Miracle-dz/UniFAR-FTUs huggingface dataset:
Square root law model for the delivery and intestinal absorption of drugs: a case of hydrophilic captopril

Abstract The in vivo release and absorption of drugs are dependent on the interplay between many factors related to compound, formulation, and physiological properties. The mathematical models of oral drug absorption attempt to strike a balance between a complete description that takes into consideration as many independent factors as possible, and simple models that operate with fewer parameters, based mainly on critical factors. The latter models are by far more robust and easier to apply to predict the extent and sometimes even the rate of absorption. The present paper attempted to develop a simple model to describe the time course of absorption of the hydrophilic drug captopril (CPT) at the early phases of absorption, with implications mainly in the induction and early stages of achieving its therapeutic effect. As a phenomenological model, the instantaneous release of CPT was considered in the gastrointestinal fluid, leading to a constant drug concentration for a prolonged time, followed by a ‘long path diffusion’ inside the intestinal wall and a very low concentration at the interface intestinal wall-blood. These conditions regarding CPT concentration were translated into initial and boundary mathematical conditions for the diffusion equation in the intestinal wall. The solution of the diffusion equation led in the end to a square root law describing the dependence between the fraction of the drug absorbed and time. The model was successfully applied to data obtained in five bioequivalence studies: three comparing plasma levels achieved after the administration of a single dose of CPT 50 mg, one evaluating CPT pharmacokinetics after a 100 mg dose, and a fifth comparing CPT pharmacokinetics of two fixed-dose combinations of CPT 50 mg and hydrochlorothiazide 25 mg.
Synthesis of Substituted 2-Phenyl-1H-indoles and their Fungicidal Activity

Heterocyclic compounds form a special class of cyclic organic compounds in which atleast one of the carbon atoms are replaced by heteroatoms like oxygen, nitrogen and sulphur, etc. These compounds are known to possess variety of bioactivities like antifungal, anticancer, antiviral and antimicrobial [1-4] etc. Indoles, also known as benzpyrrole are aromatic nitrogen heterocycles of prime importance containing fused benzene and pyrrole rings. Firstly synthesized by Baeyer and Emmerling [5] from oxindole using zinc dust, indoles have been synthesized by various methods such as catalytic reduction of o-nitrotoluenes [6], anilines and α-haloketones [7,8], cyclization of o-allylanilines [9] and Pd catalyzed coupling of alkynes with substituted iodoanilines [10]. But the Fischer indole synthesis remains the most popular method involving the condensation of phenyl hydrazines with substituted aldehydes or ketones followed by cyclization conventionally [11] as well as under microwave irradiation [12]. Indoles have registered their presence in variety of natural and synthetic compounds. Some of the naturally occurring indole derivatives include indole-3-acetic acid which is a plant growth hormone and tryptophan-derived tryptamine alkaloids like neurotransmitters i.e. serotonin and melatonin. Indoles regulate physiological aspects in bacterial cells primarily including spore formation, drug resistance along with plasmid formation and virulence [13]. Indoles also form a part of drugs like indomethacin (which is used as an anti-inflammatory, an antipyretic and an analgesic), indoxole (an anti-inflammatory and antiSynthesis of Substituted 2-Phenyl-1H-indoles and their Fungicidal Activity
Out-of-distribution detection for fungi images with similar features

In order to create a classification model for fungi, it is necessary to have robustness against out-of-distribution data from the viewpoint of practicality. Therefore, in this paper, we perform out-of-distribution detection on a fungi. Unlike the case of conventional out-of-distribution detection, the characteristics of in-distribution data and out-of-distribution data in this paper are very similar. Therefore, the problem in which conventional methods using out-of-distribution data for validation are not effective is mentioned. We also verify whether the accuracy of out-of-distribution detection can be improved using the attention branch network.
A comparative study of batch ensemble for multi-object tracking approximations in embedded vision

We present a series of adaptations in low probability distributions scenarios to detect and track multiple moving objects of interest. We investigate the benefits of the linearization of the loss trajectory1 in training neural networks, mainly addressing the lack of auto-differentiation in MOTA2 evaluations, and observe what characteristics can support parallelism3 and differential computation and to what extent these observations contributes to our objectives. Using benchmarks from DeepMOT4 and CenterNet,5 we highlight the use of sparsemax activations by mounting a finite number of independent, asynchronous detectors to augment performance and gain from compounded accuracy. ∗ Empirical results show optimistic gains when applying parallelization on low-powered, low-latency embedded systems in cases where automatic differentiation is available.
Freezing Fire – Automated Light-Passes for Stop-Motion VFX

This work proposes and evaluates a method of image-based rendering for integrating light-emitting CG assets with digital photography. The framework consists of a capture stage, in which footage of the scene under varied lighting is acquired, and a reconstruction stage, which outputs the calculated light contribution of the CG element upon the scene. This form of relighting is novel as it embraces scenarios where the light source is intended to be in the frame. The freedom to introduce emissive objects in post opens creative room for light animation and was assessed here as employed in the production of a stop-motion short-film.
Simulating Cloth Using Bilinear Elements

The most widely used cloth simulation algorithms within the computer graphics community are defined exclusively for triangle meshes. However, assets used in production are often made up of non-planar quadrilaterals. Dividing these elements into triangles and then mapping the displacements back to the original mesh results in faceting and tent-like artifacts when quadrilaterals are rendered as bilinear patches. We propose a method to simulate cloth dynamics on quadrilateral meshes directly, drawing on the well studied Koiter thin sheet model [Koiter 1960] to define consistent elastic energies for linear and bilinear elements. The algorithm elides the need for artifact-prone geometric mapping, and has computation times similar to its fully triangular counterpart.
The Tech and Art of Cyberspaces in Cyberpunk 2077

A deep dive into the technology and art behind cyberspace and braindances in Cyberpunk 2077. Braindances are the recorded memories and feelings of individuals, reprojected in the mind of the viewer. To bring this concept into reality, we decided to follow an unconventional approach to rendering environments and characters in real-time. The core visual concept was based around sparse point clouds and glitch effects. Post processes like datamoshing were used to further hide the underlying geometry, aiming for a surreal, out-of-body experience.
PS-LSTM:Popularity Analysis And Social Network For Point-Of-Interest Recommendation In Previously Unvisited Locations

With the development of technology and the gradual convenience of transportation, due to various reasons such as travel or business trip, people often leave their familiar areas and visit relatively unfamiliar areas in real life.It will be presents a new problem to the recommendation algorithm, namely the POI recommendation in previously unvisited locations. In order to make the recommendation system still provide users with high quality POI recommendation in this situation, this paper proposes a POI recommendation algorithm based on deep learning and popularity analysis.In the model, we integrate the popularity of POI and social network to alleviate the cold start problem . When integrating social information, we use attention mechanism to measure the influence of different friends on users, and then weigh it to get the social impact. When fusing the information of POI popularity, we consider that the influence of POI popularity varies with geographical distance and time, so we construct a dynamic popularity influence vector in the model.For making better utilize of the characteristics of the check-in sequence, we use the recurrent neural network to model the spatiotemporal sequence of the users’ POI check-in. Finally, MLP is used to integrate social impact, popularity characteristics and sequence information to recommend for users.The proposed algorithm is verified on yelp which is a real city dataset and compared with several classic POI recommendation algorithms.Experimental results show that the proposed algorithm could achieve a better accuracy.
RSS Remeasurement Estimation for Indoor Positioning System with Generative Adversarial Network Model

With the rapid development of computer technology in recent years, the demand for services to obtain location information is increasing day by day. The expansion of mobile computing has prompted wireless fidelity(WiFi)-based indoor localization to be one of the most attractive and promising techniques for ubiquitous application. The main problem with this technology is that received signal strength (RSS) values need to be manually sampled to create a WiFi fingerprint database in the offline database creation stage. As any change in the environment may affect signal propagation, the fingerprint database must be repeatedly updated and maintained, and this is a time-consuming task. In this study, we propose the Adaptive Context Generative Adversarial Networks (ACOGAN) model by adopting random sampling RSS values as the feedbacks and predicting the residual RSS values as the missing fingerprints to solve the remeasurement problem. By employing feedbacks, the missing fingerprints can be rebuilt efficiently and accurately using the ACOGAN model. The experimental results not only illustrate the superiority of the proposed ACOGAN model on field and simulated environments but also demonstrate its robustness to satisfy the time consumption on the learning progress.
Reflectance Estimation for Free-viewpoint Video

We present a method to infer physically-based material properties for free-viewpoint video. Given a multi-camera image feed and reconstructed geometry, our method infers material properties, such as albedo, surface normal, metallic and roughness maps. We use a physically based, differentiable renderer to generate candidate images which are compared against the image feed. Our method searches for material textures which minimise an image-space loss metric between candidate renders and the ground truth image feed. Our method produces results that approximate state of the art reflectance capture, and produces texture maps that are compatible with common real-time and offline shading models.
Global Illumination-Aware Color Remapping with Fidelity for Texture Values

Our aim is to convert an object’s appearance to an arbitrary color considering the light scattering in the entire scene, which is often called the global illumination. Existing stylization methods convert the color of an object with a 1-dimensional texture for 3-dimensional computer graphics to reproduce a typical style used in illustrations and cel animations. However, they cannot express global illumination effects such as color bleedings and soft shadows. We propose a method to compute the global illumination and convert the shading to an arbitrary color. It consists of subpath tracing from the eye to the object, and radiance estimation on the object. The radiance is stored and used later to convert its color. The method reproduces reflections in other objects with the converted color. As a result, we can convert the color of illumination effects such as soft shadows and refractions.
Spatially Adaptive Volume Tools in Bifrost

The level set method offers many advantages over e.g. meshes for modelling and visual effects, but a naïve implementation is both computationally expensive and memory intensive. Narrow band level sets alleviate both issues but are still limited by the finest detail resolved due to uniform resolution along the surface. Voxel structures that are adaptive along the surface improve this [Frisken et al. 2000], but have not seen wide adoption. This is presumably due to difficulties matching the performance of optimized narrow band implementations like industry standard OpenVDB [Museth 2013]. We present the adaptive level set implementation in Bifrost which is competitive with OpenVDB in speed while offering lower memory usage thanks to spatial adaptivity. Our contributions include novel algorithms for adaptive sharpened B-spline interpolation of volumes in general, voxelizing meshes and points into adaptive level set volumes, and meshing adaptive level sets.
Dynamic Projection Mapping for Silkworms

1 INTRIDUCTION Recently, there has been an increasing number of examples of dynamic projection mapping (DPM) applied to plants and animals. However, objects such as animals and plants are deformable, and it is difficult to obtain their shape or attach markers in advance; thus, these objects present a problem for DPM. Here, we propose an automatic generation method of DPM specially designed for silkworms. In addition, the system automatically generates visualeffect animations based on the shape of the projected object. Using this system, we conducted an experiment of projection on a real silkworm. Projections in the Forest [Schoor and Mawad 2014] is one example of a work in which PM is applied to plants and animals. In this previous work, static projection mapping was performed for plants and animals of the forest. Image registration for the mapping was performed manually by the artists, which required a substantial amount of time. For plant leaves with individual motion, a method of DPM that considers the occlusion of the projection area by the viewer has been proposed [Sueyoshi and Morimoto 2019]. This method automatically generates effects that match the shape of the plant. However, leaves exhibit small deformations, and it is difficult
Mathematical Tricks for scalable and appealing crowds in Walt Disney Animation Studios’ ”Raya and the Last Dragon”

The crowds department had to tackle a variety of challenging shots for Walt Disney Animation Studios’ ”Raya and the Last Dragon” such as beetles crawling on top of each other, immense fish simulation or dragon choreography. In order to handle this level of complexity while keeping a good amount of artistic control, we implemented some effective technical solutions such as the use of anisotropic distances in Position based Dynamics (PBD) and boids simulations, procedural animation layers for fish and dragons or distance integral invariant to detect dragon foot contacts.
Critical nodes identification based on comprehensive topological importance in complex networks

The identification of critical nodes in the network is of great significance for the research of the invulnerability and structural stability of complex networks. Most of the existing studies evaluate the importance of nodes in networks from a single structural perspective. Considering the local and global characteristics of the network, an identification algorithm of critical nodes in complex networks based on comprehensive topological importance (CTI) is proposed. The algorithm uses the theory of multiple attribute decision making (MADM) to quantitatively analyze the influence of different attributes on nodes and determine the comprehensive topology importance of nodes, which represents their structural importance in complex networks. Based on two simulation networks and five classical real networks, the proposed algorithm is proved to be superior to DC, LLS, P and WL indexes based on local information and BC indexes based on global information through the change of network efficiency under critical nodes attacking.
Photonic Rendering for Hair Cuticles using High Accuracy NS-FDTD method

The internal structure of hair consists of three layers: the cuticle, the cortex, and the medulla, and there are multiple membrane structures inside the cuticle. Light incident on these subwavelength structures is subject to scattering and interference phenomena, and the reflected highlights vary depending on the viewing angle. This phenomenon of light coloration due to the microstructure is called structural coloring or photonic coloration. It shows a unique specular highlight and determines the magnitude of the specular highlight, which is not observable in the linear optics of CG. In the case of hairs, this structural coloring or photonic coloration occurs in addition to the simple surface reflections and the backscattering lights, which penetrate the hair and are absorbed by the melanin pigment. In the present report, we mainly discuss the effects of the structural coloring first caused by the multi-layered structure in the cuticle region on the hair surface, simulating the electromagnetic field using the NS-FDTD (Non-Standard Finite Difference in Time Domain) method. In addition, we also discuss the backscattering phenomena inside the hair fibers.
Dynamic Diffuse Global Illumination Resampling

Interactive global illumination remains a challenge in radiometrically and geometrically complex scenes. Specialized sampling strategies are effective for specular and near‐specular transport because the scattering has relatively low directional variance per scattering event. In contrast, the high variance from transport paths comprising multiple rough glossy or diffuse scattering events remains notoriously difficult to resolve with a small number of samples. We extend unidirectional path tracing to address this by combining screen‐space reservoir resampling and sparse world‐space probes, significantly improving sample efficiency for transport contributions that terminate on diffuse scattering events. Our experiments demonstrate a clear improvement—at equal time and equal quality—over purely path traced and purely probe‐based baselines. Moreover, when combined with commodity denoisers, we are able to interactively render global illumination in complex scenes.
Purification and characterization of cellulase from a novel isolate of Trichoderma longibrachiatum

ABSTRACT In the present study, the isolation, purification and characterization of a complex enzyme, cellulase, was carried out using a new local isolate of the fungus Trichoderma longibrachiatum (KM274866) from wood chips, with a view to explore its utility in the biofuel industry. The fungus was grown on a selected natural substrate, sugarcane bagasse, based on cost considerations for enzyme production. The enzyme was purified 14.82 fold with a yield of 25.8% and specific activity of 30 U/mg of protein. The molecular mass of the enzyme was found to be 67 ± 1 KDa. The optimum pH was 4.8, but the enzyme was stable at a pH range of 3–6. Optimum temperature was 45 °C, but the stability range of the enzyme was 30–55 °C. Metal ions such as Ca2+, Na+, Mg2+, Zn2+ and Fe2+ enhanced enzyme activity. Triton X100 in the medium resulted in a significant increase of enzyme activity compared to other group specific reagents. KM and Vmax for the enzyme were found to be 0.121 mg/ml and 0.421 μmol/min, respectively, against the substrate carboxy methyl cellulose. As the enzyme is from an inexpensive source, it will be most useful in the preparation of bioethanol for the biofuel industry.
DNA‐Au Nanomachine Equipped with i‐Motif and G‐Quadruplex for Triple Combinatorial Anti‐Tumor Therapy

In the present study, the design, construction, and operation of a functional DNA‐decorated dynamic gold (Au) nanomachine as a therapeutic agent for triple combinatorial anti‐cancer therapy are revealed. Taking advantage of the intrinsic optical properties of Au nanoparticles, which depend on their size, a cytosine rich i‐motif sequence is employed for intracellular pH‐sensitive duplex dissociation and subsequent aggregation of the DNA‐Au nanomachine, enabling anticancer drug release and photothermal ablation upon irradiation with infrared light. Moreover, another functional DNA sequence, a G‐quadruplex, is exploited for the stable loading and intracellular delivery of a photosensitizer to achieve effective photodynamic therapy under red light illumination. The G‐quadruplex‐assisted enhanced reactive oxygen species generation, pH‐responsive dynamic aggregation behavior, consequent drug release, and the photothermal effect are investigated. Furthermore, the combinatorial chemo, photodynamic, and photothermal therapeutic effects of the functional DNA‐decorated Au nanomachines are evaluated in vitro and in vivo using a triple negative breast cancer model.
The mechanism of ultrafast supercapacitors

While microporous carbon is considered as a prime candidate for the energy storage application of supercapacitors, graphene is usually used for AC line-filtering capacitors. Surprisingly, the rate capability of the latter is a few orders of magnitude higher than that of the former. The interesting point is that such ultrafast performance can be achieved when the graphene sheets are vertically aligned, as the rate capability of ordinary graphene electrodes is similar to that of microporous supercapacitors. Understanding the actual role of the graphene alignment can shed light on the underlying mechanism to design faster supercapacitors for the energy storage purpose too. It is discussed that the classic double layer models cannot explain the critical importance of the graphene orientation. By reviewing the experimental evidence reported in the literature, the possibility of a different mechanism is justified. Furthermore, the impedance model of supercapacitors, which can be a guiding star in this direction, is explained from a practical perspective.
Global adaptive output regulation for nonlinear systems with full-state constraints

ABSTRACT The paper investigates the global adaptive output regulation problem (ORP) for nonlinear systems with full-state constraints (FSCs). First, in order to avoid the disadvantages of barrier Lyapunov functions (BLFs) method and logarithmic constraint functions, radical constraint functions method is proposed to solve the FSCs problem of nonlinear systems. Second, a new internal model is designed based on the regulator equations. Third, the ORP of nonlinear systems is transformed into a stabilization problem. Then, according to the changing supply functions method and the Lyapunov analysis method, a non-backstepping control algorithm is proposed to ensure that all signals of the closed-loop system are globally asymptotically bounded, the tracking error is asymptotically stable, and all states of the system can be constrained. Finally, two simulation examples show the effectiveness of the control algorithm.