PERFORMANCE AND EMISSION ANALYSIS OF CONSTANT SPEED SI ENGINE OPERATED ON HYTHANE (HCNG)

Energy is the basic need of human to survive in this dynamic world. The whole world is toiling hard to meet its energy demands. Every country in this world has high energy demand owing to its increasing population which is posing a threat to energy sustainability. Generally, Energy is consumed in Agriculture, Residential and Transportation sector in which transportation sector has a high percentage of energy consumption. Conventional fuels which are used to power vehicles are having limited reserves. In the present scenario, Petroleum reserves are depleting at a faster rate and causing environmental pollution. It has inspired the researchers to develop new alternate fuels. Alternate fuels are having significant energy content and lower emissions as compared to conventional fuels. Alcohol, Biodiesel, Liquefied Petroleum Gas (LPG), Compressed Natural Gas (CNG) and Hydrogen are the alternate fuels which are being used today. CNG is being used extensively all over the world. CNG is having low laminar burning velocity which makes it more prone towards knocking. Hydrogen has high laminar burning velocity which makes it a better supplement to CNG. The blend thus obtained by mixing Hydrogen and CNG is known as Hythane or HCNG. Hythane has the advantages of both the parent fuels which make it a promising fuel for automotives. This paper includes the effect of Hydrogen addition to CNG which is tested on a single cylinder, four-stroke, water cooled SI engine. Determination of optimum percentage of Hydrogen in CNG and emissions analysis is also included in the paper

The Importance of Telemedicine in a Post COVID World

Telemedicine has found immense popularity, especially in a COVID-19 affected world.  Its application shall improve the quality of health care provided to patients and help in time management as it help facilitates optimized referral systems which are based on the immediate/follow up needs of the patient, decision-making, reduction in patient’s waiting time as well as consultation time.  This review is an effort to shed light on the main practical applications of telemedicine for emphasizing potentialities, problems, and applications of this relatively new branch in medicine. The paper also highlights the various aspects of telemedicine in relation to the healthcare sector, its advantages/disadvantages in a post COVID-19 world

Occurrence of various ingredients in the lake environments at Stornes Peninsula, Ingrid Christenson Coast, East Antarctica

The Larsemann Hills is an ice-free area of approximately 50 km2, located halfway between the Vestfold Hills and the Amery Ice Shelf on the south-eastern coast of Prydz Bay, Princess Elizabeth Land, East Antarctica (69o30’S, 76o19’58”E). The area consists of two major peninsulas Stornes and Broknes, four minor peninsulas, and approximately 130 near shore islands. There are more than 150 lakes on different peninsulas and islands.Surface water samples were collected from two lakes on Stornes Peninsula during 30th Indian Scientific Expedition to Antarctica (ISEA) in mid-January 2011 and analysed for the physico-chemical parameters, major elements and trace metals. Lake waters were slightly acid, free from any colour, odour and turbidity, with dissolved oxygen close to saturation. Total dissolved solids were rather similar in both lakes, up to 71 mg/l and the dominant elements were Cl and Ca. Several minor and trace elements were very low or under detection limits. Total organic carbon was ca 0.7 mg C/l in both lakes and PO4 was at 0.002 mg/level in one lake. Several pesticide residues were all under detection limits as well as alpha and beta radiation activities. Total bacterial count was 1.6×103cfu/ml in lake ST-2 and lower in other lake while psychrophilic bacterial count was 1.6×102cfu in the former lake. Also a Pseudomonas spp. was detected in the ST-2 lake sample

Mycotoxin management through transformations – A review

Mycotoxins are toxic secondary metabolic products of various fungi, mainly belonging to the genera Fusarium (Trichothecenes, Zearalenone), Aspergillus (Aflatoxin) and Penicillium (Ochratoxin) and can be found in almost 25% of the world’s agricultural commodities. These compounds are toxic to humans, animals and plants and therefore, efforts should be made to avoid mycotoxin contamination in food and feed. It has been estimated that at least 300 of these fungal metabolites are potentially toxic to animals and humans. In India 50% losses of agricultural commodities are due to postharvest losses. A number of physical and chemical approaches have already been taken to reduce the effect of mycotoxins, but due to certain limitations of physical and chemical strategies prompted search for other solutions to the mycotoxin hazards. Thus, there is an increasing public pressure for a safer and eco-friendly alternative to control these organisms. Consequently, a new approach is applied for managing mycotoxins through transformations that offer specific, efficient and eco-friendly way for detoxification of mycotoxins. This review aims to brings about the up-to-date management strategies mainly through transformation (genetic and bio) to pre-vent or reduce post harvest damages to the crops caused by storage fungi and the contamination of food and feed by mycotoxins. It will make aware of the new technologies or management methods for mycotoxins through transformation. The transformation methods may become the technology of choice, as they offer a specific, irreversible, efficient and environment friendly way of detoxification that leaves neither toxic residues nor any undesirable by-products

Mycotoxin management through transformations – A review

Mycotoxins are toxic secondary metabolic products of various fungi, mainly belonging to the genera Fusarium (Trichothecenes, Zearalenone), Aspergillus (Aflatoxin) and Penicillium (Ochratoxin) and can be found in almost 25% of the world’s agricultural commodities. These compounds are toxic to humans, animals and plants and therefore, efforts should be made to avoid mycotoxin contamination in food and feed. It has been estimated that at least 300 of these fungal metabolites are potentially toxic to animals and humans. In India 50% losses of agricultural commodities are due to postharvest losses. A number of physical and chemical approaches have already been taken to reduce the effect of mycotoxins, but due to certain limitations of physical and chemical strategies prompted search for other solutions to the mycotoxin hazards. Thus, there is an increasing public pressure for a safer and eco-friendly alternative to control these organisms. Consequently, a new approach is applied for managing mycotoxins through transformations that offer specific, efficient and eco-friendly way for detoxification of mycotoxins. This review aims to brings about the up-to-date management strategies mainly through transformation (genetic and bio) to pre-vent or reduce post harvest damages to the crops caused by storage fungi and the contamination of food and feed by mycotoxins. It will make aware of the new technologies or management methods for mycotoxins through transformation. The transformation methods may become the technology of choice, as they offer a specific, irreversible, efficient and environment friendly way of detoxification that leaves neither toxic residues nor any undesirable by-products

Iot Solutions for Enhancing Agricultural Practices and Environmental Sustainability

This investigate points to think about the results of way better appropriation of IoT within the field of farming. The think about points to appear how made strides cultivating strategies through IoT can give superior results for the environment. The research was able to extend the keen water system and precisely anticipate the yields through optimization calculations. Agriculturists can make their farms' results way better by taking more brilliant and productive choices through Choice Back Frameworks (DSS). The savvy cultivating (accuracy cultivating) has demonstrated to be useful for the environment.  Through detailed studies and evaluations of the life cycle and impact on ecosystems, it has been revealed that this method provides healthier soil, increased biodiversity and lowers carbon emissions. The expenses of cultivation can be minimized by lowering water consumption. This is important because it lowers the issue of the shortage of water. The outputs from the model will highlight the importance of utilizing water resources in an optimized way for farming through IoT based methods. The Decision-Making Systems have been proved to be significantly useful in agricultural activities; they provide an efficient way to make important business decisions. The systems were designed to provide in-time data to the network so that farmers can make their desicions up-to-date

Assessment of genotypes, endosymbionts and clinical characteristics of <i>Acanthamoeba</i> recovered from ocular infection

INTRODUCTION: Acanthamoeba is an emerging pathogen, infamous for its resilience against antiprotozoal compounds, disinfectants and harsh environments. It is known to cause keratitis, a sight-threatening, painful and difficult to treat corneal infection which is often reported among contact lens wearers and patients with ocular trauma. Acanthamoeba comprises over 24 species and currently 23 genotypes (T1-T23) have been identified. AIMS: This retrospective study was designed to examine the Acanthamoeba species and genotypes recovered from patients with Acanthamoeba keratitis (AK), determine the presence of endosymbionts in ocular isolates of Acanthamoeba and review the clinical presentations. METHODOLOGY: Thirteen culture-confirmed AK patients treated in a tertiary eye care facility in Hyderabad, India from February to October 2020 were included in this study. The clinical manifestations, medications and visual outcomes of all patients were obtained from medical records. The Acanthamoeba isolates were identified by sequencing the ribosomal nuclear subunit (rns) gene. Acanthamoeba isolates were assessed for the presence of bacterial or fungal endosymbionts using molecular assays, PCR and fluorescence in situ hybridization (FISH). RESULTS: The mean age of the patients was 33 years (SD ± 17.4; 95% CI 22.5 to 43.5 years). Six (46.2%) cases had AK associated risk factors; four patients had ocular trauma and two were contact lens wearers. A. culbertsoni (6/13, 46.2%) was the most common species, followed by A. polyphaga and A. triangularis. Most of the isolates (12/13) belonged to genotype T4 and one was a T12; three sub-clusters T4A, T4B, and T4F were identified within the T4 genotype. There was no significant association between Acanthamoeba types and clinical outcomes. Eight (61.5%) isolates harboured intracellular bacteria and one contained Malassezia restricta. The presence of intracellular microbes was associated with a higher proportion of stromal infiltrates (88.9%, 8/9), epithelial defect (55.6%, 5/9) and hypopyon (55.6%, 5/9) compared to 50% (2/4), 25% (1/4) and 25% (1/4) AK cases without intracellular microbes, respectively. CONCLUSIONS: Genotype T4 was the predominant isolate in southern India. This is the second report of T12 genotype identified from AK patient in India, which is rarely reported worldwide. The majority of the Acanthamoeba clinical isolates in this study harboured intracellular microbes, which may impact clinical characteristics of AK. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07741-4

A quantum‐based diagnostics approach for additive manufacturing machine

Abstract Current Additive Manufacturing machines have limited techniques to observe process conditions and to decrease process errors. In order to overcome these limitations and increase the level and accuracy of machine intelligence, machine conditions need to be monitored more meticulously. A novel method for the condition monitoring of a 3D‐printer is proposed in this paper. Quantum support vector machine (QSVM) is compiled for recognizing the health condition of the 3D‐printer. The proposed quantum machine learning approach helps in monitoring the health state of the machine and classifies the same as healthy or aberrant. Classical machine learning approaches are inefficient to process the large amount of experimental data in real time. For better decision‐making on such big data, quantum machine learning approaches are deployed which are much more efficient due to their exponential speed and parallel operation on complex sensor data, they show speedups in both the dimensionality and number of experimental data deployed to train the algorithm. The simulation results show that the proposed method has higher accuracy in fault diagnosis than the traditional Support Vector Machine. All the numerical simulations and experiments have been carried out on a real quantum hardware provided by the IBM Quantum computing over the cloud