Search results for: single and multi-objective function

Authors: Dewi Retno Sari Saputro, Purnami Widyaningsih, Hendrika Handayani

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Extreme data on an observation can occur due to unusual circumstances in the observation. The data can provide important information that can’t be provided by other data so that its existence needs to be further investigated. The method for obtaining extreme data is one of them using maxima block method. The distribution of extreme data sets taken with the maxima block method is called the distribution of extreme values. Distribution of extreme values is Gumbel distribution with two parameters. The parameter estimation of Gumbel distribution with maximum likelihood method (ML) is difficult to determine its exact value so that it is necessary to solve the approach. The purpose of this study was to determine the parameter estimation of Gumbel distribution with quasi-Newton BFGS method. The quasi-Newton BFGS method is a numerical method used for nonlinear function optimization without constraint so that the method can be used for parameter estimation from Gumbel distribution whose distribution function is in the form of exponential doubel function. The quasi-New BFGS method is a development of the Newton method. The Newton method uses the second derivative to calculate the parameter value changes on each iteration. Newton's method is then modified with the addition of a step length to provide a guarantee of convergence when the second derivative requires complex calculations. In the quasi-Newton BFGS method, Newton's method is modified by updating both derivatives on each iteration. The parameter estimation of the Gumbel distribution by a numerical approach using the quasi-Newton BFGS method is done by calculating the parameter values that make the distribution function maximum. In this method, we need gradient vector and hessian matrix. This research is a theory research and application by studying several journals and textbooks. The results of this study obtained the quasi-Newton BFGS algorithm and estimation of Gumbel distribution parameters. The estimation method is then applied to daily rainfall data in Purworejo District to estimate the distribution parameters. This indicates that the high rainfall that occurred in Purworejo District decreased its intensity and the range of rainfall that occurred decreased.

Keywords: parameter estimation, Gumbel distribution, maximum likelihood, broyden fletcher goldfarb shanno (BFGS)quasi newton

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Authors: Selvia Arokiya Mary

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Introduction: Worldwide, breast cancer comprises 10.4% of all cancer incidence among women. In 2004, breast cancer caused 519,000 deaths worldwide (7% of cancer deaths; almost 1% of all deaths). Many women who undergo breast surgery suffer from ill-defined pain syndromes. STATEMENT OF THE PROBLEM: A study to assess the effectiveness of twin therapeutic approaches on certain bio-physiological parameters in breast cancer patients after breast surgery at selected hospital, Chennai. Objectives: This study is to 1. assess the level of certain biophysiological parameters in women after mastectomy. 2. assess the effectiveness of twin therapeutic approaches on certain biophysiological parameters in women after mastectomy. 3. correlate the practice of twin therapeutic approaches with certain biophysiological parameters. 4. associate the selected demographic variables with certain biophysiological parameters in women after mastectomy Research Design and Method: Pre experimental research design was used. Fifty women were selected by using convenient sampling technique at government general hospital, Chennai. Results: The Level of pain shows, in the study group 49(98%) of them had moderate in the pre test and after the intervention all of them had mild pain in the post test. In relation to level of shoulder function before the intervention shows that in the study group 49(98%) of them had movement towards gravity and after intervention 24 (48%) of them had movement against gravity maximum resistance. There was a significant reduction in pain and shoulder stiffness level at a ‘P’ level of < 0.001. There was a negative correlation between the pranayama practice and the level of pain, there was a positive correlation between the arm exercise practice and the level of shoulder function. There was no significant association between demographic and clinical variables with the level of pain and shoulder function in the study. Hypothesis: There is a significant difference in level of pain and shoulder function among women following breast surgery who receive pranayama & arm exercise programme. The pranayama had effect in terms of reduction of pain, arm exercise programme had effect in prevention of arm stiffness among post operative women following breast surgery. Thus the stated hypothesis was accepted. Conclusion: On the basis of the findings of the present study there was Advancing age related to increasing risk of breast cancer, level of pain also the type of surgery was associated with level of pain and shoulder function, There fore it is to be concluded that the study participants may get benefited by practice of pranayama and arm exercise program.

Keywords: biophysiological parameters breast surgery, lumpectomy , mastectomy, radical mastectomy, twin therapeutic approach, pranayama, arm exercise

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Authors: Zhang Yuqi

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Service facilities are the boosters for the cultivation and development of innovative functions in innovative cluster areas. At the same time, reasonable service facilities planning can better link the internal functional blocks. This paper takes Zhejiang University Zijin Co-Maker Town as the research object, based on the combination of network data mining and field research and verification, combined with the needs of its internal innovative groups. It studies the distribution characteristics and existing problems of service facilities and then proposes a targeted planning suggestion. The main conclusions are as follows: (1) From the perspective of view, the town is rich in general life-supporting services, but lacking of provision targeted and distinctive service facilities for innovative groups; (2) From the perspective of scale structure, small-scale street shops are the main business form, lack of large-scale service center; (3) From the perspective of spatial structure, service facilities layout of each functional block is too fragile to fit the characteristics of 2aggregation- distribution' of innovation and entrepreneurial activities; (4) The goal of optimizing service facilities planning should be guided for fostering function of innovation and entrepreneurship and meet the actual needs of the innovation and entrepreneurial groups.

Keywords: the cultivation of innovative function, Zhejiang University Zijin Co-Maker Town, service facilities, network data mining, space optimization advice

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Authors: Thinh Ngo, Paul Rad, Brian Kelley

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Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: classification, CNN, deep learning, prediction, SNR

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Authors: Yi Jen Wang, Yu Ju Chen

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Background: Heart rate variability (HRV) biofeedback can promote autonomic nervous function, sleep quality and reduce psychological stress. In HRV biofeedback training, it is hoped that through the guidance of machine video or audio, the patient can breathe slowly according to his own heart rate changes so that the heart and lungs can achieve resonance, thereby promoting the related effects of autonomic nerve function; while, it is also pointed out that if slow breathing of 6 times per minute can also guide the case to achieve the effect of cardiopulmonary resonance. However, there is no relevant research to explore the comparison of the effectiveness of cardiopulmonary resonance by using video or audio HRV biofeedback training and metronome-guided slow breathing. Purpose: To compare the promotion of autonomic nervous function performance between using HRV biofeedback and slow breathing guided by a metronome. Method: This research is a kind of experimental design with convenient sampling; the cases are randomly divided into the heart rate variability biofeedback training group and the slow breathing training group. The HRV biofeedback training group will conduct HRV biofeedback training in a four-week laboratory and use the home training device for autonomous training; while the slow breathing training group will conduct slow breathing training in the four-week laboratory using the mobile phone APP breathing metronome to guide the slow breathing training, and use the mobile phone APP for autonomous training at home. After two groups were enrolled and four weeks after the intervention, the autonomic nervous function-related performance was repeatedly measured. Using the chi-square test, student’s t-test and other statistical methods to analyze the results, and use p <0.05 as the basis for statistical significance. Results: A total of 27 subjects were included in the analysis. After four weeks of training, the HRV biofeedback training group showed significant improvement in the HRV indexes (SDNN, RMSSD, HF, TP) and sleep quality. Although the stress index also decreased, it did not reach statistical significance; the slow breathing training group was not statistically significant after four weeks of training, only sleep quality improved significantly, while the HRV indexes (SDNN, RMSSD, TP) all increased. Although HF and stress indexes decreased, they were not statistically significant. Comparing the difference between the two groups after training, it was found that the HF index improved significantly and reached statistical significance in the HRV biofeedback training group. Although the sleep quality of the two groups improved, it did not reach that level in a statistically significant difference. Conclusion: HRV biofeedback training is more effective in promoting autonomic nervous function than slow breathing training, but the effects of reducing stress and promoting sleep quality need to be explored after increasing the number of samples. The results of this study can provide a reference for clinical or community health promotion. In the future, it can also be further designed to integrate heart rate variability biological feedback training into the development of AI artificial intelligence wearable devices, which can make it more convenient for people to train independently and get effective feedback in time.

Keywords: autonomic nervous function, HRV biofeedback, heart rate variability, slow breathing

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Authors: Digby Wrede, Stephen Gray, Syed Hussainy

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Microalgae are extremely useful organisms but notoriously hard to harvest. The use of fungal pellets has been found to be an efficient way to flocculate numerous species of algae. However, only the flocculation of single species of algae has been investigated. Algae are generally found in complex communities in the environment comprising of numerous species of algae ranging from simple single cell algae such as Chlorella to more complex or communal algae such as Dictyosphaerium. This study investigated the flocculation capabilities of Aspergillus oryzae to flocculate four species of algae; Chlorella vulgaris, Scenedesmus quadricauda, Scenedesmus acuminatus and Dictyosphaerium sp., and the algal communities in four different types of domestic effluent from a lagoon-based treatment plant; primary effluent, secondary effluent and the high rate algal pond effluent at a natural and at a lowered pH level. Spectrophotometry was used to measure the changes in algal population. C. vulgaris, S. acuminatus and S. quadricauda, had over 90% reduction of algal in suspension after 24 hours. Dictyosphaerium sp. showed a little to no removal after 24 hours. The primary, secondary, and natural pH level HRAP had roughly a 50% removal after 24 hours, the HRAP which was grown at a lower pH level had over a 90% removal after 24 hours. pH has been shown previously to affect fungal flocculation. Fungal and algae pellets have been shown to be able to treat wastewater and can be converted to biofuels in a very similar method to how algae are currently converted. The mixture of both fungi and algae has also been shown to provide a higher yield of oils then separately and are able to more efficiently treat wastewater then algae or fungi by themselves.

Keywords: algae harvesting, Aspergillus oryzae, fungal flocculation, wastewater treatment

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-alaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-nearest neighbors algorithm, radial basis function neural network, red blood cells, support vector machine

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm

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Authors: Bo Wang

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The geometric processing of multi-source remote sensing data using control data of different scale and different accuracy is an important research direction of multi-platform system for earth observation. In the existing block bundle adjustment methods, as the controlling information in the adjustment system, the approach using single observation scale and precision is unable to screen out the control information and to give reasonable and effective corresponding weights, which reduces the convergence and adjustment reliability of the results. Referring to the relevant theory and technology of quotient space, in this project, several subjects are researched. Multi-layer quotient space of multi-geometric features is constructed to describe and filter control data. Normalized granularity merging mechanism of multi-layer control information is studied and based on the normalized scale factor, the strategy to optimize the weight selection of control data which is less relevant to the adjustment system can be realized. At the same time, geometric positioning experiment is conducted using multi-source remote sensing data, aerial images, and multiclass control data to verify the theoretical research results. This research is expected to break through the cliché of the single scale and single accuracy control data in the adjustment process and expand the theory and technology of photogrammetry. Thus the problem to process multi-source remote sensing data will be solved both theoretically and practically.

Keywords: multi-source image geometric process, high precision geometric positioning, quotient space of multi-geometric features, optimized weight selection

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Authors: Jie Yin, Jun Zhang

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Measuring the growth performance and critical supersaturation of particle group have a high reference value for constructing a supersaturated water vapor environment that can improve the removal efficiency of the high-concentration particle group. The critical supersaturation and the variation of the growth performance with supersaturation for high-concentration particles were measured by a flow cloud chamber. Findings suggest that the influence of particle concentration on the growth performance will reduce with the increase of supersaturation. Reducing residence time and increasing particle concentration have similar effects on the growth performance of the high-concentration particle group. Increasing particle concentration and shortening residence time will increase the critical supersaturation of the particle group. The critical supersaturation required to activate a high-concentration particle group is lower than that of the single-particle when the minimum particle size in the particle group is the same as that of a single particle.

Keywords: sub-micron particles, heterogeneous condensation, critical supersaturation, nucleation

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Authors: Awais Ahmad, Mudssar Ali

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Berseem is the major fodder crop grown in Pakistan and is highly preferred by cattle farmers due to its multicut nature and nutritious value. The quality seed production in berseem is largely dependent upon the activities of insect pollinators, particularly bees. In order to determine the effectiveness of native bee species in quality seed production of berseem, an experiment was conducted in the research field of MNS-University of Agriculture, Multan, Pakistan. The pollinator community of berseem was composed of four bees, three syrphid fly, and two butterfly species. Pesudapis sp. was the most abundant insect visitor, followed by Apis mellifera and A. dorsata. The visitation rate of A. mellifera was found highest, followed by Pesudapis sp. and A. dorsata. Moreover, single-visit efficacy in terms of seed per head and 1000 seed weight proved A. mellifera and Pesudapis sp as the most effective pollinators. Conserving these bee species may lead to sustainable berseem seed production in Pakistan.

Keywords: honey bees, syrphid fly, visitation rate, single visit

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Authors: M. Asato, C. Liu, N. Fujima, T. Hoshino, Y. Chen, T. Mohri

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We study the temperature dependence of the interaction energies (IEs) of X (=Ru, Rh) impurities in Pd, due to the Fermi-Dirac (FD) distribution and the thermal vibration effect by the Debye-Grüneisen model. The n-body (n=2~4) IEs among X impurities in Pd, being used to calculate the internal energies in the free energies of the Pd-rich PdX alloys, are determined uniquely and successively from the lower-order to higher-order, by the full-potential Korringa-Kohn-Rostoker Green’s function method (FPKKR), combined with the generalized gradient approximation in the density functional theory. We found that the temperature dependence of IEs due to the FD distribution, being usually neglected, is very important to reproduce the X-concentration dependence of the observed solvus temperatures of the Pd-rich PdX (X=Ru, Rh) alloys.

Keywords: full-potential KKR-green’s function method, Fermi-Dirac distribution, GGA, phase diagram of Pd-rich PdX (X=Ru, Rh) alloys, thermal vibration effect

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Authors: Jaswinder Kumar, Kulbir Singh Sandhu

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Friction stir processing (FSP) is a solid-state surface processing technique. A single-pass FSP was performed on Aluminum alloy at combinations of different tool rotational speeds with cylindrical threaded pin profiled tool. The effect of these parameters on tribological properties was studied. The wear resistance is found to be increased from base metal to a single pass FSP sample. The results revealed that with an increase in tool rotational speed, the wear rate increases. The high heat generation causes matrix softening, which results in an increased wear rate; on the other hand, high heat generation leads to coarse grains, which also affected tribological properties. Furthermore, Microstructure results showed that FSPed alloy has a more refined grain structure as compare to the base material, which may be resulted in enhancement of hardness and resistance to wear in FSP.

Keywords: friction stir processing, aluminium alloy, microhardness, microstructure

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Authors: Yugander Arra, Florence Auguy, Melissa Stiebner, Sophie Chéron, Michael M. Wudick, Van Schepler-Luu, Sébastien Cunnac, Wolf B. Frommer, Laurence Albar

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Rice yellow mottle virus (RYMV) is one of the most important diseases affecting rice in Africa. The most promising strategy to reduce yield losses is the use of highly resistant varieties. The resistance gene RYMV2 is homolog of the Arabidopsis constitutive expression of pathogenesis related protein-5 (AtCPR5) nucleoporin gene. Resistance alleles are originating from African cultivated rice Oryza glaberrima, rarely cultivated, and are characterized by frameshifts or early stop codons, leading to a non-functional or truncated protein. Rice possesses two paralogs of CPR5 and function of these genes are unclear. Here, we evaluated the role of the two rice candidate nucleoporin paralogs OsCPR5.1 (pathogenesis-related gene 5; RYMV2) and OsCPR5.2 by CRISPR/Cas9 genome editing. Despite striking sequence and structural similarity, only loss-of-function of OsCPR5.1 led to full resistance, while loss-of-function oscpr5.2 mutants remained susceptible. Short N-terminal deletions in OsCPR5.1 also did not lead to resistance. In contrast to Atcpr5 mutants, neither OsCPR5.1 nor OsCPR5.2 knock out mutants showed substantial growth defects. Taken together, the candidate nucleoporin OsCPR5.1, but not its close homolog OsCPR5.2, plays a specific role for the susceptibility to RYMV, possibly by impairing the import of viral RNA or protein into the nucleus. Whereas gene introgression from O. glaberrima to high yielding O. sativa varieties is impaired by strong sterility barriers and the negative impact of linkage drag, genome editing of OsCPR5.1, while maintaining OsCPR5.2 activity, thus provides a promising strategy to generate O. sativa elite lines that are resistant to RYMV.

Keywords: CRISPR Cas9, genome editing, knock out mutant, recessive resistance, rice yellow mottle virus

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Authors: Amir Aziz, Martin Tuner, Sebastian Verhelst, Oivind Andersson

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Partially Premixed Combustion (PPC) is a combustion concept which aims to simultaneously achieve high efficiency and low engine-out emissions. Extending the ignition delay to promote the premixing, has been recognized as one of the key factor to achieve PPC. Fuels with high octane number have been proven to be a good candidates to extend the ignition delay. In this work, E85 (85% ethanol) has been used as a PPC fuel. The aim of this work was to investigate a suitable injection strategy for PPC combustion fueled with E85 in a single-cylinder heavy-duty engine. Single and double injection strategy were applied with different injection timing and the ratio between different injection pulses was varied. The performance and emission were investigated at low load. The results show that the double injection strategy should be preferred for PPC fueled with E85 due to low emissions and high efficiency, while keeping the pressure raise rate at very low levels.

Keywords: E85, partially premixed combustion, injection strategy, performance and emission

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Authors: Muizz Sanni-Anibire

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The 21st century has witnessed growing concerns for the protection of built facilities against natural and man-made disasters. Studies in earthquake resistant buildings, fire, and explosion resistant buildings now dominate the arena. To protect people and facilities from the effects of the explosion, reinforced concrete walls have been designed to be blast resistant. Understanding the performance of these walls is a key step in ensuring the safety of built facilities. Blast walls are mostly designed using simple techniques such as single degree of freedom (SDOF) method, despite the increasing use of multi-degree of freedom techniques such as the finite element method. This study is the first stage of a continuous research into the safety and reliability of blast walls. It presents the SDOF approach applied to the analysis of a concrete wall panel under three representative bomb situations. These are motorcycle 50 kg, car 400kg and also van with the capacity of 1500 kg of TNT explosive.

Keywords: blast wall, safety, protection, explosion

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Authors: Vipin Kumar, Girish S. Setlur

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Graphene has been recognized as a promising 2D material with many new properties. However, pristine graphene is gapless which hinders its direct application towards graphene-based semiconducting devices. Graphene is a zero-gapp and linearly dispersing semiconductor. Massless charge carriers (quasi-particles) in graphene obey the relativistic Dirac equation. These Dirac fermions show very unusual physical properties such as electronic, optical and transport. Graphene is analogous to two-level atomic systems and conventional semiconductors. We may expect that graphene-based systems will also exhibit phenomena that are well-known in two-level atomic systems and in conventional semiconductors. Rabi oscillation is a nonlinear optical phenomenon well-known in the context of two-level atomic systems and also in conventional semiconductors. It is the periodic exchange of energy between the system of interest and the electromagnetic field. The present work describes the phenomenon of Rabi oscillations in graphene based systems. Rabi oscillations have already been described theoretically and experimentally in the extensive literature available on this topic. To describe Rabi oscillations they use an approximation known as rotating wave approximation (RWA) well-known in studies of two-level systems. RWA is valid only near conventional resonance (small detuning)- when the frequency of the external field is nearly equal to the particle-hole excitation frequency. The Rabi frequency goes through a minimum close to conventional resonance as a function of detuning. Far from conventional resonance, the RWA becomes rather less useful and we need some other technique to describe the phenomenon of Rabi oscillation. In conventional systems, there is no second minimum - the only minimum is at conventional resonance. But in graphene we find anomalous Rabi oscillations far from conventional resonance where the Rabi frequency goes through a minimum that is much smaller than the conventional Rabi frequency. This is known as anomalous Rabi frequency and is unique to graphene systems. We have shown that this is attributable to the pseudo-spin degree of freedom in graphene systems. A new technique, which is an alternative to RWA called asymptotic RWA (ARWA), has been invoked by our group to discuss the phenomenon of Rabi oscillation. Experimentally accessible current density shows different types of threshold behaviour in frequency domain close to the anomalous Rabi frequency depending on the system chosen. For single layer graphene, the exponent at threshold is equal to 1/2 while in case of bilayer graphene, it is computed to be equal to 1. Bilayer graphene shows harmonic (anomalous) resonances absent in single layer graphene. The effect of asymmetry and trigonal warping (a weak direct inter-layer hopping in bilayer graphene) on these oscillations is also studied in graphene systems. Asymmetry has a remarkable effect only on anomalous Rabi oscillations whereas the Rabi frequency near conventional resonance is not significantly affected by the asymmetry parameter. In presence of asymmetry, these graphene systems show Rabi-like oscillations (offset oscillations) even for vanishingly small applied field strengths (less than the gap parameter). The frequency of offset oscillations may be identified with the asymmetry parameter.

Keywords: graphene, Bilayer graphene, Rabi oscillations, Dirac fermion systems

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Authors: Debadi Chakraborty, John E. Sader

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Nanomechanical devices have emerged as a versatile platform for a host of applications due to their extreme sensitivity to environmental conditions. For example, mass measurements with sensitivity at the atomic level have recently been demonstrated. Ultrafast laser spectroscopy coherently excite the vibrational modes of metal nanoparticles and permits precise measurement of the vibration characteristics as a function of nanoparticle shape, size and surrounding environment. This study reports that the vibration of metal nanoparticles in simple liquids, like water and glycerol are not described by conventional fluid mechanics, i.e., Navier Stokes equations. The intrinsic molecular relaxation processes in the surrounding liquid are found to have a profound effect on the fluid-structure interaction of mechanical devices at nanometre scales. Theoretical models have been developed based on the non-Newtonian viscoelastic fluid-structure interaction theory to investigate the vibration of nanoparticles immersed in simple fluids. The utility of this theoretical framework is demonstrated by comparison to measurements on single nanowires and ensembles of metal rods. This study provides a rigorous foundation for the use of metal nanoparticles as ultrasensitive mechanical sensors in fluid and opens a new paradigm for understanding extremely high frequency fluid mechanics, nanoscale sensing technologies, and biophysical processes.

Keywords: fluid-structure interaction, nanoparticle vibration, ultrafast laser spectroscopy, viscoelastic damping

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Authors: Gabriella Dravecz, László Péter, Zsolt Kis

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Abstract— The growth of optical LiNbO3 single crystal and its physical and chemical properties are well known on the macroscopic scale. Nowadays the rare-earth doped single crystals became important for coherent quantum optical experiments: electromagnetically induced transparency, slow down of light pulses, coherent quantum memory. The expansion of applications is increasingly requiring the production of nano scaled LiNbO3 particles. For example, rare-earth doped nanoscaled particles of lithium niobate can be act like single photon source which can be the bases of a coding system of the quantum computer providing complete inaccessibility to strangers. The polyol method is a chemical synthesis where oxide formation occurs instead of hydroxide because of the high temperature. Moreover the polyol medium limits the growth and agglomeration of the grains producing particles with the diameter of 30-200 nm. In this work nano scaled LiNbO3 was prepared by the polyol method. The starting materials (niobium oxalate and LiOH) were diluted in H2O2. Then it was suspended in ethylene glycol and heated up to about the boiling point of the mixture with intensive stirring. After the thermal equilibrium was reached, the mixture was kept in this temperature for 4 hours. The suspension was cooled overnight. The mixture was centrifuged and the particles were filtered. Dynamic Light Scattering (DLS) measurement was carried out and the size of the particles were found to be 80-100 nms. This was confirmed by Scanning Electron Microscope (SEM) investigations. The element analysis of SEM showed large amount of Nb in the sample. The production of LiNbO3 nano particles were succesful by the polyol method. The agglomeration of the particles were avoided and the size of 80-100nm could be reached.

Keywords: lithium-niobate, nanoparticles, polyol, SEM

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Authors: Salmi-laouar Sihem, Kara Ahmed Imad

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The ichnological study of the Djebel BouarifCenomaniandeposits(Northern Aurès Range, Algeria) revealed relatively abundant and diverse sclerobiont communities that are preserved in corals, bivalves, and gastropods ; all are described herein. Fossil traces are dominated by exceptionally preserved Gastrochaenolitesoften with tracemakers (bivalves), which are preserved in situ, Entobia, and Maeandropolydora. Other borings are rare and are represented by a single specimen of Rogerella, Nihilichnus, and Spirolites. Amongsclerozoans, encrustingjuvenile oysters, and non-oyster bivalves (Pseudolimea?granulata) are the mostabundant groups. Otherepibionts, such as gastropods and polychaetes (Glomerulaserpentina), are lesscommon; dwarfgastropods were located on a single oyster Costagyraolisiponensis, whereas Glomerula specimens were clustered on the lower and upper surfaces of coral Aspidiscuscristatus. Gastrochaenoliteswith original tracemakers and all the epibionts studied herein have not been described from the Djebel BouarifCenomaniandeposits to date. The rare occurrences of Spirolites and Nihilichnus are reported from Algeria for the first time.

Keywords: bioerosion, sclerobionts, upper creataceous, southern tethys, atlasic domain

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Authors: Win-Jin Chang, Haw-Long Lee, Yu-Ching Yang

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Atomic finite element simulation is applied to investigate the vibration frequency of a single-layer gamma graphyne with an attached mass for the CCCC, SSSS, CFCF, SFSF boundary conditions using the commercial code ANSYS. The fundamental frequencies of the graphyne sheet are compared with the results of the previous study. The results of the comparison are very good in all considered cases. The attached mass causes a shift in the resonant frequency of the graphyne. The frequencies of the single-layer gamma graphyne with an attached mass for different boundary conditions are obtained, and the order based on the boundary condition is CCCC >SSSS > CFCF> SFSF. The highest frequency shift is obtained when the attached mass is located at the center of the graphyne sheet. This is useful for the design of a highly sensitive graphyne-based mass sensor.

Keywords: graphyne, finite element analysis, vibration analysis, frequency shift

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Authors: Qasim M. Kriri

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Few Saudi Arabia production companies face financial profit issues until this moment. This work presents a linear integer programming model that solves a production problem of a Saudi Food Company in Saudi Arabia. An optimal solution to the above-mentioned problem is a Linear Programming solution. In this regard, the main purpose of this project is to maximize profit. Linear Programming Technique has been used to derive the maximum profit from production of natural juice at Saudi Food Co. The operations of production of the company were formulated and optimal results are found out by using Lindo Software that employed Sensitivity Analysis and Parametric linear programming in order develop Linear Programming. In addition, the parameter values are increased, then the values of the objective function will be increased.

Keywords: parameter linear programming, objective function, sensitivity analysis, optimize profit

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Authors: Priya Kulkarni, Soumya Koppikar, Narendrakumar Wagh, Dhanshri Ingle, Onkar Lande, Abhay Harsulkar

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Cartilage is an extracellular matrix composed of aggrecan, which imparts it with a great tensile strength, stiffness and resilience. Disruption in cartilage metabolism leading to progressive degeneration is a characteristic feature of Osteoarthritis (OA). The process involves enzymatic depolymerisation of cartilage specific proteoglycan, releasing free glycosaminoglycan (GAG). This released GAG in synovial fluid (SF) of knee joint serves as a direct measure of cartilage loss, however, limited due to its invasive nature. Western Ontario and McMaster Universities Arthritis Index (WOMAC) is widely used for assessing pain, stiffness and physical-functions in OA patients. The scale is comprised of three subscales namely, pain, stiffness and physical-function, intends to measure patient’s perspective of disease severity as well as efficacy of prescribed treatment. Twenty SF samples obtained from OA patients were analysed for their GAG values in SF using DMMB based assay. LK 1.0 vernacular version was used to attain WOMAC scale. The results were evaluated using SAS University software (Edition 1.0) for statistical significance. All OA patients revealed higher GAG values compared to the control value of 78.4±30.1µg/ml (obtained from our non-OA patients). Average WOMAC calculated was 51.3 while pain, stiffness and function estimated were 9.7, 3.9 and 37.7, respectively. Interestingly, a strong statistical correlation was established between WOMAC function subscale and GAG (p = 0.0102). This subscale is based on day-to-day activities like stair-use, bending, walking, getting in/out of car, rising from bed. However, pain and stiffness subscale did not show correlation with any of the studied markers and endorsed the atypical inflammation in OA pathology. On one side, where knee pain showed poor correlation with GAG, it is often noted that radiography is insensitive to cartilage degenerative changes; thus OA remains undiagnosed for long. Moreover, active cartilage degradation phase remains elusive to both, patient and clinician. Through analysis of large number of OA patients we have established a close association of Kellgren-Lawrence grades and increased cartilage loss. A direct attempt to correlate WOMAC and radiographic progression of OA with various biomarkers has not been attempted so far. We found a good correlation in GAG levels in SF and the function subscale.

Keywords: cartilage, Glycosaminoglycan, synovial fluid, western ontario and McMaster Universities Arthritis Index

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Authors: Rohit Singh Dangi, Ravi Kant Pal, Monica Sundd

Abstract:

Acyl-CoA binding protein (ACBP) is a housekeeping protein which functions as an intracellular carrier of acyl-CoA esters. Given the fact that the amastigote stage (blood stage) of Leishmania depends largely on fatty acids as the energy source, of which a large part is derived from its host, these proteins might have an important role in its survival. In Leishmania major, genome sequencing suggests the presence of six ACBPs, whose function remains largely unknown. For functional and structural characterization, one of the ACBP genes was cloned, and the protein was expressed and purified heterologously. Acyl-CoA ester binding and stoichiometry were analyzed by isothermal titration calorimetry and Dynamic light scattering. Our results shed light on high affinity of ACBP towards longer acyl-CoA esters, such as myristoyl-CoA to arachidonoyl-CoA with single binding site. To understand the binding mechanism & dynamics, Nuclear magnetic resonance assignments of this protein are being done. The protein's crystal structure was determined at 1.5Å resolution and revealed a classical topology for ACBP, containing four alpha-helical bundles. In the binding pocket, the loop between the first and the second helix (16 – 26AA) is four residues longer from other extensively studied ACBPs (PfACBP) and it curls upwards towards the pantothenate moiety of CoA to provide a large tunnel space for long acyl chain insertion.

Keywords: acyl-coa binding protein (ACBP), acyl-coa esters, crystal structure, isothermal titration, calorimetry, Leishmania

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Authors: Aditi Jain

Abstract:

Aim: To compare the canal transportation, centering ability and remaining dentin thickness of OneShape and WaveOne system using CBCT. Objective: To identify rotary system which respects original canal anatomy. Materials and Methods: Forty extracted human single-rooted premolars were used in the present study. Pre-instrumentation scans of all teeth were taken, canal curvatures were calculated, and the samples were randomly divided into two groups with twenty samples in each group, where Group 1 included WaveOne system and Group 2 Protaper rotary system. Post-instrumentation scans were performed, and the two scans were compared to determine canal transportation, centering ability and remaining dentin thickness at 1, 3, and 5 mm from the root apex. Results: Using Student’s unpaired t test results were as follows; for canal transportation Group 1 showed statistical significant difference at 3mm, 6mm and non-significant difference was obtained at 9mm but for Group 2 non-statistical significant difference was obtained at 3mm, 6mm, and 9mm. For centering ability and remaining dentin thickness Group 1 showed non-statistical significant difference at 3mm and 9mm, while statistical significant difference at 6mm was obtained. When comparison of remaining dentin thickness was done at three levels using two groups WaveOne and ProTaper. There was non-statistical significant difference between two groups. Conclusion: WaveOne single reciprocation file respects original canal anatomy better than ProTaper. WaveOne depicted the best centering ability.

Keywords: ShapeOne, WaveOne, transportation, centering ability, dentin thickness, CBCT (Cone Beam Computed Tomography)

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Authors: Majid Haghshenas, James Wilson, Ranganathan Kumar

Abstract:

In this study, an Algebraic Coupled Level Set-Volume of Fluid (A-CLSVOF) method with capillary pressure treatment is proposed for the modeling of two-phase capillary flows. The Volume of Fluid (VOF) method is utilized to incorporate one-way coupling with the Level Set (LS) function in order to further improve the accuracy of the interface curvature calculation and resulting surface tension force. The capillary pressure is determined and treated independently of the hydrodynamic pressure in the momentum balance in order to maintain consistency between cell centered and interpolated values, resulting in a reduction in parasitic currents. In this method, both VOF and LS functions are transported where the new volume fraction determines the interface seed position used to reinitialize the LS field. The Hamilton-Godunov function is used with a second order (in space and time) discretization scheme to produce a signed distance function. The performance of the current methodology has been tested against some common test cases in order to assess the reduction in non-physical velocities and improvements in the interfacial pressure jump. The cases of a static drop, non-linear Rayleigh-Taylor instability and finally a droplets impact on a liquid pool were simulated to compare the performance of the present method to other well-known methods in the area of parasitic current reduction, interface location evolution and overall agreement with experimental results.

Keywords: two-phase flow, capillary flow, surface tension force, coupled LS with VOF

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Authors: Mohamed Mounir Tellache, Hiroyuki Kambara, Yasuharu Koike, Makoto Miyakoshi, Natsue Yoshimura

Abstract:

This study explores the practicality of using electroencephalographic (EEG) independent components to predict eight-direction finger movements in pseudo-real-time. Six healthy participants with individual-head MRI images performed finger movements in eight directions with two different arm configurations. The analysis was performed in two stages. The first stage consisted of using independent component analysis (ICA) to separate the signals representing brain activity from non-brain activity signals and to obtain the unmixing matrix. The resulting independent components (ICs) were checked, and those reflecting brain-activity were selected. Finally, the time series of the selected ICs were used to predict eight finger-movement directions using Sparse Logistic Regression (SLR). The second stage consisted of using the previously obtained unmixing matrix, the selected ICs, and the model obtained by applying SLR to classify a different EEG dataset. This method was applied to two different settings, namely the single-participant level and the group-level. For the single-participant level, the EEG dataset used in the first stage and the EEG dataset used in the second stage originated from the same participant. For the group-level, the EEG datasets used in the first stage were constructed by temporally concatenating each combination without repetition of the EEG datasets of five participants out of six, whereas the EEG dataset used in the second stage originated from the remaining participants. The average test classification results across datasets (mean ± S.D.) were 38.62 ± 8.36% for the single-participant, which was significantly higher than the chance level (12.50 ± 0.01%), and 27.26 ± 4.39% for the group-level which was also significantly higher than the chance level (12.49% ± 0.01%). The classification accuracy within [–45°, 45°] of the true direction is 70.03 ± 8.14% for single-participant and 62.63 ± 6.07% for group-level which may be promising for some real-life applications. Clustering and contribution analyses further revealed the brain regions involved in finger movement and the temporal aspect of their contribution to the classification. These results showed the possibility of using the ICA-based method in combination with other methods to build a real-time system to control prostheses.

Keywords: brain-computer interface, electroencephalography, finger motion decoding, independent component analysis, pseudo real-time motion decoding

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Authors: S. H. Arnaud Kanga, O. Hili, S. Dabo-Niang

Abstract:

Spatial prediction is an issue appealing and attracting several fields such as agriculture, environmental sciences, ecology, econometrics, and many others. Although multiple non-parametric prediction methods exist for spatial data, those are based on the conditional expectation. This paper took a different approach by examining a non-parametric spatial predictor of the conditional quantile. The study especially observes the stationary multidimensional spatial process over a rectangular domain. Indeed, the proposed quantile is obtained by inverting the conditional distribution function. Furthermore, the proposed estimator of the conditional distribution function depends on three kernels, where one of them controls the distance between spatial locations, while the other two control the distance between observations. In addition, the almost complete convergence and the convergence in mean order q of the kernel predictor are obtained when the sample considered is alpha-mixing. Such approach of the prediction method gives the advantage of accuracy as it overcomes sensitivity to extreme and outliers values.

Keywords: conditional quantile, kernel, nonparametric, stationary

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Authors: Natasha Petrovska, Mirjana Pavlovic, Maria M. Larrondo-Petrie

Abstract:

Neural stem cells (NSCs) are multi-potent, self-renewing cells that generate new neurons. Three subtypes of NSCs can be separated regarding the stages of NSC lineage: quiescent neural stem cells (qNSCs), activated neural stem cells (aNSCs) and neural progenitor cells (NPCs), but their gene expression signatures are not utterly understood yet. Single-cell examinations have started to elucidate the complex structure of NSC populations. Nevertheless, there is a lack of thorough molecular interpretation of the NSC lineage heterogeneity and an increasing need for tools to analyze and improve the efficiency and correctness of single-cell sequencing data. Feature selection and ordering can identify and classify the gene expression signatures of these subtypes and can discover novel subpopulations during the NSCs activation and differentiation processes. The aim here is to review the implementation of the feature selection technique on NSC subtypes and the classification techniques that have been used for the identification of gene expression signatures.

Keywords: feature selection, feature similarity, neural stem cells, genes, feature selection methods

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Authors: Keundong Lee, Dongha Yoo, Youngbin Tchoe, Gyu-Chul Yi

Abstract:

Light emitting diode (LED) array is an ideal optical stimulation tool for optogenetics, which controls inhibition and excitation of specific neurons with light-sensitive ion channels or pumps. Although a fiber-optic cable with an external light source, either a laser or LED mechanically connected to the end of the fiber-optic cable has widely been used for illumination on neural tissue, a new approach to use micro LEDs (µLEDs) has recently been demonstrated. The LEDs can be placed directly either on the cortical surface or within the deep brain using a penetrating depth probe. Accordingly, this method would not need a permanent opening in the skull if the LEDs are integrated with miniature electrical power source and wireless communication. In addition, multiple color generation from single µLED cell would enable to excite and/or inhibit neurons in localized regions. Here, we demonstrate flexible and color tunable µLEDs for the optogenetic device applications. The flexible and color tunable LEDs was fabricated using multifaceted gallium nitride (GaN) nanorod arrays with GaN nanorods grown on InxGa1−xN/GaN single quantum well structures (SQW) anisotropically formed on the nanorod tips and sidewalls. For various electroluminescence (EL) colors, current injection paths were controlled through a continuous p-GaN layer depending on the applied bias voltage. The electric current was injected through different thickness and composition, thus changing the color of light from red to blue that the LED emits. We believe that the flexible and color tunable µLEDs enable us to control activities of the neuron by emitting various colors from the single µLED cell.

Keywords: light emitting diode, optogenetics, graphene, flexible optoelectronics

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