This paper examines the interplay between the information strategy of an e-commerce platform and the selling mode strategy of a manufacturer within a co-opetitive supply chain, as well as the identification of the optimal supply chain strategy. We develop a supply chain model where a platform outsources production of its private label product to a manufacturer, who also sells its national brand product through the platform. The platform must decide whether to acquire consumer quality preference information at a cost and share it with the manufacturer, while the manufacturer needs to choose between the reselling mode or the agency selling mode for its national brand product. The two driving effects (competition-intensification effect and mode differentiation effect) are identified. Our findings show that the platform will acquire and share information when the acquisition cost is sufficiently low, leading to the "competition-intensification effect." Additionally, the manufacturer prefers the agency selling mode when cost-quality efficiency is low, and the reselling mode otherwise, driven by the "mode differentiation effect." In cases where information sharing is absent, the manufacturer is more likely to choose the agency selling mode. Interestingly, when the cost-quality efficiency of the manufacturer's product is moderate and the information acquisition cost is low, the "competition-intensification effect" and the "mode differentiation effect" offset each other, resulting in the expansion of the region where the manufacturer chooses the reselling mode due to the platform's information-sharing strategy. As a result, this enhances a cooperative relationship between the manufacturer and the platform. We also derive the optimal supply chain strategy, providing insights into both the manufacturer's selling mode and the platform's information strategies in online retailing.

A carbide strengthened wrought Ni-based superalloy is developed. The alloy depends on carbide dispersion strengthening. A high deformation plasticity in homogeneous alloy is shown in the 1100-1200 degrees C isothermal compression test and the improvement of microstructure can be achieved by recrystallization. After aging at 850-900 degrees C, the carbide strengthened wrought alloy appears excellent tensile strength. Carbide exists higher microstructure stability than gamma ' in the same condition. The herein reported results reflect the potential of the economical wrought Ni-based superalloy to service above 800 degrees C.

Efficient high-dimensional performance modeling of analog/RF circuits over multiple corners is an important-yet-challenging task. In this article, we propose a novel performance modeling approach for analog/RF circuits, referred to as correlated Bayesian model fusion (C-BMF). The key idea is to encode the correlation information for both model template and coefficient magnitude among different corners by using a unified prior distribution. Next, the prior distribution is combined with a few simulation samples via Bayesian inference to efficiently determine the unknown model coefficients. Two circuit examples designed in a commercial 40-nm CMOS process demonstrate that C-BMF achieves about $2\times $ cost reduction over the traditional state-of-the-art modeling technique without surrendering any accuracy.

Superalloy that can serve above 800 degrees C is urgently needed for the development of high-performance aero-engine turbine disk. Increasing the content of gamma' phase could significantly improve high temperature machinal properties, and GH4151 alloy is the typical representative of superalloys with more gamma' phase, and its.' phase content is about 55% (mass fraction, the same below). Besides, GH4151 alloy could serve at 800 degrees C and presents a broad application prospect. However, the higher content of gamma' phase also increases the difficulty of deformation. Cogging process of the homogenized ingot is an important part in preparation of turbine discs. However, there is still a lack of systematic research on the hot deformation behavior of homogenized GH4151 alloy. Therefore, the deformation behavior of homogenized GH4151 alloy was studied by isothermal hot compression test and hot processing maps were established based on flow curves. In addition, FESEM and coupled EBSD/EDS methods were utilized to analyze deformed microstructure. Based on the results of hot processing map, the domains with good workability are 1060 similar to 1090.,0.1 similar to 0.2 s(-1) and 1060 similar to 1070.,0.1 similar to 1 s(-1). A large amount of primary gamma' phase (gamma'.) in initial structure hinders the movement of dislocations to promote recrystallization, and pins the grain boundaries to refine the grains. An increasing deformation strain contributes to a larger instability domain. The main form of GH4151 alloy deformation instability is that the tensile stress at the bulging zone of deformed sample induces cracking of grain boundary and./ gamma'. phase boundary. Increasing deformation temperature and deformation rate will promote cracking.

Designing high-performance aeroengine is important for development in the aviation industry. One of the key components is turbine disk material that can operate at 800 degrees C. Among various methods for strengthening alloys, increasing the alloying degree is important, and GH4151 is one of the typical alloys with a high alloying degree. It comprises a large number of refractory metal elements and gamma'-forming elements. OM, SEM, and JMatPro software were used to study the sensitivity of GH4151 microstructure evolution during heat treatment processes. The results show that a high alloying degree produces a complex microstructure with low-melting phases, such as Laves, gamma/gamma' eutectic, and eta phases. Due to the difference in incipient melting temperature of each precipitated phase, a three-stage heat treatment was developed to effectively eliminate the harmful phases in the alloy. The contents of segregation elements Nb and Ti in the as-cast GH4151 alloy have an obvious influence on the incipient melting temperature, whereas the effect of Mo content is relatively slight, and that of W content is not obvious. Decreasing Ti content while increasing Nb and Mo contents could reduce the incipient melting temperature of the. phase. Furthermore, increasing Ti and Mo contents while decreasing Nb content could reduce the incipient melting temperature of Laves phase. A large amount of gamma'-forming elements contributes to the cooling rate sensitivity of gamma' phase evolution. 15 degrees C/min is the critical value for the irregular growth of the gamma' phase in the GH4151 alloy. When compared to alloys with low gamma'-forming elements content, the gamma' phase in GH4151 alloy has a larger size when the cooling rate is > 15 degrees C/min, and exhibits an irregular shape when the cooling rate is < 15 degrees C/min. Thus, a high alloying degree contributes to the complex and sensitive microstructure evolution behavior of GH4151

Increasing service temperature of wrought Ni-based superalloy by increasing alloying degree and fraction of γ′ phase has come to a bottleneck. In present work, an attempt is made to make maximum use of carbide to strengthen Ni-based alloy with a simpler chemical composition. Multiple morphology characterization methods and high temperature tensile test show that the newly designed Ni(bal.)-20Cr-0.80C–12Ta (wt%) alloy can be strengthened by TaC and Cr-rich M7C3 carbide and shows good ductility at 800 °C. Phase transformation characteristics detected by differential scanning calorimetry (DSC) and high-temperature confocal laser scanning microscopy (CLSM) images shows that there is a potential for dispersive precipitation of carbide in the alloy to get better mechanical property.

A turn-on fluorescence probe PQP-1 with a pyrroloquinoline skeleton has been designed and synthesized. Probe PQP-1 showed high sensitivity to HSO3−, low detection limit (16.83 nM), and a wide linear range (50–3000 μM). More importantly, probe PQP-1 could distinguish between HSO3− and SO32−. Furthermore, cell imaging experiments of HSO3− in HeLa cells revealed that probe PQP-1 had potential application value in biological systems.

As a new high-temperature material with higher strength and lighter weight, researchers have paid attention to the SiCf reinforced nickel matrix composite. However, the severe interface reaction hinders the further development of this material. Due to the severe reaction of long-time preparation, in present work the Ni/SiCf composite system was prepared by spark plasma sintering which is characterized by shorter preparation time. SEM and EDS were used to analyze the interface morphology and element distribution. The results show that Ni reacts with SiCf, and Ni3Si and carbon particles are formed. The reaction zone further reacts with Ni to generate Ni(Si,C) solid solution. There exist strong thermodynamic and kinetic conditions between Ni/SiCf system and Ni/Ni3Si system, which induce violent interface reaction. Raising sintering temperature and prolonging holding time could prompt Ni3Si and carbon particles to further dissolve. The dissolution process will shrink the reaction zone and expand the solid solution zone.

A number of recent reports indicate that SiCf-reinforced superalloy matrix composites show promise for increasing mechanical properties and lowering density. However, this has not yet been successfully demonstrated. The essence is the severe interfacial reaction. In present study, Ni, Fe, Co, Cr, Mo, 80Ni20Cr, 80Ni20Mo, 80Mo20Ni (in wt%), and Waspaloy-SiCf systems were fabricated. Interfacial reactions were analyzed by optical microscopy, field emission scanning electron microscopy and electron probe microanalysis. The results indicate that superalloy matrix elements Ni, Fe, and Co react violently with SiC, whereas strengthening elements Cr, and Mo, react mildly. Addition of other elements to form alloying systems including 80Ni20Cr, 80Ni20Mo, 80Mo20Ni and Waspaloy-SiCf fail to effectively suppress the severe reaction. Alloying could not suppress the reaction completely both in thermodynamic and kinetic. Matrix elements Ni, Fe, and Co dominate the reaction. Hence, the interface between superalloy and SiC fiber exhibits instability.

Solving the trust-region subproblem (TRS) plays a key role in numerical optimization and many other applications. Based on a fundamental result that the solution of TRS of size $n$ is mathematically equivalent to finding the rightmost eigenpair of a certain matrix pair of size $2n$, eigenvalue-based methods are promising due to their simplicity. For $n$ large, the implicitly restarted Arnoldi (IRA) and refined Arnoldi (IRRA) algorithms are well suited for this eigenproblem. For a reasonable comparison of overall efficiency of the algorithms for solving TRS directly and eigenvalue-based algorithms, a vital premise is that the two kinds of algorithms must compute the approximate solutions of TRS with (almost) the same accuracy, but such premise has been ignored in the literature. To this end, we establish close relationships between the two kinds of residual norms, so that, given a stopping tolerance for IRA and IRRA, we are able to determine a reliable one that GLTR should use so as to ensure that GLTR and IRA, IRRA deliver the converged approximate solutions with similar accuracy. We also make a convergence analysis on the residual norms by the Generalized Lanczos Trust-Region (GLTR) algorithm for solving TRS directly, the Arnoldi method and the refined Arnoldi method for the equivalent eigenproblem. A number of numerical experiments are reported to illustrate that IRA and IRRA are competitive with GLTR and IRRA outperforms IRA.

Binary Ni-Fe metal matrix composite containing continuous W-core SiC fibers was fabricated by hot isostatic pressing (HIP) method to study the interface reaction processes. Interfacial reaction products were analyzed via field emission scanning electron microscope, electron probe microanalysis and micro-zone X-ray diffractometer. The results indicate that the reactions are so dramatical that even W core can decompose during the HIP process. The whole reaction processes of W-core SiC fiber can be divided into four stages. In stage 1, SiC starts to react with metal matrix to form Ni silicides with dissolved Fe element, graphite and Kirkendall void zone. In stage 2, SiC decomposes further and W core is exposed, then W core participates in reactions. In stage 3, SiC reacts completely, W core further reacts. In stage 4, W core decomposes completely and transform to be steady WC particles, which means the whole processes terminate. A model to clarify the mechanism of the reaction processes is proposed.

In this work, to check the effect of the transposition of the rings in typical patterns, a series of pyrazoline derivatives 3a-3t bearing the characteristic 3,4,5-trimethoxy phenyl and thiophene moieties were synthesized and evaluated as tubulin polymerization inhibitors. Basically, as the concise output of our design, a majority of the synthesized compounds showed potency in inhibiting the tubulin polymerization. The top hit, 3q, exhibited potent anti-proliferation activity on cancer cell lines. It was comparable on tubulin-polymerization inhibition with the positive control Colchicine but lower toxic. The VEGFR2 inhibitory potency was introduced occasionally. The flow cytometry assay confirmed the apoptotic procedure and the confocal imaging revealed the tubulin-microtubule dynamics pattern. The anti-cancer mechanism of 3q was similar to Colchicine but not exactly the same on forming multi-polar spindles. The docking simulation visualized the possible binding patterns of 3q into tubulin and VEGFR2, respectively. The results inferred that further investigations on the transposition of the rings might lead to the improvement of tubulin polymerization inhibitory activity and the steadily introduction of the VEGFR2 inhibition.

We examine price setting and the decision to disclose quality preference-revealing information in a supply chain with two competing manufacturers supplying two quality-differentiated products to a common retailer. Consumers have complete knowledge of product quality but are uncertain about how the quality will match their own preferences. We study who should provide preference-revealing information to help consumers understand their own quality preferences, and how such information disclosure affects horizontal and vertical competitions in the supply chain. We show that the manufacturer with a higher unit quality production cost has a higher incentive to provide such information, and we show how each supply chain member sets its information policy. The role of information releaser will switch from an upstream member (a manufacturer) to the downstream member (the retailer) as the market information level (the consumer’s degree of informativeness before disclosure) increases. Information disclosure softens both horizontal and vertical competitions in the supply chain. We extend our model to examine the case in which the two manufacturers make simultaneous decisions, and the case when a supply chain member incurs a cost for implementing information disclosure.

SiC fiber reinforced metal-base composite is more and more widely used in aerospace field for its higher temperature capability and lower density. SiC fiber reinforced Ti, Al, Mg based composites have prove to be a great success. But the usage temperature of these composites has been limited by the usage temperature of base metal. In order to further increase the temperature capability of SiC fiber reinforced metal-base composite and obtain high-temperature structural material with better properties, there are some attempts for SiC fiber reinforced superalloy-base composite at home and aboard. However, the development of SiC fiber reinforced superalloy-base composite is in slow development and there has almost no breakthrough success. The bottleneck for the development of SiC fiber reinforced superalloy-base composite is the interface reaction between SiC fiber and superalloy base. Many attempts (such as a variety of interface coatings) have been made to conquer this challenge, while no mature solution has been found. Hence, it is necessary to analyze the feasibility of SiC fiber reinforced superalloy-based composite. In this research, the origin and development of SiC fiber reinforced superalloy-based composites in past decades were narrated. The failure cases and reasons were summarized. Moreover, the attempts of interface coating and disadvantages of this method were analyzed. Experiments and simulations were carried out to investigate the interface reaction between SiC fiber and major superalloy elements. The results show that the reaction between SiC fiber and major superalloy elements is severe and cannot be avoided. Further analysis on the essence of severe reaction between SiC fiber and superalloy was made. The experiment and analysis show that SiC fiber and superalloy are intrinsically incompatible, and the interface reaction trend is severe. Interface coating can hinder the reaction in some extent. But the reaction trend is so severe that any minor failure of coating will result in catastrophic result. The above reasons indicate that it is difficult for SiC fiber reinforced superalloy-base composite to be used commercially in the near future.

In this work the effects of impurity in various insulating phases of the twisted bilayer graphene (TBG) are studied. The well-accepted continuum model is employed and the local density of states (DOS) is calculated. It is found that insulating phases breaking different symmetries proposed in previous theories are distinguishable via the number and properties of in-gap bound state peaks induced by impurities in local DOS. Insulating phases breaking the same previously proposed symmetries can be further classified by the remaining anti-unitary symmetries and distinguished by the corresponding remaining Kramers degeneracy of bound states. The in-gap bound state peaks in local DOS and the degeneracy of the bound states can in principle be detected in scanning tunnelling microscopy (STM) experiments, and thus can help to the distinction of various insulating phases.

This paper describes the design, fabrication, and measurement of a magnetic resonant wireless power transfer (WPT system. The proposed parallel resonant circuit power amplifier is combined with a compact wireless transceiver coil (receiving coil diameter 7 cm, transmitting coil diameter 16cm), so that the wireless power transmission system has the ability to transmit about 1 Wpower at 10 cm, and has no change in load sensitivity, and the WPT system could can receive power from LED to linear resistance. The experimental results show that the transmission efficiency of the system is as high as 42%. This article provides a novel and concise way to achieve wireless power transfer, which may help to popularize wireless charging in the future.

With the continuous drive towards integrated circuits scaling, efficient performance modeling is becoming more crucial yet, more challenging. In this paper, we propose a novel method of hierarchical performance modeling based on Bayesian co-learning. We exploit the hierarchical structure of a circuit to establish a Bayesian framework where unlabeled data samples are generated to improve modeling accuracy without running additional simulation. Consequently, our proposed method only requires a small number of labeled samples, along with a large number of unlabeled samples obtained at almost no-cost, to accurately learn a performance model. Our numerical experiments demonstrate that the proposed approach achieves up to 3.66x runtime speed-up over the state-of-the-art modeling technique without surrendering any accuracy.

Software-defined radio (SDR) can have high communication quality with a reconfigurable RF front-end. One of the main challenges of a reconfigurable RF front-end is finding an optimal configuration among all possible configurations. In order to efficiently find an optimal configuration, Environment-Adaptable Fast (EAF) optimization utilizes calculated signal-to-interference-and-noise ratio (SINR) and narrows down the searching space (Jun et al., Environment-adaptable efficient optimization for programming of reconfigurable Radio Frequency (RF) receivers, 2014). However, we found several limitations for applying the EAF optimization to a realistic large-scale Radio Frequency-Field Programmable Gate Array (RF-FPGA) system. In this paper, we first investigated two estimation issues of RF impairments: a saturation bias of nonlinearity estimates and limited resources for RF impairment estimation. Using the estimated results, the SINR formula was calculated and used for the Environment-Adaptable Fast Multi-Resolution (EAF-MR) optimization, which was designed by applying the EAF optimization to multi-resolution optimization. Finally, our simulation set-up demonstrated the efficiency improvement of the EAF-MR optimization for a large-scale RF-FPGA.

Reconfigurable radio frequency (RF) system has recently emerged as a promising solution to cope with multiple communication standards and high spectrum density. In this paper, we propose a novel optimization framework to efficiently program a reconfigurable RF system. In particular, two novel techniques, including (i) search space reduction by adaptive resolution and (ii) global polynomial optimization based on branch and bound, are developed. When combined with a relaxation iteration scheme, our proposed method offers superior performance when programming a large-scale reconfigurable RF system designed for the WLAN 802.11g standard.

In this paper, we propose a novel methodology for detecting systematic failure patterns at the wafer level for yield learning. Our proposed methodology takes the binary testing results (i.e., pass or fail) of all dies over multiple wafers, cluster these wafers according to their spatial signatures of failures, and eventually identify the underlying systematic failure patterns. Several data processing techniques, including singular value decomposition, hierarchical clustering, etc., are adopted to make the proposed methodology robust to random failures. In addition, a Pseudo-Boolean satisfiability solver is used to extract a minimal set of systematic failure patterns that explain all wafer-level spatial signatures. These patterns help process engineers identify the root causes of failures and accelerate yield learning. The efficacy of our proposed approach is demonstrated by one synthetic data set and one industrial data set.