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The high penetration of the renewables makes the power grid operation less reliable and risky. Demand Response programs can provide flexible capacity to alleviate the operational pressure. In a typical competitive retail market, the electricity retailer can incentivize the consumers to provide demand reduction in the reserve market and obtain additional profit from the grid. In the wholesale and reserve market, the participants receive a two-part income of certain revenue and activation revenue. In this paper, the optimal strategy of the electricity retailers is studied, including two proposed retail plans as well as the retailer’s bidding strategy in the wholesale reserve market. The proposed strategy is proven effective through a case study, demonstrating that introducing incentive-based demand response in the retail plan creates a win-win-win situation for the grid, retailers, and consumers. The experiment demonstrates that competitive bundles can generate at least 22 % additional revenue for retailers, while customized bundles can bring in an additional 23 % revenue for retailers and contribute to the system with an extra 9 % in reserve capacity bidding.

ObjectiveThis study aimed to explore the relationship between smoking status and the interval to brain metastasis in patients with non-small cell lung cancer (NSCLC) and its impact on survival time after brain metastasis.MethodsData were collected from patients with NSCLC with brain metastases who were treated at our centre between January 2005 and December 2017. Clinical indices such as clinicopathological features and smoking status were recorded, and patients were followed up until 1 September 2022. Based on our inclusion and exclusion criteria, 461 patients were analysed and matched using 1:1 propensity score matching. Three balanced groups were formed: non-smoking (n = 113), smoking cessation (n = 113), and smoking (n = 113). The interval to brain metastasis and overall survival were compared between the groups.ResultsThere was a statistically significant difference in the interval to brain metastasis between the non-smoking and smoking cessation groups (p = 0.001), as well as between the non-smoking and smoking groups (p < 0.001). However, the difference between the smoking cessation and smoking groups was not statistically significant (p = 0.106). Multivariate and univariate analyses identified smoking status, clinical stage, lung cancer surgery, chemotherapy, and chest radiotherapy as independent predictors of the interval to brain metastasis. Additionally, the multivariate analysis showed that smoking status, driver gene mutations, and chest radiotherapy independently influenced survival after brain metastasis.ConclusionSmoking status in patients with NSCLC affects the interval to brain metastasis and survival after brain metastasis.

PurposeLung cancer is a devastating disease, with brain metastasis being one of the most common distant metastases of lung adenocarcinoma. This study aimed to investigate the prognostic characteristics of individuals with brain metastases originating from invasive lung adenocarcinoma of distinct pathological subtypes, providing a reference for the management of these patients.MethodsClinical data from 156 patients with lung adenocarcinoma-derived brain metastases were collected, including age, sex, smoking status, Karnofsky Performance Status scores, pathological subtype, lymph node metastasis, tumor site, treatment mode, T stage, and N stage. Patients were classified into two groups (highly differentiated and poorly differentiated) based on their pathological subtypes. Propensity score matching was used to control for confounding factors. The prognostic value of pathological subtypes was assessed using Kaplan-Meier analysis and Cox proportional hazards regression modeling.ResultsKaplan-Meier analysis indicated that patients in the moderately to highly differentiated group had better prognoses. Multivariate analysis revealed that being in the poorly differentiated group was a risk factor for poorer prognosis. Thoracic tumor radiation therapy, chemotherapy, and surgery positively influenced the time interval between lung cancer diagnosis and brain metastasis.ConclusionsThe pathological subtypes of lung adenocarcinoma-derived brain metastases are associated with patient prognosis. Patients in the poorly differentiated group have worse prognoses compared to those in the moderately to highly differentiated group. Therefore, patients in the poorly differentiated group may require more frequent follow-ups and aggressive treatment.

Plants can activate protective and defense mechanisms under biotic and abiotic stresses. Their roots naturally grow in the soil, but when they encounter sunlight in the top-soil layers, they may move away from the light source to seek darkness. Here we investigate the skototropic behavior of roots, which promotes their fitness and survival. Glutamate-like receptors (GLRs) of plants play roles in sensing and responding to signals, but their role in root skototropism is not yet understood. Light-induced tropisms are known to be affected by auxin distribution, mainly determined by auxin efflux proteins (PIN proteins) at the root tip. However, the role of PIN proteins in root skototropism has not been investigated yet. To better understand root skototropism and its connection to the distance between roots and light, we established five distance settings between seedlings and darkness to investigate the variations in root bending tendencies. We compared differences in root skototropic behavior across different expression lines of Arabidopsis thaliana seedlings (atglr3.7 ko, AtGLR3.7 OE, and pin2 knockout) to comprehend their functions. Our research shows that as the distance between roots and darkness increases, the root’s positive skototropism noticeably weakens. Our findings highlight the involvement of GLR3.7 and PIN2 in root skototropism.

The TianQin program is an independently proposed space-borne detection initiative from China. The inertial sensor, as a crucial component, is susceptible to disturbances from temperature fluctuations, the impact of which on acceleration measurements remains elusive. Therefore, a comprehensive analysis on the influence of temperature disturbance is necessary to avoid errors in acceleration measurement. In this study, we proposed a complete scheme for calculating the level of acceleration noise. Based on the traditional temperature control scheme of using a heat pipe, we developed a systematic heat transfer simulation model to obtain the temperature signals. These signals can then be converted into the frequency domain and used to calculate the acceleration noise level within the target bandwidth. Our results indicate that, with a temperature control of 0.13 K/Hz1/2@1 mHz, the largest contributions to acceleration noise come from the outgassing effect, radiometer effect, and radiative pressure effect, in descending order. The total noise peak is 3.6×10−12 m/(s2⋅Hz1/2) at 1 mHz, which is more than three orders of magnitude higher than the TianQin target of 10−15 m/(s2⋅Hz1/2). This study provides new avenues for evaluating measurement errors and solutions for the TianQin program.

Increasing incidences showed that food allergies have attracted more and more attention from researchers. BALB/c mice were sensitized with wheat gluten combined with aluminum hydroxide adjuvant via intraperitoneal injection, transdermal sensitization, and oral gavage sensitization route. Results showed that all the three sensitization methods could induce allergic symptoms; increase the serum antibody (total immunoglobulin E (IgE), specific IgE, IgG, IgA) and histamine content; promote the secretion of Th2 cytokines (interleukin (IL)-4, IL-5, IL-13) and inflammatory factors (IL-6, IL-17A, IL-10); and inhibit the production of Th1 cytokines (IFN-γ, IL-2). However, the allergic symptoms of mice sensitized by intraperitoneal injection were the most obvious among the three models. The level of serum antibodies in intraperitoneal injection group was significantly higher than control. Subsequently, 16S rRNA sequencing technology was used to analyze the intestinal flora of mice. The results showed that the abundance of Firmicutes in the wheat protein sensitized group was lower than that in the normal group, while the abundance of Bacteroidetes was higher, and Lactobacillus was the difference marker in normal group. Bacterial species diversity analysis showed that the species richness and diversity of intestinal flora in mice were decreased, the difference between mice induced by intraperitoneal injection and normal control group mice was the most significant. Taken together, these results show that among three sensitization methods used to build a mouse model with aluminum hydroxide as adjuvant, intraperitoneal injection is the comparably best way to build a mouse sensitization mode.

Coxsackievirus A10 (CVA10) has recently emerged as one of the major causative agents of hand, foot, and mouth disease. CVA10 may also cause a variety of complications. No approved vaccine or drug is currently available for CVA10. The residues of CVA10 critical for viral attachment, infectivity and in vivo pathogenicity have not been identified by experiment. Here, we report the identification of CVA10 residues important for binding to cellular receptor KREMEN1. We identified VP2 N142 as a key receptor-binding residue by screening of CVA10 mutants resistant to neutralization by soluble KREMEN1 protein. The receptor-binding residue N142 is exposed on the canyon rim but highly conserved in all naturally occurring CVA10 strains, which provides a counterexample to the canyon hypothesis. Residue N142 when mutated drastically reduced receptor-binding activity, resulting in decreased viral attachment and infection in cell culture. More importantly, residue N142 when mutated reduced viral replication in limb muscle and spinal cord of infected mice, leading to lower mortality and less severe clinical symptoms. Additionally, residue N142 when mutated could decrease viral binding affinity to anti-CVA10 polyclonal antibodies and a neutralizing monoclonal antibody and render CVA10 resistant to neutralization by the anti-CVA10 antibodies. Overall, our study highlights the essential role of VP2 residue N142 of CVA10 in the interactions with KREMEN1 receptor and neutralizing antibodies and viral virulence in mice, facilitating the understanding of the molecular mechanisms of CVA10 infection and immunity. Our study also provides important information for rational development of antibody-based treatment and vaccines against CVA10 infection.

Abstract In this study, an intelligent energy management method is introduced to deal with the hydrogen‐dominant hybrid energy system with low carbon consideration. Specially, both the new type fuel cell, solid oxide fuel cell, and chemical battery are subtly modelled to construct a high‐efficient hybrid energy system, in which the thermodynamics feature and accurate battery model characteristics, as well as low carbon effect, are considered. Because the hybrid energy system incorporates various complex dynamic operation features that are hard to capture via conventional operation strategy, an energy management method based on deep reinforcement learning techniques is proposed to guide the intelligent operation with self‐adaptive performance. In the simulation, it is observed that highly efficient use of hydrogen in the hybrid energy system with the aid of chemical battery could achieve good economic benefit, as well as low carbon advantages. Powered by the gas and chemical energy coupling storage effect and state‐of‐the‐art machine learning methods, the proposed intelligent energy management strategy can benefit more renewable energy adoption and guarantee the ultimate environmental friendly low carbon ecosystem in the long‐term future.

Abstract Background As one of the fundamental problems in bioinformatics, the double digest problem (DDP) focuses on reordering genetic fragments in a proper sequence. Although many algorithms for dealing with the DDP problem were proposed during the past decades, it is believed that solving DDP is still very time-consuming work due to the strongly NP-completeness of DDP. However, none of these algorithms consider the privacy issue of the DDP data that contains critical business interests and is collected with days or even months of gel-electrophoresis experiments. Thus, the DDP data owners are reluctant to deploy the task of solving DDP over cloud. Results Our main motivation in this paper is to design a secure outsourcing computation framework for solving the DDP problem. We at first propose a privacy-preserving outsourcing framework for handling the DDP problem by using a cloud server; Then, to enable the cloud server to solve the DDP instances over ciphertexts, an order-preserving homomorphic index scheme (OPHI) is tailored from an order-preserving encryption scheme published at CCS 2012; And finally, our previous work on solving DDP problem, a quantum inspired genetic algorithm (QIGA), is merged into our outsourcing framework, with the supporting of the proposed OPHI scheme. Moreover, after the execution of QIGA at the cloud server side, the optimal solution, i.e. two mapping sequences, would be transferred publicly to the data owner. Security analysis shows that from these sequences, none can learn any information about the original DDP data. Performance analysis shows that the communication cost and the computational workload for both the client side and the server side are reasonable. In particular, our experiments show that PP-DDP can find optional solutions with a high success rate towards typical test DDP instances and random DDP instances, and PP-DDP takes less running time than DDmap, SK05 and GM12, while keeping the privacy of the original DDP data. Conclusion The proposed outsourcing framework, PP-DDP, is secure and effective for solving the DDP problem.

Abstract Dysregulation of T cell differentiation protein 2 (MAL2) has been observed in multiple cancers, but its exact role in lung cancer is poorly understood. Here we report a role of MAL2 in accelerating cell proliferation in non-small cell lung cancer (NSCLC). MAL2 expression enhances cell proliferation in both cell and nude mouse models. Mechanistically, overexpression of MAL2 results in the hyper-activation of the MAPK/mTOR signaling pathway in NSCLC cells which leads to active ribosome biogenesis. Importantly, pharmacological inhibition of mTOR or MEK lowered the abundance of PCNA, a marker of tumor cell proliferation, and subsequently suppressed ribosome biogenesis, cell growth and xenograft growth in mouse model. MAL2 upregulation in clinical tumors is also linked to worse prognosis. Overall our data reveal that MAL2 is a potential diagnostic biomarker and targeting the MAL2/MAPK/mTOR signaling pathway may improve therapeutic strategy and efficacy for this subset of NSCLC patients.

Abstract Senecavirus A (SVA) is a cause of vesicular disease in pigs, and infection rates are rising within the swine industry. Recently, anthrax toxin receptor 1 (ANTXR1) was revealed as the receptor for SVA in human cells. Herein, the role of ANTXR1 as a receptor for SVA in pigs was investigated by CRISPR/Cas9 genome editing. Strikingly, ANTXR1 knockout (KO) pigs exhibited features consistent with the rare disease, GAPO syndrome, in humans. Fibroblasts from wild type (WT) pigs supported replication of SVA; whereas, fibroblasts from KO pigs were resistant to infection. During an SVA challenge, clinical symptoms, including vesicular lesions, and circulating viremia were present in infected WT pigs but were absent in KO pigs. Additional ANTXR1-edited piglets were generated that were homozygous for an in-frame (IF) mutation. While IF pigs presented a GAPO phenotype similar to the KO pigs, fibroblasts showed mild infection, and circulating SVA nucleic acid was decreased in IF compared to WT pigs. Thus, this new ANTXR1 mutation resulted in decreased permissiveness of SVA in pigs. Overall, genetic disruption of ANTXR1 in pigs provides a unique model for GAPO syndrome and prevents circulating SVA infection and clinical symptoms, confirming that ANTXR1 acts as a receptor for the virus.

Abstract Emergencies often result in uncontrollable bleeding, which is thought to be the leading cause of death at the scene of the injured. Among various hemostasis scenarios, collagen fiber (CF) is gradually replacing traditional hemostatic materials due to its superior properties and ease of sourcing from animals. Herein, we use CF and the natural herbaceous Bletilla striata as raw materials to prepare a collagen fiber-oxidized Bletilla striata composite hemostatic sponge (CFOB). During the cross-linking process, the triple helix structure of collagen stays intact, and its porous three-dimensional network structure brings excellent bulkiness and water absorption properties. Experiments show that the optimal amount of sponge CFOB-10, namely oxidized Bletilla striata polysaccharide 0.5 mg/mL and CF 5 mg/mL, only needed 25 ± 4.06 s for hemostasis time in the rat liver hemorrhage model. In addition, CFOB meets the safety performance requirements of cytotoxicity classification standard 0. Therefore, the optimal amount of CFOB is an excellent new hemostatic material with application potential. Graphical Abstract

Abstract Climate change has led to increasing frequency of sudden extreme heavy rainfall events in cities, resulting in great disaster losses. Therefore, in emergency management, we need to be timely in predicting urban floods. Although the existing machine learning models can quickly predict the depth of stagnant water, these models only target single points and require large amounts of measured data, which are currently lacking. Although numerical models can accurately simulate and predict such events, it takes a long time to perform the associated calculations, especially two-dimensional large-scale calculations, which cannot meet the needs of emergency management. Therefore, this article proposes a method of coupling neural networks and numerical models that can simulate and identify areas at high risk from urban floods and quickly predict the depth of water accumulation in these areas. Taking a drainage area in Tianjin Municipality, China, as an example, the results show that the simulation accuracy of this method is high, the Nash coefficient is 0.876, and the calculation time is 20 seconds. This method can quickly and accurately simulate the depth of water accumulation in high-risk areas in cities and provide technical support for urban flood emergency management.

The unified weighing scheme for the local-linear smoother in analysing functional data can deal with data that are dense, sparse or of neither type. In this paper, we focus on the convergence rate of functional principal component analysis using this method. Almost sure asymptotic consistency and rates of convergence for the estimators of eigenvalues and eigenfunctions have been established. We also provide the convergence rate of the variance estimation of the measurement error. Based on the results, the number of observations within each curve can be of any rate relative to the sample size, which is consistent with the earlier conclusions about the asymptotic properties of the mean and covariance estimators.

Preeclampsia is a multi-factorial and multi-genetic disorder that affects more than eight million mother and baby pairs each year. Currently, most of the attention to the pathogenesis of preeclampsia has been focused on placenta, but recent progresses suggest that excellent decidualization lays foundation for placentation and growth. Moreover, preeclampsia is associated with an imbalance in immunoregulatory mechanisms, however, how the immune regulatory system in the decidua affects preeclampsia is still unclear. In our study, after intersecting the genes of differentially expressed between preeclampsia and the control gotten by conventional expression profile analysis and the genes contained in the ligand receptor network, we found eight differentially expressed genes in a ligand-receptor relationship, and the eight genes have a characteristic: most of them participate in the interaction between decidual macrophages and other decidual immune cells. The results of single-cell sequencing of decidual cells further demonstrated that decidual macrophages affect the functions of other immune cells through export. As a result, abnormal gene expression affects the export function of decidual macrophages, which in turn affects the interaction of decidual macrophages with other immune cells, thereby destroying the original immune regulation mechanism, and ultimately leading to the occurrence of preeclampsia.

Arteriviruses are enveloped positive-strand RNA viruses that assemble and egress using the host cell's exocytic pathway. In previous studies, we demonstrated that most arteriviruses use a unique -2 ribosomal frameshifting mechanism to produce a C-terminally modified variant of their nonstructural protein 2 (nsp2). Like full-length nsp2, the N-terminal domain of this frameshift product, nsp2TF, contains a papain-like protease (PLP2) that has deubiquitinating (DUB) activity, in addition to its role in proteolytic processing of replicase polyproteins. In cells infected with porcine reproductive and respiratory syndrome virus (PRRSV), nsp2TF localizes to compartments of the exocytic pathway, specifically endoplasmic reticulum-Golgi intermediate compartment (ERGIC) and Golgi complex. Here, we show that nsp2TF interacts with the two major viral envelope proteins, the GP5 glycoprotein and membrane (M) protein, which drive the key process of arterivirus assembly and budding. The PRRSV GP5 and M proteins were found to be poly-ubiquitinated, both in an expression system and in cells infected with an nsp2TF-deficient mutant virus. In contrast, ubiquitinated GP5 and M proteins did not accumulate in cells infected with the wild-type, nsp2TF-expressing virus. Further analysis implicated the DUB activity of the nsp2TF PLP2 domain in deconjugation of ubiquitin from GP5/M proteins, thus antagonizing proteasomal degradation of these key viral structural proteins. Our findings suggest that nsp2TF is targeted to the exocytic pathway to reduce proteasome-driven turnover of GP5/M proteins, thus promoting the formation of GP5-M dimers that are critical for arterivirus assembly.

Objective. Preeclampsia (PE) is a severe complication in pregnancy and a leading cause of maternal and infant mortality. However, the exact underlying etiology of PE remains unknown. Emerging evidence indicates that the cause of PE is associated with genetic factors. Therefore, the aim of this study is to identify susceptibility genes to PE. Materials and Methods. Human Exome BeadChip assays were conducted using 370 cases and 482 controls and 21 loci were discovered. A further independent set of 958 cases and 1007 controls were recruited for genotyping to determine whether the genes of interest ROS1 and PTPRK are associated with PE. Immunohistochemistry was used for localization. Both qPCR and Western blotting were utilized to investigate the levels of PTPRK in placentas of 20 PE and 20 normal pregnancies. Results. The allele frequency of PTPRK rs3190930 differed significantly between PE and controls and was particularly significant in severe PE subgroup and early-onset PE subgroup. PTPRK is primarily localized in placental trophoblast cells. The mRNA and protein levels of PTPRK in PE were significantly higher than those in controls. Conclusion. These results suggest that PTPRK appears to be a previously unrecognized susceptibility gene for PE in Han Chinese women, and its expression is also associated with PE, while ROS1 rs9489124 has no apparent correlation with PE risk.

BACKGROUND: Nitric oxide (NO) has been shown to be important in sperm function, and the concentration of NO appears to determine these effects. Studies have demonstrated both positive and negative effects of NO on sperm function, but have not been able to provide a clear link between NO concentration and the extent of exposure to NO. To study the relationship between nitric oxide and sperm capacitationin vitro, and to provide a theoretical basis for the use of NO-related preparations in improving sperm motility for in vitro fertilization, we investigated the effects of NO concentration and time duration at these concentrations on in vitro sperm capacitation in both normal and abnormal sperm groups. We manipulated NO concentrations and the time duration of these concentrations using sodium nitroprusside (an NO donor) and NG-monomethyl-L-argenine (an NO synthase inhibitor). RESULTS: Compared to the normal sperm group, the abnormal sperm group had a longer basal time to reach the appropriate concentration of NO (p < 0.001), and the duration of time at this concentration was longer for the abnormal sperm group (p < 0.001). Both the basal time and the duration of time were significantly correlated with sperm viability and percentage of progressive sperm (p < 0.001). The experimental group had a significantly higher percentage of progressive sperm than the control group (p < 0.001). CONCLUSIONS: We hypothesize that there is a certain regularity to both NO concentration and its duration of time in regards to sperm capacitation, and that an adequate duration of time at the appropriate NO concentration is beneficial to sperm motility.

Quantitative analysis for the flue gas of natural gas-fired generator is significant for energy conservation and emission reduction. The traditional partial least squares method may not deal with the nonlinear problems effectively. In the paper, a nonlinear partial least squares method with extended input based on radial basis function neural network (RBFNN) is used for components prediction of flue gas. For the proposed method, the original independent input matrix is the input of RBFNN and the outputs of hidden layer nodes of RBFNN are the extension term of the original independent input matrix. Then, the partial least squares regression is performed on the extended input matrix and the output matrix to establish the components prediction model of flue gas. A near-infrared spectral dataset of flue gas of natural gas combustion is used for estimating the effectiveness of the proposed method compared with PLS. The experiments results show that the root-mean-square errors of prediction values of the proposed method for methane, carbon monoxide, and carbon dioxide are, respectively, reduced by 4.74%, 21.76%, and 5.32% compared to those of PLS. Hence, the proposed method has higher predictive capabilities and better robustness.

This paper develops the estimation method of mean and covariance functions of functional data with additional covariate information. With the strength of both local linear smoothing modeling and general weighing scheme, we are able to explicitly characterize the mean and covariance functions with incorporating covariate for irregularly spaced and sparsely observed longitudinal data, as typically encountered in engineering technology or biomedical studies, as well as for functional data which are densely measured. Theoretically, we establish the uniform convergence rates of the estimators in the general weighing scheme. Monte Carlo simulation is conducted to investigate the finite-sample performance of the proposed approach. Two applications including the children growth data and white matter tract dataset obtained from Alzheimer's Disease Neuroimaging Initiative study are also provided. [ABSTRACT FROM AUTHOR]

Abstract Fructus hippophae (Hippophae rhamnoides spp. mongolica×Hippophae rhamnoides sinensis), a hybrid variety of sea buckthorn that Hippophae rhamnoides spp. mongolica serves as the female parent and Hippophae rhamnoides sinensis serves as the male parent, is a traditional plant with great potentials of economic and medical values. Herein, we gained a chromosome-level genome of Fructus hippophae about 918.59 Mb, with the scaffolds N50 reaching 83.65 Mb. Then, we anchored 440 contigs with 97.17% of the total genome sequences onto 12 pseudochromosomes. Next, de-novo, homology and transcriptome assembly strategies were adopted for gene structure prediction. This predicted 36475 protein-coding genes, of which 36226 genes could be functionally annotated. Simultaneously, various strategies were used for quality assessment, both the complete BUSCO value (98.80%) and the mapping rate indicated the high assembly quality. Repetitive elements, which occupied 63.68% of the genome, and 1483600 bp of non-coding RNA were annotated. Here, we provide genomic information on female plants of a popular variety, which can provide data for pan-genomic construction of sea buckthorn and for the resolution of the mechanism of sex differentiation.