atomic Adsorbate by Time-Resolved X-ray Spectroscopy

The electronic excitation occurring on adsorbates at ultrafast time scales from optical lasers that initiate surface chemical reactions is still an open question. Here, we report the ultrafast temporal evolution of X-ray absorption spectroscopy (XAS) and X-ray emission spectroscopy (XES) of a simple well known adsorbate prototype system, namely carbon (C) atoms adsorbed on a nickel (Ni(100)) surface, following intense laser optical pumping at 400 nm. We observe ultrafast (~100 fs) changes in both XAS and XES showing clear signatures of the formation of a hot electron-hole pair distribution on the adsorbate. This is followed by slower changes on a few ps time scale, shown to be consistent with thermalization of the complete C/Ni system. Density functional theory spectrum simulations support this interpretation.Comment: 33 pages, 12 figures. Submitted to Physical Review Letter

Symmetry-Resolved CO Desorption and Oxidation Dynamics on O/Ru(0001) Probed at the C K-edge by Ultrafast X-Ray Spectroscopy

We report on carbon monoxide desorption and oxidation induced by 400 nm femtosecond laser excitation on the O/Ru(0001) surface probed by time-resolved x-ray absorption spectroscopy (TR-XAS) at the carbon K-edge. The experiments were performed under constant background pressures of CO (6 × 10−8 Torr) and O2 (3 × 10−8 Torr). Under these conditions, we detect two transient CO species with narrow 2π* peaks, suggesting little 2π* interaction with the surface. Based on polarization measurements, we find that these two species have opposing orientations: (1) CO favoring a more perpendicular orientation and (2) CO favoring a more parallel orientation with respect to the surface. We also directly detect gas-phase CO2 using a mass spectrometer and observe weak signatures of bent adsorbed CO2 at slightly higher x-ray energies than the 2π* region. These results are compared to previously reported TR-XAS results at the O K-edge, where the CO background pressure was three times lower (2 × 10−8 Torr) while maintaining the same O2 pressure. At the lower CO pressure, in the CO 2π* region, we observed adsorbed CO and a distribution of OC–O bond lengths close to the CO oxidation transition state, with little indication of gas-like CO. The shift toward “gas-like” CO species may be explained by the higher CO exposure, which blocks O adsorption, decreasing O coverage and increasing CO coverage. These effects decrease the CO desorption barrier through dipole–dipole interaction while simultaneously increasing the CO oxidation barrier

Denoising and Trend Terms Elimination Algorithm of Accelerometer Signals

Acceleration-based displacement measurement approach is often used to measure the polish rod displacement in the oilfield pumping well. Random noises and trend terms of the accelerometer signals are the main factors that affect the measuring accuracy. In this paper, an efficient online learning algorithm is proposed to improve the measurement precision of polish rod displacement in the oilfield pumping well. To remove the random noises and eliminate the trend term of accelerometer signals, the ARIMA model and its parameters are firstly derived by using the obtained data of time series of acceleration sensor signals. Secondly, the period of the accelerometer signals is estimated through the Rife-Jane frequency estimation approach based on Fast Fourier Transform. With the obtained model and parameters, the random noises are removed by employing the Kalman filtering algorithm. The quadratic integration of the period is calculated to obtain the polish rod displacement. Moreover, the windowed recursive least squares algorithm is implemented to eliminate the trend terms. The simulation results demonstrate that the proposed online learning algorithm is able to remove the random noises and trend terms effectively and greatly improves the measurement accuracy of the displacement