Field Induced Jet Micro-EDM

Electrical discharge machining (EDM) is of the potential of micro/nano meter scale machining capability. However, electrode wear in micro-EDM significantly deteriorates the machining accuracy, thus, it needs to be compensated in process. To solve this problem, a novel micromachining method, namely field induced jet micro-EDM, is proposed in this paper, in which the electrical field induced jet is used as the micro tool electrode. A series of experiments were carried out to investigate the feasibility of proposed method. Due to the electrolyte can be supplied automatically by the capillary effect and the electrostatic field, it is not necessary to use pump or valves. The problem of electrode wear does not exist at all in the machining process because of the field induced jet will be generated periodically. It is also found that the workpiece material can be effectively removed with a crater size of about 2 micrometer in diameter. The preliminary experimental results verified that the field induced jet micro-EDM is an effective micromachining method

Optimization of Hybrid Hub-and-Spoke Network Operation for Less-Than-Truckload Freight Transportation considering Incremental Quantity Discount

This paper presents a mixed integer linear programming model (MILP) for optimizing the hybrid hub-and-spoke network operation for a less-than-truckload transportation service. The model aims to minimize the total operation costs (transportation cost and transfer cost), given the determined demand matrix, truck load capacity, and uncapacitated road transportation. The model also incorporates an incremental quantity discount function to solve the reversal of the total cost and the total demand. The model is applied to a real case of a Chinese transportation company engaged in nationwide freight transportation. The numerical example shows that, with uncapacitated road transportation, the total costs and the total vehicle trips of the hybrid hub-and-spoke network operation are, respectively, 8.0% and 15.3% less than those of the pure hub-and-spoke network operation, and the assumed capacity constraints in an extension model result in more target costs on the hybrid hub-and-spoke network. The two models can be used to support the decision making in network operations by transportation and logistics companies

The paradox of political legitimacy: the political inclusion and entrepreneurs’ firm strategies

This paper examines the paradoxical impact of political legitimacy by exploring the relationship between legitimacy due to political inclusion by the state and subsequent strategic actions by entrepreneurs in both domestic and global contexts in a transition economy. We argue that political legitimacy conferred by the state affects a firm’s strategies in different ways because it is associated with both benefits and constraints. Using a unique dataset of more than six thousand privately owned enterprises in China, we demonstrate that after an institutional change that permitted the inclusion of entrepreneurs into an elite political system (the Communist Party of China) in 2001, private firms became more motivated to invest in their domestic production but less incentivized to form international cooperation strategies. We further find that the impact of the legitimacy from political inclusion on domestic production was less pronounced for firms in places where the market economy was more established and when entrepreneurs are female. For entrepreneurs with past work experiences in the government or in state-owned enterprises, the negative impact of political inclusion on global cooperation was strengthened. These findings have important implications for research on legitimacy, entrepreneurship, and business strategy

FOLDING OF A MULTIDOMAIN PROTEIN, WITH THE HELP OF THE RIBOSOME AND A MOLECULAR CHAPERONE

Multidomain proteins, containing several structural units within a single polypeptide, constitute a large fraction of all proteomes. Cotranslational folding is assumed to simplify the conformational search problem for large proteins, but the events leading to correctly folded structures remain poorly characterized. Additionally, how the ribosome and molecular chaperones promote efficient folding remains obscure. In this study, folding events of nascent elongation factor G, a five-domain protein that requires chaperones for folding in vivo, have been dissected by single-molecule optical tweezers. We found that the N-terminal G-domain of EF-G constitutes an independent folding unit. Upon in vitro refolding, it adopts two similar states that correspond to the natively and non-natively folded structures. The ribosome destabilizes both of them, suggesting terminal misfolding into highly stable, non-native structures is avoided. The first N-terminal two domains G and II will form misfolded off-pathway states in isolation, however, the ribosome and the chaperone trigger factor reduce inter-domain misfolding, permitting folding of the N-terminal G-domain. Successful completion of this step is crucial for folding of domain II. Unexpectedly, cotranslational folding does not proceed unidirectionally: emerging unfolded polypeptide denatures an already folded domain. Trigger factor, but not the ribosome, protects against denaturation. The chaperone thus helps multidomain proteins overcome inherent challenges during cotranslational folding. While the N-terminal two domains must fold in the order of their synthesis, the C-terminal domains do not fold sequentially. Domain III stability is dictated by the folded C-terminal IV-V, indicating a post-translational folding mechanism. In summary, as a paradigm for multidomain protein folding, this work discovered that domain-wise folding of nascent proteins can be reversed by denaturation interactions with emerging polypeptide, which can be blocked by trigger factor. Trigger factor also cooperates with the ribosome to reduce misfolding. The chaperone therefore has a dual function in promoting efficient folding of multidomain proteins. Furthermore, the folding dependency of domain II and III on their neighboring domains supports the hypothesis that domains incapable of independent folding are stabilized by favorable interactions with neighboring domains, which could be a fundamental rule for multidomain protein folding

A Multi-Stage Graph Model Analysis for the International Toxic Waste Disposal Conflict

A generic conflict model is developed to analyze international toxic waste disposal issues, and then, to provide feasible strategic resolutions for this serious environmental dispute. With the rapid growth of the global economy, toxic waste traffic from the advanced to developing nations has become a serious side effect of this globalization. The illegal transboundary movement of toxic wastes not only aggravates the burden on the poorer nations, but also negatively impacts the worldwide environment. In this thesis, the ongoing toxic waste disputes are divided into two stages consisting of the dumping prevention and dispute resolution stages. The analyses based on the methodology of Graph Model for Conflict Resolution are used in both stages in order to grasp the structure and implications of the conflict from a strategic viewpoint. The in-depth modeling of the toxic waste dumping disputes, which consist of historical and generic situations, specifies the involved parties and their options. By synthesizing the economic, political and legal factors, the relative preferences for each party can be determined. The Graphical User Interface (GUI) of the Decision Support System (DSS) GMCR II simplifies the processing of calculations. The analytical research furnishes investigators or other interested parties with possible resolutions for the disputes arising from an international waste dumping event. Sensitivity analyses are also conducted to provide a comprehensive understanding of the different situations that may occur in real-world cases. The case study of the Ivory Coast waste dumping controversy is used to demonstrate how to practically implement the generic multi-stage graph model

Data Discovery and Anomaly Detection Using Atypicality: Theory

A central question in the era of 'big data' is what to do with the enormous amount of information. One possibility is to characterize it through statistics, e.g., averages, or classify it using machine learning, in order to understand the general structure of the overall data. The perspective in this paper is the opposite, namely that most of the value in the information in some applications is in the parts that deviate from the average, that are unusual, atypical. We define what we mean by 'atypical' in an axiomatic way as data that can be encoded with fewer bits in itself rather than using the code for the typical data. We show that this definition has good theoretical properties. We then develop an implementation based on universal source coding, and apply this to a number of real world data sets.Comment: 40 page

Application of Nickel(II) Complexes to the Efficient Synthesis of α- or β-Amino Acids

Nonproteinogenic α- or β-amino acids have attracted tremendous attention, as they are widely utilized for biological, biochemical, pharmaceutical, and asymmetric chemical investigations. Recently, we developed a series of new strategies for preparing achiral and chiral nickel(ii) complexes for the synthesis of amino acids. We applied these new methods utilizing chiral nickel(ii) complexes for the asymmetric Mannich reaction to synthesize enantiopure α,β-diamino acids, the enantioselective tandem conjugate addition–elimination reaction to prepare glutamic acid derivatives, the Suzuki coupling reaction to yield β2-amino acid derivatives, the asymmetric Mannich reaction to synthesize 3-aminoaspartate, the asymmetric Michael addition reaction to give β-substituted-α,γ-diaminobutyric acid derivatives, the asymmetric alkylation reaction to prepare linear ω-trifluoromethyl containing amino acids, and the asymmetric Michael addition reaction to synthesize syn-β-substituted tryptophans

Lys169 of Human Glucokinase Is a Determinant for Glucose Phosphorylation: Implication for the Atomic Mechanism of Glucokinase Catalysis

Glucokinase (GK), a glucose sensor, maintains plasma glucose homeostasis via phosphorylation of glucose and is a potential therapeutic target for treating maturity-onset diabetes of the young (MODY) and persistent hyperinsulinemic hypoglycemia of infancy (PHHI). To characterize the catalytic mechanism of glucose phosphorylation by GK, we combined molecular modeling, molecular dynamics (MD) simulations, quantum mechanics/molecular mechanics (QM/MM) calculations, experimental mutagenesis and enzymatic kinetic analysis on both wild-type and mutated GK. Our three-dimensional (3D) model of the GK-Mg2+-ATP-glucose (GMAG) complex, is in agreement with a large number of mutagenesis data, and elucidates atomic information of the catalytic site in GK for glucose phosphorylation. A 10-ns MD simulation of the GMAG complex revealed that Lys169 plays a dominant role in glucose phosphorylation. This prediction was verified by experimental mutagenesis of GK (K169A) and enzymatic kinetic analyses of glucose phosphorylation. QM/MM calculations were further used to study the role of Lys169 in the catalytic mechanism of the glucose phosphorylation and we found that Lys169 enhances the binding of GK with both ATP and glucose by serving as a bridge between ATP and glucose. More importantly, Lys169 directly participates in the glucose phosphorylation as a general acid catalyst. Our findings provide mechanistic details of glucose phorphorylation catalyzed by GK, and are important for understanding the pathogenic mechanism of MODY