106 research outputs found
The emergence of inequality in social groups: network structure and institutions affect the distribution of earnings in cooperation games
From small communities to entire nations and society at large, inequality in wealth, social status, and power is one of the most pervasive and tenacious features of the social world. What causes inequality to emerge and persist? In this study, we investigate how the structure and rules of our interactions can increase inequality in social groups. Specifically, we look into the effects of four structural conditions—network structure, network fluidity, reputation tracking, and punishment institutions—on the distribution of earnings in network cooperation games. We analyze 33 experiments comprising 96 experimental conditions altogether. We find that there is more inequality in clustered networks compared to random networks, in fixed networks compared to randomly rewired and strategically updated networks, and in groups with punishment institutions compared to groups without. Secondary analyses suggest that the reasons inequality emerges under these conditions may have to do with the fact that fixed networks allow exploitation of the poor by the wealthy and clustered networks foster segregation between the poor and the wealthy, while the burden of costly punishment falls onto the poor, leaving them poorer. Surprisingly, we do not find evidence that inequality is affected by reputation in a systematic way but this could be because reputation needs to play out in a particular network environment in order to have an effect. Overall, our findings suggest possible strategies and interventions to decrease inequality and mitigate its negative impact, particularly in the context of mid- and large-sized organizations and online communities
REST is a hypoxia-responsive transcriptional repressor
Cellular exposure to hypoxia results in altered gene expression in a range of physiologic and pathophysiologic states. Discrete cohorts of genes can be either up- or down-regulated in response to hypoxia. While the Hypoxia-Inducible Factor (HIF) is the primary driver of hypoxia-induced adaptive gene expression, less is known about the signalling mechanisms regulating hypoxia-dependent gene repression. Using RNA-seq, we demonstrate that equivalent numbers of genes are induced and repressed in human embryonic kidney (HEK293) cells. We demonstrate that nuclear localization of the Repressor Element 1-Silencing Transcription factor (REST) is induced in hypoxia and that REST is responsible for regulating approximately 20% of the hypoxia-repressed genes. Using chromatin immunoprecipitation assays we demonstrate that REST-dependent gene repression is at least in part mediated by direct binding to the promoters of target genes. Based on these data, we propose that REST is a key mediator of gene repression in hypoxia
Abatacept in individuals at high risk of rheumatoid arthritis (APIPPRA): a randomised, double-blind, multicentre, parallel, placebo-controlled, phase 2b clinical trial
\ua9 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Background: Individuals with serum antibodies to citrullinated protein antigens (ACPA), rheumatoid factor, and symptoms, such as inflammatory joint pain, are at high risk of developing rheumatoid arthritis. In the arthritis prevention in the pre-clinical phase of rheumatoid arthritis with abatacept (APIPPRA) trial, we aimed to evaluate the feasibility, efficacy, and acceptability of treating high risk individuals with the T-cell co-stimulation modulator abatacept. Methods: The APIPPRA study was a randomised, double-blind, multicentre, parallel, placebo-controlled, phase 2b clinical trial done in 28 hospital-based early arthritis clinics in the UK and three in the Netherlands. Participants (aged ≥18 years) at risk of rheumatoid arthritis positive for ACPA and rheumatoid factor with inflammatory joint pain were recruited. Exclusion criteria included previous episodes of clinical synovitis and previous use of corticosteroids or disease-modifying antirheumatic drugs. Participants were randomly assigned (1:1) using a computer-generated permuted block randomisation (block sizes of 2 and 4) stratified by sex, smoking, and country, to 125 mg abatacept subcutaneous injections weekly or placebo for 12 months, and then followed up for 12 months. Masking was achieved by providing four kits (identical in appearance and packaging) with pre-filled syringes with coded labels of abatacept or placebo every 3 months. The primary endpoint was the time to development of clinical synovitis in three or more joints or rheumatoid arthritis according to American College of Rheumatology and European Alliance of Associations for Rheumatology 2010 criteria, whichever was met first. Synovitis was confirmed by ultrasonography. Follow-up was completed on Jan 13, 2021. All participants meeting the intention-to-treat principle were included in the analysis. This trial was registered with EudraCT (2013–003413–18). Findings: Between Dec 22, 2014, and Jan 14, 2019, 280 individuals were evaluated for eligibility and, of 213 participants, 110 were randomly assigned to abatacept and 103 to placebo. During the treatment period, seven (6%) of 110 participants in the abatacept group and 30 (29%) of 103 participants in the placebo group met the primary endpoint. At 24 months, 27 (25%) of 110 participants in the abatacept group had progressed to rheumatoid arthritis, compared with 38 (37%) of 103 in the placebo group. The estimated proportion of participants remaining arthritis-free at 12 months was 92\ub78% (SE 2\ub76) in the abatacept group and 69\ub72% (4\ub77) in the placebo group. Kaplan–Meier arthritis-free survival plots over 24 months favoured abatacept (log-rank test p=0\ub7044). The difference in restricted mean survival time between groups was 53 days (95% CI 28–78; p<0\ub70001) at 12 months and 99 days (95% CI 38–161; p=0\ub70016) at 24 months in favour of abatacept. During treatment, abatacept was associated with improvements in pain scores, functional wellbeing, and quality-of-life measurements, as well as low scores of subclinical synovitis by ultrasonography, compared with placebo. However, the effects were not sustained at 24 months. Seven serious adverse events occurred in the abatacept group and 11 in the placebo group, including one death in each group deemed unrelated to treatment. Interpretation: Therapeutic intervention during the at-risk phase of rheumatoid arthritis is feasible, with acceptable safety profiles. T-cell co-stimulation modulation with abatacept for 12 months reduces progression to rheumatoid arthritis, with evidence of sustained efficacy beyond the treatment period, and with no new safety signals. Funding: Bristol Myers Squibb
Reproducible radiomics through automated machine learning validated on twelve clinical applications
Radiomics uses quantitative medical imaging features to predict clinical outcomes. Currently, in a new clinical application, findingthe optimal radiomics method out of the wide range of available options has to be done manually through a heuristic trial-anderror process. In this study we propose a framework for automatically optimizing the construction of radiomics workflows perapplication. To this end, we formulate radiomics as a modular workflow and include a large collection of common algorithms foreach component. To optimize the workflow per application, we employ automated machine learning using a random search andensembling. We evaluate our method in twelve different clinical applications, resulting in the following area under the curves: 1)liposarcoma (0.83); 2) desmoid-type fibromatosis (0.82); 3) primary liver tumors (0.80); 4) gastrointestinal stromal tumors (0.77);5) colorectal liver metastases (0.61); 6) melanoma metastases (0.45); 7) hepatocellular carcinoma (0.75); 8) mesenteric fibrosis(0.80); 9) prostate cancer (0.72); 10) glioma (0.71); 11) Alzheimer’s disease (0.87); and 12) head and neck cancer (0.84). Weshow that our framework has a competitive performance compared human experts, outperforms a radiomics baseline, and performssimilar or superior to Bayesian optimization and more advanced ensemble approaches. Concluding, our method fully automaticallyoptimizes the construction of radiomics workflows, thereby streamlining the search for radiomics biomarkers in new applications.To facilitate reproducibility and future research, we publicly release six datasets, the software implementation of our framework,and the code to reproduce this study
Ultrasound-assisted extraction of natural products
Ultrasound-assisted extraction (USAE) is an interesting process to obtain high valuable compounds and could contribute to the increase in the value of some food by-products when used as sources of natural compounds. The main benefits will be a more effective extraction, thus saving energy, and also the use of moderate temperatures, which is beneficial for heat-sensitive compounds. For a successful application of the USAE, it is necessary to consider the influence of several process variables, the main ones being the applied ultrasonic power, the frequency, the extraction temperature, the reactor characteristics, and the solvent-sample interaction. The highest extraction rate is usually achieved in the first few minutes, which is the most profitable period. To optimize the process, rate equations and unambiguous process characterization are needed, aspects that have often been lacking. © 2011 Springer Science+Business Media, LLC.The authors thank the Generalitat Valenciana for their financial support in project PROMETEO/2010/062 and the Caja de Ahorros del Mediterraneo for M.D. Esclapez's pre-doctoral grant.Esclapez Vicente, MD.; García Pérez, JV.; Mulet Pons, A.; Cárcel Carrión, JA.; Esclapez, MD. (2011). Ultrasound-assisted extraction of natural products. Food Engineering Reviews. 3(2):108-120. https://doi.org/10.1007/s12393-011-9036-6S10812032Abad Romero B, Bou-Maroun E, Reparet JM, Blanquet J, Cayot N (2010) Impact of lipid extraction on the dearomatisation of an Eisenia foetida protein powder. Food Chem 119:459–466Adewuyi YG (2001) Sonochemistry: environmental science and engineering applications. Ind Eng Chem Res 40:4681–4715Atchley AA, Crum LA (1988) Acoustic cavitation and bubble dynamics. In: Suslick KS (ed) Ultrasound, its chemical, physical, and biological effects. VHS Publishers, Weinheim, pp 1–64Arnold G, Leiteritz L, Zahn S, Rohm H (2009) Ultrasonic cutting of cheese: composition affects cutting work reduction and energy demand. Int Dairy J 19:314–320Barbero GF, Liazid A, Palma M, Barroso CG (2008) Ultrasound-assisted extraction of capsaicinoids from peppers. Talanta 75:1332–1337Benedito J, Carcel JA, Sanjuan N, Mulet A (2000) Use of ultrasound to assess Cheddar cheese characteristics. Ultrasonics 38:727–730Benedito J, Carcel JA, Rossello C, Mulet A (2001) Composition assessment of raw meat mixtures using ultrasonics. Meat Sci 57:365–370Bhaskaracharya RK, Kentish S, Ashokkumar M (2009) Selected applications of ultrasonics in food processing. Food Eng Rev 1:31–49Boonkird S, Phisalaphong C, Phisalaphong M (2008) Ultrasound-assisted extraction of capsaicinoids from Capsicum frutescens on a lab- and pilot-plant scale. Ultrason Sonochem 15:1075–1079Cárcel JA, Benedito J, Bon J, Mulet A (2007) High intensity ultrasound effects on meat brining. Meat Sci 76:611–619Cárcel JA, Benedito J, Rosselló C, Mulet A (2007) Influence of ultrasound intensity on mass transfer in apple immersed in a sucrose solution. J Food Eng 78:472–479Cavitus (2009) Grape colour and flavour extraction (Pat. Pend.) for red must extraction http://www.cavitus.com . Crafers. Accessed 10 Jan 2011Chea Chua S, Ping Tan C, Mirhosseini H, Ming Lai O, Long K, Sham Baharin B (2009) Optimization of ultrasound extraction condition of phospholipids from palm-pressed fiber. J Food Eng 92:403–409Chena R, Menga F, Zhang S, Liu Z (2009) Effects of ultrahigh pressure extraction conditions on yields and antioxidant activity of ginsenoside from ginseng. Sep Purif Technol 66:340–346Chivate MM, Pandit AB (1995) Quantification of cavitation intensity in fluid bulk. Ultrason Sonochem 2:19–25Da Porto C, Decorti D (2009) Ultrasound-assisted extraction coupled with under vacuum distillation of flavour compounds from spearmint (carvone-rich) plants: comparison with conventional hydrodistillation. Ultrason Sonochem 16:795–799Da Porto C, Decorti D, Kikic I (2009) Flavour compounds of Lavandula angustifolia L. to use in food manufacturing: Comparison of three different extraction methods. Food Chem 112:1072–1078Domínguez H, Núñez MJ, Lema JM (1994) Enzymatic pretreatment to enhance oil extraction from fruits and oilseeds: a review. Food Chem 49:271–286Dong J, Liu Y, Liang Z, Wanga W (2010) Investigation on ultrasound-assisted extraction of salvianolic acid B from Salvia miltiorrhiza root. Ultrason Sonochem 17:61–65Entezari MH, Kruus P (1994) Effect of frequency on sonochemical reactions. I: oxidation of iodide. Ultrason Sonochem 1:75–79Esclapez MD, Sáez V, Milán-Yáñez D, Tudela I, Louisnard O, González-García J (2010) Sonoelectrochemical treatment of water polluted with trichloroacetic acid: from sonovoltammetry to pre-pilot plant scale. Ultrason Sonochem 17:1010–1020Ferraro V, Cruz IB, Ferreira R, Malcata JFX, Pintado ME, Castro PML (2010) Valorisation of natural extracts from marine source focused on marine by-products: review. Food Res Int 43:2221–2233Fischer CH, Hart EJ, Henglein AJ (1986) Hydrogen/deuterium isotope exchange in the hydrogen deuteride-water system under the influence of ultrasound. Phys Chem 90:3059–3060Garcia-Noguera J, Weller CL, Oliveira FIP, Rodrigues S, Fernandes FAN (2010) Dual-stage sugar substitution in strawberries with a Stevia-based sweetener. Innovative Food Sci Emerg Technol 11:225–230García-Pérez JV, Cárcel JA, de la Fuente-Blanco S, Riera-Franco de Sarabia E (2006) Ultrasonic drying of foodstuff in a fluidized bed: parametric study. Ultrasonics 44:539–543García-Pérez JV, García-Alvarado MA, Carcel JA, Mulet A (2010) Extraction kinetics modeling of antioxidants from grape stalk (Vitis vinifera var. Bobal): Influence of drying conditions. J Food Eng 101:49–58González-García J, Sáez V, Tudela I, Díez-Garcia MI, Esclapez MD, Louisnard O (2010) Sonochemical treatment of water polluted by chlorinated organocompounds. A review. Water 2:28–74Handa SS, Preet S, Khanuja S, Longo G, Rakesh DD (2008) Extraction Technologies for Medicinal and Aromatic Plants. United Nations Industrial Development Organization and the International Centre for Science and High Technology, TriesteHemwimol S, Pavasant P, Shotipruk A (2006) Ultrasound-assisted extraction of anthraquinones from roots of Morinda citrifolia. Ultrason Sonochem 13:543–548Hielscher (2011) Teltow http:// www.hielscher.com . Accessed 10 Jan 2011Hu Y, Wang T, Wang M, Han S, Wan P, Fan M (2008) Extraction of isoflavonoids from Pueraria by combining ultrasound with microwave vacuum. Chem Engin Process 47:2256–2261Ince NH, Tezcanli G, Belen RK, Apikyan PG (2001) Ultrasound as a catalyzer of aqueous reaction systems: the state of the art and environmental applications. Appl Catal B 29:167–176Jadhav D, Rekha BN, Gogate PR, Rathod VK (2009) Extraction of vanillin from vanilla pods: a comparison study of conventional soxhlet and ultrasound assisted extraction. J Food Eng 93:421–426Ji J-b, Lu X-h, Cai M-q, Xu C-c (2006) Improvement of leaching process of Geniposide with ultrasound. Ultrason Sonochem 13:455–462Kanthale PM, Gogate PR, Pandit AB, Wilhelm AM (2003) Mapping of an ultrasonic horn: link primary and secondary effects of ultrasound. Ultrason Sonochem 10:331–335Karki B, Lamsal BP, Jung S, van Leeuwen JH, Pometto AL III, Grewell D, Khanal SK (2010) Enhancing protein and sugar release from defatted soy flakes using ultrasound technology. J Food Eng 96:270–278Kardos N, Luche J-L (2001) Sonochemistry of carbohydrate compounds. Carbohydr Res 332:115–131Kotronarou A, Mills G, Hoffmann MR (1991) Ultrasonic Irradiation of para-Nitrophenol in Aqueous Solution. J Phys Chem 95:3630–3638Kuijpers MWA, Kemmere MF, Keurentjes JTF (2002) Calorimetric study of the energy efficiency for ultrasound-induced radical formation. Ultrasonics 40:675–678Leighton TG (2007) What is ultrasound? Prog Biophys Mol Biol 93:3–83Leonelli C, Mason TJ (2010) Microwave and ultrasonic processing: now a realistic option for industry. Chem Eng Process 49:885–900Li H, Pordesimo L, Weiss J (2004) High intensity ultrasound-assisted extraction of oil from soybeans. Food Res Int 37:731–738Liu J, Li J-W, Tang J (2010) Ultrasonically assisted extraction of total carbohydrates from Stevia rebaudiana Bertoni and identification of extracts. Food Bioprod Process 88:215–221Lianfu Z, Zelong L (2008) Optimization and comparison of ultrasound/microwave assisted extraction (UMAE) and ultrasonic assisted extraction (UAE) of lycopene from tomatoes. Ultrason Sonochem 15:731–737Liazid A, Schwarz M, Varela RM, Palma M, Guillén DA, Brigui J, Macías FA, Barroso CG (2010) Evaluation of various extraction techniques for obtaining bioactive extracts from pine seeds. Food Bioprod Process 88:247–252Londoño-Londoño J, Rodrigues de Lima V, Lara O, Gil A, Crecsynski Pasa TB, Arango GJ, Ramirez Pineda JR (2010) Clean recovery of antioxidant flavonoids from citrus peel: optimizing an aqueous ultrasound-assisted extraction method. Food Chem 119:81–87Lou Z, Wang H, Zhang M, Wang Z (2010) Improved extraction of oil from chickpea under ultrasound in a dynamic system. J Food Eng 98:13–18Louisnard O, González-García J, Tudela I, Klima J, Sáez V, Vargas-Hernández Y (2009) FEM simulation of a sono-reactor accounting for vibrations of the boundaries. Ultrason Sonochem 16:250–259Luque de Castro MD, Priego-Capote F (2007) Analytical Applications of Ultrasound, Vol. 26, Techniques and Instrumentation in Analytical Chemistry. Elsevier Science, AmsterdamMa Y, Ye X, Hao Y, Xu G, Xu G, Liu D (2008) Ultrasound-assisted extraction of hesperidin from Penggan (Citrus reticulata) peel. Ultrason Sonochem 15:227–232Ma Y, Chen J-C, Liu Dong-Hong, Ye X-Q (2009) Simultaneous extraction of phenolic compounds of citrus peel extracts: effect of ultrasound. Ultrason Sonochem 16:57–62Makino K, Mossoba MM, Riesz P (1982) Chemical effects of ultrasound on aqueous solutions. Evidence for hydroxyl and hydrogen free radicals (.cntdot. OH and. cntdot. H) by spin trapping. J Chem Soc 104:3537–3539Margulis MA, Margulis IM (2003) Calorimetric method for measurement of acoustic power absorbed in a volume of liquid. Ultrason Sonochem 10:343–345Martin CJ, Law ANR (1983) Design of thermistor probes for measurement of ultrasound intensity distributions. Ultrasonics 21:85–90Mason TJ, Lorimer JP, Bates DM, Zhao Y (1994) Dosimetry in sonochemistry: the use of aqueous terephthalate ion as a fluorescence monitor. Ultrason Sonochem 1:91–95Meinhardt (2011) Leipzig. http://www.meinhardt-ultraschall.de . Accessed 10 Jan 2011Montalbo-Lomboy M, Khanal SK, van Leeuwen JH, Raman DR, Dunn L Jr, Grewell D Jr (2010) Ultrasonic pretreatment of corn slurry for saccharification: a comparison of batch and continuous Systems. Ultrason Sonochem 17:939–946Mulet A, Cárcel JA, Sanjuán N, Bon J (2003) New food drying technologies. Use of ultrasound. Food Sci Technol Int 9:215–221Naguleswaran S, Vasanthan T (2010) Dry milling of field pea (Pisum sativum L.) groats prior to wet fractionation influences the starch yield and purity. Food Chem 118:627–633Orozco-Solano M, Ruiz-Jiménez J, Luque de Castro MD (2010) Ultrasound-assisted extraction and derivatization of sterols and fatty alcohols from olive leaves and drupes prior to determination by gas chromatography–tandem mass spectrometry. J Chromatogr A 1217:1227–1235Patist A, Bates D (2008) Ultrasonic innovations in the food industry: from the laboratory to commercial production. Innovative Food Sci Emerg Technol 9:147–154Price GJ (1990) The use of ultrasound for the controlled degradation of polymer solutions. In: Mason TJ (ed) Advances in sonochemistry, vol 1. Jai Press, Cambridge, pp 231–287Riener J, Noci G, Cronin DA, Morgan DJ, Lyng JG (2010) A comparison of selected quality characteristics of yoghurts prepared from thermosonicated and conventionally heated milks. Food Chem 119:1108–1113Riera E, Golás Y, Blanco A, Gallego JA, Blasco M, Mulet A (2004) Mass transfer enhancement in supercritical fluids extraction by means of power ultrasound. Ultrason Sonochem 11:241–244Riera E, Blanco A, García J, Benedito J, Mulet A, Gallego-Juárez JA, Blasco M (2010) High-power ultrasonic system for the enhancement of mass transfer in supercritical CO2 extraction processes. Physics Procedia 3:141–146Roldán-Gutiérrez JM, Ruiz-Jiménez J, Luque de Castro MD (2008) Ultrasound-assisted dynamic extraction of valuable compounds from aromatic plants and flowers as compared with steam distillation and superheated liquid extraction. Talanta 75:1369–1375Romdhane M, Gourdon C (2002) Investigation in solid–liquid extraction: influence of ultrasound. Chem Eng J 87:11–19Rong L, Kojima Y, Koda S, Nomura H (2008) Simple quantification of ultrasonic intensity using aqueous solution of phenolphthalein. Ultrason Sonochem 8:11–15Sáez V, Frias-Ferrer A, Iniesta J, Gonzalez-Garcıa J, Aldaz A, Riera E (2005) Chacterization of a 20 kHz sonoreactor. Part I: analysis of mechanical effects by classical and numerical methods. Ultrason Sonochem 12:59–65Sáez V, Frias-Ferrer A, Iniesta J, Gonzalez-Garcıa J, Aldaz A, Riera E (2005) Characterization of a 20 kHz sonoreactor. Part II: analysis of chemical effects by classical and electrochemical methods. Ultrason Sonochem 12:67–72Sahena F, Zaidul ISM, Jinap S, Karim AA, Abbas KA, Norulaini NAN, Omar AKM (2009) Application of supercritical CO2 in lipid extraction–A review. J Food Eng 95:240–253Science Direct Database (2011) www.sciencedirect.com (Data of consulting: February 2011)Soria AC, Villamiel M (2010) Effect of ultrasound on the technological properties and bioactivity of food: a review. Trends Food Sci Technol 21:323–331Starmans DAJ, Nijhuis HH (1996) Extraction of secondary metabolites from plant material: a review. Trends Food Sci Technol 7:191–197Sivakumar V, Lakshmi Anna J, Vijayeeswarri J, Swaminathan G (2009) Ultrasound assisted enhancement in natural dye extraction from beetroot for industrial applications and natural dyeing of leather. Ultrason Sonochem 16:782–789Stanisavljevic IT, Lazic ML, Veljkovic VB (2007) Ultrasonic extraction of oil from tobacco (Nicotiana tabacum L.) seeds. Ultrason Sonochem 14:646–652Sun Y, Liu D, Chen J, Ye X, Yu D (2011) Effects of different factors of ultrasound treatment on the extraction yield of the all-trans-b-carotene from citrus peels. Ultrason Sonochem 18:243–249Suslick KS (2001) Sonoluminescence and sonochemistry. In: Meyers RA (ed) Encyclopedia of physical science and technology, vol 17, 3rd edn. Academic Press, San Diego, pp 363–376Trabelsi F, Ait-Iyazidi H, Berlan J, Fabre PL, Delmas H, Wilhelm AM (1996) Electrochemical determination of the active zones in a high-frequency ultrasonic reactor. Ultrason Sonochem 3:125–130Veillet S, Tomao V, Chemat F (2010) Ultrasound assisted maceration: an original procedure for direct aromatisation of olive oil with basil. Food Chem 123:905–911Velickovic DT, Milenovic DM, Ristic MS, Veljkovic VB (2008) Ultrasonic extraction of waste solid residues from the Salvia sp. Essential oil hydrodistillation. Biochem Eng J 42:97–104Vercet A, Burgos J, Crelier S, Lopez-Buesa P (2001) Inactivation of proteases and lipases by ultrasound. Innovative Food Sci Emerg Technol 2:139–150Vilkhu K, Mawson R, Simons L, Bates D (2008) Applications and opportunities for ultrasound assisted extraction in the food industry—A review. Innovative Food Sci Emerg Technol 9:161–169Vinatoru M (2001) An overview of the ultrasonically assisted extraction of bioactive principles from herbs. Ultrason Sonochem 8:303–313Virot M, Tomao V, Le Bourvellec C, Renard CMCG, Chemat F (2010) Towards the industrial production of antioxidants from food processing by-products with ultrasound-assisted extraction. Ultrason Sonochem 17:1066–1074Wang J, Sun B, Cao Y, Tian Y, Li X (2008) Optimisation of ultrasound-assisted extraction of phenolic compounds from wheat bran. Food Chem 106:804–810Wang L, Weller CL (2006) Recent advances in extraction of nutraceuticals from plants. Trends Food Sci Technol 17:300–312Wei X, Chen M, Xiao Ja, Liu Y, Yu L, Zhang H, Wang Y (2010) Composition and bioactivity of tea flower polysaccharides obtained by different methods. Carbohydr Polym 79:418–422Weissler A, Cooper HW, Snyder S (1950) Chemical effects of ultrasonic waves: oxidation of potassium iodide solution by carbon tetrachloride. J Am Chem Soc 72:1769–1775Wulff-Pérez M, Torcello-Gómez A, Gálvez-Ruíz MJ, Martín-Rodríguez A (2009) Stability of emulsions for parenteral feeding: preparation and characterization of o/w nanoemulsions with natural oils and Pluronic f68 as surfactant. Food Hydrocolloids 23:1096–1102Yang B, Yang H, Li J, Li Z, Jiang Y (2011) Amino acid composition, molecular weight distribution and antioxidant activity of protein hydrolysates of soy sauce lees. Food Chem 124:551–555Yang Y, Zhang F (2008) Ultrasound-assisted extraction of rutin and quercetin from Euonymus alatus (Thunb.) Sieb. Ultrason Sonochem 15:308–313Zhang Z-S, Wang L-J, Li D, Jiao S-S, Chena XD, Maoa Z-H (2008) Ultrasound-assisted extraction of oil from flaxseed. Sep Purif Technol 62:192–198Zhang H-F, Yang X-H, Zhao L-D, Wang Y (2009) Ultrasonic-assisted extraction of epimedin C from fresh leaves of Epimedium and extraction mechanism. Innovative Food Sci Emerg Technol 10:54–60Zhang Q-A, Zhang Z-Q, Yue X-F, Fan X-H, Li T, Chen S-F (2009) Response surface optimization of ultrasound-assisted oil extraction from autoclaved almond powder. Food Chem 116:513–518Zhao S, Kwok K-C, Liang H (2007) Investigation on ultrasound assisted extraction of saikosaponins from Radix Bupleuri. Sep Purif Technol 55:307–312Zhu KX, Sun X-H, Zhou H-M (2009) Optimization of ultrasound-assisted extraction of defatted wheat germ proteins by reverse micelles. J Cereal Sci 50:266–271Zheng L, Sun D-W (2006) Innovative applications of power ultrasound during food freezing processes—a review. Trends Food Sci Technol 17:16–23Zou Y, Xie C, Fan G, Gu Z, Han Y (2010) Optimization of ultrasound-assisted extraction of melanin from Auricularia auricula fruit bodies. Innovative Food Sci Emerg Technol 11:611–61
Semi-Automated Image Analysis for the Assessment of Megafaunal Densities at the Arctic Deep-Sea Observatory HAUSGARTEN
Megafauna play an important role in benthic ecosystem function and are sensitive indicators of environmental change. Non-invasive monitoring of benthic communities can be accomplished by seafloor imaging. However, manual quantification of megafauna in images is labor-intensive and therefore, this organism size class is often neglected in ecosystem studies. Automated image analysis has been proposed as a possible approach to such analysis, but the heterogeneity of megafaunal communities poses a non-trivial challenge for such automated techniques. Here, the potential of a generalized object detection architecture, referred to as iSIS (intelligent Screening of underwater Image Sequences), for the quantification of a heterogenous group of megafauna taxa is investigated. The iSIS system is tuned for a particular image sequence (i.e. a transect) using a small subset of the images, in which megafauna taxa positions were previously marked by an expert. To investigate the potential of iSIS and compare its results with those obtained from human experts, a group of eight different taxa from one camera transect of seafloor images taken at the Arctic deep-sea observatory HAUSGARTEN is used. The results show that inter- and intra-observer agreements of human experts exhibit considerable variation between the species, with a similar degree of variation apparent in the automatically derived results obtained by iSIS. Whilst some taxa (e. g. Bathycrinus stalks, Kolga hyalina, small white sea anemone) were well detected by iSIS (i. e. overall Sensitivity: 87%, overall Positive Predictive Value: 67%), some taxa such as the small sea cucumber Elpidia heckeri remain challenging, for both human observers and iSIS
Semi-Automated Image Analysis for the Assessment of Megafaunal Densities at the Arctic Deep-Sea Observatory HAUSGARTEN
Megafauna play an important role in benthic ecosystem function and are sensitive indicators of environmental change. Non-invasive monitoring of benthic communities can be accomplished by seafloor imaging. However, manual quantification of megafauna in images is labor-intensive and therefore, this organism size class is often neglected in ecosystem studies. Automated image analysis has been proposed as a possible approach to such analysis, but the heterogeneity of megafaunal communities poses a non-trivial challenge for such automated techniques. Here, the potential of a generalized object detection architecture, referred to as iSIS (intelligent Screening of underwater Image Sequences), for the quantification of a heterogenous group of megafauna taxa is investigated. The iSIS system is tuned for a particular image sequence (i.e. a transect) using a small subset of the images, in which megafauna taxa positions were previously marked by an expert. To investigate the potential of iSIS and compare its results with those obtained from human experts, a group of eight different taxa from one camera transect of seafloor images taken at the Arctic deep-sea observatory HAUSGARTEN is used. The results show that inter- and intra-observer agreements of human experts exhibit considerable variation between the species, with a similar degree of variation apparent in the automatically derived results obtained by iSIS. Whilst some taxa (e. g. Bathycrinus stalks, Kolga hyalina, small white sea anemone) were well detected by iSIS (i. e. overall Sensitivity: 87%, overall Positive Predictive Value: 67%), some taxa such as the small sea cucumber Elpidia heckeri remain challenging, for both human observers and iSIS
Combining techniques for screening and evaluating interaction terms on high-dimensional time-to-event data
Synthesis and X-ray analysis of 1-((1S)-phenylethyl)-azetidine-(2R)-piperidinamide
Contains fulltext :
29134.pdf (publisher's version ) (Open Access
- …