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Driven by global energy transformation and the progress of artificial intelligence technology, traditional automotive engineering is undergoing profound changes. Transportation is rapidly advancing toward electrification and intelligence. Against this background, this paper identifies three emerging paradigms for the development of electric vehicles: Heart Revolution, Brain Evolution, and Network Integration. This paper points out that automobiles are evolving from traditional one-way energy consumers to dynamic energy nodes in smart grids. With the support of artificial intelligence technology, the role of automobiles is also shifting from a simple means of transportation to an intelligent mobile terminal. At the same time, this paper focuses on analyzing the application of the integration theory of “Four Networks and Four Flows” in automobile upgrading. The theory does not focus on the optimization of a single node unit but emphasizes a systematic perspective to improve overall performance and support sustainable development. This paper suggests that the development of the automobile industry must be deeply integrated with the humanity world, information world and physical world. By building a five-in-one architecture of “Human–Vehicle–Road–Cloud–Satellite”, the automobile industry could follow a practical pathway toward coordinated development. At the same time, breakthroughs in core technologies such as solid-state batteries and wide-bandgap semiconductors are also imminent. This paper aims to provide a sustainable and high-performance automobile development path and integrate the concept of human-oriented design into it. Meanwhile, China’s new energy vehicle industry is used as a representative context to illustrate its engineering and industrial implementation.

The global prevalence of gestational diabetes mellitus (GDM) is increasing, posing significant health risks to both mothers and infants. Visceral adipose tissue-derived serine protease inhibitor (Vaspin) has been identified as a potential insulin sensitizer that may mitigate insulin resistance (IR). However, the related mechanism by which Vaspin improves IR in patients with GDM remains unclear. This study aims to investigate whether Vaspin ameliorates IR in GDM via modulation of the ROS/eNOS/NO signaling pathway. Clinical samples from 58 pregnant women were collected and categorized into GDM and control (G) groups. Binary logistic regression analysis revealed significant associations between Vaspin, IR, and GDM. A GDM rat model was established using 50 female Sprague-Dawley (SD) rats, divided into GDM and G groups. Fasting blood glucose (FBG), fasting insulin (FINS), and Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) levels were measured using ELISA and steady-state model evaluation. Vaspin intervention significantly reduced FBG, FINS, and HOMA-IR levels in the GDM group, while L-NAME, an endothelial nitric oxide synthase (eNOS) inhibitor, blocked these effects. INS-1 cells were used to establish a high-glucose model, and laser confocal microscopy, ELISA, and Griess reagent were employed to detect reactive oxygen species (ROS), eNOS, and nitric oxide (NO) levels. Exogenous Vaspin administration improved ROS, eNOS, and NO levels, but these effects were inhibited by L-NAME. Collectively, these results propose a model in which the protective effect of Vaspin against insulin resistance in GDM may be mediated, at least in part, through the ROS/eNOS/NO pathway.

Background: Previous studies reflect reduced morbidity and mortality with intensive blood glucose control in critically ill patients. Unfortunately, implementation of such protocols has proved challenging. This study evaluated the degree of glucose control using manual paper-based vs computer-based insulin protocols in a trauma intensive care unit. Methods: Of 1455 trauma admissions from May 31 to December 31, 2005, a cohort of 552 critically ill patients met study entry criteria. The patients received intensive blood glucose management with IV insulin infusions. Using Fisher's exact test, the authors compared patients managed with a computerized protocol vs a paper-based insulin protocol with respect to the portion of glucose values in a target range of 80–110 mg/dL, the incidence of hyperglycemia (≥150 mg/dL), and the incidence of hypoglycemia (≤40 mg/dL). Results: Three hundred nine patients were managed with a manual paper-based protocol and 243 were managed with a computerized protocol. The total number of blood glucose values across both groups was 21,178. Mean admission glucose was higher in the computer-based protocol group (170 vs 152 mg/dL; p < .001, t-test). Despite this finding by Fisher's exact test, glucose control was superior in the computerized group; a higher portion of glucose values was in range 80–110 mg/dL (41.8% vs 34.0%; p < .001), less hyperglycemia occurred (12.8% vs 15.1%; p < .001), and less hypoglycemia occurred (0.2% vs 0.5%; p < .001). Conclusions: A computerized insulin titration protocol improves glucose control by (1) increasing the percentage of glucose values in range, (2) reducing hyperglycemia, and (3) reducing severe hypoglycemia. For a carefully defined cohort of 552 critically ill, ventilated trauma patients, a computerized insulin glycemia control protocol was compared to a previous manual protocol. Targeting 80–110 mg/dL, the computerized protocol significantly reduced hyperglycemia, with fewer hypoglycemic episodes.

Intensive insulin therapy has widely and rapidly been adopted as the standard of care for the treatment of hyperglycemia in the intensive care unit (ICU). Variability in blood glucose is increasingly recognized as an important factor in outcomes in the chronic diabetic in addition to hemoglobin A1C. We tested the hypothesis that measures of blood glucose variability would be associated with mortality in the surgical ICU. A retrospective analysis of a cohort of ventilated, critically ill surgical and trauma ICU patients placed on an automated insulin protocol was performed. Blood glucose (BG) variability was measured by comparing standard deviation, per[4cut] centile values, successive changes in blood glucose, and by calculating the triangular index for various glucose-related indices. Eight hundred and fifty-eight patients had 46,474 blood glucose and insulin dose data points. One hundred and twenty-one patients died for an overall mortality rate of 14 per cent. Several measures of blood glucose variability (maximum successive change in BG and the triangular index) were different between the groups despite similar mean BG between survivors (117 mg/dL) and nonsurvivors (118 mg/dL). Increased blood glucose variability is asso[4cut] ciated with mortality in the surgical ICU. Further studies should focus on the demographic, clinical, and genetic factors responsible for this observation and identify strategies to minimize BG variability. [PUBLICATION ABSTRACT]

Intensive insulin therapy has widely and rapidly been adopted as the standard of care for the treatment of hyperglycemia in the intensive care unit (ICU). Variability in blood glucose is increasingly recognized as an important factor in outcomes in the chronic diabetic in addition to hemoglobin A1C. We tested the hypothesis that measures of blood glucose variability would be associated with mortality in the surgical ICU. A retrospective analysis of a cohort of ventilated, critically ill surgical and trauma ICU patients placed on an automated insulin protocol was performed. Blood glucose (BG) variability was measured by comparing standard deviation, percentile values, successive changes in blood glucose, and by calculating the triangular index for various glucose-related indices. Eight hundred and fifty-eight patients had 46,474 blood glucose and insulin dose data points. One hundred and twenty-one patients died for an overall mortality rate of 14 per cent. Several measures of blood glucose variability (maximum successive change in BG and the triangular index) were different between the groups despite similar mean BG between survivors (117 mg/dL) and nonsurvivors (118 mg/dL). Increased blood glucose variability is associated with mortality in the surgical ICU. Further studies should focus on the demographic, clinical, and genetic factors responsible for this observation and identify strategies to minimize BG variability.

Puli center project protects the original soil with pipe roof technology through combining the field analysis and finite element modeling while constructing the connecting passage of foundation pit under the existing optical fiber cable, so as to avoid the optical fiber cable from producing too big settlement to cause the adverse effect, and then constructs the connecting passage of foundation pit. After field monitoring, the maximum settlement of pipeline conforms to the deformation control standard of optical fiber cable, and this technology has certain innovation, which can provide reference for the similar project.

The clinical diagnosis of neonatal sepsis is preceded by abnormal heart rate (HR) characteristics of transient decelerations and reduced variability, which intuitively appear to be more nonstationary than normal HR variability. Our goals were to investigate stationarity of HR, and to devise measures useful for early diagnosis of neonatal sepsis. In this context, we define non-stationarity to be present when the observed data differ from surrogate data generated by stationary Gaussian noise with arbitrary linear correlations. We devised statistical methods for determining stationarity of HR data based on the two-sample Kolmogorov-Smirnov (KS) test. We compared distributions of KS distances between small sample epochs from clinical data with those of isospectral surrogates and of surrogates generated using the amplitude-adjusted Fourier transform technique, reasoning that they should differ significantly for nonstationary data. We found significant evidence of non-stationarity for records longer than 1 min. We developed new HR measures based on the empirical cumulative distribution function (ECDF) that are highly significantly associated with sepsis, but are not correlated with HR measures such as moments or sample entropy. We conclude that neonatal HR data cannot be assumed to be stationary, and become even less stationary prior to sepsis.

Heart rate (HR) analysis has been regarded as one of the best ways to assess well-being of human beings. In this dissertation, two projects have been included. The first one is to predict fetal distress through fetal heart rate (FHR) monitoring during labor. The second one is to explore different stationarity properties of neonatal HR toward early diagnosis of neonatal sepsis. Project 1. Continuous monitoring of FHR during labor is based on the clinical experience that fetal hypoxia causes loss of FHR variation and the occurrence of decelerations late during uterine contraction. However, improved fetal outcome has not been shown for monitored fetuses and the benefit of electronic fetal monitoring (EFM) has been questioned. It was reasoned that this might be due to the qualitative nature of the current subjective interpretation of FHR records and to the large degree of intra- and inter-observer disagreement. Therefore, this project aimed to test the hypothesis that features important to clinician's interpretations might be used in a predictive diagnostic model. Project 2. The clinical diagnosis of neonatal sepsis is preceded by abnormal heart rate characteristics of transient decelerations and reduced variability, which intuitively appear to be more non-stationary than normal heart rate variability (HRV). In this context, non-stationarity was defined to be present when the observed data differed from surrogate data generated by stationarity Gaussian processes with arbitrary linear correlation. The goals were to investigate stationarity of HR, and to devise measures useful for early diagnosis of neonatal sepsis. The results of the work showed that HRV analysis was able to quantify the HR features that might be useful to predict or early diagnose fetal distress and neonatal sepsis clinically. (Abstract shortened by UMI.)

In nature, the dynamic contraction and relaxation of muscle in animals provide the essential force and deformation necessary for diverse locomotion, enabling them to navigate and overcome environmental challenges. However, most autonomous robotic systems still rely on conventional rigid motors, lacking the adaptability and resilience of muscle-like actuators. Existing artificial muscles, while promising for soft actuation, often require demanding operational conditions that hinder their use in onboard-powered small autonomous systems. In this work, we present the Elasto-Electromagnetic mechanism, an electromagnetic actuation strategy tailored for soft robotics. By structuring simple elastomeric materials, this mechanism mimics key features of biological muscle contraction and optimizes actuation properties. It achieves significant output force (~210 N/kg), large contraction ratio (up to 60%), rapid response (60 Hz), and low-voltage operation (<4 volts) within a robust, miniaturized framework. It also enhances energy efficiency by maintaining stable states without continuous power input, similar to catch muscles in mollusks. The resulting insect-scale soft robots, therefore, demonstrate adaptive crawling, swimming, and jumping, autonomously navigating open-field environments. This muscle-inspired electromagnetic mechanism, facilitated by elastic structural variations, expands the autonomy and functional capabilities of small-scale soft robots, with potential applications in rescue and critical signal detection. The authors develop an elasto-electromagnetic mechanism for small autonomous robots, mimicking muscle contraction using elastomeric materials and magnetic forces. The system achieves significant force, large contraction ratios, rapid response, and low-voltage operation, enhancing robot adaptability and efficiency.

Two calcite LA-ICP-MS U-Pb ages of 534 ± 26 Ma (MSWD = 5.9) and 456 ± 43 Ma (MSWD = 3.8) were obtained from the Nanfen Formation, Xihe Group in the southern Liaoning Province, northeastern China, which significantly postdate the theoretical depositional age of sampling horizon. This means they represent timing of post-depositional hydrothermal event possibly induced by synchronous far-field magmatism in the South Qinling. Occurrence of common Pb enriched muddy components coupled with input of “mantle”-like common Pb could account for the relatively low U contents and high common Pb contents in the dated muddy carbonates. We recommend that micro-domains of carbonates are prescreened by rapid in situ carbonate U-Pb geochronology to demonstrate whether they are of primary or secondary origin before utilizing them for chemostratigraphic study.