The risk factors associated with traumatic subdural effusion for patients with traumatic brain injury who did not undergo decompressive craniectomy.

PURPOSE: The main aim of this study was to investigate the risk factors of traumatic subdural effusion (TSE) development in traumatic brain injury (TBI) patients who did not undergo decompressive craniectomy (DC). METHODS: This is a retrospective study based on a database of patients treated in a single institution from January 2020 to January 2022. The clinical and demographic characteristics of the enrolled patients, including gender, age, Glasgow Coma Scale score at admission, characteristics of the initial CT scan on admission, mechanism of injury and the mannitol treatment were recorded retrospectively. RESULTS: Two hundred fifty-four patients with TBI who did not receive DC were enrolled in this study. Among them, 78 (30.71%) patients were assigned to the TSE group, while 176 patients (69.29%) without TSE were assigned to the control group. Univariate analysis showed that patients in the TSE group were more likely to be male (p = 0.019), older (p < 0.001), have a subarachnoid haemorrhage (p = 0.016) and have a basal cistern haemorrhage (p = 0.014). Logistic regression analysis identified that older age (odds ratio [OR] = 1.056, p < 0.001), presence of subarachnoid haemorrhage (OR = 2.022, p = 0.018) and presence of basal cistern haemorrhage (OR = 2.861, p = 0.027) were risk factors independently associated with the development of TSE. CONCLUSION: Our results showed that older age, presence of subarachnoid haemorrhage and presence of basal cistern haemorrhage were risk factors independently associated with the development of TSE for TBI patients without DC.

A Dual-Input Neural Network for Online State-of-Charge Estimation of the Lithium-Ion Battery throughout Its Lifetime.

Online state-of-charge (SOC) estimation for lithium-ion batteries is one of the most important tasks of the battery management system in ensuring its operation safety and reliability. Due to the advantages of learning the long-term dependencies in between the sequential data, recurrent neural networks (RNNs) have been developed and have shown their superiority over SOC estimation. However, only time-series measurements (e.g., voltage and current) are taken as inputs in these RNNs. Considering that the mapping relationship between the SOC and the time-series measurements evolves along with the battery degradation, there still remains a challenge for RNNs to estimate the SOC accurately throughout the battery's lifetime. In this paper, a dual-input neural network combining gated recurring unit (GRU) layers and fully connected layers (acronymized as a DIGF network) is developed to overcome the above-mentioned challenge. Its most important characteristic is the adoption of the state of health (SOH) of the battery as the network input, in addition to time-series measurements. According to the experimental data from a batch of LiCoO2 batteries, it is validated that the proposed DIGF network is capable of providing more accurate SOC estimations throughout the battery's lifetime compared to the existing RNN counterparts. Moreover, it also shows greater robustness against different initial SOCs, making it more applicable for online SOC estimations in practical situations. Based on these verification results, it is concluded that the proposed DIGF network is feasible for estimating the battery's SOC accurately throughout the battery's lifetime against varying initial SOCs.

A Digital Twin-Driven Life Prediction Method of Lithium-Ion Batteries Based on Adaptive Model Evolution.

Accurate life prediction and reliability evaluation of lithium-ion batteries are of great significance for predictive maintenance. In the whole life cycle of a battery, the accurate description of the dynamic and stochastic characteristics of life has always been a key problem. In this paper, the concept of the digital twin is introduced, and a digital twin for reliability based on remaining useful cycle life prediction is proposed for lithium-ion batteries. The capacity degradation model, stochastic degradation model, life prediction, and reliability evaluation model are established to describe the randomness of battery degradation and the dispersion of the life of multiple cells. Based on the Bayesian algorithm, an adaptive evolution method for the model of the digital twin is proposed to improve prediction accuracy, followed by experimental verification. Finally, the life prediction, reliability evaluation, and predictive maintenance of the battery based on the digital twin are implemented. The results show the digital twin for reliability has good accuracy in the whole life cycle. The error can be controlled at about 5% with the adaptive evolution algorithm. For battery L1 and L6 in this case, predictive maintenance costs are expected to decrease by 62.0% and 52.5%, respectively.

Therapeutic Effect of Electronic Endoscopic Hematoma Removal on Hypertensive Basal Ganglia Cerebral Hemorrhage Based on Smart Medical Technology.

The medical and health industry has successively experienced three stages of digital medical treatment, local area network medical treatment, and internet medical treatment. With the rapid development of technologies such as the Internet of Things, big data, and artificial intelligence, emerging applications and service models have gradually penetrated into all aspects of the medical and health field. At this point, the informatization development process of the medical industry has entered the stage of smart medical treatment. (Smart medical system is a new medical system that improves users' medical experience and provides users with better services. Due to the cumbersome, complicated, and mechanically rigid environment of the past medical service, there was no uniform standard. In order to create a reliable and open medical service environment, an intelligent medical system came into being.). A diversified technical foundation and smart medical protection, conducive to providing patients with high-quality medical services, are established. This article mainly introduces the analysis of the therapeutic effect of smart medical electronic endoscopic hematoma removal on hypertensive basal ganglia cerebral hemorrhage and aims to inject advanced technology and vitality of smart medical treatment into the treatment of hypertensive basal ganglia cerebral hemorrhage by hematoma removal and help the doctor to treat the patient. This article proposes the research methods of smart medical application in the treatment of hypertensive basal ganglia cerebral hemorrhage with electronic endoscopic hematoma removal, including smart medical overview, intracranial hematoma removal for hypertensive basal ganglia cerebral hemorrhage, and smart medical bioelectric signal classification. The recognition algorithm is used to realize the smart medical application of the electronic endoscopic hematoma removal in the treatment of hypertensive cerebral hemorrhage in the basal ganglia area. The experimental results show that the removal of intracranial hematoma based on smart medicine can effectively improve the removal rate of intracranial hematoma, with a recovery rate of 26.73% and a significant efficiency of 36.49%.

Investigation of Step-Stress Accelerated Degradation Test Strategy for Ultraviolet Light Emitting Diodes.

III-nitride-based ultraviolet light emitting diode (UV LED) has numerous attractive applications in air and water purification, UV photolithography, and in situ activation of drugs through optical stimulus, solid state lighting, polymer curing, and laser surgery. However, the unclear failure mechanisms and uncertainty reliability have limited its application. Therefore, a design of an appropriate reliability test plan for UV LEDs has become extremely urgent. Compared to traditional reliability tests recommended in LED lighting industry, the step-stress accelerated degradation test (SSADT) is more cost-effective and time-effective. This paper compares three SSADT testing plans with temperature and driving currents as stepwise increasing loads to determine an appropriate test strategy for UV LEDs. The study shows that: (1) the failure mechanisms among different SSADT tests seem to be very different, since the driving current determines the failure mechanisms of UV LEDs more sensitively, and (2) the stepped temperature accelerated degradation test with an appropriate current is recommended for UV LEDs.

LncRNA NKILA correlates with the malignant status and serves as a tumor-suppressive role in rectal cancer.

NF-κB interacting lncRNA (NKILA) has been found to function as a tumor-suppressive role in various human cancers. However, the role of NKILA in rectal cancer is still unknown. The objective of this study is to investigate the clinical value and biological function of NKILA in rectal cancer. The association between NKILA expression and clinical variables including prognosis was estimated in rectal cancer patients. The gain-of-function study of NKILA in rectal cancer cell was conducted to evaluate the effect of NKILA on cell proliferation, migration, invasion, and NF-κB signaling pathway. The results suggested NKILA expression was decreased in rectal cancer tissues and cells, and correlated with clinical stage, T classification, N classification and M classification. NKILA low-expression was an independent poor prognostic factor in rectal cancer patients. NKILA-inhibited rectal cancer cell proliferation, migration, and invasion via suppressing NF-κB signaling. In conclusion, NKILA serves as an antioncogenic lncRNA in rectal cancer.

An Alternative Lifetime Model for White Light Emitting Diodes under Thermal⁻Electrical Stresses.

The lifetime prediction using accelerated degradation test (ADT) method has become a main issue for white light emitting diodes applications. This paper proposes a novel lifetime model for light emitting diodes (LEDs) under thermal and electrical stresses, where the junction temperature and driving current are deemed the input parameters for lifetime prediction. The features of LEDs' lifetime and the law of lumen depreciation under dual stresses are combined to build the lifetime model. The adoption of thermal and electrical stresses overcomes the limitation of single stress, and junction temperature in accelerated degradation test as thermal stress is more reliable than ambient temperature in conventional ADT. Furthermore, verifying applications and cases studies are discussed to prove the practicability and generality of the proposed lifetime model. In addition, the lifetime model reveals that electrical stress is equally significant to the thermal stress in the degradation of LEDs, and therefore should not be ignored in the investigation on lumen decay of LEDs products.

Long Noncoding RNA LINC00958 Accelerates Gliomagenesis Through Regulating miR-203/CDK2.

Increasing evidence has indicated that long noncoding RNAs (lncRNAs) play crucial roles in various biological processes, including glioma. However, the underlying mechanism of lncRNAs in gliomagenesis is still ambiguous. In this study, we aim to investigate the role of long intergenic noncoding RNA 00958 (LINC00958) in the tumorigenesis of glioma. Results revealed that LINC00958 was significantly upregulated in glioma tissues and cell lines compared with that of adjacent normal brain tissues and normal human astrocytes. Moreover, the ectopic overexpression of LINC00958 was correlated with poor prognosis of glioma patients. Loss-of-function experiments indicated that LINC00958 knockdown suppressed glioma cell proliferation, invasion, and induced cycle arrest at G0/G1 phase in vitro, and inhibited tumor growth in vivo. Bioinformatics programs and luciferase reporter assay revealed that miR-203 shared complementary binding sites with both 3'-untranslated region of LINC00958 and CDK2. In summary, our study concludes that LINC00958 acts as an oncogenic gene in the gliomagenesis through miR-203-CDK2 regulation, providing a novel insight into glioma tumorigenesis.

A Time-Variant Reliability Model for Copper Bending Pipe under Seawater-Active Corrosion Based on the Stochastic Degradation Process.

In the degradation process, the randomness and multiplicity of variables are difficult to describe by mathematical models. However, they are common in engineering and cannot be neglected, so it is necessary to study this issue in depth. In this paper, the copper bending pipe in seawater piping systems is taken as the analysis object, and the time-variant reliability is calculated by solving the interference of limit strength and maximum stress. We did degradation experiments and tensile experiments on copper material, and obtained the limit strength at each time. In addition, degradation experiments on copper bending pipe were done and the thickness at each time has been obtained, then the response of maximum stress was calculated by simulation. Further, with the help of one kind of Monte Carlo method we propose, the time-variant reliability of copper bending pipe was calculated based on the stochastic degradation process and interference theory. Compared with traditional methods and verified by maintenance records, the results show that the time-variant reliability model based on the stochastic degradation process proposed in this paper has better applicability in the reliability analysis, and it can be more convenient and accurate to predict the replacement cycle of copper bending pipe under seawater-active corrosion.

Possible prognostic significance of p53, cyclin D1 and Ki-67 in the second primary malignancy of patients with double primary malignancies.

Patients with two types of primary cancers are rare. In this study, we investigated the expression of p53, cyclin D1, and Ki-67 in the second primary malignancy. Tissue samples were obtained from the second primary cancer site of 43 patients who met the diagnostic criteria for double primary cancer. p53, cyclin D1 and Ki-67 were determined using immunohistochemistry. Categorical variables were compared using the Chi-squared test; correlation between data scores and histology was calculated using the Spearman's rank-order correlation. The expression rates of p53, cyclin D1 and Ki-67 in the second primary malignancy site were 60.5%, 30.2% and 65.1% respectively. p53 expression showed statistically significant association with tumor occurrence interval, pathological grading and nodal metastasis (p < 0.05). Positive correlation was detected between the expression of cyclin D1 and Ki-67 and the expression of p53 (r = 0.313, p = 0.041; r = 0.319, p = 0.037, respectively). High-expressing p53 or cyclin D second primary malignancies were associated with decreased overall survival (p = 0.040 and p = 0.043, respectively). Ki-67 expression levels did not exhibit statistically significant differences in survival. In conclusion, elevated protein expression of p53, cyclin D1 and Ki-67 in the second primary malignancy is an indicator of more aggressive malignant behavior of the secondary tumor. These markers may have prognostic value in the clinical setting.