Traversal of 3D AI Objects in Virtual Game Worlds

This paper aims to highlight the underlying problem of AI traversal in virtual game worlds. AIrsquos self-awareness as an entity, solely depends on the programmer and hence can run into problems if itrsquos not coded properly. The purpose of this research is to eliminate the various factors involved in the traversal of AI and provide a simple solution to the problem that even a novice would be able to code their AI to move around the terrain of the virtual world or in-game world. By using collisions, objective markers and virtual invisible points, the AI can not only move in a 360-degree direction, but cover sufficient in-game mileage and abstain from traversing in to the lsquodanger zonesrsquo which are aptly titled due to them being inaccessible or missing the collision feature. The medium of choice to depict the virtual world is Unreal Engine 4. The reason for choosing UE4 is because it has a similar layout to other game engines like Unity and hence migration of code is possible though not without its own trials

Prescription pattern analysis of antibiotic use in a paediatric intensive care unit of a tertiary care teaching hospital in South India

Background: Antibiotic resistance is rising to alarming levels that necessitates the evaluation of prescription patterns for the rational use of antibiotics. Hence this study was conducted to evaluate antibiotic use in a government run general hospital.Methods: A prospective observational study was conducted to evaluate the rationality of antimicrobial prescription in a paediatric intensive care unit (PICU) of a government run tertiary care teaching hospital using the USAID indicators for rational use of antibiotics. Case records of 104 patients were documented and analysed.Results: The most common antimicrobials prescribed were 3rd generation Cephalosporins namely Ceftriaxone, followed by Aminoglycosides (Amikacin), Imipenams (Meropenam), Anti-Influenza Antiviral (Oseltamivir) and Oxazolidinones (Linezolid). A common trend of antibiotic overuse emerged due to paucity of resources to support decision making and choice of antibiotic. This led to patients being exposed to a high number of antibiotics with an associated increase in morbidity.Conclusions: Antibiotic resistance would remain a challenge until systems for rapid, precise and low cost detection of the causative micro-organisms and antibiotic sensitivity are developed, surveillance systems are increased and antibiotic stewardship programs are enforced

Neurotoxicity: A rare side effect of programmed cell death 1 (PD-1) inhibitors

Immunotherapy is a biological therapy that helps the body\u27s immune system to fight against cancer cells. The Food and Drug Administration (FDA) approved the first immune checkpoint inhibitor in 2011. Since 2011, many immune checkpoint inhibitors have been approved. Programmed cell death 1 (PD-1) inhibitors are now commonly used in multiple malignancies due to their remarkable response. Thus, immune-related adverse events are now coming into the limelight due to the increasing use of PD-1 inhibitors. Here, we present a case of a 54-year-old female with non-small cell lung cancers (NSCLC) treated with pembrolizumab and later presented with severe neurotoxicity

STUDY OF EFFECT OF AYURVEDIC PHARMACEUTICAL PROCESSING NAMED SHODHANA AND MARANA ON THE CHEMICAL COMPOSITION AND CRYSTALLINE STRUCTURE OF METAL IRON AND IRON-CONTAINING MINERALS USING XRD AND XRF ANALYSIS

Objective: This study was designed to evaluate the effect of Ayurvedic pharmaceutical procedures Shodhana and Marana on the chemical composition of the raw material. Methods: Iron and four iron-containing minerals were subjected to Shodhana and Marana. For Shodhana, Loha (Iron), Suvarnamakshika (Copper pyrite) and Mandura (iron slag,) were repeatedly quenched sequentially in sesamin oil, buttermilk, cow’s urine, natural vinegar and herbal decoctions. Kasisa (green vitriol) was grinded in the juice of Eclipta Alba. For Marana, these materials were first grinded in prescribed liquids and then incinerated in closed earthenware caskets in measured pits. Powdered Gairika (red ochre) was roasted in Cow’s ghee for its Shodhana. Samples of Loha (iron)-L1, Samanya Shodhita Loha–L2, Vishesha Shodhita Loha–L3, Loha bahsma-L4, Mandura (iron slag)–M1, Shodhita Mandura–M2, Mandura bahsma–M3, Suvarnamakshika (copper pyrite)-S1, Shodhita Suvarnamakshika-S2, Suvarnamakshika bhasma-S3, Kasisa (green vitriol)-K1, Shodhita Kasisa-K2, Kasisa bahsma–K3, Gairika (red ochre)-G1 and Shodhita gairika-G2; were studied using XRF and XRD techniques. Results: XRD findings suggested that the Chemical nature, elemental composition and Crystaline lattice structure of each substance were altered after extensive processings. XRF studies confirmed the multi-elemental nature of the final products. Reduction in particle size and other morphological changes were observed in intermediate and finished products during each procedure. Conclusion: The study indicates that the composition of material is altered as a result of Ayurvedic pharmaceutical processing, ’Shodhana and Marana

A new fuzzy logic approach for consistent interpretation of dissolved gas-in-oil analysis

Dissolved gas analysis (DGA) of transformer oil is one of the most effective power transformer condition monitoring tools. There are many interpretation techniques for DGA results however all these techniques rely on personnel experience more than analytical formulation. As a result, various interpretation techniques do not necessarily lead to the same conclusion for the same oil sample. Furthermore, significant number of DGA results fall outside the proposed codes of the current based-ratio interpretation techniques and cannot be diagnosed by these methods. Moreover, ratio methods fail to diagnose multiple fault conditions due to the mixing up of produced gases. To overcome these limitations, this paper introduces a new fuzzy logic approach to reduce dependency on expert personnel and to aid in standardizing DGA interpretation techniques. The approach relies on incorporating all existing DGA interpretation techniques into one expert model. DGA results of 2000 oil samples that were collected from different transformers of different rating and different life span are used to establish the model. Traditional DGA interpretation techniques are used to analyze the collected DGA results to evaluate the consistency and accuracy of each interpretation technique. Results of this analysis were then used to develop the proposed fuzzy logic model

EDDense-Net: Fully Dense Encoder Decoder Network for Joint Segmentation of Optic Cup and Disc

Glaucoma is an eye disease that causes damage to the optic nerve, which can lead to visual loss and permanent blindness. Early glaucoma detection is therefore critical in order to avoid permanent blindness. The estimation of the cup-to-disc ratio (CDR) during an examination of the optical disc (OD) is used for the diagnosis of glaucoma. In this paper, we present the EDDense-Net segmentation network for the joint segmentation of OC and OD. The encoder and decoder in this network are made up of dense blocks with a grouped convolutional layer in each block, allowing the network to acquire and convey spatial information from the image while simultaneously reducing the network's complexity. To reduce spatial information loss, the optimal number of filters in all convolution layers were utilised. In semantic segmentation, dice pixel classification is employed in the decoder to alleviate the problem of class imbalance. The proposed network was evaluated on two publicly available datasets where it outperformed existing state-of-the-art methods in terms of accuracy and efficiency. For the diagnosis and analysis of glaucoma, this method can be used as a second opinion system to assist medical ophthalmologists

Standardization of DGA interpretation techniques using fuzzy logic approach

Dissolved gas analysis (DGA) of transformer oil is one of the most effective power transformer condition monitoring tools. There are many interpretation techniques for DGA results. However, all of these techniques rely on personnel experience more than standard mathematical formulation. As a result, various DGA interpretation techniques do not necessarily lead to the same conclusion for the same oil sample. DGA interpretation is yet a challenge in the power transformer condition monitoring research area. To alleviate this issue, this paper introduces a fuzzy logic approach to help in standardizing DGA results quantification and classification using various interpretation techniques such as key gas, Rogers ratio, IEC ratio, Doernenburg and Duval triangle methods. In this context, DGA results for 2000 oil samples have been collected from different transformers of different ratings, life span and operating conditions. Traditional DGA interpretation techniques are used to analyze the results which are then compared with the results of the fuzzy logic models. Results show that the fuzzy logic models enhance the consistency among all current interpretation techniques and can eliminate the need for expert personal to interpret DGA results

Congenital giant melanocytic nevi

Nevi are common skin tumors caused by abnormal overgrowth of cells from the epidermal and dermal layers of the skin. Most nevi are benign, but some pre-cancerous nevi must be monitored or removed. The giant congenital nevus is greater than 10 cm in size, pigmented and often hairy. Between 4% and 6% of these lesions will develop into a malignant melanoma. Since approximately 50% of the melanoma develop by the age of two, and 80% by the age of seven, early removal is recommended. The objective of this paper is to present a unique case of giant nevi and their surgical management

Quantitatively evaluating the effect of social barriers: a case-control study of family members' opposition and women's intention to use contraception in Pakistan.

BACKGROUND: Uptake of family planning services in Pakistan has remained slow over the past decade despite a rapid increase in availability and awareness, indicating that social barriers may be preventing uptake. Social barriers such as opposition by family members have largely been studied qualitatively; there is a lack of quantitative evidence about the effect of different family members' opposition on women's intention to use contraceptives. The objective of this study was to quantitatively evaluate the effect of family members' opposition to family planning on intention to use contraception amongst poor women in Pakistan who have physical access to family planning services. METHODS: An unmatched case control study (nested within a larger cohort study) was conducted in two public hospitals in Karachi, Pakistan. Univariable and multivariable logistic regression analyses were conducted to compare risk factors between women that were not intending to use any contraceptive methods in the future (cases) and women that were planning to use contraceptive methods (controls). RESULTS: 248 cases and 496 controls were included in the study. Negative contraceptive intent was associated with no knowledge of contraception (AOR = 3.79 [2.43-5.90]; p < 0.001), husband's opposition (AOR = 21.87 [13.21-36.21]; p < 0.001) and mother-in-law's opposition (AOR = 4.06 [1.77-9.30]; p < 0.001). CONCLUSIONS: This study is the first to quantitatively assess the effect of opposition by different family members on women's contraceptive intent in Pakistan. Our results indicate that of all family members, husband's opposition has the strongest effect on women's intention to use contraception, even when the women have knowledge of and physical access to family planning services

The effects of residue management practices on phosphorus and potassium uptake in pineapple

Pineapple residue in Malaysia is usually burnt. The need for sustainable agricultural development coupled with the 1997 haze problem in Southeast Asia has led to the calls for "zero burning". A study was initiated at Simpang Renggam Pineapple Estate, Johore to quantify P and K uptake in pineapple parts and to also compare the efficiency of P and K uptake for burn and no-burn practices. At maturity (sixteen months after planting), three plants were sampled from each treatment and partitioned into roots, stem, leaves, fruit, peduncle and crown, and their dry weight, P and K concerntrations determined. Irrespective of treatment difference, P uptake was highest in the fruit, followed by the leaves, stem, crown and roots. The order of K was fruit, stem, peduncle, crown and roots. Between 66 and 58% of the total P and K taken up is recycled and the rest (42 and 34%) is lost through harvest. In situ burning of pineapple leaves before planting does not improve P and K uptake and yield. Major difference in P efficiency for butn (51.60%) and no-burn (53.21%) under fertilized was not observed