Search results for: muscle magnetic signal

Authors: Van-Ngoc-Cuong Le, Ngoc-Quy Le

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Approaches to the diagnosis of ectopic solid organs in the abdominopelvic cavity include Accessory liver lobe, Accessory spleens (ectopic splenic tissue), Wandering spleen, Ectopic pancreatic tissue, Ectopic kidney (Pancake kidney), Cryptorchidism (undescended testis, ectopic testis), Ectopic endometriosis. The application of diagnostic imaging techniques, of which magnetic resonance imaging is the most important, includes a clinical case study and reports. Ectopic organs and tumors are easy to confuse. This is a concern, as well as practical challenges encountered and solutions adopted in the fields of Image Analysis.

Keywords: ectopic, accessory, wandering, tumor

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Authors: Victor I. Ilgisonis, Ludmila V. Konovaltseva, Vladimir P. Lakhin, Ekaterina A. Sorokina

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The analytical solutions for geodesic acoustic eigenmodes in tokamak plasmas with circular concentric magnetic surfaces are found. In the frame of ideal magnetohydrodynamics the dispersion relation taking into account the toroidal coupling between electrostatic perturbations and electromagnetic perturbations with poloidal mode number |m| = 2 is derived. In the absence of such a coupling the dispersion relation gives the standard continuous spectrum of geodesic acoustic modes. The analysis of the existence of global eigenmodes for plasma equilibria with both off-axis and on-axis maximum of the local geodesic acoustic frequency is performed.

Keywords: tokamak, MHD, geodesic acoustic mode, eigenmode

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Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

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Authors: Adae Amoako, Daniel Montero, Peter Murray, George Pujalte

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We present a case of a 42-year-old, right-handed Caucasian male who presented to a medical orthopedics clinic with left wrist pain. The patient indicated that the pain started two months prior to the visit. He could only remember helping a friend move furniture prior to the onset of pain. Examination of the left wrist showed limited extension compared to the right. There was clicking with flexion and extension of the wrist on the dorsal aspect. Mild tenderness was noticed over the distal radioulnar joint. There was ulnar and radial deviation on provocation. Initial 4-view x-rays of the left wrist showed mild radiocarpal and scapho-trapezium-trapezoid (ST-T) osteoarthritis, with subchondral cysts seen in the lunate and scaphoid, with no obvious fractures. The patient was initially put in a wrist brace and diclofenac topical gel was prescribed for pain control, as a patient could not take non-steroidal anti-inflammatory drugs (NSAIDs) due to gastritis. Despite diclofenac topical gel use and bracing, symptoms remained, and a steroid injection with 1 mL of lidocaine with 10 mg of triamcinolone acetonide was performed under fluoroscopy. He obtained some relief but after 3 months, the injection had to be repeated. On 2-month follow up after the initial evaluation, symptoms persisted. Magnetic resonance imaging (MRI) was obtained which showed an abnormal T1 hypodense signal involving the proximal pole of the scaphoid and articular collapse proximally of the scaphoid, with marked irregularity of the overlying cartilage, suggesting a remote injury, findings consistent with avascular necrosis of the proximal pole of the scaphoid. A month after that, the patient had the left proximal pole of the scaphoid debrided and an intercompartmental supraretinacular artery vascularized. Pedicle bone graft reconstruction of the proximal pole of the left scaphoid was done. A non-vascularized autograft from the left radius was also applied. He was put in a thumb spica cast with the interphalangeal joint free for 6 weeks. On 6-week follow-up after surgery, the patient was healing well and could make a composite fist with his left hand. The diagnosis of Preiser’s disease is primarily based on radiological findings. Due to the fact that necrosis happens over a period of time, most AVNs are diagnosed at the late stages of the disease. There appear to be no specific guidelines on the management AVN of the scaphoid. In the past, immobilization and arthroscopic debridement had been used. Radial osteotomy has also been tried. Vascularized bone grafts have also been used to treat Preiser’s disease. In our patient, we used three of these treatment modalities, starting with conservative management with topical NSAIDS and immobilization, then debridement with vascularized bone grafts.

Keywords: wrist pain, avascular necrosis of the scaphoid, Preiser’s disease, vascularized bone grafts

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Authors: Neha Bhattacharyya, Soumendra Singh, Amrita Banerjee, Ria Ghosh, Oindrila Sinha, Nairit Das, Rajkumar Gayen, Somya Subhra Pal, Sahely Ganguly, Tanmoy Dasgupta, Tanusree Dasgupta, Pulak Mondal, Aniruddha Adhikari, Sharmila Sarkar, Debasish Bhattacharyya, Asim Kumar Mallick, Om Prakash Singh, Samir Kumar Pal

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Background: We aim to develop an integrated device comprised of single-probe EEG and CCD-based motion sensors for a more objective measure of Attention-deficit Hyperactivity Disorder (ADHD). While the integrated device (MAHD) relies on the EEG signal (spectral density of beta wave) for the assessment of attention during a given structured task (painting three segments of a circle using three different colors, namely red, green and blue), the CCD sensor depicts movement pattern of the subjects engaged in a continuous performance task (CPT). A statistical analysis of the attention and movement patterns was performed, and the accuracy of the completed tasks was analysed using indigenously developed software. The device with the embedded software, called MAHD, is intended to improve certainty with criterion E (i.e. whether symptoms are better explained by another condition). Methods: We have used the EEG signal from a single-channel dry sensor placed on the frontal lobe of the head of the subjects (3-5 years old pre-schoolers). During the painting of three segments of a circle using three distinct colors (red, green, and blue), absolute power for delta and beta EEG waves from the subjects are found to be correlated with relaxation and attention/cognitive load conditions. While the relaxation condition of the subject hints at hyperactivity, a more direct CCD-based motion sensor is used to track the physical movement of the subject engaged in a continuous performance task (CPT) i.e., separation of the various colored balls from one table to another. We have used our indigenously developed software for the statistical analysis to derive a scale for the objective assessment of ADHD. We have also compared our scale with clinical ADHD evaluation. Results: In a limited clinical trial with preliminary statistical analysis, we have found a significant correlation between the objective assessment of the ADHD subjects with that of the clinician’s conventional evaluation. Conclusion: MAHD, the integrated device, is supposed to be an auxiliary tool to improve the accuracy of ADHD diagnosis by supporting greater criterion E certainty.

Keywords: ADHD, CPT, EEG signal, motion sensor, psychometric test

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Authors: Junkal Gutierrez, Hernane S. Barud, Sidney J. L. Ribeiro, Agnieszka Tercjak

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Nowadays the interest on green nanocomposites and on the development of more environmental friendly products has been increased. Bacterial cellulose has been recently investigated as an attractive environmentally friendly material for the preparation of low-cost nanocomposites. The formation of cellulose by laboratory bacterial cultures is an interesting and attractive biomimetic access to obtain pure cellulose with excellent properties. Additionally, properties as molar mass, molar mass distribution, and the supramolecular structure could be control using different bacterial strain, culture mediums and conditions, including the incorporation of different additives. This kind of cellulose is a natural nanomaterial, and therefore, it has a high surface-to-volume ratio which is highly advantageous in composites production. Such property combined with good biocompatibility, high tensile strength, and high crystallinity makes bacterial cellulose a potential material for applications in different fields. The aim of this investigation work was the fabrication of novel hybrid inorganic-organic composites based on bacterial cellulose, cultivated in our laboratory, as a template. This kind of biohybrid nanocomposites gathers together excellent properties of bacterial cellulose with the ones displayed by typical inorganic nanoparticles like optical, magnetic and electrical properties, luminescence, ionic conductivity and selectivity, as well as chemical or biochemical activity. In addition, the functionalization of cellulose with inorganic materials opens new pathways for the fabrication of novel multifunctional hybrid materials with promising properties for a wide range of applications namely electronic paper, flexible displays, solar cells, sensors, among others. In this work, different pathways for fabrication of multifunctional biohybrid nanopapers with tunable properties based on BC modified with amphiphilic poly(ethylene oxide-b-propylene oxide-b-ethylene oxide) (EPE) block copolymer, sol-gel synthesized nanoparticles (titanium, vanadium and a mixture of both oxides) and functionalized iron oxide nanoparticles will be presented. In situ (biosynthesized) and ex situ (at post-production level) approaches were successfully used to modify BC membranes. Bacterial cellulose based biocomposites modified with different EPE block copolymer contents were developed by in situ technique. Thus, BC growth conditions were manipulated to fabricate EPE/BC nanocomposite during the biosynthesis. Additionally, hybrid inorganic/organic nanocomposites based on BC membranes and inorganic nanoparticles were designed via ex-situ method, by immersion of never-dried BC membranes into different nanoparticle solutions. On the one hand, sol-gel synthesized nanoparticles (titanium, vanadium and a mixture of both oxides) and on the other hand superparamagnetic iron oxide nanoparticles (SPION), Fe2O3-PEO solution. The morphology of designed novel bionanocomposites hybrid materials was investigated by atomic force microscopy (AFM) and scanning electron microscopy (SEM). In order to characterized obtained materials from the point of view of future applications different techniques were employed. On the one hand, optical properties were analyzed by UV-vis spectroscopy and spectrofluorimetry and on the other hand electrical properties were studied at nano and macroscale using electric force microscopy (EFM), tunneling atomic force microscopy (TUNA) and Keithley semiconductor analyzer, respectively. Magnetic properties were measured by means of magnetic force microscopy (MFM). Additionally, mechanical properties were also analyzed.

Keywords: bacterial cellulose, block copolymer, advanced characterization techniques, nanoparticles

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Authors: Anshul Raja

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Cystic lesions of the spleen are rare and splenic hydatid cysts account for only 0.5% to 8% of all hydatidosis. Authors hereby report a case where a 50-year-old female presented to our hospital with the complains of heaviness and pain over left upper abdomen over the past 8-10 years. On radiological examination, ultrasonography revealed findings consistent with isolated splenic hydatid cyst and was later on confirmed on Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). No other organ or system involvement was seen. The patient underwent splenectomy and hydatid cyst was confirmed on histopathology. Owing to its rarity, it offers a diagnostic challenge to physicians but can reliably be diagnosed with great confidence employing various imaging modalities like CT and MRI.

Keywords: gastrointestinal radiology, abdominal imaging, hydatid cyst, medical and health sciences

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Authors: Eunsong Lee, Gae Baik Kim, Young Pil Kim

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Bisphenol A (BPA) is one of the endocrine disruptors (EDCs), which have been suspected to be associated with reproductive dysfunction and physiological abnormality in human. Since the BPA has been widely used to make plastics and epoxy resins, the leach of BPA from the lining of plastic products has been of major concern, due to its environmental or human exposure issues. The simple detection of BPA based on the self-assembly of aptamer-mediated gold nanoparticles (AuNPs) has been reported elsewhere, yet the detection sensitivity still remains challenging. Here we demonstrate an improved AuNP-based sensor of BPA by using fluorescence-combined AuNP colorimetry in order to overcome the drawback of traditional AuNP sensors. While the anti-BPA aptamer (full length or truncated ssDNA) triggered the self-assembly of unmodified AuNP (citrate-stabilized AuNP) in the presence of BPA at high salt concentrations, no fluorescence signal was observed by the subsequent addition of SYBR Green, due to a small amount of free anti-BPA aptamer. In contrast, the absence of BPA did not cause the self-assembly of AuNPs (no color change by salt-bridged surface stabilization) and high fluorescence signal by SYBP Green, which was due to a large amount of free anti-BPA aptamer. As a result, the quantitative analysis of BPA was achieved using the combination of absorption of AuNP with fluorescence intensity of SYBR green as a function of BPA concentration, which represented more improved detection sensitivity (as low as 1 ppb) than did in the AuNP colorimetric analysis. This method also enabled to detect high BPA in water-soluble extracts from thermal papers with high specificity against BPS and BPF. We suggest that this approach will be alternative for traditional AuNP colorimetric assays in the field of aptamer-based molecular diagnosis.

Keywords: bisphenol A, colorimetric, fluoroscence, gold-aptamer nanobiosensor

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Authors: H. I. Obadiah, S. N. Wieser, E. A. Omudu, B. O. Atu, O. Byanet, L. Schnittger, M. Florin-Christensen

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Sarcocystis sp. are Apicomplexan protozoan parasites with a life cycle that involves a predator and a prey as final and intermediate hosts, respectively. In tissues of the intermediate hosts, the parasites produce sarcocysts that vary in size and morphology according to the species. When a suitable predator ingests sarcocyst-containing meat, the parasites are released in the intestine and undergo sexual reproduction producing infective sporocysts, which are excreted with the feces into the environment. The cycle is closed when a prey ingests sporocyst-contaminated water or pasture; the parasites gain access to the circulation, and eventually invade tissues and reproduce asexually yielding sarcocysts. Pig farming is a common practice in Nigeria as well as in many countries around the world. In addition to its importance as protein source, pork is also a source of several pathogens relevant to humans. In the case of Sarcocystis, three species have been described both in domestic and wild pigs, namely, S. miescheriana, S. porcifelis and S. suihominis. Humans can act both as final and aberrant intermediate hosts of S. suihominis, after ingesting undercooked sarcocyst-infested pork. Infections are usually asymptomatic but can be associated with inappetence, nausea, vomiting and diarrhea, or with muscle pain, fever, eosinophilia and bronchospasm, in humans acting as final or intermediate hosts, respectively. Moreover, excretion of infective forms with human feces leads to further dissemination of the infection. In this study, macroscopic sarcocysts of white color, oval shape and a size range of approximately 3-5 mm were observed in the skeletal muscle of a slaughtered pig in an abattoir in Makurdi, Benue State, Nigeria, destined to human consumption. Sarcocysts were excised and washed in distilled water, and genomic DNA was extracted using a commercial kit. The near-complete length of the 18S rRNA gene was analyzed after PCR amplification of two overlapping fragments, each of which were submitted to direct sequencing. In addition, the mitochondrial cytochrome oxidase (cox-1) gene was PCR-amplified and directly sequenced. Two phylogenetic trees containing the obtained sequences along with available relevant 18S rRNA and cox-1 sequences were constructed by neighbor joining after alignment, using the corresponding sequences of Toxoplasma gondii as outgroup. The results showed in both cases that the analyzed sequences grouped with S. suihominis with high bootstrap value, confirming the identity of this macroscopic sarcocyst-forming parasite as S. suihominis. To the best of our knowledge, these results represent the first demonstration of this parasite in pigs of Nigeria and the largest sarcocysts described so far for S. suihominis. The close proximity between pigs and humans in pig farms, and the frequent poor sanitary conditions in human dwellings strongly suggest that the parasite undergoes the sexual stages of its life cycle in humans as final hosts. These findings provide an important reference for the examination and control of Sarcocystis species in pigs of Nigeria.

Keywords: nigeria, pork, sarcocystis suihominis, zoonotic parasite

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Authors: Destin Kurniawati

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Asthma is one of the deadly diseases in the world. According to the World Health Organization in 2012, 300 million people suffer from asthma of different races and classes. An estimated 250,000 people die because of asthma annually.As well as more than 57% of children and 51% of adults with asthma. There two risk factors for asthma. That risk factors are the host and environmental. One of the environmental factors that can bring asthma is allergens. When an allergen enters the body, the allergen binds to IgE and cause cell granulat- issued several mediators such as histamine, leukotrienes, bradykinin or something like that. This will cause localized edema effect on bronchial walls of small, thick mucous secretions in the bronchioles, and bronchial smooth muscle spasm. Then there will be inflammation of the airways. Methodology this research is by literature. Therefore, to anticipate and cope with asthma is to control environmental factors that serve to minimize allergens and controlling one's intake in the form of antioxidant-rich foods. Foods rich in antioxidants serve to improve lung function and decrease symptoms of the disease of the respiratory tract.

Keywords: asthma, deadly disease, allergen, environmental and food control

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Authors: John E. Muñoz, Jose F. Lopez, David S. Lopez

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Attention Deficit Hyperactivity Disorder (ADHD) is a disorder that affects 1 out of 5 Colombian children, converting into a real public health problem in the country. Conventional treatments such as medication and neuropsychological therapy have been proved to be insufficient in order to decrease high incidence levels of ADHD in the principal Colombian cities. This work demonstrates a design and development of a videogame that uses a brain computer interface not only to serve as an input device but also as a tool to monitor neurophysiologic signal. The video game named “The Harvest Challenge” puts a cultural scene of a Colombian coffee grower in its context, where a player can use his/her avatar in three mini games created in order to reinforce four fundamental aspects: i) waiting ability, ii) planning ability, iii) ability to follow instructions and iv) ability to achieve objectives. The details of this collaborative designing process of the multimedia tool according to the exact clinic necessities and the description of interaction proposals are presented through the mental stages of attention and relaxation. The final videogame is presented as a tool for sustained attention training in children with ADHD using as an action mechanism the neuromodulation of Beta and Theta waves through an electrode located in the central part of the front lobe of the brain. The processing of an electroencephalographic signal is produced automatically inside the videogame allowing to generate a report of the theta/beta ratio evolution - a biological marker, which has been demonstrated to be a sufficient measure to discriminate of children with deficit and without.

Keywords: BCI, neuromodulation, ADHD, videogame, neurofeedback, theta/beta ratio

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Authors: Subhajit Das, Nirjhar Dhang

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Structural damage detection is a challenging work in the field of structural health monitoring (SHM). The damage detection methods mainly focused on the determination of the location and severity of the damage. Model updating is a well known method to locate and quantify the damage. In this method, an error function is defined in terms of difference between the signal measured from ‘experiment’ and signal obtained from undamaged finite element model. This error function is minimised with a proper algorithm, and the finite element model is updated accordingly to match the measured response. Thus, the damage location and severity can be identified from the updated model. In this paper, an error function is defined in terms of modal data viz. frequencies and modal assurance criteria (MAC). MAC is derived from Eigen vectors. This error function is minimized by teaching-learning-based optimization (TLBO) algorithm, and the finite element model is updated accordingly to locate and quantify the damage. Damage is introduced in the model by reduction of stiffness of the structural member. The ‘experimental’ data is simulated by the finite element modelling. The error due to experimental measurement is introduced in the synthetic ‘experimental’ data by adding random noise, which follows Gaussian distribution. The efficiency and robustness of this method are explained through three examples e.g., one truss, one beam and one frame problem. The result shows that TLBO algorithm is efficient to detect the damage location as well as the severity of damage using modal data.

Keywords: damage detection, finite element model updating, modal assurance criteria, structural health monitoring, teaching learning based optimization

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Authors: Sevde Altuntas, Fatih Buyukserin

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Alzheimer’s disease is responsible for irreversible neural damage of brain parts. One of the disease markers is Amyloid-β 1-42 protein that accumulates in the brain in the form plaques. The basic problem for detection of the protein is the low amount of protein that cannot be detected properly in body liquids such as blood, saliva or urine. To solve this problem, tests like ELISA or PCR are proposed which are expensive, require specialized personnel and can contain complex protocols. Therefore, Surface-enhanced Raman Spectroscopy (SERS) a good candidate for detection of Amyloid-β 1-42 protein. Because the spectroscopic technique can potentially allow even single molecule detection from liquid and solid surfaces. Besides SERS signal can be improved by using nanopattern surface and also is specific to molecules. In this context, our study proposes to fabricate diagnostic test models that utilize Au-coated nanopatterned polycarbonate (PC) surfaces modified with Thioflavin - T to detect low concentrations of Amyloid-β 1-42 protein in water and artificial saliva medium by the enhancement of protein SERS signal. The nanopatterned PC surface that was used to enhance SERS signal was fabricated by using Anodic Alumina Membranes (AAM) as a template. It is possible to produce AAMs with different column structures and varying thicknesses depending on voltage and anodization time. After fabrication process, the pore diameter of AAMs can be arranged with dilute acid solution treatment. In this study, two different columns structures were prepared. After a surface modification to decrease their surface energy, AAMs were treated with PC solution. Following the solvent evaporation, nanopatterned PC films with tunable pillared structures were peeled off from the membrane surface. The PC film was then modified with Au and Thioflavin-T for the detection of Amyloid-β 1-42 protein. The protein detection studies were conducted first in water via this biosensor platform. Same measurements were conducted in artificial saliva to detect the presence of Amyloid Amyloid-β 1-42 protein. SEM, SERS and contact angle measurements were carried out for the characterization of different surfaces and further demonstration of the protein attachment. SERS enhancement factor calculations were also completed via experimental results. As a result, our research group fabricated diagnostic test models that utilize Au-coated nanopatterned polycarbonate (PC) surfaces modified with Thioflavin-T to detect low concentrations of Alzheimer’s Amiloid – β protein in water and artificial saliva medium. This work was supported by The Scientific and Technological Research Council of Turkey (TUBITAK) Grant No: 214Z167.

Keywords: alzheimer, anodic aluminum oxide, nanotopography, surface enhanced Raman spectroscopy

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Authors: Kumar Kanudkuri, A. Sandhya

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Typically, in a MRI clinical setting, there are several protocols run, each indicated for a specific anatomy and disease condition. However, these protocols or parameters within them can change over time due to changes to the recommendations by the physician groups or updates in the software or by the availability of new technologies. Most of the time, the changes are performed by the MRI technologist to account for either time, coverage, physiological, or Specific Absorbtion Rate (SAR ) reasons. However, giving properly guidelines to MRI technologist is important so that they do not change the parameters that negatively impact the image quality. Typically a standard American College of Radiology (ACR) MRI phantom is used for Quality Control (QC) in order to guarantee that the primary objectives of MRI are met. The visual evaluation of quality depends on the operator/reviewer and might change amongst operators as well as for the same operator at various times. Therefore, overcoming these constraints is essential for a more impartial evaluation of quality. This makes quantitative estimation of image quality (IQ) metrics for MRI quality control is very important. So in order to solve this problem, we proposed that there is a need for a robust, open-source, and automated MRI image control tool. The Designed and developed an automatic analysis tool for measuring MRI image quality (IQ) metrics like Signal to Noise Ratio (SNR), Signal to Noise Ratio Uniformity (SNRU), Visual Information Fidelity (VIF), Feature Similarity (FSIM), Gray level co-occurrence matrix (GLCM), slice thickness accuracy, slice position accuracy, High contrast spatial resolution) provided good accuracy assessment. A standardized quality report has generated that incorporates metrics that impact diagnostic quality.

Keywords: ACR MRI phantom, MRI image quality metrics, SNRU, VIF, FSIM, GLCM, slice thickness accuracy, slice position accuracy

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Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: Justice Zakhele Msomi

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Nanoparticles of CdFe2O4 with particle size of about 10 nm have been synthesized by high energy ball milling and co-precipitation processes. The synthesis route appears to have some effects on the properties. The compounds have been characterized by X-ray diffraction, Fourier Transform Infrared (FTIR), transmission electron microscopy (TEM), Mössbauer and magnetization measurements. The XRD pattern of CdFe2O4 provides information about single-phase formation of spinel structure with cubic symmetry. The FTIR measurements between 400 and 4000 cm-1 indicate intrinsic cation vibration of the spinel structure. The Mössbauer spectra were recorded at 4 K and 300 K. The hyperfine fields appear to be highly sensitive on particle size. The evolution of the properties as a function of particle size is also presented.

Keywords: ferrite, nanoparticles, magnetization, Mössbauer

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Authors: Amir Davood Elmi

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From the earliest light microscope to the most innovative X-ray imaging techniques, all of them have refined and improved our knowledge about the organization and composition of living tissues. The old techniques are time consuming and ultimately destructive to the tissues under the examination. In recent few decades, thanks to the boost of technology, non-destructive visualization techniques, such as X-ray computed tomography (CT), magnetic resonance imaging (MRI), selective plane illumination microscopy (SPIM), and optical projection tomography (OPT), have come to the forefront. Among these techniques, CT is excellent for mineralized tissues such as bone or dentine. In addition, CT it is faster than other aforementioned techniques and the sample remains intact. In this article, applications, advantages, and limitations of micro-CT is discussed, in addition to some information about micro-CT of soft tissue.

Keywords: Micro-CT, hard tissue, bone, attenuation coefficient, rapid prototyping

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Authors: U. Paniveni

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A few parameters of supergranular cells are studied using intensity patterns from the Kodaikanal Solar Observatory and Dopplergrams from SOHO. The turbulent aspect of the solar supergranulation is established by examining the interrelationships amongst the parameters characterizing a supergranular cell, namely size, lifetime, area, perimeter, fractal dimension, and horizontal flow velocity. The complexity of supergranular cells depicted by their fractal dimension is indicative of their non-laminar characteristics. The findings corroborate Kolmogorov’s theory of turbulence. Some parameters of supergranular cells also show a latitudinal dependence. Supergranulation is a synonym of convective phenomenon and hence can shed light on the physical conditions in the convection zone of the Sun. It plays a major role in the transport and dispersal of magnetic fields that may have a relation to the phases of the solar cycle.

Keywords: sun, granulation, convection, turbulence

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Authors: William L. Whitehouse, Louisa H. Y. Lo, Andrew B. Kinghorn, Simon C. C. Shiu, Julian. A. Tanner

Abstract:

C-reactive protein (CRP) is an acute-phase reactant and sensitive indicator for sepsis and other life-threatening pathologies, including systemic inflammatory response syndrome (SIRS). Currently, clinical turn-around times for established CRP detection methods take between 30 minutes to hours or even days from centralized laboratories. Here, we report the development of an electrochemical biosensor using redox probe-tagged DNA aptamers functionalized onto cheap, commercially available screen-printed electrodes. Binding-induced conformational switching of the CRP-targeting aptamer induces a specific and selective signal-ON event, which enables single-step and reagentless detection of CRP in as little as 1 minute. The aptasensor dynamic range spans 5-1000nM (R=0.97) or 5-500nM (R=0.99) in 50% diluted human serum, with a LOD of 3nM, corresponding to 2-orders of magnitude sensitivity under the clinically relevant cut-off for CRP. The sensor is stable for up to one week and can be reused numerous times, as judged from repeated real-time dosing and dose-response assays. By decoupling binding events from the signal induction mechanism, structure-switching electrochemical aptamer-based sensors (SS-EABs) provide considerable advantages over their adsorption-based counterparts. Our work expands on the retinue of such sensors reported in the literature and is the first instance of an SS-EAB for reagentless CRP detection. We hope this study can inspire further investigations into the suitability of SS-EABs for diagnostics, which will aid translational R&D toward fully realized devices aimed at point-of-care applications or for use more broadly by the public.

Keywords: structure-switching, C-reactive protein, electrochemical, biosensor, aptasensor.

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Authors: Paola Leon, Hugo Garcia, Adan Leon, Samuel Munoz

Abstract:

The enhanced oil recovery by steam injection was considered a process that only generated physical recovery mechanisms. However, there is evidence of the occurrence of a series of chemical reactions, which are called aquathermolysis, which generates hydrogen sulfide, carbon dioxide, methane, and lower molecular weight hydrocarbons. These reactions can be favored by the addition of a catalyst during steam injection; in this way, it is possible to generate the original oil in situ upgrading through the production increase of molecules of lower molecular weight. This additional effect could increase the oil recovery factor and reduce costs in transport and refining stages. Therefore, this research has focused on the experimental evaluation of the catalytic aquathermolysis on a Colombian heavy oil with 12,8°API. The effects of three different catalysts, reaction time, and temperature were evaluated in a batch microreactor. The changes in the Colombian heavy oil were quantified through nuclear magnetic resonance 1H-NMR. The relaxation times interpretation and the absorption intensity allowed to identify the distribution of the functional groups in the base oil and upgraded oils. Additionally, the average number of aliphatic carbons in alkyl chains, the number of substituted rings, and the aromaticity factor were established as average structural parameters in order to simplify the samples' compositional analysis. The first experimental stage proved that each catalyst develops a different reaction mechanism. The aromaticity factor has an increasing order of the salts used: Mo > Fe > Ni. However, the upgraded oil obtained with iron naphthenate tends to form a higher content of mono-aromatic and lower content of poly-aromatic compounds. On the other hand, the results obtained from the second phase of experiments suggest that the upgraded oils have a smaller difference in the length of alkyl chains in the range of 240º to 270°C. This parameter has lower values at 300°C, which indicates that the alkylation or cleavage reactions of alkyl chains govern at higher reaction temperatures. The presence of condensation reactions is supported by the behavior of the aromaticity factor and the bridge carbons production between aromatic rings (RCH₂). Finally, it is observed that there is a greater dispersion in the aliphatic hydrogens, which indicates that the alkyl chains have a greater reactivity compared to the aromatic structures.

Keywords: catalyst, upgrading, aquathermolysis, steam

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

Abstract:

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: N. D'Amico, E. Grossi, B. Colombo, F. Rigiroli, M. Buscema, D. Fazzini, G. Cornalba, S. Papa

Abstract:

Purpose: To characterize, through a radiomic approach, the nature of nodules considered non-specific by expert radiologists, recognized in magnetic resonance mammography (MRm) with T1-weighted (T1w) sequences with paramagnetic contrast. Material and Methods: 47 cases out of 1200 undergoing MRm, in which the MRm assessment gave uncertain classification (non-specific nodules), were admitted to the study. The clinical outcome of the non-specific nodules was later found through follow-up or further exams (biopsy), finding 35 benign and 12 malignant. All MR Images were acquired at 1.5T, a first basal T1w sequence and then four T1w acquisitions after the paramagnetic contrast injection. After a manual segmentation of the lesions, done by a radiologist, and the extraction of 150 radiomic features (30 features per 5 subsequent times) a machine learning (ML) approach was used. An evolutionary algorithm (TWIST system based on KNN algorithm) was used to subdivide the dataset into training and validation test and to select features yielding the maximal amount of information. After this pre-processing, different machine learning systems were applied to develop a predictive model based on a training-testing crossover procedure. 10 cases with a benign nodule (follow-up older than 5 years) and 18 with an evident malignant tumor (clear malignant histological exam) were added to the dataset in order to allow the ML system to better learn from data. Results: NaiveBayes algorithm working on 79 features selected by a TWIST system, resulted to be the best performing ML system with a sensitivity of 96% and a specificity of 78% and a global accuracy of 87% (average values of two training-testing procedures ab-ba). The results showed that in the subset of 47 non-specific nodules, the algorithm predicted the outcome of 45 nodules which an expert radiologist could not identify. Conclusion: In this pilot study we identified a radiomic approach allowing ML systems to perform well in the diagnosis of a non-specific nodule at MR mammography. This algorithm could be a great support for the early diagnosis of malignant breast tumor, in the event the radiologist is not able to identify the kind of lesion and reduces the necessity for long follow-up. Clinical Relevance: This machine learning algorithm could be essential to support the radiologist in early diagnosis of non-specific nodules, in order to avoid strenuous follow-up and painful biopsy for the patient.

Keywords: breast, machine learning, MRI, radiomics

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Authors: S. S. Sathiesh

Abstract:

The aim of this project is to study the radiation mechanism synchrotron and Inverse Compton scattering. Theoretically, we discussed spectral energy distribution for both. Programming is done for plotting the graph of Power-law spectrum for synchrotron Radiation using fortran90. The importance of power law spectrum was discussed and studied to infer its physical parameters from the model fitting. We also discussed how to infer the physical parameters from the theoretically drawn graph, we have seen how one can infer B (magnetic field of the source), γ min, γ max, spectral indices (p1, p2) while fitting the curve to the observed data.

Keywords: blazars/quasars, beaming, synchrotron radiation, Synchrotron Self Compton, inverse Compton scattering, mrk421

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Authors: Sujata Kulkarni, Udhav Bhosle, Vijaykumar T.

Abstract:

Due to the closeness between seismic signals and non-seismic signals, it is vital to detect earthquakes using conventional methods. In order to distinguish between seismic events and non-seismic events depending on their amplitude, our study processes the data that come from seismic sensors. The authors suggest a robust noise suppression technique that makes use of a bandpass filter, an IIR Wiener filter, recursive short-term average/long-term average (STA/LTA), and Carl short-term average (STA)/long-term average for event identification (LTA). The trigger ratio used in the proposed study to differentiate between seismic and non-seismic activity is determined. The proposed work focuses on significant feature extraction for machine learning-based seismic event detection. This serves as motivation for compiling a dataset of all features for the identification and forecasting of seismic signals. We place a focus on feature vector dimension reduction techniques due to the temporal complexity. The proposed notable features were experimentally tested using a machine learning model, and the results on unseen data are optimal. Finally, a presentation using a hybrid dataset (captured by different sensors) demonstrates how this model may also be employed in a real-time setting while lowering false alarm rates. The planned study is based on the examination of seismic signals obtained from both individual sensors and sensor networks (SN). A wideband seismic signal from BSVK and CUKG station sensors, respectively located near Basavakalyan, Karnataka, and the Central University of Karnataka, makes up the experimental dataset.

Keywords: Carl STA/LTA, features extraction, real time, dataset, machine learning, seismic detection

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Authors: Pradip Kumar Jha, Manoj Kumar

Abstract:

We demonstrate in this work the effect of Rashba spin orbit interaction on multiphoton optical transitions of a quantum dot in the presence of THz laser field and external static magnetic field. This combination is solved by accurate non-perturbative Floquet theory. Investigations are made for the optical response of intraband transition between the various states of the conduction band with spin flipping. Enhancement and power broadening observed for excited states probabilities with increase of external fields are directly linked to the emission spectra of QD and will be useful for making future bioimaging devices.

Keywords: bioimaging, multiphoton processes, spin orbit interaction, quantum dot

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Authors: Sung-Suk Oh, Bong-Keun Kang, Sang-Wook Park, Hui-Jin Joo, Jong-Ryul Choi, Seong-Jun Lee, Jeong-Woo Sohn

Abstract:

The imaging phantom is utilized for the verification, evaluation and tuning of the medical imaging device and system. Although it could be costly, 3D printing is an ideal technique for a rapid, customized, multi-modal phantom making. In this article, we propose the multi-modal phantom using 3D printing. First of all, the Dicom images for were measured by CT (Computed Tomography) and 3D X-ray systems (PET/CT and Angio X-ray system of Siemens) and then were analyzed. Finally, the 3D modeling was processed using Dicom images. The 3D printed phantom was scanned by PET/CT and MRI systems and then evaluated.

Keywords: imaging phantom, MRI (Magnetic Resonance Imaging), PET / CT (Positron Emission Tomography / Computed Tomography), 3D printing

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Authors: Bruno R. A. Oliveira, Italo V. V. Braga, Jonas P. Reges, Luiz P. O. Santos, Sidney C. Duarte, Emilson R. R. Melo, Auzuir R. Alexandria

Abstract:

This project aims to building a controlled greenhouse, or for better understanding, a structure where one can maintain a given range of temperature values (°C) coming from radiation emitted by an incandescent light, as previously defined, characterizing as a kind of on-off control and a differential, which is the plotting of temperature versus time graphs assisted by MATLAB software via serial communication. That way it is possible to connect the stove with a computer and monitor parameters. In the control, it was performed using a PIC 16F877A microprocessor which enabled convert analog signals to digital, perform serial communication with the IC MAX232 and enable signal transistors. The language used in the PIC's management is Basic. There are also a cooling system realized by two coolers 12V distributed in lateral structure, being used for venting and the other for exhaust air. To find out existing temperature inside is used LM35DZ sensor. Other mechanism used in the greenhouse construction was comprised of a reed switch and a magnet; their function is in recognition of the door position where a signal is sent to a buzzer when the door is open. Beyond it exist LEDs that help to identify the operation which the stove is located. To facilitate human-machine communication is employed an LCD display that tells real-time temperature and other information. The average range of design operating without any major problems, taking into account the limitations of the construction material and structure of electrical current conduction, is approximately 65 to 70 ° C. The project is efficient in these conditions, that is, when you wish to get information from a given material to be tested at temperatures not as high. With the implementation of the greenhouse automation, facilitating the temperature control and the development of a structure that encourages correct environment for the most diverse applications.

Keywords: greenhouse, microcontroller, temperature, control, MATLAB

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Authors: Meimei Wen, Chang Nyung Kim

Abstract:

In the current study, three-dimensional liquid metal (LM) magneto-hydrodynamic (MHD) flows in a manifold with three sub-channels under a uniform magnetic field are numerically investigated. In the manifold, the electrical current can cross channel walls, thus having influence on the flow distribution in each sub-channel. A case with various arrangements of electric conductivity for different parts of channel walls is considered, yielding different current distributions as well as flow distributions in each sub-channel. Here, the imbalance of mass flow rates in the three sub-channels is addressed. Meanwhile, predicted are detailed behaviors of the flow velocity, pressure, current and electric potential of LM MHD flows with three sub-channels. Commercial software CFX is used for the numerical simulation of LM MHD flows.

Keywords: CFX, liquid metal, manifold, MHD flow

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Authors: Sahar Nasr, Lin Li, Edwin Wang

Abstract:

Bladder cancer (BLCA) is known as the 13th cause of death among cancer patients worldwide, and ~575,000 new BLCA cases are diagnosed each year. Urothelial carcinoma (UC) is the most prevalent subtype among BLCA patients, which can be categorized into muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC). Currently, various therapeutic options are available for UC patients, including (1) transurethral resection followed by intravesical instillation of chemotherapeutics or Bacillus Calmette-Guérin for NMIBC patients, (2) neoadjuvant platinum-based chemotherapy (NAC) plus radical cystectomy is the standard of care for localized MIBC patients, and (3) systematic chemotherapy for metastatic UC. However, conventional treatments may lead to several challenges for treating patients. As an illustration, some patients may suffer from recurrence of the disease after the first line of treatment. Recently, immune checkpoint therapy (ICT) has been introduced as an alternative treatment strategy for the first or second line of treatment in advanced or metastatic BLCA patients. Although ICT showed lucrative results for a fraction of BLCA patients, ~80% of patients were not responsive to it. Therefore, novel treatment methods are required to augment the ICI response rate within BLCA patients. It has been shown that the infiltration of T-cells into the tumor microenvironment (TME) is positively correlated with the response to ICT within cancerous patients. Therefore, the goal of this study is to enhance the infiltration of cytotoxic T-cells into TME through the identification of target genes within the tumor that are responsible for the non-T-cell inflamed TME and their inhibition. BLCA bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) and immune score for TCGA samples were used to determine the Pearson correlation score between the expression of different genes and immune score for each sample. The genes with strong negative correlations were selected (r < -0.2). Thereafter, the correlation between the expression of each gene and survival in BLCA patients was calculated using the TCGA data and Cox regression method. The genes that are common in both selected gene lists were chosen for further analysis. Afterward, BLCA bulk and single-cell RNA-sequencing data were ranked based on the expression of each selected gene and the top and bottom 25% samples were used for pathway enrichment analysis. If the pathways related to the T-cell infiltration (e.g., antigen presentation, interferon, or chemokine pathways) were enriched within the low-expression group, the gene was included for downstream analysis. Finally, the selected genes will be used to calculate the correlation between their expression and the infiltration rate of the activated CD+8 T-cells, natural killer cells and the activated dendric cells. A list of potential target genes has been identified and ranked based on the above-mentioned analysis and criteria. SUN-1 got the highest score within the gene list and other identified genes in the literature as benchmarks. In conclusion, inhibition of SUN1 may increase the tumor-infiltrating lymphocytes and the efficacy of ICI in BLCA patients. BLCA tumor cells with and without SUN-1 CRISPR/Cas9 knockout will be injected into the syngeneic mouse model to validate the predicted SUN-1 effect on increasing tumor-infiltrating lymphocytes.

Keywords: data analysis, gene expression analysis, gene identification, immunoinformatic, functional genomics, transcriptomics

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