ChatGPT is an AI-powered chatbot platform that enables human users to converse with machines. It utilizes natural language processing and machine learning algorithms, transforming how people interact ...with AI technology. ChatGPT offers significant advantages over previous similar tools, and its potential for application in various fields has generated attention and anticipation. However, some experts are wary of ChatGPT, citing ethical implications. Therefore, this paper shows that ChatGPT has significant potential to transform marketing and shape its future if certain ethical considerations are taken into account. First, we argue that ChatGPT-based tools can help marketers create content faster and potentially with quality similar to human content creators. It can also assist marketers in conducting more efficient research and understanding customers better, automating customer service, and improving efficiency. Then we discuss ethical implications and potential risks for marketers, consumers, and other stakeholders, that are essential for ChatGPT-based marketing; doing so can help revolutionize marketing while avoiding potential harm to stakeholders.
Although 5-methylcytosine (m
C) is a widespread modification in RNAs, its regulation and biological role in pathological conditions (such as cancer) remain unknown. Here, we provide the ...single-nucleotide resolution landscape of messenger RNA m
C modifications in human urothelial carcinoma of the bladder (UCB). We identify numerous oncogene RNAs with hypermethylated m
C sites causally linked to their upregulation in UCBs and further demonstrate YBX1 as an m
C 'reader' recognizing m
C-modified mRNAs through the indole ring of W65 in its cold-shock domain. YBX1 maintains the stability of its target mRNA by recruiting ELAVL1. Moreover, NSUN2 and YBX1 are demonstrated to drive UCB pathogenesis by targeting the m
C methylation site in the HDGF 3' untranslated region. Clinically, a high coexpression of NUSN2, YBX1 and HDGF predicts the poorest survival. Our findings reveal an unprecedented mechanism of RNA m
C-regulated oncogene activation, providing a potential therapeutic strategy for UCB.
Ubiquitous copper-oxygen species are pivotal in enabling multifarious oxidation reactions in biological and chemical transformations. We herein construct a macrocycle-protected mixed-valence cluster ...(
BuC≡CCu
)-(μ
-OH)-Cu
by merging a copper acetylide cluster with a copper-oxygen moiety formed in Glaser coupling. This merged Cu(I/II) cluster shows remarkably strong oxidation capacity, whose reduction potential is among the most positive for Cu(II) and even comparable with some Cu(III) species. Consequently, the cluster exhibits high hydrogen atom transfer (HAT) reactivity with inert hydrocarbons. In contrast, the degraded Cu
-(μ
-OH)-Cu
embedded in a small macrocyclic homologue shows no HAT reactivity. Theoretical calculations indicate that the strong oxidation ability of Cu(II) in (
BuC≡CCu
)-(μ
-OH)-Cu
is mainly ascribed to the uneven charge distribution of Cu(I) ions in the
BuC≡CCu
unit because of significant d
→ π*
back donation. The present study on in situ formed metal clusters opens a broad prospect for mechanistic studies of Cu-based catalytic reactions.
The development of efficient visible‐light‐driven photocatalysts is one of the critically important issues for solar hydrogen production. Herein, high‐efficiency visible‐light‐driven In2O3/CdZnS ...hybrid photocatalysts are explored by a facile oil‐bath method, in which ultrafine CdZnS nanoparticles are anchored on NH2‐MIL‐68‐derived fusiform In2O3 mesoporous nanorods. It is disclosed that the as‐prepared In2O3/CdZnS hybrid photocatalysts exhibit enhanced visible‐light harvesting, improves charges transfer and separation as well as abundant active sites. Correspondingly, their visible‐light‐driven H2 production rate is significantly enhanced for more than 185 times to that of pristine In2O3 nanorods, and superior to most of In2O3‐based photocatalysts ever reported, representing their promising applications in advanced photocatalysts.
High‐efficiency visible‐light‐driven In2O3/CdZnS hybrid photocatalysts are explored by a facile oil‐bath method. Benefitting from the enhanced visible‐light harvesting, improved charges transfer, and increased active sites, the photocatalytic H2 evolution rate of the optimal In2O3/CdZnS hybrid photocatalyst is enhanced for more than 185 times to that of pristine In2O3, and superior to most of In2O3‐based photocatalysts ever reported.
Evapotranspiration (ET) is an essential parameter connecting the hydrological cycle, energy balance and carbon cycle. The angular effect (AE) of remotely sensed land surface temperature (LST), one of ...the obstacles hindering the application of single-source energy balance models in continental and global ET estimates, is a long-standing issue that has rarely been witnessed in the last decade. In this study, we propose a general framework for correcting the angular effect that could be practically applied to reduce the uncertainties in the ET estimations with any single-source energy balance-based model, under the guidance of simulation of thermal radiation directionality through the integration of a directional module from the soil-canopy spectral radiances, photosynthesis, fluorescence, temperature, and energy balance (SCOPE) and an artificially added ET estimation module. The correction was conducted by adjusting the directional reflectance and then the reflectance-based fractional vegetation coverage to the view zenith angle of interest, together with estimating the soil and vegetation component temperatures. This framework was later tested on the widely applied surface energy balance system (SEBS) driven by the directional LST from the Moderate Resolution Imaging Spectroradiometer (MODIS) collected on 94 clear-sky days between 2009 and 2010 at the Yucheng site. The simulation results indicated that (1) the AE obviously increased as the view zenith angle increased; (2) the AE was more apparent in the backward scattering direction than in the forward scattering direction; and (3) most of the AE first increased evidently and then decreased with the increase in the leaf area index. The correction results related to the SEBS-based ET estimations, compared to the in situ ET measurements, showed that the proposed framework greatly improved the estimations of ET, with the root mean square error decreasing by 27.6 W/m2 (∼8%, relative to the average 339 W/m2) from 86.8 W/m2 (∼25%) to 59.2 W/m2 (∼17%) and the bias decreasing from 49.7 W/m2 (∼15%) to −6.5 W/m2 (∼2%). In conclusion, the proposed framework efficiently corrected the angular effect of remotely sensed LST on ET estimation. We expect more attention to be paid to the angular effect and hope our work could provide insight for solving this pendent issue.
•We proposed a general framework of correcting the angular effects on ET estimate.•The framework was demonstrated to greatly improve the SEBS-estimated ET.•The framework is potentially applied to any single-source energy balance ET model.
The cytokinin oxidase / dehydrogenase (CKX) gene plays a principal role in controlling cyto-kinin levels and has been shown to be a major quantitative trait locus (QTL) affecting grain number in ...rice. However, the function and evaluation of the haplotypes of the wheat CKX gene have yet to be illustrated.
In this study, TaCKX6-D1, a wheat ortholog of rice OsCKX2, was cloned and its haplotype variants were determined to be significantly associated with the 1000-grain weight on the basis of linkage mapping, association analysis and gene expression analysis.
Five TaCKX6-D1 haplotypes, designated a–e, were identified. An indel marker was developed to identify haplotype a, which was associated with higher grain weight. Haplotype a showed decreased expression relative to haplotype b in seeds at 8 d after pollination. Sequence variations among modern cultivars, landraces and wild species suggest a significant domestication signature at the TaCKX6-D1 locus in Chinese wheat germplasm.
TaCKX6-D1 may serve as a useful gene for the breeding of high-yielding wheat. A strategy for allele mining and utilization of TaCKX6-D1 was proposed. Our study also sheds light on the mechanisms of grain development and domestication of wheat, as well as the functional divergence of orthologs in comparative genomics.
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•Microalgae-based technology is a promising alternative for antibiotics removal.•The underlying mechanisms of microalgae-based antibiotics removal are summarized.•Several novel ...approaches and hybrid techniques are recommended to promote antibiotics removal.•This review also outlines future research directions of microalgae-based technology.
Antibiotics contamination is an emerging environmental concern, owing to its potential risks to ecosystems and human health. Microalgae-based technology has been widely reported as a promising alternative to conventional wastewater treatment, since it is a solar-power driven, ecologically friendly, cost-effective, and sustainable reclamation strategy. This review provides fundamental insights into the major mechanisms underpinning microalgae-based antibiotics removal, including bioadsorption, bioaccumulation, and biodegradation. The critical role of extracellular polymeric substances on bioadsorption and extracellular biodegradation of antibiotics are also covered. Moreover, this review sheds light on the important factors affecting the removal of antibiotics by microalgae, and summarizes several novel approaches to improve the removal efficiency, including acclimation, co-metabolism and microbial consortium. Besides, hybrid systems (such as, microalgae-based technologies combined with the conventional activated sludge, advanced oxidation processes, constructed wetlands, and microbial fuel cells), and genetic engineering are also recommended, which will be feasible for enhanced removal of antibiotics. Finally, this review also highlights the need for further studies aimed at optimizing microalgae-based technology, with emphasis on improving performance and expanding its application in large-scale settings, especially in terms of technical, environmental-friendly and economically competitiveness. Overall, this review summarizes current understanding on microalgae-based technologies for removal of antibiotics and outlines future research directions.
Pyrolysis experiments between 25 and 800 °C for three main components (cellulose, hemicellulose, and lignin) mixed in different proportions were conducted on a thermogravimetric analyzer (TGA) and ...pyrolysis–gas chromatography/mass spectrometer (Py-GC/MS). The interactions between the three main components during the pyrolysis of biomass were explored from two aspects, namely thermogravimetric properties and pyrolysis products. The results indicate that interactions existed among the three biomass components in the co-pyrolysis process. The presence of lignin significantly reduces the pyrolysis rate of cellulose and inhibits the formation of sugars (mainly levoglucosan) in the pyrolysis of cellulose and hemicellulose. However, the existence of cellulose or hemicellulose greatly promotes the pyrolysis of lignin to produce phenolic compounds. This finding is meaningful for the application of biomass pyrolysis.
Soil organic matter (SOM) is the main source of soil nutrients, which are essential for the growth and development of agricultural crops. Hyperspectral remote sensing is one of the most efficient ...ways of estimating the SOM content. Visible, near infrared, and mid-infrared reflectance spectroscopy, combined with the partial least squares regression (PLSR) method is considered to be an effective way of determining soil properties. In this study, we used 54 different spectral pretreatments to preprocess soil spectral data. These spectral pretreatments were composed of three denoising methods, six data transformations, and three dimensionality reduction methods. The three denoising methods included no denoising (ND), Savitzky–Golay denoising (SGD), and wavelet packet denoising (WPD). The six data transformations included original spectral data, R; reciprocal, 1/R; logarithmic, log(R); reciprocal logarithmic, log(1/R); first derivative, R’; and first derivative of reciprocal, (1/R)’. The three dimensionality reduction methods included no dimensionality reduction (NDR), sensitive waveband dimensionality reduction (SWDR), and principal component analysis (PCA) dimensionality reduction (PCADR). The processed spectra were then employed to construct PLSR models for predicting the SOM content. The main results were as follows—(1) the wavelet packet denoising (WPD)-R’ and WPD-(1/R)’ data showed stronger correlations with the SOM content. Furthermore, these methods could effectively limit the correlation between the adjacent bands and, thus, prevent “overfitting”. (2) Of the 54 pretreatments investigated, WPD-(1/R)’-PCADR yielded the model with the highest accuracy and stability. (3) For the same denoising method and spectral transformation data, the accuracy of the SOM content estimation model based on SWDR was higher than that of the model based on NDR. Furthermore, the accuracy in the case of PCADR was higher than that for SWDR. (4) Dimensionality reduction was effective in preventing data overfitting. (5) The quality of the spectral data could be improved and the accuracy of the SOM content estimation model could be enhanced effectively, by using some appropriate preprocessing methods (one combining WPD and PCADR in this study).
Land surface temperature (LST) is described as one of the most important environmental parameters of the land surface biophysical process. Commonly, the remote-sensed LST products yield a tradeoff ...between high temporal and high spatial resolution. Thus, many downscaling algorithms have been proposed to address this issue. Recently, downscaling with machine learning algorithms, including artificial neural networks (ANNs), support vector machine (SVM), and random forest (RF), etc., have gained more recognition with fast operation and high computing precision. This paper intends to make a comparison between machine learning algorithms to downscale the LST product of the moderate-resolution imaging spectroradiometer from 990 to 90 m, and downscaling results would be validated by the resampled LST product of the advanced spaceborne thermal emission and reflection radiometer. The results are further compared with the classical algorithm-thermal sharpening algorithm (TsHARP), using images derived from two representatives kind of areas of Beijing city. The result shows that: 1) all machine learning algorithms produce higher accuracy than TsHARP; 2) the performance of TsHARP on urban area is unsatisfactory than rural because of the weak indication of impervious surface by normalized difference vegetation index, however, machine learning algorithms get the desired results on both two areas, in which ANN and RF models perform well with high accuracy and fast arithmetic, SVM also gets a good result but there is a smoothing effect on land surface; and 3) additionally, machine learning algorithms are promising to achieve a universal framework which can downscale LST for any area within the training data from long spatiotemporal sequences.
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