Vibration monitoring of rotor bearing system using MFS-lite

Vibrations in rotating machinery are commonly the result of mechanical faults including mass unbalance, coupling misalignment, mechanical looseness etc. Rotating machinery with overhung rotors is very common in industries. Unbalanced rotor and misaligned shafts usually cause excessive machine vibration, generates large forces on bearings and thus reduces the machine life span and may lead to property loss and even loss of human life. Two-plane balancing of overhung rotors is one of the most challenging problem that maintenance engineers may encounter. As a prerequisite, successful diagnosis of unbalanced overhung rotor system must be performed. The vibration signatures of unbalanced overhung rotors with unknown initial conditions are different from those of the systems with centre hung rotors that has been studied in the present work. Experiments were carried out on a Machinery Fault Simulator-Lite (MFS-Lite) for both balanced and unbalanced rotor systems. The data were analysed using the Balance Quest software and efforts were focused on identifying the system characteristic signatures. Further, the results were verified through analytical methods and the results were found to be satisfactory

Comparative Analysis of Flexural Capacity of Bamboo Reinforced and Conventional Steel Reinforced Concrete Beams Through Numerical Evaluation

Steel reinforcement bars are commonly used in the building industry, but their production contributes to toxic waste and emissions. Bamboo is being marketed as a sustainable alternative due to its low cost and tensile strength. It is a readily available natural material that can potentially replace steel as a conventional reinforcement. The idea of hybrid beams (50% bamboo and 50% steel) was developed to get equal outcomes in terms of the structural reaction, and ABAQUS was used to develop a set of beams. By using conventional dimensions and material qualities, a total of five beams were modeled. According to the analysis, the maximum displacements for each beam would be different. The load-displacement curve of five beams was obtained and it was determined that when combined with steel, bamboo may partially replace it

Knowledge about asthma: A cross-sectional survey in 4 major hospitals of Karachi, Pakistan

Objective: To determine knowledge and misconceptions about asthma among the local population..Methods: This cross-sectional study was conducted at four tertiary care hospitals; Aga Khan University Hospital, Civil Hospital Karachi, Jinnah Postgraduate Medical Centre and Ojha Institute of Chest Diseases, Karachi, from October to November 2016, and comprised hospital attendants. The questionnaire used in the study comprised 26 questions answered with a true, false or not sure answer.SPSS 20 was used for data analysis.Results: There were 400 participants. The overall mean age was 41.2±14.2 years, and 214(53.5%) of the participants were males. Moreover, 75(19%) participants thought that asthma was a psychological disorder while 181(45%) considered it an infectious disease. Nearly 174(43.5%) believed that inhaled medications had significant side effects. Besides, 264(66%) participants considered steam inhalation to be an effective treatment for asthma, 269(67%) thought that patients with asthma should avoid rice in their diet and 167(42%) considered milk as a common trigger.CONCLUSIONS: Participants\u27 knowledge about asthma was poor and misconceptions were common about the condition

A novel CuBi2O4/polyaniline composite as an efficient photocatalyst for ammonia degradation

A novel polyaniline (PANI) coupled CuBi2O4 photocatalyst was successfully synthesized via in situ polymerization of aniline with pre-synthesized CuBi2O4 composites. The structure and morphology of the synthesized CuBi2O4/PANI composite photocatalyst were characterized by X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR) and the photocatalytic performance were evaluated through degradation process of ammonia in water under visible light irradiation. The resultant CuBi2O4/PANI composite showed exceptional stability as its structure and morphology persisted even after being immersed in water for 2 days. The composite photocatalyst exhibited improved charge transport properties due to the electrical conductivity of the PANI protective layer, leading to enhanced photoelectrochemical activity in water and removal of ammonia. PANI with CuBi2O4 (10% wt) heterostructure was applied for photodegradation of ammonia and exhibited a 96% ammonia removal efficiency (30 mg/l with 0.1 g photocatalyst and 180 min), as compared to PANI (78%) and CuBi2O4 (70%). The degradation was attributed to the efficient charge transfer (e− and h+) and formation of reactive oxygen species upon simulated sunlight exposure. The present work suggests that the CuBi2O4/PANI photocatalyst can be synthesized in a simple process and provides an excellent adsorption capacity, high photocatalytic activity, long term stability, and reusability making it a promising alternative for ammonia removal from wastewater

Predicting Breast Cancer Leveraging Supervised Machine Learning Techniques

Breast cancer is one of the leading causes of increasing deaths in women worldwide. The complex nature (microcalcification and masses) of breast cancer cells makes it quite difficult for radiologists to diagnose it properly. Subsequently, various computer-aided diagnosis (CAD) systems have previously been developed and are being used to aid radiologists in the diagnosis of cancer cells. However, due to intrinsic risks associated with the delayed and/or incorrect diagnosis, it is indispensable to improve the developed diagnostic systems. In this regard, machine learning has recently been playing a potential role in the early and precise detection of breast cancer. This paper presents a new machine learning-based framework that utilizes the Random Forest, Gradient Boosting, Support Vector Machine, Artificial Neural Network, and Multilayer Perception approaches to efficiently predict breast cancer from the patient data. For this purpose, the Wisconsin Diagnostic Breast Cancer (WDBC) dataset has been utilized and classified using a hybrid Multilayer Perceptron Model (MLP) and 5-fold cross-validation framework as a working prototype. For the improved classification, a connection-based feature selection technique has been used that also eliminates the recursive features. The proposed framework has been validated on two separate datasets, i.e., the Wisconsin Prognostic dataset (WPBC) and Wisconsin Original Breast Cancer (WOBC) datasets. The results demonstrate improved accuracy of 99.12% due to efficient data preprocessing and feature selection applied to the input data

Neuroprotective effects of melatonin and celecoxib against ethanol-induced neurodegeneration: A computational and pharmacological approach

© 2019 Al Kury et al. This work is published and licensed by Dove Medical Press Limited. Purpose: Melatonin and celecoxib are antioxidants and anti-inflammatory agents that exert protective effects in different experimental models. In this study, the neuroprotective effects of melatonin and celecoxib were demonstrated against ethanol-induced neuronal injury by in silico, morphological, and biochemical approaches. Methods: For the in silico study, 3-D structures were constructed and docking analysis performed. For in vivo studies, rats were treated with ethanol, melatonin, and celecoxib. Brain samples were collected for biochemical and morphological analysis. Results: Homology modeling was performed to build 3-D structures for IL1β), TNFα, TLR4, and inducible nitric oxide synthase. Structural refinement was achieved via molecular dynamic simulation and processed for docking and postdocking analysis. Further in vivo experiments showed that ethanol induced marked neuronal injury characterized by down-regulated glutathione, glutathione S-transferase, and upregulated inducible nitric oxide synthase. Additionally, ethanol increased the expression of TNFα and IL1β. Finally, neuronal apoptosis was demonstrated in ethanol-intoxicated animals using caspase 3 and activated JNK staining. On the other hand, melatonin and celecoxib treatment ameliorated the biochemical and immunohistochemical alterations induced by ethanol. Conclusion: These results demonstrated that ethanol induced neurodegeneration by activating inflammatory and apoptotic proteins in rat brain, while melatonin and celecoxib may protect rat brain by downregulating inflammatory and apoptotic markers

Assessment of total phenolic and flavonoid contents of selected fruits and vegetables

686-693This work was conceptualized with the goal to investigate different fruits and vegetables for their comparative investigation of total phenolic and total flavonoid contents. The total phenolic content of 9 fruits and 12 vegetables used in the current study was determined by Folin-Ciocalteau assay. In addition, total flavonoid content was identified through catechin and aluminum colorimetric analysis. The ratio among the phenolic and flavonoid contents of fruits and vegetables extracts were also analyzed. Our results showed that methanolic extract of Citrullus lanatus had higher contents of phenolics and flavonoids (215±1.24 mg GAE/100 g and 73±0.81 mg CE/100 g) than other fruits. Moreover, maturity process of fruits from unripened to fully ripened stage showed significant increase in the total phenolic and flavonoid contents. Fruits under study had shown flavonoids/phenolics ratio of 0.32, which indicates that these fruits contained about 32% of flavonoid contents. Among vegetables, the greatest value of phenolic contents was observed in Capsicum annuum (213±1.24 mg GAE/100 g), and total flavonoid content in Raphanus sativus (45±1.24 mg CE/100 g). Vegetables showed lower ratios of flavonoids/phenolics (0.11-0.2) indicating lesser total flavonoid content (11-20%) as compared with fruits. The obtained results indicate that fruits and vegetables could be attributed to a potential source of natural phenolics and flavonoids in the pharmaceutical and food industry. Moreover, the antioxidant activities of these selected fruits and vegetables should also be determined in order to explore their beneficial effects against the prevention and management of disorders caused by oxidative stress

Acyl pyrazole sulfonamides as new antidiabetic agents: synthesis, glucosidase inhibition studies, and molecular docking analysis

Diabetes mellitus is a multi-systematic chronic metabolic disorder and life-threatening disease resulting from impaired glucose homeostasis. The inhibition of glucosidase, particularly α-glucosidase, could serve as an effective methodology in treating diabetes. Attributed to the catalytic function of glucosidase, the present research focuses on the synthesis of sulfonamide-based acyl pyrazoles (5a-k) followed by their in vitro and in silico screening against α-glucosidase. The envisaged structures of prepared compounds were confirmed through NMR and FTIR spectroscopy and mass spectrometry. All compounds were found to be more potent against α-glucosidase than the standard drug, acarbose (IC50 = 35.1 ± 0.14 µM), with IC50 values ranging from 1.13 to 28.27 µM. However, compound 5a displayed the highest anti-diabetic activity (IC50 = 1.13 ± 0.06 µM). Furthermore, in silico studies revealed the intermolecular interactions of most potent compounds (5a and 5b), with active site residues reflecting the importance of pyrazole and sulfonamide moieties. This interaction pattern clearly manifests various structure–activity relationships, while the docking results correspond to the IC50 values of tested compounds. Hence, recent investigation reveals the medicinal significance of sulfonamide-clubbed pyrazole derivatives as prospective therapeutic candidates for treating type 2 diabetes mellitus (T2DM)

Assessment of total phenolic and flavonoid contents of selected fruits and vegetables

This work was conceptualized with the goal to investigate different fruits and vegetables for their comparative investigation of total phenolic and total flavonoid contents. The total phenolic content of 9 fruits and 12 vegetables used in the current study was determined by Folin-Ciocalteau assay. In addition, total flavonoid content was identified through catechin and aluminum colorimetric analysis. The ratio among the phenolic and flavonoid contents of fruits and vegetables extracts were also analyzed. Our results showed that methanolic extract of Citrullus lanatus had higher contents of phenolics and flavonoids (215±1.24 mg GAE/100 g and 73±0.81 mg CE/100 g) than other fruits. Moreover, maturity process of fruits from unripened to fully ripened stage showed significant increase in the total phenolic and flavonoid contents. Fruits under study had shown flavonoids/phenolics ratio of 0.32, which indicates that these fruits contained about 32% of flavonoid contents. Among vegetables, the greatest value of phenolic contents was observed in Capsicum annuum (213±1.24 mg GAE/100 g), and total flavonoid content in Raphanus sativus (45±1.24 mg CE/100 g). Vegetables showed lower ratios of flavonoids/phenolics (0.11-0.2) indicating lesser total flavonoid content (11-20%) as compared with fruits. The obtained results indicate that fruits and vegetables could be attributed to a potential source of natural phenolics and flavonoids in the pharmaceutical and food industry. Moreover, the antioxidant activities of these selected fruits and vegetables should also be determined in order to explore their beneficial effects against the prevention and management of disorders caused by oxidative stress