RORS: Enhanced Rule-based OWL Reasoning on Spark

The rule-based OWL reasoning is to compute the deductive closure of an ontology by applying RDF/RDFS and OWL entailment rules. The performance of the rule-based OWL reasoning is often sensitive to the rule execution order. In this paper, we present an approach to enhancing the performance of the rule-based OWL reasoning on Spark based on a locally optimal executable strategy. Firstly, we divide all rules (27 in total) into four main classes, namely, SPO rules (5 rules), type rules (7 rules), sameAs rules (7 rules), and schema rules (8 rules) since, as we investigated, those triples corresponding to the first three classes of rules are overwhelming (e.g., over 99% in the LUBM dataset) in our practical world. Secondly, based on the interdependence among those entailment rules in each class, we pick out an optimal rule executable order of each class and then combine them into a new rule execution order of all rules. Finally, we implement the new rule execution order on Spark in a prototype called RORS. The experimental results show that the running time of RORS is improved by about 30% as compared to Kim & Park's algorithm (2015) using the LUBM200 (27.6 million triples).Comment: 12 page

Attribute Simulation for Item Embedding Enhancement in Multi-interest Recommendation

Although multi-interest recommenders have achieved significant progress in the matching stage, our research reveals that existing models tend to exhibit an under-clustered item embedding space, which leads to a low discernibility between items and hampers item retrieval. This highlights the necessity for item embedding enhancement. However, item attributes, which serve as effective and straightforward side information for enhancement, are either unavailable or incomplete in many public datasets due to the labor-intensive nature of manual annotation tasks. This dilemma raises two meaningful questions: 1. Can we bypass manual annotation and directly simulate complete attribute information from the interaction data? And 2. If feasible, how to simulate attributes with high accuracy and low complexity in the matching stage? In this paper, we first establish an inspiring theoretical feasibility that the item-attribute correlation matrix can be approximated through elementary transformations on the item co-occurrence matrix. Then based on formula derivation, we propose a simple yet effective module, SimEmb (Item Embedding Enhancement via Simulated Attribute), in the multi-interest recommendation of the matching stage to implement our findings. By simulating attributes with the co-occurrence matrix, SimEmb discards the item ID-based embedding and employs the attribute-weighted summation for item embedding enhancement. Comprehensive experiments on four benchmark datasets demonstrate that our approach notably enhances the clustering of item embedding and significantly outperforms SOTA models with an average improvement of 25.59% on [email protected]: This paper has been accepted by the 17th ACM International Conference on Web Search and Data Mining (WSDM 2024). The camera-ready version will be available in the conference proceeding

Novel Fe-Mn binary oxide-biochar as an adsorbent for removing Cd(II) from aqueous solutions

In this study, a pristine biochar (BC) and Fe-Mn binary oxide-biochar (FMBC) were prepared using Pennisetum sp. straw as the feedstock for Cd(II) removal from aqueous solutions. Scanning electron microscopy (SEM) coupled with energy dispersive X-ray spectroscopy (EDX), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy and specific surface area (SSA) analyses revealed the physico-chemical characteristics of the pristine and designer adsorbents, suggesting that an ultrasonic treatment during synthesis enhanced the SSA and pore volume of the BC, and assisted successful loading of Fe-Mn binary oxide particles on the BC surface. The Cd(II) adsorption data of the adsorbents were fitted to the Langmuir isothermal and pseudo-second-order kinetic models. At a system temperature of 25 °C and pH 5, the maximum Cd(II) adsorption capacities of BC (30.58 mg/g) and FMBC (95.23 mg/g) were obtained. Multiple Cd(II) adsorption mechanisms by FMBC were identified, including precipitation with minerals, complexation with surface functional groups, Cd(II)-π interactions, and cation exchange. As the most dominant adsorption mechanism, Cd-O bonds were formed on the FMBC surfaces precipitating Cd(OH)2 (63.9 wt%) and CdO (36.1 wt%). The FMBC thus could be potentially used as an effective adsorbent for Cd(II) removal from aqueous solutions

SARS-CoV-2 spike-reactive naïve B cells and pre-existing memory B cells contribute to antibody responses in unexposed individuals after vaccination

IntroductionSince December 2019, the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) has presented considerable public health challenges. Multiple vaccines have been used to induce neutralizing antibodies (nAbs) and memory B-cell responses against the viral spike (S) glycoprotein, and many essential epitopes have been defined. Previous reports have identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike-reactive naïve B cells and preexisting memory B cells in unexposed individuals. However, the role of these spike-reactive B cells in vaccine-induced immunity remains unknown.MethodsTo elucidate the characteristics of preexisting SARS-CoV-2 S-reactive B cells as well as their maturation after antigen encounter, we assessed the relationship of spike-reactive B cells before and after vaccination in unexposed human individuals. We further characterized the sequence identity, targeting domain, broad-spectrum binding activity and neutralizing activity of these SARS-CoV-2 S-reactive B cells by isolating monoclonal antibodies (mAbs) from these B cells.ResultsThe frequencies of both spike-reactive naïve B cells and preexisting memory B cells before vaccination correlated with the frequencies of spike-reactive memory B cells after vaccination. Isolated mAbs from spike-reactive naïve B cells before vaccination had fewer somatic hypermutations (SHMs) than mAbs isolated from spike-reactive memory B cells before and after vaccination, but bound SARS-CoV-2 spike in vitro. Intriguingly, these germline-like mAbs possessed broad binding profiles for SARS-CoV-2 and its variants, although with low or no neutralizing capacity. According to tracking of the evolution of IGHV4-4/IGKV3-20 lineage antibodies from a single donor, the lineage underwent SHMs and developed increased binding activity after vaccination.DiscussionOur findings suggest that spike-reactive naïve B cells can be expanded and matured by vaccination and cocontribute to vaccine-elicited antibody responses with preexisting memory B cells. Selectively and precisely targeting spike-reactive B cells by rational antigen design may provide a novel strategy for next-generation SARS-CoV-2 vaccine development

LANTHANIDE-DOPED UPCONVERSION NANOCRYSTALS: SYNTHESIS, SELF-ASSEMBLY AND THERMOMETRY APPLICATION

Ph.DDOCTOR OF PHILOSOPH

A Validated Liquid Chromatographic Method for Berberine Analysis in Tissue and Application

Simple and rapid high-performance liquid chromatography methods were developed for the determination of berberine (BB) in various rat tissues so as to evaluate a P-gp inhibitor, glycyrrhetinic acid (GA), on BB’s oral bioavailability. Acetonitrile was used to extract BB from tissues and showed different extraction recoveries in diverse tissues. The intra- and interday precision and accuracy were less than 10%. Long-term stability, pre (post) -preparative stability, and freeze-thaw stability were evaluated, and the results showed it could meet the need of this study. The proposed methods were subsequently applied to investigate the possible drug-drug interaction of GA and BB in vivo from the aspect of tissue distribution. The results showed that no significant difference was found between the group of low dose and high dose at the same time point. The tissue distributions show a saturated model, i.e., the content of BB in tissue tends to be constant while its dose is more than 200 mg/kg. Besides, the contents of BB ranged from high to low according to the order of the liver, kidney, and spleen. The BB content in the liver is especially high as compared to other tissues

Enhanced Rule-based OWL Reasoning on Spark

Abstract. The rule-based OWL reasoning is to compute the deductive closure of an ontology by applying RDF/RDFS and OWL entailment rules. In previous work, we present an approach to enhancing the performance of the rule-based OWL reasoning on Spark based on a locally optimal executable strategy. However, some key optimizations that based on LUBM do not generalize to more diverse datasets. In this paper, we analyze these problems, and demonstrate the inference engine. We have evaluated the approach using the real-world datasets. The experimental results show that our approach also achieve better performance as compared to Kim & Park's algorithm (2015)

Numerical study on the effects of non-uniform corrosion and confinement conditions on the bond performance of RC beams

A 3D model is established to simulate the bond performance of corroded RC beams, in which the non-uniform corrosion of tensile reinforcement and confinement conditions (characterized by the thickness-diameter ratios of 1.9–3.8 and stirrup confinement index of 0–8.3%) are investigated. In the 3D numerical model, fine modeling was adopted to consider the influences of corrosion on the steel-concrete interface and the non-uniform corrosion was considered by separating the tensile bars into two parts with inconsistent diameter loss. Meanwhile, a two-stage numerical analysis method was utilized, to reflect the corrosion-induced concrete cracking by applying forced displacement and subsequently analyzed their flexural bond performance. In comparison to the existing experiments, the proposed 3D numerical model is proved to be reasonable. In addition, the simulation results show that the increment of the (residual) bond strength generated by the increasing thickness-diameter ratio increases with the mass loss rate, while the increases of stirrup confinement index cause much more increases in the (residual) bond strength for the corroded RC beams than the un-corroded beams. Furthermore, a bond stress-slip relationship is proposed taking the non-uniform corrosion and confinement conditions into account, which correlates well with the experiments

Lanthanide-Activated Phosphors Based on 4f-5d Optical Transitions: Theoretical and Experimental Aspects

The synthesis of lanthanide-activated phosphors is pertinent to many emerging applications, ranging from high-resolution luminescence imaging to next-generation volumetric full-color display. In particular, the optical processes governed by the 4f-5d transitions of divalent and trivalent lanthanides have been the key to enabling precisely tuned color emission. The fundamental importance of lanthanide-activated phosphors for the physical and biomedical sciences has led to rapid development of novel synthetic methodologies and relevant tools that allow for probing the dynamics of energy transfer processes. Here, we review recent progress in developing methods for preparing lanthanide-activated phosphors, especially those featuring 4f-5d optical transitions. Particular attention will be devoted to two widely studied dopants, Ce3+ and Eu2+. The nature of the 4f-5d transition is examined by combining phenomenological theories with quantum mechanical calculations. An emphasis is placed on the correlation of host crystal structures with the 5d-4f luminescence characteristics of lanthanides, including quantum yield, emission color, decay rate, and thermal quenching behavior. Several parameters, namely Debye temperature and dielectric constant of the host crystal, geometrical structure of coordination polyhedron around the luminescent center, and the accurate energies of 4f and 5d levels, as well as the position of 4f and 5d levels relative to the valence and conduction bands of the hosts, are addressed as basic criteria for high-throughput computational design of lanthanide-activated phosphors

Color-Tunable and Stable Copper Iodide Cluster Scintillators for Efficient X-Ray Imaging

The search for color-tunable, efficient, and robust scintillators plays a vital role in the development of modern X-ray radiography. The radioluminescence tuning of copper iodide cluster scintillators in the entire visible region by bandgap engineering is herein reported. The bandgap engineering benefits from the fact that the conduction band minimum and valence band maximum of copper iodide cluster crystals are contributed by atomic orbitals from the inorganic core and organic ligand components, respectively. In addition to high scintillation performance, the as-prepared crystalline copper iodide cluster solids exhibit remarkable resistance toward both moisture and X-ray irradiation. These features allow copper iodide cluster scintillators to show particular attractiveness for low-dose X-ray radiography with a detection limit of 55 nGy s(-1), a value approximate to 100 times lower than a standard dosage for X-ray examinations. The results suggest that optimizing both inorganic core and organic ligand for the building blocks of metal halide cluster crystals may provide new opportunities for a new generation of high-performance scintillation materials