Zoomorphic Mobile Robot Development for Vertical Movement Based on the Geometrical Family Caterpillar

Research in robotics is one of the promising areas in mobile robot development, which is planned to be implemented in extreme dangerous conditions of areas explored by humans. This article aims at developing and improving a prototype of zoomorphic mobile robots that are designed to repeat the existing biological objects in nature. The authors performed a detailed analysis on the structure and dynamics of the geometrical family caterpillar movement, which is passed on a practical design implemented to perform the dynamic movement on uneven vertical surfaces. Based on the obtained analysis, the design and kinematic scheme of the movement is developed. Also, the structural control scheme via the Internet technologies that allow carrying out remote control is presented in this paper, considering the dangerous mobile robot work zones. To test the recommended solutions, the authors developed detailed 3D printed models of the mobile robot constructions for the implemented hardware. The model of the mobile robot is constructed, and the control system with examples of the user program code implementations is performed. Several experiments were performed, which showed the efficiency of the achieved mobile robot for solving problems of vertical movement on uneven metal surfaces. Moreover, the obtained slow motion of the designed robot proves that the simulated robot behaves similarly to the natural behavior of caterpillar movement.

Integrating Biologging and Behavioral State Modeling to Identify Cryptic Behaviors and Post-capture Recovery Processes: New Insights From a Threatened Marine Apex Predator

Multisensor biologging provides a powerful tool for ecological research, enabling fine-scale observation of animals to directly link physiology and movement to behavior across ecological contexts. However, applied research into behavioral disturbance and recovery following human interventions (e.g., capture and translocation) has mostly relied on coarse location-based tracking or unidimensional approaches (e.g., dive profiles and activity/energetic metrics) that may not resolve behaviors and recovery processes. Biologging can improve insights into both disturbed and natural behavior, which is critical for management and conservation initiatives, although challenges remain in objectively identifying distinct behavioral modes from complex multisensor datasets. Using white sharks (Carcharodon carcharias) released from a non-lethal catch-and-release shark bite mitigation program, we explored how combining multisensor biologging (video, depth, accelerometers, gyroscopes, and magnetometers), track reconstruction and behavioral state modeling using hidden Markov models (HMMs) can improve our understanding of behavioral processes and recovery. Biologging tags were deployed on eight white sharks, recording their continuous behaviors, movements, and environmental context (habitat, interactions with other organisms/objects) for periods of 10–87 h post-release. Dive profiles and tailbeat analysis (as a standard, activity-based method for assessing recovery) indicated an immediate “disturbed” period of offshore movement, displaying rapid tailbeats and an average tailbeat-derived recovery period of 9.7 h, with evidence of smaller individuals having longer recoveries. However, further integrating magnetometer-derived headings, track reconstruction and HMM modeling revealed a cryptic shift to diurnal clockwise-counterclockwise circling behavior, which we argue represents compelling new evidence for hypothesized unihemispheric sleep amongst elasmobranchs. By simultaneously providing critical information toward conservation-focused shark management and understudied aspects of shark behavior, our study highlights how integrating multisensor information through HMMs can improve our understanding of both post-release and natural behavior, especially in species that are difficult to observe directly.

Emergent Intelligence and Distributed Stochastic Optimization

Emergent intelligence is a property of a system of elements that is not inherent in each element individually. This behavior is based on local communications. This behavior helps to adapt to emerging uncertainties and achieve a global goal. This behavior exists in the natural world. A simplified example of emergent intelligence from the natural world is given. The repetition of natural behavior with the help of simple technical devices, which are limited in resources and cheap in construction, and the use of multi-agent approaches is considered. Distributed algorithms using local communications are considered. Such algorithms are more robust to noise.

A Multimodal Approach to Investigate the Neural Mechanisms of Real World Social Vision

Eye tracking and other behavioral measurements collected from patient-participants in their hospital rooms afford a unique opportunity to study immersive natural behavior for basic and clinical-translational research, and also requires addressing important logistical, technical, and ethical challenges. Hospital rooms provide the opportunity to richly capture both clinically relevant and ordinary natural behavior. As clinical settings, they add the potential to study the relationship between behavior and physiology by collecting physiological data synchronized to behavioral measures from participants. Combining eye-tracking, other behavioral measures, and physiological measurements enables clinical-translational research into understanding the participants' disorders and clinician-patient interactions, as well as basic research into natural, real world behavior as participants eat, read, converse with friends and family, etc. Here we describe a paradigm in individuals undergoing surgical treatment for epilepsy who spend 1-2 weeks in the hospital with electrodes implanted in their brain to determine the source of their seizures. This provides the unique opportunity to record behavior using eye tracking glasses customized to address clinically-related ergonomic concerns, synchronized direct neural recordings, use computer vision to assist with video annotation, and apply multivariate machine learning analyses to multimodal data encompassing hours of natural behavior. We discuss the acquisition, quality control, annotation, and analysis pipelines to study the neural basis of real world social and affective perception during natural conversations with friends and family in participants with epilepsy. We also discuss clinical, logistical, and ethical and privacy considerations that must be addressed to acquire high quality multimodal data in this setting.

Mesoscale cortex-wide neural dynamics predict self-initiated actions in mice several seconds prior to movement

Volition - the sense of control or agency over one's voluntary actions - is widely recognized as the basis of both human subjective experience and natural behavior in non-human animals. To date, several human studies have found peaks in neural activity preceding voluntary actions, e.g. the readiness potential (RP), and some have shown upcoming actions could be decoded even before awareness. These findings remain controversial with some suggesting they pose a challenge to traditional accounts of human volition while others proposing that random processes underlie pre-movement neural activity. Here we seek to address part of this controversy by evaluating whether pre-movement neural activity in mice contains structure beyond that expected from random processes. Implementing a self-initiated water-rewarded lever pull paradigm in mice while recording widefield [Ca++] neural activity we find that cortical activity changes in variance seconds prior to movement and that upcoming lever pulls or spontaneous body movements could be predicted between 1 second to more than 10 seconds prior to movement, similar to but even earlier than in human studies. We show that mice, like humans, are biased towards initiation of voluntary actions during specific phases of neural activity oscillations but that the pre-movement neural code in mice changes over time and is widely distributed as behavior prediction improved when using all vs single cortical areas. These findings support the presence of structured multi-second neural dynamics preceding voluntary action beyond that expected from random processes. Our results also suggest that neural mechanisms underlying self-initiated voluntary action could be preserved between mice and humans.

Broiler Behaviour Differs From Males to Females When Under Different Light Wavelengths

It is well established that different light wavelengths affect broiler behavior. The present study aims to evaluate the effect of four light wavelengths on broiler behavior from 1 to 42-days of age. Birds were housed at a stocking density of 13 birds/m2, in 32 boxes of 1.56 m2. The experimental design was a completely randomized factorial of 4x2 (four colors x two sexes), with four replicates. Behavioral variables were accessed through cameras and observed in person thrice a week for 30 min per day in three different periods. Data was organized according to age groups and analyzed by data mining approach with the different light wavelengths as the classes. Natural behavior of male broilers reared in environments with green. Blue light was more relevant to the classification of male broilers behavior (96.9 and 96.9% accuracy and 0.8 and 1.0 of class precision of behavior classification, respectively). Blue and green lights affected the behavior of male broilers starting at 7-days of age, increasing the presence at the bird feeder, and reducing the idle period.

Beyond Fixation: detailed characterization of neural selectivity in free-viewing primates

Virtually all vision studies use a fixation point to stabilize gaze, rendering stimuli on video screens fixed to retinal coordinates. This approach requires trained subjects, is limited by the accuracy of fixational eye movements, and ignores the role of eye movements in shaping visual input. To overcome these limitations, we developed a suite of hardware and software tools to study vision during natural behavior in untrained subjects. We show this approach recovers receptive fields and tuning properties of visual neurons from multiple cortical areas of marmoset monkeys. Combined with high-precision eye-tracking, it achieves sufficient resolution to recover the receptive fields of foveal V1 neurons. These findings demonstrate the power of this approach for characterizing neural response while simultaneously studying the dynamics of natural behavior.

Pengaruh Sosiologis Komunitas Lesbian Gay Biseksual Dan Transgender Ditinjau Dalam Etika Kristen

The Lesbian, Gay, Bisexual, and Transgender (LGBT) in the past was something deviant, but nowadays it has become a trend that is even considered natural by many people. This of course has a sociological impact. There is a view that says that the behavior of LGBT people is a biological natural behavior, so it needs to be accepted as something that cannot be changed. Some theories agree that LGBT behavior is influenced by environmental, parenting, and economic factors so that there are pros and cons for LGBT people. This study aims to see the sociological influence of the LGBT community by using a literature review. The results of the study show that LGBT is contrary to the truth of God's creation, namely the clear separation of sex, namely male and female. Also, this is contrary to the design of marriage that God built, namely heterosexuality and monogamy.

Assessment of Brain Functional Activity Using a Miniaturized Head-Mounted Scanning Photoacoustic Imaging System in Awake and Freely Moving Rats

Understanding the relationship between brain function and natural behavior remains a significant challenge in neuroscience because there are very few convincing imaging/recording tools available for the evaluation of awake and freely moving animals. Here, we employed a miniaturized head-mounted scanning photoacoustic imaging (hmPAI) system to image real-time cortical dynamics. A compact photoacoustic (PA) probe based on four in-house optical fiber pads and a single custom-made 48-MHz focused ultrasound transducer was designed to enable focused dark-field PA imaging, and miniature linear motors were included to enable two-dimensional (2D) scanning. The total dimensions and weight of the proposed hmPAI system are only approximately 50 × 64 × 48 mm and 58.7 g (excluding cables). Our ex vivo phantom experimental tests revealed that a spatial resolution of approximately 0.225 mm could be achieved at a depth of 9 mm. Our in vivo results further revealed that the diameters of cortical vessels draining into the superior sagittal sinus (SSS) could be clearly imaged and continuously observed in both anesthetized rats and awake, freely moving rats. Statistical analysis showed that the full width at half maximum (FWHM) of the PA A-line signals (relative to the blood vessel diameter) was significantly increased in the selected SSS-drained cortical vessels of awake rats (0.58 ± 0.17 mm) compared with those of anesthetized rats (0.31 ± 0.09 mm) (p < 0.01, paired t-test). In addition, the number of pixels in PA B-scan images (relative to the cerebral blood volume (CBV)) was also significantly increased in the selected SSS-drained blood vessels of awake rats (107.66 ± 23.02 pixels) compared with those of anesthetized rats (81.99 ± 21.52 pixels) (p < 0.01, paired t-test). This outcome may result from a more active brain in awake rats than in anesthetized rats, which caused cerebral blood vessels to transport more blood to meet the increased nutrient demand of the tissue, resulting in an obvious increase in blood vessel volume. This hmPAI system was further validated for utility in the brains of awake and freely moving rats, showing that their natural behavior was unimpaired during vascular imaging, thereby providing novel opportunities for studies of behavior, cognition, and preclinical models of brain diseases.

Bio Scaffolds

Abstract‘Bio Scaffolds’ explores a series of design tectonics that emerge from a co-creation between human, machine and natural intelligences. This research establishes an integral connection between form and materiality by enabling biological materials to become a co-creator within the design and fabrication process. In this research paper, we explore a hybrid between architectural aesthetics and biological agency by choreographing natural growth through form. ‘Bio Scaffolds’ explores a series of 3D printed biodegradable scaffolds that orchestrate both Mycelia growth and degradation through form. A robotic arm is introduced into the system that can respond to the organism’s natural behavior by injecting additional Mycelium culture into a series of sacrificial frameworks. Equipped with computer vision systems, feedback controls, scanning processes and a multi-functional end-effector, the machine tends to nature by reacting to its patterns of growth, moisture, and color variation. Using this cybernetic intelligence, developed between human, machine, and Mycelium, our intention is to generate unexpected structural and morphological forms that are represented via a series of 3D printed Mycelium enclosures. ‘Bio Scaffolds’ explores an interplay between biological and computational complexity through non anthropocentric micro habitats.