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Aspect level sentiment classification aims to extract fine-grained sentiment expressed towards specific aspects from a sentence. The key to this task lies in connecting aspects and their respective sentiment contexts. Existing methods measure the dependency weights between aspects and context words via either the semantic similarity between words captured by attention mechanism or the structural proximity between words in syntactic structures. However, methods in both groups fail to fully exploit explicit syntactic dependency, which we argue should be critical to identify sentiment contexts. In this paper, we propose a novel syntactic-dependency-based attention network (SDATT) to incorporate explicit syntactic dependency for aspect level sentiment classification. SDATT first models the dependency path between each word and the aspect to characterize aspect-oriented syntactic representation of each word. The generated syntactic representations are later fed into the attention layer to help infer the dependency weights for sentiment prediction. Experimental results on five benchmark datasets show the superior performance of the proposed model over state-of-the-art baselines.

Small molecule organic photovoltaics (SMPVs) were prepared by utilizing liquid crystalline donor material BTR-Cl and two similar optical bandgap non-fullerene acceptor materials BTP-BO-4F and Y6. The BTP-BO-4F and Y6 have the similar optical bandgap and different absorption coefficients. The corresponding binary SMPVs exhibit different short circuit current density (JSC) (20.38 vs. 23.24 mA cm−2), and fill factor (FF) (70.77% vs. 67.21%). A 14.46% power conversion efficiency (PCE) is acquired in ternary SMPVs with 30 wt% Y6, companied with a JSC of 24.17 mA cm−2, a FF of 68.78% and an open circuit voltage (VOC) of 0.87 V. The improvement on PCE of ternary SMPVs should originate from the well trade-off between phase separation and photon harvesting of ternary active layers by incorporating 30 wt% Y6 in acceptors. This work may deliver insight onto the improved performance of SMPVs by superposing the superiorities of binary SMPVs with similar optical bandgap acceptors into one ternary cell.

When considering the problem of influence maximization from information cascades, one essential component is influence estimation. Traditional approaches for influence estimation generally follow a two-stage framework, i.e., learn a hypothetical diffusion model from information cascades and then calculate the influence spread according to the learned diffusion model via Monte Carlo simulation or heuristic approximation. The effectiveness of these approaches heavily relies on the correctness of the diffusion model, suffering from the problem of model misspecification. Meanwhile, these approaches are inefficient when influence estimation is conducted via lots of Monte Carlo simulations. In this paper, without assuming a diffusion model a priori, we directly learn a monotone and submodular influence function from information cascades. Once the influence function is obtained, greedy algorithm is applied to efficiently solve influence maximization. Experimental results on both synthetic and real-world datasets show the effectiveness and efficiency of the learned influence function for both influence estimation and influence maximization tasks.

According to the model of sliding ferroelectricity we proposed in 2017, a type of vertical polarization switchable via interlayer sliding may exist in a series of two-dimensional van der Waals bilayers and multilayers. Such intriguing ferroelectricity has been recently experimentally confirmed in BN and WTe2 bilayer/multilayer systems. However, they are respectively insulators and metals with weak polarizations. Here, we search for a combination of high-mobility semiconductors and ferroelectricity with relatively high polarizations, and we note that MoSi2N4 monolayer has been recently fabricated to centimeter scale based on MoN2 monolayer (Science 2020, 369, 670). We show first-principles evidence of strong interlayer sliding ferroelectricity in high-mobility semiconducting MoA2N4 (A = Si or Ge) bilayers and multilayers. They possess tunable bandgaps within the desirable range for nanoelectronics, with the current highest polarizations in sliding ferroelectrics known to date due to strong interlayer van der Waals interactions. Such a successful combination of these properties may render the long-sought and efficient computing-in-memory possible. Their high polarizations induce strong Moire potential and unique band alignments for exciton trapping in twisted MoA2N4 bilayer. The varying charge distribution of different stacking in MoN2/MoSi2N4 hetero-bilayer also gives rise to a high alternating voltage when used as a nanogenerator, suggesting promising potential for energy harvesting.

Over 200 nm thickness of active layers are essential for achieving efficient organic photovolatics (OPVs) using the roll-to-roll (R2R) large-scale production technology. In this study, a series of OPVs with 300 nm thick active layers were prepared with PM6:BTP-4F-12:BP-4F as active layers. The PM6:BTP-4F-12- and PM6:BP-4F-based binary OPVs achieve power conversion efficiencies (PCE) of 14.62% and 14.14%, respectively, with 300 nm thick active layers, also exhibiting complementary photovoltaic parameters. A PCE of 15.63% is achieved by the optimized ternary thick-film OPVs by combining the superiorities of two binary thick-film OPVs, deriving from a short circuit current density (JSC) of 26.57 mA cm−2, an open circuit voltage (VOC) of 0.840 V and a fill factor (FF) of 70.03%. The performance improvement of ternary thick-film OPVs should be mainly ascribed to the optimized molecular arrangement and phase separation for efficient charge transport in ternary thick active layers, which can be confirmed from the significantly improved FFs of ternary thick-film OPVs. This study indicates that the ternary strategy has great potential in preparing efficient thick-film OPVs.

Semitransparent organic solar cells (OSCs) were fabricated with a broad bandgap polymer D18-Cl as the donor (D), narrow bandgap small molecule Y6-1O as the acceptor (A) and ultra-narrow bandgap material Y6 as the third component. A power conversion efficiency (PCE) of 14.92% can be obtained from opaque OSCs with D18-Cl:Y6-1O (1.1 : 1.6, wt/wt or 0.7 : 1.6, wt/wt) as active layers, which is due to the dependence of the three well-balanced photovoltaic parameters on D18-Cl content in the active layer. It should be highlighted that the average visible transmittance (AVT) of blend films can be markedly enhanced from 30.3% to 47.3% with decrease in D:A from 1.1 : 1.6 to 0.7 : 1.6 (wt/wt), which is highly conducive to the preparation of semitransparent OSCs. Keeping the D:A as constant (0.7 : 1.6, wt/wt), 16.05% PCE is achieved in opaque ternary OSCs with D18-Cl:Y6-1O:Y6 (0.7 : 0.8 : 0.8, wt/wt) as the active layers, resulting from the slightly increased JSC of 23.21 mA cm−2 and FF of 76.74%. The AVT of the corresponding ternary blend films is also improved to 50.1%. Semitransparent ternary OSCs are fabricated with Au (1 nm)/Ag (20 nm, 15 nm, 10 nm) replacing 100 nm Ag as the electrode. A PCE of 13.02%, an AVT of 20.2% and light utilization efficiency of 2.63% are obtained from the semitransparent OSCs with Au (1 nm)/Ag (10 nm) as the electrode. This work indicates that adjusting D:A weight ratio and employing a ternary strategy should have great potential in simultaneously improving the PCE and AVT of semitransparent OSCs, especially using a wide bandgap polymer as the donor.

Due to their unique merits, asymmetrical fused-ring electron acceptors (FREAs) have received increasing attention in the field of organic photovoltaics (OPVs). Herein, we designed and synthesized an asymmetrical FREA, namely AY6, by employing a cross-conceptual strategy which combines the structural features of asymmetrical IT6-4F with high-performance Y6. Compared to Y-shape Y6, X-shape AY6 shows poor crystallization properties and thus a significantly blue-shifted absorption. However, it is precisely because of this unfavorable self-stacking effect that AY6 has an opportunity to pack with PM6 and form a new intermixed phase. As a result, the PM6:AY6 blend film exhibits a perfect face-on orientation with stronger π–π stacking than the PM6:Y6 blend film, which facilitates efficient exciton dissociation and balanced carrier transport, and therefore higher FF. In general, such a cross-conceptual design strategy is an effective method which not only boosts the efficiency of asymmetrical FREA-based OSCs but also increases the fill factors of OSCs based on Y6-like FREAs.

Ternary organic photovoltaics (OPVs) are fabricated with PBDB-T-2Cl:Y6 (1:1.2, wt/wt) as the host system and extra PC71BM as the third component. The PBDB-T-2Cl:Y6 based binary OPVs exhibit a power conversion efficiency (PCE) of 15.49% with a short circuit current ( J SC) of 24.98 mA cm−2, an open circuit voltage ( V OC) of 0.868 V and a fill factor (FF) of 71.42%. A 16.71% PCE is obtained in the optimized ternary OPVs with PBDB-T-2Cl:Y6:PC71BM (1:1.2:0.2, wt/wt) active layer, resulting from the synchronously improved J SC of 25.44 mA cm−2, FF of 75.66% and the constant V OC of 0.868 V. The incorporated PC71BM may prefer to mix with Y6 to finely adjust phase separation, domain size and molecular arrangement in ternary active layers, which can be confirmed from the characterization on morphology, 2D grazing incidence small and wide-angle X-ray scattering, as well as Raman mapping. In addition, PC71BM may prefer to mix with Y6 to form efficient electron transport channels, which should be conducive to charge transport and collection in the optimized ternary OPVs. This work provides more insight into the underlying reasons of the third component on performance improvement of ternary OPVs, indicating ternary strategy should be an efficient method to optimize active layers for synchronously improving photon harvesting, exciton dissociation and charge transport, while keeping the simple cell fabrication technology.

The mitochondrial genome (mitogenome) provides important information for better understanding the phylogenetic relationships within heteropteran infraorder Cimicomorpha (Hemiptera: Heteroptera), but there are still limited representations at the family level of Anthocoridae. Here we sequenced the complete mitogenome of Tetraphleps aterrimus. It is 15,803 bp in size, and contains the expected 37 genes (13 PCGs, 22 tRNAs and 2 rRNAs) and control region. Gene order is identical to that of typical cimicomorphans. In comparison with other cimicomorphans, the ratios of Ka/Ks are increasing from 0.17 for COI to 0.85 for ATP8, which demonstrates COI shows the lowest evolutionary rate, while ATP8 appears to be the highest. The ratios of conserved sites of COI is the highest, while ATP8 is the lowest, suggesting that the evolutionary rate of ATP8 is higher than COI. The phylogenetic relationships based on mitogenomes using Bayesian inference (BI) and Maximum likelihood (ML) methods show that Tetraphleps aterrimus is sister to (Orius niger + Orius sauteri), suggesting that Tetraphleps aterrimus belongs to Anthocoridae. The monophyly of each superfamily is generally well supported and Reduvioidea is placed as basal branch in Cimicomorpha. The results support the remaining superfamily groupings (Miroidea + (Cimicoidea + (Velocipedoidea + Nabioidea))).

Biothiols, such as glutathione (GSH), homocysteine (Hcy) and cysteine (Cys), are important biomarkers and play crucial roles in many physiological processes. Thus, the detection of biothiols is highly important for early diagnosis of diseases and evaluation of disease progression. Herein, new types of BODIPY-based fluorescent probes (probe 1, probe 2 and probe 3) capable of cysteine (Cys)/homocysteine (Hcy) sensing with high selectivity over other amino acids were developed. In addition, we further studied the influence of different electronegativity substituents on these probes to sensing Cys/Hcy. Ultimately, we concluded that the electron withdrawing group on probe 1 can accelerate the probe response to Cys/Hcy, and probe 1 was successfully applied for selective imaging Cys/Hcy in living cells.

The power conversion efficiency (PCE) of organic photovoltaics (OPVs) has exceeded 18% with narrow bandgap, non-fullerene materials Y6 or its derivatives when used as an electron acceptor. The PCE improvement of OPVs is due to strong photon harvesting in near-infrared light range and low energy loss. Meanwhile, ternary strategy is commonly recognized as a convenient and efficient means to improve the PCE of OPVs. In this review article, typical donor and acceptor materials in prepared efficient OPVs are summarized. From the device engineering perspective, the typical research work on ternary strategy and tandem structure is introduced for understanding the device design and materials selection for preparing efficient OPVs.

A series of ternary organic photovoltaics (OPVs) are fabricated with one wide bandgap polymer D18-Cl as donor, and well compatible Y6 and Y6-1O as acceptor. The open-circuit-voltage (VOC) of ternary OPVs is monotonously increased along with the incorporation of Y6-1O, indicating that the alloy state should be formed between Y6 and Y6-1O due to their excellent compatibility. The energy loss can be minimized by incorporating Y6-1O, leading to the VOC improvement of ternary OPVs. By finely adjusting the Y6-1O content, a power conversion efficiency of 17.91% is achieved in the optimal ternary OPVs with 30 wt% Y6-1O in acceptors, resulting from synchronously improved short-circuit-current density (JSC) of 25.87 mA cm−2, fill factor (FF) of 76.92% and VOC of 0.900 V in comparison with those of D18-Cl : Y6 binary OPVs. The JSC and FF improvement of ternary OPVs should be ascribed to comprehensively optimal photon harvesting, exciton dissociation and charge transport in ternary active layers. The more efficient charge separation and transport process in ternary active layers can be confirmed by the magneto-photocurrent and impedance spectroscopy experimental results, respectively. This work provides new insight into constructing highly efficient ternary OPVs with well compatible Y6 and its derivative as acceptor., By employing the well compatible Y6 : Y6-1O as acceptor and wide bandgap polymer D18-Cl as donor, the PCE of 17.91% is achieved in optimized ternary OPVs, resulting from the simultaneously improved JSC, FF and VOC.

The power conversion efficiency (PCE) of 13.00% was achieved in PBDB-T:Y16-based polymer solar cells (PSCs). On this basis, PCE of ternary PSCs was improved to 14.11% by incorporating 15 wt% MeIC1 in acceptors, resulting from simultaneously enhanced short circuit current (JSC) of 22.76 mA cm−2 and fill factor (FF) of 68.22%. The observed 14.11% PCE is among the highest values for all ternary PSCs. Y16 and MeIC1 preferred to form an alloyed acceptor due to good compatibility, which is beneficial to the formation of efficient electron transport channels in ternary active layers. Photon harvesting, exciton dissociation and charge transport could be synergistically optimized by incorporating 15 wt% MeIC1 in the acceptors. The optical field and photogenerated exciton distribution in active layers were calculated according to their intrinsic properties, which could provide more intuitive evidence of JSC and FF improvement. The photogenerated exciton distribution in active layers could also be optimized by employing a ternary strategy, which was beneficial for better balance charge collection efficiency and for achieving high FF of the ternary PSCs. This work further demonstrates that ternary strategies have great potential for improving the PSC performance by simultaneously optimizing photon harvesting and photogenerated exciton distribution in active layers.

Ternary-blend organic solar cells (TOSCs) are fabricated with PM6:BTP-4F-12 as the host system and IT-M as the third component. The third component IT-M takes multiple roles in improving performance of TOSCs through reducing energy-loss of the optimized TOSCs, optimizing molecular arrangement and phase separation in active-layers. The well optimized molecular arrangement and phase separation can be beneficial to charge separation and transport in TOSC, which can be confirmed by the characterization of 2D grazing incidence wide-angle X-ray scattering, transmission electron microscopy, magneto-photocurrent, as well as electrochemical impedance spectroscopy. By finely optimizing IT-M content, a power-conversion-efficiency (PCE) of 17.71% is achieved in the optimized TOSCs, benefiting from simultaneously enhanced short-circuit-current density (JSC) of 25.95 mA cm−2, open-circuit-voltage (VOC) of 0.875 V and fill-factor (FF) of 78.02% in comparison with the OSCs with PM6:BTP-4F-12 as active-layers. Furthermore, average PCE over 15% can be achieved from twenty individual TOSCs with active-layer thickness of 300 nm, indicating the optimized TOSCs have excellent thickness tolerance.

Tamibarotene (Am80) has good curative effect on advanced hepatocellular carcinoma (HCC). To improve the therapeutic efficacy furtherly, we prepared tamibarotene-loaded PLGA microspheres (Am80-PLGA-MS) for intratumoral injection. Firstly, Am80-PLGA-MS were prepared by emulsion-solvent evaporation method. Subsequently, microspheres were characterized by particle size analysis, drug loading (DL), and entrapment efficiency (EE). Finally, the drug release characteristics in vitro, pharmacokinetic, and pharmacodynamics were studied separately. According to results obtained, microspheres were spherical with a uniform particle size 7.04 ± 0.03 μm and its EE and DL were 82.23 ± 0.74 and 11.74 ± 0.11%, respectively. In vitro, Am80-PLGA-MS can release drug for 14 days and its release behavior was fitted with the Higuchi equation. In pharmacokinetic studies, the t1/2β, MRT, and AUC of microspheres were 15.43-fold, 8.62-fold, and 9.98-fold those of Am80 solution, respectively, which revealed that the utilization of drug was improved obviously. The pharmacodynamics studies showed that the tumor doubling time, growth inhibition rate, and specific growth rate of tumor of Am80-PLGA-MS were 1.34 times, 2.63 times, and 0.72 times those of drug solution, respectively, indicating that the inhibitory effect on tumor by the microspheres was significantly improved. In summary, Am80-PLGA-MS are promising carrier to enhance the inhibitory effect on tumor, which will provide significantly clinical value for treatment of HCC.

Efficient organic solar cells (OSCs) are fabricated using polymer PM6 as donor, and IPTBO-4Cl and MF1 as acceptors. The power conversion efficiency (PCE) of IPTBO-4Cl based and MF1 based binary OSCs individually arrive to 14.94% and 12.07%, exhibiting markedly different short circuit current density (JSC ) of 23.18 mA cm-2 versus 17.01 mA cm-2 , fill factor (FF) of 72.17% versus 78.18% and similar open circuit voltage (VOC ) of 0.893 V versus 0.908 V. The two acceptors, IPTBO-4Cl and MF1, have similar lowest unoccupied molecular orbital levels, which is beneficial for efficient electron transport in the ternary active layer. The PCE of optimized ternary OSCs arrives to 15.74% by incorporating 30 wt% MF1 in acceptors, resulting from the simultaneously increased JSC of 23.20 mA cm-2 , VOC of 0.897 V, and FF of 75.64% in comparison with IPTBO-4Cl based binary OSCs. The gradually increased FFs of ternary OSCs indicate the well-optimized phase separation and molecular arrangement with MF1 as morphology regulator. This work may provide a new viewpoint for selecting an appropriate third component to achieve efficient ternary OSCs from materials and photovoltaic parameters of two binary OSCs.

Due to the unique structures, photoelectric properties, good catalytic activity, and broad potential applications, gold nanoclusters (Au n ) received extensive attention in catalysis, bioengineering, environmental engineering, and so on. In the present work, the structures and properties of Au n adsorbed on the MgO(001) and TiO 2 (101) surfaces were investigated by density functional theory. The results showed that the catalytic properties of Au n will be enhanced when Au n is adsorbed on certain supports. Because the difference of the outer electronic structure of metals in supports, the direction of the charge transfer was different, thus inducing the different charge distribution on Au n . When Au n was adsorbed on MgO(001) [TiO 2 (101)] surface, Au n will have negative [positive] charges and thus higher catalytic activity in oxidation [reduction] reaction. The variation of surface charges caused by the support makes Au n possess different catalytic activity in different systems. Moreover, the electronic structure of the support will make an obvious influence on the s and d density of states of Au n , which should be the intrinsic reason that induces the variations of its structure and properties. These results should be an important theoretical reference for designing Au n as the photocatalyst applied to the different oxidation and reduction reactions.

The complicated battery reaction mechanism and the limited reversibility of the aqueous zinc ion batteries (ZIBs) significantly hindered their practical application. Herein, we prepared a common VS2 nanosheets, which was further employed as cathode for ZIBs to clarify its Zn2+ storage mechanism. The Zn/VS2 battery electrochemical reaction mechanism was experimentally demonstrated, by using XPS, ex- and in-situ Raman, as an intercalation/conversion combination reaction. Of which, the intercalation reaction in 0.4–1.0 V is reversible, while the conversion reaction in 0.8–1.0 V is irreversible. The battery cycled in 0.4–1.0 V shows a limited cyclability and energy efficiency. By controlling the recharge depth to 0.8 V, the irreversible conversion in 0.8–1.0 V can thus be blocked. The battery operated in the optimized voltage window shows a high capacity of ~118.3 mAh g−1 over 200 cycles. Moreover, a high energy efficiency of ~83.6% can be retained after 350 cycles, which could be attributed to the lower charge/discharge voltage gap and the suppression of the irreversible reactions. We believe that this work could further enhance the fundamental understanding of the Zn2+ ions’ storage mechanism of the layered-type transition metal dichalcogenides and serves as a new guideline for their future optimization.

Using density-functional theory, we investigate the electronic and magnetic properties of an adatom (Na, Cu and Fe) on ABA- and ABC-stacked (Bernal and rhombohedral) trilayer graphenes. In particular, we study the influence of an applied gate voltage on magnetism, as it modifies the electronic states of the trilayer graphene (TLG) as well as changes the adatom spin states. Our study performed for a choice of three different adatoms (Na, Cu, and Fe) shows that the nature of adatom-graphene bonding evolves from ionic to covalent in moving from an alkali metal (Na) to a transition metal (Cu or Fe). Applying an external electric field (EEF) to TLG systems with different stacking orders results in the transition between high- and low-spin states in the latter case (Cu, Fe) and induces a little of magnetism in the former (Na) without magnetism in the absence of an external electric field. Our study would be useful for controlled adatom magnetism and (organic) spintronic applications in nanotechnology.

The aim of the current work was to develop generic sustained-release tablets containing 35 mg trimetazidine dihydrochloride and to establish an in vitro–in vivo correlation that could predict the bioavailability. The marketed sustained release tablet (Vastarel MR) used as reference, a sustained-release matrix tablet was prepared using hydroxypropyl methylcellulose (HPMC) as matrix by wet granulation and the in vitro dissolution profiles of the self-made tablets were determined in four different dissolution media (0.1 M HCl, pH 4.5 PBS, pH 6.8 PBS and water). A higher similarity between prepared tablets and Vastarel MR was established, with similarity factor (f2) ranging from 60 to 75 in the four media. The in vivo pharmacokinetics was studied in six healthy beagles. Compared with Vastarel MR, the Cmax of self-made tablets was slightly decreased, while the Tmax and MRT0–t were slightly prolonged, but with no significant difference (P > 0.05). The average of relative bioavailability (F) was 102.52% based on AUC0–t. For log-transformed AUC0–t and Cmax, the upper confidence limit on the appropriate criterion is

Determining how to optimize a scientific and efficient farmland nitrogen (N) fertilizer schedule by combining existing technology is currently a hot topic. Maize is one of the major crops in China, and enhancing the yield of maize is conducive to ensuring China's food security. In this study, the central region of Jilin Province was adopted as the research object, and a three-year (2014–2016) field experiment was performed. The data from 2014 were used to calibrate the DSSAT model, and the data from 2015 were used for validation. After calibration and validation, the DSSAT model and a genetic algorithm (GA) were used to optimize the N fertilizer schedule of maize under 20 years (1973–1992) of meteorological data for Changchun. The experimental data from 2016 were used to validate the results of the optimized N fertilizer schedule. As revealed from the results, the DSSAT model effectively simulated the growth and development of maize under drip irrigation and rain-fed methods in Changchun. The model was first calibrated based on the crop yield, phenological phases and soil moisture and N content data, and good agreement was achieved between the simulated and measured data in both the calibration and validation periods. In the calibration and validation periods, the normalized root mean square error (nRMSE) for grain yield was 1.45% and 1.61%, respectively. The total amount in the new N fertilizer schedule is 198 kg/ha, which is slightly higher than that in the traditional schedule (187.5 kg/ha), and the yield of maize in the proposed N fertilizer schedule was upregulated by 7–9% compared with the conventional N fertilization schedule in the experimental results for 2016. Through an analysis of economic benefits, drip irrigation is better than the rain-fed method, and the optimized N fertilization schedule will make the economic benefits more significant (8.4%–12.4% increase). Additionally, this method is easier to combine with remote sensing and weather forecasting, forming a real-time method of field management optimization schedule decision-making.

Recently, A-DA′D-A-type small molecular acceptors (SMAs) with benzo [c][1,2,5]thiadiazole (BT)-fused central cores have shown tremendous progress in organic solar cells (OSCs). In this work, two new BT-fused pentacyclic core based SMAs, namely BTT-4F and BTTCN-Cl, were designed and synthesized. Compared to BTT-4F, BTTCN-Cl not only delivers a reduced bandgap but an elevated lowest unoccupied molecular orbital (LUMO) energy level, which leads to a higher open-circuit voltage (VOC) and thus a lower energy loss in PM6:BTTCN-Cl-based device. However, PM6:BTT-4F-based OSCs achieves a significantly higher power conversion efficiency (PCE) (10.03%) than that of BTTCN-Cl-based OSCs (6.56%) due to its higher short-circuit density (JSC) and fill factor (FF). More favorable morphology accompanying with higher and more balanced hole/electron mobilities was obtained in PM6:BTT-4F active layer, which well accounts for the high PCE in BTT-4F-based OSCs.

Semitransparent solar cells not only can generate electricity but also exhibit promising application in facades and roofs of building, as well as the coatings of vehicle. Ideal semitransparent solar cells should have a high utilization efficiency of ultraviolet and near infrared photons, and maintain an appropriate balance between absorption and transparency in visible light range. Organic semiconducting materials with adjustable optical band gap own great potential in preparing highly efficient semitransparent organic solar cells (OSCs). There are great challenges in achieving semitransparent electrodes with good conductivity and high transmittance in visible light range, as well as high reflectance in ultraviolet and near infrared range. In this critical review, we summarize the recent progress of semitransparent OSCs, concentrating on organic semiconducting materials, semitransparent top electrode and device engineering. Semitransparent OSCs have attracted more and more attention due to its great potential in energy source in door, electricity-generating windows, building-integrated photovoltaics and agricultural greenhouse.

Ternary polymer solar cells (PSCs) have been widely demonstrated as an effective method to improve device performance. Meanwhile, the simple fabrication technology can be well kept with a single bulk heterojunction active layer, which is beneficial to the potential industrialization of PSCs. The photovoltaic parameters, such as short-circuit current density, open-circuit voltage, and fill factor, of ternary PSCs can be simultaneously improved by appropriately incorporating the third component, resulting in the increased power conversion efficiency (PCE) compared with the corresponding binary PSCs. To date, the PCE of ternary PSCs has exceeded 17% with the development of effective donors and non-fullerene acceptors. The fundamental designing rules of ternary PSCs are summarized to give some available guidelines for material selection. Next, the recent progress of efficient ternary PSCs based on various types is investigated. Then, some methods are introduced to investigate the working mechanisms of ternary PSCs. At length, the perspective toward the future development of ternary PSCs is discussed.

Solution processed interfacial layers are commonly employed in bulk heterojunction organic solar cells (OSCs) for better charge collection. PDIN interfacial layers were prepared by employing a static or dynamic spin coating method from PDIN methanol solution, and defined as the S-PDIN or D-PDIN layer. The OSCs with a S-PDIN layer exhibit 13.88% power conversion efficiency (PCE) with a virtual high short circuit density (JSC) of 26.45 mA cm-2 and relatively low fill factor (FF) of 58.94% during the current density versus voltage (J-V) measurement without a shadow mask. 12.56% PCE is achieved for OSCs with a D-PDIN layer, along with a JSC of 18.85 mA cm-2 and FF of 74.88%. Over 77% FFs are obtained for OSCs with a S-PDIN or D-PDIN layer during J-V measurement with a shadow mask, and both OSCs exhibit a very similar JSC and PCE. The virtual high JSCs and relatively low FF of OSCs with a S-PDIN layer may be due to the enhanced conductivity of PEDOT:PSS during preparation of the PDIN layer by the SSC method, which can be further confirmed from the OSCs with a methanol treated PEDOT:PSS layer. This work indicates that a well-balanced JSC and FF should be an important evaluating indicator for efficient OSCs, and an appropriate shadow mask is necessary to measure the J-V curves of OSCs with a solution processed interfacial layer.

Phosphorus is a major cause of lake eutrophication. Understanding the characteristics regarding the release of phosphorus from sediments under hydrodynamic conditions is critical for the regulation of lake water quality. In this work, the effects of sediment suspension on the release characteristics of phosphorus from sediment were investigated under different hydrodynamic conditions. The experimental results showed that in the experimental process, the phosphorus was at first released quickly into the overlying water but then slowed down. Furthermore, the process of dissolved phosphorus (DP) release under hydrodynamic conditions with and without sediment suspension was simulated using a lattice Boltzmann method. The simulation showed satisfying results.

Predicting the popularity of online content on social platforms is an important task for both researchers and practitioners. Previous methods mainly leverage demographics, temporal and structural patterns of early adopters for popularity prediction. However, most existing methods are less effective to precisely capture the cascading effect in information diffusion, in which early adopters try to activate potential users along the underlying network. In this paper, we consider the problem of network-aware popularity prediction, leveraging both early adopters and social networks for popularity prediction. We propose to capture the cascading effect explicitly, modeling the activation state of a target user given the activation state and influence of his/her neighbors. To achieve this goal, we propose a novel method, namely CoupledGNN, which uses two coupled graph neural networks to capture the interplay between node activation states and the spread of influence. By stacking graph neural network layers, our proposed method naturally captures the cascading effect along the network in a successive manner. Experiments conducted on both synthetic and real-world Sina Weibo datasets demonstrate that our method significantly outperforms the state-of-the-art methods for popularity prediction.

Ternary strategy has been confirmed as an efficient method to improve the power conversion efficiency (PCE) of organic photovoltaics (OPVs). The 15.7% PCE is achieved from PM6:Y6 based binary OPVs. One nonfullerene acceptor Br-ITIC and fullerene derivative PC71BM are selected as the third component on the basis of efficient binary OPVs, respectively. The optimized ternary OPVs exhibit 16.4% and 16.2% PCE with Br-ITIC and PC71BM as the third component, respectively, corresponding to the short circuit current density (JSC) of 25.5 mA cm−2 vs. 25.6 mA cm−2, open circuit voltage (VOC) of 0.854 V vs. 0.836 V and fill factor (FF) of 75.1% vs. 75.6%. The advantage on photovoltaic parameters of two ternary OPVs may be recombined into one cell by employing PC71BM as the fourth component. A 16.8% PCE is achieved from the optimized quaternary OPVs, resulting from the further increased JSC of 25.8 mA cm−2 and FF of 76.4% compared with the optimized ternary OPVs. The third party certificated PCE of quaternary OPVs is 16.2%. In comparison to 15.7% PCE of the binary OPVs, about 4.5% and 7.0% PCE improvement are step-by-step achieved from the optimized ternary and quaternary OPVs, respectively. Multi-components strategy may provide enough room to achieve highly efficient OPVs.

Community detection or graph clustering is crucial to understanding the structure of complex networks and extracting relevant knowledge from networked data. Latent factor model, e.g., non-negative matrix factorization and mixed membership block model, is one of the most successful methods for community detection. Latent factor models for community detection aim to find a distributed and generally low-dimensional representation, or coding, that captures the structural regularity of network and reflects the community membership of nodes. Existing latent factor models are mainly based on reconstructing a network from the representation of its nodes, namely network decoder, while constraining the representation to have certain desirable properties. These methods, however, lack an encoder that transforms nodes into their representation. Consequently, they fail to give a clear explanation about the meaning of a community and suffer from undesired computational problems. In this paper, we propose a non-negative symmetric encoder-decoder approach for community detection. By explicitly integrating a decoder and an encoder into a unified loss function, the proposed approach achieves better performance over state-of-the-art latent factor models for community detection task. Moreover, different from existing methods that explicitly impose the sparsity constraint on the representation of nodes, the proposed approach implicitly achieves the sparsity of node representation through its symmetric and non-negative properties, making the optimization much easier than competing methods based on sparse matrix factorization.

An ability of modeling and predicting the cascades of resharing is crucial to understanding information propagation and to launching campaign of viral marketing. Conventional methods for cascade prediction heavily depend on the hypothesis of diffusion models, e.g., independent cascade model and linear threshold model. Recently, researchers attempt to circumvent the problem of cascade prediction using sequential models (e.g., recurrent neural network, namely RNN) that do not require knowing the underlying diffusion model. Existing sequential models employ a chain structure to capture the memory effect. However, for cascade prediction, each cascade generally corresponds to a diffusion tree, causing cross-dependence in cascade---one sharing behavior could be triggered by its non-immediate predecessor in the memory chain. In this paper, we propose to an attention-based RNN to capture the cross-dependence in cascade. Furthermore, we introduce a \emph{coverage} strategy to combat the misallocation of attention caused by the memoryless of traditional attention mechanism. Extensive experiments on both synthetic and real world datasets demonstrate the proposed models outperform state-of-the-art models at both cascade prediction and inferring diffusion tree.

Small molecules organic photovoltaics (SMPVs) were prepared with DR3TSBDT as donor, narrow band gap material Y6 and broad band gap material PC71BM as acceptor. The Y6 based binary SMPVs exhibit a power conversion efficiency (PCE) of 10.53%, with short-circuit current density (JSC) of 21.67 mA cm−2, open-circuit voltage (VOC) of 0.879 V and fill factor (FF) of 55.21%. A 12.84% PCE is achieved from the optimized ternary SMPVs with 40 wt% PC71BM in acceptors, which is attributed to the enhanced JSC of 22.19 mA cm−2 and FF of 67.27% resulting from the well-optimized phase separation with PC71BM as morphology regulator. Hollow spherical structure of PC71BM with high electron mobility may connect Y6 molecules to form the more continuous electron transport channels in ternary active layers. Meanwhile, DR3TSBDT molecular arrangement can be markedly adjusted by incorporating PC71BM to form 3D texture structure. The well-optimized phase separation degree and molecular arrangement in ternary active layers can well support the enhanced FFs of ternary SMPVs compared with that of binary SMPVs. Over 21% PCE improvement is achieved by employing ternary strategy with 40 wt% PC71BM in acceptors, the 12.84% PCE should be among the highest values of SMPVs.

Predicting the popularity of online content is highly valuable in many applications and has been studied for several years. However, existing models either work in population level---all messages are assumed to follow similar popularity dynamics, lacking flexibility to capture the intrinsic complexity of popularity dynamics, or work in individual level---the popularity dynamics of messages are independent of each other, failing to leverage other messages to improve prediction accuracy. In this paper, we propose a divide and conquer framework for popularity prediction. We first divide messages into groups, anticipating each group of messages follow similar popularity dynamics, and then, we train a group-specific model for the messages of each group. Experiments demonstrate that group-specific models improve the population-level models by about 30% and outperform state-of-the-art individual-level model.

We are now witnessing the increasing availability of event stream data, i.e., a sequence of events with each event typically being denoted by the time it occurs and its mark information (e.g., event type). A fundamental problem is to model and predict such kind of marked temporal dynamics, i.e., when the next event will take place and what its mark will be. Existing methods either predict only the mark or the time of the next event, or predict both of them, yet separately. Indeed, in marked temporal dynamics, the time and the mark of the next event are highly dependent on each other, requiring a method that could simultaneously predict both of them. To tackle this problem, in this paper, we propose to model marked temporal dynamics by using a mark-specific intensity function to explicitly capture the dependency between the mark and the time of the next event. Experiments on two datasets demonstrate that the proposed method outperforms the state-of-the-art methods at predicting marked temporal dynamics.

The goal of this study was to improve the solubility and oral bioavailability of tamibarotene by complexing it with hydroxypropyl-β-cyclodextrin (HP-β-CD). The inclusion complex of tamibarotene with hydroxypropyl-β-cyclodextrin (Am80-HP-β-CD) was prepared through a freeze-drying method at the mole ratio of 1:1 (Am80: HP-β-CD). Fourier transform infrared spectroscopy (FT-IR) and differential scanning calorimetry (DSC) indicated the formation of Am80-HP-β-CD. In vitro dissolution studies showed that the solubility and dissolution percentage of Am80-HP-β-CD was improved substantially compared to Am80. An improved dissolution with approximately 97% drug release in 3 min was observed, in comparison with Am80 with approximately 60% release in 45 min. In vivo studies indicated that the AUC0-∞ has increased 2.79 times and the Cmax 4.37 times after the formation of inclusion complex. The decrease of tmax indicated the Am80-HP-β-CD inclusion complex can be absorbed into blood faster. In short, the solubility and bio-availability of Am80 has notably increased with the complexation of HP-β-CD. Therefore, using the inclusion technique is a promising method to improve the solubility of insoluble drugs.

Modeling and predicting retweeting dynamics in social media has important implications to an array of applications. Existing models either fail to model the triggering effect of retweeting dynamics, e.g., the model based on reinforced Poisson process, or are hard to be trained using only the retweeting dynamics of individual tweet, e.g., the model based on self-exciting Hawkes process. In this paper, motivated by the observation that each retweeting dynamics is generally dominated by a handful of key nodes that separately trigger a high number of retweets, we propose a mixture process to model and predict retweeting dynamics, with each subprocess capturing the retweeting dynamics initiated by a key node. Experiments demonstrate that the proposed model outperforms the state-of-the-art model.