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Heliyon May 2024Emotion recognition technology through EEG signal analysis is currently a fundamental concept in artificial intelligence. This recognition has major practical... (Review)
Review
Emotion recognition technology through EEG signal analysis is currently a fundamental concept in artificial intelligence. This recognition has major practical implications in emotional health care, human-computer interaction, and so on. This paper provides a comprehensive study of different methods for extracting electroencephalography (EEG) features for emotion recognition from four different perspectives, including time domain features, frequency domain features, time-frequency features, and nonlinear features. We summarize the current pattern recognition methods adopted in most related works, and with the rapid development of deep learning (DL) attracting the attention of researchers in this field, we pay more attention to deep learning-based studies and analyse the characteristics, advantages, disadvantages, and applicable scenarios. Finally, the current challenges and future development directions in this field were summarized. This paper can help novice researchers in this field gain a systematic understanding of the current status of emotion recognition research based on EEG signals and provide ideas for subsequent related research.
PubMed: 38818173
DOI: 10.1016/j.heliyon.2024.e31485 -
Scientific Reports May 2024Post-traumatic stress disorder (PTSD) lacks clear biomarkers in clinical practice. Language as a potential diagnostic biomarker for PTSD is investigated in this study....
Post-traumatic stress disorder (PTSD) lacks clear biomarkers in clinical practice. Language as a potential diagnostic biomarker for PTSD is investigated in this study. We analyze an original cohort of 148 individuals exposed to the November 13, 2015, terrorist attacks in Paris. The interviews, conducted 5-11 months after the event, include individuals from similar socioeconomic backgrounds exposed to the same incident, responding to identical questions and using uniform PTSD measures. Using this dataset to collect nuanced insights that might be clinically relevant, we propose a three-step interdisciplinary methodology that integrates expertise from psychiatry, linguistics, and the Natural Language Processing (NLP) community to examine the relationship between language and PTSD. The first step assesses a clinical psychiatrist's ability to diagnose PTSD using interview transcription alone. The second step uses statistical analysis and machine learning models to create language features based on psycholinguistic hypotheses and evaluate their predictive strength. The third step is the application of a hypothesis-free deep learning approach to the classification of PTSD in our cohort. Results show that the clinical psychiatrist achieved a diagnosis of PTSD with an AUC of 0.72. This is comparable to a gold standard questionnaire (Area Under Curve (AUC) ≈ 0.80). The machine learning model achieved a diagnostic AUC of 0.69. The deep learning approach achieved an AUC of 0.64. An examination of model error informs our discussion. Importantly, the study controls for confounding factors, establishes associations between language and DSM-5 subsymptoms, and integrates automated methods with qualitative analysis. This study provides a direct and methodologically robust description of the relationship between PTSD and language. Our work lays the groundwork for advancing early and accurate diagnosis and using linguistic markers to assess the effectiveness of pharmacological treatments and psychotherapies.
Topics: Stress Disorders, Post-Traumatic; Humans; Deep Learning; Male; Machine Learning; Female; Adult; Language; Natural Language Processing; Biomarkers; Middle Aged
PubMed: 38816468
DOI: 10.1038/s41598-024-61557-7 -
Heliyon May 2024This study aims to explore the effect of eco-innovation and renewable energy on carbon dioxide emissions (CDE) for G7 countries. Using regression models, the results...
This study aims to explore the effect of eco-innovation and renewable energy on carbon dioxide emissions (CDE) for G7 countries. Using regression models, the results reveal that eco-innovation and renewable energy lead to reducing CDE in the presence of governance variables. Additional analysis is conducted to examine whether Hofstede national culture dimensions moderate the nexus of "eco-innovation- carbon emission" and "renewable energy-carbon emission". The results show that individualism, long-term orientation, and indulgence dimensions moderate positively the eco-innovation-carbon emission relationship. Moreover, power distance and uncertainty avoidance dimensions moderate the relationship between renewable energy and CDE and help reduce carbon emissions. The outcomes of this study provide new insights and directives for policymakers and regulators. In fact, increased investment in eco-innovation and renewable energy will support the environmental agenda of G7 countries. National cultural dimensions should be taken into consideration to improve awareness of environmental quality. Moreover, the combination of governance indicators plays a key role in environmental sustainability.
PubMed: 38813154
DOI: 10.1016/j.heliyon.2024.e31142 -
Evaluation and Program Planning Aug 2024Enhancing data sharing, quality, and use across siloed HIV and STI programs is critical for national and global initiatives to reduce new HIV infections and improve the...
Enhancing data sharing, quality, and use across siloed HIV and STI programs is critical for national and global initiatives to reduce new HIV infections and improve the health of people with HIV. As part of the Enhancing Linkage of STI and HIV Surveillance Data in the Ryan White HIV/AIDS Program initiative, four health departments (HDs) in the U.S. received technical assistance to better share and link their HIV and STI surveillance data. The process used to develop evaluation measures assessing implementation and outcomes of linking HIV and STI data systems involved six steps: 1) measure selection and development, 2) review and refinement, 3) testing, 4) implementation and data collection, 5) data quality review and feedback, and 6) dissemination. Findings from pilot testing warranted slight adaptations, including starting with a core set of measures and progressively scaling up. Early findings showed improvements in data quality over time. Lessons learned included identifying and engaging key stakeholders early; developing resources to assist HDs; and considering measure development as iterative processes requiring periodic review and reassessment to ensure continued utility. These findings can guide programs and evaluations, especially those linking data across multiple systems, in developing measures to track implementation and outcomes over time.
Topics: Humans; HIV Infections; Program Evaluation; Sexually Transmitted Diseases; Information Dissemination; United States; Population Surveillance; Data Accuracy; Data Collection
PubMed: 38810523
DOI: 10.1016/j.evalprogplan.2024.102435 -
AANA Journal Oct 2023Simulation is an integral part of the healthcare educational landscape and a key element in the future of graduate professional education. For the past three decades,...
Simulation is an integral part of the healthcare educational landscape and a key element in the future of graduate professional education. For the past three decades, simulation-based educational methodology has been gaining popularity in nurse anesthesia educational programs (NAEP). There is currently limited objective evidence documenting modalities used or educational outcomes addressed through simulation in NAEPs. In 2018, the American Association of Nurse Anesthesiology (AANA) established a Simulation Subcommittee of the AANA Education Committee and tasked the group with two primary goals: 1) to gain a better understanding of the current state of simulation education and 2) to review responses with regard to how NAEPs could best incorporate simulation elements within their curriculum to meet requirements while adhering to the guidelines of the Council on Accreditation of Nurse Anesthesia Educational Programs. A survey tool was developed and distributed to all programs to assess the utilization of simulation, available simulation resources, ongoing faculty development efforts, and barriers to use of this educational approach. Survey results indicated that simulation is valued as an effective method within NAEPs for a variety of teaching and learning activities and is utilized to support achievement of both technical and nontechnical learning outcomes for student registered nurse anesthetists.
Topics: Humans; Nurse Anesthetists; United States; Education, Nursing, Graduate; Curriculum; Societies, Nursing; Simulation Training; Clinical Competence; Surveys and Questionnaires
PubMed: 38809212
DOI: No ID Found -
AANA Journal Aug 2023The American Association of Nurse Anesthesiology Practice Committee and subject matter experts recently evaluated newly published cannabis guidelines titled "ASRA Pain...
The American Association of Nurse Anesthesiology Practice Committee and subject matter experts recently evaluated newly published cannabis guidelines titled "ASRA Pain Medicine Consensus Guidelines on the Management of the Perioperative Patient on Cannabis and Cannabinoids." A summative review of the evidence-based guidelines provides essential recommendations, which are directly applicable to certified registered nurse anesthetist clinical practice.
Topics: Humans; Nurse Anesthetists; Medical Marijuana; Pain Management; Practice Guidelines as Topic; United States; Consensus; Societies, Nursing
PubMed: 38809193
DOI: No ID Found -
AANA Journal Aug 2023The U.S. was at war for nearly two decades, supporting unprecedented survival on the battlefield. As the nation pivots to a relative peace, it is critical that U.S. Army...
The U.S. was at war for nearly two decades, supporting unprecedented survival on the battlefield. As the nation pivots to a relative peace, it is critical that U.S. Army certified registered nurse anesthetist (CRNA) leaders mitigate the loss of lessons learned and prepare future Army CRNAs for war. This article describes the U.S. Army CRNA Readiness Model that incorporates the knowledge, skills, and abilities required to sustain readiness. This model will provide U.S. Army nursing leaders with the framework to implement and evaluate solider readiness to provide anesthesia in operational environments.
Topics: Nurse Anesthetists; Humans; United States; Military Nursing; Models, Nursing; Clinical Competence
PubMed: 38809192
DOI: No ID Found -
AANA Journal Apr 2024Olive Berger was a true nurse anesthesia pioneer for our profession. She dedicated her life to the advancement of nurse anesthesia through her leadership, advocacy,...
Olive Berger was a true nurse anesthesia pioneer for our profession. She dedicated her life to the advancement of nurse anesthesia through her leadership, advocacy, scholarly writing, clinical achievements and innovation. She blazed the trail by forming and establishing education requirements for nurse anesthesia programs, established a state nurse anesthesia organization, and led the American Association of Nurse Anesthetists as its 14th president in 1958. She was the Chief Certified Registered Nurse Anesthetist and Program Director at the Johns Hopkins Hospital and is best known for her collaboration with surgeons Dr. Alfred Blalock and Dr. Helen Taussig, providing anesthesia care during the groundbreaking repair of tetralogy of Fallot on infants.
Topics: History, 20th Century; Nurse Anesthetists; Humans; United States; History, 19th Century
PubMed: 38809188
DOI: No ID Found -
Case Reports in Critical Care 2024Acute hypoxemic respiratory failure from infective endocarditis with septic emboli has been attributed to the vicious cycle of tissue damage and inflammatory cytokine...
Acute hypoxemic respiratory failure from infective endocarditis with septic emboli has been attributed to the vicious cycle of tissue damage and inflammatory cytokine response. Spontaneous pneumothorax is a rare complication and can be a late-onset presentation despite appropriate antibiotic therapy. We present a rare case of bilateral spontaneous pneumothoraces in a patient with tricuspid valve endocarditis and septic pulmonary emboli. We suspect that the profound inflammatory response from two different bacterial pathogens and the peripheral location of the septic thrombosis are the basis of the development of bilateral pneumothorax development in our patient.
PubMed: 38808068
DOI: 10.1155/2024/3049691 -
Current Research in Food Science 2024This study explores the effect of spray-drying (SD) inlet temperatures (T 120 and 150 °C) and wall material on the chemical and physico-chemical properties of...
This study explores the effect of spray-drying (SD) inlet temperatures (T 120 and 150 °C) and wall material on the chemical and physico-chemical properties of microencapsulated hop extracts (MHE). Hop extract was formulated with maltodextrin (MD) and gum Arabic (GA) used in single or in combination with β-cyclodextrin (βCD). MHE were evaluated for physical properties, bitter acids (BA), total polyphenol content (TPC) and encapsulation efficiency (TPC EE), and antioxidant capacity (AOC). Powders produced at T 150 °C exhibited the highest flowability and generally higher TPC yield. Besides T, MD enabled the obtaining of MHE with the highest encapsulation efficiency. Other physico-chemical and antioxidant properties differently varied depending on the T. Overall, the βCD addition positively affected α-acids, and β-acids of MHE obtained at T 120 °C. ATR-FTIR analysis showed hydrogen bond formation between hop compounds and βCD. Multifactorial ANOVA highlighted that T, W, and their interaction influenced almost all the chemical and physico-chemical properties of MHE.
PubMed: 38800638
DOI: 10.1016/j.crfs.2024.100769