Sensor placement for fault location identification in water networks: A minimum test cover approach

This paper focuses on the optimal sensor placement problem for the identification of pipe failure locations in large-scale urban water systems. The problem involves selecting the minimum number of sensors such that every pipe failure can be uniquely localized. This problem can be viewed as a minimum test cover (MTC) problem, which is NP-hard. We consider two approaches to obtain approximate solutions to this problem. In the first approach, we transform the MTC problem to a minimum set cover (MSC) problem and use the greedy algorithm that exploits the submodularity property of the MSC problem to compute the solution to the MTC problem. In the second approach, we develop a new \textit{augmented greedy} algorithm for solving the MTC problem. This approach does not require the transformation of the MTC to MSC. Our augmented greedy algorithm provides in a significant computational improvement while guaranteeing the same approximation ratio as the first approach. We propose several metrics to evaluate the performance of the sensor placement designs. Finally, we present detailed computational experiments for a number of real water distribution networks

Buffer-aided successive relay selection scheme for energy harvesting IoT networks

In this paper, we analyze the impact of buffer-aided full-duplex successive relay selection schemes with energy harvesting capability of relay nodes in amplifying and forward (AF) and decode and forward (DF) relaying environments for the Internet of Things networks. We propose to select a relay pair based on the energy harvested and signal strength at relay and destination to receive and transmit in the same time slot, respectively. Contrary to the previous relay pair selection schemes which are based on the signal strength only and cause the relay overuse problem, the proposed scheme ensures the balanced use of energy of relay nodes. The proposed relay selection scheme is implemented with the time switching (TS) and power splitting (PS)-based energy harvesting models in AF and DF relaying environments separately. Furthermore, we derive the closed-form expression of the outage probability and average throughput for both the TS and PS approaches in the DF and AF relaying modes. We compare the proposed relay selection scheme with the S-MMRS scheme and prove that the proposed scheme significantly reduces the outage probability and improves the average throughput. Furthermore, the analytical findings are reinforced with the extensive Monte Carlo simulations

Anti-obesity effect of ethanolic extract from Cosmos caudatus Kunth leaf in lean rats fed a high fat diet

BACKGROUND: Obesity is a major health concern both in developed and developing countries. The use of herbal medicines became the subject of interest for the management of obesity due to its natural origin, cost effectiveness and minimal side effects. The present study aimed at investigating anti-obesity potential of ethanolic extract from Cosmos caudatus Kunth leaf (EECCL). METHODS: In this study, the rats were randomly divided into six groups i.e., (1) Normal Diet (ND); (2) Normal Diet and 175 mg/kgBW of EECCL (ND + 175 mg/kgBW); (3) Normal Diet and 350 mg/kgBW of EECCL (ND + 350 mg/kgBW); (4) High Fat Diet (HFD); (5) High Fat Diet and 175 mg/kgBW of EECCL (HFD + 175 mg/kgBW); (6) High Fat Diet and 350 mg/kgBW of EECCL (HFD + 350 mg/kgBW). The anti-obesity potential was evaluated through analyses of changes in body weight, visceral fat weight, and blood biochemicals including total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), leptin, insulin, adiponectin, ghrelin and fecal fat content. In addition, metabolite profiling of EECCL was carried out using NMR spectroscopy. RESULTS: Rats receiving EECCL together with HFD showed significant (p  0.05) different with those of ND rats. Other related obesity biomarkers including plasma lipid profiles, insulin, leptin, ghrelin and adiponectin levels also showed significant improvement (p < 0.05). Administration of EECCL caused significant (p < 0.05) increase in fecal fat excretion, which validates the hypothesis of lipase inhibition, an anti-obesity mechanism similar to standard drug of Orlistat. The 1H-NMR spectra of EECCL ascertained the presence of catechin, quercetin, rutin, kaempherol and chlorogenic acid in the extract. CONCLUSION: Conclusively, EECCL showed anti-obesity properties by inhibition of intestinal lipid absorption and modulation of adipocytes markers

Biochemical characterization and 1H NMR based metabolomics revealed Melicope lunu-ankenda leaf extract a potent anti-diabetic agent in rats

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by continuous hyperglycemia associated with insulin resistance and /or reduced insulin secretion. There is an emerging trend regarding the use of medicinal plants for the treatment of diabetes mellitus. Melicope lunu-ankenda (ML) is one of the Melicope species belonging to the family Rutaceae. In traditional medicines, its leaves and flowers are known to exhibit prodigious health benefits. The present study aimed at investigating anti-diabetic effect of Melicope lunu-ankenda (ML) leaves extract. METHODS: In this study, anti-diabetic effect of ML extract is investigated in vivo to evaluate the biochemical changes, potential serum biomarkers and alterations in metabolic pathways pertaining to the treatment of HFD/STZ induced diabetic rats with ML extract using 1H NMR based metabolomics approach. Type 2 diabetic rats were treated with different doses (200 and 400 mg/kg BW) of Melicope lunu-ankenda leaf extract for 8 weeks, and serum samples were examined for clinical biochemistry. The metabolomics study of serum was also carried out using 1H NMR spectroscopy in combination with multivariate data analysis to explore differentiating serum metabolites and altered metabolic pathways. RESULTS: The ML leaf extract (400 mg/kg BW) treatment significantly increased insulin level and insulin sensitivity of obese diabetic rats, with concomitant decrease in glucose level and insulin resistance. Significant reduction in total triglyceride, cholesterol and low density lipoprotein was also observed after treatment. Interestingly, there was a significant increase in high density lipoprotein of the treated rats. A decrease in renal injury markers and activities of liver enzymes was also observed. Moreover, metabolomics studies clearly demonstrated that, ML extract significantly ameliorated the disturbance in glucose metabolism, tricarboxylic acid cycle, lipid metabolism, and amino acid metabolism. CONCLUSION: ML leaf extract exhibits potent antidiabetic properties, hence could be a useful and affordable alternative option for the management of T2DM

Morinda citrifolia L. leaf extract prevent weight gain in Sprague-Dawley rats fed a high fat diet

Background: Morinda citrifolia L. is widely used as a folk medicinal food plant to manage a panoply of diseases, though no concrete reports on its potential anti-obesity activity. This study aimed to evaluate the potential of M. citrifolia leaf extracts (MLE60) in the prevention of weight gain in vivo and establish its phytochemical profile. Design: Male Sprague-Dawley rats were divided into groups based on a normal diet (ND) or high fat diet (HFD), with or without MLE60 supplementation (150 and 350 mg/kg body weight) and assessed for any reduction in weight gain. Plasma leptin, insulin, adiponectin, and ghrelin of all groups were determined. 1H NMR and LCMS methods were employed for phytochemical profiling of MLE60. Results: The supplementation of MLE60 did not affect food intake indicating that appetite suppression might not be the main anti-obesity mechanism involved. In the treated groups, MLE60 prevented weight gain, most likely through an inhibition of pancreatic and lipoprotein activity with a positive influence on the lipid profiles and a reduction in LDL levels . MLE60 also attenuated visceral fat deposition in treated subjects with improvement in the plasma levels of obesity-linked factors . 1Spectral analysis showed the presence of several bioactive compounds with rutin being more predominant. Conclusion: MLE60 shows promise as an anti-obesity agents and warrants further research

Laryngocele: a rare complication of surgical tracheostomy

BACKGROUND: A laryngocele is usually a cystic dilatation of the laryngeal saccule. The etiology behind its occurrence is still unclear, but congenital and acquired factors have been implicated in its development. CASE PRESENTATION: We present a rare case of laryngocele occurring in a 77-year-old Caucasian woman. The patient presented with one month history of altered voice, no other associated symptoms were reported. The medical history of the patient included respiratory failure secondary to childhood polio at the age of ten; the airway management included a surgical tracheostomy. Flexible naso-laryngoscopy revealed a soft mass arising from the posterior pharyngeal wall obscuring the view of the posterior commissure and vocal folds. The shape of the mass altered with respiration and on performing valsalva maneuver. A plain lateral neck radiograph revealed a large air filled sac originating from the laryngeal cartilages and extending along the posterior pharyngeal wall. The patient was then treated by endoscopic laser marsupialization and reviewed annually. We discuss the complications of tracheostomy and the pathophysiology of laryngoceles and in particular the likely aetiological factors in this case. CONCLUSION: A laryngocele presenting in a female patient with tracheostomy is extremely rare and has not been to date reported in the world literature. A local mechanical condition may be the determinant factor in the pathogenesis of the disease

Fuzzy Logic in Surveillance Big Video Data Analysis: Comprehensive Review, Challenges, and Research Directions

CCTV cameras installed for continuous surveillance generate enormous amounts of data daily, forging the term “Big Video Data” (BVD). The active practice of BVD includes intelligent surveillance and activity recognition, among other challenging tasks. To efficiently address these tasks, the computer vision research community has provided monitoring systems, activity recognition methods, and many other computationally complex solutions for the purposeful usage of BVD. Unfortunately, the limited capabilities of these methods, higher computational complexity, and stringent installation requirements hinder their practical implementation in real-world scenarios, which still demand human operators sitting in front of cameras to monitor activities or make actionable decisions based on BVD. The usage of human-like logic, known as fuzzy logic, has been employed emerging for various data science applications such as control systems, image processing, decision making, routing, and advanced safety-critical systems. This is due to its ability to handle various sources of real world domain and data uncertainties, generating easily adaptable and explainable data-based models. Fuzzy logic can be effectively used for surveillance as a complementary for huge-sized artificial intelligence models and tiresome training procedures. In this paper, we draw researchers’ attention towards the usage of fuzzy logic for surveillance in the context of BVD. We carry out a comprehensive literature survey of methods for vision sensory data analytics that resort to fuzzy logic concepts. Our overview highlights the advantages, downsides, and challenges in existing video analysis methods based on fuzzy logic for surveillance applications. We enumerate and discuss the datasets used by these methods, and finally provide an outlook towards future research directions derived from our critical assessment of the efforts invested so far in this exciting field

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe