From harmful Microcystis blooms to multi-functional core-double-shell microsphere bio-hydrochar materials

Harmful algal blooms (HABs) induced by eutrophication is becoming a serious global environmental problem affecting public health and aquatic ecological sustainability. A novel strategy for the utilization of biomass from HABs was developed by converting the algae cells into hollow mesoporous biohydrochar microspheres via hydrothermal carbonization method. The hollow microspheres were used as microreactors and carriers for constructing CaO2 core-mesoporous shell-CaO2 shell microspheres (OCRMs). The CaO2 shells could quickly increase dissolved oxygen to extremely anaerobic water in the initial 40 min until the CaO2 shells were consumed. The mesoporous shells continued to act as regulators restricting the release of oxygen from CaO2 cores. The oxygen-release time using OCRMs was 7 times longer than when directly using CaO2. More interestingly, OCRMs presented a high phosphate removal efficiency (95.6%) and prevented the pH of the solution from rising to high levels in comparison with directly adding CaO2 due to the OH− controlled-release effect of OCRMs. The distinct core-doubleshell micro/nanostructure endowed the OCRMs with triple functions for oxygen controlled-release, phosphorus removal and less impact on water pH. The study is to explore the possibility to prepare smarter bio-hydrochar materials by utilizing algal blooms

Unlocking the power of big data in new product development

This study explores how big data can be used to enable customers to express unrecognised needs. By acquiring this information, managers can gain opportunities to develop customer-centred products. Big data can be defined as multimedia-rich and interactive low-cost information resulting from mass communication. It offers customers a better understanding of new products and provides new, simplified modes of large-scale interaction between customers and firms. Although previous studies have pointed out that firms can better understand customers’ preferences and needs by leveraging different types of available data, the situation is evolving, with increasing application of big data analytics for product development, operations and supply chain management. In order to utilise the customer information available from big data to a larger extent, managers need to identify how to establish a customer-involving environment that encourages customers to share their ideas with managers, contribute their know-how, fiddle around with new products, and express their actual preferences. We investigate a new product development project at an electronics company, STE, and describe how big data is used to connect to, interact with and involve customers in new product development in practice. Our findings reveal that big data can offer customer involvement so as to provide valuable input for developing new products. In this paper, we introduce a customer involvement approach as a new means of coming up with customer-centred new product development

Search for Anomalous Production of Events with a Photon, Jet, b-quark Jet, and Missing Transverse Energy

Submitted to Phys. Rev. DWe present a signature-based search for anomalous production of events containing a photon, two jets, of which at least one is identified as originating from a b quark, and missing transverse energy. The search uses data corresponding to 2.0/fb of integrated luminosity from p-pbar collisions at a center-of-mass energy of sqrt(s)=1.96 TeV, collected with the CDF II detector at the Fermilab Tevatron. From 6,697,466 events with a photon candidate with transverse energy ET> 25 GeV, we find 617 events with missing transverse energy > 25 GeV and two or more jets with ET> 15 GeV, at least one identified as originating from a b quark, versus an expectation of 607+- 113 events. Increasing the requirement on missing transverse energy to 50 GeV, we find 28 events versus an expectation of 30+-11 events. We find no indications of non-standard-model phenomena.We present a signature-based search for the anomalous production of events containing a photon, two jets, of which at least one is identified as originating from a b quark, and missing transverse energy (E̸T). The search uses data corresponding to 2.0  fb-1 of integrated luminosity from pp̅ collisions at a center-of-mass energy of √s=1.96  TeV, collected with the CDF II detector at the Fermilab Tevatron. From 6.697 47×106 events with a photon candidate with transverse energy ET>25  GeV, we find 617 events with E̸T>25  GeV and two or more jets with ET>15  GeV, at least one identified as originating from a b quark, versus an expectation of 607±113 events. Increasing the requirement on E̸T to 50 GeV, we find 28 events versus an expectation of 30±11 events. We find no indications of non-standard-model phenomena.Peer reviewe

Search for Standard Model Higgs Boson Production in Association with a W Boson using a Neural Network

We present a search for standard model Higgs boson production in association with a W boson in proton-antiproton collisions at a center of mass energy of 1.96 TeV. The search employs data collected with the CDF II detector that correspond to an integrated luminosity of approximately 1.9 inverse fb. We select events consistent with a signature of a single charged lepton, missing transverse energy, and two jets. Jets corresponding to bottom quarks are identified with a secondary vertex tagging method, a jet probability tagging method, and a neural network filter. We use kinematic information in an artificial neural network to improve discrimination between signal and background compared to previous analyses. The observed number of events and the neural network output distributions are consistent with the standard model background expectations, and we set 95% confidence level upper limits on the production cross section times branching fraction ranging from 1.2 to 1.1 pb or 7.5 to 102 times the standard model expectation for Higgs boson masses from 110 to $150 GeV/c^2, respectively.We present a search for standard model Higgs boson production in association with a W boson in proton-antiproton collisions (pp̅ →W±H→ℓνbb̅ ) at a center of mass energy of 1.96 TeV. The search employs data collected with the CDF II detector that correspond to an integrated luminosity of approximately 1.9  fb-1. We select events consistent with a signature of a single charged lepton (e±/μ±), missing transverse energy, and two jets. Jets corresponding to bottom quarks are identified with a secondary vertex tagging method, a jet probability tagging method, and a neural network filter. We use kinematic information in an artificial neural network to improve discrimination between signal and background compared to previous analyses. The observed number of events and the neural network output distributions are consistent with the standard model background expectations, and we set 95% confidence level upper limits on the production cross section times branching fraction ranging from 1.2 to 1.1 pb or 7.5 to 102 times the standard model expectation for Higgs boson masses from 110 to 150  GeV/c2, respectively.Peer reviewe

Measurements of the top-quark mass using charged particle tracking

We present three measurements of the top-quark mass in the lepton plus jets channel with approximately 1.9 fb-1 of integrated luminosity collected with the CDF II detector using quantities with minimal dependence on the jet energy scale. One measurement exploits the transverse decay length of b-tagged jets to determine a top-quark mass of 166.9+9.5-8.5 (stat) +/- 2.9 (syst) GeV/c2, and another the transverse momentum of electrons and muons from W-boson decays to determine a top-quark mass of 173.5+8.8-8.9 (stat) +/- 3.8 (syst) GeV/c2. These quantities are combined in a third, simultaneous mass measurement to determine a top-quark mass of 170.7 +/- 6.3 (stat) +/- 2.6 (syst) GeV/c2.We present three measurements of the top-quark mass in the lepton plus jets channel with approximately 1.9  fb-1 of integrated luminosity collected with the CDF II detector using quantities with minimal dependence on the jet energy scale. One measurement exploits the transverse decay length of b-tagged jets to determine a top-quark mass of 166.9-8.5+9.5(stat)±2.9(syst)  GeV/c2, and another the transverse momentum of electrons and muons from W-boson decays to determine a top-quark mass of 173.5-8.9+8.8(stat)±3.8(syst)  GeV/c2. These quantities are combined in a third, simultaneous mass measurement to determine a top-quark mass of 170.7±6.3(stat)±2.6(syst)  GeV/c2.Peer reviewe

Measurement of Higgs boson production and properties in the WW decay channel with leptonic final states

Peer reviewe

Study of double parton scattering using W+2-jet events in proton-proton collisions at √s=7 TeV

Peer reviewe

Particle Swarm Optimization with Reinforcement Learning for the Prediction of CpG Islands in the Human Genome

BACKGROUND: Regions with abundant GC nucleotides, a high CpG number, and a length greater than 200 bp in a genome are often referred to as CpG islands. These islands are usually located in the 5' end of genes. Recently, several algorithms for the prediction of CpG islands have been proposed. METHODOLOGY/PRINCIPAL FINDINGS: We propose here a new method called CPSORL to predict CpG islands, which consists of a complement particle swarm optimization algorithm combined with reinforcement learning to predict CpG islands more reliably. Several CpG island prediction tools equipped with the sliding window technique have been developed previously. However, the quality of the results seems to rely too much on the choices that are made for the window sizes, and thus these methods leave room for improvement. CONCLUSIONS/SIGNIFICANCE: Experimental results indicate that CPSORL provides results of a higher sensitivity and a higher correlation coefficient in all selected experimental contigs than the other methods it was compared to (CpGIS, CpGcluster, CpGProd and CpGPlot). A higher number of CpG islands were identified in chromosomes 21 and 22 of the human genome than with the other methods from the literature. CPSORL also achieved the highest coverage rate (3.4%). CPSORL is an application for identifying promoter and TSS regions associated with CpG islands in entire human genomic. When compared to CpGcluster, the islands predicted by CPSORL covered a larger region in the TSS (12.2%) and promoter (26.1%) region. If Alu sequences are considered, the islands predicted by CPSORL (Alu) covered a larger TSS (40.5%) and promoter (67.8%) region than CpGIS. Furthermore, CPSORL was used to verify that the average methylation density was 5.33% for CpG islands in the entire human genome

Macrophage Migration Inhibitory Factor Induces Autophagy via Reactive Oxygen Species Generation

Autophagy is an evolutionarily conserved catabolic process that maintains cellular homeostasis under stress conditions such as starvation and pathogen infection. Macrophage migration inhibitory factor (MIF) is a multifunctional cytokine that plays important roles in inflammation and tumorigenesis. Cytokines such as IL-1β and TNF-α that are induced by MIF have been shown to be involved in the induction of autophagy. However, the actual role of MIF in autophagy remains unclear. Here, we have demonstrated that incubation of human hepatoma cell line HuH-7 cells with recombinant MIF (rMIF) induced reactive oxygen species (ROS) production and autophagy formation, including LC3-II expression, LC3 punctae formation, autophagic flux, and mitochondria membrane potential loss. The autophagy induced by rMIF was inhibited in the presence of MIF inhibitor, ISO-1 as well as ROS scavenger N-acetyl-L-cysteine (NAC). In addition, serum starvation-induced MIF release and autophagy of HuH-7 cells were partly blocked in the presence of NAC. Moreover, diminished MIF expression by shRNA transfection or inhibition of MIF by ISO-1 decreased serum starvation-induced autophagy of HuH-7 cells. Taken together, these data suggest that cell autophagy was induced by MIF under stress conditions such as inflammation and starvation through ROS generation