Synthesis of quinoline attached-furan-2(3H)-ones having anti-inflammatory and antibacterial properties with reduced gastro-intestinal toxicity and lipid peroxidation

A series of 3-[2-chloroquinolin-3-yl)methylene]-5-aryl-furan-2(3H)-ones {3(a-p)} were synthesized. The required 3-(substitutedbenzoyl) propionic acids {2(a-d)} were prepared under Friedal Craft acylation reaction conditions. The substituted 2-chloroquinoline-3-carbaldehydes {1(a-d)} were synthesized by reaction of substitutedphenylethanone-oxime with phosphorus oxychloride in presence of dimethyl formamide using the Vilsmeir Haack reaction method. These compounds were screened for their anti-inflammatory and antibacterial activities along with their ulcerogenic and lipid peroxidation potentials. The compounds that showed significant anti-inflammatory activity were further screened for their analgesic activity. The compounds were less toxic in terms of ulcerogenicity as compared to a standard, which was also supported by lipid peroxidation studies. The antibacterial activities were performed against Staphylococcus aureus and Escherichia coli. Compounds 3f, 3n and 3o showed significant activity against both S. aureus and E. coli having an MIC value of 6.25μg mL-1

Innocent Preferences in Hume\u27s Morality

Hume believes it is common and natural for people to have preferences for character traits similar to their own, but he remains silent on how to separate the innocent preferences from the blameworthy ones. This paper looks to Hume\u27s morality to answer this question, ultimately arguing for two jointly sufficient criteria: 1) a preference is innocent so long as it doesn’t prevent one from adopting the general point of view and 2) a preference is innocent so long as it is not met with disapproval from a spectator viewing it from the general point of view. I argue that these criteria leave most preferences unscathed, and this result highlights a distinctive pluralism in Hume. I consider the ramifications for this pluralism and argue that it gives Hume’s morality an appeal over more rigid moral theories. I conclude by considering the challenge of factionalism that arises from my interpretation

A GIS inventory of trails in John Forrest National Park Western Australia

Protected areas are facing serious threat due to direct and indirect impacts of human activities. Official and vistor created trails monitored and investigated for management and protection purpose. Geospatial tools are highly implacable in impact assessment and inventory research. GIS inventory was conducted to understand the spatial distribution of formal and informal trails in the study area. We estimated that the linear distribution of trails is 151km of which 52% are informal trails. We have explored that the minimum width along user created trails is 0.6 meters, and the maximum width is 3 meters with a mean value of 2.3m. The inventory estimated the trail footprint covers an area of 69ha in the national park (out of 2676). User activity is an important aspect of trail inventory by analysing trails attributes (width, slope, TTF) off track activities have been identified as well. Flatter and wider trails are an indictaion of ORV and management vehicles driving on trails. Hotspots such as vandalism, TTFs, and informal boundary intersections were mapped as well, clearing vegetation on an area of 138ha in the study area. We observed that approximately 197ha of vegetation been lost due to planned, unplanned trails and hotspots. Trail slope is significant for impact assessment can be used to estimate erosion potential and hazard assessment. Slope distribution models (with 0 to 25 interval) were developed for formal, informal trails in the national park. Steeper slope, lower width is an indication of bike riding and walking on user created trails. We verified trail parameters and user related issues (Trail technical features, width, length, activity, vandalism, informal boundary intersects, ORV, bike riding on both planned and unplanned tracks) while ground-truthing survey (appendix figure 2). Comparing our inventory results with investigations conducted around the world accuracy were found around 75% to 78% (varying with a spatial and spectral resolution of available data). We concluded that GIS and remote sensing is capable of conducting inventory, efficiency can be improved by using higher spatial resolution data and then integrating inventory with field survey. We recommend that park management should involve users (bike riders) in data collection process as to educate them and understand their behaviour

Improved Behavior Monitoring and Classification Using Cues Parameters Extraction from Camera Array Images

Behavior monitoring and classification is a mechanism used to automatically identify or verify individual based on their human detection, tracking and behavior recognition from video sequences captured by a depth camera. In this paper, we designed a system that precisely classifies the nature of 3D body postures obtained by Kinect using an advanced recognizer. We proposed novel features that are suitable for depth data. These features are robust to noise, invariant to translation and scaling, and capable of monitoring fast human bodyparts movements. Lastly, advanced hidden Markov model is used to recognize different activities. In the extensive experiments, we have seen that our system consistently outperforms over three depth-based behavior datasets, i.e., IM-DailyDepthActivity, MSRDailyActivity3D and MSRAction3D in both posture classification and behavior recognition. Moreover, our system handles subject's body parts rotation, self-occlusion and body parts missing which significantly track complex activities and improve recognition rate. Due to easy accessible, low-cost and friendly deployment process of depth camera, the proposed system can be applied over various consumer-applications including patient-monitoring system, automatic video surveillance, smart homes/offices and 3D games

Cigarette smoking worsens systemic inflammation in persons with metabolic syndrome

Background Emerging data suggests that the combination of smoking and metabolic syndrome (MetS) markedly increases cardiovascular disease risk well beyond that of either condition. In this study we assess if this interaction can be explained by an additive increase in the risk of systemic inflammation by MetS and cigarette smoking. Methods We evaluated 5,503 healthy non-diabetic Brazilian subjects (mean age of 43 ± 10 years, 79% males). Participants were divided into sub-groups of smokers and non-smokers with or without MetS. High-sensitivity C reactive protein (hs-CRP) was measured to assess degree of underlying inflammation. Results Overall (19%) had hs-CRP \u3e 3 mg/L. In adjusted regression analyses, compared to non-smokers, there was a 0.19 mg/L (95% CI: 0.05, 0.32) increase in hs-CRP among smokers in the entire population and 0.63 mg/L (95% CI: 0.26, 1.01) increase among smokers with MetS while there was no significant increase among smokers without MetS (β = 0.09 95% CI: -0.05, 0.24). In a fully adjusted logistic regression model, smokers compared to non-smokers were 55% more likely to have elevated hs-CRP in the entire population (OR 1.55, 95% CI: 1.25, 1.92) and more than twice as likely to have elevated hs-CRP if they had MetS ( OR 2.05, 95% CI: 1.40, 3.01) while the risk was non-significant among those without MetS (OR = 1.29, 95% CI: 0.98, 1.69). Conclusion The study demonstrates an additive effect of cigarette smoking on the risk of systemic inflammation in MetS thus highlighting the need for determining smoking status among those with MetS and aggressively targeting smoking cessation in this population

A Depth Video-based Human Detection and Activity Recognition using Multi-features and Embedded Hidden Markov Models for Health Care Monitoring Systems

Increase in number of elderly people who are living independently needs especial care in the form of healthcare monitoring systems. Recent advancements in depth video technologies have made human activity recognition (HAR) realizable for elderly healthcare applications. In this paper, a depth video-based novel method for HAR is presented using robust multi-features and embedded Hidden Markov Models (HMMs) to recognize daily life activities of elderly people living alone in indoor environment such as smart homes. In the proposed HAR framework, initially, depth maps are analyzed by temporal motion identification method to segment human silhouettes from noisy background and compute depth silhouette area for each activity to track human movements in a scene. Several representative features, including invariant, multi-view differentiation and spatiotemporal body joints features were fused together to explore gradient orientation change, intensity differentiation, temporal variation and local motion of specific body parts. Then, these features are processed by the dynamics of their respective class and learned, modeled, trained and recognized with specific embedded HMM having active feature values. Furthermore, we construct a new online human activity dataset by a depth sensor to evaluate the proposed features. Our experiments on three depth datasets demonstrated that the proposed multi-features are efficient and robust over the state of the art features for human action and activity recognition

The Rising Epidemic of Dental Caries in Pakistan: What Clinicians Need to Know

Dental Caries is a non-communicable disease which is causing disturbance globally. It is a multifactorial disease, whose prevalence in Pakistan is more than 60%. Understanding these factors can lead to the development of policies and practices in mitigating the prevalence of dental caries. This review aims to explore different factors which leads to the rise of prevalence of dental caries and helps clinicians of Pakistan to mitigate it. Factors which lead to the development of dental caries are dietary habits, oral hygiene practices, socioeconomic factors, and cultural practices. Keeping in mind such factors, clinicians should provide tailored oral hygiene instructions. This is to ensure comprehensive and effective outcomes for all patients. So apart from addressing the chief complaint of a patient, clinician should focus on preventive dentistry as well. By doing this, rising epidemic of dental caries can be controlled.Key Words: Dental Caries, Dental Clinicians, Epidemic, Pakista

Human Depth Sensors-Based Activity Recognition Using Spatiotemporal Features and Hidden Markov Model for Smart Environments

Nowadays, advancements in depth imaging technologies have made human activity recognition (HAR) reliable without attaching optical markers or any other motion sensors to human body parts. This study presents a depth imaging-based HAR system to monitor and recognize human activities. In this work, we proposed spatiotemporal features approach to detect, track, and recognize human silhouettes using a sequence of RGB-D images. Under our proposed HAR framework, the required procedure includes detection of human depth silhouettes from the raw depth image sequence, removing background noise, and tracking of human silhouettes using frame differentiation constraints of human motion information. These depth silhouettes extract the spatiotemporal features based on depth sequential history, motion identification, optical flow, and joints information. Then, these features are processed by principal component analysis for dimension reduction and better feature representation. Finally, these optimal features are trained and they recognized activity using hidden Markov model. During experimental results, we demonstrate our proposed approach on three challenging depth videos datasets including IM-DailyDepthActivity, MSRAction3D, and MSRDailyActivity3D. All experimental results show the superiority of the proposed approach over the state-of-the-art methods

A Study of the Detection of Defects in Ceramic Insulators Based on Radio Frequency Signatures.

The presence of defects in outdoor insulators ultimately results in the initiation of partial discharge (PD) activity. Because insulation failure and the consequent breakdown of power equipment can occur due to the cumulative adverse effects of partial discharges, it is important to detect PD activity in its early stages. Current techniques used in PD off-line analyses are not suitable for detecting defective insulators in the field. The work presented in this thesis involved the investigation of a number of cases of insulator defects, with the goal of developing an online RF-based PD technique for monitoring ceramic disc insulators that exhibit a variety of defects. The first three classes examined were an intentionally cracked ceramic insulator disc; a disc with a hole through the cap, which creates internal discharges; and a completely broken insulator disc. The fourth class involved an external corona noise using a point-to-plane setup. The defective discs were considered individually and were also incorporated into strings of 2, 3, and 4 insulators as a means of capturing the radiated RF signatures under external high voltage AC power. The captured RF pulses were processed in order to extract statistical, spectral, and wavelet packet based features. Feature reduction and selection is carried out and classification results pertaining to each feature-set type were obtained. To classify the discharges arising from different types of defects, an artificial neural network (ANN) algorithm was applied to the extracted features, and recognition rates of more than 90% were reported for each class. In addition, the position of the defective insulator within the string was varied and high defect classification results exceeding 90% were reported regardless of the position

Obesity and Metabolic Phenotypes (Metabolically Healthy and Unhealthy Variants) Are Significantly Associated with Prevalence of Elevated C-Reactive Protein and Hepatic Steatosis in a Large Healthy Brazilian Population

Background. Among the obese, the so-called metabolically healthy obese (MHO) phenotype is thought to confer a lower CVD risk as compared to obesity with typical associated metabolic changes.The present study aims to determine the relationship of different subtypes of obesity with inflammatory-cardiometabolic abnormalities. Methods. We evaluated 5,519 healthy, Brazilian subjects (43 ± 10 years, 78% males), free of known cardiovascular disease. Those with \u3c2 metabolic risk factors (MRF) were considered metabolically healthy, and thosewith BMI ≥ 25 kg/m2 and/or waist circumference meetingNCEP criteria for metabolic syndrome as overweight/obese (OW). High sensitivity C reactive protein (hsCRP) was measured to assess underlying inflammation and hepatic steatosis (HS) was determined via abdominal ultrasound. Results. Overall, 40% of OWindividuals were metabolically healthy, and 12% normal-weight had ≥2 MRF.The prevalence of elevated CRP (≥3mg/dL) and HS inMHO versus normal weight metabolically healthy group was 22% versus 12%, and 40%versus 8%respectively ( \u3c 0.001). BothMHOindividuals andmetabolically unhealthy normal weight (MUNW) phenotypes were associated with elevated hsCRP and HS. Conclusion. Our study suggests that MHO and MUNW phenotypes may not be benign and physicians should strive to treat individuals in these subgroups to reverse these conditions