Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of biochar and biological fertilizer to improve soil quality and Oryza sativa L. productivity

Abstract Rice husk is an agricultural waste that can be processed into biochar as the main ameliorant to improve soil quality and crop productivity. Biochar has the potential to be combined with biological fertilizers for intensive paddy farming. This study aimed at assessing the potential of biochar and biological fertilizers to improve soil quality and lowland paddy rice (Oryza sativa L.). This study used an experimental approach and the treatment of rice plants was carried out in a greenhouse. Rice plants were given biochar and biological fertilizer containing N-fixing and P-solvent microorganisms. The completely randomized experimental design involved four replications with six treatment combinations. The effect of this treatment was analyzed using analysis of variant (ANOVA) and least significant difference (LSD) with a 95% confidence level (α 0.05). We found that the optimal combination is 10 grams of biochar with three times of fertilizer (10BC+BF) on all parts of the plant. This research showed that the combination of biochar with biological fertilizers was able to significantly affect N, P and K in the soil. Only N in rice plants was also significantly affected by the treatment. The combination capable to increase the rice productivity according to paddy clumps and yield.
Edge-Enabled Adaptive Shape Estimation of 3-D Printed Soft Actuators With Gaussian Processes and Unscented Kalman Filters

Soft actuators have the advantages of compliance and adaptability when working with vulnerable objects, but the deformation shape of the soft actuators is difficult to measure or estimate. Soft sensors made of highly flexible and responsive materials are promising new approaches to the shape estimation of soft actuators, but suffer from highly nonlinear, hysteresis, and time-variant properties. A nonlinear and adaptive state observer is essential for shape estimation from soft sensors. Current state estimation methods rely on complex nonlinear data-fitting models, and the robustness of the estimation methods is questionable. This study investigates the soft actuator dynamics and the soft sensor model as a stochastic process characterized by the Gaussian process (GP) model. The unscented Kalman filter is applied to the GP model for more reliable variance adjustment during the sequential state estimation process than conventional methods. In addition, a major limitation of the GP model is its computational complexity during online inference. To improve the real-time performance while guaranteeing accuracy, we introduce an edge server to decrease the onboard computational and memory overhead. The experiments showcase a significant improvement in estimation accuracy and real-time performance compared to baseline methods.
UV-Accelerated Synthesis of Gold Nanoparticle–Pluronic Nanocomposites for X-ray Computed Tomography Contrast Enhancement

Eco-friendly chemical methods using FDA-approved Pluronic F127 (PLU) block copolymer have garnered much attention for simultaneously forming and stabilizing Au nanoparticles (AuNPs). Given the remarkable properties of AuNPs for usage in various fields, especially in biomedicine, we performed a systematic study to synthesize AuNP-PLU nanocomposites under optimized conditions using UV irradiation for accelerating the reaction. The use of UV irradiation at 254 nm resulted in several advantages over the control method conducted under ambient light (control). The AuNP-PLU-UV nanocomposite was produced six times faster, lasting 10 min, and exhibited lower size dispersion than the control. A set of experimental techniques was applied to determine the structure and morphology of the produced nanocomposites as affected by the UV irradiation. The MTT assay was conducted to estimate IC50 values of AuNP-PLU-UV in NIH 3T3 mouse embryonic fibroblasts, and the results suggest that the sample is more compatible with cells than control samples. Afterward, in vivo maternal and fetal toxicity assays were performed in rats to evaluate the effect of AuNP-PLU-UV formulation during pregnancy. Under the tested conditions, the treatment was found to be safe for the mother and fetus. As a proof of concept or application, the synthesized Au:PLU were tested as contrast agents with an X-ray computed tomography scan (X-ray CT).
Locally Ф-integrable σ-martingale densitiesfor general semimartingales**

A --martingale density for a given stochastic process is a local -martingale starting at 1 such that the product is a --martingale. Existence of a --martingale density is equivalent to a classic absence-of-arbitrage property of , and it is invariant if we replace the reference measure with a locally equivalent measure . Now suppose that there exists a --martingale density for . Can we find another --martingale density for having some extra local integrability under ? We show that the answer is always positive for one part of that we identify, and we show that the complete answer depends in a precise quantitative way on the local integrability of the drift-to-jump ratio of the remaining ‘jumpy’ part of . Our proofs provide in addition new ideas and results in infinite-dimensional spaces.
Comparison of Digital Surface Modelling Techniques for Sloping Hill Terrain Using GPS Data

Abstract High resolution (cm level accuracy) digital terrain models (DTM) are needed for slope evaluation studies and landslide monitoring applications. The present paper investigates the efficacy of some commonly used surface interpolation techniques to generate the DTM of a sloping hill terrain influenced by an active landslide. The point co-ordinates acquired using kinematic Global Positioning System (GPS) survey are used as input data and co-ordinates of some identified control points obtained using static GPS survey are used as validation points. The main focus is on identifying the best-fit technique for terrain modelling in terms of accuracy of generated surface, which can possibly be used for quantifying temporal changes in slope parameters of steep mountainous terrains. Nowadays, for geodesy applications, one of the most productive methods is use of precise point positioning obtained through GPS . Interpolation techniques like kriging, inverse distance weightage (IDW), spline, natural neighbour and radial basis function (RBF) are tested for accuracy of the generated surface. These methods give different levels of accuracy depending upon the precision of survey, terrain complexity, sampling density and the specific parameters applied to the method. Statistical analysis reveals that the surface reconstruction accuracy varies from 0.01 to 87cm. The RMSE varies from 20 to 35cm. Variogram analysis and surface accuracy plots reveal that RBF and kriging methods best represent the surface complexities at cm level accuracies.
Exploratory Transcriptomic Profiling Reveals the Role of Gut Microbiota in Vascular Dementia

Stroke is the second most common cause of cognitive impairment and dementia. Vascular dementia (VaD), a cognitive impairment following a stroke, is common and significantly impacts the quality of life. We recently demonstrated via gut microbe transplant studies that the gut microbe-dependent trimethylamine-N-oxide (TMAO) pathway impacts stroke severity, both infarct size and long-term cognitive outcomes. However, the molecular mechanisms that underly the role of the microbiome in VaD have not been explored in depth. To address this issue, we performed a comprehensive RNA-sequencing analysis to identify differentially expressed (DE) genes in the ischemic cerebral cortex of mouse brains at pre-stroke and post-stroke day 1 and day 3. A total of 4016, 3752 and 7861 DE genes were identified at pre-stroke and post-stroke day 1 and day 3, respectively. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated pathways of neurodegeneration in multiple diseases, chemokine signaling, calcium signaling, and IL-17 signaling as the key enriched pathways. Inflammatory response genes interleukin-1 beta (Il-1β), chemokines (C–X–C motif chemokine ligand 10 (Cxcl10), chemokine ligand 2 (Ccl2)), and immune system genes (S100 calcium binding protein 8 (S100a8), lipocalin-2 (Lcn2)) were among the most significantly upregulated genes. Hypocretin neuropeptide precursor (Hcrt), a neuropeptide, and transcription factors such as neuronal PAS domain protein 4 (Npas4), GATA binding protein 3 (Gata3), and paired box 7 (Pax7) were among the most significantly downregulated genes. In conclusion, our results indicate that higher plasma TMAO levels induce differential mRNA expression profiles in the ischemic brain tissue in our pre-clinical stroke model, and the predicted pathways provide the molecular basis for regulating the TMAO-enhanced neuroinflammatory response in the brain.
Anomalous Oligomerization Behavior of E. coli Aquaporin Z in Detergent and in Nanodiscs

Aquaporins are tetrameric integral membrane proteins that act as water channels, and can also permeabilize membranes to other solutes. The monomer appears to be the functional form despite all aquaporins being organized as tetramers, which therefore must provide a clear functional advantage. In addition to this quaternary organization, some aquaporins can act as adhesion molecules in membrane junctions, when tetramers located in opposing membranes interact via their extracellular domains. These stacked forms have been observed in a range of aquaporins, whether using lipidic membrane environments, in electron crystallography, or using detergent micelles, in single-particle cryo-electron microscopy (cryo-EM). In the latter technique, structural studies can be performed when the aquaporin is reconstituted into nanodiscs of lipids that are surrounded by a protein scaffold. During attempts to study E. coli Aquaporin Z (AqpZ), we have found that in some conditions these nanodiscs tend to form filaments that appear to be either thicker head-to-tail or thinner side-to-side stacks of nanodiscs. Nanodisc oligomerization was observed using orthogonal analytical techniques analytical ultra-centrifugation and mass photometry, although the nature of the oligomers (head-to-tail or side-to-side) could not be determined. Using the latter technique, the AqpZ tetramer itself formed oligomers of increasing size when solubilized only in detergent, which is consistent with multiple stacking of AqpZ tetramers. We observed images consistent with both of these filaments in negative staining EM conditions, but only thicker filaments in cryo-EM conditions. We hypothesize that the apparent nanodisc side-to-side arrangement that can only be visualized in negative staining conditions is related to artifacts due to the sample preparation. Filaments of any kind were not observed in EM when nanodiscs did not contain AqpZ, or after addition of detergent into the nanodisc cryo-EM preparation, at concentrations that did not disrupt nanodisc formation. To our knowledge, these filaments have not been observed in nanodiscs preparations of other membrane proteins. AqpZ, like other aquaporins has a charge asymmetry between the cytoplasmic (more positive) and the extracellular sides, which may explain the likely head-to-tail stacking observed, both in nanodisc preparations and also in detergent micelles.
A Strategical Improvement in the Performance of CO2/N2 Gas Permeation via Conjugation of L-Tyrosine onto Chitosan Membrane

Rubbery polymeric membranes, containing amine carriers, have received much attention in CO2 separation because of their easy fabrication, low cost, and excellent separation performance. The present study focuses on the versatile aspects of covalent conjugation of L-tyrosine (Tyr) onto the high molecular weight chitosan (CS) accomplished by using carbodiimide as a coupling agent for CO2/N2 separation. The fabricated membrane was subjected to FTIR, XRD, TGA, AFM, FESEM, and moisture retention tests to examine the thermal and physicochemical properties. The defect-free dense layer of tyrosine-conjugated-chitosan, with active layer thickness within the range of ~600 nm, was cast and employed for mixed gas (CO2/N2) separation study in the temperature range of 25−115 °C in both dry and swollen conditions and compared to that of a neat CS membrane. An enhancement in the thermal stability and amorphousness was displayed by TGA and XRD spectra, respectively, for the prepared membranes. The fabricated membrane showed reasonably good CO2 permeance of around 103 GPU and CO2/N2 selectivity of 32 by maintaining a sweep/feed moisture flow rate of 0.05/0.03 mL/min, respectively, an operating temperature of 85 °C, and a feed pressure of 32 psi. The composite membrane demonstrated high permeance because of the chemical grafting compared to the bare chitosan. Additionally, the excellent moisture retention capacity of the fabricated membrane accelerates high CO2 uptake by amine carriers, owing to the reversible zwitterion reaction. All the features make this membrane a potential membrane material for CO2 capture.
CysB Is a Key Regulator of the Antifungal Activity of Burkholderia pyrrocinia JK-SH007

Burkholderia pyrrocinia JK-SH007 can effectively control poplar canker caused by pathogenic fungi. Its antifungal mechanism remains to be explored. Here, we characterized the functional role of CysB in B. pyrrocinia JK-SH007. This protein was shown to be responsible for the synthesis of cysteine and the siderophore ornibactin, as well as the antifungal activity of B. pyrrocinia JK-SH007. We found that deletion of the cysB gene reduced the antifungal activity and production of the siderophore ornibactin in B. pyrrocinia JK-SH007. However, supplementation with cysteine largely restored these two abilities in the mutant. Further global transcriptome analysis demonstrated that the amino acid metabolic pathway was significantly affected and that some sRNAs were significantly upregulated and targeted the iron–sulfur metabolic pathway by TargetRNA2 prediction. Therefore, we suggest that, in B. pyrrocinia JK-SH007, CysB can regulate the expression of genes related to Fe–S clusters in the iron–sulfur metabolic pathway to affect the antifungal activity of B. pyrrocinia JK-SH007. These findings provide new insights into the various biological functions regulated by CysB in B. pyrrocinia JK-SH007 and the relationship between iron–sulfur metabolic pathways and fungal inhibitory substances. Additionally, they lay the foundation for further investigation of the main antagonistic substances of B. pyrrocinia JK-SH007.
Design And Analysis Of Integrated Dual-Input Dual-Output DC-DC Converter For Electric Vehicle And Drives Applications

To enable efficient and reliable operation of Electric Vehicles (EV)/Drives, optimization of power electronic converters in terms of size and cost is necessary. EVs and also some drive applications require a minimum of two different DC voltage levels, one for supplying the electric motor and the other for auxiliary loads. To supply these loads, electric vehicles utilize a battery along with renewable sources like solar panels and fuel cell. Incorporation of several sources and loads into a single system is usually achieved using two or more conventional DC-DC converters. But this increases the size and complexity of the converter system. A new Dual-Input Dual-Output (DIDO) DC-DC converter with reduced component count is introduced as an effective alternative. This converter integrates a PV system with a battery to provide boost and buck voltages at the two output ports capable of feeding the EV loads, namely DC motor and auxiliary load rated at 72V and 24V respectively. The proposed converter is operated in battery charging and discharging mode and a system efficiency of around 90% is (a) obtained. Performance of the converter is analyzed and compared with other DIDO topologies. Simulation of the converter is carried out using MATLAB-Simulink and the results are validated.
Pore Structure Characterization of Shale Reservoir Using Nitrogen Adsorption-Desorption

This research paper aimed to quantitively characterize the pore structure of shale reservoirs. Six samples of Silurian shale from the Ahnet basin were selected for nitrogen adsorption-desorption analysis. Experimental findings showed that all the samples are mainly composed of mesopores with slit-like shaped pores, as well as the Barrett-Joyner-Halenda pore volume ranging from 0.014 to 0.046 cm3/ 100 g, where the lowest value has recorded in the AHTT-1 sample, whereas the highest one in AHTT-6, while the rest samples (AHTT-2, AHTT-3, AHTT-4, AHTT-5) have a similar average value of 0.03 cm3/ 100 g. Meanwhile, the surface area and pore size distribution were in the range of 3.8 to 11.1 m2 / g and 1.7 to 40 nm, respectively. Nanoparticle size was in the range of 540 to 1589.2 nm, this parameter showed a strong negative correlation with both the surface area and pore volume. Findings can contribute significantly to the pore structure evaluation and characterization of the Silurian shale reservoir in the Ahnet basin.
NodalNet: A Node Based Programming Interactive Educational Tool in Developing Neural Network for Beginners

Machine Learning, a subset of Artificial Intelligence, is now being integrated into image and speech classification, object and action recognition, medical image analysis, security and surveillance, and autonomous driving. It is usually executed by creating a neural network which is defined as the process of modeling a computer system to mimic the function of the human brain. However, learning to develop a neural network is a challenge for students, especially those who have little background in programming. This study focuses on developing a node-based programming tool called NodalNet, a beginner-friendly and interactive educational tool for creating a neural network designed for image classification applications. Java programming language, Java swing library, and Eclipse integrated development environment (IDE) are used to build the NodalNet. It can be used for offline deployment using laptops, and computers, and for online deployment using a technique called the application programming interface (API) method. NodalNet has built-in components that can be connected through nodes, and it has a data labeling feature that helps the users in classifying the raw data inputs used before the training process. The NodalNet can develop and train simple neural networks, some image recognition samples are FlowerNET, DogCatNET, and NumberNET which have significant results in their accuracy. A survey conducted shows that 77.78% of the respondents answered that it is easy to train using the NodalNet. This tool offers a positive impact as an interactive educational tool for developing a neural network.
A Compact Aperture-Sharing Sub-6 GHz/Millimeter-Wave Dual-Band Antenna

In this article, a microwave (MW)/millimeter wave (MMW) aperture-sharing antenna is proposed. The antenna is constructed using two orthogonal columns of grounded vias from a 3.5 GHz slot-loaded half-mode substrate-integrated waveguide (HMSIW) antenna. These vias are reused to create two sets of 1 × 4 MMW substrate-integrated dielectric resonator antenna (SIDRA) arrays. With this proposed partial structure reuse strategy, the MW antenna and MMW arrays can be integrated in a shared-aperture manner, improving space utilization and enabling dual-polarized beam steering capability in the MMW band, which is highly desirable for multiple-input multipleoutput (MIMO) applications. The integrated antenna prototype was manufactured and measured for verification. The 3.5 GHz antenna has a relative bandwidth of 3.4% (3.44–3.56 GHz) with a peak antenna gain of 5.34 dBi, and the 28 GHz antenna arrays cover the frequency range of 26.5–29.8 GHz (11.8%) and attain a measured peak antenna gain of 11.0 dBi. Specifically, the 28 GHz antenna arrays can realize dual-polarization and ±45° beam steering capability. The dual-band antenna has a very compact structure, and it is applicable for 5G mobile communication terminals.
A SECOND ORDER ACCURATE LEVEL SET METHOD ON QUADTREE GRIDS

We present a level set method on non-graded adaptive Cartesian grids, i.e. grids for which the ratio between adjacent cells is not constrained. We use quadtree and octree data structures to represent the grid and a simple algorithm to generate a mesh with the finest resolution at the interface. In particular, we present (1) a locally third order accurate reinitialization scheme that transforms an arbitrary level set function into a signed distance function, (2) a second order accurate semi-Lagrangian methods to evolve the linear level set advection equation under an externally generated velocity field, (3) a second order accurate upwind method to evolve the non-linear level set equation under a normal velocity as well as to extrapolate scalar quantities across an interface in the normal direction, and (4) a semi-implicit scheme to evolve the interface under mean curvature. Combined, we obtain a level set method on adaptive Cartesian grids with a negligible amount of mass loss. We propose numerical examples in two and three spatial dimensions to demonstrate the accuracy of the method.
Semi-Automatic Construction of Virtual Reality Environment for Highway Work Zone Training using Open-Source Tools

In this paper, we present a computer vision-based approach to assist in creating a virtual reality (VR) environment for training state transportation agency staff that inspect highway work zones. Current VR work zone environments are manually created by developers based on drive-through videos or work zone plans, which require a considerable amount of time. We leveraged two open-source tools, YOLO and Road Architect in Unity, to improve the efficiency of environment creation. The YOLO open-source tool processes the video input and creates an output file that contains work zone features (i.e., roadway geometrics and traffic signs) and their locations. The virtual environment in Unity was created by Road Architect using its user-friendly interface. Our results showed that the proposed method was able to significantly reduce the development time for creating training modules. The semi-automatic method can be applied to other training applications where VR-environment creation is time consuming.
I'm Transforming! Effects of Visual Transitions to Change of Avatar on the Sense of Embodiment in AR

Virtual avatars are more and more often featured in Virtual Reality (VR) and Augmented Reality (AR) applications. When embodying a virtual avatar, one may desire to change of appearance over the course of the embodiment. However, switching suddenly from one appearance to another can break the continuity of the user experience and potentially impact the sense of embodiment (SoE), especially when the new appearance is very different. In this paper, we explore how applying smooth visual transitions at the moment of the change can help to maintain the SoE and benefit the general user experience. To address this, we implemented an AR system allowing users to embody a regular-shaped avatar that can be transformed into a muscular one through a visual effect. The avatar's transformation can be triggered either by the user through physical action (“active” transition), or automatically launched by the system (“passive” transition). We conducted a user study to evaluate the effects of these two types of transformations on the SoE by comparing them to control conditions where there was no visual feedback of the transformation. Our results show that changing the appearance of one's avatar with an active transition (with visual feedback), compared to a passive transition, helps to maintain the user's sense of agency, a component of the SoE. They also partially suggest that the Proteus effects experienced during the embodiment were enhanced by these transitions. Therefore, we conclude that visual effects controlled by the user when changing their avatar's appearance can benefit their experience by preserving the SoE and intensifying the Proteus effects.