Search

Abstract: Herbal medicines are being used by humans since the oldest civilizations and have been an integral part of traditional and alternative medicines. In recent times, pharmaceutical and biomedical scientists are taking interest in developing nutraceutical-based medicines to overcome the side effects and adverse drug reactions caused by allopathic medicines. Nutraceuticals have started occupying the global market. Nutraceuticals have gained widespread acceptance due to their efficacy in treating difficult to treat diseases, low toxicity, low cost, easy accessibility, etc. Safety and efficacy are other important factors in the commercialization process of nutraceuticals. Different novel advanced drug delivery systems have been constantly studied to improve the efficacy and bioavailability of medicines obtained from herbal sources. The transdermal drug delivery system provides a potent alternative to the conventional method of using nutraceuticals. The development of transdermal system-based nutraceuticals could provide the advantage of enhanced bioavailability, improved solubility, bypass of the first-pass metabolism, and targeted delivery of drugs in brain-related disorders. It additionally provides the advantage of being non-invasive. This article reviews the potential effects of various nutraceuticals in brain-related disorders as well as trends in transdermal nano-systems to deliver such nutraceuticals. We have also focused on advantages, applications as well as recent United States-based patents which emphasize emerging interest towards transdermal nutraceuticals in brain disorders.

Abstract: Iridoids are monoterpenoids classed with a cyclopentanopyran framework and detected in various plants and certain special animals. In plants, it exists as glycosides, generally bound to glucose. Around six hundred iridoid glycosides are available in fifty-seven families of plants. Iridoids are abundant in dicotyledonous plants belonging to the Diervillaceae, Loganiaceae, Apocynaceae, Scrophulariaceae, Lamiaceae, and Rubiaceae families. Analytical techniques like chromatography, NMR, UPLC, etc., are used for the identification, separation, and estimation of either herbal extracts or formulations of iridoids. Advanced analytical techniques are useful for precise and accurate quantification of active ingredients responsible for therapeutic effects. They can be achieved by a developed and validated robust analytical method. Iridoids have shown diverse pharmacological properties. Some of the important activities are immunomodulatory, neuroprotective, anti-inflammatory, hepatoprotective, and cardio-protective effects. The other important activities are antimicrobial, antioxidant, hypoglycemic, hypolipidemic, anticancer, choleretic, antispasmodic, and purgative activities attributed to iridoids. There were not many efforts made in the past to gather and review the literature on various aspects of iridoids. This review article has collected a myriad of literature on old and advanced analytical techniques, including method development and validation of methods for quantitative and qualitative analysis of iridoids. The review also emphasizes the role of iridoids in the prevention of various ailments.

Large amount of food waste is generated from Indian kitchens and disposing off such a large amount possesses a great challenge in terms of environmental degradation and viable food waste processing technology. In this work, steam gasification was tested as an alternative viable technology to process the kitchen food waste. Preliminary study was carried out at low temperature on steam gasification in a fixed bed reactor to study the influence of steam flow rate (SFR) and temperature on the syngas yield, syngas composition, hydrogen yield. Performance parameters such as carbon conversion efficiency (CCE), and apparent thermal efficiency (ATE) are also calculated. Steam flow rates are varied from 0.125 mL/min to 0.75 mL/min and the temperatures are varied from 700 °C to 800 °C. The highest hydrogen yield is obtained at 0.5 mL/min SFR and 800 °C temperature and its highest value is 1.2 m3/kg. The highest value of performance parameters, CCE and ATE are found to be 63% and 1.8.

Abstract: At present, people and patients worldwide are relying on the medicinal plant as a therapeutic agent over pharmaceuticals because the medicinal plant is considered safer, especially for chronic disorders. Several medicinal plants and their components are being researched and explored for their possible therapeutic contribution to CNS disorders. Thymoquinone (TQ) is one such molecule. Thymoquinone, one of the constituents of Plant Nigella Sativa, is effective against several neurodegenerative diseases like, Alzheimer's, Depression, Encephalomyelitis, Epilepsy, Ischemia, Parkinson's, and Traumatic. This review article presents the neuropharmacological potential of TQ's, their challenges, and delivery prospects, explicitly focusing on neurological disorders along with their chemistry, pharmacokinetics, and toxicity. Since TQ has some pharmacokinetic challenges, scientists have focused on novel formulations and delivery systems to enhance bioavailability and ultimately increase its therapeutic value. In the present work, the role of nanotechnology in neurodegenerative disease and how it improves the bioavailability and delivery of a drug to the site of action has been discussed. There are a few limitations to developing novel drug formulations, including solubility, pH, and compatibility of nanomaterials. Since here we are targeting CNS disorders, the bloodbrain barrier (BBB) becomes an additional challenge. Hence, the review summarized the novel aspects of delivery and biocompatible nanoparticles-based approaches for targeted drug delivery into CNS, enhancing TQ bioavailability and its neurotherapeutic effects.

Human pose, serving as a robust appearance-invariant mid-level feature, has proven to be effective and efficient for human action recognition and intention estimation. Pose features also have a great potential to improve trajectory prediction for the Vulnerable Road User (VRU) in ADAS or automated driving applications. However, the lack of highly diverse and large VRU pose datasets makes a transfer and application to the VRU rather difficult. This paper introduces the Tsinghua-Daimler Urban Pose dataset (TDUP), a large-scale 2D VRU pose image dataset collected in Chinese urban traffic environments from on-board a moving vehicle. The TDUP dataset contains 21k images with more than 90k high-quality, manually labeled VRU bounding boxes with pose keypoint annotations and additional tags. We optimize four state-of-the-art deep learning approaches (AlphaPose, Mask R-CNN, Pose-SSD and PitPaf) to serve as baselines for the new pose estimation benchmark. We further analyze the effect of using large pre-training datasets and different data proportions as well as optional labeled information during training. Our new benchmark is expected to lay the foundation for further VRU pose studies and to empower the development of accurate VRU trajectory prediction methods in complex urban traffic scenes. The dataset (including an evaluation server) is available on www.urbanpose-dataset.com for non-commercial scientific use.

In this study, Wireless Optical Communication LOS model for underground trains to station based on FSO is designed and simulated to achieve optimum performance and reduced bit error ratio. The FSO medium is highly dependent on Air Quality and Weather conditions bit error ratio vary depending on the conditions. The aim of this design is to achieve a lower Bit error ratio and to increase the range for the communication. The simulation is designed to improve the quality of communication through FSO channel by reducing the bit error ratio through filtering techniques. The results of this simulation will help future research and implementations of the FSO based wireless optical communication for underground trains. This simulation is based on V2I architecture where the communication is based on FSO technology.

Cannabis sativa L. is an annual herbaceous dioecious plant which was first cultivated by agricultural human societies in Asia. Over the period of time, various parts of the plant like leaf, flower, and seed were used for recreational as well as therapeutic purposes. The main chemical components of Cannabis sativa are termed as cannabinoids, among them the key psychoactive constituent is Δ-9-tetrahydrocannabinol and cannabidiol (CBD) as active nonpsychotic constituent. Upon doing extensive literature review, it was found that cannabis has been widely studied for a number of disorders. Very recently, a pure CBD formulation, named Epidiolex, got a green flag from both United States Food and Drug Administration and Drug Enforcement Administration for 2 rare types of epilepsies. This laid a milestone in medical cannabis research. This review intends to give a basic and extensive assessment, from past till present, of the ethnological, plant, chemical, pharmacological, and legal aspects of C. sativa. Further, this review contemplates the evidence the studies obtained of cannabis components on Alzheimer’s, Parkinson’s, amyotrophic lateral sclerosis, multiple sclerosis, emesis, epilepsy, chronic pain, and cancer as a cytotoxic agent as well as a palliative therapy. The assessment in this study was done by reviewing in extensive details from studies on historical importance, ethnopharmacological aspects, and legal grounds of C. sativa from extensive literature available on the scientific databases, with a vision for elevating further pharmaceutical research to investigate its total potential as a therapeutic agent.

The objective of this paper is to develop a computationally efficient and generalised algorithm for the load flow calculation in an active distribution network. The available techniques for the active distribution load flow calculation have limited scope of application and, sometimes, suffer from computational complexity. The applicability of an existing technique remains limited either by DG control modes or by transformer configurations. In this paper, the load flow calculation is carried out by using the concept of Gauss-Zbus iterations, wherein the DG buses are modeled via the technique of power/current compensation. The specific distinctness of the proposed Gauss-Zbus formulation lies in overcoming the limitations imposed by DG control modes for the chosen DG bus modelling as well as in having optimized computational performance. The entire load flow calculation is carried out in the symmetrical component domain by decoupling all the sequence networks. Furthermore, a generalised network modelling is carried out to define decoupled and tap-invariant sequence networks along with maintaining the integrity of the zero sequence network under any transformer configurations.The computational efficiency and accuracy of the methodology proposed are verified through extensive case studies.

The objective of this study is to identify and eliminate unnecessary iteration loops in the load flow analysis of an active distribution network so as to improve its overall computational efficiency. The number of iteration loops is minimised through the integrated modelling of a distributed generator (DG) and the associated coupling transformer. The DG bus is not preserved in the load flow calculation and the aforementioned DG-transformer assembly is represented in the form of a voltage-dependent negative load at the point of connection to the main distribution network. Thus, the iteration stage that is involved in indirectly preserving the DG in the form of a voltage source or negative constant power load can be eliminated. This, in turn, eliminates the need for multiple rounds of forward-backward sweeps (FBS) iterations to determine the bus voltages. The power characteristics of the DG-transformer assembly are thoroughly investigated through a carefully performed case study so as to assess the general convergence performance of the proposed load flow algorithm Furthermore, extensive comparative studies are carried out to verify the computational efficiency attained via the proposed DG modelling in the load flow analysis of an active distribution network.

Priority Preemptive scheduling algorithm is a popular among various other algorithms for scheduling CPU, however it leads to the problem of starvation which happens when processes with lower priority are not given any chance of CPU utilization due to continuous CPU usage by processes with higher priorities. To eradicate this problem here, we have proposed a new algorithm for scheduling CPU which we call it as Modified Priority Preemptive Scheduling Algorithm based on a new approach where we are executing priority Preemptive scheduling in a round robin fashion taking the time quanta equal to the shortest burst time of all the available processes. On analyzing the results, it is observed that modified Preemptive algorithm not only solves the problem of starvation but also enhances the performance of regular Priority Preemptive algorithm by lowering the mean turnaround time and mean waiting time.

INTRODUCTION: Aims of this study were to examine time delays in lung cancer referral pathways in North Queensland (NQ), Australia, and explore patients' perspective of factors causing these delays. METHODS: Prospective study of patients attending three cancer centres in Townsville, Cairns and Mackay in NQ from 2009 to 2012. Times along referral pathway were divided as follows: Onset of symptoms to treatment (T1), symptoms to general practitioner(GP) (T2), GP to specialist (T3), and Specialist to treatment (T4). Quantitative and qualitative methods were used for analysis. RESULTS: 252 patients participated. T1 was influenced by remoteness (125 days in Townsville vs. 170 days for Remote, p=0.01), T2 by level of education (91 days for Primary education vs. 61 days for Secondary vs. 23 days for Tertiary/TAFE, p=0.006), and age group (14 days for 31-50 years, 61 days for 51-70 years, 45 days for >71 years, p=0.026), T3 by remoteness (15 days for Townville and 29.5 days for remote, p=0.02) and T4 by stage of disease (21 days for stage I, 11 days for Stage II, 34 days for Stage III 18 days for Stage IV, p=0.041). Competing priorities of family and work and cost & inconvenience of travel were perceived as rural barriers. CONCLUSION: Remoteness, age and level of education were related to delays in various time lines in lung cancer referral pathways in NQ. Provision of specialist services closer to home may decrease delays by alleviating burden of cost and inconvenience of travel.

The smart grid is widely considered as the advanced version of the power grid. As an essential characteristic of the smart grid, demand response can reschedule the user’s energy consumption to reduce the operating expense from expensive generators, and further to defer the capacity addition in the long run. Demand Response functions as a vital controller for the present electrical framework. From outsider see the interest reaction can be viewed as two connections, one related to customer viewpoint and the other is pertinent to energy supplier or market administrators. But both links are driven by the application of different computational techniques. Throughout the smart grid, the advanced computational technique has been properly utilized to enhance the outcome and capability of learning. The salient feature of this paper is to criticize the applicability of computational techniques for demand response. The paper explores major aspects such as DR issues, different computational techniques, and future extensions of demand response.

Distribution network advancement is the most trending topic in the power system. From reserve capacity reduction by distributed generator (DG) integration to consumer active participation for load management, all the significant changes are occurring in the distribution network. This paper proposes a consumer participation-based load management approach in presence of DGs. Distributed generators such as Photovoltaic (PV) and wind turbines are added to the distribution feeder in constant power voltage mode. Load management is proposed by providing monetary benefits to the consumer for their active participation. Excessive load shifting and formulation of the new peak is prevented by constraints such as thermal, voltage, active and reactive power limit of feeder. Special attention is paid to DGs reactive power supply. The performance of the proposed load management scheme is verified on 15-bus feeder system.

Distribution networks transfer the electrical power the last few miles from transmission to local load centers. These were at first planned as passive systems providing the one directional connection between transmission networks and power end-users. The introduction of Distributed generations (DGs) proposes energy harvesting systems with more flexibility and bidirectional power flows. DGs are intended for generators that are usually employed at a small scale. These generators produce electrical power at places nearer to a consumer or connected to a distribution network. These include both conventional and non-conventional energy resources. In unconnected areas, DGs provide monetary benefits because their installation disposes of the requirement for costly development of distribution and transmission lines. This paper provides a review on significant DG benefits, challenges, applications, drawbacks, and different approaches for DG penetration and gives an insight to power system researchers and engineers for optimal DG planning.

The power system operation needs to keep the harmony among the power generation and demand, failing which will leads to sudden rise and fall of frequency as well as transient tie-line power. AGC is one of the significant control phenomenon in power system, for control of frequency and power in an interconnected system. This paper presents the details of issues related with specific controlling techniques used in AGC at the past and with what control we can rectify those issues in future. This paper also presents a brief review of the controlling methods that has been exercised to automatic generation control (AGC) from the primeval time to the modern day. Review related to literature work of AGC in deregulated environment has been presented.

Eugenol is a bioactive compound widely available in many herbs like clove, cinnamon, tulsi, pepper etc. The compound is known for its antioxidant, antimicrobial, anesthetic, anti-inflammatory, neuroprotective, anti-diabetic, and anti-cancer activities. In pharmaceutical analysis, eugenol is used as a marker for single drugs and drug products. Dental care, household, and personal hygiene products are other areas where it has established its potential. In the food industry, eugenol is used as a flavouring agent in non-alcoholic beverages, baked foods, and chewing gums. Considering the huge potential of eugenol, this review is an attempt to collate the regulatory information, physico-chemical properties, toxicity profile, marketed conventional and novel formulations, analytical methods, extraction procedures, recent patents and clinical trials of the moiety. Based on literature survey a schematic diagram of mechanism of action has also been made.

Smart farming through IoT technology could empower farmers to upgrade profitability going from the amount of manure to be used to the quantity of water for irrigating their fields and also help them to decrease waste. Through IoT, sensors could be used for assisting farmers in the harvest field to check for light, moistness, temperature, soil dampness, etc., and robotizing the water system framework. Moreover, the farmers can screen the field conditions from anyplace and overcome the burden and fatigue to visit farms to confront problems in the fields. For example, farmers are confronting inconvenience while utilizing right quantity and time to use manures and pesticides in their fields as per the crop types. In this chapter, the authors have introduced a model where farmers can classify damaged crops and healthy crops with the help of different sensors and deep learning models. (i.e., The idea of implementing IoT concepts for the benefit of farmers and moving the world towards smart agriculture is presented.)

This paper presents the design, application and analysis of low order modified internal model controller (M-IMC) for automatic voltage regulator (AVR). The drawback of traditional IMC (T-IMC) is the poor input and output disturbance rejection performances that play the key role in AVR for industrial applications. The performance of AVR with M-IMC is compared to T-IMC and ZN tuned PID controller. To the design of low order IMCs, the Routh approximation, improved pole clustering, and truncation methods are applied for the reduction of order of AVR system. The low order controllers are reduces the complexity and computational time of overall system.

Background & Objective: Hearing loss is a common audio-vestibular-related neurosensory disability of inner ears, in which patients exhibit clinical symptoms of dizziness, gait unsteadiness, and oscillopsia, at an initial stage. While, if such disorders are untreated for a prolonged duration then the progression of disease into a chronic state significantly decreases GABA level as well as an alteration in the neurotransmission of CNS systems. Hence, to control the progression of disease into a chronic approaches for timely and targeted delivery of the drugs at the site of action in the ear is now attracting the interest of neurologists for effective and safe treatment of such disorders. Among delivery systems, owing to small dimension, better penetration, rate-controlled release, higher bioavailability; nanocarriers are preferred to overcome delivery barriers, improvement in residence time, and enhanced the performance of loaded drugs. Subsequently, these carriers also stabilize encapsulated drugs while also provide an opportunity to modify the surface of carriers to favor guided direction for site-specific targeting. Contrary to this; conventional routes of drug delivery such as oral, intravenous, and intramuscular are poorer in performance because of inadequate blood supply to the inner ear and limited penetration of blood–inner ear barrier. Conclusion: This review summarized novel aspects of non-invasive and biocompatible nanoparticles- based approaches for targeted delivery of drugs into the cochlea of the ear to reduce the rate, and extent of the emergence of any hearing loss mediated neurological disorders.

There has been an escalation in the number, diversity, and complexity of medical devices. Regulation of these devices has also advanced due to the requirement of better regulatory perspective induced due to elevation in the number of adverse events associated with medical devices. All over the globe, various measures are undertaken to provide better safety to the patients along with attempts to improve the standard of medical devices. The initial and ultimate objective of the concept happens to be unfailingly to ensure patient safety as well as impart required guidance for both manufacturers and adept authorities enabling them to superintend cases coherently and appropriately. Materiovigilance programme of India (MvPI) was launched by the Drug Controller General of India at the Indian Pharmacopoeia commission (IPC) in Ghaziabad in 2015. The main purpose of this initiative is to monitor adverse events associated with medical devices in order to generate safety data, create awareness among the various stakeholders, and prescribe best practices for patient safety. Whilst the reforms in regulations have proposed policies and designs to elucidate, consolidate and accelerate the processes involved in manufacturing and importing medical devices to India, they consistently carry their challenges and limitations. To eliminate such complications the guidelines and regulations are anticipated to be implemented appropriately with the efficacious conclusion. India has been evident in matching with advancements in the World Medical Device regulation scenario, the current review at hand takes upon the question of ‘how successful has it been so far’?

This paper is to discuss about the design a fuel car battery charging system using a foot-pump, that charges the battery enough to start the vehicle. A conventional consumer model automobile has a battery capacity of 50Ah to 60Ah that generally lasts for several years. The starting current required for starter motor of such automobiles ranges from 200A to 500A, which is supplied by the battery and the starter circuit. In scenario of failure of the battery to provide sufficient charge, the above-mentioned device would be used. The project is focused elimination of automotive battery problems, which directly or indirectly revolves around the inability of the battery to produce enough charge to start the vehicle. The occurrence of such situations is generally high in regions with extreme temperature, since a battery failure can be caused by both high and low temperatures. The effectiveness as well as demand for such device will be significantly more in cold weathers (especially in areas with perpetual cold climate). The project also rules out the necessity of jump starting the vehicle with the help of another vehicle's battery. Since the uncertainty of availability of another vehicle for jump starting is one of the major causes of being stranded, the device will prove to be of much help in such cases.

So far we have not extended the core part of Visual Studio that is used most often by the developers – the code editor. The Visual Studio editor offers a rich set of extension points, and most of its parts are extensible via the Managed Extensibility Framework (MEF). In fact, there are so many extensibility points exposed by the editor that covering each of these in details would require a book in itself. Fortunately for us, Microsoft has already documented these extensibility points and features in great depth. In this chapter, we will discuss the extensibility points of the Visual Studio editor and develop extensions for code analysis, fixes, and refactoring.

Thus far we have developed and discussed extensions on custom commands, tool windows, infobars, code generation, code editor, code analysis, and refactoring. However, as a developer, we spend most of our time coding, developing, and debugging, so in this chapter, we will look at ways by which we can enhance our productivity while coding and debugging. We will begin with a discussion on code snippets, then move on to project and item templates. Next we will have a look at adding a connected service provider. Finally, will discuss a generic approach to debug an extension. Let’s get things underway!

In the last few chapters, we have gone through a lot of theories, concepts, and fundamentals of building Visual Studio extensions. Now it’s time to put this theory to practice. In this chapter, we will develop a couple of meaningful and useful, real-world Visual Studio extensions in a step-by-step manner. In the process, we will also learn key fundamentals, concepts, and tricks to develop a Visual Studio extension that can be shipped to the Visual Studio Marketplace or shared with a wider audience.

So far we have only discussed how to develop Visual Studio extensions. Equally important is to know and learn how to ship the extension to the Visual Studio Marketplace so that other Visual Studio users can also use the developed extension. In this chapter, we will learn how we can publish our extension to the Visual Studio Marketplace to make it available for the wider audience. With the DevOps getting more traction than ever before, we will see how we can have automated build setup for the extension projects using the Azure DevOps build pipeline. We will then see how we can leverage Azure DevOps (ADO) to automate the process of publishing an extension to the marketplace. Apart from the Visual Studio Marketplace, there may be scenarios to host extensions in a private extension gallery to share extensions with only a subset of users. So, we will see how we can develop a private extension gallery and host extensions. By the end of this chapter, readers should be comfortable in