Search results for: computational brain

Authors: Olusola Olalekan Elekofehinti, Isaac Gbadura Adanlawo, Joao Batista Teixeira Rocha

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We evaluated the potential neuroprotective effect of Phyllantus nuriri against Fe2+ and SNP induced oxidative stress in mitochondria of rats brain. Cellular viability was assessed by MTT reduction, reactive oxygen species (ROS) generation was measured using the probe 2,7-dichlorofluorescein diacetate (DCFH-DA). Glutathione content was measured using dithionitrobenzoic acid (DTNB). Fe2+ (10µM) and SNP (5µM) significantly decreased mitochondrial activity, assessed by MTT reduction assay, in a dose-dependent manner, this occurred in parallel with increased glutathione oxidation, ROS production and lipid peroxidation end-products (thiobarbituric acid reactive substances, TBARS). The co-incubation with methanolic extract of Phyllantus nuriri (10-100 µg/ml) reduced the disruption of mitochondrial activity, gluthathione oxidation, ROS production as well as the increase in TBARS levels caused by both Fe2+ and SNP in a dose dependent manner. HPLC analysis of the extract revealed the presence of gallic acid (20.54±0.01), caffeic acid (7.93±0.02), rutin (25.31±0.05), quercetin (31.28±0.03) and kaemferol (14.36±0.01). This result suggests that these phytochemicals account for the protective actions of Phyllantus nuriri against Fe2+ and SNP -induced oxidative stress. Our results show that Phyllantus nuriri consist important bioactive molecules in the search for an improved therapy against the deleterious effects of Fe2+, an intrinsic producer of reactive oxygen species (ROS), that leads to neuronal oxidative stress and neurodegeneration.

Keywords: Phyllantus niruri, neuroprotection, oxidative stress, mitochondria, synaptosome

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Authors: Evangelos Koumparoudis

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The definition of death is a deep philosophical question, and no single meaning can be ascribed to it. This essay focuses on the ontological, epistemological, and ethical aspects of death and dying in view of technological progress in information technology and biomedicine. It starts with the ad hoc 1968 Harvard committee that proposed that the criterion for the definition of death be irreversible coma and then refers to the debate over the whole brain death formula, emphasizing the integrated function of the organism and higher brain formula, taking consciousness and personality as essential human characteristics. It follows with the contribution of information technology in personalized and precision medicine and anti-aging measures aimed at life prolongation. It also touches on the possibility of the creation of human-machine hybrids and how this raises ontological and ethical issues that concern the “cyborgization” of human beings and the conception of the organism and personhood based on a post/transhumanist essence, and, furthermore, if sentient AI capable of autonomous decision-making that might even surpass human intelligence (singularity, superintelligence) deserves moral or legal personhood. Finally, there is the question as to whether death and dying should be redefined at a transcendent level, which is reinforced by already-existing technologies of “virtual after-” life and the possibility of uploading human minds. In the last section, I refer to the current (and future) applications of nanomedicine in diagnostics, therapeutics, implants, and tissue engineering as well as the aspiration to “immortality” by cryonics. The definition of death is reformulated since age and disease elimination may be realized, and the criterion of irreversibility may be challenged.

Keywords: death, posthumanism, infomedicine, nanomedicine, cryonics

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Authors: Takashi Kaburagi, Masashi Takenaka, Yosuke Kurihara, Takashi Matsumoto

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Major depressive disorder (MDD) is one of the most common mental illnesses today. It is believed to be caused by a combination of several factors, including stress. Stress can be quantitatively evaluated using the State-Trait Anxiety Inventory (STAI), one of the best indices to evaluate anxiety. Although STAI scores are widely used in applications ranging from clinical diagnosis to basic research, the scores are calculated based on a self-reported questionnaire. An objective evaluation is required because the subject may intentionally change his/her answers if multiple tests are carried out. In this article, we present a modified index called the “multi-channel Laterality Index at Rest (mc-LIR)” by recording the brain activity from a wider area of the frontal lobe using multi-channel functional near-infrared spectroscopy (fNIRS). The presented index aims to measure multiple positions near the F_pz defined by the international 10-20 system positioning. Using 24 subjects, the dependencies on the number of measuring points used to calculate the mc-LIR and its correlation coefficients with the STAI scores are reported. Furthermore, a simple linear regression was performed to estimate the STAI scores from mc-LIR. The cross-validation error is also reported. The experimental results show that using multiple positions near the Fpz will improve the correlation coefficients and estimation than those using only two positions.

Keywords: frontal lobe, functional near-infrared spectroscopy, state-trait anxiety inventory score, stress

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Authors: Zerihun Ketema Tadesse, Dabbu Suman Reddy

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Brain-Computer Interfaces (BCIs) give the possibility for disabled people to communicate and control devices. This work aims at developing steady-state visual evoked potential (SSVEP)-based BCI for patients with limb disabilities. In hospitals, devices like nurse emergency call devices, lights, and TV sets are what patients use most frequently, but these devices are operated manually or using the remote control. Thus, disabled patients are not able to operate these devices by themselves. Hence, SSVEP-based BCI system that can allow disabled patients to control nurse calling device and other devices is proposed in this work. Portable LED visual stimulator that flickers at specific frequencies of 7Hz, 8Hz, 9Hz and 10Hz were developed as part of this project. Disabled patients can stare at specific flickering LED of visual stimulator and Emotiv EPOC used to acquire EEG signal in a non-invasive way. The acquired EEG signal can be processed to generate various control signals depending upon the amplitude and duration of signal components. MATLAB software is used for signal processing and analysis and also for command generation. Arduino is used as a hardware interface device to receive and transmit command signals to the experimental setup. Therefore, this study is focused on the design and development of Steady-state visually evoked potential (SSVEP)-based BCI for limb disabled patients, which helps them to operate and control devices in the hospital room/wards.

Keywords: SSVEP-BCI, Limb Disabled Patients, LED Visual Stimulator, EEG signal, control devices, hospital room/wards

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Authors: Remo Waser, Simon Maranda, Anastasia Stamatiou, Ludger J. Fischer, Joerg Worlitschek

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In latent heat storage, a phase change material (PCM) is used to store thermal energy. The heat transfer rate during solidification is limited and considered as a key challenge in the development of latent heat storages. Thus, finned heat exchangers (HEX) are often utilized to increase the heat transfer rate of the storage system. In this study, a new modeling approach to calculating the heat transfer rate in latent thermal energy storages with complex HEX geometries is presented. This model allows for an optimization of the HEX design in terms of costs and thermal performance of the system. Modeling solidification processes requires the calculation of time-dependent heat conduction with moving boundaries. Commonly used computational fluid dynamic (CFD) methods enable the analysis of the heat transfer in complex HEX geometries. If applied to the entire storage, the drawback of this approach is the high computational effort due to small time steps and fine computational grids required for accurate solutions. An alternative to describe the process of solidification is the so-called temperature-based approach. In order to minimize the computational effort, a quasi-stationary assumption can be applied. This approach provides highly accurate predictions for tube heat exchangers. However, it shows unsatisfactory results for more complex geometries such as finned tube heat exchangers. The presented simulation model uses a temporal and spatial discretization of heat exchanger tube. The spatial discretization is based on the smallest possible symmetric segment of the HEX. The heat flow in each segment is calculated using finite volume method. Since the heat transfer fluid temperature can be derived using energy conservation equations, the boundary conditions at the inner tube wall is dynamically updated for each time step and segment. The model allows a prediction of the thermal performance of latent thermal energy storage systems using complex HEX geometries with considerably low computational effort.

Keywords: modelling of solidification, finned tube heat exchanger, latent thermal energy storage

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Authors: Hamed K. Esfahani, Bithin Datta

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Transport of reactive chemical contaminant species in groundwater aquifers is a complex and highly non-linear physical and geochemical process especially for real life scenarios. Simulating this transport process involves solving complex nonlinear equations and generally requires huge computational time for a given aquifer study area. Development of optimal remediation strategies in aquifers may require repeated solution of such complex numerical simulation models. To overcome this computational limitation and improve the computational feasibility of large number of repeated simulations, Genetic Programming based trained surrogate models are developed to approximately simulate such complex transport processes. Transport process of acid mine drainage, a hazardous pollutant is first simulated using a numerical simulated model: HYDROGEOCHEM 5.0 for a contaminated aquifer in a historic mine site. Simulation model solution results for an illustrative contaminated aquifer site is then approximated by training and testing a Genetic Programming (GP) based surrogate model. Performance evaluation of the ensemble GP models as surrogate models for the reactive species transport in groundwater demonstrates the feasibility of its use and the associated computational advantages. The results show the efficiency and feasibility of using ensemble GP surrogate models as approximate simulators of complex hydrogeologic and geochemical processes in a contaminated groundwater aquifer incorporating uncertainties in historic mine site.

Keywords: geochemical transport simulation, acid mine drainage, surrogate models, ensemble genetic programming, contaminated aquifers, mine sites

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Authors: Olayiwola Moruf Oyedunsi

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This paper discusses the Modified Variational Iteration Method (MVIM) for the solution of nonlinear Burgers’ equation arising in longitudinal dispersion phenomena in fluid flow through porous media. The method is an elegant combination of Taylor’s series and the variational iteration method (VIM). Using Maple 18 for implementation, it is observed that the procedure provides rapidly convergent approximation with less computational efforts. The result shows that the concentration C(x,t) of the contaminated water decreases as distance x increases for the given time t.

Keywords: modified variational iteration method, Burger’s equation, porous media, partial differential equation

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Authors: Christopher Deekia Nwimae, Nigel Simms, Liyun Lao

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Erosion in pipe bends caused by particles is a major obstacle in the oil and gas fields and might cause the breakdown of production equipment. This work studied the effects imposed by flow velocity and impact of solid particles diameter in an elbow; erosion rate was verified with experimental data using the computational fluid dynamics (CFD) approach. Two-way coupled Euler-Lagrange and discrete phase model was employed to calculate the air/solid particle flow in an elbow. One erosion model and three-particle rebound models were used to predict the erosion rate on the 90° elbows. The generic erosion model was used in the CFD-based erosion model, and after comparing it with experimental data, results showed agreement with the CFD-based predictions as observed.

Keywords: erosion, prediction, elbow, computational fluid dynamics

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Authors: Raza Abdulla Saeed

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In this study, the three-dimensional cavitating turbulent flow in a complete Francis turbine is simulated using mixture model for cavity/liquid two-phase flows. Numerical analysis is carried out using ANSYS CFX software release 12, and standard k-ε turbulence model is adopted for this analysis. The computational fluid domain consist of spiral casing, stay vanes, guide vanes, runner and draft tube. The computational domain is discretized with a three-dimensional mesh system of unstructured tetrahedron mesh. The finite volume method (FVM) is used to solve the governing equations of the mixture model. Results of cavitation on the runner’s blades under three different boundary conditions are presented and discussed. From the numerical results it has been found that the numerical method was successfully applied to simulate the cavitating two-phase turbulent flow through a Francis turbine, and also cavitation is clearly predicted in the form of water vapor formation inside the turbine. By comparison the numerical prediction results with a real runner; it’s shown that the region of higher volume fraction obtained by simulation is consistent with the region of runner cavitation damage.

Keywords: computational fluid dynamics, hydraulic francis turbine, numerical simulation, two-phase mixture cavitation model

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Authors: Kalpana Dahiya

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This paper discusses a two-level hierarchical time minimization transportation problem, which is an important class of transportation problems arising in industries. This problem has been studied by various researchers, and a number of polynomial time iterative algorithms are available to find its solution. All the existing algorithms, though efficient, have some shortcomings. The current study proposes an alternate solution algorithm for the problem that is more efficient in terms of computational time than the existing algorithms. The results justifying the underlying theory of the proposed algorithm are given. Further, a detailed comparison of the computational behaviour of all the algorithms for randomly generated instances of this problem of different sizes validates the efficiency of the proposed algorithm.

Keywords: global optimization, hierarchical optimization, transportation problem, concave minimization

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Authors: Katie M. Clark, Adriana A. Tienda, Krista C. Paffenroth, Lindsey N. Brigante, Daniel C. Colvin, Jose Maldonado, Erin S. Calipari, Fiona E. Harrison

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Manganese (Mn) is an essential trace element required for human health and is important in antioxidant defenses, as well as in the development and function of dopaminergic neurons. However, chronic low-level Mn exposure, such as through contaminated drinking water, poses risks that may contribute to neurodevelopmental and neurodegenerative conditions, including attention deficit hyperactivity disorder (ADHD). Pharmacological inhibition of the dopamine transporter (DAT) blocks reuptake, elevates synaptic dopamine, and alleviates ADHD symptoms. This study aimed to determine whether Mn exposure in juvenile mice modifies their response to DAT blockers, amphetamine, and methylphenidate and utilize neuroimaging methods to visualize and quantify Mn distribution across dopaminergic brain regions. Male and female heterozygous DATᵀ³⁵⁶ᴹ and wild-type littermates were randomly assigned to receive control (2.5% Stevia) or high Manganese (2.5 mg/ml Mn + 2.5% Stevia) via water ad libitum from weaning (21-28 days) for 4-5 weeks. Mice underwent repeated testing in locomotor activity chambers for three consecutive days (60 mins.) to ensure that they were fully habituated to the environments. On the fourth day, a 3-hour activity session was conducted following treatment with amphetamine (3 mg/kg) or methylphenidate (5 mg/kg). The second drug was administered in a second 3-hour activity session following a 1-week washout period. Following the washout, the mice were given one last injection of amphetamine and euthanized one hour later. Using the ex-vivo brains, magnetic resonance relaxometry (MRR) was performed on a 7Telsa imaging system to map T1- and T2-weighted (T1W, T2W) relaxation times. Mn inherent paramagnetic properties shorten both T1W and T2W times, which enhances the signal intensity and contrast, enabling effective visualization of Mn accumulation in the entire brain. A subset of mice was treated with amphetamine 1 hour before euthanasia. SmartSPIM light sheet microscopy with cleared whole brains and cFos and tyrosine hydroxylase (TH) labeling enabled an unbiased automated counting and densitometric analysis of TH and cFos positive cells. Immunohistochemistry was conducted to measure synaptic protein markers and quantify changes in neurotransmitter regulation. Mn exposure elevated Mn brain levels and potentiated stimulant effects in males. The globus pallidus, substantia nigra, thalamus, and striatum exhibited more pronounced T1W shortening, indicating regional susceptibility to Mn accumulation (p<0.0001, 2-Way ANOVA). In the cleared whole brains, initial analyses suggest that TH and c-Fos co-staining mirrors behavioral data with decreased co-staining in DATT356M+/- mice. Ongoing studies will identify the molecular basis of the effect of Mn, including changes to DAergic metabolism and transport and post-translational modification to the DAT. These findings demonstrate that alterations in T1W relaxation times, as measured by MRR, may serve as an early biomarker for Mn neurotoxicity. This neuroimaging approach exhibits remarkable accuracy in identifying Mn-susceptible brain regions, with a spatial resolution and sensitivity that surpasses current conventional dissection and mass spectrometry approaches. The capability to label and map TH and cFos expression across the entire brain provides insights into whole-brain neuronal activation and its connections to functional neural circuits and behavior following amphetamine and methylphenidate administration.

Keywords: manganese, environmental toxicology, dopamine dysfunction, biomarkers, drinking water, light sheet microscopy, magnetic resonance relaxometry (MRR)

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Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

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Time history dynamic analysis of structures is considered as an exact method while being computationally intensive. Filtration of earthquake strong ground motions applying wavelet transform is an approach towards reduction of computational efforts, particularly in optimization of structures against seismic effects. Wavelet transforms are categorized into continuum and discrete transforms. Since earthquake strong ground motion is a discrete function, the discrete wavelet transform is applied in the present paper. Wavelet transform reduces analysis time by filtration of non-effective frequencies of strong ground motion. Filtration process may be repeated several times while the approximation induces more errors. In this paper, strong ground motion of earthquake has been filtered once applying each wavelet. Strong ground motion of Northridge earthquake is filtered applying various wavelets and dynamic analysis of sampled shear and moment frames is implemented. The error, regarding application of each wavelet, is computed based on comparison of dynamic response of sampled structures with exact responses. Exact responses are computed by dynamic analysis of structures applying non-filtered strong ground motion.

Keywords: wavelet transform, computational error, computational duration, strong ground motion data

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Authors: Malo Pocheau-Lesteven, Olivier Le Maître

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Engineering and optimisation of complex systems is often achieved through multi-disciplinary analysis of the system, where each subsystem is modeled and interacts with other subsystems to model the complete system. The coherence of the output of the different sub-systems is achieved through the use of compatibility constraints, which enforce the coupling between the different subsystems. Due to the complexity of some sub-systems and the computational cost of evaluating their respective models, it is often necessary to build surrogate models of these subsystems to allow repeated evaluation these subsystems at a relatively low computational cost. In this paper, gaussian processes are used, as their probabilistic nature is leveraged to evaluate the likelihood of satisfying the compatibility constraints. This paper presents infilling strategies to build accurate surrogate models of the subsystems in areas where they are likely to meet the compatibility constraint. It is shown that these infilling strategies can reduce the computational cost of building surrogate models for a given level of accuracy. An application of these methods to velocity prediction programs used in offshore racing naval architecture further demonstrates these method's applicability in a real engineering context. Also, some examples of the application of uncertainty quantification to field of naval architecture are presented.

Keywords: infilling strategy, gaussian process, multi disciplinary analysis, velocity prediction program

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Authors: Mahendra Singh, Narasimhareddy Ravuru

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For the past decade, the production of biodiesel has significantly increased along with its by-product, glycerol. Biodiesel-derived glycerol massive entry into the glycerol market has caused its value to plummet. Newer ways to utilize the glycerol by-product must be implemented or the biodiesel industry will face serious economic problems. The biodiesel industry should consider steam reforming glycerol to produce hydrogen gas. Steam reforming is the most efficient way of producing hydrogen and there is a lot of demand for it in the petroleum and chemical industries. This study investigates the feasibility of glycerol steam reforming in an industrial sized fixed bed reactor. In this paper, using computational fluid dynamic (CFD) simulations, the extent of the transport resistances that would occur in an industrial sized reactor can be visualized. An important parameter in reactor design is the size of the catalyst particle. The size of the catalyst cannot be too large where transport resistances are too high, but also not too small where an extraordinary amount of pressure drop occurs. The goal of this paper is to find the best catalyst size under various flow rates that will result in the highest conversion. Computational fluid dynamics simulated the transport resistances and a pseudo-homogenous reactor model was used to evaluate the pressure drop and conversion. CFD simulations showed that glycerol steam reforming has strong internal diffusion resistances resulting in extremely low effectiveness factors. In the pseudo-homogenous reactor model, the highest conversion obtained with a Reynolds number of 100 (29.5 kg/h) was 9.14% using a 1/6 inch catalyst diameter. Due to the low effectiveness factors and high carbon deposition rates, a fluidized bed is recommended as the appropriate reactor to carry out glycerol steam reforming.

Keywords: computational fluid dynamic, fixed bed reactor, glycerol, steam reforming, biodiesel

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Authors: Nenny Harijani, Dhandy Koesoemo Wardhana

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The aim of this study is to know the bacteriocin as antimicrobial activity produced by Lactic Acid Bacteria (LAB) as Antibacterial of Sub Clinic Mastitis on Dairy Cows. The antimicrobial is produced by LAB which isolates from cattle intestine can inhibit the growth Staphylococcus aureus, Steptocococcus agalactiae an Escherichia coli which were caused by dairy cattle subclinical mastitis. The failure of this bacteria growth was indicated by the formation of a clear zone surrounding the colonies on Brain Heart Infusion Agar plate. The bacteriocin was produced by Lactic Acid Bacteria (LAB) as antimicrobial, which could inhibit the growth of indicator bacteria Staphylococcus aureus, S.aglactiae and E.coli. This study was also developed bacteriocin to be used as a therapeutic of subclinical mastitis on dairy cows. The method used in this study was isolation, selection and identification of LAB using Mann Rogosa Sharp Medium, followed by characterization of the bacteriocin produced by LAB. The result of the study showed that bacteriocin isolated from beef cattle’s intestine could inhibit the growth Staphylococcus aureus, S. agalactiae, an Escherichia coli, which was indicated by clear zone surrounding the colonies on Brain Heart Infusion Agar plate. Characteristics of bacteriocin were heat-stable exposed to 80 0C for 30 minutes and 100 ⁰C for 15 minutes and inactivated by proteolytic enzymes such as trypsin. This approach has suggested the development of bacteriocin as a therapeutic agent for subclinical mastitis in dairy cattle.

Keywords: lactic acid bacteria, bacteriocin, staphylococcus aureus, S. agalactiae, E. coli, sub

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Authors: Indri Mahadiraka Rumamby, R. R. Dwinanti Rika Marthanty, Jessica Sjah

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Smoothed particle hydrodynamics (SPH) was originally created to simulate nonaxisymmetric phenomena in astrophysics. However, this method still has several shortcomings, namely the high computational cost required to model values with high resolution and problems with boundary conditions. The difficulty of modeling boundary conditions occurs because the SPH method is influenced by particle deficiency due to the integral of the kernel function being truncated by boundary conditions. This research aims to answer if SPH modeling with a focus on boundary layer interactions and continuous flow can produce quantifiably accurate values with low computational cost. This research will combine algorithms and coding in the main program of meandering river, continuous flow algorithm, and solid-fluid algorithm with the aim of obtaining quantitatively accurate results on solid-fluid interactions with the continuous flow on a meandering channel using the SPH method. This study uses the Fortran programming language for modeling the SPH (Smoothed Particle Hydrodynamics) numerical method; the model is conducted in the form of a U-shaped meandering open channel in 3D, where the channel walls are soil particles and uses a continuous flow with a limited number of particles.

Keywords: smoothed particle hydrodynamics, computational fluid dynamics, numerical simulation, fluid mechanics

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Authors: Alexander N. Savostyanov, Tatiana A. Dolgorukova, Elena A. Esipenko, Mikhail S. Zaleshin, Margherita Malanchini, Anna V. Budakova, Alexander E. Saprygin, Tatiana A. Golovko, Yulia V. Kovas

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EEG correlates of mathematical and trait anxiety level were studied in 52 healthy Russian-speakers during execution of error-recognition tasks with lexical, arithmetic and algebraic conditions. Event-related spectral perturbations were used as a measure of brain activity. The ERSP plots revealed alpha/beta desynchronizations within a 500-3000 ms interval after task onset and slow-wave synchronization within an interval of 150-350 ms. Amplitudes of these intervals reflected the accuracy of error recognition, and were differently associated with the three conditions. The correlates of anxiety were found in theta (4-8 Hz) and beta2 (16-20 Hz) frequency bands. In theta band the effects of mathematical anxiety were stronger expressed in lexical, than in arithmetic and algebraic condition. The mathematical anxiety effects in theta band were associated with differences between anterior and posterior cortical areas, whereas the effects of trait anxiety were associated with inter-hemispherical differences. In beta1 and beta2 bands effects of trait and mathematical anxiety were directed oppositely. The trait anxiety was associated with increase of amplitude of desynchronization, whereas the mathematical anxiety was associated with decrease of this amplitude. The effect of mathematical anxiety in beta2 band was insignificant for lexical condition but was the strongest in algebraic condition. EEG correlates of anxiety in theta band could be interpreted as indexes of task emotionality, whereas the reaction in beta2 band is related to tension of intellectual resources.

Keywords: EEG, brain activity, lexical and numerical error-recognition tasks, mathematical and trait anxiety

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Authors: Aymen Laadhari, Gábor Székely

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In this work, the hemodynamics in the sinuses of Valsalva after Transcatheter Aortic Valve Implantation is numerically examined. We focus on the physical results in the two-dimensional case. We use a finite element methodology based on a Lagrange multiplier technique that enables to couple the dynamics of blood flow and the leaflets’ movement. A massively parallel implementation of a monolithic and fully implicit solver allows more accuracy and significant computational savings. The elastic properties of the aortic valve are disregarded, and the numerical computations are performed under physiologically correct pressure loads. Computational results depict that blood flow may be subject to stagnation in the lower domain of the sinuses of Valsalva after Transcatheter Aortic Valve Implantation.

Keywords: hemodynamics, simulations, stagnation, valve

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Authors: Elham Bagheri, Yalda Mohsenzadeh

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Image memorability refers to the phenomenon where certain images are more likely to be remembered by humans than others. It is a quantifiable and intrinsic attribute of an image. Understanding how visual perception and memory interact is important in both cognitive science and artificial intelligence. It reveals the complex processes that support human cognition and helps to improve machine learning algorithms by mimicking the brain's efficient data processing and storage mechanisms. To explore the computational underpinnings of image memorability, this study examines the relationship between an image's reconstruction error, distinctiveness in latent space, and its memorability score. A trained autoencoder is used to replicate human-like memorability assessment inspired by the visual memory game employed in memorability estimations. This study leverages a VGG-based autoencoder that is pre-trained on the vast ImageNet dataset, enabling it to recognize patterns and features that are common to a wide and diverse range of images. An empirical analysis is conducted using the MemCat dataset, which includes 10,000 images from five broad categories: animals, sports, food, landscapes, and vehicles, along with their corresponding memorability scores. The memorability score assigned to each image represents the probability of that image being remembered by participants after a single exposure. The autoencoder is finetuned for one epoch with a batch size of one, attempting to create a scenario similar to human memorability experiments where memorability is quantified by the likelihood of an image being remembered after being seen only once. The reconstruction error, which is quantified as the difference between the original and reconstructed images, serves as a measure of how well the autoencoder has learned to represent the data. The reconstruction error of each image, the error reduction, and its distinctiveness in latent space are calculated and correlated with the memorability score. Distinctiveness is measured as the Euclidean distance between each image's latent representation and its nearest neighbor within the autoencoder's latent space. Different structural and perceptual loss functions are considered to quantify the reconstruction error. The results indicate that there is a strong correlation between the reconstruction error and the distinctiveness of images and their memorability scores. This suggests that images with more unique distinct features that challenge the autoencoder's compressive capacities are inherently more memorable. There is also a negative correlation between the reduction in reconstruction error compared to the autoencoder pre-trained on ImageNet, which suggests that highly memorable images are harder to reconstruct, probably due to having features that are more difficult to learn by the autoencoder. These insights suggest a new pathway for evaluating image memorability, which could potentially impact industries reliant on visual content and mark a step forward in merging the fields of artificial intelligence and cognitive science. The current research opens avenues for utilizing neural representations as instruments for understanding and predicting visual memory.

Keywords: autoencoder, computational vision, image memorability, image reconstruction, memory retention, reconstruction error, visual perception

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Authors: Noah Emil Glisik

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Alcohol use disorder (AUD) presents significant health challenges worldwide and is particularly concerning in Slovenia, where high alcohol consumption contributes to elevated rates of comorbidities, including depression and suicide. This review examines emerging evidence linking gut microbiome dysbiosis to AUD, exploring whether gut microbiome alterations merely result from alcohol use or actively contribute to the persistence of addiction. Additionally, it discusses how microbial changes may influence psychological symptoms, including anxiety and depressive states, which are closely associated with suicidality in this population. To address gaps in existing research, a systematic literature search was conducted through PubMed, Web of Science, and ScienceDirect. Inclusion criteria focused on studies examining gut microbiome changes in AUD, particularly those assessing gut-brain axis interactions and microbial species impacting inflammation and neurotransmitter pathways. Studies were excluded if they lacked peer review or did not specifically assess microbiome effects on mental health outcomes. A qualitative literature review approach was applied, synthesizing findings into key themes on microbial changes, neuroinflammatory pathways, and treatment implications. Data were organized into tables to provide a clear comparison of microbiota alterations across studies, highlighting specific bacterial species and their potential effects on AUD. This review emphasizes patterns in AUD patients, where reductions in anti-inflammatory species, such as Faecalibacterium prausnitzii and Roseburia intestinalis, coincide with increases in pro-inflammatory bacteria like Enterococcus faecalisand Lactobacillus rhamnosus. These shifts contribute to increased gut permeability and systemic inflammation, potentially influencing the kynurenine pathway, which is linked to depressive symptoms and elevated alcohol cravings. Furthermore, the review explores the potential of probiotic therapies targeting these microbial imbalances as adjunctive treatments for AUD, particularly those focusing on strains that support anti-inflammatory pathways and gut barrier integrity. Restoring microbial homeostasis through probiotics or fecal microbiota transplantation may not only reduce inflammation but also alleviate mental health symptoms associated with addiction, including suicidality. The findings underscore the need for further clinical trials assessing microbiome-targeted therapies as innovative, multifaceted approaches to AUD treatment in Slovenia and beyond.

Keywords: alcohol use disorder, gut-brain axis, microbiome dysbiosis, probiotic therapy.

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Authors: J. Joy, T. H. New, I. H. Ibrahim

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A computational study on bio-inspired NACA634-021 hydrofoils with leading-edge protuberances has been carried out to investigate their hydrodynamic flow control characteristics at a Reynolds number of 14,000 and different angles-of-attack. The numerical simulations were performed using ANSYS FLUENT and based on Reynolds-Averaged Navier-Stokes (RANS) solver mode incorporated with k-ω Shear Stress Transport (SST) turbulence model. The results obtained indicate varying flow phenomenon along the peaks and troughs over the span of the hydrofoils. Compared to the baseline hydrofoil with no leading-edge protuberances, the leading-edge modified hydrofoils tend to reduce flow separation extents along the peak regions. In contrast, there are increased flow separations in the trough regions of the hydrofoil with leading-edge protuberances. Interestingly, it was observed that dissimilar flow separation behaviour is produced along different peak- or trough-planes along the hydrofoil span, even though the troughs or peaks are physically similar at each interval for a particular hydrofoil. Significant interactions between adjacent flow structures produced by the leading-edge protuberances have also been observed. These flow interactions are believed to be responsible for the dissimilar flow separation behaviour along physically similar peak- or trough-planes.

Keywords: computational fluid dynamics, flow separation control, hydrofoils, leading-edge protuberances

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Authors: Imane Benghalia, Mohammed Zamoum, Rachid Boucetta

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Hydrodynamic cavitation is a complex physical phenomenon that appears in hydraulic systems (pumps, turbines, valves, Venturi tubes, etc.) when the fluid pressure decreases below the saturated vapor pressure. The works carried out in this study aimed to get a better understanding of the cavitating flow phenomena. For this, we have numerically studied a cavitating bubbly flow through a Venturi nozzle. The cavitation model is selected and solved using a commercial computational fluid dynamics (CFD) code. The obtained results show the effect of the inlet pressure (10, 7, 5, and 2 bars) of the Venturi on pressure, the velocity of the fluid flow, and the vapor fraction. We found that the inlet pressure of the Venturi strongly affects the evolution of the pressure, velocity, and vapor fraction formation in the cavitating flow.

Keywords: cavitating flow, CFD, phase change, venturi

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Authors: Muhammad Bilal, Amelia Jane Llyod, Habsah Mohamad, Jia Hui Wong, Abdul Aziz Mohamed Yusoff, Jafri Malin Abdullah, Jingli Zhang

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Epilepsy is one of the major brain afflictions occurs with uncontrolled excitation of cortex; disturbed 50 million of world’s population. About 25 percent of patients subjected to adverse effects from antiepileptic drugs (AEDs) such as depression, nausea, tremors, gastrointestinal symptoms, osteoporosis, dizziness, weight change, drowsiness, fatigue are commonly observed indications; therefore, new drugs are required to cure epilepsy. GABA is principle inhibitory neurotransmitter, control excitation of the brain. Mutation or dysfunction of GABA receptor is one of the primary causes of epilepsy, which is confirmed from many acquired models of epilepsy like traumatic brain injury, kindling, and status epilepticus models of epilepsy. GABA receptor has 3 distinct types such as GABA (A), GABA (B), GABA(C).GABA (A) receptor has 20 different subunits, α1β2γ2 subunits composition of GABA (A) receptor is the most used combination of subunits for screening of compounds against epilepsy. We expressed α1β2γ2s subunits of GABA (A) Receptor in Xenopus leavis oocytes and examined the enhancement potential of 4-Hydroxybenzoic acid compound on GABA (A) receptor via two-electrode voltage clamp current recording technique. Bamboo shoots are the young, tender offspring of bamboo, which are usually harvested after a cultivating period of 2 weeks. Proteins, acids, fat, starch, carbohydrate, fatty acid, vitamin, dietary fiber, and minerals are the major constituent found systematically in bamboo shoots. These shoots reported to have anticancer, antiviral, antibacterial activity, also possess antioxidant properties due to the presence of phenolic compounds. Student t-test analysis suggested that 4- hydroxybenzoic acid positively allosteric GABA (A) receptor, increased normalized current amplitude to 1.0304±0.0464(p value 0.032) compared with vehicle. 4-Hydrobenzoic acid, a compound from Dendrocalamus Asper bamboo shoot gives new insights for future studies on bamboo shoots with motivation for extraction of more compounds to investigate their effects on human and rodents against epilepsy, insomnia, and anxiety.

Keywords: α1β2γ2S, antiepileptic, bamboo shoots, epilepsy GABA (A) receptor, two-microelectrode voltage clamp, xenopus laevis oocytes

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Authors: Norhashidah Hj. Mohd Ali, Teng Wai Ping

Abstract:

In this paper, we present a high order group explicit method in solving the two dimensional Helmholtz equation. The presented method is derived from a nine-point fourth order finite difference approximation formula obtained from a 45-degree rotation of the standard grid which makes it possible for the construction of iterative procedure with reduced complexity. The developed method will be compared with the existing group iterative schemes available in literature in terms of computational time, iteration counts, and computational complexity. The comparative performances of the methods will be discussed and reported.

Keywords: explicit group method, finite difference, helmholtz equation, rotated grid, standard grid

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Authors: M. H. Alhajeri, Hamad M. Alhajeri, A. H. Alenezi

Abstract:

This paper reports a Computational Fluid Dynamics (CFD) investigation for a high-temperature high-pressure filtration (ceramic candle filter). However, parallel flow to the filter is considered in this study. Different face (filtration) velocities are examined using the CFD code, FLUENT. Different sizes of particles are tracked through the domain to find the height at which the particles will impinge on the filter surface. Furthermore, particle distribution around the filter (or filter cake) is studied to design efficient cleaning mechanisms. Gravity effect to the particles with various inlet velocities and pressure drop are both considered. In the CFD study, it is found that the gravity influence should not be ignored if the particle sizes exceed 1 micron.

Keywords: fluid flow, CFD, filtration, HTHP

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Authors: Ashish Kumar Agrahari, Amit Kumar

Abstract:

Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal blood disorder that manifests with hemolytic anemia, thrombosis, and peripheral blood cytopenias. The disease is caused by the deficiency of two glycosylphosphatidylinositols (GPI)-anchored proteins (CD55 and CD59) in the hemopoietic stem cells. The deficiency of GPI-anchored proteins has been associated with the somatic mutations in phosphatidylinositol glycan class A (PIGA). However, the mutations that do not cause PNH is associated with the multiple congenital anomalies-hypotonia-seizures syndrome 2 (MCAHS2). To best of our knowledge, no computational study has been performed to explore the atomistic level impact of PIGA mutations on the structure and dynamics of the protein. In the current work, we are mainly interested to get insights into the molecular mechanism of PIGA mutations. In the initial step, we screened the most pathogenic mutations from the pool of publicly available mutations. Further, to get a better understanding, pathogenic mutations were mapped to the modeled structure and subjected to 50ns molecular dynamics simulation. Our computational study suggests that four mutations are highly vulnerable to altering the structural conformation and stability of the PIGA protein, which illustrates its association with PNH and MCAHS2 phenotype.

Keywords: homology modeling, molecular dynamics simulation, missense mutations PNH, MCAHS2, PIGA

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Authors: Troy M. Houser

Abstract:

The successor representation balances flexible and efficient reinforcement learning by learning to predict the future, given the present. As such, the successor representation models stimuli as what future states they lead to. Therefore, two stimuli that are perceptually dissimilar but lead to the same future state will come to be represented more similarly. This is very similar to an older behavioral paradigm -the acquired equivalence paradigm, which measures the generalization of learned associations. Here, we test via computational modeling the plausibility that the successor representation is the mechanism by which people generalize knowledge learned in the acquired equivalence paradigm. Computational evidence suggests that this is a plausible mechanism for acquired equivalence and thus can guide future empirical work on individual differences in associative-based generalization.

Keywords: acquired equivalence, successor representation, generalization, decision-making

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Authors: Nagaratna Rajur, J. D. Mallapur, Y. B. Kirankumar

Abstract:

The security in mobile communication is very different from the internet or telecommunication, because of its poor user interface and limited processing capacity, as well as combination of complex network protocols. Hence, it poses a challenge for less memory usage and low computation speed based security system. Security involves all the activities that are undertaken to protect the value and on-going usability of assets and the integrity and continuity of operations. An effective network security strategies requires identifying threats and then choosing the most effective set of tools to combat them. Cryptography is a simple and efficient way to provide security in communication. RSA is an asymmetric key approach that is highly reliable and widely used in internet communication. However, it has not been efficiently implemented in mobile communication due its computational complexity and large memory utilization. The proposed algorithm modifies the current RSA to be useful in mobile communication by reducing its computational complexity and memory utilization.

Keywords: M-RSA, sensor networks, sensor applications, security

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Authors: Deepanjali Gurav, Kun Qian

Abstract:

In-vitro metabolic diagnosis relies on designed materials-based analytical platforms for detection of selected metabolites in biological samples, which has a key role in disease detection and therapeutic evaluation in clinics. However, the basic challenge deals with developing a simple approach for metabolic analysis in bio-samples with high sample complexity and low molecular abundance. In this work, we report a designer plasmonic nanoshells based platform for direct detection of small metabolites in clinical samples for in-vitro metabolic diagnostics. We first synthesized a series of plasmonic core-shell particles with tunable nanoshell structures. The optimized plasmonic nanoshells as new matrices allowed fast, multiplex, sensitive, and selective LDI MS (Laser desorption/ionization mass spectrometry) detection of small metabolites in 0.5 μL of bio-fluids without enrichment or purification. Furthermore, coupling with isotopic quantification of selected metabolites, we demonstrated the use of these plasmonic nanoshells for disease detection and therapeutic evaluation in clinics. For disease detection, we identified patients with postoperative brain infection through glucose quantitation and daily monitoring by cerebrospinal fluid (CSF) analysis. For therapeutic evaluation, we investigated drug distribution in blood and CSF systems and validated the function and permeability of blood-brain/CSF-barriers, during therapeutic treatment of patients with cerebral edema for pharmacokinetic study. Our work sheds light on the design of materials for high-performance metabolic analysis and precision diagnostics in real cases.

Keywords: plasmonic nanoparticles, metabolites, fingerprinting, mass spectrometry, in-vitro diagnostics

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Authors: P. Deepak Kumar, P. R. Maiti

Abstract:

In recent years, sediment scour near bridge piers and abutment is a serious problem which causes nationwide concern because it has resulted in more bridge failures than other causes. Scour is the formation of scour hole around the structure mounted on and embedded in erodible channel bed due to the erosion of soil by flowing water. The formation of scour hole around the structures depends upon shape and size of the pier, depth of flow as well as angle of attack of flow and sediment characteristics. The flow characteristics around these structures change due to man-made obstruction in the natural flow path which changes the kinetic energy of the flow around these structures. Excessive scour affects the stability of the foundation of the structure by the removal of the bed material. The accurate estimation of scour depth around bridge pier is very difficult. The foundation of bridge piers have to be taken deeper and to provide sufficient anchorage length required for stability of the foundation. In this study, computational model simulations using a 3D Computational Fluid Dynamics (CFD) model were conducted to examine the mechanism of scour around a cylindrical pier. Subsequently, the flow characteristics around these structures are presented for different flow conditions. Mechanism of scouring phenomenon, the formation of vortex and its consequent effect is discussed for a straight channel. Effort was made towards estimation of scour depth around bridge piers under different flow conditions.

Keywords: bridge pier, computational fluid dynamics, multigrid, pier shape, scour

Procedia PDF Downloads 297