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Aircraft health management has been researched at both component and system levels. In instances of certain aircraft faults, like the Boeing 777 fuel icing problem, there is evidence suggesting that a platform approach using an Integrated Vehicle Health Management (IVHM) system could have helped detect faults and their interaction effects earlier, before they became catastrophic. This paper reviews aircraft health management from the aircraft maintenance point of view. It emphasizes the potential of a platform solution to diagnose faults, and their interaction effects, at an early stage. The paper conducts a thorough analysis of existing literature concerning maintenance and its evolution, delves into the application of Artificial Intelligence (AI) techniques in maintenance, explains the rationale behind their employment, and illustrates how AI implementation can enhance fault detection using platform sensor data. Further, it discusses how computational severity and criticality indexes (health indexes) can potentially be complementary to the use of AI for the provision of maintenance information on aircraft components, for assisting operational decisions.

In recent years, there has been an explosion in the power requirement of modern electronic chips [1]. Although the switching power (CV2f) per transistor has remained nearly constant with scaling, the number of transistors per unit area has grown exponentially leading to a significant increase in the power density. This higher power density coupled with a larger chip size, due to increased functionality, has resulted in this explosion in power requirement. Due to excessive losses (ohmic) in delivering power at low voltages, this power has to be delivered at high voltages and then down-converted to the required chip voltage at the Point of Load (POL) [2]. This requires the use of high efficiency (>95%), miniaturized voltage convertors which need passive components like capacitors and inductors that can handle high voltages, currents, and switching frequencies, with small form factors [2]. At the other end, we have microwave and RF electronic systems in the emerging fields of high-speed communication (5G+) where impedance matching networks are needed [3]. These impedance matching networks require the use of capacitors and inductors with a different set of performance specs like high quality factor (Q), self-resonance frequency, & densities [4]. In both cases, the key bottleneck is the design, fabrication and integration of high quality miniaturized passive components that meets all the required performance specs. This can however be quite challenging and complex. In this light, the following article serves as a tutorial for new designers to understand the basic principles of integrated passive's design and integration. The several nuances and challenges that will be faced in the design flow are detailed and explored.

This paper envisions the possibility of a Conscious Aircraft: an aircraft of the future with features of consciousness. To serve this purpose, three main fields are examined: philosophy, cognitive neuroscience, and Artificial Intelligence (AI). While philosophy deals with the concept of what is consciousness, cognitive neuroscience studies the relationship of the brain with consciousness, contributing toward the biomimicry of consciousness in an aircraft. The field of AI leads into machine consciousness. The paper discusses several theories from these fields and derives outcomes suitable for the development of a Conscious Aircraft, some of which include the capability of developing “world-models”, learning about self and others, and the prerequisites of autonomy, selfhood, and emotions. Taking these cues, the paper focuses on the latest developments and the standards guiding the field of autonomous systems, and suggests that the future of autonomous systems depends on its transition toward consciousness. Finally, inspired by the theories suggesting the levels of consciousness, guided by the Theory of Mind, and building upon state-of-the-art aircraft with autonomous systems, this paper suggests the development of a Conscious Aircraft in three stages: Conscious Aircraft with (1) System-awareness, (2) Self-awareness, and (3) Fleet-awareness, from the perspectives of health management, maintenance, and sustainment.

Various methods have been described for nasal intubation in children with temporomandibular joint ankylosis with limited mouth opening. As younger children are uncooperative, they required intubation under anesthesia. When associated with hypertrophied adenoid, there is high risk of bleeding in to the unprotected airway resulting in laryngospasm and/or bronchospsm. We describe here how successful intubation was performed in a child with Magill-tipped Red rubber (Rush) cuffed tracheal tube using an adult 4.1 fibreoptic bronchoscope under intravenous anesthesia. Keywords: Temporomandibular joint (T M joint) ankylosis | Hypertrophied adenoid | Fiberscope, Case Report A six year child weighing 18 Kg with T M Joint bony ankylosis was posted for surgery for release of ankylosis. On preoperative visit, the patient had a [...]

A neonate with complex cardiac disease posted for emergency non cardiac surgery is a challenging task for anesthesiologists. There have complex pathophysiology, which can leads to unstable haemodynamics, arrhythmia and cardiac arrest during anesthesia. Here we report a case of a neonate with double outlet right ventricle with large atrial septal defect posted in emergency as suspected gangrenous bowel due to exomphalus which was also associated with exstrophy of bladder. Keywords: Double outlet right ventricle (DORV) | Tetralogy of Fallot (TOF) | exomphalus | exstrophy of bladder, Introduction A neonate with complex cardiac disease posted for emergency non cardiac surgery is a challenging task for anesthesiologists. They have a complex pathophysiology, which can lead to unstable haemodynamics, [...]

Background: Preanesthetic medication plays an important role in the anesthetic care of children by allaying anxiety, decreasing vagal stimulation and preventing postoperative psychological sequelae. Midazolam and Ketamine are used by oral route as premedicants in pediatric anesthesia. This study was undertaken to compare the two drugs. Methods: Fifty children in the age group of 1 to 7 years posted for elective surgical procedures were randomly allocated to one of two groups--'Group K' and 'Group M'. Group. Group K received Ketamine 6 mg.[kg.sup.-1] p.o. and Group M received Midazolam 0.5 mg.[kg.sup.-1] p.o. Drug acceptance was noted. Heart rate, arterial pressure, respiratory rate, sedation score, anxiolysis score were notes before drug administration, 15 min and 30 min after drug administration. Parental separation score at 30 min and mask acceptance score were also noted. Sedation scores and anxiolysis scores between the groups were compared by Mann-Whitney test; Parental separation, drug acceptance and mask tolerance were analysed by Fisher's exact test. A 'p value' of < 0.05 was considered statically significant. Results: Sedation score, anxiolysis score and mask acceptance score were significantly higher in Group-K than in Group-M (p Keywords: Pediatric anesthesia | preanesthetic medication | Midazolam | Ketamine, Background Preanesthetic medication in pediatrics patients is a challenge for anesthesiologists. It plays an important role in the anesthetic care of infants and children by allaying anxiety, decreasing vagal stimulation [...]

Neurodegenerative diseases, such as Alzheimer’s disease (AD) and Parkinson’s disease (PD), are characterized by progressive loss (and even death) of structure and function of neurons, and have created great burden to the individual and the society. The actual cause of various neurodegenerative diseases still remains a mystery in healthcare. Some of the commonly studied environmental factors causes for neurodegenerative diseases are protein degradation, oxidative stress, inflammation, environmental factor, mitochondrial defects, familial history, and abnormal protein accumulation in neuron. However ageing plays a very important role in neurodegenerative diseases. Medicinal plants and natural compounds, such as Withania somnifera(ashwagandha), Ginseng, curcumin, resveratrol, Baccopa monnieri, Ginkgo biloba, and Wolfberry have been applied to prevent or alleviate neurological diseases and relief of neurological symptoms reported in in vivo or in clinical trails. Natural compounds in nanosize range as a therapeutic agent possess the same activity as in native state. Nanodrug delivery helps to increase the bioavailability of the drug and thereby specifically target cells and tissues. Nanoparticles, polymeric nanomicelles, complex polymers nanocrystal, and nanofibers are used to carry the medicinal plants for drug delivery system in the treatment of neurodegenerative diseases. Especially, electrospinning and electrospraying as straightforward yet versatile techniques for the production of nanosized fibers and particles possess huge potential in encapsulation of natural compounds for the neurodegenerative diseases. This review is a study to understand the role of nanotechnology and natural compounds in neurodegenerative diseases associated with ageing.

Recent advances in bioprinting technology have been used to precisely dispense cell-laden biomaterials for the construction of complex 3D functional living tissues or artificial organs. Organ printing and biofabrication provides great potential for the freeform fabrication of 3D living organs using cellular spheroids, biocomposite nanofibers, or bioinks as building blocks for regenerative therapy. Vascularization is often identified as a main technological barrier for building 3D organs in tissue engineering. 3D printing of living tissues starts with potential support of biomaterials to maintain structural integrity and degradation of certain time periods after printing of the scaffolds. Biofabrication is the production of complex living and nonliving biological products from raw materials such as cells, molecules, ECM, and biomaterials. Generally, two basic methods are used for the fabrication of scaffolds such as conventional/traditional fabrication processes and advance fabrication processes for engineering organs. A wide range of polymers and biomaterials are used for the fabrication of scaffolds in tissue engineering applications. 3D additive manufacturing is advancing day-by-day; however, there are various critical challenging factors used for fabricating 3D scaffolds. This review is aimed at understanding the various scaffold fabrication techniques, types of polymers and biomaterials used for the fabrication processes, various fields of applications, and different challenges faced in their fabrication of scaffolds in regenerative therapy.

Background: Colon cancer remains among the top perpetrators of deaths linked to cancer. The probability of cancer reaching more parts of the body is extremely high in colorectal cancers. Early detection is hence, highly important for faster treatment. Method: In the current work, a hybrid approach toward the detection of colon cancers through the usage of microarray datasets, is presented. Particle Swarm Optimization (PSO) is utilized for features extraction, while Support Vector Machine (SVM) and Bagging approaches are utilized as classifiers. Results: The Colon Microarray Gene Dataset is used to evaluate minimum Redundancy Maximum Relevance (mRMR), Bagging, SVM, PSO and PSO-SVM with regard to classification accuracy, sensitivity and specificity. The proposed PSO-SVM displays best performance in all categories. Conclusion: Experiments reveal the capabilities of the proposed PSO-SVM to explore features space for the optimal features combination for gene selection from microarray data.

Background: Mammographies are a significant technology utilized in the effective detection of breast cancers prior to them becoming palpable during selfexaminations. The primary aim of the study was the determination of screening precision of mammographies as well as ultrasounds in local populations. Method: In the current study, Minimum Spanning Tree (MST) segmentations are suggested for the selection of minute weights amongst all spanning trees. In the suggested method, Fuzzy Local Binary Patterns (FLBPs) are images comprising micro-patterns. LBPs are first-order circular derivatives of patterns which are created through the concatenation of binary gradient directions. It includes fuzzy logic in LBPs through sets of fuzzy rules. Support Vector Machines (SVMs) are utilized for the classification of chosen attributes. Results: Breast cancers in ultrasounds are utilized for the valuation of KNN, SVM-0.1, Naïve Bayes, SVM-0.5 as well as SVM-0.3 approaches in terms of classification precision, sensitivities, specificities, Positive Predictive Values (PPVs) as well as Negative Predictive Values (NPVs). The suggested that SVM-0.3 showed the most optimal performance in all factors. Conclusion: Breast imaging utilizing mammographies as well as sonographies among women who display local or diffused breast pains are of considerable importance, for the assurance of patients as well as clinicians. But if imaging discoveries are symptomatic of pathologies, biopsies ought not to be put off for long.

A large proportion of cancer deaths occur in the developing world, with limited resources for palliative care. Many patients dying at home experience difficult symptoms.

Burn wounds are susceptible to microbial invasion from both resident and exogenous bacteria, which becomes a critical public health issue and causes substantial economic burden. There is a perceived demand to produce new antimicrobial wound dressings that hinder bacterial colonization while accelerating the healing process and hence would provide an improved standard of care for patients. Since ancient times, herbal extracts from medicinally important plants have extensively been used for treating burn injuries. This work reports the utility of electrospun nanofibers containing plant extracts and antibiotics combination as a multifunctional scaffold for treating second-degree burns. First, we determined the various components of plant extracts from Gymnema sylvestreby two different processing methods and their synergism with minocycline antibiotics. Then, we prepared core–shell nanofibrous dressings with poly-ε-caprolactone/gelatin laden with minocycline hydrochloride as a shell and gelatin infused with G. sylvestreextracts (ultrasound-assisted extracts and cold macerated extracts) as the core using coaxial electrospinning. The electrospun nanofibers displayed a smooth, continuous, and bead-free morphology with adequate wettability. The presence of extract components in the core–shell nanofibers resulted in enhanced mechanical properties when compared to pristine mats. The core–shell structures resulted in sustained release of the bioactive components when compared to nanofiber blends. Core–shell nanofiber mats containing plant extracts and antibiotic combinations displayed potent antimicrobial and antibiofilm properties while promoting the spread and proliferation of skin cells when compared to pristine mats. In a porcine model of cutaneous second-degree burns, we showed that wounds treated with the antimicrobial dressing improved re-epithelialization and collagen organization in comparison to untreated wounds.

In this paper, the strange nonchaotic dynamics of a quasi-periodically driven state-controlled cellular neural network (SC-CNN) based on a simple chaotic circuit is investigated using hardware experiments and numerical simulations. We report here two different routes to strange nonchaotic attractors (SNAs) taken by this SC-CNN based circuit system. These routes were confirmed using rational approximation (RA) theory, finite time Lyapunov exponents, spectrum of the largest Lyapunov exponents and their variance, and phase sensitivity exponent. It is observed that the results from both computer simulations as well as laboratory experiments have spectacular resemblance.