Decreased resting-state functional connectivity and brain network abnormalities in the prefrontal cortex of elderly patients with Parkinson's disease accompanied by depressive symptoms.

This study aimed to explore the brain network characteristics in elderly patients with Parkinson's disease (PD) with depressive symptoms. Thirty elderly PD patients with depressive symptoms (PD-D) and 26 matched PD patients without depressive symptoms (PD-NOD) were recruited based on HAMD-24 with a cut-off of 7. The resting-state functional connectivity (RSFC) was conducted by 53-channel functional near-infrared spectroscopy (fNIRS). There were no statistically significant differences in MMSE scores, disease duration, Hoehn-Yahr stage, daily levodopa equivalent dose, and MDS-UPDRS III between the two groups. However, compared to the PD-NOD group, the PD-D group showed significantly higher MDS-UPDRS II, HAMA-14, and HAMD-24. The interhemispheric FC strength and the FC strength between the left dorsolateral prefrontal cortex (DLPFC-L) and the left frontal polar area (FPA-L) was significantly lower in the PD-D group (FDR p < 0.05). As for graph theoretic metrics, the PD-D group had significantly lower degree centrality (aDc) and node efficiency (aNe) in the DLPFC-L and the FPA-L (FDR, p < 0.05), as well as decreased global efficiency (aEg). Pearson correlation analysis indicated moderate negative correlations between HAMD-24 scores and the interhemispheric FC strength, FC between DLPFC-L and FPA-L, aEg, aDc in FPA-L, aNe in DLPFC-L and FPA-L. In conclusion, PD-D patients show decreased integration and efficiency in their brain networks. Furthermore, RSFC between DLPFC-L and FPA-L regions is negatively correlated with depressive symptoms. These findings propose that targeting DLPFC-L and FPA-L regions via non-invasive brain stimulation may be a potential intervention for alleviating depressive symptoms in elderly PD patients.

Enhancing Few-Shot Learning in Lightweight Models via Dual-Faceted Knowledge Distillation.

In recent computer vision research, the pursuit of improved classification performance often leads to the adoption of complex, large-scale models. However, the actual deployment of such extensive models poses significant challenges in environments constrained by limited computing power and storage capacity. Consequently, this study is dedicated to addressing these challenges by focusing on innovative methods that enhance the classification performance of lightweight models. We propose a novel method to compress the knowledge learned by a large model into a lightweight one so that the latter can also achieve good performance in few-shot classification tasks. Specifically, we propose a dual-faceted knowledge distillation strategy that combines output-based and intermediate feature-based methods. The output-based method concentrates on distilling knowledge related to base class labels, while the intermediate feature-based approach, augmented by feature error distribution calibration, tackles the potential non-Gaussian nature of feature deviations, thereby boosting the effectiveness of knowledge transfer. Experiments conducted on MiniImageNet, CIFAR-FS, and CUB datasets demonstrate the superior performance of our method over state-of-the-art lightweight models, particularly in five-way one-shot and five-way five-shot tasks.

Associations of Triglycerides and Atherogenic Index of Plasma with Brain Structure in the Middle-Aged and Elderly Adults.

Triglyceride (TG) and atherogenic index of plasma (AIP) have been acknowledged to be risk factors for vascular insults, but their impacts on the brain system remain elusive. To fill in some gaps, we investigated associations of TG and AIP with brain structure, leveraging the UK Biobank database. TG and high-density lipoprotein cholesterol (HDL-C) were examined at baseline and AIP was calculated as log (TG/HDL-C). We build several linear regression models to estimate associations of TG and AIP with volumes of brain grey matter phenotypes. Significant inverse associations of TG and AIP with volumes of specific subcortical traits were observed, among which TG and AIP were most significantly associated with caudate nucleus (TG: ß [95% confidence interval CI] = -0.036 [-0.051, -0.022], AIP: -0.038 [-0.053, -0.023]), thalamus (-0.029 [-0.042, -0.017], -0.032 [-0.045, -0.019]). Higher TG and AIP were also considerably related with reduced cortical structure volumes, where two most significant associations of TG and AIP were with insula (TG: -0.035 [-0.048, -0.022], AIP: -0.038 [-0.052, -0.025]), superior temporal gyrus (-0.030 [-0.043, -0.017], -0.033 [-0.047, -0.020]). Modification effects of sex and regular physical activity on the associations were discovered as well. Our findings show adverse associations of TG and AIP with grey matter volumes, which has essential public health implications for early prevention in neurodegenerative diseases.

The Identification of Goat KCNJ15 Gene Copy Number Variation and Its Association with Growth Traits.

(1) Background: Copy number variation (CNV) is a critical component of genome structural variation and has garnered significant attention. High-throughput screening of the KCNJ15 gene has revealed a correlation between the CNV region and the growth traits of goats. We aimed to identify the CNV of the KCNJ15 gene in five goat breeds and analyze its association with growth characteristics. (2) Methods: We utilized 706 goats from five breeds: Guizhou black goat (GZB), Guizhou white goat (GZW), Bohuai goat (BH), Huai goat (HH), and Taihang goat (TH). To evaluate the number of copies of the KCNJ15 gene using qPCR, we analyzed the correlation between the CNV and growth characteristics and then used a universal linear model. The findings revealed variations in the distribution of different copy number types among the different goat breeds. (3) Results: Association analysis revealed a positive influence of the CNV in the KCNJ15 gene on goat growth. In GZB, individuals with duplication types exhibited superior performance in terms of cannon bone circumference (p < 0.05). In HH, individuals with duplication types exhibited superior performance in terms of body slanting length (p < 0.05). Conversely, normal TH demonstrated better body height and body weight (p < 0.05), while in GZW, when CN = 3, it performed better than other types in terms of body weight and chest circumference (p < 0.05). However, in BH, it had no significant effect on growth traits. (4) Conclusions: We confirmed that the CNV in the KCNJ15 gene significantly influences the growth characteristics of four distinct goat breeds. The correlation between KCNJ15 gene CNVs and goat growth traits offers valuable insights to breeders, enabling them to employ precise and efficient breeding methods that enhance livestock welfare, productivity, and overall economic benefits in the industry.

Transcriptomics and metabolomics of blood, urine and ovarian follicular fluid of yak at induced estrus stage.

To gain a deeper understanding of the metabolic differences within and outside the body, as well as changes in transcription levels following estrus in yaks, we conducted transcriptome and metabolome analyses on female yaks in both estrus and non-estrus states. The metabolome analysis identified 114, 13, and 91 distinct metabolites in urine, blood, and follicular fluid, respectively. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis highlighted an enrichment of pathways related to amino acid and lipid metabolism across all three body fluids. Our transcriptome analysis revealed 122 differentially expressed genes within microRNA (miRNA) and 640 within long non-coding RNA (lncRNA). Functional enrichment analysis of lncRNA and miRNA indicated their involvement in cell signaling, disease resistance, and immunity pathways. We constructed a regulatory network composed of 10 lncRNAs, 4 miRNAs, and 30 mRNAs, based on the targeted regulation relationships of the differentially expressed genes. In conclusion, the accumulation of metabolites such as amino acids, steroids, and organic acids, along with the expression changes of key genes like miR-129 during yak estrus, provide initial insights into the estrus mechanism in yaks.

Tailoring nonuniform local orbital angular momentum density.

As is well known, a light beam with a helical phase carries an optical orbital angular momentum (OAM), which can cause the orbital motion of trapped microparticles around the beam axis. Usually, the speed of the orbital motion is uniform along the azimuthal direction and depends on the amount of OAM and the light intensity. Here, we present the reverse customized method to tailor the nonuniform local OAM density along the azimuthal direction of the focal field, which has a hybrid polarization distribution and maintains a doughnut-shaped intensity profile. Theoretical analysis and experimental results about the orbital motion of the trapped polystyrene sphere show that the nonuniform local OAM density can be tailored by manipulating the polarization states of the focal field. Our results provide an ingenious way to control the local tangential optical force and the speed of the orbital motion of particles driven by the local OAM density and will promote exciting possibilities for exploring ways to control the mechanical dynamics of microparticles in optical trapping and microfluidics.

Automatic measurement system for large-aperture-angle non-holonomic spherical stitching with laser differential confocal interference.

In response to the urgent need for highly precise and efficient stitching measurements of large-aperture-angle non-holonomic spherical surfaces, a differential confocal interference automatic stitching measurement system for large-aperture-angle non-holonomic spherical surfaces was developed. The system realizes precise positioning of the confocal position through differential confocal precise focusing technology. Through the stitching model, coordinate transformation and error compensation were performed on subaperture data, and the stitching measurement of the spherical surface shape was realized. The positions and postures of the tested samples were adjusted automatically using an automatic adjustment workbench. The stitching measurement accuracy of this measurement system can attain 0.0013λ, relative error can attain 1.36%, and measurement time for eight subaperture stitching is 6 min. This system achieves automatic and rapid adjustment of large-aperture-angle spherical elements and high-precision, nondestructive, fast, and automatic measurement of surface stitching.

Impact of STAT5A-CNVs on growth traits in Chinese beef cattle breeds.

CNVs, which are a type of structural variation, make a substantial impact on diverse characteristics in multiple species. Q-PCR and data association analysis were used for STAT5A gene copy in this study. This study aimed to investigate the copy number variation (CNV) of the STAT5A gene in seven Chinese cattle breeds, namely Qinchuan cattle, Xianan cattle, Yunling cattle, Ji'an cattle, Jiaxian Red cattle, Qaidam cattle, and Guyuan yellow cattle. Blood samples were collected for CNV typing, and the correlation between CNV type and growth traits was analyzed using SPSS 23.0 software and ANOVA. The findings revealed variations in the distribution of different copy number types among the different cattle breeds. Furthermore, association analysis demonstrated a positive impact of CNV in the STAT5A gene on cattle growth: in the JX, individuals with duplication types exhibited superior performance in terms of rump length (P < 0.05). Conversely, normal GY cattle demonstrated better body height and abdomen circumference (P < 0.05), while QD cattle exhibited a significant correlation between weight and body length with normal individuals (P < 0.05). Moreover, QC bovine duplication individuals outperformed other types, with copy number variation significantly associated with chest depth, chest width, and body length (P < 0.05). The results validate the correlation between copy number variation (CNV) of the STAT5A gene and growth characteristics in five different cattle breeds, providing a reliable benchmark for the purpose of cattle breeding.

Therapeutic effects of high-dose vitamin C supplementation in patients with COVID-19: a meta-analysis.

CONTEXT: Coronavirus disease 2019 (COVID-19) could induce the "cytokine storm" due to overactivation of immune system and accompanied by acute respiratory distress syndrome as a serious complication. Vitamin C has been effective in improving lung function of patients by reducing inflammation. OBJECTIVE: The aim was to explore the therapeutic effects of high-dose vitamin C supplementation for patients with COVID-19 using meta-analysis. DATA SOURCES: Published studies were searched from PubMed, Cochrane Library, Web of Science, EMBASE, and China National Knowledge Infrastructure databases up to August 2022 using the terms "vitamin C" and "COVID-19". Data analyses were performed independently by 2 researchers using the PRISMA guidelines. DATA EXTRACTION: Heterogeneity between the included studies was assessed using I2 statistics. When I2 ≥50%, the random-effects model was used; otherwise, a fixed-effects model was applied. Stata 14.0 software was used to pool data by standardized mean differences (SMDs) with 95% CIs or odds ratios (ORs) with 95% CIs. DATA ANALYSIS: The 14 studies had a total of 751 patients and 1583 control participants in 7 randomized controlled trials and 7 retrospective studies. The vitamin C supplement significantly increased ferritin (SMD = 0.272; 95% CI: 0.059 to 0.485; P = 0.012) and lymphocyte count levels (SMD = 0.376; 95% CI: 0.153 to 0.599; P = 0.001) in patients with COVID-19. Patients administered vitamin C in the length of intensive care unit staying (SMD = 0.226; 95% CI: 0.073 to 0.379; P = 0.004). Intake of vitamin C prominently alleviate disease aggravation (OR = 0.344, 95%CI: 0.135 to 0.873, P = 0.025). CONCLUSIONS: High-dose vitamin C supplementation can alleviate inflammatory response and hinder the aggravation of COVID-19.

Potential Ability of Probiotics in the Prevention and Treatment of Colorectal Cancer.

Colorectal cancer (CRC) is the third most common cancer in the world, and its incidence rate and mortality are on the rise in many countries. In recent years, with the improvement of economic conditions, people's living habits have changed, including lack of physical activity, poor diet patterns and circadian rhythm disorder. These risk factors can change the colon environment and the composition of intestinal microbiota. This state is called intestinal imbalance, which increases the risk of cancer. Probiotics, a class of microorganisms that help maintain gut microbial homeostasis and alleviate dysbiosis, may help prevent inflammation and colorectal cancer. These probiotics inhibit or ameliorate the effects of dysbiosis through the production of short-chain fatty acids (SCFAs), modulation of immunity, maintenance of the intestinal epithelial barrier, pro-apoptotic mechanisms, and other mechanisms. This review aims to explain the interaction between probiotics, the gut microenvironment and the gut microbiota, and summarize reports on the possibility of probiotics in the prevention and treatment of colorectal cancer.

Research on the anti-ageing mechanism of Prunella vulgaris L.

Prunella vulgaris L. (P. vulgaris) has long been considered to have antipyretic, analgesic and anti-inflammatory effects, lowering blood lipids and pressure. Many studies show that in addition to the traditional telomere attrition, DNA damage and epigenetic changes, immunosenescence is also a new possibility to explore the mechanism of ageing. Therefore, this herb may have potential anti-ageing effects. Typically, there are a series of markers that identify senescent cells, such as superoxide dismutase (SOD)2, an inhibitor of CDK4 (p16INK4A), tumor necrosis factor (TNF)-α, immune cells number, proliferation, and nuclear abnormalities. These changes rarely present in young tissues, while greatly increasing in response to ageing. Firstly, the ageing model of the Institute of Cancer Research (ICR) mouse was established by D-galactose subcutaneous injection. Then, SOD2, p16INK4A and TNF-α were detected by quantitative Real-time PCR (qPCR), Western Blot (WB) and Enzyme-Linked Immunosorbent Assay (ELISA). Simultaneously, senescent cells in livers were stained by hematoxylin and eosin (HE). The viability of splenocytes was detected by Cell Counting Kit-8(CCK-8). The difference in specific immune cells (NK cells, B lymphocytes and T lymphocytes) was detected by flow cytometry. Both low (100 mg/kg) and high (300 mg/kg) concentrations of P. vulgaris treated ageing ICR mice show anti-ageing alterations, such as p16INK4A decreased approximately 1/2 and SOD2 tripled in livers, TNF-α decreased from 1 to 0.6 in plasma, and T cells increased from 0.09 to 0.19%. Compared with the ageing group, the spleen cells in the Prunella-treated group had stronger proliferation ability. Thus, P. vulgaris could have an anti-ageing effect. This is the first study to demonstrate the anti-ageing effect of P. vulgaris. It may also be capable of preventing a variety of age-related diseases.

Predicting the fatigue in Parkinson's disease using inertial sensor gait data and clinical characteristics.

Objectives: The study aimed to analyze the clinical features and gait characteristics of patients with Parkinson's disease (PD) who also suffer from fatigue and to develop a model that can help identify fatigue states in the early stages of PD. Methodology: A total of 81 PD patients have been enrolled for the Parkinson's Fatigue Scale (PFS-16) assessment and divided into two groups: patients with or without fatigue. Neuropsychological assessments of the two groups, including motor and non-motor symptoms, were collected. The patient's gait characteristics were collected using a wearable inertial sensor device. Results: PD patients who experienced fatigue had a more significant impairment of motor symptoms than those who did not, and the experience of fatigue became more pronounced as the disease progressed. Patients with fatigue had more significant mood disorders and sleep disturbances, which can lead to a poorer quality of life. PD patients with fatigue had shorter step lengths, lower velocity, and stride length and increased stride length variability. As for kinematic parameters, PD patients with fatigue had lower shank-forward swing max, trunk-max sagittal angular velocity, and lumbar-max coronal angular velocity than PD patients without fatigue. The binary logistic analysis found that Movement Disorder Society-Unified Parkinson's Disease Rating Scale-I (MDS-UPDRS-I) scores, Hamilton Depression Scale (HAMD) scores, and stride length variability independently predicted fatigue in PD patients. The area under the curve (AUC) of these selected factors in the receiver operating characteristic (ROC) analysis was 0.900. Moreover, HAMD might completely mediate the association between Hamilton Anxiety Scale (HAMA) scores and fatigue (indirect effect: ß = 0.032, 95% confidence interval: 0.001-0.062), with a percentage of mediation of 55.46%. Conclusion: Combining clinical characteristics and gait cycle parameters, including MDS-UPDRS-I scores, HAMD scores, and stride length variability, can identify PD patients with a high fatigue risk.

Intratumoural microbiota: from theory to clinical application.

Cancer is a major cause of high morbidity and mortality worldwide. Several environmental, genetic and lifestyle factors are associated with the development of cancer in humans and result in suboptimal treatment. The human microbiota has been implicated in the pathophysiological process of cancer and has been used as a diagnostic, prognostic and risk assessment tool in cancer management. Notably, both extratumoural and intratumoural microbiota are important components of the tumor microenvironment, subtly influencing tumorigenesis, progression, treatment and prognosis. The potential oncogenic mechanisms of action of the intratumoural microbiota include induction of DNA damage, influence on cell signaling pathways and impairment of immune responses. Some naturally occurring or genetically engineered microorganisms can specifically accumulate and replicate in tumors and then initiate various anti-tumor programs, ultimately promoting the therapeutic effect of tumor microbiota and reducing the toxic and side effects of conventional tumor treatments, which may be conducive to the pursuit of accurate cancer treatment. In this review, we summarise evidence revealing the impact of the intratumoural microbiota on cancer occurrence and progress and potential therapeutic and diagnostic applications, which may be a promising novel strategy to inhibit tumor development and enhance therapeutic efficacy. Video Abstract.

Molecular characterization of a cation-dependent mannose-6-phosphate receptor gene in Crassostrea hongkongensis and its responsiveness in Vibrio alginolyticus infection.

The cation-dependent mannose-6-phosphate receptor (CD-M6PR) is a P-type lectin that plays a crucial role in lysosomal enzyme transport, bacterial resistance, and viral entry. In this study, we cloned and analyzed the ORF of the CD-M6PR gene from Crassostrea hongkongensis and named it ChCD-M6PR. We analyzed the nucleotide and amino acid sequence of ChCD-M6PR, its tissue expression pattern and immune response to Vibrio alginolyticus. Our results showed that the ORF of ChCD-M6PR was 801 bp long and encoded a protein of 266 amino acids with a signal peptide at the N-terminus, as well as Man-6-P_recep, ATG27 and transmembrane structural domains. Phylogenetic analysis indicated that Crassostrea hongkongensis shared the highest similarity with Crassostrea gigas in the terms of CD-M6PR. The ChCD-M6PR gene was found to be expressed in various tissues, with the highest expression observed in the hepatopancreas and the lowest in the hemocytes by the fluorescence quantitative PCR. Furthermore, the expression of ChCD-M6PR gene was significantly up-regulated for a short time in response to Vibrio alginolyticus infection in the gill and hemocytes, while it was down-regulated in the gonads. The expression patterns of ChCD-M6PR also varied in the other tissues. The 96 h cumulative mortality rate of Crassostrea hongkongensis infected with Vibrio alginolyticus after knockdown the ChCD-M6PR gene was significantly higher. Overall, our findings suggests that ChCD-M6PR plays a crucial role in the immune response of Crassostrea hongkongensis to Vibrio alginolyticus infection, and its tissue-specific expression patterns may be indicatitive of varied immune responses across tissues.

Intelligent Microsystem for Sound Event Recognition in Edge Computing Using End-to-End Mesh Networking.

Wireless acoustic sensor networks (WASNs) and intelligent microsystems are crucial components of the Internet of Things (IoT) ecosystem. In various IoT applications, small, lightweight, and low-power microsystems are essential to enable autonomous edge computing and networked cooperative work. This study presents an innovative intelligent microsystem with wireless networking capabilities, sound sensing, and sound event recognition. The microsystem is designed with optimized sensing, energy supply, processing, and transceiver modules to achieve small size and low power consumption. Additionally, a low-computational sound event recognition algorithm based on a Convolutional Neural Network has been designed and integrated into the microsystem. Multiple microsystems are connected using low-power Bluetooth Mesh wireless networking technology to form a meshed WASN, which is easily accessible, flexible to expand, and straightforward to manage with smartphones. The microsystem is 7.36 cm3 in size and weighs 8 g without housing. The microsystem can accurately recognize sound events in both trained and untrained data tests, achieving an average accuracy of over 92.50% for alarm sounds above 70 dB and water flow sounds above 55 dB. The microsystems can communicate wirelessly with a direct range of 5 m. It can be applied in the field of home IoT and border security.

Impact of lane-changing behavior on traffic emissions of road sections in multi-dimensional mixed traffic flow environment.

This study analyzed the effect of lane-changing behavior on traffic flow emissions and energy consumption of road sections in fuel vehicle-battery electric vehicle (FV-BEV) and human-driven vehicle-cooperative adaptive cruise control (HDV-CACC) multi-dimensional mixed traffic flow environments. Based on the traditional energy consumption model, a multi-dimensional mixed traffic flow energy consumption model was established by considering the BEV and CACC penetration rates. The microscopic traffic flow theory approach was used to analyze lane-changing behavior and the influencing mechanism of lane-changing behavior on the energy consumption of multi-dimensional mixed traffic flow, and MATLAB was used for the experimental simulation. The lane-changing behavior of the leading vehicle had a negative impact on the energy consumption of road segment traffic flow. Within the 95% effective impact range, the average energy consumption of traffic flow with respect to lane-changing behavior was 7.8% higher than that of the following traffic flow. The BEV penetration rate was beneficial for reducing the energy consumption of mixed traffic flow. At an economic velocity, the energy consumption of homogeneous BEV traffic flow was only 58.3% of that of homogeneous FV traffic flow. The CACC penetration rate could increase the traffic flow toughness. When the BEV penetration rate was constant, the higher the CACC penetration rate, the smaller the impact of lane-changing behavior on emissions. When traffic flow was completely transformed to homogeneous CACC traffic flow, lane-changing behavior only increased the overall energy consumption of the traffic flow by 4.99%, which was lower than the average level. Consequently, the promotion of BEV and CACC can improve the impact of traffic emissions on air pollution. When CACC penetration is low, reducing unnecessary lane-changing behavior to ensure the stability of traffic flow is also an effective way to reduce emissions.Implications: Multi-dimensional mixed traffic flow energy consumption model is proposed.CACC penetration rate, BEV penetration rate and lane-changing behavior will change traffic energy consumption. In this paper, different influencing factors are analyzed one by one.It provides a theoretical basis for relevant departments of traffic management to optimize vehicle emissions and traffic organization.

Novel m7G-related lncRNA signature for predicting overall survival in patients with gastric cancer.

Presenting with a poor prognosis, gastric cancer (GC) remains one of the leading causes of disease and death worldwide. Long non-coding RNAs (lncRNAs) regulate tumor formation and have been long used to predict tumor prognosis. N7-methylguanosine (m7G) is the most prevalent RNA modification. m7G-lncRNAs regulate GC onset and progression, but their precise mechanism in GC is unclear. The objective of this research was the development of a new m7G-related lncRNA signature as a biomarker for predicting GC survival rate and guiding treatment. The Cancer Genome Atlas database helped extract gene expression data and clinical information for GC. Pearson correlation analysis helped point out m7G-related lncRNAs. Univariate Cox analysis helped in identifying m7G-related lncRNA with predictive capability. The Lasso-Cox method helped point out seven lncRNAs for the purpose of establishing an m7G-related lncRNA prognostic signature (m7G-LPS), followed by the construction of a nomogram. Kaplan-Meier analysis, univariate and multivariate Cox regression analysis, calibration plot of the nomogram model, receiver operating characteristic curve and principal component analysis were utilized for the verification of the risk model's reliability. Furthermore, q-PCR helped verify the lncRNAs expression of m7G-LPS in-vitro. The study subjects were classified into high and low-risk groups based on the median value of the risk score. Gene enrichment analysis confirmed the constructed m7G-LPS' correlation with RNA transcription and translation and multiple immune-related pathways. Analysis of the clinicopathological features revealed more progressive features in the high-risk group. CIBERSORT analysis showed the involvement of m7G-LPS in immune cell infiltration. The risk score was correlated with immune checkpoint gene expression, immune cell and immune function score, immune cell infiltration, and chemotherapy drug sensitivity. Therefore, our study shows that m7G-LPS constructed using seven m7G-related lncRNAs can predict the survival time of GC patients and guide chemotherapy and immunotherapy regimens as biomarker.

Research on Cold Start of Proton-Exchange Membrane Fuel Cells Based on Model Predictive Control.

The cold start of fuel cells limits their wide application. Since the water produced by fuel cells takes up more space when it freezes, it may affect the internal structure of the stack, causing collapse and densification of the pores inside the catalytic layer. This paper mainly analyzes the influence of different startup strategies on the stack cold start, focusing on the change in the stack temperature and the ice volume fraction of the catalytic layer. When designing a startup strategy, it is important to focus not only on the optimization of the startup time, but also on the principle of minimizing the damage to the stack. A lumped parameter cold-start model was constructed, which was experimentally verified to have a maximum error of 8.9%. On this basis, a model predictive control (MPC) algorithm was used to control the starting current. The MPC cold-start strategy reached the freezing point at 17 s when the startup temperature was -10 °C, which is faster than other startup strategies. Additionally, the time to ice production was controlled to about 20 s. Compared with the potentiostatic strategy and maximum power strategy, MPC is optimal and still has great potential for further optimization.