Sharif Digital Repository

Two seemingly unrelated, but fundamental challenges in evolutionary theory, are the evolution of costly signals and costly cooperative traits, both expected to reduce an individual’s fitness and diminish by natural selection. Here, by considering a well mixed population of individuals who produce signals and decide on their strategies in a game they play, based on the signals, we show that costly signals and costly cooperative strategies can co-evolve as a result of internal dynamics of the system. Costly signals evolve, despite their apparent cost, due to a favorable cooperative response they elicit. This favorable strategic response can be quantified in a fitness term which governs the... 

Being able to track objects that surround us is key for planning actions in dynamic environments. However, rigorous cognitive models for tracking of one or more objects are currently lacking. In this study, we asked human subjects to judge the time to contact (TTC) a finish line for one or two objects that became invisible shortly after moving. We showed that the pattern of subject responses had an error variance best explained by an inverse Gaussian distribution and consistent with the output of a biased drift-diffusion model. Furthermore, we demonstrated that the pattern of errors made when tracking two objects showed a level of dependence that was consistent with subjects using a single... 

Suppressor of cytokine signalling (SOCS) family comprises a group of proteins that impede JAK/STAT signalling, thus being involved in the pathogenesis of immune-related conditions. In the present work, we aimed at identification of the role of SOCS genes in the pathogenesis of periodontitis through evaluation of their expression levels both in the circulation and in the affected tissues of patients. Thus, we measured expression levels of SOCS1-3 and SOCS5 transcripts in the blood and gingival samples of patients with periodontitis in comparison with control samples obtained during dental crown lengthening. Expressions of SOCS1, SOCS2, SOCS3 and SOCS5 genes were similar between gingival... 

Analysis of cancer mutational signatures have been instrumental in identification of responsible endogenous and exogenous molecular processes in cancer. The quantitative approach used to deconvolute mutational signatures is becoming an integral part of cancer research. Therefore, development of a stand-alone tool with a user-friendly interface for analysis of cancer mutational signatures is necessary. In this manuscript we introduce CANCERSIGN, which enables users to identify 3-mer and 5-mer mutational signatures within whole genome, whole exome or pooled samples. Additionally, this tool enables users to perform clustering on tumor samples based on the proportion of mutational signatures in... 

Male infertility is mostly related to semen and spermatozoa, and any diagnosis or treatment requires the investigation of the motility patterns of spermatozoa. The movements of spermatozoa are fast and involve collision and occlusion with each other. In order to extract the motility patterns of spermatozoa, multi-target tracking (MTT) of spermatozoa is necessary. One of the most important steps of MTT is data association, in which the newly arrived observations are used to update the previous tracks. Dynamic Bayesian network (DBN) is a powerful tool for modeling and solving various types of problems such as tracking and classification. There can also be a hybrid-DBN (HDBN), in which both... 

Organizations are increasingly accepting data quality (DQ) as a major key to their success. In order to assess and improve DQ, methods have been devised. Many of these methods attempt to raise DQ by directly manipulating low quality data. Such methods operate reactively and are suitable for organizations with highly developed integrated systems. However, there is a lack of a proactive DQ method for businesses with weak IT infrastructure where data quality is largely affected by tasks that are performed by human agents. This study aims to develop and evaluate a new method for structured data, which is simple and practical so that it can easily be applied to real world situations. The new... 

Social networks are getting closer to our real physical world. People share the exact location and time of their check-ins and are influenced by their friends. Modeling the spatio-temporal behavior of users in social networks is of great importance for predicting the future behavior of users, controlling the users’ movements, and finding the latent influence network. It is observed that users have periodic patterns in their movements. Also, they are influenced by the locations that their close friends recently visited. Leveraging these two observations, we propose a probabilistic model based on a doubly stochastic point process with a periodic-decaying kernel for the time of check-ins and a... 

Cell lysis is the most important first step for molecular biology and diagnostic testing. Recently, microfluidic systems have attracted considerable attention due to advantages associated with automation, integration and miniaturization, especially in resource-limited settings. In this work, novel centrifugal microfluidic platforms with new configurations for chemical cell lysis are presented. The developed systems employ passive form of pneumatic and inertial forces for effective mixing of lysis reagents and cell samples as well as precise fluidic control. Characterizations of the developed Lab-on-a-Discs (LoaDs) have been conducted with dyed deionized (DI) waters and white blood cells... 

Unilateral coercive international political, diplomatic, and economic sanctions are regular events of international relations and international law within the landscape of foreign affairs. However, while they may be prescribed by international law, or national legal systems, for peace and security reasons they have also been imposed for political grounds by powerful States such as the United States. The US sanctions are now targeting science, academic and university domains. When applied in this way, these sanctions violate international law, principles of human rights, ethics, the autonomy of scientific institutions, and the norm of universalism in science. All of which protect and promote... 

In this article, a universal collaborative and competitive approach is introduced for deployment of digital collections in an ideal Digital Library (DL) for future's educational system. The collaborative and open-source aspects of the system guarantee its growth and the competitive aspects guarantee the accuracy  

This paper presents a Windows program providing statistics on word and non-word stimuli in Persian, including word frequency, orthographic and phonological length, orthographic and phonological neighbors, and transposed-letter neighbors. It also generates possible non-words that are orthographic neighbors of the target word. Persian is an under-represented Indo-European language that has historically been influenced by Arabic and adopted certain characteristics in its writing, e.g., the omission of short vowels. This tool aims to help researchers in psycholinguistics, specifically with regard to isolated word recognition in Persian. This downloadable program computes the aforementioned... 

Nowadays, artificial intelligence (AI) and machine learning (ML) are playing a tremendous role in all aspects of human life and they have the remarkable potential to solve many problems that classic sciences are unable to solve appropriately. Neuroscience and especially psychiatry is one of the most important fields that can use the potential of AI and ML. This study aims to develop an ML-based model to detect the relationship between resiliency and hope with the stress of COVID-19 by mediating the role of spiritual well-being. An online survey is conducted to assess the psychological responses of Iranian people during the Covid-19 outbreak in the period between March 15 and May 20, 2020, in... 

Background: We developed transformer-based deep learning models based on natural language processing for early risk assessment of Alzheimer’s disease from the picture description test. Methods: The lack of large datasets poses the most important limitation for using complex models that do not require feature engineering. Transformer-based pre-trained deep language models have recently made a large leap in NLP research and application. These models are pre-trained on available large datasets to understand natural language texts appropriately, and are shown to subsequently perform well on classification tasks with small training sets. The overall classification model is a simple classifier on... 

Karyotype is a genetic test that is used for detection of chromosomal defects. In a karyotype test, an image is captured from chromosomes during the cell division. The captured images are then analyzed by cytogeneticists in order to detect possible chromosomal defects. In this paper, we have proposed an automated pipeline for analysis of karyotype images. There are three main steps for karyotype image analysis: image enhancement, image segmentation and chromosome classification. In this paper, we have proposed a novel chromosome segmentation algorithm to decompose overlapped chromosomes. We have also proposed a CNN-based classifier which outperforms all the existing classifiers. Our... 

The social impact of robotics applied to domains such as education, religion, nursing, and therapy across the world depends on the level of technology as well as the culture in which it is used. By studying how robots are used in Iran, a technologically-savvy country with a long history and a rich culture, we explore their possible impact on interrelated areas of religious and ethical features in education in an Islamic society. To accomplish this task, a preliminary exploratory study was conducted using two social robots as teaching assistants in Islamic religion classes for 42 elementary students. More than 90% of the participants in the study absolutely preferred the robot-assisted... 

Humans have a unique ability to use language for social communication. The neural architecture for language comprehension and production may have prominently emerged in the brain areas that were originally involved in social cognition. Here, we directly tested the fundamental link between language and social processing using functional magnetic resonance data (MRI) data from over 1,000 human subjects. Cortical activations in language and social tasks showed a striking similarity with a complementary hemispheric lateralization. Within core language areas, left-lateralized activations in the language task were mirrored by right-lateralized activations in the social task. Outside these areas,... 

This study aims to identify genetic causes of familial female infertility characterized by embryonic developmental arrest (EDA) and repeated implantation failure (RIF) with oocyte donation IVF cycle. We used Whole-exome sequencing and Sanger validation to find causative genes in an Iranian consanguineous family that had 3 infertile daughters, 4 fertile daughters, and 2 fertile sons. All patients in this consanguineous family exhibited typical manifestations of unexplained RIF and EDA. Genetic analysis identified a homozygous missense variant (c.G1054C:p.G352R) in exon 13 of the TLE6 gene that cosegregated with the EDA phenotype in an autosomal recessive pattern. Other members of the family,... 

This paper presents a Windows program providing statistics on word and non-word stimuli in Persian, including word frequency, orthographic and phonological length, orthographic and phonological neighbors, and transposed-letter neighbors. It also generates possible non-words that are orthographic neighbors of the target word. Persian is an under-represented Indo-European language that has historically been influenced by Arabic and adopted certain characteristics in its writing, e.g., the omission of short vowels. This tool aims to help researchers in psycholinguistics, specifically with regard to isolated word recognition in Persian. This downloadable program computes the aforementioned... 

This paper surveys methods to aggregate redundant crowd labels in order to estimate unknown true labels. It presents a unified statistical latent model where the differences among popular methods in the field correspond to different choices for the parameters of the model. Afterward, algorithms to make inference on these models will be surveyed. Moreover, adaptive methods which iteratively collect labels based on the previously collected labels and estimated models will be discussed. In addition, this paper compares the distinguished methods and provides guidelines for future work required to address the current open issues.Recently, there has been a burst in the number of research projects... 

In the present research, human errors existed in tasks of operators working in two control rooms (Northern and Southern control rooms) in the Tehran oil refinery are identified and evaluated. Then, corrective strategies and actions are advised to decrease errors. At first, using hierarchical task analysis (HTA) method, four positions including shift controller, head operators, control room's operators, and outside operators are analyzed. Afterwards, human errors in the considered positions are identified and assessed using technique for retrospective and predictive analysis of cognitive errors (TRACEr). Results present 670 internal errors and 738 external errors in the Northern sector while...