Dynamic Changes Research Articles

Optimal design of building envelope towards life cycle performance: Impact of considering dynamic grid emission factors

Building-related carbon emissions in the construction and operation stages account for more than one-third of global energy-related emissions. Optimizing during the early design stage is an effective way to reduce building carbon emissions. However, current studies adopt a constant grid emission factor (GEF) to assess the environmental impacts of buildings while ignoring the dynamic changes of the future electricity mix. This will overestimate the operational carbon emissions of the building in the context of the increasing share of renewable energy in power generation. In this study, a dynamic life cycle assessment model based on dynamic GEF is constructed to evaluate the life cycle environmental impacts of buildings. On this basis, a building optimization design framework considering dynamic GEF is proposed, and the impact of considering future variations of GEF on the optimal design of the building envelope is explored. The study is conducted in three steps. First, dynamically changing GEFs are predicted under the future electricity mix based on scenario analysis. Second, a multi-objective optimization framework is established to minimize the life cycle carbon emissions (LCCE) of the building while optimizing its life cycle costs (LCC) and indoor discomfort hours (IDH). Finally, the proposed optimization framework is applied to a prototype office building in Shanghai, and a comparative analysis is conducted for the optimal schemes between a static and two dynamic scenarios. The result reveals that ignoring future variations will lead to overestimating the operational carbon emissions by 49.0%-64.8%, which in turn will result in an over-insulated design of the envelope (i.e., additional material consumption). In addition, compared to the static scenario, consideration of dynamic GEF results in a 38.7%-51.6% reduction in LCCE, a 5.2%-6.1% reduction in LCC, and a 5.3%-9.5% increase in IDH for the optimal solutions. This research illustrates the importance of considering dynamic GEF in identifying the optimal design parameters and can help decision-makers reasonably choose the optimal schemes during early-stage design.

The spatiotemporal analysis of SARS-CoV-2 transmission in China since the termination of the dynamic zero-COVID policy

China's dynamic zero-COVID policy has effectively curbed the spread of SARS-CoV-2, while inadvertently creating immunity gaps within its population. Subsequent surges in COVID-19 cases linked to various SARS-CoV-2 lineages post-policy termination necessitate a thorough investigation into the epidemiological landscape. This study addresses this issue by analyzing a comprehensive dataset of 39,456 high-quality genomes collected nationwide over an 11-month period since policy termination. Through lineage assignment, phylogenetic analysis, pandemic pattern comparison, phylodynamic reconstruction, and recombination detection, we found that China's post-epidemic period could be divided into three stages, along with dynamic changes in dominant lineages. Geographical clustering of similar lineages implies the importance of cross-border cooperation among neighboring regions. Compared to the USA, UK, and Japan, China exhibits unique trajectories of lineage epidemics, characterized by initial lagging followed by subsequent advancement, indicating the potential influence of diverse prevention and control policies on lineage epidemic patterns. Hong Kong, Shanghai, and Hubei emerge as pivotal nodes in the nationwide spread, marking a shift in the transmission center from east to central regions of China. Although China hasn't experienced significant variant emergence, the detection and validation of the novel recombination event, XCN lineage, underscore the ongoing virus evolution. Overall, this study systematically analyzes the spatiotemporal transmission of SARS-CoV-2 virus in China since the termination of the dynamic zero-COVID policy, offering valuable insights for regional surveillance and evidence-based public health policymaking.

The effect of urban form parameters on annual and diurnal cycles of land surface temperature with 30-meters hourly resolution

Understanding dynamic changes in urban land surface temperature (U-LST) is vital for improving urban thermal environment. Previous studies noted a close association between two/three-dimensional (2D/3D) urban form parameters (UFPs) and U-LST, but divergent conclusions emerged due to study scale and data spatiotemporal resolution. This study investigated the effect of 2D/3D UFPs on multi-temporal (hourly, diurnal, and annual) U-LSTs with 30-m spatial resolution, which is the first exploration of such dynamics at this fine scale. In addition, the influence of local climate zones (LCZs) was considered. Results showed that 2D/3D vegetation UFPs have the greatest summer cooling effect at 21:00, while 3D building UFP sky view factor (SVF) impacts minimum nighttime temperature more (5:00). The independently total explained variances (R2) of 2D UFPs (0.2-0.7) on seasonal average U-LSTs were higher than that of 3D UFPs (0.1-0.4) in most LCZs. LCZ 3 and LCZ 2 had the highest seasonal and daytime U-LST, respectively. Interestingly, SVF replaced normalized difference vegetation index as the dominant factor in LCZs 4-6 and LCZs A-C after summer. Findings of this study are useful for guiding urban planning, formulating urban heat island mitigation policies, and promoting sustainable development goals (SDGs 11, 13, 15) of cities and communities.

Low-Energy Argon Ion Beam Irradiation for the Surface Modification and Reduction of Graphene Oxide: Insights from XPS

Developing environmentally friendly methods for reducing graphene oxide (GO) is essential. This study investigates the surface modification and reduction of GO films using 200 eV argon ion (Ar+) beam irradiation. X-ray Photoelectron Spectroscopy (XPS) analysis reveals significant chemical changes on the GO surface. GO was irradiated with a 200 eV Ar+beam for varying times (0 to 80 sec). XPS survey spectra showed the presence of carbon and oxygen, with an increasing carbon atomic percentage over time. High-resolution XPS spectra of C 1s revealed peaks corresponding to sp2, C-OH, O-C-O, C=O, and O-C=O bonds. In the O 1s spectra, C=O, O-C-O, and C-OH groups were observed. Upon irradiation, the C=O peak consistently decreased, the O-C-O peak fluctuated, and the C-OH peak increased, indicating effective reduction of C=O groups, dynamic changes in O-C-O functionalities, and the formation of additional C-OH groups. The C/O ratio increased from ∼ 2.4 to 2.7, underscoring the reduction process and enhanced carbon content. This method proves to be an efficient approach for producing reduced graphene oxide (rGO) with improved properties for advanced applications.

Dynamic scheduling of hybrid flow shop problem with uncertain process time and flexible maintenance using NeuroEvolution of Augmenting Topologies

AbstractA hybrid flow shop is pivotal in modern manufacturing systems, where various emergencies and disturbances occur within the smart manufacturing context. Efficiently solving the dynamic hybrid flow shop scheduling problem (HFSP), characterised by dynamic release times, uncertain job processing times, and flexible machine maintenance has become a significant research focus. A NeuroEvolution of Augmenting Topologies (NEAT) algorithm is proposed to minimise the maximum completion time. To improve the NEAT algorithm's efficiency and effectiveness, several features were integrated: a multi‐agent system with autonomous interaction and centralised training to develop the parallel machine scheduling policy, a maintenance‐related scheduling action for optimal maintenance decision learning, and a proactive scheduling action to avoid waiting for jobs at decision moments, thereby exploring a broader solution space. The performance of the trained NEAT model was experimentally compared with the Deep Q‐Network (DQN) and five classical priority dispatching rules (PDRs) across various problem scales. The results show that the NEAT algorithm achieves better solutions and responds more quickly to dynamic changes than DQN and PDRs. Furthermore, generalisation test results demonstrate NEAT's rapid problem‐solving ability on test instances different from the training set.

Variation of volatile flavor substances in salt-baked chicken during processing

Salt-baked chicken was a traditional delicacy of Guangdong, but the effects of volatile flavor compounds at different stages of its processing remained unclear. This study utilized sensory analysis, e-nose, and GC–MS to investigate the changes in volatile flavor compounds during the processing of salt-baked chicken. The results indicated significant alterations in volatile flavor compounds at different stages of processing, resulting in flavor transitioning from the original flavor to salty, scorched, and fatty flavor. 75 volatile compounds were identified by GC–MS, with 15 key flavor compounds highlighted based on OAV, including aldehydes, alcohols, terpenes, heterocycles and esters. The research revealed the dynamic changes in volatile flavor compounds throughout the cooking process of salt-baked chicken and emphasized the important role of salt-baked in shaping its distinctive taste profile. These findings provided a theoretical foundation and practical guidance for enhancing and optimizing the authentic taste of this traditional dish, while fostering innovative advancements in prepared cuisine.

Coding smell patterns of crude oil by the electronic nose: a soil pollution case

In our study, we leveraged an electronic nose to detect the patterns of crude oils and their mixtures, sourced from the oil fields from neighboring regions in pursuit of the task of environmental impact evaluation. The temporal dynamics of oil-related patterns acquired by an electronic nose was tracked to identify the influence of high or low emissions of volatiles that depend on the oil composition. Analyzing the oils by Fourier-transform IR-spectroscopy and GC×GC-MS, we confirmed the correlation between sensor responses and the oil compositions, significantly dependent on the ratio of aromatic compounds/alkanes. Using pattern recognition techniques, Random Forest classifier enabled good accuracy of classification of oil samples and contaminated soils underscoring a high-resolution distinction between the response data. Applying these principles to determine the oil origin, we observed that the studied oil samples and contaminated soil samples corroborate with the dynamic changes in odor patterns based only on volatile and semivolatile compounds. Crude oils from the border of two oil fields facilitate a change in the odor pattern to remain one of the fields depending on the weathering time. These proposed intelligent multisensor systems show great promise as a tool for estimating oil-contaminated soils, thereby potentially enhancing environmental monitoring practices.

Evaluation of four KCNMA1 channelopathy variants on BK channel current under CaV1.2 activation

ABSTRACT Variants in KCNMA1, encoding the voltage- and calcium-activated K+ (BK) channel, are associated with human neurological disease. The effects of gain-of-function (GOF) and loss-of-function (LOF) variants have been predominantly studied on BK channel currents evoked under steady-state voltage and Ca2+ conditions. However, in their physiological context, BK channels exist in partnership with voltage-gated Ca2+ channels and respond to dynamic changes in intracellular Ca2+ (Ca2+ i). In this study, an L-type voltage-gated Ca2+ channel present in the brain, CaV1.2, was co-expressed with wild type and mutant BK channels containing GOF (D434G, N999S) and LOF (H444Q, D965V) patient-associated variants in HEK-293T cells. Whole-cell BK currents were recorded under CaV1.2 activation using buffering conditions that restrict Ca2+ i to nano- or micro-domains. Both conditions permitted wild type BK current activation in response to CaV1.2 Ca2+ influx, but differences in behavior between wild type and mutant BK channels were reduced compared to prior studies in clamped Ca2+ i. Only the N999S mutation produced an increase in BK current in both micro- and nano-domains using square voltage commands and was also detectable in BK current evoked by a neuronal action potential within a microdomain. These data corroborate the GOF effect of N999S on BK channel activity under dynamic voltage and Ca2+ stimuli, consistent with its pathogenicity in neurological disease. However, the patient-associated mutations D434G, H444Q, and D965V did not exhibit significant effects on BK current under CaV1.2-mediated Ca2+ influx, in contrast with prior steady-state protocols. These results demonstrate a differential potential for KCNMA1 variant pathogenicity compared under diverse voltage and Ca2+ conditions.

Dynamic changes of platelets before and after surgery predict the prognosis of patients with aneurysmal subarachnoid hemorrhage

ObjectiveThis investigation sought to explore the association between postoperative/preoperative platelet ratio (PPR) and the incidence of unfavorable outcomes within 90 days in individuals with aneurysmal subarachnoid hemorrhage (aSAH). MethodsThis investigation, utilizing data from 2015 to 2022, concentrated on patients diagnosed with aSAH, categorizing them into four groups based on PPR quartiles. The association between PPR levels and clinical outcomes—comprising in-hospital complications, mortality, and modified Rankin Scale (mRS) scores at discharge and 90 days thereafter—was evaluated through logistic regression analyses. To explore potential non-linear associations between PPR levels and outcomes, restricted cubic spline (RCS) regression was applied. Further, mediation analysis was performed to elucidate the role of in-hospital complications in modulating the impact of PPR levels on 90-day outcomes. ResultsThis study analyzed data from 948 patients. Upon adjustment for confounding variables, it was observed that patients in the higher quartiles showed reduced incidences of anemia, hypoproteinemia, and pneumonia, alongside a decreased frequency of unfavorable outcomes within a 90-day follow-up period. The RCS analysis indicated a linear association of PPR with pneumonia, hypoproteinemia, and adverse 90-day outcomes (p for nonlinear = 0.61, 0.52, and 0.96, respectively). Moreover, the association of PPR with anemia was found to be nonlinear (p for nonlinear = 0.01). Mediation analysis further indicated that anemia and pneumonia significantly influenced the association between PPR and unfavorable outcomes at 90 days, accounting for 15.49% and 27.61% of the effect, respectively. ConclusionsThis study establishes a significant correlation between decreased PPR levels and 90-day adverse outcomes following aSAH, potentially relating to pneumonia and anemia.

Enhancing bird habitat networks in metropolitan areas: Resilience assessment and improvement strategies – A case study from Shanghai

Constructing bird habitat networks (BHNs) is crucial for maintaining the health and service equilibrium of urban ecosystems, especially in large metropolitan areas where the pressure of urbanization is intense. However, most existing BHNs fail to account for the dynamic changes and unique requirements of local species, leading to homogenized construction outcomes and ecological corridor objectives. This study employs a comprehensive approach to identify bird habitat patches using multiple high-quality sources, then utilize circuit theory and complex network theory to construct and assess the resilience of BHN. Our key findings showed: (1)93 bird habitat sources were identified, predominantly situated in the continuous green spaces of southern and southeastern Shanghai, whereas habitat sources in the city center and other densely built-up areas are more dispersed, highlighting them as prime targets for future ecological restoration efforts. (2) The distribution of bird habitat corridors exhibits significant spatial heterogeneity, with primary corridors predominantly spanning the southwestern and eastern parts of the study area, while secondary corridors are more abundant in the western and northern parts, forming a denser network, whereas the central area shows fewer and more isolated corridors. (3) The decline in structural and functional resilience was notably more rapid under targeted attacks than under random attacks, underscoring the need to prioritize crucial bird habitat sources on the city's periphery, especially near highly urbanized areas, in urban planning and biodiversity conservation efforts to sustain ecological balance and biodiversity. These insights provide a crucial scientific basis for urban planners, emphasizing the integration of biodiversity conservation into urban development strategies by optimizing ecological sources and corridors to balance development with ecological preservation.

High-sensitivity troponin T for detection of culprit lesions in patients with out-of-hospital cardiac arrest.

Patients with an out-of-hospital cardiac arrest (OHCA) often undergo coronary angiography, although a culprit lesion is found in only 30%-40% of patients. The aim of this study was to investigate high-sensitivity troponin T (hsTnT) levels in post cardiac arrest patients with and without coronary culprit lesions; factors affecting hsTnT levels after return of spontaneous circulation (ROSC); and the diagnostic ability of hsTnT in identifying patients with culprit lesions. We hypothesized that peak hsTnT levels were higher during the initial 48 h after cardiac arrest in patients with a coronary culprit lesion. This was a retrospective observational study, which included patients admitted to the Intensive Care Unit after an OHCA and who received a coronary angiography. Peak values and dynamic changes in hsTnT were analyzed in relation to the presence of a culprit lesion at coronary angiography. A total of 238 patients were studied, of whom 140 had a culprit lesion. HsTnT levels during the initial 48 h were higher in patients with culprit lesions, longer time to ROSC and an unwitnessed cardiac arrest. At 6 to 12 h after ROSC, a hsTnT cut-off level of 1690 ng/L had a sensitivity of 64% and specificity of 84% to identify a culprit lesion. In patients without ST-elevations, hsTnT measured between 6 and 12 h after ROSC had a specificity above 90%, with a sensitivity of 46%. HsTnT levels after cardiac arrest are higher in patients with coronary culprit lesions. Presence of a culprit lesion, witnessed status and the duration of CPR are important factors affecting hsTnT levels. Repeated measurement of hsTnT within the first 12 h after admission improved diagnostic accuracy but the value of hsTnT as a predictor of culprit lesions early after OHCA is limited.

Effect of V concentration in TiSiN monolayer coating on chip formation mechanism and chip sliding velocity during dry turning of Ti–6Al–4V alloy

The current study examines how the self-lubricating characteristics of the novel TiSiVN coating affect the chip formation process and chip sliding velocity during the dry turning of Ti6Al4V titanium alloy. The serration bands tend to straighten at a cutting speed of 125 m/min, which is the main cause of the chips being straightened without tangling for both coated tools. TiSiVN coated tool accounts for higher chip sliding velocity due to the generation of lubricious phases, whereas the higher VS for uncoated tool indicates high tool wear at the highest cutting speed of 125 m/min. Further, r and θn tend to have an inverse relationship with VS, with 125 m/min cutting speed remaining an exception due to severe changes in tool wear dynamics. The reduction of friction helped to lower the localized strain along the shear bands and the effective stress at the beginning of the formation of the serrated tooth.

Unraveling the hydration dynamics of the ACC1–13K24-ATP system: From liquid to droplet to amyloid fibril

In order to achieve a comprehensive understanding of protein aggregation processes, an exploration of solvation dynamics, a key yet intricate component of biological phenomena, is mandatory. In the present study, we used Fourier transform infrared spectroscopy and terahertz spectroscopy complemented by atomic force microscopy and kinetic experiments utilizing thioflavin T fluorescence to elucidate the changes in solvation dynamics during liquid-liquid phase separation and subsequent amyloid fibril formation, the latter representing a transition from liquid to solid phase separation. These processes are pivotal in the pathology of neurodegenerative disorders such as Alzheimer’s and Parkinson’s diseases. We focus on the ACC1–13K24-ATP protein complex, which undergoes fibril formation followed by droplet generation. Our investigation reveals the importance of hydration as a driving force in these processes, offering new insights into the molecular mechanisms at play.

Linking Metabolism and Histone Acetylation Dynamics by Integrated Metabolic Flux Analysis of Acetyl-CoA and Histone Acetylation Sites

Histone acetylation is an important epigenetic modification that regulates various biological processes and cell homeostasis. Acetyl-CoA, a hub molecule of metabolism, is the substrate for histone acetylation, thus linking metabolism with epigenetic regulation. However, still relatively little is known about the dynamics of histone acetylation and its dependence on metabolic processes, due to the lack of integrated methods that can capture site-specific histone acetylation and deacetylation reactions together with the dynamics of acetyl-CoA synthesis. In this study, we present a novel proteo-metabo-flux approach that combines mass spectrometry-based metabolic flux analysis of acetyl-CoA and histone acetylation with computational modelling. We developed a mathematical model to describe metabolic label incorporation into acetyl-CoA and histone acetylation based on experimentally measured relative abundances. We demonstrate that our approach is able to determine acetyl-CoA synthesis dynamics and site-specific histone acetylation and deacetylation reaction rate constants, and that consideration of the metabolically labelled acetyl-CoA fraction is essential for accurate determination of histone acetylation dynamics. Furthermore, we show that without correction, changes in metabolic fluxes would be misinterpreted as changes in histone acetylation dynamics, whereas our proteo-metabo-flux approach allows to distinguish between the two processes.

Pipette-tip solid-phase extraction coupled with matrix-assisted laser desorption/ionization mass spectrometry enables rapid and high-throughput analysis of antidepressants in rat serum.

Therapeutic drug monitoring is essential for ensuring the efficacy and safety of medications. This study introduces a streamlined approach that combines pipette-tip solid-phase extraction (PT-SPE) with matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS), facilitating rapid and high-throughput monitoring of drug concentrations. As a demonstration, this method was applied to the extraction and quantification of antidepressants in serum. Utilizing Zip-Tip C18, the method enabled the extraction of antidepressants from complex biological matrices in less than 2min, with the subsequent MALDI-MS analysis yielding results in just 1min. Optimal extraction recoveries were achieved using a sampling solution at pH 9.0 and a 10 μL ethanol desorption solution containing 0.1% phosphoric acid. For MALDI analysis, 2,5-dihydroxybenzoic acid was identified as the most effective matrix for producing the highest signal intensity. The quantification strategy exhibited robust linearities (R2 ≥ 0.997) and satisfactory limits of quantification, ranging from 0.05 to 0.5 μg/mL for a suite of antidepressants. The application for monitoring dynamic concentration changes of antidepressants in rat serum emphasized the method's efficacy. This strategy offers the advantages of high throughput, minimal sample usage, environmental sustainability, and simplicity, providing ideas and a reference basis for the subsequent development of methods for therapeutic drug monitoring.

Soil moisture inversion based on multiple drought indices and RBFNN: A case study of northern Hebei Province

Drought has a significant impact on crop growth and productivity, highlighting the critical need for precise and timely soil moisture estimation to mitigate agricultural losses. This study focuses on soil moisture retrieval in northern Hebei Province during July 2012, utilizing eight widely employed remote sensing drought indices derived from MODIS satellite data. These indices were cross-referenced with measured soil moisture levels for analysis. Based on their correlation coefficients, a composite remote sensing drought index set comprising six indices was identified. Furthermore, a radial basis function neural network (RBFNN) was employed to estimate soil relative humidity. The accuracy evaluation of the soil moisture estimation model, which integrates multiple remote sensing drought indices and the RBFNN, demonstrated clear superiority over models relying on single drought indices. The model achieved an average estimation accuracy of 87.54 % for soil relative humidity at a depth of 10 cm (SM10) and 87.36 % for a 20 cm depth (SM20). The root mean square errors (RMSE) for the test sets were 0.093 and 0.092, respectively. Validation results for July 2013 indicated that the inversion accurately reflected the actual soil moisture conditions, effectively capturing dynamic moisture changes. These results fully verify the reliability and practicability of the model. These findings introduce a novel approach to local agricultural soil moisture estimation, with significant implications for enhancing agricultural water resource management and decision-making processes.

Dynamic functional network connectivity in children with profound bilateral congenital sensorineural hearing loss.

Functional magnetic resonance imaging (fMRI) studies have revealed extensive functional reorganization in patients with sensorineural hearing loss (SNHL). However, almost no study focuses on the dynamic functional connectivity after hearing loss. This study aimed to investigate dynamic functional connectivity changes in children with profound bilateral congenital SNHL under the age of 3years. Thirty-two children with profound bilateral congenital SNHL and 24 children with normal hearing were recruited for the present study. Independent component analysis identified 18 independent components composing five resting-state networks. A sliding window approach was used to acquire dynamic functional matrices. Three states were identified using the k-means algorithm. Then, the differences in temporal properties and the variance of network efficiency between groups were compared. The children with SNHL showed longer mean dwell time and decreased functional connectivity between the auditory network and sensorimotor network in state 3 (P < 0.05), which was characterized by relatively stronger functional connectivity between high-order resting-state networks and motion and perception networks. There was no difference in the variance of network efficiency. These results indicated the functional reorganization due to hearing loss. This study also provided new perspectives for understanding the state-dependent connectivity patterns in children with SNHL.

Wetting mechanism and alteration of nano-sized shale pores: Insights from contrast variation small angle neutron scattering

Wettability of tight shale is crucial for fluid flow and mass transport process in energy geosciences. However, understanding the interfacial chemistry and wetting mechanisms at sub-nano-pore scales remains a formidable challenge. In this study, the Contrast Variation technique of Small Angle Neutron Scattering (CV-SANS) is employed to investigate shale’s interfacial chemistry using reagents that possess a range of different polarities, including water, n-decane, toluene, and dimethyl methanamide. Through five different experimental strategies, we have demonstrated a successful modification of shale wettability, ranging from enhancement, weakening, to reversal. Delving into the mechanisms, we illustrated the crucial role of pre-existing liquid films in these changes, where the uniquely co-existing polar and non-polar functional groups in dimethyl methanamide acted as a conduit for interfacial chemistry adjustments. Furthermore, a solvent immersion led to matrix dilation as well as liberation of residual oil-occupied pores, resulting in altered pore size distributions, with hydrogen bonding playing a significant role in the polar groups. Interestingly, despite shale exhibiting a stronger affinity for oil over water, hydrophilic solvents induced more substantial dilation than lipophilic ones. Collectively, this work elucidates the dynamic change of interfacial chemistry via the configuration of polarity using chemical reagents, and the CV-SANS technique underscores its invaluable utilities in decoding the interfacial wettability traits in nanopore space of shale.

Prognostic role of dynamic changes in inflammatory indicators in patients with non-small cell lung cancer treated with immune checkpoint inhibitors-a retrospective cohort study.

Immune checkpoint inhibitors (ICIs) have become one of the standard treatments for non-small cell lung cancer (NSCLC) patients without driver mutations. However, a considerable proportion of patients suffer from severe immune side effects and fail to respond to ICIs. As effective biomarkers, programmed cell death ligand 1 (PD-L1) expression, microsatellite instability (MSI), the tumor mutation burden (TMB) and tumor-infiltrating lymphocytes (TILs) require invasive procedures that place heavy physical and psychological burdens on patients. This study aims to identify simple and effective markers to optimize patient selection through therapeutic decisions and outcome prediction. This retrospective study comprised 95 patients with metastatic NSCLC who were treated with ICIs either as the standard of care or in a clinical trial. The following data were extracted from the medical records. The baseline and dynamic neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) were calculated in the present study. Responses were assessed by computed tomography (CT) imaging and classified according to the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 every 6-12 weeks during treatment. In total, 95 patients were included in the present study. The median age of patients was 61 years, 83.2% (79/95) patients were male, 62.1% (59/95) were former or current smokers, 66.3% (63/95) had adenocarcinoma, 93.7% (89/95) had stage IV disease, and 87.4% were without molecular alterations. A higher overall response rate (ORR) and prolonged median progression-free survival (PFS) was observed in patients with a lower cycle 3 (C3) NLR [7.7 vs. 5.5 months, hazard ratio (HR): 1.70, 95% confidence interval (CI): 0.90-3.22; P=0.12] and derived NLR (dNLR) (8.2 vs. 5.6 months, HR: 1.67, 95% CI: 0.94-2.97; P=0.08). After two cycles of ICI treatment, patients who had an increased NLR, dNLR, and PLR had a lower ORR and an inferior median PFS than those with a decreased NLR (5.5 vs. 8.5 months, HR: 1.87, 95% CI: 1.09-3.21; P=0.02), dNLR (5.6 vs. 8.4 months, HR: 1.49, 95% CI: 0.87-2.57; P=0.15), and PLR (11.8 vs. 5.5 months, HR: 2.28, 95% CI: 1.32-3.94; P=0.003). Moreover, patients with both an increased NLR and PLR had a worse ORR and median PFS than those with either an increased NLR or PLR, or both an increased NLR and PLR (11.8 vs. 5.5 vs. 5.6 months, P=0.003). In addition, the dynamic changes in the PLR could serve as an independent predictive factor of PFS in NSCLC patients treated with ICIs. Elevated dynamic changes in the NLR and PLR were associated with lower response rates and shorter PFS in the patients with NSCLC treated with ICIs. Our results also highlight the role of dynamic changes in the PLR in identifying patients with NSCLC who could benefit from ICIs.

Adaptive current decoupling control scheme based on online multi-parameter identification for high-speed permanent magnet synchronous motor in fuel cell

The precise control of centrifugal hydrogen compressor (CHC) driven by high-speed permanent magnet synchronous motor (PMSM) is the key to the stable and efficient operation of hydrogen fuel cell (HFC). In this paper, an adaptive current deviation decoupling control (CDDC) strategy based on variable step size affine projection algorithm (VSS-APAs) is proposed to solve the high-speed PMSM control problem caused by current cross-coupling and parameter perturbation under complex operating conditions. Firstly, the step size is dynamically adjusted by VSS-APA through a normalized gradient descent to respond to system fluctuations, achieving rapid parameter identification during dynamic changes and accurate tracking in steady states. Secondly, stator inductance, magnetic flux linkage, stator resistance, and disturbance torque are identified in two-time-scale based on the characteristics of parameter changes, overcoming the rank deficiency in motor mathematical equations. Finally, utilizing online-identified motor parameters, the gains of the CDDC are adjusted, and compensation is applied for back electromotive force (BEMF) and disturbance torque, thereby ensuring the control accuracy of the motor under parameter perturbations and system disturbances. Experimental results demonstrate that the proposed method enhances the responsiveness and accuracy of the control strategy through efficient parameters identification. Consequently, it guarantees high-efficiency and stable performance of the CHC across different working conditions, markedly advancing the overall functionality and dependability of hydrogen energy system.