Search results for: cortical reconstruction

Authors: J. Chamorro-Servent, S. Tassani, M. A. Gonzalez-Ballester, L. J. Roca, J. Romeu, O. Camara

Abstract:

Electromagnetic and microwave imaging (MWI) have been used in medical imaging in the last years, being the most common applications of breast cancer and stroke detection or monitoring. In those applications, the subject or zone to observe is surrounded by a number of antennas, and the Nyquist criterium can be satisfied. Additionally, the space between the antennas (transmitting and receiving the electromagnetic fields) and the zone to study can be prepared in a homogeneous scenario. However, this may differ in other cases as could be intracardiac catheters, stomach monitoring devices, pelvic organ systems, liver ablation monitoring devices, or uterine fibroids’ ablation systems. In this work, we analyzed different MWI algorithms to find the most suitable method for dealing with an intrabody scenario. Due to the space limitations usually confronted on those applications, the device would have a cylindrical configuration of a maximum of eight transmitters and eight receiver antennas. This together with the positioning of the supposed device inside a body tract impose additional constraints in order to choose a reconstruction method; for instance, it inhabitants the use of well-known algorithms such as filtered backpropagation for diffraction tomography (due to the unusual configuration with probes enclosed by the imaging region). Finally, the difficulty of simulating a realistic non-homogeneous background inside the body (due to the incomplete knowledge of the dielectric properties of other tissues between the antennas’ position and the zone to observe), also prevents the use of Born and Rytov algorithms due to their limitations with a heterogeneous background. Instead, we decided to use a time-reversed algorithm (mostly used in geophysics) due to its characteristics of ignoring heterogeneities in the background medium, and of focusing its generated field onto the scatters. Therefore, a 2D time-reversed finite difference time domain was developed based on the time-reversed approach for microwave breast cancer detection. Simultaneously an in-silico testbed was also developed to compare ground-truth dielectric properties with corresponding microwave imaging reconstruction. Forward and inverse problems were computed varying: the frequency used related to a small zone to observe (7, 7.5 and 8 GHz); a small polyp diameter (5, 7 and 10 mm); two polyp positions with respect to the closest antenna (aligned or disaligned); and the (transmitters-to-receivers) antenna combination used for the reconstruction (1-1, 8-1, 8-8 or 8-3). Results indicate that when using the existent time-reversed method for breast cancer here for the different combinations of transmitters and receivers, we found false positives due to the high degrees of freedom and unusual configuration (and the possible violation of Nyquist criterium). Those false positives founded in 8-1 and 8-8 combinations, highly reduced with the 1-1 and 8-3 combination, being the 8-3 configuration de most suitable (three neighboring receivers at each time). The 8-3 configuration creates a region-of-interest reduced problem, decreasing the ill-posedness of the inverse problem. To conclude, the proposed algorithm solves the main limitations of the described intrabody application, successfully detecting the angular position of targets inside the body tract.

Keywords: FDTD, time-reversed, medical imaging, microwave imaging

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Authors: Hernandez Pardo Diego F., Guiza Arguello Viviana R., Coy Echeverria Ana, Viejo Abrante Fernando

Abstract:

The biological hydroxyapatite obtained from bovine bone arouses great interest in its application as a material for bone regeneration due to its better bioactive behavior in comparison with synthetic hydroxyapatite. For this reason, the objective of the present investigation was to determine the effect of chemical and thermal treatments in obtaining biological bovine hydroxyapatite of high purity and crystallinity. Two different chemical reagents were evaluated (NaOH and HCl) with the aim to remove the organic matrix of the bovine cortical bone. On the other hand, for analyzing the effect of thermal treatment temperature was ranged between 500 and 1000°C for a holding time of 4 hours. To accomplish the above, the materials before and after the chemical and thermal treatments were characterized by elemental compositional analysis (CHN), infrared spectroscopy by Fourier transform (FTIR), RAMAN spectroscopy, scanning electron microscopy (SEM), thermogravimetric analysis (TGA) and X-ray diffraction (XRD) and energy dispersion X-ray spectroscopy (EDS). The results allowed to establish that NaOH is more effective in the removal of the organic matrix of the bone when compared to HCl, whereas a thermal treatment at 700ºC for 4 hours was enough to obtain biological hydroxyapatite of high purity and crystallinity.

Keywords: bovine bone, hydroxyapatite, biomaterials, thermal treatment

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Authors: Anastasia Poliakova

Abstract:

Harmful algal bloom (HAB) is a known negative phenomenon that is caused both by natural factors and anthropogenic influence. HABs can result in a series of deleterious effects, such as beach fouling, paralytic shellfish poisoning, mass mortality of marine species, and a threat to human health, especially if toxins pollute drinking water or occur nearby public resorts. In South China, the problem of HABs has an ultimately important meaning. For this study, we used a 1.5 m sediment core LAX-2018-2 collected in 2018 from the Zhanjiang Mangrove National Nature Reserve (109°03´E, 20°30´N), Guangdong Province, South China. High-resolution coastal environment reconstruction with a specific focus on the HABs history during the last ca 2500 yrs was attempted. Age control was performed with five radiocarbon dates obtained from benthic foraminifera. A total number of 71 dinoflagellate cyst types was recorded. The most common types found consistently throughout the sediment sequence were autotrophic Spiniferites spp., Spiniferites hyperacanthus and S. mirabilis, S. ramosus, Operculodinium centrocarpum sensu Wall and Dale 1966, Polysphaeridium zoharyi, and heterotrophic Brigantedinium ssp., cyst of Gymnodinium catenatum and cysts mixture of Protoperidinium. Three local dinoflagellate zones LAX-1 to LAX-3 were established based on the results of the constrained cluster analysis and data ordination; additionally, the middle zone LAX-2 was derived into two subzones, LAX-2a and LAX-2b based on the dynamics of toxic and heterotrophic cysts as well as on the significant changes (probability, P=0.89) in percentages of eutrophic indicators. The total cyst count varied from 106 to 410 dinocysts per slide, with 177 cyst types on average. Dinocyst assemblages are characterized by high values of the dost-depositional degradation index (kt) that varies between 3.6 and 7.6 (averaging 5.4), which is relatively high and is very typical for the areas with selective dinoflagellate cyst preservation that is related to bottom-water oxygen concentrations.

Keywords: reconstruction of palaeoenvironment, harmful algal blooms, anthropogenic influence on coastal zones, South China Sea

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Authors: Zeynep Tanriverdi̇

Abstract:

Sustainable architecture is a design approach that provides healthy, comfortable, safe, clean space production as well as utilizes minimum resources for efficient and economical use of natural resources and energy. Traditional houses located in rural areas are sustainable structures built at the design and implementation stage in accordance with the climatic environmental data of the region and also effectively using natural energy resources. The fact that these structures are located in an earthquake geography like Türkiye brings their earthquake resistance to the agenda. Since the construction of these structures, which contain the architectural and technological cultural knowledge of the past, is shaped according to the characteristics of the regions where they are located, their resistance to earthquakes also differs. Analyses in rural areas after the earthquake show that there are light-damaged structures that can survive, severely damaged structures, and completely destroyed structures. In this regard, experts can implement repair, consolidation, and reconstruction applications, respectively. While simple repair interventions are carried out in accordance with the original data in traditional houses that have shown great resistance to earthquakes, reinforcement work blended with new technologies can be applied in damaged structures. In reconstruction work, a wide variety of applications can be seen with the possibilities of modern technologies. In rural areas experiencing earthquakes around the world, there are experimental new housing applications that are renewable, environmentally friendly, and sustainable with modern construction techniques in the light of scientific data. With these new residences, it is aimed to create earthquake-resistant, economical, healthy, and pain-relieving therapy spaces for people whose daily lives have been interrupted by disasters. In this study, the preservation of high earthquake-prone rural areas will be discussed through the knowledge transfer of traditional architecture and also permanent housing practices using new sustainable technologies to improve the area. In this way, it will be possible to keep losses to a minimum with sustainable, reliable applications prepared for the worst aspects of the disaster situation and to establish a link between the knowledge of the past and the new technologies of the future.

Keywords: sustainability, conservation, traditional construction systems and materials, new technologies, earthquake resistance

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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Authors: Hamidreza Jahani, Zahra Salehzadeh, Ehsan Amini, Mohsen Tohidifar

Abstract:

Calvarial Hyperostosis Syndrome (CHS) is a benign bone disease of the skull. It is a non-neoplastic and proliferative bone disease, and the main feature of the disease is progressive and asymmetrical bone involvement. CHS is mostly reported in young male and female bullmastiff dogs and less frequently in other breeds. The etiology of CHS is unknown. This is the first case report of CHS in Iran. A 3-month-old male Persian Mastiff was presented with chief complaints of multiple episodes of seizure, pacing, bizarre behavior, delayed growth, head pressing, and difficulty in opening the mouth. Central blindness and open fontanelles were observed in clinical examination. No abnormality was found in the complete blood count and routine blood biochemical tests. CT scan findings include cortical thickening of frontal and parietal bones and enlargement of the left retropharyngeal lymph node. For treatment, oral clindamycin for two weeks, prednisolone and phenobarbital for one month, respectively, were administrated, and the case showed improvement after a week and recovered after one month.

Keywords: calvarial hyperostosis, Persian Mastiff, frontal bone, seizure

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Authors: Minghao Liu

Abstract:

This paper uses the theory of communication in the context of mass communication, from the construction of communication symbols, communication flow organization, communication experience perception of the three levels of the old industrial factory landscape transformation research and analysis, summarizes the old industrial factory landscape in the communication process to create strategies and design methods for the old industrial factories carried by the urban culture of how to enter the public's life more widely in the existing environment and be familiar with the significance of the exploration, to provide a new idea for the renewal of the urban stock, and ultimately to achieve the sustainable development of the city.

Keywords: communication, old industrial factor, urban renewal, landscape design

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Authors: Alireza Rahpeyma

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One of the most significant challenges faced by cities is inefficient and deteriorated urban fabric. Deteriorated areas bring about numerous issues, including economic, social, physical, and infrastructural problems, sewage management, environmental concerns, and security issues. One of the crucial necessities of modern urban life is the revitalization and renovation of these urban fabrics. Another important aspect is preserving a cohesive cultural and social identity during the urban renewal process. Urban renovation and upgrading are not a one-time occurrence but rather an ongoing process that ultimately needs to become ingrained in the system. This process is not swift; it involves sensitive and intricate stages that require well-designed plans within short, medium, and long-term timeframes. To revitalize dilapidated areas, a comprehensive understanding of the urban region's sustainability is essential. The goal of this study is to provide a suitable model for the upgrading and renewal of areas 2, 4, 5, 7, 8, and 10 in Tehran, preserving the heritage within these urban fabrics (urban assets), including the valuable morphologies of these areas, to prevent financial wastage. This study was conducted descriptively and analytically using the SWOT technique and GIS software. The research results regarding urban upgrading and renewal bring about the following points: 1) Urban upgrading and renewal ensure satisfactory efficiency, justice, environmental quality, safety and security, hygiene, sewage management, and the comfort and aesthetics of urban spaces. 2) Employing the above processes in old city centers re-establishes the historical and cultural connection between people and their past, a past that is evolving and improving and will not repeat itself. 3) Despite the expansion and growth of Iranian cities, cultural and national identity can be preserved by adhering to healthy urban revitalization principles. 4) Proper urban upgrading and renewal prevent social fragmentation, deviant behavioral patterns, psychological and occupational disorders, and financial losses. In general, preserving the identity and urban life in renovation and upgrading must be comprehensive, encompassing various dimensions, including physical, social, economic, political, and administrative aspects.

Keywords: dilapidated areas, renovation, sustainable reconstruction, Tehran-Iran

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Authors: Seyedeh Zeinab Peighambarzadeh, Mehdi Tavana

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Cataract is the most common cause of blindness worldwide and its incidence will increase as the World’s population ages. Even in modern ophthalmology, there is no effective medical treatment for cataract except surgery. Development of a drug which could prevent or delay the onset of cataract will lessen this burden and reduce the number of blind patients waiting for cataract surgery. This study was undertaken to evaluate the protective effect of vitamin E on Selenite-induced Cataract in Sprague-dawely rats. Cataracts were induced in rats by administration of sodium selenite. On postpartum day ten, in group I, saline was injected subcutaneously. Group II rat pups received subcutaneous injection of vitamin E (60mg/kg B.W.) at day 8 postpartum and every other day thereafter. Group III and IV rat pups received a subcutaneous injection of sodium selenite (13mg/kg B.W.) at day 10 postpartum. Group IV also received subcutaneous injection of vitamin E (60mg/kg B.W.) at day 8 postpartum and every other day thereafter. The development of cataract in rats was assessed clinically by slit-lamp biomicroscope from day 14 up to postpartum day 28. After sacrifice, extricated pup lenses were analyzed for total and soluble protein concentrations and eletrophoretic pattern (SDS-PAGE). There was no opacification of lens in Group I and II. There was mature cataract in 95% of Group III. In group IV, 55% of rats developed sub capsular or cortical cataract. Cataractous and biochemical changes of the crystalline lens proteins due to selenite can be retard or prevented by vitamin E.

Keywords: preventive effect, selenite-induced cataract, vitamin E, rat

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Authors: Noman Shahzad, Amyn Pardhan, Hasnain Zafar

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Introduction: Though short term survival advantage of damage control laparotomy in management of critically ill trauma patients is established, there is little known about the long-term quality of life of these patients. Facial closure rate after damage control laparotomy is reported to be 20-70 percent. Abdominal wall reconstruction in those who failed to achieve facial closure is challenging and can potentially affect quality of life of these patients. Methodology: We conducted retrospective matched cohort study. Adult patients who underwent damage control laparotomy from Jan 2007 till Jun 2013 were identified through medical record. Patients who had concomitant disabling brain injury or limb injuries requiring amputation were excluded. Age, gender and presentation time matched non exposure group of patients who underwent laparotomy for trauma but no damage control were identified for each damage control laparotomy patient. Quality of life assessment was done via telephonic interview at least one year after the operation, using Urdu version of EuroQol Group Quality of Life (QOL) questionnaire EQ5D after permission. Wilcoxon signed rank test was used to compare QOL scores and McNemar test was used to compare individual parameters of QOL questionnaire. Study was approved by institutional ethical review committee. Results: Out of 32 patients who underwent damage control laparotomy during study period, 20 fulfilled the selection criteria for which 20 matched controls were selected. Median age of patients (IQ Range) was 33 (26-40) years. Facial closure rate in damage control laparotomy group was 40% (8/20). One third of those who did not achieve facial closure (4/12) underwent abdominal wall reconstruction. Self-reported QOL score of damage control laparotomy patients was significantly worse than non-damage control group (p = 0.032). There was no statistically significant difference in two groups regarding individual QOL measures. Significantly, more patients in damage control group were requiring use of abdominal binder, and more patients in damage control group had to either change their job or had limitations in continuing previous job. Our study was not adequately powered to detect factors responsible for worse QOL in damage control group. Conclusion: Quality of life of damage control patients is worse than their age and gender matched patients who underwent trauma laparotomy but not damage control. Adequately powered studies need to be conducted to explore factors responsible for this finding for potential improvement.

Keywords: damage control laparotomy, laparostomy, quality of life

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Authors: Caroline Kim

Abstract:

The designation autism spectrum disorder (ASD) groups complex disorders in the development of the brain. Autism is defined essentially as a condition in which an individual lacks a theory of mind. The theory of mind, in this sense, explains the ability of an individual to attribute feelings, emotions, or thoughts to another person. An autistic patient is characteristically unable to determine what an interlocutor is feeling, or to understand the beliefs of others. However, it is possible that autism cannot plausibly characterized as the lack of theory of mind in an individual. Genes, the bran, and its interplay with environmental factors may also cause autism. A mutation in a gene may be hereditary, or instigated by diseases such as mumps. Though an autistic patient may experience abnormalities in the cerebellum and the cortical regions, these are in fact only possible theories as to a biochemical explanation behind the disability. The prevailing theory identifying autism with lacking the theory of mind is supported by behavioral observation, but this form of observation is itself determined by socially constructed standards, limiting the possibility for empirical verification. The theory of mind infers that the beliefs and emotions of people are causally based on their behavior. This paper demonstrates the fallacy of this inference, critiquing its basis in socially constructed values, and arguing instead for a biochemical approach free from the conceptual apparatus of language and social expectation.

Keywords: autism spectrum disorder, sociology of psychology, social construction, the theory of mind

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Authors: Faizan Sultan

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Non-government organizations (NGOs) in Pakistan have the potential to deliver services such as health, education, and rural development through targeting the most vulnerable communities of society. Having this significant importance, NGOs are facing numerous challenges in service delivery. So, there is a need to identify the challenges NGOs face in community development, particularly post-conflict development. The current study has analyzed the social and political constraints in development projects in the post-conflict region of the Swat district of Khyber Pakhtunkhwa. The objectives of this study are “What are the social and political constraints faced by the nongovernmental organizations in the implementation of development aid Projects in post-conflict development of Swat and to examine the challenges in coordination mechanism between government departments, NGOs, and community in reconstruction activities”. This research is based upon both the quantitative and qualitative data that is being gathered from the NGO representatives, government officials, and community members who were involved in post-conflict development interventions in the Swat region. A purposive sampling technique was used to select respondents from the community members/activists (25 in number) and government and NGO officials (10 in number). Based on analysis against our objectives, NGOs have faced numerous constraints such as Insecurity, Negative Perceptions about NGOs, restrictions on women's mobility, government policies and regulations, lack of coordination and networking, trust deficit, and political interference while implementing their project interventions. These findings concluded that constraints have affected project implementation to a greater extent, including women's participation, involvement of marginalized populations, and equal distribution of resources. In the Swat region, NGOs cannot openly discuss sensitive projects such as human rights, gender-based projects, or women empowerment as these issues are very sensitive to the local community due to their cultural values. The community may not allow their females to go outside their homes as this region is a male-dominated society. Similarly, lack of communication and poor networking for the arrangements of the project meetings were also the major constraints.

Keywords: national disaster management authority, millennium development goals, provincial disaster management authority, provincial reconstruction, rehabilitation and settlement authority

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Authors: Theresa Chinyere ONU

Abstract:

This paper examines the effect of social terrorism on education in Nigeria. The article looked into some prevailing conditions of international political unrest and insecurity. The fear and risk of these conditions to national security and the struggle for power establishment which has further intensified and taken the shape of terrorism has imposed devastating effects on the growth and prosperity of Nigeria; as traffic patterns get disturbed, hospitals and schools get dysfunctional. This has also affected the educational standard in Nigeria as parents are no longer comfortable in sending their children to schools in some states for the fear of terrorist attacks. The study emphasized the integrated the effort of the government management institutions.

Keywords: education, social terrorism, women, Nigeria

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Authors: Snehal G. Teli, R. J. Shelke

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CNN and MultiUNet models are the framework for the proposed method for enhancing and reconstructing underwater images. Multiscale merging of features and regeneration are both performed by the MultiUNet. CNN collects relevant features. Extensive tests on benchmark datasets show that the proposed strategy performs better than the latest methods. As a result of this work, underwater images can be represented and interpreted in a number of underwater applications with greater clarity. This strategy will advance underwater exploration and marine research by enhancing real-time underwater image processing systems, underwater robotic vision, and underwater surveillance.

Keywords: convolutional neural network, image enhancement, machine learning, multiunet, underwater images

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Authors: Essam Al Daoud

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This study solves a phylogeny problem by using modified wild dog pack optimization. The least squares error is considered as a cost function that needs to be minimized. Therefore, in each iteration, new distance matrices based on the constructed trees are calculated and used to select the alpha dog. To test the suggested algorithm, ten homologous genes are selected and collected from National Center for Biotechnology Information (NCBI) databanks (i.e., 16S, 18S, 28S, Cox 1, ITS1, ITS2, ETS, ATPB, Hsp90, and STN). The data are divided into three categories: 50 taxa, 100 taxa and 500 taxa. The empirical results show that the proposed algorithm is more reliable and accurate than other implemented methods.

Keywords: least square, neighbor joining, phylogenetic tree, wild dog pack

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Authors: Ehsan Kaviani, Azin Golmoradizade

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Introduction: Traditionally, tendons are considered to only contain tenocytes that are responsible for the maintenance, repair, and remodeling of tendons. Stem cells, which are termed tendon-derived stem cells, so this study we investigate the effect of transcranial direct current stimulation combined with swallowing training on post-stroke dysphagia. Methods: This review article is about effects of transcranial direct current stimulation (tDCS) on post-stroke dysphagia that were extracted from Science Direct, Pro quest, and Pub med Data Bases. 15 articles had been selected according to inclusion criteria from 2014 to 2019, and 6 of them had been deleted by exclusion criteria. Results: The results of our systematic review suggest that tDCS may represent a promising novel treatment for post-stroke dysphagia. However, to date, little is known about the optimal parameters of tDCS for relieving post-stroke dysphagia. Further studies are warranted to refine this promising intervention by exploring the optimal parameters of tDCS. Conclusion: anodal tDCS over the affected hemisphere may be as effective as cathodal tDCS on the unaffected hemisphere to enhance recovery after subacute ischemic stroke and anodal tdcs applied over the affected pharyngeal motor cortex can enhance the outcome of swallowing training in post-stroke dysphagia.

Keywords: dysphagia, stroke, cortical stimulation, transcranial direct current stimulation

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Authors: Omar Sorour, Michael Leahy, Thomas Irvine, Vladimir Koren

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Introduction: Covid encephalitis is a rare yet dangerous complication, particularly affecting the older and immunocompromised. Symptoms range from confusion to delirium, coma, and seizures. Although neurological manifestations have become more well-characterized in COVID patients, little is known about whether priorneurological abnormalities may predispose patients to COVID encephalopathy. Case Description: A 73 y.o. male with a CT and MRI-confirmed stable, prior 9 mm cavernoma in the right frontal lobe and no past history of seizures was hospitalized with generalized weakness, abdominal pain, nausea, and shortness of breath with subsequent COVID pneumonia. Three days after the initial presentation, the patient developed a spontaneous generalized tonic-clonic seizure consistent with presumed COVID encephalitis, along with somnolence and confusion. A day later, the patient had two other seizure episodes. Follow-up EEG suggested an inter-ictal epileptic focus with sharp waves corresponding to roughly the same location as the patient’s pre-existing cavernoma. The patient’s seizures stopped shortly thereafter, while his encephalopathy continued for days. Conclusion: We illustrate that a pre-existing anatomic cortical abnormality may act as a potential nidus for new-onset seizure activity in the context of suggested COVID encephalopathy. Future studies may further demonstrate that manifestations of COVIDencephalopathy in certain patients may be more predictable than initially assumed.

Keywords: cavernoma, covid, encephalopathy, seizures

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: activities of daily living, classification, internet of things, machine learning, prediction, smart home

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Authors: Kelum N. Manamendra-Arachchi, Kalangi Rodrigo

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Bones, teeth, and shells have been acknowledged over the last two centuries as evidence of chronology, Palaeo-environment, and human activity. Faunal traces are valid evidence of past situations because they have properties that have not changed over long periods of time. Sri Lanka has been known as an Island, which has a diverse variation of prehistoric occupation among ecological zones. Defining the Paleoecology of the past societies has been an archaeological thought developed in the 1960s. It is mainly concerned with the reconstruction from available geological and biological evidence of past biota, populations, communities, landscapes, environments, and ecosystems. Sri Lanka has dealt with this subject and considerable research has been already undertaken. The fossil and material record of Sri Lanka’s Wet Zone tropical forests continues from c. 38,000–34,000 ybp. This early and persistent human fossil, technical, and cultural florescence, as well as a collection of well-preserved tropical-forest rock shelters with associated ' on-site ' Palaeoenvironmental records, makes Sri Lanka a central and unusual case study to determine the extent and strength of early human tropical forest encounters. Excavations carried out in prehistoric caves in the low country wet zone has shown that in the last 50,000 years, the temperature in the lowland rainforests has not exceeded 5 degrees. Based on Semnopithecus Priam (Gray Langur) remains unearned from wet zone prehistoric caves, it has been argued that periods of momentous climate changes during the LGM and Terminal Pleistocene/Early Holocene boundary, with a recognizable preference for semi-open ‘Intermediate’ rainforest or edges. Continuous Genus Acavus and Oligospira occupation along with uninterrupted horizontal pervasive of Canarium sp. (‘kekuna’ nut) have proven that temperatures in the lowland rain forests have not changed by at least 5 oC over the last 50,000 years. Site Catchment or Territorial analysis cannot be no longer defensible, due to time-distance based factors as well as optimal foraging theory failed as a consequences of prehistoric people were aware of the decrease in cost-benefit ratio and located sites, and generally played out a settlement strategy that minimized the ratio of energy expanded to energy produced.

Keywords: palaeo-environment, prehistory, palaeo-ecology, zooarchaeology

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Authors: B. Shukir, L. Szivos, D. Kis, P. Barzo

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Glioblastoma is the most malignant brain tumor. In general, the survival rate varies between (14-18) months. Glioblastoma consists a solid and infiltrative part. The standard therapeutic management of glioblastoma is maximum safe resection followed by chemo-radiotherapy. It’s hypothesized that the pretumoral hyperintense region in fluid attenuated inversion recovery (FLAIR) images includes both vasogenic edema and infiltrated tumor cells. In our study, we aimed to define the sensitivity and specificity of hyperintense FLAIR images preoperatively to examine how well it can define the true extent of glioblastoma. (16) glioblastoma patients included in this study. Hyperintense FLAIR region were delineated preoperatively as tumor mask. The infiltrative part of glioblastoma considered the regions where the tumor recurred on the follow up MRI. The recurrence on the CE-T1 images was marked as the recurrence masks. According to (AAL3) and (JHU white matter labels) atlas, the brain divided into cortical and subcortical regions respectively. For calculating specificity and sensitivity, the FLAIR and the recurrence masks overlapped counting how many regions affected by both . The average sensitivity and specificity was 83% and 85% respectively. Individually, the sensitivity and specificity varied between (31-100)%, and (100-58)% respectively. These results suggest that despite FLAIR being as an effective radiologic imaging tool its prognostic value remains controversial and probabilistic tractography remain more reliable available method for identifying the true extent of glioblastoma.

Keywords: brain tumors, glioblastoma, MRI, FLAIR

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Authors: Jiankang Wang, Hongyang Yu

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This paper proposes a portable online 3D modeling method. The method first utilizes a depth camera to collect data and compresses the depth data using a frame-by-frame lossless data compression method. The color image is encoded using the H.264 encoding format. After the cloud obtains the color image and depth image, a 3D modeling method based on bundlefusion is used to complete the 3D modeling. The results of this study indicate that this method has the characteristics of portability, online, and high efficiency and has a wide range of application prospects.

Keywords: 3D reconstruction, bundlefusion, lossless compression, depth image

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Authors: Chia-Yu Lin, Yu-Hsiang Shen, Cing-Ciao Ke, Chia-Hao Chang, Fan-Pin Tseng, Yu-Ching Ni, Sheng-Pin Tseng

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Tomosynthesis is an imaging system that generates a 3D image by scanning in a limited angular range. It could provide more depth information than traditional 2D X-ray single projection. Radiation dose in tomosynthesis is less than computed tomography (CT). Because of limited angular range scanning, there are many properties depending on scanning direction. Therefore, non-coplanar imaging technique was developed to improve image quality in traditional tomosynthesis. The purpose of this study was to establish the non-coplanar imaging technique of tomosynthesis system and evaluate this technique by the reconstructed image. INER prototype tomosynthesis system contains an X-ray tube, a flat panel detector, and a motion machine. This system could move X-ray tube in multiple directions during the acquisition. In this study, we investigated three different imaging techniques that were 2D X-ray single projection, traditional tomosynthesis, and non-coplanar tomosynthesis. An anthropopathic chest phantom was used to evaluate the image quality. It contained three different size lesions (3 mm, 5 mm and, 8 mm diameter). The traditional tomosynthesis acquired 61 projections over a 30 degrees angular range in one scanning direction. The non-coplanar tomosynthesis acquired 62 projections over 30 degrees angular range in two scanning directions. A 3D image was reconstructed by iterative image reconstruction algorithm (ML-EM). Our qualitative method was to evaluate artifacts in tomosynthesis reconstructed image. The quantitative method was used to calculate a peak-to-valley ratio (PVR) that means the intensity ratio of the lesion to the background. We used PVRs to evaluate the contrast of lesions. The qualitative results showed that in the reconstructed image of non-coplanar scanning, anatomic structures of chest and lesions could be identified clearly and no significant artifacts of scanning direction dependent could be discovered. In 2D X-ray single projection, anatomic structures overlapped and lesions could not be discovered. In traditional tomosynthesis image, anatomic structures and lesions could be identified clearly, but there were many artifacts of scanning direction dependent. The quantitative results of PVRs show that there were no significant differences between non-coplanar tomosynthesis and traditional tomosynthesis. The PVRs of the non-coplanar technique were slightly higher than traditional technique in 5 mm and 8 mm lesions. In non-coplanar tomosynthesis, artifacts of scanning direction dependent could be reduced and PVRs of lesions were not decreased. The reconstructed image was more isotropic uniformity in non-coplanar tomosynthesis than in traditional tomosynthesis. In the future, scan strategy and scan time will be the challenges of non-coplanar imaging technique.

Keywords: image reconstruction, non-coplanar imaging technique, tomosynthesis, X-ray imaging

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Authors: Dariusz Jacek Jakóbczak

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Mathematics and computer science are interested in methods of 2D curve interpolation and extrapolation using the set of key points (knots). A proposed method of Hurwitz- Radon Matrices (MHR) is such a method. This novel method is based on the family of Hurwitz-Radon (HR) matrices which possess columns composed of orthogonal vectors. Two-dimensional curve is interpolated via different functions as probability distribution functions: polynomial, sinus, cosine, tangent, cotangent, logarithm, exponent, arcsin, arccos, arctan, arcctg or power function, also inverse functions. It is shown how to build the orthogonal matrix operator and how to use it in a process of curve reconstruction.

Keywords: 2D data interpolation, hurwitz-radon matrices, MHR method, probabilistic modeling, curve extrapolation

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Authors: Aljoša Šorgo

Abstract:

Recent scholarship on Phrygian has begun to more closely examine the long-held belief that Greek and Phrygian are two very closely related languages. It is now clear that Graeco-Phrygian can be firmly postulated as a subclade of the Indo-European languages. The present paper will focus on the reconstruction of the phonological and phonetic segments of Proto-Graeco-Phrygian (= PGPh.) by providing relevant correspondence sets and reconstructing the classes of segments. The PGPh. basic vowel system consisted of ten phonemic oral vowels: */a e o ā ē ī ō ū/. The correspondences of the vowels are clear and leave little open to ambiguity. There were four resonants and two semi-vowels in PGPh.: */r l m n i̯ u̯/, which could appear in both a consonantal and a syllabic function, with the distribution between the two still being phonotactically predictable. Of note is the fact that the segments *m and *n seem to have merged when their phonotactic position would see them used in a syllabic function. Whether the segment resulting from this merger was a nasalized vowel (most likely *[ã]) or a syllabic nasal *[N̥] (underspecified for place of articulation) cannot be determined at this stage. There were three fricatives in PGPh.: */s h ç/. *s and *h are easily identifiable. The existence of *ç, which may seem unexpected, is postulated on the basis of the correspondence Gr. ὄς ~ Phr. yos/ιος. It is of note that Bozzone has previously proposed the existence of *ç ( < PIE *h₁i̯-) in an early stage of Greek even without taking into account Phrygian data. Finally, the system of stops in PGPh. distinguished four places of articulation (labial, dental, velar, and labiovelar) and three phonation types. The question of which three phonation types were actually present in PGPh. is one of great importance for the ongoing debate on the realization of the three series in PIE. Since the matter is still very much in dispute, we ought to, at this stage, endeavour to reconstruct the PGPh. system without recourse to the other IE languages. The three series of correspondences are: 1. Gr. T (= tenuis) ~ Phr. T; 2. Gr. D (= media) ~ Phr. T; 3. Gr. TA (= tenuis aspirata) ~ Phr. M. The first series must clearly be reconstructed as composed of voiceless stops. The second and third series are more problematic. With a bottom-up approach, neither the second nor the third series of correspondences are compatible with simple modal voicing, and the reflexes differ greatly in voice onset time. Rather, the defining feature distinguishing the two series was [±spread glottis], with ancillary vibration of the vocal cords. In PGPh. the second series was undergoing further spreading of the glottis. As the two languages split, this process would continue, but be affected by dissimilar changes in VOT, which was ultimately phonemicized in both languages as the defining feature distinguishing between their series of stops.

Keywords: bottom-up reconstruction, Proto-Graeco-Phrygian, spread glottis, syllabic resonant

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Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

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Authors: Alireza Akbari, Gelareh Babaee Khou

Abstract:

Ground Penetrating Radar (GPR) is an important nondestructive remote sensing tool that has been used in both military and civilian fields. Recently, GPR imaging has attracted lots of attention in detection of subsurface shallow small targets such as landmines and unexploded ordnance and also imaging behind the wall for security applications. For the monostatic arrangement in the space-time GPR image, a single point target appears as a hyperbolic curve because of the different trip times of the EM wave when the radar moves along a synthetic aperture and collects reflectivity of the subsurface targets. With this hyperbolic curve, the resolution along the synthetic aperture direction shows undesired low resolution features owing to the tails of hyperbola. However, highly accurate information about the size, electromagnetic (EM) reflectivity, and depth of the buried objects is essential in most GPR applications. Therefore hyperbolic curve behavior in the space-time GPR image is often willing to be transformed to a focused pattern showing the object's true location and size together with its EM scattering. The common goal in a typical GPR image is to display the information of the spatial location and the reflectivity of an underground object. Therefore, the main challenge of GPR imaging technique is to devise an image reconstruction algorithm that provides high resolution and good suppression of strong artifacts and noise. In this paper, at first, the standard back-projection (BP) algorithm that was adapted to GPR imaging applications used for the image reconstruction. The standard BP algorithm was limited with against strong noise and a lot of artifacts, which have adverse effects on the following work like detection targets. Thus, an improved BP is based on cross-correlation between the receiving signals proposed for decreasing noises and suppression artifacts. To improve the quality of the results of proposed BP imaging algorithm, a weight factor was designed for each point in region imaging. Compared to a standard BP algorithm scheme, the improved algorithm produces images of higher quality and resolution. This proposed improved BP algorithm was applied on the simulation and the real GPR data and the results showed that the proposed improved BP imaging algorithm has a superior suppression artifacts and produces images with high quality and resolution. In order to quantitatively describe the imaging results on the effect of artifact suppression, focusing parameter was evaluated.

Keywords: algorithm, back-projection, GPR, remote sensing

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

Abstract:

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: Kais Manai

Abstract:

The main part of this work focuses on the study of pion/muon separation at low energy using a nuclear Emulsion Cloud Chamber (ECC) made of lead and nuclear emulsion films. The work consists of two parts: particle reconstruction algorithm and a Neural Network that assigns to each reconstructed particle the probability to be a muon or a pion. The pion/muon separation algorithm has been optimized by using a detailed Monte Carlo simulation of the ECC and tested on real data. The algorithm allows to achieve a 60% muon identification efficiency with a pion misidentification smaller than 3%.

Keywords: nuclear emulsion, particle identification, tracking, neural network

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Authors: Chia-Feng Lu, Yuh-Jen Wang, Shin Teng, Yu-Te Wu, Sui-Hing Yan

Abstract:

Brain functional networks based on resting-state EEG data were compared between patients with mild Alzheimer’s disease (mAD) and matched patients with amnestic subtype of mild cognitive impairment (aMCI). We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions and the network analysis based on graph theory to further investigate the alterations of functional networks in mAD compared with aMCI group. We aimed at investigating the changes of network integrity, local clustering, information processing efficiency, and fault tolerance in mAD brain networks for different frequency bands based on several topological properties, including degree, strength, clustering coefficient, shortest path length, and efficiency. Results showed that the disruptions of network integrity and reductions of network efficiency in mAD characterized by lower degree, decreased clustering coefficient, higher shortest path length, and reduced global and local efficiencies in the delta, theta, beta2, and gamma bands were evident. The significant changes in network organization can be used in assisting discrimination of mAD from aMCI in clinical.

Keywords: EEG, functional connectivity, graph theory, TFCMI

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