bluuebunny/crossref_metadata_2025_split huggingface dataset:
Steady state entropy production rate for scalar Langevin field theories
Authors: Li Yuting I , Cates Michael E 
Published: January 2021

Abstract
The entropy production rate (EPR) offers a quantitative measure of time reversal symmetry breaking in non-equilibrium systems. It can be defined either at particle level or at the level of coarse-grained fields such as density; the EPR for the latter quantifies the extent to which these coarse-grained fields behave irreversibly. In this work, we first develop a general method to compute the EPR of scalar Langevin field theories with additive noise. This large class of theories includes active versions of model A (non-conserved density dynamics) and model B (conserved) and also models where both types of dynamics are simultaneously present (such as model AB (2020 J. Stat. Mech. 05206)). Treating the scalar field ϕ (and its time derivative

ϕ

̇

) as the sole observable(s), we arrive at an expression for the EPR that is non-negative for every field configuration and is quadratic in the time-antisymmetric component of the dynamics. Our general expression is a function of the quasipotential, which determines the full probability distribution for configurations, and is not generally calculable. To alleviate this difficulty, we present a small-noise expansion of the EPR, which only requires knowledge of the deterministic (mean-field) solution for the scalar field in steady state, which generally is calculable, at least numerically. We demonstrate this calculation for the case of model AB (2020 J. Stat. Mech. 05206). We then present a similar EPR calculation for model AB with the conservative and non-conservative contributions to

ϕ

̇

=

ϕ

̇

A

+

ϕ

̇

B

viewed as separately observable quantities. The results are qualitatively different, confirming that the field-level EPR depends on the choice of coarse-grained information retained within the dynamical description.
Non-monotonic nucleus-nucleus potential and incompressibility of infinite cold nuclear matter
Authors: Basak A K , Hossain S , Uddin M A , Tariq A S B 
Published: January 2021

Abstract
A novel method for the determination of the yet not well-known quantity of nuclear incompressibility, K is presented. Non-monotonic (NM) nucleus-nucleus potentials from the energy-density functional (EDF) theory including the Pauli principle have been considered for K in the range 188-266 MeV. The experimental cross sections of 16O+16O elastic scattering over the 31-350 MeV incident energies have been analyzed in the optical model using the NM potentials. Sensitivity of K on the elastic scattering data is studied and its value for infinite cold nuclear matter deduced to be 222 ± 5 MeV
Remarkable class of materials: Band structures and optical properties of non-superconducting and superconducting MAX phases
Authors: Islam A K M A 
Published: January 2021

Abstract
The MAX phases, due to their nanolaminated crystal structure, are found to be exciting materials which combine certain best attributes of metals (good electrical and thermal conductivity, low hardness, machinability, damage tolerance and thermal shock resistance) with those of ceramics (high temperature strength, high elastic moduli, oxidation and corrosion resistance). Over 70 MAX phases are in existence, amongst which there are eight low-temperature superconductors. Thus a vast majority of the MAX phases are not superconductors. In the present review, emphasis will be made on the theoretical works conducted in recent years in our laboratory to understand the band structure and optical properties of several non-superconducting (particularly Zr-metal based phases) and the available superconducting MAX phases.
Bose condensation and the Casimir effects of an imperfect Bose gas in a d-dimensional configuration space
Authors: Bhuiyan G M 
Published: January 2021

Abstract
Some properties of an ideal gas of massive bosons in a mean field potential and, confined between two infinite parallel slabs in a d-dimensional configuration space are investigated systematically. Here, one particle density of states approach is employed to study the critical temperature, shift of density, Casimir effects and critical exponents, starting from the evaluation of the grand canonical free energy in d-dimension. We have found that, the shift of density, Casimir force and the critical temperature depend on the space dimensionality. But the Casimir force decays as an inverse power law of the distance between two slabs in the condensate and, decays exponentially in the non-condensed state situated very close to the point of phase transition. Specifically, this study enabled us to predict the shift of the density of boson in the excited states due to mean field potential, and also the dimensional dependence of the critical exponent. The form of the critical exponent is found to be

1

d
−
2

for the imperfect Bose gas. This leads to a value of critical exponent 1 for d = 3. Most interestingly, in the limit when the mean field potential goes to zero the resulting expressions for the above properties coincide with those of the ideal Bose gas.
Non-monotonic potential description of alpha-40Carefractive elastic scattering
Authors: Shahinur Islam M , Billah M M , Basak A K 
Published: January 2021

Abstract
Experimental differential cross sections of elastic scattering by 40Ca, over a wide range of incident energies, have been analyzed in terms of non-monotonic (NM) potentials, generated from the energy density functional (EDF) theory using a realistic two-nucleon potential coupled with an appropriate consideration of the Pauli principle. The Airy structure of the nuclear rainbow scattering data in the energy range of 36.1–42.6 MeV is well accounted for the first time by the shallow NM potential.
Non-monotonic shallow nucleus-nucleus potential for heavy-ion elastic scattering2
Authors: Sujan Islam M , Majumder R , Hossain S , Nilima Athoy , Sayed M A , Shariful Islam M , Billah M M , Azad M M B , Tariq A S B , Uddin M A , Basak A K 
Published: January 2021

Abstract
‘Goldberg criterion’ [Goldberg and Smith, Phys. Rev. Lett. 29 (1972) 500] tells that at sufficiently high energies, where pronounced refractive scattering with nuclear rainbow oscillations are followed by an ‘exponential-type falloff’ in the angular distribution, discrete ambiguities are eliminated for the deep monotonic potential. The criterion is also confirmed in the work of Bartnitzky et al. [Phys. Lett. B 365 (1996) 23] on the 16O+16O elastic scattering in the energy range of 250 - 704 MeV. However, their finding ‘using model-independent potentials’ suggests that heavy-ion elastic scattering data unambiguously favour deep potentials. The Goldberg criterion is examined in our work for non-monotonic shallow potentials using the 16O+16O elastic scattering at energy region up to 350 MeV.
Anharmonicity in light nuclei near drip lines
Authors: Majumder Anup , Bary Malik F 
Published: January 2021

Abstract
Single-particle energy levels of nucleons moving in an anisotropic harmonic oscillator potential along with a spin-orbit and an orbit-orbit interaction have been calculated. The model proposed herein incorporates shapes generated by higher multipolar anisotropies other than the quadruple one. The gaps among the energy levels are strongly dependent on the degree of anisotropy and hence, affect the nucleonic separation energies. For large anisotropies, this characteristic disturbs the occurrences of the usual magic numbers and the sequential ordering of the shells characterized by principal quantum number, N, associated with the elementary shell model. For large asymmetries, the states characterized by higher N, may come down and lie below the energies of the states with lower N and vice versa. This feature of the model provides a natural explanation of intruder states or the island of inversion observed experimentally. For certain choices of the parameters, the large gaps in single nucleonic separation energies could occur at neutron numbers, 10,18,30, and 32 as observed, respectively, in 20Ne, 28Ne, 52Ti, and 54Ti. For neutron as well as proton number 14, the magnitude of this energy gap depends strongly on the choice of the strength of the spin-orbit and orbit-orbit terms. The model provides a simple understanding of the observed fact that some nuclei with proton or neutron number 14 sometimes exhibit this gap but not others. It also provides an interesting insight of having a low-laying (1/2
−
) state in 7He, and confirms the ground state spin and parity of 11Be to be (1/2+) and those of 9He to be (1/2+), both of which have been contentious. This investigation indicated the density distribution, i.e., the shapes of many of nuclei near drip line to be anisotropic having a symmetry about their body-fixed z-axis.
Growth and characterization of Li7La3Zr2O12 single crystals by using floating zone method for use as fast Li-ion conductor†
Authors: Razzaque Sarker Md Abdur , Watauchi Satoshi , Nagao Mashanori , Moazzem Hossain Md , Tanaka Isao 
Published: January 2021

Abstract
Large size high quality Li7La3Zr2O12 single crystals were grown successfully by floating zone (FZ) technique. The grown crystals were characterized by X-ray diffraction, etch pits density measurement, Impedance analysis, Vibrating sample magnetometry (VSM) and UV-Visible spectrometry. The investigation of structural, electrical, optical properties and defect density of the Li7La3Zr2O12 single crystals revealed that the crystals were high quality and free from defects. The chemical analysis showed that the grown crystals have uniform composition along cross-section and growth direction. The floating zone grown single crystals contain no low-angle grain boundaries, indicating that they can be used for high efficiency Li-ion batteries.
HDR brachytherapy using cylinder, tandem-ovoid (T&O) and interstitial implant with prognosis
Authors: Malik Sadiq R , Ahmed Mushfika , Reza Md Shohel , Bairagi Ashish K , Yeasmin Nilufa , Banu Parveen Akhter , Rukhsana Naheed , Naher Lutfun 
Published: January 2021

Abstract
Purpose: Among the therapeutic modalities available for the treatment of cervical cancer, irradiation is regarded to be the standerd treatment for all tumor stages, which includes external beam radiation therapy and HDR brachytherapy or a combination of these two. This modality of cancer, needless to say, is prevalent in Bangladesh as the women are coming forward for its detection. Dramatic advances have been made in brachytherapy for cervical cancer. Radiation treatment planning has evolved from two-dimensional to three-dimensional, incorporating magnetic resonance imaging and/or computed tomography into the treatment paradigm. This allows for better delineation and coverage of the tumor, as well as improved avoidance of surrounding organs. Brachytherapy applications are not restricted to one method only; any method could be combined with another, as well as other radiotherapy techniques. In cervical cancer, intracavitary brachytherapy (ICBT) has been used for practical reasons. Lately though, combination of ICBT and interstitial brachytherapy (ISBT) techniques are being evaluated in deference to feasibility, practicality and reproducibility. Advanced brachytherapy can achieve very high rates of local control with a reduction in morbidity, compared with historic approaches. This study provides an overview of state-of-the-art gynecologic brachytherapy, with a focus on recent advances and their implications for women with cervical cancer.
Materials and Methods: Three patients were selected on different staging. Three different types of applicator (Cylinder, Tandem and Ovoid and Interstitial Implant) were inserted according to the patient’s anatomy and staging. Prescribed dose were different for the implant technique.
Result: Progress from 2D- to 3D-based imaging and treatment planning for cervical cancer brachytherapy has improved local control, reduced toxicity, and improved overall survival for women.
Conclusion: The result of our study indicates that a precise delivery of treatment by applying a appropriate applicator and the choice of treatment planning technique is more important for a better outcome.
Structural, Elastic and Electronic Properties of Nitride Ti2CdN Phase in Comparison with the Carbide Ti2CdC Phase from First-principles Study
Authors: Roknuzzaman M. , Hadi M.A. , Nasir M.T. , Naqib S.H. , Islam A.K.M.A. 
Published: January 2021

Abstract
First-principles studies were conducted to investigate the structural, elastic and electronic properties of the Cd-containing synthesized MAX phase Ti2CdC in comparison with the predicted phase Ti2CdN. Our calculations show that the substitution of C by N in Ti2CdC mostly affects the lattice constant c; the lattice constant a remains almost unchanged. All the elastic constants and moduli increase when C is replaced by N. In comparison with the Ti2CdN phase, Ti2CdC is more compressible along the c-axis. The elastic anisotropy in Ti2CdC is higher in comparison with Ti2CdN. Both the two nanolaminates are brittle in nature. The calculated electronic band structures and density of states imply that the chemical bonding in these two compounds is a combination of covalent, ionic and metallic nature. Electrically, Ti2CdC is more conducting than Ti2CdN.
In-plane resistivity of hole doped cuprates: role of pseudogap and quantum criticality*
Authors: Afsana Azam M , Borhan Uddin M , Naqib S H 
Published: January 2021

Abstract
The anomalous behaviour of dc charge dynamics in high-Tc
cuprates cannot be explained by the prevalent Boltzman transport theory. In high-Tc
cuprates the in-plane and out-of-plane dc resistivities exhibit high anisotropy and unconventional temperature dependence. In this study we have modeled the temperature (T) and hole content (p) dependent in-plane resistivity, ρa
(T, p), of pure and Ca doped Y123 (Y(Ca)Ba2Cu3O7-

δ
). We have adapted and extended the formalism developed by Naqib et al. (Physica C 471 1598 (2011)) by taking account of two generic features present in all hole doped cuprates, namely - (i) the presence of the pseudogap in the quasiparticle spectrum and (ii) high-T linear behavior, to elucidate non-Fermi liquid ρa
(T, p) of Y(Ca)Ba2Cu3O7-

δ
over a wide range of temperature and hole contents. The characteristic pseudogap energy scale, εg
(p), extracted from the analysis of the resistivity data was found to agree well with those found in a variety of earlier studies. Other extracted parameters from the analysis of ρp
(T, p) data showed methodical variations with the variation of hole content. Important features of the analysis are briefly discussed.
Comparative study of optimization techniques in deep learning: Application in the ophthalmology field
Authors: Mustapha Aatila , Mohamed Lachgar , Ali Kartit 
Published: January 2021

Abstract
The optimization is a discipline which is part of mathematics and which aims to model, analyse and solve analytically or numerically problems of minimization or maximization of a function on a specific dataset. Several optimization algorithms are used in systems based on deep learning (DL) such as gradient descent (GD) algorithm. Considering the importance and the efficiency of the GD algorithm, several research works made it possible to improve it and to produce several other variants which also knew great success in DL. This paper presents a comparative study of stochastic, momentum, Nesterov, AdaGrad, RMSProp, AdaDelta, Adam, AdaMax and Nadam gradient descent algorithms based on the speed of convergence of these different algorithms, as well as the mean absolute error of each algorithm in the generation of an optimization solution. The obtained results show that AdaGrad algorithm represents the best performances than the other algorithms with a mean absolute error (MAE) of 0.3858 in 53 iterations and AdaDelta one represents the lowest performances with a MAE of 0.6035 in 6000 iterations. The case study treated in this work is based on an extract of data from the keratoconus dataset of Harvard Dataverse and the results are obtained using Python.
Transfer Learning for classifying front and rear views of vehicles
Authors: Baghdadi Sara , Aboutabit Noureddine 
Published: January 2021

Abstract
Various computer systems have been proposed to classify vehicles according to several criteria (category, brand, model). Unfortunately, there is not much research on the classification of views, especially front and rear views. Several factors make this classification very difficult including similarity in shape, size, and color. This work aims to classify front and rear views of vehicles using the Transfer Learning (TL) approach. Here, we used a pre-trained CNN (AlexNet) that has been trained on more than a million images and can classify images into 1000 object categories. Thus, we transferred its learned knowledge and applied it to our new task (Classifying vehicle views). We conducted then two experiments. The first experiment has two scenarios: the first scenario is devoted to Transfer Learning using the AlexNet model, and the second scenario aims to build a network from scratch inspired from AlexNet. Experimental results reveal that the Transfer Learning approach gives high results. On the other hand, in the second experiment, we decided to use TL-AlexNet to extract features and train them with an SVM classifier instead of fully connected layers. And also, we combined the SVM with the fully connected layers. The accuracy rates have been improved after this experiment.
Multi-Agent Reinforcement learning Approach to IoT Coordination
Authors: Belkeziz Radia , Jarir Zahi , El Kassmi Ilyass 
Published: January 2021

Abstract
Nowadays, the IoT is evolving at a very fast pace and has proven its usefulness in several areas by creating better applications and services. However, more flexible approaches proving a well-defined architecture meeting the general requirements and building blocks of IoT are still needed despite the results obtained in the literature. In this paper, we focus on the IoT coordination challenge which represents a fundamental property allowing things to collaborate and make a decision when an appropriate change is detected in its environment. This contribution proposes an agent-based approach coupled with Q-learning which is a reinforcement learning technique, to compensate for coordination in its entirety, namely objective coordination and subjective coordination. To illustrate this approach, an evacuation use case is presented.
Colouring of graphs by HB colour matrix algorithm method
Authors: Bhange A A , Bhapkar H R 
Published: January 2021

Abstract
Graph Colouring is a chief element in graph theory with tremendous applicability in computer science like data mining, clustering, networking, image segmentation etc. And a variety of implementations in aircraft scheduling, register allocation, sudoku, mobile networking, etc. Various algorithms were contrived for vertex colouring. This paper defines the HB colour matrix method and its kinds. There are three types of such matrices, Vertex HB colour matrix (VHBCM), Edge HB Colour matrix (EHBCM), and Region HB colour matrix (RHBCM). Also, the HB colour matrix algorithm is developed using a special assignment method, which gives the chromatic number of the given graph. Further, the algorithm is used to develop the python program, giving time complexity O(n) and space complexity O(n2). Also, the output of the python program for some standard graphs is calculated. The Similar algorithm can be developed for edge and face colouring of the graphs. Colouring of the graph further can be extended to perfect colouring.
An Intelligent Procedure for Dynamic Evaluation in a Scientific Learning Session
Authors: Diyer Okacha , Achtaich Naceur , Najib Khalid 
Published: January 2021

Abstract
In this research, we are interested in the evaluation of scientific subjects’ teaching components such as course questions, examples, application and deepening exercises. Thereby, we have presented a method that allows the teacher to make decisions using a system that implements interpretations based on the decision tree. The proposed system does not only propose assessing students’ learning, but it also offers the teacher intervention phases to reduce the difficulties encountered by students. This evaluation approach offers the opportunity for each student to acquire the necessary skills needed in their learning according to their abilities. In our research, we are interested in an evaluation that is based on an intelligent strategy to adjust the students learning during the classroom session. We present the interaction strategy between the teacher, the intelligent system and the students. Last but not least, we build the decision tree and interpret the results obtained, its use by the teacher for any further improvement. Consequently, this indicates the importance of this evaluation conception through artificial intelligence and its impact on machine learning by offering it an interesting database.
Rectified non-linear unit for convolution neural network
Authors: El Jaafari Ilyas , Ellahyani Ayoub , Charfi Said 
Published: January 2021

Abstract
Convolution neural network takes in input image, assign importance (learnable weights and biases) to various aspects/objects in the image and be able to differentiate one from the other. At each layer, a linear transformation is carried out on the received data. Aiming for solving non-linear problems, a mandatory unit named activation function is used by neural networks. The activation function greatly influences the success of training deep neural networks. In this paper, a new rectified non linear function unit that we call Rectified non-linear unit (ReNU) is proposed. The presented activation function returns x − log(x + 1) for positive values, and zero for negative ones. The ReNU multiplies the received gradient by values between 0 and 1 depending on the importance of neurons ( 1 for the biggest neurons and 0 for the smaller ones) unlike the ReLU that returns the same received gradient for all positive values in its back propagation. Using the proposed activation function the CNN performance remarkably raises. The ReNU has been tested on MNIST and CIFAR-10 data sets and compared to the ReLU and ELU activation functions. The experimental results are satisfactory when compared to known activation functions in terms of convergence speed and CNN accuracy.
Computer-aided diagnosis system for ulcer detection in wireless capsule endoscopy images
Authors: Ellahyani Ayoub , El jaafari Ilyas , Charfi Said 
Published: January 2021

Abstract
Diseases of the digestive tract, such as ulcers, pose a serious threat to human health. In fact, many types of endoscopy are employed to examine the patient’s gastrointestinal tract. Recently, wireless capsule endoscopy (WCE) is presented as an excellent diagnostic tool for evaluation of gastrointestinal diseases compared to traditional endoscopies. This diagnosis usually takes a long time, which is tiring, and so the doctors may miss parts where abnormalities of the gastrointestinal tract may present. Therefore, automated diagnostic technics to detect symptoms of gastrointestinal illness in WCE images is adopted as an excellent enhancement tool for these doctors. In this work, a new computer-aided diagnosis method for ulcer detection in WCE images is proposed. After a preprocessing step, fine-tuned convolutional neural network (CNN) is used to extract deep features from these images. Since the number of ulcer images in the available data sets is limited, the CNN networks used in this work were pre-trained on millions of labeled natural images (ImageNet). After the deep features extraction, a random forest classifier is employed to detect ulcer from WCE images. The proposed approach demonstrates promising results (96.73 % and 95.34 % in terms of precision and recall respectively). Those results are satisfactory when compared to recent state-of-the-art methods.