Neurofuzzy control of a low‐temperature desulphurization plant

Low‐temperature desulphurization (LTD) is a low‐cost alternative to conventional wet scrubbing for removing sulphur dioxide from flue gas produced by power generating plants. A problem in the design of conventional controllers to achieve and maintain process conditions for optimal desulphurisation is the lack of mathematical models to characterise the complex desulphurization process and unexpected environ mental disturbances. The aim of the work reported in this paper was to replace a skilled human operator who could successfully regulate the LTD plant through manipulation of low‐level controllers with a competitive neurofuzzy system, which possesses both the learning ability of neural networks and the structural transparency of fuzzy logic systems. A hierarchical control structure was adopted whereby the competitive neurofuzzy method was used at the top level for co‐ordinating actions of low‐level conventional controllers. This approach would considerably simplify the task of designing the control system and has been shown to yield high‐level controllers with performances at least equalling that of expert operators, as demonstrated in this paper. Copyright © 2001 John Wiley & Sons, Ltd.     

Enhanced removal of 1,2-dichloroethane by anodophilic microbial consortia

1,2-Dichloroethane (1,2-DCA) is a well-known recalcitrant groundwater contaminant. New environment-friendly approaches for the removal of 1,2-DCA that does not bring about volatilization of the compound are required. In this study, different anodophilic consortia enriched in microbial fuel cells (MFCs) operated under airtight conditions were shown to effectively degrade 1,2-DCA (up to 102 mg per liter reactor volume per day), while concomitantly generating a current. An anodophilic consortium previously enriched with acetate as the electron donor changed its composition at the rate of 48% per week and increased its richness (Rr) 3-fold, upon adapting to 1,2-DCA as the new electron donor. After being stable, during 1 month of operation, it removed up to 95% of the 1,2-DCA amount in the medium in the first 2 weeks, while converting 43 ± 4% of electrons available from the removal to electricity. A natural consortium from a 1,2-DCA contaminated site changed its composition at the rate of 9% per week and increased its Rr 2-fold, upon adapting to the MFC anode conditions with 1,2-DCA as the electron donor. After being stable, during 1 month of operation, it removed up to 85% of the 1,2-DCA amount in the medium in the first 2 weeks and the coulombic efficiency was 25 ± 4%. The operation of the MFCs under closed circuit conditions resulted in higher 1,2-DCA removal rates than the operation under open circuit conditions, indicating that bioelectrochemical activities enhanced the removal of 1,2-DCA in the MFC anode. The production of ethylene glycol, acetate and carbon dioxide indicated that the anodophilic bacteria oxidatively metabolized 1,2-DCA, probably by means of a hydrolysis-based pathway. The results show that MFCs can be potentially used as a practically convenient technology for the biological removal of 1,2-DCA.     

Subunit‐Specific Labeling of Ubiquitin Chains by Using Sortase: Insights into the Selectivity of Deubiquitinases

Information embedded in different ubiquitin chains is transduced by proteins with ubiquitin‐binding domains (UBDs) and erased by a set of hydrolytic enzymes referred to as deubiquitinases (DUBs). Understanding the selectivity of UBDs and DUBs is necessary for decoding the functions of different ubiquitin chains. Critical to these efforts is the access to chemically defined ubiquitin chains bearing site‐specific fluorescent labels. One approach toward constructing such molecules involves peptide ligation by sortase (SrtA), a bacterial transpeptidase responsible for covalently attaching cell surface proteins to the cell wall. Here, we demonstrate the utility of SrtA in modifying individual subunits of ubiquitin chains. Using ubiquitin derivatives in which an N‐terminal glycine is unveiled after protease‐mediated digestion, we synthesized ubiquitin dimers, trimers, and tetramers with different isopeptide linkages. SrtA was then used in combination with fluorescent depsipeptide substrates to effect the modification of each subunit in a chain. By constructing branched ubiquitin chains with individual subunits tagged with a fluorophore, we provide evidence that the ubiquitin‐specific protease USP15 prefers ubiquitin trimers but has little preference for a particular isopeptide linkage. Our results emphasize the importance of subunit‐specific labeling of ubiquitin chains when studying how DUBs process these chains.     

A novel hybrid model of Bagging-based Naïve Bayes Trees for landslide susceptibility assessment

Bulletin of Engineering Geology and the Environment - Landslide susceptibility assessment was performed using the novel hybrid model Bagging-based Naïve Bayes Trees (BAGNBT) at Mu Cang Chai...     

Highly sensitive electrochemical sensor based on zirconium oxide-decorated gold nanoflakes nanocomposite 2,4-dichlorophenol detection

Journal of Applied Electrochemistry - In this study, a sensitive and selective electrochemical sensor based on a zirconia oxide-decorated gold nanoflake nanocomposite-modified glassy carbon...     

Hidden Relationships between N-Glycosylation and Disulfide Bonds in Individual Proteins

N-Glycosylation (NG) and disulfide bonds (DBs) are two prevalent co/post-translational modifications (PTMs) that are often conserved and coexist in membrane and secreted proteins involved in a large number of diseases. Both in the past and in recent times, the enzymes and chaperones regulating these PTMs have been constantly discovered to directly interact with each other or colocalize in the ER. However, beyond a few model proteins, how such cooperation affects N-glycan modification and disulfide bonding at selective sites in individual proteins is largely unknown. Here, we reviewed the literature to discover the current status in understanding the relationships between NG and DBs in individual proteins. Our results showed that more than 2700 human proteins carry both PTMs, and fewer than 2% of them have been investigated in the associations between NG and DBs. We summarized both these proteins with the reported relationships in the two PTMs and the tools used to discover the relationships. We hope that, by exposing this largely understudied field, more investigations can be encouraged to unveil the hidden relationships of NG and DBs in the majority of membranes and secreted proteins for pathophysiological understanding and biotherapeutic development.     

Toroidal Protein Adaptor Assembles Ferrimagnetic Nanoparticle Fibers with Constructive Magnetic Coupling

Inspired by nature, the synthesis of biohybrid nanocomposites containing inorganic nanoparticles (NPs) and biopolymers such as DNA and peptides as templates offers great potential for a wide range of applications. Using selective recognition schemes of 3D protein spaces for the assembly of magnetic nanocrystals is a challenge with great promise in the field of biomedicine and magnetic data storage. Here we apply the toroidal protein Hcp1 as an interparticle connector for the directed molecular assembly and ferrimagnetic coupling of biohybrid cobalt ferrite NP wires. The resulting biohybrid NP composites show bundles of nanofibers ranging from nano‐ to the microscale in length verified by TEM, EDX analysis and focused ion beam cut. Their magnetic characterization reveals an increase of the coercive field (+12%) reaching values of high‐end Nd₂Fe₁₄B bulk magnets, enhanced saturation (+28%) and remanence magnetization (+38%) at 2 K compared to NPs lacking the protein connector. Thus, the combination of the nanoscale alignment of magnetic NPs with the molecular precision of the protein connectors leads to constructive addition of the magnetization reversal energy. This approach can be used to control magnetic properties for the design of materials with enhanced coercivity applicable for magnetic data storage, hyperthermia and theranostics.     

Robotic disassembly sequence planning using enhanced discrete bees algorithm in remanufacturing

Increasing attention is being paid to remanufacturing due to environmental protection and resource saving. Disassembly, as an essential step of remanufacturing, is always manually finished which is time-consuming while robotic disassembly can improve disassembly efficiency. Before the execution of disassembly, generating optimal disassembly sequence plays a vital role in improving disassembly efficiency. In this paper, to minimise the total disassembly time, an enhanced discrete Bees algorithm (EDBA) is proposed to solve robotic disassembly sequence planning (RDSP) problem. Firstly, the modified feasible solution generation (MFSG) method is used to build the disassembly model. After that, the evaluation criterions for RDSP are proposed to describe the total disassembly time of a disassembly sequence. Then, with the help of mutation operator, EDBA is proposed to determine the optimal disassembly sequence of RDSP. Finally, case studies based on two gear pumps are used to verify the effectiveness of the proposed method. The performance of EDBA is analysed under different parameters and compared with existing optimisation algorithms used in disassembly sequence planning (DSP). The result shows the proposed method is more suitable for robotic disassembly than the traditional method and EDBA generates better quality of solutions compared with the other optimisation algorithms.     

Energy‐efficient power control for uplink spectrum‐sharing heterogeneous networks

This article considers energy‐efficient power control schemes for interference management in uplink spectrum‐sharing heterogeneous networks that maximize the energy efficiency of users, protect the macro base station, and support users with QoS consideration. In the first scenario, we define the objective function as the weighted sum of the energy efficiencies and develop an efficient global optimization algorithm with global linear and local quadratic rate of convergence to solve the considered problem. To ensure fairness among individual user equipments (UEs) in terms of energy efficiency, we consider the max‐min problem, where the objective is defined as the weighted minimum of the energy efficiencies, and a fractional programming theory and the dual decomposition method are jointly used to solve the problem and investigate an iterative algorithm. As by‐products, we further discuss the global energy efficiency problem and consider near‐optimal schemes. Numerical examples are provided to demonstrate significant improvements of the proposed algorithms over existing interference management schemes.