EC与~（99m）Tc－GH之间的配体交换反应动力学研究

实验表明，ＥＣ浓度与配体交换反应速度常数无关，体系的ｐＨ值对速度常数和９９ｍＴｃ－ＥＣ的标记率影响较大。测定并计算了不同ｐＨ值的交换反应速度常数。结果表明，为保证用配体交换法制备９９ｍｃ－ＥＣ时９９ｍｃ－ＥＣ的标记率大于９０％，体系的ｐＨ值必须≥８。     

Anaerobic digestion of alkaline black liquor using an up-flow anaerobic sludge blanket reactor

The anaerobic digestion of alkaline black liquor from a cereal straw pulping mill was studied in batch (serum bottles) and continuous systems (up-flow anaerobic sludge blanket reactor—UASB). The batch digestion studies confirmed that lignin and related compounds (LRC) in the alkaline black liquor were the main inhibitory substances and could not be decomposed by anaerobic bacteria. At organic loading rates of 5–10 kg COD m^?3 day^?1, the UASB reactor achieved 50–60% COD removal efficiencies. Gas production was 2–3 dm³ per dm³ of alkaline black liquor. Two different sludge types were examined in the reactor: granular and cluster-like sludges. Sludge in a cluster, which involved many small granules and flocs, tended to form larger aggregates and possessed good settling ability.     

温度,压力对漂移室气体增益的影响

研究了温度及气体压力对漂移室（工作于正比区）气体放大倍数的影响，温度和气体压力的变化范围分别是５￣４０℃及９０￣１０５ｋＰａ。用实验数据拟合得到了函数关系并测量了几种饱和度下函数中的参数值。     

A conditional classification recurrent RBM for improved series mid-term forecasting

In the context of human-robot and robot-robot interactions, the better cooperation can be achieved by predicting the other party’s subsequent actions based on the current action of the other party. The time duration for adjustment is not sufficient provided by short term forecasting models to robots. A longer duration can by achieved by mid-term forecasting. But the mid-term forecasting models introduce the previous errors into the follow-up forecasting and amplified gradually, eventually invalidating the forecasting. A new mid-term forecasting with error suppression based on restricted Boltzmann machine(RBM) is proposed in this paper. The proposed model can suppress the error amplification by replacing the previous inputs with their features, which are retrieved by a deep belief network(DBN). Furthermore, a new mechanism is proposed to decide whether the forecasting result is accepted or not. The model is evaluated with several datasets. The reported experiments demonstrate the superior performance of the proposed model compared to the state-of-the-art approaches.

     

GRU-based capsule network with an improved loss for personnel performance prediction

Applied Intelligence - Personnel performance is a key factor to maintain core competitive advantages. Thus, predicting personnel future performance is a significant research domain in human...     

A graph-based QoS prediction approach for web service recommendation

Applied Intelligence - With the development of the Internet, the recommendation based on Quality of Service(QoS) is proven to be an efficient way to deal with the ever-increasing web services in...     

Analysis of emerging technology adoption for the digital content market

The digital content market is undergoing an evolution in networking and digitalization technologies, offering diverse information and services. Due to the characteristics of these emerging technologies, the digital content market is growing rapidly and traditional content providers face service transformation decisions. While a majority of the previous technology adoption studies have focused on the viewpoints of users and customers, cost reduction, or electronic channel related technologies, in this research we analyze the emerging technology adoption decisions of competing firms for providing new content services from a strategic perspective. Utilizing game theoretical models, we examine the effects of market environments (technology cost, channel cannibalization, brand power, brand extension, information asymmetry and market uncertainty) on firms’ adoption decisions. This research contributes a number of unique and interesting implications for the issues of emerging technology adoption for new content service provision.     

Adaptive synchronization of master-slave large-scale systems against bias actuators and network attenuations

This paper utilizes the adaptive technique to design a class of active synchronizing masterslave large scale systems against imperfect actuators and networked interconnections with bias faults and signal attenuations, respectively. Without the requirement of knowledge of eventual faulty factors of bias-actuators on systems, and attenuation factors of connected networks, an adaptive mechanism is designed to estimate each unknown faulty factor on-line for constructing a class of distributed adaptive controllers. Then based on the adaptive adjustment parameters and Lyapunov stability theory, Lyapunov functions are addressed to prove that the proposed adaptive master-slave large-scale system can be guaranteed to be asymptotic synchronization with the improper actuator and faulty transmitted signals. Finally, a multiple vehicle large-scale system is used to verify the efficiency of the method.     

Preparation and properties of close-packed composite materials

Monodisperse silica particles of about 0.3m diameter are suspended in methacrylate monomer using a carefully selected dispersant. Many steric dispersants are hydrocarbon chains with a reactive end-group. These are not effective as dispersants for silica in moderately polar solvents, such as esters and the methacrylate monomers. Good dispersion was obtained with a methacrylate polymer terminated by a chlorosilane end group. Settling or centrifugation of these unagglomerated dispersions gives well-packed particle beds. Polymerization of the surrounding monomer produces composite materials with high packing fractions and a high degree of regularity. Moduli and strengths of these composites are reported.