Method of moments enhancement technique for the analysis of Sierpinski pre-fractal antennas

The numerical analysis of highly iterated Sierpinski microstrip patch antennas by method of moments (MoM) involves many tiny subdomain basis functions, resulting in a very large number of unknowns. The Sierpinski pre-fractal can be defined by an iterated function system (IFS). As a consequence, the geometry has a multilevel structure with many equal subdomains. This property, together with a multilevel matrix decomposition algorithm (MLMDA) implementation in which the MLMDA blocks are equal to the IFS generating shape, is used to reduce the computational cost of the frequency analysis of a Sierpinski based structure.Peer Reviewe

Marine Microalgae: Climate, Energy, and Food Security From the Sea

Climate, energy, and food security are three of the greatest challenges society faces this century. Solutions for mitigating the effects of climate change often conflict with solutions for ensuring society’s future energy and food requirements. For example, BioEnergy with Carbon Capture and Storage (BECCS) has been proposed as an important method for achieving negative CO2 emissions later this century while simultaneously producing renewable energy on a global scale. However, BECCS has many negative environmental consequences for land, nutrient, and water use as well as biodiversity and food production. In contrast, large-scale industrial cultivation of marine microalgae can provide society with a more environmentally favorable approach for meeting the climate goals agreed to at the 2015 Paris Climate Conference, producing the liquid hydrocarbon fuels required by the global transportation sector, and supplying much of the protein necessary to feed a global population approaching 10 billion people

CamTrapAsia: a dataset of tropical forest vertebrate communities from 239 camera trapping studies

Information on tropical Asian vertebrates has traditionally been sparse, particularly when it comes to cryptic species inhabiting the dense forests of the region. Vertebrate populations are declining globally due to land-use change and hunting, the latter frequently referred as “defaunation.” This is especially true in tropical Asia where there is extensive land-use change and high human densities. Robust monitoring requires that large volumes of vertebrate population data be made available for use by the scientific and applied communities. Camera traps have emerged as an effective, non-invasive, widespread, and common approach to surveying vertebrates in their natural habitats. However, camera-derived datasets remain scattered across a wide array of sources, including published scientific literature, gray literature, and unpublished works, making it challenging for researchers to harness the full potential of cameras for ecology, conservation, and management. In response, we collated and standardized observations from 239 camera trap studies conducted in tropical Asia. There were 278,260 independent records of 371 distinct species, comprising 232 mammals, 132 birds, and seven reptiles. The total trapping effort accumulated in this data paper consisted of 876,606 trap nights, distributed among Indonesia, Singapore, Malaysia, Bhutan, Thailand, Myanmar, Cambodia, Laos, Vietnam, Nepal, and far eastern India. The relatively standardized deployment methods in the region provide a consistent, reliable, and rich count data set relative to other large-scale pressence-only data sets, such as the Global Biodiversity Information Facility (GBIF) or citizen science repositories (e.g., iNaturalist), and is thus most similar to eBird. To facilitate the use of these data, we also provide mammalian species trait information and 13 environmental covariates calculated at three spatial scales around the camera survey centroids (within 10-, 20-, and 30-km buffers). We will update the dataset to include broader coverage of temperate Asia and add newer surveys and covariates as they become available. This dataset unlocks immense opportunities for single-species ecological or conservation studies as well as applied ecology, community ecology, and macroecology investigations. The data are fully available to the public for utilization and research. Please cite this data paper when utilizing the data

Use of 1H and 31P HRMAS to evaluate the relationship between quantitative alterations in metabolite concentrations and tissue features in human brain tumour biopsies

[EN] Quantitative multinuclear high-resolution magic angle spinning (HRMAS) was performed in order to determine the tissue pH values of and the absolute metabolite concentrations in 33 samples of human brain tumour tissue. Metabolite concentrations were quantified by 1D 1 H and 31P HRMAS using the electronic reference to in vivo concentrations (ERETIC) synthetic signal. 1 H–1 H homonuclear and 1 H–31P heteronuclear correlation experiments enabled the direct assessment of the 1 H–31P spin systems for signals that suffered from overlapping in the 1D 1 H spectra, and linked the information present in the 1D 1 H and 31P spectra. Afterwards, the main histological features were determined, and high heterogeneity in the tumour content, necrotic content and nonaffected tissue content was observed. The metabolite profiles obtained by HRMAS showed characteristics typical of tumour tissues: rather low levels of energetic molecules and increased concentrations of protective metabolites. Nevertheless, these characteristics were more strongly correlated with the total amount of living tissue than with the tumour cell contents of the samples alone, which could indicate that the sampling conditions make a significant contribution aside from the effect of tumour development in vivo. The use of methylene diphosphonic acid as a chemical shift and concentration reference for the 31P HRMAS spectra of tissues presented important drawbacks due to its interaction with the tissue. Moreover, the pH data obtained from 31P HRMAS enabled us to establish a correlation between the pH and the distance between the N(CH3)3 signals of phosphocholine and choline in 1 H spectra of the tissue in these tumour samples.The authors acknowledge the SCSIE-University of Valencia Microscopy Service for the histological preparations. They also acknowledge Martial Piotto (Bruker BioSpin, France) for providing the ERETIC synthetic signal. Furthermore, they acknowledge financial support from the Spanish Government project SAF2007-6547, the Generalitat Valenciana project GVACOMP2009-303, and the E.U.'s VI Framework Programme via the project "Web accessible MR decision support system for brain tumor diagnosis and prognosis, incorporating in vivo and ex vivo genomic and metabolomic data" (FP6-2002-LSH 503094). CIBER-BBN is an initiative funded by the VI National R&D&D&i Plan 2008-2011, Iniciativa Ingenio 2010, Consolider Program, CIBER Actions, and financed by the Instituto de Salud Carlos III with assistance from the European Regional Development Fund.Esteve Moya, V.; Celda, B.; Martínez Bisbal, MC. (2012). Use of 1H and 31P HRMAS to evaluate the relationship between quantitative alterations in metabolite concentrations and tissue features in human brain tumour biopsies. Analytical and Bioanalytical Chemistry. 403:2611-2625. https://doi.org/10.1007/s00216-012-6001-zS26112625403Cheng LL, Chang IW, Louis DN, Gonzalez RG (1998) Cancer Res 58:1825–1832Opstad KS, Bell BA, Griffiths JR, Howe FA (2008) Magn Reson Med 60:1237–1242Sjobakk TE, Johansen R, Bathen TF, Sonnewald U, Juul R, Torp SH, Lundgren S, Gribbestad IS (2008) NMR Biomed 21:175–185Martinez-Bisbal MC, Marti-Bonmati L, Piquer J, Revert A, Ferrer P, Llacer JL, Piotto M, Assemat O, Celda B (2004) NMR Biomed 17:191–205Erb G, Elbayed K, Piotto M, Raya J, Neuville A, Mohr M, Maitrot D, Kehrli P, Namer IJ (2008) Magn Reson Med 59:959–965Wilson M, Davies NP, Brundler MA, McConville C, Grundy RG, Peet AC (2009) Mol Cancer 8:6Martinez-Bisbal MC, Monleon D, Assemat O, Piotto M, Piquer J, Llacer JL, Celda B (2009) NMR Biomed 22:199–206Martínez-Granados B, Monleón D, Martínez-Bisbal MC, Rodrigo JM, del Olmo J, Lluch P, Ferrández A, Martí-Bonmatí L, Celda B (2006) NMR Biomed 19:90–100Hubesch B, Sappey-Marinier D, Roth K, Meyerhoff DJ, Matson GB, Weiner MW (1990) Radiology 174:401–409Albers MJ, Krieger MD, Gonzalez-Gomez I, Gilles FH, McComb JG, Nelson MD Jr, Bluml S (2005) Magn Reson Med 53:22–29Wijnen JP, Scheenen TW, Klomp DW, Heerschap A (2010) NMR Biomed 23:968–976Podo F (1999) NMR Biomed 12:413–439Griffiths JR, Cady E, Edwards RH, McCready VR, Wilkie DR, Wiltshaw E (1983) Lancet 1:1435–1436Robitaille PL, Robitaille PA, Gordon Brown G, Brown GG (1991) J Magn Reson 92:73–84, 1969Griffiths JR (1991) Br J Cancer 64:425–427Payne GS, Troy H, Vaidya SJ, Griffiths JR, Leach MO, Chung YL (2006) NMR Biomed 19:593–598De Silva SS, Payne GS, Thomas V, Carter PG, Ind TE, deSouza NM (2009) NMR Biomed 22:191–198Wang Y, Cloarec O, Tang H, Lindon JC, Holmes E, Kochhar S, Nicholson JK (2008) Anal Chem 80:1058–1066Lehnhardt FG, Rohn G, Ernestus RI, Grune M, Hoehn M (2001) NMR Biomed 14:307–317Srivastava NK, Pradhan S, Gowda GA, Kumar R (2010) NMR Biomed 23:113–122Akoka S, Barantin L, Trierweiler M (1999) Anal Chem 71:2554–2557Albers MJ, Butler TN, Rahwa I, Bao N, Keshari KR, Swanson MG, Kurhanewicz J (2009) Magn Reson Med 61:525–532Ben Sellem D, Elbayed K, Neuville A, Moussallieh FM, Lang-Averous G, Piotto M, Bellocq JP, Namer IJ (2011) J Oncol 2011:174019Bourne R, Dzendrowskyj T, Mountford C (2003) NMR Biomed 16:96–101Martinez-Bisbal MC, Esteve V, Martinez-Granados B, Celda B (2011) J Biomed Biotechnol 2011:763684, Epub 2010 Sep 5Celda B, Montelione GT (1993) J Magn Reson B 101:189–193Esteve V, Celda B (2008) Magn Reson Mater Phys MAGMA 21:484–484Collins TJ (2007) Biotechniques 43:25–30Govindaraju V, Young K, Maudsley AA (2000) NMR Biomed 13:129–153Fan TW-M (1996) Prog Nucl Magn Reson Spectrosc 28:161–219Ulrich EL, Akutsu H, Doreleijers JF, Harano Y, Ioannidis YE, Lin J, Livny M, Mading S, Maziuk D, Miller Z, Nakatani E, Schulte CF, Tolmie DE, Kent Wenger R, Yao H, Markley JL (2008) Nucleic Acids Res 36:D402–D408Kriat M, Vion-Dury J, Confort-Gouny S, Favre R, Viout P, Sciaky M, Sari H, Cozzone PJ (1993) J Lipid Res 34:1009–1019Subramanian A, Shankar Joshi B, Roy AD, Roy R, Gupta V, Dang RS (2008) NMR Biomed 21:272–288Daykin CA, Corcoran O, Hansen SH, Bjornsdottir I, Cornett C, Connor SC, Lindon JC, Nicholson JK (2001) Anal Chem 73:1084–1090Griffin JL, Lehtimaki KK, Valonen PK, Grohn OH, Kettunen MI, Yla-Herttuala S, Pitkanen A, Nicholson JK, Kauppinen RA (2003) Cancer Res 63:3195–3201Petroff OAC, Prichard JW (1995) In: Kraicer J, Dixon SJ (eds) Methods in neurosciences. Academic, San DiegoBarton S, Howe F, Tomlins A, Cudlip S, Nicholson J, Anthony Bell B, Griffiths J (1999) Magn Reson Mater Phys Biol Med 8:121–128Sitter B, Sonnewald U, Spraul M, Fjosne HE, Gribbestad IS (2002) NMR Biomed 15:327–337Coen M, Hong YS, Cloarec O, Rhode CM, Reily MD, Robertson DG, Holmes E, Lindon JC, Nicholson JK (2007) Anal Chem 79:8956–8966Russell D, Rubinstein LJ (1998) Russel and Rubinstein's pathology of tumors of the nervous system. Arnold, LondonTynkkynen T, Tiainen M, Soininen P, Laatikainen R (2009) Anal Chim Acta 648:105–112Kjaergaard M, Brander S, Poulsen F (2011) J Biomol NMR 49:139–149Robert O, Sabatier J, Desoubzdanne D, Lalande J, Balayssac S, Gilard V, Martino R, Malet-Martino M (2011) Anal Bioanal Chem 399:987–999Chadzynski GL, Bender B, Groeger A, Erb M, Klose U (2011) J Magn Reson 212:55–63Weljie AM, Jirik FR (2011) Int J Biochem Cell Biol 43:981–989Barba I, Cabanas ME, Arus C (1999) Cancer Res 59:1861–1868Liimatainen T, Hakumaki JM, Kauppinen RA, Ala-Korpela M (2009) NMR Biomed 22:272–279Opstad KS, Bell BA, Griffiths JR, Howe FA (2008) NMR Biomed 21:677–685Schmitz JE, Kettunen MI, Hu D, Brindle KM (2005) Magn Reson Med 54:43–50Glunde K, Artemov D, Penet MF, Jacobs MA, Bhujwalla ZM (2010) Chem Rev 110:3043–3059Hertz L (2008) Neuropharmacology 55:289–309Takahashi T, Otsuguro K, Ohta T, Ito S (2010) Br J Pharmacol 161:1806–181

Pangolins in global camera trap data: Implications for ecological monitoring

Despite being heavily exploited, pangolins (Pholidota: Manidae) have been subject to limited research, resulting in a lack of reliable population estimates and standardised survey methods for the eight extant species. Camera trapping represents a unique opportunity for broad-scale collaborative species monitoring due to its largely non-discriminatory nature, which creates considerable volumes of data on a relatively wide range of species. This has the potential to shed light on the ecology of rare, cryptic and understudied taxa, with implications for conservation decision-making. We undertook a global analysis of available pangolin data from camera trapping studies across their range in Africa and Asia. Our aims were (1) to assess the utility of existing camera trapping efforts as a method for monitoring pangolin populations, and (2) to gain insights into the distribution and ecology of pangolins. We analysed data collated from 103 camera trap surveys undertaken across 22 countries that fell within the range of seven of the eight pangolin species, which yielded more than half a million trap nights and 888 pangolin encounters. We ran occupancy analyses on three species (Sunda pangolin Manis javanica, white-bellied pangolin Phataginus tricuspis and giant pangolin Smutsia gigantea). Detection probabilities varied with forest cover and levels of human influence for P. tricuspis, but were low (<0.05) for all species. Occupancy was associated with distance from rivers for M. javanica and S. gigantea, elevation for P. tricuspis and S. gigantea, forest cover for P. tricuspis and protected area status for M. javanica and P. tricuspis. We conclude that camera traps are suitable for the detection of pangolins and large-scale assessment of their distributions. However, the trapping effort required to monitor populations at any given study site using existing methods appears prohibitively high. This may change in the future should anticipated technological and methodological advances in camera trapping facilitate greater sampling efforts and/or higher probabilities of detection. In particular, targeted camera placement for pangolins is likely to make pangolin monitoring more feasible with moderate sampling efforts

Pangolins in Global Camera Trap Data: Implications for Ecological Monitoring

Despite being heavily exploited, pangolins (Pholidota: Manidae) have been subject to limited research, resulting in a lack of reliable population estimates and standardised survey methods for the eight extant species. Camera trapping represents a unique opportunity for broad-scale collaborative species monitoring due to its largely non-discriminatory nature, which creates considerable volumes of data on a relatively wide range of species. This has the potential to shed light on the ecology of rare, cryptic and understudied taxa, with implications for conservation decision-making. We undertook a global analysis of available pangolin data from camera trapping studies across their range in Africa and Asia. Our aims were (1) to assess the utility of existing camera trapping efforts as a method for monitoring pangolin populations, and (2) to gain insights into the distribution and ecology of pangolins. We analysed data collated from 103 camera trap surveys undertaken across 22 countries that fell within the range of seven of the eight pangolin species, which yielded more than half a million trap nights and 888 pangolin encounters. We ran occupancy analyses on three species (Sunda pangolin Manis javanica, white-bellied pangolin Phataginus tricuspis and giant pangolin Smutsia gigantea). Detection probabilities varied with forest cover and levels of human influence for P. tricuspis, but were low (M. javanica and S. gigantea, elevation for P. tricuspis and S. gigantea, forest cover for P. tricuspis and protected area status for M. javanica and P. tricuspis. We conclude that camera traps are suitable for the detection of pangolins and large-scale assessment of their distributions. However, the trapping effort required to monitor populations at any given study site using existing methods appears prohibitively high. This may change in the future should anticipated technological and methodological advances in camera trapping facilitate greater sampling efforts and/or higher probabilities of detection. In particular, targeted camera placement for pangolins is likely to make pangolin monitoring more feasible with moderate sampling efforts

Low exposure long-baseline neutrino oscillation sensitivity of the DUNE experiment

The Deep Underground Neutrino Experiment (DUNE) will produce world-leading neutrino oscillation measurements over the lifetime of the experiment. In this work, we explore DUNE's sensitivity to observe charge-parity violation (CPV) in the neutrino sector, and to resolve the mass ordering, for exposures of up to 100 kiloton-megawatt-years (kt-MW-yr). The analysis includes detailed uncertainties on the flux prediction, the neutrino interaction model, and detector effects. We demonstrate that DUNE will be able to unambiguously resolve the neutrino mass ordering at a 3$\sigma$ (5$\sigma$) level, with a 66 (100) kt-MW-yr far detector exposure, and has the ability to make strong statements at significantly shorter exposures depending on the true value of other oscillation parameters. We also show that DUNE has the potential to make a robust measurement of CPV at a 3$\sigma$ level with a 100 kt-MW-yr exposure for the maximally CP-violating values \delta_{\rm CP}} = \pm\pi/2. Additionally, the dependence of DUNE's sensitivity on the exposure taken in neutrino-enhanced and antineutrino-enhanced running is discussed. An equal fraction of exposure taken in each beam mode is found to be close to optimal when considered over the entire space of interest

A Gaseous Argon-Based Near Detector to Enhance the Physics Capabilities of DUNE

This document presents the concept and physics case for a magnetized gaseous argon-based detector system (ND-GAr) for the Deep Underground Neutrino Experiment (DUNE) Near Detector. This detector system is required in order for DUNE to reach its full physics potential in the measurement of CP violation and in delivering precision measurements of oscillation parameters. In addition to its critical role in the long-baseline oscillation program, ND-GAr will extend the overall physics program of DUNE. The LBNF high-intensity proton beam will provide a large flux of neutrinos that is sampled by ND-GAr, enabling DUNE to discover new particles and search for new interactions and symmetries beyond those predicted in the Standard Model