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178 results for “Verbalization”
Data from: Causes of and contributors to infant mortality in a rural community of North India: evidence from verbal and social autopsy
Objective: Retrospective analysis of routinely collected data using verbal and social autopsy tools to identify the medical causes of death and contribution of non-biological factors towards infant mortality Setting: The study site was Health and Demographic Surveillance System (HDSS), Ballabgarh, North India Participants: All infant deaths during year 2008 to 2012 were included for verbal autopsy whereas infant deaths from July 2012 to December 2012 were included for social autopsy. Outcome measures: Cause of death ascertained by validated verbal autopsy tool and level of delay based on three delay model using INDEPTH social autopsy tool were the main outcome measures. Results: Infant mortality rate during study period was 46.5/100 live births. Neonatal deaths contributed to 54.3% of infant deaths and 39% occurred on first day of life. Birth asphyxia (31.5%) followed by Low Birth Weight (LBW)/prematurity (26.5%) were the most common causes of neonatal death. While infective cause (57.8) was the most common cause of post-neonatal death. Care-seeking was delayed among 50% of neonatal deaths and 41.2% of post-neonatal deaths. Delay at level 1 was most common, observed in 32.4% of neonatal deaths and 29.4% of post-neonatal deaths. Deaths due to LBW/prematurity were mostly followed by delay at level 1. Conclusion: High proportion of preventable infant mortality still exists in an area which is under continuous health and demographic surveillance. There is need to enhance home based preventive care to enable the mother to identify and respond to danger signs. Verbal autopsy and social autopsy could be routinely done to guide policy interventions aimed at reduction of infant mortality.
VERBALIZERS OF HAPPINESS AND UNHAPPINESS IN SUBJECT REPRESENTATION (FRAME AND SLOT ANALYSIS)
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RECESSIVE AND UNIQUE ASPECTS OF VERBALIZERS OF THE CONCEPT OF "COMPARISON".
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SOME PROBLEMS OF THE VERBALIZERS OF CONCEPT OF "MAN" IN MODERN LINGUISTICS
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INTELLECTUAL FORMATION OF VERBAL ASSOCIATIONS IN CHILDREN WITH APHOTIC DISORDERS
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VERBALIZATION OF THE CONCEPT OF "SIN" IN ENGLISH DISCOURSE
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INTERACTIVE METHODS FOR TEACHING THE ENGLISH VERBALIZERS OF THE LINGUOCULTURAL CONCEPT OF "TIME" AT UZBEK HIGH SCHOOLS
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FEATURES OF UKRAINIAN STUDENTS` VERBAL REPRESENTATION OF THE GENDER INEQUALITY`S CONCEPT
<p>The study aimed to determine Ukrainian students' verbal representation of the gender inequality's concept. Verbal representations were obtained based on the use of a directed associative experiment. The study involved 309 students (199 females and 110 males) from 17 to 25 years. Gender analysis showed: women provided 539 reactions, including 530 verbal (176 originals) reactions and nine rejections; men provided 319 reactions: 310 verbal reactions (103 original) and nine rejections. The most frequent reactions to the stimulus “gender inequality" were revealed: жінка / woman (10,6%), чоловік / man (9,4%), фемінізм / feminism (4,3%), несправедливість / injustice (3,7%), права / rights (2,9%), нерівність / inequality (2,8%), стать / gender (2,7%), сексизм / sexism (2,4%), дискримінація / discrimination (2,3%), насильство / violence (2%). It was determined that the concept of "gender inequality" has a negative connotation among Ukrainian students. Cognitive interpretation of the data showed that the concept has a more negative emotional connotation for women than for men. For a significant number of women, gender inequality includes experiences associated with sexism, discrimination, and violence. Analysis of male associations has shown that men's concept has a less emotional response and is presented at a more abstract (theoretical) level.</p>
СOMPARATIVE ANALYSIS OF THE VERBALIZERS OF THE LINGUOCULTURAL CONCEPT OF "TIME" IN ENGLISH AND UZBEK
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THE TYPOLOGY OF LINGUISTIC AND CULTURAL TYPES OF VERBALIZERS OBJECTIFYING THE CONCEPT OF "COMPARISON" IN MULTI-SYSTEM LANGUAGES.
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EXPRESSION OF THE ODOR CONCEPT THROUGH VERBAL MEANS
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The Online Motivations and Adjustment Mechanisms of "Verbal Aphasiacs" from the Perspective of CMM Theory
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A Free Verbalization Method of Evaluating Sound Design: The Effectiveness of Artificially Intelligent Natural Language Processing Methods and Tools
<p>"Robot" voice sound files. Seventeen sound files were recorded in four formats; raw human voiceover (VO), and three types of robot voice: vocoded voice 1 (“robo”), vocoded voice 2 with music (“kbd”), and a “beep” voice. Each was recorded as 44.1kHz, 24-bit wav files in a professional recording studio. VO was recorded by professional voice actor DB Cooper, who has been the robot voice for several video games, as well as the voice of the DEE BMW internal car AI voice system. Cooper recorded three versions of the emotes on a Sennheiser MKH-416. Professional sound designer pdx Drescher, an expert in robot<br> and interface sound design, created three sets of robot voices from<br> the original voice files. With guidance from one of the authors,<br> pdx was tasked with trying different approaches to turning the VO<br> samples into three different types of robot voice while attempting<br> to maintain the meaning of the original sounds as described in the<br> list above through preserving the prosody/melodic contour of the<br> original. The first set, robo, used some clips from one of pdx’s prior<br> robot voice projects and integrated them to approximate the emo-<br> tional intention of the VO. Clips were re-pitched, manipulated, and<br> modulated using ProTools plugins. For the kbd takes, VO sounds<br> were played into a Shure SM58 microphone. Vocoder patches mod-<br> ified the signal by voice formants, and the pitch was determined<br> by MIDI notes and pitch-bend controllers. Output of the synthe-<br> sizer was then edited with additional synth patches and effects (EQ,<br> modulation, etc.). We made particular use of a plugin called Envy<br> by Cargo Cult, which takes the volume, pitch, and EQ envelopes of<br> one sound (the original VO) and apply them to another sound. This<br> helped make the synth resemble the prosody of the original sound<br> to some degree. The beep sounds underwent a similar development<br> process as the robo takes, but with interface “bleeps and bloops”<br> derived from various sound effects libraries, including the Star Trek<br> LCARS soundset.</p> <p>The following sounds were recorded: 1. Warning calm (“Uh-oh”) 2. Warning alarm (“ah!”) 3. Wrong/<br> error (“rrrrr”) 4. Correct/good (“yay”) 5. Surprise (neutral) (“Oh!”) 6.<br> Surprise (good) (“Oh!”) 7. Surprise (bad) “(ohhh”) 8. Love/adoration<br> (“awww”) 9. Disgust (“ew”) 10. Contempt (“ech”) 11. Guilt (“hmmm”)<br> 12. Confused (“huh?”) 13. Laugh (“ha ha”) 14. Calculating (“hmmm”)<br> 15. Sigh 16. Giggle 17. Pain (“ow ")</p>
Natural Treatments for the Management of Emotional Dysregulation in Youth With Non-verbal Learning Disability (NVLD) and/or Autism Spectrum Disorders (ASD)
ClinicalTrials.gov study NCT03757585. IPD Sharing: NO. Countries: 1. Publications: 0.
Treating Verbal Memory Deficits Following Chemotherapy for Breast Cancer
ClinicalTrials.gov study NCT03017560. IPD Sharing: NO. Countries: 0. Publications: 14.
Individualized Repetitive Transcranial Magnetic Stimulation for Auditory Verbal Hallucinations
ClinicalTrials.gov study NCT05319080. IPD Sharing: NO. Countries: 1. Publications: 0.
The Effects of Hydromorphone on Responses to Verbal Tasks
ClinicalTrials.gov study NCT02205983. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Boost rTMS for Auditory Verbal Hallucinations
ClinicalTrials.gov study NCT03544333. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Effects of Buprenorphine on Responses to Verbal Tasks
ClinicalTrials.gov study NCT01860287. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Verbal Autopsy of Maternal Deaths, Stillbirths, and Neonatal Deaths in BetterBirth
ClinicalTrials.gov study NCT03213509. IPD Sharing: YES. Countries: 1. Publications: 0.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.