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Abstract To investigate the diagnostic value of intraoperative cytology and rapid immunocytochemistry in primary central nervous system lymphoma. 254 cases of lymphoma and 82 cases of non-lymphoma were collected from 2010 to 2023. Frozen section(FS) was using alone in 44 cases during 2010–2014, FS and intraoperative cytology(IC) were using in 251 cases during 2015 to 2022. Rapid immunocytochemical(RICC, CD20, GFAP) were using with FS + IC in 41 cases during 2021 to 2023. Method One: According to the results of archives, statistic the diagnostic accuracy of lymphoma during three time periods. Method Two: All cases were randomly renumbered, 4 neuropathologists compared the accuracy of independent histology and that of combining cytology. The archives showed the diagnostic accuracy of FS in PCNSL was 77.27%, FS + IC was 86.06%, FS + IC + RICC was 92.68%. The retrospective study demonstrated the diagnostic accuracy of FS was 79.76%, FS + IC was 87.33% and FS + IC + RICC was 92.68%. The positive predictive value, negative predictive value, sensitivity, specificity and accuracy of CD20 were 100%, 76.92%, 90.32%, 100% and 92.68%, respectively. The results of the paired χ2 test was no statistically significant difference (0.05

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder distinguished by gradual depletion of motor neurons. RNA binding motif protein 5 (RBM5), an abundantly expressed RNA-binding protein, plays a critical role in the process of cellular death. However, little is known about the role of RBM5 in the pathogenesis of ALS. Here, we found that RBM5 was upregulated in ALS hSOD1G93A-NSC34 cell models and hSOD1G93A mice due to a reduction of miR-141–5p. The upregulation of RBM5 increased the apoptosis of motor neurons by inhibiting Rac1-mediated neuroprotection. In contrast, genetic knockdown of RBM5 rescued motor neurons from hSOD1G93A-induced degeneration by activating Rac1 signaling. The neuroprotective effect of RBM5-knockdown was significantly inhibited by the Rac1 inhibitor, NSC23766. These findings suggest that RBM5 could potentially serve as a therapeutic target in ALS by activating the Rac1 signalling.

BackgroundThis study aimed to evaluate the causal impact of common modifiable lifestyles on obstructive sleep apnea (OSA), which is beneficial for recommendations to prevent and manage OSA.MethodPublished genome-wide association study (GWAS) summary statistics were used to perform two-sample Mendelian randomization (MR). Variants associated with each exposure of smoking, drinking, and leisure sedentary behaviors at the genetic level were used as instrumental variables (IVs). Then, inverse-variance weighting (IVW) was considered the primary result for causality. Moreover, several complimented approaches were also included to verify the observed associations. MR-PRESSO and MR-Egger intercept were applied to test the horizontal pleiotropy. To assess heterogeneity, Cochran's Q test by IVW and MR-Egger were applied.ResultsRegular smoking history increased OSA risk in all applied approaches [OR (95% CI)IVW = 1.28 (1.12, 1.45), p = 1.853 × 10−4], while the causality of lifetime smoking index [OR (95% CI)IVW = 1.39 (1.00, 1.91), p = 0.048], alcohol intake frequency [outliers removed OR (95% CI)IVW = 1.26 (1.08, 1.45), p = 0.002], and coffee intake behavior [OR (95% CI)IVW = 1.66 (1.03, 2.68), p = 0.039] on OSA risk were not always consistent in other approaches. In addition, no robust causal associations were observed for the effect of sedentary leisure behaviors on OSA risk. In sensitivity analysis, we observed no sign of horizontal pleiotropy or heterogeneity.ConclusionEver regularly smoking has a robust causal role in increasing OSA risk, which should be discouraged as precautions from developing OSA.

Solar energy-driven semiconductor photocatalysis has broad application prospect in the environmental governance field. However, vital problems that limits its application is that the discontinuity of nature sunlight. The ability of keeping catalytic activity in the dark could tackle these problems. Herein, a simple all-day-active photocatalytic system based on carbon nitride with electron storage property was carried out, which forms highly reductive radicals with lifetime exceeding diurnal cycle under sunlight irradiation. This carbon nitride system is capable to give off its trapped electrons to perform efficient Rhodamine B (RhB) degradation and Pb2+ reduction in the dark. The all-day-active photocatalyst system can still maintain catalytic activity even when it is cloudy or closer to night. Dramatically, this carbon nitride could hold the storage electrons for days under vacuum. The system above for storing sunlight as long-lived radicals will demonstrate a new approach for environmental protection, such as the remove of low-level pollutants in cloudy days and even the underground conditions.

English holds significant importance as a foreign language in Mainland China and Hong Kong, where ongoing curriculum revisions are shaped by economic and sociocultural advancements. Previous research on English Language Teaching (ELT) curriculum comparisons in Asia has frequently overlooked the exploration of underlying sociocultural and socio-political factors that contribute to the observed similarities and differences. Adopting a governmentality Perspective informed by Dean's analytics of government theory, this cross-cultural comparative study investigates the ELT curricula in senior secondary schools in Mainland China and Hong Kong. Through this analysis, the study explores how sociocultural and socio-political factors interact to influence the educational landscapes. By examining the dimensions of problematizations, rationalities, techne, and teleology within the curricula, the research uncovers common challenges, rationales, approaches, and objectives, as well as distinctions arising from the unique sociocultural, political, and economic contexts of Mainland China and Hong Kong. This examination underscores the profound impact of these contextual factors on ELT curriculum design, contributing valuable insights to the cross-cultural discourse. Furthermore, the findings lay the groundwork for future research and policy development in the realm of ELT curricula, emphasizing the need for additional studies employing diverse methods and focusing on the implemented and experienced curriculum in senior secondary schools to provide a comprehensive understanding of English language education in both Mainland China and Hong Kong.

Since 2016, the Argo (Array for Real-Time Geostrophic Oceanography) ocean salinity data has exhibited significant drift, directly affecting the accurate quantification of the global steric sea level (SSL) rates. To further investigate how salinity drift affects the estimation of SSL rates in different depths and regions, we divide the 0–2000 m into three layers (0–300 m, 300–1000 m and 1000–2000 m) and select five open oceans (the South and North Pacific, the South and North Atlantic, and the Indian Ocean) for discussion. By comparing the SSL rates between the periods of 2005–2015 and 2005–2019, we can evaluate the impact of salinity drift. Taking the estimated results from the IPRC (provided by the International Pacific Research Center at the University of Hawaii) and BOA (provided by the Second Institute of Oceanography, China) data as examples, we find that the effect of salinity drift is the largest at the depth of 1000–2000 m, about 29% for IPRC data and about 18% for BOA data. Moreover, the South Atlantic is susceptible to the effects of salinity drift, with an approximately 13% impact for IPRC data and 21% for BOA data.

PurposeThe aim of our study is to estimate the associations and causalities of glucose metabolism traits of fasting blood glucose (FBG), fasting insulin (FINS), glycosylated hemoglobin (HbA1c), and 2-h glucose post-challenge (2hGlu) with sleep traits consisting of excessive daytime sleepiness (EDS), insomnia, and sleep duration.MethodsWe employed standard quantitative analysis procedures to assess the associations between sleep traits and glucose metabolism. Moreover, we acquired published genome-wide association studies (GWAS) summary statistics for these traits and conducted Mendelian randomization (MR) analyses to estimate their causal directions and effects. Inverse variance weighting (IVW) was employed as the primary approach, followed by sensitivity analyses.ResultsA total of 116 studies with over 840,000 participants were included in the quantitative analysis. Our results revealed that participants with abnormal glucose metabolism had higher risks for EDS (OR [95% CI] = 1.37 [1.10,1.69]), insomnia (OR [95% CI] = 1.65 [1.24,2.20]), and both short and long sleep duration (OR [95% CI] = 1.35 [1.12,1.63]; OR [95% CI] = 1.38 [1.13,1.67] respectively). In addition, individuals with these sleep traits exhibited alterations in several glycemic traits compared with non-affected controls. In MR analysis, the primary analysis demonstrated causal effects of 2hGlu on risks of EDS (OR [95% CI] = 1.022 [1.002,1.042]) and insomnia (OR [95% CI] = 1.020[1.001,1.039]). Furthermore, FINS was associated with short sleep duration (OR [95% CI] = 1.043 [1.018,1.068]), which reversely presented a causal influence on HbA1c (β [95% CI] = 0.131 [0.022,0.239]). These results were confirmed by sensitivity analysis.ConclusionOur results suggested mutual risk and causal associations between the sleep traits and glycemic traits, shedding new light on clinical strategies for preventing sleep disorders and regulating glucose metabolism. Future studies targeting these associations may hold a promising prospect for public health.

Background: ANO1 is closely correlated with the activation of EGFR and CaMKII, while EGFR and CaMKII show low activation in amyotrophic lateral sclerosis (ALS) models. Therefore, we designed experiments to verify that ANO1 may play a protective role on motor neurons in ALS by activating EGFR and CaMKII. Methods: The expression changes of ANO1, EGFR, CaMKII, pEGFR, and pCaMKII, cell survival status, and apoptosis were studied by western blot, real-time quantitative PCR, immunofluorescence, immunohistochemistry, CCK-8, and flow cytometry. The role of ANO1 in the ALS model by activating EGFR and CaMKII was studied by applying corresponding activators, inhibitors, gene silencing, and overexpression. Results: In hSOD1G93A transgenic animals and cell lines, low expression of ANO1 and low activation of EGFR and CaMKII were identified. ANO1 expression decreased gradually with the progression of ALS. Overexpression of ANO1 in the hSOD1G93A cell line and primary neurons of hSOD1G93A transgenic mice increased cell viability and decreased cell apoptosis. After the application of ANO1 inhibitor CaCC-inhA01 in hSOD1G93A cell line and primary neurons of hSOD1G93A transgenic mice, EGFR activator EGF and CaMKII activator Carbachol, increased cell viability and reduced cell apoptosis. After ANO1 was overexpressed in the hSOD1G93A cell line and primary neurons of hSOD1G93A transgenic mice, EGFR inhibitor AEE788 and CaMKII inhibitor KN93 decreased cell viability and increased cell apoptosis. Conclusions: Our results suggest that ANO1 plays an important role in the survival of ALS motor neurons. ANO1 can increase cell activity and reduce apoptosis by activating EGFR and CaMKII signals.

Abstract Various studies showed that the effect of immune activation is pro-atherogenic and coronary heart disease (CHD) should therefore be considered an autoimmune disease. This study aimed to identify potential immune-related biomarkers, pathways, and the potential regulatory networks underlying CHD. Differentially expressed genes (DEGs) between CHD and control samples were determined by analyzing GSE71226 and GSE9128. The overlapping differential expression immune-related genes (DE-IRGs) for CHD were identified by analyzing the ImmPort database and two GEO databases. A total of 384 DE-IRGs were identified. Subsequently, comprehensive enrichment analyses suggested that DE-IRGs were enriched in immune-related pathways, including autoimmune thyroid disease, the intestinal immune network for IGA production, and downstream signaling events of B cell receptors. The signature of DE-IRGs was validated using an external independent dataset GSE20681 (AUC = 0.875). Furthermore, we conducted protein–protein interaction network analysis and identified eight hub genes, which were most enriched in regulation of defense response, NF-κB signaling pathway, regulation of JNK cascade, and regulation of cytokine production. Moreover, networks of miRNAs-mRNAs and transcription factors (TFs)-mRNA underlying the integrated data were established, involving eight miRNAs and 76 TF-targeting hub genes. Ultimately, 17 SNPs in miRNA-mediated gene networks were identified. We screened potential immune-related genes in CHD and constructed miRNA-mRNA-TF and SNP-miRNA networks, which not only provide inspired insights into the occurrence and the molecular mechanisms of CHD but also lay a foundation for targeting potential biomarkers using immunotherapy and for understanding the molecular mechanisms of CHD.

Abstract Background Despite deeper understanding of the genetic landscape of acute myeloid leukemia (AML), the improvement of survival is still a great challenge. STK10 is overexpressed in several cancers with functions varying according to cancer types. But the functions of STK10 in AML has never been reported. Methods We analyzed the expression, prognosis and potential functions of STK10 utilizing public web servers. Metascape and the String database were used for functional and protein–protein interaction analyses. Results We found STK10 was enriched in blood & immune cells and overexpressed in AML. High STK10 expression was associated with poor overall survival, which was also identified in the subgroups of patients ≤ 60 years old and patients with non-high-risk cytogenetics. We demonstrated genes associated with STK10 were enriched in blood, spleen and bone marrow, influencing the immune function and biological process of AML. ITGB2 and ITGAM might directly interact with STK10 and were associated with poor prognosis. Besides, STK10 was associated with the infiltration of immune cells and immune checkpoints, like HLA-E, CD274 and GAL-9. Conclusions The present study was the original description of STK10 in AML and set the stage for developing STK10 as a new prognostic marker or therapeutic target for AML.

Drought is one of the most significant limiting factors affecting plant growth and development on the Qinghai–Tibet Plateau (QTP). Mining the drought-tolerant genes of the endemic perennial grass of the QTP, Siberian wildrye (Elymus sibiricus), is of great significance to creating new drought-resistant varieties which can be used in the development of grassland livestock and restoring natural grassland projects in the QTP. To investigate the transcriptomic responsiveness of E. sibiricus to drought stress, PEG-induced short- and long-term drought stress was applied to two Siberian wildrye genotypes (drought-tolerant and drought-sensitive accessions), followed by third- and second-generation transcriptome sequencing analysis. A total of 40,708 isoforms were detected, of which 10,659 differentially expressed genes (DEGs) were common to both genotypes. There were 2107 and 2498 unique DEGs in the drought-tolerant and drought-sensitive genotypes, respectively. Additionally, 2798 and 1850 DEGs were identified in the drought-tolerant genotype only under short- and long-term conditions, respectively. DEGs numbering 1641 and 1330 were identified in the drought-sensitive genotype only under short- and long-term conditions, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that all the DEGs responding to drought stress in E. sibiricus were mainly associated with the mitogen-activated protein kinase (MAKP) signaling pathway, plant hormone signal transduction, the linoleic acid metabolism pathway, the ribosome pathway, and plant circadian rhythms. In addition, Nitrate transporter 1/Peptide transporter family protein 3.1 (NPF3.1) and Auxin/Indole-3-Acetic Acid (Aux/IAA) family protein 31(IAA31) also played an important role in helping E. sibiricus resist drought. This study used transcriptomics to investigate how E. sibiricus responds to drought stress, and may provide genetic resources and references for research into the molecular mechanisms of drought resistance in native perennial grasses and for breeding drought-tolerant varieties.

Aim:Twin studies allow for the investigation of genetic and environmental influences on human brain development. The generalizability of their findings depends on the developmental similarity between twins and singletons. This study aimed to evaluate the structural and functional differences in a cohort of preterm-born twins and singletons at term-equivalent age.Materials and Methods:Eighteen twins and forty-seven singletons were included and scanned at the term-equivalent age. Brain volumes from 3D T1-weighted images, quantitative metrics and structural connectivity from diffusion tensor imaging, and low-frequency brain activity and functional connectivity from resting-state functional MRI (rs-fMRI) were obtained from these neonates.Results:We found no significant volumetric differences after multiple comparison correction. The diffusivity values in the cingulum cingular part, cingulate gyrus, lateral fronto-orbital gyrus, gyrus rectus, as well as medial fronto-orbital gyrus were significantly higher in the twin group than in the singleton group. Structural connectivity analysis showed higher transitivity in the twin group compared to the singletons, indicating increased local connectivity. For rs-fMRI, the twin group showed greater fractional amplitude of low-frequency fluctuation (fALFF) values in the salience network and several fronto-temporal regions compared with the singleton group. It is worth noting that we found differences both in structural and functional measurements (MD and fALFF) in the prefrontal and cingulate cortex.Conclusion:The structural and functional differences collectively indicated that preterm-born twins may have delayed brain development compared with gestational age-matched singletons at term-equivalent age, which may be related to perinatal-neonatal problems.

Quinones and humus are ubiquitous in the biosphere and play an important role in the anaerobic biodegradation and biotransformation of organic acids, poisonous compounds as well as inorganic compounds. The impact of humic model compound, anthraquinone-2, 6-disulfonate (AQDS) on anaerobic phenol and p-cresol degradation were studied. Four methanogenic AQDS-free phenol and p-cresol enrichments and two phenol-AQDS enrichments were obtained using two sludges with potential biodegradability of phenol and cresol isomers as inoculum. 16S rRNA gene-cloning analysis combined with fluorescence in situ hybridization revealed that syntrophic aromatic compound degrading bacterium Syntrophorhabdus aromaticivorans was dominant in four AQDS-free enrichments, whereas phenol degrading Cryptanaerobacter phenolicus was dominant in two phenol-AQDS enrichments. Neither co-culture of S. aromaticivorans with Methanospirillum hungatei nor two phenol-AQDS enrichments could metabolize phenol using AQDS as the terminal electron acceptor. Further degradation experiments suggested that C. phenolicus related microbes in two phenol-AQDS enrichments were responsible for the conversion of phenol to benzoate, and benzoate was further degraded by benzoate degraders of Syntrophus aciditrophicus or Sporotomaculum syntrophicum to acetate. HIGHLIGHTS Anaerobic degradation of phenol and p-cresol were faster than o- and m-cresols.; 2 mM AQDS mitigated phenol and completely inhibited p-cresol degradation.; The dominant bacteria in AQDS-free and phenol-AQDS enrichments were different.; Neither S. aromaticivorans nor C. phenolicus affinities could use AQDS as TEA.; The characteristic of key phenol degraders in phenol-AQDS enrichments was described.;

Brain development from 1 to 6 years of age anchors a wide range of functional capabilities and carries early signs of neurodevelopmental disorders. However, quantitative models for depicting brain morphology changes and making individualized inferences are lacking, preventing the identification of early brain atypicality during this period. With a sample size of 285, we characterized the age dependence of the cortical thickness and subcortical volume in neurologically normal children and constructed quantitative growth charts of all brain regions for preschool children. While the cortical thickness of most brain regions decreased with age, the entorhinal and parahippocampal regions displayed an inverted-U shape of age dependence. Compared to the cortical thickness, the normalized volume of subcortical regions exhibited more divergent trends, with some regions increasing, some decreasing, and some displaying inverted-U-shaped trends. The growth curve models for all brain regions demonstrated utilities in identifying brain atypicality. The percentile measures derived from the growth curves facilitate the identification of children with developmental speech and language disorders with an accuracy of 0.875 (area under the receiver operating characteristic curve: 0.943). Our results fill the knowledge gap in brain morphometrics in a critical development period and provide an avenue for individualized brain developmental status evaluation with demonstrated sensitivity. The brain growth charts are shared with the public (http://phi-group.top/resources.html).

Collaborative filtering (CF) is the most classical method for recommender system, but it is usually suffered from limited performance by the sparseness of user-to-item rating data. Recently, due to the powerful learning feature representation ability, deep learning components are used to leverage auxiliary information to assist recommendation. However, most existing models based on deep learning are incomplete so that merely extracting the item latent representation and ignoring the user parts. Besides, different data are not chosen from current models. This paper proposes a novel probability framework, named as joint matrix factorization (JMF). There are three components in JMF. Firstly, the modified multilayer crossing version of the factorization machine (MFM) is designed to extract the user latent factors based on user behavior information. Moreover, MFM is a general method which can be used to accomplish many tasks in terms of machine learning. Secondly, a modification of Long Short-Term Memory (LSTM), named as bidirectional LSTM (BLSTM), is used to extract the item latent factors of a document sequence from both front and back directions. Finally, we tightly integrate BLSTM and MFM into probabilistic matrix factorization (PMF) to form JMF. Compared with the classical matrix factorization and other integration models, JMF extracts document data as well as user behavioral data as item vectors and user vectors. Extensive experiments on five real-world datasets show the proposed model has better performance compared with the state-of-the-art recommendation methods.

This study applies Gravity Recovery and Climate Experiment (GRACE) data and the WaterGAP (Water Global Analysis and Prognosis) Global Hydrology Model (WGHM) to investigate the influence of the Bui reservoir operation on water storage variation within the Volta River Basin (VRB). Variation in groundwater storage anomalies (GWSA) was estimated by combining GRACE-derived terrestrial water storage anomalies (TWSA), radar altimetry records, imagery-derived reservoir (Lake Volta and Bui) surface water storage anomalies (SWSA), and Global Land Data Assimilation System (GLDAS)-simulated soil moisture storage anomalies (SMSA) from 2002 to 2016. Results showed that TWSA increased (1.30 ± 0.23 cm/year) and decreased (−0.82 ± 0.27 cm/year) during 2002–2011 and 2011–2016, respectively, within VRB, matching previous TWSA investigations in this area. It revealed that the multi-year averages of monthly GRACE-derived TWSA changes in 2011–2016 displayed an overall increasing trend, indicating storage increase in regional hydrology; while the Lake Volta water storage changes decreased. The GRACE-minus-WGHM residuals display an increasing trend in VRB water storage during the Bui reservoir impoundment during 2011–2016. The observed trend compares well with the estimated Bui reservoir SWSA, indicating that GRACE solutions can retrieve the true amplitude of large mass changes happening in a concentrated area, though Bui reservoir is much smaller than the resolution of GRACE global solutions. It also revealed that GWSA were almost stable from 2002 to 2006, before increasing and decreasing during 2006–2011 and 2012–2016 with rates of 2.67 ± 0.34 cm/year and −1.80 ± 0.32 cm/year, respectively. The observed trends in the GRACE-derived TWSA and GWSA changes are generally attributed to the hydro-meteorological conditions. This study shows that the effects of strong El-Niño Southern Oscillation events on the GWSA interannual variability within the VRB is short-term, with a lag of 6 months. This study specifically showed that the Bui reservoir operation significantly affects the TWSA changes and provides knowledge on groundwater storage changes within the VRB.

As a major contributor to global mean sea-level rise, the Greenland ice sheet (GrIS) and the patterns of its mass change have attracted wide attention. Based on Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GRACE-FO) gravimetry data, we computed monthly non-cumulative mass change time series of the GrIS, which agree with those from the mass budget method confirming the reliability of GRACE-FO-derived mass change. Over the GrIS, mass was mainly gained in winter, followed by spring. It primarily lost mass in summer, with the percentage of summer mass loss versus the corresponding annual mass loss ranging from 61% to 96%. We report that spring mass loss has become more frequent since 2015, and autumn mass gain occurred more frequently after 2014. By separating mass gain from mass loss at the annual timescale, we find that both the mass gain and mass loss showed a slightly increasing trend during 2003–2020, which might be a response to the ongoing Arctic warming. Summer mass variations highly correlated with the summer North Atlantic Oscillation index are dominated by temperature-associated precipitation and meltwater runoff. This study suggests that long-term observations would be necessary to better understand patterns of the GrIS mass variations in future.

Catalytic membranes, as a combination of heterogeneous advanced oxidation and membrane technology reaction systems, have important application prospects in the treatment of dyes and other organics. In practical applications, it is still challenging to construct catalytic membranes with excellent removal efficiency and fouling mitigation. Herein, molybdenum disulfide-iron oxyhydroxide (MoS2-FeOOH) was fabricated using iron oxide and MoS2 nanoflakes, which were synthesized by the hydrothermal method. Furthermore, by changing the concentration of MoS2-FeOOH, the MoS2-FeOOH/polyethersulfone (PES) composite ultrafiltration membrane was obtained with improved hydrophilicity, permeability, and antifouling capacity. The pure water flux of the composite membrane reached 385.3 L/(m2·h), which was 1.7 times that of the blank PES membrane. Compared with the blank membrane, with the increase of MoS2-FeOOH content, the MoS2-FeOOH/PES composite membranes had better adsorption capacity and catalytic performance, and the membrane with 3.0% MoS2-FeOOH content (M4) could be achieved at a 60.2% methylene blue (MB) degradation rate. In addition, the membrane flux recovery ratio (FRR) of the composite membrane also increased from 25.6% of blank PES membrane (M0) to more than 70% after two cycles of bovine serum albumin (BSA) filtration and hydraulic cleaning. The membrane with 2.25% MoS2-FeOOH content (M3) had the best antifouling performance, with the largest FRR and the smallest irreversible ratio (Rir). Catalytic self-cleaning of the composite membrane M3 recovered 95% of the initial flux with 0.1 mol/L H2O2 cleaning. The MoS2-FeOOH/PES composite membranes with the functions of excellent rejection and antifouling capacity have a good prospect in the treatment of printing and dyeing wastewater composed of soluble dyes.

Abstract On 27–31th August 2018, the 16th International Symposium on Geo-disaster Reduction (ISGdR) has been held in Strasburg, France, focusing on the theme of “Global Strategy for Geo-disaster Reduction”. Through Keynote Lectures, Scientific Session, Poster Session and Field Excursion, this symposium has successfully provided an international platform for scholars, scientists, industrial professionals, practitioners and students to discuss interdisciplinary research and practices in the fields of the reduction of the disasters triggered by geological and geophysical phenomena on the earth.

Blended classroom assessment (CA) has become commonplace in the post-pandemic era, offering advantages but also presenting challenges for English as a Foreign Language (EFL) teachers. These challenges can impact teachers' emotional experiences, distinct from face-to-face or purely online environments. However, scant research exists on how EFL teachers employ emotion regulation (ER) strategies in blended CA within EFL contexts. This qualitative study examines how eight EFL teachers at a university in southwestern China employed ER strategies in blended CA. Drawing on Gross's ER theory, the study identifies ten intrinsic and extrinsic ER strategies, either antecedent-focused or response-focused, utilized by EFL teachers. These strategies helped teachers maintain resilience amidst challenges posed by blended CA, including low completion rates of online learning tasks prior to face-to-face instruction, interaction in blended CA, blended assessment design, managing the workload of blending online and face-to-face assessment, and addressing issues of plagiarism and cheating. The study enriches our understanding of EFL teachers' emotions in blended CA and underscores the significance of ER competence in assessment literacy. Implications for equipping teachers with strategies to enhance their emotional well-being and resilience in blended CA are also discussed.

Satellite-based inverse modeling has the potential to drive aerosol precursor emissions, but its efficacy for improving chemistry transport models (CTMs) remains elusive because of its likely inherent dependence on the error characteristics of a specific CTM used for the inversion. This issue is quantitively assessed here by using three CTMs. We show that SO _2 emissions from global GEOS-Chem adjoint model and OMI SO _2 data, when combined with spatial variation of bottom-up emissions, can largely improve WRF-Chem and WRF-CMAQ forecast of SO _2 and aerosol optical depth (in reference to moderate resolution imaging spectroradiometer data) in China. This suggests that the efficacy of satellite-based inversion of SO _2 emission appears to be high for CTMs that use similar or identical emission inventories. With the advent of geostationary air quality monitoring satellites in next 3 years, this study argues that an era of using top-down approach to rapidly update emission is emerging for regional air quality forecast, especially over Asia having highly varying emissions.

Replacing estimates of C20 from the Gravity Recovery and Climate Experiment (GRACE) monthly gravity field solutions by those from satellite laser ranging (SLR) data and including degree one terms has become a standard procedure for proper science applications in the satellite gravimetry community. Here, we assess the impact of degree one terms, SLR-based C20 and C30 estimates on GRACE-derived polar ice sheet mass variations. We report that degree one terms recommended for GRACE Release 06 (RL06) data have an impact of 2.5 times more than those for GRACE RL05 data on the mass trend estimates over the Greenland and the Antarctic ice sheets. The latest recommended C20 solutions in GRACE Technical Note 14 (TN14) affect the mass trend estimates of ice sheets in absolute value by more than 50%, as compared to those in TN11 and TN07. The SLR-based C30 replacement has some impact on the Antarctic ice sheet mass variations, mainly depending on the length of the study period. This study emphasizes that reliable solutions of low degree spherical harmonics are crucial for accurately deriving ice sheet mass balance from satellite gravimetry.

To investigate aerosol radiative effects, the Sun–Sky Radiometer Observation Network (SONET) has performed long-term observations of columnar atmospheric aerosol properties at 20 distributed stations around China. The aerosol direct radiative forcing (RF) and efficiency (RFE, the rate at which the atmosphere is forced per unit of aerosol optical depth) were estimated using radiative transfer model simulations based on the ground-based observations dating back to 2009. Results of multi-year monthly average RF illustrated that: the dust-dominant aerosol population at arid and semi-arid sites exerted moderate cooling effects (−8.0~−31.2 W/m2) at the top and bottom of atmosphere (TOA and BOA); RF at continental background site was very weak (−0.8~−2.9 W/m2); fine-mode dominant aerosols at urban and suburban sites exerted moderate cooling effects (−9.3~−24.1 W/m2) at TOA but more significant cooling effects (−19.4~−50.6 W/m2) at BOA; RF at coastal sites was comparable with values of urban sites (−5.5~−19.5 W/m2 at TOA, and −15.6~−44.6 W/m2 at BOA), owing to combined influences by marine and urban–industrial aerosols. Differences between RFE at TOA and BOA indicated that coarse-mode dominant aerosols at arid, semi-arid, and continental background sites were less efficient to warm the atmosphere; but fine-mode dominant aerosols at urban, suburban, and coastal sites were shown to be more efficient to heat the atmosphere.

Aerosol optical depth (AOD) derived from satellite remote sensing is widely used to estimate surface PM2.5 (dry mass concentration of particles with an in situ aerodynamic diameter smaller than 2.5 µm) concentrations. In this research, a two-stage spatio-temporal statistical model for estimating daily surface PM2.5 concentrations in the Guanzhong Basin of China is proposed, using 6 km × 6 km AOD data available from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument as the main variable and meteorological factors, land-cover, and population data as auxiliary variables. The model is validated using a cross-validation method. The linear mixed effects (LME) model used in the first stage could be improved by using a geographically weighted regression (GWR) model or the generalized additive model (GAM) in the second stage, and the predictive capability of the GWR model is better than that of GAM. The two-stage spatio-temporal statistical model of LME and GWR successfully captures the temporal and spatial variations. The coefficient of determination (R2), the bias and the root-mean-squared prediction errors (RMSEs) of the model fitting to the two-stage spatio-temporal models of LME and GWR were 0.802, −0.378 µg/m3, and 12.746 µg/m3, respectively, and the model cross-validation results were 0.703, 1.451 µg/m3, and 15.731 µg/m3, respectively. The model prediction maps show that the topography has a strong influence on the spatial distribution of the PM2.5 concentrations in the Guanzhong Basin, and PM2.5 concentrations vary with the seasons. This method can provide reliable PM2.5 predictions to reduce the bias of exposure assessment in air pollution and health research.

Satellite gravimetry data acquired by the Gravity Recovery and Climate Experiment (GRACE) allows to derive the temporal evolution in ice mass for both the Antarctic Ice Sheet (AIS) and the Greenland Ice Sheet (GIS). Various algorithms have been used in a wide range of studies to generate Gravimetric Mass Balance (GMB) products. Results from different studies may be affected by substantial differences in the processing, including the applied algorithm, the utilised background models and the time period under consideration. This study gives a detailed description of an assessment of the performance of GMB algorithms using actual GRACE monthly solutions for a prescribed period as well as synthetic data sets. The inter-comparison exercise was conducted in the scope of the European Space Agency’s Climate Change Initiative (CCI) project for the AIS and GIS, and was, for the first time, open to everyone. GMB products generated by different groups could be evaluated and directly compared against each other. For the period from 2003-02 to 2013-12, estimated linear trends in ice mass vary between −99 Gt/yr and −108 Gt/yr for the AIS and between −252 Gt/yr and −274 Gt/yr for the GIS, respectively. The spread between the solutions is larger if smaller drainage basins or gridded GMB products are considered. Finally, findings from the exercise formed the basis to select the algorithms used for the GMB product generation within the AIS and GIS CCI project.

The Danjiangkou Reservoir (DJKR) is the freshwater source for the Middle Route of the South-to-North Water Diversion Project in China, and its water level and storage changes are important for water resource management. To maximize the potential capacity of the Gravity Recovery and Climate Experiment (GRACE) mission, an improved Lagrange multiplier method (ILMM) is first proposed to detect terrestrial water storage anomalies (TWSA) in the small-scale basin (DJKR). Moreover, for the first time, water diversion fingerprints are proposed to analyze the spatiotemporal pattern of the TWSA in the DJKR. The results indicate that the increased water level and storage signals due to the DJKR impoundment in 2014 can be effectively detected by using the ILMM, and they agree well with the results from altimetry and in situ data. Additionally, the water diversion fingerprints due to the DJKR impoundment are inferred, and describe the progression of spatiotemporal variability in water storage. The results show that water storage decreased in the upper Hanjiang River and increased in the DJKR as well as to the east of it during the period 2013−2015. Our research provides a scientific decision-making basis for monitoring the water resources of the DJKR and managing the South-to-North Water Diversion Project.

A thorough understanding of aerosol optical properties and their spatio-temporal variability are required to accurately evaluate aerosol effects in the climate system. In this study, a multi-year study of aerosol optical and microphysical properties was firstly performed in Xi’an based on three years of sun photometer remote sensing measurements from 2012 to 2015. The multi-year average of aerosol optical depth (AOD) at 440 nm was about 0.88 ± 0.24 (mean ± SD), while the averaged Ångström Exponent (AE) between 440 and 870 nm was 1.02 ± 0.15. The mean value of single scattering albedo (SSA) was around 0.89 ± 0.03. Aerosol optical depth and AE showed different seasonal variation patterns. Aerosol optical depth was slightly higher in winter (0.99 ± 0.36) than in other seasons (~0.85 ± 0.20), while AE showed its minimum in spring (0.85 ± 0.05) due to the impact of dust episodes. The seasonal variations of volume particle size distribution, spectral refractive index, SSA, and asymmetry factor were also analyzed to characterize aerosols over this region. Based on the aerosol products derived from sun photometer measurements, the classification of aerosol types was also conducted using two different methods in this region. Results show that the dominant aerosol types are absorbers in all seasons, especially in winter, demonstrating the strong absorptivity of aerosols in Xi’an.

Long-term (1973 to 2010) trends in visibility at Chengdu, China were investigated using meteorological data from the U.S. National Climatic Data Center. The visual range exhibited a declining trend before 1982, a slight increase between 1983 and 1995, a sharp decrease between 1996 and 2005, and some improvements after 2006. The trends in visibility were generally consistent with the economic development and implementation of pollution controls in China. Intensive PM2.5 measurements were conducted from 2009 to 2010 to determine the causes of visibility degradation. An analysis based on a modification of the IMPROVE approach indicated that PM2.5 ammonium bisulfate contributed 27.7% to the light extinction coefficient (bext ); this was followed by organic mass (21.7%), moisture (20.6%), and ammonium nitrate (16.3%). Contributions from elemental carbon (9.4%) and soil dust (4.3%) were relatively minor. Anthropogenic aerosol components (sulfate, nitrate, and elemental carbon) and moisture at the surface also were important determinants of the aerosol optical depth (AOD) at 550 nm, and the spatial distributions of both bext and AOD were strongly affected by regional topography. A Positive Matrix Factorization receptor model suggested that coal combustion was the largest contributor to PM2.5 mass (42.3%) and the dry-air light-scattering coefficient (47.7%); this was followed by vehicular emissions (23.4% and 20.5%, respectively), industrial emissions (14.9% and 18.8%), biomass burning (12.8% and 11.9%), and fugitive dust (6.6% and 1.1%). Our observations provide a scientific basis for improving visibility in this area.

Drone delivery is expected to improve operations by enhancing flexibility and reducing congestion effects induced by lastmile deliveries. With rising digitalization and urbanization, however, flight routing of drones is constantly grappling with the challenge of uncertain demand. In this study, an opportunity-constrained model that considered both the endurance and payload capacity of drones and stochastic customer demand was developed to solve the drone delivery planning problem for E-commerce in urban areas. Considering the challenging solvability of the model, historical customer demand data were leveraged to linearly transform opportunity constraints with unknown true distribution. In addition, a constructive heuristic algorithm was used to solve the established opportunity-constrained model, and an effective strategy was developed to generate the quality of initial flight paths. The experimental results based on various scales of classic cases demonstrate that an effective drone delivery route scheme can be generated by the proposed heuristic algorithm compared to traditional savings algorithm, allowing drones to complete tasks in shorter flight distances at the same payload rate, thus reducing overall costs. Compared to deterministic models, more robust flight path schemes for addressing continuously changing customer demands can be obtained. The model and insights in this study could be used as a reference for the application of drone delivery in urban areas to promote logistics efficiency. [ABSTRACT FROM AUTHOR]

Dockless bicycle-sharing system substantially impacts the present docked bicycle-sharing usage in the urban transportation system. This study explores such effects using usage data of docked bicycle-sharing systems in Xi’an before and after launching the dockless bicycle-sharing system. The influence period is divided into the no-influence stage, transition stage, and stabilization stage. The hotspot analysis method is employed to identify the most influenced areas. The geographically weighted regression model is then revised to determine the response of socioeconomic factors considering the launches of the dockless bicycle-sharing system. The results reveal that the critical impact of the dockless bicycle-sharing system on the docked system. Specifically, the weekly usage share of docked bicycle-sharing declined ranged from 0.51 % to 41.4 % in transition stage. Furthermore, population density, job density, per capita income, and per capita GDP are identified as the key contributing factors based on spatial analysis, where for each 1 % increase in the four indicators, docked bicycle-sharing system’s usage decreases by 1.014 %, 1.182 %, 2.021 %, and 0.904 %, respectively.

Plant Homeo Domain (PHD) proteins are involved in diverse biological processes during plant growth. However, the regulation of PHD genes on rice cold stress response remains largely unknown. Here, we reported that PHD17 negatively regulated cold tolerance in rice seedlings as a cleavage target of miR1320. PHD17 expression was greatly induced by cold stress, and was down-regulated by miR1320 overexpression and up-regulated by miR1320 knockdown. Through 5′RACE and dual luciferase assays, we found that miR1320 targeted and cleaved the 3′UTR region of PHD17. PHD17 was a nuclear-localized protein and acted as a transcriptional activator in yeast. PHD17 overexpression reduced cold tolerance of rice seedlings, while knockout of PHD17 increased cold tolerance, partially via the CBF cold signaling. By combining transcriptomic and physiological analyses, we demonstrated that PHD17 modulated ROS homeostasis and flavonoid accumulation under cold stress. K-means clustering analysis revealed that differentially expressed genes in PHD17 transgenic lines were significantly enriched in the jasmonic acid (JA) biosynthesis pathway, and expression of JA biosynthesis and signaling genes was verified to be affected by PHD17. Cold stress tests applied with MeJA or IBU (JA synthesis inhibitor) further suggested the involvement of PHD17 in JA-mediated cold signaling. Taken together, our results suggest that PHD17 acts downstream of miR1320 and negatively regulates cold tolerance of rice seedlings through JA-mediated signaling pathway.

Abstract This paper investigates the application of Fourier image enhancement combined with Convolutional Neural Networks (CNNs) for detecting cracks in concrete structures. Fourier enhancement is used to preprocess crack images, improving their clarity and reducing noise, which in turn enhances the performance of the CNN in accurately classifying cracks. The results demonstrate that this combination improves the classification accuracy, with the enhanced images achieving a higher accuracy compared to non-enhanced images. Additionally, the study examines the effects of this preprocessing on CNN training time. However, accuracy varies depending on the dataset used, with one dataset reaching a maximum accuracy of 95% after enhancement. These findings highlight the potential of using frequency-domain image enhancement techniques in conjunction with deep learning models for structural health monitoring.