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Unpiloted technology requires attitude measurement from global positioning system to adjust the moving direction of car. However, the measurement result from the satellites suffer from fluctuation, which reduces the control ability of system. Thus, we propose our novel algorithm. First, it builds double difference observation equation based the measurements from two satellites. Second, the least squares algorithm is utilized to calculate double difference integer ambiguity. Third, it constructs the length of baseline to calculate baseline vector, which improves the solution success rate of integer ambiguity and reduces frequency of mutation occurs in attitude angle solving process. Finally, baseline vector is employed to solve the attitude angle of unpiloted car. The extensive experimental results demonstrate that the success rate of the attitude reach 95% within 2° of error under the constraint of the baseline, and the error of the attitude is less than 1° under the dynamic condition. [ABSTRACT FROM AUTHOR]

Over the past few years, the software engineering (SE) community has widely employed deep learning (DL) techniques in many source code processing tasks. Similar to other domains like computer vision and natural language processing (NLP), the state‐of‐the‐art DL techniques for source code processing can still suffer from adversarial vulnerability, where minor code perturbations can mislead a DL model's inference. Efficiently detecting such vulnerability to expose the risks at an early stage is an essential step and of great importance for further enhancement. This paper proposes a novel black‐box effective and high‐quality adversarial attack method, namely CodeBERT‐Attack (CBA), based on the powerful large pre‐trained model (i.e., CodeBERT) for DL models of source code processing. CBA locates the vulnerable positions through masking and leverages the power of CodeBERT to generate textual preserving perturbations. We turn CodeBERT against DL models and further fine‐tuned CodeBERT models for specific downstream tasks, and successfully mislead these victim models to erroneous outputs. In addition, taking the power of CodeBERT, CBA is capable of effectively generating adversarial examples that are less perceptible to programmers. Our in‐depth evaluation on two typical source code classification tasks (i.e., functionality classification and code clone detection) against the most widely adopted LSTM and the powerful fine‐tuned CodeBERT models demonstrate the advantages of our proposed technique in terms of both effectiveness and efficiency. Furthermore, our results also show (1) that pre‐training may help CodeBERT gain resilience against perturbations further, and (2) certain pre‐training tasks may be beneficial for adversarial robustness. [ABSTRACT FROM AUTHOR]

Traffic flow prediction is a crucial research area in traffic management. Accurately predicting traffic flow in each area of the city over the long term can enable city managers to make informed decisions regarding the allocation of urban transportation resources in the future. The existing traffic flow prediction models either give insufficient attention to the interactions of long-lasting spatio-temporal regions or extract spatio-temporal features in a single scale, which ignores the identification of traffic flow patterns at various scales. In this paper, we present a multi-scale spatio-temporal information fusion model using non-local networks, which fuses traffic flow pattern features at multiple scales in space and time, complemented by non-local networks to construct the global direct dependence relationship between local areas and the entire region of the city in space and time in the past. The proposed model is evaluated through experiments and is shown to outperform existing benchmark models in terms of prediction performance. [ABSTRACT FROM AUTHOR]

Synapse loss is one of the most critical features in Alzheimer's disease (AD) and correlates with cognitive decline. Astrocytes mediate synapse elimination through multiple EGF-like domains 10 (MEGF10) pathways in the developing and adult brain to build the precise neural connectivity. However, whether and how astrocytes mediate synapse loss in AD remains unknown. We here find that the phagocytic receptor MEGF10 of astrocytes is significantly increased in vivo and in vitro, which results in excessive engulfment of synapses by astrocytes in APP/PS1 mice. We also observe that the astrocytic lysosomal-associated membrane protein 1 (LAMP1) is significantly elevated, colocalized with the engulfed synaptic puncta in APP/PS1 mice, and astrocytic lysosomes contain more engulfed synaptic puncta in APP/PS1 mice relative to wild type mice. Together, our data provide evidence that astrocytes excessively engulf synapses in APP/PS1 mice, which is mediated by increased MEGF10 and activated lysosomes. The approach targeting synapse engulfment pathway in astrocytes would be a potent therapy for AD. [ABSTRACT FROM AUTHOR]

The expression level of SLC35A3 is associated with the prognosis of many cancers, but its role in colorectal cancer (CRC) is unclear. The purpose of our study was to elucidate the role of SLC35A3 in CRC. The expression levels of SLC35A3 in CRC were evaluated through tumor immune resource assessment (TIMER), The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), International Cancer Genome Consortium (ICGC), Human Protein Atlas (HPA), qRT-PCR, and immunohistochemical evaluation. TCGA, GEO, and ICGC databases were used to analyze the diagnostic and prognostic value of SLC35A3 in CRC. A overall survival (OS) model was constructed and validated based on the expression level of SLC35A3 and multivariable analysis results. The cBioPortal tool was used to analyze SLC35A3 mutation in CRC. The UALCAN tool was used to analyze the promoter methylation level of SLC35A3 in colorectal cancer. In addition, the role of SLC35A3 in CRC was determined through GO analysis, KEGG analysis, gene set enrichment analysis (GSEA), immune infiltration analysis, and immune checkpoint correlation analysis. In vitro experiments validated the function of SLC35A3 in colorectal cancer cells. Compared with adjacent normal tissues and colonic epithelial cells, the expression of SLC35A3 was decreased in CRC tissues and CRC cell lines. Low expression of SLC35A3 was associated with N stage, pathological stage, and lymphatic infiltration, and it was unfavorable for OS, disease-specific survival (DSS), recurrence-free survival (RFS), and post-progression survival (PPS). According to the Receiver Operating Characteristic (ROC) analysis, SLC35A3 is a potential important diagnostic biomarker for CRC patients. The nomograph based on the expression level of SLC35A3 showed a better predictive model for OS than single prognostic factors and TNM staging. SLC35A3 has multiple types of mutations in CRC, and its promoter methylation level is significantly decreased. GO and KEGG analysis indicated that SLC35A3 may be involved in transmembrane transport protein activity, cell communication, and interaction with neurotransmitter receptors. GSEA revealed that SLC35A3 may be involved in energy metabolism, DNA repair, and cancer pathways. In addition, SLC35A3 was closely related to immune cell infiltration and immune checkpoint expression. Immunohistochemistry confirmed the positive correlation between SLC35A3 and helper T cell infiltration. In vitro experiments showed that overexpression of SLC35A3 inhibited the proliferation and invasion capability of colorectal cancer cells and promoted apoptosis. The results of this study indicate that decreased expression of SLC35A3 is closely associated with poor prognosis and immune cell infiltration in colorectal cancer, and it can serve as a promising independent prognostic biomarker and potential therapeutic target. [ABSTRACT FROM AUTHOR]

Metallo-helicoids are constructed by intermolecular coordination interactions between covalent linear polymer and tritopic/hexatopic molecular templates. These metallo-polymers with helicoidal conformation exhibit high antimicrobial activities against both Gram-positive and Gram-negative pathogens. [ABSTRACT FROM AUTHOR]

The cogging torque reduction methods in permanent magnet (PM) machines are more or less FEA trial and error-based and cause undesirable side effects, such as distorted back EMF, new harmonic components, and structure asymmetry. A slot-opening grouping method can address these issues. However, it needs to model all slots in FEA design validation during practical cogging torque optimization iterations, and also leads to back-EMF reduction. In this paper, a new grouping strategy, termed in-phase unit (IPU), is introduced, together with the slot-opening angle-shift method. The slot openings with the same cogging torque distribution pattern are grouped into an IPU, and the cogging torque peaks of the slot openings within an IPU can now be interleaved. Thereby, the major harmonic components of the cogging torque are cancelled out, instead of being summed up. The IPU grouping principle, the slot-opening shift angle computation, and the selection of the harmonic order to cancel are analyzed in detail. By comparison, the proposed method not only simplifies cogging torque optimization iterations by only modeling the slots in one IPU in FEA, but also compensates for the back-EMF constant reduction. The effectiveness of the proposed methods is validated by two typical interior PM machine design cases. [ABSTRACT FROM AUTHOR]

Drought is a misfortune for agriculture and human beings. The annual crop yield reduction caused by drought exceeds the sum of all pathogens. As one of the gatekeepers of China's "granary", rice is the most important to reveal the key drought tolerance factors in rice. Rice seedlings of Nipponbare (Oryza sativa L. ssp. Japonica) were subjected to simulated drought stress, and their root systems were analyzed for the non-targeted metabolome and strand-specific transcriptome. We found that both DEGs and metabolites were enriched in purine metabolism, and allantoin accumulated significantly in roots under drought stress. However, few studies on drought tolerance of exogenous allantoin in rice have been reported. We aimed to further determine whether allantoin can improve the drought tolerance of rice. Under the treatment of exogenous allantoin at different concentrations, the drought resistant metabolites of plants accumulated significantly, including proline and soluble sugar, and reactive oxygen species (ROS) decreased and reached a significant level in 100 μmol L−1. To this end, a follow-up study was identified in 100 μmol L−1 exogenous allantoin and found that exogenous allantoin improved the drought resistance of rice. At the gene level, under allantoin drought treatment, we found that genes of scavenge reactive oxygen species were significantly expressed, including peroxidase (POD), catalase (CATA), ascorbate peroxidase 8 (APX8) and respiratory burst oxidase homolog protein F (RbohF). This indicates that plants treated by allantoin have better ability to scavenge reactive oxygen species to resist drought. Alternative splicing analysis revealed a total of 427 differentially expressed alternative splicing events across 320 genes. The analysis of splicing factors showed that gene alternative splicing could be divided into many different subgroups and play a regulatory role in many aspects. Through further analysis, we restated the key genes and enzymes in the allantoin synthesis and catabolism pathway, and found that the expression of synthetase and hydrolase showed a downward trend. The pathway of uric acid to allantoin is completed by uric acid oxidase (UOX). To find out the key transcription factors that regulate the expression of this gene, we identified two highly related transcription factors OsERF059 and ONAC007 through correlation analysis. They may be the key for allantoin to enhance the drought resistance of rice. [ABSTRACT FROM AUTHOR]

Simple Summary: Previous studies have confirmed the effects of livestock grazing on the habitat use of ground-nesting birds, while little is known about the effects of livestock on their behaviour. In this study, we used camera traps to investigate the effects of livestock presence on the spatio-temporal patterns and behaviour of Reeves's Pheasant. We found that livestock presence altered the behavioural patterns of Reeves's Pheasant. The findings suggest the need to incorporate behavioural impacts into wildlife conservation. Protected areas are seeing an increase in anthropogenic disturbances in the world. Previous studies have demonstrated the impact of livestock grazing and human presence on the habitat use of birds, whereas little is known about the effect of free-ranging livestock on bird behaviour. Reeves's Pheasant (Syrmaticus reevesii) is endemic to China and has been threatened by habitat loss and fragmentation, illegal logging, and human disturbance over the past 20 years. Based on camera trapping in the Liankangshan National Nature Reserve (LKS) and the Zhonghuashan Birds Provincial Nature Reserve (ZHS), we explore the effects of livestock grazing and human activities on the spatio-temporal distribution and behavioural patterns of Reeves's Pheasant. Livestock does not appear to affect habitat use by the pheasant but changes its behavioural patterns. In addition, pheasants in areas with livestock foraged mostly during the early morning, while in areas without livestock, they foraged at dusk. Therefore, the study concludes that livestock intensity in nature reserves may have reduced pheasant suitability through altered patterns of vigilance and foraging behaviour. [ABSTRACT FROM AUTHOR]

Background: Ultraviolet (UV) radiation‐induced oxidative stress is the main cause of photodamage to the skin. Glutathione (GSH) serves important physiological functions, including scavenging oxygen‐free radicals and maintaining intracellular redox balance. γ‐glutamylcysteine (γ‐GC), as an immediate precursor of GSH and harboring antioxidant and anti‐inflammatory properties, represents an unexplored option for skin photodamage treatment. Purpose: The purpose of this study was to investigate whether γ‐GC can reduce UVB‐induced NIH‐3T3 cell damage. Methods: The experimental groups were as follows: control, UVB radiation, UVB radiation after pretreatment with γ‐GC. Cell counting kit‐8 (CCK‐8) assays were used to measure cell proliferation, flow cytometry, and immunoblotting to detect the apoptosis rate and apoptosis‐associated proteins. The levels of Reactive Oxygen Species (ROS), Superoxide Dismutase (SOD), and GSH/GSSG (oxidized GSH) were measured to assess oxidative stress. Immunoblotting and immunofluorescence were used to detect DNA damage. The members of the MAPK signaling pathways were detected by immunoblotting. Results: UVB irradiation significantly reduced cell viability and destroyed the oxidative defense system. Pretreatment with γ‐GC reduced UVB‐induced cytotoxicity, restored the oxidation defense system, and inhibited activation of the MAPK pathway. It also reduced the apoptosis rate, downregulated the levels of cleaved caspase 3 and cleaved PARP. Furthermore, pretreatment with γ‐GC reduced the accumulation of γH2AX after UVB radiation exposure, indicating that γ‐GC could protect cells from DNA damage. Conclusion: γ‐GC protected NIH‐3T3 from damage caused by UVB irradiation. The photoprotective effect of γ‐GC is mediated via strengthening the endogenous antioxidant defense system, which prevents DNA damage and inhibits the activation of the MAPK pathway. [ABSTRACT FROM AUTHOR]

The calcium signaling pathway is critical for plant growth, development, and response to external stimuli. The CBL–CIPK pathway has been well characterized as a calcium-signaling pathway. However, in most reports, only a single function for this module has been described. Here, we examined multiple functions of this module. CIPK showed a similar distribution to that of CBL, and OsCBL and OsCIPK families were retained after experiencing whole genome duplication events through the phylogenetic and synteny analysis. This study found that OsCBL8 negatively regulated rice seed germination and seedling growth by interacting with OsCIPK17 with overexpression and gene editing mutant plants as materials combining plant phenotype, physiological indicators and transcriptome sequencing. This process is likely mediated by OsPP2C77, which is a member of the ABA signaling pathway. In addition, OsCBL mediated the targeting of OsNAC77 and OsJAMYB by OsCIPK17, thus conferring resistance to high temperatures and pathogens in rice. Our work reveals a unique signaling pathway, wherein OsCBL8 interacts with OsCIPK17 and provides rice with multiple resistance while also regulating seedling growth. [ABSTRACT FROM AUTHOR]

Alcohol abuse is a major cause of alcoholic liver disease (ALD) and can result in fibrosis and cirrhosis. γ‐glutamylcysteine (γ‐GC) is a precursor of glutathione (GSH) with antioxidant and anti‐inflammatory properties. Our research aimed to explore the protective impact of γ‐GC on ALD and its potential mechanisms of efficiency in vitro and in vivo. L02 cells were pretreated with γ‐GC (20, 40, and 80 μM) for 2 h and exposed to ethanol for 24 h. Cell viability, apoptosis, oxidative stress, and inflammatory levels were measured. The expression of protein cleaved caspase‐3 and cleaved PARP and flow cytometry results indicated that γ‐GC decreases apoptosis on L02 cells after ethanol treatment. Moreover, γ‐GC also attenuated oxidative stress and mitochondrial damage in hepatocytes caused by ethanol via increasing cellular GSH, SOD activity, and mitochondrial membrane potential. In vivo experiments, γ‐GC effectively reduced the AST, ALT, and TG levels in mice. The inflammation of ALD was alleviated by γ‐GC both in vivo and in vitro. Additionally, histopathological examination demonstrated that γ‐GC treatment lessened lipid droplet formation and inflammatory damage. In conclusion, these results showed that γ‐GC has anti‐inflammatory and anti‐apoptotic effects on ALD because it could help hepatocytes maintain sufficient GSH levels to combat the excess reactive oxygen species (ROS) generated during ethanol metabolism. Practical applications: Alcohol intake is the fifth highest risk factor for premature death and disability among all risk variables. However, few medicines are both safe and effective for the treatment of ALD. As a direct precursor of GSH, γ‐GC has a broad variety of potential antioxidant and anti‐inflammatory applications for the treatment of numerous medical conditions. In conclusion, these results showed that γ‐GC could protect cells from ALD via suppressing oxidative stress, alleviating inflammation, and preventing apoptosis. [ABSTRACT FROM AUTHOR]

Anomaly detection is an important yet challenging task in medical image analysis. Most anomaly detection methods are based on reconstruction, but the performance of reconstruction-based methods is limited due to over-reliance on pixel-level losses. To address the limitation, we propose a patch-wise contrastive learning-based auto-encoder for medical anomaly detection. The key contribution is the patch-wise contrastive learning loss that provides supervision on local semantics to enforce semantic consistency between corresponding input–output patches. Contrastive learning pulls corresponding patch pairs closer while pushing non-corresponding ones apart between input and output, enabling the model to learn local normal features better and improve discriminability on anomalous regions. Additionally, we design an anomaly score based on local semantic discrepancies to pinpoint abnormalities by comparing feature difference rather than pixel variations. Extensive experiments on three public datasets (i.e. , brain MRI, retinal OCT, and chest X-ray) achieve state-of-the-art performance, with our method achieving over 99% AUC on retinal and brain images. Both the contrastive patch-wise supervision and patch-discrepancy score provide targeted advancements to overcome the weaknesses in existing approaches. • A patch-wise contrastive learning-based auto-encoder is proposed to optimize local semantic reconstruction for medical anomaly detection. • A novel local semantic discrepancy-based anomaly score is proposed to achieve improved localization to assist clinicians in lesion detection. • Experiments validate that the proposed method outperforms state-of-the-art anomaly detection results across three modalities, i.e., brain MRI, retinal OCT, and chest X-ray images. [ABSTRACT FROM AUTHOR]

The organosilicon intermediate containing hydrophilic tertiary amines was synthesized from N-Methylmonoethanolamine (MEA) and (3-glycidyloxypropyl) trimethoxy silane (GPTMS), followed by neutralization with acetic acid (Ac). Meanwhile, a polyurethane (PU) prepolymer was prepared by sequentially polymerizing hexamethylene diisocyanate trimer (HT-100) with polyethylene glycol (PEG-600) and methoxy polyethylene glycol (MPEG), and then chain extended by the intermediate. Ultimately, methyl ethyl ketone oxime (MEKO) was selected to block the remaining NCO group, forming a branched polyisocyanate crosslinker. Subsequently, a linear polyisocyanate crosslinker was prepared in the same system by polymerizing hexamethylene diisocyanate (HDI) with the intermediate. Consequently, an organosilicon-modified waterborne blocked polyisocyanate crosslinker with a semi-interpenetrating network structure was obtained and further processed through hydrolysis to obtain the corresponding crosslinker containing silanol groups. The structure and thermal properties of the crosslinkers were analyzed using 1H NMR, FT-IR, TG, and DTG. Furthermore, the comprehensive mechanical properties of the cured films were investigated. The results indicate that the crosslinker system containing silanol groups exhibits superior performance. When the films' maximum adhesion and the wiping resistance were optimized at 1.97 MPa and 72 times, respectively, the impact resistance still maintained above 85 cm. • The introduction of organosilicon into the polyisocyanate crosslinker structure can realize multiple crosslinking for resins • The crosslinker has a semi-interpenetrating network structure and exhibits excellent mechanical properties in applications • Organosilicon-modified waterborne blocked polyisocyanate might have good application prospects in waterborne coatings [ABSTRACT FROM AUTHOR]

We investigate stochastic gradient decent (SGD) for solving full infinite dimensional ill-posed problems in Hilbert spaces. We allow for batch-size versions of SGD where the randomly chosen batches incur noise fluctuations. Based on the corresponding bias-variance decomposition we provide bounds for the root mean squared error. These bounds take into account the discretization levels, the decay of the step-size, which is more flexible than in existing results, and the underlying smoothness in terms of general source conditions. This allows to apply SGD to severely ill-posed problems. The obtained error bounds exhibit three stages of the performance of SGD. In particular, the pre-asymptotic behavior can be well seen. Some numerical studies verify the theoretical predictions. [ABSTRACT FROM AUTHOR]

Simple Summary: Human disturbance has a strong impact on the movement of wild animals. The Reeves's Pheasant is listed as an endangered species by the International Union for Conservation of Nature (IUCN) and a nationally protected species in China. This study evaluated how the movement patterns of this species responded to human disturbance. We observed large differences in movement characteristics between sexes during the breeding season of Reeves's Pheasants, and found that reproduction had a significant effect on the movement of females. Males shifted their movement peaks to earlier times in the day to avoid the presence peaks of humans. The greater the distance to human-modified habitat, the higher the movement intensity of males, and the lower the movement intensity of females. This study suggested that the potential impacts of different forms of human disturbance on wildlife should be considered in future conservation planning. Human disturbance has a strong impact on the movement of wild animals. However, it remains unclear how the movement patterns of the Reeves's Pheasant (Syrmaticus reevesii) respond to human disturbance in human-dominated landscapes. We tracked the movement of 40 adult individual Reeves's Pheasants during the breeding season, and used the dynamic Brownian bridge motion model and kernel density estimation to analyze the diurnal movement patterns of Reeves's Pheasants and their response to human presence. We analyzed the paths of Reeves's Pheasants based on a partial least squares path model, considering habitat conditions, body characteristics, and reproductive behaviors. We found that males had two clear diurnal movement peaks, whereas reproductive and non-reproductive females did not show such movement peaks. Males shifted their movement peaks to earlier times in the day to avoid the presence peaks of humans. The correlation between human-modified habitat and the movement intensity of Reeves's Pheasant differed between sexes. For males, the distance to forest paths had a positive correlation with their movement intensity through affecting body conditions. For females, the distance to forest paths and farmland had a negative correlation with their movement intensity through affecting habitat conditions and reproductive behaviors. Our study provides a scientific basis for the protection of the Reeves's Pheasant and other related terrestrial forest-dwelling birds. [ABSTRACT FROM AUTHOR]

Objective: Hedyotis diffusa-Scutellaria barbata herb pair (HS) has therapeutic effects on a variety of cancers, and this study aims to systematically explore the multiple mechanisms of HS in the treatment of colorectal cancer (CRC). Methods. The active ingredients of HS were obtained from TCMSP, and the potential targets related to these ingredients were screened from the STITCH, SuperPred, and Swiss TargetPrediction databases. Targets associated with CRC were retrieved by Drugbank, TTD, DisGeNET, and GeneCards. We used a Venn diagram to screen the intersection targets and used Cytoscape to construct the herb-ingredient-target-disease network, and the core targets were selected. The Go analysis and KEGG pathway annotation were performed by R language software. We used PyMol and Autodock Vina to achieve molecular docking of core ingredients and targets. Results: A total of 33 active ingredients were obtained from the HS, and 762 CRC-related targets were reserved from the four databases. We got 170 intersection targets to construct the network and found that the four ingredients with the most targets were quercetin, luteolin, baicalein, and dinatin, which were the core ingredients. The PPI analysis showed that the core targets were STAT3, TP53, MAPK3, AKT1, JUN, EGFR, MYC, VEGFA, EGF, and CTNNB1. Molecular docking results showed that these core ingredients had good binding potential with core targets, especially the docking of each component with MAPK obtained the lowest binding energy. HS acts simultaneously on various signaling pathways related to CRC, including the PI3K-Akt signaling pathway, proteoglycans in cancer, and the MAPK signaling pathway. Conclusions: This study systematically analyzed the active ingredients, core targets, and central mechanisms of HS in the treatment of CRC. It reveals the role of HS targeting PI3K-Akt signaling and MAPK signaling pathways in the treatment of CRC. We hope that our research could bring a new perspective to the therapy of CRC and find new anticancer drugs. [ABSTRACT FROM AUTHOR]

Zn-Ni coatings were fabricated via ultrasonic-assisted cathodic plasma electrolysis deposition (US-CPED) technology. The results demonstrate that ultrasonic assistance can significantly affect the deposition and growth process of Zn-Ni coatings, which is attributed to ultrasonic vibration reducing the diameter of bubbles and inducing a more uniform distribution of the vapor gaseous envelope (VGE) on the surface of the substrate. The Zn-Ni coatings with more homogeneous microstructure were formed due to the more uniform plasma discharge process on the surface of the substrate based on the VGE uniform distribution. Compared to the Zn-Ni coatings without ultrasonic assistance, the thickness and roughness of Zn-Ni coatings with ultrasonic assistance increased by >80 % and decreased by over 40 %, respectively. Better Zn-Ni coating quality brings higher corrosion resistance. In addition, ultrasound can accelerate the iteration of bubbles in VGE to enhance the work-hardening effect, improving the mechanical properties of the Zn-Ni coatings. This work introduces a novel insight into the controllability of the CPED process and paves the way for exploring other methods to stabilize the CPED process. • Zn-Ni coating was prepared by the US-CPED method. • The application of ultrasound improves coatings' hardness and corrosion resistance. • The application of ultrasound makes the plasma discharge process more uniform. [ABSTRACT FROM AUTHOR]

How to simultaneously regulate the residence time of polydisperse particles and completely inhibit particle backmixing remains a challenge of fluidization technology. In this study, it is shown that adding elutriation pipes into multiple-chamber fluidized beds to strengthen particle elutriation and entrainment is an effective measure. Coarse-grained CFD-DEM simulation results show that the addition of the elutriation pipe can completely inhibit the particle back-mixing between adjacent chambers, and the mean residence time (MRT) ratio of coarse and fine particles can be regulated to be larger than their diameter ratio. Furthermore, a study on the numbered-up multiple-chamber fluidized beds find that (i) the MRT ratio of coarse and fine particles can be larger than the 1.5th power of their diameter ratio with full suppression of particle back-mixing between adjacent chambers; (ii) the MRT of each size of particles is a linear function of chamber number, whereas the MRT ratio approaches an asymptotic value. The results are of guiding significance for improving the overall conversion rate of polydisperse particles. [Display omitted] • Numbered-up multiple-chamber fluidized beds is optimized using coarse-grained CFD-DEM simulations. • The particle back-mixing between adjacent chambers can be completely inhibited. • The particles MRT increases linearly, the MRT ratio of coarse and fine particles has a theoretical maximum value. • The MRT ratio of coarse and fine particles can be further increased to be larger than d p c / d p f 1.5. [ABSTRACT FROM AUTHOR]

The accessibility of healthcare system is vulnerable to various types of hazards, where the failure of one system component may lead to a diffusion of the pressure and result in cascading failures. This study proposes a network-based simulation framework for robustness assessment of access to healthcare through integrating cascading failure mechanism. Weighted complex networks are constructed to model the accessible patient transfer under both general and elderly healthcare scenarios. The cascade failure mechanism is incorporated into the constructed networks, and several attack strategies (including random, initial degree (ID), initial betweenness (IB), recalculated degree (RD), and recalculated betweenness (RB) attack) are adopted to simulate the process of system robustness assessment. Results indicate that the proposed framework enables to discover the vulnerable nodes in the constructed healthcare accessibility networks, where the robustness metric combining network efficiency and relative size of the largest component acts as a benchmark; all the intentional attack strategies outperform the random attack strategy, which indicates the effectiveness of the detection of vulnerable healthcare facilities by the developed model; and the metrics of node degree and betweenness centrality make progress on identifying the vulnerable healthcare facility nodes, which should be taken heed of to optimize the management and operation of healthcare systems. [ABSTRACT FROM AUTHOR]

Convectional optimal pulsewidth modulation (PWM) current ripple reduction methods divide the vector space sectors into subsectors, where the reference vector is synthesized with a theoretically optimal sequence. However, extra CPLD/FPGA is needed for the lookup table and the PWM signal generation for alternative sequences. Moreover, when swapping in between sequences, extra switching and losses are introduced, which is particularly significant for low sample ratio operations. This article starts with an intuitive perspective on the sequence for current ripple reduction. Then, an online method is proposed to dynamically compute and select the sequence with the lower current ripples throughout the vector space. The proposed stationary frame current ripple vector locus peak computation and comparison methods can be efficiently implemented in DSPs. The proposed online method is equally effective in ripple reduction as the CPLD/FPGA based offline-optimized methods. Moreover, with low sample ratio commonly used in practice, the proposed method has even less switching losses, as it avoids extra switching during the sequences swapping. Elaborate lab setup makes it possible to obtain the switching losses of the previous methods over wide ranges of motor drive operation. Thereby, the switching losses advantages of the proposed method are validated. [ABSTRACT FROM AUTHOR]

The acceleration of low carbon development and carbon emission reduction (CER) policies have compelled power systems to act and consider carbon emissions in their dispatches. To realize CER, power system economic dispatch has become more challenging. The integrated energy system (IES) can significantly reduce the production of carbon emissions. In light of this, this paper proposes a bi-objective optimization model to coordinate the operating cost and carbon emission of the IES and a sensitivity analysis approach to evaluate the impact of CER. First, the coupling relationship between energy and carbon in the IES is analyzed. Second, the bi-objective optimization model of the IES is proposed, in which the thermal inertia is embedded to provide operational flexibility. Third, three sensitivity metrics and the corresponding models are proposed to quantify the impact of global/local CER of IES, including the cost of global CER, the cost of local CER, and the sensitivity of local CER. Finally, the dispatch procedure and algorithm are introduced. Case studies demonstrate the effectiveness of the proposed method, in which the impact of thermal inertia and battery capacity on dispatch results and CER sensitivity is analyzed. • A novel bi-objective optimization model is proposed for the low-carbon operation of IES. • Three sensitivity analysis models are proposed to quantify the impacts of global/local carbon emission reduction. • An evenly distributed Pareto frontier is obtained using the normalized normal constraint method. • The effect of the thermal inertia of the district heating system on the carbon emission reduction is investigated. [ABSTRACT FROM AUTHOR]

Background: Multiple pathological manifestations are rarely present in patients with primary hyperparathyroidism (PHPT). Here we described a case of a young woman who presented with multiple skeletal destructions and received an unclear diagnosis at several hospitals. Case presentation: A 30-year-old woman was admitted to our hospital due to pain in both knees and walking difficulty that lasted for 6 and 2 years, respectively. Her laboratory test results revealed a high parathyroid hormone level (822 pg/ml) and hypercalcemia (2.52 mmol/L) in the blood. Parathyroid imaging revealed a lumpy concentration of radioactive uptake detected at the lower pole in the right lobe of the thyroid, and was nearly 2.2 cm * 2.4 cm in size. Next, the patient was treated with parathyroidectomy that resulted in a significant improvement in physiological and clinical symptoms. Moreover, the skeletal destruction and bone mineral density were significantly improved after a 5-years follow-up period. Conclusions: Multiple skeletal destructions can be caused by PHPT that should be taken into consideration in young patients with complex bone lesions. [ABSTRACT FROM AUTHOR]

Voltage balance of series capacitors is crucial for multilevel converters. In this article, a new voltage self-balance mechanism based on zero-voltage switching (ZVS) for a three-level dc–dc converter is proposed. First, the near-CRM (critical conduction mode) to realize ZVS and its resonance transition are analyzed in detail. Then, the resonance times at peak and valley currents are analytically expressed, and it is discovered that the additional duty cycles are induced by the ZVS resonant transitions between the switch parasitic capacitors and resonance inductor. Meanwhile, the unbalanced capacitor voltages alter the initial resonance conditions, so that the resulting additional duty cycles tend to counteract the unbalanced voltages. To further quantify the proposed voltage self-balance mechanism, not only the relationships between the effective duty cycle and the unbalanced voltages are formulated, but also the overall feedback mechanism of the passive voltage self-balance is modeled and illustrated. Finally, a three-level dc–dc converter prototype is constructed to experimentally verify the ZVS and voltage self-balance mechanism in the near-CRM mode. [ABSTRACT FROM AUTHOR]

The authors consider a randomized solution to ill-posed operator equations in Hilbert spaces. In contrast to statistical inverse problems, where randomness appears in the noise, here randomness arises in the low-rank matrix approximation of the forward operator, which results in using a Monte Carlo method to solve the inverse problems. In particular, this approach follows the paradigm of the study N. Halko et al 2011 SIAM Rev. 53 217–288, and hence regularization is performed based on the low-rank matrix approximation. Error bounds for the mean error are obtained which take into account solution smoothness and the inherent noise level. Based on the structure of the error decomposition the authors propose a novel algorithm which guarantees (on the mean) a prescribed error tolerance. Numerical simulations confirm the theoretical findings. [ABSTRACT FROM AUTHOR]

Integrated energy systems (IESs) are composed of multiple heterogeneous subsystems, i.e., electrical power system, natural gas system, and district heating system (DHS), which endow the whole system with excellent performance in overall efficiency and renewable energy utilization. The paper aims to offer a concise and analytical model for the thermal dynamic characteristics (i.e., thermal inertia) of the district heating network (DHN) and buildings to facilitate the analysis, planning, and operation of IESs. Firstly, an equivalent start network is introduced for modeling the radial DHN, and a synchronous response model is proposed for buildings to approximate the optimal response of heat load. Secondly, the thermal inertia aggregation model (TIAM) is proposed, which offers an accurate DHN and buildings model for the planning and operation of IESs. Finally, some properties of the TIAM are derived to reveal its potential in general applications such as analysis and evaluation. Simulation results of different scale systems demonstrate the performance of the proposed model and reveal its advantages in the computational efficiency and sensitive information protection of DHN. [ABSTRACT FROM AUTHOR]

The continuing quest for aluminum castings with fewer defects has aroused the interest in rheological high-pressure die casting (RHPDC). A new machine, stirring integrated transfer-heat (SIT) device, based on the mechanical stirring and enhanced cooling for semisolid slurry preparation was proposed to produce the thin-walled communication shell part by RHPDC process. The influence of SIT process characteristics on the microstructure was studied. The microstructure of SIT-RHPDC shell part in different locations was investigated. Combined with simulation, the flow characteristics and the temperature field change in the melt under the stirring-only process and different stirring with internal water-cooling conditions were studied to get a better understanding of the nucleation, grain growth and solidification behavior. Under the dual action of agitation and heat dissipation in SIT device, the fluid convection has changed the temperature field of the melt significantly. The temperature field of the melt becomes relatively uniform from a great temperature gradient and the continuous cooling rate is increased to 5 °C/s. In the same time, the slurry has a greater supercooling degree, and flows more evenly in the filling process. The experimental results indicate that compared with microstructure of an HPDC component, the microstructure at different locations of SIT-RHPDC part is composed of refined rosiness and nearly spherical particles. [ABSTRACT FROM AUTHOR]

Summary: Many researchers have focused on liquid‐cooled devices with simple structure and high efficiency, which promoted the gradual development of the mini‐channel liquid‐cooled plate battery thermal management system (BTMS), due to the advancement of liquid cooling technology. This paper has proposed an electrochemical‐thermal coupling model to numerically predict the thermal behavior of the battery pack in different parameters of mini‐channel cold plates and optimize the parameter combinations. The effects of cooling plate width, mini‐channel interval, and inlet mass flow rate on the heat dissipation performance of the system were analyzed at a constant C‐rate to provide a reliable experimental basis for the optimization model. Results indicate that increasing the cold plate width and the inlet mass flow rate reduce the temperature and temperature gradients. In addition, the minimum temperature difference is obtained at the mini‐channel interval of 6 mm. The optimum cooling plate width (90 mm), mini‐channel interval (4 mm), and inlet mass flow rate (80 g/s) are determined using the orthogonal test, analysis of variance, and comprehensive analysis of multi‐index results. The addition of an auxiliary cooling system based on the optimized combination further reduces the maximum temperature and temperature difference of the battery pack by 4.9% and 9.2%, respectively. The developed strategy and methods can further improve the performance of the BTMS and provide a reference for the development of a compact battery pack at high discharge rates for engineering applications. [ABSTRACT FROM AUTHOR]

We discuss the problem of parameter choice in learning algorithms generated by a general regularization scheme. Such a scheme covers well-known algorithms as regularized least squares and gradient descent learning. It is known that in contrast to classical deterministic regularization methods, the performance of regularized learning algorithms is influenced not only by the smoothness of a target function, but also by the capacity of a space, where regularization is performed. In the infinite dimensional case the latter one is usually measured in terms of the effective dimension. In the context of supervised learning both the smoothness and effective dimension are intrinsically unknown a priori. Therefore we are interested in a posteriori regularization parameter choice, and we propose a new form of the balancing principle. An advantage of this strategy over the known rules such as cross-validation based adaptation is that it does not require any data splitting and allows the use of all available labeled data in the construction of regularized approximants. We provide the analysis of the proposed rule and demonstrate its advantage in simulations. • For smooth kernels, a power decay of effective dimensions may not be appropriate. • Learning rates under general smoothness assumptions on target functions. • Optimal learning rates in all involved norms based on a novel bound. • An adaptive parameter choice which uses the whole dataset without data splitting. [ABSTRACT FROM AUTHOR]

This paper studies a Nyström-type subsampling approach to large kernel learning methods in the misspecified case, where the target function is not assumed to belong to the reproducing kernel Hilbert space generated by the underlying kernel. This case is less understood in spite of its practical importance. To model such a case, the smoothness of target functions is described in terms of general source conditions. It is surprising that almost for the whole range of the source conditions, describing the misspecified case, the corresponding learning rate bounds can be achieved with just one value of the regularization parameter. This observation allows a formulation of mild conditions under which the plain Nyström subsampling can be realized with subquadratic cost maintaining the guaranteed learning rates. [ABSTRACT FROM AUTHOR]

An iron-catalyzed C–H sulfonylmethylation of indoles in water–PEG400 has been developed using p -toluenesulfonylmethyl isocyanide. This protocol enables direct regioselective construction of Csp2 –Csp3 bond at the C3 position of indoles with a broad range of substrate compatibility in moderate to good yields, which is cost-effective and environmentally friendly. [ABSTRACT FROM AUTHOR]

The binary mixture of magnetite powder and fine coal was used to investigate the adjustment of bed density and fluidization stability of air dense medium gas-solid fluidized bed (ADMGFB) through theoretical and experimental approaches. An optimum calculated model was selected to predict incipient fluidization velocities with different weight proportions of fine coal (x c). A modified model of the bed density of ADMGFB using binary dense media was derived based on the two-phase fluidization theory with experimental verification. Bed density stability and fluidization uniformity were achieved based on the investigation distribution of bed density and fine coal of each bed layer. The separation experiments of raw coal using ADMGFB were carried out with N of 1.3. When x c was less than 16%, the probable errors were no more than 0.07 g/cm3. Results indicated that the satisfactory separation performance of raw coal was achieved using ADMGFB based on the binary dense media. Unlabelled Image • The optimum correlation of incipient fluidization velocity was achieved. • A modified model to predict bed density was established. • The binary dense media broadened the range of the bed density. • The separation efficiency was improved using binary dense media. [ABSTRACT FROM AUTHOR]

Measuring the error by an ℓ 1 {\ell^{1}} -norm, we analyze under sparsity assumptions an ℓ 0 {\ell^{0}} -regularization approach, where the penalty in the Tikhonov functional is complemented by a general stabilizing convex functional. In this context, ill-posed operator equations A ⁢ x = y {Ax=y} with an injective and bounded linear operator A mapping between ℓ 2 {\ell^{2}} and a Banach space Y are regularized. For sparse solutions, error estimates as well as linear and sublinear convergence rates are derived based on a variational inequality approach, where the regularization parameter can be chosen either a priori in an appropriate way or a posteriori by the sequential discrepancy principle. To further illustrate the balance between the ℓ 0 {\ell^{0}} -term and the complementing convex penalty, the important special case of the ℓ 2 {\ell^{2}} -norm square penalty is investigated showing explicit dependence between both terms. Finally, some numerical experiments verify and illustrate the sparsity promoting properties of corresponding regularized solutions. [ABSTRACT FROM AUTHOR]

This paper studies the high power density bidirectional dc–dc converter with interleaving, soft-switching, and near critical conduction mode (near-CRM) operation. Systematic design and control methods are proposed to enhance the effectiveness of passive currents balancing between multiple interleaved phases without using individual phase current feedbacks. This paper first analyzes the zero voltage turn-on operation, including the turn-off energy diversion by the added snubber capacitor and the turn-off resonance models. Second, the intrinsic inverse co-relation between the phase current deviation and the resulting effective duty cycles variation is quantitatively formulated and modeled as a closed-loop mechanism that balances the currents passively. Then, the design constraints of the system parameters including the snubber capacitance, dead time, and valley currents of the near-CRM mode are formulated to guarantee the effectiveness of counteracting the current unbalance. Finally, a variable switching frequency control is proposed to actively control the valley current and maintain the current balancing effectiveness throughout the operating range. An IGBT-based 20-kW three-phase interleaved prototype with the maximum efficiency of 99.1% is constructed to verify the proposed design and control methods. [ABSTRACT FROM AUTHOR]

A room was treated to be predominantly retroreflective in the high frequency range by introducing arrays of cube corner retroreflectors (CCRs) over most surfaces (excluding the floor). In a small room (volume 55 m3), 156 CCRs in the form of square trihedra with 350 mm edge lengths were used as wall and ceiling treatment. The horizontal plane distribution of reflected energy was measured from omnidirectional sources, and a head and torso simulator was used to measure voice support. Results show a high concentration of reflected energy returned to omnidirectional source positions in high frequency octave bands (2–8 kHz). Finite-difference time-domain (FDTD) simulations of the room yielded similar distributions to the omnidirectional measurements, showing greater sound concentration when more CCRs are introduced. By contrast, FDTD simulation of an equivalent flat-surfaced room yielded no reflected sound concentration at the source, with results close to diffuse field theory in high frequency octave bands. Measured voice support values derived from oral-binaural room impulse responses exceed diffuse theory expectations by 5 dB. Thus, the paper demonstrates that retroreflective array treatment can change room acoustical conditions, concentrating reflected energy onto an arbitrarily located source. [ABSTRACT FROM AUTHOR]

The intense solids back-mixing has been one of the major disadvantages of gas-solid fluidized bed reactors for certain applications. In this study, coarse-grained CFD-DEM simulations are carried out to regulate the solids back-mixing in multiple-chamber fluidized beds by investigating the effect of the orifice size, the orifice location, the gas velocity of each chamber, and then the effect of the pipe length connecting adjacent chambers. The results indicate that optimizing the orifice size, the orifice location, and the gas velocity of each chamber can suppress the solids back-mixing to a certain extent. However, there is still a gap between the optimized design and the ideal situation. Therefore, using a sufficiently long pipe instead of a baffle with orifice is further proposed to completely suppress the solids back-mixing between adjacent chambers, which is validated using coarse-grained CFD-DEM simulations. Present results provide a means to regulate the solids back-mixing in multiple-chamber fluidized beds via proper design of bed geometry. [Display omitted] • Multiple chamber fluidized bed is optimized using coarse-grained CFD-DEM simulations. • The solids back-mixing can be regulated via proper reactor design. • A sufficiently long pipe connecting adjacent chambers enables the full suppression of solids back-mixing. [ABSTRACT FROM AUTHOR]

Abstract We consider an inverse problem arising in laser-induced thermotherapy, a minimally invasive method for cancer treatment, in which cancer tissues is destroyed by coagulation. For the dosage planning quantitatively reliable numerical simulation are indispensable. To this end the identification of the thermal growth kinetics of the coagulated zone is of crucial importance. Mathematically, this problem is a nonlinear and nonlocal parabolic inverse heat source problem. We show in this paper that the temperature dependent thermal growth parameter can be identified uniquely from a one-point measurement. [ABSTRACT FROM AUTHOR]

Highlights • W20-SPIONs are an oligomer-targeted MRI probe for early diagnosis of PD and HD. • W20-SPIONs were designed by conjugating oligomer-specific antibody W20 to SPIONs. • W20-SPIONs can reach the amyloid oligomer area in brain after intravenous injection. • W20-SPIONs can provide MRI signal to distinguish PD and HD mouse models from healthy controls. Abstract It is widely accepted that amyloid oligomers are the most toxic species to initiate the pathologic processes of Parkinson's disease (PD) and Huntingdon's disease (HD). But there is no definitive diagnosis for PD and HD at their early stages. Here, we conjugated an amyloid oligomer-specific scFv antibody (W20) to PEGylated superparamagnetic iron oxide nanoparticles (SPIONs) and detected the properties of the SPIONs conjugated with W20. The results showed that W20-SPIONs, with the size of around 11.8 nm in diameter, were stable and nontoxic, and had enough relaxation capacity to be used as an MRI contrast agent. When applied to the transgenic mouse models of PD and HD, W20-SPIONs crossed the blood-brain barrier and specifically bound to the oligomer area to give MRI signal, distinguishing PD and HD from healthy controls. These results indicated that W20-SPIONs had potential in early-stage diagnosis for PD and HD and also opened up a new strategy for evaluating the efficacy of new drugs. [ABSTRACT FROM AUTHOR]

Abstract The thermo-elastic behaviour induced by temperature in composite structures has become a significant factor in structural design. In this paper, a three-dimensional thermo-elastic theory for composite cross-ply laminated plates was discretized by a differential quadrature hierarchical finite element method (DQHFEM). The DQHFEM is a weak-form differential quadrature method using hierarchical bases that can provide highly accurate results using only a few sampling points. Flexible and efficient wedge (triangular prism) and hexahedron elements were constructed and applied to three-dimensional (3D) analyses of cross-ply laminated plates and shells for the first time. Compared with various models in literatures, the DQHFEM showed very good agreements with exact solutions based on 3D elastic theory. The thermo-mechanical analyses of cross-ply laminated plates and shells based on 3D theory indicate that the DQHFEM is an effective method for high accuracy analyses with low computational costs, because the DQHFEM can provide results with high accuracy by using only several nodes on the thickness direction. [ABSTRACT FROM AUTHOR]

Modular prefabricated buildings effectively improve the efficiency and quality of building design and construction and represent an important trend in the development of building industrialization. However, there are still many deficiencies in the design and technology of existing systems, especially in terms of the integration of architectural performance defects that cannot respond to occupants’ comfort, flexibility, and energy-saving requirements throughout the building’s life cycle. This research takes modular prefabricated steel structural systems as its research object and sets the detailed design of an integrated modular envelope system as the core content. First, the researcher chose two types of thermal insulation materials, high insulation panels and aerogel blankets, in order to study the construction details of integrated building envelopes for modular prefabricated buildings. Focusing on the weakest heat point, the thermal bridge at the modular connection point, this work used construction design and research to build an experimental building and full-scale model; the goal was to explore and verify the feasibility of the climate-responsive construction technique called “reverse install.” Second, as a response to climate change, building facades were dynamically adjusted by employing different modular building envelope units such as sunshades, preheaters, ventilation, air filtration, pest control, and other functional requirements in order to improve the building’s climate adaptability. Finally, based on the above structural design and research, this study verified the actual measurements and simulation, as well as the sustainability performance of the structure during the operational phase, and provided feedback on the design. The results highlight the environmental performance of each construction detail and optimized possibilities for an integrated envelope design for modular prefabricated buildings during both the design and renovation phases. [ABSTRACT FROM AUTHOR]

Glaucoma causes irreversible vision loss, and early detection of glaucoma is essential to protect the vision of patients. The optic cup (OC) and optic disc (OD) are two critical anatomical structures for glaucoma diagnosis. Methods based on convolutional neural networks (CNNs) have been proposed to extract OC and OD, in which OC extraction is very challenging. However, the clinical prior knowledge is not fully utilized in existing CNN methods, which limits the performance of extracting OC and OD. Besides, CNN methods cannot learn long-range semantic information interaction well due to the intrinsic locality of convolution operations. In this paper, we propose a P rior K nowledge-based R elation T ransformer N etwork (PKRT-Net), which employs the clinical prior knowledge to assist OC segmentation and model efficient long-range relation of spatial features by the transformer. PKRT-Net consists of a dual-branch module, a relation transformer fusion module, and a decoder with weighted fusion. Dual-branch module decouples the fundus image into the vessel feature space and general local feature space; the relation transformer fusion module fuses the clinical prior information with local features to obtain more representative features; the weighted fusion module fuses the multi-scale side-outputs from the decoder with the representation of relation transformer module to improve the segmentation performance. We evaluate our proposed PKRT-Net on three public available OC and OD segmentation datasets (i.e. , Drishti-GS, RIM-ONE(r3), and REFUGE). The experimental results demonstrate that our proposed PKRT-Net framework achieves state-of-the-art OC and OD segmentation results on these three public datasets. [ABSTRACT FROM AUTHOR]

Study area of process mining exhibits great potential in explaining the design performance and behavior pattern in architecture, engineering and construction industries based on event data. However, research into creativity-related behavior pattern in sustainable building design through process mining remains blank. With the global climate change and energy crisis, creativity-driven problem-solving design process is becoming crucial. Based on >41-million lines of event data from 115 participants from a green building design competition, this study explored four dimensions on creative design behavioral pattern: 1) frequently used commands; 2) frequently used objects; 3) duration of used commands and 4) experience with the tool. Secondly, this study establishes and trains artificial neural network models according to the four dimensions to evaluate level of creativity of design works. Training results prove the effectiveness of the discoveries and realize a preliminary screening on creativity for large amount of data in sustainable building design. • This study discovers behavior patterns that are significantly correlated to creativity performance in sustainable building design through process mining. • A workflow for studying creativity performance in 3D modeling design process based on event data is constructed. • Machine learning models to evaluate level of design creativity are established, which realize a preliminary screening on creativity for sustainable building design. [ABSTRACT FROM AUTHOR]

When multiple Virtual Synchronous Generators (VSGs) operate in parallel in an islanded grid, power and frequency oscillations will occur when one VSG goes offline. However, the existing literature does not cover the related analysis and transient suppression schemes for this scenario. To analyze these complex high-order system dynamics, this paper first establishes an intuitive equivalent circuit model for multiple VSGs, and the frequency domain expressions of the multi-machine VSG system during the VSG offline transient simulation are then derived. Based on the multi-VSG model and its transient oscillations analysis, this paper further proposes a configuration scheme for the equivalent circuit parameters. Equivalently, the virtual inertia, damping coefficient and virtual impedance of the VSGs can be configured. With the proposed parameter configuration scheme, the power oscillation during the VSG offline transient can be eliminated, as verified by experiments with a microgrid lab platform using three VSGs. Compared with the existing multi-VSG studies, the proposed scheme is not only the first attempt to study the transient suppression when a VSG goes offline, but also is more intuitive in analysis and less complicated in the controller parameter tuning. [ABSTRACT FROM AUTHOR]

It is well known that the Cauchy problem for Laplace equations is an ill-posed problem in Hadamard's sense. Small deviations in Cauchy data may lead to large errors in the solutions. It is observed that if a bound is imposed on the solution, there exists a conditional stability estimate. This gives a reasonable way to construct stable algorithms. However, it is impossible to have good results at all points in the domain. Although numerical methods for Cauchy problems for Laplace equations have been widely studied for quite a long time, there are still some unclear points, for example, how to evaluate the numerical solutions, which means whether they can approximate the Cauchy data well and keep the bound of the solution, and at which points the numerical results are reliable? In this paper, the authors will prove the conditional stability estimate which is quantitatively related to harmonic measures. The harmonic measure can be used as an indicate function to pointwisely evaluate the numerical result, which further enables us to find a reliable subdomain where the local convergence rate is higher than a certain order. [ABSTRACT FROM AUTHOR]

Inspired by the artificial dynamic, we solve the linear severely ill-posed problems based on the 4DVAR method arising in data assimilation. To obtain the consistency of the posterior distribution in the weak norm by a fractional order of the forward operator, we are interested in asymptotic behavior of the weak norm squared posterior contraction ( SPC L ) function. By assuming exponentially decaying spectrum of the forward operator, the estimate of the SPC L function is established for a Sobolev-like source condition. Such a result is further extended to a general source condition. In both cases, we verify that the severe ill-posedness of the inverse problem can be reduced to moderate ill-posedness by the weak norm. [ABSTRACT FROM AUTHOR]

This paper proposes a dispatch strategy for the multi-energy system (MES) that utilizes the district heating network (DHN) to realize the heat power interaction of multi cogeneration system, so as to improve the operational flexibility. A novel model for the DHN that couples multi heat sources and is under quantity regulation is proposed, based on which an optimal coordinated dispatch model (OCDM) for the MES is presented comprehensively. The DHN model comprises dispatch constraints (DCs) and linear system of temperature correction equations (TCEs). The DCs form part of the OCDM constraints, where the mass flow temperatures are treated as constants and the mass flow rates and heat power are decision variables. The TCEs are employed to update the mass flow temperatures in DCs. Subsequently, an iterative solving strategy for the OCDM is proposed. The convergence of the solving strategy is analyzed and an effective method is introduced to ensure the convergence. A modified system based on an actual MES in Changchun, China is researched in the case study. Three cases are given to verify the effectiveness of the dispatch strategy and the solution method as well as study the influence of wind power penetration and heating level to the results. [ABSTRACT FROM AUTHOR]

By introducing the concept of “data coupling” into the existing hardware-in-the-loop (HIL) for hybrid electric vehicles (HEVs), several distributed subsystems are now able to be coupled together to constitute an Internet-Distributed Vehicle-in-the-Loop (ID-VIL) simulation platform. These subsystems include: the cloud server (Cloud) which acts as the central control node, the Electric Vehicle (EV) which serves as the Vehicle-in-the-Loop (VIL), and the HIL simulation platforms for engine (EIL) and battery (BIL). The proposed ID-VIL configuration makes it possible that the EV which does not contain any hybrid powertrain can simulate the output of an HEV's power system, meanwhile the subsystems of HEV (such as engine and battery) that are actually deployed on HIL platforms can work just the same as on board. The feasibility and reliability of ID-VIL system are verified by a 10 s acceleration test, a 7 km urban road tests, and the transparency analysis of the test result. [ABSTRACT FROM PUBLISHER]

Therapeutic vaccine is a promising approach in cancer therapy. But tumor-associated antigen peptides have weak immunogenicity and cancer patients are often characterized by immunosuppression and tolerance, leading to less efficiency of immunotherapy. We here successfully developed indoleamine 2, 3-dioxygenase (IDO) siRNA nanoparticle-coated and tyrosinase-related protein 2 (Trp2)-displayed recombinant Saccharomyces cerevisiae (YCP). YCPs had positive charges with a diameter of approximately 5 μm, resulting in selective phagocytosis by APC cells. YCP-delivered siRNA and Trp2 successfully escaped from phagosomes, efficiently inhibited IDO expression in DCs, promoted the immune reaction of T cell against Trp2, increased the secretion of proinflammatory cytokines such as IFN-γ,TNF-α, and IL-6, and decreased the generation of regulatory T cells. Moreover, YCPs significantly inhibited melanoma tumor growth by alleviating immune tolerance and promoting Trp2-specific CD8 + T cell immune response. These results suggest that Saccharomyces cerevisiae as a combined immunotherapeutic platform to simultaneously delivery IDO-siRNA and Trp2 epitope peptide is a promising vaccine system for melanoma treatment. [ABSTRACT FROM AUTHOR]

As the global energy crisis, environmental pollution, and global warming grow in intensity, increasing attention is being paid to combined cooling, heating, and power (CCHP) systems that realize high-efficiency cascade utilization of energy. This paper proposes a bilateral transaction mechanism between a residential CCHP system and a load aggregator (LA). The variable energy cost of the CCHP system is analyzed, based on which an energy pricing strategy for the CCHP system is proposed. Under this pricing strategy, the electricity price is constant, while the heat/cool price is ladder-shaped and dependent on the relationship between the electrical, heat, and cool loads. For the LA, an integrated demand response program is proposed that combines electricity-load shifting and a flexible heating/cooling supply, in which a thermodynamic model of buildings is used to determine the appropriate range of heating/cooling supply. Subsequently, a two-stage optimal dispatch model is proposed for the energy system that comprises the CCHP system and the LA. Case studies consisting of three scenarios (winter, summer, and excessive seasons) are delivered to demonstrate the effectiveness of the proposed approach, and the performance of the proposed pricing strategy is also evaluated by annual operation simulations. [ABSTRACT FROM AUTHOR]