Microarchitecture of the Thymus Gland; Its Age and Disease-Associated Morphological Alterations, and Possible Means to Prolong Its Physiological Activity

Thymus is a ductless, highly organized, bilobed encapsulated gland of the lymphoid organs that contributes in thymopoiesis. Thymus plays an important function in the assortment, progress and profusion of T cells. The mature subsets of thymus dependent lymphocytes linked with the thymic epithelial and other cells developed the microstructure that protect the body from the harmful foreign micro-organism. Most of the thymic lobular areas experienced the parenchymal cells hypoplasia, undergone infiltration of stromal FCT and experienced thymic atrophy with age progression. As the host gets adult, the regression of the thymus and the thymopoiesis occurs, which ultimately boost the vulnerable situations of the host and open a gateway to autoimmune diseases. Since past decades, scientists are intensely investigated to develop some tactics for the improvements of the thymus performance including T-cell regeneration and maturation with age progression. This unique organ is continuously altered morphologically with age and disease; however, this microarchitectural alteration and its possible modulations is not yet clear. Therefore, the main purpose of this chapter is to highlight the microstructural compartments and physiological modification of the thymus with age. Also, the chapter is suggesting the possible alternative ways to improve its durable physio-morphology in vertebrates

Precise Computation of Energy Levels and Radiative Lifetimes in the s, p, d, and f Sequence of Hydrogen Isotope, with Natural Line Widths

Energy levels and Radiative lifetimes in Deuterium for the following: ns 2S1/2(n≥2), np2Po(1/2,3/2)(n≥2), nd 2D(3/2,5/2)(n≥3), and nf 2Fo(5/2,7/2)(n≥4) sequence have been  evaluated with uncertainties in energies caused due to uncertainty principal. Theoretical calculations performed utilizing the Weakest Bound Electron Potential Model Theory (WBEPMT). Both sets of data show quite an excellent agreement with the experimental data listed at NIST.  This theoretical computation is also a continuation of the work by Raza. S. et al. in Neutral Hydrogen. The high ‘n’ (principal quantum number) values for both sets  of data are presented very first time by utilizing WBEPMT. Keywords: Energy levels, Radiative lifetimes, Quantum defects, Weakest bound electron, Natural line width. DOI: 10.7176/JNSR/9-10-07 Publication date:May 31st 201

Sewing Needle as Foreign Body in Urethra of an Adolescent Boy: Case Report

Self-insertion of a foreign body in the urethra is an uncommon presentation clinically. The cases usually arise due to fulfillment of sexual desire, for recreation, play, or exploration, or the foreign body insertion may take place accidentally. We present a case of an adolescent boy with a foreign body urethra presenting to the emergency room with urinary retention, pain, and dysuria. Attending urologist suspected urethral stricture and ordered ultrasonography to investigate which turned out to be a sewing needle in his urethra. The patient was then enquired about the foreign body. He tried to self-dilate his urethra as he was experiencing lower urinary tract symptoms. The sewing needle was removed by endoscopy and he was administered with antibiotics and painkillers. The urethral foreign bodies may present with pain, dysuria, or urinary incontinence and these foreign bodies are mostly seen in the male population in the adolescent age group

Novel decision aid model for green supplier selection based on extended EDAS approach under pythagorean fuzzy Z-numbers

The main objective of this study is to identify the green suppliers that would most effectively assist manufacturing producers in implementing green manufacturing production while including uncertainty and reliability in their decision-making. For this firstly, we justify and manifest the idea of Pythagorean Fuzzy Z-numbers (PyFZNs). It has significant implications for improving the effectiveness of decision-making processes in several theories of uncertainty. It can more flexibly explain real-world data and human cognition due to its capacity to express imprecise and reliable information. Thus it is a more accurate mathematical tool for addressing accuracy and uncertainty. Secondly, we defined the Pythagorean fuzzy Z-number arithmetic aggregation operators and geometric aggregation operators. Thirdly, based on the proposed operators and EDAS (Evaluation based on distance from average solution) approach, a fast decision model is designed to deal with the issue of multi-criteria decision-making. Finally, using PyFZN data we also provide a numerical example to demonstrate the usability of the created multicriteria decision-making (MDM) approach. Moreover, a case study also proves its efficacy

A strategy for hepatitis diagnosis by using spherical q-linear Diophantine fuzzy Dombi aggregation information and the VIKOR method

Hepatitis is an infectious disease typified by inflammation in internal organ tissues, and it is caused by infection or inflammation of the liver. Hepatitis is often feared as a fatal illness, especially in developing countries, mostly due to contaminated water, poor sanitation, and risky blood transfusion practices. Although viruses are typically blamed, other potential causes of this kind of liver infection include autoimmune disorders, toxins, medicines, opioids, and alcohol. Viral hepatitis may be diagnosed using a variety of methods, including a physical exam, liver surgery (biopsy), imaging investigations like an ultrasound or CT scan, blood tests, a viral serology panel, a DNA test, and viral antibody testing. Our study proposes a new decision-support system for hepatitis diagnosis based on spherical q-linear Diophantine fuzzy sets (Sq-LDFS). Sq-LDFS form the generalized structure of all existing notions of fuzzy sets. Furthermore, a list of novel Einstein aggregation operators is developed under Sq-LDF information. Also, an improved VIKOR method is presented to address the uncertainty in analyzing the viral hepatitis categories demonstration. Interesting and useful properties of the proposed operators are given. The core of this research is the proposed algorithm based on the proposed Einstein aggregation operators and improved VIKOR approach to address uncertain information in decision support problems. Finally, a hepatitis diagnosis case study is examined to show how the suggested approach works in practice. Additionally, a comparison is provided to demonstrate the superiority and efficacy of the suggested decision technique

Impact of Hypoxia on Astrocyte Induced Pathogenesis

Astrocytes are the most abundant cells of the central nervous system. These cells are of diverse types based on their function and structure. Astrocyte activation is linked mainly with microbial infections, but long-term activation can lead to neurological impairment. Astrocytes play a significant role in neuro-inflammation by activating pro-inflammatory pathways. Activation of interleukins and cytokines causes neuroinflammation resulting in many neurodegenerative disorders such as stroke, growth of tumours, and Alzheimer’s. Inflammation of the brain hinders neural circulation and compromises blood flow by affecting the blood–brain barrier. So the oxygen concentration is lowered, causing brain hypoxia. Hypoxia leads to the activation of nuclear factor kappa B (NFkB) and hypoxia-inducible factors (HIF), which aggravates the inflammatory state of the brain. Hypoxia evoked changes in the blood–brain barrier, further complicating astrocyte-induced pathogenesis

Novel Complex Intuitionistic Hesitant Fuzzy Distance Measures for Solving Decision-Support Problems

The key objective of this article is to introduce the innovative idea of a complex intuitionistic hesitant fuzzy set (CIHFS), which blends the intuitionistic hesitant fuzzy set with the complex fuzzy set to address the uncertain information in real-life complex problems. In CIHFS, the range of the membership functions is extended from the subset of the real number to the unit disc under the hesitant environment. To determine how well the CIHFSs can be distinguished from one another, we first propose generalized distance measures and weighted generalized distance measures based on the Hamming, Euclidean, and Hausdorff metrics. Some interesting properties and their relationships are thoroughly discussed. Furthermore, a decision-making framework for selecting the optimal option from the feasible set has been proposed, which is grounded in these distance metrics. For the purpose of proving the method’s efficacy, we included examples from pattern recognition and medical diagnostics

Redefined “Maclaurin Symmetric Mean Aggregation Operators Based on Cubic Pythagorean Linguistic Fuzzy Numbers”

In this study, we highlight the errors in Sections 2.3, 2.4, 3, and 4 in the article by Fahmi et al. (J Ambient Intell Human Comput (2020). https://doi.org/10.1007/s12652-020-02272-9) by counter definitions and theorems. We find that the definition of cubic Pythagorean fuzzy set (CPFS) (Definition 2.3.1) and operational laws (Definition 2.3.2) violates the rules to consider the membership and nonmembership functions, and then, we redefined the corrected definition and their operations for CPFS. Furthermore, we redefine the concept of cubic Pythagorean linguistic fuzzy set (CPLFS) and their basic operational laws. In addition, we find that Sections 3 and 4 (consist of a list of Maclaurin symmetric mean (MSM) and dual MSM aggregation operators) are invalid, and then, we redefined the list of updated MSM and dual MSM aggregation operators in correct way. Finally, we established the numerical application of the proposed improved algorithm using cubic Pythagorean linguistic fuzzy information to show the applicability and effectiveness of the proposed technique

A model for emergency supply management under extended EDAS method and spherical hesitant fuzzy soft aggregation information

Abstract Due to the frequent occurrence of numerous emergency events that have significantly damaged society and the economy, the need for emergency decision-making has been manifest recently. It assumes a controllable function when it is critical to limit property and personal catastrophes and lessen their negative consequences on the natural and social course of events. In emergency decision-making problems, the aggregation method is crucial, especially when there are more competing criteria. Based on these factors, we first introduced some basic concepts about SHFSS, and then we introduced some new aggregation operators such as the spherical hesitant fuzzy soft weighted average, spherical hesitant fuzzy soft ordered weighted average, spherical hesitant fuzzy weighted geometric aggregation, spherical hesitant fuzzy soft ordered weighted geometric aggregation, spherical hesitant fuzzy soft hybrid average, and spherical hesitant fuzzy soft hybrid geometric aggregation operator. The characteristics of these operators are also thoroughly covered. Also, an algorithm is developed within the spherical hesitant fuzzy soft environment. Furthermore, we extend our investigation to the Evaluation based on the Distance from Average Solution method in multiple attribute group decision-making with spherical hesitant fuzzy soft averaging operators. And a numerical illustration for “supply of emergency aid in post-flooding the situation” is given to show the accuracy of the mentioned work. Then a comparison between these operators and the EDAS method is also established in order to further highlight the superiority of the established work

Artificial neural network-assisted prediction of radiobiological indices in head and neck cancer

Background and purpose: We proposed an artificial neural network model to predict radiobiological parameters for the head and neck squamous cell carcinoma patients treated with radiation therapy. The model uses the tumor specification, demographics, and radiation dose distribution to predict the tumor control probability and the normal tissue complications probability. These indices are crucial for the assessment and clinical management of cancer patients during treatment planning.Methods: Two publicly available datasets of 31 and 215 head and neck squamous cell carcinoma patients treated with conformal radiation therapy were selected. The demographics, tumor specifications, and radiation therapy treatment parameters were extracted from the datasets used as inputs for the training of perceptron. Radiobiological indices are calculated by open-source software using dosevolume histograms from radiation therapy treatment plans. Those indices were used as output in the training of a single-layer neural network. The distribution of data used for training, validation, and testing purposes was 70, 15, and 15%, respectively.Results: The best performance of the neural network was noted at epoch number 32 with the mean squared error of 0.0465. The accuracy of the prediction of radiobiological indices by the artificial neural network in training, validation, and test phases were determined to be 0.89, 0.87, and 0.82, respectively. We also found that the percentage volume of parotid inside the planning target volume is the significant parameter for the prediction of normal tissue complications probability.Conclusion: We believe that the model has significant potential to predict radiobiological indices and help clinicians in treatment plan evaluation and treatment management of head and neck squamous cell carcinoma patients