Modeling Studies Research Articles

Microplastics and Cancer Progression: A Comparative Study of 2D and 3D Gastric Cancer Models Using ISO-Compliant Protocols

Microplastics have emerged as a significant global environmental concern, yet the absence of standardized protocols for assessing their toxicity remains a challenge. To address this gap, we applied the ISO 10993-5:2009 and ISO 10993-12:2012 standards for the first time to evaluate the effects of microplastics on cancer progression. Our study utilized both two-dimensional and three-dimensional models of gastric cancer to investigate the potential role of microplastics in promoting cancer growth. The MTT assay results revealed that the highest concentrations of polyethylene microplastics (PE-MPs) and polypropylene microplastics (PP-MPs) enhanced the proliferation of gastric cancer cells at both 24 and 72 hours. After 24 hours, AGS cells treated with PE-MPs and PP-MPs exhibited increased viability, reaching 116.08% ± 15.55 and 118.78% ± 13.96, respectively; however, this increase was not statistically significant. In contrast, after 72 hours, AGS cells showed significantly enhanced growth, with viability reaching 122.37% ± 9.28 for PE-MPs and 131.51% ± 3.05 for PP-MPs (p < 0.001). In the three-dimensional model, live/dead staining results after seven days indicated that spheroids exposed to microplastics demonstrated greater cell survival compared to the control group. The percentage area growth of spheroids was 7.93% ± 1.5 for the control, 13.93% ± 4.85 for PE-MPs, and 19.59% ± 1.61 for PP-MPs, with the increase in PP-MPs being statistically significant (p < 0.05). Additionally, microplastics did not penetrate the three-dimensional gastric cancer within seven days. This research highlights the potential impact of microplastics on cancer development and introduces a novel methodological approach.

Therapeutic potential of mesenchymal stem cell-derived extracellular vesicles: A focus on inflammatory bowel disease.

Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) have emerged as key regulators of intercellular communication, orchestrating essential biological processes by delivering bioactive cargoes to target cells. Available evidence suggests that MSC-EVs can mimic the functions of their parental cells, exhibiting immunomodulatory, pro-regenerative, anti-apoptotic, and antifibrotic properties. Consequently, MSC-EVs represent a cell-free therapeutic option for patients with inflammatory bowel disease (IBD), overcoming the limitations associated with cell replacement therapy, including their non-immunogenic nature, lower risk of tumourigenicity, cargo specificity and ease of manipulation and storage. This review aims to provide a comprehensive examination of the therapeutic efficacy of MSC-EVs in IBD, with a focus on their mechanisms of action and potential impact on treatment outcomes. We examine the advantages of MSC-EVs over traditional therapies, discuss methods for their isolation and characterisation, and present mechanistic insights into their therapeutic effects through transcriptomic, proteomic and lipidomic analyses of MSC-EV cargoes. We also discuss available preclinical studies demonstrating that MSC-EVs reduce inflammation, promote tissue repair and restore intestinal homeostasis in IBD models, and compare these findings with those of clinical trials. Finally, we highlight the potential of MSC-EVs as a novel therapy for IBD and identify challenges and opportunities associated with their translation into clinical practice. The source of mesenchymal stem cells (MSCs) strongly influences the composition and function of MSC-derived extracellular vesicles (EVs), affecting their therapeutic potential. Adipose-derived MSC-EVs, known for their immunoregulatory properties and ease of isolation, show promise as a treatment for inflammatory bowel disease (IBD). MicroRNAs are consistently present in MSC-EVs across cell types and are involved in pathways that are dysregulated in IBD, making them potential therapeutic agents. For example, miR-let-7a is associated with inhibition of apoptosis, miR-100 supports cell survival, miR-125b helps suppress pro-inflammatory cytokines and miR-20 promotes anti-inflammatory M2 macrophage polarisation. Preclinical studies in IBD models have shown that MSC-EVs reduce intestinal inflammation by suppressing pro-inflammatory mediators (e.g., TNF-α, IL-1β, IL-6) and increasing anti-inflammatory factors (e.g., IL-4, IL-10). They also promote mucosal healing and strengthen the integrity of the gut barrier, suggesting their potential to address IBD pathology.

Exploring the sustainable future of social sports organizations: A comparative study of governance models in China, Japan, and South Korea

Exploring the sustainable future of social sports organizations: A comparative study of governance models in China, Japan, and South Korea

Electric Vehicle Sentiment Analysis Using Large Language Models

Sentiment analysis is a technique used to understand the public’s opinion towards an event, product, or organization. For example, sentiment analysis can be used to understand positive or negative opinions or attitudes towards electric vehicle (EV) brands. This provides companies with valuable insight into the public’s opinion of their products and brands. In the field of natural language processing (NLP), transformer models have shown great performance compared to traditional machine learning algorithms. However, these models have not been explored extensively in the EV domain. EV companies are becoming significant competitors in the automotive industry and are projected to cover up to 30% of the United States light vehicle market by 2030 In this study, we present a comparative study of large language models (LLMs) including bidirectional encoder representations from transformers (BERT), robustly optimised BERT (RoBERTa), and a generalised autoregressive pre-training method (XLNet) using Lucid Motors and Tesla Motors YouTube datasets. Results evidenced that LLMs like BERT and her variants are off-the-shelf algorithms for sentiment analysis, specifically when fine-tuned. Furthermore, our findings present the need for domain adaptation whilst utilizing LLMs. Finally, the experimental results showed that RoBERTa achieved consistent performance across the EV datasets with an F1 score of at least 92%.

Calcineurin/NFAT inhibitors maintain cognition in a preclinical prevention study in an aging canine model of Alzheimer disease

Calcineurin/NFAT inhibitors maintain cognition in a preclinical prevention study in an aging canine model of Alzheimer disease

Rain event detection and magnitude estimation during Indian summer monsoon: Comprehensive assessment of gridded precipitation datasets across hydroclimatically diverse regions

Accurate precipitation estimates are quintessential for hydrologic modeling and climate studies. Different gridded precipitation products are available in any region, and selecting the best one is essential for hydroclimatic modeling and analysis. In the current study, observation- (APHRODITE), reanalysis- (IMDAA, ERA5-Land, PGF), satellite-based (IMERG, CHIRPS, PERSIANN-CDR), and hybrid (MSWEP) gridded precipitation products with different spatial and temporal resolutions are evaluated using several continuous, categorical, graphical, and interval-based performance measures towards detecting Indian Summer Monsoon Rainfall (ISMR) events and estimating their magnitudes for the subcontinent of India, considering IMD gauge-based gridded as reference product. We confine our analysis to the monsoon season (i.e., June to September), the principal rainy season in the Indian sub-continent. The dearth of data and limited rain gauge-based observations from non-uniform sparse monitoring networks across India necessitated grid-to-grid comparative evaluations instead of point-to-grid assessments. We propose a new ranking framework to determine the suitability of precipitation datasets for twenty-seven hydroclimatic regions comprising homogeneous rainfall zones, Köppen-Geiger climate zones, and major river basins. Results from the comprehensive evaluation suggest that (1) APHRODITE, MSWEP, and ERA5-Land best approximate precipitation event occurrences across India, (2) MSWEP and ERA5-Land are most suitable (highest rank) alternatives at the regional level, while APHRODITE is found to be next suitable dataset owing to its persistent dry bias, (3) performances of CHIRPS and IMERG have reasonably lower rank score across India, (4) close agreement of examined datasets is noted over semi-arid and sub-humid regions (e.g., peninsular and central India), whereas ERA5-Land, IMDAA, and APHRODITE fail to detect and reproduce the intensity of the events along the west coast and northeastern India, (5) PGF and PERSIANN-CDR are the least situated datasets. Moreover, the present study provides a unique and innovative perspective to characterise the precipitation over a vast topographic, ecologic, and climatic gradient region like India.

Design, Synthesis, QSAR Studies, and Molecular Modeling of Some Novel Bis Methyl 2-[3-(benzo[d]thiazol-2-yl)-2-terephthaloyl-bis-4-oxo-thiazolidin- 5-ylidene]acetates and Screening of their Antioxidant and Enzyme Inhibition Properties.

Benzothiazolamine-based bisthiourea precursors were prepared in good yields. These bisthiourea derivatives were cyclized into symmetrical Bis Methyl 2-[3-(benzothiazol- 2-yl)-2-terephthaloyl-bis-4-oxo-thiazolidin-5-ylidene]acetates, by their condensation with (DMAD) dimethyl but-2-meditate in the presence of dry methanol. All these compounds were evaluated for their biological applications. Antioxidant activities were performed by adopting a DPPH radical assay, and an in vitro enzyme inhibition assay was performed to investigate their enzyme inhibitory potential against butyrylcholinesterase (BChE) and acetylcholinesterase (AChE). Molecular modeling and QSAR studies were performed to monitor the binding propensity of imidathiazolidinone derivatives with enzymes and DNA. Also, electronic and steric descriptors were calculated to determine the effect of structure on the activity of imidathiazolidinone derivatives. The characterization of all the synthesized compounds was done by their physical data, FT-IR, NMR and elemental analysis.

Refined transmission line ice-cover prediction model and optimization study

Abstract This study aims to develop a fine-grained transmission line ice-cover prediction model and conduct an optimization study. Ice cover is one of the important factors leading to transmission line accidents, so accurately predicting the ice cover of transmission lines is crucial to ensure the safe operation of power grids. In this paper, an efficient ice-cover prediction model is constructed based on advanced machine learning algorithms and optimization methods and is validated and optimized with a large amount of experimental data. The results show that the proposed model has high accuracy and prediction capability in ice cover prediction, which provides important support for the safe operation of transmission lines.

Real-time modeling of transient crustal deformation through the quantification of uncertainty deduced from GNSS data

We propose a new method for real-time uncertainty monitoring of earthquake and volcano source models using data from the global navigation satellite system (GNSS) and explore its application concerning observation station placement. The Geospatial Information Authority of Japan operates two main types of GNSS earth observation network system (GEONET) coordinates for crustal deformation monitoring on different time scales: post-processing analysis values and real-time GEONET analysis system for rapid deformation monitoring (REGARD). REGARD uses the Markov Chain Monte Carlo (MCMC) method termed real-time automatic uncertainty estimation of a coseismic single rectangular model using GNSS data (RUNE) for single rectangular fault model estimation to handle uncertainty. Thus far, no GNSS monitoring system can automatically detect transient crustal deformation events, such as volcanic activity and earthquake swarms, on timescales of a day or less. We extended RUNE and developed a core program for a new monitoring system for earthquake and volcanic source models and their uncertainties. Our program achieved automatic and stable MCMC utilization for rectangular fault, dike, Mogi, and spheroid models by increasing the computational speed, improving search efficiency, and adjusting hyperparameters. The program automatically determines the standard deviation of the likelihood function assuming a normal distribution with weights for each observation station. The calculation time was within 15 s for 1 × 106 samples on a standard 1U server. We assessed the reliability of the developed method using synthetic and observed GNSS data from the 2015 Sakurajima volcanic event. The results were consistent with the assumed model and previous studies and indicated an advantage in automatically quantifying uncertainty in a short computation time. Based on MCMC samples, we developed a new visualization algorithm to indicate areas on a map in which the number of observation stations should be expanded. We assessed the reliability using data from the 2023 Noto Peninsula earthquake [Mj 6.5]. The results indicate that the algorithm is helpful in studying the placement of stations. The above model extensions and their application are essential to achieve a rapid quantitative understanding of disaster events near urban areas and for utilizing this information in emergency response activities.Graphical

Antibacterial and anti-biofilm activities of gold-curcumin nanohybrids and its polydopamine form upon photo-sonotherapy of Staphylococcus aureus infected implants: In vitro and animal model studies

Implant-related infections are among the major post-surgery problems, and treatment of these infections is challenging due to the formation of biofilms by microorganisms such as Staphylococcus aureus. Herein, a novel gold-curcumin nanohybrid (GCNH) was synthesized for the first time and characterized. GCNH had a band gap energy of 2.41 eV, a zeta potential of −15 mV, and comprised uniform spherical particles with a mean diameter of 8 ± 2 nm. The biological macromolecule of polydopamine was then coated on GCNH to prepare a gold-curcumin-polydopamine nanohybrid (GCDNH). The nanohybrids were employed as novel dual photo-sonosensitizers for bacterial eradication by near-infrared (NIR) light and ultrasound (US) irradiations. GCNH and GCDNH represented photothermal conversion efficiencies of 26 and 32 %, respectively, and GCDNH represented a hemolysis rate of 2.3 % under both near-infrared (NIR) light and ultrasound (US) irradiations. NIR light and US irradiations (photo-sonotherapy) of Staphylococcus aureus using GCDNH depicted anti-bacterial and anti-biofilm efficiencies of 98 and 99 %, respectively, in synergistic manners, which are higher or as high as other sensitizers reported previously. The mechanism of photo-sonotherapy was related to generation of high levels of reactive oxygen species (ROS), and protein and nucleic acid leakages. In an in vivo infection model, NIR light and US irradiations annihilated Staphylococcus aureus on GCDNH-covered implants with high efficiency, without causing damage to normal tissues.

Non-optimal temperature-attributable mortality and morbidity burden by cause, age and sex under climate and population change scenarios: a nationwide modelling study in Japan

Future temperature effects on mortality and morbidity may differ. However, studies comparing projected future temperature-attributable mortality and morbidity in the same setting are limited. Moreover, these studies did not consider future population change, human adaptation, and the variations in subpopulation susceptibility. Thus, we simultaneously projected the temperature-related mortality and morbidity by cause, age, and sex under population change, and human adaptation scenarios in Japan, a super-ageing society. We used daily mean temperatures, mortality, and emergency ambulance dispatch (a sensitive indicator for morbidity) in 47 prefectures of Japan from 2015 to 2019 as the reference for future projections. Future mortality and morbidity were generated at prefecture level using four shared socioeconomic pathway (SSP) scenarios considering population changes. We calculated future temperature-related mortality and morbidity by combining baseline values with future temperatures and existing temperature risk functions by cause (all-cause, circulatory, respiratory), age (<65 years, ≥65 years), and sex under various climate change and SSP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Full human adaptation was simulated based on empirical evidence using a fixed percentile of minimum mortality or morbidity temperature (MMT), while no adaptation was simulated with a fixed absolute MMT. A future temporal decline in mortality burden attributable to non-optimal temperatures was observed, driven by greater cold-related deaths than heat-related deaths. In contrast, temperature-related morbidity increased over time, which was primarily driven by heat. In the 2050s and 2090s, under a moderate scenario, there are 83.69 (95% empirical confidence interval [eCI] 38.32-124.97) and 77.31 (95% eCI 36.84-114.47) all-cause deaths per 100,000 population, while there are 345.07 (95% eCI 258.31-438.66) and 379.62 (95% eCI 271.45-509.05) all-cause morbidity associated with non-optimal temperatures. These trends were largely consistent across causes, age, and sex groups. Future heat-attributable health burden is projected to increase substantially, with spatiotemporal variations and is particularly pronounced among individuals ≥65y and males. Full human adaptation could yield a decreasing temperature-attributable mortality and morbidity in line with a decreasing population. Our findings could support the development of targeted mitigation and adaptation strategies to address future heat-related impacts effectively. This includes improved healthcare allocations for ambulance dispatch and hospital preventive measures during heat periods, particularly custom-tailored to address specific health outcomes and vulnerable subpopulations. Japan Science and Technology Agency and Environmental Restoration and Conservation Agency and Ministry of the Environment of Japan.

Impact of the 100 days mission for vaccines on COVID-19: a mathematical modelling study

The COVID-19 pandemic has underscored the beneficial impact of vaccines. It also highlighted the need for future investments to expedite an equitable vaccine distribution. The 100 Days Mission aims to develop and make available a new vaccine against a future pathogen with pandemic potential within 100 days of that pathogen threat being recognised. We assessed the value of this mission by estimating the impact that it could have had on the COVID-19 pandemic. Using a previously published model of SARS-CoV-2 transmission dynamics fitted to excess mortality during the COVID-19 pandemic, we projected scenarios for three different investment strategies: rapid development and manufacture of a vaccine, increasing manufacturing capacity to eliminate supply constraints, and strengthening health systems to enable faster vaccine roll-outs and global equity. Each scenario was compared against the observed COVID-19 pandemic to estimate the public health and health-economic impacts of each scenario. If countries implemented non-pharmaceutical interventions (NPIs) as they did historically, the 100 Days Mission could have averted an estimated 8·33 million deaths (95% credible interval [CrI] 7·70-8·68) globally, mostly in lower-middle income countries. This corresponds to a monetary saving of US$14·35 trillion (95% CrI 12·96-17·87) based on the value of statistical life-years saved. Investment in manufacturing and health systems further increases deaths averted to 11·01 million (95% CrI 10·60-11·49). Under an alternative scenario whereby NPIs are lifted earlier on the basis of vaccine coverage, the 100 Days Mission alone could have reduced restrictions by 12 600 days (95% CrI 12 300-13 100) globally while still averting 5·76 million deaths (95% CrI 4·91-6·81). Our findings show the value of the 100 Days Mission and how these can be amplified through improvements in manufacturing and health systems equity. However, these investments must be enhanced by prioritising a more equitable global vaccine distribution. Schmidt Science Fellowship in partnership with the Rhodes Trust, WHO, UK Medical Research Council, Coalition for Epidemic Preparedness Innovations.

Exploration of 1,3,5-trisubstituted pyrazoline derivatives as human carbonic anhydrase inhibitors: Synthesis, biological evaluation and in silico studies

The human carbonic anhydrase (hCA) IX and XII isoforms are overexpressed in hypoxic conditions, contributing to cancer. Lack of isoform selectivity has been one of the main challenges associated with the existing drugs targeting hCAs. Hence, the development of alternative approaches, such as tail approach to develop more selective hCA IX and XII inhibitors is need of the hour. In the present work, we designed and synthesized 24 new 1,3.5-trisubstituted-pyrazoline derivatives with diverse substitutions. The synthesized analogs were evaluated for their hCA inhibitory activities against hCA I, II, IX, and XII isoforms. Among the tested compounds, derivative 8 displayed good inhibitory activity against hCA IX (Ki = 331 nM) and XII (Ki = 96.7 nM). In addition, 9a-g also exhibited some inhibitory activities against hCA IX and XII, with Kis ranging from 574 to 799 nM and 137–369 nM, respectively. Molecular modelling studies of compound 8 displayed metal coordination with zinc ion and hydrophobic, hydrophilic interactions with adjacent amino acid residues, and maintained stable interactions throughout 100 ns. In addition, ADMET studies demonstrated that compound 8 obeyed the Lipinski's rule of five and was found to be druggable and non-toxic. Hence, compound 8 was identified as potential lead for further development.

VOF-based modeling study of surface oscillation behavior and gas–liquid stirring dynamics in the bottom-blown reactors

Gas bottom-blown reactors are widely employed in the chemical, metallurgical, and biochemical industries due to their superior mixing capabilities. This study numerically investigates the gas–liquid flow hydrodynamics and bubble dynamics in a bottom-blown system with a circular boundary using the volume of fluid approach. Following the experimental validation of the mathematical model, the study evaluates the effects of gas flow rates, liquid heights, and fluid medium properties on both the dynamics of the bubble swarm and the mixing characteristics of the flow field. The results indicate that: (1) Rising bubbles disturb the fluid, generating numerous vortices that facilitate momentum transfer for effective gas stirring; (2) The height of the liquid surface oscillation during the bottom-blown process exhibits significant temporal variation, with the peak showing clear lateral swings; (3) Due to the nonlinear interactions involving bubble coalescence and breakup during their ascent, along with constructive and destructive interference between liquid surface waves, the liquid surface can exhibit violent fluctuations at certain moments; (4) Bubble size and aspect ratio significantly influence liquid surface oscillations; (5) The bubble rising path displays instability due to vortex shedding, with some vortices forming at locations where the bubble shape changes abruptly. A bubble velocity prediction equation is proposed: uc=σ5.2737Lcρc4.2737/16156μl9.5475.

Insufficient Transparency in Stochasticity Reporting in Large Language Model Studies for Medical Applications in Leading Medical Journals.

Insufficient Transparency in Stochasticity Reporting in Large Language Model Studies for Medical Applications in Leading Medical Journals.

Discovery of a new lead molecule to develop a novel class of human factor XIIa inhibitors.

Factor XIIa (FXIIa) is a plasma serine protease within the contact activation pathway. Inhibiting FXIIa could offer a viable therapeutic approach for achieving effective and safer anticoagulation without the bleeding risks that accompany the use of existing anticoagulants. Therefore, we investigated the anticoagulant properties of an amidine-containing molecule (inhibitor 1) to identify a potential lead molecule for subsequent development of FXIIa inhibitors. Results indicated that inhibitor 1 primarily inhibits human FXIIa with an IC50 value of ~30 µM. The inhibitor demonstrated variable selectivity against thrombin, factor IXa, factor Xa, factor XIa, and activated protein C. Michaelis-Menten kinetics indicated that the molecule is an active site inhibitor of FXIIa. Molecular modeling studies revealed that the molecule recognizes residues His57, Asp189, and Ala190 in FXIIa's active site. The inhibitor selectively and concentration-dependently prolonged the clotting time of human plasma under activated partial thromboplastin time assay conditions. The inhibitor did not exhibit significant cytotoxicity in human HEK293 cells and the in silico pharmacokinetics and toxicology data were comparable to known anticoagulants. This study introduces inhibitor 1 as a lead platform for further development as an anticoagulant to provide a more effective and safer approach to preventing and treating thromboembolic diseases.

The role of economic evaluation in modelling public health and social measures for pandemic policy: a systematic review

BackgroundDynamic transmission models are often used to provide epidemiological guidance for pandemic policy decisions. However, how economic evaluation is typically incorporated into this technique to generate cost-effectiveness estimates of pandemic policy responses has not previously been reviewed.MethodsWe systematically searched the Embase, PubMed and Scopus databases for dynamic epidemiological modelling studies that incorporated economic evaluation of public health and social measures (PHSMs), with no date restrictions, on 7 July 2024.ResultsOf the 2,719 screened studies, 51 met the inclusion criteria. Most studies (n = 42, 82%) modelled SARS-CoV-2. A range of PHSMs were examined, including school closures, testing/screening, social distancing and mask use. Half of the studies utilised an extension of a Susceptible-Exposed-Infectious-Recovered (SEIR) compartmental model. The most common type of economic evaluation was cost-effectiveness analysis (n = 24, 47%), followed by cost-utility analysis (n = 17, 33%) and cost–benefit analysis (n = 17, 33%).ConclusionsEconomic evaluation is infrequently incorporated into dynamic epidemiological modelling studies of PHSMs. The scope of this research should be expanded, given the substantial cost implications of pandemic PHSM policy responses.

Exploring non-hormonal therapies and drug repositioning for endometriosis: insights from mouse model studies

The mainstay of treatment for endometriosis is hormonal therapy, which suppresses ovulation; therefore, patients cannot conceive during treatment. There is a dilemma with ovarian-sparing surgery, known as laparoscopic cystectomy, as it can potentially damage the ovaries. Therefore, there is a need for non-hormonal drug therapies. We addressed these challenges in endometriosis treatment, aiming to maintain ovarian function while achieving effective treatment through basic research. Herein, we present two studies using different mouse models of endometriosis. The first study investigates the effects of a nucleotide-binding oligomerization domain, leucine-rich repeat, and pyrin domain-containing (NLRP) 3 inhibitor in a mouse model of ovarian endometriotic cysts. We confirmed the increased expression of NLRP in ovarian endometriotic cysts compared with that in the uterine endometrium in both patient-derived samples and mouse model lesions. Administering an NLRP3 inhibitor to model mice resulted in lesion reduction. The second study used a peritoneal lesion mouse model to examine bacterial infection in the endometrium and its association with endometriosis development. Using existing databases and patient-derived samples, we identified that Fusobacterium was involved in the development of endometriosis and lesion enlargement when infecting the endometrium in the model. Furthermore, antibiotic treatment led to a reduction in the lesions. These studies highlight the potential of repositioning existing drugs with NLRP3 inhibitory effects or antibiotics as new non-hormonal treatments for endometriosis.

Numerical simulation and mechanistic model study of gas pocket distribution characteristics in a centrifugal impeller

The formation and extension of the gas pocket in the impeller can lead to the rapid deterioration or even failure of the centrifugal pump's two-phase pressurization. It is difficult to directly measure the characteristic parameters of the gas pocket in the high-speed rotating impeller, such as the void fraction, by experimental methods. In this paper, the two-phase performance of the centrifugal pump is studied by numerical simulation and validated by the experiment. The positive pressure gradient at the end of the blade pressure surface is the main reason why the centrifugal pump can boost at high inlet gas volume fraction (IGVF). As the IGVF increases, both the length and thickness of the gas pocket gradually increase. The head coefficient of the pump has an approximately quadratic relationship with the void fraction in the impeller. The mechanism model of the gas pocket flow is established by the force analysis of the gas pocket and its downstream single bubble in the impeller channel. The model can effectively predict the extension position of the gas pocket and the void fraction in the centrifugal impeller and is validated by numerical simulation.

No Evidence of Winter Warming in Eurasia Following Large, Low-Latitude Volcanic Eruptions during the Last Millennium

Abstract We critically reexamine the question of whether volcanic eruptions cause surface warming over Eurasia in winter, in the light of recent modeling studies that have suggested internal variability may overwhelm any forced volcanic response, even for the very largest eruptions during the Common Era. Focusing on the last millennium, we combine model output, instrumental observations, tree-ring records, and ice cores to build a new temperature reconstruction that specifically targets the boreal winter season. We focus on 20 eruptions over the last millennium with volcanic stratospheric sulfur injections (VSSIs) larger than the 1991 Pinatubo eruption. We find that only 7 of these 20 large events are followed by warm surface temperature anomalies over Eurasia in the first posteruption winter. Examining the 13 events that show cold posteruption anomalies, we find no correlation between the amplitude of winter cooling and VSSI mass. We also find no evidence that the North Atlantic Oscillation is correlated with VSSI in winter, a key element of the proposed mechanism through which large, low-latitude eruptions might cause winter warming over Eurasia. Furthermore, by inspecting individual eruptions rather than combining events into a superposed epoch analysis, we are able to reconcile our findings with those of previous studies. Analysis of two additional paleoclimatic datasets corroborates the lack of posteruption Eurasian winter warming. Our findings, covering the entire last millennium, confirm the findings of most recent modeling studies and offer important new evidence that large, low-latitude eruptions are not, in general, followed by significant surface wintertime warming over Eurasia.