A hybrid neural network based on KF-SA-Transformer for SOC prediction of lithium-ion battery energy storage systems

With the widespread application of energy storage stations, BMS has become an important subsystem in modern power systems, leading to an increasing demand for improving the accuracy of SOC prediction in lithium-ion battery energy storage systems. Currently, common methods for predicting battery SOC include the Ampere-hour integration method, open circuit voltage method, and model-based prediction techniques. However, these methods often have limitations such as single-variable research, complex model construction, and inability to capture real-time changes in SOC. In this paper, a novel prediction method based on the KF-SA-Transformer model is proposed by combining model-based prediction techniques with data-driven methods. By using temperature, voltage, and current as inputs, the limitations of single-variable studies in the Ampere-hour integration method and open circuit voltage method are overcome. The Transformer model can overcome the complex modeling process in model-based prediction techniques by implementing a non-linear mapping between inputs and SOC. The presence of the Kalman filter can eliminate noise and improve data accuracy. Additionally, a sparse autoencoder mechanism is integrated to optimize the position encoding embedding of input vectors, further improving the prediction process. To verify the effectiveness of the algorithm in predicting battery SOC, an open-source lithium-ion battery dataset was used as a case study in this paper. The results show that the proposed KF-SA-Transformer model has superiority in improving the accuracy and reliability of battery SOC prediction, playing an important role in the stability of the grid and efficient energy allocation

Diffuse leptomeningeal glioneuronal tumor with atypical radiological and molecular feature: A case report and literature review

A Diffuse Leptomeningeal Glioneuronal Tumor (DLGNT), a rare entity as classified in the World Health Organization’s Fifth Edition of the Classification of Tumors of the Central Nervous System (WHO CNS5), is characterized by oligodendrocyte-like cells with MAPK pathway alterations. This report details the case of a 29-year-old female presenting with unique radiological features: extensive spinal cord dissemination involving both parenchyma and leptomeninges, without intracranial involvement. Near-total resection (NTR) was performed, revealing H3K27me3 positivity, a molecular characteristic not previously reported in DLGNTs. We also review recent studies to expand the understanding of DLGNT’s clinical, imaging, and molecular profiles, aiming to assist radiologists and clinicians in accurate diagnosis and timely management

A New Strategy for Disc Cutter Wear Status Perception Using Vibration Detection and Machine Learning

Carrying out status monitoring and fault-diagnosis research on cutter-wear status is of great significance for real-time understanding of the health status of Tunnel Boring Machine (TBM) equipment and reducing downtime losses. In this work, we proposed a new method to diagnose the abnormal wear state of the disc cutter by using brain-like artificial intelligence to process and analyze the vibration signal in the dynamic contact between the disc cutter and the rock. This method is mainly aimed at realizing the diagnosis and identification of the abnormal wear state of the cutter, and is not aimed at the accurate measurement of the wear amount. The author believes that when the TBM is operating at full power, the cutting forces are very high and the rock is successively broken, resulting in a complex circumstance, which is inconvenient to vibration signal acquisition and transmission. If only a small thrust is applied, to make the cutters just contact with the rock (less penetration), then the cutters will run more smoothly and suffer less environmental interference, which would be beneficial to apply the method proposed in this paper to detect the state of the cutters. A specific example was to use the frequency-domain characteristics of the periodic vibration waveform during the contact between the cutter and the granite to identify the wear status (including normal wear state, wear failure state, angled wear failure state) of the disc cutter through the artificial neural network, and the diagnosis accuracy rate is 90%

Epidemiology and clinical characteristics of acute respiratory tract infections among hospitalized infants and young children in Chengdu, West China, 2009–2014

Abstract Background Acute respiratory infection (ARI) is the leading cause of morbidity and mortality in pediatric patients worldwide and imposes an intense pressure on health care facilities. Data on the epidemiology profiles of ARIs are scarce in the western and rural areas of China. The purpose of the current study is to provide data on the presence of potential pathogens of ARIs in hospitalized children in Chengdu, west China. Methods Respiratory specimens were obtained from hospitalized patients (under 6 years old) with ARIs in a local hospital in Chengdu. Eight respiratory viruses were identified by PCR and 6 respiratory bacteria by biochemical reactions and Analytical Profile Index (API). Pathogens profiles, clinical characteristics and seasonality were analyzed. Results Fifty-one percent of patients were identified with at least one respiratory pathogen. Human rhinovirus (HRV) (23%), Respiratory syncytial virus (RSV) (22.7%) was the most commonly identified viruses, with Klebsiella pneumoniae (11.5%) the most commonly identified bacterium in the study. The presences of more than one pathogen were found, and multiple viral, bacterial, viral/bacterial combinations were identified in 14.9, 3.3 and 13.9% of patients respectively. Respiratory viruses were identified throughout the year with a seasonal peak in December–February. Pathogens profiles and clinical associations were different between infants ( 1 year of age). Infants with ARIs were more likely to have one or more viruses than older children. Infants identified with multiple pathogens had significantly higher proportions of tachypnea than infants that were not. Conclusions This study demonstrated that viral agents were frequently found in hospitalized children with ARI in Chengdu during the study period. This study gives us better information on the pathogen profiles, clinical associations, co-infection combinations and seasonal features of ARIs in hospitalized children, which is important for diagnoses and treatment of ARIs, as well as implementation of vaccines in this area. Moreover, future efforts in reducing the impact of ARIs will depend on programs in which available vaccines, especially vaccines on RSV, HRV and S. pneumoniae could be employed in this region and new vaccines could be developed against common pathogens

Experimental and numerical studies of axially loaded square concrete-encased concrete-filled large-diameter steel tubular short columns

This article presents experimental and numerical studies on the axial compressive behavior of square concrete-encased concrete-filled steel tubular (CECFST) short columns composed of a circular inner steel tube. Tests on six full-scale short CECFST columns with the inner circular tube diameter varying from 320 to 500 mm were carried out to study the influences of sectional diameter and the tube thickness of circular CFST columns on their axial performance. A theoretical model is developed using fiber analysis method and validated against a large test database. The accuracy of various codified design models is evaluated and a simple model is proposed to calculate their ultimate strengths. Test results show that CECFST columns have improved load carrying capacity and can sustain large axial loads without significant strength degradation. In addition, increasing the thickness of the steel tube significantly improves the composite action of the steel and concrete of the inner CFST column, which increases the compressive strength of CECFST columns by 27.3%. However, the rate of increase in the compressive strength of the core concrete of the CFST column has been found to be higher for the column with a smaller local slenderness ratio. The ductility of CECFST columns is influenced by the concrete strength and the spacing of the stirrups. Furthermore, the design model suggested in this study can provide a better estimation than the codified design models

Short term wind power prediction for regional wind farms based on spatial-temporal characteristic distribution

Accurate regional wind power prediction is of great significance to the wind farm clusters integration and the economic dispatch of the regional power grid. The complex spatiotemporally coupled characteristics between multiple wind farms bring challenges to wind power prediction (WPP) of regional wind farm clusters. In this context, this paper proposes a regional WPP method using spatiotemporally multiple clustering algorithm and hybrid neural network to learn the potential spatial-temporal dependencies of regional wind farms. In which, a long-term daily power curve similarity method is proposed to identify spatially correlative wind power plants in long-term. Furthermore, the spatio-temporal wind farm sub-clusters are dynamically recognized by the similar fluctuation trend of short-term power sequences. On this basis, a spatial-temporal integrated prediction model consisting of the improved convolutional neural network (I-CNN) and the bidirectional long short-term memory (BILSTM) network is established for spatio-temporal sub-cluster based on point clouds distribution. Finally, the effectiveness of the proposed regional wind power forecasting framework is validated by using the Wind Integration National Dataset Toolkit, and the results show that the method improves accuracy effectively. 2022 Elsevier LtdThis work is supported by the National Natural Science Foundation of China (No. 52207121 and No. 52007167 ) and the technology project of Electric Power Research Institute of State Grid Hubei Electric Power Co ., Ltd. (Grant number: B31532225680 ).Scopu

Real‐world data of chronic myelomonocytic leukemia: A chinese single‐center retrospective study

Abstract Chronic myelomonocytic leukemia (CMML) is a rare disease of elderly people characterized by the presence of sustained peripheral blood monocytosis, overlapping features of myeloproliferation, and myelodysplasia. We present a large retrospective study of 156 CMML patients in China. Mean age at diagnosis was 68 years old (range 23‐91). According to the CMML‐specific prognostic scoring system (CPSS), 10 patients (8.3%) were low risk, 27 patients (22.5%) were intermediate‐1 risk, 72 patients (60%) were intermediate‐2 risk, and 11 patients (9.2%) were high risk. A total of 90 patients (57.7%) received hypomethylating agents (HMAs) treatment, 19 patients (12.2%) received chemotherapy and 47 patients (30.1%) received the best supportive care. Seventeen patients (10.9%) underwent allogeneic hematopoietic stem cell transplantation (allo‐SCT) after HMAs treatment or chemotherapy. With a median follow‐up of 35.3 months, overall response rate (ORR) was 69.5% in the HMAs ± chemotherapy group, 79.5% in the HMAs monotherapy group, 60.0% in the HMAs + chemotherapy group, and 37.5% in the chemotherapy group. HMAs monotherapy group had prolonged OS compared with the chemotherapy group (23.57 months vs. 11.73 months; p = 0.035). Patients who achieved ORR had prolonged OS (25.83 months vs. 8.00 months; p < 0.001) and LFS (20.53 months vs. 6.80 months; p < 0.001) compared with those not achieved ORR in the HMA ± chemotherapy group. By univariate analysis, only higher hemoglobulin (≥80 g/L) and lower serum LDH levels (<300 U/L) predicted for better OS and LFS. By multivariate analysis, only Hb ≥ 80 g/L predicted for prolonged OS, Hb ≥ 80 g/L, and monocytes < 3 × 109/L predicted for prolonged LFS. In summary, our study highlights the benefit of HMAs therapy in CMML, but we still need to develop novel therapeutics to achieve better outcomes

Clinical significance of cytogenetic and molecular genetic abnormalities in 634 Chinese patients with myelodysplastic syndromes

Abstract Purpose To explore the relevance of cytogenetic or molecular genetic abnormalities to clinical variables, including clinical and laboratory characteristics and prognosis in Chinese patients with myelodysplastic syndromes (MDS). Methods A total of 634 consecutive patients diagnosed with MDS at The First Affiliated Hospital, Zhejiang University School of Medicine from June 2008 to May 2018 were retrospectively included in this study. All patients had evaluable cytogenetic analysis, and 425 patients had MDS‐related mutations sequencing. Results 38.6% of patients displayed abnormal karyotypes. The most common cytogenetic abnormality was +8 (31%). Sole +8 was related to female (p = 0.002), hemoglobin >10 g/dL (p = 0.03), and <60 years old (p = 0.046). TP53 mutations were associated with complex karyotype (CK) (p < 0.001). DNMT3A mutations correlated with ‐Y (p = 0.01) whereas NRAS mutations correlated with 20q‐ (p = 0.04). The overall survival (OS) was significantly inferior in patients with +8 compared with those with normal karyotype (NK) (p = 0.003). However, the OS of sole +8 and +8 with one additional karyotypic abnormality was not different from NK (p = 0.16), but +8 with two or more abnormalities had a significantly shorter OS than +8 and +8 with one additional karyotypic abnormality (p = 0.02). In multivariable analysis, ≥60 years old, marrow blasts ≥5% and TP53 mutations were independent predictors for poor OS (p < 0.05), whereas SF3B1 mutations indicated better prognosis. Male IDH1 and IDH2 mutations and marrow blasts ≥5% were independent risk factors for worse leukemia free survival (LFS) (p < 0.05). Conclusion In this population of Chinese patients, trisomy 8 is the most common karyotypic abnormality. Patients with +8 showed a poorer OS compared with patients with NK. Sole +8 and +8 with one additional karyotypic abnormality had similar OS with NK, whereas +8 with two or more abnormalities had a significantly shorter OS. DNMT3A mutations correlated with ‐Y and NRAS mutations correlated with 20q‐. TP53 mutations were associated with CK and had a poor OS. SF3B1 mutations indicated a favorable OS. IDH1 and IDH2 mutations independently indicated inferior LFS