41 research outputs found
Topology-aware Debiased Self-supervised Graph Learning for Recommendation
In recommendation, graph-based Collaborative Filtering (CF) methods mitigate
the data sparsity by introducing Graph Contrastive Learning (GCL). However, the
random negative sampling strategy in these GCL-based CF models neglects the
semantic structure of users (items), which not only introduces false negatives
(negatives that are similar to anchor user (item)) but also ignores the
potential positive samples. To tackle the above issues, we propose
Topology-aware Debiased Self-supervised Graph Learning (TDSGL) for
recommendation, which constructs contrastive pairs according to the semantic
similarity between users (items). Specifically, since the original user-item
interaction data commendably reflects the purchasing intent of users and
certain characteristics of items, we calculate the semantic similarity between
users (items) on interaction data. Then, given a user (item), we construct its
negative pairs by selecting users (items) which embed different semantic
structures to ensure the semantic difference between the given user (item) and
its negatives. Moreover, for a user (item), we design a feature extraction
module that converts other semantically similar users (items) into an auxiliary
positive sample to acquire a more informative representation. Experimental
results show that the proposed model outperforms the state-of-the-art models
significantly on three public datasets. Our model implementation codes are
available at https://github.com/malajikuai/TDSGL.Comment: 6 pages,8 figure
Effect of Nano-clay Filler on the Thermal Breakdown Mechanism and Lifespan of Polypropylene Film under AC Fields
The wide application of nanocomposites in the insulation system has greatly contributed to the performance improvement of power equipment. However, nano fillers are not omnipotent for improving the properties of composite dielectrics. In some situations, nano-modified materials are in fact a compromise of improving some performance features while sacrificing others. In this work, the breakdown characteristics and time-to-failure of polypropylene film with nano-clay fillers have been evaluated under combined thermal stress and AC electric fields. Experiments on plain polypropylene (PP) samples have also been carried out under the same test conditions as control. Test results indicated that the time-to-failure of the samples with nano-clay filler was shorter than those without nano filler, which is different from the previous experience. SEM and EDS analyses were conducted to study how the failure mechanism had taken place in both plain polypropylene and the nano-clay filled polypropylene. The failure phenomenon in these materials can be explained by molecular thermodynamics. The main reason for the premature thermal breakdown of PP nanocomposite is essentially due to the weak coupling between nano-clay filler and polymer matrix. Finally, suggestions are proposed for nano modification methods and lifespan prediction models of composite dielectrics
Observation of electronic nematicity driven by three-dimensional charge density wave in kagome lattice KVSb
Kagome superconductors AVSb (A = K, Rb, Cs) provide a fertile
playground for studying various intriguing phenomena such as non-trivial band
topology, superconductivity, giant anomalous Hall effect, and charge density
wave (CDW). Remarkably, the recent discovery of symmetric nematic phase
prior to the superconducting state in AVSb has drawn enormous
attention, as the unusual superconductivity might inherit the symmetry of the
nematic phase. Although many efforts have been devoted to resolve the charge
orders using real-space microscopy and transport measurements, the direct
evidence on the rotation symmetry breaking of the electronic structure in the
CDW state from the reciprocal space is still rare. The underlying mechanism is
still ambiguous. Here, utilizing the micron-scale spatially resolved
angle-resolved photoemission spectroscopy, we observed the fingerprint of band
folding in the CDW phase of KVSb, which yet demonstrates the
unconventional unidirectionality, and is indicative of the rotation symmetry
breaking from to . We then pinpointed that the interlayer coupling
between adjacent planes with -phase offset in the 222 CDW
phase would lead to the preferred twofold symmetric electronic structure.
Time-reversal symmetry is further broken at temperatures below 40 K as
characterized by giant anomalous Hall effect triggered by weak magnetic fields.
These rarely observed unidirectional back-folded bands with time-reversal
symmetry breaking in KVSb may provide important insights into its
peculiar charge order and superconductivity
Observation of nonrelativistic plaid-like spin splitting in a noncoplanar antiferromagnet
Spatial, momentum and energy separation of electronic spins in condensed
matter systems guides the development of novel devices where spin-polarized
current is generated and manipulated. Recent attention on a set of previously
overlooked symmetry operations in magnetic materials leads to the emergence of
a new type of spin splitting besides the well-studied Zeeman, Rashba and
Dresselhaus effects, enabling giant and momentum dependent spin polarization of
energy bands on selected antiferromagnets independent of relativistic
spin-orbit interaction. Despite the ever-growing theoretical predictions, the
direct spectroscopic proof of such spin splitting is still lacking. Here, we
provide solid spectroscopic and computational evidence for the existence of
such materials. In the noncoplanar antiferromagnet MnTe, the in-plane
components of spin are found to be antisymmetric about the high-symmetry planes
of the Brillouin zone, comprising a plaid-like spin texture in the
antiferromagnetic ground state. Such an unconventional spin pattern, further
found to diminish at the high-temperature paramagnetic state, stems from the
intrinsic antiferromagnetic order instead of the relativistic spin-orbit
coupling. Our finding demonstrates a new type of spin-momentum locking with a
nonrelativistic origin, placing antiferromagnetic spintronics on a firm basis
and paving the way for studying exotic quantum phenomena in related materials.Comment: Version 2, 30 pages, 4 main figures and 8 supporting figure
Edaravone Guards Dopamine Neurons in a Rotenone Model for Parkinson's Disease
3-methyl-1-phenyl-2-pyrazolin-5-one (edaravone), an effective free radical scavenger, provides neuroprotection in stroke models and patients. In this study, we investigated its neuroprotective effects in a chronic rotenone rat model for Parkinson's disease. Here we showed that a five-week treatment with edaravone abolished rotenone's activity to induce catalepsy, damage mitochondria and degenerate dopamine neurons in the midbrain of rotenone-treated rats. This abolishment was attributable at least partly to edaravone's inhibition of rotenone-induced reactive oxygen species production or apoptotic promoter Bax expression and its up-regulation of the vesicular monoamine transporter 2 (VMAT2) expression. Collectively, edaravone may provide novel clinical therapeutics for PD
Finishing the euchromatic sequence of the human genome
The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead
An Improved Method of EWT and Its Application in Rolling Bearings Fault Diagnosis
When the vibration signals of the rolling bearings contain strong interference noise, the spectrum division of the vibration signals is seriously disturbed by the noise. The traditional empirical wavelet transform (EWT) decomposes signals into a large number of components, and it is difficult to select suitable components that contain fault information. In order to address the problems above, in this paper, we proposed the improved empirical wavelet transform (IEWT) method. The simulation experiment proved that IEWT can solve the problem of a large number of EWT components and separate the impact component effectively which contains bearing fault information from noise. The IEWT method is combined with the support vector machine (SVM) to diagnosis the fault of the rolling bearings. The permutation entropy (PE) is used to construct feature vectors for its strong induction ability of dynamic changes of nonstationary and nonlinear signals. The crucial parameter penalty factor C and kernel parameter g of SVM are optimized by quantum genetic algorithm (QGA). Compared with traditional EWT and variational mode decomposition (VMD) methods, the effectiveness and advantages of this method are demonstrated in this study. The classification prediction ability of SVM is also better than that of K-nearest neighbor (KNN) and extreme learning machine (ELM)
Point-by-Point-Contact-Based Approach to Compute Position and Orientation between Parts Assembled by Multiple Non-Ideal Planes
Position and orientation deviations (PODs), being affected by surface deviations, occur after parts are assembled, which directly affects the performance of mechanical products. Moreover, mechanical parts are generally assembled with multiple constraint planes, and the generated PODs are influenced by the type of positioning. Therefore, the PODs of multiple planes should be computed in the design stage according to the predicted surface deviations, to control the product performance. However, even though the POD computation of multiple planes has been researched, the effects of surface deviations and multiple types of positioning cannot be considered simultaneously. To address this problem, this study proposes a point-by-point-contact-based approach. The six-point positioning principle is employed to determine the possible number of contact points on each mating plane. The surface deviations are modeled from the perspective of manufacturing errors. Furthermore, the contact points on each mating plane are determined successively using both the strategies of progressively approaching position and of the orientation and recursion of contact points. As a result, the PODs are acquired. The feasibility and usefulness of the proposed approach are verified through a case study. Herein, effects of surface deviations and multiple types of positioning on PODs are unified as contact point variations. Consequently, this approach is expected to assist with accurately controlling the POD influence on the performance of mechanical products in the design stage
Ontology Model for Assembly Process Planning Knowledge
International audienceAssembly process planning is a highly knowledge-intensive work. As collaborative design and manufacturing is getting increasingly popular especially for complex assembly products, assembly process planning knowledge model should be comprehensive, recognizable and reusable. Ontology meets the requirements as a semantic tool providing a source of shared and precisely defined terms that can be utilized to describe both knowledge and concepts. Many researchers have studied the ontology modeling for assembly process planning domain and they mainly focus on the geometry information, tolerance type and manufacture environment respectively. This paper presents an assembly process design knowledge ontology considering assembly requirement, spatial information, assembly operation and assembly resource. It has covered almost every important concept related to assembly process planning knowledge
Point-by-Point-Contact-Based Approach to Compute Position and Orientation between Parts Assembled by Multiple Non-Ideal Planes
Position and orientation deviations (PODs), being affected by surface deviations, occur after parts are assembled, which directly affects the performance of mechanical products. Moreover, mechanical parts are generally assembled with multiple constraint planes, and the generated PODs are influenced by the type of positioning. Therefore, the PODs of multiple planes should be computed in the design stage according to the predicted surface deviations, to control the product performance. However, even though the POD computation of multiple planes has been researched, the effects of surface deviations and multiple types of positioning cannot be considered simultaneously. To address this problem, this study proposes a point-by-point-contact-based approach. The six-point positioning principle is employed to determine the possible number of contact points on each mating plane. The surface deviations are modeled from the perspective of manufacturing errors. Furthermore, the contact points on each mating plane are determined successively using both the strategies of progressively approaching position and of the orientation and recursion of contact points. As a result, the PODs are acquired. The feasibility and usefulness of the proposed approach are verified through a case study. Herein, effects of surface deviations and multiple types of positioning on PODs are unified as contact point variations. Consequently, this approach is expected to assist with accurately controlling the POD influence on the performance of mechanical products in the design stage