scholarly journals Dynamic Handwriting Analysis for Neurodegenerative Disease Assessment: A Literary Review

2019 ◽  
Vol 9 (21) ◽  
pp. 4666 ◽  
Author(s):  
Gennaro Vessio

Studying the effects of neurodegeneration on handwriting has emerged as an interdisciplinary research topic and has attracted considerable interest from psychologists to neuroscientists and from physicians to computer scientists. The complexity of handwriting, in fact, appears to be sensitive to age-related impairments in cognitive functioning; thus, analyzing handwriting in elderly people may facilitate the diagnosis and monitoring of these impairments. A large body of knowledge has been collected in the last thirty years thanks to the advent of new technologies which allow researchers to investigate not only the static characteristics of handwriting but also especially the dynamic aspects of the handwriting process. The present paper aims at providing an overview of the most relevant literature investigating the application of dynamic handwriting analysis in neurodegenerative disease assessment. The focus, in particular, is on Parkinon’s disease (PD) and Alzheimer’s disease (AD), as the two most widespread neurodegenerative disorders. More specifically, the studies taken into account are grouped in accordance with three main research questions: disease insight, disease monitoring, and disease diagnosis. The net result is that dynamic handwriting analysis is a powerful, noninvasive, and low-cost tool for real-time diagnosis and follow-up of PD and AD. In conclusion of the paper, open issues still demanding further research are highlighted.

2020 ◽  
Vol 42 ◽  
pp. e27
Author(s):  
Kelly Kathleen Almeida Heylmann ◽  
Bruno Vasconcellos Lopes ◽  
Carolina Faccio Demarco ◽  
Thays França Afonso ◽  
Tito Roberto Sant'Anna Cadaval Júnior ◽  
...  

The current moment requires the development of new technologies that can provide alternatives to conventional treatment and that efficiently remove pollutants that are difficult to treat. Activated carbon has been highlighted as low cost material that can be used as adsorbents for the removal of contaminants. Thus, the aim of the present study was to analyse the relevant literature related to the production of activated carbon for the treatment of water. For the study, there were found 4,182 relevant studies in the database of the Web of Science and from these restrictions and readings were obtained 27 articles. The information obtained was: i - temporal evolution of publications, ii - distribution of articles by periodicals, iii - spatial distribution, iv - precursor material, v - activation technology, vi - pollutants and vii - treatment efficiency. Results show that the activated carbon produced from corn and industrial ash residues are good adsorbents. Dyes, heavy metals and phenols were the most studied pollutants, and had the higher treatment efficiency values. The approach of the present study allows to identify the main points of this new technology and it helps to support new researches and applications


2019 ◽  
Vol 34 (7) ◽  
pp. 1278-1278
Author(s):  
K Tureson ◽  
A I Gold ◽  
A D Thames

Abstract Objective Large-scale research consortium studies are increasingly used to help aid in early identification of age-related brain changes and neurodegenerative disease risk. Racial/ethnic minorities (REM) are severely underrepresented in publicly available datasets related to neurodegenerative disease. This is problematic given that the US older adult population will be comprised of 40% REM by 2050. As this population grows more diverse, it is crucial that Alzheimer’s disease (AD) risk factors are appropriately characterized and REM are represented in longitudinal research. The purpose of this study was to examine memory, Apolipoprotein E (APOE) status, and hippocampal volume (HV) data among REM participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Participants and Method We sampled 91 Latinx and Non-Hispanic Black (NHB) ADNI participants, which included 41 controls (CN; 39% Latinx) and 50 individuals with mild cognitive impairment (MCI; 52% Latinx). Measures included Logical Memory (LM) Delay, Rey Auditory Verbal Learning Test (RAVLT), Alzheimer’s Disease Assessment Cognitive 13-item Scale (ADAS13), APOE e4 and APOE e2 status, and HV. Groups did not differ by age, education, or memory performance. None of the Latinx sample were e2 carriers, whereas 32% of NHB were e2 carriers. Results For NHB and Latinx MCI groups, LM Delay scores positively predicted greater HV (NHB: R2 = .17, p = .04; Latinx: R2 = .16, p = .04). Better RAVLT performance predicted greater HV for the Latinx MCI group but not for the NHB MCI group (Latinx: R2 = .13, p = .06). For NHB CN, e4 status and ADAS13 were positively correlated (r = .59, p = .002) but negatively correlated for Latinx CN (r = -.58, p = .002). APOE e2 and RAVLT percent forgetting were negatively correlated for NHB MCI (r = -.49, p = .01). Conclusions There appears to be differential risk associated with heterozygous e4 status in Latinx and NHB. APOE e2 may have been protective in the context of e4 in NHB. The degree to which e2 is protective in Latinx is unknown. Results highlight the need for improved REM representation in large-scale studies to understand genetic risk and protective factors in REM.


2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Debby Arisandi

<p>Purpose- In the GSM seluler telephony sector, the main condition for protecting the subscriber base is to win customer to be loyalty, a key necessity for the maintenance of a brand loyalty in the long term. To achieve this aim, service quality must be measured and identified. This paper’s aim is to measure the effects of service quality towards brand loyalty on DTAC seluler service provider. This study will explore the relationship between service quality and brand loyalty in the seluler service industry.</p><p>Design/methodology/approach- The main research target sample covered 200 seluler phone users in Prince of Songka University, Hatyai campus. Field research was conducted. The questionnaire was formed by a synthesis of existing constructs in relevant literature. Reliability tests, descriptive statistic, and regressions analyses were performed to both confirm scale reliability and answer the research questions. The data were analysed by moderated regression analysis to test the hypotheses.</p><p>Findings- The findings of this study show that an overall service quality directly affects brand loyalty. Network quality, customer service, pricing structure and billing system are the service quality dimensions that have significant positive influence on brand loyalty, which in turn has a significant positive impact on brand loyalty 43,5%. Therefore, it plays a crucial role in winning customer loyalty.</p><p>Originality/value- It is of great importance for seluler operators in a mature market such as that of Thailand, to understand what the drivers of brand loyalty are. The present study produced useful findings, which can be utilized by seluler service provider managers, in their effort to develop and implement successful brand loyalty strategies. With respect to the findings, pricing structure has the most importance than others dimensions of service quality which provides positive outcomes on brand loyalty, not only in the present but also in the future. So, the effect of pricing structure on brand loyalty becomes greater than the effect of others dimenstions of service quality. Therefore, any GSM operator who wishes to preserve its existing subscriber base should concentrate on winning its subscribers’ loyalty, especially for DTAC.</p>Keywords- Seluler Services, Brand Loyalty, Service Quality


Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 357
Author(s):  
Pedro Moura ◽  
José Ignacio Moreno ◽  
Gregorio López López ◽  
Manuel Alvarez-Campana

University campuses are normally constituted of large buildings responsible for high energy demand, and are also important as demonstration sites for new technologies and systems. This paper presents the results of achieving energy sustainability in a testbed composed of a set of four buildings that constitute the Telecommunications Engineering School of the Universidad Politécnica de Madrid. In the paper, after characterizing the consumption of university buildings for a complete year, different options to achieve more sustainable use of energy are presented, considering the integration of renewable generation sources, namely photovoltaic generation, and monitoring and controlling electricity demand. To ensure the implementation of the desired monitoring and control, an internet of things (IoT) platform based on wireless sensor network (WSN) infrastructure was designed and installed. Such a platform supports a smart system to control the heating, ventilation, and air conditioning (HVAC) and lighting systems in buildings. Furthermore, the paper presents the developed IoT-based platform, as well as the implemented services. As a result, the paper illustrates how providing old existing buildings with the appropriate technology can contribute to the objective of transforming such buildings into nearly zero-energy buildings (nZEB) at a low cost.


Agriculture ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 651
Author(s):  
Shengyi Zhao ◽  
Yun Peng ◽  
Jizhan Liu ◽  
Shuo Wu

Crop disease diagnosis is of great significance to crop yield and agricultural production. Deep learning methods have become the main research direction to solve the diagnosis of crop diseases. This paper proposed a deep convolutional neural network that integrates an attention mechanism, which can better adapt to the diagnosis of a variety of tomato leaf diseases. The network structure mainly includes residual blocks and attention extraction modules. The model can accurately extract complex features of various diseases. Extensive comparative experiment results show that the proposed model achieves the average identification accuracy of 96.81% on the tomato leaf diseases dataset. It proves that the model has significant advantages in terms of network complexity and real-time performance compared with other models. Moreover, through the model comparison experiment on the grape leaf diseases public dataset, the proposed model also achieves better results, and the average identification accuracy of 99.24%. It is certified that add the attention module can more accurately extract the complex features of a variety of diseases and has fewer parameters. The proposed model provides a high-performance solution for crop diagnosis under the real agricultural environment.


Micromachines ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 882
Author(s):  
M. Munzer Alseed ◽  
Hamzah Syed ◽  
Mehmet Cengiz Onbasli ◽  
Ali K. Yetisen ◽  
Savas Tasoglu

Civil wars produce immense humanitarian crises, causing millions of individuals to seek refuge in other countries. The rate of disease prevalence has inclined among the refugees, increasing the cost of healthcare. Complex medical conditions and high numbers of patients at healthcare centers overwhelm the healthcare system and delay diagnosis and treatment. Point-of-care (PoC) testing can provide efficient solutions to high equipment cost, late diagnosis, and low accessibility of healthcare services. However, the development of PoC devices in developing countries is challenged by several barriers. Such PoC devices may not be adopted due to prejudices about new technologies and the need for special training to use some of these devices. Here, we investigated the concerns of end users regarding PoC devices by surveying healthcare workers and doctors. The tendency to adopt PoC device changes is based on demographic factors such as work sector, education, and technology experience. The most apparent concern about PoC devices was issues regarding low accuracy, according to the surveyed clinicians.


2021 ◽  
Author(s):  
Daniel Hörcher ◽  
Ramandeep Singh ◽  
Daniel J. Graham

AbstractDense urban areas are especially hardly hit by the Covid-19 crisis due to the limited availability of public transport, one of the most efficient means of mass mobility. In light of the Covid-19 pandemic, public transport operators are experiencing steep declines in demand and fare revenues due to the perceived risk of infection within vehicles and other facilities. The purpose of this paper is to explore the possibilities of implementing social distancing in public transport in line with epidemiological advice. Social distancing requires effective demand management to keep vehicle occupancy rates under a predefined threshold, both spatially and temporally. We review the literature of five demand management methods enabled by new information and ticketing technologies: (i) inflow control with queueing, (ii) time and space dependent pricing, (iii) capacity reservation with advance booking, (iv) slot auctioning, and (v) tradeable travel permit schemes. Thus the paper collects the relevant literature into a single point of reference, and provides interpretation from the viewpoint of practical applicability during and after the pandemic.


2020 ◽  
Vol 10 (1) ◽  
pp. 2 ◽  
Author(s):  
Soroush Ojagh ◽  
Sara Saeedi ◽  
Steve H. L. Liang

With the wide availability of low-cost proximity sensors, a large body of research focuses on digital person-to-person contact tracing applications that use proximity sensors. In most contact tracing applications, the impact of SARS-CoV-2 spread through touching contaminated surfaces in enclosed places is overlooked. This study is focused on tracing human contact within indoor places using the open OGC IndoorGML standard. This paper proposes a graph-based data model that considers the semantics of indoor locations, time, and users’ contexts in a hierarchical structure. The functionality of the proposed data model is evaluated for a COVID-19 contact tracing application with scalable system architecture. Indoor trajectory preprocessing is enabled by spatial topology to detect and remove semantically invalid real-world trajectory points. Results show that 91.18% percent of semantically invalid indoor trajectory data points are filtered out. Moreover, indoor trajectory data analysis is innovatively empowered by semantic user contexts (e.g., disinfecting activities) extracted from user profiles. In an enhanced contact tracing scenario, considering the disinfecting activities and sequential order of visiting common places outperformed contact tracing results by filtering out unnecessary potential contacts by 44.98 percent. However, the average execution time of person-to-place contact tracing is increased by 58.3%.


Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mi Tang ◽  
Hongmei Zhou ◽  
Qingyan Yan ◽  
Ruoyu Li ◽  
Hui Lu

PurposeHealthcare employs informatics to offer its services through information technology where the social network can aid virtual medical learning. Since the usage of the internet and other electronic tools for medical services delivery is at the initial stage, it is essential to examine the factors that condition patients and medical elements in a virtual environment can develop relationship models on the health services. So, the authors have systematically reviewed virtual medical learning and offered some suggestions for the upcoming works. The authors have also discovered gaps in the state-of-the-art papers and provided solutions for them.Design/methodology/approachNumerous novel advancements have changed the old exercise of therapeutic and analytic learning. Virtual spaces have quickly turned into a section of the learning technology vision. Given the importance of its achievements and endless low-cost expansion of the educational system, virtual education has been considered as one of the issues raised by the information communities. Medicine and health are some of the most important fields in virtual technologies. Hence, in this paper, we have used a systematic literature review to deeply examine virtual medical learning. After establishing exclusion and inclusion criteria, an independent systematic search in Google Scholar, ACM, Scopus, Eric, Science Direct, Springer link, Emerald, Global ProQuest and IEEE for relevant studies have been performed, and 21 papers have been analyzed. Detailed data have been mined out of the papers.FindingsThe authors have found that virtual medical learning improves and expands the knowledge core and meaningfully affects the exercise. Virtual learning (VL) has been used in many therapeutic zones, like therapeutic learning, surgery, diagnosing, combining and regularizing processes. It has presented a fundamental access point and a referral mechanism for all of a course's component communities. It can also simplify communicative education, allowing learners to get abilities before applying them in a real-world situation. Also, the communicative characteristics of different VL programs can somehow be like direct teaching.Research limitations/implicationsSome excellent work may be removed owing to applying the filters to select the primary papers. Surveying all the documents on the topic of virtual medical learning is impossible, too. Nevertheless, the authors have tried to present a perfect survey of virtual medical learning. The results will be helpful for scholars to propose better virtual medical learning techniques.Practical implicationsE-learning has become an indispensable additional learning tool in medical education. The introduction of new learning technologies, the exponential growth of Internet usage and the advent of the World Wide Web can change the face of higher education. The results will be helpful for scholars for the upcoming works. The application of a literature review of partial least squares theory was useful for offering comprehensive literary coverage and completing the knowledge development analysis. The authors have backed scholars and experts for better understanding the development of virtual medical learning systems via presenting comparative data and scrutinizing the present advances.Originality/valueThe paper enhances intellectual knowledge by improving the conception of virtual medical learning. It informs the development, use of virtual medical learning and the upcoming works. The lack of comprehensive papers in this field has increased the importance of this paper. The present paper can handle the pace of publications.


2021 ◽  
Author(s):  
David Unnersjoe-Jess ◽  
Amer Ramdedovic ◽  
Martin Hoehne ◽  
Linus Butt ◽  
Felix C Koehler ◽  
...  

Diseases of the glomeruli, the renal filtration units, are a leading cause of progressive kidney disease. Assessment of the ultrastructure of podocytes at the glomerular filtration barrier is essential for diagnosing diverse disease entities, providing insight into the disease pathogenesis as well as monitoring treatment responses. New technologies, including super-resolved nanoscopy and expansion microscopy, as well as new sample preparation techniques, are starting to revolutionize imaging of biopsy specimens. However, our previous approaches for simple and fast three-dimensional imaging of optically cleared samples are to date not compatible with formalin fixed paraffin-embedded (FFPE) tissue, impeding application in clinical routine. Here we provide protocols that circumvent these limitations and allow for three dimensional STED and confocal imaging of FFPE kidney tissue with similar staining and image quality as compared to our previous approaches. This would increase the feasibility to implement these protocols in clinical routines, as FFPE is the gold standard method for storage of patient samples.


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