IoT Based Fish Food Dispenser

Internet of things and Automation are two eyes that change the view of industries perspective. Automation happens in every part of the stage in day to day life. The problem statement chosen in this paper was identified during COVID pandemic situation. The problem statement was to feed the fish food into fish aquarium at work place during COVID pandemic. In order to maintain the fish tank properly it should be monitored and maintained at regular interval is necessary. During pandemic situation felt difficult in proper maintenance and feeding the fish. To overcome the difficulties, we have proposed a model to feed the food for fish. In this paper we have solved the problem by using Internet of Things, servo motor, Arduino and interfaced through Massachusetts institute of Technology (MIT) App inventor to control the device at any part of the world. © 2023 IEEE.

CoVacciDrone: An Algorithmic-Drone-Based COVID-19 Vaccine Distribution Strategy

The COVID-19 pandemic has turned out to be one of the worst disasters that mankind has ever faced. This pandemic has disturbed the homeostasis of the entire globe. Various degrees of lockdowns are being implemented worldwide to prepare the healthcare infrastructure of the country as well as to sensitize people. The new mutations in the genome of the virus are possessing a greater threat in triggering the future waves of the pandemic. Adhering to strict usage of masks, highest standards of hand hygiene, practicing social distancing and vaccination are the only weapons to battle the pandemic. Governments are rolling the vaccination plans worldwide. There are various strategies to improve the vaccination status of a country. There is a dire need for a robust, efficient delivery system for the effective transportation of the COVID-19 vaccines. This chapter proposes distribution methods for CoVacciDrone, a smart-drone-based delivery system of COVID-19 vaccines. This would enable transport of the COVID-19 vaccine to even the remotest locations of the country. Deployment of such smart systems would improve the vaccination status of the nation. This would propel the vaccination drive, which would be imperative in avoiding future waves of the COVID-19 pandemic. © 2023 selection and editorial matter, Saravanan Krishnan and M. Murugappan;individual chapters, the contributors.

Comparison of effect of two different trigger regimens;single (hCG) versus dual (hCG + Leuprolide) on outcome of fresh IVF cycles: A randomized controlled trial

Study question Does adding gonadotropin-releasing hormone agonist (GnRHa) to hCG trigger increases the number of high-grade embryos in GnRH antagonist protocol in fresh non-donor IVF? Summary answer Final oocyte maturation triggered by dual trigger increases the number of MII oocytes thus transferring good-quality embryos and cryopreserving surplus embryos compared to hCG trigger. What is known already hCG has been conventionally used as a ‘faux’ LH surge to bring about final oocyte maturation due to structural similarity between the two. GnRH agonist, on the other hand, induces a more physiological gonadotropin surge for follicular maturation, but is associated with luteal phase deficiency. Recent studies have shown that combining GnRHa with hCG trigger improves oocyte maturation and embryo quality with the added benefit of a luteal phase support, thereby improving IVF outcomes in terms of both embryological and reproductive outcomes. Study design, size, duration A single-center, open labelled, randomized controlled trial including 100 normal responder patients between 21-38 years undergoing IVF using GnRH antagonist protocol between January 2020 to August 2021. The study excluded patients with the presence of other variables of adverse outcomes like diminished ovarian reserve (AFC < 5 or AMH < 1.2 ng/ml), endocrine disorders, thin endometrium (<6mm), previous history of uterine surgeries, and high responders. Participants/materials, setting, methods 100 patients undergoing fresh IVF cycle using GnRH antagonist protocol were randomized after informed consent to receive either dual trigger (Leuprolide acetate 1 mg + rhCG 250 mcg, n = 50) or single hCG trigger (rhCG 250 mcg, n = 50). Oocyte retrieval was done 35-37 hours after trigger followed by IVF/ICSI, as indicated. Oocyte and embryo grading was done using Istanbul consensus. Analysis was done by ITT. Outcomes were analyzed using Independent t-test and Chi-square test. Main results and the role of chance The baseline characteristics were comparable in both arms. the number of MII oocytes retrieved (7.82 versus 5.92, p = 0.003) and the number of day-3 grade-1 embryos (4.24 versus 1.8, p < 0.001) were higher in the dual trigger group, whereas fertilization rates between the two groups (91.82% versus 88.51%, p=NS) were comparable. Consequently, the number of embryos cryopreserved (2.68 versus 0.94, p < 0.001) were significantly higher in the dual trigger group. However, the implantation rate between the two groups (21% versus 19.6%, p = 0.770) was comparable. The serum LH levels 12 hours post trigger were measured in both the arms and as expected, high serum LH values were documented in the dual trigger group (46.23 mIU/ml vs 0.93 mIU/ml, p < 0.0001). Limitations, reasons for caution Due to the impact of the Covid-19 pandemic causing an intermittent pause in IVF services at our center, a smaller sample size of 100 patients could be enrolled in the study, and reproductive outcomes in terms of live births and cumulative live births could not be assessed Wider implications of the findings This study, though small, has contributed to some evidence of redesigning the dual trigger in all antagonist cycles, with the exception of high responders and PCOS patients. The addition of GnRHa to hCG trigger has led to the possibility of cryopreserving surplus embryos thereby increasing the cumulative live births. Trial registration number CTRI/2020/08/027030

Teleconsultations for rheumatic diseases during CoVID-19 pandemic: Usefulness, patient response and prospects for future practice

Background/Purpose: Teleconsultations have been an important means of communicating with the patients due to the travel restrictions during the COVID-19 pandemic. We assessed its usefulness and patients' views on their future use. Methods: Patients who received teleconsultations using telephone and WhatsApp during the COVID-19 pandemic were screened and asked to fill an online questionnaire seeking their views regarding teleconsultations in terms of their usefulness, cost-effectiveness, feasibility for future use. Only those patients were included who were of age ≥18 years and had had at least 2 physical visits in the past at our hospital. Information regarding their demographic features, disease characteristics like diagnosis, duration of disease was also collected. For the final analysis, 230 responses out of the 410 participants were included for who all the desired information was available. Results: Among the 230 patients, mean age was 38 years with a mean duration of disease of 4.25 years, 68 (29%) were male, 190 (83%) had rheumatoid arthritis, 100 (43%) patients assessed their disease condition as bad/severe and 90 (39%) depended on others to use a smartphone for teleconsultations. Among these patients, 131 (57%) patients missed their scheduled OPD appointment, 115 (50%) reported worsening of symptoms, 81 (35%) needed to consult a local physician for their problems. Regarding teleconsultations, 142 (62%) patients reported benefit with the teleconsultation service and 181 (79%) graded it ≥3 on a scale of 1-5 where 5 meant very useful (Figure 1). A total of 161 (70%) patients wanted to use it for future consultations. The commonest reasons for choosing teleconsultation were ease of appointment (52%), avoiding the need of travelling (22%) and cost-effectiveness (22%). Conclusions: Teleconsultation is a useful alternative to physical consultation with a high satisfaction rate. It could be a useful costeffective tool in a resource limited setting of developing countries like India.

Challenges in the practice of traditional kolam among indian women in the Klang Valley, Malaysia

Kolam or floor drawing is an important element of the Indian cultural heritage and an integral part of the Indian traditions. This floor art is mainly performed by women from the Indian diaspora in Malaysia. The aim of this study is to highlight the challenges the Indian women encounter in practicing the traditional Kolam in the Klang Valley, Malaysia. A purposive sampling technique was used to collect data online. The questionnaire prepared was validated by Kolam experts. An online questionnaire was used because of the current COVID-19 pandemic where face-to-face survey is not feasible. The online questionnaire received 203 responses. This study employed the quantitative methodology using the SPSS software and tested with the Cronbach’s alpha tool. The result show that Malaysian Indian women faced challenges of difficult to draw, time constraints, lack of interest, materials preparation and limited space in drawing Kolam during festivals. These challenges have an impact and have posed a serious threat for the survival and maintenance of the form of traditional Kolam. Preserving traditional Kolam will give future generations the opportunity to enhance further their knowledge of traditional Kolam drawing. © 2021

A Transfer Learning Model for COVID-19 Detection with Computed Tomography and Sonogram Images

The community spread of COVID-19 has almost touched the corners of the world. So it is very essential to step towards the much earlier diagnosis of COVID-19 infection. In general, early stage diagnosis techniques mainly consider Chest X-Rays, Computed Tomography and Ultrasound videos as well as frames. Visually identifying and examining these clinical images in case of any hidden abnormalities seems to be a challenging and also time consuming task, wherein a huge amount of information needs to be processed in a limited time period given. The concept of Transfer Learning on medical imaging is currently emerging and shows a lot of research potential in terms of dealing with scarce medical images. Here, we proposed a Transfer Learning model and keras model for CT images and a separate transfer learning model for ultrasound images. As a result, the CT Transfer learning framework outperforms the CT based keras Baseline model with an ascend accuracy from 76% to 82.2%. Furthermore, our Ultrasound based Transfer learning model almost tied with an accuracy of 89% as a good performing solution. © 2021 IEEE.