Which Channel to Ask My Question? Personalized Customer Service Request Stream Routing using Deep Reinforcement Learning

Customer services are critical to all companies, as they may directly connect to the brand reputation. Due to a great number of customers, e-commerce companies often employ multiple communication channels to answer customers' questions, for example, chatbot and hotline. On one hand, each channel has limited capacity to respond to customers' requests, on the other hand, customers have different preferences over these channels. The current production systems are mainly built based on business rules, which merely considers tradeoffs between resources and customers' satisfaction. To achieve the optimal tradeoff between resources and customers' satisfaction, we propose a new framework based on deep reinforcement learning, which directly takes both resources and user model into account. In addition to the framework, we also propose a new deep-reinforcement-learning based routing method-double dueling deep Q-learning with prioritized experience replay (PER-DoDDQN). We evaluate our proposed framework and method using both synthetic and a real customer service log data from a large financial technology company. We show that our proposed deep-reinforcement-learning based framework is superior to the existing production system. Moreover, we also show our proposed PER-DoDDQN is better than all other deep Q-learning variants in practice, which provides a more optimal routing plan. These observations suggest that our proposed method can seek the trade-off where both channel resources and customers' satisfaction are optimal.Comment: 13 pages, 7 figure

Monitoring of a Nearshore Small Dolphin Species Using Passive Acoustic Platforms and Supervised Machine Learning Techniques

Passive acoustic monitoring (PAM) is increasingly being adopted as a non-invasive method for the assessment of ocean ecological dynamics. PAM is an important sampling approach for acquiring critical information about marine mammals, especially in areas where data are lacking and where evaluations of threats for vulnerable populations are required. The Indo-Pacific humpback dolphin (IPHD, Sousa chinensis) is a coastal species which inhabits tropical and warm-temperate waters from the eastern Indian Ocean throughout Southeast Asia to central China. A new population of this species was recently discovered in waters southwest of Hainan Island, China. An array of passive acoustic platforms was deployed at depths of 10–20 m (the preferred habitat of humpback dolphins), across sites covering more than 100 km of coastline. In this study, we explored whether the acoustic data recorded by the array could be used to classify IPHD echolocation clicks, with the aim of investigating the spatiotemporal patterns of distribution and acoustic behavior of this species. A number of supervised machine learning algorithms were trained to automatically classify echolocation clicks from the different types of short-broadband pulses recorded. The best performance was reported by a cubic support vector machine (Cubic SVM), which was applied to 19,215 5-min recordings (∼4.2 TB), collected over a period of 75 days at six locations. Subsequently, using spectrogram visualization and audio listening, human operators confirmed the presence of clicks within the selected files. Additionally, other dolphin vocalizations (including whistles, buzzes, and burst pulses) and different sound sources (soniferous fishes, snapping shrimps, human activities) were also reported. The detection range of IPHD clicks was estimated using a transmission loss (TL) model and the performance of the trained classifier was compared with data synchronously collected by an acoustic data logger (A-tag). This study demonstrates that the distribution and habitat use of a coastal and resident dolphin species can be monitored over a large spatiotemporal scale, using an array of passive acoustic platforms and a data analysis protocol that includes both machine learning techniques and spectrogram inspection

Roles of structural plasticity in chaperone HdeA activity are revealed by 19 F NMR

Multiple conformations of acid chaperone HdeA and their roles in activity

Predicting peritoneal carcinomatosis of gastric cancer: A simple model to exempt low-risk patients from unnecessary staging laparoscopy

BackgroundPeritoneal carcinomatosis (PC) of gastric cancer indicates a poor outcome and is mainly diagnosed by staging laparoscopy (SL). This study was designed to develop a risk stratification model based on the number of risk factors to exempt low-risk patients from unnecessary SL.MethodsThis was a retrospective cohort study based on a single institution between January 2015 and December 2019. SL is indicated for patients of advanced locoregional stage, and clinicopathologic characteristics of 535 consecutive patients were included. PC-associated variables were identified by logistic regression analysis. A risk stratification model based on the number of risk factors was constructed, and we defined its predictive value with a receiver operating characteristic (ROC) curve and negative predictive value.ResultsIn total, 15.9% of included patients were found to have PC during SL. Borrmann type IV, elevated CA125, and tumour diameter ≥5 cm were independent risk factors of PC. These three factors combined with cT4 were selected as predictive factors, and the number of predictive variables was significantly related to the possibility of PC (2.0%, 12.8%, 20.0%, 54.2%, and 100%, respectively). When the cutoff value is more than one predictive factor, the negative predictive value is 98.0%, with an area under the curve of 0.780. This model could exempt 29.8% of unnecessary SL compared to the indication of the current NCCN guideline.ConclusionsWe constructed a simple model to predict the probability of PC using the number of predictive factors. It is recommended that patients without any of these factors should be exempt from SL

Altered cardiac structure and function is related to seizure frequency in a rat model of chronic acquired temporal lobe epilepsy

Objective: This study aimed to prospectively examine cardiac structure and function in the kainic acid-induced post-status epilepticus (post-KA SE) model of chronic acquired temporal lobe epilepsy (TLE), specifically to examine for changes between the pre-epileptic, early epileptogenesis and the chronic epilepsy stages. We also aimed to examine whether any changes related to the seizure frequency in individual animals. Methods: Four hours of SE was induced in 9 male Wistar rats at 10 weeks of age, with 8 saline treated matched control rats. Echocardiography was performed prior to the induction of SE, two- and 10-weeks post-SE. Two weeks of continuous video-EEG and simultaneous ECG recordings were acquired for two weeks from 11 weeks post-KA SE. The video-EEG recordings were analyzed blindly to quantify the number and severity of spontaneous seizures, and the ECG recordings analyzed for measures of heart rate variability (HRV). PicroSirius red histology was performed to assess cardiac fibrosis, and intracellular Ca2+ levels and cell contractility were measured by microfluorimetry. Results: All 9 post-KA SE rats were demonstrated to have spontaneous recurrent seizures on the two-week video-EEG recording acquired from 11 weeks SE (seizure frequency ranging from 0.3 to 10.6 seizures/day with the seizure durations from 11 to 62 s), and none of the 8 control rats. Left ventricular wall thickness was thinner, left ventricular internal dimension was shorter, and ejection fraction was significantly decreased in chronically epileptic rats, and was negatively correlated to seizure frequency in individual rats. Diastolic dysfunction was evident in chronically epileptic rats by a decrease in mitral valve deceleration time and an increase in E/E` ratio. Measures of HRV were reduced in the chronically epileptic rats, indicating abnormalities of cardiac autonomic function. Cardiac fibrosis was significantly increased in epileptic rats, positively correlated to seizure frequency, and negatively correlated to ejection fraction. The cardiac fibrosis was not a consequence of direct effect of KA toxicity, as it was not seen in the 6/10 rats from separate cohort that received similar doses of KA but did not go into SE. Cardiomyocyte length, width, volume, and rate of cell lengthening and shortening were significantly reduced in epileptic rats. Significance: The results from this study demonstrate that chronic epilepsy in the post-KA SE rat model of TLE is associated with a progressive deterioration in cardiac structure and function, with a restrictive cardiomyopathy associated with myocardial fibrosis. Positive correlations between seizure frequency and the severity of the cardiac changes were identified. These results provide new insights into the pathophysiology of cardiac disease in chronic epilepsy, and may have relevance for the heterogeneous mechanisms that place these people at risk of sudden unexplained death

Expression of the Inhibitory Receptor TIGIT Is Up-Regulated Specifically on NK Cells With CD226 Activating Receptor From HIV-Infected Individuals

Natural killer (NK) cells are important for maintenance of innate immune system stability and serve as a first line of defense against tumors and virus infections; they can act either directly or indirectly and are regulated via co-operation between inhibitory and stimulatory surface receptors. The recently reported inhibitory receptor, TIGIT, can be expressed on the NK cell surface; however, the expression level and function of TIGIT on NK cells during HIV infection is unknown. In this study, for the first time, we investigated the expression and function of TIGIT in NK cells from HIV-infected individuals. Our data demonstrate that the level of TIGIT is higher on NK cells from patients infected with human immunodeficiency virus (HIV) compared with HIV-negative healthy controls. TIGIT expression is inversely correlated with CD4+ T cell counts and positively correlated with plasma viral loads. Additionally, levels of the TIGIT ligand, CD155, were higher on CD4+ T cells from HIV-infected individuals compared with those from healthy controls; however, there was no difference in the level of the activating receptor, CD226, which recognizes the same ligands as TIGIT. Furthermore, TIGIT was found to specifically up-regulated on CD226+ NK cells in HIV-infected individuals, and either rIL-10, or rIL-12 + rIL-15, could induce TIGIT expression on these cells. In addition, high TIGIT expression inhibited the production of interferon-gamma (IFN-γ) by NK cells, while TIGIT inhibition restored IFN-γ production. Overall, these results highlight the important role of TIGIT in NK cell function and suggest a potential new avenue for the development of therapeutic strategies toward a functional cure for HIV

NKG2C+NKG2A− Natural Killer Cells are Associated with a Lower Viral Set Point and may Predict Disease Progression in Individuals with Primary HIV Infection

Natural killer (NK) cells are the first line of defense against pathogens of the immune system and also play an important role in resistance against HIV. The activating receptor NKG2C and the inhibitory receptor NKG2A co-modulate the function of NK cells by recognizing the same ligand, HLA-E. However, the role of NKG2A and NKG2C on viral set point and the prediction of HIV disease progression have been rarely reported. In this study, we determined the expression of NKG2C or NKG2A on the surface of NK cells from 22 individuals with primary HIV infection (PHI) stage and 23 HIV-negative normal control (NC) subjects. The CD4+ T cell count and plasma level of HIV RNA in the infected individuals were longitudinally followed-up for about 720 days. The proportion of NKG2C+NKG2A− NK cells was higher in subjects from the low set point group and was negatively correlated with the viral load. In addition, strong anti-HIV activities were observed in NKG2C+ NK cells from the HIV-positive donors. Furthermore, a proportion of NKG2C+NKG2A− NK cells >35.45%, and a ratio of NKG2C/NKG2A >1.7 were predictive for higher CD4+ T cell counts 720 days after infection. Collectively, the experimental results allow us to draw the conclusion that NKG2C+ NK cells might exert an antiviral effect and that the proportion of NKG2C+NKG2A− NK cells, and the ratio of NKG2C/NKG2A, are potential biomarkers for predicting HIV disease progression