EXPLORING THE ANTI-WEAR AND EXTREME PRESSURE LUBRICATING PERFORMANCE OF JATROPHA OIL MODIFIED WITH NANO-ADDITIVES AND GARLIC OIL

It is imperative to emphasize the wear-reducing and load-sustaining abilities of the lubricating oils, as they are an essential part of their operation. In this study, the anti-wear and extreme pressure (EP) performance of Jatropha oil was explored. The investigation was executed on a 4-ball tester machine according to ASTM-D-4172 and D-2783 standards. Nano-sized Molybdenum disulfide and graphene were added to the base oil, whose addition reduced the wear on the test balls but failed to improve the EP properties. However, the addition of Garlic oil elevated the EP properties of the base oil. The Last Non-seizure load and weld point of the jatropha oil was elevated by up to 3 levels, while the Load Wear index was increased by 91.88%. The Flash Temperature Parameter of jatropha oil was increased by 658% and 250% at 100kgf and 126kgf load, respectively, after the addition of 5% garlic oil. Further, the wear scars were examined under an optical microscope and FESEM, which proved that the addition of nano-additives reduced the wear of the balls during anti-wear tests at lower loads, and garlic oil reduced the wear in EP conditions and produced smoother surfaces. These improvements were attributed to the formation of tribo-films on the surfaces as characterized by the EDS analysis. It was concluded that Garlic oil could be a substantial EP additive to vegetable oils (especially jatropha oil) to lift their load-carrying capacity without hampering their environmentally friendly nature

Analysis of quantum coherence for localized fermionic systems in an accelerated motion

Although quantum coherence is a well known phenomenon in quantum information theory and quantum optics, it has been investigated from the resource theory perspective only recently. Furthermore, quantum coherence has important implications in relativistic quantum information where the degradation of entanglement can be attributed to decoherence. In this paper, we investigate the quantum coherence of Dirac field modes localized in a cavity as observed by two relatively accelerated observers. The acceleration is assigned very small values and its effects are investigated in a perturbative regime. For this purpose, we use parameterized two-qubit pure entangled state and a Werner state. We find that coherence shows a periodic degradation due to accelerated motion. However, this degradation can be balanced by adjusting the durations of uniform and accelerated motion. Moreover, it is found that dynamics of quantum coherence closely resembles that of entanglement under the same settings. This similarity confirms the recent attempts to relate the resource theories of coherence and entanglement in a relativistic regime.publishedVersionUnit Licence Agreemen

Bacteriological Profile and their Susceptibility Pattern in Neonatal Intensive Care Unit at Tertiary Care Hospital in Wah

Introduction: Neonatal sepsis is a clinical syndrome characterized by multiple symptoms and signs of infection during the first month of life. The objective of this study is to determine the frequency of commonly isolated bacteria from patients of neonatal sepsis and their susceptibility patterns in POF hospital at Wah. Methods: This cross-sectional study was carried out in POF Hospital Neonatal intensive care unit and Microbiology laboratory from January 2018 to December 2019. The blood samples of patients suspected with neonatal sepsis were processed as per standard methodology. Results: Out of ninety blood samples, fifty-one (56.7%) yielded the growth of Gram-negative rods and thirty-nine (43.3%) yielded Gram-positive cocci. Among Gram-positive bacteria, coagulase-negative staphylococci were the most common pathogen isolated from 53.8% cases followed by methicillin-resistant Staphylococcus aureus (15.3%). Among Gram-negative bacteria, Klebsiella pneumoniae (54.90%) was the most frequently identified bacteria followed by Serratia marcescens (27.45%). The Gram-positive cocci were the most susceptible to linezolid (100%) followed by vancomycin (87.2%). The Gram-negative rods depict remarkable resistance to ciprofloxacin (92.2%), gentamicin (100%), and meropenem (54.9%). Conclusions: The study concluded a predominance of Gram-negative bacteria as a causative agent of neonatal sepsis in our setup. The bacterial isolates are highly resistant to commonly prescribed oral as well as injectable antibiotics. Implementation of infection control policies is a dire need to combat the grave situation of increasing antibiotic resistance

Unsteady MHD Bionanofluid Flow in a Porous Medium with Thermal Radiation near a Stretching/Shrinking Sheet

This research aims at providing the theoretical effects of the unsteady MHD stagnation point flow of heat and mass transfer across a stretching and shrinking surface in a porous medium including internal heat generation/absorption, thermal radiation, and chemical reaction. The fundamental principles of the similarity transformations are applied to the governing partial differential equations (PDEs) that lead to ordinary differential equations (ODEs). The transformed ODEs are numerically solved by the shooting algorithm implemented in MATLAB, and verification is done from MATLAB built-in solver bvp4c. The numerical data produced for the skin friction coefficient, the local Nusselt number, and the local Sherwood number are compared with the available result and found to be in a close agreement. The impact of involved physical parameters on velocity, temperature, concentration, and density of motile microorganisms profiles is scrutinized through graphs. It is analyzed that the skin friction coefficient enhances with increasing values of an unsteady parameter A, magnetic parameter M, and porosity parameter Kp. In addition, we observe that the density of a motile microorganisms profile enhances larger values of the bioconvection Lewis number Lb and Peclet number Pe and decreases with the increasing values of an unsteady parameter A.publishedVersio

The Impact Of Ethical Values On The Corporate Social Responsibility In Public Sector Of Pakistan

This research paper shows that ethical values in the organization have impact on the CSR activities of the organization. All the parameters, the researchers use in the  research is well tested and exercised before. To explain the  point of view in well understandable manner, a structured model is derived from the literature on the topic of the research. This result also helps the public sector organizations of PAKISTAN to understand the reasons and causes of few CSR activities in this sector. Also gives them some recommendation to improve their processes for establishing the CSR culture in their organizations. Key words: Corporate social responsibility, Ethical values, Motivatio

Enhanced quantum teleportation using multi-qubit logical states

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Mixed noise removal using adaptive median based non-local rank minimization

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In-vitro experimental analysis and numerical study of temperature in bone drilling

BACKGROUND: Bone drilling is a common practice of surgical treatments in orthopaedics and traumatology. Penetration of a high-speed drill into bone tissue is accompanied by generation of a significant amount of heat. Cooling of the drilling region is necessary to avoid potential risk of thermal damage to bone. OBJECTIVE: The purpose of this study was to measure and predict bone temperature by conducting experiments and numer- ical simulations using cooling by means of irrigation at two different temperatures. METHODS: A series of experiments and numerical studies were performed to investigate the effect of cooling conditions on the rise in bone temperature in drilling. The temperature increase in bone was assessed for different drilling speeds and feed rates in the presence irrigation at 5◦C and 25◦ C. RESULTS: Bone temperature was found to be strongly affected by the drilling parameters and cooling conditions. Irrigation with water at 5◦C kept bone temperature well below the thermal threshold level. CONCLUSION: This study strongly recommends the use of irrigation at lower temperature for safe surgical incision

Hybrid Deep Learning Framework for Reduction of Mixed Noise via Low Rank Noise Estimation

In this paper, an innovative hybridized deep learning framework (EN-CNN) is presented for image noise reduction where the noise originates from heterogeneous sources. More specifically, EN-CNN is applied to the benchmark natural images affected by a mixture of additive white gaussian noise (AWGN) and impulsive noise (IN). Reduction of mixed noise (AWGN and IN) is relatively more involved as compared to removing simply one type of noise. In fact, mitigating the impact of a mixture of multiple noise types becomes exceedingly challenging due to simultaneous presence of different noise statistics. Although, various effective deep learning approaches and the classical state-of-the-art approaches like WNNM have been used to suppress AWGN noise only, the same techniques are not suitable in case of mixed noise. In this context, EN-CNN can not only infer changed noise statistics but can also effectively eliminate residual noise. Firstly, EN-CNN employs the classical method of neighborhood filtering followed by non-local low rank estimation to respectively reduce IN noise and estimate the residual noise characteristics after reducing IN noise. As a result of this step, we obtain a pre-processed image with residual noise statistics. Secondly, convolutional neural network (CNN) is applied to the pre-processed image based on the noise statistics inferred in the first step. This two pronged strategy, in conjunction with the deep learning mechanism, effectively handles the mixed noise suppression. As a result, the suggested framework yields promising results as compared to various state-of-the-art approaches.publishedVersio