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With the increase in the integration of renewable sources, the home energy management system (HEMS) has become a promising approach to improve grid energy efficiency and relieve network stress. In this context, this paper proposes an optimization dispatching strategy for HEMS to reduce total cost with full consideration of uncertainties, while ensuring the users' comfort. Firstly, a HEMS dispatching model is constructed to reasonably schedule the start/stop time of the dispatchable appliances and energy storage system to minimize the total cost for home users. Besides, this dispatching strategy also controls the switching time of temperature-controlled load such as air conditioning to reduce the energy consumption while maintaining the indoor temperature in a comfortable level. Then, the optimal dispatching problem of HEMS is modeled as a Markov decision process (MDP) and solved by a deep reinforcement learning algorithm called deep deterministic policy gradient. The example results verify the effectiveness and superiority of the proposed method. The energy cost can be effectively reduced by 21.9% at least compared with other benchmarks and the indoor temperature can be well maintained. [ABSTRACT FROM AUTHOR]

Objective To compare genomic copy number variations (CNVs) among different subtypes of breast cancer and analyze specific CNVs in each subtype. Methods AIMS software was used for genotype breast cancer (BasL, Her2, LumA and LumB), and GISTIC2.0 software was used to analyze genome-wide CNVs in tumor tissues from TCGA. We collected and analyzed the information and samples of 324 cases of invasive breast cancer admitted to Jiangmen Central Hospital(JMCH). Fluorescence quantitative PCR was used to detect the CNV of ERBB2, TFDP1, MIR148B, CCND1, MDM2 and MIR139 genes in the tumor tissues, to verify TCGA analysis. Results 13q34 was specifically amplified and 12q13.13 was specifically deleted in BasL-type breast cancer. The 17q12 was specifically amplified in Her2 type. The 12q15 was specifically amplified and 11q13.4 was specifically deleted in LumB type, but LumA type had no specific amplification or deletion of chromosome region. The proportion of TFDP1 amplification or MIR148B deletion in BasL type were 57.8% (TCGA) and 71.4% (JMCH), which were significantly higher than other subtypes (P < 0.001). The proportion of ERBB2 amplification of Her2 type were 55.2% (TCGA) and 86.7% (JMCH), which were significantly higher than other subtypes (P < 0.001). The proportion of LumB type with CCND1 or MDM2 amplification or MIR139 deletion were 47.6% (TCGA) and 61.8% (JMCH), which were significantly higher than other subtypes (P < 0.05). Conclusion At the CNV level of breast cancer, Her2 type is characterized by the amplification of ERBB2, BasL type is characterized by the amplification of TFDP1 or the deletion of MIR148B, LumB type is characterized by the amplification of CCND1 or MDM2 or the deletion of MIR139, but LumA type lacks specific CNV characteristics.

The elimination of traditional thermal generators and the increase of renewable energy source access reduced the inertia of the power system, and thermostatically controlled loads have the potential to provide ancillary services to the power system. This paper introduces a decentralized control strategy for thermostatically controlled loads (TCLs), which focuses on assisting large-scale TCLs in providing frequency support to power systems while considering energy efficiency ratio and measurement error correction. Initially, the nonlinear relationship between heat flow and TCLs' power is modeled using a polynomial relationship, and the coefficients are determined through a data-driven method to enhance accuracy in TCLs modeling and assess their regulation potential precisely. Subsequently, a decentralized control strategy tailored for power system frequency regulation is developed. To account for measurement errors in TCLs controllers, a measurement error back-correction method is proposed. Simulation examples demonstrate the effectiveness of the proposed control strategy in achieving accurate modeling and control of TCLs and reducing power system frequency fluctuations. [ABSTRACT FROM AUTHOR]

Emergency load shedding (ELS) is a vital measure for power systems to manage extreme events, ensuring the safety, stability, and economic operation of the grid. The integration of distributed energy resources and controllable devices in modern power systems has bolstered grid flexibility. Consequently, developing precise load shedding strategies to balance economic and security goals has emerged as a prominent subject in power system optimization. However, existing methods exhibit inadequacies, including overlooking practical operability, privacy concerns, and a lack of adaptability to response time requirements. To address these gaps, this paper introduces a precise ELS approach for distributed networks with a focus on response time needs. Contributions encompass designing load shedding processes for various response times, integrating demand response, and partitioning networks for optimized load shedding. Through validation using standard test cases, the proposed approach effectively utilizes response time and demand-side resources for precise ELS control in distribution networks. It accommodates different scenarios, offering a robust solution for rapid and accurate load shedding during emergencies. [ABSTRACT FROM AUTHOR]

Additive manufacturing (3D printing) technology aligns with the direction of precision and customization in future medicine, presenting a significant opportunity for innovative development in high-end medical devices. Currently, research and industrialization of 3D printed medical devices mainly focus on nondegradable implants and degradable implants. Primary areas including metallic orthopaedic implants, polyether-ether-ketone (PEEK) bone implants, and biodegradable implants have been developed for clinical and industrial application. Recent research achievements in these areas are reviewed, with a discussion on the additive manufacturing technologies and applications for customized implants. Challenges faced by different types of implants are analyzed from technological, application, and regulatory perspectives. Furthermore, prospects and suggestions for future development are outlined.

Background: In this case report, we aimed to describe the multimodal imaging characteristics and the successful treatment of idiopathic retinal vasculitis, aneurysms, and neuroretinitis (IRVAN) syndrome in a 39-year-old man., Case Presentation: His both eyes were diagnosed with IRVAN syndrome via multimodal imaging, including fundus color photograph, multicolor imaging, infrared ray, fundus autofluorescence, fundus fluorescence angiography and optical coherence tomography angiography. Both eyes were treated with vitrectomy and laser photocoagulation. The treatment was effective. Eighteen months after discharge, the patient had visual acuity of 20/20 in both eyes., Conclusions: This case report demonstrates that vitrectomy and retinal laser photocoagulation can be successful in treating a patient with IRVAN syndrome in both eyes., Competing Interests: None., (AJTR Copyright © 2021.)