Comparison of soybean evapotranspirations measured by weighing lysimeter and Bowen ratio-energy balance methods

Lysimeters are considered the standard for evapotranspiration (ET) measurements. However, these units are often not replicated and are few in number at any given location. The Bowen ratio-energy balance (BREB) is a micrometeorological method often used to estimate ET because of its simplicity, robustness, and cost. In this paper, ET of irrigated soybean (Glycine max L.) was directly measured by weighing lysimeter and estimated by BREB method over a growing season in a semi-arid climate of eastern Mediterranean region. The study was conducted in Adana-Turkey du ring the summer of 2009 on a 0.12 ha area with a weighing lysimeter (2.0 × 2.0 × 2.5 m) located in the center of the field completely covered by well watered soybean where the prevailing direction of the wind and the upwind fetch was about 60 m. Cumulative evapotranspiration totals from the lysimeter and BREB methods were 354 and 405 mm, respectively. The BREB method showed a good performance for daily ET estimation when compared to values measured by lysimeter. This method, with a root mean square error (RMSE) of 0.79 mmd-1 and a 0.96 index of agreement, over-estimates lysimetric measurements by 15%. TheBREB method also performs well compared with lysimetric measurements for hourly ET, but produces overestimation of 14% with RMSE of 0.128 mmh-1, and a 0.92 index of agreement

İnce Kirişlerin Elastik Davranışlarının NIY ve RNIY Yöntemleri İle İncelemesi

Konferans Bildirisi -- Teorik ve Uygulamalı Mekanik Türk Milli Komitesi, 2013Conference Paper -- Theoretical and Applied Mechanical Turkish National Committee, 2013Bu çalışmada, ince kirişlerin elastik davranışlarının incelenmesi, ağsız yöntemlerden olan Noktasal İnterpolasyon (NİY) ve Radyal Noktasal İnterpolasyon (RNİY) yöntemleri ile gerçekleştirilmiştir. Her bir yöntemde, iki farklı integrasyon tekniği kullanılmıştır. Standard olarak kullanılan Gauss integrasyon tekniği, Taylor noktasal integrasyon tekniği ile karşılaştırılmış, NİY ve RNİY üzerine etkileri araştırılmıştır. Noktasal direngenlik matrisinin elde edilmesi, Bernoulli-Euler kiriş teorisine göre gerçekleştirilmiştir. Farklı etki alanı büyüklükleri ve farklı RNİY şekil parametrelerinin çözümler üzerine etkileri ayrıca ele alınmıştır. Bir ankastre kiriş problemi, serbest uca tekil yük uygulanarak çözülmüştür. Elde edilen çözümler, ANSYS paket programı kullanılarak sonlu elemanlar yöntemiyle kıyaslanmıştır.In this study, the point interpolation method (PIM) and radial point interpolation method (RPIM) solutions of elastic thin beams are compared by using standard Gaussian integration and a nodal integration based on Taylor series expansion. The effects of integration schemes, support domain sizes and RPIM shape parameters on the convergency are also investigated. Nodal stiffness matrices are obtained using Bernoulli-Euler beam theory. A cantilever beam problem with concentrated load applied on one end is solved and the results are compared with finite element solutions in ANSYS

The impact of the internet of things on information institutions from the perspective of library employees

The present paper addresses the role of the Internet of Things applications in supporting knowledge management activities in information organizations and so their services improve. To achieve this objective, the research adopts the descriptive approach through the investigation and analysis of the intellectual outcome published in the Arab and foreign countries to identify the relationship between the Internet of Things and knowledge management activities in information institutions. The results indicated that information institutions benefited from the Internet of things in tracking all the physical and intangible entities in these institutions and defining their locations in case of loss or replacement. Moreover, they could define the numbers of visitors, peak hour and the most used sources. Hence, they offered fast and interactive services that comply with the aspirations of the beneficiaries. The research recommends that various information institutions should take the initiative to benefit from the Internet of things applications that fulfill the new requirements of their beneficiaries

Singers show enhanced performance and neural representation of vocal imitation

Humans have a remarkable capacity to finely control the muscles of the larynx, via distinct patterns of cortical topography and innervation that may underpin our sophisticated vocal capabilities compared with non-human primates. Here, we investigated the behavioural and neural correlates of laryngeal control, and their relationship to vocal expertise, using an imitation task that required adjustments of larynx musculature during speech. Highly trained human singers and non-singer control participants modulated voice pitch and vocal tract length (VTL) to mimic auditory speech targets, while undergoing real-time anatomical scans of the vocal tract and functional scans of brain activity. Multivariate analyses of speech acoustics, larynx movements and brain activation data were used to quantify vocal modulation behaviour and to search for neural representations of the two modulated vocal parameters during the preparation and execution of speech. We found that singers showed more accurate task-relevant modulations of speech pitch and VTL (i.e. larynx height, as measured with vocal tract MRI) during speech imitation; this was accompanied by stronger representation of VTL within a region of the right somatosensory cortex. Our findings suggest a common neural basis for enhanced vocal control in speech and song. This article is part of the theme issue ‘Voice modulation: from origin and mechanism to social impact (Part I)’

Singers show enhanced performance and neural representation of vocal imitation

Humans have a remarkable capacity to finely control the muscles of the larynx, via distinct patterns of cortical topography and innervation that may underpin our sophisticated vocal capabilities compared with non-human primates. Here, we investigated the behavioural and neural correlates of laryngeal control, and their relationship to vocal expertise, using an imitation task that required adjustments of larynx musculature during speech. Highly trained human singers and non-singer control participants modulated voice pitch and vocal tract length (VTL) to mimic auditory speech targets, while undergoing real-time anatomical scans of the vocal tract and functional scans of brain activity. Multivariate analyses of speech acoustics, larynx movements and brain activation data were used to quantify vocal modulation behaviour and to search for neural representations of the two modulated vocal parameters during the preparation and execution of speech. We found that singers showed more accurate task-relevant modulations of speech pitch and VTL (i.e. larynx height, as measured with vocal tract MRI) during speech imitation; this was accompanied by stronger representation of VTL within a region of the right somatosensory cortex. Our findings suggest a common neural basis for enhanced vocal control in speech and song. This article is part of the theme issue ‘Voice modulation: from origin and mechanism to social impact (Part I)’

Ongoing microstructural changes in the cervical cord underpin disability progression in early primary progressive multiple sclerosis

Background: Pathology in the spinal cord of patients with primary progressive multiple sclerosis (PPMS) contributes to disability progression. We previously reported abnormal Q-space imaging (QSI)-derived indices in the spinal cord at baseline in patients with early PPMS, suggesting early neurodegeneration. / Objective: The aim was to investigate whether changes in spinal cord QSI over 3 years in the same cohort are associated with disability progression and if baseline QSI metrics predict clinical outcome. / Methods: Twenty-three PPMS patients and 23 healthy controls recruited at baseline were invited for follow-up cervical cord 3T magnetic resonance imaging (MRI) and clinical assessment after 1 year and 3 years. Cord cross-sectional area (CSA) and QSI measures were obtained, together with standard brain MRI measures. Mixed-effect models assessed MRI changes over time and their association with clinical changes. Linear regression identified baseline MRI indices associated with disability at 3 years. / Results: Over time, patients deteriorated clinically and showed an increase in cord QSI indices of perpendicular diffusivity that was associated with disability worsening, independently of the decrease in CSA. Higher perpendicular diffusivity and lower CSA at baseline predicted worse disability at 3 years. Conclusion: Increasing spinal cord perpendicular diffusivity may indicate ongoing neurodegeneration, which underpins disability progression in PPMS, independently of the development of spinal cord atrophy

Utility of diffusion MRI characteristics of cervical lymph nodes as disease classifier between patients with head and neck squamous cell carcinoma and healthy volunteers

Diffusion MRI characteristics assessed by apparent diffusion coefficient (ADC) histogram analysis in head and neck squamous cell carcinoma (HNSCC) have been reported as helpful in classifying tumours based on diffusion characteristics. There is little reported on HNSCC lymph nodes classification by diffusion characteristics. The aim of this study was to determine whether pretreatment nodal microstructural diffusion MRI characteristics can classify diseased nodes of patients with HNSCC from normal nodes of healthy volunteers. Seventy-nine patients with histologically confirmed HNSCC prior to chemoradiotherapy, and eight healthy volunteers, underwent diffusion-weighted (DW) MRI at a 1.5-T MR scanner. Two radiologists contoured lymph nodes on DW (b = 300 s/m2) images. ADC, distributed diffusion coefficient (DDC) and alpha (α) values were calculated by monoexponential and stretched exponential models. Histogram analysis metrics of drawn volume were compared between patients and volunteers using a Mann–Whitney test. The classification performance of each metric between the normal and diseased nodes was determined by receiver operating characteristic (ROC) analysis. Intraclass correlation coefficients determined interobserver reproducibility of each metric based on differently drawn ROIs by two radiologists. Sixty cancerous and 40 normal nodes were analysed. ADC histogram analysis revealed significant differences between patients and volunteers (p ≤0.0001 to 0.0046), presenting ADC distributions that were more skewed (1.49 for patients, 1.03 for volunteers; p = 0.0114) and ‘peaked’ (6.82 for patients, 4.20 for volunteers; p = 0.0021) in patients. Maximum ADC values exhibited the highest area under the curve ([AUC] 0.892). Significant differences were revealed between patients and volunteers for DDC and α value histogram metrics (p ≤0.0001 to 0.0044); the highest AUC were exhibited by maximum DDC (0.772) and the 25th percentile α value (0.761). Interobserver repeatability was excellent for mean ADC (ICC = 0.88) and the 25th percentile α value (ICC = 0.78), but poor for all other metrics. These results suggest that pretreatment microstructural diffusion MRI characteristics in lymph nodes, assessed by ADC and α value histogram analysis, can identify nodal disease

Detection of covert lesions in focal epilepsy using computational analysis of multimodal magnetic resonance imaging data

Objective: To compare the location of suspect lesions detected by computational analysis of multimodal magnetic resonance imaging data with areas of seizure onset, early propagation, and interictal epileptiform discharges (IEDs) identified with stereoelectroencephalography (SEEG) in a cohort of patients with medically refractory focal epilepsy and radiologically normal magnetic resonance imaging (MRI) scans. Methods: We developed a method of lesion detection using computational analysis of multimodal MRI data in a cohort of 62 control subjects, and 42 patients with focal epilepsy and MRI-visible lesions. We then applied it to detect covert lesions in 27 focal epilepsy patients with radiologically normal MRI scans, comparing our findings with the areas of seizure onset, early propagation, and IEDs identified at SEEG. Results: Seizure-onset zones (SoZs) were identified at SEEG in 18 of the 27 patients (67%) with radiologically normal MRI scans. In 11 of these 18 cases (61%), concordant abnormalities were detected by our method. In the remaining seven cases, either early seizure propagation or IEDs were observed within the abnormalities detected, or there were additional areas of imaging abnormalities found by our method that were not sampled at SEEG. In one of the nine patients (11%) in whom SEEG was inconclusive, an abnormality, which may have been involved in seizures, was identified by our method and was not sampled at SEEG. Significance: Computational analysis of multimodal MRI data revealed covert abnormalities in the majority of patients with refractory focal epilepsy and radiologically normal MRI that co-located with SEEG defined zones of seizure onset. The method could help identify areas that should be targeted with SEEG when considering epilepsy surgery

ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Residual Fluid Intelligence Scores from Cortical Grey Matter Morphology

We predicted fluid intelligence from T1-weighted MRI data available as part of the ABCD NP Challenge 2019, using morphological similarity of grey-matter regions across the cortex. Individual structural covariance networks (SCN) were abstracted into graph-theory metrics averaged over nodes across the brain and in data-driven communities/modules. Metrics included degree, path length, clustering coefficient, centrality, rich club coefficient, and small-worldness. These features derived from the training set were used to build various regression models for predicting residual fluid intelligence scores, with performance evaluated both using cross-validation within the training set and using the held-out validation set. Our predictions on the test set were generated with a support vector regression model trained on the training set. We found minimal improvement over predicting a zero residual fluid intelligence score across the sample population, implying that structural covariance networks calculated from T1-weighted MR imaging data provide little information about residual fluid intelligence