An empirical study of next-basket recommendations

Next Basket Recommender Systems (NBRs) function to recommend the subsequent shopping baskets for users through the modeling of their preferences derived from purchase history, typically manifested as a sequence of historical baskets. Given their widespread applicability in the E-commerce industry, investigations into NBRs have garnered increased attention in recent years. Despite the proliferation of diverse NBR methodologies, a substantial challenge lies in the absence of a systematic and unified evaluation framework across these methodologies. Various studies frequently appraise NBR approaches using disparate datasets and diverse experimental settings, impeding a fair and effective comparative assessment of methodological performance. To bridge this gap, this study undertakes a systematic empirical inquiry into NBRs, reviewing seminal works within the domain and scrutinizing their respective merits and drawbacks. Subsequently, we implement designated NBR algorithms on uniform datasets, employing consistent experimental configurations, and assess their performances via identical metrics. This methodological rigor establishes a cohesive framework for the impartial evaluation of diverse NBR approaches. It is anticipated that this study will furnish a robust foundation and serve as a pivotal reference for forthcoming research endeavors in this dynamic field.Comment: 6 pages, 2 figure

Homology Characteristics of EEG and EMG for Lower Limb Voluntary Movement Intention

In the field of lower limb exoskeletons, besides its electromechanical system design and control, attention has been paid to realizing the linkage of exoskeleton robots to humans via electroencephalography (EEG) and electromyography (EMG). However, even the state of the art performance of lower limb voluntary movement intention decoding still faces many obstacles. In the following work, focusing on the perspective of the inner mechanism, a homology characteristic of EEG and EMG for lower limb voluntary movement intention was conducted. A mathematical model of EEG and EMG was built based on its mechanism, which consists of a neural mass model (NMM), neuromuscular junction model, EMG generation model, decoding model, and musculoskeletal biomechanical model. The mechanism analysis and simulation results demonstrated that EEG and EMG signals were both excited by the same movement intention with a response time difference. To assess the efficiency of the proposed model, a synchronous acquisition system for EEG and EMG was constructed to analyze the homology and response time difference from EEG and EMG signals in the limb movement intention. An effective method of wavelet coherence was used to analyze the internal correlation between EEG and EMG signals in the same limb movement intention. To further prove the effectiveness of the hypothesis in this paper, six subjects were involved in the experiments. The experimental results demonstrated that there was a strong EEG-EMG coherence at 1 Hz around movement onset, and the phase of EEG was leading the EMG. Both the simulation and experimental results revealed that EEG and EMG are homologous, and the response time of the EEG signals are earlier than EMG signals during the limb movement intention. This work can provide a theoretical basis for the feasibility of EEG-based pre-perception and fusion perception of EEG and EMG in human movement detection

Simultaneous Identification of Multiple Causal Mutations in Rice

Next-generation sequencing technologies (NGST) are being used to discover causal mutations in ethyl methanesulfonate (EMS)-mutagenized plant populations. However, the published protocols often deliver too many candidate sites and sometimes fail to find the mutant gene of interest. Accurate identification of the causal mutation from massive background polymorphisms and sequencing deficiencies remains challenging. Here we describe a NGST-based method, named SIMM, that can simultaneously identify the causal mutations in multiple independent mutants. Multiple rice mutants derived from the same parental line were back-crossed, and for each mutant, the derived F2 individuals of the recessive mutant phenotype were pooled and sequenced. The resulting sequences were aligned to the Nipponbare reference genome, and single nucleotide polymorphisms (SNPs) were subsequently compared among the mutants. Allele index (AI) and Euclidean distance (ED) were incorporated into the analysis to reduce noises caused by background polymorphisms and re-sequencing errors. Corrections of sequence bias against GC- and AT-rich sequences in the candidate region were conducted when necessary. Using this method, we successfully identified seven new mutant alleles from Huanghuazhan (HHZ), an elite indica rice cultivar in China. All mutant alleles were validated by phenotype association assay.Guangdong Innovative Research Team Program [201001S0104725509]; Ministry of Agriculture Transgenic Project [2012ZX08001001]; National Program on Key Basic Research Project of China [973 Program] [2011CB100101, 2013CBA01402]; National High Technology Research and Development Program of China [863 Program] [2014AA10A602]; Natural Science Foundation of China [31110103917]; Shenzhen Commission on Innovation and Technology [KQF201109160004A, CXZZ20140411140647863]SCI(E)ARTICLE

An Approach for Brain-Controlled Prostheses Based on a Facial Expression Paradigm

One of the most exciting areas of rehabilitation research is brain-controlled prostheses, which translate electroencephalography (EEG) signals into control commands that operate prostheses. However, the existing brain-control methods have an obstacle between the selection of brain computer interface (BCI) and its performance. In this paper, a novel BCI system based on a facial expression paradigm is proposed to control prostheses that uses the characteristics of theta and alpha rhythms of the prefrontal and motor cortices. A portable brain-controlled prosthesis system was constructed to validate the feasibility of the facial-expression-based BCI (FE-BCI) system. Four types of facial expressions were used in this study. An effective filtering algorithm based on noise-assisted multivariate empirical mode decomposition (NA-MEMD) and sample entropy (SampEn) was used to remove electromyography (EMG) artifacts. A wavelet transform (WT) was applied to calculate the feature set, and a back propagation neural network (BPNN) was employed as a classifier. To prove the effectiveness of the FE-BCI system for prosthesis control, 18 subjects were involved in both offline and online experiments. The grand average accuracy over 18 subjects was 81.31 ± 5.82% during the online experiment. The experimental results indicated that the proposed FE-BCI system achieved good performance and can be efficiently applied for prosthesis control

Reliability sensitivity method by line sampling

Community welfare and food security in Indonesia partly depend on developments in the agricultural sector. This sector increasingly faces the problem of water scarcity caused by declining water resources and increasing competition over water with households and industries. To overcome these problems and to ensure stability, economic growth and food security, it has been recognised that the government has to reform the water policy in Indonesia. Water policies are most of the time based on the water withdrawal per sector. A useful addition to this are the concepts of water footprint and virtual water trade. The water footprint is an indicator of water use that looks at both direct and indirect water use. The water footprint of the people in a province is defined as the total amount of water that is used to produce the goods and services consumed by the inhabitants of the province. This water footprint is partly inside the province itself (the internal footprint) and partly presses somewhere else (external footprint). Virtual-water trade refers to the transfer of water in virtual form from one place to another as a result of product trade. Virtual water refers to the volume of freshwater embedded in a product, not in real but virtual sense; it refers to the water that was used to make the product. Quantitative information about the water footprint per province and interprovincial virtual water flows can feed a discussion on the role of trade in water resources management. The aim of this report is to quantify interprovincial virtual water flows related to trade in crop products and determine the water footprint related to the consumption of crop products per Indonesian province

Hydrogen-Etched TiO2−x as Efficient Support of Gold Catalysts for Water–Gas Shift Reaction

Hydrogen-etching technology was used to prepare TiO2−x nanoribbons with abundant stable surface oxygen vacancies. Compared with traditional Au-TiO2, gold supported on hydrogen-etched TiO2−x nanoribbons had been proven to be efficient and stable water–gas shift (WGS) catalysts. The disorder layer and abundant stable surface oxygen vacancies of hydrogen-etched TiO2−x nanoribbons lead to higher microstrain and more metallic Au0 species, respectively, which all facilitate the improvement of WGS catalytic activities. Furthermore, we successfully correlated the WGS thermocatalytic activities with their optoelectronic properties, and then tried to understand WGS pathways from the view of electron flow process. Hereinto, the narrowed forbidden band gap leads to the decreased Ohmic barrier, which enhances the transmission efficiency of “hot-electron flow”. Meanwhile, the abundant surface oxygen vacancies are considered as electron traps, thus promoting the flow of “hot-electron” and reduction reaction of H2O. As a result, the WGS catalytic activity was enhanced. The concept involved hydrogen-etching technology leading to abundant surface oxygen vacancies can be attempted on other supported catalysts for WGS reaction or other thermocatalytic reactions