An Application of Single-Valued Neutrosophic Sets in Medical Diagnosis

In this paper, we present the use of single-valued neutrosophic sets in medical diagnosis by using distance measures and similarity measures. Using interconnection between single-valued neutrosophic sets and symptoms of patient, we determine the type of disease. We define new distance formulas for single valued neutrosophic sets. We develop two new medical diagnosis algorithms under neutrosophic environment. We also solve a numerical example to illustrate the proposed algorithms and finally, we compare the obtained results

Area under ROC curve of energy detection over generalized fading channels

A fast and reliable detection scheme is essential in several wireless applications such as radar and cognitive radio systems. Energy detection is such a method as it does not require a priori information of the received signal while it exhibits low implementation complexity and costs. Since the detection capability of ED is largely affected by the effects of multipath fading, this paper is devoted to a thorough analysis of energy detection based spectrum sensing over generalized fading conditions. To this end, analytical expressions are firstly derived using the area under the receiver operating characteristic curve (AUC) under additive white Gaussian noise. This analysis is subsequently extended to the case of generalized fading conditions characterized by k - μ and η - μ fading distributions. The offered results are novel and are employed in analyzing the corresponding performance. It is shown that fading phenomena result to detrimental effects on the performance of spectrum sensing since the deviation between severe and non-severe conditions is rather substantial

A Comprehensive Framework for Spectrum Sensing in Non-Linear and Generalized Fading Conditions

We derive a comprehensive analytical framework for the ED over generalized, extreme, and non-linear fading conditions which addresses the topic completely. This is carried out for both conventional and diversity receptions and it is based on the area under the ROC curve (AUC), which is an efficient performance measure that is widely used in physical sciences and engineering. This differentiates the considered methodology from the aforementioned routine approaches and additionally provides generic results on the arbitrary derivatives of the MGF of useful generalized processes. The asymptotic behavior of the derived expressions is also analyzed providing direct and concrete insights on the role and effect of the involved parameters on the ED performance. The offered analytic results are subsequently employed in quantifying the performance of ED over various types of fading conditions, which exhibits that ED performance is significantly degraded by even slight variations of the severity of fading. To this end, it is shown that the detrimental effects of fading can be effectively mitigated with the aid of square-law combining and switch-and-stay combining methods, as a low number of diversity branches can ensure sufficient and holistic performance improvement even in severe fading conditions

An Unsupervised Approach for Sentiment Analysis on Social Media Short Text Classification in Roman Urdu

During the last two decades, sentiment analysis, also known as opinion mining, has become one of the most explored research areas in Natural Language Processing (NIP) and data mining. Sentiment analysis focuses on the sentiments or opinions of consumers expressed over social media or different web sites. Due to exposure on the Internet, sentiment analysis has attracted vast numbers of researchers over the globe. A large amount of research has been conducted in English, Chinese, and other languages used worldwide. However, Roman Urdu has been neglected despite being the third most used language for communication in the world, covering millions of users around the globe. Although some techniques have been proposed for sentiment analysis in Roman Urdu, these techniques are limited to a specific domain or developed incorrectly due to the unavailability of language resources available for Roman Urdu. Therefore, in this article, we are proposing an unsupervised approach for sentiment analysis in Roman Urdu. First, the proposed model normalizes the text to overcome spelling variations of different words. After normalizing text, we have used Roman Urdu and English opinion lexicons to correctly identify users\u27 opinions from the text. We have also incorporated negation terms and stemming to assign polarities to each extracted opinion. Furthermore, our model assigns a score to each sentence on the basis of the polarities of extracted opinions and classifies each sentence as positive, negative, or neutral. In order to verify our approach, we have conducted experiments on two publicly available datasets for Roman Urdu and compared our approach with the existing model. Results have demonstrated that our approach outperforms existing models for sentiment analysis tasks in Roman Urdu. Furthermore, our approach does not suffer from domain dependency

Total cholesterol and triglycerides status in autistic spectrum disorder children: a case-control study on Bangladeshi children

Background: Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by challenges in social interaction, communication, and repetitive behaviors. The association between lipid profiles, particularly total cholesterol and triglycerides, and ASD in children is a growing focus in pediatric health research. This study aimed to assess the total cholesterol and triglycerides status in autistic spectrum disorder children. Methods: This cross-sectional study was conducted in the department of physiology, Bangabandhu Sheikh Mujib Medical University, Dhaka from March 2014 to January 2015 with 100 male children, half in a healthy control group (group A) and the other half diagnosed with autism spectrum disorder (group B). Results: In this study, no significant correlation was found between the groups for age (p=0.94) or BMI (p=0.29). The mean (±SE) serum total cholesterol levels were 146±1.70 mg/dl in group A and 145.00±3.77 mg/dl in group B, showing no significant difference between the two groups (p=0.885). But, the mean (±SE) serum triglyceride levels were 86.14±3.28 mg/dl in group A and 107.74±7.91 mg/dl in group B, with significantly higher levels compared to group A (p<0.01). Conclusions: Although there is no significant difference in serum total cholesterol levels between healthy children and those with autistic spectrum disorder, there is a significant difference in serum triglyceride levels. Therefore, further studies are needed to provide a clearer understanding of the lipid profile comparison

Syntheses and crystal structures of mixed-ligand copper(II)–imidazole–carboxylate complexes

Crystallographic data for the structures in this paper have been deposited with the Cambridge Crystallographic Data Center, CCDC, 12 Union Road, Cambridge CB2 1EZ, UK. Copies of the data can be obtained free of charge on quoting depository numbers CCDC-1543434 (1), CCDC-1543435 (2) and CCDC-1543436 (3) (Fax:+44-1223-336–033; E-mail: [email protected]; http://www.ccdc.cam.ac.uk). Supplemental data for this article can be accessed at https://doi.org/10.1080/00958972.2018.1460471.Peer reviewedPostprin

A New Global Ocean Climatology

A new global ocean temperature and salinity climatology is proposed for two time periods: a long time mean using multiple sensor data for the 1900–2017 period and a shorter time mean using only profiling float data for the 2003–2017 period. We use the historical database of World Ocean Database 2018. The estimation approach is novel as an additional quality control procedure is implemented, along with a new mapping algorithm based on Data Interpolating Variational Analysis. The new procedure, in addition to the traditional quality control approach, resulted in low sensitivity in terms of the first guess field choice. The roughness index and the root mean square of residuals are new indices applied to the selection of the free mapping parameters along with sensitivity experiments. Overall, the new estimates were consistent with previous climatologies, but several differences were found. The cause of these discrepancies is difficult to identify due to several differences in the procedures. To minimise these uncertainties, a multi-model ensemble mean is proposed as the least uncertain estimate of the global ocean temperature and salinity climatology

Reconnoitering the role of long-noncoding rnas in hypertrophic cardiomyopathy: A descriptive review

Hypertrophic cardiomyopathy (HCM) is the most common form of hereditary cardiomy-opathy. It is characterized by an unexplained non-dilated hypertrophy of the left ventricle with a conserved or elevated ejection fraction. It is a genetically heterogeneous disease largely caused by variants of genes encoding for cardiac sarcomere proteins, including MYH7, MYBPC3, ACTC1, TPM1, MYL2, MYL3, TNNI3, and TNNT23. Preclinical evidence indicates that the enhanced calcium sensitivity of the myofilaments plays a key role in the pathophysiology of HCM. Notably, this is not always a direct consequence of sarcomeric variations but may also result from secondary mutation-driven alterations. Long non-coding RNAs (lncRNAs) are a large class of transcripts ≥200 nucleotides in length that do not encode proteins. Compared to coding mRNAs, most lncRNAs are not as well-annotated and their functions are greatly unexplored. Nevertheless, increasing evidence shows that lncRNAs are involved in a variety of biological processes and diseases including HCM. Accumulating evidence has indicated that lncRNAs are dysregulated in HCM, and closely related to sarcomere construction, calcium channeling and homeostasis of mitochondria. In this review, we have summarized the known regulatory and functional roles of lncRNAs in HCM

Analysis of genetic diversity in chickpea (Cicer arietinum L.) cultivars using random amplified polymorphic DNA (RAPD) markers

Genetic diversity of seven chickpea (Cicer arietinum L.) cultivars of Pakistani origin was analyzed by using random amplified polymorphic DNA (RAPD) markers, an extremely effective method to determine the variations among the chickpea cultivars. Polymerase chain reaction (PCR) conditions were optimized for RAPD and the conditions which gave the optimized results were selected for further amplifications. Using nine random decamers for seven genotypes of chickpea, 63 bands were amplified. Out of 63 bands, 50 were polymorphic in all the seven chickpea cultivars. The numbers of RAPD fragments generated per primer ranged from 3 to 11. However, majority of the primers amplified 7 to 11 fragments. The Jaccard’s similarity coefficients ranged from 0.333 to 0.651. Maximum similarity (65.1%) was observed between PK G-3 and PK G-4 and the lowest similarity (33.3%) was observed between PK G-3 and PK G-7. A dendrogram was constructed by using the unweighted pair group arithmetic mean arrangement (UPGMA) that was based on similarity coefficients. Seven chickpea cultivars were clustered in two distinct groups of which two cultivars (PK G-6 and PK G-7) stood separately in the dendrogram. The results from this study may be useful to maximize the selection of diverse parent cultivars and to broaden the germplasm base in the future for chickpea breeding programs. The information generated from this study can also be used in identifying efficient strategies for the sustainable management of the genetic resources of chickpea crop.Keywords: Random amplified polymorphic DNA (RAPD), polymerase chain reaction (PCR), chickpea cultivars, genetic diversit