Sharif Digital Repository

A search is presented for a heavy W′ boson resonance decaying to a B or T vector-like quark and a t or a b quark, respectively. The analysis is performed using proton-proton collisions collected with the CMS detector at the LHC. The data correspond to an integrated luminosity of 138 fb−1 at a center-of-mass energy of 13 TeV. Both decay channels result in a signature with a t quark, a Higgs or Z boson, and a b quark, each produced with a significant Lorentz boost. The all-hadronic decays of the Higgs or Z boson and of the t quark are selected using jet substructure techniques to reduce standard model backgrounds, resulting in a distinct three-jet W′ boson decay signature. No significant... 

The notion of compressibility of a random measure is a rather general concept which find applications in many contexts from data compression, to signal quantization, and parameter estimation. While compressibility for discrete and continuous measures is generally well understood, the case of discrete-continuous measures is quite subtle. In this paper, we focus on a class of multi-dimensional random measures that have singularities on affine lower-dimensional subsets. We refer to this class of random variables as affinely singular. Affinely singular random vectors naturally arises when considering linear transformation of component-wise independent discrete-continuous random variables. To... 

Wearable human activity recognition systems (HAR) using inertial measurement units (IMU) play a key role in the development of smart rehabilitation systems. Training of a HAR system with patient data is costly, time-consuming, and difficult for the patients. This study proposes a new scheme for the optimal design of HARs with minimal involvement of the patients. It uses healthy subject data for optimal design for a set of activities used in the rehabilitation of PD1 patients. It maintains its performance for individual PD subjects using a single session data collection and an adaptation procedure. In the optimal design, several classifiers (i.e. NM, k-NN, MLP with RBF as a hidden layer, and... 

The quality of fresh apple fruits is a major concern for consumers and manufacturers. Classification of these fruits according to their ripening stage is one of the most decisive factors in determining their quality. In this regard, the aim of this work is to develop a new method for non-destructive classification of the ripening state of Fuji apples using hyperspectral information in the visible and near-infrared (Vis/NIR) regions. Spectra of 172 apple samples in the range from 450 to 1000 nm were studied, which were selected from four different ripening stages. A convolutional neural network (CNN) model was proposed to perform the classification of the samples. The proposed method was... 

Studying the mechanical performance of concrete after being exposed to high temperatures is an important step in the damage assessment of buildings and fire safety applications. However, predicting the compressive strength of GPC accurately after exposure to high temperatures is a challenging task. In this paper, artificial neural network (ANN) and support vector regression (SVR) models were developed to predict the compressive strength of geopolymer concrete (GPC) at high temperatures ranging from 100 °C to 1000 °C. A series of experiments consisting of different mix designs were conducted at elevated temperatures to prepare a dataset. Besides experiments' results, the data of previously... 

Advancements in nanotechnology have resulted in the introduction of several nonviral delivery vectors for the nontoxic, efficient delivery of encapsulated mRNA-based vaccines. Lipid- and polymer-based nanoparticles (NP) have proven to be the most potent delivery systems, providing increased delivery efficiency and protection of mRNA molecules from degradation. Here, the authors provide an overview of the recent studies carried out using lipid NPs and their functionalized forms, polymeric and lipid-polymer hybrid nanocarriers utilized mainly for the encapsulation of mRNAs for gene and immune therapeutic applications. A microfluidic system as a prevalent methodology for the preparation of NPs... 

Aim of study: Glioblastoma Multiforme (GBM) is an aggressive brain cancer in adults that kills most patients in the first year due to ineffective treatment. Different clinical, biomedical, and image data features are needed to analyze GBM, increasing complexities. Besides, they lead to weak performances for machine learning models due to ignoring physicians' knowledge. Therefore, this paper proposes a hierarchical model based on Fuzzy C-mean (FCM) clustering, Wrapper feature selection, and twelve classifiers to analyze treatment plans. Methodology/Approach: The proposed method finds the effectiveness of previous and current treatment plans, hierarchically determining the best decision for... 

Nanocomposites containing ZrO2 and HA have been considered in various fields due to their unique mechanical properties. The principal purpose of this paper is to select the models with the maximum accuracy for the prediction of microhardness of CHA/ZrO2 nanocomposite. For this purpose, three models, including gene expression programming (GEP), gray wolf optimization algorithm (GWOA), and least squares support vector machine (LS-SVM), were implemented to predict and optimize the microhardness of the CHA/ZrO2 nanocomposite. Finally, the results showed that the data obtained from the LS-SVM model were closer to the preliminary data than the others. According to the results, the LS-SVM could... 

Tomato is an agricultural product of great economic importance because it is one of the most consumed vegetables in the world. The most crucial chemical element for the growth and development of tomato is nitrogen (N). However, incorrect nitrogen usage can alter the quality of tomato fruit, rendering it undesirable to customers. Therefore, the goal of the current study is to investigate the early detection of excess nitrogen application in the leaves of the Royal tomato variety using a non-destructive hyperspectral imaging system. Hyperspectral information in the leaf images at different wavelengths of 400–1100 nm was studied; they were taken from different treatments with normal nitrogen... 

A measurement of the forward-backward asymmetry of pairs of oppositely charged leptons (dimuons and dielectrons) produced by the Drell-Yan process in proton-proton collisions is presented. The data sample corresponds to an integrated luminosity of 138 fb−1 collected with the CMS detector at the LHC at a center-of-mass energy of 13 TeV. The asymmetry is measured as a function of lepton pair mass for masses larger than 170 GeV and compared with standard model predictions. An inclusive measurement across both channels and the full mass range yields an asymmetry of 0.612 ± 0.005 (stat) ± 0.007 (syst). As a test of lepton flavor universality, the difference between the dimuon and dielectron... 

MOG as a modified gravity theory is designed to be replaced with dark matter. In this theory, in addition to the metric tensor, a massive vector is a gravity field where each particle has a charge proportional to the inertial mass and couples to the vector field through the four-velocity of a particle. In this work, we present the Hamiltonian formalism for the dynamics of particles in this theory. The advantage of Hamiltonian formalism is a better understanding and analysing the dynamics of massive and massless particles. The massive particles deviate from the geodesics of space-time and photons follow the geodesics. We also study the dynamics of particles in the Newtonian and post-Newtonian... 

ARX algorithms are a class of symmetric-key algorithms constructed by Addition, Rotation, and XOR. To evaluate the resistance of an ARX cipher against differential and impossible-differential cryptanalysis, the recent automated methods employ constraint satisfaction solvers to search for optimal characteristics or impossible differentials. The main difficulty in formulating this search is finding the differential models of the non-linear operations. While an efficient bit-vector differential model was obtained for the modular addition with two variable inputs, no differential model for the modular addition by a constant has been proposed so far, preventing ARX ciphers including this... 

A search for pairs of Higgs bosons produced via gluon and vector boson fusion is presented, focusing on the four b quark final state. The data sample consists of proton-proton collisions at a center-of-mass energy of 13 TeV, collected with the CMS detector at the LHC, and corresponds to an integrated luminosity of 138 fb-1. No deviation from the background-only hypothesis is observed. A 95% confidence level upper limit on the Higgs boson pair production cross section is observed at 3.9 times the standard model prediction for an expected value of 7.8. Constraints are also set on the modifiers of the Higgs field self-coupling, κλ, and of the coupling of two Higgs bosons to two vector bosons,... 

Blind source separation (BSS) methods have received a great deal of attention in electroencephalogram (EEG) artifact elimination as they are routine and standard signal processing tools to remove artifacts and reserve desired neural information. On the other hand, a classifier should follow BSS methods to automatically identify artifactual sources and remove them in the following steps. In addition, removing all detected artifactual components leads to loss of information since some desired information related to neural activity leaks to these sources. So, an approach should be employed to detect and suppress the artifacts and reserve neural activity. This study introduces a novel method... 

This research aims to represent a novel approach to detect malicious nodes in Ad-hoc On-demand Distance Vector (AODV) within the next-generation smart cities. Smart city applications have a critical role in improving public services quality, and security is their main weakness. Hence, a systematic multidimensional approach is required for data storage and security. Routing attacks, especially sinkholes, can direct the network data to an attacker and can also disrupt the network equipment. Communications need to be with integrity, confidentiality, and authentication. So, the smart city and urban Internet of Things (IoT) network, must be secure, and the data exchanged across the network must... 

Regression analysis of real-world data has not always been an easy task, especially when input vectors are presented in a very low dimensional space. EEG-based fatigue detection deals with low dimensional problems and plays a major role in reducing the risk of fatal accidents. We propose a kernel projection pursuit regression algorithm which is a two-step nonlinearity encoding algorithm tailored for such low dimensional problems such as fatigue detection. In this way, data nonlinearity can be investigated from two different perspectives: by first transforming the data into a high dimensional intermediate space and then, applying their spline estimations to the output variables allowing for... 

A search is presented for single production of a vector-like T quark with charge 2/3 e, in the decay channel featuring a top quark and a Z boson, with the top quark decaying hadronically and the Z boson decaying to neutrinos. The search uses data collected by the CMS experiment in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 137 fb−1 recorded at the CERN LHC in 2016–2018. The search is sensitive to a T quark mass between 0.6 and 1.8 TeV with decay widths ranging from negligibly small up to 30% of the T quark mass. Reconstruction strategies for the top quark are based on the degree of Lorentz boosting of its final state. At 95%... 

Gene therapy has emerged as a promising tool for treating different intractable diseases, particularly cancer or even viral diseases such as COVID-19 (coronavirus disease 2019). In this context, various non-viral gene carriers are being explored to transfer DNA or RNA sequences into target cells. Here, we review the applications of the naturally occurring amino acid histidine in the delivery of nucleic acids into cells. The biocompatibility of histidine-enhanced gene delivery systems has encouraged their wider use in gene therapy. Histidine-based gene carriers can involve the modification of peptides, dendrimers, lipids or nanocomposites. Several linear polymers, such as polyethylenimine,... 

A very well-covered graph is a well-covered graph without isolated vertices such that the height of its edge ideal is half of the number of vertices. In this survey article, we gather together most of the old and new results on the edge and cover ideals of these graphs. © 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG  

Introduction: B lymphocyte-induced maturation protein 1 (BLIMP1) encoded by the positive regulatory domain 1 gene (PRDM1), is a key regulator in T cell differentiation in mouse models. BLIMP1-deficiency results in a lower effector phenotype and a higher memory phenotype. Methods: In this study, we aimed to determine the role of transcription factor BLIMP1 in human T cell differentiation. Specifically, we investigated the role of BLIMP1 in memory differentiation and exhaustion of human T cells. We used CRISPR interference (CRISPRi) to knock-down BLIMP1 and investigated the differential expressions of T cell memory and exhaustion markers in BLIMP1-deficient T cells in comparison with...