scholarly journals Development of an ELISA for Measurement of Urinary 3-Hydroxypropyl Mercapturic Acid (3-HPMA), the Marker of Stroke

2020 ◽  
Vol 8 (3) ◽  
pp. 33
Author(s):  
Akihiko Sakamoto ◽  
Takeshi Uemura ◽  
Yusuke Terui ◽  
Madoka Yoshida ◽  
Kazumasa Fukuda ◽  
...  
Keyword(s):  
Inverse Correlation ◽  
The Elderly ◽  
Mercapturic Acid ◽  
Enzyme Linked Immunosorbent Assay ◽  
Stroke Incidence ◽  
Elisa System ◽  
Brain Stroke ◽  
Cost Efficient ◽  
The Cost

We previously observed an inverse correlation between stroke and urinary 3-hydroxypropyl mercapturic acid (3-HPMA), an acrolein-glutathione metabolite, through its measurement by liquid chromatography with tandem mass spectrometry (LC-MS/MS). However, the cost of equipment for LC-MS/MS and its maintenance fee is very expensive and a cost-efficient method is required. In this study, we have developed a sensitive enzyme-linked immunosorbent assay (ELISA) system to measure 3-HPMA using a chicken antibody recognizing 3-HPMA-conjugated chicken albumin as antigen. Linearity to measure 3-HPMA was obtained from 0 to 10 μM, indicating that this ELISA system is useful for measurement of urine 3-HPMA. It was confirmed that 3-HPMA in urine of stroke patients decreased significantly compared with that of control subjects using the ELISA system. Using the ELISA kit, it became possible to evaluate the risk of brain stroke by not only plasma but also by urine. These results confirm that shortage of glutathione to detoxify acrolein is one of the major causes of stroke incidence. Our method contributes to maintenance of quality of life (QOL) of the elderly.

scholarly journals Associations between self-perceived quality of life and socio-demographic, psychosocial, and health variables in a group of elderly

2013 ◽  
Vol 29 (7) ◽  
pp. 1437-1448 ◽  
Author(s):  
Sérgio Eduardo Silva de Oliveira ◽  
Jean Von Hohendorff ◽  
Juliana de Lima Müller ◽  
Denise Ruschel Bandeira ◽  
Sílvia Helena Koller ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Inverse Correlation ◽  
The Elderly ◽  
Perceived Quality ◽  
Volunteer Work ◽  
Predictive Capacity ◽  
Elderly Individuals ◽  
Perceived Quality Of Life ◽  
Demographic Questionnaire

The objectives of this study were to investigate: (a) multiple relations between socio-demographic, psychosocial, and health variables and quality of life in the elderly and (b) the model's validity through correlation with depressive symptoms. The sample included 339 elderly individuals from 60 to 98 years of age (M = 73.4; SD = 8.3), who answered a socio-demographic questionnaire, WHOQOL-100, and BDI. Cluster analysis of the sample distributed the elders into two groups according to self-perceived quality of life (better versus worse), and logistic regression analysis identified variables that explained better quality of life. Social class, self-rated health status, volunteer work, use of medication, and data collection setting were associated with quality of life (predictive capacity for correct classification 72.3%, specificity 73.6%, and sensitivity 71.1%). The inverse correlation between the model's variables and BDI scores provided evidence of the model's validity. The model can help support public policies aimed at promoting quality of life in the elderly.

scholarly journals Gene Teller: an extensible Alexa Skill for gene-relevant databases

2020 ◽  
Author(s):  
Jon D Hill
Keyword(s):  
Short Term Memory ◽  
Consumer Electronics ◽  
Biological Research ◽  
Short Term ◽  
Conversational Interaction ◽  
Amazon Web Services ◽  
Cost Efficient ◽  
The Cost ◽  
Intuitive Manner

Abstract Summary Voice assistants have become increasingly embedded in consumer electronics, as the quality of their interaction improves and the cost of hardware continues to drop. Despite their ubiquity, these assistants remain underutilized as a means of accessing biological research data. Gene Teller is a voice assistant service based on the Alexa Skills Kit and Amazon Lambda functions that enables scientists to query for gene-centric information in an intuitive manner. It includes several features, such as synonym disambiguation and short-term memory, that enable a natural conversational interaction, and is extensible to include new resources. The underlying architecture, based on Simple Storage Service and Amazon Web Services Lambda, is cost efficient and scalable. Availability and implementation A publicly accessible version of Gene Teller is available as an Alexa Skill from the Amazon Marketplace at https://www.amazon.com/dp/B08BRD8SS8. The source code is freely available on GitHub at https://github.com/solinvicta/geneTeller.

Mobile Edge Computing

2019 ◽  
Vol 10 (3) ◽  
pp. 23-46
Author(s):  
Michael P. J. Mahenge ◽  
Chunlin Li ◽  
Camilius A. Sanga
Keyword(s):  
Mobile Network ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Efficient Design ◽  
Potential Gain ◽  
Backhaul Link ◽  
Task Processing ◽  
Cost Efficient ◽  
The Cost

The overwhelming growth of resource-intensive and latency-sensitive applications trigger challenges in legacy systems of mobile cloud computing (MCC) architecture. Such challenges include congestion in the backhaul link, high latency, inefficient bandwidth usage, insufficient performance, and quality of service (QoS) metrics. The objective of this study was to find out the cost-efficient design that maximizes resource utilization at the edge of the mobile network which in return minimizes the task processing costs. Thus, this study proposes a cooperative mobile edge computing (coopMEC) to address the aforementioned challenges in MCC architecture. Also, in the proposed approach, resource-intensive jobs can be unloaded from users' equipment to MEC layer which is potential for enhancing performance in resource-constrained mobile devices. The simulation results demonstrate the potential gain from the proposed approach in terms of reducing response delay and resource consumption. This, in turn, improves performance, QoS, and guarantees cost-effectiveness in meeting users' demands.

scholarly journals The Effectiveness of the Intervention Depression in the Elderly: A Systematic Review

2020 ◽  
Vol 8 (4) ◽  
pp. 529
Author(s):  
Mei Rianita Elfrida Sinaga
Keyword(s):  
Systematic Review ◽  
The Elderly ◽  
Research Approach ◽  
Correctional Institutions ◽  
Psychological Therapies ◽  
Spiritual Therapies ◽  
Eligible Article ◽  
The Cost ◽  
General Community

The increasing life expectancy in Indonesia has an impact on the amount of attention on the elderly population. Depression is becoming one of the health problems of elderly people in the world. This research approach using systematic review aims to gain a greater understanding about the effectiveness of interventions against depression in the elderly. Methods a systematic review was conducted by searching the literature related to the theme taken, namely “intervention”, “depression”, “elderly”. Literature search using Scient Direct, PubMed, and Google Scholar, from the years 2017-2020, so that the obtained 18 articles eligible. Article quality was evaluated using the CASP checklist The results of the articles obtained came from several countries including Indonesia. These interventions can be grouped into three categories, the first physical therapy/exercise, psychological therapies, and spiritual therapies to lower the level of depression in the elderly in a variety of settings such as in nursing homes, in correctional institutions, and the general community, including home visits, using an individual approach or group. This review helped inform some of the interventions that can be performed on the elderly, it can save the cost, feasible and easy to do, and effective to reduce the level of depression in the elderly, and can improve the quality of life, overcome other psychological problems.

scholarly journals The Importance of the Admissibility of Evidence in Lithuanian Civil Procedure

Teisė ◽  
2021 ◽  
Vol 119 ◽  
pp. 105-117
Author(s):  
Jurgis Bartkus
Keyword(s):  
Civil Procedure ◽  
Efficient Process ◽  
Civil Proceedings ◽  
Cost Efficient ◽  
Evaluation Of Evidence ◽  
The Cost

The article analyses the importance of the admissibility of evidence in Lithuanian civil proceedings. The analysis of various sources of law allows to link the admissibility of evidence in civil proceedings not only with one of the features of evidence, but also with the objectives of this institute in civil proceedings: ensuring the quality of proof, the cost-efficient process, a fair and just trial, and other values.The reduction of the importance of the admissibility of evidence is essentially influenced by aspects related to the whole evidentiary process – the principle of free evaluation of evidence, the purpose of determination of material truth, and procedural norms establishing the judge as the final assessor of admissibility of evidence and facts. The objectives of the admissibility of evidence in civil proceedings make it necessary to find possible solutions that ensure a more appropriate relationship between the admissibility of evidence and the reasons of its importance.

scholarly journals A Study of the Use of Gyroscope Measurements in Wearable Fall Detection Systems

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 649 ◽  
Author(s):  
Eduardo Casilari ◽  
Moisés Álvarez-Marco ◽  
Francisco García-Lagos
Keyword(s):  
Inertial Sensors ◽  
Fall Detection ◽  
The Elderly ◽  
Detection Systems ◽  
Combined Application ◽  
Measurement Units ◽  
Public Dataset ◽  
Cost Efficient ◽  
Wide Group

Due to the serious impact of falls on the quality of life of the elderly and on the economical sustainability of health systems, the study of new monitoring systems capable of automatically alerting about falls has gained much research interest during the last decade. In the field of Human Activity Recognition, Fall Detection Systems (FDSs) can be contemplated as pattern recognition architectures able to discriminate falls from ordinary Activities of Daily Living (ADLs). In this regard, the combined application of cellular communications and wearable devices that integrate inertial sensors offers a cost-efficient solution to track the user mobility almost ubiquitously. Inertial Measurement Units (IMUs) typically utilized for these architectures, embed an accelerometer and a gyroscope. This paper investigates if the use of the angular velocity (captured by the gyroscope) as an input feature of the movement classifier introduces any benefit with respect to the most common case in which the classification decision is uniquely based on the accelerometry signals. For this purpose, the work assesses the performance of a deep learning architecture (a convolutional neural network) which is optimized to differentiate falls from ADLs as a function of the raw data measured by the two inertial sensors (gyroscope and accelerometer). The system is evaluated against on a well-known public dataset with a high number of mobility traces (falls and ADL) measured from the movements of a wide group of experimental users.

Production and Nutritional Quality of Traditional Indian Millet Mixture of Rice, Pearl Millet and Urad Dal

2020 ◽  
Vol 11 (4) ◽  
pp. 5076-5081
Author(s):  
Caroline Jeba R ◽  
Priyanka S ◽  
Priyanka M
Keyword(s):  
Nutritional Value ◽  
Microbial Contamination ◽  
Normal Sample ◽  
Traditional Values ◽  
Nutritional Content ◽  
Microbial Analysis ◽  
Cost Efficient ◽  
The Cost ◽  
Powdered Form

Millet mix was prepared for its traditional values. The prepared sample was analyzed for its chemical and nutritional value, and by using the cost-efficient method, the nutritional content of the final product was enhanced. The improved sample was checked for its nutritional content. The objective is to make a comparison between standard and enhanced samples. ingredients were prepared in a powdered form of a sample in four different ratios. The standardized ratio of the ingredients used to make the samples were found by using tests. In the standardized ratio normal (S1) and nutrition enhanced (S2) samples were prepared using the three ingredients. For nutrition enhancement, the method of sprouting was used. Various tests were conducted for the standardized sample to verify its nutritional content, commercializing ability, microbial analysis, analysis etc. The nutritional content Analysis of the normal and nutrition enhanced samples (S1) and (S2) was done. The sample (S2) was nutritionally rich when compared to the normal sample (S1). All other test had more or less coinciding results for both the samples (S1) and (S2). By comparing the nutritional content, a conclusion arrives that the sample (S2is nutritionally rich when compared to (S1). Microbial and Physical properties results show that the product is efficient to be commercialized and stored to a specific period without microbial contamination in powdered form. The nutrient-rich mass is suitable for all age group.

The Cost Efficiency and Clinical Quality of Institutional Long-Term Care for the Elderly

2005 ◽  
Vol 8 (2) ◽  
pp. 149-156 ◽  
Author(s):  
Juha Laine ◽  
Miika Linna ◽  
Anja Noro ◽  
Unto Häkkinen
Keyword(s):  
Cost Efficiency ◽  
Long Term Care ◽  
The Elderly ◽  
Term Care ◽  
Clinical Quality ◽  
Care For The Elderly ◽  
The Cost

scholarly journals A Survey of Human Activity Recognition in Smart Homes Based on IoT Sensors Algorithms: Taxonomies, Challenges, and Opportunities with Deep Learning

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6037 ◽  
Author(s):  
Damien Bouchabou ◽  
Sao Mai Nguyen ◽  
Christophe Lohr ◽  
Benoit LeDuc ◽  
Ioannis Kanellos
Keyword(s):  
Activity Recognition ◽  
Human Activity ◽  
Smart Home ◽  
Smart Homes ◽  
The Elderly ◽  
Human Activity Recognition ◽  
Challenges And Opportunities ◽  
The Cost ◽  
Home Assistance

Recent advances in Internet of Things (IoT) technologies and the reduction in the cost of sensors have encouraged the development of smart environments, such as smart homes. Smart homes can offer home assistance services to improve the quality of life, autonomy, and health of their residents, especially for the elderly and dependent. To provide such services, a smart home must be able to understand the daily activities of its residents. Techniques for recognizing human activity in smart homes are advancing daily. However, new challenges are emerging every day. In this paper, we present recent algorithms, works, challenges, and taxonomy of the field of human activity recognition in a smart home through ambient sensors. Moreover, since activity recognition in smart homes is a young field, we raise specific problems, as well as missing and needed contributions. However, we also propose directions, research opportunities, and solutions to accelerate advances in this field.

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