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With the rapid development of smart grids and distributed energy sources, the home energy management system (HEMS) is becoming a hot topic of research as a hub for connecting customers and utilities for energy visualization. Accurate forecasting of future short-term residential electricity demand for each major appliance is a key part of the energy management system. This paper aims to explore the current research status of household-level short-term load forecasting, summarize the advantages and disadvantages of various forecasting methods, and provide research ideas for short-term household load forecasting and household energy management. Firstly, the paper analyzes the latest research results and research trends in deep learning load forecasting methods in terms of network models, feature extraction, and adaptive learning; secondly, it points out the importance of combining probabilistic forecasting methods that take into account load uncertainty with deep learning techniques; and further explores the implications and methods for device-level as well as ultra-short-term load forecasting. In addition, the paper also analyzes the importance of short-term household load forecasting for the scheduling of electricity consumption in household energy management systems. Finally, the paper points out the problems in the current research and proposes suggestions for future development of short-term household load forecasting. [ABSTRACT FROM AUTHOR]

This paper researches the identification problem for the unknown parameters of the multivariate equation-error autoregressive systems. Firstly, the original identification model is decomposed into several sub-identification models according to the number of system outputs. Then, based on the characteristic that the information vector and the parameter vector are common among the sub-identification models, the coupling identification concept is used to propose a partially coupled generalized stochastic gradient algorithm. Furthermore, by expanding the scalar innovation of each subsystem model to the innovation vector, a partially coupled multi-innovation generalized stochastic gradient algorithm is proposed. Finally, the numerical simulations indicate that the proposed algorithms are effective and have good parameter estimation performances. [ABSTRACT FROM AUTHOR]

Simple Summary: Chicken meat has been proved to be a suspected source of extraintestinal pathogenic Escherichia coli (ExPEC), causing several diseases in humans, and bacteria in healthy chickens can contaminate chicken carcasses at the slaughter; however, reports about the prevalence and molecular characteristics of ExPEC in healthy chickens are still rare. In this study, among 926 E. coli isolates from healthy chickens in China, 22 (2.4%) were qualified as ExPEC and these ExPEC isolates were clonally unrelated. A total of six serogroups were identified in this study, with O78 being the most predominant type, and all the six serogroups had been frequently reported in human ExPEC isolates in many countries. All the 22 ExPEC isolates were multidrug-resistant and most isolates carried both blaCTX-M and fosA3 resistance genes. Notably, plasmid-borne colistin resistance gene mcr-1 was identified in six ExPEC isolates, among which two carried additional carbapenemase gene blaNDM, compromising both the efficacies of the two critically important drugs for humans, carbapenems and colistin. These results highlight that healthy chickens can serve as a potential reservoir for multidrug resistant ExPEC isolates, including mcr-1-containing ExPEC. Chicken products and chickens with colibacillosis are often reported to be a suspected source of extraintestinal pathogenic Escherichia coli (ExPEC) causing several diseases in humans. Such pathogens in healthy chickens can also contaminate chicken carcasses at the slaughter and then are transmitted to humans via food supply; however, reports about the ExPEC in healthy chickens are still rare. In this study, we determined the prevalence and characteristics of ExPEC isolates in healthy chickens in China. A total of 926 E. coli isolates from seven layer farms (371 isolates), one white-feather broiler farm (78 isolates) and 17 live poultry markets (477 isolates from yellow-feather broilers) in 10 cities in China, were isolated and analyzed for antibiotic resistance phenotypes and genotypes. The molecular detection of ExPEC among these healthy chicken E. coli isolates was performed by PCRs, and the serogroups and antibiotic resistance characteristics of ExPEC were also analyzed. Pulsed-field gel electrophoresis (PFGE) and Multilocus sequence typing (MLST) were used to analyze the genetic relatedness of these ExPEC isolates. We found that the resistance rate for each of the 15 antimicrobials tested among E. coli from white-feather broilers was significantly higher than that from brown-egg layers and that from yellow-feather broilers in live poultry markets (p < 0.05). A total of 22 of the 926 E. coli isolates (2.4%) from healthy chickens were qualified as ExPEC, and the detection rate (7.7%, 6/78) of ExPEC among white-feather broilers was significantly higher than that (1.6%, 6/371) from brown-egg layers and that (2.1%, 10/477) from yellow-feather broilers (p < 0.05). PFGE and MLST analysis indicated that clonal dissemination of these ExPEC isolates was unlikely. Serogroup O78 was the most predominant type among the six serogroups identified in this study, and all the six serogroups had been frequently reported in human ExPEC isolates in many countries. All the 22 ExPEC isolates were multidrug-resistant (MDR) and the resistance rates to ampicillin (100%) and sulfamethoxazole-trimethoprim (100%) were the highest, followed by tetracycline (95.5%) and doxycycline (90.9%). blaCTX-M was found in 15 of the 22 ExPEC isolates including 10 harboring additional fosfomycin resistance gene fosA3. Notably, plasmid-borne colistin resistance gene mcr-1 was identified in six ExPEC isolates in this study. Worryingly, two ExPEC isolates were found to carry both mcr-1 and blaNDM, compromising both the efficacies of carbapenems and colistin. The presence of ExPEC isolates in healthy chickens, especially those carrying mcr-1 and/or blaNDM, is alarming and will pose a threat to the health of consumers. To our knowledge, this is the first report of mcr-1-positive ExPEC isolates harboring blaNDM from healthy chickens. [ABSTRACT FROM AUTHOR]

A microbial fungicide developed from Bacillus subtilis NCD-2 has been registered for suppressing verticillium wilt in crops in China. Spores are the main ingredient of this fungicide and play a crucial role in suppressing plant disease. Therefore, increasing the number of spores of strain NCD-2 during fermentation is important for reducing the cost of the fungicide. In this study, five kinds of carbon sources were found to promote the metabolism of strain NCD-2 revealed via Biolog Phenotype MicroArray (PM) technology. L-arabinose showed the strongest ability to promote the growth and sporulation of strain NCD-2. L-arabinose increased the bacterial concentration and the sporulation efficiency of strain NCD-2 by 2.04 times and 1.99 times compared with D-glucose, respectively. Moreover, L-arabinose significantly decreased the autolysis of strain NCD-2. Genes associated with arabinose metabolism, sporulation, spore resistance to heat, and spore coat formation were significantly up-regulated, and genes associated with sporulation-delaying protein were significantly down-regulated under L-arabinose treatment. The deletion of msmX, which is involved in arabinose transport in the Bacillus genus, decreased growth and sporulation by 53.71% and 86.46% compared with wild-type strain NCD-2, respectively. Complementing the mutant strain by importing an intact msmX gene restored the strain's growth and sporulation. [ABSTRACT FROM AUTHOR]

Fusarium wilt, caused by Fusarium oxysporum, is one of the most notorious diseases of cash crops. The use of microbial fungicides is an effective measure for controlling Fusarium wilt, and the genus Bacillus is an important resource for the development of microbial fungicides. Fusaric acid (FA) produced by F. oxysporum can inhibit the growth of Bacillus, thus affecting the control efficacy of microbial fungicides. Therefore, screening FA-tolerant biocontrol Bacillus may help to improve the biocontrol effect on Fusarium wilt. In this study, a method for screening biocontrol agents against Fusarium wilt was established based on tolerance to FA and antagonism against F. oxysporum. Three promising biocontrol bacteria, named B31, F68, and 30833, were obtained to successfully control tomato, watermelon, and cucumber Fusarium wilt. Strains B31, F68, and 30833 were identified as B. velezensis by phylogenetic analysis of the 16S rDNA, gyrB, rpoB, and rpoC gene sequences. Coculture assays revealed that strains B31, F68, and 30833 showed increased tolerance to F. oxysporum and its metabolites compared with B. velezensis strain FZB42. Further experiments confirmed that 10 µg/mL FA completely inhibited the growth of strain FZB42, while strains B31, F68, and 30833 maintained normal growth at 20 µg/mL FA and partial growth at 40 µg/mL FA. Compared with strain FZB42, strains B31, F68, and 30833 exhibited significantly greater tolerance to FA. [ABSTRACT FROM AUTHOR]

Bacillus spp. is one kind of the important representative biocontrol agents against plant diseases and promoting plant growth. In this study, the whole genomic sequence of bacterial strain HMB26553 was obtained. A phylogenetic tree based on the genome and ANI (average nucleotide identity), as well as dDDH (digital DNA–DNA hybridization), was constructed, and strain HMB26553 was identified as Bacillus velezensis. Fourteen biosynthetic gene clusters responsible for secondary metabolite were predicted via anti-SMASH, and six secondary metabolites were identified by UHPLC-QTOF-MS/MS (ultra-high-performance liquid chromatography coupled to quadrupole-time-of-flight tandem mass spectrometry). When the phytopathogen Rhizoctonia solani was treated with B. velezensis HMB26553, the mycelial structure changed, ROS (reactive oxygen species) accumulated, and the mitochondrial membrane potential decreased. Characteristics of strain HMB26553 were predicted and confirmed by genomic information and experiments, such as producing IAA, siderophore, extracellular enzymes and biofilm, as well as moving and promoting cotton growth. All these results suggested the mechanisms by which B. velezensis HMB26553 inhibits pathogen growth and promotes cotton growth, which likely provided the potential biocontrol agent to control cotton Rhizoctonia damping-off. [ABSTRACT FROM AUTHOR]

In order to study the behavior of molten blast furnace slag ligament breakup into droplets by centrifugal granulation with a spinning cup, three-dimensional transient CFD model simulations were performed in the present work to study the process of the slag deformation into ligaments upon leaving the spinning cup, which eventually disintegrate into droplets. The formation of molten slag ligaments at the edge of the spinning cup and their disintegration into droplets were numerically revealed so that the behavior and mechanism of the slag ligament breakup into droplets could be investigated. This work specifically examined the influence of cup spinning speed on the diameter and length of the molten slag ligaments around the cup periphery and the diameter of the droplets produced. The simulation results show that, for the same slag flowrate, with the increase in cup spinning speed, the slag film thickness at the cup edge decreases, the number of molten slag ligaments increases, and the diameter of the ligaments decreases, thus reducing the diameter of slag droplets. Moreover, as the number of molten slag ligaments increases as a result of the increased cup spinning speed, the flowrate of a single ligament decreases, so that the ligament disintegrates in a shorter radial distance, that is, the length of the ligament is shortened. In addition, this work also investigated the behavior and mechanism of a single molten slag ligament breakup into droplets. It was found that the process of molten slag ligament breakup into droplets under the action of centrifugal force and surface tension can also be approximately explained by the theory of the Rayleigh disintegration mechanism. [ABSTRACT FROM AUTHOR]

Aiming at the mode of liquid ligament disintegration into droplets in the process of the centrifugal granulation of molten blast furnace slag using a spinning cup, in order to gain an in-depth understanding of the behavior and mechanism of droplet formation by liquid ligament disintegration and to obtain appropriate conditions to control the size of the produced slag granules, a three-dimensional CFD model describing water–air two-phase flow with a free surface was established in this work for simulating the process of a single water ligament breakup into droplets under the action of gravity, surface tension and inertial forces, so as to compare with the process of a molten slag ligament disintegration into droplets due to centrifugal force exerted by the spinning cup. By studying the disintegration behavior and mechanism of a single water ligament, the similar phenomenon of a molten slag ligament disintegration is examined. The numerical simulation results on the breakup of a single water ligament show that the length of the ligament before its disintegration and the diameter of the droplets formed both increase with the increase of the velocity of the ligament initially exiting a capillary nozzle. In addition, an experimental set-up was established in the laboratory to conduct cold physical model simulation experiments on single water or liquid paraffin ligament disintegration. The experimental results are compared with the numerical simulation results so that the reliability of the CFD model is verified. The results of the present study show that, in the centrifugal granulation process of blast furnace slag using a spinning cup operated in the ligament disintegration mode, the breakup of a single molten slag ligament is very similar to that of a single water or liquid paraffin ligament, and both approximately follow the Rayleigh Disintegration Mechanism, which provides a theoretical basis for analyzing the breakup process of the ligaments of different liquids as references for guiding the operation of centrifugal granulation of molten slag. [ABSTRACT FROM AUTHOR]

Simple Summary: Guanine nucleotide-binding protein-like 3-like (GNL3L) is a novel GTP-binding nucleolar protein. In this study, we analyzed the expression, prognosis, and immune roles of GNL3L in pan-cancer from multiple omics analyses. The final results showed that GNL3L is differentially expressed in a variety of cancers, plays a prognostic role, and has good immune value. Moreover, GNL3L may affect the occurrence of cancer through processes such as ribonucleoprotein, ribosomal RNA processing, and cell proliferation. At the same time, we established an esophageal cancer (ESCA) prediction model with strong predictive ability and proved that GNL3L can significantly affect the proliferation ability of esophageal cancer cells through clone formation assays. In conclusion, GNL3L is an important biomarker. Guanine nucleotide-binding protein-like 3-like protein (GNL3L) is a novel, evolutionarily conserved, GTP-binding nucleolar protein. This study aimed to investigate the expression, prognosis, and immune value of GNL3L in pan-cancer from multiple omics analyses. Firstly, the expression and prognostic value of GNL3L in pan-cancer were discussed using the TIMER2 database, the GEPIA database, the cBioportal database, COX regression analysis, and enrichment analysis. The association of GNL3L with tumor mutational burden (TMB), tumor microsatellite instability (MSI), mismatch repair (MMR) genes, and immune cells was then analyzed. Finally, an esophageal cancer (ESCA) prediction model was established, and GNL3L clone formation assays were performed. The final results showed that GNL3L is differentially expressed in the vast majority of cancers, is associated with the prognosis of various cancers, and may affect cancer occurrence through processes such as ribonucleoprotein, ribosomal RNA processing, and cell proliferation. At the same time, it was found that the correlation between GNL3L and TMB, MSI, MMR, and various immune cells is significant. The established ESCA prediction model had a strong predictive ability, and GNL3L could significantly affect the proliferation of esophageal cancer cells. In conclusion, GNL3L may serve as an important prognostic biomarker and play an immunomodulatory role in tumors. [ABSTRACT FROM AUTHOR]

Coastal wetland mapping plays an essential role in monitoring climate change, the hydrological cycle, and water resources. In this study, a novel classification framework based on the gravitational optimized multilayer perceptron classifier and extended multi-attribute profiles (EMAPs) is presented for coastal wetland mapping using Sentinel-2 multispectral instrument (MSI) imagery. In the proposed method, the morphological attribute profiles (APs) are firstly extracted using four attribute filters based on the characteristics of wetlands in each band from Sentinel-2 imagery. These APs form a set of EMAPs which comprehensively represent the irregular wetland objects in multiscale and multilevel. The EMAPs and original spectral features are then classified with a new multilayer perceptron (MLP) classifier whose parameters are optimized by a stability-constrained adaptive alpha for a gravitational search algorithm. The performance of the proposed method was investigated using Sentinel-2 MSI images of two coastal wetlands, i.e., the Jiaozhou Bay and the Yellow River Delta in Shandong province of eastern China. Comparisons with four other classifiers through visual inspection and quantitative evaluation verified the superiority of the proposed method. Furthermore, the effectiveness of different APs in EMAPs were also validated. By combining the developed EMAPs features and novel MLP classifier, complicated wetland types with high within-class variability and low between-class disparity were effectively discriminated. The superior performance of the proposed framework makes it available and preferable for the mapping of complicated coastal wetlands using Sentinel-2 data and other similar optical imagery. [ABSTRACT FROM AUTHOR]

The effective cryopreservation of mesenchymal stem cells (MSCs) is indispensable to the operation of basic research and clinical transplantation. The prevalent protocols for MSC cryopreservation utilize dimethyl sulfoxide (DMSO), which is easily permeable and able to protect MSCs from cryo-injuries, as a primary cryoprotectant (CPA). However, its intrinsic toxicity and adverse effects on cell function remain the bottleneck of MSC cryopreservation. In this work, we cryopreserved human umbilical cord mesenchymal stem cells (UCMSCs) using zwitterionic betaine combined with electroporation without any addition of DMSO. Betaine was characterized by excellent compatibility and cryoprotective properties to depress the freezing point of pure water and balance the cellular osmotic stress. Electroporation was introduced to achieve intracellular delivery of betaine, intending to further provide comprehensive cryoprotection on UCMSCs. Compared with DMSO cryopreservation, UCMSCs recovered from the protocol we developed maintained the normal viability and functions and reduced the level of reactive oxygen species (ROS) that are harmful to cell metabolism. Moreover, the in vivo distribution of thawed UCMSCs was consistent with that of fresh cells monitored by a bioluminescence imaging (BLI) system. This work opens a new window of opportunity for DMSO-free MSC cryopreservation using zwitterionic compounds like betaine combined with electroporation. [ABSTRACT FROM AUTHOR]

High-definition mapping of 3D lane lines has been widely needed for the highway documentation and intelligent navigation of autonomous systems. A mobile mapping system (MMS) captures both accurate 3D LiDAR point clouds and high-resolution images of lane markings at highway driving speeds, providing an abundant data source for combined lane mapping. This paper aims to map lanes with an MMS. The main contributions of this paper include the following: (1) an intensity correction method was introduced to eliminate the reflectivity inconsistency of road-surface LiDAR points; (2) a self-adaptive thresholding method was developed to extract lane markings from their complicated surroundings; and (3) a LiDAR-guided textural saliency analysis of MMS images was proposed to improve the robustness of lane mapping. The proposed method was tested with a dataset acquired in Wuhan, Hubei, China, which contained straight roads, curved roads, and a roundabout with various pavement markings and a complex roadside environment. The experimental results achieved a recall of 96.4%, a precision of 97.6%, and an F-score of 97.0%, demonstrating that the proposed method has strong mapping ability for various urban roads. [ABSTRACT FROM AUTHOR]