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Top quark production is discussed in the framework of SUSY searches with the two general-purpose detectors at LHC, ATLAS and CMS. Top quark appears both in signal and in backgrounds, so knowing top quark features is crucial for the analysis. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike Licence  

An inclusive search for low mass SUSY using the top plus missing transverse energy signature at CMS is presented. A 5σ excess can be observed with ∼250 pb-1 at a particular low mass SUSY point. With the same analysis selection the 5σ discovery reach contours in the mSUGRA parameter space for 1 and 10 fb-1 are obtained  

An inclusive search for low mass SUSY using the top plus missing transverse energy signature at CMS is presented. A kinematic fit with the top and W masses as constraints is utilized to reconstruct the top in all-hadronic final states. A 5σ excess can be observed with ∼250 pb-1 at a particular low mass SUSY point. With the same analysis selection the 5σ discovery reach contours in the mSUGRA parameter space for 1 and 10 fb-1 are obtained. © 2007 IOP Publishing Ltd  

Partially-observed data collected by sampling methods is often being studied to obtain the characteristics of information diffusion networks. However, these methods usually do not consider the behavior of diffusion process. In this paper, we propose a novel two-step (sampling/estimation) measurement framework by utilizing the diffusion process characteristics. To this end, we propose a link-tracing based sampling design which uses the infection times as local information without any knowledge about the latent structure of diffusion network. To correct the bias of sampled data, we introduce three estimators for different categories, link-based, node-based, and cascade-based. To the best of... 

The diffusion phenomenon has a remarkable impact on Online Social Networks (OSNs). Gathering diffusion data over these large networks encounters many challenges which can be alleviated by adopting a suitable sampling approach. The contributions of this paper is twofold. First we study the sampling approaches over diffusion networks, and for the first time, classify these approaches into two categories, (1) Structure-based Sampling (SBS), and (2) Diffusion-based Sampling (DBS). The dependency of the former approach to topological features of the network, and unavailability of real diffusion paths in the latter, converts the problem of choosing an appropriate sampling approach to a trade-off.... 

Many real-world systems and applications such as World Wide Web, and social interactions can be modeled as networks of interacting nodes. However, in many cases, one encounters the situation where the pattern of the node-to-node interactions (i.e., edges) or the structure of a network is unknown. We address this issue by studying the Network Reconstruction Problem: Given a network with missing edges, how is it possible to uncover the network structure based on certain observable quantities extracted from partial measurements? We propose a novel framework called CS-NetRec based on a newly emerged paradigm in sparse signal recovery called Compressive Sensing (CS). The results demonstrate that... 

In this paper, we propose a novel method for academic assessment inspired by the decentralized applications made possible by blockchain technology. The proposed method applies to a wide range of academic material, including assignments, exams, academic papers, etc and tackles issues regarding potential personal bias and makes assessment possible without the need to rely on a few assessors. We examine the challenges and possibilities that arise with this method and further explore more general applications in areas such as education. In the experiments conducted for this research, poll results show generally positive views toward the fairness of this system compared to the traditional... 

In this paper we developed a new mathematical model for the flow inside cascade impactors and via this simplified model, we determined the particle size distribution by a fast and low cost computational method. Using cascade impactors for determining the particle size distribution, one can use comprehensive CFD methods to fully simulate the particle traces. Although the results from those CFD analyses can be very accurate, usually that is not a time and cost efficient routine. In contrast, we showed that by using our proposed calculation we can estimate the particle size distribution very fast and yet with the slight error -comparing to the results from CFD method. Cascade impactors are... 

Computer-assisted collaborative peer grading is a developing growth area in academic evaluation. However, peer assessment often needs help with problems such as the lack of reliability, transparency, fairness, grading speed, and motivation to participate among students. The literature suggests several principles that each partly address the said issues. We propose a novel decentralized approach to academic peer assessment, using blockchain as an underlying technology, to address the principal problems in traditional peer assessment. We also derive design concepts for a modern courseware (CW) application consisting of our method and apply them to implement our approach in a CW called... 

Demand response (DR) is known as a key solution in modern power systems and electricity markets for mitigating wind power uncertainties. However, effective incorporation of DR into power system operation scheduling needs knowledge of the price–elastic demand curve that relies on several factors such as estimation of a customer’s elasticity as well as their participation level in DR programs. To overcome this challenge, this paper proposes a novel autonomous DR scheme without prediction of the price–elastic demand curve so that the DR providers apply their selected load profiles ranked in the high priority to the independent system operator (ISO). The energy and reserve markets clearing... 

An adaptive neural guidance and control system is proposed in this paper for a generic fixed-wing aerial robot. Unlike most of the existing low-level control systems, which utilize a non-adaptive guidance loop, in this work both the guidance and control loops are trained using an efficient adaptive neural algorithm. A feedforward neural network is employed in each loop to identify uncertain dynamics, while an adaptive disturbance observer allows to compensate for both the external disturbances and estimation error of the neural network. This would lead to a resilient flight control system, and thus, the asymptotic stability of both the guidance and control loops can be theoretically ensured... 

Here we study the effects of many-body interactions on rate and mechanism in protein folding by using the results of molecular dynamics simulations on numerous coarse-grained Cα-model single-domain proteins. After adding three-body interactions explicitly as a perturbation to a Gō-like Hamiltonian with native pairwise interactions only, we have found (i) a significantly increased correlation with experimental φ values and folding rates, (ii) a stronger correlation of folding rate with contact order, matching the experimental range in rates when the fraction of three-body energy in the native state is ≈20%, and (iii) a considerably larger amount of three-body energy present in chymotripsin... 

Gift shopping can be challenging due to the limited prior knowledge of the recipient's preferences, leading to after-purchase regret. The effectiveness of Fashion Recommender Systems (FRS) in the context of gift purchases with limited preference data remains underexplored. We considered a gift-buying scenario and conducted an experiment with 192 pairs of participants to compare FRS versus humans in recommending fashion gifts to buyers.We find both FRS and humans score >50% correctness in recommending the right gift, even without direct interaction with gift-givers or recipients. Although the buyers know the gift receivers directly, they lead to less accuracy. Additionally, we identify... 

A new type of aggregation-induced emission (AIE) luminogen containing a dimeric metal fragment and two or three phthalazine ligands is described, which shows dynamic motions of ligands around the metal centers in solution. Based on the variable-temperature and EXSY NMR spectroscopy data, X-ray crystallography structures, and computational results, three different pathways (i.e., reversible exchange with haptotropic shifts, circulation of ligands around the dimeric metal fragment, and walking on the spot of ligands on the metal centers) were considered for this dynamic behavior. Restriction of these dynamic processes in the aggregate forms of the compounds (in H2O/CH3CN solvent mixtures)... 

Calibrating the inverse kinematics of complex robots is often a challenging task. Finding analytical solutions is not always possible and the convergence of numerical methods is not guaranteed. The model-free approaches, based on machine learning and artificial intelligence, are fast and easy to work, however, they need a huge amount of experimental training data to provide acceptable results. In this article, we proposed a hybrid method to benefit the advantage of both model-based and model-free approaches. The forward kinematics of the robot is calibrated using a model-based approach, and its inverse kinematics using a neural network. Hence, while there is no need to solve the nonlinear... 

This paper addresses the problem of finding the nearest neighbor (or one of the R-nearest neighbors) of a query object q in a database of n objects, when we can only use a comparison oracle. The comparison oracle, given two reference objects and a query object, returns the reference object most similar to the query object. The main problem we study is how to search the database for the nearest neighbor (NN) of a query, while minimizing the questions. The difficulty of this problem depends on properties of the underlying database. We show the importance of a characterization: combinatorial disorder D which defines approximate triangle inequalities on ranks. We present a lower bound of Ω(Dlog... 

Background: It is now possible to analyze cellular heterogeneity at the single-cell level thanks to the rapid developments in single-cell sequencing technologies. The clustering of cells is a fundamental and common step in heterogeneity analysis. Even so, accurate cell clustering remains a challenge due to the high levels of noise, the high dimensions, and the high sparsity of data. Results: Here, we present SCEA, a clustering approach for scRNA-seq data. Using two consecutive units, an encoder based on MLP and a graph attention auto-encoder, to obtain cell embedding and gene embedding, SCEA can simultaneously achieve cell low-dimensional representation and clustering performing various... 

On-line analytical processing (OLAP) is a mature technology as a part of the new category named Business Intelligence for decision supports that are given to managers to analyze different dimensions of multidimensional data and enable them to obtain competitive advantage by accurate analysis and examination of organizational data. So considering the factors affecting the user's acceptance and use are important to increase the benefits of such systems. The study has used Technology Acceptance Model (Davis 1989) to determine technology acceptance of an Online Analytical Processing (OLAP) in Tarbiat Modares University. This study took advantage of Structural Equation Modeling (SEM) approach to... 

Perovskite solar cells (PSCs) have experienced outstanding advances in power conversion efficiencies (PCEs) by employing new electron transport layers (ETLs), interface engineering, optimizing perovskite morphology, and improving charge collection efficiency. In this work, we study the role of a new ultrathin interface layer of titanium nitride (TiN) conformally deposited on a mesoporous TiO2 (mp-TiO2) scaffold using the atomic layer deposition method. Our characterization results revealed that the presence of TiN at the ETL/perovskite interface improves the charge collection as well as reduces the interface recombination. We find that the morphology (grain size) and optical properties of...