cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14768/apd.zarg-dh31
title: African Pollen Database: SALUT [A-L75] [B-L454] fossil pollen dataset
DOI: 10.14768/apd.vh67-rq69
title: African Pollen Database: ACHEL [12] fossil pollen dataset
DOI: 10.14768/apd.wywc-ds08
title: African Pollen Database: LKMBTU5 fossil pollen dataset
DOI: 10.14768/apd.ev9t-mb31
title: African Pollen Database: PRINCESS [1]* fossil pollen dataset
DOI: 10.14768/apd.trzd-gf40
title: African Pollen Database: PAKHUIS PASS [1166]* fossil pollen dataset
DOI: 10.14768/apd.36vk-zw81
title: African Pollen Database: LT98-2M fossil pollen dataset
DOI: 10.6084/m9.figshare.22362943
title: Complete Genome

description: Complete genome of <strong>Acinetobacter baumannii strain 04117201 isolate DstkR-1</strong>
DOI: 10.14768/apd.drb6-7m89
title: African Pollen Database: CHEM [2] fossil pollen dataset
DOI: 10.14768/apd.ycyq-1964
title: African Pollen Database: DEELPAN MERIBA [1]* fossil pollen dataset
DOI: 10.14768/apd.mb6n-e448
title: African Pollen Database: SOLAI [LSA-1] fossil pollen dataset
DOI: 10.14768/apd.6bt2-m842
title: African Pollen Database: PAKHUIS LOOSE OTHER* fossil pollen dataset
DOI: 10.14768/apd.hszr-6064
title: African Pollen Database: MORELETTA* fossil pollen dataset
DOI: 10.14768/apd.0n8m-jy41
title: African Pollen Database: OBAYI fossil pollen dataset
DOI: 10.14768/apd.9sct-5j66
title: African Pollen Database: TELEKI [TV61]* fossil pollen dataset
DOI: 10.14768/apd.eqdb-ap87
title: African Pollen Database: AMARA WEST [2_R_66] fossil pollen dataset
DOI: 10.14768/apd.qdea-7a85
title: African Pollen Database: GOMBORE fossil pollen dataset
DOI: 10.14768/apd.c41j-sz78
title: African Pollen Database: HDK99-1 fossil pollen dataset
DOI: 10.14768/apd.7nsd-0461
title: African Pollen Database: VANKER [1] fossil pollen dataset
DOI: 10.14768/apd.v6fh-9157
title: African Pollen Database: ANDOLO fossil pollen dataset
DOI: 10.14768/apd.k5kh-qr91
title: African Pollen Database: YEBBI fossil pollen dataset
DOI: 10.14768/apd.pjfz-c653
title: African Pollen Database: YOGOUM fossil pollen dataset
DOI: 10.14768/apd.xc4k-zw51
title: African Pollen Database: ODP site 175-1078C* fossil pollen dataset
DOI: 10.14768/apd.205a-xf05
title: African Pollen Database: SACRED* fossil pollen dataset
DOI: 10.14768/apd.hfcr-qz15
title: African Pollen Database: DRIEHOEK fossil pollen dataset
DOI: 10.14768/apd.byc2-7h98
title: African Pollen Database: TIZONG [T2] fossil pollen dataset
DOI: 10.14768/apd.z4tk-jn45
title: African Pollen Database: MATEMBE [3] fossil pollen dataset
DOI: 10.14768/apd.0zrk-7j39
title: African Pollen Database: DTNATRON fossil pollen dataset
DOI: 10.14768/apd.bwtv-0h34
title: African Pollen Database: LOMWE fossil pollen dataset
DOI: 10.14768/apd.x9km-wa28
title: African Pollen Database: WENCHI fossil pollen dataset
DOI: 10.14768/apd.hkyf-wd07
title: African Pollen Database: B-BASE SECTION* fossil pollen dataset
DOI: 10.14768/apd.dex1-r091
title: African Pollen Database: MB [6] fossil pollen dataset
DOI: 10.14768/apd.6j7k-cb96
title: African Pollen Database: NAMONTE fossil pollen dataset
DOI: 10.14768/apd.0h3k-ar15
title: African Pollen Database: KALWIRA fossil pollen dataset
DOI: 10.14768/apd.8ap7-hz41
title: African Pollen Database: V95-2PA fossil pollen dataset
DOI: 10.14768/apd.s2jr-xc05
title: African Pollen Database: ECKER fossil pollen dataset
DOI: 10.14768/apd.k0qy-kg57
title: African Pollen Database: ROOIBG [1]* fossil pollen dataset
DOI: 10.14768/apd.qnp4-dh69
title: African Pollen Database: TRIVA [2] fossil pollen dataset
DOI: 10.14768/apd.r2qz-ha02
title: African Pollen Database: EDW [4PC] fossil pollen dataset
DOI: 10.14768/apd.nynh-8d70
title: African Pollen Database: CORNELIA* fossil pollen dataset
DOI: 10.14768/apd.mbd5-rx43
title: African Pollen Database: EKSTEENFONTEIN* fossil pollen dataset
DOI: 10.14768/apd.m2gc-hr17
title: African Pollen Database: MITSINLA fossil pollen dataset
DOI: 10.14768/apd.daxp-ep80
title: African Pollen Database: LOBOI [1] fossil pollen dataset
DOI: 10.14768/apd.w562-4374
title: African Pollen Database: LH [3] fossil pollen dataset
DOI: 10.14768/apd.9tg2-y933
title: African Pollen Database: RUG [1] fossil pollen dataset
DOI: 10.14768/apd.9m9n-kj42
title: African Pollen Database: DANKA fossil pollen dataset
DOI: 10.14768/apd.786v-r141
title: African Pollen Database: NATRON [T63-64_Ka46] fossil pollen dataset
DOI: 10.14768/apd.wsjn-x422
title: African Pollen Database: OSSA [1] fossil pollen dataset
DOI: 10.14768/apd.y5tf-j926
title: African Pollen Database: FEJEJ [98-99] fossil pollen dataset
DOI: 10.14768/apd.ad9f-bt47
title: African Pollen Database: BOGORIA [STROMATO] fossil pollen dataset
DOI: 10.14768/apd.d0k8-e405
title: African Pollen Database: MUNDAFAN fossil pollen dataset
DOI: 10.14768/apd.0s5q-sf52
title: African Pollen Database: MATUPI fossil pollen dataset
DOI: 10.14768/apd.50jt-5h43
title: African Pollen Database: GASARE fossil pollen dataset
DOI: 10.14768/apd.j4a0-c783
title: African Pollen Database: ALB [2PC] fossil pollen dataset
DOI: 10.14768/apd.t41d-hy94
title: African Pollen Database: LOPEROT [1] fossil pollen dataset
DOI: 10.14768/apd.ahgr-fh90
title: African Pollen Database: SD [14TAN] fossil pollen dataset
DOI: 10.14768/apd.s552-yw50
title: African Pollen Database: MBI fossil pollen dataset
DOI: 10.14768/apd.2x89-ce84
title: African Pollen Database: BOUS fossil pollen dataset
DOI: 10.14768/apd.htmz-my85
title: African Pollen Database: B-SHELTER* fossil pollen dataset
DOI: 10.14768/apd.5wja-y073
title: African Pollen Database: FLORISBAD COPRO* fossil pollen dataset
DOI: 10.14768/apd.rd4h-zh69
title: African Pollen Database: WASSERF-YOUNGER fossil pollen dataset
DOI: 10.14768/apd.e03w-f673
title: African Pollen Database: ARNHEM* fossil pollen dataset
DOI: 10.14768/apd.y9j8-0d44
title: African Pollen Database: ALIWAL NORTH [1-2]* fossil pollen dataset
DOI: 10.14768/apd.hxb7-7e73
title: African Pollen Database: KS84063 fossil pollen dataset
DOI: 10.14768/apd.3bgd-t351
title: African Pollen Database: TJERI fossil pollen dataset
DOI: 10.14768/apd.jges-zq78
title: African Pollen Database: LT98_12M fossil pollen dataset
DOI: 10.14768/apd.16tk-jc50
title: African Pollen Database: KIMANA fossil pollen dataset
DOI: 10.14768/apd.k1sq-p362
title: African Pollen Database: TSWAING [1]* fossil pollen dataset
DOI: 10.14768/apd.vyw7-f404
title: African Pollen Database: LPOUL fossil pollen dataset
DOI: 10.14768/apd.xf3j-ra55
title: African Pollen Database: WADI SANA fossil pollen dataset
DOI: 10.14768/apd.sfq2-by41
title: African Pollen Database: HL fossil pollen dataset
DOI: 10.14768/apd.7zz1-a522
title: African Pollen Database: MIRABIB [A] fossil pollen dataset
DOI: 10.14768/apd.2057-bf85
title: African Pollen Database: BOGORIA [BOGN14] fossil pollen dataset
DOI: 10.14768/apd.dmr2-x041
title: African Pollen Database: NIGERDC [2] fossil pollen dataset
DOI: 10.14768/apd.kpv4-n453
title: African Pollen Database: KUL fossil pollen dataset
DOI: 10.14768/apd.myc0-1m73
title: African Pollen Database: YEV [1] fossil pollen dataset
DOI: 10.14768/apd.54jp-6e47
title: African Pollen Database: BOGUE fossil pollen dataset
DOI: 10.14768/apd.1we9-nb50
title: African Pollen Database: ROOIBG [2]* fossil pollen dataset
DOI: 10.14768/apd.h929-1726
title: African Pollen Database: KHANT fossil pollen dataset
DOI: 10.14768/apd.3784-gy88
title: African Pollen Database: MBAERE [FC 300] fossil pollen dataset
DOI: 10.14768/apd.q65h-3g24
title: African Pollen Database: DEELPAN COPROLITE* fossil pollen dataset
DOI: 10.14768/apd.eked-rk09
title: African Pollen Database: MUSISI fossil pollen dataset
DOI: 10.14768/apd.jp78-8840
title: African Pollen Database: MIRO DORA [MRD-VP-1] fossil pollen dataset
DOI: 10.14768/apd.3qdv-mb91
title: African Pollen Database: RAWRI [4] fossil pollen dataset
DOI: 10.14768/apd.fvyn-6w73
title: African Pollen Database: MASOKO [M96] fossil pollen dataset
DOI: 10.14768/apd.xkvg-bj14
title: African Pollen Database: KIMILI [B] fossil pollen dataset
DOI: 10.14768/apd.tzv1-zg05
title: African Pollen Database: MALAWI [MAL 1C] fossil pollen dataset
DOI: 10.14768/apd.63mh-7p93
title: African Pollen Database: HIMAKIBA fossil pollen dataset
DOI: 10.14768/apd.dg6s-m935
title: African Pollen Database: KHORFB fossil pollen dataset
DOI: 10.14768/apd.cety-2e11
title: African Pollen Database: OYO fossil pollen dataset
DOI: 10.14768/apd.hj55-q426
title: African Pollen Database: MK [1] fossil pollen dataset
DOI: 10.14768/apd.0wy6-fa33
title: African Pollen Database: LT98-58M fossil pollen dataset
DOI: 10.14768/apd.8b2d-ag46
title: African Pollen Database: GAMA [4] fossil pollen dataset
DOI: 10.14768/apd.q3nz-qg52
title: African Pollen Database: SD [36TAN] fossil pollen dataset
DOI: 10.14768/apd.93ba-dg07
title: African Pollen Database: BADSFONTEIN* fossil pollen dataset
DOI: 10.14768/apd.987q-jp07
title: African Pollen Database: GOBERO  BURIALS fossil pollen dataset
DOI: 10.14768/apd.h1yz-5e41
title: African Pollen Database: MAUDIT fossil pollen dataset
DOI: 10.14768/apd.yn02-1935
title: African Pollen Database: WONDERWR STALAG* fossil pollen dataset
DOI: 10.14768/apd.1swb-vv09
title: African Pollen Database: RUG [2] fossil pollen dataset
DOI: 10.14768/apd.twnr-a886
title: African Pollen Database: KWAR AL JARAMAH [KAJ 2] fossil pollen dataset
DOI: 10.14768/apd.wve2-bc90
title: African Pollen Database: B-POND [USP] fossil pollen dataset
DOI: 10.14768/apd.egwn-1d03
title: African Pollen Database: GONA [OGS-6a - OGS-7] fossil pollen dataset
DOI: 10.14768/apd.v6dk-bj61
title: African Pollen Database: KISSI [BS-6] fossil pollen dataset
DOI: 10.14768/apd.dmhn-rq03
title: African Pollen Database: M86_18P fossil pollen dataset
DOI: 10.14768/apd.zcp4-mk86
title: African Pollen Database: SELIMA fossil pollen dataset
DOI: 10.14768/apd.qs0n-dv02
title: African Pollen Database: BILGOY fossil pollen dataset
DOI: 10.14768/apd.evdt-0x76
title: African Pollen Database: ASSINIE fossil pollen dataset
DOI: 10.14768/apd.wv01-ma93
title: African Pollen Database: BOL [25] fossil pollen dataset
DOI: 10.14768/apd.36kz-vv32
title: African Pollen Database: HYK99-1 fossil pollen dataset
DOI: 10.14768/apd.q8pm-gk36
title: African Pollen Database: KAPKANYAR fossil pollen dataset
DOI: 10.14768/apd.yshw-1479
title: African Pollen Database: MUKUKWE fossil pollen dataset
DOI: 10.14768/apd.hff6-3x72
title: African Pollen Database: M86_22P fossil pollen dataset
DOI: 10.14768/apd.sv7n-j442
title: African Pollen Database: 03GUIERS fossil pollen dataset
DOI: 10.14768/apd.t8kh-a817
title: African Pollen Database: B-SECTION [BFS]* fossil pollen dataset
DOI: 10.14768/apd.t8qp-0r44
title: African Pollen Database: SITE36 fossil pollen dataset
DOI: 10.14768/apd.fav6-kg77
title: African Pollen Database: MAHOMA fossil pollen dataset
DOI: 10.14768/apd.5as1-jg39
title: African Pollen Database: BUJUKU fossil pollen dataset
DOI: 10.14768/apd.rnx1-5q40
title: African Pollen Database: ACHEL [10A] fossil pollen dataset
DOI: 10.14768/apd.94rb-0w92
title: African Pollen Database: AMPASAMB fossil pollen dataset
DOI: 10.14768/apd.05nc-cp17
title: African Pollen Database: DSDP [367] fossil pollen dataset
DOI: 10.14768/apd.yc7b-s429
title: African Pollen Database: SELE fossil pollen dataset
DOI: 10.14768/apd.6frj-vy24
title: African Pollen Database: NUWEV [1] fossil pollen dataset
DOI: 10.14768/apd.gwcs-7r06
title: African Pollen Database: GOHO fossil pollen dataset
DOI: 10.14768/apd.tyjm-4k12
title: African Pollen Database: AIR [AM 79-208] fossil pollen dataset
DOI: 10.5281/zenodo.4964673
title: Supporting data for "Rapid determination of solid-state diffusion coefficients in Li-based batteries via intermittent current interruption method"

description: This is the dataset of electrochemical and operando X-ray diffraction experiments for our publication "Rapid determination of solid-state diffusion coefficients in Li-based batteries via intermittent current interruption method". This archive contains the raw data and scripts written in R used in the analysis and presentation of the results in this manuscript. <strong>Abstract of the manuscript:</strong> The galvanostatic intermittent titration technique (GITT) is considered the go-to method for determining the Li<sup>+</sup>diffusion coefficients in insertion electrode materials. However, GITT-based methods are either time-consuming, prone to analysis pitfalls or require sophisticated interpretation models. Here, we propose the intermittent current interruption (ICI) method as a reliable, accurate and faster alternative to GITT-based methods. Using Fick’s laws, we prove that the ICI method renders the same information as the GITT within a certain duration of time since the current interruption. Via experimental measurements, we also demonstrate that the results from ICI and GITT methods match where the assumption of semi-infinite diffusion applies. Moreover, the benefit of the non-disruptive ICI method to operando materials characterization is exhibited by correlating the continuously monitored diffusion coefficient of Li<sup>+</sup> in a LiNi<sub>0.8</sub>Mn<sub>0.1</sub>Co<sub>0.1</sub>O<sub>2</sub>-based electrode to its structural changes captured by operando X-ray diffraction measurements.
DOI: 10.5281/zenodo.4964674
title: Supporting data for "Rapid determination of solid-state diffusion coefficients by intermittent current interruption"

description: This is the dataset of electrochemical and operando X-ray diffraction experiments for our publication "Rapid determination of solid-state diffusion coefficients by intermittent current interruption". This archive contains the raw data and scripts written in R used in the analysis and presentation of the results in this manuscript. <strong>Abstract for the manuscript:</strong> The galvanostatic intermittent titration technique (GITT) has been regarded as the go-to method for determining the diffusion coefficients of Li-ions in insertion electrode materials at various states of charge (SoC). However, the method is notoriously time-consuming. In this work, the intermittent current interruption (ICI) method, which has previously been employed to investigate the progression of internal resistances in Li-ion cells, is demonstrated to provide comparably accurate measurements of diffusion coefficients with a drastically reduced experimental time. Theoretically, it is first derived from Fick’s laws that the ICI method renders essentially the same information as GITT. Experimentally, both GITT and ICI are then compared side-by-side in a three-electrode half-cell of LiNi<sub>0.8</sub>Mn<sub>0.1</sub>Co<sub>0.1</sub>O<sub>2</sub> (NMC811). It is shown that the results from both methods match where the assumption of semi-infinite diffusion applies. Moreover, the benefit of the comparatively non-disruptive ICI method to operando characterization methods is demonstrated via correlation of changes in the continuously monitored diffusion coefficient of Li<sup>+</sup> in NMC811 to structural changes in the material by operando X-ray diffraction (XRD).
DOI: 10.5281/zenodo.5569522
title: Supporting data for "Rapid determination of solid-state diffusion coefficients in Li-based batteries via intermittent current interruption method"

description: This is the dataset of electrochemical and operando X-ray diffraction experiments for our publication "Rapid determination of solid-state diffusion coefficients in Li-based batteries via intermittent current interruption method". This archive contains the raw data and scripts written in R used in the analysis and presentation of the results in this manuscript. <strong>Abstract of the manuscript:</strong> The galvanostatic intermittent titration technique (GITT) is considered the go-to method for determining the Li<sup>+</sup>diffusion coefficients in insertion electrode materials. However, GITT-based methods are either time-consuming, prone to analysis pitfalls or require sophisticated interpretation models. Here, we propose the intermittent current interruption (ICI) method as a reliable, accurate and faster alternative to GITT-based methods. Using Fick’s laws, we prove that the ICI method renders the same information as the GITT within a certain duration of time since the current interruption. Via experimental measurements, we also demonstrate that the results from ICI and GITT methods match where the assumption of semi-infinite diffusion applies. Moreover, the benefit of the non-disruptive ICI method to operando materials characterization is exhibited by correlating the continuously monitored diffusion coefficient of Li<sup>+</sup> in a LiNi<sub>0.8</sub>Mn<sub>0.1</sub>Co<sub>0.1</sub>O<sub>2</sub>-based electrode to its structural changes captured by operando X-ray diffraction measurements.
DOI: 10.5281/zenodo.7786244
title: malacoctenus_tetranemus_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7786243
title: malacoctenus_tetranemus_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7644532
title: Carbon and mineral data of organic matter fractions in Siberian Yedoma permafrost

description: This file contains carbon and mineral data of organic matter fractions obtained from two permafrost drill cores L14-02 (73.33616° N; 141.32776° E) and L14-05 (73.34994° N; 141.24156° E) from Bol’shoy Lyakhovsky Island in NE Siberia in 2014. The datasets contain mass fractions of different size and density fractions, OC concentrations, OC/N ratios, data on organic matter composition based on <sup>13</sup>C-NMR, radiocarbon (<sup>14</sup>C) data, as well as data on iron (Fe) mineral phases and CO<sub>2</sub> production rates of mineral-associated organic matter. Further, carbon and organic biomarker data (<em>n</em>-alkanes) of the bulk sediment are included. The data were created to study mass partitioning of Pleistocene permafrost OC among different organic matter fractions to assess the bioavailability and stability of the organic matter. Please refer to the publication listed below for more information.
description: {"references": ["Jannik Martens, Carsten W. Mueller, Prachi Joshi, Christoph Rosinger, Markus Maisch, Andreas Kappler, Michael Bonkowski, Georg Schwamborn, Lutz Schirrmeister, Janet Rethemeyer. Stabilization of mineral-associated organic carbon in Pleistocene permafrost. Nature Communications."]}
DOI: 10.5281/zenodo.7644531
title: Carbon and mineral data of organic matter fractions in Siberian Yedoma permafrost

description: This file contains carbon and mineral data of organic matter fractions obtained from two permafrost drill cores L14-02 (73.33616° N; 141.32776° E) and L14-05 (73.34994° N; 141.24156° E) from Bol’shoy Lyakhovsky Island in NE Siberia in 2014. The datasets contain mass fractions of different size and density fractions, OC concentrations, OC/N ratios, data on organic matter composition based on <sup>13</sup>C-NMR, radiocarbon (<sup>14</sup>C) data, as well as data on iron (Fe) mineral phases and CO<sub>2</sub> production rates of mineral-associated organic matter. Further, carbon and organic biomarker data (<em>n</em>-alkanes) of the bulk sediment are included. The data were created to study mass partitioning of Pleistocene permafrost OC among different organic matter fractions to assess the bioavailability and stability of the organic matter. Please refer to the publication listed below for more information.
description: {"references": ["Jannik Martens, Carsten W. Mueller, Prachi Joshi, Christoph Rosinger, Markus Maisch, Andreas Kappler, Michael Bonkowski, Georg Schwamborn, Lutz Schirrmeister, Janet Rethemeyer. Stabilization of mineral-associated organic carbon in Pleistocene permafrost. Nature Communications."]}
DOI: 10.24342/f908bb7f-ccf5-46aa-8b64-22c0849597ea
title: Becoming in Academia

description: The dataset presents ethnographic material collected during Becoming in Academia, an artistic intervention conducted in 2020 and encompassing 14 PhD students at Aalto University, divided into two separate groups. Data collection The data was collected during 12 group interviews of 1,5 hours and during 12 workshops of 2,5 hours each, conducted face-to-face or via Zoom from March until September 2020. It includes audio- and video recordings, participants’ reflections the form of written text, recorded speech and drawings, and the researchers’ field notes and photographs. The data is stored on Aalto Network drive. Data organization We collected data from each interview and session, and this data was complemented with the participants’ reflections between the sessions. For the analysis, the data was pseudonymized. During the analysis, meaningful exchanges and insights were identified and coded. After this, we went back to the data to analyze it further. Presently, the data has been used in two articles: • Lafaire, A., Kuismin, A. Moisander, J. & Grünbaum, L. (submitted to Culture and Organization, fall 2020) ‘I realized it’s ok not to know’: Fostering learnings for well-being in doctoral education through empathy and art-based methods. • Lafaire, A., Soini, A. & Grünbaum, L. (submitted to Gender, Work & Organization, spring 2021) In lockdown with my inner saboteur - a collaborative collage on new perspectives on self-compassion during the ongoing pandemic. Keywords: artistic intervention, ethnography, PhD students, academia
DOI: 10.5281/zenodo.7786027
title: One meter integrated depth velocity (total, ageostrophy, Ekman and Stokes components) fields for the Mediterranean Sea each 6 hours (from 2007 to 2018)

description: One meter integrated depth surface velocity fields for the Mediterranean Sea from January 2007 to June 2018 calculated following the methodology in Morales-Marquez et al.(2020). This dataset provides the total velocity field, the ageostrophic, Ekman and Stokes components.
description: {"references": ["Morales\u2010M\u00e1rquez, V., Hern\u00e1ndez\u2010Carrasco, I., Simarro, G., Rossi, V., & Orfila, A. (2021). Regionalizing the Impacts of Wind\u2010and Wave\u2010Induced Currents on Surface Ocean Dynamics: A Long\u2010Term Variability Analysis in the Mediterranean Sea. Journal of Geophysical Research: Oceans, 126(9), e2020JC017104."]}
DOI: 10.5281/zenodo.7786026
title: One meter integrated depth velocity (total, ageostrophy, Ekman and Stokes components) fields for the Mediterranean Sea each 6 hours (from 2007 to 2018)

description: One meter integrated depth surface velocity fields for the Mediterranean Sea from January 2007 to June 2018 calculated following the methodology in Morales-Marquez et al.(2020). This dataset provides the total velocity field, the ageostrophic, Ekman and Stokes components.
description: {"references": ["Morales\u2010M\u00e1rquez, V., Hern\u00e1ndez\u2010Carrasco, I., Simarro, G., Rossi, V., & Orfila, A. (2021). Regionalizing the Impacts of Wind\u2010and Wave\u2010Induced Currents on Surface Ocean Dynamics: A Long\u2010Term Variability Analysis in the Mediterranean Sea. Journal of Geophysical Research: Oceans, 126(9), e2020JC017104."]}
DOI: 10.6084/m9.figshare.22331140.v3
title: Manipulating Exchange Bias in 2D Magnetic Heterojunction

description: The exchange bias effect has been instrumental in the development of a variety of spintronic devices. Here, we use pressure to tune the exchange bias effect in all van der Waals heterostructure composed of FePSe3/Fe3GeTe2.
DOI: 10.5258/soton/d2574
title: Dataset in support of the Southampton doctoral thesis : Understanding social capital and the role it plays in food security in Malawi

description: Qualitative fieldwork notes from focus group discussions (FGDs) in support of Chapter 5 of doctoral thesis "Bonding, bridging and linking social capital combinations for food access; A gendered case study exploring temporal differences in Southern Malawi." This research paper has been submitted to the Journal of Rural Studies.The FGDs were conducted with a seasonal calendar at the start, FGD and ranking exercise at the end (available in this data notes). The research themes in this data were conducted based on questions around food security, social capital, temporal changes, gender and weather, to explore how social capital typologies are used to access food.