Objectives: According to the technical intelligence hypothesis, humans are superior to all other animal species in understanding and using tools. However, the vast majority of comparative studies between humans and chimpanzees, both proficient tool users, have not controlled for the effects of age, prior knowledge, past experience, rearing conditions, or differences in experimental procedures. We tested whether humans are superior to chimpanzees in selecting better tools, using them more dexteriously, achieving higher performance and gaining access to more resource as predicted under the technical intelligence hypothesis.
Materials And Methods: Aka and Mbendjele hunter-gatherers in the rainforest of Central African Republic and the Republic of Congo, respectively, and Taï chimpanzees in the rainforest of Côte d'Ivoire were observed cracking hard Panda oleosa nuts with different tools, as well as the soft Coula edulis and Elaeis guinensis nuts. The nut-cracking techniques, hammer material selection and two efficiency measures were compared.
Results: As predicted, the Aka and the Mbendjele were able to exploit more species of hard nuts in the forest than chimpanzees. However, the chimpanzees were sometimes more efficient than the humans. Social roles differed between the two species, with the Aka and especially the Mbendjele exhibiting cooperation between nut-crackers whereas the chimpanzees were mainly individualistic.
Discussion: Observations of nut-cracking by humans and chimpanzees only partially supported the technical intelligence hypothesis as higher degrees of flexibility in tool selection seen in chimpanzees compensated for use of less efficient tool material than in humans. Nut cracking was a stronger social undertaking in humans than in chimpanzees.
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http://dx.doi.org/10.1002/ajpa.23211 | DOI Listing |
Mayo Clin Proc
January 2025
Division of Nephrology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department and Institute of Physiology, National Yang Ming Chiao Tung University, Taipei, Taiwan; Center For Intelligent Drug Systems and Smart Bio-devices (IDS(2)B) National Yang Ming Chiao Tung University, Hsinchu, Taiwan. Electronic address:
Objective: To investigate how estimated glomerular filtration rate (eGFR) decline following sodium-glucose cotransporter-2 inhibitors (SGLT2i) initiation predicts long-term cardiorenal outcomes.
Methods: From 2016 to 2020, a longitudinal cohort of 4942 diabetic patients treated with SGLT2i were enrolled and followed until December 2021. Patients were categorized into mild (≤30%), moderate (>30%∼≤40%) and severe (>40%) decline groups by the maximal eGFR change between 2 to 12 weeks after SGLT2i treatment.
Mayo Clin Proc
January 2025
Division of Pediatric Cardiology, Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN; Department of Molecular Pharmacology and Experimental Therapeutics, Windland Smith Rice Sudden Death Genomics Laboratory, Mayo Clinic, Rochester, MN; Division of Heart Rhythm Services, Department of Cardiovascular Medicine, Windland Smith Rice Genetic Heart Rhythm Clinic, Mayo Clinic, Rochester, MN. Electronic address:
Objective: To test whether an artificial intelligence (AI) deep neural network (DNN)-derived analysis of the 12-lead electrocardiogram (ECG) can distinguish patients with long QT syndrome (LQTS) from those with acquired QT prolongation.
Methods: The study cohort included all patients with genetically confirmed LQTS evaluated in the Windland Smith Rice Genetic Heart Rhythm Clinic and controls from Mayo Clinic's ECG data vault comprising more than 2.5 million patients.
Int J Lang Commun Disord
January 2025
Division of Communication Sciences and Disorders, University of Cape Town, Rondebosch, South Africa.
Background: There is a global need for synthetic speech development in multiple languages and dialects, as many children who cannot communicate using their natural voice struggle to find synthetic voices on high-technology devices that match their age, social and linguistic background.
Aims: To document multiple stakeholders' perspectives surrounding the quality, acceptability and utility of newly created synthetic speech in three under-resourced South African languages, namely South African English, Afrikaans and isiXhosa.
Methods & Procedures: A mixed methods research design was selected.
Nurs Health Sci
March 2025
Faculty of Nursing, Nursing Department, Ataturk University, Erzurum, Turkey.
The widespread adoption of artificial intelligence (AI) tools in academic settings has the potential to revolutionize learning experiences, enhance educational outcomes, and streamline academic processes. The aim of this research was to explore the perceptions of Lebanese health sciences students regarding the use of generative AI in higher education. A qualitative descriptive research design informed by descriptive phenomenology was employed.
View Article and Find Full Text PDFActa Otolaryngol
January 2025
Department of Otorhinolaryngology, Institute of Science Tokyo, Tokyo, Japan.
Background: Recent advances in artificial intelligence have facilitated the automatic diagnosis of middle ear diseases using endoscopic tympanic membrane imaging.
Aim: We aimed to develop an automated diagnostic system for middle ear diseases by applying deep learning techniques to tympanic membrane images obtained during routine clinical practice.
Material And Methods: To augment the training dataset, we explored the use of generative adversarial networks (GANs) to produce high-quality synthetic tympanic images that were subsequently added to the training data.
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