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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Crotti, Ilaria; Quiquet, Aurélien; Landais, Amaëlle; Stenni, Barbara; +6 Authors

    The data here described are presented in the submitted paper Response of the Wilkes Subglacial Basin Ice Sheet to Southern Ocean Warming During Late Pleistocene Interglacials by Crotti et al. This data set includes new high resolution measurements of d-excess, d18O and ssNa+ for the Antarctic TALDICE ice core (Latitude: -72.783330, Longitude: 159.066670, Elevation: 2315.0 m). The new data set covers the interglacials periods of MIS 5.5, MIS 7.5 and MIS 9.3 (1486 m depth - 1548 m depth). The data are drawn on the TALDICE deep1 chronology (Crotti et al. 2021). The d-excess (d = δD − 8 × δ18O) (permill) record covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 5 cm resolution and spans the following age-depths intervals: • MIS 5.5. Between 1378.5 and 1421.65 m depth, 110-135 ka • MIS 7.5. Between 1521.85 and 1524.5 m depth, 243-248 ka • MIS 9.3. Between 1541.80 and 1547.90 m depth, 320-343 ka The d18O record (permill) covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 5 cm resolution and spans the following age-depths intervals: • MIS 7.5. Between 1521.85 and 1524.5 m depth, 243-248 ka • MIS 9.3. Between 1541.80 and 1547.90 m depth, 320-343 ka The ssNa+ fluxes record covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 8 cm resolution and pans the following age-depths intervals: • MIS 7.5. Between 1521.81 and 1524.54 m depth, 243-248 ka • MIS 9.3. Between 1541.73 and 1547.96 m depth, 320-343 ka The d18O and dD (non presented here) to calculate the d-excess were analysed in Italy (University of Venice) and France (LSCE) using the Cavity Ring Down Spectroscopy (CRDS) technique. Analyses were performed using a Picarro isotope water analyser (L2130-i version for both laboratories). The data were calibrated using a three-point linear calibration with three lab-standards that were themselves calibrated versus Standard Mean Ocean Water (SMOW). The average precision for the δ18O and δD measurements is 0.1 and 0.7 ‰, respectively. The concentrations of ssNa+ were measured on TALDICE ice samples at 8 cm resolution by classical ion chromatography on discrete samples collected using a melting device connected to an auto-sampler for the MIS 7.5 and MIS 9.3 whereas Continuous Flow Analysis (CFA) was applied for MIS 5.5 samples. The total deposition ssNa+ flux was calculated multiplying the measured ice concentration of ssNa+ by the reconstructed accumulation rate. The accumulation rates were derived from the accumulation rates were obtained from the TALDICE deep1 age scale (Crotti et al. 2021).

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Crotti, Ilaria; Quiquet, Aurélien; Landais, Amaëlle; Stenni, Barbara; +6 Authors

    The data here described are presented in the submitted paper Response of the Wilkes Subglacial Basin Ice Sheet to Southern Ocean Warming During Late Pleistocene Interglacials by Crotti et al. This data set includes new high resolution measurements of d-excess, d18O and ssNa+ for the Antarctic TALDICE ice core (Latitude: -72.783330, Longitude: 159.066670, Elevation: 2315.0 m). The new data set covers the interglacials periods of MIS 5.5, MIS 7.5 and MIS 9.3 (1486 m depth - 1548 m depth). The data are drawn on the TALDICE deep1 chronology (Crotti et al. 2021). The d-excess (d = δD − 8 × δ18O) (permill) record covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 5 cm resolution and spans the following age-depths intervals: • MIS 5.5. Between 1378.5 and 1421.65 m depth, 110-135 ka • MIS 7.5. Between 1521.85 and 1524.5 m depth, 243-248 ka • MIS 9.3. Between 1541.80 and 1547.90 m depth, 320-343 ka The d18O record (permill) covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 5 cm resolution and spans the following age-depths intervals: • MIS 7.5. Between 1521.85 and 1524.5 m depth, 243-248 ka • MIS 9.3. Between 1541.80 and 1547.90 m depth, 320-343 ka The ssNa+ fluxes record covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 8 cm resolution and pans the following age-depths intervals: • MIS 7.5. Between 1521.81 and 1524.54 m depth, 243-248 ka • MIS 9.3. Between 1541.73 and 1547.96 m depth, 320-343 ka The d18O and dD (non presented here) to calculate the d-excess were analysed in Italy (University of Venice) and France (LSCE) using the Cavity Ring Down Spectroscopy (CRDS) technique. Analyses were performed using a Picarro isotope water analyser (L2130-i version for both laboratories). The data were calibrated using a three-point linear calibration with three lab-standards that were themselves calibrated versus Standard Mean Ocean Water (SMOW). The average precision for the δ18O and δD measurements is 0.1 and 0.7 ‰, respectively. The concentrations of ssNa+ were measured on TALDICE ice samples at 8 cm resolution by classical ion chromatography on discrete samples collected using a melting device connected to an auto-sampler for the MIS 7.5 and MIS 9.3 whereas Continuous Flow Analysis (CFA) was applied for MIS 5.5 samples. The total deposition ssNa+ flux was calculated multiplying the measured ice concentration of ssNa+ by the reconstructed accumulation rate. The accumulation rates were derived from the accumulation rates were obtained from the TALDICE deep1 age scale (Crotti et al. 2021).

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Montenegro-Johnson, Thomas D.; Gadêlha, Hermes; Smith, David J.; Gadelha, H.;

    Sperm traverse their microenvironment through viscous fluid by propagating flagellar waves; the waveform emerges as a consequence of elastic structure, internal active moments and low Reynolds number fluid dynamics. Engineered microchannels have recently been proposed as a method of sorting and manipulating motile cells; the interaction of cells with these artificial environments therefore warrants investigation. A numerical method is presented for large-amplitude elastohydrodynamic interaction of active swimmers with domain features. This method is employed to examine hydrodynamic scattering by a model microchannel backstep feature. Scattering is shown to depend on backstep height and the relative strength of viscous and elastic forces in the flagellum. In a ‘high viscosity’ parameter regime corresponding to human sperm in cervical mucus analogue, this hydrodynamic contribution to scattering is comparable in magnitude to recent data on contact effects, being of the order of 5°–10°. Scattering can be positive or negative depending on the relative strength of viscous and elastic effects, emphasizing the importance of viscosity on the interaction of sperm with their microenvironment. The modulation of scattering angle by viscosity is associated with variations in flagellar asymmetry induced by the elastohydrodynamic interaction with the boundary feature. Simulation resultsTrajectory and waveform data for elastohydrodynamic simulations of sperm swimming over geometric features.simulation_results.zip

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  • Authors: United States Department Of Health And Human Services. Centers For Disease Control And Prevention. National Center For Health Statistics;

    Sample weights are available for analyzing NHANES 2003-2004 data. Most data analyses require either the interviewed sample weight (variable name: WTINT2YR) or examined sample weight (variable name: WTMEC2YR). The two-year sample weights (WTINT2YR, WTMEC2YR) should be used for NHANES 2003-2004 analyses. Use of the correct sample weight for NHANES analyses is extremely important and depends on the variables being used. A good rule of thumb is to use "the least common denominator" approach. With this approach, the analyst checks the variables of interest. The variable that was collected on the smallest number of persons is the "least common denominator," and the sample weight that applies to that variable is the appropriate one to use for that particular analysis. Please refer to the NHANES 2003-2004 Analytic Guidelines provided with the data release files to determine the appropriate analytic methodology. NCHS September 2006 Version--NHANES Analytic Guidelines Beginning in 1999, the National Health and Nutrition Examination Survey (NHANES) became a continuous, annual survey rather than the periodic survey that it had been in the past. For a variety of reasons, including disclosure and reliability issues, the survey data are released on public use data files every two years. Thus, the data release cycle for the ongoing (and continuous) NHANES is described as NHANES 1999-2000, NHANES 2001-2002, NHANES 2003-2004, etc. In addition to the analysis of data from any two-year cycle, it is possible to combine two or more "cycles" (e.g., 2003-2004 and 2005-2006) to create NHANES 2003-2006, thus increasing sample size and analytic options. In order to produce estimates with greater statistical reliability, combining two or more two-year cycles of the continuous NHANES is encouraged and strongly recommended. When combining cycles of data, it is extremely important that (1) the user verify that data items collected in all combined years were comparable in wording and methods and (2) use a proper sampling weight. Beginning in 2003, the survey content for each two year period is held as constant as possible to be consistent with the data release cycle. In the first four years of the continuous survey, this was not always the case, and some special data release and data access procedures had to be developed and used for selected survey content collected in "other than two-year" intervals (see the NHANES release policy). The decision on how many years of NHANES data are required for a particular analysis can be summarized by the concept of minimum sample size required. The minimum sample size is determined by the statistic to be estimated (e.g. mean, total, proportion...), the reliability criteria (e.g. 20 or 30 percent relative standard error), the Design Effect for the statistics (DEFF defined as the variance inflation factor), and the degrees of freedom for the standard error estimate. Earlier NHANES surveys were conducted for four or more years and, thus, have larger samples than a two-year cycle of the current continuous NHANES. However, in each of those surveys, many sub-domains did not meet minimum sample size requirements and in those cases the above concerns were (and still are) relevant. When combining two or more two-year cycles of the continuous NHANES, the user should use the following procedure for calculating the appropriate combined sample weights. When combining two or more two-year cycles of the continuous NHANES, the user must calculate new sample weights before beginning any analysis of the data. NCHS will not be calculating and including all possible combinations of multiple two-year cycles of the continuous survey because it would be impractical to produce them and include them on all public release files. Because of a particular issue with Census population estimates, a set of four-year weights was created for the first four years of the continuous NHANES -- 1999-2002. The sample weights for NHANES 1999-2000 were based on population estimates developed by the Bureau of the Census before the Year 2000 Decennial Census counts became available. The two-year sample weights for NHANES 2001-2002 were based on population estimates that incorporate the year 2000 Census counts. The two population estimates were not strictly comparable. To facilitate analysis for these first four years of the continuous NHANES, appropriate four-year sample weights (comparable to Census 2000 counts) were calculated and added to the demographic data files for both 1999-2000 and 2001-2002. These sample weights have the same variable name in each file. For example, for the sample persons for whom there are MEC data items, the variable name for the four-year weight is WTMEC4YR. Thus, users of the earlier release of the NHANES 1999-2000 demographic file must use the updated demographic file to appropriately analyze the combined four-year data 1999-2002. Because NHANES 2003-2004 uses the same year 2000 Census counts as were used for NHANES 2001-2002, there is no need to create special four-year weights for 2001-2004. For a four-year estimate for 2001-2004, one can create a new variable for a four-year weight by assigning half of the two-year weight for 2001-2002 if the person was sampled in 2001-2002 or assigning half of the two-year weight for 2003-2004 if the person was sampled in 2003-2004. This is possible because the two-year weights for 2003-2004 are comparable to the 2001-2002 weights (in terms of a population basis). For an estimate for the six years 1999-2004, a six-year weight variable can be created by assigning two-thirds of the four-year weight for 1999-2002 if the person was sampled in 1999-2002, or assigning one-third of the two-year weight for 2003-2004 if the person was sampled in 2003-2004. This is possible because the 2003-2004 weights are also comparable (on a population basis) to the combined four-year weights specifically created for 1999-2002. This information summarizes the most recent analytic and reporting guidelines that should be used for most NHANES analyses and publications. It is important for users to understand the entire document and to become familiar with statistical issues in the analysis of complex survey data. These suggested guidelines provide a framework to users for producing estimates that conform to the analytic design of the survey. Because statistical methods for analyzing complex survey data are continually evolving, these recommendations may differ slightly from those used by analysts for previous NHANES surveys. It is important to remember that the statistical guidelines in this document are not absolute. When conducting analyses, the analyst needs to use his/her subject matter knowledge (including methodological issues), as well as information about the survey design. The more one deviates from the original analytic categories and original analytic objectives defined in the planning documents, the more important it is to evaluate the results carefully and to interpret the findings cautiously. Future versions of the NHANES Analytic and Reporting Guidelines will include additional topics, such as sample sizes and response rates for each NHANES survey, hypothesis testing, multivariate analysis, and a discussion of the concept of statistical versus practical significance. These are Guidelines not standards. Depending upon the subject matter and statistical efficiency, specific analyses may depart from these guidelines; but the burden of proof for statistical efficiency and for appropriate data interpretation is on the data user/analyst. Again, NHANES data files from the continuous survey are publicly released on a two-year basis (1999-2000, 2001-2002, 2003-2004, etc.) and as small, content specific files. The data files and associated documentations, as well as these analytic guidelines, may be edited and/or updated to reflect new data release files. Users should periodically check the NHANES website to determine if any new or revised data files have been released and if these analytic guidelines have been updated. Datasets: DS0: Study-Level Files DS1: Demographics DS11: Examination: Audiometry (Subsample) DS12: Examination: Audiometry Tympanometry DS13: Examination: Balance DS14: Examination: Bioelectrical Impedance DS15: Examination: Blood Pressure DS16: Examination: Body Measurements DS17: Examination: Cardiovascular Fitness DS18: Examination: Composite International Diagnostic Interview (Generalized Anxiety Disorder) (Subsample) DS19: Examination: Composite International Diagnostic Interview (Major Depression Module) (Subsample) DS20: Examination: Composite International Diagnostic Interview (Panic Disorder Module) (Subsample) DS21: Examination: Dermatology DS22: Examination: Dietary Interview (Individual Foods File -- First Day) DS23: Examination: Dietary Interview (Individual Foods File -- Second Day) DS24: Examination: Dietary Interview (Total Nutrient Intakes -- First Day) DS25: Examination: Dietary Interview (Total Nutrient Intakes -- Second Day) DS26: Examination: Dual Energy X-Ray Absorptiometry (DXX) DS27: Examination: Dual Energy X-Ray Absorptiometry Supplemental (DXX_S) DS28: Examination: Food Frequency Questionnaire -- Raw Questionnaire Responses DS29: Examination: Food Frequency Questionnaire -- DietCalc Output DS30: Examination: Lower Extremity Ankle Brachial Blood Pressure Index DS31: Examination: Lower Extremity Disease (Peripheral Neuropathy) DS32: Examination: Oral Health (Addendum) DS33: Examination: Oral Health (Dentition) DS34: Examination: Oral Health (Lower Periodontal) DS35: Examination: Oral Health (Upper Periodontal) DS36: Examination: Oral Health (Recommendation of Care/Referral) DS37: Examination: Physical Activity Monitor DS38: Examination: Vision Exam DS101: Laboratory: Antibody to Coxiella Burnetii (Q-Fever) (Surplus Sera) DS102: Laboratory: Antibody to Cytomegalovirus IgG (Surplus Sera) DS103: Laboratory: Antibody to Mumps (Surplus Sera) DS104: Laboratory: Melamine (Surplus Urine) DS105: Laboratory: Varicella-Zoster Virus Antibody (Surplus Sera) DS106: Laboratory: Lab 02 Hepatitis DS107: Laboratory: Lab 02 Hepatitis B Surface Antibody DS108: Laboratory: Lab 02 Hepatitis A Antibody DS109: Laboratory: Lab 03 Human Immunodeficiency Virus DS110: Laboratory: Lab 04 Urinary Perchlorate DS111: Laboratory: Lab 04 Volatile Organic Compounds In Blood And Water DS112: Laboratory: Lab 05 Chlamydia Trachomatis And Neisseria Gonorrhea DS113: Laboratory: Lab 06 Acrylamide And Glycidamide DS114: Laboratory: Lab 06 Blood Lead, Cadmium And Mercury DS115: Laboratory: Lab 06 Methylmalonic Acid And Homocysteine DS116: Laboratory: Lab 06 Rbc Folate, Serum Folate, And Vitamin B12 DS117: Laboratory: Lab 06 Serum Cotinine DS118: Laboratory: Lab 06 Ferritin And Transferrin Receptor DS119: Laboratory: Lab 06 Heavy Metals DS120: Laboratory: Lab 06 Urinary Iodine DS121: Laboratory: Lab 06 Urinary Phytoestrogens DS122: Laboratory: Lab 06 Urinary Total Arsenic And Speciated Arsenics DS123: Laboratory: Lab 06 Urinary Mercury DS124: Laboratory: Lab 06 Vitamin C DS125: Laboratory: Lab 06 Vitamin D DS126: Laboratory: Lab 09 Herpes I And Herpes II DS127: Laboratory: Lab 10 Glycohemoglobin DS128: Laboratory: Lab 10AM Glucose, C-Peptide, Insulin DS129: Laboratory: Lab 11 CRP DS130: Laboratory: Lab 11 PSA DS131: Laboratory: Lab 13 Total Cholesterol And HDL Cholesterol DS132: Laboratory: Lab 13AM Triglycerides And LDL Cholesterol DS133: Laboratory: Lab 16 Urinary Albumin DS134: Laboratory: Lab 17 Toxoplasma (IgG and IgM) DS135: Laboratory: Lab 19 Measles Rubella And Varicella DS136: Laboratory: Lab 20 Lead Dust DS137: Laboratory: Lab 24 Environmental Pesticides DS138: Laboratory: Lab 24 Environmental Phenols DS139: Laboratory: Lab 24 Polyfluorinated Compounds DS140: Laboratory: Lab 24 Urinary Phthalates DS141: Laboratory: Lab 25 Complete Blood Count DS142: Laboratory: Lab 26 Urinary Current Use Pesticide DS143: Laboratory: Lab 26 Urinary Organophosphate Insecticides DS144: Laboratory: Lab 28 Dioxins, Furans, and Coplanar PCBS DS145: Laboratory: Lab 28 Non-Dioxin-Like Polychlorinated Biphenyls DS146: Laboratory: Lab 28 Organochlorine Pesticides DS147: Laboratory: Lab 28 Polybrominated Diphenyl Ethers DS148: Laboratory: Lab 31 Polyaromatic Hydrocarbons DS149: Laboratory: Lab 34 Trichomonos, Vaginalis And Bacterial Vaginosis DS150: Laboratory: Lab 35 Methicillin Resistant Staphylococcus Aureus DS151: Laboratory: Lab 36 Syphilis IgG, RR and TP-PA DS152: Laboratory: Lab 37 Human Papillomavirus (HPV) DNA Hybrid Capture, PCR, and Hybridization Results from Vaginal Swab Samples DS153: Laboratory: Lab 39 Erythrocyte Protoporphyrin And Selenium DS154: Laboratory: Lab 40 Biochemistry Profile DS155: Laboratory: Lab 40 Iron, TIBC and Transferrin DS156: Laboratory: Lab 43 Vitamin B6 DS157: Laboratory: Lab 45 Vitamin A, E And Carotenoids DS158: Laboratory: Lab 52 HPV Serum DS159: Laboratory: Phlebotomy Fasting Questions DS160: Laboratory: Urine Collection (Pregnancy) DS201: Questionnaire: Acculturation DS202: Questionnaire: Alcohol Use DS203: Questionnaire: Analgesics Pain Relievers DS204: Questionnaire: Audiometry DS205: Questionnaire: Balance DS206: Questionnaire: Blood Pressure DS207: Questionnaire: Cardiovascular Disease And Health DS208: Questionnaire: Current Health Status DS209: Questionnaire: Dermatology DS210: Questionnaire: Diabetes DS211: Questionnaire: Diet Behavior And Nutrition DS212: Questionnaire: Dietary Supplement Use - Supplement Counts DS213: Questionnaire: Dietary Supplement Use - Participants Use Of Supplement DS214: Questionnaire: Dietary Supplement Use - Supplement Information DS215: Questionnaire: Dietary Supplement Use - Ingredient Information DS216: Questionnaire: Dietary Supplement Use - Supplement Blend DS217: Questionnaire: Drug Use DS218: Questionnaire: Early Childhood DS219: Questionnaire: Family Smoking DS220: Questionnaire: Food Security DS221: Questionnaire: Health Insurance DS222: Questionnaire: Hepatitis C Follow Up Questionnaire DS223: Questionnaire: Hospital Utilization DS224: Questionnaire: Housing Characteristics DS225: Questionnaire: Immunization DS226: Questionnaire: Kidney Conditions - Urology DS227: Questionnaire: Medical Conditions DS228: Questionnaire: Miscellaneous Pain DS229: Questionnaire: Occupation DS230: Questionnaire: Oral Health DS231: Questionnaire: Osteoporosis DS232: Questionnaire: Pesticide Use DS233: Questionnaire: Physical Activity DS234: Questionnaire: Physical Activity Individual Activities File DS235: Questionnaire: Physical Functioning DS236: Questionnaire: Prescription Medications DS237: Questionnaire: Drug Information DS238: Questionnaire: Prostate Conditions DS239: Questionnaire: Prostate Specific Antigen Follow Up Questionnaire DS240: Questionnaire: Reproductive Health DS241: Questionnaire: Respiratory Health And Disease DS242: Questionnaire: Smoking And Tobacco Use DS243: Questionnaire: Smoking And Tobacco Use (MEC) DS244: Questionnaire: Social Support DS245: Questionnaire: Sexual Behavior DS246: Questionnaire: Vision DS247: Questionnaire: Weight History The most recent series of data collection waves for NHANES began in 1999. Every year, approximately 7,000 individuals, of all ages, are interviewed in their homes and of these, approximately 5,000 complete the health examination component of the survey. A majority of the health examinations are conducted in mobile examination centers (MECs). The MECs provide an ideal setting for the collection of high quality data in a standardized environment. In addition to the MEC examinations, a small number of survey participants receive an abbreviated health examination in their homes if they are unable to come to the MEC. The NHANES target population is the civilian, noninstitutionalized United States population. NHANES 2003-2004 includes over-sampling of low-income persons, adolescents 12-19 years of age, persons 60 years of age and older, African Americans, and Mexican Americans. Initially, households are identified for inclusion in the NHANES sample and an advance letter is mailed to each address informing the occupant(s) that an NHANES interviewer will visit their home. The household interview component is comprised of Screener, Sample Person, and Family interviews, each of which has a separate questionnaire (please refer to the data file documentation). Trained household interviewers administer all of the questionnaires. In most cases, the interview setting was the survey participant's home. The interview data are recorded using the Blaise computer-assisted personal interview (CAPI) system. When the interviewer arrives at the home, he or she shows an official identification badge and briefly explains the purpose of the survey. If the occupant has not seen the advance letter, a copy is given to them to read. The interviewer requests that the occupant answer a brief questionnaire to determine if any household occupants are eligible to participate in NHANES. If eligible individuals are identified, the interviewer proceeds with efforts to recruit these individuals. Initially, the interviewer explains the household questionnaires to all eligible participants 16 years of age and older, informs the potential respondents of their rights, and provides assurances about the confidentiality of the survey data (reiterating what is stated in the advance letter). A majority of the household interviews are conducted during the first contact. If this is inconvenient for the survey participant, an appointment is made to administer the household interview questionnaires later. Household interviews for survey participants under 16 years of age are conducted with a proxy (usually their parent or guardian). If there is no one living in the household who is over 16, participants under 16 years of age are permitted to self-report. Respondents are asked to sign an Interview Consent Form agreeing to participate in the household interview portion of the survey. For participants 16-17 years of age a parent or guardian consents and the child gives his/her assent. After the household interview is completed, the interviewer reviews a second informed consent brochure with the participant. This brochure contains detailed information about the NHANES health examination component. All interviewed persons are asked to complete the health examination component. Those who agree to participate are asked to sign additional consent forms for the health examination component. The interviewer telephones the NHANES field office from the participant's home to schedule an appointment for the examination. The interviewer informs the participants that they will receive remuneration as well as reimbursement for transportation and childcare expenses, if necessary. Target Populations There are different target population groups for the topics within and between NHANES questionnaire sections. For example, in the Nutrition and Diet Behavior section, questions pertaining to infant nutrition and breast-feeding were asked of proxy respondents for children 6 years of age and younger, alcohol consumption frequency questions were asked of persons 20 years of age and older, and senior meal program participation questions were asked of respondents 60 years of age and older. Data users should review the survey questionnaire codebooks thoroughly to determine the target populations for each NHANES questionnaire section and sub-section. The NHANES Health Examination Component When a participant arrives at the MEC, the MEC Coordinator greets the participant and verifies all pertinent identifier information. Each participant receives a disposable paper gown and a pair of slippers to wear during their examination. Persons six years of age and older are asked to provide a urine specimen. MEC staff direct participants to the rooms where the examination components are conducted. In addition to the MEC Coordinator, each MEC survey team consists of one physician, one dentist, two dietary interviewers, three certified medical technologists, five health technicians, one phlebotomist, two interviewers and one computer data manager. Upon completion of the examination, each examinee is remunerated. Some of the medical findings from the examination are given to the examinees before they leave the MEC. The other reportable survey findings are mailed to participants after the laboratory assays and special tests are completed. MEC Operations Three MECs are equipped for use in NHANES. Each MEC consists of four large, inter-connected trailer units. An advance team sets up the MECs prior to the start of the survey examinations. Water, sewer, electrical, and communication lines are connected during set-up. The MEC equipment and data collection systems must be checked and calibrated prior to the start of survey data collection. The MECs are open a total of five days per week, and the nonoperational days change on a rotating basis so that appointments can be scheduled on any day of the week. Two examination sessions are conducted daily. For the convenience of the survey participants, appointments can be scheduled during morning, afternoon, or evening hours. The examinations require up to three hours to complete. At any given time during the survey, examinations are conducted at two survey locations simultaneously. Staff vacations are scheduled for periods of about one month at New Years and about two weeks during the summer, leaving ten and one-half months to conduct examinations. Home Examinations Participants who are 50 years and older or less than 1 year old and are unable or unwilling to travel to the MEC were offered a home examination administered by an examiner from the MEC. The National Health and Nutrition Examination Surveys (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The NHANES combines personal interviews and physical examinations, which focus on different population groups or health topics. These surveys have been conducted by the National Center for Health Statistics (NCHS) on a periodic basis from 1971 to 1994. In 1999 the NHANES became a continuous program with a changing focus on a variety of health and nutrition measurements which were designed to meet current and emerging concerns. The surveys examine a nationally representative sample of approximately 5,000 persons each year. These persons are located in counties across the United States, 15 of which are visited each year. For NHANES 2003-2004, there were 12,761 persons selected for the sample, 10,122 of those were interviewed (79.3 percent) and 9,643 (75.6 percent) were examined in the mobile examination centers (MEC). Many of the NHANES 2003-2004 questions were also asked in NHANES II 1976-1980, Hispanic HANES 1982-1984, NHANES III 1988-1994, and NHANES 1999-2002. New questions were added to the survey based on recommendations from survey collaborators, NCHS staff, and other interagency work groups. As in past health examination surveys, data were collected on the prevalence of chronic conditions in the population. Estimates for previously undiagnosed conditions, as well as those known to and reported by survey respondents, are produced through the survey. Risk factors, those aspects of a person's lifestyle, constitution, heredity, or environment that may increase the chances of developing a certain disease or condition, were examined. Data on smoking, alcohol consumption, sexual practices, drug use, physical fitness and activity, weight, and dietary intake were collected. Information on certain aspects of reproductive health, such as use of oral contraceptives and breastfeeding practices, were also collected. The diseases, medical conditions, and health indicators that were studied include: anemia, cardiovascular disease, diabetes and lower extremity disease, environmental exposures, equilibrium, hearing loss, infectious diseases and immunization, kidney disease, mental health and cognitive functioning, nutrition, obesity, oral health, osteoporosis, physical fitness and physical functioning, reproductive history and sexual behavior, respiratory disease (asthma, chronic bronchitis, emphysema), sexually transmitted diseases, skin diseases, and vision. The sample for the survey was selected to represent the United States population of all ages. Special emphasis in the 2003-2004 NHANES was on adolescent health and the health of older Americans. To produce reliable statistics for these groups, adolescents aged 15-19 years and persons aged 60 years and older were over-sampled for the survey. African Americans and Mexican Americans were also over-sampled to enable accurate estimates for these groups. Several important areas in adolescent health, including nutrition and fitness and other aspects of growth and development, were addressed. Since the United States has experienced dramatic growth in the number of older people during the twentieth century, the aging population has major implications for health care needs, public policy, and research priorities. NCHS is working with public health agencies to increase the knowledge of the health status of older Americans. NHANES has a primary role in this endeavor. In the examination, all participants visit the physician who takes their pulse or blood pressure. Dietary interviews and body measurements are included for everyone. All but the very young have a blood sample taken and see the dentist. Depending upon the age of the participant, the rest of the examination includes tests and procedures to assess the various aspects of health listed above. Usually, the older the individual, the more extensive the examination. Some persons who are unable or unwilling to come to the examination center may be given a less extensive examination in their homes. Demographic data file variables are grouped into three broad categories: (1) Status Variables: provide core information on the survey participant. Examples of the core variables include interview status, examination status, and sequence number. (Sequence number is a unique ID assigned to each sample person and is required to match the information on this demographic file to the rest of the NHANES 2003-2004 data). (2) Recoded Demographic Variables: these variables include age (age in months for persons through age 19 years, 11 months; age in years for 1- to 84-year-olds, and a top-coded age group of 85 years of age and older), gender, a race/ethnicity variable, current or highest grade of education completed, (less than high school, high school, and more than high school education), country of birth (United States, Mexico, or other foreign born), Poverty Income Ratio (PIR), income, and a pregnancy status variable (adjudicated from various pregnancy related variables). Some of the groupings were made due to limited sample sizes for the two-year data set. (3) Interview and Examination Sample Weight Variables: sample weights are available for analyzing NHANES 2003-2004 data. For a complete listing of survey contents for all years of the NHANES see the document -- Survey Content -- NHANES 1999-2010. audio computer-assisted self interview (ACASI), computer-assisted personal interview (CAPI), computer-assisted self interview (CASI), face-to-face interview, on-site questionnaire NCHS provides continuous updates/new data notification, as well as other important information for the NHANES. It is recommended that users of these data sign up for the information through the NHANES Listserv. The "What's New" page on the NHANES Web site provides updates/new information which may not be included in the listserv emails. Further, not all documentation files are included with this ICPSR release and may be found at the NHANES 2003-2004 Web site. In preparing the data files for this collection, the National Center for Health Statistics (NCHS) has removed direct identifiers and characteristics that might lead to identification of data subjects. As an additional precaution NCHS requires, under Section 308(d) of the Public Health Service Act (42 U.S.C. 242m), that data collected by NCHS not be used for any purpose other than statistical analysis and reporting. NCHS further requires that analysts not use the data to learn the identity of any persons or establishments and that the director of NCHS be notified if any identities are inadvertently discovered. ICPSR member institutions and other users ordering data from ICPSR are expected to adhere to these restrictions. Many variables that are listed in the Demographic questionnaire sections of the Household Interview were omitted (by NCHS) from this data release due to concerns about participant confidentiality. NCHS did not include confidential and administrative data in this release and further, some variables have been recoded or top-coded to protect the confidentiality of survey participants. Many of the NHANES 2003-2004 questions were also asked in NHANES II, 1976-1980, Hispanic HANES 1982-1984, and NHANES III, 1988-1994. New questions were added to the survey based on recommendations from survey collaborators, NCHS staff, and other interagency work groups. NHANES 2003-2004 survey design and demographic variables are found in Part 1 Demographics file in this release. All of the data files can be linked by using the common survey participant identification number (variable name: SEQN). Merging information from multiple NHANES 2003-2004 data files using SEQN ensures that the appropriate information for each survey participant is linked correctly. All data files should be sorted by SEQN. The NHANES 2003-2004 data files do not have the same number of records in each file. For example, there are different numbers of subjects in the Interview and Examination samples of the survey. Additionally, the number of records in each data file varies depending on gender and age profiles for the specific component(s). The sample person demographic file is composed of a limited set of core variables that are required to analyze NHANES 2003-2004 data. Per agreement with NCHS, ICPSR distributes the data file(s) and text of the technical documentation for this collection as prepared by NCHS. IMPORTANT NOTE CONCERNING THE AVAILABILITY OF DATA FILES: Dataset 37 is so large that it exceeds the software limitations for the Stata data file format (file extension .dta) and SAS Cport Transport file format (file extension .stc). As such, these files are not available. Users requiring these files are encouraged to utilize the ASCII version of the data file, along with the appropriate setup file for the desired software package. However, the setup file may need to be edited so that only a subset of the data is accessed, in an effort to avoid exceeding the software limitations. All data files have been merged with the demographics file with the exception of those parts that did not contain the linking variable SEQN, which are as follows: Questionnaire: Dietary Supplement Use - Supplement Information (Part 214), Questionnaire: Dietary Supplement Use - Ingredient Information (Part 215), Questionnaire: Dietary Supplement Use - Supplement Blend (Part 216), and Questionnaire: Drug Information (Part 237). Within the Oral Health (Dentition) File Part 33 variables "OHX02CSC through OHX15CSC and OHX18CSC through OHX31CSC, as well as OHX02SE, OHX03SE, OHX14SE, OHX15SE, OHX18SE, OHX19SE, OHX30SE, and OHX31SE" the NCHS coded multiple conditions per record. Users should consult the documentation and review the labeling of the variables in question for further information. The user guides that are presently available are comprised of documentation from the NCHS. These user guides do not reflect the merging of each file with the demographics file, as this was done by ICPSR staff. The old .tsv and .txt files have been taken down. The NHANES survey design is a stratified, multistage probability sample of the civilian noninstitutionalized United States population. The stages of sample selection are: (1) selection of Primary Sampling Units (PSUs) which are counties or small groups of contiguous counties, (2) segments within PSUs (a block or group of blocks containing a cluster of households), (3) households within segments, and (4) one or more participants within households. A total of 15 PSUs are visited during a 12-month time period. Details of the design and content of each survey are available at the NHANES Web site. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Created variable labels and/or value labels.; Standardized missing values.; Checked for undocumented or out-of-range codes.. The NHANES target population is the civilian, noninstitutionalized United States population. National Health and Nutrition Examination Survey (NHANES) and Followup Series Presence of Common Scales: DISC -- Predictive Scale

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  • Authors: Gomez-Pereira, Paola R; Hartmann, Manuela; Grob, C; Tarran, Glen A; +4 Authors

    Subtropical oceanic gyres are the most extensive biomes on Earth where SAR11 and Prochlorococcus bacterioplankton numerically dominate the surface waters depleted in inorganic macronutrients as well as in dissolved organic matter. In such nutrient poor conditions bacterioplankton could become photoheterotrophic. We assessed the photoheterotrophy of the key microbial taxa in the North Atlantic oligotrophic gyre and adjacent regions. The experimental work was performed on board the Royal Research Ship James Cook (cruise no. JC53, October-November 2010) as part of the Atlantic Meridional Transect programme, and on board the Royal Research Ship Discovery (cruise no. D369, August-September 2011). At each station, samples were collected from 20m depth with a sampling rosette of 20-l Niskin bottles mounted on aconductivity-temperature-depth profiler. Samples were collected in 1 l thermos flasks (washed with10% v/v HCl) in the dark and processed immediately. Depth of 20m was chosen because it represents the mixed layer and it was the shallowest depth unaffected by the ship's movement, including thrusting, that could artificially affect microbial metabolism in nutrient-depleted stratified surfacewaters. Molecular identification of flow-sorted cells CARD-FISH was performed on flow-sorted cells to identify the groups for which uptake rates were measured. High nucleic acid-containing bacteria, based on SYBR Green DNA staining, that had virtually undetectable chlorophyll autofluorescence, were phylogenetically affiliated with Prochlorococcus,in agreement with our previously reported results (Zubkov et al., 2007; doi:10.1111/j.1462-2920.2007.01324.x). Supplement to: Gomez-Pereira, Paola R; Hartmann, Manuela; Grob, C; Tarran, Glen A; Martin, Adrian Peter; Fuchs, Bernhard M; Scanlan, David J; Zubkov, Mikhail V (2012): Comparable light stimulation of organic nutrient uptake by SAR11 and Prochlorococcus in the North Atlantic subtropical gyre. The ISME Journal, 7(3), 603-614

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    Authors: Crotti, Ilaria; Quiquet, Aurélien; Landais, Amaëlle; Stenni, Barbara; +6 Authors

    The data here described are presented in the submitted paper Response of the Wilkes Subglacial Basin Ice Sheet to Southern Ocean Warming During Late Pleistocene Interglacials by Crotti et al. This data set includes new high resolution measurements of d-excess, d18O and ssNa+ for the Antarctic TALDICE ice core (Latitude: -72.783330, Longitude: 159.066670, Elevation: 2315.0 m). The new data set covers the interglacials periods of MIS 5.5, MIS 7.5 and MIS 9.3 (1486 m depth - 1548 m depth). The data are drawn on the TALDICE deep1 chronology (Crotti et al. 2021). The d-excess (d = δD − 8 × δ18O) (permill) record covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 5 cm resolution and spans the following age-depths intervals: • MIS 5.5. Between 1378.5 and 1421.65 m depth, 110-135 ka • MIS 7.5. Between 1521.85 and 1524.5 m depth, 243-248 ka • MIS 9.3. Between 1541.80 and 1547.90 m depth, 320-343 ka The d18O record (permill) covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 5 cm resolution and spans the following age-depths intervals: • MIS 7.5. Between 1521.85 and 1524.5 m depth, 243-248 ka • MIS 9.3. Between 1541.80 and 1547.90 m depth, 320-343 ka The ssNa+ fluxes record covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 8 cm resolution and pans the following age-depths intervals: • MIS 7.5. Between 1521.81 and 1524.54 m depth, 243-248 ka • MIS 9.3. Between 1541.73 and 1547.96 m depth, 320-343 ka The d18O and dD (non presented here) to calculate the d-excess were analysed in Italy (University of Venice) and France (LSCE) using the Cavity Ring Down Spectroscopy (CRDS) technique. Analyses were performed using a Picarro isotope water analyser (L2130-i version for both laboratories). The data were calibrated using a three-point linear calibration with three lab-standards that were themselves calibrated versus Standard Mean Ocean Water (SMOW). The average precision for the δ18O and δD measurements is 0.1 and 0.7 ‰, respectively. The concentrations of ssNa+ were measured on TALDICE ice samples at 8 cm resolution by classical ion chromatography on discrete samples collected using a melting device connected to an auto-sampler for the MIS 7.5 and MIS 9.3 whereas Continuous Flow Analysis (CFA) was applied for MIS 5.5 samples. The total deposition ssNa+ flux was calculated multiplying the measured ice concentration of ssNa+ by the reconstructed accumulation rate. The accumulation rates were derived from the accumulation rates were obtained from the TALDICE deep1 age scale (Crotti et al. 2021).

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    Authors: Bajo, Petra; Drysdale, Russell N; Woodhead, Jon D; Hellstrom, John C; +10 Authors

    2020-05-18: Correction of depth values to meter (multiplication of prior values by 100), parameter set to "DEPTH, sediment/rock" (corrected revised meters composite depth); update of PIs

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    Authors: Anderson, Harris J; Pedro, Joel B; Bostock, Helen C; Chase, Zanna; +1 Authors
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    Authors: Seresinhe, Chanuki Illushka; Preis, Tobias; Moat, Helen Susannah;

    Data for Using Deep Learning to Quantify the Beauty of Outdoor PlacesThis database lists all the Geograph images we used from Scenic-Or-Not (http://scenicornot.datasciencelab.co.uk/) to help us understand what beautiful outdoor spaces are composed of. We only include images in our analysis that have been rated more than three times.Scenic-Or-Not-Geograph_URIs.csvData for Using Deep Learning to Quantify the Beauty of Outdoor PlacesIn order to predict the scenic ratings of images for which we do not already have crowdsourced data, we use a transfer learning approach to leverage the knowledge of the Places365 CNN [1], which can predict the place category of a scene with a high degree of accuracy. We modify the Places CNN to instead predict the scenicness of an image. We fine-tune our CNN using 80% of the Scenic-Or-Not dataset [2], and use the remaining 20% test set to check our prediction accuracy. We calculate a performance measure using the Kendall Rank correlation between the predicted scenic scores and the actual scenic scores. The Scenic CNN trained using the Visual Geometry Group (VGG) convolutional neural network architecture delivers the best performance with an overall prediction accuracy of 0.658. We predict the scenicness of images of London uploaded to Geograph (http://www.geograph.org.uk/). This dataset includes all the scenic predictions used to create Figure6 "Predictions of scenic ratings for London images". [1] Zhou, B., Khosla, A., Lapedriza, A., Torralba, A., & Oliva, A. 2016 Places: An image database for deep scene understanding. arXiv preprint arXiv:1610.02055.London-Scenic-Predictions.csv Beautiful outdoor locations are protected by governments and have recently been shown to be associated with better health. But what makes an outdoor space beautiful? Does a beautiful outdoor location differ from an outdoor location that is simply natural? Here, we explore whether ratings of over 200 000 images of Great Britain from the online game Scenic-Or-Not, combined with hundreds of image features extracted using the Places Convolutional Neural Network, might help us understand what beautiful outdoor spaces are composed of. We discover that, as well as natural features such as ‘Coast’, ‘Mountain’ and ‘Canal Natural’, man-made structures such as ‘Tower’, ‘Castle’ and ‘Viaduct’ lead to places being considered more scenic. Importantly, while scenes containing ‘Trees’ tend to rate highly, places containing more bland natural green features such as ‘Grass’ and ‘Athletic Fields’ are considered less scenic. We also find that a neural network can be trained to automatically identify scenic places, and that this network highlights both natural and built locations. Our findings demonstrate how online data combined with neural networks can provide a deeper understanding of what environments we might find beautiful and offer quantitative insights for policymakers charged with design and protection of our built and natural environments.

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    Authors: Crotti, Ilaria; Quiquet, Aurélien; Landais, Amaëlle; Stenni, Barbara; +6 Authors

    The data here described are presented in the submitted paper Response of the Wilkes Subglacial Basin Ice Sheet to Southern Ocean Warming During Late Pleistocene Interglacials by Crotti et al. This data set includes new high resolution measurements of d-excess, d18O and ssNa+ for the Antarctic TALDICE ice core (Latitude: -72.783330, Longitude: 159.066670, Elevation: 2315.0 m). The new data set covers the interglacials periods of MIS 5.5, MIS 7.5 and MIS 9.3 (1486 m depth - 1548 m depth). The data are drawn on the TALDICE deep1 chronology (Crotti et al. 2021). The d-excess (d = δD − 8 × δ18O) (permill) record covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 5 cm resolution and spans the following age-depths intervals: • MIS 5.5. Between 1378.5 and 1421.65 m depth, 110-135 ka • MIS 7.5. Between 1521.85 and 1524.5 m depth, 243-248 ka • MIS 9.3. Between 1541.80 and 1547.90 m depth, 320-343 ka The d18O record (permill) covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 5 cm resolution and spans the following age-depths intervals: • MIS 7.5. Between 1521.85 and 1524.5 m depth, 243-248 ka • MIS 9.3. Between 1541.80 and 1547.90 m depth, 320-343 ka The ssNa+ fluxes record covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 8 cm resolution and pans the following age-depths intervals: • MIS 7.5. Between 1521.81 and 1524.54 m depth, 243-248 ka • MIS 9.3. Between 1541.73 and 1547.96 m depth, 320-343 ka The d18O and dD (non presented here) to calculate the d-excess were analysed in Italy (University of Venice) and France (LSCE) using the Cavity Ring Down Spectroscopy (CRDS) technique. Analyses were performed using a Picarro isotope water analyser (L2130-i version for both laboratories). The data were calibrated using a three-point linear calibration with three lab-standards that were themselves calibrated versus Standard Mean Ocean Water (SMOW). The average precision for the δ18O and δD measurements is 0.1 and 0.7 ‰, respectively. The concentrations of ssNa+ were measured on TALDICE ice samples at 8 cm resolution by classical ion chromatography on discrete samples collected using a melting device connected to an auto-sampler for the MIS 7.5 and MIS 9.3 whereas Continuous Flow Analysis (CFA) was applied for MIS 5.5 samples. The total deposition ssNa+ flux was calculated multiplying the measured ice concentration of ssNa+ by the reconstructed accumulation rate. The accumulation rates were derived from the accumulation rates were obtained from the TALDICE deep1 age scale (Crotti et al. 2021).

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Crotti, Ilaria; Quiquet, Aurélien; Landais, Amaëlle; Stenni, Barbara; +6 Authors

    The data here described are presented in the submitted paper Response of the Wilkes Subglacial Basin Ice Sheet to Southern Ocean Warming During Late Pleistocene Interglacials by Crotti et al. This data set includes new high resolution measurements of d-excess, d18O and ssNa+ for the Antarctic TALDICE ice core (Latitude: -72.783330, Longitude: 159.066670, Elevation: 2315.0 m). The new data set covers the interglacials periods of MIS 5.5, MIS 7.5 and MIS 9.3 (1486 m depth - 1548 m depth). The data are drawn on the TALDICE deep1 chronology (Crotti et al. 2021). The d-excess (d = δD − 8 × δ18O) (permill) record covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 5 cm resolution and spans the following age-depths intervals: • MIS 5.5. Between 1378.5 and 1421.65 m depth, 110-135 ka • MIS 7.5. Between 1521.85 and 1524.5 m depth, 243-248 ka • MIS 9.3. Between 1541.80 and 1547.90 m depth, 320-343 ka The d18O record (permill) covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 5 cm resolution and spans the following age-depths intervals: • MIS 7.5. Between 1521.85 and 1524.5 m depth, 243-248 ka • MIS 9.3. Between 1541.80 and 1547.90 m depth, 320-343 ka The ssNa+ fluxes record covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 8 cm resolution and pans the following age-depths intervals: • MIS 7.5. Between 1521.81 and 1524.54 m depth, 243-248 ka • MIS 9.3. Between 1541.73 and 1547.96 m depth, 320-343 ka The d18O and dD (non presented here) to calculate the d-excess were analysed in Italy (University of Venice) and France (LSCE) using the Cavity Ring Down Spectroscopy (CRDS) technique. Analyses were performed using a Picarro isotope water analyser (L2130-i version for both laboratories). The data were calibrated using a three-point linear calibration with three lab-standards that were themselves calibrated versus Standard Mean Ocean Water (SMOW). The average precision for the δ18O and δD measurements is 0.1 and 0.7 ‰, respectively. The concentrations of ssNa+ were measured on TALDICE ice samples at 8 cm resolution by classical ion chromatography on discrete samples collected using a melting device connected to an auto-sampler for the MIS 7.5 and MIS 9.3 whereas Continuous Flow Analysis (CFA) was applied for MIS 5.5 samples. The total deposition ssNa+ flux was calculated multiplying the measured ice concentration of ssNa+ by the reconstructed accumulation rate. The accumulation rates were derived from the accumulation rates were obtained from the TALDICE deep1 age scale (Crotti et al. 2021).

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Crotti, Ilaria; Quiquet, Aurélien; Landais, Amaëlle; Stenni, Barbara; +6 Authors

    The data here described are presented in the submitted paper Response of the Wilkes Subglacial Basin Ice Sheet to Southern Ocean Warming During Late Pleistocene Interglacials by Crotti et al. This data set includes new high resolution measurements of d-excess, d18O and ssNa+ for the Antarctic TALDICE ice core (Latitude: -72.783330, Longitude: 159.066670, Elevation: 2315.0 m). The new data set covers the interglacials periods of MIS 5.5, MIS 7.5 and MIS 9.3 (1486 m depth - 1548 m depth). The data are drawn on the TALDICE deep1 chronology (Crotti et al. 2021). The d-excess (d = δD − 8 × δ18O) (permill) record covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 5 cm resolution and spans the following age-depths intervals: • MIS 5.5. Between 1378.5 and 1421.65 m depth, 110-135 ka • MIS 7.5. Between 1521.85 and 1524.5 m depth, 243-248 ka • MIS 9.3. Between 1541.80 and 1547.90 m depth, 320-343 ka The d18O record (permill) covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 5 cm resolution and spans the following age-depths intervals: • MIS 7.5. Between 1521.85 and 1524.5 m depth, 243-248 ka • MIS 9.3. Between 1541.80 and 1547.90 m depth, 320-343 ka The ssNa+ fluxes record covers the periods MIS 5.5 , MIS 7.5 and 9.3 MIS is at 8 cm resolution and pans the following age-depths intervals: • MIS 7.5. Between 1521.81 and 1524.54 m depth, 243-248 ka • MIS 9.3. Between 1541.73 and 1547.96 m depth, 320-343 ka The d18O and dD (non presented here) to calculate the d-excess were analysed in Italy (University of Venice) and France (LSCE) using the Cavity Ring Down Spectroscopy (CRDS) technique. Analyses were performed using a Picarro isotope water analyser (L2130-i version for both laboratories). The data were calibrated using a three-point linear calibration with three lab-standards that were themselves calibrated versus Standard Mean Ocean Water (SMOW). The average precision for the δ18O and δD measurements is 0.1 and 0.7 ‰, respectively. The concentrations of ssNa+ were measured on TALDICE ice samples at 8 cm resolution by classical ion chromatography on discrete samples collected using a melting device connected to an auto-sampler for the MIS 7.5 and MIS 9.3 whereas Continuous Flow Analysis (CFA) was applied for MIS 5.5 samples. The total deposition ssNa+ flux was calculated multiplying the measured ice concentration of ssNa+ by the reconstructed accumulation rate. The accumulation rates were derived from the accumulation rates were obtained from the TALDICE deep1 age scale (Crotti et al. 2021).

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    Authors: Montenegro-Johnson, Thomas D.; Gadêlha, Hermes; Smith, David J.; Gadelha, H.;

    Sperm traverse their microenvironment through viscous fluid by propagating flagellar waves; the waveform emerges as a consequence of elastic structure, internal active moments and low Reynolds number fluid dynamics. Engineered microchannels have recently been proposed as a method of sorting and manipulating motile cells; the interaction of cells with these artificial environments therefore warrants investigation. A numerical method is presented for large-amplitude elastohydrodynamic interaction of active swimmers with domain features. This method is employed to examine hydrodynamic scattering by a model microchannel backstep feature. Scattering is shown to depend on backstep height and the relative strength of viscous and elastic forces in the flagellum. In a ‘high viscosity’ parameter regime corresponding to human sperm in cervical mucus analogue, this hydrodynamic contribution to scattering is comparable in magnitude to recent data on contact effects, being of the order of 5°–10°. Scattering can be positive or negative depending on the relative strength of viscous and elastic effects, emphasizing the importance of viscosity on the interaction of sperm with their microenvironment. The modulation of scattering angle by viscosity is associated with variations in flagellar asymmetry induced by the elastohydrodynamic interaction with the boundary feature. Simulation resultsTrajectory and waveform data for elastohydrodynamic simulations of sperm swimming over geometric features.simulation_results.zip

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