bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative evaluation of wavelength-scanning Otto and Kretschmann configurations of SPR biosensors for low analyte concentration measurement
Authors: Araguillin Ricardo , Méndez Ángel , González José , Costa-Vera Ćesar 
Published: July 2024

Abstract
The growing demand for compound characterization has stimulated research, particularly in surface plasmon resonance technology. This technique monitors changes in the light-reflecting properties of a sample medium in close contact and in interaction with a plasmonic surface (typically a metal such as gold) due to shifts in the fundamental plasmon resonance of the surface. The Otto and Kretschmann configurations are commonly used in this method. When an analyte is expensive, scarce, or hazardous, it is advantageous to reduce the sample required for testing, making optimization of sample use interesting. This challenge requires trade-offs between sensitivity and LoD. This work compares two sensors in the indicated configurations designed for minimal analyte requirement (in this case, Ag nanoparticle suspensions) using the wavelength scanning technique. The results show that the Kretschmann configuration is the most efficient for characterizing nanoparticle suspensions due to its construction characteristics, ease of use, and the characteristics of the obtained response. The final arrangement is a quasi-point sensor that only requires 6μL of analyte and has a sensitivity of 4.17x10−4 RIU/λ (RIU is the refractive index unit). This study contributes to the exploration of advantages and limitations in the design and operation of SPR sensors. The work also underlies the need for future research to enhance the selectivity and versatility of these devices.
Assessing the impacts of El Niño events on the Ecuadorian territory: a computational analysis of climatologies, anomalies, and deprivation index.
Authors: Paredes A J , Cruz G L , Chimborazo O V 
Published: July 2024

Abstract
This study conducts a comprehensive computational analysis to assess the climatological and socio-economic impacts of El Niño events on Ecuador, employing a detailed examination of climatologies, anomalies, and deprivation indices from 1980 to 2023. We identify significant climatic shifts and implications on regional vulnerabilities by utilizing the Essential Climate Variables dataset, alongside the Oceanic Niño Index (ONI) and the Niño 1+2 index for sea surface temperature anomalies. Additionally, the Global Gridded Relative Deprivation Index (GRDI) is integrated to evaluate socio-economic impacts, highlighting areas of heightened deprivation. Notably, regions such as Chimborazo, Cotopaxi, Azuay, Tungurahua, and Bolívar emerge as significantly vulnerable, with pronounced susceptibility to temperature changes and precipitation anomalies. Several statistical methods, including Pearson Correlation, Spearman Rank Correlation, and Kendall’s Tau are employed to establish robust causal relationships between El Niño indices and climatic anomalies. The application of Convergent Cross Mapping (CCM) provides deeper insights, particularly demonstrating causality from ONI to air temperature anomalies and from the Niño 1+2 index to precipitation anomalies. The findings of this study may suggest targeted strategies for local adaptation and resilience, contributing to a broader understanding of global climate variability.
Visualization and Segmentation of Lung Tissue in DICOM-format CT Images
Authors: Ortega Jennifer 
Published: July 2024

Abstract
In this project, two tools were developed as a preliminary step towards the creation of future Computer-Aided Diagnosis systems for the automatic detection of lung diseases. The first methodology aimed to extract information from DICOM-format files using Python and the Jupyter Notebook programming environment. The implemented process enables the generation of images in various anatomical planes, using the pixel matrix in Hounsfield units. Additionally, a custom tool was developed for anonymizing and visualizing file information. The techniques employed are independent of the grayscale image generated and are not reliant on the type of window used. The second tool introduces a lung segmentation technique for chest CT images. The segmentation uses the pixel matrix in Hounsfield units to initially identify lung tissue based on its linear X-ray attenuation. Subsequently, the Watershed algorithm based on markers is employed as the primary foundation of the technique. Various morphological operations and transformations on axial slices are applied, resulting in successful lung segmentation.
A Survey on Energy Methods for Vibroacoustic Analysis of Random Dynamic Systems and Applications
Authors: Andrade Luis 
Published: July 2024

Abstract
Engineering can be considered a field of applied physics, as for the design of dynamic systems several aspects such as the strength, parameters of motion, among others, must be estimated for dimensioning, specifications of construction procedures, and operation. In the search for an appropriate model to estimate the dynamic response of a system to a prescribed input, several energy-based methods have been explored over the last decades to address three main issues. Firstly, it is quite rare that a solution for a purely analytical model exists, particularly for complex built-up structures. Secondly, numerical approaches to solve such complex equations of motion of a structure are computationally expensive. Lastly, even if a numerical or analytical solution can be found, there is no warranty that such estimation would be true for an ensemble of nominally identical built-up systems due to uncertainties that are not usually considered by the models. The aim of this work is to present a survey of existing approaches based on equations of energy rather than motion to simplify the computational process and include the effects of uncertainties in the dynamic response, and improvements to such models in regard of other engineering aspects. Additionally, several engineering applications are presented.
Study of the thermal diffusivity in low-response optical systems combining a thermal lensing approach with a standard addition method
Authors: Teran Ana , Costa Vera Cesar 
Published: July 2024

Abstract
Thermal lensing is a local effect produced by the incidence of a light beam that heats a part of an absorbent material. Mathematical modeling of this photothermal phenomenon allows the determination of the medium’s thermal diffusivity. A pumping-modulated laser (405nm) induces the thermal lensing effect, and a test laser (650nm) generates the photothermal signal measured as a function of the modulation. The thermal diffusivity is obtained from a curve fit of the signal (calibrated for ethanol). In this work, the thermal diffusion coefficients of low-absorbance nanoparticle suspensions are established. This was achieved through the application of a standard addition method. The added analyte, enhance the optical response of SiO
2 nanoparticle suspensions. Different aliquots of tartrazine (analyte) resulted in different values for the thermal diffusion of the samples. It was found that the experimental coefficients of this colloids agree with the theoretical model. Finally, a linear regression allowed to find the thermal coefficient in the zero concentration point.
Parameters of differential equations in four-flux and two-flux models approximated for scattering and absorption results on solar thermal collector black paints
Authors: Barrios David 
Published: July 2024

Abstract
The intrinsic and extrinsic scattering and absorption coefficients of a thin black paint substrate used as a solar thermal collector, deposited on a thick glass substrate, were obtained in an approximated single-layer method, using the new solved equations recently determined from the collimated and diffuse differential equations of the four-flux model, for the intrinsic coefficients, and considering the differential equations of the two-flux model with total light intensities, for the extrinsic coefficients. In a first step, the optical constants were determined from the measurements of regular transmittance and specular reflectance, fitting them to the collimated transmittance and reflectance solutions of the four-flux model. In a second step, the intrinsic coefficients were obtained from the diffuse transmittance and reflectance measurements, considering four forward scattering ratios (for collimated and diffuse light intensities and for forward and backward light directions) and two average crossing parameters (for forward and backward light directions). In a third step, the extrinsic coefficients were obtained, using the new solved equations recently determined considering the total differential equations as the sum of the collimated and diffuse differential equations. Due to the approximated single-layer method, a simple rule of three was applied to the intrinsic and extrinsic results, relating the extinction coefficients calculated from the optical constants to those calculated from the collimated differential equations. The same external and internal diffuse interface reflectance was observed by integrating the collimated interface reflectance up to the critical angle of total internal reflection.
Optical constants and thickness gradients for light intensities in glass substrate layers and for complex electric fields in indium tin oxide (ITO) transparent conductor thin film layer, using Bode and Nyquist wavelength-dependent diagrams
Authors: Barrios David 
Published: July 2024

Abstract
The optical constants of a thin film layer of transparent conductive indium tin oxide (ITO), deposited on a thick glass substrate (G), were obtained for an ITO-G sample using a multilayer matrix method by fitting the regular transmittance and specular reflectance measurements to the collimated equations of the four-flux model, once the optical constants of the glass substrate layer had previously been obtained from a G sample of a single glass substrate layer. The accuracy of the results was validated using a feedback system called the three-extinction matching requirement, that is, obtaining the same extinction coefficients from the optical constants and from the forward and backward collimated differential equations of the four-flux model. To calculate the extinction coefficients of the glass from optical constants, the compression of the wavelength of the incident light in the glass substrate and in the thin ITO film layer was demonstrated, with a thickness less than the wavelength of incident light. The thickness gradients of the forward and backward collimated light intensities, on the glass substrate of the ITOG sample, were compared with those obtained for the single-layer G sample. Then, the thickness gradients for the complex forward and backward electric fields of the ITO thin film layer were obtained and plotted using spectral magnitude and phase Bode plots and new Nyquist plots, i.e. imaginary versus real parts, dependent on wavelength.
Erythemal weighting function adjustment for a correct calculation of UV index in high-altitude cities
Authors: Iza Telmo S. , Vásconez C. L. 
Published: July 2024

Abstract
Andean cities are mostly characterized, and appreciated, by their high elevation. Commonly above 2500m above the sea level. However, a more subtle feature is their proximity to the Equator. These two characteristics provide these cities with unique climatological conditions. Complementary to this, the main autoethnography of the zone is “mestizo”, which is characterized by its type of skin (namely types III and IV). These kind of skins are highly adapted to radiation intensity (and atmosphere density) of the equatorial zone. We use measurements of radiation from sensors located at Quito in order to provide a novel method to computing the local ultraviolet-index range risk, taking into account an action spectrum of skin types III and IV, and the recommendations of the World Health Organization. The results of this study could be applied directly to cities with climatological conditions, and with population with skin types, similar to those from the Andean region.
Using VR experience to show new subjects to undergraduate students: HalDron Project.
Authors: Chancay Hugo , Martinez-Gallego Verónica , Perez Silvio , Lobos Juan 
Published: July 2024

Abstract
The present research aimed to test if immersive technologies would help STEM undergraduate students from Ecuador to conceptualize and connect with new subjects. An application was developed for Oculus Quest 2 on Introduction to Radioactivity. The test subjects were presented with a questionnaire containing a theoretical assessment and then were exposed to a short, interactive experience about the topic with audio and video explanations from a Virtual Learning Companion and animations with small interactions and hyper-lapses in the fashion of a futuristic laboratory. A majority of the test subjects were not gamers and had little exposure to virtual reality outside of smartphones or 3D films before the experience. In a posterior questionnaire, results show that regardless of their prior experience, the users obtained a high degree of immersion that helped them understand and develop an interest in the topic. None of the students reduced their initial grade on the questionnaire, 44.8% increased their grades from one to two times, and 44.8% increased their grades 2 times or higher. Another questionnaire was presented to learn about their user experience to understand better how the immersion and their previous exposition, or lack thereof, helped them conceptualize the concepts presented.
Multi-parameter quantum estimation of single- and two-mode pure Gaussian states
Authors: Bressanini Gabriele , Genoni Marco G , Kim M S , Paris Matteo G A 
Published: July 2024

Abstract
We discuss the ultimate precision bounds on the multiparameter estimation of single- and two-mode pure Gaussian states. By leveraging on previous approaches that focused on the estimation of a complex displacement only, we derive the Holevo Cramér–Rao bound (HCRB) for both displacement and squeezing parameter characterizing single and two-mode squeezed states. In the single-mode scenario, we obtain an analytical bound and find that it degrades monotonically as the squeezing increases. Furthermore, we prove that heterodyne detection is nearly optimal in the large squeezing limit, but in general the optimal measurement must include non-Gaussian resources. On the other hand, in the two-mode setting, the HCRB improves as the squeezing parameter grows and we show that it can be attained using double-homodyne detection.
Cannabinoids detected in exhaled breath condensate after cannabis use
Authors: Berry Jennifer L , Brooks-Russell Ashley , Beuning Cheryle N , Limbacher Sarah A , Lovestead Tara M , Jeerage Kavita M 
Published: July 2024

Abstract
Cannabinoids can be detected in breath after cannabis use, but different breath matrices need to be explored as studies to date with filter-based devices that collect breath aerosols have not demonstrated that breath-based measurements can reliably identify recent cannabis use. Exhaled breath condensate (EBC) is an unexplored aqueous breath matrix that contains condensed volatile compounds and water vapor in addition to aerosols. EBC was collected from participants both before and at two time points (0.7 ± 0.2 h and 1.7 ± 0.3 h) after observed cannabis use. Eleven different cannabinoids were monitored with liquid chromatography tandem mass spectrometry. Five different cannabinoids, including Δ9-tetrahydrocannabinol (THC), were detected in EBC collected from cannabis users. THC was detected in some EBC samples before cannabis use, despite the requested abstinence period. THC was detected in all EBC samples collected at 0.7 h post use and decreased for all participants at 1.7 h. Non-THC cannabinoids were only detected after cannabis use. THC concentrations in EBC samples collected at 0.7 h showed no trend with sample metrics like mass or number of breaths. EBC sampling devices deserve further investigation with respect to modes of cannabis use (e.g, edibles), post use time points, and optimization of cannabinoid recovery.
A practical machine learning approach for predicting the quality of 3D (bio)printed scaffolds
Authors: Rafieyan Saeed , Ansari Elham , Vasheghani-Farahani Ebrahim 
Published: July 2024

Abstract
3D (Bio)printing is a highly effective method for fabricating tissue engineering scaffolds, renowned for their exceptional precision and control. Artificial intelligence (AI) has become a crucial technology in this field, capable of learning and replicating complex patterns that surpass human capabilities. However, the integration of AI in tissue engineering is often hampered by the lack of comprehensive and reliable data. This study addresses these challenges by providing one of the most extensive datasets on 3D-printed scaffolds. It provides the most comprehensive open-source dataset and employs various AI techniques, from unsupervised to supervised learning. This dataset includes detailed information on 1171 scaffolds, featuring a variety of biomaterials and concentrations—including 60 biomaterials such as natural and synthesized biomaterials, crosslinkers, enzymes, etc.—along with 49 cell lines, cell densities, and different printing conditions. We used over 40 machine learning and deep learning algorithms, tuning their hyperparameters to reveal hidden patterns and predict cell response, printability, and scaffold quality. The clustering analysis using KMeans identified five distinct ones. In classification tasks, algorithms such as XGBoost, Gradient Boosting, Extra Trees Classifier, Random Forest Classifier, and LightGBM demonstrated superior performance, achieving higher accuracy and F1 scores. A fully connected neural network with six hidden layers from scratch was developed, precisely tuning its hyperparameters for accurate predictions. The developed dataset and the associated code are publicly available on https://github.com/saeedrafieyan/MLATE to promote future research.
Production of paver blocks from polyethylene terephthalate solid waste as partial replacement of sand
Authors: Worku Getahun Demeke , Ejigu Assamen Ayalew 
Published: July 2024

Abstract
Plastic waste management is an international concern. Polyethylene terephthalate (PET) plastic waste is present everywhere in Addis Ababa relative to other types of plastic waste and it is an international concern regarding environmental problems. The amount of plastic trash produced globally is increasing at a rapid rate, and this pollution is caused by improper disposal, the waste’s non-biodegradability, and the harmful gases released during incineration pose a hazard to human health. Because it’s used in so many commonplace items, such as bottles and containers for the food and beverage sectors, polyethylene terephthalate, or PET, is one of the most widely used consumer polymers. Because of its many characteristics, including its inability to biodegrade and the gasses it releases when burned, it has grown to be a significant environmental problem. Waste made of polyethylene terephthalate (PET) must therefore be recycled and used efficiently. The purpose of this study was to produce paver blocks by partially replacing sand with waste Polyethylene Terephthalate (PET) material. Preparing the raw materials, mixing, vibrating, molding, curing, testing the flexural and compressive strengths, and curing are the steps in the production process. . The mixing proportion of paver blocks implemented for this study was 1:2:3, which is a predictable volume basis-mixing ratio of cement, aggregate, and sand correspondingly. Design-Expert 13.0.0 Three-level three factor Box–Behnken design was used for experimental design and statistical analysis of results based on the outcome and discussion. A total of 17 trials were carried out with the following parameters: 10, 20, and 30% of polyethylene terephthalate; 0.52, 0.55, and 0.58 as the water-to-cement ratio; and 7, 14, and 28 days for the curing period. The interaction effects were examined based on the examination of the experimental data. The physio-mechanical properties of Paver Blocks, including water absorption, compressive strength, and flexural strength, were examined. At a water-to-cement ratio of 0.55, obtained maximum flexural and compressive strength which is 4.92 MPa, and 29.74 MP respectively, and when PET plastic waste percentage increased, both flexural and compressive strength decreased but we got a good flexural and compressive strength value at 10% PET. And also water absorption rates were increased as PET plastic waste increased. The ideal process variables for polyethylene terephthalate percentage were 10 and 28. The paver blocks average and maximum water absorption rates were 3.39% and 3.95%, respectively. Compared to regular blocks, the resultant Paver Blocks are lighter and have superior physical and mechanical qualities. These are excellent illustrations of planned paver applications that can make use of prefabricated paver blocks.
Enhancing the functionality of sugar palm (Arenga Pinnata) fibre reinforced polylactic acid composite filament of fused deposition modelling through Taguchi method
Authors: C H Hazliza Aida , Mastura M T , Abdul Kudus S I , Muhd Mufqi A 
Published: July 2024

Abstract
Constructing functional components using Fused Deposition Modelling (FDM) is challenging due to various processing factors that influence the quality of the final product. The main reason for this is the many processing parameters involved, which have the ability to impact the quality of the produced components. The aim of this research is to use the Taguchi technique in attempt to improve the printing variables for attaining the best possible mechanical and physical qualities in the three-dimensional (3D) printed product made from sugar palm fibre reinforced polylactic acid (SPF/PLA). The layer thickness, infill density, and printing speed are characteristics that directly affect the mechanical qualities, surface roughness, and dimensional accuracy of FDM products. The research applied Taguchi’s L9 array, consisting of 9 experimental trials, with each trial including 5 duplicated specimens. Thus, a total of 45 specimens were generated by altering various processing settings. The most effective printing settings for FDM using SPF and PLA were found to be a layer thickness of 0.1 mm, infill density set to 100%, and a printing speed of 25 mm s−1. The microscopic images reveal a significant rise in the number of voids as the layer thickness is raised. Additionally, the printing speed has a substantial impact on the nead structure, making it more resilient. Overall, the results will provide a significant collection of data in the area of 3D printing, improving the utilization of indigenous plant fibres in additive manufacturing technology.