The catalogues and mid-infrared environment of Interstellar OH Masers

Data for a number of OH maser lines have been collected from surveys. The posi- tions are compared to recent mid-infrared (MIR) surveys such as Spitzer-GLIMPSE and WISE, restricting the comparison to point sources. The colors and intensities of the IR sources are compared. There are many 18 cm OH masers, but far fewer in lines arising from higher energy levels. We also make a comparison with the 5 cm Class II methanol masers. We have divided the results into 3 subsamples: those associated with OH masers only, those associated with OH masers and Class II methanol masers, and those only associated with Class II methanol masers. There are no obvious dif- ferences in the color-color or color-magnitude results for the GLIMPSE point sources. However, according to the results from the WISE 22 {\mu}m survey, the sources associ- ated with OH masers are brighter than those associated with methanol masers. We interpret the presence of OH and methanol masers mark the locations of regions where stars are forming. The OH masers are located on the borders of sharp features found in the IR. These are referred to as bubbles. If the OH masers mark the positions of protostars, the result provides indirect evidence for triggered star formation caused by the expansion of the bubbles.Comment: 23 pages (11 pages online only), 12 figures, Accepted. Monthly Notices of the Royal Astronomical Society,201

Identification of Protein Pupylation Sites Using Bi-Profile Bayes Feature Extraction and Ensemble Learning

Pupylation, one of the most important posttranslational modifications of proteins, typically takes place when prokaryotic ubiquitin-like protein (Pup) is attached to specific lysine residues on a target protein. Identification of pupylation substrates and their corresponding sites will facilitate the understanding of the molecular mechanism of pupylation. Comparing with the labor-intensive and time-consuming experiment approaches, computational prediction of pupylation sites is much desirable for their convenience and fast speed. In this study, a new bioinformatics tool named EnsemblePup was developed that used an ensemble of support vector machine classifiers to predict pupylation sites. The highlight of EnsemblePup was to utilize the Bi-profile Bayes feature extraction as the encoding scheme. The performance of EnsemblePup was measured with a sensitivity of 79.49%, a specificity of 82.35%, an accuracy of 85.43%, and a Matthews correlation coefficient of 0.617 using the 5-fold cross validation on the training dataset. When compared with other existing methods on a benchmark dataset, the EnsemblePup provided better predictive performance, with a sensitivity of 80.00%, a specificity of 83.33%, an accuracy of 82.00%, and a Matthews correlation coefficient of 0.629. The experimental results suggested that EnsemblePup presented here might be useful to identify and annotate potential pupylation sites in proteins of interest. A web server for predicting pupylation sites was developed

Implications of depressive mood in OSAHS patients: insights from event-related potential

Background: Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a chronic breathing disorder characterized by recurrent upper airway obstruction during sleep. Although previous studies have shown a link between OSAHS and depressive mood, the neurobiological mechanisms underlying mood disorders in OSAHS patients remain poorly understood. This study aims to investigate the emotion processing mechanism in OSAHS patients with depressive mood using event-related potentials (ERPs). Methods: Seventy-four OSAHS patients were divided into the depressive mood and non-depressive mood groups according to their Self-rating Depression Scale (SDS) scores. Patients underwent overnight polysomnography and completed various cognitive and emotional questionnaires. The patients were shown facial images displaying positive, neutral, and negative emotions and tasked to identify the emotion category, while their visual evoked potential was simultaneously recorded. Results: The two groups did not differ significantly in age, BMI, and years of education, but showed significant differences in their slow wave sleep ratio (P = 0.039), ESS (P = 0.006), MMSE (P < 0.001), and MOCA scores (P = 0.043). No significant difference was found in accuracy and response time on emotional face recognition between the two groups. N170 latency in the depressive group was significantly longer than the non-depressive group (P = 0.014 and 0.007) at the bilateral parieto-occipital lobe, while no significant difference in N170 amplitude was found. No significant difference in P300 amplitude or latency between the two groups. Furthermore, N170 amplitude at PO7 was positively correlated with the arousal index and negatively with MOCA scores (both P < 0.01). Conclusion: OSAHS patients with depressive mood exhibit increased N170 latency and impaired facial emotion recognition ability. Special attention towards the depressive mood among OSAHS patients is warranted for its implications for patient care

Hydrodeoxygenation of p-cresol on unsupported Ni–P catalysts prepared by thermal decomposition method

AbstractUnsupported Ni–P catalysts were prepared from the mixed precursor of NiCl2 and NaH2PO2 by thermal decomposition method, and their catalytic activities were measured using the hydrodeoxygenation (HDO) of p-cresol as probe. The effects of the H2PO2−/Ni2+ molar ratio in the precursor and the thermal decomposition temperature on the catalyst purity, crystallite size and HDO activity were studied. The HDO of p-cresol on these Ni–P catalysts proceeded with two parallel pathways yielding methylbenzene and methylcyclohexane as final products. The higher HDO catalytic activity of the catalyst was attributed to its bigger crystallite size and purer phase of Ni2P

Laser Beam Propagation through Oceanic Turbulence

Using a recently proposed model for the refractive index fluctuations in oceanic turbulence, optical beam propagation through seawater is explored. The model provides an accurate depiction of the ocean through the inclusion of both temperature and salinity fluctuations to the refractive index. Several important statistical characteristics are explored including spatial coherence radius, angle-of-arrival fluctuations, and beam wander. Theoretical values of these parameters are found based on weak fluctuation theory using the Rytov method. The results presented serve as a foundation for the study of optical beam propagation in oceanic turbulence, which may provide an important support for further researches in applications for underwater communicating, imaging, and sensing systems

Preparation and Characterization of NiO Nanoparticles by Anodic Arc Plasma Method

NiO nanoparticles with average particle size of 25 nm were successfully prepared by anodic arc plasma method. The composition, morphology, crystal microstructure, specific surface area, infrared spectra, and particle size distribution of product were analyzed by using X-ray diffraction (XRD), transmission electron microscopy (TEM) and the corresponding selected area electron diffraction (SAED), Fourier transform infrared (FTIR) spectrum, and Brunauer-Emmett-Teller (BET) N2 adsorption. The experiment results show that the NiO nanoparticles are bcc structure with spherical shape and well dispersed, the particle size distribution ranging from 15 to 45 nm with the average particle size is about 25 nm, and the specific surface area is 33 m2/g. The infrared absorption band of NiO nanoparticles shows blue shifts compared with that of bulk NiO

Understanding the global subnational migration patterns driven by hydrological intrusion exposure

Amid the escalating global climatic challenges, hydrological risks significantly influence human settlement patterns, underscoring the imperative for an in-depth comprehension of hydrological change’s ramifications on human migration. However, predominant research has been circumscribed to the national level. The study delves into the nonlinear effects of hydrological risks on migration dynamics in 46,776 global subnational units. Meanwhile, leveraging remote sensing, we procured globally consistent metrics of hydrological intrusion exposure, offering a holistic risk assessment encompassing hazard, exposure, and vulnerability dimensions, thus complementing previous work. Here, we show that exposure is the primary migration driver, surpassing socioeconomic factors. Surrounding disparities further intensified exposure’s impact. Vulnerable groups, especially the economically disadvantaged and elderly, tend to remain in high-risk areas, with the former predominantly migrating within proximate vicinities. The nonlinear analysis delineates an S-shaped trajectory for hydrological exposure, transitioning from resistance to migration and culminating in entrapment, revealing dependence on settlement resilience and adaptability