A survey on gas leakage source detection and boundary tracking with wireless sensor networks

Gas leakage source detection and boundary tracking of continuous objects have received a significant research attention in the academic as well as the industries due to the loss and damage caused by toxic gas leakage in large-scale petrochemical plants. With the advance and rapid adoption of wireless sensor networks (WSNs) in the last decades, source localization and boundary estimation have became the priority of research works. In addition, an accurate boundary estimation is a critical issue due to the fast movement, changing shape, and invisibility of the gas leakage compared with the other single object detections. We present various gas diffusion models used in the literature that offer the effective computational approaches to measure the gas concentrations in the large area. In this paper, we compare the continuous object localization and boundary detection schemes with respect to complexity, energy consumption, and estimation accuracy. Moreover, this paper presents the research directions for existing and future gas leakage source localization and boundary estimation schemes with WSNs.</p

A survey on gas leakage source detection and boundary tracking with wireless sensor networks

Gas leakage source detection and boundary tracking of continuous objects have received a significant research attention in the academic as well as the industries due to the loss and damage caused by toxic gas leakage in large-scale petrochemical plants. With the advance and rapid adoption of wireless sensor networks (WSNs) in the last decades, source localization and boundary estimation have became the priority of research works. In addition, an accurate boundary estimation is a critical issue due to the fast movement, changing shape, and invisibility of the gas leakage compared with the other single object detections. We present various gas diffusion models used in the literature that offer the effective computational approaches to measure the gas concentrations in the large area. In this paper, we compare the continuous object localization and boundary detection schemes with respect to complexity, energy consumption, and estimation accuracy. Moreover, this paper presents the research directions for existing and future gas leakage source localization and boundary estimation schemes with WSNs.</p

Optimal production and inventory decisions under demand and production disruptions

<div><p>Unanticipated events may take place and disrupt demand and/or production in a supply chain. Conditional on the type, magnitude and duration of disruptions, changes may be called to revise the original production plan. We analyse different disruption scenarios and propose optimal production–inventory models for products facing demand and production disruptions. To lower the cost, we optimise the production run time, purchasing times and order quantity for the manufacturer. Numerical experiments are conducted to examine the influences of disruption time and magnitude on optimal production and purchasing decisions.</p></div

Analysis of the glutamate dehydrogenase activity of DLDH744.

<p>(a) Analysis of the enzymatic activity using a UV spectrophotometer. (Filled circle) Reaction with NAD⁺ as coenzyme. (Filled block) Reaction without DLDH744. (Filled triangles) Reaction without glutamate substrate. (b) Analysis of the reaction product using HPLC. (i) Control. (ii) Glutamic acid standard. (iii) Reaction solution with substrates and enzyme DLDH744.</p

DataSheet_1_Sotetsuflavone Induces Autophagy in Non-Small Cell Lung Cancer Through Blocking PI3K/Akt/mTOR Signaling Pathway in Vivo and in Vitro.docx

Non-small cell lung cancer (NSCLC) is a globally scaled disease with a high incidence and high associated mortality rate. Autophagy is one of the important physiological activities that helps to control cell survival, influences the dynamics of cell death, and which plays a crucial role in the pathophysiology of NSCLC. Sotetsuflavone is a naturally derived and occurring flavonoid, and previous studies have demonstrated that sotetsuflavone possesses potential anti-cancer activities. However, whether or not sotetsuflavone induces autophagy, as well as has effects and influences cell death in NSCLC cells remains unclear. Thus, in our study, we examined and elucidated the roles and underlying mechanisms of sotetsuflavone upon the dynamics of autophagy in NSCLC in vivo and in vitro. The results indicated that sotetsuflavone was able to inhibit proliferation, migration, and invasion of NSCLC cells. Mechanistically, sotetsuflavone was able to induce apoptosis by increasing the levels of expression of cytochrome C, cleaved-caspase 3, cleaved-caspase 9, and Bax, and contrastingly decreased levels of expression of Bcl-2. In addition, we also found that decreased levels of expression of cyclin D1 and CDK4 caused arrest of the G0/G1 phases of the cell cycle. Furthermore, we also found that sotetsuflavone could induce autophagy which in turn can play a cytoprotective effect on apoptosis in NSCLC. Sotetsuflavone-induced autophagy appeared related to the blocking of the PI3K/Akt/mTOR pathway. Our in vivo study demonstrated that sotetsuflavone significantly inhibited the growth of xenograft model inoculated A549 tumor with high a degree of safety. Taken together, these findings suggest that sotetsuflavone induces autophagy in NSCLC cells through its effects upon blocking of the PI3K/Akt/mTOR signaling pathways. Our study may provide a theoretical basis for future clinical applications of sotetsuflavone and its use as a chemotherapeutic agent for treatment of NSCLC.</p

Crystal Structure of a Thermostable Alanine Racemase from <i>Thermoanaerobacter tengcongensis</i> MB4 Reveals the Role of Gln360 in Substrate Selection

<div><p>Pyridoxal 5’-phosphate (PLP) dependent alanine racemase catalyzes racemization of L-Ala to D-Ala, a key component of the peptidoglycan network in bacterial cell wall. It has been extensively studied as an important antimicrobial drug target due to its restriction in eukaryotes. However, many marketed alanine racemase inhibitors also act on eukaryotic PLP-dependent enzymes and cause side effects. A thermostable alanine racemase (Alr_Tt) from <i>Thermoanaerobacter tengcongensis</i> MB4 contains an evolutionarily non-conserved residue Gln360 in inner layer of the substrate entryway, which is supposed to be a key determinant in substrate specificity. Here we determined the crystal structure of Alr_Tt in complex with L-Ala at 2.7 Å resolution, and investigated the role of Gln360 by saturation mutagenesis and kinetic analysis. Compared to typical bacterial alanine racemase, presence of Gln360 and conformational changes of active site residues disrupted the hydrogen bonding interactions necessary for proper PLP immobilization, and decreased both the substrate affinity and turnover number of Alr_Tt. However, it could be complemented by introduction of hydrophobic amino acids at Gln360, through steric blocking and interactions with a hydrophobic patch near active site pocket. These observations explained the low racemase activity of Alr_Tt, revealed the essential role of Gln360 in substrate selection, and its preference for hydrophobic amino acids especially Tyr in bacterial alanine racemization. Our work will contribute new insights into the alanine racemization mechanism for antimicrobial drug development.</p></div

The coenzyme NAD⁺ binding sites of the DLDH744 in the active center.

<p>The key amino acids necessary for NAD⁺ binding are shown in sticks in orange. The hydrogen bonding interactions between these amino acid residues and NAD⁺ are shown in dashed lines, with the distance labeled.</p

Kinetic parameters of wild-type and mutant Alr_<i>Tt</i>.

<p>Kinetic parameters of wild-type and mutant Alr_<i>Tt</i>.</p

Phylogenetic analysis of DLDH744 with the other enzymes in D-isomer-specific 2-hydroxyacid dehydrogenase family and some non-D-specific 2-hydroxyacid dehydrogenases.

<p>The accession number of each enzyme in uniprot database (<a href="http://www.uniprot.org/" target="_blank">http://www.uniprot.org</a>) is provided in brackets. Abbreviations: D-lactate dehydrogenase (DLDH), D-erythronate-4-phosphate dehydrogenase (DEPDH), D-hydroxyisocaproate dehydrogenase (DHICDH), D-phosphoglycerate dehydrogenase (DPGDH), D-glycerate dehydrogenase (DGLDH), D-mandelate dehydrogenase (DMDH), vancomycin-resistant protein H (VANH), phenylpyruvate reductase (PPR), glyoxylate reductase (GR), 2-ketopantoate reductase (KPR), transcriptional co-repressor CtBP (CTBP), formate dehydrogenase (FDH), phosphate dehydrogenase (PPDH) and L-alanine dehydrogenase (ADH).</p

The active residue sites of DLDH744.

<p>(a) The activities of mutant lactate dehydrogenases. (b) The activities of glutamate dehydrogenase of the mutant strains. Data points and error bars represent the means and standard deviations of three parallel replicates, respectively.</p