Corrections of shipboard GPS radiosonde soundings and applications on historical records in the eastern tropical Indian Ocean and South China Sea

Shipboard radiosonde soundings are important for detecting and quantifying the multiscale variability of atmosphere-ocean interactions associated with mass exchanges.This study evaluated the accuracies of shipboard Global Positioning System(GPS)soundings in the eastern tropical Indian Ocean and South China Sea through a simultaneous balloon-borne inter-comparison of different radiosonde types.Our results indicate that the temperature and relative humidity(RH)measurements of GPS-TanKong(GPS-TK)radiosonde(used at most stations before 2012)have larger biases than those of ChangFeng-06-A(CF-06-A)radiosonde(widely used in current observation)when compared to reference data from Vaisala RS92-SGP radiosonde,with a warm bias of 5℃and dry bias of 10%during daytimes,and a cooling bias of-0.8℃and a moist bias of 6%during nighttime.These systematic biases are primarily attributed to the radiation effects and altitude deviation.An empirical correction algorithm was developed to retrieve the atmospheric temperature and RH profiles.The corrected profiles agree well with that of RS92-SGP,except for uncertainties of CF-06-A in the stratosphere.These correction algorithms were applied to the GPS-TK historical sounding records,reducing biases in the corrected temperature and RH profiles when compared to radio occultation data.The correction of GPS-TK historical records illustrated an improvement in capturing the marine atmospheric structure,with more accurate atmospheric boundary layer height,convective available potential energy,and convective inhibition in the tropical ocean.This study contributes significantly to improving the quality of GPS radiosonde soundings and promotes the sharing of observation in the eastern tropical Indian Ocean and South China Sea.

Cold filament frontogenesis and frontolysis induced by thermal convection turbulence using large eddy simulation

The frontogenetic processes of a submesoscale cold filament driven by the thermal convection turbulence are studied by a non-hydrostatic large eddy simulation.The results show that the periodic changes in the direction of the cross-filament secondary circulations are induced by the inertial oscillation.The change in the direction of the secondary circulations induces the enhancement and reduction of the horizontal temperature gradient during the former and later inertial period,which indicates that the frontogenetical processes of the cold filament include both of frontogenesis and frontolysis.The structure of the cold filament may be broken and restored by frontogenesis and frontolysis,respectively.The magnitude of the down-filament currents has a periodic variation,while its direction is unchanged with time.The coupling effect of the turbulent mixing and the frontogenesis and frontolysis gradually weakens the temperature gradient of the cold filament with time,which reduces frontogenetical intensity and enlarges the width of cold filament.

Enhanced removal of antibiotic resistance genes during chicken manure composting after combined inoculation of Bacillus subtilis with biochar

This study explored the combined effects of Bacillus subtilis inoculation with biochar on the evolution of bacterial communities,antibiotic resistance genes(ARGs),and mobile genetic elements(MGEs)during the composting of chicken manure.The results showed that B.subtilis inoculation combined with biochar increased bacterial abundance and diversity as well as prolonged the compost thermophilic period.Promoted organic matter biodegradation and facilitated the organic waste compost humification process,reduced the proliferation of ARGs by altering the bacterial composition.Firmicutes and Actinobacteriota were the main resistant bacteria related to ARGs and MGEs.The decrease in ARGs and MGEs was associated with the reduction in the abundance of related host bacteria.Compost inoculation with B.subtilis and the addition of biochar could promote nutrient transformation,reduce the increase in ARGs and MGEs,and increase the abundance of beneficial soil taxa.

One-pot synthesis of toluene from methane and methanol catalyzed by GaN nanowire

The generation of aromatic benzene,toluene,xylene(BTX)compounds from non-petroleum feedstocks is of particular interest for chemists in the eyes of sustainability.Herein,a novel synthesis of toluene catalyzed by GaN semiconductor nanowire arrays is reported.Using methane and methanol as starting materials,the GaN nanowire arrays can synergistically facilitate the facile generation of toluene under either photo-irradiation or thermal-conditions.The detailed computational studies unveiled different mechanisms involved for the photo-and thermal-toluene synthesis.

Dodecagonal bilayer graphene quasicrystal and its approximants

Dodecagonal bilayer graphene quasicrystal has 12-fold rotational order but lacks translational symmetry which prevents the application of band theory.In this paper,we study the electronic and optical properties of graphene quasicrystal with large-scale tight-binding calculations involving more than ten million atoms.We propose a series of periodic approximants which reproduce accurately the properties of quasicrystal within a finite unit cell.By utilizing the band-unfolding method on the smallest approximant with only 2702 atoms,the effective band structure of graphene quasicrystal is derived.The features,such as the emergence of new Dirac points(especially the mirrored ones),the band gap at M point and the Fermi velocity are all in agreement with recent experiments.The properties of quasicrystal states are identified in the Landau level spectrum and optical excitations.Importantly,our results show that the lattice mismatch is the dominant factor determining the accuracy of layered approximants.The proposed approximants can be used directly for other layered materials in honeycomb lattice,and the design principles can be applied for any quasi-periodic incommensurate structures.

Lattice relaxation,mirror symmetry and magnetic field effects on ultraflat bands in twisted trilayer graphene

Twisted graphene multilayers exhibit strongly correlated insulating states and superconductivity due to the presence of ultraflat bands near the charge neutral point.In this paper,the response of ultraflat bands to lattice relaxation and a magnetic field in twisted trilayer graphene(tTLG)with different stacking arrangements is investigated by using a full tight-binding model.We show that lattice relaxations are indispensable for understanding the electronic properties of tTLG,in particular,of tTLG in the presence of mirror symmetry.Lattice relaxations renormalize the quasiparticle spectrum near the Fermi energy and change the localization of higher energy flat bands.Furthermore,different from the twisted bilayer graphene,the Hofstadter butterfly spectrum can be realized at laboratory accessible strengths of magnetic field.Our work verifies tTLG as a more tunable platform than the twisted bilayer graphene in strongly correlated phenomena.

Artificial intelligence in rheumatoid arthritis research:A bibliometric analysis from 2004 to 2023

Background:Artificial intelligence(AI)holds promise for the screening,diagnosis,and management of patients with rheumatoid arthritis(RA).This study explores the current status of AI in RA from 2004 to 2023 using bibliometric analysis and outlines prospective research trends and directions.Methods:The Web of Science Core Collection database was searched for studies related to AI in patients with RA between 2004 and 2023.VOSviewer was used for bibliometric analysis.Results:A total of 601 articles from 65 countries,primarily the United States of America,China,and the United Kingdom,were included.The research revealed that the number of global studies on AI in RA surged in 2019,with the United States of America and China producing the highest numbers of articles.Brigham and Women's Hospital emerged as the leading research institution,whereas Frontiers in Immunology was the journal with the most articles on this topic.Keywords such as"rheumatoid arthritis,""machine learning,""artificial intelligence,"and"inflammation"were frequently used to indicate their significance in the field.Conclusions:The synergy of AI and big data can enhance screening,early diagnosis,therapeutic decision-making,and ground-up drug discovery for patients with RA.AI technology can assist rheumatologists more effectively in diagnosing and predicting personalized and efficacious therapeutic drugs early in disease progression and providing continuous monitoring.