The Experts below are selected from a list of 57 Experts worldwide ranked by ideXlab platform

Mohamad Sadikin - One of the best experts on this subject based on the ideXlab platform.

  • the role of Autosuggestion in geriatric patients quality of life a study on psycho neuro endocrine immunology pathway
    Social Neuroscience, 2017
    Co-Authors: Nina Kemala Sari, Siti Setiati, Akmal Taher, Martina Wiwie, Samsuridjal Djauzi, Jacub Pandelaki, Jan Sudir Purba, Mohamad Sadikin
    Abstract:

    ABSTRACTBackground: There has been no study conducted about the effect of Autosuggestion on quality of life for geriatric patients. Our aim was to evaluate the efficacy of Autosuggestion for geriatric patients’ quality of life and its impact on psycho-neuro-endocrine-immune pathway.Methods: Sixty geriatric patients aged ≥60 years in a ward were randomly assigned to either receive Autosuggestion or not. Autosuggestion was recorded in a tape to be heard daily for 30 days. Both groups received the standard medical therapy. Primary outcome was quality of life by COOP chart. Secondary outcomes were serum cortisol level, interleukin-2, interleukin-6, interferon-γ, and N-acetylaspartate/creatine ratio in limbic/paralimbic system by magnetic resonance spectroscopy. The study was single blinded due to the nature of the intervention studied.Results: Out of 60 subjects, 51 finished the study. The Autosuggestion group reported better scores than the control one for quality of life, COOP chart 1.95 vs. 2.22 (95% CI, p...

Chris Winder - One of the best experts on this subject based on the ideXlab platform.

  • mechanisms of multiple chemical sensitivity
    Toxicology Letters, 2002
    Co-Authors: Chris Winder
    Abstract:

    Abstract Sensitivity to chemicals is a toxicological concept, contained in the dose–response relationship. Sensitivity also includes the concept of hypersensitivity, although controversy surrounds the nature of effects from very low exposures. The term multiple chemical sensitivity has been used to describe individuals with a debilitating, multi-organ sensitivity following chemical exposures. Many aspects of this condition extend the nature of sensitivity to low levels of exposure to chemicals, and is a designation with medical, immunological, neuropsychological and toxicological perspectives. The basis of MCS is still to be identified, although a large number of hypersensitivity, immunological, psychological, neurological and toxicological mechanisms have been suggested, including: allergy; Autosuggestion; cacosomia; conditioned response; immunological; impairment of biochemical pathways involved in energy production; impairment of neurochemical pathways; illness belief system; limbic kindling; olfactory threshold sensitivity; panic disorder; psychosomatic condition; malingering; neurogenic inflammation; overload of biotransformation pathways (also linked with free radical production); psychological or psychiatric illness; airway reactivity; sensitisation of the neurological system; time dependent sensitisation, toxicant induced loss of tolerance. Most of these theories tend to break down into concepts involving: (1) disruption in immunological/allergy processes; (2) alteration in nervous system function; (3) changes in biochemical or biotransformation capacity; (4) changes in psychological/neurobehavioural function. Research into the possible mechanisms of MCS is far from complete. However, a number of promising avenues of investigation indicate that the possibility of alteration of the sensitivity of nervous system cells (neurogenic inflammation, limbic kindling, cacosomia, neurogenic switching) are a possible mechanism for MCS.

Michael Golebiewski - One of the best experts on this subject based on the ideXlab platform.

  • on the social and technical challenges of web search Autosuggestion moderation
    arXiv: Computers and Society, 2020
    Co-Authors: Timothy J Hazen, Alexandra Olteanu, Gabriella Kazai, Fernando Diaz, Michael Golebiewski
    Abstract:

    Past research shows that users benefit from systems that support them in their writing and exploration tasks. The Autosuggestion feature of Web search engines is an example of such a system: It helps users in formulating their queries by offering a list of suggestions as they type. Autosuggestions are typically generated by machine learning (ML) systems trained on a corpus of search logs and document representations. Such automated methods can become prone to issues that result in problematic suggestions that are biased, racist, sexist or in other ways inappropriate. While current search engines have become increasingly proficient at suppressing such problematic suggestions, there are still persistent issues that remain. In this paper, we reflect on past efforts and on why certain issues still linger by covering explored solutions along a prototypical pipeline for identifying, detecting, and addressing problematic Autosuggestions. To showcase their complexity, we discuss several dimensions of problematic suggestions, difficult issues along the pipeline, and why our discussion applies to the increasing number of applications beyond web search that implement similar textual suggestion features. By outlining persistent social and technical challenges in moderating web search suggestions, we provide a renewed call for action.

Golebiewski Michael - One of the best experts on this subject based on the ideXlab platform.

  • On the Social and Technical Challenges of Web Search Autosuggestion Moderation
    2020
    Co-Authors: Hazen, Timothy J., Olteanu Alexandra, Kazai Gabriella, Diaz Fernando, Golebiewski Michael
    Abstract:

    Past research shows that users benefit from systems that support them in their writing and exploration tasks. The Autosuggestion feature of Web search engines is an example of such a system: It helps users in formulating their queries by offering a list of suggestions as they type. Autosuggestions are typically generated by machine learning (ML) systems trained on a corpus of search logs and document representations. Such automated methods can become prone to issues that result in problematic suggestions that are biased, racist, sexist or in other ways inappropriate. While current search engines have become increasingly proficient at suppressing such problematic suggestions, there are still persistent issues that remain. In this paper, we reflect on past efforts and on why certain issues still linger by covering explored solutions along a prototypical pipeline for identifying, detecting, and addressing problematic Autosuggestions. To showcase their complexity, we discuss several dimensions of problematic suggestions, difficult issues along the pipeline, and why our discussion applies to the increasing number of applications beyond web search that implement similar textual suggestion features. By outlining persistent social and technical challenges in moderating web search suggestions, we provide a renewed call for action.Comment: 17 Pages, 4 images displayed within 3 latex figure

M Shilpa - One of the best experts on this subject based on the ideXlab platform.

  • effects of meditation compared with effects of meditation with Autosuggestion on cardiovascular variables and autonomic functions an analytical study
    National Journal of Physiology Pharmacy and Pharmacology, 2020
    Co-Authors: M Shilpa, Tejaswini K S, R Raghunandana, K Narayana, Shilpa Marigowda
    Abstract:

    Background: Primordial prevention of hypertension is a public health concern. Health benefits of meditation in reducing blood pressure (BP) are well documented by various studies. However, effects of Autosuggestion a form of self-hypnosis are not much studied. Aim and Objective: Our study intends to know the effects of meditation and added Autosuggestion on cardiovascular variables and autonomic functions. Materials and Methods: About 60 students aged 17–20 years were selected and divided into two groups randomly. Group A was made to practice meditation and Group B meditation with Autosuggestion for 3 months. Physiological parameters such as heart rate, BP, postural changes in BP, and R-R interval were recorded before and after 3 months of practice. Results: We found a statistically significant change in both groups in all the physiological parameters after the practice of meditation and also with practice of meditation with Autosuggestion. The group that practiced meditation with Autosuggestion showed a greater effect on postural changes in BP. Conclusion: These observations suggest that meditation helps to improve the cardiovascular efficiency and homeostatic control of the body, meditation with Autosuggestion has an added benefit.

  • influence of meditation with Autosuggestion on respiratory parameters as compared with meditation alone
    2015
    Co-Authors: K S Tejaswini, M Shilpa
    Abstract:

    Meditation has profound effects on psychology and physiology. However less is known about the effect of Autosuggestion on physiological parameters. So the objective of this study is to assess the effect of meditation alone and the added effects of Autosuggestion to meditation and to compare the effects of the two on respiratory parameters. The respiratory parameters like RR, TV, FVC, FEV1 and FEV1% were recorded by computerised Spirometer in 60 medical students of age group 16 to 20years, who were divided into two equal teams to be trained on meditation and meditation with Autosuggestion. Results showed significant decrease (p<0.001) in RR in both the groups after the training session. There was a significant increase in TV, FVC, FEV1 and FEV1% in both groups, but no significant differential increase between the groups, though meditation with Autosuggestion had greater increase of all above compared to only meditation group. From the above results it was concluded that meditation can bring significant improvement in respiratory performance and wellbeing.