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ABSTRACT: Background: The postpartum period is critically important for comprehensive obstetric care; however, most women are neglected during this important period. Objective: This study was carried out to determine the burden of postpartum morbidities and associated factors among the urban vulnerable population in Gautam Buddha district, Uttar Pradesh. Methods: A cross-sectional study was conducted among 150 postpartum women in urban slums of Gautam Buddha district. A semi-structured questionnaire was used along with a physical examination and assessment of anemia by Sahli's hemoglobinometer. Results: A total of 106 (70.7%) mothers reported at least one of the postpartum morbidities (PPMs). The most frequently reported morbidity was anemia (55.3%) followed by backache (29.3%). Almost a third (39, 36.8%) of all women, who suffered from PPM, did not seek any treatment for the same. Univariate analysis revealed that morbidities were higher among women with low literacy (Odds Ratio, OR: 5.63, 95% CI: 2.508–13.54, p = 0.000), low socioeconomic status (OR: 0.317, 95% CI: 0.151–0.657, p = 0.002), and inadequate antenatal care (OR: 0.108, 95% CI: 0.044–0.246, p = 0.0001). Similarly, young mothers (OR: 2.599, 95% CI: 1.332–5.14), less educated (OR = 3.603, 95% CI: 1.838–7.203, p = 0.000), those from lower economic status (OR: 0.247, 95% CI: 0.119–0.497, p = 0.001), with inadequate antenatal care (OR: 0.112, 95% CI: 0.052–0.232, p = 0.005), and low iron folic acid intake (OR: 0.371, 95% CI: 0.184–0.732, p = 0.004) showed higher prevalence of anemia. Conclusion: The role of education and adequate antenatal care are highlighted in the study. Antenatal visits should be utilized as opportunities to increase awareness regarding various aspects of care during the postnatal period. Maintaining more comprehensive support and involvement between health care providers and the mothers is needed to prevent many of these postpartum morbidities. [ABSTRACT FROM AUTHOR]

Background: Substance abuse is an important problem in today's world as it causes considerable physical and mental suffering. In India, adolescents are considered as a pillar of the nation as they are responsible for its future progress. Therefore, substance abuse control among this age group becomes even more important. Objectives: To find the prevalence, patterns and gender association of substance abuse among adolescents in urban areas of district Ghaziabad. Methods: A cross-sectional study was conducted in the schools of urban areas of district Ghaziabad. 750 adolescents including equal number of boys and girls were selected randomly from the co-education schools. A questionnaire was administered to assess the baseline information. MS Excel 2020 and SPSS were used to arrive at statistical conclusions. Results: Addicting substance was abused by 64.8% males and 33.9% females and this difference in proportions was statistically significant (p-value =0.001). The maximum number of study participants got encouragement to start the usage of addictive substances from their peers (33.0%). Four-fifths (80.3%), of the substance abusers had the desire to quit. Conclusion: In the present study, 33% of the participants started abusing addictive substances under peer pressure. School-based awareness, health education and motivation among the adolescents is the need of the hour. Role of student counsellors may prove fruitful and bring about the desired behavioural change. [ABSTRACT FROM AUTHOR]

Background: A novel coronavirus was identified in Wuhan, China in December 2019. The pandemic brought all people closer to internet to access information about the disease and its prevention. However, this intention of gaining knowledge is a spinal reaction to an adverse situation and once that has passed, the same knowledge and practices decline. Aims and Objectives: The aim of the study was to assess the apprehension regarding COVID-19 along with its demographic correlates in the post-pandemic era. Methodology: A cross-sectional study was conducted in district Ghaziabad using a predesigned, pre-tested and semi-structured questionnaire regarding the awareness and knowledge levels of COVID-19. Regression analysis was performed to determine the factors significantly associated with the knowledge of the study participants. Results: In this study, 277 (69.25%) were males and 123(30.75%) were females. The mean knowledge score was 25.09 ± 6.85 (range 4-41). Knowledge regarding various aspects of COVID-19 was better among the study participants with higher education levels. Conclusion: Even after the pandemic had passed, good knowledge levels were retained. Participants had a huge disparity in the individual levels of information. Overall higher levels of education, younger age group and nuclear family were associated with better knowledge regarding the disease. [ABSTRACT FROM AUTHOR]

Summary: The internet of things (IoT) has recently become extremely important in our lives. With the advancement in IoT, wireless sensor networks (WSNs) have gained much importance. In WSNs, the routing of clusters has gained more interest. However, there is still a problem with the hotspot. One way to address this issue is uneven clustering. In these, nodes closer to the base station have the smallest cluster size. It decreases the relay pressure of the nodes which are close to the base station. In this paper, the unequal clustering routing based on fuzzy logic and bat algorithm is proposed, that is, FUCBR. Relative intra‐cluster costs and relative inter‐cluster costs are used in a very innovative manner. Fuzzy logic is used to create unequal clusters while the bat algorithm is used for multi‐hop routing. Unequal clustering minimizes the energy utilization for the member of the clusters. A novel probability technique is implemented in the cluster‐forming process to allow cluster members to determine which cluster they wish to join. The bat algorithm's objective function is carefully chosen to optimize the cluster heads' energy usage. After simulation, it was discovered that the proposed algorithm utilizes less energy and extends the network lifespan. The simulation results show that FUCBR's performance is 30% more improved than fuzzy‐based unequal clustering algorithm, genetic algorithm based unequal clustering and routing protocol, and grey wolf optimizer‐C algorithms. It is suitable for networks that require a long life. [ABSTRACT FROM AUTHOR]

Background: COVID-19 pandemic started in India on 30th January 2020. A nationwide lockdown was enforced from 24th March onwards, and most citizens were confined to their homes causing many psychosocial problems. Objective: To find the prevalence of depression and its associated factors during COVID-19 pandemic. Methods: A community based crosssectional study, conducted among the adult population of urban Ghaziabad, Uttar Pradesh, India. Information was collected using a predesigned questionnaire with a sample size of 396 consenting individuals. Results: Of the 396 participants, 99 (25%) had depression; with mild, moderate, and severe depression found in 20.45%, 3.53% and 1% individuals, respectively. Females were affected more than males (32.1% vs 18.2%). Prevalence of depression was 50% among individuals living alone, 34.7% among unemployed people, and 30% among individuals whose income was reduced during the lockdown period. Individuals who were quarantined due to positive/suspected COVID-19 infection had a 45.5% prevalence of depression. Individuals who were divorced or separated, had an increased prevalence of depression [OR 9.2, (95% CI 1.2-73.7)]. People who practiced meditation during the lockdown period had lesser prevalence of depression [OR 2.87, (95% CI 1.1- 7.7)] than those who did not. Conclusion: The COVID-19 pandemic has had a major psycho-social impact on people. The findings from this study can help identify vulnerable individuals and prevent and/or reduce the morbidity of depression in future, both in India and other parts of the world. [ABSTRACT FROM AUTHOR]

Summary: Wireless sensor networks (WSN) encompasses millions of nodes that work jointly, senses environmental information, and transmits to the Base Station (BS). "Energy hole" or "hot‐spot" is a problem in which sensor nodes near to the BS deceasetoo early which creates the partitioning of the network. This is due to the reason of the difference in the consumption of energy by the nodes in WSN which reduces the lifespan of the sensor network. The distribution of the cluster heads and the load balancing are the major pitfalls. In this paper to deal with the statedpitfalls, a hybrid of fuzzy logic technique and harmony search algorithm is proposed to lengthen the lifetime of the network. Unequal clustering is a technique proposed by the researchers to handle the hot‐spot issue, hence it is also included. The proposed algorithm forms unequal clusters. To prove the efficiency of the proposed algorithm, some well‐known unequal clustering algorithms and harmony search based algorithmare used to compare the proposed algorithm under different network settings. In all the settings, better performance is achieved by the proposed protocol. It prolongs the lifespan of the network as compared to the different algorithms proposed so far. [ABSTRACT FROM AUTHOR]