Displaying publications 1 - 20 of 23 in total

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  1. Ghani B, Memon KR, Han H, Ariza-Montes A, Arjona-Fuentes JM
    Front Psychol, 2022;13:918065.
    PMID: 36483719 DOI: 10.3389/fpsyg.2022.918065
    The study intends to investigate the relationship between work stress and job insecurity, as well as technological changes and job insecurity, with job satisfaction acting as a mediator. The study was conducted among Pakistani retail industry employees using survey questionnaires distributed online and in stores. The sample was composed of 262 retail workers from the FMCG and shopping mall industries. The responses were screened using the statistical software tool SPSS, and hypotheses were examined through SMART-PLS. The findings show that work stress has a strong relationship with job insecurity; additionally, the relationship appears to be statistically significant (β = 55.7%, p < 0.05), indicating that there is an increased level of job insecurity if work stress is increased. However, technological advancements showed less influence on job insecurity and had statistically insignificant results (β = 5.9%, p > 0.05). This demonstrates that many technological changes cause high levels of job insecurity because employees fear that they will be unable to cope with the changing environment. Furthermore, the mediating mechanism of job satisfaction was found to be significant, as employees with lower levels of satisfaction reported higher levels of insecurity, aiding in the narrowing of the gap in this section of the study. The study also has practical implications because the results show that the retail industry needs to act quickly to make sure workers do not worry about losing their jobs, especially now that COVID-19 is spreading like wildfire.
  2. Touraine M, Gröhe H, Coffie RG, Sathasivam S, Juan M, Louardi el H, et al.
    Lancet, 2014 Sep 27;384(9949):1161-2.
    PMID: 25242037 DOI: 10.1016/S0140-6736(14)61419-7
  3. Liza S, Ohtake N, Akasaka H, Munoz-Guijosa JM
    Sci Technol Adv Mater, 2015 Jun;16(3):035007.
    PMID: 27877808
    In this work, the thermal stability and the oxidation and tribological behavior of nanoporous a-BC:H films are studied and compared with those in conventional diamond-like carbon (DLC) films. a-BC:H films were deposited by pulsed plasma chemical vapor deposition using B(CH3)3 gas as the boron source. A DLC interlayer was used to prevent the a-BC:H film delamination produced by oxidation. Thermal stability of a-BC:H films, with no delamination signs after annealing at 500 °C for 1 h, is better than that of the DLC films, which completely disappeared under the same conditions. Tribological test results indicate that the a-BC:H films, even with lower nanoindentation hardness than the DLC films, show an excellent boundary oil lubricated behavior, with lower friction coefficient and reduce the wear rate of counter materials than those on the DLC film. The good materials properties such as low modulus of elasticity and the formation of micropores from the original nanopores during boundary regimes explain this better performance. Results show that porous a-BC:H films may be an alternative for segmented DLC films in applications where severe tribological conditions and complex shapes exist, so surface patterning is unfeasible.
  4. Johnson CD, Haldeman S, Chou R, Nordin M, Green BN, Côté P, et al.
    Eur Spine J, 2018 09;27(Suppl 6):925-945.
    PMID: 30151805 DOI: 10.1007/s00586-018-5720-z
    PURPOSE: Spine-related disorders are a leading cause of global disability and are a burden on society and to public health. Currently, there is no comprehensive, evidence-based model of care for spine-related disorders, which includes back and neck pain, deformity, spine injury, neurological conditions, spinal diseases, and pathology, that could be applied in global health care settings. The purposes of this paper are to propose: (1) principles to transform the delivery of spine care; (2) an evidence-based model that could be applied globally; and (3) implementation suggestions.

    METHODS: The Global Spine Care Initiative (GSCI) meetings and literature reviews were synthesized into a seed document and distributed to spine care experts. After three rounds of a modified Delphi process, all participants reached consensus on the final model of care and implementation steps.

    RESULTS: Sixty-six experts representing 24 countries participated. The GSCI model of care has eight core principles: person-centered, people-centered, biopsychosocial, proactive, evidence-based, integrative, collaborative, and self-sustaining. The model of care includes a classification system and care pathway, levels of care, and a focus on the patient's journey. The six steps for implementation are initiation and preparation; assessment of the current situation; planning and designing solutions; implementation; assessment and evaluation of program; and sustain program and scale up.

    CONCLUSION: The GSCI proposes an evidence-based, practical, sustainable, and scalable model of care representing eight core principles with a six-step implementation plan. The aim of this model is to help transform spine care globally, especially in low- and middle-income countries and underserved communities. These slides can be retrieved under Electronic Supplementary Material.

  5. Johnson CD, Haldeman S, Nordin M, Chou R, Côté P, Hurwitz EL, et al.
    Eur Spine J, 2018 09;27(Suppl 6):786-795.
    PMID: 30151808 DOI: 10.1007/s00586-018-5723-9
    PURPOSE: The purpose of this report is to describe the Global Spine Care Initiative (GSCI) contributors, disclosures, and methods for reporting transparency on the development of the recommendations.

    METHODS: World Spine Care convened the GSCI to develop an evidence-based, practical, and sustainable healthcare model for spinal care. The initiative aims to improve the management, prevention, and public health for spine-related disorders worldwide; thus, global representation was essential. A series of meetings established the initiative's mission and goals. Electronic surveys collected contributorship and demographic information, and experiences with spinal conditions to better understand perceptions and potential biases that were contributing to the model of care.

    RESULTS: Sixty-eight clinicians and scientists participated in the deliberations and are authors of one or more of the GSCI articles. Of these experts, 57 reported providing spine care in 34 countries, (i.e., low-, middle-, and high-income countries, as well as underserved communities in high-income countries.) The majority reported personally experiencing or having a close family member with one or more spinal concerns including: spine-related trauma or injury, spinal problems that required emergency or surgical intervention, spinal pain referred from non-spine sources, spinal deformity, spinal pathology or disease, neurological problems, and/or mild, moderate, or severe back or neck pain. There were no substantial reported conflicts of interest.

    CONCLUSION: The GSCI participants have broad professional experience and wide international distribution with no discipline dominating the deliberations. The GSCI believes this set of papers has the potential to inform and improve spine care globally. These slides can be retrieved under Electronic Supplementary Material.

  6. Haldeman S, Johnson CD, Chou R, Nordin M, Côté P, Hurwitz EL, et al.
    Eur Spine J, 2018 09;27(Suppl 6):901-914.
    PMID: 30151811 DOI: 10.1007/s00586-018-5721-y
    PURPOSE: The purpose of this report is to describe the development of an evidence-based care pathway that can be implemented globally.

    METHODS: The Global Spine Care Initiative (GSCI) care pathway development team extracted interventions recommended for the management of spinal disorders from six GSCI articles that synthesized the available evidence from guidelines and relevant literature. Sixty-eight international and interprofessional clinicians and scientists with expertise in spine-related conditions were invited to participate. An iterative consensus process was used.

    RESULTS: After three rounds of review, 46 experts from 16 countries reached consensus for the care pathway that includes five decision steps: awareness, initial triage, provider assessment, interventions (e.g., non-invasive treatment; invasive treatment; psychological and social intervention; prevention and public health; specialty care and interprofessional management), and outcomes. The care pathway can be used to guide the management of patients with any spine-related concern (e.g., back and neck pain, deformity, spinal injury, neurological conditions, pathology, spinal diseases). The pathway is simple and can be incorporated into educational tools, decision-making trees, and electronic medical records.

    CONCLUSION: A care pathway for the management of individuals presenting with spine-related concerns includes evidence-based recommendations to guide health care providers in the management of common spinal disorders. The proposed pathway is person-centered and evidence-based. The acceptability and utility of this care pathway will need to be evaluated in various communities, especially in low- and middle-income countries, with different cultural background and resources. These slides can be retrieved under Electronic Supplementary Material.

  7. Haldeman S, Nordin M, Chou R, Côté P, Hurwitz EL, Johnson CD, et al.
    Eur Spine J, 2018 09;27(Suppl 6):776-785.
    PMID: 30151809 DOI: 10.1007/s00586-018-5722-x
    PURPOSE: Spinal disorders, including back and neck pain, are major causes of disability, economic hardship, and morbidity, especially in underserved communities and low- and middle-income countries. Currently, there is no model of care to address this issue. This paper provides an overview of the papers from the Global Spine Care Initiative (GSCI), which was convened to develop an evidence-based, practical, and sustainable, spinal healthcare model for communities around the world with various levels of resources.

    METHODS: Leading spine clinicians and scientists around the world were invited to participate. The interprofessional, international team consisted of 68 members from 24 countries, representing most disciplines that study or care for patients with spinal symptoms, including family physicians, spine surgeons, rheumatologists, chiropractors, physical therapists, epidemiologists, research methodologists, and other stakeholders.

    RESULTS: Literature reviews on the burden of spinal disorders and six categories of evidence-based interventions for spinal disorders (assessment, public health, psychosocial, noninvasive, invasive, and the management of osteoporosis) were completed. In addition, participants developed a stratification system for surgical intervention, a classification system for spinal disorders, an evidence-based care pathway, and lists of resources and recommendations to implement the GSCI model of care.

    CONCLUSION: The GSCI proposes an evidence-based model that is consistent with recent calls for action to reduce the global burden of spinal disorders. The model requires testing to determine feasibility. If it proves to be implementable, this model holds great promise to reduce the tremendous global burden of spinal disorders. These slides can be retrieved under Electronic Supplementary Material.

  8. Garcia-Martin R, González-Briones A, Corchado JM
    Sensors (Basel), 2019 May 25;19(10).
    PMID: 31130598 DOI: 10.3390/s19102390
    Due to fire protection regulations, a minimum number of fire extinguishers must be available depending on the surface area of each building, industrial establishment or workplace. There is also a set of rules that establish where the fire extinguisher should be placed: always close to the points that are most likely to be affected by a fire and where they are visible and accessible for use. Fire extinguishers are pressure devices, which means that they require maintenance operations that ensure they will function properly in the case of a fire. The purpose of manual and periodic fire extinguisher checks is to verify that their labeling, installation and condition comply with the standards. Security seals, inscriptions, hose and other seals are thoroughly checked. The state of charge (weight and pressure) of the extinguisher, the bottle of propellant gas (if available), and the state of all mechanical parts (nozzle, valves, hose, etc.) are also checked. To ensure greater safety and reduce the economic costs associated with maintaining fire extinguishers, it is necessary to develop a system that allows monitoring of their status. One of the advantages of monitoring fire extinguishers is that it will be possible to understand what external factors affect them (for example, temperature or humidity) and how they do so. For this reason, this article presents a system of soft agents that monitors the state of the extinguishers, collects a history of the state of the extinguisher and environmental factors and sends notifications if any parameter is not within the range of normal values.The results rendered by the SmartFire prototype indicate that its accuracy in calculating pressure changes is equivalent to that of a specific data acquisition system (DAS). The comparative study of the two curves (SmartFire and DAS) shows that the average error between the two curves is negligible: 8% in low pressure measurements (up to 3 bar) and 0.3% in high pressure (above 3 bar).
  9. Campero-Jurado I, Márquez-Sánchez S, Quintanar-Gómez J, Rodríguez S, Corchado JM
    Sensors (Basel), 2020 Nov 01;20(21).
    PMID: 33139608 DOI: 10.3390/s20216241
    Information and communication technologies (ICTs) have contributed to advances in Occupational Health and Safety, improving the security of workers. The use of Personal Protective Equipment (PPE) based on ICTs reduces the risk of accidents in the workplace, thanks to the capacity of the equipment to make decisions on the basis of environmental factors. Paradigms such as the Industrial Internet of Things (IIoT) and Artificial Intelligence (AI) make it possible to generate PPE models feasibly and create devices with more advanced characteristics such as monitoring, sensing the environment and risk detection between others. The working environment is monitored continuously by these models and they notify the employees and their supervisors of any anomalies and threats. This paper presents a smart helmet prototype that monitors the conditions in the workers' environment and performs a near real-time evaluation of risks. The data collected by sensors is sent to an AI-driven platform for analysis. The training dataset consisted of 11,755 samples and 12 different scenarios. As part of this research, a comparative study of the state-of-the-art models of supervised learning is carried out. Moreover, the use of a Deep Convolutional Neural Network (ConvNet/CNN) is proposed for the detection of possible occupational risks. The data are processed to make them suitable for the CNN and the results are compared against a Static Neural Network (NN), Naive Bayes Classifier (NB) and Support Vector Machine (SVM), where the CNN had an accuracy of 92.05% in cross-validation.
  10. Sreeramareddy CT, Rahman M, Harsha Kumar HN, Shah M, Hossain AM, Sayem MA, et al.
    PMID: 25104297 DOI: 10.1186/1472-6947-14-67
    BACKGROUND: To estimate the amount of regret and weights of harm by omission and commission during therapeutic decisions for smear-negative pulmonary Tuberculosis.
    METHODS: An interviewer-administered survey was done among young physicians in India, Pakistan and Bangladesh with a previously used questionnaire. The physicians were asked to estimate probabilities of morbidity and mortality related with disease and treatment and intuitive weights of omission and commission for treatment of suspected pulmonary Tuberculosis. A comparison with weights based on literature data was made.
    RESULTS: A total of 242 physicians completed the interview. Their mean age was 28 years, 158 (65.3%) were males. Median probability (%) of mortality and morbidity of disease was estimated at 65% (inter quartile range [IQR] 50-75) and 20% (IQR 8-30) respectively. Median probability of morbidity and mortality in case of occurrence of side effects was 15% (IQR 10-30) and 8% (IQR 5-20) respectively. Probability of absolute treatment mortality was 0.7% which was nearly eight times higher than 0.09% reported in the literature data. The omission vs. commission harm ratios based on intuitive weights, weights calculated with literature data, weights calculated with intuitive estimates of determinants adjusted without and with regret were 3.0 (1.4-5.0), 16 (11-26), 33 (11-98) and 48 (11-132) respectively. Thresholds based on pure regret and hybrid model (clinicians' intuitive estimates and regret) were 25 (16.7-41.7), and 2(0.75-7.5) respectively but utility-based thresholds for clinicians' estimates and literature data were 2.9 (1-8.3) and 5.9 (3.7-7.7) respectively.
    CONCLUSION: Intuitive weight of harm related to false-negatives was estimated higher than that to false-positives. The mortality related to treatment was eightfold overestimated. Adjusting expected utility thresholds for subjective regret had little effect.
  11. Márquez-Sánchez S, Campero-Jurado I, Herrera-Santos J, Rodríguez S, Corchado JM
    Sensors (Basel), 2021 Jul 07;21(14).
    PMID: 34300392 DOI: 10.3390/s21144652
    It is estimated that we spend one-third of our lives at work. It is therefore vital to adapt traditional equipment and systems used in the working environment to the new technological paradigm so that the industry is connected and, at the same time, workers are as safe and protected as possible. Thanks to Smart Personal Protective Equipment (PPE) and wearable technologies, information about the workers and their environment can be extracted to reduce the rate of accidents and occupational illness, leading to a significant improvement. This article proposes an architecture that employs three pieces of PPE: a helmet, a bracelet and a belt, which process the collected information using artificial intelligence (AI) techniques through edge computing. The proposed system guarantees the workers' safety and integrity through the early prediction and notification of anomalies detected in their environment. Models such as convolutional neural networks, long short-term memory, Gaussian Models were joined by interpreting the information with a graph, where different heuristics were used to weight the outputs as a whole, where finally a support vector machine weighted the votes of the models with an area under the curve of 0.81.
  12. González-Briones A, Chamoso P, Yoe H, Corchado JM
    Sensors (Basel), 2018 Mar 14;18(3).
    PMID: 29538351 DOI: 10.3390/s18030861
    The gradual depletion of energy resources makes it necessary to optimize their use and to reuse them. Although great advances have already been made in optimizing energy generation processes, many of these processes generate energy that inevitably gets wasted. A clear example of this are nuclear, thermal and carbon power plants, which lose a large amount of energy that could otherwise be used for different purposes, such as heating greenhouses. The role of GreenVMAS is to maintain the required temperature level in greenhouses by using the waste energy generated by power plants. It incorporates a case-based reasoning system, virtual organizations and algorithms for data analysis and for efficient interaction with sensors and actuators. The system is context aware and scalable as it incorporates an artificial neural network, this means that it can operate correctly even if the number and characteristics of the greenhouses participating in the case study change. The architecture was evaluated empirically and the results show that the user's energy bill is greatly reduced with the implemented system.
  13. González-Briones A, Prieto J, De La Prieta F, Herrera-Viedma E, Corchado JM
    Sensors (Basel), 2018 Mar 15;18(3).
    PMID: 29543729 DOI: 10.3390/s18030865
    At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC) systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS) deployed in a Cloud environment with a wireless sensor network (WSN) in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN). The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices.
  14. Lopez CA, Castillo LF, Corchado JM
    Sensors (Basel), 2021 Jan 06;21(2).
    PMID: 33418918 DOI: 10.3390/s21020328
    Internet of Things (IoT) should not be seen only as a cost reduction mechanism for manufacturing companies; instead, it should be seen as the basis for transition to a new business model that monetizes the data from an intelligent ecosystem. In this regard, deciphering the operation of the value creation system and finding the balance between the digital strategy and the deployment of technological platforms, are the main motivations behind this research. To achieve the proposed objectives, systems theory has been adopted in the conceptualization stage, later, fuzzy logic has been used to structure a subsystem for the evaluation of input parameters. Subsequently, system dynamics have been used to build a computational representation and later, through dynamic simulation, the model has been adjusted according to iterations and the identified limits of the system. Finally, with the obtained set of results, different value creation and capture behaviors have been identified. The simulation model, based on the conceptualization of the system and the mathematical representation of the value function, allows to establish a frame of reference for the evaluation of the behaviour of IoT ecosystems in the context of the connected home.
  15. Hollister SJ, Lin CY, Lin CY, Schek RD, Taboas JM, Flanagan CL, et al.
    Med J Malaysia, 2004 May;59 Suppl B:131-2.
    PMID: 15468853
  16. Dendooven A, Peetermans H, Helbert M, Nguyen TQ, Marcussen N, Nagata M, et al.
    BMC Nephrol, 2021 05 24;22(1):193.
    PMID: 34030637 DOI: 10.1186/s12882-021-02365-3
    BACKGROUND: Kidney biopsy registries all over the world benefit research, teaching and health policy. Comparison, aggregation and exchange of data is however greatly dependent on how registration and coding of kidney biopsy diagnoses are performed. This paper gives an overview over kidney biopsy registries, explores how these registries code kidney disease and identifies needs for improvement of coding practice.

    METHODS: A literature search was undertaken to identify biopsy registries for medical kidney diseases. These data were supplemented with information from personal contacts and from registry websites. A questionnaire was sent to all identified registries, investigating age of registries, scope, method of coding, possible mapping to international terminologies as well as self-reported problems and suggestions for improvement.

    RESULTS: Sixteen regional or national kidney biopsy registries were identified, of which 11 were older than 10 years. Most registries were located either in Europe (10/16) or in Asia (4/16). Registries most often use a proprietary coding system (12/16). Only a few of these coding systems were mapped to SNOMED CT (1), older SNOMED versions (2) or ERA-EDTA PRD (3). Lack of maintenance and updates of the coding system was the most commonly reported problem.

    CONCLUSIONS: There were large gaps in the global coverage of kidney biopsy registries. Limited use of international coding systems among existing registries hampers interoperability and exchange of data. The study underlines that the use of a common and uniform coding system is necessary to fully realize the potential of kidney biopsy registries.

  17. Yigitcanlar T, Butler L, Windle E, Desouza KC, Mehmood R, Corchado JM
    Sensors (Basel), 2020 May 25;20(10).
    PMID: 32466175 DOI: 10.3390/s20102988
    In recent years, artificial intelligence (AI) has started to manifest itself at an unprecedented pace. With highly sophisticated capabilities, AI has the potential to dramatically change our cities and societies. Despite its growing importance, the urban and social implications of AI are still an understudied area. In order to contribute to the ongoing efforts to address this research gap, this paper introduces the notion of an artificially intelligent city as the potential successor of the popular smart city brand-where the smartness of a city has come to be strongly associated with the use of viable technological solutions, including AI. The study explores whether building artificially intelligent cities can safeguard humanity from natural disasters, pandemics, and other catastrophes. All of the statements in this viewpoint are based on a thorough review of the current status of AI literature, research, developments, trends, and applications. This paper generates insights and identifies prospective research questions by charting the evolution of AI and the potential impacts of the systematic adoption of AI in cities and societies. The generated insights inform urban policymakers, managers, and planners on how to ensure the correct uptake of AI in our cities, and the identified critical questions offer scholars directions for prospective research and development.
  18. Martín DG, Florez SL, González-Briones A, Corchado JM
    Sensors (Basel), 2023 Jan 14;23(2).
    PMID: 36679779 DOI: 10.3390/s23020982
    The revolution generated by the Internet of Things (IoT) has radically changed the world; countless objects with remote sensing, actuation, analysis and sharing capabilities are interconnected over heterogeneous communication networks. Consequently, all of today's devices can connect to the internet and can provide valuable information for decision making. However, the data collected by different devices are in different formats, which makes it necessary to develop a solution that integrates comprehensive semantic tools to represent, integrate and acquire knowledge, which is a major challenge for IoT environments. The proposed solution addresses this challenge by using IoT semantic data to reason about actionable knowledge, combining next-generation semantic technologies and artificial intelligence through a set of cognitive components that enables easy interoperability and integration for both legacy systems and emerging technologies, such as IoT, to generate business value in terms of faster analytics and improved decision making. Thus, combining IoT environments with cognitive artificial intelligence services, COSIBAS builds an abstraction layer between existing platforms for IoT and AI technologies to enable cognitive solutions and increase interoperability across multiple domains. The resulting low-cost cross platform supports scalability and the evolution of large-scale heterogeneous systems and allows the modernization of legacy infrastructures with cognitive tools and communication mechanisms while reusing assets.
  19. Márquez-Sánchez S, Campero-Jurado I, Robles-Camarillo D, Rodríguez S, Corchado-Rodríguez JM
    Sensors (Basel), 2021 May 12;21(10).
    PMID: 34066186 DOI: 10.3390/s21103372
    Wearable technologies are becoming a profitable means of monitoring a person's health state, such as heart rate and physical activity. The use of the smartwatch is becoming consolidated, not only as a novelty but also as a very useful tool for daily use. In addition, other devices, such as helmets or belts, are beneficial for monitoring workers and the early detection of any anomaly. They can provide valuable information, especially in work environments, where they help reduce the rate of accidents and occupational diseases, which makes them powerful Personal Protective Equipment (PPE). The constant monitoring of the worker's health can be done in real-time, through temperature, falls, noise, impacts, or heart rate meters, activating an audible and vibrating alarm when an anomaly is detected. The gathered information is transmitted to a server in charge of collecting and processing it. In the first place, this paper provides an exhaustive review of the state of the art on works related to electronics for human activity behavior. After that, a smart multisensory bracelet, combined with other devices, developed a control platform that can improve operators' security in the working environment. Artificial Intelligence and the Internet of Things (AIoT) bring together the information to improve safety on construction sites, power stations, power lines, etc. Real-time and historic data is used to monitor operators' health and a hybrid system between Gaussian Mixture Model and Human Activity Classification. That is, our contribution is also founded on the use of two machine learning models, one based on unsupervised learning and the other one supervised. Where the GMM gave us a performance of 80%, 85%, 70%, and 80% for the 4 classes classified in real time, the LSTM obtained a result under the confusion matrix of 0.769, 0.892, and 0.921 for the carrying-displacing, falls, and walking-standing activities, respectively. This information was sent in real time through the platform that has been used to analyze and process the data in an alarm system.
  20. Kahrilas PJ, Anastasiou F, Barrett K, Beh L, Chinzon D, Doerfler B, et al.
    Br J Gen Pract, 2024 May;74(742):232-235.
    PMID: 38664044 DOI: 10.3399/bjgp24X737349
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