999 research outputs found

    Nearest neighbor vector analysis of sdss dr5 galaxy distribution

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    We present the Nearest Neighbor Distance (NND) analysis of SDSS DR5 galaxies. We give NND results for observed, mock and random sample, and discuss the differences. We find that the observed sample gives us a significantly stronger aggregation characteristic than the random samples. Moreover, we investigate the direction of NND and find that the direction has close relation with the size of the NND for the observed sample.Comment: Natural Science, Vol.5, No.1 in January 201

    The geomicrobiology of CO2 geosequestration: a focused review on prokaryotic community responses to field-scale CO2 injection

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    Our primary research paper (Mu et al., 2014) demonstrated selective changes to a deep subsurface prokaryotic community as a result of CO2 stress. Analyzing geochemical and microbial 16S rRNA gene profiles, we evaluated how in situ prokaryotic communities responded to increased CO2 and the presence of trace organic compounds, and related temporal shifts in phylogeny to changes in metabolic potential. In this focused review, we extend upon our previous discussion to present analysis of taxonomic unit co-occurrence profiles from the same field experiment, to attempt to describe dynamic community behavior within the deep subsurface. Understanding the physiology of the subsurface microbial biosphere, including how key functional groups integrate into the community, will be critical to determining the fate of injected CO2. For example, community-wide network analyses may provide insights to whether microbes cooperatively produce biofilm biomass, and/or biomineralize the CO2, and hence, induce changes to formation porosity or changes in electron flow. Furthermore, we discuss potential impacts to the feasibility of subsurface CO2 storage of selectively enriching for particular metabolic functions (e.g., methanogenesis) as a result of CO2 injection

    Applying federated learning to combat food fraud in food supply chains

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    Ensuring safe and healthy food is a big challenge due to the complexity of food supply chains and their vulnerability to many internal and external factors, including food fraud. Recent research has shown that Artificial Intelligence (AI) based algorithms, in particularly data driven Bayesian Network (BN) models, are very suitable as a tool to predict future food fraud and hence allowing food producers to take proper actions to avoid that such problems occur. Such models become even more powerful when data can be used from all actors in the supply chain, but data sharing is hampered by different interests, data security and data privacy. Federated learning (FL) may circumvent these issues as demonstrated in various areas of the life sciences. In this research, we demonstrate the potential of the FL technology for food fraud using a data driven BN, integrating data from different data owners without the data leaving the database of the data owners. To this end, a framework was constructed consisting of three geographically different data stations hosting different datasets on food fraud. Using this framework, a BN algorithm was implemented that was trained on the data of different data stations while the data remained at its physical location abiding by privacy principles. We demonstrated the applicability of the federated BN in food fraud and anticipate that such framework may support stakeholders in the food supply chain for better decision-making regarding food fraud control while still preserving the privacy and confidentiality nature of these data

    Light intensity-induced phase transitions in graphene oxide doped polyvinylidene fluoride

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    The coupling of light with low-frequency functionalities of dielectrics and liquid crystals and an ability to turn “on” and “off” the pyro-, piezo-, or ferro- electric properties of materials on demand by optical means leads to fascinating science and device applications. Moreover, to achieve all-optical control in nano-circuits, the coupling of the light with mechanical degrees of freedom is highly desirable and has been elusive until recently. In this work, we report on the light intensity-induced structural phase transitions in graphene oxide doped piezoelectric polyvinylidene fluoride (PVDF) film observed by micro-Raman spectroscopy. Increasing the laser power results in a steady transformation of the Raman spectrum featured piezoelectric phase to one of non-piezoelectric structure. This effect is accompanied by volumetric change of a PVDF unit cell by a factor of two, useful for a photostriction materials application. Furthermore, we observed the reversible switching of α and phases as a function of the light intensity (laser power between 5.7–31.3 mW). This opens up a new route for multi-functionality control where strain, piezoelectric constants and polarization can be modified by light

    Linking micellar structures to hydrogelation for salt-triggered dipeptide gelators

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    Some functionalised dipeptides can form hydrogels when salts are added to solutions at high pH. We have used surface tension, conductivity, rheology, optical, confocal and scanning electron microscopy, 1H NMR and UV-Vis spectroscopy measurements to characterise fully the phase behaviour of solutions of one specific gelator, 2NapFF, at 25 °C at pH 10.5. We show that this specific naphthalene–dipeptide undergoes structural transformations as the concentration is increased, initially forming spherical micelles, then worm-like micelles, followed by association of these worm-like micelles. On addition of a calcium salt, gels are generally formed as long as worm-like micelles are initially present in solution, although there are structural re-organisations that occur at lower concentrations, allowing gelation at lower than expected concentration. Using IR and SANS, we show the differences between the structures present in the solution and hydrogel phases

    Emerging roles for hyaluronidase in cancer metastasis and therapy

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    Hyaluronidases are a family of five human enzymes that have been differentially implicated in the progression of many solid tumor types, both clinically and in functional studies. Advances in the past five years have clarified many apparent contradictions, (1) by demonstrating that specific hyaluronidases have alternative substrates to hyaluronan (HA) or do not exhibit any enzymatic activity, (2) that high molecular weight HA polymers elicit signaling effects that are opposite those of the hyaluronidase-digested HA oligomers, and (3) that it is actually the combined overexpression of HA synthesizing enzymes with hyaluronidases that confers tumorigenic potential. This review examines the literature supporting these conclusions and discusses novel mechanisms by which hyaluronidases impact invasive tumor cell processes. In addition, a detailed structural and functional comparison of the hyaluronidases is presented with insights into substrate selectivity and potential for therapeutic targeting. Finally, technological advances in targeting hyaluronidase for tumor imaging and cancer therapy are summarized

    Adjuvant hyperthermic intraperitoneal chemotherapy (HIPEC) in patients with colon cancer at high risk of peritoneal carcinomatosis; the COLOPEC randomized multicentre trial

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    Background: The peritoneum is the second most common site of recurrence in colorectal cancer. Early detection of peritoneal carcinomatosis (PC) by imaging is difficult. Patients eventually presenting with clinically apparent PC have a poor prognosis. Median survival is only about five months if untreated and the benefit of palliative systemic chemotherapy is limited. Only a quarter of patients are eligible for curative treatment, consisting of cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CR/HIPEC). However, the effectiveness depends highly on the extent of disease and the treatment is associated with a considerable complication rate. These clinical problems underline the need for effective adjuvant therapy in high-risk patients to minimize the risk of outgrowth of peritoneal micro metastases. Adjuvant hyperthermic intraperitoneal chemotherapy (HIPEC) seems to be suitable for this purpose. Without the need for cytoreductive surgery, adjuvant HIPEC can be performed with a low complication rate and short hospital stay. Methods/Design: The aim of this study is to determine the effectiveness of adjuvant HIPEC in preventing the development of PC in patients with colon cancer at high risk of peritoneal recurrence. This study will be performed in the nine Dutch HIPEC centres, starting in April 2015. Eligible for inclusion are patients who underwent curative resection for T4 or intra-abdominally perforated cM0 stage colon cancer. After resection of the primary tumour, 176 patients will be randomized to adjuvant HIPEC followed by routine adjuvant systemic chemotherapy in the experimental arm, or to systemic chemotherapy only in the control arm. Adjuvant HIPEC will be performed simultaneously or shortly after the primary resection. Oxaliplatin will be used as chemotherapeutic agent, for 30 min at 42-43 degrees C. Just before HIPEC, 5-fluorouracil and leucovorin will be administered intravenously. Primary endpoint is peritoneal disease-free survival at 18 months. Diagnostic laparoscopy will be performed routinely after 18 months postoperatively in both arms of the study in patients without evidence of disease based on routine follow-up using CT imaging and CEA. Discussion: Adjuvant HIPEC is assumed to reduce the expected 25 % absolute risk of PC in patients with T4 or perforated colon cancer to a risk of 10 %. This reduction is likely to translate into a prolonged overall survival
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