Rotating black hole in Rastall theory Kumar, Rahul; Ghosh, Sushant G.
European physical journal. C, Particles and fields,
09/2018, Letnik:
78, Številka:
9
Journal Article
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Rotating black hole solutions in theories of modified gravity are important as they offer an arena to test these theories through astrophysical observation. The non-rotating black hole can be hardly ...tested since the black hole spin is very important in any astrophysical process. We present rotating counterpart of a recently obtained spherically symmetric exact black hole solution surrounded by perfect fluid in the context of Rastall theory, viz, rotating Rastall black hole that generalize the Kerr–Newman black hole solution. In turn, we analyze the specific cases of the Kerr–Newman black holes surrounded by matter like dust and quintessence fields. Interestingly, for a set of parameters and a chosen surrounding field, there exists a critical rotation parameter (
a
=
a
E
), which corresponds to an extremal black hole with degenerate horizons, while for
a
<
a
E
, it describes a non-extremal black hole with Cauchy and event horizons, and no black hole for
a
>
a
E
with value
a
E
is also influenced by these parameters. We also discuss the thermodynamical quantities associated with rotating Rastall black hole, and analyze the particle motion with the behavior of effective potential.
Understanding the complex nature of wear behavior of materials at high-temperature is of fundamental importance for several engineering applications, including metal processing (cutting, forming, ...forging), internal combustion engines, etc. At high temperatures (up to 1000 °C), the material removal is majorly governed by the changes in surface reactivity and wear mechanisms. The use of lubricants to minimize friction, wear and flash temperature to prevent seizing is a common approach in engine tribology. However, the degradation of conventional liquid-based lubricants at temperatures beyond 300 °C, in addition to its harmful effects on human and environmental health, is deeply concerning. Solid lubricants are a group of compounds exploiting the benefit of wear diminishing mechanisms over a wide range of operating temperatures. The materials incorporated with solid lubricants are herein called 'self-lubricating' materials. Moreover, the possibility to omit the use of conventional liquid-based lubricants is perceived. The objective of the present paper is to review the current state-of-the-art in solid-lubricating materials operating under dry wear conditions. By opening with a brief summary of the understanding of solid lubrication at a high temperature, the article initially describes the recent developments in the field. The mechanisms of formation and the nature of tribo-films (or layers) during high-temperature wear are discussed in detail. The trends and ways of further development of the solid-lubricating materials and their future evolutions are identified.
In this article, a D-shaped photonic crystal fiber based surface plasmon resonance sensor is proposed for refractive index sensing. Surface plasmon resonance effect between surface plasmon polariton ...modes and fiber core modes of the designed D-shaped photonic crystal fiber is used to measure the refractive index of the analyte. By using finite element method, the sensing properties of the proposed sensor are investigated, and a very high average sensitivity of 7700 nm/RIU with the resolution of 1.30 × 10
−5
RIU is obtained for the analyte of different refractive indices varies from 1.43 to 1.46. In the proposed sensor, the analyte and coating of gold are placed on the plane surface of the photonic crystal fiber, hence there is no necessity of the filling of voids, thus it is gentle to apply and easy to use.
Comorbidities are associated with the severity of coronavirus disease 2019 (COVID‐19). This meta‐analysis aimed to explore the risk of severe COVID‐19 in patients with pre‐existing chronic ...obstructive pulmonary disease (COPD) and ongoing smoking history. A comprehensive systematic literature search was carried out to find studies published from December 2019 to 22 March 2020 from five databases. The languages of literature included English and Chinese. The point prevalence of severe COVID‐19 in patients with pre‐existing COPD and those with ongoing smoking was evaluated with this meta‐analysis. Overall 11 case series, published either in Chinese or English language with a total of 2002 cases, were included in this study. The pooled OR of COPD and the development of severe COVID‐19 was 4.38 (fixed‐effects model; 95% CI: 2.34‐8.20), while the OR of ongoing smoking was 1.98 (fixed‐effects model; 95% CI: 1.29‐3.05). There was no publication bias as examined by the funnel plot and Egger's test (P = not significant). The heterogeneity of included studies was moderate for both COPD and ongoing smoking history on the severity of COVID‐19. COPD and ongoing smoking history attribute to the worse progression and outcome of COVID‐19.
The automatic detection of diseases in plants is necessary, as it reduces the tedious work of monitoring large farms and it will detect the disease at an early stage of its occurrence to minimize ...further degradation of plants. Besides the decline of plant health, a country’s economy is highly affected by this scenario due to lower production. The current approach to identify diseases by an expert is slow and non-optimal for large farms. Our proposed model is an ensemble of pre-trained DenseNet121, EfficientNetB7, and EfficientNet NoisyStudent, which aims to classify leaves of apple trees into one of the following categories: healthy, apple scab, apple cedar rust, and multiple diseases, using its images. Various Image Augmentation techniques are included in this research to increase the dataset size, and subsequentially, the model’s accuracy increases. Our proposed model achieves an accuracy of 96.25% on the validation dataset. The proposed model can identify leaves with multiple diseases with 90% accuracy. Our proposed model achieved a good performance on different metrics and can be deployed in the agricultural domain to identify plant health accurately and timely.
This review paper looks briefly at conventional approaches and examines the intelligent means for fault diagnosis (FD) and condition monitoring (CM) of electrical drives in detail, especially the ...ones that are common in Industry 4.0. After giving an overview on fault statistics, standard methods for the FD and CM of rotating machines are first visited, and then its orientation towards intelligent approaches is discussed. Major diagnostic procedures are addressed in detail together with their advancements to date. In particular, the emphasis is given to motor current signature analysis (MCSA) and digital signal processing techniques (DSPTs) mostly used for feature engineering. Consequently, the statistical procedures and machine learning techniques (stemming from artificial intelligence—AI) are also visited to describe how FD is carried out in various systems. The effectiveness of the amalgamation of the model, signal, and data-based techniques for the FD and CM of inductions motors (IMs) is also highlighted in this review. It is worth mentioning that a variety of neural- and non-neural-based approaches are discussed concerning major faults in rotating machines. Finally, after a thorough survey of the diagnostic techniques based on specific faults for electrical drives, several open problems are identified and discussed. The paper concludes with important recommendations on where to divert the research focus considering the current advancements in the FD and CM of rotating machines.
Background and aims
Metabolic associated fatty liver disease (MAFLD) is a novel concept proposed in 2020, the utility of which has not been tested and validated in real world. We aimed to compare the ...characteristics of MAFLD and non‐alcoholic fatty liver disease (NAFLD).
Methods
The data was retrieved from the third National Health and Nutrition Examination Surveys of the United States, which is an unbiased survey dataset and frequently used for the study of fatty liver disease.
Results
A total of 13 083 cases with completed ultrasonography and laboratory data were identified from the NHANES III database. MAFLD was diagnosed in 4087/13 083 (31.24%) participants, while NAFLD in 4347/13 083 (33.23%) amongst the overall population and 4347/12 045 (36.09%) in patients without alcohol intake and other liver diseases. Compared with NAFLD, MAFLD patients were significantly older, had higher BMI level, higher proportions of metabolic comorbidities (diabetes, hypertension) and higher HOMA‐IR, lipid and liver enzymes. MAFLD patients with alcohol consumption were younger than those without, and more likely to be male. They had less metabolic disorder but higher liver enzymes. There were more cases with advance fibrosis in MAFLD patients with alcohol consumption.
Conclusion
MAFLD definition is more practical for identifying patients with fatty liver disease with high risk of disease progression.
Type II pyridoxal phosphate-dependent decarboxylase (PLP_deC) enzymes play important metabolic roles during nitrogen metabolism. Recent evolutionary profiling of these genes revealed a sharp ...expansion of histidine decarboxylase genes in the members of Solanaceae family. In spite of the high sequence homology shared by PLP_deC orthologs, these enzymes display remarkable differences in their substrate specificities. Currently, limited information is available on the gene repertoires and substrate specificities of PLP_deCs which renders their precise annotation challenging and offers technical challenges in the immediate identification and biochemical characterization of their full gene complements in plants. Herein, we explored their evolutionary trails in a comprehensive manner by taking advantage of high-throughput data accessibility and computational approaches. We discussed the premise that has enabled an improved reconstruction of their evolutionary lineage and evaluated the factors offering constraints in their rapid functional characterization, till date. We envisage that the synthesized information herein would act as a catalyst for the rapid exploration of their biochemical specificity and physiological roles in more plant species.
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•In this review, graphene based nanocomposite electrodes are discussed.•Emphasis is given on graphene nanocomposite with metal oxides and conducting polymers.•Hybrid electrodes of ...graphene with silicon nanowires are also discussed.•The synthesis process of graphene composite is also covered.
This review covers the developments towards graphene based composite electrodes for supercapacitor application. In particular, graphene is being considered as the potential electrode material for high power supercapacitor application because of its extraordinary physical and chemical properties such as large specific surface area, good electrical conductivity and large corrosion resistance in aqueous electrolytes. However, it does not meet the requirement of high energy density for the supercapacitor. Therefore, graphene has been mixed with other materials to improve the energy density of the device. The supercapacitor performance of graphene based composites as electrodes has been significantly enhanced. In this context, synthesis and electrochemical performance of graphene based composite electrodes with metal oxides, ferrites, conducting polymers and other materials are discussed in this review.
•COVID-19 is a new respiratory and systemic disease which needs quick identification of potential critical patients.•There is a significant reduction of lymphocyte count in the severe COVID-19 group ...compared to the non-severe group.•Those with lymphopenia have a 3-fold higher risk of developing severe COVID-19.•Lymphopenia is a prominent feature of COVID-19 and lymphocyte counts may be a useful, easily available biomarker in predicting the severity and clinical outcomes.
Coronavirus Disease 2019 (COVID-19) is a new respiratory and systemic disease which needs quick identification of potential critical patients. This meta-analysis aimed to explore the relationship between lymphocyte count and the severity of COVID-19.
A comprehensive systematic literature search was carried out to find studies published from December 2019 to 22 March 2020 from five databases. The language of literatures included English and Chinese. Mean difference (MD) of lymphocyte count in COVID-19 patients with or without severe disease and odds ratio (OR) of lymphopenia for severe form of COVID-19 was evaluated with this meta-analysis.
Overall 13 case-series with a total of 2282 cases were included in the study. The pooled analysis showed that lymphocyte count was significantly lower in severe COVID-19 patients (MD -0.31×109/L; 95%CI: -0.42 to -0.19×109/L). The presence of lymphopenia was associated with nearly threefold increased risk of severe COVID-19 (Random effects model, OR=2.99, 95% CI: 1.31-6.82).
Lymphopenia is a prominent part of severe COVID-19 and a lymphocyte count of less than 1.5×109/L may be useful in predicting the severity clinical outcomes.
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