Search

With the urgent need of energy saving and consumption reduction in today's world, the topic of increasing the energy conversion efficiency of ventilation fans has been attracted a lot of attentions, it has become a key issue in the field of ventilation. The understanding on the evolution mechanism of irreversible energy loss in impeller is the premise and basis for realizing the efficient energy conversion of ventilation fans. At present, the irreversible energy loss mechanism in impeller is still lack of research. Therefore, the internal flow field of the contra-rotating axial fan at different flowrates is obtained by numerical simulation and experimental methods. A theoretical model of irreversible energy loss in impeller of ventilation fans is established based on entropy production theory, and the relationship between the irreversible energy loss in impeller and the flow field parameters is clarified. A quantitative analysis is conducted on different types of energy loss in impeller, and the spatial evolution law and causes of energy loss are clarified by combining with the flow characteristics in impeller. The results show that the entropy production method is reliable in calculating the irreversible energy loss in impeller. Direct viscous dissipation loss and wall friction loss are important components of energy loss, while turbulent dissipation is the main cause of energy loss, accounting for 60% to 80% of the total energy loss. For the front impeller, the energy loss caused by turbulent dissipation reaches the minimum at 1.0 QBEP, while the energy loss of the rear impeller increases with the decrease of flowrate. The energy loss is mainly concentrated in the region of Span=0.6−1.0, reaching 70% of the total energy loss at optimal flow condition. The spiral vortex caused by blade tip leakage flow and overflow of blade leading edge, backflow in impeller, flow separation at blade pressure and suction surface, and blade trailing edge wake will cause energy loss. The high energy loss region caused by flow separation and wake is relatively small, and the energy loss is relatively limited. However, the vortex and backflow significantly affect the flow in impeller, ultimately leading to a significant energy loss in the region near the blade tip. The research results can provide a reference for the evaluation of irreversible energy loss of ventilation fans.

Abstract Geophysical inversion usually involves ill-posed problem. Regularization is the most commonly used method to mitigate this problem. There are many regularization parameter selection methods, among which the adaptive regularization method can automatically update parameters during iteration, reducing the difficulty of parameter selection. Therefore, it is widely used in linear inversion. However, there are very few studies on the use of adaptive regularization methods in stochastic optimization algorithms. The biggest difficulty is that in stochastic optimization algorithms, the search direction of any iteration is completely random. Data fitting term and stabilizing term vary in a wide range, making it difficult for traditional methods to work. In this paper, we consider the contributions of the data fitting term and the stabilizing term in the objective function and give an improved adaptive regularization method for very fast simulated annealing (VFSA) inversion for transient electromagnetic (TEM) data. The optimized method adjusts the two terms dynamically to make them in balance. We have designed several numerical experiments, and the experimental results demonstrate that the method in this paper not only accelerates the convergence, but also the inversion results are very little affected by the initial regularization parameter. Finally, we apply this method to field data, and the inversion results show very good agreements with nearby borehole data.

The management of anesthesia in elderly patients undergoing surgery presents unique challenges, particularly in mitigating stress responses and ensuring stability. Etomidate may alleviate adrenocortical and immune stress. This study aims to investigate the anesthetic effects of combined spinal-epidural anesthesia (CSEA) supplemented with etomidate during anorectal surgery in elderly patients. The medical records of 49 cases treated with CSEA and etomidate (ETO group) and 48 cases treated with CSEA alone (control group) were reviewed and analyzed. All patients received ropivacaine hydrochloride for anesthesia, with the ETO group additionally receiving an infusion of etomidate for sedation. Parameters such as arterial blood gas, visual analog scale (VAS), Ramsay sedation scale (RSS), serum cortisol and norepinephrine levels, pro-inflammatory cytokines, and lymphocyte ratios were assessed at different time points. Compared to the control group, the ETO group showed increased mean arterial pressure, decreased heart rate, and elevated arterial SpO2 30 minutes after anesthesia. The ETO group also had higher RSS scores, lower VAS scores, and reduced serum cortisol and norepinephrine levels. Additionally, decreased levels of pro-inflammatory cytokines, such as interleukin (IL)-6, tumor necrosis factor (TNF)-α, and IL-8, were observed, along with an increase in the regulatory cytokine IL-10. An increased proportion of CD4+ T cells and a higher CD4/CD8 ratio were also noted. This study demonstrates the benefits of using etomidate to mitigate adrenocortical and immune stress in elderly patients undergoing anorectal surgery.

Based on single-cell sequencing of the hippocampi of 5× familiar Alzheimer's disease (5× FAD) and wild type mice at 2-, 12-, and 24-month of age, we found an increased percentage of microglia in aging and Alzheimer's disease (AD) mice. Blood brain barrier injury may also have contributed to this increase. Immune regulation by microglia plays a major role in the progression of aging and AD, according to the functions of 41 intersecting differentially expressed genes in microglia. Signaling crosstalk between C−C motif chemokine ligand (CCL) and major histocompatibility complex-1 bridges intercellular communication in the hippocampus during aging and AD. The amyloid precursor protein (APP) and colony stimulating factor (CSF) signals drive 5× FAD to deviate from aging track to AD occurrence among intercellular communication in hippocampus. Microglia are involved in the progression of aging and AD can be divided into 10 functional types. The strength of the interaction among microglial subtypes weakened with aging, and the CCL and CSF signaling pathways were the fundamental bridge of communication among microglial subtypes.

Abstract Background Sterile alpha motif domain and histidine-aspartate domain-containing protein 1 (SAMHD1) is a DNA end resection factor, which is involved in DNA damage repair and innate immunity. However, the role of SAMHD1 in anti-tumor immunity is still unknown. This study investigated the effects of SAMHD1 on stimulator of interferon genes (STING)-type I interferon (IFN) pathway and radiation-induced immune responses. Methods The roles of SAMHD1 in the activation of cytosolic DNA sensing STING pathway in lung adenocarcinoma (LUAD) cells were investigated with flow cytometry, immunofluorescence, immunoblotting and qPCR. The combined effects of SAMHD1 silencing and radiation on tumor cell growth and STING pathway activation were also evaluated with colony formation and CCK8 assay. The Lewis lung cancer mouse model was used to evaluate the combined efficiency of SAMHD1 silencing and radiotherapy in vivo. Macrophage M1 polarization and cytotoxic T cell infiltration were evaluated with flow cytometry. Results The single-stranded DNA (ssDNA) accumulated in the cytosol of SAMHD1-deficient lung adenocarcinoma (LUAD) cells, accompanied by upregulated DNA sensor IFN-γ-inducible protein 16 (IFI16) and activated STING pathway. The translocation of IFI16 from nucleus to cytosol was detected in SAMHD1-deficient cells. IFI16 and STING were acquired in the activation of STING-IFN-I pathway in SAMHD1-deficient cells. SAMHD1 silencing in LUAD cells promoted macrophage M1 polarization in vitro. SAMHD1 silencing synergized with radiation to activate ssDNA-STING-IFN-I pathway, inhibit proliferation, promote apoptosis and regulate cell cycle. SAMHD1 silencing cooperated with radiotherapy to inhibit tumor growth and increase CD86+MHC-IIhigh M1 proportion and CD8+ T cell infiltration in vivo. Conclusions SAMHD1 deficiency induced IFN-I production through cytosolic IFI16-STING pathway in LUAD cells. Moreover, SAMHD1 downregulation and radiation cooperated to inhibit tumor growth and enhance anti-tumor immune responses through macrophage M1 polarization and CD8+ T cell infiltration. Combination of SAMHD1 inhibition and radiotherapy may be a potentially therapeutic strategy for LUAD patients.

Abstract Background Radiotherapy has been widely used to treat various cancers, but its efficacy depends on the individual involved. Traditional gene-based machine-learning models have been widely used to predict radiosensitivity. However, there is still a lack of emerging powerful models, artificial neural networks (ANN), in the practice of gene-based radiosensitivity prediction. In addition, ANN may overfit and learn biologically irrelevant features. Methods We developed a novel ANN with Selective Connection based on Gene Patterns (namely ANN-SCGP) to predict radiosensitivity and radiocurability. We creatively used gene patterns (gene similarity or gene interaction information) to control the "on–off" of the first layer of weights, enabling the low-dimensional features to learn the gene pattern information. ANN-SCGP was trained and tested in 82 cell lines and 1,101 patients from the 11 pan-cancer cohorts. Results For survival fraction at 2 Gy, the root mean squared errors (RMSE) of prediction in ANN-SCGP was the smallest among all algorithms (mean RMSE: 0.1587–0.1654). For radiocurability, ANN-SCGP achieved the first and second largest C-index in the 12/20 and 4/20 tests, respectively. The low dimensional output of ANN-SCGP reproduced the patterns of gene similarity. Moreover, the pan-cancer analysis indicated that immune signals and DNA damage responses were associated with radiocurability. Conclusions As a model including gene pattern information, ANN-SCGP had superior prediction abilities than traditional models. Our work provided novel insights into radiosensitivity and radiocurability.

GPR87 is reported as a central player in lung adenocarcinoma and in resistance to immunotherapy, by promoting tumor cell invasion and mediating the immunogenomic landscape.

Abstract Background Tumor microenvironment (TME) is associated with tumor progression and prognosis. Previous studies provided tools to estimate immune and stromal cell infiltration in TME. However, there is still a lack of single index to reflect both immune and stromal status associated with prognosis and immunotherapy responses. Methods A novel immune and stromal scoring system named ISTMEscore was developed. A total of 15 datasets were used to train and validate this system, containing 2965 samples from lung adenocarcinoma, skin cutaneous melanoma and head and neck squamous cell carcinoma. Results The patients with high immune and low stromal scores (HL) were associated with low ratio of T cell co-inhibitory/stimulatory molecules and low levels of angiogenesis markers, while the patients with low immune and high stromal scores (LH) had the opposite characteristics. The HL patients had immune-centered networks, while the patients with low immune and low stromal scores (LL) had desert-like networks. Moreover, copy number alteration burden was decreased in the HL patients. For the clinical characteristics, our TME classification was an independent prognostic factor. In the 5 cohorts with immunotherapy, the LH patients were linked to the lowest response rate. Conclusions ISTMEscore system could reflect the TME status and predict the prognosis. Compared to previous TME scores, our ISTMEscore was superior in the prediction of prognosis and immunotherapy response.

Lung adenocarcinoma (LUAD) is the most frequent subtype of lung cancer worldwide. However, the survival rate of LUAD patients remains low. N6-methyladenosine (m6A) and long noncoding RNAs (lncRNAs) play vital roles in the prognostic value and the immunotherapeutic response of LUAD. Thus, discerning lncRNAs associated with m6A in LUAD patients is critical. In this study, m6A-related lncRNAs were analyzed and obtained by coexpression. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were conducted to construct an m6A-related lncRNA model. Kaplan-Meier analysis, principal-component analysis (PCA), functional enrichment annotation, and nomogram were used to analyze the risk model. Finally, the potential immunotherapeutic signatures and drug sensitivity prediction targeting this model were also discussed. The risk model comprising 12 m6A-related lncRNAs was identified as an independent predictor of prognoses. By regrouping the patients with this model, we can distinguish between them more effectively in terms of the immunotherapeutic response. Finally, candidate compounds aimed at LUAD subtype differentiation were identified. This risk model based on the m6A-based lncRNAs may be promising for the clinical prediction of prognoses and immunotherapeutic responses in LUAD patients.

Lung adenocarcinoma (LUAD) has high morbidity and mortality worldwide, and its prognosis remains unsatisfactory. Identification of epigenetic biomarkers associated with radiosensitivity is beneficial for precision medicine in LUAD patients. SETD2 is important in repairing DNA double-strand breaks and maintaining chromatin integrity. Our studies established a comprehensive analysis pipeline, which identified SETD2 as a radiosensitivity signature. Multi-omics analysis revealed enhanced chromatin accessibility and gene transcription by SETD2. In both LUAD bulk RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq), we found that SETD2-associated positive transcription patterns were associated with DNA damage responses. SETD2 knockdown significantly upregulated tumor cell apoptosis, attenuated proliferation and migration of LUAD tumor cells, and enhanced radiosensitivity in vitro. Moreover, SETD2 was a favorably prognostic factor whose effects were antagonized by the m6A-related genes RBM15 and YTHDF3 in LUAD. In brief, SETD2 was a promising epigenetic biomarker in LUAD patients.

Abstract Background As one of the most common malignancy, lung adenocarcinoma (LUAD) is characterized by low 5-year survival rate. This research aimed to investigate the effects of ribonucleotide reductase regulatory subunit M2 (RRM2) on malignant biological behaviors and activation of cGAS/STING pathway. We also explored the synergistic sensitization mechanisms of RRM2 and radiotherapy. Methods Bioinformatic tools were used to evaluate the clinical significance of RRM2 in LUAD patients. The roles of RRM2 in malignant phenotype and DNA damage in LUAD cells were investigated with cell proliferation, colony formation, immunofluorescence, modified Boyden chamber and comet assays. The mouse models were used to evaluate the biological significance of RRM2 in vivo. Cytotoxic T cell infiltration was evaluated via flow cytometric analysis and immunohistochemistry staining in C57BL/6 mice. We also explored the synergistic effects of RRM2 silencing and radiation on LUAD cells with apoptosis assay and immunoblotting in vitro. Results Bioinformatic analysis revealed that RRM2 had diagnostic values for LUAD patients. Higher levels of RRM2 predicted worse prognosis. RRM2 silencing inhibited LUAD cell proliferation, invasion and migration. RRM2 knockdown induced S phase arrest and DNA damage. RRM2 silencing induced cyclic GMP-AMP synthase (cGAS)/stimulator of interferon genes (STING) pathway, and the downstream targets were regulated in a STING-dependent manner. Knockdown of RRM2 suppressed tumor growth in the xenograft tumor models. RRM2 deficiency increased CD8 + T cells in the tumor tissues and spleens. Furthermore, RRM2 silencing had synergistic effects with radiation on inhibiting cell proliferation and promoting apoptosis. Meanwhile, this combination promoted the activation of cGAS/STING signaling pathway synergistically, and simultaneously increased expression of IFNβ, CCL5 and CXCL10. Conclusion Our results demonstrated that RRM2 silencing had anti-tumor values and activated the cGAS/STING signaling pathway. RRM2 silencing increased CD8 + T cells infiltration. RRM2 silencing cooperated with radiation to inhibit LUAD cell proliferation, promote apoptosis and enhance the activation of cGAS/STING signaling pathway. RRM2 could be a promising target for tumor regression through cancer immunotherapy in LUAD.

Abstract Background The expression of long non‐coding RNA (lncRNA) prostate cancer‐associated ncRNA transcripts 1 (PCAT1) is increased in non‐small cell lung cancer (NSCLC). It stimulates tumour growth and metastasis, but its role in the radioimmune responses remain unknown. We aimed to explore the impacts of PCAT1 on tumorigenesis and radioimmune responses and the underlying molecular mechanisms in NSCLC. Methods Comprehensive bioinformatics analysis was performed to identify immunosuppressive lncRNAs involved with tumour invasion in NSCLC. The expression levels of PCAT1 were analysed by in situ hybridisation in 55 paired NSCLC tissues and adjacent normal tissues. Both loss‐ and gain‐of‐function assays were performed to examine the effects of PCAT1 and SOX2 on NSCLC cell behaviours in vivo and in vitro. Bioinformatic analyses, chromatin isolation by RNA purification (ChIRP) and dual‐luciferase reporter assays were applied to validate the regulatory effects of PCAT1 on SOX2 expression. Chromatin immunoprecipitation, luciferase and rescue assays were utilised to identify the relationship between SOX2 and the cGAS/stimulator of interferon genes (STING) signalling. Results PCAT1 was immunosuppressive and related with NSCLC invasion. Increased PCAT1 was negatively correlated with immune cell infiltration in NSCLC. PCAT1 knockdown restrained proliferation, increased apoptosis, and repressed cell metastasis in vivo and in vitro. PCAT1 activated SOX2 that accelerated tumorigenesis and immunosuppression. SOX2 promoted tumour growth through inhibiting cytotoxic T‐cell immunity. Moreover, SOX2 restrained cGAS transcription and hampered downstream type I interferon (IFN)‐induced immune responses. Inhibition of PCAT1/SOX2 in collaboration with radiation further inhibited tumour growth, and initiated the cGAS/STING signalling pathway, which enhanced the immune responses of radiotherapy in NSCLC. Conclusions PCAT1/SOX2 axis promoted tumorigenesis and immunosuppression through inhibition of cGAS/STING signalling‐mediated T‐cell activation. Inhibition of PCAT1 and SOX2 synergised with radiotherapy to activate the immune response and could serve as potential therapeutic targets.

BackgroundIncreasing evidence has demonstrated that pyroptosis exerts key roles in the occurrence, development, and prognosis of uterine corpus endometrial carcinoma (UCEC). However, the mechanism of pyroptosis and its predictive value for prognosis remain largely unknown.MethodsUCEC data were acquired from The Cancer Genome Atlas (TCGA) database. The differentially expressed genes in UCEC vs. normal cases were selected to perform a weighted correlation network analysis (WGCNA). Forty-two UCEC-associated pyroptosis-related genes were identified via applying differential expression analysis. Protein–protein interaction (PPI) and gene correlation analyses were applied to explore the relationship between 21 UCEC key genes and 42 UCEC-associated pyroptosis-related genes. The expression of 42 UCEC-associated pyroptosis-related genes of different grades was also calculated. The immune environment of UCEC was evaluated. Furthermore, pyroptosis-related genes were filtered out by the co-expression. Univariate and a least absolute shrinkage and selection operator (LASSO) Cox analyses were implemented to yield a pyroptosis-related gene model. We also performed consensus classification to regroup UCEC samples into two clusters. A clinically relevant heatmap and survival analysis curve were implemented to explore the clinicopathological features and relationship between two clusters. Furthermore, a Kaplan–Meier survival analysis was implemented to analyze the risk model.ResultsTwenty-one UCEC key genes and 42 UCEC-associated pyroptosis-related genes were identified. The PPI and gene correlation analysis showed a clear relationship. The expression of 42 UCEC-associated pyroptosis-related genes of different grades was also depicted. A risk model based on pyroptosis-related genes was then developed to forecast overall survival among UCEC patients. Finally, Cox regression analysis verified this model as an independent risk factor for UCEC patients.ConclusionsThe expression of pyroptosis-related gene may influence UCEC occurrence, development, and prognosis.

Abstract Background The incidence of lung squamous cell carcinoma (LUSC) increased substantially in recent years. Systematical investigation of the immunogenomic pattern is critical to improve the prognosis of LUSC. Methods Based on the TCGA and GEO dataset, we integrated the immune-related genes (IRGs) expression profile and the overall survival (OS) of 502 patients with LUSC. The survival-related and differentially-expressed IRGs in LUSC patients were evaluated by univariate cox regression and LASSO regression analysis. By applying multivariate cox analysis, a new prognostic indicator based on IRGs was established. We also used CIBERSORT algorithms and TIMER database to analyze immune infiltration of LUSC. Both gene set enrichment analysis (GSEA) and principal component analysis (PCA) was carried out for functional annotation. With the assist of computational biology, we also investigated the latent properties and molecular mechanisms of these LUSC-specific IRGs. We analyzed the correlation between immune checkpoints and risk score. Results A novel prognostic model was established based on 11 IRGS, including CXCL5, MMP12, PLAU, ELN, JUN, RNASE7, JAG1, SPP1, AGTR2, FGFR4, and TNFRSF18. This model performed well in the prognostic forecast, and was also related to the infiltration of immune cells. Besides, the high-risk groups and the low-risk groups exhibited distinct layout modes in PCA analysis, and GSEA results showed that different immune status among these groups. Conclusions In summary, our researches screened out clinically significant IRGs and proved the significance of IRG-based, individualized immune-related biomarkers in monitoring, prognosis, and discern of LUSC.

Radiotherapy (RT) is currently considered as an essential treatment for non-small cell lung cancer (NSCLC); it can induce cell death directly and indirectly via promoting systemic immune responses. However, there still exist obstacles that affect the efficacy of RT such as tumor hypoxia and immunosuppressive tumor microenvironment (TME). Herein, we report that the biomineralized manganese oxide nanoparticles (Bio-MnO2 NPs) prepared by mild enzymatic reaction could be a promising candidate to synergistically enhance RT and RT-induced immune responses by relieving tumor hypoxia and activating cGAS-STING pathway. Bio-MnO2 NPs could convert endogenic H2O2 to O2 and catalyze the generation of reactive oxygen species so as to sensitize the radiosensitivity of NSCLC cells. Meanwhile, the release of Mn2+ into the TME significantly enhanced the cGAS-STING activity to activate radio-immune responses, boosting immunogenic cell death and increasing cytotoxic T cell infiltration. Collectively, this work presents the great promise of TME reversal with Bio-MnO2 NPs to collaborate RT-induced antitumor immune responses in NSCLC.

While increased glycolysis has been identified as a cancer marker and attracted much attention in thyroid cancer (THCA), the prognostic role of it remains to be further elucidated. Here we aimed to determine a specific glycolysis-associated risk model to predict THCA patients' survival. We also explored the interaction between this signature and tumor immune microenvironment and performed drug screening to identify specific drugs targeting the glycolysis-associated signature. Six genes (CHST6, POM121C, PPFIA4, STC1, TGFBI, and FBP2) comprised the specific model, which was an independent prognostic indicator in THCA patients determined by univariate, LASSO and multivariate Cox regression analyses. The receiver operating characteristic (ROC) curve analysis confirmed the excellent clinical performance of the prognostic signature. According to the specific gene signature, patients were categorized into high- and low-risk subgroups. The high-risk group was characterized by decreased immune score and elevated tumor purity, as well as worser survival prognosis compared to the low-risk group. We also validated the expression of these genes in clinical samples and in-vitro experiments. Lastly, we identified potential drugs targeting the glycolysis-associated signature. The derived glycolysis-related signature is an independent prognostic biomarker for THCA patients and might be used as an efficacy of biomarker for drug-sensitivity prediction.

Abstract Cell mechanotransduction signals are important targets for physical therapy. However, current physiotherapy heavily relies on ultrasound, which is generated by high‐power equipment or amplified by auxiliary drugs, potentially causing undesired side effects. To address current limitations, a robotic actuation‐mediated therapy is developed that utilizes gentle mechanical loads to activate mechanosensitive ion channels. The resulting calcium influx precisely regulated the expression of recombinant tumor suppressor protein and death‐associated protein kinase, leading to programmed apoptosis of cancer cell line through caspase‐dependent pathway. In stark contrast to traditional gene therapy, the complete elimination of early‐ and middle‐stage tumors (volume ≤ 100 mm3) and significant growth inhibition of late‐stage tumor (500 mm3) are realized in tumor‐bearing mice by transfecting mechanogenetic circuits and treating daily with quantitative robotic actuation in a form of 5 min treatment over the course of 14 days. Thus, this massage‐derived therapy represents a quantitative strategy for cancer treatment.

Aboveground biomass (AGB) serves as a crucial indicator of the carbon sequestration capacity of coastal wetland ecosystems. Conducting extensive field surveys in coastal wetlands is both time-consuming and labor-intensive. Unmanned aerial vehicles (UAVs) and satellite remote sensing have been widely utilized to estimate regional AGB. However, the mixed pixel effects in satellite remote sensing hinder the precise estimation of AGB, while high-spatial resolution UAVs face challenges in estimating large-scale AGB. To fill this gap, this study proposed an integrated approach for estimating AGB using field sampling, a UAV, and Sentinel-2 satellite data. Firstly, based on multispectral data from the UAV, vegetation indices were computed and matched with field sampling data to develop the Field–UAV AGB estimation model, yielding AGB results at the UAV scale (1 m). Subsequently, these results were upscaled to the Sentinel-2 satellite scale (10 m). Vegetation indices from Sentinel-2 data were calculated and matched to establish the UAV–Satellite AGB model, enabling the estimation of AGB over large regional areas. Our findings revealed the AGB estimation model achieved an R2 value of 0.58 at the UAV scale and 0.74 at the satellite scale, significantly outperforming direct modeling from field data to satellite (R2 = −0.04). The AGB densities of the wetlands in Xieqian Bay, Meishan Bay, and Hangzhou Bay, Zhejiang Province, were 1440.27 g/m2, 1508.65 g/m2, and 1545.11 g/m2, respectively. The total AGB quantities were estimated to be 30,526.08 t, 34,219.97 t, and 296,382.91 t, respectively. This study underscores the potential of integrating UAV and satellite remote sensing for accurately assessing AGB in large coastal wetland regions, providing valuable support for the conservation and management of coastal wetland ecosystems.

In the fringe projection profilometry (FPP), the traditional phase-shifting (TPS) algorithm and the Fourier transform (FT) algorithm are beset with a conundrum where measurement efficiency and conflicts with measurement accuracy, thereby limiting their application in dynamic three-dimensional (3D) measurements. Here, we propose a phase shift generation (PSG) method, which acquires the sinusoidal fringes by sparse sampling and reconstructs the complete phase-shifting sequence by generating the missing fringes with superimposed coupling of adjacent fringes. According to our proposed PSG method in which the sinusoidal fringe sequence size is about half of the TPS method, meaning that the PSG method will be timesaving in the phase-shifting sequence sampling process. Moreover, because of the utilization of multiframe fringes, our PSG method allows for a more accurate measurement than the FT method. Both simulation and experimental results demonstrate that our proposed PSG method can well balance the measurement accuracy and efficiency with a lower sampling rate, bearing a great potential to be applied in both scientific and industrial areas.

Typical usage scenarios for energy storage and electric vehicles (EVs) require lithium-ion batteries (LIBs) to operate under extreme conditions, including varying temperatures, high charge/discharge rates, and various depths of charge and discharge, while also fulfilling vehicle-to-grid (V2G) interaction requirements. This study empirically investigates the impact of ambient temperature, charge/discharge rate, and charge/discharge cut-off voltage on the capacity degradation rate and internal resistance growth of 18,650 commercial LIBs. The charge/discharge rate was found to have the most significant influence on these parameters, particularly the charging rate. These insights contribute to a better understanding of the risks associated with low-temperature aging and can aid in the prevention or mitigation of safety incidents.