Search results for: fractional fourier transform

Authors: Efstratios Karavasilis, Foteini Christidi, Georgios Velonakis, Agapi Plousi, Kalliopi Platoni, Nikolaos Kelekis, Ioannis Evdokimidis, Efstathios Efstathopoulos

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Introduction: Advanced structural and functional neuroimaging techniques contribute to the study of anatomical and functional brain connectivity and its role in the pathophysiology and symptoms’ heterogeneity in several neurodegenerative disorders, including multiple sclerosis (MS). Aim: In the present study, we applied multiparametric neuroimaging techniques to investigate the structural and functional cortico-cerebellar changes in MS patients. Material: We included 51 MS patients (28 with clinically isolated syndrome [CIS], 31 with relapsing-remitting MS [RRMS]) and 51 age- and gender-matched healthy controls (HC) who underwent MRI in a 3.0T MRI scanner. Methodology: The acquisition protocol included high-resolution 3D T1 weighted, diffusion-weighted imaging and echo planar imaging sequences for the analysis of volumetric, tractography and functional resting state data, respectively. We performed between-group comparisons (CIS, RRMS, HC) using CAT12 and CONN16 MATLAB toolboxes for the analysis of volumetric (cerebellar gray matter density) and functional (cortico-cerebellar resting-state functional connectivity) data, respectively. Brainance suite was used for the analysis of tractography data (cortico-cerebellar white matter integrity; fractional anisotropy [FA]; axial and radial diffusivity [AD; RD]) to reconstruct the cerebellum tracts. Results: Patients with CIS did not show significant gray matter (GM) density differences compared with HC. However, they showed decreased FA and increased diffusivity measures in cortico-cerebellar tracts, and increased cortico-cerebellar functional connectivity. Patients with RRMS showed decreased GM density in cerebellar regions, decreased FA and increased diffusivity measures in cortico-cerebellar WM tracts, as well as a pattern of increased and mostly decreased functional cortico-cerebellar connectivity compared to HC. The comparison between CIS and RRMS patients revealed significant GM density difference, reduced FA and increased diffusivity measures in WM cortico-cerebellar tracts and increased/decreased functional connectivity. The identification of decreased WM integrity and increased functional cortico-cerebellar connectivity without GM changes in CIS and the pattern of decreased GM density decreased WM integrity and mostly decreased functional connectivity in RRMS patients emphasizes the role of compensatory mechanisms in early disease stages and the disintegration of structural and functional networks with disease progression. Conclusions: In conclusion, our study highlights the added value of multimodal neuroimaging techniques for the in vivo investigation of cortico-cerebellar brain changes in neurodegenerative disorders. An extension and future opportunity to leverage multimodal neuroimaging data inevitably remain the integration of such data in the recently-applied mathematical approaches of machine learning algorithms to more accurately classify and predict patients’ disease course.

Keywords: advanced neuroimaging techniques, cerebellum, MRI, multiple sclerosis

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Authors: Tien-Hui Chiang

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The code theory, proposed by Basil Bernstein, indicates that framing can be viewed as the core element in constituting the phenomenon of cultural reproduction because it is able to regulate the transmission of pedagogical information. Strong framing increases the social relation boundary between a teacher and pupils, which obstructs information transmission, so that in order to improve underachieving students’ academic performances, teachers need to reduce to strength of framing. Weak framing enables them to transform academic knowledge into commonsense knowledge in daily life language. This study posits that most teachers would deliver strong framing due to their belief mainly confined within the aspect of instrumental rationality that deprives their critical minds. This situation could make them view the normal distribution bell curve of students’ academic performances as a natural outcome. In order to examine the interplay between framing, instrumental rationality and pedagogical action, questionnaires were completed by over 5,000 primary school teachers in Henan province, China, who were stratified sample. The statistical results show that most teachers employed psychological concepts to measure students’ academic performances and, in turn, educational inequity was legitimatized as a natural outcome in the efficiency-led approach. Such efficiency-led minds made them perform as the agent practicing the mechanism of social control and in turn sustaining the phenomenon of cultural reproduction.

Keywords: code, cultural reproduction, framing, instrumental rationality, social relation and interaction

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Authors: Tzong-Ying Hao, Mohammad T. Rahmani

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This article presents the structural health monitoring (SHM) method based on changes in wave traveling times (wave method) within a layered 1-D shear beam model of structure. The wave method measures the velocity of shear wave propagating in a building from the impulse response functions (IRF) obtained from recorded data at different locations inside the building. If structural damage occurs in a structure, the velocity of wave propagation through it changes. The wave method analysis is performed on the responses of Torre Central building, a 9-story shear wall structure located in Santiago, Chile. Because events of different intensity (ambient vibrations, weak and strong earthquake motions) have been recorded at this building, therefore it can serve as a full-scale benchmark to validate the structural health monitoring method utilized. The analysis of inter-story drifts and the Fourier spectra for the EW and NS motions during 2010 Chile earthquake are presented. The results for the NS motions suggest the coupling of translation and torsion responses. The system frequencies (estimated from the relative displacement response of the 8th-floor with respect to the basement from recorded data) were detected initially decreasing approximately 24% in the EW motion. Near the end of shaking, an increase of about 17% was detected. These analysis and results serve as baseline indicators of the occurrence of structural damage. The detected changes in wave velocities of the shear beam model are consistent with the observed damage. However, the 1-D shear beam model is not sufficient to simulate the coupling of translation and torsion responses in the NS motion. The wave method is proven for actual implementation in structural health monitoring systems based on carefully assessing the resolution and accuracy of the model for its effectiveness on post-earthquake damage detection in buildings.

Keywords: Chile earthquake, damage detection, earthquake response, impulse response function, shear beam model, shear wave velocity, structural health monitoring, torre central building, wave method

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Authors: Moustafa Osman Mohammed

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This paper introduces topological order in descried social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. Topological order is important in describing the physical systems for exploiting optical systems and improving photonic devices. The stats of topological order have some interesting properties of topological degeneracy and fractional statistics that reveal the entanglement origin of topological order, etc. Topological ideas in photonics form exciting developments in solid-state materials, that being; insulating in the bulk, conducting electricity on their surface without dissipation or back-scattering, even in the presence of large impurities. A specific type of autopoiesis system is interrelated to the main categories amongst existing groups of the ecological phenomena interaction social and medical sciences. The hypothesis, nevertheless, has a nonlinear interaction with its natural environment 'interactional cycle' for exchange photon energy with molecules without changes in topology. The engineering topology of a biosensor is based on the excitation boundary of surface electromagnetic waves in photonic band gap multilayer films. The device operation is similar to surface Plasmonic biosensors in which a photonic band gap film replaces metal film as the medium when surface electromagnetic waves are excited. The use of photonic band gap film offers sharper surface wave resonance leading to the potential of greatly enhanced sensitivity. So, the properties of the photonic band gap material are engineered to operate a sensor at any wavelength and conduct a surface wave resonance that ranges up to 470 nm. The wavelength is not generally accessible with surface Plasmon sensing. Lastly, the photonic band gap films have robust mechanical functions that offer new substrates for surface chemistry to understand the molecular design structure and create sensing chips surface with different concentrations of DNA sequences in the solution to observe and track the surface mode resonance under the influences of processes that take place in the spectroscopic environment. These processes led to the development of several advanced analytical technologies: which are; automated, real-time, reliable, reproducible, and cost-effective. This results in faster and more accurate monitoring and detection of biomolecules on refractive index sensing, antibody-antigen reactions with a DNA or protein binding. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other in order to form unique spatial structure and dynamics of biological molecules for providing the environment mutual contribution in investigation of changes due to the pathogenic archival architecture of cell clusters.

Keywords: autopoiesis, photonics systems, quantum topology, molecular structure, biosensing

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Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

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Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

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Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: information retrieval, unified medical language system, syntax based analysis, natural language processing, medical informatics

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Authors: Kanchan Yadav, Ai-Chuan Chou, Rajesh Kumar Ulaganathan, Hua-De Gao, Hsien-Ming Lee, Chien-Yuan Pan, Yit-Tsong Chen

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Optogenetics is an innovative technology now widely adopted by researchers in different fields of the biological sciences. However, due to the weak tissue penetration capability of the short wavelengths used to activate light-sensitive proteins, an invasive light guide has been used in animal studies for photoexcitation of target tissues. Upconverting nanoparticles (UCNPs), which transform near-infrared (NIR) light to short-wavelength emissions, can help address this issue. To improve optogenetic performance, we enhance the target selectivity for optogenetic controls by specifically conjugating the UCNPs with light-sensitive proteins at a molecular level, which shortens the distance as well as enhances the efficiency of energy transfer. We tagged V5 and Lumio epitopes to the extracellular N-terminal of channelrhodopsin-2 with an mCherry conjugated at the intracellular C-terminal (VL-ChR2m) and then bound NeutrAvidin-functionalized UCNPs (NAv-UCNPs) to the VL-ChR2m via a biotinylated antibody against V5 (bV5-Ab). We observed an apparent energy transfer from the excited UCNP (donor) to the bound VL-ChR2m (receptor) by measuring emission-intensity changes at the donor-receptor complex. The successful patch-clamp electrophysiological test and an intracellular Ca2+ elevation observed in the designed UCNP-ChR2 system under optogenetic manipulation confirmed the practical employment of UCNP-assisted NIR-optogenetic functionality. This work represents a significant step toward improving therapeutic optogenetics.

Keywords: Channelrhodopsin-2, near infrared, optogenetics, upconverting nanoparticles

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Authors: Nonhlanhla Nkosi, Kulsum Kondiah

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The toxicological manifestation of heavy metals motivates interest towards the development of a reliable, eco-friendly biosorption process. With that being said, the aim of the current study was to characterise the EPS from heavy-metal resistant bacteria isolated from acid mine decant on the West Rand, Gauteng, South Africa. To achieve this, six exopolysaccharide (EPS) producing, metal resistant strains (Pb101, Pb102, Pb103, Pb204, Co101, and Ni101) were identified as Bacillus safensis strain NBRC 100820, Bacillus proteolyticus, Micrococcus luteus, Enterobacter sp. Pb204, Bacillus wiedmannii and Bacillus zhangzhouensis, respectively with 16S rRNA sequencing. Thereafter, EPS was extracted using chemical (formaldehyde/NaOH) and physical (ultrasonification) methods followed by physicochemical characterisation of carbohydrate, DNA, and protein contents using chemical assays and spectroscopy (FTIR- Fourier transformed infrared and 3DEEM- three-dimensional excitation-emission matrix fluorescence spectroscopy). EPS treated with formaldehyde/NaOH showed better recovery of macromolecules than ultrasonification. The results of the present study showed that carbohydrates were more abundant than proteins, with carbohydrate and protein concentrations of 8.00 mg/ml and 0.22 mg/ml using chemical method in contrast to 5.00 mg/ml and 0.77 mg/ml using physical method, respectively. The FTIR spectroscopy results revealed that the extracted EPS contained hydroxyl, amide, acyl, and carboxyl groups that corresponded to the aforementioned chemical analysis results, thus asserting the presence of carbohydrates, DNA, polysaccharides, and proteins in the EPS. These findings suggest that identified functional groups of EPS form surface charges, which serve as the binding sites for suspended particles, thus possibly mediating adsorption of divalent cations and heavy metals. Using the extracted EPS in the development of a cost-effective biosorption solution for industrial wastewater treatment is attainable.

Keywords: biosorbent, exopolysaccharides, heavy metals, wastewater treatment

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Authors: Juan-Gabriel Cegarra-Navarro, Alexeis Garcia-Perez, Denise Bedford

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This paper provides guidelines for what constitutes a knowledge worker. Many graduates from non-managerial domains adopt, at some point in their professional careers, management roles at different levels, ranging from team leaders through to executive leadership. This is particularly relevant for professionals from an engineering background. Moving from a technical to an executive-level requires an understanding of those behaviour management techniques that can motivate and support individuals and their performance. Further, the transition to management also demands a shift of contextual enablers from tangible to intangible resources, which allows individuals to create new capacities, competencies, and capabilities. In this dynamic process, the knowledge worker becomes that key individual who can help members of the management board to transform information into relevant knowledge. However, despite its relevance in shaping the future of the organization in its transition to the knowledge economy, the role of a knowledge worker has not yet been studied to an appropriate level in the current literature. In this study, the authors review both the contextual enablers and behaviour outputs related to the role of the knowledge worker and relate these to their ability to deal with everyday management issues such as knowledge heterogeneity, varying motivations, information overload, or outdated information. This study highlights that the aggregate of capacities, competences and capabilities (CCCs) can be defined as knowledge structures, the study proposes several contextual enablers and behaviour outputs that knowledge workers can use to work cooperatively, acquire, distribute and knowledge. Therefore, this study contributes to a better comprehension of how CCCs can be managed at different levels through their contextual enablers and behaviour outputs.

Keywords: knowledge workers, capabilities, capacities, competences, knowledge structures

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Authors: Amir Moslemi, Amir movafeghi, Shahab Moradi

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One of the most important challenging factors in medical images is nominated as noise.Image denoising refers to the improvement of a digital medical image that has been infected by Additive White Gaussian Noise (AWGN). The digital medical image or video can be affected by different types of noises. They are impulse noise, Poisson noise and AWGN. Computed tomography (CT) images are subjected to low quality due to the noise. The quality of CT images is dependent on the absorbed dose to patients directly in such a way that increase in absorbed radiation, consequently absorbed dose to patients (ADP), enhances the CT images quality. In this manner, noise reduction techniques on the purpose of images quality enhancement exposing no excess radiation to patients is one the challenging problems for CT images processing. In this work, noise reduction in CT images was performed using two different directional 2 dimensional (2D) transformations; i.e., Curvelet and Contourlet and Discrete wavelet transform(DWT) thresholding methods of BayesShrink and AdaptShrink, compared to each other and we proposed a new threshold in wavelet domain for not only noise reduction but also edge retaining, consequently the proposed method retains the modified coefficients significantly that result in good visual quality. Data evaluations were accomplished by using two criterions; namely, peak signal to noise ratio (PSNR) and Structure similarity (Ssim).

Keywords: computed tomography (CT), noise reduction, curve-let, contour-let, signal to noise peak-peak ratio (PSNR), structure similarity (Ssim), absorbed dose to patient (ADP)

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Authors: M. Yilmaz, I. Yilmaz, M. Uysal

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The Earth system generates different phenomena that are observable at the surface of the Earth such as mass deformations and displacements leading to plate tectonics, earthquakes, and volcanism. The dynamic processes associated with the interior, surface, and atmosphere of the Earth affect the three pillars of geodesy: shape of the Earth, its gravity field, and its rotation. Geodesy establishes a characteristic structure in order to define, monitor, and predict of the whole Earth system. The traditional and new instruments, observables, and techniques in geodesy are related to the gravity field. Therefore, the geodesy monitors the gravity field and its temporal variability in order to transform the geodetic observations made on the physical surface of the Earth into the geometrical surface in which positions are mathematically defined. In this paper, the main components of the gravity field modeling, (Free-air and Bouguer) gravity anomalies are calculated via recent global models (EGM2008, EIGEN6C4, and GECO) over a selected study area. The model-based gravity anomalies are compared with the corresponding terrestrial gravity data in terms of standard deviation (SD) and root mean square error (RMSE) for determining the best fit global model in the study area at a regional scale in Turkey. The least SD (13.63 mGal) and RMSE (15.71 mGal) were obtained by EGM2008 for the Free-air gravity anomaly residuals. For the Bouguer gravity anomaly residuals, EIGEN6C4 provides the least SD (8.05 mGal) and RMSE (8.12 mGal). The results indicated that EIGEN6C4 can be a useful tool for modeling the gravity field of the Earth over the study area.

Keywords: free-air gravity anomaly, Bouguer gravity anomaly, global model, land gravity

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Authors: Sanjivrao Katakam, Thanumoorthi I., Antony Gerald, Ratan Kulkarni, Shaju Nair

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With increasing energy costs and its impact on the business, sustainability today has evolved from a social expectation to an economic imperative. Therefore, finding methods to reduce cost has become a critical directive for Industry leaders. Effective energy management is the only way to cut costs. However, Energy Management has been a challenge because it requires a change in old habits and legacy systems followed for decades. Today exorbitant levels of energy and operational data is being captured and stored by Industries, but they are unable to convert these structured and unstructured data sets into meaningful business intelligence. It must be noted that for quick decisions, organizations must learn to cope with large volumes of operational data in different formats. Energy analytics not only helps in extracting inferences from these data sets, but also is instrumental in transformation from old approaches of energy management to new. This in turn assists in effective decision making for implementation. It is the requirement of organizations to have an established corporate strategy for reducing operational costs through visibility and optimization of energy usage. Energy analytics play a key role in optimization of operations. The paper describes how today energy data analytics is extensively used in different scenarios like reducing operational costs, predicting energy demands, optimizing network efficiency, asset maintenance, improving customer insights and device data insights. The paper also highlights how analytics helps transform insights obtained from energy data into sustainable solutions. The paper utilizes data from an array of segments such as retail, transportation, and water sectors.

Keywords: energy analytics, energy management, operational data, business intelligence, optimization

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The interpretation of medical images benefits from anatomical and physiological priors to optimize computer- aided diagnosis applications. Segmentation of liver and liver lesion is regarded as a major primary step in computer aided diagnosis of liver diseases. Precise liver segmentation in abdominal CT images is one of the most important steps for the computer-aided diagnosis of liver pathology. In this papers, a semi- automated method for medical image data is presented for the liver and liver lesion segmentation data using mathematical morphology. Our algorithm is currency in two parts. In the first, we seek to determine the region of interest by applying the morphological filters to extract the liver. The second step consists to detect the liver lesion. In this task; we proposed a new method developed for the semi-automatic segmentation of the liver and hepatic lesions. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to improve the quality of the original image and image gradient by applying the spatial filter followed by the morphological filters. The second step consists to calculate the internal and external markers of the liver and hepatic lesions. Thereafter we proceed to the liver and hepatic lesions segmentation by the watershed transform controlled by markers. The validation of the developed algorithm is done using several images. Obtained results show the good performances of our proposed algorithm

Keywords: anisotropic diffusion filter, CT images, hepatic lesion segmentation, Liver segmentation, morphological filter, the watershed algorithm

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Authors: M. McHugh, D. Lillis

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Mobile applications are being used to perform a wide variety of tasks in day-to-day life, ranging from checking email to controlling your home heating. Application developers have recognized the potential to transform a smart device into a medical device, by using a mobile medical application i.e. a mobile phone or a tablet. When initially conceived these mobile medical applications performed basic functions e.g. BMI calculator, accessing reference material etc.; however, increasing complexity offers clinicians and patients a range of functionality. As this complexity and functionality increases, so too does the potential risk associated with using such an application. Examples include any applications that provide the ability to inflate and deflate blood pressure cuffs, as well as applications that use patient-specific parameters and calculate dosage or create a dosage plan for radiation therapy. If an unapproved mobile medical application is marketed by a medical device organization, then they face significant penalties such as receiving an FDA warning letter to cease the prohibited activity, fines and possibility of facing a criminal conviction. Regulatory bodies have finalized guidance intended for mobile application developers to establish if their applications are subject to regulatory scrutiny. However, regulatory controls appear contradictory with the approaches taken by mobile application developers who generally work with short development cycles and very little documentation and as such, there is the potential to stifle further improvements due to these regulations. The research presented as part of this paper details how by adopting development techniques, such as agile software development, mobile medical application developers can meet regulatory requirements whilst still fostering innovation.

Keywords: agile, applications, FDA, medical, mobile, regulations, software engineering, standards

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Authors: S. Naderizadeh, A. Athanassiou, I. S. Bayer

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This work describes a layer-by-layer spraying method to produce a non-wetting coating, based on thermoplastic polyurethane (TPU) and silica nanoparticles (Si-NPs). The main purpose of this work was to transform a hydrophilic polymer to superhydrophobic coating. The contact angle of pure TPU was measured about 77˚ ± 2, and water droplets did not roll away upon tilting even at 90°. But after applying a layer of Si-NPs on top of this, not only the contact angle increased to 165˚ ± 2, but also water droplets can roll away even below 5˚ tilting. The most important restriction in this study was the weak interfacial adhesion between polymer and nanoparticles, which had a bad effect on durability of the coatings. To overcome this problem, we used a very thin layer of graphene nanoplatelets (GNPs) as an interlayer between TPU and Si-NPs layers, followed by thermal treatment at 150˚C. The sample’s morphology and topography were characterized by scanning electron microscopy (SEM), EDX analysis and atomic force microscopy (AFM). It was observed that Si-NPs embedded into the polymer phase in the presence of GNPs layer. It is probably because of the high surface area and considerable thermal conductivity of the graphene platelets. The contact angle value for the sample containing graphene decreased a little bit respected to the coating without graphene and reached to 156.4˚ ± 2, due to the depletion of the surface roughness. The durability of the coatings against abrasion was evaluated by Taber® abrasion test, and it was observed that superhydrophobicity of the coatings remains for a longer time, in the presence of GNPs layer. Due to the simple fabrication method and good durability of the coating, this coating can be used as a durable superhydrophobic coating for metals and can be produced in large scale.

Keywords: graphene, silica nanoparticles, superhydrophobicity, thermoplastic polyurethane

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Authors: Ya-Hsuan Wang

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This project of intercultural education aimed to explore pluricultural people’s interpretation and evaluation of the transnational community in Taiwan. Based on transnationalism and transculturalism, this study concerns the human right issues for immigrants and pluricultural people. Research participants as immigrants in Taiwan were asked about their typical thinking styles in the transnational community, their cultural integration in terms of transnational behaviors, and their collective memory of the transnational community. Interview questions included what key factors were involved in their identity negotiation, what roles the transnational community and collective memory would be for their identity negotiation and what were the positive or negative aspects impacting cross-border identity. Based on the experiences of pluricultural people and transnational communities, this project expected to enhance the depth and width of developing transcultural knowledge in textbook reform on History in K-12 schools. It is to transform cross-border identity into knowledge embedded with local culture in response to globalization and localization. The purpose of this paper is to portrait the cross-cultural practice of transnational community for Taiwan’s immigrants. It is to report their external socio-cultural expectation of ethnic economics, to understand their internal life course of national identity, and to clarify transnational community in relation to their cross-border identity. In conclusion, the cross-cultural practice of transnational community combined the external contexts such as ethnic economic interaction among transnational communities, social report and ethnic industry, and the internal contexts such as ethnic identity, language use, and collective memory in ethnic history.

Keywords: cross-cultural practice, immigrants, pluricultural people, transnational community

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Authors: Olivier Delage, Hassan Bencherif, Alain Bourdier

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Signal decomposition approaches represent an important step in time series analysis, providing useful knowledge and insight into the data and underlying dynamics characteristics while also facilitating tasks such as noise removal and feature extraction. As most of observational time series are nonlinear and nonstationary, resulting of several physical processes interaction at different time scales, experimental time series have fluctuations at all time scales and requires the development of specific signal decomposition techniques. Most commonly used techniques are data driven, enabling to obtain well-behaved signal components without making any prior-assumptions on input data. Among the most popular time series decomposition techniques, most cited in the literature, are the empirical mode decomposition and its variants, the empirical wavelet transform and singular spectrum analysis. With increasing popularity and utility of these methods in wide ranging applications, it is imperative to gain a good understanding and insight into the operation of these algorithms. In this work, we describe all of the techniques mentioned above as well as their ability to denoise signals, to capture trends, to identify components corresponding to the physical processes involved in the evolution of the observed system and deduce the dimensionality of the underlying dynamics. Results obtained with all of these methods on experimental total ozone columns and rainfall time series will be discussed and compared

Keywords: denoising, empirical mode decomposition, singular spectrum analysis, time series, underlying dynamics, wavelet analysis

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Authors: I-Hui Hsieh, Yu-Hsuan Hu

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The powerful effect of music is often associated with changes in physiological responses such as heart rate and respiration. Previous studies demonstrate that Mayer waves of blood pressure, the spontaneous rhythm occurring at 0.1 Hz, corresponds to a progressive crescendo of the musical phrase. However, music contain dynamic changes in temporal and spectral features. As such, it remains unclear which aspects of musical structures optimally affect synchronization of cardiovascular rhythms. This study investigates the independent contribution of spectral pattern, temporal pattern, and dissonance level on synchronization of cardiovascular rhythms. The regularity of acoustical patterns occurring at a periodic rhythm of 0.1 Hz is hypothesized to elicit the strongest coherence of cardiovascular rhythms. Music excerpts taken from twelve pieces of Western classical repertoire were modulated to contain varying degrees of pattern regularity of the acoustic envelope structure. Three levels of dissonance were manipulated by varying the harmonic structure of the accompanying chords. Electrocardiogram and photoplethysmography signals were recorded for 5 minutes of baseline and simultaneously while participants listen to music excerpts randomly presented over headphones in a sitting position. Participants were asked to indicate the pleasantness of each music excerpt by adjusting via a slider presented on screen. Analysis of the Fourier spectral power of blood pressure around 0.1 Hz showed a significant difference between music excerpts characterized by spectral and temporal pattern regularity compared to the same content in random pattern. Phase coherence between heart rate and blood pressure increased significantly during listening to spectrally-regular phrases compared to its matched control phrases. The degree of dissonance of the accompanying chord sequence correlated with level of coherence between heart rate and blood pressure. Results suggest that low-level auditory features of music can entrain coherence of autonomic physiological variables. These findings have potential implications for using music as a clinical and therapeutic intervention for regulating cardiovascular functions.

Keywords: cardiovascular rhythms, coherence, dissonance, pattern regularity

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Authors: Syed Jawad Hussain Shahzad, Muhammad Zakaria, Mobeen Ur Rehman, Saniya Khaild

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This study examines the co-movement between the Pakistan, Indian, S&P 500 and Nikkei 225 stock markets using weekly data from 1998 to 2013. The time-frequency relationship between the selected stock markets is conducted by using measures of continuous wavelet power spectrum, cross-wavelet transform and cross (squared) wavelet coherency. The empirical evidence suggests strong dependence between Pakistan and Indian stock markets. The co-movement of Pakistani index with U.S and Japanese, the developed markets, varies over time and frequency where the long-run relationship is dominant. The results of cross wavelet and wavelet coherence analysis indicate moderate covariance and correlation between stock indexes and the markets are in phase (i.e. cyclical in nature) over varying durations. Pakistan stock market was lagging during the entire period in relation to Indian stock market, corresponding to the 8~32 and then 64~256 weeks scale. Similar findings are evident for S&P 500 and Nikkei 225 indexes, however, the relationship occurs during the later period of study. All three wavelet indicators suggest strong evidence of higher co-movement during 2008-09 global financial crises. The empirical analysis reveals a strong evidence that the portfolio diversification benefits vary across frequencies and time. This analysis is unique and have several practical implications for regional and international investors while assigning the optimal weightage of different assets in portfolio formulation.

Keywords: co-movement, Pakistan stock exchange, S&P 500, Nikkei 225, wavelet analysis

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Authors: Sudhaveni Naresh

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International migration is an important subject and gaining more significance andinterest among scholars in recent years. It is defined as crossing of the boundaries of political or administrative units for a certain minimum period for reasons such as education, employment, etc.International migration is not new for India because it has a long history with the Gulf region since ancient period. India is also one of the largest migrant-sending countries after China in the world. Migration towards the Gulf region became more prominent during early 1970s due to oil boom which led to rapid increase in the demand for foreign labour. Of 25 million Indian emigrants are living across the world, about six million Indian emigrants working in the Gulf. Most of these migrants were either unskilled or semi-skilled. Both the pull and push factors behind labour emigrate to Gulf countries. India is world’s leading receiver of remittances and the flow of remittances to India has been increasing steadily since the 1970s. In 2011-12, it was about 4 percent of GDP.Emigrants play a significant role in the economic development and growth of the country via the remittances and knowledge and skill transfer. Scholars see remittances as vital tool in the development for origin country. This paper examines the recent trend and pattern of migration from India to Gulf countries and explores impact of remittances on emigrants’ families at home country. It also highlights opportunities, challenges and the need for strengthening multilateral cooperation to transform migration into an efficient, orderly and humane process.The study propose to undertake a primary survey for this purpose. Both quantitative and qualitative research methods will be used to study the above issues.

Keywords: development, international migration, remittances, unskilled labour

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Authors: Cory A. Logston

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It is imperative researchers continue to explore every transformative strategy to increase empathy and awareness of racial bias. Racism is a social and political concept that uses stereotypical ideology to highlight racial inequities. Everyone has biases they may not be aware of toward disparate out-groups. There is some form of racism in every profession; doctors, lawyers, and teachers are not immune. There have been numerous successful and unsuccessful strategies to motivate and transform an individual’s unconscious biased attitudes. One method designed to induce a transformative experience and identify implicit bias is virtual reality (VR). VR is a technology designed to transport the user to a three-dimensional environment. In a virtual reality simulation, the viewer is immersed in a realistic interactive video taking on the perspective of a Black man. The viewer as the character experiences discrimination in various life circumstances growing up as a child into adulthood. For instance, the prejudice felt in school, as an adolescent encountering the police and false accusations in the workplace. Current research suggests that an immersive VR simulation can enhance self-awareness and become a transformative learning experience. This study uses virtual reality immersion and transformative learning theory to create empathy and identify any unintentional racial bias. Participants, White teachers, will experience a VR immersion to create awareness and identify implicit biases regarding Black students. The desired outcome provides a springboard to reconceptualize their own implicit bias. Virtual reality is gaining traction in the research world and promises to be an effective tool in the transformative learning process.

Keywords: empathy, implicit bias, transformative learning, virtual reality

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Authors: Raj Banerjee, Aniruddha Sengupta

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An earthquake event, associated with a typical fault rupture, initiates at the source, propagates through a rock or soil medium and finally daylights at a surface which might be a populous city. The detrimental effects of an earthquake are often quantified in terms of the responses of superstructures resting on the soil. Hence, there is a need for the estimation of amplification of the bedrock motions due to the influence of local site conditions. In the present study, field borehole log data of Mangalwadi and Walkeswar sites in Mumbai city are considered. The data consists of variation of SPT N-value with the depth of soil. A correlation between shear wave velocity (Vₛ) and SPT N value for various soil profiles of Mumbai city has been developed using various existing correlations which is used further for site response analysis. MATLAB program is developed for studying the ground response analysis by performing two dimensional linear and equivalent linear analysis for some of the typical Mumbai soil sites using pure shear (Multi Point Constraint) boundary condition. The model is validated in linear elastic and equivalent linear domain using the popular commercial program, DEEPSOIL. Three actual earthquake motions are selected based on their frequency contents and durations and scaled to a PGA of 0.16g for the present ground response analyses. The results are presented in terms of peak acceleration time history with depth, peak shear strain time history with depth, Fourier amplitude versus frequency, response spectrum at the surface etc. The peak ground acceleration amplification factors are found to be about 2.374, 3.239 and 2.4245 for Mangalwadi site and 3.42, 3.39, 3.83 for Walkeswar site using 1979 Imperial Valley Earthquake, 1989 Loma Gilroy Earthquake and 1987 Whitter Narrows Earthquake, respectively. In the absence of any site-specific response spectrum for the chosen sites in Mumbai, the generated spectrum at the surface may be utilized for the design of any superstructure at these locations.

Keywords: deepsoil, ground response analysis, multi point constraint, response spectrum

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Authors: Xiaogang Li, Jieqiong Miao

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As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines．For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

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Authors: Imen Amari, Kaouther Gasmi, Asma Rebaya, Salem Hasnaoui

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The problem of scheduling and mapping data flow applications on multi-core architectures is notoriously difficult. This difficulty is related to the rapid evaluation of Telecommunication and multimedia systems accompanied by a rapid increase of user requirements in terms of latency, execution time, consumption, energy, etc. Having an optimal scheduling on multi-cores DSP (Digital signal Processors) platforms is a challenging task. In this context, we present a novel technic and algorithm in order to find a valid schedule that optimizes the key performance metrics particularly the Latency. Our contribution is based on Satisfiability Modulo Theories (SMT) solving technologies which is strongly driven by the industrial applications and needs. This paper, describe a scheduling module integrated in our proposed Workflow which is advised to be a successful approach for programming the applications based on NoC-DSP platforms. This workflow transform automatically a Simulink model to a synchronous dataflow (SDF) model. The automatic transformation followed by SMT solver scheduling aim to minimize the final latency and other software/hardware metrics in terms of an optimal schedule. Also, finding the optimal numbers of cores to be used. In fact, our proposed workflow taking as entry point a Simulink file (.mdl or .slx) derived from embedded Matlab functions. We use an approach which is based on the synchronous and hierarchical behavior of both Simulink and SDF. Whence, results of running the scheduler which exist in the Workflow mentioned above using our proposed SMT solver algorithm refinements produce the best possible scheduling in terms of latency and numbers of cores.

Keywords: multi-cores DSP, scheduling, SMT solver, workflow

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Authors: Walid Tawfik

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The interaction of high intensity ultrashort laser pulses with plasma generates many significant applications, including soft x-ray lasers, time-resolved laser induced plasma spectroscopy LIPS, and laser-driven accelerators. The development in producing of femtosecond down to ten femtosecond optical pulses has facilitates scientists with a vital tool in a variety of ultrashort phenomena, such as high field physics, femtochemistry and high harmonic generation HHG. In this research, we generate a two-octave-wide ultrashort supercontinuum pulses with an optical spectrum extending from 3.5 eV (ultraviolet) to 1.3 eV (near-infrared) using a capillary fiber filled with neon gas. These pulses are formed according to nonlinear self-phase modulation in the neon gas as a nonlinear medium. The investigations of the created pulses were made using spectral phase interferometry for direct electric-field reconstruction (SPIDER). A complete description of the output pulses was considered. The observed characterization of the produced pulses includes the beam profile, the pulse width, and the spectral bandwidth. After reaching optimization conditions, the intensity of the reconstructed pulse autocorrelation function was applied for the shorts pulse duration to achieve transform limited ultrashort pulses with durations below 6-fs energies up to 600μJ. Moreover, the effect of neon pressure variation on the pulse width was examined. The nonlinear self-phase modulation realized to be increased with the pressure of the neon gas. The observed results may lead to an advanced method to control and monitor ultrashort transit interaction in femtochemistry.

Keywords: supercontinuum, ultrafast, SPIDER, ultra-broadband

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Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

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Authors: Yeimis Milton, Palomino Pichihua

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The city, like living organisms, originates from codes, structured information in the form of rules that condition the physical form and performance of urban space. Usually, the so-called urban codes clash with the spontaneous nature of the city, with the urban Kháos that contextualizes the free creation (poiesis) of human collectives. This contradiction is especially evident in Latin America, which, like other developing regions, lacks adequate instruments to guide urban growth. Thus constructing a hybrid between the formal and informal city, categories that are difficult to separate one from the other. This is a comparative study focusing on the urban codes created to address the pandemic. The objective is to build an overview of these innovations in the region. The sample is made up of official norms published in pandemic, directly linked to urban planning and building control (urban form). The countries analyzed are Brazil, Mexico, Argentina, Peru, Colombia, and Chile. The study uncovers a shared interest in facing future urban problems, in contrast to the inconsistency of proposed legal instruments. Factors such as the lack of articulation, validity time, and ambiguity, among others, accentuate this problem. Likewise, it evidences that the political situation of each country has a significant influence on the development of these norms and the possibility of their long-term impact. In summary, the global emergency has produced opportunities to transform urban systems from their internal rules; however, there are very few successful examples in this field. Therefore, Latin American cities have the task of learning from this defeat in order to lay the foundations for a more resilient and sustainable urban future.

Keywords: pandemic, regulation, urban planning, latin America

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Authors: M. A. Alqahtani, D. P. Coleman, N. D. Pugh, L. D. M. Nokes

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In diagnostic ultrasound, the echo graphic B-scan texture is an important area of investigation since it can be analyzed to characterize the histological state of internal tissues. An important factor requiring consideration when evaluating ultrasonic tissue texture is the depth. The effect of attenuation with depth of ultrasound, the size of the region of interest, gain, and dynamic range are important variables to consider as they can influence the analysis of texture features. These sources of variability have to be considered carefully when evaluating image texture as different settings might influence the resultant image. The aim of this study is to investigate the effect of depth on the texture features in-vivo using a 3D ultrasound probe. The left leg medial head of the gastrocnemius muscle of 10 healthy subjects were scanned. Two regions A and B were defined at different depth within the gastrocnemius muscle boundary. The size of both ROI’s was 280*20 pixels and the distance between region A and B was kept constant at 5 mm. Texture parameters include gray level, variance, skewness, kurtosis, co-occurrence matrix; run length matrix, gradient, autoregressive (AR) model and wavelet transform were extracted from the images. The paired t –test was used to test the depth effect for the normally distributed data and the Wilcoxon–Mann-Whitney test was used for the non-normally distributed data. The gray level, variance, and run length matrix were significantly lowered when the depth increased. The other texture parameters showed similar values at different depth. All the texture parameters showed no significant difference between depths A and B (p > 0.05) except for gray level, variance and run length matrix (p < 0.05). This indicates that gray level, variance, and run length matrix are depth dependent.

Keywords: ultrasound image, texture parameters, computational biology, biomedical engineering

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Authors: Anthoni Jeorge

Abstract:

Throughout the history of the world, servant leadership has been researched, and favourable results such as individual, team, and organizational have been linked to the construct. This research paper designates St. Camillus de Lellis, a practitioner of servant leadership and founder of the Ministers of the Sick as a servant leader in his approach to care for the sick. Service is the visible face of his servant leadership. First of all, despite many challenges, St. Camillus de Lellis practiced leadership by the example of compassionate service to the sick. Second, he made service to the sick the highest priority of his life. Third, Camillus displayed servant leadership such that his manner of leadership gave birth to a New School of Service to the Sick. The paper identifies the distinctive dimensions and essential elements which characterized his service-centered leadership. Furthermore, discuss the six major characteristics of a servant leader as set forth by St. Camillus’s life example. The research illustrates the transformational power of servant leadership infield healthcare in general and, in doing so, provides servant leadership seekers ways servant leadership can transform elder care in one’s own field (St. Camillus Health Systems). Thus, it ascertains that servant leadership is best-fit for humanized elder care. Supported by the review of literature, the paper ascertains that Camillus, by identifying himself with the sick, gained deeper insights concerning the pain and suffering of the population. Uniquely drawn from his true grit, Camillus’ service-centered leadership is value-based, people-oriented, and compassion-filled. His way of service to the sick is the prolongation of gestures of mercy and compassion. It is hoped that the results of this study will help health care workers and servant leadership practitioners to humanize elder care and cultivate servant leadership attitude in their health care services to the sick. By incorporating such service-oriented elements into their leadership orientation, health care workers will be true servant leaders of the sick.

Keywords: leadership, service, healthcare, compassion

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Authors: Samim Khair Mohammad, Takeshi Tsuji, Chanmaly Chhun

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The Afghan Tajik (foreland) basin, located in the depression zone between mountain axes, is under compression and deformation during the collision of India with the Eurasian plate. The southern part of the Afghan Tajik basin in the Northern part of Afghanistan has not been well studied and explored, but considered for the significant potential for oil and gas resources. The Afghan Tajik basin depositional environments (< 8km) resulted from mixing terrestrial and marine systems, which has potential prospects of Jurrasic (deep) and Tertiary (shallow) petroleum systems. We used 2D regional seismic profiles with a total length of 674.8 km (or over an area of 2500 km²) in the southern part of the basin. To characterize hydrocarbon systems and structures in this study area, we applied advanced seismic attributes such as spectral decomposition (10 - 60Hz) based on time-frequency analysis with continuous wavelet transform. The spectral decomposition results yield the (averaging 20 - 30Hz group) spectral amplitude anomaly. Based on this anomaly result, seismic, and structural interpretation, the potential hydrocarbon accumulations were inferred around the main thrust folds in the tertiary (Paleogene+Neogene) petroleum systems, which appeared to be accumulated around the central study area. Furthermore, it seems that hydrocarbons dominantly migrated along the main thrusts and then concentrated around anticline fold systems which could be sealed by mudstone/carbonate rocks.

Keywords: The Afghan Tajik basin, seismic lines, spectral decomposition, thrust folds, hydrocarbon reservoirs

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