Fine-scale modeling of failure in an adhesive layer

Rigid ceramic filter media are used for removing particulate matter from gas streams at high temperatures. As the particulate matter (dust cake) collects on the surface of the filter, the filtration pressure increases; to maintain an economical operation the dust cake must be removed periodically by back-pulse cleaning. Often the dust cake is not removed completely by the back-pulse pressure and the resulting patchy cleaning affects operation.;The thesis presents the results from a fine scale modeling of the removal of a layer of filter cake by a time dependent pressure pulse. In this model the filter cake is grid in 16,000 imaginary blocks on a filter, of area 160 cm2. The cleaning of the filter is simulated through 10 consecutive cleaning cycles. The model includes both adhesive forces between the blocks of the filter cake and the filter, as well as cohesive forces between neighboring blocks of filter cake.;The evolution of the cleaning from one cycle to the next is studied. The results show that for each cycle, cohesive forces lower the pressures required for cleaning because they increase the stress near broken adhesive bonds. They also cause thicker cakes to be removed more efficiently. An interesting observation is that there are regions where the filter cake is lifted up but not removed during one cycle; many of these regions are removed during the next cycle. The model enables a detailed quantitative investigation of way this effect depends on the filter cake thickness and the strength of the applied pressure pulse

The quality of Indian diets: A comparison of two indices to predict risk of dietary inadequacies linked to non-communicable diseases

Nutritional inadequacies lead to various health problems among Indians. Improvements in diets can be addressed when different aspects of diet quality are known. The primary objective of the study was to assess diet quality of Indian adults belonging to the high-income group. The study also wanted to compare the suitability of two diet quality indices for use in the Indian scenario. A cross sectional study design with non-probability purposive sampling was used to collect data from 589 adults (20-40 years) in Delhi, India. Nutrient intake was assessed using the 24- hour dietary recall method. Two internationally recognized diet quality indices - Diet Quality Index- International Score (DQI-I) and the Global Diet Quality Score (GDQS) were selected to measure diet quality. 78% of the participants had poor diet quality using the DQI-I; the average score was 56.4 ± 5.6. The average DQI-I component scores for variety, adequacy, moderation and overall balance were 13.1±2.6, 27.5±2.2, 15.3±2.9, 0.43±0.9 respectively. Females were more likely (OR=2.07, 95% C.I.: 1.26 – 3.401) to have DQI-I scores in the lowest quartile (p=0.04). 88% had a moderate risk of nutritional inadequacy while 11% were at a high risk of nutritional inadequacy on the basis of their GDQS scores, the average of which was 16.9±2.1. There was a positive association between GDQS and DQI- I scores (ρ =0.316, p<0.001). The GDQS is better for assessing nutrient adequacy with healthy and unhealthy food consumption being compared. On the other hand, DQI-I gives a composite score combining the nutrient and food group intake and observes variety, adequacy, moderation and overall balance. Behaviour change communication strategies that encourage healthier food selection and promote dietary diversity may help improve nutritional quality of diets in Indian populations such as this one

Data Driven Health &amp; Safety Management: Leveraging Real Time Data Management to Improve Health &amp; Safety Environment on Construction Sites

The construction industry has always been plagued with a high number of accidents and fatalities. The Dutch construction is not an exception in this case and had the highest percentage of workplace accidents among all industries in the national economy, in the year 2019. The high number of accidents and resulting fatalities can be attributed to a plethora of factors. Traditionally, the construction industry has relied on inspections by safety coordinators and supervisors to monitor compliance to the safety regulations by the workers. However, in this manual approach, accuracy of recognizing hazards and making proactive interventions is subject to experience and competency of the supervising personnel and has often proven to be unreliable. Thus, a more objective approach is required to for recognizing hazards and thereby making proactive interventions to prevent accidents.This can only be achieved by analyzing observational data from the construction site in real time. The problem is that with increased use of technology, the sheer volume of data generated by construction projects has surged exponentially. Massive amounts of data are being generated throughout a project’s life cycle but there is a dearth of data management processes which can help construction organizations manage health &amp; safety of workers on construction sites in real time. Thus, this research develops a process map to achieve data driven health &amp; safety management in the construction industry. Various causal factors of accidents in the construction industry and have been identified from literature and co-related with the ones found in archival health &amp; safety data from AECOM Netherlands and opinions of industry experts. The common factors are discerned and later steer the design of the process map. Moreover, type of data, specific data management technologies and best practices to implement these technologies to mitigate the risks, have also been identified. Based on the findings and the researchers’ critical thinking, ten requirement specifications have been formulated. The ten requirement specifications and the identified best practices are then used to design subsets pertaining to the four stages of data management process proposed by Mello et al. (2014), which are data acquisition, data organization, data analytics and data application. Furthermore, an integration framework has been developed, which is used to integrate the individual subsets and develop the final process map. The integrated process map clearly demonstrates checkpoints, placement of data acquisition technologies, data &amp; information flows, actors &amp; responsibilities, to achieve data driven health &amp; safety management on construction sites.The process map is then validated by interviewing experts from construction organizations, which have deployed the innovative technologies used to develop the process map in this research, albeit not in an integrated manner. From the information shared by the experts and their opinions, it has been deduced that the developed process map will secure the construction site against specific risks. Moreover, the developed process is expected to expedite a cultural shift towards a more organized and consistent approach to construction and establish consistency of work environment across an organization’s project portfolio. However, the developed process also has certain shortcomings as well, which in turn may give rise to secondary risks. The findings of this research are not limited to a specific type of construction projects. However, it is more suitable for implementation on large construction projects, in order to realize return on investment. The integrated process is also likely to find suitors in the upstream oil and gas industry, wherein ensuring safety of workers is more complicated. On a holistic level, this research determines that there is immense potential in data acquisition, organization, analytics and application, for the construction industry to exploit. By discerning the primary techniques and real-world solutions, the research establishes the necessary groundwork for the development of a real time health &amp; safety management system, which would help construction organizations in achieving semi-automated management of health and safety conditions on construction sites.Civil Engineering | Construction Management and Engineerin

Intake of ultra-processed food, dietary diversity and the risk of nutritional inadequacy among adults in India

ABSTRACT Objective: This study assessed diet diversity, and consumption of ultra-processed foods and explored its impact on macronutrient intake and risk of micronutrient inadequacy. Design: Cross-sectional, non-probability snowball sampling Setting: Nutrient intake was assessed using 24-hour dietary recall method and diet diversity through FAO-Diet Diversity Score (DDS). Mann-Whitney U test was used to assess differences in risk of inadequacy across gender. Spearman’s Rank correlation assessed associations between energy contributed by ultra-processed food and risk of nutrient inadequacy. Participants: A total of 589 adults (20-40 years) belonging to upper-middle and high-income groups. Results: The average individual DDS was 4.4±0.6. Most participants (>80%) had intakes less than national recommendations of pulses/eggs/flesh foods, milk/milk products, fruits, vegetables, and nuts. Ultra-processed foods contributed to 17% of total energy intake, 12 % of protein, 17% of carbohydrate, 29% of added sugar, 20% of total fat, and 33% of sodium intake. The average risk of nutrient inadequacies for zinc (98% vs 75%), folate (67% vs 22%), and niacin (83% vs 44%) was higher among males than females (p<0.001). The average risk of nutrient inadequacies for iron (58% vs 7%), vitamin B6 (95% vs 90%), and vitamin A (68% vs 44%) was higher among females than males (p<0.001). A positive correlation between energy contributed by ultra-processed food and risk of niacin (ρ =0.136, p=0.001) and folate (ρ =0.089, p=0.049) inadequacy. Conclusion: Reformulating ultra-processed food to reduce fat, sugar, and salt, increase micronutrients and behaviour change communication strategies that promote dietary diversity will improve micronutrient adequacy and diet quality

Effect of Low-level LASER Therapy on P6 Acupoint to Control Gag Reflex in Children: A Clinical Trial

Objective: To investigate the effect of low level laser therapy (LLLT) on PC6 acupuncture point in suppressing gag reflex, regulating pulse rates and oxygen saturation, thereby reducing the anxiety levels. Materials and Method: A total of 40 patients who demonstrated hyperactive gag reflex in the age group of 4-14 years were included in the study. In Group A (20 patients), maxillary impression was recorded. In the second step, PC6 acupuncture point was stimulated with LLLT followed by recording of second maxillary impression. In group B (20 patients), steps were reversed. Gag reflex, anxiety levels, pulse rate and oxygen saturation levels were assessed. Results: Values of pulse rate and oxygen saturation were regulated to normal, signifying lowered anxiety levels. Gag reflex was also significantly decreased after stimulating PC6 acupuncture point with LLLT. Conclusion: LLLT on PC6 point was found to be effective in lowering anxiety levels as observed by faces modified anxiety rating scale. Further, it was authenticated as the pulse rates were significantly reduced and oxygen saturation levels were significantly increased. Also, gag reflex was significantly controlled when LASER stimulation was done at PC6

An Optimization Tool to Formulate Diets within a Supplementary Nutrition Program for Children

Background: In large supplementary feeding programs for children, it is challenging to create and sustain contextual, acceptable, nutritionally complete, and diverse supplemental foods. For example, the Indian Supplementary Nutrition Program (SNP) supplements the dietary intake of children, pregnant and lactating women, and severely acutely malnourished (SAM) children by offering dry take home rations (THRs) or hot cooked meals (HCMs) across India, but an optimization tool is necessary to create local contextual recipes for acceptable and nutritionally adequate products. Objectives: This study aimed to create a linear programming (LP) model to optimize diverse food provisions for a SNP to meet its program guidelines, using locally available foods, within budgetary allocations. Methods: A LP algorithm with appropriate constraints was used to generate an optimal THR based on raw foods, or an optimal weekly HCM menu comprised of a lunch meal with mid-morning snacks, based on user choices of foods and recipes. The database of foods used was created by a prospective survey conducted across all states of India for this purpose, such that the recipe and food optimization was diverse and specific to the guidelines for each beneficiary group. Results: An interactive web-based app, which can optimize feeding programs at any population level, was developed for use by program implementers and is hosted at https://www.datatools.sjri.res.in/SNP/. In the Indian example analyzed here, the recommended optimized diets met the guidelines for diversified and nutritionally complete SNP provision but at a cost that was almost 25% higher than the present Indian budget allocation. Conclusions: The optimization model developed demonstrates that contextual SNP diets can be created to meet macronutrient and most essential micronutrient needs of large-scale feeding programs, but appropriate diversification entails additional costs