Automated Prompting for Non-overlapping Cross-domain Sequential Recommendation

Cross-domain Recommendation (CR) has been extensively studied in recent years to alleviate the data sparsity issue in recommender systems by utilizing different domain information. In this work, we focus on the more general Non-overlapping Cross-domain Sequential Recommendation (NCSR) scenario. NCSR is challenging because there are no overlapped entities (e.g., users and items) between domains, and there is only users' implicit feedback and no content information. Previous CR methods cannot solve NCSR well, since (1) they either need extra content to align domains or need explicit domain alignment constraints to reduce the domain discrepancy from domain-invariant features, (2) they pay more attention to users' explicit feedback (i.e., users' rating data) and cannot well capture their sequential interaction patterns, (3) they usually do a single-target cross-domain recommendation task and seldom investigate the dual-target ones. Considering the above challenges, we propose Prompt Learning-based Cross-domain Recommender (PLCR), an automated prompting-based recommendation framework for the NCSR task. Specifically, to address the challenge (1), PLCR resorts to learning domain-invariant and domain-specific representations via its prompt learning component, where the domain alignment constraint is discarded. For challenges (2) and (3), PLCR introduces a pre-trained sequence encoder to learn users' sequential interaction patterns, and conducts a dual-learning target with a separation constraint to enhance recommendations in both domains. Our empirical study on two sub-collections of Amazon demonstrates the advance of PLCR compared with some related SOTA methods

Controlling a Quadrotor Carrying a Cable-Suspended Load to Pass Through a Window

In this paper, we design an optimal control system for a quadrotor to carry a cable-suspended load flying through a window. As the window is narrower than the length of the cable, it is very challenging to design a practical control system to pass through it. Our solution includes a system identification component, a trajectory generation component, and a trajectory tracking control component. The exact dynamic model that usually derived from the first principles is assumed to be unavailable. Instead, a model identification approach is adopted, which relies on a simple but effective low order equivalent system (LOES) to describe the core dynamical characteristics of the system. After being excited by some specifically designed manoeuvres, the unknown parameters in the LOES are obtained by using a frequency based least square estimation algorithm. Based on the estimated LOES, a numerical optimization algorithm is then utilized for aggressive trajectory generation when relevant constraints are given. The generated trajectory can lead to the quadrotor and load system passing through a narrow window with a cascade PD trajectory tracking controller. Finally, a practical flight test based on an Astec Hummingbird quadrotor is demonstrated and the result validates the proposed approach

Analysis of optical absorption in GaAs nanowire arrays

In this study, the influence of the geometric parameters on the optical absorption of gallium arsenide [GaAs] nanowire arrays [NWAs] has been systematically analyzed using finite-difference time-domain simulations. The calculations reveal that the optical absorption is sensitive to the geometric parameters such as diameter [D], length [L], and filling ratio [D/P], and more efficient light absorption can be obtained in GaAs NWAs than in thin films with the same thickness due to the combined effects of intrinsic antireflection and efficient excitation of resonant modes. Optimized geometric parameters are obtained as follows: D = 180 nm, L = 2 μm, and D/P = 0.5. Meanwhile, the simulation on the absorption of GaAs NWAs for oblique incidence has also been carried out. The underlying physics is discussed in this work

Secondary structural characterization of oligonucleotide strands using electrospray ionization mass spectrometry

Differences in charge state distributions of hairpin versus linear strands of oligonucleotides are analyzed using electrospray ionization mass spectrometry (ESI-MS) in the negative ion detection mode. It is observed that the linear structures show lower charge state distribution than the hairpin strands of the same composition. The concentration of ammonium acetate and the cone voltage are major factors that cause the shift of the negative ions in the charge states. The ESI data presented here are supported by UV spectra of strands acquired at 260 nm wavelength in aqueous ammonium acetate solution. We will show that the strands that demonstrate a higher charge state distribution in the gas phase also have a higher melting temperature in solution

Inter-comparison of high-resolution satellite precipitation products over Central Asia

This paper examines the spatial error structures of eight precipitation estimates derived from four different satellite retrieval algorithms including TRMM Multi-satellite Precipitation Analysis (TMPA), Climate Prediction Center morphing technique (CMORPH), Global Satellite Mapping of Precipitation (GSMaP) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). All the original satellite and bias-corrected products of each algorithm (3B42RTV7 and 3B42V7, CMORPH_RAW and CMORPH_CRT, GSMaP_MVK and GSMaP_Gauge, PERSIANN_RAW and PERSIANN_CDR) are evaluated against ground-based Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) over Central Asia for the period of 2004 to 2006. The analyses show that all products except PERSIANN exhibit overestimation over Aral Sea and its surrounding areas. The bias-correction improves the quality of the original satellite TMPA products and GSMaP significantly but slightly in CMORPH and PERSIANN over Central Asia. 3B42RTV7 overestimates precipitation significantly with large Relative Bias (RB) (128.17%) while GSMaP_Gauge shows consistent high correlation coefficient (CC) (>0.8) but RB fluctuates between -57.95% and 112.63%. The PERSIANN_CDR outperforms other products in winter with the highest CC (0.67). Both the satellite-only and gauge adjusted products have particularly poor performance in detecting rainfall events in terms of lower POD (less than 65%), CSI (less than 45%) and relatively high FAR (more than 35%)

Evaluation of Anti-tumor and Chemoresistance-lowering Effects of Pectolinarigenin from Cirsium japonicum Fisch ex DC in Breast Cancer

Purpose: To investigate the antitumor and chemoresistance-lowering effects of pectolinarigenin on breast cancer cells.Methods: Pectolinarigenin was purified by a combination of silica gel and Sephadex LH-20 column chromatography from ethanol extracts of the aerial parts of C. japonicum DC. Breast cancer selfrenewal properties were tested by colony formation and tumor sphere formation assays. Thereafter, real-time polymerase chain reaction (PCR) was used to detect breast cancer stem cell markers. Furthermore, the effect of pectolinarigenin on breast cancer cell was evaluated by chemoresistance using 3-(4,5-dimethyl-2 thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) assay. Finally, tumor formation in nude mice was used to test the effect of pectolinarigenin on tumorigenicity of breast cancer cells in vivo.Results: The results showed that pectolinarigenin, extracted from Cirsium japonicum Fisch. ex DC., inhibited tumor cell self-renewal in MCF-7 breast cancer cells. Pectolinarigenin (25 μM) caused significant inhibition of colony formation (61.23 %, p < 0.001) and tumor sphere formation (59.49 %, p < 0.01) in MCF-7. The inhibitory effects were associated with changes in breast cancer stem cell markers. Treatment of breast cancer cells with pectolinarigenin reduced the chemoresistance of the cells to doxorubicin. At the same time, mRNA expression of chemoresistance genes (ATP binding cassette subfamily G member 2, ABCG2 and ATP binding cassette subfamily B member 1, MDR1) was repressed by pectolinarigenin. The inhibition efficiency of MDR1 and ABCG2 by 10 μM pectolinarigenin treatment was about 59.29 (p < 0.01) and 46.48 % (p < 0.01), respectively. Furthermore, pectolinarigenin reduced tumor mass in nude mice xenograft model.Conclusion: Pectolinarigenin inhibits breast cancer stem cell-like properties and lowers the chemoresistance of the cancer cells to chemotherapy. The results provide an insight into the mechanism of the anti-breast tumor effects and an experimental basis for the use of pectolinarigenin to enhance treatment of patients with breast cancer.Keywords: Pectolinarigenin, Cancer stem cells, Breast cancer, Chemoresistance, Cirsium japonicum Fisch. ex D