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Prediction of static friction at sliding surfaces is having both fundamental and practical importance. In this article, a friction model was used to predict the static friction of wet granular material on hard surface. The model is based on the fact that granular particulates form capillary bridges to adhere with substrate, and rupture of these bridges results in friction. The model also considers the frictional strength of bridges, which develop during the application of shear velocity on sliding mass. The friction model is, in turn, validated with the experimental data of static friction vs. shear velocity of wet granular layers on a smooth rock surface. Scaling laws of frictional properties are also developed using regression analysis to justify the friction model.

Supply chain management in healthcare sector plays significant role in the lives of people. Presence of intermediaries and lack of traceability has lured it towards drug counterfeiting, which reduces drug efficacy, thus hampering patients' trust and putting their lives in danger. Blockchain has emerged as a groundbreaking technology which provide a system that is immutable and transparent without the requirement of a trusted third party. This paper depicts how blockchain can provide a solution to reduce drug counterfeit in the pharmaceutical supply chain. This is achieved by creating a Blockchain Network in which each participant and the drug is registered to maintain transparency of transactions among all the participants. Realtime transfer of ownership in the blockchain creates all-round visibility among the registered participants to retrieve information like the current owner, timestamp of ownership transfer and authenticity of drugs. This paper implements PharmaChain for real-time traceability and trackability information of drugs from end-to-end of the pharmaceutical supply chain.

Blockchain technology has garnered attention from stakeholders in many domains, including healthcare, governance and supply chain management. In the context of healthcare, traceability of pharmaceutical drugs in a transparent yet secure manner can be made faster and efficient with blockchain. This paper presents a blockchain based solution for traceability known as PharmaChain. The traceability is achieved with application design and algorithms which are proposed in the work. The proposed application can be developed using hyperledger fabric deployed on dockers. The chain codes are written in javascript. The pharmaceutical blockchain proposed in this work consists of manufacturer, wholesaler, retailer and consumer. The right for registering a drug into the blockchain is granted to the manufacturers only and the ownership transfer of the drug is stored. This paper highlights the traceability of ownership transfer of the drug and validates its origin.

To investigate the role of “mifepristone” for induction of labor (IOL) in pregnant women with prior cesarean section (CS). In this retrospective study, all pregnant women with prior CS who received oral mifepristone (400 mg) for IOL (as per clear obstetric indications) [group 1] were compared with pregnant women with prior CS who had spontaneous onset of labor (SOL) [group 2], with respect to incidence of vaginal delivery, CS, duration of labor, and various maternal and fetal outcomes. During the study period, 72 women received mifepristone (group 1) for IOL and 346 had SOL (group 2). In group 1 after mifepristone administration, 40 (55.6 %) women had labor onset, and 24 (33.3 %) women had cervical ripening (Bishop Score ≥ 8) within 48 h. There were no statistically significant differences with respect to duration of labor (pvalue: 0.681), mode of delivery (i.e., normal delivery or CS—pvalue: 0.076 or 0.120, respectively), or maternal (blood loss or scar dehiscence/rupture uterus), or fetal outcomes (NICU admission) compared to women with previous CS with SOL (group 2). However, the need of oxytocin (pvalue 0.020) and dose of oxytocin requirement (pvalue 0.008) were more statistically significant in group 1. Mifepristone may be considered as an agent for IOL in women with prior CS.

To estimate the risk of uterine dehiscence/rupture in women with previous cesarean section (CS) by comparing the thickness of lower uterine segment (LUS) and myometrium with trans-abdominal (TAS) and trans-vaginal sonography (TVS). In this case-control study, in 100 pregnant women posted for elective CS (with or without previous CS; group 1 and group 2 respectively), the thickness of LUS and myometrium was measured sonographically (TAS and TVS). Intra-operatively, LUS was graded (grades I–IV), and its thickness was measured with calipers. The primary outcome of the study was correlation between echographic measurements (TAS and TVS) and features of LUS (grades I–IV) at the time of CS. Secondary outcomes were correlation between myometrial thickness, number of previous CS, and inter-delivery interval with LUS (grades I–IV). Sonographic measurements of LUS and myometrium were significantly different between the two groups (both TAS and TVS pvalue = 0.000 each). However, the number of previous CS (p= 0.440) and inter-delivery interval (p= 0.062) had no statistically significant correlation with thickness of LUS. Sonographic evaluation of LUS scar and myometrial thickness (both with TAS and TVS) is a safe, reliable, and non-invasive method for predicting the risk of scar dehiscence/rupture. Specific guidelines for TOLAC, after sonographic assessment of women with previous CS, are need of the hour.