Digital Humanities and Game Ethics: Investigating the Impact of Representation in Gaming

“Digital humanities” is about the usage of computer-assisted tools to preserve knowledge and disseminate them through technological resources. An extension of these techniques can be seen in today’s hyper realistic games with high-concept storytelling. These games immerse the players in a world that enables them to experience a different reality and often ask them to make choices that have real-life social impact. They have empowered artists to create worlds that could become a testing ground for philosophical theories. This paper concentrates on the impact of gaming on real-world ethical and political questions. This paper primarily focuses on the impact of The Last of Us Part II- an action-adventure game developed by Naughty dog- on the discussion of the inclusion of LGBTQ+ characters on already existing IP (Intellectual Property). The response that the game received among the players can be used to understand the general perspective of these elite communities on LGBTQ+ issues. This paper also includes the positive impact of such inclusion and argues that the diversification of characters in already existing IP substantially contributes to inclusivity and equality

Mechanism of joint formation and characteristics of interface in ultrasonic welding: Literature review

The study of ultrasonic welding has been going on for more than 50 years. The mechanism of joint formation and characterization of the interface in ultrasonically made joints between metal sheets and wires have been the most thought-provoking area for the researchers. The study of post-welding microstructure, the formation of any intermetallic compound at the interface and their effect on the joint strength, the presence of heat affected zone in the ultrasonically joined sheets has been explored but still, arguably the least understood. Interface characteristics are different in similar and dissimilar combinations of metals. This work presents a comprehensive review of literature regarding the studies on the microstructural analysis at the interface of the joints made by Ultrasonic Welding on different combinations of metal sheets. Additionally, this paper provides an analysis of the observations made by different scientists that promote the future scope of research in this area. The study has been confined to Ultrasonic metal welding only

A new ghost cell/level set method for moving boundary problems:application to tumor growth

In this paper, we present a ghost cell/level set method for the evolution of interfaces whose normal velocity depend upon the solutions of linear and nonlinear quasi-steady reaction-diffusion equations with curvature-dependent boundary conditions. Our technique includes a ghost cell method that accurately discretizes normal derivative jump boundary conditions without smearing jumps in the tangential derivative; a new iterative method for solving linear and nonlinear quasi-steady reaction-diffusion equations; an adaptive discretization to compute the curvature and normal vectors; and a new discrete approximation to the Heaviside function. We present numerical examples that demonstrate better than 1.5-order convergence for problems where traditional ghost cell methods either fail to converge or attain at best sub-linear accuracy. We apply our techniques to a model of tumor growth in complex, heterogeneous tissues that consists of a nonlinear nutrient equation and a pressure equation with geometry-dependent jump boundary conditions. We simulate the growth of glioblastoma (an aggressive brain tumor) into a large, 1 cm square of brain tissue that includes heterogeneous nutrient delivery and varied biomechanical characteristics (white matter, gray matter, cerebrospinal fluid, and bone), and we observe growth morphologies that are highly dependent upon the variations of the tissue characteristics—an effect observed in real tumor growth

DermAI 1.0: A Robust, Generalized, and Novel Attention-Enabled Ensemble-Based Transfer Learning Paradigm for Multiclass Classification of Skin Lesion Images

Skin lesion classification plays a crucial role in dermatology, aiding in the early detection, diagnosis, and management of life-threatening malignant lesions. However, standalone transfer learning (TL) models failed to deliver optimal performance. In this study, we present an attention-enabled ensemble-based deep learning technique, a powerful, novel, and generalized method for extracting features for the classification of skin lesions. This technique holds significant promise in enhancing diagnostic accuracy by using seven pre-trained TL models for classification. Six ensemble-based DL (EBDL) models were created using stacking, softmax voting, and weighted average techniques. Furthermore, we investigated the attention mechanism as an effective paradigm and created seven attention-enabled transfer learning (aeTL) models before branching out to construct three attention-enabled ensemble-based DL (aeEBDL) models to create a reliable, adaptive, and generalized paradigm. The mean accuracy of the TL models is 95.30%, and the use of an ensemble-based paradigm increased it by 4.22%, to 99.52%. The aeTL models' performance was superior to the TL models in accuracy by 3.01%, and aeEBDL models outperformed aeTL models by 1.29%. Statistical tests show significant p-value and Kappa coefficient along with a 99.6% reliability index for the aeEBDL models. The approach is highly effective and generalized for the classification of skin lesions

Exploring Electronic Waste Situation in Africa: A review

In recent years African countries are grappling with the increase of electronic waste (e-waste) which poses challenge to environment and human health. However, factors influencing electronic waste situation in Africa have not been explored and thus not well understood. To fill the gap, this paper aims at exploring e-waste situation in Africa and analysing factors influencing the situation.  To address the objective, a systematic literature review was adopted. Findings show that the amount of e-waste has been increasing in both developed and developing countries over time. Although there are common factors associated with the increase of e-waste, some factors are unique to Africa. These are: reduced cost of used items, taxi incentives for importation of electronic devices and increased use of ICT devices in various sectors.  Furthermore, findings show that developed and developing countries differ in terms of the risks posed by the e-waste and this difference is dependent on how e-waste is managed. Based on the findings, it can be concluded that the situation of e-waste in Africa is somehow different from developed world both in terms of the factors influencing the situation and ways of managing e-waste. In order to deal with e-waste situation, African countries need to improve awareness of their people, establish and capacitate institutions for dealing with e-waste and invest in technologies for managing e-waste

Computer simulation of glioma growth and morphology

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion

Predicting drug pharmacokinetics and effect in vascularized tumors using computer simulation

In this paper, we investigate the pharmacokinetics and effect of doxorubicin and cisplatin in vascularized tumors through two-dimensional simulations. We take into account especially vascular and morphological heterogeneity as well as cellular and lesion-level pharmacokinetic determinants like P-glycoprotein (Pgp) efflux and cell density. To do this we construct a multi-compartment PKPD model calibrated from published experimental data and simulate 2-h bolus administrations followed by 18-h drug washout. Our results show that lesion-scale drug and nutrient distribution may significantly impact therapeutic efficacy and should be considered as carefully as genetic determinants modulating, for example, the production of multidrug-resistance protein or topoisomerase II. We visualize and rigorously quantify distributions of nutrient, drug, and resulting cell inhibition. A main result is the existence of significant heterogeneity in all three, yielding poor inhibition in a large fraction of the lesion, and commensurately increased serum drug concentration necessary for an average 50% inhibition throughout the lesion (the IC50 concentration). For doxorubicin the effect of hypoxia and hypoglycemia (“nutrient effect”) is isolated and shown to further increase cell inhibition heterogeneity and double the IC50, both undesirable. We also show how the therapeutic effectiveness of doxorubicin penetration therapy depends upon other determinants affecting drug distribution, such as cellular efflux and density, offering some insight into the conditions under which otherwise promising therapies may fail and, more importantly, when they will succeed. Cisplatin is used as a contrast to doxorubicin since both published experimental data and our simulations indicate its lesion distribution is more uniform than that of doxorubicin. Because of this some of the complexity in predicting its therapeutic efficacy is mitigated. Using this advantage, we show results suggesting that in vitro monolayer assays using this drug may more accurately predict in vivo performance than for drugs like doxorubicin. The nonlinear interaction among various determinants representing cell and lesion phenotype as well as therapeutic strategies is a unifying theme of our results. Throughout it can be appreciated that macroscopic environmental conditions, notably drug and nutrient distributions, give rise to considerable variation in lesion response, hence clinical resistance. Moreover, the synergy or antagonism of combined therapeutic strategies depends heavily upon this environment