Search results for: malaria cells images

Authors: Li Cheng, Zhang Yilei, Cohen Yehuda

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Two motility mechanisms were introduced into iDynoMiCs software, which adopts an individual-based modeling method. Based on the new capabilities, along with the pressure motility developed before, influence of bacterial motility on biofilm formation was studied. Simulation results were evaluated both qualitatively through 3D structure inspections and quantitatively by parameter characterizations. It was showed that twitching motility increased the biofilm surface irregularity probably due to movement of cells towards higher nutrient concentration location whereas free motility, on the other hand, could make biofilms flatter and smoother relatively. Pressure motility showed no significant influence in this study.

Keywords: iDynoMics, biofilm structure, bacterial motility, motility mechanisms

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Authors: Nawras Kurzom, Avi Mendelsohn

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The effects of background music on learning and memory are inconsistent, partly due to the intrinsic complexity and variety of music and partly to individual differences in music perception and preference. A prominent musical feature that is known to elicit strong emotional responses is musical tension. Musical tension can be brought about by building anticipation of rhythm, harmony, melody, and dynamics. Delaying the resolution of dominant-to-tonic chord progressions, as well as using dissonant harmonics, can elicit feelings of tension, which can, in turn, affect memory formation of concomitant information. The aim of the presented studies was to explore how forming declarative memory is influenced by musical tension, brought about within continuous music as well as in the form of isolated chords with varying degrees of dissonance/consonance. The effects of musical tension on long-term memory of declarative information were studied in two ways: 1) by evoking tension within continuous music pieces by delaying the release of harmonic progressions from dominant to tonic chords, and 2) by using isolated single complex chords with various degrees of dissonance/roughness. Musical tension was validated through subjective reports of tension, as well as physiological measurements of skin conductance response (SCR) and pupil dilation responses to the chords. In addition, music information retrieval (MIR) was used to quantify musical properties associated with tension and its release. Each experiment included an encoding phase, wherein individuals studied stimuli (words or images) with different musical conditions. Memory for the studied stimuli was tested 24 hours later via recognition tasks. In three separate experiments, we found positive relationships between tension perception and physiological measurements of SCR and pupil dilation. As for memory performance, we found that background music, in general, led to superior memory performance as compared to silence. We detected a trade-off effect between tension perception and memory, such that individuals who perceived musical tension as such displayed reduced memory performance for images encoded during musical tension, whereas tense music benefited memory for those who were less sensitive to the perception of musical tension. Musical tension exerts complex interactions with perception, emotional responses, and cognitive performance on individuals with and without musical training. Delineating the conditions and mechanisms that underlie the interactions between musical tension and memory can benefit our understanding of musical perception at large and the diverse effects that music has on ongoing processing of declarative information.

Keywords: musical tension, declarative memory, learning and memory, musical perception

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

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

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

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Authors: Mohammad Kazem Mohammadi

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The use of anticancer agents forms an important part of the treatment of cancer of various types. Uranyl Complexes with DPHMP ligand have been used for the prevention and treatment of cancers. U(IV) metal complexes prepared by reaction of uranyl salt UO2 (NO3)2.6H2O with DPHMP in dry acetonitrile. Characterization of the ligand and its complexes was made by microanalyses, FT-IR, 1H NMR, 13C NMR and UV–Visible spectroscopy. These new complex showed excellent antitumor activity against two kinds of cancer cells that that are HT29:Haman colon adenocarcinoma cell line and T47D:human breast adenocarcinoma cell line.

Keywords: uranyl complexes, DPHMP ligand, antitumor activity, HT29, T47D

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Authors: D. F. Carvalho, A. O. Uscamayta, J. C. Guerrero, H. F. Oliveira, P. M. Azevedo-Marques

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The creation of vector contours slices (ROIs) on body silhouettes in oncologic patients is an important step during the radiotherapy planning in clinic and hospitals to ensure the accuracy of oncologic treatment. The radiotherapy planning of patients is performed by complex softwares focused on analysis of tumor regions, protection of organs at risk (OARs) and calculation of radiation doses for anomalies (tumors). These softwares are supplied for a few manufacturers and run over sophisticated workstations with vector processing presenting a cost of approximately twenty thousand dollars. The Brazilian project SIPRAD (Radiotherapy Planning System) presents a proposal adapted to the emerging countries reality that generally does not have the monetary conditions to acquire some radiotherapy planning workstations, resulting in waiting queues for new patients treatment. The SIPRAD project is composed by a set of integrated and interoperabilities softwares that are able to execute all stages of radiotherapy planning on simple personal computers (PCs) in replace to the workstations. The goal of this work is to present an image processing technique, computationally feasible, that is able to perform an automatic contour delineation in patient body silhouettes (SIPRAD-Body). The SIPRAD-Body technique is performed in tomography slices under grayscale images, extending their use with a greedy algorithm in three dimensions. SIPRAD-Body creates an irregular polyhedron with the Canny Edge adapted algorithm without the use of preprocessing filters, as contrast and brightness. In addition, comparing the technique SIPRAD-Body with existing current solutions is reached a contours similarity at least 78%. For this comparison is used four criteria: contour area, contour length, difference between the mass centers and Jaccard index technique. SIPRAD-Body was tested in a set of oncologic exams provided by the Clinical Hospital of the University of Sao Paulo (HCRP-USP). The exams were applied in patients with different conditions of ethnology, ages, tumor severities and body regions. Even in case of services that have already workstations, it is possible to have SIPRAD working together PCs because of the interoperability of communication between both systems through the DICOM protocol that provides an increase of workflow. Therefore, the conclusion is that SIPRAD-Body technique is feasible because of its degree of similarity in both new radiotherapy planning services and existing services.

Keywords: radiotherapy, image processing, DICOM RT, Treatment Planning System (TPS)

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Authors: Tala Toonsi, Marah Alagha, Lina Alnowaiser, Hala Rajab

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This report is about the Photomath app, which is an AI application that uses image recognition technology, specifically optical character recognition (OCR) algorithms. The (OCR) algorithm translates the images into a mathematical equation, and the app automatically provides a step-by-step solution. The application supports decimals, basic arithmetic, fractions, linear equations, and multiple functions such as logarithms. Testing was conducted to examine the usage of this app, and results were collected by surveying ten participants. Later, the results were analyzed. This paper seeks to answer the question: To what level the artificial intelligence features are accurate and the speed of process in this app. It is hoped this study will inform about the efficiency of AI in Photomath to the users.

Keywords: photomath, image recognition, app, OCR, artificial intelligence, mathematical equations.

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Authors: Alireza Akbari, Gelareh Babaee Khou

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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: Joulié Aurélien, Jourdain Elsa, Bailly Xavier, Gasqui Patrick, Yang Elise, Leblond Agnès, Rousset Elodie, Sidi-Boumedine Karim

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Q fever is a worldwide zoonosis caused by the gram-negative obligate intracellular bacterium Coxiella burnetii. Following the recent outbreaks in the Netherlands, a hyper virulent clone was found to be the cause of severe human cases of Q fever. In livestock, Q fever clinical manifestations are mainly abortions. Although the abortion rates differ between ruminant species, C. burnetii’s virulence remains understudied, especially in enzootic areas. In this study, the infectious potential of three C. burnetii isolates collected from French farms of small ruminants were compared to the reference strain Nine Mile (in phase II and in an intermediate phase) using an in vivo (CD1 mice) model. Mice were challenged with 105 live bacteria discriminated by propidium monoazide-qPCR targeting the icd-gene. After footpad inoculation, spleen and popliteal lymph node were harvested at 10 days post-inoculation (p.i). The strain invasiveness in spleen and popliteal nodes was assessed by qPCR assays targeting the icd-gene. Preliminary results showed that the avirulent strains (in phase 2) failed to pass the popliteal barrier and then to colonize the spleen. This model allowed a significant differentiation between strain’s invasiveness on biological host and therefore identifying distinct virulence profiles. In view of these results, we plan to go further by testing fifteen additional C. burnetii isolates from French farms of sheep, goat and cattle by using the above-mentioned in vivo model. All 15 strains display distant MLVA (multiple-locus variable-number of tandem repeat analysis) genotypic profiles. Five of the fifteen isolates will bee also tested in vitro on ovine and bovine macrophage cells. Cells and supernatants will be harvested at day1, day2, day3 and day6 p.i to assess in vitro multiplication kinetics of strains. In conclusion, our findings might help the implementation of surveillance of virulent strains and ultimately allow adapting prophylaxis measures in livestock farms.

Keywords: Q fever, invasiveness, ruminant, virulence

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

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

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

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Authors: Maysoon Nasser Samhan, Somaya Alkiswani, Abdullah Alzibdeh

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Background: Routine lumbar MRIs for back pain may yield normal results despite persistent symptoms, which means the possibility of other causes for this pain, which was not shown on the routine images. Research suggests including coronal STIR imaging to detect additional pathologies like sacroiliitis. Objectives: This study aims to enhance diagnostic accuracy and aid in determining treatment processes for patients with persistent back pain who have normal routine lumbar MRI (T1 and T2 images) by incorporating coronal STIR into the examination. Methods: A prospectively conducted study involving 274 patients, 115 males and 159 females, with an age range of 6–92 years, reviewed their medical records and imaging data following a lumbar spine MRI. This study included patients with back pain and sciatica as their primary complaints, all of whom underwent lumbar spine MRIs at our hospital to identify potential pathologies. Using a GE Signa HD 1.5T MRI System, each patient received a standard MRI protocol that included T1 and T2 sagittal and axial sequences, as well as a coronal STIR sequence. We collected relevant MRI findings, including abnormalities and structural variations, from radiology reports. We classified these findings into tables and documented them as counts and percentages, using Fisher’s exact test to assess differences between categorical variables. We conducted a statistical analysis using Prism GraphPad software version 10.1.2. The study adhered to ethical guidelines, institutional review board approvals, and patient confidentiality regulations. Results: Exclusion of the coronal STIR sequence led to 83 subjects (30.29%) being classified as within normal limits on MRI examination. 36 patients without abnormalities on T1 and T2 sequences showed abnormalities on the coronal STIR sequence, with 26 cases attributed to spinal pathologies and 10 to non-spinal pathologies. In addition to that, Fisher's exact test demonstrated a significant association between sacroiliitis diagnosis and abnormalities identified solely through the coronal STIR sequence (P < 0.0001). Conclusion: Implementing coronal STIR imaging as part of routine lumbar MRI protocols has the potential to improve patient care by facilitating a more comprehensive evaluation and management of persistent back pain.

Keywords: magnetic resonance imaging, lumber MRI, radiology, neurology

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Authors: Bingquan Shen

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Convolutional Neural Networks (CNN) have demonstrated their effectiveness in synthesizing 3D views of object instances at various viewpoints. Given the problem where one have limited viewpoints of a particular object for classification, we present a pose normalization architecture to transform the object to existing viewpoints in the training dataset before classification to yield better classification performance. We have demonstrated that this Pose Normalization Network (PNN) can capture the style of the target object and is able to re-render it to a desired viewpoint. Moreover, we have shown that the PNN improves the classification result for the 3D chairs dataset and ShapeNet airplanes dataset when given only images at limited viewpoint, as compared to a CNN baseline.

Keywords: convolutional neural networks, object classification, pose normalization, viewpoint invariant

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Authors: Hossein Pourbashash

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Recent experimental studies have shown that HIV can be transmitted directly from cell to cell when structures called virological synapses form during interactions between T cells. In this article, we describe a new within-host model of HIV infection that incorporates two mechanisms: infection by free virions and the direct cell-to-cell transmission. We conduct the local and global stability analysis of the model. We show that if the basic reproduction number R0 1, the virus is cleared and the disease dies out; if R0 > 1, the virus persists in the host. We also prove that the unique positive equilibrium attracts all positive solutions under additional assumptions on the parameters.

Keywords: HIV virus model, cell-to-cell transmission, global stability, Lyapunov function, second compound matrices

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Authors: Katsue Edo, Yu Hiroi

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T Increasing attention has been paid to using pictures and photographs in research since the beginning of the 21th century in social sciences. Meanwhile we have been studying the usefulness of Picture mining, which is one of the new ways for a these picture using researches. Picture Mining is an explorative research analysis method that takes useful information from pictures, photographs and static or moving images. It is often compared with the methods of text mining. The Picture Mining concept includes observational research in the broad sense, because it also aims to analyze moving images (Ochihara and Edo 2013). In the recent literature, studies and reports using pictures are increasing due to the environmental changes. These are identified as technological and social changes (Edo et.al. 2013). Low price digital cameras and i-phones, high information transmission speed, low costs for information transferring and high performance and resolution of the cameras of mobile phones have changed the photographing behavior of people. Consequently, there is less resistance in taking and processing photographs for most of the people in the developing countries. In these studies, this method of collecting data from respondents is often called as ‘participant-generated photography’ or ‘respondent-generated visual imagery’, which focuses on the collection of data and its analysis (Pauwels 2011, Snyder 2012). But there are few systematical and conceptual studies that supports it significance of these methods. We have discussed in the recent years to conceptualize these picture using research methods and formalize theoretical findings (Edo et. al. 2014). We have identified the most efficient fields of Picture mining in the following areas inductively and in case studies; 1) Research in Consumer and Customer Lifestyles. 2) New Product Development. 3) Research in Fashion and Design. Though we have found that it will be useful in these fields and areas, we must verify these assumptions. In this study we will focus on the field of fashion and design, to determine whether picture mining methods are really reliable in this area. In order to do so we have conducted an empirical research of the respondents’ attitudes and behavior concerning pictures and photographs. We compared the attitudes and behavior of pictures toward fashion to meals, and found out that taking pictures of fashion is not as easy as taking meals and food. Respondents do not often take pictures of fashion and upload their pictures online, such as Facebook and Instagram, compared to meals and food because of the difficulty of taking them. We concluded that we should be more careful in analyzing pictures in the fashion area for there still might be some kind of bias existing even if the environment of pictures have drastically changed in these years.

Keywords: empirical research, fashion and design, Picture Mining, qualitative research

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Authors: Aussara Panya, Nunghathai Sawasdee, Mutita Junking, Chatchawan Srisawat, Kiattawee Choowongkomon, Pa-Thai Yenchitsomanus

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Dengue virus (DENV) infection is a global public health problem with approximately 100 million infected cases a year. Presently, there is no approved vaccine or effective drug available; therefore, the development of anti-DENV drug is urgently needed. The clinical reports revealing the positive association between the disease severity and viral titer has been reported previously suggesting that the anti-DENV drug therapy can possibly ameliorate the disease severity. Although several anti-DENV agents showed inhibitory activities against DENV infection, to date none of them accomplishes clinical use in the patients. The surface envelope (E) protein of DENV is critical for the viral entry step, which includes attachment and membrane fusion; thus, the blocking of envelope protein is an attractive strategy for anti-DENV drug development. To search the safe anti-DENV agent, this study aimed to search for novel peptide inhibitors to counter DENV infection through the targeting of E protein using a structure-based in silico design. Two selected strategies has been used including to identify the peptide inhibitor which interfere the membrane fusion process whereby the hydrophobic pocket on the E protein was the target, the destabilization of virion structure organization through the disruption of the interaction between the envelope and membrane proteins, respectively. The molecular docking technique has been used in the first strategy to search for the peptide inhibitors that specifically bind to the hydrophobic pocket. The second strategy, the peptide inhibitor has been designed to mimic the ectodomain portion of membrane protein to disrupt the protein-protein interaction. The designed peptides were tested for the effects on cell viability to measure the toxic to peptide to the cells and their inhibitory assay to inhibit the DENV infection in Vero cells. Furthermore, their antiviral effects on viral replication, intracellular protein level and viral production have been observed by using the qPCR, cell-based flavivirus immunodetection and immunofluorescence assay. None of tested peptides showed the significant effect on cell viability. The small peptide inhibitors achieved from molecular docking, Glu-Phe (EF), effectively inhibited DENV infection in cell culture system. Its most potential effect was observed for DENV2 with a half maximal inhibition concentration (IC50) of 96 μM, but it partially inhibited other serotypes. Treatment of EF at 200 µM on infected cells also significantly reduced the viral genome and protein to 83.47% and 84.15%, respectively, corresponding to the reduction of infected cell numbers. An additional approach was carried out by using peptide mimicking membrane (M) protein, namely MLH40. Treatment of MLH40 caused the reduction of foci formation in four individual DENV serotype (DENV1-4) with IC50 of 24-31 μM. Further characterization suggested that the MLH40 specifically blocked viral attachment to host membrane, and treatment with 100 μM could diminish 80% of viral attachment. In summary, targeting the hydrophobic pocket and M-binding site on the E protein by using the peptide inhibitors could inhibit DENV infection. The results provide proof of-concept for the development of antiviral therapeutic peptide inhibitors to counter DENV infection through the use of a structure-based design targeting conserved viral protein.

Keywords: dengue virus, dengue virus infection, drug design, peptide inhibitor

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Authors: A. Bouloufa, K. Djessas

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In this paper, we reported the effect of substrate temperature on the structural, electrical and optical properties of In2S3 thin films deposited on soda-lime glass substrates by physical vapor deposition technique at various substrate temperatures. The In2Se3 material used for deposition was synthesized from its constituent elements. It was found that all samples exhibit one phase which corresponds to β-In2S3 phase. Values of band gap energy of the films obtained at different substrate temperatures vary in the range of 2.38-2.80 eV and decrease with increasing substrate temperature.

Keywords: buffer layer, In2S3, optical properties, PVD, structural properties

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Authors: Fatimah Abd Elghani, Raymonde Szargel, Vered Shani, Hazem Safory, Haya Hamza, Mor Savyon, Ruth Rott, Rina Bandopadhyay, Simone Engelender

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Background: PINK1 is a mitochondrial kinase mutated in some familial cases of Parkinson’s disease. Down regulation of PINK1 results in abnormal mitochondrial morphology and altered membrane potential. Although PINK1 has a predicted mitochondrial import sequence, it’s cellular, and submitochondrial localization remains unclear, in part because it is rapidly degraded. In this work, we investigated the mechanisms involved in PINK1 degradation and how this may affect PINK1 stability and function, with implications for mitochondrial function in PD. In addition, pharmacological inhibition of proteasome activity was shown to lead to PINK1 accumulation, indicating that PINK1 degradation depends on the ubiquitin-proteasome system (UPS). Methods: Using co-immunoprecipitation assays, we identified E3 ubiquitin ligase SIAH1 as a PINK1-interacting protein in HEK293 cells as well as on rat brain tissues. In addition, we determined the effect of SIAH 1, SIAH2 and Parkin on PINK1 steady-state levels by Western blot analysis, and checked their possibility to ubiquitinate and mediate PINK1 degradation through the proteasome carried out in vivo ubiquitination experiments. Results: We have obtained results showing that SIAH-1 interacts with and ubiquitinates PINK1. The ubiquitination promoted by SIAH-1 leads to the proteasomal degradation of PINK1. We confirmed these findings by knocking down SIAH-1 and observing important accumulation of PINK1 in cells. Besides, we found that SIAH-1 decreases PINK1 steady-state levels but not the E3 ligase Parkin. We also investigated the interaction of SIAH-1 with PINK1 disease mutants and its ability to promote their ubiquitination and degradation. Although, no clear difference in the ability of SIAH-1 to promote the degradation of PINK1 disease mutants was observed. It is possible that dysfunction of proteasomal activity in the disease may lead to the accumulation and aggregation of ubiquitinated PINK1 in patients with PINK1 mutations, with possible implications to the pathogenesis of PD. Conclusions: Here, we demonstrated that SIAH-1 ubiquitinates and promotes the degradation of PINK1. In addition, SIAH-1 represents now a target that may help the improvement of mitophagy in PD. Further investigations needed to understand how mitophagy is regulated by PINK1-SIAH-1 axis to provide targets for future therapeutics.

Keywords: PD, Parkinson's disease, PINK1, PTEN-induced kinase1, SIAH, seven in absentia homolog, SN, substantia nigra

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Authors: J. Tomilla Ajayi, Werner E. Van Zyl

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This work presents an overview of the reaction of 2, 4-diferrocenyl-1, 3-dithiadiphosphetane-2, 4-disulfide (Ferrocenyl Lawesson’s reagent) with water to produce the non-symmetric, ferocenyl dithiophosphonic acid respectively in high yields. These acids were readily deprotonated by anhydrous Ammonia to yield the corresponding ammonium salt NH4S2PFcOH. These were complex to Ni (II) in molar ratio 1:1 and 1:2. The resulting complex from the reaction formed same compound with different isomers (Cis and Trans) and also compound with multimetallic coordination. Quality X-ray crystals were formed from THF/Ether. The compounds were characterized by 1H, 31P NMR, and FTIR. Bulk purity were confirmed by either ESI-MS or elemental analysis and The XRD images were obtained using single crystal X-ray crystallographic studies. The electrochemical investigation of the Compounds were carried out using cyclic voltammetry.

Keywords: ferrocenyl, dithiophosphonate, isomer, coordination

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Authors: Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen

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Grain quality analysis is a multi-parameterized problem that includes a variety of qualitative and quantitative parameters such as grain type classification, damage type classification, and nutrient regression. Currently, these parameters require human inspection, a multitude of instruments employing a variety of sensor technologies, and predictive model types or destructive and slow chemical analysis. This paper investigates the feasibility of applying near-infrared hyperspectral imaging (NIR-HSI) to grain quality analysis. For this study two datasets of NIR hyperspectral images in the wavelength range of 900 nm - 1700 nm have been used. Both datasets contain images of sparsely and densely packed grain kernels. The first dataset contains ~87,000 image crops of bulk wheat samples from 63 harvests where protein value has been determined by the FOSS Infratec NOVA which is the golden industry standard for protein content estimation in bulk samples of cereal grain. The second dataset consists of ~28,000 image crops of bulk grain kernels from seven different wheat varieties and a single rye variety. In the first dataset, protein regression analysis is the problem to solve while variety classification analysis is the problem to solve in the second dataset. Deep convolutional neural networks (CNNs) have the potential to utilize spatio-spectral correlations within a hyperspectral image to simultaneously estimate the qualitative and quantitative parameters. CNNs can autonomously derive meaningful representations of the input data reducing the need for advanced preprocessing techniques required for classical chemometric model types such as artificial neural networks (ANNs) and partial least-squares regression (PLS-R). A comparison between different CNN architectures utilizing 2D and 3D convolution is conducted. These results are compared to the performance of ANNs and PLS-R. Additionally, a variety of preprocessing techniques from image analysis and chemometrics are tested. These include centering, scaling, standard normal variate (SNV), Savitzky-Golay (SG) filtering, and detrending. The results indicate that the combination of NIR-HSI and CNNs has the potential to be the foundation for an automatic system unifying qualitative and quantitative grain quality analysis within a single sensor technology and predictive model type.

Keywords: deep learning, grain analysis, hyperspectral imaging, preprocessing techniques

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

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

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

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Authors: Youssef. K. A. Abdalhafid, Ezaldin A. M. Mohammed, Masoud M. M. Zatout

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This study described the changes in the liver of Uromastyx acanthinura (Bell, 1825) males and females during hibernation and activity seasons. The results revealed that, hibernation causes increase fatty liver and pigment cells with abundant damage, comparing with nearly normal structure and less fatty liver after the hibernation with almost normal pattern. Genomic DNA showed apparent separation during hibernation. Also, caspase 3 and caspase 7 activity reached a high level in the liver tissue during hibernation comparing with activity season.

Keywords: histological liver, DNA fragmentation, hibernation, caspase 3 and caspase 7

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Authors: Somkait Udomhunsakul

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In this paper, a multi-focus image fusion method using Spatial Frequency Measurements (SFM) and Wavelet Packet was proposed. The proposed fusion approach, firstly, the two fused images were transformed and decomposed into sixteen subbands using Wavelet packet. Next, each subband was partitioned into sub-blocks and each block was identified the clearer regions by using the Spatial Frequency Measurement (SFM). Finally, the recovered fused image was reconstructed by performing the Inverse Wavelet Transform. From the experimental results, it was found that the proposed method outperformed the traditional SFM based methods in terms of objective and subjective assessments.

Keywords: multi-focus image fusion, wavelet packet, spatial frequency measurement

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Authors: Jui-Ting Hsu, Heng-Li Huang, Ming-Tzu Tsai, Kuo-Chih Su, Lih-Jyh Fuh

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The objectives of this study were to measure the initial stability of the dental implant (ISQ and PTV) in the artificial foam bone block with three different quality levels. In addition, the 3D bone to implant contact percentage (BIC%) was measured based on the micro-computed tomography images. Furthermore, the relation between the initial stability of dental implant (ISQ and PTV) and BIC% were calculated. The experimental results indicated that enhanced the material property of the artificial foam bone increased the initial stability of the dental implant. The Pearson’s correlation coefficient between the BIC% and the two approaches (ISQ and PTV) were 0.652 and 0.745.

Keywords: dental implant, implant stability quotient, peak insertion torque, bone-implant contact, micro-computed tomography

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Authors: Ashot Navasardian, Mariam Vardanian, Vladik Vardanian

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The photovoltaic and the semiconductor industries are in growth and it is necessary to supply a large amount of silicon to maintain this growth. Since silicon is still the best material for the manufacturing of solar cells and semiconductor components so the pure silicon like solar grade and semiconductor grade materials are demanded. There are two main routes for silicon production: metallurgical and chemical. In this article, we reviewed the electrotecnological installations and systems for semiconductor manufacturing. The main task is to design the installation which can produce SOG Silicon from river sand by one work unit.

Keywords: metallurgical grade silicon, solar grade silicon, impurity, refining, plasma

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Authors: D. G. Piliposyan

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Propagation of electro-elastic waves in a piezoelectric waveguide with finite stacks and a defect layer is studied using a modified transfer matrix method. The dispersion equation for a periodic structure consisting of unit cells made up from two piezoelectric materials with metallized interfaces is obtained. An analytical expression, for the transmission coefficient for a waveguide with finite stacks and a defect layer, that is found can be used to accurately detect and control the position of the passband within a stopband. The result can be instrumental in constructing a tunable waveguide made of layers of different or identical piezoelectric crystals and separated by metallized interfaces.

Keywords: piezoelectric layered structure, periodic phononic crystal, bandgap, bloch waves

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Authors: Kunal Bhardwaj, Christine Browne

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With the increase in global awareness of the environmental impacts of plastic-based products, there has been a massive drive to reduce our use of these products. Use of plastic-based substrates in electronic circuits has been a matter of concern recently. Plastics provide a very smooth and cheap surface for printing high-performance electronics due to their non-permeability to ink and easy mouldability. In this research, we explore the use of nano cellulose (NC) films in electronics as they provide an advantage of being 100% recyclable and eco-friendly. The main hindrance in the mass adoption of NC film as a substitute for plastic is its higher surface roughness which leads to ink penetration, and dispersion in the channels on the film. This research was conducted to tune the RMS roughness of NC films to a range where they can replace plastics in electronics(310-470nm). We studied the dependence of the surface roughness of the NC film on the following tunable aspects: 1) composition by weight of the NC suspension that is sprayed on a silicon wafer 2) the width and the depth of the channels on the silicon wafer used as a base. Various silicon wafers with channel depths ranging from 6 to 18 um and channel widths ranging from 5 to 500um were used as a base. Spray coating method for NC film production was used and two solutions namely, 1.5wt% NC and a 50-50 NC-CNC (cellulose nanocrystal) mixture in distilled water, were sprayed through a Wagner sprayer system model 117 at an angle of 90 degrees. The silicon wafer was kept on a conveyor moving at a velocity of 1.3+-0.1 cm/sec. Once the suspension was uniformly sprayed, the mould was left to dry in an oven at 50°C overnight. The images of the films were taken with the help of an optical profilometer, Olympus OLS 5000. These images were converted into a ‘.lext’ format and analyzed using Gwyddion, a data and image analysis software. Lowest measured RMS roughness of 291nm was with a 50-50 CNC-NC mixture, sprayed on a silicon wafer with a channel width of 5 µm and a channel depth of 12 µm. Surface roughness values of 320+-17nm were achieved at lower (5 to 10 µm) channel widths on a silicon wafer. This research opened the possibility of the usage of 100% recyclable NC films with an additive (50% CNC) in high-performance electronics. Possibility of using additives like Carboxymethyl Cellulose (CMC) is also being explored due to the hypothesis that CMC would reduce friction amongst fibers, which in turn would lead to better conformations amongst the NC fibers. CMC addition would thus be able to help tune the surface roughness of the NC film to an even greater extent in future.

Keywords: nano cellulose films, electronic circuits, nanocrystals and surface roughness

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Authors: O. Boussoufi, K. Lamrini Uahabi, M. Atounti

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The main purpose of this paper is to calculate the fractal dimension of some Julia Sets and Mandelbrot Set in the Misiurewicz Points. Using Matlab to generate the Julia Sets images that match the Misiurewicz points and using a Fractal software, we were able to find different measures that characterize those fractals in textures and other features. We are actually focusing on fractal dimension and the error calculated by the software. When executing the given equation of regression or the log-log slope of image a Box Counting method is applied to the entire image, and chosen settings are available in a FracLAc Program. Finally, a comparison is done for each image corresponding to the area (boundary) where Misiurewicz Point is located.

Keywords: box counting, FracLac, fractal dimension, Julia Sets, Mandelbrot Set, Misiurewicz Points

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Authors: Sangwoo Han, Saeed Khaleghi Rahimian, Ying Liu

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Vehicle electrification is gaining momentum, and many car manufacturers promise to deliver more electric vehicle (EV) models to consumers in the coming years. In controlling the battery pack, the battery management system (BMS) must maintain optimal battery performance while ensuring the safety of a battery pack. Tasks related to battery performance include determining state-of-charge (SOC), state-of-power (SOP), state-of-health (SOH), cell balancing, and battery charging. Safety related functions include making sure cells operate within specified, static and dynamic voltage window and temperature range, derating power, detecting faulty cells, and warning the user if necessary. The BMS often utilizes an RC circuit model to model a Li-ion cell because of its robustness and low computation cost among other benefits. Because an equivalent circuit model such as the RC model is not a physics-based model, it can never be a prognostic model to predict battery state-of-health and avoid any safety risk even before it occurs. A physics-based Li-ion cell model, on the other hand, is more capable at the expense of computation cost. To avoid the high computation cost associated with a full-order model, many researchers have demonstrated the use of a single particle model (SPM) for BMS applications. One drawback associated with the single particle modeling approach is that it forces to use the average current density in the calculation. The SPM would be appropriate for simulating drive cycles where there is insufficient time to develop a significant current distribution within an electrode. However, under a continuous or high-pulse electrical load, the model may fail to predict cell voltage or Li⁺ plating potential. To overcome this issue, a multi-particle reduced-order model is proposed here. The use of multiple particles combined with either linear or nonlinear charge-transfer reaction kinetics enables to capture current density distribution within an electrode under any type of electrical load. To maintain computational complexity like that of an SPM, governing equations are solved sequentially to minimize iterative solving processes. Furthermore, the model is validated against a full-order model implemented in COMSOL Multiphysics.

Keywords: battery management system, physics-based li-ion cell model, reduced-order model, single-particle and multi-particle model

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Authors: Manami Masuda, Mariko Era, Takayoshi Kawahara, Takahide Kanyama, Hiroshi Morita

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Objectives: Fatty acid salts are a type of anionic surfactant and are produced from fatty acids and alkali. Moreover, fatty acid salts are known to have potent antibacterial activities. Acanthamoeba is ubiquitously distributed in the environment including sea water, fresh water, soil and even from the air. Although generally free-living, Acanthamoeba can be an opportunistic pathogen, which could cause a potentially blinding corneal infection known as Acanthamoeba keratitis. So, in this study, we evaluated the anti-amoeba activity of fatty acid salts and fatty acids to Acanthamoeba castellanii ATCC 30010. Materials and Methods: The antibacterial activity of 9 fatty acid salts (potassium butyrate (C4K), caproate (C6K), caprylate (C8K), caprate (C10K), laurate (C12K), myristate (C14K), oleate (C18:1K), linoleate (C18:2K), linolenate (C18:3K)) tested on cells of Acanthamoeba castellanii ATCC 30010. Fatty acid salts (concentration of 175 mM and pH 10.5) were prepared by mixing the fatty acid with the appropriate amount of KOH. The amoeba suspension mixed with KOH with a pH adjusted solution was used as the control. Fatty acids (concentration of 175 mM) were prepared by mixing the fatty acid with Tween 80 (20 %). The amoeba suspension mixed with Tween 80 (20 %) was used as the control. The anti-amoeba method, the amoeba suspension (3.0 × 104 cells/ml trophozoites) was mixed with the sample of fatty acid potassium (final concentration of 175 mM). Samples were incubated at 30°C, for 10 min, 60 min, and 180 min and then the viability of A. castellanii was evaluated using plankton counting chamber and trypan blue stainings. The minimum inhibitory concentration (MIC) against Acanthamoeba was determined using the two-fold dilution method. The MIC was defined as the minimal anti-amoeba concentration that inhibited visible amoeba growth following incubation (180 min). Results: C8K, C10K, and C12K were the anti-amoeba effect of 4 log-unit (99.99 % growth suppression of A. castellanii) incubated time for 180 min against A. castellanii at 175mM. After the amoeba, the suspension was mixed with C10K or C12K, destroying the cell membrane had been observed. Whereas, the pH adjusted control solution did not exhibit any effect even after 180 min of incubation with A. castellanii. Moreover, C6, C8, and C18:3 were the anti-amoeba effect of 4 log-unit incubated time for 60 min. C4 and C18:2 exhibited a 4-log reduction after 180 min incubation. Furthermore, the minimum inhibitory concentration (MIC) was determined. The MIC of C10K, C12K and C4 were 2.7 mM. These results indicate that C10K, C12K and C4 have high anti-amoeba activity against A. castellanii and suggest C10K, C12K and C4 have great potential for antimi-amoeba agents.

Keywords: Fatty acid salts, anti-amoeba activities, Acanthamoeba, fatty acids

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Authors: Zhen Cao, Yu Zhu, Junxue Fu

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Immunoassay, i.e., antigen-antibody reaction, is crucial for disease diagnostics. To achieve the adequate signal of the antigen protein detection, a large amount of sample and long incubation time is needed. However, the amount of protein is usually small at the early stage, which makes it difficult to detect. Unlike cells and DNAs, no valid chemical method exists for protein amplification. Thus, an alternative way to improve the signal is through particle manipulation techniques to concentrate proteins, among which dielectrophoresis (DEP) is an effective one. DEP is a technique that concentrates particles to the designated region through a force created by the gradient in a non-uniform electric field. Since DEP force is proportional to the cube of particle size and square of electric field gradient, it is relatively easy to capture larger particles such as cells. For smaller ones like proteins, a super high gradient is then required. In this work, three-dimensional Ag/SiO2 nanorods arrays, fabricated by an easy physical vapor deposition technique called as oblique angle deposition, have been integrated with a DEP device and created the field gradient as high as of 2.6×10²⁴ V²/m³. The nanorods based DEP device is able to enrich bovine serum albumin (BSA) protein by 1800-fold and the rate has reached 180-fold/s when only applying 5 V electric potential. Based on the above nanorods integrated DEP platform, an immunoassay of mouse immunoglobulin G (IgG) proteins has been performed. Briefly, specific antibodies are immobilized onto nanorods, then IgG proteins are concentrated and captured, and finally, the signal from fluorescence-labelled antibodies are detected. The limit of detection (LoD) is measured as 275.3 fg/mL (~1.8 fM), which is a 20,000-fold enhancement compared with identical assays performed on blank glass plates. Further, prostate-specific antigen (PSA), which is a cancer biomarker for diagnosis of prostate cancer after radical prostatectomy, is also quantified with a LoD as low as 2.6 pg/mL. The time to signal saturation has been significantly reduced to one minute. In summary, together with an easy nanorod fabrication and integration method, this nanorods based DEP platform has demonstrated highly sensitive immunoassay performance and thus poses great potentials in applications for early point-of-care diagnostics.

Keywords: dielectrophoresis, immunoassay, oblique angle deposition, protein concentration

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Authors: Sasidhar B., Bhaskar Rao N., Ramesh Babu D. R., Ravi Shankar M.

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Segmentation of lung pleura is a preprocessing step in Computer-Aided Diagnosis (CAD) which helps in reducing false positives in detection of lung cancer. The existing methods fail in extraction of lung regions with the nodules at the pleura of the lungs. In this paper, a new method is proposed which segments lung regions with nodules at the pleura of the lungs based on curvature analysis and morphological operators. The proposed algorithm is tested on 06 patient’s dataset which consists of 60 images of Lung Image Database Consortium (LIDC) and the results are found to be satisfactory with 98.3% average overlap measure (AΩ).

Keywords: curvature analysis, image segmentation, morphological operators, thresholding

Procedia PDF Downloads 596