Medcheck:A novel software for automated de-formulation of traditional Chinese medicine(TCM)prescriptions by liquid chromatography-mass spectrometry

Prescriptions are the main clinical application of traditional Chinese medicines(TCMs).Common forms include Chinese patent medicines,Kampo formulas,and hospital decoctions.A new pre-scription called“famous classical formulas”is recently developed and expected to boom in the market.Identifying constituent me-dicinal plants in prescriptions is critical for new drug development and quality control[1],which could avoid safety issues from adulteration or substandard ingredients,as seen in the notorious Longdan Xiegan Pill event.

On the Identification of N-rich Metal-poor Field Stars with Future Chinese Space Station Telescope

During the long term evolution of globular clusters(GCs), some member stars are lost to the field. The recently found nitrogen-rich(N-rich) metal-poor field stars are promising candidates of these GC escapees, since N enhancement is the fingerprint of chemically enhanced populations in GCs. In this work, we discuss the possibility of identifying N-rich metal-poor field stars with the upcoming Chinese Space Station Telescope(CSST). We focus on the main survey camera with NUV, u, g, r, i, z, y filters and slitless spectrograph with a resolution about 200.The combination of UV sensitive equipment and prominent N-related molecular lines in the UV band bodes well for the identification: the color–color diagram of(u-g) versus(g-r) is capable of separating N-rich field stars from normal halo stars, if metallicity can be estimated without using the information on u-band photometry.Besides, the synthetic spectra show that a signal-to-noise ratio of 10 is sufficient to identify N-rich field stars. In the near future, a large sample of N-rich field stars found by CSST, combined with state-of-the-art N-body simulations will be crucial to deciphering GC-Galaxy co-evolution.

Genetic analyses of ancient tea trees provide insights into the breeding history and dissemination of Chinese Assam tea(Camellia sinensis var.assamica)

Chinese Assam tea(Camellia sinensis var.assamica)is an important tea crop with a long history of cultivation in Yunnan,China.Despite its potential value as a genetic resource,its genetic diversity and domestication/breeding history remain unclear.To address this issue,we genotyped 469 ancient tea plant trees representing 26 C.sinensis var.assamica populations,plus two of its wild relatives(six and three populations of C.taliensis and C.crassicolumna,respectively)using 16 nuclear microsatellite loci.Results showed that Chinese Assam tea has a relatively high,but comparatively lower gene diversity(H_(S)=0.638)than the wild relative C.crassicolumna(H_S=0.658).Clustering in STRUCTURE indicated that Chinese Assam tea and its two wild relatives formed distinct genetic groups,with considerable interspecific introgression.The Chinese Assam tea accessions clustered into three gene pools,corresponding well with their geographic distribution.However,New Hybrids analysis indicated that 68.48%of ancient Chinese Assam tea plants from Xishuangbanna were genetic intermediates between the Puer and Lincang gene pools.In addition,10%of the ancient Chinese Assam tea individuals were found to be hybrids between Chinese Assam tea and C.taliensis.Our results suggest that Chinese Assam tea was domesticated separately in three gene pools(Puer,Lincang and Xishuangbanna)in the Mekong River valley and that the hybrids were subsequently selected during the domestication process.Although the domestication history of Chinese Assam tea in southwestern Yunnan remains complex,our results will help to identify valuable genetic resources that may be useful in future tea breeding programs.

Estimating shear strength of high-level pillars supported with cemented backfilling using the HoekeBrown strength criterion

Deep metal mines are often mined using the high-level pillars with subsequent cementation backfilling(HLSCB)mining method.At the design stage,it is therefore important to have a reasonable method for determining the shear strength of the high-level pillars(i.e.cohesion and internal friction angle)when they are supported by cemented backfilling.In this study,a formula was derived for the upper limit of the confining pressure σ3max on a high-level pillar supported by cemented backfilling in a deep metal mine.A new method of estimating the shear strength of such pillars was then proposed based on the Hoek eBrown failure criterion.Our analysis indicates that the horizontal stress σhh acting on the cemented backfill pillar can be simplified by expressing it as a constant value.A reasonable and effective value for σ3max can then be determined.The value of s3max predicted using the proposed method is generally less than 3 MPa.Within this range,the shear strength of the high-level pillar is accurately calculated using the equivalent MohreCoulomb theory.The proposed method can effectively avoid the calculation of inaccurate shear strength values for the high-level pillars when the original HoekeBrown criterion is used in the presence of large confining pressures,i.e.the situation in which the cohesion value is too large and the friction angle is too small can effectively be avoided.The proposed method is applied to a deep metal mine in China that is being excavated using the HLSCB method.The shear strength parameters of the high-level pillars obtained using the proposed method were input in the numerical simulations.The numerical results show that the recommended level heights and sizes of the high-level pillars and rooms in the mine are rational.

Dynamic simulation analysis of molten salt reactor-coupled air-steam combined cycle power generation system

A nonlinear dynamic simulation model based on coordinated control of speed and flow rate for the molten salt reactor and combined cycle systems is proposed here to ensure the coordination and stability between the molten salt reactor and power system.This model considers the impact of thermal properties of fluid variation on accuracy and has been validated with Simulink.This study reveals the capability of the control system to compensate for anomalous situations and maintain shaft stability in the event of perturbations occurring in high-temperature molten salt tank outlet parameters.Meanwhile,the control system’s impact on the system’s dynamic characteristics under molten salt disturbance is also analyzed.The results reveal that after the disturbance occurs,the controlled system benefits from the action of the control,and the overshoot and disturbance amplitude are positively correlated,while the system power and frequency eventually return to the initial values.This simulation model provides a basis for utilizing molten salt reactors for power generation and maintaining grid stability.

El Niño and the AMO Sparked the Astonishingly Large Margin of Warming in the Global Mean Surface Temperature in 2023

In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.

A defective iron-based perovskite cathode for high-performance IT-SOFCs:Tailoring the oxygen vacancies using Nb/Ta co-doping

The sluggish kinetics of the electrochemical oxygen reduction reaction(ORR)in intermediatetemperature solid oxide fuel cells(IT-SOFCs)greatly limits the overall cell performance.In this study,an efficient and durable cathode material for IT-SOFCs is designed based on density functional theory(DFT)calculations by co-doping with Nb and Ta the B-site of the SrFeO_(3-δ)perovskite oxide.The DFT calculations suggest that Nb/Ta co-doping can regulate the energy band of the parent SrFeO_(3-δ)and help electron transfer.In symmetrical cells,such cathode with a SrFe_(0.8)Nb_(0.1)Ta_(0.1)O_(3-δ)(SFNT)detailed formula achieves a low cathode polarization resistance of 0.147Ωcm^(2) at 650℃.Electron spin resonance(ESR)and X-ray photoelectron spectroscopy(XPS)analysis confirm that the co-doping of Nb/Ta in SrFeO_(3-δ)B-site increases the balanced concentration of oxygen vacancies,enhancing the electrochemical performance when compared to 20 mol%Nb single-doped perovskite oxide.The cathode button cell with NiSDC|SDC|SFNT configuration achieves an outstanding peak power density of 1.3 W cm^(-2)at 650℃.Moreover,the button cell shows durability for 110 h under 0.65 V at 600℃ using wet H_(2) as fuel.

When Does Sora Show:The Beginning of TAO to Imaginative Intelligence and Scenarios Engineering

DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.

Review on synergistic damage effect of irradiation and corrosion on reactor structural alloys

The synergistic damage effect of irradiation and corrosion of reactor structural materials has been a prominent research focus.This paper provides a comprehensive review of the synergistic effects on the third-and fourth-generation fission nuclear energy structural materials used in pressurized water reactors and molten salt reactors.The competitive mechanisms of multiple influencing factors,such as the irradiation dose,corrosion type,and environmental temperature,are summarized in this paper.Conceptual approaches are proposed to alleviate the synergistic damage caused by irradiation and corrosion,thereby promoting in-depth research in the future and solving this key challenge for the structural materials used in reactors.

Assessments of Data-Driven Deep Learning Models on One-Month Predictions of Pan-Arctic Sea Ice Thickness

In recent years,deep learning methods have gradually been applied to prediction tasks related to Arctic sea ice concentration,but relatively little research has been conducted for larger spatial and temporal scales,mainly due to the limited time coverage of observations and reanalysis data.Meanwhile,deep learning predictions of sea ice thickness(SIT)have yet to receive ample attention.In this study,two data-driven deep learning(DL)models are built based on the ConvLSTM and fully convolutional U-net(FC-Unet)algorithms and trained using CMIP6 historical simulations for transfer learning and fine-tuned using reanalysis/observations.These models enable monthly predictions of Arctic SIT without considering the complex physical processes involved.Through comprehensive assessments of prediction skills by season and region,the results suggest that using a broader set of CMIP6 data for transfer learning,as well as incorporating multiple climate variables as predictors,contribute to better prediction results,although both DL models can effectively predict the spatiotemporal features of SIT anomalies.Regarding the predicted SIT anomalies of the FC-Unet model,the spatial correlations with reanalysis reach an average level of 89%over all months,while the temporal anomaly correlation coefficients are close to unity in most cases.The models also demonstrate robust performances in predicting SIT and SIE during extreme events.The effectiveness and reliability of the proposed deep transfer learning models in predicting Arctic SIT can facilitate more accurate pan-Arctic predictions,aiding climate change research and real-time business applications.

Real-time arrival picking of rock microfracture signals based on convolutional-recurrent neural network and its engineering application

Accurately picking P-and S-wave arrivals of microseismic(MS)signals in real-time directly influences the early warning of rock mass failure.A common contradiction between accuracy and computation exists in the current arrival picking methods.Thus,a real-time arrival picking method of MS signals is constructed based on a convolutional-recurrent neural network(CRNN).This method fully utilizes the advantages of convolutional layers and gated recurrent units(GRU)in extracting short-and long-term features,in order to create a precise and lightweight arrival picking structure.Then,the synthetic signals with field noises are used to evaluate the hyperparameters of the CRNN model and obtain an optimal CRNN model.The actual operation on various devices indicates that compared with the U-Net method,the CRNN method achieves faster arrival picking with less performance consumption.An application of large underground caverns in the Yebatan hydropower station(YBT)project shows that compared with the short-term average/long-term average(STA/LTA),Akaike information criterion(AIC)and U-Net methods,the CRNN method has the highest accuracy within four sampling points,which is 87.44%for P-wave and 91.29%for S-wave,respectively.The sum of mean absolute errors(MAESUM)of the CRNN method is 4.22 sampling points,which is lower than that of the other methods.Among the four methods,the MS sources location calculated based on the CRNN method shows the best consistency with the actual failure,which occurs at the junction of the shaft and the second gallery.Thus,the proposed method can pick up P-and S-arrival accurately and rapidly,providing a reference for rock failure analysis and evaluation in engineering applications.

Characteristics and Influencing Factors of Microplastics in Snow in the Inner Mongolia Plateau, China

Microplastics(MPs;<5 mm)have become one of the most prominent global environmental pollution problems.MPs can spread to high altitudes through atmospheric transport and can be deposited by rainfall or snowfall,potentially threatening the structure and function of natural ecosystems.MPs in terrestrial and aquatic ecosystems alter the growth and functional characteristics of organisms.However,little attention has been given to the possible harm associated with MPs deposited in snow,particularly in the context of global climate warming.MPs collected from surface snow in the Inner Mongolia Plateau,China,were used for quantitative analysis and identification.The results showed that MPs were easily detected,and the related concentration was approximately(68±10)–(199±22)MPsL1 in snow samples.Fibers were the most common morphology,the polymer composition was largely varied,and the abundance and composition of MPs were linked to human activity to a great extent.High-throughput sequencing results showed that the composition and abundance of microorganisms also differed in snow samples from areas with different MP pollution characteristics,indicating a considerable difference in microbial functional diversity.MPs may have an interference effect on the individual growth and functional expression of microorganisms in snow.In addition,the results showed that functional living areas(e.g.,landfills and suburban areas)in cities play an important role in the properties of MPs.For instance,the highest abundance of MPs was found in thermal power plants,whereas the abundance of polymers per sample was significantly lower in the suburban area.The MP contaminants hidden in snow can alter microbial structure and function and are therefore a potential threat to ecosystem health.

Deep brain implantable microelectrode arrays for detection and functional localization of the subthalamic nucleus in rats with Parkinson’s disease

The subthalamic nucleus(STN)is considered the best target for deep brain stimulation treatments of Parkinson’s disease(PD).It is difficult to localize the STN due to its small size and deep location.Multichannel microelectrode arrays(MEAs)can rapidly and precisely locate the STN,which is important for precise stimulation.In this paper,16-channel MEAs modified with multiwalled carbon nanotube/poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(MWCNT/PEDOT:PSS)nanocomposites were designed and fabricated,and the accurate and rapid identification of the STN in PD rats was performed using detection sites distributed at different brain depths.These results showed that nuclei in 6-hydroxydopamine hydrobromide(6-OHDA)-lesioned brains discharged more intensely than those in unlesioned brains.In addition,the MEA simultaneously acquired neural signals from both the STN and the upper or lower boundary nuclei of the STN.Moreover,higher values of spike firing rate,spike amplitude,local field potential(LFP)power,and beta oscillations were detected in the STN of the 6-OHDA-lesioned brain,and may therefore be biomarkers of STN localization.Compared with the STNs of unlesioned brains,the power spectral density of spikes and LFPs synchronously decreased in the delta band and increased in the beta band of 6-OHDA-lesioned brains.This may be a cause of sleep and motor disorders associated with PD.Overall,this work describes a new cellular-level localization and detection method and provides a tool for future studies of deep brain nuclei.

Off-farm employment,agriculture production activities,and household dietary diversity in environmentally and economically vulnerable areas of Asia

Access to off-farm employment has been expected to be a critical approach to ending hunger and all forms of malnutrition,two important targets of achieving Zero Hunger.This study aims to investigate the role of off-farm employment in improving dietary diversity through substitution effect and complementary effect with agricultural production activities and income effect.This study adopts Poisson/Tobit/Probit/OLS regressions and the instrument variable method based on the primary survey data collected among 1,282 households at 12 sites in environmentally and economically vulnerable areas of China,Nepal,Cambodia,Thailand,and Myanmar in 2019.The results show that off-farm employment is positively associated with household dietary diversity and the consumption of flesh meat,fish and other aquatic animals,fruits,and milk and dairy products,which are rich in protein and micronutrients.The results of mechanism analysis show that off-farm employment contributes to household dietary diversity by improving crop diversity,especially for poor households,boosting the probability of livestock raising for households with the middle one-third disposal income,and increasing household income.The positive association between off-farm employment and household dietary diversity is much higher for households with the bottom one-third disposal income,low illiteracy,and from upper-middle income countries.These findings imply that off-farm employment does play a vital role in achieving multiple benefits of poverty alleviation,malnutrition reduction,and agrobiodiversity conservation in environmentally and economically vulnerable areas.However,it may enlarge the gaps in dietary diversity between households with low human capital and from low and lower-middle income countries and those with high human capital and from middle-high countries.

Genetic dissection and validation of a major QTL for grain weight on chromosome 3B in bread wheat(Triticum aestivum L.)

Grain weight is one of the key components of wheat(Triticum aestivum L.)yield.Genetic manipulation of grain weight is an efficient approach for improving yield potential in breeding programs.A recombinant inbred line(RIL)population derived from a cross between W7268 and Chuanyu 12(CY12)was employed to detect quantitative trait loci(QTLs)for thousand-grain weight(TGW),grain length(GL),grain width(GW),and the ratio of grain length to width(GLW)in six environments.Seven major QTLs,QGl.cib-2D,QGw.cib-2D,QGw.cib-3B,QGw.cib-4B.1,QGlw.cib-2D.1,QTgw.cib-2D.1 and QTgw.cib-3B.1,were consistently identified in at least four environments and the best linear unbiased estimation(BLUE)datasets,and they explained 2.61 to 34.85%of the phenotypic variance.Significant interactions were detected between the two major TGW QTLs and three major GW loci.In addition,QTgw.cib-3B.1 and QGw.cib-3B were co-located,and the improved TGW at this locus was contributed by GW.Unlike other loci,QTgw.cib-3B.1/QGw.cib-3B had no effect on grain number per spike(GNS).They were further validated in advanced lines using Kompetitive Allele Specific PCR(KASP)markers,and a comparison analysis indicated that QTgw.cib-3B.1/QGw.cib-3B is likely a novel locus.Six haplotypes were identified in the region of this QTL and their distribution frequencies varied between the landraces and cultivars.According to gene annotation,spatial expression patterns,ortholog analysis and sequence variation,the candidate gene of QTgw.cib-3B.1/QGw.cib-3B was predicted.Collectively,the major QTLs and KASP markers reported here provide valuable information for elucidating the genetic architecture of grain weight and for molecular marker-assisted breeding in grain yield improvement.

Endogenous biosynthesis of docosahexaenoic acid(DHA)regulates fish oocyte maturation by promoting pregnenolone production

Omega-3 polyunsaturated fatty acids(n-3 PUFAs),particularly docosahexaenoic acid(22:6n-3,DHA),play crucial roles in the reproductive health of vertebrates,including humans.Nevertheless,the underlying mechanism related to this phenomenon remains largely unknown.In this study,we employed two zebrafish genetic models,i.e.,elovl2^(-/-)mutant as an endogenous DHAdeficient model and fat1(omega-3 desaturase encoding gene)transgenic zebrafish as an endogenous DHA-rich model,to investigate the effects of DHA on oocyte maturation and quality.Results show that the elovl2^(-/-)mutants had much lower fecundity and poorer oocyte quality than the wild-type controls,while the fat1 zebrafish had higher fecundity and better oocyte quality than wildtype controls.DHA deficiency in elovl2^(-/-)embryos led to defects in egg activation,poor microtubule stability,and reduced pregnenolone levels.Further study revealed that DHA promoted pregnenolone synthesis by enhancing transcription of cyp11a1,which encodes the cholesterol side-chain cleavage enzyme,thereby stabilizing microtubule assembly during oogenesis.In turn,the hypothalamic-pituitary-gonadal axis was enhanced by DHA.In conclusion,using two unique genetic models,our findings demonstrate that endogenously synthesized DHA promotes oocyte maturation and quality by promoting pregnenolone production via transcriptional regulation of cyp11a1.

Assessing the Performance of CMIP6 Models in Simulating Droughts across Global Drylands

Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6(CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed.While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33%(with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration(PET) by ~32%(17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50%(29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation(water deficit) associated with dryland droughts is overestimated by 28%(24%) compared to observations. The observed increasing trends in drought fractional area,occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s,especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs.

Millisecond dynamics of colloidal suspension studied by X-ray photon correlation spectroscopy at the Shanghai Synchrotron Radiation Facility

X-ray photon correlation spectroscopy(XPCS)has emerged as a powerful tool for probing the nanoscale dynamics of soft condensed matter and strongly correlated materials owing to its high spatial resolution and penetration capabilities.This technique requires high brilliance and beam coherence,which are not directly available at modern synchrotron beamlines in China.To facilitate future XPCS experiments,we modified the optical setup of the newly commissioned BL10U1 USAXS beamline at the Shanghai Synchrotron Radiation Facility(SSRF).Subsequently,we performed XPCS measurements on silica suspensions in glycerol,which were opaque owing to their high concentrations.Images were collected using a high frame rate area detector.A comprehensive analysis was performed,yielding correlation functions and several key dynamic parameters.All the results were consistent with the theory of Brownian motion and demonstrated the feasibility of XPCS at SSRF.Finally,by carefully optimizing the setup and analyzing the algorithms,we achieved a time resolution of 2 ms,which enabled the characterization of millisecond dynamics in opaque systems.

Comparative analysis of primate and pig cells reveals primate-specific PINK1 expression and phosphorylation

PTEN-induced putative kinase 1(PINK1),a mitochondrial kinase that phosphorylates Parkin and other proteins,plays a crucial role in mitophagy and protection against neurodegeneration.Mutations in PINK1 and Parkin can lead to loss of function and early onset Parkinson's disease.However,there is a lack of strong in vivo evidence in rodent models to support the theory that loss of PINK1 affects mitophagy and induces neurodegeneration.Additionally,PINK1 knockout pigs(Sus scrofa)do not appear to exhibit neurodegeneration.In our recent work involving non-human primates,we found that PINK1 is selectively expressed in primate brains,while absent in rodent brains.To extend this to other species,we used multiple antibodies to examine the expression of PINK1 in pig tissues.In contrast to tissues from cynomolgus monkeys(Macaca fascicularis),our data did not convincingly demonstrate detectable PINK1expression in pig tissues.Knockdown of PINK1 in cultured pig cells did not result in altered Parkin and BAD phosphorylation,as observed in cultured monkey cells.A comparison of monkey and pig striatum revealed more PINK1-phosphorylated substrates in the monkey brain.Consistently,PINK1 knockout in pigs did not lead to obvious changes in the phosphorylation of Parkin and BAD.These findings provide new evidence that PINK1expression is specific to primates,underscoring the importance of non-human primates in investigating PINK1function and pathology related to PINK1 deficiency.

Taxonomic Status of Three Recently Proposed Species of the Genus Kurixalus(Anura,Rhacophoridae),with Discussion on the ZooBank Registrations for Electronical Publication

In the present study,we propose the synonymization of Kurixalus silvaenaias with Kurixalus qionglaiensis.This conclusion is based on morphological examination and phylogenetic analysis of a series of newly collected specimens,as well as the type series of both nomenclatures.The publication dates of the two species were determined according to the related articles of the International Code of Zoological Nomenclature.Of note,the ZooBank registrations for both species are invalid.Consequently,the publication of K.silvaenaias does not qualify as a published work and the correct publication date of K.qionglaiensis should be the date on which it was physically printed.Furthermore,based on the results presented in this study and its original description,the proposal of K.inexpectatus is deemed untenable and should,therefore,be considered a junior synonym of K.idiootocus.We further provide suggestions for the authors,editors,and publishers who are working on taxonomic publications,as well as for ZooBank to improve the registering service.