FraudMemory: Explainable Memory-Enhanced Sequential Neural Networks for Financial Fraud Detection

The rapid development of electronic financial services brings significant convenience to our daily life. However, it also offers criminals the opportunity to exploit financial systems to do fraudulent transactions. Previous studies on fraud detection only deal with single type transactions and cannot adapt well to evolving environment in reality. In addition, their black box models pay less attention on the interpretability of fraud detection results. Here we propose a novel fraud detection algorithm called FraudMemory. It adopts state-of-art feature representation methods to better depict users and logs with multiple types in financial systems. Our model innovatively uses sequential model to capture the sequential patterns of each transaction and leverages memory networks to improve both the performance and interpretability. Also, with the incorporation of memory components, FraudMemory possesses high adaptability to the existence of concept drift. The empirical study proves that our model is a potential tool for financial fraud detection

Predicting Stock Price Movement Direction with Enterprise Knowledge Graph

Predicting stock price movement direction is a challenging task for financial investment. Previous researches focused on investigating the impacts of external factors (e.g., big events, economic influence and sentiments) in combination with the historical price to predict short-term stock price movement, while few researches leveraged the power of various relationships among enterprises. To bridge this gap, this research proposes power vector model and influence propagation model to mine the rich information in constructed Enterprise Knowledge Graph (EKG) for price movement prediction. In addition, Deep Neural Network (DNN) is introduced to train the model. The proposed model shows good prediction performance on the dataset of China top 500 enterprises

Multiple Injections Study Based on an Advanced Combustion Investigation System

AbstractAn advanced combustion investigation system was established in this paper. Based on this system, the multiple-injection spray development under various operating conditions was presented. The experiment result shows that the effect of ambient pressure and injection pressure on multiple injection spray are very conspicuous, especially the effect of injection fluctuation on multiple injections

Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators

Federated learning has become a popular method to learn from decentralized heterogeneous data. Federated semi-supervised learning (FSSL) emerges to train models from a small fraction of labeled data due to label scarcity on decentralized clients. Existing FSSL methods assume independent and identically distributed (IID) labeled data across clients and consistent class distribution between labeled and unlabeled data within a client. This work studies a more practical and challenging scenario of FSSL, where data distribution is different not only across clients but also within a client between labeled and unlabeled data. To address this challenge, we propose a novel FSSL framework with dual regulators, FedDure.} FedDure lifts the previous assumption with a coarse-grained regulator (C-reg) and a fine-grained regulator (F-reg): C-reg regularizes the updating of the local model by tracking the learning effect on labeled data distribution; F-reg learns an adaptive weighting scheme tailored for unlabeled instances in each client. We further formulate the client model training as bi-level optimization that adaptively optimizes the model in the client with two regulators. Theoretically, we show the convergence guarantee of the dual regulators. Empirically, we demonstrate that FedDure is superior to the existing methods across a wide range of settings, notably by more than 11% on CIFAR-10 and CINIC-10 datasets

Microglia exacerbate white matter injury via complement C3/C3aR pathway after hypoperfusion.

Microglial activation participates in white matter injury after cerebral hypoperfusion. However, the underlying mechanism is unclear. Here, we explore whether activated microglia aggravate white matter injury via complement C3-C3aR pathway after chronic cerebral hypoperfusion. Methods: Adult male Sprague-Dawley rats (n = 80) underwent bilateral common carotid artery occlusion for 7, 14, and 28 days. Cerebral vessel density and blood flow were examined by synchrotron radiation angiography and three-dimensional arterial spin labeling. Neurobehavioral assessments, CLARITY imaging, and immunohistochemistry were performed to evaluate activation of microglia and C3-C3aR pathway. Furthermore, C3aR knockout mice were used to establish the causal relationship of C3-C3aR signaling on microglia activation and white matter injury after hypoperfusion. Results: Cerebral vessel density and blood flow were reduced after hypoperfusion (p<0.05). Spatial learning and memory deficits and white matter injury were shown (p<0.05). These impairments were correlated with aberrant microglia activation and an increase in the number of reactive microglia adhering to and phagocytosed myelin in the hypoperfusion group (p<0.05), which were accompanied by the up-regulation of complement C3 and its receptors C3aR (p<0.05). Genetic deletion of C3ar1 significantly inhibited aberrant microglial activation and reversed white matter injury after hypoperfusion (p<0.05). Furthermore, the C3aR antagonist SB290157 decreased the number of microglia adhering to myelin (p<0.05), attenuated white matter injury and cognitive deficits in chronic hypoperfusion rats (p<0.05). Conclusions: Our results demonstrated that aberrant activated microglia aggravate white matter injury via C3-C3aR pathway during chronic hypoperfusion. These findings indicate C3aR plays a critical role in mediating neuroinflammation and white matter injury through aberrant microglia activation, which provides a novel therapeutic target for the small vessel disease and vascular dementia

Immune-Related Biomarkers Improve Performance of Risk Prediction Models for Survival in Patients With Hepatocellular Carcinoma

ObjectThe prediction of hepatocellular carcinoma (HCC) prognosis faced great challenge due to tumor heterogeneity. The purpose of this study was to explore the correlation between the immune infiltrate and prognosis. Moreover, we aimed to establish a risk prediction model for survival in HCC patients based on clinicopathological and immune indicators.MethodsIn this study, 316 patients with HCC who underwent radical resection in West China Hospital from 2009 to 2014 were included. Clinicopathological data and pathological specimens were collected. H&amp;E staining and immunohistochemical staining were performed on the pathological tissue sections. The evaluation of tumor-infiltrating lymphocyte (TIL) density was based on H&amp;E slices, and the assessment of the expressions of CD8, CD68, Lymphocyte activation gene-3 (LAG-3), T cell immunoglobulin domain and mucin domain-3 (TIM-3), Programmed Cell Death Protein 1 (PD-1), Programmed Cell Death Ligand 1 (PD-L1), OX40, CD66b, and Tryptase. was performed on the immunohistochemical slices. A risk prediction model for survival in HCC patients was established by integrating immune-related biomarkers and clinicopathological indicators.ResultsThe Barcelona Clinic Liver Cancer (BCLC) stage; the microvascular invasion status; the density of TILs; the expressing levels of CD66b, OX40, and PD-L1 in the immune cell; CD68; and CD8 were the predictors of patients’ overall survival (OS). The BCLC stage; the density of TILs; and the expressions of OX40, CD68, and CD8 were associated with disease-free survival (DFS). The expressions of CD66b, CD68, OX40, and CD8 had a cumulative effect on prognosis. The area under the curve of the prediction model for OS based on clinicopathological features was improved from 0.62 to 0.74 by adding to CD8, OX40, CD68, CD66b, and TILs, whereas it was improved from 0.59 to 0.73 for the DFS prediction model.ConclusionOur results, if confirmed, indicated that immune-related biomarkers should be taken into account or stratified in survival analysis for HCC

Robotic bilateral axillo-breast versus endoscopic bilateral areola thyroidectomy outcomes of 757 patients

BackgroundRemote endoscopic thyroidectomy (ET) and robotic thyroidectomy (RT) seem to be beneficial in selected situations to avoid anterior neck scars. There are limited data in the literature to determine whether RT via a bilateral axillo-breast approach (RT-BABA) is superior to ET via a bilateral areolar approach (ET-BAA). Therefore, the aim of this study was to evaluate the surgical outcomes of RT-BABA versus ET-BAA.MethodsBetween May 2013 and May 2022, 757 patients who underwent RT-BABA or ET-BAA at a high-volume Chinese thyroid center were included. Intraoperative and postoperative outcome parameters were collected and retrospectively analyzed. The moving average method was used to evaluate the learning curve.ResultsThe proportion of patients older than 45 years was greater in the RT group than in the ET group (14.8% vs. 7.4%, p &lt; 0.001). The percentage of overweight patients was greater in the RT group (28.8% vs. 9.5%, p &lt; 0.001). The number of patients treated for malignant lesions was higher in the RT group (86.8% vs. 75%, p &lt; 0.001). The rate of thyroiditis was higher in the RT group (10.9% vs. 6.6%, p &lt; 0.001). Surgical time was significantly shorter in the RT group (140 vs. 165min, p &lt; 0.001). Drainage volume was higher in the RT group (100 vs. 85ml, p &lt; 0.001). Postoperative hospital stay was shorter in the RT group (3.04 ± 0.44 vs. 3.67 ± 0.89 days, p &lt; 0.001). The cost in the RT group was higher (49627 ± 2795 vs. 25094 ± 3368 yuan, p &lt; 0.001). Transient vocal cord dysfunction was lower in the RT group (2.9% vs. 8.0%, p = 0.003). There was no significant difference between the two groups in the number of central lymph nodes sampled, positive lymph nodes, neural monitoring (EMG) results, and rate of transient hypoparathyroidism. The learning curve for RT was 26 cases, and the operative time for ET was constant throughout the study.ConclusionsRT-BABA is as safe and feasible as ET-BAA. RT-BABA performed better in some surgical outcomes. Further prospective studies are needed to confirm the safety of RT-BABA

Epistasis in neurotransmitter receptors linked to posttraumatic stress disorder and major depressive disorder comorbidity in traumatized Chinese

BackgroundPosttraumatic stress disorder (PTSD) and major depressive disorder (MDD) comorbidity occurs through exposure to trauma with genetic susceptibility. Neuropeptide-Y (NPY) and dopamine are neurotransmitters associated with anxiety and stress-related psychiatry through receptors. We attempted to explore the genetic association between two neurotransmitter receptor systems and the PTSD–MDD comorbidity.MethodsFour groups were identified using latent profile analysis (LPA) to examine the patterns of PTSD and MDD comorbidity among survivors exposed to earthquake-related trauma: low symptoms, predominantly depression, predominantly PTSD, and PTSD–MDD comorbidity. NPY2R (rs4425326), NPY5R (rs11724320), DRD2 (rs1079597), and DRD3 (rs6280) were genotyped from 1,140 Chinese participants exposed to earthquake-related trauma. Main, gene–environment interaction (G × E), and gene–gene interaction (G × G) effects for low symptoms, predominantly depression, and predominantly PTSD were tested using a multinomial logistic model with PTSD–MDD comorbidity as a reference.ResultsThe results demonstrated that compared to PTSD–MDD comorbidity, epistasis (G × G) NPY2R-DRD2 (rs4425326 × rs1079597) affects low symptoms (β = −0.66, OR = 0.52 [95% CI: 0.32–0.84], p = 0.008, pperm = 0.008) and predominantly PTSD (β = −0.56, OR = 0.57 [95% CI: 0.34–0.97], p = 0.037, pperm = 0.039), while NPY2R-DRD3 (rs4425326 × rs6280) impacts low symptoms (β = 0.82, OR = 2.27 [95% CI: 1.26–4.10], p = 0.006, pperm = 0.005) and predominantly depression (β = 1.08, R = 2.95 [95% CI: 1.55–5.62], p = 0.001, pperm = 0.001). The two G × G effects are independent.ConclusionNPY and dopamine receptor genes are related to the genetic etiology of PTSD–MDD comorbidity, whose specific mechanisms can be studied at multiple levels

Exosomes Derived From Bone Mesenchymal Stem Cells Ameliorate Early Inflammatory Responses Following Traumatic Brain Injury

Traumatic brain injury (TBI) is a leading cause of mortality and disability worldwide. Although treatment guidelines have been developed, no best treatment option or medicine for this condition exists. Recently, mesenchymal stem cells (MSCs)-derived exosomes have shown lots of promise for the treatment of brain disorders, with some results highlighting the neuroprotective effects through neurogenesis and angiogenesis after TBI. However, studies focusing on the role of exosomes in the early stages of neuroinflammation post-TBI are not sufficient. In this study, we investigated the role of bone mesenchymal stem cells (BMSCs)-exosomes in attenuating neuroinflammation at an early stage post-TBI and explored the potential regulatory neuroprotective mechanism. We administered 30 μg protein of BMSCs-exosomes or an equal volume of phosphate-buffered saline (PBS) via the retro-orbital route into C57BL/6 male mice 15 min after controlled cortical impact (CCI)-induced TBI. The results showed that the administration of BMSCs-exosomes reduced the lesion size and improved the neurobehavioral performance assessed by modified Neurological Severity Score (mNSS) and rotarod test. In addition, BMSCs-exosomes inhibited the expression of proapoptosis protein Bcl-2-associated X protein (BAX) and proinflammation cytokines, tumor necrosis factor-α (TNF-α) and interleukin (IL)-1β, while enhancing the expression of the anti-apoptosis protein B-cell lymphoma 2 (BCL-2). Furthermore, BMSCs-exosomes modulated microglia/macrophage polarization by downregulating the expression of inducible nitric oxide synthase (INOS) and upregulating the expression of clusters of differentiation 206 (CD206) and arginase-1 (Arg1). In summary, our result shows that BMSCs-exosomes serve a neuroprotective function by inhibiting early neuroinflammation in TBI mice through modulating the polarization of microglia/macrophages. Further research into this may serve as a potential therapeutic strategy for the future treatment of TBI