International Asteroid Warning Network Timing Campaign : 2019 XS

Peer reviewe

Programma obespecheniya ortopedicheskoy obuv'yu bol'nykh sakharnym diabetom v Sankt-Peterburge

Цель. Анализ ближайших результатов обеспечения ортопедической обувью больных СД, находящихся под наблюдением кабинетов диабетическая стопа? двух Городских диабетологических центров (1999-2001). Материалы и методы. Проанализированы исходы у 207 больных СД, получивших направления в кабинетах диабетическая стопа? и впоследствии наблюдавшихся в них, которым было выдано 227 пар обуви (часть пациентов получила по две пары). Тяжесть диабетической полинейропатии оценивалась тестированием 10-гр. монофиламентом. Наличие ангиопатии нижних конечностей подтверждалось отсутствием пульса хотя бы на одной из артерий стоп вне зависимости от симптомов перемежающейся хромоты. Основным критерием эффективности обеспечения ортопедической обувью при краткосрочном наблюдении (6-12 мес.) были выбраны частота ношения этой обуви, частота развития повреждений вследствие ношения ортообуви. Результаты. Из 227 пар обуви больные не носили 83 пары (36,6%). Достоверных различий между пациентами, носящими и не носящими ортообувь, по основным клиническим параметрам (возраст, длительность диабета, частота нейропатии и ангиопатии) выявлено не было. Не выявлено и достоверных различий в ношении ортообуви у больных с высоким (язва стопы/ампутация в анамнезе, нейропатия, ангиопатия, деформации стоп) и низким риском (без этих факторов) развития язвы стопы/ампутации. Анализ причин отказа от ношения уже полученной обуви показал, что основными проблемами были несоответствие формы и размера особенностям стопы пациента (35 случаев), неудобство при ходьбе, вызванное неудачными конструктивными особенностями обуви (14 пациентов), слишком жесткий верхний край обуви (голенище) ? 12 больных. Выводы. Полученные данные свидетельствуют о том, что система обеспечения орто-обувью больных сахарным диабетом, особенно имеющих высокий риск развития язв/ампутаций, нуждается в изменении

Method of separate determination of high-ohmic sample resistance and contact resistance

A method of separate determination of two-pole sample volume resistance and contact resistance is suggested. The method is applicable to high-ohmic semiconductor samples: semi-insulating gallium arsenide, detector cadmium-zinc telluride (CZT), etc. The method is based on near-contact region illumination by monochromatic radiation of variable intensity from light emitting diodes with quantum energies exceeding the band gap of the material. It is necessary to obtain sample photo-current dependence upon light emitting diode current and to find the linear portion of this dependence. Extrapolation of this linear portion to the Y-axis gives the cut-off current. As the bias voltage is known, it is easy to calculate sample volume resistance. Then, using dark current value, one can determine the total contact resistance. The method was tested for n-type semi-insulating GaAs. The contact resistance value was shown to be approximately equal to the sample volume resistance. Thus, the influence of contacts must be taken into account when electrophysical data are analyzed

sPlotOpen - An environmentally balanced, open-access, global dataset of vegetation plots

Motivation Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called 'sPlot', compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain Global, 0.01-40,000 m(2). Time period and grain 1888-2015, recording dates. Major taxa and level of measurement 42,677 vascular plant taxa, plot-level records. Software format Three main matrices (.csv), relationally linked

International Asteroid Warning Network Timing Campaign : 2019 XS

Peer reviewe

sPlot:a new tool for global vegetation analyses

Abstract Aims: Vegetation‐plot records provide information on the presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community‐weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale

sPlotOpen:an environmentally balanced, open-access, global dataset of vegetation plots

Abstract Motivation: Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained: Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain: Global, 0.01–40,000 m². Time period and grain: 1888–2015, recording dates. Major taxa and level of measurement: 42,677 vascular plant taxa, plot-level records. Software format: Three main matrices (.csv), relationally linked