Sharif Digital Repository

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... 

Nanoparticles and nanomaterials in cancer therapy as well as in all biomedical applications have been heavily investigated over the last decade. In this manner, green synthesized nanomaterials have been vastly considered as promising, cost effective, and environmentally friendly components. Also, green synthesis methods could reduce cytotoxicity as well as increase the biocompatibility of the final products. In this chapter, the role of nanomaterials obtained from biowaste specifically for cancer therapy is discussed. © 2023 Elsevier Ltd. All rights reserved  

Substantial terms have been recognized on the associated risk elements, comorbidities as well as, putative pathophysiological processes of Alzheimer disease and related dementias (ADRDs) as well as, type 2 diabetes mellitus (T2DM), a few from greatest important disease from the moments. Very much is considered regarding the biology and chemistry of each predicament, nevertheless T2DM and ADRDs are an actually similar pattern developing from the similar origins of maturing or synergistic conditions connected by aggressive patho-corporeal terms and continues to be ambiguous. In this depth-critique article, we aimed to investigate all possibilities and represented a novel and applicable... 

Substantial terms have been recognized on the associated risk elements, comorbidities as well as, putative pathophysiological processes of Alzheimer disease and related dementias (ADRDs) as well as, type 2 diabetes mellitus (T2DM), a few from greatest important disease from the moments. Very much is considered regarding the biology and chemistry of each predicament, nevertheless T2DM and ADRDs are an actually similar pattern developing from the similar origins of maturing or synergistic conditions connected by aggressive patho-corporeal terms and continues to be ambiguous. In this depth-critique article, we aimed to investigate all possibilities and represented a novel and applicable... 

The purpose of this study is to investigate separation performance of poly(ether-b-amide6) (Pebax1657)/glycerol triacetate (GTA) gel membranes for CO2 removal from H2, N2 and CH4. GTA as a low molecular weight and highly CO2-phill compound was added to membrane structure at various weight fractions, 20%, 40%, 60% and 80% of Pebax, to fabricate a new high solubility selective membrane with improved performance. Permeation of pure gases was studied at different temperatures from 25 to 65°C and pressures from 4 to 24bar and ideal selectivities were calculated. Results indicated enhancement in permeation for all tested gases. For example, at a pressure of 4bar and a temperature of 25°C, membrane... 

This letter proposes a novel normalized subband adaptive filter (NSAF) algorithm, which applies variable step sizes to subband filters to improve the convergence performance of the conventional NSAF and update only a subset of the subbands per iteration to reduce its computational complexity. The selection process for each subband is based on the amount of improvement it makes to the mean square deviation at every iteration. Simulation results show significant reduction in computational complexity, faster convergence rate, and lower misadjustment error achieved using the proposed scheme  

The aim of this paper is introducing coding scheme that can potentially achieve the sum rate-distortion bound of Gaussian IMTSC/CEO problem with arbitrary number of encoders. No previous work has been reported on code design for the IMTSC/CEO problem with the number of encoders greater than two. In this paper the framework of Slepian-Wolf coded quantization is extended to the case with the number of encoders greater than two. On the other hand, we apply the approach to the case of unequal levels of the observation noise at the encoders. Encoding process consists of trellis coded quantization (TCQ) and LDPC codes. The proposed framework can be easily used for any number of active encoders... 

Community detection in social networks has become a popular topic of research during the last decade. There exist a variety of algorithms for modularizing the network graph into different communities. However, they mostly assume that partial or complete information of the network graphs are available that is not feasible in many cases. In this article, we focus on detecting communities by exploiting their diffusion information. To this end, we utilize the Conditional Random Fields (CRF) to discover the community structures. The proposed method, community diffusion (CoDi), does not require any prior knowledge about the network structure or specific properties of communities. Furthermore, in... 

Considering the significant growth in mobile phone use by customers and its high accessibility, this device can be considered as the most suitable tool in payment category. To implement a mobile payment service, there are many actors involved such as: bank, operator and service provider. As an effective interaction role and in order to optimize efficient parameters for implementing a mobile payment solution, it is necessary to present a suitable business model. Therefore, five different business models have been surveyed in the field of mobile payment in this research; then they were compared with MCDM evaluation method applications. Since one of the most effective parameter to select an... 

This paper introduces a novel framework for modeling temporal events with complex longitudinal dependency that are generated by dependent sources. This framework takes advantage of multidimensional point processes for modeling time of events. The intensity function of the proposed process is a mixture of intensities, and its complexity grows with the complexity of temporal patterns of data. Moreover, it utilizes a hierarchical dependent nonparametric approach to model marks of events. These capabilities allow the proposed model to adapt its temporal and topical complexity according to the complexity of data, which makes it a suitable candidate for real world scenarios. An online inference... 

Access to complete data in large-scale networks is often infeasible. Therefore, the problem of missing data is a crucial and unavoidable issue in the analysis and modeling of real-world social networks. However, most of the research on different aspects of social networks does not consider this limitation. One effective way to solve this problem is to recover the missing data as a pre-processing step. In this paper, a model is learned from partially observed data to infer unobserved diffusion and structure networks. To jointly discover omitted diffusion activities and hidden network structures, we develop a probabilistic generative model called "DiffStru."The interrelations among links of... 

A Bernoulli Mixture Model (BMM) is a finite mixture of random binary vectors with independent dimensions. The problem of clustering BMM data arises in a variety of real-world applications, ranging from population genetics to activity analysis in social networks. In this paper, we analyze the clusterability of BMMs from a theoretical perspective, when the number of clusters is unknown. In particular, we stipulate a set of conditions on the sample complexity and dimension of the model in order to guarantee the Probably Approximately Correct (PAC)-clusterability of a dataset. To the best of our knowledge, these findings are the first non-asymptotic bounds on the sample complexity of learning or... 

Introduction: Artificial Intelligence (AI) represents a significant advancement in technology, and it is crucial for policymakers to incorporate AI thinking into policies and to fully explore, analyze and utilize massive data and conduct AI-related policies. AI has the potential to optimize healthcare financing systems. This study provides an overview of the AI application domains in healthcare financing. Method: We conducted a scoping review in six steps: formulating research questions, identifying relevant studies by conducting a comprehensive literature search using appropriate keywords, screening titles and abstracts for relevance, reviewing full texts of relevant articles, charting... 

With the evolution and significant growth in wireless technology and the development of mobile commerce, businesses can achieve superior performance through the implementation of platforms for mobile payment. However, there are several platforms for mobile payment to choose from which makes the selection of an appropriate platform for specific applications a challenging task. In response to this challenge, the most common mobile payment platforms recorded in the literature have been reviewed. This paper presents the result of this review describing the advantages and disadvantages of each system and offers ranking of the technologies considered. MCDM method is used for assessing and... 

Online media play an important role in information societies by providing a convenient infrastructure for different processes. Information diffusion that is a fundamental process taking place on social and information networks has been investigated in many studies. Research on information diffusion in these networks faces two main challenges: (1) In most cases, diffusion takes place on an underlying network, which is latent and its structure is unknown. (2) This latent network is not fixed and changes over time. In this article, we investigate the diffusion network extraction (DNE) problem when the underlying network is dynamic and latent. We model the diffusion behavior (existence... 

Background: In line with the advancement of Artificial Intelligence (AI), innovative solutions have been designed to improve health-related Sustainable Development Goals (SDGs). Accordingly, there is an increasing trend in the realm of AI and SDG research areas. Objectives: This study aimed to analyze the trends and patterns of AI research in health-related SDGs using bibliometric analysis. Methods: The bibliometric approach facilitated the identification of key terms and countries from previous research. We used VOSviewer to map and analyze data obtained from three databases: Scopus, Web of Science, and PubMed. Results: Our findings illustrated that research on health has been a popular... 

Zeolite SAPO-34 was used for fabrication of mixed matrix membranes (MMMs) to improve the CO2/CH4/N2 gas separation performance of the neat Pebax1074 membrane. Permeability and selectivity of the MMMs were studied at different temperatures of 25-65°C and pressures of 4-24 bars. Also sorption of different gases in MMMs was measured at 35°C and different pressures, which showed enhanced solubility coefficients. Moreover, thermal, morphological and mechanical properties of MMMs were characterized by differential scanning calorimetry (DSC), scanning electron microscope (SEM) and tensile analysis. The results showed excellent improvement in... 

Financial time series have been extensively studied within the past decades; however, the advent of machine learning and deep neural networks opened new horizons to apply supercomputing techniques to extract more insights from the underlying patterns of price data. This paper presents a tri-state labeling approach to classify the underlying patterns in price data into up, down and no-action classes. The introduction of a no-action state in our novel approach alleviates the burden of denoising the dataset as a preprocessing task. The performance of our labeling algorithm is experimented with using machine learning and deep learning models. The framework is augmented by applying the Bayesian... 

This paper proposes a new approach for corrective voltage control (CVC) of power systems in presence of uncertain wind power generation and demand values. The CVC framework deals with the condition that a power system encounters voltage instability as a result of severe contingencies. The uncertainty of wind power generation and demand values is handled using a scenario-based modeling approach. One of the features of the proposed methodology is to consider participation of demand-side resources as an effective control facility that reduces control costs. Active and reactive redispatch of generating units and involuntary load curtailment are employed along with the voluntary demand-side... 

Different aliphatic and aromatic aldehydes such as isobutyraldehyde, ethanal, n-propanal, n-butanal, n-hexanal, n-octanal, and substituted benzaldehydes were cyclotrimerized into their corresponding 2,4,6-trialkyl-1,3, 5-trioxanes in the presence of commercial bulk zinc oxide at room temperature under neat conditions within a short span of time with high yield and excellent selectivity. Liquid products were formed as a separate phase and were decanted easily, whereas solid products were isolated by simple extraction. Effect of different additives, mol % of catalyst, kind of substrate, and reaction temperature were examined on the progress of cyclotrimerization reaction