Learning-Based Non-Intrusive Electric Load Monitoring for Smart Energy Management.

State-of-the-art smart cities have been calling for economic but efficient energy management over a large-scale network, especially for the electric power system. It is a critical issue to monitor, analyze, and control electric loads of all users in the system. In this study, a non-intrusive load monitoring method was designed for smart power management using computer vision techniques popular in artificial intelligence. First of all, one-dimensional current signals are mapped onto two-dimensional color feature images using signal transforms (including the wavelet transform and discrete Fourier transform) and Gramian Angular Field (GAF) methods. Second, a deep neural network with multi-scale feature extraction and attention mechanism is proposed to recognize all electrical loads from the color feature images. Third, a cloud-based approach was designed for the non-intrusive monitoring of all users, thereby saving energy costs during power system control. Experimental results on both public and private datasets demonstrate that the method achieves superior performances compared to its peers, and thus supports efficient energy management over a large-scale Internet of Things network.

Efficient single-frequency 972†nm Yb-doped fiber amplifier with core pumping and elevated temperature.

In this work, we present a monolithic single-frequency, single-mode and polarization maintaining Yb-doped fiber (YDF) amplifier delivering up to 6.9 W at 972 nm with a high efficiency of 53.6%. Core pumping at 915 nm and elevated temperature of 300 °C were applied to suppress the unwanted 977 nm and 1030 nm ASE in YDF, so as to improve the 972 nm laser efficiency. In addition, the amplifier was further used to generate a single-frequency 486 nm blue laser with 590 mW of output power by single-pass frequency doubling.

Development and validation of a prognostic model for HER2-low breast cancer to evaluate neoadjuvant therapy.

Background: Human epidermal growth factor receptor 2 (HER2) low breast cancer (BC) accounts for 30-51% of all BCs. How to precisely assess the response to neoadjuvant therapy in this heterogenous tumor is currently unanswered. With the advance in multi-omics, refining the molecular subtyping other than the current hormone receptor (HR)-based subtyping to guide the neoadjuvant therapy for HER2-low BC is potentially feasible. Methods: The messenger RNA (mRNA), clinical, and pathological data of all HER2-low BC patients (n=368) from the Neoadjuvant I-SPY2 Trial, were retrieved. Ninety-eight patients achieved pathological complete response (pCR) were randomly divided into the training and validation sets with 8:2 ratio. The non-pCR cases were corporated into the above datasets with 1:1 ratio. The rest non-pCR cases were served as the test set. Random forest (RF), support vector machine (SVM), and fully connected neural network (FCNN) were applied to establish a 1-dimensional (1D) model based on mRNA data. The method with best prediction value among the 3 models was selected for further modeling when combining pathological features. A new classification of deep learning (CDn) was proposed based on a multi-omics model. After identifying pCR-related features by the integral gradient and unsupervised hierarchical clustering method, the responses to neoadjuvant therapy associated with these features across different subgroups were analyzed. Results: Compared with the RF and SVM models, the FCNN model achieved the best performance [area under the curve (AUC): 0.89] based on the mRNA feature. By combining mRNA and pathological features, the FCNN model proposed 2 new subtypes including CD1 and CD0 for HER2-low BC. CD1 increased the sensitivity to predict pCR by 23.5% [to 87.8%; 95% confidence interval (CI): 78% to 94%] and improved the specificity to pCR by 12.2% (to 77.4%; 95% CI: 69% to 87%) when comparing with the current HR classification for HER2-low BC. Conclusions: The new typing method (CD1 and CD0) proposed in this study achieved excellent performance for predicting the pCR to neoadjuvant therapy in HER2-low BC. The patients who were not sensitive to neoadjuvant therapy according to multi-omics models might receive surgical treatment directly.

A multi-omics signature to predict the prognosis of invasive ductal carcinoma of the breast.

BACKGROUND: Precisely evaluating the prognosis of invasive ductal carcinoma (IDC) of the breast is challenging as most prognostic signatures use single-omics data based on gene or clinical information. METHODS: Whole-slide images (WSIs), transcriptome, and clinical data of breast IDC were collected from the Cancer Genome Atlas Database. The cancer-associated fibroblast (CAF) gene sets were downloaded from the Molecular Signatures Database. The WSI feature was extracted by artificial feature engineering. The CAF prognostic genes were determined by the Gene Set Enrichment Analysis, the Wilcoxon test, and univariate Cox regression. The IDC patients were divided into the training and test sets. The prognostic signatures based on WSIs, IDC-CAFs, bi-omics, and tri-omics were constructed using multivariate Cox regression. The samples were divided into low- and high-risk groups according to the median risk score. The Kaplan-Meier survival and receiver operating characteristic curves were applied to validate the prediction performance of the four signatures. RESULTS: In total, 508 IDC patients with complete data were included. The area under the curve (AUC) of single-omics signature based on WSI characteristics and CAFs was 0.765 and 0.775, whereas the AUC of bi-omics was 0.823. The tri-omics signature based on WSIs, CAFs, and lymph node status demonstrated the best predictive value with an AUC of 0.897. CONCLUSION: The multi-omics signature based on WSIs, CAFs, and clinical characteristics showed excellent prediction ability in breast IDC patients, whose risk factors can also provide a valuable diagnostic reference for the clinical course.

Comprehensive analysis reveals potential hub genes and therapeutic drugs in an acquired lymphedema model.

Background: Acquired lymphedema is a common and often severe complication of breast cancer surgery and radiology that seriously affects patients' quality of life. Nevertheless, the pathogenesis for acquired lymphedema is complex and remains unclear. The aim of this study is to find out possible genetic markers and potential drugs for acquired lymphedema. Methods: First, the GSE4333 datasets, which include expression data for six female humanized hairless immunocompetent SKH-1 mice (the condition of whom mimics acquired lymphedema), were reanalyzed. According to the criteria of a fold change (FC) ≥1.4 and an adjusted P value <0.05, we identified the differentially expressed genes (DEGs) between a normal group and the lymphedema group. Next, we analyzed the Gene Ontology (GO) terms and enriched signaling pathways associated with these DEGs with an online tool DAVID. We also constructed protein-protein interaction (PPI) networks and selected meaningful gene modules for additional gene-drug interaction research. Finally, the extant drugs targeting these module genes were identified for further study of their therapeutic effects against acquired lymphedema. Results: A total of 481 DEGs were identified that were closely associated with the immune system, inflammatory response, and extracellular matrix (ECM) structural constituent terms, among others. Moreover, we identified the top 10 significant genes in the PPI networks and identified one extant drug, fiboflapon, that targets the ALOX5AP gene. Conclusions: We ultimately identified 10 hub genes, molecular mechanisms, and one extant drug related to acquired lymphedema. The findings identified targets and a potential drug for further research on acquired lymphedema.

Temperature dependence of energy transfer between Nd3+ and Yb3+ ions in phosphate glass.

The temperature dependence of energy transfer between Nd3+ and Yb3+ ions in phosphate glass was investigated with emission spectra, time-resolved spectroscopy, and luminescence lifetimes. The time-resolved spectrograms vividly displayed processes of both Nd3+→Yb3+ energy transfer and Yb3+→Nd3+ energy transfer. The impact of temperature on energy transfer rate has been studied by analyzing the cumulative rise times and decay times of Yb3+ upon excitation of Nd3+ and the cumulative rise times and decay times of Nd3+ upon excitation of Yb3+ at different temperatures. It has been found that both Nd3+→Yb3+ energy transfer and Yb3+→Nd3+ energy transfer are accelerated along with increasing temperatures in a certain temperature range.

Maintaining broadband gain in a Nd3+/Yb3+co-doped silica fiber amplifier via dual-laser pumping.

We report a 30 cm long Nd3+/Yb3+ co-doped silica glass fiber amplifier with well-maintained broadband gain through simultaneous dual-laser pumping at 808 and 975 nm. By controlling the ratio of the pump power at 975 (P975) and 808 nm (P808), the emission band of Yb3+/Nd3+ and the energy transfer efficiency of Nd3+→Yb3+ can be well controlled; thus, a tunable broadband and flat gain in the range of 1036-1080 nm are obtained. The theoretical calculation of the energy transfer efficiency of Nd3+→Yb3+ with dual-laser pumping of 808 and 975 nm explains well the mechanism of broadband and flat gain formation in the Nd3+/Yb3+ co-doped fiber.

Centimeter-scale Yb-free heavily Er-doped silica fiber laser.

The laser behavior of a centimeter-scale Er3+/Al3+ codoped silica fiber with core numerical aperture and core diameter of 0.15 and 8 µm, respectively, is reported. The core glass was prepared by the sol-gel method combined with high-temperature sintering; it contained Er3+ ion concentration as high as 1.32×1020 ions/cm3 and an Al/Er mole ratio of 10. The high doping homogeneity of Er3+ ions in the fiber core was confirmed by an electron probe microanalyzer element scanning, long Er3+: I13/24 emission lifetime of 11.4 ms, and low refractive index fluctuation of fiber core (±1×10-4). The signal gain of fibers with 4.6 cm, 10 cm, and 16 cm lengths was tested in the 1500-1620 nm range. A gain of 7 dB is achieved at 1560 nm in a 16-cm-long EDF under 230 mW pump power. Aimed for CO2 sensor application, the laser behavior of Er/Al codoped fiber was tested at 1572 nm. A slope efficiency of 12% and an output power of 15 mW were achieved in a 10-cm-long fiber under 166 mW absorbed pump power. The newly developed silica fiber is promising for use in high-repetition-rate lasers.

Author Correction: Fast modal decomposition for optical fibers using digital holography.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Optical-power tunable dual-wavelength laser around 1 µm in Nd3+/Yb3+ co-doped phosphate glass fiber.

This work reports the generation of an optical-power tunable 1 µm dual-wavelength fiber laser in Nd3+/Yb3+ co-doped phosphate glass fiber under 970 nm and 808 nm laser diode pumping. A bidirectional free-space pump laser setup was adopted. An optical-power tunable dual-wavelength laser can be easily realized by the control of 808 nm pump power magnitude. Based on a series of laser tests under different pump conditions and theoretical calculation of the Nd3+→Yb3+ energy transfer efficiency, the control mechanism was found to be the stimulated emission modulation of Nd3+ on Yb3+ lasing. This property is helpful to enhance the knowledge of the Nd3+/Yb3+ co-doping system.

Fast modal decomposition for optical fibers using digital holography.

Eigenmode decomposition of the light field at the output end of optical fibers can provide fundamental insights into the nature of electromagnetic-wave propagation through the fibers. Here we present a fast and complete modal decomposition technique for step-index optical fibers. The proposed technique employs digital holography to measure the light field at the output end of the multimode optical fiber, and utilizes the modal orthonormal property of the basis modes to calculate the modal coefficients of each mode. Optical experiments were carried out to demonstrate the proposed decomposition technique, showing that this approach is fast, accurate and cost-effective.

50 µm core diameter Yb³âºAl³âº/F⁻ codoped silica fiber with M²<1.1 beam quality.

This paper reports, for the first time to our best knowledge, a nearly diffraction-limited output in a Yb(3+)/Al(3+)/F(-) codoped double cladding silica fiber with a 50 µm core diameter and 0.02 core NA. The core glass with a diameter >6 mm was fabricated through solgel process combined with high temperature sintering. Laser performances of this fiber at different bend diameters were studied. The mean M2<1.1 in this 50 µm core diameter fiber was achieved at a bend diameter of 0.35 m. The core glass with the refractive index nearly equal to pure silica glass is suitable for the fiber design, such as large-mode-area photonic crystal fiber.

Electrochemically supported deoxygenation of epoxides into alkenes in aqueous solution.

An efficient synthesis of alkenes from epoxides in a mixture of saturated aqueous NH(4)Br and tetrahydrofuran (8:1) has been developed in an undivided cell fitted with a pair of zinc electrodes, and it is proposed that the reaction is mediated by Zn(0) with a hierarchically organized nanostructure.