Search results for: moderate resolution imaging spectroradiometer

Authors: Michal Spilacek, Martin Lisy, Marek Balas, Zdenek Skala

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This article is trying to determine the status of flue gas that is entering the KWH heat exchanger from combustion chamber in order to calculate the heat transfer ratio of the heat exchanger. Combination of measurement, calculation, and computer simulation was used to create a useful way to approximate the heat transfer rate. The measurements were taken by a number of sensors that are mounted on the experimental device and by a thermal imaging camera. The results of the numerical calculation are in a good correspondence with the real power output of the experimental device. Results show that the research has a good direction and can be used to propose changes in the construction of the heat exchanger, but still needs enhancements.

Keywords: heat exchanger, heat transfer rate, numerical calculation, thermal images

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Authors: N. C. van der Merwe, J. Oosthuizen, M. F. Makhetha, J. Adams, B. K. Dajee, S-R. Schneider

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Women representing high-risk breast cancer families, who tested negative for pathogenic mutations in BRCA1 and BRCA2, are four times more likely to develop breast cancer compared to women in the general population. Sequencing of genes involved in genomic stability and DNA repair led to the identification of novel contributors to familial breast cancer risk. These include BLM and PALB2. Bloom's syndrome is a rare homozygous autosomal recessive chromosomal instability disorder with a high incidence of various types of neoplasia and is associated with breast cancer when in a heterozygous state. PALB2, on the other hand, binds to BRCA2 and together, they partake actively in DNA damage repair. Archived DNA samples of 66 BRCA1/2 negative high-risk breast cancer patients were retrospectively selected based on the presence of an extensive family history of the disease ( > 3 affecteds per family). All coding regions and splice-site boundaries of both genes were screened using High-Resolution Melting Analysis. Samples exhibiting variation were bi-directionally automated Sanger sequenced. The clinical significance of each variant was assessed using various in silico and splice site prediction algorithms. Comprehensive screening identified a total of 11 BLM and 26 PALB2 variants. The variants detected ranged from global to rare and included three novel mutations. Three BLM and two PALB2 likely pathogenic mutations were identified that could account for the disease in these extensive breast cancer families in the absence of BRCA mutations (BLM c.11T > A, p.V4D; BLM c.2603C > T, p.P868L; BLM c.3961G > A, p.V1321I; PALB2 c.421C > T, p.Gln141Ter; PALB2 c.508A > T, p.Arg170Ter). Conclusion: The study confirmed the contribution of pathogenic mutations in BLM and PALB2 to the familial breast cancer burden in South Africa. It explained the presence of the disease in 7.5% of the BRCA1/2 negative families with an extensive family history of breast cancer. Segregation analysis will be performed to confirm the clinical impact of these mutations for each of these families. These results justify the inclusion of both these genes in a comprehensive breast and ovarian next generation sequencing cancer panel and should be screened simultaneously with BRCA1 and BRCA2 as it might explain a significant percentage of familial breast and ovarian cancer in South Africa.

Keywords: Bloom Syndrome, familial breast cancer, PALB2, South Africa

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Authors: Yanping Liao, Zenan Wu, Ruigang Zhao

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Frequency diverse array (FDA) beamforming is a technology developed in recent years, and its antenna pattern has a unique angle-distance-dependent characteristic. However, the beam is always required to have strong concentration, high resolution and low sidelobe level to form the point-to-point interference in the concentrated set. In order to eliminate the angle-distance coupling of the traditional FDA and to make the beam energy more concentrated, this paper adopts a multi-carrier FDA structure based on proposed power exponential frequency offset to improve the array structure and frequency offset of the traditional FDA. The simulation results show that the beam pattern of the array can form a dot-shape beam with more concentrated energy, and its resolution and sidelobe level performance are improved. However, the covariance matrix of the signal in the traditional adaptive beamforming algorithm is estimated by the finite-time snapshot data. When the number of snapshots is limited, the algorithm has an underestimation problem, which leads to the estimation error of the covariance matrix to cause beam distortion, so that the output pattern cannot form a dot-shape beam. And it also has main lobe deviation and high sidelobe level problems in the case of limited snapshot. Aiming at these problems, an adaptive beamforming technique based on exponential correction for multi-carrier FDA is proposed to improve beamforming robustness. The steps are as follows: first, the beamforming of the multi-carrier FDA is formed under linear constrained minimum variance (LCMV) criteria. Then the eigenvalue decomposition of the covariance matrix is ​​performed to obtain the diagonal matrix composed of the interference subspace, the noise subspace and the corresponding eigenvalues. Finally, the correction index is introduced to exponentially correct the small eigenvalues ​​of the noise subspace, improve the divergence of small eigenvalues ​​in the noise subspace, and improve the performance of beamforming. The theoretical analysis and simulation results show that the proposed algorithm can make the multi-carrier FDA form a dot-shape beam at limited snapshots, reduce the sidelobe level, improve the robustness of beamforming, and have better performance.

Keywords: adaptive beamforming, correction index, limited snapshot, multi-carrier frequency diverse array, robust

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Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

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Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

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Authors: T. Alghamdi, G. Alaghband

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In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution Neural Network, Edges, Face Recognition , Support Vector Machine.

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: Yun-Hsiang Lee

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Cancer is the main cause of death worldwide. With advances in medical technology, immunotherapy, which is a newly developed advanced treatment, is currently a crucial cancer treatment option. For better quality cancer care, the ability to communicate and critical thinking plays a central role in clinical oncology settings. However, few studies have explored the impact of communication skills on immunotherapy-related issues and their related factors. This study was to (i) explore the current status of communication skill ability for immunotherapy-related issues, self-efficacy for immunotherapy-related care, and critical thinking ability; and (ii) identify factors related to communication skill ability. This is a cross-sectional study. Oncology nurses were recruited from the Taiwan Oncology Nursing Society, in which nurses came from different hospitals distributed across four major geographic regions (North, Center, South, East) of Taiwan. A total of 123 oncology nurses participated in this study. A set of questionnaires were used for collecting data. Communication skill ability for immunotherapy issues, self-efficacy for immunotherapy-related care, critical thinking ability, and background information were assessed in this survey. Independent T-test and one-way ANOVA were used to examine different levels of communication skill ability based on nurses having done oncology courses (yes vs. no) and education years (< 1 year, 1-3 years, and > 3 years), respectively. Spearman correlation was conducted to understand the relationships between communication skill ability and other variables. Among the 123 oncology nurses in the current study, the majority of them were female (98.4%), and most of them were employed at a hospital in the North (46.8%) of Taiwan. Most of them possessed a university degree (78.9%) and had at least 3 years of prior work experience (71.7%). Forty-three of the oncology nurses indicated in the survey that they had not received oncology nurses-related training. Those oncology nurses reported moderate to high levels of communication skill ability for immunotherapy issues (mean=4.24, SD=0.7, range 1-5). Nurses reported moderate levels of self-efficacy for immunotherapy-related care (mean=5.20, SD=1.98, range 0-10) and also had high levels of critical thinking ability (mean=4.76, SD=0.60, range 1-6). Oncology nurses who had received oncology training courses had significantly better communication skill ability than those who had not received oncology training. Oncology nurses who had higher work experience (1-3 years, or > 3 years) had significantly higher levels of communication skill ability for immunotherapy-related issues than those with lower work experience (<1 year). When those nurses reported better communication skill ability, they also had significantly better self-efficacy (r=.42, p<.01) and better critical thinking ability (r=.47, p<.01). Taken altogether, courses designed to improve communication skill ability for immunotherapy-related issues can make a significant impact in clinical settings. Communication skill ability for oncology nurses is the major factor associated with self-efficacy and critical thinking, especially for those with lower work experience (< 1 year).

Keywords: communication skills, critical thinking, immunotherapy, oncology nurses, self-efficacy

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Authors: Adil Rasheed, Mandar Tabib

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The paper describes the ability of a high-resolution Computational Fluid Dynamics model to predict terrain-induced turbulence and wind shear close to the ground. Various sensitivity studies to choose the optimal simulation setup for modeling the flow characteristics in a complex terrain are presented. The capabilities of the model are demonstrated by applying it to the Sandnessjøen Airport, Stokka in Norway, an airport that is located in a mountainous area. The model is able to forecast turbulence in real time and trigger an alert when atmospheric conditions might result in high wind shear and turbulence.

Keywords: aviation safety, terrain-induced turbulence, atmospheric flow, alert system

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Authors: Hazem Munawer Al-Otum

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In this work, an efficient watermarking technique is proposed and can be used for detecting intentional attacks in RGB color images. The proposed technique can be implemented for image authentication and exhibits high robustness against unintentional common image processing attacks. It deploys two measures to discern between intentional and unintentional attacks based on using a quantization-based technique in a modified 2D multi-pyramidal DWT transform. Simulations have shown high accuracy in detecting intentionally attacked regions while exhibiting high robustness under moderate to severe common image processing attacks.

Keywords: image authentication, copyright protection, semi-fragile watermarking, tamper detection

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Authors: Tang, Yun-Chia, Chiu, Hung-Chang

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Authenticity in advertising, is the cornerstone of modern marketing. Despite research advances related to the role of authenticity in marketing, it remains unclear why customers respond to authentic brand stories. This study shows that different personality traits moderate the influence of various types of authenticity on people’s levels of emotion. Both indexical and iconic authenticity advertising evoke more positive emotions among extroverts and open and agreeable people. When neurotic people and conscientious people read iconic authenticity advertisements, rather than indexical authenticity ones, they produce more negative emotions. The emotion evoked by advertising in turn has a positive impact on brand attitude. These findings provide managerial implications and directions for practitioners.

Keywords: advertising, authenticity, emotion, personality traits

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Authors: Frederick Nyakudya

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In this paper, we examine the relationship between human capital, personal wealth and social capital to explain the differential start-up rates between female and male entrepreneurs. Since our dependent variable is dichotomous, we examine the determinants of these using a maximum likelihood logit estimator. We used the Global Entrepreneurship Monitor database covering the period 2006 to 2009 with 421 usable cases drawn from drawn from the Lower Layer Super Output Areas in the East Midlands in the United Kingdom. we found evidence that indicates that a female positively moderate the positive relationships between indicators of human capital, personal wealth and social capital with start-up activity. The findings have implications for programs, policies, and practices to encourage more females to engage in start-up activity.

Keywords: entrepreneurship, star-up, gender, GEM

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Authors: Aouaouche Elmaouhab, Hassina Beggar

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Solving multi-objective discrete optimization applications has always been limited by the resources of one machine: By computing power or by memory, most often both. To speed up the calculations, the grid computing represents a primary solution for the treatment of these applications through the parallelization of these resolution methods. In this work, we are interested in the study of some methods for solving multiple objective integer linear programming problem based on Branch-and-Bound and the study of grid computing technology. This study allowed us to propose an implementation of the method of Abbas and Al on the grid by reducing the execution time. To enhance our contribution, the main results are presented.

Keywords: multi-objective optimization, integer linear programming, grid computing, parallel computing

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Authors: Mehmet Bulent Ozdemir, Sultan Çagirici, Sahika Pinar Akyer, Fikri Turk

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Neuroanatomical appearance can be correlated with clinical or other characteristics of illness. With the introduction of diagnostic imaging machines, producing 3D images of anatomic structures, calculating the correlation between subjects and pattern of the structures have become possible. The aim of this study is to examine the 3D structure of hippocampus in cases with Alzheimer disease in different dementia severity. For this purpose, 62 female and 38 male- 68 patients’s (age range between 52 and 88) MR scanning were imported to the computer. 3D model of each right and left hippocampus were developed by a computer aided propramme-Surf Driver 3.5. Every reconstruction was taken by the same investigator. There were different apperance of hippocampus from normal to abnormal. In conclusion, These results might improve the understanding of the correlation between the morphological changes in hippocampus and clinical staging in Alzheimer disease.

Keywords: Alzheimer disease, hippocampus, computer-assisted anatomy, 3D

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Authors: Efren Lopez Jimenez, Maria Isabel Cajero, J. Irving-Vasqueza

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The use and processing of digital images have opened up new opportunities for the resolution of problems of various kinds, such as the calculation of different vegetation indexes, among other things, differentiating healthy vegetation from humid vegetation. However, obtaining images from which these indexes are calculated is still the exclusive subject of active research. In the present work, we propose to obtain these images using a low cost embedded system (Raspberry Pi) and its processing, using a set of libraries of open code called OpenCV, in order to obtain the Normalized Red-Green Difference Index (NGRDI).

Keywords: Raspberry Pi, vegetation index, Normalized Red-Green Difference Index (NGRDI), OpenCV

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Authors: Sofia Baldelli, Aman More

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Milk curd obstruction is commonly reported as being misdiagnosed for NEC, and they predominantly mimic each other in clinical presentation, including abdominal distension, vomiting, constipation, feeding intolerance and frank or occult blood PR. Using the case of a pre-term neonate misdiagnosed with necrotising enterocolitis when in fact, they had milk curd obstruction, we compare the two diagnoses and why they are hard to differentiate, the risk factors for clinicians to consider and the different management options. The main diagnostic tool for these conditions remains the plain radiograph and here we present the original radiograph of the neonate and discuss the classical radiological features of both diagnoses. We conclude that further imaging techniques such as ultrasound might be used to improve diagnosis when X-ray is inconclusive.

Keywords: milk curd obstruction, Necrotising Enterocolitis, radiology, pediatric surgery

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Authors: Parker Murray, Marci Johnson, Tyson S. Burnham, Alina K. Fong, Mark D. Allen, Bruce McIff

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Purpose: Pathological dysregulation of Neurovascular Coupling (NVC) caused by mild traumatic brain injury (mTBI) is the predominant source of chronic post-concussion syndrome (PCS) symptomology. fNCI has the ability to localize dysregulation in NVC by measuring blood-oxygen-level-dependent (BOLD) signaling during the performance of fMRI-adapted neuropsychological evaluations. With fNCI, 57 brain areas consistently affected by concussion were identified as PCS neural markers, which were validated on large samples of concussion patients and healthy controls. These neuromarkers provide the basis for a computation of PCS severity which is referred to as the Severity Index Score (SIS). The SIS has proven valuable in making pre-treatment decisions, monitoring treatment efficiency, and assessing long-term stability of outcomes. Methods and Materials: After being scanned while performing various cognitive tasks, 476 concussed patients received an SIS score based on the neural dysregulation of the 57 previously identified brain regions. These scans provide an objective measurement of attentional, subcortical, visual processing, language processing, and executive functioning abilities, which were used as biomarkers for post-concussive neural dysregulation. Initial SIS scores were used to develop individualized therapy incorporating cognitive, occupational, and neuromuscular modalities. These scores were also used to establish pre-treatment benchmarks and measure post-treatment improvement. Results: Changes in SIS were calculated in percent change from pre- to post-treatment. Patients showed a mean improvement of 76.5 percent (σ= 23.3), and 75.7 percent of patients showed at least 60 percent improvement. Longitudinal reassessment of 24 of the patients, measured an average of 7.6 months post-treatment, shows that SIS improvement is maintained and improved, with an average of 90.6 percent improvement from their original scan. Conclusions: fNCI provides a reliable measurement of NVC allowing for identification of concussion pathology. Additionally, fNCI derived SIS scores direct tailored therapy to restore NVC, subsequently resolving chronic PCS resulting from mTBI.

Keywords: concussion, functional magnetic resonance imaging (fMRI), neurovascular coupling (NVC), post-concussion syndrome (PCS)

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Authors: Bansal Ashwani

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Cartographic depiction and visualization of wetland changes is an important tool to map spatial-temporal information about the wetland dynamics effectively and to comprehend the response of these water bodies in maintaining the groundwater and surrounding ecosystem. This is true for the states of North Western India, i.e., J&K, Himachal, Punjab, and Haryana that are bestowed upon with several natural wetlands in the flood plains or on the courses of its rivers. Thus, the present study documents, analyses and reconstructs the lost wetlands, which existed in the flood plains of the major river basins of these states, i.e., Chenab, Jhelum, Satluj, Beas, Ravi, and Ghagar, in the beginning of the 20th century. To achieve the objective, the study has used multi-temporal datasets since the 1960s using high to medium resolution satellite datasets, e.g., Corona (1960s/70s), Landsat (1990s-2017) and Sentinel (2017). The Sentinel (2017) satellite image has been used for making the wetland inventory owing to its comparatively higher spatial resolution with multi-spectral bands. In addition, historical records, repeated photographs, historical maps, field observations including geomorphological evidence were also used. The water index techniques, i.e., band rationing, normalized difference water index (NDWI), modified NDWI (MNDWI) have been compared and used to map the wetlands. The wetland types found in the north-western states have been categorized under 19 classes suggested by Space Application Centre, India. These enable the researcher to provide with the wetlands inventory and a series of cartographic representation that includes overlaying multiple temporal wetlands extent vectors. A preliminary result shows the general state of wetland shrinkage since the 1960s with varying area shrinkage rate from one wetland to another. In addition, it is observed that majority of wetlands have not been documented so far and even do not have names. Moreover, the purpose is to emphasize their elimination in addition to establishing a baseline dataset that can be a tool for wetland planning and management. Finally, the applicability of cartographic depiction and visualization, historical map sources, repeated photographs and remote sensing data for reconstruction of long term wetlands fluctuations, especially in the northern part of India, will be addressed.

Keywords: cartographic depiction and visualization, wetland changes, NDWI/MDWI, geomorphological evidence and remote sensing

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Authors: Inderpreet Kaur, Ravinder Pal Singh, Kamal Kant Sharma

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This paper addresses the different configurations used of optical amplifiers with 16 channels in Wavelength Division Multiplexed system. The systems with 16 channels have been simulated for evaluation of various parameters; Bit Error Rate, Quality Factor, for threshold values for a range of wavelength from 1471 nm to 1611 nm. Comparison of various combination of configurations have been analyzed with EDFA and FRA but EDFA-FRA configuration performance has been found satisfactory in terms of performance indices and stable region. The paper also compared various parameters quantized with different configurations individually. It has been found that Q factor has high value with less value of BER and high resolution for EDFA-FRA configuration.

Keywords: EDFA, FRA, WDM, Q factor, BER

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Authors: Sani Shehu, Mohd Afandi Salleh

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Parliament is a law making body which provided at national, state, province and territorial level playing a parliamentary role of representing people, law making, peace, and conflict resolution, ratifying and incorporating international convention into municipal law. Parliaments are created globally to give solid legitimacy to good governance under democratic system of government, and the representatives must be elected by the people, so the ECOWAS parliament is entitled to have this legitimacy, where members must be elected by adult people among the citizens of ECOWAS member states. This paper will discuss on the roles that ECOWAS parliament plays for the achievement of regional integration and economic goals of development and cooperation in the sub-region.

Keywords: ECOWAS parliament, composition, competence, power

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Authors: Yonwaba Atyosi, Moses Cho, Abel Ramoelo, Nobuhle Majozi, Cecilia Masemola, Yoliswa Mkhize

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Spectroscopy has been widely used to understand the hyperspectral remote sensing of soils. Accurate and efficient measurement of soil moisture is essential for precision agriculture. The aim of this study was to understand the spectral behavior of soil at different soil water content levels and identify the significant spectral bands for soil moisture content retrieval at field-scale. The study consisted of 60 soil samples from a maize farm, divided into four different treatments representing different moisture levels. Spectral signatures were measured for each sample in laboratory under artificial light using an Analytical Spectral Device (ASD) spectrometer, covering a wavelength range from 350 nm to 2500 nm, with a spectral resolution of 1 nm. The results showed that the absorption features at 1450 nm, 1900 nm, and 2200 nm were particularly sensitive to soil moisture content and exhibited strong correlations with the water content levels. Continuum removal was developed in the R programming language to enhance the absorption features of soil moisture and to precisely understand its spectral behavior at different water content levels. Statistical analysis using partial least squares regression (PLSR) models were performed to quantify the correlation between the spectral bands and soil moisture content. This study provides insights into the spectral behavior of soil at different water content levels and identifies the significant spectral bands for soil moisture content retrieval. The findings highlight the potential of spectroscopy for non-destructive and rapid soil moisture measurement, which can be applied to various fields such as precision agriculture, hydrology, and environmental monitoring. However, it is important to note that the spectral behavior of soil can be influenced by various factors such as soil type, texture, and organic matter content, and caution should be taken when applying the results to other soil systems. The results of this study showed a good agreement between measured and predicted values of Soil Moisture Content with high R2 and low root mean square error (RMSE) values. Model validation using independent data was satisfactory for all the studied soil samples. The results has significant implications for developing high-resolution and precise field-scale soil moisture retrieval models. These models can be used to understand the spatial and temporal variation of soil moisture content in agricultural fields, which is essential for managing irrigation and optimizing crop yield.

Keywords: soil moisture content retrieval, precision agriculture, continuum removal, remote sensing, machine learning, spectroscopy

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Authors: Deniss Rozkov, Hendrik Idema

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This paper researches the gender-based differences among US-American institutional investors regarding their preferences for sustainable development goals (SDGs) when investing. After employing a structured questionnaire as well as applying a choice-based conjoint analysis, it is found that female investors place significantly more emphasis on SDGs, especially in the social and ecological domain, exhibiting significantly stronger “other-regarding” characteristics compared to their male counterparts. Further, the results of the survey show that females show significantly higher risk aversion than males by selecting moderately conservative and moderate risk approaches.

Keywords: sustainable development goals, investing, socially responsible investor, gender, conjoint analysis

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Authors: Donghyun Lee, Cam Nguyen

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Multi-band systems offer a great deal of benefit in modern communication and radar systems. In particular, multi-band antenna-array radar systems with their extended frequency diversity provide numerous advantages in detection, identification, locating and tracking a wide range of targets, including enhanced detection coverage, accurate target location, reduced survey time and cost, increased resolution, improved reliability and target information. An accurate calibration is a critical issue in antenna array systems. The amplitude and phase errors in multi-band and multi-polarization antenna array transceivers result in inaccurate target detection, deteriorated resolution and reduced reliability. Furthermore, the digital beam former without the RF domain phase-shifting is less immune to unfiltered interference signals, which can lead to receiver saturation in array systems. Therefore, implementing integrated front-end architecture, which can support calibration function with low insertion and filtering function from the farthest end of an array transceiver is of great interest. We report a dual K/Ka-band T/R/Calibration switch module with quasi-elliptic dual-bandpass filtering function implementing a Q-enhanced metamaterial transmission line. A unique dual-band frequency response is incorporated in the reception and calibration path of the proposed switch module utilizing the composite right/left-handed meta material transmission line coupled with a Colpitts-style negative generation circuit. The fabricated fully integrated T/R/Calibration switch module in 0.18-μm BiCMOS technology exhibits insertion loss of 4.9-12.3 dB and isolation of more than 45 dB in the reception, transmission and calibration mode of operation. In the reception and calibration mode, the dual-band frequency response centered at 24.5 and 35 GHz exhibits out-of-band rejection of more than 30 dB compared to the pass bands below 10.5 GHz and above 59.5 GHz. The rejection between the pass bands reaches more than 50 dB. In all modes of operation, the IP1-dB is between 4 and 11 dBm. Acknowledgement: This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

Keywords: microwaves, millimeter waves, T/R switch, wireless communications, wireless communications

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Authors: Nanditha Rajamani, Anirudhaa R. Rao, Divya Sriram

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One of the greatest difficulties in treating patients with pain is the highly subjective nature of pain sensation. The measurement of pain intensity is primarily dependent on the patient’s report, often with little physical evidence to provide objective corroboration. This is also complicated by the fact that there are only few and expensive existing technologies (Functional Magnetic Resonance Imaging-fMRI). The need is thus clear and urgent for a reliable, non-invasive, non-painful, objective, readily adoptable, and coefficient diagnostic platform that provides additional diagnostic information to supplement its current regime with more information to assist doctors in diagnosing these patients. Thus, our idea of developing a pain detector was conceived to take a step further the detection and diagnosis of chronic and acute pain.

Keywords: pain sensor, microwave radiometery, pain sensation, fMRI

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Authors: Achraf Al Faraj, Asma Sultana Shaik, Baraa Al Sayed

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Specific and effective targeting of drug delivery systems (DDS) to cancerous sites remains a major challenge for a better diagnostic and therapy. Recently, SWCNTs with their unique physicochemical properties and the ability to cross the cell membrane show promising in the biomedical field. The purpose of this study was first to develop a biocompatible iron oxide tagged SWCNTs as diagnostic nanoprobes to allow their noninvasive detection using MRI and their preferential targeting in a breast cancer murine model by placing an optimized flexible magnet over the tumor site. Magnetic targeting was associated to specific antibody-conjugated SWCNTs active targeting. The therapeutic efficacy of doxorubicin-conjugated SWCNTs was assessed, and the superiority of diffusion-weighted (DW-) MRI as sensitive imaging biomarker was investigated. Short Polyvinylpyrrolidone (PVP) stabilized water soluble SWCNTs were first developed, tagged with iron oxide nanoparticles and conjugated with Endoglin/CD105 monoclonal antibodies. They were then conjugated with doxorubicin drugs. SWCNTs conjugates were extensively characterized using TEM, UV-Vis spectrophotometer, dynamic light scattering (DLS) zeta potential analysis and electron spin resonance (ESR) spectroscopy. Their MR relaxivities (i.e. r1 and r2*) were measured at 4.7T and their iron content and metal impurities quantified using ICP-MS. SWCNTs biocompatibility and drug efficacy were then evaluated both in vitro and in vivo using a set of immunological assays. Luciferase enhanced bioluminescence 4T1 mouse mammary tumor cells (4T1-Luc2) were injected into the right inguinal mammary fat pad of Balb/c mice. Tumor bearing mice received either free doxorubicin (DOX) drug or SWCNTs with or without either DOX or iron oxide nanoparticles. A multi-pole 10x10mm high-energy flexible magnet was maintained over the tumor site during 2 hours post-injections and their properties and polarity were optimized to allow enhanced magnetic targeting of SWCNTs toward the primary tumor site. Tumor volume was quantified during the follow-up investigation study using a fast spin echo MRI sequence. In order to detect the homing of SWCNTs to the main tumor site, susceptibility-weighted multi-gradient echo (MGE) sequence was used to generate T2* maps. Apparent diffusion coefficient (ADC) measurements were also performed as a sensitive imaging biomarker providing early and better assessment of disease treatment. At several times post-SWCNT injection, histological analysis were performed on tumor extracts and iron-loaded SWCNT were quantified using ICP-MS in tumor sites, liver, spleen, kidneys, and lung. The optimized multi-poles magnet revealed an enhanced targeting of magnetic SWCNTs to the primary tumor site, which was found to be much higher than the active targeting achieved using antibody-conjugated SWCNTs. Iron-loading allowed their sensitive noninvasive tracking after intravenous administration using MRI. The active targeting of doxorubicin through magnetic antibody-conjugated SWCNTs nanoprobes was found to considerably decrease the primary tumor site and may have inhibited the development of metastasis in the tumor-bearing mice lung. ADC measurements in DW-MRI were found to significantly increase in a time-dependent manner after the injection of DOX-conjugated SWCNTs complexes.

Keywords: single-walled carbon nanotubes, nanomedicine, magnetic resonance imaging, cancer diagnosis and therapy

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Authors: Najwa Alsayed Omar

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With the increasing popularity of the Internet, online reading has become an essential source for EFL readers. Using strategies to comprehend information on online reading texts play a crucial role in students’ academic success. Metacognitive reading strategies are effective factors that enhance EFL learners reading comprehension. This study aimed at exploring the use of online metacognitive reading strategies by postgraduate Libyan EFL students. Quantitative data was collected using the Survey of Online Reading Strategies (OSORS). The findings revealed that the participants were moderate users of metacognitive online reading strategies. Problem solving strategies were the most frequently reported used strategies, while support reading strategies were the least. The five most and least frequently reported strategies were identified. Based on the findings, some future research recommendations were presented.

Keywords: metacognitive strategies, online reading, online reading strategies, postgraduate students

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Authors: X. Wang

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Timely and accurate information on urban building damage caused by earthquake is important basis for disaster assessment and emergency relief. Very high resolution (VHR) remotely sensed imagery containing abundant fine-scale information offers a large quantity of data for detecting and assessing urban building damage in the aftermath of earthquake disasters. However, the accuracy obtained using spectral features alone is comparatively low, since building damage, intact buildings and pavements are spectrally similar. Therefore, it is of great significance to detect urban building damage effectively using multi-source data. Considering that in general height or geometric structure of buildings change dramatically in the devastated areas, a novel multi-stage urban building damage detection method, using bi-temporal spectral, height and corner information, was proposed in this study. The pre-event height information was generated using stereo VHR images acquired from two different satellites, while the post-event height information was produced from airborne LiDAR data. The corner information was extracted from pre- and post-event panchromatic images. The proposed method can be summarized as follows. To reduce the classification errors caused by spectral similarity and errors in extracting height information, ground surface, shadows, and vegetation were first extracted using the post-event VHR image and height data and were masked out. Two different types of building damage were then extracted from the remaining areas: the height difference between pre- and post-event was used for detecting building damage showing significant height change; the difference in the density of corners between pre- and post-event was used for extracting building damage showing drastic change in geometric structure. The initial building damage result was generated by combining above two building damage results. Finally, a post-processing procedure was adopted to refine the obtained initial result. The proposed method was quantitatively evaluated and compared to two existing methods in Port au Prince, Haiti, which was heavily hit by an earthquake in January 2010, using pre-event GeoEye-1 image, pre-event WorldView-2 image, post-event QuickBird image and post-event LiDAR data. The results showed that the method proposed in this study significantly outperformed the two comparative methods in terms of urban building damage extraction accuracy. The proposed method provides a fast and reliable method to detect urban building collapse, which is also applicable to relevant applications.

Keywords: building damage, corner, earthquake, height, very high resolution (VHR)

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Authors: Bayoumy Mohamed, Khaled Alam El-Din

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In the present study, 24 years of gridded sea level anomalies (SLA) from satellite altimetry and sea surface temperature (SST) from advanced very-high-resolution radiometer (AVHRR) daily data (1993-2016) are used. These data have been used to investigate the sea level rising and warming rates of SST, and their spatial distribution in the Mediterranean Sea. The results revealed that there is a significant sea level rise in the Mediterranean Sea of 2.86 ± 0.45 mm/year together with a significant warming of 0.037 ± 0.007 °C/year. The high spatial correlation between sea level and SST variations suggests that at least part of the sea level change reported during the period of study was due to heating of surface layers. This indicated that the steric effect had a significant influence on sea level change in the Mediterranean Sea.

Keywords: altimetry, AVHRR, Mediterranean Sea, sea level and SST changes, trend analysis

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Authors: Ibrahim M Hassan, Lorna Que, Michael Rutland

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Type I SOD is usually diagnosed by anatomical imaging such as ultrasound, CT and MRCP. However, the types II and III SOD yield negative results despite the presence of significant symptoms. In particular, the type III is difficult to diagnose due to the absence of significant biochemical or anatomical abnormalities. Nuclear Medicine can aid in this diagnostic dilemma by demonstrating functional changes in the bile flow. Low dose Morphine (0.04mg/Kg) stimulates the tone of the sphincter of Oddi (SO) and its usefulness has been shown in diagnosing SOD by causing a delay in bile flow when compared to a non morphine provoked - baseline scan. This work expands on that process by using sublingual GTN at 60 minutes post tracer and morphine injection to relax the SO and induce an improvement in bile outflow, and in some cases show immediate relief of morphine induced abdominal pain. The criteria for positive SOD are as follows: if during the first hour of the morphine provocation showed (1) delayed intrahepatic biliary ducts tracer accumulation; plus (2) delayed appearance but persistent retention of activity in the common bile duct, and (3) delayed bile flow into the duodenum. In addition, patients who required GTN within the first hour to relieve abdominal pain were regarded as highly supportive of the diagnosis. Retrospective analysis of 85 patients (pts) (78F and 6M) referred for suspected SOD (type III) who had been intensively investigated because of recurrent right upper quadrant or abdominal pain post cholecystectomy. 99mTc-HIDA scan with morphine-provocation is performed followed by GTN at 60 minutes post tracer injection and a further thirty minutes of dynamic imaging are acquired. 30 pts were negative. 55 pts were regarded as positive for SOD and 38/55 (60%) of these patients with an abnormal result were further evaluated with a baseline 99mTc-HIDA. As expected, all 38 pts showed better bile flow characteristics than during the morphine provocation. 20/55 (36%) patients were treated by ERCP sphincterotomy and the rest were managed conservatively by medical therapy. In all cases regarded as positive for SOD, the sublingual GTN at 60 minutes showed immediate improvement in bile flow. 11/55(20%) who developed severe post-morphine abdominal pain were relieved by GTN almost instantaneously. We propose that GTN is a useful agent in the diagnosis of SOD when performing 99mTc-HIDA scan and that the satisfactory response to the sublingual GTN could offer additional information in patients who have severe pain at the time the procedure or when presenting to the emergency unit because of biliary pain. And also in determining whether a trial of medical therapy may be used before considering surgery.

Keywords: GTN, HIDA, MORPHINE, SOD

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Authors: Leslie M. Gutman

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Conduct problems (CP) represent a major dilemma, with wide-ranging and long-lasting individual and societal impacts. Children experience heterogeneous patterns of conduct problems; based on the age of onset, developmental course and related risk factors from around age 3. Early childhood represents a potential window for intervention efforts aimed at changing the trajectory of early starting conduct problems. Using the UK Millennium Cohort Study (n = 17,206 children), this study (a) identifies trajectories of conduct problems from ages 3 to 14 years and (b) assesses the cumulative and interactive effects of individual, family and socioeconomic risk factors from ages 9 months to 14 years. The same factors according to three domains were assessed, including child (i.e., low verbal ability, hyperactivity/inattention, peer problems, emotional problems), family (i.e., single families, parental poor physical and mental health, large family size) and socioeconomic (i.e., low family income, low parental education, unemployment, social housing). A cumulative risk score for the child, family, and socioeconomic domains at each age was calculated. It was then examined how the cumulative risk scores explain variation in the trajectories of conduct problems. Lastly, interactive effects among the different domains of cumulative risk were tested. Using group-based trajectory modeling, four distinct trajectories were found including a ‘low’ problem group and three groups showing childhood-onset conduct problems: ‘school-age onset’; ‘early-onset, desisting’; and ‘early-onset, persisting’. The ‘low’ group (57% of the sample) showed a low probability of conducts problems, close to zero, from 3 to 14 years. The ‘early-onset, desisting’ group (23% of the sample) demonstrated a moderate probability of CP in early childhood, with a decline from 3 to 5 years and a low probability thereafter. The ‘early-onset, persistent’ group (8%) followed a high probability of conduct problems, which declined from 11 years but was close to 70% at 14 years. In the ‘school-age onset’ group, 12% of the sample showed a moderate probability of conduct problems from 3 and 5 years, with a sharp increase by 7 years, increasing to 50% at 14 years. In terms of individual risk, all factors increased the likelihood of being in the childhood-onset groups compared to the ‘low’ group. For cumulative risk, the socioeconomic domain at 9 months and 3 years, the family domain at all ages except 14 years and child domain at all ages were found to differentiate childhood-onset groups from the ‘low’ group. Cumulative risk at 9 months and 3 years did not differentiate between the ‘school-onset’ group and ‘low’ group. Significant interactions were found between the domains for the ‘early-onset, desisting group’ suggesting that low levels of risk in one domain may buffer the effects of high risk in another domain. The implications of these findings for preventive interventions will be highlighted.

Keywords: conduct problems, cumulative risk, developmental trajectories, early childhood, adolescence

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Authors: Ibrahim Abouelkhir

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Background: Prior to this project, the number of CT aorta requests from our Emergency Department (ED) was reported by the radiology department to be high with a low positive event rate: only 1- 2% of CT aortas performed were positive for acute aortic syndrome. This trend raised concerns about the time required to process and report these scans, potentially impacting the timely reporting of other high-priority imaging, such as trauma-related scans. Other harms identified were unnecessary radiation, patients spending longer in ED contributing to overcrowding, and, most importantly, the patient not getting the right care the first time. The radiology department also raised the problem of reporting bias because they expected our CT aortas to be normal. Aim: The main aim of this project was to reduce the number of unnecessary CT aortas requested, which would be shown by 1. Number of CT aortas requested and 2. Positive event rate. Methodology: This was a quality improvement project carried out in the ED at Frimley Park Hospital, UK. Starting from 1 st January 2024, we recorded the number of days required to reach 35 CT aorta requests. We looked at all patients presenting to the ED over the age of 16 for whom a CT aorta was requested by the ED team. We looked at how many of these scans were positive for acute aortic syndrome. The intervention was a change in practice: all CT aortas should be approved by an ED consultant or ST4+ registrar (5th April 2024). We then reviewed the number of days it took to reach a total of 35 CT aorta requests following the intervention and again reviewed how many were positive. Results: Prior to the intervention, 35 CT Aorta scans were performed over a 20-day period. Following the implementation of the ED senior doctor vetting process, the same number of CT Aorta scan requests was observed over 50 days - more than twice the pre-intervention period. This indicates a significant reduction in the rate of CT Aorta scans being requested. During the pre-intervention phase, there were two positive cases of acute aortic syndrome. In the post-intervention period, there were zero. Conclusion: The mandatory review of CT Aorta scan requested by the ED consultant effectively reduced the number of scans requested. However, this intervention did not lead to an increase in positive scan results. We noted that post-intervention, approximately 50% of scans had been approved by registrar-grade doctors and, only 50% had been approved by ED consultants, and the majority were not in-person reviews. We wonder if restricting the approval to consultant grade only might improve the results, and furthermore, in person reviews should be the gold standard.

Keywords: quality improvement project, CT aorta scans, emergency department, radiology department, aortic dissection, scan request vetting, clinical outcomes, imaging efficiency

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