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Non-intrusive load monitoring (NILM) of residential houses is an important research content of the user demand side of smart grids, and the energy consumption analysis and power consumption management of residential loads are key steps in achieving energy conservation, emission reduction, and sustainable development. Aiming at the problems of poor recognition performance of traditional algorithms and difficulty in adapting to the current complex electricity environment, a NILM load recognition method integrating convolutional neural network (CNN)-self-attention mechanism is proposed from the optimization idea of enhancing the feature extraction performance of classification algorithms. Firstly, the power data of eight different household appliances are collected to establish a U-I trajectory curve database. Secondly, the feature aggregation ability of CNN is improved by using squeeze-and-excitation network (SENet) attention mechanism to complete the feature extraction and load identification of U-I trajectory curves of different electrical appliances. Finally, the private dataset and PLAID dataset are tested, and the example results show that the proposed method has high recognition accuracy and good generalization performance in different operational scenarios.

With the help of the Nevanlinna theory and the Hadamard factorization theory of meromorphic functions, we mainly give a description of the existence and the forms of the transcendental entire solutions of several product-type complex partial differential equations systems (a1fz1+a2fz2)(a3gz1+a4gz2)=eh1,(a1gz1+a2gz2)(a3fz1+a4fz2)=eh2,\left\{\begin{array}{l}({a}_{1}{f}_{{z}_{1}}+{a}_{2}{f}_{{z}_{2}})({a}_{3}{g}_{{z}_{1}}+{a}_{4}{g}_{{z}_{2}})={e}^{{h}_{1}},\\ ({a}_{1}{g}_{{z}_{1}}+{a}_{2}{g}_{{z}_{2}})({a}_{3}{f}_{{z}_{1}}+{a}_{4}{f}_{{z}_{2}})={e}^{{h}_{2}},\end{array}\right. and (a1fz1+a2gz1)(a3fz2+a4gz2)=eh1,(a1fz2+a2gz2)(a3fz1+a4gz1)=eh2,\left\{\begin{array}{l}({a}_{1}{f}_{{z}_{1}}+{a}_{2}{g}_{{z}_{1}})({a}_{3}{f}_{{z}_{2}}+{a}_{4}{g}_{{z}_{2}})={e}^{{h}_{1}},\\ ({a}_{1}{f}_{{z}_{2}}+{a}_{2}{g}_{{z}_{2}})({a}_{3}{f}_{{z}_{1}}+{a}_{4}{g}_{{z}_{1}})={e}^{{h}_{2}},\end{array}\right. where fzt=∂ft∂zt{f}_{{z}_{t}}=\frac{\partial {f}_{t}}{\partial {z}_{t}}, gzt=∂gt∂zt{g}_{{z}_{t}}=\frac{\partial {g}_{t}}{\partial {z}_{t}}, t=1,2t=1,2; aj∈C,j=1,2,3,4{a}_{j}\in {\mathbb{C}},\hspace{0.33em}j=1,2,3,4, and h1{h}_{1} and h2{h}_{2} are the polynomials in C2{{\mathbb{C}}}^{2}. More importantly, we list some examples to explain that our results about the forms of solutions of such systems are precise to some extent.

Purpose: Benign prostate hyperplasia (BPH) is a common age-related chronic condition. Its pathogenesis involves androgen imbalance, inflammation, oxidative stress, and endoplasmic reticulum (ER) stress. This study aims to assess the protective effect of finasteride, a 5α-reductase inhibitor, against testosterone propionate (TP)-induced BPH in rats and explore its potential mechanism of action. Materials and Methods: TP-induced BPH rats received either saline or finasteride (1 mg/kg) orally once a day for 7 weeks. Prior to sacrificing the animals, blood samples were collected. After sacrifice, prostate and tissue around the prostate were dissected from seminal vesical for further analysis. Body weight, prostate weight, dihydrotestosterone (DHT), 5α-reductase type 2 (5-AR2), and prostate-specific antigen (PSA) levels were measured. In addition, HIF-1α, VEGF, MMP-2 expressions in prostate, oxidative stress, inflammation, and ER stress responses were analyzed to understand the mechanism of action of finasteride. Results: Finasteride administration inhibited prostate enlargement, DHT, 5-AR2, and PSA levels in BPH rats. Additionally, finasteride inhibited angiogenesis markers such as HIF-1α, VEGF, and MMP-2. Moreover, components of oxidative stress, inflammation, and ER stress responses were significantly regulated by finasteride treatment. Conclusions: This study suggests that finasteride prevents BPH-associated symptoms by regulating angiogenesis, reactive oxygen species, ER stress responses, and inflammation, another mechanism to explain the effect of the 5α-reductase against BPH.

This paper presents the design of a high-efficiency spot size converter (SSC) for photonic crystal fiber (PCF) to silicon-based waveguides, utilizing composite optical waveguide structures. The SSC is composed of a series of waveguide cores, with one core progressively widening to enable all cores to collectively serve as a composite input port, while the broader core functions as the output port. Simulation results reveal that the proposed design efficiently facilitates mode and energy transfer between the waveguide and the PCF, achieving a coupling efficiency of up to 93.99% over a length of 66 μm. Additionally, the SSC exhibits polarization insensitivity, with the high circularity of the output beam enhancing vertical alignment tolerance, and maintaining excellent performance over a wide wavelength range. In sum, this SSC demonstrates excellent coupling efficiency and holds significant promise for applications in optical communication systems and optical integrated circuit systems.

BackgroundThe application of neoadjuvant immunotherapy in the treatment of esophageal cancer needs further exploration. This study aimed to investigate the safety and effectiveness of tislelizumab, an anti-PD-1 antibody, combined with chemotherapy as neoadjuvant treatment for locally advanced esophageal squamous cell carcinoma (LA-ESCC).MethodsIn this phase II study, patients with clinical stages of II-IVA (T3-T4 and/or node positive) potentially resectable LA-ESCC were enrolled. Patients received neoadjuvant tislelizumab and chemotherapy every 3 weeks for 4 cycles before surgery and adjuvant tislelizumab for 9 months. The primary endpoint was pathological complete response (pCR) rate. Secondary endpoints included R0 resection, disease free survival (DFS), adverse events (AE), and biomarkers for predicting efficacy.ResultsThe study included 30 patients. 25 patients completed neoadjuvant chemoimmunotherapy and underwent surgery, 96% with R0 resection. The pCR and MPR rate was 44% and 52%. The 6-month and 1-year DFS rate was 100% and 75.3%. 43.3% patients experienced severe (grade 3-4) treatment-related adverse events (TRAEs) and 5 patients developed severe immune-related adverse events (irAEs). Further exploration found that a group of peripheral lymphocyte subsets increased significantly after 2 cycles of neoadjuvant therapy in patients who achieved pCR, suggesting the importance of dynamic monitoring of circulating lymphocyte.ConclusionsThe combination of perioperative tislelizumab and neoadjuvant chemotherapy has achieved an encouraging pCR rate and demonstrated a manageable safety profile in patients with potentially resectable ESCC.Clinical Trial Registrationhttps://www.chictr.org.cn/, identifier ChiCTR2100043772.

Abstract Underwater pottery relics salvaged from shipwrecks are vulnerable to physical, chemical and biological corrosion. In this study, the microscopic morphology and structural composition of glazed pottery fragments excavated from the South China Sea as well as purple clay teapot samples from the Yangtze River Estuary II shipwreck were analyzed by means of optical microscopy, scanning electron microscope equipped with energy dispersive spectrometer, X-ray diffraction, X-ray photoelectron spectroscopy, Fourier infrared transform spectroscopy and photoluminescence spectroscopy. According to the research results, the corrosion products deposited on the surface of the glazed pottery fragment from the South China Sea mainly included FeOOH and MnO2, whereas those on the surface of the purple clay teapot fragment from the Yangtze River Estuary II shipwreck primarily incorporated FeS2 and FeS. According to the corrosion phenomenon, it was speculated that the underwater pottery relics were mainly corroded by different microorganisms in the underwater environment, including manganese-oxidizing bacteria, dissimilatory metal-reducing bacteria and sulfate-reducing bacteria. As the corrosion process of these cultural artifacts was described and related models were established, this study provides valuable reference for the disease removal and protection of pottery relics.

With the increase of the scale of animal husbandry, the negative effect of nitrogen and phosphorus, antibiotics, heavy metals and other pollutants in livestock wastewater has been increasing. Natural adsorption materials are a new type of environmental protection materials that have attracted attention in recent years. Many researchers have developed natural adsorption materials using microorganisms, algae, animal and plant derivatives and industrial and agricultural wastes. However, there has been no systematic review regarding the natural adsorbents for the purpose to treat the livestock wastewater. In this paper, the pollutants and their hazards in livestock wastewater were reviewed. The characteristics of such pollutants were introduced in detail, and the research progress of natural adsorbent materials and their effect on livestock wastewater treatment was summarized. This review is intended to provide ideas and references for the development and application of natural adsorbent.

Abstract Background With the rapidly increasing morbidity and mortality, lung cancer has been considered one of the serious malignant tumors, affecting millions of patients globally. Currently, the pathogenesis of lung cancer remains unclear, hindering the development of effective treatment. This study aims to investigate the mechanisms of lung cancer and develop an effective therapeutic approach for intervention in preventing lung cancer progress. Methods The USP5 levels are detected in lung cancerous and paracancerous tissue by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting methods to explore their roles in lung cancer progression. MTT, colony assay, and transwell chamber approaches are employed to measure cell viability, proliferation, and migration, respectively. Further, flow cytometry experiments are performed to examine the effect of USP5 on lung cancer. Finally, the investigations in vivo are executed using the mice subcutaneous tumor model to identify the effect of USP5 in promoting lung cancer development. Results Notably, USP5 is highly expressed in lung cancer, USP5 overexpression promoted the proliferation and migration in the lung cancer cell lines, H1299 and A549, while knockdown of USP5 inhibited these via regulating the PARP1-mediated mTOR signaling pathway. Furthermore, the subcutaneous tumors model was established in C57BL/6 mice, and the volume of subcutaneous tumors was significantly reduced after silencing USP5, while increased after USP5 overexpression and decreased significantly with shRARP1 treatment at the same time. Conclusions Together, USP5 could promote the progression of lung cancer cells by mTOR signaling pathway and interacting with PARP1, indicating that USP5 may become a new target for lung cancer treatment.

Combined heat and power (CHP) system has the outstanding advantages of environmental protection,economy and flexible operation mode,and has a better development prospect. Based on the different characteristics of electricity and heat in transmission and storage,a two-stage optimal scheduling method for CHP system considering thermal inertia is proposed. In the first stage,considering the structure and operation characteristics of the heating network,the optimal scheduling model of the CHP system based on model predictive control is established,and the strategy of intra-day controllable equipment output and grid interactive power is optimized. In the second stage,the goal is minimize the output adjustment of each unit in CHP system,and the real-time prediction error of renewable energy and load is taken into account to dynamically adjust the economic scheduling strategy in the first stage. The example shows that the two-stage optimal scheduling model can improve the economy of system operation and make up for the imbalance of supply and demand. Combined with the thermal inertia of the system,the building can store or release heat according to load demand and time-of-use electricity price,which can reduce the impact of renewable energy and load uncertainty on scheduling,smooth power fluctuations,and promote heat and power complementation.

The ‘Yangtze River Estuary No. 2’ shipwreck of the Qing Dynasty (1636–1912 CE) is one of the most well-preserved ancient wooden shipwrecks discovered underwater in China to date. Unfortunately, most green lead-glazed cups salvaged out of the shipwreck have severely degraded and generally blackened in the underwater environment. In this study, the degradation mechanism of the lead glaze in the underwater environment were investigated in depth. It was found that the degradation of lead glaze involved several complex chemical and physical processes. The special environmental conditions caused by the corrosion of iron components in the shipwrecks may be an important reason for the loss of Si elements in corrosion layers. The appearance changes of the green glaze are related to the leaching of Cu2+ ions and the gradual transformation to a lead-rich corrosion layer. The iridescent phenomenon may be related to the thin-film interference of the laminated corrosion layers.

Abstract Background Oesophageal leiomyomas are one of the most common benign oesophageal tumours. This retrospective, observational study summarized and compared the clinical outcomes of thoracoscopic enucleation of oesophageal leiomyoma between single-lumen endotracheal intubation with a bronchial blocker and double-lumen endotracheal intubation. Methods A total of 36 patients who underwent thoracoscopic enucleation of oesophageal leiomyoma at Peking Union Medical College Hospital between 2014 and 2020 were retrospectively analysed. Fifteen patients received single-lumen endotracheal intubation combined with a right bronchial blocker (SLT-B group), and twenty-one patients received double-lumen endotracheal intubation (DLT group). Clinical data, surgical variables, and postoperative complications were analysed and compared. Results The average tumour size in all patients was 4.3 ± 2.0 cm. The average tumour size among symptomatic patients was significantly larger than that among asymptomatic patients (5.1 ± 2.0 cm vs 3.7 ± 1.7 cm, P

Muddy sediments are the most prominent constituents of sedimentary successions in tide-dominated river deltas and have highly complex depositional mechanisms. In this study, we performed fine-grained (4–11 μm) quartz optically stimulated luminescence (OSL) dating on two sediment cores collected at a shipwreck site in the turbidity maximum zone (TMZ) of the modern Yangtze River mouth, China, which were compared with previously published dating results including 45–63 um quartz OSL dating, radionuclide dating, porcelain artifacts recovered from the wreck, macro-plastics, and the morphological history recorded in marine charts. We investigate the luminescence characteristics of muddy sediments trapped in the TMZ and discuss the implications of OSL ages in understanding depositional mechanisms in tide-dominated river mouths. The results indicate that most OSL ages of muddy sediments in the delta front setting are overestimated compared with other dating methods. We suggest that OSL age overestimation reflects the trapping of sediments from offshore in the TMZ imported by saltwater intrusions and storm events. The offshore inputs contain high percentages of residual luminescence and are also subjected to incomplete bleaching due to turbid water conditions and near-bed dispersal in the salt-wedge river mouth. We thus suggest that the reduced bleaching efficiency of muddy sediments in delta front settings needs to be accounted for in understanding sedimentary processes and distinguishing between different sedimentary facies in tide-dominated river mouths. Furthermore, we propose that differences in quartz OSL ages of fine- and medium-grained fractions may arise in response to extreme events.

The control of matte grade determines the production cost of the copper smelting process. In this paper, an optimal matte-grade control model is established to derive the optimal matte grade with the objective of minimizing the cost in the whole process of copper smelting. This paper also uses the prediction capability of the BP (Backpropagation) neural network to establish a BP neural network prediction model for the matte grade, considering various factors affecting matte grade (including the input copper concentrate amount and its composition content, air drumming amount, oxygen drumming amount, melting agent amount, and other process parameters). In addition, the paper also uses the optimal matte grade to optimize the dosing, air supply/oxygen supply, and oxygen supply for the ISA and other furnaces. When using BP networks only, it is a nonconvex problem with gradient descent, which tends to fall into local minima and has some bias in the prediction results. This problem can be solved by optimizing its weights and thresholds through GA (Genetic Algorithm) to find the optimal solution. The analysis results show that the average absolute error of the simulation of the BP neural network prediction model for ice copper grade after GA optimization is 0.51%, which is better than the average absolute error of 1.17% of the simulation of the single BP neural network model.

Abstract Background Isolated diaphragmatic metastasis is rarely associated with periosteal osteosarcoma. Case presentation A 24-year-old female patient was found to have periosteal osteosarcoma of the right humerus 11 years ago. Computed tomography showed a mass in her left chest in 2018, and thoracotomy was performed to remove the tumour. The tumour showed the same characteristics as the original periosteal osteosarcoma. Genetic analysis of the tumour sample showed a TP53 point mutation and CCNE1 gene copy number variants. Conclusions We believe this is the first case report of haematogenous metastasis to the diaphragm of periosteal osteosarcoma, and an investigation of the genetic factors may help to unravel the underlying cause of periosteal osteosarcoma.

With the proliferation of the Internet of Things, a large amount of data is generated constantly by industrial systems, corresponding in many cases to critical tasks. It is particularly important to detect abnormal data to ensure the accuracy of data. Aiming at the problem that the training data are contaminated with anomalies in autoencoder-based anomaly detection, which makes it difficult to distinguish abnormal data from normal data, this paper proposes a data anomaly detection method that combines an isolated forest (iForest) and autoencoder algorithm. In this method (iForest-AE), the iForest algorithm was used to calculate the anomaly score of energy data, and the data with a lower anomaly score were selected for model training. After the test data passed through the autoencoder trained by normal data, the data whose reconstruction error was larger than the threshold were determined as an anomaly. Experiment results on the electricity consumption dataset showed that the iForest-AE method achieved an F1 score of 0.981, which outperformed other detection methods, and a significant advantage in anomaly detection.

When a solar ship is navigating in the ocean, the swaying motion of a photovoltaic panel will affect the output power of the photovoltaic (PV) power generation system more frequently and violently. In addition to considering multiple climatic factors, this paper also adopts a ship swaying motion and radiation level of sunlight to establish a suitable calculation model for the output power of photovoltaic systems, which are rarely considered at the same time in previous studies, and also to make ultrashort-term power predictions. Furthermore, this paper proposes a multilayer heterogeneous particle swarm optimization (PSO) algorithm to design the weights and thresholds of a long short-term memory (LSTM) neural network to improve the accuracy of forecasting the changes of a photovoltaic panel’s angle, which is used for accurate power output prediction for the purpose of power planning. The case analysis shows the effectiveness of the algorithm, which provides a more reliable method for designing a power prediction system.

PURPOSE: To compare the variation patterns of ADC and T2 values in different age and intervertebral disc (IVD) levels, thus to identify their sensitivities in assessing age and disc level related IVDs changes. MATERIALS AND METHODS: The T2 and ADC values were recorded from 345 IVDs of 69 volunteers. Kendall's correlation analysis was used to identify the relationship between age and T2/ADC mean values respectively. The one-way analysis of variance (ANOVA) with post hoc analysis was then applied to test the differences of T2 and ADC values among different IVD levels and age groups, followed by linear regression analysis between age (45 years) and T2/ADC mean values. This study was approved by the Ethics Committee of the Chinese Academy of Medical Sciences and the Peking Union Medical College Hospital. RESULTS: Significant negative correlation was observed between age and T2/ADC mean values. The T2 and ADC values showed significant differences among IVD levels and among age groups except for T2 values in age group 1 (25-34 years) and group 2 (35-44 years), and for ADC values at L1-2 level. Both T2 and ADC values showed significant differences between young (age45 years) at each IVD level. A linear relationship was observed between age and T2/ADC mean values in the elderly group as well as in the young group for the ADC mean values, while no such tendency was identified in the young group for the T2 mean values. CONCLUSIONS: ADC values may be a more sensitive parameter than T2 in assessing age and disc level related intervertebral disc changes.