VW-PINNs: A volume weighting method for PDE residuals in physics-informed neural networks

Physics-informed neural networks (PINNs) have shown remarkable prospects in the solving the forward and inverse problems involving partial differential equations (PDEs). The method embeds PDEs into the neural network by calculating PDE loss at a series of collocation points, providing advantages such as meshfree and more convenient adaptive sampling. However, when solving PDEs using nonuniform collocation points, PINNs still face challenge regarding inefficient convergence of PDE residuals or even failure. In this work, we first analyze the ill-conditioning of the PDE loss in PINNs under nonuniform collocation points. To address the issue, we define volume-weighted residual and propose volume-weighted physics-informed neural networks (VW-PINNs). Through weighting the PDE residuals by the volume that the collocation points occupy within the computational domain, we embed explicitly the spatial distribution characteristics of collocation points in the residual evaluation. The fast and sufficient convergence of the PDE residuals for the problems involving nonuniform collocation points is guaranteed. Considering the meshfree characteristics of VW-PINNs, we also develop a volume approximation algorithm based on kernel density estimation to calculate the volume of the collocation points. We verify the universality of VW-PINNs by solving the forward problems involving flow over a circular cylinder and flow over the NACA0012 airfoil under different inflow conditions, where conventional PINNs fail; By solving the Burgers' equation, we verify that VW-PINNs can enhance the efficiency of existing the adaptive sampling method in solving the forward problem by 3 times, and can reduce the relative error of conventional PINNs in solving the inverse problem by more than one order of magnitude

mixiTUI:A Tangible Sequencer for Electronic Live Performances

With the rise of crowdsourcing and mobile crowdsensing techniques, a large number of crowdsourcing applications or platforms (CAP) have appeared. In the mean time, CAP-related models and frameworks based on different research hypotheses are rapidly emerging, and they usually address specific issues from a certain perspective. Due to different settings and conditions, different models are not compatible with each other. However, CAP urgently needs to combine these techniques to form a unified framework. In addition, these models needs to be learned and updated online with the extension of crowdsourced data and task types, thus requiring a unified architecture that integrates lifelong learning concepts and breaks down the barriers between different modules. This paper draws on the idea of ubiquitous operating systems and proposes a novel OS (CrowdOS), which is an abstract software layer running between native OS and application layer. In particular, based on an in-depth analysis of the complex crowd environment and diverse characteristics of heterogeneous tasks, we construct the OS kernel and three core frameworks including Task Resolution and Assignment Framework (TRAF), Integrated Resource Management (IRM), and Task Result quality Optimization (TRO). In addition, we validate the usability of CrowdOS, module correctness and development efficiency. Our evaluation further reveals TRO brings enormous improvement in efficiency and a reduction in energy consumption

Integrative analysis of non-targeted metabolome and transcriptome reveals the mechanism of volatile formation in pepper fruit

Introduction: Aroma is a key inherent quality attributes of pepper fruit, yet the underlying mechanisms of aroma compound biosynthesis remain unclear.Methods: In this study, the volatile profile of the QH (cultivated Capsicum chinense) and WH (cultivated Capsicum annuum) pepper varieties were putatively identified during fruit development using gas chromatography-mass spectrometry (GC-MS).Results and discussion: The results identified 203 volatiles in pepper, and most of the esters, terpenes, aldehydes and alcohols were significantly down-regulated with fruit ripening. The comparison of volatile components between varieties revealed that aldehydes and alcohols were highly expressed in the WH fruit, while esters and terpenes with fruity or floral aroma were generally highly accumulated in the QH fruit, providing QH with a fruity odor. Transcriptome analysis demonstrated the close relationship between the synthesis of volatiles and the fatty acid and terpene metabolic pathways, and the high expression of the ADH, AAT and TPS genes was key in determining the accumulation of volatiles in pepper fruit. Furthermore, integrative metabolome and transcriptome analysis revealed that 208 differentially expressed genes were highly correlated with 114 volatiles, and the transcription factors of bHLH, MYB, ARF and IAA were identified as fundamental for the regulation of volatile synthesis in pepper fruit. Our results extend the understanding of the synthesis and accumulation of volatiles in pepper fruit

Identification of Atrial Transmural Conduction Inhomogeneity Using Unipolar Electrogram Morphology

(1) Background: Structural remodeling plays an important role in the pathophysiology of atrial fibrillation (AF). It is likely that structural remodeling occurs transmurally, giving rise to electrical endo-epicardial asynchrony (EEA). Recent studies have suggested that areas of EEA may be suitable targets for ablation therapy of AF. We hypothesized that the degree of EEA is more pronounced in areas of transmural conduction block (T-CB) than single-sided CB (SS-CB). This study examined the degree to which SS-CB and T-CB enhance EEA and which specific unipolar potential morphology parameters are predictive for SS-CB or T-CB. (2) Methods: Simultaneous endo-epicardial mapping in the human right atrium was performed in 86 patients. Potential morphology parameters included unipolar potential voltages, low-voltage areas, potential complexity (long double and fractionated potentials: LDPs and FPs), and the duration of fractionation. (3) Results: EEA was mostly affected by the presence of T-CB areas. Lower potential voltages and more LDPs and FPs were observed in T-CB areas compared to SS-CB areas. (4) Conclusion: Areas of T-CB could be most accurately predicted by combining epicardial unipolar potential morphology parameters, including voltages, fractionation, and fractionation duration (AUC = 0.91). If transmural areas of CB indeed play a pivotal role in the pathophysiology of AF, they could theoretically be used as target sites for ablation

Cancer-associated fibroblast related gene signature in Helicobacter pylori-based subtypes of gastric carcinoma for prognosis and tumor microenvironment estimation in silico analysis

IntroductionGastric cancer (GC) remains the major constituent of cancer-related deaths and a global public health challenge with a high incidence rate. Helicobacter pylori (HP) plays an essential role in promoting the occurrence and progression of GC. Cancer-associated fibroblasts (CAFs) are regarded as a significant component in the tumor microenvironment (TME), which is related to the metastasis of GC. However, the regulation mechanisms of CAFs in HP-related GC are not elucidated thoroughly.MethodsHP-related genes (HRGs) were downloaded from the GSE84437 and TCGA-GC databases. The two databases were combined into one cohort for training. Furthermore, the consensus unsupervised clustering analysis was obtained to sort the training cohort into different groups for the identification of differential expression genes (DEGs). Weighted correlation network analysis (WGCNA) was performed to verify the correlation between the DEGs and cancer-associated fibroblasts which were key components in the tumor microenvironment. The least absolute shrinkage and selection operator (LASSO) was executed to find cancer-associated fibroblast-related differential expression genes (CDEGs) for the further establishment of a prognostic model.Results and discussionIn this study, 52 HP-related genes (HRGs) were screened out based on the GSE84437 and TCGA-GC databases. A total of 804 GC samples were analyzed, respectively, and clustered into two HP-related subtypes. The DEGs identified from the two subtypes were proved to have a relationship with TME. After WGCNA and LASSO, the CAFs-related module was identified, from which 21 gene signatures were confirmed. Then, a CDEGs-Score was constructed and its prediction efficiency in GC patients was conducted for validation. Overall, a highly precise nomogram was established for enhancing the adaptability of the CDEGs-Score. Furthermore, our findings revealed the applicability of CDEGs-Score in the sensitivity of chemotherapeutic drugs. In general, our research provided brand-new possibilities for comprehending HP-related GC, evaluating survival, and more efficient therapeutic strategies

Role of melatonin in enhancing arbuscular mycorrhizal symbiosis and mitigating cold stress in perennial ryegrass (Lolium perenne L.)

Melatonin is a biomolecule that affects plant development and is involved in protecting plants from environmental stress. However, the mechanisms of melatonin’s impact on arbuscular mycorrhizal (AM) symbiosis and cold tolerance in plants are still unclear. In this research, AM fungi inoculation and exogenous melatonin (MT) were applied to perennial ryegrass (Lolium perenne L.) seedlings alone or in combination to investigate their effect on cold tolerance. The study was conducted in two parts. The initial trial examined two variables, AM inoculation, and cold stress, to investigate the involvement of the AM fungus Rhizophagus irregularis in endogenous melatonin accumulation and the transcriptional levels of its synthesis genes in the root system of perennial ryegrass under cold stress. The subsequent trial was designed as a three-factor analysis, encompassing AM inoculation, cold stress, and melatonin application, to explore the effects of exogenous melatonin application on plant growth, AM symbiosis, antioxidant activity, and protective molecules in perennial ryegrass subjected to cold stress. The results of the study showed that compared to non-mycorrhizal (NM) plants, cold stress promoted an increase in the accumulation of melatonin in the AM-colonized counterparts. Acetylserotonin methyltransferase (ASMT) catalyzed the final enzymatic reaction in melatonin production. Melatonin accumulation was associated with the level of expression of the genes, LpASMT1 and LpASMT3. Treatment with melatonin can improve the colonization of AM fungi in plants. Simultaneous utilization of AM inoculation and melatonin treatment enhanced the growth, antioxidant activity, and phenylalanine ammonia-lyase (PAL) activity, while simultaneously reducing polyphenol oxidase (PPO) activity and altering osmotic regulation in the roots. These effects are expected to aid in the mitigation of cold stress in Lolium perenne. Overall, melatonin treatment would help Lolium perenne to improve growth by promoting AM symbiosis, improving the accumulation of protective molecules, and triggering in antioxidant activity under cold stress

An Active Learning Approach for Rapid Characterization of Endothelial Cells in Human Tumors

Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers

Comparative mRNA and microRNA Expression Profiling of Three Genitourinary Cancers Reveals Common Hallmarks and Cancer-Specific Molecular Events

Genome-wide gene expression profile using deep sequencing technologies can drive the discovery of cancer biomarkers and therapeutic targets. Such efforts are often limited to profiling the expression signature of either mRNA or microRNA (miRNA) in a single type of cancer.Here we provided an integrated analysis of the genome-wide mRNA and miRNA expression profiles of three different genitourinary cancers: carcinomas of the bladder, kidney and testis.Our results highlight the general or cancer-specific roles of several genes and miRNAs that may serve as candidate oncogenes or suppressors of tumor development. Further comparative analyses at the systems level revealed that significant aberrations of the cell adhesion process, p53 signaling, calcium signaling, the ECM-receptor and cell cycle pathways, the DNA repair and replication processes and the immune and inflammatory response processes were the common hallmarks of human cancers. Gene sets showing testicular cancer-specific deregulation patterns were mainly implicated in processes related to male reproductive function, and general disruptions of multiple metabolic pathways and processes related to cell migration were the characteristic molecular events for renal and bladder cancer, respectively. Furthermore, we also demonstrated that tumors with the same histological origins and genes with similar functions tended to group together in a clustering analysis. By assessing the correlation between the expression of each miRNA and its targets, we determined that deregulation of 'key' miRNAs may result in the global aberration of one or more pathways or processes as a whole.This systematic analysis deciphered the molecular phenotypes of three genitourinary cancers and investigated their variations at the miRNA level simultaneously. Our results provided a valuable source for future studies and highlighted some promising genes, miRNAs, pathways and processes that may be useful for diagnostic or therapeutic applications