Volume Tables Research Articles

The Siberian spruce (Picea obovata L.) stem formation in the Yenisei Range

The present research investigated the Siberian spruce stem formation features, basing on materials from 15 sample plots, where we cut and measured 160 model trees. We indicated that the stem form factor is 12-17% less than the average in current volume tables, which entails errors in determining stem and growing stock volumes. We established features of the spruce bark formation at different relative lengths. We did not reveal any influence of bark on the stem shape. We also made some recommendations for the inventory assessment of spruce stands in the study area.

Table of Content Volume 24 No.2 July 2021

Table of Content Volume 24 No.2 July 2021

The teak log volume estimation model for Sawn Timber: Case in Forest Management Unit (FMU) Bojonegoro – Perhutani – East Java - Indonesia

Cultivation of teak continues to be developed. The decision to harvest teak trees depends on the economic value. The economic value of the teak tree is the money value contained in the teak trunk which is divided into parts which are then called nodes. The determination of the part is based on the diameter size. Perhutani recognizes three classes of nodes namely A1 (10 - 19 cm), A2 (20 - 29 cm) and A3 (> 30 cm) and are expressed in the log volume table (TVL). Perhutani’s TVL stated the relationship between tree circumference and log volume. This relationship is expressed in the estimator model and classified by nodes. To enter these numbers using constants that are difficult to account for. For this reason, this study aims to provide a volume estimator model for teak logs. The method used is a destructive method and regression analysis. The results showed that TVL in FMU can be explained based on the class of nodes but ignores the place of growth. The shape of the model is compound. This model works well at tree circumference intervals of 50 - 250 cm. Research like this needs to be propagated with wider tree circumference intervals.

Table of Content Volume 60, Number 8, August 2021

Genes, Chromosomes and CancerVolume 60, Issue 8 p. 527-530 ISSUE INFORMATION – TOCFree Access Table of Content Volume 60, Number 8, August 2021 First published: 10 June 2021 https://doi.org/10.1002/gcc.22869AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume60, Issue8August 2021Pages 527-530 RelatedInformation

Parameterized Splitting of Summed Volume Tables

AbstractSummed Volume Tables (SVTs) allow one to compute integrals over the data values in any cubical area of a three‐dimensional orthogonal grid in constant time, and they are especially interesting for building spatial search structures for sparse volumes. However, SVTs become extremely memory consuming due to the large values they need to store; for a dataset of n values an SVT requires 𝒪(n log n) bits. The 3D Fenwick tree allows recovering the integral values in 𝒪(log3 n) time, at a memory consumption of 𝒪(n) bits. We propose an algorithm that generates SVT representations that can flexibly trade speed for memory: From similar characteristics as SVTs, over equal memory consumption as 3D Fenwick trees at significantly lower computational complexity, to even further reduced memory consumption at the cost of raising computational complexity. For a 641 × 9601 × 9601 binary dataset, the algorithm can generate an SVT representation that requires 27.0GB and 46 · 8 data fetch operations to retrieve an integral value, compared to 27.5GB and 1521·8 fetches by 3D Fenwick trees, a decrease in fetches of 97%. A full SVT requires 247.6GB and 8 fetches per integral value. We present a novel hierarchical approach to compute and store intermediate prefix sums of SVTs, so that any prescribed memory consumption between 𝒪(n) bits and 𝒪(n log n) bits is achieved. We evaluate the performance of the proposed algorithm in a number of examples considering large volume data, and we perform comparisons to existing alternatives.

Table of Content Volume 60, Number 7, July 2021

Table of Content Volume 60, Number 7, July 2021

Table of Content Volume 24 No.1 March 2021

Table of Content Volume 24 No.1 March 2021

Table of Content Volume 60, Number 6, June 2021

Table of Content Volume 60, Number 6, June 2021

Investigation of the compatibility taper equations of Schima superba based on nonlinear measurement errors

Forest resource environment monitoring aims to observe, analyze, and evaluate both the number and quality of forest resources, which has aroused great attention by scholars from all over the world. Investigating stand growth condition is of great significance to the number estimation and management of forest resources. In order to more accurately estimate the increment and stand volume of Schima superba Gardn. et Champ., this study focused on forest survey data of Schima superba artificial forest and determined the optimal basic models of the DBH growth, the tree height curve, and the taper equation using the TOPSIS method with entropy weights, during which the coefficient of determination (R2), the model prediction precision (P (%)), the model accuracy (V), the absolute bias (AB), the root-mean-square error (RMSE), and the sum of squares of errors (SSE) were selected as the evaluation indexes. Then, the equations were combined using nonlinear measurement error method for parameter solving. Results show that the new model shows higher precision with remarkably enhanced evaluation indexes. Among the three optimal basic models, the V, AB, the RMSE, and the SSE decreased significantly. According to the paired t test results, the predicted values using the new model with measurement error model exhibit no significant difference from the measured data, suggesting good adaptivity. Moreover, the present results can more accurately calculate the diameter and stand volume of any part of Schima superba, provide the basis for calculating both biomass and carbon sequestration, and offer technical supports for formulating the merchantable volume table. Therefore, owing to the consideration of model parameter inaccuracy caused by the measurement errors in forest survey, the established equation performs well in compatibility and consistency. The present study can provide scientific theoretical basis and decision schemes for the forest environment monitoring and evaluation, forest management, etc.

Table of Content Volume 24 No.1 March 2021

Table of Content Volume 24 No.1 March 2021

Table of Content Volume 60, Number 5, May 2021

Table of Content Volume 60, Number 5, May 2021

Abstract P505: Prediction of Infarct Volume at the 24 Hours After Late Window Presentation With Perfusion Imaging in Patients With Anterior Circulation Large Vessel Occlusion

Introduction: We sought to evaluate the accuracy of perfusion-weighted imaging (PWI) in late presenting patients for estimating the infarct volume at 24 hours after presentation. Methods: This is a secondary analysis of DEFUSE 3, which included stroke patients with anterior circulation occlusion within 6-16 hours of last known normal. The primary outcome is the final infarct volume on a 24-hour MRI scan (volume of DWI positive tissue), adjusted for the baseline infarct volume. We censored 3 patients with 24-hour follow-up MRI infarct volumes >300 mL, which we considered non-physiologic for a hemispheric stroke. The primary predictors are the baseline volume of Tmax >6s, Tmax >10s, and hypoperfusion intensity ratio (HIR: Tmax10/Tmax6) on CT/MR perfusion at hospital admission. We stratified the cohort into 4 categories (untreated, TICI 0-2a, TICI 2b, and TICI3) and fit linear regression models to each of our predictors. Results: We included 147 patients, of which 69 were untreated, 17 had TICI 0-2a, 46 had TICI 2b, and 15 had TICI 3. In untreated patients, both HIR and Tmax10 volume were predictive of adjusted 24-hour follow-up infarct volume (Table). In treated patients, there were no consistent relationships between the perfusion imaging variables and adjusted final infarct volume (Table). Conclusion: For patients with late window anterior circulation large vessel occlusion stroke, HIR and Tmax10 volume appear to be reliable predictors of subsequent infarct volume in untreated patients. For patients treated with thrombectomy, further research is warranted to better understand the more complex relationship between baseline perfusion imaging and the 24 hour, and beyond, infarct volume.

Table of Content Volume 60, Number 4, April 2021

Table of Content Volume 60, Number 4, April 2021

Table of Content Volume 60, Number 3, March 2021

Table of Content Volume 60, Number 3, March 2021

Table of Contents Volume 12 Number 1 January 2021

Table of Contents Volume 12 Number 1 January 2021

Local Volume Equations and Tables for two Forest Management Units in Bhutan: An Attempt to Provide FMU Specific Estimate of Timber Volume for Sustainable Forest Management

This study developed tree species specific local volume equations and tables for Lingmethang and Rongmanchu Forest Management Units. The field work was conducted between December, 2019 and January 2020. Data was collected for five species (Schima sp., Ltihocarpus sp., Acrocarpus fraxinifolius, Pinus roxburghii and Castanopsis tribuloides) for Lingmethang FMU and six species (Beilschmedia sp., Persea sp., Quercus sp., Alnus nepalensis, Schima wallichii and Cinnamomum sp.) of trees for Rongmanchu FMU. The height and diameter over bark were measured for every sample trees. Using the height and diameter, volumes for each sample tree was calculated and then the models generated were fitted with a minimum of 32 trees per species, which were destructively felled for the purpose. The models were run in R version 3.4.4. A total of 16 models were fitted and tested for each species. The selected models performed well with small deviation for individual trees.

Development of Volume Tables for JKSCED and JKSCEU Clones of <i>Eucalyptus</i> for Southern Odisha

Eucalyptus has proved itself as a species highly suited for agro-forestry in India and is commercially grown by farmers in their fields. JK Papers introduced two new hybrid clones JKSCED and JKSCEU which have become very popular with farmers and are being extensively planted in South Odisha. Volume tables, developed for the mentioned clones on the basis of regression models using a variety of predictors will be useful to farmers/ growers, research workers and planners in their respective areas, for predicting future yields, estimating increment and to assess returns on capital and also for scientific purposes. The model with product of square of diameter at breast height and height (d 2 h) as predictable variable was observed to be the best for both the clones.

Table of Content Volume 60, Number 2, February 2021

Table of Content Volume 60, Number 2, February 2021

Table of Content Volume 23 No.3 November 2020

Table of Content Volume 23 No.3 November 2020

Volume 72 Table of Contents

Arthritis Care & ResearchVolume 72, Issue 12 p. 1835-1854 Volume 72 Table of Contents Volume 72 Table of Contents First published: 27 November 2020 https://doi.org/10.1002/acr.24506 AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat Volume72, Issue12December 2020Pages 1835-1854 RelatedInformation