Miracle-dz/UniFAR-FTUs huggingface dataset:
Occlusion filling in depth-image-based rendering

With the LDV format, it is possible to broadcast 3D content existing of a 2D image and the corresponding depth map. The display system can render this information into two or more views, which can be shown to the users. During this shifting, holes with no content occur in some or all the views. These holes need to be filled to get a better image quality. The process of filling these holes is named de-occlusion, and there are different methods available. Three perceptional experiments were done for testing some methods for de-occlusion. The tested methods were background extrapolation, occlusion layer, mirroring, copy background and depth map filtering. The first two experiments used stimuli synthesized with only two depth levels, a foreground plane and a background plane. In the first experiment, four different background contents were used and in the second, two. The foreground objects stayed the same in the experiments. The third experiment included more realistic content in addition to the two depth level synthetic content. Beside the background extrapolation and mirroring, a newly designed algorithm was used which is a combination of both and a vertical background extrapolation algorithm. Depending on the texture of the content around the hole, one of them is applied. In all the experiments, the images were rendered with two disparities, resulting in more or less depth in the images. In all experiments there was a dependency of the preferred algorithm on the content, which is why the combination algorithm was designed for the third experiment. In the first experiment a dependency on screen disparity was found, but not in the other experiments. The differences in preference between the algorithms were smaller for the realistic content than for the synthetic content. The holes were smaller in case of the realistic content because of smaller depth changes in the content. Therefore it was more difficult for the participants to see differences between the algorithms.
On the Generalized Kinetic Equation for Surface Gravity Waves, Blow-Up and Its Restraint

This article is concerned with the non-linear interaction of homogeneous random ocean surface waves. Under this umbrella, numerous kinetic equations have been derived to study the evolution of the spectral action density, each employing slightly different assumptions. Using analytical and numerical tools, and providing exact formulas, we demonstrate that the recently derived generalized kinetic equation exhibits blow up in finite time for certain degenerate quartets of waves. This is discussed in light of the assumptions made in the derivation, and this equation is contrasted with other kinetic equations for the spectral action density.
CONTENT BASED MEDICAL IMAGE RETRIEVAL USING SHAPE DESCRIPTORS

- Content-Based Image Retrieval (CBIR) refers to image retrieval system that is based on visual properties of image objects rather than textual annotation. Contents of an image can be of various forms like, texture, color, and shape etc. In this work, shape is selected as a primary feature in indexing the image database. CBIR for medical images has become a major necessity with the growing technological advancements. This paper presents the basics of image retrieval process that includes the two techniques for image retrieval and about the Fourier descriptor to extract the features of image which is one of the important research contents in content based image retrieval process. Different shape signatures have been exploited to derive Fourier descriptors, however Fourier descriptors derived from different signatures can have significant different effect on the retrieval process.
Post stack seismic data processing for enhancing subsurface reservoir mapping in the Shushan basin, Western Desert, Egypt

ABSTRACT Reprocessing of seismic reflection data over Nader field in the Egyptian Western Desert, improved the images of the surface structural framework. The appearance of seismic data can be affected by various factors apart from subsurface structure, including data acquisition problems and processing artefacts. Different post-stack processing steps were tested and compared to the original seismic data determine the enhancement of data quality and improvements on imaging the subsurface. The applied post-stack processing sequence increased the seismic data resolution through increasing the signal-to-noise ratio, enhancing faults detection, and reflectors sharpness and continuity. The Time Variant Frequency Filter (TVF) application is found to be better than applying the filter in one time window and provided more detailed frequency contents and in turn better reflectors identification. The Frequency/Wave Number (F/K) filter removed lot of the existing linear noises resulted in more clear images. The Frequency/Distance (F/X) Deconvolution enhanced the data coherency by removing the existing random noises. The Spiking Deconvolution showed remarkable enhancement in compressing the reflectors and increasing their continuity. The reprocessed data interpretation of Abu Roash C member in Nader Filed, Shushan basin, North Western Desert, Egypt, comparing to the original, showed better mapping and faults detection, which highlighted new potential structures that could act as hydrocarbon traps.
A Microfluidic Experimental Method for Studying Cell-to-Cell Exosome Delivery–Taking Stem Cell–Tumor Cell Interaction as a Case

Cell-to-cell communication must occur through molecular transport in the intercellular fluid space. Nanoparticles, such as exosomes, diffuse or move more slowly in fluids than small molecules. To find a microfluidic technology for real-time exosome experiments on intercellular communication between living cells, we use the microfluidic culture dish’s quaternary ultra-slow microcirculation flow field to accumulate nanoparticles in a specific area. Taking stem cell–tumor cell interaction as an example, the ultra-slow microcirculatory flow field controls stem cell exosomes to interfere with tumor cells remotely. Under static coculture conditions (without microfluidics), the tumor cells near stem cells (<200 µm) show quick breaking through from its Matrigel drop to meet stem cells, but this ‘breaking through’ quickly disappears with increasing distance. In programmed ultra-slow microcirculation, stem cells induce tumor cells 5000 μm far at the site of exosome deposition (according to nanoparticle simulations). After 14 days of programmed coculture, the glomeration and migration of tumor cells were observed in the exosome deposition area. This example shows that the ultra-slow microcirculation of the microfluidic culture dish has good prospects in quantitative experiments to study exosome communication between living cells and drug development of cancer metastasis.
Canine circovirus among dogs and cats in China: first identification in cats

Canine circovirus (CanineCV) is a virus associated with respiratory and digestive diseases in dogs and often occurs in coinfections with other pathogens, thereby aggravating the symptoms of infected dogs. CanineCV was first reported in the United States in 2012. Subsequently, it was reported among dogs in Europe, Asia, and South America. To investigate the prevalence of CanineCV in dogs in China, 331 dog samples were collected in this study. The PCR results showed that 9.06% (30/331, 95% CI = 6.2% ~ 12.7%) of the dog samples were CanineCV positive. CanineCV has also been detected in some carnivorous wild animals, indicating the potential risk of cross-species transmission of this virus. And, cats are also one of the most common pets in our daily lives, who is close contact with dogs. Thus, this study first investigated the prevalence of CanineCV in cats. The PCR results showed that 3.42% (14/409, 95% CI = 1.9% ~ 5.7%) of the cat samples were CanineCV positive. Moreover, 14 canine-derived CanineCV whole genomes and the first cat-derived CanineCV whole genome were obtained in this study. Rep and Cap are the major nonstructural proteins and structural proteins of CanineCV, respectively. In nucleic acid homology analyses, these 15 CanineCV strains showed a high degree of variation in Rep (85.9 ~ 99%) and Cap (85.6 ~ 100%). In phylogenetic analyses, the 15 CanineCV strains clustered into 3 different genotypes (genotypes 1, 3, and 4). Among them, the first cat-derived CanineCV belonged to CanineCV-3. In addition, 4 genetic recombination events were predicted in these 15 CanineCV strains, occurring in multiple regions of the genome. In conclusion, this study is the first to provide evidence of CanineCV infection in cats and successfully obtained the first whole genome of cat-derived CanineCV. The complex circulation and high prevalence of CanineCV among dogs and cats emphasize the importance of continuous monitoring of this virus in various animal species.
Map vector tile construction for arable land spatial connectivity analysis based on the Hadoop cloud platform

The concentrated connection of arable land is one of the important indicators reflecting the quality of cultivated land, and large-scale arable land blocks are more conducive to agricultural mechanization operation, thereby improving the land use efficiency. However, the calculation of farmland connectivity is essentially a large-scale calculation of spatial vector data, especially for the national or global farmland patch data. This article proposes a framework for calculating farmland connectivity based on spatial vector map tiles and parallelizes the algorithm based on the Hadoop cloud platform. The framework is based on the tile pyramid model and uses the Douglas–Peucker algorithm to simplify the data to meet the needs of rapid display of large-scale data under multi-scale. The consistency and integrity of the front display of vector tiles are ensured using the setting tile buffer. Meanwhile, the parallelization of the vector tile construction algorithm is realized based on the MapReduce programming mode. Finally, the effectiveness and usability of this framework were verified through the calculation of patch connectivity on the tillage map. Experiments show that the algorithm can not only meet the rapid construction requirements of large-scale vector tile data but also support the cultivated land spatial connectivity analysis and greatly improve the efficiency of supporting data calculation.
Overview of the Application of Computer-Aided Tools in Information Systems Development

Developing Information Systems (IS) using computer-aided tools (CATs) yields immense benefits realized by following a set of activities and techniques. Apart from revolutionizing IS development, another key benefit of computer-aided approach remains the improvement of the overall IS development process. While integrated CATs could be used throughout the phases of IS development life-cycle, others are only meant serve specific phases. The present paper provides a short review on the concepts in IS Development using CATs. Furthermore, the paper highlights the most prominent CATs that are widely used and how these tools fit into different phases of IS development. It also describes how using CATs paved the way to the recent trends in user-centred and end-user IS development approaches.
Oceanographic Applications of Remote Sensing

(Section Headings) Ocean Circulation Dynamics Mesoscale Variability Tides, Shelf Circulation, and Internal Waves Basin-Scale Circulation Equatorial Dynamics Water Properties Large Scale Ocean Temperature Ocean Color Wind, Wind Waves, and the Marine Boundary Layer Wind and Wind Stress Wind-Generated Waves Marine Boundary Layer Application to Sea Ice Ice Surface Condition Ice Movement Waves in Ice-Covered Oceans Appendices
Mothers with Neuroticism: Parenting When Faced with Challenges

SYNOPSIS Objective. The study documents how the personality trait of neuroticism is implicated in two aspects of parenting under two forms of challenge, low income and rearing a difficult child. Design. Relations of maternal neuroticism with sensitivity and stimulation in parenting and the total HOME score were examined when children were 54 months old and 5th grade, with a focus on how neuroticism moderates the effect of low household income and child temperament on parenting. Results. Mothers high in neuroticism were less likely to manifest sensitivity or provide stimulation. Maternal neuroticism moderated the effects of low income on sensitivity, stimulation, and the overall home environment, particularly at 54 months. However, significant interactions between maternal neuroticism and child difficult temperament were only found for the total HOME score at age 11. Conclusions. Living in adverse circumstances may make it difficult for mothers with neuroticism to engage productively in parenting.
Enhancing Light Harvesting in Dye-Sensitized Solar Cells through Mesoporous Silica Nanoparticle-Mediated Diffuse Scattering Back Reflectors

Dye-sensitized solar cells (DSSCs) hold unique promise in solar photovoltaics owing to their low-cost fabrication and high efficiency in ambient conditions. However, to improve their commercial viability, effective, and low-cost methods must be employed to enhance their light harvesting capabilities, and hence photovoltaic (PV) performance. Improving the absorption of incoming light is a critical strategy for maximizing solar cell efficiency while overcoming material limitations. Mesoporous silica nanoparticles (MSNs) were employed herein as a reflective layer on the back of transparent counter electrodes. Chemically synthesized MSNs were applied to DSSCs via bar coating as a facile fabrication step compatible with roll-to-roll manufacturing. The MSNs diffusely scatter the unused incident light transmitted through the DSSCs back into the photoactive layers, increasing the absorption of light by N719 dye molecules. This resulted in a 20% increase in power conversion efficiency (PCE), from 5.57% in a standard cell to 6.68% with the addition of MSNs. The improved performance is attributed to an increase in photon absorption which led to the generation of a higher number of charge carriers, thus increasing the current density in DSSCs. These results were corroborated with electrochemical impedance spectroscopy (EIS), which showed improved charge transport kinetics. The use of MSNs as reflectors proved to be an effective practical method for enhancing the performance of thin film solar cells. Due to silica’s abundance and biocompatibility, MSNs are an attractive material for meeting the low-cost and non-toxic requirements for commercially viable integrated PVs.
An economic evaluation of nitrogen fertilization of Montana winter wheat

Relationships between yield and protein response of winter wheat to nitrogen fertilizer and various soil and climatic variables were determined using data from 43 fertility experiments conducted in Montana during the years 1967, 1968, 1970, and 1971. Relationships were estimated using a generalized nonlinear least squares algorithm. Additive and multiplicative error models were examined. Explanatory variables were applied nitrogen, applied phosphorus, April through July precipitation, NO3-N to 4 feet in early spring, and soil water to 4 feet in early spring. Variables important in explaining yield response were first 1 determined using an additive error model. Precipitation, NO3-N, and applied nitrogen were important in explaining yield response. A multiplicative error model was then estimated and additive and multiplicative models were compared. Multiplicative models were chosen for estimating yield and protein response based on the properties associated with the error term. Important variables for explaining protein response were precipitation, NO3-N, applied nitrogen, and applied phosphorus. Estimated yield and protein response equations were used to determine optimal rates of nitrogen application under varying nitrogen-wheat price conditions. Optimal rates were first determined without a protein premium structure. Protein response and a protein premium structure were then included to illustrate the magnitude of the effect protein premiums may have on optimal nitrogen fertilization practices. High levels of soil nitrate did not prevent economic application of nitrogen fertilizer. As expected, protein premiums increased optimal rates of nitrogen application under most conditions. In the final section, a 25-percent marginal rate of return was specified and used to derive optimal nitrogen rates without a protein premium. Specification of this marginal rate of return reduced optimal nitrogen rates. STATEMENT OF PERMISSION TO COPY In presenting this thesis in partial fulfillment of the require­ ments for an advanced degree at Montana State University, I agree that the Library shall make it freely available for inspection. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by my major professor, or, in his absence, by the Director of Libraries. It is understood that any copying or publication of this thesis for financial gain shall not be allowed without my written permission.
Development of an Extended Reality-Based Collaborative Platform for Engineering Education: Operator 5.0

With the shift towards the human centric, sustainable, and resilient Industry 5.0, the need for training operators in complex industrial systems has become increasingly crucial. This paper explores the significance of collaborative extended reality (XR)-based engineering education in the preparation of the next generation of operators, denoted as Operator 5.0. By leveraging immersive technologies, operators can gain hands-on training experience in virtual or augmented environments. By incorporating these elements, operators can undergo comprehensive and personalized training, resulting in improved performance, reduced downtime, enhanced safety, and increased operational efficiency. Additionally, the framework is tested within a laboratory environment in three different case studies, focusing on maintenance and repair operations in the context of modern manufacturing in order to test its functionalities. Therefore, in this research, the current developments have been debugged and examined in order to test all of the functionalities of the digital platform so that the revised and improved version of the digital platform can be tested with a wider industrial and educational audience.
Oolong tea cultivars categorization and germination period classification based on multispectral information

Recognizing and identifying tea plant (Camellia sinensis) cultivar plays a significant role in tea planting and germplasm resource management, particularly for oolong tea. There is a wide range of high-quality oolong tea with diverse varieties of tea plants that are suitable for oolong tea production. The conventional method for identifying and confirming tea cultivars involves visual assessment. Machine learning and computer vision-based automatic classification methods offer efficient and non-invasive alternatives for rapid categorization. Despite advancements in technology, the identification and classification of tea cultivars still pose a complex challenge. This paper utilized machine learning approaches for classifying 18 oolong tea cultivars based on 27 multispectral characteristics. Then the SVM classification model was executed using three optimization algorithms, namely genetic algorithm (GA), particle swarm optimization (PSO), and grey wolf optimizer (GWO). The results revealed that the SVM model optimized by GWO achieved the best performance, with an average discrimination rate of 99.91%, 93.30% and 92.63% for the training set, test set and validation set, respectively. In addition, based on the multispectral information (h, s, r, b, L, Asm, Var, Hom, Dis, σ, S, G, RVI, DVI, VOG), the germination period of oolong tea cultivars can be completely evaluated by Fisher discriminant analysis. The study indicated that the practical protection of tea plants through automated and precise classification of oolong tea cultivars and germination periods is feasible by utilizing multispectral imaging system.
Seasonal Differences in Leaf Photoprotective Potential between Adults and Juveniles of Two Mediterranean Perennials with Distinct Growth Forms: A Comparative Field Study

The photosynthetic differences between adult and juvenile Mediterranean plants were previously studied under field conditions, yet the corresponding differentiation of their photoprotective efficiency has not been sufficiently investigated. The present study aims to examine possible differences in the photoprotective potential between adults and juveniles of two native Mediterranean plants with distinct growth forms. Thus, the seasonal variations in individual carotenoids, electron transport rate (ETR), and non-photochemical quenching (NPQ) were monitored in fully exposed mature leaves from adults and juveniles of the winter deciduous tree Cercis siliquastrum L. and the evergreen sclerophyllous shrub Nerium oleander L. All plants were grown under apparently similar field conditions. In both species, juveniles displayed substantially lower ETR and increased NPQ values than adults in spring, with the differences intensifying during summer drought and diminishing in autumn. Concomitantly, juveniles showed significantly higher chlorophyll-based total carotenoids in spring and summer mainly due to the higher investment in xanthophyll cycle components (VAZ), in combination with an increased mid-day de-epoxidation state (DEPS) and partial retention of zeaxanthin in the dark. In N. oleander, although ETR was lower in juveniles during winter, NPQ was extremely low in both ages. In conclusion, juveniles exhibit enhanced photoprotection potential, especially in the summer, due to their reduced photochemical capacity. The photosynthetic superiority of adults during the favorable spring period may be attributed to the needs of the co-existing reproductive effort.
A Contactless Smart WiFi-Based Application Presence or Fall Detection System: Analyzing Channel State Information (CSI) Signals

Falls are considered to be the most common accident among people of determination and the elderly. Recently, many solutions have been proposed, whether wearable or noncontact, for people presence or falling detection (FD). These solutions can use wearable sensors to effectively monitor the health condition of elderly people at home and ensure their performance. However, all of these solutions require users to always wear specialized devices and sensors in their bodies, which limits the deployment of large-scale systems. Additionally, camera-based systems can raise privacy concerns. Recently, the non-contact Wi-Fi approach is becoming more and more popular because of its ubiquitous and non-invasiveness. In this paper, we propose a smart contactless system that uses Artificial Intelligence (AI) to analyze the Channel State Information (CSI) signals extracted from Wi-Fi signals. Our proposed application can help the people of determination and senior citizens (e.g., remote monitoring of the elderly) to be engaged all the time through closed monitoring based on ability to analyse the CSI signals extracted from Wi-Fi signals. This system can detect the presence, and falls of users without requiring them to wear any specialized devices or sensors. We believe that this application can help elderly and disabled people to remain engaged and monitored at all times, providing their communities with the means to better care for and serve them.