Search results for: multiscale entropy

Authors: Lei Li, Ming M. Chai, Xiao X. Lu, Jia W. Wang

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The mixing process of two liquid layers in a cylindrical container includes the upper liquid with higher density rushing into the lower liquid with lighter density, the lower liquid rising into the upper liquid, meanwhile the two liquid layers having interactions with each other, forming vortices, spreading or dispersing in others, entraining or mixing with others. It is a complex process constituted of flow instability, turbulent mixing and other multiscale physical phenomena and having a fast evolution velocity. In order to explore the mechanism of the process and make further investigations, some experiments about the interfacial instability and mixing behavior between two liquid layers bounded in different volumes are carried out, applying the planar laser induced fluorescence (PLIF) and the high speed camera (HSC) techniques. According to the results, the evolution of interfacial instability between immiscible liquid develops faster than theoretical rate given by the Rayleigh-Taylor Instability (RTI) theory. It is reasonable to conjecture that some mechanisms except the RTI play key roles in the mixture process of two liquid layers. From the results, it is shown that the invading velocity of the upper liquid into the lower liquid does not depend on the upper liquid's volume (height). Comparing to the cases that the upper and lower containers are of identical diameter, in the case that the lower liquid volume increases to larger geometric space, the upper liquid spreads and expands into the lower liquid more quickly during the evolution of interfacial instability, indicating that the container wall has important influence on the mixing process. In the experiments of miscible liquid layers’ mixing, the diffusion time and pattern of the liquid interfacial mixing also does not depend on the upper liquid's volumes, and when the lower liquid volume increases to larger geometric space, the action of the bounded wall on the liquid falling and rising flow will decrease, and the liquid interfacial mixing effects will also attenuate. Therefore, it is also concluded that the volume weight of upper heavier liquid is not the reason of the fast interfacial instability evolution between the two liquid layers and the bounded wall action is limited to the unstable and mixing flow. The numerical simulations of the immiscible liquid layers’ interfacial instability flow using the VOF method show the typical flow pattern agree with the experiments. However the calculated instability development is much slower than the experimental measurement. The numerical simulation of the miscible liquids’ mixing, which applying Fick’s diffusion law to the components’ transport equation, shows a much faster mixing rate than the experiments on the liquids’ interface at the initial stage. It can be presumed that the interfacial tension plays an important role in the interfacial instability between the two liquid layers bounded in finite volume.

Keywords: interfacial instability and mixing, two liquid layers, Planar Laser Induced Fluorescence (PLIF), High Speed Camera (HSC), interfacial energy and tension, Cahn-Hilliard Navier-Stokes (CHNS) equations

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Authors: A. Dinelka Panagoda, Bathiya Bandara, Chamod Wijetunga, Chathura Malinda, Lakmal Rupasinghe, Chethana Liyanapathirana

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This research takes us forward with the concepts of Federated Learning and Software-Defined Networking (SDN) to introduce an efficient malware detection technique and provide a mitigation mechanism to give birth to a resilient and automated healthcare sector network system by also adding the feature of extended privacy preservation. Due to the daily transformation of new malware attacks on hospital Integrated Clinical Environment (ICEs), the healthcare industry is at an undefinable peak of never knowing its continuity direction. The state of blindness by the array of indispensable opportunities that new medical device inventions and their connected coordination offer daily, a factor that should be focused driven is not yet entirely understood by most healthcare operators and patients. This solution has the involvement of four clients in the form of hospital networks to build up the federated learning experimentation architectural structure with different geographical participation to reach the most reasonable accuracy rate with privacy preservation. While the logistic regression with cross-entropy conveys the detection, SDN comes in handy in the second half of the research to stack up the initial development phases of the system with malware mitigation based on policy implementation. The overall evaluation sums up with a system that proves the accuracy with the added privacy. It is no longer needed to continue with traditional centralized systems that offer almost everything but not privacy.

Keywords: software-defined network, federated learning, privacy, integrated clinical environment, decentralized learning, malware detection, malware mitigation

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Authors: J. J. Rickard, A. Belli, P. Goldberg Oppenheimer

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Medical diagnostics, environmental monitoring, homeland security and forensics increasingly demand specific and field-deployable analytical technologies for quick point-of-care diagnostics. Although technological advancements have made optical methods well-suited for miniaturization, a highly-sensitive detection technique for minute sample volumes is required. Raman spectroscopy is a well-known analytical tool, but has very weak signals and hence is unsuitable for trace level analysis. Enhancement via localized optical fields (surface plasmons resonances) on nanoscale metallic materials generates huge signals in surface-enhanced Raman scattering (SERS), enabling single molecule detection. This enhancement can be tuned by manipulation of the surface roughness and architecture at the sub-micron level. Nevertheless, the development and application of SERS has been inhibited by the irreproducibility and complexity of fabrication routes. The ability to generate straightforward, cost-effective, multiplex-able and addressable SERS substrates with high enhancements is of profound interest for SERS-based sensing devices. While most SERS substrates are manufactured by conventional lithographic methods, the development of a cost-effective approach to create nanostructured surfaces is a much sought-after goal in the SERS community. Here, a method is established to create controlled, self-organized, hierarchical nanostructures using electrohydrodynamic (HEHD) instabilities. The created structures are readily fine-tuned, which is an important requirement for optimizing SERS to obtain the highest enhancements. HEHD pattern formation enables the fabrication of multiscale 3D structured arrays as SERS-active platforms. Importantly, each of the HEHD-patterned individual structural units yield a considerable SERS enhancement. This enables each single unit to function as an isolated sensor. Each of the formed structures can be effectively tuned and tailored to provide high SERS enhancement, while arising from different HEHD morphologies. The HEHD fabrication of sub-micrometer architectures is straightforward and robust, providing an elegant route for high-throughput biological and chemical sensing. The superior detection properties and the ability to fabricate SERS substrates on the miniaturized scale, will facilitate the development of advanced and novel opto-fluidic devices, such as portable detection systems, and will offer numerous applications in biomedical diagnostics, forensics, ecological warfare and homeland security.

Keywords: hierarchical electrohydrodynamic patterning, medical diagnostics, point-of care devices, SERS

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Authors: Aleksandra Dudkowska, Gabriela Gic-Grusza

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Wind wave-induced sediment transport is an important multidimensional and multiscale dynamic process affecting coastal seabed changes and coastline evolution. The knowledge about sediment transport rate is important to solve many environmental and geotechnical issues. There are many types of sediment transport models but none of them is widely accepted. It is bacause the process is not fully defined. Another problem is a lack of sufficient measurment data to verify proposed hypothesis. There are different types of models for longshore sediment transport (LST, which is discussed in this work) and cross-shore transport which is related to different time and space scales of the processes. There are models describing bed-load transport (discussed in this work), suspended and total sediment transport. LST models use among the others the information about (i) the flow velocity near the bottom, which in case of wave-currents interaction in coastal zone is a separate problem (ii) critical bed shear stress that strongly depends on the type of sediment and complicates in the case of heterogeneous sediment. Moreover, LST rate is strongly dependant on the local environmental conditions. To organize existing knowledge a series of sediment transport models intercomparisons was carried out as a part of the project “Development of a predictive model of morphodynamic changes in the coastal zone”. Four classical one-grid-point models were studied and intercompared over wide range of bottom shear stress conditions, corresponding with wind-waves conditions appropriate for coastal zone in polish marine areas. The set of models comprises classical theories that assume simplified influence of turbulence on the sediment transport (Du Boys, Meyer-Peter & Muller, Ribberink, Engelund & Hansen). It turned out that the values of estimated longshore instantaneous mass sediment transport are in general in agreement with earlier studies and measurements conducted in the area of interest. However, none of the formulas really stands out from the rest as being particularly suitable for the test location over the whole analyzed flow velocity range. Therefore, based on the models discussed a new unified formula for longshore sediment transport rate estimation is introduced, which constitutes the main original result of this study. Sediment transport rate is calculated based on the bed shear stress and critical bed shear stress. The dependence of environmental conditions is expressed by one coefficient (in a form of constant or function) thus the model presented can be quite easily adjusted to the local conditions. The discussion of the importance of each model parameter for specific velocity ranges is carried out. Moreover, it is shown that the value of near-bottom flow velocity is the main determinant of longshore bed-load in storm conditions. Thus, the accuracy of the results depends less on the sediment transport model itself and more on the appropriate modeling of the near-bottom velocities.

Keywords: bedload transport, longshore sediment transport, sediment transport models, coastal zone

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Authors: Abobakr Khidir Ziyada, Cecilia Devi Wilfred

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In the present work, a new series of 3-propanenitrile imidazolium-based Room Temperature Ionic Liquids (RTILs), incorporating dioctyl sulfosuccinate (DOSS) were prepared by reacting imidazole with acrylonitrile and then reacting the product with allyl chloride, 2-chloroethanol, and benzyl chloride. After the reaction had been completed, metathesis reaction was carried out using sodium dioctyl sulfosuccinate. The densities and viscosities of the present RTILs were measured at atmospheric pressure at T=293.15 to 353.15 K, the refractive index was measured at T=293.15 to 333.15 K, whereas, the start and decomposition temperatures were determined at heating rate 10°C. min^-1. The thermal expansion coefficient, densities at a range of temperatures and pressures, molecular volume, molar refraction, standard entropy and the lattice energy of these RTILs were also estimated. The present RTILs showed higher densities, similar refractive indices, and higher viscosities compared to the other 1-alkyl-3-propanenitrile imidazolium-based RTILs. The densities of the present synthesized RTILs are lower compared to the other nitrile-functionalized ILs. These present RTILs showed a weak temperature dependence on the thermal expansion coefficients, αp=5.0 × 10^−4 to 7.50 × 10−4 K^-1. Empirical correlations were proposed to represent the present data on the physical properties. The lattice energy for the present RTILs was similar to other nitrile–based imidazolium RTILs. The present RTILs showed very high molar refraction when compared similar RTILs incorporating other anions.

Keywords: dioctyl sulfosuccinate, nitrile ILs, 3-propanenitrile, anion, room temperature ionic liquids, RTIL

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Authors: Shrikant Ghadage

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Study of shock waves generated in the Scramjet engine is typically restricted to pressure, temperature, density, entropy and Mach number variation across the shock wave. The present work discusses the impact of inlet shock wave angles on the specific impulse of the Scramjet engine. A mathematical analysis has done for the isentropic hypersonic flow of air flowing through a Scramjet with hydrogen fuel at an altitude of 30 km. Analysis has been done in order to get optimum shock wave angle to achieve maximum impulse. Since external drag has excluded from the analysis, the losses due to friction are not considered for the present analysis. When Mach number of the airflow at the entry of the nozzle reaches unity, then that flow is choked. This condition puts limitations on increasing the inlet shock wave angle. As inlet shock wave angle increases, speed of the flow entering into the nozzle decreases, which results in an increase in the specific impulse of the engine. When the speed of the flow at the entry of the nozzle reduces below sonic speed, then there is no further increase in the specific impulse of the engine. Here the Conclusion is the thrust and specific impulse of a scramjet engine, which increases gradually with an increase in inlet shock wave angle up to the condition when airflow speed reaches sonic velocity at the exit of the combustor. In addition to that, variation in drag force at the inlet of the scramjet and variation in hypersonic flow conditions at every stage of the scramjet also studied in order to understand variation on flow characteristics with respect to flow deflection angle. Essentially, it helps in designing inlet profile for the Scramjet engine to achieve optimum specific impulse.

Keywords: hypersonic flow, scramjet, shock waves, specific impulse, mathematical analysis

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Authors: Sun fang, Zhang Wenxin

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This paper establishes an evaluation index system for spatio-temporal patterns of urbanization, with the county as research unit. We use the Entropy Weight method, coefficient variance, the Theil index and ESDA-GIS to analyze spatial patterns and evolutionary characteristics of New-Type Urbanization in the Central Plains Economic Region (CPER) between 2000 and 2011. Results show that economic benefit, non-agricultural employment level and level of market development are the most important factors influencing the level of New-Type Urbanization in the CPER; overall regional differences in New-Type Urbanization have declined while spatial correlations have increased from 2000 to 2011. The overall spatial pattern has changed little, however; differences between the western and eastern areas of the CPER are clear, and the pattern of a strong west and weak east did not change significantly over the study period. Areas with high levels of New-Type Urbanization were mostly distributed along the Beijing-Guangzhou and LongHai Railways on both sides, a new influx of urbanization was tightly clustered around ZhengZhou in the Central Henan Urban Agglomeration, but this trend was found to be weakening slightly. The level of New-Type Urbanization in municipal districts was found to be much higher than it was in the county generally. Provincial borders experienced a lower rate of growth and a lower level of New-Type Urbanization than did any other areas, consistently forming clusters of cold spots and sub-cold spots. The analysis confirms that historical development, location, and diffusion effects of urban agglomeration are the main drivers of changes in New-Type Urbanization patterns in CPER.

Keywords: new-type urbanization, spatial pattern, central plains economic region, spatial evolution

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Authors: Akbar Gharbali, Ali Abbasian Ardekani, Afshin Mohammadi

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Introduction: Thyroid nodules have an incidence of 33-68% in the general population. More than 5-15% of these nodules are malignant. Early detection and treatment of thyroid nodules increase the cure rate and provide optimal treatment. Between the medical imaging methods, Ultrasound is the chosen imaging technique for assessment of thyroid nodules. The confirming of the diagnosis usually demands repeated fine-needle aspiration biopsy (FNAB). So, current management has morbidity and non-zero mortality. Objective: To explore diagnostic potential of automatic texture analysis (TA) methods in differentiation benign and malignant thyroid nodules by ultrasound imaging in order to help for reliable diagnosis and monitoring of the thyroid nodules in their early stages with no need biopsy. Material and Methods: The thyroid US image database consists of 70 patients (26 benign and 44 malignant) which were reported by Radiologist and proven by the biopsy. Two slices per patient were loaded in Mazda Software version 4.6 for automatic texture analysis. Regions of interests (ROIs) were defined within the abnormal part of the thyroid nodules ultrasound images. Gray levels within an ROI normalized according to three normalization schemes: N1: default or original gray levels, N2: +/- 3 Sigma or dynamic intensity limited to µ+/- 3σ, and N3: present intensity limited to 1% - 99%. Up to 270 multiscale texture features parameters per ROIs per each normalization schemes were computed from well-known statistical methods employed in Mazda software. From the statistical point of view, all calculated texture features parameters are not useful for texture analysis. So, the features based on maximum Fisher coefficient and the minimum probability of classification error and average correlation coefficients (POE+ACC) eliminated to 10 best and most effective features per normalization schemes. We analyze this feature under two standardization states (standard (S) and non-standard (NS)) with Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Non-Linear Discriminant Analysis (NDA). The 1NN classifier was performed to distinguish between benign and malignant tumors. The confusion matrix and Receiver operating characteristic (ROC) curve analysis were used for the formulation of more reliable criteria of the performance of employed texture analysis methods. Results: The results demonstrated the influence of the normalization schemes and reduction methods on the effectiveness of the obtained features as a descriptor on discrimination power and classification results. The selected subset features under 1%-99% normalization, POE+ACC reduction and NDA texture analysis yielded a high discrimination performance with the area under the ROC curve (Az) of 0.9722, in distinguishing Benign from Malignant Thyroid Nodules which correspond to sensitivity of 94.45%, specificity of 100%, and accuracy of 97.14%. Conclusions: Our results indicate computer-aided diagnosis is a reliable method, and can provide useful information to help radiologists in the detection and classification of benign and malignant thyroid nodules.

Keywords: ultrasound imaging, thyroid nodules, computer aided diagnosis, texture analysis, PCA, LDA, NDA

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Authors: Mohd Tariq, Shyamal K. Nandi, Indra D. Bhatt

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Paris polyphylla Smith (Family- Liliaceae; English name-Love apple: Local name- Satuwa) is an important folk medicinal herb of the Indian subcontinent, being a source of number of bioactive compounds for drug formulation. The rhizomes are widely used as antihelmintic, antispasmodic, digestive stomachic, expectorant and vermifuge, antimicrobial, anti-inflammatory, heart and vascular malady, anti-fertility and sedative. Keeping in view of this, the species is being constantly removed from nature for trade and various pharmaceuticals purpose, as a result, the availability of the species in its natural habitat is decreasing. In this context, it would be pertinent to conserve this species and reintroduce them in its natural habitat. Predictive distribution modelling of this species was performed in Western Himalayan Region. One such recent method is Ecological Niche Modelling, also popularly known as Species distribution modelling, which uses computer algorithms to generate predictive maps of species distributions in a geographic space by correlating the point distributional data with a set of environmental raster data. In case of P. polyphylla, and to understand its potential distribution zones and setting up of artificial introductions, or selecting conservation sites, and conservation and management of their native habitat. Among the different districts of Uttarakhand (28°05ˈ-31°25ˈ N and 77°45ˈ-81°45ˈ E) Uttarkashi, Rudraprayag, Chamoli, Pauri Garhwal and some parts of Bageshwar, 'Maximum Entropy' (Maxent) has predicted wider potential distribution of P. polyphylla Smith. Distribution of P. polyphylla is mainly governed by Precipitation of Driest Quarter and Mean Diurnal Range i.e., 27.08% and 18.99% respectively which indicates that humidity (27%) and average temperature (19°C) might be suitable for better growth of Paris polyphylla.

Keywords: biodiversity conservation, Indian Himalayan region, Paris polyphylla, predictive distribution modelling

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Authors: Samsher Gautam, Apoorva Roy, Bhuvan Aggarwal

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Vapor absorption refrigeration systems can replace vapor compression systems in many applications as they can operate on a low-grade heat source and are environment-friendly. Widely used refrigerants such as CFCs and HFCs cause significant global warming. Natural refrigerants can be an alternative to them, among which carbon dioxide is promising for use in automotive air conditioning systems. Its inherent safety, ability to withstand high pressure and high heat transfer coefficient coupled with easy availability make it a likely choice for refrigerant. Various properties of the ionic liquid [bmim][PF₆], such as non-toxicity, stability over a wide temperature range and ability to dissolve gases like carbon dioxide, make it a suitable absorbent for a vapor absorption refrigeration system. In this paper, an absorption chiller consisting of a generator, condenser, evaporator and absorber was studied at an operating temperature of 70⁰C. A thermodynamic model was set up using the Peng-Robinson equations of state to predict the behavior of the refrigerant and absorbent pair at different points in the system. A MATLAB code was used to obtain the values of enthalpy and entropy at selected points in the system. The exergy destruction in each component and exergetic coefficient of performance (ECOP) of the system were calculated by performing an exergy analysis based on the second law of thermodynamics. Graphs were plotted between varying operating conditions and the ECOP obtained in each case. The effect of every component on the ECOP was examined. The exergetic coefficient of performance was found to be lesser than the coefficient of performance based on the first law of thermodynamics.

Keywords: [bmim][PF₆] as absorbent, carbon dioxide as refrigerant, exergy analysis, Peng-Robinson equations of state, vapor absorption refrigeration

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: anti-spoofing, CNN, fingerprint recognition, loss function, optimizer

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Authors: Milton Manyangadze, Joseph Govha, T. Bala Narsaiah, Ch. Shilpa Chakra

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The availability and access to fresh water is today a serious global challenge. This has been a direct result of factors such as the current rapid industrialization and industrial growth, persistent droughts in some parts of the world, especially in the sub-Saharan Africa as well as population growth. Growth of the chemical processing industry has also seen an increase in the levels of pollutants in our water bodies which include heavy metals among others. Heavy metals are known to be dangerous to both human and aquatic life. As such, they have been linked to several diseases. This is mainly because they are highly toxic. They are also known to be bio accumulative and non-biodegradable. Lead for example, has been linked to a number of health problems which include damage of vital internal body systems like the nervous and reproductive system as well as the kidneys. From this background therefore, the removal of the toxic heavy metal, Pb2+ from waste water was investigated using nano silica hollow spheres (NSHS) as the adsorbent. Synthesis of NSHS was done using a three-stage process in which CaCO3 nanoparticles were initially prepared as a template. This was followed by treatment of the formed oxide particles with NaSiO3 to give a nanocomposite. Finally, the template was destroyed using 2.0M HCl to give NSHS. Characterization of the nanoparticles was done using analytical techniques like XRD, SEM, and TGA. For the adsorption process, both thermodynamic and equilibrium studies were carried out. Thermodynamic studies were carried out and the Gibbs free energy, Enthalpy and Entropy of the adsorption process were determined. The results revealed that the adsorption process was both endothermic and spontaneous. Equilibrium studies were also carried out in which the Langmuir and Freundlich isotherms were tested. The results showed that the Langmuir model best described the adsorption equilibrium.

Keywords: characterization, endothermic, equilibrium studies, Freundlich, Langmuir, nanoparticles, thermodynamic studies

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Authors: Saâd Oukkass, Abderrahim Bouftou, Rachid Ouchn, L. Lebrun, Miloudi Hlaibi

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We invariably exist in a world steeped in colors, whether in our clothing, food, cosmetics, or even medications. However, most of the dyes we use pose significant problems, being both harmful to the environment and resistant to degradation. Among these dyes, methylene blue and acid yellow 61 stand out, commonly used to dye various materials such as cotton, wood, and silk. Fortunately, various methods have been developed to treat and remove these polluting dyes, among which membrane processes play a prominent role. These methods are praised for their low energy consumption, ease of operation, and their ability to achieve effective separation of components. Adsorption on activated carbon is also a widely employed technique, complementing the basic processes. It proves particularly effective in capturing and removing organic compounds from water due to its substantial specific surface area while retaining its properties unchanged. In the context of our study, we examined two crucial aspects. Firstly, we explored the possibility of selectively extracting methylene blue from a mixture containing another dye, acid yellow 61, using a polymer inclusion membrane (PIM) made of PVA. After characterizing the morphology and porosity of the membrane, we applied kinetic and thermodynamic models to determine the values of permeability (P), initial flux (J0), association constant (Kass), and apparent diffusion coefficient (D*). Subsequently, we measured activation parameters (activation energy (Ea), enthalpy (ΔH#ass), entropy (ΔS#)). Finally, we studied the effect of activated carbon on the processes carried out through the membrane, demonstrating a clear improvement. These results make the membrane developed in this study a potentially pivotal player in the field of membrane separation.

Keywords: dyes, methylene blue, membrane, activated carbon

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Authors: Saeid Gharechelou, Stuart Green, Fiona Cawkwell

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Hedgerow has an important role for a wide range of ecological habitats, landscape, agriculture management, carbon sequestration, wood production. Hedgerow detection accurately using satellite imagery is a challenging problem in remote sensing techniques, because in the special approach it is very similar to line object like a road, from a spectral viewpoint, a hedge is very similar to a forest. Remote sensors with very high spatial resolution (VHR) recently enable the automatic detection of hedges by the acquisition of images with enough spectral and spatial resolution. Indeed, recently VHR remote sensing data provided the opportunity to detect the hedgerow as line feature but still remain difficulties in monitoring the characterization in landscape scale. In this research is used the TerraSAR-x Spotlight and Staring mode with 3-5 m resolution in wet and dry season in the test site of Fermoy County, Ireland to detect the hedgerow by acquisition time of 2014-2015. Both dual polarization of Spotlight data in HH/VV is using for detection of hedgerow. The varied method of SAR image technique with try and error way by integration of classification algorithm like texture analysis, support vector machine, k-means and random forest are using to detect hedgerow and its characterization. We are applying the Shannon entropy (ShE) and backscattering analysis in single and double bounce in polarimetric analysis for processing the object-oriented classification and finally extracting the hedgerow network. The result still is in progress and need to apply the other method as well to find the best method in study area. Finally, this research is under way to ahead to get the best result and here just present the preliminary work that polarimetric image of TSX potentially can detect the hedgerow.

Keywords: TerraSAR-X, hedgerow detection, high resolution SAR image, dual polarization, polarimetric analysis

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Authors: Nikolaos Papadimas, Joanna Bennett, Amir Sakhaei, Timothy Dodwell

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Composite modeling of consolidation processes is playing an important role in the process and part design by indicating the formation of possible unwanted prior to expensive experimental iterative trial and development programs. Composite materials in their uncured state display complex constitutive behavior, which has received much academic interest, and this with different models proposed. Errors from modeling and statistical which arise from this fitting will propagate through any simulation in which the material model is used. A general hyperelastic polynomial representation was proposed, which can be readily implemented in various nonlinear finite element packages. In our case, FEniCS was chosen. The coefficients are assumed uncertain, and therefore the distribution of parameters learned using Markov Chain Monte Carlo (MCMC) methods. In engineering, the approach often followed is to select a single set of model parameters, which on average, best fits a set of experiments. There are good statistical reasons why this is not a rigorous approach to take. To overcome these challenges, A hierarchical Bayesian framework was proposed in which population distribution of model parameters is inferred from an ensemble of experiments tests. The resulting sampled distribution of hyperparameters is approximated using Maximum Entropy methods so that the distribution of samples can be readily sampled when embedded within a stochastic finite element simulation. The methodology is validated and demonstrated on a set of consolidation experiments of AS4/8852 with various stacking sequences. The resulting distributions are then applied to stochastic finite element simulations of the consolidation of curved parts, leading to a distribution of possible model outputs. With this, the paper, as far as the authors are aware, represents the first stochastic finite element implementation in composite process modelling.

Keywords: data-driven , material consolidation, stochastic finite elements, surrogate models

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Authors: Leng Jian-Wei, Wang Lai-Jun, Li Ye

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In order to measure and analyze the transportation situation within the counties of Shaanxi province over a certain period of time and to promote the province's future transportation planning and development, this paper proposes a reasonable layout plan and compares model rationality. The study uses entropy weight method to measure the transportation advantages of 107 counties in Shaanxi province from three dimensions: road network density, trunk line influence and location advantage in 2013 and 2021, and applies spatial autocorrelation analysis method to analyze the spatial layout and development trend of county-level transportation, and conducts ordinary least square (OLS)regression on transportation impact factors and other influencing factors. The paper also compares the regression fitting degree of the Geographically weighted regression(GWR) model and the OLS model. The results show that spatially, the transportation advantages of Shaanxi province generally show a decreasing trend from the Weihe Plain to the surrounding areas and mainly exhibit high-high clustering phenomenon. Temporally, transportation advantages show an overall upward trend, and the phenomenon of spatial imbalance gradually decreases. People's travel demands have changed to some extent, and the demand for rapid transportation has increased overall. The GWR model regression fitting degree of transportation advantages is 0.74, which is higher than the OLS regression model's fitting degree of 0.64. Based on the evolution of transportation advantages, it is predicted that this trend will continue for a period of time in the future. To improve the transportation advantages of Shaanxi province increasing the layout of rapid transportation can effectively enhance the transportation advantages of Shaanxi province. When analyzing spatial heterogeneity, geographic factors should be considered to establish a more reliable model

Keywords: traffic dominance, GWR model, spatial autocorrelation analysis, temporal and spatial evolution

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Authors: Sobia Mushtaq, Firdaus E. Bareen, Asma Tayyeb

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This study conducted to investigate the metal biosorption potential of indigenous Trichoderma species (T. harzianum KS05T01, T. longibrachiatum KS09T03, Trichoderma sp KS17T09., T. viridi KS17T011, T. atrobruneo KS21T014, and T. citrinoviride) that have been isolated from contaminated soil of Kasur Tannery Waste Management Agency. The effect of different biosorption parameters as initial metal ion concentration, pH, contact time , and temperature of incubation was investigated on the biosorption potential of these species. The metal removal efficiency and (E%) and metal uptake capacity (mg/g) increased along with the increase of initial metal concentration in media. The Trichoderma species can tolerate and survive under heavy metal stress up to 800mg/L. Among the two isotherm models were applied on the biosorption data, Langmuir isotherm model and Freundlich isotherm model, maximum correlation coefficients values (R 2 ) of 1was found for Langmuir model, which showed the better fitted model for the Trichoderma biosorption. The metal biosorption was increased with the increase of temperature and pH of the media. The maximum biosorption was observed between 25-30 o C and at pH 6.-7.5, while the biosorption rate was increased from 3-6 days of incubation, and then the rate of biosorption was slowed down. The biosorption data was better fitted for Pseudo kinetic first order during the initial days of biosorption. Thermodynamic parameters as standard Gibbs free energy (G), standard enthalpy change (H), and standard entropy (S) were calculated. The results confirmed the heavy metal biosorption by Trichoderma species was endothermic and spontaneous reaction in nature. The FTIR spectral analysis and SEM-EDX analysis of the treated and controlled mycelium revealed the changes in the active functional sites and morphological variations of the outer surface. The data analysis envisaged that high metal tolerance exhibited by Trichoderma species indicates its potential as efficacious and successful mediator for bioremediation of the heavy metal polluted environments.

Keywords: heavy metal, fungal biomass, biosorption, kinetics

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Authors: Joseph F. Cabrera, Rachael Dela Cruz

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This study specifically examines patterns that define ethnoracially diverse neighborhoods. Ethnoracial diversity is important as it facilitates cross-racial interactions within neighborhoods which have been theorized to be associated with such outcomes as intergroup harmony, the reduction of racial and ethnic prejudice and discrimination, and increases in racial tolerance. Los Angeles (LA) is an ideal location to study ethnoracial spatial patterns as it is one of the most ethnoracially diverse cities in the world. A large influx of Latinos, as well as Asians, have contributed to LA’s urban landscape becoming increasingly diverse over several decades. Our dataset contains all census tracts in Los Angeles County in 2016 and incorporates Census and ACS demographic and spatial data. We quantify ethnoracial diversity using a derivative of Simpson’s Diversity Index and utilize this measure to test previous literature that suggests Latinos are one of the key drivers of changing ethnoracial spatial patterns in Los Angeles. Preliminary results suggest that there has been an overall increase in ethnoracial diversity in Los Angeles neighborhoods over the past sixteen years. Patterns associated with this trend include decreases in predominantly white and black neighborhoods, increases in predominantly Latino and Asian neighborhoods, and a general decrease in the white populations of the most diverse neighborhoods. A similar pattern is seen in neighborhoods with large Latino increases- a decrease in white population, but with an increase in Asian and black populations. We also found support for previous research that suggests increases in Latino and Asian populations act as a buffer, allowing for black population increases without a sizeable decrease in the white population. Future research is needed to understand the underlying causes involved in many of the patterns and trends highlighted in this study.

Keywords: race, race and interaction, racial harmony, social interaction

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Authors: H. Hajimolahoseini, J. Hashemi, D. Redfearn

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Background: Catheter ablation is an effective therapy for symptomatic atrial fibrillation (AF). The intracardiac electrocardiogram (IEGM) collected during this procedure contains precious information that has not been explored to its full capacity. Novel processing techniques allow looking at these recordings from different perspectives which can lead to improved therapeutic approaches. In our previous study, we showed that variation in amplitude measured through Shannon Entropy could be used as an AF recurrence risk stratification factor in patients who received Ibutilide before the electrograms were recorded. The aim of this study is to further investigate the effect of Ibutilide on characteristics of the recorded signals from the left atrium (LA) of a patient with persistent AF before and after administration of the drug. Methods: The IEGMs collected from different intra-atrial sites of 12 patients were studied and compared before and after Ibutilide administration. First, the before and after Ibutilide IEGMs that were recorded within a Euclidian distance of 3 mm in LA were selected as pairs for comparison. For every selected pair of IEGMs, the Probability Distribution Function (PDF) of the amplitude in time domain and magnitude in frequency domain was estimated using the regression analysis. The PDF represents the relative likelihood of a variable falling within a specific range of values. Results: Our observations showed that in time domain, the PDF of amplitudes was fitted to a Gaussian distribution while in frequency domain, it was fitted to a Rayleigh distribution. Our observations also revealed that after Ibutilide administration, the IEGMs would have significantly narrower short-tailed PDFs both in time and frequency domains. Conclusion: This study shows that the PDFs of the IEGMs before and after administration of Ibutilide represents significantly different properties, both in time and frequency domains. Hence, by fitting the PDF of IEGMs in time domain to a Gaussian distribution or in frequency domain to a Rayleigh distribution, the effect of Ibutilide can easily be tracked using the statistics of their PDF (e.g., standard deviation) while this is difficult through the waveform of IEGMs itself.

Keywords: atrial fibrillation, catheter ablation, probability distribution function, time-frequency characteristics

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Authors: Kevin A. Droguett, Edwin G. Pérez, Denis Fuentealba, Margarita E. Aliaga, Angélica M. Fierro

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Supramolecular chemistry is a field of growing interest. Moreover, studying the formation of host-guest complexes between macrocycles and dyes is highly attractive due to their potential applications. Examples of the above are drug delivery, catalytic process, and sensing, among others. There are different dyes of interest in the literature; one example is the quinolinone derivatives. Those molecules have good optical properties and chemical and thermal stability, making them suitable for developing fluorescent probes. Secondly, several macrocycles can be seen in the literature. One example is the cucurbiturils. This water-soluble macromolecule family has a hydrophobic cavity and two identical carbonyl portals. Additionally, the thermodynamic analysis of those supramolecular systems could help understand the affinity between the host and guest, their interaction, and the main stabilization energy of the complex. In this work, two 7-(diethylamino) quinoline-2 (1H)-one derivative (QD1-2) and their interaction with cucurbit[7]uril (CB[7]) were studied from an experimental and in-silico point of view. For the experimental section, the complexes showed a 1:1 stoichiometry by HRMS-ESI and isothermal titration calorimetry (ITC). The inclusion of the derivatives on the macrocycle lends to an upward shift in the fluorescence intensity, and the pKa value of QD1-2 exhibits almost no variation after the formation of the complex. The thermodynamics of the inclusion complexes was investigated using ITC; the results demonstrate a non-classical hydrophobic effect with a minimum contribution from the entropy term and a constant binding on the order of 106 for both ligands. Additionally, dynamic molecular studies were carried out during 300 ns in an explicit solvent at NTP conditions. Our finding shows that the complex remains stable during the simulation (RMSD ~1 Å), and hydrogen bonds contribute to the stabilization of the systems. Finally, thermodynamic parameters from MMPBSA calculations were obtained to generate new computational insights to compare with experimental results.

Keywords: host-guest complexes, molecular dynamics, quinolin-2(1H)-one derivatives dyes, thermodynamics

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Authors: Yaolin Tian, Shanxiong Chen, Fujia Zhao, Xiaoyu Lin, Hailing Xiong

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Ancient books are significant culture inheritors and their background textures convey the potential history information. However, multi-style texture recovery of ancient books has received little attention. Restricted by insufficient ancient textures and complex handling process, the generation of ancient textures confronts with new challenges. For instance, training without sufficient data usually brings about overfitting or mode collapse, so some of the outputs are prone to be fake. Recently, image generation and style transfer based on deep learning are widely applied in computer vision. Breakthroughs within the field make it possible to conduct research upon multi-style texture recovery of ancient books. Under the circumstances, we proposed a network of layout analysis and image fusion system. Firstly, we trained models by using Deep Convolution Generative against Networks (DCGAN) to synthesize multi-style ancient textures; then, we analyzed layouts based on the Position Rearrangement (PR) algorithm that we proposed to adjust the layout structure of foreground content; at last, we realized our goal by fusing rearranged foreground texts and generated background. In experiments, diversified samples such as ancient Yi, Jurchen, Seal were selected as our training sets. Then, the performances of different fine-turning models were gradually improved by adjusting DCGAN model in parameters as well as structures. In order to evaluate the results scientifically, cross entropy loss function and Fréchet Inception Distance (FID) are selected to be our assessment criteria. Eventually, we got model M8 with lowest FID score. Compared with DCGAN model proposed by Radford at el., the FID score of M8 improved by 19.26%, enhancing the quality of the synthetic images profoundly.

Keywords: deep learning, image fusion, image generation, layout analysis

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Authors: P. Selyshchev

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Construction materials for nuclear facilities are operated under extreme thermal and radiation conditions. First of all, they are nuclear fuel, fuel assemblies, and reactor vessel. It places high demands on the control of their state, stability of their state, and their operating conditions. An irradiated material is a typical example of an open non-equilibrium system with nonlinear feedbacks between its elements. Fluxes of energy, matter and entropy maintain states which are far away from thermal equilibrium. The links that arise under irradiation are inherently nonlinear. They form the mechanisms of feed-backs that can lead to instability. Due to this instability the temperature of the sample, heat transfer, and the defect density can exceed the steady-state value in several times. This can lead to change of typical operation and an accident. Therefore, it is necessary to take into account the thermal instability to avoid the emergency situation. The point is that non-thermal energy can be accumulated in materials because irradiation produces defects (first of all these are vacancies and interstitial atoms), which are metastable. The stored energy is about energy of defect formation. Thus, an annealing of the defects is accompanied by releasing of non-thermal stored energy into thermal one. Temperature of the material grows. Increase of temperature results in acceleration of defect annealing. Density of the defects drops and temperature grows more and more quickly. The positive feed-back is formed and self-reinforcing annealing of radiation defects develops. To describe these phenomena a theoretical approach to thermal instability is developed via formalism of complex systems. We consider system of nonlinear differential equations for different components of microstructure and temperature. The qualitative analysis of this non-linear dynamical system is carried out. Conditions for development of instability have been obtained. Points of bifurcation have been found. Convenient way to represent obtained results is a set of phase portraits. It has been shown that different regimes of material state under irradiation can develop. Thus degradation of irradiated material can be limited by means of choice appropriate kind of evolution of materials under irradiation.

Keywords: irradiation, material, non-equilibrium state, nonlinear feed-back, thermal instability

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Authors: Abdelhalim. N. Mohammed, Mohammed. Y. Esmail

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In the course of recent decades, medical imaging has been dominated by the use of costly film media for review and archival of medical investigation, however due to developments in networks technologies and common acceptance of a standard digital imaging and communication in medicine (DICOM) another approach in light of World Wide Web was produced. Web technologies successfully used in telemedicine applications, the combination of web technologies together with DICOM used to design a web-based and open source DICOM viewer. The Web server allowance to inquiry and recovery of images and the images viewed/manipulated inside a Web browser without need for any preinstalling software. The dynamic site page for medical images visualization and processing created by using JavaScript and HTML5 advancements. The XAMPP ‘apache server’ is used to create a local web server for testing and deployment of the dynamic site. The web-based viewer connected to multiples devices through local area network (LAN) to distribute the images inside healthcare facilities. The system offers a few focal points over ordinary picture archiving and communication systems (PACS): easy to introduce, maintain and independently platforms that allow images to display and manipulated efficiently, the system also user-friendly and easy to integrate with an existing system that have already been making use of web technologies. The wavelet-based image compression technique on which 2-D discrete wavelet transform used to decompose the image then wavelet coefficients are transmitted by entropy encoding after threshold to decrease transmission time, stockpiling cost and capacity. The performance of compression was estimated by using images quality metrics such as mean square error ‘MSE’, peak signal to noise ratio ‘PSNR’ and compression ratio ‘CR’ that achieved (83.86%) when ‘coif3’ wavelet filter is used.

Keywords: DICOM, discrete wavelet transform, PACS, HIS, LAN

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Authors: Shrawan Baghel, Helen Cathcart, Biall J. O'Reilly

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Amorphous drug formulations have great potential to enhance solubility and thus bioavailability of BCS class II drugs. However, the higher free energy and molecular mobility of the amorphous form lowers the activation energy barrier for crystallization and thermodynamically drives it towards the crystalline state which makes them unstable. Accurate determination of the crystallization tendency/kinetics is the key to the successful design and development of such systems. In this study, dipyridamole (DPM) and cinnarizine (CNZ) has been selected as model compounds. Thermodynamic fragility (m_T) is measured from the heat capacity change at the glass transition temperature (Tg) whereas dynamic fragility (m_D) is evaluated using methods based on extrapolation of configurational entropy to zero 〖(m〗_(D_CE )), and heating rate dependence of Tg 〖(m〗_(D_Tg)). The mean relaxation time of amorphous drugs was calculated from Vogel-Tammann-Fulcher (VTF) equation. Furthermore, the correlation between fragility and glass forming ability (GFA) of model drugs has been established and the relevance of these parameters to crystallization of amorphous drugs is also assessed. Moreover, the crystallization kinetics of model drugs under isothermal conditions has been studied using Johnson-Mehl-Avrami (JMA) approach to determine the Avrami constant ‘n’ which provides an insight into the mechanism of crystallization. To further probe into the crystallization mechanism, the non-isothermal crystallization kinetics of model systems was also analysed by statistically fitting the crystallization data to 15 different kinetic models and the relevance of model-free kinetic approach has been established. In addition, the crystallization mechanism for DPM and CNZ at each extent of transformation has been predicted. The calculated fragility, glass forming ability (GFA) and crystallization kinetics is found to be in good correlation with the stability prediction of amorphous solid dispersions. Thus, this research work involves a multidisciplinary approach to establish fragility, GFA and crystallization kinetics as stability predictors for amorphous drug formulations.

Keywords: amorphous, fragility, glass forming ability, molecular mobility, mean relaxation time, crystallization kinetics, stability

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Authors: Mahdi Allaoua Seklab, Süleyman BaşTürk

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In the quest to enhance coastal environmental health, this study introduces a fully autonomous beach cleaning machine, a breakthrough in leveraging green energy and advanced artificial intelligence for ecological preservation. Designed to operate independently, the machine is propelled by a solar-powered system, underscoring a commitment to sustainability and the use of renewable energy in autonomous robotics. The vehicle's autonomous navigation is achieved through a sophisticated integration of LIDAR and a camera system, utilizing an SSD MobileNet V2 object detection model for accurate and real-time trash identification. The SSD framework, renowned for its efficiency in detecting objects in various scenarios, is coupled with the lightweight and precise highly MobileNet V2 architecture, making it particularly suited for the computational constraints of on-board processing in mobile robotics. Training of the SSD MobileNet V2 model was conducted on Google Colab, harnessing cloud-based GPU resources to facilitate a rapid and cost-effective learning process. The model was refined with an extensive dataset of annotated beach debris, optimizing the parameters using the Adam optimizer and a cross-entropy loss function to achieve high-precision trash detection. This capability allows the machine to intelligently categorize and target waste, leading to more effective cleaning operations. This paper details the design and functionality of the beach cleaning machine, emphasizing its autonomous operational capabilities and the novel application of AI in environmental robotics. The results showcase the potential of such technology to fill existing gaps in beach maintenance, offering a scalable and eco-friendly solution to the growing problem of coastal pollution. The deployment of this machine represents a significant advancement in the field, setting a new standard for the integration of autonomous systems in the service of environmental stewardship.

Keywords: autonomous beach cleaning machine, renewable energy systems, coastal management, environmental robotics

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Authors: Dario Milani, Guido Morgenthal

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Fluid dynamic computation of wind caused forces on bluff bodies e.g light flexible civil structures or high incidence of ground approaching airplane wings, is one of the major criteria governing their design. For such structures a significant dynamic response may result, requiring the usage of small scale devices as guide-vanes in bridge design to control these effects. The focus of this paper is on the numerical simulation of the bluff body problem involving multiscale phenomena induced by small scale devices. One of the solution methods for the CFD simulation that is relatively successful in this class of applications is the Vortex Particle Method (VPM). The method is based on a grid free Lagrangian formulation of the Navier-Stokes equations, where the velocity field is modeled by particles representing local vorticity. These vortices are being convected due to the free stream velocity as well as diffused. This representation yields the main advantages of low numerical diffusion, compact discretization as the vorticity is strongly localized, implicitly accounting for the free-space boundary conditions typical for this class of FSI problems, and a natural representation of the vortex creation process inherent in bluff body flows. When the particle resolution reaches the Kolmogorov dissipation length, the method becomes a Direct Numerical Simulation (DNS). However, it is crucial to note that any solution method aims at balancing the computational cost against the accuracy achievable. In the classical VPM method, if the fluid domain is discretized by Np particles, the computational cost is O(Np2). For the coupled FSI problem of interest, for example large structures such as long-span bridges, the aerodynamic behavior may be influenced or even dominated by small structural details such as barriers, handrails or fairings. For such geometrically complex and dimensionally large structures, resolving the complete domain with the conventional VPM particle discretization might become prohibitively expensive to compute even for moderate numbers of particles. It is possible to reduce this cost either by reducing the number of particles or by controlling its local distribution. It is also possible to increase the accuracy of the solution without increasing substantially the global computational cost by computing a correction of the particle-particle interaction in some regions of interest. In this paper different strategies are presented in order to extend the conventional VPM method to reduce the computational cost whilst resolving the required details of the flow. The methods include temporal sub stepping to increase the accuracy of the particles convection in certain regions as well as dynamically re-discretizing the particle map to locally control the global and the local amount of particles. Finally, these methods will be applied on a test case and the improvements in the efficiency as well as the accuracy of the proposed extension to the method are presented. The important benefits in terms of accuracy and computational cost of the combination of these methods will be thus presented as long as their relevant applications.

Keywords: adaptation, fluid dynamic, remeshing, substepping, vortex particle method

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Authors: Mikaela Kutrolli, Noah S. Pereira, Vanessa Scanlon, Mohamadmahdi Samandari, Ali Tamayol

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Bone tissue engineering has drawn significant attention and various biomaterials have been tested. Polymers such as polycaprolactone (PCL) offer excellent biocompatibility, reasonable mechanical properties, and biodegradability. However, PCL scaffolds suffer a critical drawback: a lack of micro/mesoporosity, affecting cell attachment, tissue integration, and mineralization. It also results in a slow degradation rate. While 3D-printing has addressed the issue of macroporosity through CAD-guided fabrication, PCL scaffolds still exhibit poor smaller-scale porosity. To overcome this, we generated composites of PCL, hydroxyapatite (HA), and powdered sucrose (PS). The latter serves as a sacrificial material to generate porous particles after sucrose dissolution. Additionally, we have incorporated dexamethasone (DEX) to boost the PCL osteogenic properties. The resulting scaffolds maintain controlled macroporosity from the lattice print structure but also develop micro/mesoporosity within PCL fibers when exposed to aqueous environments. The study involved mixing PS into solvent-dissolved PCL in different weight ratios of PS to PCL (70:30, 50:50, and 30:70 wt%). The resulting composite was used for 3D printing of scaffolds at room temperature. Printability was optimized by adjusting pressure, speed, and layer height through filament collapse and fusion test. Enzymatic degradation, porogen leaching, and DEX release profiles were characterized. Physical properties were assessed using wettability, SEM, and micro-CT to quantify the porosity (percentage, pore size, and interconnectivity). Raman spectroscopy was used to verify the absence of sugar after leaching. Mechanical characteristics were evaluated via compression testing before and after porogen leaching. Bone marrow stromal cells (BMSCs) behavior in the printed scaffolds was studied by assessing viability, metabolic activity, osteo-differentiation, and mineralization. The scaffolds with a 70% sugar concentration exhibited superior printability and reached the highest porosity of 80%, but performed poorly during mechanical testing. A 50% PS concentration demonstrated a 70% porosity, with an average pore size of 25 µm, favoring cell attachment. No trace of sucrose was found in Raman after leaching the sugar for 8 hours. Water contact angle results show improved hydrophilicity as the sugar concentration increased, making the scaffolds more conductive to cell adhesion. The behavior of bone marrow stromal cells (BMSCs) showed positive viability and proliferation results with an increasing trend of mineralization and osteo-differentiation as the sucrose concentration increased. The addition of HA and DEX also promoted mineralization and osteo-differentiation in the cultures. The integration of PS as porogen at a concentration of 50%wt within PCL scaffolds presents a promising approach to address the poor cell attachment and tissue integration issues of PCL in bone tissue engineering. The method allows for the fabrication of scaffolds with tunable porosity and mechanical properties, suitable for various applications. The addition of HA and DEX further enhanced the scaffolds. Future studies will apply the scaffolds in an in-vivo model to thoroughly investigate their performance.

Keywords: bone, PCL, 3D printing, tissue engineering

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Authors: Hsin Lee, Hsuan Lee

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Legal artificial intelligence (LegalAI) has been increasing applications within legal systems, propelled by advancements in natural language processing (NLP). Compared with general documents, legal case documents are typically long text sequences with intrinsic logical structures. Most existing language models have difficulty understanding the long-distance dependencies between different structures. Another unique challenge is that while the Judiciary of Taiwan has released legal judgments from various levels of courts over the years, there remains a significant obstacle in the lack of labeled datasets. This deficiency makes it difficult to train models with strong generalization capabilities, as well as accurately evaluate model performance. To date, models in Taiwan have yet to be specifically trained on judgment data. Given these challenges, this research proposes a Longformer-based pre-trained language model explicitly devised for retrieving similar judgments in Taiwanese legal documents. This model is trained on a self-constructed dataset, which this research has independently labeled to measure judgment similarities, thereby addressing a void left by the lack of an existing labeled dataset for Taiwanese judgments. This research adopts strategies such as early stopping and gradient clipping to prevent overfitting and manage gradient explosion, respectively, thereby enhancing the model's performance. The model in this research is evaluated using both the dataset and the Average Entropy of Offense-charged Clustering (AEOC) metric, which utilizes the notion of similar case scenarios within the same type of legal cases. Our experimental results illustrate our model's significant advancements in handling similarity comparisons within extensive legal judgments. By enabling more efficient retrieval and analysis of legal case documents, our model holds the potential to facilitate legal research, aid legal decision-making, and contribute to the further development of LegalAI in Taiwan.

Keywords: legal artificial intelligence, computation and language, language model, Taiwanese legal cases

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Authors: Supriya Gupta, Paresh Chokshi

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Polymer-particle interactions can be effectively utilized to produce composites that possess physicochemical properties superior to that of neat polymer. The incorporation of fillers with dimensions comparable to polymer chain size produces composites with extra-ordinary properties owing to very high surface to volume ratio. The dispersion of nanoparticles is achieved by inducing steric repulsion realized by grafting particles with polymeric chains. A comprehensive understanding of the interparticle interaction between these functionalized nanoparticles plays an important role in the synthesis of a stable polymer nanocomposite. With the focus on incorporation of clay sheets in a polymer matrix, we theoretically construct the polymer mediated interparticle potential for two nanosheets grafted with polymeric chains. The self-consistent field theory (SCFT) is employed to obtain the inhomogeneous composition field under equilibrium. Unlike the continuum models, SCFT is built from the microscopic description taking in to account the molecular interactions contributed by both intra- and inter-chain potentials. We present the results of SCFT calculations of the interaction potential curve for two grafted nanosheets immersed in the matrix of polymeric chains of dissimilar chemistry to that of the grafted chains. The interaction potential is repulsive at short separation and shows depletion attraction for moderate separations induced by high grafting density. It is found that the strength of attraction well can be tuned by altering the compatibility between the grafted and the mobile chains. Further, we construct the interaction potential between two nanosheets grafted with diblock copolymers with one of the blocks being chemically identical to the free polymeric chains. The interplay between the enthalpic interaction between the dissimilar species and the entropy of the free chains gives rise to a rich behavior in interaction potential curve obtained for two separate cases of free chains being chemically similar to either the grafted block or the free block of the grafted diblock chains.

Keywords: clay nanosheets, polymer brush, polymer nanocomposites, self-consistent field theory

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Authors: Aziza S. Al Adhoobi, Amna Al Ruheili, Saud M. Al Jufaili

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This study investigates the potential effects of climate change on the habitat suitability of two Aphaniops species (Teleostei: Aphaniidae) found in the Oman Mountains and the Southwestern Arabian Coast. Aphaniops kruppi, an endemic species, is found in various water bodies such as wadis, springs, aflaj, spring-fed streams, and some coastal backwaters. Aphaniops stoliczkanus, on the other hand, inhabits brackish and freshwater habitats, particularly in the lower parts of wadies and aflaj, and exhibits euryhaline characteristics. Using Maximum Entropy Modeling (MaxEnt) in conjunction with ArcGIS (10.8.2) and CHELSA bioclimatic variables, topographic indices, and other pertinent environmental factors, the study modeled the potential impacts of climate change based on three Representative Concentration Pathways (RCPs 2.6, 7.0, 8.5) for the periods 2011-2040, 2041-2070, and 2071-2100. The model demonstrated exceptional predictive accuracy, achieving AUC values of 0.992 for A. kruppi and 0.983 for A. stoliczkanus. For A. kruppi, the most influential variables were the mean monthly climate moisture index (Cmi_m), the mean diurnal range (Bio2), and the sediment transport index (STI), accounting for 39.9%, 18.3%, and 8.4%, respectively. As for A. stoliczkanus, the key variables were the sediment transport index (STI), stream power index (SPI), and precipitation of the coldest quarter (Bio19), contributing 31%, 20.2%, and 13.3%, respectively. A. kruppi showed an increase in habitat suitability, especially in low and medium suitability areas. By 2071-2100, high suitability areas increased slightly by 0.05% under RCP 2.6, but declined by -0.02% and -0.04% under RCP 7.0 and 8.5, respectively. A. stoliczkanus exhibited a broader range of responses. Under RCP 2.6, all suitability categories increased by 2071-2100, with high suitability areas increasing by 0.01%. However, low and medium suitability areas showed mixed trends under RCP 7.0 and 8.5, with declines of -0.17% and -0.16%, respectively. The study highlights that climatic and topographical factors significantly influence the habitat suitability of Aphaniops species in Oman. Therefore, species-specific conservation strategies are crucial to address the impacts of climate change.

Keywords: Aphaniops kruppi, Aphaniops stoliczkanus, Climate change, Habitat suitability, MaxEnt

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