Deep Item-based Collaborative Filtering for Top-N Recommendation

Item-based Collaborative Filtering(short for ICF) has been widely adopted in recommender systems in industry, owing to its strength in user interest modeling and ease in online personalization. By constructing a user's profile with the items that the user has consumed, ICF recommends items that are similar to the user's profile. With the prevalence of machine learning in recent years, significant processes have been made for ICF by learning item similarity (or representation) from data. Nevertheless, we argue that most existing works have only considered linear and shallow relationship between items, which are insufficient to capture the complicated decision-making process of users. In this work, we propose a more expressive ICF solution by accounting for the nonlinear and higher-order relationship among items. Going beyond modeling only the second-order interaction (e.g. similarity) between two items, we additionally consider the interaction among all interacted item pairs by using nonlinear neural networks. Through this way, we can effectively model the higher-order relationship among items, capturing more complicated effects in user decision-making. For example, it can differentiate which historical itemsets in a user's profile are more important in affecting the user to make a purchase decision on an item. We treat this solution as a deep variant of ICF, thus term it as DeepICF. To justify our proposal, we perform empirical studies on two public datasets from MovieLens and Pinterest. Extensive experiments verify the highly positive effect of higher-order item interaction modeling with nonlinear neural networks. Moreover, we demonstrate that by more fine-grained second-order interaction modeling with attention network, the performance of our DeepICF method can be further improved.Comment: 25 pages, submitted to TOI

Probing chemical structures and physical processes with nanopores

This thesis develops and applies the nanopore tool to probe chemical structures and physical processes at the single-molecule level: from single ions to DNA molecules. Nanopore experiments electrically measure the ionic transport through the pore and its modulation from the local environment which can be caused by translocations of an analyte such as objects like DNA molecules or change of the physical conditions such as surface charge. Its precision relies on the physical dimension of the nanopore probe. In this thesis, the atom by atom engineering of single-layer molybdenum disulfide (MoS2) nanopores was achieved using transmission electron microscopy (TEM) or controlled electrochemical reaction (ECR), which further enabled the following investigations. On the translational side, the key driver of the application of nanopores is single molecule DNA sequencing. The sequence of DNA can be extracted based on the modulation of ionic current through the pore by individual nucleotides. To this end, we realized for the first time with solid-state nanopores, identification of all four types of nucleotides by introducing an ionic liquid based viscosity gradient system to control the translocation dynamics. This method provides a potential route for sequencing with solid-state nanopores. On the fundamental side, nanopore experiments could probe physics of single ion transport and with subnanometer pores, we discovered Coulomb blockade for the first time in ionic transport, as the counterpart of quantum dots, and proposed a new mesoscopic understanding for biological ion channel transport. From an engineering perspective, measurement with a single nanopore can avoid averaging over many pores and allow accurately identifying individual parameters for membrane-based processes. With single-layer MoS2 nanopores, we realized the first exploration of a two-dimensional (2D) membrane for osmotic power generation. This thesis demonstrates that nanoscopic, atomically thin pores allow for the exploration of applications in DNA sequencing and investigations of fundamental ion transport for biological ion channels and membrane-based processes

Identification of single nucleotides in MoS2 nanopores

Ultrathin membranes have drawn much attention due to their unprecedented spatial resolution for DNA nanopore sequencing. However, the high translocation velocity (3000-50000 nt/ms) of DNA molecules moving across such membranes limits their usability. To this end, we have introduced a viscosity gradient system based on room-temperature ionic liquids (RTILs) to control the dynamics of DNA translocation through a nanometer-size pore fabricated in an atomically thin MoS2 membrane. This allows us for the first time to statistically identify all four types of nucleotides with solid state nanopores. Nucleotides are identified according to the current signatures recorded during their transient residence in the narrow orifice of the atomically thin MoS2 nanopore. In this novel architecture that exploits high viscosity of RTIL, we demonstrate single-nucleotide translocation velocity that is an optimal speed (1-50 nt/ms) for DNA sequencing, while keeping the signal to noise ratio (SNR) higher than 10. Our findings pave the way for future low-cost and rapid DNA sequencing using solid-state nanopores.Comment: Manuscript 24 pages, 4 Figures Supporting Information 24 pages, 12 Figures, 2 Tables Manuscript in review Nature Nanotechnology since May 27th 201

Research on the Demand Forecasting Method of Sichuan Social Logistics Based on Positive Weight Combination

The macro-social logistics demand forecast is of great strategic significance to optimize the national or regional economic structure, improve the investment environment and improve the overall competitiveness of regional economy. In this study, the total amount of social logistics in Sichuan province was selected to reflect the social logistics demand, the factors influencing the social logistics demand in Sichuan province were analyzed, and eight economic indicators were summarized. This study first USES the time series prediction model (including the time response model GM (1, 1)), an exponential smoothing model, causal relation model (including multidimensional prediction model GM (1, n) and BP neural network model), to build four methods combination model, weight given solution of linear programming each forecast model, the forecasting result of combination forecast model deviation is minimal. The posterior difference test was applied to the above five models to compare the prediction results of each prediction method

Performance of Water Desalination and Modern Irrigation Systems for Improving Water Productivity

Desalination is the process that is performed to remove excess salts from water to become potable or agriculture. This applied science is now concerned by many countries suffering from water shortage. Over the next ten years, this science is expected to grow significantly due to the expected water crises in many countries. The consumption of energy in the desalination process is one of the important problems and difficult obstacles that need to be overcome. The Egyptian water strategy should include increasing amount of desalinated water to more than 50%, especially since Egypt is in a very rich location in saltwater sources and they can be utilized to the maximum extent possible. The researchers have attempted to develop varieties of some traditional crops such as wheat, saline resistant to salinity using local selective ecotourism techniques and using genetic engineering through which saline-tolerant genes are added, but it can be said that so far these efforts have not resulted in the production of candidate seawater breeds The maximum salinity of irrigation water in the long term, even for the most salt-tolerant crops such as date palm, is still less than 5 mmol

Why Are the Disabled People Willing to Participate in Sports: Taking Chinese Disabled Table Tennis Players as the Object of Investigation?

Abstract In this paper, questionnaire survey and data analysis are the main research methods. Its main purpose is to try to answer the question "why are the disabled people willing to participate in sports" and to explore some of the important factors that affect the participation of persons with disabilities. The object of the study is the 83 disabled table tennis players in the national training base. "Questionnaire of Motivation Adapted Athletes (AQAM)" is an international standard. Through descriptive analysis and independent sample T test data analysis, this study concludes three points: 1) "enhancing physical fitness", "loving table tennis sport" and "winning the respect of others" are the main reasons that contribute to the participation in sports of disabled persons; 2) The motives of male and female athletes with disabilities to participate in sports are quite different; 3) The sports participation motivation of persons with disabilities is positively related to their family circumstances

TransVCL: Attention-enhanced Video Copy Localization Network with Flexible Supervision

Video copy localization aims to precisely localize all the copied segments within a pair of untrimmed videos in video retrieval applications. Previous methods typically start from frame-to-frame similarity matrix generated by cosine similarity between frame-level features of the input video pair, and then detect and refine the boundaries of copied segments on similarity matrix under temporal constraints. In this paper, we propose TransVCL: an attention-enhanced video copy localization network, which is optimized directly from initial frame-level features and trained end-to-end with three main components: a customized Transformer for feature enhancement, a correlation and softmax layer for similarity matrix generation, and a temporal alignment module for copied segments localization. In contrast to previous methods demanding the handcrafted similarity matrix, TransVCL incorporates long-range temporal information between feature sequence pair using self- and cross- attention layers. With the joint design and optimization of three components, the similarity matrix can be learned to present more discriminative copied patterns, leading to significant improvements over previous methods on segment-level labeled datasets (VCSL and VCDB). Besides the state-of-the-art performance in fully supervised setting, the attention architecture facilitates TransVCL to further exploit unlabeled or simply video-level labeled data. Additional experiments of supplementing video-level labeled datasets including SVD and FIVR reveal the high flexibility of TransVCL from full supervision to semi-supervision (with or without video-level annotation). Code is publicly available at https://github.com/transvcl/TransVCL.Comment: Accepted by the Thirty-Seventh AAAI Conference on Artificial Intelligence(AAAI2023

Evolution of the Surface Structures on SrTiO3_3(110) Tuned by Ti or Sr Concentration

The surface structure of the SrTiO$_3$(110) polar surface is studied by scanning tunneling microscopy and X-ray photoelectron spectroscopy. Monophased reconstructions in (5$\times$1), (4$\times$1), (2$\times$8), and (6$\times$8) are obtained, respectively, and the evolution between these phases can be tuned reversibly by adjusting the Ar$^{+}$ sputtering dose or the amount of Sr/Ti evaporation. Upon annealing, the surface reaches the thermodynamic equilibrium that is determined by the surface metal concentration. The different electronic structures and absorption behaviors of the surface with different reconstructions are investigated.Comment: 10 pages, 14 figure

PolarLight: a CubeSat X-ray Polarimeter based on the Gas Pixel Detector

The gas pixel detector (GPD) is designed and developed for high-sensitivity astronomical X-ray polarimetry, which is a new window about to open in a few years. Due to the small mass, low power, and compact geometry of the GPD, we propose a CubeSat mission Polarimeter Light (PolarLight) to demonstrate and test the technology directly in space. There is no optics but a collimator to constrain the field of view to 2.3 degrees. Filled with pure dimethyl ether (DME) at 0.8 atm and sealed by a beryllium window of 100 micron thick, with a sensitive area of about 1.4 mm by 1.4 mm, PolarLight allows us to observe the brightest X-ray sources on the sky, with a count rate of, e.g., ~0.2 counts/s from the Crab nebula. The PolarLight is 1U in size and mounted in a 6U CubeSat, which was launched into a low Earth Sun-synchronous orbit on October 29, 2018, and is currently under test. More launches with improved designs are planned in 2019. These tests will help increase the technology readiness for future missions such as the enhanced X-ray Timing and Polarimetry (eXTP), better understand the orbital background, and may help constrain the physics with observations of the brightest objects.Comment: Accepted for publication in Experimental Astronom