AdaRec: Adaptive Sequential Recommendation for Reinforcing Long-term User Engagement

Growing attention has been paid to Reinforcement Learning (RL) algorithms when optimizing long-term user engagement in sequential recommendation tasks. One challenge in large-scale online recommendation systems is the constant and complicated changes in users' behavior patterns, such as interaction rates and retention tendencies. When formulated as a Markov Decision Process (MDP), the dynamics and reward functions of the recommendation system are continuously affected by these changes. Existing RL algorithms for recommendation systems will suffer from distribution shift and struggle to adapt in such an MDP. In this paper, we introduce a novel paradigm called Adaptive Sequential Recommendation (AdaRec) to address this issue. AdaRec proposes a new distance-based representation loss to extract latent information from users' interaction trajectories. Such information reflects how RL policy fits to current user behavior patterns, and helps the policy to identify subtle changes in the recommendation system. To make rapid adaptation to these changes, AdaRec encourages exploration with the idea of optimism under uncertainty. The exploration is further guarded by zero-order action optimization to ensure stable recommendation quality in complicated environments. We conduct extensive empirical analyses in both simulator-based and live sequential recommendation tasks, where AdaRec exhibits superior long-term performance compared to all baseline algorithms.Comment: Preprint. Under Revie

Bioactivities of EF24, a Novel Curcumin Analog: A Review

Curcumin is an attractive agent due to its multiple bioactivities. However, the low oral bioavailability and efficacy profile hinders its clinical application. To improve the bioavailability, many analogs of curcumin have been developed, among which EF24 is an excellent representative. EF24 has enhanced bioavailability over curcumin and shows more potent bioactivity, including anti-cancer, anti-inflammatory, and anti-bacterial. EF24 inhibits tumor growth by inducing cell cycle arrest and apoptosis, mainly through its inhibitory effect on the nuclear factor kappa B (NF-κB) pathway and by regulating key genes through microRNA (miRNA) or the proteosomal pathway. Based on the current structure, more potent EF24 analogs have been designed and synthesized. However, some roles of EF24 remain unclear, such as whether it induces or inhibits reactive oxygen species (ROS) production and whether it stimulates or inhibits the mitogen activated kinase-like protein (MAPK) pathway. This review summarizes the known biological and pharmacological activities and mechanisms of action of EF24

An Open Invitation to Join the International Brugada Electrocardiographic Indices Registry

Background: The Brugada Electrocardiographic Indices Registry is a comprehensive data registry composed of patients with Brugada patterns on the electrocardiogram (ECG). The aim is to test the hypotheses that (i) ECG indices combining both depolarization and repolarization abnormalities can better predict spontaneous ventricular arrhythmias than existing ECG markers in Brugada syndrome and (ii) that serial ECG measurements will provide additional information for risk stratification, especially in asymptomatic patients. Methods: Patients with both Brugada pattern ECGs and Brugada syndrome are eligible for inclusion in this registry. Baseline characteristics and ECG variables reflecting depolarization and repolarization will be determined. The primary outcome is spontaneous ventricular tachycardia/ventricular fibrillation or sudden cardiac death. Secondary outcomes are inducible ventricular tachycardia/ventricular fibrillation and syncope. Results: As of November 15, 2019, 39 investigators from 32 cities in 18 countries had joined this registry. As of December 15, 2019, 1383 cases had been enrolled. Conclusions: The Brugada Electrocardiographic Indices Registry will evaluate the disease life course, risk factors, and prognosis in a large series of Brugada patients. It will therefore provide insights for improving risk stratification

Research on the Mechanical Mechanism of the Shuffle Problem of Electric Vehicles and the Sensitivity to Clearances

In order to address the shuffle problem of the electric powertrain system that occurs at the moment of torque reversing, a multibody dynamics model of the powertrain system, with the measured motor torque applied as the input loading, has been established to analyze the generating mechanism of the rotating speed ripple of the drive system which is regarded the root of shuffle. The influence on speed ripple from cumulative gap size and motor torque has been investigated. The model was validated by showing good agreement between the simulated speed response and the measured data. Perturbance on each backlash was performed in the simulation to reveal the sensitivity of the speed ripple on the size of the backlash. Much higher speed-to-gap sensitivities have been observed for the low-speed engagement pairs than the high-speed engagement pairs, indicating that compressing the backlashes of the former could achieve more NVH (noise, vibration, harshness, i.e., NVH) performance improvement

Analysis of Vibration and Noise for the Powertrain System of Electric Vehicles under Speed-Varying Operating Conditions

Whine noise from the electric powertrain system of electric vehicles, including electromagnetic noise and gear-meshing noise, significantly affects vehicle comfort and has been getting growing concern. In order to identify and avoid whine problems as early as possible in the powertrain development process, this paper presents a vibration and noise simulation methodology for the electric powertrain system of vehicles under speed-varying operating conditions. The electromagnetic forces on the stator teeth of the motor and the bearing forces on the gearbox for several constant-speed operating conditions are obtained first by electromagnetic field simulation and multi-body dynamic simulation, respectively. Order forces for the speed-varying operating condition are generated by interpolation between the obtained forces, before they are applied on the mechanical model whose natural modes have been calibrated in advance by tested modes. The whine noise radiated from the powertrain is then obtained based on acoustic boundary element analysis. The simulated bearing forces indicate that the overlooking of the motor torque ripple does not result in significant loss in simulation accuracy of electromagnetic noise. The simulation results and tested data show good consistency, with the relative frequency deviation of local peaks being less than 8% and the error of the average sound pressure level (SPL) being mostly below 10 dB (A)

Research on the Mechanical Mechanism of the Shuffle Problem of Electric Vehicles and the Sensitivity to Clearances

In order to address the shuffle problem of the electric powertrain system that occurs at the moment of torque reversing, a multibody dynamics model of the powertrain system, with the measured motor torque applied as the input loading, has been established to analyze the generating mechanism of the rotating speed ripple of the drive system which is regarded the root of shuffle. The influence on speed ripple from cumulative gap size and motor torque has been investigated. The model was validated by showing good agreement between the simulated speed response and the measured data. Perturbance on each backlash was performed in the simulation to reveal the sensitivity of the speed ripple on the size of the backlash. Much higher speed-to-gap sensitivities have been observed for the low-speed engagement pairs than the high-speed engagement pairs, indicating that compressing the backlashes of the former could achieve more NVH (noise, vibration, harshness, i.e., NVH) performance improvement

MicroRNA-1298-5p inhibits cell proliferation and invasion of bladder cancer via downregulating connexin 43

MicroRNA (miR)-1298 is widely down-regulated in a variety of malignant tumors, which facilitates cell proliferation, invasiveness, and migration. However, the specific biological function of miR-1298 in bladder cancer (BC) is still unknown. Connexin 43 (Cx43) is often up-regulated in tumors. Identifying miRNAs that target Cx43 in the setting of BC will help to develop Cx43-based therapies for BC. In this study, the results demonstrated that the expression levels of miR-1298 and Cx43 were significantly down-regulated and up-regulated, respectively, in BC tissues. Overexpression of miR-1298 inhibited cell proliferation, migration, and invasiveness in two BC cell lines as determined using MTT assays, cell cycle assays, colony formation assays, Transwell assays, gelatin zymography, and Western blot. In addition, we found that miR-1298 decreased Cx43 expression by directly targeting the 3′-UTR. Further, we observed that the promotion of BC cell proliferation, migration, and invasiveness from Cx43 on could be partially attenuated by overexpressing miR-1298. Moreover, the protein expression of p-ERK was ameliorated after transfection with overexpressed-miR-1298. Knockdown of Cx43 reversed the promotion of cell migration and invasiveness due to decreased expression of miR-1298. All of the data from our study indicate that miR-1298 could be a diagnostic marker of BC and a potential therapeutic agent via inhibiting Cx43.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

A Multi-Omics Study of Chicken Infected by Nephropathogenic Infectious Bronchitis Virus

Chicken gout resulting from nephropathogenic infectious bronchitis virus (NIBV) has become a serious kidney disease problem in chicken worldwide with alterations of the metabolic phenotypes in multiple metabolic pathways. To investigate the mechanisms in chicken responding to NIBV infection, we examined the global transcriptomic and metabolomic profiles of the chicken’s kidney using RNA-seq and GC–TOF/MS, respectively. Furthermore, we analyzed the alterations in cecal microorganism composition in chickens using 16S rRNA-seq. Integrated analysis of these three phenotypic datasets further managed to create correlations between the altered kidney transcriptomes and metabolome, and between kidney metabolome and gut microbiome. We found that 2868 genes and 160 metabolites were deferentially expressed or accumulated in the kidney during NIBV infection processes. These genes and metabolites were linked to NIBV-infection related processes, including immune response, signal transduction, peroxisome, purine, and amino acid metabolism. In addition, the comprehensive correlations between the kidney metabolome and cecal microbial community showed contributions of gut microbiota in the progression of NIBV-infection. Taken together, our research comprehensively describes the host responses during NIBV infection and provides new clues for further dissection of specific gene functions, metabolite affections, and the role of gut microbiota during chicken gout

pRedis: Penalty and locality aware memory allocation in Redis

Due to large data volume and low latency requirements of modern web services, the use of in-memory key-value (KV) cache often becomes an inevitable choice (e.g. Redis and Memcached). The in-memory cache holds hot data, reduces request latency, and alleviates the load on background databases. Inheriting from the traditional hardware cache design, many existing KV cache systems still use recency-based cache replacement algorithms, e.g., LRU or its approximations. However, the diversity of miss penalty distinguishes a KV cache from a hardware cache. Inadequate consideration of penalty can substantially compromise space utilization and request service time. KV accesses also demonstrate locality, which needs to be coordinated with miss penalty to guide cache management. We propose pRedis, Penalty and Locality Aware Memory Allocation in Redis, which synthesizes data locality and miss penalty, in a quantitative manner, to guide memory allocation and replacement in Redis. At the same time, we also explore the diurnal behavior of a KV store and exploit long-term reuse. We replace the original passive eviction mechanism with an automatic dump/load mechanism, in order to smooth the transition between access peaks and valleys. Our evaluation shows that pRedis effectively reduces the average and tail access latency with minimal time and space overhead. For both real-world and synthetic workloads, our approach delivers an average of 14% ~ 52% latency reduction over a state-of-the-art penalty aware cache management scheme, Hyperbolic Caching, and shows more quantitative predictability of performance