Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Relationship between the Invariance and Conservation Laws of Differential Equations

In this paper, we highlight the complimentary nature of the results of Anco & Bluman and Ibragimov in the construction of conservation laws that whilst the former establishes the role of multipliers, the latter presents a formal procedure to determine the flows. Secondly, we show that there is an underlying relationship between the symmetries and conservation laws in a general setting, extending the results of Kara & Mahomed. The results take apparently differently forms for point symmetry generators and higher-order symmetries. Similarities exist, to some extent, with a previously established result relating symmetries and multipliers of a differential equation. A number of examples are presented.
High-Dimensional Topological Field Theory, Positivity, and Exotic Smooth Spheres

In previous work, we proposed a general framework of positive topological field theories (TFTs) based on Eilenberg's notion of summation completeness for semirings. In the present paper, we apply this framework in constructing explicitly a concrete positive TFT defined on smooth manifolds of any dimension greater than 1. We prove that this positive TFT detects exotic smooth spheres. We show further that polynomial invariants (subject to boundary conditions) can be extracted from the state sum if the dimension of the cobordisms is at least 3.
Enhancement of fluoride release in glass ionomer cements modified with titanium dioxide nanoparticles

Background: Several efforts have been made to improve the glass ionomer cements (GICs) properties with nanotechnology. Fluoride release in once of most beneficial properties of GICs. The purpose of this study was to evaluate the fluoride release, recharge, and cytotoxicity in GICs reinforced with titanium dioxide nanoparticles (TiO2N). Objective: Evaluate the fluoride release, recharge, and cytotoxicity in GICs reinforced with TiO2N. Methods: Four GICs, FUJI IX EXTRA (G1c), KETAC MOLAR (G2c), IONOFILL MOLAR (G3c), and FUJI IX (G4c) were combined with TiO2N (G1e, G2e, G3e, and G4e) and divided into blocks of 5-mm width and 1-mm thickness 10 each. A total of 80 samples were arranged as follows: GICs alone as negative control (n = 40) and GICs + TiO2N as experimental groups (n = 40). The fluoride release was determined for periods of 1, 2, 6, 10, 31, 90, 180, 240, and 300 days. On days 30 and 179, samples were recharged by submerging in 1 mL of 20,000 ppm sodium fluoride gel. Cytotoxic activity was carried out with gingival fibroblasts, using 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide cell viability assay. Results: The experimental groups obtained the highest and more constant fluoride released when compared to control groups. After the first recharge, experimental groups (G1e, G3e, and G4e) showed statistically significant results (P = .001, 0.010, and 0.001 respectively) enhancing their recharge ability regarding control groups. The second recharge showed better results in G1e concerning the rest of the groups. No cytotoxic activity was observed in all experimental groups, although significant differences were observed in G3e and G4e regarding control group. Conclusion: The incorporation of TiO2N enhance the fluoride release in glass ionomers with a noncytotoxic effect on human gingival fibroblasts.
The efficacy and safety of catheter balloon dilatation in the treatment of dysphagia after stroke: A protocol for systematic review and meta-analysis

Background: Dysphagia is a serious complication after stroke, which has a significant influence on the health as well as life quality of global people. Patients with dysphagia tend to be a higher risk rate of an aspiration than general person. Catheter balloon dilatation is an additional therapy for treating dysphagia in recent years, which can improve the symptom of achalasia of cricopharyngeal muscle. This research will be used for confirming the efficacy and safety of the catheter balloon dilatation for resolving dysphagia. Methods: We intend to search literature related to the research in different databases, for instance, China National Knowledge Infrastructure, Wanfang Data, PubMed, Cochrane Library, and Embase up to January 2022. Literature selection, data collection, as well as assessment of bias risk, will be carried out by 2 independent researchers. Data analysis will be conducted by using Stata and review manager 5.4. Results: The results will be submitted to a peer-reviewed journal. Conclusion: The research will verify whether or not catheter balloon dilatation can improve dysphagia by submitting high-quality data syntheses. Registration number: CRD42022358433.
Polyadic systems, representations and quantum groups

Polyadic systems and their representations are reviewed and a classification of general polyadic systems is presented. A new multiplace generalization of associativity preserving homomorphisms, a 'heteromorphism' which connects polyadic systems having unequal arities, is introduced via an explicit formula, together with related definitions for multiplace representations and multiactions. Concrete examples of matrix representations for some ternary groups are then reviewed. Ternary algebras and Hopf algebras are defined, and their properties are studied. At the end some ternary generalizations of quantum groups and the Yang-Baxter equation are presented.
Solutions and reductions for radiative energy transport in laser-heated plasma

A full symmetry classification is given for models of energy transport in radiant plasma when the mass density is spatially variable and the diffusivity is nonlinear. A systematic search for conservation laws also leads to some potential symmetries and to an integrable nonlinear model. Classical point symmetries, potential symmetries, and nonclassical symmetries are used to effect variable reductions and exact solutions. The simplest time-dependent solution is shown to be stable and relevant to a closed system.
Avoiding extremes using partial control

Dynamical systems can be prone to severe fluctuations due to the presence of chaotic dynamics. This paper explains for a toy chaotic economic model how such a system can be regulated by the application of relatively weak control to keep the system confined to a bounded region of the phase space, even in the presence of strong external disturbances. Since the control here is weaker than the disturbance, the system cannot be controlled to a particular trajectory, but under certain circumstances it can be partially controlled to avoid extreme values. Partial control depends on the existence of a certain set called a ‘safe sets’. We describe the safe set and how it varies with parameters, sometimes continuously and sometimes discontinuously.
Lifting Galois representations to ramified coefficient fields

Let $p>5$ be a prime integer and $K/\mathbb{Q}_p$ a finite ramified extension with ring of integers $\mathcal{O}$ and uniformizer $\pi$. Let $n>1$ be a positive integer and $\rho_n:G_\mathbb{Q} \to \text{GL}_2(\mathcal{O}/\pi^n)$ be a continuous Galois representation. In this article we prove that under some technical hypotheses the representation $\rho_n$ can be lifted to a representation $\rho:G_\mathbb{Q} \to \text{GL}_2(\mathcal{O})$. Furthermore, we can pick the lift restriction to inertia at any finite set of primes (at the cost of allowing some extra ramification) and get a deformation problem whose universal ring is isomorphic to $W(\mathbb{F})[[X]]$. The lifts constructed are "nearly ordinary" (not necessarily Hodge-Tate) but we can prove the existence of ordinary modular points (up to twist).
Holomorphic simplicity constraints for 4D spinfoam models

Within the framework of spinfoam models, we revisit the simplicity constraints reducing topological BF theory to 4D Riemannian gravity. We use the reformulation of SU(2) intertwiners and spin networks in terms of spinors, which has come out from both the recently developed U(N) framework for SU(2) intertwiners and the twisted geometry approach to spin networks and spinfoam boundary states. Using these tools, we are able to perform a holomorphic/anti-holomorphic splitting of the simplicity constraints and define a new set of holomorphic simplicity constraints, which are equivalent to the standard ones at the classical level and which can be imposed strongly on intertwiners at the quantum level. We then show how to solve these new holomorphic simplicity constraints using coherent intertwiner states. We further define the corresponding coherent spin network functionals and introduce a new spinfoam model for 4D Riemannian gravity based on these holomorphic simplicity constraints and whose amplitudes are defined from the evaluation of the new coherent spin networks.
Improving SAGA via a Probabilistic Interpolation with Gradient Descent

We develop and analyze a new algorithm for empirical risk minimization, which is the key paradigm for training supervised machine learning models. Our method---SAGD---is based on a probabilistic interpolation of SAGA and gradient descent (GD). In particular, in each iteration we take a gradient step with probability $q$ and a SAGA step with probability $1-q$. We show that, surprisingly, the total expected complexity of the method (which is obtained by multiplying the number of iterations by the expected number of gradients computed in each iteration) is minimized for a non-trivial probability $q$. For example, for a well conditioned problem the choice $q=1/(n-1)^2$, where $n$ is the number of data samples, gives a method with an overall complexity which is better than both the complexity of GD and SAGA. We further generalize the results to a probabilistic interpolation of SAGA and minibatch SAGA, which allows us to compute both the optimal probability and the optimal minibatch size. While the theoretical improvement may not be large, the practical improvement is robustly present across all synthetic and real data we tested for, and can be substantial. Our theoretical results suggest that for this optimal minibatch size our method achieves linear speedup in minibatch size, which is of key practical importance as minibatch implementations are used to train machine learning models in practice. Moreover, empirical evidence suggest that a linear speedup in minibatch size can be attained with a parallel implementation.
MilliFit: Millimeter-Wave Wireless Sensing Based At-Home Exercise Classification

The proliferation of smart, ubiquitous devices has inspired many researchers to develop at-home personal documentation systems. One application of such systems is at-home exercise monitoring, which is important for remote healthcare and fitness regimens. This work explores a millimeter-wave (mmWave) wireless sensing based at-home exercise monitoring using commodity devices. We leverage the mmWave signals reflected off a person exercising and design a deep-learning network that uses a combination of CNN and LSTM to classify the activities. We evaluate the performance of our classifier extensively, using several input signal representations.
MDT-based Intelligent Route Selection for 5G-Enabled Connected Ambulances

The fifth generation of cellular network (5G) can facilitate in-ambulance patient monitoring, diagnosis, and treatment by a remote specialist. However, 5G coverage and link quality can vary in time and location. The ambulance route selection can help meet the communication requirements of the in-ambulance applications. In this paper, we propose an innovative ambulance route selection framework which combines the communication requirements along with the network coverage and resources. The framework leverages the minimization of drive test (MDT) data to estimate the network coverage along the ambulance routes. To address the uneven distribution of location-based user-generated MDT data, we examine the performance and trustworthiness of several interpolation techniques to enrich the global MDT map for route selection. A simulated analysis shows that the proposed framework can dynamically adapt to varying application requirements as well as rapidly changing network conditions such as outages. Results also reveal that nearest neighbor and kriging interpolation techniques help complement the proposed framework by addressing the data sparsity problem.
Absorption Kinetics of Gas Influxes into Nonaqueous Fluids During Riser Gas Handling Events

The absorption kinetics of an influx of hydrocarbon gas into a nonaqueous base fluid was experimentally investigated under various conditions. The gas influx was simulated by continuously injecting methane at different pressures and superficial gas velocities into an experimental column filled with nonaqueous base fluids. The concentration of gas dissolved into the base fluids was measured at various time steps until complete saturation was reached. A model containing an absorption coefficient, 𝑘 # 𝑎 , was used to describe the process. The time dependent absorption mass transfer coefficient can be determined for each set of experimental conditions to develop a relationship between 𝑘 # 𝑎 and the input parameters. The effects of pressure, superficial gas velocity and base fluid on the mass transfer absorption coefficient were examined in the study. The impact of the time-dependent gas absorption process on gas migration behaviors during a riser gas handling event, were simulated using a simplified two-phase model along with a kinetic mass transfer sub-model based on the experimental study performed in this work. The results of this experimental study and numerical simulations provide better understanding of time dependent absorption of gas influx into uncontaminated muds while migrating and its effects on unloading behaviors with different backpressures, and therefore can be used to optimize and guide operations in such events. during a gas influx will help with earlier kick detection and prevent the influx from going undetected. To better understand this mass transfer between the influx of natural gas and nonaqueous drilling fluid, experimental tests were conducted to
International Journal of Research Publication and Reviews

Cryptography is the facility and glance of secure communication techniques and used for converting the original messages into unreadable form. cipher is classified into classical and modern cipher Caesar cipher is a technique of encrypting messages into unreadable form to protect it from dissentients. Caesar cipher comes under symmetric techniques which contains a secret key for converting the message. The challenges faced by Caesar cipher are that it is easy to hack, provide less security and by looking at patterns. The entire message can be decrypted. To provide more security using techniques like affine cipher, Vigenere cipher, three-pass protocol, columnar cipher all these are used to create an encrypted text which is very hard to decode. Caesar cipher can be encrypted by using all ASCII and extended ASCII characters including alphabets. This will provide an enriched side of Caesar cipher which can defeat all the threats endured by the Caesar cipher.
Optimal switching of a nanomagnet assisted by microwaves

We develop an efficient and general method for optimizing the microwave field that achieves magnetization switching with a smaller static field. This method is based on optimal control and renders an exact solution for the 3D microwave field that triggers the switching of a nanomagnet with a given anisotropy and in an oblique static field. Applying this technique to the particular case of uniaxial anisotropy, we show that the optimal microwave field, that achieves switching with minimal absorbed energy, is modulated both in frequency and in magnitude. Its role is to drive the magnetization from the metastable equilibrium position towards the saddle point and then damping induces the relaxation to the stable equilibrium position. For the pumping to be efficient, the microwave field frequency must match at the early stage of the switching process the proper precession frequency of the magnetization, which depends on the magnitude and direction of the static field. We investigate the effect of the static field (in amplitude and direction) and of damping on the characteristics of the microwave field. We have computed the switching curves in the presence of the optimal microwave field. The results are in qualitative agreement with micro-SQUID experiments on isolated nanoclusters. The strong dependence of the microwave field and that of the switching curve on the damping parameter may be useful in probing damping in various nanoclusters.
Transient Pressure Behavior in Wellbores due to Fluid Gelation

Drilling fluids are desired to develop a gelled structure to improve cutting transport ability during circulation, and to prevent precipitation of cuttings and other constituents in static or no circulation conditions. Despite these advantages, gelation can be detrimental when the circulation is resumed after a period of time due to any operational circumstances since additional energy is required to overcome such a gelled structure. Resultant pressure peaks could fracture the formation, leading to possible safety risks and tremendous cost. In particular, this is important for complex drilling operations with narrow geo-pressure windows, such as those in offshore wells. For these reasons, pressure peaks created when circulation is resumed and the accompanying transient pressure behavior are of significant importance. This study focuses on predicting pressure peaks when pumps are restarted after a static period of time. It includes laboratory and flow loop experiments which enable investigation of such behavior in both small and large scales. Two models are also proposed to predict transient shear stress behavior which permits determination of pressure gradient by considering different shear rates after a variety of resting time intervals. Understanding potential pressure peaks is expected to help if extra care is required when restarting the circulation. Also, predicting such transient pressure behavior might be useful for an automated drilling control system to avoid generating downhole pressure above fracturing pressure gradient of the open hole section.
Arrested phase separation and gel collapse in oil-continuous drilling fluids; a route to barite sag

Static barite sag can occur through a range of mechanisms. In extreme cases and under quiescent conditions in oil-continuous drilling fluids, a free oil layer forms at the upper fluid surface. Such oil-continuous formulations form a strong gel which exhibits the phenomenology of delayed gel collapse commensurate with much simpler depletion flocculated systems described in the recent literature. Here we present a range of data illustrating drilling fluid gel collapse through simple disperse-phase height evolution and x-ray tomography, consistent with arrested phase separation and through intermittency in the gel collapse process consistent with subsequent structural coarsening. Thus, we interpret our results, and therefore one static sag behaviour, as resulting from a complex interplay of structures within the gel.
Face Identification and Expression Recognition using Deep Learning Techniques

In recent years, there has been a lot of research on facial detection and recognition. Identity verification, biometric applications, and numerous securi- ty cameras all rely heavily on facial recognition technology. A deep learning application is facial recognition (DL). Convolution neural networks (CNN) have developed into a reliable facial recognition technique. Due to the great degree of structural similarity between features, it is challenging to recognize comparable faces in the field of face recognition. To advance in this area, the next two elements are required: large scale identical face training datasets are readily available, and a fine-grained face recognition technique is also available. To recognize and analyse various images, a variety of algorithmic procedures like image eigenvalue extraction, recognition, and convolution are performed. Face identification in CNN uses a traditional feature-based classifier that combines features from the Haar cascade and Viola jones algorithms with the open CV library.A face expres- sion identification approach based on a convolutional neural network (CNN) and an image edge detection method is proposed in order to eliminate the labor-intensive procedure of explicit feature extraction in traditional facial expression recognition. Finally, picture edge detection is used to recog- nize facial expressions. The image is normalized, and during the convolution process, the edge of each layer of the image is retrieved. To avoid the edge structure information of the texture image, the extracted edge information is placed on each feature image. The maximum pooling method is then used to process the dimensionally reduced retrieved implicit features. it is impossible to ignore the image's edge information. A portion of the im-age's edge information is lost, which causes blurred edge information in the final synthesis result and has an impact on the table. This study preserves the edge structure information of the texture image by first extracting the edge of each layer of the image during the convolution process, and then superimposing the retrieved edge information on each feature map
Discovering Vulnerabilities in WebAssembly with Code Property Graphs

WebAssembly is a new technology that allows web developers to run native C/C++ on a webpage with near-native performance and therefore much faster than typical JavaScript applications. Currently supported by the most popular browsers, WebAssembly brings implications for the web platform since it enables more complex client apps to run on the browser. The compact binary format, performance, and safety mechanisms present in the language led it to be used beyond the browser platform, being employed in the context of server-side run-times, IoT platforms and edge computing. However, in spite of its be-neﬁts, WebAssembly technology brings some security concerns attached. In particular, vulnerabilities from C and C++ such buﬀer overﬂows can be imported to WebAssembly. The goal of this project is to design and implement a new tool that can statically ﬁnd vulnerabilities in Web-Assembly code. Our approach is to use code property graphs (CPGs), a program representation that has been successfully applied to the detection of vulnerabilities in high-level languages. We propose to adopt this representation into the realm of WebAssembly programs.
An exactly solvable PT?>-symmetric dimer from a Hamiltonian system of nonlinear oscillators with gain and loss

We show that a pair of coupled nonlinear oscillators, of which one oscillator has positive and the other one negative damping of equal rate, can form a Hamiltonian system. Small-amplitude oscillations in this system are governed by a PT? >-symmetric nonlinear Schrödinger dimer with linear and cubic coupling. The dimer also represents a Hamiltonian system and is found to be exactly solvable in elementary functions. We show that the nonlinearity softens the PT? >-symmetry breaking transition in the nonlinearly-coupled dimer: stable periodic and quasiperiodic states with large enough amplitudes persist for an arbitrarily large value of the gain–loss coefficient.
Universal Gysin formulas for the universal Hall-Littlewood functions

It is known that the usual Schur $S$- and $P$-polynomials can be described via the Gysin homomorphisms for flag bundles in the ordinary cohomology theory. Recently, P. Pragacz generalized these Gysin formulas to the Hall-Littlewood polynomials. In this paper, we introduce a {\it universal} analogue of the Hall-Littlewood polynomials, which we call the {\it universal Hall-Littlewood functions}, and give Gysin formulas for various flag bundles in the complex cobordism theory. Furthermore, we give two kinds of the {\it universal} analogue of the schur polynomials, and some Gysin formulas for these functions are established.