Internet of Things Based Smart Health Monitoring of Industrial Standard Motors

The Industry 4.0 vision provides recommendations how companies can ease the challenges.  In an industrial environment, it is beneficial to  have a predictive approach to make smart industry using IoT. The Predictive approach includes automating the maintenance activities of machines which help to deliver safety, performance, customer experience, capacity, cost efficiency and sustainability of the key business assets.  It helps to improve work force safety which reduces the need to access the infrastructure, develop technologies to enable activities to be remotely controlled from safe areas and automate processes to remove manual tasks and helps to increase infrastructure reliability.  It also improves the precision and accuracy of data collection, introducing data analytics, removing human bias, improving reproducibility.  This will improve information about asset condition, inform inspection and repair schedules based  on asset risks. By implementing predictive and preventive maintenance, one can improve equipment life and avoid any unplanned maintenance activity and thus reducing unscheduled downtime.  We in this work have an unit which could be easily attached to the motor units and this does not demand any wiring to carried out. The sensor monitor signals from the motor, accurately measuring key parameters at regular interval of time, as desired.  And, the data is sent to the cloud, which in our case is adafruit.  From there, the data is analysed and it produces meaningful information. The  server then sends alert message to the users about critical data of machine.   This will help in fixing any technical issue with ease without incurring much delay

Computing fuzzy rough approximations in large scale information systems

Rough set theory is a popular and powerful machine learning tool. It is especially suitable for dealing with information systems that exhibit inconsistencies, i.e. objects that have the same values for the conditional attributes but a different value for the decision attribute. In line with the emerging granular computing paradigm, rough set theory groups objects together based on the indiscernibility of their attribute values. Fuzzy rough set theory extends rough set theory to data with continuous attributes, and detects degrees of inconsistency in the data. Key to this is turning the indiscernibility relation into a gradual relation, acknowledging that objects can be similar to a certain extent. In very large datasets with millions of objects, computing the gradual indiscernibility relation (or in other words, the soft granules) is very demanding, both in terms of runtime and in terms of memory. It is however required for the computation of the lower and upper approximations of concepts in the fuzzy rough set analysis pipeline. Current non-distributed implementations in R are limited by memory capacity. For example, we found that a state of the art non-distributed implementation in R could not handle 30,000 rows and 10 attributes on a node with 62GB of memory. This is clearly insufficient to scale fuzzy rough set analysis to massive datasets. In this paper we present a parallel and distributed solution based on Message Passing Interface (MPI) to compute fuzzy rough approximations in very large information systems. Our results show that our parallel approach scales with problem size to information systems with millions of objects. To the best of our knowledge, no other parallel and distributed solutions have been proposed so far in the literature for this problem

Consultant-led UK paediatric palliative care services: Professional configuration, services, funding

Objectives: To systematically gather information on the professional team members, services provided, funding sources and population served for all consultant-led specialised paediatric palliative care (SPPC) teams in the UK. Methods: Two-part online survey. Results: Survey 1: All 17 medical leads from hospital-based or hospice-based SPPC teams responded to the survey (100% response rate). Only six services met the NICE guidance for minimum SPPC team. All services reported providing symptom management, specialist nursing care, end-of-life planning and care, and supporting discharges and transfers to home or hospice for the child's final days-hours. Most services also provided care coordination (n=14), bereavement support (n=13), clinical psychology (n=10) and social work-welfare support (n=9). Thirteen had one or more posts partially or fully funded by a charity. Survey 2: Nine finance leads provided detailed resource/funding information, finding a range of statutory and charity funding sources. Only one of the National Health Service (NHS)-based services fully funded by the NHS. Conclusions: One-third of services met the minimum criteria of professional team as defined by NICE. Most services relied on charity funding to fund part or all of one professional post and only one NHS-based service received all its funding directly from the NHS

Lower dietary intake of plant protein is associated with genetic risk of diabetes-related traits in urban Asian Indian adults

The increasing prevalence of type 2 diabetes among South Asians is caused by a complex interplay between environmental and genetic factors. We aimed to examine the impact of dietary and genetic factors on metabolic traits in 1062 Asian Indians. Dietary assessment was performed using a validated semi-quantitative food frequency questionnaire. Seven single nucleotide polymorphisms (SNPs) from the Transcription factor 7-like 2 and fat mass and obesity-associated genes were used to construct two metabolic genetic risk scores (GRS): 7-SNP and 3-SNP GRSs. Both 7-SNP GRS and 3-SNP GRS were associated with a higher risk of T2D (p = 0.0000134 and 0.008, respectively). The 3-SNP GRS was associated with higher waist circumference (p = 0.010), fasting plasma glucose (FPG) (p = 0.002) and glycated haemoglobin (HbA1c) (p = 0.000066). There were significant interactions between 3-SNP GRS and protein intake (% of total energy intake) on FPG (Pinteraction = 0.011) and HbA1c (Pinteraction = 0.007), where among individuals with lower plant protein intake (1 risk allele had higher FPG (p = 0.001) and HbA1c (p = 0.00006) than individuals with ≤1 risk allele. Our findings suggest that lower plant protein intake may be a contributor to the increased ethnic susceptibility to diabetes described in Asian Indians. Randomised clinical trials with increased plant protein in the diets of this population are needed to see whether the reduction of diabetes risk occurs in individuals with prediabetes

A ferritin-based COVID-19 nanoparticle vaccine that elicits robust, durable, broad-spectrum neutralizing antisera in non-human primates

While the rapid development of COVID-19 vaccines has been a scientific triumph, the need remains for a globally available vaccine that provides longer-lasting immunity against present and future SARS-CoV-2 variants of concern (VOCs). Here, we describe DCFHP, a ferritin-based, protein-nanoparticle vaccine candidate that, when formulated with aluminum hydroxide as the sole adjuvant (DCFHP-alum), elicits potent and durable neutralizing antisera in non-human primates against known VOCs, including Omicron BQ.1, as well as against SARS-CoV-1. Following a booster ~one year after the initial immunization, DCFHP-alum elicits a robust anamnestic response. To enable global accessibility, we generated a cell line that can enable production of thousands of vaccine doses per liter of cell culture and show that DCFHP-alum maintains potency for at least 14 days at temperatures exceeding standard room temperature. DCFHP-alum has potential as a once-yearly (or less frequent) booster vaccine, and as a primary vaccine for pediatric use including in infants

End of life care for infants, children and young people (ENHANCE): Protocol for a mixed methods evaluation of current practice in the United Kingdom [version 1; peer review: 2 approved]

Background: Although child mortality has decreased over the last few decades, around 4,500 infants and children die in the UK every year, many of whom require palliative care. There is, however, little evidence on paediatric end-of-life care services. The current National Institute for Health and Care Excellence (NICE) guidance provides recommendations about what should be offered, but these are based on low quality evidence. The ENHANCE study aims to identify and investigate the different models of existing end-of-life care provision for infants, children, and young people in the UK, including an assessment of the outcomes and experiences for children and parents, and the cost implications to families and healthcare providers. Methods: This mixed methods study will use three linked workstreams and a cross-cutting health economics theme to examine end-of-life care models in three exemplar clinical settings: infant, children and young adult cancer services (PTCs), paediatric intensive care units (PICUs), and neonatal units (NNUs). Workstream 1 (WS1) will survey current practice in each setting and will result in an outline of the different models of care used. WS2 is a qualitative comparison of the experiences of staff, parents and patients across the different models identified. WS3 is a quantitative assessment of the outcomes, resource use and costs across the different models identified. Discussion: Results from this study will contribute to an understanding of how end-of-life care can provide the greatest benefit for children at the end of their lives. It will also allow us to understand the likely benefits of additional funding in end-of-life care in terms of patient outcomes

End of life care for infants, children and young people (ENHANCE) : Protocol for a mixed methods evaluation of current practice in the United Kingdom

Background: Although child mortality has decreased over the last few decades, around 4,500 infants and children die in the UK every year, many of whom require palliative care. There is, however, little evidence on paediatric end-of-life care services. The current National Institute for Health and Care Excellence (NICE) guidance provides recommendations about what should be offered, but these are based on low quality evidence. The ENHANCE study aims to identify and investigate the different models of existing end-of-life care provision for infants, children, and young people in the UK, including an assessment of the outcomes and experiences for children and parents, and the cost implications to families and healthcare providers. Methods: This mixed methods study will use three linked workstreams and a cross-cutting health economics theme to examine end-of-life care models in three exemplar clinical settings: infant, children and young adult cancer services (PTCs), paediatric intensive care units (PICUs), and neonatal units (NNUs). Workstream 1 (WS1) will survey current practice in each setting and will result in an outline of the different models of care used. WS2 is a qualitative comparison of the experiences of staff, parents and patients across the different models identified. WS3 is a quantitative assessment of the outcomes, resource use and costs across the different models identified. Discussion: Results from this study will contribute to an understanding of how end-of-life care can provide the greatest benefit for children at the end of their lives. It will also allow us to understand the likely benefits of additional funding in end-of-life care in terms of patient outcomes

Mediastinal lymphadenopathy – A case report

In our day-to-day practice, as a pulmonologist, the mediastinal lymphadenopathy is a common finding, the cause of which is difficult to diagnose. Although in endemic countries like India, tuberculosis is the common cause, there are also other causes which are associated with it. Therefore, it is important to get a tissue diagnosis before we arrive at a conclusion

Preparation, nutritional and glycemic properties of multigrain instant “adai” mix

Background and Objectives: “Adai” is a traditional South Indian breakfast prepared using the wet ground batter of white rice and pulses. Convenience foods are gaining popularity and owing to the increasing prevalence of noncommunicable diseases such as diabetes, there is a need for food products with lower glycemic index (GI). The current study aimed to develop an instant adai mix using brown rice, millets, pulses, and spices. Materials and Methods: The instant adai mix was prepared by blending pulverized brown rice, sorghum, and pulses (green gram, horse gram, decorticated and split red gram, black gram, and chickpea) along with roasted cumin, red chilies, and salt. The nutritional composition of the instant adai mix was analyzed, and GI of “adai” was evaluated in healthy human volunteers using International organization for standardization protocol. Results: The instant adai mix was rich in whole grains (48%) and pulses (45%). Nutritional profiling of the instant adai mix revealed that it is rich in protein and dietary fiber. One hundred grams of instant adai mix fulfill 27.8% of protein and 29.6% of dietary fiber requirements of recommended dietary allowance of adult male. Likewise, 100 g of instant adai mix fulfill 34.9% of protein requirements of the estimated average requirement of an adult male. The “adai” prepared from the instant mix exhibited medium GI (65.1). Conclusion: The instant “adai” mix was found to be nutritionally superior, and the adai prepared from the mix showed a medium GI. It can be a healthy option compared with instant mixes containing refined grains such as white rice. More formulation trials are needed to prepare an adai mix to achieve a low GI. Reformulation of traditional foods with nutritious ingredients and achieving a lower GI can expand the healthier food choices for this vulnerable population who are at risk for type 2 diabetes

Data from: Using public surveys to reliably and rapidly estimate the distributions of multiple invasive species on the Andaman archipelago

To effectively manage multiple biological invasions, information on their distributions must be generated rapidly and over large spatial scales. Using public surveys in a false-positive occupancy framework, we reliably estimate the distributions of three synanthropic invasive species on the Andaman Islands