Aspect-based sentiment analysis (ABSA) aims to detect the targets (which are composed by continuous words), aspects and sentiment polarities in text. Published datasets from SemEval-2015 and SemEval-2016 reveal that a sentiment polarity depends on both the target and the aspect. However, most of the existing methods consider predicting sentiment polarities from either targets or aspects but not from both, thus they easily make wrong predictions on sentiment polarities. In particular, where the target is implicit, i.e., it does not appear in the given text, the methods predicting sentiment polarities from targets do not work. To tackle these limitations in ABSA, this paper proposes a novel method for target-aspect-sentiment joint detection. It relies on a pre-trained language model and can capture the dependence on both targets and aspects for sentiment prediction. Experimental results on the SemEval-2015 and SemEval-2016 restaurant datasets show that the proposed method achieves a high performance in detecting target-aspect-sentiment triples even for the implicit target cases; moreover, it even outperforms the state-of-the-art methods for those subtasks of target-aspect-sentiment detection that they are competent to.

ABox abduction is an important reasoning facility in Description Logics (DLs). It finds all minimal sets of ABox axioms, called abductive solutions, which should be added to a background ontology to enforce entailment of an observation which is a specified set of ABox axioms. However, ABox abduction is far from practical by now because there lack feasible methods working in finite time for expressive DLs. To pave a way to practical ABox abduction, this paper proposes a new problem for ABox abduction and a new method for computing abductive solutions accordingly. The proposed problem guarantees finite number of abductive solutions. The proposed method works in finite time for a very expressive DL, , which underpins the W3C standard language OWL 2, and guarantees soundness and conditional completeness of computed results. Experimental results on benchmark ontologies show that the method is feasible and can scale to large ABoxes.

By employing a conjugated amine-functionalized dicarboxylic ligand (HL = 2,2'-diamino-4,4'-stilbenedicarboxylic acid, HSDCA-NH), we have successfully synthesized and characterized a porous and visible light responsive zirconium metal-organic framework ([ZrO(OH)(L)]·8DMF, denoted as Zr-SDCA-NH). This Zr-MOF showed good chemical stability and broad visible light absorption with an absorption edge at about 600 nm. When used as a photocatalyst, Zr-SDCA-NH exhibits visible-light activity for CO reduction with a formate formation rate of 96.2 μmol h mmol, which is higher than the series of reported amine-functionalized Zr-MOFs. Mott-Schottky measurements, photoluminescence study and photocatalytic experiments demonstrated that the Zr oxo cluster through the LMCT process and the organic ligand both contributed to the CO photoreduction. This study indicates that the combination of amino groups and highly conjugated molecules is a feasible and simple strategy to extend light absorption of the organic ligand, which is beneficial for designing a visible light responsive MOF photocatalyst.

A multifunctional porous N-rich polymer containing s-triazine and Tröger's base was synthesized. It shows selective adsorption for CO2, colorimetric performance for HCl and good catalytic activity in the Knoevenagel condensation.

A new rigid and symmetrical tetracarboxylic ligand 2,3,5,6-tetrakis­(4-carboxyphenyl)­pyrazine (H4TCPP) with aggregation-induced emission effect has been designed and synthesized. By using such a ligand, a novel multifunctional metal–organic framework Zn-TCPP has been successfully constructed. The cross-linkage of dinuclear Zn2(COO)4 clusters and organic TCPP4– ligands results in the three-dimensional channel structure of Zn-TCPP, which has a four connected lvt topology with the point symbol of {42.84}. Zn-TCPP not only displays bright blue luminescence arising from the matrix coordination-induced emission effect of the TCPP4– ligand, but also exhibits effective detection for picric acid and Fe3+ ions. In addition, the activated Zn-TCPP possesses a highly porous framework with a Brunauer–Emmett–Teller surface area of 984 m2 g–1 and CO2 adsorption capacity up to 135 cm3 g–1 at 273 K and 732 mmHg. This work represents a successful example of constructing metal–organic frameworks with desired functions based on the designed organic ligand.

Conjugated microporous polymers based on N,N,N′,N′-tetraphenyl-1,4-phenylenediamine exhibit ultrahigh iodine vapor uptake and good CO2 adsorption.

Ionic porous organic polymers have attracted much attention due to their broad applications in catalysis, energy storage/conversion, proton conduction, etc. In this paper, an ionic porous organic polymer, CMP-PM-Me, was synthesized through post-synthetic modification of a pyrimidine-based conjugated microporous polymer, CMP-PM, which was constructed by the palladium catalyzed Sonogashira reaction of 1,3,5-triethynylbenzen and 2,5-dibromopyrimidine. These two polymers are porous with Brunauer-Emmett-Teller surface areas of 416 and 241 m g for CMP-PM and CMP-PM-Me, respectively. Due to the cationic framework, CMP-PM-Me exhibits a much faster and more efficient adsorption performance to anionic dyes such as Congo red (CR) and methyl orange (MO) than that of CMP-PM with a neutral framework. The uptakes for CR are 400.0 mg g for CMP-PM-Me and 344.8 mg g for CMP-PM, respectively. Furthermore, CMP-PM-Me could quickly and drastically separate anionic dyes from the binary mixed solution of anionic and nonanionic dyes within a short time. This work not only enriches the family of ionic organic porous polymers and widens their synthetic utility, but also demonstrates their applications in the adsorption and separation of anionic dyes in water.

Conjugated microporous polymers based on biphenylene exhibit selective adsorption CO2 over CH4 and N2 and luminescence sensing for picric acid.