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In this study; bending properties of beech wood (Fagus orientalis) were predicted using stress - wave method and compared with static bending tests. First, lumbers which were different in length and cross section were weighed and dimensions were measured. Then, moisture contents were obtained via moisture meter. By using the density, moisture, and dimensions of the samples in MTG Timber Grader device, dynamic modulus of elasticity values were determined. And then, samples were subjected to 3 point bending test. Modulus of elasticity and bending strengths were calculated using load - deformation curves. Regression models were developed to interpret relationships between dynamic modulus elasticity and bending properties. Results showed that there is a high regression coefficient (0,86) between dynamic modulus of elasticity and static modulus of elasticity. Regression coefficient between dynamic modulus of elasticity and static bending strength was measured as (0,72) and regression coefficient between static modulus of elasticity and static bending strength was measured as (0,74). Results indicate that bending properties of beech wood lumber can be predicted using stress wave method.

In this study; bending properties of beech wood (Fagus orientalis) were predicted using stress - wave method and compared with static bending tests. First, lumbers which were different in length and cross section were weighed and dimensions were measured. Then, moisture contents were obtained via moisture meter. By using the density, moisture, and dimensions of the samples in MTG Timber Grader device, dynamic modulus of elasticity values were determined. And then, samples were subjected to 3 point bending test. Modulus of elasticity and bending strengths were calculated using load - deformation curves. Regression models were developed to interpret relationships between dynamic modulus elasticity and bending properties. Results showed that there is a high regression coefficient (0,86) between dynamic modulus of elasticity and static modulus of elasticity. Regression coefficient between dynamic modulus of elasticity and static bending strength was measured as (0,72) and regression coefficient between static modulus of elasticity and static bending strength was measured as (0,74). Results indicate that bending properties of beech wood lumber can be predicted using stress wave method.

In this study; bending properties of beech wood (Fagus orientalis) were predicted using stress - wave method and compared with static bending tests. First, lumbers which were different in length and cross section were weighed and dimensions were measured. Then, moisture contents were obtained via moisture meter. By using the density, moisture, and dimensions of the samples in MTG Timber Grader device, dynamic modulus of elasticity values were determined. And then, samples were subjected to 3 point bending test. Modulus of elasticity and bending strengths were calculated using load - deformation curves. Regression models were developed to interpret relationships between dynamic modulus elasticity and bending properties. Results showed that there is a high regression coefficient (0,86) between dynamic modulus of elasticity and static modulus of elasticity. Regression coefficient between dynamic modulus of elasticity and static bending strength was measured as (0,72) and regression coefficient between static modulus of elasticity and static bending strength was measured as (0,74). Results indicate that bending properties of beech wood lumber can be predicted using stress wave method.

In this study; bending properties of beech wood (Fagus orientalis) were predicted using stress - wave method and compared with static bending tests. First, lumbers which were different in length and cross section were weighed and dimensions were measured. Then, moisture contents were obtained via moisture meter. By using the density, moisture, and dimensions of the samples in MTG Timber Grader device, dynamic modulus of elasticity values were determined. And then, samples were subjected to 3 point bending test. Modulus of elasticity and bending strengths were calculated using load - deformation curves. Regression models were developed to interpret relationships between dynamic modulus elasticity and bending properties. Results showed that there is a high regression coefficient (0,86) between dynamic modulus of elasticity and static modulus of elasticity. Regression coefficient between dynamic modulus of elasticity and static bending strength was measured as (0,72) and regression coefficient between static modulus of elasticity and static bending strength was measured as (0,74). Results indicate that bending properties of beech wood lumber can be predicted using stress wave method.

Serhat Ozkan,1 Demet Ozbabalik Adapinar,1 Nese Tuncer Elmaci,2 Didem Arslantas31Department of Neurology, Eskisehir Osmangazi University Medical Faculty, Eskisehir, Turkey; 2Department of Neurology, Marmara University Medical Faculty, Istanbul, Turkey; 3Department of Public Health, Eskisehir Osmangazi University Medical Faculty, Eskisehir, TurkeyAbstract: Although ideomotor limb apraxia is considered to be a typical sign of cortical pathologies such as Alzheimer’s disease (AD), it has been also reported in subcortical neurodegenerative diseases and vascular lesions. We aimed to investigate the difference between AD, subcortical vascular dementia (SVaD) and mild cognitive impairment (MCI) patients by means of ideomotor limb apraxia frequency and severity. Ninety-six AD, 72 SVaD, and 84 MCI patients were assessed with the mini-mental status examination (MMSE), clinical dementia rating (CDR) and the apraxia screening test of TULIA (AST). Apraxia was significantly more frequent in the AD patients (32.3%) than in both of the SVaD (16.7%) and MCI (4.8%) patients. The frequency of apraxia was also significantly higher in SVaD patients than in MCI patients. AD patients had significantly lower apraxia scores than both SVaD and MCI patients. In addition, a significant difference was found between SVaD and MCI patients in terms of apraxia scores. These results suggest that the widespread belief of the association between apraxia and cortical dementias is not exactly correct. The significant difference between both of the dementia groups and the MCI patients suggests that the absence of apraxia can be an indicator for MCI diagnosis.Keywords: apraxia, Alzheimer’s disease, subcortical vascular dementia, mild cognitive impairment