The incorporation of trace metals into land snail shells may record the ambient environmental conditions, yet this potential remains largely unexplored. In this study, we analyzed modern snail shells (Cathaica sp.) collected from 16 sites across the Chinese Loess Plateau to investigate their trace metal compositions. Our results show that both the Sr/Ca and Ba/Ca ratios exhibit minimal intra-shell variability and small inter-shell variability at individual sites. A significant positive correlation is observed between the shell Sr/Ca and Ba/Ca ratios across the plateau, with higher values being recorded in the northwestern sites where less monsoonal rainfall is received. We propose that shell Sr/Ca and Ba/Ca ratios, which record the composition of soil solution, may be controlled by the Rayleigh distillation in response to prior calcite precipitation. Higher rainfall amounts may lead to a lower degree of Rayleigh distillation and thus lower shell Sr/Ca and Ba/Ca ratios. This is supported by the distinct negative correlation between summer precipitation and shell Sr/Ca and Ba/Ca ratios, enabling us to reconstruct summer precipitation amounts using the Sr/Ca and Ba/Ca ratios of Cathaica sp. shells. The potential application of these novel proxies may also be promising for other terrestrial mollusks living in the loess deposits globally.

The primary focus of this article is to capture heterogeneous treatment effects measured by the conditional average treatment effect. A model averaging estimation scheme is proposed with multiple candidate linear regression models under heteroskedastic errors, and the properties of this scheme are explored analytically. First, it is shown that our proposal is asymptotically optimal in the sense of achieving the lowest possible squared error. Second, the convergence of the weights determined by our proposal is provided when at least one of the candidate models is correctly specified. Simulation results in comparison with several related existing methods favor our proposed method. The method is applied to a dataset from a labor skills training program.

This study delves into the intricate relationship between chief executive officers' (CEOs') experiences of poverty and the digital transformation of their firms. Employing comprehensive data collection on CEOs' birthplaces and leveraging advanced text analytics to quantify digitalization, our analysis encompasses a wide array of listed companies in China. The findings reveal that CEOs' impoverished experiences exert a detrimental influence on their firms' digital transformation efforts, primarily due to a lack of motivation and social resources necessary for such initiatives. However, this adverse effect can be ameliorated when CEOs gain access to substantial social resources in later life. Our conclusions are robust, supported by rigorous testing, and underscore not only the impact of CEOs' early-life poverty on corporate digitalization but also the potential for overcoming these challenges through the acquisition of external social resources and connections in adulthood. This study contributes significantly to existing literature and offers practical implications for enhancing corporate digital transformation strategies.

Although it is well established that gestational diabetes mellitus (GDM) is associated with fetal overgrowth in singleton pregnancies, little is known about its role in twins. We aimed to explore the relationship between GDM and the longitudinal fetal growth in twin pregnancies. This was a retrospective matched cohort study of GDM and non-GDM twin pregnancies delivered ≥36 weeks without other complications. All the women performed ≥3 ultrasounds after 22 weeks. Linear mixed models (LMMs) were used to explore the relationships between longitudinal fetal growth trajectories and GDM. Group-based trajectory modeling (GBTM) and generalized estimating equation (GEE) were applied to identify the latent growth patterns and investigate their relationships with GDM. In total, 215 GDM and 645 non-GDM twins were included, the majority of the patients did not require medication therapy (n = 202, GDMA1). LMM revealed that, compared with non-GDM, GDM was associated with an average increase in fetal weight of 4.36 g (95% CI [1.25, 7.48]) per week. GBTM and GEE further revealed that GDM increased the odds of fetal weight trajectory to nearly 40% of the total fetal weight trajectory, classified into the high-speed group (aOR = 1.39, 95% CI [1.03, 1.88]), associating with a 49.44 g (95% CI [11.41, 87.48]) increase in birth weight. Subgroup analysis revealed that all these differences were only significant among the GDMA1 pregnancies (p < .05). GDM (GDMA1) is significantly associated with an increase in fetal weight during gestation in twin pregnancies. However, this acceleration is mild, and its significance requires further exploration.

Predicting epidemic trends of coronavirus disease 2019 (COVID-19) remains a key public health concern globally today. However, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection rate in previous studies of the transmission dynamics model was mostly a fixed value. Therefore, we proposed a meta-Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) model by adding a time-varying SARS-CoV-2 reinfection rate to the transmission dynamics model to more accurately characterize the changes in the number of infected persons. The time-varying reinfection rate was estimated using random-effect multivariate meta-regression based on published literature reports of SARS-CoV-2 reinfection rates. The meta-SEIRS model was constructed to predict the epidemic trend of COVID-19 from February to December 2023 in Sichuan province. Finally, according to the online questionnaire survey, the SARS-CoV-2 infection rate at the end of December 2022 in Sichuan province was 82.45%. The time-varying effective reproduction number in Sichuan province had two peaks from July to December 2022, with a maximum peak value of about 15. The prediction results based on the meta-SEIRS model showed that the highest peak of the second wave of COVID-19 in Sichuan province would be in late May 2023. The number of new infections per day at the peak would be up to 2.6 million. We constructed a meta-SEIRS model to predict the epidemic trend of COVID-19 in Sichuan province, which was consistent with the trend of SARS-CoV-2 positivity in China. Therefore, a meta-SEIRS model parameterized based on evidence-based data can be more relevant to the actual situation and thus more accurately predict future trends in the number of infections.

Chinese characters hold great potential to help inform and enrich psycholinguistic research on lexical ambiguity as a large portion of them are ambiguous in nature with meaning varying from context to context. This report presents a psycholinguistic database that contains over 2000 characters with normative measures for meaning dominance and meaning balance, that is, the relative frequency of each meaning associated with a target character and the degree of balance across the meanings of the character. The measurement process takes advantage of the fact that, in Chinese, generating words containing a target character is the most convenient way to specify and disambiguate character meanings. Character meanings stored in ordinary people’s mental lexicon are identified based on the words, along with a small portion of meaning descriptions, listed by over 900 native speakers. The measures of meaning dominance and meaning balance for the characters are derived from computing the relative frequencies of the meanings. Potential research and practical applications of the database, as a valuable tool, to enhance our understanding of the acquisition, representation, and processing of ambiguous lexical items are discussed.

Unraveling the neurobiological foundations of childhood maltreatment is important due to the persistent associations with adverse mental health outcomes. However, the mechanisms through which abuse and neglect disturb resting-state network connectivity remain elusive. Moreover, it remains unclear if positive parenting can mitigate the negative impact of childhood maltreatment on network connectivity. We analyzed a cohort of 194 adolescents and young adults (aged 14–25, 47.42% female) from the Neuroscience in Psychiatry Network (NSPN) to investigate the impact of childhood abuse and neglect on resting-state network connectivity. Specifically, we examined the SAN, DMN, FPN, DAN, and VAN over time. We also explored the moderating role of positive parenting. The results showed that childhood abuse was linked to stronger connectivity within the SAN and VAN, as well as between the DMN-DAN, DMN-VAN, DMN-SAN, SAN-DAN, FPN-DAN, SAN-VAN, and VAN-DAN networks about 18 months later. Positive parenting during childhood buffered the negative impact of childhood abuse on network connectivity. To our knowledge, this is the first study to demonstrate the protective effect of positive parenting on network connectivity following childhood abuse. These findings not only highlight the importance of positive parenting but also lead to a better understanding of the neurobiology and resilience mechanisms of childhood maltreatment.

Previous studies have revealed an association between dietary factors and atopic dermatitis (AD). To explore whether there was a causal relationship between diet and AD, we performed Mendelian randomisation (MR) analysis. The dataset of twenty-one dietary factors was obtained from UK Biobank. The dataset for AD was obtained from the publicly available FinnGen consortium. The main research method was the inverse-variance weighting method, which was supplemented by MR‒Egger, weighted median and weighted mode. In addition, sensitivity analysis was performed to ensure the accuracy of the results. The study revealed that beef intake (OR = 0·351; 95 % CI 0·145, 0·847; P = 0·020) and white bread intake (OR = 0·141; 95 % CI 0·030, 0·656; P = 0·012) may be protective factors against AD. There were no causal relationships between AD and any other dietary intake factors. Sensitivity analysis showed that our results were reliable, and no heterogeneity or pleiotropy was found. Therefore, we believe that beef intake may be associated with a reduced risk of AD. Although white bread was significant in the IVW analysis, there was large uncertainty in the results given the wide 95 % CI. Other factors were not associated with AD in this study.

Convolutional sequence to sequence (CNN seq2seq) models have met success in abstractive summarization. However, their outputs often contain repetitive word sequences and logical inconsistencies, limiting the practicality of their application. In this paper, we find the reasons behind the repetition problem in CNN-based abstractive summarization through observing the attention map between the summaries with repetition and their corresponding source documents and mitigate the repetition problem. We propose to reduce the repetition in summaries by attention filter mechanism (ATTF) and sentence-level backtracking decoder (SBD), which dynamically redistributes attention over the input sequence as the output sentences are generated. The ATTF can record previously attended locations in the source document directly and prevent the decoder from attending to these locations. The SBD prevents the decoder from generating similar sentences more than once via backtracking at test. The proposed model outperforms the baselines in terms of ROUGE score, repeatedness, and readability. The results show that this approach generates high-quality summaries with minimal repetition and makes the reading experience better.

Light-absorbing impurities (LAIs, e.g. black carbon (BC), organic carbon (OC), mineral dust (MD)) deposited on snow cover reduce albedo and accelerate its melting. Northern Xinjiang (NX) is an arid and semi-arid inland region, where snowmelt leads to frequent floods that have been a serious threat to local ecological security. There is still a lack of quantitative assessments of the effects of LAIs on snowmelt in the region. This study investigates spatial variations of LAIs in snow and its effect on snow albedo, radiative forcing (RF) and snowmelt across NX. Results showed that concentrations of BC, OC (only water-insoluble OC), MD ranged from 32 to 8841 ng g−1, 77 to 8568 ng g−1 and 0.46 to 236 µg g−1, respectively. Weather Research and Forecasting Chemistry model suggested that residential emission was the largest source of BC. Snow, Ice, and Aerosol Radiative modelling showed that the average contribution of BC and MD to snow albedo reduction was 17 and 3%, respectively. RF caused by BC significantly exceeded RF caused by MD. In different scenarios, changes in snow cover duration (SCD) caused by BC and MD decreased by 1.36 ± 0.61 to 6.12 ± 3.38 d. Compared with MD, BC was the main dominant factor in reducing snow albedo and SCD across NX.

Using ethanol adsorption calorimetry, the surface energetics of two carbon substrates and two products in microwave-assisted carbon nanotube (CNT) growth was studied. In this study, the ethanol adsorption enthalpies of the two graphene-based samples at 25 °C were measured successfully. Specifically, the near-zero differential enthalpies of ethanol adsorption are −75.7 kJ/mol for graphene and −63.4 kJ/mol for CNT-grafted graphene. Subsequently, the differential enthalpy curve of each sample becomes less exothermic until reaching a plateau, −55.8 kJ/mol for graphene and −49.7 kJ/mol for CNT-grafted graphene, suggesting favorable adsorbate–adsorbent binding. Moreover, the authors interpreted and discussed the partial molar entropy and chemical potential of adsorption as the ethanol surface coverage (loading) increases. Due to the low surface areas of carbon black–based samples, adsorption calorimetry could not be performed. This model study demonstrates that using adsorption calorimetry as a fundamental tool and ethanol as the molecular probe, the overall surface energetics of high–surface area carbon materials can be estimated.

Magnetic iron oxide nanoparticles (MIONPs) are particularly attractive in biosensor, antibacterial activity, targeted drug delivery, cell separation, magnetic resonance imaging tumor magnetic hyperthermia, and so on because of their particular properties including superparamagnetic behavior, low toxicity, biocompatibility, etc. Although many methods had been developed to produce MIONPs, some challenges such as severe agglomeration, serious oxidation, and irregular size are still faced in the synthesis of MIONPs. Thus, various strategies had been developed for the surface modification of MIONPs to improve the characteristics of them and obtain multifunctional MIONPs, which will widen the applicational scopes of them. Therefore, the processes, mechanisms, advances, advantages, and disadvantages of six main approaches for the synthesis of MIONPs; surface modification of MIONPs with inorganic materials, organic molecules, and polymer molecules; applications of MIONPs or modified MIONPs; the technical challenges of synthesizing MIONPs; and their limitations in biomedical applications were described in this review to provide the theoretical and technological guidance for their future applications.

In order to investigate the benefits of compound waterways more fully, this study reveals vessel navigational mode and traffic conflicts in a compound waterway through a case analysis, following which a type of simplified prototype of a compound waterway is proposed and three key conflict areas are specified. Based on the three key sub-models of slot allocation for vessels in a waterway entrance, traffic flow conversion of a main and auxiliary waterway in a precautionary area, and traffic flow coordination of division and confluence in a Y crossing area, a vessel traffic scheduling optimisation model is presented, with the minimum waterway occupancy time and minimum total waiting time of vessels as the objective. Furthermore, a multi-objective genetic algorithm is proposed to solve the model and a simulation experiment is carried out. By analysing the optimised solution and comparing it with other scheduling schemes in common use, the results indicate that this method can effectively improve navigation safety and efficiency in a compound waterway.

A novel luminogen-functionalized SBA-15, denoted as SNT, was developed by incorporating tris(4-bromophenyl)amine (TBPA) into SBA-15 via a “fixation-induced emission” strategy. The emission of TBPA on the matrix of SBA-15 was greatly enhanced, making the SNT possible as a fluorescence sensor. Cefalexin, a typical antibiotic, was chosen as the model analyte to be assayed and sensitive detection performance was achieved. This is the first time for cefalexin to be detected by a fluorescent method. Moreover, the SNT can be recycled by simply washing with proper solvents then used for next detection. This work provides a strategy to greatly improve the emission characteristics of fluorophores, even if a mediocre small fluorophore. It can be extended to design practical fluorescent sensors with high performance and recyclability by this strategy.

Nanomaterials have been intensively studied over the past decades with many advantages over traditional bulk materials in many applications. Nanomaterials' properties are largely governed by their chemical compositions, sizes, shapes, dimensions, morphologies and structures, which are primarily controlled with the chemical and/or physical fabrication methods and processes. This prospective will highlight recent progress on the modifications of oxide nanomaterials' properties by hydrogenation, namely heat treatment under hydrogen or hydrogen plasma environment, for various applications.