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Online identification of time-variant parameters without knowledge of external loads is an important but challenging task for structural health monitoring and vibration control. In this study, a two-stage approach, named extended Kalman filter with forgetting factor matrix under unknown inputs (EKF-FFM-UI), is proposed for simultaneously identifying the time-variant parameters and external loads. In stage 1, an extended Kalman filter under unknown inputs (EKF-UI) approach previously proposed by the authors is employed for estimating the structural states and unknown loads. This EKF-UI approach is solely suitable for time-invariant system identification. Therefore, the aim of stage 2 is to improve this approach for the purpose of possessing tracking capability. In this stage, the acceleration responses are first reconstructed by using the differential equation of motion and employed for improving the accuracy of estimated structural states. A forgetting factor matrix is introduced into the priori estimation error covariance matrix to track time-varying parameters. The square errors between the measurements and the corresponding estimates are defined as an index and used for detecting the damage time instant. Then, a covariance resetting technique is employed to assure that such changes in structural parameters can be efficiently captured. A shear-type building structure without/with magneto-rheological (MR) dampers and a fixed beam structure are used as numerical examples for validating the effectiveness of the proposed approach. Experimental tests on a six-story building model are also conducted. Results show the time-varying parameters and unknown inputs can be simultaneously identified with acceptable accuracy. [ABSTRACT FROM AUTHOR]

Knowledge graph completion is an important technology for supplementing knowledge graphs and improving data quality. However, the existing knowledge graph completion methods ignore the features of triple relations, and the introduced entity description texts are long and redundant. To address these problems, this study proposes a multi-task learning and improved TextRank for knowledge graph completion (MIT-KGC) model. The key contexts are first extracted from redundant entity descriptions using the improved TextRank algorithm. Then, a lite bidirectional encoder representations from transformers (ALBERT) is used as the text encoder to reduce the parameters of the model. Subsequently, the multi-task learning method is utilized to fine-tune the model by effectively integrating the entity and relation features. Based on the datasets of WN18RR, FB15k-237, and DBpedia50k, experiments were conducted with the proposed model and the results showed that, compared with traditional methods, the mean rank (MR), top 10 hit ratio (Hit@10), and top three hit ratio (Hit@3) were enhanced by 38, 1.3%, and 1.9%, respectively, on WN18RR. Additionally, the MR and Hit@10 were increased by 23 and 0.7%, respectively, on FB15k-237. The model also improved the Hit@3 and the top one hit ratio (Hit@1) by 3.1% and 1.5% on the dataset DBpedia50k, respectively, verifying the validity of the model. [ABSTRACT FROM AUTHOR]

• An AEKF-UM approach is proposed for identifying time-variant parameters with unknown mass distribution. • A real-time updating procedure is presented for improving the process and measurement noise covariance matrices. • An index is defined basing on dramatic increase of measurement noise covariance for damage instant detection. • The covariance resetting technique is used to enhance the tracking capability for effectively capturing the time-varying parameters. Although the extended Kalman filter (EKF) provides a promising way for structural state estimation, it cannot effectively track time-varying parameters online. Besides, the structural mass distribution is usually assumed to be known in advance for many EKF-based methods, limiting their applications. In this paper, by using limited observations, an adaptive EKF with unknown mass coefficients (AEKF-UM) approach is proposed for the identification of time-variant parameters and mass distribution at the same time. A real-time updating procedure is presented for improving the process and measurement noise covariance matrices at each time step to assure the stability and accuracy of convergence results. Based on the dramatic increase of measurement noise covariance, an index is defined for determining the damage instant. A covariance resetting technique is then used to enhance the tracking capability for the purpose of effectively capturing the time-varying parameters. The unknown mass coefficients can be estimated at the same time by adding them into the extended state vector. To validate the effectiveness of the proposed approach, two numerical cases are considered, i.e. (i) the Phase I ASCE structural health monitoring benchmark building structure, and (ii) a four-story nonlinear structure equipped with a magneto-rheological (MR) damper. Experimental tests on a four-story building model subject to base excitation are also conducted to investigate the performance of the proposed approach. Results show that the proposed approach is capable of satisfactorily tracking abrupt changes of stiffness parameters with unknown mass distributions. [ABSTRACT FROM AUTHOR]

The development of graphene oxide/rare earth complexes luminescent materials is limited due to the strong quenching ability of graphene oxide. However, the hybrid materials with pyromellitic acid (PMA) as ligand not only have better performance, but also have stronger luminescence intensity. Herein we tested the effect of the carboxylic acid structure of PMA on the luminescence intensity of graphene oxide/rare earth complexes hybrid materials. Phthalic acid (PA), Isophthalic acid (i-PA) and Terephthalic acid (p-PA) are selected as test ligand, representing the o-position, meta-position and para-position effects of PMA. By comparing the luminescence intensity, we found that o-position effect is helpful for the ligand to sensitize rare earth ions, and meta-position and para-position effects are helpful for the graphene oxide sheets (GOSs) to improve the luminescence intensity of hybrid materials and inhibit the quenching effect of the GOSs. Furthermore, we speculate on the relationship between the distance of π–π stacking of GOSs and rare earth complexes and luminescence intensity of hybrid materials. This work provides an important reference for the design of graphene oxide/rare-earth aromatic carboxylic acid hybrid luminescent materials. [ABSTRACT FROM AUTHOR]

Terbium(III)-functionalized zirconium-based MOFs (Tb3+@UIO-67) were synthesized by doping Tb3+ into UIO-67 using a post-synthetic modification. The Tb3+@UIO-67 (solid or aqueous dispersion) shows only blue fluorescence (emission peaks at 420 nm) under an ultraviolet lamp (254 nm). Upon addition of 2,6-pyridinedicarboxylic acid (DPA; an anthrax biomarker), the color of the Tb3+@UIO-67 aqueous dispersion under an ultraviolet lamp changes from blue to green. This is mainly because DPA has a good sensitization effect on Tb3+. DPA can be determined by measurement of the ratio of the fluorescence intensities at 544 nm and 420 nm (excitation at 278 nm). The method allows DPA to be detected in the 0.3 to 6 μM concentration range, with a detection limit of 36 nM. [ABSTRACT FROM AUTHOR]

The identification of parameters of linear or nonlinear systems under unknown inputs and limited outputs is an important but still challenging topic in the context of structural health monitoring. Time-domain analysis methodologies, such as extend Kalman filter (EKF), have been actively studied and shown to be powerful for parameter identification. However, the conventional EKF is not applicable when the input is unknown or unmeasured. In this paper, by introducing a projection matrix in the observation equation, a time-domain EKF-based approach is proposed for the simultaneous identification of structural parameters and the unknown excitations with limited outputs. A revised version of observation equation is presented. The unknown inputs are identified using the least squares estimation based on the limited observations and the estimated structural parameters at the current time step. Particularly, an analytical recursive solution is derived. The accuracy and effectiveness of the proposed approach is first demonstrated via several numerical examples. Then it was validated by the shaking table tests on a five-story building model for the robustness in application to real structures. The results show that the proposed approach can satisfactorily identify the parameters of linear or nonlinear structures under unknown inputs. [ABSTRACT FROM AUTHOR]

This paper develops a strategy for assisting two players in allocating multiple resources in a strategic sequential game. The defender first needs to allocate deception and defense efforts among targets to deceive the attacker and strengthen the target, respectively. Then, the attacker chooses a type of threat and a target to attack. The defender aims at mitigating the possible damage to the targets, whereas the attacker strives to cause maximum damage to the targets. Traditional modeling approaches typically focus only on the defender's homogeneous resource in defense and are not well suited to effectively capture the complex interplay between players. Given scarce resources, a game‐theoretic model is proposed for determining optimal strategies for both players. The key novel features of this model include: (1) the attacker's learning and the defender's counter‐learning efforts are considered; (2) trade‐offs between deception and defense efforts among different targets for the defender are investigated; and (3) sensitive analysis is carried out to see how different parameters can affect the equilibrium results. An illustrative example is presented to demonstrate the procedure of this game‐theoretic model and show its effectiveness. The results can provide additional insights for defense and deception strategies. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • L-Tryptophan functionalized graphene quantum dots were prepared via a thermal cracking method. • Doping of L-Tryptophan effectively improves the luminescent properties of GQDs. • This quantum dots exhibit a good liner relationship between fluorescence response and pH variation of 4–12. • This quantum dots perform well in sensitivity to pH values in real water samples. Abstract L-Tryptophan (Trp) functionalized graphene quantum dots (Trp-GQDs) were prepared via a thermal cracking method, using Trp and citric acid (CA) as raw material. The as-obtained Trp-GQDs show stronger blue photoluminescence (PL) than simple graphene quantum dots (GQDs). The presence of Trp can obviously improve the luminescent properties of GQDs. The possible mechanism was investigated for the formation and luminescence properties of the Trp-GQDs. Furthermore, the Trp-GQDs exhibit a good liner relationship between fluorescence response and pH variation within the pH range of 4–12. More importantly, Trp-GQDs still perform well in sensitivity to pH values in real water samples. The results indicate that the probe shows great potential in pH detection. [ABSTRACT FROM AUTHOR]

Graphene oxide sheet-modified zinc complexes named Zn-PMA/GOSs have been synthesized based on the non-covalent interactions of Zn-PMA and graphene oxide sheets (GOSs) via an in situ reaction. Then, the as-synthesized products are characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), thermogravimetric analysis (TGA) and fluorescence spectroscopy. Zn-PMA/GOSs not only show strong luminescence intensity and better thermal stability than pure zinc complexes but also have good dispersibility in aqueous solutions, and they are further used as fluorescence probes for detecting Fe3+. They show relative selectivity and high sensitivity to Fe3+ (Stern–Volmer constant KSV = 4 × 106 L mol−1), suggesting that Zn-PMA/GOSs can be a promising luminescent probe for selectively sensing Fe3+ ions. Moreover, the possible mechanisms of ion-selective detection are also discussed. [ABSTRACT FROM AUTHOR]

In this paper, a novel modified graphene oxide sheets (GOSs) has been synthesized based on pyromellitic acid (PMA) depositing on the surface of GOSs via noncovalent approach. Fourier Transform Infrared spectra (FT-IR), X-ray diffraction patterns (XRD) and scanning electron microscopy (SEM) were adopted to investigate its structure. The as-prepared materials are dispersed in Rhodamine-B (RB) solutions which show highly efficient fluorescence. This phenomenon suggests the quenching effect of graphene oxide can be effectively weakened via rational structural modification. Moreover, this dispersion serving as a fluorescent probe still has a relatively high selectivity and sensitivity (Stern-Volmer constant K SV = 4.58*10 4  L mol −1 ) to Fe 3+ ions. [ABSTRACT FROM AUTHOR]

It is a huge challenge to synthesize high luminescent performance of graphene oxide-rare earth hybrid materials, due to the strong quenching effect of graphene oxide. Herein we reveal a novel graphene oxide/rare-earth complexes hybrid materials that the Eu 3+ -2-thenoyltrifluoroacetone (TTA)-pyromellitic acids (PMA) were deposited on the surface of graphene oxide sheets (GOSs) via noncovalent approach between GOSs and PMA. This materials exhibit stronger luminescence intensity, longer decay lifetime and better thermal stability than pure Eu 3+ complexes. It is confirmed by Fourier transform infrared spectroscopy, scanning electron microscopy, X-ray diffraction and luminescent data. Moreover, we observed PMA plays a significant role in improving the luminescence intensity and prolonging the decay lifetime of hybrid materials. [ABSTRACT FROM AUTHOR]

In this study, a new method is proposed to address group decision making (GDM) using incomplete reciprocal preference relations (RPRs). More specifically, the multiplicative transitivity property of RPRs is first used to estimate missing values and measure the consistency of preferences provided by experts. Following this, experts are assigned weights by combining consistency weights and trust weights. The former are derived by conducting a multiplicative consistency analysis of the opinions of each expert, whereas the latter are used to measure the degree of trust in an expert harbored by others. Experts with satisfactory consistency and large trust weights should typically be assigned large weights. The consensus level is then checked to determine whether the decision making process moves forward to the selection process. If it is negative, a hybrid method consisting of delegation and feedback mechanisms is used to improve the process of arriving at a consensus. The delegation occurs when some experts decide to leave the process, which is common in GDM involving large numbers of participants. The feedback mechanism, one of the main novelties of the proposed approach, generates different advice for experts based on their consistency and trust weights. Finally, a numerical example was studied to show the practicality and efficiency of the proposed method, and the results indicated that it can provide useful insights into the GDM process. [ABSTRACT FROM AUTHOR]

• We study a sequential defender-attacker game; • Multiple strategies and targets are considered; • Learning and counter-learning behaviors are modeled; • The interaction between targets resulting in additional utility is allowed; • Comparative studies are implemented to see how parameters affect the equilibrium. Appropriate resource allocation among multiple targets plays a vital role in the defender-attacker game. Traditional methods seldom consider the optimal resource allocation with more than one strategy among multiple targets. Accordingly, we assume that the defender moves first, allocating resources in deploying different false targets and strengthening the genuine ones among multiple targets. The attacker moves after observing the defender's move, distributing resources in identifying false targets and then attacking the genuine ones concerning multiple targets. Each player aims to maximize their own overall expected utility given any of the other player's move. The optimal resource distribution between target intelligence/protection for the defender and target identification/attack efforts among multiple targets for the attacker is studied. We model and obtain analytical equilibrium results under various parameter settings. Our results show that increased intelligence (impact) contest intensities lead to lower (higher) attacker resources in intelligence (attack). Moreover, the zero-sum game where both players share the same preferences without additional payoff consideration results in the worst losses for the defender. The forgoing method offers an original way to approach the resource allocation problems in security defense fields. [ABSTRACT FROM AUTHOR]

NaYF 4 :Yb, Er with nitrogen-doped graphene quantum dots (N-GQDs) mixture was synthesized by a simple one-pot hydrothermal method. The as-obtained mixture shows green color under the irradiation of infrared light (980 nm), and exhibits blue color by means of ultraviolet excitation (365 nm). The luminescence of NaYF 4 :Yb, Er and N-GQDs are not affected by each other. And the synthesized mixture directly incorporated into a polyvinyl alcohol (PVA) matrix can obtain a transparent luminescent film. The luminescent film also shows different luminescent colors under different light irradiation (980 nm or 365 nm). This result indicates that it has a potential application value in anti-counterfeiting packaging. • The NaYF 4 :Yb, Er with N-GQDs mixture was synthesized by a one-pot hydrothermal method. • The obtained material exhibits shows green color under 980 nm and blue color under 365 nm. • A polymer luminescent film was synthesized by self-assembly of the mixture and PVA. • The obtained film has a potential application value in anti-counterfeiting packaging. [ABSTRACT FROM AUTHOR]

The compound Zn(L 1) 2 (L 2) phosphor with yellow light under blue-light excitation has great potential application in the field of white-light-emitting diodes. • A novel compound Zn(L 1) 2 (L 2) was prepared by simple one pot method. • Single crystal X-ray diffraction of Zn(L 1) 2 (L 2) is illustrated. • The optimal excitation and emission wavelengths of Zn(L 1) 2 (L 2) are 467 nm and 574 nm. • The compound Zn(L 1) 2 (L 2) exhibits potential application in white-LED. In this paper, a novel Zn(L 1) 2 (L 2) phosphor with yellow light under blue-light excitation was synthesized using simple one pot method by introducing the second ligand 4-dimethylaminopyridine (L 2) to the reaction that uses 5-chloro-8-hydroxyquinoline (L 1) and zinc acetate to prepare the coordination compound Zn(L 1) 2. The structure of Zn(L 1) 2 (L 2) was determined with single crystal X-ray diffraction techniques. Besides, the compounds Zn(L 1) 2 and Zn(L 1) 2 (L 2) were characterized by Fourier transform infrared spectroscopy (FT-IR), powder X-ray diffraction (PXRD), fluorescence spectroscopy, and thermo-gravimetric analysis (TGA). Compared with the compound Zn(L 1) 2 , the optimal excitation and emission wavelengths of the compound Zn(L 1) 2 (L 2) have red-shifted, with the excitation wavelength of 467 nm and the emission wavelength of 574 nm. The special luminescent properties and simple synthesis method of the Zn(L 1) 2 (L 2) make it become a promising candidate in the field of white-light-emitting diodes. [ABSTRACT FROM AUTHOR]

The ammonia sensors, achieving fluorescence quenching and fluorescence recovery of the hydrogels in ammonia atmosphere, take advantage of the limited coordination between Eu3+ and salicylic acid in hydrogel environment and it achieve the fluorescence self-recovery at room temperature. • The rapid excited intramolecular proton transfer of salicylic acid is suppressed in the Eu(Sal) 3 complexes and the ammonia affect the energy transfer from ligand to rare earths ions. • The lanthanide complexes and functional group of hydrogels have different competitive coordination ability in hydrogels system. • The EuL n -Fm/PVA hydrogels achieve diverse responses for the ammonia gas. Herein, we report an ammonia-responsive of lanthanide (Eu(Sal) 3 , Sal = salicylic acid) complexes hydrogel sensors based on the amine molecule affecting the energy transfer process. In this system, the ammonia stimulation causes the coordination and decomposition of Eu(Sal) 3 in the hydrogel, thus leading the fluorescence quenching and recovery of Sal in the ammonia atmosphere. Furthermore, the EuL n -Fm/PVA hydrogel composed of Eu(Sal) 3 and Eu(TTA) 3 complexes (TTA = 2-Thenoyltrifluoroacetone, L = Sal and TTA, Fm = formamide, n = 1-3) was prepared by an one-pot process, which achieves the continuous detection for ammonia gas. Meanwhile, EuL n -Fm/PVA hydrogel also achieved diverse responses for ammonia gas. This device could be a promising strategy for developing fluorescence hydrogels with potential applications due to its desirable advantages such as simple preparation, cost-effectiveness, etc.. [ABSTRACT FROM AUTHOR]

Usage of false targets has proven to be an effective way to enhance the survivability of a genuine target in a defender–attacker game. Time, as an important factor, however, is seldom taken into account in the existing game theoretic models. This paper studies the complex interplay between two players and analyzes the equilibrium strategies and payoffs under various situations. In particular, both players make a simultaneous move at certain time points. The attacker chooses to either learn or attack whereas the defender chooses to either strengthen the genuine target or deploy more false targets. If learning behavior is chosen, the state of the system changes and the game continues. If attacking behavior is chosen, the game ends with probabilistic payoffs. We carry out experiments and obtain the corresponding equilibrium results (i.e. the optimal number of false targets for the defender and the optimal attack time for the attacker) under different learning and contest intensities. It shows that under certain conditions (high attacker resource, low learning intensity) the defender benefits from deploying more false targets with greater probabilities, whereas the attacker benefits from learning fewer targets and attacking earlier with greater probabilities with low resource, or high learning intensity. The results shed light on making enhanced decisions in terms of defense and deception strategies. • We study a strategic defender–attacker game using false targets. • Time is considered as an important factor in the process. • Learning and counter-learning behaviors are modeled. • Comparative studies are implemented to see how parameters affect the equilibrium. [ABSTRACT FROM AUTHOR]

In this work, a framework is provided for identifying intracranial electroencephalography (iEEG) seizures based on discrete wavelet transform (DWT) analysis of iEEG signals using forward propagation and feedback neural networks. The performance of 5 different data sets combination classifications is studied using the probabilistic neural network (PNN), learning vector quantization neural network (LVQ) and Elman neural network (ENN). Different feature combinations serve as the input vectors of the classifiers to obtain the best outcomes. It has been found that PNN has less running time and provides better classification accuracy (CA) than ENN and LVQ classifiers for all 5 classification problems. It is worth noticing that the CA for the C-D classification task, which shows the status of pre-ictal versus post-ictal, has been greatly improved, and reached 83.13%. Hence, the epilepsy iEEG signals pattern recognition based on DWT statistical features using the PNN classifier is more suitable for forming a reliable, automatic classification system in order to assist doctors in diagnosis. [ABSTRACT FROM AUTHOR]

• The NaYF 4 :Ln/NaYF 4 :Eu composite possesses up-conversion and down-shifting luminescence properties. • The composite possesses excellent compatibility and fluorescence purity. • They can be prepared into fluorescent patterns and provide a potentiality for anti-counterfeiting. Herein, a series of novel dual-mode NaYF 4 :Ln/NaYF 4 :Eu (Ln = Yb, Er, Tm) composites involving up-conversion and down-shifting luminescence have been prepared by a facile synthetic method. X-ray diffraction, scanning electron microscopy, transmission electron microscopy, energy dispersive X-ray analysis, up-conversion and down-shifting fluorescence spectrometer were used to characterize the materials. By doping different lanthanide ions and tailoring the molar ratio of the doped lanthanide ions, three kinds of composites were obtained which could exhibit three-primary-color (red-green-blue, abbreviating as RGB) up-conversion luminescence under the irradiation of 980 nm laser, and generate red down-shifting color under the excitation of 393 nm. The composites show excellent photoluminescence properties, which attribute to NaYF 4 served as a major matrix for both the up-conversion and down-shifting materials. Moreover, the work provides a promising material for anti-counterfeiting application. [ABSTRACT FROM AUTHOR]

In this paper, a graphene oxide/rare-earth complexes hybrid material without 1,10-Phenanthroline based on 4′-paraphenyl-carboxyl-2,2':6′,2″-terpyridine (Hcptpy) as ligand, graphene oxide sheets (GOSs) as inorganic matrix and europium ion as luminescence center has been synthesized via non-covalent approach between GOSs and Hcptpy. This obtained hybrid material exhibits stronger luminescence intensity, better thermal stability and longer decay lifetime than pure Eu3+ complexes. Moreover, a transparent and strongly luminescent thin film also is prepared by self-assembly at room temperature. This thin film shows great potential applications in the area of optics. • A GOSs/rare-earth complexes hybrid material was synthesized without Phen. • The obtained hybrid material exhibits better performance than pure Eu3+ complexes. • A polymer film was synthesized by self-assembly of Eu-Hcptpy/GOSs and PMMA. • The obtained film has excellent transmittance and luminescent properties. [ABSTRACT FROM AUTHOR]

The method to regulate the concentration of graphene oxide (GO) via changing polarity of solution was developed, then the Tb(acac)n(PMA)n/GO composites were synthesized by coordination bond. The tunable photoluminescence property is achieved under different concentration of GO dispersion. The mechanism of tunable luminescence also is elucidated in details. Simultaneously, the strong thermal stability of Tb(acac)n(PMA)n/GO complexes series is performed because of the function of PMA, which suggests potential application in optical fields such as photo-electric device. [ABSTRACT FROM AUTHOR]

We report a facile combustion method synthesis of reduced graphene oxide/CuI composites as a photocatalyst, in which CuI nanoparticles were homogeneously distributed on the surface of reduced graphene oxide (rGO), showing a good visible light response. The rGO-supported and unsupported CuI hybrids were tested over the photocatalytic reduction of CO 2 for methanol evolution in visible light. In the current study rGO-CuI composites have shown excellent yields (19.91 μmol g-cat −1 ). rGO provides a light-weight, charge complementary and two-dimensional material that interacts effectively with the CuI nanoparticles. [ABSTRACT FROM AUTHOR]

It has been proved that the usage of multi-type observations including global and local information for structural health monitoring (SHM) outperforms that of solo-type measurement. Kalman filter (KF) is a simple but powerful tool for the online state estimation. However, external force is required for the classic KF. Moreover, direct implementation of KF in time domain may be time consuming especially for large structures with many degrees-of-freedoms (DOFs) involved. From these points of view, the idea of modal Kalman filter (MKF) is introduced. An MKF-based approach is then proposed for joint estimation of multi-scale responses and unknown loadings with data fusion of multi-type observations. By using a projection matrix and the selected several modes, a modified observation equation in modal domain is derived. Limited multi-type measurements are fused together for online estimating multi-scale responses of structure at its critical locations. The unknown excitation is simultaneously identified by least squares estimation (LSE). The drift problem of the real time estimation of structural responses and unknown loads is avoided. The effectiveness of the proposed approach is numerically demonstrated via several examples. Results show that the proposed approach is capable of satisfactorily estimating the unmeasured multi-scale responses and identifying the unknown loadings. [ABSTRACT FROM AUTHOR]

Background: An emergency response to a medical situation is generally considered to be a risk decision-making problem. When an emergency event occurs, it makes sense to take into account more than one decision maker's opinions and psychological behaviors. The existing research tends to ignore these multidimensional aspects. To fill this literature gap, we propose a multi-attribute model.Methods: The model is based on cumulative prospect theory (CPT), considering multiple experts' psychological factors. By not assuming full rationality, we extend existing models to allow multiple experts' risk preferences to be incorporated into the decision-making process in the case of an emergency. Then, traditional CPT is extended by allowing for multiple attributes. In addition, rather than using crisp data, interval values are adopted to tackle the usual uncertainties in reality.Results: The multi-attribute CPT based model proposed can deal with the selection of potential emergency alternatives. The model incorporates interval values to allow more uncertainty and the comparative studies show that the optimal solution changes under different scenarios.Conclusions: Our illustrative example and comparative study show that considering multiple experts and multiple attributes is more reasonable, especially in complicated situations under an emergency. In addition, decision-makers' risk preferences highly affect the selection outcomes, highlighting their importance in the medical decision-making process. Our proposed model can be applied to similar fields with appropriate modifications. [ABSTRACT FROM AUTHOR]

• O 2 can improve GFA of P-containing Fe-based BMGs while fails for FeCoBSiNb alloy. • Surface composition of P-containing Fe-based varied much with casting atmospheres. • P segregation takes place for P-containing Fe-based liquids during melting process. • P segregation leads to the crystallization start in surface rather than in center. • Enhancement of GFA by oxidizing atmosphere was ascribed to elimination of P element. Generally, amorphous alloys are fabricated in an inert atmosphere—Ar to avoid crystallization and gain high glass forming ability (GFA). In this work, the effect of non-inert casting atmospheres (N 2 , air and O 2) on the GFA of Fe 76 Si 9 B 10 P 5 , Fe 76 Si 8 B 10 P 5 Mo 1 , Fe 77 Mo 2 P 10 C 4 B 4 Si 3 and [(Fe 0.8 Co 0.2) 0.75 B 0.2 Si 0.05 ] 96 Nb 4 soft magnetic bulk metallic glasses (BMGs) was systematically investigated. Surprisingly, contrary to existing experience, while the GFA of [(Fe 0.8 Co 0.2) 0.75 B 0.2 Si 0.05 ] 96 Nb 4 alloy remains the same as cast in Ar, it was found that the non-inert casting atmospheres can dramatically improve the GFA of P-containing Fe-based BMGs, especially in oxidizing casting atmosphere, with no influence in their thermal properties and magnetic properties. The results also indicated the surface composition of the P-containing Fe-based BMGs varied much with the casting atmospheres whilst the bulk composition remain unchanged. Moreover, plausible reasons were eliminated and underlying mechanism was elucidated. The decreased surface tension resulted from the segregation of P element of the P-containing Fe-based liquids during the melting process leads to the crystallization occurring in the surface layer rather than in the central area. At last, the enhancement of GFA by non-inert casting atmospheres were mainly ascribed to the increased surface tension resulting from the elimination of oxygen element for the oxidizing (air and O 2) atmosphere and the alloying effect of nitrogen element for the N 2 atmosphere, respectively. The new understanding about the non-inert atmosphere and metallic amorphous formation is expected to benefit the composition design of amorphous materials with better GFA and advances in the manufacture of amorphous alloys. [ABSTRACT FROM AUTHOR]

The cylindrical saddle-shaped gradient coils are essential components for micro comagnetometers, generating gradient magnetic fields perpendicular to the symmetry axis. The aspect ratios of the coils limit the miniaturization of comagnetometers. A hybrid design method for small-volume saddle-shaped transverse gradient coils is proposed in this paper. The derivatives of the gradient fields generated by saddle-shaped gradient coils at the isocenter of the coils are provided innovatively, and combined with volume constraints and relative errors along the x-axis as the fitness function. The structural parameters are obtained through a PSO (Particle Swarm Optimization) algorithm with exponential adaptive inertia weights. The aspect ratios of the optimized coils are reduced by 61.01% (dB z /dx coil) and 12.24% (dB x /dx coil), while the relative magnetic field errors in the volume of interest are reduced by 88.39% (dB z /dx coil) and 29.46% (dB x /dx coil), respectively. Experimental results verify the validity of the proposed method. As a result, the magnetic compensation from optimized transverse gradient coils (dB z /dx) in the Rb-Xe comagnetometers increases the transverse relaxation time of 129Xe by more than 12%. [Display omitted] • The proposed optimization method effectively improves the linearity of gradient fields within the volume of interest. • The proposed optimization method polishes up its convergence accuracy through the improved intelligent algorithm. • The optimized saddle-shaped gradient coils reduce the aspect ratios effectively, compared with original design. • The applications of transverse gradient coils in Rb-Xe comagnetometers increase the transverse relaxation time of 129Xe. [ABSTRACT FROM AUTHOR]

The innate immune system plays a critical role in the host response against pathogenic microbial infection. However, aberrant activation of the innate immune pathways is a characteristic feature of various diseases. Thus, targeted drugs must be developed based on the understanding of the innate immune signaling pathways. This study demonstrated that an allene small molecule (DWL-4-140) can efficiently and selectively exert regulatory effects on the stimulator of interferon genes (STING), resulting in the downregulation of DNA-induced interferon responses. Mechanistically, DWL-4-140 targeted the cyclized nucleotide-binding domain (CBD) of STING, inhibiting the assembly of the STING multimeric complex and the recruitment of downstream signaling mediators. In addition to downregulating the 10-carboxymethyl-9-acridanone-induced production of inflammatory factors, DWL-4-140 alleviated the pathological features of Trex1 deletion-induced lupus in mice. Thus, this study demonstrated that DWL-4-140 pharmacologically inhibits STING with potential therapeutic applications in auto-inflammatory diseases. [Display omitted] • We prepared a novel alkene compound (DWL-4-140). • DWL-4-140 targets the CBD region of STING. • DWL-4-140 inhibits STING recruitment to TBK1. • DWL-4-140 effectively alleviates the lupus-like phenotype in Trex1 -/- mice. [ABSTRACT FROM AUTHOR]

Highly transparent ultrathin films (UTFs) were fabricated via layer-by-layer assembly of 110-Phenanthroline monohydrate (Phen)–8-hydroxyquinoline (Hq)–Al3+(Phen–Hq–Al), polyvinyl alchol(PVA) and Mg–Al-layered double hydroxide (LDH)nanosheets. UV–visible absorption and fluorescence spectroscopy showed regular growth of UTFs increasing the numbers of assembly. The structure and morphology of Mg–Al-layered double hydroxide and UTFs were measured by Fourier transform infrared spectroscopy, XRD and SEM. We found that it can detect Fe3+ ion with relative selectivity and high sensitivity (Ksv = 2.214 × 104 M−1) which indicates that UTFs can be a potential fluorescent probe for selectively of the Fe3+ ion. [ABSTRACT FROM AUTHOR]

Abstract An efficient photocatalyst consisting of nitrogen-doped graphene quantum dots (N-GQDs) dispersed on the surface of the three-dimensional hierarchical bismuth oxyhalide (BiOX, X = Br, Cl) was synthesized via a simple solvothermal method. The catalysts were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), UV–vis diffuse reflectance spectrophotometer (DRS), and photoluminescence spectroscopy (PL). The N-GQDs play an important role in the improvement of photocatalytic performance because it significantly increases BiOX absorption of visible light and effectively traps photogenerated electrons to accelerate the separation of photogenerated electron-hole pairs. The superior activity of N-GQDs/BiOX was exhibited to the organic contaminant degradation under visible light. The 7 wt% N-GQDs/BiOBr and 7 wt% N-GQDs/BiOCl exhibited strong catalytic activity, in which RhB was almost completely removed after irradiation for 60 and 75 min, respectively. In our work, we provide a strategy that for improving the photocatalytic activity of BiOX with semiconductor quantum dots. [ABSTRACT FROM AUTHOR]

To clarify the underlying mechanism of effects of P on amorphous forming ability (AFA) for Fe–Si–B–P alloy system, the AFA and melting viscosity of (Fe 76 Si 9 B 10) (100- x)/95 P x (x = 0–3) amorphous alloys measured in the temperature range of 1200–1450 °C by oscillating cup method were investigated. A viscosity hysteresis occurs at about 1350 °C between the heating and cooling processes for all alloys, and the values of viscosity almost increase as P content increases at each measured temperature under cooling process. However, only considering viscosity cannot provide a satisfactory explanation for the trend of AFA for this alloy system. Afterwards, the mechanism was well revealed by calculating the Gibbs free-energy difference and speculating the interfacial tension. In addition, a positive correlation between magnetic properties (coercivity and effective permeability) and the AFA of this alloy system was also founded, which can provide an auxiliary in understanding the mechanism of AFA to some extent. Meanwhile, when x = 3, the alloy shows excellent soft magnetic properties including low coercivity of 0.9 A/m and high effective permeability of 17,000, which is promising for future electromagnetic device application. • The viscosity of FeSiBP alloys presents a increase trend with P content rising. • The free-energy difference of FeSiBP alloys decreases as increasing P content. • Correlation among the AFA, viscosity and free-energy difference was established. • A minimum H c of 0.9 A/m and a maximum μ e of 17,000 was obtained. [ABSTRACT FROM AUTHOR]

Under the background of green and low-carbon economy, comprehensively analyzing the influential factors and apply them to accurately estimate energy-related CO 2 emissions make great sense for Chinese green-economy development. In this paper, the grey incidence analysis is employed to identify the influential factors that may generate strong and nonlinear effects on emissions. To consider these nonlinear effects, a new discrete grey power model is designed, through introducing grey power indexes into the model structure. Additionally, one-step ahead rolling mechanism is associated with the proposed technique so as to further improve its forecasting precision. To demonstrate its efficacy, the rolling discrete grey power model is utilized to forecast Chinese energy-related carbon emissions from 2011 to 2015, and then compared to projections provided by diversified competing techniques - the empirical applications show that the newly proposed rolling model clearly outperform other benchmark models in accordance with three measuring indices. Therefore, by using this optimum model, Chinese carbon emissions from 2016 to 2020 are quantified, which infers that it will rise to over 9936 million tons in 2020, and is consistent with those provided by other international agencies and scholars. Eventually, based on the forecasts, suggestions on reducing the CO 2 emissions are provided for decision-makers. • The influential factors of CO 2 emissions are determined by using the Grey Incidence Analysis. • A novel nonlinear discrete grey power model is designed for forecasting Chinese CO 2 emissions. • The trends of influential variables are predicted by using the rolling NOGM(1,1) model. • The future CO 2 emissions are predicted by using rolling DGPM(1,N) model from 2016 to 2020. [ABSTRACT FROM AUTHOR]